the perfect filter approach in reducing uncertainty in the safety evaluation of internal erosion in embankment dams
محل انتشار: سمپوزیوم برآورد عدم قطعیت در مهندسی سد
سال انتشار: 1384
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 1,011
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شناسه ملی سند علمی:
SUADE01_079
تاریخ نمایه سازی: 15 آبان 1390
چکیده مقاله:
Internal erosion is a major threat to fill dams. The perfect filter approach to the design of filters relates the permeability of filters to the size of particle that they will trap. It was devised following a serious erosion incident at Balderhead dam. It approaches the matter from fundamentals, identifying the size of the floc that will exist in clay fills and determining the permeability (as a measure of the pore size) that will trap them. It does not depend on ‘self-filtering’. In addition to being a rigorous method to design filters in new dams, the perfect filter relationship between permeability and filtering capability can be used, to check the filtering capabilities of existing filters by measuring permeability in-situ. Most importantly it can be used, by measuring their permeability in-situ, to assess the filtering capability of the fills in the downstream shoulders of fill dams in which there are no formal filters. A knowledge of the filtering capability of the fills in an existing dam can improve understanding of its behaviour should internal erosion occur. If it can be shown that some, not necessarily all, of the eroded material would be trapped, the failure process may be one of the formation of sinkholes, rather than sudden catastrophic failure, and this allows time to save lives by releasing water in a controlled manner from the reservoir and/or evacuating people out of the floodway downstream of a failing dam. The perfect filter approach offers the means to improve on methods currently used to enumerate the probability of failure of dams by internal erosion.
کلیدواژه ها:
نویسندگان
R. C. BRIDLE
Civil Engineer, Rodney Bridle Ltd, UK
P. R. VAUGHAN
Department of Civil and Environmental Engineering, Imperial College, London, UK
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