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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Dynamic responses of submerged components in advanced reactors: experimental and numerical studies

The seismic design of an advanced nuclear reactor must consider the interaction of vessel internal components with the surrounding coolant: fluid–structure interaction (FSI). Available analytical solutions for FSI of submerged components do not accommodate multiple-component, intense seismic inputs and complex reactor and internal geometries. Physical testing of reactor vessels and internals to inform seismic design is impractical and cost-prohibitive, leaving the use of verified and validated, robust numerical models as the only plausible option for analysis and design. Physical data that could be used for validating such numerical models for multi-component shaking are not available. This article describes an experimental program performed on a 6-degree-of-freedom earthquake simulator to generate data that could support validation of seismic FSI numerical models for submerged components in commercial finite element codes. A scaled model of a base-supported reactor vessel with simplified representations of submerged internals was tested to generate submerged-component response histories for a range of seismic inputs. The generated data were used to validate numerical models in the finite element code LS-DYNA. Numerical models were validated for calculation of hydrodynamic pressure responses on internals, in-water frequencies of internals, and acceleration responses of internals. The generated data and the analysis recommendations could aid engineering analysts designing submerged components and systems for seismic effects.

Engineering↗
DOE OSTI2021

High pressure, high flow rate batch mixing apparatus for high throughput experiments

An automated, high pressure, high flow rate batch mixing apparatus has been designed and constructed for rapid, stable, and repeatable mixing of multiple gases and vapors. The apparatus operates as an intermittent batch mixer with cycles of topping off fresh mixture to maintain pressure in an accumulator tank until consumed in an experimental apparatus. At high duty cycles, the apparatus can also function at steady state. This style of mixing is suitable for experiments such as high repetition rate shock tubes and other devices with intermittent flow demands. It is compact and portable, facilitating use in locations such as synchrotron light sources. The entire apparatus is heated to permit the mixing of vapors from species with low volatilities. The apparatus is fully automated and runs for extended periods with the only intervention being to refresh reagent supplies. Here, the accuracy and repeatability of the apparatus were verified by periodic gas sampling and analysis with gas chromatography. Multi-component mixtures spanning a wide range of complexity, dilution, and volatility of constituents have been prepared. The compositions of the majority of the mixture were found to be stable over several filling cycles, repeatable, and with the proper calibration of set-point conditions, accurate. Challenges were encountered preparing a mixture from multi-component liquids, and potential solutions are discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

An experimental and kinetic modeling study of cyclopentane and dimethyl ether blends

Cyclopentane is a suitable naphthene, or cycloalkane, in a palette for multi-component gasoline surrogate fuels due to its presence in market fuels and its relevance to alkyl substituted cyclopentanes also present. However, the previous oxidation studies of cyclopentane have primarily focused on neat mixtures. Blending cyclopentane with dimethyl ether in this work therefore serves to inform our understanding of, and improve predictive models for, multi-component mixtures. Here, the auto-ignition of cyclopentane/dimethyl ether blends was studied in a high-pressure shock tube and in a rapid compression machine. A wide range of temperatures (650 – 1350 K) and elevated pressures of 20 and 40 bar were studied at equivalence ratios of 0.5, 1.0 and 2.0 in air for two blending ratios (30/70 and 70/30 mole% cyclopentane/di-methyl ether mixtures). A detailed kinetic model for cyclopentane was revised to capture the measured ignition delay times and apparent heat release rates in this study. Literature ignition delay time, jet-stirred reactor, and laminar burning velocity measurements of neat cyclopentane were used as additional validation. Improvements to the kinetic model were based on recent literature studies related to sub-models including cyclopentene and cyclopentadiene which allowed the removal of previous local rate-constant optimizations. Low temperature reactivity of cyclopentane was found to be controlled by the branching ratio between concerted elimination of HO͘ 2 and the strained formation of Q&#775OOH radicals in agreement with previous studies. In this study, the low branching ratio of Q&#775OOH formation increases the influence of a competing consumption pathway for cyclopentyl-peroxy (CPTO͘ 2 J) radicals. The sensitivity of the simulated ignition delay times to the formation of cyclopentyl hydroperoxide (CPTO 2 H), from CPTO͘ 2 J and HO͘ 2 , is discussed. The current model is used to analyze the influence of dimethyl ether on the reactivity of cyclopentane in the context of previous literature studies of dimethyl ether binary blends with ethanol and toluene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Heat transfer in directly-irradiated high-temperature solid–gas flows laden with polydisperse particles

