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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Modeling Henry's law and phase separations of water–NaCl–organic mixtures with solvation and ion-pairing

Empirical measurements of solution vapor pressure of ternary acetonitrile (MeCN) H 2 O–NaCl–MeCN mixtures were recorded, with NaCl concentrations ranging from zero to the saturation limit, and MeCN concentrations ranging from zero to an absolute mole fraction of 0.64. After accounting for speciation, the variability of the Henry's law coefficient at vapor–liquid equilibrium (VLE) of MeCN ternary mixtures decreased from 107% to 5.1%. Solute speciation was modeled using a mass action solution model that incorporates solute solvation and ion-pairing phenomena. Two empirically determined equilibrium constants corresponding to solute dissociation and ion pairing were utilized for each solute. When speciation effects were considered, the solid–liquid equilibrium of H 2 O–NaCl–MeCN mixtures appear to be governed by a simple saturation equilibrium constant that is consistent with the binary H 2 O–NaCl saturation coefficient. Further, our results indicate that the precipitation of NaCl in the MeCN ternary mixtures was not governed by changes in the dielectric constant. Our model indicates that the compositions of the salt-induced liquid–liquid equilibrium (LLE) boundary of the H 2 O–NaCl–MeCN mixture correspond to the binary plateau activity of MeCN, a range of concentrations over which the activity remains largely invariant in the binary water–MeCN system. Broader comparisons with other ternary miscible organic solvent (MOS) mixtures suggest that salt-induced liquid–liquid equilibrium exists if: (1) the solution displays a positive deviation from the ideal limits governed by Raoult's law; and (2) the minimum of the mixing free energy profile for the binary water-MOS system is organic-rich. Finally, this work is one of the first applications of speciation-based solution models to a ternary system, and the first that includes an organic solute.

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

Extreme compression of planetary gases: High-accuracy pressure-density measurements of hydrogen-helium mixtures above fourfold compression

Hydrogen (H 2 ) and helium (He), the most abundant elements in the universe, pose a unique challenge in measuring the equation of state of the mixture, owing to their differing physical properties. There remains a need for data with high enough precision to discriminate between existing equation of state (EOS) mix models in order to understand the internal structure of gas-giant planets. Here, we have measured the EOS of precompressed H 2 - He mixtures at conditions directly relevant to the planetary interiors using hypervelocity gas guns and Sandia’s Z machine with less than 10% uncertainty in density, enabling validation of mixture models. We precompressed 50:50 molar mixtures of H 2 -He to 0.1–0.2 GPa and directly measured particle velocity (in gas-gun experiments) and shock velocities (in Z-machine experiments). To complement the experimental efforts, we also computed the Hugoniots of precompressed H 2 -He mixtures using density-functional-theory-based molecular dynamics. Furthermore, we observe approximately 3- to 4.3-fold density compression at pressures up to 44 GPa.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Evaluation of possible reactivation of undetected faults during CO 2 injection

Geologic storage of carbon dioxide can efficiently contribute to reduce greenhouse gas emissions to the atmosphere. Two major hazards of this technology are leakage towards the ground surface and fluid-induced seismicity. While major faults may be detected and avoided during site characterization, undetected subseismic faults could be encountered once injection has started. This paper investigates leakage and reactivation of undetected faults through coupled thermal–hydraulic–mechanical modeling. The simulations are performed using a recently developed sequential simulator, TOUGH-Pylith, that allows to accurately account for the thermodynamics of brine-CO 2 injection mixtures, and to model faults as surfaces of discontinuity using state-of-the-art fault friction laws. The simulator is benchmarked against well-known analytical solutions and subsequently applied to investigate two cases of CO 2 injection injection close to undetected faults under normal and strike-slip faulting regimes. Furthermore, although the scenarios are generic and represent unfavorable conditions, they suggest that leakage could occur and that undetected faults could trigger minor seismic events. Therefore, careful site characterization and continuous monitoring during operations should be always performed.

58 GEOSCIENCES↗
DOE OSTI2026

Electrocatalytic Hydrotreatment of Bio-Oil: Exploring Interactions Between Functional Groups

Electrocatalytic hydrotreatment (ECH) is being explored as a sustainable route for upgrading bio-oil to renewable fuels and chemicals. Bio-oil, produced by the fast pyrolysis of lignocellulosic biomass, is a complex mixture of compounds with various oxygen-containing functional groups, such as anhydrosugars, carboxylic acids, ketones, aldehydes, furans, phenols and alcohols. The ECH of several bio-oil model compound binary mixtures was conducted to investigate the interactions between these functional groups. Notably, phenolic compound reduction was significantly inhibited in the presence of aldehydes, particularly furfural. A strategy involving the reagent-based reduction of the aldehyde to an alcohol prior to ECH was shown to partially mitigate this inhibitory effect. Additionally, qualitative studies on the ECH of catalytic fast pyrolysis (CFP) oil with low aldehyde content showed promising results. These studies achieved the conversion of cyclopentenones and phenolic compounds present in the CFP oil to cyclopentanols and cyclohexanols, respectively.

