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At least 649 records · Page 36

Euler solutions to nonlinear acoustics of non-lifting rotor blades

For the first time a computational fluid dynamics (CFD) method is used to calculate directly the high-speed impulsive (HSI) noise of a non-lifting hovering rotor blade out to a distance of over three rotor radii. In order to accurately propagate the acoustic wave in a stable and efficient manner, an implicit upwind-biased Euler method is solved on a grid with points clustered along the line of propagation. A detailed validation of the code is performed for a rectangular rotor blade at tip Mach numbers ranging from 0.88 to 0.92. The agreement with experiment is excellent at both the sonic cylinder and at 2.18 rotor radii. The agreement at 3.09 rotor radii is still very good, showing improvements over the results from the best previous method. Grid sensitivity studies indicate that with special attention to the location of the boundaries a grid with approximately 60,000 points is adequate. This results in a computational time of approximately 40 minutes on a Cray-XMP. The practicality of the method to calculate HSI noise is demonstrated by expanding the scope of the investigation to examine the rectangular blade as well as a highly swept and tapered blade over a tip Mach number range of 0.80 to 0.95. Comparisons with experimental data are excellent and the advantages of planform modifications are clearly evident. New insight is gained into the mechanisms of nonlinear propagation and the minimum distance at which a valid comparison of different rotors can be made: approximately two rotor radii from the center of rotation.

Baeder, J. D.↗

A heterogeneous computing environment for simulating astrophysical fluid flows

In the Concurrent Computing Laboratory in the Department of Physics and Astronomy at Louisiana State University we have constructed a heterogeneous computing environment that permits us to routinely simulate complicated three-dimensional fluid flows and to readily visualize the results of each simulation via three-dimensional animation sequences. An 8192-node MasPar MP-1 computer with 0.5 GBytes of RAM provides 250 MFlops of execution speed for our fluid flow simulations. Utilizing the parallel virtual machine (PVM) language, at periodic intervals data is automatically transferred from the MP-1 to a cluster of workstations where individual three-dimensional images are rendered for inclusion in a single animation sequence. Work is underway to replace executions on the MP-1 with simulations performed on the 512-node CM-5 at NCSA and to simultaneously gain access to more potent volume rendering workstations.

Cazes, J.↗

"Electrostructural Phase Changes" In Charged Particulate Clouds: Planetary and Astrophysical Implications

There is empirical evidence that freely-suspended triboelectrostatically charged particulate clouds of dielectric materials undergo rapid conversion from (nominally) monodispersed "aerosols" to a system of well-defined grain aggregates after grain motion or fluid turbulence ceases within the cloud. In United States Microgravity Laboratory Space Shuttle experiments USML-1 and USML-2, it was found that ballistically-energized grain dispersions would rapidly convert into populations of filamentary aggregates after natural fluid (air) damping of grain motion. Unless continuously disrupted mechanically, it was impossible to maintain a non-aggregated state for the grain clouds of sand-size materials. Similarly, ground- based experiments with very fine dust-size material produced the same results: rapid, impulsive "collapse" of the dispersed grains into well-defined filamentary structures. In both ground-based and microgravity experiments, the chains or filaments were created by long-range dipole electrostatic forces and dipole-induced dielectric interactions, not by monopole interactions. Maintenance of the structures was assisted by short-range static boundary adhesion forces and van der Waals interactions. When the aggregate containers in the USML experiments were disturbed after aggregate formation, the quiescently disposed filaments would rearrange themselves into fractal bundles and tighter clusters as a result of enforced encounters with one another. The long-range dipole interactions that bring the grains together into aggregates are a product of randomly-distributed monopole charges on the grain surfaces. In computer simulations, it has been shown that when the force vectors of all the random charges (of both sign) on a grain are resolved mathematically by assuming Coulombic interaction between them, the net result is a dipole moment on individual grains, even though the grains are electrically neutral insofar as there is no predominance, on their surface, of one charge sign over another. The random charges of both sign derive from natural grain-to-grain interactions that produce triboelectrification via charge exchange every time grain surfaces make contact with one another. The conversion from a random distribution of grains (upon which there are randomly distributed charges) into an organization of electrostatically-ordered aggregates, can be regarded (within the framework of granular-material science) as an "electrical or Coulombic phase change" of the particulate cloud. It is not totally dissimilar from the more normal phase-change concept in which, for example, a gas with long free-path-molecules suddenly becomes a solid as a result of structural ordering of the molecules (notably, also the result of electronic forces, albeit at a different scale). In both the gas-to-solid case, and the aerosol-to-aggregate case, the same materials and charges are present before and after the phase change, but their arrangement now has a higher degree of order and a lower-energy configuration. An input of energy into the system is required to reverse the situation. The aggregates in the USML experiments were observed to undergo at least two phase changes as noted above. The point about phase changes, and by implication, the "electrostructural" reorganizations in particulate clouds, is the following: (a) they can occur very rapidly, almost spontaneously, above a critical cloud density, (b) in going from a higher energy state to a lower energy state, they convert to a denser system, (c) energy must be required to reverse the situation, implying that energy is released during the high-to-low energy phase change. In applying this information to natural particulate clouds, some inferences can be made (it is stressed that reference is still to dielectric materials attracted by dipole forces). There are several natural settings to which the USML observations apply, and to which the phase-change implications likewise apply. Dense clouds of triboelectrically-charged, kinetically-energized grains are to be found in volcanic eruptions (particularly on earth), aeolian dust storms (particularly on Mars), meteorite impact ejecta curtains (on all planets), in "immature" debris rings around planets (e.g., that from which our own Moon may have condensed), and in gravitationally collapsing protoplanetary dust/planetesimal debris disks where dielectric granules are being increasingly brought into collisional relationships with one another (increasing both charge exchange and physical proximity). It is noted that in many of these cases, the degree of electrical charging on the grains is likely to be much higher than that in the USML experiments where charging was not enhanced above the "normal", naturally encountered level for the particular materials (quartz, glass, and various silicate minerals). Application of the phase-change concept suggests that volcanic, aeolian, and impact debris clouds may, under certain circumstances, undergo rapid, impulsive, or even catastrophic collapse into a denser state that will lead to rapid precipitation or fall-out of suspended particulates. Although this idea has been suggested previously by the author , the phase change concept possibly permits some new insights into cloud-system behavior. For example, in a protoplanetary debris disk, the work of gravity may suddenly be enhanced by electrostatically driven collapse of the system when materials reach a critical intergranular spacing or grain number density. This might reduce the rate of planet formation by orders of magnitude (considering the ratio of g-forces to electrostatic ones for very small grains in close proximity), and indeed, it might drive the collapse into a system configuration that would perhaps not be created by gravity alone. Additional information is contained in the original.

