Distributed Large-scale Mixed-Integer Optimization with Application to Energy and Multi-robot Networks

Several decision and control tasks in cyber-physical networks can be formulated as large- scale optimization problems with coupling constraints. In these "constraint-coupled" problems, each agent is associated to a local decision variable, subject to individual constraints. This thesis explores the use of primal decomposition techniques to develop tailored distributed algorithms for this challenging set-up over graphs. We first develop a distributed scheme for convex problems over random time-varying graphs with non-uniform edge probabilities. The approach is then extended to unknown cost functions estimated online. Subsequently, we consider Mixed-Integer Linear Programs (MILPs), which are of great interest in smart grid control and cooperative robotics. We propose a distributed methodological framework to compute a feasible solution to the original MILP, with guaranteed suboptimality bounds, and extend it to general nonconvex problems. Monte Carlo simulations highlight that the approach represents a substantial breakthrough with respect to the state of the art, thus representing a valuable solution for new toolboxes addressing large-scale MILPs. We then propose a distributed Benders decomposition algorithm for asynchronous unreliable networks. The framework has been then used as starting point to develop distributed methodologies for a microgrid optimal control scenario. We develop an ad-hoc distributed strategy for a stochastic set-up with renewable energy sources, and show a case study with samples generated using Generative Adversarial Networks (GANs). We then introduce a software toolbox named ChoiRbot, based on the novel Robot Operating System 2, and show how it facilitates simulations and experiments in distributed multi-robot scenarios. Finally, we consider a Pickup-and-Delivery Vehicle Routing Problem for which we design a distributed method inspired to the approach of general MILPs, and show the efficacy through simulations and experiments in ChoiRbot with ground and aerial robots.

A methodological approach for the performance optimization of transient seepage models through inverse analysis

The topic of the Ph.D project focuses on the modelling of the soil-water dynamics inside an instrumented embankment section along Secchia River (Cavezzo (MO)) in the period from 2017 to 2018 and the quantification of the performance of the direct and indirect simulations . The commercial code Hydrus2D by Pc-Progress has been chosen to run the direct simulations. Different soil-hydraulic models have been adopted and compared. The parameters of the different hydraulic models are calibrated using a local optimization method based on the Levenberg - Marquardt algorithm implemented in the Hydrus package. The calibration program is carried out using different types of dataset of observation points, different weighting distributions, different combinations of optimized parameters and different initial sets of parameters. The final goal is an in-depth study of the potentialities and limits of the inverse analysis when applied to a complex geotechnical problem as the case study. The second part of the research focuses on the effects of plant roots and soil-vegetation-atmosphere interaction on the spatial and temporal distribution of pore water pressure in soil. The investigated soil belongs to the West Charlestown Bypass embankment, Newcastle, Australia, that showed in the past years shallow instabilities and the use of long stem planting is intended to stabilize the slope. The chosen plant species is the Malaleuca Styphelioides, native of eastern Australia. The research activity included the design and realization of a specific large scale apparatus for laboratory experiments. Local suction measurements at certain intervals of depth and radial distances from the root bulb are recorded within the vegetated soil mass under controlled boundary conditions. The experiments are then reproduced numerically using the commercial code Hydrus 2D. Laboratory data are used to calibrate the RWU parameters and the parameters of the hydraulic model.

Optimization of the power electronics system associated with ocean wave electric generators

The present thesis is focused on wave energy, which is a particular kind of ocean energy, and is based on the activity carried out during the EU project SEA TITAN. The main scope of this work is the design of a power electronic section for an innovative wave energy extraction system based on a switched-reluctance machine. In the first chapter, the general features of marine wave energy harvesting are treated. The concept of Wave Energy Converter (WEC) is introduced as well as the mathematical description of the waves, their characterization and measurement, the WEC classification, the operating principles and the standardization framework. Also, detailed considerations on the environmental impact are presented. The SEA TITAN project is briefly described. The second chapter is dedicated to the technical issues of the SEA TITAN project, such as the operating principle, the performance optimization carried out in the project, the main innovations as well as interesting demonstrations on the behavior of the generator and its control. In the third chapter, the power electronics converters of SEA TITAN are described, and the design choices, procedures and calculations are shown, with a further insight into the application given by analyzing the MATLAB Simulink model of the system and its control scheme. Experimental tests are reported in the fourth chapter, with graphs and illustrations of the power electronic apparatus interfaced with the real machine. Finally, the conclusion in the fifth chapter offers a global overview of the project and opens further development pathways.

