Ducted Fuel Injection: A New Approach for Lowering Soot Emissions from Direct-Injection Engines.
Abstract not provided.
Mueller, Charles J.↗
SEARCH · Search NASA
Results for “DIRECT INJECTION ENGINES”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Particulate Matter Sampling and Volatile Organic Compound Removal for Characterization of Spark Ignited Direct Injection Engine Emissions
More stringent emissions regulations are continually being proposed to mitigate adverse human health and environmental impacts of internal combustion. With that in mind, it has been proposed that vehicular particulate matter (PM) emissions should be regulated based on particle number in addition to particle mass. One aspect of this project is to study different sample handling methods for number based aerosol measurements, specifically, two different methods for removing volatile organic compounds (VOCs) from an aerosol sample. One method is a Dekati Thermodenuder (TD) and the other is an evaporative chamber/diluter (EvCh). These sample handling methods have been implemented for this project in an engine test cell built around a direct injection spark ignited (DISI) engine. The engine was designed for stoichiometric, homogeneous combustion. Direct injection is of particular interest for improved fuel efficiency but this comes with the production of a significant amount of (PM) and may therefore be subject to the proposed number based regulation. Another aspect of this project is to characterize PM from this engine in terms of particle number and composition. The first interesting observation is that PM number distributions, acquired using a TSI SMPS, have a large accumulation mode (30-294 nm) but a very small nuclei mode (8-30 nm). This is understood to represent a lack of condensation particles meaning that neither the exhaust conditions nor the sample handling conditions are conducive to condensation. This lack of nuclei mode does not, however, represent a lack of VOCs in the sample. It has been observed, using mass spectral analysis (limited to PM>50 nm), that PM from the DISI engine has approximately 40% organic content through varying operating conditions. This begs the question of how effective different sample handling methods are at removing these VOCs. For one specific operating condition, called Cold Start, the un-treated PM was 40% organic. The TD reduced this by 7% while the EvCh reduced it by 13%. For other operating conditions, PM treated for volatile removal actually exhibited an increase in organic fraction on the order of 5%. This addition appears to be sensitive to the gaseous hydrocarbon concentrations in the exhaust although a precise correlation has not yet been derived. It has been concluded that VOCs are tightly bound to the PM carbon core and thus are not effectively removed by either treatment method.
Environmental Molecular Sciences Laboratory↗
Investigation of the Impact of Fuel Properties on Particulate Number Emission of a Modern Gasoline Direct Injection Engine
Gasoline Direct Injection (GDI) has become the preferred technology for spark-ignition engines resulting in greater specific power output and lower fuel consumption, and consequently reduction in CO2 emission. However, GDI engines face a substantial challenge in meeting new and future emission limits, especially the stringent particle number (PN) emissions recently introduced in Europe and China. Studies have shown that the fuel used by a vehicle has a significant impact on engine out emissions. In this study, nine fuels with varying chemical composition and physical properties were tested on a modern turbo-charged side-mounted GDI engine with design changes to reduce particulate emissions. The fuels tested included four fuels meeting US certification requirements; two fuels meeting European certification requirements; and one fuel meeting China 6 certification requirements being proposed at the time of this work. Two risk safeguard fuels (RSG), representing the properties of worst case market fuels in Europe and China, were also included. The particle number concentration of the solid particulates was measured in the engine-out exhaust flow at steady state engine operations with load and speed sweeps, and semi-transient load steps. The test results showed a factor of 6 PN emission difference among all certification fuels tested. Combined with detailed fuel analyses, this study evaluated important factors (such as oxygenates, carbon chain length and thermo-physical properties) that cause PN emissions which were not included in PMI index. A linear regression was performed to develop a PN predictive model which showed improved fitting quality than using PMI.
