Machine learning-aided damage identification of mock-up spent nuclear fuel assemblies in a sealed dry storage canister

Zhuang, Bozhou; Arcaro, Anna; Gencturk, Bora; Ghanem, Roger

doi:10.1016/j.engappai.2023.107484

Cited by 9 publications

(1 citation statement)

References 37 publications

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“…The wavelength λ was determined to be twice the thickness of the canister wall, or 25.4 mm. Therefore, the desired excitation frequency was determined to be f = c steel / λ = (5,800 / 25.4) kHz= 228 kHz (2) where c steel is the longitudinal wave speed in steel (taken as 5,800 m/s). Therefore, the excitation frequency was taken as 225 kHz.…”

Section: Optimization Of Excitation Frequencymentioning

confidence: 99%

Optimizing transmission of acoustic signals to monitor internal conditions of canisters for dry storage of commercial spent nuclear fuel

Zhuang,

Sinkov,

Good

et al. 2024

Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2024

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Safe storage of spent nuclear fuel (SNF) is critical to the nuclear fuel cycle and the future of nuclear energy. In the United States, SNF is primarily stored via two methods regulated by the U.S. Nuclear Regulatory Commission (U.S. NRC): wet storage in SNF pools, and dry storage in dry cask storage systems (DCSSs). After about five years of cooling in spent fuel pools, the fuel assemblies are transferred into DCSSs, and the systems are filled with helium and sealed by welding. Deterioration of conditions inside of a DCSS will be reflected by changes in the internal gas properties which motivates the development of acoustic techniques to monitor internal gas properties, over extended storage periods, using sensors mounted on the exterior of the storage packages. However, a major challenge in collecting acoustic signals is the impedance mismatch between the steel canister shell and the gas. Only a small fraction of the ultrasonic signal can be transmitted through the gas medium. In this paper, experimental studies on a full-scale canister mock-up were conducted to capture the gas-borne signals. Damping materials were pasted on the outside and blocking and unblocking tests were conducted to identify the gas-borne signal. The results showed that the excitation frequency plays an important role in maximizing the gas-borne signal. The gas-borne signal was successfully detected at around the theoretical timeof-flight (TOF). A high signal-to-noise ratio (SNR) was achieved in the measurements. Next, the acoustic impedance matching (AIM) layers were introduced, and the gas signal was drastically improved compared with no AIM layers.

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Section: Optimization Of Excitation Frequencymentioning

confidence: 99%