Harry Lehtiniemi

MODELING DIESEL SPRAY IGNITION USING DETAILED CHEMISTRY WITH A PROGRESS VARIABLE APPROACH

In this work, a progress variable approach is used to model diesel spray ignition with detailed chemistry. The flow field and the detailed chemistry are coupled using the flamelet assumption. A flamelet progress variable is transported by the computational fluid dynamics (CFD) code. The progress variable source term is obtained from an unsteady flamelet library that is evaluated in each grid cell. The progress variable chosen is based on sensible enthalpy. By using an unsteady flamelet library for the progress variable, the impact of local effects, for example variations in the turbulence field, effects of wall heat transfer etc. on the autoignition chemistry can be considered on a cell level. The coupling between the unsteady flamelet library and the transport equation for total enthalpy follows the ideas of the representative interactive flamelet (RIF) approach. The method can be compared to having an interactive flamelet in each computational cell in the CFD grid. The results obtained using the proposed model are compared to results obtained using the RIF model. Differences are exhibited during the autoignition process. After ignition, the results obtained using the proposed model and RIF are virtually identical. The model was used to study lift-off lengths in sprays as function of nozzle diameter and injection pressure. A good agreement between model predictions and experimental trends was found.

Aspects of modeling soot formation in turbulent diffusion flames

Soot formation in a turbulent jet diffusion flame is modeled using an unsteady flamelet approach. In the present work, we study the effects of the choice of the dependence of scalar dissipation rate on mixture fraction and agglomeration processes on the predicted soot volume fraction. It is found that good predictions of soot volume fraction can be obtained without considering preferential diffusion effects.

Modeling Diesel Engine Combustion With Detailed Chemistry Using a Progress Variable Approach

In this work, we present an unsteady flamelet progress variable approach for diesel engine CFD combustion modelling. The progress variable is based on sensible enthalpy integrated over the flamelet and describes the transient flamelet ignition process. By using an unsteady flamelet library for the progress variable, the impact of local effects, for example variations in the turbulence field, effects of wall heat transfer, etc., on the autoignition chemistry can be considered on a cell level. The coupling between the unsteady flamelet library and the transport equation for total enthalpy follows the ideas of the representative interactive flamelet approach. Since the progress variable gives a direct description of the state in the flamelet, the method can be compared to having a flamelet in each computational cell in the CFD grid. The progress variable approach is applied to high-EGR, late injection operating conditions, and we demonstrate that the model can be applied for 3D engine simulations. (Less)

Stochastic model for the investigation of the influence of turbulent mixing on engine knock

A stochastic model based on a probability density function (PDF) was developed for the investigation of different conditions that determine knock in spark ignition (SI) engine, with focus on the turbulent mixing. The model used is based on a two-zone approach, where the burned and unburned gases are described as stochastic reactors. By using a stochastic ensemble to represent the PDF of the scalar variables associated with the burned and the unburned gases it is possible to investigate phenomena that are neglected by the regular existing models (as gas non-uniformity, turbulence mixing, or the variable gas-wall interaction). Two mixing models are implemented for describing the turbulent mixing: the deterministic interaction by exchange with the mean (IEM) model and the stochastic coalescence/ dispersal (C/D) model. Also, a stochastic jump process is employed for modeling the irregularities in the heat transfer. Parameter studies are carried out in order to assess the influence of the turbulence intensity and of the fluctuations in the gas - wall interactions.

