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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Corrosion of Rare-Earth Disilicate Environmental Barrier Coatings in Gas Turbine Environments—Part 2: Microstructure Model

A model for the volatization of ytterbium disilicate (YbDS) by water vapor is developed. The new model is based on the Deal & Grove theory of the thermal oxidation of silicon [1], generalized here to account for the multi-step, second-order chemical reactions for silica depletion, multi-component mixture effects, and the unsteady porous microstructural evolution of the corroded inner zone. With the new model, the fundamental kinetic rate and standard porous media parameters are determined using the atmospheric steam jet impingement experiment of Ridley & Opila [2] and compared to results from the original Deal & Grove model. Fixing the input parameters in each respective model, a validation study (blind prediction) is presented for the high Reynolds number (1 × 105) and high pressure (14.7 atm) burner rig experiment of Wan et al. [3].

Cha, Chong M [Rolls Royce]↗
DOE OSTI2025

MCCCS-MN

The MCCCS‒MN (Monte Carlo for Complex Chemical Systems‒Minnesota) software is developed by the Siepmann research group at the University of Minnesota. MCCCS‒MN allows for the simulation of multi-component molecular systems in the canonical, isobaric-isothermal (including constant stress for solids), grand-canonical, semi-grand, and Gibbs (NVT, NPT, and more than two simulation boxes) ensembles. It uses the configurational-bias Monte Carlo method to efficiently sample phase space for linear, branched and cyclic chain molecules, the adiabatic nuclear and electronic sampling Monte Carlo method to treat many-body polarization effects, and the aggregation-volume-bias Monte Carlo algorithm to efficiently sample the spatial distribution of associating molecules. MCCCS-MN employs a molecular representation of the system where force fields contain bonded and non-bonded terms. Funding for the development of MCCCS-MN through grants from the National Science Foundation (simulation of fluid phase equilibria and chromatography) and the Department of Energy (simulation of adsorption equilibria) is gratefully acknowledged.

Siepmann, J.Ilja [University of Minnesota - Twin C↗
DOE OSTI2024

Utah FORGE 2-2439v2: Characterizing In-Situ Stress with Laboratory Modelling and Field Measurements - 2024 Annual Workshop Presentation

This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the Utah FORGE Site: Laboratory Modelling and Field Measurements project by The University of Pittsburgh, presented by Andrew Bunger. The project characterizes the stress in the Utah FORGE EGS reservoir using three methods: Method 1: Demonstrate complimentary laboratory rock-core stress estimation combined with Machine Learning approach for measuring in-situ stress from field sonic log data; Method 2: Complete field based in-situ measurement (mini-frac); and Method 3: Develop a mechanics-based method for connection near wellbore stress measurements to stresses away from the well-bore. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 14, 2024.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Plasma Surface Interactions: Predicting the Performance and Impact of Dynamic PFC Surfaces

The objective of this project is to develop, and integrate, high-performance simulation tools capable of predicting plasma-facing component (PFC) operating lifetime and the impact of the evolving surface morphology of tungsten-based PFCs on plasma contamination, including the dynamic recycling of fuel species and tritium retention, in future magnetic fusion devices. Establishing a fundamental physical understanding and developing predictive capabilities of plasma-surface interactions (PSI) requires simultaneously addressing complex and diverse physics occurring over a wide range of length (Angstroms to meters) and time (femtoseconds to years) scales, as well as integrating extensive physical processes across the plasma–surface interface. This requires development of not only detailed physics models and computational strategies at each scale, but also algorithms and methods to couple them effectively in a way that can be robustly validated. Deploying these tools requires the continued development and coupling of leadership-scale computational codes to describe the boundary plasma and the evolving PFC surface, as well as a host of simulations that bridge disparate scales to address complex physical and computational issues at the plasma–surface interface in multi-component materials systems for magnetic fusion energy development beyond ITER.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Lower-length-scale modeling of chemical additions, corrosion and fission products in select MSR base salts

