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Results for “empirical validation”

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 325 records · Page 18

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NASA NTRS1981

Satellite and correlative measurements of the stratospheric aerosol. I An optical model for data conversions

A description is presented of an empirically based model of stratospheric aerosol optical properties (size distributions and refractive indices) and their variations. The need for such a model arose in the data validation and archival programs for two satellite sensors, SAM II and SAGE. These programs require the ability to convert measurements of a given aerosol macroproperty (e.g., volume extinction coefficient, volume backscatter coefficient, particle number or mass per unit volume) to best estimates of other aerosol macroproperties, and to assess quantitatively the uncertainties in the conversion process. The described model provides the information on size distributions, refractive indices and their variations necessary for these tasks, and also defines a procedure for combining the model information with empirical data in a way that facilitates automatic data processing. Although the model was developed for use in the satellite validation and archival programs, it also has proven useful in other studies of stratospheric aerosol.

Russell, P. B.↗

DOE OSTI2021

Discovering the 3D Structure and Dynamics of the Sun-Interstellar Medium System on a Global Scale Los Alamos LDRD Report

We discover the 3D plasma structure of the Sun-interstellar medium interaction region, called the heliosheath. This is enabled by (1) the completion of a full solar cycle of observations of hydrogen energetic neutral atoms (ENAs) emanating from this region and detected by the Los Alamos-led IBEX-Hi ENA imager on NASA’s Interstellar Boundary Explorer (IBEX) mission, and (2) the development of tools to fully exploit all data from the IBEX-Hi imager, leading to a significant increase in the effective instrument sensitivity. This effort prepares us for optimizing the design and data exploitation of the IMAP-Hi imager, the Los Alamos-led next generation imager that will fly on the Interstellar Mapping and Acceleration Probe (IMAP) mission, currently under production. This project realized its goals as evidenced by two main outcomes: (1) The publication of the first-ever empirical 3D map of the interstellar boundary, and (2) the development and release of a new validated ENA data set that has tripled the amount of data available for scientific analysis of the outer heliosphere.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

A Perspective on Traditional and Data Driven Electrochemical Modeling and Analysis

To understand the behavior of electrochemical systems, we need to reduce the dimensionality of the measured current-voltage-time (I-V-t) data by fitting models, thus enabling us to analyze and compare the governing physics. Traditionally, the process for this is an 'expert first' approach: defining the model and its explicit assumptions based on inductive reasoning or empirical observation, fitting small portions of the I-V-t data where assumptions are most valid or carefully designing experiments to enforce key assumptions, and then interpreting the model parameters. However, modern data-driven methods enable a new paradigm: a 'data first' approach, where the latent behaviors governing the system's measured response are identified directly using machine-learning models that optimize both model structure and parameters from the I-V-t data, guaranteeing that the learned model explains as much of the observed system response as possible. After model identification, the model can then be interrogated by an expert to connect observed behaviors with underlying physics. This talk will review several different types of electrochemical analysis (electrochemical impedance, differential voltage-capacity, electrochemical kinetics) and compare the traditional and data-driven methods for analyzing the data.

42 ENGINEERING↗

NASA NTRS1979

Man-machine analysis of translation and work tasks of Skylab films

An objective approach to determine the concurrent validity of computer-graphic models is real time film analysis. This technique was illustrated through the procedures and results obtained in an evaluation of translation of Skylab mission astronauts. The quantitative analysis was facilitated by the use of an electronic film analyzer, minicomputer, and specifically supportive software. The uses of this technique for human factors research are: (1) validation of theoretical operator models; (2) biokinetic analysis; (3) objective data evaluation; (4) dynamic anthropometry; (5) empirical time-line analysis; and (6) consideration of human variability. Computer assisted techniques for interface design and evaluation have the potential for improving the capability for human factors engineering.

