Politecnico di Milano
Recent publications
The Inverse Finite Element method (iFEM), employing a network of strain sensors installed on a structure reconstructs the displacement field independently of the structural loading conditions and material properties. However, the solution is compromised when the sensor network, due to logistic or cost constraints, is sparse and measureless finite elements are present. To overcome this issue the iFEM minimizes a weighted functional, assigning smaller weights to the elements missing experimental measures. Strain field pre-extrapolation techniques have been proposed to improve the iFEM performance, although still assigning arbitrarily small weights to the extrapolated strains. The current paper proposes a Gaussian Process as the pre-extrapolation technique for the strain field, which natively incorporates measurement uncertainty, therefore providing a metric to assign the functional weights, as well as confidence intervals for the displacement field computed through the iFEM. The proposed technique is validated with a virtual experiment; advantages and limitations of the proposed approach are also discussed.
Structural Health Monitoring (SHM) via data-driven techniques can be based upon vibrations acquired by sensor networks. However, technical and economic reasons may prevent the deployment of pervasive sensor networks over civil structures, thus limiting their reliability in terms of damage detection. Moreover, the effects of environmental (and operational) variability may lead to false alarms. To address these challenges, a multi-stage machine learning (ML) method is here proposed by exploiting autoregressive (AR) spectra as damage-sensitive features. The proposed method is framed as follows: (i) computing the distances between different sets of the AR spectra via the log-spectral distance (LSD), providing also the training and test datasets; (ii) removing the potential environmental variability by an auto-associative artificial neural network (AANN), to set normalized training and test datasets; (iii) running a statistical analysis via the Mahalanobis-squared distance (MSD) for early damage detection. The effectiveness of the proposed approach is assessed in the case of limited vibration data for the laboratory truss structure known as the Wooden Bridge. Comparative studies show that the AR spectrum is a reliable feature, sensitive to damage even in the presence of a limited number of sensors in the network; additionally, the multi-stage ML methodology succeeds in early detecting damage under environmental variability.
Palazzo Lombardia is one of the tallest buildings in Milan and the site of the regional government. For these reasons, some years ago a monitoring system was installed in order to assure its continuous operation. The system is based on accelerometers and clinometers at different floors used for dynamic and static monitoring, respectively. A statistical model was developed, such that the time trend of the first eigenfrequencies of the building were modelled through the trend of the clinometer signals and the root mean square (RMS) of some of the accelerometers. This because it was observed that the clinometer signals and the acceleration RMSs are linked to different environmental variables. As examples: the changes of the static configuration of the building due to sun exposure can be described by clinometer signals and acceleration RMSs can take into account the effect of wind. The use of these signals and indexes simplifies the development of the predictive model, compared to the use of measured environmental quantities. The model showed good performances in foreseeing the trend of the first eigenfrequencies. This paper analyses how the reliability of the model, developed with data acquired in 2015–2016, has changed relying on new data acquired in 2021–2022.
Although relevant examples of systems devoted to shape sensing, damage detection, load identification, etc., do exist, even based on fiber optic sensors, they are barely suited for installation on real aerospace applications due to important criticalities in the application of the fiber. However, all HUMS application based on fiber optics can be enabled thanks to the proposed Smart Veil: a technology consisting of a thin composite membrane incorporating fiber optics placed on a complex path. This integrated element makes the monitoring system easy to use/handle, robust and reliable in real operating scenarios, capable of guaranteeing precise measurements. The effectiveness of this technological solution is proven by means of the manufacturing of a sensorized helicopter blade mockup. Among the several techniques that can be adopted using a fiber optic, FBG (Fiber Bragg Grating) sensors have been selected, allowing a robust punctual measure in specific locations. The choice of sensors position was led by the idea to exploit a digital twin for shape reconstruction and load identification, so all the components of the relevant loads acting on a tail rotor blade during operation can be obtained: axial, beam bending, chord bending and torsion. All sensors benefit from the use of the smart veil that guarantees robust and precise measures. Particularly, the torsional sensors do, since they need to be placed on an ad hoc path. The static calibration test and a comparison with a strain gauges system permitted a validation and showed the advantages of the technological solution proposed.
