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3D Printable Designs of Rigid and Deformable Models

Yao, Miaojun
http://rave.ohiolink.edu/etdc/view?acc_num=osu1502906675481174

Abstract Details

2017, Doctor of Philosophy, Ohio State University, Computer Science and Engineering.
3D printing has become increasingly popular in recent years, thanks to the substantial flexibility it provides to 3D designers and manufacturers. However, there are still some significant problems to be solved before 3D printing can be widely used in our daily life and the manufacturing industries. First, the high cost of printing material and printing time usually makes it unaffordable to 3D printer users. Second, the build volume of a 3D printer is limited and large objects have to be decomposed so each part can fit into the printer. When it comes to decomposition, problems arise such as how to arrange the parts in a container so the packed size can be minimized and how to achieve stable assembly of those parts. Finally, soft models are usually difficult to design when specific target deformed shapes are desired, due to the complex nonlinearity of elastic deformation. In this dissertation, we focus on solving those problems with novel 3D modeling approaches. First, we present a level-set-based system to divide a 3D model into multiple parts to achieve minimal packed size, as well as other partitioning qualities such as minimal stress load and surface detail alignment. A container structure is constructed meanwhile to facilitate the packing process. We find that this system can serve both space saving and fast printing purposes effectively. Second, we propose a computational framework to design an interlocking structure of a partitioned shell model given a mesh segmentation input. We search for the optimal installation order and installation directions of the pieces based on data-driven and simulation-based metrics, and build male and female connectors on the boundary between pieces. Both time and material can be significantly reduced when printing such partitioned shell models and the assembled object is strong against separation. Finally, we develop a new method to optimize the rest shape of an elastic model so that it can be deformed to a target shape. The algorithm iteratively runs a gradient descent step to optimize the rest shape and a Newton step to obtain quasistatic equilibrium, both of which can be easily parallelized on GPU. The performance can be further improved by not solving the steps exactly in every iteration. To prevent the volumetric mesh from degeneration, we introduce an embedded mesh scheme, where only the embedded surface mesh is changed during the optimization while the volumetric cage mesh is not. Our experiment shows that the method can handle various nonlinear elastic material models and deformation goals fast and robustly.
Huamin Wang (Advisor)
Yusu Wang (Committee Member)
Han-Wei Shen (Committee Member)
Brian Joseph (Other)
120 p.
Computer Engineering; Computer Science
3D printing, 3D packing, interlocking structure, shell modeling, shape partitioning, shape optimization, multi-phase level set, mesh segmentation, inverse elastic problem, GPU computing

Recommended Citations

Citations

  • Yao, M. (2017). 3D Printable Designs of Rigid and Deformable Models [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1502906675481174

    APA Style (7th edition)

  • Yao, Miaojun. 3D Printable Designs of Rigid and Deformable Models. 2017. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1502906675481174.

    MLA Style (8th edition)

  • Yao, Miaojun. "3D Printable Designs of Rigid and Deformable Models." Doctoral dissertation, Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1502906675481174

    Chicago Manual of Style (17th edition)

osu1502906675481174
514
© 2017, some rights reserved.Creative Commons License 3D Printable Designs of Rigid and Deformable Models by Miaojun Yao is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by The Ohio State University and OhioLINK.