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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Modeling neutrino-induced scale-dependent galaxy clustering for photometric galaxy surveys

Abstract The increasing statistical precision of photometric redshift surveys requires improved accuracy of theoretical predictions for large-scale structure observables to obtain unbiased cosmological constraints. In ΛCDM cosmologies, massive neutrinos stream freely at small cosmological scales, suppressing the small-scale power spectrum. In massive neutrino cosmologies, galaxy bias modeling needs to accurately relate the scale-dependent growth of the underlying matter field to observed galaxy clustering statistics. In this work, we implement a computationally efficient approximation of the neutrino-induced scale-dependent bias (NISDB). Through simulated likelihood analyses of Dark Energy Survey Year 3 (DESY3) and Legacy Survey of Space and Time Year 1 (LSSTY1) synthetic data that contain an appreciable NISDB, we examine the impact of linear galaxy bias and neutrino mass modeling choices on cosmological parameter inference. We find model misspecification of the NISDB approximation and neutrino mass models to decrease the constraining power of photometric galaxy surveys and cause parameter biases in the cosmological interpretation of future surveys. We quantify these biases and devise mitigation strategies.

Astronomy & Astrophysics↗
NASA NTRS2011

Verification of Small Hole Theory for Application to Wire Chaffing Resulting in Shield Faults

Our work is focused upon developing methods for wire chafe fault detection through the use of reflectometry to assess shield integrity. When shielded electrical aircraft wiring first begins to chafe typically the resulting evidence is small hole(s) in the shielding. We are focused upon developing algorithms and the signal processing necessary to first detect these small holes prior to incurring damage to the inner conductors. Our approach has been to develop a first principles physics model combined with probabilistic inference, and to verify this model with laboratory experiments as well as through simulation. Previously we have presented the electromagnetic small-hole theory and how it might be applied to coaxial cable. In this presentation, we present our efforts to verify this theoretical approach with high-fidelity electromagnetic simulations (COMSOL). Laboratory observations are used to parameterize the computationally efficient theoretical model with probabilistic inference resulting in quantification of hole size and location. Our efforts in characterizing faults in coaxial cable are subsequently leading to fault detection in shielded twisted pair as well as analysis of intermittent faulty connectors using similar techniques.

Schuet, Stefan R.↗
NASA NTRS2018

Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity from Observations

An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2-radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.

Marvel, Kate↗
NASA NTRS2007

Using Remotely-Sensed Estimates of Soil Moisture to Infer Soil Texture and Hydraulic Properties across a Semi-arid Watershed

Near-surface soil moisture is a critical component of land surface energy and water balance studies encompassing a wide range of disciplines. However, the processes of infiltration, runoff, and evapotranspiration in the vadose zone of the soil are not easy to quantify or predict because of the difficulty in accurately representing soil texture and hydraulic properties in land surface models. This study approaches the problem of parameterizing soils from a unique perspective based on components originally developed for operational estimation of soil moisture for mobility assessments. Estimates of near-surface soil moisture derived from passive (L-band) microwave remote sensing were acquired on six dates during the Monsoon '90 experiment in southeastern Arizona, and used to calibrate hydraulic properties in an offline land surface model and infer information on the soil conditions of the region. Specifically, a robust parameter estimation tool (PEST) was used to calibrate the Noah land surface model and run at very high spatial resolution across the Walnut Gulch Experimental Watershed. Errors in simulated versus observed soil moisture were minimized by adjusting the soil texture, which in turn controls the hydraulic properties through the use of pedotransfer functions. By estimating a continuous range of widely applicable soil properties such as sand, silt, and clay percentages rather than applying rigid soil texture classes, lookup tables, or large parameter sets as in previous studies, the physical accuracy and consistency of the resulting soils could then be assessed. In addition, the sensitivity of this calibration method to the number and timing of microwave retrievals is determined in relation to the temporal patterns in precipitation and soil drying. The resultant soil properties were applied to an extended time period demonstrating the improvement in simulated soil moisture over that using default or county-level soil parameters. The methodology is also applied to an independent case at Walnut Gulch using a new soil moisture product from active (C-band) radar imagery with much lower spatial and temporal resolution. Overall, results demonstrate the potential to gain physically meaningful soils information using simple parameter estimation with few but appropriately timed remote sensing retrievals.

