变幅载荷作用下的疲劳裂纹扩展情况更能够反映海洋结构物真实的疲劳行为。已有的关于载荷次序问题的研究中,多是考虑在定幅值载荷历程中加入单个或多个超载/低载,或加入块状超载/低载,使变幅载荷序列得到简化。文章则主要研究更接近真...变幅载荷作用下的疲劳裂纹扩展情况更能够反映海洋结构物真实的疲劳行为。已有的关于载荷次序问题的研究中,多是考虑在定幅值载荷历程中加入单个或多个超载/低载,或加入块状超载/低载,使变幅载荷序列得到简化。文章则主要研究更接近真实情况的随机载荷序列,超载、低载随机相互作用下的载荷次序效应对海洋结构疲劳裂纹扩展率的影响。首先介绍了载荷次序效应问题的研究现状和基本结论,总结了考虑载荷次序效应的变幅载荷作用下疲劳裂纹扩展模型,然后简单介绍了文中应用的疲劳寿命预报统一方法 (Unified Fatigue Life Prediction,UFLP)的基本思想,最后给出了随机载荷作用下,应用UFLP法计算海洋结构物疲劳裂纹扩展的示例。展开更多
Marine structures are mostly made of metals and always experience complex random loading during their service periods. The fatigue crack growth behaviors of metal materials have been proved from laboratory tests to be...Marine structures are mostly made of metals and always experience complex random loading during their service periods. The fatigue crack growth behaviors of metal materials have been proved from laboratory tests to be sensitive to the loading sequence encountered. In order to take account of the loading sequence effect, fatigue life prediction should be based on fatigue crack propagation（FCP） theory rather than the currently used cumulative fatigue damage（CFD） theory. A unified fatigue life prediction（UFLP） method for marine structures has been proposed by the authors＇ group. In order to apply the UFLP method for newly designed structures, authorities such as the classification societies should provide a standardized load-time history（SLH） such as the TWIST and FALSTAFF sequences for transport and fighter aircraft. This paper mainly aims at proposing a procedure to generate the SLHs for marine structures based on a short-term loading sample and to provide an illustration on how to use the presented SLH to a typical tubular T-joint in an offshore platform based on the UFLP method.展开更多
The artificial bee colony(ABC)algorithm is an evolutionary optimization algorithm based on swarm intelligence and inspired by the honey bees’food search behavior.Since the ABC algorithm has been developed to achieve ...The artificial bee colony(ABC)algorithm is an evolutionary optimization algorithm based on swarm intelligence and inspired by the honey bees’food search behavior.Since the ABC algorithm has been developed to achieve optimal solutions by searching in the continuous search space,modification is required to apply it to binary optimization problems.In this study,we modify the ABC algorithm to solve binary optimization problems and name it the improved binary ABC(IbinABC).The proposed method consists of an update mechanism based on fitness values and the selection of different decision variables.Therefore,we aim to prevent the ABC algorithm from getting stuck in a local minimum by increasing its exploration ability.We compare the IbinABC algorithm with three variants of the ABC and other meta-heuristic algorithms in the literature.For comparison,we use the well-known OR-Library dataset containing 15 problem instances prepared for the uncapacitated facility location problem.Computational results show that the proposed algorithm is superior to the others in terms of convergence speed and robustness.The source code of the algorithm is available at https://github.com/rafetdurgut/ibinABC.展开更多
The multi-wave algorithm(Glover, 2016)integrates tabu search and strategic oscillation utilizing repeated waves(nested iterations) of constructive search or neighborhood search. We propose a simple multi-wave algorith...The multi-wave algorithm(Glover, 2016)integrates tabu search and strategic oscillation utilizing repeated waves(nested iterations) of constructive search or neighborhood search. We propose a simple multi-wave algorithm for solving the Uncapacitated Facility Location Problem(UFLP) to minimize the combined costs of selecting facilities to be opened and of assigning each customer to an opened facility in order to meet the customers' demands. The objective is to minimize the overall cost including the costs of opening facilities and the costs of allocations. Our experimental tests on a standard set of benchmarks for this widely-studied class of problems show that our algorithm outperforms all previous methods.展开更多
