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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Psychological stress measurement through voice output analysis

Audio tape recordings of selected Skylab communications were processed by a psychological stress evaluator. Strip chart tracings were read blind and scores were assigned based on characteristics reported by the manufacturer to indicate psychological stress. These scores were analyzed for their empirical relationships with operational variables in Skylab judged to represent varying degrees of situational stress. Although some statistically significant relationships were found, the technique was not judged to be sufficiently predictive to warrant its use in assessing the degree of psychological stress of crew members in future space missions.

Older, H. J.↗
NASA NTRS1977

Snow parameters from Nimbus-6 electrically scanned microwave radiometer

Two sites in Canada were selected for detailed analysis of the ESMR-6/ snow relationships. Data were analyzed for February 1976 for site 1 and January, February and March 1976 for site 2. Snowpack water equivalents were less than 4.5 inches for site 1 and, depending on the month, were between 2.9 and 14.5 inches for site 2. A statistically significant relationship was found between ESMR-6 measurements and snowpack water equivalents for the Site 2 February and March data. Associated analysis findings presented are the effects of random measurement errors, snow site physiolography, and weather conditions on the ESMR-6/snow relationship.

Abrams, G.↗
NASA NTRS1984

Prediction of the space adaptation syndrome

The univariate and multivariate relationships of provocative measures used to produce motion sickness symptoms were described. Normative subjects were used to develop and cross-validate sets of linear equations that optimally predict motion sickness in parabolic flights. The possibility of reducing the number of measurements required for prediction was assessed. After describing the variables verbally and statistically for 159 subjects, a factor analysis of 27 variables was completed to improve understanding of the relationships between variables and to reduce the number of measures for prediction purposes. The results of this analysis show that none of variables are significantly related to the responses to parabolic flights. A set of variables was selected to predict responses to KC-135 flights. A series of discriminant analyses were completed. Results indicate that low, moderate, or severe susceptibility could be correctly predicted 64 percent and 53 percent of the time on original and cross-validation samples, respectively. Both the factor analysis and the discriminant analysis provided no basis for reducing the number of tests.

Reschke, M. F.↗
NASA NTRS1991

Visible and infrared investigations of planet-crossing asteroids and outer solar system objects

The project is supporting lightcurve photometry, colorimetry, thermal radiometry, and astrometry of selected asteroids. Targets include the planet-crossing population, particularly Earth approachers, which are believed to be the immediate source of terrestrial meteorites, future spacecraft targets, and those objects in the outer belt, primarily the Hilda and Trojan populations, that are dynamically isolated from the main asteroid belt. Goals include the determination of population statistics for the planet-crossing objects, the characterization of spacecraft targets to assist in encounter planning and subsequent interpretation of the data, a comparison of the collisional evolution of dynamically isolated Hilda and Trojan populations with the main belt, and the determination of the mechanism driving the activity of the distant object 2060 Chiron.

Tholen, David J.↗
NASA NTRS1992

Greenhouse Effect Detection Experiment (GEDEX). Selected data sets

This CD-ROM contains selected data sets compiled by the participants of the Greenhouse Effect Detection Experiment (GEDEX) workshop on atmospheric temperature. The data sets include surface, upper air, and/or satellite-derived measurements of temperature, solar irradiance, clouds, greenhouse gases, fluxes, albedo, aerosols, ozone, and water vapor, along with Southern Oscillation Indices and Quasi-Biennial Oscillation statistics.

