This paper addresses urban sustainability challenges amid global urbanization, emphasizing the need for innova tive approaches aligned with the Sustainable Development Goals. While traditional tools and linear models ...This paper addresses urban sustainability challenges amid global urbanization, emphasizing the need for innova tive approaches aligned with the Sustainable Development Goals. While traditional tools and linear models offer insights, they fall short in presenting a holistic view of complex urban challenges. System dynamics (SD) models that are often utilized to provide holistic, systematic understanding of a research subject, like the urban system, emerge as valuable tools, but data scarcity and theoretical inadequacy pose challenges. The research reviews relevant papers on recent SD model applications in urban sustainability since 2018, categorizing them based on nine key indicators. Among the reviewed papers, data limitations and model assumptions were identified as ma jor challenges in applying SD models to urban sustainability. This led to exploring the transformative potential of big data analytics, a rare approach in this field as identified by this study, to enhance SD models’ empirical foundation. Integrating big data could provide data-driven calibration, potentially improving predictive accuracy and reducing reliance on simplified assumptions. The paper concludes by advocating for new approaches that reduce assumptions and promote real-time applicable models, contributing to a comprehensive understanding of urban sustainability through the synergy of big data and SD models.展开更多
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
Computational Fluids Dynamics(CFD)simulations are essential for optimizing the design of a cockpit’s internal environment,but the complex geometric models consume a significant amount of computational resources and t...Computational Fluids Dynamics(CFD)simulations are essential for optimizing the design of a cockpit’s internal environment,but the complex geometric models consume a significant amount of computational resources and time.Arbitrary simplification of geometric models may result in inaccurate calculations of physical fields.To address this issue,this study establishes a geometric model simplification strategy and successfully applies it to a cockpit.The implementation of the whole approach is divided into three steps,summarized in three methods,namely Sensitivity Analysis Method(SAM),Detail Suppression Method(DSM),and Evaluation Standards Method(ESM).Sensitivity analysis of the detailed features of the geometric model is performed using the adjoint method.The details of the geometric model are suppressed based on the principle of curvature continuity.After evaluation,the suppression degrees of detailed features with different sensitivity levels are obtained.The results demonstrate that this strategy can be employed to achieve precise simplification standards,thereby avoiding excessive deviations caused by arbitrary simplification and reducing the significant costs associated with trial-and-error simplification.展开更多
Data-driven reduced-order modeling opens new avenues of understanding,predicting,controlling,and optimizing system behavior.Simple systems may have state spaces in which sparse human-interpretable dynamical systems ca...Data-driven reduced-order modeling opens new avenues of understanding,predicting,controlling,and optimizing system behavior.Simple systems may have state spaces in which sparse human-interpretable dynamical systems can be identified.This approach has been pioneered by Brunton et al.(2016,PNAS)with sparse identification of nonlinear dynamics.Complex systems,however,cannot be expected to benefit from such simple analytical descriptions.Yet,smoothness may be exploited by analytical local descriptions.In this paper,we identify a clusterwise polynomial dynamics from time-resolved snapshot data.The full state space is partitioned into clusters with a reduced-order polynomial description for each cluster and a global patching strategy.The resulting clusterwise modeling is entirely data-driven and requires no prior knowledge of the system dynamics.We illustrate the approach on the well-known chaotic Lorenz and Rössler systems,on the more challenging chaotic fluid flow dynamics of higher state-space dimensions,on a noisy electrocardiogram signal,and finally on the time evolution of the monthly sunspot number.Clusterwise modeling offers a powerful and interpretable paradigm for dynamical modeling.Nonlinear dynamics can be approximated by assembling many simple local models of different resolutions,opening new paths to understand and control intricate nonlinearities.展开更多
Efficiency and safety are paramount concerns for commuters, operators, and designers in subway stations. This study conducted controlled experiments and developed a modified force-based model to investigate the dynami...Efficiency and safety are paramount concerns for commuters, operators, and designers in subway stations. This study conducted controlled experiments and developed a modified force-based model to investigate the dynamics of pedestrian counterflow at bottlenecks, utilizing subway passenger alighting and boarding as a case study. Specifically, the efficiency and safety of three distinct movement modes: the cooperative mode(Coop), the combination of cooperative and competitive mode(C & C), and the competitive mode(Comp), were examined and compared. The experimental findings revealed that the C & C mode exhibited a clear lane formation phenomenon and demonstrated a higher flow rate than the Comp and Coop modes. This