复杂地形风电场流动具有强烈的非定常现象和多尺度特征,其准确模拟是风资源精细化评估的难点。为兼顾宏观中尺度大气环流和微观非定常流动细节,该文结合中尺度气象研究与预报(weather research and forecasting,WRF)模式和微尺度计算流...复杂地形风电场流动具有强烈的非定常现象和多尺度特征,其准确模拟是风资源精细化评估的难点。为兼顾宏观中尺度大气环流和微观非定常流动细节,该文结合中尺度气象研究与预报(weather research and forecasting,WRF)模式和微尺度计算流体动力学(computational fluid dynamics,CFD)技术,构建一套WRF-CFD模式耦合的复杂地形风电场非定常仿真方法。以国际经典案例Askervein山和Bolund岛为验证对象,研究复杂地形流场中平均风速和湍流强度的分布特征,并简要分析复杂地形中风力机布置策略。结果表明,基于WRF-CFD模式的数值模拟结果与实验观测值有较好的一致性,且优于中尺度数值模拟结果,在选取的特征点位置,风速绝对误差均在2 m/s以内。结果可为风力机的设计、布局、载荷评估及风电场运行控制提供一定参考。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
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
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
Kinetic impact is the most practical planetary-defense technique,with momentum-transfer efficiency central to deflection design.We present a Monte Carlo photometric framework that couples ejecta sampling,dynamical evo...Kinetic impact is the most practical planetary-defense technique,with momentum-transfer efficiency central to deflection design.We present a Monte Carlo photometric framework that couples ejecta sampling,dynamical evolution,and image synthesis to compare directly with HST,LICIACube,ground-based and Lucy observations of the DART impact.Decomposing ejecta into(1)a highvelocity(~1600 m/s)plume exhibiting Na/K resonance,(2)a low-velocity(~1 m/s)conical component shaped by binary gravity and solar radiation pressure,and(3)meter-scale boulders,we quantify each component’s mass and momentum.Fitting photometric decay curves and morphological evolution yields size-velocity distributions and,via scaling laws,estimates of Dimorphos’bulk density,cratering parameters,and cohesive strength that agree with dynamical constraints.Photometric ejecta modeling therefore provides a robust route to constrain momentum enhancement and target properties,improving predictive capability for kinetic-deflection missions.展开更多
As China's high-speed railway technology advances,high-speed trains have emerged as a pivotal mode of transportation,instrumental in facilitating passenger and freight mobility while fostering robust regional eco-...As China's high-speed railway technology advances,high-speed trains have emerged as a pivotal mode of transportation,instrumental in facilitating passenger and freight mobility while fostering robust regional eco-nomic and trade interactions.Nonetheless,the safety of train operations remains a paramount concern,prompting extensive research into the dynamic behavior of critical components,which is essential to ensuring seamless and secure transportation services.This article commences by comprehensively reviewing the current landscape and evolutionary trajectory of dynamic model analysis for both traditional bearings and axle box bearings.Emphasis is placed on elucidating the profound influence of diverse bearing fault types on the system's kinematic state,alongside delving into the research methodologies employed in developing multi-physics field coupling models.Subsequently,it expounds on the content of investigations focusing on various wheel and track impairments,grounded in the dynamic modeling of the bearing vehicle coupling system.Concurrently,the intricate interplay between wheel-rail excitation and axle box bearing faults on the system's performance is elucidated.Concludingly,the article underscores the inadequacy of current multi-source fault diagnosis meth-odologies in tackling the intricacies of complex train operating environments,thereby highlighting its sig-nificance as a pressing and vital research agenda for the future.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
文摘复杂地形风电场流动具有强烈的非定常现象和多尺度特征,其准确模拟是风资源精细化评估的难点。为兼顾宏观中尺度大气环流和微观非定常流动细节,该文结合中尺度气象研究与预报(weather research and forecasting,WRF)模式和微尺度计算流体动力学(computational fluid dynamics,CFD)技术,构建一套WRF-CFD模式耦合的复杂地形风电场非定常仿真方法。以国际经典案例Askervein山和Bolund岛为验证对象,研究复杂地形流场中平均风速和湍流强度的分布特征,并简要分析复杂地形中风力机布置策略。结果表明,基于WRF-CFD模式的数值模拟结果与实验观测值有较好的一致性,且优于中尺度数值模拟结果,在选取的特征点位置,风速绝对误差均在2 m/s以内。结果可为风力机的设计、布局、载荷评估及风电场运行控制提供一定参考。
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 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.
基金supported by the National Natural Science Foundation of China(Grant No.12272018)the National Key Basic Research Project(2022JCJQZD20600).
文摘Kinetic impact is the most practical planetary-defense technique,with momentum-transfer efficiency central to deflection design.We present a Monte Carlo photometric framework that couples ejecta sampling,dynamical evolution,and image synthesis to compare directly with HST,LICIACube,ground-based and Lucy observations of the DART impact.Decomposing ejecta into(1)a highvelocity(~1600 m/s)plume exhibiting Na/K resonance,(2)a low-velocity(~1 m/s)conical component shaped by binary gravity and solar radiation pressure,and(3)meter-scale boulders,we quantify each component’s mass and momentum.Fitting photometric decay curves and morphological evolution yields size-velocity distributions and,via scaling laws,estimates of Dimorphos’bulk density,cratering parameters,and cohesive strength that agree with dynamical constraints.Photometric ejecta modeling therefore provides a robust route to constrain momentum enhancement and target properties,improving predictive capability for kinetic-deflection missions.
基金Supported by the National Natural Science Foundation of China(Grant Nos.12393783,12302067,12172235,52072249)Joint Funds of the National Natural Science Foundation of China(Grant No.U24A2003)+3 种基金College Education Scientific Research Project of Hebei Province(Grant No.JZX2024006)Central Guiding Local Scientific and Technological Development Funding Project(Grant No.246Z2206G)the Key Research Project of China State Railway Group Co.,Ltd.(Grant No.N2024T009)S&T Program of Hebei(Grant No.21567622H).
文摘As China's high-speed railway technology advances,high-speed trains have emerged as a pivotal mode of transportation,instrumental in facilitating passenger and freight mobility while fostering robust regional eco-nomic and trade interactions.Nonetheless,the safety of train operations remains a paramount concern,prompting extensive research into the dynamic behavior of critical components,which is essential to ensuring seamless and secure transportation services.This article commences by comprehensively reviewing the current landscape and evolutionary trajectory of dynamic model analysis for both traditional bearings and axle box bearings.Emphasis is placed on elucidating the profound influence of diverse bearing fault types on the system's kinematic state,alongside delving into the research methodologies employed in developing multi-physics field coupling models.Subsequently,it expounds on the content of investigations focusing on various wheel and track impairments,grounded in the dynamic modeling of the bearing vehicle coupling system.Concurrently,the intricate interplay between wheel-rail excitation and axle box bearing faults on the system's performance is elucidated.Concludingly,the article underscores the inadequacy of current multi-source fault diagnosis meth-odologies in tackling the intricacies of complex train operating environments,thereby highlighting its sig-nificance as a pressing and vital research agenda for the future.
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.