Effect of Turbulence and Initial Temperature Inhomogeneity on Homogeneous Charge Compression Ignition Combustion

A 0.5-liter optical HCCI engine firing a mixture of n-heptane (50%) and iso-octane (50%) with air/fuel ratio of 3 is studied using large eddy simulation (LES) and laser diagnostics. Formaldehyde and OH LIF and in-cylinder pressure were measured in the experiments to characterize the ignition process. The LES made use of a detailed chemical kinetic mechanism that consists of 233 species and 2019 reactions. The auto-ignition simulation is coupled with LES by the use of a renormalized reaction progress variable. Systematic LES study on the effect of initial temperature inhomogeneity and turbulence intensity has been carried out to delineate their effect on the ignition process. It was shown that the charge under the present experimental condition would not be ignited without initial temperature inhomogeneity. Increasing temperature inhomogeneity leads to earlier ignition whereas increasing turbulence intensity would retard the ignition. This is mostly due to the effect of turbulence on the bulk flow that turbulence tends to decrease the temperature inhomogeneity by enhanced eddy heat transfer. The LES results suggest that desirable ignition timing could be achieved by controlling the turbulence intensity and temperature inhomogeneity.

Aspects of 0D and 3D Modeling of Soot Formation for Diesel Engines

In this work, zero-dimensional (0D) and three-dimensional (3D) models were applied to the same engine experiment, investigating aspects of 0D and 3D modeling of combustion and soot formation for diesel engines. The 0D simulations were carried out using a direct injection stochastic reactor model (DI-SRM), which is built on a probability density function (PDF) approach. The 0D model allows for the use of detailed chemistry for calculation of combustion, emission formation, and interaction between chemistry and turbulent flow. The 3D computational fluid dynamics (CFD) simulations were performed using a PDF-time scale combustion model and a flamelet library soot source term model. The DI-SRM results demonstrate the applicability of the flamelet model for the combustion process and also elucidate the limitations of the interactive flamelet model when calculating emission formation. The emission results, if plotted in mixture fraction space, show a dispersion for species such as NO and CO, but a flamelet structure for species such as C2H2 and OH, which makes the latter ones applicable for calculation of the source terms of soot formation in mixture fraction space. The CFD calculations were used to verify assumptions made in the DI-SRM and the DI-SRM results were used to verify the assumptions inferred by using tabulated chemistry. It is demonstrated that the DI-SRM can be used for soot modeling under diesel engine conditions and that the flamelet library approach for modeling of soot formation in CFD is sound.

Potential Levels of Soot, NO x , HC and CO for Methanol Combustion

Methanol is today considered a viable green fuel for combustion engines because of its low soot emissions and the possibility of it being produced in a CO2-neutral manner. Methanol as a fuel for combustion engines have attracted interest throughout history and much research was conducted during the oil crisis in the seventies. In the beginning of the eighties the oil prices began to decrease and interest in methanol declined. This paper presents the emission potential of methanol. T-Φ maps were constructed using a 0-D reactor with constant pressure, temperature and equivalence ratio to show the emission characteristics of methanol. These maps were compared with equivalent maps for diesel fuel. The maps were then complemented with engine simulations using a stochastic reactor model (SRM), which predicts end-gas emissions. The SRM was validated using experimental results from a truck engine running in Partially Premixed Combustion (PPC) mode at medium loads. The SRM was able to predict the combustion in terms of pressure trace and rate of heat release. The CO and NOx emissions were matched, however, the HC emissions were underestimated. Finally, the trajectories from the SRM simulations were superimposed on the T-Φ maps to investigate the in engine conditions. The T-Φ map analysis shows that emission of soot are non-existent, formaldehyde can be avoided and that emissions of methane are kept at, compared to diesel combustion, low levels, however CO and NOx levels are similar to diesel combustion. These results were confirmed for engine conditions by the SRM simulations and the engine experiments.