Olsen, Lola M.↗
NASA NTRS1995

SWICS/Ulysses and MASS/wind observations of solar wind sulfur charge states

As Ulysses journeys from the southern to the northern solar pole, the newly launched Wind spacecraft is monitoring the solar wind near 1 AU, slightly upstream of the Earth. Different solar wind structures pass over both spacecraft as coronal holes and other features rotate in and out of view. Ulysses and Wind are presently on opposing sides of the sun allowing us to monitor these streams for extended periods of time. Composition measurements made by instruments on both spacecraft provide information concerning the evolution and properties of these structures. We have combined data from the Solar Wind Ion Composition Spectrometer (SWICS) on Ulysses and the high mass resolution spectrometer (MASS) on Wind to determine the charge state distribution of sulfur in the solar wind. Both instruments employ electrostatic deflection with time-of-flight measurement. The high mass resolution of the MASS instrument (M/Delta-M approximately 100) allows sulfur to be isolated easily while the stepping energy/charge selection provides charge state information. SWICS measurements allow the unique identification of heavy ions by their mass and mass/charge with resolutions of M/Delta-M approximately 3 and M/q/Delta(M/q) approximately 20. The two instruments complement each other nicely in that MASS has the greater mass resolution while SWICS has the better mass/charge resolution and better statistics.

Cohen, C. M. S.↗
NASA NTRS2001

Accuracy Assessment of Response Surface Approximations for Supersonic Turbine Design

There is a growing trend to employ CFD tools to supply the necessary information for design optimization of fluid dynamics components/systems. Such results are prone to uncertainties due to reasons including discretization. errors, incomplete convergence of computational procedures, and errors associated with physical models such as turbulence closures. Based on this type of information, gradient-based optimization algorithms often suffer from the noisy calculations, which can seriously compromise the outcome. Similar problems arise from the experimental measurements. Global optimization techniques, such as those based on the response surface (RS) concept are becoming popular in part because they can overcome some of these barriers. However, there are also fundamental issues related to such global optimization technique such as RS. For example, in high dimensional design spaces, typically only a small number of function evaluations are available due to computational and experimental costs. On the other hand, complex features of the design variables do not allow one to model the global characteristics of the design space with simple quadratic polynomials. Consequently a main challenge is to reduce the size of the region where we fit the RS, or make it more accurate in the regions where the optimum is likely to reside. Response Surface techniques using either polynomials or and Neural Network (NN) methods offer designers alternatives to conduct design optimization. The RS technique employs statistical and numerical techniques to establish the relationship between design variables and objective/constraint functions, typically using polynomials. In this study, we aim at addressing issues related to the following questions: (1) How to identify outliers associated with a given RS representation and improve the RS model via appropriate treatments? (2) How to focus on selected design data so that RS can give better performance in regions critical to design optimization? (3) How to combine NN and polynomial techniques for improving the accuracy of the RS model?

Papila, Nilay↗
NASA NTRS2004

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

Source record↗
DOE OSTI2015

Patterns of Relapse From a Phase 3 Study of Response-Based Therapy for Intermediate-Risk Hodgkin Lymphoma (AHOD0031): A Report From the Children's Oncology Group

Purpose: The study was designed to determine whether response-based therapy improves outcomes in intermediate-risk Hodgkin lymphoma. We examined patterns of first relapse in the study. Patients and Methods: From September 2002 to July 2010, 1712 patients <22 years old with stage I-IIA with bulk, I-IIAE, I-IIB, and IIIA-IVA with or without doxorubicin, bleomycin, vincristine, etoposide, prednisone, and cyclophosphamide were enrolled. Patients were categorized as rapid (RER) or slow early responders (SER) after 2 cycles of doxorubicin, bleomycin, vincristine, etoposide, prednisone, and cyclophosphamide (ABVE-PC). The SER patients were randomized to 2 additional ABVE-PC cycles or augmented chemotherapy with 21 Gy involved field radiation therapy (IFRT). RER patients were stipulated to undergo 2 additional ABVE-PC cycles and were then randomized to 21 Gy IFRT or no further treatment if complete response (CR) was achieved. RER without CR patients were non-randomly assigned to 21 Gy IFRT. Relapses were characterized without respect to site (initial, new, or both; and initial bulk or initial nonbulk), and involved field radiation therapy field (in-field, out-of-field, or both). Patients were grouped by treatment assignment (SER; RER/no CR; RER/CR/IFRT; and RER/CR/no IFRT). Summary statistics were reported. Results: At 4-year median follow-up, 244 patients had experienced relapse, 198 of whom were fully evaluable for review. Those who progressed during treatment (n=30) or lacked relapse imaging (n=16) were excluded. The median time to relapse was 12.8 months. Of the 198 evaluable patients, 30% were RER/no CR, 26% were SER, 26% were RER/CR/no IFRT, 16% were RER/CR/IFRT, and 2% remained uncategorized. The 74% and 75% relapses involved initially bulky and nonbulky sites, respectively. First relapses rarely occurred at exclusively new or out-of-field sites. By contrast, relapses usually occurred at nodal sites of initial bulky and nonbulky disease. Conclusion: Although response-based therapy has helped define treatment for selected RER patients, it has not improved outcome for SER patients or facilitated refinement of IFRT volumes or doses.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Using Field-Metered Data to Quantify Annual Energy Use of Portable Air Conditioners