Hosler, W. W.↗

NASA NTRSDate not supplied

Learjet Acoustics Flight Test – An Initial Look

The motivation for the work is the need for an improved ability to predict takeoff noise of future commercial supersonic aircraft. The overall objective is to validate as well as improve the conversion of facility scale-model data and semi-empirical jet-noise predictions to flight noise. As a first step, the processing of data and results from an acoustics flight test are described. The next step involves the comparison of the flight acoustic data and complementary rig-test results. This will be presented in future reports. Ultimately, the goal is improved noise-prediction methods for system studies of future commercial supersonic aircraft.

aeroacoustics, jet noise, flyover noise↗

NASA NTRSDate not supplied

Learjet Update Flight and Scale-Model-Nozzle Acoustics Test

The impetus for the work is the need for an improved ability to predict takeoff noise of future supersonic commercial transport aircraft. The overall objective is to validate as well as improve the conversion of facility scale-model data and semi-empirical jet-noise predictions to flight noise. Acoustic data from a Learjet-25 flyover test and a complementary rig-test are compared. The uncertainty in the rig-to-flight transformation is presented. Ultimately, the goal is improved noise-prediction methods for system studies of future commercial supersonic aircraft.

Lennart S Hultgren↗

DOE OSTI2023

Machine-Learning Assisted Identification of Battery Life Models

Predictive battery life models are commonly utilized to extrapolate degradation trends observed during accelerated aging tests for simulation of degradation in real-world applications. Thus, fitting accelerated aging data as accurately as possible and with low uncertainty is crucial for making believable projections of battery lifetime, but it is challenging to identify algebraic expressions that accurately fit multivariate degradation trends. A review of models published in literature reveal some common expressions for fitting calendar aging data, which is only dependent on temperature and state-of-charge, but no consistency across many models for fitting cycle aging data, indicating the need for a statistically rigorous data driven approach for developing empirical models. This talk will describe a machine-learning assisted method for identification of predictive battery life models utilizing bilevel optimization and symbolic regression. Bilevel optimization with cross-validation is used to statistically determine cell- and stress-dependent model parameters, while symbolic regression identifies both linear and multiplicative candidate expressions to predict stress-dependent degradation rates by selecting low-order subsets of features from a generated feature library. Because model expressions are identified empirically, it is crucial to ensure resulting models behave according to physical expectations, so the stability of models for interpolation or extrapolation is interrogated qualitatively through simulation and quantitatively through cross-validation and uncertainty quantification via bootstrap resampling. This model identification approach substantially improves upon models identified purely using expert judgement in terms of both accuracy and uncertainty. Model simulation and validation is then conducted by deriving a state-equation form of the predictive model, enabling simulation of battery aging under dynamic stresses. This enables validation of the predictive battery model on lab-based tests with varying conditions or on drive-cycle or application-cycle testing protocols. Parameter uncertainty can be carried forward into model simulation, giving lifetime estimates and confidence windows for cell- or system-level lifetime. The financial impact of battery model uncertainty can be estimated by incorporating uncertainty into a technoeconomic model.

battery↗

DOE OSTI2022

Verification, Validation, and Uncertainty Quantification in Thermal Hydraulics, Freeman Scholar Lecture (2019)

Engineering problems are generally solved by analytical models or computer codes. These models, in addition to conservation equations, also include many empirical relationships and approximate numerical methods. Each of these components contributes to the uncertainty in the prediction. A systematic approach to judge the applicability of the code to the intended application is needed. It starts from verification of implementation of formulation in the code, identification of important phenomena, finding relevant tests with quantified uncertainty for these phenomena, and validation of the code by comparing predictions with the relevant test data. The relevant tests must address phenomena as expected in the intended application. In case of small size or limited condition tests, the scaling analyses are needed to assess the relevancy of the tests. Finally, a statement of uncertainty in the prediction is needed. Systematic approaches are described to aggregate uncertainties from different components of the code for intended application. Here, verification, validation, and uncertainty quantifications (VVUQs) are briefly described.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

