Development of advanced methods for the simulation of the reacting mixture formation in internal combustion engines with the use of machine learning algorithms

Besides increasing the share of electric and hybrid vehicles, in order to comply with more stringent environmental protection limitations, in the mid-term the auto industry must improve the efficiency of the internal combustion engine and the well to wheel efficiency of the employed fuel. To achieve this target, a deeper knowledge of the phenomena that influence the mixture formation and the chemical reactions involving new synthetic fuel components is mandatory, but complex and time intensive to perform purely by experimentation. Therefore, numerical simulations play an important role in this development process, but their use can be effective only if they can be considered accurate enough to capture these variations. The most relevant models necessary for the simulation of the reacting mixture formation and successive chemical reactions have been investigated in the present work, with a critical approach, in order to provide instruments to define the most suitable approaches also in the industrial context, which is limited by time constraints and budget evaluations. To overcome these limitations, new methodologies have been developed to conjugate detailed and simplified modelling techniques for the phenomena involving chemical reactions and mixture formation in non-traditional conditions (e.g. water injection, biofuels etc.). Thanks to the large use of machine learning and deep learning algorithms, several applications have been revised or implemented, with the target of reducing the computing time of some traditional tasks by orders of magnitude. Finally, a complete workflow leveraging these new models has been defined and used for evaluating the effects of different surrogate formulations of the same experimental fuel on a proof-of-concept GDI engine model.

Optimization and development of low environmental impact propulsion systems

The aim of the Ph.D. research project was to explore Dual Fuel combustion and hybridization. Natural gas-diesel Dual Fuel combustion was experimentally investigated on a 4-Stroke, 2.8 L, turbocharged, light-duty Diesel engine, considering four operating points in the range between low to medium-high loads at 3000 rpm. Then, a numerical analysis was carried out using a customized version of the KIVA-3V code, in order to optimize the diesel injection strategy of the highest investigated load. A second KIVA-3V model was used to analyse the interchangeability between natural gas and biogas on an intermediate operating point. Since natural gas-diesel Dual Fuel combustion suffers from poor combustion efficiency at low loads, the effects of hydrogen enriched natural gas on Dual Fuel combustion were investigated using a validated Ansys Forte model, followed by an optimization of the diesel injection strategy and a sensitivity analysis to the swirl ratio, on the lowest investigated load. Since one of the main issues of Low Temperature Combustion engines is the low power density, 2-Stroke engines, thanks to the double frequency compared to 4-Stroke engines, may be more suitable to operate in Dual Fuel mode. Therefore, the application of gasoline-diesel Dual Fuel combustion to a modern 2-Stroke Diesel engine was analysed, starting from the investigation of gasoline injection and mixture formation. As far as hybridization is concerned, a MATLAB-Simulink model was built to compare a conventional (combustion) and a parallel-hybrid powertrain applied to a Formula SAE race car.

Modelling, control and testing of internal combustion engines to minimize consumption and pollutant emissions

The objective of the PhD thesis was to research technologies and strategies to reduce fuel consumption and pollutants emission produced by internal combustion engines. In order to meet this objective my activity was focused on the research of advanced controls based on cylinder pressure feedback. These types of control strategies were studied because they present promising results in terms of engine efficiency enhancement. In the PhD dissertation two study cases are presented. The first case is relative to a control strategy to be used at the test bench for the optimisation of the spark advance calibration of motorcycle Engine. The second case is relative to a control strategy to be used directly on board of mining engines with the objective or reducing the engine consumption and correct ageing effects. In both cases the strategies proved to be effective but their implementation required the use of specific toolchains for the measure of the cylinder pressure feedback that for a matter of cost makes feasible the strategy use only for applications: • At test bench • In small-markets like large off-road engines The major bottleneck that prevents the implementation of these strategies on mass production is the cost of cylinder pressure sensor. In order to tackle this issue, during the PhD research, the development of a low-cost sensor for the estimation of cylinder pressure was studied. The prototype was a piezo-electric washer designed to replace the standard spark-plug washer or high-pressure fuel injectors gasket. From the data analysis emerged the possibility to use the piezo-electric prototype signal to evaluate with accuracy several combustion metrics compatible for the implementation of advanced control strategies in on-board applications. Overall, the research shows that advanced combustion controls are feasible and beneficial, not only at the test bench or on stationary engines, but also in mass-produced engines.

