Radiation-Induced Degradation and Service Life Prediction of Nuclear Concrete Infrastructure

Abstract:  

We are currently living the second nuclear energy renaissance, marked by a rapid expansion in reactor construction and the development of diverse reactor technologies. Civil infrastructure plays a critical role in ensuring public safety, structural integrity, and overall capital cost efficiency. Accordingly, a clear understanding of the long-term performance of reinforced concrete under harsh reactor operating and accidental conditions is essential.
This presentation provides a detailed overview of key radiation-induced degradation mechanisms affecting reinforced concrete, alongside a holistic multi-scale experimental and computational framework for assessing and predicting structural service life. The discussion draws on multi-year research supported by the Department of Energy Light Water Reactor Sustainability program and the U.S. Nuclear Regulatory Commission. It also highlights key differences between the existing reactor fleet and emerging advanced reactor designs.

Bio:
Dr. Mohammed Alnaggar is a Senior Research Scientist in the Nuclear Infrastructure Development and Operation Group at Oak Ridge National Laboratory. Prior to joining ORNL, Dr. Alnaggar was an assitant professor at Rensselaer Polytechnic Institute. His work centers on multi-scale, multi-physics modeling of material aging under extreme conditions, with contributions spanning cementitious materials (ASR, creep, shrinkage, chloride ingress, irradiation effects), thermal fatigue of fusion plasma-facing materials, coating delamination under hygro-thermal exposure, and infrastructure-scale concrete 3D printing.
He is an active member of multiple American Concrete Institute committees (349, 209, 446, 239, 564; Chair of 564-0D). His research integrates AI/ML with physics-based modeling, including parameter identification and physics-informed learning for ultrasonic damage assessment in ASR-affected concrete. His work is supported by LWRS, NEUP, Fusion Energy Sciences (ORNL), and the U.S. NRC, and implemented in platforms such as MOOSE, Abaqus, Project Chrono, and MARS.