09 BIOMASS FUELS↗
DOE OSTI2024

Effects of spatiotemporal plasma power distribution on the modeling of ignition kernel evolution in quiescent and turbulent methane/air mixtures

Abstract The present work improves a phenomenological plasma-assisted combustion model by integrating the spatiotemporal distribution of plasma power density, thereby considering the evolution of plasma streamers in the modeling, and subsequently, better predicting the ignition kernel evolution. The improved phenomenological model is validated against experiments representing the plasma discharge and post-discharge ignition kernel evolution. Specifically, the new model demonstrates a more accurate prediction of ultrafast gas heating and O 2 dissociation during the plasma discharge, compared to the original model. In addition, the new model is found to closely match the experimental pressure wave and heated channel profiles post-discharge without the need for tuning the energy deposition (unlike the original model), highlighting its accuracy of post-discharge ignition kernel dynamics. The improved phenomenological model is then employed to investigate ignition kernel evolution for a stoichiometric methane-air discharge across various discharge gap configurations. Simulations reveal a non-uniform temperature and streamer distribution progressing from the electrode tips toward the center, contrasting uniform cylindrical discharges previously described in the original model. Streamer propagation is observed to be faster for larger gaps when maintained at the same average electric field for different discharge gaps. The tendency of smaller gaps to produce detached toroidal ignition kernels is observed, while larger gaps promote cylindrical and attached ignition kernels. Interactions between successive ignition kernels from consecutive discharges varied significantly, with the smallest gap (1 mm) promoting the quenching of the preceding ignition kernel due to the initial kernel–kernel separation. The intermediate gap (2 mm) promotes detached kernel growth. In contrast, in the largest gap (4 mm), kernels consistently combine and expand attached to electrodes. The impact of homogeneous isotropic turbulence is also explored, showing the persistence of ignition kernels early on but eventually quenching due to enhanced radical and heat losses with pronounced turbulence intensity.

Johnson, Praise Noah↗
DOE OSTI2024

Uncertainty quantification of mass models using ensemble Bayesian model averaging

Developments in the description of the masses of atomic nuclei have led to various nuclear mass models that provide predictions for masses across the whole chart of nuclides. These mass models play an important role in understanding the synthesis of heavy elements in the rapid neutron capture ( r ) process. However, it is still a challenging task to estimate the size of uncertainty associated with the predictions of each mass model. In this work, a method called ensemble Bayesian model averaging (EBMA) is introduced to quantify the uncertainty of one-neutron separation energies (S 1 n ) which are directly relevant in the calculations of r -process observables. Here, this Bayesian method provides a natural way to perform model averaging, selection, and uncertainty quantification, by combining the mass models as a mixture of normal distributions whose parameters are optimized against the experimental data, employing the Markov chain Monte Carlo method using the no-u-turn sampler. The EBMA model optimized with all the experimental S 1 n from the AME2003 nuclides are shown to provide reliable uncertainty estimates when tested with the new data in the AME2020.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Calibration of the 2-Phase Bubble Tracking Model for Liquid Mercury Target Simulation with Machine Learning Surrogate Models

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory is one of the most powerful accelerator-driven neutron sources in the world. The intense protons strike on SNS's mercury target to provide bright neutron beams, which also leads to severe fluid-structure interactions inside the target. Prediction of resultant loading on the target is difficult particularly when helium gas is injected into mercury to reduce the loading and mitigate the pitting damage on vessel walls. A 2-phase material model that incorporates the Rayleigh-Plesset (R-P) model is expected to address this multi-physics problem. However, several uncertain parameters in the R-P model require intensive simulations to determine their optimal values. With the help of machine learning and the measured target strain, we have studied the major uncertain parameters in this R-P model and developed a framework to identify optimal parameters that significantly reduce the discrepancy between simulations and experimental strains. The preliminary results show the possibility of using this mercury/helium mixture and surrogate models to predict a better match of target strain response when the helium gas is injected.