Soot Source Term Tabulation Strategy for Diesel Engine Simulations with SRM

In this work a soot source term tabulation strategy for soot predictions under Diesel engine conditions within the zero-dimensional Direct Injection Stochastic Reactor Model (DI-SRM) framework is presented. The DI-SRM accounts for detailed chemistry, in-homogeneities in the combustion chamber and turbulence-chemistry interactions. The existing implementation [1] was extended with a framework facilitating the use of tabulated soot source terms. The implementation allows now for using soot source terms provided by an online chemistry calculation, and for the use of a pre-calculated flamelet soot source term library. Diesel engine calculations were performed using the same detailed kinetic soot model in both configurations. The chemical mechanism for n-heptane used in this work is taken from Zeuch et al. [2] and consists of 121 species and 973 reactions including PAH and thermal NO chemistry. The engine case presented in [1] is used also for this work. The case is a single-injection part-load passenger car Diesel engine with 27 % EGR fueled with regular Diesel fuel. The two different approaches are analyzed and a detailed comparison is presented for the different soot processes globally and in the mixture fraction space. The contribution of the work presented in this paper is that a method which allows for a direct comparison of soot source terms - calculated online or retrieved from a flamelet table - without any change in the simulation setup has been developed within the SRM framework. It is a unique tool for model development. Our analysis supports our previous conclusion [1] that flamelet soot source terms libraries can be used for multi-dimensional modeling of soot formation in Diesel engines.

Three-dimensional computational fluid dynamics engine knock prediction and evaluation based on detailed chemistry and detonation theory:

Engine knock is an important phenomenon that needs consideration in the development of gasoline-fueled engines. In our days, this development is supported using numerical simulation tools to further understand and predict in-cylinder processes. In this work, a model tool chain which uses a detailed chemical reaction scheme is proposed to predict the auto-ignition behavior of fuels with different octane ratings and to evaluate the transition from harmless auto-ignitive deflagration to knocking combustion. In our method, the auto-ignition characteristics and the emissions are calculated using a gasoline surrogate reaction scheme containing pathways for oxidation of ethanol, toluene, n-heptane, iso-octane and their mixtures. The combustion is predicted using a combination of the G-equation based flame propagation model utilizing tabulated laminar flame speeds and well-stirred reactors in the burned and unburned zone in three-dimensional Reynolds-averaged Navier–Stokes. Based on the detonation theory by Bradley et al., the character and the severity of the auto-ignition event are evaluated. Using the suggested tool chain, the impact of fuel properties can be efficiently studied, the transition from harmless deflagration to knocking combustion can be illustrated and the severity of the auto-ignition event can be quantified.

Advanced Predictive Diesel Combustion Simulation Using Turbulence Model and Stochastic Reactor Model

Today numerical models are a major part of the diesel engine development. They are applied during several stages of the development process to perform extensive parameter studies and to investigate flow and combustion phenomena in detail. The models are divided by complexity and computational costs since one has to decide what the best choice for the task is. 0D models are suitable for problems with large parameter spaces and multiple operating points, e.g. engine map simulation and parameter sweeps. Therefore, it is necessary to incorporate physical models to improve the predictive capability of these models. This work focuses on turbulence and mixing modeling within a 0D direct injection stochastic reactor model. The model is based on a probability density function approach and incorporates submodels for direct fuel injection, vaporization, heat transfer, turbulent mixing and detailed chemistry. The advantage of the probability density function approach compared to mean value models is its capability to account for temperature and mixture inhomogeneities. Therefore, notional particles are introduced each with its own temperature and composition. The particle condition is changed by mixing, injection, vaporization, chemical reaction and heat transfer. Mixing is modeled using the one-dimensional Euclidean minimum spanning tree mixing model, which requires the scalar mixing frequency as input. Therefore, a turbulence model is proposed to calculate the mixing time depending on turbulent kinetic energy and its dissipation. The turbulence model accounts for density, swirl, squish and injection effects on turbulent kinetic energy within the combustion chamber. Finally, the 0D stochastic reactor model is tested for 40 different operating points distributed over the whole engine map. The results show a close match of experimental heat release rate and NOx emissions. The trends of measured CO and HC concentrations are captured qualitatively. Additionally, the 0D simulation results are compared to more detailed 3D CFD combustion simulation results for three operating points differing in engine speed and load. The comparison shows that the 0D stochastic reactor model is able to capture turbulence effects on local temperature and mixture distribution, which in turn affect NOx, CO and HC emission formation. Overall, the 0D stochastic reactor model has proven its predictive capability for the investigated diesel engine and can be assigned to tasks concerning engine map simulation and parameter sweeps.