Saran Srikanth Bodda

Automation in digital analysis solutions for nuclear design-construction integration using BIM-FEM interoperability

Sandhu, H. K., Ashe, W., Crowder, N., Gupta, A., Han, K., & Bodda, S. S. (2025, September 24). International Journal of Pressure Vessels and Piping.

Enhancing computational efficiency of Bayesian Inference by identifying the intensity measure range to update seismic fragility curves

Mahanta, M. J., Bodda, S. S., Gupta, A., & Ha, J.-G. (2025, May 30). Nuclear Engineering and Design.

False sensor-data detection strategy for post-hazard condition monitoring of nuclear systems using statistical approaches and long short-term memory

Sandhu, H. K., Lee, J., Bodda, S. S., Gupta, A., & Dinh, N. (2025, September 22). International Journal of Pressure Vessels and Piping, Vol. 219.

Physics-trained artificial intelligence framework to detect chloride induced degradation in concrete

Patel, P., Gupta, A., Bodda, S. S., & Sandhu, H. K. (2025, January 10). Journal of Infrastructure Intelligence and Resilience.

A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Sandhu, H. K., Bodda, S. S., Yan, E., Sabharwall, P., & Gupta, A. (2024, January 12). Mechanical Systems and Signal Processing.

Evaluation of Fault Tree Analysis Algorithms for Probabilistic Risk Assessment: A Systematic Comparative Study

Afshan, N., Bodda, S. S., Gupta, A., & Han, K. (2024, January 1). Lecture Notes in Civil Engineering.

A Future with Machine Learning: Review of Condition Assessment of Structures and Mechanical Systems in Nuclear Facilities

Sandhu, H. K., Bodda, S. S., & Gupta, A. (2023, March 10). Energies.

Computationally efficient approach for risk-informed decision making

Vaishanav, P., Bodda, S. S., & Gupta, A. (2023, November 30). Progress in Nuclear Energy.

Condition Monitoring of Nuclear Equipment-Piping Systems Subjected to Normal Operating Loads Using Deep Neural Networks

Sandhu, H. K., Bodda, S. S., Sauers, S., & Gupta, A. (2023, May 3). Journal of Pressure Vessel Technology.

Computer-Vision-Based Vibration Tracking Using a Digital Camera: A Sparse-Optical-Flow-Based Target Tracking Method

Nie, G.-Y., Bodda, S. S., Sandhu, H. K., Han, K., & Gupta, A. (2022, September 11). Sensors.

Digital Engineering for Integrated Modeling and Simulation for Building-Piping Systems Through Interoperability Solutions

Crowder, N., Lee, J., Gupta, A., Han, K., Bodda, S., & Ritter, C. (2022, May 12). Nuclear Science and Engineering.

Post-hazard condition assessment of nuclear piping-equipment systems: Novel approach to feature extraction and deep learning

Sandhu, H. K., Bodda, S. S., & Gupta, A. (2022, November 11). International Journal of Pressure Vessels and Piping.

A Methodological Approach to Update Ground Motion Prediction Models Using Bayesian Inference

Bodda, S. S., Keller, M., Gupta, A., & Senfaute, G. (2021, November 30). Pure and Applied Geophysics.

Application of Risk-Informed Validation Framework to a Flooding Scenario

Bodda, S. S., Gupta, A., & Sewell, R. T. (2021, July 27). ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part A Civil Engineering.

Modeling the behavior of reinforced concrete slabs subjected to impact

Patel, P., Bodda, S. S., & Gupta, A. (2021, October 28). Nuclear Engineering and Design.

Limitations of traditional tools for beyond design basis external hazard PRA

Vaishanav, P., Gupta, A., & Bodda, S. S. (2020, October 28). Nuclear Engineering and Design.

Risk informed validation framework for external flooding scenario

Bodda, S. S., Gupta, A., & Dinh, N. (2019, November 1). Nuclear Engineering and Design, Vol. 356.

Fragility of a Flood Defense Structure Subjected to Multi-Hazard Scenario

Bodda, S. S., Sandhu, H. K., & Gupta, A. (2016, June 26).