Journal of Wind Engineering and Industrial Aerodynamics最新文献

To verify the existence of the large-scale meandering flow structure that causes flow-induced vibration (FIV) of high-speed trains traveling in tunnels, the vertical flow velocities on the sides of the cars of a high-speed train running in a tunnel and in the open air are estimated by a simple method of tuft visualization in running experiments on a real train without conducting large-scale measurements. Tufts are attached to the side windows of the 3rd and the 14th car of the 16-car Shinkansen train, and the mean and peak values of vertical flow velocity fluctuations are estimated from the movement of the tufts. First, the steady flow field around the 16-car train is estimated from the mean values of vertical flow velocity fluctuations. Then, the existence of the large-scale meandering flow structure along the train traveling in the tunnel is identified from the peak values by comparing the results between the numerical simulation of previous research and the running experiments. The results of this study support the validity of the mechanism proposed in the numerical simulation, in which the large-scale meandering flow structure is formed along the train traveling in the tunnel, generating aerodynamic forces acting on the sides of the car.

This document serves as an extension of the keynote presentation delivered in Florence during the 16th International Conference on Wind Engineering. It elucidates the objectives and reviews the challenges related to two pivotal issues at the juncture of wind and structural engineering: (i) the computation of Equivalent Static Wind Loads and (ii) the reconstruction of the envelope of structural responses. Various existing techniques are examined in this paper, accompanied by practical insights drawn from a simple academic example, accessible as supplementary material. Additionally, the notion of Aerodynamic-Structural Complexity is introduced as a pertinent indicator, effectively capturing the intertwined intricacies of both wind aerodynamics and structural behavior.

Short-term wind speed prediction is an effective measure for the rational integration of wind energy into the grid system. Subject to the complex characteristics of natural winds, achieving accurate predictions often pose a significant challenge. For this purpose, this paper develops a new hybrid forecasting method based on multivariate variational mode decomposition (MVMD), four different predictors and correntropy loss-enhanced selective combination. Specifically, MVMD is first used to decompose the multi-height wind speed data into a number of subseries groups with a well mode-alignment attribute, thereby avoiding the problem of model aliasing to some extent. Then, four predictors with different design principles (i.e., the consideration of model diversity) are constructed for capturing multiple data features. Further, the correntropy loss is used to replace the conventional mean square error loss for reflecting the actual noise environment in a robust manner. On this basis, an improved group method of data handling with high practicability is developed to realize the selective combination prediction. Finally, numerical examples based on three groups of multi-channel datasets are employed to demonstrate the forecasting ability of the proposed method. The results indicate that this method is superior to the other concerned methods. For example, compared with VMD-based method, the average improvement realized via the proposed method in term of mean absolute error is 20.3343%.

Quantifying turbulence effects is crucial for understanding building aerodynamics and for ensuring accurate wind tunnel test methods. This is especially important in wind tunnel methods that require post-experiment adjustments because approximate wind fields are used, such as the Partial Turbulence Simulation (PTS) approach. Understanding and analyzing these effects enables load adjustments since the PTS method only requires matching the high frequency portions of the upstream spectra of the longitudinal velocity component in model and full-scale. However, the limits for which the PTS method is applicable are unclear in terms of the allowable range of wind field characteristics that can be used in the wind tunnel simulation. To address this, the paper utilizes two nondimensional parameters, one representing the small-scale turbulence energy, E_S, and the other the large-scale turbulence energy, E_L, to elaborate the aerodynamic effects of turbulence intensity and integral length scales in the upstream wind. The results show that the maximum allowable mismatch ratio of integral length scales and of Jensen numbers between model and full-scale simulations depend on the target small-scale turbulence energy and the maximum allowable deviation of small-scale energy. By quantifying the effects of E_S and E_L on area-averaged pressure coefficients, the allowable limits are identified for wind tunnel test parameters that lead to negligible differences in the resultant pressure coefficient statistics in regions of separated-reattaching flow on the roof of a low-rise building.

Based on the 3rd-order softened Hermite nonlinear equations, a new simplified formula of the Hermite moment model is proposed. According to the wind tunnel pressure test data of a flat roof, the new and existing simplified formulas are used to calculate the Hermite parameters and peak factors respectively. The calculation accuracies of different simplified formulas are compared and analyzed to verify the applicability of the new simplified formula. The results show that the new simplified formula has higher accuracy for the peak factor calculation of high-order softened time histories, and the relative error is kept within 15%. And the applicability for mild non-Gaussian time histories is relatively better. For low-order softened time histories, the calculation errors of the new simplified formula are relatively large for the Hermite parameters, but the calculation accuracy of the peak factor is kept within the applicable range. Specifically, the calculation errors of the negative peak factors distributed only in the 1st-order softened applicable range are less than 20%, and the calculation errors of the negative peak factors distributed only in the 2nd-order softened applicable range are less than 15%. Finally, the new simplified formula shows good applicability to the extreme value analysis of the high-order and low-order softened wind pressure time histories.

Meteorological numerical forecast models can provide a more accurate typhoon wind fields compared to engineering typhoon models due to their incorporate atmospheric multiphysical processes. However, the latest advancements in supercomputing power indicate that the current finest level of real-time weather forecasting typically operates on grid scales ranging from 1 to 4 km, while the convergence of typhoon intensity and turbulent field characteristics occurs at scales as fine as 62–185 m. Therefore, the primary scientific inquiry lies in determining how to achieve high-precision turbulent wind fields while considering the realistic atmospheric multiphysical processes, that means establish a “bridge” of typhoon wind field between kilometer-level and hundred-meter scales. This study investigates the super-resolution reconstruction of wind fields across different horizontal grid scales, utilizing a benchmark wind field at a 62 m horizontal grid scale (ground truth), which is based on a hybrid down-sampling skip connection (DSC)/multi-scale (MS) model. The research findings demonstrate that compared to traditional interpolation methods, the DSC/MS method significantly improves reconstruction accuracy, albeit with some residual high-frequency energy dissipation issues. Additionally, the DSC/MS method currently exhibits better reconstruction performance for 62 m scale wind fields based on kilometer-scale and smaller horizontal grid scales (1 km, 555 m, 185 m), with improved reconstruction as grid scale decreases. However, significant errors are observed in reconstructing fine turbulent fields at 62 m scale based on wind fields at 1.67 km horizontal grid scale. The findings presented in the present study can provide real and high-precision turbulent wind fields for structural wind engineering and wind energy assessment studies, thereby holding significant scientific and engineering application value.