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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

EXPERIMENTAL AND MODELING STUDY OF MOLECULAR TRANSPORT PHENOMENA IN COMPLEX LIQUID MIXTURES USING COVALENT ORGANIC FRAMEWORK MEMBRANES

Currently, 10-15% of the world’s energy is consumed by chemical separations, and more than 80% of that is used to purify organic liquids and recover rare earth elements and critical minerals. Membrane nanofiltration presents an energy-efficient, cost-effective, and eco-friendly alternative to current separation technologies. These complex liquid environments require high- performance, chemically-resistant membrane materials. Recently discovered Covalent Organic Frameworks (COFs) possess desirable properties as membrane materials for complex liquid separations. COFs are highly crystalline, chemically and thermally stable, with tunable size and charge. COFs, especially two-dimensional highly crystalline COFs, possess narrow pore-size distribution and controlled porous structures. Two-dimensional COFs are also resistant to swelling, another feature beneficial in complex liquid separations. Molecular interactions in complex liquid systems often dictate final membrane performance, resulting in a discrepancy between designed and apparent COF properties. Understanding and resolving this discrepancy is critical in utilizing COF membranes as a viable alternative to energy-intensive separations. The primary objective of this thesis was to use a commercially available COF TpPa-1 as a platform to investigate how mixed solvent environment affects COF membrane performance via experimental and molecular modeling studies. Specifically, the effects of solution pH, solvent- solvent-solute interactions in mixed solvents, and COF chemistry were carefully examined on apparent TpPa-1 pore size and permeability and targeted solute rejection of COF membranes for neat and mixed solvents. Experimental COF filtration performance was compared and corroborated with modeling predication. Findings from this study will provide guidance for future COF design, synthesis, and desired functional COF membrane performance.

Barnes, Anastasia↗
NASA NTRS2006

Spectral Variability among Rocks in Visible and Near Infrared Multispectral Pancam Data Collected at Gusev Crater: Examinations using Spectral Mixture Analysis and Related Techniques

Visible and Near Infrared (VNIR) multispectral observations of rocks made by the Mars Exploration Rover Spirit s Panoramic camera (Pancam) have been analysed using a spectral mixture analysis (SMA) methodology. Scenes have been examined from the Gusev crater plains into the Columbia Hills. Most scenes on the plains and in the Columbia Hills could be modeled as three endmember mixtures of a bright material, rock, and shade. Scenes of rocks disturbed by the rover s Rock Abrasion Tool (RAT) required additional endmembers. In the Columbia Hills there were a number of scenes in which additional rock endmembers were required. The SMA methodology identified relatively dust-free areas on undisturbed rock surfaces, as well as spectrally unique areas on RAT abraded rocks. Spectral parameters from these areas were examined and six spectral classes were identified. These classes are named after a type rock or area and are: Adirondack, Lower West Spur, Clovis, Wishstone, Peace, and Watchtower. These classes are discriminable based, primarily, on near-infrared (NIR) spectral parameters. Clovis and Watchtower class rocks appear more oxidized than Wishstone class rocks and Adirondack basalts based on their having higher 535 nm band depths. Comparison of the spectral parameters of these Gusev crater rocks to parameters of glass-dominated basaltic tuffs indicates correspondence between measurements of Clovis and Watchtower classes, but divergence for the Wishstone class rocks which appear to have a higher fraction of crystalline ferrous iron bearing phases. Despite a high sulfur content, the rock Peace has NIR properties resembling plains basalts.

Farrand, W. H.↗
NASA NTRS1978

An empirical model for the complex dielectric permittivity of soils as a function of water content

The recent measurements on the dielectric properties of soils shows that the variation of dielectric constant with moisture content depends on soil types. The observed dielectric constant increases only slowly with moisture content up to a transition point. Beyond the transition it increases rapidly with moisture content. The moisture value of transition region was found to be higher for high clay content soils than for sandy soils. Many mixing formulas were compared with, and were found incompatible with, the measured dielectric variations of soil-water mixtures. A simple empirical model was proposed to describe the dielectric behavior of ths soil-water mixtures. The relationship between transition moisture and wilting point provides a means of estimating soil dielectric properties on the basis of texture information.

