The coastal communities from the Gulf States to the Carolinas have witnessed destructive damages on coastal infrastructures, including coastal bridges and residential home buildings, etc., from hurricane induced strong winds and high waves in several hurricane events [36,138]. With the rapid increase of the bridge’s span length to cross large bodies of water, the reduction of fundamental frequency of the coastal
bridges due to the increasing slenderness has increased the damaging fluid-structure interactions since large portions of the energies in winds and waves are concentrated in the low frequency ranges. Such interactions between the coastal slender bridges and winds and waves could possibly lead to progressive damage accumulations or catastrophic failures in extreme hurricane events or other coastal natural hazards events. Meanwhile, as the transient nonstationary features of strong winds and high waves are often observed during hurricane events [18,19], the interactions of winds, waves and coastal slender bridges could be complicated due to the nonlinearity of the structural system and fluid-structure interactions. To better evaluate structural safety and reliability of coastal slender bridges, it is important to accurately predict the dynamic responses and possible fatigue damage accumulations of the coastal slender bridges when subjected to strong winds and high waves during hurricane events. With many existing studies focusing on the dynamic responses of coastal bridges subjected to either strong winds for long-span bridges [28,88] or solitary waves for short-span low-laid bridges [53,59], few studies have been focused on the dynamic interactions of coastal slender bridges with both wind and wave loads. Serving as the important inputs for the coupled bridge-wind-wave (BWW) dynamic system, realistic simulation of the wind and wave fields has been essential to quantify the system performance for the coupled dynamic system under extreme
* This chapter is adapted from a paper published in the ASCE Journal of Bridge of Engineering [198] with permission from
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For weather prediction or hurricane risk analysis, many efforts have been made to simulate hurricane associated wind field and wave field in a larger temporal and spatial scale. The research on hurricane near- surface wind field (i.e. time-varying mean) modeling can be traced back to Chow’s work in 1971 [7] and much improvement has been made since then [8–10]. Based on the planetary boundary layer (PBL), the hurricane wind field model uses a finite-difference scheme to solve for the steady-state wind field based on a set of nested rectangular grids. As an alternative approach, the parametric hurricane wind model is more frequently used for long-term wind and surge risk assessment and structural design due to its simplicity and efficiency [11]. In the parametric hurricane wind model, the near-surface time-varying mean wind is assumed as a vector summation of storm vortex associated with the hurricane itself and the environmental background wind vector related to the storm movement. However, none of the current hurricane wind models include wind turbulent fluctuations, which could introduce considerable dynamic response of structures [12].
Since wind is one of the major driving forces for waves, many methods were proposed, ranging from simple formulae for estimating wave field at a given site by using wind speed, fetch, and duration, to numerical models for wave field simulation covering large sea areas based on the input wind field time histories. Some sophisticated numerical wave prediction models, such as SWAN, WAM, WAVEWATCH models, were developed and have been widely used in various applications of weather prediction and ocean dynamics in the past few decades [13]. However, due to their large spatiotemporal scales, the resolutions for the simulated wind and waves are still low and the wind and wave time histories are still not appreciable for the dynamic analysis of coastal infrastructures [14,15]. For example, the input wind data for the SWAN model [14] for wave simulation in the Black Sea has the spatial resolution of 0.25º in both longitude and latitude with a temporal resolution of 6 h, and the output wave data has the spatial resolution of 1.3 km 1.83 km.
In addition, in the extreme weather conditions, both wind and wave could be nonstationary. The evolutionary power spectral density (EPSD) functions, which could include the energy distribution over
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both time and spectral domains [16], were used to characterize such transient features for wind fluctuations and wind driven waves [17,18]. As the frequency structures in normalized EPSDs of wind fluctuations of the downburst and typhoon were found to evolve very slightly with time, the nonstationary wind fluctuations, therefore, were assumed to be uniformly modulated processes [17,19,20]. Similarly, for the nonstationary wave, it is natural to extend the available stationary wave spectra to nonstationary ones, based on the slow-change assumption for the large-scale structure of the hurricane [9]. The power spectral density (PSD) function at each infinitely small interval, therefore, is treated to be stationary following the existing stationary wave spectrum. By combining these time-varying PSDs, a simplified nonstationary wave spectrum can be obtained and could be extended to describe the nonstationary wave after introducing the time-varying mean wind speed. With the prescribed PSD/EPSD, a number of approaches, such as Spectral Representation Method (SRM), linear filter method (e.g., Autoregressive-moving-average (ARMA)), wavelet based method, Proper Orthogonal Decomposition (POD), Empirical Mode Decomposition together with Hilbert Transform (EMD–HT) approach, etc., have been proposed to simulate the stationary/nonstationary Gaussian process [21]. In the present study, SRM is used to generate the sample functions for the nonstationary wind fluctuations and waves due to its simplicity and efficiency [139,140]. In the present study, a numerical scheme is proposed to simulate the nonstationary wind and wave fields around a coastal slender bridge during hurricane events that can be further used in the coupled bridge- wind-wave dynamic analyses. The wind field is simulated by adding the time-varying mean wind speed generated by parametric hurricane wind model and the nonstationary wind fluctuations generated by spectral representation model. The wave field is simulated based on spectral component method through the use of a proposed nonstationary wave spectrum. Both of the nonstationary wind fluctuations and waves are characterized in terms of their evolutionary power spectral density (EPSD) functions. This chapter is organized as follows. First, the wind field is simulated including modeling of deterministic time-varying mean by using parametric hurricane wind model and modeling of wind fluctuation as a uniformly modulated process. For comparison, four different gradient wind profile models under two synthetic storms with different intensities, are used for simulation. The time-varying mean winds are used to estimate the
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EPSDs of nonstationary wind and waves. Then, the stationary directional wave spectrum is extended to nonstationary one, based on the slow-change assumption of the large-scale structure of the hurricane. After the coupled bridge-wind-wave dynamic system is briefly introduced, simulation of the hurricane associated nonstationary wind and wave fields around a coastal slender bridge will be carried out. A brief summary and concluding remarks are provided at the end of this chapter.