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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Variable Polytropic gas cosmology

We mainly study a cosmological scenario represented by the variable Polytropic gas (VPG) unified energy density proposal. To reach this aim, we start with reconstructing a variable form of the original Polytropic gas (OPG) definition. We show that this model is a generalization of the OPG, cosmological constant plus cold dark matter (ΛCDM) and two different Chaplygin gas models. Later, we fit the auxiliary parameters given in the model and discuss essential cosmological features of the VPG proposal. Besides, we compare the VPG with the OPG by focusing on recent observational dataset given in literature including Planck 2018 results. We see that the VPG model yields better results than the OPG description and it fits very well with the recent experimental data. Moreover, we discuss some thermodynamical features of the VPG and conclude that the model describes a thermodynamically stable system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Calculating electronic tunnel currents in networks of disordered irregularly shaped nanoparticles by mapping networks to arrays of parallel nonlinear resistors

We have shown both theoretically and experimentally that tunnel currents in networks of disordered irregularly shaped nanoparticles (NPs) can be calculated by considering the networks as arrays of parallel nonlinear resistors. Each resistor is described by a one-dimensional or a two-dimensional array of equal size nanoparticles that the tunnel junction gaps between nanoparticles in each resistor is assumed to be equal. The number of tunnel junctions between two contact electrodes and the tunnel junction gaps between nanoparticles are found to be functions of Coulomb blockade energies. In addition, the tunnel barriers between nanoparticles were considered to be tilted at high voltages. Furthermore, the role of thermal expansion coefficient of the tunnel junction gaps on the tunnel current is taken into account. The model calculations fit very well to the experimental data of a network of disordered gold nanoparticles, a forest of multi-wall carbon nanotubes, and a network of few-layer graphene nanoplates over a wide temperature range (5-300 K) at low and high DC bias voltages (0.001 mV–50 V). Our investigations indicate, although electron cotunneling in networks of disordered irregularly shaped NPs may occur, non-Arrhenius behavior at low temperatures cannot be described by the cotunneling model due to size distribution in the networks and irregular shape of nanoparticles. Non-Arrhenius behavior of the samples at zero bias voltage limit was attributed to the disorder in the samples. Unlike the electron cotunneling model, we found that the crossover from Arrhenius to non-Arrhenius behavior occurs at two temperatures, one at a high temperature and the other at a low temperature.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

O'Hare Airport roadway traffic prediction via data fusion and Gaussian process regression

This study proposes an approach of leveraging information gathered from multiple traffic data sources at different resolutions to obtain approximate inference on the traffic distribution of Chicago's O'Hare Airport area. Specifically, it proposes the ingestion of traffic datasets at different resolutions to build spatiotemporal models for predicting the distribution of traffic volume on the road network. Due to its good adaptability and flexibility for spatiotemporal data, the Gaussian process (GP) regression was employed to provide short-term forecasts using data collected by loop detectors (sensors) and supplemented by telematics data. The GP regression is used to make predictions of the distribution of the proportion of sensor data traffic volume represented by the telematics data for each location of the sensors. Consequently, the fitted GP model can be used to determine the approximate traffic distribution for a testing location outside of the training points. Policymakers in the transportation sector can find the results of this work helpful for making informed decisions relating to current and future transportation conditions in the area.

42 ENGINEERING↗
DOE OSTI2014

Multi-epoch very long baseline interferometric observations of the nuclear starburst region of NGC 253: Improved modeling of the supernova and star formation rates

The results of multi-epoch observations of the southern starburst galaxy, NGC 253, with the Australian Long Baseline Array at 2.3 GHz are presented. As with previous radio interferometric observations of this galaxy, no new sources were discovered. By combining the results of this survey with Very Large Array observations at higher frequencies from the literature, spectra were derived and a free-free absorption model was fitted of 20 known sources in NGC 253. The results were found to be consistent with previous studies. The supernova remnant, 5.48-43.3, was imaged with the highest sensitivity and resolution to date, revealing a two-lobed morphology. Comparisons with previous observations of similar resolution give an upper limit of 10{sup 4} km s{sup –1} for the expansion speed of this remnant. We derive a supernova rate of <0.2 yr{sup –1} for the inner 300 pc using a model that improves on previous methods by incorporating an improved radio supernova peak luminosity distribution and by making use of multi-wavelength radio data spanning 21 yr. A star formation rate of SFR(M ≥ 5 M {sub ☉}) < 4.9 M {sub ☉} yr{sup –1} was also estimated using the standard relation between supernova and star formation rates. Our improved estimates of supernova and star formation rates are consistent with studies at other wavelengths. The results of our study point to the possible existence of a small population of undetected supernova remnants, suggesting a low rate of radio supernova production in NGC 253.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Design and Analysis of Multifidelity Finite Element Simulations

