STABILITY ANALYSIS OF TUNNEL SUPPORT SYSTEMS USING NUMERICAL AND INTELLIGENT SIMULATIONS (CASE STUDY: KOUHIN TUNNEL OF QAZVIN-RASHT RAILWAY)
According to underground construction development and its high cost process, an accurate assessment and prevention of probable risks are of significant importance. Different methods have been developed to assess underground constructions. In this paper, the aim is to develop a new soft computing mod...
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| Format: | Article |
| Language: | English |
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Faculty of Mining, Geology and Petroleum Engineering
2019-01-01
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| Series: | Rudarsko-geološko-naftni Zbornik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/318474 |
| _version_ | 1797207510553198592 |
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| author | Reza Mikaeil Hadi Bakhshinezhad Sina Shaffiee Haghshenas Mohammad Ataei |
| author_facet | Reza Mikaeil Hadi Bakhshinezhad Sina Shaffiee Haghshenas Mohammad Ataei |
| author_sort | Reza Mikaeil |
| collection | DOAJ |
| description | According to underground construction development and its high cost process, an accurate assessment and prevention of probable risks are of significant importance. Different methods have been developed to assess underground constructions. In this paper, the aim is to develop a new soft computing model to evaluate tunnel support systems. Firstly, a numerical analysis was performed using the explicit finite difference model by FLAC2D software to excavate a sequence model and support system installation. The design loads including the axial force, moment, and shear force were calculated for some important points of the support system including the crown, the middle of the bottom and the side walls. In order to analyse the stability of the support system, the section points were evaluated into 3 clusters by the artificial bee colony as a meta-heuristic algorithm and a k-means algorithm using Matlab software. The results of clustering were compared by the safety factor of the support system. The results indicated that the section points that are in cluster 1 have a lower safety factor than clusters 3 and 2, respectively. It concluded that the artificial bee colony can be reliably used in the initial assessment of tunnel support systems based on the axial force, moment, and shear force. |
| first_indexed | 2024-04-24T09:24:04Z |
| format | Article |
| id | doaj.art-e1ac8a23334a4db1bf616bfd8bf73c57 |
| institution | Directory Open Access Journal |
| issn | 0353-4529 1849-0409 |
| language | English |
| last_indexed | 2024-04-24T09:24:04Z |
| publishDate | 2019-01-01 |
| publisher | Faculty of Mining, Geology and Petroleum Engineering |
| record_format | Article |
| series | Rudarsko-geološko-naftni Zbornik |
| spelling | doaj.art-e1ac8a23334a4db1bf616bfd8bf73c572024-04-15T15:26:02ZengFaculty of Mining, Geology and Petroleum EngineeringRudarsko-geološko-naftni Zbornik0353-45291849-04092019-01-0134211010.17794/rgn.2019.2.1STABILITY ANALYSIS OF TUNNEL SUPPORT SYSTEMS USING NUMERICAL AND INTELLIGENT SIMULATIONS (CASE STUDY: KOUHIN TUNNEL OF QAZVIN-RASHT RAILWAY)Reza Mikaeil0Hadi Bakhshinezhad1Sina Shaffiee Haghshenas2Mohammad Ataei3Dept. of Mining and Metallurgical Engineering, Urmia University of Technology, Urmia, IranDept. of Mining and Metallurgical Engineering, Urmia University of Technology, Urmia, IranYoung Researchers and Elite Club, Rasht Branch, Islamic Azad University, Rasht, IranFaculty of Mining, Petroleum & Geophysics, Shahrood University of Technology, Shahrood, IranAccording to underground construction development and its high cost process, an accurate assessment and prevention of probable risks are of significant importance. Different methods have been developed to assess underground constructions. In this paper, the aim is to develop a new soft computing model to evaluate tunnel support systems. Firstly, a numerical analysis was performed using the explicit finite difference model by FLAC2D software to excavate a sequence model and support system installation. The design loads including the axial force, moment, and shear force were calculated for some important points of the support system including the crown, the middle of the bottom and the side walls. In order to analyse the stability of the support system, the section points were evaluated into 3 clusters by the artificial bee colony as a meta-heuristic algorithm and a k-means algorithm using Matlab software. The results of clustering were compared by the safety factor of the support system. The results indicated that the section points that are in cluster 1 have a lower safety factor than clusters 3 and 2, respectively. It concluded that the artificial bee colony can be reliably used in the initial assessment of tunnel support systems based on the axial force, moment, and shear force.https://hrcak.srce.hr/file/318474soft computingartificial bee colonyclusteringsupport systemsafety factor |
| spellingShingle | Reza Mikaeil Hadi Bakhshinezhad Sina Shaffiee Haghshenas Mohammad Ataei STABILITY ANALYSIS OF TUNNEL SUPPORT SYSTEMS USING NUMERICAL AND INTELLIGENT SIMULATIONS (CASE STUDY: KOUHIN TUNNEL OF QAZVIN-RASHT RAILWAY) Rudarsko-geološko-naftni Zbornik soft computing artificial bee colony clustering support system safety factor |
| title | STABILITY ANALYSIS OF TUNNEL SUPPORT SYSTEMS USING NUMERICAL AND INTELLIGENT SIMULATIONS (CASE STUDY: KOUHIN TUNNEL OF QAZVIN-RASHT RAILWAY) |
| title_full | STABILITY ANALYSIS OF TUNNEL SUPPORT SYSTEMS USING NUMERICAL AND INTELLIGENT SIMULATIONS (CASE STUDY: KOUHIN TUNNEL OF QAZVIN-RASHT RAILWAY) |
| title_fullStr | STABILITY ANALYSIS OF TUNNEL SUPPORT SYSTEMS USING NUMERICAL AND INTELLIGENT SIMULATIONS (CASE STUDY: KOUHIN TUNNEL OF QAZVIN-RASHT RAILWAY) |
| title_full_unstemmed | STABILITY ANALYSIS OF TUNNEL SUPPORT SYSTEMS USING NUMERICAL AND INTELLIGENT SIMULATIONS (CASE STUDY: KOUHIN TUNNEL OF QAZVIN-RASHT RAILWAY) |
| title_short | STABILITY ANALYSIS OF TUNNEL SUPPORT SYSTEMS USING NUMERICAL AND INTELLIGENT SIMULATIONS (CASE STUDY: KOUHIN TUNNEL OF QAZVIN-RASHT RAILWAY) |
| title_sort | stability analysis of tunnel support systems using numerical and intelligent simulations case study kouhin tunnel of qazvin rasht railway |
| topic | soft computing artificial bee colony clustering support system safety factor |
| url | https://hrcak.srce.hr/file/318474 |
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