12 resultados para Combustion Aerosols
em AMS Tesi di Dottorato - Alm@DL - Università di Bologna
Resumo:
It is well known that the deposition of gaseous pollutants and aerosols plays a major role in causing the deterioration of monuments and built cultural heritage in European cities. Despite of many studies dedicated to the environmental damage of cultural heritage, in case of cement mortars, commonly used in the 20th century architecture, the deterioration due to air multipollutants impact, especially the formation of black crusts, is still not well explored making this issue a challenging area of research. This work centers on cement mortars – environment interactions, focusing on the diagnosis of the damage on the modern built heritage due to air multi-pollutants. For this purpose three sites, exposed to different urban areas in Europe, were selected for sampling and subsequent laboratory analyses: Centennial Hall, Wroclaw (Poland), Chiesa dell'Autostrada del Sole, Florence (Italy), Casa Galleria Vichi, Florence (Italy). The sampling sessions were performed taking into account the height from the ground level and protection from rain run off (sheltered, partly sheltered and exposed areas). The complete characterization of collected damage layer and underlying materials was performed using a range of analytical techniques: optical and scanning electron microscopy, X ray diffractometry, differential and gravimetric thermal analysis, ion chromatography, flash combustion/gas chromatographic analysis, inductively coupled plasma-optical emission spectrometer. The data were elaborated using statistical methods (i.e. principal components analyses) and enrichment factor for cement mortars was calculated for the first time. The results obtained from the experimental activity performed on the damage layers indicate that gypsum, due to the deposition of atmospheric sulphur compounds, is the main damage product at surfaces sheltered from rain run-off at Centennial Hall and Casa Galleria Vichi. By contrast, gypsum has not been identified in the samples collected at Chiesa dell'Autostrada del Sole. This is connected to the restoration works, particularly surface cleaning, regularly performed for the maintenance of the building. Moreover, the results obtained demonstrated the correlation between the location of the building and the composition of the damage layer: Centennial Hall is mainly undergoing to the impact of pollutants emitted from the close coal power stations, whilst Casa Galleria Vichi is principally affected by pollutants from vehicular exhaust in front of the building.
Resumo:
DI Diesel engine are widely used both for industrial and automotive applications due to their durability and fuel economy. Nonetheless, increasing environmental concerns force that type of engine to comply with increasingly demanding emission limits, so that, it has become mandatory to develop a robust design methodology of the DI Diesel combustion system focused on reduction of soot and NOx simultaneously while maintaining a reasonable fuel economy. In recent years, genetic algorithms and CFD three-dimensional combustion simulations have been successfully applied to that kind of problem. However, combining GAs optimization with actual CFD three-dimensional combustion simulations can be too onerous since a large number of calculations is usually needed for the genetic algorithm to converge, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes. In order to make the optimization process less time-consuming, CFD simulations can be more conveniently used to generate a training set for the learning process of an artificial neural network which, once correctly trained, can be used to forecast the engine outputs as a function of the design parameters during a GA optimization performing a so-called virtual optimization. In the current work, a numerical methodology for the multi-objective virtual optimization of the combustion of an automotive DI Diesel engine, which relies on artificial neural networks and genetic algorithms, was developed.
Resumo:
This work demonstrates that the plasma - induced combustion of intermediate to low-level radioactive waste is a suitable method for volume reduction and stabilization. Weaknesses of existing facilities can be overcome with novel developments. Plasma treatment of LILW has a high economical advantage by volume reduction for storage in final repositories.
Resumo:
This manuscript reports the overall development of a Ph.D. research project during the “Mechanics and advanced engineering sciences” course at the Department of Industrial Engineering of the University of Bologna. The project is focused on the development of a combustion control system for an innovative Spark Ignited engine layout. In details, the controller is oriented to manage a prototypal engine equipped with a Port Water Injection system. The water injection technology allows an increment of combustion efficiency due to the knock mitigation effect that permits to keep the combustion phasing closer to the optimal position with respect to the traditional layout. At the beginning of the project, the effects and the possible benefits achievable by water injection have been investigated by a focused experimental campaign. Then the data obtained by combustion analysis have been processed to design a control-oriented combustion model. The model identifies the correlation between Spark Advance, combustion phasing and injected water mass, and two different strategies are presented, both based on an analytic and semi-empirical approach and therefore compatible with a real-time application. The model has been implemented in a combustion controller that manages water injection to reach the best achievable combustion efficiency while keeping knock levels under a pre-established threshold. Three different versions of the algorithm are described in detail. This controller has been designed and pre-calibrated in a software-in-the-loop environment and later an experimental validation has been performed with a rapid control prototyping approach to highlight the performance of the system on real set-up. To further make the strategy implementable on an onboard application, an estimation algorithm of combustion phasing, necessary for the controller, has been developed during the last phase of the PhD Course, based on accelerometric signals.
Resumo:
The thesis work deals with topics that led to the development of innovative control-oriented models and control algorithms for modern gasoline engines. Knock in boosted spark ignition engines is the widest topic discussed in this document because it remains one of the most limiting factors for maximizing combustion efficiency in this kind of engine. First chapter is thus focused on knock and a wide literature review is proposed to summarize the preliminary knowledge that even represents the background and the reference for discussed activities. Most relevant results achieved during PhD course in the field of knock modelling and control are then presented, describing every control-oriented model that led to the development of an adaptive model-based combustion control system. The complete controller has been developed in the context of the collaboration with Ferrari GT and it allowed to completely redefine the knock intensity evaluation as well as the combustion phase control. The second chapter is focused on the activity related to a prototyping Port Water Injection system that has been developed and tested on a turbocharged spark ignition engine, within the collaboration with Magneti Marelli. Such system and the effects of injected water on the combustion process were then modeled in a 1-D simulation environment (GT Power). Third chapter shows the development and validation of a control-oriented model for the real-time calculation of exhaust gas temperature that represents another important limitation to the performance increase in modern boosted engines. Indeed, modelling of exhaust gas temperature and thermocouple behavior are themes that play a key role in the optimization of combustion and catalyst efficiency.
Resumo:
This work resumes a wide variety of research activities carried out with the main objective of increasing the efficiency and reducing the fuel consumption of Gasoline Direct Injection engines, especially under high loads. For this purpose, two main innovative technologies have been studied, Water Injection and Low-Pressure Exhaust Gas Recirculation, which help to reduce the temperature of the gases inside the combustion chamber and thus mitigate knock, being this one of the main limiting factors for the efficiency of modern downsized engines that operate at high specific power. A prototypal Port Water Injection system was developed and extensive experimental work has been carried out, initially to identify the benefits and limitations of this technology. This led to the subsequent development and testing of a combustion controller, which has been implemented on a Rapid Control Prototyping environment, capable of managing water injection to achieve knock mitigation and a more efficient combustion phase. Regarding Low-Pressure Exhaust Gas Recirculation, a commercial engine that was already equipped with this technology was used to carry out experimental work in a similar fashion to that of water injection. Another prototypal water injection system has been mounted to this second engine, to be able to test both technologies, at first separately to compare them on equal conditions, and secondly together in the search of a possible synergy. Additionally, based on experimental data from several engines that have been tested during this study, including both GDI and GCI engines, a real-time model (or virtual sensor) for the estimation of the maximum in-cylinder pressure has been developed and validated. This parameter is of vital importance to determine the speed at which damage occurs on the engine components, and therefore to extract the maximum performance without inducing permanent damages.
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
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.