Quantitative risk assessment through hybrid causal logic approach

Abstract

In this paper, a hybrid causal logic (HCL) model is improved by mapping a fuzzy fault tree (FFT) into a Bayesian network (BN). The first step is to substitute an FFT for the traditional FT. The FFT is based on the Takagi-Sugeno model and the translation rules needed to convert the FFT into a BN are derived. The proposed model is demonstrated in a study of a fire hazard on an offshore oil production facility. It is clearly shown that the FFT can be directly converted into a BN and that the parameters of the FFT can be estimated more accurately using the basic inference techniques of a BN. The improved HCL approach is able to both accurately determine how failures cause an undesired problem using FFT and also model non-deterministic cause-effect relationships among system elements using the BN.

Quantification of human error probability towards the gas inerting process on-board crude oil tankers

“…The analysis was conducted with respect to the IMO G7 guidelines. Moreover, a hybrid risk analysis approach was introduced by mapping a fuzzy fault tree into a Bayesian network (Wang et al, 2011). In the paper, the authors demonstrated a hybrid approach to a fire hazard in an offshore oil production facility.…”

Methods and models in process safety and risk management: Past, present and future

“…Røed et al (2009) also developed a methodology which combines BN and a method which represents the causal relationship of an accident, named HCL (Hybrid Causal Logic) and validated this with an offshore case study. An improved version of HCL mapping fuzzy fault tree (FFT) into a Bayesian Network (BN) was discussed by Wang et al (2011).…”

Timed Fault Tree Models of the China Yongwen Railway Accident

“…For example, as the smallest time unit is 0.1 seconds in this case, the duration time of B (Wrong localisation initialization) B (10) (Brake system failure)…”

“…These applications include a number of high hazard industries such as nuclear power [9], the oil industry [10], and traffic [2], as well as applications in mechanical engineering [11], [12]. In general, FTA is useful to analyse and predict system reliability and safety [13].…”