Effects of Manufacturing Features Associated with Automated Fiber Placement on Performance of Advanced Composite Structures with Fiber Steering

Abstract

The primary goal of this research is to investigate the impact of manufacturing features/defects associated with automated processes on the performance of composite structures. Secondary goals include the use of in-process sensorsfor machine learning in order to minimize defects formation and the use of high-fidelity mesh independent analysis techniques such as extended finite element methods (x-FEM) and discrete crack networking (DCN) for predicting the effects of such anomalies on failure strength and failure mode.

Document Details

Document Type
DoD Grant Award
Publication Date
Apr 24, 2019
Source ID
N000141912168

Entities

People

  • Waruna Seneviratne

Organizations

  • Office of Naval Research
  • United States Navy
  • Wichita State University

Tags

Readers

  • Computational Fluid Dynamics (CFD)
  • Defense Technology Research and Development.
  • Structural Health Monitoring of Composite Structures.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference