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
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
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
In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error...In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error between the numerical solution and the exact solution is obtained,and then compared with the error formed by the difference method,it is concluded that the Lagrange interpolation method is more effective in solving the variable coefficient ordinary differential equation.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
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
The feasibility of using a problem-dependent method to solve systems of second order ODEs is corroborated by an eigen-based theory and a methodology to develop such a numerical method is constructed.The key steps of t...The feasibility of using a problem-dependent method to solve systems of second order ODEs is corroborated by an eigen-based theory and a methodology to develop such a numerical method is constructed.The key steps of this methodology are to decouple a system of ODEs of second order into a set of uncoupled ODEs of second order;next,an eigen-dependent method is proposed to approximate the solution of each uncoupled ODE of second order.It is vital to transform all eigen-dependent methods to a problem-dependent method to bypass an Eigen analysis.The development of an eigen-dependent method plays a key role in this methodology so that slow eigenmodes can be accurately integrated while there is no instability or excessive amplitude growth in fast eigenmodes.This can explain why a problem-dependent method can simultaneously combine the explicitness of each step and A-stability.Consequently,huge computational efforts can be saved for solving nonlinear stiff problems.A new family of problem-dependent methods is developed in this work so that the feasibility of the proposed methodology can be affirmed.It has almost the same performance as that of the HHT-αmethod.However,it can save more than 99.5%of CPU demand in approximating a solution for a system of 1000 nonlinear second order ODEs.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
In order to predict the long-term rutting of asphalt pavement, the effective temperature for pavement rutting is calculated using the numerical simulation method. The transient temperature field of asphalt pavement wa...In order to predict the long-term rutting of asphalt pavement, the effective temperature for pavement rutting is calculated using the numerical simulation method. The transient temperature field of asphalt pavement was simulated based on actual meteorological data of Nanjing. 24-hour rutting development under a transient temperature field was calculated in each month. The rutting depth accumulated under the static temperature field was also estimated and the relationship between constant temperature parameters was analyzed. Then the effective temperature for pavement rutting was determined based on the rutting equivalence principle. The results show that the monthly effective temperature is above 40 t in July and August, while in June and September it ranges from 30 to 40 Rutting development can be ignored when the monthly effective temperature is less than 30 t. The yearly effective temperature for rutting in Nanjing is around 38. 5 t. The long-term rutting prediction model based on the effective temperature can reflect the influences of meteorological factors and traffic time distribution.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
To address the problems of low accuracy by the CONWEP model and poor efficiency by the Coupled Eulerian-Lagrangian(CEL)method in predicting close-range air blast loads of cylindrical charges,a neural network-based sim...To address the problems of low accuracy by the CONWEP model and poor efficiency by the Coupled Eulerian-Lagrangian(CEL)method in predicting close-range air blast loads of cylindrical charges,a neural network-based simulation(NNS)method with higher accuracy and better efficiency was proposed.The NNS method consisted of three main steps.First,the parameters of blast loads,including the peak pressures and impulses of cylindrical charges with different aspect ratios(L/D)at different stand-off distances and incident angles were obtained by two-dimensional numerical simulations.Subsequently,incident shape factors of cylindrical charges with arbitrary aspect ratios were predicted by a neural network.Finally,reflected shape factors were derived and implemented into the subroutine of the ABAQUS code to modify the CONWEP model,including modifications of impulse and overpressure.The reliability of the proposed NNS method was verified by related experimental results.Remarkable accuracy improvement was acquired by the proposed NNS method compared with the unmodified CONWEP model.Moreover,huge efficiency superiority was obtained by the proposed NNS method compared with the CEL method.The proposed NNS method showed good accuracy when the scaled distance was greater than 0.2 m/kg^(1/3).It should be noted that there is no need to generate a new dataset again since the blast loads satisfy the similarity law,and the proposed NNS method can be directly used to simulate the blast loads generated by different cylindrical charges.The proposed NNS method with high efficiency and accuracy can be used as an effective method to analyze the dynamic response of structures under blast loads,and it has significant application prospects in designing protective structures.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