33 ADVANCED PROPULSION SYSTEMS↗
Numerical modeling of hydrogen mixing in a direct-injection engine fueled with gaseous hydrogen
Hydrogen is considered as one of the most promising options to achieve effective decarbonization of the energy and transportation sectors. As such, it has recently been receiving increasing attention because of its promising potential as an energy carrier for advanced energy and propulsion systems. With a focus on internal combustion engines, direct injection (DI) of gaseous hydrogen during the compression stroke offers great potential for high engine efficiency and specific power while reducing the risk of backfiring and pre-ignition issues. Therefore, many experimental and numerical efforts have recently been dedicated to understanding the physical and chemical behaviors of hydrogen in engine during mixing and combustion. This study focuses on computational fluid dynamics (CFD) modeling of the hydrogen DI process in a hydrogen optical research engine. Under the conditions studied, gaseous hydrogen is injected into the combustion chamber via a centrally located single-hole injector at a pressure of 100 bar. Two configurations, namely low-and high-tumble, are investigated to understand the impact of different in-cylinder flow patterns on the fuel-air mixture preparation. Simulations are carried out using the commercial CFD software CONVERGE. Here, the in-cylinder turbulence is modeled with an unsteady Reynolds-averaged Navier-Stokes (URANS) formulation closed by the renormalization group (RNG) k-ε model. Several numerical methods and model constants, including but not limited to turbulent Schmidt number, are evaluated. The numerical results are systematically compared against experimental measurements of velocity and hydrogen concentration fields on the vertical center plane to assess the performance of the CFD model, unveil the physics of hydrogen mixing, and establish best practices for modeling hydrogen DI under relatively high injection pressure conditions.
33 ADVANCED PROPULSION SYSTEMS↗
Spark-ignited direct-injection engine combustion systems
A direct-injection stratified charge internal combustion engine includes a combustion cylinder to receive an air-fuel mixture, and an air intake port to inlet air into the combustion cylinder. The direct-injection engine also includes a fuel injector configured to deliver fuel within the cylinder in a spray pattern substantially aligned to a cylinder central axis to create the air-fuel mixture. A spark igniter is located within a path of the spray pattern to ignite combustion of the air-fuel mixture. The direct-injection engine further includes a movable piston defining a lower boundary of the combustion cylinder to contain the combustion of the air-fuel mixture. The piston is configured to include a bowl portion having local geometric features located on an intake port side of the combustion cylinder to redirect fluid flow towards a vortex in fluid communication with a combustion location near the cylinder central axis.
42 ENGINEERING↗
Time-Sequenced Flow Field Prediction in an Optima Spark-Ignition Direct-Injection Engine Using Bidirectional Recurrent Neural Network (bi-RNN) with Long Short-Term Memory
To further improve the energy conversion efficiency of internal combustion engine, the transient and complex air flow movement inside the cylinder needs to be better understood and controlled. Although the in-cylinder flow fields are highly stochastic with strong cycle-to-cycle fluctuations, machine learning can still provide an efficient way to learn and regress the complex flow movement process inside the cylinder. In this work, a bidirectional recurrent neural network (bi-RNN) model with long short-term memory was applied to predict the in-cylinder flow fields at different time steps using training data from mull-cycle particle image velocimetry (PIV) measurements. To evaluate the agreement between the true and predicted flow fields, structure and magnitude comparison indices are calculated both globally and locally. The comparison results show that the bi-RNN model can accurately predict the bulk flow and vortex motions from early intake stroke to compression stroke. This work demonstrates that the machine learning model has the potential to predict the underlying dynamics of the interaction between in-cylinder flows and provides a reliable way to improve temporal resolution in PIV flow data to better reveal transient in-cylinder flow features.
Bi-RNN model↗
Effects of Gasoline Direct Injection Engine Operating Parameters on Particle Number Emissions
A single-cylinder, wall-guided, spark ignition direct injection engine was used to study the impact of engine operating parameters on engine-out particle number (PN) emissions. Experiments were conducted with certification gasoline and a splash blend of 20% fuel grade ethanol in gasoline (E20), at four steady-state engine operating conditions. Independent engine control parameter sweeps were conducted including start of injection, injection pressure, spark timing, exhaust cam phasing, intake cam phasing, and air-fuel ratio. The results show that fuel injection timing is the dominant factor impacting PN emissions from this wall-guided gasoline direct injection engine. The major factor causing high PN emissions is fuel liquid impingement on the piston bowl. By avoiding fuel impingement, more than an order of magnitude reduction in PN emission was observed. Increasing fuel injection pressure reduces PN emissions because of smaller fuel droplet size and faster fuel-air mixing. PN emissions are insensitive to cam phasing and spark timing, especially at high engine load. Cold engine conditions produce higher PN emissions than hot engine conditions due to slower fuel vaporization and thus less fuel-air homogeneity during the combustion process. E20 produces lower PN emissions at low and medium loads if fuel liquid impingement on piston bowl is avoided. At high load or if there is fuel liquid impingement on piston bowl and/or cylinder wall, E20 tends to produce higher PN emissions. This is probably a function of the higher heat of vaporization of ethanol, which slows the vaporization of other fuel components from surfaces and may create local fuel-rich combustion or even pool-fires.
