國立虎尾科技大學 |

Fine-Scale Structure Design for 3D Printing.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Fine-Scale Structure Design for 3D Printing./
作者:	Panetta, Francis Julian.
面頁冊數:	1 online resource (186 pages)
附註:	Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
標題:	Computer science. -
電子資源:	click for full text (PQDT)
ISBN:	9780355128741

Fine-Scale Structure Design for 3D Printing.
Panetta, Francis Julian.

Fine-Scale Structure Design for 3D Printing. - 1 online resource (186 pages)

Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.

Thesis (Ph.D.)--New York University, 2017.

Includes bibliographical references

Modern additive fabrication technologies can manufacture shapes whose geometric complexities far exceed what existing computational design tools can analyze or optimize. At the same time, falling costs have placed these fabrication technologies within the average consumer's reach. Especially for inexpert designers, new software tools are needed to take full advantage of 3D printing technology.

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

Mode of access: World Wide Web

ISBN: 9780355128741Subjects--Topical Terms:

573171
Computer science.
Index Terms--Genre/Form:

554714
Electronic books.

Fine-Scale Structure Design for 3D Printing.
LDR:04328ntm a2200421K 4500 001 914100
005 20180703084421.5
006 m o u
007 cr mn||||a|a||
008 190606s2017 xx obm 000 0 eng d
020 $a 9780355128741
035 $a (MiAaPQ)AAI10261771
035 $a (MiAaPQ)nyu:12973
035 $a AAI10261771
040 $a MiAaPQ $b eng $c MiAaPQ
100 1 $a Panetta, Francis Julian. $3 1187201
245 1 0 $a Fine-Scale Structure Design for 3D Printing.
264 0 $c 2017
300 $a 1 online resource (186 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: 78-12(E), Section: B.
500 $a Adviser: Denis Zorin.
502 $a Thesis (Ph.D.)--New York University, 2017.
504 $a Includes bibliographical references
520 $a Modern additive fabrication technologies can manufacture shapes whose geometric complexities far exceed what existing computational design tools can analyze or optimize. At the same time, falling costs have placed these fabrication technologies within the average consumer's reach. Especially for inexpert designers, new software tools are needed to take full advantage of 3D printing technology.
520 $a This thesis develops such tools and demonstrates the exciting possibilities enabled by fine-tuning objects at the small scales achievable by 3D printing. The thesis applies two high-level ideas to invent these tools: two-scale design and worst-case analysis.
520 $a The two-scale design approach addresses the problem that accurately simulating---let alone optimizing---the full-resolution geometry sent to the printer requires orders of magnitude more computational power than currently available. However, we can decompose the design problem into a small-scale problem (designing tileable structures achieving a particular deformation behavior) and a macro-scale problem (deciding where to place these structures in the larger object). This separation is particularly effective, since structures for every useful behavior can be designed once, stored in a database, then reused for many different macroscale problems.
520 $a Worst-case analysis refers to determining how likely an object is to fracture by studying the worst possible scenario: the forces most efficiently breaking it. This analysis is needed when the designer has insufficient knowledge or experience to predict what forces an object will undergo, or when the design is intended for use in many different scenarios unknown a priori.
520 $a The thesis begins by summarizing the physics and mathematics necessary to rigorously approach these design and analysis problems. Specifically, the second chapter introduces linear elasticity and periodic homogenization.
520 $a The third chapter presents a pipeline to design microstructures achieving a wide range of effective isotropic elastic material properties on a single-material 3D printer. It also proposes a macroscale optimization algorithm placing these microstructures to achieve deformation goals under prescribed loads.
520 $a The thesis then turns to worst-case analysis, first considering the macroscale problem: given a user's design, the fourth chapter aims to determine the distribution of pressures over the surface creating the highest stress at any point in the shape. Solving this problem exactly is difficult, so we introduce two heuristics: one to focus our efforts on only regions likely to concentrate stresses and another converting the pressure optimization into an efficient linear program.
520 $a Finally, the fifth chapter introduces worst-case analysis at the microscopic scale, leveraging the insight that the structure of periodic homogenization enables us to solve the problem exactly and efficiently. Then we use this worst-case analysis to guide a shape optimization, designing structures with prescribed deformation behavior that experience minimal stresses in generic use.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Computer science. $3 573171
650 4 $a Applied mathematics. $3 1069907
650 4 $a Materials science. $3 557839
655 7 $a Electronic books. $2 local $3 554714
690 $a 0984
690 $a 0364
690 $a 0794
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a New York University. $b Computer Science. $3 1184382
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10261771 $z click for full text (PQDT)