Analytical instrumental approaches and strategies to support the sensory assessment of virgin olive oils

At the beginning, this Ph.D. project led to an overview of the most common and emerging types of fraud and possible countermeasures in the olive oil sector. Furthermore, possible weaknesses in the current conformity check system for olive oil were highlighted. Among those, despite the organoleptic assessment is a fundamental tool for establishing the virgin olive oils (VOOs) quality grade, the scientific community has evidenced some drawbacks in it. In particular, the application of instrumental screening methods to support the panel test could reduce the work of sensory panels and the cost of this analysis (e.g. for industries, distributors, public and private control laboratories), permitting the increase in the number and the efficiency of the controls. On this basis, a research line called “Quantitative Panel Test” is one of the main expected outcomes of the OLEUM project that is also partially discussed in this doctoral dissertation. In this framework, analytical activities were carried out, within this PhD project, aimed to develop and validate analytical protocols for the study of the profiles in volatile compounds (VOCs) of the VOOs headspace. Specifically, two chromatographic approaches, one targeted and one semi-targeted, to determine VOCs were investigated in this doctoral thesis. The obtained results, will allow the possible establishment of concentration limits and ranges of selected volatile markers, as related to fruitiness and defects, with the aim to support the panel test in the commercial categorization of VOOs. In parallel, a rapid instrumental screening method based on the analysis of VOCs has been investigated to assist the panel test through a fast pre-classification of VOOs samples based on a known level of probability, thus increasing the efficiency of quality control.

Nonlinear Control Strategies for Cooperative Control of Multi-Robot Systems

This thesis deals with distributed control strategies for cooperative control of multi-robot systems. Specifically, distributed coordination strategies are presented for groups of mobile robots. The formation control problem is initially solved exploiting artificial potential fields. The purpose of the presented formation control algorithm is to drive a group of mobile robots to create a completely arbitrarily shaped formation. Robots are initially controlled to create a regular polygon formation. A bijective coordinate transformation is then exploited to extend the scope of this strategy, to obtain arbitrarily shaped formations. For this purpose, artificial potential fields are specifically designed, and robots are driven to follow their negative gradient. Artificial potential fields are then subsequently exploited to solve the coordinated path tracking problem, thus making the robots autonomously spread along predefined paths, and move along them in a coordinated way. Formation control problem is then solved exploiting a consensus based approach. Specifically, weighted graphs are used both to define the desired formation, and to implement collision avoidance. As expected for consensus based algorithms, this control strategy is experimentally shown to be robust to the presence of communication delays. The global connectivity maintenance issue is then considered. Specifically, an estimation procedure is introduced to allow each agent to compute its own estimate of the algebraic connectivity of the communication graph, in a distributed manner. This estimate is then exploited to develop a gradient based control strategy that ensures that the communication graph remains connected, as the system evolves. The proposed control strategy is developed initially for single-integrator kinematic agents, and is then extended to Lagrangian dynamical systems.

Automotive diesel engine transient operation: modeling, optimization and control

Traditionally, the study of internal combustion engines operation has focused on the steady-state performance. However, the daily driving schedule of automotive engines is inherently related to unsteady conditions. There are various operating conditions experienced by (diesel) engines that can be classified as transient. Besides the variation of the engine operating point, in terms of engine speed and torque, also the warm up phase can be considered as a transient condition. Chapter 2 has to do with this thermal transient condition; more precisely the main issue is the performance of a Selective Catalytic Reduction (SCR) system during cold start and warm up phases of the engine. The proposal of the underlying work is to investigate and identify optimal exhaust line heating strategies, to provide a fast activation of the catalytic reactions on SCR. Chapters 3 and 4 focus the attention on the dynamic behavior of the engine, when considering typical driving conditions. The common approach to dynamic optimization involves the solution of a single optimal-control problem. However, this approach requires the availability of models that are valid throughout the whole engine operating range and actuator ranges. In addition, the result of the optimization is meaningful only if the model is very accurate. Chapter 3 proposes a methodology to circumvent those demanding requirements: an iteration between transient measurements to refine a purpose-built model and a dynamic optimization which is constrained to the model validity region. Moreover all numerical methods required to implement this procedure are presented. Chapter 4 proposes an approach to derive a transient feedforward control system in an automated way. It relies on optimal control theory to solve a dynamic optimization problem for fast transients. From the optimal solutions, the relevant information is extracted and stored in maps spanned by the engine speed and the torque gradient.

