Grid sensitivity study of in-cylinder engine meshing appropriate for flow and combustion analysis using computational fluid dynamics (CFD)
This thesis deals with grid sensitivity study where it analyze the grid size as an input parameter. The change of grid size will give effect on the accuracy of result and computing time taken for analysis. The key objective for this project is to determined the suitable or acceptable grid size by co...
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| Format: | Undergraduates Project Papers |
| Language: | English |
| Published: |
2009
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| Online Access: | http://umpir.ump.edu.my/id/eprint/1074/ http://umpir.ump.edu.my/id/eprint/1074/ http://umpir.ump.edu.my/id/eprint/1074/1/Umar_Shafee.pdf |
| Summary: | This thesis deals with grid sensitivity study where it analyze the grid size as an input parameter. The change of grid size will give effect on the accuracy of result and computing time taken for analysis. The key objective for this project is to determined the suitable or acceptable grid size by considering the accuracy of result and computing time. This thesis describe on technique to tackle the objective from the start of modelling until finish the project. The analysis is focus on spark ignition (SI) combustion of the baseline engine design, Mitsubishi Magma 4G15 1.5L. The domain of in-cylinder engine was developed from CAD software and analysis using Computational Fluid Dynamics (CFD). 2-dimensionall (2D) domain was used in order to reduce the time consume instead of 3-dimensional (3D). Numbers of grid size is generated before it is analyzed. The speed of engine is fixed at 2000 revolution per minute (rpm) and the turbulence model is k-epsilon (k-ϵ) model. The iteration number is set to 2000 iteration per time step. There are six different cases analyzed with different grid size. The grid size was set from 1mm to 4mm. The analysis is to predict the behavior of in-cylinder engine’s combustion process. Different grid size give different result of accuracy and computing time. The accuracy test is based on cylinder pressure and the simulation data is validated with experiment data. Smaller grid size will resulted the better accuracy while consume more computing time. Case 3 of grid size 2.5mm has given the best as and most acceptable result. |
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