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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Millimeter-wave experiments for cometary space missions

Predicted brightness temperatures, computed by means of radiative transfer techniques adapted from the modeling of terrestrial ice and snow fields, are given for cometary nucleus models consisting of homogeneous layers of water ice and refractory grain mixtures presented as functions of wavelength. The computed millimeter-wave spectra are sensitive to the values of such physically significant nucleus parameters as (1) crust thickness, (2) subsurface temperature gradient, and (3) sublimating surface boundary temperature. Although antenna beam dilution is a major obstacle for ground-based molecular spectral line radio observations of comets, a millimeter-wave radiometer in the vicinity of the comet would be immune to this effect and able to make observations of several candidate parent molecules in the gas phase.

Hobbs, R. W.↗
NASA NTRS2004

Aerodynamic Shape Optimization Based on Free-form Deformation

This paper presents a free-form deformation technique suitable for aerodynamic shape optimization. Because the proposed technique is independent of grid topology, we can treat structured and unstructured computational fluid dynamics grids in the same manner. The proposed technique is an alternative shape parameterization technique to a trivariate volume technique. It retains the flexibility and freedom of trivariate volumes for CFD shape optimization, but it uses a bivariate surface representation. This reduces the number of design variables by an order of magnitude, and it provides much better control for surface shape changes. The proposed technique is simple, compact, and efficient. The analytical sensitivity derivatives are independent of the design variables and are easily computed for use in a gradient-based optimization. The paper includes the complete formulation and aerodynamics shape optimization results.

Samareh, Jamshid A.↗
NASA NTRS2004

Note on the Effect of Horizontal Gradients for Nadir-Viewing Microwave and Infrared Sounders

Passive microwave and infrared nadir sounders such as the Advanced Microwave Sounding Unit A (AMSU-A) and the Atmospheric InfraRed Sounder (AIRS), both flying on NASA s EOS Aqua satellite, provide information about vertical temperature and humidity structure that is used in data assimilation systems for numerical weather prediction and climate applications. These instruments scan cross track so that at the satellite swath edges, the satellite zenith angles can reach approx. 60 deg. The emission path through the atmosphere as observed by the satellite is therefore slanted with respect to the satellite footprint s zenith. Although radiative transfer codes currently in use at operational centers use the appropriate satellite zenith angle to compute brightness temperature, the input atmospheric fields are those from the vertical profile above the center of the satellite footprint. If horizontal gradients are present in the atmospheric fields, the use of a vertical atmospheric profile may produce an error. This note attempts to quantify the effects of horizontal gradients on AIRS and AMSU-A channels by computing brightness temperatures with accurate slanted atmospheric profiles. We use slanted temperature, water vapor, and ozone fields from data assimilation systems. We compare the calculated slanted and vertical brightness temperatures with AIRS and AMSU-A observations. We show that the effects of horizontal gradients on these sounders are generally small and below instrument noise. However, there are cases where the effects are greater than the instrument noise and may produce erroneous increments in an assimilation system. The majority of the affected channels have weighting functions that peak in the upper troposphere (water vapor sensitive channels) and above (temperature sensitive channels) and are unlikely t o significantly impact tropospheric numerical weather prediction. However, the errors could be significant for other applications such as stratospheric analysis. Gradients in ozone and tropospheric temperature appear to be well captured by the analyses. In contrast, gradients in upper stratospheric and mesospheric temperature as well as upper tropospheric humidity are less well captured. This is likely due in part to a lack of data to specify these fields accurately in the analyses. Advanced new sounders, like AIRS, may help to better specify these fields in the future.

Joiner, J.↗
DOE OSTI2020

Formulation and solution approach for calibrating activity-based travel demand model-system via microsimulation

