Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session G16: Extreme Mechanics
11:30 AM–2:30 PM,
Tuesday, March 7, 2023
Room: Room 208
Sponsoring
Unit:
DSOFT
Chair: Jayson Paulose, University of Oregon
Abstract: G16.00004 : An implicit simulation framework to handle frictional contact in elastic rods*
12:06 PM–12:18 PM
Presenter:
Dezhong Tong
(University of California, Los Angeles)
Authors:
Dezhong Tong
(University of California, Los Angeles)
Andrew Choi
(University of California, Los Angeles)
Jungseock Joo
(University of California, Los Angeles)
Mohammad Khalid Jawed
(University of California, Los Angeles)
Mathematically, frictional contact is usually regarded as constraints for a physical system's equations of motion (EOM). Researchers in mechanics and computer graphics implemented different ways to incorporate such constraints in EOMs to achieve better performance in computation speed and physical accuracy. Commonly, the constraints of frictional contact are usually treated as additional variables and computed independently at every time step in a dynamics system. Although physical accuracy is guaranteed, such methods decrease the computation speed of the simulation a lot. We propose a fully implicit penalty-based frictional contact framework, Implicit Contact Model (IMC), which combines the constraints with the degrees of freedom (DOF)s directly. IMC can capture the frictional contact responses in rod-rod contact scenarios with good efficiency and accuracy. We showcase IMC’s performance in achieving physically accurate results for knot-tying cases and visually realistic results for a challenging and novel contact scenario of flagella bundling in fluid medium. In addition, we offer a side-by-side comparison with Incremental Potential Contact (IPC), a state-of-the-art contact handling algorithm, which has excellent performance in computation efficiency and visual realism. The comparison shows that IMC has comparable performance to IPC while faster converging speed.
*We acknowledge support from the National Science Foundation (US) under Grant Numbers IIS-1925360, CAREER-2047663, CMMI-2101751, and CMMI-2053971.
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