Configuring computational fluid dynamics(CFD)simulations typically demands extensive domain expertise,limiting broader access.Although large language models(LLMs)have advanced scientific computing,their use in automat...Configuring computational fluid dynamics(CFD)simulations typically demands extensive domain expertise,limiting broader access.Although large language models(LLMs)have advanced scientific computing,their use in automating CFD workflows is underdeveloped.We introduce a novel approach centered on domain-specific LLM adaptation.By fine-tuning Qwen2.5-7B-Instruct on NL2FOAM,our custom dataset of 28,716 natural language-to-OpenFOAM configuration pairs with chain-of-thought(CoT)annotations enables direct translation from natural language descriptions to executable CFD setups.A multi-agent system orchestrates the process,autonomously verifying inputs,generating configurations,running simulations,and correcting errors.Evaluation on a benchmark of 21 diverse flow cases demonstrates state-of-the-art performance,achieving 88.7%solution accuracy and 82.6%first-attempt success rate.This significantly outperforms larger general-purpose models such as Qwen2.5-72B-Instruct,DeepSeek-R1,and Llama3.3-70B-Instruct,while also requiring fewer correction iterations and maintaining high computational efficiency.The results highlight the critical role of domain-specific adaptation in deploying LLM assistants for complex engineering workflows.Our code and fine-tuned model have been deposited at https://github.com/YYgroup/AutoCFD.展开更多
Within the prefrontal-cingulate cortex,abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions,contributing to the development of mental disorders such as depression.Despite ...Within the prefrontal-cingulate cortex,abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions,contributing to the development of mental disorders such as depression.Despite this understanding,the neural circuit mechanisms underlying this phenomenon remain elusive.In this study,we present a biophysical computational model encompassing three crucial regions,including the dorsolateral prefrontal cortex,subgenual anterior cingulate cortex,and ventromedial prefrontal cortex.The objective is to investigate the role of coupling relationships within the prefrontal-cingulate cortex networks in balancing emotions and cognitive processes.The numerical results confirm that coupled weights play a crucial role in the balance of emotional cognitive networks.Furthermore,our model predicts the pathogenic mechanism of depression resulting from abnormalities in the subgenual cortex,and network functionality was restored through intervention in the dorsolateral prefrontal cortex.This study utilizes computational modeling techniques to provide an insight explanation for the diagnosis and treatment of depression.展开更多
Electric vehicles,powered by electricity stored in a battery pack,are developing rapidly due to the rapid development of energy storage and the related motor systems being environmentally friendly.However,thermal runa...Electric vehicles,powered by electricity stored in a battery pack,are developing rapidly due to the rapid development of energy storage and the related motor systems being environmentally friendly.However,thermal runaway is the key scientific problem in battery safety research,which can cause fire and even lead to battery explosion under impact loading.In this work,a detailed computational model simulating the mechanical deformation and predicting the short-circuit onset of the 18,650 cylindrical battery is established.The detailed computational model,including the anode,cathode,separator,winding,and battery casing,is then developed under the indentation condition.The failure criteria are subsequently established based on the force–displacement curve and the separator failure.Two methods for improving the anti-short circuit ability are proposed.Results show the three causes of the short circuit and the failure sequence of components and reveal the reason why the fire is more serious under dynamic loading than under quasi-static loading.展开更多
This paper investigates the capabilities of large language models(LLMs)to leverage,learn and create knowledge in solving computational fluid dynamics(CFD)problems through three categories of baseline problems.These ca...This paper investigates the capabilities of large language models(LLMs)to leverage,learn and create knowledge in solving computational fluid dynamics(CFD)problems through three categories of baseline problems.These categories include(1)conventional CFD problems that can be solved using existing numerical methods in LLMs,such as lid-driven cavity flow and the Sod shock tube problem;(2)problems that require new numerical methods beyond those available in LLMs,such as the recently developed Chien-physics-informed neural networks for singularly perturbed convection-diffusion equations;and(3)problems that cannot be solved using existing numerical methods in LLMs,such as the ill-conditioned Hilbert linear algebraic systems.The evaluations indicate that reasoning LLMs overall outperform non-reasoning models in four test cases.Reasoning LLMs show excellent performance for CFD problems according to the tailored prompts,but their current capability in autonomous knowledge exploration and creation needs to be enhanced.展开更多
The underlying electrophysiological mechanisms and clinical treatments of cardiovascular diseases,which are the most common cause of morbidity and mortality worldwide,have gotten a lot of attention and been widely exp...The underlying electrophysiological mechanisms and clinical treatments of cardiovascular diseases,which are the most common cause of morbidity and mortality worldwide,have gotten a lot of attention and been widely explored in recent decades.Along the way,techniques such as medical imaging,computing modeling,and artificial intelligence(AI)have always played significant roles in above studies.In this article,we illustrated the applications of AI in cardiac electrophysiological research and disease prediction.We summarized general principles of AI and then focused on the roles of AI in cardiac basic and clinical studies incorporating magnetic resonance imaging and computing modeling techniques.The main challenges and perspectives were also analyzed.展开更多
