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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Outbursts of luminous blue variable stars from variations in the helium opacity

Luminous blue variables are massive, evolved stars that exhibit large variations in luminosity and size on timescales from months to years, with high associated rates of mass loss1,2,3,4,5. In addition to this on-going variability, these stars exhibit outburst phases, during which their size increases and as a result their effective temperature decreases, typically to about 9,000 kelvin3,6. Outbursts are believed to be caused by the radiation force on the cooler, more opaque, outer layers of the star balancing or even exceeding the force of gravity, although the exact mechanisms are unknown and cannot be determined using one-dimensional, spherically symmetric models of stars because such models cannot determine the physical processes that occur in this regime7. Here we report three-dimensional simulations of massive, radiation-dominated stars, which show that helium opacity has an important role in triggering outbursts and setting the observed effective temperature during outbursts of about 9,000 kelvin. It probably also triggers the episodic mass loss at rates of 10 -7 to 10 -5 solar masses per year. The peak in helium opacity is evident in our three-dimensional simulations only because the density and temperature of the stellar envelope (the outer part of the star near the photosphere) need to be determined self-consistently with convection, which cannot be done in one-dimensional models that assume spherical symmetry. The simulations reproduce observations of long-timescale variability, and predict that convection causes irregular oscillations in the radii of the stars and variations in brightness of 10–30 per cent on a typical timescale of a few days. The amplitudes of these short-timescale variations are predicted to be even larger for cooler stars (in the outburst phase). This short-timescale variability should be observable with high-cadence observations.

Science & Technology - Other Topics↗
DOE OSTI2021

In Situ X-ray Diffraction of High Density Polyethylene During Dynamic Compression: Polymer Chain Compression and Phase Transformations

Polymers are widely implemented materials often used for safety and security in our daily lives. However, we do not have a thorough understanding of the phase transformations of these materials when exposed to extreme condition, high strain rate, events. To study polymers in these severe environments, we performed plate impact experiments that impart a one-dimensional shock wave, at high pressures and temperatures, to observe the materials response. Generally, velocimetry is the experimental diagnostic used to capture the movement of high velocity interfaces to then calculate the mechanical variables associated with shock compression. However, when a material undergoes a phase transition, such as between two crystalline phases or melting to decomposition during shock compression, velocimetry does not explicitly indicate what structural change occurred. At the Dynamic Compression Sector at the Advanced Photon Source gas gun driven compression has been paired with x-ray diffraction, providing the ability to study both the shock parameters and structural changes concurrently. We explored high density polyethylene (HDPE) both on its reactants Hugoniot (<10.12 GPa) and within its transition region (24.3 GPa) where HDPE is hypothesized to decompose from reactants to products. With x-ray diffraction we observed both polymer chain compression and crystal structure reorientation from orthorhombic to monoclinic above 6 GPa, as well as either a possible phase change or chemical decomposition at 24.3 GPa. With these experiments we were able to determine the crystalline and amorphous Hugoniot loci at pressures below the polymer transition region.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The Triple Catalytic Action of Tertiary Nitrogen Catalysts in Recyclable Epoxy-Anhydride Thermosets

The thermosetting polymer matrix in fiber reinforced composites is an important component for energy related applications, such as the lightweighting of vehicles or their use in wind and waterpower turbine blades, due to their ability to provide superior adhesion, stiffness, and applicability to a wide range of manufacturing processes. Despite these benefits, today's thermosets are widely considered to be unrecyclable; thus, there is a large interest in redesigning these materials to be inherently recyclable so that energy intensive production of fibers and monomers can be circumvented, bolstering composite manufacture supply chains. Polyester covalent adaptable networks (PECANs) are one such promising alternative to the incumbent, nonrecyclable epoxy-amine thermosets. PECANs can be formed from the ring-opening co-polymerization (ROCOP) of epoxy-anhydride monomer mixtures and subsequent curing at mild temperatures to exhibit similar performance to conventional epoxies while also possessing unique dynamic chemistries along the ester-hydroxyl backbone that are capable of transesterification and thus reprocessability. While significant advancements have been made in formulating these materials for improved mechanical properties or optimizing solvolysis and reprocessing strategies, less attention has been placed on the impact of the residing amine catalyst used to generate the polyester network. In this work, we evaluated the triple-catalytic efficacy of 12 tertiary amines that act as a curing (bulk ROCOP), a transesterification (internal bond exchange), and a deconstruction (methanolysis) catalyst for PECAN thermosets. Specifically, we first distinguish between chain-growth and step-growth polymerization mechanisms for epoxy-amine and epoxy-anhydride mechanisms. We also utilized density functional theory (DFT) to estimate the basicity (pKb) of each catalyst. Of the tested catalysts, the ROCOP of the studied PECAN network can be completed between 95 and 247 min (at 80 degrees C), with variable gelation phenomena. Additionally, the stress relaxation (transesterification metric) efficiency of the tested PECAN networks with alternative embedded catalysts ranged from 95% to 15% reduction in stress after 5 h at 200 degrees C, and the depolymerization efficacy ranged from 2.5% to 9.8% deconstruction after 36 h at 130 degrees C. Overall, the nitrogen-based moieties were demonstrated to influence polymerization kinetics, catalyze the dynamic transesterification exchange mechanism, and aid in the solvolysis of the thermosets at end-of-life.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Single- and dual-variant atomic ordering in GaAsP compositionally graded buffers on GaP and Si substrates

