Changes
On December 16, 2020 at 11:33:09 AM UTC, Administrator:
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Renamed resource Data Access over HTTP to Data Access in Unconfined compression experiments and 3D CT images of spherical model snow and RG snow samples
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Changed value of field
resource_size
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in resource Data Access in Unconfined compression experiments and 3D CT images of spherical model snow and RG snow samples -
Changed value of field
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of resource Data Access to{"allowed_users": "", "level": "public", "shared_secret": ""}
(previously{"shared_secret": "", "allowed_users": "", "level": "public"}
) in Unconfined compression experiments and 3D CT images of spherical model snow and RG snow samples
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25 | "doi": "10.16904/envidat.83", | 25 | "doi": "10.16904/envidat.83", | ||
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39 | "license_title": "ODbL with Database Contents License (DbCL)", | 39 | "license_title": "ODbL with Database Contents License (DbCL)", | ||
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n | 46 | "metadata_modified": "2020-12-16T11:32:52.370557", | n | 46 | "metadata_modified": "2020-12-16T11:33:09.778686", |
47 | "name": "spherical-model-snow-compression-3dct", | 47 | "name": "spherical-model-snow-compression-3dct", | ||
48 | "notes": "For the investigation of microstructural and mechanical | 48 | "notes": "For the investigation of microstructural and mechanical | ||
49 | properties of snow unconfined compression experiments and 3D computed | 49 | properties of snow unconfined compression experiments and 3D computed | ||
50 | tomography (CT) imaging were performed on sintered rounded grain snow | 50 | tomography (CT) imaging were performed on sintered rounded grain snow | ||
51 | and spherical model snow. The spherical model snow was generated to | 51 | and spherical model snow. The spherical model snow was generated to | ||
52 | create geometrically simplified, well-defined microstructures for | 52 | create geometrically simplified, well-defined microstructures for | ||
53 | calibration of numerical models, such as discrete element models (DEM) | 53 | calibration of numerical models, such as discrete element models (DEM) | ||
54 | in which the microstructure is represented by spherical particles. | 54 | in which the microstructure is represented by spherical particles. | ||
55 | \r\nIn the experiments, microstructural variation was created by | 55 | \r\nIn the experiments, microstructural variation was created by | ||
56 | varying the sintering time (contact size) and the density of the ice | 56 | varying the sintering time (contact size) and the density of the ice | ||
57 | sphere samples (number of contacts). The 3D CT images allow for a | 57 | sphere samples (number of contacts). The 3D CT images allow for a | ||
58 | complete reconstruction of the entire experimental sample (cylindrical | 58 | complete reconstruction of the entire experimental sample (cylindrical | ||
59 | sample dimension: diameter = 33.6 mm; height = 14 mm). \r\n\r\n", | 59 | sample dimension: diameter = 33.6 mm; height = 14 mm). \r\n\r\n", | ||
60 | "num_resources": 4, | 60 | "num_resources": 4, | ||
61 | "num_tags": 6, | 61 | "num_tags": 6, | ||
62 | "organization": { | 62 | "organization": { | ||
63 | "approval_status": "approved", | 63 | "approval_status": "approved", | ||
64 | "created": "2018-11-15T15:27:32.106204", | 64 | "created": "2018-11-15T15:27:32.106204", | ||
65 | "description": "The core topic of the team \"Snow Physics\" is | 65 | "description": "The core topic of the team \"Snow Physics\" is | ||
66 | structure and property of snow and firn at different scales. Our most | 66 | structure and property of snow and firn at different scales. Our most | ||
67 | important tools in the cold laboratory are micro-computed tomography | 67 | important tools in the cold laboratory are micro-computed tomography | ||
68 | (micro-CT), nature-identical snow production, and our in-house | 68 | (micro-CT), nature-identical snow production, and our in-house | ||
