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The design and testing of the valve train for a new two-stroke diesel engine concept [1,2] is presented. The gas exchange of this process requires extremely fast-acting inlet valves, which constituted a very demanding designing task. A simulation model of the prototype valve train was constructed with commercially available software. The simulation program served as the main tool for optimizing the dynamic behavior of the valve train. The prototype valve train was built according to the simulations and valve acceleration measurements were performed in order to validate the simulation results. The simulations and measurements are presented in detail in this paper.

New measurements have been done in order to obtain information concerning the effect of EGR and a paraffinic hydrotreated fuel for the smoke and NO emissions of a heavy-duty diesel engine. Measured smoke number and NO emissions are explained using detailed chemical kinetic calculations and CFD simulations. The local conditions in the research engine are analyzed by creating equivalence ratio - temperature (Phi-T) maps and analyzing the CFD results within these maps. The study uses different amount of EGR and two different diesel fuels; standard EN590 diesel fuel and a paraffinic hydrotreated vegetable oil (HVO). The detailed chemical kinetic calculations take into account the different EGR rates and the properties of the fuels. The residence time in the kinetical calculations is used to explain sooting combustion behavior within diesel combustion. It was observed that NO emission trends can be well captured with the Phi-T maps but the situation is more difficult with the engine smoke.

The engine fueled with methane/diesel is a promising and highly attractive operation mode due to its high performance-to-cost ratio and clean-burning qualities. However, the combustion process and chemical reactions in dual fuel combustion are highly complex, involving short transient pilot-fuel injection into the premixed gaseous fuel charge, autoignition, and combustion mode transition into premixed flame propagation. The motivation of the current investigation is to gain an insight into the combustion dynamics in dual fuel combustion engine based on chemical radicals and thermal radiation. The chemiluminescence (CL) and natural luminosity (NL) are expected to provide specific characteristics in combustion control and monitoring. To visualize the highly unsteady combustion process in terms of OH*, CH2O* radicals and natural luminous emissions, the band pass filters with 308 nm, 330 nm combined with an image doubler are employed to visualize the OH* and CH2O* CL simultaneously.

Non-evaporating diesel sprays have been simulated utilizing the ETAB and the WAVE atomization and breakup models and have been compared with experimental data. The experimental penetrations and widths were determined from back-lit spray images and the droplet sizes have been measured by means of a Malvern particle sizer. The model evaluation criteria include the spray penetration, the spray width and the local droplet size. The comparisons have been performed for variations of the injection pressure, the gas density and the fuel viscosity. The fuel nozzle exit velocities used in the simulations have been computed with a special code that considers the effect of in-nozzle cavitation. The simulations showed good overall agreement with experimental data. However, the capabilities of the models to predict the droplet size for different fuels could be improved.

Combustion simulations utilizing the characteristic time combustion model have been performed for four DI diesel engines ranging in size from heavy-duty to large-bore designs. It has been found that the pre-factor to the turbulent characteristic time acts as a scaling parameter between the engines. This phenomenon is explained in terms of the non-equilibrium behavior of the turbulent time and length scales, as is encountered in the rapidly distorting, spray-induced flows of DI diesel engines. In fact, the equilibrium assumption between turbulence production and dissipation, which forms the basis for the employed k-ε-type turbulence models, does not hold in these situations. For such flows, the real turbulent dissipation time scale is locally proportional to the turbulent characteristic time scale which is determined by a typical eddy turnover time.

A modified version of the Laminar and Turbulent Characteristic Time combustion model and the Hiroyasu-Magnussen soot model have been implemented in the flow solver Star-CD. Combustion simulations of three DI diesel engines, utilizing the standard k-ε turbulence model and a modified version of the RNG k-ε turbulence model, have been performed and evaluated with respect to combustion performance and emissions. Adjustments of the turbulent characteristic combustion time coefficient, which were necessary to match the experimental cylinder peak pressures of the different engines, have been justified in terms of non-equilibrium turbulence considerations. The results confirm the existence of a correlation between the integral length scale and the turbulent time scale. This correlation can be used to predict the combustion time scale in different engines.

Real gas effects are studied during the compression stroke of a diesel engine. Several different real gas models are compared to the ideal gas law and to the experimental pressure history. Comparisons are done with both 1-D and CFD simulations, and reasons and answers are found out for the observed differences between simulations and experimental data. The engine compression ratio was measured for accurate model predictions. In addition, a 300bar extreme pressure case is also analyzed with the real gas model since an engine capable for this performance level is currently being built at the Aalto University School of Science and Technology. Real gas effects are even more important in these extreme conditions than in normal operating pressures. Finally, it is shown that the predicted pressure history during an engine compression stroke by a real gas model is more accurately predicted than by the ideal gas law.

