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DOE OSTI2025

A simplified approach for creep damage and remaining life calculation for materials surveillance in advanced reactors

High temperature reactor materials will experience a combination of mechanical degradation caused by creep and fatigue and environmental degradation caused by neutron irradiation and, in some cases, exposure to corrosive coolants. A materials surveillance program is one option for ensuring the safe, reliable operation of key reactor components under these conditions. Such a program would monitor the degradation in key material properties over time, using this data to predict how changes in the material properties affect components performance. This could then be used to make plant operational decisions and support eventual plant license extensions. Past work de-scribes such a material surveillance program based on passively actuated mechanical test articles that impose creep-fatigue type loading on test materials driven only by changes in temperature, for example those experienced by components under standard operating cycles. This report focuses on two aspects of the proposed material surveillance program: how to design the test articles to mimic the mechanical response of the corresponding component and how to use ex-situ test data to deter-mine the amount of damaged experienced by the test article (and hence the corresponding compo-nent) in service. Specifically, this report derives and validated simplified methods for both tasks, replacing earlier, more complicated approaches based on simulating the test article response and finding the best specimen design or current damage via complex numerical optimization. The sim-plified methods for each task developed here can be implemented in spreadsheet software and are simple enough for practical use in future operating plants. This report derives the methods (one for sizing and two options for damage inference), verifies the simplified approaches versus more so-phisticated methods, and compares the results of applying the simplified methods to previous re-sults using the complex numerical optimization approach. The report also provides a worked sam-pled problem applying the simplified techniques to a realistic high temperature reactor component.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

PTT System Performance Evaluation in 3-D Imaging of Calibrated Defects: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Research activity in this project is aimed at developing pulsed thermal tomography (PTT) architecture and algorithms for in-service non-destructive examination (NDE) of additively manufactured (AM) reactor components and materials. Recent advances in AM technology could allow cost-efficient fabrication of parts for operating reactors. However, because of stringent safety requirements, long-term performance of AM reactor components needs to be investigated before AM is widely accepted. Because of the complex shapes and significant surface roughness of components due to layer-by-layer welding process in AM, conventional methods might not be useful for in-service NDE of AM components. PTT is ideally suited for in-service NDE of AM metallic components because the method is non-contact, and offers high resolution #-D imaging of material flaws. The objective of this report is to provide initial evaluate of PTT performance sin detecting calibrated flaws in reactor structural materials. Preliminary COMSOL models were developed to conduct super computing simulations of PTT. In the experimental studies, high strength Stainless Steel 316 and Inconel 718 alloys were considered, as well as lower grade Stainless Steel 304, Nickel 200, and Hastelloy C276. Specimens investigated in this report consisted of approximately 1/4in-thick plates made out of these alloys using conventional manufacturing methods. The calibrated defects were created in the form of flat bottom holes (FBH) drilled in metallic plates. The diameters of FBH's varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. The size of the smallest FBH was limited to 1mm because conventional mechanic drills were used for creating the holes. PTT imaging results have shown that 1mm-diameter FBH located 1mm and 2mm below the surface were detectable. Larger size FBH were detectable at greater depth. For example, 6mm-diameter FBH could be detected at 8mm depth. Image contrast varied slightly between the specimens, with the best reconstructions obtained in SS316 and C276 plates. In addition, a 2/3in-thick Inconel 718 nozzle plate produced with additive manufacturing method was imaged with PTT. It was shown that PTT can scan through the plate in approximately 20s. Several modes of 3-D data visualization were explored, including using ImageJ and MATLAB software packages.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

New Designed Containers for Activated ILW from NPP Decommissioning - 20208

The paper focuses on packaging of dismantled and fragmented reactor components into containers and their transport to their storage and/or disposal facility within the immediate dismantling strategy applied on decommissioning of nuclear power plant (NPP) finally shutdown after standard operation. The main purpose of the paper is to present the process of design, manufacture, testing and use of new transport and storage containers for activated intermediate level waste (ILW) from V1 NPP decommissioning at Jaslovske Bohunice site. Legislation conditions, container selection process, requirements on their design and manufacture, scope of associated licensing documentation and technical procedures applied up to their use on site are described in detail. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Treatment of Problematic Reactive Metal Wastes Using the GeoMelt{sup R} In-Container Vitrification (ICV{sup TM}) Process - 20326

