Development of the Conditional Source-term Estimation (CSE) framework including finite-rate kinetics and non-prescribed radiation applied to a methanol pool fire

Abstract

The objective of this paper is to assess the new developments of Conditional Source-term Estimation (CSE) framework with improved radiation modeling in large eddy simulation applied to a medium-scale methanol pool fire. Tabulated detailed chemistry is included. Radiation is treated in two ways. The first is the optically thin approximation neglecting absorption. The second is through solution of the radiative transfer equation to account for absorption. The weighted-sum of gray-gases model is included in both cases and turbulence–radiation interactions are accounted for. Predictions of the time-averaged and root mean square temperature and velocity profiles, are compared with the experimental measurements at several locations. On the centerline, time-averaged temperature predictions agree well with the experiments except close to the pool where the temperatures are underpredicted. The predicted radial profiles are close to the experiments. The centerline species concentrations show a general agreement in trends, but there are some discrepancies especially towards the downstream regions of the fire. Sources of discrepancy are discussed. Overall, the different treatments of radiation show comparable predictions, but larger benefits of the current CSE framework are expected for more complex scenarios.

Novelty and Significance Statement

The novelty of the present study is the development of a combined turbulent combustion modeling framework, Conditional Source-term Estimation (CSE), including detailed chemical kinetics with advanced radiation models through solution of the radiative transfer equation. In this paper, absorption effects are included in the radiative fluxes, the optically thin assumption is discussed and turbulence–radiation interactions are accounted for. Inclusion of these coupled thermo-chemical–physical phenomena within CSE and using conditional averages in the context of pool fire simulation is a significant contribution. A rigorous validation is performed for a well-documented medium-scale methanol pool fire. This study lays the foundations for more complex fire scenarios of different scales, fuels and conditions.