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Information Journal Paper

Title

COMPARING BETWEEN PREDICTED OUTPUT TEMPERATURE OF FLAT-PLATE SOLAR COLLECTOR AND EXPERIMENTAL RESULTS: COMPUTATIONAL FLUID DYNAMICS AND ARTIFICIAL NEURAL NETWORK

Pages

  298-311

Abstract

 Introduction: The significant of solar energy as a renewable energy source, clean and without damage to the environment, for the production of electricity and heat is of great importance. Furthermore, due to the oil crisis as well as reducing the cost of home heating by 70%, solar energy in the past two decades has been a favorite of many researchers. Solar collectors are devices for collecting solar radiant energy through which this energy is converted into heat and then heat is transferred to a fluid (usually air or water). …

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    APA: Copy

    NADI, F., ABDANAN MEHDIZADEH, S., & NOURANI ZONOUZ, O.. (2017). COMPARING BETWEEN PREDICTED OUTPUT TEMPERATURE OF FLAT-PLATE SOLAR COLLECTOR AND EXPERIMENTAL RESULTS: COMPUTATIONAL FLUID DYNAMICS AND ARTIFICIAL NEURAL NETWORK. JOURNAL OF AGRICULTURAL MACHINERY, 7(1), 298-311. SID. https://sid.ir/paper/201315/en

    Vancouver: Copy

    NADI F., ABDANAN MEHDIZADEH S., NOURANI ZONOUZ O.. COMPARING BETWEEN PREDICTED OUTPUT TEMPERATURE OF FLAT-PLATE SOLAR COLLECTOR AND EXPERIMENTAL RESULTS: COMPUTATIONAL FLUID DYNAMICS AND ARTIFICIAL NEURAL NETWORK. JOURNAL OF AGRICULTURAL MACHINERY[Internet]. 2017;7(1):298-311. Available from: https://sid.ir/paper/201315/en

    IEEE: Copy

    F. NADI, S. ABDANAN MEHDIZADEH, and O. NOURANI ZONOUZ, “COMPARING BETWEEN PREDICTED OUTPUT TEMPERATURE OF FLAT-PLATE SOLAR COLLECTOR AND EXPERIMENTAL RESULTS: COMPUTATIONAL FLUID DYNAMICS AND ARTIFICIAL NEURAL NETWORK,” JOURNAL OF AGRICULTURAL MACHINERY, vol. 7, no. 1, pp. 298–311, 2017, [Online]. Available: https://sid.ir/paper/201315/en

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