SAM Code Validation on Frictional Pressure Drop through Pebble Beds

The System Analysis Module (SAM) is currently under development at Argonne National Laboratory as a modern system-level modeling and simulation tool for safety analyses of advanced non-light water reactors. This report presents a recent effort to validate the capability of SAM to predict the frictional pressure drop through pebble beds. Selected experimental data were used for code validation, including data from test facilities at Texas A&M University, Missouri University of Science and Technology, and North-West University of South Africa. SAM implements three empirical correlations to predict frictional pressure drop: the classical Ergun correlation; the KTA correlation, which is widely used in high-temperature gas-cooled reactor applications; and the Eisfeld and Schnitzlein correlation, which explicitly considers wall effect. Code validation was performed using all three correlations. For all selected experimental data, the KTA correlation shows the best performance and agrees very well with experimental measurement; the Eisfeld and Schnitzlein correlation, explicitly considering wall effects, shows acceptable accuracy, while there is no evidence that it is better than the KTA correlation; the Ergun correlation, however, over-predicts frictional pressure drop for most selected data points.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Dissolved gas recovery from water using a sidestream hollow-fiber membrane module: First principles model synthesis and steady-state validation

This paper presents a first-principles model for the recovery of dissolved gases from liquids using a sidestream hollow-fiber membrane module. The model avoids the use of new empirical coefficients, thus providing a parametric understanding of the process behavior for future design and optimization of membrane modules. This type of first-principles model could be particularly useful when gas recovery is beneficial to biological or chemical reactions of interest, such as the acetogenesis reactions in two-stage anaerobic digesters. The steady-state behavior of the model was validated against both new experimental data for the recovery of H 2 , CH 4 and H 2 –CH 4 mixtures from pure water, as well as existing published data. The modeled gas recovery predictions agreed with experimental data to an absolute average error of 13%, and an average R value of 0.98. Parametric analysis of mixed-gas recovery suggests possible key transition points in the composition of the recovered gases. For example, at 40 °C, increasing trans-membrane pressure while keeping hydraulic residence time (HRT) under 0.5 s will result in an increase in the ratio of H 2 to CH 4 recovered. Otherwise, increasing trans-membrane pressure will instead decrease the ratio of H 2 to CH 4 recovered. The model has potential to be extended to transient analysis, but has yet to be validated with transient experimental data. Furthermore, this model was successfully implemented in both Python and MATLAB, and provides valuable insights for future net-energy optimization for anaerobic digestion systems with in-situ gas recovery.

Anaerobic Digestion↗

NASA NTRS2003

Angular Distribution Models for Top-of-Atmosphere Radiative Flux Estimation from the Clouds and the Earth's Radiant Energy System Instrument on the Tropical Rainfall Measuring Mission Satellite: Validation - Part II

Top-of-atmosphere (TOA) radiative fluxes from the Clouds and the Earth s Radiant Energy System (CERES) are estimated from empirical angular distribution models (ADMs) that convert instantaneous radiance measurements to TOA fluxes. This paper evaluates the accuracy of CERES TOA fluxes obtained from a new set of ADMs developed for the CERES instrument onboard the Tropical Rainfall Measuring Mission (TRMM). The uncertainty in regional monthly mean reflected shortwave (SW) and emitted longwave (LW) TOA fluxes is less than 0.5 W/sq m, based on comparisons with TOA fluxes evaluated by direct integration of the measured radiances. When stratified by viewing geometry, TOA fluxes from different angles are consistent to within 2% in the SW and 0.7% (or 2 W/sq m) in the LW. In contrast, TOA fluxes based on ADMs from the Earth Radiation Budget Experiment (ERBE) applied to the same CERES radiance measurements show a 10% relative increase with viewing zenith angle in the SW and a 3.5% (9 W/sq m) decrease with viewing zenith angle in the LW. Based on multiangle CERES radiance measurements, 18 regional instantaneous TOA flux errors from the new CERES ADMs are estimated to be 10 W/sq m in the SW and, 3.5 W/sq m in the LW. The errors show little or no dependence on cloud phase, cloud optical depth, and cloud infrared emissivity. An analysis of cloud radiative forcing (CRF) sensitivity to differences between ERBE and CERES TRMM ADMs, scene identification, and directional models of albedo as a function of solar zenith angle shows that ADM and clear-sky scene identification differences can lead to an 8 W/sq m root-mean-square (rms) difference in 18 daily mean SW CRF and a 4 W/sq m rms difference in LW CRF. In contrast, monthly mean SW and LW CRF differences reach 3 W/sq m. CRF is found to be relatively insensitive to differences between the ERBE and CERES TRMM directional models.

