Higher Institute on Territorial Systems for Innovation
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A Two-Step Sub-Sampling Approach for a Computationally Efficient Particle Filter-Based Prognosis
Full text linkSince their introduction, prognostic algorithms based on Particle Filtering (PF) have secured a leading position wherever reliable, grounded, and explainable predictions are required. If this success led to a plethora of research aimed at further enhancing accuracy and explainability, comparatively less attention has been paid to addressing the high computational costs associated with particle propagation. Against this backdrop, this paper approaches the idea of sub-sampling the prediction steps, allowing the propagation of the system state directly between non-consecutive time instants, thus obtaining an optimized trade-off between accuracy and computational effort. In particular, driven by the idea that predictions should be more accurate towards the end of life, this research proposes a novel strategy based on sub-sampling with two different sampling frequencies. The two-phase sub-sampling scheme divides the prognostic horizon into two phases, identifying the ideal set of the three driving parameters: the frequency for the first phase, the switching time, and the higher frequency for the last phase. The computationally intensive tasks are delegated to an offline calibration phase, during which an XGBoost-based recommendation model is trained. In contrast, the online phase involves a single, rapid inference to recommend the optimal configuration, enabling the particle filter (PF) to operate with the selected two-rate propagation strategy while adhering to a user-defined computational time budget. On an experimental Li-ion battery-discharge case study, the framework reduces online computational time by up to 95 percent while keeping the relative error below 3 percent and achieving MAPE lower than 0.52 percent with respect to the standard PF. Comparative analysis demonstrates the framework's capacity to identify an optimal time-error trade-off, thus effectively merging those qualities that have made PF-based approaches the go-to solutions for explainable prognostic with the computational efficiency required for online implementation
Urban Wunderkammer: Physical and Digital Experiences in the Historic Center of Turin
No full textThrough this contribution, the authors aim to illustrate a pathway for the knowledge, communication, and accessibility of urban heritage by utilising and applying current survey and representation tools based on AR technologies. Specifically, the area of focus is Piazza IV Marzo, located in the centre of Turin, whose original Roman layout has been modified over the centuries. Our research begins with a historical and philological study of the square, followed by the acquisition of metric data using a laser scanner. We then develop a three-dimensional reconstruction of the buildings through BIM processes, create a 1:500 scale 3D-printed model of the square, and conduct AR experience tests applied to the scaled model. Harnessing the power of augmented reality and interactive media, our prototype, Urban Wunderkammer, is an attempt to transform a “passive” informational experience into an active and exploratory one, with the potential to revolutionise the way we interact with and understand our urban heritage
Symmetric Bernoulli distributions and minimal dependence copulas
Full text linkThe key result of this paper is to characterize all multivariate symmetric Bernoulli distributions whose sum is minimal under the convex order. In doing so, we automatically characterize extremal negative dependence among Bernoulli variables, since multivariate distributions with minimal convex sums are known to be strongly negative dependent. Moreover, beyond its interest per se, this result provides insight into negative dependence within the class of copulas. In particular, two classes of copulas can be built from multivariate symmetric Bernoulli distributions: extremal mixture copulas and FGM copulas. We analyze the extremal negative dependence structures of copulas constructed from symmetric Bernoulli vectors with minimal convex sums and explicitly find a class of minimal dependence copulas. This analysis is completed by investigating minimal pairwise dependence measures and correlations. Our main results derive from the geometric and algebraic representations of multivariate symmetric Bernoulli distributions, which effectively encode key statistical properties
Kinetics and Redox Activity of Copper/Cerium Mixed Oxides (CuO/CeO 2 ) for Thermochemical Energy Storage Applications
No full textUltra-Wideband System for Museum Visitors Tracking: Towards the Integration of the Positioning System with the Vision Sensors
Full text linkIndoor positioning systems (IPSs) are increasingly applied in indoor settings where satellite-
based GNSS signals are unavailable, including museums and other cultural heritage
spaces. Within the META-MUSEUM project, we present a pilot study integrating an
Ultra-Wideband (UWB) positioning system and an eye-tracking device to monitor and
quantify visitor behavior in a real museum environment. The absence of common times-
tamps between the two systems, and the presence of UWB signal noise, have been the main
challenges to address. A cross-correlation–based synchronization method was developed
to align the two independent UWB and eye-tracking datasets. Data were collected from
100 visitors, of whom 7 different clusters were considered based on the characteristics of the
visitors. The results demonstrate the system’s feasibility and provide two complementary
metrics, Normalized Engagement and Collective Engagement, which are used to quan-
tify the duration and spatial distribution of visitor engagement at specific exhibits. This
work establishes a scalable multi-sensor foundation by addressing practical deployment
challenges under real-world conditions. These findings form the basis for the project’s
broader goal of linking spatial visitor behavior with neurophysiological responses, opening
new possibilities for improving visitor engagement and supporting interactive cultural
heritage experiences
Microstructure, mechanical properties, and fatigue performance of a PBF-LB Al2139ZrTi alloy
Full text linkThis study investigates the microstructure, tensile, and fatigue behavior of post-aged powder bed fused-laser
beam (PBF-LB) Al2139ZrTi alloy, developed by EOS North America. The microstructure exhibits an equiaxed
grain structure with an average grain size of approximately 1.5 μm and lacks any strong crystallographic texture.
