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At least 883 records · Page 49

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NASA NTRS2011

High-Throughput, Adaptive FFT Architecture for FPGA-Based Spaceborne Data Processors

Exponential growth in microelectronics technology such as field-programmable gate arrays (FPGAs) has enabled high-performance spaceborne instruments with increasing onboard data processing capabilities. As a commonly used digital signal processing (DSP) building block, fast Fourier transform (FFT) has been of great interest in onboard data processing applications, which needs to strike a reasonable balance between high-performance (throughput, block size, etc.) and low resource usage (power, silicon footprint, etc.). It is also desirable to be designed so that a single design can be reused and adapted into instruments with different requirements. The Multi-Pass Wide Kernel FFT (MPWK-FFT) architecture was developed, in which the high-throughput benefits of the parallel FFT structure and the low resource usage of Singleton s single butterfly method is exploited. The result is a wide-kernel, multipass, adaptive FFT architecture. The 32K-point MPWK-FFT architecture includes 32 radix-2 butterflies, 64 FIFOs to store the real inputs, 64 FIFOs to store the imaginary inputs, complex twiddle factor storage, and FIFO logic to route the outputs to the correct FIFO. The inputs are stored in sequential fashion into the FIFOs, and the outputs of each butterfly are sequentially written first into the even FIFO, then the odd FIFO. Because of the order of the outputs written into the FIFOs, the depth of the even FIFOs, which are 768 each, are 1.5 times larger than the odd FIFOs, which are 512 each. The total memory needed for data storage, assuming that each sample is 36 bits, is 2.95 Mbits. The twiddle factors are stored in internal ROM inside the FPGA for fast access time. The total memory size to store the twiddle factors is 589.9Kbits. This FFT structure combines the benefits of high throughput from the parallel FFT kernels and low resource usage from the multi-pass FFT kernels with desired adaptability. Space instrument missions that need onboard FFT capabilities such as the proposed DESDynl, SWOT (Surface Water Ocean Topography), and Europa sounding radar missions would greatly benefit from this technology with significant reductions in non-recurring cost and risk.

NguyenKobayashi, Kayla↗

NASA NTRS1991

Software reliability experiments data analysis and investigation

The objectives are to investigate the fundamental reasons which cause independently developed software programs to fail dependently, and to examine fault tolerant software structures which maximize reliability gain in the presence of such dependent failure behavior. The authors used 20 redundant programs from a software reliability experiment to analyze the software errors causing coincident failures, to compare the reliability of N-version and recovery block structures composed of these programs, and to examine the impact of diversity on software reliability using subpopulations of these programs. The results indicate that both conceptually related and unrelated errors can cause coincident failures and that recovery block structures offer more reliability gain than N-version structures if acceptance checks that fail independently from the software components are available. The authors present a theory of general program checkers that have potential application for acceptance tests.

Walker, J. Leslie↗

NASA NTRS2004

Evaluation and Validation of Case 2 Algorithms in Chesapeake Bay

The high temporal and spatial resolution of satellite ocean color observations will prove invaluable for monitoring the health of coastal ecosystems where physical and biological variability demands sampling scales beyond that possible by ship. However, ocean color remote sensing of Case 2 waters is a challenging undertaking due to the optical complexity of the water. The focus of this SIMBIOS support has been to provide in situ optical measurements form Chesapeake Bay (CB) and adjacent mid-Atlantic bight (MAB) waters for use in algorithm development and validation efforts to improve the satellite retrieval of chlorophyll (chl a) in Case 2 waters. CB provides a valuable site for validation of data from ocean color sensors for a number of reasons. First, the physical dimensions of the Bay (greater than 6,500 square kilometers) make retrievals from satellites with a spatial resolution of approximately 1 kilometer (i.e., SeaWiFS) or less (i.e., MODIS) reasonable for most of the ecosystem. Second, CB is highly influenced by freshwater flow from major rivers, making it a classic Case 2 water body with significant concentrations of chlorophyll, particulates and chromophoric dissolved organic matter (CDOM) that highly impact the shape of reflectance spectra. Finally, past and ongoing research efforts provided an expensive data set of optical observations that support the goal of this project.

