DAMS: A Model to Assess Domino Effects by Using Agent-Based Modeling and Simulation
Authored by Laobing Zhang, Gabriele Landucci, Genserik Reniers, Nima Khakzad, Jianfeng Zhou
Date Published: 2018
DOI: 10.1111/risa.12955
Sponsors:
Chinese National Natural Science Foundation
Platforms:
AnyLogic
Model Documentation:
Other Narrative
Flow charts
Model Code URLs:
Model code not found
Abstract
Historical data analysis shows that escalation accidents, so-called
domino effects, have an important role in disastrous accidents in the
chemical and process industries. In this study, an agent-based modeling
and simulation approach is proposed to study the propagation of domino
effects in the chemical and process industries. Different from the
analytical or Monte Carlo simulation approaches, which normally study
the domino effect at probabilistic network levels, the agent-based
modeling technique explains the domino effects from a bottom-up
perspective. In this approach, the installations involved in a domino
effect are modeled as agents whereas the interactions among the
installations (e.g., by means of heat radiation) are modeled via the
basic rules of the agents. Application of the developed model to several
case studies demonstrates the ability of the model not only in modeling
higher-level domino effects and synergistic effects but also in
accounting for temporal dependencies. The model can readily be applied
to large-scale complicated cases.
Tags
Agent-based modeling
vulnerability
networks
Computational experiments
Prevention
Hazard
Quantitative assessment
Domino effect
Major
accident hazard
User-friendly software
Process plants
Fragment projection