Avalanche Simulation Research Articles

A novel approach for bridging the gap between climate change scenarios and avalanche hazard indication mapping

The influence of climate change on snow avalanches, particularly for the end of this century, remains uncertain, underscoring the need for further research. To assess the possible consequences of potential changes in snow accumulation and temperature and their impact on avalanche hazard, we introduce a comprehensive multi-step framework. It includes the analysis of climate change scenarios as well as the modeling of future snow covers and the simulation of avalanches in a case study region in central Switzerland.Using a downscaling and a quantile mapping approach, we considered the high emission RCP8.5 from the CH2018 Swiss climate change scenarios and simulated a potential snow cover of more than 100 future winters with the snow cover model SNOWPACK. Changing snow accumulation and snow cover temperature was taken into account for two future time frames. The changed parameters were used in the RAMMS::EXTENDED avalanche simulation software on large scale.The results indicate that changes in snow accumulation and temperature have a considerable impact on the run-out of avalanches. The results strongly depend on the climate model, without a clear overall trend in snow accumulation across the selected model chains. Snow accumulation and layer temperature can increase or decrease. However, for snow cover temperature, an increase in the mean snow temperature, especially towards the end of the century, can be expected. In future scenarios with reduced snow accumulation and rising temperatures, avalanche simulations show a decrease in the affected area.The workflow from climate scenario analysis to avalanche hazard modeling serves as an initial method for estimating future avalanche extents in the context of climate change on a large scale and can be useful for achieving future protection and adaptation goals.

A Study on Powder Spreading Quality in Powder Bed Fusion Processes Using Discrete Element Method Simulation

Powder deposition is a very important aspect of PBF-based additive manufacturing processes. Discrete Element Method (DEM) is commonly utilized by researchers to examine the physically complex aspects of powder-spreading methods. This work focuses on vibration-assisted doctor blade powder recoating. The aim of this work is to use experiment-verified DEM simulations in combination with Taguchi Design of Experiments (DoE) to identify optimum spreading parameters based on robust layer quality criteria. The verification of the used powder model is performed via angle of repose and angle of avalanche simulation–experiment cross-checking. Then, four criteria, namely layer thickness deviation, surface coverage ratio, surface root-mean-square roughness and true packing density, are defined. It has been proven that the doctor blade’s translational speed plays the most important role in defining the quality of the deposited layer. The true packing density was found to be unaffected by the spreading parameters. The vertical vibration of the doctor blade recoater was found to have a beneficial effect on the quality of the deposited layer. Ultimately, a weighted mean quality criteria analysis is mapped out. Skewness and kurtosis were proven to function as effective indicators of layer quality, showing a linear relation to the weighted means of the defined quality criteria. The specific weights that optimize this linearity were identified.

AvaFrame com1DFA (v1.3): a thickness-integrated computational avalanche module – theory, numerics, and testing

Abstract. Simulation tools are important to investigate and predict mobility and the destructive potential of gravitational mass flows (e.g., snow avalanches). AvaFrame – the open avalanche framework – offers well-established computational modeling approaches, tools for data handling and analysis, and ready-to-use modules for evaluation and testing. This paper presents the theoretical background, derivation, and model verification for one of AvaFrame's core modules, the thickness-integrated computational model for avalanches with flow or mixed form of movement, named com1DFA. Particular emphasis within the description of the utilized numerical particle–grid method is given to the computation of spatial gradients and the accurate implementation of driving and resisting forces. The implemented method allows us to provide a time–space criterion connecting the numerical particles, grid, and time discretization. The convergence and robustness of the numerical implementation is checked with respect to the spatiotemporal evolution of the flow variables using tests with a known analytical solution. In addition, we present a new test for verifying the accuracy of the numerical simulation in terms of runout (angle and distance). This test is derived from the total energy balance along the center-of-mass path of the avalanche. This article, particularly in combination with the code availability (open-source code repository) and detailed online documentation provides a description of an extendable framework for modeling and verification of avalanche simulation tools.

