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9 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Manufacturing porous U10Zr fuels with controlled porosities by SPS and thermal properties

To accommodate the swelling of metallic fuels induced by the fission gas release during burnup in sodium fast reactor for a sodium-free fuel option, advanced U-10Zr fuels with controlled porosity were designed and demonstrated by spark plasma sintering. U-10Zr fuel pellets with manufactured porosities varying from 35% up to fully dense fuel pellets have been fabricated by controlling ball milling times of the starting uranium powders, sintering temperature, pressure, and duration, and the correlation among the microstructure control – porosity – sintering conditions has been established. To further mimick the pore structure in irradiated fuels, different pore formers (NaCl and NH4HCO3) have been used to control the pore size and distribution. Microstructure characterization indicates a lamellar reaction zone of U and Zr, differing from the arc-melted U-10Zr as a result of rapid consolidation of SPS at lower temperature and short durations. The thermal conductivity of U10Zr with different porosities are also measured. Here this work demonstrates the success in manufacturing new metallic fuel forms with controlled porosities and pore distribution, which can be used as model systems to investigate the thermal transfer behavior of metallic fuels in the reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Thermomechanical Processing of Uranium Alloys with 10 and 50 Weight Percent Zirconium

This work focuses on casting and thermomechanical processing for moderate sized (500-1000g) 10% by weight and 50% by weight uranium-zirconium alloys. Three castings of uranium – 10wt% zirconium and a fourth casting of uranium – 50wt% zirconium were completed using different castings processes. The first casting process relied on only induction mixing within the VIM system thereby eliminating the need for an arc-melting feedstock preparation step. The second casting process used the arc-melting process prior for feedstock to the same VIM system. In this study, the induction mixing process alone with a graphite crucible appears insufficient for the fabrication of UZr alloys. Graphite is suitable with the use of master alloy UZr feedstock produced by arc-melting. There was a moderate increase of approximately 100 ppm of carbon within the U10Zr alloys. However, there was a near 1000 ppm increase of carbon in the U50Zr alloy. This carbon content is considered too high for forming processes, and therefore, warrants the use of a ceramic crucible for UZr castings near 50wt% zirconium. Zirconia does not appear suitable for UZr castings near 50wt% zirconium. The use of Beryllia or Thoria may be a more suitable option. However, due to the significantly lower liquidus and lower zirconium content, Zirconia crucibles do appear viable for carbon reduction in the U10Zr system. Two thermomechanical processes are also studied in this work - hot extrusion of the U50Zr system and heat treatment in an argon atmosphere. This work demonstrated that extrusion of the U50Zr alloy near 680°C is a viable choice even with +1000 ppm carbon. Extrusion of the U50Zr system near 630°C was unsuccessful and does not appear viable unless significant force and tooling strength is available. There appears to be a moderate increase in extrudate hardness when compared to as-cast. Heat-treatment reduced the hardness of as-cast alloys in the U10Zr castings as well as resolve some variance in the microstructures. However, for the U50Zr billet that did not successfully extrude at 630°C, heat treatment at 900°C for 96 hours did not have a significant impact on hardness or microstructure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Degradation and Failure Phenomena of Advanced Reactor Fuel Concepts: Sodium-Cooled Fast Reactor Metallic Fuel

The U.S. Nuclear Regulatory Commission (NRC) is anticipating licensing applications and commercial use of new fuel types in advanced nuclear power reactors that would be designed and built in the United States. Pacific Northwest National Laboratory (PNNL) is providing technical assistance to the NRC related to the newly proposed nuclear fuel and cladding designs that would be deployed in these reactors. This report focuses specifically on the metallic fuel that is being considered for sodium-cooled fast reactors and specifically on mechanisms that would cause damage or failure to the fuel under reactor operating conditions and design basis accident conditions. There is historic experience with both metallic and oxide fuels in experimental sodium-cooled fast reactors, but this report will focus solely on metallic fuel. Currently two U.S.-based reactor designers are engaged with the NRC in the application or pre-application review and considering a sodium-cooled fast reactor. TerraPower is engaged with NRC in pre-application review of its Natrium reactor. The current design for this fuel uses a sodium-bonded uranium-10wt% zirconium (U10Zr) fuel clad in HT9 stainless steel. ARC Clean Technology is engaged with NRC in pre-application review of its ARC-100 reactor. The current design for this fuel uses a sodium-bonded uranium-10wt% zirconium (U10Zr) fuel with steel cladding. This report will focus on this fuel system specifically, with broader information given regarding other metallic fuel systems with other stainless steel alloy claddings. To support the NRC’s readiness efforts, this report will identify and discuss degradation and failure modes of metallic fuel concepts for sodium-cooled fast reactors, including fuel performance characteristics that may not be addressed within existing regulatory documents.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

