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Opposed-piston two-stroke engines offer numerous advantages over conventional four-stroke engines, both in terms of fundamental principles and technical aspects. The reduced heat losses and large volume-to-surface area ratio inherently result in a high thermodynamic efficiency. Additionally, the mechanical design is simpler and requires fewer components compared to conventional four-stroke engines. When combining this engine concept with alternative fuels such as hydrogen and pre-chamber technology, a potential route for carbon-neutral powertrains is observed. To ensure safe engine operation using hydrogen as fuel, it is crucial to consider strict safety measures to prevent issues such as knock, pre-ignition, and backfiring. One potential solution to these challenges is the use of direct injection, which has the potential to improve engine efficiency and expand the range of load operation.

Hydrogen is anticipated to play a pivotal role as a green energy carrier in both heavy industry and transportation. Utilizing hydrogen directly in internal combustion engines (ICE) could offer several advantages compared to alternative technologies. To achieve this objective, a proper understanding of the physical mechanisms and dynamics involved in the injection of this fuel is needed. This study applied high-fidelity computational fluid dynamics (CFD) simulations to describe the flow characteristics of hydrogen injection using hollow- and single- and multi-solid-cone injectors and their effect on mixing quality and characteristics in a constant volume quiescent environment. A reference hollow-cone configuration was used to validate the model. The results indicate that solid-cone configurations achieve greater penetration due to the flow patterns they generate. However, an increase in the number of holes leads to reduced penetration length, projected area, and induced turbulence.

The urgent need to combat global warming has spurred legislative efforts within the transport sector to transition away from fossil fuels. Hydrogen is increasingly being utilised as a green energy vector, which can aid the decarbonisation of transport, including internal combustion engines. Computational fluid dynamics (CFD) is widely used as a tool to study and optimise combustion systems especially in combination with new fuels like hydrogen. Since the behaviour of the injection event significantly impacts combustion and emissions formation especially in direct injection applications, the accurate modelling of H2 injection is imperative for effective design of hydrogen combustion systems. This work aims to evaluate unsteady Reynolds-Averaged Navier Stokes (URANS) modelling of the advective transport process and related numerical methods.

Calibration of automotive engines to ensure compliance with emission regulations is a critical phase in product development. Control of engine-out particulate emissions, which directly impact the environment and public health, is particularly important. Detailed physics-based models are typically used to gain a rich understanding of the complex physical phenomena that drive the soot particle formation in an engine cylinder. However, such models often fail to correctly represent the highly dynamic nature of the underlying mechanisms under transient combustion conditions. Moreover, most physics-based models were initially developed for diesel engine applications and their applicability to gasoline engines remains questionable due to differences in flame structure and fuel-wall interactions. Black-box models have been previously proposed to predict engine-out soot emissions, but their lack of physical interpretability is an unsolved drawback.

The Wankel rotary engine has been an attractive alternative for transportation due to its unique features of lightweight construction, small size, high power density, and adaptability to various fuels. This paper aims to investigate the performance of air-fuel mixing in a hydrogen-fuelled Wankel rotary engine using different fuelling strategies. To achieve this, 3D computational fluid dynamics (CFD) simulations were conducted using CONVERGE software on a prototype engine with a displacement of 225 cc, manufactured by Advanced Innovative Engineering UK. Initially, the simulations were validated by comparing the results with experimental data obtained from the engine fuelled with conventional gasoline under both motored and fired conditions. After validating the model, simulations were conducted on the premixed hydrogen engine combustion, followed by more detailed simulations of port fuel injection (PFI) and direct injection (DI) of hydrogen in the engine.

Typical automotive emission testing systems usually employ Flame Ionization Detection (FID) analyzers to measure unburned fuel species in the exhaust, but the technique is not suitable for engines operating on alcohol fuels. The FID method is not sensitive to measuring unburned alcohol fuels due to the presence of oxygen bonds in the fuel molecule. Other techniques, such as Fourier Transform Infrared (FTIR), can provide accurate unburned fuel measurements with alcohol fuel. However, these techniques are expensive and are less accessible compared to FID analyzers. In this study, the unburned fuel emissions from the engine exhaust were measured simultaneously with FID and FTIR analyzers, with the engine operating on pure alcohols, which are methanol, ethanol, and n-butanol. While most previous work focuses on stoichiometric air-fuel mixtures, a wide range of lean operating conditions between global-λ 1.6 to 2.8 will be tested in this study.

The pre-chamber combustion can extend the lean limit of internal combustion engines (ICE) and hence increase their overall efficiency. Compared to active pre-chambers equipped with an auxiliary fuel supply system, passive pre-chambers have lower manufacturing costs and require minimal or no design modifications to the conventional spark plug engines. The major challenge of the passive pre-chamber is to extend the lean limit as much as the active pre-chamber. Computational fluid dynamics (CFD) simulations were conducted on a light-duty single-cylinder engine geometry fitted with a passive pre-chamber and using iso-octane as fuel to investigate and optimize the passive pre-chamber fuel enrichment through the pre-chamber nozzles. The non-reacting flow simulations were performed from the intake valve open (IVO) to spark timing.

