On the computation of parameters that model snow avalanche motion

1981 ◽  
Vol 18 (1) ◽  
pp. 121-130 ◽  
Author(s):  
S. Bakkehøi ◽  
T. Cheng ◽  
U. Domaas ◽  
K. Lied ◽  
R. Perla ◽  
...  

This paper explores the computational problem of finding suitable numbers to use in a two-parameter model of snow avalanche dynamics. The two parameters are friction, μ, and a ratio of avalanche mass to drag, M/D. Given a path profile, and a maximum avalanche speed, then it is possible to compute unique values for u and M/D. If only the path profile and the stopping position are known, then it is possible to compute tables of pairs {μ, M/D} which can be tested as predictors of avalanche speeds. To generate these tables it is convenient to scale M/D in multiples of the total vertical drop of the path. The computations were tested on 136 avalanche paths. Values of {μ, M/D} were stratified, and certain values were rejected as unrealistic.

1980 ◽  
Vol 26 (94) ◽  
pp. 197-207 ◽  
Author(s):  
R. Perla ◽  
T. T. Cheng ◽  
D.M. McClung

AbstractVoellmy’s (1955) method for computing the run-out distance of a snow avalanche includes an unsatisfactory feature: the a priori selection of a midslope reference where the avalanche is assumed to begin decelerating from a computed steady velocity. There is no objective criterion for selecting this reference, and yet the choice critically determines the computed stopping position of the avalanche. As an alternative, a differential equation is derived in this paper on the premise that the only logical reference is the starting position of the avalanche. The equation is solved numerically for paths of complex geometry. Solutions are based on two parameters: a coefficient of friction μ; and a ratio of avalanche mass–to–drag, M⁄D. These are analogous to the two parameters in Voellmy’s model, μ and ξH. Velocity and run-out distance data are needed to estimate μ and M⁄D to useful precision. The mathematical properties of two–parameter models are explored, and it is shown that some difficulties arise since similar results are predicted by dissimilar pairs of μ and M⁄D.


1980 ◽  
Vol 26 (94) ◽  
pp. 197-207 ◽  
Author(s):  
R. Perla ◽  
T. T. Cheng ◽  
D.M. McClung

Abstract Voellmy’s (1955) method for computing the run-out distance of a snow avalanche includes an unsatisfactory feature: the a priori selection of a midslope reference where the avalanche is assumed to begin decelerating from a computed steady velocity. There is no objective criterion for selecting this reference, and yet the choice critically determines the computed stopping position of the avalanche. As an alternative, a differential equation is derived in this paper on the premise that the only logical reference is the starting position of the avalanche. The equation is solved numerically for paths of complex geometry. Solutions are based on two parameters: a coefficient of friction μ; and a ratio of avalanche mass–to–drag, M⁄D. These are analogous to the two parameters in Voellmy’s model, μ and ξH. Velocity and run-out distance data are needed to estimate μ and M⁄D to useful precision. The mathematical properties of two–parameter models are explored, and it is shown that some difficulties arise since similar results are predicted by dissimilar pairs of μ and M⁄D.


2021 ◽  
Author(s):  
Daeha Kim ◽  
Jong Ahn Chun

<p>While the Budyko framework has been a simple and convenient tool to assess runoff (Q) responses to climatic and surface changes, it has been unclear how parameters of a Budyko function represent the vertical land-atmosphere interactions. Here, we explicitly derived a two-parameter equation by correcting a boundary condition of the Budyko hypothesis. The correction enabled for the Budyko function to reflect the evaporative demand (E<sub>p</sub>) that actively responds to soil moisture deficiency. The derived two-parameter function suggests that four physical variables control surface runoff; namely, precipitation (P), potential evaporation (E<sub>p</sub>), wet-environment evaporation (E<sub>w</sub>), and the catchment properties (n). We linked the derived Budyko function to a definitive complementary evaporation principle, and assessed the relative elasticities of Q to climatic and land surface changes. Results showed that P is the primary control of runoff changes in most of river basins across the world, but its importance declined with climatological aridity. In arid river basins, the catchment properties play a major role in changing runoff, while changes in E<sub>p</sub> and E<sub>w</sub> seem to exert minor influences on Q changes. It was also found that the two-parameter Budyko function can capture unusual negative correlation between the mean annual Q and E<sub>p</sub>. This work suggests that at least two parameters are required for a Budyko function to properly describe the vertical interactions between the land and the atmosphere.</p>


2020 ◽  
Author(s):  
Xingyue Li ◽  
Betty Sovilla ◽  
Chenfanfu Jiang ◽  
Johan Gaume

Abstract. Snow avalanches cause fatalities and economic damages. Key to their mitigation entails the understanding of snow avalanche dynamics. This study investigates the dynamic behaviors of snow avalanches, using the Material Point Method (MPM) and an elastoplastic constitutive law for porous cohesive materials. By virtue of the hybrid Eulerian-Lagrangian nature of MPM, we can handle processes involving large deformations, collisions and fractures. Meanwhile, the elastoplastic model enables us to capture the mixed-mode failure of snow, including tensile, shear and compressive failure. Using the proposed numerical approach, distinct behaviors of snow avalanches, from fluid-like to solid-like, are examined with varied snow mechanical properties. In particular, four flow regimes reported from real observations are identified, namely, cold dense, warm shear, warm plug and sliding slab regimes. Moreover, notable surges and roll-waves are observed peculiarly for flows in transition from cold dense to warm shear regimes. Each of the flow regimes shows unique flow characteristics in terms of the evolution of the avalanche front, the free surface shape, and the vertical velocity profile. We further explore the influence of slope geometry on the behaviors of snow avalanches, including the effect of slope angle and path length on the maximum flow velocity, the $\\alpha$ angle and the deposit height. Unified trends are obtained between the normalized maximum flow velocity and the scaled $\\alpha$ angle as well as the scaled deposit height, reflecting analogous rules with different geometry conditions of the slope. It is found the maximum flow velocity is mainly controlled by the friction between the bed and the flow, the geometry of the slope, and the snow properties. In addition to the flow behavior before reaching the deposition zone, which has long been regarded as the key factor governing the $\\alpha$ angle, we reveal the crucial effect of the stopping behavior in the deposition zone. Furthermore, our MPM model is benchmarked with simulations of real snow avalanches. The evolution of the avalanche front position and velocity from the MPM modeling shows reasonable agreement with the measurement data from literature. The MPM approach serves as a novel and promising tool to offer systematic and quantitative analysis for mitigation of gravitational hazards like snow avalanches.


