Loading rate and mineralogical controls on tensile strength of rocks: a machine learning view
Machine learning models show the effects of loading rate and mineralogical composition on rock tensile strength. Difference between the indirect and direct tensile strengths becomes larger with a higher loading rate. Training with dissimilar mineralogical compositions reduces prediction reliability...
Saved in:
| Main Authors: | , , , |
|---|---|
| 其他作者: | |
| 格式: | Article |
| 語言: | English |
| 出版: |
2023
|
| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/170052 |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
| id |
sg-ntu-dr.10356-170052 |
|---|---|
| record_format |
dspace |
| spelling |
sg-ntu-dr.10356-1700522023-08-22T08:07:21Z Loading rate and mineralogical controls on tensile strength of rocks: a machine learning view Tie, Jiahao Meng, Wenzhao Wei, Mingdong Wu, Wei School of Civil and Environmental Engineering Engineering::Civil engineering Tensile Strength Loading Rate Machine learning models show the effects of loading rate and mineralogical composition on rock tensile strength. Difference between the indirect and direct tensile strengths becomes larger with a higher loading rate. Training with dissimilar mineralogical compositions reduces prediction reliability of machine learning models. 2023-08-22T08:07:21Z 2023-08-22T08:07:21Z 2023 Journal Article Tie, J., Meng, W., Wei, M. & Wu, W. (2023). Loading rate and mineralogical controls on tensile strength of rocks: a machine learning view. Rock Mechanics and Rock Engineering, 56(8), 6119-6125. https://dx.doi.org/10.1007/s00603-023-03354-8 0723-2632 https://hdl.handle.net/10356/170052 10.1007/s00603-023-03354-8 2-s2.0-85158144138 8 56 6119 6125 en Rock Mechanics and Rock Engineering © 2023 The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature. All rights reserved. |
| institution |
Nanyang Technological University |
| building |
NTU Library |
| continent |
Asia |
| country |
Singapore Singapore |
| content_provider |
NTU Library |
| collection |
DR-NTU |
| language |
English |
| topic |
Engineering::Civil engineering Tensile Strength Loading Rate |
| spellingShingle |
Engineering::Civil engineering Tensile Strength Loading Rate Tie, Jiahao Meng, Wenzhao Wei, Mingdong Wu, Wei Loading rate and mineralogical controls on tensile strength of rocks: a machine learning view |
| description |
Machine learning models show the effects of loading rate and mineralogical composition on rock tensile strength. Difference between the indirect and direct tensile strengths becomes larger with a higher loading rate. Training with dissimilar mineralogical compositions reduces prediction reliability of machine learning models. |
| author2 |
School of Civil and Environmental Engineering |
| author_facet |
School of Civil and Environmental Engineering Tie, Jiahao Meng, Wenzhao Wei, Mingdong Wu, Wei |
| format |
Article |
| author |
Tie, Jiahao Meng, Wenzhao Wei, Mingdong Wu, Wei |
| author_sort |
Tie, Jiahao |
| title |
Loading rate and mineralogical controls on tensile strength of rocks: a machine learning view |
| title_short |
Loading rate and mineralogical controls on tensile strength of rocks: a machine learning view |
| title_full |
Loading rate and mineralogical controls on tensile strength of rocks: a machine learning view |
| title_fullStr |
Loading rate and mineralogical controls on tensile strength of rocks: a machine learning view |
| title_full_unstemmed |
Loading rate and mineralogical controls on tensile strength of rocks: a machine learning view |
| title_sort |
loading rate and mineralogical controls on tensile strength of rocks: a machine learning view |
| publishDate |
2023 |
| url |
https://hdl.handle.net/10356/170052 |
| _version_ |
1779156801818722304 |