observation suggests that a combination of cooperative and competitive behaviors among pedestrians can positively enhance traffic efficiency and safety during the alighting and boarding process. In contrast, pedestrians exhibited increased detouring in their paths and more fluctuating trajectories in the Comp mode. Additionally, a questionnaire survey assessing the level of competition and cooperation among pedestrians provided a comprehensive analysis of the psychological dynamics of passengers during the alighting and boarding activities. Lastly, the proposed force-based model was calibrated and validated, demonstrating a good performance in accurately replicating the overall characteristics of the experimental process. Overall, this study offers valuable insights into enhancing the pedestrian traffic efficiency and safety within subway systems.展开更多
It is well known that the A-square term must be considered in both cavity and circuit quantum electrodynamics systems,because it arises in the derivation from the minimal coupling Hamiltonian at any finite coupling st...It is well known that the A-square term must be considered in both cavity and circuit quantum electrodynamics systems,because it arises in the derivation from the minimal coupling Hamiltonian at any finite coupling strength.In this paper,we study the quantum Rabi model with A-square terms using the Bogoliubov operator approach.After a unitary transformation,the A-square terms can be eliminated,resulting in a modified quantum Rabi model with renormalized parameters.A transcendental function responsible for the exact solution is then derived.The presence of the A-square terms is found to significantly alter the energy spectrum.The dynamics are also studied using the obtained exact wave function,which is sensitive to the strength of the A-square terms at strong coupling.We believe that these results could be observed in future light–matter interaction systems in the ultra-strong and deep strong coupling regimes.展开更多
In recent years,there has been a surge of interest in air-ground collaborative robotics technologies.Our research group designs a novel combination-separation air-ground robot(CSAGR),which exhibits rapid automatic com...In recent years,there has been a surge of interest in air-ground collaborative robotics technologies.Our research group designs a novel combination-separation air-ground robot(CSAGR),which exhibits rapid automatic combination and separation capabilities.During the combination process,contact effects between robots,as well as between robots and the environment,are unavoidable.Therefore,it is essential to conduct detailed and accurate modeling and analysis of the collision impact intensity and transmission pathways within the robotic system to ensure the successful execution of the combination procedure.This paper addresses the intricate surface geometries and multi-point contact challenges present in the contact regions of dual robots by making appropriate modifications to the traditional continuous contact force model and applying equivalent processing techniques.The validity of the developed model is confirmed through comparisons with results obtained from finite element analysis(FEA),which demonstrates its high fidelity.Additionally,the impact of this model on control performance is analyzed within the flight control system,thereby further ensuring the successful completion of the combination process.This research represents a pioneering application and validation of continuous contact theory in the dynamics of collisions within dual robot systems.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
Research on scale effects on flows over weirs has been conducted on a limited basis, primarily focusing on flows upstream of a single-type weir, such as ogee, broad-crested, and sharp-crested (linear and non-linear) w...Research on scale effects on flows over weirs has been conducted on a limited basis, primarily focusing on flows upstream of a single-type weir, such as ogee, broad-crested, and sharp-crested (linear and non-linear) weirs. However, the scale effects downstream of these single-type weirs have not been thoroughly investigated. This study examined the scale effects on flows over a combined weir system consisting of an ogee weir and a sharp-crested weir, both upstream and downstream, utilizing physical modeling at a 1:33.33 scale based on Froude similarity and three-dimensional (3D) computational fluid dynamics (CFD) modeling. The sharp-crested weir in this study was represented by two sluice gates that remain closed and submerged during flood events. The experimental data confirmed that the equivalent discharge coefficients of the combined weir system behaved similarly to those of a sharp-crested weir across various H/P (where H is the total head, and P is the weir height) values. However, scale effects on the discharge rating curve due to surface tension and viscosity could only be minimized when H/P > 0.4, Re > 26 959, and We > 240 (where Re and We are the Reynolds and Weber numbers, respectively), provided that the water depth exceeded 0.042 m above the crest. Additionally, Re greater than 4 × 104 was necessary to minimize scale effects caused by viscosity in flows in the spillway channel and stilling basin (with baffle blocks). The limiting criteria aligned closely with existing literature. This study offers valuable insights for practical applications in hydraulic engineering in the future.展开更多
