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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/65195


    Title: 台灣西南部地區考慮經驗場址修正之隨機式地動模擬;Site Correction of Stochastic Ground Motion Simulation in Southwestern Taiwan
    Authors: 黃琮倫;Huang,Cong-lun
    Contributors: 地球科學學系
    Keywords: 場址修正;隨機式模擬;經驗轉換函數;Site Correction;Stochastic Simulation;Empirical Transfer Function
    Date: 2014-07-08
    Issue Date: 2014-10-15 14:43:03 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 發生在1906年3月17日芮氏規模7.1的梅山地震,對台灣西南部地區造成了難以數計的災害(鄭世楠和葉永田,1998),藉由這個地震事件我們認知到,強地動預估在降低地震造成的災害方面是相當重要的一環。
    本研究利用隨機式點震源模擬法(Stochastic Point Source Simulation,Boore, 1983; Boore, 2003a),模擬臺灣地區強地動觀測計畫(TSMIP)自1991~2013年間的淺源事件紀錄,並利用雙站法(Borcheret, 1970)計算觀測與模擬紀錄之間的差值,建立西南部地區強地動測站0.2Hz到10Hz的經驗地層轉換函數(Empirical Transfer Function)。我們利用此轉換函數針對數個目標地震進行場址修正後得到預估PGA值,與Jean et al. (2006)和張毓文等人(2010)使用的強地動預估模式(Ground Motion Prediction Equation, GMPE)計算得到結果並無太大的差異。而針對規模較大且破裂機制較為複雜的目標地震,我們使用隨機式有限斷層模擬法(Stochastic Finite Fault Simulation,Beresnev and Atkinson, 1998; Motezedian and Atkinson, 2005; Boore, 2009)模擬並同樣利用經驗轉換函數進行場址修正。結果顯示針對甲仙地震,本研究方法所得之預估PGA值會優於GMPE的預估結果,而此方法也能提供0.2Hz到10Hz間的可信頻譜。而我們認為未來在建立經驗地層轉換函數時,除了震源深度與規模外,還可以加入方位角與PGA大小作為篩選的依據。
    最後本研究參考台灣地震模型(TEM)提供的梅山斷層基本參數,依照日本防災科學技術研究所公布的強地動預估方法”Recipe”(NIED, 2009)計算其餘參數,接著利用隨機式有限斷層法進行模擬,並使用經驗地層轉換函數進行場址修正得到預估PGA值。結果顯示針對梅山斷層進行的特徵地動模擬,利用本研究方法獲得的PGA大小與分布狀況和GMPE預估的結果差異性並不大。藉由本次研究可以得知,使用隨機式模擬方法配合經驗地層轉換函數進行場址修正,在強地動預估上能有不錯的表現,未來在地震紀錄較少的地區可以使用此方法進行強地動預估的工作。
    ;On March 17, 1906, the Meishan earthquake (ML7.1) hit southwestern Taiwan, caused severe damage and lost (鄭世楠和葉永田,1998). This event noticed that the ground motion prediction plays an important role in reducing the earthquake hazard.
    In this study, we simulate the shallow earthquake event which record by TSMIP from 1991 to 2013, with the stochastic point source simulation (Boore, 1983; Boore, 2003a). The empirical transfer function from 0.2Hz to 10Hz for each station in southwester area will be calculated by H/H method (Borcheret, 1970). After doing the site correction with these empirical transfer functions for several target event, the prediction of PGA shows no large difference compare to the result calculating by ground motion prediction equation (GMPE, Jean et al., 2006; 張毓文,2010). The stochastic finite fault simulation (Stochastic Finite Fault Simulation,Beresnev and Atkinson, 1998; Motezedian and Atkinson, 2005; Boore, 2009) and empirical site correction also show well performance on March 4, 2010, Jiashiang earthquake. The result not only shows the PGA prediction is better than the result calculate by GMPE but also provides reliable spectrum form 0.2Hz to 10Hz. We think the earthquake azimuth and PGA value are to be concerned in calculating the empirical transfer function except the depth and magnitude in the future.
    The last part is the Meishan fault ground motion simulation with the parameters provides by TEM and calculate with strong ground motion prediction method “Recipe” (NIED, 2009). Both the PGA value and PGA distribution are according with the GMPE result and it represent that the empirical site correction of stochastic simulation can provide good result in ground motion prediction.
    Appears in Collections:[地球物理研究所] 博碩士論文

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