Aguirrechurch4450

The experimental results show that the sizes of elongated grains in a cold-rolled aluminum are evaluated as 1086 ± 8, 90 ± 4, and 10 ± 1 μm in the x, y, and z directions, where the exact values are 1184.2 ± 11.9, 80.7 ± 5.2, and 8.3 ± 0.5 μm according to metallographic measurements.Some models of speech production propose that speech variation reflects an adaptive trade-off between the needs of the listener and constraints on the speaker. The current study considers communicative load as both a situational and lexical variable that influences phonetic variation in speech to real interlocutors. The current study investigates whether the presence or absence of a target word in the sight of a real listener influences speakers' patterns of variation during a communicative task. To test how lexical difficulty also modulates intelligibility, target words varied in phonological neighborhood density (ND), a measure of lexical difficulty. Acoustic analyses reveal that speakers produced longer vowels in words that were not visually present for the listener to see, compared to when the listener could see those words. This suggests that speakers assess in real time the presence or absence of supportive visual information in assessing listener comprehension difficulty. Furthermore, the presence or absence of the word interacted with ND to predict both vowel duration and hyperarticulation patterns. These findings indicate that lexical measures of a word's difficulty and speakers' online assessment of lexical intelligibility (based on a word's visual presence or not) interactively influence phonetic modifications during communication with a real listener.The acoustic performance of a silencer containing elastic membranes backed by cavities and porous material is investigated. The modeled waveguide configuration contains porous screens as well as the metallic fairings at interfaces between the inlet and outlet and the expansion chamber. The mode-matching solution is developed to analyze the attenuation of the silencer. The governing eigen-sub-systems are Sturm-Liouville and non-Sturm-Liouville types. buy dcemm1 In the latter case, the exploitation of generalized orthogonality conditions reveals the point-wise convergence of the solution to the governing eigen-systems. The study shows that by tuning the material parameters of the isotropic membranes and altering the bounding wall conditions, the performance of the physical device can be improved. It enables the model configuration to be adopted as a passive or reactive noise control device.Differences in the perception of segmental contrasts by native and non-native listeners have been analyzed as the results of language-specific weightings of acoustic cues in their perception grammar [e.g., Escudero and Boersma, Stud. Second Lang. Acquis. 26, 551-585 (2004)]. However, less attention has been paid to the weighting of prosodic cues. This study investigated the relative importance of four prosodic cues-word duration, pauses, pitch, and intensity-in the resolution of English syntactic ambiguity by native English listeners and Korean learners of English. In a forced-choice processing task, English listeners' disambiguation relied most heavily on pitch, followed by pause and intensity cues, whereas pauses were the only heavily weighted cue for Korean listeners, indicating an influence from their native language. Moreover, Korean listeners' use of prosody for disambiguation was found to be influenced by their age of English acquisition and English proficiency.Aging, noise exposure, and ototoxic medications lead to cochlear synapse loss in animal models. As cochlear function is highly conserved across mammalian species, synaptopathy likely occurs in humans as well. Synaptopathy is predicted to result in perceptual deficits including tinnitus, hyperacusis, and difficulty understanding speech-in-noise. The lack of a method for diagnosing synaptopathy in living humans hinders studies designed to determine if noise-induced synaptopathy occurs in humans, identify the perceptual consequences of synaptopathy, or test potential drug treatments. Several physiological measures are sensitive to synaptopathy in animal models including auditory brainstem response (ABR) wave I amplitude. However, it is unclear how to translate these measures to synaptopathy diagnosis in humans. This work demonstrates how a human computational model of the auditory periphery, which can predict ABR waveforms and distortion product otoacoustic emissions (DPOAEs), can be used to predict synaptic loss in individual human participants based on their measured DPOAE levels and ABR wave I amplitudes. Lower predicted synapse numbers were associated with advancing age, higher noise exposure history, increased likelihood of tinnitus, and poorer speech-in-noise perception. These findings demonstrate the utility of this modeling approach in predicting synapse counts from physiological data in individual human subjects.Advancements in additive manufacturing (AM) technology are promising for the creation of acoustic materials. Acoustic metamaterials and metasurfaces are of particular interest for the application of AM technologies as theoretical predictions suggest the need for precise arrangements of dissimilar materials within specified regions of space to reflect, transmit, guide, or absorb acoustic waves in ways that exceed the capabilities of currently available acoustic materials. This work presents the design of an acoustic metasurface (AMS) with Willis constitutive behavior, which is created from an array of multi-material inclusions embedded in an elastomeric matrix, which displays the asymmetric acoustic absorption. The finite element models of the AMS show that the asymmetric absorption is dependent on asymmetry in the distribution of materials within the inclusion and highly sensitive to small changes in the inclusion geometry. It is shown that the performance variability can be used to place