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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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

The loss and depth of CO2 ice in comet nuclei

The chemical differentiation of a homogeneous, initially unmantled cometary nucleus whose composition encompasses water ice, unclathrated CO2 ice, and silicate dust, is presently simulated by an analytical model to test whether the selective sublimation of any free CO2 ice in the new comet will produce a surface layer of water ice and dust covering the undifferentiated core. The model encompasses the effects of nucleus rotation, arbitrary rotatiuon axis orientation, latitude, nucleus heat conduction, and CO2 gas outflow restriction by the water ice and dust layer.

Fanale, Fraser P.↗
DOE OSTI2021

Short-term apartment-level load forecasting using a modified neural network with selected auto-regressive features

Residential electricity load profiles and their diversity have become increasingly important to realize the benefits of Smart or Transactive Energy Networks (TENs). An important element of TENs will be practical, accurate, and implementable residential load forecasting techniques. While there have been many approaches to short-term load forecasting, few have included forecasting for individual households, partly because the high volatility and idiosyncrasies present in individual household load data can pose significant challenges. In this study, we develop a Convolutional Long Short-Term Memory-based neural network with Selected Autoregressive Features (termed a CLSAF model) to improve short-term household electricity load forecasting accuracy by employing three strategies: autoregressive features selection, exogenous features selection, and a “default” state to avoid overfitting at times of high load volatility. We include aggregations of apartments to floor and building level, because utilities may favor transactive approaches that rely on aggregator models, e.g., a cluster of consumers as opposed to an individual. We demonstrate that the CLSAF model, by virtue of its enhanced feature representation and modest computational resources, can accomplish load forecasting in a multi-family residential building across three spatial granularities (individual apartment/household, floor, and building levels), with an accuracy improvement of up to 25% compared to a persistence model. We propose a data screening technique to characterize time-series electricity-load data. This technique is suitable for integration into a TEN ecosystem and allows one to estimate confidence levels of the load forecasts to optimize computational resources and the risks associated with uncertain forecasts.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1976

Evaluation of transmittance of selected infrared bands

Computer programs were developed for evaluating homogeneous path transmittance with line-by-line and quasi-random band model formulations. Spectral transmittances for some selected bands of different gases (CO, N2O, CO2, H2O) were obtained using these programs. Results of theoretical computations are compared with available experimental measurements. Significant errors are observed in the results obtained from a quasi-random band model formulation, indicating that it is inadequate to meet the accuracy requirements for atmospheric work.

Gupta, S. K.↗
NASA NTRS1977

Oblique orthographic projections and contour plots

Oblique orthographic projections allow model to be viewed in any selected orientation specified by Euler-angle transformation. This transformation resolves coordinate system of model to principal plane on which display is to be plotted.

Giles, G. L.↗
NASA NTRS1978

Lunar mare ridge orientation - Implications for lunar tectonic models

Four circular mare basins were selected for ridge orientation analysis: Crisium, Imbrium, Serenitatis and Tranquillitatis. In each basin a central area was identified in which ridges were neither concentric with basin edges nor seemed to be extensions of significant highland structural trends. Ridge orientations in these central areas and in the remaining marginal areas were measured separately and rose diagrams plotted for each. Rose diagrams of ridge orientations in the four circular mare basins show a narrow dispersion with a statistical average nearly north. Trends of basin margin ridges have a high deviation and are polymodal with maxima in the northwest, north and northeast directions. Mare ridges which display a preferred northern trend result from an east-west compressive stress field.

Fagin, S. W.↗
NASA NTRS2011

GEM-CEDAR Challenge: Comparing Ionospheric Models with Poynting Flux from DMSP Observations

As part to the GEM-CEDAR challenge we are extending the model-data comparisons to electrodynamic in-situ measurements in low-Earth orbit. We use DMSP observations of electric and magnetic fields to compute Poynting Flux values along the satellite track in high latitudes including the auroral zones and the polar cap. Models of the ionosphere that include electrodynamic parameters have been run for five events selected for the GEM-CEDAR modeling challenge for which DMSP data are available for comparison. Combined with a magnetic field model we use the modeled electric fields to compute Poynting Flux and Joule Dissipation values from outputs of CTIPe, TIE-GCM, the ionospheric electrodynamics solvers of the SWMF, LFM and OpenGGCM magnetosphere-ionosphere coupled models, and the Weimer electric field model. The online metrics analysis tool at the Community Coordinated Modeling Center (CCMC) has been updated to handle the analysis of separate short segments of available data (high-latitude sections of the satellite orbit) with model outputs to analyze how well auroral patterns are being reproduced by the models. We present initial results from the new analysis tool in terms of model yields (ratio of the difference between maximum and minimum values of model results to the observation), timing/location errors of local maxima in the inbound and outbound auroral crossings as well as cross-correlations for individual passes. We collect the information for many DMSP passes and present an analysis for model performance during quiet and geomagnetically disturbed time periods using half-orbit integrated values as well.

