Lower Explosion Limits Measurements and Prediction for Binary Liquid Mixtures

Jiakai Cao, Li Ding, Yong Pan, Jianping Zhao

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations

Abstract

The lower explosion limit (LEL) is an important physicochemical parameter for characterizing the flammable and explosive hazard potential of chemicals. In this study, the LEL values of 21 groups of binary liquid mixtures with different compositions and ratios were tested, and the change law of LEL with compositions and ratios were revealed. Then four different physicochemical parameters were employed as the input parameters for the LEL prediction of mixtures. Both the multiple linear regression (MLR) and multiple nonlinear regression (MNR) methods were employed to model the possible quantitative relationships between these parameters and the LEL of binary mixtures. The resulted models showed satisfactory prediction ability, with the average absolute error being 0.188% for the MLR model and 0.196% for the MNR model, respectively. Model validations were also performed to check the stability and predictivity of the presented models, and the results showed that both models were valid and predictive requiring only some common physicochemical parameters of the pure components. This study can provide a simple, yet accurate way for engineering to predict the LELs of binary liquid mixtures as applied in the assessment of fire and explosion hazards and the development of inherently safer designs for chemical processes.

Original languageEnglish
Article number012072
JournalIOP Conference Series: Materials Science and Engineering
Volume585
Issue number1
DOIs
StatePublished - 13 Aug 2019
Event5th Annual International Workshop on Materials Science and Engineering, IWMSE 2019 - Hunan, Changsha, China
Duration: 17 May 201918 May 2019

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