000			01367nam a2200133Ia 4500
008			220621s9999||||xx |||||||||||||| ||und||
020			_a9783040000000
245		0	_aEmpowering Materials Processing and Performance from Data and AI
546			_aEnglish[eng]
650			_aplasticity||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
700			_aChinesta, Francisco||Cueto, Elías||Klusemann, Benjamin
856			_uhttps://mdpi.com/books/pdfview/book/4327
942			_cEB
999			_c35687 _d35687