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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Advanced Fuels Campaign Execution Plan

The Advanced Fuels Campaign (AFC) Execution Plan outlines the strategy, mission, scope, near-term and long-term goals, structure, and organization associated with nuclear fuels and materials research, development, and demonstration activities within the Department of Energy’s (DOE) Nuclear Fuel Cycle and Supply Chain (NFCSC) program. NFCSC has been given responsibility to identify and mature advanced fuel technologies for the DOE using a science-based approach, focused on developing a fundamental understanding of nuclear fuels and materials to drive development of integrated nuclear fuel and materials technology. This science-based approach combines theory, experiments, and multiscale modeling and simulation to achieve a predictive understanding of relevant behaviors ranging from fuel fabrication processes (and their resulting fuel microstructures) through fuel/cladding performance under irradiation (in contrast to more empirical, observation-based approaches frequently used in fuel performance modeling and fuel qualification). The traditional scope of AFC includes the evaluation and development of multiple fuel forms to support two fuel cycle options: once-through and full recycle. The word “fuel” is used generically to include conventional fuels, transmutation targets, and any associated cladding or duct materials. The once-through fuel cycle addresses advanced light water reactor fuels with enhanced performance, extended burnup, and reduced waste generation. In fiscal year (FY) 2012, AFC’s scope expanded to include research, development, and demonstration (RD&D) for light water reactor (LWR) fuels with enhanced accident tolerance. Fuel fabrication activities include the development of innovative methods to enhance process efficiencies, reduce waste, and improve control over as-fabricated fuel microstructural properties to achieve desired in-reactor performance. Using modern modeling and simulation approaches, the objective is to predict fresh fuel properties given the feedstock characteristics and fabrication process parameters. The performance-related activities include small-scale, in-reactor, and out-of-reactor phenomenological testing (distinct from, but synergistic with, integral prototypic testing) and extensive, quantitative characterization (focusing on characterization of fuel and cladding materials at the scale of microstructure) both before and after testing. Larger-scale, prototypic experiments are conducted in concert with phenomenological testing to drive a Fuel Development and Qualification program, incorporating a fundamental understanding of fuel behavior performance characteristics. Then, using the tools developed under the productive science-based approach, fuels will be optimized to meet specific performance requirements, thereby minimizing the need to repeatedly perform large-scale, integral experiments over a wide parametric range as a means of experimental exploration. Two significant initiatives are underway within AFC. First, a gap analysis completed in early FY 2019 identified critical irradiation testing needs that are lacking within the national light water reactor (LWR) fuels testbed since the shutdown of the Halden Reactor in 2018. The identified gaps are for instrumented, prototypic testing of LWR fuels, especially under boiling water reactor conditions, ramp conditions, and conditions leading to fuel failure; these needs exist for supporting current LWR fuels and their possible extension to higher burnups, but are especially urgent relative to near-term development and qualification of accident-tolerant fuels. Recommendations that resulted from the Halden Gap Analysis focused on enhancements at Advanced Test Reactor (ATR) and Transient Reactor Test Facility (TREAT) to fill gaps in testing capabilities relative to these needs. Second, a concerted effort to develop and demonstrate a systematic approach to accelerating the development, testing, and qualification of new fuel systems has been initiated. This is highlighted by a test strategy that combines the considerable advances in multiscale, mechanistic fuel modeling of recent years with a MiniFuel separate effects test program in the High Flux Isotope Reactor (HFIR) and a Fission Accelerated Steady-state Testing (FAST) semi-integral accelerated test program in ATR. This approach is being tested/demonstrated using the metallic fuel system, but if successful it is expected to be extensible to multiple fuel types and diverse applications. This document includes an overview of the NFCSC program, a definition of science-based development of nuclear fuels, near-term goals for Advanced LWR fuels (ALFs), and longer-term goals for Advanced Reactor Fuels (ARFs) RD&D. This includes the activities that will be conducted to achieve success toward the grand challenge, as well as the goals and milestones to be achieved over the next few decades of research and development. Long-term goals are based on the DOE Office of Nuclear Energ

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Active Learning A Neural Network Model For Gold Clusters & Bulk From Sparse First Principles Training Data

