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Data-driven Multi-scale Analyses of ...

Northwestern University.

Data-driven Multi-scale Analyses of Materials and Structures.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Data-driven Multi-scale Analyses of Materials and Structures./
作者:	Bessa, Miguel A.
面頁冊數:	1 online resource (110 pages)
附註:	Source: Dissertation Abstracts International, Volume: 78-02(E), Section: B.
Contained By:	Dissertation Abstracts International78-02B(E).
標題:	Mechanical engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9781369154153

Data-driven Multi-scale Analyses of Materials and Structures.
Bessa, Miguel A.

Data-driven Multi-scale Analyses of Materials and Structures. - 1 online resource (110 pages)

Source: Dissertation Abstracts International, Volume: 78-02(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

Data-driven research has the potential for groundbreaking achievements in the design of materials and large-scale engineering structures. A new data-driven computational framework for the design of heterogeneous materials is created. The framework recursively integrates design of experiments, efficient computational analyses of each design, and data mining. This enables the discovery of the influence of the microstructure and its building blocks on the macroscopic material behavior by creating a property-structure-performance feedback loop. The framework is applied to advanced composites by developing a high-fidelity multi-scale model for these materials and then using a general method that reduces the computational cost of the high-fidelity analyses called self-consistent clustering analysis. The overarching goal of this dissertation is to enable the future design of new materials with new capabilities.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369154153Subjects--Topical Terms:

557493
Mechanical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Data-driven Multi-scale Analyses of Materials and Structures.
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100 1 $a Bessa, Miguel A. $3 1180285
245 1 0 $a Data-driven Multi-scale Analyses of Materials and Structures.
264 0 $c 2016
300 $a 1 online resource (110 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertation Abstracts International, Volume: 78-02(E), Section: B.
500 $a Advisers: Wing K. Liu; Ted Belytschko.
502 $a Thesis (Ph.D.) $c Northwestern University $d 2016.
504 $a Includes bibliographical references
520 $a Data-driven research has the potential for groundbreaking achievements in the design of materials and large-scale engineering structures. A new data-driven computational framework for the design of heterogeneous materials is created. The framework recursively integrates design of experiments, efficient computational analyses of each design, and data mining. This enables the discovery of the influence of the microstructure and its building blocks on the macroscopic material behavior by creating a property-structure-performance feedback loop. The framework is applied to advanced composites by developing a high-fidelity multi-scale model for these materials and then using a general method that reduces the computational cost of the high-fidelity analyses called self-consistent clustering analysis. The overarching goal of this dissertation is to enable the future design of new materials with new capabilities.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Mechanical engineering. $3 557493
650 4 $a Aerospace engineering. $3 686400
650 4 $a Civil engineering. $3 561339
655 7 $a Electronic books. $2 local $3 554714
690 $a 0548
690 $a 0538
690 $a 0543
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Northwestern University. $b Mechanical Engineering. $3 1180174
773 0 $t Dissertation Abstracts International $g 78-02B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10160508 $z click for full text (PQDT)

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