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Calculating dense-snow avalanche runout using a Voellmy-fluid model with active/passive longitudinal straining

Published online by Cambridge University Press:  20 January 2017

P. Bartelt
Affiliation:
Swiss Federal Institute for Snow and Avalanche Research, CH-7260 Davos Dorf, Switzerland
B. Salm
Affiliation:
Quaderstrasse 19, CH-7205 Zizers, Switzerland
U. Gruber
Affiliation:
Swiss Federal Institute for Snow and Avalanche Research, CH-7260 Davos Dorf, Switzerland
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Abstract

A quasi-one-dimensional dense-snow avalanche model has been developed to predict avalanche runout and flow velocity in a general two-dimensional terrain. The model contains three different dense-snow-avalanche flow laws. These are: (1) a Voellmy-fluid flow law with longitudinal active/passive straining, (2) a Voellmy-fluid flow-law advanced by Russian researchers in which the Coulomb-like dry friction is limited by a yield stress, and (3) a modified Criminale—Ericksen—Filby fluid model proposed by Norwegian researchers. The application of the Voellmy-fluid law with active/passive straining to solve practical avalanche-dynamics problems is evaluated by applying the model to simulate laboratory experiments and field case-studies. The model is additionally evaluated by comparing simulation results using the Russian and Norwegian models. In a final analysis the influence of the initial conditions on avalanche runout is investigated. We conclude that the model resolves many of the shortcomings of the Voellmy–Salm model, which is traditionally used in Switzerland to predict avalanche runout. Furthermore, since the model contains the three well-calibrated parameters of the Swiss Guidelines on avalanche calculation it can be readily applied in practice. We discuss why we believe the Russian and Norwegian models are not ready for practical application. Finally, we show that many problems remain, such as the specification of the initial release conditions. We conclude that numerical models require a more detailed description of initial fracture conditions.

Information

Type
Research Article
Copyright
Copyright © The Author(s) 1999 
Figure 0

Fig. 1. Voellmy fluid.

Figure 1

Fig. 2. Vertical velocity profile assumed in the NIS model. Definition of flow variables.

Figure 2

Fig. 3. Computer simulation of a laboratory chute experiment in which 4 kg of glass beads were released down a 60° inclined chute. (a) Shortly after release; (b) transition zone; (c) at-rest position. The flow heights are increased by a factor if 3. The final deposition form agrees well with the experimental results. Simulation parameters: μ = 0.49, ø = 26° and = 2000 m s−2.

Figure 3

Fig. 4. Comparison between measured front, rear and maximum height positions and computer simulation shown in Figure 3. Simulation parameters: μ = 0.49, ø = 26° and ζ= 2000 m s−2.

Figure 4

Fig. 5. The Ariefa/Samedan avalanche. Predicted avalanche flow heights (a) in the release zone, (b) in the transition zone, (c) in the runout zone. (b) also depicts maximum flow velocities over the length of the avalanche track. (c) also shows simulated dynamic impact pressures. The simulated avalanche reaches a terminal velocity of >30 m s−1 and travels > 1.5km in 60 seconds. The flow heights are increased by a factor of 15. The arrow marks the measured runout distance.

Figure 5

Fig. 6. Computer simulation of Mettlenruns avalanche, showing maximum flow velocities. (a) Voellmy-fluid model; (b) Russian yield-stress model; (c) Norwegian NIS model. The flow heights are increased by a factor of 15. The arrow marks the observed runout position. The measurement panel is located at 910 m a.s.l.

Figure 6

Fig. 7. Computer simulation of Mettlenruns avalanche, showing maximum flow heights. (a) Voellmy-fluid model; (b) Russian yield-stress model; (c) Norwegian NIS model. The flow heights are increased by a factor of 15. The arrow marks the observed runout position.

Figure 7

Fig. 8. Computer simulation of the Mettlenruns avalanche using (a) the Voellmy-fluid model and (b) the Norwegian NIS model. Three different dry-friction values were used for the Voellmy-fluid simulations (μ = 25, μ = 0.30 and μ = 0.35) and NIS model simulations (b = 0.45, b = 0.50 and b = 0.55). In all cases, the higher the dry friction the lower the flow velocity. Note the large difference in flow velocity predicted by the NIS model.

Figure 8

Fig. 9. (a) Flow velocity at point Pas a function of fracture volume. (b) Runout distance S as a function of fracture volume. In the first series of simulations the fracture height was increased; in the second series the fracture length was increased. For the first case the numerical model predicts that Up α and S α h0, which is in agreement with the VS model.

Figure 9

Fig. 10. Predicted terminal flow velocity for different fracture heights and lengths. Note that as the fracture length increased, the results of the numerical model converge with the VS results. Simulation parameters: μ = 0.155, ζ= 2000 m s−2 and λρ = 2.5.

Figure 10

Fig. 11. Predicted deposition heights for the Swiss Guideline VS model and numerical Voellmy-fluid model. Even for large fracture volumes, the numerical model predicts smaller deposition heights.

Figure 11

Fig. 12. Runout distance S vs fracture height h0 for different fracture lengths.

Figure 12

Fig. 13. (a) Runout distance S vs fracture height h0 using Equation (22). (b) Velocity at point P Up us fracture height h0 using Equation (22).