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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

A Novel Photonic Clock and Carrier Recovery Device

As data communication rates climb toward ten Gb/s, clock recovery and synchronization become more difficult, if not impossible, using conventional electronic circuits. We present in this article experimental results of a high speed clock and carrier recovery using a novel device called a photonic oscillator that we recently developed in our laboratory. This device is capable of recovering clock signals up to 70 GHz. To recover the clock, the incoming data is injected into the photonic oscillator either through the optical injection port or the electrical injection port. The free running photonic oscillator is tuned to oscillate at a nominal frequency equal to the clock frequency of the incoming data. With the injection of the data, the photonic oscillator will be quickly locked to clock frequency of the data stream while rejecting other frequency components associated with the data. Consequently, the output of the locked photonic oscillator is a continuous periodical wave synchronized with the incoming data or simply the recovered clock. We have demonstrated a clock to spur ratio of more than 60 dB of the recovered clock using this technique. Similar to the clock recovery, the photonic oscillator can be used to recover a high frequency carrier degraded by noise and an improvement of about 50 dB in signal-to-noise ratio was demonstrated. The photonic oscillator has both electrical and optical inputs and outputs and can be directly interfaced with a photonic system without signal conversion. In addition to clock and carrier recovery, the photonic oscillator can also be used for (1) stable high frequency clock signal generation, (2) frequency multiplication, (3) square wave and comb frequency generation, and (4) photonic phase locked loop.

Yao, X. Steve↗
NASA NTRS2016

Wind Tunnel Balance Calibration: Are 1,000,000 Data Points Enough?

Measurement systems are typically calibrated based on standard practices established by a metrology standards laboratory, for example the National Institute for Standards and Technology (NIST), or dictated by an organization's metrology manual. Therefore, the calibration is designed and executed according to an established procedure. However, for many aerodynamic research measurement systems a universally accepted standard, traceable approach does not exist. Therefore, a strategy for how to develop a calibration protocol is left to the developer or user to define based on experience and recommended practice in their respective industry. Wind tunnel balances are one such measurement system. Many different calibration systems, load schedules and procedures have been developed for balances with little consensus on a recommended approach. Especially lacking is guidance the number of calibration data points needed. Regrettably, the number of data points tends to be correlated with the perceived quality of the calibration. Often, the number of data points is associated with ones ability to generate the data rather than by a defined need in support of measurement objectives. Hence the title of the paper was conceived to challenge recent observations in the wind tunnel balance community that shows an ever increasing desire for more data points per calibration absent of guidance to determine when there are enough. This paper presents fundamental concepts and theory to aid in the development of calibration procedures for wind tunnel balances and provides a framework that is generally applicable to the characterization and calibration of other measurement systems. Questions that need to be answered are for example: What constitutes an adequate calibration? How much data are needed in the calibration? How good is the calibration? This paper will assist a practitioner in answering these questions by presenting an underlying theory on how to evaluate a calibration based on objective measures. This will enable the developer and user to design calibrations with quantified performance in terms of their capability to meet the user's objectives and a basis for comparing existing calibrations that may have been developed in an ad-hoc manner.

Rhew, Ray D.↗
NASA NTRS2017

HMI Data Driven Magnetohydrodynamic Model Predicted Active Region Photospheric Heating Rates: Their Scale Invariant, Flare Like Power Law Distributions, and Their Possible Association With Flares

