In this paper, the multi-objective optimization of R-245fa vapour condensation inside horizontal tube has been carried out using teaching–learning-based optimization algorithm. The teaching–learning-based optimization algorithm is teaching–learning procedure motivated and works on the impact of a teacher on the outcome of students in a class. Heat transfer coefficient and pressure drop with two parameters have been considered to evaluate the performance of the tube. The mass flux and vapour quality of refrigerant are taken as the parameters. The limit of mass flux and vapour quality are from 100 to 300 kg/m2 s and 0.1 to 0.8, respectively. The optimum values of heat transfer coefficient 2820.5 W/m2 K and pressure drop 1360.2 Pa are obtained with mass flux 137.65 kg/m2 s and vapour quality 0.77 using teaching–learning-based optimization algorithm.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Multi-objective optimization of condensation heat transfer using teaching–learning-based optimization algorithm


    Beteiligte:


    Erscheinungsdatum :

    2017




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch



    Klassifikation :

    BKL:    52.30 / 52.50 / 52.50 Energietechnik: Allgemeines / 52.30 Strömungskraftmaschinen, Turbomaschinen
    Lokalklassifikation TIB:    275/5345/5365/5500




    Optimization of Heat Exchanger of Vuilleumier Heat Pump using Teaching-Learning Based Algorithm

    Gadiraju, Siddhartha / Bedekar, Yogesh / Longtin, Jon P. et al. | AIAA | 2014



    Multi-Objective Optimization of Plain Fin-and-Tube Heat Exchanger Using Evolutionary Algorithm

    Hajabdollahi, Hassan / Ahmadi, Pouria / Dincer, Ibrahim | AIAA | 2011


    Improved Artificial Weed Colonization Based Multi-objective Optimization Algorithm

    Liu, Ruochen / Wang, Ruinan / He, Manman et al. | Springer Verlag | 2017