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At least 379 records · Page 21

Reliability of the Danish Aerospace Corporation Portable Pulmonary Function System

Metabolic gas analysis is a critical component of investigations that measure cardio-pulmonary exercise responses during and after long-duration spaceflight. The primary purpose of the current study was to determine the reliability and intra-subject repeatability of a metabolic gas analysis device, the Portable Pulmonary Function System (PPFS), designed for use on the International Space Station (ISS). The second objective of this study was to directly compare PPFS measurements of expired oxygen and carbon dioxide (FEO2 and FECO2) to values obtained from a well-validated clinical metabolic gas analysis system (ParvoMedics TrueOne (c) [PM]). Eight subjects performed four peak cycle tests to maximal exertion. The first test was used to prescribe work rates for the subsequent test sessions. Metabolic gas analysis for this test was performed by the PM, but samples of FEO2 and FECO2 also were simultaneously collected for analysis by the PPFS. Subjects then performed three additional peak cycle tests, consisting of three 5-min stages designed to elicit 25%, 50%, and 75% maximal oxygen consumption (VO2max) followed by stepwise increases of 25 W/min until subjects reached volitional exhaustion. Metabolic gas analysis was performed using the PPFS for these tests. Intraclass correlation coefficients (ICC), within-subject standard deviations (WS SD), and coefficients of variation (CV%) were calculated for the repeated exercise tests. Mixed model regression analysis was used to compare paired FEO2 and FECO2 values obtained from the PPFS and the PM during the initial test. The ICC values for oxygen consumption (VO2), carbon dioxide production (VCO2), and ventilation (VE) indicate that the PPFS is highly reliable (0.79 to 0.99) for all exercise levels tested; however, ICCs for respiratory exchange ratio (RER) were low ( 0.11 - 0.51), indicating poor agreement between trials during submaximal and maximal exercise. Overall, CVs ranged from 1.6% to 6.7% for all measurements, a finding consistent with reported values that were obtained using other metabolic gas analysis techniques. The PPFS and PM produced comparable FEO2 data; however, there was less agreement between measures of FECO2 obtained from the two devices, particularly at lower CO2 concentrations. The PPFS appears, in practically all respects, to yield highly reliable metabolic gas analysis data. Lower reliability of RER measurements reported in the literature and likely is not a function of the PPFS device. Further examination of PPFS CO2 data is warranted to better understand the limitations of these PPFS measurements. Overall, the PPFS when used for repeated measures of cardio-pulmonary exercise should provide accurate and reliable data for studies of human adaptation to spaceflight.

Portable Pulmonary Function System (PPFS)↗

The Application of Nonstandard Analysis to the Study of Inviscid Shock Wave Jump Conditions

The use of conservation laws in nonconservative form for deriving shock jump conditions by Schwartz distribution theory leads to ambiguous products of generalized functions. Nonstandard analysis is used to define a class of Heaviside functions where the jump from zero to one occurs on an infinitesimal interval. These Heaviside functions differ by their microstructure near x = 0, i.e., by the nature of the rise within the infinitesimal interval it is shown that the conservation laws in nonconservative form can relate the different Heaviside functions used to define jumps in different flow parameters. There are no mathematical or logical ambiguities in the derivation of the jump conditions. An important result is that the microstructure of the Heaviside function of the jump in entropy has a positive peak greater than one within the infinitesimal interval where the jump occurs. This phenomena is known from more sophisticated studies of the structure of shock waves using viscous fluid assumption. However, the present analysis is simpler and more direct.

Farassat, F.↗

Analysis of complete quasar samples to obtain parameters of luminosity and evolution functions

A parametric likelihood analysis of the joint redshift-luminosity distribution is presented for a composite, complete sample of 32 quasars with B between 17.0 and 19.2 selected on the basis of ultraviolet excess. Best estimates and joint confidence regions are determined for the parameters of several models of the quasar optical luminosity and evolution function. These models are also tested explicitly for their acceptability. A steeper luminosity function is found than was found for previous samples. A model invoking pure density evolution is rejected on the basis of its extrapolation to fainter magnitudes through comparisons with the optical number counts and independently with the observed 2 keV X-ray background. Assuming an average value for L(x)/L(opt), the contribution of quasars to the X-ray background at 2 keV is discussed.

Marshall, H. L.↗

An empirical analysis of the distribution of overshoots in a stationary Gaussian stochastic process

The frequency distribution of overshoots in a stationary Gaussian stochastic process is analyzed. The primary processes involved in this analysis are computer simulation and statistical estimation. Computer simulation is used to simulate stationary Gaussian stochastic processes that have selected autocorrelation functions. An analysis of the simulation results reveals a frequency distribution for overshoots with a functional dependence on the mean and variance of the process. Statistical estimation is then used to estimate the mean and variance of a process. It is shown that for an autocorrelation function, the mean and the variance for the number of overshoots, a frequency distribution for overshoots can be estimated.

