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Details of Grant 

EPSRC Reference: GR/N24803/01
Title: DEVELOPMENT OF PROBABILISTIC METHODS FOR PREDICTING ENTRAINMENT & TRANSPORT RATES IN GRADED SEDIMENTS
Principal Investigator: McEwan, Dr I
Other Investigators:
Tait, Professor S
Researcher Co-Investigators:
Project Partners:
H R Wallingford Ltd University of Padua
Department: Engineering
Organisation: University of Aberdeen
Scheme: Standard Research (Pre-FEC)
Starts: 01 August 2001 Ends: 31 October 2003 Value (£): 101,547
EPSRC Research Topic Classifications:
Coastal & Waterway Engineering
EPSRC Industrial Sector Classifications:
Water
Related Grants:
GR/N24810/01
Panel History:  
Summary on Grant Application Form
Various graded sediment transport models are in current usage. These have been developed using empirically based hiding functions to adjust single size transport rate predictions. In general these do not provide an adequate description of the physical mechanisms present when a graded sediment deposit is mobilised. Therefore these techniques perform poorly when applied to the wide range of sediment and hydraulic conditions found in nature. Solution methods can only be significantly improved if conceptual and mathematical formulations of the important physical processes are improved. The proposed project aims to develop a probabilistic prediction method based on determining the probability distributions describing near bed turbulent shear stresses and critical grain entrainment thresholds. Development of novel imaging laboratory equipment will be used to make numerous observations linking the instantaneous fluid shear stress and grain entrainment and excursion length. A discrete particle model will be used to determine the distribution of critical grain entrainment thresholds. These two unique data sets of complimentary probability distributions will be combined using joint probability methods to yield an estimate of fractional grain entrainment and transport rates. The reliability of this approach will be tested against experimental data including that from the Series C programme at HR Wallingford.
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