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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Metabolic rate control during extravehicular activity simulations and measurement techniques during actual EVAS

A description of the methods used to control and measure metabolic rate during ground simulations is given. Work levels attained at the Space Environment Simulation Laboratory are presented. The techniques and data acquired during ground simulations are described and compared with inflight procedures. Data from both the Skylab and Apollo Program were utilized and emphasis is given to the methodology, both in simulation and during flight. The basic techniques of work rate assessment are described. They include oxygen consumption, which was useful for averages over long time periods, heart rate correlations based on laboratory calibrations, and liquid cooling garment temperature changes. The relative accuracy of these methods as well as the methods of real-time monitoring at the Mission Control Center are discussed. The advantages and disadvantages of each of the metabolic measurement techniques are discussed. Particular emphasis is given to the problem of utilizing oxygen decrement for short time periods and heart rate at low work levels. A summary is given of the effectiveness of work rate control and measurements; and current plans for future EVA monitoring are discussed.

David J. Horrigan↗
NASA NTRS1977

The finite element method in computational fluid mechanics

A finite element solution algorithm is established for a general statement of the time-averaged Navier-Stokes equations governing multi-dimensional turbulent flows. Numerical results are presented which evaluate factors affecting solution accuracy for a broad spectrum of linear and non-linear problem classes.

Baker, A. J.↗
NASA NTRS1985

Surface radiation in the tropical Pacific

Monthly surface radiative fluxes have been calculated for the tropical Pacific between January 1970 and February 1978, using a radiative transfer parameterization. The radiative transfer parameterization included detailed treatments of the molecular and droplet absorptions, and surface and cloud reflections. The input data used in the calculations were obtained from the National Climatic Center (NCC), the National Center for Atmospheric Research (NCAR), and from the University of Hawaii. The results show that the distribution of surface radiation closely follows the distribution of cloudiness, and, to a lesser degree, humidity. The rms net error in the surface radiation estimates was about 15 W per sq m, with the largest contribution from uncertainties in the cloud cover and humidity data. The sensitivity of surface radiation parameterizations to input data errors is discussed, and some accuracy requirements for satellite retrievals of atmospheric and cloud parameters are proposed. The calculations are presented in the annually-averaged maps of surface radiation variations.

Chou, M.-D.↗
NASA NTRS1988

Fluctuations and massive separation in three-dimensional shock-wave/boundary-layer interactions

Shock-wave unsteadiness was observed in rapidly compressed supersonic turbulent boundary layer flows with significant separation. A Mach 2.85 shock-wave/turbulent boundary layer flow was set up over a series of cylinder-flare bodies in the High Reynolds Number Channel 1. The transition from fully attached to fully separated flow was studied using axisymmetric flares with increasing compression angles. In the second phase, the 30 deg flare was inclined relative to the cylinder axis, so that the effect on a separated flow of increasing 3 dimensionality could be observed. Two 3-D separated cases are examined. A simple conditional sampling technique is applied to the data to group them according to an associated shock position. Mean velocities and turbulent kinetic energies, computed from the conditionally samples data, are compared to those from the unsorted data and to computed values. Three basic questions were addressed: can conditional sampling be used to provide snapshots of the flow; are averaged turbulence quantities dominated by the bimodal nature of the interaction; and is the shock unsteadiness really important to computational accuracy.

Kussoy, M. I.↗
NASA NTRS1988

Fluctuations and massive separation in three-dimensional shock-wave/boundary-layer interactions

Shock-wave unsteadiness was observed in rapidly compressed supersonic turbulent boundary layer flows with significant separation. A Mach 2.85 shock-wave/turbulent boundary layer flow was set up over a series of cylinder-flare bodies in the High Reynolds Number Channel 1. The transition from fully attached to fully separated flow was studied using axisymmetric flares with increasing compression angles. In the second phase, the 30-deg flare was inclined relative to the cylinder axis, so that the effect on a separated flow of increasing three-dimensionality could be observed. Two 3-D separated cases are examined. A simple conditional sampling technique is applied to the data to group them according to an associated shock position. Mean velocities and turbulent kinetic energies, computed from the conditionally sampled data, are compared to those from the unsorted data and to computed values. Three basic questions were addressed: can conditional sampling be used to provide snapshots of the flow; are averaged turbulence quantities dominated by the bimodal nature of the interaction; and is the shock unsteadiness really important to computational accuracy.

