Application of Adaptive Local Mesh Refinement (ALMR) Approach for the Modeling of Reacting Biodiesel Fuel Spray using OpenFOAM

Paper #:
  • 2014-01-2565

Published:
  • 2014-10-13
Citation:
Mohamed Ismail, H., Ng, H., Gan, S., and Lucchini, T., "Application of Adaptive Local Mesh Refinement (ALMR) Approach for the Modeling of Reacting Biodiesel Fuel Spray using OpenFOAM," SAE Technical Paper 2014-01-2565, 2014, https://doi.org/10.4271/2014-01-2565.
Pages:
9
Abstract:
Modeling the combustion process of a diesel-biodiesel fuel spray in a 3-dimensional (3D) computational fluid dynamics (CFD) domain remains challenging and time-consuming despite the recent advancement in computing technologies. Accurate representation of the in-cylinder processes is essential for CFD studies to provide invaluable insights into these events, which are typically limited when using conventional experimental measurement techniques. This is especially true for emerging new fuels such as biodiesels since fundamental understanding of these fuels under combusting environment is still largely unknown. The reported work here is dedicated to evaluating the Adaptive Local Mesh Refinement (ALMR) approach in OpenFOAM® for improved simulation of reacting biodiesel fuel spray. An in-house model for thermo-physical and transport properties is integrated to the code, along with a chemical mechanism comprising 113 species and 399 reactions. Simulation results are compared against data from the Chalmers High-Pressure-High-Temperature Constant-Volume Combustion Chamber (HPHT-CVCC) experimental test-bed studies in terms of liquid-droplet penetration length, vapour penetration length and spray temporal distribution. Good trends are achieved for the penetration lengths and vapour distributions when using ALMR approach. The computing time is found to be lower with ALMR approach as compared to the static grid approach. With accurate representation of the reacting fuel spray processes, more detailed understanding of various biodiesel-diesel fuel mixtures can be investigated with minimal computing time and cost.
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