Prediction and validation of the mean flow and the acoustic performance of reactive mufflers using computational fluid dynamics

Download files
Access & Terms of Use
open access
Copyright: Middelberg, Jason Mark
Virtually all reciprocating internal combustion engines are fitted with mufflers. The muffler fitted to an engine is intended to reduce the pressure pulses associated with the exhaust gas leaving the cylinders of the engine. Generally mufflers fitted to such engines are essentially reactive devices as opposed to being dissipative devices. The aim of this research is to develop a computational fluid dynamics (CFO) model to predict the acoustic and mean flow performance of reactive mufflers used with large diesel engines for agriculture, mining, transport and marine applications. Currently such mufflers are designed on a simplified theoretical and/or empirical basis. Consequently the design is generally conservative and so it results in weight and cost penalties. The basis of the CFD acoustic modelling approach is to apply a pulse of suitable amplitude and duration at the inlet of the muffler. The time dependent CFD model determines flow variables associated with the resulting perturbation at the outlet of the muffler. The inlet and outlet pressure time histories derived from the CFD analysis can be Fourier transformed to allow the frequency-dependent transmission loss of the muffler to be found. The acoustic pulse can also be superimposed on a steady flow at the inlet and the resulting perturbation superimposed on the steady flow at the outlet can be determined. Thus the frequency-dependent transmission loss for the acoustic with mean flow performance of the muffler can be found. This CFD modelling approach is used to predict the performance of various types of reactive mufflers and the CFD models are validated against laboratory and published results of full-scale silencers.
Persistent link to this record
Link to Publisher Version
Link to Open Access Version
Additional Link
Middelberg, Jason Mark
Conference Proceedings Editor(s)
Other Contributor(s)
Corporate/Industry Contributor(s)
Publication Year
Resource Type
Degree Type
PhD Doctorate
UNSW Faculty
download Middelberg-014954389.pdf 26.97 MB Adobe Portable Document Format
Related dataset(s)