Andy Rivas

A System Predictive Maintenance Framework for Advanced Reactors Using a Data-Driven Digital Twin

Rivas, A., Delipei, G. K., & Hou, J. (2024, August 2). Nuclear Science and Engineering, Vol. 8.

A component diagnostic and prognostic framework for pump bearings based on deep learning with data augmentation

Rivas, A., Delipei, G. K., Davis, I., Bhongale, S., Yang, J., & Hou, J. (2024, April 3). Reliability Engineering & System Safety, Vol. 247.

A system diagnostic and prognostic framework based on deep learning for advanced reactors

Rivas, A., Delipei, G. K., Davis, I., Bhongale, S., & Hou, J. (2024, February 13). Progress in Nuclear Energy, Vol. 170.

Modeling a generic Pebble Bed High-Temperature Gas-Cooled Reactor to perform load-following using Simulink

Rivas, A., Delipei, G. K., & Hou, J. (2024, August 5). Nuclear Engineering and Design, Vol. 428.

Operation Optimization Framework for Advanced Reactors Using a Data-Driven Digital Twin

Rivas, A., Delipei, G. K., & Hou, J. (2024, October 4). Journal of Nuclear Engineering and Radiation Science, Vol. 4.

Reinforcement Learning-Based Control Sequence Optimization for Advanced Reactors

Nguyen, K. H. N., Rivas, A., Delipei, G. K., & Hou, J. (2024, July 1). Journal of Nuclear Engineering, Vol. 5, pp. 209–225.

Nuclear data uncertainty propagation applied to the versatile test reactor conceptual design

Rivas, A., Martin, N. P., Bays, S. E., Palmiotti, G., Xu, Z., & Hou, J. (2022, April 14). Nuclear Engineering and Design, Vol. 392, p. 111744.

Predictions of component Remaining Useful Lifetime Using Bayesian Neural Network

Rivas, A., Delipei, G. K., & Hou, J. (2022, February 21). Progress in Nuclear Energy, Vol. 146, p. 104143.

Propagating neutronic uncertainties for FFTF LOFWOS Test #13

Rivas, A., Stauff, N., Sumner, T., & Hou, J. (2021, February 26). Nuclear Engineering and Design, Vol. 375, p. 111047.