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Showing 1 to 5 of 5 for “"Material Property Prediction"”.
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New Computational Methodologies for Microstructure Quantification
… physics-based and data-driven methods for material property prediction for metallic microstructures while indicating the context and benefit for microstructure- sensitive design. From this, the use of shape moment invariants is offered as solution to quantifying microstructure topology …
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Implementation of Multivariate Artificial Neural Networks Coupled with Genetic Algorithms for the Multi-Objective Property Prediction and Optimization of Emulsion Polymers
… These trends can then be used to make predictions on new data and explore entirely new design spaces. Methods vary from simple linear regression to highly complex neural networks, but the end goal is similar. The application of these methods to material property prediction and new …
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Advancing computational materials design and model development using data-driven approaches
… affecting the development of the novel hybrid materials. A certain application demanding the need for a desired function can be cherished through the hybrids with a blend of new properties by a combination of pure materials. However, to run MD simulations, an accurate representation of the …
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Inverse Modelling of Material Parameters for Rubber-like material: Create a New Methodology of Predicting the Material Parameters using Indentation Bending Test
Rubber-like materials and thin membrane materials have been widely used in industries, such as engineering fields and biomedical fields. The mechanics of membranes and material parameters identification is an important research area. In this work, different inverse FE modelling approaches to …
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Lattice to continuum: A theoretical framework to calculate elastic fields in lattice scale
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-05-01