Carter, M. C.↗

Science Workflows using Kamodo

Kamodo is a powerful python software package based on data functionalization. Once a given data set is functionalized, a large variety of capabilities are easily accessible in Kamodo, including unit conversions, custom analysis via function composition, interactive publication quality visualizations, and LaTeX encoding. The entirety of capabilities available in Kamodo are easily applied to both simulated and observed data across the multiple domains of Heliophysics and even in other disciplines. This work includes a variety of science workflows using Kamodo in combination with other resources, including with other python software packages, that expand the utility of Kamodo even further. These workflows include model-data comparisons, ensemble modeling examples, satellite mission planning examples, and other applications, all of which are freely available on CCMC’s Kamodo Github page for the community to adapt to their own uses (https://github.com/nasa/Kamodo). We invite the community to use these workflows and to contribute their own to share.

software↗

Science Workflows using Kamodo

Kamodo is a powerful python software package based on data functionalization. Once a given data set is functionalized, a large variety of capabilities are easily accessible in Kamodo, including unit conversions, custom analysis via function composition, interactive publication quality visualizations, and LaTeX encoding. The entirety of capabilities available in Kamodo are easily applied to both simulated and observed data across the multiple domains of Heliophysics and even in other disciplines. This work includes a variety of science workflows using Kamodo in combination with other resources, including with other python software packages, that expand the utility of Kamodo even further. These workflows include model-data comparisons, ensemble modeling examples, satellite mission planning examples, and other applications, all of which are freely available on CCMC’s Kamodo Github page for the community to adapt to their own uses (https://github.com/nasa/Kamodo). We invite the community to use these workflows and to contribute their own to share.

python↗

Development and Application of an Integrated Approach toward NASA Airspace Systems Research

The National Aeronautics and Space Administration's (NASA) Airspace Systems Program is contributing air traffic management research in support of the 2025 Next Generation Air Transportation System (NextGen). Contributions support research and development needs provided by the interagency Joint Planning and Development Office (JPDO). These needs generally call for integrated technical solutions that improve system-level performance and work effectively across multiple domains and planning time horizons. In response, the Airspace Systems Program is pursuing an integrated research approach and has adapted systems engineering best practices for application in a research environment. Systems engineering methods aim to enable researchers to methodically compare different technical approaches, consider system-level performance, and develop compatible solutions. Systems engineering activities are performed iteratively as the research matures. Products of this approach include a demand and needs analysis, system-level descriptions focusing on NASA research contributions, system assessment and design studies, and common systemlevel metrics, scenarios, and assumptions. Results from the first systems engineering iteration include a preliminary demand and needs analysis; a functional modeling tool; and initial system-level metrics, scenario characteristics, and assumptions. Demand and needs analysis results suggest that several advanced concepts can mitigate demand/capacity imbalances for NextGen, but fall short of enabling three-times current-day capacity at the nation s busiest airports and airspace. Current activities are focusing on standardizing metrics, scenarios, and assumptions, conducting system-level performance assessments of integrated research solutions, and exploring key system design interfaces.

Barhydt, Richard↗

Predictability experiments using a low order empirically corrected dynamical model

It is generally accepted that day to day weather variations possess a finite range of predictability estimated to be approximately two weeks (e.g., Lorenz, 1965). However, considerable observational evidence points to the existence of a number of low frequency flow regimes which are potentially predictable beyond this limit. These include blocking events and teleconnection patterns such as those described in Wallace and Gutzler (1981). The problem of the predictability of such modes is addressed by employing a highly simplified dynamical model projected onto the modes of interest. These modes are computed from an empirical orthogonal function (EOF) analysis of 10-day averaged anomalies (deviations from the mean seasonal cycle) of the 500 mb stream function for the winters of 1967-76. The first three EOF's are associated with an index cycle and some of the teleconnection patterns. The fourth and ninth are related to North Pacific and North Atlantic blocking, respectively.

Schubert, S.↗

Building a functional, integrated GIS/remote sensing resource analysis and planning system

To be an effective tool for resource analysis and planning, a geographic information system (GIS) needs to be integrated with a digital remote sensing capability. To be truly functional, the paired system must be driven by grass roots local needs. A case study couched in a Soil Conservation District in northern Utah is presented. Agency representatives determined that the most fundamental data sets to be entered into the GIS system analysis system in the first round were: land use/land cover; geomorphic/soil unit data; hydrologic unit data; and digital terrain. The least expensive and best ways to obtain these data were determined. Data were acquired and formatted to enter the state's PRIME/ARC-INFO GIS, and are being interrogated for resource management decisions related to such issues as agricultural preservation, urban expansion, soil erosion control, and dam siting.

