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Volumn 5, Issue 6, 2009, Pages 662-670

Artificial neural network model for prediction of friction factor in pipe flow

Author keywords

Artificial neural network; Friction factor; Modelling; Pipe flow; Pressure head

Indexed keywords


EID: 69049083805     PISSN: 1816157X     EISSN: 1819544X     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (22)

References (18)
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    • Simple and Explicit Formulas for the friction factor in Turbulent Pipe Flow
    • Haaland, S.E., 1983. Simple and Explicit Formulas for the friction factor in Turbulent Pipe Flow. Journal of Fluids Engineering, 30: 89-90.
    • (1983) Journal of Fluids Engineering , vol.30 , pp. 89-90
    • Haaland, S.E.1
  • 5
    • 0013313791 scopus 로고
    • Turbulent Flow in Pipes with Particular Reference to Thetransition Region Between the Smooth and Rough pipe Laws
    • Colebrook, C.F., 1939. "Turbulent Flow in Pipes with Particular Reference to Thetransition Region Between the Smooth and Rough pipe Laws." Proc. Institution Civil Engrs., 12: 393-422.
    • (1939) Proc. Institution Civil Engrs. , vol.12 , pp. 393-422
    • Colebrook, C.F.1
  • 6
    • 0000254670 scopus 로고
    • Experiments with Fluid- Friction in Roughened Pipes
    • Colebrook, C.F. and C.M. White, 1937. Experiments with Fluid- Friction in Roughened Pipes. Proc. Royal Soc. London, 161: 367-381.
    • (1937) Proc. Royal Soc. London , vol.161 , pp. 367-381
    • Colebrook, C.F.1    White, C.M.2
  • 7
    • 85146230273 scopus 로고
    • Friction Factors for Pipe Flow
    • Moody, L.F., 1944. Friction Factors for Pipe Flow. Trans. ASME, 66: 671-678.
    • (1944) Trans. ASME , vol.66 , pp. 671-678
    • Moody, L.F.1
  • 8
    • 33646726754 scopus 로고    scopus 로고
    • An Adaptive Wavelet Network Model for Forecasting Daily Total Solar Radiation
    • Mellit, A., M. Benghanen and S.A. Kalogirou, 2006. An Adaptive Wavelet Network Model for Forecasting Daily Total Solar Radiation. Applied Energy, 83: 705-722.
    • (2006) Applied Energy , vol.83 , pp. 705-722
    • Mellit, A.1    Benghanen, M.2    Kalogirou, S.A.3
  • 11
    • 0036373412 scopus 로고    scopus 로고
    • A Neural Network Technique to Improve Computational Efficiency of Numerical Oceanic Models
    • Krasnopolsky, V.M., D.V. Chalikov, H.L. Tolman, 2002. A Neural Network Technique to Improve Computational Efficiency of Numerical Oceanic Models. Ocean Modelling, 4: 363-383.
    • (2002) Ocean Modelling , vol.4 , pp. 363-383
    • Krasnopolsky, V.M.1    Chalikov, D.V.2    Tolman, H.L.3
  • 14
    • 0000235347 scopus 로고    scopus 로고
    • The Application of Expert Systems and Neural Networks to Gas Turbine Prognostics and Diagnostics, Journal of Engineering for Gas Tiurbines and Power
    • Depold, H.R. and F.D. Gass, 1999. The Application of Expert Systems and Neural Networks to Gas Turbine Prognostics and Diagnostics. Journal of Engineering for Gas Tiurbines and Power, ASME, 121: 607-612.
    • (1999) ASME , vol.121 , pp. 607-612
    • Depold, H.R.1    Gass, F.D.2
  • 15
    • 69049106767 scopus 로고
    • 2nd Ed. Advanced Series on Circuits and Systems World Scientific Publishing Co. Pte. Ltd
    • Grauppe, D., 1995. Principles of Artificial Neural Networks, 2nd Ed.Advanced Series on Circuits and Systems - Vol. 6, World Scientific Publishing Co. Pte. Ltd.
    • (1995) Principles of Artificial Neural Networks , Issue.6
    • Grauppe, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.