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- YU Bosong
- 九州大学
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- SHIMADA Hideki
- 九州大学
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- SASAOKA Takashi
- 九州大学
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- HAMANAKA Akihiro
- 九州大学
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- MATSUMOTO Fumihiko
- Alpha Civil Engineering
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- MORITA Tomo
- Alpha Civil Engineering
説明
Box-jacking is an increasingly popular means for installing underground utilities and infrastructure. Accurately estimating the expected jacking forces in box-jacking is a key design concern, which can ensure the available thrust is not exceeded, to prevent damage to the box-culverts and/or launch shaft, and the construction efficacy of the jacking project. However, prediction of the total jacking force is complicated due to a multitude of influencing factors. The development of jacking force can be influenced by the site geology, the lubricant performance, work stoppages, shape of box culvert, and tunnel boring machine driving style. In this paper, a probabilistic observational approach is introduced aimed at prediction of jacking forces during the box-jacking process. Markov Chain Monte Carlo (MCMC) was adopted for this purpose which allows forecasts to be performed within a probabilistic framework. The proposed framework was applied to a box-jacking case histories completed in Kanagawa: a 150-m drive in fine and medium sands. The forecasts were appraised through comparisons to predictions determined using a classical optimization technique, namely genetic algorithms. The results show that the proposed framework yields highly accurate predictions for the monitored field data, and the prediction accuracy improves obviously as more data are acquired from the drive.
収録刊行物
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- International Journal of the JSRM
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International Journal of the JSRM 20 (2), 1-12, 2024-01-05
一般社団法人 岩の力学連合会
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詳細情報 詳細情報について
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- CRID
- 1390017223513523072
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- ISSN
- 21898405
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- HANDLE
- 2324/7162085
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- IRDB
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- 抄録ライセンスフラグ
- 使用不可