Titanium-silicon(Ti-Si)alloy system shows significant potential for aerospace and automotive applications due to its superior specific strength,creep resistance,and oxidation resistance.For Si-containing Ti alloys,the...Titanium-silicon(Ti-Si)alloy system shows significant potential for aerospace and automotive applications due to its superior specific strength,creep resistance,and oxidation resistance.For Si-containing Ti alloys,the sufficient content of Si is critical for achieving these favorable performances,while excessive Si addition will result in mechanical brittleness.Herein,both physical experiments and finite element(FE)simulations are employed to investigate the micro-mechanisms of Si alloying in tailoring the mechanical properties of Ti alloys.Four typical states of Si-containing Ti alloys(solid solution state,hypoeutectoid state,near-eutectoid state,hypereutectoid state)with varying Si content(0.3-1.2 wt.%)were fabricated via in-situ alloying spark plasma sintering.Experimental results indicate that in-situ alloying of 0.6 wt.%Si enhances the alloy’s strength and ductility simultaneously due to the formation of fine and uniformly dispersed Ti_(5)Si_(3)particles,while higher content of Si(0.9 and 1.2 wt.%)results in coarser primary Ti_(5)Si_(3)agglomerations,deteriorating the ductility.FE simulations support these findings,highlighting the finer and more uniformly distributed Ti_(5)Si_(3)particles contribute to less stress concentration and promote uniform deformation across the matrix,while agglomerated Ti_(5)Si_(3)particles result in increased local stress concentrations,leading to higher chances of particle fracture and reduced ductility.This study not only elucidates the micro-mechanisms of in-situ Si alloying for tailoring the mechanical properties of Ti alloys but also aids in optimizing the design of high-performance Si-containing Ti alloys.展开更多
Based on BERTopic Model,the paper combines qualitative and quantitative methods to explore the reception of Can Xue’s translated works by analyzing readers’book reviews posted on Goodreads and Lovereading.We first c...Based on BERTopic Model,the paper combines qualitative and quantitative methods to explore the reception of Can Xue’s translated works by analyzing readers’book reviews posted on Goodreads and Lovereading.We first collected book reviews from these two well-known websites by Python.Through topic analysis of these reviews,we identified recurring topics,including details of her translated works and appreciation of their translation quality.Then,employing sentiment and content analysis methods,the paper explored the emotional attitudes and the specific thoughts of readers toward Can Xue and her translated works.The fingdings revealed that,among the 408 reviews,though the reception of Can Xue’s translated works was relatively positive,the current level of attention and recognition remains insufficient.However,based on the research results,the paper can derive valuable insights into the translation and dissemination processes such as adjusting translation and dissemination strategies,so that the global reach of Chinese literature and culture can be better facilitated.展开更多
Metaverse technologies are increasingly promoted as game-changers in transport planning,connectedautonomous mobility,and immersive traveler services.However,the field lacks a systematic review of what has been achieve...Metaverse technologies are increasingly promoted as game-changers in transport planning,connectedautonomous mobility,and immersive traveler services.However,the field lacks a systematic review of what has been achieved,where critical technical gaps remain,and where future deployments should be integrated.Using a transparent protocol-driven screening process,we reviewed 1589 records and retained 101 peer-reviewed journal and conference articles(2021–2025)that explicitly frame their contributions within a transport-oriented metaverse.Our reviewreveals a predominantly exploratory evidence base.Among the 101 studies reviewed,17(16.8%)apply fuzzymulticriteria decision-making,36(35.6%)feature digital-twin visualizations or simulation-based testbeds,9(8.9%)present hardware-in-the-loop or field pilots,and only 4(4.0%)report performance metrics such as latency,throughput,or safety under realistic network conditions.Over time,the literature evolves fromearly conceptual sketches(2021–2022)through simulation-centered frameworks(2023)to nascent engineering prototypes(2024–2025).To clarify persistent gaps,we synthesize findings into four foundational layers—geometry and rendering,distributed synchronization,cryptographic integrity,and human factors—enumerating essential algorithms(homogeneous 4×4 transforms,Lamport clocks,Raft consensus,Merkle proofs,sweep-and-prune collision culling,Q-learning,and real-time ergonomic feedback loops).A worked bus-fleet prototype illustrates how blockchain-based ticketing,reinforcement learning-optimized traffic signals,and extended reality dispatch can be integrated into a live digital twin.This prototype is supported by a threephase rollout strategy.Advancing the transport metaverse from blueprint to operation requires open data schemas,reproducible edge–cloud performance benchmarks,cross-disciplinary cyber-physical threat models,and city-scale sandboxes that apply their mathematical foundations in real-world settings.展开更多
This study presents an innovative development of the exponentially weighted moving average(EWMA)control chart,explicitly adapted for the examination of time series data distinguished by seasonal autoregressive moving ...This study presents an innovative development of the exponentially weighted moving average(EWMA)control chart,explicitly adapted for the examination of time series data distinguished by seasonal autoregressive moving average behavior—SARMA(1,1)L under exponential white noise.Unlike previous works that rely on simplified models such as AR(1)or assume independence,this research derives for the first time an exact two-sided Average Run Length(ARL)formula for theModified EWMAchart under SARMA(1,1)L conditions,using a mathematically rigorous Fredholm integral approach.The derived formulas are validated against numerical integral equation(NIE)solutions,showing strong agreement and significantly reduced computational burden.Additionally,a performance comparison index(PCI)is introduced to assess the chart’s detection capability.Results demonstrate that the proposed method exhibits superior sensitivity to mean shifts in autocorrelated environments,outperforming existing approaches.The findings offer a new,efficient framework for real-time quality control in complex seasonal processes,with potential applications in environmental monitoring and intelligent manufacturing systems.展开更多
