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This paper presents a DOD E3 program overview on integrated circuit immunity. The topics include: 1) EMI Immunity Testing; 2) Threshold Definition; 3) Bias Tee Function; 4) Bias Tee Calibration Set-Up; 5) EDM Test Figure; 6) EMI Immunity Levels; 7) NAND vs. and Gate Immunity; 8) TTL vs. LS Immunity Levels; 9) TP vs. OC Immunity Levels; 10) 7805 Volt Reg Immunity; and 11) Seventies Chip Set. This paper is presented in viewgraph form.
This paper proposes a methodology for the analysis and design optimization of models subject to parametric uncertainty, where hard inequality constraints are present. Hard constraints are those that must be satisfied for all parameter realizations prescribed by the uncertainty model. Emphasis is given to uncertainty models prescribed by norm-bounded perturbations from a nominal parameter value, i.e., hyper-spheres, and by sets of independently bounded uncertain variables, i.e., hyper-rectangles. These models make it possible to consider sets of parameters having comparable as well as dissimilar levels of uncertainty. Two alternative formulations for hyper-rectangular sets are proposed, one based on a transformation of variables and another based on an infinity norm approach. The suite of tools developed enable us to determine if the satisfaction of hard constraints is feasible by identifying critical combinations of uncertain parameters. Since this practice is performed without sampling or partitioning the parameter space, the resulting assessments of robustness are analytically verifiable. Strategies that enable the comparison of the robustness of competing design alternatives, the approximation of the robust design space, and the systematic search for designs with improved robustness characteristics are also proposed. Since the problem formulation is generic and the solution methods only require standard optimization algorithms for their implementation, the tools developed are applicable to a broad range of problems in several disciplines.
The liftoff phase induces some of the highest acoustic loading over a broad frequency for a launch vehicle. These external acoustic environments are used in the prediction of the internal vibration responses of the vehicle and components. Thus, predicting these liftoff acoustic environments is critical to the design requirements of any launch vehicle but there are challenges. Present liftoff vehicle acoustic environment prediction methods utilize stationary data from previously conducted hold-down tests; i.e. static firings conducted in the 1960's, to generate 1/3 octave band Sound Pressure Level (SPL) spectra. These data sets are used to predict the liftoff acoustic environments for launch vehicles. To facilitate the accuracy and quality of acoustic loading, predictions at liftoff for future launch vehicles such as the Space Launch System (SLS), non-stationary flight data from the Ares I-X were processed in PC-Signal in two forms which included a simulated hold-down phase and the entire launch phase. In conjunction, the Prediction of Acoustic Vehicle Environments (PAVE) program was developed in MATLAB to allow for efficient predictions of sound pressure levels (SPLs) as a function of station number along the vehicle using semiempirical methods. This consisted, initially, of generating the Dimensionless Spectrum Function (DSF) and Dimensionless Source Location (DSL) curves from the Ares I-X flight data. These are then used in the MATLAB program to generate the 1/3 octave band SPL spectra. Concluding results show major differences in SPLs between the hold-down test data and the processed Ares IX flight data making the Ares I-X flight data more practical for future vehicle acoustic environment predictions.
Correlation-consistent basis sets are compared with Pople-type basis sets for the calculation of atomization energies using the G2(B3LYP/MP2/CC) approach. Without a higher-level correction, the smallest errors are found for the augmented- correlation-consistent polarized valence triple zeta plus tight d basis sets. However, after inclusion of a higher-level correction, the combination of the 6-311G** basis set for the high-level correlation treatment and 6-311+G(3df,2p) for the MP2 step yields the best results. At the spin-unrestricted CCSD(T) level and for the basis set considered in this work, the G2(B3LYP/MP2/CC) approach works better than the PCIX approach for the atomization energies of the 55 G2 molecules.
An algorithm for synthesizing optimal aircraft trajectories for specified range was developed and implemented in a computer program written in FORTRAN IV. The algorithm, its computer implementation, and a set of example optimum trajectories for the Boeing 727-100 aircraft are described. The algorithm optimizes trajectories with respect to a cost function that is the weighted sum of fuel cost and time cost. The optimum trajectory consists at most of a three segments: climb, cruise, and descent. The climb and descent profiles are generated by integrating a simplified set of kinematic and dynamic equations wherein the total energy of the aircraft is the independent or time like variable. At each energy level the optimum airspeeds and thrust settings are obtained as the values that minimize the variational Hamiltonian. Although the emphasis is on an off-line, open-loop computation, eventually the most important application will be in an on-board flight management system.
