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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Probing UV-sensitive Pathways for CN and HCN Formation in Protoplanetary Disks with the Hubble Space Telescope

The UV radiation field is a critical regulator of gas-phase chemistry in surface layers of disks around young stars. In an effort to understand the relationship between photocatalyzing UV radiation fields and gas emission observed at infrared and submillimeter wavelengths, we present an analysis of new and archival Hubble Space Telescope (HST), Spitzer, ALMA, IRAM, and SMA data for five targets in the Lupus cloud complex and 14 systems in Taurus-Auriga. The HST spectra were used to measure Lyα and far-UV (FUV) continuum fluxes reaching the disk surface, which are responsible for dissociating relevant molecular species (e.g., HCN, N{sub 2}). Semi-forbidden C ii] λ2325 and UV-fluorescent H{sub 2} emission were also measured to constrain inner disk populations of C{sup +} and vibrationally excited H{sub 2}. We find a significant positive correlation between 14 μm HCN emission and fluxes from the FUV continuum and C ii] λ2325, consistent with model predictions requiring N{sub 2} photodissociation and carbon ionization to trigger the main CN/HCN formation pathways. We also report significant negative correlations between submillimeter CN emission and both C ii] and FUV continuum fluxes, implying that CN is also more readily dissociated in disks with stronger FUV irradiation. No clear relationships are detected between either CN or HCN and Lyα or UV-H{sub 2} emission. This is attributed to the spatial stratification of the various molecular species, which span several vertical layers and radii across the inner and outer disk. We expect that future observations with the James Webb Space Telescope will build on this work by enabling more sensitive IR surveys than were possible with Spitzer.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

First-Principles Modeling of the Repassivation of Corrosion Resistant Alloys: Part I. O and Cl Adsorption Energy

To understand the mechanism of repassivation, a key process that controls the performance of corrosion resistant alloys (CRAs), it is useful to obtain some fundamental parameters that describe the atomistic processes. Oxygen and chlorine adsorption energies were systematically calculated with density functional theory for Ni-22Cr alloys with seven different solute elements: Co, Cu, Fe, Mn, Mo, Ru and W. All elements other than Cu enhance both O and Cl adsorption to alloy surfaces. Cr has the strongest effect among these elements. Surface configurations that give stronger O adsorption also tend to give stronger Cl adsorption. While this makes it difficult to differentiate the effect of these solute elements on the oxidation/repassivation tendency of alloys, these fundamental properties provide the foundation for higher scale models that could be used to study the oxidation process during corrosion and potentially inform the design of CRAs. Bader charge analysis reveals a strong relationship between the adatom adsorption energy and the Bader charges of both O and Cl adatom. In conclusion, the work function of alloy surfaces is increased by O while decreased by Cl, suggesting that Cl adsorption can have an intrinsic negative impact on corrosion resistance by decreasing the barrier to electron transfer.

36 MATERIALS SCIENCE↗
DOE OSTI2022

MSU Disentanglement Analysis Software

This software is used to disentangle the forced-versus-unforced components of tropospheric temperature change over the satellite era (after 1979) using maps of surface temperature change as a predictor. In general, the software assembles training datasets (from pre-computed surface temperature trend maps and domain averaged tropospheric warming rates), trains statistical/machine learning (ML) algorithms, applies the trained statistical/ML model to climate model data and observations, and then saves the results. A leave-one-out approach is used in which the statistical/ML models are iteratively trained on (N- 1) climate model and then applied to the remaining climate model (and observations). Each model includes a large ensemble (i.e., >10) of model simulations. The software relies on scikit-learn ridge regression, PLS regression, and neural network algorithms.