Design and testing of innovative, artificial intelligence-based techniques to model and control the combustion process and to reduce the Co2 emissions in modern, high-performance, gasoline direct injection engines

This work deals with the development of calibration procedures and control systems to improve the performance and efficiency of modern spark ignition turbocharged engines. The algorithms developed are used to optimize and manage the spark advance and the air-to-fuel ratio to control the knock and the exhaust gas temperature at the turbine inlet. The described work falls within the activity that the research group started in the previous years with the industrial partner Ferrari S.p.a. . The first chapter deals with the development of a control-oriented engine simulator based on a neural network approach, with which the main combustion indexes can be simulated. The second chapter deals with the development of a procedure to calibrate offline the spark advance and the air-to-fuel ratio to run the engine under knock-limited conditions and with the maximum admissible exhaust gas temperature at the turbine inlet. This procedure is then converted into a model-based control system and validated with a Software in the Loop approach using the engine simulator developed in the first chapter. Finally, it is implemented in a rapid control prototyping hardware to manage the combustion in steady-state and transient operating conditions at the test bench. The third chapter deals with the study of an innovative and cheap sensor for the in-cylinder pressure measurement, which is a piezoelectric washer that can be installed between the spark plug and the engine head. The signal generated by this kind of sensor is studied, developing a specific algorithm to adjust the value of the knock index in real-time. Finally, with the engine simulator developed in the first chapter, it is demonstrated that the innovative sensor can be coupled with the control system described in the second chapter and that the performance obtained could be the same reachable with the standard in-cylinder pressure sensors.

Development of multicomponent models for the prediction of lubricant oil-fuel dilution in internal combustion engines

The current environmental crisis is forcing the automotive industry to face tough challenges for the Internal Combustion Engines development in order to reduce the emissions of pollutants and Greenhouse gases. In this context, in the last decades, the main technological solutions adopted by the manufacturers have been the direct injection and the engine downsizing, which led to the rising of new concerns related to the fuel-cylinder walls physical interaction. The fuel spray possibly impacts the cylinder liner wall, which is wetted by the lubricant oil thus causing the derating of the lubricant properties, increasing the oil consumption, and contaminating the lubricant oil in the crankcase. Also, concerning hydrogen fuelled internal combustion engines, it is likely that the high near-wall temperature, which is typical of the hydrogen flame, results in the evaporation of a portion of the lubricant oil, increasing its consumption. With regards on the innovative combustion systems and their control strategies, optical accessible engines are fundamental tools for experimental investigations on such combustion systems. Though, due to the optical measurement line, optical engines suffer from a high level of blow-by, which must be accounted for. In light of the above, this thesis work aims to develop numerical methodologies with the aim to build useful tools for supporting the design of modern engines. In particular, a one-dimensional modelling of the lubricant oil-fuel dilution and oil evaporation has been performed and coupled with an optimization algorithm to achieve a lubricant oil surrogate. Then, a quasi-dimensional blow-by model has been developed and validated against experimental data. Such model, has been coupled with CFD 3D simulations and directly implemented in CFD 3D. Finally, CFD 3D simulations coupled with the VOF method have been performed in order to validate a methodology for studying the impact of a liquid droplet on a solid surface.

