Full
Outline
To enhance the efficiency and accuracy of three‑dimensional finite element model updating for nuclear power valve piping systems and ensure the reliability of analysis results，a three‑dimensional finite element model updating technique based on an inverse response surface model is proposed. First，a radial basis function‑backpropagation neural network is employed to fit an inverse response surface model that directly maps the resonant frequencies，anti‑resonant frequencies，and structural parameters of the valve piping system. Then，the measured frequencies are used as inputs to solve for the correction parameters，addressing challenges such as the difficulty in modeling vibration control equations for the three‑dimensional finite element model，the uncertainty of results from intelligent optimization algorithms，and the inefficiency of iterative updating processes. The proposed method is validated using an actual valve piping system. The results demonstrate that after measuring the actual dynamic characteristics，the trained inverse response surface model can complete the three‑dimensional model updating within seconds. The maximum error between the calculated frequencies of the updated model and the measured frequencies is reduced from 15.43% to 3.53%.The proposed method can be applied in engineering practice to update the three‑dimensional finite element model of nuclear power valve piping systems using measured frequencies.
100
34
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
关闭全屏
No. 86 Xueyuan South Road, Haidian District, Beijing
010-62662699(Operation and Technical Support)
qkjq@cast.org.cn
Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House
