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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1947

The NACA mixture analyzer and its application to mixture-distribution measurement in flight

The NACA mixture analyzer was developed as a research instrument for the continuous indication of fuel-air ratios of aircraft engine installations throughout the range of engine operation. It has been evaluated by using it to measure the mixture distribution of a nine-cylinder radial aircraft engine in flight. The mixture distribution among the cylinders in flight was obtained at normal operating conditions for the engine at an altitude of 5000 feet. Some limited data was also obtained at an altitude of 20,000 feet. Results of these flight tests showed that the NACA mixture analyzer is a satisfactory and dependable instrument for continuous indication of the mixture in flight at all engine conditions regardless of altitude and temperature.

Gerrish, Harold C↗
NASA NTRS1952

Effect of Initial Mixture Temperature on Flame Speed of Methane-Air, Propane-Air, and Ethylene-Air Mixtures

Flame speeds based on the outer edge of the shadow cast by the laminar Bunsen cone were determined as functions of composition for methane-air mixtures at initial mixture temperatures ranging from -132 degrees to 342 degrees c and for propane-air and ethylene-air mixtures at initial mixture temperatures ranging from -73 degrees to 344 degrees c. The data showed that maximum flame speed increased with temperature at an increasing rate. The percentage change in flame speed with change in initial temperature for the three fuels followed the decreasing order, methane, propane, and ethylene. Empirical equations were determined for maximum flame speed as a function of initial temperature over the temperature range covered for each fuel. The observed effect of temperature on flame speed for each of the fuels was reasonably well predicted by either the thermal theory as presented by Semenov or the square-root law of Tanford and Pease.

Dugger, Gordon L↗
DOE OSTI2025

A Fast Framework for Generating Radioactive Mixture Spectra and Its Application to Remote High-Performance Mixture Identification

Remote detection of radioactive materials in mixtures using handheld or portal detectors remains a challenge because of factors such as low concentration, environmental interference, sensor noise, and other complications. This work introduces a fast framework for generating realistic mixture spectra. Moreover, we present mixture isotope identification using data generated by the fast framework. Researchers have examined a range of conventional and recent algorithms within the fields of machine learning and deep learning. An application to uranium enrichment-level prediction has been included. Extensive simulation experiments validated the efficacy of the proposed framework.

GADRAS↗
DOE OSTI2025

Multidimensional Modeling of Mixture Formation in a Hydrogen-Fueled Heavy-Duty Optical Engine With Direct Injection

Hydrogen (H 2 ), as a carbon-free fuel, is considered as one of the most promising solutions to reduce the carbon footprint of hard-to-decarbonize energy and transportation sectors. As such, hydrogen-fueled internal combustion engines (H 2 ICEs) have recently been receiving increasing attention, particularly in applications such as on-road/off-road heavy-duty transport and combined heat and power. The direct injection (DI) of gaseous hydrogen into the combustion chamber offers great potential for achieving high power density and high engine efficiency, while mitigating the risk of backfire and reducing pre-ignition. However, the numerical simulation of H 2 DI system remains a formidable challenge associated with the high computational cost of reproducing compressible supersonic flow and shocks in narrow injector passages and in near-nozzle regions. In general, there is a lack of well-established and validated practices for the modeling of high-pressure H 2 DI in large-bore engines. Here, to this end, this study focuses on computational fluid dynamics (CFD) modeling of the mixture formation process in a heavy-duty optical engine employing a medium-pressure H 2 DI system. Both large eddy simulations (LES) and Reynolds Averaged Navier–Stokes (RANS) simulations are performed and evaluated against optical data. Gaseous hydrogen is injected into the combustion chamber via a centrally located outward opening hollow-cone injector at a pressure of 40 bar. Simulations are carried out for two injection timings, namely, −120 and −60 °CA. The numerical predictions for H 2 distribution in different horizontal and vertical planes during the compression stroke are systematically compared against optical data obtained through planar laser-induced fluorescence (PLIF) measurements. Overall, the LES approach using the Dynamic Structure model is found to have good predictive capabilities for the early jet penetration in terms of length and shape, as well as the later H 2 distributions. However, the unsteady RANS approach with the renormalization group $k - ϵ$ model, which is widely used by industry to model heavy-duty ICEs, significantly underpredicts the H 2 mixing, even at similar mesh resolution to that used in LES. These results indicate that there is a need for the improvement of mixing submodels within the RANS approach when applied to H 2 DI simulations.

