Impact of inlet boundary number and locations on gas diffusion and flow in a typical chemical industrial park near uneven terrain

2022 ◽  
Author(s):  
Zeya Shen ◽  
Jianlei Lang ◽  
Mengzhen Li ◽  
Shushuai Mao ◽  
Feng Hu ◽  
...  
Keyword(s):  
Gas Diffusion ◽  
Industrial Park ◽  
Uneven Terrain ◽  
Chemical Industrial Park

The Quantitative Assessment of Domino Effects Based on Stochastic Petri Nets

2008 ◽  
Vol 44-46 ◽  
pp. 537-544
Author(s):  
Shi Yi Bao ◽  
Jian Xin Zhu ◽  
Li J. Wang ◽  
Ning Jiang ◽  
Zeng Liang Gao
Keyword(s):  
Petri Nets ◽  
State Space ◽  
Petri Net ◽  
Quantitative Assessment ◽  
Stochastic Petri Nets ◽  
Industrial Park ◽  
Domino Effect ◽  
State Space Explosion ◽  
Stochastic Petri Net ◽  
Chemical Industrial Park

The quantitative analysis of “domino” effects is one of the main aspects of hazard assessment in chemical industrial park. This paper demonstrates the application of heterogeneous stochastic Petri net modeling techniques to the quantitative assessment of the probabilities of domino effects of major accidents in chemical industrial park. First, five events are included in the domino effect models of major accidents: pool fire, explosion, boiling liquid expanding vapour explosion (BLEVE) giving rise to a fragment, jet fire and delayed explosion of a vapour cloud. Then, the domino effect models are converted into Generalized Stochastic Petri net (GSPN) in which the probability of the domino effect is calculated automatically. The Stochastic Petri nets’ models, which are state-space based ones, increase the modeling flexibility but create the state-space explosion problems. Finally, in order to alleviate the state-space explosion problems of GSPN models, this paper employs Stochastic Wellformed Net (SWN), a particular class of High-Level (colored) SPN. To conduct a case study on a chemical industrial park, the probability of domino effects of major accidents is calculated by using the GSPN model and SWN model in this paper.

Study on the Risk Analysis and Emergency Measures to the PX Projects of Dalian Dagushan which Impact on the Marine Environment

2014 ◽  
Vol 675-677 ◽  
pp. 325-328
Author(s):  
Jun Zhang ◽  
Jian Guo Lin ◽  
Han Zhang
Keyword(s):  
Risk Analysis ◽  
Marine Environment ◽  
Chemical Properties ◽  
Industrial Park ◽  
Physical And Chemical Properties ◽  
Environmental Assessments ◽  
Chemical Industrial Park ◽  
Physical And Chemical ◽  
Emergency Measures ◽  
And Chemical Properties

By investigating and analyzing PX demand in recent years and the distribution of PX projects in Dagushan chemical industrial park, combining its physical and chemical properties and marine environment near Dalian Dagushan, aim to make environmental assessments on the damage caused by PX to the marine environment and propose appropriate emergency measures.

scholarly journals Dynamic Early Warning Method for Major Hazard Installation Systems in Chemical Industrial Park

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Yaguang Kong ◽  
Chenfeng Xie ◽  
Song Zheng ◽  
Peng Jiang ◽  
Meng Guan ◽  
...  
Keyword(s):  
Early Warning ◽  
Future Trend ◽  
Quantitative Risk Assessment ◽  
Industrial Park ◽  
Fuzzy Evaluation ◽  
Dynamic Prediction ◽  
Dynamic Evaluation ◽  
Risk Levels ◽  
Chemical Industrial Park ◽  
Data Driven Approach

The production and storage of major hazard installations (MHIs) bring potential risks to chemical industrial park (CIP). In the production system of MHIs, its dangerous degree is mainly determined by key parameters, and abnormal key parameters often lead to accidents. To predict the real-time risk values of MHIs and improve accident prevention ability of CIP, we need a method that can combine dynamic prediction and assessment. Quantitative risk assessment (QRA) is not capable of modelling risk variations during the operation of a process. Therefore, this paper adopts the data-driven approach. Inspired by visual qualitative analysis and quantitative analysis, a dynamic early warning method is proposed for MHIs. We can get the future trend of these key parameters by using strongly correlation variables to predict key parameters. Fuzzy evaluation analysis is performed on the risk levels of key parameters, and the dynamic evaluation index of these MHIs is obtained. This method can be applied to the dynamic evaluation of MHIs system in CIP. It can contribute to the safety of CIP in some aspects.

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