Sviluppo di un framework per l'automazione dei test al banco e la prototipazione di algoritmi di controllo di motori a combustione interna

Negli ultimi anni, i limiti sempre più stringenti sulle emissioni inquinanti dei gas di scarico, hanno portato ad un notevole aumento della complessità dei motori a combustione interna. Questa complicazione determina un aumento esponenziale del numero di test da effettuare nella sala prova. I metodi tipici di gestione dei test non possono più essere utilizzati, ma è essenziale creare un sistema che ottimizzi le prove. Per ridurre drasticamente il tempo di esecuzione, è necessario implementare un'architettura in grado di facilitare lo scambio di dati tra i sistemi presenti nella sala prova, e, in aggiunta, definire le strategie di automazione dei test. L'approccio a taluni metodi si presenta ancora complicato in molti gruppi di sviluppo di strategie di controllo motore, anche se, una volta sviluppati, portano e a grandi benefici durante la fase di test. Il lavoro illustra i metodi implementati per la gestione di queste strategie. Prima si descrive l'approccio utilizzato nella calibrazione di anticipo di accensione per mantenere livelli accettabili di detonazione durante il processo di calibrazione. Successivamente è mostrato il sistema di automazione dei test che consente il pieno controllo del punto di funzionamento del motore, la gestione dell'acquisizione e la verifica della stabilità delle condizioni ottenute. L'ultima parte mostra sistemi di prototipazione rapida per la gestione di componenti innovatici del motore.

Development and experimental validation of a knock induced damage model and real-time implementation of model-based strategies to control knock intensity in boosted gasoline engines

This PhD thesis reports the main activities carried out during the 3 years long “Mechanics and advanced engineering sciences” course, at the Department of Industrial Engineering of the University of Bologna. The research project title is “Development and analysis of high efficiency combustion systems for internal combustion engines” and the main topic is knock, one of the main challenges for boosted gasoline engines. Through experimental campaigns, modelling activity and test bench validation, 4 different aspects have been addressed to tackle the issue. The main path goes towards the definition and calibration of a knock-induced damage model, to be implemented in the on-board control strategy, but also usable for the engine calibration and potentially during the engine design. Ionization current signal capabilities have been investigated to fully replace the pressure sensor, to develop a robust on-board close-loop combustion control strategy, both in knock-free and knock-limited conditions. Water injection is a powerful solution to mitigate knock intensity and exhaust temperature, improving fuel consumption; its capabilities have been modelled and validated at the test bench. Finally, an empiric model is proposed to predict the engine knock response, depending on several operating condition and control parameters, including injected water quantity.

Employment of Real-Time/FPGA Architectures for Test and Control of Automotive Engines

Nowadays the production of increasingly complex and electrified vehicles requires the implementation of new control and monitoring systems. This reason, together with the tendency of moving rapidly from the test bench to the vehicle, leads to a landscape that requires the development of embedded hardware and software to face the application effectively and efficiently. The development of application-based software on real-time/FPGA hardware could be a good answer for these challenges: FPGA grants parallel low-level and high-speed calculation/timing, while the Real-Time processor can handle high-level calculation layers, logging and communication functions with determinism. Thanks to the software flexibility and small dimensions, these architectures can find a perfect collocation as engine RCP (Rapid Control Prototyping) units and as smart data logger/analyser, both for test bench and on vehicle application. Efforts have been done for building a base architecture with common functionalities capable of easily hosting application-specific control code. Several case studies originating in this scenario will be shown; dedicated solutions for protype applications have been developed exploiting a real-time/FPGA architecture as ECU (Engine Control Unit) and custom RCP functionalities, such as water injection and testing hydraulic brake control.

Development and chemo-mechanical characterization of eco-compatible extenders containing REOB and recycled tyres’ rubber for the production of greener bituminous binders

The concepts of circular economy and sustainability are the basis of the present experimental research that seeks to reduce the environmental impact of traditional road construction materials. This study mainly focuses on the development and the chemo-mechanical characterization of bitumen extenders containing rubber (R) from end-of-life tyres (ELTs) and re-refined engine oil bottoms (REOBs) for the production of innovative and eco-friendly extended bitumens (i.e. bituminous binders containing 25%wt. of recycled products) and asphalt mixtures. In order to create more sustainable asphalt mixes, also recycled aggregates are used for partial replacement of virgin natural aggregates in the aggregate skeleton. The experimental program encompassed five successive steps: (i) the evaluation of physicochemical properties of R and REOB, (ii) the definition of the optimal extenders by the development of a new protocol and their characterizations, (iii) the realization and investigation of the chemo-rheological responses of the extended bitumens at different boundary conditions, (iv) the assessment of the effectiveness of analytical method to predict the rheological parameters of extended bitumens and, finally, (v) the analysis of the mechanical performances of the corresponding asphalt mixtures. A standard 50/70 penetration grade bitumen was chosen as a reference material and the main constituent of the innovative bituminous products. The results of this study underlined the importance of material characterization. The incorporation of R-REOB extenders strongly affects the chemo-rheological responses of the resulting extended bitumens and asphalt mixtures overall the boundary conditions. While the presence of R and the consequent formation of a polymer network improves the elasticity of the final products, especially at high test temperatures; the addition of REOB, softens the bituminous binders and asphalt mixes increasing their response at low test temperatures. Nonetheless, the use of recycled products increased the susceptibility of bituminous material under damaging conditions, which would need further investigations.

