A detailed chemical mechanism to predict NO cycle-to-cycle variation in homogeneous engine combustion

2012 ◽  
Vol 45 (30) ◽  
pp. 408-415 ◽  
Author(s):  
Apostolis T. Karvountzis-Kontakiotis ◽  
Leonidas Ntziachristos
Keyword(s):  
Chemical Mechanism ◽  
Cycle Variation ◽  
Engine Combustion ◽  
Detailed Chemical

3D CFD Modeling of a Biodiesel-Fueled Diesel Engine Based on a Detailed Chemical Mechanism

2012 ◽  
Author(s):  
Junfeng Yang ◽  
Monica Johansson ◽  
Chitralkumar Naik ◽  
Karthik Puduppakkam ◽  
Valeri Golovitchev ◽  
...  
Keyword(s):  
Diesel Engine ◽  
Chemical Mechanism ◽  
Cfd Modeling ◽  
Detailed Chemical

scholarly journals Mechanism of Emission Reduction in HSDI Diesel Engine: Split Injection

2015 ◽  
Vol 09 (2) ◽  
Keyword(s):  
Diesel Engine ◽  
Heat Release ◽  
Temporal Distribution ◽  
Reaction Rates ◽  
Chemical Mechanism ◽  
Symmetric Model ◽  
Diesel Combustion ◽  
Split Injection ◽  
Engine Combustion ◽  
Experimental Values

In order to meet the stringent emission standards significant efforts have been imparted to the research and development of cleaner IC engines. Diesel combustion and the formation of pollutants are directly influenced by spatial and temporal distribution of the fuel injected. The development and validation of computational fluid dynamics (CFD) models for diesel engine combustion and emissions is described. The complexity of diesel combustion requires simulation with many complex interacting sub models in order to have a success in improving the performance and to reduce the emissions. In the present work an attempt has been made to develop a multidimensional axe-symmetric model for CI engine combustion and emissions. Later simulations have been carried out using split injection for single, double and three pulses (split injection) for which commercial validation tool FLUENT was used for simulation. The tool solves basic governing equations of fluid flow that is continuity, momentum, species transport and energy equation. Using finite volume method turbulence was modeled by using RNG K-ɛ model. Injection was modeled using La Grangian approach and reaction was modeled using non premixed combustion which considers the effects of turbulence and detailed chemical mechanism into account to model the reaction rates. The specific heats were approximated using piecewise polynomials. Subsequently the simulated results have been validated with the existing experimental values. The peak pressure obtained by simulation for single and double is 10% higher than to that of experimental value. Whereas for triple injections 5% higher than to that of experimental value. For quadruple injection the pressure has been decreased by 10% when compared to triple injection.NOX have been decreased in simulation for single, double and triple injections by 15%, 28% and 20%.For quadruple injection NOX were reduced in quadruple injection by 20% to that of triple injection. The simulated value of soot for single, double and triple injections are 12%, 22% and 12% lesser than the experimental values. For quadruple injection the soot levels were almost negligible. The simulated heat release rates for single, double and triple were reduced by 12%, 18% and 11%. For quadruple injection heat release is reduced same as to that of triple injection.

Detailed chemical mechanism of the phase transition in nano-SrTiO3 perovskite with visible luminescence

2020 ◽  
Vol 120 ◽  
pp. 108125
Author(s):  
Sonali Mehra ◽  
Swati Bishnoi ◽  
Lalit Goswami ◽  
Govind Gupta ◽  
Avanish Kumar Srivastava ◽  
...  
Keyword(s):  
Phase Transition ◽  
Chemical Mechanism ◽  
Visible Luminescence ◽  
Detailed Chemical

Predicting Lean Blowout and Emissions of Aircraft Engine Combustion Chamber Based on CRN