Molten salts play a crucial role in advancing Generation IV nuclear energy technology, with chloride-based salts like NaCl-UCl 3 garnering significant attention due to their distinctive properties. However, the corrosive nature of molten salts causes the dissolution of chromium (Cr), leading to the formation of CrCl 2 and CrCl 3 species in molten chlorides. Moreover, the radioactive decay of nuclear fuel gives rise to fission products, including Cs, Sr, and I chlorides. The first part of this report presents a comprehensive study utilizing ab initio molecular dynamics (AIMD) simulations to investigate the properties of eutectic NaCl-UCl 3 molten salt in the presence of corrosion products (CrCl 2 and CrCl 3 ) and fission product (CsCl). The study focuses on essential structural and thermophysical properties such as density, mixing energy, coordination numbers (CN), and Radial Distribution Functions (RDF) of the salts with varying compositions of corrosion products and fission product, covering a range from 0% to 13.5%. The results offer valuable insights into the behavior of corrosion and fission products in uranium-based molten salts, providing essential data that can be used as input to the MTDB-TC and MSTDB-TP property databases being developed by the NEAMS program. Due to their favorable characteristics such as low melting points, high boiling points, and low costs, MgCl 2 +NaCl+KCl (MNK) eutectic salts have recently attracted attention as high-temperature heat transfer fluids. The incorporation of LiCl into MNK salts can further reduce their melting points and increase their specific heat capacities, which is de- sirable for high-temperature heat transfer applications. The second part of this report presents the development and validation of a new shell-model potential for the MgCl 2 +NaCl+KCl+LiCl system, which captures the polarization of Cl anions. The extensive comparison with experimental data and AIMD simulations demonstrates the accuracy and reliability of the potential. Furthermore, using this potential, we elucidate the intricate network structure in MNK eutectic salts that is formed through polyhedron sharing. This research contributes to a fundamental understanding of the atomic structures and thermophysical properties of multi-component molten salts, which is crucial for future development of heat transfer fluids for applications in molten salt reactors.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ML-based Data Assimilation and History Matching: Application to the IBDP CCS Project

It is crucial to monitor the CO2 plume effectively throughout the life cycle of a geologic CO2 sequestration project to ensure safety and storage efficiency. However, the computational cost of existing data assimilation methods can be prohibitively expensive due to the complex physics with multi-component non-isothermal simulation and high dimensionality of large-scale reservoir models. We address this challenge by proposing an accelerated deep learning-based workflow for model calibration and prediction of CO2 plume evolution in the reservoir.The power and efficacy of our workflow is demonstrated by application to the Illinois Basin-Decatur Project (IBDP), a large-scale CO2 storage test in saline aquifer. The data assimilation process is implemented rapidly by the proposed workflow with given field measurements including distributed pressure and temperature sensing (DTS) data at an injection and a monitoring well. CO2 plume evolution is predicted by running the simulations of the calibrated reservoir models.

Nagao, Masahiro↗
DOE OSTI2025

Developing Open-Source Tools for Increasing the Efficiency of Synthetic Aviation Turbine Fuel Certification Process

FuelLib is an open-source Python-based fuel library, developed by NREL, that leverages the group contribution method (GCM) of [1] to systematically estimate the thermodynamic and transport properties of hydrocarbon fuels. FuelLib predicts these properties based on the molecular structure of individual compounds or compound families, using weight percentages of a fuel's composition, typically measured using techniques such as gas chromatography (GC). FuelLib enables property estimation over a wide range of temperatures and pressures of multi-component fuels in the absence of detailed molecular composition data, making it particularly valuable for complex fuel mixtures where detailed experimental characterization of fuel composition is unavailable. These capabilities contribute directly to synthetic aviation turbine fuels (SATF) development, supporting the short-term American Society for Testing and Materials (ASTM) qualification of drop-in fuels while potentially expanding ASTM boundaries to certify a broader range of fuels.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Dusty Gas Model for Solid Oxide Fuel Cell Fuel Electrode

This model applies the Dusty Gas Model simulate multi-component species transport in SOFC (solid oxide fuel cell) anodes which considers the pressure gradient across the fuel electrode. This studyhas been verified with the analytical solution for different fuel electrode thicknesses and with literature values. The model was developed using the VoronoiFVM platform in Julia which is a built in implicit and semi implicit solver that integrates electrochemical behavior, microstructural effects, and transient analysis for accurate prediction of species transport under varying conditions.

