探討新增鑽孔位置與地層不確定性之關係

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：41

、訪客IP：3.17.154.184

姓名

邱柏昇(Bo-Sheng Ciou) 查詢紙本館藏

畢業系所

土木工程學系

論文名稱

探討新增鑽孔位置與地層不確定性之關係

相關論文

★ 利用連續及非連續隨機場分析地層與參數變異性對液化潛能指數不確定性的影響

★ 建立砂性土的SPT-CPT關係式之新方法

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

在大地工程討論中，地質不確定性有兩個來源：（1）地層模型不確定性（stratigraphic uncertainty）及（2）地工參數的不確定性。雖然大地工程設計上常考慮到大地材料性質的不確定性，但少有考慮地層不確定性之設計。一般而言，設置新增鑽孔會降低地層的不確定性，然而新增鑽孔位置對地層不確定性之量化關係卻鮮少被提及。
本文先假設之合成地層模型（已知地層模型），於其設置既有鑽孔及新增鑽孔，再利用馬可夫隨機場（Markov random field, MRF）模擬數百個潛在的地層模型，透過信息熵（information entropy）及總信息熵（total information entropy, TH）來量化地層模型的不確定性；經由一系列鑽孔位置及MRF的參數研究，得到不同新增鑽孔位置及MRF參數下，地層模型的不確定性（TH）。此外，本文根據合成地層模型與MRF模擬的地層模型進行比較，得到MRF模擬地層模型的準確度。研究結果顯示：（1）在本文案例中，TH為相對鑽孔位置的二次函數，最小值出現在新增鑽孔位置於兩既有鑽孔的中間；（2）MRF參數之空間影響半徑比越大代表地層的異向性越明顯，地層模型不確定性也較低，反之亦然；（3）空間影響半徑比傾角對TH較不顯著，但仍會影響地層模型及信息熵的分布；（4）根據上述3點，本文提出新增鑽孔位置、MRF參數及TH之迴歸模型，並透過隨機地層案例進行驗證；最後，以一案例說明提出的迴歸模型於工程案例之應用。

摘要(英)

The uncertainty involved in the interpreted geological model may be categorized as: (1) the stratigraphic uncertainty and (2) the properties uncertainty. Although the inﬂuence of the properties uncertainty on the behavior or performance of the geotechnical system and the geotechnical design has been extensively reported in the literature, the studies that address the stratigraphic uncertainty are seldom. Generally, drilling an additional borehole will decrease the stratigraphic uncertainty. However, there has no systematic and comprehensive study to investigate the above relation.
This paper utilized the stochastic Markov random ﬁeld (MRF) to simulate hundreds of potential stratigraphic models (realizations) based on the designed borehole locations in a synthetic stratigraphic model (a benchmark model). The stratigraphic model uncertainty can be quantified by the information entropy that was calculated by the probability of soil type from the MRF simulations. The systematic parametric studies of borehole locations and MRF parameters were conducted. Additionally, the accuracy of MRF simulation was performed via the comparison of a synthetic stratigraphic mode and stratigraphic models generated by MRF. The results show that (1) the total information entropy is a quadratic function of the additional borehole location; the minimum value appears when the additional borehole at the middle of two inherent boreholes. (2) the stratigraphic uncertainty decreases with the increasing influence radius ratio and vice versa. (3) The dip of stratigraphic anisotropic ratio has no significant influence on the total information entropy. (4) Based on (1)-(3), the correlations among an additional borehole location, stratigraphic anisotropic ratio, and total information entropy were obtained by using multivariate regression analysis, which were verified with the case studies.

關鍵字(中)

★ 新增鑽孔位置
★ 地層模型不確定性
★ 信息熵
★ 馬可夫隨機場

關鍵字(英)

論文目次

摘要 V
誌謝 VII
目錄 VIII
圖目錄 XI
表目錄 XV
符號表 XVI
第一章緒論 1
1.1 研究動機 1
1.2 研究目的 3
1.3 論文架構 3
第二章文獻回顧 4
2.1 隨機場理論 4
2.2 馬可夫隨機場 4
2.3 地層模型的不確定性 9
2.4 地層不確定性與新增鑽孔位置之關係 14
2.5 隨機地形生成 15
第三章分析方法 16
3.1 研究流程 16
3.2 建立合成地層模型及新增鑽孔位置之設定 17
3.3 馬可夫地層模型之建立 18
3.4 MRF地層模型之準確度 20
3.5 量化地層不確定性 21
3.6 隨機場參數及地層參數之設定 22
3.7 迴歸模型 22
第四章數值模擬與分析結果 25
4.1 新增鑽孔位置的影響 25
4.2 空間影響半徑比的影響 31
4.3 地層傾角的影響 36
4.4 空間影響半徑比傾角的影響 42
4.5 隨機場及地層參數與總信息熵之關係 46
4.6 迴歸模型驗證 49
第五章虛擬案例應用 54
5.1 單一案例 54
5.2 複合案例 55
第六章結論與建議 61
6.1 結論 61
6.2 建議 62
參考文獻 63
附錄 65

