process, was introduced by Peters in 1983  (see Eq. 3.1 in Section 3.2.1). Historically, Williams was the first to rewrite, under unity Lewis number assumption, the species transport equations by separating the diffusion normal to mixture fraction iso-contours and that in tangential directions . Peters introduced additional simplifications to make use of the flamelet formulation in reacting flow simulations, namely, combustion processes take place in a thin layer close to the flame front, diffusion in the direction parallel to the local iso-surface of mixture fraction is negligible, and the local flame surfaces are essentially flat. Based on these three assumptions, multi-dimensional non- premixed flames can be modeled as an ensemble of piecewise one-dimensional flame structures, termed flamelets. The LDF model has been a popular modeling approach in simulating both laminar non-premixed flames [53, 54, 55] and turbulent non-premixed flames [56, 57, 58, 59, 60, 61, 22, 62]. The distinct advantage offered by the flamelet model, compared to the numerical simulation using finite-rate chemistry model, is that flow properties and chemical kinetics are essentially decoupled . More specifically, steady-state flamelet equations are solved in advance to build a flamelet database. This database is then tabulated as a function of the mixture fraction, Z , and the scalar dissipation rate, χ, as shown in Fig. 1.4. In simulations, the values of Z and χ are computed locally, based on
A comparative study of two combustion models based on non-premixed assumption and partially premixed assumptions using the overall models of Zimont Turbulent Flame Speed Closure Method (ZTFSC) and Extended Coherent Flamelet Method (ECFM) are conducted through Reynolds stress turbulence modelling of Tay model gas turbine combustor for the first time. The Tay model combustor retains all essential features of a realistic gas turbine combustor. It is seen that the non-premixedcombustion model fails to predict the combustion completely due to an incorrect assumption of diffusion flame scenario invoking infinitely fast chemistry in complicated flow environments while the two partially premixedcombustion models accurately predict the flame pattern in the primary region of the combustor. The ZTFSC model outperformed the ECFM model by producing a better temperature agreement with the experimental result. The latter model predicts lower temperature due to the underestimation of reaction progress. Additionally, a cross-comparison of the present RSM prediction invoking ZTFSC model with LES prediction reported in the literature is conducted. The former produces more accurate species concentration and flame pattern than the latter. This is mainly due to the incorrect assumption of non- premixedcombustion used in LES prediction reported in the literature. It is interesting to find that when non- premixedcombustion model is used for both RSM and LES predictions, the LES predicts higher temperature closer to the injection nozzle of combustor than the RSM model, though the flame shape in both cases is incorrect. This is mainly due to the fact that the traditional RANS model dissipates the energy of swirling flow too fast in the primary region of the combustor. The weaker centre recirculation zone (CRZ) created by vortex breakdown recirculate less air to the area near the injection nozzle resulting in fuel rich combustion. It indicates that the temperature difference between predicted results using RSM in conjunction with ZTFC model and experimental results can be improved by using less energy dissipating turbulence models such as scale resolving simulation (SRS).
iteration of a computation. This complexity is generally not feasible for domains of any significant size. Intrinsic Low Dimensional Manifold (IDLM) is used to reduce the overall picture of a more detailed mechanism. This procedure separates the reactive species, focusing on the ones with slower chemical- reaction time scales. Requiring fewer species to reach a solution facilitates a more tractable solution, however, neglecting the species with faster time scales limits the range of flame conditions that can be modeled (Maas & Pope, 1992). IDLM works best with reactions that always progress to equilibrium, but it falls short in scenarios such as extinction and re-ignition where the faster reaction rates are affected by the turbulent characteristics. Another promising method designed to handle the complex chemistry needed for reactive DNS studies is the In Situ Tabulation (ISAT) method, where the chemical source values at a given state are stored in a dynamically constructed table. With the ISAT procedure, the state vector is represented using a binary tree, and the chemical source terms are stored for recently performed calculations (Pope S. , 1997). Later in the computation, when the same state conditions are encountered again, the calculations can be skipped in lieu of a table lookup. As expected, this procedure works best with problems where local equilibria are predominant. While these methods provide excellent options for capturing more detailed chemical compositions, they come with a cost: the limitations resulting from assumptions and bounding conditions. As stated before, each method tends to improve the solution capacity in one way by restricting it in others.