Po-Chedley, StephenD↗
DOE OSTI2020

Opportunities for Using the Industrial Assessment Center Database for Industrial Water Use Analysis

The manufacturing sector accounted for approximately 5–6% of total U.S. water use in 2015. Of that amount, 75–80% is self supplied withdrawal from surface-water and groundwater sources and the remainder is from public water supplies. Although manufacturing facilities commonly locate in water-scarce areas, water scarcity still poses a great risk to the manufacturing sector. Reliable water is necessary for any facility that relies on it for process and comfort cooling, cleaning, employee use, and steam generation. One of these barriers to water efficiency is the lack of reliable data on overall U.S. industrial water use—how it is used and the quantities required for each sector. If a facility cannot be easily compared with a facility of similar size and sector, knowing if it is effectively using water conservation best practices is difficult. One potential source of industrial water use data is the U.S. Department of Energy (DOE)–sponsored Industrial Assessment Centers (IACs). IACs are university-based organizations that provide free audits to small- and medium-sized manufacturing facilities to identify productivity improvement and waste and energy reduction opportunities. The IACs also maintain a database of all the audits conducted, which currently holds more than 19,267 assessments and 145,000 recommendations (as of July 24, 2020). This database also contains energy utility (electricity, natural gas, and other fuels) and water utility data, making it a potential data source for industrial water use. This report attempts to create regression models to predict a small- or medium-sized industrial facility’s annual water use or cost based on its industrial subsector and several possible relevant variables. Using data collected by IAC assessments, models for several industrial subsectors were generated via stepwise regression techniques to determine which variables (annual sales, number of employees, facility/plant area, annual production hours, and a water stress metric) are relevant.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Numerical Analysis of High-Order Modes in SRF Resonators for Particle Accelerators

Over the past decades, superconducting technology has rapidly evolved towards high accelerating gradients and low surface resistance, making it possible to operate particle accelerators with high average beam currents and large duty factors. However, RF losses due to coherent excitation of the HOM become the limiting factor for these regimes. Unlike the cavity operating mode, which is tuned separately, the HOM parameters can significantly vary from one cavity to another due to finite mechanical tolerances during the manufacturing process. Thus, it is of utmost importance to know the HOM parameter spread in advance in order to predict unexpected cryogenic losses, overheating of beam line components and maintain stable beam dynamics. In this paper, we present a method for generating cavity geometry with an arbitrary spread of mechanical imperfections and numerically evaluating HOM statistics. Knowing the spread of HOM parameters, we calculated the probability of resonant HOM losses in SRF accelerating cavities used in CW beam current machines such as the PIP-II and LCLS-II linacs, as well as for the SRF crab-cavity for the ILC project. Finally, we present experimental results of HOM spectra measurements in hundreds of 1.3 GHz cavities installed in LCLS-II cryomodules. Studying the effects of HOM excitation results in specifications of the SRF cavity and cryomodule and can significantly impact the efficiency and reliability of the machine operation.

Lunin, Andrei [Fermilab] (ORCID:0000000290096792)↗
DOE OSTI2024

Analysis of Tank 38H (HTF-38-24-53, -56) and Tank 43H (HTF-43-24-54, -55) Samples for Support of the Enrichment Control and Corrosion Control Programs

Savannah River National Laboratory analyzed samples from Tank 38H and Tank 43H to support the Enrichment Control Program (ECP) and Corrosion Control Program (CCP). The results indicate the concentrations of most soluble species in the Tank 38H surface sample increased from the previous Tank 38H surface sample. The current Tank 38H subsurface sample shows similar Na, free hydroxide, and anions in comparison to the previous subsurface sample. However, the 38H subsurface sample shows lower concentrations of Al, Ca, Fe, Mn, and Si in comparison to the previous Tank 38H subsurface sample. Measurement of the wt.% insoluble solids in the Tank 38H subsurface sample and associated uncertainty analysis indicates that the calculated average wt.% insoluble solids is 0.45 ± 0.75 wt.%. Significant differences in the concentrations of major components between the Tank 38H surface and subsurface samples indicate significant stratification of solution species between these two locations within Tank 38H.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

A Novel Dew Point Meter: Application to the Measurement of the Sulfuric Acid Dew Point for Combustion Flue Gas

