Scaling model for a speed-dependent vehicle noise spectrum

Abstract Considering the well-known features of the noise emitted by moving sources, a number of vehicle characteristics such as speed, unladen mass, engine size, year of registration, power and fuel were recorded in a dedicated monitoring campaign performed in three different places, each characterized by different number of lanes and the presence of nearby reflective surfaces. A full database of 144 vehicles (cars) was used to identify statistically relevant features. In order to compare the vehicle transit noise in different environmental condition, all 1/3-octave band spectra were normalized and analysed. Unsupervised clustering algorithms were employed to group together spectrum levels with similar profiles. Our results corroborate the well-known fact that speed is the most relevant characteristic to discriminate between different vehicle noise spectrum. In keeping with this fact, we present a new approach to predict analytically noise spectra for a given vehicle speed. A set of speed-dependent analytical functions are suggested in order to fit the normalized average spectrum profile at different speeds. This approach can be useful for predicting vehicle speed based purely on its noise spectrum pattern. The present work is complementary to the accurate analysis of noise sources based on the beamforming technique

Investigation on clusters stability in DYNAMAP's monitoring network during Covid-19 outbreak

Abstract From March 23rd to May 3rd 2020, Italy underwent a complete lockdown in the attempt to contain the spread of the pandemic due to Covid-19 outbreak. During this period, a new kind of environment has been experienced in all cities, resulting in an abatement of traffic noise levels. Consequently, due to the prohibition of all non-essential activities, traffic noise dynamics changed as well. In this paper, we analyse the data recorded from the permanent noise monitoring network installed in the pilot area of the city of Milan, Italy. The results show how, besides a dramatic reduction of the noise levels (about 6 dB on average), also the noise pattern was profoundly changed. This is particularly important in the framework of DYNAMAP, a statistically based European project able to predict traffic noise over an extended area based on the noise recorded by limited number of monitoring stations. The change of the traffic dynamics, resulting in different noise patterns of the normalized hourly median profiles for each sensor, pose some limitations about the use of such predicting tool during extraordinary situations such as that experienced during a lockdown

Simulations of shock generation and propagation in laser-plasmas

AbstractWe analyze the results of a recent experiment performed at the PALS laboratory and concerning ablation pressure at 0.44 µm laser wavelength measured at irradiance up to 2 × 1014 W/cm2. Using the code "ATLANT," we have performed two-dimensional (2D) hydrodynamics simulations. Results show that 2D effects did not affect the experiment and also give evidence of the phenomenon of delocalized absorption of laser light

Advances in the investigation of shock-induced reflectivity of porous carbon

AbstractWe studied the behavior of porous carbon compressed by laser-generated shock waves. In particular, we developed a new design for targets, optimized for the investigation of carbon reflectivity at hundred-GPa pressures and eV/k temperatures. Specially designed "two-layer-two materials" targets, comprising porous carbon on transparent substrates, allowed the probing of carbon reflectivity and a quite accurate determination of the position in the P, T plane. This was achieved by the simultaneous measurement of shock breakout times, sample temperature (by optical pyrometry) and uid velocity. The experiments proved the new scheme is reliable and appropriate for reflectivity measurements of thermodynamical states lying out of the standard graphite or diamond hugoniot. An increase of reflectivity in carbon has been observed at 260 GPa and 14,000 K while no increase in reflectivity is found at 200 GPa and 20,000 K. We also discuss the role of numerical simulations in the optimization of target parameters and in clarifying shock dynamics

Peculiarities of Functional Connectivity—including Cross-Modal Patterns—in Professional Karate Athletes: Correlations with Cognitive and Motor Performances