Santanello, Joseph A.↗
DOE OSTI2022

Altering Terahertz Sound Propagation in a Liquid upon Nanoparticle Immersion

One of the grand challenges of new generation Condensed Matter physicists is the development of novel devices enabling the control of sound propagation at terahertz frequency. Indeed, phonon excitations in this frequency window are the leading conveyor of heat transfer in insulators. Their manipulation is thus critical to implementing heat management based on the structural design. To explore the possibility of controlling the damping of sound waves, we used high spectral contrast Inelastic X-ray Scattering (IXS) to comparatively study terahertz acoustic damping in a dilute suspension of 50 nm nanospheres in glycerol and on pure glycerol. Bayesian inference-based modeling of measured spectra indicates that, at sufficiently large distances, the spectral contribution of collective modes in the glycerol suspension becomes barely detectable due to the enhanced damping, the weakening, and the slight softening of the dominant acoustic mode.

36 MATERIALS SCIENCE↗
NASA NTRS2013

Lumped Parameter Modeling for Rapid Vibration Response Prototyping and Test Correlation for Electronic Units

Present preliminary work using lumped parameter models to approximate dynamic response of electronic units to random vibration; Derive a general N-DOF model for application to electronic units; Illustrate parametric influence of model parameters; Implication of coupled dynamics for unit/board design; Demonstrate use of model to infer printed wiring board (PWB) dynamics from external chassis test measurement.

random vibration↗
DOE OSTI2022

Study of Stark broadening of krypton helium-$\beta$ lines and estimation of electron density and temperature in NIF compressed capsules

Here the National Ignition Facility (NIF) diagnostic instrument manipulator (DIM) - based high resolution (dHIRES) x-ray spectrometer was used to measure the time evolution of the electron density (n e ) and temperature (T e ) in the hot spot of four NIF compressed capsules with 25 ps time resolution during the 'stagnation' phase. The electron density was inferred by comparing the measured Stark broadening of the krypton (Kr) Heβ spectral complex with theoretical calculations that include ion dynamic effects, and the electron temperature was inferred by comparing the measured ratio of the intensity of a dielectronically excited Li-like Kr line to the intensity of the Kr Heβ resonance line with calculations using the spectroscopic collisional radiative atomic model (SCRAM) and CRETIN collisional-radiative models. The inferred, time averaged n e values mainly agree with n e values from neutron diagnostics within uncertainties, but the neutron time-of-flight values of T ion are consistently higher than dHIRES T e values by 200–700 eV. The dHIRES measurements and measurement techniques, method of uncertainty analysis, and discussion of comparisons with measurements from neutron diagnostics are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Inferring the spread of COVID-19: the role of time-varying reporting rate in epidemiological modelling

The role of epidemiological models is crucial for informing public health officials during a public health emergency, such as the COVID-19 pandemic. However, traditional epidemiological models fail to capture the time-varying effects of mitigation strategies and do not account for under-reporting of active cases, thus introducing bias in the estimation of model parameters. To infer more accurate parameter estimates and to reduce the uncertainty of these estimates, we extend the SIR and SEIR epidemiological models with two time-varying parameters that capture the transmission rate and the rate at which active cases are reported to health officials. Using two real data sets of COVID-19 cases, we perform Bayesian inference via our SIR and SEIR models with time-varying transmission and reporting rates and via their standard counterparts with constant rates; our approach provides parameter estimates with more realistic interpretation, and 1-week ahead predictions with reduced uncertainty. Furthermore, we find consistent under-reporting in the number of active cases in the data that we consider, suggesting that the initial phase of the pandemic was more widespread than previously reported.

42 ENGINEERING↗
DOE OSTI2024

Quantitative radiography for determining density fluctuations in HED experiments

We have developed a method to extract density fluctuation measurements from x-ray radiographs of high-energy density (HED) instability growth and turbulence experiments. We use this information to calculate density fluctuation statistics for constraining the performance of turbulent mix models in HED systems. The density calculation combines image filtering, removal of systemic effects such as backlighter variation, calculation of transmission across multiple materials, and use of tracer materials to generate an approximate single-material density field. From the density map, we calculate both average density and a variance-like moment b (density-specific-volume covariance), which we compare to our models. We infer both quantities from a single image, which is significantly more information than the historic single scalar mix width measurements. We also develop a method of analyzing simulation outputs that incorporate both the density fluctuation metric from a turbulence model and the bulk material maps from the hydrodynamic code. This analysis helps address the question of how to initialize the simulations for best comparison to data from systems with large separations of scale in the mixing perturbation initial condition. We find that our data analysis method yields 1D average density and b curves with similar morphology and amplitudes as those from preliminary simulation comparisons.

