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Abstract: This work aims to describe the spatial distribution of flow from characteristics of the underlying pore structure in heterogeneous porous media. Thousands of two-dimensional samples of polydispersed granular media are used to (1) obtain the velocity field via direct numerical simulations, and (2) conceptualize the pore network as a graph in each sample. Analysis of the flow field allows us to distinguish preferential from stagnant flow regions and to quantify how channelized the flow is. Then, the graph’s edges are weighted by geometric attributes of their corresponding pores to find the path of minimum resistance of each sample. Overlap between the preferential flow paths and the predicted minimum resistance path determines the accuracy in individual samples. An evolutionary algorithm is employed to determine the “fittest” weighting scheme (here, the channel’s arc length to pore throat ratio) that maximizes accuracy across the entire dataset while minimizing over-parameterization. Finally, the structural similarity of neighboring edges is analyzed to explain the spatial arrangement of preferential flow within the pore network. We find that connected edges within the preferential flow subnetwork are highly similar, while those within the stagnant flow subnetwork are dissimilar. The contrast in similarity between these regions increases with flow channelization, explaining the structural constraints to local flow. The proposed framework may be used for fast characterization of porous media heterogeneity relative to computationally expensive direct numerical simulations. Article Highlights: 1.A quantitative assessment of flow channeling is proposed that distinguishes pore-scale flow fields into preferential and stagnant flow regions.2.Geometry and topology of the pore network are used to predict the spatial distribution of fast flow paths from structural data alone.3.Local disorder of pore networks provides structural constraints for flow separation into preferential v stagnant regions and informs on their velocity contrast.

The development of common bean cultivars with high technological quality that are biofortified with minerals, is required to meet the demand for food with health benefits. The objectives of this study were to evaluate whether common bean genotypes differ in terms of technological and mineral biofortification traits, to study the correlations between these characters, to analyze the genetic dissimilarity of common bean genotypes, and to select superior lines for these traits. For this, 14 common bean genotypes were evaluated in experiments conducted in three growing seasons in the Rio Grande do Sul State, Brazil. A significant genotype x environment interaction was observed for technological quality (mass of 100 grains and cooking time) and biofortification traits (concentration of potassium, phosphorus, calcium, iron, zinc, and copper). Positive correlation estimates were obtained between phosphorus and potassium (r = 0.575), iron and zinc (r = 0.641), copper and iron (r = 0.729), and copper and phosphorus (r = 0.533). In the main component cluster analysis, four groups of genotypes were formed. The following lines are recommended for selection: LP 11-363 for fast-cooking, CNFC 11 948 for high iron concentration, and LEC 03-14 for high potassium, phosphorus, and calcium concentrations in grains. Common bean lines with high phosphorus and iron concentrations in grains can be indirectly selected based on higher potassium, copper, and zinc concentrations. Controlled crossings between LP 11-363 x CNFC 11 948 and LP 11-363 x LEC 03-14 are recommended to obtain segregating lines that are fast-cooking and biofortified with minerals.