As many regions of the United States experience rising temperatures, consumers have come to rely increasingly on cooling appliances (including portable air conditioners) to provide a comfortable indoor temperature. Home occupants sometimes use a portable air conditioner (PAC) to maintain a desired indoor temperature in a single room or enclosed space. Although PACs in residential use are few compared to centrally installed and room air conditioning (AC) units, the past few years have witnessed an increase of PACs use throughout the United States. There is, however, little information and few research projects focused on the energy consumption and performance of PACs, particularly studies that collect information from field applications of PACs. The operation and energy consumption of PACs may differ among geographic locations and households, because of variations in cooling load, frequency, duration of use, and other user-selected settings. In addition, the performance of building envelope (thermal mass and air leakage) as well as inter-zonal mixing within the building would substantially influence the ability to control and maintain desirable indoor thermal conditions. Lawrence Berkeley National Laboratory (LBNL) conducted an initial field-metering study aimed at increasing the knowledge and data related to PAC operation and energy consumption in the United States. LBNL performed its field-metering study from mid-April to late October 2014. The study, which monitored 19 sites in the Northeastern United States (4 in upstate New York and 15 near Philadelphia), collected real-time data on PAC energy consumption along with information regarding housing characteristics, consumer behavior, and environmental conditions that were expected to affect PAC performance. Given the limited number of test sites, this study was not intended to be statistically representative of PAC users in the United States but rather to understand the system response to the cooling demand and to some extent, the operating hours of the studied units. Specifically, the primary objectives of the field-metering study were to (1) expand knowledge of the installation, energy consumption profiles, consumer patterns of use, and environmental parameters related to PAC use; (2) develop distributions of hours of PAC operation for three operating modes: standby, 1 fan-only, and cooling; and (3) describe how individual consumers’ selection of PAC capacity, the area of the space to be cooled, the temperature set point, and environmental conditions affect energy use. Beginning to understand the energy consumption of PACs operating in American homes and commercial settings will help develop a more accurate energy use profile that characterizes relevant variables. This report on LBNL’s field-metering study of PAC energy use describes: a general definition of a PAC and how it operates (section 2); current practices and sources of data for estimating PAC energy use (section 3); the process LBNL used to select field-metering sites, along with characteristics of the sites and the PACs studied (section 4); data collection methods and instrumentation (section 5); analysis methods (section 6); results and discussion (section 7); and conclusions (section 8).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2010

Selecting Tasks for Evaluating Human Performance as a Function of Gravity

A challenge in understanding human performance as a function of gravity is determining which tasks to research. Initial studies began with treadmill walking, which was easy to quantify and control. However, with the development of pressurized rovers, it is less important to optimize human performance for ambulation as rovers will likely perform gross translation for them. Future crews are likely to spend much of their extravehicular activity (EVA) performing geology, construction and maintenance type tasks, for which it is difficult to measure steady-state-workloads. To evaluate human performance in reduced gravity, we have collected metabolic, biomechanical and subjective data for different tasks at varied gravity levels. Methods: Ten subjects completed 5 different tasks including weight transfer, shoveling, treadmill walking, treadmill running and treadmill incline walking. All tasks were performed shirt-sleeved at 1-g, 3/8-g and 1/6-g. Off-loaded conditions were achieved via the Active Response Gravity Offload System. Treadmill tasks were performed for 3 minutes with reported oxygen consumption (VO2) averaged over the last 2 minutes. Shoveling was performed for 3 minutes with metabolic cost reported as ml O2 consumed per kg material shoveled. Weight transfer reports metabolic cost as liters O2 consumed to complete the task. Statistical analysis was performed via repeated measures ANOVA. Results: Statistically significant metabolic differences were noted between all 3 gravity levels for treadmill running and incline walking. For the other 3 tasks, there were significant differences between 1-g and each reduced gravity, but not between 1/6-g and 3/8-g. For weight transfer, significant differences were seen between gravities in both trial-average VO2 and time-to-completion with noted differences in strategy for task completion. Conclusion: To determine if gravity has a metabolic effect on human performance, this research may indicate that tasks should be selected that require the subject to work vertically against the force of gravity.