Nonlinear frequency generation at the nanoscale is a hot research topic which is gaining increasing attention in nanophotonics. The generation of harmonics in subwavelength volumes is historically associated with the enhancement of electric fields in the interface of plasmonic structures. Recently, new platforms based on high-index dielectric nanoparticles have emerged as promising alternatives to plasmonic structures for many applications. By exploiting optically induced electric and magnetic response via multipolar Mie resonances, dielectric nanoelements may lead to innovative opportunities in nanoscale nonlinear optics. Dielectric optical nanoantennas enlarge the volume of light–matter interaction with respect to their plasmonic counterpart, since the electromagnetic field can penetrate such materials, and therefore producing a high throughput of the generated harmonics. In this review, we first recap recent developments obtained in high refractive index structures, which mainly concern nonlinear second order effects. Moreover, we discuss configurations of dielectric nano-devices where reconfigurable nonlinear behavior is achieved. The main focus of this work concerns efficient Sum Frequency Generation in dielectric nano-platforms. The reported results may serve as a reference for the development of new nonlinear devices for nanophotonic applications.
Cage stability is an essential indicator of the guaranteed efficiency and reliability of the rolling element bearing. Moreover, cage instability can greatly shorten the bearing's service life. The whirl characteristics of the cage caused by ball-cage collisions are closely related to the overall bearing skidding degree. To explore the stability and skidding characteristics of self-lubricated cages used in spacecraft angular contact bearings, a comprehensive bearing dynamic model focused on cage characteristics is proposed. The cage was divided into Nb (number of balls) segments owing to the low stiffness of the cage material (porous polyimide). The model comprised ball self-rotating and revolution motions with 4*Nb degrees of freedom (DOF) and cage motions with Nb + 3 DOF. In the latter, 3 represents the cage whirling motion in the translational and axial directions. The ball-pocket normal and tangential forces, ball-pocket axial collisions, the ball-raceway traction force and moment, imbalances, centrifugal force, and thin oil film lubrication are included in the model. A test bench for exploring the cage motion with a high-speed camera to capture cage images was developed. Three experimental case studies investigating the effects of operating speed and applied load validated the effectiveness and accuracy of the model. Several indicators describing cage stability and cage skidding degree were proposed based on the experimental and theoretical results. It was found that the rate of increase of the whirl radius reduced with a linear increase in the rotation speed. The whirling radius displayed an approximate hyperbolic downward trend with increasing axial force. The skidding results suggested that applying a large axial load to the bearing may have been counterproductive in preventing bearing skidding. In addition, the cage was prone to instability as the radial load increased owing to intensive cage-guide ring rubbing.
In recent years, research in child-computer interaction shifted the focus from design with children for giving them a voice in the design process, to design by children so as to bring child participants different benefits, such as engagement and learning. Design workshops, encompassing different stages, are however challenging in terms of engagement and learning, e.g., they take a prolonged commitment and concentration capabilities. They are potentially more challenging when held at a distance, as it was the case in recent years due to the COVID-19 pandemic. This paper explores at-a-distance smart-thing design with children, and how it can engage different children and support their learning in programming. The paper reports on a series of design workshops with 20 children, aged from 8 to 16 years old, all held at a distance. They were uniformly framed with the DigiSNaP design framework and toolkit. The first workshop enabled children to explore what smart things are, start ideating their own and scaffold their programming. The other workshops enabled children to evolve their own smart-thing ideas and programs. Data were gathered in relation to children’s engagement and learning, from different sources. Results are promising for future editions of smart-thing design at a distance or in hybrid modality. They are discussed in the conclusions of the paper, along with guidelines and difficulties faced with design by children at a distance.
Background: Prone positioning improves survival in moderate-to-severe acute respiratory distress syndrome (ARDS) unrelated to the novel coronavirus disease (COVID-19). This benefit is probably mediated by a decrease in alveolar collapse and hyperinflation and a more homogeneous distribution of lung aeration, with fewer harms from mechanical ventilation. In this preliminary physiological study we aimed to verify whether prone positioning causes analogue changes in lung aeration in COVID-19. A positive result would support prone positioning even in this other population. Methods: Fifteen mechanically-ventilated patients with COVID-19 underwent a lung computed tomography in the supine and prone position with a constant positive end-expiratory pressure (PEEP) within three days of endotracheal intubation. Using quantitative analysis, we measured the volume of the non-aerated, poorly-aerated, well-aerated, and over-aerated compartments and the gas-to-tissue ratio of the ten vertical levels of the lung. In addition, we expressed the heterogeneity of lung aeration with the standardized median absolute deviation of the ten vertical gas-to-tissue ratios, with lower values indicating less heterogeneity. Results: By the time of the study, PEEP was 12 (10-14) cmH2O and the PaO2:FiO2 107 (84-173) mmHg in the supine position. With prone positioning, the volume of the non-aerated compartment decreased by 82 (26-147) ml, of the poorly-aerated compartment increased by 82 (53-174) ml, of the normally-aerated compartment did not significantly change, and of the over-aerated compartment decreased by 28 (11-186) ml. In eight (53%) patients, the volume of the over-aerated compartment decreased more than the volume of the non-aerated compartment. The gas-to-tissue ratio of the ten vertical levels of the lung decreased by 0.34 (0.25-0.49) ml/g per level in the supine position and by 0.03 (- 0.11 to 0.14) ml/g in the prone position (p < 0.001). The standardized median absolute deviation of the gas-to-tissue ratios of those ten levels decreased in all patients, from 0.55 (0.50-0.71) to 0.20 (0.14-0.27) (p < 0.001). Conclusions: In fifteen patients with COVID-19, prone positioning decreased alveolar collapse, hyperinflation, and homogenized lung aeration. A similar response has been observed in other ARDS, where prone positioning improves outcome. Therefore, our data provide a pathophysiological rationale to support prone positioning even in COVID-19.
