A novel strip-coil-baffle structure used to enhance heat transfer and support the tube bundle for a tube-shell heat exchanger is proposed. The new structure can sleeve the tubes in bundle alternatively to create a vor...A novel strip-coil-baffle structure used to enhance heat transfer and support the tube bundle for a tube-shell heat exchanger is proposed. The new structure can sleeve the tubes in bundle alternatively to create a vortex flow in a heat exchanger. The numerical simulation on the flow and heat transfer characteristics for this new structure heat exchanger is conducted. The computational domain consists of two strip-coil sleeved tubes and two bare tubes oppositely placed at each comer of a square. The velocity and temperature fields in such strip-coil-baffled channel are simulated using FLUENT software. The effects of the strip-coil-baffles on heat transfer enhancement and flow resistance in relation to the Reynolds number are analyzed. The results show that this new structure bundle can enhance the heat transfer coefficient up to a range of 40% to 55% in comparison with a bare tube bundle; meanwhile, higher flow resistance is also accompanied. It is believe that the strip-coil- baffled heat exchanger should have promising applications in many industry fields.展开更多
Heat transfer mechanisms and their thermal performances need to be comprehensively studied in order to optimize efficiency and minimize energy losses.Different nanoparticles in the base fluid are investigated to upgra...Heat transfer mechanisms and their thermal performances need to be comprehensively studied in order to optimize efficiency and minimize energy losses.Different nanoparticles in the base fluid are investigated to upgrade the thermal performance of heat exchangers.In this numerical study,a finned shell and tube heat exchanger has been designed and different volume concentrations of nanofluid were tested to determine the effect of utilizing nanofluid on heat transfer.Fe_(2)O_(3)/water nanofluids with volume concentration of 1%,1.5% and 2% were utilized as heat transfer fluid in the heat exchanger and the obtained results were compared with pure water.ANSYS Fluent software as a CFD method was employed in order to simulate the mentioned problem.Numerical simulation results indicated the successful utilization of nanofluid in the heat exchanger.Also,increasing the ratio of Fe_(2)O_(3) nanoparticles caused more increment in thermal energy without important pressure drop.Moreover,it was revealed that the highest heat transfer rate enhancement of 19.1% can be obtained by using nanofluid Fe_(2)O_(3)/water with volume fraction of 2%.展开更多
This work used artificial neural network(ANN)to predict the heat transfer rates of shell-and-tube heatexchangers with segmental baffles or continuous helical baffles,based on limited experimental data.The BackPropagat...This work used artificial neural network(ANN)to predict the heat transfer rates of shell-and-tube heatexchangers with segmental baffles or continuous helical baffles,based on limited experimental data.The BackPropagation (BP) algorithm was used in training the networks.Different network configurations were alsostudied.The deviation between the predicted results and experimental data was less than 2%.Comparison withcorrelation for prediction shows ANN superiority.It is recommended that ANN can be easily used to predict theperformances of thermal systems in engineering applications,especially to model heat exchangers for heattransfer analysis.展开更多
基金The National Basic Research Program of China(973Program) (NoG2000026303)the National Natural Science Foun-dation of China (No50176008)
文摘A novel strip-coil-baffle structure used to enhance heat transfer and support the tube bundle for a tube-shell heat exchanger is proposed. The new structure can sleeve the tubes in bundle alternatively to create a vortex flow in a heat exchanger. The numerical simulation on the flow and heat transfer characteristics for this new structure heat exchanger is conducted. The computational domain consists of two strip-coil sleeved tubes and two bare tubes oppositely placed at each comer of a square. The velocity and temperature fields in such strip-coil-baffled channel are simulated using FLUENT software. The effects of the strip-coil-baffles on heat transfer enhancement and flow resistance in relation to the Reynolds number are analyzed. The results show that this new structure bundle can enhance the heat transfer coefficient up to a range of 40% to 55% in comparison with a bare tube bundle; meanwhile, higher flow resistance is also accompanied. It is believe that the strip-coil- baffled heat exchanger should have promising applications in many industry fields.
文摘Heat transfer mechanisms and their thermal performances need to be comprehensively studied in order to optimize efficiency and minimize energy losses.Different nanoparticles in the base fluid are investigated to upgrade the thermal performance of heat exchangers.In this numerical study,a finned shell and tube heat exchanger has been designed and different volume concentrations of nanofluid were tested to determine the effect of utilizing nanofluid on heat transfer.Fe_(2)O_(3)/water nanofluids with volume concentration of 1%,1.5% and 2% were utilized as heat transfer fluid in the heat exchanger and the obtained results were compared with pure water.ANSYS Fluent software as a CFD method was employed in order to simulate the mentioned problem.Numerical simulation results indicated the successful utilization of nanofluid in the heat exchanger.Also,increasing the ratio of Fe_(2)O_(3) nanoparticles caused more increment in thermal energy without important pressure drop.Moreover,it was revealed that the highest heat transfer rate enhancement of 19.1% can be obtained by using nanofluid Fe_(2)O_(3)/water with volume fraction of 2%.
文摘This work used artificial neural network(ANN)to predict the heat transfer rates of shell-and-tube heatexchangers with segmental baffles or continuous helical baffles,based on limited experimental data.The BackPropagation (BP) algorithm was used in training the networks.Different network configurations were alsostudied.The deviation between the predicted results and experimental data was less than 2%.Comparison withcorrelation for prediction shows ANN superiority.It is recommended that ANN can be easily used to predict theperformances of thermal systems in engineering applications,especially to model heat exchangers for heattransfer analysis.