Decommissioning of sodium-cooled reactors and fast reactor technologies has generated a number of reactive metal waste configurations that are problematic to treat and typically lack cost effective treatment methods and disposition options. As a result, Veolia Nuclear Solutions, under contract with Idaho National Laboratory (owned by the U.S. Department of Energy and managed and operated by Battelle Energy Alliance, LLC) demonstrated its GeoMelt{sup R} In-Container Vitrification (ICV){sup TM} technology to safely convert sodium metal to a non-reactive vitrified oxide form. The demonstration project, supported by glass formulation and crucible testing, consisted of a series of ICV{sup TM} melts that processed elemental sodium into stable non-reactive glass. INL is currently implementing GeoMelt{sup R} technology as a means to safely and reliably convert radioactive reactive metal residues that contaminate sodium cooled reactor components into waste forms that comply with existing disposition pathways. Reactive metal wastes require treatment in order to remove the Resource Conservation and Recovery Act (RCRA) reactivity and ignitability characteristics to comply with land disposal restrictions. GeoMelt{sup R}, which is an alternative to other potential treatment approaches, provides a robust approach that chemically converts the reactive metals to an inert oxide while also immobilizing radionuclides in a vitrified waste form with durability equal to or better than vitrified nuclear fuel reprocessing wastes (very robust and inert waste forms). Most other treatment approaches generate hydrogen gas which is problematic. In 2016, Veolia Nuclear Solutions first demonstrated the effectiveness of the GeoMelt{sup R} ICV{sup TM} process in deactivating reactive sodium metal. Crucible, bench-scale, and engineering-scale demonstrations were conducted on several surrogate waste configurations with various ratios of sodium metal and glass formers. Each ratio and configuration demonstrated complete deactivation of the surrogate sodium metal. Follow-on work in 2017 demonstrated the deactivation of reactive sodium by GeoMelt{sup R} ICV{sup TM} at a higher waste loading relative to previously demonstrated work performed in 2016; the higher waste loading optimized glass chemistry while enhancing the economical full-scale treatment of reactive metals. Additionally, follow-on demonstration testing in 2018 and 2019 focused on more complex shapes and other reactive-metals (mocked up Experimental Breeder Reactor II [EBR-II] subassembly, sodium filled heat exchanger, and a can containing sodium potassium alloy) which were all performed at engineering scale. Veolia Nuclear Solutions designed, installed, and commissioned in September 2018, at Perma-Fix Northwest in Richland Washington, a 10-metric ton full-scale GeoMelt unit (GeoMelt{sup R} Richland) for the treatment of reactive metal wastes. As of September 2019, over 900 55-gallon drums containing a total of around 3,500 lb of sodium with low levels of radioactivity have been treated at GeoMelt{sup R} Richland, with resulting glass monoliths disposed at the Nevada National Security Site (NNSS). A full-scale radiological demonstration melt on an actual EBR-II subassembly has also been performed using the full-scale melter in 2019. The GeoMelt{sup R} technology is a proven radioactive waste treatment technology capable of immobilizing radioactive wastes, including bulk rubble such as drums and other steel vessels usually without pretreatment. Utilizing the GeoMelt{sup R} technology to treat reactive metals eliminates pretreatment steps resulting from having to separate the reactive metal from steel containers or jackets as GeoMelt{sup R} can easily operate at temperatures sufficient to melt the steel and expose the reactive metal for treatment. Eliminating handling steps of reactive metals is a significant safety advantage since reactive metals are pyrophoric. The results generated as a part of the 2018-2019 demonstration program are presented in the paper. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

Radiation response of alloy T91 at damage levels up to 1000 peak dpa

Ferritic/martensitic alloys are required for advanced reactor components to survive 500e600 neutroninduced dpa. Ion-induced void swelling of ferritic/martensitic alloy T91 in the quenched and tempered condition has been studied using a defocused, non-rastered 3.5 MeV Fe-ion beam at 475 C to produce damage levels up to 1000 peak displacements per atom (dpa). The high peak damage level of 1000 dpa is required to reach 500e600 dpa level due to injected interstitial suppression of void nucleation in the peak dpa region, requiring data extraction closer to the surface at lower dpa levels. At a relatively low peak damage level of 250 dpa, voids began to develop, appearing first in the near-surface region. With increasing ion fluence, swelling was observed deeper in the specimen, but remained completely suppressed in the back half of the ion range, even at 1000 peak dpa. The local differences in dpa rate in the front half of the ion range induce an “internal temperature shift” that strongly influences the onset of swelling, with shorter transient regimes resulting from lower dpa rates, in agreement not only with observations in neutron irradiation studies but also in various ion irradiations. Swelling was accompanied by radiation-induced precipitation of Cu-rich and Si, Ni, Mn-rich phases were observed by atom probe tomography, indicating concurrent microchemical evolution was in progress. In comparison to other ferritic/martensitic alloys during ion irradiation, T91 exhibits good swelling resistance with a swelling incubation period of about 400 local dpa.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2021

