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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Ecological acclimation: A framework to integrate fast and slow responses to climate change

Ecological responses to climate change occur across vastly different time-scales, from minutes for physiological plasticity to decades or centuries for community turnover and evolutionary adaptation. Accurately predicting the range of ecosystem trajectories will require models that incorporate both fast processes that may keep pace with climate change and slower ones likely to lag behind and generate disequilibrium dynamics. However, the knowledge necessary for this integration is currently fragmented across disciplines. We develop ‘ecological acclimation’ as a unifying framework to emphasize the similarity of dynamics driven by processes operating on dramatically different time-scales and levels of biological organization. The framework focuses on ecoclimate sensitivities, measured as the change in an ecological response variable per unit of climate change. Acclimation processes acting at different time-scales cause these sensitivities to shift in magnitude and even direction over time. We highlight shifting ecoclimate sensitivities in case studies from diverse ecosystems, including terrestrial plant communities, coral reefs and soil microbiomes. Models predicting future ecosystem states inevitably make assumptions about acclimation processes; these assumptions must be explicit for users to evaluate whether a model is appropriate for a given forecast horizon. Similarly, decision frameworks that clearly account for multiple acclimation processes and their distinct time-scales will help natural resource managers plan for ecological impacts of climate change from years to many decades into the future. We outline a synthetic research programme focused on the time-scales of ecological acclimation to reduce uncertainty in ecological forecasts.

climate adaptation↗
DOE OSTI2025

Thermal and photoinduced chemistry of the aromatic Criegee intermediate, benzaldehyde oxide: Implications for indoor air quality

Essential oils contain a complex mixture of volatile organic compounds, ranging from terpenes to aromatics. When released into the indoor air environment or into the atmosphere, they may undergo oxidation to generate complex reactive intermediates that affect indoor air quality. Cinnamaldehyde is one such aromatic molecule that is abundant in essential oils. When released into the indoor air environment, it may undergo oxidation to form a carbonyl oxide (Criegee intermediate) with an aromatic substituent: benzaldehyde oxide. In this manuscript, we present a high-level quantum chemical study that shows that, unlike smaller atmospherically relevant Criegee intermediates, benzaldehyde oxide is expected to undergo solar photolysis on timescales that are competitive with its ground state unimolecular and bimolecular chemistry. We show that aromatic substitution leads to a drastic bathochromic shift in the spectroscopically relevant excited states, revealing that photolysis in the indoor or outdoor environment should not be neglected when modeling the climate and air quality implications of Criegee intermediates with extended conjugation. Here, we predict a range of products that may be important for forming lower volatility compounds via tropospherically relevant photochemistry. To motivate future experimental validation of our results, we propose a viable synthetic procedure of the relevant precursor for generating and stabilizing benzaldehyde oxide.

atmospheric photochemistry↗
DOE OSTI2025

ARCH: Large-scale knowledge graph via aggregated narrative codified health records analysis

Objective: Electronic health record (EHR) systems contain a wealth of clinical data stored as both codified data and free-text narrative notes (NLP). The complexity of EHR presents challenges in feature representation, information extraction, and uncertainty quantification. Here, to address these challenges, we proposed an efficient Aggregated naRrative Codified Health (ARCH) records analysis to generate a large-scale knowledge graph (KG) for a comprehensive set of EHR codified and narrative features. Methods: Using data from 12.5 million Veterans Affairs patients, ARCH first derives embedding vectors and generates similarities along with associated p-values to measure the strength of relatedness between clinical features with statistical certainty quantification. Next, ARCH performs a sparse embedding regression to remove indirect linkage between features to build a sparse KG. Finally, ARCH was validated on various clinical tasks, including detecting known relationships between entity pairs, predicting drug side effects, disease phenotyping, as well as sub-typing Alzheimer’s disease patients. Results: ARCH produces high-quality clinical embeddings and KG for over 60,000 codified and narrative EHR concepts. The KG and embeddings are visualized in the R-shiny powered web-API.3 ARCH achieved high accuracy in detecting EHR concept relationships, with AUCs of 0.926 (codified) and 0.861 (NLP) for similar EHR concepts, and 0.810 (codified) and 0.843 (NLP) for related pairs. It detected drug side effects with a 0.723 AUC, which improved to 0.826 after fine-tuning. Using both codified and NLP features, the detection power increased significantly. Compared to other methods, ARCH has superior accuracy and enhances weakly supervised phenotyping algorithms’ performance. Notably, it successfully categorized Alzheimer’s patients into two subgroups with varying mortality rates. Conclusion: The proposed ARCH algorithm generates large-scale high-quality semantic representations and knowledge graph for both codified and NLP EHR features, useful for a wide range of predictive modeling tasks.