69 | designed snow-breeders.\r\n\r\nBased on the three-dimensional | 69 | designed snow-breeders.\r\n\r\nBased on the three-dimensional | ||
70 | representation of snow, we can now calculate fundamental structural | 70 | representation of snow, we can now calculate fundamental structural | ||
71 | parameters as density variations at a spatial resolution of a few | 71 | parameters as density variations at a spatial resolution of a few | ||
72 | millimeters, e.g. revealing the finely layered structure of weak | 72 | millimeters, e.g. revealing the finely layered structure of weak | ||
73 | layers or of polar firn. In addition, the readily available data are | 73 | layers or of polar firn. In addition, the readily available data are | ||
74 | used to calculate the correlation function in all 3D, which enables a | 74 | used to calculate the correlation function in all 3D, which enables a | ||
75 | deeper understanding of the interactions between structure and | 75 | deeper understanding of the interactions between structure and | ||
76 | functional properties, e.g. for microwaves.\r\n\r\nIn addition, we are | 76 | functional properties, e.g. for microwaves.\r\n\r\nIn addition, we are | ||
77 | able to use the exact microstructure of snow for numerical | 77 | able to use the exact microstructure of snow for numerical | ||
78 | simulations. Our own or adapted codes allow to calculate thermal | 78 | simulations. Our own or adapted codes allow to calculate thermal | ||
79 | conductivity, mechanical properties, and optical properties. Direct | 79 | conductivity, mechanical properties, and optical properties. Direct | ||
80 | numerical simulation proves to be a highly valuable tool to understand | 80 | numerical simulation proves to be a highly valuable tool to understand | ||
81 | the complexity of snow.\r\n\r\nOur micro-CT is equipped with the | 81 | the complexity of snow.\r\n\r\nOur micro-CT is equipped with the | ||
82 | ability to perform time-lapse tomography using so called | 82 | ability to perform time-lapse tomography using so called | ||
83 | snow-breeders. The snow breeder made the first in-situ time-lapse | 83 | snow-breeders. The snow breeder made the first in-situ time-lapse | ||
84 | movie of metamorphosing snow under a temperature gradient | 84 | movie of metamorphosing snow under a temperature gradient | ||
85 | possible.\r\n\r\nOur developments don't stop at the microstructure. | 85 | possible.\r\n\r\nOur developments don't stop at the microstructure. | ||
86 | The quantification of snow properties at the larger scale of a snow | 86 | The quantification of snow properties at the larger scale of a snow | ||
87 | profile or on a field requires new techniques to link the micro- to | 87 | profile or on a field requires new techniques to link the micro- to | ||
88 | the macro-scale. For this purpose we developed the SnowMicroPen, a | 88 | the macro-scale. For this purpose we developed the SnowMicroPen, a | ||
89 | high-resolution penetrometer, which is able to discern different snow | 89 | high-resolution penetrometer, which is able to discern different snow | ||
90 | types using signal processing. Near-infrared photography has become a | 90 | types using signal processing. Near-infrared photography has become a | ||
91 | standard tool to quantify spatial variation of the specific surface | 91 | standard tool to quantify spatial variation of the specific surface | ||
92 | area, and, concurrently, the equivalent optical grain size. Currently, | 92 | area, and, concurrently, the equivalent optical grain size. Currently, | ||
93 | we are developing new optical techniques which try to measure density | 93 | we are developing new optical techniques which try to measure density | ||
94 | and specific surface area at the same time.", | 94 | and specific surface area at the same time.", | ||
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98 | "is_organization": true, | 98 | "is_organization": true, | ||
99 | "name": "snow-physics", | 99 | "name": "snow-physics", | ||
100 | "state": "active", | 100 | "state": "active", | ||
101 | "title": "Snow Physics", | 101 | "title": "Snow Physics", | ||
102 | "type": "organization" | 102 | "type": "organization" | ||