This study addresses the problem of calibrating utility-maximizing nested logit activity-based travel demand model-systems. After estimation, it is common practice to use aggregate measurements to calibrate the estimated model-system’s parameters prior to their application in transportation planning, policy making, and operations. However, calibration of activity-based model-systems has received much less attention. Existing calibration approaches are myopic heuristics in the sense that they do not consider the fundamental inter-dependencies among choice-models and do not have a systematic way to adjust model parameters. Also, other purely simulation-based approaches do not perform well in large-scale applications. In this study, we focus on utility-maximizing nested logit activity-based model-systems and calibrating aggregate statistics such as activity shares, mode shares, time-dependent & mode-specific OD flows, and time-dependent & mode-specific sensor counts. We formulate the calibration problem as a simulation-based optimization problem and propose a stochastic gradient-based solution procedure to solve it. The solution procedure relies on microsimulation to calculate expectations of the aggregate statistics of interest to the calibration problem. Additionally, we derive approximate analytical expressions for the gradient of the objective function —that are evaluated through microsimulation on mini-batches of the population. The proposed solution procedure is sensitive to the fundamental structure of the activity-based model-system and is non-myopic in considering the dependencies across its model components. The formulated optimization problem is non-convex, highly nonlinear, and potentially has multiple-minima. Lastly, we show —through a real-world application— that the proposed solution procedure outperforms other state-of-the-art purely simulation-based optimization approaches in terms of computational efficiency, stability, and convergence. We also compare various gradient-based solution algorithms to determine the best algorithm to update the parameters. This work has the potential to facilitate wider and easier application of activity-based model-systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

Analysis of Transition-Sensitized Turbulent Transport Equations

The dynamics of an ensemble of linear disturbances in boundary-layer flows at various Reynolds numbers is studied through an analysis of the transport equations for the mean disturbance kinetic energy and energy dissipation rate. Effects of adverse and favorable pressure-gradients on the disturbance dynamics are also included in the analysis Unlike the fully turbulent regime where nonlinear phase scrambling of the fluctuations affects the flow field even in proximity to the wall, the early stage transition regime fluctuations studied here are influenced cross the boundary layer by the solid boundary. The dominating dynamics in the disturbance kinetic energy and dissipation rate equations are described. These results are then used to formulate transition-sensitized turbulent transport equations, which are solved in a two-step process and applied to zero-pressure-gradient flow over a flat plate. Computed results are in good agreement with experimental data.

Rumsey, Christopher L.↗
DOE OSTI2021

Preliminary Cryogenic Cold Test Results of the First 9-Cell LSF Shape Cavity

Following successful prototyping and testing of single- & 5-cell LSF shape cavities *, **, the first 9-cell LSF shape cavity LSF9-1 was successfully constructed using an innovative process at JLab with the in-house facilities. The cavity was then shipped to KEK for post-fabrication mechanical adjustment and ILC TDR style treatment and surface processing. Cold testing was carried out at the JLab VTA facility, instrumented with a suite of Kyoto instruments. Favorable values for the bath pressure detuning sensitivity and Lorentz force detuning coefficient were experimentally measured, validating the design improvement in cell stiffeners. Pass-band measurements indicate 4 out of 9 cells reaching gradient capability of > 45 MV/m, including 2 cells reaching 51 MV/m. Cornell OST detectors identified the cell and location responsible for the current hard quench limit. Multipacting-like barriers observed in end cells are investigated both analytically and numerically. The cavity was shipped to FNAL and received a light EP at the joint ANL/FNAL facility for further cold testing at Jlab. Two new 9-cell LSF cavities are being constructed including one made of large-grain niobium material.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

A STUDY OF SOLAR PHOTOSPHERIC TEMPERATURE GRADIENT VARIATION USING LIMB DARKENING MEASUREMENTS

The variation in area of quiet magnetic network measured over the sunspot cycle should modulate the spatially averaged photospheric temperature gradient, since temperature declines with optical depth more gradually in magnetic flux tube atmospheres. Yet, limb darkening measurements show no dependence upon activity level, even at an rms precision of 0.04%. We study the sensitivity of limb darkening to changes in area filling factor using a 3D MHD model of the magnetized photosphere. The limb darkening change expected from the measured 11-year area variation lies below the level of measured limb darkening variations, for a reasonable range of magnetic flux in quiet network and internetwork regions. So the remarkably constant limb darkening observed over the solar activity cycle is not inconsistent with the measured 11-year change in area of quiet magnetic network. Our findings offer an independent constraint on photospheric temperature gradient changes reported from measurements of the solar spectral irradiance from the Spectral Irradiance Monitor, and recently, from wavelength-differential spectrophotometry using the Solar Optical Telescope aboard the HINODE spacecraft.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Effects of input gradient regularization on neural networks time-series forecasting of thermal power systems