Here, we investigate the material properties of GaAsP graded buffers on both GaP and Si substrates in order to determine limitations to dislocation glide in GaAsP. Phase separation is not observed in these GaAsP buffers, but CuPt B atomic ordering is present, and has an impact on the Burgers vector distribution of gliding dislocations. Tellurium surfactant eliminates ordering in GaAsP, allowing control over the glide plane distribution while highlighting the importance of the growth surface and choice of dopant. The impact of single-variant CuPtB ordering of GaAsP buffers grown on GaP substrates is investigated by monitoring the threading dislocation density throughout the buffer in sequential steps. The dislocation density rises steadily throughout the graded buffer, implying that factors other than ordering-induced glide plane switches play a dominant role in the final dislocation density. We observe an increase in surface roughness throughout the buffer and speculate that a dislocation nucleation source on the surface has a low activation energy and may lead to increased threading dislocation density. On Si substrates, the GaAsP buffer displays dual-variant CuPt B ordering rather than single-variant ordering due to the surface step geometry. We discuss how dual-variant ordering leads to a variable glide force, and thus has a different impact on dislocation dynamics than single-variant ordering. Because the III-V on Si nucleation procedure determines the step geometry, it also influences the dislocation dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Coal-based Bricks & Blocks (CBBs): Process Development to Prototype Fabrication Coupled with Techno-Economic Analysis and Market Survey

Coal-based bricks and blocks (CBBs) were formulated using anthracite and thermoplastic binder. Lab scale test composites were formed by hot-press molding and commercial extrusion for test articles and for a full-scale prototype. Formulations and test matrices followed a systematic experimental design to examine the effects of and interactions among three primary independent variables: a) thermoplastic type, b) weight fractions of binder relative to the total anthracite weight, and c) relative proportions of large versus small (milled) anthracite size fractions. Technical performance metrics include compressive strength, modulus, porosity/permeability and density. These DoE studies establish composition-property relations and identify the best combination for any desired property of interest – in particular, strength. Based on CBB composition and fabrication process, validated against technical performance metrics, a techno-economic analysis was constructed which incorporated a process flow model, engineering design (with scaling), and calculated capital plus operating costs. Based on measured property metrics and estimated process economics and a projected price by TEA (techno-economic analysis), building and construction target markets were identified by a market survey assessment. With known cost, price, performance metrics and competitive advantages for CBBs matched with commercial applications/uses, a technical gap analysis was performed to identify further development required for scale-up and commercialization.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2017

Effects of fuel thickness on thermal and mechanical performance of U10-Mo monolithic fuel plates

