Date of Award
Summer 8-2022
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Computational Modeling & Simulation Engineering
Program/Concentration
Modeling and Simulation
Committee Director
Yuzhong Shen
Committee Member
Rafael Diaz
Committee Member
Jiang Li
Committee Member
Hong Yang
Abstract
Recently the number, variety, and complexity of interconnected systems have been increasing while the resources available to increase resilience of those systems have been decreasing. Therefore, it has become increasingly important to quantify the effects of risks and the resulting disruptions over time as they ripple through networks of systems. This dissertation presents a novel modeling and simulation methodology which quantifies resilience, as impact on performance over time, and risk, as the impact of probabilistic disruptions. This work includes four major contributions over the state-of-the-art which are: (1) cyclic dependencies are captured by separation of performance variables into layers which can have different topologies, (2) temporal dependence is modeled using Bayesian networks to allow for incorporation of evidence-based data over time and produce a dynamic model incorporating risk and resilience behavior over time, (3) a combined approach maps from discrete random variables in the risk network to continuous variables in the system network allowing for the propagation of risk throughout the system, and (4) a decomposable architecture allows various components to be represented at different level of detail and overall system reconfiguration to be explored. Applications are provided in supply chain analysis and port logistics to demonstrate the performance and effectiveness of the methodology.
Rights
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
DOI
10.25777/2pfb-yz37
ISBN
9798352694725
Recommended Citation
Smith, Katherine L..
"Adaptive Risk Network Dependency Analysis of Complex Hierarchical Systems"
(2022). Doctor of Philosophy (PhD), Dissertation, Computational Modeling & Simulation Engineering, Old Dominion University, DOI: 10.25777/2pfb-yz37
https://digitalcommons.odu.edu/msve_etds/69
ORCID
0000-0002-5026-4501
Included in
Artificial Intelligence and Robotics Commons, Computer Engineering Commons, Risk Analysis Commons, Systems Science Commons