Politecnio die Bari - Catalogo di prodotti della Ricerca
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Managing Water-Ecosystem-Food Nexus using participatory approaches: insights from an innovative methodological approach developed in two Mediterranean areas
Get PDFThe formulation of effective policies to address both the present allocation and future conservation of natural resources in an integrated way remains an essential and challenging task. In this regard, managing the Nexus is increasingly seen as a priority in resource governance. Nature-based Solutions (NbS) are gradually being advocated to enhance sustainable and resilient Nexus management efforts. Designing and planning NbS tailored to local contexts requires a thorough understanding of the specific challenges and perspectives, as well as the divergent perspectives among stakeholders. This paper presents and analyses an effective stakeholder engagement strategy, based on the Learning & Action Alliances (LAA) scheme and aimed at identifying Water-Ecosystems-Food (WEF) Nexus challenges and selecting NbS in two case studies in the Mediterranean area (Greece and Italy). In total, 60 stakeholders were engaged in more than 40 events (workshops, seminars, open days, field trips etc.), while 25 individual interviews were also conducted. By fostering collaboration and stakeholder ownership, the methodology provided actionable insights and promoted context-specific solutions. The stakeholders proposed 24 NbSs in the Italian case study, most of which were related to agricultural landscape management, while in the Greek case study, 2 of the 4 top-ranked measures were NbSs. The findings underline the importance of participatory approaches and transdisciplinary tools in addressing Nexus challenges, offering a replicable framework for sustainable resource management in resource-stressed regions
Flutter Calculations Using the Unsteady Source and Doublet Panel Method
No full textThe source and doublet panel method (SDPM) developed by Morino in the 1970s can model unsteady compressible ideal flow around wings and bodies. In this work, the SDPM is adapted to the calculation of aeroelastic solutions for wings. A second-order nonlinear version of Bernoulli's equation is transformed to the frequency domain and written in terms of the generalized mode shapes and displacements. It is shown that the pressure component at the oscillating frequency is a linear function of the generalized displacements, velocities, and accelerations and can therefore be used to formulate a linear flutter problem. The proposed approach has several advantages over the usual doublet lattice method (DLM) approach: the exact geometry is modeled (including thickness, camber, and twist effects), the motion of the surface can be represented using all six degrees of freedom, the pressure calculation is of higher order, and the aerodynamic mass, damping, and stiffness terms are calculated explicitly. The complete procedure is validated using experimental data from the weakened AGARD 445.6 wing, a NACA 0012 rectangular wing with pitch and plunge degrees of freedom, and an experimental model of a T-tail, yielding flutter predictions that lie closer to the experimental observations than those obtained from the DLM, particularly in the case of the T-tail
Electronic skin technologies: From hardware building blocks and tactile sensing to control algorithms and applications
No full textE-skin technologies are poised to reshape numerous sectors, offering new possibilities through their thin, flexible, and highly sensitive interfaces. By integrating advanced transducer mechanisms and edge artificial intelligence computing, these interfaces not only enhance the quality of services and products but also promote greater user interaction and real-time data processing. Prosthetic and rehabilitation devices equipped with human-machine interfaces can improve the lives of people with disabilities, enabling them to interact more naturally with their environment. Furthermore, recent studies and advanced sensors have achieved sensitivity and accuracy levels not only comparable to human tactile receptors but even superior, enabling unprecedented touch perception and interaction. In the field of robotics, e-skins provide robots with human-like tactile sensitivity, enhancing their efficiency and safety when interacting with humans, machines, and the environment. The integration of e-skins with soft robotics and edge AI technology opens new frontiers in device design, making them more adaptable and capable of dynamically responding to user needs. Recent advances in flexible interfaces have led to improved transducer sensitivity and energy-efficient processing, ensuring better integration with wearable devices and interactive systems. These developments highlight the growing emphasis on real-time data processing and adaptive learning algorithms, key to the future of human-machine interactions. This paper delves into the materials, structures, and mechanisms that constitute flexible electronic interfaces and their applications. Progress and challenges in implementing effective human-machine interfaces are examined. The paper concludes with a discussion on the prospects and current challenges in the field of human-machine interfaces, particularly in medical robotics
Mitigation of motion sickness in automated vehicles