The BOREAS RSS-14 team collected and processed several GOES-7 and GOES-8 image data sets that covered the BOREAS study region. The level-1 BOREAS GOES-8 images are raw data values collected by RSS-14 personnel at FSU and delivered to BORIS. The data cover 14-Jul-1995 to 21-Sep-1995 and 01-Jan-1996 to 03-Oct-1996. The data start out containing three 8-bit spectral bands and end up containing five 10-bit spectral bands. No major problems with the data have been identified. The data are contained in binary image format files. Due to the large size of the images, the level-1 GOES-8 data are not contained on the BOREAS CD-ROM set. An inventory listing file is supplied on the CD-ROM to inform users of what data were collected. The level-1 GOES-8 image data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). See sections 15 and 16 for more information. The data files are available on a CD-ROM (see document number 20010000884).
Simulation and analysis for modern engineering systems now routinely requires the merging of multiple disciplines, physical-domains, time-scales, and data sets — all at ever increasing levels. These capabilities are especially needed in the domain of Advanced Air Mobility, where rapidly emerging vehicle designs are significantly more complex, while having to be both cost-effective and safe. To meet these engineering challenges, machine learning methods are an attractive option for merging models and data across multiple areas while providing uncertainty quantification and maintaining computational efficiency. This paper examines the use of Gaussian process machine learning to generalize and enhance the commonly used class of quasi-Linear Parameter Varying models for fast full-envelope simulation while also supporting control system design and analysis with model uncertainty. Gaussian process machine learning is selected because it: can fuse multiple data sets, enables an easy trade-off between data fitting and smoothing, provides model uncertainty quantification, scales well with increasing complexity, and does not generally require starting from a large training data set. To demonstrate the benefits of the approach, a robust stability analysis with Gaussian process uncertainty is shown for a NASA reference design of an electric quad-rotor air-taxi concept vehicle with motor parameter uncertainty.
The concept of the sphere quadtree (SQT) is introduced to enable the structuring of spherically distributed data to be consistent with its geometry and facilitate mapping of the data onto a flat file system. The SQT is based on the recursive subdivision of the spherical triangles that result from the projection of the faces of an icosahedron onto a sphere. The SQT concept is insensitive to the distortions that occur far from the equator in spherically distributed data sets. Geographic data can be shown at several levels and at any resolution, allowing a system of referencing between data sets of different resolutions as well as data that are not geographically registered. SQTs are found to facilitate the search for particular spherically distributed data sets and improve the efficiency of surface rendering algorithms.
In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. In a NASA-funded project supporting the National Climate Assessment, we are providing historical and future measures of extreme heat to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The project s emphasis is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM output, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons, 2040 and 2090, are the focus of future assessments; these are compared to the recent past period of 1981-2000. We are characterizing regional-scale temperature and humidity conditions using GCM output for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM output have been analyzed to develop a heat stress climatology based on statistics of extreme heat indicators. Differences between the two future and past periods have been used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes, combined with hourly historical meteorological data at a spatial scale (12 km) much finer than that of GCMs, enable us to create future climate realizations, from which we compute the daily heat stress measures and related spatially-specific climatological fields. These include the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. All output is being provided at the 12 km spatial scale and will also be aggregated to the county level, which is a popular scale of analysis for public health researchers. County-level statistics will be made available by our collaborators at the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. CDC WONDER makes the information resources of the CDC available to public health professionals and the general public. This addition of heat stress measures to CDC WONDER will allow decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. It will also allow public health researchers and policy makers to better include such heat stress measures in the context of national health data available in the CDC WONDER system. The users will be able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.
The concept of a 'best approximating m-dimensional subspace' for a given set of vectors in n-dimensional whole space is introduced. Such a subspace is easily described in terms of the eigenvectors of an associated Gram matrix. This technique is used to approximate an achievable set for a discrete linear time-invariant dynamical system. This approximation characterizes the part of the state space that may be reached using modest levels of control. If the achievable set can be closely approximated by a proper subspace of the whole space then the system is 'essentially uncontrollable'. The notion finds application in studies of failure-tolerant systems, and in decoupling.