103 | }, | 103 | }, | ||
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106 | "publication": "{\"publisher\": \"EnviDat\", \"publication_year\": | 106 | "publication": "{\"publisher\": \"EnviDat\", \"publication_year\": | ||
107 | \"2019\"}", | 107 | \"2019\"}", | ||
108 | "publication_state": "published", | 108 | "publication_state": "published", | ||
109 | "related_datasets": "", | 109 | "related_datasets": "", | ||
110 | "related_publications": " * Willibald C., Scheuber S., L\u00f6we H., | 110 | "related_publications": " * Willibald C., Scheuber S., L\u00f6we H., | ||
111 | Dual J. and Schneebeli M. (2019). Ice Spheres as Model Snow: Tumbling, | 111 | Dual J. and Schneebeli M. (2019). Ice Spheres as Model Snow: Tumbling, | ||
112 | Sintering, and Mechanical Tests. Front. Earth Sci. 7:229. | 112 | Sintering, and Mechanical Tests. Front. Earth Sci. 7:229. | ||
113 | /10.3389/feart.2019.00229](https://doi.org/10.3389/feart.2019.00229)", | 113 | /10.3389/feart.2019.00229](https://doi.org/10.3389/feart.2019.00229)", | ||
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231 | "id": "b34a4a43-c989-44f9-9047-177bb6c1e64b", | 232 | "id": "b34a4a43-c989-44f9-9047-177bb6c1e64b", | ||
232 | "name": "3D CT IMAGES", | 233 | "name": "3D CT IMAGES", | ||
233 | "state": "active", | 234 | "state": "active", | ||
234 | "vocabulary_id": null | 235 | "vocabulary_id": null | ||
235 | }, | 236 | }, | ||
236 | { | 237 | { | ||
237 | "display_name": "DISCRETE ELEMENT MODELLING", | 238 | "display_name": "DISCRETE ELEMENT MODELLING", | ||
238 | "id": "6120840b-365a-4a50-973b-7d360313a363", | 239 | "id": "6120840b-365a-4a50-973b-7d360313a363", | ||
239 | "name": "DISCRETE ELEMENT MODELLING", | 240 | "name": "DISCRETE ELEMENT MODELLING", | ||
240 | "state": "active", | 241 | "state": "active", | ||
241 | "vocabulary_id": null | 242 | "vocabulary_id": null | ||
242 | }, | 243 | }, | ||
243 | { | 244 | { | ||
244 | "display_name": "MICROSTRUCTURE", | 245 | "display_name": "MICROSTRUCTURE", | ||
245 | "id": "a35c8ef3-af06-46f3-890d-3038179b53c7", | 246 | "id": "a35c8ef3-af06-46f3-890d-3038179b53c7", | ||
246 | "name": "MICROSTRUCTURE", | 247 | "name": "MICROSTRUCTURE", | ||
247 | "state": "active", | 248 | "state": "active", | ||
248 | "vocabulary_id": null | 249 | "vocabulary_id": null | ||
249 | }, | 250 | }, | ||
250 | { | 251 | { | ||
251 | "display_name": "SNOW MECHANICS", | 252 | "display_name": "SNOW MECHANICS", | ||
252 | "id": "31bab9c5-b32e-452d-bce1-f7500696beab", | 253 | "id": "31bab9c5-b32e-452d-bce1-f7500696beab", | ||
253 | "name": "SNOW MECHANICS", | 254 | "name": "SNOW MECHANICS", | ||
254 | "state": "active", | 255 | "state": "active", | ||
255 | "vocabulary_id": null | 256 | "vocabulary_id": null | ||
256 | }, | 257 | }, | ||
257 | { | 258 | { | ||
258 | "display_name": "SPHERICAL MODEL SNOW", | 259 | "display_name": "SPHERICAL MODEL SNOW", | ||
259 | "id": "b739561a-ce20-4821-a574-d8407db654f1", | 260 | "id": "b739561a-ce20-4821-a574-d8407db654f1", | ||
260 | "name": "SPHERICAL MODEL SNOW", | 261 | "name": "SPHERICAL MODEL SNOW", | ||
261 | "state": "active", | 262 | "state": "active", | ||
262 | "vocabulary_id": null | 263 | "vocabulary_id": null | ||
263 | }, | 264 | }, | ||
264 | { | 265 | { | ||
265 | "display_name": "UNCONFINED COMPRESSION EXPERIMENTS", | 266 | "display_name": "UNCONFINED COMPRESSION EXPERIMENTS", | ||
266 | "id": "874ed67e-5e22-4b6c-a65c-c020e2cebc8f", | 267 | "id": "874ed67e-5e22-4b6c-a65c-c020e2cebc8f", | ||
267 | "name": "UNCONFINED COMPRESSION EXPERIMENTS", | 268 | "name": "UNCONFINED COMPRESSION EXPERIMENTS", | ||
268 | "state": "active", | 269 | "state": "active", | ||
269 | "vocabulary_id": null | 270 | "vocabulary_id": null | ||
270 | } | 271 | } | ||
271 | ], | 272 | ], | ||
272 | "title": "Unconfined compression experiments and 3D CT images of | 273 | "title": "Unconfined compression experiments and 3D CT images of | ||
273 | spherical model snow and RG snow samples", | 274 | spherical model snow and RG snow samples", | ||
274 | "type": "dataset", | 275 | "type": "dataset", | ||
275 | "url": null, | 276 | "url": null, | ||
276 | "version": "1.0" | 277 | "version": "1.0" | ||
277 | } | 278 | } |