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Numerical Heat Transfer, Part A: Applications
An International Journal of Computation and Methodology
Volume 79, 2021 - Issue 8
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Original Articles

A novel stochastic approach to study water droplet/flame interaction of water mist systems

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Pages 570-593 | Received 03 Nov 2020, Accepted 06 Dec 2020, Published online: 27 Jan 2021
 

Abstract

Analyzing the heat transfer effectiveness of fire suppression systems at droplet level through experimentation is difficult and costly. To overcome this issue, traditional Eulerian–Lagrangian model has been modified to track droplet histories in association with computational fluid dynamics (CFD) fluid models. This allows a comprehensive description of the flame interaction energy migration process of water droplets. The modified Eulerian–Lagrangian approach is adopted to trace every droplet parcel coupled with the fluid closure. Using the in-house code, the histogram of key parameters (e.g. temperature, velocity, mass, etc.) of droplets on microscopic level during suppression are obtained over time-iterations, then subsequently analyzed by statistical approaches, which made the concept of water utilization rate advocated for the first time. Through combination with other key parameters, this concept can effectively indicate the suppression efficiency at droplet level, and thus provide key insights to the design of water mist or more advanced systems. Among the cases studied, with similar suppression time, it is discovered that the water utilization rate can vary from 10% to 26%, based on different design. Tracing the transient movement and evaporation process of water droplets formulates a new approach to effectively study the heat transfer efficiency of water-based fire suppression systems.

Acknowledgments

The authors would like to thank Mr. Jason Fang for his help in developing the data processing code. This research was undertaken with the assistance of resources and services from the National Computational Infrastructure (NCI), which is supported by the Australian Government.

Disclosure statement

The authors declare no conflict of interest.

Additional information

Funding

This research was sponsored by the Australian Research Council (ARC Industrial Transformation Training Center IC170100032).

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