Fluidic Topology Optimization with an Anisotropic Mixture Model
We present a topology optimization pipeline for designing Stokes-flow fluidic systems. Our method automatically creates the structure of this fluidic twister on an 100 × 100 × 100 grid after optimizing nearly 4,000,000 decision variables. The goal of this device is to generate a swirl flow at its outlet, given a constant flow flushing from its inlet. Our method automatically synthesizes a propeller-like structure to facilitate the vortex generation near the outlet.
Abstract
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 two million design parameters.
Demos
For details refer to the paper Sec 7. Applications. Below we show three design problems: Twister, Tree Diffuser and Circuit. We visualize the final design and the design domain for each of the problem.
Twister
Domain Size: 100x100x100
Tree Diffuser
Domain Size: 80x80x80
Circuit
Domain Size: 80x80x80
Demo Video
Presentation
Acknowledgement
Yifei Li acknowledges the emotional support from 🐱🐈 Yihui Li . Wojciech Matusik acknowledges the funding support from NSF IIS-2106962 and the Defense Advanced Research Projects Agency (DARPA) under grant No. FA8750-20-C-0075. Bo Zhu acknowledges the funding supports from NSF IIS-2106733. Eftychios Sifakis acknowledges the funding supports from NSF IIS-2106768, IIS-2008584, IIS-1763638.
Citation
@article{li2022anisotropicStokes,
author = {Li, Yifei and Du, Tao and Grama Srinivasan, Sangeetha and Wu, Kui and Zhu, Bo and Sifakis, Eftychios and Matusik, Wojciech},
title = {Fluidic Topology Optimization with an Anisotropic Mixture Model},
year = {2022},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
issn = {0730-0301},
url = {https://doi.org/10.1145/3550454.3555429},
doi = {10.1145/3550454.3555429},
abstract = {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 two million design parameters.},
journal = {ACM Trans. Graph.},
month = {nov},
articleno = {239},
numpages = {14},
keywords = {Topology optimization, Stokes flow, computational design, fluidic system design}
}
Keywords
fluidic devices, topology optimization, flow device optimization, differentiable simulation, physics simulation, computational fabrication, fluid topology optimization, Stokes flow optimization