臺灣博碩士論文加值系統

Comparing with safety factor method, reliability-based design method can quantify the uncertainty to design geotechnical structure in a more systematical and economical design. In this study, a multivariate probability distribution model for nine parameters of intact rock is constructed based on the ROCK/9/4069 database. These nine parameters are:(1)unit weight (γ);(2)porosity (n);(3)L-type Schmidt hammer hardness (RL);(4)Shore scleroscope hardness (Sh);(5)Brazilian tensile strength (σbt);(6)point load strength index (Is50);(7)uniaxial compressive strength (σc);(8)Young’s modulus (E);(9)compressional wave velocity (VP). Consistency is shown that the multivariate probability distribution can capture the correlation among the nine parameters. Using the Bayesian analysis framework, the original distributions of the design rock parameters (σc, E) would serve as prior distributions and can be updated into posterior distributions by using different multivariate site-specific information. The forms of posterior distributions were summarized into tables so that detailed Bayesian analysis need not be conducted. From the results, the transformation uncertainty of predicted posterior distribution can be effectively reduced as the multivariate site-specific information increases. With smaller uncertainty, reliability-based design can reduce more economical design.

口試委員審定書…………………………………………………………………………i
誌謝….…………………………………………………………………………………..ii
摘要..…….……………………………………………………………………………...iii
Abstract.….……………………………………………………………………………...iv
目錄…….………………………………………………………………………………..v
圖目錄…………………………………………………………………………………viii
表目錄…...…………………………………………………………………………….. xi
第一章 前言 1
1.1 研究背景與動機 1
1.2 研究方法 1
1.3 研究內容 2
第二章 文獻回顧 5
2.1 室內試驗和單壓強度之轉換模型 5
2.1.1 n-σc 5
2.1.2 RL-σc 5
2.1.3 Sh-σc 6
2.1.4 σbt-σc 6
2.1.5 Is50-σc 7
2.1.6 VP-σc 7
2.2 單壓強度和楊氏模數之轉換模型 8
2.3 室內試驗和楊氏模數之轉換模型 9
2.3.1 RL-E 9
2.3.2 Sh-E 9
2.3.3 VP-E 9
第三章 資料庫 26
3.1 資料庫ROCK/9/4069 26
3.2 與前人轉換模型之比較 27
3.3 量化轉換誤差 29
3.4 實際目標參數之機率分佈 32
第四章 多變數機率分佈模型 51
4.1 參數彼此間之相關性 51
4.1.1 資料庫回顧 51
4.1.2 (Yi, Yj)間之相關係數 52
4.1.3 (Xi, Xj)間之相關係數 53
4.2 Johnson分佈系統 55
4.3 模擬資料 59
4.3.1 n-σc模型 59
4.3.2 RL-σc模型 59
4.3.3 Sh-σc模型 60
4.3.4 σbt-σc模型 60
4.3.5 Is50-σc模型 60
4.3.6 VP-σc模型 60
4.3.7 RL-E模型 60
4.3.8 Sh-E模型 60
4.3.9 σc-E模型 61
4.3.10 VP-E模型 61
第五章 貝氏分析 76
第六章 成果展示與驗證 86
6.1 成果演示 86
6.2 驗證 88
6.2.1 案例一 88
6.2.2 案例二 89
第七章 結論與未來建議 95
7.1 結論 95
7.2 未來建議 96
參考文獻…………………………………………………………………………… 97
附錄A 資料庫ROCK/9/4069之基本資訊……………………………………….. 104
附錄B 論文口試─問題與回覆………………………………………………….. 136

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