Time-dependent hyper-viscoelastic parameter identification of human articular cartilage and substitute materials.
J Mech Behav Biomed Mater
; 138: 105618, 2023 02.
Article
in En
| MEDLINE
| ID: mdl-36566662
ABSTRACT
Numerical simulations are a valuable tool to understand which processes during mechanical stimulations of hydrogels for cartilage replacement influence the behavior of chondrocytes and contribute to the success or failure of these materials as implants. Such simulations critically rely on the correct prediction of the material response through appropriate material models and corresponding parameters. In this study, we identify hyper-viscoelastic material parameters for numerical simulations in COMSOL Multiphysics® v. 5.6 for human articular cartilage and two replacement materials, the commercially available ChondroFillerliquid and oxidized alginate gelatin (ADA-GEL) hydrogels. We incorporate the realistic experimental boundary conditions into an inverse parameter identification scheme based on data from multiple loading modes simultaneously, including cyclic compression-tension and stress relaxation experiments. We provide individual parameter sets for the unconditioned and conditioned responses and discuss how viscoelastic effects are related to the materials' microstructure. ADA-GEL and ChondroFillerliquid exhibit faster stress relaxation than cartilage with lower relaxation time constants, while cartilage has the largest viscoelastic stress contribution. The elastic response predominates in ADA-GEL and ChondroFillerliquid, while the viscoelastic response predominates in cartilage. These results will help to simulate mechanical stimulations, support the development of suitable materials with distinct mechanical properties in the future and provide parameters and insight into the time-dependent material behavior of human articular cartilage.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Cartilage, Articular
Type of study:
Diagnostic_studies
/
Prognostic_studies
Limits:
Humans
Language:
En
Journal:
J Mech Behav Biomed Mater
Journal subject:
ENGENHARIA BIOMEDICA
Year:
2023
Document type:
Article