以SPT-N結合Vs-N之經驗模型進行土壤液化評估;Soil liquefaction assessment using SPT-N values coupled with Vs-N empirical models

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題名:	以SPT-N結合Vs-N之經驗模型進行土壤液化評估;Soil liquefaction assessment using SPT-N values coupled with Vs-N empirical models
作者:	李知庭;Li, Chih-Ting
貢獻者:	土木工程學系
關鍵詞:	液化機率;安全係數;SPT;Vs;liquefaction probability;factors of safety;SPT;Vs
日期:	2023-06-07
上傳時間:	2024-09-19 14:12:13 (UTC+8)
出版者:	國立中央大學
摘要:	本研究根據強震測站場址工程地質資料庫(Engineering Geological Database for TSMIP, EGDT)中土層原始資料進行參考，進而設定經驗模型的地質條件，主要著重在砂土層的液化評估，並且參考了Andrus and Stokoe [1]在繪製Vs及CRR曲線之四個限制：(1)地下水位面設在0.5 - 6公尺。(2)剪力波速須在100-200 m/s之間。(3)全新世未膠結土壤。和(4)所量測土層之平均深度為10 m。加上大、中、小不同地震與不同細粒料含量的情況下分析17組經驗公式中的數據庫，共1683個數據點。基於三種土壤液化評估程序 [1-3]，以及17組SPT-N (標準貫入試驗)與剪力波速(Vs)的關係 [12-28]，計算求得各個安全係數，有效的觀察出其中差異，找出使用SPT-N或是Vs哪個在工程安全上比較保守的建議，最後開發出基於SPT與Vs的安全係數之比值的液化評估模型。研究結果顯示R的機率分布之平均值為1.76和標準差為0.59，利用Kolmogorov-Smirnov (K-S)檢定求出此為對數常態分布，則此機率模型可以幫助我們透過簡單的確定性計算進而容易地評估液化機率，且根據105次驗證測試的結果，該模型在統計學上是穩健的。 ;The study is based on an actual soil profile from the Engineering Geological Database for TSMIP (EGDT), and then sets the geological conditions of the empirical model, mainly focusing on the soil liquefaction assessment of the sandy soil layer, referring to Andrus and Stokoe [1] made the following recommendations, or constraints: (1) groundwater table is situated at 0.5-6 m, (2) the soil’s Vs is within 100-200 m/s, (3) uncemented soils of Holocene (< 10,000 years), and (4) the middle point of the target (sandy) layer is no deeper than 10 m. In addition, the database in 17 N-Vs relationships was analyzed under the conditions of different earthquakes and different fines content, with a total of 1683 data points. Mainly based on three soil liquefaction assessment procedures [1-3], 17 empirical relationships between shear wave velocity and SPT-N values [12-28], calculate each factor of safety, effectively observe the difference, and find out which is more conservative in engineering. Next, we developed the liquefaction assessment model which is based on the ratio of SPT- to Vs-based liquefaction factors of safety. It shows that the probability distribution of R can be well modeled by the lognormal distribution with mean value = 1.76 and standard deviation (SD) = 0.59. This probability model can help us estimate soil liquefaction probability more easily, via an unsophisticated, deterministic calculation. Last but not least, the model is statistically robust according to the results of 105 verification tests.
顯示於類別:	[土木工程研究所] 博碩士論文

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