System-of-Systems Resilience Analysis and Design Using Bayesian and Dynamic Bayesian Networks

被引:0
|
作者
Jiao, Tianci [1 ]
Yuan, Hao [2 ]
Wang, Jing [1 ]
Ma, Jun [1 ]
Li, Xiaoling [1 ]
Luo, Aimin [2 ]
机构
[1] Natl Univ Def Technol, Coll Comp, Changsha 410075, Peoples R China
[2] Natl Univ Def Technol, Coll Syst Engn, Changsha 410075, Peoples R China
基金
中国国家自然科学基金;
关键词
resilience analysis; resilience design; Bayesian Networks; Dynamic Bayesian Networks; budget allocation; 90-10; SEISMIC RESILIENCE; HIERARCHY; FRAMEWORK;
D O I
10.3390/math12162510
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
A System-of-Systems (SoS) is characterized both by independence and by inter-dependency. This inter-dependency, while allowing an SoS to achieve its objectives, also means that failures can cascade throughout the SoS. An SoS needs to be resilient to deal with the impact of complex internal and external environments. In this paper, we propose a resilience analysis method of an SoS based on a hierarchy structure. Firstly, we establish a hierarchy structure, which is ranked from high to low as capability level, activity level and system level. Then, Bayesian Networks (BNs) and Dynamic Bayesian Networks (DBNs) are used to analyze the resilience of the SoS. A resilience-based system importance metric is introduced, which is used in the budget allocation optimization problem during the development domain of an SoS. This paper proposes a mathematical programming model aimed at optimizing SoS resilience by optimally using budget to the subsystem. The application of the proposed approach is demonstrated using a case study: a Next Generation Air Transportation setting. The study results provide evidence that the proposed inter-dependency analysis based on Bayesian theory and the SoS resilience design approach can assist SoS system engineers in increasing expected SoS resilience during the development domain.
引用
收藏
页数:22
相关论文
共 50 条
  • [1] Predictive Resilience Analysis of Complex Systems Using Dynamic Bayesian Networks
    Yodo, Nita
    Wang, Pingfeng
    Zhou, Zhi
    [J]. IEEE TRANSACTIONS ON RELIABILITY, 2017, 66 (03) : 761 - 770
  • [2] Probabilistic framework to evaluate the resilience of engineering systems using Bayesian and dynamic Bayesian networks
    Kammouh, Omar
    Gardoni, Paolo
    Cimellaro, Gian Paolo
    [J]. RELIABILITY ENGINEERING & SYSTEM SAFETY, 2020, 198
  • [3] RESILIENCE MODELING AND QUANTIFICATION FOR DESIGN OF COMPLEX ENGINEERED SYSTEMS USING BAYESIAN NETWORKS
    Hosseini, Seyedmohsen
    Yodo, Nita
    Wang, Pingfeng
    [J]. PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, 2014, VOL 2A, 2014,
  • [4] Resilience Modeling and Quantification for Engineered Systems Using Bayesian Networks
    Yodo, Nita
    Wang, Pingfeng
    [J]. JOURNAL OF MECHANICAL DESIGN, 2016, 138 (03)
  • [5] The Adaptive Seismic Resilience of Infrastructure Systems: A Bayesian Networks Analysis
    Tang, Hui
    Zhong, Qingping
    Chen, Chuan
    Martek, Igor
    [J]. SYSTEMS, 2023, 11 (02):
  • [6] Development Interdependency Modeling for System-of-Systems (SoS) using Bayesian Networks: SoS Management Strategy Planning
    Han, Seung Yeob
    DeLaurentis, Daniel
    [J]. 2013 CONFERENCE ON SYSTEMS ENGINEERING RESEARCH, 2013, 16 : 698 - 707
  • [7] Resilience assessment of process industry facilities using dynamic Bayesian networks
    Tong, Qi
    Gernay, Thomas
    [J]. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION, 2023, 169 : 547 - 563
  • [8] Quantifying resilience of socio-ecological systems through dynamic Bayesian networks
    Franco-Gaviria, Felipe
    Amador-Jimenez, Monica
    Millner, Naomi
    Durden, Charlotte
    Urrego, Dunia H.
    [J]. FRONTIERS IN FORESTS AND GLOBAL CHANGE, 2022, 5
  • [9] Dynamic availability analysis using dynamic Bayesian and evidential networks
    Bougofa, Mohammed
    Taleb-Berrouane, Mohammed
    Bouafia, Abderraouf
    Baziz, Amin
    Kharzi, Rabeh
    Bellaouar, Ahmed
    [J]. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION, 2021, 153 (153) : 486 - 499
  • [10] Gait Type Analysis Using Dynamic Bayesian Networks
    Kozlow, Patrick
    Abid, Noor
    Yanushkevich, Svetlana
    [J]. SENSORS, 2018, 18 (10)