A New Approach for Modeling Coke Particle Emissions from Large Diesel Engines Using Heavy Fuel Oil

2017-01-2381

10/08/2017

Features
Event
International Powertrains, Fuels & Lubricants Meeting
Authors Abstract
Content
In the present study, a new approach for modelling emissions of coke particles or cenospheres from large diesel engines using HFO (Heavy fuel oil) was studied. The model used is based on a multicomponent droplet mass transfer and properties model that uses a continuous thermodynamics approach to model the complex composition of the HFO fuel and the resulting evaporation behavior of the fuel droplets. Cenospheres are modelled as the residue left in the fuel droplets towards the end of the simulation. The mass-transfer and fuel properties models were implemented into a cylinder section model based on the Wärtsilä W20 engine in the CFD-code Star CD v.4.24. Different submodels and corresponding parameters were tuned to match experimental data of cylinder pressures available from Wärtsilä for the studied cases. The results obtained from the present model were compared to experimental results found in the literature. The performance of the model was found to be promising although conclusive validation of the model would require more detailed experimental results about cenosphere emissions from the specific case studied here. According to the results obtained from this model the emissions of cenospheres are a function of both operating conditions and fuel properties. While the droplet evaporation and properties models were used in this study to model cenosphere emissions, the approach could also be used to study the combustion behavior of HFO in a broader sense.
Meta TagsDetails
DOI
https://doi.org/10.4271/2017-01-2381
Pages
20
Citation
Hentelä, K., Kaario, O., Garaniya, V., Goldsworthy, L. et al., "A New Approach for Modeling Coke Particle Emissions from Large Diesel Engines Using Heavy Fuel Oil," SAE Technical Paper 2017-01-2381, 2017, https://doi.org/10.4271/2017-01-2381.
Additional Details
Publisher
Published
Oct 8, 2017
Product Code
2017-01-2381
Content Type
Technical Paper
Language
English