Monolithic fuels are being considered for conversion of high performance research and test reactors. These plate-type fuels are comprised of a low enrichment, high density U-Mo alloy fuels within an aluminum cladding. Although the plates have demonstrated satisfactory performance; still, use of a high density fuel in a foil form retains technical challenges that could affect the overall performance. To understand performance of this new design during fabrication and irradiation, the plates have been evaluated for various geometrical and operational variables. As a part of these set of parametric sensitivity studies, effects of foil thickness on performance were studied. Because high performance research reactors will utilize different fuel thicknesses, it is necessary to evaluate possible effects for a range of thicknesses that are being considered for various designs. Based on the preliminary design specifications, the fuel thicknesses were varied between the limiting cases. The bounding fuel thicknesses were 0.203 mm as minimum that is projected for ATR, and 0.635 mm as maximum that is projected for MITR. To study possible effects, a behavioral model was developed for a selected plate from RERTR-12 experiments and the plate was simulated with as run irradiation history. The simulations were repeated for a range of fuel thicknesses, while keeping the cladding thickness and the operational parameters the same. The results have indicated that the plates with thicker fuels would have higher temperatures, deformations and shutdown stresses. To investigate the effects of fuel thickness exclusively, operational parameters were scaled. In particular, a second set of simulations with prorated volumetric heat generation rates were performed. The results indicated that the fabrication stresses in the fuel foil decrease with an increasing fuel thickness. On contrary, irradiation stresses of the fuel at shutdown are higher for the plates with thicker fuels. Greater peak deformations occurred in plates with thicker fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Roll Compaction of Powdered Radioactive Wastes - 18251

Most of low- and intermediate-level radioactive wastes must be solidified by a proper binding matrix and disposed at the centralized disposal site. So it is desirable to achieve a high loading of radwastes in a drum to reduce the disposal fee while meeting both the national regulations and the waste acceptance criteria of the disposal site. In general, the radioactive wastes (liquid, dried powder and sludge) were solidified by mixing with a proper binding matrix (cement, polymer, asphalt, etc.), but their solidified volume inevitably increases due to the limitation of incorporating of radwaste into a binding matrix. To solve this problem, some Korean NPPs operate both a CTS (Concentrate Treatment System, evaporation and granulation) and a polymer solidification system. The size distribution of granulated wastes produced by CTS is so broad (diameter; several μm ∼ several cm) that a polymer cannot impregnate the void space between particles due to their small size. However, if the powdered radwaste can be compacted into high density pellets, and the pellets can be loaded in a drum with maximum waste loading, then the binding matrix can fill the void between pellets, it might be more desirable to keep the size distribution of pellets constant to reduce the solidified waste volume. This compaction methodology can greatly reduce the disposal fee due to the reduction of the solidified waste volume, and can facilitate polymer solidification due to the constant size of the radwaste pellets. This methodology is also applicable to solidify powdered wastes such a depleted uranium used as a catalyst, ash and sludge. Loading radwaste compacted with bentonite pellets versus particles into a container serves, as an engineered or natural barrier in a deep geologic disposal system. Roll compaction is a typical agglomeration process for dry powders and depends on the device parameters and the material properties. This study, firstly, was focused on the design of roll compactor (briquetting machine), the shape and size of pellet, and secondly the loading method of pellets into a drum, their solidification in polymer, and evaluating the overall volume reduction. We used bentonite (particle size; 85 ∼ 100 μm) as a material to be compacted instead of radwaste powders (concentrates and depleted uranium wastes) without the addition of agglomeration agents. In the design of roll, we considered the diameter (200 mm) and width (41 mm) of roll, two types of pocket shapes (< 9 mm, 0.275 ml), and the surface of the pocket. Fig. 2 shows two pellet shapes, tetragonal and circular. The pressure of roll compactor, one of the main process variables, is > 320 kg f/cm{sup 2}, and the roll gap is 0.5 mm. The powders are compacted in a compaction zone between two counter-rotating rolls according to the complicated mechanisms. As a result of the state and the apparent density of the pellets obtained by changing the pressure from 0 to 286 kg f/cm{sup 2}, the pellets were unstable at pressure=0, but above 148 kg f/cm{sup 2} the pellets were more stable, and the apparent density of the pellets was 2.63 g/cm{sup 3} at 148 kg f/cm{sup 3}, and 2.68 g/cm{sup 3} at 286 kg f/cm{sup 2}. The roller speed (rpm) can determine the capacity (kg/h) of a compactor, and depends on both the compaction pressure and the feeding rate. By increasing the roll speed from 2 to 4 rpm, the apparent density of pellets was decreased gradually from 2.74 g/cm{sup 3} to 1.45 g/cm{sup 3}. We designed the special feeding system in order to feed powders uniformly to the roll gripping zone and to supply powders into the narrowest part of the roll gap. At a constant roll speed (3 rpm) and a constant compaction pressure (286 kg f/cm{sup 2}), the apparent density of the pellets was linearly proportional to the feeding rate from 2.18 to 2.74 g/cm{sup 3} by changing the feeding rate of powders from 8 to 12 rpm. In the polymer solidification of the obtained pellets, we used epoxy resin as a solidification agent, and showed their solidified waste forms in Fig. 5. The incorporation ratio (wt.%) of powders/polymer was about 71.7/28.3 in tetragonal pellets, 71.9/28.1 in circular pellets. We calculated the volume reduction in an aspect of powders itself and the solidified waste form. In powder case, through the comparison of the apparent density of the obtained pellets (2.74 g/cm{sup 3}) and raw powders (0.93 g/cm{sup 3}), the volume reduction was calculated as about 2.74/0.93 = 2.95 times. This means that powders can be compacted to 1/2.95 times. And in waste form case, the weight ratio of powder/polymer in a mixing method (workable) and a compaction method is about 0.42, 2.56, individually. Therefore the volume reduction was calculated as about 2.56/0.42 = 6.01 times. We found a compaction methodology for the volume reduction of powdered radioactive wastes, and their polymer solidification will be more effective to reduce the volume of radwastes to be disposed. After a characterization of the solidified waste form incorporated pellets (including sintered pellets), this methodology will be applied to treat depleted uranium wastes used as catalyst, and to solve the problem of NPPs' polymer solidification system, as mentioned above. (authors)

