Analytical closed-form model for predicting the power and efficiency of Stirling engines based on a comprehensive numerical model and the genetic programming

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@Article{Babaelahi:2016:Energy,
  author =       "Mojtaba Babaelahi and Hoseyn Sayyaadi",
  title =        "Analytical closed-form model for predicting the power
                 and efficiency of Stirling engines based on a
                 comprehensive numerical model and the genetic
                 programming",
  journal =      "Energy",
  volume =       "98",
  pages =        "324--339",
  year =         "2016",
  ISSN =         "0360-5442",
  DOI =          "doi:10.1016/j.energy.2016.01.031",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0360544216000505",
  abstract =     "High accuracy and simplicity in use are two important
                 required features of thermal models of Stirling
                 engines. A new numerical second-order thermal model was
                 presented through the improvement of our previous
                 modified-PSVL model in order to have an elevated
                 accuracy. The modified-PSVL model was modified by
                 considering a non-isothermal model for heater and
                 cooler. Then, the model called as CPMS-Comprehensive
                 Polytropic Model of Stirling engine, was used to
                 simulate the GPU-3 Stirling engine, and the obtained
                 results were compared with those of the previous
                 thermal models as well as the experimental data. For
                 the sack of the simplicity, the combination of the CPMS
                 model and genetic programming was employed to generate
                 analytical closed-form correlation. In this regards, a
                 comprehensive data bank of results of the CPMS was
                 constructed and exported to the GP tool and analytical
                 expressions of the power, efficiency, and polytropic
                 indexes were obtained. It was shown that the analytical
                 correlations not only had the same accuracy as the CPMS
                 model, but also, it can be simply used without
                 difficulties of numerical models. The CPMS and its out
                 coming analytical expressions, predicted the power and
                 efficiency of the GPU-3 Stirling with +1.13percent and
                 +0.45 (as difference), respectively.",
  keywords =     "genetic algorithms, genetic programming, Closed-form
                 model, Comprehensive numerical model of Stirling
                 engines, CPMS model, Non-isothermal heat exchangers,
                 Polytropic model",
}

Genetic Programming entries for Mojtaba Babaelahi Hoseyn Sayyaadi

Citations