Tag: Computational fluid dynamics

New publication in the journal Physical Review Fluids

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Work I’ve recently done with my colleagues has just been published in the journal Physical Review Fluids. The paper, Continuity waves in resolved-particle simulations of fluidized beds, analyzes a series of computational simulations performed by software I developed that look a lot like this, only with more particles:

output
1,000 fluidized particles.

Though not at all obvious from this video, these particles are actually bumping into each other and sending waves of high particle density up the column even though the mean particle velocity is zero. This behavior had not previously been investigated in three-dimensional columns of fluid. We found many interesting details about the way these particles move around, including that a theory developed for one-dimensional motion still does a good job of predicting the speed of the high density waves in a three-dimensional setting.

Figure 10
Our 3D results (symbols) support existing 1D theory (lines) predicting the relationship between particle volume fraction (φ) and continuity wave speed (c).

Abstract:

The results of a fully resolved simulation of up to 2000 spheres suspended in a vertical liquid stream are analyzed by a method based on a truncated Fourier series expansion. It is shown that, in this way, it is possible to identify continuity (or kinematic) waves and to determine their velocity, which is found to closely agree with the theory of one-dimensional continuity waves based on the Richardson-Zaki drag correlation.

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New publication in the Journal of Computational Physics

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I’m excited to announce the publication of work with my colleagues in a new paper, Fully resolved simulation of particulate flows with particles-fluid heat transfer, in the Journal of Computational Physics. This paper describes an extension of my previous work, adding the ability to account for heat transfer between particles and the surrounding fluid.

Fig. 10
Time-dependence of the temperature of a particle immersed in a warmer uniform flow with Re = 50. The solid lines are the present results and the dashed lines the results of Balachandar, S., Ha, M. Y., 2001.

This is an especially important new capability because particle flows are so frequently used in industrial chemical processing applications where temperature must be closely controlled. Whether heat is being added to catalyze a chemical reaction or is a result of the chemical reaction itself, our new method is able to simulate this phenomenon accurately and efficiently.

Implemented to run on GPUs, our method can simulate thousands of particles, providing a new window though which we can work to improve our understanding of the behavior of particle flows. By learning more about particle flows, we can make existing chemical processing technologies faster, safer, and less expensive.

Abstract:

The Physalis method for the fully resolved simulation of particulate flows is extended to include heat transfer between the particles and the fluid. The particles are treated in the lumped capacitance approximation. The simulation of several steady and time-dependent situations for which exact solutions or exact balance relations are available illustrates the accuracy and reliability of the method. Some examples including natural convection in the Boussinesq approximation are also described.

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New publication in the Journal Computer Physics Communications

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My paper, GPU-centric resolved-particle disperse two-phase flow simulation using the Physalis method, has recently been published in the Journal Computer Physics Communications. The sibling to my previous paper, Resolved-particle simulation by the Physalis method: Enhancements and new capabilities, the current work more thoroughly details the algorithmic advancements I developed to improve the computational throughput of the Physalis method itself. As can be seen in the figure below, the largest simulations run more than 60 times faster when using an Nvidia Titan GPU than an Intel CPU alone.

sierakowski-2016-f9

Abstract:

We present work on a new implementation of the Physalis method for resolved-particle disperse two-phase flow simulations. We discuss specifically our GPU-centric programming model that avoids all device-host data communication during the simulation. Summarizing the details underlying the implementation of the Physalis method, we illustrate the application of two GPU-centric parallelization paradigms and record insights on how to best leverage the GPU’s prioritization of bandwidth over latency. We perform a comparison of the computational efficiency between the current GPU-centric implementation and a legacy serial-CPU-optimized code and conclude that the GPU hardware accounts for run time improvements up to a factor of 60 by carefully normalizing the run times of both codes.

New publication in the Journal of Computational Physics

~ Adam ~ 2 Comments

I’m excited to announce the publication of my new paper, Resolved-particle simulation by the Physalis method: Enhancements and new capabilities, in the Journal of Computational Physics. The paper summarizes the theory and numerical methods that I, along with my doctoral advisor Andrea Prosperetti, have refined and developed for the simulation of particles in a fluid flow (think sand kicked up by waves on a beach).

sed-duct-combined
A simulation of 2048 particles falling through a duct. The colors represent velocity magnitude, where blue is slow and red is fast. Image Copyright (c) 2016 Adam Sierakowski

The computer code, freely available for download at PhysalisCFD.org, is the first tool that performs such simulations using a graphics processing unit (GPU) as the primary computing engine. By using a GPU, simulations run up to 90 times faster than before, allowing us to simulate thousands of particles in the same amount of time it used to take to simulate ten.

Abstract:

We present enhancements and new capabilities of the Physalis method for simulating disperse multiphase flows using particle-resolved simulation. The current work enhances the previous method by incorporating a new type of pressure-Poisson solver that couples with a new Physalis particle pressure boundary condition scheme and a new particle interior treatment to significantly improve overall numerical efficiency. Further, we implement a more efficient method of calculating the Physalis scalar products and incorporate short-range particle interaction models. We provide validation and benchmarking for the Physalis method against experiments of a sedimenting particle and of normal wall collisions. We conclude with an illustrative simulation of 2048 particles sedimenting in a duct. In the appendix, we present a complete and self-consistent description of the analytical development and numerical methods.

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