Networks and landscapes: a framework for setting goals and evaluating performance at the large landscape scale

Treesearch

R Patrick Bixler; Shawn Johnson; Kirk Emerson; Tina Nabatchi; Melly Reuling; Charles Curtin; Michele Romolini; Morgan Grove

2016-01-01

The objective of large landscape conser vation is to mitigate complex ecological problems through interventions at multiple and overlapping scales. Implementation requires coordination among a diverse network of individuals and organizations to integrate local-scale conservation activities with broad-scale goals. This requires an understanding of the governance options...

Performance of Extended Local Clustering Organization (LCO) for Large Scale Job-Shop Scheduling Problem (JSP)

NASA Astrophysics Data System (ADS)

Konno, Yohko; Suzuki, Keiji

This paper describes an approach to development of a solution algorithm of a general-purpose for large scale problems using “Local Clustering Organization (LCO)” as a new solution for Job-shop scheduling problem (JSP). Using a performance effective large scale scheduling in the study of usual LCO, a solving JSP keep stability induced better solution is examined. In this study for an improvement of a performance of a solution for JSP, processes to a optimization by LCO is examined, and a scheduling solution-structure is extended to a new solution-structure based on machine-division. A solving method introduced into effective local clustering for the solution-structure is proposed as an extended LCO. An extended LCO has an algorithm which improves scheduling evaluation efficiently by clustering of parallel search which extends over plural machines. A result verified by an application of extended LCO on various scale of problems proved to conduce to minimizing make-span and improving on the stable performance.

Application of multivariate analysis and mass transfer principles for refinement of a 3-L bioreactor scale-down model--when shake flasks mimic 15,000-L bioreactors better.

PubMed

Ahuja, Sanjeev; Jain, Shilpa; Ram, Kripa

2015-01-01

Characterization of manufacturing processes is key to understanding the effects of process parameters on process performance and product quality. These studies are generally conducted using small-scale model systems. Because of the importance of the results derived from these studies, the small-scale model should be predictive of large scale. Typically, small-scale bioreactors, which are considered superior to shake flasks in simulating large-scale bioreactors, are used as the scale-down models for characterizing mammalian cell culture processes. In this article, we describe a case study where a cell culture unit operation in bioreactors using one-sided pH control and their satellites (small-scale runs conducted using the same post-inoculation cultures and nutrient feeds) in 3-L bioreactors and shake flasks indicated that shake flasks mimicked the large-scale performance better than 3-L bioreactors. We detail here how multivariate analysis was used to make the pertinent assessment and to generate the hypothesis for refining the existing 3-L scale-down model. Relevant statistical techniques such as principal component analysis, partial least square, orthogonal partial least square, and discriminant analysis were used to identify the outliers and to determine the discriminatory variables responsible for performance differences at different scales. The resulting analysis, in combination with mass transfer principles, led to the hypothesis that observed similarities between 15,000-L and shake flask runs, and differences between 15,000-L and 3-L runs, were due to pCO2 and pH values. This hypothesis was confirmed by changing the aeration strategy at 3-L scale. By reducing the initial sparge rate in 3-L bioreactor, process performance and product quality data moved closer to that of large scale. © 2015 American Institute of Chemical Engineers.

Performance of lap splices in large-scale column specimens affected by ASR and/or DEF-extension phase.

DOT National Transportation Integrated Search

2015-03-01

A large experimental program, consisting of the design, construction, curing, exposure, and structural load : testing of 16 large-scale column specimens with a critical lap splice region that were influenced by varying : stages of alkali-silica react...

Vapor and healing treatment for CH3NH3PbI3-xClx films toward large-area perovskite solar cells

NASA Astrophysics Data System (ADS)

Gouda, Laxman; Gottesman, Ronen; Tirosh, Shay; Haltzi, Eynav; Hu, Jiangang; Ginsburg, Adam; Keller, David A.; Bouhadana, Yaniv; Zaban, Arie

2016-03-01

Hybrid methyl-ammonium lead trihalide perovskites are promising low-cost materials for use in solar cells and other optoelectronic applications. With a certified photovoltaic conversion efficiency record of 20.1%, scale-up for commercial purposes is already underway. However, preparation of large-area perovskite films remains a challenge, and films of perovskites on large electrodes suffer from non-uniform performance. Thus, production and characterization of the lateral uniformity of large-area films is a crucial step towards scale-up of devices. In this paper, we present a reproducible method for improving the lateral uniformity and performance of large-area perovskite solar cells (32 cm2). The method is based on methyl-ammonium iodide (MAI) vapor treatment as a new step in the sequential deposition of perovskite films. Following the MAI vapor treatment, we used high throughput techniques to map the photovoltaic performance throughout the large-area device. The lateral uniformity and performance of all photovoltaic parameters (Voc, Jsc, Fill Factor, Photo-conversion efficiency) increased, with an overall improved photo-conversion efficiency of ~100% following a vapor treatment at 140 °C. Based on XRD and photoluminescence measurements, We propose that the MAI treatment promotes a ``healing effect'' to the perovskite film which increases the lateral uniformity across the large-area solar cell. Thus, the straightforward MAI vapor treatment is highly beneficial for large scale commercialization of perovskite solar cells, regardless of the specific deposition method.Hybrid methyl-ammonium lead trihalide perovskites are promising low-cost materials for use in solar cells and other optoelectronic applications. With a certified photovoltaic conversion efficiency record of 20.1%, scale-up for commercial purposes is already underway. However, preparation of large-area perovskite films remains a challenge, and films of perovskites on large electrodes suffer from non-uniform performance. Thus, production and characterization of the lateral uniformity of large-area films is a crucial step towards scale-up of devices. In this paper, we present a reproducible method for improving the lateral uniformity and performance of large-area perovskite solar cells (32 cm2). The method is based on methyl-ammonium iodide (MAI) vapor treatment as a new step in the sequential deposition of perovskite films. Following the MAI vapor treatment, we used high throughput techniques to map the photovoltaic performance throughout the large-area device. The lateral uniformity and performance of all photovoltaic parameters (Voc, Jsc, Fill Factor, Photo-conversion efficiency) increased, with an overall improved photo-conversion efficiency of ~100% following a vapor treatment at 140 °C. Based on XRD and photoluminescence measurements, We propose that the MAI treatment promotes a ``healing effect'' to the perovskite film which increases the lateral uniformity across the large-area solar cell. Thus, the straightforward MAI vapor treatment is highly beneficial for large scale commercialization of perovskite solar cells, regardless of the specific deposition method. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr08658b

Efficient On-Demand Operations in Large-Scale Infrastructures

ERIC Educational Resources Information Center

Ko, Steven Y.

2009-01-01

In large-scale distributed infrastructures such as clouds, Grids, peer-to-peer systems, and wide-area testbeds, users and administrators typically desire to perform "on-demand operations" that deal with the most up-to-date state of the infrastructure. However, the scale and dynamism present in the operating environment make it challenging to…

Leading Educational Change and Improvement at Scale: Some Inconvenient Truths about System Performance

ERIC Educational Resources Information Center

Harris, Alma; Jones, Michelle

2017-01-01

The challenges of securing educational change and transformation, at scale, remain considerable. While sustained progress has been made in some education systems (Fullan, 2009; Hargreaves & Shirley, 2009) generally, it remains the case that the pathway to large-scale, system improvement is far from easy or straightforward. While large-scale…

Large-scale Labeled Datasets to Fuel Earth Science Deep Learning Applications

NASA Astrophysics Data System (ADS)

Maskey, M.; Ramachandran, R.; Miller, J.

2017-12-01

Deep learning has revolutionized computer vision and natural language processing with various algorithms scaled using high-performance computing. However, generic large-scale labeled datasets such as the ImageNet are the fuel that drives the impressive accuracy of deep learning results. Large-scale labeled datasets already exist in domains such as medical science, but creating them in the Earth science domain is a challenge. While there are ways to apply deep learning using limited labeled datasets, there is a need in the Earth sciences for creating large-scale labeled datasets for benchmarking and scaling deep learning applications. At the NASA Marshall Space Flight Center, we are using deep learning for a variety of Earth science applications where we have encountered the need for large-scale labeled datasets. We will discuss our approaches for creating such datasets and why these datasets are just as valuable as deep learning algorithms. We will also describe successful usage of these large-scale labeled datasets with our deep learning based applications.

Gravity versus radiation models: on the importance of scale and heterogeneity in commuting flows.

PubMed

Masucci, A Paolo; Serras, Joan; Johansson, Anders; Batty, Michael

2013-08-01

We test the recently introduced radiation model against the gravity model for the system composed of England and Wales, both for commuting patterns and for public transportation flows. The analysis is performed both at macroscopic scales, i.e., at the national scale, and at microscopic scales, i.e., at the city level. It is shown that the thermodynamic limit assumption for the original radiation model significantly underestimates the commuting flows for large cities. We then generalize the radiation model, introducing the correct normalization factor for finite systems. We show that even if the gravity model has a better overall performance the parameter-free radiation model gives competitive results, especially for large scales.

Small-scale test program to develop a more efficient swivel nozzle thrust deflector for V/STOL lift/cruise engines

NASA Technical Reports Server (NTRS)

Schlundt, D. W.

1976-01-01

The installed performance degradation of a swivel nozzle thrust deflector system obtained during increased vectoring angles of a large-scale test program was investigated and improved. Small-scale models were used to generate performance data for analyzing selected swivel nozzle configurations. A single-swivel nozzle design model with five different nozzle configurations and a twin-swivel nozzle design model, scaled to 0.15 size of the large-scale test hardware, were statically tested at low exhaust pressure ratios of 1.4, 1.3, 1.2, and 1.1 and vectored at four nozzle positions from 0 deg cruise through 90 deg vertical used for the VTOL mode.

NAEP Validity Studies: Improving the Information Value of Performance Items in Large Scale Assessments. Working Paper No. 2003-08

ERIC Educational Resources Information Center

Pearson, P. David; Garavaglia, Diane R.

2003-01-01

The purpose of this essay is to explore both what is known and what needs to be learned about the information value of performance items "when they are used in large scale assessments." Within the context of the National Assessment of Educational Progress (NAEP), there is substantial motivation for answering these questions. Over the…

Large-Scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation

DTIC Science & Technology

2016-08-10

AFRL-AFOSR-JP-TR-2016-0073 Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation ...2016 4.  TITLE AND SUBTITLE Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation 5a...performances on various machine learning tasks and it naturally lends itself to fast parallel implementations . Despite this, very little work has been

Visual Data-Analytics of Large-Scale Parallel Discrete-Event Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ross, Caitlin; Carothers, Christopher D.; Mubarak, Misbah

Parallel discrete-event simulation (PDES) is an important tool in the codesign of extreme-scale systems because PDES provides a cost-effective way to evaluate designs of highperformance computing systems. Optimistic synchronization algorithms for PDES, such as Time Warp, allow events to be processed without global synchronization among the processing elements. A rollback mechanism is provided when events are processed out of timestamp order. Although optimistic synchronization protocols enable the scalability of large-scale PDES, the performance of the simulations must be tuned to reduce the number of rollbacks and provide an improved simulation runtime. To enable efficient large-scale optimistic simulations, one has tomore » gain insight into the factors that affect the rollback behavior and simulation performance. We developed a tool for ROSS model developers that gives them detailed metrics on the performance of their large-scale optimistic simulations at varying levels of simulation granularity. Model developers can use this information for parameter tuning of optimistic simulations in order to achieve better runtime and fewer rollbacks. In this work, we instrument the ROSS optimistic PDES framework to gather detailed statistics about the simulation engine. We have also developed an interactive visualization interface that uses the data collected by the ROSS instrumentation to understand the underlying behavior of the simulation engine. The interface connects real time to virtual time in the simulation and provides the ability to view simulation data at different granularities. We demonstrate the usefulness of our framework by performing a visual analysis of the dragonfly network topology model provided by the CODES simulation framework built on top of ROSS. The instrumentation needs to minimize overhead in order to accurately collect data about the simulation performance. To ensure that the instrumentation does not introduce unnecessary overhead, we perform a scaling study that compares instrumented ROSS simulations with their noninstrumented counterparts in order to determine the amount of perturbation when running at different simulation scales.« less

Demonstrating a new framework for the comparison of environmental impacts from small- and large-scale hydropower and wind power projects.

