Multi-body dynamics,relative coordinates and graph theory are combined to analyze the structure of a vehicle suspension.The dynamic equations of the left front suspension system are derived for modeling.First,The pure...Multi-body dynamics,relative coordinates and graph theory are combined to analyze the structure of a vehicle suspension.The dynamic equations of the left front suspension system are derived for modeling.First,The pure tire theory model is used as the input criteria of the suspension multibody system dynamic model in order to simulate the suspension K&C characteristics test.Then,it is important to verify the accuracy of this model by comparing and analyzing the experimental data and simulation results.The results show that the model has high precision and can predict the performance of the vehicle.It also provides a new solution for the vehicle dynamic modeling.展开更多
Based on the principle of vehicle-track coupling dynamics, SIMPACK multi-body dynamics software is used to establish a C80 wagon line-coupled multi-body dynamics model with 73 degrees of freedom. And the reasonablenes...Based on the principle of vehicle-track coupling dynamics, SIMPACK multi-body dynamics software is used to establish a C80 wagon line-coupled multi-body dynamics model with 73 degrees of freedom. And the reasonableness of the line-coupled dynamics model is verified by using the maximum residual acceleration, the nonlinear critical speed of the wagon. The experimental results show that the established vehicle line coupling dynamics model meets the requirements of vehicle line coupling dynamics modeling.展开更多
To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework ba...To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.展开更多
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
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
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
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
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 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
With the benefits of small turning radius and high trafficability, the articulated steering half-track tractor had been widely utilized in orchard and small spaced farmland. To study the dynamic performance of the art...With the benefits of small turning radius and high trafficability, the articulated steering half-track tractor had been widely utilized in orchard and small spaced farmland. To study the dynamic performance of the articulated steering half-track tractor and provide a model basis for studying the path tracking control, an accurate multi-body dynamic model of the tractor was required. In this study, the crucial parameters in the dynamic model construction of the tractor were investigated. Firstly, the topology model of the components of the half-track tractor was built by RecurDyn, in which the movement subs and driver functions were given. Secondly, considering the difference of dynamic characteristic of the articulated steering tractor with respect to different pavement hardnesses, the soft and hard pavement models were constructed by employing the harmonic superposition method. Finally, the simulations of the half-track tractor under straight-line and swerve had been conducted on the two types of pavements, and the simulation results were compared with the experimental and theoretical results. The results indicated that the average speed error of the dynamic model on hard pavement and farmland soft pavement were 2.7% and 2.1% compared with the real tractor tests. At the same time, the straight-line driving offset errors of the dynamic model on the two pavements were 1.6% and 3.8% for the front wheels and the rear wheels offset errors were 3.9% and 2.4%, respectively. Furthermore, the turning radius error under front wheel steering was 8.2% and the error under articulated steering was 5.3%. It is proved that the established dynamic model had high accuracy, which provides an efficient approach to analyze the dynamic features of the half-track tractor.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
In lifting sub-system of deep-sea mining system, spherical joint is used to connect lifting pipes to replace fixed joint. Based on Dynamics of Flexible Multi-body systems, the mechanics model of articulated lifting sy...In lifting sub-system of deep-sea mining system, spherical joint is used to connect lifting pipes to replace fixed joint. Based on Dynamics of Flexible Multi-body systems, the mechanics model of articulated lifting system is established. Under the four-grade and six-grade oceanic condition, dynamic responses of lifting system are simulated and experiment verified. The simulation results are consistent with experimental ones. The maximum moment of flexion is 322 kN-m on the first pipe under six-grade sea condition. It is seen that the articulated connection can reduce the moment of flexion. The bending deformation of pipe center is researched, and the maximum is 0. 000479 m on the first pipe. Deformation has a little effect on the motion of system. It is feasible to analyze articulated lifting system by applying the theory of flexible multi-body dynamics. The articulated lifting system is obviously better than the fixed one.展开更多
As the largest pool of terrestrial organic carbon, soils interact strongly with atmosphere composition, climate, and land change. Soil organic carbon dynamics in ecosystem plays a great role in global carbon cycle and...As the largest pool of terrestrial organic carbon, soils interact strongly with atmosphere composition, climate, and land change. Soil organic carbon dynamics in ecosystem plays a great role in global carbon cycle and global change. With development of mathematical models that simulate changes in soil organic carbon, there have been considerable advances in understanding soil organic carbon dynamics. This paper mainly reviewed the composition of soil organic matter and its influenced factors, and recommended some soil organic matter models worldwide. Based on the analyses of the developed results at home and abroad, it is suggested that future soil organic matter models should be developed toward based-process models, and not always empirical ones. The models are able to reveal their interaction between soil carbon systems, climate and land cover by technique and methods of GIS (Geographical Information System) and RS (Remote Sensing). These models should be developed at a global scale, in dynamically describing the spatial and temporal changes of soil organic matter cycle. Meanwhile, the further researches on models should be strengthen for providing theory basis and foundation in making policy of green house gas emission in China.展开更多
