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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Calculation of residual principal stresses in CVD boron on carbon filaments

A three-dimensional finite element model of the chemical vapor deposition of boron on a carbon substrate (B/C) is developed. The model includes an expansion of the boron after deposition due to atomic rearrangement and includes creep of the boron and carbon. Curves are presented showing the variation of the principal residual stresses and the filament elongation with the parameters defining deposition strain and creep. The calculated results are compared with experimental axial residual stress and elongation measurements made on B/C filaments. For good agreement between calculated and experimental results, the deposited boron must continue to expand after deposition, and the build up of residual stresses must be limited by significant boron and carbon creep rates.

Behrendt, D. R.↗
NASA NTRS2001

Constraints Pb-210 and Be-7 on Wet Deposition and Transport in a Global Three-Dimensional Chemical Tracer Model Driven by Assimilated Meteorological Fields

The atmospheric distributions of the aerosol tracers Pb-210 and Be-7 are simulated with a global three-dimensional model driven by assimilated meteorological observations for 1991-1996 from the NASA Goddard Earth Observing System (GEOSl). The combination of terrigenic Pb-210 and cosmogenic Be-7 provides a sensitive test of wet deposition and vertical transport in the model. Our simulation of moist transport and removal includes scavenging in wet convective updrafts (40% scavenging efficiency per kilometer of updraft), midlevel entrainment and detrainment, first-order rainout and washout from both convective anvils and large-scale precipitation, and cirrus precipitation. Observations from surface sites in specific years are compared to model results for the corresponding meteorological years, and observations from aircraft missions over the Pacific are compared to model results for the days of the flights. Initial simulation of Be-7 showed that cross-tropopause transport in the GEOSl meteorological fields is too fast by a factor of 3-4. We adjusted the stratospheric Be-7 source to correct the tropospheric simulation. Including this correction, we find that the model gives a good simulation of observed Pb-210 and Be-7 concentrations and deposition fluxes at surface sites worldwide, with no significant global bias and with significant success in reproducing the observed latitudinal and seasonal distributions. We achieve several improvements over previous models; in particular, we reproduce the observed Be-7 minimum in the tropics and show that its simulation is sensitive to rainout from convective anvils. Comparisons with aircraft observations up to 12-km altitude suggest that cirrus precipitation could be important for explaining the low concentrations in the middle and upper troposphere.

Liu, Hong-Yu↗
NASA NTRS2004

Modeling of Sheath Ion-Molecule Reactions in Plasma Enhanced Chemical Vapor Deposition of Carbon Nanotubes

In many plasma simulations, ion-molecule reactions are modeled using ion energy independent reaction rate coefficients that are taken from low temperature selected-ion flow tube experiments. Only exothermic or nearly thermoneutral reactions are considered. This is appropriate for plasma applications such as high-density plasma sources in which sheaths are collisionless and ion temperatures 111 the bulk p!asma do not deviate significantly from the gas temperature. However, for applications at high pressure and large sheath voltages, this assumption does not hold as the sheaths are collisional and ions gain significant energy in the sheaths from Joule heating. Ion temperatures and thus reaction rates vary significantly across the discharge, and endothermic reactions become important in the sheaths. One such application is plasma enhanced chemical vapor deposition of carbon nanotubes in which dc discharges are struck at pressures between 1-20 Torr with applied voltages in the range of 500-700 V. The present work investigates The importance of the inclusion of ion energy dependent ion-molecule reaction rates and the role of collision induced dissociation in generating radicals from the feedstock used in carbon nanotube growth.

Hash, David B.↗
DOE OSTI2020

Transport of colloidal particles in microscopic porous medium analogs with surface charge heterogeneity: experiments and fundamental role of single-bead deposition

Understanding colloid transport in subsurface environments is challenging due to complex interactions between colloids, ground water, and porous media over several length scales. Here, we study the transport of colloidal particles through bead-assembled microfluidic porous media analogs (PMAs) with surface charge heterogeneity. The pore-scale dynamics of colloidal particle deposition were measured, as well as the breakthrough curves (BTC) and retention profiles (RP) of deposited colloidal particles at the scale of the entire PMA. From pore-scale experiments, the maximum surface coverage (?max = 0.51) was measured directly, from which the surface blocking function and deposition coefficient (kpore = 3.56 s-1) were obtained. Using these pore-scale parameters, the transport of colloidal particles was modeled using a one-dimensional advection-dispersion equation under the assumption of irreversible adsorption between oppositely charged beads and colloids, showing good agreement with experimental data. This work presents a new approach to fabricate chemically heterogeneous porous media in a microfluidic device that enables direct measurements of pore-scale colloidal deposition. The approach allows a quantitative prediction of colloidal breakthrough and retention via coupling of direct measurements and an advection-dispersion-deposition model.

