Resilient design in nuclear energy: Critical lessons from a cross-disciplinary analysis of the Fukushima Dai-ichi nuclear accident

Ayoub, Ali; Wainwright, Haruko M.; Sansavini, Giovanni; Gauntt, Randall; Saito, Kimiaki

doi:10.1016/j.isci.2024.109485

iScience

2024

DOI: 10.1016/j.isci.2024.109485

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Resilient design in nuclear energy: Critical lessons from a cross-disciplinary analysis of the Fukushima Dai-ichi nuclear accident

Ali Ayoub,

Haruko M. Wainwright,

Giovanni Sansavini

et al.

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Cited by 2 publications

References 68 publications

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An enhanced fourier neural operator surrogate for radioactive plume transport forecasting

Ayoub,

Wainwright,

Wang

et al. 2024

Stoch Environ Res Risk Assess

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Accurate real-time forecasts of atmospheric plume behavior are crucial for effective management of environmental release incidents. However, the computational demands of weather simulations and particle transport codes limit their applicability during emergencies. In this study, we employ a U-Net enhanced Fourier Neural Operator (U-FNO) to statistically emulate the calculations of the WSPEEDI dose forecasting numerical simulator, using pre-calculated ensemble simulations. The developed emulator is capable of effectively simulating any radioactive-release scenario and generating the time series of dose distribution in the environment 4000 times faster than the numerical simulator, while still maintaining high accuracy. It predicts the plume direction, extent, and dose-rate magnitudes using initial- and boundary-condition meteorological data as input. The speed and efficiency of this framework offers a powerful tool for swift decision-making during emergencies, facilitating risk-informed protective actions, evacuation execution, and zone delineation. Its application extends to various contaminant release and transport problems, and can be instrumental in engineering tasks requiring uncertainty quantification (UQ) for environmental risk assessment.

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An enhanced fourier neural operator surrogate for radioactive plume transport forecasting

Ayoub,

Wainwright,

Wang

et al. 2024

Stoch Environ Res Risk Assess

View full text Add to dashboard Cite

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Machine learning-enabled weather forecasting for real-time radioactive transport and contamination prediction

Ayoub,

Wainwright,

Sansavini

2024

Progress in Nuclear Energy

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Resilient design in nuclear energy: Critical lessons from a cross-disciplinary analysis of the Fukushima Dai-ichi nuclear accident

Cited by 2 publications

References 68 publications

An enhanced fourier neural operator surrogate for radioactive plume transport forecasting

An enhanced fourier neural operator surrogate for radioactive plume transport forecasting

Machine learning-enabled weather forecasting for real-time radioactive transport and contamination prediction

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