A machine-learning-aided data recovery approach for predicting multi-material thermal behaviors in advanced test reactor capsules

Instrumented experiments conducted at test reactors are essential to the deployment of new advanced reactor systems. Designing new experiments and generating data on specific reactor conditions require significant investments in terms of both time and cost. Finite element analysis software can be used to create high-fidelity models of experiment environments in order to support the actual experiments, but computation time remains a concern in terms of applying outcomes to real-time usage of data (e.g., a digital twin [DT]). Here, the present research proposes a machine-learning (ML) aided approach to making temperature and displacement predictions based on the thickness of the outer gas gap on the experimental capsule used for in-pile demonstration of a novel new thermal conductivity probe in the Advanced Test Reactor (ATR). This capsule consisted of U10Zr fuel, a rodlet, sodium, and inner and outer capsules. Gas gaps existed between the fuel and the rodlet, and between the inner and the outer capsule. The learning data pertained to an experimental capsule's radial distributions of temperature and displacement, as obtained based on Abaqus and the physical features. For the first step of ML sequence, the temperature was predicted using three positional parameters. Next, the displacement was predicted using seven additional parameters. Each physical feature was normalized in order to be both nondimensional and standardized. The temperature and displacement predictions showed good agreement with the simulation results in all cases involving interpolation and extrapolation. Furthermore, data similarity enhancement increased the similarity between the training and the target data, thereby increasing the predictive accuracy of the ML models. In certain extrapolation cases involving limited original ML model accuracy, data similarity enhancement and data recovery was able to somewhat improve this accuracy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Design of a first-of-A-kind instrumented advanced test reactor irradiation Capsule experiment for In situ thermal conductivity measurements of metallic fuel

Metallic fuel undergoes dramatic microstructural changes early in life due to fission gas swelling until ~2–3 at% burnup which affects the conductivity of the material, however the evolution of metallic fuel thermal conductivity during this early phase burnup has never been successfully measured in situ. The Irradiated Material Properties Accelerated Characterization Test (IMPACT) experiment will be the first in a series of experiments to irradiate advanced nuclear metallic fuel specimens with novel embedded thermal conductivity probes in ATR. In the current work the IMPACT experiment final design and supporting analysis is reported in detail. Results are evaluated for various reactor operational conditions to meet the functional requirements of the experiment. Finally, the first iteration of this IMPACT experiment will provide data regarding thermal properties evolution in uranium-zirconium (U10Zr) fuel, but this experiment vehicle is envisioned for future advanced fuels and structural materials irradiations in ATR.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Technoeconomic Design Optimization for Fast Reactors. Part II: Impact of Technoeconomic Constraints on Optimal Design

There is a current drive toward optimizing reactors, particularly small/micro reactors to minimize cost and maximize performance. Previous work has investigated the development of technoeconomic workflows for the design optimization of pool-type fast reactors that aim to deploy into district energy grids. Initial scoping studies verified that the workflow was capable of capturing design trends throughout a variety of design configurations and problem formulations while remaining sufficiently flexible. In this paper, this methodology is applied to understand how cost functions and technoeconomic constraints can drive optimal reactor design. Specifically, the UPu10Zr-fueled fast reactor model from Part I is adapted to include changes in the fissile content limits, control rod worth limits, control rod drive cost, and assumed fuel form. In the case of constraint relaxation at fixed power (fissile content and control rod worth limits), cost sensitivities of 5% to 10% were uncovered. Multi-objective optimization at varying reactor power levels with individualized control rod drives for each assembly (as opposed to one operational and one safety drive) increased cost by $\$10$ to $\$25$ million and substantially altered the optimal core geometry, favoring geometries with substantially fewer control rod placements relative to baseline optimization. Finally, a multi-objective optimization was performed at varying power levels with the fuel form overhauled to metallic, high-assay low-enriched uranium–based U10Zr with more refined fuel cost models. In the case of uranium fueling, the costs increased by at least $50 million relative to the baseline case. Furthermore, economic fuel zoning and lower reactivity swing cores were recovered. Each case serves to demonstrate the value of applying technoeconomic workflows to initial reactor design scoping studies to better understand the trade-off for a proposed concept between different design options.