Heat transfer in directly-irradiated high-temperature solid–gas flows laden with polydisperse particles is investigated using a novel transient three-dimensional computational fluid dynamics model. The model couples particle–gas hydrodynamics of solid–gas flows laden with polydisperse particles, radiative heat transfer in non-grey absorbing, emitting and anisotropically-scattering multi-component participating media, conduction heat transfer in the gas phase, and interfacial convection heat transfer. The multiphase particle-in-cell method is used to predict high-fidelity solid–gas flow characteristics, such as the local discrete particle size distribution, with increased computational efficiency by combining the advantages of both Eulerian and Lagrangian methods. The multi-component radiative transfer model is implemented using an advanced collision-based Monte Carlo ray-tracing method. The number of the prescribed discrete particle components is found to be the key parameter affecting the computational accuracy and efficiency, which primarily depends on the size distribution of the particles. For the model particle–gas flow featuring free-falling Gamma-distributed ceramic particles exposed to concentrated solar irradiation, the particle volume fraction, radiative, fluid flow and thermal characteristics appear to converge with the increasing number of the discrete particle components. Five particle components are sufficient to obtain physically meaningful results. A further increase in the number of the particle components only slightly increases the accuracy of the numerical predictions at the expense of a rapidly increasing computational time. For five particle components, the particle vertical velocity at the receiver exit for particles with the diameter of 43.4 μm is 57% of that for the particles with the diameter of 202.8 μm. The temperatures of these two particle components increase from the initial ambient values by factors of 2 and 1.2, respectively, during the simulation time. In conclusion, the model developed allows for increased fidelity of particle–gas flow simulations with significant radiative effects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Ab initio property predictions of quinary solid solutions using small binary cells

The Set of Small Ordered Structures (SSOS) approach is an ab initio technique for modelling random solid solutions in which many small structures are averaged so that their correlation functions match those of a desired composition. SSOS has been shown to be effective in reducing the cost of density functional theory calculations relative to other well-known techniques such as cluster expansions and special quasirandom structures for modelling solid solutions. Here in this work, we demonstrate that SSOS’s can be constructed using cells with only a subset of elements while still accurately modelling multi-component systems. Specifically, we show that small binary cells can effectively model two quinary high entropy alloys – NbTaTiHfZr and MoNbTaVW – accurately capturing properties such as formation energy, lattice parameters, elastic constants, and root-mean-square atomic displacements. Overall, this insight is useful for those looking to construct databases of such small structures for predicting the properties of multi-component solid solutions, as it greatly decreases the number of structures that needs to be considered.

