The Affecting Factors of Slope Stability Based on Orthogonal Design

Jiang, Zhao; Wang, Le Hua

doi:10.4028/www.scientific.net/amr.690-693.756

Cited by 5 publications

(2 citation statements)

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“…To rank the sensitivity for parameters, we also conducted a parameter sensitivity analysis using the orthogonal method, which is commonly used in experimental tests (Jiang & Wang, 2013;Lee, Filliben, Micheals, & Phillips, 2013). Here we illustrate the sensitivity analysis using the T-fADE model (1).…”

Section: Model Parameter Calibration and Sensitivity Analysismentioning

confidence: 99%

“…Therefore, four factors representing the four parameters in the T‐fADE ), which are v , γ , β and λ , were considered for the sensitivity analysis, and each factor has three levels (representing three possible regions for each parameter; listed in Table 1). This motivated us to select the L18 (18 represents the total number of sensitivity tests) calculation scheme (containing 3 6 values, which are applicable for three levels and four factors, plus two dummy factors, listed in Table 2) for our orthogonal design, which is suitable for the four‐factor sensitivity analysis according to the orthogonal design sheet (Jiang & Wang, 2013). Parameter levels and the testing results of the orthogonal design are listed in Table 1 and Table 2, respectively.…”

Section: Nonlocal Models In Simulating Complex Transport In Water: Review and Applicationmentioning

confidence: 99%

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Nonlocal transport models for capturing solute transport in one‐dimensional sand columns: Model review, applicability, limitations and improvement

Zhang

Zhou

Yin

et al. 2020

Hydrological Processes

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Modelling pollutant transport in water is one of the core tasks of computational hydrology, and various physical models including especially the widely used nonlocal transport models have been developed and applied in the last three decades. No studies, however, have been conducted to systematically assess the applicability, limitations and improvement of these nonlocal transport models. To fill this knowledge gap, this study reviewed, tested and improved the state-of-the-art nonlocal transport models, including their physical background, mathematical formula and especially the capability to quantify conservative tracers moving in one-dimensional sand columns, which represents perhaps the simplest real-world application. Applications showed that, surprisingly, neither the popular time-nonlocal transport models (including the multi-rate mass transfer model, the continuous time random walk framework and the time fractional advection-dispersion equation), nor the spatiotemporally nonlocal transport model (ST-fADE) can accurately fit passive tracers moving through a 15-m-long heterogeneous sand column documented in literature, if a constant dispersion coefficient or dispersivity is used. This is because pollutant transport in heterogeneous media can be scale-dependent (represented by a dispersion coefficient or dispersivity increasing with spatiotemporal scales), non-Fickian (where plume variance increases nonlinearly in time) and/or pre-asymptotic (with transition between non-Fickian and Fickian transport). These different properties cannot be simultaneously and accurately modelled by any of the transport models reviewed by this study. To bypass this limitation, five possible corrections were proposed, and two of them were tested successfully, including a time fractional and space Hausdorff fractal model which minimizes the scaledependency of the dispersion coefficient in the non-Euclidean space, and a two-region time fractional advection-dispersion equation which accounts for the spatial mixing of solute particles from different mobile domains. Therefore, more efforts are still needed to accurately model transport in non-ideal porous media, and the five model corrections proposed by this study may shed light on these indispensable modelling efforts.

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Section: Model Parameter Calibration and Sensitivity Analysismentioning

confidence: 99%

Section: Nonlocal Models In Simulating Complex Transport In Water: Review and Applicationmentioning

confidence: 99%