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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 1,153 records · Page 64

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NASA NTRS1992

High-order wide-band frequency domain identification using composite curve fitting

A method is presented for curve fitting nonparametric frequency domain data so as to identify a parametric model composed of two models in parallel, where each model has dynamics in a specified portion of the frequency band. This decomposition overcomes the problem of numerical sensitivity since lower order polynomials can be used compared to existing methods which estimate the model as a single entity. Consequently, composite curve fitting is useful for frequency domain identification of high-order systems and/or systems whose dynamics are spread over a large bandwidth. The approach can be extended to identify an arbitrary number of parallel subsystems in specified frequency regimes.

Bayard, D. S.↗

NASA NTRS2000

Relativistically Skewed Iron Emission and Disk Reflection in Galactic Microquasar XTE J1748-288

We report evidence for an Fe K-alpha fluorescence line feature in the Very High, High, and Low state X-ray spectra of the galactic microquasar XTE JI748-288 during its June 1998 outburst. Spectral analyses were made on observations spread across the outburst, gathered with the Rossi X-ray Timing Explorer. Gaussian line. disk emission line, relativistic disk emission line, and disk reflection models are fit to the data. In the Very High State, the line profile is strongly redshifted and consistent with emission from the innermost radius of a maximally rotating Kerr black hole, 1.235 R(sub g). The line profile is less redshifted in the High State, but increasingly prominent. In the Low State, the line profile is very strong and centered af approx. 6.7 keV; disk line emission models constrain the inner edge of the disk to fluctuate between approx.20 and approx.59 R(sub g). We trace the disk reflection fraction across the full outburst of this source, and find well-constrained fractions below those observed in AGN in the Very High and High States, but consistent with other galactic sources in the Low State. We discuss the possible implications for black hole X-ray binary system dynamics and accretion flow geometry.

Miller, J. M.↗

NASA NTRS2020

On Orbit Flight Testing of the Roll-Out Solar Array

The Roll-Out Solar Array (ROSA) is an innovative, lightweight solar array with a flexible substrate that makes use of the stored strain energy in its composite structural members to provide deployment without the use of motors while still packaging efficiently. The ROSA flight experiment was launched to the International Space Station (ISS)on June 3rd, 2017 as a part of the eleventh SpaceX commercial resupply mission. After two weeks of storage, ROSA was extracted from the Dragon spacecraft, deployed, and put through a week of tests to verify its structural characteristics as well as the performance of photovoltaics. The structural dynamics experiments included active excitation of out-of-plane bending modes, and a study of the thermal-structural interaction of the structure during day-night transitions. Data was gathered from a small number of accelerometers located at key points on the solar array and from cameras observing numerous photogrammetry targets spread out over the structure and the photovoltaic blanket. The goal in this effort was to better understand the performance of ROSA and to improve modeling efforts for future designs of similar solar arrays. Of particular interest are the first few system modes and mode shapes of the array, the amount of structural damping present, and degree of structural-thermal interaction seen during eclipse exit.

ROSA↗

NASA NTRS2014

Reducing Uncertainty in Chemistry Climate Model Predictions of Stratospheric Ozone

Chemistry climate models (CCMs) are used to predict the future evolution of stratospheric ozone as ozone-depleting substances decrease and greenhouse gases increase, cooling the stratosphere. CCM predictions exhibit many common features, but also a broad range of values for quantities such as year of ozone-return-to-1980 and global ozone level at the end of the 21st century. Multiple linear regression is applied to each of 14 CCMs to separate ozone response to chlorine change from that due to climate change. We show that the sensitivity of lower atmosphere ozone to chlorine change deltaO3/deltaCly is a near linear function of partitioning of total inorganic chlorine (Cly) into its reservoirs; both Cly and its partitioning are controlled by lower atmospheric transport. CCMs with realistic transport agree with observations for chlorine reservoirs and produce similar ozone responses to chlorine change. After 2035 differences in response to chlorine contribute little to the spread in CCM results as the anthropogenic contribution to Cly becomes unimportant. Differences among upper stratospheric ozone increases due to temperature decreases are explained by differences in ozone sensitivity to temperature change deltaO3/deltaT due to different contributions from various ozone loss processes, each with their own temperature dependence. In the lower atmosphere, tropical ozone decreases caused by a predicted speed-up in the Brewer-Dobson circulation may or may not be balanced by middle and high latitude increases, contributing most to the spread in late 21st century predictions.