dusty gas model (DGM)↗
DOE OSTI2025

SAM Enhancements for Air-Ingress Event Modeling in HTGRs

The SAM code is under development and supported by DOE-NE’s Nuclear Energy Advanced Modeling and Simulation program as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. These advanced reactor concepts incorporate novel and improved approaches to achieve safety and economic feasibility. This report summarizes recent efforts and progress in addressing the code capability gaps in SAM for the modeling of the air-ingress phenomenon in High-Temperature Gas-Cooled Reactors (HTGRs). The capability enhancements implemented to the code include: a multi-component flow model to capture the air-helium mixture during air ingress, a 0-D graphite oxidation model to capture the reaction of graphite with oxygen in the air, and an isentropic critical flow model to more accurately predict the de-pressurization of the reactor system due to a small break in the primary loop. Verification cases and demonstrations are provided to showcase these capabilities in SAM. Existing gaps in the code’s capability are also identified.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Probing Condensed-Phase Structure and Dynamics in Hierarchical Zeolites and Nanosheets for Catalytic Upgradation of Biomass (Final Report)

Understanding complex reaction pathways in systems governed by multi-scale collective interactions across time and length scales remains a central scientific challenge. This project was guided by the hypothesis that the interplay among oligomers, solvents, and active sites can be tuned by a suitable choice of solvation environment and pore architecture in solid-acid catalysts to direct chemical transformations relevant to biomass conversion. Zeolites and zeolite nanosheets were used as model platforms, allowing for the interaction of macromolecules with the surface of the zeolite nanosheets and with smaller pores that host catalytically active sites. To investigate these coupled phenomena, we employ a multi-scale computational framework that integrates molecular-level descriptions with advanced sampling approaches to capture key physical and chemical interactions. Our work through this project improved fundamental understanding of how reactants and solid-acid catalysts interact in solvent-rich environments, thereby enabling the rational design of catalytic systems that upgrade biomass with enhanced selectivity and energy efficiency. In addition, the project developed advanced sampling methodologies critical for disentangling complex, reactive processes in multi-component catalytic environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

FY24 Task 4: Studies of Phosphate and Fluoride Solubility for Dissolution of High Phosphate Tank Waste

Knowledge gaps have been identified in phosphate solubility in almost every single- and multi-component system, and particularly for aluminate in phosphate/hydroxide, where uncertainties in predicted values of aluminum solubility are greater than 50%. Solubility data of multicomponent, aqueous electrolytes containing sodium hydroxide, sodium fluoride, sodium phosphate, sodium nitrite, sodium nitrate, and dissolved gibbsite are also sparse. For example, for solutions of (i) sodium nitrate and sodium phosphate, data are only available at 30 and 50 °C, and for (ii) dissolved gibbsite in sodium hydroxide and sodium phosphate, only two data points are available at 20 and 40 °C. There is no data available on mixtures of sodium hydroxide, sodium phosphate, sodium fluoride, and dissolved gibbsite. These knowledge gaps were identified in a technical review of waste solubility data and the impact of dilution on solution stabilities and will be addressed in this work to predict aluminum hydroxide and sodium phosphate solubility in multicomponent electrolytes upon dilution, and upon variation of temperature. Results will provide the technical basis to develop accurate models for (i) gibbsite solubility and mass transfer of aluminum between solid and liquid forms following the sluicing of sludge and saltcake with water; and (ii) further blending of these suspensions with bismuth from bismuth phosphate waste, and zirconium and uranium left from the fuel decladding. This work will be essential to developing a disposition path for retrieval solutions from bismuth phosphate wastes. This effort would also support sludge washing to further reduce phosphate concentration if that process were to be added back to the flowsheet in the future.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Evaluation of Additively Manufactured Monolithic SiC and SiC Ceramic Matrix Composites for CSP- Fabrication and Testing of Receiver Design Feature Specimens in a Simulating Lab Test via Laser Heating

Critical to the creation of a multi-component SiC receiver design concept capable of meeting the SETO CST cost goal objectives of <$150/kWth is the optimal utilization of material for solar absorption and heat transfer to transport fluid. This is to maximize the solar-thermal efficiency in the techno-economic analysis of derived use case. As a first step in preparation of sub-component design for on-sun test evaluations we use different proposed SiC absorber element in a customized laser heat flux test to assess an effective heat transfer coefficient characteristic of the design. The test results are analyzed to extract the effective heat transfer coefficient, thus enable optimization of the geometry of receiver components for heat transfer, efficiency attributes and the thermo-structural management of the components. High intensity CO2 laser is used in combination with air flow through the test specimen to assess the effective heat transfer coefficient under heat flux conditions corresponding to high solar concentrations in the range of 1000-2000 suns.

