Higher Institute on Territorial Systems for Innovation
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Prime tracce per una "Basiliade" lombarda
Get PDFFrutto della collaborazione tra il Ministero della Difesa e alcune università italiane – Bologna, Cagliari, Politecnico di Milano e di Torino, Università di Trento e IUAV di Venezia – questo volume rappresenta una visione di come il nostro patrimonio architettonico e storico possa essere preservato e valorizzato nel contesto di una città metropolitana in continua espansione.
Il progetto di ampliamento funzionale per l’Ospedale militare di Baggio, elaborato dal gruppo del DAD-Politecnico di Torino, trova una sua legittimazione attraverso alcune significative costanti della formazione urbana di Milano che vedono nell’assistenza e nella cura, ma anche nell’accoglienza e nell’ospitalità – estesa all’intera dimensione lombarda – un carattere identitario del tutto singolare in molti casi radicato contestualmente nella tipologia del recinto. Così, se per l’irrisolta Piazza d’Armi di Milano sembra pertinente il rimando allo straordinario segno antoliniano per l’incompiuto Foro Bonaparte, per l’area dell’ospedale militare – organizzata attraverso la ridistribuzione delle attività sanitarie già presenti (ambulatori, sale comuni, uffici, refettorio) – la nuova pista di atletica, a quattro corsie, per le prove fisiche militari, aperta anche ad un uso pubblico, diviene fulcro principale nel ridisegno dell’impianto generale
Solar-driven membrane distillation with direct ambient-temperature feed heating: design, modeling, and experimental validation
Get PDFFreshwater scarcity in off-grid regions necessitates the development of simple and sustainable desalination systems. Conventional membrane distillation (MD), while promising, typically relies on external preheating and complex solar collectors, limiting its compactness and practical applicability. This study presents the design, numerical modeling, and experimental validation of a compact direct contact MD prototype powered exclusively by distributed solar energy. The system operates without external feedwater preheating or centralized solar collectors. Instead, the custom-built module integrates a solar absorber directly into the top surface of the feed channel, enabling direct solar heating of the ambient-temperature feed stream. The flat-sheet module employs reduced channel thickness to enhance thermal coupling and minimize temperature polarization. An extensive experimental campaign was conducted under realistic conditions, covering a broad range of feed flow rates. A numerical model was developed to simulate coupled heat and mass transfer processes, and validated against experimental results, showing strong agreement. The model was subsequently used to explore alternative configurations and guide system optimization through internal heat recovery. A promising thermal management strategy is thus introduced, enabling simultaneous feed preheating and permeate cooling, thus increasing effective transmembrane temperature difference without additional energy input. A maximum distillate flux of 0.51 +/- 0.02 kg m-2 h-1 was achieved under 1000 W m-2 solar irradiation, representing 59% improvement over comparable tested systems lacking internal heat recovery. Results demonstrate the feasibility of a modular and scalable system suitable for off-grid or decentralized water purification. Future work will investigate multistage implementations and integration with alternative low-grade heat sources
Aeroacoustic impact of heat exchanger installation in an industrial engine cooling module
Get PDFEngine cooling fan noise becomes even more difficult to predict when considering the presence of the heat exchanger upstream. This paper investigates the impact of different heat exchanger installations on the noise sources of an industrial engine cooling fan using high-fidelity lattice-Boltzmann simulations. The heat exchanger is simulated using an equivalent porous medium upstream of the fan. Four configurations are analyzed at free discharge: full cooling module (i) without and (ii) with a gap between the heat exchanger and its casing, (iii) Fan+Frame, and (iv) Fan. For the sake of comparison, configurations (iii) and (iv) are simulated by imposing a pressure difference that matches the one across the heat exchanger, to ensure that the same operating point is maintained. Results show negligible differences in the overall aerodynamic performance since the same average pressure rise is achieved. The presence of the porous medium affects the spatial distribution of the pressure field upstream of the fan, thus causing a higher tonal content compared to the configurations (iii) and (iv). Further subharmonic humps are caused by the interaction of the blades with vortex structures generated by flow separation at the tip and the casing’s support structures. The presence of a geometry transition from square to round in the casing causes inflow distortions, increasing low-frequency broadband noise
Printed Zinc Tin Oxide Memristors for Reservoir Computing
Get PDFIn this work, fully patterned zinc tin oxide (ZTO) memristors are introduced using inkjet printing. By targeting a scalable, solution-based fabrication approach, highly stable devices with excellent reproducibility and minimal variability are achieved, using ZTO as the active layer, silver (Ag) as the top electrode, and molybdenum as the bottom electrode. The use of sustainable materials like ZTO enhances scalability and environmental compatibility, paving the way for next-generation, low-power neuromorphic computing. The devices successfully fulfill the fundamental criteria for in materia implementation of physical reservoir computing (PRC), including nonlinearity and fading memory property. The devices are successfully trained for classification tasks with MNIST handwritten dataset, achieving 89.4% accuracy and 86.5% by processing 4-bit and 5-bit input temporal sequences. The integration of printed memristors into hardware-based PRC architecture simplifies training complexity, making them particularly advantageous for energy-efficient, wearable AI systems
Full-wave modeling of arcs within the ITER ICRF antenna for usage in the simulations and design of the RADAR Arc Detection system
