<p>The properties of the material with which an industrial component is manufactured determine, to a large extent, its behavior and its ability to withstand the working conditions to which it is subjected during its operation; as insufficient performance can lead to premature failure, especially in demanding environments where service conditions can be particularly critical. For this reason, it is essential to have tools that allow selecting the most appropriate material for each application, being numerical simulation, advanced data analytics and artificial intelligence some of the techniques that present the greatest potential thanks to technological development and access to information. Specifically, metallic materials and some composite materials play a fundamental role in the industrial field since they belong to two of the most prominent groups of structural materials due to their qualities; but it can be very costly, in time and resources, to characterize its behavior and its properties experimentally using the techniques traditionally employed for this purpose. In particular, it is of interest to know the behavior of a metallic material in order to determine its response to various stresses. Additionally, it should be considered that certain composite materials can be excellent alternatives in certain demanding applications. This study examines the ability of finite element simulations, artificial neural networks and techniques based on machine learning and artificial intelligence to predict the behavior and properties of metallic materials and polymeric matrix composites.</p>

Prediction of Material Properties by Using the Finite Element Method and Artificial Intelligence

Paper Proceedings: https://asmedigitalcollection.asme.org/MSEC/MSEC2021/volume/85062

2021 International Manufacturing Science and Engineering Conference (MSEC2021)

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