Study On Experiment And Optimization Theory Of Sub-Atmosphere Heat Exchanger In He ? System

With the development of cryogenic engineering technology,He ? systems are increasingly used in scientific research and engineering,and play an important role in high-energy particle physics,nuclear science and technology and other fields.Sub-atmosphere heat exchanger is used to transfer cooling capacity between sub-atmosphere helium vapor and liquid helium in He ? system.As a key equipment of the He ? system,its heat transfer and pressure drop performance have important impact on the overall capacity of the He ? system.The working fluids of the sub-atmosphere heat exchanger have small heat transfer temperature differences,low working temperatures,and are in sub-atmosphere working conditions.However,there are higher requirements on its heat transfer and pressure drop performance in the cryogenic system.Because of this contradiction,it is very important to carry out the precise design and optimization of the sub-atmosphere heat exchanger.This article focuses on the performance test and optimization theory of sub-atmosphere heat exchangers.The main research works of this article are shown as follows:Design and build an experiment platform for the test of atmosphere heat exchanger of He ? system.The process design of the experiment platform was based on the principle of He ? system.According to the special requirements of the He ? system,the thermal insulation scheme,structure,measurement and control system of the experimental platform were designed to meet the requirements of low heat leakage and high measurement accuracy.The structure and experiment process of the experiment platform were optimized according to the thermoacoustic oscillation and gas block phenomenon in the operation.The results show that the experiment platform can achieve the performance test of the heat exchanger under the condition of the limit flowrate less than 1.5 g/s and the limit pressure less than 3000 Pa.The temperature measurement accuracy under the test condition is less than 2%,and the heat leakage of helium tanks are less than 1 W.The experiment researches were conducted on the new-type finned tube heat exchanger and plate-fin heat exchanger.The heat transfer model of the heat exchanger was established by the thermal resistance analysis method,and the calculation model was simplified.The experiment researches were carried out based on the low temperature experiment platform of the sub-atmosphere heat exchanger.According to the experiment results,the experiment correlations of Colburn factor j and Fanning friction factor f of different heat exchangers were established.The distributed parameter differential element method was used to establish the heat exchanger calculation model.The spiral tube heat exchanger was taken as the research object,and the heat exchanger calculation model was established and solved by the distributed parameter differential element method.The experiment results were compared with the calculation results to verify the calculation method.The optimization methods and optimization variables of sub-atmosphere heat exchanger were studied.Taken the cross-flow plate-fin heat exchanger as the object in the research,the modified entropy generation number and the entransy dissipation number were used as the optimization objective function.The single-objective optimization genetic algorithm SEGA and the multi-objective optimization genetic algorithm NSGA II were used to optimize the heat exchanger.Through the comparison of the results,the influence of different objective functions on the optimization results of the heat exchanger was obtained.On this basis,the distribution parameter differential element method was combined with NSGA II for the first time.Taking the modified entropy generation number as the objective function,the sub-atmosphere plate-fin heat exchanger was optimized.According to different initial parameters,the different temperature fields of the plate-fin heat exchanger were obtained through multiple iterations.After obtaining the Pareto solution by the multi-objective genetic algorithm,the optimal solution was obtained through the TOPSIS strategy.