Computational and Experimental Simulations in Engineering

Graphene, a honeycomb-like sheet of carbon just one atom thick, is used as a new reinforcement to make high-performance composites due to its unprecedented physical and chemical properties. Here we focus on the elastic properties of multi-layer graphene to simulate the mechanical properties of their composites. On the basis of the methods of state-based peridynamics and periodic boundary conditions, a unit cell model of graphene was established at the microscopic scale. Considering six pure load cases, the response of the periodic material under the action of macroscopically uniform deformation gradient is obtained. The effect of van der Waals forces and Brenner interatomic potentials with optimized parameters has been taken into account in the analysis of interaction between carbon atoms in graphene. The results obtained from the present numerical solution are in good agreement with the data in the existing literature, indicating that the model can well simulate the elastic properties of graphene, and give a significant reference for the further studies of the properties of graphene-based composites.

The double-walled cooling structure can achieve high cooling efficiency but has a higher risk of failure compared to traditional structures. In order to optimize the structural variables of the structure, a fast and accurate temperature field prediction method is urgently proposed This study establishes a deep learning model using MLPs and SRCNN modules to predict the 3D temperature field of the outer wall of a double-walled cooling structure (DWCS) unit. The model takes in geometric structure variables and working condition variables as inputs. To train the model, a temperature field dataset is generated by CFD numerical simulation. The results demonstrate that the deep learning method can accurately predict the 3D temperature field of the DWCS unit at multiple scales, and the model training can be convergent with the proper design of the model architecture and training strategies. Compared to numerical simulation, the deep learning model can predict the temperature field quickly and be combined with machine learning optimization algorithms for the optimization of DWCS variables.

Laminate cooling structures are extensively used in the design of turbine blades for aircraft engines. There are two types of mass flow related problems in the design of laminate cooling structures: the forward problem of predicting the mass flow rate of cooling air, and the inverse problem of designing the geometric parameters given the target mass flow rate. The present study constructed a dataset for neural network training and testing using numerical simulation methods. A neural network model was established to solve the forward problem of predicting the mass flow rate, with four hidden layers and 64 neurons per layer. The average relative error of the predicted mass flow rate was 1.46%. A solution method for the inverse problem based on predicting the diameter of the film cooling holes was proposed. Using this method, six sets of geometric parameters for the laminate cooling structure were designed under known target mass flow rate conditions, with a design time of 0.014 s. Numerical simulation verification showed that the maximum relative error and average relative error between the designed mass flow rate and the target value were 2.9% and 1.54%, respectively, demonstrating the practicality of the proposed method.

In recent years, supersized rectangle pipe-jacking method has been widely used and the monolithic pre-cast pipe tube is extensively adopted. However, the application of supersized rectangle pipe-jacking method in the urban area is severely limited, because of the oversized volume and weight as well as the difficulty of transportation and lifting. Therefore, it is imperative to explore the new structure of the supersized rectangular pipe tube. This paper introduces two-half-assembled precast concrete tube to reduce the aforementioned difficulties. Depending on the excellent early-strength performance, mechanical performance, and durability performance of ultra-high performance concrete (UHPC), quick connection of the wet-joint can be achieved on-site and maintenance only needs 3 days before propulsion operation. The mechanical and waterproofing performance of the interface between UHPC and PC are explored by prototype test. The main conclusions are summarized as follows: (1) the bearing capacity of the wet-joint is much higher than the actual need after 3-day maintenance; (2) the waterproofing performance of the interface by the laboratory test meets the design requirements; (3) the interface of the prototype test has barely waterproofing performance; (4) after special treatment on the interface, waterproofing performance is improved and meets the demands, which it is successfully applied to the actual project.

Urban development and renewal reduce the performance of shield tunnels and may cause structural safety hazards. Thus, a new plug-in fast connector is developed for shield tunnels to improve structural resilience. The connector does not require additional tightening, and the segment opening and dislocation are small. Taking a 650 mm thick segment as the prototype, this paper conducts the tensile and shearing tests of the plug-in fast connector, to investigate the structural form, material properties, and the force transmission between the connection and concrete segment. In addition, the theoretical value of the connector is employed to compare experimental values. The main conclusions are as follows: (1) The insufficient bond strength between the embedded sleeves and concrete causes the fast connector to be pulled out and the tensile failure of concrete is occurred. (2) The yield strength of the connector is about 150 kN, and the failure strength is about 200 kN, which is slightly lower than the design value. (3) With the increase of the shearing displacement, damage occurs inside the embedded sleeves and then the concrete of the upper surface is crushed. Finally, the tightness between CR and sleeves is invalid and the shear strength of each connector is 210 kN. (4) The shear stiffness of the plug-in fast connector is fitted by two straight lines, and K1 and K2 are 2.611 kN/mm and 18.544 kN/mm respectively. (5) The new plug-in fast connector can improve the longitudinal mechanical performance of a shield tunnel. The subsequent research should focus on the selection of materials for embedded sleeves and the bond strength between the sleeve and concrete.

With the increasing complexity of artificial intelligence technology and network environments, cybersecurity is facing massive and complex data. Knowledge graphs have the potential to aggregate, represent, manage, and reason with this knowledge. Therefore, applying knowledge graphs to cybersecurity can help to characterize and present security situations, support security decision-making, and predict warnings. Over the past two decades, research on knowledge graphs for cybersecurity has received growing attention in data processing, construction, and visualization. This review provides a comprehensive comparative analysis of key technologies and application scenarios of cybersecurity knowledge graphs. Firstly, basic concepts of knowledge graphs and cybersecurity knowledge graphs are outlined, and the required datasets for their construction are compared and analyzed from both general-purpose and specialized perspectives. On this basis, a framework for building cybersecurity knowledge graphs is summarized, and key techniques for building cybersecurity knowledge graphs, including ontology construction, information extraction, and knowledge reasoning, are detailed. Finally, application scenarios of knowledge graphs in the field of cybersecurity are sorted out from the perspective of application objectives. The challenges knowledge graphs face and future development trends in this field are also pointed out.

The control of hypersonic vehicle is characterized by strong coupling, large parameter fluctuation, nonlinearity and uncertainty. To solve the above technical difficulties, active disturbance rejection control (ADRC) is presented to track the expected pitch angle of hypersonic vehicles. Due to the problem that extended state observer (ESO) and nonlinear state error feedback (NLSEF) parameters in ADRC need to be debugged many times, this paper develops a Q-learning algorithm to adjust the optimal parameters of ADRC within a certain range. Simulation results indicate that the proposed control strategy has a better tracking performance.

Deformation and cracks are valuable clues for evaluating the condition of existing concrete structures. In previous studies, computer vision technology has been proven to be an efficient and accurate means for detailed deformation and crack information acquisition. But there is still a gap in determining the functional level of structures directly from the extracted information. In this study, six concrete beams with different reinforcements were loaded to failure, and the loading processes were recorded by cameras. The dynamic evolution of deformation and cracks under different load steps was analyzed by our designed image processing pipeline. It was found deformation and crack evolution were strongly related to failure mode. On this basis, a crack characteristic parameter system used for structure monitoring was established, which is composed of the initial position, width, length, direction, and occurrence time of the fracture, corresponding characterization and extraction methods also were proposed. The established parameter system can be used to solve reverse problems such as failure mode pre-diction and load estimating.

In this study, the expanded perlite (EP) powder and expanded graphite (EG) were used as supports to stabilize paraffin wax (PW) for preparing composite phase change materials (PCMs). The impregnation method was used to prepared PW/EP, PW/EP/EG1, PW/EP/EG3 and PW/EP/EG5. The enhancement effect of EG with different mass proportions on the heat storage/release performance of PW/EP, and the improvement effect of carbon nanotubes (CNTs) on the solar-thermal conversion performance of pure PW and composite PCMs were studied by three-dimensional numerical simulation. The thermal conductivities of composite phase change materials were 1.26–2.13 times higher than the pure PW. The PW/EP/EG5 had wonderful thermal physical property in heat energy storage and release process. The solar-thermal conversion performance could be effective improved by adding CNTs cover; Compared to C-PW, the phase change time of C-PW/EP, C-PW/EP/EG1, C-PW/EP/EG3 and C-PW/EP/EG5 decreased by 4%, 19%, 26% and 31%, respectively; the performance of PW/EP was improved the most and that PW/EP/EG5 was improved the least; but C-PW/EP/EG5 had the best solar-thermal conversion and storage performance.

The presence of a large number of natural fracture clusters in fractured reservoirs has a significant impact on fracture propagation during hydraulic fracturing. A two-dimensional fluid–solid coupled hydraulic fracture intersection extension finite element model was established considering the coupling between the deformation of rock and the fluid flow inside the fracture as well as the interaction between natural fracture (NF) and hydraulic fracture (HF). The results indicate that when HF intersects NF with a high approach angle at a low horizontal stress difference, HF tends to pass through NF directly, and vice versa, HF tends to activate NF; with the increase of horizontal stress difference, the fracture as a whole extends in a zigzag shape along the direction of maximum principal stress. As the NF angle is higher, HF is prone to divert to activate the NF and the fracture extends in a step-like shape along the NF, and the higher the NF angle the straighter the fracture is, and the greater the fracture initiation pressure. The higher the injection rate, the more HF tends to penetrate the NF, and the straighter the HF morphology. The fracturing fluid viscosity has less influence on the expansion of HFs, and the HF morphology is approximately similar. This study has certain theoretical guiding significance for clarifying the propagation path of hydraulic fractures under natural fracture distribution and formulating the stimulation plan of fractured reservoirs.

It is the trend of future energy development to blend a certain proportion of hydrogen into natural gas for utilization due to the zero carbon emissions characteristic of hydrogen after combustion. The hydrogen embrittlement and other hydrogen damages caused by metal pipelines can be effectively avoided by using non-metallic pipelines to transport hydrogen-enriched natural gas (HENG). However, due to the material characteristics, the degree of gas permeation of non-metal pipelines is greater than that of metal pipelines. In the study, the molecular dynamics combined with Giant Canonical Monte Carlo method is used to investigate the dissolution, diffusion and permeation characteristics of HENG with different hydrogen blending ratios (HBR, 5–20%) in amorphous polyethylene at temperatures of 270–310 K and pressures of 0.1–0.7 MPa. Results show that the solubility coefficient of hydrogen increases with increasing temperature and HBR, while the solubility coefficient of methane presents the opposite trend. The diffusion coefficients of hydrogen and methane increase with the rise of temperature and pressure but decrease with the increase of HBR. The permeability coefficients of hydrogen and methane increase with the increase of temperature. In addition, with the increase of HBR, the permeability coefficient of hydrogen increases, while that of methane decreases.

The prediction of global hourly solar radiation is of great significance for the development of solar energy resources in energy conversion countries. Based on this view, this study used RF and SVM models to simulate solar radiation data distributed at three weather stations in Australia based on different input combinations. In the training of the model, the meteorological data included in the parameter combination selected in this study include average temperature, relative humidity, extraterrestrial radiation and precipitation. The results showed that the simulation accuracy of SVM model was better than that of RF model, and the average RMSE was 0.61 and 0.68 MJ m−2 h−1, respectively. The model with Z2 input was significantly better than the model with Z1 input. The RMSE was reduced by 25% and the R2 was increased by 10%. Temperature had an important influence on solar radiation.

In order to study the influence of different condition parameters on the process of floating transportation of steel guard cylinder, taking the floating transportation and sinking of 3.9 m super-large diameter steel guard cylinder of a continuous rigid frame bridge pile in Suichang, Zhejiang Province as an example, the basic working principle of the floating transportation method of super-large diameter steel guard cylinder and the process of floating transportation and sinking in the construction process are studied. The water entry depth of the steel sheath under different equilibrium tilt angles is discussed and the corresponding theoretical calculation formula is given. When the balance tilt Angle is fixed, the influence of the water inlet velocity and water inlet area on the speed and water entry time of the steel sheath is studied, and the corresponding theoretical calculation formula is put forward respectively. The results show that the floating method of steel protecting tube sinking construction can effectively guarantee the accuracy of the liners of the large diameter into the water, improve the overall stability of the sinking process of the steel liners, reduce the risk of the steel liners capsized, for rational selection of the steel liners of the construction conditions to provide the corresponding theoretical support, and for the future similar steel protecting tube into the water sink to provide the corresponding reference.