14 SOLAR ENERGY↗
DOE OSTI2026

HTGR Multiphysics Application Drivers FY26 Updates

This report summarizes FY26 progress under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program's high-temperature gas-cooled reactor (HTGR) application driver work, covering a wide range of activities such as code validation and multi-physics code assessment. 1) A detailed SAM model of the High-Temperature Engineering Test Reactor (HTTR) was developed using a unique-block grouping approach, with an extended parallel thermal network method to capture block-to-block conduction and radiation heat transfer, and applied to steady-state simulations of the HTTR 30~MW and 9~MW cases. 2) In another activity, SAM's newly implemented multi-component gas flow model was validated against the Natural convection Shutdown heat removal Test Facility (NSTF) argon ingress experiment, correctly capturing the density-driven suppression and thermal recovery of natural circulation observed when argon is introduced into the air-cooled Reactor Cavity Cooling System (RCCS) loop. 3) For the OECD/NEA High Temperature Test Facility (HTTF) benchmark, we co-led the international benchmark activities as well as the OECD/NEA final benchmark report to be released at the end of this year. 4) Finally, the coupled Griffin-SAM modeling capability for pebble-bed HTGRs was advanced by verifying the Griffin neutronics solution against Serpent Monte Carlo for a realistic non-uniform temperature distribution, resolving several deficiencies in the SAM-to-Griffin temperature transfer scheme, and enabling distinct fuel kernel, moderator, and coolant temperatures for cross section feedback. These new features were demonstrated in a PBR load-following transient.

Lee, Alvin↗
DOE OSTI2024

Chiral, Topological, and Knotted Colloids in Liquid Crystals

The geometric shape, symmetry, and topology of colloidal particles often allow for controlling colloidal phase behavior and physical properties of these soft matter systems. In liquid crystalline dispersions, colloidal particles with low symmetry and nontrivial topology of surface confinement are of particular interest, including surfaces shaped as handlebodies, spirals, knots, multi-component links, and so on. These types of colloidal surfaces induce topologically nontrivial three-dimensional director field configurations and topological defects. Director switching by electric fields, laser tweezing of defects, and local photo-thermal melting of the liquid crystal host medium promote transformations among many stable and metastable particle-induced director configurations that can be revealed by means of direct label-free three-dimensional nonlinear optical imaging. The interplay between topologies of colloidal surfaces, director fields, and defects is found to show a number of unexpected features, such as knotting and linking of line defects, often uniquely arising from the nonpolar nature of the nematic director field. This review article highlights fascinating examples of new physical behavior arising from the interplay of nematic molecular order and both chiral symmetry and topology of colloidal inclusions within the nematic host. Furthermore, the article concludes with a brief discussion of how these findings may lay the groundwork for new types of topology-dictated self-assembly in soft condensed matter leading to novel mesostructured composite materials, as well as for experimental insights into the pure-math aspects of low-dimensional topology.

chirality↗
DOE OSTI2023

Ultra-high temperature carbide foams and methods of fabricating the same

Ultra-high temperature carbide (UHTC) foams and methods of fabricating and using the same are provided. The UHTC foams are produced in a three-step process, including UHTC slurry preparation, freeze-drying, and spark plasma sintering (SPS). The fabrication methods allow for the production of any kind of single- or multi-component UHTC foam, while also providing flexibility in the shape and size of the UHTC foams to produce near-net-shape components.

Agarwal, Arvind↗
DOE OSTI2024

Accelerating Thermochemical Equilibrium Calculations for Nuclear Reactor Applications