Norcross, J. R.↗
DOE OSTI2025

Random heteropolymers as enzyme mimics

Despite successes in replicating the primary–secondary–tertiary structure hierarchy of protein, it remains elusive to synthetically materialize protein functions that are deeply rooted in their chemical, structural and dynamic heterogeneities. We propose that for polymers with backbone chemistries different from that of proteins, programming spatial and temporal projections of sidechains at the segmental level can be effective in replicating protein behaviours; and leveraging the rotational freedom of polymer can mitigate deficiencies in monomeric sequence specificity and achieve behaviour uniformity at the ensemble level. Here, guided by the active site analysis of about 1,300 metalloproteins, we design random heteropolymers (RHPs) as enzyme mimics based on one-pot synthesis. We introduce key monomers as the equivalents of the functional residues of protein and statistically modulate the chemical characteristics of key monomer-containing segments, such as segmental hydrophobicity. The resultant RHPs form pseudo-active sites that provide key monomers with protein-like microenvironments, co-localize substrates with catalytic or cofactor-binding sidechains and catalyse reactions such as oxidation and cyclization of citronellal with isopulegol/menthoglycol selectivity. This RHP design led to enzyme-like materials that can retain catalytic activity under non-biological conditions, are compatible with scalable processing and have expanded substrate scope, including environmentally long-lasting antibiotic tetracycline.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Uncertainty propagation in pore water chemical composition calculation using surrogate models

Performance assessment in deep geological nuclear waste repository systems necessitates an extended knowledge of the pore water chemical conditions prevailing in host-rock formations. In the last two decades, important progress has been made in the experimental characterization and thermodynamic modeling of pore water speciation, but the influence of experimental artifacts and uncertainties of thermodynamic input parameters are seldom evaluated. In this respect, we conducted an uncertainty propagation study in a reference geochemical model describing the pore water chemistry of the Callovian-Oxfordian clay formation. Nineteen model input parameters were perturbed, including those associated to experimental characterization (leached anions, exchanged cations, cation exchange selectivity coefficients) and those associated to generic thermodynamic databases (solubilities). A set of 13 quantities of interest were studied by the use of polynomial chaos expansions built non-intrusively with a least-squares forward stepwise regression approach. Training and validation sets of simulations were carried out using the geochemical speciation code PHREEQC. The statistical results explored the marginal distribution of each quantity of interest, their bivariate correlations as well as their global sensitivity indices. The influence of the assumed distributions for input parameters uncertainties was evaluated by considering two parametric domain sizes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Towards emulating cosmic shear data: revisiting the calibration of the shear measurements for the Kilo-Degree Survey

Exploiting the full statistical power of future cosmic shear surveys will necessitate improvements to the accuracy with which the gravitational lensing signal is measured. We present a framework for calibrating shear with image simulations that demonstrates the importance of including realistic correlations between galaxy morphology, size, and more importantly, photometric redshifts. This realism is essential to ensure that selection and shape measurement biases can be calibrated accurately for a tomographic cosmic shear analysis. We emulate Kilo-Degree Survey (KiDS) observations of the COSMOS field using morphological information from Hubble Space Telescope imaging, faithfully reproducing the measured galaxy properties from KiDS observations of the same field. We calibrate our shear measurements from lens fit, and find through a range of sensitivity tests that lens fit is robust and unbiased within the allowed two per cent tolerance of our study. Our results show that the calibration has to be performed by selecting the tomographic samples in the simulations, consistent with the actual cosmic shear analysis, because the joint distributions of galaxy properties are found to vary with redshift. Ignoring this redshift variation could result in misestimating the shear bias by an amount that exceeds the allowed tolerance. To improve the calibration for future cosmic shear analyses, it will also be essential to correctly account for the measurement of photometric redshifts, which requires simulating multi-band observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

