The rapid expansion of enterprises makes product collaborative design （PCD） a critical issue under the distributed heterogeneous environment, but as the collaborative task of large-scale network becomes more complic...The rapid expansion of enterprises makes product collaborative design （PCD） a critical issue under the distributed heterogeneous environment, but as the collaborative task of large-scale network becomes more complicated, neither unified task decomposition and allocation methodology nor Agent-based network management platform can satisfy the increasing demands. In this paper, to meet requirements of PCD for distributed product development, a collaborative design mechanism based on the thought of modularity and the Agent technology is presented. First, the top-down 4-tier process model based on task-oriented modular and Agent is constructed for PCD after analyzing the mapping relationships between requirements and functions in the collaborative design. Second, on basis of sub-task decomposition for PCD based on a mixed method, the mathematic model of task-oriented modular based on multi-objective optimization is established to maximize the module cohesion degree and minimize the module coupling degree, while considering the module executable degree as a restriction. The mathematic model is optimized and simulated by the modified PSO, and the decomposed modules are obtained. Finally, the Agent structure model for collaborative design is put forward, and the optimism matching Agents are selected by using similarity algorithm to implement different task-modules by the integrated reasoning and decision-making mechanism with the behavioral model of collaborative design Agents. With the results of experimental studies for automobile collaborative design, the feasibility and efficiency of this methodology of task-oriented modular and Agent-based collaborative design in the distributed heterogeneous environment are verified. On this basis, an integrative automobile collaborative R＆D platform is developed. This research provides an effective platform for automobile manufacturing enterprises to achieve PCD, and helps to promote product numeralization collaborative R＆D and management development.展开更多
Mobile Edge Computing(MEC)is a promising technology that provides on-demand computing and efficient storage services as close to end users as possible.In an MEC environment,servers are deployed closer to mobile termin...Mobile Edge Computing(MEC)is a promising technology that provides on-demand computing and efficient storage services as close to end users as possible.In an MEC environment,servers are deployed closer to mobile terminals to exploit storage infrastructure,improve content delivery efficiency,and enhance user experience.However,due to the limited capacity of edge servers,it remains a significant challenge to meet the changing,time-varying,and customized needs for highly diversified content of users.Recently,techniques for caching content at the edge are becoming popular for addressing the above challenges.It is capable of filling the communication gap between the users and content providers while relieving pressure on remote cloud servers.However,existing static caching strategies are still inefficient in handling the dynamics of the time-varying popularity of content and meeting users’demands for highly diversified entity data.To address this challenge,we introduce a novel method for content caching over MEC,i.e.,PRIME.It synthesizes a content popularity prediction model,which takes users’stay time and their request traces as inputs,and a deep reinforcement learning model for yielding dynamic caching schedules.Experimental results demonstrate that PRIME,when tested upon the MovieLens 1M dataset for user request patterns and the Shanghai Telecom dataset for user mobility,outperforms its peers in terms of cache hit rates,transmission latency,and system cost.展开更多
Based on multidisciplinary design optimization（MDO）,a new design method is put forward for hydraulic shift mechanism of heavy-duty vehicle automated manual transmission（AMT）.Taking a shift cylinder for example,the...Based on multidisciplinary design optimization（MDO）,a new design method is put forward for hydraulic shift mechanism of heavy-duty vehicle automated manual transmission（AMT）.Taking a shift cylinder for example,the collaborative optimization（CO）method for the design problem of a cylinder is devided into one system level design optimization problem and three subsystem level design optimization problems.The system level is an economic model and the subsystem level is mechanics,kinetics,and a reliability model.Application of the multidisciplinary design optimization software iSIGHT modeling and solving,optimal solution of the shifting cylinder CO model is obtained.According to the optimal solution,oil cylinders are machined out and installed on the gearbox of an AMT system for the bench cycle shift test.The results show that the output force and action speed of the optimized mechanism can meet requirements very well.In addition,the optimized mechanism has a better performance compared to the structure of the traditional design method,which indicates that the CO method can optimize the design of hydraulic transmission.展开更多