A numerical model for multi-component gas Darcy flow in porous media is proposed in this paper. The model is capable of simulating underground gas storage operations and cushion gas flow while accounting for gas compressibility and coupling gas density and pressure. Gas properties are calculated using the Benedict–Webb–Rubin–Starling (BWRS) equation and the non-polar gas viscosity equation. The finite volume method is employed for discretization. Moreover, the computational stability of the proposed method is analyzed and verified. Compared to classical methods, the proposed method exhibits faster convergence with larger time steps. This is a significant advantage as it allows for more efficient simulations and faster results. To demonstrate the applicability of our model, we simulate two cases of UGS: a single well injection and a multiple wells injection. We find that the multiple wells injection method can effectively reduce the diffusion of cushion gas and increase the gas storage capacity.

In this paper, to solve the problem of vehicle following tracking control in the vehicle following scenario, an intelligent queue following optimization control method is proposed based on the Internet of Things communication network. Firstly, the Internet of Things network is used to obtain the network information, based on which optimization algorithm is designed for car following distance to improve the driving safety, road traffic capacity and driving safety. Secondly, the following controller is given by using the backstepping method to achieve the following of the optimal following distance. Finally, the validity of the proposed scheme is verified via a simulation example.

The real-time monitoring of fatigue crack length is crucial for estimating the damage tolerance and the residual lifetime of aircraft metallic structures. This paper proposed a deep learning-based approach for predicting the fatigue crack size of metallic structures using strain monitoring data. By constructing learning models for Cycle Consistent Adversarial Networks, crack sizes are classified and quantified, and the correlation between the measured strain data and finite element simulation data was established. The proposed approach was applied for monitoring the growth of fatigue crack in a central hole plate subjected to random fatigue loads. The predictions show that the proposed model can monitor the fatigue crack lengths with high accuracy, where the prediction error of the crack length is less than 1 mm. This approach provides a reliable and accurate method for predicting the fatigue crack size of metallic structures, which may have important practical applications in aviation industry.

With the development of technology, the term metaverse is becoming more known. Metaverses hope to turn imagination into reality through the integration of various technologies. Metaverses are the latest stage in the development of visual immersive technology with four characteristics: spatio-temporality, authenticity, independence, and connectivity. The purpose of this paper is to study the construction of a Confucian culture learning environment in a 3D metaverse, where students connect to a platform constructed by a 3D virtual world through a Head-Mounted Display (HMD). Students can learn about Confucianism, Confucius’ life and stories, as well as visit Confucian cultural buildings. The platform is based on a virtual scene built on The Sims 4, and the HMD is used as a connection between the metaverse and the real world enriching the user's experience with the same features and perceptions as the real world, which will make the online learning approach more meaningful. Finally, this paper presents the content of the metaverse exhibition through an experimental approach.

The increase in the running speed aggravated the influence of the pantograph aerodynamic uplift force on the pantograph-catenary contact force. Moreover, the longitudinal asymmetry of the pantograph makes the aerodynamic uplift force vary greatly under the operating conditions of the knuckle-downstream and knuckle-upstream. Therefore, it is of great significance to optimize the aerodynamic characteristics of the pantograph and ensure the consistency of the aerodynamic uplift force of the pantograph under the two operating conditions. A hybrid infill criterion (HIC) is proposed combining the improved expectation infill criterion (EIC) and the Pareto solution infill criterion (PIC) to improve the optimization efficiency, and the multi-objective aerodynamic optimization of the high-speed pantograph is carried out based on the HIC surrogate model. Taking the single- and multi-objective test function as an example, the convergence speed of EIC, PIC and HIC surrogate models is compared. The results show that the optimization efficiency of the HIC surrogate model is improved by 50.0% compared with the EIC and the PIC surrogate model in the single-objective optimization. For the multi-objective test function, the efficiency of the HIC surrogate model is improved by 62.5%. Further, the Pareto solution set of the pantograph multi-objective optimization is obtained using the PIC surrogate model and genetic algorithm, and the aerodynamic uplift forces of the optimal pantograph under the knuckle-downstream and knuckle-upstream are 36.1 N and 39.9 N, respectively. The pantograph-catenary contact force satisfies the standard considering the static uplift force. Meanwhile, the difference in the aerodynamic uplift forces of the pantograph under two operating conditions is only 3.8 N, and the aerodynamic resistance of the knuckle-downstream and knuckle-upstream operating conditions of the pantograph has been reduced by 1.2%.

In the past few years, forest fire and building fire accidents occurred frequently, which has been attracting more and more attentions on the prevention and control of such kind of fire. In view of the timeliness and accuracy limitations of typical early fire spread measurement and detection methods, this paper proposes a new digital image processing based fire spread rate measurement method. The color and motion characteristics of flame images has been examined to perform image segmentation, resulting in the extracted fires in image space. Then, fire spreading rate is calculated after geometric correction. Results indicate that the proposed method has the advantages of simple implementation, rapid acquisition and accurate results.

In recent years, metaverse has become one of the frontier fields that countries around the world pay attention to and has gradually entered the public's field of vision. The emergence of metaverse brings new consumption scenarios and models to industrial digitization, and will bring together more industrial resources such as social networking, entertainment, finance, and education, thereby creating a brand new digital world. However, since the metaverse is an emerging technology and business form, it is not perfect in terms of laws, regulations and regulatory policies. At the same time, there are many industry participants in the metaverse, with various business forms, and its development is still in its early stages. There are uncertainties in the global supervision of the metaverse. Standards need to be used to guide it to promote the healthy development of the metaverse. Therefore, it is particularly important to do a good job in the forward-looking analysis of metaverse standardization. From the perspective of standardization, this paper proposes a metaverse standard system based on the current situation of the metaverse, sorts out the existing standards related to the metaverse, and gives some suggestions on the standardization construction of the metaverse.

Plunger-type wavemakers have been and will be utilized in numerous wave tanks around the world, mainly due to their high efficiency in relatively deep water, space-saving in the wave direction, etc. Although theoretical methods for generating second-order Stokes waves based on a piston-type wavemaker are nearly mature, they cannot be extended to the plunger-type wavemaker. How to control the plunger motion to produce high-quality second-order Stokes waves is still an unsolved but practically meaningful issue. In this study, new formulae that relate the vertical motion of a cylinder-shaped plunger to the target second-order Stokes waves are derived, based on the conservation between the change in the immersion volume of the cylinder and the volume of the generated waves. Constraints on the generation of second-order Stokes waves are also proposed. Then, a numerical wave flume is established based on the Smoothed Particle Hydrodynamics (SPH) method. After examining its accuracy and analyzing its convergence by reproducing a physical experiment reported in the literature, the flume is used to simulate the second-order Stokes wave generation. The computed wave profiles, flow velocities, and pressures are compared with analytical solutions to verify the reliability of the proposed wave-making theory. The results show that the second-order Stokes waves produced by a plunger-type wavemaker are both precise and stable. Besides, high-quality second-order Stokes waves can be generated within a short distance, saving the precious laboratory space and computational domain between the wavemaker and the structure if exists.

Offshore LNG import has become one of the four major natural gas import channels. One of the potential targets of gas reservoir reconstruction around coastal developed areas is offshore near-exhausted gas reservoir resources. Therefore, in recent years, the related research on offshore gas storage is gradually carried out. In view of the congested shipping lanes in China’s coastal areas, the “onshore gas reverse transport” mode used in the construction of offshore gas storage abroad may be difficult to solve the gas source problem of offshore gas storage due to the scarce resources of LNG receiving stations, busy sea lanes and other problems. Therefore, this paper innovated and proposed a brand new storage construction mode—the whole-sea offshore gas storage construction mode, which provides a new idea for offshore gas storage construction. The main difference between this model and other offshore gas storage models is that in this model, the gasification storage units are located at sea, and the main gasification units used are floating gasification storage units (FSRU, Floating Storage and re-to-feedstock Unit); GBS (Gravity Based Structure). Taking H gas field in Bohai Sea as an example, this paper studies the scheme of reservoir construction under this model. The research results show that H gas field can be converted into “whole sea” offshore gas storage, which can provide reference for other offshore gas storage construction.

In the domain of concrete penetration, test data are often limited in quantity and unevenly distributed, which leads to poor accuracy of the machine learning-based model for predicting the depth of concrete penetration. This paper aims to improve the accuracy of the model within the constraints of limited penetration test data. In this paper, based on collecting a large amount of penetration test data, the penetration data was extended by data augmentation methods such as linear interpolation and adding Gaussian noise. The genetic algorithm and greedy algorithm were used to optimize four common machine learning models’ hyperparameters: multilayer perceptron (MLP), radial basis neural network (RBF), support vector regression (SVR), and extreme gradient boosting tree (XGBoost). The results show that using linear interpolation and adding Gaussian noise can effectively alleviate the problems of insufficient data and uneven data distribution. The average error of MLP, RBF, and XGBoost decreases by 2.7%, 3%, and 0.8%, respectively, after using data augmentation. In addition, the average error of the optimal machine learning-based method is 8.4%, and the global accuracy of this model is better than the commonly used empirical formulas. The machine learning-based model can effectively predict the depth of concrete penetration and meet engineering applications’ requirements.

As the subway lines are rapidly developing in the cities, the pressure wave in different subway tunnel constructures is urgently needed to be studied and receded. In this study, a subway tunnel pressure wave experimental system was designed, constructed, and tested. The influence of train model head shape, train model speed, shaft number in the tunnel, and bypass number in the tunnel on the pressure wave amplitude were experimented with and analyzed. The results show that the train model head shapes significantly impact the amplitude of the initial compression wave in the tunnel. The blunter train model head generates a greater amplitude of the initial compression wave. When the train passes through a single-track tunnel, the maximum positive pressure amplitude of the pressure wave in the tunnel is at the first compression wave at the tunnel entrance. The maximum negative pressure value in the tunnel is at the superposition of the initial compression wave reflected from the first time and the train’s body, which is related to the length of the train’s body, tunnel length, train’s speed, and sound speed. The shaft set in the tunnel decreases the amplitude of the initial compression wave in the tunnel space behind, but it will increase the pressure wave’s amplitude reflected in the tunnel when the train passes through the shaft. After the bypass tunnel is added, the initial compression wave propagation in the tunnel behind the bypass tunnel is receded. It also increases the negative pressure amplitude when the train passes.

In this work, we present a peridynamic-based simulation method for modeling quasi-static fracture propagation in isotropic and transverse isotropic rock within the framework of peridynamic least square minimization (PDLSM). The isotropic elastic PDLSM is further extended to investigate the elastic deformation and fracture propagation in transverse isotropic materials. The proposed model naturally employs Hooke’s law for transverse isotropic material to determine peridynamic internal force and uses a transverse isotropic maximum bond stretch failure criterion to judge the bond breakage, thereby characterizing crack propagation and damage evolution. To demonstrate the effectiveness of the proposed model, simulations of elastic deformation of a transverse isotropic plate and fracture evolution in rock under semi-circular bending (SCB) tests are presented and compared with finite element method (FEM) analysis and experimental results, respectively. It is shown that the proposed model effectively simulates transverse isotropic elastic deformation and captures the fracture trajectory of isotropic and transverse isotropic SCB specimens.

In recent years, using a passing vehicle to detect damage has attracted extensive attention. Among these works, the tap-scan damage detection method can achieve a high signal to noise ratio by applying the tapping force at a sensitive frequency that is higher than the frequency band of environmental noises. Further analysis shows that this method can detect the stiffness transition of beam structures, because the vehicle acceleration is very sensitive to the stiffness gradient. This paper will further report the new design of the passive tap-scan damage detection vehicle updated for practical implementations. The results from two field tests are used to demonstrate that this vehicle can not only find the damage on beam surface, but also give the quantitative estimation of damage severity. All these findings demonstrate the practical potential of the passive tap-scan method.

