Leveraging AI modelling for FDS with Simvue: monitor and optimise for more sustainable simulations

• URL: http://arxiv.org/abs/2509.26139v1
• Date: Tue, 30 Sep 2025 11:57:38 GMT
• Title: Leveraging AI modelling for FDS with Simvue: monitor and optimise for more sustainable simulations
• Abstract summary: We show the ability of a custom machine learning surrogate model to predict the dynamics of heat propagation orders of magnitude faster than state-of-the-art CFD software.<n>We also demonstrate how a guided optimisation procedure can decrease the number of simulations required to meet an objective.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: There is high demand on fire simulations, in both scale and quantity. We present a multi-pronged approach to improving the time and energy required to meet these demands. We show the ability of a custom machine learning surrogate model to predict the dynamics of heat propagation orders of magnitude faster than state-of-the-art CFD software for this application. We also demonstrate how a guided optimisation procedure can decrease the number of simulations required to meet an objective; using lightweight models to decide which simulations to run, we see a tenfold reduction when locating the most dangerous location for a fire to occur within a building based on the impact of smoke on visibility. Finally we present a framework and product, Simvue, through which we access these tools along with a host of automatic organisational and tracking features which enables future reuse of data and more savings through better management of simulations and combating redundancy.

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