Modeling the Effect of Parametric Variations on Soot Particle Size Distribution in a Diesel Engine

2019 ◽  
Vol 142 (3) ◽  
Author(s):  
Pavan Prakash Duvvuri ◽  
Sujith Sukumaran ◽  
Rajesh Kumar Shrivastava ◽  
Sheshadri Sreedhara

Abstract Stringent emission legislations, increasing environmental and health issues, have driven extensive research on combustion engines to control pollutants. Modeling of emissions offers a cost-saving alternative to experimental analysis for combustion chamber design and optimization. Soot modeling in diesel engines has evolved over four decades from simple empirical relations to detailed kinetics involving polycyclic aromatic hydrocarbons (PAHs) and complex particle dynamics. Although numerical models have been established for predicting soot mass for parametric variations, there is a lack of modeling studies for predicting soot particle size distribution for parametric variations. This becomes important considering the inclusion of limits on soot particle count in recent emission norms. The current work aims at modeling the soot particle size distribution inside a heavy-duty diesel engine and validating the results for a parametric variation in injection pressure and intake temperature. Closed cycle combustion simulations have been performed using converge, a 3D computational fluid dynamics (CFD) code. A sectional soot model coupled with gas-phase kinetics has been used with source terms for inception, condensation, surface reactions, and coagulation. Numerical predictions for soot mass and particle size distribution at the exhaust show good agreement with experimental data after increasing the transition regime collision frequency by a factor of 100.

Author(s):  
Pavan P. Duvvuri ◽  
Sujith Sukumaran ◽  
Rajesh K. Shrivastava ◽  
Sheshadri Sreedhara

Stringent emission legislations, increasing environmental and health issues have driven extensive research in combustion engines to control pollutants. Modeling of emissions offers a cost saving alternative to experimental analysis for combustion chamber design and optimization. Soot modeling in diesel engines has evolved over four decades from simple empirical relations to detailed kinetics involving polycyclic aromatic hydrocarbons (PAH) and complex particle dynamics. Although numerical models have been established for predicting soot mass for parametric variations, there is a lack of modeling studies for predicting soot particle size distribution for parametric variations. This becomes important considering the inclusion of limits on soot particle count in recent emission norms. The current work aims at modeling the soot particle size distribution inside a heavy duty diesel engine and validating the results for a parametric variation of injection pressure and intake temperature. Closed cycle combustion simulations have been performed using CONVERGE, a 3D computational fluid dynamics (CFD) code. A sectional soot model coupled with gas phase kinetics has been used with source terms for inception, condensation, surface reactions and coagulation. Numerical predictions for soot mass and particle size distribution at the exhaust show good agreement with experimental data after increasing the transition regime collision frequency by a factor of 100.


2005 ◽  
Vol 62 (12) ◽  
pp. 4206-4221 ◽  
Author(s):  
Wanda Szyrmer ◽  
Stéphane Laroche ◽  
Isztar Zawadzki

Abstract The authors address the problem of optimization of the microphysical information extracted from a simulation system composed of high-resolution numerical models and multiparameter radar data or other available measurements. As a tool in the exploration of this question, a bulk microphysical scheme based on the general approach of scaling normalization of particle size distribution (PSD) is proposed. This approach does not rely on a particular functional form imposed on the PSD and naturally leads to power-law relationships between the PSD moments providing an accurate and compact PSD representation. To take into account the possible evolution of the shape/curvature of the distribution, ignored within standard one- and two-moment microphysical schemes, a new three-moment scheme based on the two-moment scaling normalization is proposed. The methodology of the moment retrieval included in the three-moment scheme can also be useful as a retrieval algorithm combining different remote sensing observations. The developed bulk microphysical scheme presents a unified formulation for microphysical parameterization using one, two, or three independent moments, suitable in the context of data assimilation. The effectiveness of the scheme with different combinations of independent moments is evaluated by comparison with a very high resolution spectral model within a 1D framework on representative microphysical processes: rain sedimentation and evaporation.


2018 ◽  
Vol 193 ◽  
pp. 54-60 ◽  
Author(s):  
Baiyang Lin ◽  
Hao Gu ◽  
Hong Ni ◽  
Bin Guan ◽  
Zhongzhao Li ◽  
...  

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