This study focuses on the identification of the lateral preferential flow at the hillslope scale and the estimation of the saturated hydraulic conductivity for the fast-flow region, K-s,K-f based on infiltration exper...
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This study focuses on the identification of the lateral preferential flow at the hillslope scale and the estimation of the saturated hydraulic conductivity for the fast-flow region, K-s,K-f based on infiltration experiments carried out at different spatial scales (point- and plot-scales), and at different soil depths. The discrepancies between the considered scales were mainly attributed to macropore flow and the difficulty in adequately embodying the macropore network on small sampled soil volumes. Conversely, at the plot-scale, the sampled volume was sufficient to activate the macropore network. This information helped establish the usability of a given technique to determine the parameters describing the hydraulic properties of the soil in the matrix and fast-flow regions. While K-s data obtained from the Beerkan method with the Beerkan Estimation of soil Transfer (best) parameter algorithm (point-scale) were used to describe the matrix (K-s,K-m), the saturated hydraulic conductivity for the fast flow region was estimated using the soil block method (plot-scale). Estimated K-s,K-f values were one to three orders of magnitude higher than K-s,K-m. The overall decrease of K-s,K-f with the soil depth supported the hypothesis that the macropore density decreased as a function of depth, yielding higher macropore flow variability. The soil block method, in association with the Beerkan infiltration runs, allowed the estimation of the saturated hydraulic conductivity for the fast-flow region based on a relatively simple field procedure.
SmartSort Visualizer, integrating Data Structures and algorithms with Java, offers a tool for sorting and algorithm analysis. Users can choose from various algorithms, including Bubble Sort, Selection Sort, Insertion ...
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Stormwater management techniques in urban areas, such as sustainable urban drainage systems (SuDS), are designed to manage rainwater through an infiltration process. In order to determine the infiltration capacities o...
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Stormwater management techniques in urban areas, such as sustainable urban drainage systems (SuDS), are designed to manage rainwater through an infiltration process. In order to determine the infiltration capacities of different SuDS and to identify their unsaturated hydraulic properties, measurements with the Beerkan method (i.e., single ring infiltration tests) were carried out on four types of common infiltration structures in an urban zone of Lyon (France): A drainage ditch with an underlying storage structure, a parking lot with a waterproof pavement that transfers runoff water toward the ditch, a vegetated hollow core slab, and an embankment of a grass-covered garden that was used as a reference for rainwater infiltration capacity. The novelty of this study lies in the use of three Beerkan estimation of soil transfer parameters (best) algorithms: best-slope, best-intercept, and best-steady to analyze infiltration data. The best methods are based on the analysis of the infiltration rate from transient to steady-state flow. They allow the determination of both shape and scale parameters of the soil water retention curve h() and the hydraulic conductivity curve K(). The three best methods are efficient and simple for hydraulic characterization of SuDS. The study of the hydrodynamic behavior of the four structures revealed the infiltration inefficiency of some of them. Their average infiltration rates are considerably lower than the reference infiltration rain garden. The results confirmed the impact of some physical conditions, such as pore structure modification due to invasive vegetation colonization and the presence of soil organic matter, on soil hydrodynamic behavior degradation.
Aim of this research is to investigate the performance characteristics of thermoacoustic engine using multi stopping criterion multi feature-based multi-objective cohort intelligence (MOCI) algorithm. MOCI and the sta...
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Aim of this research is to investigate the performance characteristics of thermoacoustic engine using multi stopping criterion multi feature-based multi-objective cohort intelligence (MOCI) algorithm. MOCI and the state-of-the-art algorithms are applied to study performance characteristics of a thermoacoustic engine (TAE). Exploratory and statistical analyses revealed better performance of the MOCI algorithm on qualitative and quantitative performance metrics. Post optimality analysis showed a better region of interest for an analyst and the desirable working ranges for each variable of TAE design. Pressure-frequency relationship showed high correlation and it is useful for future study and detailed investigation of thermoacoustic phenomenon. MOCI established competitive results which are useful in benchmarking TAE performances in future researches. The effective design of TAE using MOCI algorithm aids in the sustainable development of society in terms of affordable and clean energy, clean climate and responsible consumption and production.
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