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Workshop: From Molecules to Materials: ICLR 2023 Workshop on Machine learning for materials (ML4Materials)

SimuStruct: Simulated Structural Plate with Holes Dataset with Machine Learning Applications

João Alves Ribeiro · Bruno Alves Ribeiro


This paper introduces SimuStruct: Simulated Structural Parts Dataset, a dataset that contains 2D structural parts, their respective meshes and the outputs of numerical simulations for different properties for linear and elastic material, boundary and loading conditions, and for varying levels of refinement. SimuStruct comprises the classic case of plates with holes since it is a 2D simple case with analytical resolution and which is found in different mechanical design applications. The SimuStruct dataset comprises many different cases, where each case is solved using standard Finite Element Methods (FEMs) with the open-source package FEniCS. Compared to other datasets similar in purpose, SimuStruct is more diversified and realistic because it aims to comprises diverse real cases for different loading and boundary conditions, different properties for linear and elastic material, and different levels of refinement. In addition, SimuStruct is more flexible, versatile, and scalable because all algorithms and codes are implemented using open-source libraries. The main goal of the SimuStruct dataset is to serve both as training and evaluation data for Machine Learning (ML)-based methods in structural analysis and optimal mesh generation and therefore support the development of ML-based optimal mechanical design solutions. An application of SimuStruct is presented to train and test an ANN model to predict stress-strain fields. SimuStruct will contribute to the connection of the Mechanical Engineering and ML communities, which will allow accelerating and exploitation the research in the computational design field.

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