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Watching viscous flow, but faster

A state-of-the-art methodology for modeling the conduct of liquids described by KAUST researchers represents a breakthrough in computational velocity for viscous liquids. Credit: KAUST.

By redesigning how fluids are simulated, KAUST researchers have demonstrated a greater than tenfold velocity improve on the earlier cutting-edge for slow-flowing viscous liquids.

Modeling the conduct of liquids is necessary for a variety of purposes, from industrial processes and medical devices to computer graphics and visible simulations.

Nevertheless, regardless of a few years of growth and identified physics relationship again over 100 years, the flexibility to precisely simulate liquid movement stays one of the crucial computationally difficult points of making digital replicas of the true world.

It is because the movement and conduct of liquids is decided by each the strain distribution via the liquid and, within the case of thick viscous liquids, the pressure-dependent inner resistance to that movement. Exactly calculating these complicated and time-varying distributions may be very computationally intensive, and so many optimization schemes have been developed to hurry up this calculation course of on the expense of accuracy.

Now, Han Shao, Libo Huang and Dominik Michels have made a big breakthrough in computational velocity for viscous liquids by combining environment friendly arithmetic with the low-level parallel computational capabilities of contemporary laptop processors.

“The simulation of fluid dynamics has been an evergreen topic in computer graphics research for many years, and the existing methods still have much potential for performance improvement,” says Shao. “In this research, we propose the Unsmoothed Aggregation Algebraic Multigrid method as a sophisticated multigrid framework that fully utilizes modern CPU features and introduces new numerical methods.”

The analysis staff began with the concept extra environment friendly mathematical strategies could possibly be used for the basic matrix-vector calculations wanted to compute the strain distribution via the liquid, in addition to simplifying the calculation of trivial values on the fluid boundary.

Basically, the researchers had been capable of present that when many values within the matrices are the identical, as is the case within the bulk of a viscous liquid, a single calculation can be utilized throughout many parts permitting many calculations to be skipped.

The staff then harnessed the synergy of mixing their environment friendly matrix-vector calculation code with the one instruction a number of knowledge (SIMD) functionality of contemporary CPUs, which permits the identical operation to be utilized to many knowledge inputs on the identical time. This enabled them to assemble a modeling method that might simulate viscous fluids as much as 15 instances sooner than the present cutting-edge (the Houdini physics engine).

“Our framework can be used immediately by industrial users for faster simulation, using the code available on our project website,” Shao says.

The research was revealed in ACM Transactions on Graphics.

In specially coated tubes, the more viscous a liquid is, the faster it flows

Extra info:
Han Shao et al, A quick unsmoothed aggregation algebraic multigrid framework for the large-scale simulation of incompressible movement, ACM Transactions on Graphics (2022). DOI: 10.1145/3528223.3530109

Watching viscous movement, however sooner (2022, July 28)
retrieved 28 July 2022

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