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Dynamic risk assessment of a nonlinear non-Gaussian system using a particle filter and detailed consequence analysis

journal contribution
posted on 2023-05-19, 10:36 authored by Zadakbar, O, Faisal KhanFaisal Khan, Imtiaz, S
This paper presents a dynamic risk assessment using a comprehensive economic consequence methodology in combination with a multivariate model-based fault detection method. The proposed approach aims to calculate process risk dynamically at each sampling instant, and also to identify and screen the faults that are not hazardous. The approach relies on a particle filter combined with a comprehensive economic consequence methodology. The fault detection module uses a state space model of the process plant and a particle filter algorithm that calculates the probability of the fault. The output of this module is then combined with the consequence module, which uses loss functions to relate process deviations to economic losses. The consequence module identifies, quantifies, and integrates losses for a given scenario. Combining the two modules for risk assessment makes this approach more reliable in the analysis of realistic nonlinear process systems, and improves decision-making for process design and risk management.

History

Publication title

Canadian Journal of Chemical Engineering

Volume

93

Issue

7

Pagination

1201-1211

ISSN

0008-4034

Department/School

Australian Maritime College

Publisher

Wiley-Blackwell Publishing Ltd.

Place of publication

USA

Rights statement

Copyright 2015 Canadian Society for Chemical Engineering

Repository Status

  • Restricted

Socio-economic Objectives

Expanding knowledge in engineering