Geological CO_(2) storage is a promising strategy for reducing greenhouse gas emissions and has become a growing focus of research and deployment.This paper presents numerical simulations of CO_(2) injection and stora...Geological CO_(2) storage is a promising strategy for reducing greenhouse gas emissions and has become a growing focus of research and deployment.This paper presents numerical simulations of CO_(2) injection and storage in a depleted gas reservoir within the B Depression and evaluates associated CO_(2) trapping mechanisms.In the base case,a constant injection rate of 3500 m^(3)/d over fifteen years resulted in a cumulative injection of 19.2×10^(6) m^(3).The CO_(2) plume expanded radially during injection and subsequently migrated up-dip under buoyancy forces.The final stored mass of CO_(2) in the reservoir was 10.6 million tonnes(Mt),representing less than 10% of its theoretical capacity.The plume was projected to reach the entrapment crest and the top of the reservoir within a century,indicating secure long-term containment.Structural,stratigraphic,and residual trapping dominate in Reservoir A(approximately 90%).Anticlinal closures with thick overlying mudstones in the Zhujiang Formation provide effective seals,further enhancing storage security.Reservoir properties and heterogeneity play a crucial role in controlling CO_(2) storage.However,reservoir heterogeneity exerts only a limited influence when intrinsic properties are favorable.Overall,the study and implementation of CO_(2) capture,utilization,and storage(CCUS)in China's offshore basins show promising prospects.展开更多
Deeply buried mountain tunnels are often exposed to the risk of rock bursts,which always cause serious damage to the supporting structures and threaten the safety of the engineers.Due to the limited data available,a s...Deeply buried mountain tunnels are often exposed to the risk of rock bursts,which always cause serious damage to the supporting structures and threaten the safety of the engineers.Due to the limited data available,a suitable approach to predict the rockburst tendency at the preliminary stage becomes very important.In this study,an integrated methodology combining 3D initial stress inversion and rockburst tendency prediction was developed and subsequently applied to a case study of the Sangzhuling Tunnel on the Sichuan–Tibet Railway.The numerical modelling involved inverting the initial stress field using a multiple linear regression method.The tunnel excavation was simulated separately by FDM and DEM,based on a stress boundary condition from the inverted stress field.The comparative analysis demonstrates that the rockburst ratio calculated using DEM(76.70%)exhibits a slight increase compared to FDM(75.38%),and the rockburst location is consistent with the actual situation.This suggests that DEM is more suitable for simulating the stress redistribution during excavation in a jointed rock mass.The numerical simulation combined with the deviatoric stress approach effectively predicts rockburst tendency,meeting the engineering requirements.Despite its limitations,numerical simulation remains a reliable method for predicting rock bursts.展开更多
The uplift resistance of the soil overlying shield tunnels significantly impacts their anti-floating stability.However,research on uplift resistance concerning special-shaped shield tunnels is limited.This study combi...The uplift resistance of the soil overlying shield tunnels significantly impacts their anti-floating stability.However,research on uplift resistance concerning special-shaped shield tunnels is limited.This study combines numerical simulation with machine learning techniques to explore this issue.It presents a summary of special-shaped tunnel geometries and introduces a shape coefficient.Through the finite element software,Plaxis3D,the study simulates six key parameters—shape coefficient,burial depth ratio,tunnel’s longest horizontal length,internal friction angle,cohesion,and soil submerged bulk density—that impact uplift resistance across different conditions.Employing XGBoost and ANN methods,the feature importance of each parameter was analyzed based on the numerical simulation results.The findings demonstrate that a tunnel shape more closely resembling a circle leads to reduced uplift resistance in the overlying soil,whereas other parameters exhibit the contrary effects.Furthermore,the study reveals a diminishing trend in the feature importance of buried depth ratio,internal friction angle,tunnel longest horizontal length,cohesion,soil submerged bulk density,and shape coefficient in influencing uplift resistance.展开更多
Software systems are vulnerable to security breaches as they expand in complexity and functionality.The confidentiality,integrity,and availability of data are gravely threatened by flaws in a system’s design,implemen...Software systems are vulnerable to security breaches as they expand in complexity and functionality.The confidentiality,integrity,and availability of data are gravely threatened by flaws in a system’s design,implementation,or configuration.To guarantee the durability&robustness of the software,vulnerability identification and fixation have become crucial areas of focus for developers,cybersecurity experts and industries.This paper presents a thorough multi-phase mathematical model for efficient patch management and vulnerability detection.To uniquely model these processes,the model incorporated the notion of the learning phenomenon in describing vulnerability fixation using a logistic learning function.Furthermore,the authors have used numerical methods to approximate the solution of the proposed framework where an analytical solution is difficult to attain.The suggested systematic architecture has been demonstrated through statistical analysis using patch datasets,which offers a solid basis for the research conclusions.According to computational research,learning dynamics improves security response and results in more effective vulnerability management.The suggested model offers a systematic approach to proactive vulnerability mitigation and has important uses in risk assessment,software maintenance,and cybersecurity.This study helps create more robust software systems by increasing patch management effectiveness,which benefits developers,cybersecurity experts,and sectors looking to reduce security threats in a growing digital world.展开更多
The multi-scale modeling combined with the cohesive zone model(CZM)and the molecular dynamics(MD)method were preformed to simulate the crack propagation in NiTi shape memory alloys(SMAs).The metallographic microscope ...The multi-scale modeling combined with the cohesive zone model(CZM)and the molecular dynamics(MD)method were preformed to simulate the crack propagation in NiTi shape memory alloys(SMAs).The metallographic microscope and image processing technology were employed to achieve a quantitative grain size distribution of NiTi alloys so as to provide experimental data for molecular dynamics modeling at the atomic scale.Considering the size effect of molecular dynamics model on material properties,a reasonable modeling size was provided by taking into account three characteristic dimensions from the perspective of macro,meso,and micro scales according to the Buckinghamπtheorem.Then,the corresponding MD simulation on deformation and fracture behavior was investigated to derive a parameterized traction-separation(T-S)law,and then it was embedded into cohesive elements of finite element software.Thus,the crack propagation behavior in NiTi alloys was reproduced by the finite element method(FEM).The experimental results show that the predicted initiation fracture toughness is in good agreement with experimental data.In addition,it is found that the dynamics initiation fracture toughness increases with decreasing grain size and increasing loading velocity.展开更多