Streptococcus suis(S.suis)is a major disease impacting pig farming globally.It can also be transferred to humans by eating raw pork.A comprehensive study was recently carried out to determine the indices throughmultip...Streptococcus suis(S.suis)is a major disease impacting pig farming globally.It can also be transferred to humans by eating raw pork.A comprehensive study was recently carried out to determine the indices throughmultiple geographic regions in China.Methods:The well-posed theorems were employed to conduct a thorough analysis of the model’s feasible features,including positivity,boundedness equilibria,reproduction number,and parameter sensitivity.Stochastic Euler,Runge Kutta,and EulerMaruyama are some of the numerical techniques used to replicate the behavior of the streptococcus suis infection in the pig population.However,the dynamic qualities of the suggested model cannot be restored using these techniques.Results:For the stochastic delay differential equations of the model,the non-standard finite difference approach in the sense of stochasticity is developed to avoid several problems such as negativity,unboundedness,inconsistency,and instability of the findings.Results from traditional stochastic methods either converge conditionally or diverge over time.The stochastic non-negative step size convergence nonstandard finite difference(NSFD)method unconditionally converges to the model’s true states.Conclusions:This study improves our understanding of the dynamics of streptococcus suis infection using versions of stochastic with delay approaches and opens up new avenues for the study of cognitive processes and neuronal analysis.Theplotted interaction behaviour and new solution comparison profiles.展开更多
A finite-element model of the thermosetting epoxy asphalt mixture（EAM） microstructure is developed to simulate the indirect tension test（IDT）.Image techniques are used to capture the EAM microstructure which is di...A finite-element model of the thermosetting epoxy asphalt mixture（EAM） microstructure is developed to simulate the indirect tension test（IDT）.Image techniques are used to capture the EAM microstructure which is divided into two phases：aggregates and mastic.A viscoelastic constitutive relationship,which is obtained from the results of a creep test,is used to represent the mastic phase at intermittent temperatures.Model simulation results of the stiffness modulus in IDT compare favorably with experimental data.Different loading directions and velocities are employed in order to account for their influence on the modulus and the localized stress of the microstructure model.It is pointed out that the modulus is not consistent when the loading direction changes since the heterogeneous distribution of the mixture internal structure,and the loading velocity affects the localized stress as a result of the viscoelasticity of the mastic.The study results can provide a theoretical basis for the finite-element method,which can be extended to the numerical simulations of asphalt mixture micromechanical behavior.展开更多
The perfectly matched layer （PML） is a highly efficient absorbing boundary condition used for the numerical modeling of seismic wave equation. The article focuses on the application of this technique to finite-eleme...The perfectly matched layer （PML） is a highly efficient absorbing boundary condition used for the numerical modeling of seismic wave equation. The article focuses on the application of this technique to finite-element time-domain numerical modeling of elastic wave equation. However, the finite-element time-domain scheme is based on the second- order wave equation in displacement formulation. Thus, the first-order PML in velocity-stress formulation cannot be directly applied to this scheme. In this article, we derive the finite- element matrix equations of second-order PML in displacement formulation, and accomplish the implementation of PML in finite-element time-domain modeling of elastic wave equation. The PML has an approximate zero reflection coefficients for bulk and surface waves in the finite-element modeling of P-SV and SH wave propagation in the 2D homogeneous elastic media. The numerical experiments using a two-layer model with irregular topography validate the efficiency of PML in the modeling of seismic wave propagation in geological models with complex structures and heterogeneous media.展开更多
To achieve high quality of service （QoS） on computational grids, the QoS-aware job scheduling is investigated for a hierarchical decentralized grid architecture that consists of multilevel schedulers. An integrated ...To achieve high quality of service （QoS） on computational grids, the QoS-aware job scheduling is investigated for a hierarchical decentralized grid architecture that consists of multilevel schedulers. An integrated QoS-aware job dispatching policy is proposed, which correlates priorities of incoming jobs used for job selecting at the local scheduler of the grid node with the job dispatching policies at the global scheduler for computational grids. The stochastic high-level Petri net （SHLPN） model of a two-level hierarchy computational grid architecture is presented, and a model refinement is made to reduce the complexity of the model solution. A performance analysis technique based on the SHLPN is proposed to investigate the QoS-aware job scheduling policy. Numerical results show that the QoS-aware job dispatching policy outperforms the QoS-unaware job dispatching policy in balancing the high-priority jobs, and thus enables priority-based QoS.展开更多
Three-dimensional forward modeling magnetotellurics （MT） problems. We present a is a challenge for geometrically complex new edge-based finite-element algorithm using an unstructured mesh for accurately and efficien...Three-dimensional forward modeling magnetotellurics （MT） problems. We present a is a challenge for geometrically complex new edge-based finite-element algorithm using an unstructured mesh for accurately and efficiently simulating 3D MT responses. The electric field curl-curl equation in the frequency domain was used to deduce the H （curl） variation weak form of the MT forward problem, the Galerkin rule was used to derive a linear finite-element equation on the linear-edge tetrahedroid space, and, finally, a BI-CGSTAB solver was used to estimate the unknown electric fields. A local mesh refinement technique in the neighbor of the measuring MT stations was used to greatly improve the accuracies of the numerical solutions. Four synthetic models validated the powerful performance of our algorithms. We believe that our method will effectively contribute to processing more complex MT studies.展开更多
