Engine Combustion Network Spray Research Articles

Modeling Spray C and Spray D with FGM within the framework of RANS and LES

In this study, two different diesel-like igniting sprays are investigated: Engine Combustion Network (ECN) Spray C and D. In particular, this study focuses on the respective performances of the RANS and LES models to predict a turbulent, igniting spray using the OpenFOAM platform. The breakup model, discretization schemes, and case setups, including the combustion model, are kept constant in order to mitigate any potential effect on the simulation apart from intrinsic differences due to turbulence modeling. A classic κ-ε model is applied for the RANS approach, while a dynamic structure model is used to solve the momentum equation in the LES approach. The κ-ε model constants are tuned to obtain a suitable prediction of inert experiments. Both approaches exhibit a reasonable agreement with the inert experiments regarding the global spray characteristics, the liquid length, and the vapor penetration. However, the transient local properties, including the spatial distribution of mixture fraction variance and the species distributions, are not identical. For reacting conditions, the Flamelet Generate Manifold (FGM) model is adopted in both the LES and RANS simulations, using several enthalpy levels as the fourth dimension in the tabulation to account for local heat loss. The results show good agreement between the two turbulence models, in terms of liquid length, vapor penetration, and lift-off length, while a short ignition delay is registered for both sprays and turbulence frameworks. Turbulence–chemistry interaction (TCI) is considered by applying a presumed probability density function (β-PDF) to the mixture fraction, and is found to play a key role in the reproduction of species distribution in the domain.

Unsteady Flamelet modeling study on OMEx-type fuels under Engine Combustion Network Spray A conditions

Poly-Oxymethylene Dimethyl Ethers OMEx are synthetic and potentially-renewable fuels that lead to a notable reduction of the lifecycle CO2 emissions while promoting lower soot emissions than conventional Diesel fuel. In the present contribution, a computational study with a single component OME1 and a multicomponent OMEx fuel has been carried out under reference Spray A conditions from the Engine Combustion Network (ECN), which mimic in-cylinder conditions representative of Diesel engines. For both fuels, three ambient temperature conditions have been swept at constant ambient density. Calculations have been carried out using an Unsteady Flamelet Progress Variable (UFPV) combustion model and detailed chemical mechanisms. For both OMEx-type fuels, low temperature ignition in flamelet configurations start in lean mixtures, which shifts towards the fuel-rich zone and eventually leads to high temperature ignition, similar to typical hydrocarbons. In agreement with corresponding fuel cetane numbers, ignition of OMEx occurs at timings similar to those of n-dodecane, which is the reference fuel for ECN studies, while a delayed ignition is obtained for OME1. However, the actual difference in ignition timing between OMEx and n-dodecane depends on diffusion in the mixture fraction space. Moreover, ignition in spray calculations seems to occur fully on the lean side, especially for OME1, as well as for the low temperature cases. This difference in ignitable mixture range between the canonical flamelet configuration and the spray calculations results from the finite residence time for relevant mixtures in the latter case, compared to an infinite residence time in flamelets. Comparison with experiments show that the modeling approach predicts most combustion metrics for both fuels and temperature values. The combination of ambient temperature and fuel-related reactivity has enabled a transition from a short ignition lifted diffusion flame structure (OMEx at 1000–900 K) towards long ignition cases, where lift-off length may eventually be longer than the maximum length of the stoichiometric surface. This results in a reaction front stabilization at very lean conditions, i.e. a type of lean mixing-controlled flame.

On the effect of mixing-driven vaporization in a homogeneous relaxation modeling framework

The homogeneous relaxation model (HRM) is one of the most widely used models to describe the liquid–gas phase transition in multiphase flows due to the occurrence of cavitation. However, in its original formulation, the HRM does not account for the presence of ambient gas species, which generally limits its applicability to the injector's internal flow where ambient gases are negligible. In this work, a mixing-driven vaporization (MDV) model was developed to extend the capability of the HRM in handling the mixing effect in the regions external to the nozzle, where vapor–liquid equilibrium for multi-species mixtures of fuel and ambient gas is considered. To assess the model performance, simulations of the Engine Combustion Network's Spray G injector were performed with the HRM and the MDV model under both flash-boiling and evaporating conditions. It was found that the MDV model led to a better match against x-ray measurements of fuel density in the near-nozzle region. In contrast to the HRM, the MDV model was able to reproduce the vaporization process in the mixing zone at the edge of the fuel jet, which aligns with the expected physics. This resulted in substantial differences in the prediction of other flow characteristics such as mixture temperature and pressure. Furthermore, this work demonstrates that evaporation timescales have a considerable effect on the MDV model's predictions, as shown by a parametric study in which a time factor was introduced to mimic the effect of different timescales due to different phase change mechanisms.

