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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Simulation of fan formation using a debris mass model / Formation d'un cône de dejection, simulation par un modèle de masse de débris

Shao, Songdong January 2002 (has links)
Yes / Based on the particle-in-cell computing method, a debris mass model has been established to simulate debris flow fan formation over large downstream areas. Under the assumption that the debris medium is an assembly of many small, identical debris particle masses, the overall flowbehavior is obtained by averaging the flow parameters of neighboring debris masses at fixed grid points. The equation of motion for each debris mass is based on the depthaveraged Navier-Stokes equation in two horizontal dimensions. The friction slope of debris flow is modeled by combining the effects of both the liquid phase (slurry composed ofwater and fine particles) modeled as a Bingham fluid and solid phase (coarse particles) in the debris mixture. The rheological parameters are evaluated according to the density and particle size distribution of the debris material. Convergence of the method is demonstrated by repeatedly doubling the number of debris masses employed in the computation until insignificant change is observed. The debris mass model is demonstrated through a prototype application to a documented 1991 debris flowdeposited in the lower reach of the Shawan Ravine inYunnan Province, China. The final alluvial fan was formed by eight consecutive debris flow events, each lasting about 2000 seconds with a discharge rate of 250 m3/s. The simulation results are in good agreement with field observations. The general features of debris fan development and configuration are well predicted.

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