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Small lots of special-purpose integrated circuits are fabricated from standard transitor arrays. Folded linear order of cells minimzes interconnection length and puts cell in juxtaposition. Cell-placement technique is carried out via computer program.
High accuracy is obtained by combining analog and digital corrections. Proximity-sensor linearization circuit has two stages. First-stage linearization is accurate to about 3 percent; accuracy of final output is better than 0.5 percent. By modifying contents of the Programable Read-Only Memory (PROM), circuit can also be used to derive a nonlinear output.
The linear boundary layer stability analyses and their correlation with data of 18 cases from a natural laminar flow (NLF) flight test program using a Cessna Citation 3 business jet are described. The transition point varied from 5% to 35% chord for these conditions, and both upper and lower wing surfaces were included. Altitude varied from 10,000 to 43,000 ft and Mach number from 0.3 to 0.8. Four cases were at nonzero sideslip. Although there was much scatter in the results, the analyses of boundary layer stability at the 18 conditions led to the conclusion that crossflow instability was the primary cause of transition. However, the sideslip cases did show some interaction of crossflow and Tollmien-Schlichting disturbances. The lower surface showed much lower Tollmien-Schlichting amplification at transition than the upper surface, but similar crossflow amplifications. No relationship between Mach number and disturbance amplification at transition could be found. The quality of these results is open to question from questionable wing surface quality, inadequate density of transition sensors on the wing upper surface, and an unresolved pressure shift in the wing pressure data. The results of this study show the need for careful preparation for transition experiments. Preparation should include flow analyses of the test surface, boundary layer disturbance amplification analyses, and assurance of adequate surface quality in the test area. The placement of necessary instruments and usefulness of the resulting data could largely be determined during the pretest phase.
The problem of turbulent flow past a backward facing step is important in many technological applications and has been used as a standard test case to evaluate the performance of turbulence models in the prediction of separated flows. It is well known that the commonly used kappa-epsilon (and K-l) models of turbulence yield inaccurate predictions for the reattachment points in this problem. By an analysis of the mean vorticity transport equation, it will be argued that the intrinsically inaccurate prediction of normal Reynolds stress differences by the Kappa-epsilon and K-l models is a major contributor to this problem. Computations using a new nonlinear kappa-epsilon model (which alleviates this deficiency) are made with the TEACH program. Comparisons are made between the improved results predicted by this nonlinear kappa-epsilon model and those obtained from the linear kappa-epsilon model as well as from second-order closure models.
The problem of turbulent flow past a backward facing step is important in many technological applications and has been used as a standard test case to evaluate the performance of turbulence models in the prediction of separated flows. It is well known that the commonly used kappa-epsilon (and K-l) models of turbulence yield inaccurate predictions for the reattachment points in this problem. By an analysis of the mean vorticity transport equation, it will be argued that the intrinsically inaccurate prediction of normal Reynolds stress differences by the kappa-epsilon and K-l models is a major contributor to this problem. Computations using a new nonlinear Kappa-epsilon model (which alleviates this deficiency) are made with the TEACH program. Comparisons are made between the improved results predicted by this nonlinear kappa-epsilon model and those obtained from the linear kappa-epsilon model as well as from second-order closure models.
For more than twelve years the International Ultraviolet Explorer (IUE) satellite has consistently monitored about 44 spectrophotometric standard stars. This monitoring program was set up mostly to fit some particular needs of the IUE mission, such as the study of the detector linearity, sensitivity, degradation, and scattered light profiles. The impressive body of data accumulated over the years of about 7000 images, is unique and particularly suited for stellar studies on the stars themselves. The most frequently observed early type stars used as baseline calibration standards are studied. Part of what has been learnt about the cameras from studies of these spectral images and which has indirectly affected most of the published studies is presented. Possible improvements in flux accuracy which will be incorporated in the IUE final archives are discussed.
This paper has two purposes: first, to document the structure and evolution of two strong thunderstorms in Alabama using radar multiparameter data; and second, to relate the inferred microphysics to the resulting upwelling microwave radiance observed concurrently by high altitude aircraft. These measurements were collected during the COHMEX field program in the summer of 1986. The radar analysis includes a description of the parameters reflectivity Z, differential reflectivity Z(DR), linear depolarization ratio LDR, and hail signal HS for two thunderstorm cases on July 11, 1986. The simultaneous aircraft data include passive microwave brightness temperature, T(B), measurements at four frequencies ranging from 18 to 183 GHz, as well as visible and infrared data. The remote radar observations reveal the existence of large ice particles within the storms, which is likely to have caused the observed low microwave brightness temperatures. By relating the evolution of the radar measureables to the microwave T(B)s it has been found that knowledge of the storm microphysics and its evolution is important to adequately understand the microwave T(B)s.
