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DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 卿建業(Jian-Ye Ching) | |
dc.contributor.author | Shih-Hsiang Yuan | en |
dc.contributor.author | 袁士翔 | zh_TW |
dc.date.accessioned | 2021-06-15T16:22:27Z | - |
dc.date.available | 2020-08-21 | |
dc.date.copyright | 2020-08-21 | |
dc.date.issued | 2020 | |
dc.date.submitted | 2020-08-06 | |
dc.identifier.citation | 陳玫臻 (2015). 黏土層深開挖引致連續壁側向位移之預測。碩士論文 國立台灣科技大學。台北。 吳俊廷 (2019). 黏土壓密參數多變數分布模型的建置。碩士論文 國立台灣大學。台北。 Bjerrum, L., and Eide, O., (1956). Stability of Strutted Excavation in Clay. Géotechnique, 6, 32-47. Ching, J., (2018). What Does the Soil Parameter Estimated from a Transformation Model Really Mean? Journal of GeoEngineering, 13(3), 105-113. Ching, J., and Phoon, K. K., (2012). Establishment of Generic Transformations for Geotechnical Design Parameters. Structural Safety, 35, 52-62. Ching, J., and Phoon, K. K., (2014a). Transformations and Correlations among Some Clay Parameters — the Global Database. Canadian Geotechnical Journal, 51(6), 663-685. Ching, J., and Phoon, K. K., (2014b). Correlations among Some Clay Parameters — the Multivariate Distribution. Canadian Geotechnical Journal, 51(6), 686-704. Ching, J., and Phoon, K. K., (2015). Constructing Multivariate Distributions for Soil Parameters. Chap. 1 in Risk and Reliability in Geotechnical Engineering, Ed, K. K. Phoon and J. Ching Ching, J., Wu, S., and Ou, C. Y. (2014). Calibration of Model Uncertainties in Base Heave Stability for Wide Excavations in Clay. Soils and Foundations, 54(6), 1159-1174. Ching, J., Wu, S., and Phoon, K.K. (2020). Constructing Quasi-Site-Specific Multivariate Probability Distribution using Hierarchical Bayesian Model, in review by ASCE, Journal of Engineering Mechanics. Clough, G. W., and T. D. O'Rourke, (1990). Construction Induced Movements of in Situ Walls, Design and Performance of Earth Retaining Structures, ASCE Geotechnical Special Publication No. 25, ASCE, 439-470. Hsieh, P. G., Ou, C. Y. (2015). Simplified Approach to Estimate the Maximum Wall Deflection for Deep Excavations with Cross Walls in Clay Under the Undrained Condition. Acta Geotechnica, 177-189. Huang, A., and Wand, M. P., (2013). Simple Marginally Noninformative Prior Distributions for Covariance Matrices. Bayesian. Analysis, 8(2), 439–452. Kung, T. C., Juang, C. H., Hsiao, C. L., and Hashash Y. M. A. (2007). Simplified Model for Wall Deflection and Ground-Surface Settlement Caused by Braced Excavation in Clays. Journal of Geotechnical and Environmental Engineering, 133(6), 731-747. Long, M., (2001). Database for Retaining Wall and Ground Movement due to Deep Excavations. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 127(3). Ou, C. Y., Hsieh, P. G., and Chiou, D. C., (1993). Characteristics of Ground Surface Settlement during Excavation, Canadian Geotechnical Journal, 30(5), 758-767. Phoon, K. K., (2006). Modeling and Simulation of Stochastic Data. GeoCongress 2006, ASCE, Reston, VA. Slifker, J. F., and Shapior, S. S., (1980). The Johnson System: Selection and Parameter Estimation. Technometrics, 22(2), 239-246. Tan, Y., and Li, M. W. (2011). Measured Performance of a 26 m Deep Top-Down Excavation in Downtown Shanghai. Canadian Geotechnical Journal, 48(5), 704-719. Terzaghi, K., (1943). Theoretical Soil Mechanics. John Wiley and Sons, Inc. Wu, S., Ching, J., and Ou, C. Y., (2013). Predicting Wall Displacements for Excavations with Cross Walls in Soft Clay. Journal of Geotechnical and Geoenvironmental Engineering, 139(6), 914-927. Zhang, W., Zhang, R., and Goh, A. T. C. (2017). Multivariate Adaptive Regression Splines Approach to Estimate Lateral Wall Deflection Profiles Caused by Braced Excavations in Clays. Geotechnical and Geological Engineering. Geotechnical and Geological Engineering, 36(2), 1349-1363. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/52665 | - |