A variable-fidelity method can remarkably improve the efficiency of a design optimization based on a high-fidelity and expensive numerical simulation,with assistance of lower-fidelity and cheaper simulation(s).However...A variable-fidelity method can remarkably improve the efficiency of a design optimization based on a high-fidelity and expensive numerical simulation,with assistance of lower-fidelity and cheaper simulation(s).However,most existing works only incorporate‘‘two"levels of fidelity,and thus efficiency improvement is very limited.In order to reduce the number of high-fidelity simulations as many as possible,there is a strong need to extend it to three or more fidelities.This article proposes a novel variable-fidelity optimization approach with application to aerodynamic design.Its key ingredient is the theory and algorithm of a Multi-level Hierarchical Kriging(MHK),which is referred to as a surrogate model that can incorporate simulation data with arbitrary levels of fidelity.The high-fidelity model is defined as a CFD simulation using a fine grid and the lower-fidelity models are defined as the same CFD model but with coarser grids,which are determined through a grid convergence study.First,sampling shapes are selected for each level of fidelity via technique of Design of Experiments(DoE).Then,CFD simulations are conducted and the output data of varying fidelity is used to build initial MHK models for objective(e.g.C_D)and constraint(e.g.C_L,C_m)functions.Next,new samples are selected through infillsampling criteria and the surrogate models are repetitively updated until a global optimum is found.The proposed method is validated by analytical test cases and applied to aerodynamic shape optimization of a NACA0012 airfoil and an ONERA M6 wing in transonic flows.The results confirm that the proposed method can significantly improve the optimization efficiency and apparently outperforms the existing single-fidelity or two-level-fidelity method.展开更多
A three-dimensional model for gas-solid flow in a circulating fluidized bed（CFB） riser was developed based on computational particle fluid dynamics（CPFD）.The model was used to simulate the gas-solid flow behavior ...A three-dimensional model for gas-solid flow in a circulating fluidized bed（CFB） riser was developed based on computational particle fluid dynamics（CPFD）.The model was used to simulate the gas-solid flow behavior inside a circulating fluidized bed riser operating at various superficial gas velocities and solids mass fluxes in two fluidization regimes,a dilute phase transport（DPT） regime and a fast fluidization（FF） regime.The simulation results were evaluated based on comparison with experimental data of solids velocity and holdup,obtained from non-invasive automated radioactive particle tracking and gamma-ray tomography techniques,respectively.The agreement of the predicted solids velocity and holdup with experimental data validated the CPFD model for the CFB riser.The model predicted the main features of the gas-solid flows in the two regimes;the uniform dilute phase in the DPT regime,and the coexistence of the dilute phase in the upper region and the dense phase in the lower region in the FF regime.The clustering and solids back mixing in the FF regime were stronger than those in the DPT regime.展开更多
A modeling tool for simulating three-dimensional land frequency-domain controlled-source electromagnetic surveys,based on a finite-element discretization of the Helmholtz equation for the electric fields,has been deve...A modeling tool for simulating three-dimensional land frequency-domain controlled-source electromagnetic surveys,based on a finite-element discretization of the Helmholtz equation for the electric fields,has been developed.The main difference between our modeling method and those previous works is edge finite-element approach applied to solving the three-dimensional land frequency-domain electromagnetic responses generated by horizontal electric dipole source.Firstly,the edge finite-element equation is formulated through the Galerkin method based on Helmholtz equation of the electric fields.Secondly,in order to check the validity of the modeling code,the numerical results are compared with the analytical solutions for a homogeneous half-space model.Finally,other three models are simulated with three-dimensional electromagnetic responses.The results indicate that the method can be applied for solving three-dimensional electromagnetic responses.The algorithm has been demonstrated,which can be effective to modeling the complex geo-electrical structures.This efficient algorithm will help to study the distribution laws of3-D land frequency-domain controlled-source electromagnetic responses and to setup basis for research of three-dimensional inversion.展开更多
Reliable computational foot models offer an alternative means to enhance knowledge on the biomechanics of human foot. Model validation is one of the most critical aspects of the entire foot modeling and analysis proce...Reliable computational foot models offer an alternative means to enhance knowledge on the biomechanics of human foot. Model validation is one of the most critical aspects of the entire foot modeling and analysis process.This paper presents an in vivo experiment combining motion capture system and plantar pressure measure platform to validate a three-dimensional finite element model of human foot.The Magnetic Resonance Imaging(MRI)slices for the foot modeling and the experimental data for validation were both collected from the same volunteer subject.The validated components included the comparison of static model predictions of plantar force,plantar pressure and foot surface deformation during six loading conditions,to equivalent measured data.During the whole experiment,foot surface deformation,plantar force and plantar pressure were recorded simultaneously during six different loaded standing conditions.The predictions of the current FE model were in good agreement with these experimental results.展开更多
The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical r...The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.展开更多
In this work,the computational complexity of a spin-glass three-dimensional(3D)Ising model(for the lattice sizeN=lmn,wherel,m,n are thenumbersof lattice points along three crystallographic directions)is studied.We pro...In this work,the computational complexity of a spin-glass three-dimensional(3D)Ising model(for the lattice sizeN=lmn,wherel,m,n are thenumbersof lattice points along three crystallographic directions)is studied.We prove that an absolute minimum core(AMC)model consisting of a spin-glass 2D Ising model interacting with its nearest neighboring plane,has its computational complexity O(2mn).Any algorithms to make the model smaller(or simpler)than the AMC model will cut the basic element of the spin-glass 3D Ising model and lost many important information of the original model.Therefore,the computational complexity of the spin-glass 3D Ising model cannot be reduced to be less than O(2mn)by any algorithms,which is in subexponential time,superpolynomial.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.52306126,22350710788,12432010,11988102,92270203)the Xplore Prize.