After a short introduction on the historical context, the paper deals with the existence of the solution of Parker’s ideal body problem, namely the body of minimum constant density generating a given external potential. A crucial element of the proof is the use of a recently introduced topological space of closed sets, closed and compact with the distance defined as the Lebesgue measure of the symmetric difference of a couple of sets. Such a space is indeed smaller than that of all closed sets of a given B, but larger than that of star-shaped Lipschitz domains, where previous studies of the inverse gravimetric problem (with constant density) have been conducted. However, with the present knowledge, it is only in this class that a uniqueness theorem holds.
The ongoing trend toward Industry 4.0 has revolutionised ordinary workplaces, profoundly changing the role played by humans in the production chain. Research on ergonomics in industrial settings mainly focuses on reducing the operator’s physical fatigue and discomfort to improve throughput and avoid safety hazards. However, as the production complexity increases, the cognitive resources demand and mental workload could compromise the operator’s performance and the efficiency of the shop floor workplace. State-of-the-art methods in cognitive science work offline and/or involve bulky equipment hardly deployable in industrial settings. This paper presents a novel method for online assessment of cognitive load in manufacturing, primarily assembly, by detecting patterns in human motion directly from the input images of a stereo camera. Head pose estimation and skeleton tracking are exploited to investigate the workers’ attention and assess hyperactivity and unforeseen movements. Pilot experiments suggest that our factor assessment tool provides significant insights into workers’ mental workload, even confirmed by correlations with physiological and performance measurements. According to data gathered in this study, a vision-based cognitive load assessment has the potential to be integrated into the development of mechatronic systems for improving cognitive ergonomics in manufacturing.
This paper proposes a methodology to the experimental vibroacoustic modal analysis on a coupled plate-cavity system. The method is based on the nonlinear curve fitting to the Frequency Response Functions (FRFs) obtained through a roving hammer test. These FRFs are divided into two groups: one is for the acceleration of the plate; the other is for the sound pressure inside the cavity. The modal parameters are estimated independently in each group using both the single/multi-mode all-curve and the all-mode single-curve fitting techniques. Such a way overcomes the identification difficulties when the natural frequencies of the coupled system slightly change over the roving hammer process. Meanwhile, the mode shapes extraction is eased from the different scales between structural and acoustic responses. The two groups of FRFs are fitted by two different types of FRF models, respectively. The results are in agreement with respect to the natural frequencies and modal damping ratios. Particularly, the FRF models are in alternative forms instead of the conventional ones, and they fit the measured FRFs very well with the estimation outcomes applied. Furthermore, the identified modal parameters are verified by the counterpart estimation based on the conventional FRF models formulated by partial fraction expansions. It is shown that the proposed FRF models contain fewer unknown parameters but do not downgrade the estimation accuracy, making the curve fitting process more practical and efficient. Hence, the two-group strategy with the proposed FRF models provides a practical and efficient way for the experimental modal analysis of vibroacoustic systems.
We report on a room temperature Kerr-lens mode-locked chromium-doped zinc selenide (Cr:ZnSe) laser emitting four optical-cycles pulses in the mid-infrared spectral region in which the laser polycrystal has been treated by hot isostatic pressing (HIP). The laser emits 34 fs pulses at 2.4 μm, with a repetition rate of 171 MHz and average output power capabilities of up to 150 mW. This is the first mode-locking investigation conducted using the HIP treated material and to our knowledge, is the shortest pulse width demonstrated, to date, from polycrystalline Cr:ZnSe. The experimental comparison with respect to an untreated polycrystal indicates that HIP treatment is advantageous for mode-locking action of this active material.
