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Data Centric Design for Microstructural Materials Systems

Description:

Materials science has been central to human advancement since time immemorial. There has always been curiosity around studying the processes required to extract materials, examine their structure, and ultimately tailor their properties to meet human needs. Over the last few centuries, the ability to tailor material properties was driven by...

Keyword:

Gaussian Process, Mixed Variable Machine Learning, Data Centric Design, Multicriteria Optimization, and Microstructure

Subject:

Materials Science, Statistics, and Design

Creator:

Iyer, Akshay

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

02/02/2022

Date Created:

2021-01-01

Resource Type:

Dissertation

Alternate Identifier:

etdadmin_upload_851800 and http://dissertations.umi.com/northwestern:15801
Quantification of Microstructure Induced Uncertainty in Multiscale Materials with Random Processes

Description:

The heart of computational materials science lies in providing fundamental insights and understanding of materials behavior and properties across different scales. The significance of this task is highlighted by the Materials Genome Initiative and the emergence of computational tools and frameworks such as materials by design, microstructure sensitive design, and...

Keyword:

random Process, Multiscale simulation, Microstructure, Gaussian process, and Uncertainty

Subject:

Materials Science, Statistics, and Mechanical engineering

Creator:

Bostanabad, Ramin

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

02/12/2020

Date Created:

2019-01-01

Resource Type:

Dissertation

Alternate Identifier:

http://dissertations.umi.com/northwestern:14508 and etdadmin_upload_638165

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Data Centric Design for Microstructural Materials Systems

Quantification of Microstructure Induced Uncertainty in Multiscale Materials with Random Processes

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