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

Quantitative comparison of power production and power quality onshore and offshore: a case study from the eastern United States

Abstract. A major issue in quantifying potential power generation from prospective wind energy sites is the lack of observations from heights relevant to modern wind turbines, particularly for offshore where blade tip heights are projected to increase beyond 250 m. We present analyses of uniquely detailed data sets from lidar (light detection and ranging) deployments in New York State and on two buoys in the adjacent New York Bight to examine the relative power generation potential and power quality at these on- and offshore locations. Time series of 10 min wind power production are computed from these wind speeds using the power curve from the International Energy Agency 15 MW reference wind turbine. Given the relatively close proximity of these lidar deployments, they share a common synoptic-scale meteorology and seasonal variability with lowest wind speeds in July and August. Time series of power production from the on- and offshore location are highly spatially correlated with the Spearman rank correlation coefficient dropping below 0.4 for separation distances of approximately 350 km. Hence careful planning of on- and offshore wind farms (i.e., separation of major plants by > 350 km) can be used reduce the system-wide probability of low wind energy power production. Energy density at 150 m height at the offshore buoys is more than 40 % higher, and the Weibull scale parameter is 2 m s−1 higher than at all but one of the land sites. Analyses of power production time series indicate annual energy production is almost twice as high for the two offshore locations. Further, electrical power production quality is higher from the offshore sites that exhibit a lower amplitude of diurnal variability, plus a lower probability of wind speeds below the cut-in and of ramp events of any magnitude. Despite this and the higher resource, the estimated levelized cost of energy (LCoE) is higher from the offshore sites mainly due to the higher infrastructure costs. Nonetheless, the projected LCoE is highly competitive from all sites considered.

Foody, Rebecca↗
DOE OSTI2024

Statistical Treatment of Convolutional Neural Network Superresolution of Inland Surface Wind for Subgrid-Scale Variability Quantification

Abstract Machine learning models have been employed to perform either physics-free data-driven or hybrid dynamical downscaling of climate data. Most of these implementations operate over relatively small downscaling factors because of the challenge of recovering fine-scale information from coarse data. This limits their compatibility with many global climate model outputs, often available between ∼50- and 100-km resolution, to scales of interest such as cloud resolving or urban scales. This study systematically examines the capability of a type of superresolving convolutional neural network (SR-CNNs) to downscale surface wind speed data over land from different coarse resolutions (25-, 48-, and 100-km resolution) to 3 km. For each downscaling factor, we consider three convolutional neural network (CNN) configurations that generate superresolved predictions of fine-scale wind speed, which take between one and three input fields: coarse wind speed, fine-scale topography, and diurnal cycle. In addition to fine-scale wind speeds, probability density function parameters are generated through which sample wind speeds can be generated, accounting for the intrinsic stochasticity of wind speed. For assessing generalization to new data, CNN models are tested on regions with different topography and climate that are unseen during training. The evaluation of superresolved predictions focuses on subgrid-scale variability and the recovery of extremes. Models with coarse wind and fine topography as inputs exhibit the best performance when compared with other model configurations, operating across the same downscaling factor. Our diurnal cycle encoding results in lower out-of-sample generalizability when compared with other input configurations.

