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Program was written to include integration of surface pressure in order to obtain axial-force, normal-force, and pitching-moment coefficients. Program was written in CDC FORTRAN for the CDC-6600 computer system.
A 2-D boundary layer computer code developed to process data for an arbitrary number of streamlines is presented. Provisions are included for the computer code to determine either mass transfer rates necessary for an effective boundary layer displacement of zero thickness or the effective displacement thickness for a specified mass transfer-rate distribution. The computer code was developed to be compatible with other computer codes which are being modified and/or developed at the NASA-Langley Research Center in order to design the three dimensional, contoured, wind tunnel liner used in transonic testing of a laminar flow control system installed on a supercritical airfoil section. A brief discription of the liner design procedure, representative liner calculations, adaptive-wall design for a two dimensional wind tunnel test, and other applications are reported.
The temperature distribution in liquid-cooled turbine blades determines the amount of cooling required to reduce the blade temperature to permissible values at specified locations. This report presents analytical methods for computing temperature distributions in liquid-cooled turbine blades, or in simplified shapes used to approximate sections of the blade. The individual analyses are first presented in terms of their mathematical development. By means of numerical examples, comparisons are made between simplified and more complete solutions and the effects of several variables are examined. Nondimensional charts to simplify some temperature-distribution calculations are also given.
Improving the numerical linear algebra routines for use in new Navier-Stokes codes, specifically Tim Barth's unstructured grid code, with spin-offs to TRANAIR is reported. A fast distance calculation routine for Navier-Stokes codes using the new one-equation turbulence models is written. The primary focus of this work was devoted to improving matrix-iterative methods. New algorithms have been developed which activate the full potential of classical Cray-class computers as well as distributed-memory parallel computers.
The photon-starved channel for optical communications from deep space requires the development of detector technology that can achieve photon-counting sensitivities with high bandwidth. In this article, a near-infrared enhanced photomultiplier tube (PMT) with a quantum e.ciency of 0.08 at a 1.06- m wavelength is characterized in the laboratory. A Polya distribution model is used to compute the probability distribution function of the emitted secondary photoelectrons from the PMT. The model is compared with measured pulse-height distributions with reasonable agreement. The model accounts for realistic device parameters, such as the individual dynode stage gains and a shape parameter that is representative of the spatial uniformity of response across the photocathode and dynodes. Bit-error rate (BER) measurements also are presented for 4- and 8-pulse-position modulation (PPM) modulation schemes with data rates of 20 to 30 Mb/s. A BER of 10-2 is obtained for a mean of 8 detected photons.
A reference architecture is defined for an object-oriented implementation of domains, arrays, and distributions written in the programming language Chapel. This technology primarily addresses domains that contain arrays that have regular index sets with the low-level implementation details being beyond the scope of this discussion. What is defined is a complete set of object-oriented operators that allows one to perform data distributions for domain arrays involving regular arithmetic index sets. What is unique is that these operators allow for the arbitrary regions of the arrays to be fragmented and distributed across multiple processors with a single point of access giving the programmer the illusion that all the elements are collocated on a single processor. Today's massively parallel High Productivity Computing Systems (HPCS) are characterized by a modular structure, with a large number of processing and memory units connected by a high-speed network. Locality of access as well as load balancing are primary concerns in these systems that are typically used for high-performance scientific computation. Data distributions address these issues by providing a range of methods for spreading large data sets across the components of a system. Over the past two decades, many languages, systems, tools, and libraries have been developed for the support of distributions. Since the performance of data parallel applications is directly influenced by the distribution strategy, users often resort to low-level programming models that allow fine-tuning of the distribution aspects affecting performance, but, at the same time, are tedious and error-prone. This technology presents a reusable design of a data-distribution framework for data parallel high-performance applications. Distributions are a means to express locality in systems composed of large numbers of processor and memory components connected by a network. Since distributions have a great effect on the performance of applications, it is important that the distribution strategy is flexible, so its behavior can change depending on the needs of the application. At the same time, high productivity concerns require that the user be shielded from error-prone, tedious details such as communication and synchronization.
