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E-grāmata: Additive and Advanced Manufacturing, Inverse Problem Methodologies and Machine Learning and Data Science, Volume 4: Proceedings of the 2023 Annual Conference & Exposition on Experimental and Applied Mechanics

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Additive and Advanced Manufacturing, Inverse Problem Methodologies and Machine Learning and Data Science, Volume 4: Proceedings of the 2023 Annual Conference & Exposition on Experimental and Applied MechanicsPalielināt
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Additive 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
Chapter
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.
Sharlotte L.B. KramerSandia National Laboratories, NM, USA; Emily RetzlaffUnited States Naval Academy, MD, USA; Piyush ThakreDow Inc., TX,USA; Johan HoefnagelsEindhoven University of Technology, Netherlands; Marco RossiUniversitą Politecnica delle Marche, Italy; Attilio LattanziCalifornia Institute of Technology, CA, USA; Franēois HemezLawrence Livermore National Laboratory, CA, USA; Mostafa MirshekariCarnegie Mellon University, PA, USA; Austin DowneyUniversity of South Carolina, SC, USA
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