In order to intensify market competition, manufacturing enterprises must improve their product innovation capability. It is difficult to integrate the system modeling, simulation and collaborative process management i...In order to intensify market competition, manufacturing enterprises must improve their product innovation capability. It is difficult to integrate the system modeling, simulation and collaborative process management in complex product development. A collaborative platform for complex product development based on multi-domain unified modeling and simulation is proposed in this paper. The architecture of the platform is firstly stated. The idea and realization of three key technologies, i.e. multi-domain modeling and simulation for complex product, knowledge management for product design and simulation, multi-domain collaborative mechanism, are emphasized. Finally, an industry case is given. The demonstration of the system shows that integration architecture is the effective infrastructure for multi-domain collaborative product development.展开更多
The widespread adoption of aluminumalloy electric buses,known for their energy efficiency and eco-friendliness,faces a challenge due to the aluminum frame’s susceptibility to deformation compared to steel.This issue ...The widespread adoption of aluminumalloy electric buses,known for their energy efficiency and eco-friendliness,faces a challenge due to the aluminum frame’s susceptibility to deformation compared to steel.This issue is further exacerbated by the stringent requirements imposed by the flammability and explosiveness of batteries,necessitating robust frame protection.Our study aims to optimize the connectors of aluminum alloy bus frames,emphasizing durability,energy efficiency,and safety.This research delves into Multi-Objective Coordinated Optimization(MCO)techniques for lightweight design in aluminum alloy bus body connectors.Our goal is to enhance lightweighting,reinforce energy absorption,and improve deformation resistance in connector components.Three typical aluminum alloy connectors were selected and a design optimization platform was built for their MCO using a variety of software and methods.Firstly,through three-point bending experiments and finite element analysis on three types of connector components,we identified optimized design parameters based on deformation patterns.Then,employing Optimal Latin hypercube design(OLHD),parametric modeling,and neural network approximation,we developed high-precision approximate models for the design parameters of each connector component,targeting energy absorption,mass,and logarithmic strain.Lastly,utilizing the Archive-based Micro Genetic Algorithm(AMGA),Multi-Objective Particle Swarm Optimization(MOPSO),and Non-dominated SortingGenetic Algorithm(NSGA2),we explored optimized design solutions for these joint components.Subsequently,we simulated joint assembly buckling during bus rollover crash scenarios to verify and analyze the optimized solutions in three-point bending simulations.Each joint component showcased a remarkable 30%–40%mass reduction while boosting energy absorption.Our design optimization method exhibits high efficiency and costeffectiveness.Leveraging contemporary automation technology,the design optimization platform developed in this study is poised to facilitate intelligent optimization of lightweight metal components in future applications.展开更多
We postulate and analyze a nonlinear subsampling accuracy loss(SSAL)model based on the root mean square error(RMSE)and two SSAL models based on the mean square error(MSE),suggested by extensive preliminary simulations...We postulate and analyze a nonlinear subsampling accuracy loss(SSAL)model based on the root mean square error(RMSE)and two SSAL models based on the mean square error(MSE),suggested by extensive preliminary simulations.The SSAL models predict accuracy loss in terms of subsampling parameters like the fraction of users dropped(FUD)and the fraction of items dropped(FID).We seek to investigate whether the models depend on the characteristics of the dataset in a constant way across datasets when using the SVD collaborative filtering(CF)algorithm.The dataset characteristics considered include various densities of the rating matrix and the numbers of users and items.Extensive simulations and rigorous regression analysis led to empirical symmetrical SSAL models in terms of FID and FUD whose coefficients depend only on the data characteristics.The SSAL models came out to be multi-linear in terms of odds ratios of dropping a user(or an item)vs.not dropping it.Moreover,one MSE deterioration model turned out to be linear in the FID and FUD odds where their interaction term has a zero coefficient.Most importantly,the models are constant in the sense that they are written in closed-form using the considered data characteristics(densities and numbers of users and items).The models are validated through extensive simulations based on 850 synthetically generated primary(pre-subsampling)matrices derived from the 25M MovieLens dataset.Nearly 460000 subsampled rating matrices were then simulated and subjected to the singular value decomposition(SVD)CF algorithm.Further validation was conducted using the 1M MovieLens and the Yahoo!Music Rating datasets.The models were constant and significant across all 3 datasets.展开更多
