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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 OSTI2014

Toward Understanding the Effect of Low-Activity Waste Glass Composition on Sulfur Solubility

The concentration of sulfur in nuclear waste glass melter feed must be maintained below the point where salt accumulates on the melt surface. The allowable concentrations may range from 0.37 to over 2.05 weight percent (of SO3 on a calcined oxide basis). If the amount of sulfur exceeds its tolerance level a molten salt will accumulate and upset melter operations and potentially shorten melter useful life. Therefore relatively conservative limits have been placed on sulfur loading in melter feed which in-turn significantly impacts the amount of glass that will be produced, in particular at the Hanford site. Crucible-scale sulfur solubility data and scaled melter sulfur tolerance data have been collected on simulated Hanford waste glasses over the last 15 years. These data were compiled and analyzed. A model was developed to predict the solubility of SO3 in glass based on 312 individual glass compositions. This model was shown to well represent the data, accounting for over 80% of the variation in data and was well validated. The model was also found to accurately predict the tolerance for sulfur in melter feed based on 19 scaled melter tests. The model is appropriate for control of waste glass processing which includes uncertainty quantification. The model also gives quantitative estimates of component concentration effects on sulfur solubility. The components that most increase sulfur solubility are Li2O > V2O5 ≈ TiO2 < CaO < P2O5 ≈ ZnO. The components that most decrease sulfur solubility are Cl > Cr2O3 > SiO2 ≈ ZrO2 > Al2O3.

Borosilicate↗
DOE OSTI2023

Canister Centerline Cooling Experiments for DPF5-336 Reference Material Made with ERV3b Salt Simulant

This report provides experimental details and results on the elemental distributions (compositions), crystalline/amorphous phase distribution, and microstructures for DPF5-336 reference materials made with ERV3b salt that were subjected to the canister centerline cooling (CCC) heat treatment process. To fabricate these materials, ammonium dihydrogen phosphate was mixed with ERV3b salt simulant and a dechlorination procedure was run in the generation-2 dechlorinator at the Pacific Northwest National Laboratory up to 600°C in an alumina crucible. After the dechlorination process, the product was removed from the crucible, lightly crushed, loaded into a new alumina crucible, Fe 2 O 3 was added, and this was vitrified at 1100°C for 1 hour and quenched. The quenched material was mostly amorphous but showed some small diffraction peaks attributed to Li 3 Fe 2 (PO 4 ) 3 . This quenched material was ground to a fine particle size in a milling chamber, and this was subjected to the CCC cooling profile in duplicate within alumina and fused quartz crucibles. The CCC experiment is designed to simulate the slowest cooling profile (the vertical centerline) of a 0.61-m diameter canister where the slower cooling profile often results in the production of a variety of different crystalline phases upon formation of which result in a residual glass of unknown composition and properties. The information gleaned from these types of experiments will lead to improved composition-property predictions for materials with similar compositions. The results of the alumina and fused quartz experiments show different microstructures but similar diffraction patterns providing evidence of similar crystalline phases being present in each sample. Both samples had monazite [i.e., (Ce,Nd)PO 4 ] and mixtures of phases containing P, Fe, and alkali metal elements. This report completes the milestone M4FT-23PN030104042 with details provided in Appendix B.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Impact of High Performance Computing on the Detailed Simulation of Subsurface Flow and Contaminant Transport Using eSTOMP - 16341

The ability to model subsurface processes at the field-scale is essential to site closure and remedial action decisions. Field-scale models often require high-performance computing to meet the computational demands associated with complex systems, model calibration, and uncertainty quantification. eSTOMP, a parallel version of STOMP, is an analytical tool that meets the need for investigating coupled processes in the subsurface involving regional multi-fluid flow and biogeochemistry. The scalability of eSTOMP makes it ideal for simulating contaminant and geochemical reactive transport when long run times result from execution of a serial code. To demonstrate the impact of high-performance computation on subsurface analyses, the application of eSTOMP is presented for two sites. The first site involves uranium surface complexation within a highly dynamic, variably saturated flow field. The use of this model in conjunction with continued field monitoring is expected to provide a rigorous basis for developing operational strategies for field remediation and for defining defensible remediation endpoints. The second site involves the long-term dissolution of low-level radioactive glass emplaced within a near-surface repository. The waste form release rate is evaluated by modeling the basic physical and chemical processes that are known to control the waste form dissolution behavior, including pH and composition of the fluid contacting the glass. Simulations demonstrate that glass dissolution rates vary both in time and as a function of position within the disposal system, and that a 'leach rate' or radionuclide release rate parameter can only be estimated after identifying these impacts in a dynamic system. (authors)