文摘Configuring computational fluid dynamics(CFD)simulations typically demands extensive domain expertise,limiting broader access.Although large language models(LLMs)have advanced scientific computing,their use in automating CFD workflows is underdeveloped.We introduce a novel approach centered on domain-specific LLM adaptation.By fine-tuning Qwen2.5-7B-Instruct on NL2FOAM,our custom dataset of 28,716 natural language-to-OpenFOAM configuration pairs with chain-of-thought(CoT)annotations enables direct translation from natural language descriptions to executable CFD setups.A multi-agent system orchestrates the process,autonomously verifying inputs,generating configurations,running simulations,and correcting errors.Evaluation on a benchmark of 21 diverse flow cases demonstrates state-of-the-art performance,achieving 88.7%solution accuracy and 82.6%first-attempt success rate.This significantly outperforms larger general-purpose models such as Qwen2.5-72B-Instruct,DeepSeek-R1,and Llama3.3-70B-Instruct,while also requiring fewer correction iterations and maintaining high computational efficiency.The results highlight the critical role of domain-specific adaptation in deploying LLM assistants for complex engineering workflows.Our code and fine-tuned model have been deposited at https://github.com/YYgroup/AutoCFD.
基金supported by the Major Research Instrument Development Project of the National Natural Science Foundation of China(82327810)the Foundation of the President of Hebei University(XZJJ202202)the Hebei Province“333 talent project”(A202101058).
文摘Within the prefrontal-cingulate cortex,abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions,contributing to the development of mental disorders such as depression.Despite this understanding,the neural circuit mechanisms underlying this phenomenon remain elusive.In this study,we present a biophysical computational model encompassing three crucial regions,including the dorsolateral prefrontal cortex,subgenual anterior cingulate cortex,and ventromedial prefrontal cortex.The objective is to investigate the role of coupling relationships within the prefrontal-cingulate cortex networks in balancing emotions and cognitive processes.The numerical results confirm that coupled weights play a crucial role in the balance of emotional cognitive networks.Furthermore,our model predicts the pathogenic mechanism of depression resulting from abnormalities in the subgenual cortex,and network functionality was restored through intervention in the dorsolateral prefrontal cortex.This study utilizes computational modeling techniques to provide an insight explanation for the diagnosis and treatment of depression.
基金supported by the National Natural Science Foundation of China(Grant Numbers:12172149 and 12172151).
文摘Electric vehicles,powered by electricity stored in a battery pack,are developing rapidly due to the rapid development of energy storage and the related motor systems being environmentally friendly.However,thermal runaway is the key scientific problem in battery safety research,which can cause fire and even lead to battery explosion under impact loading.In this work,a detailed computational model simulating the mechanical deformation and predicting the short-circuit onset of the 18,650 cylindrical battery is established.The detailed computational model,including the anode,cathode,separator,winding,and battery casing,is then developed under the indentation condition.The failure criteria are subsequently established based on the force–displacement curve and the separator failure.Two methods for improving the anti-short circuit ability are proposed.Results show the three causes of the short circuit and the failure sequence of components and reveal the reason why the fire is more serious under dynamic loading than under quasi-static loading.
基金supported by the National Natural Science Foundation of China Basic Science Center Program for“Multiscale Problems in Nonlinear Mechanics”(Grant No.11988102)the National Natural Science Foundation of China(Grant No.12202451).
文摘This paper investigates the capabilities of large language models(LLMs)to leverage,learn and create knowledge in solving computational fluid dynamics(CFD)problems through three categories of baseline problems.These categories include(1)conventional CFD problems that can be solved using existing numerical methods in LLMs,such as lid-driven cavity flow and the Sod shock tube problem;(2)problems that require new numerical methods beyond those available in LLMs,such as the recently developed Chien-physics-informed neural networks for singularly perturbed convection-diffusion equations;and(3)problems that cannot be solved using existing numerical methods in LLMs,such as the ill-conditioned Hilbert linear algebraic systems.The evaluations indicate that reasoning LLMs overall outperform non-reasoning models in four test cases.Reasoning LLMs show excellent performance for CFD problems according to the tailored prompts,but their current capability in autonomous knowledge exploration and creation needs to be enhanced.
基金the Hainan Provincial Natural Science Foundation of China(No.820RC625)the National Natural Science Foundation of China(No.82060332)。
文摘The underlying electrophysiological mechanisms and clinical treatments of cardiovascular diseases,which are the most common cause of morbidity and mortality worldwide,have gotten a lot of attention and been widely explored in recent decades.Along the way,techniques such as medical imaging,computing modeling,and artificial intelligence(AI)have always played significant roles in above studies.In this article,we illustrated the applications of AI in cardiac electrophysiological research and disease prediction.We summarized general principles of AI and then focused on the roles of AI in cardiac basic and clinical studies incorporating magnetic resonance imaging and computing modeling techniques.The main challenges and perspectives were also analyzed.