02 PETROLEUM↗
Particulate Characteristics for Varying Engine Operation in a Gasoline Spark Ignited, Direct Injection Engine
The objective of this research is a detailed investigation of particulate sizing and number count from a direct-injection spark-ignited (DISI) engine at different operating conditions. The engine is a 549 [cc] single-cylinder, four valve engine with a flat-top piston, fueled by Tier II EEE. A baseline engine operating condition, with a low number of particulates, was established and repeatability at this condition was ascertained. This baseline condition is specified as 2000 rpm, 320 kPa IMEP, 280 [°bTDC] end of injection (EOI), and 25 [°bTDC] ignition timing. The particle size distributions were recorded for particle sizes between 7 and 289 [nm]. The baseline particle size distribution was relatively flat, around 1E6 [dN/dlogDp], for particle diameters between 7 and 100 [nm], before dropping off to decreasing numbers at larger diameters. Distributions resulting from a matrix of different engine conditions were recorded. These varied parameters include load, air-to-fuel ratio (A/F), spark timing, injection timing, fuel rail pressure, and oil and coolant temperatures. Most conditions resulted with uni-modal type distributions usually with an increase in magnitude of particles in comparison to the baseline, with the exception of lean operation with retarded ignition timing. Further investigation revealed high sensitivity of the particle number and size distribution to changes in the engine control parameters. There was also a high sensitivity of the particle size distributions to small variations in A/F, ignition timing, and EOI. Investigations revealed the possibility of emissions oxidation in the exhaust and engine combustion instability at later EOI timings which therefore ruled out late EOI as the benchmark condition. Attempts to develop this benchmark revealed engine sensitivity to A/F and ignition timing, especially at later EOI operation
Environmental Molecular Sciences Laboratory↗
Correlation of nanoparticle size distribution features to spatiotemporal flame luminosity in gasoline direct injection engines
Particle size distribution measured by mobility instruments is a common diagnostic used to characterize ultrafine and nanoparticle emissions in engine exhaust; however, some features of particle size distribution data are poorly correlated to in-cylinder combustion phenomena. In this work, in-cylinder spatiotemporal flame luminosity is quantitatively correlated to features in the solid particle size distribution measured in the exhaust of a gasoline direct injection engine operating in lean and stoichiometric combustion modes. A multi-channel optical sensor was used to measure diffusion flame light intensity in different areas of the combustion chamber. Furthermore, total solid particle number and particle size distribution in the exhaust were measured using a scanning mobility particle sizer after a catalytic stripper that removed semi-volatile compounds. Results of the experiments showed that different flame phenomenon resulted in distinct particle size distribution characteristics. A large accumulation mode (particles with diameter of 50–100 nm) in the particle size distribution from stoichiometric engine operation with early injection resulted from anomalous diffusion flames like piston-top pool fires. In lean operation incorporating a secondary fuel injection, particle emissions were dominated by flame propagation through fuel-rich regions of the combustion chamber resulting in a comparatively broad particle size distribution. More generally, this work illustrates how particle size distribution data can be more accurately used to diagnose soot formation in gasoline direct injection engines.
33 ADVANCED PROPULSION SYSTEMS↗
Spatiotemporal flame propagations, combustion and solid particle emissions from lean and stoichiometric gasoline direct injection engine operation
Increased particle number and mass emissions in gasoline direct injection (GDI) engines should require to investigate in-cylinder flame and combustion characteristics associated with primary source of particle emissions. In this article, in-cylinder spatiotemporal flame luminosity is quantitatively characterized to features combustion process and solid particle emissions from a GDI engine operating in two lean and one stoichiometric modes. Low- and high-steady state operating points were used to compare combustion strategies on flame development and emission characteristics. A fiber-optic sensor composed of eight measurement channels detected the flame front and the direction of the flame propagation in the combustion chamber. Solid particle emissions in the exhaust were measured using an engine exhaust particle sizer and a micro soot sensor. Results of the experiments showed that two lean combustion modes by injection strategies resulted in distinct combustion and flame development. Lean combustion modes generated high diffusion flame by burning stratified rich-mixture. Although the lean cases resulted in strong diffusion flames, the lean-homogeneous produced similar particle size distributions with the stoichiometric mode with high ash particles. Piston pool fires on the piston surface in the lean-stratified mode induced a large accumulation mode with high particle mass concentrations.
