A constrained particle swarm optimization algorithm for hyperelastic and visco-hyperelastic characterization of soft biological tissues. Issue 4 (3rd July 2020)

• Record Type: Journal Article
• Authors: Ramzanpour, Mohammadreza; Hosseini-Farid, Mohammad; Ziejewski, Mariusz; Karami, Ghodrat
• Is Part Of: International journal for computational methods in engineering science and mechanics. Volume 21:Issue 4(2020)
• Page Start: 169
• Page End: 184
• Publication Date: 2020-07-03
• Subjects: Constrained optimization -- particle swarm optimization -- curve fitting -- soft tissues -- material characterization -- constitutive modeling -- hyperelastic -- visco-hyperelastic; Engineering -- Data processing -- Periodicals; Engineering mathematics -- Periodicals; Computer-aided engineering -- Periodicals; 620.00420285
• DOI: 10.1080/15502287.2020.1767725
• Languages: English
• ISSNs: 1550-2287

Abstract

Abstract: A constrained particle swarm optimization algorithm (C-PSO) is introduced and modified for hyperelastic and visco-hyperelastic characterization of bovine brain tissue at three different strain rates. Using the elasticity compatibility and Drucker's stability criterion, the constraints of the hyperelastic and visco-hyperelastic models are identified and implemented in the C-PSO algorithm and its performance is compared with the classic curve fitting algorithms including Levenberg-Marquardt and trust region reflective. The accuracy of the C-PSO was found to be superior for visco-hyperelastic characterization, as for some strain rates, the trust region reflective algorithm failed to provide a reasonable approximation.