LES↗
NASA NTRS1952

Theoretical performance of liquid ammonia, hydrazine and mixture of liquid ammonia and hydrazine as fuels with liquid oxygen biflouride as oxidant for rocket engines : I-mixture of liquid ammonia and hydrazine

Theoretical performance for mixture of 36.3 percent liquid ammonia and 63.7 percent hydrazine with liquid oxygen bifluoride as rocket propellant was calculated on assumption of equilibrium composition during expansion for a wide range of fuel-oxidant and expansios ratios. Parameters included were specific impulse, combustion-chamber temperature, nozzle exit temperature, composition mean molecular weight, characteristic velocity, coefficient of thrust and ratio of nozzle-exit area to throat area. For chamber pressure of 300 pounds per square inch absolute and expansion to 1 atmosphere, maximum specific impulse was 295.8 pound-seconds per pound. Five percent by weight of water in the hydrazine lowered specific impulse from about one to three units over a wide range of weight-percent fuel.

Huff, Vearl N↗
DOE OSTI2024

Implementation of new mixture rules has a substantial impact on combustion predictions for H 2 and NH 3

Complex-forming reactions comprise a substantial fraction of all important combustion reactions and are central to combustion behavior. Despite being often called “pressure-dependent” reactions, their rate constants depend on not only the pressure but also the composition. While modern combustion codes allow arbitrarily high accuracy in treating pressure dependence, recent work has consistently demonstrated dramatic failures of essentially all available treatments of mixture dependence. In situations where mixture dependence is treated at all, it is inevitably treated through specification of pressure-dependent rate constants for a set of pure bath gases, which are then combined to estimate the rate constant in a mixture via a “mixture rule.” While there had been a generally unquestioning confidence in these mixture rules, they had, in reality, been scarcely tested until the last decade, when comparisons against master equation calculations revealed order-of-magnitude errors for important pressure-dependent reactions. New mixture rules, based on the reduced pressure, have recently been proposed and shown to reproduce master equation calculations for broad classes of complex-forming reactions very accurately. Here, in this work, we present an implementation of one such new mixture rule (“LMR-R”) in Cantera and then use it to enable simulations that use new high-accuracy ab initio data for individual bath gases (for the first time, since codes previously could not accommodate the complex bath gas dependence). Demonstrations focus on combustion of H 2 and NH 3 , where (1) high-accuracy ab initio data are available and (2) the impact is expected to be large due to the high fractions of efficient colliders (e.g., H 2 O and NH 3 ) in the burned and unburned gases. Indeed, we find the impact of this treatment to be substantial and may explain previous modeling difficulties for these important carbon-free fuels, particularly for NH 3 , whose extraordinarily high third-body efficiency (~20) is often omitted from kinetic models.

Ammonia↗
DOE OSTI2024

Bioactivity Profiling of Chemical Mixtures for Hazard Characterization

Abstract The assessment and regulation of chemical toxicity to protect human health and the environment are done one chemical at a time and seldom at environmentally relevant concentrations. However, chemicals are found in the environment as mixtures, and their toxicity is largely unknown. Understanding the hazard posed by chemicals within the mixture is critical to enforce protective measures. Here, we demonstrate the application of bioactivity profiling of environmental water samples using the sentinel and ecotoxicology model species Daphnia to reveal the biomolecular response induced by exposure to real-world mixtures. We exposed a Daphnia strain to 30 sampled waters of the Chaobai River and measured the gene expression response profiles. Using a multiblock correlation analysis, we establish correlations between chemical mixtures identified in 30 water samples with gene expression patterns induced by these chemical mixtures. We identified 80 metabolic pathways putatively activated by mixtures of inorganic ions, heavy metals, polycyclic aromatic hydrocarbons, industrial chemicals, and a set of biocides, pesticides, and pharmacologically active substances. Our data-driven approach discovered both known bioactivity signatures with previously described modes of action and new pathways linked to undiscovered potential hazards. This study demonstrates the feasibility of reducing the complexity of real-world mixture toxicity to characterize the biomolecular effects of a defined number of chemical components based on gene expression monitoring of the sentinel species Daphnia.

