The rod ejection accident (REA) is the design-basis reactivity initiated event and an important aspect for a pressurized water reactor (PWR). The consequence of REA is that it introduces a large positive reactivity insertion in a core, which leads to a fast large power excursion and other parameters changing. Thus, it is important to understand the uncertainty in the parameters of reactor core when REA happens. This paper applies support vector regression (SVR) to analyze accident scenarios with control rod ejection. SVR is an approach based on machine learning and soft computing. SVR, by definition, is an application of support vector machine (SVM) to nonlinear regression problem. Furthermore, the objective of this paper is to train SVR model to identify both safe and potentially unsafe power plant conditions based on real time plant data. The data is obtained from computer generated accident scenarios and is divided into two datasets, training datasets and test datasets. The training dataset are used to train the SVR model and the test dataset are used to test the validation of this model. And then the results obtained by SVR model are compared with that of artificial neural network (ANN) model. The comparison results show that SVR model has superior performance over ANN model and agree well with the general understanding. Because the proposed methodology achieve accurate results, it is likely to be suitable for other data processing of nuclear engineering.
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2012 20th International Conference on Nuclear Engineering and the ASME 2012 Power Conference
July 30–August 3, 2012
Anaheim, California, USA
Conference Sponsors:
- Nuclear Engineering Division
- Power Division
ISBN:
978-0-7918-4499-1
PROCEEDINGS PAPER
On the Use of Support Vector Regression Technique for the Analysis of Rod Ejection Accidents Available to Purchase
Botao Jiang,
Botao Jiang
Xi’an Jiaotong University, Xi’an, Shaanxi, China
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Yang Liu,
Yang Liu
Xi’an Jiaotong University, Xi’an, Shaanxi, China
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Fuyu Zhao
Fuyu Zhao
Xi’an Jiaotong University, Xi’an, Shaanxi, China
Search for other works by this author on:
Botao Jiang
Xi’an Jiaotong University, Xi’an, Shaanxi, China
Yang Liu
Xi’an Jiaotong University, Xi’an, Shaanxi, China
Fuyu Zhao
Xi’an Jiaotong University, Xi’an, Shaanxi, China
Paper No:
ICONE20-POWER2012-54266, pp. 99-102; 4 pages
Published Online:
October 30, 2013
Citation
Jiang, B, Liu, Y, & Zhao, F. "On the Use of Support Vector Regression Technique for the Analysis of Rod Ejection Accidents." Proceedings of the 2012 20th International Conference on Nuclear Engineering and the ASME 2012 Power Conference. Volume 5: Fusion Engineering; Student Paper Competition; Design Basis and Beyond Design Basis Events; Simple and Combined Cycles. Anaheim, California, USA. July 30–August 3, 2012. pp. 99-102. ASME. https://doi.org/10.1115/ICONE20-POWER2012-54266
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