Harding, Lawrence W., Jr.↗

NASA NTRS2013

Doppler Lidar Sensor for Precision Navigation in GPS-Deprived Environment

Landing mission concepts that are being developed for exploration of solar system bodies are increasingly ambitious in their implementations and objectives. Most of these missions require accurate position and velocity data during their descent phase in order to ensure safe, soft landing at the pre-designated sites. Data from the vehicle's Inertial Measurement Unit will not be sufficient due to significant drift error after extended travel time in space. Therefore, an onboard sensor is required to provide the necessary data for landing in the GPS-deprived environment of space. For this reason, NASA Langley Research Center has been developing an advanced Doppler lidar sensor capable of providing accurate and reliable data suitable for operation in the highly constrained environment of space. The Doppler lidar transmits three laser beams in different directions toward the ground. The signal from each beam provides the platform velocity and range to the ground along the laser line-of-sight (LOS). The six LOS measurements are then combined in order to determine the three components of the vehicle velocity vector, and to accurately measure altitude and attitude angles relative to the local ground. These measurements are used by an autonomous Guidance, Navigation, and Control system to accurately navigate the vehicle from a few kilometers above the ground to the designated location and to execute a gentle touchdown. A prototype version of our lidar sensor has been completed for a closed-loop demonstration onboard a rocket-powered terrestrial free-flyer vehicle.

Amzajerdian, F.↗

NASA NTRS1984

Somali current studied from SEASAT altimetry

Mesoscale variability has been obtained for the world ocean from satellite altimetry by using the repetitive tracks data of SEASAT. No significant results were obtained for the Somali current area for two main reasons: the repetitive tracks are too sparse to cover the expected eddy pattern and these data were obtained in late September and early October when the current is strongly decaying. The non-repetitive period of SEASAT offers the possibility to study a dozen of tracks parallel to the eddy axis or crossing it. These are used here to deduce the dynamic topography of the Somali current. Data error reduction and tide and orbit corrections are addressed. A local geoid was built using a collocation inverse method to combine surface gravity data and altimetry: the repetitive tracks show no variability (which confirms that the current is quasi-inexistent at that time) and can be used as data for the local geoid. This should provide a measure of the absolute dynamic topography of the Somali current.

Perigaud, C.↗

NASA NTRS1998

RXTE Observation of Cygnus X-1: Spectral Analysis - 1

We present the results of the analysis of the broad-band spectrum of Cygnus X-1 from 3.0 to 200 keV, using data from a 10 ksec observation by the Rossi X-ray Timing Explorer. The spectrum can be well described phenomenologically by an exponentially cut-off power law with a photon index Gamma = 1.45(+0.01 -0.02) (a value considerably harder 0.02 than typically found), e-folding energy E(sub f) = 162(+9 -8) keV, plus a deviation from a power law that formally can be modeled as a thermal blackbody with temperature kT(sub bb) = 1.2(+0.0 -0.1) keV. Although the 3-30 keV portion of the spectrum can be fit with a reflected power law with Gamma = 1.81 + or - 0.01 and covering fraction f = 0.35 + or - 0.02, the quality of the fit is significantly reduced when the HEXTE data in the 30-100 keV range is included, as there is no observed hardening in the power law within this energy range. As a physical description of this system, we apply the accretion disc corona models of Dove, Wilms & Begelman (1997a) - where the temperature of the corona is determined self-consistently. A spherical corona with a total optical depth pi = 1.6 + or - 0.1 and an average temperature kT(sub c) = 87 + or - 5 keV, surrounded by an exterior cold disc, does provide a good description of the data (X(exp 2 sub red) = 1.55). These models deviate from red the data by up to 7% in the 5 - 10 keV range, and we discuss possible reasons for these discrepancies. However, considering bow successfully the spherical corona reproduces the 10 - 200 keV data, such "pboton-starved" coronal geometries seem very promising for explaining the accretion processes of Cygnus X-1.