Numerical investigation of n-dodecane ECN spray and combustion characteristics using the one-way coupled Eulerian-Lagrangian approach

This work investigated the spray and combustion characteristics of the Engine Combustion Network (ECN) n-dodecane injections using a one-way coupled Eulerian-Lagrangian approach. The actual X-ray measured injector geometries from the Argonne National Laboratory were adopted for Eulerian simulations. The multi-phase flow was modeled using the Volume-of-Fluid (VoF) method with the high-resolution interface capturing scheme to track the fluid-gas interface. The generated parcel data from the Eulerian simulations were mapped and utilized in the Lagrangian simulations to ensure fidelity. The simulation results agree well with the experimental data in terms of the projected density, mass flow rates, spray penetrations, mixture distributions, and ignition delays. The diverging nozzle channel in the Spray C injector resulted in cavitation and air entrainment, which reduced the mass flow rate. Because of the low oxygen concentration, the low-temperature combustion (LTC) reactions made a significant contribution to the heat release process. In comparison, similar jet-flame structures were observed for the Spray A, C, and D cases, consisting of the upstream LTC region, midstream intermediate-temperature combustion region, downstream fuel-rich high-temperature combustion (HTC) region, and downstream premixed HTC region. The higher ambient temperature led to a more advanced combustion phasing but shorter lift-off length. As a result, the mixing time was reduced to result in a higher concentration of acetylene. In addition, upon increasing the injection pressure, no significant difference was observed in the jet flame structure. On the other hand, the higher injection velocity resulted in a higher flame tip and broader HTC region.

Large eddy simulation of transient combustion and soot recession in the ECN Spray A and D flames

This paper presents the numerical results of combustion and soot recession in the Engine Combustion Network (ECN) Spray A and D flames using large eddy simulations (LES). The nominal injector nozzle diameters for the ECN Spray A and D are 90μm and 186μm. A two-equation soot model is implemented to model the soot formation and oxidation processes. The numerical model is validated by comparing the simulated and measured data in terms of ignition delay time (IDT), lift-off-length (LOL), and temporal evolution of soot mass. The combustion and soot recession processes are analyzed after the end-of-injection (AEOI). The combustion recession processes are first driven by auto-ignition wave propagation followed also by the convective flow in both the Spray A and D flames. A separated high-temperature flame structure is observed in the Spray A flame due to having small favorable mixture regions for the auto-ignition to occur upstream of the quasi-steady lift-off position AEOI. In contrast, a spatially-continuous high-temperature flame structure is formed in the Spray D flame due to having more ignitable mixture regions upstream of the quasi-steady lift-off position and a higher heat release. Soot recession is observed in the Spray D flame but not in the Spray A flame. This is attributed to the mixture upstream of the quasi-steady state soot region becoming favorable to promote soot formation in the Spray D flame, but it becomes fuel-lean AEOI in the Spray A flame.

ECN Spray G: Coupled Eulerian internal nozzle flow and Lagrangian spray simulation in flash boiling conditions