Kussoy, M. I.↗
NASA NTRS1990

The effect of small-scale roughness on the main flow profile of a laminar boundary layer

The profile distortion due to a single roughness element, to two such elements, and to many elements is investigated. Signal-averaging of the velocity difference due to the roughness being alternately present or absent is employed in order to improve accuracy. The primary objective of examining the distributed-roughness profiles for any evidence of instability-enhancing form is not met, but the results are reconsidered, and relevant hypotheses and suggestions are presented. It is noted that the reason for not meeting the objective of estimating Tollmien-Schlichting amplification from rough-wall profiles is that much of the distortion occurs close to the wall and below the element tops.

Kendall, James M., Jr.↗
NASA NTRS1993

Infrared radiation parameterizations for the minor CO2 bands and for several CFC bands in the window region

Fast and accurate parameterizations have been developed for the transmission functions of the CO2 9.4- and 10.4-micron bands, as well as the CFC-11, CFC-12, and CFC-22 bands located in the 8-12-micron region. The parameterizations are based on line-by-line calculations of transmission functions for the CO2 bands and on high spectral resolution laboratory measurements of the absorption coefficients for the CFC bands. Also developed are the parameterizations for the H2O transmission functions for the corresponding spectral bands. Compared to the high-resolution calculations, fluxes at the tropopause computed with the parameterizations are accurate to within 10 percent when overlapping of gas absorptions within a band is taken into account. For individual gas absorption, the accuracy is of order 0-2 percent. The climatic effects of these trace gases have been studied using a zonally averaged multilayer energy balance model, which includes seasonal cycles and a simplified deep ocean. With the trace gas abundances taken to follow the Intergovernmental Panel on Climate Change Low Emissions 'B' scenario, the transient response of the surface temperature is simulated for the period 1900-2060.

Kratz, David P.↗
NASA NTRS2018

A Global Spatially Contiguous Solar-Induced Fluorescence (CSIF) Dataset Using Neural Networks

Satellite-retrieved solar-induced chlorophyll fluorescence (SIF) has shown great potential to monitor the photosynthetic activity of terrestrial ecosystems. However, several issues, including low spatial and temporal resolution of the gridded datasets and high uncertainty of the individual retrievals, limit the applications of SIF. In addition, inconsistency in measurement footprints also hinders the direct comparison between gross primary production (GPP) from eddy covariance (EC) flux towers and satellite-retrieved SIF. In this study, by training a neural network (NN) with surface reflectance from the MODerate-resolution Imaging Spectroradiometer (MODIS) and SIF from Orbiting Carbon Observatory-2 (OCO-2), we generated two global spatially contiguous SIF (CSIF) datasets at moderate spatiotemporal (0.05° 4-day) resolutions during the MODIS era, one for clear-sky conditions (2000–2017) and the other one in all-sky conditions (2000–2016). The clear-sky instantaneous CSIF (CSIF(sub clear-inst)) shows high accuracy against the clear-sky OCO-2 SIF and little bias across biome types. The all-sky daily average CSIF (CSIF(sub all-daily)) dataset exhibits strong spatial, seasonal and interannual dynamics that are consistent with daily SIF from OCO-2 and the Global Ozone Monitoring Experiment-2 (GOME-2). An increasing trend (0.39 %) of annual average CSIFall-daily is also found, confirming the greening of Earth in most regions. Since the difference between satellite-observed SIF and CSIF is mostly caused by the environmental down-regulation on SIF(sub yield), the ratio between OCO-2 SIF and CSIF(sub clear-inst) can be an effective indicator of drought stress that is more sensitive than the normalized difference vegetation index and enhanced vegetation index. By comparing CSIF(sub all-daily) with GPP estimates from 40 EC flux towers across the globe, we find a large cross-site variation (c.v. = 0.36) of the GPP–SIF relationship with the highest regression slopes for evergreen needleleaf forest. However, the cross-biome variation is relatively limited (c.v. = 0.15). These two contiguous SIF datasets and the derived GPP–SIF relationship enable a better understanding of the spatial and temporal variations of the GPP across biomes and climate.