Dove, James B.↗

NASA NTRS2006

Symbolic Constraint Maintenance Grid

Version 3.1 of Symbolic Constraint Maintenance Grid (SCMG) is a software system that provides a general conceptual framework for utilizing pre-existing programming techniques to perform symbolic transformations of data. SCMG also provides a language (and an associated communication method and protocol) for representing constraints on the original non-symbolic data. SCMG provides a facility for exchanging information between numeric and symbolic components without knowing the details of the components themselves. In essence, it integrates symbolic software tools (for diagnosis, prognosis, and planning) with non-artificial-intelligence software. SCMG executes a process of symbolic summarization and monitoring of continuous time series data that are being abstractly represented as symbolic templates of information exchange. This summarization process enables such symbolic- reasoning computing systems as artificial- intelligence planning systems to evaluate the significance and effects of channels of data more efficiently than would otherwise be possible. As a result of the increased efficiency in representation, reasoning software can monitor more channels and is thus able to perform monitoring and control functions more effectively.

James, Mark↗

NASA NTRS1995

Study of the Effect of Two-Dimensional Cavities on the Boundary Layer in an Adverse Pressure Gradient

One concept for high lift aerodynamics is the trapped-vortex. Recently it has been suggested that several spoilers located at different chordwise locations on an airfoil could be deployed to form several cavities in the chordwise direction. This may provide a means of increasing upper surface camber and thereby increase wing lift. It is envisioned that the cavities would be located on an airfoil in its pressure recovery region. Investigations of the effect of one or more cavities on the adjacent boundary layer in an adverse boundary layer were not found in a literature survey. Since flow separation can be caused by flow over cavities, boundary layer measurements were made in the vicinity of cavities which were located in an adverse pressure gradient to study the associated flow in an effort to identify any benefits. The experimental data from the present investigation indicate a minimal impact on the boundary layer profiles is caused by the presence of cavities in either a constant pressure freestream or an adverse pressure gradient. The data from the experimental investigation has been obtained and analyzed. The computational investigation using an incompressible Navier-Stokes code show that reasonable results are being obtained when they are compared with the experimental data.

Margason, Richard J.↗

NASA NTRS1972

Structure and orientations of solar-wind interaction fronts - Pioneer 6.

An analysis is given of five stream-stream interaction events observed in the Pioneer 6 plasma and field data. That the time profiles of all the parameters are consistent among the events and with previous descriptions given in the literature substantiates the notion of a common interaction type. The velocity variations in four of the events tend to lie in planes approximately parallel to the corotation spiral; thus it is implied that the events are reasonably stationary in time in the corotating frame. The data are interpreted in terms of a corotating interaction front, which is a ridge of high pressure parallel to a corotating spiral. The increased pressure is due to radial compression of the streams. The east-west (zonal) flow directions also occur in the front and are shown to be produced by the zonal pressure gradient of the pressure ridge.

Siscoe, G. L.↗

NASA NTRS2022

A Robust Machine Learning Schema for Developing, Maintaining, and Disseminating Machine Learning Models

Recent advances in the development of machine learning (ML) algorithms have enabled the creation of predictive models that can improve decision making, decrease computational cost, and improve efficiency in a variety of fields. As an organization begins to develop and implement such models, the data used in the training, validation, and testing of ML models, the model parameters, and the use cases or limitations of the models must be properly stored to ensure models are both fully traceable and used correctly. In the context of predicting material behavior, advances in computationally intense, physics-based modeling of material behavior at various length scales and the emergence of Integrated Computational Materials Engineering (ICME) have driven the need for developing data-driven surrogate models of the physics-based simulation tools using ML techniques. Surrogate model development allows for accurate material behavior prediction at a fraction of the cost of its physics-based counterpart, allowing for multiscale simulations of real-world applications, further enabling the ability to design fit-for-purpose materials for a reasonable computational investment. However, training such models requires extensive data, and thus, effective data management is necessary to reach the full potential that ML can offer to material design and ICME. This paper proposes a generalized, robust schema that allows organizations to store both real (experimental) and virtual (simulation) data used to train ML models and the defining model parameters and architectures within the Granta MI Platform. The developed schema allows for various types of data inputs and outputs, including single point values, time-series data, and images that can be used in the prediction of material behavior, while following outlined best practices for effective data management. An effective schema for ML data and models can help prevent the recreation of virtual/real training data and surrogate models, help reduce the time to create new models similar to existing ones by offering a starting point in the hyperparameter determination stages, minimize resources devoted to verification and validation (V&V) and certification of models, and ensure that data and surrogate models are not misused due to full traceability of both the data and ML model. It also allows organizations access to models that have already been developed, such that they can be used in the design of new materials, enabling the overall goals of ICME.

