Thermal shock response behaviour of carbon fibre reinforced silicon carbide matrix composites prepared by chemical vapour infiltration at different heating rates

The present work investigated the effects of thermal cycles in air on the tensile properties of a two-dimensional carbon fibre reinforced silicon carbide composite (2D C/SiC) prepared by chemical vapour infiltration at different heating rates. The composite was exposed to different cycles of thermal shock between 20 °C and 1300 °C in air. The damage mechanisms were investigated by AE online monitoring and fractured morphology offline analysis. The tensile strength of 2D-C/SiC decreases with increasing thermal cycles. However, the modulus only decrease within 40 cycles. Due to oxidation, with the decrease in heating rate, the residual properties of the material decrease more obviously. Meanwhile, the results of AE online monitoring and fracture analysis show that the matrix damage is more serious at higher heating rate and that more delamination occours in tensile fractures. The above results indicate that for the thermal shock of 2D C/SiC composites in air, oxidative damage plays a key role in the residual properties.     

Saliency4ASD: Challenge,dataset and tools for visual attention modeling for autism spectrum disorder

The recent studies showing that gaze features can be useful in the identification of Autism Spectrum Disorder (ASD), have opened a new domain where Visual Attention (VA) modeling could be of great help. In this sense, this paper presents a report of the Grand Challenge “Saliency4ASD: Visual attention modeling for Autism Spectrum Disorder”, organized at IEEE ICME’19, aiming at supporting the research on VA modeling towards this healthcare societal challenge. In particular, this paper describes the workflow, obtained results, and datasets and tools that were used within this activity, in order to help on the development and evaluation of two types of VA models: (1) to predict saliency maps that fit gaze behavior of people with ASD, and (2) to identify individuals with ASD from typical development.     

Investigation of the Ga-Sb-S chalcogenide glass with low thermo-optic coefficient as an acousto-optic material

In this study, two series of Ga_xSb_40-xS₆₀ (x = 4, 6, 8, 10 mol%) and Ga_ySb₃₆S_64-y (y = 3, 5, 6 mol%) glasses were prepared and the relationship between their compositional and acousto-optic (AO) properties was investigated systematically for the first time. In the Ga_ySb₃₆S_64-y system, the AO figure of merit (M₂) increased as the Ga increased, and the maximum M₂ of the Ga₆Sb₃₆S₅₈ glass was 455.78 × 10^?18 s³/g, which is ～301 times greater than that of fused silica and ～2.5 times greater than that of As₂S₃ chalcogenide (ChG) glass at 1550 nm. However, its thermo-optic coefficients (dn/dT) varied greatly (32.1 × 10^?6 °C^?1–57.2 × 10^?6 °C^?1), and acoustic attenuations (α) at 10 MHz were high, from 5.446 dB/cm to 7.274 dB/cm. In the Ga_xSb_40-xS₆₀ glass system, the M₂ value and α at different ultrasonic frequencies gradually decreased with the improvement of Ga. Compared with the Ga_ySb₃₆S_64-y system, the Ga_xSb_40-xS₆₀ glass system had lower α (at 10 MHz) and dn/dT, which are 5.001 dB/cm–5.563 dB/cm and 17.3 × 10^?6 °C^?1–55.6 × 10^?6 °C^?1, respectively. These results provide a significant reference for the further development of novel ChG glasses and help expand their application fields.     

Seasonal movements of muskellunge in the St. Clair – Detroit River System: Implications for multi-jurisdictional fisheries management

The St. Clair-Detroit River System contains a world-class Great Lakes muskellunge (Esox masquinongy) fishery that has avoided the declines observed in many Great Lakes muskellunge populations. Muskellunge are an upper trophic level predator, and therefore a naturally low-density species. Limited fishery-independent data exist on which to base management decisions. To remedy this, we initiated an acoustic telemetry study in May of 2016, in collaboration with the Great Lakes Acoustic Telemetry Observation System. Our objective was to describe patterns of movement of muskellunge in this large and open system to better understand their spatial ecology. We acoustically tagged 133 muskellunge in the Detroit River and Lake St. Clair, and movements of 58 fish that passed our data quality control screens were analyzed. We utilized mixed modelling to assess the effects of sex, length, release location, and season on daily movement rates. We found that movement rates only differed among seasons, with highest movement rates occurring in the fall and lowest movement rates in the winter. Muskellunge tagged at different locations exhibited distinct residency patterns, and fish frequently crossed jurisdictional and waterbody boundaries. Ultimately our study highlights the scope and patterns of muskellunge movement in a large, unimpounded system and demonstrates that management of these fish would benefit from consideration of their full distribution covering multiple management jurisdictions.     