Accurate knowledge of acid dew point is essential for industrial and applied combustion applications. Sulfur in the fuel or raw materials is converted to sulfur dioxide (SO2) during combustion, and a portion of the SO2 is oxidized to sulfur trioxide (SO3). The SO3 will react to form H2SO4 vapor when in the presence of water vapor. Even with just trace levels of H2SO4 vapor in the gas phase (1-10 ppm), the dew point can reach 100°C and higher. To avoid acid condensation and the resulting corrosion on heat recovery equipment, plant engineers must ensure that surface temperatures are above the acid dew point, but this decreases the efficiency of thermal energy recovery. Thus, there is a trade-off between minimizing equipment corrosion and maximizing thermal energy recovery, and the acid dew point is a key parameter for this optimization. Commercially available acid dew point meters use electric conductivity sensors. These sensors are known to greatly underestimate the dew point due to their low sensitivity. In addition, no validation testing has been reported for these units and they are often expensive. In this work, we analyze the theory of the sulfuric acid condensation and develop a novel dew point meter based on this analysis. The meter consists of a novel optical instrument that is designed to monitor the slightest appearance of condensation on a hydrophobic window surface as the surface temperature of the window is slowly decreased. In this way, an accurate measurement of the dew point is obtained under a wide range of concentrations. The basis of the instrument is that a collimated beam from a diode laser will generate forward scattered light when the beam encounters surface condensate, and a sophisticated array detector is used to sensitively monitor the onset of light scattering. The measurement procedures are established to rapidly find the acid dew point, while minimizing error. Further, to calibrate the dew point meter we developed a calibration system based on a liquid bubbler that can generate a stable gas flow with a known sulfuric acid dew point. Test results show that the dew point meter can accurately measure acid dew point over a wide range. For H2SO4 vapor concentrations as low as 6 ppm the acid dew point is measured with an error of only ~1°C. To demonstrate the versatility of this instrument, the dew point meter was adapted for use with a high-pressure flow cell to allow for measurements of the dew point of flue gas from pressurized oxy-fuel combustion in a 100 kWth pressurized reactor.

Cheng, Mao↗
DOE OSTI2023

Investigation of process history and underlying phenomena associated with the synthesis of plutonium oxides using Vector Quantizing Variational Autoencoder

Accurate, high throughput, and unbiased analysis of plutonium oxide particles is needed for analysis of the phenomenology associated with process parameters in their synthesis. Compared to qualitative and taxonomic descriptors, quantitative descriptors of particle morphology through scanning electron microscopy (SEM) have shown success in analyzing process parameters of uranium oxides. Among other candidates, a neural network called a Vector Quantizing Variational Autoencoder (VQ-VAE) has shown the ability to quantitatively describe particle morphology to attain >85% accuracy in identifying uranium oxide processing routes. We utilize a VQ-VAE to quantitatively describe plutonium dioxide (PuO 2 ) particles created in a designed experiment and investigate their phenomenology and prediction of their process parameters. PuO 2 was calcined from Pu(III) oxalates that were precipitated under varying synthetic conditions that related to concentrations, temperature, addition and digestion times, precipitant feed, and strike order; the surface morphology of the resulting PuO 2 powders were analyzed by SEM. A pipeline was developed to extract and quantify useful image representations for individual particles with the VQ-VAE, then further reduce the dimensionality of the feature space using a bottlenecking neural network fit to perform multiple classification tasks simultaneously. The reduced feature space could predict process parameters with greater than 80% accuracies for some parameters with a single particle. They also showed utility for grouping particles with similar surface morphology characteristics together. Both the clustering and classification results reveal valuable information regarding which chemical process parameters chiefly influence the PuO 2 particle morphologies: strike order and oxalic acid feedstock. Doing the same analysis with multiple particles was shown to improve the classification accuracy on each process parameter over the use of a single particle, with statistically significant results generally seen with as few as four particles in a sample.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Early-stage uranium-hydrogen corrosion kinetics and mechanism

Research into the early-stage uranium-hydrogen degradation mechanism lacks unified interpretation and understanding due to inadequate temporal and spatial characterization resolution required to unify reaction observations. In this study, white-light interferometry was adapted to characterize the uranium-hydrogen reaction at a temperature of 50 °C and hydrogen pressure of 13.8 kPa. The uranium surface remained unchanged for 62 min during the hydride induction period before the first hydride blister appeared. This blister was monitored from induction through critical spallation and UH₃ powder release during rapid surface hydriding. The critical spallation dimensions measured for height, diameter, area, and perimeter of the first blister were 1.79 µm, 17.58 µm, 187.7 µm 2 and 59.79 µm. Hydriding growth kinetics were assessed by tracking the first hydride site over the reaction time. Analysis shows that the spall-front velocity of the hydride was changing at a rate of 0.91 µm/min which compares favorably with legacy Sievert’s experiments in literature. Total percentage of the surface area hydrided after 242 min was 42.7%, and post-characterization of the UH 3 powders shows both α-UH 3 and β-UH 3 . This work highlights the strength of characterizing the early-stage uranium-hydrogen reaction using white-light interferometry, but more importantly, unifying the understanding and mechanism of the uranium-hydrogen reaction kinetics.