Coal underground gasification(UCG)transforms the physical extraction of coal into the chemical extraction of gas,which is effective for exploiting deep coal deposits.Numerical simulation technology for UCG is a crucia...Coal underground gasification(UCG)transforms the physical extraction of coal into the chemical extraction of gas,which is effective for exploiting deep coal deposits.Numerical simulation technology for UCG is a crucial tool for studying the complex processes involved in coal gasification.This study was conducted to determine the direction in which UCG numerical simulation is developing,specifically by reviewing the research progress and achievements made in this area and identifying the existing problems and future research directions.The findings indicate the following:(1)Research has focused on the reaction issues of coal underground gasification,considering mass and heat transfer effects and gasification cavity expansion.Chemical equilibrium,gasification block,packed bed,and gasification channel models have been developed,which have certain advantages in solving gasification reaction problems influenced by cavity structure and reasonable simplifications capable of describing local issues.(2)The dynamic description of gasification cavity structures is a challenging problem that UCG numerical simulation needs to address.The cavity expansion mechanism includes thermochemical consumption,coal spalling,roof collapse,and debris accumulation.Thermochemical consumption causes the mechanical properties of coal and rock to change,leading to spalling under stress.(3)Process models emphasize dynamic simulations of the gasification process,including cavity evolution and gasification products.The reactor combination model,continuous medium equivalent model,and multimodule integration model are primarily used.(4)Future UCG numerical simulation technology development will prioritize modularity,systematization,and intelligence.There is an urgent need to facilitate the chemical reaction kinetics of large coal blocks,the coupling of discontinuous media,and the integration of multifunctional systems,including that of numerical simulation technology with artificial intelligence.With continuous improvements,numerical simulation technology will play a greater technical supporting role in UCG industrialization.展开更多
This article reviews the application and progress of deep learning in efficient numerical computing methods.Deep learning,as an important branch of machine learning,provides new ideas for numerical computation by cons...This article reviews the application and progress of deep learning in efficient numerical computing methods.Deep learning,as an important branch of machine learning,provides new ideas for numerical computation by constructing multi-layer neural networks to simulate the learning process of the human brain.The article explores the application of deep learning in solving partial differential equations,optimizing problems,and data-driven modeling,and analyzes its advantages in computational efficiency,accuracy,and adaptability.At the same time,this article also points out the challenges faced by deep learning numerical computation methods in terms of computational efficiency,interpretability,and generalization ability,and proposes strategies and future development directions for integrating with traditional numerical methods.展开更多
To improve the photovoltaic conversion efficiency(PCE)of silicon heterojunction(SHJ)solar cells,this study focuses on optimizing the physical parameters of the sun-side-doped layer and proposes strategies to address t...To improve the photovoltaic conversion efficiency(PCE)of silicon heterojunction(SHJ)solar cells,this study focuses on optimizing the physical parameters of the sun-side-doped layer and proposes strategies to address the challenges posed by Fermi level pinning in wide bandgap designs.Using AFORS-HET simulations,we systematically investigate the effects of bandgap width,doping concentration,and defect state distribution on the energy band structure,interface electric field,and carrier transport dynamics.The results reveal that maintaining the Fermi level within 0.3 eV of the conduction band is essential for optimal device performance.A wider bandgap(>1.8 eV)enhances the utilization of short-wavelength light and significantly suppresses interface recombination,leading to an increase in short-circuit current density(J_(sc))by 0.8 mA/cm^(2).This benefit comes with a delicate balance between minimizing defect state density and improving doping efficiency.This study provides theoretical insights into the optimization of doped layer physical parameters and proposes practical solutions,including nano-crystallization and low-doping interface strategies,to improve the performance of SHJ solar cells and support industrial applications.展开更多
This review paper provides a comprehensive introduction to various numerical methods for the phase-field model used to simulate the phase separation dynamics of diblock copolymer melts.Diblock copolymer systems form c...This review paper provides a comprehensive introduction to various numerical methods for the phase-field model used to simulate the phase separation dynamics of diblock copolymer melts.Diblock copolymer systems form complex structures at the nanometer scale and play a significant role in various applications.The phase-field model,in particular,is essential for describing the formation and evolution of these structures and is widely used as a tool to effectively predict the movement of phase boundaries and the distribution of phases over time.In this paper,we discuss the principles and implementations of various numerical methodologies for this model and analyze the strengths,limitations,stability,accuracy,and computational efficiency of each method.Traditional approaches such as Fourier spectral methods,finite difference methods and alternating direction explicit methods are reviewed,as well as recent advancements such as the invariant energy quadratization method and the scalar auxiliary variable scheme are also presented.In addition,we introduce examples of the phase-field model,which are fingerprint image restoration and 3D printing.These examples demonstrate the extensive applicability of the reviewed methods and models.展开更多
Drilling and blasting,characterized by their efficiency,ubiquity,and cost-effectiveness,have emerged as predominant techniques in rock excavation;however,they are accompanied by enormous destructive power.Accurately c...Drilling and blasting,characterized by their efficiency,ubiquity,and cost-effectiveness,have emerged as predominant techniques in rock excavation;however,they are accompanied by enormous destructive power.Accurately controlling the blasting energy and achieving the directional fracture of a rock mass have become common problems in the field.A two-dimensional blasting(2D blasting)technique was proposed that utilizes the characteristic that the tensile strength of a rock mass is significantly lower than its compressive strength.After blasting,only a 2D crack surface is generated along the predetermined direction,eliminating the damage to the reserved rock mass caused by conventional blasting.However,the interior of a natural rock mass is a"black box",and the process of crack propagation is difficult to capture,resulting in an unclear 2D blasting mechanism.To this end,a single-hole polymethyl methacrylate(PMMA)test piece was used to conduct a 2D blasting experiment with the help of a high-speed camera to capture the dynamic crack propagation process and the digital image correlation(DIC)method to analyze the evolution law of surface strain on the test piece.On this basis,a three-dimensional(3D)finite element model was established based on the progressive failure theory to simulate the stress,strain,damage,and displacement evolution process of the model under 2D blasting.The simulation results were consistent with the experimental results.The research results reveal the 2D blasting mechanism and provide theoretical support for the application of 2D blasting technology in the field of rock excavation.展开更多
Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing addit...Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing additive-induced defects,and alleviating residual stress and deformation,all of which are critical for enhancing the mechanical performance of the manufactured parts.Integrating interlayer friction stir processing(FSP)into WAAM significantly enhances the quality of deposited materials.However,numerical simulation research focusing on elucidating the associated thermomechanical coupling mechanisms remains insufficient.A comprehensive numerical model was developed to simulate the thermomechanical coupling behavior in friction stir-assisted WAAM.The influence of post-deposition FSP on the coupled thermomechanical response of the WAAM process was analyzed quantitatively.Moreover,the residual stress distribution and deformation behavior under both single-layer and multilayer deposition conditions were investigated.Thermal analysis of different deposition layers in WAAM and friction stir-assisted WAAM was conducted.Results show that subsequent layer deposition induces partial remelting of the previously solidified layer,whereas FSP does not cause such remelting.Furthermore,thermal stress and deformation analysis confirm that interlayer FSP effectively mitigates residual stresses and distortion in WAAM components,thereby improving their structural integrity and mechanical properties.展开更多
Existing numerical methods for complex composites, such as multiscale simulation and neural network algorithms, face significant limitations. Multiscale techniques are often prohibitively expensive for large models, w...Existing numerical methods for complex composites, such as multiscale simulation and neural network algorithms, face significant limitations. Multiscale techniques are often prohibitively expensive for large models, while neural networks struggle to represent underlying microscopic material properties. To overcome these challenges, a meso-micro scale numerical method using a virtual node approach is developed in this study. A Wbraid/Al/Epoxy functional structural material is fabricated, and a representative periodic unit cell is identified based on its architecture. The complex structure is then discretized into nodes, and mechanical interactions are governed by pre-defined computation rules. This virtual node method is systematically compared against both multiscale simulation and a neural network algorithm, with validation provided through mechanical experiments. The results demonstrate that the nodal operation strategy significantly reduces computational resource requirements. By quantifying microscopic bonding with coefficients, explicit interface treatment is avoided, granting the method strong adaptability to lattice materials. The method can simulate extremely complex structures using parameters from simple tests and is suited for large systems. Compared to three-point bending experiments, errors for multiscale, virtual node, and neural network methods were 12.4%, 6.9%, and 34.5%, respectively. Under dynamic compression, the errors were 2.7%, 9.3%, and 15.43%. The virtual node method demonstrated superior accuracy under static conditions, enabling efficient prediction and auxiliary development of complex structural materials.展开更多
Marine thin plates are susceptible to welding deformation owing to their low structural stiffness.Therefore,the efficient and accurate prediction of welding deformation is essential for improving welding quality.The t...Marine thin plates are susceptible to welding deformation owing to their low structural stiffness.Therefore,the efficient and accurate prediction of welding deformation is essential for improving welding quality.The traditional thermal elastic-plastic finite element method(TEP-FEM)can accurately predict welding deformation.However,its efficiency is low because of the complex nonlinear transient computation,making it difficult to meet the needs of rapid engineering evaluation.To address this challenge,this study proposes an efficient prediction method for welding deformation in marine thin plate butt welds.This method is based on the coupled temperature gradient-thermal strain method(TG-TSM)that integrates inherent strain theory with a shell element finite element model.The proposed method first extracts the distribution pattern and characteristic value of welding-induced inherent strain through TEP-FEM analysis.This strain is then converted into the equivalent thermal load applied to the shell element model for rapid computation.The proposed method-particularly,the gradual temperature gradient-thermal strain method(GTG-TSM)-achieved improved computational efficiency and consistent precision.Furthermore,the proposed method required much less computation time than the traditional TEP-FEM.Thus,this study lays the foundation for future prediction of welding deformation in more complex marine thin plates.展开更多
Burden is one of the main parameters in blast design.However,field tests,either single-or multi-hole blasts,used to determine an appropriate burden,are difficult to capture crack propagation,evolution of breakage angl...Burden is one of the main parameters in blast design.However,field tests,either single-or multi-hole blasts,used to determine an appropriate burden,are difficult to capture crack propagation,evolution of breakage angle,and the mechanism governing these processes in the rock.In this study,a single-hole bench blasting model is developed using LS-DYNA software to comprehensively investigate the relationship between burden and rock breakage.The simulation results show that the breakage angle decreases with the increase in burden,and the blasted volume reaches a peak value with a burden of 4 m.Meanwhile,backbreak distance increases with increasing burden.The optimum burden in this simulation is found to be 4.0 m,as the ratio of burden to blasthole diameter is equal to 20.62 and the ratio of burden to bench height is 0.44,based on a comprehensive analysis of the blasted volume,average damage,and total damage.Under the optimum burden condition,tensile stress wave regions are simultaneously generated at the free surfaces of both the bench top and bench slope,allowing more effective utilization of the two free surfaces and resulting in a more uniform damage distribution within the burden region.展开更多
Ice crystal icing is an important cause of accidents in aircraft engines.Ice formation in aircraft engines can cause internal blades to freeze,affecting the quality of the air flow field and blocking the flow path.On ...Ice crystal icing is an important cause of accidents in aircraft engines.Ice formation in aircraft engines can cause internal blades to freeze,affecting the quality of the air flow field and blocking the flow path.On the other hand,the entry of ice crystal particles into the combustion chamber can cause a decrease in temperature or even flameout,leading to engine surge or shutdown.Therefore,it is necessary to conduct multiphase flow tests on ice crystals for aircraft components such as aircraft engines.Conducting ice crystal multiphase flow tests on aircraft is an effective research method,but it requires the construction of an ice crystal multiphase flow test platform that meets relevant technical requirements.The paper focuses on the relevant experimental requirements and combines wind tunnel test structures to conduct multiphase flow numerical simulations on various forms of jet pipelines,obtaining particle motion distribution results.After comparison,the optimal form of jet structure is obtained,providing the best selection scheme for the design of relevant wind tunnel structures.展开更多
