Journal of Experimental & Theoretical Artificial Intelligence · 2015 · 435 citations · 37 references
EngineeringMechanical EngineeringEnergy SystemsHeat TransferRenewable Energy SystemsHeat PumpsRenewable EnergySolar Energy SystemsSolar Thermal SystemsFuzzy Inference SystemsGround Source Heat PumpsGround-source Heat Pump SystemsHeat Exchanger PerformanceHeat Pump System ModelingHeat Pump SystemsNeural Network ModelingPump Performance Modeling
In this study, slinky (the slinky-loop configuration is also known as the coiled loop or spiral loop of flexible plastic pipe)type ground heat exchanger (GHE) was established for a solar-assisted ground source heat pump system. System modelling is performed with the data obtained from the experiment. Artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are used in modelling. The slinky pipes have been laid horizontally and vertically in a ditch. The system coefficient of performance (COPsys) and the heat pump coefficient of performance (COPhp) have been calculated as 2.88 and 3.55, respectively, at horizontal slinky-type GHE, while COPsys and COPhp were calculated as 2.34 and 2.91, respectively, at vertical slinky-type GHE. The obtained results showed that the ANFIS is more successful than that of ANN for forecasting performance of a solar ground source heat pump system.
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Experimental methods for engineers
Ann M. Anderson · Experimental Thermal and Fluid Science · 1994 · 3.4K citations
Public Health, Mechanical Engineering, Applied Mechanics +10