No full textThis dissertation addresses the pressing challenge of motion sickness in automated vehicles, emphasising the development of motion planning and control strategies to enhance passenger comfort. With the advent of autonomous driving, vehicles are no longer controlled by a driver who can intuitively adjust manoeuvres based on passenger comfort, making the issue of motion sickness more prominent. Automated driving offers numerous benefits and can lead to unpredictable vehicle dynamics from a passenger’s perspective, resulting in a heightened incidence of discomfort and motion sickness. This dissertation investigates methods to mitigate these effects to improve user experience and support wider acceptance of autonomous vehicle technology. The research begins by exploring the phenomenon of motion sickness and examining its causes, symptoms, and physiological impacts on passengers. Various theories are reviewed to explain why motion sickness occurs, including sensory conflict, postural instability, and subjective vertical mismatch theories, each offering insight into how human perception and control systems respond to unpredictable or sustained vehicle motion. The dissertation delves into methods for evaluating motion sickness, discussing different models, questionnaires, and indexes that quantify the likelihood or severity of motion sickness in various driving scenarios. Furthermore, it examines existing mitigation methods, categorising them into three broad approaches: behavioural practices, medical and supplementary solutions, and technological interventions related to vehicle design and control. This comprehensive understanding of motion sickness forms the foundation for the control and planning strategies proposed later in the dissertation. A central focus of the research is motion planning for comfort, identifying the significance of designing trajectories that reduce abrupt changes in speed and direction. Motion planning is positioned as one of the most promising methods for mitigating motion sickness, as it allows for pre-emptive control of vehicle dynamics to maintain smooth and predictable motion. The dissertation evaluates several planning algorithms and methodologies, illustrating how strategic trajectory design can contribute to reducing the lateral and longitudinal forces that typically lead to discomfort. By emphasising smooth, predictable movements, motion planning significantly enhances passenger comfort, supporting the hypothesis that a tailored approach to trajectory design can minimise motion sickness. In addition to motion planning, the dissertation explores nonlinear model predictive control (NMPC) algorithms, which are particularly suited to handling the complex, nonlinear dynamics involved in automated driving. Several NMPC strategies are discussed, including traction control, torque vectoring, and active suspension systems. Through simulations and experiments, the NMPC strategies demonstrate their capacity for precisely modulating vehicle dynamics, paving the way for further investigation of their efficiency in counteracting the potential sources of motion sickness by keeping movements within comfortable bounds. This combination of motion planning and NMPC strategies could offer a holistic approach to enhancing passenger comfort in autonomous vehicles. The findings illustrate that by integrating smooth trajectory planning with advanced control algorithms, it is possible to create an automated driving experience that prioritises comfort and reduces the risk of motion sickness. Concluding the dissertation, the research points to future directions that could build on these results, such as refining motion sickness modelling, developing more adaptive control systems, and validating the methods in real-world driving scenarios. Through its in-depth investigation of motion sickness and its proposed mitigation methods, this dissertation contributes valuable insights to the field of autonomous vehicle design, aiming to make autonomous driving more comfortable and appealing for passengers
Additive manufacturing for electrical actuation systems and sensing
No full textLa Manifattura Additiva (AM) è diventata una tecnologia fondamentale per l'Industria 4.0 grazie alla sua convenienza economica, basso impatto ambientale, automazione, elevato livello di libertà nella fabbricazione e personalizzazione. In particolare, l'Extrusione di Materiale (MEX), una tecnologia AM ampiamente utilizzata, sta guadagnando un enorme interesse per la realizzazione di strutture intelligenti, che possono essere auto-attuate, auto-sensibili e auto-riparanti, come attuatori morbidi, sensori e dispositivi reattivi agli stimoli. MEX è stato impiegato per il suo alto livello di personalizzazione, adattandosi a estrudere materiali non convenzionali come inchiostri funzionali, polimeri conduttivi e silicone. MEX è ideale per applicazioni in robotica morbida, sensori e anche batterie stampate in 3D, consentendo un'integrazione avanzata di molteplici funzionalità delle strutture stampate.
In questa tesi di dottorato, la tecnologia MEX è stata utilizzata per fabbricare diverse strutture intelligenti, come attuatori con sensori integrati, sensori auto-riparanti e strutture elettromagnetiche: sono stati ottenuti notevoli riduzioni nei costi di fabbricazione, miglioramenti delle prestazioni meccaniche e di rilevamento attraverso approcci innovativi di fabbricazione e impianti di stampa 3D personalizzati.
In primo luogo, sono stati studiati attuatori stampati in 3D e robot morbidi con sensori integrati e canali riempiti di metallo, attuati tramite corrente elettrica e campo magnetico, dimostrando il potenziale della fabbricazione "one-shot" di strutture intelligenti pronte all'uso. L'effetto Mullins degli attuatori intelligenti è stato ridotto studiando il comportamento in vibrazione durante i movimenti di piegamento: è stata ottenuta una riduzione del 16% incorporando nervature geometriche nell'area di piegatura (giunto). Successivamente, il giunto è stato studiato e implementato per fabbricare un dito multi-materiale e multi-attuazione, attuato tramite: i) polimero a memoria di forma (SMP) riscaldato tramite un filo di Nicromo incorporato, e ii) tendine azionato, risultando in movimenti complessi che combinano entrambi i metodi di attuazione.
