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At least 1,459 records · Page 81

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NASA NTRS1987

Main rotor broadband noise study in the DNW

An acoustics test of a 2/5 scale model BO-105 helicopter main rotor was conducted in the Duits-Nederlandse Windtunnel (DNW). A range of operating conditions was tested from hover to moderately high flight speeds for various climb and descent rates at different thrust settings. Diagnostic tests including rotor speed and blade geometry changes were made to better isolate and study particular broadband self noise sources. Acoustic data in the form of acoustic pressure time histories and power spectra are used to demonstrate the regions of importance of the different broadband noise sources and their sensitivity to operating conditions. To help interpret the data, comparisons are made to predictions of rotor broadband noise. The predictions are based on self noise data previously obtained from isolated airfoil sections and the use of the NASA ROTONET program to define rotor performance and to sum contributions of noise from individual blade segments. An important result herein is the identification and articulation of a previously unheralded rotor broadband noise source. This source is blade-turbulent wake interaction (BWI) noise which dominates the spectra in the mid-frequencies for off-peak blade-vortex interaction (BVI) noise flight conditions.

Brooks, Thomas F.↗

NASA NTRS1988

An Imaging Spectrometric Observatory (ISO)

The Imaging Spectrometric Observatory (ISO) is designed for low light level spectroscopy of both the day and night side of the earth. The instrument is composed of five spectrometers, each of which covers part of the total wavelength range of 30 to 1300 nm spanned by the instrument. Wavelength resolution varies between 0.2 and 0.6 nm over the spectral range. The five spectrometers are each optimized for a portion of the spectrum by the choice of mirror reflective coatings and detector photocathode materials. The full spectral range for each spectrometer is covered in a total of 11 grating steps. The Imaging Spectrometric Observatory was flown for the first time on the Spacelab 1 mission during which it acquired almost 40 hr of observations. The ISO investigation to be flown on the Atmospheric Laboratory for Applications and Science (ATLAS 1) mission will draw on the experience gained from the data gathered on Spacelab 1. The detector system in each spectrometer was upgraded to provide both higher sensitivity at low light levels and simultaneous imaging over larger spectral segments than was achieved on Spacelab 1. In addition, the instrument and the observing sequences were modified to allow observation of the sun in the extreme ultraviolet. A summary of ISO parameters for ATLAS 1 (scheduled for late 1990) is given.

Torr, M. R.↗

NASA NTRS1994

An adaptive technique to maximize lossless image data compression of satellite images

Data compression will pay an increasingly important role in the storage and transmission of image data within NASA science programs as the Earth Observing System comes into operation. It is important that the science data be preserved at the fidelity the instrument and the satellite communication systems were designed to produce. Lossless compression must therefore be applied, at least, to archive the processed instrument data. In this paper, we present an analysis of the performance of lossless compression techniques and develop an adaptive approach which applied image remapping, feature-based image segmentation to determine regions of similar entropy and high-order arithmetic coding to obtain significant improvements over the use of conventional compression techniques alone. Image remapping is used to transform the original image into a lower entropy state. Several techniques were tested on satellite images including differential pulse code modulation, bi-linear interpolation, and block-based linear predictive coding. The results of these experiments are discussed and trade-offs between computation requirements and entropy reductions are used to identify the optimum approach for a variety of satellite images. Further entropy reduction can be achieved by segmenting the image based on local entropy properties then applying a coding technique which maximizes compression for the region. Experimental results are presented showing the effect of different coding techniques for regions of different entropy. A rule-base is developed through which the technique giving the best compression is selected. The paper concludes that maximum compression can be achieved cost effectively and at acceptable performance rates with a combination of techniques which are selected based on image contextual information.

Stewart, Robert J.↗

NASA NTRS1997

Polar Spin Axis Anomaly

The Global Geospace Science (GGS) Polar Plasma Laboratory (POLAR) spacecraft was launched on February 24, 1996, by a Delta 2. The spacecraft, a major axis spinner, appeared to function nominally throughout the early mission phase, which included several deployments, and orbit and attitude maneuvers. Of particular interest is the fact that the spacecraft was launched with a deliberate dynamic imbalance. During a segment of early orbit operations, a pair of Lanyard Deployed Booms (LDB) were extended. These booms were not identical; the intent was that the spacecraft would be nearly dynamically balanced after they were deployed. The spacecraft contained two dynamic balance mechanisms intended to fine tune the balance on orbit. However, subsequent images taken by the science instruments on the Despun Platform during the dynamic balancing segment indicated an offset of the principal spin axis from the geometric axis. This offset produced a sinusoidal blurring of the science images sufficiently large to degrade science data below mission requirement specifications. In the end, the imbalance encountered in flight was significantly outside the correction capability of the balances. The purpose of this paper is to examine the flight data during the various deployment and maneuver stages of the early orbit operations coupled with analytical simulations to discuss some of the potential causes of the resultant imbalance.

