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At least 1,297 records · Page 72

Large Scale Data Mining to Improve Usability of Data: An Intelligent Archive Testbed

Research in certain scientific disciplines - including Earth science, particle physics, and astrophysics - continually faces the challenge that the volume of data needed to perform valid scientific research can at times overwhelm even a sizable research community. The desire to improve utilization of this data gave rise to the Intelligent Archives project, which seeks to make data archives active participants in a knowledge building system capable of discovering events or patterns that represent new information or knowledge. Data mining can automatically discover patterns and events, but it is generally viewed as unsuited for large-scale use in disciplines like Earth science that routinely involve very high data volumes. Dozens of research projects have shown promising uses of data mining in Earth science, but all of these are based on experiments with data subsets of a few gigabytes or less, rather than the terabytes or petabytes typically encountered in operational systems. To bridge this gap, the Intelligent Archives project is establishing a testbed with the goal of demonstrating the use of data mining techniques in an operationally-relevant environment. This paper discusses the goals of the testbed and the design choices surrounding critical issues that arose during testbed implementation.

Ramapriyan, Hampapuram↗

Connecting Large‐Scale Meteorological Patterns to Extratropical Cyclones in CMIP6 Climate Models Using Self‐Organizing Maps

Abstract Extratropical cyclones (ETCs) are responsible for the majority of cool‐season extreme events in the northeastern United States (NEUS), often leading to high‐impact weather conditions that can have wide‐ranging socioeconomic impacts. Evaluating the ability of climate models to adequately simulate ETC dynamics is essential for improving model performance and increasing confidence in future projections used by stakeholders and policymakers. ETCs are traditionally studied using techniques such as case studies and synoptic typing, however, these approaches can be time‐consuming, require subjective analysis, and do not necessarily identify the coincident large‐scale meteorological patterns (LSMPs). Here, we apply self‐organizing maps (SOMs) as an automated machine‐learning approach to characterize the LSMPs and associated frequency and intensity of discrete ETC events over NEUS. The dominant patterns of geopotential height variability are identified through SOM analysis of five reanalysis products during the last four decades. ETC events are tracked using TempestExtremes and are integrated with SOMs to classify the accumulated cyclone activity (ACA) associated with each pattern. We then evaluate the skill of CMIP6 historical experiments in simulating the LSMPs and ETC events identified in the SOM. Our results identify a robust bias toward more zonal patterns, with models struggling to reproduce the more amplified patterns typically associated with the highest cyclone activity. While model resolution has some impact on simulation credibility, model configuration appears to be more important in LSMP representation. The vast majority of CMIP6 models produce too few ETCs, although model errors are distributed around historical reanalyses when ACA is normalized by storm frequency.

54 ENVIRONMENTAL SCIENCES↗

Increased Greenland Melt Triggered by Large-Scale, Year-Round Cyclonic Moisture Intrusions

Surface melting is a major driver of Greenland's mass loss. Yet, the mechanisms that trigger melt are still insufficiently understood because seasonally based studies blend processes initiating melt with positive feedbacks. Here, we focus on the triggers of melt by examining the synoptic atmospheric conditions associated with 313 rapid melt increases, detected in a satellite-derived melt extent product, equally distributed throughout the year over the period 1979-2012. By combining reanalysis and weather station data, we show that melt is initiated by a cyclone-driven, southerly flow of warm, moist air, which gives rise to large-scale precipitation. A decomposition of the synoptic atmospheric variability over Greenland suggests that the identified, melt-triggering weather pattern accounts for approximately 40 percent of the net precipitation, but increases in the frequency, duration and areal extent of the initiated melting have shifted the line between mass gain and mass loss as more melt and rainwater run off or accumulate in the snowpack. Using a regional climate model, we estimate that the initiated melting more than doubled over the investigated period, amounting to approximately 28 percent of the overall surface melt and revealing that, despite the involved mass gain, year-round precipitation events are participating in the ice sheet's decline.