Electronic health records↗
DOE OSTI2026

Implementing the finite-volume three-pion scattering formalism across all non-maximal isospins

We present a numerical exploration of the relativistic-field-theory (RFT) formalism for three pions with all possible values of non-maximal isospin, I πππ = 2, 1 and 0. Using the generic-isospin extension of the RFT formalism [1] and applying our open-source Python library to implement the framework, we predict a range of three-pion energies for illustrative values of the two-to-two scattering amplitudes for various finite-volume irreps also with non-zero total momentum P in the finite-volume frame. The results restrict attention to the case of a vanishing intrinsic three-body interaction so that the spectra can be understood as a baseline. In future lattice QCD calculations, deviations from these values will be translated into evidence for intrinsic three-body effects in the various scattering channels.

hadronic spectroscopy↗
DOE OSTI2023

Mechanisms of dissolution from gibbsite step edges elucidated by ab initio molecular dynamics with enhanced sampling

Surface reactions underpin our collective understanding of mineral dissolution. This impacts a range of predictive geochemical models (for weathering, the fate and transport of metals) as well as industrial utilization of minerals. Yet atomistic details are rarely known due to the complex mineral/fluid interfacial environment. There is significant need to understand the mechanistic details of dissolution reactions and how they depend on surface morphology and solution conditions. This work utilizes surface pit models in conjunction with changes to solution composition that mimic pH to explore surface detachment of aluminate from gibbsite, which is a primary source of Al in soils and within the industrial processing of aluminum. Ab initio molecular dynamics simulations with enhanced sampling has been used to explore the detailed process of the detachment, the results of which indicate two potential pathways that are differentiated based upon the extent of water hydration. Here, the heights of the energy barriers depend upon the local morphology which influence the number of bridges (quasi-)simultaneously broken (1 or 2) or the Al-O coordination of the neighboring aluminum atoms (5 or 6) at the armchair edge. pH effects are significant, with a nearly 50% reduction in barrier height under alkaline conditions that are relevant to geothermal fluids and Al extraction from minerals.

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

Chemometric modeling of power conversion efficiency of organic dyes in dye sensitized solar cells for the future renewable energy

The present study reports chemometric modeling of power conversion efficiency (PCE) of dye sensitized solar cells (DSSCs) using the biggest available data set till date which comprises around 1200 dyes covering 7 chemical classes. To extract the best structural features required for higher PCE, we have developed multiple partial least squares (PLS) quantitative structure-property relationship (QSPR) models for the Triphenylamine, Phenothiazine, Indoline, Porphyrin, Coumarin, Carbazole and Diphenylamine chemical classes using descriptors derived from the best subset selection method followed by selection of best five models in each dataset based on the Mean Absolute Error (MAE) values. The models were validated both internally and externally followed by the consensus predictions employing “Intelligent Consensus Predictor” tool to examine whether the quality of predictions can be improved with the “intelligent” selection of multiple PLS models. The quality of predictions for the respective external sets showed that the consensus models (CM) are better than the individual models (IM) in most of the cases. From the insights of the developed models, we concluded that attributes like a packed structure toward higher conductivity of electrons, auxiliary donor fragment of aromatic tertiary amines, number of thiophenes inducing the bathochromic shift and augmenting the absorption, presence of additional electron donors, enhancement of electron-donating abilities, number of non-aromatic conjugated C(sp 2 ) which helps as conjugation extension units to broaden the absorption and highly conjugated $π$-systems exert positive contributions to the PCE. On the contrary, features negatively contributing to PCE are the followings: fragments which lower the tendency of localized $π–π*$ transition, fragments related to larger volume and surface area of dyes along with hydrophobicity resulting in poor adhesion, fragment RC = N causing dye hydrolysis, steric hindrance for π electronic mobility, fragments enhancing polarity, etc. Finally, the identified features from the best QSPR model of the coumarin dataset was employed in designing of ten more efficient coumarin dyes (predicted %PCE ranging from 8.93 to 10.62) than the existing ones.