Flash-boiling of fuel sprays occurs when a super-heated fuel is discharged into an environment whose pressure is lower than the saturation pressure of the fuel and can dramatically alter spray formation due to complex two-phase flow effects and rapid droplet vaporization. In gasoline direct injection (GDI) engines, typically, it occurs during the injection process when high fuel temperatures make its saturation pressures higher than the in-cylinder one. Flash boiling significantly affects the spray structure and fuel-air mixture formation, with, potentially, if spray collapse is avoided, positive consequences for the engine performance and pollutant emissions. Hence, this paper developed a modelling approach based on the coupling of Eulerian multi-phase and Eulerian-Lagrangian simulations to reproduce flash boiling sprays physics. It allows a comprehensive description of the flash-boiling phenomena that begins within the injector’s ducts and continues outside, where a particular mechanism for primary breakup occurs. Experimental data of the Engine Combustion Network (ECN) Spray G injector, covering various operating conditions, were exploited to assess the reliability of the numerical technique adopted. The validation was performed taking into account various parameters such as axial liquid and vapour penetrations, droplet size and images regarding the near-nozzle zone. The numerical model achieves a pretty good level of agreement with the experimental data and, in particular, it is sensitive to the spray behaviour in the different operating conditions.

Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Large-Eddy Simulations of ECN Spray C

<div class="section abstract"><div class="htmlview paragraph">Large-eddy simulation (LES) is an important tool to understand and analyze sprays, such as those found in engines. Subfilter models are crucial for the accuracy of spray-LES, thereby signifying the importance of their development for predictive spray-LES. Recently, new subfilter models based on physics-informed generative adversarial networks (GANs) were developed, known as physics-informed enhanced super-resolution GANs (PIESRGANs). These models were successfully applied to the Spray A case defined by the Engine Combustion Network (ECN). This work presents technical details of this novel method, which are relevant for the modeling of spray combustion, and applies PIESRGANs to the ECN Spray C case. The results are validated against experimental data, and computational challenges and advantages are particularly emphasized compared to classical simulation approaches.</div></div>

Fast reactive flow simulations using analytical Jacobian and dynamic load balancing in OpenFOAM

Detailed chemistry-based computational fluid dynamics (CFD) simulations are computationally expensive due to the solution of the underlying chemical kinetics system of ordinary differential equations (ODEs). Here, we introduce a novel open-source library aiming at speeding up such reactive flow simulations using OpenFOAM, an open-source software for CFD. First, our dynamic load balancing model by Tekgül et al. [“DLBFoam: An open-source dynamic load balancing model for fast reacting flow simulations in OpenFOAM,” Comput. Phys. Commun. 267, 108073 (2021)] is utilized to mitigate the computational imbalance due to chemistry solution in multiprocessor reactive flow simulations. Then, the individual (cell-based) chemistry solutions are optimized by implementing an analytical Jacobian formulation using the open-source library pyJac, and by increasing the efficiency of the ODE solvers by utilizing the standard linear algebra package. We demonstrate the speed-up capabilities of this new library on various combustion problems. These test problems include a two-dimensional (2D) turbulent reacting shear layer and three-dimensional (3D) stratified combustion to highlight the favorable scaling aspects of the library on ignition and flame front initiation setups for dual-fuel combustion. Furthermore, two fundamental 3D demonstrations are provided on non-premixed and partially premixed flames, viz., the Engine Combustion Network Spray A and the Sandia flame D experimental configurations, which were previously considered unfeasible using OpenFOAM. The novel model offers up to two orders of magnitude speed-up for most of the investigated cases. The openly shared code along with the test case setups represent a radically new enabler for reactive flow simulations in the OpenFOAM framework.

The Corrected Distortion model for Lagrangian spray simulation of transcritical fuel injection

In this work, we present a detailed implementation and validation of the droplet modeling framework proposed by Dahms and Oefelein (2016) into the engine commercial CFD software CONVERGE using the User Defined Function (UDF) interface. The model accounts for the nonlinear deformation and oscillation experienced by liquid spray droplet injected into high pressure and temperature. Lagrangian spray simulations of Engine Combustion Network (ECN) Spray A are performed. Model validation against standard experimental measurements of liquid velocity, vapor mixture fraction is conducted. To perform more rigorous model validation, new experimental measurements based on Diffused Back Illumination (DBI) are introduced. The new measurements are processed for Projected Liquid Volume (PLV), which offers as close as possible one-to-one model validation for liquid penetration while offering new insights into the spray physics. Comparison with a One-D model based on adiabatic mixing theory by Siebers (1999) and Desantes et al. (2007) are also conducted. Through these model validation exercises, it is shown that the new framework improves liquid-phase penetration predictions, following a tendency for enhanced evaporation, compared to the standard approach for both Reynolds Average Navier Stokes (RANS) and Large Eddy Simulation (LES). At the liquid length, maximum mixture fraction values predicted by the new approach are in good agreement those of an adiabatic mixing model. Qualitative analysis of the spray behaviors during the early stage of the injection process reveals that the proposed framework predicts significant increase in droplet evaporation rate with lower drop drag compared to the current standard approach.

