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Eulerian finite volume method for musculoskeletal simulation and data-driven activation

University of British Columbia

This thesis describes a solid simulation method and its application to musculoskeletal simulation. The presented solid simulation method features Eulerian discretization and avoids mesh tangling during large deformation. Unlike existing Eulerian solid simulation methods, our method applies to elastoplastic material and volume-preserving material. To further increase the utility of Eulerian simulations for solids, we introduce Lagrangian modes to the simulation and present a new solver that handles close contact while simultaneously distributing motion between the Lagrangian and Eulerian modes. This Eulerian-on-Lagrangian method enables unbounded simulation domains and reduces the time step restrictions that often plague Eulerian simulation. We also introduce a framework for simulating the dynamics of musculoskeletal systems, with volumetric muscles and a novel muscle activation model. Muscles are simulated using the solid simulator developed and therefore enjoys volume preservation which is crucial for accurately capturing the dynamics of muscles and other biological tissues. Unlike previous work, in our system muscle deformation is tightly coupled to the dynamics of the skeletal system, and not added as an after effect. Our physiologically based muscle activation model utilizes knowledge of the active shapes of muscles, which can be manually drawn or easily obtained from medical imaging data. Finally we demonstrate results with models derived from MRI data and models designed for artistic effect.

Text

2014-01-10

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/44645

Computer Science

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/