Field-measured Study Of Boundary Layer Wind Characteristics And Modal Parameters Of Super-tall Buildings

With the continuous development of modern science and technology,the flexibility of modern building structures gradually increases,especially for super tall structures and long-span bridge structures.At this time,the structures were very sensitive to wind loads.Notably,the modal parameters(natural frequency,damping ratio)and wind characteristics were the vital factors affecting the wind effect assessment of these large building structures.Most of the present structural modal parameter identification technology assumed that the excitation signal is considered as stationary random signal,which is inconsistent with the non-stationary characteristics of the strong wind loads.The applicability of these methods is naturally questioned.In order to accurately estimate structural natural frequency and damping ratio under non-stationary excitation,methods of structure modal parameter identification under ambient excitation were studied in this article.In terms of the extreme wind environments such as strong wind or typhoons,the wind characteristic parameters depend largely on the time-varying mean(TVM)of wind speed.Therefore,extracting the TVM based on the wind speed records becomes an essential part of establishing non-stationary wind speed model to evaluate wind characteristic parameters.In general,the low-frequency component of wind speed is generally regarded as the TVM in practice,and there exist some common used approaches to obtain the TVM from the measured wind speed records,for example,polynomial curve fitting,moving average,high-order filtering and wavelet transform.However,these processing methods always lack the quantitative guideline for the TVM,and the extraction effect depends on the user’s experience and the identified parameter values.Therefore,developing an effective method for extracting and evaluating TVM has become an urgent task in establishing non-stationary wind speed models.In order to circumvent the aforementioned problem,this paper also carried out research on extraction method for the optimal TVM of non-stationary wind speed,and the main contents were as follows.Chapter 2 presented the theories of two decomposition algorithms(empirical wavelet transform(EWT)and variational mode decomposition(VMD)),and some modal recognition methods,namely,improved random decrement technique(IRDT),natural excitation technique(NEx T),Hilbert transform(HT),discrete energy separation algorithm(DESA)and half-cycle energy algorithm(HCEA).Combining the aforementioned algorithms,two methods were developed for structural modal parameter identification under non-stationary ambient excitation,which were called EWT-IRDT and VMD-SH,respectively.The numerical simulations of the frame structures were employed to discuss the effectiveness of the developed approaches in this section.Chapter 3 introduces Ping An International Finance Center and its structural health monitoring system.Meanwhile,the Typhoon NIDA and the related sensor arrangement were further described.Furthermore,the measured acceleration responses of Ping An Financial Center during Typhoon NIDA were analyzed based on the EWT-IRDT and VMD-SH.The vibration frequencies and damping ratios of Ping An Financial Center were identified in detail.Meanwhile,the instantaneous characteristics(including the instantaneous amplitude and the instantaneous frequency)of the building were investigated.The findings of this study were valuable for health monitoring and vibration control of super tall structures.Two conditions were firstly proposed for extracting the optimal TVM in the chapter 5.The first condition is namely that the derived TVM could represent the overall trend of the wind speed data,and the number of local maximum or minimum must not exceed 6.Meanwhile,the necessity of satisfying the previous condition was proved in view of the dynamic amplification factor.In addiiton,the second condition requires that the probability density function of fluctuating component should follow the modified Gaussian function.At this time,modified Gaussian deviation coefficient(MGDC)is newly defined as an evaluation index for evaluating TVM.The maller the MGDC is,the better the derived TVM is.Then,the acquisition process of optimal TVM is given in detail,based on the empirical mode decomposition(EMD).Four numerical examples are employed to verify the effectiveness of this method in extracting TVM.Finally,the optimal TVM of measured non-stationary wind speeds at 47 meters,120 meters and 280 meters from ultrasonic anemometer at the Beijing Meteorological Tower were obtained by using the developed method,which expand the engineering practicality of this approach.Chapter 6 developed a new approach based on Vondrak filter and genetic algorithm to extract optimal TVM.Firstly,the MGDC was defined as the objective function,and the optimal smoothing factor(OSF)of Vondrak filter is obtained by genetic algorithm as modified order,K,is taken as a certain number.The TVM is then derived by Vondrak filter with the aforementioned OSF.This approach was then employed to derive the optimal TVM of the non-stationary wind speeds measured by the ultrasonic anemometer on the Beijing Meteorological Tower and the Hong Kong International Financial Center.At this situation,wind parameters of each ten-minute measured wind speed data obtained by this new approach,such as gust factor,turbulence integral scale,turbulence intensity and wind spectrum,were compared with those derived from the traditional stationary model,and some meaningful conclusions are obtained,for instance,the turbulence integral scale of non-stationary model increases with the increase of wind speed,and their slopes at different heights are roughly equal.Besides,the degree of divergence of the turbulence integral scale increases as the height increases.Consequently,a modified longitudinal wind spectrum,suitable for different heights,is obtained by fitting the fluctuating wind spectrum of non-stationary wind speed model.