Engineering↗
NASA NTRS1950

Foaming of mixtures of pure hydrocarbons

Mixtures of pure liquid hydrocarbons are capable of foaming. Nine hydrocarbons were mixed in pairs, in all possible combinations, and four proportions of each combination. These mixtures were sealed in glass tubes, and the foaming was tested by shaking. Mixtures of aliphatic with other aliphatic hydrocarbons, or of alkyl benzenes with other alkyl benzenes, did not foam. Mixtures of aliphatic hydrocarbons with alkyl benzenes did foam. The proportions of the mixtures greatly affected the foaming, the maximum foaming of 12 of 20 pairs being at the composition 20 percent aliphatic hydrocarbon, 80 percent alkyl benzene. Six seconds was the maximum foam lifetime of any of these mixtures. Aeroshell 120 lubricating oil was fractionated into 52 fractions and a residue by extraction with acetone in a fractionating extractor. The index of refraction, foam lifetime, color, and viscosity of these fractions were measured. Low viscosity and high index fractions were extracted first. The viscosity of the fractions extracted rose and the index decreased as fractionation proceeded. Foam lifetimes and color were lowest in the middle fractions. Significance is attached to the observation that none of the foam lifetimes of the fractions or residue is as high as the foam lifetime of the original Aeroshell, indicating that the foaming is not due to a particular foaming constituent, but rather to the entire mixture.

LUBRICATING OILS - DISTILLATION↗
NASA NTRS1981

Laboratory measurements of selected optical, physical, chemical, and remote-sensing properties of five water mixtures containing Calvert clay and a nonfluorescing dye

Total suspended solids concentrations ranged from 6.1 ppm to 24.3 ppm and sizes ranged between 1.5 micrometers and 10 micrometers with the most frequently occurring size less than 2 micrometers. Iron concentration was less than 1 percent of the total suspended solids. Nonfluorescing dye concentrations of the two mixtures were 20 ppm and 40 ppm. Attenuation coefficient for the five mixtures ranged from 4.8/m to 21.3/m. Variations in volume scattering function with phase angle were typical. Variations in attenuation and absorption coefficient with wavelength were similar for the mixtures without the dye. Attenuation coefficient of the mixtures with the dye increased for wavelengths less than 600 nm due to the dye's strong absorption peak near 500 nm. Reflectance increased as the concentration of Calvert clay increased and peaked near 600 nm. The nonfluorescent dye decreased the magnitude of the peak, but had practically no effect on the variation for wavelengths greater than 640 nm. At wavelengths less than 600 nm, the spectral variations of the mixtures with the dye were significantly different from those mixtures without the dye.

Usry, J. W.↗
DOE OSTI2025

Using Neural Networks to Identify Mixture Components in Hyperspectral Reflectance Data

Neural networks have been employed to identify materials of interest from hyperspectral data (generally imagery) based on their unique spectral signatures. This approach assumes that there is a single material that is standing out from the rest of the spectrum to be identified. However, pixels often contain more than one material, or a material of interest may itself be a mixture of multiple materials. Neural networks are only as good as the data used to train them, and it takes a great deal of work in the laboratory to identify, make, and measure all potential mixtures of interest. Thus, researchers often calculate synthetic spectra using algorithms with varying degrees of fidelity to the physics that govern the interactions between light and multiple materials. In this work, we have (1) adapted a neural network designed to identify mixture components from Raman spectroscopy to work with visible to near‐infrared reflectance data and (2) tested three common mixture algorithms to determine the most accurate and least computationally expensive method to build synthetic training datasets. With our initial test dataset, we have achieved accuracies of > 90% and found that the synthetic training dataset produced using the Hapke mixture model provides the best results.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Direct Simulations of H–He Mixtures at Planetary Interior Conditions: Demixing, Insulator–Metal Transition and Miscibility Boundaries

