Metodologie per la simulazione fluidodinamica di pompe gerotor

La modellazione di una pompa gerotor può essere svolta mediante l'utilizzo di modelli matematici di tipo numerico. Questo tipo di soluzione prevedere la realizzazione di un dominio fluido discretizzato. In questo lavoro l'analisi è stata effettuata mediante il software STAR-CCM+. Sono state applicate due tecniche per la discretizzazione del dominio, l'Overset ed il Morphing, applicabili in problemi di interazione tra fluido e struttura in movimento. Analizzate le due tecniche, la seconda è stata applicata nello studio del comportamento di una pompa gerotor. I risultati ottenuti hanno portato alla definizione di un secondo modello ottimizzato mediante la variazione della luce di aspirazione.

Analisi del non-equilibrio termico locale nella conduzione non-stazionaria in uno strato poroso

Lo scopo di questo lavoro di tesi si focalizza sullo studio, sia dal punto di vista analitico che da quello numerico, della conduzione del calore non stazionaria di un mezzo poroso rettangolare saturo di fluido. Per descrivere tale fenomeno sono state adoperate le equazioni di bilancio dell’energia modellate tramite la teoria del non-equilibrio termico locale, cioè una coppia di equazioni di bilancio dell’energia sia per la fase solida sia per la fase fluida, dipendenti l’una dall’altra in quanto legate dal termine generativo di interfase. La necessità di avere due equazioni di bilancio dell’energia è dovuta a una caratteristica importante dei processi di trasferimento del calore in una schiuma metallica. In questo elaborato verranno risolte numericamente le equazioni di biliancio dell’energia del non-equilibrio termico locale, tramite l’ausilio del programma di calcolo MATLAB e il suo solutore “pdepe”, indagando e proponendo una soluzione al “paradosso” introdotto da Vadazs* nel suo articolo. Tale paradosso si presenta quando si risolvono analiticamente le equazioni di bilancio dell’energia del non-equilibrio termico locale applicando due metodi differenti: il metodo di sostituzione delle variabili e il metodo di separazione delle variabili dipendenti. Dai risultati ottenuti da Vadasz emerge una discrepanza tra i due metodi in quanto uno dei due porta a predire un comportamento di equilibrio termico tra le due fasi a ogni istante di tempo, mentre l’altro predirebbe un comportamento di non-equilibrio termico locale tra le due fasi, particolarmente evidente nei primi istanti di tempo. Successivamente si è analizzato il problema di conduzione studiandone la variazione dei transitori termici del campo di temperatura della fase solida e dalla fase fluida al mutare dei parametri adimensionali che caratterizzano le equazioni di bilancio dell’energia nella sue forme adimensionalizzate.

Caratterizzazione fluidodinamica di un digestore anaerobico modello tramite tecniche di diagnostica ottica

L’aumento del consumo di energia globale e le problematiche legate all’inquinamento stanno rendendo indispensabile lo spostamento verso fonti di energia rinnovabile. La digestione anaerobica rappresenta una possibile soluzione in quanto permette di produrre biogas da biomassa organica di scarto ma, l’ottimizzazione del processo risulta difficoltosa a causa delle numerose variabili chimiche, biologiche, fisiche e geometriche correlate. Nel presente elaborato, concentrandosi sulle problematiche relative alla miscelazione interna, è stata investigata la fluidodinamica interna di un reattore modello ottenuto tramite scale-down di un digestore anaerobico industriale che presentava problemi di sedimentazione di sostanza solida sul fondo del reattore. Tramite tecniche di diagnostica ottiche, è stato studiato il movimento del fluido, prima utilizzando acqua demineralizzata e poi una soluzione di gomma di xantano come fluido di processo, al fine di studiare il campo di moto medio interno al reattore. Le tecniche utilizzate sono la Particle Image Velocimetry (PIV) e la Planar Laser Induced Fluorescence (PLIF). Al fine di rendere il sistema investigato il più rappresentativo possibile del digestore industriale, è stato utilizzato come fluido di processo per alcune delle prove raccolte, una soluzione acquosa 1,0g/kg di gomma di xantano, le cui proprietà reologiche sono state investigate grazie ad un Reometro Anton Paar MCR 301.

Modelling of ORC components and systems for low-medium temperature heat recovery applications with reduced environmental impact

Although its great potential as low to medium temperature waste heat recovery (WHR) solution, the ORC technology presents open challenges that still prevent its diffusion in the market, which are different depending on the application and the size at stake. Focusing on the micro range power size and low temperature heat sources, the ORC technology is still not mature due to the lack of appropriate machines and working fluids. Considering instead the medium to large size, the technology is already available but the investment is still risky. The intention of this thesis is to address some of the topical themes in the ORC field, paying special attention in the development of reliable models based on realistic data and accounting for the off-design performance of the ORC system and of each of its components. Concerning the “Micro-generation” application, this work: i) explores the modelling methodology, the performance and the optimal parameters of reciprocating piston expanders; ii) investigates the performance of such expander and of the whole micro-ORC system when using Hydrofluorocarbons as working fluid or their new low GWP alternatives and mixtures; iii) analyzes the innovative ORC reversible architecture (conceived for the energy storage), its optimal regulation strategy and its potential when inserted in typical small industrial frameworks. Regarding the “Industrial WHR” sector, this thesis examines the WHR opportunity of ORCs, with a focus on the natural gas compressor stations application. This work provides information about all the possible parameters that can influence the optimal sizing, the performance and thus the feasibility of installing an ORC system. New WHR configurations are explored: i) a first one, relying on the replacement of a compressor prime mover with an ORC; ii) a second one, which consists in the use of a supercritical CO2 cycle as heat recovery system.

