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Fluidic Topology Optimization with an Anisotropic Mixture Model
by
Matusik, Wojciech
, Zhu, Bo
, Du, Tao
, Li, Yifei
, Sifakis, Eftychios
, Sangeetha Grama Srinivasan
, Wu, Kui
in
Boundary conditions
/ Constitutive models
/ Design optimization
/ Design parameters
/ Fluid flow
/ Fluid mechanics
/ Geometric accuracy
/ Industrial applications
/ Mathematical models
/ Representations
/ Stokes flow
/ Systems design
/ Topology optimization
2022
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Fluidic Topology Optimization with an Anisotropic Mixture Model
by
Matusik, Wojciech
, Zhu, Bo
, Du, Tao
, Li, Yifei
, Sifakis, Eftychios
, Sangeetha Grama Srinivasan
, Wu, Kui
in
Boundary conditions
/ Constitutive models
/ Design optimization
/ Design parameters
/ Fluid flow
/ Fluid mechanics
/ Geometric accuracy
/ Industrial applications
/ Mathematical models
/ Representations
/ Stokes flow
/ Systems design
/ Topology optimization
2022
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Do you wish to request the book?
Fluidic Topology Optimization with an Anisotropic Mixture Model
by
Matusik, Wojciech
, Zhu, Bo
, Du, Tao
, Li, Yifei
, Sifakis, Eftychios
, Sangeetha Grama Srinivasan
, Wu, Kui
in
Boundary conditions
/ Constitutive models
/ Design optimization
/ Design parameters
/ Fluid flow
/ Fluid mechanics
/ Geometric accuracy
/ Industrial applications
/ Mathematical models
/ Representations
/ Stokes flow
/ Systems design
/ Topology optimization
2022
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Fluidic Topology Optimization with an Anisotropic Mixture Model
Paper
Fluidic Topology Optimization with an Anisotropic Mixture Model
2022
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Overview
Fluidic devices are crucial components in many industrial applications involving fluid mechanics. Computational design of a high-performance fluidic system faces multifaceted challenges regarding its geometric representation and physical accuracy. We present a novel topology optimization method to design fluidic devices in a Stokes flow context. Our approach is featured by its capability in accommodating a broad spectrum of boundary conditions at the solid-fluid interface. Our key contribution is an anisotropic and differentiable constitutive model that unifies the representation of different phases and boundary conditions in a Stokes model, enabling a topology optimization method that can synthesize novel structures with accurate boundary conditions from a background grid discretization. We demonstrate the efficacy of our approach by conducting several fluidic system design tasks with over four million design parameters.
Publisher
Cornell University Library, arXiv.org
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