Loeb, N. G.↗

DOE OSTI2024

Aboveground Biomass Estimation Using NISAR Simulated ALOS-2 Time Series Data

Aboveground biomass (AGB) is a critical parameter to better understand the global carbon cycle and to develop sustainable forest management. However, a large uncertainty prevails. L-band SAR data have demonstrated strong potential to accurately retrieve AGB over low-biomass regions (<100 Mg ha-1). The upcoming NASA-ISRO Synthetic Aperture Radar mission will collect data at L- and S-band over earth’s landmass with a repeat period of 12 days, allowing us to have ample data for monitoring biomass and its dynamics. One of the key science requirements of the mission is to produce annual AGB maps at 1-ha resolution with RMS accuracy of 20 Mg/ha for 80 percentage of area over low-biomass regions in Calibration/Validation sites. The NISAR biomass algorithm will generate AGB maps based on the parameterization of semi-empirical model along with NISAR time-series dual pol data (HH and HV). To calibrate and validate the model for mission requirements, the mission will use reference estimates of AGB produced from ground inventory plots and airborne LiDAR data collected over selected sites distributed across different global ecoregions. This paper presents the initial results of the calibration/validation of the NISAR AGB retrieval algorithm over the Lenoir Landing (LENO), Alabama, USA site using NISAR simulated ALOS-2 time series data. Five multi-temporal dual-pol HH and HV NISAR Simulated ALOS 2 data collections were used as input to assess the performance of the model. The model AGB retrieval results shows that the NISAR model was able to achieve RMS accuracy within 20 Mg/ha.

Ramachandran, Naveen [Jet Propulsion Laboratory, C↗

NASA NTRS1991

The use of analytical models in human-computer interface design

Some of the many analytical models in human-computer interface design that are currently being developed are described. The usefulness of analytical models for human-computer interface design is evaluated. Can the use of analytical models be recommended to interface designers? The answer, based on the empirical research summarized here, is: not at this time. There are too many unanswered questions concerning the validity of models and their ability to meet the practical needs of design organizations.

Gugerty, Leo↗

NASA NTRS1997

Combined Numerical/Analytical Perturbation Solutions of the Navier-Stokes Equations for Aerodynamic (Ejector Nozzle) Flows

In spite of the rapid advances in both scalar and parallel computational tools, the large number and breadth of variables involved in aerodynamic systems make the use of parabolized or even boundary layer fluid flow models impractical for both preliminary design and inverse design problems. Given this restriction, we have concluded that reduced or approximate models are an important family of tools for design purposes. This study of a combined perturbation/numerical modeling methodology with an application to ejector-mixer nozzles (shown schematically in the following figure) is nearing completion. The work is being funded by a grant from the NASA Lewis Research Center to Texas A&M University. These ejector-mixer nozzle models are designed to be of use to the High Speed Civil Transport Program and may be adopted by both NASA and industry. A computer code incorporating the ejector-mixer models is under development. This code, the Differential Reduced Ejector/Mixer Analysis (DREA), can be run fast enough to be used as a subroutine or to be called by a design optimization routine. Simplified conservation equations--x-momentum, energy, and mass conservation--are used to define the model. Unlike other preliminary design models, DREA requires minimal empirical input and includes vortical mixing and a fully compressible formulation among other features. DREA is being validated by comparing it with results obtained from open literature and proprietary industry data. Preliminary results for a subsonic ejector and a supersonic ejector are shown. In addition, dedicated experiments have been performed at Texas A&M. These experiments use a hydraulic/gas flow analog to provide information about the inviscid mixing interface structure. Final validation and documentation of this work is expected by May of 1997. However, preliminary versions of DREA can be expected in early 1997. In summary, DREA provides a sufficiently detailed and realistic ejector-mixer nozzle model at a computational cost compatible with preliminary design applications.

