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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

What controls the interannual variation of Hadley cell extent in the Northern Hemisphere: physical mechanism and empirical model for edge variation

Abstract The Hadley circulation is the most prominent atmospheric meridional circulation, reducing the radiatively driven equator-to-pole temperature gradient. While the Hadley cell extent varies by several degrees from year to year, the detailed dynamical mechanisms behind such variations have not been well elucidated. During the expanded phase of the Hadley cell, many regions on the periphery of the subtropics experience unfavorable climatic conditions. In this study, using ERA5 reanalysis data, we examine the physical chain of events responsible for the interannual variation of the Hadley cell edge (HCE) latitude in the Northern Hemisphere. This variation is mainly caused by changing eddy activity and wave breaking from both stationary and transient waves. In particular, we show that transient waves cause the HCE to shift poleward by increasing the eddy momentum flux divergence (EMFD) and reducing the baroclinicity over 20°–40°N, shifting the region of peak baroclinicity poleward. El Niño/La Niña and the Arctic Oscillation (AO) account for a significant portion (60%) of the interannual fluctuation of the HCE latitude. Through the poleward displacement of eddy activity, La Niña and a positive AO state are associated with the poleward shift of the HCE. The analysis of 28 CMIP5 models reveals statistical relationships between EMFD, vertical shear, and HCE latitude similar to those observed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A Thermal Model for the Performance Analysis of Large Scale Spent Fuel Cooling Pond - 19173

This paper presents a thermal model for the performance analysis of a large scale cooling pond for the long term storage of spent nuclear fuel. The model has been developed using the knowledge gained from fundamental investigation using CFD and has been validated by comparing against reliable experimental and/or numerical data. It was then applied in the context of operation of a large scale pond to ascertain the sensitivity of various operational and environmental conditions. To develop the model, the water body along with the heating elements was considered as one zone and humid air inside the building as another zone, both of which are considered as well-mixed zones. Various input conditions namely, total heat load from the heat source, environmental temperature and relative humidity, ventilation rate, efficiency of the cooling tower, recirculation and make-up water flow rates have been programmed in the model. The statistical method AVONA has been used to assess the influence of the above variables. The results reveal that the efficiency of the cooling tower is the most influential parameter on the cooling performance of cooling pond within the considered values of heat load. It has also been found that the majority of the heat is taken by the recirculating water for very high heat load while the other modes of heat transfer are small but not insignificant. The model is capable of simulating the scenario of loss of cooling water and suggests that it can be used for managing a large pond efficiently as well as recovery from an accident situation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1983

A stochastic-dynamic model for the spatial structure of forecast error statistics

The present investigation is concerned with the presentation of a simplified model of the spatial structure of forecast error statistics, a comparison of the model with actual numerical weather prediction results, and the extent to which simplifying assumptions made in the model are justified. A stochastic-dynamic model is derived for the spatial structure of the global atmospheric mass-field forecast error. The model states that the relative potential vorticity of the forecast error is random. The covariance function of the model's solutions is found to be governed by a simple deterministic equation. The agreement between the stochastic model and actual mass-field forecast errors fields for 12-36 h periods validates the assumptions on which the model is derived. Within this period, the difference between the potential voriticity fields of the atmosphere and of the numerical forecasts used in the comparison is well represented by white noise.

Balgovind, R.↗
DOE OSTI2021

Aerosol emissions from water-lean solvents for post-combustion CO 2 capture

Advanced water-lean solvents (WLS) for post-combustion CO 2 capture have been gaining interest due to their ability to reduce the parasitic penalty from energy needed for solvent regeneration. Commercial implementation of these novel CO 2 capture technologies hinges on successful control of amine emissions. RTI conducted a parametric study of fundamental and operational variables influence on overall amine aerosol and vapor emissions from our water-lean solvent eCO 2 Sol™ using our 6-kW equivalent bench-scale gas absorption system. The parametric testing used a simulated flue gas with 15 % CO 2 , 2.3–4.2 % H 2 O, and 0–6 ppm sulfite (SO 3 ) to examine the impact of the presence of aerosols to the capture performance and amine emissions from the system. The SO 3 reacts with water in the flue gas to create H 2 SO 4 , which forms liquid aerosol droplets and provide nucleation sites for growth of aerosols. Scanning Mobility Particle Sizer and Aerodynamic Particle Sizer instruments monitored the aerosol particle size distribution. Parametric testing results suggested that the presence of the aerosols in the flue gas could increase the overall amine emissions by 10X compared to the baseline emissions from WLS’s vapor pressure. Principal component analysis (PCA) and projection to latent squares (PLS) developed models to predict the aerosol-based amine emissions from process data. The predictive PLS model had a correlation coefficient (Q 2 ) of 0.92 and could predict the aerosol-based emissions from the NAS process with ±15 % accuracy (average absolute deviation, AAD). The PLS regression model also identified key variables affecting aerosol-based emissions from WLS.

