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Identification of constitutive parameters for fractional viscoelasticity
Institution:1. Department of Physics, University of Surrey, Guildford, Surrey, GU2 7XH, UK;2. Physics Department, Umm AL-Qura University, Makkah, Kingdom of Saudi Arabia;3. Department of Medical Physics and Clinical Engineering, Abertawe Bro Morgannwg UHB and School of Medicine, Swansea University, Swansea SA2 8PP, UK;4. School of Physics and Material Studies, UiTM, 72000 Kuala Pilah, Malaysia;5. Department of Medical Physics, The Royal Surrey County Hospital NHS Trust, Guildford, GU2 7XX Surrey, UK;6. Department of Radiological Sciences, King Saud University, Riyadh 11432, Kingdom of Saudi Arabia;7. Department of Physics, University of Malaya, Campus of Negeri Sambilan, 72000 Kuala Pilah, Malaysia;1. School of Science, Chongqing Jiaotong University, Chongqing 400074, PR China;2. School of Mathematical Science, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, PR China;3. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 610054, PR China;1. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China;2. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China;3. Key Laboratory for Neuroinformation of Ministry of Education, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China
Abstract:This paper develops a numerical model to identify constitutive parameters in the fractional viscoelastic field. An explicit semi-analytical numerical model and a finite difference (FD) method based numerical model are derived for solving the direct homogenous and regionally inhomogeneous fractional viscoelastic problems, respectively. A continuous ant colony optimization (ACO) algorithm is employed to solve the inverse problem of identification. The feasibility of the proposed approach is illustrated via the numerical verification of a two-dimensional identification problem formulated by the fractional Kelvin–Voigt model, and the noisy data and regional inhomogeneity etc. are taken into account.
Keywords:Parameters identification  Inverse problem  Viscoelasticity  Fractional derivatives  Ant colony optimization algorithm
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