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  • 學位論文

2006屏東地震系列經驗強地動預估式

Empirical Predictive Equations for Strong-Ground Motions in the 2006 Pingtung Earthquake Sequence

指導教授 : 邱宏智 吳逸民

摘要


2006年12月26日發生在台灣西南外海地震,是該地區自強震觀測以來收錄到最大的地震,這些地震系列收錄的強震資料可用於重新評估該地區地震對核三廠安全性及南台灣的地震危害度。本研究利用中央氣象局自由場強地動觀測網計畫(TSMIP)在這地震系列中三個較大地震所收錄的強震記錄,推導進行此項評估所需的強地動預估式。所探討的強地動參數包括最大水平地表加速度(PGA)、最大水平地表速度(PGV)、最大水平地表位移(PGD)與週期0.01~10秒之擬加速度反應譜(PSA)的變化情形。所使用之經驗預估式以地震矩規模為震源參數,震央距為波傳遞參數,並引進三種場址參數。這三種參數分別為傳統的地盤分類、地表下30公尺內之平均剪力波速(VS30)及放大倍率(Amp)。推導經驗預估式之係數則使用基因演算法,藉由其全域搜尋的特性,求得預估式之各項係數的最佳解。這些經驗強地動預估式的係數列於本文之表4.1及表4.2。 根據殘差值的分析可評估加入場址參數的影響,一般而言加入場址參數都可減少預估的殘差值,以PGA而言VS30是最好的參數,但對PGV而言,傳統的分類方式可能較好,而放大倍率對台北盆地及蘭陽平原修正比其他兩種方法好些。另外從分析殘差值隨空間變化的結果,顯示並無特定場址參數是絕對優於其他參數,因此這三種方法均值得使用其他組資料檢驗。 本文使用的三個地震,主震為正斷層,其他為走向滑移斷層,通常在相同規模及距離下,走向斷層比正斷層造成的地動值大,本研究的結果也吻合此推論。 以本研究求得之PGA預估式重新推估核三廠在主震發生時之PGA值,以Amp求得的103.3 cm/s/s最為接近核三廠的記錄156.8 cm/s/s。此外,根據本研究的結果與他人研究相比,顯示此屏東地震系列及東北部隱沒帶地震之地動值隨距離衰減較台灣淺地殼地震慢。

並列摘要


The December 26, 2006 Pingtung earthquake is the largest event observed in the southwest Taiwan. In order to provide the basic data for reevaluating the seismic hazard of this power plant and the southern Taiwan, we derive empirical predictive equations for peak ground acceleration(PGA), peak ground velocity(PGV), peak ground displacement (PGD) and pseudo-spectral acceleration(PSA)at 0.01~10 periods using the strong-motion data obtained from the Taiwan Strong Motion Instrumentation Program(TSMIP). We select moment magnitude as the source parameter, epicentral distance as the wave propagation parameter and consider three types of site effects terms in our predictive model. These site parameters include the traditional site classification,VS30 and site amplification factor estimated in this study. For obtaining coefficients of these predictive equations, we apply genetic algorithm for global searching. The complete listings of coefficients for of all the predictive equations are given in Tables 4.1 and 4.2. According to the residual analyses, we can evaluate the performance of various site-effect terms introduced in our predictive model. Results show that the VS30 gives a best estimation in PGA but it fails in PGV estimation. On the other hand, the traditional site classification reduces a significant uncertainty in the PGV estimation. The amplification factor does not improve much in the overall estimation, but it improves the PGA estimations in Taipei basin and Ilan plain. Therefore, we conclude that no single site-effect term can give best estimation for all types of ground motions in this study. Our predictive equations are also applied to an independent observation in the Power Plant No. 3. One free-field observation inside the power plant is 156.8cm/s/s while our predictions are about 103.3 cm/s/s. However, this observation still falls within one standard error of our predictive equations. Comparing with other independent study in Taiwan, we found that the attenuation in our predictive model is less than that of an island-wide shallow crustal model or that of the subduction zone in the northeastern Taiwan.

參考文獻


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