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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 217 records · Page 12

Response of wind shear warning systems to turbulence with implication of nuisance alerts

The objective was to predict the inherent turbulence response characteristics of candidate wind shear warning system concepts and to assess the potential for nuisance alerts. Information on the detection system and associated signal processing, physical and mathematical models, wind shear factor root mean square turbulence response and the standard deviation of the wind shear factor due to turbulence is given in vugraph form.

Bowles, Roland L.↗

Statistical structural analysis of rotor impact ice shedding

The statistical characteristics of impact ice shear strength are analyzed, with emphasis placed on the most probable shear strength and statistical distribution of an ice deposit. Several distribution types are considered: the Weibull, two-parameter Weibull, and exponential distributions, as well as the Gumbell distribution of the smallest extreme and the Gumbell distribution of the largest extreme. It is concluded that the Weibull distribution yields the best results; however, the expected life, shape parameter, and scale parameter should be determined separately for each case of varying wind speed and droplet size. The theoretical predictions of shear stresses in a specific rotating ice shape are compared, and it is noted that when the effects of lift are added to the theoretical model and the interference is calculated with a new mean and standard deviation, the probability of ice shed is computed as 36.64 pct.

Kellacky, C. J.↗

Global analysis of fermion mixing with exotics

The limits are analyzed on deviation of the lepton and quark weak-couplings from their standard model values in a general class of models where the known fermions are allowed to mix with new heavy particles with exotic SU(2) x U(1) quantum number assignments (left-handed singlets or right-handed doublets). These mixings appear in many extensions of the electroweak theory such as models with mirror fermions, E(sub 6) models, etc. The results update previous analyses and improve considerably the existing bounds.

Nardi, Enrico↗

Evaluations of Risks from the Lunar and Mars Radiation Environments

Protecting astronauts from the space radiation environments requires accurate projections of radiation in future space missions. Characterization of the ionizing radiation environment is challenging because the interplanetary plasma and radiation fields are modulated by solar disturbances and the radiation doses received by astronauts in interplanetary space are likewise influenced. The galactic cosmic radiation (GCR) flux for the next solar cycle was estimated as a function of interplanetary deceleration potential, which has been derived from GCR flux and Climax neutron monitor rate measurements over the last 4 decades. For the chaotic nature of solar particle event (SPE) occurrence, the mean frequency of SPE at any given proton fluence threshold during a defined mission duration was obtained from a Poisson process model using proton fluence measurements of SPEs during the past 5 solar cycles (19-23). Analytic energy spectra of 34 historically large SPEs were constructed over broad energy ranges extending to GeV. Using an integrated space radiation model (which includes the transport codes HZETRN [1] and BRYNTRN [2], and the quantum nuclear interaction model QMSFRG[3]), the propagation and interaction properties of the energetic nucleons through various media were predicted. Risk assessment from GCR and SPE was evaluated at the specific organs inside a typical spacecraft using CAM [4] model. The representative risk level at each event size and their standard deviation were obtained from the analysis of 34 SPEs. Risks from different event sizes and their frequency of occurrences in a specified mission period were evaluated for the concern of acute health effects especially during extra-vehicular activities (EVA). The results will be useful for the development of an integrated strategy of optimizing radiation protection on the lunar and Mars missions. Keywords: Space Radiation Environments; Galactic Cosmic Radiation; Solar Particle Event; Radiation Risk; Risk Analysis; Radiation Protection.