Current data processing practice limits the volume and variety of relevant geoscience data that can practically be applied to important problems. File archives in centralized data centers are the principal means by which Earth Science data are accessed. This approach, however, requires laborious search, retrieval, and eventual customization/adaptation for the data to be used. Such fractionation makes it even more difficult to share outcomes, i.e. research artifacts and data products, hampering reusability and repeatability, since end users generally have their own research agenda and preferences as well as scarce resources. Thus, while finding and downloading data files from central data centers are already costly for end users working in their own field, using data products from other disciplines rapidly becomes prohibitive. This curtails scientific productivity, limits avenues of study, and endangers quality and reproducibility. The Spatio-Temporal Adaptive Resolution Encoding (STARE) is a unifying scheme that facilitates the indexing, access, and fusion of diverse Earth Science data. STARE implements an innovative encoding of geo-spatiotemporal information, originally developed for aligning datasets with diverse spatiotemporal characteristics in an array database. The spatial component of STARE recursively quadfurcates a root polyhedron, producing a hierarchical scheme for addressing geographic locations and regions. The temporal component of STARE uses conventional date-time units as an indexing hierarchy. The additional encoding of spatial and temporal resolution information in STARE enables comparisons and conditional selections across diverse datasets. Moreover, spatiotemporal set-operations, e.g. union and intersection, are mapped to efficient integer operations with STARE. Applied to existing data models (point, grid, spacecraft swath) and corresponding granules, STARE indexes provide a streamlined description usable as geo-spatiotemporal metadata. When coupled with large scale, distributed hardware and software, STARE-based data access reduces pre-analysis data preparation costs by offering a convenient means to align different datasets spatiotemporally without specialized effort in parallel computing or distributed data management.
The use of Computational Fluid Dynamics (CFD) has been investigated for the analysis and design of aircraft forebodies at high angle of attack combined with sideslip. The results of the investigation show that CFD has reached a level of development where computational methods can be used for high angle of attack aerodynamic design. The classic wind tunnel experiment for the F-5A forebody directional stability has been reproduced computationally over an angle of attack range from 10 degrees to 45 degrees, and good agreement with experimental data was obtained. Computations have also been made at combined angle of attack and sideslip over a chine forebody, demonstrating the qualitative features of the flow, although not producing good agreement with measured experimental pressure distributions. The computations were performed using the code known as cfl3D for both the Euler equations and the Reynolds equations using a form of the Baldwin-Lomax turbulence model. To study the relation between forebody shape and directional stability characteristics, a generic parametric forebody model has been defined which provides a simple analytic math model with flexibility to capture the key shape characteristics of the entire range of forebodies of interest, including chines.
The steady full-potential equation is written in the form of Poisson's equation, and the solution of the velocity field is expressed in terms of an integral equation. The solution consists of a surface integral of vorticity distribution on the wing and its free-vortex sheets and a volume integral of source distribution within a volume around the wing and its free-vortex sheets. The solution is obtained through successive iteration cycles. The source distribution is computed by using a mixed finite-difference scheme of the Murman-Cole type. The method is applied to delta wings. Numerical examples show that a conical shock is captured on the suction side of the wing. It is attached to the lower surface of the leading-edge vortex but does not necessarily reach to the wing surface.
An experimental investigation of distributed sand-grain surface roughness effects on hypersonic boundary-layer transition and turbulent heating has been performed. Two representative entry vehicle geometries, a sphere-cone aeroshell and a spherical-cap aeroshell, were considered. Cast ceramic models of each geometry were fabricated with distributed sand-grain roughness patterns of different heights that simulated an ablated thermal protection system. Wind tunnel testing was performed at Mach 6 over a range of Reynolds numbers sufficient to produce laminar, transitional, and turbulent flow. Aeroheating and boundary-layer transition onset data were obtained using global phosphor thermography. The experimental heating data are presented herein, as are comparisons to laminar and turbulent smooth-wall heat transfer distributions from computational flow field simulations. The boundary-layer transition data were found to correlate with a functional representation developed in prior roughness studies, although the data scatter was greater owing to the height variability of distributed sand-grain roughness.