Abstract The numerical accuracy of finite element analysis (FEA) depends on the number of finite elements used in the discretization of the space, which can be varied using the mesh size. The larger the number of elements, the more accurate the results are. However, the computational cost increases with the number of elements. In current practice, the experimenter chooses a mesh size that is expected to produce a reasonably accurate result, and for which the computer simulation can be completed in a reasonable amount of time. Improvements to this approach have been proposed using multifidelity modeling by choosing two or three mesh sizes. However, mesh size is a continuous parameter, and therefore, multifidelity simulations can be performed easily by choosing a different value for the mesh size for each of the simulations. In this article, we develop a method to optimally find the mesh sizes for each simulation and satisfy the same time constraints as a single or a double mesh size experiment. A range of different mesh sizes used in the proposed method allows one to fit multifidelity models more reliably and predict the outcome when meshes approach infinitesimally small, which is impossible to achieve in actual simulations. We illustrate our approach using an analytical function and a cantilever beam finite element analysis experiment.

Engineering↗
DOE OSTI2024

Geophysical and Environmental Monitoring Data, and Subsurface Flow Modelling Results for Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO

This dataset includes geoelectrical monitoring data acquired between October 2021 and November 2022, soil moisture and temperature data, groundwater data obtained from borehole SNIB covering the period from June 2021 to September 2022, and hydrological modelling results. The data were acquired to investigate how variations in bedrock type and topography, and vegetation cover control subsurface flow dynamics. To provide insights into the subsurface flow dynamics and their controls, a monitoring transect was installed at the Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO, measuring the spatio-temporal variations of soil moisture, soil and snow temperature, subsurface electrical resistivity variations, and groundwater dynamics. Field data are organized in a folder structure, with Electrical Resistivity Tomography (ERT) data being provided as one file per measurement, and data of the soil moisture and temperature sensors being provided as text files covering the entire monitoring period. The ‘Locations.csv’ file contains the location of all sensors, given in NAD83 – UTM Zone 13N. ERT monitoring data has been processed to filter data based on reciprocal errors (data with errors > 30% were removed), a linear error model was fitted to each survey, and to ensure a constant set of measurements for time-lapse inversion, filtered data were interpolated and assigned a 100% measurement error. Soil moisture and temperature data were acquired at 15 min intervals, and averaged to provide 1h data. Weather data and borehole data (groundwater depth, conductivity and temperature) were acquired at 30 min intervals, and are provided as daily measurements; all measurements are averaged, except of precipitation values, which are given as daily accumulation. The hydrological model was set up along the ERT monitoring transect, and net infiltration was used as surface boundary condition and derived from the weather data. Four different results are provided, (1) results for a parameterization using hydraulic permeability and porosity as derived from the ERT data through petrophysical relationships, and (2) three simplified model results, using 1 to 3 geological layers above the bedrock. Modelling was performed using PFLOTRAN, and for each model the PFLOTRAN input files are provided. The result files include weekly hydrological modelling results (e.g., saturation, velocities, pressures), as well as the model parameterization. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Learning electric vehicle driver range anxiety with an initial state of charge-oriented gradient boosting approach

This manuscript focuses on the modeling of electric vehicle (EV) driver’s range anxiety, a fear that a vehicle does not have sufficient range, or state of charge (SOC) of the battery pack, to reach its destination and would strand its occupants. Despite numerous research studies on the modeling of charging behaviors, modeling efforts to understand at what battery percentages do EV drivers charge their vehicles, and what are the associated contributing factors, are rather limited. To this end, an ensemble learning model based on gradient boosting is developed. The model sequentially fits new predictors to new residuals of the previous prediction and, then, minimizes the loss when adding the latest prediction. A total of 18 features are defined and extracted from the multisource data, which cover information on driver, vehicles, stations, traffic conditions, as well as spatial-temporal context information of the charging events. The analyzed dataset includes 4.5-year’s charging event log data from 3,096 users and 468 public charging stations in Kansas City Missouri, and the macroscopic travel demand model maintained by the metropolitan planning organization. Here, the result shows the proposed model achieved a satisfactory result with a R square value of 0.54 and root mean square error of 0.14, both better than multiple linear regression model and random forest model. To reduce range anxiety, it is suggested that the priorities of deploying new charging facilities should be given to the areas with higher daily traffic prediction, with more conservative EV users or that are further from residential areas.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

A dendritic strontium river isoscape for fisheries applications in the Sacramento River basin, California, USA