Kim, Myung-Hee↗

Modelling TOVS radiances of synoptic systems

Two operational analysis models, produced by ECMWF and NMC, are compared against observed satellite radiances by converting the analyzed variables into synthetic radiances using a radiative transfer model (RTM). Observed TOVS satellite radiances are used as a ground truth, since they are the only source of continuous, synoptic-scale resolution observations available over the data-sparse tropical Pacific Ocean. It is assumed that if the analysis models correctly simulate atmospheric conditions, the observed and modelled radiance fields will have similar patterns and magnitudes. In each of seven TOVS channels examined, the mean temperature difference between the models was small, but the differences between the models and the observations were large. The mean temperature difference within each channel was larger than the standard deviation in most cases. The moisture channels of the RTM were sensitive to changes in moisture content, but none of the channels were significantly affected by changes in temperature. Single-day modelled radiance analyses contain synoptic information similar to the satellite observations. ECMWF is often too noisy, producing features not verified by the satellite; NMC is often too smooth. NMC more closely resembles the TOVS contours. Modelled water vapor channel analyses resemble observed monthly and composited observations well, but do not accurately reproduce the highly-variable single-day fields. ECMWF generally has more accurate gradients. Neither model simulates the tropics well. The water vapor channels, especially channel eleven (weighted at 700 mb), most closely resembled the tropical plume composite described by McGuirk and Ulsh. The only plume evidence found in the thermal or microwave channels, in either the observations or the models, was a composite trough situated in the correct location, extending from the mid-latitudes into the subtropics. This feature was not readily discernable until the definition and mature stages. Additional information besides the modelled temperatures would be required to produce an accurate forecast for the tropics. Model patterns more closely resembled the observations in the quiescent atmosphere, though the magnitudes were not any closer. ECMWF simulates the TOVS quiescent state better than NMC. The moisture channels continue to present the most realistic patterns. The models contained more detail in the tropics than was verified by the satellite observations, apparently trying to force an active ITCZ. Lag correlations showed TOVS to be more persistent than the models. TOVS also showed a smoother lag trend, but all products appeared to have adequate ability to react to changes in the atmosphere over time.

Coe, Thomas Eddy↗

Computer simulation of fibrillation threshold measurements and electrophysiologic testing procedures

A finite element model of cardiac conduction was used to simulate two experimental protocols: 1) fibrillation threshold measurements and 2) clinical electrophysiologic (EP) testing procedures. The model consisted of a cylindrical lattice whose properties were determined by four parameters: element length, conduction velocity, mean refractory period, and standard deviation of refractory periods. Different stimulation patterns were applied to the lattice under a given set of lattice parameter values and the response of the model was observed through a simulated electrocardiogram. The studies confirm that the model can account for observations made in experimental fibrillation threshold measurements and in clinical EP testing protocols.

NASA Discipline Cardiopulmonary↗

An Introduction to the NASA GMAO Coupled Atmosphere-Ocean System - GEOS-S2S Version 3

Recently NASA's Global Modeling and Assimilation Office (GMAO) has developed a new Subseasonal to Seasonal Prediction system Version 3 (GEOS-S2S-3). This upgrade replaces the GEOS-S2S-2 which is NASA's current contribution to the North American Multi-Model Experiment seasonal prediction project (Kirtman et al., 2014). The main improvements for our S2S-3 system include 1) a higher resolution MOM5 (Griffies et al., 2005) ocean model (now 0.25o x 0.25o x 50 layers), 2) an improved atmospheric/ocean interface layer (Akella and Suarez, 2018), and 3) assimilation of a long-track satellite salinity into the ocean model (Hackert et al, 2019). Atmospheric forcing is provided by the NASA MERRA-2 reanalysis (Gelaro et al., 2017). Initialization for the ocean relies on the GMAO ocean reanalysis system which assimilates all available in situ temperature and salinity, satellite sea surface salinity, and sea level using the Local Ensemble Transform Kalman Filter (LETKF) implementation of (Penny et al., 2013) on a 5 day assimilation cycle with 20 fixed ensemble members.In this presentation, we will authenticate our new S2S-3 ocean reanalysis using standard GODAE validation metrics. For example, we will compare gridded fields of mean and standard deviation of the ocean reanalysis versus observed fields. We will show correlation/RMS of model versus observations and temperature and salinity mean profiles for the various basins and latitude bands. Basin-scale volume transports, such as the Atlantic Meridional Overturning Circulation and the Indonesian Throughflow will be validated. Equatorial ocean waves will be compared by decomposing sea level into Kelvin and Rossby components. For each of these metrics, we plan to validate the results and then compare our new S2S-3 against the current production version, S2S-2. Finally, we will compare 9-month seasonal forecasts initialized from these two systems for the tropical Pacific NINO3.4 region over the period 1981-present.

Molod, Andrea↗

Regression Analysis of Top of Descent Location for Idle-thrust Descents

In this paper, multiple regression analysis is used to model the top of descent (TOD) location of user-preferred descent trajectories computed by the flight management system (FMS) on over 1000 commercial flights into Melbourne, Australia. The independent variables cruise altitude, final altitude, cruise Mach, descent speed, wind, and engine type were also recorded or computed post-operations. Both first-order and second-order models are considered, where cross-validation, hypothesis testing, and additional analysis are used to compare models. This identifies the models that should give the smallest errors if used to predict TOD location for new data in the future. A model that is linear in TOD altitude, final altitude, descent speed, and wind gives an estimated standard deviation of 3.9 nmi for TOD location given the trajec- tory parameters, which means about 80% of predictions would have error less than 5 nmi in absolute value. This accuracy is better than demonstrated by other ground automation predictions using kinetic models. Furthermore, this approach would enable online learning of the model. Additional data or further knowl- edge of algorithms is necessary to conclude definitively that no second-order terms are appropriate. Possible applications of the linear model are described, including enabling arriving aircraft to fly optimized descents computed by the FMS even in congested airspace. In particular, a model for TOD location that is linear in the independent variables would enable decision support tool human-machine interfaces for which a kinetic approach would be computationally too slow.

