Parametric Numerical Study and Multi-Objective Optimization of Composite Curing through Infrared Radiation

Abstract

Composite curing through infrared radiation (IR) has become a popular autoclave alternative due to lower energy costs and short curing cycles. As such, understanding and measuring the effect of all parameters involved in the process can aid in selecting the proper constituents as well as curing cycles to produce parts with a high degree of cure and low curing time. In this work, a numerical model that takes inputs such as part geometry, material properties, curing-related properties and applied curing cycle is created. Its outputs include the degree of cure, maximum curing temperature and total curing time. A genetic algorithm and a design of experiments (DOE) sequence cover the range of each input variable and multiple designs are evaluated. Correlations are examined and factor analysis on each output is performed, indicating that the most important inputs are activation energy, specimen precuring, applied curing temperature and curing duration, while all the others can be considered constant. Finally, response surfaces are created in order to effectively map and provide estimations of the design space, resulting in a curing cycle optimizer given certain restrictions over the input parameters.

Keywords

• numerical modeling
• polymer–matrix composites
• infrared radiation curing
• design space exploration
• multi-objective optimization