Marshall, J. R.↗

Unsupervised classification of Space Acceleration Measurement System (SAMS) data using ART2-A

The Space Acceleration Measurement System (SAMS) has been developed by NASA to monitor the microgravity acceleration environment aboard the space shuttle. The amount of data collected by a SAMS unit during a shuttle mission is in the several gigabytes range. Adaptive Resonance Theory 2-A (ART2-A), an unsupervised neural network, has been used to cluster these data and to develop cause and effect relationships among disturbances and the acceleration environment. Using input patterns formed on the basis of power spectral densities (psd), data collected from two missions, STS-050 and STS-057, have been clustered.

STS-57 Shuttle Project↗

Performance Assessment of OVERFLOW on Distributed Computing Environment

The aerodynamic computer code, OVERFLOW, with a multi-zone overset grid feature, has been parallelized to enhance its performance on distributed and shared memory paradigms. Practical application benchmarks have been set to assess the efficiency of code's parallelism on high-performance architectures. The code's performance has also been experimented with in the context of the distributed computing paradigm on distant computer resources using the Information Power Grid (IPG) toolkit, Globus. Two parallel versions of the code, namely OVERFLOW-MPI and -MLP, have developed around the natural coarse grained parallelism inherent in a multi-zonal domain decomposition paradigm. The algorithm invokes a strategy that forms a number of groups, each consisting of a zone, a cluster of zones and/or a partition of a large zone. Each group can be thought of as a process with one or multithreads assigned to it and that all groups run in parallel. The -MPI version of the code uses explicit message-passing based on the standard MPI library for sending and receiving interzonal boundary data across processors. The -MLP version employs no message-passing paradigm; the boundary data is transferred through the shared memory. The -MPI code is suited for both distributed and shared memory architectures, while the -MLP code can only be used on shared memory platforms. The IPG applications are implemented by the -MPI code using the Globus toolkit. While a computational task is distributed across multiple computer resources, the parallelism can be explored on each resource alone. Performance studies are achieved with some practical aerodynamic problems with complex geometries, consisting of 2.5 up to 33 million grid points and a large number of zonal blocks. The computations were executed primarily on SGI Origin 2000 multiprocessors and on the Cray T3E. OVERFLOW's IPG applications are carried out on NASA homogeneous metacomputing machines located at three sites, Ames, Langley and Glenn. Plans for the future will exploit the distributed parallel computing capability on various homogeneous and heterogeneous resources and large scale benchmarks. Alternative IPG toolkits will be used along with sophisticated zonal grouping strategies to minimize the communication time across the computer resources.

