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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 253 records · Page 14

Structure–Transport Relationships of Water–Organic Solvent Co-transport in Carbon Molecular Sieve (CMS) Membranes

We explore the effects of the carbon molecular sieve (CMS) microstructure on the separation performance and transport mechanism of water–organic mixtures. Specifically, we utilize PIM-1 dense films and integrally skinned asymmetric hollow fiber membranes as polymer precursors for the CMS materials. The PIM-1 membranes were pyrolyzed under several different pyrolysis atmospheres (argon, carbon dioxide, and diluted hydrogen gas) and at multiple pyrolysis temperatures. Detailed gas physisorption measurements reveal that membranes pyrolyzed under 4% H 2 and CO 2 had broadened ultramicropore distributions (pore diameter <7 Å) compared to Ar pyrolysis, and pyrolysis under CO 2 increased ultramicropore volume and broadened micropore distributions at increased pyrolysis temperatures. Gravimetric water and p-xylene sorption and diffusion measurements reveal that the PIM-1-derived CMS materials are more hydrophilic than other CMS materials that have been previously studied, which leads to sorption-diffusion estimations showing water-selective permeation. Water permeation in the vapor phase, pervaporation, and liquid-phase hydraulic permeation reveal that the isobaric permeation modes (vapor permeation and pervaporation) are reasonably well predicted by the sorption-diffusion model, whereas the hydraulic permeation mode is significantly underpredicted (>250×). Conversely, the permeation of p-xylene is well predicted by the sorption-diffusion model in all cases. The collection of pore size analysis, vapor sorption and diffusion, and permeation in different modalities creates a picture of a combined transport mechanism in which water–under high transmembrane pressures–permeates via a Poiseuille-style mechanism, whereas p-xylene solutes in the mixture permeate via sorption-diffusion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Laminar flamelet modeling of turbulent diffusion flames

In modeling turbulent combustion, decoupling the chemistry from the turbulence is of great practical significance. In cases in which the equilibrium chemistry model breaks down, laminar flamelet modeling (LFM) is a promising approach to decoupling. Here, the validity of this approach is investigated using direct numerical simulation of a simple chemical reaction in two-dimensional turbulence.

Mell, W. E.↗

A Quasielastic Neutron Scattering Study of Water Diffusion in Model Anion Exchange Membranes over Localized and Extended Volume Increments

Anion exchange membranes provide the basis for potentially more cost-effective fuel cells, electrochemical energy conversion, and energy storage. The membranes consist of a polymer domain with tethered cationic side groups and a pervading aqueous domain that conducts water and anions. Water diffusion is investigated through temperature-dependent quasielastic neutron scattering (QENS) at application relevant water contents, employing the BASIS spectrometer at ORNL. The spectrometer resolves two distinct quasielastic components corresponding to localized water diffusion (on length scales lower than the water domain thickness) and to extended water diffusion (on length scales approaching the water domain thickness). Water diffusion coefficients in membranes are time and length scale dependent and water exchanges between diffusion on a localized and extended volume increment. An exchange model for QENS is developed to describe the exchange of water between the two volume increments. In conclusion, the populations and lifetimes of water in each volume are discussed in terms of their connection to long-range water transport and membrane nanomorphology.

Diffusion↗

Modeling of diffuse interstellar clouds - The case of Gamma Arae

Observations of the interstellar cloud toward Gamma Arae (Morton and Hu, 1975) are analyzed with an improved version of the isobaric, steady-state model of Glassgold and Langer (1974). Good agreement is obtained using parameters which are close to those which represent the average properties of many diffuse interstellar clouds. The successful correlation of the data for H, H2, C II, C I, OI, CO, and OH supports current concepts on interstellar thermodynamics and chemistry.

Federman, S. R.↗

Impact of combustion products from Space Shuttle launches on ambient air quality

The present work describes some multilayer diffusion models and a computer program for these models developed to predict the impact of ground clouds formed during Space Shuttle launches on ambient air quality. The diffusion models are based on the Gaussian plume equation for an instantaneous volume source. Cloud growth is estimated on the basis of measurable meteorological parameters: standard deviation of the wind azimuth angle, standard deviation of wind elevation angle, vertical wind-speed shear, vertical wind-direction shear, and depth of the surface mixing layer. Calculations using these models indicate that Space Shuttle launches under a variety of meteorological regimes at Kennedy Space Center and Vandenberg AFB are unlikely to endanger the exposure standards for HCl; similar results have been obtained for CO and Al2O3. However, the possibility that precipitation scavenging of the ground cloud might result in an acidic rain that could damage vegetation has not been investigated.

