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Case Studies on Predictability in University Chemistry Experiment Accidents

机译:大学化学实验事故可预测性的案例研究

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In this study, we investigated prediction of fire accidents of university’s chemical experiments based on properties or data of chemicals used. By referencing hazardous compounds and their properties in the Fire Service Act in Japan, potentially dangerous operations were picked up from the textbook of General Chemistry Laboratory for undergraduate students in Department of Chemistry, Faculty of Science, Tokyo University of Science. Moreover, previous examples of fire accidents associated with such hazardous compounds and experimental operations were also searched from some databases. Comparing both facts, we concluded that most of fire accidents are predictable, and some difficult cases (i) required common sense for chemical experiments (implicit knowledge with experience) and (ii) are state-dependent properties of the hazardous compounds, e.g. very reactive nanoparticles. The results will also suggest possibility of AI-aided prediction of fire accidents in the future, the range of data required to be learnt, and remaining technical problems.
机译:在这项研究中,我们根据所用化学品的性质或数据调查了大学化学实验中火灾事故的预测。通过参考日本《消防法》中的有害化合物及其特性,从东京化学大学理学院化学系面向普通学生的通用化学实验室教科书中提取了潜在的危险操作。此外,还从一些数据库中搜索了与此类危险化合物和实验操作相关的火灾事故的先前示例。比较这两个事实,我们得出结论,大多数火灾事故是可以预见的,并且某些困难的情况(i)化学实验需要常识(具有经验的隐性知识),以及(ii)危险化合物的状态依赖性,例如反应性很强的纳米粒子。这些结果还将表明AI辅助预测未来火灾事故的可能性,需要学习的数据范围以及剩余的技术问题。

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