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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 307 records · Page 17

A Standardized Analysis Process Using Digital Image Correlation to Calculate In Situ Cladding Strain from Modified Burst Tests for Fuel Performance Code Validation

Historical data collection on nuclear fuel cladding materials has focused on generating a statistically significant amount of data to assess the material and its failure behavior. Furthermore, data generated to support material model and failure criteria development were previously posttest evaluations, so a large number of tests was required to gain new understanding. A way to expedite this process is to develop techniques capable of generating large, high-fidelity data sets from a single test with lower uncertainty or quantified uncertainty. One such example of this approach is Oak Ridge National Laboratory’s use of modified burst tests (MBTs) to analyze the mechanical behavior and failure conditions of cladding during a simulated reactivity-initiated accident (RIA). Each test incorporates digital image correlation (DIC) analysis techniques that are used to assess the accumulated strain in situ, as well as eventual cladding failure. This work has been fruitful in defining strain-to-failure conditions for materials like silicon carbide (SiC) fiber–reinforced/SiC matrix composite tubes (SiC/SiC), iron-chromium-aluminum (FeCrAl) alloy tubes, and chromium-coated Zircaloy-4 tubes. However, there are numerous DIC software available, including open-source and proprietary software. The different DIC software use various algorithms to process images and calculate displacement values. Using these different software and algorithms can lead to varying results, and perhaps larger-than-expected uncertainties. In the present study, previously published MBT data encompassing a variety of test conditions were reanalyzed with two different DIC software to assess the variance in the calculated strain results. The data consisted of SiC/SiC, FeCrAl, and chromium-coated Zircaloy-4 tubes. Plots of the calculated strains during the transient revealed good agreement between the two DIC software. The average root-mean-square errors between the two software was 0.20% strain, which is slightly larger than a previously reported error value for these tests. In conclusion, this variance in results is low enough that this analysis method can be used for code validation.

Reactivity-initiated accident↗

Patterns of patient specific dosimetry in total body irradiation

Purpose: Total body irradiation (TBI) has been used for bone marrow transplant for hematologic and immune deficiency conditions. The goal of TBI is to deliver a homogeneous dose to the entire body, with a generally accepted range of dose uniformity being within {+-}10% of the prescribed dose. The moving table technique for TBI could make dose uniform in whole body by adjusting couch speed. However, it is difficult to accurately estimate the actual dose by calculation and hence in vivo dosimetry (IVD) is routinely performed. Here, the authors present patterns of patient-specific IVD in 161 TBI patients treated at our institution. Methods: Cobalt-60 teletherapy unit (Model C9 Cobalt-60 teletherapy unit, Picker X-ray Corporation) with customized moving bed (SITI Industrial Products, Inc., Fishers, IN) were used for TBI treatment. During treatment, OneDose{sup TM} (Sicel Technology, NC) Metal Oxide-silicon Semiconductor Field Effect Transistor detectors were placed at patient body surface; both entrance and exit side of the beam at patient head, neck, mediastinum, umbilicus, and knee to estimate midplane dose. When large differences (>10%) between the prescribed and measured dose were observed, dose delivery was corrected for subsequent fractions by the adjustment of couch speed and/or bolus placement. Under IRB exempt status, the authors retrospectively analyzed the treatment records of 161 patients who received TBI treatment between 2006 and 2011. Results: Across the entire cohort, the median {+-} SD (range) percent variance between calculated and measured dose for head, neck, mediastinum, umbilicus, and knee was -2.3 {+-} 10.2% (-66.2 to +35.3), 1.1 {+-} 11.5% (-62.2 to +40.3), -1.9 {+-} 9.5% (-66.4 to +46.6), -1.1 {+-} 7.2% (-35.2 to +42.9), and 3.4 {+-} 12.2% (-47.9 to +108.5), respectively. More than half of treatments were within {+-}10% of the prescribed dose for all anatomical regions. For 80% of treatments (10%-90%), dose at the umbilicus was within {+-}10%. However, some large differences greater than 35% were also found at several points. For one case, the knee received double the prescribed dose. When the dose differences for multiple fractions were averaged, compliance ({+-}10%) between the prescription and measured dose was improved compared to the dose difference of the first single fraction, for example, as at umbilicus, which improved from 83.9% to 98.5%. Conclusions: Actual dose measurement analysis of TBI patients revealed a potentially wide variance from the calculated dose. Based from their IVD method for TBI using Cobalt-60 irradiator and moving table, {+-}10% over entire body is hard to achieve. However, it can be significantly improved with immediate feedback after the first fraction prior to subsequent treatments.

