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      Model Reduction of Muscle-Driven Tissue Models

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      WIDING-THESIS-2018.pdf (6.784Mb)
      Date
      2018-11-06
      Author
      Widing, Erik H 1987-
      ORCID
      0000-0001-9545-2154
      Type
      Thesis
      Degree Level
      Masters
      Metadata
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      Abstract
      Biomechanical simulations are a necessary tool for a proper understanding of biomechanics and hence are subject to intense research. One field that relies on this research is articulatory speech synthesis as it attempts to simulate the physics of the speech production process. Out of the many aspects involved, muscle driven tissue is one of the most important as it is required to simulate the deformable structures of the vocal tract. Modelling of muscle driven tissue requires continuum models of high complexity for the purpose of accuracy. On the other hand, time-efficient models are desirable in order to provide fast simulations which enable the user to test input parameters interactively. These requirements impose limitations on each other as the time-efficiency of a model is reduced with increasing complexity, hence techniques that can bridge the gap between these requirements are needed. This thesis attempts to bridge this gap through two major contributions. Model reduction techniques, that up until now have only been applied to inactive materials, have been implemented and tested for muscle driven tissue models. The implementation has been made in a general way to ensure that it can be used for biomechanical simulations in other fields than articulatory speech synthesis. In addition, the implementation has been made such that it can handle more advanced simulations than those investigated in this thesis. The simulations show acceptable but not ideal accuracy in both dynamic simulations and in measurements of equilibrium configurations. In addition, the reduced simulations using hyperreduction show good speedup for the more complex models investigated.
      Degree
      Master of Science (M.Sc.)
      Department
      Computer Science
      Program
      Computer Science
      Supervisor
      Stavness, Ian
      Committee
      Neufeld, Eric; Osgood, Nathaniel; Dolovich, Allan T
      Copyright Date
      September 2018
      URI
      http://hdl.handle.net/10388/11492
      Subject
      Model Reduction
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      • Graduate Theses and Dissertations
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