Design and Off-design modelling of advanced Power-to-Gas energy storage systems

Power-to-Gas storage systems have the potential to address grid-stability issues that arise when an increasing share of power is generated from sources that have a highly variable output. Although the proof-of-concept of these has been promising, the behaviour of the processes in off-design conditions is not easily predictable. The primary aim of this PhD project was to evaluate the performance of an original Power-to-Gas system, made up of innovative components. To achieve this, a numerical model has been developed to simulate the characteristics and the behaviour of the several components when the whole system is coupled with a renewable source. The developed model has been applied to a large variety of scenarios, evaluating the performance of the considered process and exploiting a limited amount of experimental data. The model has been then used to compare different Power-to-Gas concepts, in a real scenario of functioning. Several goals have been achieved. In the concept phase, the possibility to thermally integrate the high temperature components has been demonstrated. Then, the parameters that affect the energy performance of a Power-to-Gas system coupled with a renewable source have been identified, providing general recommendations on the design of hybrid systems; these parameters are: 1) the ratio between the storage system size and the renewable generator size; 2) the type of coupled renewable source; 3) the related production profile. Finally, from the results of the comparative analysis, it is highlighted that configurations with a highly oversized renewable source with respect to the storage system show the maximum achievable profit.

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.

Development of Advanced Combustions using Cylinder Pressure Signal

Zero-carbon powertrains development has become one of the main challenges for automotive industries around the world. Following this guideline, several approaches such as powertrain electrification, advanced combustions, and hydrogen internal combustion engines have been aimed to achieve the goal. Low Temperature Combustions, characterized by a simultaneous reduction of fuel consumption and emissions, represent one of the most studied solutions moving towards a sustainable mobility. Previous research demonstrate that Gasoline partially premixed Compression Ignition combustion is one of the most promising LTC. Mainly characterized by the high-pressure direct-injection of gasoline and the spontaneous ignition of the premixed air-fuel mixture, GCI combustion has shown a good potential to achieve the high thermal efficiency and low pollutants in compression ignited engines required by future emission regulations. Despite its potential, GCI combustion might suffer from low combustion controllability and stability, because gasoline spontaneous ignition is significantly affected by slight variations of the local in-cylinder thermal conditions. Therefore, to properly control GCI combustion assuring the maximum performance, a deep knowledge of the combustion process, i.e., gasoline auto-ignition and the effect of the control parameters on the combustion and pollutants, is mandatory. This PhD dissertation focuses on the study of GCI combustion in a light-duty compression ignited engine. Starting from a standard 1.3L diesel engine, this work describes the activities made moving toward the full conversion of the engine. A preliminary study of the GCI combustion was conducted in a “Single-Cylinder” engine configuration highlighting combustion characteristics and dependencies on the control parameters. Then, the full engine conversion was performed, and a wide experimental campaign allowed to confirm the benefits of this advanced combustion methodologies in terms of pollutants and thermal efficiency. The analysis of the in-cylinder pressure signal allowed to study in depth the GCI combustion and develop control-oriented models aimed to improve the combustion stability.

Impiego dell’ecografia ad alta risoluzione nella diagnosi di anomalie cerebrali fetali difficili. Focus sul complesso anteriore.

In questo lavoro di tesi vengono prese in esame le principali anomalie cerebrali fetali a carico del complesso anteriore, formato dal cavo del setto pellucido e dai corni frontali dei ventricoli laterali. Si è poi concentrata l’attenzione sull’oloprosencefalia e sull’obliterazione del cavo del setto pellucido, analizzando i casi che sono stati riferiti c/o la U.O. di Ostetricia e Medicina dell’Età Prenatale del Policlinico di S. Orsola – IRCCS. L’oloprosencefalia racchiude in sé uno spettro di anomalie cerebrali caratterizzate da un difetto di formazione della linea mediana con forme variabili di fusione degli emisferi cerebrali. Le forme alobari mostrano una distorsione della anatomia cerebrale, con un singolo ventricolo e sono spesso associate ad anomalie extracerebrali e del cariotipo. Nelle forme semilobari e lobari il setto pellucido è generalmente assente nei piani assiali, con corni frontali fusi ed ipoplasici, ma queste caratteristiche possono essere di difficile interpretazione ad un esame di screening. Le anomalie facciali sono invece più sfuggenti. L’obliterazione del cavo del setto consiste in un suo aspetto ecogeno, normalmente disteso da fluido; è ritenuta una variante della norma, ma queste conclusioni sono basate su casistiche limitate. Anche in questo caso abbiamo riportato l’eventuale presenza di anomalie associate ed abbiamo poi rivalutato questi bambini mediante una visita specialistica presso la U.O. di Neuropsichiatria Infantile. Nella nostra esperienza di 16 casi, la neurosonografia è stata in grado di definire la presenza o meno di anomalie cerebrali associate (1 caso di cisti interemisferiche e corpo calloso disgenetico) al pari della risonanza magnetica. Nei casi apparentemente isolati, in circa il 20% tale reperto è stato transitorio nel corso della gravidanza e non sono state riportate anomalie del cariotipo. Tutte le visite di follow up eseguite nel contesto dello studio (risultati parziali di 7/15 bambini) hanno dimostrato uno sviluppo nella norma per l’età del bambino.

