Empowering Materials Processing and Performance from Data and AI

Third millennium engineering address new challenges in materials sciences and engineering. In particular, the advances in materials engineering combined with the advances in data acquisition, processing and mining as well as artificial intelligence allow for new ways of thinking in designing new mat...

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Detaylı Bibliyografya
Diğer Yazarlar:	Chinesta, Francisco (Editör), Cueto, Elías (Editör), Klusemann, Benjamin (Editör)
Materyal Türü:	Kitap Bölümü
Baskı/Yayın Bilgisi:	Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Konular:	Technology: general issues plasticity machine learning constitutive modeling manifold learning topological data analysis GENERIC soft living tissues hyperelasticity computational modeling data-driven mechanics TDA Code2Vect nonlinear regression effective properties microstructures model calibration sensitivity analysis elasto-visco-plasticity Gaussian process high-throughput experimentation additive manufacturing Ti-Mn alloys spherical indentation statistical analysis Gaussian process regression nanoporous metals open-pore foams FE-beam model data mining mechanical properties hardness principal component analysis structure-property relationship microcompression nanoindentation analytical model finite element model artificial neural networks model correction feature engineering physics based data driven laser shock peening residual stresses data-driven multiscale nonlinear stochastics neural networks n/a
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Yer Numarası:	A1234.567
Kopya Bilgisi 1	Kütüphanede

Empowering Materials Processing and Performance from Data and AI

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