Djomehri, M. Jahed↗

Upper Atmosphere Research Satellite (UARS) trade analysis

The Upper Atmosphere Research Satellite (UARS) which will collect data pertinent to the Earth's upper atmosphere is described. The collected data will be sent to the central data handling facility (CDHF) via the UARS ground system and the data will be processed and distributed to the remote analysis computer systems (RACS). An overview of the UARS ground system is presented. Three configurations were developed for the CDHF-RACS system. The CDHF configurations are discussed. The IBM CDHF configuration, the UNIVAC CDHF configuration and the vax cluster CDHF configuration are presented. The RACS configurations, the IBM RACS configurations, UNIVAC RACS and VAX RACS are detailed. Due to the large on-line data estimate to approximately 100 GB, a mass storage system is considered essential to the UARS CDHF. Mass storage systems were analyzed and the Braegan ATL, the RCA optical disk, the IBM 3850 and the MASSTOR M860 are discussed. It is determined that the type of mass storage system most suitable to UARS is the automated tape/cartridge device. Two devices of this type, the IBM 3850 and the MASSTOR MSS are analyzed and the applicable tape/cartridge device is incorporated into the three CDHF-RACS configurations.

Fox, M. M.↗

General-Purpose Image-Data Program

Image Database computer program, IBASE, is general-purpose imagery-information system. Use accomplished either by commands or through hierarchy of menus. Analytical capabilities of IBASE include contigency tables, image filtering (low-, high-, and band-pass), proximity maps, clustering, histograms, regression, slope calculations, scaling, and Boolean manipulations. Also has interface to Cheshire Image Classification expert system. Written in FORTRAN 77.

Engle, Steven W.↗

Fresh look at floating shock fitting

A fast implicit upwind procedure for the two-dimensional Euler equations is described that allows accurate computations of shocked flows on nonadapted meshes. Away from shocks, the second-order accurate upwinding is based on the split-coefficient-matrix (SCM) method. In the presence of shocks, the difference stencils are modified using a floating shock fitting technique. Rapid convergence to steady-state solutions is attained with a diagonalized approximate factorization (AF) algorithm. Results are presented for Riemann's problem, for a regular shock reflection at an inviscid wall, for supersonic flow past a cylinder, and for a transonic airfoil. All computed shocks are ideally sharp and in excellent agreement with other numerical results or 'exact' solutions. Most importantly, this has been accomplished on unusually crude meshes without any attempt to align grid lines with shock fronts or to cluster grid lines around shocks.

Hartwich, PETER-M.↗

A hydrodynamic approach to cosmology - Texture-seeded cold dark matter and hot dark matter cosmogonies

Hydrodynamical simulations of galaxy formation in a texture-seeded cosmology are presented, with attention given to Omega = 1 galaxies dominated by both hot dark matter (HDM) and cold dark matter (CDM). The simulations include both gravitational and hydrodynamical physics with a detailed treatment of collisional and radiative thermal processes, and use a cooling criterion to estimate galaxy formation. Background radiation fields and Zel'dovich-Sunyaev fluctuations are explicitly computed. The derived galaxy mass function is well fitted by the observed Schechter luminosity function for a baryonic M/L of 3 and total M/L of 60 in galaxies. In both HDM and CDM texture scenarios, the 'galaxies' and 'clusters' are significantly more strongly correlated than the dark matter due to physical bias processes. The slope of the correlation function in both cases is consistent with observations. In contrast to Gaussian models, peaks in the dark matter density distributrion are less correlated than average.

Cen, R. Y.↗

Unsupervised segmentation of polarimetric SAR data using the covariance matrix

An unsupervised selection of polarimetric features useful for the segmentation and analysis of polarimetric synthetic aperture radar (SAR) data is presented. The technique is based on multidimensional clustering of the parameters composing the polarimetric covariance matrix of the data. Clustering is performed on the logarithm of these quantities. Once the polarimetric cluster centers have been determined, segmentation of the polarimetric data into regions is performed using a maximum likelihood polarimetric classifier. Segmentation maps are further improved using a Markov random field to describe the statistics of the regions and computing the maximum of the product of the local conditional densities. Examples with real polarimetric SAR imagery are given to illustrate the potential of this method.

