The use of optimization in fire development modeling, The use of optimization techniques for estimation of pyrolysis model input parameters
Abstract
This paper deals with the use of the optimization techniques for obtaining the input parameters from the bench scale experimental data that are used for property based fire modeling. Two multidimensional optimization techniques - Genetic algorithm (GA) and Shuffled complex evolution (SCE) - are discussed. Their performance is compared based on the algorithms application to estimation of the material properties of one of the commonly used structural materials – wood.
Downloads
Published
Issue
Section
License
Authors who publish with ASFE agree to the following terms:
1. Authors retain copyright and grant the ASFE right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).