14 SOLAR ENERGY↗
DOE OSTI2023

Comparative study of two Saccharomyces cerevisiae strains with kinetic models at genome-scale

The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13 C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Ion Size Effects on the Thermodynamic, Kinetic, and Mechanical Properties during Ion Exchange in Solid-State Electrolytes

Ion exchange offers a pathway to impose residual compressive stresses to mitigate the electro-chemo-mechanical cracking of solid-state electrolytes such as lithium lanthanum zirconium oxide. This study uses a coupled multiscale framework (integrating density functional theory (DFT), molecular dynamics (MD), and continuum modeling) to examine how exchange ion size influences stress, diffusion, fracture toughness, and electronic properties. Larger isovalent ions (Na + , Ag + , K + ) were exchanged with Li + , with DFT confirming their preference for octahedral 96h sites and a linear relationship between ion size and chemical free expansion coefficient. MD simulations reveal stress and concentration effects on exchange ion diffusivity at elevated temperatures, with Na + and Ag + maintaining favorable mobility while K + showing concentration-dependent clustering. Continuum modeling predicts the range of fracture strength improvements and the required ion exchange concentration profile. It was shown that a 5% surface exchange concentration can induce ∼0.6 GPa of surface compressive stress using Na + and ∼1.0 GPa of surface compressive stress using Ag + . On the other hand, larger ion exchange species may penalize Li + diffusivity by increasing the activation volume and activation energy. Interestingly, Na + has a negligible penalty on Li-ion diffusivity. The room temperature Li + ion diffusivity is reduced by ∼40% with Ag + ion exchange. Electronic band structure analysis shows no size-dependent change in the bandgap, though Ag + introduces localized defect states near the valence band maximum. This study highlights ion size as a key factor in optimizing LLZO properties, offering a framework to improve the solid-state battery performance.

Jagad, Harsh D. [Brown Univ., Providence, RI (Unit↗
DOE OSTI2021

Viromes outperform total metagenomes in revealing the spatiotemporal patterns of agricultural soil viral communities

Abstract Viruses are abundant yet understudied members of soil environments that influence terrestrial biogeochemical cycles. Here, we characterized the dsDNA viral diversity in biochar-amended agricultural soils at the preplanting and harvesting stages of a tomato growing season via paired total metagenomes and viral size fraction metagenomes (viromes). Size fractionation prior to DNA extraction reduced sources of nonviral DNA in viromes, enabling the recovery of a vaster richness of viral populations (vOTUs), greater viral taxonomic diversity, broader range of predicted hosts, and better access to the rare virosphere, relative to total metagenomes, which tended to recover only the most persistent and abundant vOTUs. Of 2961 detected vOTUs, 2684 were recovered exclusively from viromes, while only three were recovered from total metagenomes alone. Both viral and microbial communities differed significantly over time, suggesting a coupled response to rhizosphere recruitment processes and/or nitrogen amendments. Viral communities alone were also structured along an 18 m spatial gradient. Overall, our results highlight the utility of soil viromics and reveal similarities between viral and microbial community dynamics throughout the tomato growing season yet suggest a partial decoupling of the processes driving their spatial distributions, potentially due to differences in dispersal, decay rates, and/or sensitivities to soil heterogeneity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Accurate prediction of oxygen vacancy concentration with disordered A-site cations in high-entropy perovskite oxides