Computer image processing techniques have been applied to particle counting and sizing in electron microscope images. Distributions of particle sizes were computed for several images and compared to manually computed distributions. The results of these experiments indicate that automatic particle counting within a reasonable error and computer processing time is feasible. The significance of the results is that the tedious task of manually counting a large number of particles can be eliminated while still providing the scientist with accurate results.
The use of digital computational techniques in the analysis and synthesis of DLA (distributed lumped active) networks is considered. This class of networks consists of three distinct types of elements, namely, distributed elements (modeled by partial differential equations), lumped elements (modeled by algebraic relations and ordinary differential equations), and active elements (modeled by algebraic relations). Such a characterization is applicable to a broad class of circuits, especially including those usually referred to as linear integrated circuits, since the fabrication techniques for such circuits readily produce elements which may be modeled as distributed, as well as the more conventional lumped and active ones.
Massive parallelism appears in three domains of action of concern to scientists, where it produces collective action that is not possible from any individual agent's behavior. In the domain of data parallelism, computers comprising very large numbers of processing agents, one for each data item in the result will be designed. These agents collectively can solve problems thousands of times faster than current supercomputers. In the domain of distributed parallelism, computations comprising large numbers of resource attached to the world network will be designed. The network will support computations far beyond the power of any one machine. In the domain of people parallelism collaborations among large groups of scientists around the world who participate in projects that endure well past the sojourns of individuals within them will be designed. Computing and telecommunications technology will support the large, long projects that will characterize big science by the turn of the century. Scientists must become masters in these three domains during the coming decade.
Optical radiation from the sea is influenced by pigments dissolved in the water and contained in discrete organisms suspended in the sea, and by pigmented and unpigmented inorganic and organic particles. The problem of extracting the information concerning these pigments and particulates from the optical properties of the sea is addressed and the properties which determine characteristics of the radiation that a remote sensor will detect and measure are considered. The results of the application of the volume scattering function model to the data collected in the Gulf of Mexico and its environs indicate that the size distribution of the concentrations of particles found in the sea can be predicted from measurements of the volume scattering function. Furthermore, with the volume scattering function model and knowledge of the absorption spectra of dissolved pigments, the radiative transfer model can compute a distribution of particle sizes and indices of refraction and concentration of dissolved pigments that give an upwelling light spectrum that closely matches measurements of that spectrum at sea.
In an effort to test the techniques and communication lines of the entire International Halley watch (IHW) organization, comet Crommelin was selected as a comet that would act as a trial run for the future observations of comets Halley and Giacobini-Zinner. Astrometry network members were asked to provide a few observations of comet Crommelin during a period within a few months on either side of the comet's perihelion passage. Special comet Crommelin star catalogs were distributed and each observer was asked to observe, reduce and transmit their data as quickly as possible. Some 372 astrometric observations from 42 different observatories were received at the orbit determination center. Orbit information and up-to-date ephemerides were computed and distributed by the same communication channels. The comet Crommelin trial run was successful in pointing out some areas that need to be improved to make the data more accurate and the communication channels more efficient.