In this investigation,a hybrid approach integrating the IDDES turbulence model and FW-H is employed to forecast the hydroacoustic of the rim driven thruster(RDT)under non-cavitation and uniform flow conditions at vary...In this investigation,a hybrid approach integrating the IDDES turbulence model and FW-H is employed to forecast the hydroacoustic of the rim driven thruster(RDT)under non-cavitation and uniform flow conditions at varying loading conditions(J=0.3 and J=0.6).It is revealed that the quadrupole term contribution in the P-FWH method significantly affects the monopole term in the low-frequency region,while it mainly affects the dipole term in the high-frequency region.Specifically,the overall sound pressure levels(SPL)of the RDT using the P-FWH method are 2.27 dB,10.03 dB,and 16.73 dB at the receiving points from R1 to R3 under the heavy-loaded condition,while they increase by 0.67 dB at R1,and decrease by 14.93 dB at R2,and 22.20 dB at R3,for the light-loaded condition.The study also utilizes the pressure-time derivatives to visualize the numerical noise and to pinpoint the dynamics of the vortex cores,and the optimization of the grid design can significantly reduce the numerical noise.The computational accuracy of the P-FWH method can meet the noise requirements for the preliminary design of rim driven thrusters.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 a novel class of purely organic fluores-cent materials,multiple resonance thermal-ly activated delayed fluorescence(MR-TADF)compounds hold significant promise for next-generation display technologies.The efficiency...As a novel class of purely organic fluores-cent materials,multiple resonance thermal-ly activated delayed fluorescence(MR-TADF)compounds hold significant promise for next-generation display technologies.The efficiency of exciton utilization and the overall performance of organic light-emit-ting devices are closely linked to the singlet-triplet energy gap(ΔE_(ST))of MR-TADF emitters.Identifying an economic and accu-rate theoretical approach to predictΔE_(ST)would be beneficial for high-throughput screening and facilitate the inverse design of MR-TADF molecules.In this study,we evaluated the S_(1)state energy(E(S_(1))),T_(1)state ener-gy(E(T_(1))),andΔE_(ST)using three different physical interpretations:adiabatic excitation ener-gy,vertical absorption energy,and vertical emission energy.We employed the time-depen-dent density functional theory(TDDFT)and delta self-consistent field(ΔSCF)methods to calculate E(S_(1)),E(T_(1)),andΔE_(ST)for 20 MR-TADF molecules reported in the literature.We compared these calculated values with experimental data obtained from fluorescence spec-troscopy at room-temperature(or 77 K)and phosphorescence spectroscopy conducted at 77 K.Our findings indicate that the vertical absorption energy at the S0 state minimum,deter-mined by theΔSCF method,accurately predicts the S_(1)state energy.Similarly,the vertical absorption energy at the S0 state minimum,calculated using the TDDFT method,effectively predicts the T_(1)state energy.TheΔE_(ST)derived from the difference between these two excita-tion energies exhibited the smallest mean absolute error of only 0.039 eV compared to the ex-perimental values.This combination represents the most accurate and cost-effective method reported to date for predicting theΔE_(ST)of MR-TADF molecules,and can be integrated into AI-driven inverse design workflows for new emitters.展开更多
Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers of...Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers offer advantages such as reduced material usage,lower refrigerant charge,and compact structure.However,they also face challenges,including increased refrigerant pressure drop and smaller heat transfer area inside the tubes.This paper combines the advantages and disadvantages of both small and large-diameter tubes and proposes a combined-diameter heat exchanger,consisting of large and small diameters,for use in the indoor units of split-type air conditioners.There are relatively few studies in this area.In this paper,A theoretical and numerical computation method is employed to establish a theoretical-numerical calculation model,and its reliability is verified through experiments.Using this model,the optimal combined diameters and flow path design for a combined-diameter heat exchanger using R32 as the working fluid are derived.The results show that the heat transfer performance of all combined diameter configurations improves by 2.79%to 8.26%compared to the baseline design,with the coefficient of performance(COP)increasing from 4.15 to 4.27~4.5.These designs can save copper material,but at the cost of an increase in pressure drop by 66.86%to 131.84%.The scheme IIIH,using R32,is the optimal combined-diameter and flow path configuration that balances both heat transfer performance and economic cost.展开更多
