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Volumn 33, Issue 2, 2004, Pages 139-143

Flow geometry optimization of channels with baffles using neural network and second law of thermodynamics (Computational Mechanics (2003) 33:2 (139-143) DOI:10.1007/s00466-003-0509-1);Flow geometry optimization of channels with baffles using neural networks and second law of thermodynamics

Author keywords

Baffles; Heat transfer; Neural network

Indexed keywords

ALGORITHMS; BACKPROPAGATION; COMPUTER SIMULATION; CONSTRAINT THEORY; HEAT TRANSFER; HEAT TRANSFER COEFFICIENTS; NEURAL NETWORKS; PRANDTL NUMBER; PRESSURE DROP; THERMODYNAMICS; TURBULENT FLOW;

EID: 3042739419     PISSN: 01787675     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00466-006-0083-4     Document Type: Erratum
Times cited : (12)

References (12)
  • 2
    • 0026205389 scopus 로고
    • Neural network methodology for heat transfer data analysis
    • Thibault J, Grandjean BPA (1991) Neural network methodology for heat transfer data analysis. Int. J. Heat and Mass Trans. 34(8): 2063-2070
    • (1991) Int. J. Heat and Mass Trans. , vol.34 , Issue.8 , pp. 2063-2070
    • Thibault, J.1    Grandjean, B.P.A.2
  • 11
    • 0344518254 scopus 로고
    • Experimental investigations of transient forced convection in ducts for a time wise varying inlet temperature
    • Ding Y (1986) Experimental investigations of transient forced convection in ducts for a time wise varying inlet temperature. Int. J. Heat and Mass Trans. 29: 495-1501
    • (1986) Int. J. Heat and Mass Trans. , vol.29 , pp. 495-1501
    • Ding, Y.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.