17 WIND ENERGY↗
DOE OSTI2025

Multi-seasonal measurements of the ground-level atmospheric ice-nucleating particle abundance on the North Slope of Alaska

Atmospheric ice-nucleating particles (INPs) are an important subset of aerosol particles that are responsible for the heterogeneous formation of ice crystals. INPs modulate the arctic cloud phase (liquid vs. ice), resulting in implications for radiative feedbacks. The number of arctic INP studies investigating specific INP episodes or sources increased recently. However, existing studies are based on short-duration field data, and long-term datasets are lacking. Continuous, long-term measurements are key to determining the abundance and variability of ambient arctic INPs and constraining aerosol–cloud interactions, e.g., to verify and/or improve simulations of mixed-phase clouds. Here, we present a new long-duration INP dataset from the Arctic: 2 years of predominantly immersion-mode INP concentrations (n INP ) measured continuously at the National Oceanic and Atmospheric Administration's Barrow Atmospheric Baseline Observatory (BRW) on the North Slope of Alaska. A portable ice nucleation experiment chamber (PINE-03), which simulates adiabatic expansion cooling, was used to directly measure the ground-level INP abundance with an approximately 12 min time resolution from October 2021 to December 2023. We document PINE-03 n INP measurements as well as estimated ice nucleation active surface site density (n s ) over a wide range of heterogeneous freezing temperatures from −16 to −31 °C from which we introduce new season-specific parameterizations suitable for modeling mixed-phase clouds. Collocated aerosol and meteorological data were analyzed to assess the correlation between ambient n INP , air mass origin region, and meteorological variability. Our findings suggest (1) very high freezing efficiency of INPs across the measured temperatures (n s ≈ 2×10 8 –10 10 m −2 for −16 to −31 °C), which is a factor of 10–1000 times greater efficiency as compared to that found in the previous mid-latitude INP measurements in fall using the same instrument; (2) surprisingly high n INP (≥ 1 L −1 at −25 °C) for the examined temperatures throughout the year that were not measured by PINE-03 at other sites; and (3) high n INP in spring, possibly related to arctic haze episodes. Relatively low concentrations of aerosol surface area and contrasting high-INP concentrations at BRW relative to mid-latitude sites are the possible reasons for the observed high freezing efficiency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Effective field theory of dissipative fluids

We develop an effctive fi eld theory for dissipative fluids which governs the dynamics of long-lived gapless modes associated with conserved quantities. The resulting theory gives a path integral formulation of fluctuating hydrodynamics which systematically incorporates nonlinear interactions of noises. The dynamical variables are mappings between a "fluid spacetime" and the physical spacetime and an essential aspect of our formulation is to identify the appropriate symmetries in the fluid spacetime. The theory applies to nonlinear disturbances around a general density matrix. For a thermal density matrix, we require an additional Z2 symmetry, to which we refer as the local KMS condition. This leads to the standard constraints of hydrodynamics, as well as a nonlinear generalization of the Onsager relations. It also leads to an emergent supersymmetry in the classical statistical regime, and a higher derivative deformation of supersymmetry in the full quantum regime.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Cooperativity and Metal–Linker Dynamics in Spin Crossover Framework Fe(1,2,3-triazolate) 2

Cooperative interactions are responsible for the useful properties of spin crossover (SCO) materials–large hysteresis windows, critical temperatures near room temperature, and abrupt transitions–with hybrid framework materials exhibiting the greatest cooperativity and hysteresis of all SCO systems. However, little is known about the chemical origin of cooperativity in frameworks. Here, we present a combined experimental–computational approach for identifying the origin of cooperativity in the metal–organic framework (MOF) Fe(1,2,3-triazolate) 2 (Fe(TA) 2 ), which exhibits the largest known hysteresis window of all SCO materials and unusually high transition temperatures, as a roadmap for understanding the manipulation of SCO behavior in general. Variable-temperature vibrational spectroscopy provides evidence that “soft modes” associated with dynamic metal–linker bonding trigger the cooperative SCO transition. Thermodynamic analysis also confirms a cooperativity magnitude much larger than those of other SCO systems, while electron density calculations of Fe(TA) 2 support previous theoretical predictions that large cooperativity arises in materials where SCO produces considerable differences in metal–ligand bond polarities between different spin states. Taken together, this combined experimental–computational study provides a microscopic basis for understanding cooperative magnetism and highlights the important role of dynamic bonding in the functional behavior of framework materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Correlating Mechanical Sensitivity with Spin Transition in the Explosive Spin Crossover Complex [Fe(Htrz) 3 ] n [ClO 4 ] 2 n

