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The laminar burning speed is an important intrinsic property of an air-fuel mixture determining key combustion characteristics such as turbulent flame propagation. It is a function of the mixture composition (mixture fraction and residual gas mass fraction) and of the thermodynamic conditions. Experimental measurements of Laminar Flame Speeds (LFS) are common in literature, but initial pressure and temperature are limited to low values due to the test conditions: typical pressure values for LFS detection are lower than 25 bar, and temperature rarely exceeds 550 K. Actual trends in spark ignition engines are to increase specific power output by downsizing and supercharging, thus the flame front involves even more higher pressure and temperature since the beginning of combustion.

The performance optimization of modern Spark Ignition engines is limited by knock occurrence: heavily downsized engines often are forced to work in the Knock-Limited Spark Advance (KLSA) range. Knock control systems monitor the combustion process, allowing to achieve a proper compromise between performance and reliability. Combustion monitoring is usually carried out by means of accelerometers or ion sensing systems, but recently the use of cylinder pressure sensors is also becoming frequent in motorsport applications. On the other hand, cylinder pressure signals are often available in the calibration stage, where SA feedback-control based on the pressure signal can be used to avoid damages to the engine during automatic calibration. A predictive real-time combustion model could help optimizing engine performance, without exceeding the allowed knock severity.

This paper presents a methodology for the 3D CFD simulation of the intake and compression processes of four stroke internal combustion engines.The main feature of this approach is to provide very accurate initial conditions by means of a cost-effective initialization step. Calculations are applied to a low stroke-to-bore SI engine, operated at full load and maximum engine speed. It is demonstrated that initial conditions for this kind of engines have an important influence on flow field development, particularly in terms of mean velocities close to the firing TDC. Simulation results are used to discuss the choice of a set of parameters for the flow field characterization of low stroke-to-bore engines, as well as to provide an insight into the flow patterns during the overlapping period.

Knocking combustions heavily limits the efficiency of Spark Ignition engines. The compression ratio is limited in the design stage of the engine development, letting to Spark Advance control the task of reducing the odds of abnormal combustions. A detailed analysis of knocking events can help improving engine performance and diagnosis strategies. An effective way is to use advanced 3D CFD (Computational Fluid Dynamics) simulation for the analysis and prediction of combustion performance. Standard 3D CFD approach is based on RANS (Reynolds Averaged Navier Stokes) equations and allows the analysis of the mean engine cycle. However knocking phenomenon is not deterministic and it is heavily affected by the cycle to cycle variation of engine combustions. A methodology for the evaluation of the effects of CCV (Cycle by Cycle Variability) on knocking combustions is here presented, based on both the use of Computation Fluid Dynamics (CFD) tools and experimental information.

Water injection is becoming a technology of increasing interest for SI engines development to comply with current and prospective regulations. To perform a rapid optimization of the main parameters involved by the water injection process, it is necessary to have reliable CFD methodologies capable of capturing the most important phenomena. In the present work, a methodology for the CFD simulation of combustion cycles of SI GDI turbocharged engines under water injection operation is proposed. The ECFM-3Z model adopted for combustion and knock simulations takes advantages by the adoption of correlations for the laminar flame speed, flame thickness and ignition delay times prediction obtained by a detailed chemistry calculation. The latter uses machine learning algorithms to reduce the time to generate the full database while still maintaining an even distribution along the variables of interest.

Compression-ignited engines are still considered the most efficient and reliable technology for automotive applications. However, current and future emission regulations, which severely limit the production of NOx, particulate matter and CO2, hinder the use of diesel-like fuels. As a matter of fact, the spontaneous ignition of directly-injected Diesel leads to a combustion process that is heterogeneous by nature, therefore characterized by the simultaneous production of particulate matter and NOx. In this scenario, several innovative combustion techniques have been investigated over the past years, the goal being to benefit from the high thermal efficiency of compression-ignited engines, which results primarily from high Compression Ratio and lean and unthrottled operation, while simultaneously mitigating the amount of pollutant emissions.

The increasing of the overall engine performance requires the investigation of the unsteady engine phenomena affecting intake air flow and the air-fuel mixing process. The “standard” RANS methodology often doesn't allow one to achieve a qualitative and quantitative accurate prediction of these phenomena. The aim of this paper is to show the potential and the limits of LES numerical technique in the simulation of actual IC engine flows and to assess the influence of some basic parameters on the LES simulation results. The paper introduces the use of a merit parameter suggested by Pope for evaluating the quality of the LES solution. The CFD code used is Fluent v6.2 and two basic test cases have been simulated. The first one is the flow over a backward facing step in order to perform a preliminary parametric numerical analysis. A one-equation dynamic subgrid-scales turbulence model is used.