Small metal clusters are of fundamental scientific interest and of tremendous significance in catalysis. These nanoscale clusters display diverse geometries and structural motifs depending on the cluster size; a knowledge of this size-dependent structural motifs and their dynamical evolution has been of longstanding interest. Given the high computational cost of first-principles calculations, molecular modeling and atomistic simulations such as molecular dynamics (MD) has proven to be an important complementary tool to aid this understanding. Classical MD typically employ predefined functional forms which limits their ability to capture such complex size-dependent structural and dynamical transformation. Neural Network (NN) based potentials represent flexible alternatives and in principle, well-trained NN potentials can provide high level of flexibility, transferability and accuracy on-par with the reference model used for training. A major challenge, however, is that NN models are interpolative and requires large quantities (similar to 10 4 or greater) of training data to ensure that the model adequately samples the energy landscape both near and far-from-equilibrium. A highly desirable goal is minimize the number of training data, especially if the underlying reference model is first-principles based and hence expensive. In this work, we introduce an active learning (AL) scheme that trains a NN model on-the-fly with minimal amount of first-principles based training data. Our AL workflow is initiated with a sparse training dataset (similar to 1 to 5 data points) and is updated on-the-fly via a Nested Ensemble Monte Carlo scheme that iteratively queries the energy landscape in regions of failure and updates the training pool to improve the network performance. Using a representative system of gold clusters, we demonstrate that our AL workflow can train a NN with similar to 500 total reference calculations. Using an extensive DFT test set of similar to 1100 configurations, we show that our AL-NN is able to accurately predict both the DFT energies and the forces for clusters of a myriad of different sizes. Our NN predictions are within 30 meV/atom and 40 meV/angstrom of the reference DFT calculations. Moreover, our AL-NN model also adequately captures the various size-dependent structural and dynamical properties of gold clusters in excellent agreement with DFT calculations and available experiments. We finally show that our AL-NN model also captures bulk properties reasonably well, even though they were not included in the training data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Closing the Loops on Solar Photovoltaics Modules: An Agent-Based Modeling Approach for the Study of Circular Economy Strategies

Solar photovoltaics (PV) installed capacity have grown exponentially since the early 2000s (average annual growth rate of 50%). With 4,700 GW projected installed capacity by 2050, the volume of PV panels waste is also expected to become substantial. Though renewables are a sine qua non to the establishment of a truly circular economy (CE), the issue arising from their end-of-life management needs to be resolved. The management of PV end-of-life also represent a singular opportunity to create value, from recovered valuable, rare or critical materials (e.g. silver, tellurium, indium). Moreover, the PV case illustrates some of the current barriers to CE; for instance, the need for a common definition of waste (PV are defined as e-waste in the European Union but as general waste in the United States) and potential loss of innovations' advantages (PV average efficiency has continuously grown the past 10 years). In this study, an agent-based modeling (ABM) approach is proposed to simulate PV end-of-life management in the United States. The model explores how the decisions of the various actors involved in handling PV waste affect the quantities of PV that are reused, recycled, or land-filled. In the model, manufacturers, residential, and nonresidential PV owners, installers, and recyclers are represented by agents while governmental policies and regulations are treated as exogenous variables. PV-market data are used to define agents' characteristics (e.g., installed PV capacities or producing costs). Agents' decision rules draw on the literature related to industrial symbiosis (IS) and peoples' waste behaviors as they appear as the most widely used model to implement CE principles at a meso level. Specifically, the concepts of mutual trust between IS actors and knowledge about the IS philosophy are yielded to define the agents' decision process. The primary outputs of the ABM are the costs and volume of waste associated with each end-of-life pathway. Preliminaries results indicate recycling of residential PV is affected by the cost, perceived difficulty of recycling behaviors, and social norms. Moreover, the type of network connecting agents and the initial recycling rate strongly influence results. The model also highlights the crucial role of recycling behavior adoption: in case of early failure of PV, recycled volumes increase by about 40%. This represents an additional 5.7 billion USD from potential recovered silver. Finally, although results for the PV case are presented here, the developed ABM aims at being a general tool for the study of CE strategies and the CE transition. Furthermore, steps of this research include extending the model to encompass circular economy strategies (e.g., design for recycling or lifetime extension) and validating its general architecture from various case studies.