trajectory prediction↗

Benchmarking soil moisture and its relationship to ecohydrologic variables in Earth System Models

Soil moisture (SM) is a key regulator of ecosystem biogeophysics, influencing plant water relations and land-atmosphere energy exchanges. We evaluate the representation of SM in 16 Earth System Models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) using the International Land Model Benchmarking (ILAMB) framework, focusing on surface (0–5, 0–10 cm) and rootzone (0–100 cm) depths, as well as key ecohydrological variables like gross primary productivity (GPP), leaf area index (LAI), and evapotranspiration (ET), and their coupling. Models are benchmarked against multiple observational and assimilated datasets to assess both state variables and cross-variable relationships. Surface SM is generally well represented (r > 0.87), while rootzone SM variability is systematically overestimated (normalized standard deviation > 1). ET shows strong agreement with observations (r > 0.9), whereas GPP and LAI exhibit larger inter-model spread. Skill in individual variables does not guarantee realistic SM–ecohydrology coupling, which varies strongly across models and depends on the reference dataset. Köppen-based regional analyses reveal strong regime dependence, with several models performing well in Tropical and Temperate regions but degrading in Continental (high-latitude) zones. Across both global and regional benchmarks, models cluster by land surface framework, indicating that structural choices in soil hydrology and soil–plant coupling exert a first-order control on performance. These results provide process-relevant benchmarks and suggest that improving the representation of vertical soil structure, rooting depth distributions, and soil–plant hydraulic coupling will be central to advancing soil moisture realism in next-generation Earth system models.

CMIP6↗

Forecasting the Arrival Time of Coronal Mass Ejections: Analysis of the CCMC CME Scoreboard

Accurate forecasting of the properties of coronal mass ejections (CMEs) as they approach Earth is now recognized as an important strategic objective for both NOAA and NASA. The time of arrival of such events is a key parameter, one that had been anticipated to be relatively straightforward to constrain. In this study, we analyze forecasts submitted to the Community Coordinated Modeling Center at NASA's Goddard Space Flight Center over the last 6 years to answer the following questions: (1) How well do these models forecast the arrival time of CME-driven shocks? (2) What are the uncertainties associated with these forecasts? (3) Which model(s) perform best? (4) Have the models become more accurate during the past 6 years? We analyze all forecasts made by 32 models from 2013 through mid-2018, and additionally focus on 28 events, all of which were forecasted by six models. We find that the models are generally able to predict CME-shock arrival times, in an average sense, to within ±10 hr, but with standard deviations often exceeding 20 hr. The best performers, on the other hand, maintained a mean error (bias) of 1 hr, a mean absolute error of 13 hr, and a precision (standard deviation) of 15 hr. Finally, there is no evidence that the forecasts have become more accurate during this interval. We discuss the intrinsic simplifications of thevarious models analyzed, the limitations of this investigation, and suggest possible paths to improve these forecasts in the future.

space weather↗

A comprehensive framework to assess elemental mercury in the Department of Energy: A time series analysis

Objective: This study investigated whether seasonal categories affect airborne mercury concentrations in the U.S. Department of Energy operations. Methods: We conducted an initial assessment of the general variability of airborne elemental mercury time-weighted average (TWA) samples. Then, we performed a two-component time series analysis to determine whether long-term, cyclical temperature change patterns affect mercury concentrations. Results: Both ARIMA time series models demonstrated stationary, non-random means (χ² = 83.8, p < 0.001) and standard deviation (χ² = 55.8, p < 0.001) of mercury concentrations. Here, our results indicate that the seasonal factors did not influence mercury concentration. Conclusions: Our results demonstrate that mercury concentrations primarily emanate from operational activities, work practices, and/or transient environmental conditions rather than seasonal fluctuations.

