AgroDB - integration of database management systems with crop models.

2016

The effect of different training systems on vegetative and productive performance of apple trees cultivar 'maxigala' - in southern Brazil.

2016

Investigation of innovative combustion systems for reduced fuel consumption and increased specific power production

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.

Gross and Microscopic Morphological Anatomical Study of the Guinea Pig (Cavia porcellus) and the Capybara (Hydrochoerus hydrochaeris), Aimed at the Preparation of a Comparative Anatomical Atlas of the Different Systems

In recent years, there has been an exponential increase in the so-called “new pets”, including the domestic guinea pig (Cavia porcellus) and the capybara (Hydrochoerus hydrochaeris), two closely related Caviid rodents native to South America. Both historically bred for food purposes, they have more recently become increasingly popular as pets in the European and American continents, respectively. This led to an increasing veterinary interest in deepening the knowledge regarding their normal anatomy, as a basic contribution to other fields of veterinary medicine, including diagnostic imaging, surgery, and pathological anatomy. Being part of a bilateral framework co-tutelage agreement leading to a joint Doctoral Degree between the Alma Mater Studiorum of Bologna, Italy and the Universidad Nacional del Litoral of Santa Fe, Argentina, this research project was partly carried out in Italy (study of guinea pigs) and partly in Argentina (study of capybaras). It consisted in the macroscopic study, through anatomical dissections of carcasses of both species as well as the use of anatomical casts, and in the histological study of the various systems in the two species, and was aimed at creating a gross and microscopic comparative anatomical atlas. From the gross and microscopic morphological and morphometrical anatomical study of the different system of the guinea pig and capybara, several analogies and differences emerged. The creation of a comparative anatomical atlas of gross and microscopic anatomy of the capybara and the guinea pig might prove useful for clinical, zootechnical and research purposes.

Models for reliability estimation of HVDC cable systems

The work carried out in this thesis aims at: - studying – in both simulative and experimental methods – the effect of electrical transients (i.e., Voltage Polarity Reversals VPRs, Temporary OverVoltages TOVs, and Superimposed Switching Impulses SSIs) on the aging phenomena in HVDC extruded cable insulations. Dielectric spectroscopy, conductivity measurements, Fourier Transform Infra-Red FTIR spectroscopy, and space charge measurements show variation in the insulating properties of the aged Cross-Linked Polyethylene XLPE specimens compared to non-aged ones. Scission in XLPE bonds and formation of aging chemical bonds is also noticed in aged insulations due to possible oxidation reactions. The aged materials show more ability to accumulate space charges compared to non-aged ones. An increase in both DC electrical conductivity and imaginary permittivity has been also noticed. - The development of life-based geometric design of HVDC cables in a detailed parametric analysis of all parameters that affect the design. Furthermore, the effect of both electrical and thermal transients on the design is also investigated. - The intrinsic thermal instability in HVDC cables and the effect of insulation characteristics on the thermal stability using a temperature and field iterative loop (using numerical methods – Finite Difference Method FDM). The dielectric loss coefficient is also calculated for DC cables and found to be less than that in AC cables. This emphasizes that the intrinsic thermal instability is critical in HVDC cables. - Fitting electrical conductivity models to the experimental measurements using both models found in the literature and modified models to find the best fit by considering the synergistic effect between field and temperature coefficients of electrical conductivity.

Network assimilation methodology and sectorization of water distribution systems by graph mining and optimization algorithm

Water Distribution Networks (WDNs) play a vital importance rule in communities, ensuring well-being band supporting economic growth and productivity. The need for greater investment requires design choices will impact on the efficiency of management in the coming decades. This thesis proposes an algorithmic approach to address two related problems:(i) identify the fundamental asset of large WDNs in terms of main infrastructure;(ii) sectorize large WDNs into isolated sectors in order to respect the minimum service to be guaranteed to users. Two methodologies have been developed to meet these objectives and subsequently they were integrated to guarantee an overall process which allows to optimize the sectorized configuration of WDN taking into account the needs to integrated in a global vision the two problems (i) and (ii). With regards to the problem (i), the methodology developed introduces the concept of primary network to give an answer with a dual approach, of connecting main nodes of WDN in terms of hydraulic infrastructures (reservoirs, tanks, pumps stations) and identifying hypothetical paths with the minimal energy losses. This primary network thus identified can be used as an initial basis to design the sectors. The sectorization problem (ii) has been faced using optimization techniques by the development of a new dedicated Tabu Search algorithm able to deal with real case studies of WDNs. For this reason, three new large WDNs models have been developed in order to test the capabilities of the algorithm on different and complex real cases. The developed methodology also allows to automatically identify the deficient parts of the primary network and dynamically includes new edges in order to support a sectorized configuration of the WDN. The application of the overall algorithm to the new real case studies and to others from literature has given applicable solutions even in specific complex situations.

