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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Persistent Sub-Yearly Chromospheric Variations in Lower Main-Sequence Stars: Tau Booe and alpha Com

The recent discoveries of extrasolar planetary systems around lower main-sequence stars such as tau Booe (HD 120136) has prompted further investigation into their stellar activity. A cursory analysis of tau Booe for cyclic chromospheric activity, based on its 30-yr record of Ca 2 H and K fluxes obtained as part of the HK Project from Mount Wilson Observatory, finds an intermediate, sub-yearly period (approximately 117 d) in chromospheric activity in addition to, and separate from, both its rotation (3.3 d) and long-term variability. As a persistent subyearly period in surface magnetic activity is unprecedented, we investigate this apparent anomaly further by examining chromospheric activity levels of other stars with similar mass, searching for variability in chromospheric activity with periods of less than one year, but longer than measured or predicted rotation. An examination of the time series of 40 mid-to-late F dwarfs yielded one other star for further analysis: alpha Com (HD 114378, P approximately 132 d). The variations for these two stars were checked for persistence and coherence. Based on these determinations, we eliminate the possibilities of rotation, long-term activity cycle, and the evolution of active regions as the cause of this variation in both stars. In particular, for tau Booe we infer that the phenomenon may be chromospheric in origin; however, beyond this, it is difficult to identify anything further regarding the cause of the activity variations, or even whether the observed modulation in the two stars have the same origin.

Maulik, Davesh↗
NASA NTRS1986

Flash spectroscopic studies of the kinetics of the halorhodopsin photocycle

The photoreactions of halorhodopsin are complicated by the fact that the parent pigment and its photoproducts interact with chloride. Thus, in any photoreaction scheme at least four species have to be accounted for: HR565 and HR578 Cl-, as well as HR640 and HR520 Cl-. A photocycle scheme proposed earlier places the two main photointermediates of halorhodopsin, HR520 Cl- and HR640, into a single photocycle, with a chloride-dependent equilibrium between them [Oesterhelt, D., Hegemann, P., & Tittor, J. (1985) EMBO J. 4, 2351-2356]. This scheme, with the additional feature of direct photoproduction of HR640 from HR565, was tested in this work by using numerical solutions of the appropriate differential equations to simulate flash-induced absorption changes at 500 nm (production of HR520 Cl-) and at 660 nm (production of HR640). The time scale of the simulation was ms following the flash. Comparison of the simulated curves with experimental traces yielded a unique set of three rate constants. The proposed photocycle scheme and these rate constants predict well the shapes and amplitudes of flash traces at various chloride concentrations. It appears from the photocycle scheme, and the numerical values of rate constants, that chloride is bound with high affinity to the parent halorhodopsin molecule, but with much lower affinity to its main photointermediate. This may be the consequence of the fact that in the parent halorhodopsin in the retinal configuration is all-trans, but in the two photointermediates it is 13-cis.

Non-NASA Center↗
NASA NTRS1996

A test of the deadline model for speed-accuracy tradeoffs

Two experiments were conducted to evaluate the deadline model for speed-accuracy tradeoffs. According to the deadline model, participants in speeded-response tasks terminate stimulus discrimination as soon as it has run to completion or as soon as a predetermined time deadline has arrived, whichever comes first. Speed is traded for accuracy by varying the time deadlines; short deadlines yield fast but sometimes inaccurate responses, whereas long deadlines allow for slow, accurate responses. A new prediction of this model, based on a comparison of reaction time distributions, was derived and tested in experiments involving the joint manipulation of speed stress and stimulus discriminability. Clear violations of this prediction were observed when participants made relative brightness judgments (Experiment 1) and when they made lexical decisions (Experiment 2), rejecting both the deadline model and the fast-guess model. Several alternative models for speed-accuracy tradeoffs, including random-walk and accumulator models, are compatible with the results.

Discrimination (Psychology)↗
NASA NTRS2013

Does Aspartic Acid Racemization Constrain the Depth Limit of the Subsurface Biosphere?

