Chemistry Solver Research Articles

A mixing controlled direct chemistry (MCDC) model for diesel engine combustion modelling using large eddy simulation

A mixing controlled direct chemistry (MCDC) combustion model with sub-grid scale (SGS) mixing effects and chemical kinetics has been evaluated for Large Eddy Simulation (LES) of diesel engine combustion. The mixing effect is modelled by a mixing timescale based on mixture fraction variance and sub-grid scalar dissipation rate. The SGS scalar dissipation rate is modelled using a similarity term and a scaling factor from the analysis of Direct Numerical Simulation (DNS) data. The chemical reaction progress is estimated from a kinetic timescale based on local internal energy change rate and equilibrium state internal energy. An optical research engine operating at conventional operating conditions and Low Temperature Combustion (LTC) conditions was used for evaluation of the combustion model. From the simulation results, the effect of SGS scalar mixing is evaluated at different stages of combustion. In the context of LES, the new approach provides improved engine modelling results compared to the Direct Chemistry Solver (DCS) combustion model.

An improved high-order scheme for DNS of low Mach number turbulent reacting flows based on stiff chemistry solver

We present an improved numerical scheme for numerical simulations of low Mach number turbulent reacting flows with detailed chemistry and transport. The method is based on a semi-implicit operator-splitting scheme with a stiff solver for integration of the chemical kinetic rates, developed by Knio et al. [O.M. Knio, H.N. Najm, P.S. Wyckoff, A semi-implicit numerical scheme for reacting flow II. Stiff, operator-split formulation, Journal of Computational Physics 154 (2) (1999) 428–467]. Using the material derivative form of continuity equation, we enhance the scheme to allow for large density ratio in the flow field. The scheme is developed for direct numerical simulation of turbulent reacting flow by employing high-order discretization for the spatial terms. The accuracy of the scheme in space and time is verified by examining the grid/time-step dependency on one-dimensional benchmark cases: a freely propagating premixed flame in an open environment and in an enclosure related to spark-ignition engines. The scheme is then examined in simulations of a two-dimensional laminar flame/vortex-pair interaction. Furthermore, we apply the scheme to direct numerical simulation of a homogeneous charge compression ignition (HCCI) process in an enclosure studied previously in the literature. Satisfactory agreement is found in terms of the overall ignition behavior, local reaction zone structures and statistical quantities. Finally, the scheme is used to study the development of intrinsic flame instabilities in a lean H2/air premixed flame, where it is shown that the spatial and temporary accuracies of numerical schemes can have great impact on the prediction of the sensitive nonlinear evolution process of flame instability.

Numerical and Experimental Study on the Combustion and Emission Characteristics of a Dimethyl Ether (DME) Fueled Compression Ignition Engine

A numerical investigation was carried out to study on the combustion and emission characteristics of dimethyl ether (DME) with wide ranges of injection timings in compression ignition engines. In order to simulate DME combustion processes, a KIVA-3V code coupled with a chemistry solver was used to solve the detailed chemical kinetics model of DME oxidation. In addition, the Kelvin-Helmholtz-Rayleigh-Taylor (KH-RT) hybrid breakup model and Renormalization Group (RNG) k-e models were applied to analyze the spray characteristics and turbulent flow, respectively. To predict the NOx formation during DME combustion, a reduced Gas Research Institute (GRI) NO mechanism was used. From these results on the combustion and emission, the calculated results were compared with experimental ones for the same operating conditions. In the combustion characteristics, the calculated combustion pressure and heat release rates agreed well with experimental results. The levels of experimental NOx emissions was reduced as the start of the injection timing retarded, and also these trends appeared in calculated emission characteristics. Additionally, the calculated CO and HC emissions show an increasing trend as the start of the injection is retarded.

Optimization of combustion chamber geometry and engine operating conditions for compression ignition engines fueled with dimethyl ether

This paper describes the optimization of compression ignition engines fueled with dimethyl ether (DME), an alternative to diesel fuel. In order to calculate in-cylinder flow and combustion processes, a KIVA code, coupled with the Chemkin chemistry solver, was used. The optimization processes were performed based on a micro-genetic algorithm with a population number of five for each generation. The optimization processes were performed for one hundred generations. In addition, the computational mesh generated an auto-mesh generator, which was able to produce a computational mesh based on the given parameters, such as cup depth and Beizer curve definitions. The optimized design for the DME engine was also compared to that of conventional diesel engines for combustion and emission characteristics.The results showed that significant merit value improvements were achieved for both DME and diesel engines with the presented optimization. For the optimized design of DME engines, the combustion and emission characteristics were significantly different from those of diesel engines because of differences in fuel properties. For conventional diesel engine cases, a 136% improvement in merit value was achieved during the optimization process from the baseline to the optimized design.