On the motion planning & control of nonlinear robotic systems

In the last decades, we saw a soaring interest in autonomous robots boosted not only by academia and industry, but also by the ever in- creasing demand from civil users. As a matter of fact, autonomous robots are fast spreading in all aspects of human life, we can see them clean houses, navigate through city traffic, or harvest fruits and vegetables. Almost all commercial drones already exhibit unprecedented and sophisticated skills which makes them suitable for these applications, such as obstacle avoidance, simultaneous localisation and mapping, path planning, visual-inertial odometry, and object tracking. The major limitations of such robotic platforms lie in the limited payload that can carry, in their costs, and in the limited autonomy due to finite battery capability. For this reason researchers start to develop new algorithms able to run even on resource constrained platforms both in terms of computation capabilities and limited types of endowed sensors, focusing especially on very cheap sensors and hardware. The possibility to use a limited number of sensors allowed to scale a lot the UAVs size, while the implementation of new efficient algorithms, performing the same task in lower time, allows for lower autonomy. However, the developed robots are not mature enough to completely operate autonomously without human supervision due to still too big dimensions (especially for aerial vehicles), which make these platforms unsafe for humans, and the high probability of numerical, and decision, errors that robots may make. In this perspective, this thesis aims to review and improve the current state-of-the-art solutions for autonomous navigation from a purely practical point of view. In particular, we deeply focused on the problems of robot control, trajectory planning, environments exploration, and obstacle avoidance.

Multiscale modeling of light-harvesting systems based on rhodamine B aggregates

Rhodamine B (RB) has been successfully exploited in the synthesis of light harvesting systems, but since RB is prone to form dimers acting as quenchers for the fluorescence, high energy transfer efficiencies can be reached only when using bulky and hydrophobic counterions acting as spacers between RBs. In this PhD thesis, a multiscale theoretical study aimed at providing insights into the structural, photophysical and optical properties of RB and its aggregates is presented. At the macroscopic level (no atomistic details) a phenomenological model describing the fluorescence decay of RB networks in presence of both quenching from dimers and exciton-exciton annihiliation is presented and analysed, showing that the quenching from dimers affects the decay only at long times, a feature that can be exploited in global fitting analysis to determine relevant chemical and photophysical information. At the mesoscopic level (atomistic details but no electronic structure) the RB aggregation in water in presence of different counterions is studied with molecular dynamics (MD) simulations. A new force field has been parametrized for describing the RB flexibility and the RB-RB interaction driving the dimerization. Simulations correctly predict the RB/counterion aggregation only in presence of bulky and hydrophobic counterion and its ability to prevent the dimerization. Finally, at the microscopic level, DFT calculations are performed to demonstrate the spacing action of bulky counterions, but standard TDDFT calculations are showed to fail in correctly describing the excited states of RB and its dimers. Moreover, also standard procedures proposed in literature for obtaining ad hoc functionals are showed to not work properly. A detailed analysis on the effect of the exact exchange shows that its short-range contribution is the crucial quantity for ameliorating results, and a new functional containing a proper amount of such an exchange is proposed and successfully tested.

Exact and heuristic algorithms for the integrated planning of multi-energy systems

The aim of this thesis is to present exact and heuristic algorithms for the integrated planning of multi-energy systems. The idea is to disaggregate the energy system, starting first with its core the Central Energy System, and then to proceed towards the Decentral part. Therefore, a mathematical model for the generation expansion operations to optimize the performance of a Central Energy System system is first proposed. To ensure that the proposed generation operations are compatible with the network, some extensions of the existing network are considered as well. All these decisions are evaluated both from an economic viewpoint and from an environmental perspective, as specific constraints related to greenhouse gases emissions are imposed in the formulation. Then, the thesis presents an optimization model for solar organic Rankine cycle in the context of transactive energy trading. In this study, the impact that this technology can have on the peer-to-peer trading application in renewable based community microgrids is inspected. Here the consumer becomes a prosumer and engages actively in virtual trading with other prosumers at the distribution system level. Moreover, there is an investigation of how different technological parameters of the solar Organic Rankine Cycle may affect the final solution. Finally, the thesis introduces a tactical optimization model for the maintenance operations’ scheduling phase of a Combined Heat and Power plant. Specifically, two types of cleaning operations are considered, i.e., online cleaning and offline cleaning. Furthermore, a piecewise linear representation of the electric efficiency variation curve is included. Given the challenge of solving the tactical management model, a heuristic algorithm is proposed. The heuristic works by solving the daily operational production scheduling problem, based on the final consumer’s demand and on the electricity prices. The aggregate information from the operational problem is used to derive maintenance decisions at a tactical level.