Guo, Yang↗
DOE OSTI2021

Accounting for uncertainty in complex alluvial aquifer modeling by Bayesian multi-model approach

Alluvial aquifers by nature are complex caused by varied depositional environments. Developing a reliable groundwater model to represent an alluvial aquifer is non-trivial. Also, relying on a single best calibrated model may not be sufficient because of an inadequate choice of model parameter values. To better understand groundwater dynamics and improve model prediction reliability, this study presents a Bayesian multi-model uncertainty quantification (BMMUQ) framework to account for model parameter uncertainty in complex alluvial groundwater modeling. The methodology was applied to the agriculturally intensive Mississippi River alluvial aquifer (MRAA), Northeast Louisiana. An aquifer architecture was first constructed using 7,259 well logs in the MRAA area which covers three fluvial deposits (alluvium, braided-stream terrace, and braided-stream terrace-loess). A 12-layer MODFLOW model was then developed to address the alluvial aquifer complexity and well calibrated through a genetic algorithm. This study quantified model parameter uncertainty in hydraulic conductivity and specific storage of sand facies. Bayesian model averaging (BMA) with the Expectation Maximization (EM) algorithm was adopted to derive posterior model weights and head variances of 50 alternative conceptual groundwater flow models, and thereby obtains BMA ensemble model predictions instead of only relying on the best calibrated conceptual model. Overall, results show that an estimated around 950 million m3 of groundwater storage loss occurs in 2015 with respect to the beginning of 2004, due to high groundwater demand for irrigation in the MRAA area. Explicitly quantifying model uncertainty can produce more reliable groundwater level predictions from BMA ensemble model. The presented groundwater modeling framework improves our understanding of the MRAA and provides a valuable tool to assist agricultural water management.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

The Effect of Gravity Axis Orientation on the Growth of Phthalocyanine Thin Films

Experimentally, many of the functions of electrical circuits have been demonstrated using optical circuits and, in theory, all of these functions may be accomplished using optical devices made of nonlinear optical materials. Actual construction of nonlinear optical devices is one of the most active areas in all optical research being done at this time. Physical vapor transport (PVT) is a promising technique for production of thin films of a variety of organic and inorganic materials. Film optical quality, orientation of microcrystals, and thickness depends critically on type of material, pressure of buffer gas and temperature of deposition. An important but understudied influence on film characteristics is the effect of gravity-driven buoyancy. Frazier, Hung, Paley, Penn and Long have recently reported mathematical modelling of the vapor deposition process and tested the predictions of the model on the thickness of films grown by PVT of 6-(2-methyl-4-nitroanilino)-2,4-hexadiyn-l-ol (DAMNA). In an historic experiment, Debe, et. al. offered definitive proof that copper phthalocyanine films grown in a low gravity environment are denser and more ordered than those grown at 1 g. This work seeks to determine the influence on film quality of gravity driven buoyancy in the low pressure PVT film growth of metal-free phthalocyanine.

Pearson, Earl F.↗
DOE OSTI2025

Density functional theory-based surrogate kinetic models for heterogeneous reactions of hydrocarbon intermediates on silicon carbide

The increasing demand for high-performance materials in advanced technologies highlights the importance of achieving a fundamental understanding and potential control of silicon carbide (SiC) deposition processes. However, existing models often lack sufficient theoretical detail, relying heavily on empirical data and offering limited predictive capability. In particular, the complex surface chemistry governing SiC growth remains poorly understood. This study addresses these challenges by employing density functional theory (DFT) to investigate key heterogeneous reactions involving hydrocarbon intermediates on SiC surfaces, including dehydrogenation, hydrogenation, and carbon deposition. Transition state searches were conducted to identify reaction pathways and energy barriers. While first-principles calculations offer high accuracy, they are computationally intensive. To extend the utility of these first-principles results, vibrational analyses were performed using phonon-based statistical thermochemistry to compute temperature-dependent reaction rates which were used to develop Arrhenius-type surrogate kinetic models. Furthermore, the resulting framework provides a more rigorous, physically grounded basis for integrating atomistic insights into continuum-scale modeling, ultimately enabling improved prediction and optimization of SiC film growth in high-performance material systems.