42 ENGINEERING↗
DOE OSTI2020

Probabilistic Solar Power Forecasting Using Bayesian Model Averaging

There is rising interest in probabilistic forecasting to mitigate risks from solar power uncertainty, but the numerical weather prediction (NWP) ensembles readily available to system operators are often biased and underdispersed. We propose a Bayesian model averaging (BMA) post-processing method suitable for forecasting power from utility-scale photovoltaic (PV) plants at multiple time horizons up to at least the day-ahead timescale. BMA is a kernel dressing technique for NWP ensembles in which the forecast is a weighted sum of member-specific probability density functions. We tailor BMA for utility-scale PV forecasting by modeling power clipping at the AC inverter rating and advance the theory of BMA with a new beta kernel parameterization that accommodates theoretical constraints not previously addressed. BMA is demonstrated for a case study of 11 utility-scale PV plants in Texas, forecasting at hourly resolution for the complete year 2018. BMA's mixture-model approach mitigates underdispersion of the raw ensemble to significantly improve forecast calibration, while consistently outperforming an ensemble model output statistics (EMOS) parametric approach from the literature. At 4-hour lead time, the BMA post-processing achieves continuous ranked probability skill scores of 2--36% over the raw ensemble, with consistent performance at multiple lead times suitable for power system operations.

14 SOLAR ENERGY↗
NASA NTRS1994

Statistical mechanics in biology: how ubiquitous are long-range correlations?

The purpose of this opening talk is to describe examples of recent progress in applying statistical mechanics to biological systems. We first briefly review several biological systems, and then focus on the fractal features characterized by the long-range correlations found recently in DNA sequences containing non-coding material. We discuss the evidence supporting the finding that for sequences containing only coding regions, there are no long-range correlations. We also discuss the recent finding that the exponent alpha characterizing the long-range correlations increases with evolution, and we discuss two related models, the insertion model and the insertion-deletion model, that may account for the presence of long-range correlations. Finally, we summarize the analysis of long-term data on human heartbeats (up to 10(4) heart beats) that supports the possibility that the successive increments in the cardiac beat-to-beat intervals of healthy subjects display scale-invariant, long-range "anti-correlations" (a tendency to beat faster is balanced by a tendency to beat slower later on). In contrast, for a group of subjects with severe heart disease, long-range correlations vanish. This finding suggests that the classical theory of homeostasis, according to which stable physiological processes seek to maintain "constancy," should be extended to account for this type of dynamical, far from equilibrium, behavior.

Non-NASA Center↗
DOE OSTI2024

Optimizing Prediction Error for Time-dependent Solar Radiation Modeling

Numerical weather forecasting models and statistical methods have found wide use to help power companies estimate renewable output, but better methods are needed, particularly for extended forecasts. Machine learning approaches have been used here as well, but so far a major limitation is the ability to also predict the corresponding uncertainty in a forecast. Here we show that both can be done and demonstrate this using a long-term-short memory neural network where the difference between predicted and ground truth data are used to train a model for the corresponding forecast uncertainties.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

FACETS Dynamical Downscaling Simulations over North America by the CAM-MPAS Variable-Resolution Model

Comprehensive assessment of climate datasets created by statistical or dynamical models is important for effectively communicating model projection and associated uncertainty to stakeholders and decision-makers. The Department of Energy FACETS project aims to foster such communication through development of metrics and their demonstration on a hierarchy of downscaled climate datasets to quantify aspects of climate change projections that are credible, particularly for supporting decisions related to the energy-water-land nexus. As a part of this effort, we have produced a regional climate dataset using the Model for Prediction Across Scales coupled to the Community Atmosphere Model (CAM-MPAS). This global modeling framework is configured with variable-resolution meshes featuring higher resolutions over North America, as well as quasi-uniform resolution meshes across the globe. The variable-resolution configurations allow fine-scale features to be better resolved inside the refinement and interact with global-scale circulations. The dataset includes multiple uniform- (240km and 120km) and variable-resolution (200-50km, 100-25km, and 46-12km) simulations that are designed to be compatible with other regional climate simulations that contribute to the hierarchy of downscaled climate datasets of the project. Furthermore, the dataset consists of simulations for both the present-day (1989-2010) and future (2079-2100) climate and post-processing of the model output has been coordinated across the project for consistency to facilitate common analysis across the hierarchy of datasets. Altogether, this CAM-MPAS model dataset provides a unique opportunity to assess the influence of resolutions and modeling framework on model credibility and climate change projection.

