While most research about the relationship between land use and watershed hydrological output has focused primarily on land-use types and their impact on hydrological processes, the relationship between characteristics of land-use patterns (such as pattern fragmentation, connectivity, and coherence) and hydrological processes has not been well examined. Using historical stormwater data, this study evaluates the hydrological effects of different land-use scenarios in the Qing-shui watershed in Beijing, China, at a variety of spatial scales. This study demonstrates that planning and managing land-use patterns can significantly reduce runoff under different scales, particularly for small storm events. In contrast to other aspects of land-use structure characteristics, such as the shape complexity of land-use patches, fragmented level of the patches of land-use types appear as dominant drivers of runoff. The results of the study suggest that land-use pattern management should be an important component of Best Management Practices to reduce the impacts of urbanization on natural hydrological processes.
The efficient and accurate prediction of the aeroheating performance of hypersonic vehicles is a challenging task in the thermal protection system structure design process, which is greatly affected by grid distribution, numerical schemes, and iterative steps. From the inspiration of the theoretical analysis and machine learning strategy, a new wall heat flux prediction framework is proposed first by establishing the relationship between the wall heat flux and the flow variables at an extreme temperature point (ETP) in the normal direction of the corresponding wall grid cell, which is named the machine learning (ML)-ETP method. In the training phase, the flow properties and their gradients at the ETP and the distance from the ETP normal to the wall are employed as feature values, and the accurate wall heat flux predicted by the converged fine grid is regarded as the tag value. With the assistance of the trained regression model, the heat flux of the same configuration with a coarse grid in the wall-normal direction could be predicted accurately and efficiently. Moreover, test cases of different configurations and inflow conditions with a coarse grid are also carried out to assess the model’s generalization performance. All comparison results demonstrate that the ML-ETP strategy could predict wall heat flux more rapidly and accurately than the traditional numerical method due to its nonstrict grid distribution requirements. The improvement of the predictive capability of the coarse-graining model could make the ML-ETP method an effective tool in hypersonic engineering applications, especially for unsteady ablation simulations or aerothermal optimizations.
Morphing aircraft has adjustable aerodynamic shapes and is suitable for variable flight conditions. And there have been growing interests in recent years. However, the forces and moments are highly nonlinear, bringing challenges in design and modeling of flight control system (FCS). In this paper, unsteady Computational Fluid Dynamics (CFD) simulations are performed by solving the Arbitrary Lagrangian–Eulerian (ALE) governing equations on unstructured dynamic mesh, then unsteady aerodynamic characteristics of a variable-sweep morphing aircraft at hypersonic speed are acquired. The nonlinearity index theory is employed to analyze the nonlinearity of pitching moments. FCS is designed using nonlinear dynamic inversion control, taking attitude angles and sweep angle into consideration. Unsteady flow simulation is performed using unsteady CFD coupled with FCS. Cases of open and close loop morphing flight over the variation of sweep angle corresponding to flight conditions are studied. Results show that the nonlinearity of unsteady forces and moments are significant. The combination of unsteady CFD and FCS provides a powerful approach to the study of morphing aircraft.
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