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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Functional Fault Modeling Conventions and Practices for Real-Time Fault Isolation

The purpose of this paper is to present the conventions, best practices, and processes that were established based on the prototype development of a Functional Fault Model (FFM) for a Cryogenic System that would be used for real-time Fault Isolation in a Fault Detection, Isolation, and Recovery (FDIR) system. The FDIR system is envisioned to perform health management functions for both a launch vehicle and the ground systems that support the vehicle during checkout and launch countdown by using a suite of complimentary software tools that alert operators to anomalies and failures in real-time. The FFMs were created offline but would eventually be used by a real-time reasoner to isolate faults in a Cryogenic System. Through their development and review, a set of modeling conventions and best practices were established. The prototype FFM development also provided a pathfinder for future FFM development processes. This paper documents the rationale and considerations for robust FFMs that can easily be transitioned to a real-time operating environment.

Ferrell, Bob↗
NASA NTRS1993

Evaluation of two January - June 1992 ERS-1 AMI wind vector data sets

A Jan. - Jun. 1992 10 m height wind vector field was computed with the CMOD2 model function. Freilich and Dunbar used ESA measurements of AMI (Active Microwave Instrument) sigma-naught to derive a refined model function and to produce an alternate Jan. - Jun. 1992 10 m height wind vector field, named FD data. The ESA and FD model functions and algorithms were substantially different. The FD wind vectors were in better agreement with the climatological mean wind field and with moored buoy wind measurements. The average correlation coefficients between monthly mean and daily averaged FD and moored buoy matchups of the Cartesian wind components were 0.84 and 0.74, respectively. The average root mean square differences between the monthly mean and daily averaged FD and moored buoy matchups of the Cartesian wind components were 1.25 and 3.0 m/s, respectively.

Halpern, D.↗
DOE OSTI2021

Landmark-embedded Gaussian process with applications for functional data modeling

In practice, we often need to infer the value of a target variable from functional observation data. A challenge in this task is that the relationship between the functional data and the target variable is very complex: the target variable not only influences the shape but also the location of the functional data. In addition, due to the uncertainties in the environment, the relationship is probabilistic, that is, for a given fixed target variable value, we still see variations in the shape and location of the functional data. To address this challenge, we present a landmark-embedded Gaussian process model that describes the relationship between the functional data and the target variable. A unique feature of the model is that landmark information is embedded in the Gaussian process model so that both the shape and location information of the functional data are considered simultaneously in a unified manner. Gibbs-Metropolis-Hasting algorithm is used for model parameters estimation and target variable inference. The performance of the proposed framework is evaluated by extensive numerical studies and a case study of nano-sensor calibration.

42 ENGINEERING↗
NASA NTRS1998

Global Nonlinear Parametric Modeling with Application to F-16 Aerodynamics

A global nonlinear parametric modeling technique is described and demonstrated. The technique uses multivariate orthogonal modeling functions generated from the data to determine nonlinear model structure, then expands each retained modeling function into an ordinary multivariate polynomial. The final model form is a finite multivariate power series expansion for the dependent variable in terms of the independent variables. Partial derivatives of the identified models can be used to assemble globally valid linear parameter varying models. The technique is demonstrated by identifying global nonlinear parametric models for nondimensional aerodynamic force and moment coefficients from a subsonic wind tunnel database for the F-16 fighter aircraft. Results show less than 10% difference between wind tunnel aerodynamic data and the nonlinear parameterized model for a simulated doublet maneuver at moderate angle of attack. Analysis indicated that the global nonlinear parametric models adequately captured the multivariate nonlinear aerodynamic functional dependence.

