An empirical approach of overbreak resistance factor for tunnel blasting
© 2019 Elsevier Ltd The assessment of overbreak is proposed by means of a novel empirical approach; the ‘overbreak resistance factor’ (ORF), to predict and manage the overbreak phenomenon in tunnel drill-and-blast operations. The proposed ORF is formulated by analysing the relationship between uncon...
| Main Authors: | , , |
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| Format: | Journal Article |
| Language: | English |
| Published: |
PERGAMON-ELSEVIER SCIENCE LTD
2019
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| Online Access: | http://hdl.handle.net/20.500.11937/76946 |
| _version_ | 1848763792852254720 |
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| author | Jang, Hyong Doo Kawamura, Y. Shinji, U. |
| author_facet | Jang, Hyong Doo Kawamura, Y. Shinji, U. |
| author_sort | Jang, Hyong Doo |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 2019 Elsevier Ltd The assessment of overbreak is proposed by means of a novel empirical approach; the ‘overbreak resistance factor’ (ORF), to predict and manage the overbreak phenomenon in tunnel drill-and-blast operations. The proposed ORF is formulated by analysing the relationship between uncontrollable parameters of the overbreak phenomenon, i.e., geological parameters, and the corresponding overbreak measurements. Ninety data sets were collected from the Shin-Hakoishi Tunnel operation in Japan. Initially, an identical weight was applied to all geological parameters to generate ORF subfactors. The contribution of these subfactors to the measured overbreak was analysed through the use of five overbreak prediction artificial neuron network (ANN) models. A sensitivity analysis was conducted on the ANN models to reveal the contributions of input factors to measured overbreak. The discontinuities factors demonstrated the highest influence on overbreak with an overall sensitivity of 55.20%, whereas the strength factors, the weathering factors and the face condition factors showed less sensitivity, at 27.18%, 9.43%, and 8.18% respectively. The sensitivity analysis results were applied back to the initial unweighted data sets to generate a weighted record of subfactors. The ORF values showed a clear inverse proportional relation to the measured overbreak values, through linear regression analysis. Consequently, a five-step ORF prediction chart was developed, which can be directly applied to estimate overbreak in any drill-and-blast tunnel project. |
| first_indexed | 2025-11-14T11:09:06Z |
| format | Journal Article |
| id | curtin-20.500.11937-76946 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:09:06Z |
| publishDate | 2019 |
| publisher | PERGAMON-ELSEVIER SCIENCE LTD |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-769462021-08-06T06:08:37Z An empirical approach of overbreak resistance factor for tunnel blasting Jang, Hyong Doo Kawamura, Y. Shinji, U. Science & Technology Technology Construction & Building Technology Engineering, Civil Engineering Overbreak Tunnel Blast damage ANN ORF ROCK MASS QUALITY BLASTABILITY SYSTEM FRAGMENTATION PREDICTION PARAMETERS DAMAGE © 2019 Elsevier Ltd The assessment of overbreak is proposed by means of a novel empirical approach; the ‘overbreak resistance factor’ (ORF), to predict and manage the overbreak phenomenon in tunnel drill-and-blast operations. The proposed ORF is formulated by analysing the relationship between uncontrollable parameters of the overbreak phenomenon, i.e., geological parameters, and the corresponding overbreak measurements. Ninety data sets were collected from the Shin-Hakoishi Tunnel operation in Japan. Initially, an identical weight was applied to all geological parameters to generate ORF subfactors. The contribution of these subfactors to the measured overbreak was analysed through the use of five overbreak prediction artificial neuron network (ANN) models. A sensitivity analysis was conducted on the ANN models to reveal the contributions of input factors to measured overbreak. The discontinuities factors demonstrated the highest influence on overbreak with an overall sensitivity of 55.20%, whereas the strength factors, the weathering factors and the face condition factors showed less sensitivity, at 27.18%, 9.43%, and 8.18% respectively. The sensitivity analysis results were applied back to the initial unweighted data sets to generate a weighted record of subfactors. The ORF values showed a clear inverse proportional relation to the measured overbreak values, through linear regression analysis. Consequently, a five-step ORF prediction chart was developed, which can be directly applied to estimate overbreak in any drill-and-blast tunnel project. 2019 Journal Article http://hdl.handle.net/20.500.11937/76946 10.1016/j.tust.2019.103060 English http://creativecommons.org/licenses/by-nc-nd/4.0/ PERGAMON-ELSEVIER SCIENCE LTD fulltext |
| spellingShingle | Science & Technology Technology Construction & Building Technology Engineering, Civil Engineering Overbreak Tunnel Blast damage ANN ORF ROCK MASS QUALITY BLASTABILITY SYSTEM FRAGMENTATION PREDICTION PARAMETERS DAMAGE Jang, Hyong Doo Kawamura, Y. Shinji, U. An empirical approach of overbreak resistance factor for tunnel blasting |
| title | An empirical approach of overbreak resistance factor for tunnel blasting |
| title_full | An empirical approach of overbreak resistance factor for tunnel blasting |
| title_fullStr | An empirical approach of overbreak resistance factor for tunnel blasting |
| title_full_unstemmed | An empirical approach of overbreak resistance factor for tunnel blasting |
| title_short | An empirical approach of overbreak resistance factor for tunnel blasting |
| title_sort | empirical approach of overbreak resistance factor for tunnel blasting |
| topic | Science & Technology Technology Construction & Building Technology Engineering, Civil Engineering Overbreak Tunnel Blast damage ANN ORF ROCK MASS QUALITY BLASTABILITY SYSTEM FRAGMENTATION PREDICTION PARAMETERS DAMAGE |
| url | http://hdl.handle.net/20.500.11937/76946 |