DeChant, Lawrence J.↗

NASA NTRS2012

Experimental Validation of a Forward Looking Interferometer for Detection of Clear Air Turbulence due to Mountain Waves

The Forward-Looking Interferometer (FLI) is an airborne sensor concept for detection and estimation of potential atmospheric hazards to aircraft. The FLI concept is based on high-resolution Infrared Fourier Transform Spectrometry technologies that have been developed for satellite remote sensing. The FLI is being evaluated for its potential to address multiple hazards, during all phases of flight, including clear air turbulence, volcanic ash, wake vortices, low slant range visibility, dry wind shear, and icing. In addition, the FLI is being evaluated for its potential to detect hazardous runway conditions during landing, such as wet or icy asphalt or concrete. The validation of model-based instrument and hazard simulation results is accomplished by comparing predicted performance against empirical data. In the mountain lee wave data collected in the previous FLI project, the data showed a damped, periodic mountain wave structure. The wave data itself will be of use in forecast and nowcast turbulence products such as the Graphical Turbulence Guidance and Graphical Turbulence Guidance Nowcast products. Determining how turbulence hazard estimates can be derived from FLI measurements will require further investigation.

Schaffner, Philip R.↗

NASA NTRS2018

Aeroacoustic Validation of Installed Low Noise Propulsion for NASA's N+2 Supersonic Airliner

An aeroacoustic test was conducted at NASA Glenn Research Center on an integrated propulsion system designed to meet noise regulations of ICAO Chapter 4 with 10EPNdB cumulative margin. The test had two objectives: to demonstrate that the aircraft design did meet the noise goal, and to validate the acoustic design tools used in the design. Variations in the propulsion system design and its installation were tested and the results compared against predictions. Far-field arrays of microphones measured the acoustic spectral directivity, which was transformed to full scale as noise certification levels. Phased array measurements confirmed that the shielding of the installation model adequately simulated the full aircraft and provided data for validating RANS-based noise prediction tools. Particle image velocimetry confirmed that the flow field around the nozzle on the jet rig mimicked that of the full aircraft and produced flow data to validate the RANS solutions used in the noise predictions. The far-field acoustic measurements confirmed the empirical predictions for the noise. Results provided here detail the steps taken to ensure accuracy of the measurements and give insights into the physics of exhaust noise from installed propulsion systems in future supersonic vehicles.

aeroacousti↗

NASA NTRS2018

Aeroacoustic Validation of Installed Low Noise Propulsion for NASA's N+2 Supersonic Airliner

supersonic↗

NASA NTRS2022

Thermospheric Neutral Density Variation During the “SpaceX” Storm: Implications From Physics-Based Whole Geospace Modeling

The Starlink satellites launched on 3 February 2022 were lost before they fully arrived in their designated orbits. The loss was attributed to two moderate geomagnetic storms that occurred consecutively on February 3-4. We investigate the thermospheric neutral mass density variation during these storms with the Multiscale Atmosphere-Geospace Environment (MAGE) model, a first-principles, fully coupled geospace model. Simulated neutral density enhancements are validated by Swarm satellite measurements at the altitude of 400-500 km. Comparison with standalone TIEGCM and empirical NRLMSIS 2.0 and DTM-2012 models suggests better performance by MAGE in predicting the maximum density enhancement and resolving the gradual recovery process. Along the Starlink satellite orbit in the middle thermosphere (∼ 200 km altitude), MAGE predicts up to 150% density enhancement near the second storm peak while standalone TIEGCM, NRLMSIS 2.0 and DTM-2012 suggest only ∼ 50% increase. MAGE also suggests altitudinal, longitudinal, and latitudinal variability of storm-time percentage density enhancement due to height dependent Joule heating deposition per unit mass, thermospheric circulation changes, and travelling atmospheric disturbances. This study demonstrates that a moderate storm can cause substantial density enhancement in the middle thermosphere. Thermospheric mass density strongly depends on the strength, timing, and location of high-latitude energy input, which cannot be fully reproduced with empirical models. A physics-based, fully coupled geospace model that can accurately resolve the high-latitude energy input and its variability is critical to modeling the dynamic response of thermospheric neutral density during storm time.

Starlink↗