{"title":"复杂系统功能模型的广泛弹性分析","authors":"Yann Guillouët, Oliver Keszöcze, F. S. Torres","doi":"10.1109/RWS52686.2021.9611802","DOIUrl":null,"url":null,"abstract":"The knowledge about the responses to hazardous events is of importance throughout the whole life cycle of a complex system, regardless whether during design or operation phases. These responses also allow to draw conclusions about the resilience of the system. Consequently, there is a need for an extensive consideration of all possible hazardous events a system can be exposed to. This work presents a method for determining the hazards with the most critical system response in terms of resilience. Therefore, we introduce a method for modeling failure propagation under consideration of dynamic behavior in function models. This method is then extended for assessing resilience for random hazard scenarios. Finally, we propose two solutions for determining the most critical hazard scenarios, and thus, provide a base for improvements of the system.","PeriodicalId":294639,"journal":{"name":"2021 Resilience Week (RWS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Extensive resilience analysis of function models of complex systems\",\"authors\":\"Yann Guillouët, Oliver Keszöcze, F. S. Torres\",\"doi\":\"10.1109/RWS52686.2021.9611802\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The knowledge about the responses to hazardous events is of importance throughout the whole life cycle of a complex system, regardless whether during design or operation phases. These responses also allow to draw conclusions about the resilience of the system. Consequently, there is a need for an extensive consideration of all possible hazardous events a system can be exposed to. This work presents a method for determining the hazards with the most critical system response in terms of resilience. Therefore, we introduce a method for modeling failure propagation under consideration of dynamic behavior in function models. This method is then extended for assessing resilience for random hazard scenarios. Finally, we propose two solutions for determining the most critical hazard scenarios, and thus, provide a base for improvements of the system.\",\"PeriodicalId\":294639,\"journal\":{\"name\":\"2021 Resilience Week (RWS)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Resilience Week (RWS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RWS52686.2021.9611802\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Resilience Week (RWS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RWS52686.2021.9611802","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extensive resilience analysis of function models of complex systems
The knowledge about the responses to hazardous events is of importance throughout the whole life cycle of a complex system, regardless whether during design or operation phases. These responses also allow to draw conclusions about the resilience of the system. Consequently, there is a need for an extensive consideration of all possible hazardous events a system can be exposed to. This work presents a method for determining the hazards with the most critical system response in terms of resilience. Therefore, we introduce a method for modeling failure propagation under consideration of dynamic behavior in function models. This method is then extended for assessing resilience for random hazard scenarios. Finally, we propose two solutions for determining the most critical hazard scenarios, and thus, provide a base for improvements of the system.