Application of Machine Learning Techniques to Formulate Simulation Inputs for Fire Models

Inspired by the advanment of repid development in “machine learning” techniques, we now proposed using genetic algorithm theory to optimise the pyrolysis kinetics input data of any polymer composites for our fire field models (i.e. computational fluid dynamics based). Typically, pyrolysis kinetics is extracted via thermal gravemetry (TGA), where the solid decomposition is studied in Read more about Application of Machine Learning Techniques to Formulate Simulation Inputs for Fire Models[…]