Objective Understanding the origins and movements of fish is fundamental to effective conservation and fisheries management. Strontium isotope ratios ( 87 Sr/ 86 Sr) in otoliths provide a powerful tracer of natal origin and migratory pathways. However, existing 87 Sr/ 86 Sr isoscapes for the Sacramento River basin, an ecosystem that supports ecologically and economically important salmon populations, rely on discrete classification approaches that overlook unsampled habitats and do not incorporate spatial uncertainty. Our objective was to develop a continuous, network-explicit 87 Sr/ 86 Sr isoscape with quantified uncertainty to fill in data gaps and enable probabilistic assignments of fish origin and movement. Methods We used river water 87 Sr/ 86 Sr data from 106 sites (1997–2021) to develop spatial stream network models that use dendritic connectivity and watershed characteristics (lithology, bedrock age, and land cover) to predict river water 87 Sr/ 86 Sr throughout the basin. Models were fitted using maximum and restricted likelihood and were evaluated via Akaike’s information criterion and leave-one-out cross validation. We produced both historical (pre-dam) and present-day (below-dam) isoscapes, delineated uncertainty-informed isotopic ranges using k -means clustering, and applied a proof-of-concept Bayesian assignment to estimate natal origins and early rearing habitats for two endangered winter-run Chinook Salmon Oncorhynchus tshawytscha. Results Cross validation indicated strong performance of the 87 Sr/ 86 Sr model (leave-one-out cross validation: R 2 = 0.91; root mean square error = 0.0005). Uncertainty-informed clustering identified 19 isotopic “suites” (reaches with indistinguishable 87 Sr/ 86 Sr values) in present-day anadromous habitats and 25 suites in the historical network. Example natal and early rearing assignments included predictions that challenged expectations for juvenile salmon migration based on predicted river 87 Sr/ 86 Sr compositions. Conclusions This study developed a continuous, network-explicit 87 Sr/ 86 Sr isoscape that integrates existing river data to predict 87 Sr/ 86 Sr in unsampled reaches and the likely achievable range and resolution of otolith-based origin and life history inference. The resulting river isoscape provides a valuable tool to predict salmon movements and identify habitats supporting their survival and growth that otherwise might remain undetected. Coupling these predictions with complementary approaches that ground-truth juvenile presence (e.g., targeted fish surveys) represents an important step toward science-informed restoration and management of critical habitats throughout the Sacramento River basin.

Environmental sciences↗
NASA NTRS2010

Probabilistic Assessment of Cancer Risk from Solar Particle Events

For long duration missions outside of the protection of the Earth s magnetic field, space radiation presents significant health risks including cancer mortality. Space radiation consists of solar particle events (SPEs), comprised largely of medium energy protons (less than several hundred MeV); and galactic cosmic ray (GCR), which include high energy protons and heavy ions. While the frequency distribution of SPEs depends strongly upon the phase within the solar activity cycle, the individual SPE occurrences themselves are random in nature. We estimated the probability of SPE occurrence using a non-homogeneous Poisson model to fit the historical database of proton measurements. Distributions of particle fluences of SPEs for a specified mission period were simulated ranging from its 5 th to 95th percentile to assess the cancer risk distribution. Spectral variability of SPEs was also examined, because the detailed energy spectra of protons are important especially at high energy levels for assessing the cancer risk associated with energetic particles for large events. We estimated the overall cumulative probability of GCR environment for a specified mission period using a solar modulation model for the temporal characterization of the GCR environment represented by the deceleration potential (^). Probabilistic assessment of cancer fatal risk was calculated for various periods of lunar and Mars missions. This probabilistic approach to risk assessment from space radiation is in support of mission design and operational planning for future manned space exploration missions. In future work, this probabilistic approach to the space radiation will be combined with a probabilistic approach to the radiobiological factors that contribute to the uncertainties in projecting cancer risks.

Kim, Myung-Hee Y.↗
NASA NTRS2012

Resolving the Origin of the Diffuse Soft X-ray Background

In January 1993, the Diffuse X-ray Spectrometer (DXS) measured the first high-resolution spectrum of the diffuse soft X-ray background between 44-80A. A line-dominated spectrum characteristic of a 10(exp 6)K collisionally ionized plasma' was expected but while the observed spectrum was clearly line-dominated, no model would fit. Then in 2003 the Cosmic Hot Interstellar Plasma Spectrometer (CHIPS) launched and observed the diffuse extreme-ultraviolet (EUV) spectrum between 90- 265A. Although many emission lines were again expected; only Fe IX at 171.1A was detected. The discovery of X-rays from comets led to the realization that heavy ions (Z=6-28) in the solar wind will emit soft X-rays as the ions interact via charge exchange with neutral atoms in the heliosphere and geocorona. Using a new model for solar wind charge exchange (SWCX) emission, we show that the diffuse soft X-ray background can be understood as a combination of emission from charge exchange onto the slow and fast solar wind together with a more distant and diffuse hot (10(exp 6)K) plasma.

