Integration of Finite Element Analysis and Laboratory Analysis on 3D Models for Methodology Calibration

Area of Science:

• Materials Science and Engineering
• Mechanical Engineering
• Computational Mechanics

Background:

• Accurate prediction of mechanical behavior, material damage, and fatigue crack initiation/propagation is crucial for engineering applications.
• Modern tools are needed to simulate scenarios, optimize decisions, and integrate diverse data sources for enhanced predictive capabilities.
• Early warning systems for material degradation can improve damage control strategies and economic sustainability.

Purpose of the Study:

• To present the calibration and integration of a multi-sensor system for creating volumetric models.
• To develop retopologized models for use with Finite Element Analysis (FEA) software.
• To enhance the prediction of material failure, fatigue, and crack propagation.

Main Methods:

• Integration of photogrammetry, laser scanning, and strain gauges for data acquisition.
• Application of cyclic loading to car suspension components instrumented with strain gauges.
• Calibration of a multi-sensor system using photogrammetry and experimental strain gauge measurements.

Main Results:

• Successful calibration of a combined sensor system for generating volumetric models.
• Demonstration of a methodology for predicting failure using FEA software.
• Acquisition of experimental strain gauge data to measure component deformation under cyclic loading.

Conclusions:

• The synergetic implementation of NDE-based protocols provides early warning outcomes for mechanical and fatigue behavior.
• Developed retopologized models, coupled with FEA, can improve the prediction of material damage and crack propagation.
• This approach enhances preparedness for economically sustainable damage control scenarios.