Feasibility of non-destructive evaluation for apple crispness based on portable acoustic signal

In this paper, apple crispness was evaluated by sensory evaluation and compared with non-destructive measurements of portable acoustic signal to discuss the feasibility of non-destructive evaluation for apple crispness based on portable acoustic signal. Acoustic eigenvalues from the acoustic signal were processed by time domain and Hilbert–Huang transform (HHT), followed by analysing the correlations with apple crispness that had been evaluated via sensory evaluation. Multiple linear regression (MLR) and artificial neural network (ANN) were applied to predict apple crispness. The results proved that crispness correlates significantly (P < 0.01) with four acoustic eigenvalues, including waveform index, sound intensity, energy of low frequency and energy of high frequency. The average relative error of apple crispness predicted by ANN was 1.42 ± 1.9%, remarkably lower (P < 0.01) that of MLR (6.79 ± 5.64%), implying that the model predicted by ANN is more accurate than that of MLR.     

Freeze-thaw crack determination in cementitious materials using 3D X-ray computed tomography and acoustic emission

As concrete freezes and thaws cracks may develop. These cracks can provide a path for water and ionic species to penetrate the concrete. This may reduce the service-life of the concrete element. In this study, X-ray computed tomography (CT) was used as a non-destructive technique to characterize the microstructure of mortar samples that were exposed to different levels of freeze-thaw damage by varying degree of saturation in the samples (75, 90, 95, and 100% degrees of saturation). Acoustic emission (AE) experiments were performed during freezing and thawing to investigate sample cracking behavior. The volume of cracks present within the mortar samples after freezing and thawing were determined using X-ray CT and compared to passive acoustic emission data. The location/source of cracks was also determined using X-ray CT. The crack sources (i.e., void, aggregate, interfacial transition zone, or paste) were determined using X-ray CT and were related to AE activities during cracking. Crack volumes were found to increase with increased levels of saturation, and visual observations of cracking were found to correlate with AE signatures of various crack sources.     

A simple and effective approach for evaluating unconfined hydrogen/air cloud explosions

The topic of hydrogen safety assessment has been focused by many researchers. The overpressure evaluation of vapor cloud explosion (VCE), is an important issue for both designing and evaluating on chemical plants, as well as buildings. Unknown flame radius history limits the original acoustic approximation model's application. The objective of this work is to develop an achievable model for hydrogen/air deflagration assessment in engineering applications, and the model should have high computational efficiency. A tentative scheme that starts from flame/piston speed history solving was adopted, and the flame/piston radius and acceleration history will be obtained subsequently. Thus, the overpressure history for far field could be gotten based on the acoustic approximation model. A simplified scheme was employed for the region inside the flame cloud. The model proposed in this paper could be solved in several seconds, because there are no differential equations but only algebraic equations. The model was verified by hydrogen/air deflagration tests from small scale to large scale. Compared with the experimental data, the model appeared well agreements in the medium and large scale cases. In the small scale cases, the model obtained acceptable solutions.     

Analysis of acoustic Doppler current profiler mean velocity measurements in shallow flows

Acoustic Doppler current profilers (ADCPs) are commonly used instruments for measurement of natural streamflow and flow in manmade channels. Velocities measured in a profile by the instrument are used to estimate the discharge in a channel. A Teledyne RD Instruments StreamPro ADCP was used to measure the mean velocity simultaneously with a laser Doppler anemometer (LDA) in a laboratory flume. An average of 3.9% under-prediction of the mean velocity measured by the ADCP occurred when compared to the measurements of the LDA. Moreover, this study shows that the sampling duration of the measurements significantly impacts the mean point velocities measured by up to 50%.     

A Unified Analysis of Structured Sonar-Terrain Data Using Bayesian Functional Mixed Models

Sonar emits pulses of sound and uses the reflected echoes to gain information about target objects. It offers a low cost, complementary sensing modality for small robotic platforms. Although existing analytical approaches often assume independence across echoes, real sonar data can have more complicated structures due to device setup or experimental design. In this article, we consider sonar echo data collected from multiple terrain substrates with a dual-channel sonar head. Our goals are to identify the differential sonar responses to terrains and study the effectiveness of this dual-channel design in discriminating targets. We describe a unified analytical framework that achieves these goals rigorously, simultaneously, and automatically. The analysis was done by treating the echo envelope signals as functional responses and the terrain/channel information as covariates in a functional regression setting. We adopt functional mixed models that facilitate the estimation of terrain and channel effects while capturing the complex hierarchical structure in data. This unified analytical framework incorporates both Gaussian models and robust models. We fit the models using a full Bayesian approach, which enables us to perform multiple inferential tasks under the same modeling framework, including selecting models, estimating the effects of interest, identifying significant local regions, discriminating terrain types, and describing the discriminatory power of local regions. Our analysis of the sonar-terrain data identifies time regions that reflect differential sonar responses to terrains. The discriminant analysis suggests that a multi- or dual-channel design achieves target identification performance comparable with or better than a single-channel design. Supplementary materials for this article are available online.