chemistry climate models↗

DOE OSTI2023

A combined experimental and crystal plasticity study of grain size effects in magnesium alloys

This work presents a method to incorporate the micro Hall-Petch equation into the crystal plasticity finite element (CPFE) framework accounting for the microstructural features to understand the coupling between grain size, texture, and loading direction in magnesium alloys. The effect of grain size and texture is accounted for by modifying the slip resistances of individual basal and prismatic systems based on the micro Hall-Petch equation. The modification based on the micro Hall-Petch equation endows every slip system at each microstructural point with a slip system-level grain size and maximum compatibility factor, which are in turn used to modify the slip resistance. While the slip-system level grain size is a measure of the grain size, the maximum compatibility factor encodes the effect of the grain boundary on the slip system resistance modification and is computed based on the Luster-Morris factor. The model is calibrated using experimental stress-strain curves of Mg-4Al samples with three different grain sizes from which the Hall-Petch coefficients are extracted and compared with Hall-Petch coefficients predicted using original parameters from previous work. The predictability of the model is then evaluated for a Mg-4Al sample with different texture and three grain sizes subjected to loading in different directions. The calibrated parameters are then used for some parametric studies to investigate the variation of Hall-Petch slope for different degrees of simulated spread in basal texture, variation of Hall-Petch slope with loading direction relative to basal poles for a microstructure with strong basal texture, and variation of yield strength with change in grain morphology. The proposed approach to incorporate the micro Hall-Petch equation into the CPFE framework provides a foundation to quantitatively model more complicated scenarios of coupling between grain size, texture and loading direction in the plasticity of Mg alloys.

Crystal plasticity↗

NASA NTRS2015

Concurrent Flame Growth, Spread and Extinction over Composite Fabric Samples in Low Speed Purely Forced Flow in Microgravity

As a part of the NASA BASS and BASS-II experimental projects aboard the International Space Station, flame growth, spread and extinction over a composite cotton-fiberglass fabric blend (referred to as the SIBAL fabric) were studied in low-speed concurrent forced flows. The tests were conducted in a small flow duct within the Microgravity Science Glovebox. The fuel samples measured 1.2 and 2.2 cm wide and 10 cm long. Ambient oxygen was varied from 21% down to 16% and flow speed from 40 cm/s down to 1 cm/s. A small flame resulted at low flow, enabling us to observe the entire history of flame development including ignition, flame growth, steady spread (in some cases) and decay at the end of the sample. In addition, by decreasing flow velocity during some of the tests, low-speed flame quenching extinction limits were found as a function of oxygen percentage. The quenching speeds were found to be between 1 and 5 cm/s with higher speed in lower oxygen atmosphere. The shape of the quenching boundary supports the prediction by earlier theoretical models. These long duration microgravity experiments provide a rare opportunity for solid fuel combustion since microgravity time in ground-based facilities is generally not sufficient. This is the first time that a low-speed quenching boundary in concurrent spread is determined in a clean and unambiguous manner.

concurrent↗

NASA NTRSDate not supplied

Challenges in Observing, Modeling, and Forecasting the June 2023 Smoke Event Over the Northeast United States

