Center for Nuclear Energy Facilities and Structures - 2024

Akins, A., Furlong, A., Kohler, L., Clifford, J., Brady, C., Alsafadi, F., & Wu, X. (2024). ARTISANS—Artificial Intelligence for Simulation of Advanced Nuclear Systems for Nuclear Fission Technology. Nuclear Engineering and Design. https://doi.org/10.1016/j.nucengdes.2024.113170

Sandhu, H. K., Bodda, S. S., Yan, E., Sabharwall, P., & Gupta, A. (2024, March 1). A comparative study on deep learning models for condition monitoring of advanced reactor piping systems. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, Vol. 209. https://doi.org/10.1016/j.ymssp.2023.111091

Wang, L., Lee, J., Nimawat, J., Han, K., & Gupta, A. (2024). Integrated 4D Design Change Management Model for Construction Projects. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT, 150(5). https://doi.org/10.1061/JCEMD4.COENG-14246

Lee, D., Nie, G.-Y., & Han, K. (2024). Automatic and Real-Time Joint Tracking and Three-Dimensional Scanning for a Construction Welding Robot. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT, 150(3). https://doi.org/10.1061/JCEMD4.COENG-14135

Xie, Z., Yaseen, M., & Wu, X. (2024). Functional PCA and deep neural networks-based Bayesian inverse uncertainty quantification with transient experimental data. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 420. https://doi.org/10.1016/j.cma.2023.116721

Vaishanav, P., Bodda, S. S., & Gupta, A. (2024). Computationally efficient approach for risk-informed decision making. PROGRESS IN NUCLEAR ENERGY, 167. https://doi.org/10.1016/j.pnucene.2023.104983