Fundamentals of Multiscale Modeling of Structural Materials

Author: Xia, Wenjie

Brand: Elsevier

Edition: 1

Number Of Pages: 448

EAN: 9780128230213

Release Date: 25-11-2022

Package Dimensions: 9.0 x 6.0 x 1.1 inches

Languages: English

Binding: paperback

Details: Fundamentals of Multiscale Modeling of Structural Materials provides a robust introduction to the computational tools, underlying theory, practical applications, and governing physical phenomena necessary to simulate and understand a wide-range of structural materials at multiple time and length scales. The book offers practical guidelines for modeling common structural materials with well-established techniques, outlining detailed modeling approaches for calculating and analyzing mechanical, thermal and transport properties of various structural materials such as metals, cement/concrete, polymers, composites, wood, thin films, and more.

Computational approaches based on artificial intelligence and machine learning methods as complementary tools to the physics-based multiscale techniques are discussed as are modeling techniques for additively manufactured structural materials. Special attention is paid to how these methods can be used to develop the next generation of sustainable, resilient and environmentally-friendly structural materials, with a specific emphasis on bridging the atomistic and continuum modeling scales for these materials. Synthesizes the latest cutting-edge computational multiscale modeling techniques for an array of structural materials Emphasizes the foundations of the field and offers practical guidelines for modeling material systems with well-established techniques Covers methods for calculating and analyzing mechanical, thermal and transport properties of various structural materials such as metals, cement/concrete, polymers, composites, wood, and more Highlights underlying theory, emerging areas, future directions and various applications of the modeling methods covered Discusses the integration of multiscale modeling and artificial intelligence