Dumbauld, R. K.↗

Measuring Moisture Levels in Graphite Epoxy Composite Sandwich Structures

Graphite epoxy composite (GEC) materials are used in the construction of rocket fairings, nose cones, interstage adapters, and heat shields due to their high strength and light weight. However, they absorb moisture depending on the environmental conditions they are exposed to prior to launch. Too much moisture absorption can become a problem when temperature and pressure changes experienced during launch cause the water to vaporize. The rapid state change of the water can result in structural failure of the material. In addition, heat and moisture combine to weaken GEC structures. Diffusion models that predict the total accumulated moisture content based on the environmental conditions are one accepted method of determining if the material strength has been reduced to an unacceptable level. However, there currently doesn t exist any field measurement technique to estimate the actual moisture content of a composite structure. A multi-layer diffusion model was constructed with Mathematica to predict moisture absorption and desorption from the GEC sandwich structure. This model is used in conjunction with relative humidity/temperature sensors both on the inside and outside of the material to determine the moisture levels in the structure. Because the core materials have much higher diffusivity than the face sheets, a single relative humidity measurement will accurately reflect the moisture levels in the core. When combined with an external relative humidity measurement, the model can be used to determine the moisture levels in the face sheets. Since diffusion is temperaturedependent, the temperature measurements are used to determine the diffusivity of the face sheets for the model computations.

Nurge, Mark↗

A closure model of diffusion transport of the Reynolds-stress equations and its application to a turbulent step flow

A study is made for the development and computations of the separating and reattaching shear flows. The highlight of the study is an attempt to predict the third-moments of turbulent velocity which is responsible for the diffusion transport of the Reynolds stresses. The present computations show that the third-moments obtained by employing the low-Reynolds number model of transport equations improve the prediction of the third-moments.

Amano, R. S.↗

Improving unfolding and systematic uncertainty estimation using generative diffusion networks (Final Technical Report)

This final technical report summarizes the key accomplishments on the unfolding using diffusion model project, a DOE award received by PI Pierre-Hugues Beauchemin at Tufts University. This project main goal was to investigate the potential of diffusion models for unfolding experimental High Energy Physics data from detector effects while controlling systematics uncertainties. The project accomplished its goals by completing the following objectives: 1) Performing an object-by-object, event-by-event unfolding of various kinematic distributions reconstructed from detector data in HEP in a way that keeps correlations between unfolded observables while demonstrating competitive performance compared to standard algorithms used in the field; 2) Address the generalization problem by developing an unfolding algorithm capable to correctly infer the underlying distributions of observables and processes never seen before, while controlling the dominant theoretical uncertainties affecting the process, therefore increasing the effectiveness, the precision, and the applicability of the developed algorithm; 3) Understand the theoretical foundations between the developed algorithm so to extend it to applications beyond experimental HEP, for broader benefits to the society. This report provides an overview of the accomplishments related to each of these key objectives.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A model of spatio-temporal regulation within biomaterials using DNA reaction–diffusion waveguides

In multi-cellular organisms, cells and tissues coordinate biochemical signal propagation across length scales spanning micrometres to metres. Designing synthetic materials with similar capacities for coordinated signal propagation could allow these systems to adaptively regulate themselves across space and over time. Here, we combine ideas from cell signalling and electronic circuitry to propose a biochemical waveguide that transmits information in the form of a concentration of a DNA species on a directed path. The waveguide could be seamlessly integrated into a soft material because there is virtually no difference between the chemical or physical properties of the waveguide and the material it is embedded within. We propose the design of DNA strand displacement reactions to construct the system and, using reaction–diffusion models, identify kinetic and diffusive parameters that enable super-diffusive transport of DNA species via autocatalysis. Finally, to support experimental waveguide implementation, we propose a sink reaction and spatially inhomogeneous DNA concentrations that could mitigate the spurious amplification of an autocatalyst within the waveguide, allowing for controlled waveguide triggering. Chemical waveguides could facilitate the design of synthetic biomaterials with distributed sensing machinery integrated throughout their structure and enable coordinated self-regulating programmes triggered by changing environmental conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Research in the use of electrets in measuring effluents from rocket exhaust of the space shuttle (6.4 percent scaled model) and Viking 1 launch

