Tag: Journal of Computational Physics

New publication in the Journal of Computational Physics

~ Adam ~ Leave a comment

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 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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