Generally, when a model is made of the same material as the prototype in shaking table tests, the equivalent material density of the scaled model is greater than that of the prototype because mass is added to the model to satisfy similitude criteria. When the water environment is modeled in underwater shaking table tests, however, it is difficult to change the density of water. The differences in the density similitude ratios of specimen materials and water can affect the similitude ratios of the hydrodynamic and wave forces with those of other forces. To solve this problem, a coordinative similitude law is proposed for underwater shaking table tests by adjusting the width of the upstream face of the model or the wave height in the model test to match the similitude ratios of hydrodynamic and wave forces with those of other forces. The designs of the similitude relations were investigated for earthquake excitation, wave excitation, and combined earthquake and wave excitation conditions. Series of numerical simulations and underwater shaking table tests were performed to validate the proposed coordinative similitude law through a comparison of coordinative model and conventional model designed based on the coordinative similitude law and traditional artificial mass simulation, respectively. The results show that the relative error was less than 10% for the coordinative model, whereas it reached 80% for the conventional model. The coordinative similitude law can better reproduce the dynamic responses of the prototype, and thus, this similitude law can be used in underwater shaking table tests. 相似文献
Natural Hazards - Land subsidence induced by groundwater exploitation is a typically multi-scale and multi-field coupling process. The adjustment process and action mechanism of soil mesostructure... 相似文献
While recent observational studies have shown the critical role of atmospheric transient eddy (TE) activities in midlatitude unstable air-sea interaction, there is still a lack of a theoretical framework characterizing such an interaction. In this study, an analytical coupled air-sea model with inclusion of the TE dynamical forcing is developed to investigate the role of such a forcing in midlatitude unstable air-sea interaction. In this model, the atmosphere is governed by a barotropic quasi-geostrophic potential vorticity equation forced by surface diabatic heating and TE vorticity forcing. The ocean is governed by a baroclinic Rossby wave equation driven by wind stress. Sea surface temperature (SST) is determined by mixing layer physics. Based on detailed observational analyses, a parameterized linear relationship between TE vorticity forcing and meridional second-order derivative of SST is proposed to close the equations. Analytical solutions of the coupled model show that the midlatitude air-sea interaction with atmospheric TE dynamical forcing can destabilize the oceanic Rossby wave within a wide range of wavelengths. For the most unstable growing mode, characteristic atmospheric streamfunction anomalies are nearly in phase with their oceanic counterparts and both have a northeastward phase shift relative to SST anomalies, as the observed. Although both surface diabatic heating and TE vorticity forcing can lead to unstable air-sea interaction, the latter has a dominant contribution to the unstable growth. Sensitivity analyses further show that the growth rate of the unstable coupled mode is also influenced by the background zonal wind and the air–sea coupling strength. Such an unstable air-sea interaction provides a key positive feedback mechanism for midlatitude coupled climate variabilities.
Gaussian elimination is an efficient and numerically stable algorithm for estimating parameters and their precision. However, before estimating the parameters, it is often prudent to perform statistical tests to achieve the best fitting model. We use Gaussian elimination to select the best fitting model among candidate models. A succinct relationship between the weighted sum of squared residuals and the previous one is revealed by a volume formula. For quick parameter estimation and determination of weighted sum of squared residuals, a recursive elimination algorithm is proposed in the context of Gaussian elimination. In order to improve the model selection efficiency, the parameter estimation and the determination of the weighted sum of squared residuals are carried out in parallel using the proposed recursive elimination algorithm in which the improvement at each recursive stage is judged by the Bayesian information criterion. Ultimately, the computational complexity and numerical stability of the recursive elimination proposed are briefly discussed, and a GNSS orbit interpolation example is used to verify the results. It shows that the proposed recursive elimination algorithm inherits the numerical stability of the Gaussian elimination, and this algorithm can be used to examine the gain from the newly introduced parameter, dynamically assess the fitting model, and fix the optimal model efficiently. The optimal fitting model with the lowest information is very close to the real situation verified by checkpoints. 相似文献