Materials science↗
DOE OSTI2021

Mechanistic Pathways for the Molecular Step Growth of Calcium Oxalate Monohydrate Crystal Revealed by In Situ Liquid-Phase Atomic Force Microscopy

Calcium oxalate monohydrate (COM) crystal is the most common crystalline component of human kidney stones. The molecular-scale inhibitory mechanisms of COM crystal growth by urinary biomolecules such as citrate and osteopontin adsorbed onto the crystal surface are now well understood. However, the pathways by which dissolved calcium and oxalate ions are incorporated into the molecular step of the COM crystal surface, leading to COM crystal growth—a prerequisite to be elucidated for developing effective therapeutics to inhibit COM stones—remain unknown. Here, using in situ liquid-phase atomic microscopy along with a step kinetic model, we reveal the pathways of the calcium and oxalate ions into the COM molecular step via the growth speed analysis of the molecular steps with respect to their step width at the nanoscale. Our results show that, primarily, the ions are adsorbed onto the terrace of the crystal surface from the solution—the rate-controlling stage for the molecular step growth, i.e., COM crystal growth—and then diffuse over it and are eventually incorporated into the steps. This primary pathway of the ions is unaffected by the model peptide D-Asp6 adsorbed on the COM crystal surface, suggesting that urinary biomolecules will not alter the pathway. These new findings rendering an essential understanding of the fundamental growth mechanism of COM crystal at the nanoscale provide crucial insights beneficial to the development of effective therapeutics for COM kidney stones.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

In Situ Synthesis of Graphene-Coated Silicon Monoxide Anodes from Coa-Derived Humic Acid for High-Performance Lithium-Ion Batteries

Silicon monoxide (SiO) is attaining extensive interest amongst silicon-based materials due to its high capacity and long cycle life; however, its low intrinsic electrical conductivity and poor coulombic efficiency strictly limit its commercial applications. Here low-cost coal-derived humic acid (HA) is used as a feedstock to synthesize in-situ graphene-coated disproportionated SiO (D-SiO@G) anode with a facile method. HRTEM and XRD confirm the well-coated graphene layers on an SiO surface. Scanning Transmission X-ray Microscopy (STXM) and X-ray Absorption Near-Edge Structure (XANES) spectra analysis indicate that the graphene coating effectively hinders the side-reactions between the electrolyte and SiO particles . As a result, the D-SiO@G anode presents an initial discharge capacity of 1937.6 mAh g -1 at 0.1 A g -1 and an initial coulombic efficiency (ICE) of 78.2%. High reversible capacity (1023 mAh g -1 at 2.0 A g -1 ), excellent cycling performance ( 72.4% capacity retention after 500 cycles at 2.0 A g -1 ), and rate capability (774 mAh g -1 at 5 A g -1 ) results are substantial. Full coin cells assembled with LiFePO 4 electrodes and D-SiO@G electrodes display impressive rate performance. These results indicate a promising potential for practical use in high-performance lithium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

Nanoscale Antiferromagnetic Domain Imaging using Full-Field Resonant X-ray Magnetic Diffraction Microscopy

The physical properties of magnetic materials frequently depend not only on the microscopic spin and electronic structures, but also on the structures of mesoscopic length scales that emerge, for instance, from domain formations, or chemical and/or electronic phase separations. However, experimental access to such mesoscopic structures is currently limited, especially for antiferromagnets with net zero magnetization. Here, full-field microscopy and resonant magnetic X-ray diffraction are combined to visualize antiferromagnetic (AF) domains of the spin–orbit Mott insulator Sr 2 IrO 4 with area over ≈0.1 mm 2 and with spatial resolution as high as ≈150 nm. With the unprecedented wide field of views and high spatial resolution, an intertwining of two AF domains on a length comparable to the measured average AF domain wall width of 545 nm is revealed. This mesoscopic structure comprises a substantial portion of the sample surface, and thus can result in a macroscopic response unexpected from its microscopic magnetic structure. In particular, the symmetry analysis presented in this work shows that the inversion symmetry, which is preserved by the microscopic AF order, becomes ill-defined at the mesoscopic length scale. We report this result underscores the importance of this novel technique for a thorough understanding of the physical properties of antiferromagnets.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Complete Phase Transformation of Ir Nanowire Network into Defect-Rich Oxide Catalyst for High-Performance PEM Water Electrolysis