Wang, J. R.↗
DOE OSTI2023

Monte Carlo goodness-of-fit tests for degree corrected and related stochastic blockmodels

Abstract We construct Bayesian and frequentist finite-sample goodness-of-fit tests for three different variants of the stochastic blockmodel for network data. Since all of the stochastic blockmodel variants are log-linear in form when block assignments are known, the tests for the latent block model versions combine a block membership estimator with the algebraic statistics machinery for testing goodness-of-fit in log-linear models. We describe Markov bases and marginal polytopes of the variants of the stochastic blockmodel and discuss how both facilitate the development of goodness-of-fit tests and understanding of model behaviour. The general testing methodology developed here extends to any finite mixture of log-linear models on discrete data, and as such is the first application of the algebraic statistics machinery for latent-variable models.

Karwa, Vishesh↗
DOE OSTI2021

A generalized distillation network synthesis model

In this report we propose a generalized superstructure-based distillation network synthesis model with improved modeling capabilities resulting in an extended solution space. The model can assign multiple mixtures to be separated (e.g., reactor network effluents) to different columns of the network while considering the interactions among different separation steps. In terms of outlets, products with general specifications, including pure components and multi-component mixtures, as well as streams without strict specifications (e.g., reactor recycle streams) can be readily handled. Furthermore, stream bypass is considered to avoid unnecessary separations, and thermal coupling is considered to yield novel solutions. The proposed model enables seamless integration with reactor network synthesis models thereby leading to solutions that are superior to the ones obtained by conventional sequential approaches.

42 ENGINEERING↗
NASA NTRS1993

Analytical and Numerical Modeling of Flame-Balls in Hydrogen-Air Mixtures

Flame-balls are stationary spherical premixed flames observed in certain near-limit mixtures. It is believed that radiative heat losses are an important stabilizing influence. Numerical solutions of flame balls are constructed for hydrogen-air mixtures using an accurate description of the chemical kinetics, diffusive transport, and radiation losses. A lean limit equivalence ratio of 0.0866 is predicted and a rich limit of 2,828. For any equivalence ratio between the two limits there are two solutions. One is characterized by a small flame, incomplete reactant consumption, and negligible radiation losses. The other by a large flame, complete consumption of one of the reactants, and significant radiation losses. The maximum temperature varies between 1200 and 900 K as the two solution branches are traversed. Much of our discussion is a reprise and modification of previously published analytical results, for these provide physical insight into the nature of the solutions, and suggest that a portion of the large flame branch near the lean limit is stable and so corresponds to observable flames.

Buckmaster, J.↗
NASA NTRSDate not supplied

A Computational Study of Plume Modeling for Space Launch System Abort Scenarios

A series of viscous CFD simulations depicting Space Launch System (SLS) post Mode-1abort scenarios are conducted and analyzed. The primary purpose of these simulations is to study the effect of launch abort vehicle attitude control motor (ACM) and abort motor(AM) plume modeling fidelity on the drag of the aborted core stage. The simulations are first conducted with a fully-coupled, multi-species and chemically reacting model for the freestream gases and the solid rocket abort motor combustion products. Following this, equivalent species are created for the ACM and AM exhaust gases. These equivalent species aim to provide near the same results for core stage drag as the chemically reacting model at a significantly lower computational cost. Finally, the exhaust gases are modeled as calorically perfect air. It was concluded that under most scenarios, both the equivalent species and the perfect air models predict the drag of the aborted core stage sufficiently close to that predicted by the chemically reacting simulations. In these cases, the flow and geometry conditions did not induce significant changes in the composition of the ‘true’ exhaust gas via afterburning of the combustion products. For cases where this was not the case, the properties of the essentially frozen equivalent species and perfect air models deviated from the true mixture, yielding unsatisfactory results. Finally, the accuracy improvements by using the chemically reacting model are weighed against the significant increase in associated computational costs. It was found that the simplified exhaust gas models are at least 4 times less expensive than the chemically reacting model. This may justify the judicious use of these simple models in future work.