In view of the buckling failure caused by large deformation of Mesozoic soft rock roadway in Shajihai mining area, such as serious roof fall, rib spalling, floor heave, etc., based on the detail site investigation,the...In view of the buckling failure caused by large deformation of Mesozoic soft rock roadway in Shajihai mining area, such as serious roof fall, rib spalling, floor heave, etc., based on the detail site investigation,theoretical analysis, mineral composition test, microstructure test, water-physical property test and field experiments were carried out. And we revealed the compound failure mechanism of Mesozoic soft rock roadway in Shajihai mining area, namely the molecule expansion-shear slip of weak structural plane-construction disturbance. On this basis, the coupling support technology whose core is constant resistance with large deformation bolt was proposed. The feature of this supporting technology is that a new type of structural composite material was used, which makes the supporting system not only has the ideal deformation characteristics, but also has high supporting resistance. Thus the fully release of plastic energy within surrounding rock and reasonable control of the thickness of the plastic ring were realized. Then the differential deformation between the surrounding rock and support was eliminated by the secondary coupling support of bolt–mesh–cable, and the bolt with high strength was applied in the base angle to control floor. Eventually the collaborative bearing system of surrounding rock–support was formed. Through field tests the validity and rationality of support was also verified.展开更多
The development of information technology has propelled technological reform in artificial intelligence(AI).To address the needs of diversified and complex applications,AI has been increasingly trending towards intell...The development of information technology has propelled technological reform in artificial intelligence(AI).To address the needs of diversified and complex applications,AI has been increasingly trending towards intelligent,collaborative,and systematized development across different levels and tasks.Research on intelligent,collaborative and systematized AI can be divided into three levels:micro,meso,and macro.Firstly,the micro-level collaboration is illustrated through the introduction of swarm intelligence collaborative methods related to individuals collaboration and decision variables collaboration.Secondly,the meso-level collaboration is discussed in terms of multi-task collaboration and multi-party collaboration.Thirdly,the macro-level collaboration is primarily in the context of intelligent collaborative systems,such as terrestrial-satellite collaboration,space-air-ground collaboration,space-air-ground-air collaboration,vehicle-road-cloud collaboration and end-edge-cloud collaboration.Finally,this paper provides prospects on the future development of relevant fields from the perspectives of the micro,meso,and macro levels.展开更多
基金Supported by National Science and Technology Major Project of China(Grant No.2009ZX04014-103)PhD Programs Foundation of Ministry of Education of China(Grant No.20100072110038)+1 种基金National Natural Science Foundation of China(Grant Nos.61075064,61034004,61005090)Program for New Century Excellent Talents in University of Ministry of Education of China(Grant No.NECT-10-0633)
文摘The rapid expansion of enterprises makes product collaborative design （PCD） a critical issue under the distributed heterogeneous environment, but as the collaborative task of large-scale network becomes more complicated, neither unified task decomposition and allocation methodology nor Agent-based network management platform can satisfy the increasing demands. In this paper, to meet requirements of PCD for distributed product development, a collaborative design mechanism based on the thought of modularity and the Agent technology is presented. First, the top-down 4-tier process model based on task-oriented modular and Agent is constructed for PCD after analyzing the mapping relationships between requirements and functions in the collaborative design. Second, on basis of sub-task decomposition for PCD based on a mixed method, the mathematic model of task-oriented modular based on multi-objective optimization is established to maximize the module cohesion degree and minimize the module coupling degree, while considering the module executable degree as a restriction. The mathematic model is optimized and simulated by the modified PSO, and the decomposed modules are obtained. Finally, the Agent structure model for collaborative design is put forward, and the optimism matching Agents are selected by using similarity algorithm to implement different task-modules by the integrated reasoning and decision-making mechanism with the behavioral model of collaborative design Agents. With the results of experimental studies for automobile collaborative design, the feasibility and efficiency of this methodology of task-oriented modular and Agent-based collaborative design in the distributed heterogeneous environment are verified. On this basis, an integrative automobile collaborative R＆D platform is developed. This research provides an effective platform for automobile manufacturing enterprises to achieve PCD, and helps to promote product numeralization collaborative R＆D and management development.