Previous studies of the subsurface biosphere have deduced average cellular doubling times of hundreds to thousands of years based upon geochemical models. We have directly constrained the in situ average cellular protein turnover or doubling times for metabolically active micro-organisms based on cellular amino acid abundances, D/L values of cellular aspartic acid, and the in vivo aspartic acid racemization rate. Application of this method to planktonic microbial communities collected from deep fractures in South Africa yielded maximum cellular amino acid turnover times of approximately 89 years for 1 km depth and 27 C and 1-2 years for 3 km depth and 54 C. The latter turnover times are much shorter than previously estimated cellular turnover times based upon geochemical arguments. The aspartic acid racemization rate at higher temperatures yields cellular protein doubling times that are consistent with the survival times of hyperthermophilic strains and predicts that at temperatures of 85 C, cells must replace proteins every couple of days to maintain enzymatic activity. Such a high maintenance requirement may be the principal limit on the abundance of living micro-organisms in the deep, hot subsurface biosphere, as well as a potential limit on their activity. The measurement of the D/L of aspartic acid in biological samples is a potentially powerful tool for deep, fractured continental and oceanic crustal settings where geochemical models of carbon turnover times are poorly constrained. Experimental observations on the racemization rates of aspartic acid in living thermophiles and hyperthermophiles could test this hypothesis. The development of corrections for cell wall peptides and spores will be required, however, to improve the accuracy of these estimates for environmental samples.

cellular↗
NASA NTRS2014

Flight Deck Robustness/Conformance Testing with a Surface Management System: An Integrated Pilot-Controller Human-in-the-Loop Surface Operations Simulation

An integrated flight deck and controller human-in-the-loopsimulation was conducted with a total of 120 Dallas-Ft.Worth (DFW) taxi-out operations. In this first integratedPilot-Controller Spot and Runway Departure Advisor(SARDA) simulation, ATC Ground and Local Controllersused the SARDA decision support tool to plan and issuespot release clearances and departure clearances. TheAirport and Terminal Area Simulator (ATAS), a simulatedB737NG piloted, in turn, by 10 commercial transportparticipant pilots, was integrated into the realisticsimulation traffic environment. In the simulation,controllers used SARDA advisories to issue spot release,taxi route, and runway/departure radio voice clearances toall aircraft on the airport surface. Simulation resultsindicated that under a variety of observed pilot/aircraftperformance variations, SARDA yielded controlleradvisories that were: Supportive of current-day time-basedoperations; Compatible with controllers’ expectations;Predictive of actual take-off times; and, Adaptable to offnominalevents. An Information Sharing Display, thatpresented SARDA sequence and timing information on theflight deck, was considered useful for both NextGenoperations and current-day time-based Traffic ManagementInitiative (TMI) operations.

Foyle, David C.↗
NASA NTRS2020

How Satellite Soil Moisture Data Can Help to Monitor the Impacts of Climate Change: SMAP Case Studies

Socially and economically costly extreme weather events have become more prevalent in the last decade. Monitoring and early warning systems could help mitigate the impact of such events by allowing people to better prepare themselves to manage their responses to these events. One significant element of an effective warning system is soil moisture because it is a key determinant of the exchange of water and heat energy between the land and atmosphere, the partitioning of precipitation between infiltration and runoff, and therefore has an influence on weather patterns and streamflow. In addition, soil moisture governs plant water availability – the key to crop yield forecasting. For these reasons, a wide range of organizations use soil moisture information to better predict and monitor climate and weather phenomena such as floods and droughts. By improving soil moisture estimates, it may be possible to improve the monitoring and early warning systems upon which these organizations rely, and hence better mitigate the impacts of extreme weather events. Through case studies, this article discusses several uses of soil moisture data products from NASA’s Soil Moisture Active Passive (SMAP) mission to help improve soil moisture-related monitoring and early warning systems.