CFD↗
NASA NTRSDate not supplied

A Computational Study of Plume Modeling for Space Launch System Abort Scenarios

A series of viscous CFD simulations depicting Space Launch System (SLS) post Mode-1abort scenarios are conducted and analyzed. The primary purpose of these simulations is to study the effect of launch abort vehicle attitude control motor (ACM) and abort motor(AM) plume modeling fidelity on the drag of the aborted core stage. The simulations are first conducted with a fully-coupled, multi-species and chemically reacting model for the freestream gases and the solid rocket abort motor combustion products. Following this, equivalent species are created for the ACM and AM exhaust gases. These equivalent species aim to provide near the same results for core stage drag as the chemically reacting model at a significantly lower computational cost. Finally, the exhaust gases are modeled as calorically perfect air. It was concluded that under most scenarios, both the equivalent species and the perfect air models predict the drag of the aborted core stage sufficiently close to that predicted by the chemically reacting simulations. In these cases, the flow and geometry conditions did not induce significant changes in the composition of the ‘true’ exhaust gas via afterburning of the combustion products. For cases where this was not the case, the properties of the essentially frozen equivalent species and perfect air models deviated from the true mixture, yielding unsatisfactory results. Finally, the accuracy improvements by using the chemically reacting model are weighed against the significant increase in associated computational costs. It was found that the simplified exhaust gas models are at least 4 times less expensive than the chemically reacting model. This may justify the judicious use of these simple models in future work.

CFD↗
DOE OSTI2024

Glass Design Using Machine Learning Property Models with Prediction Uncertainties: Nuclear Waste Glass Formulation

The United States Department of Energy is responsible for managing the legacy nuclear waste stored in underground tanks at the Hanford Site. The waste will be separately vitrified as low-activity waste and high-level waste fractions. Waste glass formulation algorithms have been traditionally developed using partial quadratic mixture property-composition models. Recently, machine learning (ML) techniques have been used to predict glass properties and discover new glass materials for nuclear waste vitrification, and these advancements can be utilized to improve waste glass composition design. In this proof-of-principle study, ML algorithms such as Gaussian process regression (GPR) were used to interpolate glass properties (e.g., viscosity, electrical conductivity, chemical durability). After selecting appropriate sets of GPR hyper-parameters for each property, an optimization program was developed to formulate glass compositions to maximize waste loading while simultaneously satisfying property within constraints. The results of the ML-based waste loadings and glass compositions were compared to those obtained using the traditional methods. Comparing to the previous glass design framework, the ML-based optimization methods offer improved glass designs and a streamlined approach to generation of optimally designed data and near real-time updates.

glass formulation, machine learning, constraints, ↗
NASA NTRS1976

A global average model of atmospheric aerosols for radiative transfer calculations

A global average model is proposed for the size distribution, chemical composition, and optical thickness of stratospheric and tropospheric aerosols. This aerosol model is designed to specify the input parameters to global average radiative transfer calculations which assume the atmosphere is horizontally homogeneous. The model subdivides the atmosphere at multiples of 3 km, where the surface layer extends from the ground to 3 km, the upper troposphere from 3 to 12 km, and the stratosphere from 12 to 45 km. A list of assumptions made in construction of the model is presented and discussed along with major model uncertainties. The stratospheric aerosol is modeled as a liquid mixture of 75% H2SO4 and 25% H2O, while the tropospheric aerosol consists of 60% sulfate and 40% soil particles above 3 km and of 50% sulfate, 35% soil particles, and 15% sea salt below 3 km. Implications and consistency of the model are discussed.

