Article ID Journal Published Year Pages File Type
172484 Computers & Chemical Engineering 2014 10 Pages PDF
Abstract

•Serial reacting flow code was parallelized using multi-cores and GPUs.•OpenMP constructs are multi-threading and was used for surface chemistry.•Multi-threading was used for material property calculations and species equations.•Linear solvers were accelerated using GPUs.•4–5× speedup was attained for multi-channel catalytic combustor simulation.

Computational Fluid Dynamic modeling of full-scale monolithic catalytic reactors has remained elusive due to the extreme computational requirements. While simulation of full-scale catalytic reactors would require domain decomposition based parallelism and use of multiple central processing units, significant performance enhancement can be achieved by fully utilizing the compute resources available within each node in emerging architectures. Here, a serial reacting flow solver was used as a starting point. Performance was enhanced using multi-threading for acceleration of surface chemistry, material properties calculations, and species equation solvers, and using graphical processing units for acceleration of the linear solvers and pre-conditioners. Of the two test cases presented here, the largest test case entails steady-state calculations for catalytic methane–air combustion with 22 reaction steps and 19 species within a 13-channel catalytic monolith reactor discretized using 313,872 control volumes. For this particular test case, a speed-up factor of about 4.5 over serial calculations is noted.

Related Topics
Physical Sciences and Engineering Chemical Engineering Chemical Engineering (General)
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