With the development of the hypersonic weapon system, the non-circular cross-section projectile with more space utilization has attracted extensive attention. The high-velocity penetration mechanism of the non-circular cross-section projectile is a crucial issue that must be solved. Based on the truncated conical head structure of a typical anti-ship warhead and the elliptical section projectile shape, the resistance characteristics of the projectile and the damage mechanism of the metal sheet are studied by numerical simulation. The load of the projectile is divided into two parts: shear punching resistance and ductile enlargement resistance. The results show that the elliptical cross-section truncated ogive projectile (ETOP) penetrating the metal sheet can be divided into the head and body penetration stages. In the head invasion stage, the failure mode of the sheet is decomposed into the shear plugging caused by the truncated cone platform and the ductility enlargement of the curved surface of the head. Under high-velocity impact, the damage to the sheet caused by the ogive/blunt projectile with the elliptic-section is different from that caused by low-velocity impact. When the ogive projectile penetrates the sheet, ductile enlargement failure occurs. When a blunt projectile impacts the sheet at high velocity, the coupled failure mode of shear punching and ductile enlargement occurs. The resistance of the elliptical cross-section projectile is the same as that of the circular cross-section projectile with the same area. The difference is that the asymmetric structure of the elliptical cross-section leads to non-uniform load distribution.

Long horizontal Wells have been widely used in the development and utilization of unconventional oil and gas resources such as shale oil and gas. However, excessive torque has been a limiting factor for the length of horizontal Wells. Accurate prediction of downhole torque is a key technique to improve the rate of penetration and achieve safe drilling in the horizontal section. However, it is currently difficult to directly measure downhole torque due to the limitations of downhole measuring tools. Therefore, a new downhole torque prediction method based on soft sensing ideas combining artificial intelligence with string mechanics is proposed in this paper. Firstly, GA-BP with field-measured data is used to predict rotary torque. Then, the downhole torque is inverted by the soft rope model. Finally, the efficiency of torque transfer during drilling is evaluated. The results show that the downhole torque only accounts for 27.6% of surface torque due to the presence of drag and torque. The research results have important guiding significance for the safety control and optimization of long horizontal well drilling.

With the advancement of oil and gas exploration at home and abroad in the direction of deep-sea, deep and unconventional resources, it is increasingly difficult to calculate the wellbore pressure accurately during the drilling process. Moreover, a large number of studies have shown that the traditional rheological models such as Bingham model and power-law model are not very consistent with the actual rheology of drilling fluid in the wellbore. Besides, temperature and pressure have a great influence on the rheology of drilling fluid. Therefore, it is important to select the optimal rheological model at different temperatures and pressures to describe the rheology of drilling fluid for accurate calculation of wellbore pressure. In this study, FannIX77 high temperature and high pressure automatic rheometer is used to carry out rheology test experiments of water-based and oil-based drilling fluids. It is found that the rheology of drilling fluid is greatly affected by temperature and pressure, and the influence of temperature is more significant. Using the 1st OPT software and regression fitting algorithm, it is found that the rheology of water-based drilling fluid is more in line with the Herschel-Bulkley model when the temperature is less than 100 °C, and more in line with the four-parameter model when the temperature is greater than 100 °C. The rheology of oil-based drilling fluid is more in line with the Herschel-Bulkley model when the temperature is less than 140 °C, and more in line with the four-parameter model when the temperature is greater than 140 °C. Therefore, this study establishes a wellbore temperature and pressure field model considering the segmented rheological model. Then, this study uses example well data to compare with the calculation results of wellbore friction pressure drop of the model and under wellbore temperature and pressure field model with different rheological models. It is found that the calculation results of the wellbore temperature and pressure field model considering the segmented rheological model are more consistent with the actual data in the field. This study provides theoretical guidance for accurate calculation of wellbore pressure.

To enhance the aerodynamic performance of high-speed trains in crosswinds, the aerodynamic forces and flow structures of the high-speed train with the deflector are investigated in this work, while the influence of deflectors on the train’s leeward side in various positions on the train’s aerodynamic performance is also compared. The results show that the deflector configured on the leeward side of the train has a notable effect on reducing the rolling moment coefficient (CMx), as compared to the case without a deflector, resulting in a decrement of 4.39%, 11.66%, and 19.80% at position A, position B and position C, respectively. The flow structures around the train further reveal that the deflector plate inhibits the winding and acceleration of vortexes formed in the leeward side of the train and weakens the concentrated as well as strong energy of the vortices, compared to the case without deflector, and therefore leading to an improvement in the train's aerodynamic performance in crosswind environments.

In recent years, due to the impact of COVID-19, international geopolitics, market supply and demand, the international DES spot price of liquefied natural gas (LNG) has fluctuated dramatically. At the same time, China's imported LNG accounts for about 65% of total imported gas. To minimize the impact of international prices on China, the idea of a “multi-source collaborative gas supply” was proposed by LNG terminal, underground gas storage (UGS), and domestic produced gas. To study the feasibility of a “multi-source collaborative supply”, the domestic gas infrastructure construction and pipeline connectivity, gas well production system, underground gas storage capacity and other aspects of collaborative supply technical feasibility were analyzed. The idea of a multi-source collaborative supply and gas resource swap was put forward, and from this, the full life cycle management of “production, injection, storage and sale” of high-quality gas reservoirs could be realized. It also provided ideas for integrating gas field development and UGS construction, which can avoid the repeated construction of UGS after gas reservoir exhaustion and improve China’s ability to ensure a long-term stable supply of gas.

The mechanical properties of foam materials are closely related to the mechanical properties of the matrix material and the geometrical characteristics of the microstructure. In this paper, a novel method of constructing a microstructural model of transverse isotropic closed-cell foam is proposed and uniaxial tensile simulations of PVC foam are carried out based on this model. The simulation results of the established finite element model are in good agreement with the experimental results. The effect of the change in aspect ratio and relative density on the mechanical properties in compression of the isotropic microstructure into a transverse isotropic microstructure is then investigated through numerical simulations, and the prediction equations for the tensile modulus and tensile yield strength of the closed-cell PVC foam are established. Finally, a relatively simple uniaxial tensile constitutive equation is proposed, so that the tensile stress–strain curve can be determined by as few parameters as possible. The parameters in the equation are related to the relative density and aspect ratio, and the phenomenological tensile constitutive equation is established.

Bitcoin is widely used as the most classic electronic currency for various electronic services such as exchanges, gambling, marketplaces, and also scams such as high-yield investment projects. Identifying the services operated by a Bitcoin address can help determine the risk level of that address and build an alert model accordingly. Feature engineering can also be used to flesh out labeled addresses and to analyze the current state of Bitcoin in a small way. In this paper, we address the problem of identifying multiple classes of Bitcoin services, and for the poor classification of individual addresses that do not have significant features, we propose a Bitcoin address identification scheme based on joint multi-model prediction using the mapping relationship between addresses and entities. The innovation of the method is to (1) Extract as many valuable features as possible when an address is given to facilitate the multi-class service identification task. (2) Unlike the general supervised model approach, this paper proposes a joint prediction scheme for multiple learners based on address-entity mapping relationships. Specifically, after obtaining the overall features, the address classification and entity clustering tasks are performed separately, and the results are subjected to graph-based maximization consensus. The final result is made to baseline the individual address classification results while satisfying the constraint of having similarly behaving entities as far as possible. By testing and evaluating over 26,000 Bitcoin addresses, our feature extraction method captures more useful features. In addition, the combined multi-learner model obtained results that exceeded the baseline classifier reaching an accuracy of 77.4%.

Issues such as technology, application and future development based on blockchain have always been hot topics. Future forms such as Web3.0 and the Metaverse are inseparable from digital identities and virtual tokens. This paper focuses on the recently popular Soulbound Token (SBT), introduces the concepts of digital identity, blockchain, and Decentralized Identity (DID) related to it, analyzes the shortcomings and challenges of SBT, and combines the consortium blockchain and DID. A new concept of Soulbound Token (DSBT) based on the decentralized identity of the consortium blockchain is proposed, which aims to make up for the technical deficiencies of SBT, and through the new concept of Displayable Credentials (DCs), DSBT combines DID for identity authentication, The advantages of access, in turn, can realize the concept of “programmable privacy” expected by SBT. Finally, the coping mechanism is proposed for the possible risks of DSBT, the application scenarios of DSBT in the active health intelligent care platform for the elderly are listed, and the future development of blockchain, DID and DSBT is expected.

The complex morphology of hydraulic fractures has been reported in layered formations due to the frequent occurrence of bedding. The success of hydraulic fracturing heavily depends on the vertical growth of hydraulic fractures. However, hydraulic fracture propagation in laminated rocks poses a complex problem due to the heterogeneity of the formations and bedding plane properties. This study employs a 3D finite element modeling considering bedding plane properties to simulate hydraulic fracture propagation in multi-lithologic interbedded strata and then validate the results with laboratory experiments. The hydromechanical coupled model proposed in this paper accounting for contact types, bedding friction coefficient and conductivity, rock layer distribution, stress and viscous fluid flow, which can well simulate the mutual interaction between hydraulic fractures and bedding planes. Numerical predictions are in good agreement with true triaxial fracturing experiments conducted. According to the numerical simulation and experiments results, the hydraulic fracture can exhibit one of the following behaviors: it may pass through the interface directly, extend along the interface after turning, or stop before reaching the interface. The results indicate that higher overburden pressure promotes the cross-layer propagation of hydraulic fractures. Only when the coefficient of variation between the vertical stress and the minimum horizontal stress reaches a certain threshold can the fracture penetrate the bedding. Hydraulic fractures may be arrested at the interface due to weak bedding strength or roughness. In the presence of multiple interfaces, hydraulic fractures may propagate along weakly-bonded interfaces with conductivity, which can lead to a decrease in the effective fracture area and a reduced efficiency of hydraulic fracturing. This study conducts further investigations and discussions on the influence of parameters, such as interlayer roughness and strength, interface permeability, on the fracture propagation. This research can provide insights into the mechanics of hydraulic fracture propagation in layered rocks and contribute to the development of unconventional reservoirs with more effective hydraulic fracturing techniques.

Low permeability fractured reservoir has the characteristics of non-even and non-continuous fracture distribution. In this paper, the equivalent permeability tensor is used to characterize fractured reservoirs based on the equivalent continuum media model. The initial fracture network model is generated based on the geological fracture description data, and then the equivalent permeability tensor is determined by the equal flow fundamental. Therefore, the fractured reservoir can be approximated as an anisotropic reservoir by the continuous equivalent media model. The meshless generalized finite difference method is a natural multi-point flow calculation scheme. It uses Taylor’s formula and weighted least squares method to obtain a generalized difference approximation scheme for the spatial derivative of an unknown function in the node influence domain. Compared with the multi-point flow approximation, this method can deal with the anisotropic permeability tensor more conveniently and reduce the calculation cost to some extent. In addition, the computational domain discretization scheme based on the meshless point cloud is more suitable for the irregular geometry of the actual reservoir. This method avoids the difficulty of grid-like numerical computation, which is to generate high quality matched mesh characterizing boundary to ensure the stability of computation at the boundary. The effectiveness and computational performance of the proposed method are verified by the examples of complex boundary crack networks, and the sensitivity of the influence radius to the computational accuracy is discussed. In summary, this work provides a new idea for numerical simulation of low permeability fractured reservoir.

Concrete prefabrication techniques have been popularized and utilized in building construction industry for years. To further improve the construction efficiency and quality for low-rise buildings, a prestressed hollow core wall system is proposed. Nonlinear mechanical behaviors of such a structural system are strongly determined by the occurrence timing and order of splitting and sliding of joints as well as cracking of concrete wall panels. In this paper, a detailed finite element model was developed in ANSYS to provide a tool for investigating the seismic behaviors of prestressed hollow core wall structures. Contact elements were applied to simulate the interaction between material interfaces. Techniques including coupling of degrees of freedom of overlapped nodes and deactivation of concrete elements were adopted, along with restart analysis to simulate nonlinear mechanical behaviors of the structural system. The developed modeling method was verified by experimental test results and was shown to accurately predict the global and local behaviors such as failure modes and load bearing capacities of precast hollow core walls. Pros and cons of the proposed simulation method were summarized, and suggestions were provided so as to improve the accuracy and versatility of this method to predict the global seismic behaviors of prestressed hollow core wall structures.