60 APPLIED LIFE SCIENCES↗

Experimental analysis of spatial correlation effects on capillary trapping of supercritical CO 2 at the intermediate laboratory scale in heterogeneous porous media

Several numerical studies have demonstrated that the heterogeneous nature of typical sedimentary formations can favorably dampen the accumulation of mobile CO 2 phase underneath the caprock. Core flooding experiments have also shown that contrasts in capillary entry pressure can lead to buildup of nonwetting fluid phase (NWP) at interfaces between facies. Explicit representation of geological heterogeneity at the intermediate (cm-to-m) scale is a powerful approach to identify the key mechanisms that control multiphase flow dynamics in porous media. The ability to carefully control flow regime and permeability contrast at a scale that is relevant to CO 2 plume dynamics in saline formations offers valuable information to understand immiscible displacement processes and provides a benchmark for mathematical models. To provide insight into the impact of capillary heterogeneity on flow dynamics and trapping efficiency of supercritical CO 2 under successive drainage and imbibition conditions, we present an experimental investigation conducted in a synthetic sand reservoir. By mimicking the interplay of governing forces at reservoir conditions via application of surrogate fluids, we performed three immiscible displacement experiments to observe the entrapment of NWP in heterogeneous porous media. Capillary trapping performance is evaluated for each scenario through spatial and temporal variations of NWP saturation; for this reason we adopted X-ray attenuation to precisely measure phase saturation throughout the flow domain and apply spatial moment analysis. Furthermore, the sweeping performance of two different permeability fields with comparable variance but distinct spatial correlation was compared against a homogeneous base case with equivalent mean permeability by means of spatial moment analysis.

58 GEOSCIENCES↗

Quantifying the relative contribution of factors to household vehicle miles of travel

Household vehicle miles of travel (VMT) has been exhibiting a steady growth in post-recession years in the United States and has reached record levels in 2017. With transportation accounting for 27 percent of greenhouse gas emissions, planning professionals are increasingly seeking ways to curb vehicular travel to advance sustainable, vibrant, and healthy communities. Although there is considerable understanding of the various factors that influence household vehicular travel, there is little knowledge of their relative contribution to explaining variance in household VMT. This paper presents a holistic analysis to identify the relative contribution of socio-economic and demographic characteristics, built environment attributes, residential self-selection effects, and social and spatial dependency effects in explaining household VMT production. The modeling framework employs a simultaneous equations model of residential location (density) choice and household VMT generation. The analysis is performed using household travel survey data from the New York metropolitan region. Model results showed insignificant spatial dependency effects, with socio-demographic variables explaining 33 percent, density (as a key measure of built environment attributes) explaining 12 percent, and self-selection effects explaining 11 percent of the total variance in the logarithm of household VMT. The remaining 44 percent remains unexplained and attributable to omitted variables and unobserved idiosyncratic factors, calling for further research in this domain to better understand the relative contribution of various drivers of household VMT.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

UV–Vis–NIR Reflectance Spectroscopy and Chemometrics for Monitoring Pu Directly on an Ion Exchange Column

Here, we present a fiber-optic UV–vis–NIR reflectance spectroscopy method for direct, noninvasive monitoring of Pu(IV) in a glass ion exchange column during dynamic loading and elution in a glovebox. A movable probe enables spatially resolved spectral acquisition along the column axis, capturing distinct features associated with Pu(IV) nitrate complexes during loading and free ions during elution. Principal component analysis was applied to extract the dominant spectral variance and resolve relative concentration profiles without requiring precise knowledge of optical penetration depth or species identity. This in situ approach reveals spatial gradients and speciation dynamics in real time, which provides actionable insight into Pu(IV) ion migration, resin saturation, and breakthrough behavior under evolving flow conditions. The method offers a practical, fiber-compatible strategy to monitor glass column–based separations for Pu and other lanthanides or actinides and to characterize metal–resin interactions in flow-through systems.