Embedding Sensors in 3D Printed Metal Structures

The Transformational Challenge Reactor (TCR) program is leveraging recent advances in modeling and simulation, materials, and additive manufacturing (AM) technologies to design a modern nuclear reactor. Some of the main TCR technologies include in situ monitoring and the integration of sensors during the manufacturing of quality-significant nuclear reactor components. This report describes the general procedure and process optimization for embedding sensors within generic stainless steel 316 (SS316) components using laser powder bed fusion (LPBF). A more detailed, quality-significant test plan and supporting procedures are available upon request (ORNL/TM-2021/2127). LPBF involves the use of a scanning laser to selectively melt regions of a powder bed, additively building a part layer by layer. This report describes the LPBF processing technique and discusses the effects of LPBF processing parameters on the success of the sensor embedding process. Experiments used machined cavities in the form of channels in an SS316 base for the sensors to lay in while material is additively built over the top, thereby embedding them in an SS316 matrix. A preliminary investigation involved using empty SS316 sheaths as surrogates to explore the effects of various LPBF processing parameters and the dimensional requirements of the machined channels. Microstructural investigations showed that a smaller channel width/depth combination closer to the sensor’s diameter was best for the embedding process. After the desired parameters were selected, Type-K thermocouples were embedded and evaluated post-embedding using nondestructive thermal testing, as well as destructive sectioning and microscopy. Post-build characterization showed that the thermocouples were well-bonded to the SS316 matrix and were fully functional after embedding. During thermal testing to temperatures up to 500 °C, the embedded thermocouples read consistently with one another and deviated only slightly from the readings of a nonembedded thermocouple located within the furnace. This slight discrepancy was most likely due to differences in the thermal time constants for a nonembedded thermocouple vs. a thermocouple embedded in a solid SS316 block. The results presented in this report will serve as the foundation for future work that will focus on embedding sensors in relevant TCR reactor components and eventually testing those components under neutron irradiation.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Big Data Framework with Machine Learning for D and D Applications - 19108

The nuclear industry is experiencing a steady increase in maintenance costs even though plants are maintained under high levels of safety, capability and reliability. Nuclear power plants are expected to run every unit at maximum capacity at all times, efficiently utilizing assets with minimal downtime. Surveillance and maintenance of nuclear decommissioning infrastructure provides lot challenges with respect to maintenance or decommissioning of the buildings. There is a need for a framework to analyze the huge amount of data generated by the sensors on the nuclear reactor components as well as structures, to monitor the conditions of these building over a period of time. Emerging technologies such as big data analytics have become a requirement in the nuclear industry to improve structural health monitoring and diagnostics. FIU will make use of existing mature technologies in the areas of imaging, robotics, big data, and machine learning/deep learning to assess the structural integrity of aging facilities at DOE sites. As these facilities await decommissioning, there is a need to understand the structural health of these structures. Many of these facilities were built over 50 years ago and in some cases these facilities have gone beyond the operational life expectancy. In other cases, the facilities have been placed in a state of 'cold and dark' and they are sitting unused, awaiting decommissioning. Finally, some older facilities are one-of-a-kind operational/production facilities supporting critical DOE missions and cannot be shut down. In any of these scenarios, the structural integrity of these facilities may be compromised, so it is imperative that adequate inspections and data collection/analysis be performed on a continuous and ongoing basis. The primary goals of the research include collecting various formats of data such as structured, unstructured and streaming data from the various sensors deployed in buildings, collect videos/pictures from various imaging sources, ingest them using a Hadoop distributed file system and process the data using Spark to perform batch processing and real time analytics. Research and development on various machine learning/deep learning algorithms will also be performed to analyze the heterogeneous data collected from nuclear decommission infrastructure. FIU will design the big data framework to ingest, store and process huge amounts of heterogeneous data collected from many sources and optimize the algorithms to provide insights into the data and predict anomalies observed when compared against baseline conditions. Various modules of this framework will include heterogeneous data sources, message broker, Hadoop distributed file system, Spark for stream and batch processing, machine learning/ deep learning, Cassandra - persistent data store and visualization. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Risk-informed Graded Approach for Reliability and Performance Assessment of Machine Learning and Artificial Intelligence for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Risk-informed Graded Approach for Reliability and Performance Assessment for Advanced Condition Monitoring Techniques