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

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

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

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Demonstration of sulfur solubility determinations in high waste loading, low-activity waste glasses

A method recommended by Pacific Northwest National Laboratory (PNNL) for sulfate solubility determinations in simulated low-activity waste glasses was demonstrated using three compositions from a recent Hanford high waste loading glass study. Sodium and sulfate concentrations in the glasses increased after each re-melting step. Visual observations of the glasses during the re-melting process reflected the changes in composition. The measured compositions showed that the glasses met the targeted values. The amount of SO 3 retained in the glasses after washing was relatively high, ranging from 1.6 to 2.6 weight percent (wt %). Measured SnO 2 concentrations were notably low in all of the study glasses. The composition of the wash solutions should be measured in future work to determine whether SnO 2 is present with the excess sulfate washed from the glass. Increases in batch size and the amount of sodium sulfate added did not have a measureable impact on the amount of sulfate retained in the glass, although this was tested for only a single glass composition. A batch size of 250 g and a sodium sulfate addition targeting 7 wt %, as recommended by PNNL, will be used in future experiments.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Study of the processes of degradation of the optical properties of mesoporous and macroporous silicon upon exposure to simulated solar radiation

The effect of solar radiation on the surface composition of mesoporous and macroporous silicon is studied by infrared spectroscopy, Raman spectroscopy, and photoluminescence measurements in order to analyze the possibility of using these materials as a material for solar-power engineering. The studies are conducted in the laboratory environment, with the use of a solar-radiation simulator operating under conditions close to the working conditions of standard silicon solar cells. The studies show that, in general, the materials meet the requirements of solar-power engineering, if it is possible to preclude harmful effects associated with the presence of heat-sensitive and photosensitive bonds at the nanomaterial surface by standard processing methods.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Update of Residential Load Profile for WECC Load Composition Model Using Cross-Correlation Method

The Western Electricity Coordinating Council (WECC) initiated the development of a composite load model for transmission-level power system simulators. To more precisely utilize the model to represent the power consumption pattern for various locations of the WECC network, an up-to-date load composition dataset is required. The study in this paper aims to reconstruct the residential sector of the load composition model (LCM) dataset using latest survey or measurement data. The LCM residential dataset contains load profiles for twelve climate zones and five season types. The northwest energy efficiency alliance (NEEA) launched a study to generate the load profiles for four climate zones in the Pacific Northwest. Based on the NEEA database, a component-wise cross-correlation-based approach has been developed in this paper to update the obsolete residential load profiles of the four pacific northwest climate zones and populate the new load shape data into the other eight climate zones.

Liu, Yuan↗
DOE OSTI2020

Multiscale-Informed Modeling of High Temperature Component Response with Uncertainty Quantification

This report summarizes a joint effort between Argonne National Laboratory, Idaho National Laboratory, and Los Alamos National Laboratory to develop and deploy constitutive models targeted at predicting the life of Grade 91 alloy components subjected to high temperature environments typical of those that structural components in advanced nuclear reactors would experience. Two distinct, but complementary constitutive modeling approaches have been taken here. The first employs a phenomenological viscoplastic model for which parameters have been calibrated based on experimental data for a wide range of Grade 91 alloy that has undergone a variety of processing. A Bayesian approach was used to derive distributions of uncertain parameters for this model based on this data set. The second approach is a reduced order model suitable for engineering-scale analysis that is based on the results of a large set of mesoscale simulations. Mesoscale models allow for the microstructure and composition of a particular alloy to be directly taken into account in the computation of the viscoplastic response, but are computationally expensive, which makes it impractical to directly call those models for the material constitutive response in an engineering-scale simulation. The reduced-order representation of the response of the underlying model used here allows for an engineering-scale model to take into account the characteristics of the underlying microstructure, while only incurring a reasonable computational expense. Both of these approaches have different strengths, and are applicable for different parts of the design/analysis process. The phenomenological models can be readily parameterized based on a set of experimental data for a given class of materials and used for scoping calculations. Once a specific material is chosen and adequately characterized, the reduced order models can accurately predict the response of that specific alloy, and because the models are based on predictive models of the underlying microstructure, they can be used to more confidently predict the response under conditions in regions where there is limited experimental data. Both of these models have been integrated in the Grizzly code, which is used here to perform proof-of-concept uncertainty quantification analyses of a simple component under prototypical conditions. The built- in stochastic analysis capabilities in the MOOSE framework that Grizzly is built on are used here to run large sets of simulations for this uncertainty quantification analysis. As would be expected, because the reduced order models are developed for a much more tightly defined alloy, they predict tighter distributions of the time to failure than the phenomenological models, which are calibrated to a broader set of data. Also important is that these simulations demonstrate that a reduced order modeling approach can be successfully deployed to propagate uncertainties from the material scale to practical engineering-scale component simulations.

