Dataset and ANN model prediction of performance of graphene nanolubricant with R600a in domestic refrigerator system.

ABSTRACT: This work evaluated the steady state performance of R600a in the base lubricant and graphene nanolubricant. The measuring instruments required and their uncertainties were provided, step by step method and procedures for preparation of graphene nanolubricant concentration and substituting it with the base lubricant in domestic refrigerator system are described. The system temperatures data was captured at the inlet and outlet of the system components. Also, the pressures data was recorded at the compressor inlet and outlet. The data was recorded for 3 h at 30 min interval at an ambient temperature of 27 °C. The experimental dataset, Artificial Neural Network (ANN) training and testing dataset are provided. The artificial intelligence approach of ANN model to predict the performance of grap

SUBMITTER: Babarinde TO 

PROVIDER: S-EPMC7451762 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature