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.     

Dynamic adaptive chemistry for turbulent flame simulations

The use of large chemical mechanisms in flame simulations is computationally expensive due to the large number of chemical species and the wide range of chemical time scales involved. This study investigates the use of dynamic adaptive chemistry (DAC) for efficient chemistry calculations in turbulent flame simulations. DAC is achieved through the directed relation graph (DRG) method, which is invoked for each computational fluid dynamics cell/particle to obtain a small skeletal mechanism that is valid for the local thermochemical condition. Consequently, during reaction fractional steps, one needs to solve a smaller set of ordinary differential equations governing chemical kinetics. Test calculations are performed in a partially-stirred reactor (PaSR) involving both methane/air premixed and non-premixed combustion with chemistry described by the 53-species GRI-Mech 3.0 mechanism and the 129-species USC-Mech II mechanism augmented with recently updated NO _x pathways, respectively. Results show that, in the DAC approach, the DRG reduction threshold effectively controls the incurred errors in the predicted temperature and species concentrations. The computational saving achieved by DAC increases with the size of chemical kinetic mechanisms. For the PaSR simulations, DAC achieves a speedup factor of up to three for GRI-Mech 3.0 and up to six for USC-Mech II in simulation time, while at the same time maintaining good accuracy in temperature and species concentration predictions.     

A dynamic adaptive chemistry scheme for reactive flow computations

An on-the-fly kinetic mechanism reduction scheme, referred to as dynamic adaptive chemistry (DAC), has been developed to incorporate detailed chemical kinetics into reactive flow computations with high efficiency and accuracy. The procedure entails reducing a detailed mechanism to locally and instantaneously accurate sub-mechanisms at each hydrodynamic time step of the calculation, and consequently no a priori information regarding simulation conditions is needed. The reduction utilizes an extended version of the directed relation graph (DRG) method in which the edges are weighted by a value that measures the dependence of the tail species (vertex) on the head species. An R-value is then defined at each vertex as the maximum of the products of these weights along all paths to that vertex from an initiating species. Active species are identified by their R-values exceeding a threshold value, ε_R, using a modified breadth-first search (BFS) that starts from a pre-defined set of initiating species. Chemical kinetics equations are then formulated with respect to the active species, with the inactive species considered only as third body collision partners. The DAC method is implemented into CHEMKIN and tested by simulating homogeneous charge compression ignition (HCCI) combustion using detailed and pre-reduced n-heptane mechanisms (578 species and 178 species, respectively) as the full mechanisms. The DAC scheme reproduces with high accuracy the pressure curves and species mass fractions obtained using the full mechanisms. The on-the-fly mechanism reduction scheme introduces minimal computational overhead and achieves more than 30-fold time reduction in calculations using the 578-species mechanism.     

Combustion and emission modelling of a direct-injection spark-ignition engine by combining flamelet models for premixed and diffusion flames

The combustion and emission production processes of a DISI (direct-injection spark-ignition) engine were modelled by combining flamelet models for premixed and diffusion flames. A new surrogate fuel was proposed to approximate the complicated composition of real gasoline. In contrast to simpler conventional models, the fuel was modelled as a ternary mixture of three hydrocarbons: iso-octane, n-heptane and toluene. Turbulent flame propagation in a partially premixed field was modelled by a premixed flamelet model. The mass fractions of the detailed composition of species in burnt gas were predicted by a diffusion flamelet model. For the pollutant formation modelling, a two-step oxidation of CO and H₂ was used to simulate the secondary diffusion flame. The extended Zeldovich mechanism was used to model NOx formation, while a phenomenological model was used to model soot formation. This model was initially applied to a simple geometry to investigate the fundamentals of the model's behaviour, after which three-dimensional computational fluid dynamic (CFD) simulations were performed in a realistic engine geometry.     

