同位网格摄动有限体积格式求解浮力驱动方腔流

利用对流扩散方程的摄动有限体积格式,在Rayleigh数从10~3到10~8的范围内对浮力驱动方腔流动问题作了数值模拟.对流扩散方程的摄动有限体积格式具有一阶迎风格式的简洁形式,使用相同的基点,重构近似精度高,特别是两相邻控制体中心到公共界面的距离相等或不相等,PFV格式公式相同等优点.在数值模拟中,无论均匀网格还是非均匀网格均获得与DSC方法、自适应有限元法、多重网格法等Benchmark解相符较好的数值结果,证明UPFV格式对高Rayleigh数对流传热问题的适用性和有效性.

Numerical simulation of condensation of bubbles under microgravity conditions by moving mesh method in the double-staggered grid

A numerical 2D method for simulation of two-phase flows including phase change under microgravity conditions is presented in this paper, with a level set method being coupled with the moving mesh method in the double-staggered grid systems. When the grid lines bend very much in a curvilinear grid, great errors may be generated by using the collocated grid or the staggered grid. So the double-staggered grid was adopted in this paper. The level set method is used to track the liquid-vapor interface. The numerical analysis is fulfilled by solving the Navier-Stokes equations using the SIMPLER method, and the surface tension force is modeled by a continuum surface force approximation. A comparison of the numerical results obtained with different numerical strategies shows that the double-staggered grid moving-mesh method presented in this paper is more accurate than that used previously in the collocated grid system. Based on the method presented in this paper, the condensation of a single bubble in the cold water under different level of gravity is simulated. The results show that the condensation process under the normal gravity condition is different from the condensation process under microgravity conditions. The whole condensation time is much longer under the normal gravity than under the microgravity conditions.

Remote sensing of ocean waves by along-track interferometric synthetic aperture radar

A new wave retrieval method for the Along-Track Interferometric Synthetic Aperture Radar (AT-InSAR) phase image is presented. The new algorithm, named parametric retrieval algorithm (PRA), uses the full nonlinear mapping relations. It differs from previous retrieval algorithms in that it does not require a priori information about the sea state or the wind vector from scatterometer data. Instead, it combines the observed AT-InSAR phase spectrum and assumed wind vector to estimate the wind sea spectrum. The method has been validated using several C-band and X-band HH-polarized AT-InSAR observations collocated with spectral buoy measurements. In this paper, X-band and C-band HH-polarized AT-InSAR phase images of ocean waves are first used to study AT-InSAR wave imaging fidelity. The resulting phase spectra are quantitatively compared with forward-mapped in situ directional wave spectra collocated with the AT-InSAR observations. Subsequently, we combine the parametric retrieval algorithm (PRA) with X-band and C-band HH-polarized AT-InSAR phase images to retrieve ocean wave spectra. The results show that the ocean wavelengths, wave directions, and significant wave heights estimated from the retrieved ocean wave spectra are in agreement with the buoy measurements.

整合多尺度地球物理数据建立高分辨率储层模型的方法及应用

Most of the fields in China are in the middle-late development phase or are mature fields. It becomes more and more difficult to develop the remaining oil/gas. Therefore, it is import to enhance oil/gas recovery in order to maintain the production. Fine scale modeling is a key to improve the recovery. Incorporation of geological, seismic and well log data to 3D earth modeling is essential to build such models. In Ken71 field, well log, cross-well seismic and 3D seismic data are available. A key issue is to build 3D earth model with these multi-scales data for oil field development.In this dissertation, studies on sequential Gaussian-Bayesian simulation have been conducted. Its comparison with cokriging and sequential Gaussian simulation has been performed. The realizations generated by sequential Gaussian-Bayesian simulation have higher vertical resolution than those generated by other methods. Less differences between these realization and true case are observed. With field data, it is proved that incorporating well log, cross-well seismic and 3D seismic into 3D fine scale model is reliable. In addition, the advantages of sequential Gaussian-Bayesian simulation and conditions for input data are demonstrated. In Ken71 field, the impedance difference between sandstone and shale is small. It would be difficult to identify sandstone in the reservoir with traditional impedance inversion. After comparisons of different inversion techniques, stochastic hillclimbing inversion was applied. With this method, shale content inversion is performed using 3D seismic data. Then, the inverted results of shale content and well log data are incorporated into 3D models. This demonstrates a procedure to build fine scale models using multi scale seismic data, especially 3D seismic amplitude volume.The models generated through sequential Gaussian-Bayesian simulation have several advantages including: (1) higher vertical resolution compared with 3D inverted acoustic impedance (AI); (2) consistency of lateral variation as 3D inverted AI; (3) more reliability due to integration cross-well seismic data. It is observed that the precision of the model depends on the 3D inversion.