Density Functional Theory↗
NASA NTRS1980

Calculation of residual principal stresses in CVD boron on carbon filaments

A three-dimensional finite element model of the chemical vapor deposition (CVD) of boron on a carbon substrate (B/C) is developed. The model includes an expansion of the boron after deposition due to atomic rearrangement and includes creep of the boron and carbon. Curves are presented to show how the principal residual stresses and the filament elongation vary as the parameters defining deposition strain and creep are varied. The calculated results are compared with experimental axial residual stress and elongation measurements made on B/C filaments. This comparison requires that for good agreement between calculated and experimental results, the deposited boron must continue to expand after deposition, and that the build-up of residual stresses is limited by significant boron and carbon creep rates.

Behrendt, D. R.↗
NASA NTRS1993

Numerical modeling of ooid size and the problem of Neoproterozoic giant ooids

Temporal variation in ooid size reflects important changes in physical and chemical characteristics of depositional environments. Two numerical models are used to evaluate the effects of several processes influencing ooid size. The first demonstrates that low supply of new ooid nuclei and high cortex growth rate each promote growth of large ooids. The second model demonstrates that high average water velocity and velocity gradient also enhance ooid growth. Several Neoproterozoic oolites contain unusually large ooids, some reaching diameters of up to 16 mm. While lower nuclei supply and higher ooid growth rate may have prevailed prior to the evolution of carbonate-secreting organisms, neither difference can explain the presence of giant ooids in Neoproterozoic deposits because Archean through Mesoproterozoic ooids rarely exceed 5 mm in diameter. In the presence of lower nuclei supply and higher growth rate, high average water velocity may have allowed growth of such large ooids. Higher average water velocity could have been due to a prevalence of carbonate ramps over rimmed shelves during Neoproterozoic time.

NASA Discipline Exobiology↗
NASA NTRS1991

MOCVD of GaAs in a horizontal reactor - Modeling and growth

A two-dimensional model for metalorganic chemical vapor deposition of GaAs in a horizontal reactor is presented. The model is characterized by the following parameters: reactor geometry and operating pressure, thermal boundary conditions, ratio of reactants, chemical reactions, total inlet gas flow rate, as well as molecular weights, thermal conductivities, heat capacities, viscosities, and binary diffusion coefficients of the gas-phase species. Film thickness profiles predicted by the model are compared with those of GaAs thin films grown in the modeled reactor. Results obtained show a good agreement between the predictions and data over the entire length of the deposition region for the low pressure and high flow rate run. Attention is also given to the reactor design and growth conditions.

Clark, Ivan O.↗
DOE OSTI2022

Towards fast and accurate predictions of radio frequency power deposition and current profile via data-driven modelling: applications to lower hybrid current drive

Three machine learning techniques (multilayer perceptron, random forest and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modelling and real-time control applications. The machine learning models use a database of more than 16 000 GENRAY/CQL3D simulations for training, validation and testing. Latin hypercube sampling methods ensure that the database covers the range of nine input parameters ( $n_{e0}$ , $T_{e0}$ , $I_p$ , $B_t$ , $R_0$ , $n_{\|}$ , $Z_{{\rm eff}}$ , $V_{{\rm loop}}$ and $P_{{\rm LHCD}}$ ) with sufficient density in all regions of parameter space. The surrogate models reduce the inference time from minutes to $\sim$ ms with high accuracy across the input parameter space.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

A Stochastic Transport Model for the Cumulative Number of Fissions and Deposited Fission Energy

The stochastic theory of neutron transport is extended to describe the cumulative distribution of fission numbers and deposited fission energy in a multiplying assembly. Solutions for the probability distributions are obtained using analytical approximations and Monte Carlo simulation in lumped geometry and in symmetric homogeneous and heterogeneous spheres. The results show the development of a power-law tail in the steady state fission number and deposited energy distributions when the medium is critical, independent of the fission neutron multiplicity distribution and domain heterogeneity. In contrast, the asymptotic decay is faster than exponential in subcritical media due to rapid chain extinction and in supercritical media due to the increasing probability of chain divergence. Here, a formal asymptotic analysis of the problem in lumped geometry with an arbitrary fission neutron multiplicity confirms the existence of power-law tails at critical.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Arctic Black Carbon Aerosol Deposition Study North Slope of Alaska 2020- UHSAS Measurements