Electrets used to detect the chemical composition of rocket exhaust effluents were investigated. The effectiveness of electrets was assessed while comparisons were made with hydrogen chloride measuring devices from chamber and field tests, and computed results from a multilayer diffusion model. The experimental data used were obtained from 18 static test firings, chamber tests, and the Viking 1 launch to Mars. Results show that electrets have multipollutant measuring capabilities, simplicity of deployment, and speed of assessment. The electrets compared favorably with other hydrogen chloride measuring devices. The summary of the measured data from the electrets and the hydrogen chloride detectors was within the upper and lower bounds of the computed hydrogen chloride concentrations from the multilayer diffusion model.

Susko, M.↗

Mass Transport Limitations and Kinetic Consequences of Corn Stover Deacetylation

Alkaline pretreatment of herbaceous feedstocks such as corn stover prior to mechanical refining and enzymatic saccharification improves downstream sugar yields by removing acetyl moieties from hemicellulose. However, the relationship between transport phenomena and deacetylation kinetics is virtually unknown for such feedstocks and this pretreatment process. Here, we report the development of an experimentally validated reaction–diffusion model for the deacetylation of corn stover. A tissue-specific transport model is used to estimate transport-independent kinetic rate constants for the reactive extraction of acetate, hemicellulose and lignin from corn stover under representative alkaline conditions (5–7 g L -1 NaOH, 10 wt% solids loadings) and at low to mild temperatures (4–70°C) selected to attenuate individual component extraction rates under differential kinetic regimes. The underlying transport model is based on microstructural characteristics of corn stover derived from statistically meaningful geometric particle and pore measurements. These physical descriptors are incorporated into distinct particle models of the three major anatomical fractions (cobs, husks and stalks) alongside an unsorted, aggregate corn stover particle, capturing average Feret lengths of 917–1239 μm and length-to-width aspect ratios of 1.8–2.9 for this highly heterogeneous feedstock. Individual reaction–diffusion models and their resulting particle model ensembles are used to validate and predict anatomically-specific and bulk feedstock performance under kinetic-controlled vs. diffusion-controlled regimes. In general, deacetylation kinetics and mass transfer processes are predicted to compete on similar time and length scales, emphasizing the significance of intraparticle transport phenomena. Critically, we predict that typical corn stover particles as small as ~2.3 mm in length are entirely diffusion-limited for acetate extraction, with experimental effectiveness factors calculated to be 0.50 for such processes. Debilitatingly low effectiveness factors of 0.021–0.054 are uncovered for cobs—implying that intraparticle mass transfer resistances may impair observable kinetic measurements of this anatomical fraction by up to 98%. These first-reported quantitative maps of reaction vs. diffusion control link fundamental insights into corn stover anatomy, biopolymer composition, practical size reduction thresholds and their kinetic consequences. These results offer a guidepost for industrial deacetylation reactor design, scale-up and feedstock selection, further establishing deacetylation as a viable biorefinery pretreatment for the conversion of lignocellulosics into value-added fuels and chemicals.

09 BIOMASS FUELS↗

Rocket exhaust ground cloud/atmospheric interactions

An attempt to identify and minimize the uncertainties and potential inaccuracies of the NASA Multilayer Diffusion Model (MDM) is performed using data from selected Titan 3 launches. The study is based on detailed parametric calculations using the MDM code and a comparative study of several other diffusion models, the NASA measurements, and the MDM. The results are discussed and evaluated. In addition, the physical/chemical processes taking place during the rocket cloud rise are analyzed. The exhaust properties and the deluge water effects are evaluated. A time-dependent model for two aerosol coagulations is developed and documented. Calculations using this model for dry deposition during cloud rise are made. A simple model for calculating physical properties such as temperature and air mass entrainment during cloud rise is also developed and incorporated with the aerosol model.