Geosciences ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 466
Author(s):  
Dieter Issler

Data on the disastrous snow avalanche that occurred on 18 January 2017 at the spa hotel Rigopiano, municipality of Farindola in the Abruzzo region of central Italy, are analyzed in different ways. The main results are the following. (i) The 2017 Rigopiano avalanche went beyond the run-out point predicted by the topographic-statistical α-β model with standard Norwegian calibration, while avalanches in neighboring paths appear to have run no farther than the β-point of their respective paths during the same period. (ii) The curvature and super-elevation of the trimline between 1500 and 1300 m a.s.l. indicate that the velocity of the front was around 40 m s−1. In contrast, the tail velocity of the avalanche can hardly have exceeded 25 m s−1 in the same segment. (iii) The deposits observed along all of the lower track and in the run-out zone suggest that the avalanche eroded essentially the entire snow cover, but fully entrained only a moderate amount of snow (and debris). The entrainment appears to have had a considerable decelerating effect on the flow front. (iv) Estimates of the degree to which different parts of the building were damaged is combined with information about the location of the persons in the building and their fates. This allows to refine a preliminary vulnerability curve for persons in buildings obtained from the 2015 Longyearbyen avalanche, Svalbard.


Author(s):  
Anson Maitland ◽  
Chi Jin ◽  
John McPhee

Abstract We introduce the Restricted Newton’s Method (RNM), a basic optimization method, to accelerate model predictive control turnaround times. RNM is a hybrid of Newton’s method (NM) and gradient descent (GD) that can be used as a building block in nonlinear programming. The two parameters of RNM are the subspace on which we restrict the Newton steps and the maximal size of the GD step. We present a convergence analysis of RNM and demonstrate how these parameters can be selected for MPC applications using simple machine learning methods. This leads to two parameter selection strategies with different convergence behaviour. Lastly, we demonstrate the utility of RNM on a sample autonomous vehicle problem with promising results.


1993 ◽  
Vol 25 (03) ◽  
pp. 714-716
Author(s):  
K. D. Glazebrook

We propose a two-parameter family of conjugate prior distributions for the number of undiscovered objects in a class of Bayesian search models. The family contains the one-parameter Euler and Heine families as special cases. The two parameters may be interpreted respectively as an overall success rate and a rate of depletion of the source of objects. The new family gives enhanced flexibility in modelling.


2016 ◽  
Vol 30 (23) ◽  
pp. 1650154 ◽  
Author(s):  
Cuihua Zhang ◽  
Huili Yi ◽  
Jianxiang Tian

In this paper, we analyzed the ability of Lielmezs–Herrick (LH) correlation for the temperature-dependent surface tension of 28 hydrocarbons. We found that compared with other published correlations, the original LH correlation stands well only for four fluids. By using new data in REFPROP database, we refitted the two parameters of LH correlation. Two sets values are obtained. One is the updated corresponding state LH correlation, which is fluid independent. The other is the two-parameter LH correlation, which is fluid dependent. We found that the former clearly improves the accuracy of the original LH correlation and the latter is the best among all of the correlations we know.


2012 ◽  
Vol 79 (2) ◽  
Author(s):  
A. Nobili

This paper presents a Hamiltonian variational formulation to determine the energy minimizing boundary conditions (BCs) of the tensionless contact problem for an Euler–Bernoulli beam resting on either a Pasternak or a Reissner two-parameters foundation. Mathematically, this originates a free-boundary variational problem. It is shown that the BCs setting the contact loci, which are the boundary points of the contact interval, are always given by second order homogeneous forms in the displacement and its derivatives. This stands for the nonlinear nature of the problem and calls for multiple solutions in the displacement, together with the classical result of multiple solutions in the contact loci position. In particular, it is shown that the Pasternak soil possesses an extra solution other than Kerr’s, although it is proved that such solution must be ruled out owing to interpenetration. The homogeneous character of the BCs explains the well-known load scaling invariance of the contact loci position. It is further shown that the Reissner foundation may be given two mechanical interpretations, which lead to different BCs. Comparison with the established literature is drawn and numerical solutions shown which confirm the energy minimizing nature of the assessed BCs.


Author(s):  
Wenhao Gui

In this paper, we deal with the problem of estimating the reliability function of the two-parameter exponential distribution. Classical Maximum likelihood and Bayes estimates for one and two parameters and the reliability function are obtained on the basis of progressively type-II censored samples. The inverted gamma conjugate prior density is assumed for the one-parameter case, whereas the joint prior density of the two-parameter case is composed of the inverted gamma and the uniform densities. A comparison between the obtained estimators is made through a Monte Carlo simulation study. A real example is used to illustrate the proposed methods.


Sign in / Sign up

Export Citation Format

Share Document