Distillation properties of gasoline are regulated to ensure the safe and efficient operation of SI-engines. Blending various gasoline components affects the distillation values in a non-linear fashion, making the prediction of these properties challenging. Furthermore, the rise of renewable components necessitates the development of new property prediction methods. In this work, a variety of Machine Learning models were created to predict the distillation points of gasoline blends based on the blending recipe. As input data, real industrial data from a refinery was used together with data from blends created for R&D purposes. The predicted properties were the evaporated volume at the 70 and 100 °C distillation points (E70 and E100). Altogether four different machine learning models were trained, cross-validated and tested using seven different pre-processing methods. It was found that Support Vector Regression (SVR) was the most effective at predicting the distillation points.

Pre-ignition in a boosted spark-ignition engine can be triggered by several mechanisms, including oil-fuel droplets, deposits, overheated engine components and gas-phase autoignition of the fuel-air mixture. A high pre-ignition resistance of the fuel used mitigates the risk of engine damage, since pre-ignition can evolve into super-knock. This paper presents the pre-ignition propensities of 11 RON 89-100+ gasoline fuel blends in a single-cylinder research engine. Albeit the addition of two high-octane components (methanol and reformate) to a toluene primary reference fuel improved the pre-ignition resistance, one high-RON fuel experienced runaway pre-ignition at relatively low boost pressure levels. A comparison of RON 96 blends showed that the fuel composition can affect pre-ignition resistance at constant RON.

A dual-piston, two-stroke, compression ignition free piston engine has been simulated with zero- and one-dimensional performance simulation codes. The simulation models used in the codes have been developed to analyze and improve the internal combustion engine process of a hydraulic free piston engine prototype. The prototype was designed and constructed in Tampere University of Technology at the Institute of Hydraulics and Automation. Performance simulation analyses were conducted in Helsinki University of Technology at the Internal Combustion Engine Laboratory. The zero-dimensional model is used for the simulation of piston dynamics. The one-dimensional model is used for performance simulation, especially for the simulation of gas exchange process. The simulation results were verified through prototype engine measurements.

The current study was focused on flow field measurements of diesel sprays. The global fuel spray characteristics, such as spray penetration, have also been measured. Particle Image Velocimetry (PIV) was utilized for flow field measurements and the global spray characteristics were recorded with high-speed back light photographing. The flow field was scanned to get an idea of the compatibility of PIV technique applied to dense and high velocity sprays. It is well proven that the PIV technique can be utilized at areas of low number density of droplets, but the center of the spray is way beyond the ideal PIV measurement conditions. The depth at which accurate flow field information can be gathered was paid attention to.

Optimal fuel injection strategies are obtained with a micro-genetic algorithm and an adaptive gradient method for a nonroad, medium-speed DI diesel engine equipped with a multi-orifice, asynchronous fuel injection system. The gradient optimization utilizes a fast-converging backtracking algorithm and an adaptive cost function which is based on the penalty method, where the penalty coefficient is increased after every line search. The micro-genetic algorithm uses parameter combinations of the best two individuals in each generation until a local convergence is achieved, and then generates a random population to continue the global search. The optimizations have been performed for a two pulse fuel injection strategy where the optimization parameters are the injection timings and the nozzle orifice diameters.

The objective of this study is the development of a computationally efficient CFD-based tool with the capability of finding optimal engine operating conditions with respect to emissions and fuel consumption. The approach taken uses a conjugate gradient method, where the line search is performed with a backtracking algorithm. The initial backtracking step employs an adaptive step size mechanism which depends on the steepness of the search direction. The engine simulations are performed with a KIVA-3-based code which is equipped with well-established spray, combustion and emission models. The cost function is based on the idea of the penalty method and is minimized over the unit cube in n-dimensional space, which represents the set of normalized injection parameters under investigation. The application of this optimization tool is demonstrated for the Sulzer S20, a central-injection, non-road DI diesel engine.