To elucidate the complex characteristics of pre-chamber combustion engines, the interaction of the hot gas jets initiated by an active narrow throated pre-chamber with lean premixed CH4/air in a heavy-duty engine was studied computationally. A twelve-hole KAUST proprietary pre-chamber geometry was investigated using CONVERGE software. The KAUST pre-chamber has an upper conical part with the spark plug, and fuel injector, followed by a straight narrow region called the throat and nozzles connecting the chambers. The simulations were run for an entire cycle, starting at the previous cycle's exhaust valve opening (EVO). The SAGE combustion model was used with the chemistry modeled using a reduced methane oxidation mechanism based on GRI Mech 3.0, which was validated against in-house OH chemiluminescence data from the optical engine experiments.

This paper investigated the spray characteristics of methanol under the flash and non-flash boiling conditions defined by the Engine Combustion Network (ECN) Spray G. As a counterpart, the spray features of iso-octane were also simulated and compared to methanol. The Volume of Fluid (VOF) approach under the Eulerian scheme was employed to model the internal nozzle flow details, which information was used to initialize the spray parcels and taken as input for the Lagrangian simulations, namely, the one-way coupling method. Since the Eulerian high-fidelity simulations allow capturing the effects of the flow inside the non-symmetrical injector, the rate of injection (ROI) profile, discharge coefficient, and plume angle et al. are not required for the Lagrangian simulations. The simulation results show that the flash boiling led to longer penetrations and higher evaporation compared to the non-flash boiling condition for both fuels.

This work presents a numerical study of the Spray A (n-dodecane) characteristics using Eulerian and Lagrangian models in a finite-volume framework. The standard k-ε turbulence model was applied for the spray simulations. For Eulerian simulations, the X-ray measured injector geometries from the Engine Combustion Network (ECN) were employed. The High-Resolution Interface Capturing (HRIC) scheme coupled with a cavitation model was utilized to track the fluid-gas interface. Simulations under both the cool and hot ambient conditions were performed. The effects of various grid sizes, turbulence constants, nozzle geometries, and initial gas volume within the injector sac on the modeling results were evaluated. As indicated by the Eulerian simulation results, no cavitation was observed for the Spray A injector; a minimum mesh size of 15.6 μm could achieve a reasonably convergent criterion; the nominal nozzle geometry predicted similar results to the X-ray measured nozzle geometry.

On-board diagnostics (OBD) data contain valuable information including real-world measurements of vehicle powertrain parameters. These data can be used to gain a richer data-driven understanding of complex physical phenomena like emissions formation during combustion. In this study, we develop a physics-based machine learning framework to predict and analyze trends in engine-out NOx emissions from diesel and diesel-hybrid heavy-duty vehicles. This model differs from black-box machine learning models presented in previous literature because it incorporates engine combustion parameters that allow physical interpretation of the results. Based on chemical kinetics and the characteristics of diffusive combustion, NOx emissions from compression ignition engines primarily depend non-linearly on three parameters: adiabatic flame temperature, the oxygen concentration in the cylinder when the intake valves are closed, and combustion time duration.

The high-pressure isobaric combustion has been proposed as the most suitable combustion mode for the double compre4ssion expansion engine (DCEE) concept. Previous experimental and simulation studies have demonstrated an improved efficiency compared to the conventional diesel combustion (CDC) engine. In the current study, isobaric combustion was achieved using a single injector with multiple injections. Since this concept involves complex phenomena such as spray to spray interactions, the computational models were extensively validated against the optical engine experiment data, to ensure high-fidelity simulations. The considered optical diagnostic techniques are Mie-scattering, fuel tracer planar laser-induced fluorescence (PLIF), and natural flame luminosity imaging. Overall, a good agreement between the numerical and experimental results was obtained.

High-pressure internal combustion engines promise high efficiency, but a proper injection strategy to minimize heat losses and pollutant emissions remain a challenge. Previous studies have concluded that two injectors, placed at the piston bowl's rim, simultaneously improve the mixing and reduce the heat losses. The two-injector configuration further improves air utilization while keeping hot zones away from the cylinder walls. This study investigates how the two-injector concept delivers even higher efficiency by providing additional control of spray -and injection angles. Three-dimensional Reynolds-averaged Navier-Stokes simulations examined several umbrella angles, spray-to-spray angles, and injection orientations by comparing the two-injector cases with a reference one-injector case. The study focused on heat transfer reduction, where the two-injector approach reduces the heat transfer losses by up to 14.3 % compared to the reference case.