文摘变幅载荷作用下的疲劳裂纹扩展情况更能够反映海洋结构物真实的疲劳行为。已有的关于载荷次序问题的研究中,多是考虑在定幅值载荷历程中加入单个或多个超载/低载,或加入块状超载/低载,使变幅载荷序列得到简化。文章则主要研究更接近真实情况的随机载荷序列,超载、低载随机相互作用下的载荷次序效应对海洋结构疲劳裂纹扩展率的影响。首先介绍了载荷次序效应问题的研究现状和基本结论,总结了考虑载荷次序效应的变幅载荷作用下疲劳裂纹扩展模型,然后简单介绍了文中应用的疲劳寿命预报统一方法 (Unified Fatigue Life Prediction,UFLP)的基本思想,最后给出了随机载荷作用下,应用UFLP法计算海洋结构物疲劳裂纹扩展的示例。
基金financially supported by the Fourth Term of"333 Engineering"Program of Jiangsu Province(Grant No.BRA2011116)Youth Foundation of Jiangsu Province(Grant No.BK2012095)Special Program for Hadal Science and Technology of Shanghai Ocean University(Grant No.HAST-T-2013-01)
文摘Marine structures are mostly made of metals and always experience complex random loading during their service periods. The fatigue crack growth behaviors of metal materials have been proved from laboratory tests to be sensitive to the loading sequence encountered. In order to take account of the loading sequence effect, fatigue life prediction should be based on fatigue crack propagation（FCP） theory rather than the currently used cumulative fatigue damage（CFD） theory. A unified fatigue life prediction（UFLP） method for marine structures has been proposed by the authors＇ group. In order to apply the UFLP method for newly designed structures, authorities such as the classification societies should provide a standardized load-time history（SLH） such as the TWIST and FALSTAFF sequences for transport and fighter aircraft. This paper mainly aims at proposing a procedure to generate the SLHs for marine structures based on a short-term loading sample and to provide an illustration on how to use the presented SLH to a typical tubular T-joint in an offshore platform based on the UFLP method.
文摘The artificial bee colony(ABC)algorithm is an evolutionary optimization algorithm based on swarm intelligence and inspired by the honey bees’food search behavior.Since the ABC algorithm has been developed to achieve optimal solutions by searching in the continuous search space,modification is required to apply it to binary optimization problems.In this study,we modify the ABC algorithm to solve binary optimization problems and name it the improved binary ABC(IbinABC).The proposed method consists of an update mechanism based on fitness values and the selection of different decision variables.Therefore,we aim to prevent the ABC algorithm from getting stuck in a local minimum by increasing its exploration ability.We compare the IbinABC algorithm with three variants of the ABC and other meta-heuristic algorithms in the literature.For comparison,we use the well-known OR-Library dataset containing 15 problem instances prepared for the uncapacitated facility location problem.Computational results show that the proposed algorithm is superior to the others in terms of convergence speed and robustness.The source code of the algorithm is available at https://github.com/rafetdurgut/ibinABC.
基金funded by ELSAT 2020 project,which is cofinanced by the European Union with the European Regional Development Fund,the France state and the Hauts de France Region Council
文摘The multi-wave algorithm(Glover, 2016)integrates tabu search and strategic oscillation utilizing repeated waves(nested iterations) of constructive search or neighborhood search. We propose a simple multi-wave algorithm for solving the Uncapacitated Facility Location Problem(UFLP) to minimize the combined costs of selecting facilities to be opened and of assigning each customer to an opened facility in order to meet the customers' demands. The objective is to minimize the overall cost including the costs of opening facilities and the costs of allocations. Our experimental tests on a standard set of benchmarks for this widely-studied class of problems show that our algorithm outperforms all previous methods.