When aircrafts fly through thunderstorm areas, it is inevitable to suffer the impact of raindrops. The structures may be damaged by the multiple impacts. Therefore, rain erosion test is very important to evaluate the safety and service life of aerospace structures and involved materials. In the work, a multistage system is designed for high-speed raindrop emission based on the split Hopkinson bar technique, and is achieved experimentally. The high-speed camera is used to record the experimental process, and the size and velocity of raindrop are obtained. The results show that the velocity of the raindrop jet increased with the enhancement of loading speed, and the increase is greater than the loading speed. When the velocity of the striker bar is up to 28.22 m/s, the jet velocity can reach 50.90 m/s via acceleration of the emission system. Meanwhile, the raindrop mass is 365.03 mg, and the interval times can be up to more than 5 times. This work could fill the gap of the current high-speed raindrop impact loading technique, and provide the experimental techniques for the anti-raindrop properties of materials and structures from aeronautics and astronautics.

Bridge prefabrication and assembly construction technology has been popularized and applied from normal span bridges to large span bridges. The Nanyang Xiangjiang River Bridge in Wushi-Yiyang Highway is facing severe challenges such as: extreme environmental protection requirements in Dongting Lake area, deep and soft foundation and short construction period etc. The bridge adopts (76.3 + 3 × 120 + 76.3) m span corrugated steel web composite box girder with variable cross-section depth, erecting by factory prefabrication and site assembly. The design concept innovation and detailed structure of the bridge are introduced in this paper. In addition, the construction process and operation state of the bridge are simulated by finite element methods. The calculation results show that the overall bearing capacity of the bridge, the shear bearing capacity of the corrugated steel webs, the horizontal shear bearing capacity of the corrugated steel web connectors, and the bending bearing capacity of the corners of the corrugated steel web connectors meet the stress requirements. And the anti-slip margin coefficient of the corrugated steel web connectors is above 1.29, while the maximum tensile stress of the external prestressed steel strand of the bridge is 1043 MPa. At present, the bridge has been completed and opened to traffic, saving the construction period of 4 months, providing a significant reference for similar projects.

In this paper, the meshless generalized finite difference method (GFDM) is applied to the gas–water two-phase flow equation of complex-shape shale gas reservoirs. GFDM is a regional meshless method, in which the partial derivatives of unknown functions at any node can be expressed as differential approximations of other node functions in the node influence domain by using Taylor series expansion of multiple functions and least squares approximation. It overcomes the dependence of the discrete fracture method (DFM) on the grids and can obtain the finite difference approximation with higher precision. Compared with DFM, the meshless GFDM is based on the point cloud discretization which is more flexible to describe the complex geometric of the field case. Thus, reducing the computational freedom of the numerical model and the calculation cost. In the last, the numerical examples of the complex boundary demonstrate the computational performance of the proposed method for gas–water two-phase flow in shale gas reservoirs. In conclusion, this work provides an efficient meshless GFDM-based calculation method for solving the gas–water two-phase flow problem with the complex boundary conditions in shale gas reservoirs, and reveals the tremendous application potential of meshless GFDM in the numerical simulation of shale reservoirs with the complex boundary conditions.

Insufficient hole cleaning is one of the main reasons for pipes stuck in extended-reach drilling, especially while tripping. The mechanism of cuttings transport while tripping is with this investigated. First, a dynamic layering method with the Eulerian-Granular approach is established and verified. The dynamic layering method can simulate the axial movement of the pipe, and the Eulerian-Granular approach can simulate the two-phase flow. Next, the tripping operations of a connector-furnished pipe with and without circulation are simulated, and the sensitive parameter analysis is conducted. The results demonstrate that cuttings dune piles up in front of the connector (lower right corner), and the dune’s height increases with time. Moreover, the cuttings concentration around the connector when tripping with circulation is higher than that without circulation. So, it is safe to use the large flow rate after the cuttings have passed through the connector while tripping. Furthermore, the highest cuttings concentration decreases with the connector’s length, while increases with the connector’s diameter. This exploration is an essential guide to predicting and controlling tight spots while tripping.

Sea-crossing bridges are built for connecting important coastal cities. These bridges are subjected to extreme ocean wave actions, which pose serious threats to the bridges. In this context, this study examines the solitary wave impacts on a suspended flat plate and a coastal-bridge deck numerically by using the SPH (Smoothed Particle Hydrodynamics) open-source code SPHinXsys. The physical quantities including the wave profile, the velocity distribution near superstructures and the impact load on superstructures will be investigated. The research findings will provide some guidance on how to consider the extreme wave impacts in the design and maintenance of sea-crossing bridges.

The occurrence of fire in tunnel results in significant human losses and economic damages. The smoke propagation mechanism in tunnel has attracted a lot of attentions all over the world. Most of the previous studies focus on the stationary fire source scenario. However, few researches consider the transient movement of a burning vehicle and its effect on smoke propagation in tunnel. Therefore, to fill the research gap, this paper studies the influence of the moving vehicle on the smoke diffusion distance in tunnel using the dynamic mesh. Based on the geometrical parameters of an urban road tunnel, a 520 m long tunnel model is established. The dynamic mesh method used in this paper is verified by the experimental results by Kim. Multiple variables including the fire heat release rate and the vehicle speed are considered in the simulation. The results show that the propagation of smoke inside tunnel is mainly affected by the vehicle moving speed. Based on the simulation results, an empirical equation of smoke diffusion length is proposed to be used in the practical engineering application.

This paper presents the static aeroelastic analysis of the electric vertical takeoff and landing aircraft (eVTOL) ET480 by using the inner-house code AeLasV2.0.4. Firstly, the structure modeling of complete configuration for this type of eVTOL are implemented by using the geometrical nonlinear beam elements. The structural deformations are then predicted according to this finite element model. Secondly, when affording the high resolution CFD meshes, the aerodynamic performance is simulated accurately by solving the Renolds-Averaged-Navier-Stokes (RANS) equations. Third, the data interface between structural deformations and aerodynamic pressures are carefully designed to transfer information for the CFD/CSD coupling simulation. Finally, the static aeroelastic analysis is performed by AeLasV2.0.4 to estimate the aeroelastic behavior of ET480 to support its aerodynamic designing and structural designing.

During the exploitation of deep and ultra-deep sour gas-bearing gas wells in Sichuan, the casing-cement sheath-formation combination has been under high pressure and acidic environment for a long time. The stress variation law of the combination is complex, and the problem of sealing failure annulus pressure is serious. In this paper, the finite element software is used to establish a model of casing-cement sheath-formation combination with corrosion defects under high-pressure acid gas production conditions. The stress variation law of the combination under the change of casing internal pressure and formation pressure is clarified, and the sealing failure mechanism of casing-cement sheath-formation combination is revealed. The results show that corrosion is the key factor affecting the sealing failure caused by the stress change of the assembly, and the sealing failure of the assembly is related to the corrosion position. When the casing is subjected to uniform corrosion, as the degree of corrosion increases, the overall stress of the combination becomes larger, resulting in plastic strain between the cement sheath and the casing, and debonding between the plastic strain and the cement-well interface. The two factors together aggravate the continuous expansion of the microannulus at the cement-well interface. When the cement sheath is corroded, the cementation strength of the local cementing interface will be destroyed. With the expansion of the corrosion range, the stress of the combination is redistributed, and the stress distribution is gradually complicated. A certain degree of stress concentration is easy to occur at the corrosion position, resulting in plastic strain between the cement sheath and the casing, which in turn aggravates the failure risk of the cementing interface. In the design of gas well cement slurry containing acid gas, the corrosion resistance and the sealing performance of the cementing interface should be considered.

IP geolocation technology can estimate or determine the geographical location of terminal device through IP address, which is an important basis for location-based network services. The existing IP geolocation methods based on network measurement cannot accurately obtain the network environment when the target does not respond to the detection message, so it is difficult to achieve high-precision geolocation. To solve this problem, a reachable landmark grouping based IP geolocation method for unreachable target (RLGBG) is proposed in this manuscript. RLGBG first detects landmark data extensively, filters, evaluates and retains reliable and accessible landmarks. Secondly, RLGBG counts the topological relationship and geographical distribution among the reachable landmarks, groups the landmarks according to the common router, and divides the landmarks into different groups after checking by geographical location. Then, the continuous IP segments are divided into IP blocks according to landmark groups, and the location range of each IP block is calculated by the landmarks within each group. Finally, RLGBG counts the IP blocks containing the target, merges those IP blocks that are geographically coincident and topologically related, and estimates the target’s location by calculating the landmark center within the IP blocks. The geolocation experiments based on four cities in China show that RLGBG can effectively estimate the location of unreachable IP targets, and its accuracy and coverage are higher than the existing typical method and IP location databases.

Offshore oil and gas resources are hot spots for development in various countries, but developing deepwater formations will inevitably encounter problems such as ultra-HTHP (high temperature and pressure), narrow safety density window, and complex formation structures. Improper handling can cause kick, blowout and other drilling complications, which will not only cause environmental pollution, but also threaten engineers’ lives. At present, the basic means to deal with kick is still through the engineer to control the opening of choke valve, but the manual control has long adjustment time, large pressure fluctuations, and extremely dependent on the engineer's work experience. With the development and advancement of artificial intelligence and automation technology, oil and gas well pressure control also needs to integrate artificial intelligence and automation technology to carry out research on automatic control system for choke and well killing manifold in deep water for accurate and fast control of wellbore pressure. In this paper, we designed a deepwater choke and well killing manifold automatic control pressure system based on the optimized PID control method and built equipment to conduct simulation experiments to test the ability of the system to track the target pressure stably and quickly as well as the ability to track the continuous pressure curve. The results show that the system can adjust choke valve in place within 35 s during the experimental process of simulating kick and automatic pressure control, at which time the system pressure is stable and the pressure fluctuation is less than 0.02 MPa. This indicates that the deepwater choke and well killing manifold automatic control pressure system established in this paper has the advantages of fast pressure adjustment and high adjustment accuracy, which can replace engineers in automatic control to a certain extent and provide a guarantee for the safe development of offshore It provides a guarantee for the safe development of oil and gas.

The formation pressure system of Yinggehai Basin has the characteristics of poor horizontal distribution regularity and severe vertical distribution changes. This paper proposes a new method for predicting the horizontal and vertical distribution trend of formation pressure for the situation of limited offshore drilling data. The method is based on the topological triangulation algorithm, combined with the data set to fit the multivariate interpolation function, and conveniently realizes the prediction and visualization of the three-dimensional horizontal and vertical distribution trend of regional formation pressure. On this basis, through the analysis of the relevant data of the complex accident points that have been drilled, the characteristics of the single well safety density window and the regional safety density window are clarified. The study found that there is no high pressure in the shallow layer of the block, and the formation pressure spreads smoothly in the lateral direction; the high pressure top surface is at 3500 m, and the formation pressure gradually increases with the increase in longitude and decrease in latitude in the lateral direction. The formation pressure rises extremely rapidly with the increase of depth in the longitudinal direction, which has the characteristic of “broken line pressurization”. The safety density window of single well is in the shape of funnel with the characteristic of turning back, and the turning section is between 3500 and 4000 m. The safety density window feature of the block can be divided into three stages according to the depth, and the window appears extremely narrow after 3500 m (< 0.3 g/cm3).

A multi-level substructure framework is built on the SiPESC (Software Integration Platform for Engineering and Scientific Computation).FEM. The framework separates the essential functions of the substructure method, such as domain decomposition, static condensation, and task scheduling, from the software function design perspective. The functionalities of multi-process computing and multi-threaded computing are separated into multiple plug-ins by separating task management and calculation. The framework is used to compute static analysis, transient response analysis, frequency response analysis, vibration eigenvalue analysis, and buckling eigenvalue analysis, among others. The framework is explained in three layers: software architecture design, component design, and parallel design. This article investigated and discussed graph partitioning, memory control in large-scale computing, and the computation of comparable structures. This article demonstrates the domain decomposition, various analysis type simulation, cluster-based parallel computing examples, and hundreds of millions of degrees of freedom examples to demonstrate the framework's practicability and dependability.