Crouse, Patrick L.↗

NASA NTRS1998

Improving Acoustic Models by Watching Television

Obtaining sufficient labelled training data is a persistent difficulty for speech recognition research. Although well transcribed data is expensive to produce, there is a constant stream of challenging speech data and poor transcription broadcast as closed-captioned television. We describe a reliable unsupervised method for identifying accurately transcribed sections of these broadcasts, and show how these segments can be used to train a recognition system. Starting from acoustic models trained on the Wall Street Journal database, a single iteration of our training method reduced the word error rate on an independent broadcast television news test set from 62.2% to 59.5%.

Witbrock, Michael J.↗

NASA NTRS1999

MOLA-derived Roughness Data Used to Predict Surface Scattering for Mars Subsurface Radar Sounding

The Mars Express orbiter, to be launched by the European Space Agency in 2003, will carry a low-frequency radar sounding instrument, MARSIS (Mars Advanced Radar for Subsurface and Ionospheric Sounding). The primary goal of MARSIS is to map the distribution of water, both solid and (if present) liquid, in the upper several km of the martian crust. Detecting discontinuities in the crust, such as an ice-water transition, presents many challenges for a Mars orbital radar sounder. One challenge that must be overcome is the presence of radar scattering (echoes) from the surface of Mars, expected to be detected by the sounder antennas at the same time as any echoes aris-ing from subsurface interfaces. As the transmitted spherical wavefront spreads within the crust of Mars,. it also interacts with surface topography at off-nadir positions, creating a "clutter" signal that can mask the subsurface echoes. The MARSIS instrument will utilize Doppler filtering to limit the off-nadir clutter in the along-track direction, and a nadir-null secondary antenna to identify strong off-nadir clutter from the cross-track direction. To evaluate the effects of off-nadir surface clutter and the capability of these schemes to reduce the clutter, it is necessary to predict the range of scattering behavior that may be expected from martian surface topography. In this paper, we utilize Mars Orbital Laser Altimeter (MOLA) data from the current Mars Global Surveyor mission to characterize the topographic roughness of a variety of martian terrain types, at scales relevant to the MARSIS clutter problem. Segments of MOLA altimetry profiles are reduced to the topographic parameters rms slope and fractal dimension, which then are used as inputs to a near-nadir radar scattering model to predict the strength of the clutter signal. Additional information is contained in the original extended abstract.

Plaut, J. J.↗

NASA NTRS2003

Spatial Analysis of Great Lakes Regional Icing Cloud Liquid Water Content

Abstract Clustering of cloud microphysical conditions, such as liquid water content (LWC) and drop size, can affect the rate and shape of ice accretion and the airworthiness of aircraft. Clustering may also degrade the accuracy of cloud LWC measurements from radars and microwave radiometers being developed by the government for remotely mapping icing conditions ahead of aircraft in flight. This paper evaluates spatial clustering of LWC in icing clouds using measurements collected during NASA research flights in the Great Lakes region. We used graphical and analytical approaches to describe clustering. The analytical approach involves determining the average size of clusters and computing a clustering intensity parameter. We analyzed flight data composed of 1-s-frequency LWC measurements for 12 periods ranging from 17.4 minutes (73 km) to 45.3 minutes (190 km) in duration. Graphically some flight segments showed evidence of consistency with regard to clustering patterns. Cluster intensity varied from 0.06, indicating little clustering, to a high of 2.42. Cluster lengths ranged from 0.1 minutes (0.6 km) to 4.1 minutes (17.3 km). Additional analyses will allow us to determine if clustering climatologies can be developed to characterize cluster conditions by region, time period, or weather condition. Introduction

