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The response of gobi surfaces to the near-surface air flow can be characterized quantitatively by drag coefficients. By using wind tunnel tests, an attempt is made to define the relationship between the drag coefficients of gobi surfaces and gravel size and coverage. It is concluded that the drag coefficients of gobi surfaces tend to be constants when gravel coverage is over 40%-50%. Consequently, we think that the gobi deflation planes expanding vastly in the arid Northwestern China are aerodynamically stable, at least not the supplying sources of current dust storms, and therefore the emphasis on dust storm control should be paid on the so-called "earth gobi" that has low gravel coverage. The prediction model for drag coefficients of gobi surfaces has been developed by regressing drag coefficients on gravel size and coverage, the predicted results are in reasonably good agreement with wind tunnel results (R 2 = 0.94). The change of drag coefficients with gravel friction Reynolds number implies that the development extent of drag effect increases with gravel size and coverage. 相似文献
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由于介观尺度的孔隙流体流动,弹性波传播过孔隙岩层时在地震频段表现出较强的频散和衰减。Johnson理论给出了在任意孔隙形状的条件下,部分气水饱和孔隙介质的理论相速度和品质因子的解析解。本文在Johnson模型的基础上,通过对Q值曲线的低频和高频近似,推导了Q值曲线的近似公式,以及基于孔隙介质基本地球物理参数和孔隙斑块几何形态参数T和比表面积S/V的最大衰减Qmin近似公式。通过与理论值的对比,对Qmin近似公式存在的线性误差进行改正,进一步提高了精度。复杂的斑块形态对最大衰减Qmin和过渡频率ftr的都产生一定影响,且对ftr影响更大。因为数值模拟直接求解介观尺度的Biot孔隙介质方程需要极大的计算量,我们使用Zener模型建立了等效粘弹模型,有效地模拟了地震频带内的衰减和频散现象。 相似文献
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Quantification of parametric uncertainty of ANN models with GLUE method for different streamflow dynamics 总被引:1,自引:1,他引:1
Hakan?TongalEmail authorView authors OrcID profile Martijn?J.?Booij 《Stochastic Environmental Research and Risk Assessment (SERRA)》2017,31(4):993-1010
This study describes the parametric uncertainty of artificial neural networks (ANNs) by employing the generalized likelihood uncertainty estimation (GLUE) method. The ANNs are used to forecast daily streamflow for three sub-basins of the Rhine Basin (East Alpine, Main, and Mosel) having different hydrological and climatological characteristics. We have obtained prior parameter distributions from 5000 ANNs in the training period to capture the parametric uncertainty and subsequently 125,000 correlated parameter sets were generated. These parameter sets were used to quantify the uncertainty in the forecasted streamflow in the testing period using three uncertainty measures: percentage of coverage, average relative length, and average asymmetry degree. The results indicated that the highest uncertainty was obtained for the Mosel sub-basin and the lowest for the East Alpine sub-basin mainly due to hydro-climatic differences between these basins. The prediction results and uncertainty estimates of the proposed methodology were compared to the direct ensemble and bootstrap methods. The GLUE method successfully captured the observed discharges with the generated prediction intervals, especially the peak flows. It was also illustrated that uncertainty bands are sensitive to the selection of the threshold value for the Nash–Sutcliffe efficiency measure used in the GLUE method by employing the Wilcoxon–Mann–Whitney test. 相似文献
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