Effect of viscosity and heterogeneity on dispersion in porous media during miscible flooding processes

In this paper, a mathematical model has been developed to quantitatively examine the effect of viscosity and heterogeneity on dispersion in porous media at the pore scale during miscible flooding processes. More specifically, the Navier-Stokes equation and advection-diffusion equation are coupled with supplementary equations to describe the solvent transport behaviour. Two-dimensional heterogeneous models are numerically developed as a function of porosity and permeability, assuming that the grain sizes satisfy normal distribution. In addition, the performance of miscible hydrocarbon gas injection in heterogeneous porous media is comprehensively evaluated. It is found that a larger aspect ratio (ratio of pore throat size) in the single non-flowing pore model results in a greater asymmetry of the concentration curve. As for single non-flowing pore models and heterogeneous models, the dispersion coefficients increase with the expansion of the non-flowing domain. Both the heterogeneity of porous media and the variable viscosity of th fluid mixture contribute to the asymmetry of the concentration curve in the heterogeneous model. A negative correlation is established between the sorting coefficients of pore throat size and the power-law coefficients. As for slug injection, the injected solvent slug size along the longitudinal direction does not effectively influence the longitudinal length of the mixing zone for a given porous medium and fluids, though the Peclet number and the porosity greatly affect the length and concentration distribution of the mixing zone.Cited as: Bai, Z., Song, K., Fu, H., Shi, Y., Liu, Y., Chen, Z. Effect of viscosity and heterogeneity on dispersion in porous media during miscible flooding processes. Advances in Geo-Energy Research, 2022, 6(6): 460-471. https://doi.org/10.46690/ager.2022.06.0

Identification of a latent pathogen on mulberry tree with a disease of mosaic dwarf

A disease on mulberries with the typical symptoms of mosaic and dwarf leaves was found in middle areas of China in 1980s. Presently, this disease became serious and spread out. Based on previous finding, we detected a viroid-like small molecular RNA in diseased mulberries tissues. In this paper, we further identified the pathogen of mulberry mosaic dwarf disease (MMDD) according to the Koch's postulates and reported the diagnostic method of the pathogen by using PCR with two sets of specific primers. The result might be helpful to control the disease extension

GitNet: Geometric Prior-based Transformation for Birds-Eye-View Segmentation

Birds-eye-view (BEV) semantic segmentation is critical for autonomous driving for its powerful spatial representation ability. It is challenging to estimate the BEV semantic maps from monocular images due to the spatial gap, since it is implicitly required to realize both the perspective-to-BEV transformation and segmentation. We present a novel two-stage Geometry Prior-based Transformation framework named GitNet, consisting of (i) the geometry-guided pre-alignment and (ii) ray-based transformer. In the first stage, we decouple the BEV segmentation into the perspective image segmentation and geometric prior-based mapping, with explicit supervision by projecting the BEV semantic labels onto the image plane to learn visibility-aware features and learnable geometry to translate into BEV space. Second, the pre-aligned coarse BEV features are further deformed by ray-based transformers to take visibility knowledge into account. GitNet achieves the leading performance on the challenging nuScenes and Argoverse Datasets. The code will be publicly available