The analytic energy gradient for the single and double excitation coupled-cluster (CCSD) wave function has been reformulated and implemented in a new set of programs. The reformulated set of gradient equations have a smaller computational cost than any previously published. The iterative solution of the linear equations and the construction of the effective density matrices are fully vectorized, being based on matrix multiplications. The new method has been used to investigate the Cl2O2 molecule, which has recently been postulated as an important intermediate in the destruction of ozone in the stratosphere. In addition to reporting computational timings, the CCSD equilibrium geometries, harmonic vibrational frequencies, infrared intensities, and relative energetics of three isomers of Cl2O2 are presented.
An iterative logic array (ILA) architecture for synchronous sequential circuits is presented. This technique utilizes linear algebra to produce the design equations. The ILA realization of synchronous sequential logic can be fully automated with a computer program. A programmable design procedure is proposed to fullfill the design task and layout generation. A software algorithm in the C language has been developed and tested to generate 1 micron CMOS layouts using the Hewlett-Packard FUNGEN module generator shell.
This is an overview of the Ballistic Missile Defense Organization (BMDO) Photovoltaic Program. Areas discussed are: (1) BMDO advanced Solar Array program; (2) Brilliant Eyes type satellites; (3) Electric propulsion; (4) Contractor Solar arrays; (5) Iofee Concentrator and Cell development; (6) Entech linear mini-dome concentrator; and (7) Flight test update/plans.
A decentralized control is investigated for applicability to the autonomous formation flying control algorithm developed by GSFC for the New Millenium Program Earth Observer-1 (EO-1) mission. This decentralized framework has the following characteristics: The approach is non-hierarchical, and coordination by a central supervisor is not required; Detected failures degrade the system performance gracefully; Each node in the decentralized network processes only its own measurement data, in parallel with the other nodes; Although the total computational burden over the entire network is greater than it would be for a single, centralized controller, fewer computations are required locally at each node; Requirements for data transmission between nodes are limited to only the dimension of the control vector, at the cost of maintaining a local additional data vector. The data vector compresses all past measurement history from all the nodes into a single vector of the dimension of the state; and The approach is optimal with respect to standard cost functions. The current approach is valid for linear time-invariant systems only. Similar to the GSFC formation flying algorithm, the extension to linear LQG time-varying systems requires that each node propagate its filter covariance forward (navigation) and controller Riccati matrix backward (guidance) at each time step. Extension of the GSFC algorithm to non-linear systems can also be accomplished via linearization about a reference trajectory in the standard fashion, or linearization about the current state estimate as with the extended Kalman filter. To investigate the feasibility of the decentralized integration with the GSFC algorithm, an existing centralized LQG design for a single spacecraft orbit control problem is adapted to the decentralized framework while using the GSFC algorithm's state transition matrices and framework. The existing GSFC design uses both reference trajectories of each spacecraft in formation and by appropriate choice of coordinates and simplified measurement modeling is formulated as a linear time-invariant system. Results for improvements to the GSFC algorithm and a multiple satellite formation will be addressed. The goal of this investigation is to progressively relax the assumptions that result in linear time-invariance, ultimately to the point of linearization of the non-linear dynamics about the current state estimate as in the extended Kalman filter. An assessment will then be made about the feasibility of the decentralized approach to the realistic formation flying application of the EO-1/Landsat 7 formation flying experiment.
Mr. Weir presented source location results obtained from an engine test as part of the Engine Validation of Noise Reduction Concepts program. Two types of microphone arrays were used in this program to determine the jet noise source distribution for the exhaust from a 4.3 bypass ratio turbofan engine. One was a linear array of 16 microphones located on a 25 ft. sideline and the other was a 103 microphone 3-D "cage" array in the near field of the jet. Data were obtained from a baseline nozzle and from numerous nozzle configuration using chevrons and/or tabs to reduce the jet noise. Mr. Weir presented data from two configurations: the baseline nozzle and a nozzle configuration with chevrons on both the core and bypass nozzles. This chevron configuration had achieved a jet noise reduction of 4 EPNdB in small scale tests conducted at the Glenn Research Center. IR imaging showed that the chevrons produced significant improvements in mixing and greatly reduced the length of the jet potential core. Comparison of source location data from the 1-D phased array showed a shift of the noise sources towards the nozzle and clear reductions of the sources due to the noise reduction devices. Data from the 3-D array showed a single source at a frequency of 125 Hz. located several diameters downstream from the nozzle exit. At 250 and 400 Hz., multiple sources, periodically spaced, appeared to exist downstream of the nozzle. The trend of source location moving toward the nozzle exit with increasing frequency was also observed. The 3-D array data also showed a reduction in source strength with the addition of chevrons. The overall trend of source location with frequency was compared for the two arrays and with classical experience. Similar trends were observed. Although overall trends with frequency and addition of suppression devices were consistent between the data from the 1-D and the 3-D arrays, a comparison of the details of the inferred source locations did show differences. A flight test is planned to determine if the hardware tested statically will achieve similar reductions in flight.