In spite of the wealth of information regarding the modeling attempts found in the literature, a systematic and comprehensive attempt to describing the gas phase is still found elusive. In fact, only very few models were reported previously regarding the gas phase modeling. Therefore, it is challenging to develop a model that can describe burning of combustible materials by considering both gas and solid phases  and one that yields a good agreement with experimental data. The previous studies also showed that differences, of varying degrees, exist between the modeling outcomes and experimental results, as is evident from the following reports. Riccio et al.  have developed a numerical model to simulate the behavior of composite materials in a fire environment providing the mass loss rate, heat release rate and total heat released through the influence of a heat source. Marquis et al.  have also developed a model describing the de-volatilization processes of a sandwich material on smaller scale. Yuen et al.  have developed a mathematical model for describing the pyrolysis of wet wood that coupled the gas phase combustion to the analyses of a wood samples ignited in a cone calorimeter.
Combustion ignition study is important due to the combustion process becoming more lean and efficient. This paper studied the recirculation zone and ignition location for the bluff-body non-premixed MILD burner with biogas used as fuel. The location of the ignition was critical to ensure the spark energy supply during the ignition process is successful ignite the mixture of air and fuel. The numerical calculations were done using the commercial code ANSYS-Fluent to simulate the furnace with bluff-body burner to determine the recirculation zone. The turbulence model used was the realizable k-ε model. The inner recirculation zone between the air and fuel nozzle is the best location for the ignition point since low velocity of air and fuel mixing will assist the ignition process. This is because the ignition energy will have time to ignite the mixture in the low speed of turbulent swirl flow. The most suitable location with the highest possibility of ignition is the centre of the recirculation zone.
The dominant mechanism of the effect of non-equilibrium plasma on ignition and combustion is associated with the gen- eration of active particles in the discharge plasma. Numerical simulation of discharge processes is based on the solution of the Boltzmann equation for electrons and of the balance equations for active particles. The input data are electron– molecule cross sections and rate constants for reactions with excited and charged particles. Numerical simulation of the streamer discharge, including the transition from avalanche to streamer and streamer propagation, is too challenging from the computational point of view. To accelerate the simulation of streamers, different approximations have been proposed to reduce the computation time spent on calculations. In the developed model, plasma is treated is ideal gas.
The finite difference schemes, as agreed by most of the scientific community, were first used by Euler (1707-1783)  to find an approximate solution of a differential equation. It was invented prior to boundary element methods (BEM), finite element methods (FEM), spectral methods, and discontinuous spectral element methods . FDM is still relevant and remain competitive as a discretisation method for use in many applications and can be used to solve problems with simple and complex geometry, such as fluid flows and gas reaction [57,58]. The Finite difference method (FDM) is a numerical method for approximating the solutions to partial differential equations by using finite difference equations to approximate derivatives based on the properties of Taylor expansions and on the straightforward application of the definition of derivatives . The objectives are to transform the calculus problem to algebra as from a continuous equation to a discrete equation. The discretisation process is a mathematical process that divides the continuous physical domain into a discrete finite difference grid and then approximates each individual partial derivative in the partial differential equation. Using the Taylor expansion method, a partial differential equation was discretised in order to transform it to FORTRAN code. FORTRAN is a high level of programming language developed by team of IBM programmers led by John Backus in 1954. The name of FORTRAN was derived from the words “Formula Translation”, started from 1957 when the first FORTRAN compiler was used. It has evolved through FORTRAN II, FORTRAN 66, until now FORTRAN 2008. FORTRAN 90 was used in this study. From the CMC equation, to study the discretisation and code it in FORTRAN, simplifications of the CMC equation were used: the conditional chemical source term 𝑊 𝑍 and conditional generation due to droplet evaporation term 𝑆 𝑍 were not considered. So the homogeneous and passive CMC is equation (31):
Soot emissions (PM 2.5) from land-based sources pose a substantial health risk, and now are sub- ject to new and tougher EPA regulations. Flaring produces significant amount of particulate matter in the form of soot, along with other harmful gas emissions. A few experimental studies have pre- viously been done on flames burning in a controlled condition. In these lab-experiments, great ef- fort is needed to collect, sample, and analyze the soot so that the emission rate can be calculated. Soot prediction in flares is tricky due to variable conditions such as radiation and surrounding air available for combustion. Work presented in this paper simulates some lab-scale flares in which soot yield for methane flame mixture was measured under different conditions. The focus of this paper is on soot modeling with various flair operating conditions. The computational fluid dy- namics software ANSYS Fluent 13 is used. Different soot models were explored along with other chemistry mechanisms. The effect of radiation models, quantity of air supplied, different fuel mixture and its effect over soot formations were also studied.