The oil production rate of the ultra-low permeability reservoir decreases rapidly after volume fracturing, and reservoir energy replenishment is in urgent need to enhance the production performance. However, due to the poor reservoir physical property, water injection into the ultra-low permeability reservoir is quite difficult, resulting in unsatisfactory development effect. To evaluate the effectiveness of water alternating CO2 (CO2-WAG) flooding in ultra-low permeability reservoir block Z, oil samples from a typical well were used to carry out laboratory experiments, including oil composition analysis, constant composition expansion and CO2 swelling test. After fitting the experimental results, a numerical simulation model containing four five-point patterns developed by CO2-WAG flooding was established. The production and seepage characteristics of CO2-WAG flooding were studied, and the parameter sensitivity analysis was conducted. The results showed that: (1) CO2-WAG flooding could maintain a longtime stable production with high oil rate, and significantly improve the production effect of the ultra-low permeability reservoir; besides, dynamic CO2 storage could be achieved with the storage percent of 70% during the flooding process. (2) CO2-WAG flooding has the following effects, including replenishing reservoir energy, expanding sweeping volume and improving oil displacement efficiency, and the development effect is obviously better than that of water flooding. (3) When the CO2-WAG flooding was implemented immediately at the reservoir starting production with 6-month alternating cycle and 1:1 CO2-Water ratio, good production performance could be achieved. The results obtained from this research can provide guidance in effectively developing block Z.

Because of the heterogeneity of the formation, different parameters such as formation permeability and porosity may occur in the three zones. Contamination zones exist at the regional intersection due to the mismatch between extraneous fluids and formation fluids meanwhile, especially in low-permeability reservoirs, where the effect of such contamination zones is more obvious. According to the situation of this kind of radial composite reservoir, a test well model for a three-zone dual-porosity radial composite reservoir was established by considering the effects of wellbore storage, interface skin effects, and interfacial resistance, by introducing an “interfacial skin” into the interfacial conditions. Through Laplace transform and numerical inversion method, the typical well test curve was drawn, and the effect of various factors on the typical well test curve was analyzed. Through the analysis of the characteristic curve, it is shown that the interface resistance has certain effect on the bottomhole pressure of the dual-porosity three-zone radial composite reservoir.

The tight oil reservoir has large resources, but the reservoir has poor physical properties, and there are problems such as rapid decline in oil recovery rate and low recovery rate after volume fracturing. To solve these problems, taking block X as an example, the production characteristics of CO2 huff-and-puff were numerically studied using CMG software on the basis of experimental data fitting. The results show that: CO2 huff and puff can significantly increase the daily oil production level, with the highest daily oil production increasing nearly four times, significantly improving the recovery rate of tight oil reservoirs; CO2 huff and puff can better supplement formation energy, expand swept volume and improve oil flooding efficiency; Higher oil production can be obtained with higher CO2 injection rate and longer soaking time. With the increase of gas injection rate, the oil production has a certain fluctuation; Under the research conditions of this paper, when the Cumulative oil production is 1500 t/d, the soaking time is 50 d, and the CO2 injection rate is 50 t/d, the effect of CO2 huff and puff mining tight reservoir is better. The research results are helpful to strengthen the understanding of the production characteristics of tight reservoirs developed by CO2 huff and puff.

In this paper, a steel stiffened plate is used as the research object and its blast response under the action of air blast load is simulated and studied. Assuming that the deformation mode of the dynamic response of the reinforced plate is the same as the static limit deformation mode, the energy principle and the plastic deformation principle of the reinforced plate structure are used to analyze and obtain the motion control equations of its plastic dynamic response under the action of the blast impact load. Meanwhile, the simulation analysis of the stiffened plate under the air blast load is carried out using the finite element software ABAQUS, and the deformation theory of the reinforced plate structure is verified according to the simulation analysis results. It provides a reference for the design and impact resistance evaluation of steel stiffened plates.

Power big data technology is playing an increasingly important role in the regulation and data analysis of smart grids, which face “data silos” and privacy issues. Federated Learning is a distributed machine learning framework and allows model training to be done without compromising user raw data. To protect private information, the model parameters uploaded by the user are usually trained in cipher text. However, the presence of ciphertext data makes it difficult to audit the quality of data uploaded by users. Smart grid federated analysis tasks are vulnerable to attackers launching attacks such as data poisoning and free-riding, which can have a serious impact on the global model trained. To defend against data poisoning and free-riding attacks, there is a need to audit encrypted grid data uploaded by users. In this paper, we propose a blockchain-based power-related data quality audit method that can ensure the correctness of the smart grid federated analysis model. In particular, we design an efficient noise addition mechanism that makes the aggregation model parameter noise sum to zero, which can protect user data privacy while ensuring the usability of the aggregation model. In addition, we propose a grouped aggregated data quality audit algorithm that can quickly locate users who upload malicious data. We conducted experimental evaluations on both the Real Power dataset and the MNIST dataset, the results showed that our approach is effective against data poisoning and free-riding attacks.

The rapid development of the federated machine learning paradigm has broken down the data barriers in technology between different organizations and individuals, allowing data that was previously difficult to analyze collaboratively to be used to unimaginable value. Among them, federated random forest has gradually gained popularity among collaborative analysis users for its good adaptability to structured data. However, the contradiction between the demand for collaborative analysis services and users’ awareness of privacy-preserving is becoming increasingly prominent and has become a bottleneck hindering the healthy and orderly development of the big data industry. To this end, this paper comprehensively analyzes the privacy preservation and usability requirements faced by federated random forest, and investigates a differential privacy-based federated random forest approach FEDEST. Users design privacy budgets locally, build CART decision trees with noise through a selective noise addition mechanism, and then upload them to the server for aggregation into a random forest, and optimize the random forest model through multiple rounds of iterations. FEDEST can improve the accuracy of business analysis models while safeguarding the privacy information of collaborative analysis participants. Experiments on the Adult and BRFSS datasets show that FEDEST has the highest classification accuracy of 91% and 87%, respectively, which is close to the classification accuracy of non-federated forest.

This paper analyzes the structural response of folded steel sandwich plates under an air explosion shock load. According to the analytical calculation method of the sandwich plate's structural deformation, the structural deformation prediction formula under the action of explosion impact load is obtained. At the same time, the nonlinear finite element analysis software ABAQUS was used to simulate the related calculation conditions and verify the structural plastic deformation formula. On this basis, the sensitivity analysis of parameters of sandwich panel structural size was conducted to study the influence of parameters on sandwich panel structural size, and the applicability of the analytical calculation method for folding sandwich panel was verified, providing a reference for the design and impact resistance evaluation of steel folding sandwich panel.

With the rapid development of ships, the problem of bow slamming becomes very prominent. In this paper, based on the impact test data of water entry, a two-dimensional wedge shape test model was established by ANSYS/LS-DYNA finite element software, and simulation analysis was carried out on the model, focusing on the impact of different oblique lifting Angle and water entry speed on the impact load, the change of pressure during the impact process and the liquid level lifting phenomenon of the structure during water entry. The results show that when the wedge contacts the water surface, the slamming pressure increases instantly, then decreases gradually and becomes stable. With the decrease of tilt Angle and the increase of water entry velocity, the slamming pressure increases obviously, and the vertical slamming force also increases. When the inclined rise Angle is small, the peak value of the slamming pressure obtained by numerical simulation and impact test has a slight deviation. In this case, the thinner jet needs to be simulated with a denser grid. The research results can provide a reference for related research.

This paper investigates a fuzzy-logic-based integrated orbit-attitude-vibration prescribed-time controller for large-scale flexible spacecraft to achieve the high-precision orbit-attitude-vibration stabilization. Due to the existence of nonlinear coupling effects, a refined T-S fuzzy model based on the orbit-attitude-vibration dynamics of large-scale flexible spacecraft is constructed to represent the nonlinear characteristics and avoid the calculation singularity. Then, a prescribed-time controller is designed to stabilize the closed-loop system within a prescribed time with precise convergence rate where Lyapunov stability analysis is performed to prove the prescribed-time stability. Simulation results shows the effectiveness of the proposed control strategy.

The high overload and high maneuverability in the training course result in the structural damage and the life consumption speed is accelerated, the use of each model is obviously higher than the expected use, which greatly increases the risk of the operation of aircraft. The life design and verification work based on the design load spectrum in the design stage cannot meet the requirements of ensuring the flight safety in the whole life of aircraft. How to ensure the security of active military aircraft under the change of actual use mission has become an urgent problem to be solved. Based on the analysis method of structural fatigue individual aircraft tracking, this paper expounds the design method and task profile of individual aircraft, studies the calculation of equivalent damage of individual aircraft, puts forward three classification methods of usage severity of aircraft, which are mild severity, severity moderate and heavy severity, and carries out the determination of reference equivalent damage for the object aircraft. In addition, the interval classification method is used to classify the usage severity, and the method of the usage severity analysis is provided.

Six degrees-of-freedom (6-DOF) motion of structures and fluid–structure interactions (FSI) widely exist in engineering fields. It is significant to study the 6-DOF motion for simulating the motion trajectory and fluid–structure interactions. In this paper, the smoothed particle hydrodynamics (SPH) method combined with improved numerical techniques is used to simulate the fluid–structure interactions, and the 6-DOF equations based on the quaternion method are adopted to simulate the 6-DOF motion of skipping stones in the three-dimensional numerical tank. The accuracy of this method is verified by comparing it with the experimental snapshots, which can prove that the simulation results of skipping stones are in good agreement with the experimental results. As a result, the quaternion method can simulate water entry processes of structures with high-speed spin more accurately and is more suitable for the calculation of 6-DOF motion.

Recent years have witnessed the rapid development of aerospace science and technology, and the orbital game technology has shown great potential value in the field of failed satellite maintenance, debris removal, etc. In this case, orbital game is often characterized by nonlinear dynamic model, unknown state information, high randomness, but the existing approaches to deal with game problem are difficult to be applied. The analytical method based on game theory is only applicable to simple scenarios, and it is challenging to find the optimal strategy for such complex scenarios as satellite swarm game. It should be noted that deep reinforcement learning has some research basis in the cooperative decision-making and control of multi-agents. In view of its powerful perception and decision ability, this paper applies deep reinforcement learning to solve the orbital game problem of satellite swarm. Firstly, the game scenario is modeled, where typical constraints, e.g., minimum time, optimal fuel, and collision avoidance, are taken into consideration in the game process, and then the multi-agent reinforcement learning algorithm is developed to solve the optimal maneuver strategy. The algorithm is based on the Actor-Critic architecture and uses a centralized training and decentralized execution approach to solve the optimal joint maneuver strategy. For different task scenarios, the action space, state observation space, and reward space are designed to introduce more rewards that match the specific game tasks to make the algorithm converge quickly, so that the satellite swarm emerges and executes better intelligent strategies to complete the corresponding game task.

The existence of the vacuum tube train can improve the efficiency of transportation. However, the complex aerodynamic phenomena cause drastic environmental fluctuations in the tube, which are concentrated on pressure and temperature. On the background of an under-constructed test platform, using three-dimensional numerical methods, a vacuum tube train model is established to analyze the environmental changes on the surface of the train dynamically during the acceleration process, uniform motion process and deceleration process. The result proposed that the specific aerodynamic phenomena such as shock wave, expansion wave and choked flow, are the main reasons for the changes of pressure and temperature. During the acceleration process, the generation of the shock wave, expansion wave and choked flow causes the drastic changes of the temperature and pressure. During the uniform motion process, a normal shock wave generated in front of the choked flow enhances the increase of temperature and pressure, yielding the maximum values at the end of this process. During the deceleration process, the disappearance of shock wave and the reflection of the expansion waves in the rear cause the sudden changes on the temperature and pressure.