In the first week of May 2023, boreal Canada began an early start to the biomass burning season when fires erupted across Alberta and western Saskatchewan. Smoke entered the troposphere and spread across the United States as biomass burning emissions in Canada quadrupled the prior maximum since the onset of the MODIS satellite record. Adding to the already existing smoke, wildfires ignited in Quebec on June 2, 2023, producing a heavy plume of aerosol over the northeastern part of the continent. Meteorological factors, including an area of low pressure situated, nearly stationary, over Maine, transported the smoke into a densely populated corridor containing the cities of Washington, DC, Baltimore, Philadelphia, and New York City. Air quality alerts became widespread as near-surface levels of fine particulate matter (PM2.5) exceeded harmful levels due the low altitude of the smoke plume. Forecasting the smoke transport and impacts of such events requires a complex combination of observed initial conditions for meteorology and aerosols, knowledge of the emissions from wildfires, and a state-of-the-art Earth System model that couples these components together. Using a case-study perspective with the Goddard Earth Observing System (GEOS), challenges associated with near real time forecasting of the smoke plume are presented. Analyzed and forecasted aerosol optical depth will be evaluated using available satellite and AERONET observations, while surface aerosol will be assessed relative to observations of PM2.5. Lacking real time estimates of biomass burning emissions for inputs to our forecast model, particular attention is given to the use of day-old biomass burning emissions throughout the forecast period covering the first ten days in June 2023, and the resulting reduction in forecast skill will be quantified.

Allison Collow↗

NASA NTRSDate not supplied

Challenges in Observing, Modeling, and Forecasting the June 2023 Smoke Event over the Northeast United States

In the first week of May 2023, boreal Canada began an early start to the biomass burning season when fires erupted across Alberta and western Saskatchewan. Smoke entered the troposphere and spread across the United States as biomass burning emissions in Canada quadrupled the prior maximum since the onset of the MODIS satellite record. Adding to the already existing smoke, wildfires ignited in Quebec on June 2, 2023, producing a heavy plume of aerosol over the northeastern part of the continent. Meteorological factors, including an area of low pressure situated, nearly stationary, over Maine, transported the smoke into a densely populated corridor containing the cities of Washington, DC, Baltimore, Philadelphia, and New York City. Air quality alerts became widespread as near-surface levels of fine particulate matter (PM2.5) exceeded harmful levels due the low altitude of the smoke plume. Forecasting the smoke transport and impacts of such events requires a complex combination of observed initial conditions for meteorology and aerosols, knowledge of the emissions from wildfires, and a state-of-the-art Earth System model that couples these components together. Using a case-study perspective with the Goddard Earth Observing System (GEOS ), challenges associated with near real time forecasting of the smoke plume are presented. Analyzed and forecasted aerosol optical depth will be evaluated using available satellite and AERONET observations, while surface aerosol will be assessed relative to observations of PM2.5. Lacking real time estimates of biomass burning emissions for inputs to our forecast model, particular attention is given to the use of day-old biomass burning emissions throughout the forecast period covering the first ten days in June 2023, and the resulting reduction in forecast skill will be quantified.

Allison Collow↗

DOE OSTI2021

McMillan electron lens in a system with space charge

Space charge (SC) forces of a circulating beam in a ring have both linear (defocusing) and nonlinear components, due to a nonuniform beam distribution. The linear component of SC forces produces a betatron tune shift, which is the largest for a zero-amplitude particle, while the nonlinear component produces an amplitude-dependent betatron tune spread. These SC effects are responsible for several undesirable phenomena in accelerators: emittance growth, particle losses, beam halo, etc. In this paper, we investigate the possibility to mitigate the distributed SC forces by a thin McMillan lens, providing an axially-symmetric kick, which is qualitatively opposite to the accumulated effect of beam's own SC. Experimentally, the proposed concept can be tested in Fermilab's IOTA ring. A thin McMillan lens can be implemented by a short (70) insertion of an electron beam with a specifically chosen density distribution in transverse directions. In this article, to test if McMillan lenses can reduce the tune spread induced by SC, we make several simulations with a 6-D particle tracking code, Synergia. We choose such beam and lattice parameters that the SC tune spread is roughly 0.5 and the emittance growth due to the half-integer resonance is clearly observed without the SC compensation. Then, we focus on reducing the emittance growth by adjusting the bare betatron tunes using the ring quadrupoles, and reducing the tune spread by the McMillan lenses. The results of reducing a large tune spread (≈ 0.5), reported here, are not perfect, but substantial. There is still room for further investigation. The simulations performed so far in this work indicate that McMillan lenses can cope with an SC tune spread of ≈ 0.1 per lens.