Objectives This review aimed to systematically synthesize the available research on the disclosure of diagnosis and related issues in childhood cancer from the perspectives of healthcare professionals,with the goal of...Objectives This review aimed to systematically synthesize the available research on the disclosure of diagnosis and related issues in childhood cancer from the perspectives of healthcare professionals,with the goal of informing the optimization of disclosure processes and meeting the communication needs of affected families.Methods In accordance with the Joanna Briggs Institute(JBI)methodology for mixed methods systematic reviews,the convergent segregated approach was used in this review.Articles were retrieved from 11 databases,including PubMed,Web of Science,CINAHL,CENTRAL,Embase,Ovid/Medline,PsycINFO,PsycArticles,Scopus,ERIC,and China National Knowledge Infrastructure(CNKI).The quality of the selected articles was assessed using the Mixed Method Appraisal Tool(MMAT).The review protocol was registered on PROSPERO(CRD42024542746).Results A total of 21 studies from 10 countries were included.Their methodological quality was generally medium to high,with MMAT scores ranging from 60%to 100%.The synthesis yielded three core themes:1)the spectrum of professional and societal attitudes toward disclosure;2)the dynamic practices of navigating disclosure amid uncertainty,including timing and environment,stakeholders,and content of disclosure;and 3)factors influencing disclosure,including children’s,parental,healthcare professionals’,and socio-cultural factors.Conclusions This review synthesized the perspectives and experiences of healthcare professionals regarding disclosure in childhood cancer,highlighting the complexity and multidimensional nature of this process in clinical practice.Future research should further investigate the experiences and needs of children and their parents,explore cultural variations in disclosure practices,develop context-appropriate assessment tools,and construct multidimensional intervention strategies to enhance the humanistic care and professional effectiveness of the disclosure process.展开更多
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 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.
文摘In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error between the numerical solution and the exact solution is obtained,and then compared with the error formed by the difference method,it is concluded that the Lagrange interpolation method is more effective in solving the variable coefficient ordinary differential equation.
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.
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.
文摘The feasibility of using a problem-dependent method to solve systems of second order ODEs is corroborated by an eigen-based theory and a methodology to develop such a numerical method is constructed.The key steps of this methodology are to decouple a system of ODEs of second order into a set of uncoupled ODEs of second order;next,an eigen-dependent method is proposed to approximate the solution of each uncoupled ODE of second order.It is vital to transform all eigen-dependent methods to a problem-dependent method to bypass an Eigen analysis.The development of an eigen-dependent method plays a key role in this methodology so that slow eigenmodes can be accurately integrated while there is no instability or excessive amplitude growth in fast eigenmodes.This can explain why a problem-dependent method can simultaneously combine the explicitness of each step and A-stability.Consequently,huge computational efforts can be saved for solving nonlinear stiff problems.A new family of problem-dependent methods is developed in this work so that the feasibility of the proposed methodology can be affirmed.It has almost the same performance as that of the HHT-αmethod.However,it can save more than 99.5%of CPU demand in approximating a solution for a system of 1000 nonlinear second order ODEs.
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.
基金The National Natural Science Foundation of China(No.51378121)the Fok Ying Tung Education Foundation(No.141076)the Scientific Innovation Research of College Graduates in Jiangsu Province(No.KYLX_0164)
文摘In order to predict the long-term rutting of asphalt pavement, the effective temperature for pavement rutting is calculated using the numerical simulation method. The transient temperature field of asphalt pavement was simulated based on actual meteorological data of Nanjing. 24-hour rutting development under a transient temperature field was calculated in each month. The rutting depth accumulated under the static temperature field was also estimated and the relationship between constant temperature parameters was analyzed. Then the effective temperature for pavement rutting was determined based on the rutting equivalence principle. The results show that the monthly effective temperature is above 40 t in July and August, while in June and September it ranges from 30 to 40 Rutting development can be ignored when the monthly effective temperature is less than 30 t. The yearly effective temperature for rutting in Nanjing is around 38. 5 t. The long-term rutting prediction model based on the effective temperature can reflect the influences of meteorological factors and traffic time distribution.
