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Systems Dynamics Applied to the Analysis of Risk at an Industrial Installation

  • Emmanuel Garbolino
  • Jean-Pierre Chéry
  • Franck Guarnieri
Chapter
Part of the Advanced Sciences and Technologies for Security Applications book series (ASTSA)

Abstract

This chapter presents a framework for the implementation of the dynamic modelling of systems to support risk management at an industrial facility. This approach, implemented using the STELLA® software package, provides the decision maker with a way to model a system and simulate its behaviour over time. It takes a dynamic approach to the analysis of industrial risks, based on four complementary stages that facilitate detailed analyses and the continuous improvement of risk management (Fig. 2.1):
  • Design of the dynamic model and simulation of system behaviour: This stage involves: identifying the variables that describe the state of continuously interacting system components; defining hypotheses that establish the interactions with a view to formalizing the proposed system; developing a model of causal relationships between variables; formulating these relationships as differential equations; and implementing them in software (Forrester 1961; Donnadieu and Karsky 2002).

  • Comprehensive failure analysis: This stage uses a classical risk analysis method, HAZOP (Andrews and Moss 2002). This method is used to try to identify all potential failures. Using the dynamic model, potential changes in the system’s behaviour can be analysed.

  • Comprehensive simulation of the consequences of failures: This stage uses the PHAST® software package (see the DNV website) to simulate hazardous phenomena (toxic emissions, overpressure, thermal flows, etc.) and assess their potential consequences.

  • Testing of prevention and protection methods: This stage consists of assessing the effectiveness of prevention, protection and backup measures. It makes it possible to define new measures, if necessary. The model can then be re-developed based on the assumption that the identified prevention and protection measures have been implemented (Garbolino et al. 2009).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Emmanuel Garbolino
    • 1
  • Jean-Pierre Chéry
    • 2
  • Franck Guarnieri
    • 1
  1. 1.MINES ParisTech/PSL Research University, CRCSophia Antipolis CedexFrance
  2. 2.AgroParisTechMontpellierFrance

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