共查询到4条相似文献,搜索用时 15 毫秒
1.
压水堆核电厂在严重事故下将发生堆芯熔化事故而形成熔融池。形成熔融池的过程具有很大的不确定性,这影响到反应堆压力容器熔融物堆内滞留(IVR)策略的有效性。本工作以AP1000核电厂两层IVR模型为研究对象,对成功实施反应堆压力容器外部冷却(ERVC)的假想严重事故进行了熔融池参数不确定性分析,包括参数的敏感性分析和使用拉丁超立方抽样的概率分析。结果表明:衰变功率对IVR评价参数影响最大,应采取措施(如上堆腔注水)尽量延缓堆芯熔化的时间;熔融物中不锈钢的质量将对金属层参数造成较大影响,可考虑在压力容器内布置牺牲性材料来减小金属层的集热效应;氧化物层外压力容器失效的概率仅为1.2%,但金属层外压力容器失效的概率高达20%。本结果对今后IVR策略研究和设计具有一定的指导意义,同时也为压水堆核电厂安全评审提供理论支持。 相似文献
2.
严重事故下一回路管道可能会发生蠕变失效,若出现蠕变诱发的蒸汽发生器传热管破裂(SGTR),则会导致安全壳旁路失效;若出现蠕变诱发热段或波动管的失效,则产生的破口将会使一回路迅速卸压。因此,评估严重事故下蠕变诱发反应堆冷却剂系统(RCS)破裂的可能性是开展严重事故分析、特别是二级概率安全分析(PSA)的重要基础。本工作基于蠕变失效模型,考虑传热管的缺陷,建立了评价蠕变诱发RCS破裂的确定论模型。在此基础上,运用拉丁超立方体抽样方法,考虑重要参数的不确定性,开发了严重事故下蠕变诱发RCS破裂的概率评估程序。随后对典型的事故序列进行了蠕变诱发RCS破裂的概率评估。结果表明,对于高压事故序列,存在一定的蠕变诱发SGTR概率,也存在较高的蠕变诱发热段或波动管失效概率。 相似文献
3.
Masaki Matsushita Tomohiro Endo Akio Yamamoto 《Journal of Nuclear Science and Technology》2020,57(5):573-589
ABSTRACTSevere accident codes (e.g. MAAP, RELAP, and MELCORE) model various physical phenomena during severe accidents. Many analyses using these codes for safety margin evaluation are impractical due to large computational costs. Surrogate models have an advantage of quickly reproducing multiple results with a low computational cost. In this study, we apply the singular value decomposition to the time-series results of a severe accident code to develop a reduced order modeling (ROM). Using the ROM, the probabilistic safety margin analysis for the station blackout with a total loss of feedwater capabilities at a boiling water reactor is carried out. The dominant parameters to the accident progression are assumed to be the down-time and the recovery-time of the reactor core isolation cooling system, and decay heat. To reduce the number of RELAP5/SCDAPSIM analyses while maintaining the prediction accuracy of ROM, we develop a data sampling method based on adaptive sampling, which selects the new sampling data based on the dissimilarity with the existing training data for ROM. Our ROM can rapidly reproduce the time-series results and can estimate core conditions. By reproducing multiple results by ROM, a time-dependent core damage probability distribution is calculated instead of the direct use of RELAP5/SCDAPSIM. 相似文献
4.
Advanced nuclear water reactors rely on containment behaviour in realization of some of their passive safety functions. Steam condensation on containment walls, where non-condensable gas effects are significant, is an important feature of the new passive containment concepts, like the AP600/1000 ones.In this work the international reactor innovative and secure (IRIS) was taken as reference, and the relevant condensation phenomena involved within its containment were investigated with different computational tools. In particular, IRIS containment response to a small break LOCA (SBLOCA) was calculated with GOTHIC and RELAP5 codes. A simplified model of IRIS containment drywell was implemented with RELAP5 according to a sliced approach, based on the two-pipe-with-junction concept, while it was addressed with GOTHIC using several modelling options, regarding both heat transfer correlations and volume and thermal structure nodalization. The influence on containment behaviour prediction was investigated in terms of drywell temperature and pressure response, heat transfer coefficient (HTC) and steam volume fraction distribution, and internal recirculating mass flow rate. The objective of the paper is to preliminarily compare the capability of the two codes in modelling of the same postulated accident, thus to check the results obtained with RELAP5, when applied in a situation not covered by its validation matrix (comprising SBLOCA and to some extent LBLOCA transients, but not explicitly the modelling of large dry containment volumes).The option to include or not droplets in fluid mass flow discharged to the containment was the most influencing parameter for GOTHIC simulations. Despite some drawbacks, due, e.g. to a marked overestimation of internal natural recirculation, RELAP5 confirmed its capability to satisfactorily model the basic processes in IRIS containment following SBLOCA. 相似文献