42 ENGINEERING↗
Optimization of spray breakup model parameters for predicting fuel spray and film characteristics in gasoline direct injection engines
This study investigated the behavior of gasoline direct injection (GDI) sprays using computational fluid dynamics (CFD). The authors developed an approach to identify optimal spray breakup model parameters by evaluating an error function across numerous simulations, with the goal of minimizing discrepancies from experimental data. Using the optimal setup, the simulated spray matched well with projected liquid volume distributions, liquid penetration, and spray width measured in a constant-pressure continuous-flow chamber. To further validate the approach, the same setup was tested across various fuels, injectors, and operating conditions. Subsequently, the optimal setup, along with a recently developed spray-wall interaction model, were applied to a direct-injection spark-ignited engine under late-injection conditions to predict and evaluate fuel film formation and evolution at varying engine coolant temperatures. Here, with the centrally mounted injector directing the spray toward the piston, simulations indicated that the spray tends to impinge on the piston surface. The proposed simulation framework also accurately captured the aggregate film area on the piston surface, aligning with previously published experimental results. Moreover, simulations showed that increasing the coolant temperature from cold start conditions (333 K) to warm conditions (363 K) reduced the fuel mass deposited on the piston by roughly 50%. Furthermore, for the spray-guided engine configuration studied in this work, the CFD model predicted minimal film deposition on the spark plug electrodes regardless of the coolant temperatures due to a relatively weak in-cylinder flow during the compression phase.
Computational fluid dynamics (CFD)↗
Impact of ethanol blending into gasoline on aromatic compound evaporation and particle emissions from a gasoline direct injection engine
This study examined the interactions of ethanol with aromatic compounds on aromatic species evolution during gasoline evaporation and the consequent impacts on particle emissions from a single-cylinder, gasoline direct injection engine. From a chemical kinetic standpoint, the dilution of the aromatic species in gasoline by ethanol blending should reduce particle emissions because aromatics are the primary species that form particles during gasoline combustion. However, increased evaporative cooling from the ethanol and ethanol's effect on when aromatics in the fuel droplet (or surface film or pool) evaporate can drive an increase in particle emissions. The objective of this study was to quantify these competing effects. The results show that a combination of ethanol's increased evaporative cooling and impact on aromatic compound vapor-liquid equilibrium can extend droplet lifetime and cause aromatics to evaporate later in the droplet evaporation process than would be the case without ethanol. When fuels were burned in a direct-injection single-cylinder engine at high speed (2500 rpm) and relatively high load, ethanol blending caused an increase in particle emissions for fuels containing a low vapor pressure aromatic. At a lower speed (1500 rpm), no statistically significant increase in particle emissions was observed, likely because more time was available for evaporation and mixing to occur. In contrast, particle emissions from a fuel blended with a high vapor pressure aromatic were either insensitive to or reduced by ethanol blending, likewise to engine operating conditions. Current models for predicting particle emissions from gasoline engines, such as particulate matter index (PMI), generally lack variables for non-linear interactions between ethanol and gasoline hydrocarbons. To identify nonlinear interactions between predictor variables that might better explain the observed particle emissions, the least absolute shrinkage and selection operator (LASSO) regularized regression approach was employed. Among the predictor variables evaluated was the Yield Sooting Index (YSI) which is as an improved measure to quantify the aromatic's chemical tendency to generate particle emissions. Following this analysis, two variables were selected based on their frequent appearance. The first was ethanol mole percent multiplied by aromatic mole percent divided by aromatic vapor pressure [(EtOH * Aro%)/Aro VP@443 K]. The second was aromatic mole percent multiplied by aromatic YSI divided by aromatic molecular weight [(Aro% * Aro YSI)/Aro MW]. The results of linear regression including only these two combined explanatory variables achieved an r 2 = 0.959, substantially improved over the PMI model (r 2 = 0.688) and provides insight into how the PMI formalism might be modified to account for non-linear oxygenate-hydrocarbon coupling.