Abstract Entropic stabilized ABO 3 perovskite oxides promise many applications, including the two-step solar thermochemical hydrogen (STCH) production. Using binary and quaternary A-site mixed {A}FeO 3 as a model system, we reveal that as more cation types, especially above four, are mixed on the A-site, the cell lattice becomes more cubic-like but the local Fe–O octahedrons are more distorted. By comparing four different Density Functional Theory-informed statistical models with experiments, we show that the oxygen vacancy formation energies ( $${E}_{V}^{f}$$ E V f ) distribution and the vacancy interactions must be considered to predict the oxygen non-stoichiometry ( δ ) accurately. For STCH applications, the $${E}_{V}^{f}$$ E V f distribution, including both the average and the spread, can be optimized jointly to improve Δ δ (difference of δ between the two-step conditions) in some hydrogen production levels. This model can be used to predict the range of water splitting that can be thermodynamically improved by mixing cations in {A}FeO 3 perovskites.

08 HYDROGEN↗
DOE OSTI2020

Prospects for n -type doping of (Al x Ga 1– x ) 2 O 3 alloys

Here we systematically explore the properties of group-IV (C, Si, Ge, and Sn) and transition metal (Hf, Zr, and Ta) dopants substituting on the cation site in (Al x Ga 1– x ) 2 O 3 (AlGO) alloys using first-principles calculations with a hybrid functional. In Ga 2 O 3 , each of these dopants acts as a shallow donor. In Al 2 O 3 , they are deep defects characterized by the formation of either DX centers or positive- U (+/0) levels. Combining our calculations of dopant charge-state transition levels with information of the AlGO alloy band structure, we estimate the critical Al composition at which each dopant transitions from being a shallow to a deep donor. We identify Si to be the most efficient dopant to achieve n -type conductivity in high Al-content AlGO alloys, acting as a shallow donor over the entire predicted stability range for AlGO solid solution alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Toward first principles-based simulations of dense hydrogen

Accurate knowledge of the properties of hydrogen at high compression is crucial for astrophysics (e.g., planetary and stellar interiors, brown dwarfs, atmosphere of compact stars) and laboratory experiments, including inertial confinement fusion. There exists experimental data for the equation of state, conductivity, and Thomson scattering spectra. However, the analysis of the measurements at extreme pressures and temperatures typically involves additional model assumptions, which makes it difficult to assess the accuracy of the experimental data rigorously. On the other hand, theory and modeling have produced extensive collections of data. They originate from a very large variety of models and simulations including path integral Monte Carlo (PIMC) simulations, density functional theory (DFT), chemical models, machine-learned models, and combinations thereof. At the same time, each of these methods has fundamental limitations (fermion sign problem in PIMC, approximate exchange–correlation functionals of DFT, inconsistent interaction energy contributions in chemical models, etc.), so for some parameter ranges accurate predictions are difficult. Recently, a number of breakthroughs in first principles PIMC as well as in DFT simulations were achieved which are discussed in this review. Here we use these results to benchmark different simulation methods. We present an update of the hydrogen phase diagram at high pressures, the expected phase transitions, and thermodynamic properties including the equation of state and momentum distribution. Furthermore, we discuss available dynamic results for warm dense hydrogen, including the conductivity, dynamic structure factor, plasmon dispersion, imaginary-time structure, and density response functions. We conclude by outlining strategies to combine different simulations to achieve accurate theoretical predictions that are based on first principles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

High-pressure characterization of Ag 3 AuTe 2 : Implications for strain-induced band tuning