Machine learning-assisted methods for rapid and accurate prediction of temperature field,mushy zone,and grain size were proposed for the heating−cooling combined mold(HCCM)horizontal continuous casting of C70250 alloy...Machine learning-assisted methods for rapid and accurate prediction of temperature field,mushy zone,and grain size were proposed for the heating−cooling combined mold(HCCM)horizontal continuous casting of C70250 alloy plates.First,finite element simulations of casting processes were carried out with various parameters to build a dataset.Subsequently,different machine learning algorithms were employed to achieve high precision in predicting temperature fields,mushy zone locations,mushy zone inclination angle,and billet grain size.Finally,the process parameters were quickly optimized using a strategy consisting of random generation,prediction,and screening,allowing the mushy zone to be controlled to the desired target.The optimized parameters are 1234℃for heating mold temperature,47 mm/min for casting speed,and 10 L/min for cooling water flow rate.The optimized mushy zone is located in the middle of the second heat insulation section and has an inclination angle of roughly 7°.展开更多
Regenerative catalytic oxidizers(RCO)are widely used to remove volatile organic compounds(VOCs)due to their energy-saving and stability.In this study,a multi-component catalytic reaction model was constructed to numer...Regenerative catalytic oxidizers(RCO)are widely used to remove volatile organic compounds(VOCs)due to their energy-saving and stability.In this study,a multi-component catalytic reaction model was constructed to numerically investigate the reaction process of hydrocarbon-containing VOCs in RCO using computational fluid dynamics(CFD)simulation.To obtain the conversion characteristics of multi-component hydrocarbons,the effects of intake load,equivalence ratio,and the composition of multi-component hydrocarbons on the flow,heat transfer,and conversion rate of the reactor were analyzed.A feasibility study plan targeting the hard-to-convert components was also proposed.The results indicated that as the load increases,the conversion rates of the various components decrease,while the reaction rates increase.Moreover,increasing the flow velocity intensifies turbulence and enhances the collision frequency between the gas and the wall surfaces.This,in turn,amplifies the resistance effect of the porous medium.As the equivalence ratio of VOCs to oxygen increases,the oxygen-deficient condition leads to a decrease in the molecular weight of the hydrocarbons involved in the reaction.The reaction temperature also shows a downward trend.A comparative analysis of the catalytic combustion characteristics of multi-component VOCs and single-component gases reveals that adding ethane and propane can facilitate methane oxidation.展开更多
Hydraulic fracturing serves as a critical technology for reservoir stimulation in deep coalbed methane(CBM)development,where the mechanical properties of gangue layers exert a significant control on fracture propagati...Hydraulic fracturing serves as a critical technology for reservoir stimulation in deep coalbed methane(CBM)development,where the mechanical properties of gangue layers exert a significant control on fracture propagation behavior.To address the unclear mechanisms governing fracture penetration across coal-gangue interfaces,this study employs the Continuum-Discontinuum Element Method(CDEM)to simulate and analyze the vertical propagation of hydraulic fractures initiating within coal seams,based on geomechanical parameters derived from the deep Benxi Formation coal seams in the southeastern Ordos Basin.The investigation systematically examines the influence of geological and operational parameters on cross-interfacial fracture growth.Results demonstrate that vertical stress difference,elastic modulus contrast between coal and gangue layers,interfacial stress differential,and interfacial cohesion at coal-gangue interfaces are critical factors governing hydraulic fracture penetration through these interfaces.High vertical stress differences(>3 MPa)inhibit interfacial dilation,promoting predominant crosslayer fracture propagation.Reduced interfacial stress contrasts and enhanced interfacial cohesion facilitate fracture penetration across interfaces.Furthermore,smaller elastic modulus contrasts between coal and gangue correlate with increased interfacial aperture.Finally,lower injection rates effectively suppress vertical fracture propagation in deep coal reservoirs.This study elucidates the characteristics and mechanisms governing cross-layer fracture propagation in coal–rock composites with interbedded partings,and delineates the dynamic evolution laws and dominant controlling factors involved.Thefindings provide critical theoretical insights for the optimization of fracture design and the efficient development of deep coalbed methane reservoirs.展开更多
As binary geological media,soil-rock mixtures(SRMs)exhibit a distinct gradational composition,leading to their unique mechanical behaviors.To appraise the stability of SRM slopes,it is essential to determine equivalen...As binary geological media,soil-rock mixtures(SRMs)exhibit a distinct gradational composition,leading to their unique mechanical behaviors.To appraise the stability of SRM slopes,it is essential to determine equivalent parameters of SRMs,which are typically obtained through experimental and numerical methods.In contrasted to other numerical methods,the numerical manifold method(NMM)is more effective in addressing SRM problems.This is because the high-precision regular mathematical meshes in NMM can be used without aligning with the soil-rock interfaces and boundaries of SRMs.In the current research,the equivalent strength parameters of SRMs,i.e.the equivalent cohesion ce and internal friction angleϕ_(e),are determined using NMM.Initially,an NMM triaxial numerical model is established and validated based on triaxial experiments.Subsequently,the soil and rock parameters are derived through parameter inversion.Moreover,the impacts of rock content,size,shape and rock blocks'major-axis orientation on ce andϕ_(e) of SRMs are thoroughly examined using the NMM triaxial numerical model.Additionally,a fitting function is proposed to linkϕ_(e) to the rock content and size of SRMs.When other influencing factors are fixed,the above fitting model leads to the following conclusions:(1)the predictedϕ_(e) of SRMs increase with the increase of rock content;and(2)SRM samples with smaller rocks display a higher predictedϕ_(e).展开更多
