Session: 03-05-01: Integrated Computational Materials Engineering

Paper Number: 121553

121553 - Layer-Wise Modeling of Temperature Distributions and Degree of Cure to Evaluate Process-Induced Deformation and Residual Stress 

Composite materials have increasingly caught on in the aerospace and automotive industries due to their excellent mechanical properties. The use of an autoclave in the curing process of composite materials allows for increased mechanical performance, but at the same time, it can lead to residual stresses and strains. Predicting temperature distribution and degree of cure distributions within thick geometries during the process is the first step in assessing residual strains and stresses.   

In this work, a cure simulation based on a one-dimensional thermochemical model is used for predicting the evolution of temperature and degree of cure along the thickness of the composite component during the curing cycle. The one-dimensional heat transfer governing equation through the thickness is coupled with the curing kinetics of the thermoset composite material. Temperatures and degree of cure are then used for a thermo-mechanical analysis using layer-wise 1D elements based on the Carrera Unified Formulation (CUF).

Using 1D models allows for computational costs and enables fast numerical analyses. The impact of various parameters on the process-induced dimensional changes and residual stresses is evaluated, e.g., thickness, lamination, and cure cycles. Spring-in angles, warpage, and 3D stress distributions are evaluated.

The results show the influence of a non-uniform degree of cure along the thickness, resulting in a consequent variation of material properties depending on the layer considered. In addition, it is shown how process parameters such as the fiber volume fraction and holding temperature have a greater influence on final performance. 

Future developments may be to use innovative cure cycles to improve performance and reduce the energy impact of the process and thus costs or to use the combination of virtual manufacturing and Artificial Intelligence to optimize the process and mitigate defects in composite structures.

Presenting Author: Enrico Zappino Politecnico di Torino

Presenting Author Biography: Enrico Zappino is an Associate professor at Politecnico di Torino and part of the MUL2 team since the 2010.
Under the mentorship of Prof. Carrera he obtained his Ph.D. in 2014 with a thesis on variable kinematics models for the study of composite structures. After his Ph.D. he has continued the development of advanced numerical
models applying them to different fields: smart structures, aeroelasticity, thermo-elastic problems, global-local approaches. Recently, thanks to the collaborations with UBC and UW he is developing models for virtual manufacturing of composite structures.