Topic
Integrated computational materials engineering
About: Integrated computational materials engineering is a research topic. Over the lifetime, 431 publications have been published within this topic receiving 10600 citations.
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TL;DR: In this paper, numerical implementation of materials science principles provides a hierarchy of computational models defining subsystem design parameters that are integrated, through computational thermodynamics, in the comprehensive design of materials as interactive systems.
Abstract: A systems approach that integrates processing, structure, property, and performance relations has been used in the conceptual design of multilevel-structured materials. For high-performance alloy steels, numerical implementation of materials science principles provides a hierarchy of computational models defining subsystem design parameters that are integrated, through computational thermodynamics, in the comprehensive design of materials as interactive systems. Designed properties combine strength, toughness, and resistance to impurity embrittlement. The methods have also been applied to nonferrous metals, ceramics, and polymers.
1,084 citations
TL;DR: In this paper, the typical mode of and basic procedures for applying machine learning in materials science are outlined and compared, and the current research status is reviewed with regard to applications of ML in material property prediction, in new materials discovery and for other purposes.
717 citations
TL;DR: In this article, the authors look at how data-driven techniques are playing a big role in deciphering processing-structure-property-performance relationships in materials, with illustrative examples of both forward models (property prediction) and inverse models (materials discovery).
Abstract: Our ability to collect “big data” has greatly surpassed our capability to analyze it, underscoring the emergence of the fourth paradigm of science, which is data-driven discovery. The need for data informatics is also emphasized by the Materials Genome Initiative (MGI), further boosting the emerging field of materials informatics. In this article, we look at how data-driven techniques are playing a big role in deciphering processing-structure-property-performance relationships in materials, with illustrative examples of both forward models (property prediction) and inverse models (materials discovery). Such analytics can significantly reduce time-to-insight and accelerate cost-effective materials discovery, which is the goal of MGI.
705 citations
TL;DR: In this article, the authors highlight some of the key aspects regarding materials qualification needs across the additive manufacturing (AM) spectrum, including various process-, microstructure-, and fracture-modeling activities in addition to integrating these with lifing activities targeting specific components.
Abstract: This overview highlights some of the key aspects regarding materials qualification needs across the additive manufacturing (AM) spectrum. AM technology has experienced considerable publicity and growth in the past few years with many successful insertions for non-mission-critical applications. However, to meet the full potential that AM has to offer, especially for flight-critical components (e.g., rotating parts, fracture-critical parts, etc.), qualification and certification efforts are necessary. While development of qualification standards will address some of these needs, this overview outlines some of the other key areas that will need to be considered in the qualification path, including various process-, microstructure-, and fracture-modeling activities in addition to integrating these with lifing activities targeting specific components. Ongoing work in the Advanced Manufacturing and Mechanical Reliability Center at Case Western Reserve University is focusing on fracture and fatigue testing to rapidly assess critical mechanical properties of some titanium alloys before and after post-processing, in addition to conducting nondestructive testing/evaluation using micro-computerized tomography at General Electric. Process mapping studies are being conducted at Carnegie Mellon University while large area microstructure characterization and informatics (EBSD and BSE) analyses are being conducted at Materials Resources LLC to enable future integration of these efforts via an Integrated Computational Materials Engineering approach to AM. Possible future pathways for materials qualification are provided.
435 citations
Book•
13 Feb 2007
TL;DR: The Materials 3e text as discussed by the authors is an introductory course in materials engineering text and resource for students developing skills and understanding of materials properties and selection for engineering applications, with a focus on visual communication.
Abstract: This is the essential materials engineering text and resource for students developing skills and understanding of materials properties and selection for engineering applications. Taking a unique design-led approach that is broader in scope than other texts, Materials 3e meets the curriculum needs of a wide variety of courses in the materials and design field, including introduction to materials science and engineering, engineering materials, materials selection and processing, and materials in design. This new edition retains its design-led focus and strong emphasis on visual communication while expanding its inclusion of the underlying science of materials to fully meet the needs of instructors teaching an introductory course in materials. Design-led approach motivates and engages students in the study of materials science and engineering through real-life case studies and illustrative applicationsHighly visual full color graphics facilitate understanding of materials concepts and propertiesChapters on materials selection and design are integrated with chapters on materials fundamentals, enabling students to see how specific fundamentals can be important to the design processFor instructors, a solutions manual, lecture slides, online image bank and materials selection charts for use in class handouts or lecture presentations are available at http: //textbooks.elsevier.com Links with the Cambridge Engineering Selector (CES EduPack), the powerful materials selection software. See www.grantadesign.com for information NEW TO THIS EDITION: Text and figures have been revised and updated throughoutThe number of worked examples has been increased by 50%The number of standard end-of-chapter exercises in the text has been doubledCoverage of materials and the environment has been updated with a new section on Sustainability and Sustainable Technology
384 citations