Improved Hybrid Method for the Generation of Ground Motions Compatible with the Multi-Damping Design Spectra

ABSTRACT

Spectra-compatible artificial ground motions are used extensively in the time history analysis of nuclear power plants. Owing to reasons such as the dense controlling frequency points and stringent requirements for the number of small response points, it is difficult for the conventional matching methods to generate artificial ground motions that are highly compatible with multi-damping design spectra. In this paper, to resolve the problems of high precision and robustness, an improved hybrid method for constructing a multi-parameter adjustment curve in the time domain is proposed. Different from artificial intelligence methods, the improved hybrid method is a deterministic iterative method that combines the advantages of the simulated annealing algorithm (SAA) and the time domain adjustment method. The SAA is used to determine the optimal weights of the corrective time histories of all the damping ratios at a specific frequency, which controls the influences of the corrective time histories on the response spectra. Subsequently, based on the optimal weights, the artificial ground motion is adjusted in the time domain to reduce the fitting error of all the damping ratios at a specific frequency. Moreover, the multi-damping design spectra matching problem of frequencies and damping ratios is simplified to a one-dimensional problem of frequencies using the SAA. Numerical examples are presented to demonstrate the versatility of the proposed improved hybrid method.

KEYWORDS:

• multi-damping design spectra
• simulated annealing algorithm
• nuclear power plant
• deterministic iterative method

Acknowledgments

The authors would like to acknowledge the financial supports of the National Natural Science Foundation of China (Grant No. 52178460), the Fundamental Research Funds for the Central Universities (Grant No. DUT20TD209).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [52178460]; the Fundamental Research Funds for the Central Universities [DUT20TD209].