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2014

Characteristic evaluation of cooling technique using liquid nitrogen and metal porous media

A remountable high-temperature superconducting magnet, whose segments can be mounted and demounted repeatedly, has been proposed for construction and maintenance of superconducting magnet and inner reactor components of a fusion reactor. One of the issues in this design is that the performance of the magnet deteriorates by a local temperature rise due to Joule heating in jointing regions. In order to prevent local temperature rise, a cooling system using a cryogenic coolant and metal porous media was proposed and experimental studies have been carried out using liquid nitrogen. In this study, flow and heat transfer characteristics of cooling system using subcooled liquid nitrogen and bronze particle sintered porous media are evaluated through experiments in which the inlet degree of subcooling and flow rate of the liquid nitrogen. The flow characteristics without heat input were coincided with Ergun’s equation expressing single-phase flow in porous materials. The obtained boiling curve was categorized into three conditions; convection region, nucleate boiling region and mixed region with nucleate and film boiling. Wall superheat did not increase drastically with porous media after departure from nucleate boiling point, which is different from a situation of usual boiling curve in a smooth tube. The fact is important characteristic to cooling superconducting magnet to avoid its quench. Heat transfer coefficient with bronze particle sintered porous media was at least twice larger than that without the porous media. It was also indicated qualitatively that departure from nucleate boiling point and heat transfer coefficient depends on degree of subcooling and mass flow rate. The quantitative evaluation of them and further discussion for the cooling system will be performed as future tasks.

42 ENGINEERING↗

DOE OSTI2019

Considerations for Application of Additive Manufacturing to Nuclear Reactor Core Components

The following chapter represents the current state of literature on the selected additive manufacturing technologies and was written with an emphasis on quality control and material performance repeatability. Research and standards published by government entities such as the National Institute of Standards and Technology (NIST) and Department of Energy (DOE) have been included where applicable. It is recommended that literature be reviewed, and new knowledge integrated no less frequently than every four years due to the rapid pace of advancements in additive manufacturing and associated industries. AM presents unique challenges in certification for NPP applications such as anisotropic material properties, porosity, underdeveloped process control feedback systems, and reproducibility. This chapter begins with an overview of the selected AM technologies, followed by a systematic review of literature to detail the fabrication process and difficulties with repeatably fabricating fully dense, geometrically accurate components with known material properties.

36 MATERIALS SCIENCE↗

DOE OSTI2016

System for In-Situ NDI of Nuclear Reactor Graphite Components

Explore the source record for details and available documents.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Predictive Modeling and Uncertainty Quantification in Condition Monitoring of Active Components: A Reactor Coolant Pump Use Case

This work develops data-driven models for onset of thermal barrier leakage in reactor coolant pumps. It incorporates uncertainty quantification to enhance the reliability and robustness of pre- dictions. Using synthetic data generated by the Generic Pressurized Water Reactor simulator, realistic degradation scenarios were simulated across lifecycle stages—beginning, middle, and end of life. Key variables, including differential pressure, flow rate, vibration, and temperatures, were analyzed using machine learning framework. The fully connected neural network models demonstrated exceptional performance, achieving R2 scores exceeding 0.99 and root mean square errors as low as around 8.23 × 10-2 gallon per minute (gpm) for the three stages of the lifecy- cle. UQ analysis further validated the model’s robustness, with narrow uncertainty bounds during steady-state operations and appropriately wider bounds during transitional phases, reflecting the physical behavior of the system. This work addresses important gaps in real-time condition moni- toring and regulatory compliance by integrating advanced condition monitoring technologies with UQ into IST programs. The ability to detect thermal barrier leakage early and quantify prediction reliability supports optimizing maintenance strategies while ensuring nuclear power plants’ safe and reliable operation.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2017