47 OTHER INSTRUMENTATION↗
NASA NTRS2021

Modelled land use and land cover change emissions – a spatio-temporal comparison of different approaches

Quantifying the net carbon flux from land use and land cover changes (fLULCC) is critical for understanding the global carbon cycle and, hence, to support climate change mitigation. However, large-scale fLULCC is not directly measurable and has to be inferred from models instead, such as semi-empirical bookkeeping models and process-based dynamic global vegetation models (DGVMs). By definition, fLULCC estimates are not directly comparable between these two different model types. As an important example, DGVM-based fLULCC in the annual global carbon budgets is estimated under transient environmental forcing and includes the so-called loss of additional sink capacity (LASC). The LASC results from the impact of environmental changes on land carbon storage potential of managed land compared to potential vegetation and accumulates over time, which is not captured in bookkeeping models. The fLULCC from transient DGVM simulations, thus, strongly depends on the timing of land use and land cover changes mainly because LASC accumulation is cut off at the end of the simulated period. To estimate the LASC, the fLULCC from pre-industrial DGVM simulations, which is independent of changing environmental conditions, can be used. Additionally, DGVMs using constant present-day environmental forcing enable an approximation of bookkeeping estimates. Here, we analyse these three DGVM-derived fLULCC estimations (under transient, pre-industrial, and present-day forcing) for 12 models within 18 regions and quantify their differences as well as climate- and CO2-induced components and compare them to bookkeeping estimates. Averaged across the models, we find a global fLULCC (under transient conditions) of 2.0±0.6 PgC/yr for 2009–2018, of which ∼40 % are attributable to the LASC (0.8±0.3 PgC/yr). From 1850 onward, the fLULCC accumulated to 189±56 PgC with 40±15 PgC from the LASC. Around 1960, the accumulating nature of the LASC causes global transient fLULCC estimates to exceed estimates under present-day conditions, despite generally increased carbon stocks in the latter. Regional hotspots of high cumulative and annual LASC values are found in the USA, China, Brazil, equatorial Africa, and Southeast Asia, mainly due to deforestation for cropland. Distinct negative LASC estimates in Europe (early reforestation) and from 2000 onward in the Ukraine (recultivation of post-Soviet abandoned agricultural land), indicate that fLULCC estimates in these regions are lower in transient DGVM compared to bookkeeping approaches. Our study unravels the strong dependence of fLULCC estimates on the time a certain land use and land cover change event happened to occur and on the chosen time period for the forcing of environmental conditions in the underlying simulations. We argue for an approach that provides an accounting of the fLULCC that is more robust against these choices, for example by estimating a mean DGVM ensemble fLULCC and LASC for a defined reference period and homogeneous environmental changes (CO2 only).

land use and land cover change↗
NASA NTRS1992

Software design as a problem in learning theory (a research overview)

Our interest in automating software design has come out of our research in automated reasoning, inductive inference, learnability, and algebraic machine theory. We have investigated these areas extensively, in connection with specific problems of language representation, acquisition, processing, and design. In the case of formal context-free (CF) languages we established existence of finite learnable models ('behavioral realizations') and procedures for constructing them effectively. We also determined techniques for automatic construction of the models, inductively inferring them from finite examples of how they should 'behave'. These results were obtainable due to appropriate representation of domain knowledge, and constraints on the domain that the representation defined. It was when we sought to generalize our results, and adapt or apply them, that we began investigating the possibility of determining similar procedures for constructing correct software. Discussions with other researchers led us to examine testing and verification processes, as they are related to inference, and due to their considerable importance in correct software design. Motivating papers by other researchers, led us to examine these processes in some depth. Here we present our approach to those software design issues raised by other researchers, within our own theoretical context. We describe our results, relative to those of the other researchers, and conclude that they do not compare unfavorably.

