Barcelos Carneiro M Da R, Iuri; Kerfriden, P. (Pierre); Frans van der Meer (2020): Data presented in the paper: "Micromechanics-based surrogate models for the response of composites: A critical comparison between a classical mesoscale constitutive model, hyper-reduction and neural networks". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:45d11acd-3906-4474-ace4-e1073b45b8d2

Dataset

• Mechanical Engineering
• Materials Engineering

Artificial neural networks, Hyper-reduction, Laminated composites, Reduced-order modeling

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Iuri Rocha , P. (Pierre) Kerfriden , Frans van der Meer

This package contains the data presented in the following publication: I.B.C.M. Rocha, P. Kerfriden, F.P. van der Meer, "Micromechanics-based surrogate models for the response of composites: A critical comparison between a classical mesoscale constitutive model, hyper-reduction and neural networks", European Journal of Mechanics A/Solids 2020. All data have been generated with simulations with the in-house finite element code as described in the paper. Simulation results have been processed to generate the relevant plots for the paper. The data stored here is the processed data as used for generating the plots.

• 2020-03-19 first online, published, posted

4TU.Centre for Research Data

media types: application/zip, text/plain

• Netherlands Organization for Scientific Research (NWO), 16464

Delft University of Technology, Faculty of Civil Engineering and Geosciences, Department of Materials, Management & Design (3Md)