Accurate knowledge of the electrical and thermal conductivities and structural properties of hydrogen–helium mixtures under thermodynamic conditions within and beyond the immiscibility range is very important to predict the thermal evolution and internal structure of gas giant planets like Jupiter and Saturn. Here, we propose a novel method to determine the immiscibility boundary accurately without the need for free energy calculations, while providing consistent insights into structural and transport properties of mixtures. We show with direct large-scale ab initio simulations that the insulator–metal transition (IMT) of the hydrogen subsystem is strongly affected by an admixture with a small fraction of helium and occurs at temperatures significantly higher than those of pure hydrogen. At pressures below 150 GPa, the IMT boundary is not related anymore to the H 2 subsystem dissociation, the system remains insulating even after the full dissociation of H 2 molecules and its transition to an H–He mixture. The offset of the IMT in the H–He mixture relative to the dissociation region in the hydrogen subsystem and the significant reduction of static electrical and thermal conductivity by a factor between two and a few thousand relative to pure hydrogen found in mixtures have consequences for Jupiter and Saturn’s thermal evolution, internal structure, and dynamo action, affecting a large fraction of the interior of both planets.

Helium↗
DOE OSTI2025

Energy resolution and gain measurements in Argon-based gas mixtures: Exploring Ar:CF 4 for low energy measurements with TPCs

Time Projection Chambers (TPCs) are among the most advanced charged-particle detectors. Gas-filled TPCs have tracking capabilities that provide 3D-imaging of charged particles with a good energy resolution for spectroscopy. Different gas mixtures have different properties that determine the energy resolution as well as the spatial resolution. Therefore, optimization of operating conditions is required to simultaneously obtain adequate gain, energy resolution, spatial/track resolution, as well as higher drift velocities for high counting rates applications. Ar:CF 4 gas mixture has higher electron drift velocities and lower electron diffusion, which makes it an attractive candidate for TPC filling gas for low energy nuclear physics applications as compared to commonly used Ar:CH 4 and Ar:CO 2 gas mixtures, namely when tracking information is needed. However, other properties, including energy resolution and gain, remain largely unexplored in Ar:CF 4 especially at pressures and other operating conditions relevant for low-energy nuclear physics applications. Here, in this paper we report on gain and energy resolution measurements, using Gas Electron Multipliers (GEMs), in the less explored Ar:CF 4 mixture (Alfonsi et al., 2006), as well as in the more commonly used gas mixtures Ar:CH 4 and Ar:CO 2 . In addition to obtaining energy resolution and gain, we provide results from Garfield++ simulations for gain fluctuations, and their impact on energy resolution is discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Effect of particle shape on stratification in drying films of binary colloidal mixtures

The role of particle shape in evaporation-induced auto-stratification in polydisperse colloidal suspensions is explored with molecular dynamics simulations of mixtures of spheres and aspherical particles. A unified framework based on the competition between diffusion and diffusiophoresis is proposed to understand the effects of shape and size dispersity. In general, particles diffusing more slowly (e.g., larger particles) tend to accumulate more strongly at the evaporation front. However, larger particles have larger surface areas and therefore greater diffusiophoretic mobility. Hence, they are more likely to be driven away from the evaporation front via diffusiophoresis. For a rapidly dried bidisperse suspension containing small and large spheres, the competition leads to “small-on-top” stratification. Here, we employ a computational model in which the diffusion coefficient is inversely proportional to particle mass. For a mixture of spheres and aspherical particles with similar mass, the diffusion contrast is reduced, and the spheres are always enriched at the evaporation front as they have the smallest surface area for a given mass and, therefore, the lowest diffusiophoretic mobility. Furthermore, for a mixture of solid and hollow spheres that have the same outer radius and thus the same surface area, the diffusiophoretic contrast is suppressed, and the system is dominated by diffusion. Consequently, the solid spheres, which have a larger mass and diffuse more slowly, accumulate on top of the hollow spheres. Finally, for a mixture of thin disks and long rods that differ significantly in shape but have similar mass and surface area, both diffusion and diffusiophoresis contrasts are suppressed, and the mixture does not stratify.

Classical molecular dynamic simulations↗