Fass, Leona F.↗
DOE OSTI2024

AesFA: An Aesthetic Feature-Aware Arbitrary Neural Style Transfer

Neural style transfer (NST) has evolved significantly in recent years. Yet, despite its rapid progress and advancement, existing NST methods either struggle to transfer aesthetic information from a style effectively or suffer from high computational costs and inefficiencies in feature disentanglement due to using pre-trained models. This work proposes a lightweight but effective model, AesFA---Aesthetic Feature-Aware NST. The primary idea is to decompose the image via its frequencies to better disentangle aesthetic styles from the reference image while training the entire model in an end-to-end manner to exclude pre-trained models at inference completely. Finally, to improve the network's ability to extract more distinct representations and further enhance the stylization quality, this work introduces a new aesthetic feature: contrastive loss. Extensive experiments and ablations show the approach not only outperforms recent NST methods in terms of stylization quality, but it also achieves faster inference. Codes are available at https://github.com/Sooyyoungg/AesFA.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Modelled land use and land cover change emissions – a spatio-temporal comparison of different approaches

Abstract. Quantifying the net carbon flux from land use and land cover changes (fLULCC) is critical for understanding the global carbon cycle and, hence, to support climate change mitigation. However, large-scale fLULCC is not directly measurable and has to be inferred from models instead, such as semi-empirical bookkeeping models and process-based dynamic global vegetation models (DGVMs). By definition, fLULCC estimates are not directly comparable between these two different model types. As an important example, DGVM-based fLULCC in the annual global carbon budgets is estimated under transient environmental forcing and includes the so-called loss of additional sink capacity (LASC). The LASC results from the impact of environmental changes on land carbon storage potential of managed land compared to potential vegetation and accumulates over time, which is not captured in bookkeeping models. The fLULCC from transient DGVM simulations, thus, strongly depends on the timing of land use and land cover changes mainly because LASC accumulation is cut off at the end of the simulated period. To estimate the LASC, the fLULCC from pre-industrial DGVM simulations, which is independent of changing environmental conditions, can be used. Additionally, DGVMs using constant present-day environmental forcing enable an approximation of bookkeeping estimates. Here, we analyse these three DGVM-derived fLULCC estimations (under transient, pre-industrial, and present-day forcing) for 12 models within 18 regions and quantify their differences as well as climate- and CO2-induced components and compare them to bookkeeping estimates. Averaged across the models, we find a global fLULCC (under transient conditions) of 2.0±0.6 PgC yr−1 for 2009–2018, of which ∼40 % are attributable to the LASC (0.8±0.3 PgC yr−1). From 1850 onward, the fLULCC accumulated to 189±56 PgC with 40±15 PgC from the LASC. Around 1960, the accumulating nature of the LASC causes global transient fLULCC estimates to exceed estimates under present-day conditions, despite generally increased carbon stocks in the latter. Regional hotspots of high cumulative and annual LASC values are found in the USA, China, Brazil, equatorial Africa, and Southeast Asia, mainly due to deforestation for cropland. Distinct negative LASC estimates in Europe (early reforestation) and from 2000 onward in the Ukraine (recultivation of post-Soviet abandoned agricultural land), indicate that fLULCC estimates in these regions are lower in transient DGVM compared to bookkeeping approaches. Our study unravels the strong dependence of fLULCC estimates on the time a certain land use and land cover change event happened to occur and on the chosen time period for the forcing of environmental conditions in the underlying simulations. We argue for an approach that provides an accounting of the fLULCC that is more robust against these choices, for example by estimating a mean DGVM ensemble fLULCC and LASC for a defined reference period and homogeneous environmental changes (CO2 only).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

Comparison of field-aligned currents at ionospheric and magnetospheric altitudes

Using the empirical terrestrial magnetospheric magnetic field models of Tsyganenko and Usmanov (1982) and Tsyganenko (1987) the average field-aligned currents (FACs) in the magnetosphere were determined as a function of the Kp index. Three major model FAC systems were identified, namely, the dayside region 1, the nightside region 1, and the nightside polar cap. The models provide information about the sources of the current systems. Mapped ionospheric model FACs are compared with low-altitude measurements obtained by the spacecraft. It is found that low-altitude data can reveal either classic region 1/2 or more highly structured FAC patterns. Therefore, statistical results either obtained from observations or inferred from models are expected to be averages over temporally and spatially shifting patterns.