Sakaguchi, Koichi↗
DOE OSTI2023

$\Sigma (1385)^{\pm }$ resonance production in Pb–Pb collisions at $\sqrt{s_{\textrm{NN}}} = 5.02$ TeV

Hadronic resonances are used to probe the hadron gas produced in the late stage of heavy-ion collisions since they decay on the same timescale, of the order of 1–10 fm/c, as the decoupling time of the system. In the hadron gas, (pseudo)elastic scatterings among the products of resonances that decayed before the kinetic freeze-out and regeneration processes counteract each other, the net effect depending on the resonance lifetime, the duration of the hadronic phase, and the hadronic cross sections at play. In this context, the Σ(1385) ± particle is of particular interest as models predict that regeneration dominates over rescattering despite its relatively short lifetime of about 5.5 fm/c. The first measurement of the Σ(1385) ± resonance production at midrapidity in Pb–Pb collisions at $\sqrt{s_{NN}}$=5.02 TeV with the ALICE detector is presented in this Letter. The resonances are reconstructed via their hadronic decay channel, Λπ, as a function of the transverse momentum (p T ) and the collision centrality. The results are discussed in comparison with the measured yield of pions and with expectations from the statistical hadronization model as well as commonly employed event generators, including PYTHIA8/Angantyr and EPOS3 coupled to the UrQMD hadronic cascade afterburner. None of the models can describe the data. For Σ(1385) ± , a similar behaviour as K*(892) 0 is observed in data unlike the predictions of EPOS3 with afterburner.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2016

Theory of Alike Selectivity in Biological Channels

We introduce a statistical mechanical model of the selectivity filter that accounts for the interaction between ions within the channel and derive Eisenman equation of the filter selectivity directly from the condition of barrier-less conduction.

alike selectivity↗
NASA NTRSDate not supplied

Evaluation of the Maximum Soluble Water Recovery from Pretreated Urine Brines in Low Earth Orbit

The Urine Processor Assembly (UPA) on the International Space Station recovers water from pretreated urine by thin-film, vacuum compression distillation (VCD). A number of iterative improvements to the distiller assembly (DA) have enabled increases in on-orbit water recovery and improved distillate water quality at on-orbit recoveries up to 87% by volume relative to the volume of pretreated urine. The phosphoric acid-based pretreatment formulation has enabled these higher recoveries on-orbit since May of 2016. Application of simple empirical chemistry models have allowed water recovery of sulfuric-acid pretreated urine from the Russian Orbiting segment to be distilled with phosphoric acid pretreated urine from the U.S. Orbiting Segment. Returned liquid brine from brine filters in the UPA brine loop have enabled empirical measurement of gypsum solubility as a function of recovery, conductivity, or mass density in the real brines of ISS. Calculations of maximum soluble recovery, MSR, are based on preventing the precipitation of gypsum, which is the first mineral to precipitate for both types of pretreated urine. A statistical urine model of urine composition provides an estimate of worst-case urine from a crew of three during one year of operations on ISS. The MSR is defined based on the worst-case concentrations of urinary calcium and urinary sulfate that are pretreated, pooled, and distilled. The potential to increase water recoveries above 87% without gypsum precipitation are evaluated. The potential benefits and costs of the addition of a conductivity sensor or a Coriolis mass flow meter to the brine loop are evaluated.

Dean L Muirhead↗
DOE OSTI2021

Constraining the hadronic spectrum and repulsive interactions in a hadron resonance gas via fluctuations of conserved charges

We simultaneously incorporate two common extensions of the hadron resonance gas model, namely the addition of extra, unconfirmed resonances to the particle list and the excluded volume repulsive interactions. We emphasize the complementary nature of these two extensions and identify combinations of conserved charge susceptibilities that allow to constrain them separately. In particular, ratios of second-order susceptibilities like $\chi_{11}^{BQ}/\chi_2^B$ and $\chi_{11}^{BS}/\chi_2^B$ are sensitive only to the baryon spectrum, while fourth-to-second order ratios like $\chi_4^B/\chi_2^B$, $\chi_{31}^{BS}/\chi_{11}^{BS}$, or $\chi_{31}^{BQ}/\chi_{11}^{BQ}$ are mainly determined by repulsive interactions. Analysis of the available lattice results suggests the presence of both the extra states in the baryon-strangeness sector and the repulsive baryonic interaction, with indications that hyperons have a smaller repulsive core than non-strange baryons. Furthermore, the modified hadron resonance gas model presented here significantly improves the description of lattice QCD susceptibilities at chemical freeze-out and can be used for the analysis of event-by-event fluctuations in heavy-ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1997