Toon, O. B.↗
NASA NTRS1987

Deconvolution of spectra for intimate mixtures

Visible to near infrared reflectance spectra of macroscopic mixtures have been shown to be linear combinations of the reflections of the pure mineral components in the mixture. However, for microscopic mixtures the mixing systematics are in general nonlinear. The systematics may be linearized by conversion of reflectance to single scattering albedo (w), where the equations which relate reflectance to w depend on the method of data collection. Several proposed mixing models may be used to estimate mineral abundances from the reflectance spectra of intimate mixtures. These models are summarized and a revised model is presented. A noniterative (linear) least squares approach was used for curve fitting and the data, measured as bi-directional reflectance with incidence and emergence angles of 30 and 0 deg were converted to w by a simplified version of Hapke's equation for bi-directional reflectance. This model was tested with two mixture series composed of 45 to 75 micron particles: an anorthite-enstatite series and an olivine-magnetite series. The data indicate that the simplified Hapke's equation may be used to convolve reflectance spectra into mineral abundances if appropriate endmembers are known or derived from other techniques. For surfaces that contain a significant component of very low albedo material, a somewhat modified version of this technique will need to be developed. Since the abundances are calculated using a noniterative approach, the application of this method is especially efficient for large spectral data sets, such as those produced by mapping spectrometers.

Mustard, John F.↗
NASA NTRS1989

Photometric phase functions of common geologic minerals and applications to quantitative analysis of mineral mixture reflectance spectra

The mass fractional abundance of components in intimately mixed, particulate surfaces is calculated from laboratory reflectance spectra using Hapke's (1981) model for bidirectional reflectance. It is found that a simplified version of the model is accurate to within 7 percent for mixtures not containing low albedo components. The model is not appropriate for mixtures with very low and high albedo components. Consideration is given to the possible improvement of the method's accuracy by using an empirical single-particle phase function to describe the scattering characteristics of all minerals, or by solving for the single-particle phase function of the minerals involved exactly using extensive bidirectional reflectance measurements and Hapke's equations for bidirectional reflectance. Also, the results are used to examine the general scattering behavior of particulate mineral surfaces.

Mustard, John F.↗
NASA NTRS1991

Computer codes for the evaluation of thermodynamic and transport properties for equilibrium air to 30000 K

The computer codes developed here provide self-consistent thermodynamic and transport properties for equilibrium air for temperatures from 500 to 30000 K over a temperature range of 10 (exp -4) to 10 (exp -2) atm. These properties are computed through the use of temperature dependent curve fits for discrete values of pressure. Interpolation is employed for intermediate values of pressure. The curve fits are based on mixture values calculated from an 11-species air model. Individual species properties used in the mixture relations are obtained from a recent study by the present authors. A review and discussion of the sources and accuracy of the curve fitted data used herein are given in NASA RP 1260.

Thompson, Richard A.↗
NASA NTRS2004

Interstellar Dust Models Consistent with Extinction, Emission, and Abundance Constraints

We present new interstellar dust models which have been derived by simultaneously fitting the far ultraviolet to near infrared extinction, the diffuse infrared emission, and, unlike previous models, the elemental abundances in dust for the diffuse interstellar medium. We found that dust models consisting of a mixture of spherical graphite and silicate grains, polycyclic aromatic hydrocarbon (PAH) molecules, in addition to porous composite particles containing silicate, organic refractory, and water ice, provide an improved .t to the UV-to-infrared extinction and infrared emission measurements, while consuming the amounts of elements well within the uncertainties of adopted interstellar abundances, including B star abundances. These models are a signi.cant improvement over the recent Li & Draine (2001, ApJ, 554, 778) model which requires an excessive amount of silicon to be locked up in dust: 48 ppm (atoms per million of H atoms), considerably more than the solar abundance of 34 ppm or the B star abundance of 19 ppm.

Zubko, Viktor↗
NASA NTRS2017

Improving Slip Prediction on Mars Using Thermal Inertia Measurements

Rovers operating on Mars have been delayed, diverted, and trapped by loose granular materials. Vision-based mobility prediction approaches often fail because hazardous sand is difficult to distinguish from safe sand based on surface appearance alone. Unlike surface appearance, the thermal inertia of terrain is directly correlated to the same geophysical properties that control slip. This paper presents a quantitative analysis showing that considering thermal inertia improves rover slip prediction on Mars using in-situ data from the Curiosity rover. Thermal inertia is estimated for each slip measurement in sand using both on-board and orbital instruments. Slip models are learned using a mixture of experts approach where the experts are identified using thermal inertia. Two-expert models are compared to a single-expert, vision-only model to show that slip predictions are improved by separating high-slip, low thermal inertia sand from low-slip, high thermal inertia sand. These results support the hypothesis that the consideration of thermal inertia improves mobility estimates for rovers on Mars.