Ground flutter simulation test (GFST), which simulates the unsteady aerodynamic force on the structure through the excitation forces generated by shakers, is a semi-physical simulation test method on the ground to verify the aeroelastic stability boundary of the real structure without the wind tunnel. However, when the structure is excited by multiple electrodynamic shakers, the dynamic characteristics of the shakers and the coupling effects between the structure and shakers make the actual exciting forces acting on the structure are usually not equal to the required values that is supposed to be, such as the simulated aerodynamic forces. To deal with this issue, a model-based decoupling control framework for aerodynamic loading system is proposed to trace the simulated aerodynamic force for each shaker, which is divided into the following two parts: (1) the modeling of aerodynamic loading system; (2) the pre-feedback compensation decoupling controller. The state space model of aerodynamic loading system is established with substructure synthesis method, which couples the FEM model of structure to lumped parameters model of shakers. In order to enhance the robustness and control accuracy of the controller, genetic algorithm is used to optimize the model parameters of the aerodynamic loading system model before the decoupling controller is designed. Subsequently, both the excitation force waveform control experiments and the GFSTs are conducted on the GFST system composed of a fin model and four shakers to demonstrate the proposed method. Results show that the aerodynamic loading system can trace the simulated aerodynamics forces accurately within the target frequency range. The model-based pre-feedback compensation decoupling method can effectively eliminate the coupling effects among the shakers, and have the advantage of a simple decoupling network, a wide control frequency range and good robustness. Therefore, using the aerodynamic loading system with the proposed control method can effectively expand the application of ground aeroelastic simulation test.

Differential privacy is applied to machine learning for privacy protection because of its formal privacy guarantee. Differentially private algorithm needs to inject enough noise to limit the overall privacy disclosure risk of the training set. In the case of unbalanced data sets, however, this privacy protection intensity is excessive for most datasets, leading to significant loss of utility. In this paper, we adjust the training set by assessing the risk of disclosure of data privacy and its contribution to model accuracy to improve the utility of differentially private ML. Specifically, we quantify the risk of data privacy disclosure through membership inference attacks and evaluate the contribution of data to improving model accuracy through ablation experiments. Our experiments show that when the training set of the model is unbalanced, the model accuracy can be substantially improved by adjusting the training set to our assessment method under the same budget of privacy.

The existence of the ultra-wide road tunnels improves the transportation efficiency and promotes economic development. However, fire hazards cannot be ignored. Thus, a single entrance 4-lane road tunnel is selected to explore the fire smoke control effect of an ultra-wide road tunnel with lateral exhaust. First, a scale model experiment is utilized to verify the accuracy of the numerical model and then in the influence of the most unfavorable position of the fire source, the number of open smoke outlets and the amount of smoke exhaust volumes on the smoke control effect of tunnel fire under the lateral exhaust mode is simulated by a three-dimensional model. The results show that the distribution pattern of fire smoke in an ultra-wide road tunnel under the lateral exhaust mode is affected by the lateral position of the fire source. When the fire source is closer to the sidewall of the exhaust duct, the smoke distribution that is inclined to the sidewall of the tunnel is more obvious. Based on the comparison among the time of the smoke spreading to the tunnel entrance, the spreading distance of 60 °C smoke, and the smoke exhaust efficiency under various working conditions, it is concluded that the most unfavorable lateral fire source location is in the middle of the tunnel. What’s more, 4 open smoke exhaust ports with 200 m3/s exhaust volume near the fire source can achieve the best smoke control effect.

Using kinetic energy to crush high-strength rocks and then collect particle samples has attracted much attention in the Near-Earth Asteroid (NEA) sampling scheme. In this study, two deformable special-shaped projectiles of tantalum: petal-penetrating type (T1), petal-non-penetrating type (T2), and high-speed (453.0–612.0 m/s) impact experiments, were designed to study the projectile-target interaction and rock fracture mechanisms based on a 14 mm ballistic gun platform. Results shown that deformation of the Special-Shaped Projectile is related to the plasticity of material and projectile configuration; The projectile-target interaction of the T2 is two-phase processes: multi-point simultaneous impact and the Taylor impact, which increase the diameter and depth of the crushing zone and raise the mass of spalled-rock particles about three times than T1. The two-phase processes inspiring to create the projectile’s head and cylinder section from different properties of materials respectively. This research inspires the design of the deformable special-shaped projectile and the comprehension of the fracture mechanisms of rocks under high-speed impact.

The Enhanced Geothermal System (EGS) involves a complex thermo-hydro-mechanical-chemical (THMC) coupling process during long-term heat extraction. However, many models used to solve fractured reservoir problems are computationally time-consuming, especially when dealing with reservoir-scale engineering problems. To address this challenge, this paper proposes a novel THMC coupling model that solves the governing equations using a unified FVM framework based on the embedded discrete fracture model (EDFM). The accuracy of the model is confirmed by comparing the THC coupling and displacement (M) results with the Fully Resolved Solution Method (FRSM) from MRST software and COMSOL, respectively. Moreover, the model developed is utilized to simulate and analyze the spatiotemporal behavior of pressure, temperature, concentration, and mechanical deformation in EGS. The results suggest that the model is appropriate for effectively assessing the long-term production performance of EGS.

In the current booming big data boom, many fields still face the problem of data scarcity. Synthetic data, as a new technology in the field of big data, not only tries to retain the main features of the original data for analysis, but also tries to avoid containing information that may cause privacy leakage. Synthetic data provides a new solution for the problems of data security sharing and artificial intelligence training. This paper summarizes the main methods, performance evaluation indexes and application of synthetic data, looks forward to its military application prospect, and puts forward the preliminary idea of military application of synthetic data, which provides reference for the research in related fields.

According to the performance evaluation and optimization research requirement of counter-rotating propellers aeroacoustics, based on ground acoustic environment, a set of counter-rotating propeller aeroacoustics test platform was built. The aeroacoustic test of counter-rotating propeller was carried out in a semi-anechoic chamber. The aerodynamic performance and far-field noise characteristics of the counter-rotating propeller were obtained, and the distribution of far-field noise were analyzed. The results show that the tension, torque and power increase with the increase of rotating speed. The amplitude distribution of sound pressure level of far-field noise will move with the change of speed. The discrete noise at each passing frequency is also different. The test platform and the test scheme could provide help for the aeroacoustic evaluation and optimization design of counter-rotating propeller under ground takeoff condition.

The rapid development of the global economy and the sharp rise in population has increased human demand for energy. Hot dry rock (HDR) geothermal energy has attracted much attention because of its wide distribution, huge reserves, and high stability. Enhanced geothermal systems (EGS) are used for the extraction of HDR, whose recovery performance has a highly non-linear relationship with actual production constraints. Therefore, accurately predicting geothermal productivity is an important task for managing sustainable geothermal systems. In this paper, we use a convolutional neural network (CNN), a long short-term memory network (LSTM), and hybrid models based on a convolutional neural network and a long short-term memory network model (CNN-LSTM) for prediction. The dataset is obtained from numerical simulations on the dynamic economic performance of EGS extraction with different well model parameters and fracture parameters. The performance of different neural networks for geothermal capacity prediction is evaluated comprehensively. The results show that the CNN-LSTM neural network can predict geothermal energy production accurately and stably. Compared with the original LSTM and CNN neural networks, the combined network has the best geothermal capacity prediction accuracy, stability, and generalization ability. This study provides a highly accurate and efficient prediction method for geothermal capacity prediction.

Dynamic buckling of submerged cylindrical shells subjected to underwater explosion (UNDEX) seriously threatens the safety of structures. Due to fluid–structure interaction, geometric and material nonlinearities, the relevant theoretical, numerical and experimental studies are very limited. Dynamic buckling of a stiffened cylindrical shell subjected to the UNDEX shock wave is numerically studied by the coupled acoustic-structural formulation in ABAQUS/Explicit, and the influence of the mesh size of the cylindrical shell on the buckling behavior is investigated. Both the hydrostatic pressure and the UNDEX shock wave acting on the shell are considered in the finite element model. The mesh size for the static buckling analysis of unstiffened cylindrical shells, $$\sqrt {R{\text{t}}} /2$$ R t / 2 , is taken as the benchmark of the mesh size of the cylindrical shell, where R is the radius of the cylindrical shell, and t is the thickness of the shell. Then, different smaller mesh sizes of the cylindrical shell and the flow filed are adopted. Numerical results show that the mesh size of the cylindical shell has significant influence on the dynamic buckling of the cylindrical shell subjected to UNDEX shock wave. Furthermore, the suggested mesh size of the cylindrical shell is proposed.

Distributed denial-of-service (DDoS) attacks have become a constant threat to modern networks, and how to detect and respond to them is a key challenge for network operators. Data plane programmability is a promising technology that enables fast control loops to detect and mitigate cyberattacks. At the same time, the domain-specific language P4 used by the programmable switch allows users to flexibly customize DDoS detection methods and attack mitigation behaviors, so the programmable switch can bring some new opportunities for DDoS attack detection. This paper proposes an in-network architecture for DDoS attack detection that combines the entropy of statistical measures describing traffic distribution and machine learning models for network devices. The proposed sliding window detection mechanism completes the fine-grained detection of a single packet within the linear time complexity, and the machine learning model can perform secondary detection of the flow of normal packets in the suspected DDoS attack window to improve the accuracy of detection. We evaluated the proposed framework using real publicly available traffic tracing as input to the experiment, the results show that our framework has the advantages of high accuracy, fine-graininess, and coverage of a wide range of attack types compared with state-of-the-art methods, and is completely executed on the data plane.

With the increasing proportion of car transportation in the school-wide mode, the traffic jam of different degrees will be formed at the entrance of every primary school in Shenzhen, this phenomenon not only wastes the time of parents and students, affects personal safety, but also causes great pressure to the traffic operation and management around. At present, there is no good solution to this problem, and there is also a lack of in-depth research. As an effective way to ease the parking problem in the city center, “Parking sharing” has attracted the attention of some scholars at home and abroad in recent years. However, most of the existing studies are biased towards the specific parking lot to do a period of time in the future parking supply forecast, and do not take into account the parking demand of primary schools, in the actual operation process, there is a common situation that the prediction precision of shared parking is not enough and can not fully meet the parking demand. Based on the theory of shared parking spaces, this paper transfers the parking demand of primary school to the surrounding social parking lots, which can alleviate the traffic disorder in front of school and ensure the safety, the utility model can also improve the utilization rate of parking spaces in social parking lots. The supply of parking spaces plays an important role in evaluating the social and economic benefits of parking spaces. The supply law of parking spaces is different in different types of allocated parking lots, the trend of free shared berth is different with time. With the aim of improving the clarity and reliability of the information on free parking spaces in car parks, this paper takes three key primary schools in Luohu District as an example, and obtains the time-varying data of historical parking spaces in various types of car parks around primary schools through the parking space sharing platform, the ARIMA and BP neural network models are used to forecast the time span of parking lots in different land use types, and the applicable prediction methods of shared parking spaces are found. The results show that the smaller the time span is, the higher the prediction accuracy is. BP neural network model is more suitable for office area and part of commercial area, while ARIMA model is more suitable for residential area. This study has great practical significance for mining the parking supply capacity, reducing the construction of parking facilities and investment, reducing the demand for parking space, optimizing the transportation environment in primary schools, and improving social and public benefits.

Multi-lateral well technology is a new drilling technology developed after directional well, lateral drilling and horizontal well technology. As the extension and development of horizontal well technology, multi-lateral well technology has obvious technical and economic advantages in reducing drilling cost and improving recovery efficiency of new and old oil fields. Multi-branch well technology takes drilling and completion technology as the main difficulty to tackle. Multi-branch well technology is a new drilling and completion technology to increase the production of oil and gas well by increasing the drainage area of oil and gas reservoir. It is one of the important technologies in the field of drilling in the twenty-first century. This paper, by investigating the progress of multi-branch well at home and abroad, focuses on the types of multi-branch well and the application of key drilling and completion technologies, as well as the application of multi-branch well technology in the oilfield, and gives an outlook on the current multi-branch well technology.

In this paper, a double-boundary CHIEF method is constructed based on the idea of the combined Helmholtz integral equation formulation (CHIEF) method by adding supplementary equation for overcoming the non-uniqueness of the boundary integral equation at the eigenfrequency. The conventional boundary element method (CBEM) equation is coupled with the virtual indirect boundary element method (VIBEM) equation. Because the CBEM equation and the VIBEM equation are located at different boundaries, their eigenfrequencies are not coincident, which theoretically avoids the failure of the supplementary equation in the traditional CHIEF method. At the same time, according to the equivalence of the coefficient matrix between the CBEM and VIBEM, the singular matrix is obtained indirectly by replacement calculation. Through the analysis and verification of numerical examples, the non-singular dual-boundary CHIEF method proposed in this paper can effectively overcome the non-uniqueness of the conventional boundary element method at the eigenfrequency, and can obtain high-precision and robust results in the full wavenumber domain. The accuracy of the proposed method is much higher than that of CBEM and Burton-Miller method without singular integral processing.

