Vulcanian fountain collapse mechanisms revealed by multiphase numerical simulations: Influence of volatile leakage on eruptive style and particle-size segregation by A.B. Clarke, B. Voight, A. Neri & G. Macedonio

Outline Montserrat Vulcanian explosions Here we test the effect of volatile leakage on Vulcanian explosions using a first-order leakage model to supply initial conditions for an axisymmetric, multiphase numerical model –Volatile loss can cause change in eruptive style from explosive to effusive (Jaupart and Allegre, 1991; Jaupart, 1998) Comparison of models to real events

Andesite dome-building eruption Ongoing since was a very active year, including 88 Vulcanian explosions Soufrière Hills volcano, Montserrat, BWI

Events preceding Vulcanian explosions on Montserrat

Duration < 1 minute Plume height 10 km (3 – 15) Magma ejected 0.8 x 10 9 kg Exit velocity 40 – 140 m s -1 Fountain collapse height 300 – 650 m Ash-cloud surge velocity 30 – 60 m s -1 Pumice flow runout 3 – 6 km Explosion interval 10 hours

Numerical model Solves Mass, Momentum and Energy for 3 particle sizes and a gas phase Unsteady vent parameters (mass flux of each phase) calculated by model Initial conditions and geometric parameters obtained from field data (Geometry & topography; OP = 10MPa from pumice; 3 particle sizes from deposits) Results of pyroclastic dispersal compared to field observations

Radial Volatile Leakage q is mass flow rate of gas per unit area  g &  g are gas density and viscosity  is gas volume fraction P c is gas pressure in the conduit P l is lithostatic pressure K is permeability of country rock From Jaupart & Allegre, (1991) Begin with reference simulation and apply the leakage model: 10 MPa OP; 3 particle sizes; 20 m cap; 4.3 wt.%H 2 0; 65vol% crystals

Results: effects of volatile leakage SimB (volatile loss) more energetic plume overhang style less mass to flows-68% higher & later fountain collapse elutriation of fines from pyroclastic current SimC (3x SimB loss) less energetic plume boil-over style more mass to flows-82% lower & earlier fountain collapse elutriation of fines from pyroclastic current

Overhang styleBoil-over style

Overhang styleBoil-over style

Elutriation of fines Occurred for all simulations & was observed in real events Elutriation was more dramatic for overhang-style SimB at 80 s ~50% of fines were part of pf, but by150 s only 12% of fines remained part of the pf

Conclusions Duplication of real explosions requires some volatile leakage and/or delayed exsolution Lateral volatile leakage plays an important role in explosion style (as well as strength) Simulations revealed important mechanisms of fountain collapse and particle size segregation

Conduit model assumptions * flow has stagnated no viscosity changes with depth * equilibrium degassing * constant crystal volume fraction with depth * constant overpressure with depth Reasonably duplicated real behavior --- however permeability (or anything that would reduce gas volume fraction, such as non-equilibrium degassing) proved to be significant in overall plume development

How should we improve the conduit model? Results from Melnik 1999 suggest a few things * Still assume equilibrium degassing * Allow for viscosity changes due to crystal growth degassing * Resulting in a non-constant overpressure with depth and corresponding vesicularities How do these changes affect explosion results?

Accounting for viscosity changes during ascent * had little affect on plume ascent rate * changed qualitative behavior of plume * changed pyroclastic flow runout distance

How do we test which conduit model best represents reality? Pumice samples from a single event assume pumice records pre-fragmentation conditions Does pumice record pressure, temperature, and vesicularity variations with depth? If so, how do we measure these parameters?

Methods Comparison against experiments on the same magma Matrix glass K2O composition (varies as the inverse of P and T) An content (increases with increasing P and T) Measure matrix glass water content In conjunction with density to better understand gas lost from system