The educational problem that MOOCs could solve: professional development for teachers of disadvantaged students

The demographics of massive open online course (MOOC) analytics show that the great majority of learners are highly qualified professionals, and not, as originally envisaged, the global community of disadvantaged learners who have no access to good higher education. MOOC pedagogy fits well with the combination of instruction and peer community learning found in most professional development. A UNESCO study therefore set out to test the efficacy of an experimental course for teachers who need but do not receive high-quality continuing professional development, as a way of exploiting what MOOCs can do indirectly to serve disadvantaged students. The course was based on case studies around the world of information and communication technology (ICT) in primary education and was carried out to contribute to the UNESCO “Education For All” goal. It used a co-learning approach to engage the primary teaching community in exploring ways of using ICT in primary education. Course analytics, forums and participant surveys demonstrated that it worked well. The paper concludes by arguing that this technology has the power to tackle the large-scale educational problem of developing the primary-level teachers needed to meet the goal of universal education.

Development and validation of an echocardiography score for diagnosis of cardiac masses

Background Echocardiography is the cornerstone in the evaluation of cardiac masses and provides accurate characterization. Despite, its accuracy in diagnosis of cardiac masses (CM) remains challenging and, up to date, no validated diagnostic algorithm is validated. Purpose The aim of our study was to evaluate the diagnostic accuracy of echocardiography, to identify the echocardiographic predictors of malignancy and to develop and then validate a multiparametric echocardiographic score that could be used to estimate the likelihood of the histological nature of a CM. Materials and methods The final sample consisted of 273 consecutive patients who had a 2D-echocardiographic evaluation and a histologic diagnosis. Logistic regression was performed to evaluate the ability of echocardiographic findings to discriminate benign versus malignant masses, then a scoring system was developed and validated in a separate test cohort. Results Of the 322 patients initially included in the Bologna Cardiac Masses Registry, 13 with a poor acoustic window, 27 with no histological examination patients and 9 extra-cardiac masses were excluded. In the remaining 273 patients, classical 2-D echocardiogram identified 249 masses with a diagnostic accuracy of 88%. A weighted score [Diagnostic Echocardiographic Mass (DEM) Score] ranging from 0 to 9 was obtained from 6 variables: infiltration, polylobate mass, moderate-severe pericardial effusion. The AUC for the score was 0.965 (95% CI [0.938-0.993]). In a logistic regression analysis using the DEM score as a predictor, the likelihood of malignant CM increased more than 4 times for a 1-unit increase in the score (OR=4.468; 95% CI 2.733-7.304). A score < 3 denoted a high probability of a benign diagnosis, and a score ≥ 5 points corresponded to a higher risk of malignancy. Conclusion 2D-Echocardiography provides a high diagnostic accuracy in identifying cardiac masses and our multiparametric echocardiographic score could be useful to predict the histological nature of cardiac masses.

Development and characterization of deep learning techniques for neuroimaging data

Deep learning methods are extremely promising machine learning tools to analyze neuroimaging data. However, their potential use in clinical settings is limited because of the existing challenges of applying these methods to neuroimaging data. In this study, first a data leakage type caused by slice-level data split that is introduced during training and validation of a 2D CNN is surveyed and a quantitative assessment of the model’s performance overestimation is presented. Second, an interpretable, leakage-fee deep learning software written in a python language with a wide range of options has been developed to conduct both classification and regression analysis. The software was applied to the study of mild cognitive impairment (MCI) in patients with small vessel disease (SVD) using multi-parametric MRI data where the cognitive performance of 58 patients measured by five neuropsychological tests is predicted using a multi-input CNN model taking brain image and demographic data. Each of the cognitive test scores was predicted using different MRI-derived features. As MCI due to SVD has been hypothesized to be the effect of white matter damage, DTI-derived features MD and FA produced the best prediction outcome of the TMT-A score which is consistent with the existing literature. In a second study, an interpretable deep learning system aimed at 1) classifying Alzheimer disease and healthy subjects 2) examining the neural correlates of the disease that causes a cognitive decline in AD patients using CNN visualization tools and 3) highlighting the potential of interpretability techniques to capture a biased deep learning model is developed. Structural magnetic resonance imaging (MRI) data of 200 subjects was used by the proposed CNN model which was trained using a transfer learning-based approach producing a balanced accuracy of 71.6%. Brain regions in the frontal and parietal lobe showing the cerebral cortex atrophy were highlighted by the visualization tools.

