Intelligent Automation, Inc. — Department of Defense SBIR Phase I: N211-008

Description

Autoclaves are widely applied for processing the fiber reinforced polymer (FRP) components. Current modeling methods focus on predicting composite part quality by assuming uniform air temperature and hydrostatic pressure. Without spatial-temporal temperature and pressure boundary conditions derived from computational fluid dynamics (CFD) analysis, it is often difficult to accurately capture the anticipated defects and failure modes in the composites. To address the critical challenge, Intelligent Automation Inc. (IAI) and collaborators propose to develop an innovative multi-physics analysis and Machine Learning (ML) based analysis tool for autoclave composite processing. In Phase I, the research team will work together to develop the foundation modules of the analysis tool, including fluid flow and heat transfer analysis, and thermochemical simulation of composite curing process. Moreover, the team will formulate the ML framework that can combine experimental data to improve simulation accuracy and enhance computational efficiency. Additionally, a detailed test plan will be developed, and calibration and validation tests will be conducted based on representative carbon fiber reinforced polymer (CFRP) part with simple geometries.