PubMed

Bakken, Tor Haakon; Aase, Anne Guri; Hagen, Dagmar; Sundt, Håkon; Barton, David N; Lujala, Päivi

2014-07-01

Climate change and the needed reductions in the use of fossil fuels call for the development of renewable energy sources. However, renewable energy production, such as hydropower (both small- and large-scale) and wind power have adverse impacts on the local environment by causing reductions in biodiversity and loss of habitats and species. This paper compares the environmental impacts of many small-scale hydropower plants with a few large-scale hydropower projects and one wind power farm, based on the same set of environmental parameters; land occupation, reduction in wilderness areas (INON), visibility and impacts on red-listed species. Our basis for comparison was similar energy volumes produced, without considering the quality of the energy services provided. The results show that small-scale hydropower performs less favourably in all parameters except land occupation. The land occupation of large hydropower and wind power is in the range of 45-50 m(2)/MWh, which is more than two times larger than the small-scale hydropower, where the large land occupation for large hydropower is explained by the extent of the reservoirs. On all the three other parameters small-scale hydropower performs more than two times worse than both large hydropower and wind power. Wind power compares similarly to large-scale hydropower regarding land occupation, much better on the reduction in INON areas, and in the same range regarding red-listed species. Our results demonstrate that the selected four parameters provide a basis for further development of a fair and consistent comparison of impacts between the analysed renewable technologies. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Large-scale synthesis of high-quality hexagonal boron nitride nanosheets for large-area graphene electronics.

PubMed

Lee, Kang Hyuck; Shin, Hyeon-Jin; Lee, Jinyeong; Lee, In-yeal; Kim, Gil-Ho; Choi, Jae-Young; Kim, Sang-Woo

2012-02-08

Hexagonal boron nitride (h-BN) has received a great deal of attention as a substrate material for high-performance graphene electronics because it has an atomically smooth surface, lattice constant similar to that of graphene, large optical phonon modes, and a large electrical band gap. Herein, we report the large-scale synthesis of high-quality h-BN nanosheets in a chemical vapor deposition (CVD) process by controlling the surface morphologies of the copper (Cu) catalysts. It was found that morphology control of the Cu foil is much critical for the formation of the pure h-BN nanosheets as well as the improvement of their crystallinity. For the first time, we demonstrate the performance enhancement of CVD-based graphene devices with large-scale h-BN nanosheets. The mobility of the graphene device on the h-BN nanosheets was increased 3 times compared to that without the h-BN nanosheets. The on-off ratio of the drain current is 2 times higher than that of the graphene device without h-BN. This work suggests that high-quality h-BN nanosheets based on CVD are very promising for high-performance large-area graphene electronics. © 2012 American Chemical Society

Linear static structural and vibration analysis on high-performance computers

NASA Technical Reports Server (NTRS)

Baddourah, M. A.; Storaasli, O. O.; Bostic, S. W.

1993-01-01

Parallel computers offer the oppurtunity to significantly reduce the computation time necessary to analyze large-scale aerospace structures. This paper presents algorithms developed for and implemented on massively-parallel computers hereafter referred to as Scalable High-Performance Computers (SHPC), for the most computationally intensive tasks involved in structural analysis, namely, generation and assembly of system matrices, solution of systems of equations and calculation of the eigenvalues and eigenvectors. Results on SHPC are presented for large-scale structural problems (i.e. models for High-Speed Civil Transport). The goal of this research is to develop a new, efficient technique which extends structural analysis to SHPC and makes large-scale structural analyses tractable.

Computing the universe: how large-scale simulations illuminate galaxies and dark energy

NASA Astrophysics Data System (ADS)

O'Shea, Brian

2015-04-01

High-performance and large-scale computing is absolutely to understanding astronomical objects such as stars, galaxies, and the cosmic web. This is because these are structures that operate on physical, temporal, and energy scales that cannot be reasonably approximated in the laboratory, and whose complexity and nonlinearity often defies analytic modeling. In this talk, I show how the growth of computing platforms over time has facilitated our understanding of astrophysical and cosmological phenomena, focusing primarily on galaxies and large-scale structure in the Universe.

Improved technique that allows the performance of large-scale SNP genotyping on DNA immobilized by FTA technology.

PubMed

He, Hongbin; Argiro, Laurent; Dessein, Helia; Chevillard, Christophe

2007-01-01

FTA technology is a novel method designed to simplify the collection, shipment, archiving and purification of nucleic acids from a wide variety of biological sources. The number of punches that can normally be obtained from a single specimen card are often however, insufficient for the testing of the large numbers of loci required to identify genetic factors that control human susceptibility or resistance to multifactorial diseases. In this study, we propose an improved technique to perform large-scale SNP genotyping. We applied a whole genome amplification method to amplify DNA from buccal cell samples stabilized using FTA technology. The results show that using the improved technique it is possible to perform up to 15,000 genotypes from one buccal cell sample. Furthermore, the procedure is simple. We consider this improved technique to be a promising methods for performing large-scale SNP genotyping because the FTA technology simplifies the collection, shipment, archiving and purification of DNA, while whole genome amplification of FTA card bound DNA produces sufficient material for the determination of thousands of SNP genotypes.

Comparison of Large eddy dynamo simulation using dynamic sub-grid scale (SGS) model with a fully resolved direct simulation in a rotating spherical shell

NASA Astrophysics Data System (ADS)

Matsui, H.; Buffett, B. A.

2017-12-01

The flow in the Earth's outer core is expected to have vast length scale from the geometry of the outer core to the thickness of the boundary layer. Because of the limitation of the spatial resolution in the numerical simulations, sub-grid scale (SGS) modeling is required to model the effects of the unresolved field on the large-scale fields. We model the effects of sub-grid scale flow and magnetic field using a dynamic scale similarity model. Four terms are introduced for the momentum flux, heat flux, Lorentz force and magnetic induction. The model was previously used in the convection-driven dynamo in a rotating plane layer and spherical shell using the Finite Element Methods. In the present study, we perform large eddy simulations (LES) using the dynamic scale similarity model. The scale similarity model is implement in Calypso, which is a numerical dynamo model using spherical harmonics expansion. To obtain the SGS terms, the spatial filtering in the horizontal directions is done by taking the convolution of a Gaussian filter expressed in terms of a spherical harmonic expansion, following Jekeli (1981). A Gaussian field is also applied in the radial direction. To verify the present model, we perform a fully resolved direct numerical simulation (DNS) with the truncation of the spherical harmonics L = 255 as a reference. And, we perform unresolved DNS and LES with SGS model on coarser resolution (L= 127, 84, and 63) using the same control parameter as the resolved DNS. We will discuss the verification results by comparison among these simulations and role of small scale fields to large scale fields through the role of the SGS terms in LES.