Multidimensional chemistry coordinate mapping approach for combustion modelling with finite-rate chemistry

A multidimensional chemistry coordinate mapping (CCM) approach is presented for efficient integration of chemical kinetics in numerical simulations of turbulent reactive flows. In CCM the flow transport is integrated in the computational cells in physical space, whereas the integration chemical reactions are carried out in a phase space made up of a few principal variables. Each cell in the phase space corresponds to several computational cells in the physical space, resulting in a speedup of the numerical integration. In reactive flows with small hydrocarbon fuels two principal variables have been shown to be satisfactory to construct the phase space. The two principal variables are the temperature (T) and the specific element mass ratio of the H atom (J _H). A third principal variable, σ=?J _H·?J _H, which is related to the dissipation rate of J _H, is required to construct the phase space for combustion processes with an initially non-premixed mixture. For complex higher hydrocarbon fuels, e.g. n-heptane, care has to be taken in selecting the phase space in order to model the low-temperature chemistry and ignition process. In this article, a multidimensional CCM algorithm is described for a systematic selection of the principal variables. The method is evaluated by simulating a laminar partially remixed pre-vaporised n-heptane jet ignition process. The CCM approach is then extended to simulate n-heptane spray combustion by coupling the CCM and Reynolds averaged Navier–Stokes (RANS) code. It is shown that the computational time for the integration of chemical reactions can be reduced to only 3–7%, while the result from the CCM method is identical to that of direct integration of the chemistry in the computational cells.     

Low- and high-temperature study of n-heptane combustion chemistry

n-Heptane has been used extensively in various fundamental combustion experiments as a prototypical hydrocarbon fuel. While the formation of polycyclic aromatic hydrocarbon (PAH) in n-heptane combustion has been studied preferably in premixed flames, this study aims to investigate the combustion chemistry of n-heptane in less-studied diffusion flame and highly rich high-temperature homogeneous oxidation configurations by using a counterflow burner and a flow reactor, respectively. This work addresses the formation of higher-molecular species in the mass range up to about 160 u in both configurations. Samples are analyzed by time-of-flight (TOF) molecular beam mass spectrometry (MBMS) using electron-impact (EI) and single-photon ionization (PI). Highly resolved speciation data are reported. Laminar flow reactor experiments cover a wide temperature range. Especially the measurements at low temperatures provide speciation data of large oxygenates produced in the low-temperature oxidation of n-heptane, which are scarce in the literature. Important precursor molecules for PAH and soot formation, such as C₉H₈, C₁₀H₈, C₁₁H_10, and C₁₂H₈, are formed during the high-temperature combustion process in the counterflow flame, while oxygenated growth species are observed under low-temperature conditions, even at the fuel-rich equivalence ratio of ?=4.00.Numerical modeling for both conditions is performed by using a newly developed kinetic model of n-heptane, which includes the n-heptane and PAH formation chemistry with state-of-the-art kinetic knowledge. Good agreement between model predictions and experimental data of counterflow flame and flow reactor is observed for the major species and some intermediates of n-heptane oxidation. While the concentrations of benzene and toluene measured in the counterflow burner are well-reproduced, the numerical results for flow reactor data are not satisfactory. Differences are found between the formation pathways of fulvene, from whose isomerization benzene is produced in diffusion flame and flow reactor.     

Influence of pilot-fuel mixing on the spatio-temporal progression of two-stage autoignition of diesel-sprays in low-reactivity ambient fuel-air mixture

The spatial and temporal locations of autoignition for direct-injection compression-ignition engines depend on fuel chemistry, temperature, pressure, and mixing trajectories in the fuel jets. Dual-fuel systems can provide insight into both fuel-chemistry and physical effects by varying fuel reactivities and engine operating conditions. In this context, the spatial and temporal progression of two-stage autoignition of a diesel-fuel surrogate, n-heptane, in a lean-premixed charge of synthetic natural-gas (NG) and air is imaged in an optically accessible heavy-duty diesel engine. The lean-premixed charge of NG is prepared by fumigation upstream of the engine intake manifold. Optical diagnostics include high-speed (15kfps) cool-flame chemiluminescence-imaging as an indicator of low-temperature heat-release (LTHR) and OH* chemiluminescence-imaging as an indicator high-temperature heat-release (HTHR). NG prolongs the ignition delay of the pilot fuel and increases the combustion duration. Zero-dimensional chemical-kinetics simulations provide further understanding by replicating a Lagrangian perspective for mixtures evolving along streamlines originating either at the fuel nozzle or in the ambient gas, for which the pilot-fuel concentration is either decreasing or increasing, respectively. The zero-dimensional simulations predict that LTHR initiates most likely on the air streamlines before transitioning to HTHR, either on fuel-streamlines or on air-streamlines in regions of near-constant ?. Due to the relatively short pilot-fuel injection-durations, the transient increase in entrainment near the end of injection (entrainment wave) is important for quickly creating auto-ignitable mixtures. To achieve desired combustion characteristics, e.g., multiple ignition-kernels and favorable combustion phasing and location (e.g., for reducing wall heat-transfer or optimizing charge stratification), adjusting injection parameters could tailor mixing trajectories to offset changes in fuel ignition chemistry.     