Morelli, Eugene A.↗
NASA NTRS1997

Global Nonlinear Parametric Modeling with Application to F-16 Aerodynamics

A global nonlinear parametric modeling technique is described and demonstrated. The technique uses multivariate orthogonal modeling functions generated from the data to determine nonlinear model structure, then expands each retained modeling function into an ordinary multivariate polynomial. The final model form is a finite multivariate power series expansion for the dependent variable in terms of the independent variables. Partial derivatives of the identified models can be used to assemble globally valid linear parameter varying models. The technique is demonstrated by identifying global nonlinear parametric models for nondimensional aerodynamic force and moment coefficients from a subsonic wind tunnel database for the F-16 fighter aircraft. Results show less than 10% difference between wind tunnel aerodynamic data and the nonlinear parameterized model for a simulated doublet maneuver at moderate angle of attack. Analysis indicated that the global nonlinear parametric models adequately captured the multivariate nonlinear aerodynamic functional dependence.

Morelli, Eugene A.↗
DOE OSTI2016

Testing a land model in ecosystem functional space via a comparison of observed and modeled ecosystem flux responses to precipitation regimes and associated stresses in a Central U.S. forest: Test Model in Ecosystem Functional Space

Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitation regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.

58 GEOSCIENCES↗
DOE OSTI2022

Dynamic Rupture Modeling of the 1999 Chi-Chi, Taiwan Earthquake Using 3DFinite Element Method. Sensitivity Analysis of Slip Rate Function to Model Parameters of Crustal Weak-Zone

The main objective of this study was the dynamic rupture modeling of the M7.3 1999 Chi-Chi, Taiwan earthquake. The purpose of the numerical modeling was two folded. First, using models of rupture dynamics, derive kinematic rupture characteristics, including spatial and temporal variations of the slip rate time history and rupture speed, in the long-period ground motion generation area (LMGA), strong motion generation areas (SMGAs) and background fault area for a thrust shallow rupture. Second, investigate the sensitivity of source time function characteristics in the LMGA and SMGA areas to model parameterization of low-velocity weak zone, such as thickness and shear wave velocity.

58 GEOSCIENCES↗
NASA NTRS1983

Advanced single permanent magnet axipolar ironless stator ac motor for electric passenger vehicles

A program was conducted to design and develop an advanced-concept motor specifically created for propulsion of electric vehicles with increased range, reduced energy consumption, and reduced life-cycle costs in comparison with conventional systems. The motor developed is a brushless, dc, rare-earth cobalt, permanent magnet, axial air gap inductor machine that uses an ironless stator. Air cooling is inherent provided by the centrifugal-fan action of the rotor poles. An extensive design phase was conducted, which included analysis of the system performance versus the SAE J227a(D) driving cycle. A proof-of-principle model was developed and tested, and a functional model was developed and tested. Full generator-level testing was conducted on the functional model, recording electromagnetic, thermal, aerodynamic, and acoustic noise data. The machine demonstrated 20.3 kW output at 1466 rad/s and 160 dc. The novel ironless stator demonstated the capability to continuously operate at peak current. The projected system performance based on the use of a transistor inverter is 23.6 kW output power at 1466 rad/s and 83.3 percent efficiency. Design areas of concern regarding electric vehicle applications include the inherently high windage loss and rotor inertia.

Beauchamp, E. D.↗
NASA NTRS1997

Work Functions for Models of Scandate Surfaces

The electronic structure, surface dipole properties, and work functions of scandate surfaces have been investigated using the fully relativistic scattered-wave cluster approach. Three different types of model surfaces are considered: (1) a monolayer of Ba-Sc-O on W(100), (2) Ba or BaO adsorbed on Sc2O3 + W, and (3) BaO on SC2O3 + WO3. Changes in the work function due to Ba or BaO adsorption on the different surfaces are calculated by employing the depolarization model of interacting surface dipoles. The largest work function change and the lowest work function of 1.54 eV are obtained for Ba adsorbed on the Sc-O monolayer on W(100). The adsorption of Ba on Sc2O3 + W does not lead to a low work function, but the adsorption of BaO results in a work function of about 1.6-1.9 eV. BaO adsorbed on Sc2O3 + WO3, or scandium tungstates, may also lead to low work functions.

Mueller, Wolfgang↗
DOE OSTI2022

Can Cooling and Heating Functions Be Modeled with Homogeneous Radiation Fields?