Brandon L. Hearley↗

NASA NTRSDate not supplied

Predicting Fiber Failure of Plain Weave Fabric with Recursive Multiscale Micromechanics

Recent advances in the development of machine learning (ML) algorithms have enabled the creation of predictive models that can improve decision making, decrease computational cost, and improve efficiency in a variety of fields. As an organization begins to develop and implement such models, the data used in the training, validation, and testing of machine learning models, the model parameters, and the use cases or limitations of the models must be properly stored to ensure models are both fully traceable and used correctly. In the context of predicting material behavior, advances in computationally intense, physics-based, modeling of material behavior at various length scales, and the emergence of Integrated Computational Materials Engineering (ICME) have driven the need for developing data-driven surrogate models of the physics-based simulation tools using machine learning (ML) techniques. Surrogate model development allows for accurate material behavior prediction at a fraction of the cost of its physics-based counterpart, allowing for multiscale simulations of real-world applications, further enabling the ability to design fit-for-purpose materials for a reasonable computational investment. However, training such models requires extensive data, and thus effective data management is necessary to reach the full potential that ML can offer to material design and ICME. This paper proposes a generalized, robust schema that allows organizations to store both real (experimental) and virtual (simulation) data used to train machine learning models and the defining model parameters and architectures. The developed schema allows for various types of data inputs and outputs, including single point values, time-series data, and images that can be used in for various types of machine learning models while following outlined best practices for effective data management. An effective schema for machine learning data and models can help prevent the recreation of virtual/real training data and surrogate models, can help reduce the time to create new models similar to existing ones by offering a starting point in the hyperparameter determination stages, minimize resources devoted to verification and validation (V&V) and certification of models, and ensure that data and surrogate models are not misused due to full traceability of both the data and ML model. It also allows organizations access to models that have already been developed, such that they can be used in the design of new materials, enabling the overall goals of ICME.

Failure↗

NASA NTRS1993

Certification of ICI 1012 optical data storage tape

ICI has developed a unique and novel method of certifying a Terabyte optical tape. The tape quality is guaranteed as a statistical upper limit on the probability of uncorrectable errors. This is called the Corrected Byte Error Rate or CBER. We developed this probabilistic method because of two reasons why error rate cannot be measured directly. Firstly, written data is indelible, so one cannot employ write/read tests such as used for magnetic tape. Secondly, the anticipated error rates need impractically large samples to measure accurately. For example, a rate of 1E-12 implies only one byte in error per tape. The archivability of ICI 1012 Data Storage Tape in general is well characterized and understood. Nevertheless, customers expect performance guarantees to be supported by test results on individual tapes. In particular, they need assurance that data is retrievable after decades in archive. This paper describes the mathematical basis, measurement apparatus and applicability of the certification method.

Howell, J. M.↗

NASA NTRS2016

Constructing the 'Best' Reliability Data for the Job - Developing Generic Reliability Data from Alternative Sources Early in a Product's Development Phase

Reliability practitioners advocate getting reliability involved early in a product development process. However, when assigned to estimate or assess the (potential) reliability of a product or system early in the design and development phase, they are faced with lack of reasonable models or methods for useful reliability estimation. Developing specific data is costly and time consuming. Instead, analysts rely on available data to assess reliability. Finding data relevant to the specific use and environment for any project is difficult, if not impossible. Instead, analysts attempt to develop the "best" or composite analog data to support the assessments. Industries, consortia and vendors across many areas have spent decades collecting, analyzing and tabulating fielded item and component reliability performance in terms of observed failures and operational use. This data resource provides a huge compendium of information for potential use, but can also be compartmented by industry, difficult to find out about, access, or manipulate. One method used incorporates processes for reviewing these existing data sources and identifying the available information based on similar equipment, then using that generic data to derive an analog composite. Dissimilarities in equipment descriptions, environment of intended use, quality and even failure modes impact the "best" data incorporated in an analog composite. Once developed, this composite analog data provides a "better" representation of the reliability of the equipment or component. It can be used to support early risk or reliability trade studies, or analytical models to establish the predicted reliability data points. It also establishes a baseline prior that may updated based on test data or observed operational constraints and failures, i.e., using Bayesian techniques. This tutorial presents a descriptive compilation of historical data sources across numerous industries and disciplines, along with examples of contents and data characteristics. It then presents methods for combining failure information from different sources and mathematical use of this data in early reliability estimation and analyses.