Development and optimization of fibre-shaped dye-sensitized solar cells employing an innovative fully organic sensitizer

The quality of human life depends to a large degree on the availability of energy. In recent years, photovoltaic technology has been growing extraordinarily as a suitable source of energy, as a consequence of the increasing concern over the impact of fossil fuels on climate change. Developing affordable and highly efficiently photovoltaic technologies is the ultimate goal in this direction. Dye-sensitized solar cells (DSSCs) offer an efficient and easily implementing technology for future energy supply. Compared to conventional silicon solar cells, they provide comparable power conversion efficiency at low material and manufacturing costs. In addition, DSSCs are able to harvest low-intensity light in diffuse illumination conditions and then represent one of the most promising alternatives to the traditional photovoltaic technology, even more when trying to move towards flexible and transparent portable devices. Among these, considering the increasing demand of modern electronics for small, portable and wearable integrated optoelectronic devices, Fibre Dye-Sensitized Solar Cells (FDSSCs) have gained increasing interest as suitable energy provision systems for the development of the next-generation of smart products, namely “electronic textiles” or “e-textiles”. In this thesis, several key parameters towards the optimization of FDSSCs based on inexpensive and abundant TiO2 as photoanode and a new innovative fully organic sensitizer were studied. In particular, the effect of various FDSSCs components on the device properties pertaining to the cell architecture in terms of photoanode oxide layer thickness, electrolytic system, cell length and electrodes substrates were examined. The photovoltaic performances of the as obtained FDSSCs were fully characterized. Finally, the metal part of the devices (wire substrate) was substituted with substrates suitable for the textile industry as a fundamental step towards commercial exploitation.

Formulations and Metaheuristics for combinatorial optimization problems

Combinatorial optimization problems have been strongly addressed throughout history. Their study involves highly applied problems that must be solved in reasonable times. This doctoral Thesis addresses three Operations Research problems: the first deals with the Traveling Salesman Problem with Pickups and Delivery with Handling cost, which was approached with two metaheuristics based on Iterated Local Search; the results show that the proposed methods are faster and obtain good results respect to the metaheuristics from the literature. The second problem corresponds to the Quadratic Multiple Knapsack Problem, and polynomial formulations and relaxations are presented for new instances of the problem; in addition, a metaheuristic and a matheuristic are proposed that are competitive with state of the art algorithms. Finally, an Open-Pit Mining problem is approached. This problem is solved with a parallel genetic algorithm that allows excavations using truncated cones. Each of these problems was computationally tested with difficult instances from the literature, obtaining good quality results in reasonable computational times, and making significant contributions to the state of the art techniques of Operations Research.

PCM-based battery thermal management systems, energy saving materials and LCA strategy for automotive