Comparison of two 2-D numerical models for snow avalanche simulation

Snow avalanches are gravitational processes characterised by the rapid movement of a snow mass, threatening inhabitants and damaging infrastructure in mountain areas. Such phenomena are complex events, and for this reason, different numerical models have been developed to reproduce their dynamics over a given topography. In this study, we focus on the two-dimensional numerical simulation tools RAMMS::AVALANCHE and FLO-2D, aiming to compare their performance in predicting the deposition area of snow avalanches. We also aim to assess the employment of the FLO-2D simulation model, normally used in water flood or mud/debris flow simulations, in predicting the motion of snow avalanches. For this purpose, two well-documented avalanche events that occurred in the Province of Bolzano (IT) were analyzed (Knollgraben, Pichler Erschbaum avalanches). The deposition area of each case study was simulated with both models through back-analysis processes. The simulation results were evaluated primarily by comparing the simulated deposition area with the observed one through statistical indices. Subsequently, the maximum flow depth, velocity and deposition depth were also compared between the simulation results. The results showed that RAMMS::AVALANCHE generally reproduced the observed deposits better compared to FLO-2D simulation. FLO-2D provided suitable results for wet and dry snow avalanches after a meticulous calibration of the rheological parameters, since they are not those typically considered in avalanche rheology studies. The results showed that FLO-2D can be used to study the propagation of snow avalanches and could also be adopted by practitioners to define hazard areas, expanding its field of application.

A Fokker–Planck-based Monte Carlo method for electronic transport and avalanche simulation in single-photon avalanche diodes

We present an efficient simulation method for electronic transport and avalanche in single-photon avalanche diodes (SPAD). Carrier transport is simulated in the real space using a particle Monte Carlo approach based on the Fokker–Planck point of view on an advection-diffusion equation, that enables us to reproduce mobility models, including electric fields and doping dependencies. The avalanche process is computed thanks to impact ionization rates implemented using a modified Random Path Length algorithm. Both transport and impact ionization mechanisms are computed concurrently from a statistical point of view, which allows us to achieve a full multi-particle simulation. This method provides accurate simulation of transport and avalanche process suitable for realistic three-dimensional SPADs, including all relevant stochastic aspects of these devices, together with a huge reduction of the computational time required, compared to standard Monte Carlo methods for charge carrier transport. The efficiency of our method empowers the possibility to precisely evaluate SPADs figures of merit and to explore new features that were untrackable by conventional methods. An extensive series of comparisons with experimental data on state-of-the art SPADs shows a very good accuracy of the proposed approach.

Bayesian networks and intelligence technology applied to climate change: An application of fuzzy logic based simulation in avalanche simulation risk assessment using GIS in a Western Himalayan region

Avalanches are snowfalls that cascade down a mountainside, although rockfalls and debris flows can also occur. The study identifies the snow meteorological data for the avalanche risk forecast through various associated factors and models a tool for forecasting avalanches according to the reference database. The terrain factors such as aspect, slope, and altitude have been studied using the Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM) at 90 m resolution. Snow meteorological observed data 2540 records were obtained for Snow and Avalanche Study Establishment (SASE) Nov 2004 to April 2009 for five years data. In the present study, nine parameters were used for Avalanche forecast in the Western Himalaya. The Bayesian classification algorithm may improve the feedback system of prediction than the existing one. Fuzzy logic decides to improve the system to predict the level of danger by studying the influence of parameters. Hazard mitigation strategies applying the Bayesian classification algorithm and Fuzzy logic were combined with Integrated GIS-based methods to determine the risk zones better to identify snow avalanches in three-dimensional terrain.