The pH-sensitive hydrogels play a crucial role in applications such as soft robotics,drug delivery,and biomedical sensors,as they require precise control of swelling behaviors and stress distributions.Traditional expe...The pH-sensitive hydrogels play a crucial role in applications such as soft robotics,drug delivery,and biomedical sensors,as they require precise control of swelling behaviors and stress distributions.Traditional experimental methods struggle to capture stress distributions due to technical limitations,while numerical approaches are often computationally intensive.This study presents a hybrid framework combining analytical modeling and machine learning(ML)to overcome these challenges.An analytical model is used to simulate transient swelling behaviors and stress distributions,and is confirmed to be viable through the comparison of the obtained simulation results with the existing experimental swelling data.The predictions from this model are used to train neural networks,including a two-step augmented architecture.The initial neural network predicts hydration values,which are then fed into a second network to predict stress distributions,effectively capturing nonlinear interdependencies.This approach achieves mean absolute errors(MAEs)as low as 0.031,with average errors of 1.9%for the radial stress and 2.55%for the hoop stress.This framework significantly enhances the predictive accuracy and reduces the computational complexity,offering actionable insights for optimizing hydrogel-based systems.展开更多
The rapid advancement of technology and the increasing speed of vehicles have led to a substantial rise in energy consumption and growing concern over environmental pollution.Beyond the promotion of new energy vehicle...The rapid advancement of technology and the increasing speed of vehicles have led to a substantial rise in energy consumption and growing concern over environmental pollution.Beyond the promotion of new energy vehicles,reducing aerodynamic drag remains a critical strategy for improving energy efficiency and lowering emissions.This study investigates the influence of key geometric parameters on the aerodynamic drag of vehicles.A parametric vehicle model was developed,and computational fluid dynamics(CFD)simulations were conducted to analyse variations in the drag coefficient(C_(d))and pressure distribution across different design configurations.The results reveal that the optimal aerodynamic performance—characterized by a minimized drag coefficient—is achieved with the following parameter settings:engine hood angle(α)of 15°,windshield angle(β)of 25°,rear window angle(γ)of 40°,rear upwards tail lift angle(θ)of 10°,ground clearance(d)of 100 mm,and side edge angle(s)of 5°.These findings offer valuable guidance for the aerodynamic optimization of vehicle body design and contribute to strategies aimed at energy conservation and emission reduction in the automotive sector.展开更多
Road pavements in tunnels are usually made of asphalt mixtures,which,unfortunately,are flammable materials.Hence,this type of pavement could release heat,and more specifically smoke,in the event of a tunnel fire,there...Road pavements in tunnels are usually made of asphalt mixtures,which,unfortunately,are flammable materials.Hence,this type of pavement could release heat,and more specifically smoke,in the event of a tunnel fire,thereby worsening the environmental conditions for human health.Extensive research has been conducted in recent years to enhance the fire reaction of traditional asphalt mixtures for the road pavements used in tunnels.The addition of the Flame Retardants(FRs)in conventional asphalt mixtures appears to be promising.Nevertheless,the potential effects of the FRs in terms of the reduction in consequences on tunnel users in the event of a large fire do not seem to have been sufficiently investigated by using fluid dynamics analysis as a computational tool.Given this gap of knowledge,this article aims to quantitatively evaluate whether the use of flame-retarded asphalt mixtures,as opposed to traditional ones without FRs,might mitigate the adverse effects on the safety of evacuees and fire brigade by performing numerical analyses in the case of a tunnel fire.To achieve this goal,3D Computational Fluid Dynamics(CFD)models,which were executed using the Fire Dynamics Simulator(FDS)tool,were established in the case of a major fire of a Heavy Goods Vehicle(HGV)characterized by a maximum Heat Release Rate(HRRmax)of 100 MW.The people evacuation process was also simulated,and the Evac tool was used.Compared to the traditional asphalt pavements without FRs,the simulation findings indicated that the addition of the FRs causes a reduction in CO and CO_(2)levels in the tunnel during the aforementioned fire,with a minor number of evacuees being exposed to the risk of incapacity to self-evacuate,as well as certain safety benefits for the operability of the firefighters entering the tunnel downstream of the fire when the tunnel is naturally ventilated.展开更多
Captive model tests are one of the most common methods to calculate the maneuvering hydrodynamic coefficients and characteristics of surface and underwater vehicles.Considerable attention must be paid to selecting and...Captive model tests are one of the most common methods to calculate the maneuvering hydrodynamic coefficients and characteristics of surface and underwater vehicles.Considerable attention must be paid to selecting and designing the most suitable laboratory equipment for towing tanks.A computational fluid dynamics(CFD)-based method is implemented to determine the loads acting on the towing facility of the submarine model.A reversed topology is also used to ensure the appropriateness of the load cells in the developed method.In this study,the numerical simulations were evaluated using the experimental results of the SUBOFF benchmark submarine model of the Defence Advanced Research Projects Agency.The maximum and minimum loads acting on the 2.5-meter submarine model were measured by determining the body’s lightest and heaviest maneuvering test scenarios.In addition to having sufficient endurance against high loads,the precision in measuring the light load was also investigated.The horizontal planar motion mechanism(HPMM)facilities in the National Iranian Marine Laboratory were developed by locating the load cells inside the submarine model.The results were presented as a case study.A numerical-based method was developed to obtain the appropriate load measurement facilities.Load cells of HPMM test basins can be selected by following the two-way procedure presented in this study.展开更多