基金supported by the Natural Science Foundation of Hunan Province(Grant No.2023JJ40353)the National Key Research and Development Program of China(No.2019YFE03120001).
文摘Titanium-silicon(Ti-Si)alloy system shows significant potential for aerospace and automotive applications due to its superior specific strength,creep resistance,and oxidation resistance.For Si-containing Ti alloys,the sufficient content of Si is critical for achieving these favorable performances,while excessive Si addition will result in mechanical brittleness.Herein,both physical experiments and finite element(FE)simulations are employed to investigate the micro-mechanisms of Si alloying in tailoring the mechanical properties of Ti alloys.Four typical states of Si-containing Ti alloys(solid solution state,hypoeutectoid state,near-eutectoid state,hypereutectoid state)with varying Si content(0.3-1.2 wt.%)were fabricated via in-situ alloying spark plasma sintering.Experimental results indicate that in-situ alloying of 0.6 wt.%Si enhances the alloy’s strength and ductility simultaneously due to the formation of fine and uniformly dispersed Ti_(5)Si_(3)particles,while higher content of Si(0.9 and 1.2 wt.%)results in coarser primary Ti_(5)Si_(3)agglomerations,deteriorating the ductility.FE simulations support these findings,highlighting the finer and more uniformly distributed Ti_(5)Si_(3)particles contribute to less stress concentration and promote uniform deformation across the matrix,while agglomerated Ti_(5)Si_(3)particles result in increased local stress concentrations,leading to higher chances of particle fracture and reduced ductility.This study not only elucidates the micro-mechanisms of in-situ Si alloying for tailoring the mechanical properties of Ti alloys but also aids in optimizing the design of high-performance Si-containing Ti alloys.
基金supported by the 2023 Youth Fund for Humanities and Social Sciences Research by the Ministry of Education of the People’s Republic of China(Grant No.23YJC740004).
文摘Based on BERTopic Model,the paper combines qualitative and quantitative methods to explore the reception of Can Xue’s translated works by analyzing readers’book reviews posted on Goodreads and Lovereading.We first collected book reviews from these two well-known websites by Python.Through topic analysis of these reviews,we identified recurring topics,including details of her translated works and appreciation of their translation quality.Then,employing sentiment and content analysis methods,the paper explored the emotional attitudes and the specific thoughts of readers toward Can Xue and her translated works.The fingdings revealed that,among the 408 reviews,though the reception of Can Xue’s translated works was relatively positive,the current level of attention and recognition remains insufficient.However,based on the research results,the paper can derive valuable insights into the translation and dissemination processes such as adjusting translation and dissemination strategies,so that the global reach of Chinese literature and culture can be better facilitated.
基金financial support from the Centro de Matematica da Universidade doMinho(CMAT/UM),through project UID/00013.
文摘Metaverse technologies are increasingly promoted as game-changers in transport planning,connectedautonomous mobility,and immersive traveler services.However,the field lacks a systematic review of what has been achieved,where critical technical gaps remain,and where future deployments should be integrated.Using a transparent protocol-driven screening process,we reviewed 1589 records and retained 101 peer-reviewed journal and conference articles(2021–2025)that explicitly frame their contributions within a transport-oriented metaverse.Our reviewreveals a predominantly exploratory evidence base.Among the 101 studies reviewed,17(16.8%)apply fuzzymulticriteria decision-making,36(35.6%)feature digital-twin visualizations or simulation-based testbeds,9(8.9%)present hardware-in-the-loop or field pilots,and only 4(4.0%)report performance metrics such as latency,throughput,or safety under realistic network conditions.Over time,the literature evolves fromearly conceptual sketches(2021–2022)through simulation-centered frameworks(2023)to nascent engineering prototypes(2024–2025).To clarify persistent gaps,we synthesize findings into four foundational layers—geometry and rendering,distributed synchronization,cryptographic integrity,and human factors—enumerating essential algorithms(homogeneous 4×4 transforms,Lamport clocks,Raft consensus,Merkle proofs,sweep-and-prune collision culling,Q-learning,and real-time ergonomic feedback loops).A worked bus-fleet prototype illustrates how blockchain-based ticketing,reinforcement learning-optimized traffic signals,and extended reality dispatch can be integrated into a live digital twin.This prototype is supported by a threephase rollout strategy.Advancing the transport metaverse from blueprint to operation requires open data schemas,reproducible edge–cloud performance benchmarks,cross-disciplinary cyber-physical threat models,and city-scale sandboxes that apply their mathematical foundations in real-world settings.
基金financially by the National Research Council of Thailand(NRCT)under Contract No.N42A670894.
文摘This study presents an innovative development of the exponentially weighted moving average(EWMA)control chart,explicitly adapted for the examination of time series data distinguished by seasonal autoregressive moving average behavior—SARMA(1,1)L under exponential white noise.Unlike previous works that rely on simplified models such as AR(1)or assume independence,this research derives for the first time an exact two-sided Average Run Length(ARL)formula for theModified EWMAchart under SARMA(1,1)L conditions,using a mathematically rigorous Fredholm integral approach.The derived formulas are validated against numerical integral equation(NIE)solutions,showing strong agreement and significantly reduced computational burden.Additionally,a performance comparison index(PCI)is introduced to assess the chart’s detection capability.Results demonstrate that the proposed method exhibits superior sensitivity to mean shifts in autocorrelated environments,outperforming existing approaches.The findings offer a new,efficient framework for real-time quality control in complex seasonal processes,with potential applications in environmental monitoring and intelligent manufacturing systems.