36 MATERIALS SCIENCE↗
NASA NTRS2010

Optimized Li-Ion Electrolytes Containing Fluorinated Ester Co-Solvents

A number of experimental lithium-ion cells, consisting of MCMB (meso-carbon microbeads) carbon anodes and LiNi(0.8)Co(0.2)O2 cathodes, have been fabricated with increased safety and expanded capability. These cells serve to verify and demonstrate the reversibility, low-temperature performance, and electrochemical aspects of each electrode as determined from a number of electrochemical characterization techniques. A number of Li-ion electrolytes possessing fluorinated ester co-solvents, namely trifluoroethyl butyrate (TFEB) and trifluoroethyl propionate (TFEP), were demonstrated to deliver good performance over a wide temperature range in experimental lithium-ion cells. The general approach taken in the development of these electrolyte formulations is to optimize the type and composition of the co-solvents in ternary and quaternary solutions, focusing upon adequate stability [i.e., EC (ethylene carbonate) content needed for anode passivation, and EMC (ethyl methyl carbonate) content needed for lowering the viscosity and widening the temperature range, while still providing good stability], enhancing the inherent safety characteristics (incorporation of fluorinated esters), and widening the temperature range of operation (the use of both fluorinated and non-fluorinated esters). Further - more, the use of electrolyte additives, such as VC (vinylene carbonate) [solid electrolyte interface (SEI) promoter] and DMAc (thermal stabilizing additive), provide enhanced high-temperature life characteristics. Multi-component electrolyte formulations enhance performance over a temperature range of -60 to +60 C. With the need for more safety with the use of these batteries, flammability was a consideration. One of the solvents investigated, TFEB, had the best performance with improved low-temperature capability and high-temperature resilience. This work optimized the use of TFEB as a co-solvent by developing the multi-component electrolytes, which also contain non-halogenated esters, film forming additives, thermal stabilizing additives, and flame retardant additives. Further optimization of these electrolyte formulations is anticipated to yield improved performance. It is also anticipated that much improved performance will be demonstrated once these electrolyte solutions are incorporated into hermetically sealed, large capacity prototype cells, especially if effort is devoted to ensure that all electrolyte components are highly pure.

Prakash, G. K. Surya↗
DOE OSTI2024

Down-selection of Innovative Fusion Materials

The goal of this proposal is to develop and fundamentally understand the microstructure of refractory multi-component alloys (MCA) as fusion-relevant plasma facing and structural materials, a step to down-select innovative fusion materials prior to the process of advancing their technology readiness level (TRL). Developing materials is paramount to enable fusion as energy source since no existing material is capable of coping with such extreme conditions. We will aim at understanding the role of chemistry and microstructure in these complex multi-component alloys systematically comparing their performance with pure tungsten materials in terms of mechanical properties and manufacturability. Such understanding will open opportunities to optimize MCAs for fusion applications and has a potential of attracting industry partnership.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Development of SAM Code Capabilities for Safety Analysis of GCR Air-ingress Events

Air-ingress following a depressurized loss-of-forced-cooling (DLOFC) event is a challenging, multiphysics safety scenario for High-Temperature Gas-Cooled Reactors (HTGRs), involving coupled gas composition transport, buoyancy-driven flow redistribution, graphite oxidation, and structural heat-up. Despite its importance — air ingress is a key scenario identified in the PIRT process for the HTGRs — existing system-level safety codes have lacked the integrated capability to simulate the complete event sequence with high confidence. This report documents the development, validation, and demonstration of three new capabilities in the SAM code to address this gap: (1) a multi-component gas mixture flow model with binary diffusion to track the helium-air composition and its effect on system density and flow; (2) a 0-D graphite oxidation model based on the Roes correlation, including oxygen consumption and exothermic heat release; and (3) an isentropic critical flow model for accurate representation of primary system depressurization through a break. These capabilities are validated against two benchmark experiments. The NSTF heavy-gas ingress experiment validates the multi-component flow model: SAM correctly reproduces the rapid buoyancydriven flow stagnation and subsequent natural circulation recovery driven by composition-dependent density changes. The NACOK graphite oxidation experiment validates the oxidation model: SAM predicts a bottom-level graphite weight loss of 25%, in close agreement with the measured 24%, and reproduces the strong axial nonuniformity and block-geometry dependence of oxidation, at a level comparable to the SPECTRA and TINTE codes. The validated capabilities are then exercised together in an integrated, reactor-scale simulation of a DLOFC air-ingress transient in a simplified HTR-PM pebble-bed reactor. In a single calculation spanning approximately 8 days, SAM reproduces the complete accident sequence: rapid depressurization, densityand diffusion-driven air ingress over ˜15 hours, onset of buoyancy-driven natural circulation, exothermic graphite oxidation with a peak fuel temperature at ˜62 hours, and eventual passive cooldown. These results demonstrate that SAM now provides the nuclear community with a preliminarily validated, modern systemlevel tool for HTGR air-ingress safety analysis, filling a recognized capability gap. Future extensions to broaden species tracking, improve oxidation chemistry, and refine the reactor model are discussed.