actinide↗

Angular dependence of primordial trispectra and CMB spectral distortions

Under the presence of anisotropic sources in the inflationary era, the trispectrum of the primordial curvature perturbation has a very specific angular dependence between each wavevector that is distinguishable from the one encountered when only scalar fields are present, characterized by an angular dependence described by Legendre polynomials. We examine the imprints left by curvature trispectra on the TT μ bispectrum, generated by the correlation between temperature anisotropies (T) and chemical potential spectral distortions (μ) of the Cosmic Microwave Background (CMB). Due to the angular dependence of the primordial signal, the corresponding TT μ bispectrum strongly differs in shape from TT μ sourced by the usual g {sub NL} or τ{sub NL} local trispectra, enabling us to obtain an unbiased estimation. From a Fisher matrix analysis, we find that, in a cosmic-variance-limited (CVL) survey of TT μ, a minimum detectable value of the quadrupolar Legendre coefficient is d {sub 2} ∼ 0.01, which is 4 orders of magnitude better than the best value attainable from the TTTT CMB trispectrum. In the case of an anisotropic inflationary model with a f (φ) F {sup 2} interaction (coupling the inflaton field φ with a vector kinetic term F {sup 2}), the size of the curvature trispectrum is related to that of quadrupolar power spectrum asymmetry, g {sub *}. In this case, a CVL measurement of TT μ makes it possible to measure g {sub *} down to 10{sup −3}.

79 ASTRONOMY AND ASTROPHYSICS↗

Performance and community structure dynamics of microbial electrolysis cells operated on multiple complex feedstocks

Microbial electrolysis is a promising technology for converting aqueous wastes into hydrogen. However, substrate adaptability is an important feature, seldom documented in microbial electrolysis cells (MECs). In addition, the correlation between substrate composition and community structure has not been well established. This study used an MEC capable of producing over 10 L/L-day of hydrogen from a switchgrass-derived bio-oil aqueous phase and investigated four additional substrates, tested in sequence on a mature biofilm. The additional substrates included a red oak-derived bio-oil aqueous phase, a corn stover fermentation product, a mixture of phenol and acetate, and acetate alone. The MECs fed with the corn stover fermentation product resulted in the highest performance among the complex feedstocks, producing an average current density of 7.3 ± 0.51 A/m 2 , although the acetate fed MECs outperformed complex substrates, producing 12.3 ± 0.01 A/m 2 . 16S rRNA gene sequencing showed that community structure and community diversity were not predictive of performance, and replicate community structures diverged despite identical inoculum and enrichment procedure. The trends in each replicate, however, were indicative of the influence of the substrates. Geobacter was the most dominant genus across most of the samples tested, but its abundance did not correlate strongly to current density. High-performance liquid chromatography (HPLC) showed that acetic acid accumulated during open circuit conditions when MECs were fed with complex feedstocks and was quickly degraded once closed circuit conditions were applied. The largest net acetic acid removal rate occurred when MECs were fed with red oak bio-oil aqueous phase, consuming 2.93 ± 0.00 g/L-day. Principal component analysis found that MEC performance metrics such as current density, hydrogen productivity, and chemical oxygen demand removal were closely correlated. Net acetic acid removal was also found to correlate with performance. However, no bacterial genus appeared to correlated to these performance metrics strongly, and the analysis suggested that less than 70% of the variance was accounted for by the two components. This study demonstrates the robustness of microbial communities to adapt to a range of feedstocks and conditions without relying on specific species, delivering high hydrogen productivities despite differences in community structure. The results indicate that functional adaptation may play a larger role in performance than community composition. Further investigation of the roles each microbe plays in these communities will help MECs to become integral in the 21st-century bioeconomy to produce zero-emission fuels.

09 BIOMASS FUELS↗

Utah FORGE: Phase 3 Microgravity Data

A 4D microgravity survey began in early 2019 in order to benchmark surface and subsurface elevations prior to Phase 3 drilling and stimulation campaigns. Microgravity stations are collocated with GPS deformation benchmarks and use the same location survey data. Surveys are undertaken on a quarterly basis. The focus of current activities is comparative analysis of GPS survey results and InSAR analysis (see GDR Submission 1251) to check seasonal variance and to evaluate possible changes in the groundwater elevation. The attached zip file contains a text file and an Excel spreadsheet containing Utah FORGE Phase 3 processed "final" microgravity data through time. The data are identical in both files. The spreadsheet is only supplied for convenience. There is also a ReadMe.txt file that describes the field headings.