Rastaetter, Lutz↗
NASA NTRSDate not supplied

Validation of the Corcos Model for the Space Launch System using Unsteady Pressure Sensitive Paint

During atmospheric ascent launch vehicles (LVs) experience large dynamic loads at transonic conditions where aerodynamic buffet is most critical. To estimate buffet loads, coupled loads analyses typically utilize suitable forcing functions, called buffet forcing functions (BFFs). One of the key buffet environment contributors is the turbulent boundary layer (TBL) on the LV outer skin. The TBL-induced fluctuating pressures can be estimated using the widely-accepted Corcos model. In the context of transonic buffet, the performance of this model is not well established, partly because of lack of data. To fill this gap, NASA recently acquired extremely high-spatial-density data for the Space Launch System (SLS) vehicle, using the unsteady pressure sensitive paint (uPSP) optical measurement technique. A methodology is developed for validation of the Corcos model using these unique data, with a focus on the LV-design application. The model hypotheses are verified and the model parameters are empirically tuned. For selected panels on the vehicle, BFF coherence factors are derived based on the Corcos model and the associated panel BFFs are compared to uPSP data. It is shown that the modeled BFFs are in agreement with direct integration of uPSP data, except for regions where pressure fluctuations are spatially nonuniform. In those regions, the Corcos-based BFFs exhibit inherent limitations of BFF estimation methods that rely on discrete pressure measurements.

buffet↗
NASA NTRSDate not supplied

Validation of the Corcos Model for the Space Launch System using Unsteady Pressure Sensitive Paint

During atmospheric ascent launch vehicles (LVs) experience large dynamic loads at transonic conditions where aerodynamic buffet is most critical. To estimate buffet loads, coupled loads analyses typically utilize suitable forcing functions, called buffet forcing functions (BFFs). One of the key buffet environment contributors is the turbulent boundary layer (TBL) on the LV outer skin. The TBL-induced fluctuating pressures can be estimated using the widely-accepted Corcos model. In the context of transonic buffet, the performance of this model is not well established, partly because of lack of data. To fill this gap, NASA recently acquired extremely high-spatial-density data for the Space Launch System (SLS) vehicle, using the unsteady pressure sensitive paint (uPSP) optical measurement technique. A methodology is developed for validation of the Corcos model using these unique data, with a focus on the LV-design application. The model hypotheses are verified and the model parameters are empirically tuned. For selected panels on the vehicle, BFF coherence factors are derived based on the Corcos model and the associated panel BFFs are compared to uPSP data. It is shown that the modeled BFFs are in agreement with direct integration of uPSP data, except for regions where pressure fluctuations are spatially nonuniform. In those regions, the Corcos-based BFFs exhibit inherent limitations of BFF estimation methods that rely on discrete pressure measurements.

buffet↗
NASA NTRS2023

Space Launch System Unsteady Forces Developed from Unsteady-Pressure-Sensitive-Paint–Based Corcos Model Parameters

During atmospheric ascent, launch vehicles (LVs) experience large dynamic loads at transonic conditions where aerodynamic buffet is most critical. To estimate buffet loads, coupled loads analyses typically utilize suitable forcing functions, called buffet forcing functions (BFFs). One of the key buffet environment contributors is the turbulent boundary layer (TBL) on the LV outer skin. The TBL-induced fluctuating pressures can be estimated using the widely-accepted Corcos model. In the context of transonic buffet, the performance of this model is not well established, partly because of lack of data. To fill this gap, NASA recently acquired extremely high-spatial-density data for the Space Launch System (SLS) vehicle, using the unsteady pressure sensitive paint (uPSP) optical measurement technique. A methodology is developed for validation of the Corcos model using these unique data, with a focus on the LV-design application. The model hypotheses are verified and the model parameters are empirically tuned. For selected panels on the vehicle, BFF coherence factors are derived based on the Corcos model and the associated panel BFFs are compared to uPSP data. It is shown that the modeled BFFs are in agreement with direct integration of uPSP data, except for regions where pressure fluctuations are spatially nonuniform. In those regions, the Corcos-based BFFs exhibit inherent limitations of BFF estimation methods that rely on discrete pressure measurements.