Flow visualisation in real-size optical injectors of conventional, additised, and renewable gasoline blends

Research on renewable and alternative fuels is crucial for improving the energy and environmental efficiency of modern gasoline internal combustion engines. To highlight the influence of fuel rheological and thermodynamic properties on phase change and atomisation processes, three types of gasoline blends were tested. More specifically, the campaign comprised a reference gasoline, an ethanol/gasoline blend (10% v/v) representative of renewable fuels, and an additised gasoline sample treated with viscoelasticity-inducing agents. High-speed imaging of the transient two-phase flow field arising in the internal geometry and the near-nozzle spray region of gasoline injectors was performed employing Diffuse Backlight Illumination. The metallic body of a commercial injector was modified to fit transparent tips realising two nozzle layouts, namely a two-hole real size model resembling the Engine Combustion Network spray G injector and an enraged replica with an offset hole. Experiments were conducted at realistic operating conditions comprising an injection pressure of 100 bar and ambient pressures in the range of 0.1–6.0 bar to cover the entire range of chamber pressures prevailing in Gasoline Direct Injection engines. The action of viscoelastic additives was verified to have a suppressive effect on in-nozzle cavitation (6% reduction in cavitation extent) , while also enhancing spray atomisation at flash-boing conditions, in a manner resembling the more volatile gasoline/ethanol blends. Finally, persisting liquid ligaments were found to form after the end of injection for the additised sample, owing to the surfactant nature of the additives.

Numerical and experimental investigations of the early injection process of Spray G in a constant volume chamber and an optically accessible DISI engine

In this work, the Engine Combustion Network Spray G injector was mounted in the Darmstadt optical-accessible engine to study phenomena typical of multi-hole, early direct-injection events in spark-ignition engines characterized by tumble flow charge motion. Dedicated experimental measurements of both in-cylinder spray morphology and flow velocities before and after the injection process were carried out to assess the adopted numerical setup under real engine conditions. A dynamic secondary breakup model from the literature was coupled with an atomization multi-motion regime model. The model was validated against state-of-the-art ECN Spray G experiments for a constant-volume chamber under low evaporating condition. Then, the simulation of the spray injection in the engine was carried out and the achieved results were compared against the experimental data. Overall, good agreement between experiments and simulations was observed for the spray morphology and velocity fields in both cases. With reference to engine calculations the intake flow was seen to induce spray asymmetry. A partial vortex generated during the intake phase on the tumble plane interacts with the spray, developing into a full vortex which induces an upward flow that stabilizes the spray. The upward flows below the intake valve increase the dilution of the plume outside the tumble plane, which therefore exhibits reduced penetration. Moreover, the intake valves protect from the energetic intake flow the recirculation vortex generated at the tip of the plumes that lie outside the tumble plane. The intake flow helps fuse the vapor fuel clouds of the individual plumes near the injector tip, obtaining a vapor fuel with a shape like that generated by a horseshoe multi-hole injector. Finally, a phenomenological model of the interaction between the multi-hole injector jets and the engine intake flow was introduced to describe the spray evolution in a typical DISI engine.