Understanding the wing twist of the active aeroelastic wing F/A-18 aircraft is a fundamental research objective for the program and offers numerous benefits. In order to clearly understand the wing flexibility characteristics, a model was created to predict real-time wing twist. A reliable twist model allows the prediction of twist for flight simulation, provides insight into aircraft performance uncertainties, and assists with computational fluid dynamic and aeroelastic issues. The left wing of the aircraft was heavily instrumented during the first phase of the active aeroelastic wing program allowing deflection data collection. Traditional data processing steps were taken to reduce flight data, and twist predictions were made using linear regression techniques. The model predictions determined a consistent linear relationship between the measured twist and aircraft parameters, such as surface positions and aircraft state variables. Error in the original model was reduced in some cases by using a dynamic pressure-based assumption and by using neural networks. These techniques produced excellent predictions for flight between the standard test points and accounted for nonlinearities in the data. This report discusses data processing techniques and twist prediction validation, and provides illustrative and quantitative results.
Understanding the wing twist of the active aeroelastic wing (AAW) F/A-18 aircraft is a fundamental research objective for the program and offers numerous benefits. In order to clearly understand the wing flexibility characteristics, a model was created to predict real-time wing twist. A reliable twist model allows the prediction of twist for flight simulation, provides insight into aircraft performance uncertainties, and assists with computational fluid dynamic and aeroelastic issues. The left wing of the aircraft was heavily instrumented during the first phase of the active aeroelastic wing program allowing deflection data collection. Traditional data processing steps were taken to reduce flight data, and twist predictions were made using linear regression techniques. The model predictions determined a consistent linear relationship between the measured twist and aircraft parameters, such as surface positions and aircraft state variables. Error in the original model was reduced in some cases by using a dynamic pressure-based assumption. This technique produced excellent predictions for flight between the standard test points and accounted for nonlinearities in the data. This report discusses data processing techniques and twist prediction validation, and provides illustrative and quantitative results.
We report airborne measurements of atmospheric pressure made using an integrated path differential absorption (IPDA) lidar that operates in the oxygen A-band near 765 nm. Remote measurements of atmospheric temperature and pressure are needed for NASA s Active Sensing of CO2 Emissions Over Nights, Days, and Seasons (ASCENDS) mission to measure atmospheric CO2. Accurate measurements of tropospheric CO2 on a global scale are very important in order to better understand its sources and sinks and to improve our predictions of climate change. The goal of ASCENDS is to determine the CO2 dry mixing ratio with lidar measurements from space at a level of ~1 ppm. Analysis to date shows that with current weather models, measurements of both the CO2 column density and the column density of dry air are needed. Since O2 is a stable molecule that uniformly mixed in the atmosphere, measuring O2 absorption in the atmosphere can be used to infer the dry air density. We have developed an airborne (IPDA) lidar for Oxygen, with support from the NASA ESTO IIP program. Our lidar uses DFB-based seed laser diodes, a pulsed modulator, a fiber laser amplifier, and a non-linear crystal to generate wavelength tunable 765 nm laser pulses with a few uJ/pulse energy. The laser pulse rate is 10 KHz, and average transmitted laser power is ~20 mW. Our lidar steps laser pulses across a selected line O2 doublet near 764.7 nm in the Oxygen A-band. The direct detection lidar receiver uses a 20 cm diameter telescope, a Si APD detector in Geiger mode, and a multi-channel scalar to detect and record the time resolved laser backscatter in 40 separate wavelength channels. Subsequent analysis is used to estimate the transmission line shape of the doublet for the laser pulses reflected from the ground. Ground based data analysis allows averaging from 1 to 60 seconds to increase SNR in the transmission line shape of the doublet. Our retrieval algorithm fits the expected O2 lineshapes against the measurements and determines the atmospheric pressure by minimizing the error between the observations and model. We first demonstrated our airborne lidar during flights during summer 2010. We made several improvements and made measurements during the Ascends flights during July 2011. More information about the technique, lidar instrument, airborne measurements, and pressure estimates will be described in the presentation.
