Power Prediction with Artificial Neural Network in Experimental Organic Rankine Cycle
作者: Hasan Hüseyin BİLGİÇ Hüseyin YAĞLI Ali KOÇ Ahmet YAPICI
刊名: Selcuk University Journal of Engineering, Science & Technology, 2016, Vol.4 (1)
来源数据库: Selcuk University Journal of Engineering, Science and Technology
DOI: 10.15317/Scitech.2016116091
关键词: Organic Rankine cycleArtificial neural networksWaste heatPower prediction
原始语种摘要: In the simulation programs that used to estimate the power of the organic Rankine cycle; high error rates may have occurred due to accepting ideal or near-ideal behaviour differ from the actual behaviour of system components. Predictions made via artificial neural networks may be more close to actual results in the system which is of non-linear behaviour. In this study, network was trained by evaporator waste heat input- output temperatures and mass flow rate, cooling fluid input- output temperatures and mass flow rate taken from an experimental organic Rankine cycle. The power prediction was made with trained network and then the experimental and prediction results of the 10 kW organic Rankine cycle was compared. At the end of the study, the values obtained from artificial neural network...
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  • Rankine 兰金
  • network 网络
  • behaviour 性质
  • artificial 人为的
  • organic 有机的
  • prediction 预报
  • trained 受过训练的
  • ideal 理想
  • output 输出
  • experimental 实验的