17 research outputs found
Validation of a stochastic digital packing algorithm for porosity prediction in fluvial gravel deposits
Porosity as one of the key properties of sediment mixtures is poorly understood. Most of the existing porosity predictors based upon grain size characteristics have been unable to produce satisfying results for fluvial sediment porosity, due to the lack of consideration of other porosity-controlling factors like grain shape and depositional condition. Considering this, a stochastic digital packing algorithm was applied in this work, which provides an innovative way to pack particles of arbitrary shapes and sizes based on digitization of both particles and packing space. The purpose was to test the applicability of this packing algorithm in predicting fluvial sediment porosity by comparing its predictions with outcomes obtained from laboratory measurements. Laboratory samples examined were two natural fluvial sediments from the Rhine River and Kall River (Germany), and commercial glass beads (spheres). All samples were artificially combined into seven grain size distributions: four unimodal distributions and three bimodal distributions. Our study demonstrates that apart from grain size, grain shape also has a clear impact on porosity. The stochastic digital packing algorithm successfully reproduced the measured variations in porosity for the three different particle sources. However, the packing algorithm systematically overpredicted the porosity measured in random dense packing conditions, mainly because the random motion of particles during settling introduced unwanted kinematic sorting and shape effects. The results suggest that the packing algorithm produces loose packing structures, and is useful for trend analysis of packing porosity
Taking a closer look at the causes and impacts of fine sediment infiltration into gravel beds : development and application of an extended theory of fine sediment infiltration based on grain scale numerical simulations
The presence of fine sediment (e.g. sand, clay, and silt) in streams, regardless of its origin - natural or anthropogenic - represents a potential ecological and economic threat, especially if the bed material is predominantly (coarse) gravel. Fine sediment can be incorporated into gravel beds through concurrent deposition of both, fine and coarse particles but fine sediment can also infiltrate the bed driven by gravity or intra gravel flow, while the coarse bed material is immobile. If the gravel bed becomes clogged through input and deposition of fine sediment within the intersticial pores, the resulting porosity and permeability decrease causes significant economic and ecological damage. For stream managers, it is essential to estimate the potential damage of fine sediment infiltration (FSI), e.g. due to increased energy consumption of pumping wells, lower survival rates of fish spawn, or reduction of hyporheic exchange of oxygen and nutrients. As clay and silt are known to act as sinks for various contaminants (e.g. PCB, heavy metals, endocrine disruptors), FSI has a large impact on contaminant transport as well. In this thesis, the infiltration process of sand into gravel beds was investigated with a novel approach of high performance high resolution numerical simulation methods where the position, shape, and rotation of each sediment grain was fully resolved. As a first step, numerical methods were reviewed, validated, and assessed with regard to their accuracy, stability, and computational performance. The validated methods were then employed to perform an extensive systematic set of simulations to generate virtual gravel streambeds, investigate the impacts of sediment grain size and sorting on the infiltration process, and to determine the reduction of streambed permeability due to clogging with fine sediment. In total, almost 200 high scale simulations were performed and evaluated in course of this thesis. Virtual gravel beds were generated with grain sizes in the range 0.5~~0.32, no FSI was observed and fine sediment deposited on the surface of the bed (FSS, Fines Surface Sealing). Apart from the investigation of the influence of grain size properties on the fine sediment infiltration process, the influence of FSI on the porosity and permeability of the river bed was further determined. It was found that, depending on the type of infiltration process (USP, FDI, or FSS), large differences in porosity reduction occured. As mentioned earlier, at small relative grain sizes (~~0.32), no reduction in pore volume in the bed was observed, but complete sealing of the bed surface. The comparison of permeability values of beds before and after FSI showed a local decrease of permeability in the area where fines were present of more than one magnitude. Based on computations of depth average bed permeability, it was shown that FSI significantly affects the bed permeability up to a depth of several meters. The results of this thesis show that fine sediment infiltration has a significant impact on several properties of streambeds. Since the reduction of porosity and permeability causes economic and ecological damage, FSI must be considered in integrated stream management. This thesis provides tools to estimate the potential damage of FSI and tools to assess the performance of possible counter measures. Still, further research is needed, e.g. on the effects of flow and sediment concentration on FSI, in order to be able to quantify the effects of FSI for a broader set of environmental influences