Zhang, Yao↗
DOE OSTI2020

Accuracy of volumetric flow rate inflow/outflow measurement by integrating PIV velocity fields

In this paper, the usefulness of planar Particle Image Velocimetry (PIV) measurements to determine the volumetric flow rate from a rectangular or round jet exit is assessed. Both two-component PIV (2C–PIV) and through-plane three-component (3C) stereo PIV (SPIV) data sets were acquired at the exit of a turbulent, rectangular nozzle and a round nozzle with Reynolds numbers between 10 000 and 100 000. The PIV data sets were processed using a variety of algorithms. The time-averaged results were then spatially integrated across the jet exits and compared to a calibrated flow meter. Recommendations for each method are developed and discussed with potential drawbacks. The accuracy of the measurement was found to be a weak function of the Reynolds number of the flow. Furthermore, two-component PIV was found to underestimate the volumetric flow rate by 1%–4% depending on the integration scheme and SPIV underestimated volumetric flow rate by 2%.

47 OTHER INSTRUMENTATION↗
NASA NTRSDate not supplied

Exploring the Accuracy of RANS Simulations for Mars Entry Vehicles

Accurate yet inexpensive predictions of aerodynamic coefficients for Mars entry vehicles have remained a consistent challenge over the past five decades. Below Mach 6, drag on the backshell becomes significant and must be accurately predicted. Steady Reynolds-averaged Navier-Stokes (RANS) models are commonly used, despite their poor predictions of backshell pressure. While scale-resolving simulations have shown promise in the past decade, there is still a need for cheap, accurate RANS predictions for large aerodynamic databases. The Mars Science Laboratory (MSL) is used as a case study to examine predictive accuracy and known shortcomings for RANS predictions of Mars entry vehicles. Several different grid generation techniques are compared, including a comparison between prismatic boundary layer grids and fully unstructured, tetrahedral grids. Comparisons are made to experimental data for Mach 2.5, 3.5, and 4.5. The accuracy of predicted aerodynamic coefficients is examined. Overpredictions in axial force and drag are explained by a closer examination of the surface pressure. These findings document sensitivities and best practices for future RANS database development of Mars entry vehicles.

RANS↗
NASA NTRSDate not supplied

Exploring the Accuracy of RANS Simulations for Mars Entry Vehicles

Accurate yet inexpensive predictions of aerodynamic coefficients for Mars entry vehicles have remained a consistent challenge over the past five decades. Below Mach 6, drag on the backshell becomes significant and must be accurately predicted. Steady Reynolds-averaged Navier-Stokes (RANS) models are commonly used, despite their poor predictions of backshell pressure. While scale-resolving simulations have shown promise in the past decade, there is still a need for cheap, accurate RANS predictions for large aerodynamic databases. The Mars Science Laboratory (MSL) is used as a case study to examine predictive accuracy and known shortcomings for RANS predictions of Mars entry vehicles. Several different grid generation techniques are compared, including a comparison between prismatic boundary layer grids and fully unstructured, tetrahedral grids. Comparisons are made to experimental data for Mach 2.5, 3.5, and 4.5. The accuracy of predicted aerodynamic coefficients is examined. Overpredictions in axial force and drag are explained by a closer examination of the surface pressure. These findings document sensitivities and best practices for future RANS database development of Mars entry vehicles.

CFD↗
NASA NTRS2018

Blind Study Validating Parametric Costing Tools PRICE TruePlanning and SEER-H for NASA Science Missions

Two of the primary parametric costing tools used to estimate the development and production cost of future spacecraft hardware are PRICE TruePlanning - Space Missions Catalog by PRICE Systems, and SEER-H by Galorath. These are standard tools used by NASA and industry to estimate the cost of new aerospace hardware. However, no independent verification of the accuracy of these tools is publicly available. Both PRICE Systems and Galorath have completed internal validation studies of their parametric cost estimating tools; however, they only provided the results of the studies and did not detail the exact methods used to perform the validation. In the present study, cost estimators used PRICE TruePlanning and SEER-H to estimate the cost of twelve different past NASA science missions. The estimators were prevented from knowing the actual cost of the missions in an effort to minimize cognitive biases. In the present study, SEER had an average error of 23%, median error of -0.3%, with a standard deviation of 43%. PRICE had an average error of 52%, median error of 50%, and standard deviation of 45%. There were several factors independent of PRICE and SEER which may have affected the accuracy of the results in the present study including: uncertainty in the technical data used for the estimates, the methods used to estimate uncertainty in spacecraft component mass and numbers of prototypes, and the experience of the estimators.