Development and testing of methodologies for the control and diagnosis of innovative combustion systems

In pursuit of aligning with the European Union's ambitious target of achieving a carbon-neutral economy by 2050, researchers, vehicle manufacturers, and original equipment manufacturers have been at the forefront of exploring cutting-edge technologies for internal combustion engines. The introduction of these technologies has significantly increased the effort required to calibrate the models implemented in the engine control units. Consequently the development of tools that reduce costs and the time required during the experimental phases, has become imperative. Additionally, to comply with ever-stricter limits on 〖"CO" 〗_"2" emissions, it is crucial to develop advanced control systems that enhance traditional engine management systems in order to reduce fuel consumption. Furthermore, the introduction of new homologation cycles, such as the real driving emissions cycle, compels manufacturers to bridge the gap between engine operation in laboratory tests and real-world conditions. Within this context, this thesis showcases the performance and cost benefits achievable through the implementation of an auto-adaptive closed-loop control system, leveraging in-cylinder pressure sensors in a heavy-duty diesel engine designed for mining applications. Additionally, the thesis explores the promising prospect of real-time self-adaptive machine learning models, particularly neural networks, to develop an automatic system, using in-cylinder pressure sensors for the precise calibration of the target combustion phase and optimal spark advance in a spark-ignition engines. To facilitate the application of these combustion process feedback-based algorithms in production applications, the thesis discusses the results obtained from the development of a cost-effective sensor for indirect cylinder pressure measurement. Finally, to ensure the quality control of the proposed affordable sensor, the thesis provides a comprehensive account of the design and validation process for a piezoelectric washer test system.

Produzione di biogas dagli scarti della lavorazione dell’alga ulva lactuca coltivata in mare aperto

Il presente lavoro si pone tre obiettivi: studio dei possibili utilizzi del sottoprodotto algale di Ulva L., a valle di un processo di estrazione dell’azienda South Agro srl che produce biofertilizzanti da alghe; digestione anaerobica del sottoprodotto, presso i laboratori dell’Università di Bologna, per determinarne il BMP; analisi costi-benefici per tre scenari diversi per un impianto a biogas di piccola taglia. Il primo obiettivo, è stato conseguito tramite una panoramica bibliografica delle vie di biovalorizzazione della biomassa Ulva L. Emerge che Ulva L. presenta numerose potenzialità dall’ambito alimentare ai chemicals, dall’ambito energetico a quello dei fertilizzanti. In questo lavoro esploreremo la conversione per valorizzazione energetica. Per il secondo obiettivo, è stato effettuato lo studio del potenziale biochimico del metano del residuo dell’azienda: ha prodotto una quantità di metano inferiore alla quota minima emersa dalle ricerche, che incrociano valutazioni del BMP alle fattibilità economiche di transformazione per la produzione di biometano. Questo suggerisce una possibile digestione anaerobica con un feed costituito da diversi residui algali a disposizione della stessa azienda, dato che tratta tre macroalghe. Considerando un valore di BMP di 180 Nmq / t SV, corrispondente a un feed di 3,3 t/g proveniente da tre alghe diverse, emerge una potenzialità di biometano prodotto economicamente possibile per un impianto a biogas di piccola taglia. Per il terzo obiettivo, è stata effettuata un’analisi costi-benefici tramite MATLAB e fogli Excel, basate su ricerche di impianti a biogas di piccola taglia e applicazione degli incentivi vigenti dalle normative. Il tutto è servito per creare tre scenari diversi (100, 200 e 300 kWel) che avvierebbero diversi benefici a livello territoriale, oltre che per l’azienda in questione: efficientamento energetico, economici, ambientali, simbiosi industriale e anche di avviamento di processi d’economia circolare.