Engineering in Transition. Approaches, strategies and technologies for implementing system innovation towards sustainability

With the aim to provide people with sustainable options, engineers are ethically required to hold the safety, health and welfare of the public paramount and to satisfy society's need for sustainable development. The global crisis and related sustainability challenges are calling for a fundamental change in culture, structures and practices. Sustainability Transitions (ST) have been recognized as promising frameworks for radical system innovation towards sustainability. In order to enhance the effectiveness of transformative processes, both the adoption of a transdisciplinary approach and the experimentation of practices are crucial. The evolution of approaches towards ST provides a series of inspiring cases which allow to identify advances in making sustainability transitions happen. In this framework, the thesis has emphasized the role of Transition Engineering (TE). TE adopts a transdisciplinary approach for engineering to face the sustainability challenges and address the risks of un-sustainability. With this purpose, a definition of Transition Technologies is provided as a valid instruments to contribute to ST. In the empirical section, several transition initiatives have been analysed especially at the urban level. As a consequence, the model of living-lab of sustainability has crucially emerged. Living-labs are environments in which innovative technologies and services are co-created with users active participation. In this framework, university can play a key role as learning organization. The core of the thesis has concerned the experimental application of transition approach within the School of Engineering and Architecture of University of Bologna at Terracini Campus. The final vision is to realize a living-lab of sustainability. Particularly, a Transition Team has been established and several transition experiments have been conducted. The final result is not only the improvement of sustainability and resilience of the Terracini Campus, but the demonstration that university can generate solutions and strategies that tackle the complex, dynamic factors fuelling the global crisis.

Big data analytics and modeling for Human Mobility

The fast development of Information Communication Technologies (ICT) offers new opportunities to realize future smart cities. To understand, manage and forecast the city's behavior, it is necessary the analysis of different kinds of data from the most varied dataset acquisition systems. The aim of this research activity in the framework of Data Science and Complex Systems Physics is to provide stakeholders with new knowledge tools to improve the sustainability of mobility demand in future cities. Under this perspective, the governance of mobility demand generated by large tourist flows is becoming a vital issue for the quality of life in Italian cities' historical centers, which will worsen in the next future due to the continuous globalization process. Another critical theme is sustainable mobility, which aims to reduce private transportation means in the cities and improve multimodal mobility. We analyze the statistical properties of urban mobility of Venice, Rimini, and Bologna by using different datasets provided by companies and local authorities. We develop algorithms and tools for cartography extraction, trips reconstruction, multimodality classification, and mobility simulation. We show the existence of characteristic mobility paths and statistical properties depending on transport means and user's kinds. Finally, we use our results to model and simulate the overall behavior of the cars moving in the Emilia Romagna Region and the pedestrians moving in Venice with software able to replicate in silico the demand for mobility and its dynamic.

Patterns of long-term settlement and land exploitation in the region of the Nile First Cataract (Egypt)

The First Cataract region (Egypt) has always played a crucial role as a border area and a crossroads for cultures and people living in adjacent landscapes. The region has its central point in the modern city of Aswan, but it extends up to the Kom Ombo Plain in the north and reaches the Bab el-Kalabsha in the south. Its eastern and western limits cannot be defined with the same precision, given that they are located in deserts. This research focused on the landscape analysis of the region intended as a complex entanglement of archaeological evidence in a geographical and natural environment whose changes impacted and, simultaneously, were influenced by human activities. Settlement patterns and land use can give interesting information on how these relationships worked from a diachronic perspective and how they shaped the region’s characteristics. To understand the links between the human presence and its evidence and the landscape of the First Cataract region, the integration of various datasets was needed, from historical and archaeological ones to the remote sensing observation of large areas. An area corresponding to ca. 18.000 km2 has been selected for this research. The chronological framework has been chosen to cover a considerable period, from the beginning of the 5th millennium BCE to the 7th century AD. Multi-temporality and multifunctionality appear as two essential aspects when the archaeological evidence of the First Cataract region is considered in its geographical and topographical setting as a general context for settlement patterns and resource exploitation analyses. A combination of remote sensing data and topographical materials has been integrated with archaeological evidence to obtain information about resource exploitation strategies and settlement adaptation from a diachronic perspective.