Spin crossover complexes are known to undergo bond length, volume, and enthalpy changes during spin transition. In an explosive spin crossover complex, these changes could affect the mechanical and initiation sensitivity of the explosive and lead to the development of a new class of sensitivity switchable materials. To explore this relationship, the well-known spin crossover compound [Fe(Htrz) 3 ] n [ClO 4 ] 2n (1) was re-evaluated for its explosive properties, and its mechanical impact sensitivity was correlated to spin transition. A variable temperature impact test was developed and used to evaluate the impact sensitivity of 1 in the low spin (LS, S = 0), thermally accessed high spin (HS, S = 2), and mixed LS and HS states. For comparison, the structurally similar Ni compound, [Ni(Htrz) 3 ] n [ClO 4 ] 2n (2), which does not undergo a spin transition at accessible temperatures, was synthesized and characterized, and its explosive properties and variable temperature impact sensitivity measured. These results reveal a correlation between impact sensitivity and spin transition, where 1 exhibits lower impact sensitivity in the LS state and increases in sensitivity upon transition to the HS state. Here, density functional theory was used to predict structural changes that occur upon spin transition that correlate to the change in sensitivity. This demonstrates, for the first time, an explosive spin crossover compound (ExSCO) that exhibits switchable impact sensitivity with a fully reversible internal switching mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Divertor turbulent transport in the single null and snowflake in the TCV tokamak

The relative importance of divertor radial turbulent particle fluxes is considered by comparing it against the fluxes in the main-chamber outer midplane (OMP) in a variety of conditions and divertor geometries in the tokamak à configuration variable. Within the first power falloff length, the radial turbulent fluxes in the leg of the outer divertor are consistently found to be small, and about 1/5th the magnitude measured at the OMP. In a low-density single null divertor, magnetic shear is found to play a strong role in isolating the main-chamber turbulence from the divertor. The snowflake divertor is purported to have turbulence-enhancing properties in the volume between the two X-points but was instead found to further reduce the divertor turbulent fluxes compared to the single null. Depending on the collisionality, the electric field fluctuations and radial turbulent fluxes were higher near the X-point than at the outer midplane, which is likely due to the binormal compression of the flux bundles consistent with analytical models of the resistive X-point mode. Density and potential fluctuation amplitudes decrease monotonically with distance from the OMP with a slope that depends on collisionality.

Physics↗
DOE OSTI2020

Geometric and Material Variability Influences Stress States Relevant to Coastal Permafrost Bluff Failure

Scientific knowledge and engineering tools for predicting coastal erosion are largely confined to temperate climate zones that are dominated by non-cohesive sediments. The pattern of erosion exhibited by the ice-bonded permafrost bluffs in Arctic Alaska, however, is not well-explained by these tools. Investigation of the oceanographic, thermal, and mechanical processes that are relevant to permafrost bluff failure along Arctic coastlines is needed. We conducted physics-based numerical simulations of mechanical response that focus on the impact of geometric and material variability on permafrost bluff stress states for a coastal setting in Arctic Alaska that is prone to toppling mode block failure. Our three-dimensional geomechanical boundary-value problems output static realizations of compressive and tensile stresses. We use these results to quantify variability in the loci of potential instability. We observe that niche dimension affects the location and magnitude of the simulated maximum tensile stress more strongly than the bluff height, ice wedge polygon size, ice wedge geometry, bulk density, Young's Modulus, and Poisson's Ratio. Our simulations indicate that variations in niche dimension can produce radically different potential failure areas and that even relatively shallow vertical cracks can concentrate displacement within ice-bonded permafrost bluffs. These findings suggest that stability assessment approaches, for which the geometry of the failure plane is delineated a priori, may not be ideal for coastlines similar to our study area and could hamper predictions of erosion rates and nearshore sediment/biogeochemical loading.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Uncertainty and Sensitivity Analysis of TREAT Transient Test #15