Iridium-based catalysts remain the most reliable option for the oxygen evolution reaction (OER) in proton exchange membrane water electrolyzers (PEMWEs). However, their high cost and limited performance represent critical barriers to the commercialization of this green hydrogen production technology. Herein, we report the creation of a metallic Ir nanowire network (IrNWN), which exhibits superior OER performance through its in-situ transition into an oxide structure with high intrinsic activity. At a low loading of 0.25 mgIr/cm2 in PEMWEs, IrNWN achieved a current density of 3.13 A/cm2 at a cell voltage of 1.8 V, outperforming the commercial Ir-based catalyst and surpassing the Department of Energy (DOE) 2026 technical target. Moreover, the high activity of IrNWN was maintained for 900 hours in a durability test at 2 A/cm2, showing a low degradation rate of 0.042 mV/hour. Structural analysis of the electrochemically oxidized IrNWN revealed the presence of mixed Ir oxidation states and a high density of surface terminal oxygen groups (μ1-O), which contributed to a reduced energy barrier for the rate-determining O-O coupling step.

oxygen evolution reaction↗
DOE OSTI2024

Hydrogen Peroxide‐Induced Overoxidation of Fe−N−C Catalysts: Implications for ORR Activity

Fe−N−C (iron-nitrogen-carbon) electrocatalysts have emerged as promising alternatives to precious metals for the oxygen reduction reaction (ORR), but they remain insufficiently stable for widespread adoption in fuel cell technologies. One plausible mechanism to explain this lack of stability, and the associated catalyst degradation, is oxidative attack on the catalyst surface by hydrogen peroxide, a non-selective byproduct of the ORR. In this work, we perform a detailed analysis of this degradation mechanism, using a combination of periodic Density Functional Theory (DFT) calculations and ab-initio molecular dynamics (AIMD) simulations to probe the thermodynamics and kinetics of hydrogen peroxide activation on a series of candidate active sites for the Fe−N−C catalyst. The results demonstrate that carbon atoms neighbouring FeN 4 active sites can be strongly over-oxidized via formation of hydroxyl or epoxy groups when hydrogen peroxide is present in the electrolyte. In most cases, the interaction between the over-oxidizing groups and the ORR reaction intermediates reduces the ORR activity, and we further propose that the over-oxidized sites are likely precursors to irreversible carbon corrosion and further catalyst deactivation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Catalytic Conversion of Model Compounds of Plastic Pyrolysis Oil over ZSM-5

Mechanistic investigation of the catalytic conversion of model compounds for plastic pyrolysis oil (1-octene, octadiene, octane, and toluene) over ZSM-5 in a fixed-bed reactor was studied. 1-Octene breaks down into smaller olefins, which undergo further cracking, oligomerization, cyclization, and hydrogen transfer to eventually produce benzene, toluene, xylene (BTX), coke, and hydrogen. The effect of contact time on 1-octene conversion was further investigated and compared with thermodynamics analyses to elucidate the reaction network. Under the reaction conditions (500 oC, 1 atm), octadiene undergoes thermal coking, significantly contributing to reactor fouling. The products from octane cracking are similar to the products from 1-octene conversion whereas toluene undergoes disproportionation, dealkylation and coking. The analysis of spent catalyst showed long-chain hydrocarbons created by oligomerization reactions filled the pores and covered the surface of the catalyst. As a result, when mesoporous ZSM-5 is used instead of conventional, product selectivity is maintained for 70 hours in time-on-stream experiments.

