Current Issue : January-March Volume : 2023 Issue Number : 1 Articles : 5 Articles
Thermal conductivity of rock wool boards was investigated in this study. Although distribution of fibers in a realistic rock wool board is unclear, it can be simulated by computer X-ray tomography technique (CT) followed by rearrangement through the random generation-growth (RGG) model. An ideal CT-RGG structure model of rock wool boards (CT-random generation-growth model) was established by simplifying material properties based on the mesostructure parameters of the RGG model. Thermal conductivity of rock wool boards with different apparent densities and fiber diameters was studied, and the CT-RGG model was analyzed by explicit jump (EJ) diffusion equations solved by the fast Fourier transform method. We found that thermal conductivity of a single rock wool fiber can be successfully determined. Simulation and measurement results show that thermal conductivity increases consistently with the increase of apparent density and fiber diameter, particularly when the apparent density of rock wool board is greater than 140 kgm− 3. Compared with the existing theoretical models, the proposed method does not depend on the empirical parameters; therefore, it is useful in designing and optimizing the thermal conductivity of rock wool boards....
Studying the failure behaviour of engineered or natural materials under dynamic loading scenarios is of high importance, for example to investigate the fracture mechanics and to prevent catastrophic failures of constructions. When dynamic loading is coupled to high-speed X-ray imaging, not only surface information but images of the interior of the specimens during failure are accessible. Here, a custom designed Split Hopkinson Tension Bar (SHTB) coupled a Universal Testing Machine (UTM) has been developed, dedicated to study quasi-static and dynamic response using ultra-high speed X-ray phase contrast imaging. Both systems follow a compact design which allows them to be temporarily installed at a synchrotron beamline. A brief description of the installation and usage of these setups are outlined. Selected example applications outline the potential of these systems. Both systems can be considered for proposal experiments at beamline ID19 of the European synchrotron ESRF on request....
We have studied the variation of the time profile of X‐ray emission of solar flares that occurred during the second half of solar cycle 23 (SC 23) and for about the full solar cycle 24 (SC 24) (2002–2018). We define a new index, called the “ratio index” (Rf), for all X‐ray solar flares. This index is defined as the ratio of the flare’s rising time interval by its total duration period. According to the ratio index, the X‐ray solar flares are classified into two types: (1) sudden flares [Rf < 0.5], and (2) gradual flares [Rf > 0.5]. The sudden flare type, with fast‐rising and slow recovery, is more common and represents most of the flares that happen most of the time during the solar cycles but are less common during the minimum solar activity years. On the other hand, the gradual flare type (or Rf > 0.5) is less common but predominates during the minimum solar activity epochs. Sudden flares tend to be strong, large, and numerous in the polar regions, while gradual flares are weak, short, and countable in the latitude range between 50 and 70, both for northern and southern latitudes. However, both types appear to happen in the lower latitudes and the solar equatorial regions....
P-type delafossite CuGaO2 is a wide-bandgap semiconductor for optoelectronic applications, and its lattice parameters are very similar to those of n-type semiconductor wurtzite ZnO. Accordingly, the investigation of crystalline heterostructures of CuGaO2 and ZnO has attracted significant attention. In this study, interfacial CuGaO2/ZnO hetero-compounds were examined through X-ray diffraction (XRD) analysis, confocal micro-Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS). XRD and Raman analysis revealed that the hydrothermal deposition of ZnO on hexagonal platelet CuGaO2 base crystals was successful, and the subsequent reduction process could induce a unique, unprecedented reaction between CuGaO2 and ZnO, depending on the deposition parameters. XPS allowed the comparison of the binding energies (peak position and width) of the core level electrons of the constituents (Cu, Ga, Zn, and O) of the pristine CuGaO2 single crystallites and interfacial CuGaO2/ZnO hybrids. The presences of Cu2+ ions and strained GaO6 octahedra were the main characteristics of the CuGaO2/ZnO hybrid interface. The XPS and modified Auger parameter analysis gave an insight into a specific polarization of the interface, promising for further development of CuGaO2/ZnO hybrids....
Security inspection is extremely important for the safety of public places. In this research, we are trying to propose a novel algorithm and investigated theoretically in the X-ray dataset, which can optimize the relative low detection accuracy and the latent omission detection of smaller objects when using You Only Look Once version 5 (YOLOv5). For one side, the transform detection network is selected to be added at the bottom layer of backbone structure to avoid the loss of useful information during sequential calculation. On another side, we attempt to adjust the existing PANet structural elements of the model, including their connections and other related parameters to improve the detection performance. We integrate an efficient BiFPN with the CA mechanism, which can enhance feature extraction, and named it attention-BiFPN. Experimental consequences demonstrate that the detection accuracy of the proposed model, which we name “TB-YOLOv5,” has obvious advantages in check performance compared with the mainstream one-stage object detection models. Meanwhile, compared with YOLOv5, the data results display an improvement of up to 14.9%, and the average precision at 0.5 IOU even reached 23.4% higher in the region of small object detection. Our purpose was to explore the potential of changing a popular detection algorithm such as YOLO to address specific tasks and provide insights on how specialized adjustments can influence the detection of small objects. Our work can supply an effective method of enhancing the performance of X-ray security inspection and show promising potential for deep learning in related fields....
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