The multi-scale modeling combined with the cohesive zone model(CZM)and the molecular dynamics(MD)method were preformed to simulate the crack propagation in NiTi shape memory alloys(SMAs).The metallographic microscope ...The multi-scale modeling combined with the cohesive zone model(CZM)and the molecular dynamics(MD)method were preformed to simulate the crack propagation in NiTi shape memory alloys(SMAs).The metallographic microscope and image processing technology were employed to achieve a quantitative grain size distribution of NiTi alloys so as to provide experimental data for molecular dynamics modeling at the atomic scale.Considering the size effect of molecular dynamics model on material properties,a reasonable modeling size was provided by taking into account three characteristic dimensions from the perspective of macro,meso,and micro scales according to the Buckinghamπtheorem.Then,the corresponding MD simulation on deformation and fracture behavior was investigated to derive a parameterized traction-separation(T-S)law,and then it was embedded into cohesive elements of finite element software.Thus,the crack propagation behavior in NiTi alloys was reproduced by the finite element method(FEM).The experimental results show that the predicted initiation fracture toughness is in good agreement with experimental data.In addition,it is found that the dynamics initiation fracture toughness increases with decreasing grain size and increasing loading velocity.展开更多
Quantum well infrared photodetectors(QWIPs) based on intersubband transitions hold significant potential for high bandwidth operation. In this work, we establish a carrier transport optimization model incorporating el...Quantum well infrared photodetectors(QWIPs) based on intersubband transitions hold significant potential for high bandwidth operation. In this work, we establish a carrier transport optimization model incorporating electron injection at the emitter to investigate the carrier dynamics time and impedance spectroscopy in GaAs/AlGaAs QWIPs. Our findings provide novel evidence that the escape time of electrons is the key limiting factor for the 3-dB bandwidth of QWIPs. Moreover, to characterize the impact of carrier dynamics time and non-equilibrium space charge region on impedance, we developed an equivalent circuit model where depletion region resistance and capacitance are employed to describe non-equilibrium space charge region. Using this model, we discovered that under illumination, both net charge accumulation caused by variations in carrier dynamics times within quantum wells and changes in width of non-equilibrium space charge region exert different dominant influences on depletion region capacitance at various doping concentrations.展开更多
Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes...Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes and leaf-related biophysical para-meter leaf area index(LAI),which are not completely synchronized in seasonality with GPP.In this study,we proposed chlorophyll content-based light use efficiency model(CC-LUE)to improve GPP estimates,as chlorophyll is the direct site of photosynthesis,and only the light absorbed by chlorophyll is used in the photosynthetic process.The CC-LUE model is constructed by establishing a linear correlation between satellite-derived canopy chlorophyll content(Chlcanopy)and FPAR.This method was calibrated and validated utiliz-ing 7-d averaged in-situ GPP data from 14 eddy covariance flux towers covering deciduous broadleaf forest ecosystems across five dif-ferent climate zones.Results showed a relatively robust seasonal consistency between Chlcanopy with GPP in deciduous broadleaf forests under different climatic conditions.The CC-LUE model explained 88% of the in-situ GPP seasonality for all validation site-year and 56.0% of in-situ GPP variations through the growing season,outperforming the three widely used LUE models(MODIS-GPP algorithm,Vegetation Photosynthesis Model(VPM),and the eddy covariance-light use efficiency model(EC-LUE)).Additionally,the CC-LUE model(RMSE=0.50 g C/(m^(2)·d))significantly improved the underestimation of GPP during the growing season in semi-arid region,re-markably decreasing the root mean square error of averaged growing season GPP simulation and in-situ GPP by 75.4%,73.4%,and 37.5%,compared with MOD17(RMSE=2.03 g C/(m^(2)·d)),VPM(RMSE=1.88 g C/(m^(2)·d)),and EC-LUE(RMSE=0.80 g C/(m^(2)·d))model.The chlorophyll-based method proved superior in capturing the seasonal variations of GPP in forest ecosystems,thereby provid-ing the possibility of a more precise depiction of forest seasonal carbon uptake.展开更多
基金sponsored by the U.S.Department of Housing and Urban Development(Grant No.NJLTS0027-22)The opinions expressed in this study are the authors alone,and do not represent the U.S.Depart-ment of HUD’s opinions.