This study proposes using neural networks, specifically gated recurrent unit (GRU), long-short-term memory (LSTM), and transformer networks, to improve control strategies in a 450 MW coal-fired power plant. However, neural networks face issues of becoming overly dependent on just a few variables to make predictions, which negatively impacts control decisions that rely on the model to determine the value of all manipulated variables. The paper introduces regularization techniques, including noise injection and input gradient regularization, during the training phase. Here, the work presents novel contributions in adapting neural networks to control industrial systems and applying regularization techniques from computer vision to industrial process control. Results demonstrate the effectiveness of input gradient regularization in reducing model dependence on subsets of variables, emphasizing the balance between fidelity and controllability. Further exploration is recommended, including the development of recurrent transformers, closed-loop control testing, and a sensitivity analysis on computer models to provide further insight.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2019

Revealing the Distribution of Metal Carboxylates in Oil Paint from the Micro- to Nanoscale

Oil paints comprise pigments, drying oils, and additives that together confer desirable properties, but can react to form metal carboxylates (soaps) that may damage artworks over time. To obtain information on soap formation and aggregation, we introduce in this study a new tapping-mode measurement paradigm for the photothermal induced resonance (PTIR) technique that enables nanoscale IR spectroscopy and imaging on highly heterogenous and rough paint thin sections. PTIR is used in combination with μ-computed tomography and IR microscopy to determine the distribution of metal carboxylates in a 23-year old oil paint of known formulation. Results show that heterogeneous agglomerates of Al-stearate and a Zn-carboxylate complex with Zn-stearate nano-aggregates in proximity are distributed randomly in the paint. The gradients of zinc carboxylates are unrelated to the Al-stearate distribution. These measurements open a new chemically sensitive nanoscale observation window on the distribution of metal soaps that can bring insights for understanding soap formation in oil paint.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Spatiotemporal modeling of ecological and sociological predictors of West Nile virus in Suffolk County, NY, mosquitoes

Abstract Suffolk County, New York, is a locus for West Nile virus ( WNV ) infection in the American northeast that includes the majority of Long Island to the east of New York City. The county has a system of light and gravid traps used for mosquito collection and disease monitoring. In order to identify predictors of WNV incidence in mosquitoes and predict future occurrence of WNV , we have developed a spatiotemporal Bayesian model, beginning with over 40 ecological, meteorological, and built‐environment covariates. A mixed‐effects model including spatially and temporally correlated errors was fit to WNV surveillance data from 2008 to 2014 using the R package “R‐INLA,” which allows for Bayesian modeling using the stochastic partial differential equation ( SPDE ) approach. The integrated nested Laplace approximation ( INLA ) SPDE allows for simultaneous fitting of a temporal parameter and a spatial covariance, while incorporating a variety of likelihood functions and running in R statistical software on a home computer. We found that land cover classified as open water and woody wetlands had a negative association with WNV incidence in mosquitoes, and the count of septic systems was associated with an increase in WNV . Mean temperature at two‐week lag was associated with a strong positive impact, while mean precipitation at no lag and one‐week lag was associated with positive and negative impacts on WNV , respectively. Incorporation of spatiotemporal factors resulted in a marked increase in model goodness‐of‐fit. The predictive power of the model was evaluated on 2015 surveillance results, where the best model achieved a sensitivity of 80.9% and a specificity of 77.0%. The spatial covariate was mapped across the county, identifying a gradient of WNV prevalence increasing from east to west. The Bayesian spatiotemporal model improves upon previous approaches, and we recommend the INLA SPDE methodology as an efficient way to develop robust models from surveillance data to develop and enhance monitoring and control programs. Our study confirms previously found associations between weather conditions and WNV and suggests that wetland cover has a mitigating effect on WNV infection in mosquitoes, while high septic system density is associated with an increase in WNV infection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

On the Departure from Monin–Obukhov Surface Similarity and Transition to the Convective Mixed Layer

Large-eddy simulations are used to evaluate mean profile similarity in the convective boundary layer (CBL). Particular care is taken regarding the grid sensitivity of the profiles and the mitigation of inertial oscillations in the simulation spin-up. The nondimensional gradients Φ for wind speed and air temperature generally align with Monin–Obukhov similarity across cases but have a steeper slope than predicted within each profile. The same trend has been noted in several other recent studies. The Businger-Dyer relations are modified here with an exponential cutoff term to account for the decay in Φ to first-order approximation, yielding improved similarity from approximately 0.05z i to above 0.3z i , where z i is the CBL depth. The necessity for the exponential correction is attributed to an extended transition from surface scaling to zero gradient in the mixed layer, where the departure from Monin–Obukhov similarity may be negligible at the surface but becomes substantial well below the conventional surface layer height of 0.1 z i .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Resource assessment of ocean thermal energy conversion in Puerto Rico and U.S. Virgin Islands