15 GEOTHERMAL ENERGY↗

Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps

While it is not generally reflected in the `nice' datasets used for benchmarking machine learning algorithms, the real-world is full of processes that would be best described as many-to-many. That is, a single input can potentially yield many different outputs (whether due to noise, imperfect measurement, or intrinsic stochasticity in the process) and many different inputs can yield the same output (that is, the map is not injective). For example, imagine a sentiment analysis task where, due to linguistic ambiguity, a single statement can have a range of different sentiment interpretations while at the same time many distinct statements can represent the same sentiment. When modeling such a multivalued function $f: X \rightarrow Y$, it is frequently useful to be able to model the distribution on $f(x)$ for specific input $x$ as well as the distribution on fiber $f^{-1}(y)$ for specific output $y$. Such an analysis helps the user (i) better understand the variance intrinsic to the process they are studying and (ii) understand the range of specific input $x$ that can be used to achieve output $y$. Following existing work which used a fiber bundle framework to better model many-to-one processes we describe how morphisms of fiber bundles provide a template for building models which naturally capture the structure of many-to-many processes.

Coda, Elizabeth D.↗

The South Pole Telescope AGN Monitoring Campaign: First Release of SPTpol Bright AGN Light Curves

The South Pole Telescope (SPT) collaboration has recently embarked upon a campaign to monitor the brightness of a sample of active galactic nuclei (AGN), both in real time and in archival SPT data. The original design of the SPT was optimized for observations of the cosmic microwave background (CMB) at arc-minute and larger angular scales, and it has been used for this purpose for nearly twenty years, using three generations of CMB cameras. Recently it has been recognized that data from CMB experiments have the potential to be used for AGN monitoring. In this paper, we present the first public release of data from a full sample of SPT-monitored AGN, comprising 158 AGN light curves and associated data from the SPTpol camera, which was operational from 2012-2016. These light curves were created using observations from the SPTpol 500 deg$^{2}$ survey, in which the instrument was used to scan a 500 deg$^2$ patch of the sky several times per day with detectors sensitive to radiation in bands centered at 90 and 150 GHz. We provide a comprehensive description of the observations, the data processing methods, and the resulting light curve catalog. As an example of analyses that these data enable, we searched for a correlation between variability and spectral index, and we looked for ``bluer-when-brighter'' trends in the sample. Our analysis finds $> 10 σ$ correlation between fractional intrinsic variance and mean spectral index in the sample, but no significant evidence for bluer-when-brighter trends. The datasets from this study can be accessed through the SPT Treasury Record of AGN With Historical Activity and Time-Series or STRAWHAT catalog. This initial data release includes SPTpol light curves at 90 and 150 GHz, focusing on total intensity. In later updates, SPTpol polarization data and new observations from the SPT-3G instrument at 90, 150, and 220 GHz will be included.

Hood, J.C., II [Chicago U., KICP; Chicago U., Astr↗

A variance-based decomposition and global sensitivity index method for uncertainty quantification: Application to retrieved ice cloud properties

This study develops a novel uncertainty quantification (UQ) method for cloud microphysical property retrievals using variance-based decomposition and global sensitivity index. In this UQ framework, empirical orthogonal function (EOF) analysis is applied to the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) ground-based observations, which are the inputs for the cloud retrieval studied here. The principal components (PCs) in the EOF expansion are parameterized as random input variables, and hence, the input dimension is greatly reduced (up to a factor of 50), allowing large ensemble of random samplings. The EOF expansion improves the accuracy of the uncertainty estimation by taking into account the cross correlations in the input data profiles. Here, this method enables a probabilistic representation of a retrieval process by adding normally distributed perturbations into PCs of sample means of input data profiles within a time window. Therefore, it effectively facilitates objective validation of climate models against cloud retrievals under a probabilistic framework for rigorous statistical inferences. Moreover, the variance-based global sensitivity index analysis, part of this method, attributes the output uncertainties to each individual source, thus providing directions for improving retrieval algorithms and observation strategies. For demonstration, we apply this method to quantify the uncertainties of the ARM program's baseline cloud retrieval algorithm for an ice cloud case observed at the Southern Great Plains site on 9 March 2000.

