A dataset for machine learning research in the field of stress analyses of mechanical structures

Published: 25 June 2020| Version 1 | DOI: 10.17632/wzbzznk8z3.1
Contributor:
Jaroslav Matej

Description

This is a dataset prepared and intended as a data source for development of stress analysis methods based on machine learning. The dataset is based on finite element (FEM/FEA) stress analyses of generated mechanical structures using PyCalculix Python API. The dataset contains more than 270,794 pairs of stress analyses images (von Mises stress) of randomly generated 2D structures with predefined thickness and material properties. All the structures are fixed at their bottom edges and loaded with gravity force only. See PREVIEW directory with some examples.

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Institutions

Technicka Univerzita vo Zvolene

Categories

Artificial Intelligence, Mechanical Engineering, Artificial Neural Networks, Machine Learning, Finite Element Methods, Stress Analysis, Artificial Intelligence in Computer-Aided Design, Mechanical Structure, Deep Learning

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