Influence of NOx chemistry on the prediction of natural gas end-gas autoignition in CFD engine simulations

Natural gas (NG) represents a promising low-cost/low-emission alternative to diesel fuel when used in high-efficiency internal combustion engines. Advanced combustion strategies utilizing high EGR rates and controlled end-gas autoignition can be implemented with NG to achieve diesel-like efficiencies; however, to support the design of these next-generation NG ICEs, computational tools, including single- and multi-dimensional simulation packages will need to account for the complex chemistry that can occur between the reactive species found in EGR (including NOx) and the fuel. Research has shown that NOx plays an important role in the promotion/inhibition of large hydrocarbon autoignition and when accounted for in CFD engine simulations, can significantly improve the prediction of end-gas autoignition for these fuels. However, reduced NOx-enabled NG mechanisms for use in CFD engine simulations are lacking, and as a result, the influence of NOx chemistry on NG engine operation remains unknown. Here, we analyze the effects of NOx chemistry on the prediction of NG/oxidizer/EGR autoignition and generate a reduced mechanism of a suitable size to be used in engine simulations. Results indicate that NG ignition is sensitive to NOx chemistry, where it was observed that the addition of EGR, which included NOx, promoted NG autoignition. The modified mechanism captured well all trends and closely matched experimentally measured ignition delay times for a wide range of EGR rates and NG compositions. The importance of C2-C3 chemistry is noted, especially for wet NG compositions containing high fractions of ethane and propane. Finally, when utilized in CFD simulations of a Cooperative Fuels Research (CFR) engine, the new reduced mechanism was able to predict the knock onset crank angle (KOCA) to within one crank angle degree of experimental data, a significant improvement compared to previous simulations without NOx chemistry.     

LES modelling of turbulent non-premixed jet flames with correlated dynamic adaptive chemistry

Large eddy simulations (LES) for turbulent flames with detailed kinetic mechanisms have received growing interest. However, a direct implementation of detailed kinetic mechanisms in LES modelling of turbulent combustion remains a challenge due to the requirement of huge computational resources. An on-the-fly mechanism reduction method named correlated dynamic adaptive chemistry (CoDAC) is proposed to overcome this issue. A LES was conducted for Sandia Flame-D, with the reaction mechanism of GRI-Mech 3.0 consisting of 53 species and 325 reactions. The reduction threshold used in LES was obtained a priori by using auto-ignition model and partially stirred reactor (PaSR) with pairwise mixing model. LES results with CoDAC are in good agreement with experimental data and those without reduction. The conditional mean of the number of selected species indicates that a large size of locally reduced mechanism is required in the reaction zone where CH₄ is destructed. A computational time analysis shows that the PaSR model predicts better than the auto-ignition model on the wall time reduction with CoDAC in LES.     

Investigation of the Livengood–Wu integral for modelling autoignition in a high-pressure bomb

The reaction progress variable, which is widely used in premixed and diffusion combustion studies, comprises a set of pre-selected intermediate species to denote reaction progress. Progress towards autoignition can also be traced by the Livengood–Wu (LW) integral. Autoignition occurs when the LW integral attains a value of unity. This concept is further explored by applying it to an inhomogeneous mixture scenario, to determine the time and place of autoignition occurrence. A semidetailed mechanism (137 species and 633 reactions) for n-heptane/iso-octane/toluene is used in this study. Two numerical schemes based on the LW integral are proposed and incorporated into a computational fluid dynamics platform, to model autoignition in a 3D configuration, when a spray is injected into a constant volume bomb under diesel engine conditions. Tabulated chemistry, a traditional method of modelling autoignition using information from pre-calculated igniting diffusion flames, is also used for comparison purposes. The associated predicted pressure profiles are compared with experimental measurements.