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Modeling Complex Material Systems Using Stochastic Reconstruction and Lattice Particle Simulation.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Modeling Complex Material Systems Using Stochastic Reconstruction and Lattice Particle Simulation./
作者:	Xu, Yaopengxiao.
面頁冊數:	1 online resource (115 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.
標題:	Petroleum engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9780355929850

Modeling Complex Material Systems Using Stochastic Reconstruction and Lattice Particle Simulation.
Xu, Yaopengxiao.

Modeling Complex Material Systems Using Stochastic Reconstruction and Lattice Particle Simulation. - 1 online resource (115 pages)

Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.

Thesis (Ph.D.)--Arizona State University, 2018.

Includes bibliographical references

In this dissertation, three complex material systems including a novel class of hyperuniform composite materials, cellularized collagen gel and low melting point alloy (LMPA) composite are investigated, using statistical pattern characterization, stochastic microstructure reconstruction and micromechanical analysis. In Chapter 1, an introduction of this report is provided, in which a brief review is made about these three material systems. In Chapter 2, detailed discussion of the statistical morphological descriptors and a stochastic optimization approach for microstructure reconstruction is presented. In Chapter 3, the lattice particle method for micromechanical analysis of complex heterogeneous materials is introduced. In Chapter 4, a new class of hyperuniform heterogeneous material with superior mechanical properties is investigated. In Chapter 5, a bio-material system, i.e., cellularized collagen gel is modeled using correlation functions and stochastic reconstruction to study the collective dynamic behavior of the embed tumor cells. In chapter 6, LMPA soft robotic system is generated by generalizing the correlation functions and the rigidity tunability of this smart composite is discussed. In Chapter 7, a future work plan is presented.

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

Mode of access: World Wide Web

ISBN: 9780355929850Subjects--Topical Terms:

896906
Petroleum engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Modeling Complex Material Systems Using Stochastic Reconstruction and Lattice Particle Simulation.
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300 $a 1 online resource (115 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.
500 $a Adviser: Yang Jiao.
502 $a Thesis (Ph.D.)--Arizona State University, 2018.
504 $a Includes bibliographical references
520 $a In this dissertation, three complex material systems including a novel class of hyperuniform composite materials, cellularized collagen gel and low melting point alloy (LMPA) composite are investigated, using statistical pattern characterization, stochastic microstructure reconstruction and micromechanical analysis. In Chapter 1, an introduction of this report is provided, in which a brief review is made about these three material systems. In Chapter 2, detailed discussion of the statistical morphological descriptors and a stochastic optimization approach for microstructure reconstruction is presented. In Chapter 3, the lattice particle method for micromechanical analysis of complex heterogeneous materials is introduced. In Chapter 4, a new class of hyperuniform heterogeneous material with superior mechanical properties is investigated. In Chapter 5, a bio-material system, i.e., cellularized collagen gel is modeled using correlation functions and stochastic reconstruction to study the collective dynamic behavior of the embed tumor cells. In chapter 6, LMPA soft robotic system is generated by generalizing the correlation functions and the rigidity tunability of this smart composite is discussed. In Chapter 7, a future work plan is presented.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Petroleum engineering. $3 896906
655 7 $a Electronic books. $2 local $3 554714
690 $a 0765
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Arizona State University. $b Materials Science and Engineering. $3 845715
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10792249 $z click for full text (PQDT)