Predicting time-dependent pier scour depth with support vector regression
The temporal variation of local pier scour depth is very complex, especially for cases where the bed comprises a sediment mixture. Many semi-empirical models have been proposed to predict the time-dependent local pier scour depth. In this paper, an alternative approach, the support vector regression...
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2013
|
| Online Access: | https://hdl.handle.net/10356/96851 http://hdl.handle.net/10220/11643 |
| _version_ | 1811681266312937472 |
|---|---|
| author | Hong, Jian-Hao Goyal, Manish Kumar Chiew, Yee-Meng Chua, Lloyd Hock Chye |
| author2 | School of Civil and Environmental Engineering |
| author_facet | School of Civil and Environmental Engineering Hong, Jian-Hao Goyal, Manish Kumar Chiew, Yee-Meng Chua, Lloyd Hock Chye |
| author_sort | Hong, Jian-Hao |
| collection | NTU |
| description | The temporal variation of local pier scour depth is very complex, especially for cases where the bed comprises a sediment mixture. Many semi-empirical models have been proposed to predict the time-dependent local pier scour depth. In this paper, an alternative approach, the support vector regression method (SVR) is used to estimate the temporal variation of pier-scour depth with non-uniform sediments under clear-water conditions. Based on dimensional analyses, the temporal variation of scour depth was modeled as a function of seven dimensionless input parameters, namely flow shallowness (y/Dp), sediment coarseness (Dp/d50), densimetric Froude number (Fd), the difference between the actual and critical densimetric Froude number (Fd − Fdβ), geometric standard deviation of the sediment particle size distribution (σg), pier Froude number (U/gDp) and one of the following three dimensionless time scales (T1 = t/tR1, T2 = t/tR2 and T3 = t/tR3). The SVR model not only estimates the time-dependent scour depth more accurately than conventional regression models, but also provides results that are consistent with the physics of the scouring process. |
| first_indexed | 2024-10-01T03:38:13Z |
| format | Journal Article |
| id | ntu-10356/96851 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:38:13Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/968512020-03-07T11:43:38Z Predicting time-dependent pier scour depth with support vector regression Hong, Jian-Hao Goyal, Manish Kumar Chiew, Yee-Meng Chua, Lloyd Hock Chye School of Civil and Environmental Engineering The temporal variation of local pier scour depth is very complex, especially for cases where the bed comprises a sediment mixture. Many semi-empirical models have been proposed to predict the time-dependent local pier scour depth. In this paper, an alternative approach, the support vector regression method (SVR) is used to estimate the temporal variation of pier-scour depth with non-uniform sediments under clear-water conditions. Based on dimensional analyses, the temporal variation of scour depth was modeled as a function of seven dimensionless input parameters, namely flow shallowness (y/Dp), sediment coarseness (Dp/d50), densimetric Froude number (Fd), the difference between the actual and critical densimetric Froude number (Fd − Fdβ), geometric standard deviation of the sediment particle size distribution (σg), pier Froude number (U/gDp) and one of the following three dimensionless time scales (T1 = t/tR1, T2 = t/tR2 and T3 = t/tR3). The SVR model not only estimates the time-dependent scour depth more accurately than conventional regression models, but also provides results that are consistent with the physics of the scouring process. 2013-07-17T02:30:43Z 2019-12-06T19:35:44Z 2013-07-17T02:30:43Z 2019-12-06T19:35:44Z 2012 2012 Journal Article Hong, J.-H., Goyal, M. K., Chiew, Y.-M.,& Chua, L. H. C. (2012). Predicting time-dependent pier scour depth with support vector regression. Journal of Hydrology, 468-469, 241-248. 0022-1694 https://hdl.handle.net/10356/96851 http://hdl.handle.net/10220/11643 10.1016/j.jhydrol.2012.08.038 en Journal of hydrology © 2012 Elsevier B.V. |
| spellingShingle | Hong, Jian-Hao Goyal, Manish Kumar Chiew, Yee-Meng Chua, Lloyd Hock Chye Predicting time-dependent pier scour depth with support vector regression |
| title | Predicting time-dependent pier scour depth with support vector regression |
| title_full | Predicting time-dependent pier scour depth with support vector regression |
| title_fullStr | Predicting time-dependent pier scour depth with support vector regression |
| title_full_unstemmed | Predicting time-dependent pier scour depth with support vector regression |
| title_short | Predicting time-dependent pier scour depth with support vector regression |
| title_sort | predicting time dependent pier scour depth with support vector regression |
| url | https://hdl.handle.net/10356/96851 http://hdl.handle.net/10220/11643 |
| work_keys_str_mv | AT hongjianhao predictingtimedependentpierscourdepthwithsupportvectorregression AT goyalmanishkumar predictingtimedependentpierscourdepthwithsupportvectorregression AT chiewyeemeng predictingtimedependentpierscourdepthwithsupportvectorregression AT chualloydhockchye predictingtimedependentpierscourdepthwithsupportvectorregression |