43 PARTICLE ACCELERATORS↗

NASA NTRS2011

Climate Change, Extreme Weather Events, and Fungal Disease Emergence and Spread

Empirical evidence from multiple sources show the Earth has been warming since the late 19th century. More recently, evidence for this warming trend is strongly supported by satellite data since the late 1970s from the cryosphere, atmosphere, oceans, and land that confirms increasing temperature trends and their consequences (e.g., reduced Arctic sea ice, rising sea level, ice sheet mass loss, etc.). At the same time, satellite observations of the Sun show remarkably stable solar cycles since the late 1970s, when direct observations of the Sun's total solar irradiance began. Numerical simulation models, driven in part by assimilated satellite data, suggest that future-warming trends will lead to not only a warmer planet, but also a wetter and drier climate depending upon location in a fashion consistent with large-scale atmospheric processes. Continued global warming poses new opportunities for the emergence and spread of fungal disease, as climate systems change at regional and global scales, and as animal and plant species move into new niches. Our contribution to this proceedings is organized thus: First, we review empirical evidence for a warming Earth. Second, we show the Sun is not responsible for the observed warming. Third, we review numerical simulation modeling results that project these trends into the future, describing the projected abiotic environment of our planet in the next 40 to 50 years. Fourth, we illustrate how Rift Valley fever outbreaks have been linked to climate, enabling a better understanding of the dynamics of these diseases, and how this has led to the development of an operational predictive outbreak model for this disease in Africa. Fifth, We project how this experience may be applicable to predicting outbreaks of fungal pathogens in a warming world. Lastly, we describe an example of changing species ranges due to climate change, resulting from recent warming in the Andes and associated glacier melt that has enabled amphibians to colonize higher elevation lakes, only to be followed shortly by the emergence of fungal disease in the new habitats.

Tucker, Compton J.↗

DOE OSTI2025

Modeling inter‐reader variability in clinical target volume delineation for soft tissue sarcomas using diffusion model

Abstract Background Accurate delineation of the clinical target volume (CTV) is essential in the radiotherapy treatment of soft tissue sarcomas. However, this process is subject to inter‐reader variability due to the need for clinical assessment of risk and extent of potential microscopic spread. This can lead to inconsistencies in treatment planning, potentially impacting treatment outcomes. Most existing automatic CTV delineation methods do not account for this variability and can only generate a single CTV for each case. Purpose This study aims to develop a deep learning‐based technique to generate multiple CTV contours for each case, simulating the inter‐reader variability in the clinical practice. Methods We employed a publicly available dataset consisting of fluorodeoxyglucose positron emission tomography (FDG‐PET), x‐ray computed tomography (CT), and pre‐contrast T1‐weighted magnetic resonance imaging (MRI) scans from 51 patients with soft tissue sarcoma, along with an independent validation set containing five additional patients. An experienced reader drew a contour of the gross tumor volume (GTV) for each patient based on multi‐modality images. Subsequently, two additional readers, together with the first one, were responsible for contouring three CTVs in total based on the GTV. We developed a diffusion model‐based deep learning method that is capable of generating arbitrary number of different and plausible CTVs to mimic the inter‐reader variability in CTV delineation. The proposed model incorporates a separate encoder to extract features from the GTV masks, leveraging the critical role of GTV information in accurate CTV delineation. Results The proposed diffusion model demonstrated superior performance with the highest Dice Index (0.902 compared to values below 0.881 for state‐of‐the‐art models) and the best generalized energy distance (GED) (0.209 compared to values exceeding 0.221 for state‐of‐the‐art models). It also achieved the second‐highest recall and precision metrics among the compared ambiguous image segmentation models. Results from both datasets exhibited consistent trends, reinforcing the reliability of our findings. Additionally, ablation studies exploring different model structures and input configurations highlighted the significance of incorporating prior GTV information for accurate CTV delineation. Conclusions The proposed diffusion model successfully generates multiple plausible CTV contours for soft tissue sarcomas, effectively capturing inter‐reader variability in CTV delineation.