constraints on the manufacturing-induced variability to ensure that an as-built AMS will perform using the as-designed parameters. The evaluation of the AMS performance is computationally expensive, thus, the design is performed with a classifier-based metamodel to support more efficient Monte Carlo simulations and quantify the sensitivity of the candidate design performance to the manufacturing variability. This work explores combinations of material choices and dimensional accuracies to demonstrate how a robust design approach can be used to help select AM fabrication methods or guide process development toward an AM process that is capable of fabricating acoustic material structures.Sea-surface acoustic scattering is investigated using observations from the 2016-2017 Canada Basin Acoustic Propagation Experiment. The motions of the low-frequency acoustic source and/or receiver moorings were measured using long-baseline acoustic navigation systems in which the signals transmitted once per hour by the mooring instruments triggered high-frequency replies from the bottom-mounted transponders. The moorings recorded these replies, giving the direct path and single-bounce surface-reflected arrivals, which have grazing angles near 50°. The reflected signals are used here to quantify the surface scattering statistics in an opportunistic effort to infer the changing ice characteristics as a function of time and space. Five scattering epochs are identified (1) open water, (2) initial ice formation, (3) ice solidification, (4) ice thickening, and (5) ice melting. Significant changes in the ice scattering observables are seen using the arrival angle, moment of reflected intensity and its probability density function, and pulse time spread. The largest changes took place during the formation, solidification, and melting. The statistical characteristics across the experimental region are similar, suggesting consistent ice properties. To place the results in some physical context, they are interpreted qualitatively using notions of the partial and fully saturated wave fields, a Kirchhoff-like approximation for the rough surface, and a thin elastic layer reflection coefficient model.The influence of the ground and atmosphere on sound generation and propagation from wind turbines creates uncertainty in sound level estimations. Realistic simulations of wind turbine noise thus require quantifying the overall uncertainty on sound pressure levels induced by environmental phenomena. This study proposes a method of uncertainty quantification using a quasi-Monte Carlo method of sampling influential input data (i.e., environmental parameters) to feed an Amiet emission model coupled with a Parabolic Equation propagation model. This method allows for calculation of the probability distribution of the output data (i.e., sound pressure levels). As this stochastic uncertainty quantification method requires a large number of simulations, a metamodel of the global (emission-propagation) wind turbine noise model was built using the kriging interpolation technique to drastically reduce calculation time. When properly employed, the metamodeling technique can quantify statistics and uncertainties in sound pressure levels at locations downwind from wind turbines. This information provides better knowledge of sound pressure variability and will help to better control the quality of wind turbine noise prediction for inhomogeneous outdoor environments.Measures of "aided" speech intelligibility (SI) for listeners wearing hearing aids (HAs) are commonly obtained using rather artificial acoustic stimuli and spatial configurations compared to those encountered in everyday complex listening scenarios. In the present study, the effect of hearing aid dynamic range compression (DRC) on SI was investigated in simulated real-world acoustic conditions. A spatialized version of the Danish Hearing In Noise Test was employed inside a loudspeaker-based virtual sound environment to present spatialized target speech in background noise consisting of either spatial recordings of two real-world sound scenarios or quadraphonic, artificial speech-shaped noise (SSN). Unaided performance was compared with results obtained with a basic HA simulator employing fast-acting DRC. Speech reception thresholds (SRTs) with and without DRC were found to be significantly higher in the conditions with real-world background noise than in the condition with artificial SSN. Improvements in SRTs caused by the HA were only significant in conditions with real-world background noise and were related to differences in the output signal-to-noise ratio of the HA signal processing between the real-world versus artificial conditions. The results may be valuable for the design, development, and evaluation of HA signal processing strategies in realistic, but controlled, acoustic settings.Wind-induced noise recorded with a compact microphone array can be exploited to infer the mean velocity of the free-field airflow. In this work, a model-based method to estimate the wind flow speed and direction is proposed that uses spectro-spatial correlations of closely spaced microphone signals. As shown in a recent work by the present authors, the normalized cross-power spectral density of flow-induced noise measured with closely spaced microphones, also referred to as the spatial coherence, can be approximated by a semi-empirical model, named the Corcos model. Due to the dependency of the Corcos model on the airflow velocity, the measured spatial coherence provides information on the sought quantity. Speed and direction can be resolved by fitting the measured spatial coherence to the analytical Corcos model in the least squares sense. The accuracy of the proposed method is investigated across a range of wind speed between 0.5 and 12 ms-1 and all directions, using observation lengths from 5 s to 1 h. The audio samples under test were recorded indoors and outdoors and labeled by an ultrasonic anemometer.