Spacecraft materials selection is based on an upward flammability test conducted in a quiescent environment in the highest-expected oxygen-concentration environment. However, NASA s advanced space exploration program is anticipating using various habitable environments. Because limited data is available to support current program requirements, a different test logic is suggested to address these expanded atmospheric environments through the determination of materials self-extinguishment limits. This paper provides additional pressure effects data on oxygen concentration and partial pressure self-extinguishment limits under quiescent conditions. For the range of total pressures tested, the oxygen concentration and oxygen partial pressure flammability thresholds show a near linear function of total pressure. The oxygen concentration/oxygen partial pressure flammability thresholds depend on the total pressure and appear to increase with increasing oxygen concentration (and oxygen partial pressure). For the Constellation Program, the flammability threshold information will allow NASA to identify materials with increased flammability risk because of oxygen concentration and total pressure changes, minimize potential impacts, and allow for development of sound requirements for new spacecraft and extraterrestrial landers and habitats.
This study is a direct result of an on-going project to model the reliability of a large real-time control avionics system. In previous modeling efforts with this system, hardware reliability models were applied in modeling the reliability behavior of this system. In an attempt to enhance the performance of the adapted reliability models, certain software attributes were introduced in these models to control for differences between programs and also sequential executions of the same program. As the basic nature of the software attributes that affect software reliability become better understood in the modeling process, this information begins to have important implications on the software development process. A significant problem arises when raw attribute measures are to be used in statistical models as predictors, for example, of measures of software quality. This is because many of the metrics are highly correlated. Consider the two attributes: lines of code, LOC, and number of program statements, Stmts. In this case, it is quite obvious that a program with a high value of LOC probably will also have a relatively high value of Stmts. In the case of low level languages, such as assembly language programs, there might be a one-to-one relationship between the statement count and the lines of code. When there is a complete absence of linear relationship among the metrics, they are said to be orthogonal or uncorrelated. Usually the lack of orthogonality is not serious enough to affect a statistical analysis. However, for the purposes of some statistical analysis such as multiple regression, the software metrics are so strongly interrelated that the regression results may be ambiguous and possibly even misleading. Typically, it is difficult to estimate the unique effects of individual software metrics in the regression equation. The estimated values of the coefficients are very sensitive to slight changes in the data and to the addition or deletion of variables in the regression equation. Since most of the existing metrics have common elements and are linear combinations of these common elements, it seems reasonable to investigate the structure of the underlying common factors or components that make up the raw metrics. The technique we have chosen to use to explore this structure is a procedure called principal components analysis. Principal components analysis is a decomposition technique that may be used to detect and analyze collinearity in software metrics. When confronted with a large number of metrics measuring a single construct, it may be desirable to represent the set by some smaller number of variables that convey all, or most, of the information in the original set. Principal components are linear transformations of a set of random variables that summarize the information contained in the variables. The transformations are chosen so that the first component accounts for the maximal amount of variation of the measures of any possible linear transform; the second component accounts for the maximal amount of residual variation; and so on. The principal components are constructed so that they represent transformed scores on dimensions that are orthogonal. Through the use of principal components analysis, it is possible to have a set of highly related software attributes mapped into a small number of uncorrelated attribute domains. This definitively solves the problem of multi-collinearity in subsequent regression analysis. There are many software metrics in the literature, but principal component analysis reveals that there are few distinct sources of variation, i.e. dimensions, in this set of metrics. It would appear perfectly reasonable to characterize the measurable attributes of a program with a simple function of a small number of orthogonal metrics each of which represents a distinct software attribute domain.
Design procedures and supporting data necessary for configuring light aircraft to obtain desired responses to pilot commands and gusts are presented. The procedures employ specializations of modern military and jet transport practice where these provide an improvement over earlier practice. General criteria for riding and handling qualities are discussed in terms of the airframe dynamics. Methods available in the literature for calculating the coefficients required for a linearized analysis of the airframe dynamics are reviewed in detail. The review also treats the relation of spin and stall to airframe geometry. Root locus analysis is used to indicate the sensitivity of airframe dynamics to variations in individual stability derivatives and to variations in geometric parameters. Computer programs are given for finding the frequencies, damping ratios, and time constants of all rigid body modes and for generating time histories of aircraft motions in response to control inputs. Appendices are included presenting the derivation of the linearized equations of motion; the stability derivatives; the transfer functions; approximate solutions for the frequency, damping ratio, and time constants; an indication of methods to be used when linear analysis is inadequate; sample calculations; and an explanation of the use of root locus diagrams and Bode plots.