Towards Inner Magnetosphere Particle and Field Models

We report on the initial stages of an effort to construct comprehensive empirical models of the plasma and fields in the inner magnetosphere. The models are based not only on archival data (e.g., SCATHA) but also on current spacecraft mission data (e.g., POLAR). In this component of the effort, we incorporate the recently archived data provided by the SCATRA (Spacecraft Charging AT High Altitude) satellite. The SCAT14A satellite was in a near-geostationary orbit and was in operation for more than a decade. In this paper, we focus on the SCATRA plasma and magnetic field data from approximately the first two years of operation. The time-series data are binned according to spatial location and geomagnetic activity. Examples of statistical, empirical models from this initial effort are presented; even the simply-constructed preliminary models reveal such subtle features as the previously reported warm (greater than 100 eV) plasma density enhancement near the magnetic equator.

Spence, H. E.↗
NASA NTRS1994

A statistical equilibrium analysis of interstellar CO toward zeta Ophiuchi as recorded by the Goddard High Resolution Spectrograph

High-resolution and high signal-to-noise ratio echelle observations made by the Goddard High Resolution Spectrograph (GHRS), aboard the Hubble Space Telescope, of molecular (12)C(16)O and (13)C(16)O in the absorbing gas toward zeta Oph are reported. A statistical equilibrium model, incorporating a different way of dealing with the radiation field in the interstellar clouds, is presented. Based upon previous observations, two velocity components of the gas at V(sub LSR) = - 0.79 and 0.39 km/s, corresponding to solar velocity = -14.6 and -13.4 km/s, together with three different sets of velocity dispersions are adopted in our models. The ratios of the computed emergent intensities (I(sub em)) resulting from the emission lines in the lowest transitions (J = 1 goes to 0, 2 goes to 1, 3 goes to 2) of ground state of CO are presented. The ratios for the two velocity components, (I(sub em)(1 goes to 0)(sub 1))/(I(sub em)(1 goes to 0)(sub 2)), and (I(sub em)(2 goes to 1)(sub 1))/I(sub em)(1 goes to 0)(sub 1)) are comparable to the observed corrected antenna temperature ratios. From the solutions to the statistical equilibrium equations including the six lowest rotational transitions of CO and from multiple Voigt profile fits, the observed (12)CO and (13)CO UV abroption features are successfully reproduced. Profile fitting and double cloud curve-of-growth analysis using the GHRS and Copernicus data indicate that the abundance of CO is (1.8 +/- 0.2) x 10(exp 15)/sq cm. The most recently measured wavelength of the (6 goes to 0) (13)CO band by Haridass & Huber (R(0) = 1370.616 A) shows that the tentative (13)CO features in the GHRS data are unquestionably identified. If there is no blending from any other unknown interstellar species, the isotope ratio of (12)CO/(13)CO is approximately 82 +/- 25. This result is close to the terrestrial value of 90 and implies that the CO is not substantially fractionated, and (12)C(16)O experiences little preferential self-shielding through the selective isotopic photodissociation process. This conclusion differs strongly with that of Sheffer et al. Other implications of the results are discussed.

Lyu, Cheng-Hsuan↗
NASA NTRS2015

Sensitivity of Simulated Global Ocean Carbon Flux Estimates to Forcing by Reanalysis Products

Reanalysis products from MERRA, NCEP2, NCEP1, and ECMWF were used to force an established ocean biogeochemical model to estimate air-sea carbon fluxes (FCO2) and partial pressure of carbon dioxide (pCO2) in the global oceans. Global air-sea carbon fluxes and pCO2 were relatively insensitive to the choice of forcing reanalysis. All global FCO2 estimates from the model forced by the four different reanalyses were within 20% of in situ estimates (MERRA and NCEP1 were within 7%), and all models exhibited statistically significant positive correlations with in situ estimates across the 12 major oceanographic basins. Global pCO2 estimates were within 1% of in situ estimates with ECMWF being the outlier at 0.6%. Basin correlations were similar to FCO2. There were, however, substantial departures among basin estimates from the different reanalysis forcings. The high latitudes and tropics had the largest ranges in estimated fluxes among the reanalyses. Regional pCO2 differences among the reanalysis forcings were muted relative to the FCO2 results. No individual reanalysis was uniformly better or worse in the major oceanographic basins. The results provide information on the characterization of uncertainty in ocean carbon models due to choice of reanalysis forcing.