Dong, Yafei [Yale Biomedical Imaging Institute Yal↗

NASA NTRS2018

GEOS-CF Model Assessment of PM2.5 During Wildfires: Inferring the Impact of PM2.5 Exposure on Adverse Respiratory & Cardiovascular Conditions

Exposure to fine particulate matter (PM2.5) can aggravate pre-existing respiratory and cardiovascular conditions. When PM2.5 is inhaled it can cause damage to the lungs such as reduced lung function and shortness of breath. After being inhaled PM2.5 can enter the bloodstream and cause harm to the heart. One major natural source of PM2.5 exposure is from wildfire smoke. The particulates within the smoke from the wildfires can spread from the initial source region, potentially impacting communities both near and far. During and after wildfire events, PM2.5 levels can exceed the WHO air quality guidelines (10 gm^3 annual mean; 25 gm^3 daily mean), becoming hazardous to an individual's health. Global models can be used to simulate the emission and transport of these particulates and subsequently they can be valuable to air quality forecasting in highly polluted areas. The NASA Goddard Earth Observing System (GEOS) version 5 Composition Forecast (GEOS-CF) system has been used to produce near-real time air quality forecasts of atmospheric composition at a high global resolution of 25 km. The GEOS-CF system utilizes the GEOS weather forecast model coupled with GEOS-Chem (version 11) chemistry module to provide analyses and forecasts of various toxic air pollutants, including PM2.5. The GEOS-CF simulated high levels of PM2.5 (40 gm^3 to 250 gm^3 ), exceeding the WHO guidelines, during multiple recent regional and global wildfire seasons, including the 2017 Seattle, WA and Los Angeles, CA wildfire seasons, and biomass burning events in India. Furthermore, the GEOS-CF simulated PM2.5 applied to a human health assessment model, BenMAP (The Environmental Benefits Mapping and Analysis Program, version 1.3), estimates the impact on adverse respiratory health conditions due to PM2.5 exposure from wildfires. The GEOS-CF predicted PM2.5 during the wildfire season with the corresponding BenMAP results provides an assessment of the human health impact of PM2.5 exposure.

Saunders, Emily↗

DOE OSTI2023

Particle-in-cell modeling of electron beam generated plasma

Plasmas generated using energetic electron beams are well known for their low electron temperature (T e ) and plasma potential, which makes them attractive for atomic-precision plasma processing applications such as atomic layer etch and deposition. A 2-dimensional particle-in-cell model for an electron beam-generated plasma in argon confined by a constant applied magnetic field is described here in this article. Plasma production primarily occurs in the path of the beam electrons in the center of the chamber. The resulting plasma spreads out in the chamber through non-ambipolar diffusion with a short-circuiting effect allowing unequal electron and ion fluxes to different regions of the bounding conductive chamber walls. The cross-field transport of the electrons (and thus the steady-state characteristics of the plasma) are strongly impacted by the magnetic field. T e is anisotropic in the electron beam region, but low and isotropic away from the plasma production zone. The plasma density increases and the plasma becomes more confined near the region of production when the magnetic field strengthens. The magnetic field reduces both electron physical and energy transport perpendicular to the magnetic field. T e is uniform along the magnetic field lines and slowly decreases perpendicular to it. Electrons are less energetic in the sheath regions where the sheath electric field repels and confines the low-energy electrons from the bulk plasma. Even though electron and ion densities are similar in the bulk plasma due to quasi-neutrality, electron and ion fluxes on the grounded chamber walls are unequal at most locations. Electron confinement by the magnetic field weakens with increasing pressure, and the plasma spread out farther from the electron beam region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1984

The p-wave upper mantle structure beneath an active spreading centre - The Gulf of California

Over 1400 seismograms of earthquakes in Mexico are analyzed and data sets for the travel time, apparent phase velocity, and relative amplitude information are utilized to produce a tightly constrained, detailed model for depths to 900 km beneath an active oceanic ridge region, the Gulf of California. The data are combined by first inverting the travel times, perturbing that model to fit the p-delta data, and then performing trial and error synthetic seismogram modelling to fit the short-period waveforms. The final model satisfies all three data sets. The ridge model is similar to existing upper mantle models for shield, tectonic-continental, and arc-trench regimes below 400 km, but differs significantly in the upper 350 km. Ridge model velocities are very low in this depth range; the model 'catches up' with the others with a very large velocity gradient from 225 to 390 km.