Based on the surrounding rock arching and hingeless arch structure theories,a theoretical formula for the minimum overburden thickness was derived.By substituting different mechanical parameters of multiple tunnels at...Based on the surrounding rock arching and hingeless arch structure theories,a theoretical formula for the minimum overburden thickness was derived.By substituting different mechanical parameters of multiple tunnels at home and abroad into this formula,minimum self-supporting arch formulas under different surrounding rock classes were obtained.Based on the actual engineering case of a dual-mode shield tunnel,a numerical model for the tunnel boring machine excavation mode was established to verify the theoretical formulas.Next,three surrounding rock classes,four soil layer thickness gradients,and twelve overburden thickness gradients were designed,resulting in 144 models formed by the combination of the three factors.Uniform tests were conducted,and the pressure arch heights under different surrounding rock classes were obtained.The results show that in the theoretical formulas,the tunnel radius has a linear positive correlation with the pressure arch height,while the tunnel depth has a linear positive correlation with the square of the pressure arch height.According to numerical simulation results,the pressure arch height increases with the increase of the overburden thickness and then tends toward a critical value of twice the tunnel diameter.Finally,the results of the numerical model are in good agreement with those calculated using the theoretical formulas,verifying the rationality of the established theoretical formulas.展开更多
基金funded by the National Natural Science Foundation of China(Grant No.42102169)the Shaanxi Province key Research and Development Project(Grant No.2023-ZDLSF-64)+1 种基金the Scientific Research and Technological Development Project of China National Logging Corporation(Grant No.25ZYCJSG013-2504)the Youth Science and Technology Special Fund of PetroChina(Grant No.2024DQ03172)。
文摘Geological CO_(2) storage is a promising strategy for reducing greenhouse gas emissions and has become a growing focus of research and deployment.This paper presents numerical simulations of CO_(2) injection and storage in a depleted gas reservoir within the B Depression and evaluates associated CO_(2) trapping mechanisms.In the base case,a constant injection rate of 3500 m^(3)/d over fifteen years resulted in a cumulative injection of 19.2×10^(6) m^(3).The CO_(2) plume expanded radially during injection and subsequently migrated up-dip under buoyancy forces.The final stored mass of CO_(2) in the reservoir was 10.6 million tonnes(Mt),representing less than 10% of its theoretical capacity.The plume was projected to reach the entrapment crest and the top of the reservoir within a century,indicating secure long-term containment.Structural,stratigraphic,and residual trapping dominate in Reservoir A(approximately 90%).Anticlinal closures with thick overlying mudstones in the Zhujiang Formation provide effective seals,further enhancing storage security.Reservoir properties and heterogeneity play a crucial role in controlling CO_(2) storage.However,reservoir heterogeneity exerts only a limited influence when intrinsic properties are favorable.Overall,the study and implementation of CO_(2) capture,utilization,and storage(CCUS)in China's offshore basins show promising prospects.
基金financially supported by the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection(Chengdu University of Technology)(Grant No.SKLGP2020Z007)。
文摘Deeply buried mountain tunnels are often exposed to the risk of rock bursts,which always cause serious damage to the supporting structures and threaten the safety of the engineers.Due to the limited data available,a suitable approach to predict the rockburst tendency at the preliminary stage becomes very important.In this study,an integrated methodology combining 3D initial stress inversion and rockburst tendency prediction was developed and subsequently applied to a case study of the Sangzhuling Tunnel on the Sichuan–Tibet Railway.The numerical modelling involved inverting the initial stress field using a multiple linear regression method.The tunnel excavation was simulated separately by FDM and DEM,based on a stress boundary condition from the inverted stress field.The comparative analysis demonstrates that the rockburst ratio calculated using DEM(76.70%)exhibits a slight increase compared to FDM(75.38%),and the rockburst location is consistent with the actual situation.This suggests that DEM is more suitable for simulating the stress redistribution during excavation in a jointed rock mass.The numerical simulation combined with the deviatoric stress approach effectively predicts rockburst tendency,meeting the engineering requirements.Despite its limitations,numerical simulation remains a reliable method for predicting rock bursts.
基金Guangzhou Metro Scientific Research Project(No.JT204-100111-23001)Chongqing Municipal Special Project for Technological Innovation and Application Development(No.CSTB2022TIAD-KPX0101)Science and Technology Research and Development Program of China State Railway Group Co.,Ltd.(No.N2023G045)。
文摘The uplift resistance of the soil overlying shield tunnels significantly impacts their anti-floating stability.However,research on uplift resistance concerning special-shaped shield tunnels is limited.This study combines numerical simulation with machine learning techniques to explore this issue.It presents a summary of special-shaped tunnel geometries and introduces a shape coefficient.Through the finite element software,Plaxis3D,the study simulates six key parameters—shape coefficient,burial depth ratio,tunnel’s longest horizontal length,internal friction angle,cohesion,and soil submerged bulk density—that impact uplift resistance across different conditions.Employing XGBoost and ANN methods,the feature importance of each parameter was analyzed based on the numerical simulation results.The findings demonstrate that a tunnel shape more closely resembling a circle leads to reduced uplift resistance in the overlying soil,whereas other parameters exhibit the contrary effects.Furthermore,the study reveals a diminishing trend in the feature importance of buried depth ratio,internal friction angle,tunnel longest horizontal length,cohesion,soil submerged bulk density,and shape coefficient in influencing uplift resistance.
基金supported by grants received by the first author and third author from the Institute of Eminence,Delhi University,Delhi,India,as part of the Faculty Research Program via Ref.No./IoE/2024-25/12/FRP.
文摘Software systems are vulnerable to security breaches as they expand in complexity and functionality.The confidentiality,integrity,and availability of data are gravely threatened by flaws in a system’s design,implementation,or configuration.To guarantee the durability&robustness of the software,vulnerability identification and fixation have become crucial areas of focus for developers,cybersecurity experts and industries.This paper presents a thorough multi-phase mathematical model for efficient patch management and vulnerability detection.To uniquely model these processes,the model incorporated the notion of the learning phenomenon in describing vulnerability fixation using a logistic learning function.Furthermore,the authors have used numerical methods to approximate the solution of the proposed framework where an analytical solution is difficult to attain.The suggested systematic architecture has been demonstrated through statistical analysis using patch datasets,which offers a solid basis for the research conclusions.According to computational research,learning dynamics improves security response and results in more effective vulnerability management.The suggested model offers a systematic approach to proactive vulnerability mitigation and has important uses in risk assessment,software maintenance,and cybersecurity.This study helps create more robust software systems by increasing patch management effectiveness,which benefits developers,cybersecurity experts,and sectors looking to reduce security threats in a growing digital world.