Mathematical models of tire-longitudinal road adhesion for use in the study of road vehicle dynamics are set up so as to express the relations of longitudinal adhesion coefficients with the slip ratio. They perfect th...Mathematical models of tire-longitudinal road adhesion for use in the study of road vehicle dynamics are set up so as to express the relations of longitudinal adhesion coefficients with the slip ratio. They perfect the Pacejka's models in practical use by taking into account the influences of all essential parameters such as road surface condition. vehicle velocity. slip angle. vertical load and slip ratio on the longitudinal adhesion coefficients. The new models are more comprehensive more concise. simpler and more convenient in application in all kinds of simulations of car dynamics in various sorts of braking modes.展开更多
The distributions of local structural units of calcium silicate melts were quantified by means of classical molecular dynamics simulation and a newly constructed structural thermodynamic model. The distribution of fiv...The distributions of local structural units of calcium silicate melts were quantified by means of classical molecular dynamics simulation and a newly constructed structural thermodynamic model. The distribution of five kinds of Si-O tetrahedra Qi from these two methods was compared with each other and also with the experimental Raman spectra, an excellent agreement was achieved. These not only displayed the panorama distribution of microstructural units in the whole composition range, but also proved that the thermodynamic model is suitable for the utilization as the subsequent application model of spectral experiments for the thermodynamic calculation. Meanwhile, the five refined regions mastered by different disproportionating reactions were obtained. Finally, the distributions of two kinds of connections between Qi were obtained, denoted as Qi-Ca-Qj and Qi-[Ob]-Qj, from the thermodynamic model, and a theoretical verification was given that the dominant connections for any composition are equivalent connections.展开更多
Mathematical models of tire-lateral mad adhesion for use in mad vehicle dynamics studies are set up to express the relations of adhesion coefficients with slip ratio in lateral direction.The models of tire-lateral mad...Mathematical models of tire-lateral mad adhesion for use in mad vehicle dynamics studies are set up to express the relations of adhesion coefficients with slip ratio in lateral direction.The models of tire-lateral mad adhesion revolutionize the Pacejka's model in concept and therefore make it possible for applications in vehicle dynamics studies by the expression of lateral adhesion coefficient as a function of wheel slip ratio,instead of the wheel slip angle,taking into account in the mean time the influences of mad surface condition, vehicle velocity,vertical load,tire slip angle,and wheel camber angle.展开更多
基金Supported by the National Key Research and Development Program of China(2017YFB0103801)
文摘Multi-body dynamics,relative coordinates and graph theory are combined to analyze the structure of a vehicle suspension.The dynamic equations of the left front suspension system are derived for modeling.First,The pure tire theory model is used as the input criteria of the suspension multibody system dynamic model in order to simulate the suspension K&C characteristics test.Then,it is important to verify the accuracy of this model by comparing and analyzing the experimental data and simulation results.The results show that the model has high precision and can predict the performance of the vehicle.It also provides a new solution for the vehicle dynamic modeling.
文摘Based on the principle of vehicle-track coupling dynamics, SIMPACK multi-body dynamics software is used to establish a C80 wagon line-coupled multi-body dynamics model with 73 degrees of freedom. And the reasonableness of the line-coupled dynamics model is verified by using the maximum residual acceleration, the nonlinear critical speed of the wagon. The experimental results show that the established vehicle line coupling dynamics model meets the requirements of vehicle line coupling dynamics modeling.
基金supported by the confidential research grant No.a8317。
文摘To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.
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.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 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 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.
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 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supported by the National Key R&D Program of China (Grant No.2022YFD2202102).
文摘With the benefits of small turning radius and high trafficability, the articulated steering half-track tractor had been widely utilized in orchard and small spaced farmland. To study the dynamic performance of the articulated steering half-track tractor and provide a model basis for studying the path tracking control, an accurate multi-body dynamic model of the tractor was required. In this study, the crucial parameters in the dynamic model construction of the tractor were investigated. Firstly, the topology model of the components of the half-track tractor was built by RecurDyn, in which the movement subs and driver functions were given. Secondly, considering the difference of dynamic characteristic of the articulated steering tractor with respect to different pavement hardnesses, the soft and hard pavement models were constructed by employing the harmonic superposition method. Finally, the simulations of the half-track tractor under straight-line and swerve had been conducted on the two types of pavements, and the simulation results were compared with the experimental and theoretical results. The results indicated that the average speed error of the dynamic model on hard pavement and farmland soft pavement were 2.7% and 2.1% compared with the real tractor tests. At the same time, the straight-line driving offset errors of the dynamic model on the two pavements were 1.6% and 3.8% for the front wheels and the rear wheels offset errors were 3.9% and 2.4%, respectively. Furthermore, the turning radius error under front wheel steering was 8.2% and the error under articulated steering was 5.3%. It is proved that the established dynamic model had high accuracy, which provides an efficient approach to analyze the dynamic features of the half-track tractor.