This paper investigates the stress and geometry shape of a pedestrian bridge with a curved beam and an inclined arch during the construction process using numerical simulation and field testing. The results reveal that the stress and geometry of the arch ribs and the main beam would vary noticeably as a result of the initial development of the beam-arch combination system after the cable is tensioned, which may result in a significant safety risk. During the whole construction process, the measured stress and geometry of the bridge show a good agreement with the numerical results by means of the finite element (FE) method, and are subjected to the requirements in the design, which indicates that the construction control of the bridge is reasonable. The output of this study can provide important scientific insights as well as practical applications for similar bridges.

In the exploration and development of oil and gas wells, perforation completion is the most commonly applied method of well completion. The formation of fracture networks near the wellbore during perforation is directly influenced by fractures near the wellbore, which have direct effects on the flow of hydraulic fracturing fluid. A three-dimensional perforation numerical calculation model is developed using the FEM-SPH coupling method. This is coupled with the theory of impact dynamics. FEM-SPH coupled perforation numerical models have been used to investigate fracture formation and propagation laws during perforation. In the study, it was found that when perforating the rock along the direction of maximum principal stress, a significant number of fractures could be formed. In addition, the length of these fractures was relatively long. Fractures are formed as a result of the radial tensile stress of the rock near the wellbore, and fractures are formed along the radial direction during the perforation process. It is primarily the circumferential tensile stress of the rock that determines the expansion of fractures near the wellbore. Perforation parameters and fracture parameters can be improved by using the research results presented in this paper as a reference.

The durability problem of concrete and prestressed concrete structures caused by corrosive effects of various media in the environment has become a hot topic in engineering and academic circles. However, the research results on the deterioration of prestressed concrete performance under various corrosive media in typical industrial environment are still insufficient. Combined with acidic industrial environment of the corrosive medium, the corrosion mechanism of prestressed concrete is clarified, and on this basis, time-varying models of prestressed concrete material with engineering practicability is explored. An original model of concrete strength degradation described with pH is established, and a constitutive model considering the stress corrosion of the prestressed strand is put forward. Based on the stochastic process theory of component resistance and the corrosion degradation model of materials, the time-varying performance analysis of corroded components with bearing capacity is carried out using the statistical theory and the Monte-Carlo event-based simulation. Compared with the existing test results the accuracy of the material deterioration model is verified. At the same time, according to the simulation results, it is concluded that the corrosion of steel bars in the elastic stage has little influence on the mechanical properties, but has great influence on the stiffness and bearing capacity of the beam after cracking.

Horizontal well is the main well type of ultra-deep shale oil exploitation, and the prediction of temperature field in the horizontal well managed pressure cementing (MPC) process is of great significance to the field construction. Based on energy conservation and thermal resistance method, taking conventional three-stage well as an example, the prediction model of wellbore temperature field in ultra-deep horizontal wells of shale oil was established. The effect of well trajectory and fluid performance parameters on temperature field were considered comprehensively to improve the prediction accuracy of the model. A well in China was taken as an example to verify the model, and the model can simulate the changing law of various parameters and has good applicability. The influence factors of temperature field were analyzed. The results show that the temperature of drill pipe and annulus decreases with the increase of cycle time. The formation temperature at wellhead increases with the increase of cycle time, while the formation temperature at bottom hole decreases with the increase of cycle time. The length of horizontal section has little effect on bottom hole temperature. The inlet temperature of cementing fluid has little influence on the long horizontal section. Increasing cementing fluid density, displacement, and time can reduce bottomhole temperature. The research results provide a theoretical basis for the exploration and development of ultra-deep shale oil.

In the context of the information age, electronic documents have replaced traditional paper documents and become the most commonly used data carrier in work. Compared with traditional paper documents, the cost of electronic documents is lower, and it is convenient for the modification and transmission of information, which brings great convenience to the work of users. However, while electronic documents bring convenience to users, digital copyright infringements are ubiquitous because of their ease of duplication. To protect the user’s document security, this paper develops a decentralized electronic document sharing framework based on blockchain non-fungible token (NFT) technology. We have designed an on-chain and off-chain collaborative storage solution for off-chain storage of source files and on-chain storage proofs for file storage. By setting the challenge period and extracting file keyword groups for file duplication detection, the user's copyright is protected. And develop smart contracts based on solidity language, design access control mechanisms, realize copyright deposit certificates, copyright confirmation, copyright infringement detection, and document sharing.

As a part of aviation flight guarantee, physical and chemical testing in the aviation industry plays a very important role. The traditional physical and chemical testing industry has problems such as long process waiting time and slow generation of test results and reports. Although laboratory management systems such as the LIMS (Laboratory Information Management System) have improved these problems to a certain extent, the LIMS system has not fundamentally changed the above problems and lead to new problems. Based on the particularity of the aviation physical and chemical testing system, as well as the requirements for high consensus, high synchronization, and high traceability of data, blockchain technology is very suitable as a means of improvement. Based on blockchain technology, this paper designs a new type of the aviation physical and chemical testing system strives to improve the problems existing in the current aviation physical and chemical testing system and improve production efficiency.

Inadequate hole cleaning is one of the main reasons for pipe stuck in extended-reach drilling, especially while back reaming. The mechanism of cuttings transport while back reaming is hereby investigated. First, a coupled dynamic layering and sliding method with the Eulerian-Granular approach is established and verified. The sliding mesh method is applied to simulate the pipe rotation, and the layering mesh method is used to simulate the movement in the axial direction. Next, the tripping operation of a connector-furnished pipe is simulated, and the sensitive parameter analysis is conducted. The results demonstrate that cuttings pile up in front of the connector while tripping, which may bring a risk of a stuck pipe. The cuttings pile decreases with the circulation time and rotational speed of the pipe. The tripping velocity has minimal effect on the cuttings distribution after the cuttings pass through the connector. Moreover, the significant flow rate can be more safely employed after the cuttings have passed through the connector furnished with a large diameter, such as the bottom hole assembly. This exploration is an essential guide to predicting and controlling tight spots while tripping.

The integration of two technologies, Cloud Computing and Software Defined Network (SDN) has placed cooperative orchestration between cloud and network into the focus of attention. However, with the continuous expansion of network scale, the data center would inevitably accommodate multiple SDN network devices which are produced from various manufacturers, and even these devices are associated with different SDN technologies. Therefore, application scenario with multi-domain heterogeneous SDN networks occurs. The interoperability and orchestration of cross-domain services, as well as unified management of devices from multiple domains, have become a challenge. At present, except for OpenFlow, the mainstream technologies for SDN implementation include segment routing technology based on MPLS (SR-MPLS) and that based on IPv6 (SRv6). This paper proposes a general SDN controller system framework. This framework is able to shield the discrepancies, which is caused by different SDN technologies, between northbound interfaces of SDN controllers from multiple manufacturers. Besides, it supports unified management of network resources to solve the difficulties of orchestration of cross-domain service in SDN network. Furthermore, this system framework follows the design principles of high cohesion and low coupling, and regard every adapter that manages one SDN domain with specific technology as one sub-module in the whole adapter module, hence with flexible expansion.

Objective: To systematically analyze the efficacy and safety of rivastigmine combined with memantine in the treatment of mild to moderate Alzheimer’s disease. Methods: In this paper we searched the Chinese and English literature from the date of establishment to August 9, 2022, the included studies met the requirements of rivastigmine combined with memantine for the treatment of Alzheimer’s disease as the trial group, and rivastigmine or memantine alone for the treatment of Alzheimer’s disease was the control group and two researchers performed screening for inclusion, quality evaluation and risk assessment according to the criteria, extracted data and performed statistical analysis of mental status scores and adverse events using generalised linear model Meta-analysis with Markov chain Monte Carlo algorithm. Results: The final study included 8 publications containing 382 patients in the trial group and 376 patients in the control group, for a total of 758 patients. 8 studies had a total MMSE assessment score [weighted mean difference (WMD) = 1.52, 95% CI (0.32–2.73), P = 0.01] and 5 studies had adverse events [dominance ratio (RR) = 1.09, 95% CI (0.92–1.29), P = 0.31], and the results of the reticulated Meta-analysis remained generally consistent with the results of the binary Meta-analysis. Conclusions: The MCMC algorithm has a high degree of accuracy, the combination of rivastigmine and memantine has an advantage over single dosing in improving mental status in mild to moderate Alzheimer’s disease, MMSE scores are influenced by multiple factors such as age and treatment period, and the combination has a better safety and tolerability profile.

Because perlite has good cold insulation effect and is widely used in LNG full capacity tanks, in this paper, the final perlite lateral pressure can be obtained by repeated iterative calculation using Janssen formula, and the perlite lateral pressure is applied to the inner tank of LNG full capacity tanks for statics finite element simulation. The results show that the deformation of the inner tank is within a reasonable range. At the same time, the perlite lateral pressure buckling analysis is carried out for the inner tank of the LNG tank under the empty tank state. The results show that the tank does not buckle under the empty tank state, and the critical buckling pressure of the inner tank is 3.14 times of the applied pressure, which verifies the rationality of the tank design.

Catenary risers have been broadly adopted for mass transportation between seabed and platform during offshore oil and gas production due to its characteristics such as simple construction and relative low delivery cost. However, because of the dynamic conditions in deep water, a simple steel catenary riser (SCR) is vulnerable to yielding and short fatigue life at the critical sections such as hang-off zone (HOZ) and the touch down zone (TDZ). The conventional SCRs are subjected to even more challenges for ultra-deep field developments. Therefore, many new riser system concepts have been proposed in order to solve the related stress and fatigue challenges, in which steel lazy wave catenary riser (SLWR) is the most popular one in recent years. In this work, a simplified static model and tool based on catenary theory and static equilibrium in mechanics was developed for an initial screening of SLWR configuration in the riser early design phase. According to the analysis, it is implied that each section of the SLWR is conformed to a hyperbolic function numerically. Using the configuration tool developed, a trial calculation case has been carried out assuming a water depth of 1500 m, and the critical sensitive factors including hang-off angle, elevation, and content density have been discussed respectively. The findings can provide certain reference information for the further study and detailed design in the future engineering phases.

It is easy to misjudge the breathing effect as kick and take killing measures to cause malignant loss, which will increase the risk and cost of deep-water operation and seriously harm the safety and efficiency of deep-water drilling. In this paper, the mechanism of breathing effect induced by drilling in deep-water shallow formations was studied, and the COMSOL was used to simulate the whole process of breathing effect during drilling in deep-water shallow formations, so as to study the influence of formation characteristics, mud properties and pressure difference on breathing effect. The simulation results show that the breathing effect observed during drilling in deep-water shallow formations belongs to the transient permeability-induced breathing effect. Which is very easy to occur in formations with low elastic modulus, low Poisson’s ratio, and high porosity and permeability. However, through using the mud with high viscosity and high yield stress and balanced or near-balanced drilling mode (achieved by reducing displacement and mud density, etc.) is conducive to suppressing the breathing effect. When drilling in formations with low elastic modulus, low Poisson’s ratio, high porosity and high permeability, measures should be taken in advance, such as adding filtrate reducer and reducing pump rate, to reduce the impact of breathing effect. The study results can provide some references for the identification, prevention and control the breathing effect during drilling in deep-water shallow formations.

The vector form intrinsic finite element (VFIFE) method is a numerical analysis method based on the theory of vector mechanics. With the underlying concepts of point value description, path element and fictitious reverse motion, the numerical model is established for the mechanical behavior of the structure. In comparison with the traditional finite element (FE) methods, there is no assembling for the global stiffness matrices in VFIFE method. VFIFE method can effectively handle the complicated behavior analysis involving large deformation, large displacement, geometric and material non-linearity, contact and collision, fracture and collapse, buckling or wrinkling failure, etc. The differences in basic theory between traditional FE methods and VFIFE method are summarized before demonstrating the recent progress, development and applications in various fields and structures. Existing researches proved the strong capability and high accuracy of VFIFE method. Moreover, the application trends of VFIFE method are discussed, including dynamic behavior of large scale structures, cloud-based high-speed parallel computing, hybrid simulation, and digital twin technology.

