Correlation between the Joint Roughness Coefficient and Rock Joint Statistical Parameters at Different Sampling Intervals
Joint roughness coefficient (JRC) is a major factor that affects the mechanical properties of rock joints. Statistical methods that are used to calculate the JRC increasingly depend on a sampling interval (Δx). The variation rules of fitting parameters a, b, and b/a at different Δx values were analy...
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2019-01-01
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Series: | Advances in Civil Engineering |
Online Access: | http://dx.doi.org/10.1155/2019/1643842 |
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doaj-b961ba06ec0b4f6c9b1ee9ba219ef7ab2020-11-25T00:33:42ZengHindawi LimitedAdvances in Civil Engineering1687-80861687-80942019-01-01201910.1155/2019/16438421643842Correlation between the Joint Roughness Coefficient and Rock Joint Statistical Parameters at Different Sampling IntervalsMan Huang0Cia-chu Xia1Peng Sha2Cheng-rong Ma3Shi-gui Du4Ph.D., Department of Geotechnical Engineering, Tongji University, Shanghai 200092, ChinaProfessor, Department of Geotechnical Engineering, Tongji University, Shanghai 200092, ChinaLecturer, College of Civil Engineering, Shaoxing University, 508 Huancheng West Road, Shaoxing 312000, ChinaPh.D., Department of Geotechnical Engineering, Tongji University, Shanghai 200092, ChinaProfessor, College of Civil Engineering, Shaoxing University, 508 Huancheng West Road, Shaoxing 312000, ChinaJoint roughness coefficient (JRC) is a major factor that affects the mechanical properties of rock joints. Statistical methods that are used to calculate the JRC increasingly depend on a sampling interval (Δx). The variation rules of fitting parameters a, b, and b/a at different Δx values were analyzed on the basis of the relationship between the JRC and statistical parameter Z2. The relationship between the fitting parameters a and b was deduced in accordance with the ten standard profiles proposed by Barton. Empirical formulas for the JRC, Z2, and Δx were also established. The estimation accuracy of the JRC was the highest in the analysis of Δx values within 0.1–5.0 mm. JRC tests were conducted through inverse value comparative analysis. Results showed that the outcome calculated using the general formula and the JRC inverse values demonstrate improved agreement and verify the rationality of the general formula. The proposed formula can perform rapid and simple JRC calculation within the Δx range of 0.1–5.0 mm using Z2, thereby indicating favorable application prospects.http://dx.doi.org/10.1155/2019/1643842 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Man Huang Cia-chu Xia Peng Sha Cheng-rong Ma Shi-gui Du |
spellingShingle |
Man Huang Cia-chu Xia Peng Sha Cheng-rong Ma Shi-gui Du Correlation between the Joint Roughness Coefficient and Rock Joint Statistical Parameters at Different Sampling Intervals Advances in Civil Engineering |
author_facet |
Man Huang Cia-chu Xia Peng Sha Cheng-rong Ma Shi-gui Du |
author_sort |
Man Huang |
title |
Correlation between the Joint Roughness Coefficient and Rock Joint Statistical Parameters at Different Sampling Intervals |
title_short |
Correlation between the Joint Roughness Coefficient and Rock Joint Statistical Parameters at Different Sampling Intervals |
title_full |
Correlation between the Joint Roughness Coefficient and Rock Joint Statistical Parameters at Different Sampling Intervals |
title_fullStr |
Correlation between the Joint Roughness Coefficient and Rock Joint Statistical Parameters at Different Sampling Intervals |
title_full_unstemmed |
Correlation between the Joint Roughness Coefficient and Rock Joint Statistical Parameters at Different Sampling Intervals |
title_sort |
correlation between the joint roughness coefficient and rock joint statistical parameters at different sampling intervals |
publisher |
Hindawi Limited |
series |
Advances in Civil Engineering |
issn |
1687-8086 1687-8094 |
publishDate |
2019-01-01 |
description |
Joint roughness coefficient (JRC) is a major factor that affects the mechanical properties of rock joints. Statistical methods that are used to calculate the JRC increasingly depend on a sampling interval (Δx). The variation rules of fitting parameters a, b, and b/a at different Δx values were analyzed on the basis of the relationship between the JRC and statistical parameter Z2. The relationship between the fitting parameters a and b was deduced in accordance with the ten standard profiles proposed by Barton. Empirical formulas for the JRC, Z2, and Δx were also established. The estimation accuracy of the JRC was the highest in the analysis of Δx values within 0.1–5.0 mm. JRC tests were conducted through inverse value comparative analysis. Results showed that the outcome calculated using the general formula and the JRC inverse values demonstrate improved agreement and verify the rationality of the general formula. The proposed formula can perform rapid and simple JRC calculation within the Δx range of 0.1–5.0 mm using Z2, thereby indicating favorable application prospects. |
url |
http://dx.doi.org/10.1155/2019/1643842 |
work_keys_str_mv |
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