Modeling of fire with CFD for nuclear power plants (NPPs)

In enclosed fire situations, the flame interacts with ceiling and its length extension take place, altering the fire severity significantly. Fire safety analysis demand a generic flame extension model. A generic reliable model is not available as the construct of flame itself had wide variation in literature. The present paper aims to develop a Machine Learning (ML) based generic model of non-dimensional flame extension as a function of non-dimensional Heat Release Rate (HRR). The non-dimensional scaling reduces the number of parameter and also provide a generic nature. Literature review was utilized to collect the data from various open literature sources. This eliminates the limitations of individual correlations and gives a best optimized model which is valid for a wide range of flow regimes and conditions as compared to a specific correlation. Various simple ML models are compared for their performance against test data and a MARS based model was finally recommended. The MARS model was tested against the data which was not used in training and also against the other reported correlation. The developed model has performed well against the test data and marked improvement over other reported correlation as a better optimized performance over an extended range of non-dimensional range. The results of the model were also conservative as compared to another model in the most of the practical requirement of NPPs. A Large Eddy Simulation (LES) based CFD code FDS was also used to generate the flame extension data for demonstrating conservative nature of the ML model.

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Numerical Simulations of a Postulated Methanol Pool Fire Scenario in a Ventilated Enclosure Using a Coupled FVM-FEM Approach

Tiwari

Bale

Das

et al. 2022

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Numerical investigations have been carried out for a postulated enclosure fire scenario instigated due to methanol pool ignition in a chemical cleaning facility. The pool fire under consideration is radiation-dominated and poses a risk to the nearby objects if appropriate safety requirements are not met. The objective of the current study was to numerically evaluate the postulated fire scenario and provide safety recommendations to prevent/minimize the hazard. To do this, the fire scenario was first modeled using the finite volume method (FVM) based solver to predict the fire characteristics and the resulting changes inside the enclosure. The FDS predicted temperatures were then used as input boundary conditions to conduct a three-dimensional heat transfer analysis using the finite element method (FEM). The coupled FVM–FEM simulation approach enabled detailed three-dimensional conjugate heat transfer analysis. The proposed FVM–FEM coupled approach to analyze the fire dynamics and heat transfer will be helpful to safety engineers in carrying out a more robust and reliable fire risk assessment.

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Modeling of fire with CFD for nuclear power plants (NPPs)

Cited by 3 publications

References 47 publications

Application of high-fidelity modelling approach to predict smoke and fire propagation in a nuclear fire scenario

Application of high-fidelity modelling approach to predict smoke and fire propagation in a nuclear fire scenario

Generic flame extension model development based on machine learning for NPPs fire hazard analysis (FHA)

Numerical Simulations of a Postulated Methanol Pool Fire Scenario in a Ventilated Enclosure Using a Coupled FVM-FEM Approach

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