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Hierarchical Materials Informatics
Novel Analytics for Materials Data
- 1st Edition - August 6, 2015
- Author: Surya R. Kalidindi
- Language: English
- Hardback ISBN:9 7 8 - 0 - 1 2 - 4 1 0 3 9 4 - 8
- eBook ISBN:9 7 8 - 0 - 1 2 - 4 1 0 4 5 5 - 6
Custom design, manufacture, and deployment of new high performance materials for advanced technologies is critically dependent on the availability of invertible, high fidelity, st… Read more
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Request a sales quoteCustom design, manufacture, and deployment of new high performance materials for advanced technologies is critically dependent on the availability of invertible, high fidelity, structure-property-processing (SPP) linkages. Establishing these linkages presents a major challenge because of the need to cover unimaginably large dimensional spaces. Hierarchical Materials Informatics addresses objective, computationally efficient, mining of large ensembles of experimental and modeling datasets to extract this core materials knowledge. Furthermore, it aims to organize and present this high value knowledge in highly accessible forms to end users engaged in product design and design for manufacturing efforts. As such, this emerging field has a pivotal role in realizing the goals outlined in current strategic national initiatives such as the Materials Genome Initiative (MGI) and the Advanced Manufacturing Partnership (AMP). This book presents the foundational elements of this new discipline as it relates to the design, development, and deployment of hierarchical materials critical to advanced technologies.
- Addresses a critical gap in new materials research and development by presenting a rigorous statistical framework for the quantification of microstructure
- Contains several case studies illustrating the use of modern data analytic tools on microstructure datasets (both experimental and modeling)
Materials scientists and engineers and mechanical engineers and researchers across academia, government and industry who are working in the area of new materials design, development and deployment; graduate students in materials science and engineering.
- Acknowledgments
- 1. Materials, Data, and Informatics
- 1.1 PSP Linkages
- 1.2 Material Internal Structure
- 1.3 Inverse Problems in Materials and Process Design
- 1.4 Data, Information, Knowledge, and Wisdom
- 1.5 Digital Representations
- 1.6 Hierarchical Materials Informatics
- References
- 2. Microstructure Function
- 2.1 Length Scales
- 2.2 Local States and Local State Spaces
- 2.3 Microstructure Function
- 2.4 Digital Representation of Functions
- 2.5 Digital Representation of Microstructure Function
- 2.6 Spectral Representations of Microstructure Function
- References
- 3. Statistical Quantification of Material Structure
- 3.1 Spatial Correlations
- 3.2 Computation and Visualization of 2-Point Spatial Correlations
- 3.3 Higher Order Spatial Correlations
- 3.4 Reconstructions of Microstructures from Spatial Correlations
- 3.5 Reconstructions from Partial Sets of 2-Point Statistics
- 3.6 Representative Microstructures
- References
- 4. Reduced-Order Representations of Spatial Correlations
- 4.1 Principal Component Analyses
- 4.2 Application to Spatial Correlations
- 4.3 Case Study: α−β Ti Micrographs
- 4.4 Case Study: Nonmetallic Inclusions/Steel Composite System
- 4.5 Case Study: MD Simulation Datasets
- References
- 5. Generalized Composite Theories
- 5.1 Conventions and Notations
- 5.2 Review of Continuum Mechanics
- 5.3 Concept of Homogenization
- 5.4 Higher Order Homogenization Theory
- References
- 6. Structure–Property Linkages
- 6.1 Data-Driven Framework for Homogenization Linkages
- 6.2 Main Steps of the Data-Driven Framework for Homogenization Linkages
- 6.3 Case Study: Microstructure–Property Relationships in Porous Transport Layers
- 6.4 Case Study: Structure-Property Linkages in Inclusions/Steel Composites
- 6.5 MKS: Data-Driven Framework for Localization Linkages
- 6.6 Case Study: MKS for Elastic Response of Composites
- 6.7 Case Study: MKS for Elastic Response of Higher Contrast Composites
- 6.8 Case Study: MKS for Elastic Response of Polycrystals
- 6.9 Case Study: MKS for Perfectly Plastic Response of Composites
- References
- 7. Process–Structure Linkages
- 7.1 Mathematical Framework
- 7.2 Case Study: Microstructure Evolution Using Phase-Field Models
- 7.3 Case Study: DFT Databases for Crystal Plasticity Computations
- References
- 8. Materials Innovation Cyberinfrastructure
- References
- Index
- No. of pages: 230
- Language: English
- Edition: 1
- Published: August 6, 2015
- Imprint: Butterworth-Heinemann
- Hardback ISBN: 9780124103948
- eBook ISBN: 9780124104556
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