The flow in a liquid falling film is predominantly laminar,and the liquid-side mass transfer is limited by molecular diffusion.The effective way to enhance the mass transfer is to improve the liquid film flow behavior...The flow in a liquid falling film is predominantly laminar,and the liquid-side mass transfer is limited by molecular diffusion.The effective way to enhance the mass transfer is to improve the liquid film flow behavior.The falling film behaviors of water,ethanol and ethylene glycol in nine different wavy microchannels were simulated by Computational Fluid Dynamics.The simulation results show that the falling film thickness exhibits a waveform distribution resulting in a resonance phenomenon along the wavy microchannel.The fluctuation of liquid film surface increases the gas-liquid interface area,and the internal eddy flow inside the liquid film also improves the turbulence of liquid film,the gas-liquid mass transfer in falling film microchannels is intensified.Compared with flat microchannel,the CO_(2) absorption efficiency in water in the wavy microchannel is improved over 41%.Prediction models of liquid film amplitude and average liquid film thickness were established respectively.展开更多
In this paper,the multi-objective optimization of wavy microchannel heat sinks is performed by combining numerical calculation,prediction algorithm and genetic algorithm.In numerical calculation,the fluid-solid conjug...In this paper,the multi-objective optimization of wavy microchannel heat sinks is performed by combining numerical calculation,prediction algorithm and genetic algorithm.In numerical calculation,the fluid-solid conjugate heat transfer of heat sinks with different parameters are simulated in Fluent.On this basis,the vari-able parameters and objective parameters are used to complete the training of neural network model,which aims to achieve accurate prediction of objective parameters.Finally,the multi-objective genetic algorithm is applied to find the Pareto front according to different requirements on the foundation of the prediction model.Results show that the coefficient of determination of the neural network models are all greater than 0.85,which proves that the prediction model has a high accuracy.The Pareto fronts are obtained by non-dominated sorting genetic algorithm(NSGA-II)with different objective parameters and they reveal that the channel with the optimal performance corresponds to a larger channel width or Reynolds number.In addition,it is also found the dimensionless temperature difference is correlated with Nusselt number.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.21576168)。
文摘The flow in a liquid falling film is predominantly laminar,and the liquid-side mass transfer is limited by molecular diffusion.The effective way to enhance the mass transfer is to improve the liquid film flow behavior.The falling film behaviors of water,ethanol and ethylene glycol in nine different wavy microchannels were simulated by Computational Fluid Dynamics.The simulation results show that the falling film thickness exhibits a waveform distribution resulting in a resonance phenomenon along the wavy microchannel.The fluctuation of liquid film surface increases the gas-liquid interface area,and the internal eddy flow inside the liquid film also improves the turbulence of liquid film,the gas-liquid mass transfer in falling film microchannels is intensified.Compared with flat microchannel,the CO_(2) absorption efficiency in water in the wavy microchannel is improved over 41%.Prediction models of liquid film amplitude and average liquid film thickness were established respectively.
文摘In this paper,the multi-objective optimization of wavy microchannel heat sinks is performed by combining numerical calculation,prediction algorithm and genetic algorithm.In numerical calculation,the fluid-solid conjugate heat transfer of heat sinks with different parameters are simulated in Fluent.On this basis,the vari-able parameters and objective parameters are used to complete the training of neural network model,which aims to achieve accurate prediction of objective parameters.Finally,the multi-objective genetic algorithm is applied to find the Pareto front according to different requirements on the foundation of the prediction model.Results show that the coefficient of determination of the neural network models are all greater than 0.85,which proves that the prediction model has a high accuracy.The Pareto fronts are obtained by non-dominated sorting genetic algorithm(NSGA-II)with different objective parameters and they reveal that the channel with the optimal performance corresponds to a larger channel width or Reynolds number.In addition,it is also found the dimensionless temperature difference is correlated with Nusselt number.
