Fluidic Topology Optimization with an Anisotropic Mixture Model

Sun, 18 Sep 2022 00:00:00 +0000

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

DiffCloth: Differentiable Cloth Simulation with Dry Frictional Contact

Fri, 01 Apr 2022 00:00:00 +0000

Keywords

diffcloth, projective dynamics, jacobi solver, cloth simulation, differentiable simulation, physics simulation, inverse problems

Code 💻

Follow our Github repository Diffcloth

Demos

For details refer to the paper Sec 6. Applications.

Hat: Trajectory Optimization

Optimize manipulator end effector trajectories to move the hat onto the head.
1737 Dof, h=1/100s, 400 Timesteps, 18 Design Parameters

Sock: Trajectory Optimization

Optimize manipulator end effector trajectories to put on the sock.
3165 Dof, h=1/160s, 400 Timesteps, 36 Design Parameters

Hat-Controller: Closed-Loop Control

We train a generalizable closed-loop controller that can put on the hat from different initial positions.
1737 Dof, h=1/100s, 400 Timesteps, 117126 Design Parameters

Dress: Inverse Design

Optimize dress material parameters so that the spinning angle of the dress is 50 degrees.
10902 Dof, h=1/120s, 125 Timesteps, 2 Design Parameters

Sphere: System Identification

Optimize the fricitonal coefficient between the sphere and the cloth to match target trajectory.
1875 Dof, h=1/180s, 350 Timesteps, 1 Design Parameters

T-shirt: System Identification

Optimize wind model and cloth material parameters to match target trajectory.
4278 Dof, h=1/90s, 250 Timesteps, 6 Design Parameters

Demo

Presentation

Citation

@article{li2022diffcloth,
author = {Li, Yifei and Du, Tao and Wu, Kui and Xu, Jie and Matusik, Wojciech},
title = {DiffCloth: Differentiable Cloth Simulation with Dry Frictional Contact},
year = {2022},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
issn = {0730-0301},
url = {https://doi.org/10.1145/3527660},
doi = {10.1145/3527660},
abstract = {Cloth simulation has wide applications in computer animation, garment design, and robot-assisted dressing. This work presents a differentiable cloth simulator whose additional gradient information facilitates cloth-related applications. Our differentiable simulator extends a state-of-the-art cloth simulator based on Projective Dynamics (PD) and with dry frictional contact&nbsp;[Ly et&nbsp;al. 2020]},
note = {Just Accepted},
journal = {ACM Trans. Graph.},
month = {mar},
keywords = {cloth simulation, differentiable simulation, Projective Dynamics}
}

Acknowledgement

We thank Marco Renedo for his helpful discussions on the preconditioners, Junbang Liang for his help with running the baseline comparison code, and the anonymous reviewers for their helpful comments. This work was supported in part by the Defense Advanced Research Projects Agency (DARPA) under grant No. FA8750-20-C-0075.

simulation | Yifei Li

Fluidic Topology Optimization with an Anisotropic Mixture Model

Demos

Twister

Tree Diffuser

Circuit

Demo Video

Presentation

Acknowledgement

Citation

Keywords

DiffCloth: Differentiable Cloth Simulation with Dry Frictional Contact

Keywords

Code 💻

Demos

Hat: Trajectory Optimization

Sock: Trajectory Optimization

Hat-Controller: Closed-Loop Control

Dress: Inverse Design

Sphere: System Identification

T-shirt: System Identification

Demo

Presentation

Citation

Acknowledgement