Investigation of fuel injection pattern on soot formation and oxidation processes in a light-duty diesel engine using integrated CFD-reduced chemistry

In this reported work, simulation studies of in-cylinder diesel combustion and soot formation processes under different configuration of the split-main injection scheme were presented. Numerical computation was performed by linking a plug-in chemistry solver CHEMKIN-CFD into ANSYS FLUENT package, in order to integrate chemical kinetic mechanism and Computational Fluid Dynamics (CFD) computations. For improved computational runtime, an in-house reduced chemical mechanism was coupled with the CFD code. The reduced mechanism comprises 112 reactions with 46 species essential to diesel ignition/combustion and the formation of soot precursors and nitrogen monoxide (NO). Numerical models were first validated against experimental combustion characteristics as well as concentrations of engine-out soot and NO of a single-cylinder, light-duty diesel engine when using a split-main injection scheme. Parameters of this injection scheme were then investigated, which included start of injection (SOI) timings, fuel mass ratios of the injection pulses and the dwell period in between injections. The key interest here was to elucidate how these affect exhaust NO and soot levels, and in particular the in-cylinder soot formation and oxidation events. Fuel mass injected, duration of the injection and in-cylinder temperature were found to shape the soot formation and oxidation processes, which eventually produced the observed variations in the soot density at exhaust valve opening time. Based on all the simulation data from this reported work, power law was found to accurately describe the correlations between soot surface growth rate and gas mass fraction with a temperature range of 1400–2800K and an equivalence ratio values of greater than unity. The values of both constants of the power law were highly sensitive to the in-cylinder mean gas temperatures. The findings here are helpful in providing a better understanding of in-cylinder diesel soot formation and oxidation processes in this combustion system.

MS3-4 A CPU Efficient SI In-Cylinder Combustion and Knock Prediction Model Utilizing a Stochastic Reactor Approach, Turbulent Flame Propagation and Detailed Chemistry(MS: Modeling and Simulation,General Session Papers)

An accurate in-cylinder combustion model for SI-engines has been constructed by combining a stochastic reactor model with predictive turbulent flame propagation. The computational time for full cycle calculations is kept low through load balanced parallelization and particle clustering. This paper presents a two-zone zero dimensional transported probability density function model, utilizing a stochastic reactor for solution of the ordinary differential equations in each zone. A turbulent flame propagation model is applied, and laminar flame speed is achieved from a flame speed library built with detailed chemistry. The flame front is tracked with a CPU efficient polygon method. Knock and emissions are calculated using on-line detailed chemistry. The model has previously shown very good predictability of combustion as well as knock. In this work, the model calculation time has been decreased through load balanced distribution of the on-line chemistry calculations on a large number of CPU's. In addition, an algorithm for chemical state based particle clustering in each zone has been developed. Particles are clumped into groups based on user provided dispersion thresholds for any number of cluster tracking parameters. As a consequence, not all particles need to be treated during the chemistry step; only one cluster representative particle needs to be passed to the chemistry solver. The paper presents the clustering algorithm, and its verification. It is shown that a very limited number of clustering parameters can be used, and that the dispersion thresholds can be set high. On average, the clustering yields a factor 3-4 in speedup of chemistry calculations and CPU times of about a minute per cycle are achieved. Since chemistry and in-homogeneities are taken into account this yields a model suitable for e.g. fuel analysis and performance studies.

Optimization of injection strategy to reduce fuel consumption for stoichiometric diesel combustion

In the present study, optimization of engine operating conditions was performed to reduce fuel consumption for stoichiometric diesel combustion. Microgenetic algorithms were used, and variations of injection strategy, spray included angle, and initial conditions (such as temperature and pressure) were evaluated. The KIVA code, coupled with the Chemkin chemistry solver, was used for three-dimensional CFD modeling, and the ignition and combustion processes were modeled using a reduced n-heptane mechanism. The KIVA code in use was verified against pressure histories and emissions for stoichiometric diesel combustion obtained experimentally.Optimized engine operating conditions for minimum fuel consumption were found at the 43rd generation. The optimized case includes 50–50% split injection, reduced spray included for reduction of unburned HC in crevices, and lower oxygen concentration to retard combustion phasing. This optimization yielded an 11.8% improvement in fuel consumption, along with simultaneous reductions of soot, NOx, CO, and HC.

