Numerical models for seamlessly predicting internal diffusion and re-emission of leaked liquid toluene from indoor mortar materials
Journal of Building Engineering, ISSN: 2352-7102, Vol: 57, Page: 104976
2022
- 2Citations
- 7Captures
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Article Description
There have been serious hazardous liquid chemical leakage cases in factories, chemical plants, and laboratories owing to natural disasters or contingent human accidents. Regarding risk management, when high-risk liquid chemical substances are assumed to leak inside enclosed indoor spaces, reasonable prediction of transient and heterogeneous concentration distributions formed around the human body is necessary to develop an appropriate evacuation plan. In particular, understanding the air-phase concentration level in the breathing zone and its duration for inhalation exposure is essential for short-term and high-concentration exposure health risk assessment. Transient and non-uniform concentration distributions can be predicted using computational fluid dynamics (CFD) and in silico human body analysis. However, the development of practical chemical emission models considering internal diffusion and direct evaporative diffusion from floor materials and their seamless boundary conditions must be addressed for practical application. In this study, liquid toluene was assumed to be a representative hazardous chemical substance for risk assessment, and fundamental experiments and corresponding numerical analyses of liquid toluene leaks on mortar materials were conducted. The experimental results suggest that the effective diffusion coefficient of the mortar sample has a significant effect on the sorption timescales of liquid toluene into the materials and significantly changes the air-phase toluene concentrations. The three-dimensional CFD analysis incorporating the practical toluene emission models reproduces the external and internal emission characteristics of leaked toluene on the mortar material and reasonably agrees with the experimental data.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S235271022200986X; http://dx.doi.org/10.1016/j.jobe.2022.104976; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85134694317&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S235271022200986X; https://dx.doi.org/10.1016/j.jobe.2022.104976
Elsevier BV
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