A data driven, near photospheric, 3 D, non-force free magnetohydrodynamic model pre- dicts time series of the complete current density, and the resistive heating rate Q at the photosphere in neutral line regions (NLRs) of 14 active regions (ARs). The model is driven by time series of the magnetic field B observed by the Helioseismic & Magnetic Imager on the Solar Dynamics Observatory (SDO) satellite. Spurious Doppler periods due to SDO orbital motion are filtered out of the time series for B in every AR pixel. Errors in B due to these periods can be significant. The number of occurrences N(q) of values of Q > or = q for each AR time series is found to be a scale invariant power law distribution, N(Q) / Q−s, above an AR dependent threshold value of Q, where 0.3952 < or = s < or = 0.5298 with mean and standard deviation of 0.4678 and 0.0454, indicating little variation between ARs. Observations show that the number of occurrences N(E) of coronal flares with a total energy released > or = E obeys the same type of distribution, N(E) / E−S, above an AR dependent threshold value of E, with 0.38 < or approx. S < or approx. 0.60, also with little variation among ARs. Within error margins the ranges of s and S are nearly identical. This strong similarity between N(Q) and N(E) suggests a fundamental connection between the process that drives coronal flares and the process that drives photospheric NLR heating rates in ARs. In addition, results suggest it is plausible that spikes in Q, several orders of magnitude above background values, are correlated with times of the subsequent occurrence of M or X flares.

Goodman, Michael L.↗
NASA NTRS2017

HMI Data Driven Magnetohydrodynamic Model Predicted Active Region Photospheric Heating Rates: Their Scale Invariant, Flare Like Power Law Distributions, and Their Possible Association With Flares

A data driven, near photospheric, 3 D, non-force free magnetohydrodynamic model predicts time series of the complete current density, and the resistive heating rate Q at the photosphere in neutral line regions (NLRs) of 14 active regions (ARs). The model is driven by time series of the magnetic field B observed by the Helioseismic and Magnetic Imager on the Solar Dynamics Observatory (SDO) satellite. Spurious Doppler periods due to SDO orbital motion are filtered out of the time series for B in every AR pixel. Errors in B due to these periods can be significant. The number of occurrences N(q) of values of Q > or = q for each AR time series is found to be a scale invariant power law distribution, N(Q) / Q−s, above an AR dependent threshold value of Q, where 0.3952 < or = s < or = 0.5298 with mean and standard deviation of 0.4678 and 0.0454, indicating little variation between ARs. Observations show that the number of occurrences N(E) of coronal flares with a total energy released > or = E obeys the same type of distribution, N(E) / E−S, above an AR dependent threshold value of E, with 0.38 < or approx. S < or approx. 0.60, also with little variation among ARs. Within error margins the ranges of s and S are nearly identical. This strong similarity between N(Q) and N(E) suggests a fundamental connection between the process that drives coronal flares and the process that drives photospheric NLR heating rates in ARs. In addition, results suggest it is plausible that spikes in Q, several orders of magnitude above background values, are correlated with times of the subsequent occurrence of M or X flares.

Goodman, Michael L.↗
NASA NTRS1992

Microburst characteristics determined from 1988-1991 TDWR testbed measurements

This paper presents some recent results germane to airborne windshear system design and certification. We first discuss the data analysis procedure and the associated caveats. The relative frequency, severity, and duration of microburst hazards at the various locations is important for determining the tradeoffs between safety and operational impact of false alerts which are encompassed in detection system thresholds. We then consider radar/lidar design issues such as reflective in microbursts and the vertical structure of outflows. Finally, we provide recent surface thermodynamic data associated with microbursts.

Biron, Paul J.↗
NASA NTRS2014

Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data

A code for predicting supersonic jet broadband shock-associated noise was assessed using a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify deficiencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the measured data, a sensitivity analysis of the model parameters with emphasis on the definition of the convection velocity parameter, and a least-squares fit of the predicted to the measured shock-associated noise component spectra, resulted in a new definition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.

Dahl, Milo D.↗
NASA NTRS1993

Geologic mapping using integrated AIRSAR, AVIRIS, and TIMS data

The multi-sensor aircraft campaign called the 'Geologic Remote Sensing Field Experiment' (GRSFE), conducted during 1989 in the southwestern United States, collected multiple airborne remote sensing data sets and associated field and laboratory measurements. The GRSFE airborne data sets used in this study include the airborne Synthetic Aperture Radar (AIRSAR), the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and the Thermal Infrared Multispectral Scanner (TIMS). Each sensor's unique characteristics were used for this study in a combined analysis scheme for geologic mapping. AIRSAR was used to map structures and landforms, AVIRIS was used to map mineralogy, and TIMS was used to map lithology. Visual data integration using IHS transforms and combined numerical analysis using derived geophysical and geologic parameters with 'multispectral' techniques resulted in improved geologic mapping over that possible using each data set individually.

