8th International Symposium on Reliability Engineering and Risk Management最新文献_第10页

Classification of power spectra from data sets with high spectral variance for reliability, analysis of dynamic structures 从高频谱方差数据集中进行功率谱分类，用于可靠性，动态结构分析

8th International Symposium on Reliability Engineering and Risk Management Pub Date : 1900-01-01 DOI: 10.3850/978-981-18-5184-1_ms-11-160-cd

Marco Behrendt, M. Kitahara, T. Kitahara, Liam A. Comerford, M. Beer

引用次数: 0

Full Probabilistic Analysis with FEM for the Retaining Wall of a Deep Excavation 某深基坑挡土墙有限元全概率分析

8th International Symposium on Reliability Engineering and Risk Management Pub Date : 1900-01-01 DOI: 10.3850/978-981-18-5184-1_ms-13-104-cd

A. Ene, T. Schweckendiek, H. Popa

引用次数: 0

Time-variant reliability analysis for high-dimensional nonlinear systems under non-white excitation based on the globally-evolving-based generalized density evolution equation 基于全局演化广义密度演化方程的非白色激励下高维非线性系统时变可靠度分析

8th International Symposium on Reliability Engineering and Risk Management Pub Date : 1900-01-01 DOI: 10.3850/978-981-18-5184-1_ms-01-212-cd

Meng-Ze Lyu, Jian-Bing Chen

引用次数: 0

Development of a Framework for Implementing Asset Register Solutions 开发实施资产登记解决方案的框架

8th International Symposium on Reliability Engineering and Risk Management Pub Date : 1900-01-01 DOI: 10.3850/978-981-18-5184-1_ms-17-010-cd

L. English, A. Yunusa‐Kaltungo

引用次数: 0

Probabilistic Foundation Settlement using A Hardening Soil Model on Layered and Spatially Variable Soil 基于硬化土模型的层状空间变土概率地基沉降

8th International Symposium on Reliability Engineering and Risk Management Pub Date : 1900-01-01 DOI: 10.3850/978-981-18-5184-1_ms-13-189-cd

Teshager D.K., Chwała M., P. W.

引用次数: 0

Resilience Assessment of Road Network Subjected to Ground Motion and Tsunami Caused by the, Earthquake Along the Japan Trench 日本海沟沿线地震引起的地面运动和海啸对道路网的恢复力评价

8th International Symposium on Reliability Engineering and Risk Management Pub Date : 1900-01-01 DOI: 10.3850/978-981-18-5184-1_ms-11-115-cd

H. Ishibashi, M. Akiyama, S. Koshimura

{"title":"Resilience Assessment of Road Network Subjected to Ground Motion and Tsunami Caused by the, Earthquake Along the Japan Trench","authors":"H. Ishibashi, M. Akiyama, S. Koshimura","doi":"10.3850/978-981-18-5184-1_ms-11-115-cd","DOIUrl":"https://doi.org/10.3850/978-981-18-5184-1_ms-11-115-cd","url":null,"abstract":"The countermeasures against the megathrust earthquake along the Japan Trench (Japan Trench earthquake), where the 2011 Great East Japan earthquake occurred, should be taken to enhance the disaster resilience in Japan. In this paper, the resilience of a road network subjected to both seismic and tsunami impacts due to the anticipated Japan Trench earthquake is estimated. The seismic and tsunami fragility curves of a road are developed empirically using the damage data observed in the 2011 Great East Japan earthquake. The effects of seismic damage prior to tsunami attack are considered when estimating tsunami fragility curves. The failure probability of individual routes in a road network is calculated based on the developed fragility curves and the hazard intensity of the anticipated Japan Trench earthquake. The resilience is defined as post-disaster traffic-carrying capacity and assessed for each route in a road network based on the failure probability. Finally, the routes which can be used after the earthquake are discussed based on the resilience.","PeriodicalId":106132,"journal":{"name":"8th International Symposium on Reliability Engineering and Risk Management","volume":"197 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121147906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-Hazard Power Resilience Modelling using Synthetically Generated Distribution Networks 基于综合发电配电网的多灾种电力弹性模型

8th International Symposium on Reliability Engineering and Risk Management Pub Date : 1900-01-01 DOI: 10.3850/978-981-18-5184-1_ms-19-088-cd

C. Zhai, J. P. S. Chhabra, Y. Kim, S. Guikema, S. Patel

引用次数: 0

An effective method for load and resistance factors design based on third-moment transformation 基于三阶矩变换的载荷和阻力系数设计的有效方法

8th International Symposium on Reliability Engineering and Risk Management Pub Date : 1900-01-01 DOI: 10.3850/978-981-18-5184-1_ms-05-009-cd