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financially supported by the National Natural Science Foundation of China(Grant Nos.52271317 and 52071149)the Fundamental Research Funds for the Central Universities(HUST:2019kfy XJJS007)。
文摘To address the problems of low accuracy by the CONWEP model and poor efficiency by the Coupled Eulerian-Lagrangian(CEL)method in predicting close-range air blast loads of cylindrical charges,a neural network-based simulation(NNS)method with higher accuracy and better efficiency was proposed.The NNS method consisted of three main steps.First,the parameters of blast loads,including the peak pressures and impulses of cylindrical charges with different aspect ratios(L/D)at different stand-off distances and incident angles were obtained by two-dimensional numerical simulations.Subsequently,incident shape factors of cylindrical charges with arbitrary aspect ratios were predicted by a neural network.Finally,reflected shape factors were derived and implemented into the subroutine of the ABAQUS code to modify the CONWEP model,including modifications of impulse and overpressure.The reliability of the proposed NNS method was verified by related experimental results.Remarkable accuracy improvement was acquired by the proposed NNS method compared with the unmodified CONWEP model.Moreover,huge efficiency superiority was obtained by the proposed NNS method compared with the CEL method.The proposed NNS method showed good accuracy when the scaled distance was greater than 0.2 m/kg^(1/3).It should be noted that there is no need to generate a new dataset again since the blast loads satisfy the similarity law,and the proposed NNS method can be directly used to simulate the blast loads generated by different cylindrical charges.The proposed NNS method with high efficiency and accuracy can be used as an effective method to analyze the dynamic response of structures under blast loads,and it has significant application prospects in designing protective structures.
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.
基金The National Natural Science Foundation of China(Grant No.52201376)the Natural Science Foundation of Hubei Province,China(Grant No.2023AFB683).
文摘In this investigation,a hybrid approach integrating the IDDES turbulence model and FW-H is employed to forecast the hydroacoustic of the rim driven thruster(RDT)under non-cavitation and uniform flow conditions at varying loading conditions(J=0.3 and J=0.6).It is revealed that the quadrupole term contribution in the P-FWH method significantly affects the monopole term in the low-frequency region,while it mainly affects the dipole term in the high-frequency region.Specifically,the overall sound pressure levels(SPL)of the RDT using the P-FWH method are 2.27 dB,10.03 dB,and 16.73 dB at the receiving points from R1 to R3 under the heavy-loaded condition,while they increase by 0.67 dB at R1,and decrease by 14.93 dB at R2,and 22.20 dB at R3,for the light-loaded condition.The study also utilizes the pressure-time derivatives to visualize the numerical noise and to pinpoint the dynamics of the vortex cores,and the optimization of the grid design can significantly reduce the numerical noise.The computational accuracy of the P-FWH method can meet the noise requirements for the preliminary design of rim driven thrusters.
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support provided by the National Natural Science Foundation of China(No.22273043).