Ryerson, Charles C.↗

NASA NTRS2007

Wavefront Control Toolbox for James Webb Space Telescope Testbed

We have developed a Matlab toolbox for wavefront control of optical systems. We have applied this toolbox to the optical models of James Webb Space Telescope (JWST) in general and to the JWST Testbed Telescope (TBT) in particular, implementing both unconstrained and constrained wavefront optimization to correct for possible misalignments present on the segmented primary mirror or the monolithic secondary mirror. The optical models implemented in Zemax optical design program and information is exchanged between Matlab and Zemax via the Dynamic Data Exchange (DDE) interface. The model configuration is managed using the XML protocol. The optimization algorithm uses influence functions for each adjustable degree of freedom of the optical mode. The iterative and non-iterative algorithms have been developed to converge to a local minimum of the root-mean-square (rms) of wavefront error using singular value decomposition technique of the control matrix of influence functions. The toolkit is highly modular and allows the user to choose control strategies for the degrees of freedom to be adjusted on a given iteration and wavefront convergence criterion. As the influence functions are nonlinear over the control parameter space, the toolkit also allows for trade-offs between frequency of updating the local influence functions and execution speed. The functionality of the toolbox and the validity of the underlying algorithms have been verified through extensive simulations.

Shiri, Ron↗

NASA NTRS2017

Cleared for Launch - Lessons Learned from the OSIRIS-REx System Requirements Verification Program

Requirements verification of a large flight system is a challenge. It is especially challenging for engineers taking on their first role in space systems engineering. This paper describes our approach to verification of the Origins, Spectral Interpretation, Resource Identification, Security-Regolith Explorer (OSIRIS-REx) system requirements. It also captures lessons learned along the way from developing systems engineers embroiled in this process. We begin with an overview of the mission and science objectives as well as the project requirements verification program strategy. A description of the requirements flow down is presented including our implementation for managing the thousands of program and element level requirements and associated verification data. We discuss both successes and methods to improve the managing of this data across multiple organizational interfaces. Our approach to verifying system requirements at multiple levels of assembly is presented using examples from our work at instrument, spacecraft, and ground segment levels. We include a discussion of system end-to-end testing limitations and their impacts to the verification program. Finally, we describe lessons learned that are applicable to all emerging space systems engineers using our unique perspectives across multiple organizations of a large NASA program.

Requirements Verification↗

NASA NTRS2021

The role of analysis error in the convergence of reanalysis production streams in MERRA-2

Due to production time constraints, most reanalyses are produced in multiple parallel streams instead of a single continuous one. These streams cover separate segments of the reanalysis time period with short overlaps to allow reconstruction of the official record. A fundamental assumption justifying this approach is that the streams will be assimilating the same observations during the periods where they overlap, and so will eventually converge to a similar atmospheric state, making discontinuities at stream junctions negligible. This assumption is revisited in this work by examining the impact of analysis error on the differences between MERRA-2 overlapping streams in three historical periods. Comparison results are shown in terms of standard deviations of stream differences as well as the spectral decomposition of the variance of their differences. Residual differences were found at the end of each year of overlap, with larger values observed in the earlier segments of the presatellite era. By drawing parallels with analysis error statistics estimated from the GMAO OSSE system, these differences are shown to reflect the varying constraint of data with the varying observing network, and to further carry the imprint of errors that the data assimilation process is not able to mitigate. As such, they are unlikely to be reduced by longer spinup periods. The ability of data assimilation to ensure continuity in the parallel streams is put into question when the observing system coverage is inadequate or simply when the data assimilation system as a whole is suboptimal.

Amal El Akkraoui↗

DOE OSTI2025

Generative learning for slow manifolds and bifurcation diagrams

In dynamical systems characterized by separation of time scales, the approximation of so called “slow manifolds”, on which the long term dynamics lie, is a useful step for model reduction. Initializing on such slow manifolds is a useful step in modeling, since it circumvents fast transients, and is crucial in multiscale algorithms (like the equation-free approach) alternating between fine scale (fast) and coarser scale (slow) simulations. In a similar spirit, when one studies the infinite time dynamics of systems depending on parameters, the system attractors (e.g., its steady states) lie on bifurcation diagrams (curves for one-parameter continuation, and more generally, on manifolds in state parameter space. Sampling these manifolds gives us representative attractors (here, steady states of ODEs or PDEs) at different parameter values. Algorithms for the systematic construction of these manifolds (slow manifolds, bifurcation diagrams) are required parts of the “traditional” numerical nonlinear dynamics toolkit. In more recent years, as the field of Machine Learning develops, conditional score-based generative models (cSGMs) have been demonstrated to exhibit remarkable capabilities in generating plausible data from target distributions that are conditioned on some given label. It is tempting to exploit such generative models to produce samples of data distributions (points on a slow manifold, steady states on a bifurcation surface) conditioned on (consistent with) some quantity of interest (QoI, observable). In this work, we present a framework for using cSGMs to quickly (a) initialize on a low-dimensional (reduced-order) slow manifold of a multi-time-scale system consistent with desired value(s) of a QoI (a “label”) on the manifold, and (b) approximate steady states in a bifurcation diagram consistent with a (new, out-of-sample) parameter value. This conditional sampling can help uncover the geometry of the reduced slow-manifold and/or approximately “fill in” missing segments of steady states in a bifurcation diagram. Finally, the quantity of interest, which determines how the sampling is conditioned, is either known a priori or identified using manifold learning-based dimensionality reduction techniques applied to the training data.