Smith, Randall K.↗
DOE OSTI2023

A data-driven method for modelling dissipation rates in stratified turbulence

We present a deep probabilistic convolutional neural network (PCNN) model for predicting local values of small-scale mixing properties in stratified turbulent flows, namely the dissipation rates of turbulent kinetic energy and density variance, $\varepsilon$ and $\chi$ . Inputs to the PCNN are vertical columns of velocity and density gradients, motivated by data typically available from microstructure profilers in the ocean. The architecture is designed to enable the model to capture several characteristic features of stratified turbulence, in particular the dependence of small-scale isotropy on the buoyancy Reynolds number $Re_b:=\varepsilon /(\nu N^2)$ , where $\nu$ is the kinematic viscosity and $N$ is the background buoyancy frequency, the correlation between suitably locally averaged density gradients and turbulence intensity and the importance of capturing the tails of the probability distribution functions of values of dissipation. Empirically modified versions of commonly used isotropic models for $\varepsilon$ and $\chi$ that depend only on vertical derivatives of density and velocity are proposed based on the asymptotic regimes $Re_b\ll 1$ and $Re_b\gg 1$ , and serve as an instructive benchmark for comparison with the data-driven approach. When trained and tested on a simulation of stratified decaying turbulence which accesses a range of turbulent regimes (associated with differing values of $Re_b$ ), the PCNN outperforms assumptions of isotropy significantly as $Re_b$ decreases, and additionally demonstrates improvements over the fitted empirical models. A differential sensitivity analysis of the PCNN facilitates a comparison with the theoretical models and provides a physical interpretation of the features enabling it to make improved predictions.

42 ENGINEERING↗
DOE OSTI2017

Detection of Baryon Acoustic Oscillation features in the large-scale 3-point correlation function of SDSS BOSS DR12 CMASS galaxies

We present the large-scale 3-point correlation function (3PCF) of the SDSS DR12 CMASS sample of 777,202 Luminous Red Galaxies, the largest-ever sample used for a 3PCF or bispectrum measurement. We make the first high-significance (4.5σ) detection of Baryon Acoustic Oscillations (BAO) in the 3PCF. Using these acoustic features in the 3PCF as a standard ruler, we measure the distance to z=0.57 to 1.7% precision (statistical plus systematic). We find D V = 2024 ± 29Mpc (stat) ± 20Mpc(sys) for our fiducial cosmology (consistent with Planck 2015) and bias model. This measurement extends the use of the BAO technique from the 2-point correlation function (2PCF) and power spectrum to the 3PCF and opens an avenue for deriving additional cosmological distance information from future large-scale structure redshift surveys such as DESI. Our measured distance scale from the 3PCF is fairly independent from that derived from the pre-reconstruction 2PCF and is equivalent to increasing the length of BOSS by roughly 10%; reconstruction appears to lower the independence of the distance measurements. In conclusion, fitting a model including tidal tensor bias yields a moderate significance (2.6σ) detection of this bias with a value in agreement with the prediction from local Lagrangian biasing.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1985

Role of long-wavelength degrees of freedom in the rod-to-coil transition in polymers

An analytical model is fitted to experimental data to show that rod-to-coil (RTC) transformations in single strand polymers (SSPs) are close to true phase transitions. The RTC are known to occur when the temperature or pH of a solvent in which the SSP is immersed is varied abruptly. Long wavelength degrees of freedom in the SSPs induce long range interactions in the molecule which lead to a first order phase transition. The Landau formalism suggests that a long-range ordered state can appear at a low temperature. A microscopic model of the phonon degrees of freedom identifies the nonzero temperature threshold at which the phase transition will occur. The phenomenology described is similar to a previous model for transitions in double-strand polymers.

Goldenfeld, N.↗
DOE OSTI2022

Exploring cryo-electron microscopy with molecular dynamics

Single particle analysis cryo-electron microscopy (EM) and molecular dynamics (MD) have been complimentary methods since cryo-EM was first applied to the field of structural biology. The relationship started by biasing structural models to fit low-resolution cryo-EM maps of large macromolecular complexes not amenable to crystallization. The connection between cryo-EM and MD evolved as cryo-EM maps improved in resolution, allowing advanced sampling algorithms to simultaneously refine backbone and sidechains. Moving beyond a single static snapshot, modern inferencing approaches integrate cryo-EM and MD to generate structural ensembles from cryo-EM map data or directly from the particle images themselves. We summarize the recent history of MD innovations in the area of cryo-EM modeling. The merits for the myriad of MD based cryo-EM modeling methods are discussed, as well as, the discoveries that were made possible by the integration of molecular modeling with cryo-EM. Lastly, current challenges and potential opportunities are reviewed.

