Saran Srikanth Bodda
Bio
https://ccee.ncsu.edu/cnefs/saranbodda/
Publications
- Automation in digital analysis solutions for nuclear design-construction integration using BIM-FEM interoperability , International Journal of Pressure Vessels and Piping (2025)
- Enhancing computational efficiency of Bayesian Inference by identifying the intensity measure range to update seismic fragility curves , Nuclear Engineering and Design (2025)
- False sensor-data detection strategy for post-hazard condition monitoring of nuclear systems using statistical approaches and long short-term memory , International Journal of Pressure Vessels and Piping (2025)
- Physics-trained artificial intelligence framework to detect chloride induced degradation in concrete , Journal of Infrastructure Intelligence and Resilience (2025)
- A comparative study on deep learning models for condition monitoring of advanced reactor piping systems , Mechanical Systems and Signal Processing (2024)
- Evaluation of Fault Tree Analysis Algorithms for Probabilistic Risk Assessment: A Systematic Comparative Study , Lecture notes in civil engineering (2024)
- A Future with Machine Learning: Review of Condition Assessment of Structures and Mechanical Systems in Nuclear Facilities , Energies (2023)
- Computationally efficient approach for risk-informed decision making , Progress in Nuclear Energy (2023)
- Condition Monitoring of Nuclear Equipment-Piping Systems Subjected to Normal Operating Loads Using Deep Neural Networks , Journal of Pressure Vessel Technology (2023)
- Computer-Vision-Based Vibration Tracking Using a Digital Camera: A Sparse-Optical-Flow-Based Target Tracking Method , Sensors (2022)
Grants
There have been and will continue to be rapid advances in 3D scanning and augmented/virtual reality technologies to improve construction costs and schedules, especially in the nuclear energy industry that has suffered from construction cost escalation and delays. A key challenge faced in the implementation of these modern technologies relates to changes needed in the regulatory practice and approvals. It is vital for regulatory agencies like USNRC to understand the fundamental basis of these technologies and characterize the accuracy and consistency in them. This project is aimed at conducting the research needed to support this effort which would eventually be needed in the near future. More specifically, it is proposed to: (i) characterize technical specifications and the associated parameters that govern the accuracy of virtual inspections, and (ii) identify items at a construction or manufacturing site that are conducive to virtual inspections and the items that are not.