Per sviluppare e fabbricare strutture intelligenti innovative, sono stati studiati diversi impianti di stampa 3D e materiali non convenzionali: è stato scoperto un metodo per migliorare la stampabilità del silicone (sia puro che con nanoparticelle magnetiche) e implementato un impianto di stampa 3D IDEX personalizzato in grado di estrudere contemporaneamente silicone e polimero termoplastico nello stesso ciclo di stampa. Questo impianto sfrutta la forza elettrica di Lorentz nella testa di estrusione del silicone per: i) ridurre la forza di stampa (21,08%) permettendo l'estrusione di strutture sottili e precise, e ii) fabbricare strutture multi-materiale auto-attuate che possono muoversi utilizzando stimoli esterni (come il campo magnetico). Inoltre, è stato implementato un impianto personalizzato per aumentare la sensibilità dei sensori multi-materiale stampati in 3D impiegando tecniche di rolling e studiando i parametri di stampa dell'ironing: quest'ultimo ha aumentato la sensibilità dei sensori stampati in 3D dell'83%, grazie alla riduzione del 50% dei vuoti. È stato anche esplorato un nuovo approccio per fabbricare strutture intelligenti auto-riparanti: è stata sviluppata una macchina di stampa 3D personalizzata in grado di estrudere sia materiali auto-riparanti a base di filamento che a base di inchiostro. È stato implementato un innovativo Sistema di Riscaldamento Separato (SHS) per controllare meglio le temperature di pre-estrusione ed estrusione tramite PID, migliorando le prestazioni meccaniche, geometriche, di guarigione (95%) e di rilevamento dei sensori stampati in 3D.
Infine, è stata presentata una revisione completa delle batterie stampate in 3D con tecnologia MEX, evidenziando i problemi, le sfide e i progressi in questo nuovo campo. La revisione della letteratura prevede la possibilità futuristica di dispositivi stampati in 3D in un'unica fase, composti da sensori, attuatori e batterie, pronti per essere utilizzati dopo la rimozione dalla piattaforma di stampa 3D.Additive Manufacturing (AM) has become a key technology for Industry 4.0 due to its cost-effectiveness, low environmental impact, automation, high-level of freedom in fabrication and customization. Particularly, Material Extrusion (MEX), a widely used AM technology, is gaining tremendous interest for the fabrication of smart structures, that can be self-actuated, self-sense, and self-heal, such as soft actuators, sensors, and stimuli-responsive devices. MEX has been employed for its high level of customization, fitting it to extrude non-conventional materials such as functional inks, conductive polymers, and silicone. MEX is ideal for applications in soft robotics, sensors, and even 3D-printed batteries, allowing for advanced integration of multiple functionalities of the printed structures.
In this PhD thesis, MEX technology was used to fabricate several smart structures, such as actuators with embedded sensors, self-healing sensors, and electro- and magnetic-driven structures: a remarkable reduction in fabrication cost, improvement of mechanical and sensing performances, were achieved through innovative fabrication approaches and custom-made 3D printing setups.
First, 3D printed actuators and soft robots with embedded sensors and metal filled channels, actuated via electrical current and magnetic field, were investigated, proving the potentiality of one-shot fabrication of ready-to-use smart structures. Mullins effect of the smart actuators was decreased studying the vibration behavior during of the bending movements: a reduction of 16% was achieved incorporating geometrical ribs in the bending area (joint). Afterwards, the joint was studied and implemented to fabricate a multi-material and multi-actuation finger actuated using: i) shape memory polymer (SMP) heated via embedded electrical Nichrome wire, and ii) tendon driven, resulting in complex movements combining both actuation methods.
To develop and fabricate innovative smart structures, several 3D printing setups and non-conventional materials were studied: a method to improve the printability of silicone (such as pure or with magnetic nano particles) was discovered, implemented a custom-made IDEX 3D printing setup able to extrude at the same time silicone and thermoplastic polymer in the same printing cycle. This setup leverages the electrical Lorentz force in the silicone extrusion head to: i) reduce the printing force (21.08%) enabling thin walled and accurate structures extrusion, and ii) fabricate self-actuated multi-material structures that can move using external stimuli (such as magnetic field). Moreover, a custom-made setup was implemented for increasing the sensitivity of 3D printed multi-material sensors employing rolling technics and studying ironing printing parameters: the latter increased the sensitivity of the 3D printed sensors of 83%, due to 50% void reduction. A new approach to fabricate self-healing smart structures was also explored: a custom-made 3D printing machine capable of extruding both filament- and ink-based self-healing materials was developed. An innovative Separate Heating System (SHS) was implemented to better control pre-extrusion and extrusion temperatures via PID, resulting in improved mechanical, geometrical, healing (95%), and sensing performance of the 3D printed sensors.
