首页> 外文会议>14th International Conference on Nuclear Engineering 2006(ICONE14) vol.1 >NON INVASIVE WATER LEVEL MONITORING ON BOILING WATER REACTORS USING INTERNAL GAMMA RADIATION - APPLICATION OF SOFT COMPUTING METHODS
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NON INVASIVE WATER LEVEL MONITORING ON BOILING WATER REACTORS USING INTERNAL GAMMA RADIATION - APPLICATION OF SOFT COMPUTING METHODS

机译:内部伽玛辐射对沸腾水反应器的无侵入水位监测-软计算方法的应用

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To provide best knowledge about safety-related water level values in boiling water reactors (BWR) is essentially for operational regime. For the water level determination hydrostatic level measurement systems are almost exclusively applied, because they stand the test over many decades in conventional and nuclear power plants (NPP). Due to the steam generation especially in BWR a specific phenomenon occurs which leads to a water-steam mixture level in the reactor annular space and reactor plenum. The mixture level is a high transient non-measurable value concerning the hydrostatic water level measuring system and it significantly differs from the measured collapsed water level. In particular, during operational and accidental transient processes like fast negative pressure transients, the monitoring of these water levels is very important. In addition to the hydrostatic water level measurement system a diverse water level measurement system for BWR should be used. A real physical diversity is given by gamma radiation distribution inside and outside the reactor pressure vessel correlating with the water level. The vertical gamma radiation distribution depends on the water level, but it is also a function of the neutron flux and the coolant recirculation pump speed. For the water level monitoring, special algorithms are required. An analytical determination of the gamma radiation distribution outside the reactor pressure vessel is impossible due to the multitude of radiation of physical processes, complicated non-stationary radiation source distribution and complex geometry of fixtures. For creating suited algorithms Soft Computing methods (Fuzzy Sets Theory, Artificial Neural Networks, etc.) will be used. Therefore, arndatabase containing input values (gamma radiation distribution) and output values (water levels) had to be built. Here, the database was established by experiments (data from BWR and from a test setup) and simulation with the authorised thermofluid code ATHLET.
机译:要提供有关沸水反应堆(BWR)中与安全相关的水位值的最佳知识,本质上是针对运行方案。在静水位测量系统中,几乎只能使用静水位测量系统,因为它们在常规和核电厂(NPP)中经受了数十年的考验。由于蒸汽的产生,特别是在BWR中,会发生一种特殊的现象,从而导致反应堆环形空间和反应堆气室中水蒸汽混合物的液位升高。混合液位是有关静水位测量系统的高瞬态不可测量值,它与测得的塌陷水位明显不同。尤其是在操作和意外过渡过程(例如快速负压过渡)中,这些水位的监控非常重要。除静水水位测量系统外,还应使用BWR的多种水位测量系统。实际的物理多样性是由与水位相关的反应堆压力容器内部和外部的伽马辐射分布给出的。垂直伽马辐射分布取决于水位,但它也是中子通量和冷却剂再循环泵速度的函数。对于水位监控,需要特殊的算法。由于多种物理过程的辐射,复杂的非平稳辐射源分布以及固定装置的复杂几何形状,因此无法对反应堆压力容器外部的伽马辐射分布进行分析确定。为了创建合适的算法,将使用软计算方法(模糊集理论,人工神经网络等)。因此,必须建立包含输入值(伽马辐射分布)和输出值(水位)的arndatabase。在这里,数据库是通过实验(来自BWR和测试设置的数据)和授权热流体代码ATHLET进行仿真而建立的。

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