Kleinhammer, Roger K.↗

NASA NTRS1976

Direct measurements at Mach 6 of turbulent skin-friction reduction by injection from single and multiple flush slots

The surface skin-friction reduction downstream of one to four successive flush slots injecting at an angle of 10 deg into a turbulent Mach 6 boundary layer has been determined from direct measurements of surface shear. Increasing the number of succeeding slots increases the skin-friction reduction, but this trend reverses at high injection rates. The incremental improvement in skin-friction reduction decreases with increasing number of slots. Comparison with previously reported step slot data indicates that step slots with tangential injection are more effective in reducing skin friction than the present flush slot configuration. Finite-difference predictions are in reasonable agreement with skin-friction and boundary-layer profile data.

Srokowski, A. J.↗

NASA NTRS1990

A structure for maturing intelligent tutoring system student models

A special structure is examined for evolving a detached model of the user of an intelligent tutoring system. Tutoring is used in the context of education and training devices. A detached approach to populating the student model data structure is examined in the context of the need for time dependent reasoning about what the student knows about a particular concept in the domain of interest. This approach, to generating a data structure for the student model, allows an inference engine separate from the tutoring strategy determination to be used. This methodology has advantages in environments requiring real-time operation.

Holmes, Willard M.↗

NASA NTRS1976

The sodium chloride primary pressure gauge

The failure of a central force model for sodium chloride is discussed. It is noted that it does not closely satisfy the Cauchy conditions at low temperatures, and that it fails the central force requirement of the Love condition. The available shock data for sodium chloride and its analysis is examined, and two reasons why the Hugoniot transformation pressure is likely to be less than 231 kbar are discussed. The important (but unjustified) theoretical assumptions made in converting Hugoniot to isothermal data is discussed; it is noted that serious error can enter for very large pressures for a given material and that at such high pressures the isothermal data should thus be considered only semiquantitative even if the Hugoniot data itself is accurate. An alternate method of estimating the isothermal transformation pressure from the Hugoniot transformation pressure is used. This method is based on the temperature derivative of the transformation pressure. On this basis it is concluded that an upper bound for the isothermal transformation of NaCl (to a CsCl-type structure) at room temperature is 257 kbar; it is noted that the actual value may be considerably less than this.

Ruoff, A. L.↗

NASA NTRS1978

Microwave brightness of polar firn as measured by Nimbus 5 and 6 ESMR

The microwave emission from a half-space medium characterized by coordinate dependent scattering and absorbing centers was calculated by numerically solving the radiative transfer equation by the method of invariant imbedding. A Mie scattering phase function and surface polarization was included in the calculation. Also included are the physical temperature profile and the temperature variation of the index of refraction for ice. Using published values of grain size and temperature profile data of polar firn, the brightness temperature was calculated for the 1.55 cm and 0.8 cm wavelengths. For selected regions in Greenland and Antarctica, the results are in reasonable agreement with the observed Nimbus-5 and Nimbus-6 ESMR data.

Chang, A. T. C.↗

NASA NTRS1982

An initial model for estimating soybean development stages from spectral data

A model, utilizing a direct relationship between remotely sensed spectral data and soybean development stage, has been proposed. The model is based upon transforming the spectral data in Landsat bands to greenness values over time and relating the area of this curve to soybean development stage. Soybean development stages were estimated from data acquired in 1978 from research plots at the Purdue University Agronomy Farm as well as Landsat data acquired over sample areas of the U.S. Corn Belt in 1978 and 1979. Analysis of spectral data from research plots revealed that the model works well with reasonable variation in planting date, row spacing, and soil background. The R-squared of calculated U.S. observed development stage exceeded 0.91 for all treatment variables. Using Landsat data the calculated U.S. observed development stage gave an R-squared of 0.89 in 1978 and 0.87 in 1979. No difference in the models performance could be detected between early and late planted fields, small and large fields, or high and low yielding fields.

Henderson, K. E.↗