Kruse, Fred A.↗
NASA NTRS2000

Comparison of Daily Total Precipitable Water From Satellite and Model Reanalysis Fields

Previous studies have shown that there is fairly good agreement between the monthly values of total precipitable water (TPW) from the NVAP data set, a multi satellite and radiosonde merged data product, and the NCEP reanalysis TPW data. However, there are regions and time periods where significant differences between the data sets are found in the monthly mean TPW time series and period of record trends. To better understand these differences seen in the monthly data values, the daily mean TPW data are examined. Possible contributions to the TPW differences such as data quality of the individual NVAP data set components associated with missing or irregular daily values are addressed. Also, effects associated with the weighting of the individual NVAP data set components to form a merged product are considered. The daily variations in TPW exhibited by each data set are also quantified and compared between the data sets.

Jedlovec, Gary J.↗
NASA NTRS2005

Smart Sensors' Role in Integrated System Health Management

During the last decade, there has been a major effort in the aerospace industry to reduce the cost per pond of payload and become competitive in the international market. Competition from Europe, Japan, and China has reduced this cost to almost a third from 1990 to 2000. This cost has leveled in recent years to an average price of around $12,000/pound of payload. One of NASA's goals is to promote the development of technologies to reduce this cost by a factor of 10 or more Exploration of space, specially manned exploration missions, involves very complex launch and flight vehicles, associated ground support systems, and extensive human support during all phases of the mission. When considering the Space Shuttle Program, we can see that vehicle and ground support systems' processing, operation, and maintenance represent a large percentage of the program cost and time. Reducing operating, processing and maintenance costs will greatly reduce the cost of Exploration programs. The Integrated System Health Management (ISHM) concept is one of the technologies that will help reduce these operating, processing and maintenance costs. ISHM is an integrated health monitoring system applicable to both flight and ground systems. It automatically and autonomously acquires information from sensors and actuators and processes that information using the ISHM-embedded knowledge. As a result, it establishes the health of the system based on the acquired information and its prior knowledge. When this concept is fully implemented, ISHM systems shall be able to perform failure prediction and remediation before actual hard failures occurs, preventing its costly consequences. Data sources, sensors, and their associated data acquisition systems, constitute the foundation of the system. A smart sensing architecture is required to support the acquisition of reliable, high quality data, required by the ISHM. A thorough definition of the smart sensor architectures, their embedded diagnostic agents, and communication protocols need to be established and standardized to allow the embedding and exchange of health information among sensors and ISHM. This workshop is aimed to foster the exchange of ideas and lessons learned between government, industry and academia to aid in the establishment of ISHM (and smart sensors) standards and guidelines as well as to identify present technology gaps that will have to be overcome to successfully achieve this goal.

Perotti, Jose M.↗
NASA NTRS2014

Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data

A code for predicting supersonic jet broadband shock-associated noise was assessed us- ing a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify de ciencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the mea- sured data, a sensitivity analysis of the model parameters with emphasis on the de nition of the convection velocity parameter, and a least-squares t of the predicted to the mea- sured shock-associated noise component spectra, resulted in a new de nition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.

Dahl, Milo D.↗
NASA NTRS1990

An estimating formula for ion-atom association rates in gases

A simple estimating formula is derived for rate coefficients of three-body ion atom association in gases and compare its predictions to experimental data on ion association and three-body radiative charge transfer reactions of singly- and doubly-charged rare-gas ions. The formula appears to reproduce most experimental data quite well. It may be useful for estimating the rates of reactions that have not been studied in the laboratory.