42 ENGINEERING↗
DOE OSTI2022

Effective radiative forcing of anthropogenic aerosols in E3SMv1: historical changes, causality, decomposition, and parameterization sensitivities

The effective radiative forcing of anthropogenic aerosols (ERF aer ) is an important measure of the anthropogenic aerosol effects simulated by a global climate model. Here we analyze ERF aer simulated by the E3SMv1 atmosphere model using both century-long free-running atmosphere-land simulations and short nudged simulations. We relate the simulated ERF aer to characteristics of the aerosol composition and optical properties, and evaluate the relationships between key aerosol and cloud properties. In terms of historical changes from the year 1870 to 2014, our results show that the global mean anthropogenic aerosol burden and optical depth increase during the simulation period as expected, but the regional averages show large differences in the temporal evolution. The largest regional differences are found in the emission-induced evolution of the burden and optical depth of the sulfate aerosol: a strong decreasing trend is seen in the Northern Hemisphere high-latitude region after around 1970, while a continued increase is simulated in the tropics. Consequently, although the global mean anthropogenic aerosol burden and optical depth increase from 1870 to 2014, the ERF aer magnitude does not increase after around year 1970. The relationships between key aerosol and cloud properties (relative changes between preindustrial and present-day conditions) also show evident changes after 1970, diverging from the linear relationships exhibited for the period from 1870 to 2014. The ERF aer in E3SMv1 is relatively large compared to the recently published multi-model estimates; the primary reason is the large indirect aerosol effect (i.e., through aerosol-cloud interactions). Compared to other models, E3SMv1 features a stronger sensitivity of the cloud droplet effective radius to changes in the cloud droplet number concentration. Large sensitivity is also seen in the liquid cloud optical depth, which is determined by changes in both the effective radius and liquid water path. Aerosol-induced changes in liquid and ice cloud properties in E3SMv1 are found to have a strong correlation, as the evolution of anthropogenic sulfate aerosols affects both the liquid cloud formation and the homogeneous ice nucleation in cirrus clouds. The ERF aer estimates in E3SMv1 for the shortwave and longwave components are sensitive to the parameterization changes in both liquid and ice cloud processes. When the parameterization of ice cloud processes is modified, the top-of-atmosphere forcing changes in the shortwave and longwave components largely offset each other, so the net effect is negligible. This suggests that, to reduce the magnitude of the net ERF aer , it would be more effective to reduce the anthropogenic aerosol effect through liquid or mixed-phase clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Controlled surface segregation leads to efficient coke-resistant nickel/platinum bimetallic catalysts for the dry reforming of methane

Surface composition and structure are of vital importance for heterogeneous catalysts, especially for bimetallic catalysts, which often vary as a function of reaction conditions (known as surface segregation). The preparation of bimetallic catalysts with controlled metal surface composition and structure is very challenging. In this study, we synthesize a series of Ni/Pt bimetallic catalysts with controlled metal surface composition and structure using a method derived from surface organometallic chemistry. The evolution of the surface composition and structure of the obtained bimetallic catalysts under simulated reaction conditions is investigated by various techniques, which include CO-probe IR spectroscopy, high-angle annular dark-field scanning transmission electron microscopy, energy-dispersive X-ray spectroscopy, extended X-ray absorption fine structure analysis, X-ray absorption near-edge structure analysis, XRD, and X-ray photoelectron spectroscopy. It is demonstrated that the structure of the bimetallic catalyst is evolved from Pt monolayer island-modified Ni nanoparticles to core–shell bimetallic nanoparticles composed of a Ni-rich core and a Ni/Pt alloy shell upon thermal treatment. As a result, these catalysts are active for the dry reforming of methane, and their catalytic activities, stabilities, and carbon formation vary with their surface composition and structure.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The relation between lignin sequence and its 3D structure

