Bi, X.Lau, T.Sun, Z.Nathan, G.2024-11-062024-11-062022Proceedings of the 23rd Australasian Fluid Mechanics Conference (AFMC2022), 2022, pp.1-82653-0597https://hdl.handle.net/2440/143153Paper No: AFMC2022-53Particles free-falling from a densely-seeded hopper with a rectangular outlet were experimentally studied utilising a combination of shadowgraphy and mass flow rate measurements. The study comprised a systematic assessment of the influence of the size of sintered bauxite particles (dp = 163, 192, 216, 257, 363, 399 and 500 μm) and hopper outlet thickness (D = 3, 4, 5 and 8 mm) on the particle distributions downstream from the hopper. A pulsed backlighting system comprising two CCD cameras synchronised with a LED panel was developed to image the particles within a falling distance of ≈ 1 m from the hopper exit. The mass flow rate of the particles was measured simultaneously with the imaging by recording the instantaneous weight of the hopper and its contents at a sampling rate of 1000 Hz. The results show that the particle distribution can be classified into three different regimes, namely a near-field expansion, a neck zone and an intermediate-field expansion. The expansion gradient of the near-field generally increases with the increase of dp and D, and was found to be strongly influenced by the exit particle Stokes number (SK₀). The intermediate-field expansion gradient decreases with the increase of dp, but was found to be insensitive to D, consistent with the current understanding of momentum-driven particle-laden jets. The classified flow regimes reveal the different dominant particle dynamics under different conditions, providing a guidance for the future in-depth studies of the various controlling mechanisms of free-falling particle flows.enCopyright is held by the author(s) through the Creative Commons BY-NC 4.0 License.Experimental study of densely-seeded gravity-driven particle-laden flowConference paper2024-09-16708162Bi, X. [0000-0001-9084-7325]Lau, T. [0000-0003-1851-706X]Sun, Z. [0000-0001-7899-9676]Nathan, G. [0000-0002-6922-848X]