Distributed and synchronized measurements for the wide-area observation of electric power systems in distorted and low-inertia conditions

With the aim of heading towards a more sustainable future, there has been a noticeable increase in the installation of Renewable Energy Sources (RES) in power systems in the latest years. Besides the evident environmental benefits, RES pose several technological challenges in terms of scheduling, operation, and control of transmission and distribution power networks. Therefore, it raised the necessity of developing smart grids, relying on suitable distributed measurement infrastructure, for instance, based on Phasor Measurement Units (PMUs). Not only are such devices able to estimate a phasor, but they can also provide time information which is essential for real-time monitoring. This Thesis falls within this context by analyzing the uncertainty requirements of PMUs in distribution and transmission applications. Concerning the latter, the reliability of PMU measurements during severe power system events is examined, whereas for the first, typical configurations of distribution networks are studied for the development of target uncertainties. The second part of the Thesis, instead, is dedicated to the application of PMUs in low-inertia power grids. The replacement of traditional synchronous machines with inertia-less RES is progressively reducing the overall system inertia, resulting in faster and more severe events. In this scenario, PMUs may play a vital role in spite of the fact that no standard requirements nor target uncertainties are yet available. This Thesis deeply investigates PMU-based applications, by proposing a new inertia index relying only on local measurements and evaluating their reliability in low-inertia scenarios. It also develops possible uncertainty intervals based on the electrical instrumentation currently used in power systems and assesses the interoperability with other devices before and after contingency events.

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.

Integration of ROS for the control of industrial robotic systems in a proprietary environment

The paper deals with the integration of ROS, in the proprietary environment of the Marchesini Group company, for the control of industrial robotic systems. The basic tools of this open-source software are deeply studied to model a full proprietary Pick and Place manipulator inside it, and to develop custom ROS nodes to calculate trajectories; speaking of which, the URDF format is the standard to represent robots in ROS and the motion planning framework MoveIt offers user-friendly high-level methods. The communication between ROS and the Marchesini control architecture is established using the OPC UA standard; the tasks computed are transmitted offline to the PLC, supervisor controller of the physical robot, because the performances of the protocol don’t allow any kind of active control by ROS. Once the data are completely stored at the Marchesini side, the industrial PC makes the real robot execute a trajectory computed by MoveIt, so that it replicates the behaviour of the simulated manipulator in Rviz. Multiple experiments are performed to evaluate in detail the potential of ROS in the planning of movements for the company proprietary robots. The project ends with a small study regarding the use of ROS as a simulation platform. First, it is necessary to understand how a robotic application of the company can be reproduced in the Gazebo real world simulator. Then, a ROS node extracts information and examines the simulated robot behaviour, through the subscription to specific topics.

Towards the circularity of outdoor lighting systems

In recent years, there has been increasing attention to lighting energy efficiency, due to economics - lower energy costs - and environmental reasons - maninduced climate change. Driven by strict energy-efficiency requirements, the lighting industry started to replace the traditional lamps with LED lighting solutions, ignoring the limits of their maintenance and recycling. Faced with an increasing global population, rising resource consumption and associated negative environmental impacts, shifting from a traditional economic linear model to a more sustainable paradigm of growth is now becoming increasingly urgent. Whereas the topic of circular economy has been widely investigated in literature in the past, little attention has been reserved for the different evaluation tools to assess and improve product circularity and how companies can become more resource-efficient. Hence, the present thesis investigates the implementation of a circular economy in the lighting industry through the use of circularity indicators and ecodesign strategies. Concerning the real luminaire products, the role of the luminaire in the circular economy and recycling industry is explored, highlighting the limits of their End-of-life process. The main conclusions of the thesis reveal the significance of initial product development, reuse, remanufacturing and repair strategies in a transition towards a circular economy.

Axis control optimization: autotuning techniques and frequency response analysis of industrial mechatronic systems

In the field of industrial automation, there is an increasing need to use optimal control systems that have low tracking errors and low power and energy consumption. The motors we are dealing with are mainly Permanent Magnet Synchronous Motors (PMSMs), controlled by 3 different types of controllers: a position controller, a speed controller, and a current controller. In this thesis, therefore, we are going to act on the gains of the first two controllers by going to find, through the TwinCAT 3 software, what might be the best set of parameters. To do this, starting with the default parameters recommended by TwinCAT, two main methods were used and then compared: the method of Ziegler and Nichols, which is a tabular method, and advanced tuning, an auto-tuning software method of TwinCAT. Therefore, in order to analyse which set of parameters was the best,several experiments were performed for each case, using the Motion Control Function Blocks. Moreover, some machines, such as large robotic arms, have vibration problems. To analyse them in detail, it was necessary to use the Bode Plot tool, which, through Bode plots, highlights in which frequencies there are resonance and anti-resonance peaks. This tool also makes it easier to figure out which and where to apply filters to improve control.

Fractional dynamics in financial indexes

The goal of this study is the analysis of the dynamical properties of financial data series from 32 worldwide stock market indices during the period 2000–2009 at a daily time horizon. Stock market indices are examples of complex interacting systems for which a huge amount of data exists. The methods and algorithms that have been explored for the description of physical phenomena become an effective background in the analysis of economical data. In this perspective are applied the classical concepts of signal analysis, Fourier transform and methods of fractional calculus. The results reveal classification patterns typical of fractional dynamical systems.