Effect of the Fracturing Degree of the Source Rock on Rock Avalanche River-Blocking Behavior Based on the Coupled Eulerian-Lagrangian Technique

In this study, the effect of the fracturing degree of the source rock on rock avalanche river-blocking behavior was investigated. The study included the analysis of mass movement behavior, impulse wave behavior, and the formation of landslide dams. The study included a series of simulations of rock avalanche river-blocking based on the coupled Eulerian-Lagrangian (CEL) technique. Prior to the simulation, a water column collapse model was applied to validate the use of the CEL technique on fluid-structure interaction, and to calibrate the material parameters. The source rock in the rock avalanche simulation was cut by different groups of structural planes, with the number of 0 × 0 × 0, 1 × 1 × 1, 4 × 4 × 4, 9 × 9 × 9, 14 × 14 × 14, 19 × 19 × 19 in each dimension, respectively, to represent different fracturing degrees, on the premise of the same volume and shape of the source rock. The simulation results showed that the sliding mass exhibited structure stabilization, such that the structure of the sliding mass gradually stabilized to a steady status over time, in the mass movement process. The structure stabilization made the center of the sliding mass constantly decrease, and provided a higher speed of movement for the rock avalanches with higher fracturing degrees of the source rock. As for the impulse wave behavior, with the increase in the fracturing degree of the source rock, the maximum kinetic energy of the water decreased, and the maximum height and propagation speed of the impulse waves decreased, which indicated that the maximum height and the propagation speed of the impulse waves were positively correlated with the maximum kinetic energy of the water. In regard to the formation of the landslide dams, when the fracturing degree of the source rock was low, the shape of the landslide dam was very different. With the increase of the fracturing degree of the source rock, the shapes of the landslide dams stabilized, and varied slightly after the fracturing degree of the source rock reached a threshold value.

Garfield++ simulation of a TH-GEM based detector for standard mammography beam dosimetry

The TH-GEM based detector is a robust, simple to manufacture, high-gain gaseous electron multiplier. Its operation is based on a standard printed circuit board (PCB) coated on both sides by metallic material, perforated in a millimeter pattern, and immersed in gas. In order to study the feasibility of using TH-GEM type detectors in dosimetric applications for standard mammography beams, a prototype with adequate dimensions and materials was produced. The present work encompasses the calculations of electric fields by the Gmsh and Elmer software packages and the avalanche simulation using Garfield++ library of a TH-GEM detector filled with Ar/CO2 mixture at atmospheric pressure.

Simulation and Analysis of a Snow Avalanche Accident in Lower Western Himalaya, India

In Western Himalaya, an average 49 person die every year due to snow avalanche activities and this death rate is very high as compared to other Asian countries. A snow avalanche accident was observed on 5 January 2018 on Chowkibal–Tangdhar (CT) road axis at avalanche site number CT-8 located near Chowkibal village in Kupwara district, union territory Jammu and Kashmir, India. In the present paper, we discuss snow avalanche simulation, the climatic condition, avalanche debris height and length, and suggested solutions to handle avalanche situations. Rapid Mass MovementS numerical model in combination with digital elevation model and potential release area has been used to simulate avalanche accident occurred on 5 January 2018 at CT-8. The analysis demonstrates maximum snow avalanche velocity, impact of pressure and height of flow to be ~ 25 ms−1, ~ 9.39 × 104 kgm−1 s−2, and ~ 3.0 m respectively on 5 January 2018 at CT-8. Further simulated avalanche debris height and length form road has been validated with ground observed data. Ground reconnaissance of the location was conducted by a team of Snow and Avalanche Study Establishment, Chandigarh and it has been observed that lack of ‘avalanche awareness and Standard Operating Procedures during movement in avalanche prone areas’ among the travellers on the road cause accident . The present paper seems to be first to investigate snow avalanche accident in Western Himalaya and recommend that proper campaigning of avalanche awareness among the people residing in avalanche prone areas of Himalaya could reduce such accidents significantly.