14 SOLAR ENERGY↗
DOE OSTI2025

Uncertainty Quantification Enabled by Automatic Differentiation for Hydrodynamic Simulation of Shock‐to‐Detonation Transition in High Explosives

Quantifying the effects of uncertainty in a reactive burn model on the run-to-detonation time in high explosives (HEs) provides a robust methodology for assessing the probability of an HE failing the IHE qualification standard. Moreover, uncertainty quantification helps evaluate whether the model calibration accurately represents data outside the calibration set. This study uses a specialized hydrodynamic simulation code for modeling detonation to determine the run-to-detonation time of the HE PBX 9502 for various impact velocities. To quickly approximate uncertainties in the model, a surrogate was constructed using a Taylor series expansion centered at the mean of the input parameters. To obtain the sensitivities required for constructing the Taylor series, HYP-percomplex Automatic Differentiation (HYPAD) was implemented. HYPAD is a methodology for infusing existing codes with automatic differentiation capabilities by augmenting variables with one or more imaginary units to compute step-size independent partial derivatives. These derivatives are accurate to machine precision with respect to the implemented numerical algorithm, meaning their accuracy reflects that of the underlying method (e.g., integration or discretization schemes). Using reduced order modeling techniques, the mean and standard deviation of the run-to-detonation time of a shock within PBX 9502 were computed for a number of initial impact velocities. A weighted least squares regression was then performed to obtain a best fit curve and prediction interval for the computed statistics. Historical data points from explosively driven wedge tests were utilized to validate the prediction interval, ensuring its reliability in predicting future outcomes. With this prediction interval and a known safety constraint curve, the most probable point of failure and the probability of failure for the HE PBX 9502 were determined.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

White Paper on Case Study of Safe Installation of Second-Life Energy Storage System

This technical report provides for a case study for the safe installation of a second-life, or repurposed, battery, that has been reconfigured for use as a stationary energy storage systems (ESS). Driven by legislative requirements such as California Senate Bill 615 and projections that retired EV batteries could meet a substantial portion of U.S. grid ESS needs beginning in 2035, the repurposing of EV batteries is anticipated to grow significantly. However, safety concerns arise from the effects of aging, unknown prior usage history, and changes in thermal runaway behavior, which may increase failure risks compared to new batteries. NFPA 855, the predominant U.S. standard for ESS installation, mandates that second-life batteries meet all requirements for new batteries, with repurposers complying with UL 1974 in addition to obtaining UL 9540 and UL 1973 listings. These are certifications that few repurposers have achieved and represent a regulatory barrier to entry for the market as a whole.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

The Long-term Storage of ILW: Building Stores with the Appropriate Environmental Controls - 20294

In the UK, containers for the storage and disposal of intermediate level radioactive waste (ILW) typically use stainless steel due to its excellent mechanical properties and corrosion resistance. The period of interim storage before a disposal facility is available, however, is longer than available engineering experience with stainless steels in relevant environmental conditions. Additionally, after disposal the ability of ILW containers to withstand further periods of exposure to the environment is expected to provide substantial benefits to the operation of a disposal facility and the safety case underpinning its closure. For these reasons, although there have been no instances of failure of stainless steels in indoor storage conditions, a focused R and D programme has been carried out to identify the environmental envelope over which the material does not significantly degrade. In this study we summarise experimental and modelling studies carried out over the last decade to build a solid mechanistic understanding of the corrosion behaviour of stainless steels in indoor atmospheric conditions. We then identify suitable environmental regimes to minimise the risk of degradation processes and explore approaches to monitoring the storage conditions to gain confidence in the long-term performance of the system. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

AGR-5/6/7 Thermal Model with Non-uniform Gas Gaps

Fuel compact temperatures are a crucial factor in assessing irradiation performance of the Tristructural isotropic fuel particles. In the absence of direct measurement, fuel compact temperatures were calculated using a three-dimensional finite element thermal model, which is subject to simulation uncertainty. The most dominant factor in uncertainty of calculated fuel temperature is the gas gap uncertainty due to the nub-to-shell clearance because of fabrication error. A revision to the thermal model was made to examine the most probable offset position for four different dates of interest. The offset position options varied in magnitude and azimuthal direction of offset of the holder top and bottom position. The best-fit offset of the holder is estimated based on the minimum root mean square error of residuals for all operational thermocouples (TCs). From these results, the following conclusions were made: 1) During earlier cycles (162A – 164A) when numerous TCs were still operational, the best-fit offset distance varied in range [0.002 – 0.0035 in.] for both the top and bottom holder while offset azimuthal direction varied widely, especially for the holder bottom. 2) Holder offset led to slightly lower Capsule 1 average temperature, but wider temperature variation (lower minimum and higher peak fuel temperatures). 3) The maximum offset of 0.006 in. to the northwest direction for both the top and bottom holder yielded a much higher temperature than the original peak fuel temperature, which increased from 1422 to 1557 ? (or 135 ? increase). This could be one of the reasons for massive particle failure near the end of Cycle 165A. 4) Even though, the highest temperature at the TC-1-7 tip reached slightly higher than 1000?, the temperature along the TC wire reached as high as 1335? assuming a holder offset of 0.006 in. to the northwest. Consequently, at this temperature nickel from this TC wire could cause particle failures in Capsule 1.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Thermal and electric field driven rf breakdown precursor formation on metal surfaces

