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Polynomially oscillatory multipliers on Gelfand–Shilov spaces
No full textWe study continuity of the multiplier operator acting on Gelfand-Shilov spaces, where is a polynomial on of degree at least two with real coefficients. In the parameter quadrant for the spaces, we identify a wedge that depends on the polynomial degree for which the operator is continuous. We also show that in a large part of the complement region the operator is not continuous in dimension one. The results give information on well-posedness for linear evolution equations that generalize the Schr & ouml;dinger equation for the free particle
Fillet radius influence for keyway subjected to fatigue: An investigation on an actual application
No full textThe keyway is a widely employed solution to link a hub with a shaft. This paper underlines the importance of the fillet
radius at the keyway base, highlights the combined effect between bending and torsion and verifies the stress concentra-
tion factors present in the literature thanks to Finite Element Method. Starting from a first analytical analysis of the shaft,
a series of FE analyses were carried out with the aim of understanding why certain shaft failures occurred. In these analy-
ses, the key presence is considered and the torque is transmitted through it. The analysis reveals that standard verifica-
tion could fail for some configurations and for the precise evaluation of the fatigue behaviour, for this reason a numerical
model is always suggested
Simulation-based decision-making framework for sustainable intermodal transport including next-generation freight electric multiple-units
No full textThe objective of this paper is to propose a decision-making framework for evaluating alternative inland freight transport chains with the goal of increasing the use of intermodal transport and reducing negative externalities. Particularly, the combined transportation alternatives considered the use of conventional trains and next generation Freight Electric Multiple Unit (FEMU) trains in Italy. Customs Fast Corridor impact is evaluated, too. The methodological approach relies on Multi-Criteria Analysis (MCA) informed by railway microsimulation and DES models for transport times. The MCA considers also additional factors such as transport reliability, energy performance, greenhouse gases emission and local pollution. The proposed methodology has been applied to the Italian context, comparing all-road and combined transport chains from the port of Genoa to inland destinations ranging from 140 to 1000 kilometers. Results show viability of combined transport starting from around 250 km, lower than the 300 km suggested by European Union
Space–time regression and interpolation of metocean measurements: A focus on satellite data for the offshore energy sector
No full textOcean phenomena are characterised by a degree of complexity that prevents their effective modelling and
simulation, making it necessary to rely on measuring their properties for monitoring and assessments. For these
phenomena, obtaining a complete and exhaustive set of measurements is not trivial. Localised information on
wind and wave conditions is of paramount importance for the proper design of offshore structures and offshore
renewable energy plants. In such cases, a possible way to artificially extend the availability of information is by
using regression and interpolation techniques. This review paper formalises the regression and interpolation
problems with a focus on the offshore energy sector. It then presents the most common in-situ metocean
measuring devices adopted in the offshore applications, followed by a description of the usage of satellites for
performing measurements in this field. Subsequently, a brief description of the most adopted regression and
interpolation techniques in the sector is provided. We review the state-of-the-art adoption of regression and
interpolation techniques for extending measurements of such complex systems, focusing on the application
of satellite measurements in the offshore renewable energy sector. The studies are categorised based on the
family of regression and interpolation techniques applied, with each category further analysed, compared, and
critically assessed. The main findings are reported, highlighting the adoption of machine learning techniques
and the combinations of different regression and interpolation methods adopted to tackle the problems related
to offshore energy sector resource assessment
Concrete Waste and CDW Powders as Portland Cement Replacement in Mortar: A Preliminary Study
No full textThe construction industry’s heavy reliance on Ordinary Portland Cement (OPC) significantly contributes to global CO2 emissions, prompting the search for sustainable alternatives. This study investigates the partial substitution of Portland cement with construction and demolition waste (CDW) powder and concrete waste (CON) powder in mortar mixes. Replacement levels of 5%, 10%, 15%, and 20% by weight were tested following EN 196-1 standards to evaluate the mechanical performance of the resulting materials. X-ray diffraction (XRD), X-ray fluorescence (XRF), and thermo-gravimetric analyses confirmed that CDW and CON powders consist mainly of quartz and calcite, with chemical compositions compatible with cementitious systems. Mechanical testing revealed that compressive strength was maintained or slightly improved at replacement levels up to 10%, while higher substitutions led to moderate reductions due to dilution effects. The use of CDW and CON powders effectively transformed a 52.5 R Type I cement into a 42.5 R Type II equivalent, demonstrating the feasibility of producing sustainable binders with acceptable performance
First Explore, Then Settle: A Theoretical Analysis of Evolvability as a Driver of Adaptation
