报告地点：主楼C1-213

报告人1：Carlos Guedes Soares

报告题目：Simulation Methods for Structural Reliability Assessment

报告摘要：The structural reliability methods are presently in a mature state of development and have been used in different fields in the implementation of reliability- and risk-based methodologies for design, maintenance and inspection planning of structural systems. The first- and second-order reliability methods (FORM/SORM) and the Monte Carlo based simulation methods (MCS) are presently two well-established classes of methods that can be used to compute the typically small failure probabilities found in practical engineering applications. The FORM/SORM methods have been widely used and accepted for practical applications due to their efficiency. However, they have known limitations with respect to the accuracy and general applicability to solve complex structural system reliability assessment problems. The MCS methods are nowadays a viable alternative to the FORM/SORM methods due to the presently available computational resources and efficient simulation strategies, making feasible their use in a practical engineering context. Presently, they are recognized as the most versatile and robust methods for structural reliability analysis, which can provide arbitrarily accurate failure probability predictions irrespective of the complexity of the limit states of the structural system. They overcome the limitations of accuracy and general applicability of the FORM/SORM methods and can provide an error estimate for the failure probability predictions. An overview of different MCS methods for structural reliability analysis will be given in this lecture, with focus on classical variance reduction techniques such as the importance sampling and directional simulation and more advanced methods based on asymptotic techniques and subset simulation. A critical qualitative comparison of the different MCS methods will be given. Some application problems in the context of reliability analysis of marine structures will be presented, with focus on problems requiring the use of surrogate models for time-consuming implicit limit states and large structural systems.

报告人简介：Carlos Guedes Soares received the M.S. and Ocean Engineer degrees from the Massachusetts Institute of Technology, USA in 1976, the Ph.D. degree from the Norwegian Institute of Technology, in Trondheim, in 1984, and the Doctor of Science degree from the Technical University of Lisbon, Portugal, in 1991. He is a Professor at the Engineering Faculty (Instituto Superior Tecnico) of the University of Lisbon and the Head of the Centre for Marine Technology and Ocean Engineering (CENTEC), which is a research center of the University of Lisbon that is recognized and funded by the Portuguese Foundation for Science and Technology. He has supervised 35 concluded Phd thesis and 38 Pos-doc Researchers. He has coauthored more than 450 journal papers and has been involved in more than 70 international research projects and 30 national projects. He has received Doctor Honoris Causa degrees from the Technical University of Varna in 2003 and the University “Dunarea de Jos” Galati, in 2004. He has received Awards from the University of Lisbon, the Brazilian Association of Naval Architects and Marine Engineers and the Confederation of European Maritime Technology Societies for the excellence of his work.  He was founding member and has been General Secretary and Chairman of the European Safety and Reliability Association (ESRA), was Chairman of the International Maritime Association of the Mediterranean (IMAM) and is currently Chairman of the International Ship and Offshore Structures Congress (ISSC). He is Editor in Chief of Reliability Engineering and System Safety and member of the Editorial Board of about 15 Journals.

报告人2：Guoliang Huang

报告题目：Adaptive Elastic Metamaterials and Their Novel Applications

报告摘要：Over the past decade, acoustic/elastic metamaterials have attracted a great deal of attention due to their peculiar dynamic properties, including a negative mass density and stiffness, which are not observed in natural materials. One of the greatest challenges in the development of acoustic/elastic metamaterials is how to tune, broaden and optimize their wave performance without requiring microstructural modifications. An adaptive metamaterial through the use of electronically controlled elements is studied to make metamaterials attain tunable properties/functions. Both theoretical and physical realization of adaptive elastic metamaterials are performed to realize controllable effective mass densities and moduli through electromechanical coupling and electric circuit designs. Specifically, we will employ the adaptive meta-composite to perform broadband and adaptive signal amplification functions in addition to being a broadband wave control.

报告人简介：Dr. Guoliang Huang is currently an associate professor, Department of Mechanical and Aerospace Engineering at University of Missouri. He received his Ph.D. degree in Mechanical Engineering from University of Alberta, Canada. He works in the broad area in elastic/acoustic metamaterials, structural dynamics, structural health monitoring, solar cell thin film, bioinspired materials, and micro/nano mechanics. Dr. Huang’s research projects are mainly funded by NSF, Air Force of Scientific Research (AFSOR), NSF EPSCoR and NASA, Department of Energy (DOE), and industries. Dr. Huang has published more than 110 technique papers, including Nature Communication, Journal of Mechanics and Physics Solids, Applied Physics Letters, et al. Recently, he has co-edited a book “Theories and Designs of Acoustic Metamaterials”.

报告人3：Yi-Kuei Lin

报告题目：Spare routing problem with multiple minimal paths for a time-based stochastic flow network

报告摘要：To discuss the system reliability of spare routing for a computer network, a model of time-based stochastic flow network (TBSFN), in which each arc has several possible capacities/states and a lead time, is addressed in this study. The minimum transmission time to send a given amount of data through a single minimal path is uncertain. Although the transmission time will be shortened even if the data are sent through p (p > 1) disjoint minimal paths simultaneously, it is still variable in a TBSFN. This study is concerned with evaluating the probability that a specified amount of data can be sent through p minimal paths simultaneously within a time threshold. Such a probability, named the system reliability, can be treated as a performance index for measuring the transmission ability. An efficient methodology to assess the system reliability is proposed firstly. Furthermore, a spare routing for boosting the system reliability is established in advance to indicate the main and spare p minimal paths. Subsequently, the system reliability of the spare routing can be computed easily, which shows the contribution of the spare design. From the viewpoint of decision making, we may conduct the sensitive analysis to find out the most important arc which will increase/decrease the system reliability most significantly.

报告人简介：Yi Kuei Lin works currently as a Professor of Industrial Management Department at National Taiwan University of Science and Technology, Taiwan. He received the B.S. degree from the Applied Mathematics Department, National Chiao Tung University, Taiwan. He obtained his M.A. and Ph.D. degrees from the Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Taiwan. His research interests include performance evaluation, stochastic network reliability, operations research, and telecommunication management.He has published several papers in journals like European Journal of Operational Research, Computers and Operations Research, Reliability Engineering & System Safety, IEEE Transactions on Reliability, International Journal of Industrial Engineering, Computers and Mathematics with Applications, International Journal of Advanced Manufacturing Technology, IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans, International Journal of Reliability, Quality and Safety Engineering, Journal of the Operations Research Society of Japan, Mathematical and Computer Modeling, Computers and Industrial Engineering, Journal of the Chinese Institute of Engineers, Journal of Quantitative Management, and Journal of Chinese Institute of Industrial Engineers.