Paul D Friz↗
NASA NTRS1992

Airborne remote sensing of tropospheric water vapor using a near infrared DIAL system

Summarized here are the results of airborne water vapor measurements in the lower middle and upper troposphere using the Differential Absorption Lidar (DIAL) technique in the near infrared. The measurements were performed in July 1990 in Southern Bavaria between Allersberg and Straubing from 20 to 23 UTC taking advantage of night time conditions. The tropospheric H2O profiles were range investigated both horizontally and vertically. With the DIAL system that was used, water vapor measurements in the upper troposphere have been carried out for the first time. To calibrate the H2O-retrievals, effective absorption cross sections of selected H2O lines in terms of altitude around 724 nm were calculated using line parameter data from the literature (B. E. Grossmann et al). The frequency of the on-line measurements was adjusted by the spectra of a Polyacenic Semiconductor (PAS) cell filled with H2O. We found that the calibration error ranged between 0.005 and 0.015 cm(exp -1). The systematic errors of the H2O as a function of altitude were estimated below 7 km and 12 percent accuracy in the upper troposphere. The vertical H2O profile agrees well with in situ measurements in the investigated range between the top of the planetary boundary layer (PBL) up to near the tropopause. Horizontal and vertical H2O profiles are calculated by means of averaging single lidar returns. Typical horizontal resolutions range from 4 km in the lower to 11 km in the upper troposphere with vertical resolutions varying from 0.3 km up to 1 km, respectively, in order to satisfy a 5 - 10 percent accuracy in the statistical error. The measurement sensibility of the water vapor mixing ration in the upper troposphere is 0.01 g/kg.

Ehret, G.↗
DOE OSTI2021

Forecasting Solar-Thermal Systems Performance under Transient Operation Using a Data-Driven Machine Learning Approach Based on the Deep Operator Network Architecture

Modeling and prediction of the dynamic behavior of thermal systems operating under intermittent energy input and variable load requirements represent one of the greatest challenges in the development of efficient and reliable renewable-based power generation technologies. In this work, a data-driven machine learning modeling framework was developed based on a modified version of the Deep Operator Network architecture where the time coordinate in the trunk net is replaced with historical data of the predicting quantity. The modeling framework can be used to accurately predict the performance of renewable-based energy conversion technologies including wind- and solar-based power plants. This novel framework was applied on a solar-thermal system that consists of a solar collection loop using a flat plate collector, a power generation loop comprising an Organic Rankine Cycle, and a thermal energy storage tank connecting both loops. Variable solar irradiance, air temperature, and power load profiles were used by the Deep Operator Network to predict the State-of-Charge and the efficiency of the thermal system for several days. The results were compared with the State-of-Charge and efficiency functions calculated using a physics-based model. For a simple operation scenario, characterized by a clear sky solar irradiance profile and constant load, the standard deviation in the State-of-Charge prediction by Deep Operator Network is below 0.9% during a seven-day prediction time horizon. For the most realistic operation scenario that considers real solar irradiance and a rough load profile, the maximum standard deviation in the predictions for the State-of-Charge and efficiency are below 6.8% and 2.5%, respectively. A comparison between Deep Operator Network and Long Short Term Memory network was also performed. In general, both networks predict very well the State-of-Charge for different data density conditions; however, a higher accuracy, with a standard deviation below 2.0%, is obtained by the Deep Operator Network during three and half days using sparser training data of 20-minute points. The same accuracy for the State-of-Charge prediction with the Long Short Term Memory network is achieved only for 14 h. Average standard deviations for the State-of-Charge prediction of 1.1% with the Deep Operator Network and 1.5% with the Long Short Term Memory network are obtained for a four-day prediction time using a denser training data of 5-minute points.

DeepONet↗
DOE OSTI2025

Resolving Mesoscale Convective Systems: Grid Spacing Sensitivity in the Tropics and Midlatitudes