This PhD work arises from the necessity to give a contribution to the energy saving field, regarding automotive applications. The aim was to produce a multidisciplinary work to show how much important is to consider different aspects of an electric car realization: from innovative materials to cutting-edge battery thermal management systems (BTMSs), also dealing with the life cycle assessment (LCA) of the battery packs (BPs). Regarding the materials, it has been chosen to focus on carbon fiber composites as their use allows realizing light products with great mechanical properties. Processes and methods to produce carbon fiber goods have been analysed with a special attention on the university solar car Emilia 4. The work proceeds dealing with the common BTMSs on the market (air-cooled, cooling plates, heat pipes) and then it deepens some of the most innovative systems such as the PCM-based BTMSs after a previous experimental campaign to characterize the PCMs. After that, a complex experimental campaign regarding the PCM-based BTMSs has been carried on, considering both uninsulated and insulated systems. About the first category the tested systems have been pure PCM-based and copper-foam-loaded-PCM-based BTMSs; the insulated tested systems have been pure PCM-based and copper-foam-loaded-PCM-based BTMSs and both of these systems equipped with a liquid cooling circuit. The choice of lighter building materials and the optimization of the BTMS are strategies which helps in reducing the energy consumption, considering both the energy required by the car to move and the BP state of health (SOH). Focusing on this last factor, a clear explanation regarding the importance of taking care about the SOH is given by the analysis of a BP production energy consumption. This is why a final dissertation about the life cycle assessment (LCA) of a BP unit has been presented in this thesis.

Development and application of a computer-based methodology for design for additive manufacturing of automotive components

The research project aims to improve the Design for Additive Manufacturing of metal components. Firstly, the scenario of Additive Manufacturing is depicted, describing its role in Industry 4.0 and in particular focusing on Metal Additive Manufacturing technologies and the Automotive sector applications. Secondly, the state of the art in Design for Additive Manufacturing is described, contextualizing the methodologies, and classifying guidelines, rules, and approaches. The key phases of product design and process design to achieve lightweight functional designs and reliable processes are deepened together with the Computer-Aided Technologies to support the approaches implementation. Therefore, a general Design for Additive Manufacturing workflow based on product and process optimization has been systematically defined. From the analysis of the state of the art, the use of a holistic approach has been considered fundamental and thus the use of integrated product-process design platforms has been evaluated as a key element for its development. Indeed, a computer-based methodology exploiting integrated tools and numerical simulations to drive the product and process optimization has been proposed. A validation of CAD platform-based approaches has been performed, as well as potentials offered by integrated tools have been evaluated. Concerning product optimization, systematic approaches to integrate topology optimization in the design have been proposed and validated through product optimization of an automotive case study. Concerning process optimization, the use of process simulation techniques to prevent manufacturing flaws related to the high thermal gradients of metal processes is developed, providing case studies to validate results compared to experimental data, and application to process optimization of an automotive case study. Finally, an example of the product and process design through the proposed simulation-driven integrated approach is provided to prove the method's suitability for effective redesigns of Additive Manufacturing based high-performance metal products. The results are then outlined, and further developments are discussed.

Towards cheaper, safer and low environmental impact materials for energy storage devices: natural resources-derived carbon based electrodes and aqueous electrolytes for supercapacitors

The growing market of electrical cars, portable electronics, photovoltaic systems..etc. requires the development of efficient, low-cost, and low environmental impact energy storage devices (ESDs) including batteries and supercapacitors.. Due to their extended charge-discharge cycle, high specific capacitance, and power capabilities supercapacitors are considered among the most attractive ESDs. Over the last decade, research and development in supercapacitor technology have accelerated: thousands of articles have been published in the literature describing the electrochemical properties of the electrode materials and electrolyte in addition to separators and current collectors. Carbon-based supercapacitor electrodes materials have gained increasing attention due to their high specific surface area, good electrical conductivity, and excellent stability in harsh environments, as well as other characteristics. Recently, there has been a surge of interest in activated carbon derived from low-cost abundant sources such as biomass for supercapacitor electrode materials. Also, particular attention was given to a major challenging issue concerning the substitution of organic solutions currently used as electrolytes due to their highest electrochemical stability window even though their high cost, toxicity, and flammability. In this regard, the main objective of this thesis is to investigate the performances of supercapacitors using low cost abundant safe, and low environmental impact materials for electrodes and electrolytes. Several prototypes were constructed and tested using natural resources through optimization of the preparation of appropriate carbon electrodes using agriculture by-products waste or coal (i.e. Argan shell or Anthracite from Jerrada). Such electrodes were tested using several electrolyte formulations (aqueous and water in salt electrolytes) beneficing their non-flammability, lower cost, and environmental impact; the characteristics that provide a promising opportunity to design safer, inexpensive, and environmentally friendly devices compared to organic electrolytes.