Mars delivery service - development of the electro-mechanical systems of the Sample Fetch Rover for the Mars Sample Return Campaign

This thesis describes the development of the Sample Fetch Rover (SFR), studied for Mars Sample Return (MSR), an international campaign carried out in cooperation between the National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA). The focus of this document is the design of the electro-mechanical systems of the rover. After placing this work into the general context of robotic planetary exploration and summarising the state of the art for what concerns Mars rovers, the architecture of the Mars Sample Return Campaign is presented. A complete overview of the current SFR architecture is provided, touching upon all the main subsystems of the spacecraft. For each area, it is discussed what are the design drivers, the chosen solutions and whether they use heritage technology (in particular from the ExoMars Rover) or new developments. This research focuses on two topics of particular interest, due to their relevance for the mission and the novelty of their design: locomotion and sample acquisition, which are discussed in depth. The early SFR locomotion concepts are summarised, covering the initial trade-offs and discarded designs for higher traverse performance. Once a consolidated architecture was reached, the locomotion subsystem was developed further, defining the details of the suspension, actuators, deployment mechanisms and wheels. This technology is presented here in detail, including some key analysis and test results that support the design and demonstrate how it responds to the mission requirements. Another major electro-mechanical system developed as part of this work is the one dedicated to sample tube acquisition. The concept of operations of this machinery was defined to be robust against the unknown conditions that characterise the mission. The design process led to a highly automated robotic system which is described here in its main components: vision system, robotic arm and tube storage.

Development of new collagen cross-linkers for adhesive bonding stabilization

Aims: This thesis aimed to investigate the influence of different collagen cross-linkers, as separate primers or contained within desensitizing agents, on the longevity of dental restorations and on the dentinal enzymatic activity immediately, or after aging in vitro. Methods: A series of studies was conducted using several different cross-linking molecules and several adhesive systems. Four studies investigated the longevity of the hybrid layer by means of microtensile bond strength test, and the enzymatic activity using gelatin and in situ zymography, immediately or after 1 year of aging in the artificial saliva. The first study tested samples bonded with or without a cross-linking agent, that were previously aged for 5 years. The degradation of the hybrid layer was observed using transmission electron microscopy, the enzymatic activity in the hybrid layer using in situ zymography. Raman spectroscopy was used to investigate whether the active substance was still within the hybrid layer after 5 years. Results: The results of the studies showed that collagen cross-linkers were efficient in preserving bond strength after aging in vitro when used as separate primers on demineralized or partially demineralized dentin. In the cases when the cross-linker was utilized on mineralized dentin, bond strength results were higher than in the control groups immediately and after aging, however, no difference in enzymatic activity was detected after aging. Conclusions: The tested cross-linker molecules used as separate primers in etch-and-rinse and self-etch adhesives seem to be clinically applicable, since the procedure is not overly time-consuming and seems to preserve the hybrid layer over time. As for the cross-linkers contained in the desensitizing agent, when utilized before the adhesive procedures, it has shown to increase the bond strength of self-etch adhesives, but further studies are needed to better understand its effect on the enzymatic activity and crosslinking effects on mineralized dentin.

Development and characterization of cutting-edge equipment for EMC measurements and advanced power line filter design

This Doctoral Thesis aims at studying, developing, and characterizing cutting edge equipment for EMC measurements and proposing innovative and advanced power line filter design techniques. This document summarizes a three-year work, is strictly industry oriented and relies on EMC standards and regulations. It contains the main results, findings, and effort with the purpose of bringing innovative contributions at the scientific community. Conducted emissions interferences are usually suppressed with power line filters. These filters are composed by common mode chokes, X capacitors and Y capacitors in order to mitigate both the differential mode and common mode noise, which compose the overall conducted emissions. However, even at present days, available power line filter design techniques show several disadvantages. First of all, filters are designed to be implemented in ideal 50 Ω systems, condition which is far away from reality. Then, the attenuation introduced by the filter for common or differential mode noise is analyzed independently, without considering the possible mode conversion that can be produced by impedance mismatches, or asymmetries in either the power line filter itself or the equipment under test. Ultimately, the instrumentation used to perform conducted emissions measurement is, in most cases, not adequate. All these factors lead to an inaccurate design, contributing at increasing the size of the filter, making it more expensive and less performant than it should be.