2019 ◽  
Vol 36 (2) ◽  
pp. 147-156 ◽  
Author(s):  
Yinli Xiao ◽  
Zhengxin Lai ◽  
Zupeng Wang ◽  
Kefei Chen
Keyword(s):  
Combustion Chamber ◽  
Initial Conditions ◽  
Aircraft Engine ◽  
Chemical Reactor ◽  
Pollutant Emissions ◽  
Chemical Mechanism ◽  
Lean Blowout ◽  
Operating Modes ◽  
Engine Combustion ◽  
Set Up

Abstract To predict the pollutant emissions and lean blowout, chemical reactor network (CRN) model is applied to the modern aircraft engine combustion chamber. In this study, the CRN which represent the major features of aerodynamics and combustion in the combustion chamber is set up based on the OpenFOAM simulation results. The boundary and the initial conditions used for the CRN derive from the operating modes of typical aircraft engine cycle. A 21 species 30 steps chemical mechanism of kerosene is employed in the CRN method. The levels of pollutant emissions are obtained under four ICAO engine power settings of idle, approach climb and take off. The lean blowout equivalent ratio is evaluated at the idle power setting. The results will be helpful to predict the aircraft engine exhaust emissions and lean blowout (LBO).

scholarly journals Nonlinear Dynamic Analysis of Shale Gas Engine Combustion Stability

2021 ◽  
Author(s):  
Shuai Liu ◽  
Libin Zhang ◽  
Zhong Wang ◽  
Lun Hua ◽  
Qiushi Zhang
Keyword(s):  
Phase Space ◽  
Shale Gas ◽  
Combustion Process ◽  
Combustion Stability ◽  
Working Process ◽  
Gas Engine ◽  
Cycle Variation ◽  
Engine Combustion ◽  
Phase Space Trajectory ◽  
Combustion Cycle

Abstract The traditional analysis method of engine combustion cycle variation is a statistical method based on a small amount of data. In essence, the obtained cycle variation is random data. In order to reveal the dynamic nature of the cyclical changes during the combustion of a shale gas engine, a nonlinear dynamics method was used to study the stability of the combustion process. The motion law of the phase space trajectory is analyzed, the influence of the shale gas composition on the trajectory distribution is analyzed, the return mapping point of the average indicated pressure in the cylinder is discussed. The relationship between adjacent combustion characteristic parameters is studied; the chaotic characteristics of the shale gas engine combustion process are discussed. The results show that during the working process of the shale gas engine, the in-cylinder pressure shows a similar quasi-periodic state in the entire phase space, and the working process has a certain chaotic law; with the increase of the CH4, N2 and CO2 content in the shale gas, the combustion cycle variation increases, and the randomness of the engine working process increases. The phase space trajectory shows a monotonously increasing distribution of Poincaré mapping points on the ∑XY+ section. With the increase of the combustion cycle, the linear relationship of the scattered points gradually increases, and the randomness of the combustion process increases. The return map points of the engine combustion characteristic parameters are distributed in a cluster. When the CH4 content increases, the distribution range of the average indicated pressure return map points increases. With the increase of N2 and CO2 content, abnormal combustion phenomena such as partial combustion or misfire occur during the engine combustion process, the uncertainty of the combustion process increases, and the combustion stability decreases. With the increase of engine speed, the correlation dimension and the maximum Lyapunov exponent increase, the randomness of the combustion process increases, and the chaotic characteristics of the engine working process are obvious; the time series of the cylinder pressure is more sensitive to the content of inert gas. With the increase of N2 and CO2 content in the gas, the correlation dimension and the maximum Lyapunov exponent increase significantly, the complexity of the phase space trajectory increases, and the chaotic characteristics become more obvious.

