LEADER 03099nam 22006375 450 001 9911047824203321 005 20251124120643.0 010 $a3-031-89529-0 024 7 $a10.1007/978-3-031-89529-6 035 $a(CKB)43900246000041 035 $a(MiAaPQ)EBC32484356 035 $a(Au-PeEL)EBL32484356 035 $a(DE-He213)978-3-031-89529-6 035 $a(EXLCZ)9943900246000041 100 $a20251124d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDeep Learning in Computational Mechanics $eAn Introductory Course /$fby Leon Herrmann, Moritz Jokeit, Oliver Weeger, Stefan Kollmannsberger 205 $a2nd ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (690 pages) 225 1 $aIntelligent Technologies and Robotics Series 311 08$a3-031-89528-2 327 $aComputational Mechanics Meets Arti?cial Intelligence -- Neural Networks -- Machine Learning in Computational Mechanics -- Methodological Overview of Deep Learning in Computational Mechanics -- Index. 330 $aThis book provides a first course without requiring prerequisite knowledge. Fundamental concepts of machine learning are introduced before explaining neural networks. With this knowledge, prominent topics in deep learning for simulation are explored. These include surrogate modeling, physics-informed neural networks, generative artificial intelligence, Hamiltonian/Lagrangian neural networks, input convex neural networks, and more general machine learning techniques. The idea of the book is to provide basic concepts as simple as possible but in a mathematically sound manner. Starting point are one-dimensional examples including elasticity, plasticity, heat evolution, or wave propagation. The concepts are then expanded to state-of-the-art applications in material modeling, generative artificial intelligence, topology optimization, defect detection, and inverse problems. 410 0$aIntelligent Technologies and Robotics Series 606 $aComputational intelligence 606 $aMachine learning 606 $aThermodynamics 606 $aHeat engineering 606 $aHeat$xTransmission 606 $aMass transfer 606 $aComputational Intelligence 606 $aMachine Learning 606 $aEngineering Thermodynamics, Heat and Mass Transfer 615 0$aComputational intelligence. 615 0$aMachine learning. 615 0$aThermodynamics. 615 0$aHeat engineering. 615 0$aHeat$xTransmission. 615 0$aMass transfer. 615 14$aComputational Intelligence. 615 24$aMachine Learning. 615 24$aEngineering Thermodynamics, Heat and Mass Transfer. 676 $a620.1 700 $aHerrmann$b Le?on$0165001 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911047824203321 996 $aDeep Learning in Computational Mechanics$94531543 997 $aUNINA