Ridd, M. K.↗

Independent Orbiter Assessment (IOA): Analysis of the auxiliary power unit

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. This report documents the independent analysis results corresponding to the Orbiter Auxiliary Power Unit (APU). The APUs are required to provide power to the Orbiter hydraulics systems during ascent and entry flight phases for aerosurface actuation, main engine gimballing, landing gear extension, and other vital functions. For analysis purposes, the APU system was broken down into ten functional subsystems. Each level of hardware was evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the severity of the effect for each failure mode. A preponderance of 1/1 criticality items were related to failures that allowed the hydrazine fuel to escape into the Orbiter aft compartment, creating a severe fire hazard, and failures that caused loss of the gas generator injector cooling system.

Barnes, J. E.↗

Computer Program Predicts Turbine-Stage Performance

MTSBL updated version of flow-analysis programs MERIDL and TSONIC coupled to boundary-layer program BLAYER. Method uses quasi-three-dimensional, inviscid, stream-function flow analysis iteratively coupled to calculated losses so changes in losses result in changes in flow distribution. Manner effects both configuration on flow distribution and flow distribution on losses taken into account in prediction of performance of stage. Written in FORTRAN IV.

Boyle, Robert J.↗

Introduction to the computational structural mechanics testbed

The Computational Structural Mechanics (CSM) testbed software system based on the SPAR finite element code and the NICE system is described. This software is denoted NICE/SPAR. NICE was developed at Lockheed Palo Alto Research Laboratory and contains data management utilities, a command language interpreter, and a command language definition for integrating engineering computational modules. SPAR is a system of programs used for finite element structural analysis developed for NASA by Lockheed and Engineering Information Systems, Inc. It includes many complementary structural analysis, thermal analysis, utility functions which communicate through a common database. The work on NICE/SPAR was motivated by requirements for a highly modular and flexible structural analysis system to use as a tool in carrying out research in computational methods and exploring computer hardware. Analysis examples are presented which demonstrate the benefits gained from a combination of the NICE command language with a SPAR computational modules.

Lotts, C. G.↗

Aeroelastic Flight Data Analysis with the Hilbert-Huang Algorithm

This report investigates the utility of the Hilbert Huang transform for the analysis of aeroelastic flight data. It is well known that the classical Hilbert transform can be used for time-frequency analysis of functions or signals. Unfortunately, the Hilbert transform can only be effectively applied to an extremely small class of signals, namely those that are characterized by a single frequency component at any instant in time. The recently-developed Hilbert Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert Huang algorithm affords time-frequency analysis of a large class of signals. This powerful tool has been applied in the analysis of scientific data, structural system identification, mechanical system fault detection, and even image processing. The purpose of this report is to demonstrate the potential applications of the Hilbert Huang algorithm for the analysis of aeroelastic systems, with improvements such as localized online processing. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Online stability analyses and modal identification are also presented. Examples are given using aeroelastic test data from the F-18 Active Aeroelastic Wing airplane, an Aerostructures Test Wing, and pitch plunge simulation.

Brenner, Martin J.↗

The use of cross-section warping functions in composite rotor blade analysis

During the contracted period, our research was concentrated into three areas. The first was the development of an accurate and a computationally efficient method for predicting the cross-section warping functions in an arbitrary cross-section composed of isotropic and/or anisotropic materials. The second area of research was the development of a general higher-order one-dimensional theory for anisotropic beams. The third area of research was the development of an analytical model for assessing the extension-bend-twist coupling behavior of nonhomogeneous anisotropic beams with initial twist. In the remaining six chapters of this report, the three different research areas and associated sub-research areas are covered independently including separate introductions, theoretical developments, numerical results, and references.

Kosmatka, J. B.↗

Methods utilized in evaluating the profitability of commercial space processing

Profitability analysis is applied to commercial space processing on the basis of business concept definition and assessment and the relationship between ground and space functions. Throughput analysis is demonstrated by analysis of the space manufacturing of surface acoustic wave devices. The paper describes a financial analysis model for space processing and provides key profitability measures for space processed isoenzymes.

Bloom, H. L.↗

Aeroelastic Flight Data Analysis with the Hilbert-Huang Algorithm

This paper investigates the utility of the Hilbert-Huang transform for the analysis of aeroelastic flight data. It is well known that the classical Hilbert transform can be used for time-frequency analysis of functions or signals. Unfortunately, the Hilbert transform can only be effectively applied to an extremely small class of signals, namely those that are characterized by a single frequency component at any instant in time. The recently-developed Hilbert-Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert-Huang algorithm affords time-frequency analysis of a large class of signals. This powerful tool has been applied in the analysis of scientific data, structural system identification, mechanical system fault detection, and even image processing. The purpose of this paper is to demonstrate the potential applications of the Hilbert-Huang algorithm for the analysis of aeroelastic systems, with improvements such as localized/online processing. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Online stability analyses and modal identification are also presented. Examples are given using aeroelastic test data from the F/A-18 Active Aeroelastic Wing aircraft, an Aerostructures Test Wing, and pitch-plunge simulation.

Brenner, Marty↗