expensive, comprehensive experimental studies (Chandrasekharan, 2013). Building computational models gives researchers deeper insights into problems than building an experimental setup. Despite the benefits of computational methods, however, the experiment method is still an important step to compare and validate the computational result. This feedback can be used to improve the computational method. Computational Fluid Dynamics (CFD) offers a cost-effective method especially at the beginning of the combustor design and parameter setting stage. It was therefore used here to study the recirculation zone and optimize the ignition location. The first CFD modeling work for MILD combustion was started by the Japanese heating industry where a few researchers (Ishii, Zhang, & Sugiyama, 1997; Zhang, Ishii, & Sugiyama, 1997; Hino, Zhang, & Ishii, 1998) carried out simulations of a continuous slab reheating furnace with emphasis on NO x formation. The simulation work was successful and continued with an
Calculations of non-premixed and partially premixed laminar counterflow flames with detailed chemistry have been performed with a simulated spark to understand the factors affecting ignition success in non- premixedcombustion. The results showed that there is a critical strain rate, which depends on the igniter, above which forced ignition is impossible for all spark positions. This critical value can be less than the extinction strain rate at which a steady flame becomes impossible, even for a spark thickness and energy that would ignite a stoichiometric homogeneous mixture. For a particular spark position relative to the
Due to the non-linearity of the Navier-Stokes equations, and their coupled dependence on initial and boundary conditions, only a handful of exact analytical solutions exist. Rather, for most engineering applications, numerical solutions must be attained. For the most part, there are three main classes of techniques for modeling and simulating turbulent flows. They are Direct Numerical Simulation (DNS), Large Eddy Simulation (LES) and Reynolds Averaged Navier-Stokes (RANS). These three categories can be thought to lie on a spectrum, Figure 2.1. At one end of the spectrum lies DNS, which incorporates the most physical representation of the flow but at the price of the highest computational expense. At the other end lies RANS, which is less expensive to implement, but requires a large amount of empirical modeling to properly account for the turbulence of the flowfield. LES lies somewhere in the middle and has attributes of both extremes. There are different implementations of LES, each one at different points along the spectrum. Below is a brief introduction to each category listed above.
combustors with inlet diameters of 0.42, 0.22 and 0.12 mm have been modeled. The numerical results indicate that the flame temperature is lower for the smaller combustor. This has been explained by the fact that as the combustion chamber size decreases, the ratio of surface area to volume increases. Consequently, heat loss from the wall of chamber is increased, which affect on flame temperature. In this study, it has been showed that a moderated feed flow rate is required for a stable power generation in micro combustors. When feed flow rate is too low, the performance of the combustor is limited by flame quenching in the chamber. However, at high mass flow rates of fuel-air, the inlet gas mixture have not enough time for reaction and flame may be blown out, which also leads to low combustion efficiency. The results of this study reveal that the wall thermal conductivity is another parameter which plays an important role in the performance of micro combustor. The results show that lower wall heat conductivity can reduces the heat loss from the system and causes a stable combustion. On the contrary, the higher heat conductivity can increases preheating of reactants and decreasing wall thermal stress. From this investigation, it can be concluded that the split of hydrogen feed along the combustor allowed a noticeable decrease in maximum temperature of the combustion chamber. The hydrogen feed splitting can causes a more uniform temperature to be established in the chamber. Finally, it can be concluded that by CFD modeling of combustion of premixed hydrogen-air mixture in a micro scaled chamber, it is possible to design an efficient system without need to many expensive experimental analysis.
Abstract : This research describes unsteady two-dimensional reacting flow around a circular cylinder. The numerical solution combines random vortex method for incompressible two- dimensional viscous fluid flow with a Simple Line Interface Calculation (SLIC) algorithm for propagation of flame interface. To simplify the governing equations, two fundamental assumptions namely Low Mach Number and Thin Flame Thickness are used. Numerical and graphical representation of vorticity field, velocity variation on the wake axis, the effect of combustion on stream line pattern and location of vortex element at Reynolds numbers of 3000 and 9500 are discussed. The numerical results for the non-reacting flows fall within the range of the experimental measurements while the results of the reacting case are qualitatively following the physics.