基金Funded by the National Natural Science Foundation of China Academy of Engineering Physics and Jointly Setup"NSAF"Joint Fund(No.U1430119)。
文摘The multi-scale modeling combined with the cohesive zone model(CZM)and the molecular dynamics(MD)method were preformed to simulate the crack propagation in NiTi shape memory alloys(SMAs).The metallographic microscope and image processing technology were employed to achieve a quantitative grain size distribution of NiTi alloys so as to provide experimental data for molecular dynamics modeling at the atomic scale.Considering the size effect of molecular dynamics model on material properties,a reasonable modeling size was provided by taking into account three characteristic dimensions from the perspective of macro,meso,and micro scales according to the Buckinghamπtheorem.Then,the corresponding MD simulation on deformation and fracture behavior was investigated to derive a parameterized traction-separation(T-S)law,and then it was embedded into cohesive elements of finite element software.Thus,the crack propagation behavior in NiTi alloys was reproduced by the finite element method(FEM).The experimental results show that the predicted initiation fracture toughness is in good agreement with experimental data.In addition,it is found that the dynamics initiation fracture toughness increases with decreasing grain size and increasing loading velocity.
基金supported by Natural Science Research Project of Yangzhou University Guangling College,China(Grant No.ZKZD25002)Youth Science and Technology Special Project of PetroChina(Grant No.2024DQ03221)Basic Research Project of Institute Research Institute of Exploration and Development,PetroChina(Grant No.101001cq0b52394).
文摘Coal underground gasification(UCG)transforms the physical extraction of coal into the chemical extraction of gas,which is effective for exploiting deep coal deposits.Numerical simulation technology for UCG is a crucial tool for studying the complex processes involved in coal gasification.This study was conducted to determine the direction in which UCG numerical simulation is developing,specifically by reviewing the research progress and achievements made in this area and identifying the existing problems and future research directions.The findings indicate the following:(1)Research has focused on the reaction issues of coal underground gasification,considering mass and heat transfer effects and gasification cavity expansion.Chemical equilibrium,gasification block,packed bed,and gasification channel models have been developed,which have certain advantages in solving gasification reaction problems influenced by cavity structure and reasonable simplifications capable of describing local issues.(2)The dynamic description of gasification cavity structures is a challenging problem that UCG numerical simulation needs to address.The cavity expansion mechanism includes thermochemical consumption,coal spalling,roof collapse,and debris accumulation.Thermochemical consumption causes the mechanical properties of coal and rock to change,leading to spalling under stress.(3)Process models emphasize dynamic simulations of the gasification process,including cavity evolution and gasification products.The reactor combination model,continuous medium equivalent model,and multimodule integration model are primarily used.(4)Future UCG numerical simulation technology development will prioritize modularity,systematization,and intelligence.There is an urgent need to facilitate the chemical reaction kinetics of large coal blocks,the coupling of discontinuous media,and the integration of multifunctional systems,including that of numerical simulation technology with artificial intelligence.With continuous improvements,numerical simulation technology will play a greater technical supporting role in UCG industrialization.
文摘This article reviews the application and progress of deep learning in efficient numerical computing methods.Deep learning,as an important branch of machine learning,provides new ideas for numerical computation by constructing multi-layer neural networks to simulate the learning process of the human brain.The article explores the application of deep learning in solving partial differential equations,optimizing problems,and data-driven modeling,and analyzes its advantages in computational efficiency,accuracy,and adaptability.At the same time,this article also points out the challenges faced by deep learning numerical computation methods in terms of computational efficiency,interpretability,and generalization ability,and proposes strategies and future development directions for integrating with traditional numerical methods.
基金supported by the National Natural Science Foundation of China(Grant Nos.61991441 and 62004218)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB01000000)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(Grant No.2021005).
文摘To improve the photovoltaic conversion efficiency(PCE)of silicon heterojunction(SHJ)solar cells,this study focuses on optimizing the physical parameters of the sun-side-doped layer and proposes strategies to address the challenges posed by Fermi level pinning in wide bandgap designs.Using AFORS-HET simulations,we systematically investigate the effects of bandgap width,doping concentration,and defect state distribution on the energy band structure,interface electric field,and carrier transport dynamics.The results reveal that maintaining the Fermi level within 0.3 eV of the conduction band is essential for optimal device performance.A wider bandgap(>1.8 eV)enhances the utilization of short-wavelength light and significantly suppresses interface recombination,leading to an increase in short-circuit current density(J_(sc))by 0.8 mA/cm^(2).This benefit comes with a delicate balance between minimizing defect state density and improving doping efficiency.This study provides theoretical insights into the optimization of doped layer physical parameters and proposes practical solutions,including nano-crystallization and low-doping interface strategies,to improve the performance of SHJ solar cells and support industrial applications.
文摘This review paper provides a comprehensive introduction to various numerical methods for the phase-field model used to simulate the phase separation dynamics of diblock copolymer melts.Diblock copolymer systems form complex structures at the nanometer scale and play a significant role in various applications.The phase-field model,in particular,is essential for describing the formation and evolution of these structures and is widely used as a tool to effectively predict the movement of phase boundaries and the distribution of phases over time.In this paper,we discuss the principles and implementations of various numerical methodologies for this model and analyze the strengths,limitations,stability,accuracy,and computational efficiency of each method.Traditional approaches such as Fourier spectral methods,finite difference methods and alternating direction explicit methods are reviewed,as well as recent advancements such as the invariant energy quadratization method and the scalar auxiliary variable scheme are also presented.In addition,we introduce examples of the phase-field model,which are fingerprint image restoration and 3D printing.These examples demonstrate the extensive applicability of the reviewed methods and models.
基金supported by the National Natural Science Foundation of China(Grant Nos.52404155 and 52304111)State Key Laboratory for Geomechanics and Deep Underground Engineering,China University of Mining&Technology,Beijing(Grant No.XD2024006).
文摘Drilling and blasting,characterized by their efficiency,ubiquity,and cost-effectiveness,have emerged as predominant techniques in rock excavation;however,they are accompanied by enormous destructive power.Accurately controlling the blasting energy and achieving the directional fracture of a rock mass have become common problems in the field.A two-dimensional blasting(2D blasting)technique was proposed that utilizes the characteristic that the tensile strength of a rock mass is significantly lower than its compressive strength.After blasting,only a 2D crack surface is generated along the predetermined direction,eliminating the damage to the reserved rock mass caused by conventional blasting.However,the interior of a natural rock mass is a"black box",and the process of crack propagation is difficult to capture,resulting in an unclear 2D blasting mechanism.To this end,a single-hole polymethyl methacrylate(PMMA)test piece was used to conduct a 2D blasting experiment with the help of a high-speed camera to capture the dynamic crack propagation process and the digital image correlation(DIC)method to analyze the evolution law of surface strain on the test piece.On this basis,a three-dimensional(3D)finite element model was established based on the progressive failure theory to simulate the stress,strain,damage,and displacement evolution process of the model under 2D blasting.The simulation results were consistent with the experimental results.The research results reveal the 2D blasting mechanism and provide theoretical support for the application of 2D blasting technology in the field of rock excavation.