Drought monitoring↗
NASA NTRS2020

Modelling climate change impacts on maize yields under low nitrogen input conditions in sub‐Saharan Africa

Smallholder farmers in sub‐Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low‐input systems is currently lacking. We evaluated the impact of varying [CO2], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi‐arid Rwanda, hot subhumid Ghana and hot semi‐arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in‐season soil water content from 2‐year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO2], temperature and rainfall. Without N fertilizer input, maize (i) benefited less from an increase in atmospheric [CO2], (ii) was less affected by higher temperature or decreasing rainfall and (iii) was more affected by increased rainfall because N leaching was more critical. The model inter-comparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low-input systems. Climate change and N input interactions have strong implications for the design of robust adaptation practices across SSA, because the impact of climate change will be modified if farmers intensify maize production with more mineral fertilizer.

Crop simulation model↗
NASA NTRS2020

How Satellite Soil Moisture Data Can Help to Monitor the Impacts of Climate Change: SMAP Case Studies

Socially and economically costly extreme weather events have become more prevalent in the last decade. Monitoring and early warning systems could help mitigate the impact of such events by allowing people to better prepare themselves to manage their responses to these events. One significant element of an effective warning system is soil moisture because it is a key determinant of the exchange of water and heat energy between the land and atmosphere, the partitioning of precipitation between infiltration and runoff, and therefore has an influence on weather patterns and streamflow. In addition, soil moisture governs plant water availability - the key to crop yield forecasting. For these reasons, a wide range of organizations use soil moisture information to better predict and monitor climate and weather phenomena such as floods and droughts. By improving soil moisture estimates, it may be possible to improve the monitoring and early warning systems upon which these organizations rely, and hence better mitigate the impacts of extreme weather events. Through case studies, this article discusses several uses of soil moisture data products from NASA's Soil Moisture Active Passive (SMAP) mission to help improve soil moisture-related monitoring and early warning systems.

agriculture↗
DOE OSTI2025

Delay-resolved spectroscopy in terahertz photonic circuits

Photonic integrated circuits incorporating intersubband transitions are ideal for mid-infrared and terahertz nanophotonics. However, the design of epitaxies has long been inhibited by two factors: the modest predictivity of ab initio theory and the absence of absolute intersubband gain and loss measurements under operating conditions. Existing measurements either yield inaccurate gain profiles or do not accurately assess dependence on frequency, bias, and temperature. Here, we present a delay-resolved absolute-referencing method for accurate gain evaluation without these limitations, addressing a long-standing challenge. By creating a photonic circuit that allows broadband pulses to traverse different lengths of a gain medium, we measure the absolute transmission of intersubband structures. Gain profiles match theoretical predictions at lower temperatures, with gain and dispersion clamping after lasing, and faster-than-expected degradation occurs at higher temperatures. Our approach provides a precise experimental evaluation of temperature-dependent gain performance and gives insight into optimizing temperature performance and frequency comb designs.

Optical spectroscopy↗
NASA NTRS1986

Flared landing approach flying qualities. Volume 2: Appendices

An in-flight research study was conducted utilizing the USAF/Total In-Flight Simulator (TIFS) to investigate longitudinal flying qualities for the flared landing approach phase of flight. A consistent set of data were generated for: determining what kind of command response the pilot prefers/requires in order to flare and land an aircraft with precision, and refining a time history criterion that took into account all the necessary variables and the characteristics that would accurately predict flying qualities. Seven evaluation pilots participated representing NASA Langley, NASA Dryden, Calspan, Boeing, Lockheed, and DFVLR (Braunschweig, Germany). The results of the first part of the study provide guidelines to the flight control system designer, using MIL-F-8785-(C) as a guide, that yield the dynamic behavior pilots prefer in flared landings. The results of the second part provide the flying qualities engineer with a derived flying qualities predictive tool which appears to be highly accurate. This time-domain predictive flying qualities criterion was applied to the flight data as well as six previous flying qualities studies, and the results indicate that the criterion predicted the flying qualities level 81% of the time and the Cooper-Harper pilot rating, within + or - 1%, 60% of the time.