Island communities often struggle to establish and maintain traditional electric grids and are therefore heavily reliant on costly imported fossil fuels. In the case of Puerto Rico, these challenges are enhanced by extreme weather and other natural hazards that threaten the local electricity generation and transmission infrastructure. Ocean thermal energy conversion (OTEC) could play an important role in establishing a more resilient electrical grid in the region. Here, in this study, a detailed analysis is conducted to characterize the ocean thermal resource and power potential of OTEC in Puerto Rico based on a 14-year dataset of modeled ocean temperature. The assessment considers seasonal and interannual variability in the region's thermal resource and examines the operational limitations associated with minimal thermal gradients required to run a typical OTEC heat engine. Notably, the local thermal resource is found to be sensitive to El Niño-Southern Oscillation (ENSO) climate patterns, with La Niña conditions linked to greater OTEC power availability. Seven areas of opportunity are identified based on their resource potential and proximity to existing electrical distribution lines, including two that could benefit the nearby U.S. Virgin Islands. The greatest OTEC power potential is observed to the south of the main island of Puerto Rico in the Caribbean Sea with an estimated capacity of 138 MW for a plant pumping cold water from a depth of 1,000 m, or the equivalent amount of electricity required to power 219,000 households.

OTEC↗
DOE OSTI2022

The Madden–Julian Oscillation in the Energy Exascale Earth System Model Version 1

Abstract The present study examines the characteristics of the Madden–Julian Oscillation (MJO) events represented in the Energy Exascale Earth System Model version 1 (E3SMv1), DOE’s new Earth system model. The coupled E3SMv1 realistically simulates the eastward propagation of precipitation and moist static energy (MSE) anomalies associated with the MJO. As in observations, horizontal moisture advection and longwave radiative feedback are found to be the dominant processes in E3SMv1 that lead to the eastward movement and maintenance of the MJO MSE anomalies, respectively. Modulation of the diurnal cycle of precipitation in the Maritime Continent region by the MJO is also well represented in the model despite systematic biases in the magnitude and phase of the precipitation diurnal cycle. On the MJO impact over the midlatitude, E3SMv1 reasonably captures the pattern of the MJO teleconnections across the North Pacific and North America, with improvement in the performance in a high‐resolution version, despite the magnitude being a bit weaker than the observed. Regarding the interannual variability of the MJO, the El Niño‐Southern Oscillation (ENSO) modulation of the zonal extent of MJO’s eastward propagation, as well as associated changes in the mean state moisture gradient in the tropical west Pacific, are well reproduced in the model. However, MJO in E3SMv1 exhibits no sensitivity to the Quasi‐Biennial Oscillation (QBO), with the MJO propagation characteristics being almost identical between easterly QBO and westerly QBO years. Processes that have been suggested as critical to MJO simulation are also examined by utilizing recently developed process‐oriented diagnostics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Controlling superconductivity of CeIrIn 5 microstructures by substrate selection

Superconductor/metal interfaces are usually fabricated in heterostructures that join these dissimilar materials. A conceptually different approach has recently exploited the strain sensitivity of heavy-fermion superconductors, selectively transforming regions of the crystal into the metallic state by strain gradients. The strain is generated by differential thermal contraction between the sample and the substrate. Here, we present an improved finite-element model that reliably predicts the superconducting transition temperature in CeIrIn 5 even in complex structures. Different substrates are employed to tailor the strain field into the desired shapes. Using this approach, both highly complex and strained as well as strain-free microstructures are fabricated to validate the model. This enables a high degree of control over the microscopic strain fields and forms the basis for more advanced structuring of superconductors as in Josephson junctions yet also finds natural use cases in any material class in which a modulation of the physical properties on a chip is desirable.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Weighted active space protocol for multireference machine-learned potentials

