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Assessment of the Material Performance for TCR Applications (Progress Report)

The objective of Argonne’s materials research activities for the Transformational Challenge Reactor (TCR) program is to improve the understanding of material properties from additive manufacturing with the focus on understanding the creep and fatigue properties of additively manufactured materials. The material work conducted by Argonne provides support in developing and qualifying advanced materials and manufacturing processes to allow for innovative reactor design and licensing for the TCR. In FY 2020, Oak Ridge National Laboratory (ORNL) provided six ASTM standard sized creep specimens of additively-manufactured 316L stainless steel (AM 316L SS) for evaluation of the effect of post-build heat treatment on the creep property. Two different teat treatments were conducted on the as-built specimens, namely 1050°C/1h and 650°C/1h before creep testing. All specimens were creep tested at 550°C and 275 MPa to understand the effect of heat treatments. We have also received AM 316L SS printed in various forms including rods and sheets, wrought 316 L SS (as a reference material), and AM IN718 for tensile, creep and fatigue testing. Both ASTM standard sized specimens and subsized specimens are being fabricated or tested to contribute to a comprehensive mechanical property database of AM materials and to provide location-specific property data to the TCR digital platform. Mechanical testing at Argonne is conducted to ASME NQA-1 or its lab equivalent for quality assurance. This report presents the results of the creep tests at 550°C and microstructural characterization for the assessment of the effect of the post-build heat treatment on the creep behavior of AM 316L SS. It also discusses ongoing efforts on obtaining location-dependent properties of AM 316L SS.

36 MATERIALS SCIENCE↗

Demonstration of Embedded Sensors in Ceramic Structures

The Transformational Challenge Reactor (TCR) program seeks to demonstrate an advanced 3D printed nuclear reactor core. A binder jet additive manufacturing process is used to fabricate the complex SiC ceramic components of the TCR core. After printing, the components are densified via chemical vapor infiltration (CVI). This process allows complex cavities to be created in which sensors can be placed at strategic locations. Inserting the sensors during the CVI process allows the sensors to be embedded within the component as it is infiltrated. The primary challenge for embedding the sensors is identifying the sensors and sensor sheath materials that can survive the temperatures (>1,000°C) and chemical exposure to H 2 and HCl during CVI. The embedded sensors that are being investigated for use during TCR operation include thermocouples, self-powered neutron detectors, and spatially distributed fiber-optic temperature sensors. This report describes the CVI materials compatibility tests and initial trials for embedding functional sensors. Mo is identified as the most suitable sensor sheath material based on its availability in small diameter tubing, relatively low neutron absorption cross section, and compatibility with H 2 , HCl, and the surrounding SiC matrix at the process temperatures. Amorphous SiO2 fiber-optic samples with Au and Cu metal coatings were successfully embedded in SiC along with bare fibers, although the metal coatings showed some evidence of localized melting during CVI. Initial experiments attempting to embed functional sensors showed that the sensors can be embedded in 3D printed SiC parts, but there are still challenges that must be overcome to ensure that the sensors and sensor sheaths do not fail during CVI. In particular, Nb-sheathed Mo-Nb thermocouples failed at temperatures far lower than expected despite thermodynamic calculations and materials compatibility tests that show the Nb sheath to be compatible with the CVI environment. One potential explanation for the large expansion of the Nb sheath could be related to hydride formation in the lower temperature region of the sheath. Future work will focus on Mo-sheathed thermocouples instead of Nb. The fiberoptic sensors tested during the instrumented experiment broke due to the lack of mechanical protection after their polymer-based coatings were vaporized. Future instrumented experiments will use metal-coated optical fibers for strain sensing to provide additional mechanical protection. However, custom coatings with higher melting points than commercially available Au and Cu might be required. Regardless, fiber-optic sensors are still candidates for spatially distributed temperature measurements since they can be inserted into an embedded metal sheath after CVI.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Mechanical Properties and Deformation Behavior of Additively Manufactured 316L Stainless Steel (FY2020)