It also contains a dense dispersion of fine, uniformly distributed precipitates including: (i) Al3(Zr,Ti) dispersoids
with L12-type structure, acting as semi-coherent nucleation sites that contribute to grain refinement; (ii) a unique
Al3(Zr,Ti) plate-like phase, further confirming Zr–Ti-driven modification of precipitation pathways; (iii) Al
(CuFeMn) and Al(MnCu) intermetallics, notably Al7Cu2 (Fe,Mn) and Al20Cu2Mn3(T-phase), and (iv) Mg oxides,
pointing to minor oxidation during processing. Notably, Al2Cu-based θ′ and Ω phases are sparse, with only coarse
θ-phase particles (~0.5–1 μm) at grain boundaries and fine plate-like Ω-phase (~tens of nm thick) along the
[100] zone axis. Mechanical properties were evaluated via tensile testing, yielding ~ 470 MPa yield stress (YS),
~570 MPa ultimate tensile strength (UTS), and ~ 6.5 % elongation. Conventional (servo-hydraulic) and ultrasonic fatigue tests were performed to cover high cycle and very high cycle fatigue responses spanning up to 109
cycles. Fractographic analyses, including optical and electron microscopy techniques, were carried out to
quantify the crack initiation mechanisms in the mentioned regime
“Campus delle Architetture, del Design e della Pianificazione” Project: WebAR for Public Engagement
No full textThe design of the Politecnico di Torino “Campus delle Architetture, del Design e della Pianificazione” has an enormous strategic value, both for the reorganisation of the University, and for the city dynamics, contributing to the overall development of the Po cultural axis. The transformation involved by the new campus will significantly impact the life of the area, radically changing its intensity with the daily flows of thousands of people and making the park an actual natural connective tissue. The communication project includes the realisation of events aimed at presenting the Campus to disseminate and popularise the outcomes of the realisation process to different stakeholders, showing a scale model of the area. Among the innovative features of the communication proposal is the superimposition of digital layers on the physical model for audience engagement through a webAR that activates a step-by-step journey with descriptions of different aspects of the campus project
Fire Safety Analysis of Alternative Vehicles in Confined Spaces: A Study of Underground Parking Facilities
Full text linkThis study investigates the fire behaviour of Battery Electric Vehicles (BEVs) and Internal Combustion Engine Vehicles (ICEVs) in confined environments such as underground parking facilities and tunnels. Using the Fire Dynamics Simulator (FDS), several scenarios were modelled to analyse the effects of ventilation and automatic suppression systems on fire growth, heat release, and smoke propagation. Three ventilation configurations—reduced, standard, and increased airflow—were evaluated to determine their influence on combustion dynamics and thermal development. Results show that BEV fires produce higher peak Heat Release Rates (up to 7 MW) and longer combustion durations than ICEVs, mainly due to self-sustained battery reactions. Increased ventilation enhances smoke removal but intensifies flames and radiant heat transfer, while limited airflow restricts combustion yet leads to hazardous smoke accumulation. The inclusion of a sprinkler system effectively reduced temperatures by over 60% within 100 s of activation, though residual heat in BEVs poses a risk of re-ignition. This underlines the need for tailored ventilation and suppression strategies in modern underground facilities to ensure safety in the transition toward electric mobility
Filtering acoustic from hydrodynamic velocity using modal decomposition methods on an acoustic liner under grazing turbulent flow
Full text linkThe separation of acoustic-induced velocity from the turbulent velocity fluctuations is tackled on a numerical database representing a segment of an acoustic liner subjected to a grazing acoustic wave and turbulent flow. This scenario is meaningful due to the challenge of distinguishing sound-induced fluctuations from aerodynamic ones, and it has practical implications on the estimation of the liner’s impedance and sound absorption properties. The separation is performed employing modal decomposition methods: proper orthogonal decomposition (POD), spectral proper orthogonal decomposition (SPOD), and canonical correlation decomposition (CCD). The acoustic-induced velocity is reconstructed by selecting a limited number of modes representative of the acoustic-induced flow. All the decomposition methods are influenced by the acoustic-to-hydrodynamic fluctuation ratio, i.e., the relative amplitude of the acoustic waves and turbulent fluctuations. The CCD and SPOD outperform POD when the acoustic amplitude is low compared to the flow turbulence intensity. The acoustic forcing frequency must be known a priori or easily identifiable in the spectrum for SPOD. CCD better captures non-linear effects, e.g., due to the vortex shedding at high sound pressure levels, which are associated with high-order modes