文摘This paper addresses urban sustainability challenges amid global urbanization, emphasizing the need for innova tive approaches aligned with the Sustainable Development Goals. While traditional tools and linear models offer insights, they fall short in presenting a holistic view of complex urban challenges. System dynamics (SD) models that are often utilized to provide holistic, systematic understanding of a research subject, like the urban system, emerge as valuable tools, but data scarcity and theoretical inadequacy pose challenges. The research reviews relevant papers on recent SD model applications in urban sustainability since 2018, categorizing them based on nine key indicators. Among the reviewed papers, data limitations and model assumptions were identified as ma jor challenges in applying SD models to urban sustainability. This led to exploring the transformative potential of big data analytics, a rare approach in this field as identified by this study, to enhance SD models’ empirical foundation. Integrating big data could provide data-driven calibration, potentially improving predictive accuracy and reducing reliance on simplified assumptions. The paper concludes by advocating for new approaches that reduce assumptions and promote real-time applicable models, contributing to a comprehensive understanding of urban sustainability through the synergy of big data and SD models.
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 National Natural Science Foundation of China(Grant No.51878442).
文摘Computational Fluids Dynamics(CFD)simulations are essential for optimizing the design of a cockpit’s internal environment,but the complex geometric models consume a significant amount of computational resources and time.Arbitrary simplification of geometric models may result in inaccurate calculations of physical fields.To address this issue,this study establishes a geometric model simplification strategy and successfully applies it to a cockpit.The implementation of the whole approach is divided into three steps,summarized in three methods,namely Sensitivity Analysis Method(SAM),Detail Suppression Method(DSM),and Evaluation Standards Method(ESM).Sensitivity analysis of the detailed features of the geometric model is performed using the adjoint method.The details of the geometric model are suppressed based on the principle of curvature continuity.After evaluation,the suppression degrees of detailed features with different sensitivity levels are obtained.The results demonstrate that this strategy can be employed to achieve precise simplification standards,thereby avoiding excessive deviations caused by arbitrary simplification and reducing the significant costs associated with trial-and-error simplification.
基金supported by the National Natural Science Foundation of China(Grant Nos.12172109,12202121,and 12302293)the China Postdoctoral Science Foundation(Grant Nos.2023M730866 and 2023T160166)+1 种基金the Guangdong Basic and Applied Basic Research Foundation(Grant No.2022A1515011492)the Shenzhen Science and Technology Program(Grant Nos.JCYJ20220531095605012,KJZD20230923115210021,and 29853MKCJ202300205).
文摘Data-driven reduced-order modeling opens new avenues of understanding,predicting,controlling,and optimizing system behavior.Simple systems may have state spaces in which sparse human-interpretable dynamical systems can be identified.This approach has been pioneered by Brunton et al.(2016,PNAS)with sparse identification of nonlinear dynamics.Complex systems,however,cannot be expected to benefit from such simple analytical descriptions.Yet,smoothness may be exploited by analytical local descriptions.In this paper,we identify a clusterwise polynomial dynamics from time-resolved snapshot data.The full state space is partitioned into clusters with a reduced-order polynomial description for each cluster and a global patching strategy.The resulting clusterwise modeling is entirely data-driven and requires no prior knowledge of the system dynamics.We illustrate the approach on the well-known chaotic Lorenz and Rössler systems,on the more challenging chaotic fluid flow dynamics of higher state-space dimensions,on a noisy electrocardiogram signal,and finally on the time evolution of the monthly sunspot number.Clusterwise modeling offers a powerful and interpretable paradigm for dynamical modeling.Nonlinear dynamics can be approximated by assembling many simple local models of different resolutions,opening new paths to understand and control intricate nonlinearities.