Engine Knock Prediction Using Multi Zone Model for Spark Ignition Engines

2006 ◽  
Author(s):  
A. Ahmedi ◽  
O. Stenla˚a˚s ◽  
B. Sunde´n ◽  
R. Egnell ◽  
F. Mauss
Keyword(s):  
Flame Front ◽  
Compression Ratio ◽  
Chemical Kinetic ◽  
Chemical Mechanism ◽  
Combustion Model ◽  
Zone Model ◽  
Chemical Kinetic Model ◽  
Engine Knock ◽  
Si Engines ◽  
Detailed Chemical

Autoignition in SI engines is an abnormal combustion mode and may lead to engine knock in SI engines. Knock may cause damage and it is a source of noise in engines. It limits the compression ratio of the engine and a low compression ratio means low fuel conversion efficiency of the engine. In this paper a multi zone model based on an existing two zone model Hajireza et al., [1 and 12] and Stenla˚a˚s et al., [30] is developed and validated against the experimental results. The validation is done by using the same detailed chemical mechanism consisting of 141 species and about 1405 reactions under the same conditions. The model is a zero dimensional model capable of simulating a full engine cycle. The two zone combustion model consists of a burned and an unburned zone, separated by a thin adiabatic flame front. The multi zone model differs in the handling of the burned gas. In the multi zone case a number of burned zones are present. The number of zones is decided by the temperature difference between the flame front and the last generated burned zone. The detailed chemical mechanism is taken into account in each zone, while the propagating flame front is calculated from the Wiebe function. Each zone is assumed to be a homogeneous mixture with a uniform temperature, mole and mass fractions of species. The spatial variation of the pressure is neglected, i.e., it is assumed to be the same in the whole combustion chamber at every instant of time. Autoignition is handled by the chemical kinetic model. As the unburned zone is assumed homogeneous the effect of auto ignition is a single pressure peak. The model is not designed to predict the pressure oscillations seen in engine knock.

scholarly journals Simulating the detailed chemical composition of secondary organic aerosol formed on a regional scale during the TORCH 2003 campaign in the southern UK

2006 ◽  
Vol 6 (2) ◽  
pp. 419-431 ◽  
Author(s):  
D. Johnson ◽  
S. R. Utembe ◽  
M. E. Jenkin
Keyword(s):  
Chemical Composition ◽  
Secondary Organic Aerosol ◽  
Regional Scale ◽  
Equilibrium Phase ◽  
Organic Aerosol ◽  
Oxidation Products ◽  
Chemical Mechanism ◽  
Phase Partitioning ◽  
Biogenic Voc ◽  
Detailed Chemical

Abstract. Following on from the companion study (Johnson et al., 2006), a photochemical trajectory model (PTM) has been used to simulate the chemical composition of organic aerosol for selected events during the 2003 TORCH (Tropospheric Organic Chemistry Experiment) field campaign. The PTM incorporates the speciated emissions of 124 non-methane anthropogenic volatile organic compounds (VOC) and three representative biogenic VOC, a highly-detailed representation of the atmospheric degradation of these VOC, the emission of primary organic aerosol (POA) material and the formation of secondary organic aerosol (SOA) material. SOA formation was represented by the transfer of semi- and non-volatile oxidation products from the gas-phase to a condensed organic aerosol-phase, according to estimated thermodynamic equilibrium phase-partitioning characteristics for around 2000 reaction products. After significantly scaling all phase-partitioning coefficients, and assuming a persistent background organic aerosol (both required in order to match the observed organic aerosol loadings), the detailed chemical composition of the simulated SOA has been investigated in terms of intermediate oxygenated species in the Master Chemical Mechanism, version 3.1 (MCM v3.1). For the various case studies considered, 90% of the simulated SOA mass comprises between ca. 70 and 100 multifunctional oxygenated species derived, in varying amounts, from the photooxidation of VOC of anthropogenic and biogenic origin. The anthropogenic contribution is dominated by aromatic hydrocarbons and the biogenic contribution by α- and β-pinene (which also constitute surrogates for other emitted monoterpene species). Sensitivity in the simulated mass of SOA to changes in the emission rates of anthropogenic and biogenic VOC has also been investigated for 11 case study events, and the results have been compared to the detailed chemical composition data. The role of accretion chemistry in SOA formation, and its implications for the results of the present investigation, is discussed.

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