Lin, Lianshan↗
DOE OSTI2025

Inverse Thermodynamics: Designing Interactions for Targeted Phase Behavior

The traditional goal of inverse self-assembly is to design interactions that drive particles toward a desired target structure. However, achieving successful self-assembly also requires tuning the thermodynamic conditions under which the structure is stable. In this work, we extend the inverse design paradigm to explicitly address this challenge by developing a framework for inverse thermodynamics, i.e., the design of interaction potentials that realize specific thermodynamic behavior. As a step in this direction, using patchy particle mixtures as a model system, we demonstrate how precise control over both bonding topology and bond energetics enables the programming of targeted phase behavior. In particular, we establish design principles for azeotropic demixing and show how to create mixtures that exhibit azeotropy at any prescribed composition. Our predictions are validated through Gibbs-ensemble simulations [Panagiotopoulos, Mol. Phys. 1987, 61, 813−826]. These results highlight the necessity of coupling structural design with thermodynamic engineering, and provide a blueprint for controlling complex phase behavior in multicomponent systems.

Azeotropes↗
DOE OSTI2021

Quantitative modeling of carcinogenesis induced by single beams or mixtures of space radiations using targeted and non-targeted effects

Abstract Ionizing radiations encountered by astronauts on deep space missions produce biological damage by two main mechanisms: (1) Targeted effects (TE) due to direct traversals of cells by ionizing tracks. (2) Non-targeted effects (NTE) caused by release of signals from directly hit cells. The combination of these mechanisms generates non-linear dose response shapes, which need to be modeled quantitatively to predict health risks from space exploration. Here we used a TE + NTE model to analyze data on APC (1638N/+) mouse tumorigenesis induced by space-relevant doses of protons, 4 He, 12 C, 16 O, 28 Si or 56 Fe ions, or γ rays. A customized weighted Negative Binomial distribution was used to describe the radiation type- and dose-dependent data variability. This approach allowed detailed quantification of dose–response shapes, NTE- and TE-related model parameters, and radiation quality metrics (relative biological effectiveness, RBE, and radiation effects ratio, RER, relative to γ rays) for each radiation type. Based on the modeled responses for each radiation type, we predicted the tumor yield for a Mars-mission-relevant mixture of these radiations, using the recently-developed incremental effect additivity (IEA) synergy theory. The proposed modeling approach can enhance current knowledge about quantification of space radiation quality effects, dose response shapes, and ultimately the health risks for astronauts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Application of high-speed, species-specific chemiluminescence imaging for laminar flame speed and Markstein length measurements in spherically expanding flames

A high-speed chemiluminescence imaging diagnostic system has been developed and characterized for measuring species-specific properties of spherically expanding flames, with the objective of obtaining synchronized measurements of multiple flame properties from a single flame experiment. The imaging system comprises a high-speed camera coupled to a high-speed image intensifier and optical filters to isolate emission from desired excited species. Here this study validates the diagnostic scheme specifically for measuring laminar flame speed and Markstein length from chemiluminescence at three wavelength bands corresponding to OH*, CH*, and total chemiluminescence, respectively. Mixtures of methane-air and methane/ethane-air were tested at initial conditions of atmospheric pressure and room temperature. An under-utilized methodology for computing unburned Markstein length from burned Markstein length was implemented. Flame speed modeling of each mixture was conducted in Chemkin using AramcoMech 2.0. No significant differences were observed between the results derived from the three emission wavelength bands for the flame speeds nor the Markstein lengths. For both of these properties, excellent agreement was observed between the experimental results and the values reported in the literature. Because laminar flame speed and Markstein length show no dependency on the imaging wavelength, the present results imply that multiple flame properties, such as laminar flame speed, Markstein length, flame thickness, and excited-species intensity profiles, can all be acquired simultaneously for the same flame using this method.

42 ENGINEERING↗
DOE OSTI2023

Droplet burning of n-butyl acetate/n-heptane mixtures in the standard atmosphere: experiments and numerical modeling

Blending petroleum fuels with oxygenates is a common approach to stem the depletion of crude oil while also mitigating the impact of their combustion on the environment. It has recently been considered that n-butyl acetate (BA, C6H12O2 , boiling point of 399K) could be a viable oxygenate additive to diesel fuel. In this application it is important to determine the influence of the fractional amount of BA on burning of the mixture. This presentation considers this problem from an experimental and computational approach using n-heptane (C7H14 , boiling point of 372K) as an essentially single component surrogate for diesel fuel. The burning configuration considered was ostensibly spherical symmetry as promoted by burning droplets under conditions where forced and natural convection effects were minimized. In this configuration the droplet and flame are concentric spheres and soot aggregates are trapped in a shell structure between the droplet and flame. Measurements were made of the droplet, flame and soot shell diameters through video imaging of the burning process. The experimental results were used to validate a detailed numerical model of the spherically symmetric droplet burning process that incorporated a consistent combustion kinetic mechanism for BA/heptane mixtures, comprised of 402 species and 16,872 reactions inclusive of soot chemistry. A model for soot formation was also included in the simulation to predict formation of the soot shell. The simulations agreed well with measured droplet and flame diameters. It was found both experimentally and computationally that adding BA to heptane had a minimal effect on the mixture burning rate, while the flame was positioned closer to the droplet surface and the simulated soot volume fraction decreased. The implications of these results are discussed for using BA as a potential additive to diesel fuel.

