LF
L. Ferilli
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Finite Element Modeling of NiTiNol in Transcatheter Aortic Valve Implantation: Assessing Material Influence on Simulation Reliability
Verification, Validation, and Uncertainty Quantification of NiTiNol Behavior in TAVI Computational Modeling
This study investigates the impact of shape-memory alloy (NiTiNol) parameter variability on the predictive reliability of finite element (FE) models for transcatheter aortic valve implantation (TAVI). A fully verified and validated FE model was developed following ASME V&V 40 guidelines, integrating experimental tests, numerical verification, and uncertainty quantification to isolate material effects from numerical artifacts. A Monte Carlo parameter fitting approach was employed using three independent tensile datasets to calibrate the NiTiNol model, resulting in a quantified uncertainty range of ±5.34%. Simulation results revealed that only Austenite Young’s modulus significantly influenced the mechanical response under physiological loading, while other transformation parameters had negligible effects. In contrast, literature-derived parameters introduced up to 30% deviation, highlighting the inadequacy of non-case-specific data. This work emphasizes the critical need for validated material parameters to ensure simulation credibility, particularly in clinical and regulatory contexts where simulation outcomes increasingly inform patient-specific treatment and device design.
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This study investigates the impact of shape-memory alloy (NiTiNol) parameter variability on the predictive reliability of finite element (FE) models for transcatheter aortic valve implantation (TAVI). A fully verified and validated FE model was developed following ASME V&V 40 guidelines, integrating experimental tests, numerical verification, and uncertainty quantification to isolate material effects from numerical artifacts. A Monte Carlo parameter fitting approach was employed using three independent tensile datasets to calibrate the NiTiNol model, resulting in a quantified uncertainty range of ±5.34%. Simulation results revealed that only Austenite Young’s modulus significantly influenced the mechanical response under physiological loading, while other transformation parameters had negligible effects. In contrast, literature-derived parameters introduced up to 30% deviation, highlighting the inadequacy of non-case-specific data. This work emphasizes the critical need for validated material parameters to ensure simulation credibility, particularly in clinical and regulatory contexts where simulation outcomes increasingly inform patient-specific treatment and device design.