基金Project supported by the National Natural Science Foundation of China (Grant No. 72301184)the Natural Science Foundation of Sichuan Province of China (Grant No. 2024NSFSC1073)the Fundamental Research Funds for the Central Universities (Grant No. YJ202329)。
文摘Efficiency and safety are paramount concerns for commuters, operators, and designers in subway stations. This study conducted controlled experiments and developed a modified force-based model to investigate the dynamics of pedestrian counterflow at bottlenecks, utilizing subway passenger alighting and boarding as a case study. Specifically, the efficiency and safety of three distinct movement modes: the cooperative mode(Coop), the combination of cooperative and competitive mode(C & C), and the competitive mode(Comp), were examined and compared. The experimental findings revealed that the C & C mode exhibited a clear lane formation phenomenon and demonstrated a higher flow rate than the Comp and Coop modes. This observation suggests that a combination of cooperative and competitive behaviors among pedestrians can positively enhance traffic efficiency and safety during the alighting and boarding process. In contrast, pedestrians exhibited increased detouring in their paths and more fluctuating trajectories in the Comp mode. Additionally, a questionnaire survey assessing the level of competition and cooperation among pedestrians provided a comprehensive analysis of the psychological dynamics of passengers during the alighting and boarding activities. Lastly, the proposed force-based model was calibrated and validated, demonstrating a good performance in accurately replicating the overall characteristics of the experimental process. Overall, this study offers valuable insights into enhancing the pedestrian traffic efficiency and safety within subway systems.
基金supported by the National Science Foundation of China under Grant Nos.12305009(XYC)and 11834005(QHC)the China Postdoctoral Science Foundation under Grant No.2022M720387(XYC).
文摘It is well known that the A-square term must be considered in both cavity and circuit quantum electrodynamics systems,because it arises in the derivation from the minimal coupling Hamiltonian at any finite coupling strength.In this paper,we study the quantum Rabi model with A-square terms using the Bogoliubov operator approach.After a unitary transformation,the A-square terms can be eliminated,resulting in a modified quantum Rabi model with renormalized parameters.A transcendental function responsible for the exact solution is then derived.The presence of the A-square terms is found to significantly alter the energy spectrum.The dynamics are also studied using the obtained exact wave function,which is sensitive to the strength of the A-square terms at strong coupling.We believe that these results could be observed in future light–matter interaction systems in the ultra-strong and deep strong coupling regimes.
基金Supported by National Natural Science Foundation of China(Grant Nos.T2121003 and 91748201).
文摘In recent years,there has been a surge of interest in air-ground collaborative robotics technologies.Our research group designs a novel combination-separation air-ground robot(CSAGR),which exhibits rapid automatic combination and separation capabilities.During the combination process,contact effects between robots,as well as between robots and the environment,are unavoidable.Therefore,it is essential to conduct detailed and accurate modeling and analysis of the collision impact intensity and transmission pathways within the robotic system to ensure the successful execution of the combination procedure.This paper addresses the intricate surface geometries and multi-point contact challenges present in the contact regions of dual robots by making appropriate modifications to the traditional continuous contact force model and applying equivalent processing techniques.The validity of the developed model is confirmed through comparisons with results obtained from finite element analysis(FEA),which demonstrates its high fidelity.Additionally,the impact of this model on control performance is analyzed within the flight control system,thereby further ensuring the successful completion of the combination process.This research represents a pioneering application and validation of continuous contact theory in the dynamics of collisions within dual robot systems.
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supported by the Ministry of Public Works and Housing of Indonesia and Parahyangan Catholic University(Grant No.II/PD/2023-07/02-SJ).
文摘Research on scale effects on flows over weirs has been conducted on a limited basis, primarily focusing on flows upstream of a single-type weir, such as ogee, broad-crested, and sharp-crested (linear and non-linear) weirs. However, the scale effects downstream of these single-type weirs have not been thoroughly investigated. This study examined the scale effects on flows over a combined weir system consisting of an ogee weir and a sharp-crested weir, both upstream and downstream, utilizing physical modeling at a 1:33.33 scale based on Froude similarity and three-dimensional (3D) computational fluid dynamics (CFD) modeling. The sharp-crested weir in this study was represented by two sluice gates that remain closed and submerged during flood events. The experimental data confirmed that the equivalent discharge coefficients of the combined weir system behaved similarly to those of a sharp-crested weir across various H/P (where H is the total head, and P is the weir height) values. However, scale effects on the discharge rating curve due to surface tension and viscosity could only be minimized when H/P > 0.4, Re > 26 959, and We > 240 (where Re and We are the Reynolds and Weber numbers, respectively), provided that the water depth exceeded 0.042 m above the crest. Additionally, Re greater than 4 × 104 was necessary to minimize scale effects caused by viscosity in flows in the spillway channel and stilling basin (with baffle blocks). The limiting criteria aligned closely with existing literature. This study offers valuable insights for practical applications in hydraulic engineering in the future.