基金supported by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia[KFU250259].
文摘Streptococcus suis(S.suis)is a major disease impacting pig farming globally.It can also be transferred to humans by eating raw pork.A comprehensive study was recently carried out to determine the indices throughmultiple geographic regions in China.Methods:The well-posed theorems were employed to conduct a thorough analysis of the model’s feasible features,including positivity,boundedness equilibria,reproduction number,and parameter sensitivity.Stochastic Euler,Runge Kutta,and EulerMaruyama are some of the numerical techniques used to replicate the behavior of the streptococcus suis infection in the pig population.However,the dynamic qualities of the suggested model cannot be restored using these techniques.Results:For the stochastic delay differential equations of the model,the non-standard finite difference approach in the sense of stochasticity is developed to avoid several problems such as negativity,unboundedness,inconsistency,and instability of the findings.Results from traditional stochastic methods either converge conditionally or diverge over time.The stochastic non-negative step size convergence nonstandard finite difference(NSFD)method unconditionally converges to the model’s true states.Conclusions:This study improves our understanding of the dynamics of streptococcus suis infection using versions of stochastic with delay approaches and opens up new avenues for the study of cognitive processes and neuronal analysis.Theplotted interaction behaviour and new solution comparison profiles.
基金Program for New Century Excellent Talents in University(No. NCET-08-0118)Specialized Research Fund for the Doctoral Program of Higher Education (No. 20090092110049)
文摘A finite-element model of the thermosetting epoxy asphalt mixture（EAM） microstructure is developed to simulate the indirect tension test（IDT）.Image techniques are used to capture the EAM microstructure which is divided into two phases：aggregates and mastic.A viscoelastic constitutive relationship,which is obtained from the results of a creep test,is used to represent the mastic phase at intermittent temperatures.Model simulation results of the stiffness modulus in IDT compare favorably with experimental data.Different loading directions and velocities are employed in order to account for their influence on the modulus and the localized stress of the microstructure model.It is pointed out that the modulus is not consistent when the loading direction changes since the heterogeneous distribution of the mixture internal structure,and the loading velocity affects the localized stress as a result of the viscoelasticity of the mastic.The study results can provide a theoretical basis for the finite-element method,which can be extended to the numerical simulations of asphalt mixture micromechanical behavior.
基金sponsored by the National Natural Science Foundation of China Research(Grant No.41274138)the Science Foundation of China University of Petroleum(Beijing)(No.KYJJ2012-05-02)
文摘The perfectly matched layer （PML） is a highly efficient absorbing boundary condition used for the numerical modeling of seismic wave equation. The article focuses on the application of this technique to finite-element time-domain numerical modeling of elastic wave equation. However, the finite-element time-domain scheme is based on the second- order wave equation in displacement formulation. Thus, the first-order PML in velocity-stress formulation cannot be directly applied to this scheme. In this article, we derive the finite- element matrix equations of second-order PML in displacement formulation, and accomplish the implementation of PML in finite-element time-domain modeling of elastic wave equation. The PML has an approximate zero reflection coefficients for bulk and surface waves in the finite-element modeling of P-SV and SH wave propagation in the 2D homogeneous elastic media. The numerical experiments using a two-layer model with irregular topography validate the efficiency of PML in the modeling of seismic wave propagation in geological models with complex structures and heterogeneous media.
基金The National Natural Science Foundation of China(No60673054,90412012)
文摘To achieve high quality of service （QoS） on computational grids, the QoS-aware job scheduling is investigated for a hierarchical decentralized grid architecture that consists of multilevel schedulers. An integrated QoS-aware job dispatching policy is proposed, which correlates priorities of incoming jobs used for job selecting at the local scheduler of the grid node with the job dispatching policies at the global scheduler for computational grids. The stochastic high-level Petri net （SHLPN） model of a two-level hierarchy computational grid architecture is presented, and a model refinement is made to reduce the complexity of the model solution. A performance analysis technique based on the SHLPN is proposed to investigate the QoS-aware job scheduling policy. Numerical results show that the QoS-aware job dispatching policy outperforms the QoS-unaware job dispatching policy in balancing the high-priority jobs, and thus enables priority-based QoS.
基金National High Technology Research and Development Program(863 Program)(No.2006AA06Z105,2007AA06Z134)
文摘Three-dimensional forward modeling magnetotellurics （MT） problems. We present a is a challenge for geometrically complex new edge-based finite-element algorithm using an unstructured mesh for accurately and efficiently simulating 3D MT responses. The electric field curl-curl equation in the frequency domain was used to deduce the H （curl） variation weak form of the MT forward problem, the Galerkin rule was used to derive a linear finite-element equation on the linear-edge tetrahedroid space, and, finally, a BI-CGSTAB solver was used to estimate the unknown electric fields. A local mesh refinement technique in the neighbor of the measuring MT stations was used to greatly improve the accuracies of the numerical solutions. Four synthetic models validated the powerful performance of our algorithms. We believe that our method will effectively contribute to processing more complex MT studies.
基金sponsored by the National Natural Science Foundation of China(Nos.11772261 and 11972305)Aeronautical Science Foundation of China(No.2016ZA53011)Foundation of National Key Laboratory(No.JCKYS2019607005).