Oltmanns, Marilena↗

Testing of the NASA Hypersonics Project Combined Cycle Engine Large Scale Inlet Mode Transition Experiment (CCE LlMX)

Status on an effort to develop Turbine Based Combined Cycle (TBCC) propulsion is described. This propulsion technology can enable reliable and reusable space launch systems. TBCC propulsion offers improved performance and safety over rocket propulsion. The potential to realize aircraft-like operations and reduced maintenance are additional benefits. Among most the critical TBCC enabling technologies are: 1) mode transition from turbine to scramjet propulsion, 2) high Mach turbine engines and 3) TBCC integration. To address these TBCC challenges, the effort is centered on a propulsion mode transition experiment and includes analytical research. The test program, the Combined-Cycle Engine Large Scale Inlet Mode Transition Experiment (CCE LIMX), was conceived to integrate TBCC propulsion with proposed hypersonic vehicles. The goals address: (1) dual inlet operability and performance, (2) mode-transition sequences enabling a switch between turbine and scramjet flow paths, and (3) turbine engine transients during transition. Four test phases are planned from which a database can be used to both validate design and analysis codes and characterize operability and integration issues for TBCC propulsion. In this paper we discuss the research objectives, features of the CCE hardware and test plans, and status of the parametric inlet characterization testing which began in 2011. This effort is sponsored by the NASA Fundamental Aeronautics Hypersonics project

Saunders, J. D.↗

Large-Scale Computational Fluid Dynamics Simulations of Aerospace Configurations on the Frontier Exascale System

Over the past fifteen years, the high performance computing landscape has undergone a seismic shift in both hardware and software paradigms, which has been necessary to realize a 1000× leap in computational performance while meeting stringent constraints on power consumption. A historical overview of a long-term research effort aimed at addressing these challenges within the context of a commonly-used aerospace computational fluid dynamics (CFD) application is presented. Details of the current implementation as they relate to the new era of exascale-relevant hardware architectures and programming models are described. Two large-scale simulations of aerospace configurations are performed using the entire Frontier exascale system, currently ranked as the most powerful supercomputing system in the world. The effort serves to address a 2024 milestone posed a decade ago by the seminal CFD Vision 2030 Study.

Eric J Nielsen↗

Relation of large-scale coronal X-ray structure and cosmic rays. II - Coronal control of interplanetary injection of 300 keV protons

We report the striking coronal control of low-energy solar particles from the solar flare of September 7, 1973. The flare was at S18, W46 (Carrington longitude 188 deg) in McMath Plage Region 12307. We find strong intensity gradients in heliolongitude (about 10% per deg) that are nearly identical in protons, helium, and medium nuclei at energies about 0.5 MeV/nuc, as well as relativistic electrons and 3 MeV protons. This pervasive gradient occurs at longitudes over bright X-ray emission structures east of the flare site which interconnect large-scale chromospheric polarity regions identifiable in H-alpha filtergrams.

Roelof, E. C.↗

On the possibility of detecting large-scale crustal remanent magnetization with Magsat vector magnetic anomaly data

Magnetic anomaly component data measured by Magsat is compared with synthetic anomaly component fields arising from an equivalent source dipole array at the earth's surface generated from total field anomaly data alone. It is found that the synthetic components fit the component data regardless of the dipole orientation assigned to the equivalent sources and of the dipole spacing. Tentative conclusions are: (1) over the U.S., vector anomaly fields can be determined to the accuracy of the measurements from the total field anomaly data alone; and (2) the equivalent source technique is not useful for determining the direction of large-scale crustal magnetization.

Galliher, S. C.↗

Influences of Local Sea-Surface Temperatures and Large-scale Dynamics on Monthly Precipitation Inferred from Two 10-year GCM-Simulations