Nesnas, Issa A.↗
DOE OSTI2021

Phase Separation in Ultramassive White Dwarfs

We report ultramassive white dwarfs are extreme endpoints of stellar evolution. Recent findings, such as a missing multi-Gyr cooling delay for a number of ultramassive white dwarfs and a white dwarf with a quasi-Chandrasekhar mass, motivate a better understanding of their evolution. A key process still subject to important uncertainties is the crystallization of their dense cores, which are generally assumed to be constituted of 16 O, 20 Ne, and a mixture of several trace elements (most notably 23 Na and 24 Mg). In this work, we use our recently developed Clapeyron integration technique to compute accurate phase diagrams of three-component mixtures relevant to the modeling of O/Ne ultramassive white dwarfs. We show that, unlike the phase separation of 22 Ne impurities in C/O cores, the phase separation of 23 Na impurities in O/Ne white dwarfs cannot lead to the enrichment of their cores in 23 Na via a distillation process. This severely limits the prospect of transporting large quantities of 23 Na toward the center of the star, as needed in the white dwarf core-collapse mechanism recently proposed by Caiazzo et al. We also show that despite representing ≈10% of the ionic mixture, 23 Na and 24 Mg impurities only have a negligible impact on the O/Ne phase diagram, and the two-component O/Ne phase diagram can be safely used in white dwarf evolution codes. We provide analytic fits to our high-accuracy O/Ne phase diagram for implementation in white dwarf models.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2003

Post-flight Analysis of the Argon Filled Ion Chamber

Atmospheric ionizing radiation is a complex mixture of primary galactic and solar cosmic rays and a multitude of secondary particles produced in collision with air nuclei. The first series of Atmospheric Ionizing Radiation (AIR) measurement flights on the NASA research aircraft ER-2 took place in June 1997. The ER-2 flight package consisted of fifteen instruments from six countries and were chosen to provide varying sensitivity to specific components. These AIR ER-2 flight measurements are to characterize the AIR environment during solar minimum to allow the continued development of environmental models of this complex mixture of ionizing radiation. This will enable scientists to study the ionizing radiation health hazard associated with the high-altitude operation of a commercial supersonic transport and to allow estimates of single event upsets for advanced avionics systems design. The argon filled ion chamber representing about 40 percent of the contributions to radiation risks are analyzed herein and model discrepancies for solar minimum environment are on the order of 5 percent and less. Other biologically significant components remain to be analyzed.

Tai, H.↗
NASA NTRS1994

Canopy reflectance modelling of semiarid vegetation

Three different types of remote sensing algorithms for estimating vegetation amount and other land surface biophysical parameters were tested for semiarid environments. These included statistical linear models, the Li-Strahler geometric-optical canopy model, and linear spectral mixture analysis. The two study areas were the National Science Foundation's Jornada Long Term Ecological Research site near Las Cruces, NM, in the northern Chihuahuan desert, and the HAPEX-Sahel site near Niamey, Niger, in West Africa, comprising semiarid rangeland and subtropical crop land. The statistical approach (simple and multiple regression) resulted in high correlations between SPOT satellite spectral reflectance and shrub and grass cover, although these correlations varied with the spatial scale of aggregation of the measurements. The Li-Strahler model produced estimated of shrub size and density for both study sites with large standard errors. In the Jornada, the estimates were accurate enough to be useful for characterizing structural differences among three shrub strata. In Niger, the range of shrub cover and size in short-fallow shrublands is so low that the necessity of spatially distributed estimation of shrub size and density is questionable. Spectral mixture analysis of multiscale, multitemporal, multispectral radiometer data and imagery for Niger showed a positive relationship between fractions of spectral endmembers and surface parameters of interest including soil cover, vegetation cover, and leaf area index.

Franklin, Janet↗