Spence, H. E.↗
DOE OSTI2019

Coupled flow accumulation and atmospheric blocking govern flood duration

Abstract We present a physically based Bayesian network model for inference and prediction of flood duration that allows for a deeper understanding of the nexus of antecedent flow regime, atmospheric blocking, and moisture transport/release mechanisms. Distinct scaling factors at the land surface and regional atmospheric levels are unraveled using this Bayesian network model. Land surface scaling explains the variability in flood duration as a function of cumulative exceedance index, a new measure that represents the evolution of the flood in the basin. Dynamic atmospheric scaling explains the cumulative exceedance index using the interaction between atmospheric blocking system and the synergistic model of wind divergence and atmospheric water vapor. Our findings underline that the synergy between a large persistent low-pressure blocking system and a higher rate of divergent wind often triggers a long-duration flood, even in the presence of moderate moisture supply in the atmosphere. This condition in turn causes an extremely long-duration flood if the basin-wide cumulative flow prior to the flood event was already high. Thus, this new land-atmospheric interaction framework integrates regional flood duration scaling and dynamic atmospheric scaling to enable the coupling of ‘horizontal’ (for example, streamflow accumulation inside the basin) and ‘vertical’ flow of information (for example, interrelated land and ocean-atmosphere interactions), providing an improved understanding of the critical forcing of regional hydroclimatic systems. This Bayesian model approach is applied to the Missouri River Basin, which has the largest system of reservoirs in the United States. Our predictive model can aid in decision support systems for the protection of national infrastructure against long-duration flood events.

Najibi, Nasser (ORCID:0000000205157192)↗
NASA NTRS2014

Geological Structures in the WaIls of Vestan Craters

A compelling case can be made that Vesta is the parent asteroid for the howardite, eucrite and diogenite (HED) meteorites [1], although this interpretation has been questioned [2]. Generalized models for the structure of the crust of Vesta have been developed based on petrologic studies of basaltic eucrites, cumulate eucrites and diogenites. These models use inferred cooling rates for different types of HEDs and compositional variations within the clan to posit that the lower crust is dominantly diogenitic in character, cumulate eucrites occur deep in the upper crust, and basaltic eucrites dominate the higher levels of the upper crust [3-5]. These models lack fine-scale resolution and thus do not allow for detailed predictions of crustal structure. Geophysical models predict dike and sill intrusions ought to be present, but their widths may be quite small [6]. The northern hemisphere of Vesta is heavily cratered, and the southern hemisphere is dominated by two 400-500 km diameter basins that excavated deep into the crust [7-8]. Physical modeling of regolith formation on 300 km diameter asteroids predicts that debris layers would reach a few km in thickness, while on asteroids of Vesta's diameter regolith thicknesses would be less [9]. This agrees well with the estimated ≤1 km thickness of local debris excavated by a 45 km diameter vestan crater [10]. Large craters and basins may have punched through the regolith/megaregolith and exposed primary vestan crustal structures. We will use Dawn Framing Camera (FC) [11] images and color ratio maps from the High Altitude and Low Altitude Mapping Orbits (HAMO, ~65 m/pixel; LAMO, ~20 m/pixel) to evaluate structures exposed on the walls of craters: two examples are discussed here.

Mittlefehldt, David↗
NASA NTRS2014

Retrieval of Methane Source Strengths in Europe Using a Simple Modeling Approach to Assess the Potential of Spaceborne Lidar Observations

We investigate the sensitivity of future spaceborne lidar measurements to changes in surface methane emissions. We use surface methane observations from nine European ground stations and a Lagrangian transport model to infer surface methane emissions for 2010. Our inversion shows the strongest emissions from the Netherlands, the coal mines in Upper Silesia, Poland, and wetlands in southern Finland. The simulated methane surface concentrations capture at least half of the daily variability in the observations, suggesting that the transport model is correctly simulating the regional transport pathways over Europe. With this tool we can test whether proposed methane lidar instruments will be sensitive to changes in surface emissions. We show that future lidar instruments should be able to detect a 50% reduction in methane emissions from the Netherlands and Germany, at least during summer.

surface fluxes↗
DOE OSTI2024

What Are Ontologies and When Should They Be Used?

Data without description is at best unusable, and at worst, misused. If we do not understand the assumptions and meaning of our data, we are unable to confidently use it. Data today is largely described within a database’s schema, detailing structure and primitive datatypes as part of a relational model, but if we require assurance some data value can be correctly evaluated alongside others beyond the immediate systems in which they are defined, a more portable, richer semantics is needed. Ontologies define knowledge unambiguously across systems and establish the means to reason upon said knowledge using logical inference. They model neutral domains of information rather than data definitions from software or databases that would only serve to enrich a single system’s idiosyncrasies. In this paper, we take a casual stance to explore what ontologies are, how they are built, why they are useful, and when they should be used.

97 MATHEMATICS AND COMPUTING↗