Politecnio die Bari - Catalogo di prodotti della Ricerca
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On the lubricant oil potential to serve as auto-ignition centre in hydrogen engines: reactivity alteration, chemical ignition, and propagation modes
No full textThe present study intends to investigate whether a suspended lubricant oil droplet in a H2/air environment can initiate an undesired local self-ignition of the charge, while also providing preliminary insights into the nature of the combustion event that might result. A relatively simple analytical model was developed to derive plausible distributions of the temperature and oil vapour mass fraction around the droplet. Based on these results, zero-dimensional numerical simulations were conducted within the OpenSMOKE++ framework to quantify alterations in charge reactivity in the vicinity of the oil droplet induced by temperature and composition inhomogeneities. The “HyLube” chemical model, developed specifically for this purpose in a previous recent work, was employed in the simulations to emulate the reactivity properties of the H2/oil/air mixture. Thermodynamic conditions comparable to those achievable in the cylinder of an internal combustion engine at the end of the compression stroke were considered. The auto-ignition propagation modes potentially arising from the oil-droplet-induced contamination were then assessed through an analysis based on the comparison between the characteristic times of the reaction and the acoustic waves. To this end, the concept of a “hot spot” serving as the auto-ignition centre originally conceived in the related theory developed by Bradley and colleagues, has been extended to that of a “sensitive spot”, including composition variations. Finally, it was verified whether the energy released by the low-temperature chemical activity suffices to ignite the combustible mixture in the vicinity of the droplet and effectively initiate an uncontrolled combustion process. The findings reveal the capability of lubricant oil to alter the charge reactivity and promote early flame development within the combustion chamber of hydrogen-fuelled engines
SoilEye: An Interactive Web App Prototype for Soil Sealing Monitoring
No full textClimate change problems are intensifying rapidly, making it essential to monitor environmental and geospatial issues in real time. With the advent of cloud computing, researchers and experts can develop more sustainable solutions in a shorter timeframe. In the geospatial field, the introduction of Google Earth Engine has been a game changer. As a powerful cloud computing platform, Google Earth Engine enables large-scale geospatial analysis by leveraging extensive public data and open-source geospatial datasets. One of the most impactful features introduced by such a tool is creating a web-based application, known as Google Earth Engine Apps. These Apps allow users to visualize, modify, share, and interact with their analysis, results, and outputs in real time. This paper focuses on the creation of “SoilEye”, an innovative Google Earth Engine App designed to observe soil sealing patterns over the metropolitan area of Bari. It provides a detailed, step-by-step methodology for developing the app, highlighting its potential and functionality. This app tracks land use changes over approximately six years, from 2018 to 2024, by combining satellite images collected by the Sentinel 2 mission with other geospatial data. It identifies places that have been impacted by soil sealing and evaluates its trend over time. As a result, this App will serve as a valuable tool for policymakers, offering an interactive platform to monitor soil sealing dynamics continuously. This will aid the sustainable urban environment management and help planners make more informed decisions
Optimizing personnel allocation: An integer linear programming problem for enhanced workplace efficiency
No full textIn large organizations, the allocation of personnel within office spaces presents significant challenges, particularly with the adoption of modern working methodologies such as smart working, co-working, and agile working. This paper addresses the optimization of workspace assignments to balance occupancy levels while ensuring cohesion within organizational units and compliance with individual work schedules. The proposed approach incorporates constraints to prevent overcrowding, maintain consistent desk assignments, and enforce separation between specific personnel groups. A multi-objective Integer Linear Programming formulation is developed and validated through a real case study. Results demonstrate that the methodology effectively reduces peak occupancy imbalances and strengthens team cohesion, providing human resources departments with a practical decision-support tool that requires minimal technical expertise. The solution features an intuitive web interface that facilitates efficient space management in dynamic working environments
Investigation of the role of photoacoustic phase in N2O(v) vibrational relaxation rate determination
No full textThis study investigates the relaxation dynamics of the ν3 energy level of nitrous oxide (N2O) molecules in synthetic air using a 4.5 μm distributed feedback quantum cascade laser (DFB-QCL) combined with photoacoustic spectroscopy (PAS) technique. A comprehensive theoretical model coupling vibration-translation (V-T) relaxation processes and vibration-vibration (V-V) energy transfer was developed, enabling a rigorous theoretical derivation of the system-wide vibrational relaxation time. Through in-depth analysis of photoacoustic signal phase characteristics, the molecular relaxation times of both N2O (ν3) (1.6 μs atm) and H2O (0.33 μs atm) were simultaneously extracted. Thorough cross-validation against literature values demonstrated that photoacoustic phase information serves as a highly sensitive probe for detecting gas molecular energy relaxation processes. This research not only validates the technical feasibility and analytical superiority of PAS phase technology in measuring gas relaxation times but also introduces a novel high-precision spectroscopic analysis method for studying vibrational dynamics in complex molecular systems, showcasing its potential applications in environmental monitoring and molecular dynamics research