文摘The pH-sensitive hydrogels play a crucial role in applications such as soft robotics,drug delivery,and biomedical sensors,as they require precise control of swelling behaviors and stress distributions.Traditional experimental methods struggle to capture stress distributions due to technical limitations,while numerical approaches are often computationally intensive.This study presents a hybrid framework combining analytical modeling and machine learning(ML)to overcome these challenges.An analytical model is used to simulate transient swelling behaviors and stress distributions,and is confirmed to be viable through the comparison of the obtained simulation results with the existing experimental swelling data.The predictions from this model are used to train neural networks,including a two-step augmented architecture.The initial neural network predicts hydration values,which are then fed into a second network to predict stress distributions,effectively capturing nonlinear interdependencies.This approach achieves mean absolute errors(MAEs)as low as 0.031,with average errors of 1.9%for the radial stress and 2.55%for the hoop stress.This framework significantly enhances the predictive accuracy and reduces the computational complexity,offering actionable insights for optimizing hydrogel-based systems.
基金funded by the“Hundred Outstanding Talents”Support Program of Jining University,a provincial-level key project in the field of natural sciences,grant number 2023ZYRC23Jining Key R&D Program(Soft Science)Project,No.2024JNZC010Shandong Province Key Research and Development Program(Technology-Based Small and Medium-sized Enterprises Innovation Capability Improvement)Project No.2025TSGCCZZB0679.
文摘The rapid advancement of technology and the increasing speed of vehicles have led to a substantial rise in energy consumption and growing concern over environmental pollution.Beyond the promotion of new energy vehicles,reducing aerodynamic drag remains a critical strategy for improving energy efficiency and lowering emissions.This study investigates the influence of key geometric parameters on the aerodynamic drag of vehicles.A parametric vehicle model was developed,and computational fluid dynamics(CFD)simulations were conducted to analyse variations in the drag coefficient(C_(d))and pressure distribution across different design configurations.The results reveal that the optimal aerodynamic performance—characterized by a minimized drag coefficient—is achieved with the following parameter settings:engine hood angle(α)of 15°,windshield angle(β)of 25°,rear window angle(γ)of 40°,rear upwards tail lift angle(θ)of 10°,ground clearance(d)of 100 mm,and side edge angle(s)of 5°.These findings offer valuable guidance for the aerodynamic optimization of vehicle body design and contribute to strategies aimed at energy conservation and emission reduction in the automotive sector.
文摘Road pavements in tunnels are usually made of asphalt mixtures,which,unfortunately,are flammable materials.Hence,this type of pavement could release heat,and more specifically smoke,in the event of a tunnel fire,thereby worsening the environmental conditions for human health.Extensive research has been conducted in recent years to enhance the fire reaction of traditional asphalt mixtures for the road pavements used in tunnels.The addition of the Flame Retardants(FRs)in conventional asphalt mixtures appears to be promising.Nevertheless,the potential effects of the FRs in terms of the reduction in consequences on tunnel users in the event of a large fire do not seem to have been sufficiently investigated by using fluid dynamics analysis as a computational tool.Given this gap of knowledge,this article aims to quantitatively evaluate whether the use of flame-retarded asphalt mixtures,as opposed to traditional ones without FRs,might mitigate the adverse effects on the safety of evacuees and fire brigade by performing numerical analyses in the case of a tunnel fire.To achieve this goal,3D Computational Fluid Dynamics(CFD)models,which were executed using the Fire Dynamics Simulator(FDS)tool,were established in the case of a major fire of a Heavy Goods Vehicle(HGV)characterized by a maximum Heat Release Rate(HRRmax)of 100 MW.The people evacuation process was also simulated,and the Evac tool was used.Compared to the traditional asphalt pavements without FRs,the simulation findings indicated that the addition of the FRs causes a reduction in CO and CO_(2)levels in the tunnel during the aforementioned fire,with a minor number of evacuees being exposed to the risk of incapacity to self-evacuate,as well as certain safety benefits for the operability of the firefighters entering the tunnel downstream of the fire when the tunnel is naturally ventilated.
文摘Captive model tests are one of the most common methods to calculate the maneuvering hydrodynamic coefficients and characteristics of surface and underwater vehicles.Considerable attention must be paid to selecting and designing the most suitable laboratory equipment for towing tanks.A computational fluid dynamics(CFD)-based method is implemented to determine the loads acting on the towing facility of the submarine model.A reversed topology is also used to ensure the appropriateness of the load cells in the developed method.In this study,the numerical simulations were evaluated using the experimental results of the SUBOFF benchmark submarine model of the Defence Advanced Research Projects Agency.The maximum and minimum loads acting on the 2.5-meter submarine model were measured by determining the body’s lightest and heaviest maneuvering test scenarios.In addition to having sufficient endurance against high loads,the precision in measuring the light load was also investigated.The horizontal planar motion mechanism(HPMM)facilities in the National Iranian Marine Laboratory were developed by locating the load cells inside the submarine model.The results were presented as a case study.A numerical-based method was developed to obtain the appropriate load measurement facilities.Load cells of HPMM test basins can be selected by following the two-way procedure presented in this study.
