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NHR200-Ⅱ卧式蒸汽发生器的比例缩放试验设计

Scaling Experimental Design of Horizontal Steam Generator in NHR200-II
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摘要 为拓宽200 MW低温核供热堆(NHR200-Ⅱ)的应用范围和提高其经济性,重新对其中间回路进行设计,并提出包含卧式蒸汽发生器(HSG)在内的新型过热蒸汽供应系统。因原型尺度的验证试验成本高、周期长,故采用多级双层比例分析(H2TS)方法对HSG内的两相自然循环开展比例模化分析研究,并通过理论推导给出了在等物性条件下的比例分析准则和不同比例条件下的比例数值。原型和模型均选用水作为试验工质,再结合RELAP5程序对原型和模型进行仿真建模。仿真计算结果表明模型和原型的关键参数比例关系符合理论推导结果。综合考虑试验经济性、准确性、安全性等因素,最终确定模型和原型的长度比例为1∶4作为后续验证试验的长度比值,对应的功率比为1∶96。 To broaden the application range and improve the economic feasibility of 200 MW Low-Temperature Nuclear Heating Reactor(NHR200-Ⅱ),a redesign of its intermediate loop has been proposed,including a new superheated steam supply system that incorporates horizontal steam generators(HSG).Due to the high cost and long period of prototype scale verification tests,a scaling modeling analysis of the two-phase natural circulation within the HSG was employed using the Hierarchical Two Tiered Scaling(H2TS)method.Theoretical derivations provided scaling analysis criteria under isothermal conditions and scaling numerical values under various scaling conditions.Both the prototype and the model employed water as the test fluid,and numerical modeling of the prototype and the model was conducted by using the RELAP5 code.The numerical calculations indicated that the key parameters’proportional relationships between the model and the prototype were consistent with the theoretically derived results.Considering factors such as test economy,accuracy,and safety,a 1:4 scale model-to-prototype length ratio was ultimately selected as the scaling factor for subsequent verification tests,corresponding to a power ratio of 1:96.
作者 李宗洋 郝文涛 张文文 李卫华 杨星团 Li Zongyang;Hao Wentao;Zhang Wenwen;Li Weihua;Yang Xingtuan(Institute of Nuclear and New Energy Technology,Tsinghua University,Beijing,100084,China)
出处 《核动力工程》 EI CAS CSCD 北大核心 2024年第5期136-141,共6页 Nuclear Power Engineering
基金 中国博士后科学基金第74批面上资助(2023M741913)。
关键词 200 MW低温核供热堆(NHR200-Ⅱ) 卧式蒸汽发生器(HSG) 比例分析 仿真 200 MW Low-Temperature Nuclear Heating Reactor(NHR200-Ⅱ) Horizontal steam generator(HSG) Scaling analysis Simulation
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