The phenomenon of electric breakdown poses serious challenges to the design of devices that operate in high electric field environments. Experimental evidence points toward breakdown events that are accompanied by elevated temperatures and dark current spikes, which is attributed to high-asperity nanostructure formation that enhances the local electric field and triggers a runaway process. However, the exact mechanistic origin of such nanostructures under typical macroscopic operational conditions of electric field and magnetic-field-mediated heating remains poorly understood. In this work, we simulate the evolution of a copper surface under the combined action of the electric fields and elevated temperatures. Using a mesoscale curvature-driven surface evolution model, we show how a copper surface can undergo a type of dynamical instability that naturally leads to the formation of sharp asperities in realistic experimental conditions. Exploring the combined effect of fields and temperature rise, we identify the critical regimes that allow for the formation of breakdown precursors. The results show that thermoelastic stresses, while not essential, can significantly lower the critical electric field required for runaway surface instability, which is consistent with experimental observations that thermal effects can increase breakdown rates. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

BISON Capability, Validation and Demonstration for Reactivity-Initiated Accidents

Reactivity Initiated Accidents (RIA) are design basis accidents that could have adverse impacts on the core coolability. In the unlikely event that sufficient reactivity is inserted into the reactor core by the ejected/dropped control rod, prompt energy deposition into the fuel can occur, which when sufficiently high can lead to fuel rod failure or, at large energy deposition levels, expulsion of UO2 fragments or molten UO2 material from the fuel rod. This results in a release of fission product and fuel into the coolant and has the potential to compromise core coolability and threatening the pressure boundary of the primary coolant system. The design basis RIA is one of the industry challenging problems that the CASL aimed to address; the CASL RIA Challenge Problem Charter [1] states, ?The Pressurized Water Reactor (PWR) Rod Ejection Accident (REA) and Boiling Water Reactor (BWR) Control Rod Drop Accident (CRDA) are postulated accidents with consequences that are important to nuclear safety (fuel rod integrity and core coolability). Currently each reload core design must be analyzed to meet regulatory acceptance criteria. The goal of CASLs ModSim capability for RIA is to model the event at a higher fidelity, with validation to existing tests, to better model the transient neutronics and the progression of the fuel and cladding thermal-mechanical behavior. These improved analytical capabilities can be used to better inform reload core design, limits on fuel assembly discharge burnup, restrictions on placement of fuel in the reactor, control rod insertion limits, operating margin, and performance sensitivities.? In support of that charter, BISON, the fuel performance code has been used to demonstrate the simulation of thermal-mechanical behavior of LWR fuels during a reactivity-initiated accident. The combination of mechanical, thermal, and thermal-hydraulic phenomena all present during an RIA makes a multi-physics code such as BISON a valuable tool for modeling these scenarios. This paper will highlight many of the activities associated with BISON relevant to reactivity-initiated accident capability development and validation efforts. These efforts have been performed under both CASL and the Nuclear Energy Advanced Modeling and Simulation (NEAMS) programs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Value proposition of coatings or new alloys on hammer wear

