Politecnio die Bari - Catalogo di prodotti della Ricerca
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Analysis of an asymptotic thermofluid dynamic model for parabolic trough power plants
No full textParabolic trough power plants transform solar radiative energy into thermal energy which is then typically used
to produce electricity. We consider a model derived in [2,3] to describe parabolic trough power plants. In particular, the
thermofluid dynamics is studied in a single collector pipe where the solar radiation is concentrated. The model is the result
of simplifying assumptions and asymptotic processes on the underlying mass, momentum and energy balance equations.
We show existence of solutions for the model. In addition, we study the longtime behavior and the stationary problem
On-Chip Biosensing and Gas Sensing by Photonic Slot Waveguides: A Review
No full textPhotonic slot waveguides enhance light-matter interactions by confining the optical field in regions with a low refractive index, making them highly effective for detecting a wide range of biological and chemical analytes. This article reviews the application of photonic slot waveguides in biosensing and gas sensing, showcasing their ability to be integrated into on-chip platforms often intended for point-of-care testing with enhanced sensitivity and specificity. In biosensing, these waveguides are particularly suited for applications in medical diagnostics and environmental monitoring, allowing for the detection of biomarkers and other biological molecules with high sensitivity. For gas sensing, photonic slot waveguides have been employed effectively in the near-infrared and mid-infrared spectrum to detect various gases, including hazardous and greenhouse gases, which is crucial for both industrial safety and environmental protection. This review also explores the potential of these waveguides in noninvasive diagnostic methods, such as liquid biopsy, breath analysis, and breath biopsy, which offer new avenues for early disease detection and monitoring. By summarizing recent advancements and outlining future directions, this review underscores the transformative potential of photonic slot waveguides in advancing on-chip sensing technologies across multiple fields
Temperature-Induced Effects on Wet-Spun Artificial Spider Silk Fibers
Full text linkSilk-based materials are sought after across various industries due to their remarkable properties, including high strength and flexibility. However, their practical application depends largely on how well these properties are maintained under different environmental conditions. Despite significant advancements in the large-scale production of artificial silk fibers, the effects of temperature on their mechanical behavior are understudied. In this study, the mechanical properties of artificial spider silk fibers between −80 and +120 °C are examined and compared to both synthetic and natural silk fibers. The findings reveal that artificial silk fibers maintain their strength up to +120 °C, though the strain at break slightly decreases, remaining above 60%. At −80 °C, the fibers exhibit increased strength, but the strain at break is reduced. While these artificial fibers closely mimic the behavior of natural silk, they show a noticeable reduction in extensibility at low temperatures. Complementing experimental data, differential scanning calorimetry, and thermogravimetric analysis are also conducted, proposing a simple physical model to explain the observed temperature-induced softening. Encouragingly, the degradation temperature of artificial silk is comparable to that of native silkworm and spider silk. This study underscores the importance of enhancing the mechanical robustness of artificial silk to expand its applications
A novel mode shape identification approach for structures having planes with rigid-like behavior
No full textThe identification of mode shapes of structures through Operational Modal Analysis (OMA) often requires the application of data merging techniques to compensate for the lack of information on mode shapes scaling factors, which is inherent in OMA. In this paper, we propose a novel mode shape identification approach for structures having planes with rigid- like behavior, such as steel or reinforced concrete buildings with rigid floors. The approach is based on a theoretical model that generalizes the mechanical features of the structures under considerations. We show that the mode shapes of the model can be reconstructed starting from two components, i.e., modal centers of rotation and modal rotations; modal rotations depend on scaling factors of mode shapes, while modal centers of rotation turn out to be invariant with respect to mode shape scaling. Afterwards, we develop a method for identifying modal centers of rotation and modal rotations from experimental data, and then for reconstructing mode shapes. Numerical experiments have been performed to assess the capability of the approach with respect to a structural specimen having known modal properties. Compared with classic merging techniques, our approach enables a significant simplification of the experimental setup and a deeper analysis of mode shapes
Digital Product Innovation Within Family Firms: A Construal Level Perspective