Achieving a Successful Scale-Down Model and Optimized Economics through Parvovirus Filter Validation using Purified TrueSpikeTM Viruses.

PubMed

De Vilmorin, Philippe; Slocum, Ashley; Jaber, Tareq; Schaefer, Oliver; Ruppach, Horst; Genest, Paul

2015-01-01

This article describes a four virus panel validation of EMD Millipore's (Bedford, MA) small virus-retentive filter, Viresolve® Pro, using TrueSpike(TM) viruses for a Biogen Idec process intermediate. The study was performed at Charles River Labs in King of Prussia, PA. Greater than 900 L/m(2) filter throughput was achieved with the approximately 8 g/L monoclonal antibody feed. No viruses were detected in any filtrate samples. All virus log reduction values were between ≥3.66 and ≥5.60. The use of TrueSpike(TM) at Charles River Labs allowed Biogen Idec to achieve a more representative scaled-down model and potentially reduce the cost of its virus filtration step and the overall cost of goods. The body of data presented here is an example of the benefits of following the guidance from the PDA Technical Report 47, The Preparation of Virus Spikes Used for Viral Clearance Studies. The safety of biopharmaceuticals is assured through the use of multiple steps in the purification process that are capable of virus clearance, including filtration with virus-retentive filters. The amount of virus present at the downstream stages in the process is expected to be and is typically low. The viral clearance capability of the filtration step is assessed in a validation study. The study utilizes a small version of the larger manufacturing size filter, and a large, known amount of virus is added to the feed prior to filtration. Viral assay before and after filtration allows the virus log reduction value to be quantified. The representativeness of the small-scale model is supported by comparing large-scale filter performance to small-scale filter performance. The large-scale and small-scale filtration runs are performed using the same operating conditions. If the filter performance at both scales is comparable, it supports the applicability of the virus log reduction value obtained with the small-scale filter to the large-scale manufacturing process. However, the virus preparation used to spike the feed material often contains impurities that contribute adversely to virus filter performance in the small-scale model. The added impurities from the virus spike, which are not present at manufacturing scale, compromise the scale-down model and put into question the direct applicability of the virus clearance results. Another consequence of decreased filter performance due to virus spike impurities is the unnecessary over-sizing of the manufacturing system to match the low filter capacity observed in the scale-down model. This article describes how improvements in mammalian virus spike purity ensure the validity of the log reduction value obtained with the scale-down model and support economically optimized filter usage. © PDA, Inc. 2015.

Large-Scale Wind Turbine Testing in the NASA 24.4m (80) by 36.6m(120) Wind Tunnel

NASA Technical Reports Server (NTRS)

Zell, Peter T.; Imprexia, Cliff (Technical Monitor)

2000-01-01

The 80- by 120-Foot Wind Tunnel at NASA Ames Research Center in California provides a unique capability to test large-scale wind turbines under controlled conditions. This special capability is now available for domestic and foreign entities wishing to test large-scale wind turbines. The presentation will focus on facility capabilities to perform wind turbine tests and typical research objectives for this type of testing.

Self-consistency tests of large-scale dynamics parameterizations for single-column modeling

DOE PAGES

Edman, Jacob P.; Romps, David M.

2015-03-18

Large-scale dynamics parameterizations are tested numerically in cloud-resolving simulations, including a new version of the weak-pressure-gradient approximation (WPG) introduced by Edman and Romps (2014), the weak-temperature-gradient approximation (WTG), and a prior implementation of WPG. We perform a series of self-consistency tests with each large-scale dynamics parameterization, in which we compare the result of a cloud-resolving simulation coupled to WTG or WPG with an otherwise identical simulation with prescribed large-scale convergence. In self-consistency tests based on radiative-convective equilibrium (RCE; i.e., no large-scale convergence), we find that simulations either weakly coupled or strongly coupled to either WPG or WTG are self-consistent, butmore » WPG-coupled simulations exhibit a nonmonotonic behavior as the strength of the coupling to WPG is varied. We also perform self-consistency tests based on observed forcings from two observational campaigns: the Tropical Warm Pool International Cloud Experiment (TWP-ICE) and the ARM Southern Great Plains (SGP) Summer 1995 IOP. In these tests, we show that the new version of WPG improves upon prior versions of WPG by eliminating a potentially troublesome gravity-wave resonance.« less

Improving parallel I/O autotuning with performance modeling

DOE PAGES

Behzad, Babak; Byna, Surendra; Wild, Stefan M.; ...

2014-01-01

Various layers of the parallel I/O subsystem offer tunable parameters for improving I/O performance on large-scale computers. However, searching through a large parameter space is challenging. We are working towards an autotuning framework for determining the parallel I/O parameters that can achieve good I/O performance for different data write patterns. In this paper, we characterize parallel I/O and discuss the development of predictive models for use in effectively reducing the parameter space. Furthermore, applying our technique on tuning an I/O kernel derived from a large-scale simulation code shows that the search time can be reduced from 12 hours to 2more » hours, while achieving 54X I/O performance speedup.« less

Performance/price estimates for cortex-scale hardware: a design space exploration.

PubMed

Zaveri, Mazad S; Hammerstrom, Dan

2011-04-01

In this paper, we revisit the concept of virtualization. Virtualization is useful for understanding and investigating the performance/price and other trade-offs related to the hardware design space. Moreover, it is perhaps the most important aspect of a hardware design space exploration. Such a design space exploration is a necessary part of the study of hardware architectures for large-scale computational models for intelligent computing, including AI, Bayesian, bio-inspired and neural models. A methodical exploration is needed to identify potentially interesting regions in the design space, and to assess the relative performance/price points of these implementations. As an example, in this paper we investigate the performance/price of (digital and mixed-signal) CMOS and hypothetical CMOL (nanogrid) technology based hardware implementations of human cortex-scale spiking neural systems. Through this analysis, and the resulting performance/price points, we demonstrate, in general, the importance of virtualization, and of doing these kinds of design space explorations. The specific results suggest that hybrid nanotechnology such as CMOL is a promising candidate to implement very large-scale spiking neural systems, providing a more efficient utilization of the density and storage benefits of emerging nano-scale technologies. In general, we believe that the study of such hypothetical designs/architectures will guide the neuromorphic hardware community towards building large-scale systems, and help guide research trends in intelligent computing, and computer engineering. Copyright © 2010 Elsevier Ltd. All rights reserved.