Several studies confirmed a possibility of reaching low soot and NO x emissions using a fuel with high octane number. The effect of different cetane numbers (CN) to retard the first ignition timing on multiple stage diesel combustion has been investigated by Hashizume et al.  via numericalmodeling and experiments. They demonstrated that in this kind of combustion, first stage ignition is retarded and combustion starts at about TDC using a fuel with 19 CN in compared to fuel with 62 CN. Also the fuel consumption improved for the lower cetane number fuel due to the degree of constant volume combustion at first stage combustion is increased largely. Shimazaki et al.  have shown that a fuel with low cetane number (CN=19) accompanied with a narrow injection angle and shallow dish combustion chamber, improve fuel-air mixing and enable low soot and NOx combustion at higher ignition delay. Kalghatgi et al. [12, 13] investigated effect of fuel auto-ignition quality on engine ignition timings and emissions experimentally for four different fuels with different CN and volatility, including conventional gasoline. Their results indicate that there is significantly higher soot with diesel compared to the gasoline fuel due to
The axisymmetric premixed flame simulations described in Chapters 5 and 6 below are performed with the Cantera reacting-flow software package (Goodwin 2003), using the one-dimensional model from Kee et al. (1989, 2003) validated against non-reacting impinging-jet experiments and axisym- metric two-dimensional direct numerical simulations in Bergthorson et al. (2005b). The velocity and velocity gradient are set to zero at the stagnation wall, x = 0 mm (no-penetration and no-slip condi- tions), and are specified at the inlet: ∼ 1 mm upstream of the flame. The results are not found to be sensitive to this choice (Bergthorson 2005a, Section 3.1.2). The fluid-velocity and velocity-gradient values specified at the inlet are determined from the experimental particle-velocity profile (Bergth- orson et al. 2005a), taking into account the lag of the tracer particles (Bergthorson & Dimotakis 2006). The inlet composition, inlet temperature, and stagnation-wall temperature are specified from measurements of fuel & air volumetric flow rates and from temperature measurements, respectively. A no-flux (multi-component with thermal diffusion) boundary condition for species is applied at the wall. The boundary conditions for each experiment are reported in Table D.1.
Science is a business of developing and testing models of the physical world. Signiﬁcant progress has been made in the simulation of complicated ﬂuid mechanics problems. The simulation of realistic combustion problems has, however, faced several diﬃculties. In ﬂuid mechanics, general conservation equations (mass, momentum, energy) and an equation of state suﬃce to describe the behavior. The complexity associated with many ﬂows indicates the wide variety of behavior that these equations allow. In combustion, the inclusion of chemistry requires a conservation equation for each species present in the ﬂame, including source and sink terms due to chemical reactions. The reaction rates in the source and sink terms are themselves functions of the local composition, temperature, and, in some cases, pressure. Each chemical reaction must be modeled to account for these dependencies. A chemical-kinetics mechanism is a compilation of these individual reactions, each with an associated rate constant expression, that models the combustion chemistry. The inclusion of chemistry results in a very large, complicated, and numerically stiﬀ problem. The large computational cost associated with implementing realistic chemistry models has impeded progress towards simulating practical combustor geometries. To reduce the computational cost, premixed laminar “ﬂamelets” have been used to simulate turbulent combustion problems (e.g., Peters 1986; Williams 2000; Law & Sung 2000). These laminar ﬂamelets rely on modeling, simulations, and experiments to determine the ﬂame response to turbulent straining. The simulations of ﬂamelets are typically performed using simpliﬁed one-dimensional hydrodynamic equations. In these simpliﬁed ﬂows, detailed chemistry models may be utilized without excessive computational cost. Examples of such simpliﬁed ﬂame geometries are the premixed laminar ﬂame and the strained stagnation-point ﬂame. It is interesting to note that even 50 years ago, many chemists “dismiss(ed) ﬂames as being too hopelessly compli- cated for fruitful study in any fundamental way” (Fristrom & Westenberg 1965; preface). The large number of species and reactions required to describe the ﬂame propagation of simple hydrocarbon fuels such as methane and ethylene supports this pessimistic view.