Chemical Mechanism Solvers in Air Quality Models

The solution of chemical kinetics is one of the most computationally intensivetasks in atmospheric chemical transport simulations. Due to the stiff nature of the system,implicit time stepping algorithms which repeatedly solve linear systems of equations arenecessary. This paper reviews the issues and challenges associated with the construction ofefficient chemical solvers, discusses several families of algorithms, presents strategies forincreasing computational efficiency, and gives insight into implementing chemical solverson accelerated computer architectures.

Development of an integrated reduced fuel oxidation and soot precursor formation mechanism for CFD simulations of diesel combustion

In this reported work, a reduced chemical mechanism of surrogate diesel fuel was developed for diesel engine simulations. The aim here was to employ an appropriate reduction scheme to create a compact yet sufficiently comprehensive model which can accurately account for in-cylinder diesel combustion and soot precursor formation processes. The Combustion Engine Research Center (CERC) mechanism of Chalmers University of Technology was used as the base mechanism since this is the most extensively validated and applied mechanism. The reduction scheme involved firstly identifying and then eliminating unimportant species/reactions in the ignition and soot precursor formation processes through the computed production rates and temperature sensitivity coefficients using CHEMKIN-PRO software. Subsequently, reactions were assimilated based on the quasi-steady state assumption (QSSA). The final reduced mechanism, which consists of 109 elementary reactions with 44 species, was first validated under 48 shock tube conditions. Ignition delay (ID) periods predicted by the reduced and base CERC mechanisms were found to be in good agreement, although percentage errors of up to 20% were observed. Further validation was performed by incorporating the reduced mechanism into multi-dimensional CFD code, ANSYS FLUENT through a plug-in chemistry solver, CHEMKIN-CFD. Here, simulation results of combustion characteristics and soot production profiles were compared against data from an experimental study on a heavy-duty, direct injection diesel engine. Simulated peak pressures in cases with short and long ID periods were identical to those recorded from experiments and the maximum ID offset was maintained to within 1 crank angle degree. Spatial and temporal evolutions of in-cylinder soot were also captured successfully in both cases. Significant qualitative relationship between input parameters and soot evolution was elucidated from this study. The implementation of the reduced mechanism has achieved a 38% reduction in computational runtime when compared with that of the base mechanism.

The effects of active chlorine on photooxidation of 2-methyl-2-butene

Active chlorine comprising hypochlorite (OCl −), hypochlorous acid (HOCl) and chlorine (Cl 2) is the active constituent in bleach formulations for a variety of industrial and consumer applications. However, the strong oxidative reactivity of active chlorine can cause adverse effects on both human health and the environment. In this study, aerosolized Oxone® [2KHSO 5, KHSO 4, K 2SO 4] with saline solution has been utilized to produce active chlorine (HOCl and Cl 2). To investigate the impact of active chlorine on volatile organic compound (VOC) oxidation, 2-methyl-2-butene (MB) was photoirradiated in the presence of active chlorine using a 2-m 3 Teflon film indoor chamber. The resulting carbonyl products produced from photooxidation of MB were derivatized with O-(2,3,4,5,6-pentafluorobenzyl) hydroxyamine hydrochloride (PFBHA) and analyzed using gas chromatograph–ion trap mass spectrometer (GC/ITMS). The photooxidation of MB in the presence of active chlorine was simulated with an explicit kinetic model using a chemical solver (Morpho) which included both Master Chemical Mechanism (MCM) and Cl radical reactions. The reaction rate constants of a Cl radical with MB and its oxidized products were estimated using a Structure–Reactivity Relationship method. Under dark conditions no effect of active chlorine on MB oxidation was apparent, whereas under simulated daylight conditions (UV irradiation) rapid MB oxidation was observed due to photo-dissociation of active chlorine. The model simulation agrees with chamber data showing rapid production of oxygenated products that are characterized using GC/ITMS. Ozone formation was enhanced when MB was oxidized in the presence of irradiated active chlorine and NO x .