The U.S. Department of Energy (DOE) is preparing for the resumption of transient testing using the Transient Reactor Test Facility (TREAT) located at the Idaho National Laboratory (INL). In order to support the analysis of TREAT operation and experiment planning, the MAMMOTH reactor physics team has recently begun development of uncertainty and sensitivity analysis for the TREAT core simulated via MAMMOTH. MAMMOTH is a high-fidelity three-dimensional transient multi-physics code developed at INL under the DOE-NE Advanced Modeling and Simulation program (NEAMS) [1]. This research is part of the development presenting some initial uncertainty and sensitivity analysis of TREAT Transient Test #15 [2]. In this summary, we employ the Sobol sampling strategy implemented in RAVEN [3] to efficiently perform the sensitivity and uncertainty analysis. The idea is using Sobol functional decomposition with generalized polynomial chaos (gPC) expansions to estimate the responses of interest [4]. The gPC coefficients are then computed via the spectral projection method with sparse grid approach. In addition, this strategy includes evaluation of the second or higher order sensitivity indices, allowing the study of interactions between several input variables. The principal focus of this analysis is to quantify the uncertainties in the total power and maximum fuel temperatures with respect to uncertainties in the initial transient conditions, such as rated power, fuel temperature, graphite fuel density and control rod boron concentration. In addition, both the first order and second order time-dependent sensitivity indices are computed and analyzed. The results show that the interactions between initial control rod boron concentration and the rated power will contribute at most 1% to the total uncertainty of the power peak.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Uncertainty and Sensitivity Analysis of TREAT Transient Test no. 15

The U.S. Department of Energy (DOE) is preparing for the resumption of transient testing using the Transient Reactor Test Facility (TREAT) located at the Idaho National Laboratory (INL). In order to support the analysis of TREAT operation and experiment planning, the MAMMOTH reactor physics team has recently begun development of uncertainty and sensitivity analysis for the TREAT core simulated via MAMMOTH. MAMMOTH is a high-fidelity three-dimensional transient multi-physics code developed at INL under the DOE-NE Advanced Modeling and Simulation program (NEAMS). This research is part of the development presenting some initial uncertainty and sensitivity analysis of TREAT Transient Test no. 15. In this summary, we employ the Sobol sampling strategy implemented in RAVEN to efficiently perform the sensitivity and uncertainty analysis. The idea is using Sobol functional decomposition with generalized polynomial chaos (gPC) expansions to estimate the responses of interest. The gPC coefficients are then computed via the sparse grid spectral projection method. In addition, this strategy includes evaluation of the second or higher order sensitivity indices, allowing the study of interactions between several input variables. The principal focus of this analysis is to quantify the uncertainties in the total power and maximum fuel temperatures with respect to uncertainties in the initial transient conditions, such as rated power, fuel temperature, graphite fuel density and control rod boron concentration. In addition, both the first order and second order time-dependent sensitivity indices are computed and analyzed. The results show that the interactions between initial control rod boron concentration and the rated power will contribute at most 1% to the total uncertainty of the power peak.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Variable Grid Method

NETL’s Variable Grid Method (VGM) is a novel approach that leverages GIS capabilities to simultaneously visualize and quantify spatial data trends and underlying data uncertainty. The flexible VGM approach utilizes a range of spatial datasets and uncertainty quantifications, which can be calculated using data related to sample density, sample variance, interpolation error, multiple simulations, etc., to create an integrated visualization of data and uncertainty. The intuitive manner of the VGM helps communicate the relationship between uncertainty and spatial data to effectively guide research, support advanced computation analyses, and helps inform research, management and policy decisions. The VGM approach is being developed into a standalone tool designed to integrate into a variety of research workflows, providing users the capabilities to utilize the VGM for their datasets, analysis, and models in support of their decision making needs. The VGM approach was developed as part of NETL’s Offshore portfolio. It was further matured and utilized in projects associated with both NETL’s Unconventional Resources and Carbon Storage portfolios, and is now being further developed by Varigrid, LLC.

Carbon Storage↗