Two parallel sets of 10-year long: January 1, 1982 to December 31, 1991, simulations were made with the finite volume General Circulation Model (fvGCM) in which the model integrations were forced with prescribed sea-surface temperature fields (SSTs) available as two separate SST-datasets. One dataset contained naturally varying monthly SSTs for the chosen period, and the oth& had the 12-monthly mean SSTs for the same period. Plots of evaporation, precipitation, and atmosphere-column moisture convergence, binned by l C SST intervals show that except for the tropics, the precipitation is more strongly constrained by large-scale dynamics as opposed to local SST. Binning data by SST naturally provided an ensemble average of data contributed from disparate locations with same SST; such averages could be expected to mitigate all location related influences. However, the plots revealed: i) evaporation, vertical velocity, and precipitation are very robust and remarkably similar for each of the two simulations and even for the data from 1987-ENSO-year simulation; ii) while the evaporation increased monotonically with SST up to about 27 C, the precipitation did not; iii) precipitation correlated much better with the column vertical velocity as opposed to SST suggesting that the influence of dynamical circulation including non-local SSTs is stronger than local-SSTs. The precipitation fields were doubly binned with respect to SST and boundary-layer mass and/or moisture convergence. The analysis discerned the rate of change of precipitation with local SST as a sum of partial derivative of precipitation with local SST plus partial derivative of precipitation with boundary layer moisture convergence multiplied by the rate of change of boundary-layer moisture convergence with SST (see Eqn. 3 of Section 4.5). This analysis is mathematically rigorous as well as provides a quantitative measure of the influence of local SST on the local precipitation. The results were recast to examine the dependence of local rainfall on local SSTs; it was discernible only in the tropics. Our methodology can be used for computing relationship between any forcing function and its effect(s) on a chosen field.

Sud, Y. C.↗

The relationship between large-scale vertical motion, highly reflective cloud, and sea surface temperature in the tropical Pacific region

Vertical motion fields at 850 mbar over the tropical Pacific region are calculated from the 1963-1973 mean wind fields for 4 months of the year and for October 1972, the peak month in the 1972-1973 El Nino event. These vertical motion fields are derived using the projective separation technique, which has the unique property of separating vertical motion into components due to meridional wind convergence and zonal wind convergence. This separation permits investigation of the response of the Hadley and Walker circulations to annual and interannual variation of the sea surface temperature in the tropical Pacific. The large-scale features of the computed vertical motion fields are in agreement with those of highly reflective clouds, which indicate the locations of deep convection. Examination of the annual cycle of the vertical motion and its components shows no strong variation of the Walker circulation with the east-west gradient of sea surface temperature. On the other hand, a strong correlation is found between meridional overturning in the eastern Pacific and the local equatorial sea surface temperature: during El Nino events, the eastern and central Pacific contribution to the Hadley circulation tends to increase.

Zimmermann, Peter H.↗

Galaxy evolution and large-scale structure in the far-infrared. I - IRAS pointed observations

Redshifts for 66 galaxies were obtained from a sample of 93 60-micron sources detected serendipitously in 22 IRAS deep pointed observations, covering a total area of 18.4 sq deg. The flux density limit of this survey is 150 mJy, 4 times fainter than the IRAS Point Source Catalog (PSC). The luminosity function is similar in shape with those previously published for samples selected from the PSC, with a median redshift of 0.048 for the fainter sample, but shifted to higher space densities. There is evidence that some of the excess number counts in the deeper sample can be explained in terms of a large-scale density enhancement beyond the Pavo-Indus supercluster. In addition, the faintest counts in the new sample confirm the result of Hacking et al. (1989) that faint IRAS 60-micron source counts lie significantly in excess of an extrapolation of the PSC counts assuming no luminosity or density evolution.