Abstract Cooling and heating functions describe how radiative processes impact the thermal state of a gas as a function of its temperature and other physical properties. In a most general case the functions depend on the detailed distributions of ionic species and on the radiation spectrum. Hence, these functions may vary on a very wide range of spatial and temporal scales. In this paper, we explore cooling and heating functions between 5 ≤ z ≤ 10 in simulated galaxies from the Cosmic Reionization On Computers project. We compare three functions: (1) the actual cooling and heating rates of hydrodynamic cells as a function of cell temperature, (2) the median cooling and heating functions computed using median interstellar medium (ISM) properties (median ISM), and (3) the median of the cooling and heating functions of all gas cells (instantaneous). We find that the median ISM and instantaneous approaches to finding a median cooling and heating function give identical results within the spread due to cell-to-cell variation. However, the actual cooling (heating) rates experienced by the gas at different temperatures in the simulations do not correspond to either summarized cooling (heating) functions. In other words, the thermodynamics of the gas in the simulations cannot be described by a single set of a cooling plus a heating function with a spatially constant radiation field that could be computed with common tools, such as CLOUDY.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1981

Modeling procedures for handling qualities evaluation of flexible aircraft

This paper presents simplified modeling procedures to evaluate the impact of flexible modes and the unsteady aerodynamic effects on the handling qualities of Supersonic Cruise Aircraft (SCR). The modeling procedures involve obtaining reduced order transfer function models of SCR vehicles, including the important flexible mode responses and unsteady aerodynamic effects, and conversion of the transfer function models to time domain equations for use in simulations. The use of the modeling procedures is illustrated by a simple example.

Govindaraj, K. S.↗
NASA NTRS1976

Probabilistic and deterministic aspects of linear estimation in geodesy

Recent advances in observational techniques related to geodetic work (VLBI, laser ranging) make it imperative that more consideration should be given to modeling problems. Uncertainties in the effect of atmospheric refraction, polar motion and precession-nutation parameters, cannot be dispensed with in the context of centimeter level geodesy. Even physical processes that have generally been previously altogether neglected (station motions) must now be taken into consideration. The problem of modeling functions of time or space, or at least their values at observation points (epochs) is explored. When the nature of the function to be modeled is unknown. The need to include a limited number of terms and to a priori decide upon a specific form may result in a representation which fails to sufficiently approximate the unknown function. An alternative approach of increasing application is the modeling of unknown functions as stochastic processes.

Dermanis, A.↗
DOE OSTI2025

EPR and 31 P ENDOR Characterization of Pseudo-Jahn–Teller Dynamics and N 2 Activation in Functional Nitrogenase Models, P 3 E M(N 2 ) (M = Fe, Co; E = Si, B, C)

Here, the nominally trigonal, pseudo-Jahn-Teller (PJT)-active, S = ½ N 2 -bound transition-metal complexes, P 3 E M(N 2 ), M = Fe, Co, with three in-plane phosphine-ligands and axial donors, E = Si, B, C, include functional nitrogenase models that catalyze reduction of N 2 to NH 3 . We applied EPR, 31 P ENDOR spectroscopy and DFT computations to characterize the PJT-induced distortions of four selected P 3 E M(N 2 ), revealing how the metal-ion and axial ligand E together tune both PJT dynamics and N 2 activation for reduction. Comparisons reveal an unrecognized correlation between PJT distortion, M-E bond elasticity, and N 2 activation, providing guidelines for designing bioinspired N 2 -reduction catalysts.

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

Density-Functional-Theory Modeling of Cation Diffusion in Bulk La 1 - x Sr x MnO 3 ± δ ( x = 0.0 – 0.25 ) for Solid-Oxide Fuel-Cell Cathodes

In this work, the A - and B -site cation migration pathways involving defect complexes in bulk La 1-x Sr x MnO 3±δ (LSM) at x = 0.0-0.25 are investigated based on density-functional-theory modeling for solid-oxide fuel-cell (SOFC) cathode applications. We propose a dominant A -site cation migration mechanism which involves an A -site cation (e.g., La$x\atop{A}$) V A "' of a V A "' -V B "' cluster, where La$x\atop{A}$, V A "' and V B "' are La 3+ , A-site vacancy, and B-site vacancy in bulk LSM, respectively, and V A "' -V B "' is the first nearest-neighbor V A "' and V B "' pair. This hop exhibits an approximately 1.6-eV migration barrier as compared to approximately 2.9 eV of the La$x\atop{A}$ hop into a V A "'. This decrease in the cation migration barrier is attributed to the presence of the V B "' relieving the electrostatic repulsion and steric constraints to the migrating A-site cations in the transition-state image configurations.

