Robust and accurate simulation of elastodynamics and contact / Minchen Li.

Format:

Book

Thesis/Dissertation

Author/Creator:

Li, Minchen, author.

Contributor:

Jiang, Chenfanfu, degree supervisor.

University of Pennsylvania. Department of Computer and Information Science, degree granting institution.

Language:

English

Subjects (All):

Computer science.

Mechanical engineering.

Computational physics.

Computer and Information Science--Penn dissertations.

Penn dissertations--Computer and Information Science.

Local Subjects:

Computer science.

Mechanical engineering.

Computational physics.

Computer and Information Science--Penn dissertations.

Penn dissertations--Computer and Information Science.

Genre:

Academic theses.

Physical Description:

1 online resource (233 pages)

Contained In:

Dissertations Abstracts International 82-07B.

Place of Publication:

[Philadelphia, Pennsylvania] : University of Pennsylvania ; Ann Arbor : ProQuest Dissertations & Theses, 2020.

Language Note:

English

System Details:

Mode of access: World Wide Web.

text file

Summary:

Simulating elastodynamics and contact in a robust and accurate way not only benefitsdesigning realistic and intriguing animations and visual effects in computer graphics,but is also essential for industrial design, robotics, mechanical engineering analysis, etc.However, existing methods are constructed under strong assumptions that limit theirapplication scenarios to a relatively narrow range, which also make the methods sensitiveto algorithmic parameters such that extensive parameter tuning often needs to be performedfor nearly each different example to obtain consistent quality results. To tackle thesechallenges, we propose a robust, accurate, and differentiable elastodynamics and contactsimulation framework that can always reliably produce consistent quality results for anycodimensional solids (volumes, shells, rods, and particles) in a wide range of material, timestep size, boundary condition, and resolution settings with interpenetration-free guaranteesbut do not require algorithmic parameter tuning. Based on solid theoretical foundations,our methods provide controllable trade-off between efficiency and accuracy for differentapplication scenarios. All the proposed features of our methods are thoroughly verified byperforming extensive experiments and analyses including comparisons to state-of-the-artmethods and ablation study on multiple design choices. Our framework frees designersfrom extensive parameter tuning as when traditional methods are used, enables simulatingbrand new phenomena that are never achieved before, and already demonstrate effectivenessin a broader range of application scenarios like robotics design and engineering analysis.

Notes:

Source: Dissertations Abstracts International, Volume: 82-07, Section: B.

Advisors: Jiang, Chenfanfu; Committee members: Norman Badler; Stephen Lane; Cynthia Sung; Danny Kaufman.

Department: Computer and Information Science.

Ph.D. University of Pennsylvania 2020.

Local Notes:

School code: 0175

ISBN:

9798557059640

Access Restriction:

Restricted for use by site license.

This item must not be sold to any third party vendors.