Numerical investigation of the three-dimensional secondary instabilities in the time-developing compressible mixing layer

Mixing layers are present in very different types of physical situations such as atmospheric flows, aerodynamics and combustion. It is, therefore, a well researched subject, but there are aspects that require further studies. Here the instability of two-and three-dimensional perturbations in the compressible mixing layer was investigated by numerical simulations. In the numerical code, the derivatives were discretized using high-order compact finite-difference schemes. A stretching in the normal direction was implemented with both the objective of reducing the sound waves generated by the shear region and improving the resolution near the center. The compact schemes were modified to work with non-uniform grids. Numerical tests started with an analysis of the growth rate in the linear regime to verify the code implementation. Tests were also performed in the non-linear regime and it was possible to reproduce the vortex roll-up and pairing, both in two-and three-dimensional situations. Amplification rate analysis was also performed for the secondary instability of this flow. It was found that, for essentially incompressible flow, maximum growth rates occurred for a spanwise wavelength of approximately 2/3 of the streamwise spacing of the vortices. The result demonstrated the applicability of the theory developed by Pierrehumbet and Widnall. Compressibility effects were then considered and the maximum growth rates obtained for relatively high Mach numbers (typically under 0.8) were also presented.

Aplicação do ultra-som em sistemas eletroquímicos: considerações teóricas e experimentais

The aim of this review is to present and discuss the applications of ultrasound in electrochemical systems such as in sonoelectroanalysis and sonoelectrolysis for the electrochemical combustion of organic compounds. Initially, theoretical and experimental aspects are discussed, particularly those related to the enhancement of mass transport and the surface cleaning effects. Some results are included to illustrate alternative geometries for the experimental measurements and the working electrodes used in these systems. In the sequence, the available publications are presented and discussed to demonstrate that ultrasound combined with electrochemical techniques is a powerful set-up for the detection of analytes such as metals and/or organic compounds in hostile media and for the effective destruction of toxic organic substances. At the end, a table summarizes the results already published in the literature.

Quantification and source identification of atmospheric particulate polycyclic aromatic hydrocarbons and their dry deposition fluxes at three sites in Salvador Basin, Brazil, impacted by mobile and stationary sources

The present work has aimed to determine the 16 US EPA priority PAH atmospheric particulate matter levels present in three sites around Salvador, Bahia: (i) Lapa bus station, strongly impacted by heavy-duty diesel vehicles; (ii) Aratu harbor, impacted by an intense movement of goods, and (iii) Bananeira village on Maré Island, a non vehicle-influenced site with activities such as handcraft work and fisheries. Results indicated that BbF (0.130-6.85 ng m-3) is the PAH with highest concentration in samples from Aratu harbor and Bananeira and CRY (0.075-6.85 ng m-3) presented higher concentrations at Lapa station. PAH sources from studied sites were mainly of anthropogenic origin such as gasoline-fueled light-duty vehicles and diesel-fueled heavy-duty vehicles, discharges in the port, diesel burning from ships, dust ressuspension, indoor soot from cooking, and coal and wood combustion for energy production.

Queimadas de cana-de-açúcar no Brasil: efeitos à saúde respiratória

O artigo objetivou atualizar as informações sobre a produção científica referente aos efeitos da queima da cana-de-açúcar à saúde respiratória, em vista da expansão das plantações de cana no Brasil e no estado de São Paulo. São comentados estudos publicados no período de 1996-2006 que tratam de efeitos à saúde da queima da cana e/ou de poluentes atmosféricos produzidos pela queima. Os estudos sugerem que uma parcela da população - sobretudo de idosos, crianças e asmáticos - tem sua saúde agravada pela queima da cana-de-açúcar, demandando atendimento dos serviços de saúde e assim onerando os serviços de saúde e suas famílias

Evaluation technique for determining wheel performance in the grinding of aerospace materials

Nickel-based super alloys are used in a variety of applications in which high-temperature strength and resistance to creep, corrosion, and oxidation are required, such as in aircraft gas turbines, combustion chambers, and automotive engine valves. The properties that make these materials suitable for these applications also make them difficult to grind. Grinding systems for such materials are often built around vitrified cBN (cubic boron nitride) wheels to realize maximum productivity and minimum cost per part. Conditions that yield the most economical combination of stock removal rate and wheel wear are key to the successful implementation of the grinding system. Identifying the transition point for excessive wheel wear is important. The aim of this study is to compare the performance of different cBN wheels when grinding difficult-to-grind (DTG) materials by determining the 'wheel wear characteristic curve', which correlates the G-ratio to the calculated tangential force per abrasive grain. With the proposed methodology, a threshold force per grit above which the wheel wear rate increases rapidly can be quickly identified. A comparison of performance for two abrasive product formulations in the grinding of three materials is presented. The obtained results can be applied for the development of grinding applications for DTG materials.

