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, and they are commonly determined by inverse modeling and optimization algorithms at constant heat flux. However, in practical scenarios, the imposed heat flux frequently varies with time, and related thermo...

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Main Authors: Haoyu Pan, Junhui Gong
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/16/14/5302
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author Haoyu Pan
Junhui Gong
author_facet Haoyu Pan
Junhui Gong
author_sort Haoyu Pan
collection DOAJ
description The thermodynamics of a solid are crucial in predicting thermal responses and fire behaviors, and they are commonly determined by inverse modeling and optimization algorithms at constant heat flux. However, in practical scenarios, the imposed heat flux frequently varies with time, and related thermodynamics determination methods are rarely reported. In this study, the particle swarm optimization (PSO) algorithm and a 1D numerical model were utilized to determine temperature-dependent thermal conductivity and specific heat of beech wood and polymethyl methacrylate (PMMA). Surface, 3 and 6 mm in-depth temperatures were measured in three sets of ignition tests where constant and time-dependent heat fluxes (HFs) were applied. In each set, PSO was implemented at individual HFs, and the average value was deemed as the final outcome. Reliability of the optimized thermodynamics was verified by comparing with the reported values in the literature and predicting the experimental measurements that were not employed during parameterization. The results showed that wood thermodynamics attained under constant and time-dependent HFs in agreement with previously reported ones. Similar optimization procedures were conducted for PMMA, and good agreement with literature values was found. Using the obtained thermodynamics of wood under constant HF, the numerical model successfully captured the surface temperature at time-dependent HFs. Meanwhile, comparisons using wood temperatures at constant HFs and PMMA temperatures at linear HFs also verified the feasibility of PSO.
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spelling doaj.art-b1518c87cf404aa8a7bdf11aef2a1a782023-11-18T19:08:22ZengMDPI AGEnergies1996-10732023-07-011614530210.3390/en16145302Application of Particle Swarm Optimization (PSO) Algorithm in Determining Thermodynamics of Solid CombustiblesHaoyu Pan0Junhui Gong1College of Safety Science and Engineering, Nanjing Tech University, Nanjing 210009, ChinaCollege of Safety Science and Engineering, Nanjing Tech University, Nanjing 210009, ChinaThe thermodynamics of a solid are crucial in predicting thermal responses and fire behaviors, and they are commonly determined by inverse modeling and optimization algorithms at constant heat flux. However, in practical scenarios, the imposed heat flux frequently varies with time, and related thermodynamics determination methods are rarely reported. In this study, the particle swarm optimization (PSO) algorithm and a 1D numerical model were utilized to determine temperature-dependent thermal conductivity and specific heat of beech wood and polymethyl methacrylate (PMMA). Surface, 3 and 6 mm in-depth temperatures were measured in three sets of ignition tests where constant and time-dependent heat fluxes (HFs) were applied. In each set, PSO was implemented at individual HFs, and the average value was deemed as the final outcome. Reliability of the optimized thermodynamics was verified by comparing with the reported values in the literature and predicting the experimental measurements that were not employed during parameterization. The results showed that wood thermodynamics attained under constant and time-dependent HFs in agreement with previously reported ones. Similar optimization procedures were conducted for PMMA, and good agreement with literature values was found. Using the obtained thermodynamics of wood under constant HF, the numerical model successfully captured the surface temperature at time-dependent HFs. Meanwhile, comparisons using wood temperatures at constant HFs and PMMA temperatures at linear HFs also verified the feasibility of PSO.https://www.mdpi.com/1996-1073/16/14/5302particle swarm optimization (PSO)thermal conductivityspecific heatbeech woodpolymethyl methacrylate (PMMA)
spellingShingle Haoyu Pan
Junhui Gong
Application of Particle Swarm Optimization (PSO) Algorithm in Determining Thermodynamics of Solid Combustibles
Energies
particle swarm optimization (PSO)
thermal conductivity
specific heat
beech wood
polymethyl methacrylate (PMMA)
title Application of Particle Swarm Optimization (PSO) Algorithm in Determining Thermodynamics of Solid Combustibles
title_full Application of Particle Swarm Optimization (PSO) Algorithm in Determining Thermodynamics of Solid Combustibles
title_fullStr Application of Particle Swarm Optimization (PSO) Algorithm in Determining Thermodynamics of Solid Combustibles
title_full_unstemmed Application of Particle Swarm Optimization (PSO) Algorithm in Determining Thermodynamics of Solid Combustibles
title_short Application of Particle Swarm Optimization (PSO) Algorithm in Determining Thermodynamics of Solid Combustibles
title_sort application of particle swarm optimization pso algorithm in determining thermodynamics of solid combustibles
topic particle swarm optimization (PSO)
thermal conductivity
specific heat
beech wood
polymethyl methacrylate (PMMA)
url https://www.mdpi.com/1996-1073/16/14/5302
work_keys_str_mv AT haoyupan applicationofparticleswarmoptimizationpsoalgorithmindeterminingthermodynamicsofsolidcombustibles
AT junhuigong applicationofparticleswarmoptimizationpsoalgorithmindeterminingthermodynamicsofsolidcombustibles