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

NASA Technical Reports Server (NTRS)

Shameldin, Ramez Ahmed; Bowling, Shannon R.

2010-01-01

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

A large-scale photonic node architecture that utilizes interconnected OXC subsystems.

PubMed

Iwai, Yuto; Hasegawa, Hiroshi; Sato, Ken-ichi

2013-01-14

We propose a novel photonic node architecture that is composed of interconnected small-scale optical cross-connect subsystems. We also developed an efficient dynamic network control algorithm that complies with a restriction on the number of intra-node fibers used for subsystem interconnection. Numerical evaluations verify that the proposed architecture offers almost the same performance as the equivalent single large-scale cross-connect switch, while enabling substantial hardware scale reductions.

Fabrication and performance analysis of 4-sq cm indium tin oxide/InP photovoltaic solar cells

NASA Technical Reports Server (NTRS)

Gessert, T. A.; Li, X.; Phelps, P. W.; Coutts, T. J.; Tzafaras, N.

1991-01-01

Large-area photovoltaic solar cells based on direct current magnetron sputter deposition of indium tin oxide (ITO) into single-crystal p-InP substrates demonstrated both the radiation hardness and high performance necessary for extraterrestrial applications. A small-scale production project was initiated in which approximately 50 ITO/InP cells are being produced. The procedures used in this small-scale production of 4-sq cm ITO/InP cells are presented and discussed. The discussion includes analyses of performance range of all available production cells, and device performance data of the best cells thus far produced. Additionally, processing experience gained from the production of these cells is discussed, indicating other issues that may be encountered when large-scale productions are begun.

Performance of Grey Wolf Optimizer on large scale problems

NASA Astrophysics Data System (ADS)

Gupta, Shubham; Deep, Kusum

2017-01-01

For solving nonlinear continuous problems of optimization numerous nature inspired optimization techniques are being proposed in literature which can be implemented to solve real life problems wherein the conventional techniques cannot be applied. Grey Wolf Optimizer is one of such technique which is gaining popularity since the last two years. The objective of this paper is to investigate the performance of Grey Wolf Optimization Algorithm on large scale optimization problems. The Algorithm is implemented on 5 common scalable problems appearing in literature namely Sphere, Rosenbrock, Rastrigin, Ackley and Griewank Functions. The dimensions of these problems are varied from 50 to 1000. The results indicate that Grey Wolf Optimizer is a powerful nature inspired Optimization Algorithm for large scale problems, except Rosenbrock which is a unimodal function.

Development and Applications of a Modular Parallel Process for Large Scale Fluid/Structures Problems

NASA Technical Reports Server (NTRS)

Guruswamy, Guru P.; Kwak, Dochan (Technical Monitor)

2002-01-01

A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel supercomputers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.

Development and Applications of a Modular Parallel Process for Large Scale Fluid/Structures Problems

NASA Technical Reports Server (NTRS)

Guruswamy, Guru P.; Byun, Chansup; Kwak, Dochan (Technical Monitor)

2001-01-01

A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel super computers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.

Requirements for a mobile communications satellite system. Volume 3: Large space structures measurements study

NASA Technical Reports Server (NTRS)

Akle, W.

1983-01-01

This study report defines a set of tests and measurements required to characterize the performance of a Large Space System (LSS), and to scale this data to other LSS satellites. Requirements from the Mobile Communication Satellite (MSAT) configurations derived in the parent study were used. MSAT utilizes a large, mesh deployable antenna, and encompasses a significant range of LSS technology issues in the areas of structural/dynamics, control, and performance predictability. In this study, performance requirements were developed for the antenna. Special emphasis was placed on antenna surface accuracy, and pointing stability. Instrumentation and measurement systems, applicable to LSS, were selected from existing or on-going technology developments. Laser ranging and angulation systems, presently in breadboard status, form the backbone of the measurements. Following this, a set of ground, STS, and GEO-operational were investigated. A third scale (15 meter) antenna system as selected for ground characterization followed by STS flight technology development. This selection ensures analytical scaling from ground-to-orbit, and size scaling. Other benefits are cost and ability to perform reasonable ground tests. Detail costing of the various tests and measurement systems were derived and are included in the report.

Copy of Using Emulation and Simulation to Understand the Large-Scale Behavior of the Internet.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adalsteinsson, Helgi; Armstrong, Robert C.; Chiang, Ken

2008-10-01

We report on the work done in the late-start LDRDUsing Emulation and Simulation toUnderstand the Large-Scale Behavior of the Internet. We describe the creation of a researchplatform that emulates many thousands of machines to be used for the study of large-scale inter-net behavior. We describe a proof-of-concept simple attack we performed in this environment.We describe the successful capture of a Storm bot and, from the study of the bot and furtherliterature search, establish large-scale aspects we seek to understand via emulation of Storm onour research platform in possible follow-on work. Finally, we discuss possible future work.3

Fire extinguishing tests -80 with methyl alcohol gasoline

NASA Astrophysics Data System (ADS)

Holmstedt, G.; Ryderman, A.; Carlsson, B.; Lennmalm, B.

1980-10-01

Large scale tests and laboratory experiments were carried out for estimating the extinguishing effectiveness of three alcohol resistant aqueous film forming foams (AFFF), two alcohol resistant fluoroprotein foams and two detergent foams in various poolfires: gasoline, isopropyl alcohol, acetone, methyl-ethyl ketone, methyl alcohol and M15 (a gasoline, methyl alcohol, isobutene mixture). The scaling down of large scale tests for developing a reliable laboratory method was especially examined. The tests were performed with semidirect foam application, in pools of 50, 11, 4, 0.6, and 0.25 sq m. Burning time, temperature distribution in the liquid, and thermal radiation were determined. An M15 fire can be extinguished with a detergent foam, but it is impossible to extinguish fires in polar solvents, such as methyl alcohol, acetone, and isopropyl alcohol with detergent foams, AFFF give the best results; and performances with small pools can hardly be correlated with results from large scale fires.

