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Microstructure-sensitive design of a compliant beam

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TLDR
In this article, the authors considered polycrystalline microstructure as a continuous design variable and used a spectral representation space for the design of a compliant fixed-guided beam.
Abstract
We show that mechanical design can be conducted where consideration of polycrystalline microstructure as a continuous design variable is facilitated by use of a spectral representation space. Design of a compliant fixed-guided beam is used as a case study to illustrate the main tenets of the new approach, called microstructure-sensitive design (MSD). Selection of the mechanical framework for the design (e.g., mechanical constitutive model) dictates the dimensionality of the pertinent representation. Microstructure is considered to be comprised of basic elements that belong to the material set. For the compliant beam problem, these are uni-axial distribution functions. The universe of pertinent microstructures is found to be the convex hull of the material set, and is named the material hull. Design performance, in terms of specified design objectives and constraints, is represented by one or more surfaces (often hyperplanes) of finite dimension that intersect the material hull. Thus, the full range of microstructure, and concomitant design performance, can be exploited for any material class. Optimal placement of the salient iso-property surfaces within the material hull dictates the optimal set of microstructures for the problem. Extensions of MSD to highly constrained design problems of higher dimension is also described.

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Microstructure Sensitive Design for Performance Optimization

TL;DR: This review presents the MSD framework in the context of both the engineering advances that have led to its creation, and those that complement or provide alternative methods for design of materials (meaning ‘optimization of material structure’ in this context).
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Key computational modeling issues in Integrated Computational Materials Engineering

TL;DR: Computational and information aspects of design of materials with hierarchical microstructures are explored and key underdeveloped elements essential to supporting ICME are identified.
Journal ArticleDOI

A predictive machine learning approach for microstructure optimization and materials design

TL;DR: A systematic framework consisting of random data generation, feature selection and classification algorithms is developed and experiments show that this framework outperforms traditional optimization methods with the average running time reduced by as much as 80% and with optimality that would not be achieved otherwise.
Journal ArticleDOI

Reduced-order structure-property linkages for polycrystalline microstructures based on 2-point statistics

TL;DR: In this article, a novel framework is described for extracting S-P linkages in polycrystalline microstructures that are obtained using 2-point spatial correlations to quantify the material's microstructure, and principal component analysis (PCA) to represent this information in a reduced dimensional space.
References
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Book

Theory of Dislocations

TL;DR: Dislocations in Isotropic Continua: Effects of Crystal Structure on Dislocations and Dislocation-Point-Defect Interactions at Finite temperatures.
Journal ArticleDOI

The Elastic Behaviour of a Crystalline Aggregate

TL;DR: The connection between the elastic behavior of an aggregate and a single crystal is considered in this article, with special reference to the theories of Voigt, Reuss, and Huber and Schmid.
Book

Interfaces in Crystalline Materials

TL;DR: The geometry of interfaces Dislocation for interfaces Models of interatomic forces at interfaces Models and experimental observations of structure Thermodynamics of interfaces Interface phases and phase transitions Segregation of solute atoms to interfaces Diffusion at interfaces Conservative motion of interfaces: interfaces as sources/sinks for diffusional fluxes.