INL/EXT-15-36683 Light Water Reactor Sustainability Program Monitoring, Modeling, and Diagnosis of Alkali-Silica Reaction in Small Concrete Samples September 2015 U.S. Department of Energy Office of Nuclear Energy DISCLAIMER This information was prepared as an account of work sponsored by an agency of the U.S. Government. Neither the U.S. Government nor any agency thereof, nor any of their employees, makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness, of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. References herein to any specific commercial product, process, or service by trade name, trade mark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the U.S. Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the U.S. Government or any agency thereof. INL/EXT-15-36683 Revision 0 Monitoring, Modeling, and Diagnosis of Alkali-Silica Reaction in Small Concrete Samples Vivek Agarwal1, Guowei Cai2, Andrei V. Gribok1, Paromita Nath2, Reagan Hansley2, Kyle Neal2, Yanqing Bao2, and Sankaran Mahadevan2 September 2015 1Idaho National Laboratory Idaho Falls, Idaho 83415 http://www.inl.gov 2Vanderbilt University, Civil and Environmental Engineering Nashville, Tennessee 37235 Prepared for the U.S. Department of Energy Office of Nuclear Energy Under DOE Idaho Operations Office Contract DE-AC07-05ID14517 (This page intentionally left blank) ABSTRACT Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on existing safety code margins. Structural health monitoring of concrete structures aims to understand the current health condition of a structure based on heterogeneous measurements to produce high-confidence actionable information regarding structural integrity that supports operational and maintenance decisions. This report describes alkali-silica reaction (ASR) degradation mechanisms and factors influencing ASR. A fully coupled thermo-hydro-mechanical- chemical model (developed by Saouma and Perotti, 2006) that considers the effects of stress on the reaction kinetics and anisotropic volumetric expansion is presented in this report. This model is implemented in the GRIZZLY code based on the Multiphysics Object-Oriented Simulation Environment. The implemented model in the GRIZZLY code is randomly used to initiate ASR in a two- and three-dimensional lattice to study the percolation aspects of concrete. The percolation aspects help determine the transport properties of the material and the durability and service life of concrete. This report summarizes the effort to develop small-sized concrete samples with embedded glass to mimic ASR. The concrete samples were treated in water and sodium hydroxide solution at an elevated temperature to study how ingress of sodium ions and hydroxide ions impact concrete samples embedded with glass. A thermal camera was used to monitor the changes in the concrete samples and the subsequent results are summarized in this report. v (This page intentionally left blank) vi EXECUTIVE SUMMARY One challenge for the current fleet of light water reactors in the United States (U.S.) is age-related degradation of their passive assets that include concrete, cables, piping, and reactor pressure vessel. As the current fleet of nuclear power plants (NPPs) continue to operate up to 60 years or beyond, it is important to understand the current and the future health condition of passive assets under different operating conditions that would support operational and maintenance decisions. To ensure long-term safe and reliable operation of the current fleet, the U.S. Department of Energy’s Office of Nuclear Energy funds the Light Water Reactor Sustainability (LWRS) Program to develop the scientific basis for extending the operation of commercial light water reactors beyond the current license extension period. The LWRS Program has three pathways. The online monitoring research of assets in nuclear power plants is within the scope of research activities performed within the advanced instrumentation, information, and control systems technologies pathway. This effort also leverages the research performed within the material aging and degradation pathway. Among different passive assets of interest, concrete structures are investigated in this research project. Reinforced concrete structures found in NPPs can be grouped into four categories: primary containment, containment internal structures, secondary containments/reactor buildings, and spent fuel pool and cooling towers. These concrete structures are affected by a variety of degradation mechanisms, related to chemical, physical, and mechanical causes, and irradiation. The age-related degradation of concrete results in gradual microstructural changes (slow hydration, crystallization of amorphous constituents, reactions between cement paste and aggregates, etc.). Changes over long periods of time must be measured, monitored, and analyzed to best support long-term operation and maintenance decisions. Structural health monitoring (SHM) of concrete structures aims to understand the current health condition of a structure based on heterogeneous measurements to produce high-confidence actionable information regarding structural integrity and reliability. To