We study the topology of large-scale structure in the Center for Astrophysics Redshift Survey, which now includes approximately 12,000 galaxies with limiting magnitude m(sub B) is less than or equal to 15.5. The dense sampling and large volume of this survey allow us to compute the topology on smoothing scales from 6 to 20/h Mpc; we thus examine the topology of structure in both 'nonlinear' and 'linear' regimes. On smoothing scales less than or equal to 10/h Mpc this sample has 3 times the number of resolution elements of samples examined in previous studies. Isodensity surface of the smoothed galaxy density field demonstrate that coherent high-density structures and large voids dominate the galaxy distribution. We compute the genus-threshold density relation for isodensity surfaces of the CfA survey. To quantify phase correlation in these data, we compare the CfA genus with the genus of realizations of Gaussian random fields with the power spectrum measured for the CfA survey. On scales less than or equal to 10/h Mpc the observed genus amplitude is smaller than random phase (96% confidence level). This decrement reflects the degree of phase coherence in the observed galaxy distribution. In other words the genus amplitude on these scales is not good measure of the power spectrum slope. On scales greater than 10/h Mpc, where the galaxy distribution is rougly in the 'linear' regime, the genus ampitude is consistent with the random phase amplitude. The shape of the genus curve reflects the strong coherence in the observed structure; the observed genus curve appears broader than random phase (94% confidence level for smoothing scales less than or equal to 10/h Mpc) because the topolgoy is spongelike over a very large range of density threshold. This departre from random phase consistent with a distribution like a filamentary net of 'walls with holes.' On smoothing scales approaching approximately 20/h Mpc the shape of the CfA genus curve is consistent with random phase. There is very weak evidence for a shift of the genus toward a 'bubble-like' topology. To test cosmological models, we compute the genus for mock CfA surveys drawn from large (L greater than or approximately 400/h Mpc) N-body simulations of three variants of the cold dark matter (CDM) cosmogony. The genus amplitude of the 'standard' CDM model (omega h = 0.5, b = 1.5) differs from the observations (96% confidence level) on smoothing scales is less than or approximately 10/h Mpc. An open CDM model (omega h = 0.2) and a CDM model with nonzero cosmological constant (omega h = 0.24, lambda (sub 0) = 0.6) are consistent with the observed genus amplitude over the full range of smoothing scales. All of these models fail (97% confidence level) to match the broadness of the observed genus curve on smoothing scales is less than or equal to 10/h Mpc.
Experimental work in support of stress studies in high speed silicon sheet growth has been emphasized in this quarter. Creep experiments utilizing four-point bending have been made in the temperature range from 1000 C to 1360 C in CZ silicon as well as on EFG ribbon. A method to measure residual stress over large areas using laser interferometry to map strain distributions under load is under development. A fiber optics sensor to measure ribbon temperature profiles has been constructed and is being tested in a ribbon growth furnace environment. Stress and temperature field modeling work has been directed toward improving various aspects of the finite element computing schemes. Difficulties in computing stress distributions with a very high creep intensity and with non-zero interface stress have been encountered and additional development of the numerical schemes to cope with these problems is required. Temperature field modeling has been extended to include the study of heat transfer effects in the die and meniscus regions.
Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events, as well as faster responses such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if individual nodes can communicate directly with their neighbors. Previously, a method was developed by which machine learning classification algorithms could collaborate to achieve high performance autonomously (without requiring human intervention). This method worked for supervised learning algorithms, in which labeled data is used to train models. The learners collaborated by exchanging labels describing the data. The new advance enables clustering algorithms, which do not use labeled data, to also collaborate. This is achieved by defining a new language for collaboration that uses pair-wise constraints to encode useful information for other learners. These constraints specify that two items must, or cannot, be placed into the same cluster. Previous work has shown that clustering with these constraints (in isolation) already improves performance. In the problem formulation, each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. Each learner clusters its data and then selects a pair of items about which it is uncertain and uses them to query its neighbors. The resulting feedback (a must and cannot constraint from each neighbor) is combined by the learner into a consensus constraint, and it then reclusters its data while incorporating the new constraint. A strategy was also proposed for cleaning the resulting constraint sets, which may contain conflicting constraints; this improves performance significantly. This approach has been applied to collaborative clustering of seismic and infrasonic data collected by the Mount Erebus Volcano Observatory in Antarctica. Previous approaches to distributed clustering cannot readily be applied in a sensor network setting, because they assume that each node has the same view of the data set. A view is the set of features used to represent each object. When a single data set is partitioned across several computational nodes, distributed clustering works; all objects have the same view. But when the data is collected from different locations, using different sensors, a more flexible approach is needed. This approach instead operates in situations where the data collected at each node has a different view (e.g., seismic vs. infrasonic sensors), but they observe the same events. This enables them to exchange information about the likely cluster membership relations between objects, even if they do not use the same features to represent the objects.