Fracture networks in sea ice

Vevatne, Jonas Nesland; Rimstad, Eivind; Hope, Sigmund Mongstad; Korsnes, Reinert; Hansen, Alex

doi:10.3389/fphy.2014.00021

Cited by 13 publications

(13 citation statements)

References 25 publications

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“…The analysis of the mechanical DFN model shows disassortative mixing, as shown in Tables 1, 2, indicating that the limitations on fracture propagation have a significant impact on the degree mixing. This is consistent with a previous study of fractures in sea ice by Vevatne et al where it was shown that a simple growing fracture network model could produce disassortative mixing if existing fractures could stop the propagation of fractures growing into them [39]. In the model by Vevatne et al the fractures ability to arrest intersecting fractures was a fixed probability, equal for all fractures [39].…”

Section: The Mechanical (M) Model Is Compared For the Competitive (C)supporting

confidence: 80%

Topological impact of constrained fracture growth

et al. 2015

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The topology of two discrete fracture network models is compared to investigate the impact of constrained fracture growth. In the Poissonian discrete fracture network model the fractures are assigned length, position and orientation independent of all other fractures, while in the mechanical discrete fracture network model the fractures grow and the growth can be limited by the presence of other fractures. The topology is found to be impacted by both the choice of model, as well as the choice of rules for the mechanical model. A significant difference is the degree mixing. In two dimensions the Poissonian model results in assortative networks, while the mechanical model results in disassortative networks. In three dimensions both models produce disassortative networks, but the disassortative mixing is strongest for the mechanical model.

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Section: The Mechanical (M) Model Is Compared For the Competitive (C)supporting

confidence: 80%

Topological impact of constrained fracture growth

et al. 2015

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“…Previous studies of two-dimensional fracture networks have shown a strong connection between fracture size and the degree of the corresponding node [8,23]. This follows from the chance of connecting with other fractures increases with the size of the fractures.…”

Section: Resultsmentioning

confidence: 86%

Network topology of the desert rose

et al. 2015

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Desert roses are gypsum crystals that consist of intersecting disks. We determine their geometrical structure using computer assisted tomography. By mapping the geometrical structure onto a graph, the topology of the desert rose is analyzed and compared to a model based on diffusion limited aggregation. By comparing the topology, we find that the model gets a number of the features of the real desert rose right, whereas others do not fit so well.

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“…Prominent contributions to a systematic understanding and modelling of our Planet have been provided by the analysis of satellite observations. [3][4][5][6][7][8] Motivated by such general observation and the underlying theoretical concepts, the present investigation is thus addressed to identify characteristic patterns and quantify the structure and dynamics of image sets acquired by the LANDSAT Thematic Mapper (TM) satellite in different locations worldwide with the general purpose to obtain meaningful indicators for assessing ecosystem organization, dynamics, stability, and functions of key relevance to the sustainable management of natural resources, social organizations and technological infrastructures.…”

Section: Introductionmentioning

confidence: 99%

Hurst exponent for fractal characterization of LANDSAT images

et al. 2014

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In this research the Hurst exponent H is used for quantifying the fractal features of LANDSAT images. The Hurst exponent is estimated by means of the Detrending Moving Average (DMA), an algorithm based on a generalized high-dimensional variance around a moving average low-pass filter. Hence, for a two-dimensional signal, the algorithm first generates an average response for different subarrays by varying the size of the moving low-pass filter. For each subarray the corresponding variance value is calculated by the difference between the original and the averaged signals. The value of the variance obtained at each subarray is then plotted on log-log axes, with the slope of the regression line corresponding to the Hurst exponent. The application of the algorithm to a set of LANDSAT imagery has allowed us to estimate the Hurst exponent of specific areas on Earth surface at subsequent time instances. According to the presented results, the value of the Hurst exponent is directly related to the changes in land use, showing a decreasing value when the area under study has been modified by natural processes or human intervention. Interestingly, natural areas presenting a gradual growth of man made activities or an increasing degree of pollution have a considerable reduction in their corresponding Hurst exponent.

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Fracture networks in sea ice

Cited by 13 publications

References 25 publications

Topological impact of constrained fracture growth

Topological impact of constrained fracture growth

Network topology of the desert rose

Hurst exponent for fractal characterization of LANDSAT images

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