Distributed optimization and games over networks: a system theoretical perspective

Several decision and control tasks involve networks of cyber-physical systems that need to be coordinated and controlled according to a fully-distributed paradigm involving only local communications without any central unit. This thesis focuses on distributed optimization and games over networks from a system theoretical perspective. In the addressed frameworks, we consider agents communicating only with neighbors and running distributed algorithms with optimization-oriented goals. The distinctive feature of this thesis is to interpret these algorithms as dynamical systems and, thus, to resort to powerful system theoretical tools for both their analysis and design. We first address the so-called consensus optimization setup. In this context, we provide an original system theoretical analysis of the well-known Gradient Tracking algorithm in the general case of nonconvex objective functions. Then, inspired by this method, we provide and study a series of extensions to improve the performance and to deal with more challenging settings like, e.g., the derivative-free framework or the online one. Subsequently, we tackle the recently emerged framework named distributed aggregative optimization. For this setup, we develop and analyze novel schemes to handle (i) online instances of the problem, (ii) ``personalized'' optimization frameworks, and (iii) feedback optimization settings. Finally, we adopt a system theoretical approach to address aggregative games over networks both in the presence or absence of linear coupling constraints among the decision variables of the players. In this context, we design and inspect novel fully-distributed algorithms, based on tracking mechanisms, that outperform state-of-the-art methods in finding the Nash equilibrium of the game.

Drive up electrochemical and electrochemiluminescence signal through biosensing mechanism optimization

Biomarkers are biological indicators of human health conditions. Their ultra-sensitive quantification is of cardinal importance in clinical monitoring and early disease diagnosis. Biosensors are some worldwide simple and easy-to-use analytical devices as a matter of fact, biosensors using electrochemiluminescence (ECL) are one of the most promising biosensors that needs an ever-increasing sensitivity for improving its clinical effectiveness. The principal aspiration of this project is the investigation of the ECL generation mechanisms for enhancing the ECL intensity and the development of an ultrasensitive sensor, the use of metal-oxide materials (Mox) and the substitution of metal-free dyes. Novel dyes such as BODIPY, TADF are used to improve the sensitivity of ECL techniques thanks to their advantageous and tunable properties, enhancing the signal and also the ECL efficiency. Additionally, the use of Mox could be beneficial for the investigation of two different ECL mechanisms, which occur simultaneously. In this thesis, the investigation of size and distance effects on electrochemical (EC) mechanisms was carried out through the innovative combination of a standard detection system using different size of micromagnetic beads (MBs). That allowed the discovery of an unexpected and highly efficient mechanistic path for electrochemical generation at small distances from the electrode’s surface. The smallest MBs (0.1μm) demostrate an enhancement of electrochemical signal than the bigger one (2.8μm) until 4 times of magnitude. Finally, a novel ultrasensitive sensor, based on the coreactant-luminophores mechanism, was developed for the determination of whole viral genome specific for cardiac HBV and COVID-19 virus. In conclusion, the ECL and the use of EC techniques (such as amperometry), improved the understanding of mechanisms responsible for the ECL/EC signal led to a great enhancement in the signal.

