Full three-dimensional modelling of curvature-dependent snow metamorphism: first results and comparison with experimental tomographic data

Flin, Frédéric; Brzoska, Jean-Bruno; Lesaffre, Bernard; Coléou, Cécile; Pieritz, Romeu André

doi:10.1088/0022-3727/36/10a/310

Cited by 85 publications

(115 citation statements)

References 16 publications

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“…The real part is that of Warren and Brandt (2008). For the imaginary part, Gosse et al (1995) recommend 4.26×10 −4 at −22 • C, with an error of 3% and a temperature dependence of 0.6% K −1 (Warren and Brandt, 2008), so that our value is within the acceptable range. The effect of using modified optical constants is small.…”

Section: Reflectance Modeling At 1310 Nmmentioning

confidence: 64%

“…Snow grain size has long been used as a substitute for SSA (Gow, 1969), but given the variety of grain shapes, from dendritic to rounded to hollow, the definition of grain size is ambiguous and observer-dependent (Aoki et al, 2000). With the example of hollow depth hoar crystals, Taillandier et al (2007) have shown that effective grain size deduced from SSA (Eq.…”

Section: Introductionmentioning

confidence: 99%

“…The smaller structures are easily perturbed by the liquid and by microtoming, and are often unresolved by optical photography. Lastly, X-ray tomography can also produce SSA values (Flin et al, 2003;Kerbrat et al, 2008;Kaempfer and Schneebeli, 2007) but this is not easy to use in the field and the resolution is currently insufficient if SSA>70 m 2 kg −1 (Kerbrat et al, 2008), a value frequently exceeded in fresh snow.…”

Section: Introductionmentioning

confidence: 99%

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Measurement of the specific surface area of snow using infrared reflectance in an integrating sphere at 1310 and 1550 nm

et al. 2009

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Abstract. Even though the specific surface area (SSA) and the snow area index (SAI) of snow are crucial variables to determine the chemical and climatic impact of the snow cover, few data are available on the subject. We propose here a novel method to measure snow SSA and SAI. It is based on the measurement of the hemispherical infrared reflectance of snow samples using the DUFISSS instrument (DUal Frequency Integrating Sphere for Snow SSA measurement). DUFISSS uses the 1310 or 1550 nm radiation of laser diodes, an integrating sphere 15 cm in diameter, and InGaAs photodiodes. For SSA<60 m 2 kg −1 , we use the 1310 nm radiation, reflectance is between 15 and 50% and the accuracy of SSA determination is 10%. For SSA>60 m 2 kg −1 , snow is usually of low density (typically 30 to 100 kg m −3 ), resulting in insufficient optical depth and 1310 nm radiation reaches the bottom of the sample, causing artifacts. The 1550 nm radiation is therefore used for SSA>60 m 2 kg −1 . Reflectance is then in the range 5 to 12% and the accuracy on SSA is 12%. We propose empirical equations to determine SSA from reflectance at both wavelengths, with that for 1310 nm taking into account the snow density. DUFISSS has been used to measure the SSA of snow and the SAI of snowpacks in polar and Alpine regions.

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Section: Reflectance Modeling At 1310 Nmmentioning

confidence: 64%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Measurement of the specific surface area of snow using infrared reflectance in an integrating sphere at 1310 and 1550 nm

et al. 2009

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“…Synchrotron radiation produces Xray beams which are highly collimated and have orders of magnitude higher intensities than those from bench-top devices. This approach is particularly adapted to the study of the snow pack microstructure, because it gives µm voxel resolution images in a much shorter scanning time Flin et al, 2003;Flin and Brzoska, 2008). The aim of this study was to set up a technique to enable such a highresolution synchrotron-based tomography of tiny (sub-mm) graupel particles.…”

Section: F Enzmann Et Al: 3-d Imaging and Quantification Of Graupelmentioning

confidence: 99%

3-D imaging and quantification of graupel porosity by synchrotron-based micro-tomography

et al. 2011

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Abstract. The air bubble structure is an important parameter to determine the radiation properties of graupel and hailstones. For 3-D imaging of this structure at micron resolution, a cryo-stage was developed. This stage was used at the tomography beamline of the Swiss Light Source (SLS) synchrotron facility. The cryo-stage setup provides for the first time 3-D-data on the individual pore morphology of ice particles down to infrared wavelength resolution. In the present study, both sub-mm size natural and artificial ice particles rimed in a wind tunnel were investigated. In the natural rimed ice particles, Y-shaped air-filled closed pores were found. When kept for half an hour at −8 • C, this morphology transformed into smaller and more rounded voids well known from literature. Therefore, these round structures seem to represent an artificial rather than in situ pore structure, in contrast to the observed y-shaped structures found in the natural ice particles. Hence, for morphological studies on natural ice samples, special care must be taken to minimize any thermal cycling between sampling and measurement, with least artifact production at liquid nitrogen temperatures.

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“…After segmenting the data into snow and pores, a method to measure local curvature from snow surface normal vectors and porosity medial axis was developed [13]. This technique has been further developed by Flin et al [14] and explored using µXRT data to study curvature evolution over time and to model grain growth and the sintering process [15].…”

Section: Introductionmentioning

confidence: 99%

Automated measurement of sintering degree in optical microscopy through image analysis of particle joins

Nellros

Thurley

Jönsson

et al. 2015

Pattern Recognition

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In general terms, sintering describes the bonding of particles into a more coherent structure, where joins form between packed particles, usually as a result of heating. Characterization of sintering is an important topic in the fields of metallurgy, steel, iron ore pellets, ceramics, and snow for understanding material properties and material strength. Characterization using image analysis has been applied in a number of these fields but is either semi-automatic, requiring human interaction in the analysis, or based on statistical sampling and stereology to characterize the sample. This paper presents a novel fully automatic image analysis algorithm to analyze and determine the degree of sintering based on analysis of the particle joins and structure. Quantitative image analysis of the sintering degree is demonstrated for samples of iron ore pellets but could be readily applied to other packed particle materials. Microscope images of polished cross-sections of iron ore pellets have been imaged in their entirety and automated analysis of hundreds of images has been performed. Joins between particles have been identified based on morphological image processing and features have been calculated based on the geometric properties and curvature of these joins. The features have been analyzed and determined to hold discriminative power based on a statistical evaluation using the Welch t-test and display properties consistent with sintering theory and results from traditional pellet diameter measurements on the heated samples.

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Full three-dimensional modelling of curvature-dependent snow metamorphism: first results and comparison with experimental tomographic data

Cited by 85 publications

References 16 publications

Measurement of the specific surface area of snow using infrared reflectance in an integrating sphere at 1310 and 1550 nm

Measurement of the specific surface area of snow using infrared reflectance in an integrating sphere at 1310 and 1550 nm

3-D imaging and quantification of graupel porosity by synchrotron-based micro-tomography

Automated measurement of sintering degree in optical microscopy through image analysis of particle joins

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