Bayesian Inference in Snow Avalanche Simulation with r.avaflow

Simulation tools for gravitational mass flows (e.g., avalanches, debris flows) are commonly used for research and applications in hazard assessment or mitigation planning. As a basis for a transparent and reproducible decision making process, associated uncertainties need to be identified in order to quantify and eventually communicate the associated variabilities of the results. Main sources of variabilities in the simulation results are associated with parameter variations arising from observation and model uncertainties. These are connected to the measurement inaccuracies or poor process understanding and the numerical model implementation. Probabilistic approaches provide various theoretical concepts to treat these uncertainties, but their direct application is not straightforward. To provide a comprehensive tool, introducing conditional runout probabilities for the decision making process we (i) introduce a mathematical framework based on well-established Bayesian concepts, (ii) develop a work flow that couples this framework to the existing simulation tool r.avaflow, and (iii) apply the work flow to two case studies, highlighting its application potential and limitations. The presented approach allows for back, forward and predictive calculations. Back calculations are used to determine parameter distributions, identifying and mapping the model, implementation and data uncertainties. These parameter distributions serve as a base for forward and predictive calculations, embedded in the probabilistic framework. The result variability is quantified in terms of conditional probabilities with respect to the observed data and the associated simulation and data uncertainties. To communicate the result variability the conditional probabilities are visualized, allowing to identify areas with large or small result variability. The conditional probabilities are particularly interesting for predictive avalanche simulations at locations with no prior information where visualization explicitly shows the result variabilities based on parameter distributions derived through back calculations from locations with well-documented observations.

Simulation of natural shallow avalanches with the μ(I) rheology

A μ(I) rheology–based avalanche flow model whose governing equations are established in a rectangular Cartesian coordinate system is proposed in this paper. The motivation is updating the term related to gradients of the depth-averaged pressure and extending the application of μ(I) rheology to natural avalanche simulation. The main advantage of the proposed method is that it captures the constitutive properties of the avalanche by introducing the μ(I) rheology. The main novelty of the present model that distinguishes other μ(I) rheology–based approaches is that the in-plane shear is not considered in our model (consistent with the traditional Savage–Hutter theory); thus, the μ(I) rheology only plays a part in describing the normal transverse stresses. Experimental example shows that the proposed model can predict the moving process of granular flow satisfactorily. Simulation of a natural case (the Ermanshan avalanche in China) demonstrates that the simulation can approximately reproduce real avalanches tolerably well.

Determining forest parameters for avalanche simulation using remote sensing data

Mountain forests offer effective, natural and cost-efficient protection against avalanches. Trees reduce the probability of an avalanche formation and can significantly decelerate small to medium size avalanches. Remote sensing methods enable an efficient assessment of forest structural parameters on large scale and therefore determine the protective capacity of a specific forest. The aims of this study are: (i) to evaluate the quality of forest structural parameters obtained from remote sensing data using two different methods; and (ii) to determine how forest parameters and forest cover changes influence avalanche runout. We compared the control assessment of maximum tree height and crown coverage in 107 plots (50 in evergreen and 57 in deciduous forests). The same parameters were analysed using (i) a photogrammetry-based vegetation height model (VHMP) and (ii) a LiDAR-based vegetation height model (VHML). The control assessment of surface roughness was compared to the analysis of a digital terrain model (DTM). We then simulated two avalanche case studies near Davos (Switzerland) with forest parameters estimated by the remote sensing and control methods. Tree height and crown coverage assessed with both remote sensing methods (VHMP and VHML) did not differ significantly from the control measurements. However, surface roughness was underestimated. This had a significant influence on simulation results. For the first case study, a wet-snow avalanche, the simulated runout distances did not differ significantly, when using forest parameters from either of the two tested remote sensing methods. The simulated runout distance increased for an avalanche scenario with less forest cover in the release area and/or less forest cover after forest destruction by a preceding avalanche event. For the second case study, a dry-snow avalanche, the forest cover was underestimated by the VHMP, which led to longer simulated runout distances. Our study indicates that available remote sensing methods are increasingly suitable for the determination of forest parameters which are relevant for avalanche simulation models. However, more research is needed on the precise estimation of forest cover in release areas and understanding how forest cover changes affect avalanche runout.

Accelerating avalanche simulation in gas based charged particle detectors

The development and optimization of Micro Pattern Gaseous Detectors relies heavily on the simulation of the geometry, the avalanche process and the signal generation inside the detector. In complex scenarios where high detector gas gains are required, the simulation can be computationally expensive and can become a bottleneck for the R&D process. In this paper we present two approaches to reduce the simulation execution time when using the Garfield++ simulation package. We present the two approaches and discuss the results.

