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Experimental study of the fragmentation characteristics of brittle rocks by the effect of a freefall round hammer

机译:自由落体式圆锤效应对脆性岩石破碎特性的实验研究

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The dynamic fragmentation of brittle rocks (slate, granite, marble and limestone) under low-velocity impact was investigated using freefall round hammer experiments. A three-parameter generalized extreme value distribution was used to characterize the fragment sizes, and the finest particles were neglected. A transformation of fragment size was adopted to overcome the problem that the interval of adjacent fragments size increases as the fragment size grows. The results reveal that the frequency distributions and num-based cumulative frequency distributions based on number have a certain change law with variations in impact energy and hammer size; the frequency distribution curve became narrower, and the cumulative frequency distribution curve moved toward the left as the impact energy increased, and the hammer size decreased. Marble was most easily broken followed by granite, limestone and slate, which was proved by scanning electron microscope images of the fracture surfaces of the four rocks. Because fragmentation is a stochastic process, the equivalent diameters of the fragments always had a more obvious regularity than the major and minor axes in the histograms. Therefore, the mean value of the equivalent diameter was used as the experimental average fragment size. Comparing the experimental results with the theoretical results of average fragment sizes that were predicted by four normalized models, it was determined that Levy and Molinari's model and Zhou et al.'s model better forecasted the fragment sizes.
机译:使用自由落体圆锤实验研究了脆性岩石(板岩,花岗岩,大理石和石灰石)在低速冲击下的动态破碎。使用三参数广义极值分布来表征碎片大小,而忽略了最细的颗粒。为了克服随着片段大小的增加,相邻片段大小的间隔增大的问题,采用了片段大小的变换。结果表明,频率分布和基于数量的基于num的累积频率分布具有一定的变化规律,其冲击能量和锤头尺寸会发生变化。频率分布曲线变窄,并且随着冲击能量的增加,累积频率分布曲线向左移动,并且音锤尺寸减小。大理石最容易破碎,其次是花岗岩,石灰石和板岩,这是通过扫描这四个岩石的断裂面的电子显微镜图像证明的。由于碎片是随机过程,因此碎片的等效直径始终比直方图中的长轴和短轴具有更明显的规律性。因此,将等效直径的平均值用作实验平均碎片尺寸。将实验结果与四种归一化模型预测的平均片段大小的理论结果进行比较,可以确定Levy和Molinari模型以及Zhou等人的模型可以更好地预测片段大小。

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