Characterizing Spatial Patterns of Phenology in Cropland of China Based on Remotely Sensed Data

This study used time-series of global inventory modeling and mapping studies （GIMMS） normalized difference vegetation index （NDVI） datasets at a spatial resolution of 8 km and 15-d interval to investigate the spatial patterns of cropland phenology in China. A smoothing algorithm based on an asymmetric Gaussian function was first performed on NDVI dataset to minimize the effects of anomalous values caused by atmospheric haze and cloud contamination. Subsequent processing for identifying cropping systems and extracting phenological parameters, the starting date of growing season （SGS） and the ending date of growing season （EGS） was based on the smoothed NVDI time-series data. The results showed that the cropping systems in China became complex as moving from north to south of China. Under these cropping systems, the SGS and EGS for the first growing season varied largely over space, and those regions with multiple cropping systems generally presented a significant advanced SGS and EGS than the regions with single cropping patterns. On the contrary, the phenological events of the second growing season including both the SGS and EGS showed little difference between regions. The spatial patterns of cropping systems and phenology in Chinese cropland were highly related to the geophysical environmental factors. Several anthropogenic factors, such as crop variety, cultivation levels, irrigation, and fertilizers, could profoundly influence crop phenological status. How to discriminate the impacts of biophysical forces and anthropogenic drivers on phenological events of cultivation remains a great challenge for further studies.

Investigation of rotating stall for a centrifugal pump impeller using various SGS models

The accurate modeling and prediction of the rotating stall in a centrifugal pump is a significant challenge. One of the modeling techniques that can improve the accuracy of the flow predictions is the large eddy simulation （LES）. The quality of the LES predictions depends on the sub-grid-scale （SGS） model implemented in the LES. This paper assesses the influence of various SGS models that are suitable for predicting rotating stall in a low-specific speed centrifugal pump impeller. The SGS models considered in the present work include the Smagorinsky model （SM）, the dynamic Smagorinsky model （DSM）, the dynamic non-linear model （DNM）, the dynamic mixed model （DMM） and the dynamic mixed non-linear model （DMNM）. The results obtained from these models are compared with the PIV and LDV experimental data. The analysis of the results shows that the SGS models have significant influences on the flow field. Among the models, the DSM, the DMM and the DMNM can successfully predict the ＂two-channel＂ stall phenomenon, but not the SM and the DNM. According to the simulations, the DMNM gives the best prediction on the mean velocity flow field and also indicates improvements for the simulation of the turbulent flow. Moreover, the high turbulent kinetic energy predicted by the DMNM is in the best agreement with the experiment data.

LARGE-EDDY AND DETACHED-EDDY SIMULATIONS OF THE SEPARATED FLOW AROUND A CIRCULAR CYLINDER

The separated turbulent flow around a circular cylinder is investigated using Large-Eddy Simulation （LES）, Detached-Eddy Simulation （DES, or hybrid RANS/LES methods）, and Unsteady Reynolds-Averaged Navier-Stokes （URANS）. The purpose of this study is to examine some typical simulation approaches for the prediction of complex separated turbulent flow and to clarify the capability of applying these approaches to a typical case of the separated turbulent flow around a circular cylinder. Several turbulence models, i.e. dynamic Sub-grid Scale （SGS） model in LES, the DES-based Spalart-Allmaras （S-A） and κ-ω Shear-Stress- Transport （SST） models in DES, and the S-A and SST models in URANS, are used in the calculations. Some typical results, e.g., the mean pressure and drag coefficients, velocity profiles, Strouhal number, and Reynolds stresses, are obtained and compared with previous computational and experimental data. Based on our extensive calculations, we assess the capability and performance of these simulation approaches coupled with the relevant turbulence models to predict the separated turbulent flow.