Cannady, Ryan T. [Oak Ridge National Laboratory (O↗

A general model for the textural evolution of lunar soil

The investigation reported is concerned with the qualitative expansion of an earlier model developed by Lindsay (1971, 1972, 1973). Questions regarding the maturity of lunar soils are examined. A multivariate model related to textural maturity is considered, taking into account mean and standard deviations, the asymmetry of the grain size curve, the kurtosis anomaly, and pyroclastic materials. It is concluded that the mean grain size and the standard deviation of the lunar soil can be used as general indicators of the textural maturity of the soil anywhere on the lunar surface.

Lindsay, J. F.↗

Investigation of environmental change pattern in Japan

The author has identified the following significant results. In the Plains of Tokachi, where the scale of agricultural field was comparatively large in Japan, LANDSAT data with its accuracy have proved to be useful enough to observe the actual condition of agricultural land use and changes more accurately than present methods. Species and ages of grasses in pasture were identified and soils were classified into several types. The actual land cover and ecological environment were remarkably changeable at the rapidly industrialized area by the urbanization in the flat plane and also by the forest works and road construction in the mountainous area. The practical use of the recognition results was proved as the base map of the field survey or the retouching work of the vegetation and land use. There was a 10% cut in cost, labor, and time. Vegetation cover in Tokyo districts was estimated by both the multiregression model and the parametric model. Multicorrelation coefficient between observed value and estimated value was 0.87 and standard deviation was + or - 15%. Vegetation cover in Tokyo was mapped into five levels with equal intervals of 20%.

Maruyasu, T.↗

Ellipsoidal geometry in asteroid thermal models - The standard radiometric model

The major consequences of ellipsoidal geometry in an othewise standard radiometric model for asteroids are explored. It is shown that for small deviations from spherical shape a spherical model of the same projected area gives a reasonable aproximation to the thermal flux from an ellipsoidal body. It is suggested that large departures from spherical shape require that some correction be made for geometry. Systematic differences in the radii of asteroids derived radiometrically at 10 and 20 microns may result partly from nonspherical geometry. It is also suggested that extrapolations of the rotational variation of thermal flux from a nonspherical body based solely on the change in cross-sectional area are in error.

Brown, R. H.↗

Analysis of wind perturbation activity for the NSTS launches

A method for statistical analysis of wind perturbation activity is proposed for application in NSTS prelaunch assessment of the wind environment. Methods for comparing day-of-launch wind perturbation standard deviations with historical data at the launch site are described. A statistical model based on the Gumbel extreme value distribution is developed for the largest vector and component perturbations in a wind profile as a function of high-pass filter cutoff wavelength. Application of the model is proposed for assessing extreme perturbations within prelaunch sequential Jimsphere wind profiles.

Adelfang, Stanley I.↗

Uncertainty Analysis of Decomposing Polyurethane Foam

Sensitivity/uncertainty analyses are necessary to determine where to allocate resources for improved predictions in support of our nation's nuclear safety mission. Yet, sensitivity/uncertainty analyses are not commonly performed on complex combustion models because the calculations are time consuming, CPU intensive, nontrivial exercises that can lead to deceptive results. To illustrate these ideas, a variety of sensitivity/uncertainty analyses were used to determine the uncertainty associated with thermal decomposition of polyurethane foam exposed to high radiative flux boundary conditions. The polyurethane used in this study is a rigid closed-cell foam used as an encapsulant. Related polyurethane binders such as Estane are used in many energetic materials of interest to the JANNAF community. The complex, finite element foam decomposition model used in this study has 25 input parameters that include chemistry, polymer structure, and thermophysical properties. The response variable was selected as the steady-state decomposition front velocity calculated as the derivative of the decomposition front location versus time. An analytical mean value sensitivity/uncertainty (MV) analysis was used to determine the standard deviation by taking numerical derivatives of the response variable with respect to each of the 25 input parameters. Since the response variable is also a derivative, the standard deviation was essentially determined from a second derivative that was extremely sensitive to numerical noise. To minimize the numerical noise, 50-micrometer element dimensions and approximately 1-msec time steps were required to obtain stable uncertainty results. As an alternative method to determine the uncertainty and sensitivity in the decomposition front velocity, surrogate response surfaces were generated for use with a constrained Latin Hypercube Sampling (LHS) technique. Two surrogate response surfaces were investigated: 1) a linear surrogate response surface (LIN) and 2) a quadratic response surface (QUAD). The LHS techniques do not require derivatives of the response variable and are subsequently relatively insensitive to numerical noise. To compare the LIN and QUAD methods to the MV method, a direct LHS analysis (DLHS) was performed using the full grid and timestep resolved finite element model. The surrogate response models (LIN and QUAD) are shown to give acceptable values of the mean and standard deviation when compared to the fully converged DLHS model.