This paper presents an integrated approach to multidisciplinary collaborative simulation for complex engineering systems. The formulized paradigm of multidisciplinary collaborative simulation for com- plex engineering...This paper presents an integrated approach to multidisciplinary collaborative simulation for complex engineering systems. The formulized paradigm of multidisciplinary collaborative simulation for com- plex engineering systems is principally analyzed. An IEEE HLA and web services based framework is proposed to provide a heterogeneous, distributed and collaborative running environment where multidisciplinary modeling, running management and post-processing of collaborative simulation are undertaken. The mechanism of multidisciplinary collaborative modeling, disciplinary model transformation, and time-synchronized simulation advancement are studied in detail. A prototype with the functions of multidisciplinary modeling, running management and post-processing for collaborative simulations is developed, and a typical complex engineering system is chosen as a case study to demonstrate the effectiveness of this new approach towards collaborative simulation.展开更多
The power split hybrid electric vehicle(HEV)adopts a power coupling configuration featuring dual planetary gearsets and multiple clutches,enabling diverse operational modes through clutch engagement and disengagement....The power split hybrid electric vehicle(HEV)adopts a power coupling configuration featuring dual planetary gearsets and multiple clutches,enabling diverse operational modes through clutch engagement and disengagement.The multi-clutch configuration usually involves the collaboration of two clutches during the transient mode switching process,thereby substantially elevating control complexity.This study focuses on power split HEVs that integrate multi-clutch mechanisms and investigates how different clutch collaboration manners impact the characteristics of transient mode switching.The powertrain model for the power-split HEV is established utilizing matrix-based methodologies.Through the formulation of clutch torque curves and clutch collaboration models,this research systematically explores the effects of clutch engagement timing and the duration of clutch slipping state on transient mode switching behaviors.Building upon this analysis,an optimization problem for control parameters pertaining to the two collaborative clutches is formulated.The simulated annealing algorithm is employed to optimize these control parameters.Simulation results demonstrate that the clutch collaboration manners have a great influence on the transient mode switching performance.Compared with the pre-calibrated benchmark and the optimal solution derived by the genetic algorithm,the maximal longitudinal jerk and clutch slipping work during the transient mode switching process is reduced obviously with the optimal control parameters derived by the simulated annealing algorithm.The study provides valuable insights for the dynamic coordinated control of the power-split HEVs featuring complex clutch collaboration mechanisms.展开更多
基金Supported by the National Natural Science Foundation of China (60736019)the National High Technology Research and Development Program of China (863 Program) (2007AA40603)
文摘In order to intensify market competition, manufacturing enterprises must improve their product innovation capability. It is difficult to integrate the system modeling, simulation and collaborative process management in complex product development. A collaborative platform for complex product development based on multi-domain unified modeling and simulation is proposed in this paper. The architecture of the platform is firstly stated. The idea and realization of three key technologies, i.e. multi-domain modeling and simulation for complex product, knowledge management for product design and simulation, multi-domain collaborative mechanism, are emphasized. Finally, an industry case is given. The demonstration of the system shows that integration architecture is the effective infrastructure for multi-domain collaborative product development.
基金the National Natural Science Foundation of China(Grant Number 52075553)the Postgraduate Research and Innovation Project of Central South University(School-Enterprise Association)(Grant Number 2021XQLH014).
文摘The widespread adoption of aluminumalloy electric buses,known for their energy efficiency and eco-friendliness,faces a challenge due to the aluminum frame’s susceptibility to deformation compared to steel.This issue is further exacerbated by the stringent requirements imposed by the flammability and explosiveness of batteries,necessitating robust frame protection.Our study aims to optimize the connectors of aluminum alloy bus frames,emphasizing durability,energy efficiency,and safety.This research delves into Multi-Objective Coordinated Optimization(MCO)techniques for lightweight design in aluminum alloy bus body connectors.Our goal is to enhance lightweighting,reinforce energy absorption,and improve deformation resistance in connector components.Three typical aluminum alloy connectors were selected and a design optimization platform was built for their MCO using a variety of software and methods.Firstly,through three-point bending experiments and finite element analysis on three types of connector components,we identified optimized design parameters based on deformation patterns.Then,employing Optimal Latin hypercube design(OLHD),parametric modeling,and neural network approximation,we developed high-precision approximate models for the design parameters of each connector component,targeting energy absorption,mass,and logarithmic strain.Lastly,utilizing the Archive-based Micro Genetic Algorithm(AMGA),Multi-Objective Particle Swarm Optimization(MOPSO),and Non-dominated SortingGenetic Algorithm(NSGA2),we explored optimized design solutions for these joint components.Subsequently,we simulated joint assembly buckling during bus rollover crash scenarios to verify and analyze the optimized solutions in three-point bending simulations.Each joint component showcased a remarkable 30%–40%mass reduction while boosting energy absorption.Our design optimization method exhibits high efficiency and costeffectiveness.Leveraging contemporary automation technology,the design optimization platform developed in this study is poised to facilitate intelligent optimization of lightweight metal components in future applications.