Hwang, B.↗

Theoretical calculations of ion acceleration in the vicinity of comet Giacobini-Zinner

Ionization of cometary neutral molecules produces ions which are picked up by the solar wind. The cometary ion pickup process for comet Giacobini-Zinner is studied in two ways: (1) with a test particle method in which trajectories are numerically calculated for several thousand ions whose initial locations were chosen randomly with probability proportional to the neutral density and (2) with a quasi-linear diffusion model. The cometary ion distribution function was calculated with the test particle model at several locations upstream of the bow shock and for several types of magnetic fluctuations (or waves). These waves were allowed to propagate in both directions along the magnetic field at the Alfven speed. Both pitch angle scattering and energy diffusion are evident in the derived ion distributions. The monochromatic waves result in less ion acceleration than turbulent fluctuations with about the same amplitude. The calculated ion distribution functions are in reasonable agreement with the distributions measured in the vicinity of comet Giacobini-Zinner in 1985 by particle detectors on the ICE spacecraft when the ratio of power in sunward propagating Alfven waves to the power in antisunward propagating waves is assumed to lie between about 20% and 50%. However, the quasi-linear diffusion model results agree best with the measured distribution functions when the power ratio is only about 3 percent.

Mckenzie, M. L.↗

Tunable Atomic Layer Deposition into Ultra-High-Aspect-Ratio (>60000:1) Aerogel Monoliths Enabled by Transport Modeling

Atomic layer deposition (ALD) modification of ultra-high-aspect-ratio structures (>10,000:1) is a powerful platform with applications in catalysis, filtration, and energy conversion. However, the deposition of conformal and tunable ALD coatings at these aspect ratios remains challenging, resulting in empirical tradeoffs between precursor utilization and reaction time. Here, we demonstrate tunable control of the ALD infiltration depth into an aerogel monolith (AM) and develop a reaction-diffusion model to accurately describe the coating process. Specifically, we investigate the ALD exposure time and precursor dose needed to conformally coat a silica AM with pore sizes of ~20 nm, a monolith thickness of ~2.5 mm, and aspect ratios exceeding 60,000:1. We demonstrate complete infiltration into the AM, which is quantified by elemental mapping. A reaction-diffusion model is developed, which accounts for multiple doses and precursor depletion in the ALD chamber during an exposure step. The experimentally validated model enables the prediction and tuning of infiltration depth into a tortuous, high-aspect-ratio structure such as an AM, allowing for the synthesis of rationally designed material architectures. Additionally, the model allows for co-optimization of the total deposition time and percentage of unreacted precursor, which are important for the manufacturability and sustainability of ALD processing. Lastly, we demonstrate that ultra-thin ALD Al 2 O 3 coatings can be used to stabilize silica AMs against structural degradation under high-temperature annealing conditions (700-800 °C), by limiting changes in surface area and monolith volume. As a result, this improved high-temperature stability has implications for numerous aerogel applications, including catalysis and thermal insulation.

14 SOLAR ENERGY↗

Timescales of mafic magmatic fractionation documented by paleosecular variation in basaltic drill core, Snake River Plain volcanic province, Idaho, USA

Abstract The timescales over which fractional crystallization and recharge work in mafic volcano-plutonic provinces is subject to great uncertainty. Currently modeled processes are subject to the scale of measurement: monogenetic basaltic fields accumulate over hundreds of thousands of years, consistent with U-Th-Ra isotopic variations that imply 50% crystallization of basic magmas on timescales of 100,000 years or more, whereas crystal diffusion modeling implies phenocryst residence times of ~1–1000 years. Monogenetic basalts of the Snake River Plain in southern Idaho, USA, are up to 2 km thick and postdate passage over the Yellowstone–Snake River Plain hotspot. Detailed lithologic and geophysical logging of core from deep drill holes, along with chemical stratigraphy and high-resolution paleomagnetic inclination measurements, document individual eruptive units, compound lava flows, and basaltic flow groups that accumulated over 1–6 m.y. Hiatuses are commonly marked by loess or fluvial interbeds that vary from ~0.1 m thick to 20 m thick. Radiometric (40Ar-39Ar, detrital zircon U-Pb) and paleomagnetic timescale ages show that the deepest hole (Kimama drill hole, 1912 m total depth) accumulated over ~6 m.y. Cycles of fractional crystallization and recharge are recognized in the chemical stratigraphy as up-section shifts in major and trace elements; these fractionation cycles commonly represent 40%–50% fractionation. Individual fractionation cycles may comprise 20–40 eruptive units (8–17 lava flows) with little to no change in paleomagnetic inclination (0°–1°), whereas adjacent cycles may differ by several degrees from one another or reflect changes in polarity. Rates of paleosecular variation in Holocene lavas and sediments dated using 14C document significant shifts in magnetic inclination over short timescales, ranging from ~0.05° to 2°/decade, with an average of ~0.5°/decade and a minimum rate of 0.05°/decade. This implies that fractionation cycles with ≤1° variation in magnetic inclination formed on timescales of a few decades up to a few centuries (20–200 years). Thus, the lavas collectively represent only a few thousand years of eruptive activity, with major flow groups separated in time by tens to hundreds of thousands of years. We suggest that the rates defined by paleosecular variation capture the timescales of magmatic chamber evolution (fractionation/recharge) in the seismically imaged mid-crustal sill complex; in contrast, we suggest that crystal diffusion modeling captures the residence times in shallow subvolcanic magmatic chambers that underlie individual monogenetic volcanoes.