Yang, Gang↗
DOE OSTI2024

A General Framework for Error-controlled Unstructured Scientific Data Compression

Data compression plays a key role in reducing storage and I/O costs. Traditional lossy methods primarily target data on rectilinear grids and cannot leverage the spatial coherence in unstructured mesh data, leading to suboptimal compression ratios. We present a multi-component, error-bounded compression framework designed to enhance the compression of floating-point unstructured mesh data, which is common in scientific applications. Our approach involves interpolating mesh data onto a rectilinear grid and then separately compressing the grid interpolation and the interpolation residuals. This method is general, independent of mesh types and typologies, and can be seamlessly integrated with existing lossy compressors for improved performance. We evaluated our framework across twelve variables from two synthetic datasets and two real-world simulation datasets. The results indicate that the multi-component framework consistently outperforms state-of-the-art lossy compressors on unstructured data, achieving, on average, a 2.3 − 3.5× improvement in compression ratios, with error bounds ranging from 1 × 10 the −6 to 1×10−2. We further investigate impact of hyperparameters, such as grid spacing and error allocation, to deliver optimal compression ratios in diverse datasets.

Gong, Qian↗
DOE OSTI2025

Accelerating the discovery of low-energy structure configurations: A computational approach that integrates first-principles calculations, Monte Carlo sampling, and Machine Learning

Finding Minimum Energy Configurations (MECs) is essential in fields such as physics, chemistry, and materials science, as they represent the most stable states of the systems. In particular, identifying such MECs in multi-component alloys considered candidate PFMs is key because it determines the most stable arrangement of atoms within the alloy, directly influencing its phase stability, structural integrity, and thermo-mechanical properties. However, since the search space grows exponentially with the number of atoms considered, obtaining such MECs using computationally expensive first-principles DFT calculations often results in a cumbersome task. To escape the above compromise between physical fidelity and computational efficiency, we have developed a novel physics-based data-driven approach that combines Monte Carlo sampling, first-principles DFT calculations, and Machine Learning to accelerate the discovery of MECs in multi-component alloys. More specifically, we have leveraged well-established Cluster Expansion (CE) techniques with Local Outlier Factor models to establish strategies that enhance the reliability of the CE method. In this work, we demonstrated the capabilities of the proposed approach for the particular case of a tungsten-based quaternary high-entropy alloy. However, the method is applicable to other types of alloys and enables a wide range of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Data analytics approach to predict high-temperature cyclic oxidation kinetics of NiCr-based Alloys

Abstract Although of practical importance, there is no established modeling framework to accurately predict high-temperature cyclic oxidation kinetics of multi-component alloys due to the inherent complexity. We present a data analytics approach to predict the oxidation rate constant of NiCr-based alloys as a function of composition and temperature with a highly consistent and well-curated experimental dataset. Two characteristic oxidation models, i.e., a simple parabolic law and a statistical cyclic oxidation model, have been chosen to numerically represent the high-temperature oxidation kinetics of commercial and model NiCr-based alloys. We have successfully trained machine learning (ML) models using highly ranked key input features identified by correlation analysis to accurately predict experimental parabolic rate constants ( k p ). This study demonstrates the potential of ML approaches to predict oxidation kinetics of alloys over wide composition and temperature ranges. This approach can also serve as a basis for introducing more physically meaningful ML input features to predict the comprehensive cyclic oxidation behavior of multi-component high-temperature alloys with proper constraints based on the known underlying mechanisms.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Micron-sized spinel crystals in high level waste glass compositions: Determination of crystal size and crystal fraction

