Presentation Details
A Novel Parameter Identification Toolbox for the Selection of Hyperelastic Constitutive Models from Experimental Data
Thursday, 12 Oct 2017; 16:00 - 16:20 in room 7.22
In Session:
MS17-3: Smart and Active Materials: Experiments, Modelling, and Simulation (Show complete Mini Symposium)
Thursday, 12 Oct 2017; 16:00 - 18:00 in room 7.22
Show complete Session
1st and presenting Author
Hüsnü Dal
Department of Mechanical Engineering
Middle East Technical University
Ankara, Turkey
Department of Mechanical Engineering
Middle East Technical University
Ankara, Turkey
2nd Author
Yashar Badienia
Department of Mechanical Engineering
Middle East Technical University
Ankara, Turkey
Department of Mechanical Engineering
Middle East Technical University
Ankara, Turkey
3rd Author
Kemal Açıkgöz
Department of Mechanical Engineering
Middle East Technical University
Ankara, Turkey
Department of Mechanical Engineering
Middle East Technical University
Ankara, Turkey
4th Author
Funda Aksu Denli
Department of Mechanical Engineering
Middle East Technical University
Ankara, Germany
Department of Mechanical Engineering
Middle East Technical University
Ankara, Germany
Micro Abstract:
This paper presents a novel parameter identification toolbox based on various multi-objective optimization strategies for the selection of the best constitutive models from a given set of homogeneous experiments. The toolbox aims at providing an objective model selection procedure along with the material parameters for the rubber compound at hand. To this end, we utilize the multi-objective optimization using genetic algorithm of MATLAB. For the validation purposes, we use 24 constitutive laws.