Professional karate is a sport activity requiring both physical and psychological skills that have been associated with a better "global neural efficacy." By means of resting state functional magnetic resonance imaging (rs-fMRI), we investigated the neural correlates of cognitive and kinematic abilities in a group of 14 professional karateka and 14 heathy matched controls. All subjects underwent an extensive cognitive test battery for the identification of individual multidimensional cognitive profile and rs-fMRI scans investigating functional connectivity (FC). Moreover, kinematic performances in athletes were quantified by the Ergo-Mak, an integrated system developed for measuring motor reactivity, strength, and power of athletic gestures. Karateka performed significantly better than controls in the visual search task, an ability linked with increased positive correlations in FC between the right superior parietal lobe and bilateral occipital poles. Kinematic performances of athletic feats were sustained by increased positive correlations between subcortical (cerebellum and left thalamus) and cortical (inferior frontal cortex, superior parietal cortex, superior temporal cortex) regions. An unexpected FC increase between auditory and motor-related areas emerged in karateka, possibly reflecting a cross-modal coupling due to the continuous exposure to either internal or external auditory cues, positing this sensory channel as a possible target for novel training strategies. Results represent a further step in defining brain correlates of "neural efficiency" in these athletes, whose brain can be considered a model of continuous plastic train-related adaptation

Efficient aberrations pre-compensation and wavefront correction with a deformable mirror in the middle of a petawatt-class CPA laser system

AbstractIn this paper, we describe the experimental validation of the technique of correction of wavefront aberration in the middle of the laser amplifying chain. This technique allows the correction of the aberrations from the first part of the laser system, and the pre-compensation of the aberrations built in the second part. This approach will allow an effective aberration management in the laser chain, to protect the optical surfaces and optimize performances, and is the only possible approach for multi-petawatt laser system from the technical and economical point of view. This approach is now possible after the introduction of new deformable mirrors with lower static aberrations and higher dynamic than the standard devices

Eco-Acoustic Indices to Evaluate Soundscape Degradation Due to Human Intrusion

The characterization of environmental quality and the detection of the first sign of environmental stress, with reference to human intrusion, is currently a very important goal to prevent further environmental degradation, and consequently habitat destruction, in order to take appropriate preservation measures. Besides the traditional field observation and satellite remote sensing, geophonic and/or biophonic sounds have been proposed as potential indicators of terrestrial and aquatic settings’ status. In this work, we analyze a series of short audio-recordings taken in urban parks and bushes characterized by the presence of different human-generated-noise and species abundance. This study aims to propose a tool devoted to the investigation of urban and natural environments in a context with different soundscape qualities, such as, for example, those that can be found in urban parks. The analysis shows the ways in which it is possible to distinguish among different habitats by the use of a combination of different acoustic and sound ecology indices

Application of the Intermittency Ratio Metric for the Classification of Urban Sites Based on Road Traffic Noise Events

Human hearing adapts to steady signals, but remains very sensitive to fluctuations as well as to prominent, salient noise events. The higher these fluctuations are, the more annoying a sound is possibly perceived. To quantify these fluctuations, descriptors have been proposed in the literature and, among these, the intermittency ratio (IR) has been formulated to quantify the eventfulness of an exposure from transportation noise. This paper deals with the application of IR to urban road traffic noise data, collected in terms of 1 s A-weighted sound pressure level (SPL), without being attended, monitored continuously for 24 h in 90 sites in the city of Milan. IR was computed on each hourly data of the 251 time series available (lasting 24 h each), including different types of roads, from motorways to local roads with low traffic flow. The obtained hourly IR values have been processed by clustering methods to extract the most significant temporal pattern features of IR in order to figure out a criterion to classify the urban sites taking into account road traffic noise events, which potentially increase annoyance. Two clusters have been obtained and a “non-acoustic” parameter x, determined by combination of the traffic flow rate in three hourly intervals, has allowed to associate each site with the cluster membership. The described methodology could be fruitfully applied on road traffic noise data in other cities. Moreover, to have a more detailed characterization of noise exposure, IR, describing SPL short-term temporal variations, has proved to be a useful supplementary metric accompanying LAeq, which is limited to measure the energy content of the noise exposure