The goal of this Case Study was to elucidate the value of improving of the life of parts that wear within a system in terms of the additional material cost that it takes to reach the level of improvement. We recognize that the failure limits and system performance are representative of a single system that may or may not exist in the real world, however, our goal of this project was not to provide an answer for a specific system or to provide a full understanding the economics of all potential systems. The analysis was performed using relative changes from the base alloy cost and considered relative improvements in part life in order to generalize the comparison without referencing specific alloys or coatings that might be employed. Ultimately, this work provides a first check of the potential for improving wear characteristics of grinder hammers to provide a meaningful and impactful benefit to biomass preprocessing and conversion systems. Key takeaways include: • Increasing the life of hammers by 3× provides a delivered feedstock cost benefit of approximately $\$2.25$/dry ton assuming that the relative cost of the hammer material of construction is not increased. • The feasible area of relative hammer cost increase ranges from 110% to 122% of the relative life increase, i.e., a 3× life increase can cost 3.66× the cost of the original hammers • Beyond a 3× increase in relative hammer life, little economic benefit is realized • Even when moisture impacts are included, the relationship between relative hammer cost and relative hammer life was reduced only slightly to a range of 108% to 116% • From the simulation we would expect delivered feedstock costs to be within ±$1.10/dry ton, based on the uncertainty analysis

09 BIOMASS FUELS↗
DOE OSTI2023

Machine learning based approach to predict ductile damage model parameters for polycrystalline metals

Damage models for ductile materials typically need to be parameterized, often with the appropriate parameters changing for a given material depending on the loading conditions. This can make parameterizing these models computationally expensive, since an inverse problem must be solved for each loading condition. Using standard inverse modeling techniques typically requires hundreds or thousands of high-fidelity computer simulations to estimate the optimal parameters. Additionally, the time of a human expert is required to set up the inverse model. Machine learning has recently emerged as an alternative approach to inverse modeling in these settings, where the machine learning model is trained in an offline manner and new parameters can be quickly generated on the fly, after training is complete. Here, this work utilizes such a workflow to enable the rapid parameterization of a ductile damage model called TEPLA with a machine learning inverse model. The machine learning model can efficiently estimate the model parameters much faster, as compared to previously employed methods, such as Bayesian calibration. The results demonstrate good accuracy on a synthetic test dataset and is validated against experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Analysis of iron-chromium-aluminum samples exposed to accident conditions followed by quench in the QUENCH-19 experiment

The QUENCH-19 experiment was a first-of-its-kind full-bundle test simulating accident conditions followed by water quench on accident-tolerant fuel (ATF) cladding. Here, a type of FeCrAl(Y) alloy, B136Y3, was developed at Oak Ridge National Laboratory and tested at the Karlsruhe Institute of Technology using Kanthal APM corner rods, a shroud, and Kanthal AF spacer grids. Testing conditions were similar to those in QUENCH-15—which tested ZIRLO cladding behavior—so that B136Y3 and ZIRLO cladding could be compared. QUENCH-19 consisted of an initial pre-oxidation heating followed by a transient. Then, a maximum power hold, which was not present in QUENCH-15, was executed to extend the heating period for the FeCrAl(Y) rods. Finally, a rapid water quench was executed that was similar to emergency core coolant system (ECCS) actuation. Compared with the ZIRLO rods in QUENCH-15, the bundle in QUENCH-19 released significantly less H 2 (9.2 g vs. 47.6 g) and achieved a much lower maximum temperature (1455°C vs. 1880°C). Furthermore, no breakaway oxidation was observed in QUENCH-19. Metallographic mounts revealed that despite the symmetry of the setup, at elevations near the maximum temperature, cladding and thermocouples were heavily damaged, substantial melting and oxidation occurred, and the cladding underwent chemical interaction with the thermocouple sheaths. Additionally, the ZrO 2 spacers detrimentally interacted with the cladding, leading to mixed oxide debris and the full destruction of some rods. Additional failure was found in certain cooler rods that may have risen due to the high thermal expansion coefficient of FeCrAl alloys. This paper presents an analysis of this work, which suggests that FeCrAl cladding can chemically survive anticipated loss-of-coolant accident events followed by rapid ECCS quench if the correct geometry and core design are present.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Calculating Methane Emissions from Offshore Facilities Using Bottom-Up Methods

