• Title/Summary/Keyword: dynamic and fast loading rates

Search Result 1, Processing Time 0.017 seconds

Fragmentation and energy absorption characteristics of Red, Berea and Buff sandstones based on different loading rates and water contents

  • Kim, Eunhye;Garcia, Adriana;Changani, Hossein
    • Geomechanics and Engineering
    • /
    • v.14 no.2
    • /
    • pp.151-159
    • /
    • 2018
  • Annually, the global production of construction aggregates reaches over 40 billion tons, making aggregates the largest mining sector by volume and value. Currently, the aggregate industry is shifting from sand to hard rock as a result of legislation limiting the extraction of natural sands and gravels. A major implication of this change in the aggregate industry is the need for understanding rock fragmentation and energy absorption to produce more cost-effective aggregates. In this paper, we focused on incorporating dynamic rock and soil mechanics to understand the effects of loading rate and water saturation on the rock fragmentation and energy absorption of three different sandstones (Red, Berea and Buff) with different pore sizes. Rock core samples were prepared in accordance to the ASTM standards for compressive strength testing. Saturated and dry samples were subsequently prepared and fragmented via fast and dynamic compressive strength tests. The particle size distributions of the resulting fragments were subsequently analyzed using mechanical gradation tests. Our results indicate that the rock fragment size generally decreased with increasing loading rate and water content. In addition, the fragment sizes in the larger pore size sample (Buff sandstone) were relatively smaller those in the smaller pore size sample (Red sandstone). Notably, energy absorption decreased with increased loading rate, water content and rock pore size. These results support the conclusion that rock fragment size is positively correlated with the energy absorption of rocks. In addition, the rock fragment size increases as the energy absorption increases. Thus, our data provide insightful information for improving cost-effective aggregate production methods.