dc.description.abstract | 大數據分析(BIG DATA analytics)近年來在不同領域已取得相當顯著的成效,利用當中的龐大真實數據資料來進行不同的預測與評估,因此本研究透過蒐集世界各地的黏土深開挖工程案例,建立了一個關於黏土深開挖的全球性資料庫,當中包含了開挖的設計參數、土壤性質、擋土壁體勁度與變形量等等資訊,並且使用資料庫中的這些大數據建置一個多變數機率模型,針對開挖造成的擋土壁體變形以及變形變形發生位置進行預測。 透過相關文獻的回顧,去了解與蒐集深開挖相關的參數以及容易影響擋土壁體變形量的因子來建立全球資料庫,在篩選出我們認為有能探討之相關性的參數,包含:(1)正規化開挖寬度(B/He);(2)開挖隆起安全係數(FS);(3)開挖深度(He);(4)正規化最大修正壁體變形量(δhm/He);(5)正規化最大壁體變形量發生位置(H1/He);(6)壁體系統勁度(Sw);(7)支撐軸向剛度(Sa)。 為了建置多變數機率模型,先利用Johnson分布系統將參數轉換至標準常態空間,再利用吉普斯取樣法、共軛條件與階段式貝氏模型(hierarchical Bayesian model, HBM)中的學習階段填補資料庫中空缺的資料,並訓練出代表資料庫資訊的超參數,接著在階段式貝氏模型中推估階段的架構下,藉由所得到的超參數與目標現地的已知參數條件更新驗機率分布函數,便可以較客觀且經濟的進行開挖變形的預測與評估,於可靠度的觀念下能更加準確地去進行開挖設計。 | zh_TW |
dc.description.abstract | BIG DATA analytics uses the huge real data to make different predictions. In recent years, it has achieved remarkable results in different fields. Therefore, this study established a global database of deep excavation in clay by collecting deep excavation engineering cases worldwide, which contains information about excavation geometry and sequence, soil profiles and properties, wall stiffness and deformations, etc. Use the BIG DATA in the database to build a multivariate probability model, which can be used to predict the deformation of the retaining wall. The parameters in the database are: (1) normalized excavation width (B/He);(2) factor of safety against base heave (FS);(3) excavation depth (He);(4) normalized maximum wall deformation (δhm/He);(5) normalized location of maximum wall deformation (H1/He);(6) system stiffness of retaining wall (Sw);(7) support axial rigidity (Sa). Using Johnson distribution system to convert the parameters into standard normal distributions, then applying Gibbs sampler method, conjugate conditions and the hierarchical Bayesian model (HBM) to fill the missing data and output the hyperparamaters. Base on the HBM method and the target site information, we can get the predicted wall deformation results samples from the multivariate probability model and predict the deformation more objectively and economically. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T16:22:27Z (GMT). No. of bitstreams: 1 U0001-0608202014092100.pdf: 6934769 bytes, checksum: 96ba58f444b92398c2b98baa15879f6c (MD5) Previous issue date: 2020 | en |
dc.description.tableofcontents | 誌謝 i 摘要 ii Abstract iii 目錄 iv 圖目錄 vi 表目錄 viii 第一章 前言 1.1研究背景與動機 1 1.2研究方法 2 1.3研究流程 2 1.4本文內容 4 第二章 文獻回顧 5 2.1擋土壁體變形行為 5 2.2擋土壁體變形之影響因素 6 2.3擋土壁體變形量修正 12 2.4底部隆起之安全係數 12 第三章 資料庫 16 3.1本研究資料庫介紹 16 3.2本研究資料庫資料與前人經驗圖之對比 21 第四章 多變數機率分布模型建置與模擬 29 4.1前言 29 4.2 Johnson分布系統 30 4.2.1常態分布與多維度常態分布 30 4.2.2 Johnson 分布系統類型 31 4.3 階段式貝氏模型hierarchical Bayesian model 41 4.3.1貝氏分析(Bayesian analysis) 41 4.3.2階段式貝氏模型hierarchical Bayesian model 41 4.4共軛先驗(conjugate prior)與吉普斯取樣法(Gibbs sampler) 42 4.4.1共軛先驗(conjugate prior) 43 4.4.2吉普斯取樣法(Gibbs sampler) 45 4.5 模擬結果 51 第五章 現地案例預測與驗證 61 5.1 目標參數預測 61 5.2 驗證案例一(非資料庫資料) 62 5.3 驗證案例二(資料庫資料) 81 5.4 大數據分析法與回歸公式之比較(資料庫資料) 95 5.4.1驗證案例一之比較 95 5.4.2驗證案例二之比較 99 5.4.3驗證案例三之比較 102 5.4.4驗證案例四之比較 107 第六章 結論與未來建議 112 6.1 結論 112 6.2 未來建議 113 參考文獻 114 附錄Ⅰ 資料庫資訊 116 附錄Ⅰ 資料庫參考文獻 125 附錄Ⅱ 口試問答紀錄 132 | |
dc.language.iso | zh-TW | |
dc.title | 以大數據分析黏土深開挖過程中的牆變形 | zh_TW |
dc.title | BIG DATA analytics for wall deformation during deep excavation in clay | en |
dc.type | Thesis | |
dc.date.schoolyear | 108-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 歐章煜(Chang-Yu Ou),王泰典(Tai-Tien Wang) | |
dc.subject.keyword | 大數據分析,深開挖工程,全球資料庫,多變數分布模型,超參數,階段式貝氏模型, | zh_TW |
dc.subject.keyword | BIG DATA analytics,deep excavation,global database,multivariate distribution model,hyper parameters,hierarchical Bayesian model, | en |
dc.relation.page | 133 | |
dc.identifier.doi | 10.6342/NTU202002531 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2020-08-06 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 土木工程學研究所 | zh_TW |
顯示於系所單位: | 土木工程學系 |
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