Phase Field Modelling of Failure in Thermoset Composites Under Cure-Induced Residual Stress

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Manufacturing defects are very important for producing composite parts with ideal thermal and mechanical properties. This article is focused on examining the influence of "locked-in" internal residual stress fields on the load-carrying capacity and strength of composite parts. The work has a certain significance on developing virtual manufacturing processes that incorporate new resin formulations in the industry. Before considering publication in JCS, some questions should be answered as under:

1. In paragraph 2 of Results and Discussion, Author stated that “The CTEs and CCSs are considered independent of the degree of cure……” Actually, both CTEs and CCSs are very close to the degree of cure. How to understand this and consider this into analog computation?

2. Author should provide the experiment details.

3. Even the three-dwell cure cycles are very important, how to confirm the condition of 3-dwell cure cycles according to different epoxy resin and hardener?

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript explores the impact of cure-induced residual stress on the failure mechanisms of unidirectional thermoset composites under quasi-static loading. A coupled computational framework integrates the Cure Hardening Instantaneously Linear Elastic (CHILE) model for stress analysis and the Phase Field (PF) model for damage simulation. By incorporating structural tensors, the models account for material anisotropy, enabling predictions of crack propagation and delamination. Numerical benchmarks validate the models against experimental data, demonstrating their accuracy in representing residual stresses and failure mechanisms. Applications to L-shaped parts highlight the influence of residual stress on load-bearing capacity and crack initiation, offering insights for optimizing manufacturing processes. I recommend publication after addressing the following questions:

1. Clearly articulate the study's novel contributions compared to existing computational frameworks. How does the coupling of CHILE and PF models improve predictions over standalone approaches?
2. The authors should also summarize key findings early in the abstract to capture the reader’s interest.
3. How sensitive are the computational results to the choice of parameters in the CHILE and PF models, such as the anisotropic constant (𝜍) or the length scale (𝑙𝜙)?
4. Could the methodology be adapted for real-time monitoring or quality control in manufacturing processes?
5. What are the computational limitations of implementing this coupled framework in large-scale industrial applications?

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

This manuscript can be published this time.