achieve this research objective, Vanderbilt University, in collaboration with Idaho National Laboratory (INL) and Oak Ridge National Laboratory has proposed a probabilistic framework of research activities for the health monitoring of NPP concrete structures subject to physical, chemical, and mechanical degradation. A systematic approach proposed to assess and manage aging concrete structures requires an integrated framework that includes the following four elements: damage modeling, monitoring, data analytics, and uncertainty quantification. After proposing the above framework, INL and Vanderbilt University demonstrated through a simple concrete sample each element of the proposed probabilistic SHM framework. The research was focused on concrete SHM measurements, data analytics, and development of uncertainty-quantified diagnostic and prognostics models that will support continuous assessment of concrete performance. In this ongoing effort, the focus is to understand the alkali-silica reaction (ASR) in a concrete structure. ASR is a chemical reaction between the alkali hydroxides (Na, K, and OH) from the cement and unstable silica (silicon dioxide) in some type of aggregate. The reaction produces an alkali-silica gel that expands internally by absorbing water from the surrounding paste and eventually leading to cracking of the surrounding concrete. This degradation is intrinsic and extremely difficult to detect. To develop suitable instrumentation/monitoring techniques to detect ASR, it is important to theoretically understand its development mechanism in presence of different influencing factors. Therefore, in this phase of the research, mathematical model developed by Saouma and Perotti (2006) is used to understand ASR expansion. Saouma and Perotti (2006) developed a fully coupled thermo-hydro- mechanical-chemical for ASR based on Ulm et al. (2000) model, and considered the effects of stress on the reaction kinetics and anisotropic volumetric expansion induced by gel. The model was implemented in the GRIZZLY code based on the Multiphysics Object-Oriented Simulation Environment framework. These experimental measurements are used to validate the anisotropic ASR swelling model implemented in GRIZZLY. The simulation of ASR expansion using GRIZZLY code provided essential insight on the vii volumetric expansion mechanism and would lay the foundation for development of monitoring techniques. The implemented model in the GRIZZLY code is randomly used to initiate ASR in a two- and three- dimensional lattice to study the percolation aspects of concrete. Percolation theory plays an important role in interpreting and understanding the microstructure of cement-based material. The percolation aspects help determine the transport properties of the material and therefore the durability and service life of concrete. These transport properties are function of percolation threshold. In a parallel activity, Vanderbilt University developed small sized concrete samples with embedded glass (basically silica), which has a strong ability to form ASR and provides a quick proof-of-concept for the proposed SHM framework. The silica in glass reacts with the calcium in cement to form calcium silicate hydride (ASR gel) in the presence of sodium hydroxide. Two sets of three samples each sized 9 in. × 5 in. × 2 in. were cast. For better test sample control, aggregates were replaced by glass (approximately 75% silicon dioxide) in these experiments. By performing data analysis of thermal images, the deformation of glass under thermal loading profile was studied. In the next phase of the research, Vanderbilt University in collaboration with Professor Eric Giannini of University of Alabama will be working on developing medium sized concrete samples (2 ft × 2 ft × 6 in.) using reactive aggregates with and without steel reinforcement. Full field imaging techniques will be applied to detect ASR expansion in the medium sized sample. A strong theoretical basis will be established and validated to support the proposed monitoring techniques. A data analytics and visualization framework will be developed to analyze and visualize heterogeneous data on a unified and easy-to-use visualization platform. Diagnostic uncertainty quantification will also be formed. In fiscal year 2016, a collaborative research effort will be performed between the Advanced Instrumentation, Information, and Control and Material Aging and Degradation pathways under the LWRS Program to support large concrete sample instrumentation, data analysis, and uncertainty quantification elements of the SHM framework. viii ACKNOWLEDGMENTS This report was made possible through funding by the U.S. Department of Energy (DOE) Light Water Reactor Sustainability Program. We are grateful to Richard Reister of DOE, and Bruce Hallbert and Kathryn McCarthy at Idaho National Laboratory for championing this effort. We thank Jodi L. Vollmer for her technical editing and formatting of the document. We also thank Benjamin W. Spencer and Hai Huang at Idaho National Laboratory for providing access to the GRIZZLY code and for their technical guidance on code implementation. ix (This page intentionally left blank) x