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Modeling Complex Material Systems Us...

Xu, Yaopengxiao.

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

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Modeling Complex Material Systems Using Stochastic Reconstruction and Lattice Particle Simulation./
作者:	Xu, Yaopengxiao.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	115 p.
附註:	Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.
Contained By:	Dissertation Abstracts International79-09B(E).
標題:	Petroleum engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10792249
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. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 115 p.

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

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

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.

ISBN: 9780355929850Subjects--Topical Terms:

566616
Petroleum engineering.

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