03 NATURAL GAS↗
NASA NTRS2002

A Parametric Study of Fine-scale Turbulence Mixing Noise

The present paper is a study of aerodynamic noise spectra from model functions that describe the source. The study is motivated by the need to improve the spectral shape of the MGBK jet noise prediction methodology at high frequency. The predicted spectral shape usually appears less broadband than measurements and faster decaying at high frequency. Theoretical representation of the source is based on Lilley's equation. Numerical simulations of high-speed subsonic jets as well as some recent turbulence measurements reveal a number of interesting statistical properties of turbulence correlation functions that may have a bearing on radiated noise. These studies indicate that an exponential spatial function may be a more appropriate representation of a two-point correlation compared to its Gaussian counterpart. The effect of source non-compactness on spectral shape is discussed. It is shown that source non-compactness could well be the differentiating factor between the Gaussian and exponential model functions. In particular, the fall-off of the noise spectra at high frequency is studied and it is shown that a non-compact source with an exponential model function results in a broader spectrum and better agreement with data. An alternate source model that represents the source as a covariance of the convective derivative of fine-scale turbulence kinetic energy is also examined.

Khavaran, Abbas↗
DOE OSTI2019

Machine-learning error models for approximate solutions to parameterized systems of nonlinear equations

Here, this work proposes a machine-learning framework for constructing statistical models of errors incurred by approximate solutions to parameterized systems of nonlinear equations. These approximate solutions may arise from early termination of an iterative method, a lower-fidelity model, or a projection-based reduced-order model, for example. The proposed statistical model comprises the sum of a deterministic regression-function model and a stochastic noise model. The method constructs the regression-function model by applying regression techniques from machine learning (e.g., support vector regression, artificial neural networks) to map features (i.e., error indicators such as sampled elements of the residual) to a prediction of the approximate-solution error. The method constructs the noise model as a mean-zero Gaussian random variable whose variance is computed as the sample variance of the approximate-solution error on a test set; this variance can be interpreted as the epistemic uncertainty introduced by the approximate solution. This work considers a wide range of feature-engineering methods, data-set-construction techniques, and regression techniques that aim to ensure that (1) the features are cheaply computable, (2) the noise model exhibits low variance (i.e., low epistemic uncertainty introduced), and (3) the regression model generalizes to independent test data. Finally, numerical experiments performed on several computational-mechanics problems and types of approximate solutions demonstrate the ability of the method to generate statistical models of the error that satisfy these criteria and significantly outperform more commonly adopted approaches for error modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Scalable Volume Visualization for Big Scientific Data Modeled by Functional Approximation

Considering the challenges posed by the space and time complexities in handling extensive scientific volumetric data, various data representations have been developed for the analysis of large-scale scientific data. Multivariate functional approximation (MFA) is an innovative data model designed to tackle substantial challenges in scientific data analysis. It computes values and derivatives with high-order accuracy throughout the spatial domain, mitigating artifacts associated with zero- or first-order interpolation. However, the slow query time through MFA makes it less suitable for interactively visualizing a large MFA model. In this work, we develop the first scalable interactive volume visualization pipeline, MFA-DVV, for the MFA model encoded from large-scale datasets. Our method achieves low input latency through distributed architecture, and its performance can be further enhanced by utilizing a compressed MFA model while still maintaining a high-quality rendering result for scientific datasets. We conduct comprehensive experiments to show that MFA-DVV can decrease the input latency and achieve superior visualization results for big scientific data compared with existing approaches.

big scientific dataset↗