A model based bayesian solution for characterization of complex damage scenarios in aerospace composite structures.

Area of Science:

• Materials Science
• Aerospace Engineering
• Nondestructive Evaluation (NDE)

Background:

• Guided wave-based ultrasonic methods are increasingly used for NDE of aerospace composites.
• Dispersive waves in real structures complicate damage assessment, especially with complex damage scenarios.
• Accurate three-dimensional finite element models (FEMs) are crucial for understanding guided wave interactions with damage.

Purpose of the Study:

• To develop an inverse solution for realistic composite damage characterization.
• To compare experimental and simulated ultrasonic inspection data using wavenumber-frequency spectra.
• To enable flexible damage modeling for complex geometries, such as impact-induced delaminations.

Main Methods:

• Utilized three-dimensional finite element models (FEMs) for guided wave propagation and interaction with damage.
• Employed a Bayesian solution (Markov chain Monte Carlo) for material property verification and uncertainty quantification.
• Applied a transdimensional Markov chain Monte Carlo solution for characterizing complex damage geometry and delamination petals.

Main Results:

• Verified composite laminate material properties with uncertainty quantification.
• Assessed the efficacy of the proposed damage model and comparative metrics.
• Determined posterior probability distributions for individual delamination petals and the overall damage site envelope.

Conclusions:

• The developed inverse solution effectively characterizes realistic composite damage, including complex impact-induced scenarios.
• The transdimensional Markov chain Monte Carlo approach provides a flexible model for adapting to intricate damage geometries.
• This method enhances the capability of guided wave-based NDE for aerospace composite components.