| Summary: | 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.
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