基金National Key Research and Development Program of China(2022YFB4600902)Shandong Provincial Science Foundation for Outstanding Young Scholars(ZR2024YQ020)。
文摘Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing additive-induced defects,and alleviating residual stress and deformation,all of which are critical for enhancing the mechanical performance of the manufactured parts.Integrating interlayer friction stir processing(FSP)into WAAM significantly enhances the quality of deposited materials.However,numerical simulation research focusing on elucidating the associated thermomechanical coupling mechanisms remains insufficient.A comprehensive numerical model was developed to simulate the thermomechanical coupling behavior in friction stir-assisted WAAM.The influence of post-deposition FSP on the coupled thermomechanical response of the WAAM process was analyzed quantitatively.Moreover,the residual stress distribution and deformation behavior under both single-layer and multilayer deposition conditions were investigated.Thermal analysis of different deposition layers in WAAM and friction stir-assisted WAAM was conducted.Results show that subsequent layer deposition induces partial remelting of the previously solidified layer,whereas FSP does not cause such remelting.Furthermore,thermal stress and deformation analysis confirm that interlayer FSP effectively mitigates residual stresses and distortion in WAAM components,thereby improving their structural integrity and mechanical properties.
文摘Existing numerical methods for complex composites, such as multiscale simulation and neural network algorithms, face significant limitations. Multiscale techniques are often prohibitively expensive for large models, while neural networks struggle to represent underlying microscopic material properties. To overcome these challenges, a meso-micro scale numerical method using a virtual node approach is developed in this study. A Wbraid/Al/Epoxy functional structural material is fabricated, and a representative periodic unit cell is identified based on its architecture. The complex structure is then discretized into nodes, and mechanical interactions are governed by pre-defined computation rules. This virtual node method is systematically compared against both multiscale simulation and a neural network algorithm, with validation provided through mechanical experiments. The results demonstrate that the nodal operation strategy significantly reduces computational resource requirements. By quantifying microscopic bonding with coefficients, explicit interface treatment is avoided, granting the method strong adaptability to lattice materials. The method can simulate extremely complex structures using parameters from simple tests and is suited for large systems. Compared to three-point bending experiments, errors for multiscale, virtual node, and neural network methods were 12.4%, 6.9%, and 34.5%, respectively. Under dynamic compression, the errors were 2.7%, 9.3%, and 15.43%. The virtual node method demonstrated superior accuracy under static conditions, enabling efficient prediction and auxiliary development of complex structural materials.
基金Supported by the National Natural Science Foundation of China under Grant No.51975138the High-Tech Ship Scientific Research Project from the Ministry of Industry and Information Technology under Grant No.CJ05N20the National Defense Basic Research Project under Grant No.JCKY2023604C006.
文摘Marine thin plates are susceptible to welding deformation owing to their low structural stiffness.Therefore,the efficient and accurate prediction of welding deformation is essential for improving welding quality.The traditional thermal elastic-plastic finite element method(TEP-FEM)can accurately predict welding deformation.However,its efficiency is low because of the complex nonlinear transient computation,making it difficult to meet the needs of rapid engineering evaluation.To address this challenge,this study proposes an efficient prediction method for welding deformation in marine thin plate butt welds.This method is based on the coupled temperature gradient-thermal strain method(TG-TSM)that integrates inherent strain theory with a shell element finite element model.The proposed method first extracts the distribution pattern and characteristic value of welding-induced inherent strain through TEP-FEM analysis.This strain is then converted into the equivalent thermal load applied to the shell element model for rapid computation.The proposed method-particularly,the gradual temperature gradient-thermal strain method(GTG-TSM)-achieved improved computational efficiency and consistent precision.Furthermore,the proposed method required much less computation time than the traditional TEP-FEM.Thus,this study lays the foundation for future prediction of welding deformation in more complex marine thin plates.
基金supported by the European Union in the frame of Horizon Europe AVANTIS project,Grant Agreement No.101137552.
文摘Burden is one of the main parameters in blast design.However,field tests,either single-or multi-hole blasts,used to determine an appropriate burden,are difficult to capture crack propagation,evolution of breakage angle,and the mechanism governing these processes in the rock.In this study,a single-hole bench blasting model is developed using LS-DYNA software to comprehensively investigate the relationship between burden and rock breakage.The simulation results show that the breakage angle decreases with the increase in burden,and the blasted volume reaches a peak value with a burden of 4 m.Meanwhile,backbreak distance increases with increasing burden.The optimum burden in this simulation is found to be 4.0 m,as the ratio of burden to blasthole diameter is equal to 20.62 and the ratio of burden to bench height is 0.44,based on a comprehensive analysis of the blasted volume,average damage,and total damage.Under the optimum burden condition,tensile stress wave regions are simultaneously generated at the free surfaces of both the bench top and bench slope,allowing more effective utilization of the two free surfaces and resulting in a more uniform damage distribution within the burden region.
文摘Ice crystal icing is an important cause of accidents in aircraft engines.Ice formation in aircraft engines can cause internal blades to freeze,affecting the quality of the air flow field and blocking the flow path.On the other hand,the entry of ice crystal particles into the combustion chamber can cause a decrease in temperature or even flameout,leading to engine surge or shutdown.Therefore,it is necessary to conduct multiphase flow tests on ice crystals for aircraft components such as aircraft engines.Conducting ice crystal multiphase flow tests on aircraft is an effective research method,but it requires the construction of an ice crystal multiphase flow test platform that meets relevant technical requirements.The paper focuses on the relevant experimental requirements and combines wind tunnel test structures to conduct multiphase flow numerical simulations on various forms of jet pipelines,obtaining particle motion distribution results.After comparison,the optimal form of jet structure is obtained,providing the best selection scheme for the design of relevant wind tunnel structures.