An experimental study with renewable fuels using ECN Spray A and D nozzles

The decarbonization process of the automotive industry and the road transport sector has raised the interest on the development of cleaner fuels. A proper characterization of their properties and behavior under different operating conditions is mandatory to achieve an effective implementation in commercial engines. With this objective, the current work presents a comparison of two injectors from the Engine Combustion Network (ECN), namely Spray A and Spray D injectors, in terms of spray characteristics and combustion behavior for different fuels: diesel, dodecane, Hydrotreated Vegetable Oil (HVO), and two types of oxymethylene ethers (OME1 and OME x). The aim is to analyze how differences in nozzle geometry affect the behavior of different types of fuels. The experiments were carried out in a High Temperature and High Pressure test rig and operating conditions were chosen following ECN guidelines. Visualization techniques such as high speed schlieren imaging, OH* chemiluminescence and diffused back illumination were implemented to analyze the differences in liquid length, vapor penetration, auto ignition, flame lift-off length, and soot formation for both nozzles. In general, results showed the same trend for all the fuels tested: longer liquid length and faster vapor penetration for Spray D, as well as higher ignition delay and longer lift-off length. However, it was found that these parameters were less sensitive to the nozzle diameter for the oxygenated fuels tested. Furthermore, a different trend was observed for OME1, in terms of ignition behavior, in comparison to the other fuels. In terms of soot production, the Spray D nozzle increases its formation with the non-oxygenated fuels. In contrast, no soot was observed with the oxygenated ones under any operating conditions.

Numerical simulation of n-dodecane spray combustion based on OpenFOAM

For the purpose of providing the scientific insights to combustion characteristics of spray jet, numerical calculations of reacting and non-reacting spray cases are performed for ECN (engine combustion network) Spray A (n-dodecane spray combustion) which coupled finite chemistry combustion model PaSR and detailed chemical reaction kinetics based on OpenFOAM. The applicability and accuracy of the spray model is verified in the non-reacting spray case, and it is found that the predicted spray characteristics such as the penetration length of liquid and vapor and the mixture fraction are in good agreement with the test results. The two processes of low-temperature reaction and high-temperature ignition experienced by n-dodecane spray ignition are analyzed in reacting spray case, and it is found that the low-temperature reaction continues to exothermic before high-temperature ignition, and continues to proceed stably after high-temperature ignition, which promotes high-temperature ignition and flame stability. Finally, the effects of different fuel injection pressures on ignition delay time and flame lift-off length are studied.

Comparison of soot models for reacting sprays in diesel engine-like conditions

Stringent emission legislations and growing health concerns have contributed to the evolution of soot modeling in diesel engines from simple empirical relations to methods involving detailed kinetics and complex aerosol dynamics. In this paper, four different soot models have been evaluated for the high temperature, high pressure combusting dodecane spray cases of engine combustion network (ECN) spray A which mimics engine-relevant conditions. The soot models considered include an empirical, a multistep, a method of moments based, and a discrete sectional method soot model. Two experimental cases with ambient oxygen volume of 21% and 15% have been modeled. A good agreement between simulations and experiments for vapor penetration and heat release rate has been obtained. Quasi-steady soot volume fraction contours for the four soot models have been compared with experiments. Contours of the species and source terms involved in soot modeling have also been compared for a better understanding of soot processes. The empirical soot model results in higher magnitude and spread of soot due to a lack of modeling framework for oxidation through OH species. Among the four models studied, the multistep soot model has been observed to provide the most promising agreement with the experimental data in terms of distribution of soot and location of peak soot volume fraction. Due to a two-way coupling of soot models, the detailed models predict an upstream location for soot as compared to the multi-step soot model which is one way coupled. A significant difference (of an order of magnitude) in the concentration of PAH (polycyclic aromatic hydrocarbons) precursor between multistep and detailed soot models has been observed because of precursor consumption due to the coupling of detailed soot models with chemical kinetics. It is recommended that kinetic schemes, especially those concerning PAH, be validated with experimental data with a kinetics-coupled soot model.

Machine-learning enabled prediction of 3D spray under engine combustion network spray G conditions

