Turbulent uniformity fluctuations in automotive catalysts – A RANS vs DES assessment
Journal article, 2022

Attaining sufficient flow uniformity in catalytic aftertreatment systems is a major challenge for the automotive industry. Computational fluid dynamics (CFD) simulations offer means of analyzing and quantifying this flow uniformity in silico. In this work, predictions from numerical simulations of flow uniformity obtained using a conventional steady-state Reynolds-Averaged Navier-Stokes (RANS) approach are contrasted against comprehensive Detached Eddy Simulations (DES) where the large-scale turbulence is resolved in space and time. It is shown that the DES approach provides access to data on flow uniformity fluctuations that could be significant for the catalyst light-off behavior. However, the computational cost of the DES is approximately three orders of magnitude larger than that of the corresponding RANS simulation.

Turbulence Modeling Automotive catalysis Conversion Computational fluid dynamics scale-resolving simulation Flow uniformity

Author

Pratheeba Chanda Nagarajan

Chalmers, Mechanics and Maritime Sciences (M2), Combustion and Propulsion Systems

Jacob Larsson

Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics

Oskar Tylén

Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics

Aravind Murali

Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics

Axel Larsson

Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics

Ehsan Peyvandi

Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics

Sunil Rangaswamy

Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics

Jonas Sjöblom

Chalmers, Mechanics and Maritime Sciences (M2), Combustion and Propulsion Systems

Henrik Ström

Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics

Results in Engineering

25901230 (eISSN)

Vol. 16 100772

Driving Forces

Sustainable development

Areas of Advance

Transport

Energy

Subject Categories

Chemical Engineering

Fluid Mechanics and Acoustics

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

DOI

10.1016/j.rineng.2022.100772

More information

Latest update

4/21/2023