Get PDFThe ITER ICRF antenna has been carefully designed to feature electrical fields below tolerable limits (typically, below 2 or 3 kV/mm depending on the location and orientation) when operating at a maximum voltage of 45 kV. In particular, this allows avoiding arcs. However, as for any high-power RF system, arcs can still occur in the ICRF antenna and its power feeding system, during normal operation and especially during the commissioning. Whenever an arc is detected, the RF power shall be immediately tripped (μs timescale) to avoid strong local energy deposition at the location of the arc. Undetected arcs are forbidden. To this aim, several complementary and redundant Arc Detection (AD) systems are foreseen to protect the ITER ICRF antenna. Among these AD systems is the RADAR Arc Detection (or RAAD [2]) which is currently under evaluation for implementation on the ITER ICRF system To provide a first numerical proof of concept of RAAD, full-wave simulations of the ITER ICRF antenna and its power feeding transmission lines have been performed in the radar bandwidth of operation (up to 350 MHz) with the help of CST Studio Suite and ANSYS HFSS commercial codes. In these simulations, the plasma loading has been approximated by a salty water load (with a relative dielectric permittivity 80 and electrical conductivity 1 S/m), while arcs have been modelled with both perfect electric conductor (PEC) cylinders or lumped element shorts. The obtained S-matrices have been then loaded and processed by the RAAD timedomain circuit simulations and signal processing calculations. This paper describes the challenges to simulate the full ITER ICRF antenna with arcs, considering different loading conditions, different materials and different solutions for the arc insertion. It also provides a comparison of the scattering parameters with and without arcs
Early warning in Molten Salt Fast Reactors based on a data-driven method for the online incident detection and diagnosis
Get PDFThis paper presents an innovative online incident detection and classification method, which aims at improving the safety, reliability and availability of Molten Salt Fast Reactor (MSFR) power plant, focusing on scenarios characterized by deviations from normal operational conditions. The first part of the paper is devoted to describing and discussing the proposed online data-driven incident detection and classification methodology (based on adaptive Singular Value Decomposition-SVD and kNN algorithm), which aims at identifying abnormal plant conditions thanks to a continuous monitoring of some measurable parameters and variables (e.g., the molten salt temperatures in the secondary circuit). The developed incident detection algorithm is trained on a set of simulated scenarios featured by deviations of the main MSFR plant parameters from their nominal values. The data-driven model is then assessed considering increasingly complex incident classification rules and tasks, showing satisfactory performances in detecting and classifying plant anomalies (with an accuracy ranging between 89 % and 99 %). Finally, a fault diagnosis framework is proposed to carry out probabilistic inference on the most likely root causes (or precursors) - e.g., combinations of physical parameter values and component failures - that lead the system to the detected abnormal states
Enhancing E-Voting with Multiparty Class Group Encryption
No full textCHide is one of the most prominent e-voting protocols,
which, while combining security and efficiency, suffers from having very
long encrypted credentials. In this paper, starting from CHide, we propose a new protocol, based on multiparty Class Group Encryption (CGE)
instead of discrete logarithm cryptography over known order groups. We
achieve a computational complexity of .O(nr), for . n votes and . r voters,
while calling the MixNet algorithm one time. The homomorphic properties of CGE allow for credentials that are shorter by a factor of 20 while
maintaining the same level of security, at the cost of a small slowdown
in efficiency
Mapping Urban Resilience Responses: Testing a Spatial Indicator Approach in Turin
No full textThe complex and dynamic nature of urban resilience makes it both essential and challenging to define an appropriate qualitative-quantitative approach for its measurement that combines context-sensitive indicators with spatial analysis. The method proposed in this paper balances standardised frameworks with local specificity through the application of selected resilience indicators in the city of Turin (Italy). By spatially mapping territorial response elements related to natural vulnerabilities and socio-institutional dynamics, it emphasises cross-sectoral integration for effective resilience strategies for spatial planning. It further stresses the importance of developing actionable indicators capable of informing planning tools and supporting adaptive, inclusive territorial governance. These insights are useful for the ongoing revision of Turin’s land use plan and other supra-local planning tools, aiming to address socio-economic and environmental challenges more cohesively
Lead-free perovskites and derivatives for photogeneration: a roadmap to sustainable approaches for photovoltaics and photo(electro)catalysis
Get PDFThis roadmap provides a comprehensive overview of the latest advancements in lead-free perovskite materials for photovoltaic and photoelectrochemical /photocatalytic applications. It highlights the urgent need for sustainable energy solutions, emphasizing the role of lead-free perovskites in addressing challenges related to toxicity, scalability, and efficiency. The roadmap is designed to guide the reader from application-driven perspectives to fundamental materials insights, characterization techniques, fabrication strategies and overreaching sustainability considerations. The document explores key material families, including tin-, bismuth-, antimony-, and copper-based perovskites, detailing their optoelectronic properties, fabrication techniques, and application potential. Special attention is given to advanced characterization methods, green processing strategies, the integration of artificial intelligence and machine learning for material design and optimization and lifecycle impact assessments to ensure environmental sustainability. By bringing together insights from global research communities, this roadmap serves as a strategic guide for advancing lead-free perovskite technology, fostering interdisciplinary collaboration, and accelerating the transition to next-generation solar energy solutions