The compositions utilized for immobilization of nuclear waste are controlled using glass property models to avoid the deleterious effects of crystallization in the high-level waste (HLW) vitrification melters. The type and size of the crystals that precipitate during melter operations (typically at 1150 °C) and idling (~ 1000 °C) are significantly impacted by glass composition and thermal history. This study was conducted to measure the impact of melt composition and heat treatment temperature on crystal size and fraction. A matrix of 31 multi-component glasses canvasing the expected Hanford HLW compositional space was developed and the glasses fabricated and heat treated at 850 = T = 950°C. The crystal filling fraction values, as determined by X-ray diffraction, varied from 0.2 to 41.0 wt%. Spinel filling fraction values ranged from 0.0 to 13.8 wt%. One glass of the matrix did not precipitate spinel and contained 0.2 wt% RuO 2 , which was assumed to be undissolved from the melting process. All compositions contained crystals in the as-quenched glass. All of the spinel based crystals present in the glasses were less than 10 µm in diameter, as determined by scanning electron microscopy. Composition and temperature dependent models were generated using the resulting data and the best model fit was obtained by only considering spinel filling fractions (R 2 = 0.83). Two glasses were unable to be characterized due to an inability to process the glass under the conditions of this study. Those glasses were utilized to give insight into a potential multi-component constraint to aid in future statistical composition designs.

Lonergan, C. E.↗
DOE OSTI2025

Disentangling atmospheric, hydrological, and coupling uncertainties in compound flood modeling within a coupled Earth system model

Compound riverine and coastal flooding is usually driven by complex interactions among meteorological, hydrological, and ocean extremes. However, existing efforts to model this phenomenon often do not integrate hydrological processes across atmosphere–land–river–ocean systems, leading to substantial uncertainties that have not been fully examined. To bridge this gap, we leverage the new capabilities of the Energy Exascale Earth System Model (E3SM) that enable a multi-component framework that integrates coastally refined atmospheric, terrestrial, and oceanic components. We evaluate compound uncertainties arising from two-way land–river–ocean coupling in E3SM and track the cascading meteorological and hydrological uncertainties through ensemble simulations over the Delaware River basin and estuary during Hurricane Irene (2011). Our findings highlight the importance of two-way river–ocean coupling to compound flood modeling and demonstrate E3SM's capability in capturing compound flood extent near the coast, with a hit rate over 0.75. Our study shows the growing uncertainties that transition from atmospheric forcings to flood distribution and severity. Furthermore, an analysis based on artificial neural networks is used to assess the roles of hydrological drivers, such as infiltration and soil moisture, in the generation of compound flooding. The response of compound floods to tropical cyclones (TCs) is found to be susceptible to these often overlooked drivers. For instance, the flooded area could increase more than 2-fold (∼2.4) if Hurricane Irene were preceded by an extreme antecedent soil moisture condition (AMC). The results not only support the use of a multi-component framework for interactive flooding processes, but also underscore the necessity of broader definitions of compound flooding that encompass the simultaneous occurrence of intense precipitation, storm surge, and high AMC during TCs.

Feng, Dongyu [Pacific Northwest National Laborator↗
DOE OSTI2023

Plastic homogeneity in nanoscale heterostructured binary and multicomponent metallic eutectics: An overview

Heterostructured materials comprised of relatively soft/hard disparate phases typically exhibit composite strengthening but lack plastic deformability at ambient temperatures. However, heterostructured systems comprised of nanoscale phases can simultaneously enhance yield strength and strain hardening, thereby promoting uniform distribution of plastic flow. In this review, the atomic-scale deformation mechanisms in model systems of eutectic alloys, Al-Al 2 Cu and Al-Si, refined to nanoscales via laser rapid solidification are discussed, and compared with literature on multi-component (high entropy) eutectics such as Ni-Al-Fe-based with Cr and/or Co additions. The nano-lamellar Al-Al 2 Cu structures exhibit unit defect mechanisms not reported in monolithic Al 2 Cu intermetallic: localized shear on {0 1 1} and shear-induced faults on {1 2 1} planes, constrained by closely-spaced dislocation arrays in Al confined by Al/Al 2 Cu interfaces. The unexpected plasticity mechanisms are enabled by slip continuity in nanoscale Al-Al 2 Cu eutectics associated with the orientation relationship and interface habit planes. In nano-fibrous Al-Si eutectic, tensile ductility at strength approaching 600 MPa is observed resulting from dislocation plasticity in the nano-Al channels and cracking in Si nanofibers. Molecular dynamics simulations show that Al dislocations easily cross-slip (screw) or climb (edge) along Al-Si interfaces, making slip transmission difficult. The propagation of nano-cracks is suppressed by surrounding strain hardening Al, retaining good ductility of the sample, in spite of lack of direct slip transmission. Finally, the critical unit mechanisms of slip transmission and interface-enabled plasticity observed in nanoscale eutectic binary systems can also explain the strength-ductility relationship in multi-component eutectics and homogeneously distributed plastic flow with increasing microstructural heterogeneity.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Evaluation of Tellurium as a Fuel Additive in Neodymium-Containing U-Zr Metallic Fuel