No full textEvolvability is defined as the ability of a population to generate heritable variation to facilitate its adaptation to new environments or selection pressures. In this article, we consider evolvability as a phenotypic trait subject to evolution and discuss its implications in the adaptation of populations of asexual individuals. We explore the evolutionary dynamics of an actively proliferating population of individuals, subject to changes in their proliferative potential and their evolvability, through mathematical simulations of a stochastic individual-based model and its deterministic continuum counterpart. We find robust adaptive trajectories that rely on individuals with high evolvability rapidly exploring the phenotypic landscape and reaching the proliferative potential with the highest fitness. The strength of selection on the proliferative potential, and the cost associated with evolvability, can alter these trajectories such that, if both are sufficiently constraining, highly evolvable populations can become extinct in our individual-based model simulations. We explore the impact of this interaction at various scales, discussing its effects in undisturbed environments and also in disrupted contexts, such as cancer
A multi-level annotated sensor dataset of gait freezing manifestations and severity in Parkinson’s disease
Get PDFWe present FoG-STAR, a dataset collected using wearable sensors, designed to support the development and evaluation of algorithms for detecting and characterizing freezing of gait (FoG) in people with Parkinson’s disease (PD). The dataset includes recordings from 22 participants who performed a series of standardized motor tasks while wearing four inertial measurement units (IMUs) on the ankles, wrist, and lower back. Each IMU recorded tri-axial accelerometer and gyroscope data. Participants completed seven structured tasks, including walking with/without cognitive/motor dual-tasks, 360-degree turning, and the timed-up-and-go test, which comprises six types of activities (sitting, standing, sit-to-stand, stand-to-sit, walking, and turning). The dataset features detailed annotations from two expert clinical raters, who marked the onset and offset of 101 FoG episodes, and labelled specific FoG manifestations. In addition, the duration of each activity and task segment was annotated. This multi-level annotation framework allows for studying FoG in the context of dynamic motor behavior and provides a valuable resource for the development of machine learning models aimed at FoG detection, severity assessment, and activity recognition in PD
Fuel-based thermal management systems for aircraft electrification: modelling and performance analysis
No full textRecent trends in the context of aircraft propulsion and systems electrification are met with challenges, as new sources of on-board waste heat generation are introduced. The development and optimisation of innovative thermal management systems (TMS) for aviation is a key asset in addressing those challenges. Leveraging the intrinsic thermal capacity of Jet-A fuel appears as a promising solution to provide heat source cooling for both conventional and hybrid-electric aircraft configurations. In this paper, the feasibility of a fuel-based thermal management system (F-TMS) is investigated to support thermal control of fuel cells in the context of hybrid-propulsion electrification for a regional transport aircraft. A modelling approach is proposed for the dynamic simulation of the stored fuel mass and temperature, along with a preliminary investigation of the passive heat rejection through the tank walls. The performance of the F-TMS is simulated for two primary cooling architectures, and their thermal endurance is compared across some realistic flight mission profiles. Finally, the influence of altitude, range and alternate flight is investigated to identify critical scenarios of F-TMS utilisation and derive the maximum degree of supported hybridisation
Recupero e valorizzazione dei depositi ferroviari circolari
No full textIl patrimonio ferroviario è una testimonianza significativa dello sviluppo economico, industriale e tecnologico di un Paese. Esso rappresenta non solo l'evoluzione dei sistemi di trasporto, ma anche i cambiamenti sociali, culturali e territoriali che la ferrovia ha contribuito a determinare. L'infrastruttura ferroviaria è infatti un elemento identificativo che racconta la transizione da un'economia agricola a una società industriale con la creazione di grandi reti nazionali; preservare questo patrimonio significa quindi preservare la memoria di una parte importante della storia recente del Paese. La presentazione si concentra sul deposito ferroviario circolare, ampiamente utilizzato in diversi paesi europei, evidenziando le misure di conservazione, restauro e valorizzazione che sono state realizzate nel deposito ferroviario di Torino, nella rotonda ferroviaria di Chambéry e nei due depositi circolari del Deutsches Technikmuseum e dell'Industriesalon Schöneweide a Berlino
3D printing with biobased epoxidized formulations based on vegetable oils with dynamic polymer network properties
No full textIn this work, we developed and characterized bio-based formulations derived from functionalized vegetable oils, aiming to create sustainable resins suitable for 3D printing with dynamic polymer network (DPN) properties. Epoxidized castor oil (ECO), known for its inherent DPN behaviour due to the presence of hydroxyl groups enabling transesterification, was used as the primary component. However, its high viscosity at room temperature limits its printability. To address this, epoxidized soybean oil (ESO), a less viscous and equally bio-based alternative, was blended with ECO in varying weight ratios: 100% ECO, 100% ESO, ECO–ESO 70–30, and ECO–ESO 50–50. UV-curing characterization of the prepared formulations was performed through FTIR and photo-DSC. Their thermal and mechanical properties were investigated through DMTA and tensile tests, while rheological analyses were conducted to assess their printability. DPN behaviour was evaluated via stress relaxation tests in the presence of a bio-based transesterification catalyst, eugenol-based phosphate ester (EUGP). Among the blends, the ECO–ESO 70–30 formulation retained good DPN dynamics, while in the 50–50 blend, this feature decreased due to the lack of hydroxyl groups in ESO. The DPN systems demonstrated successful 3D printability and were proven to be thermally reprocessable. This work highlights the potential of renewable, plant-oil-based materials in advancing circular and sustainable additive manufacturing technologies