09 BIOMASS FUELS↗
DOE OSTI2019

Combustion Research I.1 Sprays, Flow, Heat Transfer and Turbulent Mixing

LANL is working with the Partnership for Advance Combustion Engines (PACE) a DOE sponsored consortium of national laboratories for the research and development for creating smarter engine design tools for sustainable transportation. Much of that effort is focused on heat, mass and momentum transfer within and engine. LANL’s focus in 2019, in particular under PACE has been spray modeling and engine mixture formulation, development of conjugate heat transfer analysis (heat transfer to the environment surrounding the combustion chamber). Our efforts relay on the Fast, Easy, Accurate and Robust Continuum Engineering (FEARCE) software developed at LANL as the next generation of engine modeling software for turbulent reactive and multiphase flow, a 2019 R&D 100 winner. This work is relevant to the DOE Vehicle Technologies Office efforts at addressing national energy security as well. Less dependence on petroleum products leads to greater energy security. By Environmental Protection Agency standards, some vehicles are now reaching 42–50 mpg mark. These are conventional gasoline engines. With continued investment and research into new technical innovations, the potential exists to save more than 4 million barrels of oil per day or approximately $200 to $400 million per day. This would be a significant decrease in emissions and use of petroleum and a very large stimulus to the U.S. economy. Better understanding of fuel injection and fuel–air mixing, thermodynamic combustion losses, and combustion/emission formation processes enhances our ability to minimize fuel use and unwanted emissions. Helping to accomplish this understanding, the FEARCE modeling program is working to provide state-of-theart capability for accurately simulating combustion processes: to have a predictive methodology in a software helping industry and researchers not only meet national goals on fuel usage and emissions, but global goals. In addition, a predictive, robust, and accurate capability for simulating the engine combustion process helps to minimize time and labor for development of new engine technology.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

First Principle based Thermal Conductivity Modeling of Metal Alloys with Applications on Uranium Alloys

Thermal conductivity is an important materials property related to heat transport, which is essential to many applications, ranging from thermoelectrics to nuclear reactor materials. High- quality thermal conductivity data is critical to these materials and their associated technologies, including the nuclear fuel materials like traditional oxide fuels and metallic uranium (U) fuels, e.g. U-Zr and U-Mo alloys. And thermal conductivity modeling is widely used to interpolate or extrapolate experimental data, to obtain high-quality thermal conductivity data over wide temperature and composition range, and to understand the impacts of different factors including defects and microstructures. However, a general thermal conductivity model for metal alloys which can work regrading different phase components is still missing. Also, for U alloys, a thermal conductivity model working with different phases is needed. Therefore, in this work, we developed thermal conductivity models for metal alloys, based on ab-initio calculations, semi-classical physics rules, and limited experimental data. The goals of these models are to help obtain high- quality thermal conductivity data within a little experimental input as possible, have models that are extendable to varying microstructures, including different types of irradiation effects, and provide mechanistic understanding of heat transfer in the modeled alloys. In this work, our model solves several challenges in the development. The DFT-BTE approach is applied to decrease the reliance on experimental data and make the model extendable to composition changes and defects. A practical and efficient way to combine the DFT inputs with physics rules is pointed out in this work too. A staged approach, which starts from simple cases of elemental metals, then extends to solid solutions, different compound phases, and multi-phase mixtures, is presented to work with the metal alloys in different phase components. Our models are demonstrated respectively on aU for elemental metal model, on U-Zr and U-Mo alloys in aU temperature range for multi-phase mixture model, on high-temperature U-Zr, U-Nb, and U-Mo alloys in the body-centered cubic phase for concentrated solid solution model, and on irradiated U-Mo alloys for irradiated metal alloy model. All models show great agreement with experimental data. In these demonstrations, our model shows its advantages compared to previous empirical fitting model. Our model requires fewer experimental data, due to the inputs from DFT. The quantitative insights into the different physical factors are provided in our model, as it incorporates the electron and phonon scattering mechanisms. Our model also can be extended to incorporate the contributions of point defects, grain boundaries, and noble gas bubbles, to integrate their effects on heat transfer. This model can serve as both a foundation for understanding the more complex thermal conductivity of realistic U alloy fuels and a useful tool to guide further modeling of thermal conductivity to aid materials and device design.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Thermodynamic modeling of double azeotropy systems

