Flat-panel composite curing distortion dataset: raw simulation outputs

This record presents the raw simulation outputs of a synthetic dataset of process-induced distortion in flat laminated composite panels generated within the DIDEAROT project (DIgital DEsign strategies to certify and mAnufacture Robust cOmposite sTructures). The dataset has been produced using the Process Induced Distortion (PID) synthetic data generator, a high-fidelity numerical workflow based on Alya’s simulation framework. Each case corresponds to a finite-element simulation of a flat rectangular composite laminate subjected to a cure cycle, with the objective of capturing the distortion that emerges after tool release due to residual stresses developed during manufacturing.

The simulations account for the coupled effects of thermoelastic residual stresses and chemical shrinkage, providing a physically grounded description of post-cure out-of-plane deformation. This record preserves the original case-level simulation outputs and associated artefacts in their raw form, enabling full traceability, detailed inspection, reprocessing, and reconstruction of derived quantities through the original post-processing workflow.

The dataset is released through two complementary Zenodo records. The present record contains the raw simulation outputs, while the companion record provides the curated tabular data and representative deformed surfaces, offering the user-facing, analysis-ready version of the dataset for exploratory analysis, benchmarking, surrogate modelling, and machine learning workflows. This dataset is one of the synthetic data assets developed within the DIDEAROT framework to enable data-driven methodologies for robust composite design and certification. Additional details on the simulation framework, modelling assumptions, and workflow implementation can be found in Deliverable D3.7 of DIDEAROT and in the work entitled “A High-Fidelity HPC Workflow for Predicting Process-Induced Distortions in Composites Using Surrogate Models” [1].

[1] M. Teixidor-Vilarrasa, A. Quintanas-Corominas, A. Ortega, I. Zárate, E. Marquinez, I. Otero and G. Guillamet, A High-Fidelity HPC Workflow for Predicting Process-Induced Distortions in Composites Using Surrogate Models, Materiales Compuestos (Online first). URL https://www.scipedia.com/public/Vilarrasa_et_al_2025a 

This project has received funding from the European Union’s Horizon Europe Framework Programme under grant agreement No. 101056682 for the project “DIgital DEsign strategies to certify and mAnufacture Robust cOmposite sTructures (DIDEAROT)”. The contents of this publication are the sole responsibility of the participants and do not necessarily reflect the opinion of the European Union. Neither the European Union nor the granting authority can be held responsible for them.