MARC보기
LDR00000nam u2200205 4500
001000000433998
00520200226135141
008200131s2019 ||||||||||||||||| ||eng d
020 ▼a 9781088371060
035 ▼a (MiAaPQ)AAI22588748
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 620
1001 ▼a Cheng, Lin.
24510 ▼a Functionally Graded Lattice Infill and Cooling Channel Design Optimization for Additive Manufacturing.
260 ▼a [S.l.]: ▼b University of Pittsburgh., ▼c 2019.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2019.
300 ▼a 348 p.
500 ▼a Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
500 ▼a Advisor: To, Albert C.
5021 ▼a Thesis (Ph.D.)--University of Pittsburgh, 2019.
506 ▼a This item must not be sold to any third party vendors.
520 ▼a To realize the full potential of additive manufacturing (AM) techniques, a lattice structure design optimization methodology is proposed to design functionally graded lattice structures, in order to achieve optimal performance while satisfying manufacturing constraints. A lattice structure topology optimization (LSTO) method is first proposed and the framework includes three key steps: (1) Asymptotic homogenization (AH) is developed to calculate effective properties of 3D printed lattice materials, such as elastic modulus, yield strength, thermal conductivity and forced convection heat transfer coefficient
590 ▼a School code: 0178.
650 4 ▼a Mechanical engineering.
650 4 ▼a Engineering.
690 ▼a 0548
690 ▼a 0537
71020 ▼a University of Pittsburgh. ▼b Swanson School of Engineering.
7730 ▼t Dissertations Abstracts International ▼g 81-04B.
773 ▼t Dissertation Abstract International
790 ▼a 0178
791 ▼a Ph.D.
792 ▼a 2019
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15493119 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 202002 ▼f 2020
990 ▼a ***1008102
991 ▼a E-BOOK