文摘As a novel class of purely organic fluores-cent materials,multiple resonance thermal-ly activated delayed fluorescence(MR-TADF)compounds hold significant promise for next-generation display technologies.The efficiency of exciton utilization and the overall performance of organic light-emit-ting devices are closely linked to the singlet-triplet energy gap(ΔE_(ST))of MR-TADF emitters.Identifying an economic and accu-rate theoretical approach to predictΔE_(ST)would be beneficial for high-throughput screening and facilitate the inverse design of MR-TADF molecules.In this study,we evaluated the S_(1)state energy(E(S_(1))),T_(1)state ener-gy(E(T_(1))),andΔE_(ST)using three different physical interpretations:adiabatic excitation ener-gy,vertical absorption energy,and vertical emission energy.We employed the time-depen-dent density functional theory(TDDFT)and delta self-consistent field(ΔSCF)methods to calculate E(S_(1)),E(T_(1)),andΔE_(ST)for 20 MR-TADF molecules reported in the literature.We compared these calculated values with experimental data obtained from fluorescence spec-troscopy at room-temperature(or 77 K)and phosphorescence spectroscopy conducted at 77 K.Our findings indicate that the vertical absorption energy at the S0 state minimum,deter-mined by theΔSCF method,accurately predicts the S_(1)state energy.Similarly,the vertical absorption energy at the S0 state minimum,calculated using the TDDFT method,effectively predicts the T_(1)state energy.TheΔE_(ST)derived from the difference between these two excita-tion energies exhibited the smallest mean absolute error of only 0.039 eV compared to the ex-perimental values.This combination represents the most accurate and cost-effective method reported to date for predicting theΔE_(ST)of MR-TADF molecules,and can be integrated into AI-driven inverse design workflows for new emitters.
基金supported by Supported by the Scientific Research Foundation for High-Level Talents of Zhoukou Normal University(ZKNUC2024018).
文摘Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers offer advantages such as reduced material usage,lower refrigerant charge,and compact structure.However,they also face challenges,including increased refrigerant pressure drop and smaller heat transfer area inside the tubes.This paper combines the advantages and disadvantages of both small and large-diameter tubes and proposes a combined-diameter heat exchanger,consisting of large and small diameters,for use in the indoor units of split-type air conditioners.There are relatively few studies in this area.In this paper,A theoretical and numerical computation method is employed to establish a theoretical-numerical calculation model,and its reliability is verified through experiments.Using this model,the optimal combined diameters and flow path design for a combined-diameter heat exchanger using R32 as the working fluid are derived.The results show that the heat transfer performance of all combined diameter configurations improves by 2.79%to 8.26%compared to the baseline design,with the coefficient of performance(COP)increasing from 4.15 to 4.27~4.5.These designs can save copper material,but at the cost of an increase in pressure drop by 66.86%to 131.84%.The scheme IIIH,using R32,is the optimal combined-diameter and flow path configuration that balances both heat transfer performance and economic cost.
基金supported by the Fuxing Nursing Research Foundation of Fudan University[FNF202352].
文摘Objectives This review aimed to systematically synthesize the available research on the disclosure of diagnosis and related issues in childhood cancer from the perspectives of healthcare professionals,with the goal of informing the optimization of disclosure processes and meeting the communication needs of affected families.Methods In accordance with the Joanna Briggs Institute(JBI)methodology for mixed methods systematic reviews,the convergent segregated approach was used in this review.Articles were retrieved from 11 databases,including PubMed,Web of Science,CINAHL,CENTRAL,Embase,Ovid/Medline,PsycINFO,PsycArticles,Scopus,ERIC,and China National Knowledge Infrastructure(CNKI).The quality of the selected articles was assessed using the Mixed Method Appraisal Tool(MMAT).The review protocol was registered on PROSPERO(CRD42024542746).Results A total of 21 studies from 10 countries were included.Their methodological quality was generally medium to high,with MMAT scores ranging from 60%to 100%.The synthesis yielded three core themes:1)the spectrum of professional and societal attitudes toward disclosure;2)the dynamic practices of navigating disclosure amid uncertainty,including timing and environment,stakeholders,and content of disclosure;and 3)factors influencing disclosure,including children’s,parental,healthcare professionals’,and socio-cultural factors.Conclusions This review synthesized the perspectives and experiences of healthcare professionals regarding disclosure in childhood cancer,highlighting the complexity and multidimensional nature of this process in clinical practice.Future research should further investigate the experiences and needs of children and their parents,explore cultural variations in disclosure practices,develop context-appropriate assessment tools,and construct multidimensional intervention strategies to enhance the humanistic care and professional effectiveness of the disclosure process.