參考文獻

董家鈞，2013，「知之為知之，不知為不知，是知也：淺談地質模型不確定性」，大地技師期刊，第20期，第72-83頁
Bardossy, G., Fodor, J. 2001. Traditional and new ways to handle uncertainty in geology. Natural Resources Research. pp. 179-187.
Chien, W.Y., Lu, Y.C., Juang, C.H., Dong, J.J., and Hung, W.Y. 2021. Effect of stratigraphic model uncertainty at a given site on its liquefaction potential index: comparing two random field approaches. (under review)
Erwin C. 2015. Visualization of the diamond square algorithm. Wikipedia
https://en.wikipedia.org/wiki/Diamond-square_algorithm.
Gong, W., Tang, H., Wang, H, Wang, H., and Juang, C.H. 2019. Probabilistic analysis and design of stabilizing piles in slope considering stratigraphic uncertainty.
Engineering Geology. 105162.
Gong, W., Juang, C.H., Martin II, J.R., Tang, H., Wang, Q., and Huang, H. 2018. Probabilistic analysis of tunnel longitudinal performance based upon conditional random ﬁeld simulation of soil properties. Tunnelling and Underground Space Technology. Volume 73,pp. 1–14
Hassanipak, A.A. 2004. GET: A Function for Preferential Site Selection of Additional Borehole Drilling. Exploration and Mining Geology. pp.139-146.
Hsu, Y.H. , Lu, Y.C., Khoshnevisanc, S., Juang, C.H., and Hwang, J.H. 2021. Effect of geological uncertainties on the design of offshore wind turbine foundations. Engineering Geology. (under review)
Juang, C.H., Khoshnevisan, S., and Zhang, J. 2015. Chapter 4: Maximum likelihood principle and its application in soil liquefaction assessment. In Phoon, K.K. & Ching, J. (eds), Risk and Reliability in Geotechnical Engineering. CRC Press, Boca Raton, Florida.
Juang, C.H., Zhang, J., Shend, M., and Hu, J. 2019. Probabilistic methods for unified treatment of geotechnical and geological uncertainties in a geotechnical analysis. Engineering Geology. Volume 249, pp. 148-161.
Keaton, Jeffrey. 2014. A suggested geologic model complexity rating system.
Engineering Geology. Volume 6. pp.363-366.
Li, Z., Wang, X., Wang, H., and Robert Y. Liang. 2016. Quantifying stratigraphic uncertainties by stochastic simulation techniques based on Markov random field. Engineering Geology. pp.106-122.
Liu, L.L., Cheng, Y. M., and Zhang, S.H. 2017. Conditional random field reliability analysis of a cohesion-frictional slope. Computers and Geotechnics. pp.173-186.
Mann, C. J. 1993. Uncertainty in geology. In: Davis, J. C. and Herzfeld, U. C. (editors). Computers in Geology.25 Years of Progress. pp. 241-254.
Norberg, T., Rosén, L., Baran, A., and Baran, S. 2002. On modelling discrete geological structures as Markov random ﬁelds. Mathematical Geology. Volume 34,pp. 63–77.
Wellmann, J.F., and Klaus, R.L. 2012. Uncertainties have a meaning: Information entropy as a quality measure for 3-D geological models. Tectonophysics. pp.173-186.
Wang, X., Wang, H., Liang, R.Y., Zhu, H., and Di, H. 2018. A hidden Markov random ﬁeld model based approach for probabilistic site characterization using multiple cone penetration test data. Structural Safety. Volume 70, pp. 128–138.
Zhao, C., Gong, W., Li, T., Juang, C.H., Tang, H., and Wang, H. 2021. Probabilistic characterization of subsurface stratigraphic configuration with modified random field approach. Engineering Geology.Volume288. pp.106-138.

指導教授

莊長賢盧育辰(Charng-Hsein juang Yu-Chen Lu)

審核日期

2022-1-25

推文