Lonsdale, Carol J.↗

Large-scale characteristics of interstellar dust from COBE DIRBE observations

Observations from the COBE Diffuse Infrared Background Experiment of the 140 and 240 micrometer emissions from the Galatic plane region (absolute value of b less than 10 deg) are combined with radio surveys that trace the molecular (H2), neutral atomic (H I), and extended low-density (n(sub e) approximately 10 to 100/cm(exp 3)) ionized (H II) gas phases of the interstellar medium to derive physical conditions such as the dust temperature, dust-to-gas mass ratio, and far-infrared emissivity (1) averaged over these gas phases along each line of sight and (2) within each of these three gas phases. This analysis shows large-scale longitudinal and latitudinal gradients in the dust temperature and a decrease in dust temperature with increasing Galactocentric distance. The derived dust temperatures are significantly different from those derived in similar analyses using the Infrared Astronomical Satellite (IRAS) 60 and 100 micrometer data, suggesting that small (5 A approximately less than radius approximately less than 200 A) transiently heated dust particles contribute significantly o the Galactic 60 micrometer emission. It is found that 60% to 75% of the far-infrared luminosity arises from cold (approximately 17 to 22 K) dust associated with diffuse H I clouds, 15% to 30% from cold (approximately 19 K) dust associated with molecular gas, and less than 10% from warm (approximately 29 K) dust in extended low-density H II regions, consistent with the results of the IRAS analyses of the Galactic 60 and 100 micrometer emission. Within 2 deg of longitude of the Galactic center, the derived gas-to-dust mass ratio along the line of sight, G(sub d), reverses its general trend of decreasing G(sub d) toward the inner Galaxy and increases by a factor of approximately 2 to 3 toward the Galactic center. One possible explanation for this result is that the ratio of H2 column density to (12)CO intensity is lower in the Galactic center region than in the Galactic disk.

Sodroski, T. J.↗

Large-scale wind turbine structures

The purpose of this presentation is to show how structural technology was applied in the design of modern wind turbines, which were recently brought to an advanced stage of development as sources of renewable power. Wind turbine structures present many difficult problems because they are relatively slender and flexible; subject to vibration and aeroelastic instabilities; acted upon by loads which are often nondeterministic; operated continuously with little maintenance in all weather; and dominated by life-cycle cost considerations. Progress in horizontal-axis wind turbines (HAWT) development was paced by progress in the understanding of structural loads, modeling of structural dynamic response, and designing of innovative structural response. During the past 15 years a series of large HAWTs was developed. This has culminated in the recent completion of the world's largest operating wind turbine, the 3.2 MW Mod-5B power plane installed on the island of Oahu, Hawaii. Some of the applications of structures technology to wind turbine will be illustrated by referring to the Mod-5B design. First, a video overview will be presented to provide familiarization with the Mod-5B project and the important components of the wind turbine system. Next, the structural requirements for large-scale wind turbines will be discussed, emphasizing the difficult fatigue-life requirements. Finally, the procedures used to design the structure will be presented, including the use of the fracture mechanics approach for determining allowable fatigue stresses.

Spera, David A.↗

Large-scale real-time signal processing in physics experiments: the ALICE TPC FPGA pipeline

For LHC Run 3, the ALICE Time Projection Chamber was upgraded to operate in continuous readout mode. Interaction rates of up to 50 kHz in Pb-Pb collisions require real-time processing of more than 3 TB s -1 of raw detector data. This requirement is met by a custom FPGA-based processing pipeline that performs the complete front-end data treatment fully in-stream, including common-mode correction, pedestal subtraction, ion-tail filtering, zero suppression, and dense data packing. A central element of the design is a highly parallel common-mode correction algorithm operating directly on the streaming data. It robustly identifies signal-free readout channels on a time-bin basis and applies pad-dependent scaling to compensate for local variations in capacitive coupling in the GEM readout. In combination with pedestal subtraction and ion-tail filtering, this enables accurate baseline restoration under extreme high-occupancy conditions, preventing signal loss while efficiently suppressing noise prior to zero suppression. The pipeline operates continuously at the full detector bandwidth and reduces the raw input rate of approximately 3 TB s -1 to about 900 GBps for Pb-Pb collisions at the target interaction rate. Overall, it represents a large-scale FPGA-based real-time signal-processing implementation for high-energy physics detector readout.

Digital signal processing (DSP)↗

Large-scale computations in fluid mechanics; Proceedings of the Fifteenth Summer Seminar on Applied Mathematics, University of California, La Jolla, CA, June 27-July 8, 1983. Parts 1 & 2

Papers are presented on such topics as the use of semi-Lagrangian advective schemes in meteorological modeling; computation with high-resolution upwind schemes for hyperbolic equations; dynamics of flame propagation in a turbulent field; a modified finite element method for solving the incompressible Navier-Stokes equations; computational fusion magnetohydrodynamics; and a nonoscillatory shock capturing scheme using flux-limited dissipation. Consideration is also given to the use of spectral techniques in numerical weather prediction; numerical methods for the incorporation of mountains in atmospheric models; techniques for the numerical simulation of large-scale eddies in geophysical fluid dynamics; high-resolution TVD schemes using flux limiters; upwind-difference methods for aerodynamic problems governed by the Euler equations; and an MHD model of the earth's magnetosphere.