Snow avalanche simulation with TITAN2D. Part 1: comparison with chute experiment results

雪崩を質点や剛体と仮定した運動モデルでは，雪崩の厚さや広がりがわからないなど防災上不備な点も多い．こうした背景のもと，土石流や地すべりなどの粒状体に加えて溶岩流の流動や堆積の再現にも実績がある連続体モデルTITAN2Dを用いて雪崩の運動シミュレーションを試みた．本稿では，実際の雪崩への適用に先立ち，雪粒子を含む3 種類の粒子を用いた室内実験を実施し，TITAN2Dによる計算結果との比較を通してモデルの性能評価を行った．TITAN2Dが浅水流近似により導かれたモデルであること，さらには底面摩擦角の測定の困難さが起因して，流れの先端速度，最大高さ（厚さ）と広がりに相違が見られた場合があるものの，全体的にはTITAN2Dは実験結果を再現しており，実際の雪崩現象への拡張も十分に可能と結論された．

A new solver for granular avalanche simulation: Indoor experiment verification and field scale case study

A new solver based on the high-resolution scheme with novel treatments of source terms and interface capture for the Savage-Hutter model is developed to simulate granular avalanche flows. The capability to simulate flow spread and deposit processes is verified through indoor experiments of a two-dimensional granular avalanche. Parameter studies show that reduction in bed friction enhances runout efficiency, and that lower earth pressure restraints enlarge the deposit spread. The April 9, 2000, Yigong avalanche in Tibet, China, is simulated as a case study by this new solver. The predicted results, including evolution process, deposit spread, and hazard impacts, generally agree with site observations. It is concluded that the new solver for the Savage-Hutter equation provides a comprehensive software platform for granular avalanche simulation at both experimental and field scales. In particular, the solver can be a valuable tool for providing necessary information for hazard forecasts, disaster mitigation, and countermeasure decisions in mountainous areas.

Snow Avalanche Susceptibility Based Assessment of Release Zones over Complex Terrain of Siachen Glacier Applying Ramms and Dsr as Active Macroclimatic Factor

Glaciers are a critical component of the earth system and environment, both in Polar regions and high altitude terrains. At glaciated terrain, local physiographical and climatological variance causes natural hazard which can lead to local and regional consequences. However, focusing the local complex terrain, the snow avalanches are not easily predictable. RAMMS (Rapid mass movement) application has applied successfully to determine the release areas for snow avalanche dimensions, yet the local microclimatic parameters have not been considered. To assess and identify the susceptible zones on basis of snow avalanche susceptibility, we applied RAMMS-avalanche simulation for avalanche dimension and MTLCIM-XL (Mountain Microclimate) simulator to calculate downward shortwave radiation (DSR) integration as the active microclimatic factor, at target release areas over the Siachen glacier. We obtain high dimension values (above assume a maximum value of pressure 50-80kPa) for the selected release areas from the resultant simulation of snow avalanche maximum dimension. Additional integrative approach base assessment of DSR calculation revealed high values (threshold of daily mean ≥ 350-400W/m2) specifically over three release zones for critical month of April (daily mean based). Prospectively, the conclusive susceptibility analysis depicts the target release areas as potential zones for snow avalanche. In conclusion, the combined approach of RAMMS avalanche simulation with the consideration of local microclimatic parameters show better results; and will need to be considered in future studies of snow avalanche susceptibility and preparedness.