Phase-stability in a U-Zr-Te-Nd multi-component metallic fuel for advanced nuclear reactors is systematically investigated by taking into account binary, ternary and quaternary interactions between elements involved. Historically, the onset of fuel-cladding chemical interactions (FCCI) greatly limits the burnup potential of U-Zr fuels primarily due to interactions between lanthanide fission products and cladding constituents. Tellurium (Te) is evaluated as a potential additive for U-Zr fuels to bind with lanthanide fission products, e.g. neodymium (Nd), negating or mitigating the FCCI effect. Potential fresh fuel alloy compositions with the Te additive, U-Zr-Te, are characterized. Te is found to completely bind with Zr within the U-Zr matrix. Alloys simulating the formation of the lanthanide element Nd within U-Zr-Te are also evaluated, where the Te-Nd binary interaction dominates and NdTe is found to form as a high temperature stable compound. The experimental observations agree well with the trends obtained from density functional theory calculations. According to the calculated enthalpy of mixing, Zr-Te compound formation is favored in the U-Zr-Te alloy whereas NdTe compound formation is favored in the U-Zr-Te-Nd alloy. Further, the calculated charge density distribution and density of states provide sound understanding of the mutual chemical interactions between elements and phase-stability within the multi-component fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1994

On the dynamics of a shock-bubble interaction

We present a detailed numerical study of the interaction of a weak shock wave with an isolated cylindrical gas inhomogenity. Such interactions have been studied experimentally in an attempt to elucidate the mechanisms whereby shock waves propagating through random media enhance mixing. Our study concentrates on the early phases of the interaction process which are dominated by repeated refractions of acoustic fronts at the bubble interface. Specifically, we have reproduced two of the experiments performed by Haas and Sturtevant : M(sub s) = 1.22 planar shock wave, moving through air, impinges on a cylindrical bubble which contains either helium or Refrigerant 22. These flows are modelled using the two-dimensional, compressible Euler equations for a two component fluid (air-helium or air-Refrigerant 22). Although simulations of shock wave phenomena are now fairly commonplace, they are mostly restricted to single component flows. Unfortunately, multi-component extensions of successful single component schemes often suffer from spurious oscillations which are generated at material interfaces. Here we avoid such problems by employing a novel, nonconservative shock-capturing scheme. In addition, we have utilized a sophisticated adaptive mesh refinement algorithm which enables extremely high resolution simulations to be performed relatively cheaply. Thus we have been able to reproduce numerically all the intricate mechanisms that were observed experimentally (e.g., transitions from regular to irregular refraction, cusp formation and shock wave focusing, multi-shock and Mach shock structures, jet formation, etc.), and we can now present an updated description for the dynamics of a shock-bubble interaction.

Quirk, James J.↗
DOE OSTI2020

Solvent-Free Self-Assembly for Scalable Preparation of Highly Crystalline Mesoporous Metal Oxides

Mesoporous metal oxides (MMOs) have been demonstrated great potential in various applications. Up to now, the direct synthesis of MMOs is still limited to the solvent induced inorganic-organic self-assembly process. In this work, we develop a facile, general, and high throughput solvent-free self-assembly strategy to synthesize a series of MMOs including single-component MMOs and multi-component MMOs (e.g., doped MMOs, composite MMOs, and polymetallic oxide) with high crystallinity and remarkable porous properties by grinding and heating raw materials. Compared with the traditional solution self-assembly process, the avoidance of solvents in this method not only greatly increases the yield of target products and synthesis efficiency, but also reduces the environmental pollution and the consumption of cost and energy. We believe the presented approach will pave a new avenue for scalable production of advanced mesoporous materials for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