Chatterjee, B. K.↗
NASA NTRS1997

Gaseous abundances and methane supersaturation in Titan's troposphere

Various properties of Titan's troposphere are inferred from an analysis of Voyager I infrared spectrometer (IRIS) data between 200 and 600/ cm. Two homogeneous spectral averages acquired at widely separated emission angles are chosen for the analysis. Both data sets are associated with northern low latitudes very close to that of the radio science ingress occultation point. Solutions require simultaneous nonlinear least-squares fits to the two IRIS data sets, coupled with iteration of the radio occultation refractivity data. Values and associated 1-sigma uncertainties of several parameters are inferred from our analysis. These include mole fractions for molecular hydrogen (approx. 0.0011), argon (small), and methane near the surface ( approx. 0.057). Solutions are also obtained for the hydrogen parafraction (close to equilibrium, with considerable uncertainty), air temperature near the surface ( approx. 93 K), surface surface temperature discontinuity (approx. 1 K), and maximum degree of methane supersaturation in the upper troposphere (approx. 1.5). Actual values for the above-mentioned parameters depend on the amount of ethane cloud near the tropopause. There is no evidence for methane clouds in the upper troposphere, nor is their presence compatible with large degrees of supersaturation. A wave number dependence for the stratospheric haze opacity is inferred similar to that found for a polymeric residue created in laboratory discharge experiments. This haze appears to be uniformly distributed with latitude between altitudes of 40 and 160 km, provided those nighttime data at southern high latitudes that are discounted.

Samuelson, Robert E.↗
NASA NTRS1987

Studies and analyses of the space shuttle main engine. Failure information propagation model data base and software

The failure information propagation model (FIPM) data base was developed to store and manipulate the large amount of information anticipated for the various Space Shuttle Main Engine (SSME) FIPMs. The organization and structure of the FIPM data base is described, including a summary of the data fields and key attributes associated with each FIPM data file. The menu-driven software developed to facilitate and control the entry, modification, and listing of data base records is also discussed. The transfer of the FIPM data base and software to the NASA Marshall Space Flight Center is described. Complete listings of all of the data base definition commands and software procedures are included in the appendixes.

Tischer, A. E.↗
NASA NTRS1974

Automated Data Management Information System (ADMIS)

ADMIS stores and controls data and documents associated with manned space flight effort. System contains all data oriented toward a specific document; it is primary source of reports generated by the system. Each group of records is composed of one document record, one distribution record for each recipient of the document, and one summary record.

Blackstone, C.↗
NASA NTRS2014

Data Used in Quantified Reliability Models

Data is the crux to developing quantitative risk and reliability models, without the data there is no quantification. The means to find and identify reliability data or failure numbers to quantify fault tree models during conceptual and design phases is often the quagmire that precludes early decision makers consideration of potential risk drivers that will influence design. The analyst tasked with addressing a system or product reliability depends on the availability of data. But, where is does that data come from and what does it really apply to? Commercial industries, government agencies, and other international sources might have available data similar to what you are looking for. In general, internal and external technical reports and data based on similar and dissimilar equipment is often the first and only place checked. A common philosophy is "I have a number - that is good enough". But, is it? Have you ever considered the difference in reported data from various federal datasets and technical reports when compared to similar sources from national and/or international datasets? Just how well does your data compare? Understanding how the reported data was derived, and interpreting the information and details associated with the data is as important as the data itself.

DeMott, Diana↗
NASA NTRS2002

A Data Management System for International Space Station Simulation Tools

Groups associated with the design, operational, and training aspects of the International Space Station make extensive use of modeling and simulation tools. Users of these tools often need to access and manipulate large quantities of data associated with the station, ranging from design documents to wiring diagrams. Retrieving and manipulating this data directly within the simulation and modeling environment can provide substantial benefit to users. An approach for providing these kinds of data management services, including a database schema and class structure, is presented. Implementation details are also provided as a data management system is integrated into the Intelligent Virtual Station, a modeling and simulation tool developed by the NASA Ames Smart Systems Research Laboratory. One use of the Intelligent Virtual Station is generating station-related training procedures in a virtual environment, The data management component allows users to quickly and easily retrieve information related to objects on the station, enhancing their ability to generate accurate procedures. Users can associate new information with objects and have that information stored in a database.

