engleski

Novel methods of describing mechanical behaviour through machine learning

Traditional methods of modelling mechanical behaviour include matrices that contain material constants and provide a link between stress and strain. Such formulations are well established in solid mechanics and are used in real-world problems for centuries. They are often simplified but still provide a good model for engineers. However new engineering challenges have given rise to a need for new materials and these materials are often poorly described by conventional models or a multitude of models are used to describe the same behaviour for different materials. A possible way of describing new material properties is the use of machine learning that could use raw experiment data to describe the behaviour of materials avoiding the need for specific material models and speeding up the implementation in engineering calculations.

Machine learning, solid mechanics, nonlinear, materials

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