4.5 Article

CFD Simulations of Fire Propagation in Horizontal Cable Trays Using a Pyrolysis Model with Stochastically Determined Geometry

Journal

FIRE TECHNOLOGY
Volume 58, Issue 5, Pages 3039-3065

Publisher

SPRINGER
DOI: 10.1007/s10694-022-01291-6

Keywords

Cable tray; Fire spread; Pyrolysis; CFD

Funding

  1. Technical Research Centre of Finland (VTT)

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This paper constructs a pyrolysis model for a PVC cable using experimental results and verifies it through simulation. The study develops a novel stochastic method for creating simplified cable tray geometries and adjusts the surface area. Unlike previous numerical approaches, this method does not rely on empirical correlations or full-scale experiments to predict fire propagation. Comparison with experimental results shows an average overprediction of 8% for the maximum heat release rate.
In this paper, a pyrolysis model for a PVC cable is constructed using results from thermogravimetric analysis, microscale combustion calorimeter and cone calorimeter experiments. The pyrolysis model is used to simulate fire propagation in horizontal cable trays. The simulated arrangement corresponds to a cable tray fire experiment from OECD PRISME 2 project. As laying the cables loosely along the horizontal trays is a random process, a novel stochastic method is developed for making the simplified cable tray geometries for the computational fluid dynamics model. In addition, as the simplified cable tray geometry has significantly smaller surface area than a real tray full of cables, the surface area was parametrically adjusted. In contrast to most of the earlier published numerical approaches for simulating cable tray fires, the presented approach does not use empirical correlations for predicting fire propagation and does not require any results from full-scale experiments for calibrating the model. The simulation results are compared to experimental results in terms of heat release rate, mass loss, tray ignition times and lateral flame spread rates. The maximum heat release rate was overpredicted by 8% on average.

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