文摘We postulate and analyze a nonlinear subsampling accuracy loss(SSAL)model based on the root mean square error(RMSE)and two SSAL models based on the mean square error(MSE),suggested by extensive preliminary simulations.The SSAL models predict accuracy loss in terms of subsampling parameters like the fraction of users dropped(FUD)and the fraction of items dropped(FID).We seek to investigate whether the models depend on the characteristics of the dataset in a constant way across datasets when using the SVD collaborative filtering(CF)algorithm.The dataset characteristics considered include various densities of the rating matrix and the numbers of users and items.Extensive simulations and rigorous regression analysis led to empirical symmetrical SSAL models in terms of FID and FUD whose coefficients depend only on the data characteristics.The SSAL models came out to be multi-linear in terms of odds ratios of dropping a user(or an item)vs.not dropping it.Moreover,one MSE deterioration model turned out to be linear in the FID and FUD odds where their interaction term has a zero coefficient.Most importantly,the models are constant in the sense that they are written in closed-form using the considered data characteristics(densities and numbers of users and items).The models are validated through extensive simulations based on 850 synthetically generated primary(pre-subsampling)matrices derived from the 25M MovieLens dataset.Nearly 460000 subsampled rating matrices were then simulated and subjected to the singular value decomposition(SVD)CF algorithm.Further validation was conducted using the 1M MovieLens and the Yahoo!Music Rating datasets.The models were constant and significant across all 3 datasets.
基金Supported by the National Natural Science Foundation of China (Grant No. 60674079)the Key Laboratory of Beijing Simulation Center(Grant No. B0420060524)
文摘This paper presents an integrated approach to multidisciplinary collaborative simulation for complex engineering systems. The formulized paradigm of multidisciplinary collaborative simulation for com- plex engineering systems is principally analyzed. An IEEE HLA and web services based framework is proposed to provide a heterogeneous, distributed and collaborative running environment where multidisciplinary modeling, running management and post-processing of collaborative simulation are undertaken. The mechanism of multidisciplinary collaborative modeling, disciplinary model transformation, and time-synchronized simulation advancement are studied in detail. A prototype with the functions of multidisciplinary modeling, running management and post-processing for collaborative simulations is developed, and a typical complex engineering system is chosen as a case study to demonstrate the effectiveness of this new approach towards collaborative simulation.
基金funded by the National Natural Science Foundation of China(Grant No.51905219,No.52272368)the Postdoctoral Science Foundation of China(Grant No.2023M731444)+2 种基金the Young Elite Scientists Sponsorship Program by CAST(2020QNRC001)the Key Research and Development Program of Zhenjiang City(No.GY2021001)the Project of Faculty of Agricultural Equipment of Jiangsu University(No.NZXB20210103).
文摘The power split hybrid electric vehicle(HEV)adopts a power coupling configuration featuring dual planetary gearsets and multiple clutches,enabling diverse operational modes through clutch engagement and disengagement.The multi-clutch configuration usually involves the collaboration of two clutches during the transient mode switching process,thereby substantially elevating control complexity.This study focuses on power split HEVs that integrate multi-clutch mechanisms and investigates how different clutch collaboration manners impact the characteristics of transient mode switching.The powertrain model for the power-split HEV is established utilizing matrix-based methodologies.Through the formulation of clutch torque curves and clutch collaboration models,this research systematically explores the effects of clutch engagement timing and the duration of clutch slipping state on transient mode switching behaviors.Building upon this analysis,an optimization problem for control parameters pertaining to the two collaborative clutches is formulated.The simulated annealing algorithm is employed to optimize these control parameters.Simulation results demonstrate that the clutch collaboration manners have a great influence on the transient mode switching performance.Compared with the pre-calibrated benchmark and the optimal solution derived by the genetic algorithm,the maximal longitudinal jerk and clutch slipping work during the transient mode switching process is reduced obviously with the optimal control parameters derived by the simulated annealing algorithm.The study provides valuable insights for the dynamic coordinated control of the power-split HEVs featuring complex clutch collaboration mechanisms.