buffet↗
DOE OSTI2022

Intergranular oxidation and oxygen transport in Ni-20Cr during exposure to model dry and wet oxidation environments

Selective oxidation is a critical component of the proposed internal oxidation mechanism of stress corrosion cracking (SCC) for Ni-based alloys in primary water reactor (PWR) operation. To isolate and study this process, the binary Ni-20Cr was exposed to pressurized water and a CO/CO2 gas mixture. In both environments, the oxygen potential was kept under the Ni/NiO line to stimulate penetrative intergranular attack. A combination of electron microscopy and atom probe tomography was used to study the nanometer-scale details of the passivation and penetrative intergranular oxidation processes at high-energy grain boundaries. Oxygen transport towards the terminating oxidation front is elucidated with dedicated usage of oxygen isotopic tracer exchange experiments to support classical theories of internal oxidation, revealing preferred oxygen transport paths were visualized with sub-nanometer resolution.

Weiser, Martin↗
NASA NTRS1992

Modeling of SAR returns from a red pine stand

Bright P-band radar returns from red pine forests have been observed on synthetic aperture radar (SAR) images in Bangor, Maine. A plot of red pine trees was selected for the characterization and modeling to understand the cause of the high P-band returns. The red pine stand under study consisted of mature trees. Diameter at breast height (DBH) measurements were made to determine stand density as a function of tree diameter. Soil moisture and bulk density measurements were taken along with ground rough surface profiles. Detailed biomass measurements of the needles, shoots, branches, and trunks were also taken. These site statistics have been used in a distorted Born approximation model of the forest. Computations indicate that the direct-reflected or the double-bounce contributions from the ground are responsible for the high observed P-band returns for HH polarization.

Lang, R. H.↗
DOE OSTI2020

Assessing mean climate change signals in the global CORDEX-CORE ensemble

The new Coordinated Output for Regional Evaluations (CORDEX-CORE) ensemble provides high-resolution, consistent regional climate change projections for the major inhabited areas of the world. It serves as a solid scientific basis for further research related to vulnerability, impact, adaptation and climate services in addition to existing CORDEX simulations. The aim of this study is to investigate and document the climate change information provided by the CORDEX-CORE simulation ensemble, as a part of the World Climate Research Programme (WCRP) CORDEX community. An overview of the annual and monthly mean climate change information in selected regions in different CORDEX domains is presented for temperature and precipitation, providing the foundation for detailed follow-up studies and applications. Initially, two regional climate models (RCMs), REMO and RegCM were used to downscale global climate model output. The driving simulations by AR5 global climate models (AR5-GCMs) were selected to cover the spread of high, medium, and low equilibrium climate sensitivity at a global scale. The CORDEX-CORE ensemble has doubled the spatial resolution compared to the previously existing CORDEX simulations in most of the regions (25 $\,\mathrm {km}$ (0.22 $^{\circ }$ /jats:inline-formula>) versus 50 $\,\mathrm {km}$ (0.44 $^{\circ }$ )) leading to a potentially improved representation of, e.g., physical processes in the RCMs. The analysis focuses on changes in the IPCC physical climate reference regions. The results show a general reasonable representation of the spread of the temperature and precipitation climate change signals of the AR5-GCMs by the CORDEX-CORE simulations in the investigated regions in all CORDEX domains by mostly covering the AR5 interquartile range of climate change signals. The simulated CORDEX-CORE monthly climate change signals mostly follow the AR5-GCMs, although for specific regions they show a different change in the course of the year compared to the AR5-GCMs, especially for RCP8.5, which needs to be investigated further in region specific process studies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Nonlinear aerodynamic modeling using multivariate orthogonal functions

A technique was developed for global modeling of nonlinear aerodynamic coefficients using multivariate orthogonal functions based on the data. Each orthogonal function retained in the model was decomposed into an expansion of ordinary polynomials in the independent variables, so that the final model could be interpreted as selectively retained terms from a multivariable power series expansion. A predicted squared-error metric was used to determine the orthogonal functions to be retained in the model; analytical derivatives were easily computed. The approach was demonstrated on the Z-body axis aerodynamic force coefficient (Cz) wind tunnel data for an F-18 research vehicle which came from a tabular wind tunnel and covered the entire subsonic flight envelope. For a realistic case, the analytical model predicted experimental values of Cz very well. The modeling technique is shown to be capable of generating a compact, global analytical representation of nonlinear aerodynamics. The polynomial model has good predictive capability, global validity, and analytical differentiability.

