scholarly journals A Two–Parameter Model of Snow–Avalanche Motion

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.

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.


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.


Author(s):  
Nikolay A. Kudryashov ◽  
Mikhail Chmykhov ◽  
Michael Vigdorowitsch

Abstract A simple SIS-type mathematical model of infection expansion is presented and analysed with focus on the case SARS-Cov-2. It takes into account two processes, namely, infection and recovery/decease characterised by two parameters in total: contact rate and recovery/decease rate. Its solution has a form of a quasi-logistic function for which we have introduced an infection index that, should it become negative, can also be considered as a recovery/decease index with decrease of infected down to zero. Based on the data from open sources for the SARS-Cov-2 pandemic, seasonal influenza epidemics and a pandemic in the fauna world, a threshold value of the infection index has been shown to exist above which an infection expansion pretends to be considered as pandemic. Lean (two-parameter) SIR models affined with the warning SIS model have been built. Their general solutions have been obtained, analysed and shown to be a priori structurally adjusted to the infectives’ peak in epidemiological data.


Author(s):  
Maria A. Milkova

Nowadays the process of information accumulation is so rapid that the concept of the usual iterative search requires revision. Being in the world of oversaturated information in order to comprehensively cover and analyze the problem under study, it is necessary to make high demands on the search methods. An innovative approach to search should flexibly take into account the large amount of already accumulated knowledge and a priori requirements for results. The results, in turn, should immediately provide a roadmap of the direction being studied with the possibility of as much detail as possible. The approach to search based on topic modeling, the so-called topic search, allows you to take into account all these requirements and thereby streamline the nature of working with information, increase the efficiency of knowledge production, avoid cognitive biases in the perception of information, which is important both on micro and macro level. In order to demonstrate an example of applying topic search, the article considers the task of analyzing an import substitution program based on patent data. The program includes plans for 22 industries and contains more than 1,500 products and technologies for the proposed import substitution. The use of patent search based on topic modeling allows to search immediately by the blocks of a priori information – terms of industrial plans for import substitution and at the output get a selection of relevant documents for each of the industries. This approach allows not only to provide a comprehensive picture of the effectiveness of the program as a whole, but also to visually obtain more detailed information about which groups of products and technologies have been patented.


Author(s):  
Muhammad Ghifari Arfananda ◽  
◽  
Surya Michrandi Nasution ◽  
Casi Setianingsih ◽  
◽  
...  

The rapid development of information and technology, the city of Bandung tourism has also increased. However, tourists who visit the city of Bandung have problems with a limited time when visiting Bandung tourist attractions. Traffic congestion, distance, and the number of tourist destinations are the problems for tourists travel. The optimal route selection is the solution for those problems. Congestion and distance data are processed using the Simple Additive Weighting (SAW) method. Route selection uses the Floyd-Warshall Algorithm. In this study, the selection of the best route gets the smallest weight with a value of 5.127 from the Algorithm process. Based on testing, from two to five tourist attractions get an average calculation time of 3 to 5 seconds. This application is expected to provide optimal solutions for tourists in the selection of tourist travel routes.


Author(s):  
Laure Fournier ◽  
Lena Costaridou ◽  
Luc Bidaut ◽  
Nicolas Michoux ◽  
Frederic E. Lecouvet ◽  
...  

Abstract Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials. Key Points • Data-driven processes like radiomics risk false discoveries due to high-dimensionality of the dataset compared to sample size, making adequate diversity of the data, cross-validation and external validation essential to mitigate the risks of spurious associations and overfitting. • Use of radiomic signatures within clinical trials requires multistep standardisation of image acquisition, image analysis and data mining processes. • Biological correlation may be established after clinical validation but is not mandatory.


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>


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