Hobbs, Michael L.↗

Aerosol Absorption in Global Models From AeroCom Phase III

Aerosol-induced absorption of shortwave radiation can modify the climate through local atmospheric heating, which affects lapse rates, precipitation, and cloud formation. Presently, the total amount of aerosol absorption is poorly constrained, and the main absorbing aerosol species (black carbon (BC), organic aerosols (OA), and mineral dust) are diversely quantified in global climate models. As part of the third phase of the Aerosol Comparisons between Observations and Models (AeroCom) intercomparison initiative (AeroCom phase III), we here document the distribution and magnitude of aerosol absorption in current global aerosol models and quantify the sources of intermodel spread, highlighting the difficulties of attributing absorption to different species. In total, 15 models have provided total present-day absorption at 550 nm (using year 2010 emissions), 11 of which have provided absorption per absorbing species. The multi-model global annual mean total absorption aerosol optical depth (AAOD) is 0.0054 (0.0020 to 0.0098; 550 nm), with the range given as the minimum and maximum model values. This is 28 % higher compared to the 0.0042 (0.0021 to 0.0076) multi-model mean in AeroCom phase II (using year 2000 emissions), but the difference is within 1 standard deviation, which, in this study, is 0.0023 (0.0019 in Phase II). Of the summed component AAOD, 60 % (range 36 %–84 %) is estimated to be due to BC, 31 % (12 %–49 %) is due to dust, and 11 % (0 %–24 %) is due to OA; however, the components are not independent in terms of their absorbing efficiency. In models with internal mixtures of absorbing aerosols, a major challenge is the lack of a common and simple method to attribute absorption to the different absorbing species. Therefore, when possible, the models with internally mixed aerosols in the present study have performed simulations using the same method for estimating absorption due to BC, OA, and dust, namely by removing it and comparing runs with and without the absorbing species. We discuss the challenges of attributing absorption to different species; we compare burden, refractive indices, and density; and we contrast models with internal mixing to models with external mixing. The model mean BC mass absorption coefficient (MAC) value is 10.1 (3.1 to 17.7) m 2 g −1 (550 nm), and the model mean BC AAOD is 0.0030 (0.0007 to 0.0077). The difference in lifetime (and burden) in the models explains as much of the BC AAOD spread as the difference in BC MAC values. The difference in the spectral dependency between the models is striking. Several models have an absorption Ångstrøm exponent (AAE) close to 1, which likely is too low given current knowledge of spectral aerosol optical properties. Most models do not account for brown carbon and underestimate the spectral dependency for OA.

Aerosol absorption↗

Quantifying Uncertainties in Modeling Wind Resource Data from Different PBL Schemes in the WRF Model: A Case Study Over the Puerto Rico Region

This study examines the modeling uncertainty of wind resource data stemming from the use of various planetary boundary layer (PBL) parameterizations available in the Weather Research and Forecasting (WRF) model. WRF-based wind simulations spanning 20 years at 3-km resolution using 11 different PBL schemes are used to objectively investigate the uncertainty in modeling wind speed for land-based wind (LBW) and offshore wind (OSW) locations in Puerto Rico. The uncertainty in the wind modeling for the 20-year dataset is quantified using the spread index (SI) and standard deviation (SD). For virtual LBW and OSW sites, the SI and SD values are analyzed as calculated across various spatial and temporal scales. Because the PBL's atmospheric stability conditions can be characterized into two dominant categories, the study focuses on analyzing the SI and SD for daytime (mainly unstable PBL conditions) and nighttime (mainly stable PBL conditions). For wind shear (10 m-200 m) at the OSW and LBW sites, WRF-based numerical experiments indicate the following SI (or SD) ranges: 39%-94% (0.74 m/s-1.44 m/s) during the daytime for OSW, 50%-75% (0.68 m/s-1.19 m/s) during the daytime for LBW, 37%-60% (0.73 m/s-1.12 m/s) during the nighttime for OSW, and 57%-143 % (0.65 m/s-1.43 m/s) during the nighttime for LBW. While a high SI is observed when modeling LBW during the nighttime, there are notable modeling uncertainties during the daytime on the leeward side of the orographic barriers for Puerto Rico.

17 WIND ENERGY↗