Betts, Bradley J.↗
NASA NTRS2018

GMI-IPS: Python Processing Software for Aircraft Campaigns

NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the spatial grid of the flight path as defined by the pressure, latitude, and longitude points at each flight time record, a weighted average is then calculated from the nearest neighbors in two dimensions (latitude, longitude). Using SciPya's Regular Grid Interpolator, interpolation functions are generated for the GMI model grid and the calculated weighted averages. The flight path points are then extracted from the ATom ICARTT instrument file, and are sent to the multi-dimensional interpolating functions to generate GMI field quantities along the spatial path of the flight. The interpolated field quantities are then written to a ICARTT data file, which is stored for further manipulation. The GMI-IPS is aware of a generic ATom ICARTT header format, containing basic information for all flight campaigns. The GMI-IPS includes logic to edit metadata for the derived field quantities, as well as modify the generic header data such as processing dates and associated instrument files. The ICARTT interpolated data is then appended to the modified header data, and the ICARTT processing is complete for the given flight and ready for collaboration. The output ICARTT data adheres to the ICARTT file format standards V1.1. The visualization component of the GMI-IPS uses Matplotlib extensively and has several functions ranging in complexity. First, it creates a model background curtain for the flight (time versus model eta levels) with the interpolated flight data superimposed on the curtain. Secondly, it creates a time-series plot of the interpolated flight data. Lastly, the visualization component creates averaged 2D model slices (longitude versus latitude) with overlaid flight track circles at key pressure levels. The GMI-IPS consists of a handful of classes and supporting functionality that have been generalized to be compatible with any ICARTT file that adheres to the base class definition. The base class represents a generic ICARTT entry, only defining a single time entry and 3D spatial positioning parameters. Other classes inherit from this base class; several classes for input ICARTT instrument files, which contain the necessary flight positioning information as a basis for data processing, as well as other classes for output ICARTT files, which contain the interpolated model data. Utility classes provide functionality for routine procedures such as: comparing field names among ICARTT files, reading ICARTT entries from a data file and storing them in data structures, and returning a reduced spatial grid based on a collection of ICARTT entries. Although the GMI-IPS is compatible with GMI model data, it can be adapted with reasonable effort for any simulation that creates Hierarchical Data Format (HDF) files. The same can be said of its adaptability to ICARTT files outside of the context of the ATom mission. The GMI-IPS contains just under 30,000 lines of code, eight classes, and a dozen drivers and utility programs. It is maintained with GIT source code management and has been used to deliver processed GMI model data for the ATom campaigns that have taken place to date.

Damon, M. R.↗
NASA NTRS1985

Aircraft measurements of the atmospheric electrical global circuit during the period 1971-1984

This report will update an investigation of the global circuit conducted over the last 14 years through aircraft measurements of the variation of ionospheric potential and associated parameters. The data base included electric field, conductivity, and air-earth current density profiles from the tropics (25 deg N) to the Arctic (79 deg N). Almost all of the data have been obtained over the ocean to reduce noise associated with local generators, aerosols, and convection. Recently, two aircraft have been utilized to obtain, for the first time, quasi-periodic sets of simultaneous ionospheric potential (VI) soundings at remote locations and extending over time spans sufficiently long so that the universal time diurnal variation (Carnegie curve) could be observed. In additon, these measurements provided the first detection of the modulation of electric fields in the troposphere caused by the double vortex ionospheric convection pattern. Besides summarizing these measurements and comparing them to similar data obtained by other groups, this report discusses meteorological sources of error and criteria for determining if the global circuit is being measured rather than variations caused by local meteorological processes.

Markson, R.↗