The flow resistance characteristics of supercritical carbon dioxide(S-CO_2) are still unclear

and the generalization ability of existing resistance prediction formula is poor. The resistance characteristics of S-CO_2turbulent flow in a vertically ascending smooth circular tube were experimentally studied

and the effects of mass flow rate

pressure and heat flux on friction resistance of S-CO_2 were systematically analyzed. The experimental parameters' range are: 750～2 200 kg/(m2·s) of mass flow rate

10～20 MPa of fluid pressure

200～340 kW/m2 of heat flux and 60～500 ℃ of bulk temperature(away from the pseudo critical point). The experimental results show that

the friction resistance of S-CO_2 decreases with the increase of heat flux

which is beneficial to the engineering application of S-CO_2 power generation. The flow friction resistance of S-CO_2 decreases with the increase of pressure

which is mainly because the fluid density increases with the pressure. Furthermore

a Bayesianregularization BP neural network model was established to predict the flow friction resistance of S-CO_2 effectively.The correlation coefficient R between the predicted values and the experimental values is 0.998 6

and more than 98% of the predicted values are within the error range of 10%

indicating that the model has good generalization ability and high fitting accuracy.