The blistering and spallation failures in alumina films formed on Kanthal substrates have gained significant attention due to the importance of high-temperature materials in various industrial applications. This work aims to investigate the underlying mechanism for the circular interfacial separations that develop spontaneously under the constant compressive residual stresses at room temperature. This study employed analytical mechanical models and finite element simulations that are based on the conventional buckling theories. In detail, the thermal mismatch stress, alumina growth stress and creep of the substrate are included and the linear fracture locus criterion with the fracture toughnesses in mode I and II are used. The finite element model is established and the results reveal the initial separation is essential for blistering triggered by buckling. However, for the originally intact interface, the pockets of energy concentration theories are suggested to use. The present work highlights the difficulties for the blistering and spallation failures in thin films, having significant implications for the design and performance of high-temperature materials.

In Autonomous Underwater Vehicles (AUVs) design, hull resistance is an important factor in determining the power requirements and range of vehicle and consequently affects battery size, weight, and volume requirement of the design. In this paper, we leverage on AI based optimization algorithm along with Computational Fluid Dynamics (CFD) simulation to study the optimal hull design that minimizes the resistance. By running the CFD based optimization at different operating velocity and turbulence intensity, we want to study/search the possibility of a universal design that will provide least resistance/ near optimal design across all operating condition (operating velocity) and environmental conditions (turbulence intensity). Early result demonstrated that the optimal design found at low velocity and low turbulence condition performs very poor at high velocity and high turbulence conditions. However, design that is optimal at high velocity and high turbulence condition performs near optimal across many considered velocity and turbulence conditions.

Additive manufacturing is a printing successive layer process with the capability to manufacture complex geometries. Due to that the process consist on forming layers of material following a previously designed 3D shape, it is useful for many kind of materials as metals, ceramics, polymers, composites and biological systems. For many years, additive manufacturing was only used for prototypes, but now days, by its versatility, it is used in many industries, mainly in automotive and aerospace industry to manufacture components as gearboxes, airboxes, dashboards, motorcycle stands and suspension systems. However, this versatility can be also counterproductive because the measurement and control of the involved variables in this process is complicated, due to the different material’s properties. For this reason, a previous simulation results important before to carry out additive manufacturing process. This article is a review of research of additive manufacturing simulations with different materials, as well as their results, focusing on additive manufacturing processes with metals.

The interaction between fluid and immersed solid is a nonlinear multi-physical phenomenon in science and engineering. Due to the challenges of large structural deformation, topological changes in the fluid domain, complexity of the geometry of the structure and computational efficiency and robustness for simulating fluid structure interaction (FSI) problems, developing accurate and efficient finite element numerical methods has always been a research focus in the field of computational fluid dynamics. To overcome these difficulties, we present an efficient stabilised immersed framework involving finite element method called CutFEM and a second-order accurate staggered numerical scheme for fluid–solid coupling. In the following work, we apply this novel framework of computational FSI to several numerical examples to verify the efficiency and robustness of the proposed scheme, and the accuracy is also validated by the results by using the present scheme compared with the reference values.

The fatigue life of the spindle system of the point the bit rotary steerable system largely determines its service life. At present, the mechanical modeling of the spindle system of the point the bit rotary steerable system generally simplifies the force of eccentric rings on the spindle to a known concentrated bias force, and fails to consider the constraint moment of eccentric rings to the spindle, which needs further optimization. Therefore, in this paper, the control and constraint conditions of the tool are considered, and a mechanical model of the biasing spindle with unknown binding force and constrained moment at the eccentric rings is established. On this basis, the geometric and mechanical equations of the spindle system are established, the expressions of deflection and rotation angle at each section of the spindle are derived, and the dimensions of the structure are taken as the known conditions to solve the unknown binding force and the constrained moment. In order to increase the service life of the spindle system, the optimization analysis of the structural dimension parameters involved in the model is carried out to reduce the binding force and constraint moment of the spindle system. According to the analysis results, the optimal value range of the distance ratio from eccentric rings to cantilever bearing and eccentric rings to ball bearing is 2–2.5.

Slim-hole drilling technology has the advantages of high yield, low environmental protection and low cost, and it has been gradually paid attention to by various oil fields in recent years. However, in hydraulics calculation, especially the calculation of annular pressure loss, the established models by different researchers through laboratory experiments are often not universal and practical. The key point of this problem is that there is a big difference between laboratory experiment parameters and genuine parameters in the field. Therefore, in this study, an annular drilling fluid flow model is established by using numerical simulation technology. Then, a mixed level orthogonal experiment is carried out with four annulus sizes, four groups of drilling fluid rheological parameters, four common annulus flow velocity, four eccentricities and 16 drill pipe rotation speeds, and the experimental results is fitted into an influencing factor of drill string rotation suitable for slim holes. Finally, considering the influence of drill string eccentricity and drill string joint on the annulus pressure loss of slim hole, a model of annulus pressure loss is suitable for slim hole. It can be seen that the calculation results of the model are consistent with the data of laboratory experiments. In addition, to verify the accuracy of the model, the model established in this study was applied to Mahu oilfield, and the average error rate is only 4.6%, which indicates the applicability of this model in the field. Therefore, this model can be applied to design and calculate hydraulic parameters of slim hole and guide engineering practice.

Resilience is a key component of system safety evaluation and optimization, and research on natural gas pipeline network system (NGPNS) resilience indices and corresponding evaluation is still in early stages. To evaluate the resilience of NGPNS more synthetically and realistically, and to take into account different forms of disruptions, an integrated simulation model combining the topology and operational parameters is provided. The properties of deterministic disruptions, such as earthquakes and equipment breakdowns, are investigated. The maximum flow method and the shortest path method are combined with operational and structural parameters, to assess the amounts and routes of gas supply before and after disturbance; using complex networks theory and graph theory, the traditional view point is changed from the entire system to the affected area. The results can help guide NGPNS topological design and the development of prewarning schemes, including spare gas sources and gas route optimization, as well as pipeline maintenance strategy. They can also aid in the rapid analysis of disturbance consequences and the improvement of NGPNS resilience evaluating accuracy.

In this article, the deployment problem of LEO satellite communication is investigated and analyzed by the financial tool, i.e. real option theory. Traditional methods often neglect the existence of uncertainty and underestimates the value of staged deployment decisions. Real option theory pays more attention to the value of flexibility in large-scale complex engineering system, such as satellite constellation. The objective of this work is to analyze the flexible approach of staged deployment for mega-constellation and deduce the option price equations. Finally, a simple example is given to demonstrate the fact that staged deployment brings the flexibility for the system and real option theory can evaluate this value more exactly.

In order to research the hydrate decomposition behaviors and multiphase flow characteristics during hydrate mining, a full transient non-isothermal gas-liquid-solid multiphase flow model was established. The model considered the heat and mass transfer due to hydrate phase transition. The calculated results of the model are in good agreement with the measured data of MWD. The model is used to analyze the changes of wellbore temperature and pressure, hydrate decomposition rate, and the volume fraction of each phase over time during the hydrate particles transportation. The numerical simulation results show that: within 2 h before mining, the hydrate decomposition rate is relatively slow, and the volume fraction of each phase in the wellbore changes little; with the increase of time, the volume fraction of each phase in the wellbore varies significantly; it arrives stable state after about 5 h of mining. Meanwhile, the gas volume fraction of the wellhead reaches about 40%. In addition, at the position of the downhole lift pump, the solid-liquid volume fractions both undergo significant mutations. These research results have a particular reference value for the in-depth understanding of the behavior of multiphase flow in hydrate mining.

The managed pressure drilling dynamic control (MPDDC) technology of has the advantages of short control time and no need to shut in the well to deal with the gas influx problem. Based on drift flow model and transient solubility calculation model of gas in oil-based drilling fluid, a multi-phase flow model of MPDDC is established. The accuracy and reliability of the model were verified based on the experimental data of gas kick in oil-based drilling fluid. The simulation results show that the change of wellhead back pressure and bottom hole pressure during MPDDC can be divided into three stages with the upward migration of intrusive gas. The multiphase flow behavior and pressure response characteristics of gas dissolution, wellbore heat transfer and kill rate on dynamic well control of managed pressure drilling are discussed and analyzed. Increase drilling fluid displacement (wellhead back pressure, pit gain) during MPDDC. Faster gas kick can be controlled, helping to reduce maximum wellhead back pressure and maximum pit gain. The research results are helpful to improve the calculation accuracy of wellhead back pressure in well control process and provide engineering guidance for MPDDC technology.

There are abundant nonlinear phenomena in a fluid, such as the nonlinear waves and their interactions. In this paper, a (3+1)-dimensional generalized B-type Kadomtsev-Petviashvili equation in a fluid, which is used to describe the long waves and has the application in water percolation, is investigated. Via the Hirota method, we obtain a bilinear auto-B äcklund transformation as well as shock-wave, breather and X-type soliton solutions. We graphically show the shock waves and breathers, observe that the amplitudes and shapes of shock waves and breathers keep unchanged during the propagation, and show the X-type soliton on a periodic background. We also analysis the influence of the coefficients in the equation on the above waves.

In recent years, safety accidents have occurred frequently in natural gas pipelines, mostly due to leakage of natural gas pipelines. Most long-distance natural gas pipelines are large-diameter and high pressure pipelines. A large amount of natural gas is stored in the pipeline, which will have serious consequences in case of leakage. The thinning of pipeline wall thickness is an important factor causing the leakage of natural gas pipeline, so it is necessary to monitor the wall thickness of key points of the pipeline. At present, the recognized monitoring points in the industry are elbows and tees of natural gas stations, but no relevant standards have been formulated for the more detailed detection scope of monitoring points. The author uses fluent simulation software to establish the model, and then uses the pressure sensor for on-site detection to modify the model with the detection results. Then, according to the new model, the stress areas of monitoring points (elbows and tees) with different pipe diameter and curve diameter ratio are studied and summarized, and the detection ranges of different monitoring points are determined on this basis. The detection scope provides reference for the daily work of on-site operators, so as to ensure the safe and stable operation of long-distance natural gas pipeline.

Board-level drop responses are critical to evaluate the mechanical reliability of solder joints to serve as electrical and mechanical connections in electronic devices to resist failure due to drop impact. In this paper, by applying the elastoplastic constitutive models of solder materials and polymer materials in the BGA packaging structure, drop impact simulations of board-level packaging structure are performed according to the new version of JEDEC revised in 2016, JESD22-B111A for the drop test standard for portable electronic products. Particularly, the Input-G method is adopted, using a semi-sinusoidal acceleration pulse load with a peak of 1500G and a pulse time of 0.5 ms. The overall finite element model establishes a 1/4 model thanks to the symmetry of the board-level packaging structure. According to the simulation results, we explored the failure mode of the solder joint and polymer layer. At the same time, the mechanical reliability of different solder joints in the packaging structure is also discussed according to the production requirements. The results show that the solder joint far away from the center point of the PCB board is subjected to the greatest stress, which is the most vulnerable solder joint. It is found that the stress component in the vertical direction plays a leading role, which can be treated as the peeling stress. Peeling stress is the major reason to cause the crack occurrence and propagation in the solder joint, which is the main failure mode for solder joint. Under the same load, three BGA models with different solder joint distributions are compared.

Image registration is a key problem and a technical difficulty in the field of machine vision and image processing research. For the problems that the detection accuracy of the machine learning method depends on a large number of training samples, and it is difficult to take samples in the LED chip production process, a graphical computing-based LED chip image registration method is proposed. The geometrical representation of the LED chip image features is used to realize the registration of the chip image in the form of geometric calculation. Image morphology processing and Hough transform are used to calculate the registration angle of chip images. With the variational thinking of tessellation grid, a simplified computational model of tessellation grid is proposed to replace the global information with key features of the image for fast registration. The step-by-step generalized image registration algorithm is designed for multiple types of LED chip image characteristics to achieve efficient registration of multiple LED chip images. According to the experimental results of multi-type LED chip image registration, it shows that the proposed graphical computational registration method has a high average registration accuracy and a good registration effect for a variety of LED chip images, which can lay a good foundation for large-scale online detection of LED chip defects.