Stability of volcanic ash aggregates and break-up processes

Abstract

Numerical modeling of ash plume dispersal is an important tool for forecasting and mitigating potential hazards from volcanic ash erupted during explosive volcanism. Recent tephra dispersal models have been expanded to account for dynamic ash aggregation processes. However, there are very few studies on rates of disaggregation during transport. It follows that current models regard ash aggregation as irrevocable and may therefore overestimate aggregation-enhanced sedimentation. In this experimental study, we use industrial granulation techniques to artificially produce aggregates. We subject these to impact tests and evaluate their resistance to break-up processes. We find a dependence of aggregate stability on primary particle size distribution and solid particle binder concentration. We posit that our findings could be combined with eruption source parameters and implemented in future tephra dispersal models.

Figure 1

(a) Pressurized air-gun setup at Aarhus University, Denmark. Aggregates were shot with overpressure against a vertical metal wall. Applied overpressures ranged between 0.5 and 4 bar, resulting in impact velocities of 2.9–7.8 m.s⁻¹. (b) Impact setup at LMU Munich, Germany. Aggregates were dropped from heights between 5 and 200 cm onto a metal plate. Impact speed was monitored with a high-speed camera and used to calculate impact energy. (c) Modes of break-up that were observed throughout experiments: surface chipping (<10 wt% loss of material from parent aggregate), fragmentation (10–90 wt% material loss from parent aggregate) and total disintegration (>90 wt% material loss from parent aggregate).

Figure 2

Sequence of photos taken with a high-speed camera; aggregates impact on metal wall of the Aarhus setup. (a) Sequence shows surface chipping of aggregate, (b) fragmentation and (c) total disintegration.

Figure 3

(a,b) The influence of particle size on aggregate stability. (c,d) The influence of NaCl binder concentration on aggregate stability. (d) The influence of primary particle surface morphology on aggregate stability.

Figure 4

(a) An intact solid NaCl bridge connecting two glass beads. (b) A failed solid NaCl bridge with the once connected glass bead missing. (c) Cohesive failure within a solid NaCl bridge. (d) Adhesive failure between a solid NaCl bridge and a glass bead.

Figure 5

Solid NaCl bridge volumes evaluated from SEM analysis are plotted against total available surface of the two particles connected through the solid bridge. Maximum salt bridge volumes show exponential dependence on available particle surface area.

Figure 6

SEM image of aggregated glass beads. The two glass beads (a) and (b) are connected with each other through a smaller solid NaCl bridge than they are to glass bead (c). Glass bead (c) is larger in volume and therefore surface and allows for the establishment of more voluminous bridges.

Figure 7

Aggregate strength σ_cr of artificial aggregates have been computed, following the models of Johnson et al. and Rumpf. Solid salt bridge neck radii represent SEM analysis results or our artificial aggregates. (a) shows aggregate strengths for tensile stress case and aggregate porosities ε of 0.5 and 0.8. (b) shows aggregate strengths for compressive stress case and aggregate porosity of 0.5 and 0.8.