Unknown

Dataset Information

0

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


ABSTRACT: 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.

SUBMITTER: Huang L 

PROVIDER: S-EPMC4785530 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

altmetric image

Publications

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

Huang Lei L   Tang Huiming H   Tan Qinwen Q   Wang Dingjian D   Wang Liangqing L   Ez Eldin Mutasim A M MA   Li Changdong C   Wu Qiong Q  

Scientific reports 20160310


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  ...[more]

Similar Datasets

| S-EPMC3276270 | biostudies-literature
| S-EPMC7652792 | biostudies-literature
| S-EPMC2811084 | biostudies-literature
| S-EPMC8777061 | biostudies-literature
| S-EPMC4592333 | biostudies-literature
| S-EPMC3546795 | biostudies-literature
| S-EPMC4653383 | biostudies-literature
| S-EPMC8494131 | biostudies-literature
| S-EPMC10103949 | biostudies-literature
| S-EPMC3129672 | biostudies-literature