EVALUATION AND ANALYSIS OF TRAPPING EFFICIENCY OF VORTEX TUBE EJECTOR USING SOFT COMPUTING TECHNIQUES
Publication details: Roorkee Indian Water Resources Society 2019Edition: Vol, 39(3), JulyDescription: 1-9pSubject(s): Online resources: In: Journal of indian water resource societySummary: The problem of sedimentation is a global concern linked with the design of intake structures and hydel channels. Sedimentation decreases the water transporting capacity of canals and hydel channels. Vortex tube silt placed across the channel, is used to extract sediments from the canalin an efficient and economical way. Experiments have been conducte withvortex tube models having variation in the size diameter (t/d), and extraction ratio (%).To fit the observed data set and to relate trapping efficiency with the input parame Process Regression (GP) and Support Vector Machine(SVM) techniques were applied to estimate the trapping ef tube silt ejector. Out of 144 observations collected from experiments, the modelsare trained with 100 observations chosen arb the total data and tested with the remaining 44 observations. Modeling results are also proposed for vortex tube silt ejection devices.Parameter sensitivity results implysediment size and the extraction ratio are variables influencing the trapping performance of a vortex tube device.| Item type | Current library | Status | Barcode | |
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Articles Abstract Database
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School of Engineering & Technology (PG) Archieval Section | Not for loan | 2021-2022192 |
The problem of sedimentation is a global concern linked with the design of intake structures and hydel channels. Sedimentation decreases the
water transporting capacity of canals and hydel channels. Vortex tube silt
placed across the channel, is used to extract sediments from the canalin an efficient and economical way. Experiments have been conducte
withvortex tube models having variation in the size
diameter (t/d), and extraction ratio (%).To fit the observed data set and to relate trapping efficiency with the input parame
Process Regression (GP) and Support Vector Machine(SVM) techniques were applied to estimate the trapping ef
tube silt ejector. Out of 144 observations collected from experiments, the modelsare trained with 100 observations chosen arb
the total data and tested with the remaining 44 observations. Modeling results are also
proposed for vortex tube silt ejection devices.Parameter sensitivity results implysediment size and the extraction ratio are
variables influencing the trapping performance of a vortex tube device.
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