Determination of Optimum Pressure Loss Coefficient and Flow Distribution at Unsymmetrical Pipe Trifurcation Using Experimental and Numerical Technique
Basappa Meti,
Nagaraj Sitaram
Issue:
Volume 1, Issue 2, December 2017
Pages:
41-47
Received:
3 March 2017
Accepted:
27 April 2017
Published:
26 June 2017
DOI:
10.11648/j.ae.20170102.11
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Abstract: The branching of pipes is common in fluid distribution system, in penstocks of hydroelectric power plants. Junction introduces extra energy losses due to deviation of flow direction and change in magnitude of velocity and flow rate and separation the flow at the sharp corner. Hydraulic analysis is needed to optimize the head losses occurring pipe junctions. Flow prediction at pipe trifurcation junction due to combining streamlines, curvature, turbulence, anisotropy and recalculating region at high Reynolds number is complex. An attempt is made to study the pressure loss (‘K=ΔP’) for unsymmetrical pipe trifurcation (15°-45°, 30°-15°and 35°-20°) using experimental and numerical techniques. It is found that the turbulence and unequal angle of trifurcation are the main reasons for losses and separation of flow. Combined trifurcation loss coefficient (K) and branch loss coefficients have been correlated between split flow ratios.
Abstract: The branching of pipes is common in fluid distribution system, in penstocks of hydroelectric power plants. Junction introduces extra energy losses due to deviation of flow direction and change in magnitude of velocity and flow rate and separation the flow at the sharp corner. Hydraulic analysis is needed to optimize the head losses occurring pipe j...
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Modelling a Structure of a Fuzzy Data Warehouse
Alain Kuyunsa Mayu,
Nathanael Kasoro Mulenda,
Rostin Mabela Matendo
Issue:
Volume 1, Issue 2, December 2017
Pages:
48-56
Received:
12 April 2017
Accepted:
22 April 2017
Published:
28 June 2017
DOI:
10.11648/j.ae.20170102.12
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Abstract: In this article, we represent the structure of a fuzzy data warehouse. The elements of classification to build the fuzzy data warehouse are presented through the three following tasks: identification of the target-attribute, identification of linguistic terms and definition of membership functions. From these tasks, we present an approach of a fuzzy data warehouse modelling. This allows us to integrate fuzzy logic without affecting the data warehouse base.
Abstract: In this article, we represent the structure of a fuzzy data warehouse. The elements of classification to build the fuzzy data warehouse are presented through the three following tasks: identification of the target-attribute, identification of linguistic terms and definition of membership functions. From these tasks, we present an approach of a fuzz...
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