The Transformational Challenge Reactor (TCR) program plans to build most of the TCR core components through additive manufacturing (AM) processes. These processes include laser powder bed fusion (LPBF) for the metallic (316L) components and the newly developed combined process of binderjet printing and chemical vapor infiltration (CVI) for the SiC fuel matrix. Mechanical testing and characterization tasks have been carried out since the beginning of the TCR program to (1) build a property database for the AM materials that will be used in TCR core and (2) to assess the materials’ performance in TCR-relevant conditions. This document reports the outcome of the testing and characterization efforts for the fiscal year with a focus on the mechanical performance data of AM 316L stainless steel (SS). Baseline tensile testing over a wide temperature range of room temperature–600 °C was completed for the AM 316L alloy in as-built, stress-relieved, and solution-annealed conditions. The as-built 316L showed the highest strength, and the alloy after the post-build treatments showed reduced strengths in the low-strain range. However, the strength differences among the AM materials became insignificant in the later part of deformation. Furthermore, regardless of post-build processing, the AM 316L SS showed higher strength and comparable ductility when compared with wrought 316L SS. Thermal creep testing and microstructural evolution during creep deformation were also performed under selected conditions. It was found that the AM 316L steel showed the best creep resistance in the stress-relieved condition. In-situ tensile tests were performed using scanning electron microscopy and 1-ID beamline at the Advanced Photon Source to elucidate the deformation and fracture behavior of AM 316L and the evolution of crystalline stress, dislocations, and pore distribution. Using these in-situ testing data, an in-depth analysis of the roles of microstructural features in deformation and fracture processes is presented herein. The final section of the document introduces ongoing and future activities for materials testing and characterization, including irradiation effect studies and ball punch testing on AM 316L and AM IN718 alloys.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Features that Further Performance Limits of Nuclear Fuel Fabrication: Opportunities for Additive Manufacturing of Nuclear Fuels

One goal of the Transformational Challenge Reactor (TCR) program is to fully assess the opportunity space for additive manufacturing (AM) to overcome the material limitations restricting development and deployment of nuclear power. This report presents an initial analysis of the opportunities for using AM to significantly impact the nuclear fuel fabrication paradigm. The conventional limitations of the three basic solid fuel types are examined herein, and. possibilities for fabrication technologies to overcome these limitations are outlined. Areas that can be most significantly improved by AM are those in which conventional nuclear fuel fabrication routes are known to limit performance. For monolithic systems, one high priority area is fabrication of heterogeneous duplex and compositionally graded structures— fuel designs that bring significant benefits to fuel utilization. A critical first step in meeting this challenge is to successfully demonstrate AM’s ability to achieve representative density and microstructures for fuel materials such as UO 2 . The area with the highest potential for pairing AM methodology with the challenges of nuclear fuel deployment is advanced matrices for particle and dispersion fuels that are free from conventional processing constraints. AM has the potential to achieve packing fractions and matrix quality that are superior to those available through conventional methods. Finally, the use of digital twin data collection, which is possible through in situ build diagnostics, may greatly reduce uncertainty regarding distribution of uranium in these systems. A subsequent FY19 TCR milestone will examine the suitability of existing commercial systems to address these challenges.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Development of Monitoring Techniques for Binderjet Additive Manufacturing of Silicon Carbide Structures

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to fabricate nuclear components to be assembled into a fully functional microreactor core. Compared with traditional manufacturing technologies, AM technologies allow (1) observation of the manufacturing process at a much higher resolution in real-time using in situ monitoring technologies to capture the sensor signature that scientifically describes each event occurring over time and space and (2) validation of the manufacturing process quality using domain-informed data analytics techniques as a potential qualification and certification methodology for the final component. This report provides an update on the program work on binder jetting in situ process monitoring and associated data analytics results, as well as sample placement and tracking for the subsequent chemical vapor infiltration (CVI) process. Examples are provided to illustrate the progress. Elements of the Digital Thread and data management are discussed in the main document, and an extensive supplemental material section is provided detailing the Digital Platform, as well as its implementation and components. In conclusion the path forward for the next fiscal year is discussed.

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Development of Monitoring Techniques for Laser Powder Bed Additive Manufacturing of Metal Structures (Progress Report)

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to fabricate nuclear grade components to be assembled into a fully functional microreactor core. Compared to traditional manufacturing technologies, additive manufacturing technologies allow (1) observation of the manufacturing process at a much higher resolution in real time using in situ monitoring technologies to capture the sensor signature that scientifically describes each event occurring over time and space, and (2) validation of the manufacturing process quality using domain-informed data analytics techniques as a potential qualification and certification methodology for the final component. This report provides an update on the program work on laser powder bed fusion in-situ process monitoring and associated data analytics results. Examples are provided to illustrate the progress. Elements of the Digital Thread and data management are discussed in the main document, and an extensive supplemental material section is provided detailing the Digital Platform, as well as its implementation and components. In conclusion the path forward for the next fiscal year is discussed.