Local atomic structure in tetragonal pure ZrO(2) nanopowders

The local atomic structures around the Zr atom of pure (undoped) ZrO(2) nanopowders with different average crystallite sizes, ranging from 7 to 40 nm, have been investigated. The nanopowders were synthesized by different wet-chemical routes, but all exhibit the high-temperature tetragonal phase stabilized at room temperature, as established by synchrotron radiation X-ray diffraction. The extended X-ray absorption fine structure (EXAFS) technique was applied to analyze the local structure around the Zr atoms. Several authors have studied this system using the EXAFS technique without obtaining a good agreement between crystallographic and EXAFS data. In this work, it is shown that the local structure of ZrO(2) nanopowders can be described by a model consisting of two oxygen subshells (4 + 4 atoms) with different Zr-O distances, in agreement with those independently determined by X-ray diffraction. However, the EXAFS study shows that the second oxygen subshell exhibits a Debye-Waller (DW) parameter much higher than that of the first oxygen subshell, a result that cannot be explained by the crystallographic model accepted for the tetragonal phase of zirconia-based materials. However, as proposed by other authors, the difference in the DW parameters between the two oxygen subshells around the Zr atoms can be explained by the existence of oxygen displacements perpendicular to the z direction; these mainly affect the second oxygen subshell because of the directional character of the EXAFS DW parameter, in contradiction to the crystallographic value. It is also established that this model is similar to another model having three oxygen subshells, with a 4 + 2 + 2 distribution of atoms, with only one DW parameter for all oxygen subshells. Both models are in good agreement with the crystal structure determined by X-ray diffraction experiments.

Crystallite size-dependent phases in nanocrystalline ZrO(2)-Sc(2)O(3)

ZrO(2)-10, 12 and 14 mol% Sc(2)O(3) nanopowders were prepared by using a nitrate-lysine gel-combustion synthesis. These materials were studied by synchrotron X-ray powder diffraction (SXPD) and Raman spectroscopy after calcination at different temperatures from 650 to 1200 degrees C, which led to samples with different average crystallite sizes, up to about 100 nm. The results from SXPD and Raman analyses indicate that, depending on Sc(2)O(3) content, the metastable t ''-form of the tetragonal phase or the cubic phase are fully retained at room temperature in nanocrystalline powders, provided an average crystallite sizes lower than similar to 30 nm. By contrast, powders with larger average crystallite sizes exhibit the stable rhombohedral, beta and gamma, phases and do not retain or very partially retain the metastable t '' and cubic ones.

Synchrotron X-ray powder diffraction and extended X-ray absorption fine structure spectroscopy studies on nanocrystalline ZrO(2)-CaO solid solutions

The crystal structure and the local atomic order of a series of nanocrystalline ZrO(2)-CaO solid solutions with varying CaO content were studied by synchrotron radiation X-ray powder diffraction and extended X-ray absorption fine structure (EXAFS) spectroscopy. These samples were synthesized by a pH-controlled nitrate-glycine gel-combustion process. For CaO contents up to 8 mol%, the t' form of the tetragonal phase (c/a > 1) was identified, whereas for 10 and 12 mol% CaO, the t '' form (c/a=1; oxygen anions displaced from their ideal positions in the cubic phase) was detected. Finally, the cubic phase was observed for solid solutions with CaO content of 14 mol% CaO or higher. The t'/t '' and t ''/cubic compositional boundaries were determined to be at 9 (1) and 13 (1) mol% CaO, respectively. The EXAFS study demonstrated that this transition is related to a tetragonal-to-cubic symmetry change of the first oxygen coordination shell around the Zr atoms.