During the last years the deep re-examination of the engine design for lowering engine emissions involved two-wheel vehicles too. The IC engine overall efficiency plays a fundamental role in determining final raw emissions. From this point of view, the optimization of the in-cylinder flow organization is mandatory. In detail, in SI engines the generation of a coherent tumble vortex having dimensions comparable to the engine stroke could be of primary importance to extend the engines' ignition limits toward the field of the dilute/lean mixtures. For motorbike and motor scooter applications, the optimization of the tumble generation is considered an effective way to improve the combustion system efficiency and to lower emissions, considering also that the two-wheels layout represents an obstacle in adopting the advanced post-treatment concepts designed for automotive applications.

Measurement of particle number was introduced in the Euro 5/6 light duty vehicle emissions regulation. Due to the complex nature of combustion exhaust particles, and to transportation, transformation and deposition mechanisms, such type of measurement is particularly complex, and regression analysis is commonly used for the comparison of different measurement systems. This paper compares various commercial instruments, developing a correlation analysis focused on PN (Particle Number) measurement, and isolating the factors that mainly influence each measuring method. In particular, the experimental activity has been conducted to allow critical comparisons between measurement techniques that are imposed by current regulations and instruments that can be used also on the test cell. The paper presents the main results obtained by analyzing instruments based on different physical principles, and the effects of different sampling locations and different operating parameters.

Two cavitation models are evaluated based on their ability to reproduce the development of cavitation experimentally observed by Winklhofer et al. inside injector hole geometries. The first is Singhal's model, derived from a reduced form of the Rayleigh-Plesset equation, implemented in the commercial CFD package Fluent. The second is the homogeneous relaxation model, a continuum model that uses an empirical timescale to reproduce a range of vaporization mechanisms, implemented in the OpenFOAM framework. Previous work by Neroorkar et al. validated the homogeneous relaxation model for one of the nozzle geometries tested by Winklhofer et al. The present work extends that validation to all the three geometries considered by Winklhofer et al in order to compare the models' ability to capture the effects of nozzle convergence.

Due to the ever increasingly stringent emission regulations for passenger vehicles, the efficiency and performance increase of Spark Ignition (SI) engines have been under the focus of the engine manufacturers. The quest for efficiency and performance increase has led to the development of increasingly complex powertrains and control strategies. The development process requires novel methods that feature a smooth transition between the real and the virtual prototypes. Furthermore, to reduce the development time and cost, developing an engine simulator with a low computational effort and good accuracy, which predicts the engine behavior on the entire operating range, plays a crucial role. This work proposes an Artificial Intelligence-based engine simulator for a Spark Ignition engine. The simulator relies on Neural Networks for the calculation of the main combustion metrics. In the first part of this paper, the data acquired at the engine test cell are analyzed.

This work focuses on the development and validation of a data-driven model capable of predicting the maximum in-cylinder pressure during the operation of an internal combustion engine, with the least possible computational effort. The model is based on two parameters, one that represents engine load and another one the combustion phase. Experimental data from four different gasoline engines, two turbocharged Gasoline Direct Injection Spark Ignition, a Naturally Aspirated SI and a Gasoline Compression Ignition engine, was used to calibrate and validate the model. Some of these engines were equipped with technologies such as Low-Pressure Exhaust Gas Recirculation and Water Injection or a compression ignition type of combustion in the case of the GCI engine. A vast amount of engine points were explored in order to cover as much as possible of the operating range when considering automotive applications and thus confirming the broad validity of the model.

The modern spark ignition engines, due to the introduced strategies for limiting the consumption without reducing the power, are sensitive to both the detonation and the increase of the inlet turbine temperature. In order to reduce the risk of detonation, the use of dilution with the products of combustion (EGR) is an established practice that has recently improved with the use of water vapor obtained via direct or indirect injection. The application and optimization of these strategies cannot ignore the knowledge of physical quantities characterizing the combustion such as the laminar flame speed and the ignition delay, both are intrinsic property of the fuel and are function of the mixture composition (mixture fraction and dilution) and of its thermodynamic conditions. The experimental measurements of the laminar flame speed and the ignition delay available in literature, rarely report the effects of dilution by EGR or water vapor.