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

QUEST (\url{www.quest-scidac.org}) is a SciDAC Institute that is focused on uncertainty quantification (UQ) in large-scale scientific computations. Our goals are to (1) advance the state of the art in UQ mathematics, algorithms, and software; and (2) provide modeling, algorithmic, and general UQ expertise, together with software tools, to other SciDAC projects, thereby enabling and guiding a broad range of UQ activities in their respective contexts. QUEST is a collaboration among six institutions (Sandia National Laboratories, Los Alamos National Laboratory, the University of Southern California, Massachusetts Institute of Technology, the University of Texas at Austin, and Duke University) with a history of joint UQ research. Our vision encompasses all aspects of UQ in leadership-class computing. This includes the well-founded setup of UQ problems; characterization of the input space given available data/information; local and global sensitivity analysis; adaptive dimensionality and order reduction; forward and inverse propagation of uncertainty; handling of application code failures, missing data, and hardware/software fault tolerance; and model inadequacy, comparison, validation, selection, and averaging. The nature of the UQ problem requires the seamless combination of data, models, and information across this landscape in a manner that provides a self-consistent quantification of requisite uncertainties in predictions from computational models. Accordingly, our UQ methods and tools span an interdisciplinary space across applied math, information theory, and statistics. The MIT QUEST effort centers on statistical inference and methods for surrogate or reduced-order modeling. MIT personnel have been responsible for the development of adaptive sampling methods, methods for approximating computationally intensive models, and software for both forward uncertainty propagation and statistical inverse problems. A key software product of the MIT QUEST effort is the MIT Uncertainty Quantification library, called MUQ (\url{muq.mit.edu}).

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1977

JAN transistor and diode characterization test program: JANTX diode 1N759A

The necessary data to create a new class of specifications was the objective of this characterization program. Sample selection was made according to the following criteria: (1) manufacturer or qualified distributor; (2) two vendors; and (3) two date codes. The general guidelines for procurement were two QPL vendors, JAN or JANTX, and two manufacturing lots, 27 from each lot. All data were acquired with three digit accuracy. The data processing and calculation of statistical parameters were performed by the Tektronix computer system using 4 digit display.

Takeda, H.↗
NASA NTRS1981

Evaluation of the effects of a freeze/thaw environment on cellular glass

Using the evaluation criteria of water vapor permeability and conformability, a protective butylrubber/silicone conformal coating system was selected for use on Foamglas substrates in a freeze/thaw environment. The selection of a specific freeze/thaw cycle which closely models field conditions is discussed. A sampling plan is described which allows independent evaluation of the effects of conformal coatings, cycle number and location within the environmental chamber. The results of visual examination, measurement of density, modulus of rupture and Young's modulus are reported. Based upon statistical evaluation of the experimental results, it is concluded that no degradation in mechanical properties of either coated or uncoated Foamglas occurred within the duration of the test (53 freeze/thaw cycles).

Frickland, P.↗
NASA NTRS1982

Concepts for on board satellite image registration. Volume 4: Impact of data set selection on satellite on board signal processing

The NASA NEEDS program goals present a requirement for on-board signal processing to achieve user-compatible, information-adaptive data acquisition. This volume addresses the impact of data set selection on data formatting required for efficient telemetering of the acquired satellite sensor data. More specifically, the FILE algorithm developed by Martin-Marietta provides a means for the determination of those pixels from the data stream effects an improvement in the achievable system throughput. It will be seen that based on the lack of statistical stationarity in cloud cover, spatial distribution periods exist where data acquisition rates exceed the throughput capability. The study therefore addresses various approaches to data compression and truncation as applicable to this sensor mission.

Ruedger, W. H.↗