Quantitative risk assessment integrated with dynamic process simulation for reactor section in heavy oil desulfurization process

Authors
Ko, ChangjunLee, HodongKim, KyeongsuLee, Won Bo
Issue Date
2020-07
Publisher
ELSEVIER SCI LTD
Citation
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES, v.66
Abstract
A new methodology for quantitative risk assessment (QRA) integrated with dynamic simulation and accident simulation is proposed. The objective of this study is to discover inherent risks that are undetectable by conventional risk analysis methods based on steady-state conditions. The target process is the reactor section in the heavy oil desulfurization (HOD) process, which is likely to pose vast potential risks due to the high operating conditions of pressure and temperature. First, a dynamic simulation of a shut-down procedure was performed to observe the behavior of process variables using Aspen HYSYS V10, which is a commercially available process software. Based on the results of the dynamic simulation, several blind spots indicating a higher operating pressure than that in the steady-state simulation were identified. To assess the risks of the detected blind spots, a QRA was performed using the commercial software of SAFETI V8.22, which performs risk calculation based on consequence and frequency data. As a result of applying the proposed method to the HOD process, the risk assessment outcome was identified as intolerably risky unlike that of steady-state conditions, thereby indicating that dynamic simulations can serve as a method to spot inherent risks that are undetectable in steady-state conditions. In addition, mitigation procedures that reduce the risk of the process to a tolerable level are performed, thereby enabling a safer and more reliable process.
Keywords
HAZOP; DESIGN; QRA; Heavy oil desulfurization; Dynamic simulation; Quantitative risk assessment; Blind spots; Inherent risk
ISSN
0950-4230
URI
https://pubs.kist.re.kr/handle/201004/118415
DOI
10.1016/j.jlp.2020.104158
Appears in Collections:
KIST Article > 2020
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