Stochastic and High-fidelity Modeling for Fatigue Life Prediction of Composite Laminates

Abstract

The complexity associated with the deformation response and failure mode interactions in carbon fiber reinforced laminates (CFRL) leads to significant challenges in fatigue life prediction of composite aerostructures. The authors of this proposal have successfully developed a high fidelity and computationally efficient modeling framework (SD2M) for quasi-static response predictions of CFRL. The framework has been validated against multiple test cases and proven to be accurate, including the prediction of scatter in the outcomes due to the stochastic nature of the SD2M formulation. In the proposed work, the challenging problem of predicting the fatigue life of CFRL is undertaken, starting with coupon level configurations and extending the validation to structural predictions. We will extend the SD2M and the enhanced SD2M framework for predicting fatigue damage and failure due to cyclic loading. This is a three year project that can lead to significant cost savings for the US Air Force.

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 06, 2025
Source ID
FA95502410213

Entities

People

  • Anthony Waas

Organizations

  • Air Force Office of Scientific Research
  • Arizona State University
  • United States Air Force

Tags

Readers

  • Computational Fluid Dynamics (CFD)
  • Nuclear and Radiation Engineering.
  • Structural Health Monitoring of Composite Structures.