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A novel method for correcting scanline-observational bias of discontinuity orientation

Scanline observation is known to introduce an angular bias into the probability distribution of orientation in three-dimensional space. In this paper, numerical solutions expressing the functional relationship between the scanline-observational distribution (in one-dimensional space) and the inheren...

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Autores principales: Huang, Lei, Tang, Huiming, Tan, Qinwen, Wang, Dingjian, Wang, Liangqing, Ez Eldin, Mutasim A. M., Li, Changdong, Wu, Qiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4785530/
https://www.ncbi.nlm.nih.gov/pubmed/26961249
http://dx.doi.org/10.1038/srep22942
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author Huang, Lei
Tang, Huiming
Tan, Qinwen
Wang, Dingjian
Wang, Liangqing
Ez Eldin, Mutasim A. M.
Li, Changdong
Wu, Qiong
author_facet Huang, Lei
Tang, Huiming
Tan, Qinwen
Wang, Dingjian
Wang, Liangqing
Ez Eldin, Mutasim A. M.
Li, Changdong
Wu, Qiong
author_sort Huang, Lei
collection PubMed
description Scanline observation is known to introduce an angular bias into the probability distribution of orientation in three-dimensional space. In this paper, numerical solutions expressing the functional relationship between the scanline-observational distribution (in one-dimensional space) and the inherent distribution (in three-dimensional space) are derived using probability theory and calculus under the independence hypothesis of dip direction and dip angle. Based on these solutions, a novel method for obtaining the inherent distribution (also for correcting the bias) is proposed, an approach which includes two procedures: 1) Correcting the cumulative probabilities of orientation according to the solutions, and 2) Determining the distribution of the corrected orientations using approximation methods such as the one-sample Kolmogorov-Smirnov test. The inherent distribution corrected by the proposed method can be used for discrete fracture network (DFN) modelling, which is applied to such areas as rockmass stability evaluation, rockmass permeability analysis, rockmass quality calculation and other related fields. To maximize the correction capacity of the proposed method, the observed sample size is suggested through effectiveness tests for different distribution types, dispersions and sample sizes. The performance of the proposed method and the comparison of its correction capacity with existing methods are illustrated with two case studies.
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spelling pubmed-47855302016-03-11 A novel method for correcting scanline-observational bias of discontinuity orientation Huang, Lei Tang, Huiming Tan, Qinwen Wang, Dingjian Wang, Liangqing Ez Eldin, Mutasim A. M. Li, Changdong Wu, Qiong Sci Rep Article Scanline observation is known to introduce an angular bias into the probability distribution of orientation in three-dimensional space. In this paper, numerical solutions expressing the functional relationship between the scanline-observational distribution (in one-dimensional space) and the inherent distribution (in three-dimensional space) are derived using probability theory and calculus under the independence hypothesis of dip direction and dip angle. Based on these solutions, a novel method for obtaining the inherent distribution (also for correcting the bias) is proposed, an approach which includes two procedures: 1) Correcting the cumulative probabilities of orientation according to the solutions, and 2) Determining the distribution of the corrected orientations using approximation methods such as the one-sample Kolmogorov-Smirnov test. The inherent distribution corrected by the proposed method can be used for discrete fracture network (DFN) modelling, which is applied to such areas as rockmass stability evaluation, rockmass permeability analysis, rockmass quality calculation and other related fields. To maximize the correction capacity of the proposed method, the observed sample size is suggested through effectiveness tests for different distribution types, dispersions and sample sizes. The performance of the proposed method and the comparison of its correction capacity with existing methods are illustrated with two case studies. Nature Publishing Group 2016-03-10 /pmc/articles/PMC4785530/ /pubmed/26961249 http://dx.doi.org/10.1038/srep22942 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Huang, Lei
Tang, Huiming
Tan, Qinwen
Wang, Dingjian
Wang, Liangqing
Ez Eldin, Mutasim A. M.
Li, Changdong
Wu, Qiong
A novel method for correcting scanline-observational bias of discontinuity orientation
title A novel method for correcting scanline-observational bias of discontinuity orientation
title_full A novel method for correcting scanline-observational bias of discontinuity orientation
title_fullStr A novel method for correcting scanline-observational bias of discontinuity orientation
title_full_unstemmed A novel method for correcting scanline-observational bias of discontinuity orientation
title_short A novel method for correcting scanline-observational bias of discontinuity orientation
title_sort novel method for correcting scanline-observational bias of discontinuity orientation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4785530/
https://www.ncbi.nlm.nih.gov/pubmed/26961249
http://dx.doi.org/10.1038/srep22942
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