本論文探討使用強制振動方式對高層建築順風向之氣彈行為進行系統識別，最後歸納出頻率相關之氣動力阻尼與氣動力勁度。藉由白噪音之強制振動，本文提出一套新識別方法，使用基因演算法來曲線擬合不同風速實驗下所得之氣彈互制頻率轉換函數，進而識別出結構的氣動力阻尼與氣動力勁度。為驗證此方法之可行性，本實驗使用高寬比為7的兩個高層建築模型（一為正方形斷面、一為長方形斷面）為代表在淡江大學土木系風洞進行識別試驗。 將識別得到之氣動力阻尼與氣動力勁度，配合紊流場由力平衡儀所量測到的結構基底彎矩歷時，以數值模擬方式預測高層建築在紊流場下的抖振位移反應；並將其結果與紊流場試驗之直接量測結果做比較。比較結果發現預測與直接量測的結果非常接近，因此印證所識別出的氣動力阻尼與氣動力勁度之正確性。 This thesis investigated the frequency-dependent aerodynamic damping and stiffness of high-rise buildings for the along-wind motion by utilizing forced excitation technique. Through the white noise excitation to an elastic model, a new approach that involves the curve-fitting for aero-elastic frequency response function and genetic algorithm for global minimization was presented to identify the frequency-dependent aerodynamic damping and stiffness. For demonstration, two prisms (one square-shape, the other rectangular shape) with a height/width ratio of 7 as the high-rise building models were used in the wind tunnel tests to perform the identification following the approach presented.
The identified results were further used to numerically predict the buffeting response of the same building model under the disturbance of wind gust within an atmospheric boundary layer, and the comparisons were made with the direct measurements from wind tunnel experiment. As demonstrated from the remarkable correlation between the simulations and experiments, the validity of the frequency-dependent damping and stiffness identified were well verified