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.
基金This research project was financially supported by China Ocean Mineral Resources R&D Association(Grant No.DY105-03-02-17)Ph.D.Programs Foundation of Ministry of Education of China(Grant No.20060008025)
文摘In lifting sub-system of deep-sea mining system, spherical joint is used to connect lifting pipes to replace fixed joint. Based on Dynamics of Flexible Multi-body systems, the mechanics model of articulated lifting system is established. Under the four-grade and six-grade oceanic condition, dynamic responses of lifting system are simulated and experiment verified. The simulation results are consistent with experimental ones. The maximum moment of flexion is 322 kN-m on the first pipe under six-grade sea condition. It is seen that the articulated connection can reduce the moment of flexion. The bending deformation of pipe center is researched, and the maximum is 0. 000479 m on the first pipe. Deformation has a little effect on the motion of system. It is feasible to analyze articulated lifting system by applying the theory of flexible multi-body dynamics. The articulated lifting system is obviously better than the fixed one.
基金The research is funded by National Natural Science Foundation (40231016) and Canadian International Development Agency (CIDA).
文摘As the largest pool of terrestrial organic carbon, soils interact strongly with atmosphere composition, climate, and land change. Soil organic carbon dynamics in ecosystem plays a great role in global carbon cycle and global change. With development of mathematical models that simulate changes in soil organic carbon, there have been considerable advances in understanding soil organic carbon dynamics. This paper mainly reviewed the composition of soil organic matter and its influenced factors, and recommended some soil organic matter models worldwide. Based on the analyses of the developed results at home and abroad, it is suggested that future soil organic matter models should be developed toward based-process models, and not always empirical ones. The models are able to reveal their interaction between soil carbon systems, climate and land cover by technique and methods of GIS (Geographical Information System) and RS (Remote Sensing). These models should be developed at a global scale, in dynamically describing the spatial and temporal changes of soil organic matter cycle. Meanwhile, the further researches on models should be strengthen for providing theory basis and foundation in making policy of green house gas emission in China.
文摘Mathematical models of tire-longitudinal road adhesion for use in the study of road vehicle dynamics are set up so as to express the relations of longitudinal adhesion coefficients with the slip ratio. They perfect the Pacejka's models in practical use by taking into account the influences of all essential parameters such as road surface condition. vehicle velocity. slip angle. vertical load and slip ratio on the longitudinal adhesion coefficients. The new models are more comprehensive more concise. simpler and more convenient in application in all kinds of simulations of car dynamics in various sorts of braking modes.
基金Project(2012CB722805)supported by the National Basic Research Program of ChinaProjects(50504010,50974083,51174131,51374141)supported by the National Natural Science Foundation of China+1 种基金Project(50774112)supported by the Joint Fund of NSFC and Baosteel,ChinaProject(07QA4021)supported by the Shanghai"Phosphor"Science Foundation,China
文摘The distributions of local structural units of calcium silicate melts were quantified by means of classical molecular dynamics simulation and a newly constructed structural thermodynamic model. The distribution of five kinds of Si-O tetrahedra Qi from these two methods was compared with each other and also with the experimental Raman spectra, an excellent agreement was achieved. These not only displayed the panorama distribution of microstructural units in the whole composition range, but also proved that the thermodynamic model is suitable for the utilization as the subsequent application model of spectral experiments for the thermodynamic calculation. Meanwhile, the five refined regions mastered by different disproportionating reactions were obtained. Finally, the distributions of two kinds of connections between Qi were obtained, denoted as Qi-Ca-Qj and Qi-[Ob]-Qj, from the thermodynamic model, and a theoretical verification was given that the dominant connections for any composition are equivalent connections.
文摘Mathematical models of tire-lateral mad adhesion for use in mad vehicle dynamics studies are set up to express the relations of adhesion coefficients with slip ratio in lateral direction.The models of tire-lateral mad adhesion revolutionize the Pacejka's model in concept and therefore make it possible for applications in vehicle dynamics studies by the expression of lateral adhesion coefficient as a function of wheel slip ratio,instead of the wheel slip angle,taking into account in the mean time the influences of mad surface condition, vehicle velocity,vertical load,tire slip angle,and wheel camber angle.