The nonlinear coupling between bending and torsional vibrations would greatly affect the dynamic behavior of the rotor system. Different from the traditional way, in this paper the unbalance mass that causes the internal and external couplings is treated as an independent nonlinear element when establishing a finite element model of the coupled bending-torsional (CBT) rotor system with six degrees of freedom for each node. To improve the efficiency of transient numerical simulation, a general algorithm named with linear and nonlinear nodes separation method is proposed, which decreases the dimension of nonlinear iteration matrix, resulting in a great calculation efficiency of solving transient vibration responses of the high-dimension nonlinear motion equation. With the presented nonlinear CBT model, simulations for steady and transient torsional excitation processes are carried out, resulting that the torsional excitation would generate sideband frequency components in the spectra of lateral vibrations and vice versa, and the effect of gravity is considerable and non-negligible in CBT modeling. Additionally, results of experiments with two different scales of setups, a laboratory test-rig and an industrial centrifugal compressor platform, are well agreed with the numerical ones. The investigation provides a complete modeling and high efficient solution method not only for CBT rotordynamic problems, but also for other problems with nonlinear forces.
Water reuse technologies may alleviate the water scarcity problems that affect many world regions, but their adoption is still limited. In particular, key actors in the adoption of water reuse technologies are water utilities, that provide both urban water and wastewater treatment services. Water utilities are embedded in the urban water system, which includes several stakeholders (urban water users, citizens at large, the environment) that may drive or pose barriers to water reuse adoption. Therefore, to ensure a smooth introduction of water reuse technologies, it is fundamental to understand how water reuse interacts with the existing urban water system and impacts its stakeholders. This paper contributes to the ongoing debate on water reuse by conceptualizing the interaction between water reuse technologies and the urban water system and its stakeholders, and addressing the adoption decision of water utilities by assessing its economic and environmental consequences. Based on a review of literature, policy and other secondary documents, and on primary data coming from interviews with experts from a water utility operating in Southern Italy, the study models the utility's response to a shift from urban to reuse water. It then simulates how reuse water introduction impacts on the utility and other stake-holders of the water system, under various regulatory and operational scenarios defined through a thorough analysis of policy documents and literature. Results show that the adoption of water reuse reduces the utility's margin by cannibalizing urban water demand, but appropriate policy measures may enhance the economic sustainability of reuse. System-level performances, such as impact on freshwater savings, costs for users, effects on the public budget, are also assessed, showing how different regulatory options moderate the intensity of impacts for the different stakeholders of the water system. Furthermore, the adoption of reuse water by the most distant users is found to enhance the economic sustainability of reuse and positively impact the utility's margin.
A quantized version of the Sierpinski gasket is proposed, on purely topological grounds, as a C⁎-algebra A∞ with a suitable form of self-similarity. Several properties of A∞ are studied, in particular its nuclearity, the structure of ideals as well as the description of irreducible representations and extremal traces. A harmonic structure is introduced, giving rise to a self-similar Dirichlet form E. A spectral triple is also constructed, extending the one already known for the classical gasket, from which E can be reconstructed. Moreover we show that A∞ is a compact quantum metric space.
Considering the relevance of photovoltaic technology in the power generation system, degradation and failure of photovoltaic modules are becoming particularly relevant. To adopt and coordinate preventive measures or actions, defects must be understood, detected and their economic impact evaluated. The variety of different degrading effects are categorized and the most significant ones as well as in-field characterization methods are described in detail. This information is summarized in a matrix showing signatures of important defects using different inspection methods and stating related power losses. The development of economic assessments is shown, resulting in a cost-based failure modes and effects analysis with the recently developed cost priority number. How the economic impact of a defect is estimated by the cost priority number is shown in three use cases, namely cell cracks, short circuit bypass diode and potential induced degradation. For each case, the fixing costs are evaluated in comparison to defect related downtime costs. Ultimately, to rank the usefulness of the calculations, influences beyond the financial factor are discussed.
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29,180 members
Stefano Maffei
  • Department of Design
Giacomo Verticale
  • Department of Electronics, Information, and Bioengineering
Edie Miglio
  • Department of Mathematics "Francesco Brioschi"
Fabrizio D'Errico
  • Department of Mechanical Engineering
Paolo volonté
  • Department of Design
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