Spray evolution in diesel engines plays a crucial role in fuel-air mixing, ignition behavior, combustion characteristics, and emissions. There is a variety of phenomenological spray models and computational fluid dynamics (CFD) simulations have been applied to characterize the spray evolution and fuel-air mixing. However, most studies were focused on the spray phenomenon under a limited range of injection and ambient conditions. Especially, the prediction of spray geometry in multi-hole injectors remains a great challenge due to the lack of understanding of the complicated flow dynamics. To overcome the challenges, a series of spray experiments were carried out in a constant volume spray chamber (CVSC) coupled with high-speed Mie-scattering imaging to obtain the spray characteristics at various injection and ambient conditions.

The objective of this study was to build up an optical access into a large bore medium-speed research engine and carry out the first fuel spray Particle Image Velocimetry (PIV) measurements in the running large bore medium-speed engine in high pressure environment. The aim was also to measure spray penetration with same optical access and apparatus. The measurements were performed in a single-cylinder large bore medium-speed research engine, the Extreme Value Engine (EVE) with optical access into the combustion chamber. The authors are not aware of any other studies on optical spray measurements in large bore medium-speed diesel engines. Successful optical measurements of the fuel spray penetration and the velocity fields were carried out. This confirms that the exceptional component design and laser sheet alignment used in this study proved to be valid for optical fuel spray measurements in large-bore medium-speed diesel engines.

A novel two-stroke engine concept is introduced. The cylinder scavenging takes place during the upward motion of the piston. The gas exchange valves are similar to typical four-stroke valves, but the intake valves are smaller and lighter. The scavenging air pressure is remarkably higher than in present-day engines. The high scavenging air pressure is produced by an external compressor. The two-stroke operation is achieved without the drawbacks of port scavenged engines. Moreover, the combustion circumstances, charge pressure and temperature and internal exhaust gas re-circulation (EGR) can be controlled by using valve timings. There is good potential for a substantial reduction in NOx emissions through the use of adjustable compression pressure and temperature and by using the adjustable amount of exhaust gas re-circulation.

This study presents a novel crank mechanism which enables easy and fast compression ratio adjustment. The novel crank mechanism and piston travel are explained and highlighted. The basic idea is that eccentric gear is installed on a crankshaft web. Eccentric gear is fitted to the big end of the connection rod and eccentricity is controlled by rotating the control gear a discrete amount. Thus the position of eccentricity is varied and controls an effective stroke length. The compression ratio is adjusted to best fit current load demand, either optimizing fuel efficiency or engine power and torque. Adjustments are individual to each cylinder. The system is capable of adjusting from min to max within 10 milliseconds [ms]. Emphasis is on reduction of CO2 emissions and reducing fuel consumption, especially at part load condition. The governing mechanical equations are presented.

A correction for the turbulence dissipation, based on non-equilibrium turbulence considerations from rapid distortion theory, has been derived and implemented in combination with the RNG k - ε model in a KIVA-based code. This model correction has been tested and compared with the standard RNG k - ε model for the compression and the combustion phase of two heavy duty DI diesel engines. The turbulence behavior in the compression phase shows clear improvements over the standard RNG k - ε model computations. In particular, the macro length scale is consistent with the corresponding time scale and with the turbulent kinetic energy over the entire compression phase. The combustion computations have been performed with the characteristic time combustion model. With this dissipation correction no additional adjustments of the turbulent characteristic time model constant were necessary in order to match experimental cylinder pressures and heat release rates of the two engines.

The objective of this study is to achieve high reduction of NOx emissions in a medium-speed single-cylinder research engine. The main feature of this research engine is that the gas exchange valve timing is completely adjustable with electro-hydraulic actuators. The study is carried out at high engine load and using a very advanced Miller valve timing. Since the engine has no turbocharger, but a separate charge air system, 1-D simulations are carried out to find the engine setup, which would be close to the operating points of a real engine. The obtained NOx reduction is over 40% with no penalty in fuel consumption.

The present-day transport sector needs sustainable energy solutions. Substitution of fossil-fuels with fuels produced from biomass is one of the most relevant solutions for the sector. Nevertheless, bringing biofuels into the market is associated with many challenges that policymakers, feedstock suppliers, fuel producers, and engine manufacturers need to overcome. The main objective of this research is an investigation of the impact of alternative fuel properties on light vehicle engine performance and greenhouse gases (GHG). The purpose of the present study is to provide decision-makers with tools that will accelerate the implementation of biofuels into the market. As a result, two models were developed, that represent the impact of fuel properties on engine performance in a uniform and reliable way but also with very high accuracy (coefficients of determination over 0.95) and from the end-user point of view.