Radamesh: cosmological radiative transfer for Adaptive Mesh Refinement simulations

We present a new three-dimensional radiative transfer (RT) code, RADAMESH, based on a ray-tracing, photon-conserving and adaptive (in space and time) scheme. RADAMESH uses a novel Monte Carlo approach to sample the radiation field within the computational domain on a "cell-by-cell" basis. Thanks to this algorithm, the computational efforts are now focused where actually needed, i.e. within the Ionization-fronts (I-fronts). This results in an increased accuracy level and, at the same time, a huge gain in computational speed with respect to a "classical" Monte Carlo RT, especially when combined with an Adaptive Mesh Refinement (AMR) scheme. Among several new features, RADAMESH is able to adaptively refine the computational mesh in correspondence of the I-fronts, allowing to fully resolve them within large, cosmological boxes. We follow the propagation of ionizing radiation from an arbitrary number of sources and from the recombination radiation produced by H and He. The chemical state of six species (HI, HII, HeI, HeII, HeIII, e) and gas temperatures are computed with a time-dependent, non-equilibrium chemistry solver. We present several validating tests of the code, including the standard tests from the RT Code Comparison Project and a new set of tests aimed at substantiating the new characteristics of RADAMESH. Using our AMR scheme, we show that properly resolving the I-front of a bright quasar during Reionization produces a large increase of the predicted gas temperature within the whole HII region. Also, we discuss how H and He recombination radiation is able to substantially change the ionization state of both species (for the classical Stroemgren sphere test) with respect to the widely used "on-the-spot" approximation.

REIONIZATION SIMULATIONS POWERED BY GRAPHICS PROCESSING UNITS. I. ON THE STRUCTURE OF THE ULTRAVIOLET RADIATION FIELD

We present a set of cosmological simulations with radiative transfer in order to model the reionization history of the universe from z = 18 down to z = 6. Galaxy formation and the associated star formation are followed self-consistently with gas and dark matter dynamics using the RAMSES code, while radiative transfer is performed as a post-processing step using a moment-based method with the M1 closure relation in the ATON code. The latter has been ported to a multiple Graphics Processing Unit (GPU) architecture using the CUDA language together with the MPI library, resulting in an overall acceleration that allows us to tackle radiative transfer problems at a significantly higher resolution than previously reported: 10243 + 2 levels of refinement for the hydrodynamic adaptive grid and 10243 for the radiative transfer Cartesian grid. We reach a typical acceleration factor close to 100× when compared to the CPU version, allowing us to perform 1/4 million time steps in less than 3000 GPU hr. We observe good convergence properties between our different resolution runs for various volume- and mass-averaged quantities such as neutral fraction, UV background, and Thomson optical depth, as long as the effects of finite resolution on the star formation history are properly taken into account. We also show that the neutral fraction depends on the total mass density, in a way close to the predictions of photoionization equilibrium, as long as the effect of self-shielding are included in the background radiation model. Although our simulation suite has reached unprecedented mass and spatial resolution, we still fail in reproducing the z ∼ 6 constraints on the neutral fraction of hydrogen and the intensity of the UV background. In order to account for unresolved density fluctuations, we have modified our chemistry solver with a simple clumping factor model. Using our most spatially resolved simulation (12.5 Mpc h−1 with 10243 particles) to calibrate our subgrid model, we have resimulated our largest box (100 Mpc h−1 with 10243 particles) with the modified chemistry, successfully reproducing the observed level of neutral hydrogen in the spectra of high-redshift quasars. We however did not reproduce the average photoionization rate inferred from the same observations. We argue that this discrepancy could be partly explained by the fact that the average radiation intensity and the average neutral fraction depend on different regions of the gas density distribution, so that one quantity cannot be simply deduced from the other.

An adaptive reduction algorithm for efficient chemical calculations in global atmospheric chemistry models

We present a computationally efficient adaptive method for calculating the time evolution of the concentrations of chemical species in global 3-D models of atmospheric chemistry. Our strategy consists of partitioning the computational domain into fast and slow regions for each chemical species at every time step. In each grid box, we group the fast species and solve for their concentration in a coupled fashion. Concentrations of the slow species are calculated using a simple semi-implicit formula. Separation of species between fast and slow is done on the fly based on their local production and loss rates. This allows for example to exclude short-lived volatile organic compounds (VOCs) and their oxidation products from chemical calculations in the remote troposphere where their concentrations are negligible, letting the simulation determine the exclusion domain and allowing species to drop out individually from the coupled chemical calculation as their production/loss rates decline. We applied our method to a 1-year simulation of global tropospheric ozone-NO x -VOC-aerosol chemistry using the GEOS-Chem model. Results show a 50% improvement in computational performance for the chemical solver, with no significant added error.