No full textDigital product innovation (DPI) is critical for the survival of firms, especially those operating in traditional industrial-age industries. While research has started to investigate digital innovation in family firms (FFs) considering them as a monolithic group, we still lack a more nuanced perspective that considers heterogeneity among FFs with respect to DPI and what drives such variance. Drawing on construal level theory to explain the risk behavior and goal time horizon of FF owner-managers, we propose and find that the presence of later family generations in control positively influences DPI in FFs, while the presence of a family CEO is detrimental to DPI. Furthermore, we propose that these relationships are moderated by the size of the top management team (TMT), finding that a larger TMT weakens the positive relationship between later generations in control and DPI. We base our analysis on a longitudinal sample of 103 FFs in the automotive, industrial engineering, and pharmaceutical sectors observed from 2013 to 2020. This first empirical study applying construal level theory to the family business literature has important implications for the FF digital innovation literature and for FF owner-managers interested in achieving DPI
How obstructed jets experience detrainment
No full textA comprehensive understanding of turbulent jets discharged into obstructed environments remains a critical gap in the current literature. This issue holds significant importance for applications ranging from environmental fluid dynamics to industrial processes. The primary goal of this study is to theoretically investigate the dynamics of planar turbulent non-buoyant jets interacting with arrays of rigid obstacles, supported by a comparison between theoretical predictions and experimental data. Specifically, our analysis focuses on the entrainment process, revealing that obstructions in non-stratified flows impede entrainment, reversing it into detrainment. This finding is novel because (i) detrainment in natural settings is typically associated with buoyancy-driven flows, such as plumes or density currents in stratified environments, and (ii) to the best of the authors' knowledge, this is the first validation of theoretical entrainment coefficients with experimental data for obstructed non-buoyant jets. Experiments were conducted with turbulent non-buoyant jets using particle image velocimetry, providing detailed insights into flow structure and entrainment dynamics. Furthermore, the study explores jet particle dispersion and diffusivity through a Lagrangian framework. The results demonstrate significant differences in dispersion behavior between unobstructed and obstructed jets, showing that obstacle-induced blockage profoundly influences flow characteristics and jet detrainment. In particular, obstructions play a fundamental role, initially affecting the dispersion mechanism through obstacle diameter and later through the free spacing between obstacles. These findings provide valuable contributions to understanding flow physics in complex environments and have implications for engineering and environmental applications
Dinamiche innovative: alloggi temporanei e cambiamenti demografici. Verso nuove frontiere di innovazione e rigenerazione
No full textL'indagine esplora gli alloggi temporanei per studenti nel contesto dei cambiamenti strutturali nella società contemporanea. Un consenso diffuso suggerisce che la crescita urbana e l'innovazione siano direttamente proporzionali allo sviluppo del capitale umano e sociale, con la costruzione di "comunità di apprendimento" come elemento chiave (Longworth).
La città contemporanea affronta trasformazioni significative, tra cui la riduzione e trasformazione dei nuclei familiari, la crescente mobilità degli abitanti e la necessità di alloggi temporanei per rispondere alla transitorietà delle dinamiche sociali ed economiche. Questo dinamismo urbano, alimentato da studenti, docenti, lavoratori temporanei e famiglie in transito, richiede soluzioni abitative flessibili. Il contributo dei campus e dei centri universitari alle dinamiche socio-economiche urbane è ampiamente riconosciuto, ma deve essere opportunamente programmato per evitare interferenze negative e tensioni sociali. Il paper confronta i modelli di “Cittadella dello Studente” e “Città con gli studenti”, evidenziando come il secondo modello, sebbene in crisi, offra maggiori soluzioni per lo sviluppo urbano e sociale. Infine, propone l'adozione di sistemi abitativi misti diffusi a livello urbano come soluzione per il fabbisogno abitativo e il rafforzamento dei legami sociali e culturali nelle città italiane
Modellazione numerica sperimentale a supporto della Artificial Neural Network: valutazione predittiva della resistenza all’accelerazione di collasso tramite curve di progetto degli edifici in muratura
Full text linkThe aim of this research is to develop an innovative and efficient methodology for the expedited
assessment of seismic vulnerability in masonry buildings, leveraging the capabilities of
artificial neural networks (ANN) integrated with an experimental numerical modeling
approach. Following catastrophic seismic events, masonry structures are often significantly
compromised, resulting in their classification as unsafe and uninhabitable. Traditionally, the
evaluation of such buildings relies on qualitative assessments performed by inspectors, who
provide preliminary estimates of structural reliability based on visual inspection and
experience. However, this process is inherently subjective and prone to inaccuracies, leading to
potential misclassifications that can either overestimate or underestimate the actual risk posed
by these structures.