Spatial scale and distribution of neurovascular signals underlying decoding of orientation and eye of origin from fMRI data

PubMed Central

Harrison, Charlotte; Jackson, Jade; Oh, Seung-Mock; Zeringyte, Vaida

2016-01-01

Multivariate pattern analysis of functional magnetic resonance imaging (fMRI) data is widely used, yet the spatial scales and origin of neurovascular signals underlying such analyses remain unclear. We compared decoding performance for stimulus orientation and eye of origin from fMRI measurements in human visual cortex with predictions based on the columnar organization of each feature and estimated the spatial scales of patterns driving decoding. Both orientation and eye of origin could be decoded significantly above chance in early visual areas (V1–V3). Contrary to predictions based on a columnar origin of response biases, decoding performance for eye of origin in V2 and V3 was not significantly lower than that in V1, nor did decoding performance for orientation and eye of origin differ significantly. Instead, response biases for both features showed large-scale organization, evident as a radial bias for orientation, and a nasotemporal bias for eye preference. To determine whether these patterns could drive classification, we quantified the effect on classification performance of binning voxels according to visual field position. Consistent with large-scale biases driving classification, binning by polar angle yielded significantly better decoding performance for orientation than random binning in V1–V3. Similarly, binning by hemifield significantly improved decoding performance for eye of origin. Patterns of orientation and eye preference bias in V2 and V3 showed a substantial degree of spatial correlation with the corresponding patterns in V1, suggesting that response biases in these areas originate in V1. Together, these findings indicate that multivariate classification results need not reflect the underlying columnar organization of neuronal response selectivities in early visual areas. NEW & NOTEWORTHY Large-scale response biases can account for decoding of orientation and eye of origin in human early visual areas V1–V3. For eye of origin this pattern is a nasotemporal bias; for orientation it is a radial bias. Differences in decoding performance across areas and stimulus features are not well predicted by differences in columnar-scale organization of each feature. Large-scale biases in extrastriate areas are spatially correlated with those in V1, suggesting biases originate in primary visual cortex. PMID:27903637

Exploring the large-scale structure of Taylor–Couette turbulence through Large-Eddy Simulations

NASA Astrophysics Data System (ADS)

Ostilla-Mónico, Rodolfo; Zhu, Xiaojue; Verzicco, Roberto

2018-04-01

Large eddy simulations (LES) of Taylor-Couette (TC) flow, the flow between two co-axial and independently rotating cylinders are performed in an attempt to explore the large-scale axially-pinned structures seen in experiments and simulations. Both static and dynamic LES models are used. The Reynolds number is kept fixed at Re = 3.4 · 104, and the radius ratio η = ri /ro is set to η = 0.909, limiting the effects of curvature and resulting in frictional Reynolds numbers of around Re τ ≈ 500. Four rotation ratios from Rot = ‑0.0909 to Rot = 0.3 are simulated. First, the LES of TC is benchmarked for different rotation ratios. Both the Smagorinsky model with a constant of cs = 0.1 and the dynamic model are found to produce reasonable results for no mean rotation and cyclonic rotation, but deviations increase for increasing rotation. This is attributed to the increasing anisotropic character of the fluctuations. Second, “over-damped” LES, i.e. LES with a large Smagorinsky constant is performed and is shown to reproduce some features of the large-scale structures, even when the near-wall region is not adequately modeled. This shows the potential for using over-damped LES for fast explorations of the parameter space where large-scale structures are found.

Participation in International Large-Scale Assessments from a US Perspective

ERIC Educational Resources Information Center

Plisko, Valena White

2013-01-01

International large-scale assessments (ILSAs) play a distinct role in the United States' decentralized federal education system. Separate from national and state assessments, they offer an external, objective measure for the United States to assess student performance comparatively with other countries and over time. The US engagement in ILSAs…

Sensitivity analysis for large-scale problems

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.; Whitworth, Sandra L.

1987-01-01

The development of efficient techniques for calculating sensitivity derivatives is studied. The objective is to present a computational procedure for calculating sensitivity derivatives as part of performing structural reanalysis for large-scale problems. The scope is limited to framed type structures. Both linear static analysis and free-vibration eigenvalue problems are considered.

Science Competencies That Go Unassessed

ERIC Educational Resources Information Center

Gilmer, Penny J.; Sherdan, Danielle M.; Oosterhof, Albert; Rohani, Faranak; Rouby, Aaron

2011-01-01

Present large-scale assessments require the use of item formats, such as multiple choice, that can be administered and scored efficiently. This limits competencies that can be measured by these assessments. An alternative approach to large-scale assessments is being investigated that would include the use of complex performance assessments. As…

Towards Productive Critique of Large-Scale Comparisons in Education

ERIC Educational Resources Information Center

Gorur, Radhika

2017-01-01

International large-scale assessments and comparisons (ILSAs) in education have become significant policy phenomena. How a country fares in these assessments has come to signify not only how a nation's education system is performing, but also its future prospects in a global economic "race". These assessments provoke passionate arguments…

Survey on large scale system control methods

NASA Technical Reports Server (NTRS)

Mercadal, Mathieu

1987-01-01

The problem inherent to large scale systems such as power network, communication network and economic or ecological systems were studied. The increase in size and flexibility of future spacecraft has put those dynamical systems into the category of large scale systems, and tools specific to the class of large systems are being sought to design control systems that can guarantee more stability and better performance. Among several survey papers, reference was found to a thorough investigation on decentralized control methods. Especially helpful was the classification made of the different existing approaches to deal with large scale systems. A very similar classification is used, even though the papers surveyed are somehow different from the ones reviewed in other papers. Special attention is brought to the applicability of the existing methods to controlling large mechanical systems like large space structures. Some recent developments are added to this survey.