Weingarten, Norman C.↗
NASA NTRS1989

Prediction of fatigue-crack growth in a high-strength aluminum alloy under variable-amplitude loading

The present paper is concerned with the application of an analytical crack-closure model to study crack growth under various load histories. The model was based on a crack-tip plasticity concept like the Dugdale model, but modified to leave plastically deformed material in the wake of the advancing crack tip. The effect of material thickness on plasticity was accounted for by using a constraint factor on tensile yielding at the crack tip. The model was used to correlate crack-growth rates under constant-amplitude loading, and to predict crack growth under variable-amplitude loading on a high-strength aluminum alloy (7475-T7351) sheet material. The experimental data were obtained from Zhang et al. Predicted crack-growth lives agreed well with experimental data. For ten crack-growth tests subjected to various variable-amplitude load histories, the ratio of predicted-to-experimental lives ranged from 0.54 to 1.19. The mean value of the ratio of predicted-to-experimental lives was 0.95 and the standard error was 0.2 using a constraint factor of 1.9 in the model. Crack-opening stresses calculated from the model were significantly different from those determined by Zhang et al. using a striation-based experimental method.

Newman, J. C., Jr.↗
NASA NTRS1991

Organic synthesis in the outer Solar System: Recent laboratory simulations for Titan, the Jovian planets, Triton and comets

We tabulate the most abundant gases and their radiation yields, for two experimental pressures: 0.24 mb, more relevant to upper atmosphere excitation, and 17 mb, more relevant to tropospheric, cosmic ray excitation. The yields computed in the 0.24 mb experiment combined with measured electronic fluxes and a simple, eddy diffusion model of Titan's atmosphere predict abundances of detected molecules in agreement with those found by Voyager and for heavier products, in somewhat better agreement with observation than photochemical absolute reaction rate kinetics models. All Voyager organics are accounted for and no detectable products are found that Voyager did not detect. A striking increase of products with multiple bonds is found with decreasing pressure. Hydrocarbon abundances decline slowly with increasing carbon number. Additionally, we list preliminary estimates for the yield of the heteropolymer, which seems to be produced in a quantity comparable (in moles of C+N consumed) to the total amount of gaseous product. The production rate required to sustain Titan's haze against sedimentation also indicates yields of this order. As can be seen from the table, over 10(exp 9) years substantial amounts of these products can accumulate on the surface -- ranging from cm thickness for the (C+N equals 4) species to a meter or more for HCN and C2H2; we also expect a meter or more of tholins. Similar analyses have been or are being done for the Jovian planets and Triton. Charged particle irradiation of hydrocarbon clathrates or mixed hydrocarbon/water ices produces a range of organic products, reddening and darkening of the ices and characteristic infrared spectra. From such spectra, the predicted emission by fine particles in cometary comae well-matches the observed 3.4 micron emission spectra of Comet Halley and other recent comets. Heliocentric evolution of organic emission features in comets is predicted. Organic products of such ice irradiation may account for colors and albedos on some of the satellites in the outer solar system, especially Triton and Pluto, where solid methane is known to exist.

Sagan, C.↗
DOE OSTI2026

Optimizing resource allocation in Miscanthus breeding via sparse testing designs for genomic prediction

