scholarly journals Mathematically Reduced Chemical Reaction Mechanism Using Neural Networks

2006 ◽  
Author(s):  
Nelson Butuk
Keyword(s):  
Neural Networks ◽  
Reaction Mechanism ◽  
Chemical Reaction ◽  
Chemical Reaction Mechanism

Parametric Study of Moss-Brookes (MB) and Moss-Brookes-Hall (MBH) Model Constants for Prediction of Soot Formation in a Turbulent Hydrocarbon Flames

2013 ◽  
Author(s):  
Pravin Rajeshirke ◽  
Pravin Nakod ◽  
Rakesh Yadav ◽  
Stefano Orsino
Keyword(s):  
Reaction Mechanism ◽  
Chemical Reaction ◽  
Parametric Study ◽  
Soot Formation ◽  
Hydrocarbon Flames ◽  
Oxidation Rates ◽  
Numerical Predictions ◽  
Chemical Reaction Mechanism ◽  
Soot Precursors ◽  
Original Works

In the present work, two equation soot models proposed by Moss-Brookes (MB) and Moss-Brookes-Hall (MBH), available in ANSYS FLUENT14.5, are used to study the soot formation in a turbulent kerosene-air flame. The model constants in the original works of MB and MBH model were primarily tuned for the methane-air or other lower hydrocarbon flames. In this work, the emphasis has been given on the applicability of these models in modeling the soot formation in heavy hydrocarbon fuels. The current work is primarily focused on the parametric study of the various modeling constants for calculating the soot inception and oxidation rates. A parametric study is performed to calculate the soot inception rates by considering different soot precursors like C2H2, C2H4, C6H6 and C6H5. Steady laminar flamelet approach with a detailed chemical reaction mechanism (Jet_SurF_2.0), is used for modeling gas phase combustion. The current numerical predictions are compared with experimental results of Young et al. [1] and earlier published numerical results of Wen et al. [2]. The study is further extended to understand the role of chemical reaction mechanism on soot predictions considering detailed versus reduced (JP10revC) chemical mechanisms.

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