The wind parameter distribution law at a bridge midspan in a U-shaped valley has important influence on the wind strength of this bridges. In this paper, the wind characteristics were researched by computational fluid dynamics (CFD). The surface roughness, the inlet wind speed, the wind speed profile, and the oncoming wind direction were selected as the initial conditions; the wind speed, the wind attack angle, and the wind azimuth angle were set as wind parameters; and the effect of the four initial conditions on the wind parameters was comprehensively analyzed. An innovative quantification model used to connect the coefficient of sensitivity factors with scale values was established, and the influence of initial conditions on wind parameters was studied by analytic hierarchy process (AHP) for the first time. The results show that the spatial distribution of wind characteristics in a U-shaped valley is complex and obviously affected by the initial conditions. The established quantification model has certain practicability. The AHP evaluation results showed that the influence of the oncoming wind direction on wind parameters was the most obvious. The influence degree of oncoming wind direction and wind speed profile on wind speed was just as important, accounting for 77.4%. The sensitivity of wind attack angle to oncoming wind direction was 60.8%, which was much higher than the surface roughness, inlet wind speed, and wind speed profile. The influence degree of oncoming wind direction on wind azimuth angle was the sum of the other three initial conditions.

This study provides a comprehensive investigation into the influence of L-shaped deflector dimensions on the vortex-induced vibration (VIV) of a closed-box girder, based on synchronized wind tunnel tests with vibration and pressure measurements, spectral proper orthogonal decomposition (SPOD), and numerical simulations. Results indicate that vertical bending VIV occurs within a single response interval and is suppressed with the increasing horizontal plate size. In contrast, torsional VIV exhibits two distinct response intervals with increasing deflector dimensions and is generally amplified by the vertical plate. Vertical bending VIV is primarily governed by the horizontal plate, whereas torsional responses are dominated by the vertical plate. For vertical bending VIV, vortex-excited forces exhibit marked nonlinearity and frequency multiplication. In torsional cases, the first torsional interval exhibits smaller amplitudes but higher vortex-excited force moments, while the second shows stronger nonlinearity and more prominent higher harmonics. Across all vibration types, the upper surface consistently contributes most to the aerodynamic force, especially in the downstream region, while the inclined web exerts positive effects mainly under torsional conditions. SPOD analysis reveals that the first-order mode exhibits a streamwise-traveling structure in all cases, while the second torsional interval shows greater modal energy concentration and spatial coherence than the first. Flow field evolution further confirms that vertical bending VIV is governed by symmetric counter-rotating vortices, whereas torsional VIV arises from pronounced phase differences in vortex shedding between the upper and lower surfaces, leading to significant flow asymmetry.

To investigate the non-stationary characteristics of the wind field at the U-shaped canyon bridge site and its impact on fluctuating wind characteristics, a wind observation tower was installed near a cable-stayed bridge. The Augmented Dickey–Fuller (ADF) test was employed to assess the stationarity of wind speed series, while the discrete wavelet transform (DWT) was applied to reconstruct the time-varying mean wind and analyze its effect on fluctuating wind characteristics. Results indicate that wind speeds in this region exhibit bimodal distribution characteristics, with the Weibull-Gamma mixed distribution model providing the best fit. The proportion of non-stationary samples increases with height. Autocorrelation function (ACF), partial autocorrelation function (PACF) tests, and power spectral density (PSD) analysis determined the optimal wavelet decomposition level for wind speed in this region. Analysis of non-stationary samples using db10 wavelet reconstruction reveals that the stationary wind speed model overestimates turbulence intensity but underestimates the turbulence integral scale. The downwind spectrum deviates from the Kaimal spectrum in both low- and high-frequency bands, whereas the vertical spectrum aligns well with the Panofsky spectrum. The findings demonstrate that the wavelet reconstruction method more accurately captures fluctuating wind characteristics under the complex terrain conditions of this canyon area.