Advance High Temperature Inspection Capabilities for Small Modular Reactors: Part 1 - Ultrasonics

The project objective was to investigate the development non-destructive evaluation techniques for advanced small modular reactors (aSMR), where the research sought to provide key enabling inspection technologies needed to support the design and maintenance of reactor component performance. The project tasks for the development of inspection techniques to be applied to small modular reactor are being addressed through two related activities. The first is focused on high temperature ultrasonic transducers development (this report Part 1) and the second is focused on an advanced eddy current inspection capability (Part 2). For both inspection techniques the primary aim is to develop in-service inspection techniques that can be carried out under standby condition in a fast reactor at a temperature of approximately 250°C in the presence of liquid sodium. The piezoelectric material and the bonding between layers have been recognized as key factors fundamental for development of robust ultrasonic transducers. Dielectric constant characterization of bismuth scantanate-lead titanate ((1-x)BiScO 3 -xPbTiO 3 ) (BS-PT) has shown a high Curie temperature in excess of 450°C , suitable for hot stand-by inspection in liquid metal reactors. High temperature pulse-echo contact measurements have been performed with BS-PT bonded to 12.5 mm thick 1018-low carbon steel plate from 20C up to 260 C. High temperature air-backed immersion transducers have been developed with BS-PT, high temperature epoxy and quarter wavlength nickel plate, needed for wetting ability in liquid sodium. Ultrasonic immersion measurements have been performed in water up to 92C and in silicone oil up to 140C. Physics based models have been validated with room temperature experimental data with benchmark artifical defects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Environmentally Assisted Fatigue in Light Water Reactor Environment

This report summarizes the Environmentally Assisted Fatigue (EAF) research conducted at ANL under the US DOE Light Water Reactor Sustainability (LWRS) program. Starting from a rich background in theoretical and experimental EAF, ANL previously developed an approach to evaluate fatigue performance of reactor materials in light water reactor environments with the correction factor F en . The approach was based on a large body of experimental work performed at ANL and elsewhere, and was consistent with American Society of Mechanical Engineers (ASME)’s methodology governing the design and construction of reactor components. In recent years, the program was focused on component fatigue prediction and made several major and fundamental contributions in this area. These accomplishments help meet the needs identified by the industry concerning component level fatigue predictions in complex, transient conditions. The main contribution of the ANL program involved the development of a system-level model for estimating residual strain and life of nuclear reactor coolant system components under connected-system-thermal-mechanical boundary conditions. The goal was to predict the stress hotspots, strain residuals, strain amplitudes and the resulting fatigue lives. Thermal-mechanical stress analysis was performed considering thermal stratification and a design-basis reactor loading cycle. Based on the finite element (FE) model results, the strain residuals, strain amplitudes and resulting fatigue lives of reactor coolant system (RCS) components were predicted. The results show that some of the RCS components can have significantly different strain amplitudes, residual strain, and fatigue lives, despite having similar geometry and material. In addition, the simulated component-level strain profile can guide the selection of appropriate test inputs for conducting laboratory-scale EAF tests. Building upon the system-level model, ANL developed a digital twin (DT) framework to predict the structural states and associated fatigue life of components in real-time. This framework is a comprehensive system designed to predict the structural states and fatigue lives of reactor components. It includes multiple models and integrates artificial intelligence (AI), machine learning (ML), and FE based modeling tools to evaluate the structural states and fatigue lives.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

Evaluation of Optical Fiber Bragg Gratings in a Nuclear Reactor

Optical fiber-based sensors are capable of distributed temperature and/or strain measurements with high accuracy and sub-cm spatial resolution. Optical fibers have a small diameter ({approx}100 {mu}m), a small mass (and therefore fast response time), and are fabricated from high temperature-tolerant, radiation-hard materials. These qualities make optical fiber-based instrumentation a promising candidate for in-pile sensing applications, monitoring fuel performance during irradiation in test reactors, or embedding fibers in other commercial reactor components or structures. The Department of Energy and Idaho National Laboratory are restarting the TREAT reactor (Transient Reactor Test facility) and are interested in updating the reactor's instrumentation regarding the analysis of the test fuel. The ability of optical fibers to make distributed temperature measurements coupled with its small footprint makes optical fiber a viable candidate to monitor fuel performance in the TREAT reactor. The work presented in this paper focuses on the radiation hardness of various types of optical fiber Bragg gratings. Previous experiments have shown that the inscription of Bragg gratings into optical fiber can extend the radiation survivability of distributed sensing in optical fibers, and so the goal is to determine which types of Bragg gratings survive the best in a reactor environment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2016