P.-P. Li, Zhaohua Lu, Y.-G. Zhao

{"title":"An effective method for load and resistance factors design based on third-moment transformation","authors":"P.-P. Li, Zhaohua Lu, Y.-G. Zhao","doi":"10.3850/978-981-18-5184-1_ms-05-009-cd","DOIUrl":"https://doi.org/10.3850/978-981-18-5184-1_ms-05-009-cd","url":null,"abstract":"Load and resistance factor design (LRFD) is a suitable format for the reliability-based limit state design of structures. It has been adopted in many countries, such as the United States, Europe, Canada, and Japan. Usually, the first-order reliability method (FORM) is used to estimate the load and resistance factors, but it requires the determination of design points and complicated double iterative computations. Therefore, FORM is not easy or practical for engineers to use. This paper presents a simple, accurate method to determine the load and resistance factors utilizing the three-moment transformation, which does not require derivative-based iterations and can estimate the load and resistance factors without using the distribution of random variables. In addition, the proposed method provides enough accurate results within a wide range of target reliability indices. Therefore, this method should be effective and convenient for determining the load and resistance factors in actual practice. Three numerical examples illustrate the proposed method's efficiency and accuracy; FORM provides a benchmark for comparison.","PeriodicalId":106132,"journal":{"name":"8th International Symposium on Reliability Engineering and Risk Management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129513056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development and Application of A Cyber-Physical System Resilience Assessment Framework 网络物理系统弹性评估框架的开发与应用

8th International Symposium on Reliability Engineering and Risk Management Pub Date : 1900-01-01 DOI: 10.3850/978-981-18-5184-1_ms-23-190-cd

B. Cassottana, G. Sansavini

{"title":"Development and Application of A Cyber-Physical System Resilience Assessment Framework","authors":"B. Cassottana, G. Sansavini","doi":"10.3850/978-981-18-5184-1_ms-23-190-cd","DOIUrl":"https://doi.org/10.3850/978-981-18-5184-1_ms-23-190-cd","url":null,"abstract":"Automation and digitization trends have caused Cyber-Physical Systems (CPSs) to be deployed at an extremely fast rate. Due to the complexity and the heterogeneity of their components, CPSs face significant challenges to their security and protection. In recent years, several studies have been published to ensure the cyber-security of these systems. However, they adopt a qualitative approach or do not consider the post-disruption system recovery. In order to fill these gaps, we propose a resilience assessment framework for CPSs. The framework addresses the problem of cyber-security from a resilience perspective by providing quantitative methods for the assessment of known threats and the identification of currently unknown threats with large impact. The framework integrates the analysis of the recovery phase following a disruption and proposes a standardized workflow to assess the resilience of CPSs before and after the occurrence of a disruption. The framework develops around three phases, namely (1) modeling the CPS, (2) identifying disruption scenarios that may cause damage to the CPS, and (3) assessing the effects of resilience strategies. The application of the proposed framework is exemplified with reference to a power substation and associated communication network. The application does not strive to be exhaustive, rather, it guides the deployment of resilience assessment tools tailored to specific CPSs. Remarkably, the proposed framework supports resilience decision-making by quantifying the effects of the implementation of resilience strategies.","PeriodicalId":106132,"journal":{"name":"8th International Symposium on Reliability Engineering and Risk Management","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129516933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Active learning for system reliability analysis using PC-Kriging, subset simulation and sensitivity analysis 基于PC-Kriging、子集仿真和灵敏度分析的主动学习系统可靠性分析

8th International Symposium on Reliability Engineering and Risk Management Pub Date : 1900-01-01 DOI: 10.3850/978-981-18-5184-1_ms-16-193-cd

Pietro Parisi, M. Moustapha, S. Marelli, B. Sudret

{"title":"Active learning for system reliability analysis using PC-Kriging, subset simulation and sensitivity analysis","authors":"Pietro Parisi, M. Moustapha, S. Marelli, B. Sudret","doi":"10.3850/978-981-18-5184-1_ms-16-193-cd","DOIUrl":"https://doi.org/10.3850/978-981-18-5184-1_ms-16-193-cd","url":null,"abstract":"Structural reliability analysis aims at assessing the safety of structures which often operate under uncertain conditions. Approximation-, simulation- or surrogate-based methods are used in this context to estimate the failure probability. Surrogate-based methods are the least computationally intensive and consist in building a cheaper proxy of the original limit-state function, which is calibrated using a limited set of samples known as the experimental design. The latter is sequentially enriched to increase the accuracy of the surrogate in areas of interest, hence allowing for an accurate estimation of the failure probability. A large number of such techniques has been recently developed in the literature ( e.g. , active Kriging - Monte Carlo simulation). However most of these techniques consider a single limit-state function. These methods lose efficiency when used to solve system reliability problems, where failure is defined by a non-trivial combination of multiple limit-states. This is due to some peculiarities of the system problem such as the presence of disjoint failure domains or the uneven contribution of each limit-state to the overall failure. In this work, we propose an efficient algorithm combining Kriging/PC-Kriging and subset simulation to solve system reliability problems in their most general setting, i.e., with an arbitrary combination of components. We devise a new learning function which first identifies candidate samples and then selects for enrichment the specific limit-state that contributes the most to system failure. The algorithm is validated on a set of analytical functions and compared with existing methods in the literature.","PeriodicalId":106132,"journal":{"name":"8th International Symposium on Reliability Engineering and Risk Management","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121705106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0