09 BIOMASS FUELS↗
Realistic fuel spray modeling for gasoline direct injection engine applications
Fuel spray modeling plays a critical role during modern gasoline direct injection (GDI) engine development due to fuel injection’s dominant impact on engine performance and emissions as well as the complex physical processes involved. In engineering three-dimensional (3D) computational fluid dynamics (CFD) simulations, the liquid-phase fuel atomization, evaporation, and mixing are usually modeled with the discrete droplet model (DDM) adopting a Lagrangian approach for multiphase CFD simulations. To this end, general practices heavily depend on the reduced order characterization of the injector nozzle flow. However, such simplified injector modeling may lead to insufficient representations of the complex spray dynamics. To tackle this problem, this study proposes a novel workflow to numerically evaluate GDI sub-cooled and flash-boiling sprays under engine-relevant conditions using a side-mounted GDI injector together with real gasoline fuel properties. The workflow introduces a one-way coupling (OWC) method leveraging high-fidelity nozzle flow simulations to provide realistic boundary conditions to the Lagrangian injector model. The proposed workflow was first verified in a constant volume chamber (CVC) environment and then implemented in a practical GDI engine setup to study spray morphology, fuel-air mixing, and wall-wetting propensity. In addition, detailed comparison was performed between the OWC method and the conventional rate of injection (ROI) routine. In conclusion, quantitative analysis of spray characteristics was conducted to highlight possible source of discrepancies of the conventional ROI method.
33 ADVANCED PROPULSION SYSTEMS↗
Enabling Lean and Stoichiometric Gasoline Direct Injection Engines through Mitigation of Nanoparticle Emissions
This project had the objective to efficiently reduce particulate mass (PM) and particulate number (PN) from lean and stoichiometric gasoline direction injection engines used in light duty vehicle applications. It also sought to use suspended particle instruments to measure the effective density, illustrating a pathway for new methods for accurately measuring soot mass at low concentration. The three-year effort took a systems level approach to evaluate fuel and lubricant impacts on GDI soot formation in lean and stoichiometric operation and to evaluate the impact of these factors on soot filtration aftertreatment in three-way catalyst-coated gasoline particulate filters (GPFs).
33 ADVANCED PROPULSION SYSTEMS↗
Filter-based control of particulate matter from a lean gasoline direct injection engine
New regulations requiring increases in vehicle fuel economy are challenging automotive manufacturers to identify fuel-efficient engines for future vehicles. Lean gasoline direct injection (GDI) engines offer significant increases in fuel efficiency over the more common stoichiometric GDI engines already in the marketplace. However, particulate matter (PM) emissions from lean GDI engines, particularly during stratified combustion modes, are problematic for lean GDI technology to meet U.S. Environmental Protection Agency Tier 3 and other future emission regulations. As such, the control of lean GDI PM with wall-flow filters, referred to as gasoline particulate filter (GPF) technology, is of interest. Since lean GDI PM chemistry and morphology differ from diesel PM (where more filtration experience exists), the functionality of GPFs needs to be studied to determine the operating conditions suitable for efficient PM removal. In addition, lean GDI engine exhaust temperatures are generally higher than diesel engines which results in more continuous regeneration of the GPF and less presence of the soot cake layer common to diesel particulate filters. Since the soot layer improves filtration efficiency, this distinction is important to consider. Research on the emission control of PM from a lean GDI engine with a GPF was conducted on an engine dynamometer. PM, after dilution, was characterized with membrane filters, organic vs. elemental carbon characterization, and size distribution techniques at various steady state engine speed and load points. The engine was operated in three primary combustion modes: stoichiometric, lean homogeneous, and lean stratified. In addition, rich combustion was utilized to simulate PM from engine operation during active regeneration of lean NOx control technologies. High (>95%) PM filtration efficiencies were observed over a wide range of conditions; however, some PM was observed to slip through the GPF at high speed and load conditions. The PM characterization at various engine speeds and loads will help enable optimized GPF design and control to achieve more fuel efficient lean GDI vehicles with low PM emissions.