54 ENVIRONMENTAL SCIENCES↗

Meta-analysis of the Alpha/Beta Ratio for Prostate Cancer in the Presence of an Overall Time Factor: Bad News, Good News, or No News?

Purpose: To present a novel method for meta-analysis of the fractionation sensitivity of tumors as applied to prostate cancer in the presence of an overall time factor. Methods and Materials: A systematic search for radiation dose-fractionation trials in prostate cancer was performed using PubMed and by manual search. Published trials comparing standard fractionated external beam radiation therapy with alternative fractionation were eligible. For each trial the {alpha}/{beta} ratio and its 95% confidence interval (CI) were extracted, and the data were synthesized with each study weighted by the inverse variance. An overall time factor was included in the analysis, and its influence on {alpha}/{beta} was investigated. Results: Five studies involving 1965 patients were included in the meta-analysis of {alpha}/{beta}. The synthesized {alpha}/{beta} assuming no effect of overall treatment time was -0.07 Gy (95% CI -0.73-0.59), which was increased to 0.47 Gy (95% CI -0.55-1.50) if a single highly weighted study was excluded. In a separate analysis, 2 studies based on 10,808 patients in total allowed extraction of a synthesized estimate of a time factor of 0.31 Gy/d (95% CI 0.20-0.42). The time factor increased the {alpha}/{beta} estimate to 0.58 Gy (95% CI -0.53-1.69)/1.93 Gy (95% CI -0.27-4.14) with/without the heavily weighted study. An analysis of the uncertainty of the {alpha}/{beta} estimate showed a loss of information when the hypofractionated arm was underdosed compared with the normo-fractionated arm. Conclusions: The current external beam fractionation studies are consistent with a very low {alpha}/{beta} ratio for prostate cancer, although the CIs include {alpha}/{beta} ratios up to 4.14 Gy in the presence of a time factor. Details of the dose fractionation in the 2 trial arms have critical influence on the information that can be extracted from a study. Studies with unfortunate designs will supply little or no information about {alpha}/{beta} regardless of the number of subjects enrolled.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Impact of three-dimensional hot-spot flow asymmetry on ion-temperature measurements in inertial confinement fusion experiments

Three-dimensional (3-D) implosion asymmetries lead to signficant variations in ion-temperature measurements in inertial confinement fusion experiments. We present an analytical method to generalize the physical properties of velocity variance in the Brysk ion-temperature model. This analysis provides a consistent explanation for the 3-D effects of inferred ion-temperature variations for various single modes and multimodes modeled by the deceleration-phase hydrocode DEC3D and the neutron transport code IRIS3D . The effect of the hot-spot ow asymmetry on variations in ion-temperature measurement is shown uniquely determined by a complete set of six hot-spot flow parameters. An approximated solution to the minimum inferred ion temperature is derived and shown to be close to the thermal ion temperature for low mode l = 1, which exhibits the largest anisotropic velocity variance in the single-mode spectrum. In conclusion, the isotropic velocity variance for low mode l = 2 is shown to result in the minimum inferred ion temperatures being well above the thermal ion temperature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Multiscale Approach to High-Resolution Ocean Profile Observations within a 4DVAR Analysis System

Most ocean data assimilation systems are tuned to process and assimilate observations to constrain features on the order of the mesoscale and larger. Typically this involves removal of observations or computing averaged observations. This procedure, while necessary, eliminates many observations from the analysis step and can reduce the overall effectiveness of a particular observing platform. Simply including these observations is not an option as doing so can produce an overdetermined, ill-conditioned problem that is more difficult to solve. An approach, presented here, aims to avoid such issues while at the same time increasing the number of observations within the assimilation. A two-step assimilation procedure with the four-dimensional variational data assimilation (4DVAR) system is adopted. The first step attempts to constrain the large-scale features by assimilating a set of super observations with appropriate background error correlation scales and error variances. The second step then attempts to correct smaller-scale features by assimilating the full observation set with shorter background error correlation scales and appropriate error variances; here the background state is taken as the analysis from the first step. Results using a real high-density observation set from underwater gliders in the region southeast of Iceland, collected during the 2017 Nordic Recognized Environmental Picture (NREP) experiment, will be shown using the Navy Coastal Ocean Model 4DVAR (NCOM-4DVAR).