基金financially supported by the National Key Research and Development Program of China (No. 2023YFB3812601)the National Natural Science Foundation of China (No. 51925401)the Young Elite Scientists Sponsorship Program by CAST, China (No. 2022QNRC001)。
文摘Machine learning-assisted methods for rapid and accurate prediction of temperature field,mushy zone,and grain size were proposed for the heating−cooling combined mold(HCCM)horizontal continuous casting of C70250 alloy plates.First,finite element simulations of casting processes were carried out with various parameters to build a dataset.Subsequently,different machine learning algorithms were employed to achieve high precision in predicting temperature fields,mushy zone locations,mushy zone inclination angle,and billet grain size.Finally,the process parameters were quickly optimized using a strategy consisting of random generation,prediction,and screening,allowing the mushy zone to be controlled to the desired target.The optimized parameters are 1234℃for heating mold temperature,47 mm/min for casting speed,and 10 L/min for cooling water flow rate.The optimized mushy zone is located in the middle of the second heat insulation section and has an inclination angle of roughly 7°.
基金supported by National Key Research&Development Program of China(2022YFB4101500).
文摘Regenerative catalytic oxidizers(RCO)are widely used to remove volatile organic compounds(VOCs)due to their energy-saving and stability.In this study,a multi-component catalytic reaction model was constructed to numerically investigate the reaction process of hydrocarbon-containing VOCs in RCO using computational fluid dynamics(CFD)simulation.To obtain the conversion characteristics of multi-component hydrocarbons,the effects of intake load,equivalence ratio,and the composition of multi-component hydrocarbons on the flow,heat transfer,and conversion rate of the reactor were analyzed.A feasibility study plan targeting the hard-to-convert components was also proposed.The results indicated that as the load increases,the conversion rates of the various components decrease,while the reaction rates increase.Moreover,increasing the flow velocity intensifies turbulence and enhances the collision frequency between the gas and the wall surfaces.This,in turn,amplifies the resistance effect of the porous medium.As the equivalence ratio of VOCs to oxygen increases,the oxygen-deficient condition leads to a decrease in the molecular weight of the hydrocarbons involved in the reaction.The reaction temperature also shows a downward trend.A comparative analysis of the catalytic combustion characteristics of multi-component VOCs and single-component gases reveals that adding ethane and propane can facilitate methane oxidation.
文摘Hydraulic fracturing serves as a critical technology for reservoir stimulation in deep coalbed methane(CBM)development,where the mechanical properties of gangue layers exert a significant control on fracture propagation behavior.To address the unclear mechanisms governing fracture penetration across coal-gangue interfaces,this study employs the Continuum-Discontinuum Element Method(CDEM)to simulate and analyze the vertical propagation of hydraulic fractures initiating within coal seams,based on geomechanical parameters derived from the deep Benxi Formation coal seams in the southeastern Ordos Basin.The investigation systematically examines the influence of geological and operational parameters on cross-interfacial fracture growth.Results demonstrate that vertical stress difference,elastic modulus contrast between coal and gangue layers,interfacial stress differential,and interfacial cohesion at coal-gangue interfaces are critical factors governing hydraulic fracture penetration through these interfaces.High vertical stress differences(>3 MPa)inhibit interfacial dilation,promoting predominant crosslayer fracture propagation.Reduced interfacial stress contrasts and enhanced interfacial cohesion facilitate fracture penetration across interfaces.Furthermore,smaller elastic modulus contrasts between coal and gangue correlate with increased interfacial aperture.Finally,lower injection rates effectively suppress vertical fracture propagation in deep coal reservoirs.This study elucidates the characteristics and mechanisms governing cross-layer fracture propagation in coal–rock composites with interbedded partings,and delineates the dynamic evolution laws and dominant controlling factors involved.Thefindings provide critical theoretical insights for the optimization of fracture design and the efficient development of deep coalbed methane reservoirs.
基金supported by the National Natural Science Foundation of China(Grant Nos.12272393 and 52130905).
文摘As binary geological media,soil-rock mixtures(SRMs)exhibit a distinct gradational composition,leading to their unique mechanical behaviors.To appraise the stability of SRM slopes,it is essential to determine equivalent parameters of SRMs,which are typically obtained through experimental and numerical methods.In contrasted to other numerical methods,the numerical manifold method(NMM)is more effective in addressing SRM problems.This is because the high-precision regular mathematical meshes in NMM can be used without aligning with the soil-rock interfaces and boundaries of SRMs.In the current research,the equivalent strength parameters of SRMs,i.e.the equivalent cohesion ce and internal friction angleϕ_(e),are determined using NMM.Initially,an NMM triaxial numerical model is established and validated based on triaxial experiments.Subsequently,the soil and rock parameters are derived through parameter inversion.Moreover,the impacts of rock content,size,shape and rock blocks'major-axis orientation on ce andϕ_(e) of SRMs are thoroughly examined using the NMM triaxial numerical model.Additionally,a fitting function is proposed to linkϕ_(e) to the rock content and size of SRMs.When other influencing factors are fixed,the above fitting model leads to the following conclusions:(1)the predictedϕ_(e) of SRMs increase with the increase of rock content;and(2)SRM samples with smaller rocks display a higher predictedϕ_(e).
基金The National Natural Science Foundation of China(No.52478426)the Natural Science Foundation of Hunan Province(No.2024JJ5428).
文摘Based on the surrounding rock arching and hingeless arch structure theories,a theoretical formula for the minimum overburden thickness was derived.By substituting different mechanical parameters of multiple tunnels at home and abroad into this formula,minimum self-supporting arch formulas under different surrounding rock classes were obtained.Based on the actual engineering case of a dual-mode shield tunnel,a numerical model for the tunnel boring machine excavation mode was established to verify the theoretical formulas.Next,three surrounding rock classes,four soil layer thickness gradients,and twelve overburden thickness gradients were designed,resulting in 144 models formed by the combination of the three factors.Uniform tests were conducted,and the pressure arch heights under different surrounding rock classes were obtained.The results show that in the theoretical formulas,the tunnel radius has a linear positive correlation with the pressure arch height,while the tunnel depth has a linear positive correlation with the square of the pressure arch height.According to numerical simulation results,the pressure arch height increases with the increase of the overburden thickness and then tends toward a critical value of twice the tunnel diameter.Finally,the results of the numerical model are in good agreement with those calculated using the theoretical formulas,verifying the rationality of the established theoretical formulas.