Walck, M. C.↗

NASA NTRS2009

Hybrid Reynolds-Averaged/Large-Eddy Simulations of a Co-Axial Supersonic Free-Jet Experiment

Reynolds-averaged and hybrid Reynolds-averaged/large-eddy simulations have been applied to a supersonic coaxial jet flow experiment. The experiment utilized either helium or argon as the inner jet nozzle fluid, and the outer jet nozzle fluid consisted of laboratory air. The inner and outer nozzles were designed and operated to produce nearly pressure-matched Mach 1.8 flow conditions at the jet exit. The purpose of the computational effort was to assess the state-of-the-art for each modeling approach, and to use the hybrid Reynolds-averaged/large-eddy simulations to gather insight into the deficiencies of the Reynolds-averaged closure models. The Reynolds-averaged simulations displayed a strong sensitivity to choice of turbulent Schmidt number. The baseline value chosen for this parameter resulted in an over-prediction of the mixing layer spreading rate for the helium case, but the opposite trend was noted when argon was used as the injectant. A larger turbulent Schmidt number greatly improved the comparison of the results with measurements for the helium simulations, but variations in the Schmidt number did not improve the argon comparisons. The hybrid simulation results showed the same trends as the baseline Reynolds-averaged predictions. The primary reason conjectured for the discrepancy between the hybrid simulation results and the measurements centered around issues related to the transition from a Reynolds-averaged state to one with resolved turbulent content. Improvements to the inflow conditions are suggested as a remedy to this dilemma. Comparisons between resolved second-order turbulence statistics and their modeled Reynolds-averaged counterparts were also performed.

Baurle, R. A.↗

DOE OSTI2025

Development and validation of non-axisymmetric heat flux simulations with 3D fields using the HEAT code

A new comprehensive module to simulate heat fluxes from three-dimensional (3D) magnetic fields has been implemented in the HEAT code. Especially compact tokamaks like SPARC require tools to predict and manage large heat fluxes. Existing release versions of HEAT can only simulate axisymmetric heat flux on 3D plasma facing components. The new module uses an M3D-C1 perturbed equilibrium and the MAFOT code to trace field lines of the perturbed 3D magnetic field. Heat flux is then assigned to the resulting footprints via a 3D layer model. The model distinguishes between the scrape-off layer, the magnetic lobes and the private flux region, and employs only 0D parameters like the layer width, diffusive spread and the last closed flux surface position in the perturbed edge to generate a heat flux profile. The magnitude is normalized to the total input power. Resulting heat flux simulations are compared and validated against infrared measurements in the DIII-D tokamak with applied 3D fields; good agreement is found for several cases. The new module can now be applied to the SPARC tokamak; a preliminary result for applied rotating 3D fields is shown.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1974

Investigation of the starting transients of high performance solid-propellant motors

The starting transients of solid propellant engines were investigated to develop design principles for predicting transients in high performance igniter and engine configurations. Research and diagnosis were conducted on the processes affecting ignition transients, such as heat flux, igniter, flame spreading over the surface, and nonsteady combustion gas dynamics. Abstracts of published reports related to this research are presented. Topics discussed include: development of an analytical model, analytical prediction of the entire ignition transient, transient behavior of pressure and regression rate during reignition after shut-down, and problems associated with restarting hybrid rocket engines.

Summerfield, M.↗

NASA NTRS1980

Assessment of space sensors for ocean pollution monitoring

Several passive and active microwave, as well as passive optical remote sensors, applicable to the monitoring of oil spills and waste discharges at sea, are considered. The discussed types of measurements relate to: (1) spatial distribution and properties of the pollutant, and (2) oceanic parameters needed to predict the movement of the pollutants and their impact upon land. The sensors, operating from satellite platforms at 700-900 km altitudes, are found to be useful in mapping the spread of oil in major oil spills and in addition, can be effective in producing wind and ocean parameters as inputs to oil trajectory and dispersion models. These capabilities can be used in countermeasures.

Alvarado, U. R.↗