Rignot, Eric↗

SANs and Large Scale Data Migration at the NASA Center for Computational Sciences

Evolution and migration are a way of life for provisioners of high-performance mass storage systems that serve high-end computers used by climate and Earth and space science researchers: the compute engines come and go, but the data remains. At the NASA Center for Computational Sciences (NCCS), disk and tape SANs are deployed to provide high-speed I/O for the compute engines and the hierarchical storage management systems. Along with gigabit Ethernet, they also enable the NCCS's latest significant migration: the transparent transfer of 300 Til3 of legacy HSM data into the new Sun SAM-QFS cluster.

Salmon, Ellen M.↗

Use of multiresolution wavelet feature pyramids for automatic registration of multisensor imagery

The problem of image registration, or the alignment of two or more images representing the same scene or object, has to be addressed in various disciplines that employ digital imaging. In the area of remote sensing, just like in medical imaging or computer vision, it is necessary to design robust, fast, and widely applicable algorithms that would allow automatic registration of images generated by various imaging platforms at the same or different times and that would provide subpixel accuracy. One of the main issues that needs to be addressed when developing a registration algorithm is what type of information should be extracted from the images being registered, to be used in the search for the geometric transformation that best aligns them. The main objective of this paper is to evaluate several wavelet pyramids that may be used both for invariant feature extraction and for representing images at multiple spatial resolutions to accelerate registration. We find that the bandpass wavelets obtained from the steerable pyramid due to Simoncelli performs best in terms of accuracy and consistency, while the low-pass wavelets obtained from the same pyramid give the best results in terms of the radius of convergence. Based on these findings, we propose a modification of a gradient-based registration algorithm that has recently been developed for medical data. We test the modified algorithm on several sets of real and synthetic satellite imagery.

Evaluation Studies↗

Theoretical Modeling of Formic Acid (HCOOH), Formate (HCOO(-)), and Ammonia (NH(4)) Vibrational Spectra in Astrophysical Ices

Ions embedded in icy grain mantles are thought to account for various observed infrared spectroscopic features, particularly in certain young stellar objects. The dissociation of formic acid (HCOOH) in astrophysical ices to form the formate ion (HCOO(-)) was modeled with density functional theory cluster calculations. Like isocyanic acid (HOCN), HCOOH was found to spontaneously deprotonate when sufficient water is present to stabilize charge transfer complexes. Both ammonia and water can serve as proton acceptors, yielding ammonium (NH4(+)) and hydronium (H3O(+)) counterions. Computed frequencies of weak infrared features produced by stretching and bending modes in both HCOO(-) and HCOOH were compared with experimental and astronomical data. Our results confirm laboratory assignments that a band at 1381 cm(exp -1) can be attributed to the CH bend in either HCOO(-) or HCOOH, but a band at 1349 cm(exp -1) corresponds to CO stretching in HCOO(-). Another feature at 1710 cm(exp -1) (5.85 m) can possibly be assigned to a CO stretching mode in HCOOH, as suggested by experiment, but the agreement is less satisfactory. In addition, we examine and analyze spectroscopic features associated with NH+4, both as a counterion to HCOO(-) or OCN(-) and in isolation, in order to compare with experimental and astronomical data in the 7 m region.

Park, Jin-Young↗

A study of the x ray environment of radio galaxies

We are currently working on a program to use extensive x-ray and radio databases to investigate the relationship between extended radio emission and environment in clusters of galaxies. The radio galaxy morphology is determined using VLA imaging and the x-ray properties are determined from Einstein IPC images. This study is motivated by the hypothesis that the key to understanding radio galaxies lies in the local environment. To test this hypothesis we have studied the detailed relationship between galaxy radio emission and the x-ray morphology of their parent clusters. In this pilot study we have used 35 radio sources found in 27 clusters. We have determined the position angle of the x-ray and radio emission, and x-ray and radio luminosities. The x-ray position was taken to be the position of peak flux of the subclump containing the radio galaxy. The radio position was taken to be the position of the galaxy. We do not find a correlation between the x-ray and radio source position angle. This remains true when the sample is divided into subsamples according to radio morphology (wide angle tail, twin jet, narrow angle tail galaxies). We find a weak correlation between the radio source luminosity and the x-ray luminosity. We have computed the distance from the radio galaxy position to the center of the x-ray clump. We find a mean distance from the x-ray clump center of 0.16 Mpc for the radio galaxies in this sample. The mean distance to the nearest clump of x-ray emission is typically half the distance to the optical cluster center. We thus find strong evidence that radio galaxies are located very close to clumps of x-ray emission. These subclumps are not always affiliated with the central cluster x-ray emission. This supports our hypothesis that x-ray emission may provide a key to understanding radio galaxy morphology. We find evidence that radio galaxies occur in clusters that contain prominent substructures. Radio galaxies may thus provide an added diagnostic of the cluster dynamical state.

