دورية أكاديمية

Optimization of the model of Ogden energy by the genetic algorithm method

التفاصيل البيبلوغرافية
العنوان: Optimization of the model of Ogden energy by the genetic algorithm method
المؤلفون: Blaise Bale Baidi, Betchewe Gambo, Beda Tibi
المصدر: Applied Rheology, Vol 29, Iss 1, Pp 21-29 (2019)
بيانات النشر: De Gruyter, 2019.
سنة النشر: 2019
المجموعة: LCC:Materials of engineering and construction. Mechanics of materials
مصطلحات موضوعية: hyperelastic, model, parameters, genetic-algorithm, Materials of engineering and construction. Mechanics of materials, TA401-492
الوصف: The model of Ogden, is a density of energy used in the modeling of hyperelastic materials behavior. This model of energy presents a high number of material parameters to identify. In this paper, we expose a method of identification of these parameters:Genetic Algorithm. This method contrary to the method of Beda-Chevalier, Least Squares, directed programming object method, PSA (Pattern Search Algorithm) and LMA (Levenberg-Marquardt), allows to identify quickly good parameters which give to the Ogden model a very good prediction in uniaxial tension, biaxial tension and pure shear. This prediction is considered to be better becausewe better bring the experimental curve closer to Treloar one with the parameters optimized by the genetic algorithm.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1617-8106
Relation: https://doaj.org/toc/1617-8106
DOI: 10.1515/arh-2019-0003
URL الوصول: https://doaj.org/article/94f9e6b3f49c4a21b1a27c8ed2435890
رقم الأكسشن: edsdoj.94f9e6b3f49c4a21b1a27c8ed2435890
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:16178106
DOI:10.1515/arh-2019-0003