4.5 Article

Safety assessment: predicting fatality rates in methanol plant incidents

期刊

HELIYON
卷 8, 期 11, 页码 -

出版社

CELL PRESS
DOI: 10.1016/j.heliyon.2022.e11610

关键词

Methanol plant incidents; Fatality rate prediction; ANFIS

资金

  1. School of Chemical Engineering, College of Engineering, Universiti Teknologi MARA (UiTM), Ministry of Higher Education, Malaysia [Ministry of Higher Education (MOHE) [600-RMC/FRGS 5/3 (168/2021, 600-RMC/SRC/5/3 (010/2020)]
  2. Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia [IFKSURG-476]

向作者/读者索取更多资源

This article studied the prediction of fatality accident rate at a methanol plant using different assessment methods. The methods were performed and simulated using HYSYS, ALOHA, MARPLOT, and MATLAB software. The study aimed to highlight the accuracy of the fatality rate prediction by using the ANFIS method, which was found to be a simpler and alternative prediction method compared to the conventional consequence method.
In this article, the prediction of fatality accident rate at methanol (MeOH) plant was studied using different assessment methods. The prediction method was performed and simulated using HYSYS, ALOHA, MARPLOT, and MATLAB software. Recent studies for pressure variation up to 442 bar in MeOH synthesis by carbon dioxide (CO2) hydrogenation showed that three times more MeOH was produced than in conventional plants, with 90% CO2 conversion and 95% MeOH selectivity. However, safety concerns were noted when MeOH production was operated at pressures above 76-500 bar. Therefore, a safety assessment of the pressures between 76 and 500 bar was performed to predict the fatality rate at the MeOH plant. Adaptive Neuro-Fuzzy Inference System (ANFIS) was compared with a conventional analysis by using the consequence method to predict the fatality rate. First, 26 input parameters were simulated in HYSYS, ALOHA, and MARPLOT software by using the consequence method. Then, the input parameters were reduced to six, namely, pressure, mass, volume, leakage size, wind speed, and wind direction, for prediction using ANFIS tool in MATLAB. This study aimed to highlight the accuracy of the fatality rate prediction by using the ANFIS method. In this manner, accurate prediction of fatality rate for MeOH plant incidents was achieved. The prediction values for the ANFIS method was validated using the standard error of the regression. The percent error measurement obtained the lowest regression of 0.0088 and the lowest percent error of 0.02% for Hydrogen (H-2) Vapor Cloud Explosion (VCE) ident. Therefore, the ANFIS method was found to be a simpler and alternative prediction method for the fatality rate than the conventional consequence method.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据