
handle: 11104/0268006
This contribution reports on experiments on uniaxial compression of random layers of dry granular materials of various types of anisometric particles. The goal is twofold. First, to characterize their compressibility features for their classification. Second, to select a suitable material for further breakage studies that can be compared with numerical simulations of fragile particles. Eight different particulate materials were tested, both real- and model-shaped, and both inorganic and organic. The compression was performed using four different instruments to cover a wide range of loads. Based on the results obtained, according to their compressibility, the particles can be divided into several classes: elastic materials (glass fibres), breakable /fragile/ materials (rod-like graphite, hair-like pasta, rod-like pasta), hard cohesive materials (terephtalic acid), and hard non-cohesive /cohesion-less/ materials (KMnO4, PbCl2). The class of breakable materials was selected for further studies. The hair-like pasta was excluded, since its shape is ill-defined. Thus, the two candidates remained: rod-like pasta and rod-like graphite. They were examined for certain strength-related material properties in the threepoint rigidity test (consistency, stiffness, bending moment etc.).
anisometric particles, compressibility, breakable materials
anisometric particles, compressibility, breakable materials
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
