Buch, Englisch, 230 Seiten, Format (B × H): 152 mm x 229 mm
Integrating a New Era of Computational Modeling and Machine Learning
Buch, Englisch, 230 Seiten, Format (B × H): 152 mm x 229 mm
ISBN: 978-1-77964-046-8
Verlag: Apple Academic Press
Technologies for materials modeling play a key role in investigating, comprehending, and eventually forecasting the behavior of materials. This new volume presents a selection of studies on new advances, developments, and trends in industrial manufacturing and materials, exploring the new era of advanced materials, composites, nanomaterials, and advanced machining processes. The book also explores combining modern materials science with computer techniques such as artificial intelligence, machine learning, and other smart technologies.
The volume presents studies that showcase modeling and simulation of materials behavior as essential tools in industrial R&D, which assists in making decisions about the creation or improvement of new goods and production techniques. The volume discusses 2D and 3D computational modeling for new advanced materials, evaluating mechanical and optical properties, fiber-matrix interface in fiber-reinforced polymer (FRP) composites, mechanical and corrosion behavior of certain materials, techniques the management of waste materials, using machine learning for reliability prediction, and more.
Zielgruppe
Academic and Postgraduate
Autoren/Hrsg.
Weitere Infos & Material
Preface 1. Computational Modeling of 3D Fabrics for Ballistic and Stab Protective Uses 2. In the New Era of Advanced Materials: A Critical Study 3. Mechanical and Optical Properties of Side-Emitting Optical Fibers 4. Modeling of 2D and 3D Woven Structures and Properties 5. A Critical Analysis of the Use of Machine Learning in the Field of Reliability Prediction 6. Intrinsic Aspects of Fiber-Matrix Interface in FRP Composites: Special Focus on Utility 7. Mechanical and Corrosion Behavior of Friction Stir Processed AA7075 Hybrid Surface Composites 8. Role of Slag Viscosity in the Blast Furnace Process of Pig Iron Production and Its Estimation Index