文摘Mobile Edge Computing(MEC)is a promising technology that provides on-demand computing and efficient storage services as close to end users as possible.In an MEC environment,servers are deployed closer to mobile terminals to exploit storage infrastructure,improve content delivery efficiency,and enhance user experience.However,due to the limited capacity of edge servers,it remains a significant challenge to meet the changing,time-varying,and customized needs for highly diversified content of users.Recently,techniques for caching content at the edge are becoming popular for addressing the above challenges.It is capable of filling the communication gap between the users and content providers while relieving pressure on remote cloud servers.However,existing static caching strategies are still inefficient in handling the dynamics of the time-varying popularity of content and meeting users’demands for highly diversified entity data.To address this challenge,we introduce a novel method for content caching over MEC,i.e.,PRIME.It synthesizes a content popularity prediction model,which takes users’stay time and their request traces as inputs,and a deep reinforcement learning model for yielding dynamic caching schedules.Experimental results demonstrate that PRIME,when tested upon the MovieLens 1M dataset for user request patterns and the Shanghai Telecom dataset for user mobility,outperforms its peers in terms of cache hit rates,transmission latency,and system cost.
基金Supported by the National High Technology Research and Development Program of China(863 Program)(2011AA11A223)
文摘Based on multidisciplinary design optimization（MDO）,a new design method is put forward for hydraulic shift mechanism of heavy-duty vehicle automated manual transmission（AMT）.Taking a shift cylinder for example,the collaborative optimization（CO）method for the design problem of a cylinder is devided into one system level design optimization problem and three subsystem level design optimization problems.The system level is an economic model and the subsystem level is mechanics,kinetics,and a reliability model.Application of the multidisciplinary design optimization software iSIGHT modeling and solving,optimal solution of the shifting cylinder CO model is obtained.According to the optimal solution,oil cylinders are machined out and installed on the gearbox of an AMT system for the bench cycle shift test.The results show that the output force and action speed of the optimized mechanism can meet requirements very well.In addition,the optimized mechanism has a better performance compared to the structure of the traditional design method,which indicates that the CO method can optimize the design of hydraulic transmission.
基金support by the National Natural Science Foundation of China (Nos. 51374106 and 51434006)
文摘In view of the buckling failure caused by large deformation of Mesozoic soft rock roadway in Shajihai mining area, such as serious roof fall, rib spalling, floor heave, etc., based on the detail site investigation,theoretical analysis, mineral composition test, microstructure test, water-physical property test and field experiments were carried out. And we revealed the compound failure mechanism of Mesozoic soft rock roadway in Shajihai mining area, namely the molecule expansion-shear slip of weak structural plane-construction disturbance. On this basis, the coupling support technology whose core is constant resistance with large deformation bolt was proposed. The feature of this supporting technology is that a new type of structural composite material was used, which makes the supporting system not only has the ideal deformation characteristics, but also has high supporting resistance. Thus the fully release of plastic energy within surrounding rock and reasonable control of the thickness of the plastic ring were realized. Then the differential deformation between the surrounding rock and support was eliminated by the secondary coupling support of bolt–mesh–cable, and the bolt with high strength was applied in the base angle to control floor. Eventually the collaborative bearing system of surrounding rock–support was formed. Through field tests the validity and rationality of support was also verified.
基金supported in part by the National Natural Science Foundation of China(62036006,61906146)in part by the Fundamental Research Funds for the Central Universities.
文摘The development of information technology has propelled technological reform in artificial intelligence(AI).To address the needs of diversified and complex applications,AI has been increasingly trending towards intelligent,collaborative,and systematized development across different levels and tasks.Research on intelligent,collaborative and systematized AI can be divided into three levels:micro,meso,and macro.Firstly,the micro-level collaboration is illustrated through the introduction of swarm intelligence collaborative methods related to individuals collaboration and decision variables collaboration.Secondly,the meso-level collaboration is discussed in terms of multi-task collaboration and multi-party collaboration.Thirdly,the macro-level collaboration is primarily in the context of intelligent collaborative systems,such as terrestrial-satellite collaboration,space-air-ground collaboration,space-air-ground-air collaboration,vehicle-road-cloud collaboration and end-edge-cloud collaboration.Finally,this paper provides prospects on the future development of relevant fields from the perspectives of the micro,meso,and macro levels.
