Flat-panel composite curing distortion dataset: curated tabular data and representative deformed surfaces

This record presents a curated 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 sample 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. The released dataset includes design parameters, laminate descriptors, derived geometric quantities, scalar distortion metrics, and selected numerical and runtime metadata. It is intended to support exploratory data analysis, benchmarking, surrogate modelling, and machine learning workflows focused on composite manufacturing and structural response prediction. The dataset is released through two complementary Zenodo records. One provides the raw simulation outputs, preserving the original case-level results generated by the PID workflow and intended for full traceability, detailed inspection, and reprocessing. The present record provides the curated tabular data and representative deformed surfaces, offering the user-facing, analysis-ready version of the dataset. 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.