The results of data obtained at The University of Texas at Austin in conjunction with the ATS-6 millimeter wave experiment are presented. Attenuation measurements at 30 GHz and sky noise data at 20 GHz were obtained for 93 days simultaneously at each of two sites separated by 11 km and for 314 days at one site. The ratio of the loss at 30 GHz to that at 20 GHz due to rain varied from about 2 to about 4 with a median value of 2.65. This value was used to estimate 30 GHz losses for the 38.6% of time during attenuation events for which the satellite link was not available. Space diversity reduced outage time for a system in Austin, Texas, with a 10 db fade margin at 30 GHz from 3.8 hours to 4.1 minutes for the 93 days. Extrapolated to a yearly base this corresponds to 15 hours and to 16 minutes respectively. A plot of maximum observed cloud height against maximum hourly attenuation indicates that for a given attenuation level a lower limit is set for the maximum cloud height.
Portions of a forest supporting density levels that affect natural resource yields must be quantified to estimate the operational feasibility of a proposed management system. Estimates of average parameters do not necessarily provide complete knowledge, particularly with frequently skewed forest parameters. Instead, another statistic, the portion of a forest supporting minimum density levels would be useful to set realistic limits to the implementation of management systems and to establish priorities for operational programs. Such a statistic can be obtained from solutions of forest stocking equations generated by applications of multiple-stage remote sensing techniques.
The paper describes a computer-operated image-scanning and data-collection system for the magnetograph at the Mt. Wilson 150-foot Tower telescope. The system is based on a minicomputer with a 32K word core memory and a generalized interface unit for controlling image motion, a keyboard, and an associated television screen. Operation of the solar image guider and the data-collection assembly is outlined along with the observation and data-reduction procedures. Advantages of the system include the ability to move the image in almost any conceivable fashion, a wide choice of integration times, and increased accuracy in magnetic and Doppler calibrations as well as in setting of the magnetic zero level.
Line profiles and curves of growth were computed for both reflected and transmitted radiation for typical lines in CO2 bands (in the photographic infrared) which occur in the spectrum of Venus. In the model, the pressure variation with altitude was considered, and the base of the cloud deck was set at the 2 bar level. The temperature was held constant at 250 K, and a Voigt profile was used for the line shape. It was also assumed that the scale height of the cloud particles was equal to the scale height of the gas. The calculations were made for four values of the scattering optical thickness (0.1, 1.0, and 100) using a continuum single-scattering albedo of 0.9975 (which gives a Bond albedo of 0.896 for a scattering optical thickness of 100, the value observed for Venus at these wavelengths). Curves of growth are also presented for reflected radiation which has been averaged over the visible disk for three values of the Venus phase angle (0, 86, and 166 deg).
System designed to reduce intraocular pressure hydraulically to any level desired by physician over set time and in controlled manner has number of uses in ophthalmology. Device may be most immediately useful in treatment of glaucoma.
The complete model is a semispectral model in which the longitudinal dependence is represented by expansion in zonal harmonics while the latitude and height dependencies are represented by a finite difference grid. The model is based on the primitive equations in the log pressure coordinate system. The lower boundary of the model domain is set at the 100 mb level (i.e., near the tropopause) and the effects of tropospheric forcing are included in the lower boundary condition. The upper boundary is at approximately 96 km, and the latitudinal extent is either global or hemispheric. The basic differential equations and boundary conditions are outlined. The finite difference equations are described. The initial conditions are discussed and a sample calculation is presented. The FORTRAN code is given in the appendix.
The R and D activities addressing the development, administration, and evaluation of a set of transportable, college-level courses to educate science and engineering students in the effective use of automated scientific and technical information storage and retrieval systems, and, in particular, in the use of the NASA RECON system, are discussed. The long-range scope and objectives of these contracted activities are overviewed and the progress which has been made toward these objectives during FY 1983-1984 is highlighted. In addition, the results of a survey of 237 colleges and universities addressing course needs are presented.
The North Bengal University (NBU) air shower array has been in operation in conjunction with two muon magnetic spectrographs. The array incorporates 21 particle density sampling detectors around the magnetic spectrographs covering an area of 900 sq m. The layout of the array is based on the arrangement of detectors in a square symmetry. The array set up on the ground level is around a 10 m high magnetic spectrograph housing. This magnetic spectrograph housing limits the zenith angular acceptance of the incident showers to a few degrees. Three hundred muons in the fitted showers of size range 10 to the 4th power to 10 to the 5th power particles have so far been scanned and the momenta determined in the momentum range 2 - 440 GeV/c. More than 1500 recorded showers are now in the process of scanning and fitting. A lateral distribution of muons of energy greater than 300 MeV in the shower size range 10 to the 5th power to 7 x 10 to the 5th power has been obtained.