Abstract: This study investigated dual-fuel operation with a light duty Diesel engine with Natural gas over a wide engine load range. Natural gas was hereby injected into the intake duct, while Diesel was injected directly into the cylinder. At low loads, high fuel shares are critical in terms of combustion stability and emissions of unburnt hydrocarbons. Dual-fuel combustion has the advantage of providing diesel-like efficiency with Natural gas as the primary fuel, providing potential increases in efficiency of 50% while reducing emissions. Typically a small liquid fuel pilot is injected into a lean mixture of air and a more volatile fuel that is less inclined to auto-ignite. Often it is difficult to simulate the separate chemical effects of the two fuels. In present study we are using nonpremixed type of combustion model for better mixing and penetration of fuel and air so the complete combustion is achieved and emission is reduced by a great amount as compare to premixed method. NOx emission is reduced as compare to previous base research. Fluent accurately tracks flame propagation, which is critical for dual-fuel cases where the injection and auto-ignition of the liquid pilot fuel serves to initiate the flame propagation. In Fluent the simulation can simultaneously consider both auto-ignition and flame-propagation modes of combustionprogress. Fluent fluid flow allows investigations of fuel or additive composition effects, impacts on liquid pilot amount and timing, and NOx reduction techniques such as EGR, etc.
3 Combustion process requires a molecular mixing between the fuel and oxidizer. In turbulent combustion the mixing processes depends on the turbulent mixing which takes place at macro scale level. The chemical reaction could be assumed to be single step reaction which takes place at certain level or multi- step reaction with many time scales. Turbulence has many macro scales and combustion has many micro scales expect for very slow chemistry, what the relation between them. Turbulence enhances the mixing through the eddy break up process which enhances the combustion [2, 3]. The combustion releases heat which increases the instability and turbulence. Although these effects are observed experimentally many times, it is unclear how these effects could be modeled. Navier-stokes equations describe the macro scale properties only, which is the main challenge in turbulent combustionmodeling.
flames with curvature, a few reduced-order models for thermal diffusion have been proposed, in addition to iterative techniques for the multicomponent model . One of the first mixture-averaged thermal diffusion models is attributed to Chapman and Cowling  (in particular, §18.43). This model, based on the first approxima- tion of the thermal diffusion ratio, [ k Ti ] 1 , is derived from kinetic theory and reduces the cost of finding thermal diffusion coefficients by evaluating a simple set of alge- braic equations. This is in contrast to inverting a large linear system as is done in classical multicomponent diffusion modeling [37, 66]. Recently, a semi-empirical model  and polynomial fits  for the thermal diffusion coefficients have been proposed. While a fourth-order polynomial fit seemed to predict the species profiles in a specific configuration, the polynomial was acquired a posteriori  and, as such, extensive work would be necessary to show that the model is valid for a range of fuel mixtures and operating conditions. Thus, there is also a need to develop and evaluate a reduced-order thermal diffusion model applicable to a wide range of fuel mixtures and flame configurations.
Abstract: Alternative fuels have been getting more attention as concerns escalate over exhaust pollutant emissions produced by internal combustion engines, higher fuel costs, and the depletion of crude oil. Various solutions have been proposed, including utilizing alternative fuels as a dedicated fuel in spark ignited engines, diesel pilot ignition engines, gas turbines, and dual fuel and bi-fuel engines. Among these applications, one of the most promising options is the diesel derivative dual fuel engine with Alternate fuel as the supplement fuel. In present study we are using Ethanol as alternate fuel with Diesel to investigate the Dual fuel model with non-premixed & premixedcombustion and compare on the basic of combustion efficiency and pollutant emissions rate like carbonic oxides and nitric oxides. Ethanol is taking as an Alternate fuel which is cheaper in cost and easily available as compare to the conventional fuels. CFD Results shows a excellent flow phenomenon which is stable in nature and due to this the accuracy of the simulation results are higher for layer formation system in combustion. The pollutant emissions (Carbonic oxides) are decreasing in nonpremixedcombustion as compare to the premixedcombustion that shows the complete combustion rate is increased. NOx emissions are also decreasing in Non-premixed dual fuel (Diesel + Ethanol) model as compare to premixedcombustion. In second part of the study we are using Chemkin (Chemical kinetic) mechanism for evaluating the NOx pollutant which is responsible for thermal NOx . CFD Simulation results in Table no. 2 are clearly shows that mass fraction of NO, NO2 and N2O is