Thermochemical properties play a key role in modeling and simulation of several key phenomena in nuclear reactors. There has been an increasing interest in incorporating CALPHAD-based formulations in multiphysics simulations including for Molten Salt Reactors where knowledge of phase evolution of the salt and the chemical potentials of various elements are of utmost importance in source term analyses and redox control. However, the size of such simulations is often limited by the high computational cost of full thermodynamic equilibrium calculations. This work discusses the current efforts aimed at accelerating thermochemical equilibrium calculations for multiphysics simulations performed using the open-source finite element / finite volume code Multiphysics Object Oriented Simulation Environment (MOOSE) [1]. While several methods have been proposed for accelerating phase equilibrium calculations [2], most focus on relatively small systems and often rely on a- priori knowledge of the state-space of the system. Nuclear materials, however, are often multi-component systems owing to the evolution of composition under irradiation and an approach based on a-priori mapping of phase diagram is often not enough. This work is aimed at demonstrating an on-the-fly surrogate modeling framework that uses active learning to reduce the number of full equilibrium calculations that must be performed. By combining with efficient coupling approaches, the surrogate framework helps in reducing the computational cost of thermodynamic equilibrium informed multiphysics simulations of nuclear materials. The performance is benchmarked against full coupling with the thermochemistry library Thermochimica [3]. This work uses a machine learning based approach for constructing surrogate models to predict the stable phases in a multicomponent system. The surrogates were constructed using neural networks and Gaussian process classification. In this work, we compare the relative performance of the two methods. We also demonstrate the use of caching previous calculations by interpolating the values from nearest neighbors. References [1] Lindsay, A.D., et al. "2.0 – MOOSE: Enabling massively parallel multiphysics simulation", SoftwareX, 20 (2022): 101202. [2] Roos, W.A. and Zietsman J.H. "Accelerating complex chemical equilibrium calculations – A Review", Calphad, 77 (2022): 102380. [3] Piro, M.H.A., et al. "The thermochemistry library Thermochimica", Computational Materials Science, 67 (2013): 266-272.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Elucidating the Radiation-Induced Redox Chemistry of Plutonium Under Used Nuclear Fuel Reprocessing Conditions

Plutonium plays a critical role in the development of sustainable nuclear fuel cycles, and yet, our fundamental understanding of this element’s inherent radiation-induced redox chemistry and associated impacts on nuclear fuel cycle technologies is limited. Unanticipated changes in oxidation state distribution can influence the speciation and transport of plutonium in a given process. Control of these parameters is especially important for used nuclear fuel reprocessing technologies, wherein the separation and recovery of plutonium is typically achieved by the selective formation, maintenance, and complexation of specific oxidation states. Furthermore, plutonium’s inherent radiation-induced redox chemistry has the capacity to influence the radiolytic behavior of its complexes, the longevity of which are critical in the design of efficient and cost-effective advanced reprocessing technologies. These radiation-induced processes are unavoidable under fuel cycle conditions owing to the inherency of ionizing radiation fields to the decay of plutonium’s isotopes and to the various other radioisotopes generated by nuclear fission and neutron-capture process and the subsequent radioactive decay of their products. As such, mechanistically understanding the response of plutonium’s multiple oxidation states to multi-component ionizing radiation fields is essential for predicting the behavior of this critical element under used nuclear fuel reprocessing conditions. Here, through a combination of time-resolved (electron pulse) and steady-state (alpha and gamma) irradiation experiments complemented by quantitative, multiscale modeling calculations, we present advances in our understanding of radiation-induced plutonium redox chemistry!

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

Characterizing the GD-1 Stream with DESI DR2 Data: Thin Stream and Hot Cocoon

GD-1 is among the longest, coldest stellar streams in the Milky Way, making it an ideal target for probing dark matter substructure through dynamical heating. We present a catalog of 608 spectroscopically confirmed GD-1 members from the first three years of Dark Energy Spectroscopic Instrument (DESI) observations. This constitutes the largest homogeneous spectroscopic sample of GD-1, doubling the number of members previously available only through heterogeneous compilations combining multiple surveys with different systematics. Using these data, we derive updated stream tracks in sky position, proper motion, and radial velocity that extend over $100^\circ$ of the stream. We apply a Gaussian mixture model to decompose the stream into a dynamically cold thin component ($σ_V = 2.49\pm 0.28$ km s$^{-1}$, width $= 0.23\pm0.01^\circ$) and a kinematically hot cocoon ($σ_V = 6.13\pm0.75$ km s$^{-1}$, width $= 2.18\pm0.17^\circ$). The cocoon contains $\sim30\%$ of members and its velocity dispersion is consistent with $\sim11$ Gyr of heating by cold dark matter subhalos. We also detect a large proper motion dispersion ($41.36\pm4.98$ km s$^{-1}$) along the stream direction in the cocoon component. This feature indicates a significant line-of-sight distance spread in the cocoon, and its origin will be further explored in a forthcoming paper. These measurements demonstrate the power of DESI spectroscopy for characterizing the multi-component phase-space structure of stellar streams and constraining small-scale dark matter substructure.

Jarvis, Emma [Toronto U.] (ORCID:0009000656127336)↗