Recent band structure calculations have suggested the potential for band tuning in the chiral semiconductor Ag 3 AuTe 2 to zero upon application of negative strain. In this study, we report on the synthesis of polycrystalline Ag 3 AuTe 2 and investigate its transport and optical properties and mechanical compressibility. Transport measurements reveal the semiconducting behavior of Ag 3 AuTe 2 with high resistivity and an activation energy E a of 0.2 eV. The optical bandgap determined by diffuse reflectance measurements is about three times wider than the experimental E a ⁠. Despite the difference, both experimental gaps fall within the range of predicted bandgaps by our first-principles density functional theory (DFT) calculations employing the Perdew–Burke–Ernzerhof and modified Becke–Johnson methods. Furthermore, our DFT simulations predict a progressive narrowing of the bandgap under compressive strain, with a full closure expected at a strain of –4% relative to the lattice parameter. To evaluate the feasibility of gap tunability at such substantial strain, the high-pressure behavior of Ag 3 AuTe 2 was investigated by in situ high-pressure x-ray diffraction up to 47 GPa. Mechanical compression beyond 4% resulted in a pressure-induced structural transformation, indicating the possibility of substantial gap modulation under extreme compression conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Dependence of dark matter - electron scattering on the galactic dark matter velocity distribution

The rate of dark matter-electron scattering depends on the underlying velocity distribution of the dark matter halo. Importantly, dark matter-electron scattering is particularly sensitive to the high-velocity tail, which differs significantly amongst the various dark matter halo models. In this work, we summarize the leading halo models and discuss the various parameters which enter them. We recommend updated values for these parameters based on recent studies and measurements. Furthermore, we quantify the dependence of the dark matter-electron scattering rate on the choice of halo model and parameters, and demonstrate how these choices propagate to the predicted cross-section limits. The rate is most sensitive to changes in the circular velocity v 0 ; in silicon targets, we find that the changes in the rate predictions can range from Script $\mathcal{O}$(0.01%) to Script $\mathcal{O}$(100%) for contact interactions and Script $\mathcal{O}$(10%) to Script $\mathcal{O}$(100%) for long-range interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Pseudospin-lattice coupling and electric control of the square-lattice iridate Sr2IrO4

Sr 2 IrO 4 is an archetypal spin-orbit-coupled Mott insulator and has been extensively studied in part because of a wide range of predicted states. Limited experimental characterization of these states thus far brings to light the extraordinary susceptibility of the physical properties to the lattice, particularly, the Ir-O-Ir bond angle. Here, we report a microscopic rotation of the IrO 6 octahedra below 50 K measured by single crystal neutron diffraction. Overall, this sharp lattice anomaly provides keys to understanding the anomalous low-temperature physics and a direct confirmation of a crucial role that the Ir-O-Ir bond angle plays in determining the ground state. Indeed, as also demonstrated in this study, applied electric current readily weakens the antiferromagnetic order via the straightening of the Ir-O-Ir bond angle, highlighting that even slight change in the local structure can disproportionately affect the physical properties in the spin-orbit-coupled system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Impacts of Climate Change on Groundwater Availability and Spring Flows: Observations from the Highly Productive Medicine Lake Highlands/Fall River Springs Aquifer System

Medicine Lake Highlands/Fall River Springs Aquifer System, located in northeastern California, is home to some of the largest first-order springs in the United States. This work assesses the likely effects of projected climate change on spring flow. Four anticipated climate futures (GFDL A2, GFDL B1, CCSM4 rcp 8.5, CNRM rcp 8.5) for California, which predict a range of conditions (generally warming and transitioning from snow to rain with variable amounts of total precipitation), are postulated to affect groundwater recharge primarily by changing evapotranspiration. The linkages between climate variables and spring flow are evaluated using a water balance model that represents the physics of evapotranspiration and recharge, the Basin Characterization Model. Three of the four climate scenarios (GFDL A2, GFDL B1, CCSM4 rcp 8.5) project that by the year 2100, groundwater recharge (and consequently decreased spring flow) will decrease by 27%, 21%, and 9%, respectively. The fourth scenario (CNRM rcp 8.5) showed an increase in recharge of 32% due to a significant increase in precipitation (27%). Evapotranspiration increases due to a shift in the type of precipitation and a longer growing season. While the likelihood of each scenario is outside the scope of this work, unless total precipitation increases dramatically in the future, increased temperatures and decreasing precipitation will likely result in reduced spring flows, along with warmer water temperatures in downstream habitats.