54 ENVIRONMENTAL SCIENCES↗

Sensitivity Analysis of OECD Benchmark Tests in BISON

This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simulation) project focused on sensitivity analysis of a fuels performance benchmark problem. The benchmark problem was defined by the Uncertainty Analysis in Modeling working group of the Nuclear Science Committee, part of the Nuclear Energy Agency of the Organization for Economic Cooperation and Development (OECD ). The benchmark problem involv ed steady - state behavior of a fuel pin in a Pressurized Water Reactor (PWR). The problem was created in the BISON Fuels Performance code. Dakota was used to generate and analyze 300 samples of 17 input parameters defining core boundary conditions, manuf acturing tolerances , and fuel properties. There were 24 responses of interest, including fuel centerline temperatures at a variety of locations and burnup levels, fission gas released, axial elongation of the fuel pin, etc. Pearson and Spearman correlatio n coefficients and Sobol' variance - based indices were used to perform the sensitivity analysis. This report summarizes the process and presents results from this study.

97 MATHEMATICS AND COMPUTING↗

Global sensitivity analysis in stochastic simulators of uncertain reaction networks

Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol’s decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes that the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. Here, a sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.

97 MATHEMATICS AND COMPUTING↗

Major to trace element imaging and analysis of iron age glasses using stage scanning in the analytical dual beam microscope (tandem)

Dark and clear silicate glasses formed during an iron age vitrification event ≈ 1500 years ago at the Broborg hillfort near Uppsala, Sweden have been analyzed using a scanning electron microscope equipped with a micro-X-ray fluorescence (μXRF) spectrometer. Correlated µXRF and electron beam-induced energy dispersive spectrometry (EDS) X-ray maps were collected via stage-scanning at constant velocity. This coupled procedure represents a new approach for the cultural heritage community to conduct analytical studies of archaeometric specimens composed of metal, ceramic, or mixed inorganic/organic materials, where major and trace element compositions are registered in space for areas up to the centimeter-length scale at micrometer-scale resolution. Overview images were used to select areas for EDS beam scan maps correlated with multispectral cathodoluminescence (CL) imaging and co-located quantitative EDS and μXRF point analysis. Fe, Ca, Mg, Ti, P, Mn, Zr, Zn, and Y are enriched in the dark glass, while Si, Al, K, Na, Ba, Sr, Rb, and Ga are enriched in the clear glass. Unmelted material is comprised predominately of quartz (SiO 2 ) along with trace apatite (Ca 5 (PO 4 ) 3 [Cl,OH]) and zircon (ZrSiO 4 ). Multivariate statistical analysis was used to measure the area fractions of high variance components while lower variance components represented phase mixtures. Differences between calculated melt viscosities for the glass compositions are consistent with field and laboratory observations. Coupled large area EDS and μXRF imaging shows significant promise for informed selection of higher spatial resolution and higher sensitivity follow-up studies, e.g., those performed using synchrotron analysis.

36 MATERIALS SCIENCE↗

Sensitivity analysis of thermal contact conductance modeling to inform MiniFuel irradiation capsule designs

The MiniFuel irradiation platform has been developed by Oak Ridge National Laboratory as a flexible, high-throughput separate effects testing capability within the High Flux Isotope Reactor (HFIR). Finite element thermal models are relied upon to design MiniFuel experiments to achieve a specific time-averaged irradiation temperature for experimental objectives. A previous study identified that uncertainty in the component heat generation rates and thermal contact conductance (TCC) model are the most significant contributors to predicted fuel temperature variance. To address both sources of uncertainty, this work performs sensitivity analysis on the TCC model to identify high-impact, high-uncertainty parameters that contribute to fuel temperature variance. The TCC model is analyzed in increasing detail, first using a standalone Python code, then again after coupling Python to the BISON fuel performance code. Furthermore, the parameters with the largest contributions to fuel temperature variance which can be reduced through design changes are identified as the initial subcapsule gas pressure, contact pressure between the fuel and dish, and the effective surface roughness of the interface. A set of design recommendations for future capsule designs has been established and applied to reduce the previously quantified average fuel temperature uncertainty ranges of ± 40 °C in the HFIR vertical experiment facilities (VXF) and ± 80 °C in the removable beryllium (RB) reflector to approximately ± 32 °C and ± 53 °C, respectively. This equates to a 21 % and 33 % reduction in the uncertainty range of the average fuel temperature for VXF and RB, respectively.

BISON↗