Multireference methods such as multiconfiguration pair-density functional theory accurately capture electronic correlation in systems with strong multiconfigurational character, but their cost precludes direct use in molecular dynamics. Combining these methods with machine-learned interatomic potentials (MLPs) can extend their reach. However, the sensitivity of multireference calculations to the choice of the active space complicates the consistent evaluation of energies and gradients across structurally diverse nuclear configurations. To overcome this limitation, we introduce the weighted active space protocol (WASP), a systematic approach to assign a consistent active space for a given system across uncorrelated configurations. By integrating WASP with MLPs and enhanced sampling techniques, we propose a data-efficient active learning cycle that enables the training of an MLP on multireference data. We demonstrated the approach on the TiC + -catalyzed C–H activation of methane, a reaction that poses challenges for Kohn–Sham density functional theory due to its significant multireference character. This framework enables accurate and efficient modeling of catalytic dynamics, establishing a paradigm for simulating complex reactive processes beyond the limits of conventional electronic-structure methods.

enhanced sampling↗
DOE OSTI2021

Embedded training of neural-network subgrid-scale turbulence models

We report that the weights of a deep neural-network model are optimized in conjunction with the governing flow equations to provide a model for subgrid-scale stresses in a temporally developing plane turbulent jet at Reynolds number Re 0 = 6000 . The objective function for training is first based on the instantaneous filtered velocity fields from a corresponding direct numerical simulation, and the training is by a stochastic gradient descent method, which uses the adjoint Navier-Stokes equations to provide the end-to-end sensitivities of the model weights to the velocity fields. In-sample and out-of-sample testing on multiple dual-jet configurations show that its required mesh density in each coordinate direction for prediction of mean flow, Reynolds stresses, and spectra is half that needed by the dynamic Smagorinsky model for comparable accuracy. The same neural-network model trained directly to match filtered subgrid-scale stresses, without the constraint of being embedded within the flow equations during the training, fails to provide a qualitatively correct prediction. The coupled formulation is generalized to train based only on mean-flow and Reynolds stresses, which are more readily available in experiments. The mean-flow training provides a robust model, which is important, though a somewhat less accurate prediction for the same coarse meshes, as might be anticipated due to the reduced information available for training in this case. The anticipated advantage of the formulation is that the inclusion of resolved physics in the training increases its capacity to extrapolate. This is assessed for the case of passive scalar transport, for which it outperforms established models due to improved mixing predictions.

42 ENGINEERING↗
DOE OSTI2019

Effective Cloud Detection and Segmentation Using a Gradient-Based Algorithm for Satellite Imagery: Application to Improve PERSIANN-CCS

The effective identification of clouds and monitoring of their evolution are important toward more accurate quantitative precipitation estimation and forecast. In this study, a new gradient-based cloud-image segmentation algorithm is developed using image processing techniques. This method integrates morphological image gradient magnitudes to separate cloud systems and patches boundaries. A varying scale kernel is implemented to reduce the sensitivity of image segmentation to noise and to capture objects with various finenesses of the edges in remote sensing images. The proposed method is flexible and extendable from single to multispectral imagery. Case studies were carried out to validate the algorithm by applying the proposed segmentation algorithm to synthetic radiances for channels of the Geostationary Operational Environmental Satellite ( GOES-16) simulated by a high-resolution weather prediction model. The proposed method compares favorably with the existing cloud-patch-based segmentation technique implemented in the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Cloud Classification System (PERSIANN-CCS) rainfall retrieval algorithm. Evaluation of event-based images indicates that the proposed algorithm has potentials comparing to the conventional segmentation technique used in PERSIANN-CCS to improve rain detection and estimation skills with an accuracy rate of up to 98% in identifying cloud regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Final Technical Report: Quantification of Uncertainty in Extreme Scale Computations (QUEST)

QUEST is a SciDAC Institute comprising Sandia National Laboratories, Los Alamos National Laboratory, University of Southern California, Massachusetts Institute of Technology, University of Texas at Austin, and Duke University. The mission of QUEST is to: (1) develop a broad class of uncertainty quantification (UQ) methods/tools, and (2) provide UQ expertise and software to other SciDAC projects, thereby enabling/guiding their UQ activities. The Duke effort focused on the development of algorithms and utility software for non-intrusive sparse UQ representations, and on participation in the organization of annual workshops and tutorials to disseminate UQ tools to the community, and to gather input in order to adapt approaches to the needs of SciDAC customers. In particular, fundamental developments were made in (a) multiscale stochastic preconditioners, (b) gradient-based approaches to inverse problems, (c) adaptive pseudo-spectral approximations, (d) stochastic limit cycles, and (e) sensitivity analysis tools for noisy systems. In addition, large-scale demonstrations were performed, namely in the context of ocean general circulation models.

97 MATHEMATICS AND COMPUTING↗