A non-linear risk assessment method for chemical clusters based on fuzzy measure and Choquet integral. (July 2022)
- Record Type:
- Journal Article
- Title:
- A non-linear risk assessment method for chemical clusters based on fuzzy measure and Choquet integral. (July 2022)
- Main Title:
- A non-linear risk assessment method for chemical clusters based on fuzzy measure and Choquet integral
- Authors:
- He, Zhichao
Fu, Ming
Weng, Wenguo - Abstract:
- Abstract: The risk assessment of chemical clusters faces two challenges. First, the synergistic effects in chemical accidents introduce nonlinearity into the risk. The second challenge is the lack of cooperation and information exchange. A novel method for risk assessment in chemical clusters with the application of a Choquet integral and a multiple linear regression model, is proposed to overcome the challenges in this paper. This method is intended to achieve non-linear risk assessment and determine the distribution of individual risk in chemical clusters without significantly increasing the investment in cooperation and communication between companies. The application of the fuzzy measure and the Choquet integral enables the consideration of the synergistic effects. To evaluate the effectiveness of the method, a cluster of gas stations in Hefei, China, was used as a case study. The risk in chemical clusters was found to increase due to the domino and synergistic effects. The lack of cooperation and information exchange in such clusters leads to the disregard of the domino and synergistic effects and the underestimation of the risk. The new risk assessment method can provide guidance for the process safety, accident prevention, and land-use planning in chemical clusters. Graphical abstract: Image 1 Highlights: A new quantitative risk assessment method is proposed for chemical clusters. Choquet integral and multiple linear regression model are the basis of the method.Abstract: The risk assessment of chemical clusters faces two challenges. First, the synergistic effects in chemical accidents introduce nonlinearity into the risk. The second challenge is the lack of cooperation and information exchange. A novel method for risk assessment in chemical clusters with the application of a Choquet integral and a multiple linear regression model, is proposed to overcome the challenges in this paper. This method is intended to achieve non-linear risk assessment and determine the distribution of individual risk in chemical clusters without significantly increasing the investment in cooperation and communication between companies. The application of the fuzzy measure and the Choquet integral enables the consideration of the synergistic effects. To evaluate the effectiveness of the method, a cluster of gas stations in Hefei, China, was used as a case study. The risk in chemical clusters was found to increase due to the domino and synergistic effects. The lack of cooperation and information exchange in such clusters leads to the disregard of the domino and synergistic effects and the underestimation of the risk. The new risk assessment method can provide guidance for the process safety, accident prevention, and land-use planning in chemical clusters. Graphical abstract: Image 1 Highlights: A new quantitative risk assessment method is proposed for chemical clusters. Choquet integral and multiple linear regression model are the basis of the method. Synergistic effects in accidents are subjectively considered by the fuzzy measure. The method can non-linearly assess the risk with low demand on information exchange. A case study using the method shows the impact of the domino and synergistic effects. … (more)
- Is Part Of:
- Journal of loss prevention in the process industries. Volume 77(2022)
- Journal:
- Journal of loss prevention in the process industries
- Issue:
- Volume 77(2022)
- Issue Display:
- Volume 77, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 77
- Issue:
- 2022
- Issue Sort Value:
- 2022-0077-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-07
- Subjects:
- Chemical process industry -- Synergistic effect -- Multiple linear regression -- Choquet integral
Chemical industries -- Safety measures -- Periodicals
660.2804 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09504230/ ↗
http://www.journals.elsevier.com/journal-of-loss-prevention-in-the-process-industries/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jlp.2022.104778 ↗
- Languages:
- English
- ISSNs:
- 0950-4230
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5010.562000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21756.xml