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Updated: Jan 7, 2026

A Coupled Experiment-finite Element Modeling Methodology for Assessing High Strain Rate Mechanical Response of Soft Biomaterials
Published on: May 18, 2015
Verification, validation, and uncertainty quantification of finite element analysis results for pedicle screw
On Sim1, Byeong Cheol Jeong1, Chiseung Lee2,3
1Department of Biomedical Engineering, Graduate School, Pusan National University, Busan, Republic of Korea.
Introduction:
This study conducted verification, validation, and uncertainty quantification of finite element analysis (FEA) results for pedicle screw assemblies subjected to static flexion and extension loading conditions, in accordance with the ASTM F1717-15 standard.
Methods:
Four screw configurations and two material types, titanium alloy and titanium grade 23, were modeled to replicate the experimental setup. Simulations incorporated five types of contact conditions at the screw-block interface: frictionless; coefficient of friction (COF) of 0.1, 0.2, or 0.5; and bonded.
Results:
Experimental results demonstrated high repeatability, with maximum deviations of 6.4% for stiffness, 9.1% for yield displacement, 7.2% for yield force, and 7.5% for force at 20 mm displacement. The FEA results qualitatively captured the experimental trends but quantitatively overestimated mechanical responses, particularly under bonded contact conditions. The largest prediction errors were 19.8% for stiffness, 21.5% for yield force, and 18.4% for force at 20 mm, while the greatest deviation in yield displacement, 14.2%, occurred under frictionless conditions. When targeting an ASME VandV 40 Level 3 agreement (difference <10%), we found that no single interface model satisfied all validation metrics across screws and loading modes. When construct stiffness and force at 20 mm were prioritized as primary validation metrics, COF values in the range 0.10-0.20 yielded the most consistent agreement with experiment. Sensitivity analysis revealed that force and stiffness outputs were highly influenced by contact assumptions, whereas displacement outputs exhibited moderate sensitivity.
Discussion:
These findings highlight the importance of accurately defining contact conditions and experimentally characterizing interface behavior. To ensure predictive accuracy and regulatory relevance, validated friction models should be applied and contact parameters precisely calibrated, which can enhance the credibility of spinal biomechanics simulations. Relative to prior F1717-based simulations, this work quantifies the dominant impact of interface modeling and provides actionable parameter bounds for validation (μ = 0.10-0.20 for the tested constructs).
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