Initial Results from the High Fluence UCSB ATR-2 Irradiation

A primary focus of the Department of Energy, Office of Nuclear Energy Light Water Reactor Sustainability Program (LWRSP) is the safe operation of nuclear reactors to extended lifetimes of up to 80 years. One of the primary reactor components of concern is the reactor pressure vessel (RPV), which is increasingly embrittled over time due to damage from high energy neutrons created in the reactor core. Radiation damage leads to the formation of nm-scale precipitates and solute-defect clusters, which result in an increase in the steel's ductile to brittle transition temperature. Transition temperature shifts (TTS) are used to quantify and regulate embrittlement. Extended life operation will subject some RPVs to higher neutron fluences than previously experienced by in-service vessels. Thus, robust prediction methods must be developed that ensure the safety of our nation's fleet of reactors. Current models underpredict embrittlement data from high flux test reactor irradiations at extended life fluences. It has been hypothesized that one reason for this underprediction is the formation of so-called 'Late- Blooming Phase' Mn-Ni-Si precipitates, which form and grow only at high fluence and that are currently not included in regulatory models. Recent research has demonstrated the existence of high volume fractions of intermetallic Mn-Ni-Si precipitate (MNSP) phases at high fluence and have generated significant insight into their character. However, a number of questions remain regarding MNSPs, such as: 1) what alloys are most susceptible to MNSP formation; 2) how is MNSP formation affected by flux (φ), fluence (φt) and irradiation temperature (T{sub irr}); and, 3) how to accurately predict TTS under extended life low flux service conditions? The fact that no two RPVs are exactly the same, both in terms of the steel composition and vessel service conditions, makes these questions particularly difficult to answer. Further, understanding the effect of flux differences between test reactor irradiations and in-vessel service is absolutely critical. Hence, physical models must be developed that predict TTS as a function of alloy solute content and vessel service conditions. A large-scale irradiation designed to develop and validate an extended life embrittlement prediction model was recently completed in the Advanced Test Reactor (ATR) at the Idaho National Laboratory as part of the DOE sponsored Nuclear Scientific User Facilities. This experiment, called the UCSB ATR-2 irradiation, is a collaboration between Oak Ridge National Lab (ORNL) and the University of California, Santa Barbara (UCSB) and is now primarily supported by the DOE Light Water Reactor Sustainability Program. The experiment is designed to investigate the single and combined effects of neutron φ, φt, T{sub irr} and alloy chemistry on precipitate formation, hardening and embrittlement. While postirradiation examinations (PIE) is ongoing, and is expected to take several years to complete, the first preliminary results are presented below. It should also be noted that Rolls-Royce has been a collaborator in UCSB ATR-2 from the start, and there are several other national and international institutions supporting the PIE. (authors)

36 MATERIALS SCIENCE↗

DOE OSTI2023

Codes and standards for ceramic composite core materials for High Temperature Reactor applications

Fiber-reinforced ceramic matrix composites are attractive for high-temperature nuclear applications due to excellent thermal and mechanical properties as well as reasonable-to-outstanding radiation resistance. Over the past 20 years, the use of ceramic matrix composite applications expanded to many commercial non-nuclear industries as fabrication and application of the technologies mature. The ASME Boiler Pressure Vessel Code, under Section III Division 5, provides the design and construction rules for High Temperature Reactor components. It published the first rules for ceramic matrix composites to be used for reactor core components. The rules lay out the quality requirements together with the design and materials criteria for the use and application of silicon carbide- and carbon-based matrix material technologies. As with the established graphite rules, the ceramic composite material rules are structured in Subsection HH (from Section III), that addresses the criteria for class SN nonmetallic core components. The code rules rely heavily on the development and publication of standards for composite specification, classification, and testing of mechanical, thermal, and other properties. These test methods are developed in ASTM Committee C28 on Advanced Ceramics, with a current focus on ceramic composite tubes. This article describes the detail of the composites code, the design methodology and similarities to the graphite code, the guidance for the development of specifications for ceramic composites (for nuclear applications) including recent standard developments, and it mentions the next steps to support licensing aspects by validating the code with benchmarking data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