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Report on Progress of correlation of in-situ and ex-situ data and the use of artificial intelligence to predict defects

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to fabricate nuclear components which will be assembled into a fully functional microreactor core. Compared with traditional manufacturing technologies, AM technologies allow (1) real-time observation of the manufacturing process at a much higher resolution using in-situ monitoring technologies to capture the sensor signatures that scientifically describe each event occurring over time and space and (2) validation of the manufacturing process quality using domain-informed data analytics techniques as a potential qualification and certification methodology for the final component. This report provides an update on the program work on in-situ and ex-situ data correlation and associated data analytics results. Examples are provided to illustrate progress with respect to laser powder bed fusion (L-PBF), binder jetting, computed tomography (CT) reconstruction, and mechanical testing. Elements of the Digital Thread and data management infrastructure are discussed in the main document, and an extensive supplemental appendix is provided detailing the Digital Platform, as well as its implementation and subcomponents. In conclusion, the path forward for the next fiscal year is also discussed.

42 ENGINEERING↗

Progress Report on the Assessment of the Material Performance for TCR Applications

The objective of Argonne’s materials research activities for the Transformational Challenge Reactor (TCR) program is to improve the understanding of material properties from additive manufacturing with the focus on understanding the creep and fatigue properties of additively manufactured materials. The material work conducted by Argonne provides support in developing and qualifying advanced materials and manufacturing processes to allow for innovative reactor design and licensing for the TCR. In this report, we present the creep data at temperatures of 550, 600 and 650°C and stresses between 175 and 300 MPa for 316L stainless steel produced by a laser powder bed fusion process. We conducted five different post-build heat treatments, namely 650°C/1h, 750°C/1h, 800°C/1h, 900°C/1h and 1050°C/1h. Creep tests of the heat-treated specimens were performed under the same test condition, 550°C/275 MPa to evaluate and understand the effect of post-build heat treatment on the creep behavior of additively-manufactured 316L SS. Creep tests were conducted to ASME NQA-1 or its lab equivalent for quality assurance.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Evaluation of Binder Jetting and Chemical Vapor Infiltration as a Production Method for Silicon Carbide Parts for Nuclear Applications

Application of silicon carbide (SiC) is often sought within nuclear energy systems due to its high thermal conductivity, mechanical and environmental stability at elevated temperatures, corrosion resistance, and exceptional displacement damage irradiation tolerance. As such, the transformational challenge reactor (TCR) program is considering its application in its additively manufactured core. SiC may be used as the matrix for the TCR fuel blocks that comprise of TRISO fuel particles embedded inside this material or used as core non-fuel-bearing peripherical structures such as bottom support manifolds. The core peripherical structures serves to support the overall core geometry, direct and guide coolant flow, and also reflect back leaked neutrons into the core. SiC has very low neutron absorption and adequate scattering cross sections that makes it an ideal material for utilization in the TCR core. Like many ceramics, however, SiC is difficult and at times impractical to shape into complex geometries via traditional machining due to its brittleness. Further, large structures comprising nuclear-grade SiC, i.e. highly pure and crystalline, are costly. Additive manufacturing (AM), however, offers the ability to shape materials by adding layer-by-layer rather than subtracting, contributing new possibilities for previously difficult-to-shape materials. Thus, exploring AM as a method to shape SiC offers a highly cost-effective method and is strategic to developing the next generation of components for nuclear reactors. This report outlines an evaluation of binder jet additive manufacturing combined with chemical vapor infiltration (CVI) to produce nearly-dense silicon carbide artifacts in complex geometries suitable for advanced nuclear reactor designs. The focus is placed on the binder jet printing technologies at large scale for nonfuel-bearing structures relevant to the TCR core and other advanced reactors. Among all AM processes, binder jet delivers the highest resolution capability while still maintaining large print sizes, making it the ideal candidate for nuclear component production.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Performance of Embedded Sensors in 3D Printed SiC