Monitoring Long-Term Trends in Aglianico Vineyards Using a Mann-Kendall Test Approach, Sen's Slope Estimator, and Sentinel-2 Time Series
No full textThe vineyard sector is a key economic driver in the Mediterranean Basin, particularly in Italy, requiring a scientifically sound management plan to optimize yield and quality. Geomatic techniques provide a fast, cost-effective, and non-destructive way to collect data, with remote sensing excelling in long-term grape monitoring. The Sentinel-2 mission, launched by the European Space Agency in 2015, captures multispectral images with spatial resolutions of 10 m, 20 m, and 60 m, depending on the spectral band. While this resolution does not allow for detailed analysis at the scale of individual grape rows or leaves, it enables vineyard monitoring at the field scale with medium spatial resolution. This study explores the potential of Sentinel-2 data for analysing long-term trends using two non-parametric statistical methods: the Mann-Kendall test and Sen’s slope estimator. The former detects monotonic trends, while the latter quantifies the magnitude of change over time. A time series of Sentinel-2 imagery, comprising 1,348 images spanning a ten-year period (2015–2025), was collected and pre-processed. After cloud masking and resampling all bands to a 10m spatial resolution, four vegetation indices were computed and subjected to statistical analysis. The resulting maps served as input for the aforementioned non-parametric tests. Findings highlight the effectiveness of a well-structured management plan, though certain areas require closer attention. In particular, all statistical tests consistently indicate negative long-term trends in the lower portion of the field. These results emphasize the necessity of integrating geospatial big data to enhance decision-making, surpassing the limitations of management strategies based solely on farmers’ experience
Piezoelectric tuning forks employed as photodetectors for hydrogen sensing
No full textA study on the H2 spectral properties and a comparison between two different piezoelectric resonators employed as infrared detectors for hydrogen sensing are reported. A quartz tuning fork (QTF) and a lithium niobate tuning fork (LiNTF) are implemented in the same light-induced thermoelastic spectroscopy experimental set-up, employing i) a laser diode to target the hydrogen absorption feature at 4712.90 cm−1, characterized by low interference from other contaminants; ii) a multi-pass cell with a 10.4 m pathlength, to enhance the interaction between light and H2 molecules. Both resonators demonstrate a linear response with respect to the hydrogen concentration and a minimum detection limit (MDL) of 0.50 % and of 1.50 % at 0.1 s of integration time with the QTF and the LiNTF, respectively. The long-term stability analysis highlights a bias instability for the QTF, mainly addressed to the inhomogeneities at the edge of the active area. Conversely, the uniform surface of the LiNTF returns a highly stable detection, allowing an MDL as low as 0.1 % at 64 s of integration time. This first demonstration of a LiNTF as photodetector paves the way to the realization of fully integrated sensors based on lithium-niobate-on-insulator platforms
Urban Green Spaces and Housing Prices: The Impact of Metric Choice on Econometric Models
No full textIt is widely recognized that green urban areas play a significant role in enhancing environmental quality, social and economic well-being within cities. In the context of urban planning and sustainable development, the study of their impact on housing prices can guide administrations more effectively in the design and allocation of green spaces. However, the choice of metrics for this purpose has the potential to influence the results. The present study aims to investigate how the choice of urban green space metrics influences the econometric analysis of real estate prices in a densely populated Italian city. The case study focuses on the city of Rome, which, being one of the European capitals with the largest extension of green urban surface, represents a particularly relevant context for investigating the effects on real estate values. The investigation employs a regression-based methodology, utilizing three green space metrics: total absolute surface, percentage coverage, and the presence or absence of green areas. The dependent variable in this study is housing prices, while the independent variables relate to socio-economic and environmental issues, including construction and social quality. The findings of this study underscore the significance of judicious selection of metrics in order to achieve reliable results. In contrast to the extant literature, which has hitherto concentrated exclusively on the presence of green spaces, this research examines how different metrics influence their estimated impact on property values. The findings offer valuable insights for urban planners and policymakers in optimizing the integration of green spaces into urban valuation models
On certain surface integrals related to the conormal derivative problem
No full textThe non-homogeneous conormal derivative problems for nonlinear, second-order divergence form elliptic equations with singular data appear naturally in mathematical modeling of real phenomena involving problems of image recovery, the thermistor problem, or studies of non-Newtonian fluids.
We prove suitable estimates for certain surface integrals, related to non-homogeneous conormal derivative problems, which lead to essential boundedness of the weak solutions under quite general hypotheses on the data