Particles are removed from the atmosphere through both wet and dry deposition. These processes are poorly understood, though they constitute important uncertainties in climate and air quality models. This project aims to use observational constraints on particle fluxes to improve model representations of dry deposition. Within this data set, we measured fluxes of size resolved particles with an ultrahigh sensitivity aerosol spectrometer (UHSAS) at the ARM facility’s North Slope Alaska site. Measurements were made at the meteorological tower between 9 Sept and 25 Oct 2021. This site is a coastal tundra location and received snow during the project.

Aerosol concentration↗
DOE OSTI2025

Arctic Black Carbon Aerosol Deposition Study North Slope of Alaska 2020- SP2 Measurements

Particles are removed from the atmosphere through both wet and dry deposition. These processes are poorly understood, though they constitute important uncertainties in climate and air quality models. This project aims to use observational constraints on particle fluxes to improve model representations of dry deposition. Within this data set, we measured refractory black carbon with a single particle soot photometer (SP2) at the ARM facility’s North Slope of Alaska site. Measurements were made at the meteorological tower between 9 Sept and 27 Oct 2021. This site is a coastal tundra location, and received snow during the project.

Black carbon mass concentration↗
DOE OSTI2025

Arctic Black Carbon Aerosol Deposition Study North Slope of Alaska 2020- Sonic Anemometer Measurements

Particles are removed from the atmosphere through both wet and dry deposition. These processes are poorly understood, though they constitute important uncertainties in climate and air quality models. This project aims to use observational constraints on particle fluxes to improve model representations of dry deposition. Within this data set, we measured wind properties using a sonic anemometer. Measurements were made at the meteorological tower between 9 Sept and 25 Oct 2021. This site is a coastal tundra location, and received snow during the project.

Gill Windmaster 3D Ultrasonic Anemometer↗
DOE OSTI2026

Arctic Black Carbon Aerosol Deposition Study North Slope of Alaska 2020- ACSM Measurements

Particles are removed from the atmosphere through both wet and dry deposition. These processes are poorly understood, though they constitute important uncertainties in climate and air quality models. This project aims to use observational constraints on particle fluxes to improve model representations of dry deposition. In support of black carbon (SP2) and particles (UHSAS) flux measurements at the meteorological tower, we measured non-refractory chemically-speciated aerosol composition with an Aerosol Chemical Speciation Monitor at the the NSA Central Facility (C1). ACSM measurements were made between 9 Sept and 26 Oct 2021. This site is a coastal tundra location, and received snow during the project.

Chl_ACSM↗
DOE OSTI2026

Arctic Black Carbon Aerosol Deposition Study North Slope of Alaska 2020- ACSM Measurements

Particles are removed from the atmosphere through both wet and dry deposition. These processes are poorly understood, though they constitute important uncertainties in climate and air quality models. This project aims to use observational constraints on particle fluxes to improve model representations of dry deposition. In support of black carbon (SP2) and particles (UHSAS) flux measurements at the meteorological tower, we measured non-refractory chemically-speciated aerosol composition with an Aerosol Chemical Speciation Monitor at the the NSA Central Facility (C1). ACSM measurements were made between 9 Sept and 26 Oct 2021. This site is a coastal tundra location, and received snow during the project.

Aerosol Chemical Speciation Monitor↗
DOE OSTI2022

Towards Fast and Accurate Predictions of Radio Frequency Power Deposition and Current Profile via Data-driven Modeling

Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modeling and real-time control applications. The machine learning models use a database of 16,000+ GENRAY/CQL3D simulations for training, validation, and testing. Latin hypercube sampling methods ensure that the database covers the range of 9 input parameters ($n_{e0}$, $T_{e0}$, $I_p$, $B_t$, $R_0$, $n_{||}$, $Z_{eff}$, $V_{loop}$, $P_{LHCD}$) with sufficient density in all regions of parameter space. The surrogate models reduce the inference time from minutes to ~ms with high accuracy across the input parameter space.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