土壤液化一直是大地工程中很重要的課題，因此也發展出許多不同的液化評估法，其中簡易經驗評估法則為工程界所常用。自從Nemat-Nasser and Shokooh (1979)提出地震能量消散與孔隙水壓增量有關的概念後，根據能量觀點來探討液化之發生可能性便成為液化評估主要的研究方向之一。本研究利用室內反覆三軸試驗所得之土壤應力-應變關係之遲滯圈能量概念，針對土壤液化有關參數透過倒傳遞類神經網路訓練及模擬後，推求液化時之遲滯圈能量。研究中並運用大地離心機所模擬之地震案例與室內反覆三軸試驗發展出之類神經網路模型相互比較，藉以驗證類神經網路模型之適用性。本研究亦採921地震時所調查之現地資料，配合類神經網路液化能量模型，運用統計學中的判別分析來定義現地液化判別線；此外，並由判別分析推算液化機率，建立一現地土層能量式液化評估之經驗準則。結果顯示本研究所提出之能量式液化評估模式有其合理之評估能力，可擴展應用於大地工程理論與實務設計時之參考。
關鍵詞：土壤液化、類神經網路、遲滯圈能量、反覆三軸試驗。

The study of soil liquefaction has been one of the most important topics in the geotechnical engineering. There are many different methods, including simplified empirical methods which were in common used, have been developed to evaluate the liquefaction of soils. Since Nemat-Nasser and Shokooh (1979) proposed a concept relating to the relationship between earthquake energy and generation of excess pore water pressure during shaking, the investigation of soil liquefaction in accordance with energy principles has become one of the major research areas. In this study, the concept of hysteresis-loop energy of stress-strain relation was adopted and the experimental values of hysteresis-loop energy were obtained from triaxial tests. The hysteresis-loop energy on liquefaction state was trained and simulated by using Artificial Neural Networks (ANN). The hysteresis-loop energy obtained from geotechnical centrifuge tests was adopted to verify the suitability of the simulated hysteresis-loop energy by using ANN. Based on field observations of performance of sites subjected to Chi-Chi earthquake in 1999, the energy assessing in-situ liquefaction potential was also described. In this study, discriminate analysis was used to determine the equation of the boundary curve separating the data points with and without liquefaction. The proposed method shows capability in evaluating the probability of soil liquefaction and can be used for practice.
Keywords: Soil liquefaction; Artificial Neural network; Hysteresis-loop energy; Cyclic triaxial test

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