Phenotyping high-biomass perennial crops is laborious and the rate of genetic gain in conventional perennial crop breeding programs is typically low. So, it is especially important to identify methods that produce efficiency gains in the breeding process. Miscanthus is a C4 perennial grass with favorable characteristics for producing biomass as a feedstock for biofuels and diverse bio-based products. Increasing biomass yield will increase profitability and environmental benefits, so it is a key target for Miscanthus breeding. In addition, the identification of well-adapted genotypes across a wide range of environmental conditions requires the establishment of multi-environment trials (METs). Sparse testing is a genomic prediction-based strategy that reduces the phenotyping costs in METs by selecting a subset of genotypes to evaluate in a subset of environments and then predicts the performance of the unobserved genotype-environment combinations. A Miscanthus sacchariflorus (MSA) population comprising 336 genotypes observed across three environments was analyzed implementing sparse testing designs. Three prediction models considering main effects (environments, genotypes, genomic) and interaction effects (genotype-by-environment; G×E interaction) were implemented for forecasting dry biomass yield (YDY), total culm (TCM), average internode length (AIL), and culm node number (CNN). Multiple calibration sets based on different compositions and sizes were considered to evaluate performance in terms of the predictive ability (PA) and the mean square error (MSE) for a fixed testing set size. The training set size ranged from 52 to 112 to predict a fixed set of 224 unobserved genotypes across all three environments. The results showed that the model accounting for G×E interaction consistently presented the highest PA and the lowest MSE: for CNN (PA: ~0.77, MSE: ~0.5) and YDY (PA: ~0.70, MSE: ~1.3) while for TCM and AIL these ranged from ~0.28 to 0.41 and ~1.3 to 4.3, respectively. Overall, varying training sets and allocation strategies did not affect PA and MSE, with 52 non-overlapping and 0 overlapping genotypes per environment as the optimal cost-effective allocation framework. This suggests that implementing sparse testing designs could significantly reduce phenotyping costs by fivefold, without compromising PA in breeding programs for perennial crops such as Miscanthus.

Miscanthus sacchariflorus (MSA)↗
NASA NTRS2017

Resolution of Orbit Determination Prediction Instabilities at Titan During Cassini's Solstice Mission

The Cassini spacecraft has been in orbit about Saturn since 2004. Exploration of the Saturn system is driven by gravitational flybys of the moon Titan which alter the spacecraft trajectory. The Cassini Navigation Team receives regular updates to the Saturn satellites ephemeris from JPL's Solar System Dynamics group. The difference between subsequent ephemeris deliveries can be hundreds of meters in the position of Titan at the time of a flyby. Errors in Titan's position propagate downstream to the next flyby through the estimated spacecraft trajectory. Prior to 2013, the Cassini Orbit Determination Team estimated the Saturn satellite ephemeris parameters and used the a posteriori states and covariance of an operations arc as a priori inputs to subsequent estimation arcs. Since 2013, the OD Team has only been considering errors in the ephemeris and not estimating a correction to the satellite positions. The T119 Titan flyby exhibited a 3D miss distance of 2.44 km and the following T120 flyby yielded a smaller miss of 1.06 km at the 2.9s error level. These discrepancies between pre-flyby prediction and post-flyby trajectory reconstruction were due to errors in the Titan ephemeris. In order to improve the targeting of Titan in future flybys, the team restarted the satellite ephemeris estimation process for orbit determination solutions. Subsequent flybys had target misses of less than 1 km at the sub-3 error level. This paper describes the method of scaling the a priori satellite ephemeris covariance in the orbit determination process to allow larger corrections to the satellite system and improve the prediction of the spacecraft’s Titan-relative position at the time of encounters.

Boone, Dylan↗
DOE OSTI2023

Predictive models of long COVID

Background: The cause and symptoms of long COVID are poorly understood. It is challenging to predict whether a given COVID-19 patient will develop long COVID in the future. Methods: We used electronic health record (EHR) data from the National COVID Cohort Collaborative to predict the incidence of long COVID. We trained two machine learning (ML) models — logistic regression (LR) and random forest (RF). Features used to train predictors included symptoms and drugs ordered during acute infection, measures of COVID-19 treatment, pre-COVID comorbidities, and demographic information. We assigned the ‘long COVID’ label to patients diagnosed with the U09.9 ICD10-CM code. The cohorts included patients with (a) EHRs reported from data partners using U09.9 ICD10-CM code and (b) at least one EHR in each feature category. We analysed three cohorts: all patients (n = 2,190,579; diagnosed with long COVID = 17,036), inpatients (149,319; 3,295), and outpatients (2,041,260; 13,741). Findings: LR and RF models yielded median AUROC of 0.76 and 0.75, respectively. Ablation study revealed that drugs had the highest influence on the prediction task. The SHAP method identified age, gender, cough, fatigue, albuterol, obesity, diabetes, and chronic lung disease as explanatory features. Models trained on data from one N3C partner and tested on data from the other partners had average AUROC of 0.75. Interpretation: ML-based classification using EHR information from the acute infection period is effective in predicting long COVID. SHAP methods identified important features for prediction. Cross-site analysis demonstrated the generalizability of the proposed methodology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