Morelli, Eugene A.↗
NASA NTRS1989

Constructor selection research

The process of space construction is defined by the construction goal and by the construction system selected to accomplish that goal. The former provides the tasks that must be executed, while the latter provides the capabilities to execute them. This presentation outlines a high-level model of space construction and illustrates the relationship between constructor and task. The construction model is then utilized to develop a preliminary theory of constructor selection. The need for broad models of construction, constructor selection, and constructor management is identified. From this preliminary work it can be concluded that task decomposition is dependent upon both task and constructor; the selection process is separable from the optimization process; and that logical, defensible selection is possible.

Helleckson, Brent↗
DOE OSTI2022

Pyomo.DOE: An open-source package for model-based design of experiments in Python

Predictive mathematical models are a cornerstone of science and engineering. Yet selecting, calibrating, and validating said science-based models often remains an art in practice. Model-based design of experiments (MBDoE) provides a systematic framework to maximize information gain from experiments while minimizing time and resource costs. But MBDoE remains limited to niche application areas, in part because practitioners must integrate expertise in statistics, computational optimization, and modeling. To help reduce this barrier, we introduce Pyomo.DOE, an open-source package for MBDoE. Pyomo.DOE uses a nonlinear sensitivity analysis code k_aug to quickly approximate the Fisher information matrix and leverages a new stochastic programming abstraction. We demonstrate Pyomo.DOE with the first application of MBDoE to fixed-bed breakthrough experiments, which highlights the power of Pyomo.DOE to quantify the value of experimental modifications a priori for large-scale partial differential-algebraic equation (PDAE) models. Here we also provide a mathematical primer on MBDoE targeted at general chemical engineers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Combining artificial intelligence and physics-based modeling to directly assess atomic site stabilities: from sub-nanometer clusters to extended surfaces

The performance of functional materials is dictated by chemical and structural properties of individual atomic sites. In catalysts, for instance, the thermodynamic stability of constituting atomic sites is a key descriptor from which more complex properties, such as molecular adsorption energies and reaction rates, can be derived. In this study, we present a widely applicable machine learning (ML) approach to instantaneously compute the stability of individual atomic sites in structurally and electronically complex nano-materials. Conventionally, we determine such site stabilities using computationally intensive first-principles calculations. With our approach, we predict the stability of atomic sites in sub-nanometer metal clusters of 3–55 atoms with mean absolute errors in the range of 0.11–0.14 eV. To extract physical insights from the ML model, we introduce a genetic algorithm (GA) for feature selection. This algorithm distills the key structural and chemical properties governing the stability of atomic sites in size-selected nanoparticles, allowing for physical interpretability of the models and revealing structure–property relationships. The results of the GA are generally model and materials specific. In the limit of large nanoparticles, the GA identifies features consistent with physics-based models for metal–metal interactions. By combining the ML model with the physics-based model, we predict atomic site stabilities in real time for structures ranging from sub-nanometer metal clusters (3–55 atom) to larger nanoparticles (147 to 309 atoms) to extended surfaces using a physically interpretable framework. Finally, we present a proof of principle showcasing how our approach can determine stable and active nanocatalysts across a generic materials space of structure and composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Version of GCAM-USA used for National Climate Assessment 5, Chapter 5: GCAM-USA-v5.3-IM3-NCA5

Overview GCAM-USA-v5.3-IM3-NCA5 is developed using GCAM-USA-v5.3 as its core, with the impact of the thermodynamic global warming scenario "RCP8.5_hotter" on runoff, heating and cooling degree-hours, and agricultural yield and the SSP5 socioeconomic scenario. These scenarios were produced as part of the Integrated Multisector, Multiscale Modeling (IM3) project and used by National Climate Assessment 5. Detailed Information This software package includes the output dataset, which is located in "output/database_rcp85hotter_ssp5". For reproducibility, the model is setup and ready to run for the selected IM3 scenario "rcp85hotter_ssp5". To execute the model, double click "exe/run-gcam.bat".

Climate Change↗