Rhee, George F.↗

Investigations on the usefulness of the Massively Parallel Processor for study of electronic properties of atomic and condensed matter systems

The usefulness of the Massively Parallel Processor (MPP) for investigation of electronic structures and hyperfine properties of atomic and condensed matter systems was explored. The major effort was directed towards the preparation of algorithms for parallelization of the computational procedure being used on serial computers for electronic structure calculations in condensed matter systems. Detailed descriptions of investigations and results are reported, including MPP adaptation of self-consistent charge extended Hueckel (SCCEH) procedure, MPP adaptation of the first-principles Hartree-Fock cluster procedure for electronic structures of large molecules and solid state systems, and MPP adaptation of the many-body procedure for atomic systems.

Das, T. P.↗

Accelerated Simulation of Air Pollution Using NVIDIA RAPIDS

Atmospheric chemistry models are a central tool to study and forecast the impact of air pollution on the environment, vegetation, and human health. However, the numerical simulation of chemical kinetics is computationally expensive due to the stiffness of the system of ordinary differential equations that describes atmospheric chemistry. Here we present an alternative approach to the computation of atmospheric chemistry based on machine learning. Our training data set is produced using the NASA Goddard Earth Observing System (GEOS) model with GEOS-Chem chemistry, run on the NASA Center for Climate Simulation (NCCS) Discover supercomputing cluster on 384 Intel Xeon Haswell cores. This model spends more than 50% of total run time on solving atmospheric chemistry. The data set contains as input features the air pollution concentrations before solving the differential equations, together with some key physical parameters such as temperature and sun intensity. As target variables we define the air pollution concentrations after solving the differential equations. Using Dask-cuDF and Dask-XGBoost on the NVIDIA RAPIDS platform on 8 Tesla V100 GPUs, we generate from this training set gradient boosted decision tree models that can reproduce the simulation of chemical kinetics. We do this on the NCCS Advanced Data Analytics Platform (ADAPT) science cloud environment. Our application takes full advantage of recent advances in Dask-XGBoost, such as multi-node and multi-GPU scaling for distributed training with large data sets. The increase in training data size enabled by this is critical to capture the full range of chemical environments encountered across the globe and all annual seasons.The boosted tree models offer good predictability and show many of the features of the full chemistry reference simulation. Further improvements can be achieved through mass balance considerations and by accounting for error correlations. We incorporate the boosted tree models into the GEOS reference model using XGBoost's C API. This enables a seamless integration of the GPU trained models into GEOS-Chem, which is written in Fortran and optimized for use in a massively parallel CPU environment. We show the benefits of this approach and discuss the potential speedup of this machine learning accelerated atmospheric chemistry model.

Keller, Christoph A.↗

Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning

The ability to perform ab initio molecular dynamics simulations using potential energy surfaces provided by quantum computers would open the door to virtually exact dynamics for a variety of chemical and biochemical systems, with impacts on catalysis and biophysics. Nonetheless, performing molecular dynamics on surfaces produced by quantum hardware has been hampered by the noisy energies typically produced by quantum computers and challenges associated with computing gradients and scaling to large systems interest. A recent set of advances in machine learning, known as transfer learning, provides a new path forward for molecular dynamics simulations on quantum hardware. Transfer learning offers a workaround, where one first trains models on larger, less accurate classical datasets and then refines them on smaller, more accurate quantum datasets. We explore this approach by training machine learning models to predict a molecule's potential energy based on its geometric structure using Behler-Parrinello neural networks. When successfully trained, the model enables energy gradient predictions necessary for dynamic simulations. To reduce the quantum resources needed, the model is initially trained with data derived from classical density functional theory and subsequently refined with a smaller dataset obtained from a variational quantum eigensolver optimization of the unitary coupled cluster ansatz. We show that this approach significantly reduces the size of the needed quantum training dataset while capturing the high accuracies needed within quantum chemistry simulations. The success of this two-step training method opens more opportunities to apply machine learning models on quantum data, a significant stride towards efficient quantum-classical hybrid computational models.

quantum computing↗

A study of nucleation and growth of thin films by means of computer simulation: General features

Some of the processes involved in the nucleation and growth of thin films were simulated by means of a digital computer. The simulation results were used to study the nucleation and growth kinetics resulting from the various processes. Kinetic results obtained for impingement, surface migration, impingement combined with surface migration, and with reevaporation are presented. A substantial fraction of the clusters may form directly upon impingement. Surface migration results in a decrease in cluster density, and reevaporation of atoms from the surface causes a further reduction in cluster density.

Salik, J.↗