Dynamical systems↗

NASA NTRS2014

Biomechanics of the Treadmill Locomotion on the International Space Station

Exercise prescriptions completed by International Space Station (ISS) crewmembers are typically based upon evidence obtained during ground-based investigations, with the assumption that the results of long-term training in weightlessness will be similar to that attained in normal gravity. Coupled with this supposition are the assumptions that exercise motions and external loading are also similar between gravitational environments. Normal control of locomotion is dependent upon learning patterns of muscular activation and requires continual monitoring of internal and external sensory input [1]. Internal sensory input includes signals that may be dependent on or independent of gravity. Bernstein hypothesized that movement strategy planning and execution must include the consideration of segmental weights and inertia [2]. Studies of arm movements in microgravity showed that individuals tend to make errors but that compensation strategies result in adaptations, suggesting that control mechanisms must include peripheral information [3-5]. To date, however, there have been no studies examining a gross motor activity such as running in weightlessness other than using microgravity analogs [6-8]. The objective of this evaluation was to collect biomechanical data from crewmembers during treadmill exercise before and during flight. The goal was to determine locomotive biomechanics similarities and differences between normal and weightless environments. The data will be used to optimize future exercise prescriptions. This project addresses the Critical Path Roadmap risks 1 (Accelerated Bone Loss and Fracture Risk) and 11 (Reduced Muscle Mass, Strength, and Endurance). Data were collected from 7 crewmembers before flight and during their ISS missions. Before launch, crewmembers performed a single data collection session at the NASA Johnson Space Center. Three-dimensional motion capture data were collected for 30 s at speeds ranging from 1.5 to 9.5 mph in 0.5 mph increments with a 12-camera system. During flight, each crewmember completed up to 6 data collection sessions spread across their missions, performing their normal exercise prescription for the test day, resulting in varying data collection protocols between sessions. Motion data were collected by a single HD video camera positioned to view the crewmembers' left side, and tape markers were placed on their feet, legs, and neck on specific landmarks. Before data collection, the crewmembers calibrated the video camera. Video data were collected during the entire exercise session at 30 Hz. Kinematic data were used to determine left leg hip, knee, and ankle range of motion and contact time, flight time, and stride time for each stride. 129 trials in weightlessness were analyzed. Mean time-normalized strides were found for each trial, and cross-correlation procedures were used to examine the strength and direction of relationships between segment movement pattern timing in each gravitational condition. Cross-correlation analyses between gravitational conditions revealed highly consistent movement patterns at each joint. Peak correlation coefficients occurred at 0% phase, indicating there were no lags in movement timing. Joint ranges of motion were similar between gravitational conditions, with some slight differences between subjects. Motion patterns in weightlessness were highly consistent at a given speed with those occurring in 1G, indicating that despite differing sensory input, subjects maintain running kinematics. The data suggest that individuals are capable of compensating for loss of limb weight when creating movement strategies. These results have important implications for creating training programs for use in weightlessness as practitioners can have greater confidence in running motions transferring across gravitational environments. Furthermore, these results have implications for use by researchers investigating motor control mechanisms and investigating hypotheses related to movement strategies when using sensory input that is dependent upon gravity.

DeWitt, John↗

DOE OSTI2025

Understanding Multifamily Energy Use in the Colorado Mountains: Building Stock Segmentation for Retrofit Planning

This report is an addendum to a publication series that focuses on approximately 100 different local geographies, or "clusters". This addendum expands the report series to include large multifamily building characteristics as well as energy and emission data for each local geography. The intention of this addendum is to help policymakers at the city, county, and state levels better understand building energy use and emissions in large multifamily buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025