This report summarizes recent advances in embedding sensors in 3D printed silicon carbide (SiC) ceramic components under the Transformational Challenge Reactor (TCR) program. The additive manufacturing technologies developed under this program will enable fabrication of complex structures with embedded fuels and sensors. The sensors will be capable of characterizing fuel performance using spatially distributed measurements at the most strategic locations that would be otherwise inaccessible using conventional manufacturing techniques. While previous programmatic updates describe initial concepts for embedding sensors, materials selection, and initial characterization of the embedded sensors, the technology requires further demonstration, and quality-significant procedures must be established before the embedding technology is ready for adoption by industry. To this end, this report describes the most effective techniques that have been used to embed functional sensors in 3D printed components using a combination of binder-jet additive manufacturing and chemical vapor infiltration (CVI). A detailed procedure describes each step in the process and is available upon request. Molybdenum (Mo)-sheathed thermocouples have been successfully embedded in complex SiC components, and temperatures were monitored in situ during the embedding process. Post-embedding measurements showed no significant hysteresis, and characterization of the interface revealed qualitatively strong bonding around the entire perimeter of the sensor sheath. Distributed fiber-optic temperature sensors were able to briefly measure temperature profiles during CVI, but they ultimately failed prior to completion of the CVI run. The failure appears to be related to the fiber coating at temperatures close to 1,000°C. Future work will focus on irradiation testing of embedded thermocouples and other sheathed electrical sensors, as well as the identification of fiber-optic sensor coatings that can survive CVI.

42 ENGINEERING↗

Production and Characterization Package of Reference and Advanced Feedstock

This milestone report summarizes the synthesis routes used to produce ceramic nuclear fuel feedstock at Oak Ridge National Laboratory (ORNL). The solution-gelation process is used to fabricate microspheres, which are then converted to ceramic fuel materials using various processing conditions. Resulting fuel materials include uranium dioxide (UO 2 ), uranium monocarbide (UC), and uranium mononitride (UN). The microsphere size distribution, density, and composition of the fuels can be altered using the conversion routes defined in this report. The resulting materials can be used as the feedstock in a number of additive manufacturing (AM) processes. The present materials were prepared using depleted or natural uranium to facilitate exploratory development activities. However, the laboratories used for this work are authorized for enriched uranium and are actively utilized for this purpose to fabricate fuel test articles for irradiation. If desired, the techniques demonstrated in this document can be readily used for enriched material production to support the Transformational Challenge Reactor (TCR) program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Safety Design Strategy for the Transformational Research Reactor

The Department of Energy Office of Nuclear Energy is embarking on the Transformational Challenge Reactor (TCR) program to demonstrate application of advanced technologies in enabling rapid and cost effective deployment of nuclear power systems. The TCR program will design, manufacture, and operate a small nuclear reactor at the Oak Ridge National Laboratory incorporating advanced manufacturing. DOE Order 420.1C requires the integration of safety in the design process. Therefore, the general approach in DOE-STD-1189 as described in this Safety Design Strategy is applied to the project to establish requirements for safety design for the resultant Categorized Nuclear Facility/Activity and to ultimately allow the Department of Energy to authorize operation of the facility.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

TCR Data Management Plan

The Oak Ridge National Laboratory (ORNL) Transformation Challenge Reactor (TCR) program is developing additive manufacturing and artificial intelligence (AI) to deliver enabling technologies for advanced reactors. Through the application of these advanced technologies, the program targets delivering solutions to the high costs and lengthy deployment timelines that threaten the future of nuclear energy—the country’s largest source of carbon-free energy. This document describes the plan for integrating and managing TCR data from multiple sources throughout ORNL and external sources, including novel data sources associated with advanced manufacturing, characterization systems, and the TCR Digital Platform that incorporates various levels of AI and data analytics.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

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↗

Monitoring for Additive Manufacturing Technologies: Report on Progress, Achievements, and Limitations of Monitoring Techniques

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to produce multiple nuclear components to be assembled into a fully functional microreactor core. AM was selected as the main manufacturing technology of choice for TCR because it has the potential to disrupt the nuclear industry on two fronts: (1) it enables the manufacturing of very complex geometries with optimized and tailored material properties for the intended use of the component, opening up new options for reactor designs, and (2) it allows for a better understanding of the manufacturing process through real-time in situ monitoring, data analytics, and artificial intelligence that can lead to a streamlined qualification and certification process. Within TCR, the development and deployment of a digital platform aims at addressing the latter opportunity. As part of this effort, the collection of pedigree data sets is vital, should these data be generated before, during, or after the manufacturing process. This report focuses on the collection of manufacturing process data using systems instrumentation and monitoring. It presents an inventory of the various monitoring modalities installed on the manufacturing systems by the machine manufacturer or specifically designed by our team to fill information gaps. It also provides details on other relevant data streams available and leverageable to evaluate the manufacturing process on all classes of AM systems investigated during the first year of this program. Through examples, the report gives an overview of the data collected and presents a path forward for the digital platform.