Argonne Reactor Computation (ARC) codes↗
DOE OSTI2023

Machine-Learning-aided Approach for Predicting the Thermal Expansion Behaviors in Advanced Test Reactor Capsules (NURETH-20 full paper)

Instrumented experiments at test reactors are essential to deploying new advanced reactor systems. Designing new experiments and generating data on specific conditions require both time and cost investment. A high-fidelity model of the experiment environment can be created using finite element analysis software to support the actual experiments, but computation time is still a concern in applying outcomes to real-time usage (e.g., a digital twin). This research proposes a machine-learning-aided approach to temperature and displacement predictions, based on the thickness of the outer gas gap on the experimental capsule used for the in-pile demonstration of a novel thermal conductivity probe in the Advanced Test Reactor. The capsule consisted of U10Zr fuel, a rodlet, sodium, and inner and outer capsules. There were gas gaps between the fuel and rodlet and between the inner and outer capsule. The learning data consisted of an experimental capsule’s radial distributions of temperature and displacement, as obtained from Abaqus and the physical features. For the first step, temperature was predicted using three positional parameters. Then the displacement was predicted using six different positional parameters. Each physical feature was normalized to be both nondimensional and standardized. The temperature and displacement predictions showed good agreement in all cases involving interpolation and extrapolation. Also, data similarity enhancement increased the similarity between training and target data increasing the predictive accuracy of machine-learning models. In some cases of extrapolation, the accuracy of the machine-learning model showed limited performance, but still data similarity enhancement improved the accuracy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

A Fast Reactor Irradiation Experiment Design in the ATR

Modern modeling techniques were used to investigate a proposed method for fast neutron irradiations in an existing thermal-spectrum reactor, the Advanced Test Reactor (ATR). This method builds upon pre-existing ideas, where fast flux is increased by surrounding the specimens with fissionable “booster fuel” but diverges from historical approaches by using an already developed fuel element design used in the Belgian Reactor 2 (BR2) as the booster fuel while leveraging modern 3-D modeling and simulation techniques. Design evaluations and neutronics simulations were performed to evaluate the performance of a BR2 fuel element irradiated in an ATR flux trap with test pins in the central channel of the BR2 fuel element. These efforts have yielded promising results. Adding a BR2 fuel element in the northeast (NE) flux trap of ATR was predicted to result in a 150% increase to the incident fast neutron flux with a fast (>0.1 MeV) to thermal (<0.625 eV) neutron flux ratio ranging from approximately 50 to 150, dependent on the material used for thermal neutron filtering and volume of moderator within the central channel of the BR2 element. The predicted annual fast neutron fluence (>0.1 MeV) ranges from 7.9 × 1021 to 9.1 × 1021 n/cm2. Given the relatively large fast to thermal neutron flux ratio, the calculated radial power profiles within 4.3 mm outer diameter U10Zr fueled specimens irradiated within the BR2 booster fuel element are adequate representations of those within fast neutron reactors. The predicted radial power profiles are not flat, but they are more prototypic than those seen in advanced fuels tests which began in ATR in 2003. Another distinct advantage of this experiment design is that full-scale test pins can be irradiated to augment the ongoing series of reduced scale advanced fuels tests. The proposed experiment design irradiated within a BR2 fuel element in a flux trap of ATR offers an improved alternative to the current testing of advanced reactor fuels in ATR. Selected results from this design evaluation are presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

SEM Milestone Report for MARMOT Validation Project

MARMOT is a meso-scale fuel code under development by NEAMS designed to predict the microstructure evolution of fuel materials to determine updated thermal and mechanical property models. These updated models can be used by engineering scale codes such as BISON. To support its development and validation the MARMOT Validation Project (MVP) was initiated and consists of extensive microstructure and thermal characterization of U-10Zr fuel material before and at discreet levels of irradiation. This report summarizes the SEM and EDS characterization of the lowest burnup samples (1.5% FIMA) and how they compare to pre-irradiation SEM and EDS.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