On the large eddy simulation of turbulent flows in complex geometry

NASA Technical Reports Server (NTRS)

Ghosal, Sandip

1993-01-01

Application of the method of Large Eddy Simulation (LES) to a turbulent flow consists of three separate steps. First, a filtering operation is performed on the Navier-Stokes equations to remove the small spatial scales. The resulting equations that describe the space time evolution of the 'large eddies' contain the subgrid-scale (sgs) stress tensor that describes the effect of the unresolved small scales on the resolved scales. The second step is the replacement of the sgs stress tensor by some expression involving the large scales - this is the problem of 'subgrid-scale modeling'. The final step is the numerical simulation of the resulting 'closed' equations for the large scale fields on a grid small enough to resolve the smallest of the large eddies, but still much larger than the fine scale structures at the Kolmogorov length. In dividing a turbulent flow field into 'large' and 'small' eddies, one presumes that a cut-off length delta can be sensibly chosen such that all fluctuations on a scale larger than delta are 'large eddies' and the remainder constitute the 'small scale' fluctuations. Typically, delta would be a length scale characterizing the smallest structures of interest in the flow. In an inhomogeneous flow, the 'sensible choice' for delta may vary significantly over the flow domain. For example, in a wall bounded turbulent flow, most statistical averages of interest vary much more rapidly with position near the wall than far away from it. Further, there are dynamically important organized structures near the wall on a scale much smaller than the boundary layer thickness. Therefore, the minimum size of eddies that need to be resolved is smaller near the wall. In general, for the LES of inhomogeneous flows, the width of the filtering kernel delta must be considered to be a function of position. If a filtering operation with a nonuniform filter width is performed on the Navier-Stokes equations, one does not in general get the standard large eddy equations. The complication is caused by the fact that a filtering operation with a nonuniform filter width in general does not commute with the operation of differentiation. This is one of the issues that we have looked at in detail as it is basic to any attempt at applying LES to complex geometry flows. Our principal findings are summarized.

A study on the required performance of a 2G HTS wire for HTS wind power generators

NASA Astrophysics Data System (ADS)

Sung, Hae-Jin; Park, Minwon; Go, Byeong-Soo; Yu, In-Keun

2016-05-01

YBCO or REBCO coated conductor (2G) materials are developed for their superior performance at high magnetic field and temperature. Power system applications based on high temperature superconducting (HTS) 2G wire technology are attracting attention, including large-scale wind power generators. In particular, to solve problems associated with the foundations and mechanical structure of offshore wind turbines, due to the large diameter and heavy weight of the generator, an HTS generator is suggested as one of the key technologies. Many researchers have tried to develop feasible large-scale HTS wind power generator technologies. In this paper, a study on the required performance of a 2G HTS wire for large-scale wind power generators is discussed. A 12 MW class large-scale wind turbine and an HTS generator are designed using 2G HTS wire. The total length of the 2G HTS wire for the 12 MW HTS generator is estimated, and the essential prerequisites of the 2G HTS wire based generator are described. The magnetic field distributions of a pole module are illustrated, and the mechanical stress and strain of the pole module are analysed. Finally, a reasonable price for 2G HTS wire for commercialization of the HTS generator is suggested, reflecting the results of electromagnetic and mechanical analyses of the generator.

Scalable Performance Measurement and Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gamblin, Todd

2009-01-01

Concurrency levels in large-scale, distributed-memory supercomputers are rising exponentially. Modern machines may contain 100,000 or more microprocessor cores, and the largest of these, IBM's Blue Gene/L, contains over 200,000 cores. Future systems are expected to support millions of concurrent tasks. In this dissertation, we focus on efficient techniques for measuring and analyzing the performance of applications running on very large parallel machines. Tuning the performance of large-scale applications can be a subtle and time-consuming task because application developers must measure and interpret data from many independent processes. While the volume of the raw data scales linearly with the number ofmore » tasks in the running system, the number of tasks is growing exponentially, and data for even small systems quickly becomes unmanageable. Transporting performance data from so many processes over a network can perturb application performance and make measurements inaccurate, and storing such data would require a prohibitive amount of space. Moreover, even if it were stored, analyzing the data would be extremely time-consuming. In this dissertation, we present novel methods for reducing performance data volume. The first draws on multi-scale wavelet techniques from signal processing to compress systemwide, time-varying load-balance data. The second uses statistical sampling to select a small subset of running processes to generate low-volume traces. A third approach combines sampling and wavelet compression to stratify performance data adaptively at run-time and to reduce further the cost of sampled tracing. We have integrated these approaches into Libra, a toolset for scalable load-balance analysis. We present Libra and show how it can be used to analyze data from large scientific applications scalably.« less

Approximate Computing Techniques for Iterative Graph Algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Panyala, Ajay R.; Subasi, Omer; Halappanavar, Mahantesh

Approximate computing enables processing of large-scale graphs by trading off quality for performance. Approximate computing techniques have become critical not only due to the emergence of parallel architectures but also the availability of large scale datasets enabling data-driven discovery. Using two prototypical graph algorithms, PageRank and community detection, we present several approximate computing heuristics to scale the performance with minimal loss of accuracy. We present several heuristics including loop perforation, data caching, incomplete graph coloring and synchronization, and evaluate their efficiency. We demonstrate performance improvements of up to 83% for PageRank and up to 450x for community detection, with lowmore » impact of accuracy for both the algorithms. We expect the proposed approximate techniques will enable scalable graph analytics on data of importance to several applications in science and their subsequent adoption to scale similar graph algorithms.« less

Scale Up of Malonic Acid Fermentation Process: Cooperative Research and Development Final Report, CRADA Number CRD-16-612

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schell, Daniel J

The goal of this work is to use the large fermentation vessels in the National Renewable Energy Laboratory's (NREL) Integrated Biorefinery Research Facility (IBRF) to scale-up Lygos' biological-based process for producing malonic acid and to generate performance data. Initially, work at the 1 L scale validated successful transfer of Lygos' fermentation protocols to NREL using a glucose substrate. Outside of the scope of the CRADA with NREL, Lygos tested their process on lignocellulosic sugars produced by NREL at Lawrence Berkeley National Laboratory's (LBNL) Advanced Biofuels Process Development Unit (ABPDU). NREL produced these cellulosic sugar solutions from corn stover using amore » separate cellulose/hemicellulose process configuration. Finally, NREL performed fermentations using glucose in large fermentors (1,500- and 9,000-L vessels) to intermediate product and to demonstrate successful performance of Lygos' technology at larger scales.« less

Study of LANDSAT-D thematic mapper performance as applied to hydrocarbon exploration

NASA Technical Reports Server (NTRS)

Everett, J. R. (Principal Investigator)

1983-01-01

Two fully processed test tapes were enhanced and evaluated at scales up to 1:10,000, using both hardcopy output and interactive screen display. A large scale, the Detroit, Michigan scene shows evidence of an along line data slip every sixteenth line in TM channel 2. Very large scale products generated in false color using channels 1,3, and 4 should be very acceptable for interpretation at scales up to 1:50,000 and useful for change mapping probably up to scale 1:24,000. Striping visible in water bodies for both natural and color products indicates that the detector calibration is probably performing below preflight specification. For a set of 512 x 512 windows within the NE Arkansas scene, the variance-covariance matrices were computed and principal component analyses performed. Initial analysis suggests that the shortwave infrared TM 5 and 6 channels are a highly significant data source. The thermal channel (TM 7) shows negative correlation with TM 1 and 4.