Snow avalanche friction relation based on extended kinetic theory

Abstract. Rheological models for granular materials play an important role in the numerical simulation of dry dense snow avalanches. This article describes the application of a physically based model from the field of kinetic theory to snow avalanche simulations. The fundamental structure of the so-called extended kinetic theory is outlined and the decisive model behavior for avalanches is identified. A simplified relation, covering the basic features of the extended kinetic theory, is developed and implemented into an operational avalanche simulation software. To test the obtained friction relation, simulation results are compared to velocity and runout observations of avalanches, recorded from different field tests. As reference we utilize a classic phenomenological friction relation, which is commonly applied for hazard estimation. The quantitative comparison is based on the combination of normalized residuals of different observation variables in order to take into account the quality of the simulations in various regards. It is demonstrated that the extended kinetic theory provides a physically based explanation for the structure of phenomenological friction relations. The friction relation derived with the help of the extended kinetic theory shows advantages to the classic phenomenological friction, in particular when different events and various observation variables are investigated.

Simulation study on single event burnout in linear doping buffer layer engineered power VDMOSFET**Project supported by the National Natural Science Foundation of China (No. 61176071), the Doctoral Fund of Ministry of Education of China (No. 20111103120016), and the Science and Technology Program of State Grid Corporation of China (No. SGRI-WD-71-13-006).

The addition of a buffer layer can improve the device's secondary breakdown voltage, thus, improving the single event burnout (SEB) threshold voltage. In this paper, an N type linear doping buffer layer is proposed. According to quasi-stationary avalanche simulation and heavy ion beam simulation, the results show that an optimized linear doping buffer layer is critical. As SEB is induced by heavy ions impacting, the electric field of an optimized linear doping buffer device is much lower than that with an optimized constant doping buffer layer at a given buffer layer thickness and the same biasing voltages. Secondary breakdown voltage and the parasitic bipolar turn-on current are much higher than those with the optimized constant doping buffer layer. So the linear buffer layer is more advantageous to improving the device's SEB performance.

Multivariate parameter optimization for computational snow avalanche simulation

AbstractSnow avalanche simulation software is a commonly used tool for hazard estimation and mitigation planning. In this study a depth-averaged flow model, combining a simple entrainment and friction relation, is implemented in the software SamosAT. Computational results strongly depend on the simulation input, in particular on the employed model parameters. A long-standing problem is to quantify the influence of these parameters on the simulation results. We present a new multivariate optimization approach for avalanche simulation in three-dimensional terrain. The method takes into account the entire physically relevant range of the two friction parameters (Coulomb friction, turbulent drag) and one entrainment parameter. These three flow model parameters are scrutinized with respect to six optimization variables (runout, matched and exceeded affected area, maximum velocity, average deposition depth and mass growth). The approach is applied to a documented extreme avalanche event, recorded in St Anton, Austria. The final results provide adjusted parameter distributions optimizing the simulation–observation correspondence. At the same time, the degree of parameter–variable correspondence is determined. We show that the specification of optimal values for certain model parameters is near-impossible, if corresponding optimization variables are neglected or unavailable.

Computational snow avalanche simulation in forested terrain

Abstract. Two-dimensional avalanche simulation software operating in three-dimensional terrain is widely used for hazard zoning and engineering to predict runout distances and impact pressures of snow avalanche events. Mountain forests are an effective biological protection measure against avalanches; however, the protective capacity of forests to decelerate or even to stop avalanches that start within forested areas or directly above the treeline is seldom considered in this context. In particular, runout distances of small- to medium-scale avalanches are strongly influenced by the structural conditions of forests in the avalanche path. We present an evaluation and operationalization of a novel detrainment function implemented in the avalanche simulation software RAMMS for avalanche simulation in forested terrain. The new approach accounts for the effect of forests in the avalanche path by detraining mass, which leads to a deceleration and runout shortening of avalanches. The relationship is parameterized by the detrainment coefficient K [kg m−1 s−2] accounting for differing forest characteristics. We varied K when simulating 40 well-documented small- to medium-scale avalanches, which were released in and ran through forests of the Swiss Alps. Analyzing and comparing observed and simulated runout distances statistically revealed values for K suitable to simulate the combined influence of four forest characteristics on avalanche runout: forest type, crown closure, vertical structure and surface cover, for example, values for K were higher for dense spruce and mixed spruce-beech forests compared to open larch forests at the upper treeline. Considering forest structural conditions within avalanche simulations will improve current applications for avalanche simulation tools in mountain forest and natural hazard management.