Optimization of a heavy-duty compression–ignition engine fueled with diesel and gasoline-like fuels

Optimal injection strategies for a heavy-duty compression–ignition engine fueled with diesel and gasoline-like fuels (#91 gasoline and E10) and operated under mid- and high-load conditions are investigated. A state-of-the-art engine CFD tool with detailed fuel chemistry was used to evaluate the engine performance and pollutant emissions. The CFD tools feature a recently developed efficient chemistry solver that allowed the optimization tasks to be completed in practical computer times. A Non-dominated Sorting Genetic Algorithm II (NSGA II) was coupled with the CFD tool to seek optimal combinations of injection system variables to achieve clean and efficient combustion. The optimization study identified several key parameters that influence engine performance. It was found that the fuel volatility and reactivity both play important roles at the mid-load condition, while the high-load condition is less sensitive to the fuel reactivity. However, high volatility fuels, such as gasoline and E10, were found to be beneficial to fuel economy at high-load. The study indicates that with an optimized injection system gasoline-like fuels are promising for heavy-duty CI engines due to their lower NOx and soot emissions and higher fuel economy compared to conventional diesel fuels. However, the high in-cylinder gas pressure rise rate associated with Partially Premixed Combustion of gasoline-like fuels can become problematic at high-load and the low-load operating limit is also a challenge. Potential solutions are discussed based on the present optimization results.

Acceleration of the chemistry solver for modeling DI engine combustion using dynamic adaptive chemistry (DAC) schemes

Acceleration of the chemistry solver for engine combustion is of much interest due to the fact that in practical engine simulations extensive computational time is spent solving the fuel oxidation and emission formation chemistry. A dynamic adaptive chemistry (DAC) scheme based on a directed relation graph error propagation (DRGEP) method has been applied to study homogeneous charge compression ignition (HCCI) engine combustion with detailed chemistry (over 500 species) previously using an R-value-based breadth-first search (RBFS) algorithm, which significantly reduced computational times (by as much as 30-fold). The present paper extends the use of this on-the-fly kinetic mechanism reduction scheme to model combustion in direct-injection (DI) engines. It was found that the DAC scheme becomes less efficient when applied to DI engine simulations using a kinetic mechanism of relatively small size and the accuracy of the original DAC scheme decreases for conventional non-premixed combustion engine. The present study also focuses on determination of search-initiating species, involvement of the NOx chemistry, selection of a proper error tolerance, as well as treatment of the interaction of chemical heat release and the fuel spray. Both the DAC schemes were integrated into the ERC KIVA-3v2 code, and simulations were conducted to compare the two schemes. In general, the present DAC scheme has better efficiency and similar accuracy compared to the previous DAC scheme. The efficiency depends on the size of the chemical kinetics mechanism used and the engine operating conditions. For cases using a small n-heptane kinetic mechanism of 34 species, 30% of the computational time is saved, and 50% for a larger n-heptane kinetic mechanism of 61 species. The paper also demonstrates that by combining the present DAC scheme with an adaptive multi-grid chemistry (AMC) solver, it is feasible to simulate a direct-injection engine using a detailed n-heptane mechanism with 543 species with practical computer time.

Computational Fluid Dynamics modelling of ultra-lean porous burners

Porous burners offer potential for ultra-lean methane emission mitigation by combustion. In these systems, heat recirculation between the porous medium and the fuel stream leads to enhanced combustion behaviour. In this research, conductive, convective and radiative heat transfer models were added in the commercial Computational Fluid Dynamics (CFD) code ANSYS CFX, to describe the interaction between the porous solid and the fluid. Relatively detailed skeletal kinetic mechanisms were implemented and a stiff chemistry solver was used to account for the differing chemical and fluid dynamics timescales. Results from test cases are presented to illustrate the model performance and to highlight some computational issues.