Finally, a comprehensive review of MEX 3D printed batteries was presented, highlighting problems, challenges, and advancement in this new field. The literature review envisions the futuristic possibility of one-shot 3D print devices composed of sensors, actuators and batteries, ready to be used after their removal from the 3D printing platform
Schrödinger equation in dimension two with competing logarithmic self-interaction
No full textIn this paper we study the equation (Formula presented.) where 8/3<4. By means of variational arguments, we find infinitely many radially symmetric classical solutions. The main difficulties rely on the competition between the two nonlocal terms and on the presence of logarithmic kernels, which have not a prescribed sign. In addition, in order to find finite energy solutions, a suitable functional setting analysis is require
From single to multi-risk perspective: How heatwaves risk mitigation solutions can reduce terrorist risk in historic outdoor open areas
No full textHistorical outdoor Open Areas (hOA) are relevant “hot-spots” in urban built environments, attracting many users due to morphological and use-related features. Besides significant heritage vulnerability, hOAs can also be affected by critical levels of users’ exposure and vulnerability, exacerbating the effects of natural and anthropogenic risks. Mitigation solutions for one risk may impact others due to mutual interactions among different phenomena, necessitating multi-risk evaluations. This work focuses on how heatwaves-mitigation solutions (“slowly” impacting how users behave and gather in hOAs) can support risk-reduction for terrorist acts (“suddenly" striking users and implying evacuation) emerging in heatwaves-affected scenarios and, thus, multi-risk mitigation. To this end, an innovative approach for hOAs multi-risk analysis methodology is applied to a relevant case study (Piazza dell’Odegitria, Bari, Italy), using previously validated behavioural-based simulators. Original and post-retrofit (involving sustainable/highly reversible/compatible strategies with historical and cultural relevance of the place) scenarios are compared through multi-risk metrics, by analysing effects on hosted users. Results suggest remarkable and effective multi-risk reduction (>15 %) by combining, at least, cool pavement and barriers implemented with green elements. Moreover, the findings highlight the approach's capability to support policymakers in sustainably evaluating and comparing different scenarios for preliminary analyses of mitigation strategies
Local Generalized Nash Equilibria with Nonconvex Coupling Constraints
No full textWe address a class of Nash games with nonconvex coupling constraints for which we define a novel notion of local equilibrium, here named local generalized Nash equilibrium (LGNE). Our first technical contribution is to show the stability in the game theoretic sense of these equilibria on a specific local subset of the original feasible set. Remarkably, we show that the proposed notion of local equilibrium can be equivalently formulated as the solution of a quasi-variational inequality with equal Lagrange multipliers. Next, under the additional proximal smoothness assumption of the coupled feasible set, we define conditions for the existence and local uniqueness of a LGNE. To compute such an equilibrium, we propose two discrete-time dynamics, or fixed-point iterations implemented in a centralized fashion. Our third technical contribution is to prove convergence under (strongly) monotone assumptions on the pseudo- gradient mapping of the game and proximal smoothness of the coupled feasible set. Finally, we apply our theoretical results to a noncooperative version of the optimal power flow control problem
Risk management in wine supply chain: A state-of-the-art analysis
No full textAlthough the wine market is experiencing significant growth, the Wine Supply Chain (WSC) remains remarkably fragile and susceptible to risky events that can impact vine health and wine quality. These factors, in turn, affect the performance of the entire chain. The distribution of vineyards is highly diverse, and in some cases, situated in extremely fragile territories. The evolution of climate change further exacerbates these vulnerabilities, exposing farms to several risks that, if not properly managed, can threaten production. To navigate the highly dynamic environment characterizing the Wine Supply Chain, there is an increasing need for proactive strategies through the introduction of tools that assist managers in avoiding and/or mitigating potential risks within the value chain. These strategies aim to preserve product quality and integrity, enhancing the resilience of the entire WSC. Despite the higher relevance of risk management in wine than in other agricultural industries and related supply chains, as the raw-material transformation constitutes high-level value-added processes, the scientific literature seems to lack an overall analysis related to the risk strategies and methods developed over the last years in the field of WSC. Therefore, the primary objective of this research is to provide a comprehensive analysis of the current state of Risk Management in the Wine Supply Chain. The study aims to: (i) identify the main processes and associated risks, (ii) establish the primary methods and tools developed by researchers to date, and (iii) highlight the key gaps that need to be addressed. The findings indicate a growing focus on agricultural risk events and reveal a lack of comprehensive methods that encompass the entire Wine Supply Chain - from farmers to end consumers - despite technological advancements in agriculture, logistics, and production. This gap underscores the need for integrated risk management approaches to prevent the degradation of business performance