Computational tool for three-point hitch geometry optimization

The weight-transfer effect, consisting of the change in dynamic load distribution between the front and the rear tractor axles, is one of the most impairing phenomena for the performance, comfort, and safety of agricultural operations. Excessive weight transfer from the front to the rear tractor axle can occur during operation or maneuvering of implements connected to the tractor through the three-point hitch (TPH). In this respect, an optimal design of the TPH can ensure better dynamic load distribution and ultimately improve operational performance, comfort, and safety. In this study, a computational design tool (The Optimizer) for the determination of a TPH geometry that minimizes the weight-transfer effect is developed. The Optimizer is based on a constrained minimization algorithm. The objective function to be minimized is related to the tractor front-to-rear axle load transfer during a simulated reference maneuver performed with a reference implement on a reference soil. Simulations are based on a 3-degrees-of-freedom (DOF) dynamic model of the tractor-TPH-implement aggregate. The inertial, elastic, and viscous parameters of the dynamic model were successfully determined through a parameter identification algorithm. The geometry determined by the Optimizer complies with the ISO-730 Standard functional requirements and other design requirements. The interaction between the soil and the implement during the simulated reference maneuver was successfully validated against experimental data. Simulation results show that the adopted reference maneuver is effective in triggering the weight-transfer effect, with the front axle load exhibiting a peak-to-peak value of 27.1 kN during the maneuver. A benchmark test was conducted starting from four geometries of a commercially available TPH. As result, all the configurations were optimized by above 10%. The Optimizer, after 36 iterations, was able to find an optimized TPH geometry which allows to reduce the weight-transfer effect by 14.9%.

Design, synthesis and photovoltaic properties of some thiophene-based conjugated polymers for organic solar cells

The current issue of the resource of energy combined with the tendency to give a green footprint to our lifestyle have prompted the research to focus the attention on alternative sources with great strides in the optimization of polymeric photovoltaic devices. The research work described in this dissertation consists in the study of different semiconducting π-conjugated materials based on polythiophenes (Chapter I). In detail, the GRIM polymerization was deepened defining the synthetic conditions to obtain regioregular poly(3-alkylthiophene) (Chapter II). Since the use of symmetrical monomers functionalized with oxygen atom(s) allows to adopt easy synthesis leading to performing materials, disubstituted poly(3,4-dialkoxythiophene)s were successfully prepared, characterized and tested as photoactive materials in solar cells (Chapter III). A “green” resource of energy should be employed through sustainable devices and, for this purpose, the research work was continued on the synthesis of thiophene derivatives soluble in eco-friendly solvents. To make this possible, the photoactive layer was completely tailored starting from the electron-acceptor material. A fullerene derivative soluble in alcohols was successfully synthetized and adopted for the realization of the new devices (Chapter IV). New water/alcohol soluble electron-donor materials with different functional groups were prepared and their properties were compared (Chapter V). Once found the best ionic functional group, a new double-cable material was synthetized optimizing the surface area between the different materials (Chapter VI). Finally, other water/alcohol soluble materials were synthetized, characterized and used as cathode interlayers in eco-friendly devices (Chapter VII). In this work, all prepared materials were characterized by spectroscopy analyses, gel permeation chromatography and thermal analyses. Cyclic voltammetry, X-ray diffraction, atomic force microscopy and external quantum efficiency were used to investigate some peculiar aspects.

A ROS-based software architecture for a versatile collaborative dual-armed autonomous mobile robot for the manufacturing industry

The industrial context is changing rapidly due to advancements in technology fueled by the Internet and Information Technology. The fourth industrial revolution counts integration, flexibility, and optimization as its fundamental pillars, and, in this context, Human-Robot Collaboration has become a crucial factor for manufacturing sustainability in Europe. Collaborative robots are appealing to many companies due to their low installation and running costs and high degree of flexibility, making them ideal for reshoring production facilities with a short return on investment. The ROSSINI European project aims to implement a true Human-Robot Collaboration by designing, developing, and demonstrating a modular and scalable platform for integrating human-centred robotic technologies in industrial production environments. The project focuses on safety concerns related to introducing a cobot in a shared working area and aims to lay the groundwork for a new working paradigm at the industrial level. The need for a software architecture suitable to the robotic platform employed in one of three use cases selected to deploy and test the new technology was the main trigger of this Thesis. The chosen application consists of the automatic loading and unloading of raw-material reels to an automatic packaging machine through an Autonomous Mobile Robot composed of an Autonomous Guided Vehicle, two collaborative manipulators, and an eye-on-hand vision system for performing tasks in a partially unstructured environment. The results obtained during the ROSSINI use case development were later used in the SENECA project, which addresses the need for robot-driven automatic cleaning of pharmaceutical bins in a very specific industrial context. The inherent versatility of mobile collaborative robots is evident from their deployment in the two projects with few hardware and software adjustments. The positive impact of Human-Robot Collaboration on diverse production lines is a motivation for future investments in research on this increasingly popular field by the industry.