Engquist, B. E.↗

Entropy and Boundary Based Adversarial Learning for Large Scale Unsupervised Domain Adaptation

Supervised semantic segmentation methods provide state-of-the-art performance, but their performance is limited by the amount of quality labeled data they need for training. Scarcity of labeled data and non-transferablity of models, due to cross-domain discrepancy makes it a bigger challenge for remote sensing imagery analysis. In this work, we approach this problem through adversarial learning, driven by entropy and boundary of region-of-interest for unsupervised domain adaptation. This concept helps with better boundary prediction and encourages target domain entropy maps (probability/uncertainty maps) to be similar to source domains. In particular, we showed that deriving informative entropy through the adversarial learning is essential to enable the adaptation. We used a large scale cross country building extraction dataset to validate the framework. The experimental results show the usefulness of considering boundary and entropy driven adversarial learning for adaptation.

Makkar, Nikhil↗

Evidence for the interaction of large scale magnetic structures in solar flares

By modeling the observed vertical magnetic field of an active region AR 2372 by the potential field of an ensemble of magnetic dipoles, the likely location of the separatrices, surfaces that separates cells of different field line connectivities, and of the separator which is the intersection of the separatrices, is derived. Four of the five off-band H-alpha kernels of a flare that occurred less than 20 minutes before obtaining the magnetogram are shown to have taken place near or at the separatrices. These H-alpha kernels are connected by field lines that pass near the separator. This indicates that the flare may have resulted from the interaction in the separator region of large scale magnetic structures.

Mandrini, C. H.↗

Large-Scale Hollow Retroreflectors for Lunar Laser Ranging at Goddard Space Flight Center

Laser ranging to the retroreflector arrays placed on the lunar surface by the Apollo astronauts and the Soviet Luna missions have dramatically increased our understanding of gravitational physics along with Earth and Moon geophysics, geodesy, and dynamics. Although the precision of the range measurements has historically been limited by the ground station capabilities, advances in the APOLLO instrument at the Apache Point facility in New Mexico is beginning to be limited by errors associated with the lunar arrays. We report here on efforts at Goddard Space Flight Center to develop the next generation of lunar retroreflectors. We will describe a new facility that is being used to design, assemble, and test large-scale hollow retroreflectors. We will also describe results from investigations into various bonding techniques used to assemble the open comer cubes and mirror coatings that have dust mitigation properties.

Preston, Alix↗

Learning to Solve Large-Scale Security-Constrained Unit Commitment Problems

Security-constrained unit commitment (SCUC) is a fundamental problem in power systems and electricity markets. In practical settings, SCUC is repeatedly solved via mixed-integer linear programming (MIP), sometimes multiple times per day, with only minor changes in input data. In this work, we propose a number of machine learning techniques to effectively extract information from previously solved instances in order to significantly improve the computational performance of MIP solvers when solving similar instances in the future. Based on statistical data, we predict redundant constraints in the formulation, good initial feasible solutions, and affine subspaces where the optimal solution is likely to lie, leading to a significant reduction in problem size. Computational results on a diverse set of realistic and large-scale instances show that using the proposed techniques, SCUC can be solved on average 4.3 times faster with optimality guarantees and 10.2 times faster without optimality guarantees, with no observed reduction in solution quality. Out-of-distribution experiments provide evidence that the method is somewhat robust against data-set shift. Summary of Contribution. The paper describes a novel computational method, based on a combination of mixed-integer linear programming (MILP) and machine learning (ML), to solve a challenging and fundamental optimization problem in the energy sector. The method advances the state-of-the-art, not only for this particular problem, but also, more generally, in solving discrete optimization problems via ML. We expect that the techniques presented can be readily used by practitioners in the energy sector and adapted, by researchers in other fields, to other challenging operations research problems that are solved routinely.

Machine Learning↗