Geology↗

Simulations of the churning mode: Toroidally symmetric plasma convection and turbulence around the X-points in a snowflake divertor

Using a reduced MHD model, extended to include field-aligned thermal conduction, we present numerical simulations of the churning mode (CM): a toroidally symmetric, non-linear plasma vortex in the vicinity of the null points in a snowflake (SF) divertor [D. D. Ryutov et al., Phys. Scr. 89, 088002 (2014)]. Simulations are carried out across a range of inter-null separations, d xx ⁠, and inter-null orientations, θ⁠, primarily in conditions relevant to the MAST-U tokamak. We find that, when d xx is small, the CM induces additional transport across the X-points when β pm ≳8%, where β pm is the ratio of the plasma pressure in the null region to poloidal magnetic pressure at the midplane. This transport also increases approximately linearly as d xx is reduced. A diffusive model of this transport is shown to predict the total transport across the null points, where diffusion coefficients of up to ∼ 10 2 m 2 s −1 centered on a small region around the X-points are used. However, the CM also results in significant changes to the flux surfaces in the null region, which is not captured by this diffusive model. The changes in magnetic geometry mean the fractional exhaust power delivered to each divertor leg is highly sensitive to β pm ⁠, d xx ⁠, and θ⁠. For small values of θ⁠, the CM can induce a change in topology, redirecting exhaust power from a secondary divertor leg on the high field side to one on the low field side. Similar behavior is found in the fraction of exhaust power going to the inner and outer divertor. Such changes in the flux surfaces may not be captured by Grad–Shafranov solvers and so may be a source of error in the magnetic reconstruction of SF experiments. We consistently find that the fractional exhaust power going to a secondary divertor leg on the high field side is small, consistent with SF experiments.

Computer simulation↗

Resolving turbulent magnetohydrodynamics: a hybrid operator-diffusion framework

We present a hybrid machine learning framework that combines physics-informed neural operators (PINOs) with score-based generative diffusion models to simulate the full spatio-temporal evolution of two-dimensional, incompressible, resistive magnetohydrodynamic turbulence across a broad range of Reynolds numbers (Re). The framework leverages the equation-constrained generalization capabilities of PINOs to predict coherent, low-frequency dynamics, while a conditional diffusion model stochastically corrects high-frequency residuals, enabling accurate modeling of fully developed turbulence. Trained on a comprehensive ensemble of high-fidelity simulations with Re ϵ {100, 250, 500, 750, 1000, 3000, 10000}, the approach achieves state-of-the-art accuracy in regimes previously inaccessible to deterministic surrogates. At Re = 1000 and 3000, the model faithfully reconstructs the full spectral energy distributions of both velocity and magnetic fields late into the simulation, capturing non-Gaussian statistics, intermittent structures, and cross-field correlations with high fidelity. At extreme turbulence levels (Re = 10 000), it remains the first surrogate capable of recovering the high-wavenumber evolution of the magnetic field, preserving large-scale morphology and enabling statistically meaningful predictions.

Diffusion-Integrated Neural Operators↗

Numerical solution of the problem of flame propagation by the use of the random element method

A numerical, grid-free algorithm is presented for one-dimensional reaction-diffusion model of laminar flame propagation in premixed gases. It is based on the random element method we developed for the analysis of diffusional processes. The effect of combustion is taken into account by applying the principle of fractional steps to separate the process of diffusion, modeled by the random walk of computational elements, from the exothermic effects of chemical reaction, monitoring their strength. The validity of the algorithm is demonstrated by application to flame propagation problems for which exact solutions exist. The flame speed evaluated by its use oscillates around the exact value at a relatively small amplitude, while the temperature and species concentration profiles are self-correcting in their convergence to the exact solution. A satisfactory resolution is obtained by the use of quite a small number of computational elements which automatically adjust their distribution of fit sharp gradients.

Ghoniem, A. F.↗