With changing demands in regulation, understanding methane emissions from offshore oil and gas production infrastructure has become increasingly important. Reported emissions from facilities in the Gulf of Mexico range from zero to thousands of tons of methane per hour, but these is currently no clear understanding of how this range compares to expected emissions from normally operating facilities. To generate realistic emission estimates, we create two bottom-up models that simulate emissions from facilities operating in the Gulf of Mexico. We estimate type 1 prototypical facilities (typically unmanned, older, lower-producing platforms in shallow water with little processing equipment, compressors, or storage tanks) to emit an average of 13 kg CH 4 h −1 , which corresponds to a loss of 2.7% of the average facility production. Type 2 prototypical facilities (continuously manned, higher production and operate in deeper water with processing equipment, oil storage tanks, compressors and power generation) emit an average of 88 kg CH 4 h −1 , which corresponds to a loss of 2.5% of production. The average measured emission from type 1 facilities was 18 kg CH 4 h −1 with a median production loss estimated at 8%. The average measured emission from type 2 facilities was 36 kg CH 4 h −1 with a median production loss estimated at 2.4%. Using emission factors that consider the long-tail emission distribution partly reconciles the difference between modelled and measured emission estimates, but we suggest the current the fugitive emission estimate may be an underestimate and more data on the number and size of fugitive emissions could explain differences between the modelled and measured emission estimate. We suggest the bottom-up approach described here that uses production data coupled with facility equipment could be used to identify facilities that have abnormally large measured emissions, caused by methodological failure or larger than expected fugitive emissions, which should be targeted for further evaluation resulting in remeasurement or identification of source type so that a more accurate estimates can be made on the absolute emission.

bottom-up↗
DOE OSTI2024

Intermediate Principal Stress Effects on the 3D Cracking Behavior of Flawed Rocks Under True Triaxial Compression

Crack initiation, growth, and coalescence in flawed rocks have been extensively studied for 2D (planar, penetrating) flaws under uniaxial/biaxial compression. However, little is known as to the mechanisms and processes of cracking from 3D flaws under true triaxial compression, where the intermediate principal stress (σ 2 ) is distinguished from the major and minor principal stresses. In this work, we systematically investigate the effects of σ 2 on the 3D cracking behavior of rock specimens with preexisting flaws, through the use of mechanistic simulations of mixed-mode fracture in rocks. We explore how two characteristics of σ 2 , namely, (i) its orientation with respect to the flaw and (ii) its magnitude, affect two aspects of the cracking behavior, namely, (i) the cracking pattern and (ii) the peak stress. Results show that the orientation of σ 2 exerts more control over the cracking pattern than the flaw inclination angle. The peak stress becomes highest when σ 1 is parallel to the flaw, whereas it becomes lowest when σ 2 is parallel to the flaw. Also, the effects of σ 2 magnitude are more significant when σ 2 becomes more oblique to the flaw plane. On the basis of our observations, we propose mechanisms underlying the cracking behavior of 3D flawed rocks under true triaxial compression.

58 GEOSCIENCES↗
DOE OSTI2024

Tailoring Carbide Dispersed Steels: A Path to Increased Strength and Hydrogen Tolerance

The use of transition metal carbides is reported for use as a hydrogen trapping mechanism for ferritic and austenitic steel materials. The program combined computational modeling and simulations to guide experiments towards candidate metal carbide traps, both for interfacial and interior trapping. It was found that interfacial trapping is less effective than interior trapping, with the group IVB transition metal carbides being the most effect internal traps with a loss of carbon. The sub-stoichiometric rocksalt structure accommodate the hydrogen atoms in its octahedral interstices. Using percolation theory, carbon loss of approximately 25% or more was sufficient to ensure an interconnected network of vacancies for such trapping from the surface to the internal sites within the carbide. Using this as a guide, the program developed a means to provide a uniform dispersion of ZrC nanoparticles with either Fe or 304L micron-scale powders which was then consolidated by direct current sintering. Electrolytic hydrogen diffusivity studies confirmed the reduction of hydrogen diffusion in the matrix with increasing ZrC content, which was a linear response over the sample range studied (0.01 to 1.0 wt.%). The consolidated material was micro-tensile tested in either a non-hydrogen or hydrogen charge condition and compared to a control with no carbides. Additions up to 0.05 wt.% ZrC increased the yield strength with no loss in ductility in either the non-hydrogen or hydrogen tested condition. ZrC concentrations above this amount further increased the yield strength at the expense of ductility. While these samples had a lower absolute ductility value prior to failure, the relative change in ductility between the non-hydrogen and hydrogen charge states was less for the carbides than that of the control. Metal-rich ZrC nanoparticles were fabricated through a conformal coating process yielding ZrC0.66 particles that were then incorporated into a metal matrix. Notch fatigue testing in a hydrogen environment was conducted where the number of cycles to failure was found to be less in the control than that of the carbide addition. However, the spread in experimental data and the number of samples tested limits a conclusive outcome based on defects noticed in the gauge section of all the powder processed samples. The collective outcomes of this report provide further insight into the mechanisms by which carbides act as hydrogen traps; a means to process such carbides through powder metallurgy; and their associated mechanical performance in either a non-hydrogen or hydrogen-charged condition.

