Research on the dynamic tensile characteristics and surface crack evolution of coal under impact loading.

The tensile properties of coal under dynamic loading are important mechanical characteristics of coal and are highly important for controlling coal rock stability under impact loading conditions, selecting blasting engineering parameters, and studying the mechanism of rockburst disasters. To investigate the dynamic tensile failure process of coal subjected to impact loading, this study used high-speed photography and digital image correlation technology to capture the dynamic tensile failure of coal under impact loading. The dynamic tensile evolution was quantitatively analyzed from the beginning of coal sample being loaded to failure. The captured images of the coal were processed, and the fractal dimension was used to quantitatively describe the evolution of the coal surface cracks under impact loading. The following conclusions were drawn from the experimental results: (1) An empirical formula was established to describe the dynamic tensile strength characteristics of coal under different loading rates. (2) Under impact loading, the maximum strain of a Brazilian disc coal sample first appeared at the contact end between the sample and the incident rod. (3) Under impact loading, a Brazilian disc coal sample cracked from the center of the sample outward, and the crack subsequently extended toward both ends. The fractal dimension of the crack exhibited a power function relationship with time, and the variation range of the fractal dimension of the crack was 1.05-1.39.

A new contrast-to-noise ratio for image quality characterization of a coded-aperture γ camera.

The gamma-ray imaging technique was developed and is widely used in several nuclear engineering fields. Specifically, compared with the traditional point-by-point radiation detector, the coded-aperture gamma camera has advantages of a wide field of view, high angular resolution, and high efficiency. Several methods for characterizing image quality, including the figure of merit (FOM) method and the contrast-to-noise ratio (CNR) method, were assessed and developed. These methods have their respective drawbacks depending on the circumstances. The FOM lacks reliability in exhibiting the impact of background noise fluctuation on the purity of a real image. The CNR characterizes image quality with inconsistent sensitivity while the source moves along the X and Y directions. Therefore, a new CNR method was proposed to achieve better performance and greater consistency in real imaging. With our coded-aperture imaging system developed in the laboratory, we performed simulations within the MATLAB and Geant4 platforms and real imaging experiments to analyze and compare images and the results of these three characterization methods. The results show that the new CNR method is reliable and practical in regard to real imaging performance.