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研究生:林怡君
研究生(外文):Yi-Chun Lin
論文名稱:水力內寬不確定性:影響因子與現地資料分析方法之探討
指導教授:董家鈞董家鈞引用關係
指導教授(外文):Jia-Jyug Dong
學位類別:碩士
校院名稱:國立中央大學
系所名稱:應用地質研究所
學門:自然科學學門
學類:地球科學學類
論文出版年:2020
畢業學年度:108
語文別:中文
論文頁數:139
中文關鍵詞:人工合成水力內寬現地水力內寬量測不確定性統計分析Barton-Bandis 模式深度岩性位態不連續面粗糙係數不連續面壁面強度
外文關鍵詞:synthetic hydraulic aperturein-situ measurementuncertaintystatistical analysisBarton-Bandis modeldepthlithologyorientationJRCJCS
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不連續面水力內寬為評估岩盤中流體傳輸能力的重要參數,然而工程實務中對於現地不連續面水力內寬的量測值卻不多,因此,放射性廢棄物最終處置安全評估之地下水流場分析即具有不確定性。為了解不同資料統計分析方法對水力內寬不確定性之影響,本研究根據特定場址(砂岩與硬頁岩出露地區)蒐集所得資料,假設岩盤不連續面之合理參數統計分布條件,隨機生成不同岩性不連續面的位態、不連續面粗糙係數(Joint Roughness Coefficient, JRC)及不連續面壁面強度(Joint Compressive Strength, JCS),並採Barton-Bandis模式,在合理現地應力條件下,生成力學內寬資料組後,再藉由經驗式將力學內寬轉換成水力內寬,進而完成人工合成案例之水力內寬資料生成;本研究亦蒐集一現地案例之水力內寬量測資料進行不確定性分析研究。
根據人工合成案例及現地案例測試結果,水力內寬之機率密度分布符合對數常態分布,工程實務不宜直接假設水力內寬為常態分布進行資料統計。分析資料時若不考慮影響因子(如:深度、岩性、裂隙特性…),水力內寬的標準差最大,隨著考慮不同岩性分開統計、水力內寬隨深度減小,統計所得標準差也逐漸下降,而多變量分析中,同時考慮岩性、深度、不連續面之傾角、JRC與JCS時,統計所得標準差會降至最小,根據立方律,其導水係數標準差為不考慮任何影響因子標準差的0.56%。在現地案例的分析結果中,當考慮水力內寬隨著深度變深而減小的趨勢時,同樣顯示出不確定性的顯著降低。
Hydraulic aperture of joints is an important parameter for estimating the fluid flow capability of rock mass. However, the measurements of hydraulic apertures are not common and uncertainty encountered accordingly in the groundwater flow modelling for safety assessment of the radioactive waste final disposal. A synthetic hydraulic aperture dataset was used to evaluate the statistical characteristics of hydraulic apertures via different analysis methods. First of all, reasonable statistical distributions of different parameters of joints (joint roughness coefficient JRC, joint compressive strength JCS, and joint orientation) are assumed according to the data collected from specific sites where the sandstone and argillite outcropped. Secondly, the joints with different orientation, JRC and JCS are randomly generated on the basis of different lithology (sandstone and argillite) at different depth. Thirdly, the Barton-Bandis model was used to calculate the mechanical apertures of each joint under assigned in-situ stresses. Finally, synthetic hydraulic aperture dataset can be obtained according to the mechanical aperture and empirical function described the relation between hydraulic and mechanical apertures. In addition to the synthetic case, we collected a real case where the hydraulic apertures at different depth are available.
According to the testing results of synthetic case and real case, the probability density distribution of the hydraulic aperture conforms to the lognormal distribution. In engineering practice, a normal distribution assumption of hydraulic apertures could be problematic. The standard deviations of the hydraulic apertures are largest when the influence of depth, lithology, and joint characteristics (joint orientation, JRC and JCS) is neglected. When the hydraulic apertures of different lithology were separately analyzed, the uncertainty dropped. If the decreasing trend of hydraulic apertures with depth was considered, the uncertainty dropped further. When the multivariate regression analysis model considering the depth and joint characteristics was used to analysis the synthetic hydraulic apertures of sandstone and argillite separately, the standard deviation is the lowest among others. According to the cubic law, the standard deviation of the joint transmissivity can be reduced to 0.56% of the one where neglecting all of the influential factors when making statistical analysis of the synthetic hydraulic fracture. The analysis result of real case also shows a significant reduced uncertainty when the decreasing trend of hydraulic apertures with increasing depth was considered.
摘要 i
Abstract iii
致謝 v
目錄 vi
圖目錄 ix
表目錄 xiii
一、緒論 1
1.1研究動機與目的 1
1.2研究流程 2
二、文獻回顧 5
2.1不連續面內寬之重要性 5
2.2力學內寬與水力內寬 7
2.2.1力學內寬 7
2.2.2水力內寬 8
2.3取得不連續面內寬之現地試驗方法 9
2.3.1注水試驗(水力內寬Hydraulic aperture) 9
2.3.2壓力試驗(水力內寬Hydraulic aperture) 11
2.3.3示蹤劑試驗(質量平衡內寬Mass balance aperture) 14
2.3.4抽水試驗與示蹤劑試驗(摩擦損失內寬Frictional loss aperture) 15
2.4由力學內寬推求水力內寬 17
2.5不連續面內寬受力閉合行為 17
三、研究方法 20
3.1合成案例(Synthetic case)水力內寬資料生成方式 20
3.1.1不連續面參數範圍設定依據 21
3.1.2 生成力學內寬與水力內寬隨深度變化之分布 29
3.2水力內寬統計分析方法對資料不確定性之影響 37
3.2.1檢驗資料分布特性 37
3.2.2混合岩性或砂岩及硬頁岩分開統計 38
3.2.3直接平均所有水力內寬值並求取標準差(方法1) 38
3.2.4水力內寬隨深度變深以自然指數關係遞減(方法2) 38
3.2.5多變量統計分析(方法3) 40
3.2.6殘差分析 40
四、結果 41
4.1合成案例水力內寬不確定性分析結果 41
4.1.1水力內寬機率密度分布 41
4.1.2直接平均所有水力內寬值並求取標準差(方法1) 44
4.1.3水力內寬隨深度變深以自然指數關係遞減(方法2) 48
4.1.4多變量統計分析(方法3) 52
4.2現地案例水力內寬資料統計分析 58
4.2.1水力內寬機率密度分布 59
4.2.2直接平均所有水力內寬值並求取標準差(方法1) 60
4.2.3水力內寬隨深度變深以自然指數關係遞減(方法2) 61
五、討論 62
5.1假設水力內寬符合常態分布之統計分析 62
5.2 合成案例資料生成之參數特殊限制 66
5.3參數敏感度探討 71
5.3.1不連續面之深度、傾角、JRC及JCS對水力內寬之影響 71
5.3.2 Barton-Bandis模式內岩石風化與否對各物理量之影響 77
六、結論與建議 86
6.1結論 86
6.2建議 89
參考文獻 90
附錄A 95
程式碼-合成案例水力內寬資料生成 95
程式碼-合成案例水力內寬資料分析 106
附錄B 114
不取對數直接平均所有水力內寬值並求取標準差之分析結果 114
取對數水力內寬隨深度變深以自然指數關係遞減之分析結果 117
取對數水力內寬之多變量統計分析結果 120
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