To overcome these limitations, the proposed research adopts a machine learning framework,
specifically an ANN, to estimate the seismic response of masonry buildings with rectangular
geometries. This method allows for a comprehensive and data-driven evaluation of structural
vulnerability by incorporating a wide range of building geometries and material properties. The
study considers twelve distinct building geometries, twenty-four unique combinations of
mechanical parameters, and five different seismic loading directions, resulting in the simulation
of 34,560 configurations. These extensive simulations were then summarized through a
synthetic polynomial representation, which efficiently encapsulates the complexity of the
dataset while enabling streamlined analysis.
The ANN was trained, tested, and validated using results from an experimental numerical
approach grounded in the Distinct Element Method (DEM), a well-established analytical
method for the assessment of structural behavior under seismic loads. The performance of the
ANN, when compared to DEM-generated results, demonstrated a high level of accuracy, with
predictions differing by approximately 10%.
This confirms the viability of using machine learning techniques for the reliable prediction of
seismic performance in masonry structures. The primary outcome of this research is the
development of a comprehensive database of design curves, which can be employed for the
rapid assessment of the seismic vulnerability of masonry buildings. These design curves offer
a practical tool for engineers and decision-makers in the aftermath of earthquakes, providing a
quantitative and objective basis for classifying buildings as safe or unsafe.
The proposed methodology represents a significant advancement over traditional assessment
techniques, which are often limited by their reliance on subjective judgment. By combining
machine learning with established numerical methods, this research contributes to the
development of more reliable and scalable tools for the assessment of building safety in seismicprone areas
A sulfur dioxide detection platform based on photoacoustic spectroscopy and a 266.22 nm high-power stabilized LD-pumped solid-state Q-switched laser
Full text linkA ppb-level sulfur dioxide (SO2) monitoring platform was developed by exploiting standard photoacoustic spectroscopy and a novel, highly stable UV laser. A 266.22 nm LD-pumped solid-state, acousto-optic modulator Q-switched laser with high beam quality (M2 =1.0275) and excellent output optical power stability (δPσ ˂ 1 % ∼24 h) was selected as light source of the photoacoustic sensor. The performance of the SO2 sensor was evaluated in terms of gas flow rate, pressure, and detection sensitivity. An ultimate detection limit of 3 ppb for SO2 detection in N2 was demonstrated with 1 s integration time, in laboratory environment. Continuous outdoor monitoring for five days verified the excellent stability and reliability of the reported SO2 photoacoustic sensor
Large eddy simulation of a turbulent submerged jet interacting with a wave environment
No full textAbstract We use numerical simulations to study the interaction between a turbulent jet, discharged vertically from a circular nozzle at the bottom of a horizontal liquid layer of height h0 = 0.35 m, and surface waves. All simulations are run at a fixed value of the jet Reynolds number (Rej = 20,000, based on the nozzle diameter) and for two different values of the surface waves elevation, H = 0.02 m (simulation R1) and H = 0.03 m (simulation R2). A reference simulation, assuming a free surface without waves, is also performed for comparison purposes (simulation R0). We focus on the influence of the surface waves on the jet flow field, considering in particular the behavior of the jet width and of the mean jet velocity—which we analyze applying a phase-averaged technique. Our results show that surface waves induce a reduction of the vertical component of the jet velocity, and a corresponding increase of the horizontal components of the jet velocity. In particular, we observe that the reduction of the centerline mean vertical velocity (along the vertical direction z) is linear in the region close to the jet nozzle, W0/Wm ∼ z, but can be faster than linear (superlinear) in the region close to the liquid surface, for the larger amplitude waves. Correspondingly, the jet width increases linearly with z, b ∼ C (z/d0), but at a slope C that does depend on the distance from the liquid surface. These findings suggest that surface waves enhance entrainment and dilution, offering insights for improving jet–wave interaction models and parameterizations