Quantitative risk assessment integrated with dynamic process simulation for reactor section in heavy oil desulfurization process. (July 2020)

• Record Type: Journal Article
• Authors: Ko, Changjun; Lee, Hodong; Kim, Kyeongsu; Lee, Won Bo
• Is Part Of: Journal of loss prevention in the process industries. Volume 66(2020)
• Publication Date: 2020-07
• Subjects: Heavy oil desulfurization -- Dynamic simulation -- Quantitative risk assessment -- Blind spots -- Inherent risk; Chemical industries -- Safety measures -- Periodicals; 660.2804
• DOI: 10.1016/j.jlp.2020.104158
• Languages: English
• ISSNs: 0950-4230

Abstract

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. Highlights: The QRA integrated with dynamic simulation in chemical processes. Dynamic simulation to detect blind spots w are underestimated risks in steady-state. Accident simulation to assess the risk of updated process conditions in quantitative basis. Discovery of inherent risks and more reliable and trustable process operation.