• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.223-228
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• 2022

In chemical processes, unintended faults can make serious accidents. To tackle them, proper fault diagnosis models should be designed to identify the root cause of faults. To design a fault diagnosis model, a process and its data should be analyzed. However, most previous researches in the field of fault diagnosis just handle the data set of benchmark processes simulated on commercial programs. It indicates that it is really hard to get fresh data sets on real processes. In this study, real faulty conditions of an industrial polystyrene process are tested. In this process, a runaway reaction occurred and this caused a large loss since operators were late aware of the occurrence of this accident. To design a proper fault diagnosis model, we analyzed this process and a real accident data set. At first, a mode classification model based on support vector machine (SVM) was trained and principal component analysis (PCA) model for each mode was constructed under normal operation conditions. The results show that a proposed model can quickly diagnose the occurrence of a fault and they indicate that this model is able to reduce the potential loss.

• Journal of the Korean Institute of Gas
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• v.2 no.2
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• pp.1-11
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• 1998

A quantitative risk assessment and consequence analysis for PBL(Poly Butadiene Latex) reaction processes were performed. As a result of the Quantitative risk assessment, for the accident probability of PBL reactors causing a reaction runaway, was calculated as $9.197{\times}10^{-5}/yr$ The most important factor that affected the accident probability of PBL reactor was the relief device. When the reactor exploded, peak overpressure at the target point was $5.066{\times}10^5(Pa)$ and the range of effects windows to be broken occurred in almost all of the factory areas. The maximum radius of effect was 27m, in which workers could be die by the direct for eardrum damage was calculated at 77m. When the PBL reactor exploded, the extent of structural damage to buildings was calculated from the center of the explosion to a range of 52m. The results of the study's assessment have provided a direction for facility's improvement as well as effective safety investment.

• Korean Chemical Engineering Research
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• v.57 no.6
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• pp.781-789
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• 2019

There are frequent accidents by chemicals during laboratory experiments and pilot plant and reactor operations. It is necessary to find and comprehend relevant information to prevent accidents before starting synthesis experiments. In the process design stage, reaction information is also necessary to prevent runaway reactions. Although there are various sources available for synthesis information, including the Internet, it takes long time to search and is difficult to choose the right path because the substances used in each synthesis method are different. In order to solve these problems, we propose an intelligent synthetic path search system to help researchers shorten the search time for synthetic paths and identify hazardous intermediates that may exist on paths. The system proposed in this study automatically updates the database by collecting information existing on the Internet through Web scraping and crawling using Selenium, a Python package. Based on the depth-first search, the path search performs searches based on the target substance, distinguishes hazardous chemical grades and yields, etc., and suggests all synthetic paths within a defined limit of path steps. For the benefit of each research institution, researchers can register their private data and expand the database according to the format type. The system is being released as open source for free use. The system is expected to find a safer way and help prevent accidents by supporting researchers referring to the suggested paths.