Spray and air–fuel mixing in gasoline direct-injection (GDI) engines play a crucial role in combustion and emission characteristics. While a variety of phenomenological spray models and computational fluid dynamics (CFD) simulations have been applied to identify air–fuel mixture distribution, most research efforts so far were concentrated on single axial-nozzle injectors and limited range of ambient conditions. Especially, the prediction of flash-boiling sprays in multi-hole injectors remains a great challenge due to the lack of understanding of the complicated two-phase flow dynamics. For the specific conditions, the question can arise concerning the capability of machine-learning algorithms to predict complex flash-boiling sprays. We developed a machine-learning algorithm, as a simple variant of linear regression, that is capable of predicting the spray 3D topology for various fuels and ambient conditions. A series of spray experiments were carried out in a constant-flow spray vessel coupled with high-speed diffused back-illumination extinction imaging to produce a data set for algorithm training. Nine different test fuels, including single component iso-octane (ic8) and multi-component EEE gasoline, that cover a wide range of fuel properties were injected using Engine Combustion Network (ECN) Spray G injector under ECN G2 (50 kPa absolute), G3 (100 kPa absolute), and G3HT (G3 with 393 K ambient temperature) conditions. Among the test fuels, ic8ib2 (ic8 80%, iso-butanol 20% v/v) and EEE gasoline were specified as target fuels for spray prediction by the machine-learning algorithm, thus they were not included in the training data. The macroscopic spray analysis based on projected liquid volume (PLV) and computed tomographic (CT) reconstruction showed that the spray prediction by the machine-learning algorithm showed excellent agreement with true values from the experimental data. The maximum differences in liquid penetration for ic8ib2 and EEE fuel were 3.6 mm (7.3% error) and 1.3 mm (2.32% error), respectively. The 3D spray predicted had a consistent trend to experimental data showing slight plume movement for ic8ib2 but complete spray collapsing for EEE gasoline fuel. The plume direction angle enabled by the CT data showed differences up to 2° compared to true values during the injection period. The quantitative validation results showed that the machine-learning algorithm is capable of predicting spray performance with nine input features (fuel properties and ambient conditions), and is actually superior to CFD performance for these same number of spray parameters.

Application of a MEMS heat flux sensor to heat transfer research on an impinging diesel jet

To clarify the mechanisms of heat transfer on an engine wall is an important challenge because the heat loss on the wall is one of the dominant factors that limit the thermal efficiency. A thin-film resistance type heat flux sensor fabricated with Micro-Electro-Mechanical Systems (MEMS) technologies was applied to research on the heat transfer of an impinging diesel jet. The MEMS sensor had a high sensitivity and multiple measurement points with a scale comparable to the turbulence of in-cylinder flow for the investigation of local instantaneous heat transfer characteristics in engines. Measurements of wall temperature and heat flux were conducted in a constant volume chamber under the reference conditions of Engine Combustion Network (ENC) Spray A with variations in injection pressure. As a result, the maximum heat flux and heat transfer coefficient reached about 5 MW/m2 and 3 MW/(m2 K), respectively. The results were compared to those obtained with a commercially available thermocouple, and both sensors produced similar trends. In addition, fluid motion near the wall was estimated from the heat flux fluctuations using a cross-correlation analysis. The relationship between heat transfer and flow was investigated in a dimensionless number fashion, and it was compared to a semi-theoretical prediction that was based on a steady state laminar flow heat transfer model.

X-RAY RADIOGRAPHY AND PHASE-CONTRAST IMAGING OF THE ENGINE COMBUSTION NETWORK SPRAY B SPRAYS AND INJECTION

X-ray measurements of diesel sprays from two of the Engine Combustion Network (ECN) Spray B injectors are described. Measurements in these three-hole nozzles complement both visible light measurements of these sprays and previous x-ray measurements of the axial single-hole ECN Spray A injectors. Both axial and lateral motions of the injector needle valve were measured with x-ray phase contrast imaging. The liquid mass distribution in room temperature sprays at elevated ambient pressure was determined with x-ray radiography. Measurements of both needle valve motion and spray distribution were performed at both the standard Spray A/B conditions and with selected variations of injection pressure, ambient density, and injection timing. The needle valve motion for the Spray B injectors is quite similar to that of the Spray A injectors, though little lateral motion is seen in either Spray B injector. Compared to the sprays from the Spray A injectors, the sprays from Spray B penetrate more slowly in the near-nozzle region, demonstrate a broader, more uniform distribution in the transverse direction, and are significantly more variable with respect to time. These differences demonstrate the importance of studies with multi-hole nozzles to provide insight into applied diesel combustion.