Lewis, Sr, Samuel Arthur↗
Identification of engine oil-derived ash nanoparticles and ash formation process for a gasoline direct-injection engine
Engine oil-derived ash particles emitted from internal combustion (IC) engines are unwanted by-products, after oil is involved in in-cylinder combustion process. Since they typically come out together with particulate emissions, no detail has been reported about their early-stage particles other than agglomerated particles loaded on aftertreatment catalysts and filters. To better understand ash formation process during the combustion process, here differently formulated engine oils were dosed into a fuel system of a gasoline direct injection (GDI) engine that produces low soot mass emissions at normal operating conditions to increase the chances to find stand-alone ash particles separated from soot aggregates in the sub-20-nm size range. In addition to them, ash/soot aggregates in the larger size range were examined using scanning transmission electron microscopy (STEM)-X-ray electron dispersive spectroscopy (XEDS) to present elemental information at different sizes of particles from various oil formulations. The STEM-XEDS results showed that regardless of formulated oil type and particle size, Ca, P and C were always contained, while Zn was occasionally found on relatively large particles, suggesting that these elements get together from an early stage of particle formation. The S, Ca and P K-edge X-ray absorption near edge structure (XANES) analyses were performed for bulk soot containing raw ash. The linear combination approach & cross-checking among XANES results proposed that Ca 5 (OH)(PO 4 ) 2 , Ca 3 (PO 4 ) 2 and Zn 3 (PO 4 ) 2 are potentially major chemical compounds in raw ash particles, when combined with the STEM-XEDS results. Despite many reports that CaSO 4 is a major ash chemical when ash found in DPF/GFP systems was examined, it was observed to be rarely present in raw ashes using the S K-edge XANES analysis, suggesting ash transformation.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Lube oil-dependent ash chemistry on soot oxidation reactivity in a gasoline direct-injection engine
Gasoline particulate filters (GPF) are considered an enabling technology to meet stringent particulate matter (PM) regulations for gasoline direct-injection (GDI) engines, which are known to produce significant PM emissions. While ash loading in filters has been recognized to be detrimental in filter performance by increasing back pressure, increased ash fractions in soot were observed to enhance soot oxidation. In this study, GDI soot samples derived from different gasoline/lube oil blends were evaluated to identify potential promoting factors when formulated lube oils were dosed into gasoline fuel. Ca-derived ash enhanced soot oxidation remarkably, while P- and ZDDP-derived ash deteriorated soot oxidation. It is apparent that the promoting effect of lube oil-derived ash is due mainly to the Ca component that is the most abundant among additive components in lube oil. Bulk and surface analyses of these ash compounds indicate that Ca-derived ash would be complex compounds, while the contribution of CaSO 4 , which is one of the most abundant ash compounds from diesel engines, is almost negligible. For the validation of the ash promoting impact in filters, the regeneration experiments were compared for a TWC-coated GPF in a GDI engine before and after ash loading was performed. The pressure drop of the ash-loaded GPF decreased noticeably in the initial regeneration stage and it increased gradually, whereas that of no ash-loaded GPF increased gradually without any reduction. So, it is concluded that the ash layer in the GPF assisted soot oxidation in the early regeneration stage when it was in close contact with soot.
33 ADVANCED PROPULSION SYSTEMS↗
Multi-dimensional modeling of mixture preparation in a direct injection engine fueled with gaseous hydrogen
With the recent advances of direct injection (DI) technology, introducing hydrogen into the combustion chamber through DI is being considered as a viable approach to circumvent backfire and pre-ignition encountered in early generations of hydrogen engines. As part of a broader vision to develop a robust numerical model to study hydrogen spark ignition (SI) combustion in internal combustion (IC) engines, the present numerical investigation focuses on mixture preparation in a hydrogen DI SI engine. This study is carried out with a single hole injector with gaseous hydrogen injected at 100 bar injection pressure. Simulations are carried out for high and low tumble configurations and validated against optical data acquired from planar laser induced fluorescence (PLIF) measurements. Varying mesh configurations are investigated for the impact on in-cylinder mixture distribution. A particular emphasis is placed on the effect of nozzle geometry and mesh orientation near the wall. Overall, the computational model is found to predict the mixture distribution in the combustion cylinder reasonably well. The results showed that the alignment of mesh with the flow direction is important to achieve good agreement between numerical analysis and optical measurement data.
08 HYDROGEN↗