Biochemistry & Molecular Biology↗
NASA NTRS1998

New Approach to Diagnosing Properties of Protoplanetary Disks

In this paper we suggest that subjecting the observationally derived properties of protoplanetary disks to the evolutionary interpretation yields new insights into the working of those disks, and offers valuable constraints on their models. We propose that the global properties of individual disks, such as their accretion rates and disk masses, sorted by the mass of the central star, can be indexed by the age of the star to simulate the evolution of a single disk. Using data from published surveys of T Tauri stars, we show that accretion rate data, and disk mass data for the lowest mass stars, form well-defined evolutionary tracks. The higher mass stars show a definitive negative correlation between accretion rates and star ages. We use the time-dependent alpha-disk model of the viscous protoplanetary disk to link the theory to observations. The data are consistent with the standard theoretical paradigm, but not with the layered accretion model. The best fits to the data are obtained for the standard models that start with disks that are about one-third of the mass of the central star and have their angular momenta, j, and alpha-coefficients linked by the relationship j varies as Solar mass(exp 3/2)alpha(exp 1/3). The proportionality constant in this relationship, when derived from the accretion rate data, differs from the constant derived from the disk mass data. We argue that the accretion rate data are more reliable. Taking into account typical values of the specific angular momentum of disk-forming matter, we obtain alpha is greater than or equal to 10(exp -2). A complete time-dependent standard disk model, built on the parameters determined from the best-fit procedure, is presented. Such a model constitutes a good point of departure for various theoretical studies aimed at the issue of formation of planetary systems and the character of protoplanetary disks.

Stepinski, Tomasz F.↗
DOE OSTI2026

Linking Community‐Climate Disequilibrium to Ecosystem Function

Turnover in species composition often lags behind the pace of climate change, resulting in mismatches between climate and communities. However, the impact of these community‐climate disequilibria on ecosystem functions is rarely considered, and current methods for measuring disequilibria assume that species ranges were, until recently, in equilibrium with climate. Here, in this work, we develop a simple theoretical model to address both of these problems by linking community‐climate disequilibrium with ecosystem functioning. We show how disequilibrium can impair functioning in the near‐term even when climate change is expected to enhance functioning in the long‐term. Responses are most likely to change over time in communities where turnover is slow, the impact of disequilibrium counteracts the direct effects of climate on ecosystem function, and pre‐existing disequilibrium is large. These findings emphasise the importance of precise and unbiased estimates of community‐climate disequilibria for improving ecological forecasts. By fitting our model to time series of both climate and ecosystem function from a metacommunity simulation, we show the potential for community‐climate disequilibrium to be inferred without direct knowledge about species' distributions or climatic tolerances. We end by outlining a research agenda to apply dynamic disequilibrium concepts and test novel hypotheses across diverse ecosystems.

climate change↗
NASA NTRS2012

Use of MODIS Satellite Data to Evaluate Juniperus spp. Pollen Phenology to Support a Pollen Dispersal Model, PREAM, to Support Public Health Allergy Alerts

Juniperus spp. pollen is a significant aeroallergen that can be transported 200-600 km from the source. Local observations of Juniperus spp. phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. Methods: The Dust REgional Atmospheric Model (DREAM)is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and quantities of dust. We successfully modified the DREAM model to incorporate pollen transport (PREAM) and used MODIS satellite images to develop Juniperus ashei pollen input source masks. The Pollen Release Potential Source Map, also referred to as a source mask in model applications, may use different satellite platforms and sensors and a variety of data sets other than the USGS GAP data we used to map J. ashei cover type. MODIS derived percent tree cover is obtained from MODIS Vegetation Continuous Fields (VCF) product (collection 3 and 4, MOD44B, 500 and 250 m grid resolution). We use updated 2010 values to calculate pollen concentration at source (J. ashei ). The original MODIS derived values are converted from native approx. 250 m to 990m (approx. 1 km) for the calculation of a mask to fit the model (PREAM) resolution. Results: The simulation period is chosen following the information that in the last 2 weeks of December 2010. The PREAM modeled near-surface concentrations (Nm-3) shows the transport patterns of J. ashei pollen over a 5 day period (Fig. 2). Typical scales of the simulated transport process are regional.

Luvall, J. C.↗