$\overline{\Sigma }^{\pm }$ production in $\text {pp}$ and $\text {p}{-}\text{Pb}$ collisions at $\sqrt{s_{\textrm{NN}}} = 5.02$ TeV with ALICE

The transverse momentum spectra and integrated yields of anti-$Σ$ hyperons ($\overline{\Sigma}^{\pm}$) have been measured in and collisions at $\sqrt{s_{\textrm{NN}}} = 5.02$ TeV with the ALICE experiment. Measurements are performed via the newly accessed decay channel $\overline{\Sigma}^{\pm}$ → $\bar{\textrm{n}}π^±$. A new method of antineutron reconstruction with the PHOS electromagnetic spectrometer is developed and applied to this analysis. The p T spectra of $\overline{\Sigma}^{\pm}$ are measured in the range 0.5 < p T < 3 GeV/c and compared to predictions of the PYTHIA 8, DPMJET, PHOJET, EPOS LHC and EPOS4 models. The EPOS LHC and EPOS4 models provide the best descriptions of the measured spectra both in pp and p-Pb collisions, while models which do not account for multiparton interactions provide a considerably worse description at high p T . The total yields of $\overline{\Sigma }^{\pm }$ in both pp and p-Pb collisions are compared to predictions of the Thermal-FIST model and dynamical models PYTHIA 8, DPMJET, PHOJET, EPOS LHC and EPOS4. All models reproduce the total yields in both colliding systems within uncertainties. The nuclear modification factors R pPb for both $\overline{\Sigma}^{+}$ and $\overline{\Sigma}^{-}$ are evaluated and compared to those of protons, $Λ$ and $Ξ$ hyperons, and predictions of EPOS LHC and EPOS4 models. No deviations of R pPb for $\overline{\Sigma}^{\pm}$ from the model predictions or measurements for other hadrons are found within uncertainties.

Abualrob, I. J. [University of Houston] (ORCID:000↗
DOE OSTI2025

A hybrid surrogate modeling framework for the Digital Twin of a Fluoride-salt-cooled High-temperature Reactor (FHR)

While nuclear energy is a non-greenhouse-gas emitting energy source, expensive operational costs due to the high-level of safety requirements decreases their competitiveness in the sustainable energy market. Advanced reactor concepts paired with Digital Twins aim to increase the commercialization gains of nuclear energy by reducing operational costs, increasing reactor reliability and enhancing power generation. To support Digital Twin tasks such as real-time autonomous control, proactive maintenance monitoring or optimizing power demand operations, a fast and accurate virtual representation of the Nuclear Power Plant (NPP) is required. The computational cost of high-fidelity, physics-based models are unsuitable for real-time analysis or scalability. Here, in this work, a hybrid surrogate modeling framework is developed fora Fluoride-salt-cooled High-temperature Reactor (FHR) that leverages physics-inspired models for key reactor components and uses data-driven methods for rapid system state space prediction. The Xenon reactivity feedback model is integrated to inform the surrogate model about the reactor core and the homologous pump theory model is the basis for representing pump degradation. Using a detailed, two dimensional thermal hydraulics model to generate data on the FHR, we train a network of Vectorized Autoregressive Moving-Average with eXogenous input (VARMAX) models to predict the remaining state values. The result is a surrogate model that provides a detailed reactor state representation of 41 system states and a pump degradation analysis. The framework is applied to Load Follows profiles, yielding high accuracy and a speedup that is more than 4000x faster compared to the higher- fidelity thermal hydraulics model, enabling real-time operational intelligence and applications in long horizon predictions. While the surrogate model framework is demonstrated for the particular case of FHR, the hybrid physical/data-driven modeling approach including the network of surrogates and the underlying modularity has the potential to be applied to other physical asset systems.

Digital Twins↗