MERRA↗
DOE OSTI2020

Constraining the destruction rate of K 40 in stellar nucleosynthesis through the study of the Ar 40 ( p , n ) K 40 reaction

Background: We present that K 40 plays a significant role in the radiogenic heating of Earth-like exoplanets, which can affect the development of a habitable environment on their surfaces. The initial amount of K 40 in the interior of these planets depends on the composition of the interstellar clouds from which they formed. Within this context, nuclear reactions that regulate the production of K 40 during stellar evolution can play a critical role. Purpose: In this study, we constrain for the first time the astrophysical reaction rate of K 40 ( n , p ) Ar 40 , which is responsible for the destruction of K 40 during stellar nucleosynthesis. We provide to the nuclear physics community high-resolution data on the cross section and angular distribution of the Ar 40 ( p , n ) K 40 reaction. These are important to various applications involving Ar 40 . The associated reaction rate of the Ar 40 ( p , n ) K 40 process addresses a reaction rate gap in the Joint Institute for Nuclear Astrophysics REACLIB database in the region of intermediate-mass isotopes. Methods: We performed differential cross-section measurements on the Ar 40 ( p , n ) K 40 reaction, for six energies in the center-of-mass system between 3.2 and 4.0 MeV and various angles between 0 ° and 135 ° . The experiment took place at the Edwards Accelerator Laboratory at Ohio University using the beam swinger target location and a standard neutron time-of-flight technique. We extracted total and partial cross sections by integrating the double differential cross sections we measured. Results: The total and partial cross sections varied with energy due to the contribution from isobaric analog states and Ericson type fluctuations. The energy-averaged neutron angular distributions were symmetrical relative to 90 ° . Based on the experimental data, local transmission coefficients were extracted and were used to calculate the astrophysical reaction rates of Ar 40 ( p , n ) K 40 and K 40 ( n , p ) Ar 40 reactions. The new rates were found to vary significantly from the theoretical rates in the REACLIB library. We implemented the new rates in network calculations to study nucleosynthesis via the slow neutron capture process, and we found that the produced abundance of K 40 is reduced by up to 10% compared to calculations with the library rates. At the same time, the above result removes a significant portion of the previous theoretical uncertainty on the K 40 yields from stellar evolution calculations. Conclusions: Our results support a destruction rate of K 40 in massive stars via the K 40 ( n , p ) Ar 40 reaction that is larger compared to previous estimates. The rate of K 40 destruction via the K 40 ( n , p ) Ar 40 reaction now has a dramatically reduced uncertainty based on our measurement. Lastly, this result directly affects the predicted stellar yields of K 40 from nucleosynthesis, which is a critical input parameter for the galactic chemical evolution models that are currently employed for the study of significant properties of exoplanets.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Machine-Learning-Based Predictive Modeling of Glass Transition Temperatures: A Case of Polyhydroxyalkanoate Homopolymers and Copolymers

Polyhydroxyalkanoate-based polymers—being ecofriendly, biosynthesizable, and economically viable and possessing a broad range of tunable properties—are currently being actively pursued as promising alternatives for petroleum-based plastics. The vast chemical complexity accessible within this class of polymers gives rise to challenges in the rational discovery of novel polymer chemistries for specific applications. Here, the burgeoning field of polymer informatics addresses this challenge via providing tools and strategies for accelerated property prediction and materials design via surrogate machine-learning models built on reliable past data. In this contribution, we use glass transition temperature T g as an example target property to demonstrate promise of the data-enabled route to accelerated learning of accurate structure–property mappings in PHA-based polymers. Our analysis uses a data set of experimentally measured T g values, polymer molecular weights, and a polydispersity index for PHA-based homo- and copolymers that was carefully assembled from the literature. A fingerprinting scheme that captures key properties based on topology, shape, and charge/polarity of specific chemical units or motifs forming the polymer backbone was devised to numerically represent the polymers. A validated statistical learning model is then developed to allow for a mapping of the polymer fingerprints onto the property space in a physically meaningful and reliable manner. Once developed, the model can not only rapidly predict the property of new PHA polymers but also provide uncertainties underlying the predictions. The model is further combined with an evolutionary-algorithm-based search strategy to efficiently identify multicomponent polymer compositions with a prespecified T g . While the present contribution is focused specifically on T g , the surrogate model development approach put forward here is general and can, in principle, be extended to a range of other properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