Background: Lignin, the second most abundant biopolymer on earth, plays a major structural role in plants, conferring mechanical strength and regulating water conduction. Understanding the three-dimensional structure of lignin is important for fundamental reasons as well as engineering plants towards lignin valorization. Lignin lacks a specific primary sequence, making its average chemical composition the focus of most recent studies. However, it remains unclear whether the 3D structure of lignin molecules depends on their sequence. Methods: In this work, we performed all-atom molecular dynamics simulation of three S/G-lignin molecules with the same average composition but different sequence. Results: A detailed statistical analysis of the radius of gyration and relative shape anisotropy reveals that the lignin sequence has no statistically significant effect on the global three-dimensional structure. We found however, that homopolymers of C-lignin with the same molecular weight have smaller radii of gyration than S/G-lignin. We attribute this to lower hydroxyl content of C-lignin, which makes it more compact and rigid. Conclusions: The 3D structure of lignin is influenced by the overall content of monomeric units and interunit linkages and not by its precise primary sequence. General Significance: Lignin is assumed to not have a well-defined primary structure. The results presented here demonstrate there are no significant differences in the global 3D structure of lignin molecules with the same average composition but different primary sequence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Shock Loading of Granular Ni/Al Composites. Part 1. Mechanics of Loading

We present molecular dynamics simulations of the thermomechanical response under shock loading of a granular material consisting of laminated Ni/Al grains. We observe two regimes: At low piston velocities (up ≲ 1km/s), the shock wave is diffuse, and the width of the shock front decreases with increasing piston velocity. Beyond a critical shock strength, however, the width remains relatively constant at approximately the mean grain radius. This change in behavior follows from an evolution of the mechanism of compaction with increasing insult strength. Furthermore, the mechanism evolves from plastic deformation-mediated pore collapse for relatively weak shocks, to solid extrusion and fluid ejecta filling pores ahead of the shock front at intermediate strengths, and finally to atomic jetting into the pore for very strong shocks (up ≳ 2 km/s). High-energy fluid ejecta into pores leads to the formation of flow vorticity and can result in a large fraction of the input energy localizing into translational kinetic energy components including the formation of hot spots. This has implications for the mechanical mixing of Ni and Al in these reactive composites.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Drying model of a high salt content cementitious waste form: Effect of capillary forces and salt solution

Highlights: • Drying model for a high salt content cementitious waste form is developed. • Water vapor diffusion and capillary liquid flow are distinguished. • Capillary and salt solution effects are considered in vapor-liquid equilibrium. A water transport model coupling capillary liquid flow with vapor diffusion is developed to describe the drying process for a cementitious waste form with high salinity porewater. Vapor-liquid equilibrium is formulated as the driving force for vapor diffusion and the model accounts for pore capillary and high salinity effects on water thermodynamic activity. Pore filling and porewater surface tension as a function of pore size distribution and water saturation have been quantified for the material. Geochemical speciation modeling is used to simulate porewater activity as a function of composition over the range of saturation. The theoretical relationship between relative humidity and water saturation generally agrees with experimental measurement, and the developed model is capable of predicting drying rates under various external relative humidity conditions. The model was developed to be incorporated into reactive transport models considering the effects of drying such as salt redistribution and efflorescence.

36 MATERIALS SCIENCE↗
DOE OSTI2016

A multiscale hydro-geochemical-mechanical approach to analyze faulted CO 2 reservoirs: Original Research Article: A multiscale hydro-geochemical-mechanical approach to analyze faulted CO 2 reservoirs

This paper applies a multiscale hydro-geochemical-mechanical approach to analyze faulted CO 2 reservoirs using the STOMP-CO 2 -R code that is coupled to the ABAQUS® finite element package. STOMP-CO 2 -R models the reactive transport of CO 2 causing mineral volume fraction changes that are captured by an Eshelby-Mori-Tanka model implemented in ABAQUS®. A three-dimensional (3D) STOMP-CO 2 -R model for a reservoir containing an inclined fault was built to analyze a formation containing a reaction network with 5 minerals: albite, anorthite, calcite, kaolinite and quartz. A 3D finite element mesh that exactly maps the STOMP-CO 2 -R grid is developed for coupled hydro-geochemical-mechanical analyses. The model contains alternating sandstone and shale layers. The impact of reactive transport of CO 2 on the geomechanical properties of reservoir rocks and seals are studied in terms of mineral composition changes that affect their geomechanical responses. Simulations assuming extensional and compressional stress regimes with and without coupled geochemistry are performed to study the stress regime effect on the risk of hydraulic fracture. The tendency for the fault to slip is examined in terms of stress regime, geomechanical and geochemical-mechanical effects as well as fault inclination. The results show that mineralogical changes due to long-term injection of CO 2 reduce the permeability and elastic modulus of the reservoir, leading to increased risk of hydraulic fracture in the injection location and at the caprock seal immediately above the injection zone. Fault slip is not predicted to occur. However, fault inclination and stress regime have an important impact on the slip tendency factor.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Nonparametric Multiparticle Set Methods for Interpreting Environmental Samples

