Accurate prediction of thermal conductivity of supercritical propane using LSSVM

Recently supercritical fluids have found impressive applications in different industries. According to this, researchers have been interested to study thermophysical properties of supercritical fluids. Due to high price and time consuming process of experiments related to supercritical condition, the attention to computational study were increased. In present contribution, a new LSSVM-GA model were proposed to estimate the thermal conductivity of supercritical propane. The thermal conductivity data were extracted from open literature. By Applying LSSVM-GA on 380 data points and finding optimum parameters, the estimated values of thermal conductivity of supercritical propane were compared with experimental data and it was confirmed that the predictive modeling performed in acceptable manner based on reported errors and fitting parameters. Consequently, the model is reliable that can be utilized to forecast the thermal conductivity of supercritical propane.