LEADER 05465nam 22007695 450 001 9910838279403321 005 20240307124807.0 010 $a87-438-0420-9 010 $a87-438-0052-1 010 $a3-031-50474-7 024 7 $a10.1007/978-3-031-50474-7 035 $a(MiAaPQ)EBC31169172 035 $a(Au-PeEL)EBL31169172 035 $a(DE-He213)978-3-031-50474-7 035 $a(CKB)30464659000041 035 $a(OCoLC)1424749214 035 $a(EXLCZ)9930464659000041 100 $a20240219d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdditive and Advanced Manufacturing, Inverse Problem Methodologies and Machine Learning and Data Science, Volume 4 $eProceedings of the 2023 Annual Conference & Exposition on Experimental and Applied Mechanics /$fedited by Sharlotte L.B. Kramer, Emily Retzlaff, Piyush Thakre, Johan Hoefnagels, Marco Rossi, Attilio Lattanzi, François Hemez, Mostafa Mirshekari, Austin Downey 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (101 pages) 225 1 $aConference Proceedings of the Society for Experimental Mechanics Series,$x2191-5652 311 08$a3-031-50473-9 327 $aChapter 1. Quantifying residual stresses generated by laser powder bed fusion of metallic samples -- Chapter 2. Loading-Unloading Compressive Response and Energy Dissipation of Liquid Crystal Elastomers and Their 3D Printed Lattice Structures at Low and Intermediate Strain Rates -- Chapter 3. Residual Stress Induced in Thin Plates During Additive Manufacturing -- Chapter 4. Investigating the Effects of Acetone Vapor Treatment and Post Drying Conditions on Tensile and Fatigue behavior of 3D Printed ABS Components -- Chapter 5. Mechanics of Novel Double-Rounded-V Hierarchical Auxetic Structure - Finite Element Analysis and Experiments Using Three-dimensional Digital Image Correlation -- Chapter 6. Repeatability of Residual Stress in Replicate Additively Manufactured 316L Stainless Steel Samples -- Chapter 7. Acoustic nondestructive characterization of metal pantographs for material and defect identification -- Chapter 8. Rapid prototyping of a micro-scale spectroscopic system by two-photondirect laser writing -- Chapter 9. Bioinspired Interfaces for Improved Interlaminar Shear Strength in 3D Printed Multi-Material Polymer Composites -- Chapter 10. Thermo-mechanical Characterization of High-strength Steel through Inverse Methods -- Chapter 11. A multi-testing approach for the full calibration of 3D anisotropic plasticity models via inverse methods -- Chapter 12. Finite Element Based Material Property Identification Utilizing Full-Field Deformation Measurements -- Chapter 13. Data-driven material models for engineering materials subjected to arbitrary loading paths: influence of the dimension of the dataset -- Chapter 14. Data-driven methodology to extract stress fields in materials subjected to dynamic loading. 330 $aAdditive and Advanced Manufacturing, Inverse Problem Methodologies and Machine Learning and Data Science, Volume 4 of the Proceedings of the 2023 SEM Annual Conference & Exposition on Experimental and Applied Mechanics, the fourth volume of five from the Conference, brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on a wide range of topics and includes papers in the following general technical research areas: AM Composites and Polymers Dynamic Behavior of Additively Manufactured Materials and Structures Joint Residual Stress and Additive Manufacturing ML for Material Model Identification Novel AM Structures Novel Processing and Testing of Additively Manufactured Materials Plasticity and Complex Material Behavior Virtual Fields Method. 410 0$aConference Proceedings of the Society for Experimental Mechanics Series,$x2191-5652 606 $aIndustrial engineering 606 $aProduction engineering 606 $aMachine learning 606 $aArtificial intelligence$xData processing 606 $aMaterials$xAnalysis 606 $aIndustrial and Production Engineering 606 $aMachine Learning 606 $aData Science 606 $aMaterials Characterization Technique 615 0$aIndustrial engineering. 615 0$aProduction engineering. 615 0$aMachine learning. 615 0$aArtificial intelligence$xData processing. 615 0$aMaterials$xAnalysis. 615 14$aIndustrial and Production Engineering. 615 24$aMachine Learning. 615 24$aData Science. 615 24$aMaterials Characterization Technique. 676 $a670 700 $aKramer$b Sharlotte L. B$01726326 701 $aRetzlaff$b Emily$01726327 701 $aThakre$b Piyush$01726328 701 $aHoefnagels$b Johan$01726329 701 $aRossi$b Marco$0307761 701 $aLattanzi$b Attilio$01726330 701 $aHemez$b François$01460542 701 $aMirshekari$b Mostafa$01726331 701 $aDowney$b Austin$01726332 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910838279403321 996 $aAdditive and Advanced Manufacturing, Inverse Problem Methodologies and Machine Learning and Data Science, Volume 4$94132047 997 $aUNINA