Diffusing alpha particles radiation treatment optimization in clinical settings

Alpha-particle emitters, notably used in 224Ra-DaRT, have emerged as effective in overcoming radiation resistance and providing targeted cancer therapy. These emitters cause DNA double-strand breaks, visualizable in human lymphocytes. The 224Ra DaRT technique, using a decay chain from seeds, extends alpha particle range, achieving complete tumor destruction while sparing healthy tissue. This thesis examines a biokinetic model, validated with patient data, and a feasibility study on skin squamous cell carcinomas are discussed. The study reports 75% tumor complete response rate and 48% patients experiencing acute grade 2 toxicity, resolving within a month. An observed abscopal effect (AE), where tumor regression occurs at non-irradiated sites, is examined, highlighting DaRT's potential in triggering anti-tumor immune responses. This effect, coupled with DaRT's high-linear energy transfer (LET), suggests its superiority over low-LET radiation in certain clinical scenarios. Improvements to DaRT, including the use of an external radio-opaque template for treatment planning, are explored. This advancement aids in determining source numbers for optimal tumor coverage, enhancing DaRT’s safety. The thesis outlines a typical DaRT procedure, from tumor measurements to source assessment and administration, emphasizing the importance of precise seed positioning. Furthermore, the thesis discusses DaRT's potential in treating prostate cancer, a prevalent global health issue, by offering an alternative to traditional salvage therapies. DaRT seeds, delivering alpha particle-based interstitial radiation, require precision in seed insertion due to their limited tissue range. In conclusion, the thesis advocates for DaRT's role in treating solid tumors, emphasizing its improved radiobiological potency and potential benefits over beta and gamma source-based therapies. Ongoing studies are assessing DaRT's feasibility in treating various solid tumors, including pancreatic, breast, prostate, and vulvar malignancies, suggesting a promising future in cancer treatment.

Development of processes for the valorization of lignocellulosic biomass based on renewable energies

The world grapples with climate change from fossil fuel reliance, prompting Europe to pivot to renewable energy. Among renewables, biomass is a bioenergy and bio-carbon source, used to create high-value biomolecules, replacing fossil-based products. Alkyl levulinates, derived from biomass, hold promise as bio-additives and biofuels, especially via acid solvolysis of hexose sugars, necessitating further exploration. Alkyl levulinate's potential extends to converting into γ-valerolactone (GVL), a bio-solvent produced via hydrogenation with molecular-hydrogen. Hydrogen, a key reagent and energy carrier, aids renewable energy integration. This thesis delves into a biorefinery system study, aligning with sustainability goals, integrating biomass valorization, energy production, and hydrogen generation. It investigates optimizing technologies for butyl levulinate production and subsequent GVL hydrogenation. Sustainability remains pivotal, reflecting the global shift towards renewable and carbon bio-resources. The research initially focuses on experimenting with the optimal technology for producing butyl levulinate from biomass-derived hexose fructose. It examines the solvolysis process, investigating optimal conditions, kinetic modeling, and the impact of solvents on fructose conversion. The subsequent part concentrates on the technological aspect of hydrogenating butyl levulinate into GVL. It includes conceptual design, simulation, and optimization of the fructose-to-GVL process scheme based on process intensification. In the final part, the study applies the process to a real case study in Normandy, France, adapting it to local biomass availability and wind energy. It defines a methodology for designing and integrating the energy-supply system, evaluating different scenarios. Sustainability assessment using economic, environmental, and social indicators culminates in an overall sustainability index, indicating scenarios integrating the GVL biorefinery system with wind power and hydrogen energy storage as promising due to high profitability and reduced environmental impact. Sensitivity analyses validate the methodology's reliability, potentially extending to other technological systems.