08 HYDROGEN↗
DOE OSTI2024

Structural and mechanical properties of monolayer amorphous carbon and boron nitride

Amorphous materials exhibit various characteristics that are not featured by crystals and can sometimes be tuned by their degree of disorder (DOD). Here, we report results on the mechanical properties of monolayer amorphous carbon (MAC) and monolayer amorphous boron nitride (maBN) with different DOD. The pertinent structures are obtained by kinetic-Monte-Carlo (kMC) simulations using machine-learning potentials (MLP) with density-functional-theory (DFT)-level accuracy. An intuitive order parameter, namely the areal fraction F x occupied by crystallites within the continuous random network, is proposed to describe the DOD. We find that F x captures the essence of the DOD: Samples with the same F x but different sizes and arrangements of crystallites, obtained using two distinct kMC procedures, have virtually identical radial distributions functions as well as bond-length and bond-angle distributions. Furthermore, by simulating the fracture process with molecular dynamics, we found that the mechanical responses of MAC and maBN before fracture are mainly determined by F x and are insensitive to the sizes and specific arrangements and to some extent the numbers and area distributions of the crystallites. The behavior of cracks in the two materials is analyzed and found to mainly propagate in meandering paths in the CRN region and to be influenced by crystallites in distinct ways that toughen the material. Furthermore, the present results reveal the relation between structure and mechanical properties in amorphous monolayers and may provide a universal toughening strategy for 2D materials.

2-dimensional systems↗
DOE OSTI2024

Impact of LWR assembly structural features on cladding burst behavior under LOCA conditions

This provides an initial scoping study on clad balloon and burst behavior for burnup extension of reactor fuel. The associated issues with burnup extension are fuel fragmentation, relocation, and dispersal in the event of cladding failure. The general finding of this work is that the structural features, spacer grids and mixing vanes, locally suppress cladding deformation but have little impact on the overall clad performance during loss-of-coolant accidents. The work detailed in a previous report by Capps et al. focused on core optimization via neutronics, thermal hydraulics and thermomechanical analysis for burnups beyond 62 GWD/tU and enrichments above 5%. Uncertainty of fuel fragmentation relocation and dispersal in high-burnup rods during accident conditions was also investigated. The dispersal aspect of fuel fragmentation depends on cladding rupture. Thus, assessing uncertainties in the rupture behavior is helpful in estimating the dispersal of high-burnup fuel. This study builds on the previous work by assessing the impact of assembly structural features on cladding balloon and burst behavior in a full-length fuel rod. In this work, the BISON fuel performance code was used to generate 2D radial and height meshes containing structural features commonly used in nuclear fuel assemblies. First, meshes were generated with spacer grids. Results were then compared to the cladding burst temperature and balloon strain results from the previous work. A mesh sensitivity study was performed to ensure that mixing vanes and spacer grid effects were appropriately considered, resulting in a more refined mesh than the previous study. The balloon deformation and burst times of the cladding were compared to the original case. Consideration was also given to the effect of rod initial pressure. In conclusion, 3D quarter rod simulations were also performed and found good agreement with the 2D simulations in clad deformation and reasonable agreement in burst times.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Microstructure based modeling of friction stir welded joint of dissimilar metals using crystal plasticity

We report the friction stir welding (FSW) process shows promising results in joining dissimilar metals which are otherwise almost impossible to join using traditional welding techniques. Being a new technique, the deformation and the failure mechanism of the joints made by the FSW process needs to be investigated. In this work, a joint between AZ31 Mg alloy and DP590 steel is modeled using phenomenological crystal plasticity formulation on the mesoscale in the form of a representative volume element (RVE). The interface of the two materials is modeled using a cohesive zone model. A parametric study has been performed to understand the effect of grain size and interface fracture toughness as well as strength on the mechanical performance of the joint. It was found that the grain size of AZ31 Mg alloy, as well as DP590 steel, has little effect on the overall joint performance. On the other hand, interface fracture toughness and strength have a significant impact on the mechanical properties of the joint

36 MATERIALS SCIENCE↗