Plastic forming is one of enabling and fundamental technologies in advanced manufacturing chains. Design optimization is a critical way to improve the performance of the forming system, exploit the advantages of high ...Plastic forming is one of enabling and fundamental technologies in advanced manufacturing chains. Design optimization is a critical way to improve the performance of the forming system, exploit the advantages of high productivity, high product quality, low production cost and short time to market and develop precise, accurate, green, and intelligent(smart) plastic forming technology. However, plastic forming is quite complicated, relating to multi-physics field coupling,multi-factor influence, multi-defect constraint, and triple nonlinear, etc., and the design optimization for plastic forming involves multi-objective, multi-parameter, multi-constraint, nonlinear,high-dimensionality, non-continuity, time-varying, and uncertainty, etc. Therefore, how to achieve accurate and efficient design optimization of products, equipment, tools/dies, and processing as well as materials characterization has always been the research frontier and focus in the field of engineering and manufacturing. In recent years, with the rapid development of computing science, data science and internet of things(Io T), the theories and technologies of design optimization have attracted more and more attention, and developed rapidly in forming process. Accordingly, this paper first introduced the framework of design optimization for plastic forming. Then, focusing on the key problems of design optimization, such as numerical model and optimization algorithm,this paper summarized the research progress on the development and application of the theories and technologies about design optimization in forming process, including deterministic and uncertain optimization. Moreover, the applicability of various modeling methods and optimization algorithms was elaborated in solving the design optimization problems of plastic forming. Finally, considering the development trends of forming technology, this paper discusses some challenges of design optimization that may need to be solved and faced in forming process.展开更多
The advancements of sensing technologies,including remote sensing,in situ sensing,social sensing,and health sensing,have tremendously improved our capability to observe and record natural and social phenomena,such as ...The advancements of sensing technologies,including remote sensing,in situ sensing,social sensing,and health sensing,have tremendously improved our capability to observe and record natural and social phenomena,such as natural disasters,presidential elections,and infectious diseases.The observations have provided an unprecedented opportunity to better understand and respond to the spatiotemporal dynamics of the environment,urban settings,health and disease propagation,business decisions,and crisis and crime.Spatiotemporal event detection serves as a gateway to enable a better understanding by detecting events that represent the abnormal status of relevant phenomena.This paper reviews the literature for different sensing capabilities,spatiotemporal event extraction methods,and categories of applications for the detected events.The novelty of this review is to revisit the definition and requirements of event detection and to layout the overall workflow(from sensing and event extraction methods to the operations and decision-supporting processes based on the extracted events)as an agenda for future event detection research.Guidance is presented on the current challenges to this research agenda,and future directions are discussed for conducting spatiotemporal event detection in the era of big data,advanced sensing,and artificial intelligence.展开更多
基金the National Natural Science Foundation of China (Nos. 51775441&51835011)the National Science Fund for Excellent Young Scholars (No.51522509)Research Fund of the State Key Laboratory of Solidification Processing (NWPU) of China (KP201608)。
文摘Plastic forming is one of enabling and fundamental technologies in advanced manufacturing chains. Design optimization is a critical way to improve the performance of the forming system, exploit the advantages of high productivity, high product quality, low production cost and short time to market and develop precise, accurate, green, and intelligent(smart) plastic forming technology. However, plastic forming is quite complicated, relating to multi-physics field coupling,multi-factor influence, multi-defect constraint, and triple nonlinear, etc., and the design optimization for plastic forming involves multi-objective, multi-parameter, multi-constraint, nonlinear,high-dimensionality, non-continuity, time-varying, and uncertainty, etc. Therefore, how to achieve accurate and efficient design optimization of products, equipment, tools/dies, and processing as well as materials characterization has always been the research frontier and focus in the field of engineering and manufacturing. In recent years, with the rapid development of computing science, data science and internet of things(Io T), the theories and technologies of design optimization have attracted more and more attention, and developed rapidly in forming process. Accordingly, this paper first introduced the framework of design optimization for plastic forming. Then, focusing on the key problems of design optimization, such as numerical model and optimization algorithm,this paper summarized the research progress on the development and application of the theories and technologies about design optimization in forming process, including deterministic and uncertain optimization. Moreover, the applicability of various modeling methods and optimization algorithms was elaborated in solving the design optimization problems of plastic forming. Finally, considering the development trends of forming technology, this paper discusses some challenges of design optimization that may need to be solved and faced in forming process.
基金supported by NSF[CNS 1841520 and ACI 1835507]NASA Goddard[80NSSC19P2033]the NSF Spatiotemporal I/UCRC IAB members.
文摘The advancements of sensing technologies,including remote sensing,in situ sensing,social sensing,and health sensing,have tremendously improved our capability to observe and record natural and social phenomena,such as natural disasters,presidential elections,and infectious diseases.The observations have provided an unprecedented opportunity to better understand and respond to the spatiotemporal dynamics of the environment,urban settings,health and disease propagation,business decisions,and crisis and crime.Spatiotemporal event detection serves as a gateway to enable a better understanding by detecting events that represent the abnormal status of relevant phenomena.This paper reviews the literature for different sensing capabilities,spatiotemporal event extraction methods,and categories of applications for the detected events.The novelty of this review is to revisit the definition and requirements of event detection and to layout the overall workflow(from sensing and event extraction methods to the operations and decision-supporting processes based on the extracted events)as an agenda for future event detection research.Guidance is presented on the current challenges to this research agenda,and future directions are discussed for conducting spatiotemporal event detection in the era of big data,advanced sensing,and artificial intelligence.