Nowadays, in the perspective of a full electric automotive scenario, internal combustion engines can still play a central role in the fulfilment of different needs if the efficiency will be improved, and the tailpipe emission will be further limited. Gasoline Compression Ignition engines can offer a favourable balance between NOx, particulate, operating range. Stable operations are ensured by ultra-high gasoline injection pressure and tailored injection patterns in order to design the most proper local fuel distribution. In this context, engine simulations by means of CFD codes can provide insights on the design of the injection parameters, and emphasis must be placed on the capture of spray-wall impingement behaviour under those non-conventional conditions. This paper aims to analyse the spray-wall impingement behaviour of ultra-high gasoline spray using a combined experimental-CFD approach.

Metallic open-cell foams have proven to be valuable for many engineering applications. Their success is mainly related to mechanical strength, low density, high specific surface, good thermal exchange, low flow resistance and sound absorption properties. The present work aims to investigate three principal aspects of real foams: the geometrical characterization, the flow regime characterization, the effects of the pore size and the porosity on the pressure drop. The first aspect is very important, since the geometrical properties depend on other parameters, such as porosity, cell/pore size and specific surface. A statistical evaluation of the cell size of a foam sample is necessary to define both its geometrical characteristics and the flow pattern at a given input velocity. To this purpose, a procedure which statistically computes the number of cells and pores with a given size has been implemented in order to obtain the diameter distribution.

The recent search for extremely efficient spark-ignition engines has implied a great increase of in-cylinder pressure and temperature levels, and knocking combustion mode has become one of the most relevant limiting factors. This paper reports the main results of a specific project carried out as part of a wider research activity, aimed at modelling and real-time controlling knock-induced damage on aluminum forged pistons. The paper shows how the main damage mechanisms (erosion, plastic deformation, surface roughness, hardness reduction) have been identified and isolated, and how the corresponding symptoms may be measured and quantified. The second part of the work then concentrates on understanding how knocking combustion characteristics affect the level of induced damage, and which parameters are mainly responsible for piston failure.

This paper presents simulation and experimental results of the effects of intake water injection on the main combustion parameters of a turbo-charged, direct injection spark ignition engine. Water injection is more and more considered as a viable technology to further increase specific output power of modern spark ignition engines, enabling extreme downsizing concepts and the associated efficiency increase benefits. The paper initially presents the main results of a one-dimensional simulation analysis carried out to highlight the key parameters (injection position, water-to-fuel ratio and water temperature) and their effects on combustion (in-cylinder and exhaust temperature reduction and knock tendency suppression). The main results of such study have then been used to design and conduct preliminary experimental tests on a prototype direct-injection, turbocharged spark ignition engine, modified to incorporate a new multi-point water injection system in the intake runners.

Pre-ignition combustions are extremely harmful and undesired, but the recent search for extremely efficient spark-ignition engines has implied a great increase of the in-cylinder pressure and temperature levels, forcing engine operation to conditions that may trigger this type of anomalous combustion much more frequently. For this reason, an accurate on-board diagnosis system is required to adopt protective measures, preventing engine damage. Ion current signal provides relevant information about the combustion process, and it results in a good compromise between cost, durability and information quality (signal to noise ratio levels). The GDI turbocharged engine used for this study was equipped with a production ion current sensing system, while in-cylinder pressure sensors were installed for research purposes, to better understand the pre-ignition phenomenon characteristics, and to support the development of an on-board diagnostic system solely based on ion current measurements.

The optimization of turbocharging systems for automotive applications has become crucial in order to increase engine performance and meet the requirements for pollutant emissions and fuel consumption reduction. Unfortunately, performing an optimal turbocharging system control is very difficult, mainly due to the fact that the flow through compressor and turbine is highly unsteady, while only steady flow maps are usually provided by the manufacturer. For these reasons, one of the most important quantities to be used onboard for optimal turbocharger system control is the rotational speed fluctuation, since it provides information both on turbocharger operating point and on the energy of the unsteady flow in the intake and exhaust circuits. This work presents a methodology that allows determining the instantaneous turbocharger rotational speed through a proper frequency processing of the signal coming from one accelerometer mounted on the turbocharger compressor.

Scaled models are often used to check the aerodynamic performance of full scale aircraft and airship concepts, which have gone through a conceptual and preliminary design process. Results from these tests can be quite useful to improve the design of unconventional airships whose aerodynamics might be quite different from classical configurations. Once the airship geometry has been defined, testing is required to acquire aerodynamic data necessary to implement the mathematical model of the airship needed by the flight control system to develop full autonomous capabilities. Rapid prototyping has the great potential of playing a beneficial role in unconventional autonomous airship design similarly to the success obtained in the design process of conventional aircrafts.