42 ENGINEERING↗
DOE OSTI2022

THERMAL MODELING OF HANFORD LEAD CANISTER’S HEATER BENCH TESTS

A computational fluid dynamics (CFD) model was built to simulate planned testing of heater assemblies for the Hanford Lead Canister (HLC) project. The HLC is a canister storage system that will contain heaters to simulate the decay heat of nuclear material and provide the canister storage system with environmental conditions equivalent to the operating conditions on a dry storage pad. The HLC will be equipped with long-term data collection and monitoring systems to provide an early warning of corrosion, pitting, cracking, or other signs of canister degradation that might threaten the integrity of the containment boundary over the potentially long term of dry storage. An important part of the HLC development is to confirm the function and ability of the electric heater assemblies that were specially designed to provide heating similar to the decay heat of nuclear material contained within the canister storage system. Heater bench testing is planned for early 2022 in a test configuration that does not include the canister. The goal of the bench testing is to verify that the heaters can replicate the decay heat of a canister with nuclear material and to validate the thermal models, which are critical to understanding the HLC’s thermal environment, including the local air flow within the canister storage system. Testing of the heater assemblies inside the canister system are planned in the future to validate canister level thermal models, and rigorous pre-deployment testing of the complete HLC cask and canister system is intended to be completed before the HLC is deployed in the 2025-2026 timeframe. This study presents the pre-test temperature predictions of the bench testing. A description of the heater assemblies and planned bench testing is presented. The model was developed with the commercial CFD code STAR-CCM+. An uncertainty analysis was run with the CFD model to determine the uncertainty in the temperature predictions and provide a range over which the predicted temperatures are expected to vary. The uncertainty analysis was performed by coupling STAR-CCM+ with the software Dakota, which provides advanced parametric analyses, including quantification of margins and uncertainty with computational models. This work is expected to provide insight into SNF canister behavior.

Suffield, Sarah R.↗
DOE OSTI2024

THERMAL MODELING OF HANFORD CESIUM AND STRONTIUM CANISTERS DURING SIMULATED LOADING

A computational fluid dynamics (CFD) model was built to simulate planned testing of heater assemblies within a canister and overpack for the Hanford Lead Canister (HLC) project. The HLC is a canister storage system that will contain heaters to simulate the decay heat of nuclear material and provide the canister storage system with environmental conditions equivalent to the operating conditions on a dry storage pad. The HLC will be equipped with long-term data collection and monitoring systems to provide an early warning of corrosion, pitting, cracking, or other signs of canister degradation that might threaten the integrity of the containment boundary over the potentially long term of dry storage. An important part of the HLC development is to make pretest numerical predictions for the behavior of the heated canister during the simulated radiolytic decay heat testing, which simulates the dry storage system during loading operations. The simulated radiolytic decay heat test is planned for mid-2024 in a configuration that includes the heater assembly, overpack, and canister, but with the lids removed to allow loading cesium and strontium capsules into the canister. One of the goals of the test is to evaluate the thermal behavior of the canister and overpack assembly in the ambient air of the test facility, which will provide data critical to validating the thermal models and understanding how the HLC will perform as a system once deployed. To best approximate real-world conditions, the CFD model includes the full air volume of the mock-up truck bay the heated canister test will be performed in, enabling detailed investigation of how the heated canister affects airflow around it. Rigorous pre-deployment testing of the complete HLC cask and canister system is intended to be completed before the HLC is deployed in the 2028 timeframe. This study presents the pre-test temperature predictions of the simulated radiolytic decay heat test. A description of the heater assembly, canister, and overpack system is presented. The model was developed with the commercial CFD software STAR-CCM+. An uncertainty analysis was run with the CFD model to determine the uncertainty in the temperature predictions and provide a range over which the predicted temperatures are expected to vary. The uncertainty analysis was preformed by coupling STAR-CCM+ with the software Dakota, which provides advanced parametric analyses, including quantification of margins and uncertainty with computational models. This work is expected to provide insight into SNF canister behavior.

Carpenter-Graffy, Dina E.↗