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

Elucidating the Impact of Flow on Material-Sensitive Critical Heat Flux and Boiling Heat Transfer Coefficients: An Experimental Study with Various Materials

In this work, steady-state internal flow boiling critical heat flux (CHF) experiments were carried out at 10°C inlet subcooling and atmospheric pressure (84 kPa at an altitude of about 5300 feet) with mass flux ranging from 200 to 2,000 kg/m 2 -s on seven tube materials, including the accident-tolerant fuel cladding candidate FeCrAl (C26M) alloy. At a relatively low flow rate, the sensitivity of CHF to different materials was appreciable (the average difference among the tested materials was 19% at 200 kg/m 2 -s). As the absolute CHF differences stayed constant for higher flow rates, the increased flow rate led to reduced relative CHF differences among the tested materials (average relative difference of 15% at 1,000 kg/m 2 -s). FeCrAl alloy claddings that were oxidized under simulated Light Water Reactor (LWR) conditions yielded CHF comparable to as-received FeCrAl alloy cladding, with less than 1.8% difference. Experimental CHF results imply marginal material sensitivity impacts on the departure from nucleate boiling ratio in steady-state nuclear reactor cores. Yet, for accident progression analysis, material sensitivity may hold importance, as boiling behavior variation at low mass flux is appreciable. Macroscopic material parameters (surface wettability, surface roughness, and thermal properties) do not provide a suitable explanation for observed material-sensitive CHFs. Yet, surface roughness and thermal effusivity revealed power and linear relations, respectively, to the nucleate boiling heat transfer coefficients at low mass flux. At high mass flux, material sensitivity on nucleate boiling heat transfer significantly decreased due to the increased shear stress on boiling surface overwhelming material-related boiling implications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A trait syndrome ties cell morphology to glycolysis across the yeast subphylum

Co-variation of traits provides fundamental insights into constraints governing their evolution. An inverse correlation between glucose uptake rates (GURs) and cell surface area-to-volume (SA:V) ratios across 11 yeast species was recently reported. Here, we expand the analysis to 282 species to assess the generalizability of this correlation across Saccharomycotina yeasts and the contribution of shared evolutionary history to the co-variation of these traits. Using phylogenetic regression models, we found extracellular acidification rates (ECARs, used as a proxy for GURs) were weakly, but significantly, correlated with SA:V across Saccharomycotina. ECARs were also correlated with genome sizes and growth rates. Our findings support the reported correlation between GURs and SA:V ratios, but suggest other associated traits, including genome sizes. Specifically, yeasts that consume glucose faster tend to have lower SA:V, faster growth rates, and larger genomes, suggesting a trait syndrome governing several metabolic, genomic, and morphological traits across the yeast subphylum.

biological sciences↗
DOE OSTI2024

Wrought FeCrAl alloy (C26M) cladding behavior and burst under simulated loss-of-coolant accident conditions

Cladding burst experiments for FeCrAl cladding were performed in the Severe Accident Test Station facility at Oak Ridge National Laboratory. These experiments were simulated using the BISON fuel performance code to better understand the cladding plastic behavior and failure under simulated loss-of-coolant accident conditions. 3D cladding surface boundary conditions were generated using composite axial and azimuthal profiles from experiment thermocouple data. To improve the simulation analysis capabilities in BISON for cladding burst behavior, new thermal creep, plasticity, and failure stress models specific to C26M, a wrought FeCrAl alloy, were developed and implemented. Initial cladding burst results indicated a general underprediction in the failure temperature of the six cladding burst simulations versus the observed failure temperatures. Close investigation of the experiment timing versus the underlying tensile test data revealed that, compared with the tensile specimens, the cladding tubes did not experience the same long holding time at high temperatures. New tensile tests were performed at high temperatures using a temperature ramp similar to the simulated loss-of-coolant accident experiments. These new tensile curves showed an approximately 80% increase in the ultimate tensile strength of the C26M alloy, indicating that a holding time of 10 min at 700 °C and 800 °C allows annealing to change the material microstructure. Using the updated tensile properties, the burst temperatures and stresses from the simulations showed remarkable agreement with the experimental results. This study was then extended by varying the initial pressure to highlight the burst temperature difference between standard Zircaloy-4 and C26M cladding under equivalent conditions. The results show that C26M has a burst temperature that is approximately 70–130 K greater than that of Zircaloy-4. In conclusion, these modeling predictions can be further improved by collecting high-temperature tensile data for C26M beyond the temperature ranges used in this work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