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Study On Heat Transfer Characteristics Of Mixed Flow In Tee Junctions

Posted on:2020-07-26Degree:MasterType:Thesis
Country:ChinaCandidate:Z W LiFull Text:PDF
GTID:2392330590972159Subject:Machine and Environmental Engineering
Abstract/Summary:PDF Full Text Request
Nuclear power technology brings the dawn of resolving the energy crisis in the world,but also has great potential danger.The damage of thermal pipeline is one of the important reasons leading to nuclear power accidents.During the shutdown period of nuclear power plant,the mixing of lowtemperature water from the waste heat removal system(RRA)and high-temperature water from the reactor coolant system(RCP)occurs in the tee junctions.The downstream pipe wall of the tee junctions bears periodic temperature fluctuation,which makes the pipeline bear alternating thermal stress load,and eventually causes the thermal fatigue cracking of the pipeline.The study of the mixing characteristics of the tee junctions has great significance for the safe operation of the nuclear power pipeline.Significance.In this paper,the concrete work on the mixing process of cold and hot in tee junctions is as follows:(1)The thermal-hydraulic test bench was built to study the mixing process of tee junctions under different inlet temperature difference,flow ratio/velocity ratio.The temperature field data near the wall of tee junctions were recorded by thermocouple,and the temperature field data were processed.The temperature difference and temperature gradient distribution near the wall were obtained.(2)Embedded large eddy simulation method is used to simulate the mixing process in the threeway pipe.The flow field and temperature field characteristics of the whole mixing area downstream of the three-way pipe are further studied.The development process of mixing with time and the influence of flow ratio and import temperature difference on the mixing process are clarified.(3)Based on BP neural network algorithm,a temperature prediction model is trained with the temperature field data obtained from experiments,and the accuracy of the prediction model is verified by individual experimental data.The model can predict the temperature field near the wall of the tee pipe in the mixing process,which provides support for further calculation of the thermal stress of the pipeline and evaluation of the life of the pipeline.
Keywords/Search Tags:Tee junctions, Thermal mixing, ELES, Temperature oscillation, BP neural network, Temperature field prediction
PDF Full Text Request
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