Study of low grade temperature CCHP systems for the realization of zero power buildings

Combined Cooling Heat and Power Generation (CCHP) or trigeneration has been considered worldwide as a suitable alternative to traditional energy systems in terms of significant energy saving and environmental conservation. The development and evaluation of a solar driven micro-CCHP system based on a ORC cogenerator and an Adsorption Chiller (AC) experimental prototypes has been the focus of this PhD research. The specific objectives of the overall project are: • To design, construct and evaluate an innovative Adsorption Chiller in order to improve the performances of the AC technology. • To thermodynamically model the proposed micro-scale solar driven CHP system and to prove that the concept of trigeneration through solar energy combined with an organic Rankine turbine cycle (ORC) and an adsorption chiller (AC) is suitable for residential applications.

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.

Performance assessment of vehicular connectivity in hybrid electric vehicles for fuel and emissions reduction

Nowadays, the spreading of the air pollution crisis enhanced by greenhouse gases emission is leading to the worsening of global warming. Recently, several metropolitan cities introduced Zero-Emissions Zones where the use of the Internal Combustion Engine is forbidden to reduce localized pollutants emissions. This is particularly problematic for Plug-in Hybrid Electric Vehicles, which usually work in depleting mode. In order to address these issues, the present thesis presents a viable solution by exploiting vehicular connectivity to retrieve navigation data of the urban event along a selected route. The battery energy needed, in the form of a minimum State of Charge (SoC), is calculated by a Speed Profile Prediction algorithm and a Backward Vehicle Model. That value is then fed to both a Rule-Based Strategy, developed specifically for this application, and an Adaptive Equivalent Consumption Minimization Strategy (A-ECMS). The effectiveness of this approach has been tested with a Connected Hardware-in-the-Loop (C-HiL) on a driving cycle measured on-road, stimulating the predictions with multiple re-routings. However, even if hybrid electric vehicles have been recognized as a valid solution in response to increasingly tight regulations, the reduced engine load and the repeated engine starts and stops may reduce substantially the temperature of the exhaust after-treatment system (EATS), leading to relevant issues related to pollutant emission control. In this context, electrically heated catalysts (EHCs) represent a promising solution to ensure high pollutant conversion efficiency without affecting engine efficiency and performance. This work aims at studying the advantages provided by the introduction of a predictive EHC control function for a light-duty Diesel plug-in hybrid electric vehicle (PHEV) equipped with a Euro 7-oriented EATS. Based on the knowledge of future driving scenarios provided by vehicular connectivity, engine first start can be predicted and therefore an EATS pre-heating phase can be planned.

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.

Two stroke cycle, novel combustion concepts and electrification for a new generation of internal combustion engines

The pursuit of decarbonization and increased efficiency in internal combustion engines (ICE) is crucial for reducing pollution in the mobility sector. While electrification is a long-term goal, ICE still has a role to play if coupled with innovative technologies. This research project explores various solutions to enhance ICE efficiency and reduce emissions, including Low Temperature Combustion (LTC), Dual fuel combustion with diesel and natural gas, and hydrogen integration. LTC methods like Dual fuel and Reactivity Controlled Compression Ignition (RCCI) show promise in lowering emissions such as NOx, soot, and CO2. Dual fuel Diesel-Natural Gas with hydrogen addition demonstrates improved efficiency, especially at low loads. RCCI Diesel-Gasoline engines offer increased Brake Thermal Efficiency (BTE) compared to standard diesel engines while reducing specific NOx emissions. The study compares 2-Stroke and 4-Stroke engine layouts, optimizing scavenging systems for both aircraft and vehicle applications. CFD analysis enhances specific power output while addressing injection challenges to prevent exhaust short circuits. Additionally, piston bowl shape optimization in Diesel engines running on Dual fuel (Diesel-Biogas) aims to reduce NOx emissions and enhance thermal efficiency. Unconventional 2-Stroke architectures, such as reverse loop scavenged with valves for high-performance cars, opposed piston engines for electricity generation, and small loop scavenged engines for scooters, are also explored. These innovations, alongside ultra-lean hydrogen combustion, offer diverse pathways toward achieving climate neutrality in the transport sector.