文摘A variable-fidelity method can remarkably improve the efficiency of a design optimization based on a high-fidelity and expensive numerical simulation,with assistance of lower-fidelity and cheaper simulation(s).However,most existing works only incorporate‘‘two"levels of fidelity,and thus efficiency improvement is very limited.In order to reduce the number of high-fidelity simulations as many as possible,there is a strong need to extend it to three or more fidelities.This article proposes a novel variable-fidelity optimization approach with application to aerodynamic design.Its key ingredient is the theory and algorithm of a Multi-level Hierarchical Kriging(MHK),which is referred to as a surrogate model that can incorporate simulation data with arbitrary levels of fidelity.The high-fidelity model is defined as a CFD simulation using a fine grid and the lower-fidelity models are defined as the same CFD model but with coarser grids,which are determined through a grid convergence study.First,sampling shapes are selected for each level of fidelity via technique of Design of Experiments(DoE).Then,CFD simulations are conducted and the output data of varying fidelity is used to build initial MHK models for objective(e.g.C_D)and constraint(e.g.C_L,C_m)functions.Next,new samples are selected through infillsampling criteria and the surrogate models are repetitively updated until a global optimum is found.The proposed method is validated by analytical test cases and applied to aerodynamic shape optimization of a NACA0012 airfoil and an ONERA M6 wing in transonic flows.The results confirm that the proposed method can significantly improve the optimization efficiency and apparently outperforms the existing single-fidelity or two-level-fidelity method.
基金support by the National Basic Research Program (Grant No. 2010CB226906,and 2012CB215000)
文摘A three-dimensional model for gas-solid flow in a circulating fluidized bed（CFB） riser was developed based on computational particle fluid dynamics（CPFD）.The model was used to simulate the gas-solid flow behavior inside a circulating fluidized bed riser operating at various superficial gas velocities and solids mass fluxes in two fluidization regimes,a dilute phase transport（DPT） regime and a fast fluidization（FF） regime.The simulation results were evaluated based on comparison with experimental data of solids velocity and holdup,obtained from non-invasive automated radioactive particle tracking and gamma-ray tomography techniques,respectively.The agreement of the predicted solids velocity and holdup with experimental data validated the CPFD model for the CFB riser.The model predicted the main features of the gas-solid flows in the two regimes;the uniform dilute phase in the DPT regime,and the coexistence of the dilute phase in the upper region and the dense phase in the lower region in the FF regime.The clustering and solids back mixing in the FF regime were stronger than those in the DPT regime.
基金Projects(41674080,41674079)supported by the National Natural Science Foundation of China
文摘A modeling tool for simulating three-dimensional land frequency-domain controlled-source electromagnetic surveys,based on a finite-element discretization of the Helmholtz equation for the electric fields,has been developed.The main difference between our modeling method and those previous works is edge finite-element approach applied to solving the three-dimensional land frequency-domain electromagnetic responses generated by horizontal electric dipole source.Firstly,the edge finite-element equation is formulated through the Galerkin method based on Helmholtz equation of the electric fields.Secondly,in order to check the validity of the modeling code,the numerical results are compared with the analytical solutions for a homogeneous half-space model.Finally,other three models are simulated with three-dimensional electromagnetic responses.The results indicate that the method can be applied for solving three-dimensional electromagnetic responses.The algorithm has been demonstrated,which can be effective to modeling the complex geo-electrical structures.This efficient algorithm will help to study the distribution laws of3-D land frequency-domain controlled-source electromagnetic responses and to setup basis for research of three-dimensional inversion.
基金supported by the "Mechanical Virtual Human of China"project funded by the National Natural Science Foundation of China(30530230)further support was from the UK Royal Scoiety(Grant:IPJ/2006/R3)
文摘Reliable computational foot models offer an alternative means to enhance knowledge on the biomechanics of human foot. Model validation is one of the most critical aspects of the entire foot modeling and analysis process.This paper presents an in vivo experiment combining motion capture system and plantar pressure measure platform to validate a three-dimensional finite element model of human foot.The Magnetic Resonance Imaging(MRI)slices for the foot modeling and the experimental data for validation were both collected from the same volunteer subject.The validated components included the comparison of static model predictions of plantar force,plantar pressure and foot surface deformation during six loading conditions,to equivalent measured data.During the whole experiment,foot surface deformation,plantar force and plantar pressure were recorded simultaneously during six different loaded standing conditions.The predictions of the current FE model were in good agreement with these experimental results.
文摘The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.
基金This work has been supported by the National Natural Science Foundation of China under grant numbers 51590883 and 51331006by the State Key Project of Research and Development of China(No.2017YFA0206302).
文摘In this work,the computational complexity of a spin-glass three-dimensional(3D)Ising model(for the lattice sizeN=lmn,wherel,m,n are thenumbersof lattice points along three crystallographic directions)is studied.We prove that an absolute minimum core(AMC)model consisting of a spin-glass 2D Ising model interacting with its nearest neighboring plane,has its computational complexity O(2mn).Any algorithms to make the model smaller(or simpler)than the AMC model will cut the basic element of the spin-glass 3D Ising model and lost many important information of the original model.Therefore,the computational complexity of the spin-glass 3D Ising model cannot be reduced to be less than O(2mn)by any algorithms,which is in subexponential time,superpolynomial.