42 ENGINEERING↗

Mechanical Properties of Additively Manufactured 316L Stainless Steel Before and After Neutron Irradiation (FY21)

This report presents the materials property data of additively manufactured (AM) 316L stainless steel (SS) accumulated for the assessment of core materials in the Transformational Challenge Reactor (TCR) program. The TCR manufacturing approach includes using the laser powder bed fusion (LPBF) method for metallic (316L and Inconel 718) components. To assess the mechanical performance of printed components in reactor-relevant conditions and build a property database for the AM materials, mechanical tests and evaluations were performed before and after neutron irradiation. Miniature tensile specimens were irradiated in the High Flux Isotope Reactor to 0.2, 2, 8, and 10 dpa at target temperatures of 300 and 600°C. Postirradiation evaluation for the 0.2 and 2 dpa specimens was performed during FY20 and FY21, and the results are presented and discussed in this document.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Hydrogen Diffusivity Measurements of YH 1.87 Moderator Material with Incoherent Quasielastic Neutron Scattering

Yttrium hydride is an optimal choice of moderator material for thermal neutron spectrum reactors requiring small core volumes. The Transformation Challenge Reactor (TCR) program at Oak Ridge National Laboratory (ORNL) aims to develop an additively manufactured microreactor core by leveraging recent advances in materials, manufacturing, data analytics, and high-fidelity modeling and simulation. Yttrium hydride was selected as the moderator material for TCR due to its high moderating power, which enables the spatially efficient reactor design and thermal stability that is superior when compared with zirconium hydride. Hydrogen desorption from yttrium hydride is expected at elevated temperatures, posing safety and performance concerns. As a lifetime component in advanced reactors, appropriate strategies to mitigate hydrogen release from yttrium hydride over long-term reactor operation are required. Understanding hydrogen mobility in yttrium hydride provides the scientific basis for developing a hydrogen barrier for hydride moderator and predicting the hydrogen redistribution within the material during various operational conditions. This study investigated the hydrogen motion in YH 1.87 as a function of temperature ranging from 200 to 1,173 K using incoherent quasielastic neutron scattering (IQNS) at the Spallation Neutron Source (SNS). The results are presented and discussed in terms of hydrogen self-diffusion coefficients, activation energy for translational hydrogen motion, and hydrogen jump distances. Based on the IQNS data, YH 1.87 is found to be stable at high temperatures with no translational H motion below 1,023 K within the IQNS detection limits. In the temperature range of 1,073–1,173 K, hydrogen diffusivity in YH 1.87 is $D = 4.57 X 10^{⁻3} [m^2/s] exp (⁻\frac{1.73[eV]}{RT}$). The hydrogen concentration’s dependence on hydrogen diffusivity is also discussed in this report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Artificial Intelligence for Multiphysics Nuclear Design Optimization with Additive Manufacturing

The geometric flexibility of additively manufactured metals and ceramics generates a very large and open design space that requires advanced modeling and simulation tools for physics simulations and the rigorous definition of design problems. This effort deploys artificial intelligence (AI) and machine learning (ML) algorithms to understand the design space, evaluate potential designs, and more efficiently generate optimized results. The Transformational Challenge Reactor (TCR) program is leveraging advances in several scientific areas—including materials, manufacturing, sensors and control systems, data analytics, and high-fidelity modeling and simulation—to accelerate the design, manufacturing, qualification, and deployment of advanced nuclear energy systems. Through a manufacturing-informed design approach, the TCR program seeks to integrate digital data for rapid nuclear innovation; accelerate the adoption of advances in manufacturing, materials, and computational sciences for nuclear applications; and dramatically reduce deployment costs and timelines for new nuclear reactor technologies. This report documents efforts under the TCR program to leverage advanced modeling and simulation techniques driven by AI/ML algorithms on high-performance computing (HPC) systems to yield more optimized TCR core designs. A multiphysics ML surrogate model was developed to run on the HPC architectures. The surrogate model is trained on high-fidelity simulation data of coupled neutronics and thermofluidics and is used to quickly evaluate thousands of candidate core designs in parallel, which drives the evolution of the cooling channel shapes to minimize temperature peaking and material stress. Outcomes from these activities provide design information and feedback into the core design efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