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Operational modal analysis for characterization of mechanical and thermal-hydraulic fluctuations in simulated neutron noise

机译:模拟中子噪声机械和热液压波动特征的操作模态分析

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To overcome these limitations, in this work, the Frequency Domain Decomposition (FDD) of the Operational Modal Analysis (OMA) is applied to the spectral characterization of the neutron noise.In the study of the neutron noise in KWU pre-Konvoi PWRs, the Hilbert Huang Transform and the widely-used Fourier analysis are employed to extract spectral characteristics. However, both techniques are limited in decomposing the signal in the same frequency range to distinguish the contributions from different phenomena, such as the thermal-hydraulic and the mechanical perturbations. In addition, it is difficult for these two techniques to gather and present all the results in a single plot that shows the response of the core as a whole. To overcome these limitations, in this work, the Frequency Domain Decomposition (FDD) of the Operational Modal Analysis (OMA) is applied to the spectral characterization of the neutron noise. The OMA is widely used in the study of the dynamic properties of systems and structures. The FDD was performed on a series of neutron noise signals from simulated scenarios based on the transient nodal code SIMULATE-3 K. The simulations considered different single-source fluctuations and their combinations. The methodology separates in the two first singular values and singular vectors the responses due to mechanical vibrations and thermal-hydraulic fluctuation in all the frequency range, which allows distinguishing the effects of different phenomena on the spectral characteristics at the same frequency range of the neutron noise. The good performance of OMA in the present study provides promising possibilities to infer characteristics of the input excitation from the neutron noise data in PWR. Finally, the methodology shows remarkable advantages in the compilation of the results which can be utilized for monitoring purposes.
机译:为了克服这些限制,在这项工作中,操作模态分析(OMA)的频域分解(FDD)应用于中子噪声的光谱表征。在KWU前Konvoi PWR的中子噪声研究中, Hilbert Huang变换和广泛使用的傅立叶分析用于提取光谱特性。然而,这两种技术都受到限制,用于将信号分解在相同的频率范围内,以区分不同现象的贡献,例如热液压和机械扰动。此外,这两种技术难以收集并在单个图中收集并展示所有结果,该曲线显示整个核心的响应。为了克服这些限制,在这项工作中,操作模态分析(OMA)的频域分解(FDD)被应用于中子噪声的光谱表征。 OMA广泛用于研究系统和结构的动态性质。基于瞬态节点代码模拟-3k,在来自模拟场景的一系列中子噪声信号上进行FDD。模拟被认为是不同的单源波动及其组合。该方法在两个第一奇异值和奇异载体中分开了由于机械振动和所有频率范围内的热液压波动的响应,这允许区分不同现象对中子噪声相同频率范围的光谱特性的影响。本研究中OMA的良好性能提供了有希望的可能性,可以从PWR中从中子噪声数据推断出输入激励的特征。最后,该方法在可以用于监测目的的结果的汇编中表现出显着的优点。

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