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Modelling evolution of bed profile and grain size distribution in unsurveyed rivers

International Journal of Sediment Research 2009年第2期24卷 127-144页

作者： P. RONCO G. FASOLATO G. DiSILVIO Department of Hydraulic Maritime Environmental and Geotechnical EngineeringUniversity of Padua Department of Hydraulic Maritime Environmental & Geotechnical EngineeringUniversity of Padua

The water flow and sediment transport equations have been linearized and analytically solved under the hypothesis of quasi-equilibrium conditions. This solution permits to reconstruct the river bathymetry from planimetric data,the only ones available from satellite images for most of the large rivers of the world. The linearized quasi-equilibrium solution provides a criterion to evaluate the accuracy of the approximate(uniform-flow) model,compared to the regular(steady-flow) model. For non-equilibrium conditions,a further constraint on time resolution should be added,which is however generally satisfied for long-term morphological simulations. The uniform-flow solution presents many advantages which become crucial for long-term numerical computations at watershed scale. The article provides a detailed numerical comparison of the accuracy and resolution of both steadyand uniform-flow models,with an application to the evolution of the lower Zambezi River,which confirms the theoretical criterion. The accuracy of the uniform-flow solution appears to improve when the river is schematized with a coarse computational grid although,of course,with a corresponding loss of spatial resolution.

关键词： Morphological data One-dimensional model Sediment transport Long-term morphodynamics Bathymetric survey space resolution

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Clustering mechanism for electric tomography imaging

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Science China(Information Sciences) 2012年第12期55卷 2849-2864页

作者： WU Teresa School of Computing InformaticsDecision Systems EngineeringArizona State University

Electrical tomography(ET) imaging,developed in the 1980s,has attracted much industrial and research attentions owing to its low cost,quick response,lack of radiation exposure,and non-intrusiveness compared to other tomography modalities.However,to date applications thereof have been limited owing to its low imaging resolution.The issue with space resolution in existing ET imaging reconstruction methods is that they employ a mathematical approach based on an ill-posed equation with inconsistent solutions.In this paper,we propose a novel ET imaging method based on a data-driven approach.By recovering the cluster structures hidden in the ET imaging process followed by the application of a fuzzy clustering algorithm to identify the cluster structures,there is no need to study the ill-posed mathematical formulation.The proposed method has been tested by means of three experiments,including image reconstructions of a human lung image and plastic rode shape,as well as two simulations executed on the Comsol platform.The results show that the proposed method can reconstruct ET images with much higher space resolution more quickly than the existing algorithms.

关键词： electrical tomography ill-posed problem fuzzy clustering space resolution

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