基金Funded by the National Natural Science Foundation of China Academy of Engineering Physics and Jointly Setup"NSAF"Joint Fund(No.U1430119)。
文摘The multi-scale modeling combined with the cohesive zone model(CZM)and the molecular dynamics(MD)method were preformed to simulate the crack propagation in NiTi shape memory alloys(SMAs).The metallographic microscope and image processing technology were employed to achieve a quantitative grain size distribution of NiTi alloys so as to provide experimental data for molecular dynamics modeling at the atomic scale.Considering the size effect of molecular dynamics model on material properties,a reasonable modeling size was provided by taking into account three characteristic dimensions from the perspective of macro,meso,and micro scales according to the Buckinghamπtheorem.Then,the corresponding MD simulation on deformation and fracture behavior was investigated to derive a parameterized traction-separation(T-S)law,and then it was embedded into cohesive elements of finite element software.Thus,the crack propagation behavior in NiTi alloys was reproduced by the finite element method(FEM).The experimental results show that the predicted initiation fracture toughness is in good agreement with experimental data.In addition,it is found that the dynamics initiation fracture toughness increases with decreasing grain size and increasing loading velocity.
基金financially supported by the National Natural Science Foundation of China (Grant No. 61991442)。
文摘Quantum well infrared photodetectors(QWIPs) based on intersubband transitions hold significant potential for high bandwidth operation. In this work, we establish a carrier transport optimization model incorporating electron injection at the emitter to investigate the carrier dynamics time and impedance spectroscopy in GaAs/AlGaAs QWIPs. Our findings provide novel evidence that the escape time of electrons is the key limiting factor for the 3-dB bandwidth of QWIPs. Moreover, to characterize the impact of carrier dynamics time and non-equilibrium space charge region on impedance, we developed an equivalent circuit model where depletion region resistance and capacitance are employed to describe non-equilibrium space charge region. Using this model, we discovered that under illumination, both net charge accumulation caused by variations in carrier dynamics times within quantum wells and changes in width of non-equilibrium space charge region exert different dominant influences on depletion region capacitance at various doping concentrations.
基金Under the auspices of the National Key Research and Development Program of China(No.2019YFA0606603)。
文摘Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes and leaf-related biophysical para-meter leaf area index(LAI),which are not completely synchronized in seasonality with GPP.In this study,we proposed chlorophyll content-based light use efficiency model(CC-LUE)to improve GPP estimates,as chlorophyll is the direct site of photosynthesis,and only the light absorbed by chlorophyll is used in the photosynthetic process.The CC-LUE model is constructed by establishing a linear correlation between satellite-derived canopy chlorophyll content(Chlcanopy)and FPAR.This method was calibrated and validated utiliz-ing 7-d averaged in-situ GPP data from 14 eddy covariance flux towers covering deciduous broadleaf forest ecosystems across five dif-ferent climate zones.Results showed a relatively robust seasonal consistency between Chlcanopy with GPP in deciduous broadleaf forests under different climatic conditions.The CC-LUE model explained 88% of the in-situ GPP seasonality for all validation site-year and 56.0% of in-situ GPP variations through the growing season,outperforming the three widely used LUE models(MODIS-GPP algorithm,Vegetation Photosynthesis Model(VPM),and the eddy covariance-light use efficiency model(EC-LUE)).Additionally,the CC-LUE model(RMSE=0.50 g C/(m^(2)·d))significantly improved the underestimation of GPP during the growing season in semi-arid region,re-markably decreasing the root mean square error of averaged growing season GPP simulation and in-situ GPP by 75.4%,73.4%,and 37.5%,compared with MOD17(RMSE=2.03 g C/(m^(2)·d)),VPM(RMSE=1.88 g C/(m^(2)·d)),and EC-LUE(RMSE=0.80 g C/(m^(2)·d))model.The chlorophyll-based method proved superior in capturing the seasonal variations of GPP in forest ecosystems,thereby provid-ing the possibility of a more precise depiction of forest seasonal carbon uptake.