Development of gripping devices based on electroadhesive forces

In a context of technological innovation, the aim of this thesis is to develop a technology that has gained interest in both scientific and industrial realms. This technology serves as a viable alternative to outdated and energy-consuming industrial systems. Electro-adhesive devices (EADs) leverage electrostatic forces for grasping objects or adhering to surfaces. The advantage of employing electrostatics lies in its adaptability to various materials without compromising the structure or chemistry of the object or surface. These benefits have led the industry to explore this technology as a replacement for costly vacuum systems and suction cups currently used for handling most products. Furthermore, the broad applicability of this technology extends to extreme environments, such as space with ultra-high vacuum conditions. Unfortunately, research in this area has yet to yield practical results for industrially effective gripper prototyping. This is primarily due to the inherent complexity of electro-adhesive technology, which operates on basic capacitive principles that does not find satisfying physical descriptions. This thesis aims to address these challenges through a series of studies, starting with the manufacturing process and testing of an EAD that has become the standard in our laboratory. It then delves into material and electrode geometry studies to enhance system performance, ultimately presenting potential industrial applications of the technology. All the presented results are encouraging, as they have yielded shear force values three times higher than those previously reported in the literature. The various applications have demonstrated the significant effectiveness of EADs as brakes or, more broadly, in exerting shear forces. This opens up the possibility of utilizing cutting-edge technologies to push the boundaries of technology to the fullest.

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.

Fighting child marriage in developing countries: design and development of a mobile application

Child marriage is still a great issue in developing countries and even if the interventions to prevent it are having results, they are not enough to eliminate the problem. Among the strategies that seem to work most to fight child marriage, there is the empowerment of girls with information combined with education of parents and community. As smartphones are more accessible year after year in developing countries, this thesis wants to investigate if a mobile app could be effective in fighting child marriage and which characteristics such an app should have. The research was organized in four phases and used design and creation and case study methodologies. Firstly, the literature was analyzed and an initial design was proposed. Secondly, expert interviews were performed to gain feedback on the proposed design, and afterwards prototype was built. Thirdly, a case study in the Democratic Republic of Congo (DRC) was performed to test the prototype, gaining insights and improvements through group interviews with 26 girls aged 15-19. Finally, a first version of the app was developed and a second phase of the case study was run in the DRC to understand if the girls were able to use the app. This phase included 14 girls of which 6 had participated in the prototype testing and used questionnaires as a data generation method. The app was built following the Principles for Digital Development. Even if this app is built based on the case study in DRC is modular and easily adaptable to other contexts as it is not content-specific. It was shown that is worth continuing to study this topic and it was defined a conceptual framework for designing learning apps for developing countries, in particular, to fight child, early, and forced marriage.

Development and testing of a safety module for diagnostics and protection from hazards in secondary woodworking machinery

The main theme covered by this dissertation is safety, set in the context of automatic machinery for secondary woodworking. The thesis describes in detail the project of a software module for CNC machining centers to protect the operator against hazards and to report errors in the machine safety management. Its design has been developed during an internship at SCM Group technical department. The development of the safety module is addressed step by step in a detailed way: first the company and the reference framework are introduced and then all the design choices are explained and justified. The discussion begins with a detailed analysis of the standards concerning woodworking machines and safety-related software. In this way, a clear and linear procedure can be established to develop and implement the internal structure of the module, its interface, and its application to specific safety-critical conditions. Afterwards, particular attention is paid to software testing, with the development of a comprehensive test procedure for the module, and to diagnostics, especially oriented towards signal management in IoT mode. Finally, the safety module is used as an anti-regression tool to initiate a design improvement of the machine control program. The refactoring steps performed in the process are explained in detail and the SCENT approach is introduced to test the result.

Query Library Development and Anomaly Detection on Flight Data

During the last semester of the Master’s Degree in Artificial Intelligence, I carried out my internship working for TXT e-Solution on the ADMITTED project. This paper describes the work done in those months. The thesis will be divided into two parts representing the two different tasks I was assigned during the course of my experience. The First part will be about the introduction of the project and the work done on the admittedly library, maintaining the code base and writing the test suits. The work carried out is more connected to the Software engineer role, developing features, fixing bugs and testing. The second part will describe the experiments done on the Anomaly detection task using a Deep Learning technique called Autoencoder, this task is on the other hand more connected to the data science role. The two tasks were not done simultaneously but were dealt with one after the other, which is why I preferred to divide them into two separate parts of this paper.