Numerical Study on Combustion and Emission Characteristics of Homogeneous Charge Compression Ignition Engines Fueled with Biodiesel

This paper describes a numerical study on the effect of the mixing ratio of biodiesel on combustion and emission characteristics of homogeneous charge compression ignition engines. The KIVA code coupled with Chemkin chemistry solver was used to simulated combustion and emission formation processes. A modified reduced methyl butanoate mechanism was used after combining with a reduced n-heptane mechanism to model ignition and combustion of biodiesel. The mixing ratio of biodiesel was varied from 0% (conventional diesel) to 100% (pure biodiesel). Operating ranges covered up to a 2.0 equivalence ratio. The fueling rate was fixed at 18 mg/cyc, which corresponds to a medium engine load. Results of the present study showed that the ignition delay of biodiesel is shorter than that of conventional diesel fuel because of the higher cetane number of biodiesel. Little differences of emission maps for CO and NOx emissions are found between biodiesel and conventional diesel. However, higher concentration regions for hy...

A global method for coupling transport with chemistry in heterogeneous porous media

Modeling reactive transport in porous media, using a local chemical equilibrium assumption, leads to a system of advection–diffusion PDEs coupled with algebraic equations. When solving this coupled system, the algebraic equations have to be solved at each grid point for each chemical species and at each time step. This leads to a coupled non-linear system. In this paper, a global solution approach that enables to keep the software codes for transport and chemistry distinct is proposed. The method applies the Newton–Krylov framework to the formulation for reactive transport used in operator splitting. The method is formulated in terms of total mobile and total fixed concentrations and uses the chemical solver as a black box, as it only requires that one be able to solve chemical equilibrium problems (and compute derivatives) without having to know the solution method. An additional advantage of the Newton–Krylov method is that the Jacobian is only needed as an operator in a Jacobian matrix times vector product. The proposed method is tested on the MoMaS reactive transport benchmark.

Implementation and evaluation of an array of chemical solvers in the Global Chemical Transport Model GEOS-Chem

Abstract. This paper discusses the implementation and performance of an array of gas-phase chemistry solvers for the state-of-the-science GEOS-Chem global chemical transport model. The implementation is based on the Kinetic PreProcessor (KPP). Two perl parsers automatically generate the needed interfaces between GEOS-Chem and KPP, and allow access to the chemical simulation code without any additional programming effort. This work illustrates the potential of KPP to positively impact global chemical transport modeling by providing additional functionality as follows. (1) The user can select a highly efficient numerical integration method from an array of solvers available in the KPP library. (2) KPP offers a wide variety of user options for studies that involve changing the chemical mechanism (e.g., a set of additional reactions is automatically translated into efficient code and incorporated into a modified global model). (3) This work provides access to tangent linear, continuous adjoint, and discrete adjoint chemical models, with applications to sensitivity analysis and data assimilation.

An adaptive multi-grid chemistry (AMC) model for efficient simulation of HCCI and DI engine combustion

There is a need to reduce the computational expense of practical multidimensional combustion simulations. Simulation of Homogeneous Charge Compression Ignition (HCCI) engine processes requires consideration of detailed chemistry in order to capture the ignition and combustion characteristics. Even with relatively coarse numerical meshes and reduced chemistry mechanisms, calculation times are still unacceptably long. For the simulation of Direct Injection (DI) engines, fine meshes are needed to achieve the resolution required by the spray and mixing models, and they are computationally expensive even with reduced chemistry. In addition, the increasing application of CFD for engine design optimization is pushing the demand to reduce computational time. In current design optimizations, depending on the size of the parametric space, hundreds of individual simulations are needed. This work presents an efficient Adaptive Multi-grid Chemistry (AMC) model that can be used in engine CFD codes for simulations of HCCI and DI engines with detailed chemistry. It was found that the number of cells computed with the chemistry solver can be reduced by two orders of magnitude for HCCI engines. The results predicted by the present KIVA AMC code are also consistent with those calculated by the original code using every cell. In the method, progressively coarser grids are used for cells with similar gas properties in the chemistry calculation (up to four neighbour levels) or in the global method, cells are grouped without regard for their locations in the cylinder. Averaged and gradient-preserving remapping techniques used in multi-zone engine simulations were also explored. A parametric study was conducted for determining the model variables, such as the degree of local homogeneity for the multi-grid solvers. The simulation results were compared with experimental data obtained from a Honda engine operated with n-heptane under HCCI conditions for which directly measured in-cylinder temperature and H2O mole fraction data are available. In addition, simulation results were found to agree well with experimental data from a DI diesel engine operated under PCCI conditions with ultra-high EGR rates. It was found that computer time was reduced by a factor of ten for HCCI cases and two to three for DI cases without losing prediction accuracy.