Projects per year
Abstract
Hyperelastic constitutive models are investigated and compared on their ability to predict the elastic, isothermal and rate-independent response of rubber. Constitutive model parameters are identified in an optimization problem by minimizing the difference between homogeneous experimental data and their analytical solutions. The results are presented for ten hyperelastic constitutive models over four case studies where varying extents of experimental data are used. The choice of constitutive model is found to determine how accurately experimental data is fitted, though this has different implications depending on the extent of available experimental data. With a complete data set, an accurate fit generally indicates an overall accurate prediction of the material’s response. However, an accurate fit to a reduced set of experimental data may not indicate an accurate prediction of the overall response. With reduced data, accurate predictions are obtained only if the constitutive model is capable of predicting unfitted deformations and the appropriate experimental data is used.
Original language | English |
---|---|
Title of host publication | Constitutive Models for Rubber XI |
Subtitle of host publication | Proceedings of the 11th European Conference on Constitutive Models for Rubber (ECCMR 2019), June 25-27, 2019, Nantes, France |
Editors | Bertrand Huneau, Jean-Benoît Le Cam, Yann Marco, Erwan Verron |
Place of Publication | London |
Number of pages | 6 |
Publication status | Published - 20 Jun 2019 |
Event | 11th European Conference on Constitutive Models for Rubbers - Nantes, France Duration: 25 Jun 2019 → 27 Jun 2019 |
Conference
Conference | 11th European Conference on Constitutive Models for Rubbers |
---|---|
Country/Territory | France |
City | Nantes |
Period | 25/06/19 → 27/06/19 |
Keywords
- parameter identification
- hyperelasticity
- experimental data
Fingerprint
Dive into the research topics of 'The implications of constitutive model selection in hyperelastic parameter identification'. Together they form a unique fingerprint.Projects
- 1 Finished
-
Doctoral Training Partnership (DTP 2016-2017 University of Strathclyde) | Connolly, Stephen
MacKenzie, D. (Principal Investigator), Gorash, Y. (Co-investigator) & Connolly, S. (Research Co-investigator)
EPSRC (Engineering and Physical Sciences Research Council)
1/10/16 → 22/06/20
Project: Research Studentship - Internally Allocated
Datasets
-
Data for: "Numerical modelling of rubber hyperelasticity: parameter identification and finite element implementations"
Connolly, S. J. (Creator), MacKenzie, D. (Supervisor) & Gorash, Y. (Supervisor), University of Strathclyde, 24 Jun 2020
DOI: 10.15129/006b5a11-c4f9-4e30-aea5-d722d072b3a5
Dataset