Oxymethylene ether – n-dodecane blend spray combustion: Experimental study and large-eddy simulations

E-fuels, made from renewable electricity and a CO2 source, have been proposed as a renewable alternative for the mobility sector. In this work, the ignition process and soot formation of the e-fuel oxymethylene ether 1 (OME1) and its blends with n-dodecane are investigated. Experiments of the spray ignition of both neat fuels and a promising fuel blend are conducted under the Engine Combustion Network Spray A conditions in a high-pressure spray chamber and it is found that the fuel blend ignites very similar to n-dodecane. To investigate this behavior in more detail, first a kinetic reaction mechanism for blends of OME1 and n-dodecane is developed and validated using new shock tube measurements. Large-eddy simulations are then performed for the experimental conditions, and spray characteristics as well as ignition delay and flame structure agree well with the experimental results. A super-linear reduction in common soot precursors in the gas phase is found for the fuel blend, which is mainly attributed to a shift of soot precursor production towards higher mixture fractions due to the oxygen content in the fuel. The ignition behavior of OME1 and the fuel blend is investigated in mixture fraction space using one-dimensional unsteady flamelets. It is found that the slow ignition behavior of OME1 is rooted in its high stoichiometric mixture fraction, shifting the most reactive mixture for second stage ignition to very fuel-rich regions, which have a low temperature in a spray case with a cold fuel side. The ignition process of the fuel blend is dominated by its n-dodecane fraction up to 60 mol% OME1 in the blend, and the low increase of ignition delay in this range can be explained by dilution of n-dodecane with OME1.

Computational study of ECN Spray A and Spray D combustion at different ambient temperature conditions

The combustion process of the Engine Combustion Network (ECN) Spray A and Spray D is studied over a wide range of ambient temperatures from 750 K to 900 K. With nominal diameters of 89.4 μm for the Spray A and 190.3 μm for the Spray D, these n-dodecane sprays are representative for light- and heavy-duty compression ignition engine applications, respectively. Computational Fluid Dynamics calculations are carried out using a Lagrangian parcel Eulerian fluid approach in a Reynolds averaged Navier–Stokes framework. For the Spray D reference condition, two sub-grid flame structure assumptions and the effect of turbulence chemistry interaction (TCI) on autoignition and flame structure at quasi-steady state are assessed in the context of a well-mixed and an Unsteady Flamelet Progress Variable (UFPV) combustion model. After that, UFPV approach is used to evaluate combustion behavior for the different ambient temperature conditions. Reference condition results show that both well-mixed and flamelet assumptions lead to a similar autoignition sequence. In terms of ignition delay time, TCI plays an important role, within the UFPV model, in reproducing the experimental trend observed for the increase in nozzle diameter. In terms of lift-off length, the well-mixed model is observed to predict a longer value compared to the flamelet-based sub-grid assumption. Lastly, the analysis of the autoignition sequence and flame structure at quasi-steady state is also extended over the whole range of ambient temperature conditions.

Large eddy simulation of spray combustion using flamelet generated manifolds combined with artificial neural networks

In the present work, artificial neural networks (ANN) technique combined with flamelet generated manifolds (FGM) is proposed to mitigate the memory issue of FGM models. A set of ANN models is firstly trained using a 68-species mass fractions in mixture fraction-progress variable space. The ANN prediction accuracy is examined in large eddy simulation (LES) and Reynolds averaged Navier-Stokes (RANS) simulations of spray combustion. It is shown that the present ANN models can properly replicate the FGM table for most of the species mass fractions. The network models with relative error less than 5% are considered in RANS and LES to simulate the Engine Combustion Network (ECN) Spray H flames. Validation of the method is firstly conducted in the framework of RANS. Both non-reacting and reacting cases show the present method predicts very well the trend of spray and combustion process under different ambient temperatures. The results show that FGM-ANN can replicate the ignition delay time (IDT) and lift-off length (LOL) precisely as the conventional FGM method, and the results agree very well with the experiments. With the help of ANN, it is possible to achieve high efficiency and accuracy, with a significantly reduced memory requirement of the FGM models. LES with FGM-ANN is then applied to explore the detailed spray combustion process. Chemical explosive mode analysis (CEMA) approach is used to identify the local combustion modes. It is found that before the spray flame is developed to the steady-state, the high CH2O zone is always associated with ignition mode. However, high CH2O zone together with high OH zone is dominated by the burned mode after the steady-state. The lift-off position is dominated mainly by the diffusion mode.