Abstract Mesoscale convective systems (MCSs) are a critical global water cycle component and drive extreme precipitation events in tropical and midlatitude regions. However, simulating deep convection remains challenging for modern numerical weather and climate models due to the complex interactions of processes from microscales to synoptic scales. Recent models with kilometer‐scale horizontal grid spacings offer notable improvements in simulating deep convection compared to coarser‐resolution models. Still, deficiencies in representing key physical processes, such as entrainment, lead to systematic biases. Additionally, evaluating model outputs using process‐oriented observational data remain difficult. This study presents an ensemble of MCS simulations with spanning the deep convective gray zone ( from 12 km to 125 m) in the Southern Great Plains of the U.S. and the Amazon Basin. Comparing these simulations with Atmospheric Radiation Measurement (ARM) wind profiler observations, we find greater sensitivity in the Amazon Basin compared to the Great Plains. Convective drafts converge structurally at sub‐kilometer scales, but some deficiencies remain. In both regions, simulated up and downdrafts are too deep and extreme downdrafts are not strong enough. Furthermore, Amazonian updrafts are too strong. Overall, we observe higher sensitivity in the tropics, including an artificial buildup in vertical kinetic energy at scales of , suggesting a need for 250 m in this region. Nevertheless, bulk convergence—agreement of storm‐average statistics—is achievable with kilometer‐scale simulations within a 10% error margin with 1 km providing a good balance between accuracy and computational cost.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks

Machine learning has emerged as a powerful approach in materials discovery. Its major challenge is selecting features that create interpretable representations of materials, useful across multiple prediction tasks. We introduce an end-to-end machine learning model that automatically generates descriptors that capture a complex representation of a material’s structure and chemistry. This approach builds on computational topology techniques (namely, persistent homology) and word embeddings from natural language processing. It automatically encapsulates geometric and chemical information directly from the material system. We demonstrate our approach on multiple nanoporous metal–organic framework datasets by predicting methane and carbon dioxide adsorption across different conditions. Our results show considerable improvement in both accuracy and transferability across targets compared to models constructed from the commonly-used, manually-curated features, consistently achieving an average 25–30% decrease in root-mean-squared-deviation and an average increase of 40–50% in R 2 scores. A key advantage of our approach is interpretability: Our model identifies the pores that correlate best to adsorption at different pressures, which contributes to understanding atomic-level structure–property relationships for materials design.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

X-ray multi-probe data acquisition: A novel technique for laser pump x-ray transient absorption spectroscopy

We report the development and implementation of a novel data acquisition (DAQ) technique for synchrotron-based laser pump X-ray Transient Absorption (XTA) spectroscopy, called X-ray Multi-Probe DAQ (XMP DAQ). This technique utilizes high performance analog to digital converters and home-built software to efficiently measure and process the XTA signal from all x-ray pulses between laser excitations. XMP DAQ generates a set of time resolved x-ray absorption spectra at thousands of different pump–probe time delays simultaneously. Two distinct XMP DAQ schemes are deployed to accommodate different synchrotron storage ring filling patterns. Current Integration (CI) DAQ is a quasi-analog technique that implements a fitting procedure to extract the time resolved absorption intensity from the averaged fluorescence detector response. The fitting procedure eliminates issues associated with small drifts in the voltage baseline and greatly enhances the accuracy of the technique. Photon Counting (PC) DAQ is a binary technique that uses a time resolved histogram to calculate the XTA spectrum. While PC DAQ is suited to measure XTA data with closely spaced x-ray pulses (~10 ns) and a low count rate (<1 detected photon/pulse), CI DAQ works best for widely spaced pulses (tens of ns or greater) with a high count rate (>1 detected photon/pulse). XMP DAQ produces a two-dimensional XTA dataset, enabling efficient quantitative analysis of photophysical and photochemical processes from the sub-nanosecond timescale to 100 μs and longer.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Slater transition methods for core-level electron binding energies

Methods for computing core-level ionization energies using self-consistent field (SCF) calculations are evaluated and benchmarked. These include a “full core hole” (or “ΔSCF”) approach that fully accounts for orbital relaxation upon ionization, but also methods based on Slater’s transition concept in which the binding energy is estimated from an orbital energy level that is obtained from a fractional-occupancy SCF calculation. A generalization that uses two different fractional-occupancy SCF calculations is also considered. The best of the Slater-type methods afford mean errors of 0.3–0.4 eV with respect to experiment for a dataset of K-shell ionization energies, a level of accuracy that is competitive with more expensive many-body techniques. An empirical shifting procedure with one adjustable parameter reduces the average error below 0.2 eV. Here, this shifted Slater transition method is a simple and practical way to compute core-level binding energies using only initial-state Kohn–Sham eigenvalues. It requires no more computational effort than ΔSCF and may be especially useful for simulating transient x-ray experiments where core-level spectroscopy is used to probe an excited electronic state, for which the ΔSCF approach requires a tedious state-by-state calculation of the spectrum. As an example, we use Slater-type methods to model x-ray emission spectroscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