Collection and analysis of environmental samples is commonly used by a range of stakeholders in nuclear safeguards and security contexts. While the ubiquity of samples and their transport in the environment allow regular collection, developing and demonstrating methods for analyzing these samples is difficult. In this work, an environmental sample consists of a set of one or more individual particles. Recent advances in reactor simulation have allowed us to generate data that are more representative of real-world environmental samples, enabling statistically defensible method development and testing. The most notable of these advances is a drastic increase in the number of material depletion regions, which allows our simulations to capture the variation in isotopic composition seen at length scales consistent with environmental samples. Traditional approaches for handling multiparticle samples treat each particle in the sample individually, estimating the quantity of interest (e.g., core-average burnup) resulting from measurement and analysis of signatures (e.g., nuclide assays) from each individual particle. Individual estimates are then averaged to generate a single estimate of the quantity of interest over the entire sample. In this presentation, we introduce two novel approaches for interpreting environmental samples that comprise of multiple particles: (1) the Quantile-Quantile Comparator, which uses a multivariate generalization of quantile-quantile plots for comparing unknown statistical distributions, and (2) the Set Transformer, an attention-based neural network module designed to model interactions among elements (particles) in the input set (sample). Statistically representative sampling cannot be guaranteed as samples are passively collected and are beholden to what particles are available in the environment. These new analysis methods for set-input problems are expected to be more robust than traditional approaches to issues of sampling bias where particles are not uniformly distributed throughout regions of interest, as well as generally outperform traditional approaches by jointly considering all elements in the set. We will present results comparing the performance of traditional single particle approaches and the novel Quantile-Quantile Comparator and Set Transformer for interpretation of simulated environmental samples.

Phathanapirom, Birdy↗
DOE OSTI2021

Scoreboard

Emerging HPC machines have given rise to enhanced compute power that far outstrips the machine's ability to save large scale results for post-processing. To combat this, in situ data analysis techniques are slowly being adopted. With in situ data management favoring workflows composed of multiple simulations and analyses connected in transit on heterogeneous machines, scientists and engineers need a tool that enables them to create data extracts, visualizations, and interactively monitor and steer their simulations. Scoreboard Phase II is a next generation analysis software that supports composite in transit workflows on heterogeneous architectures and restores interactivity to in situ data analysis through simulation monitoring and computational steering. Scoreboard provides a simulation dashboard with graphs of metrics over time, controls for setting custom simulation steering parameters, controls for managing the set of data extracts being produced in the simulation, as well as the ability to explore data extracts, all from a web browser. Realizing the vision outlined in this project required research into making a system that integrates end to end from simulations all the way to the user. In situ tools generally suffer from complexity and excessive software dependencies. Scoreboard, by contrast, is easy to build and integrate into simulation codes and it provides first class FORTRAN support. The Scoreboard library is capable of in situ and in transit data analysis that can produce data extracts commonly needed for Computational Fluid Dynamics (CFD) analysis. Simulations can transparently stage data in transit to a Scoreboard Endpoint program, which can accept their data and produce the requested data extracts. This lets simulations return to their work while the Endpoint works on the analysis. Efficiently staging the data at scale was a topic of this research. Scoreboard provides the means to let the user manage data extracts and monitor/steer many simulations from a web browser. This area of the research focused on discovery of in transit network components to expose and control their steering parameters within an interactive browser-based user interface that includes: system topology, gathered metrics, notifications, dynamically-generated steering controls, and exploration of visualization data products.

Whitlock, BradJoseph [Intelligent Light] (00000001↗
DOE OSTI2014

Structural, vibrational, and elastic properties of a calcium aluminosilicate glass from molecular dynamics simulations: The role of the potential

We study a calcium aluminosilicate glass of composition (SiO{sub 2}){sub 0.60}(Al{sub 2}O{sub 3}){sub 0.10}(CaO){sub 0.30} by means of molecular dynamics. To this end, we conduct parallel simulations, following a consistent methodology, but using three different potentials. Structural and elastic properties are analyzed and compared to available experimental data. This allows assessing the respective abilities of the potentials to produce a realistic glass. We report that, although all these potentials offer a reasonable glass structure, featuring tricluster oxygen atoms, their respective vibrational and elastic predictions differ. This allows us to draw some general conclusions about the crucial role, or otherwise, of the interaction potential in silicate systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