Application of Particle Swarm Optimization (PSO) Algorithm in Determining Thermodynamics of Solid Combustibles

The thermodynamics of a solid are crucial in predicting thermal responses and fire behaviors, they commonly determined by inverse modeling optimization algorithms at constant heat flux. However, practical scenarios, the imposed flux frequently varies with time, related determination methods rarely reported. In this study, particle swarm (PSO) algorithm 1D numerical model were utilized to determine temperature-dependent conductivity specific beech wood polymethyl methacrylate (PMMA). Surface, 3 6 mm in-depth temperatures measured three sets ignition tests where time-dependent fluxes (HFs) applied. each set, PSO was implemented individual HFs, average value deemed as final outcome. Reliability optimized verified comparing reported values literature experimental measurements that not employed during parameterization. results showed attained under HFs agreement previously ones. Similar procedures conducted for PMMA, good found. Using obtained HF, successfully captured surface temperature HFs. Meanwhile, comparisons using PMMA linear also feasibility PSO.