Azeotropes are boiling liquid mixtures which have identical vapor and liquid compositions. Known as polyazeotropy, azeotropic mixtures may exhibit more than one azeotrope at a given temperature or pressure. While the thermodynamic condition for azeotrope formation in vapor-liquid equilibrium is well established, thermodynamic modeling of mixtures exhibiting polyazeotropy remains challenging and prior modeling studies often failed to satisfactorily correlate the polyazeotropic behavior of associating systems. Based on the association NRTL model, this study presents successful correlation and analysis of double azeotrope formation for three diverse systems: strongly associating methanol + diethylamine binary, weakly associating ammonia + pentafluoroethane binary, and non-associating benzene + hexafluorobenzene binary systems. Furthermore, these systems exhibit polyazeotropic behavior as the temperature increases and approaches their Bancroft points.

42 ENGINEERING↗
DOE OSTI2020

Increasing Compressed Gas Energy Storage Density Using CO2–N2 Gas Mixture

This paper demonstrates a new method by which the energy storage density of compressed air systems is increased by 56.8% by changing the composition of the compressed gas to include a condensable component. A higher storage density of 7.33 MJ/m3 is possible using a mixture of 88% CO2 and 12% N2 compared to 4.67 MJ/m3 using pure N2. This ratio of gases representing an optimum mixture was determined through computer simulations that considered a variety of different proportions from pure CO2 to pure N2. The computer simulations are based on a thermodynamic equilibrium model that predicts the mixture composition as a function of volume and pressure under progressive compression to ultimately identify the optimal mixture composition (88% CO2 + 12% N2). The model and simulations predict that the optimal gas mixture attains a higher energy storage density than using either of the pure gases.

25 ENERGY STORAGE↗
DOE OSTI2022

Altering the Supply of Shielding Gases to Fabricate Distinct Geometry in GMA Additive Manufacturing

Wire arc additive manufacturing (WAAM) is the process by which large, metallic structures are built, layer-by-layer, using a welding arc to melt wire feedstock. In this process, the proper selection of the shielding gas plays a vital role in the achievement of structurally acceptable part geometries and quality surface finishes. In this study, the authors used either a ternary mix (He, Ar and CO 2 ) or a binary mix (Ar and CO 2 ) of shielding gases to deposit wall geometries using an open loop-controlled WAAM system developed at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility. The binary blend produced a wider and shorter geometry, while the ternary blend resulted in a narrower build that was more equivalent to the CAD geometry. The data indicated that the binary blend provided a higher oxygen concentration in the weld as compared to that of the ternary blend. The results imply that the arc characteristics and heat input had a significantly higher impact on the weld penetration than the surface tension effect of surface active elements. This was further verified by developing and applying a high-fidelity computational fluid dynamics (CFD) model of the thermophysical properties of gas mixtures. The results from the model showed that, while the influence of increased oxygen concentration on the surface tension for the binary blend led to a deeper penetration, the ternary blend gave rise to heat flux to the workpiece.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Data-Driven Many-Body Models for Molecular Fluids: CO 2 /H 2 O Mixtures as a Case Study

In this study, we extend the scope of the many-body TTM-nrg and MB-nrg potential energy functions (PEFs), originally introduced for halide ion–water and alkali-metal ion–water interactions, to the modeling of carbon dioxide (CO2) and water (H2O) mixtures as prototypical examples of molecular fluids. Both TTM-nrg and MB-nrg PEFs are derived entirely from electronic structure data obtained at the coupled cluster level of theory and are, by construction, compatible with MB-pol, a many-body PEF that has been shown to accurately reproduce the properties of water. Although both TTM-nrg and MB-nrg PEFs adopt the same functional forms for describing permanent electrostatics, polarization, and dispersion, they differ in the representation of short-range contributions, with the TTM-nrg PEFs relying on conventional Born–Mayer expressions and the MB-nrg PEFs employing multidimensional permutationally invariant polynomials. By providing a physically correct description of many-body effects at both short and long ranges, the MB-nrg PEFs are shown to quantitatively represent the global potential energy surfaces of the CO 2 –CO 2 and CO 2 –H 2 O dimers and the energetics of small clusters, as well as to correctly reproduce various properties in both gas and liquid phases. Furthermore, building upon previous studies of aqueous systems, our analysis provides further evidence for the accuracy and efficiency of the MB-nrg framework in representing molecular interactions in fluid mixtures at different temperature and pressure conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