Pre-chamber combustion (PCC) engines allow extending the lean limit of operation compared to common SI engines, thus being a candidate concept for the future clean transportation targets. To understand the fundamental mechanisms of the main chamber charge ignition in PCC engines, the effects of the composition in the pre-chamber were investigated numerically. A well-stirred reactor combustion model coupled with a methane oxidation mechanism reduced from GRI 3.0 was used. An open-cycle simulation was run with initialization at exhaust valve opening (EVO). For posterior simulations, the initial flow field was attained by mapping the field variables obtained from the full cycle simulation. The entire simulation domain (pre-chamber and main chamber) global excess air ratio (λ) was set to 1.3.

To achieve full automation in self-driving vehicles, environmental perception sensing accuracy is critically important. However, ambient particles in adverse weather like foggy, rainy, or snowy conditions can significantly scatter the incident laser beam, and therefore contaminate the intensity and accuracy of light detection and ranging (LiDAR) sensors. Especially compared to the rapidity of technology development in self-driving vehicles, there is a significant lack of documented research on LiDAR systems with wavelength longer than 1 μm for application in Advanced Driver-Assistance Systems. In this work, experimental studies were performed with a state-of-the-art 1.55 μm wavelength automotive-grade LiDAR system in a controlled laboratory fog chamber. The goal of the research is to correlate laser attenuation and the optical properties of fog particles.

The utilization of H2 to catalytically treat NO emissions under lean-burn engine exhaust conditions was studied on Pt- and Pd-containing catalysts supported on CeO2 and MgO. The catalytic performance was examined using a fixed-bed reactor whose dry effluent gas stream was analyzed by an online FTIR analyzer. The catalysts NO conversion and N2 selectivity were measured in the range of 125-3000C with a feed gas composition of 0.05%NO/1%H2/10%O2/N2. The CeO2-based catalysts exhibited higher NO conversion, and the most effective catalyst was Pd/CeO2, with a conversion of 67% and selectivity of 70% near 2300C. The prepared solids were characterized using different techniques (BET, ICP-OES, CO pulse chemisorption, STEM, EELS and EDS) to correlate the structural and morphological properties of the metallic phase and the support with the catalytic activity. CeO2 is a more effective support as it yields higher metal dispersion and better facilitates the reduction of the Pt and Pd catalysts.

In order to understand supercritical jet flows further, well resolved large eddy simulations (LES) of a n-dodecane jet mixing with surrounding nitrogen are conducted. A real fluid thermodynamic model is used to account for the fuel compressibility and variable thermophysical properties due to the solubility of ambient gas and liquid jet using the cubic Peng-Robinson equation of state (PR-EOS). A molar averaged homogeneous mixing rule is used to calculate the mixing properties. The thermodynamic model is coupled with a pressure-based solver to simulate multispecies reacting flows. The numerical model is based on a second order accurate method implemented in the open source OpenFOAM-6 software. First, to evaluate the present numerical model for sprays, 1D advection and shock tube benchmark problems at supercritical conditions are shown.

The focus of this study is to aid the development of the isobaric combustion engine by investigating multiple injection strategies at moderately high pressures. A three-dimensional (3D) commercial computational fluid dynamics (CFD) code, CONVERGE, was used to conduct simulations. The validation of the isobaric combustion case was carried out through the use of a single injector with multiple injections. The computational simulations were matched to the experimental data using methods outlined in this paper for different multiple injection cases. A sensitivity analysis to understand the effects of different modeling components on the quantitative prediction was carried out. First, the effects of the kinetic mechanisms were assessed by employing different chemical mechanisms, and the results showed no significant difference in the conditions under consideration.

Towards a fundamental understanding of the ignition characteristics of pre-chamber (PC) combustion engines, computational fluid dynamics (CFD) simulations were conducted using CONVERGE. To assist the initial design of the KAUST pre-chamber engine experiments, the primary focus of the present study was to assess the impact of design parameters such as throat diameter, nozzle diameter, and nozzle length. The well-stirred reactor combustion model coupled with a methane oxidation mechanism reduced from GRI 3.0 was used. A homogeneous charge of methane and air with λ = 1.3 on both the PC and main chamber (MC) was assumed. The geometrical parameters were shown to affect the pre-chamber combustion characteristics, such as pressure build-up, radical formation, and heat release as well as the composition of the jets penetrating and igniting the main chamber charge. In addition, the backflow of species pushed inside the pre-chamber due to the flow reversal (FR) event was analyzed.

To provide insights into the fundamental characteristics of pre-chamber combustion engines, the ignition of lean premixed CH4/air due to hot gas jets initiated by a passive narrow throated pre-chamber in a heavy-duty engine was studied computationally. A twelve-hole pre-chamber geometry was investigated using CONVERGETM software. The numerical model was validated against the experimental results. To elucidate the main-chamber ignition mechanism, the spark plug location and spark timing were varied, resulting in different pressure gradient during turbulent jet formation. Different ignition mechanisms were observed for turbulent jet ignition of lean premixed CH4/air, based on the geometry effect. Ignition behavior was classified into the flame and jet ignition depending on the significant presence of hot active radicals. The jet ignition, mainly due to hot product gases was found to be advanced by the addition of a small concentration of radicals.