Multiresolution comparison of precipitation datasets for large-scale models

NASA Astrophysics Data System (ADS)

Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.

2014-12-01

Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.

Space transportation booster engine thrust chamber technology, large scale injector

NASA Technical Reports Server (NTRS)

Schneider, J. A.

1993-01-01

The objective of the Large Scale Injector (LSI) program was to deliver a 21 inch diameter, 600,000 lbf thrust class injector to NASA/MSFC for hot fire testing. The hot fire test program would demonstrate the feasibility and integrity of the full scale injector, including combustion stability, chamber wall compatibility (thermal management), and injector performance. The 21 inch diameter injector was delivered in September of 1991.

Quantitative analysis of voids in percolating structures in two-dimensional N-body simulations

NASA Technical Reports Server (NTRS)

Harrington, Patrick M.; Melott, Adrian L.; Shandarin, Sergei F.

1993-01-01

We present in this paper a quantitative method for defining void size in large-scale structure based on percolation threshold density. Beginning with two-dimensional gravitational clustering simulations smoothed to the threshold of nonlinearity, we perform percolation analysis to determine the large scale structure. The resulting objective definition of voids has a natural scaling property, is topologically interesting, and can be applied immediately to redshift surveys.

Sex differences in virtual navigation influenced by scale and navigation experience.

PubMed

Padilla, Lace M; Creem-Regehr, Sarah H; Stefanucci, Jeanine K; Cashdan, Elizabeth A

2017-04-01

The Morris water maze is a spatial abilities test adapted from the animal spatial cognition literature and has been studied in the context of sex differences in humans. This is because its standard design, which manipulates proximal (close) and distal (far) cues, applies to human navigation. However, virtual Morris water mazes test navigation skills on a scale that is vastly smaller than natural human navigation. Many researchers have argued that navigating in large and small scales is fundamentally different, and small-scale navigation might not simulate natural human navigation. Other work has suggested that navigation experience could influence spatial skills. To address the question of how individual differences influence navigational abilities in differently scaled environments, we employed both a large- (146.4 m in diameter) and a traditional- (36.6 m in diameter) scaled virtual Morris water maze along with a novel measure of navigation experience (lifetime mobility). We found sex differences on the small maze in the distal cue condition only, but in both cue-conditions on the large maze. Also, individual differences in navigation experience modulated navigation performance on the virtual water maze, showing that higher mobility was related to better performance with proximal cues for only females on the small maze, but for both males and females on the large maze.

Large-Scale, Three–Dimensional, Free–Standing, and Mesoporous Metal Oxide Networks for High–Performance Photocatalysis

PubMed Central

Bai, Hua; Li, Xinshi; Hu, Chao; Zhang, Xuan; Li, Junfang; Yan, Yan; Xi, Guangcheng

2013-01-01

Mesoporous nanostructures represent a unique class of photocatalysts with many applications, including splitting of water, degradation of organic contaminants, and reduction of carbon dioxide. In this work, we report a general Lewis acid catalytic template route for the high–yield producing single– and multi–component large–scale three–dimensional (3D) mesoporous metal oxide networks. The large-scale 3D mesoporous metal oxide networks possess large macroscopic scale (millimeter–sized) and mesoporous nanostructure with huge pore volume and large surface exposure area. This method also can be used for the synthesis of large–scale 3D macro/mesoporous hierarchical porous materials and noble metal nanoparticles loaded 3D mesoporous networks. Photocatalytic degradation of Azo dyes demonstrated that the large–scale 3D mesoporous metal oxide networks enable high photocatalytic activity. The present synthetic method can serve as the new design concept for functional 3D mesoporous nanomaterials. PMID:23857595

UAS in the NAS Project: Large-Scale Communication Architecture Simulations with NASA GRC Gen5 Radio Model

NASA Technical Reports Server (NTRS)

Kubat, Gregory

2016-01-01

This report provides a description and performance characterization of the large-scale, Relay architecture, UAS communications simulation capability developed for the NASA GRC, UAS in the NAS Project. The system uses a validated model of the GRC Gen5 CNPC, Flight-Test Radio model. Contained in the report is a description of the simulation system and its model components, recent changes made to the system to improve performance, descriptions and objectives of sample simulations used for test and verification, and a sampling and observations of results and performance data.

Field-aligned currents' scale analysis performed with the Swarm constellation

NASA Astrophysics Data System (ADS)

Lühr, Hermann; Park, Jaeheung; Gjerloev, Jesper W.; Rauberg, Jan; Michaelis, Ingo; Merayo, Jose M. G.; Brauer, Peter

2015-01-01

We present a statistical study of the temporal- and spatial-scale characteristics of different field-aligned current (FAC) types derived with the Swarm satellite formation. We divide FACs into two classes: small-scale, up to some 10 km, which are carried predominantly by kinetic Alfvén waves, and large-scale FACs with sizes of more than 150 km. For determining temporal variability we consider measurements at the same point, the orbital crossovers near the poles, but at different times. From correlation analysis we obtain a persistent period of small-scale FACs of order 10 s, while large-scale FACs can be regarded stationary for more than 60 s. For the first time we investigate the longitudinal scales. Large-scale FACs are different on dayside and nightside. On the nightside the longitudinal extension is on average 4 times the latitudinal width, while on the dayside, particularly in the cusp region, latitudinal and longitudinal scales are comparable.

Diagnostics of a large-scale irregularity in the electron density near the boundary of the radio transparency frequency range of the ionosphere

NASA Astrophysics Data System (ADS)

Afanasiev, N. T.; Markov, V. P.

2011-08-01

Approximate functional relationships for the calculation of a disturbed transionogram with a trace deformation caused by the influence of a large-scale irregularity in the electron density are obtained. Numerical and asymptotic modeling of disturbed transionograms at various positions of a spacecraft relative to a ground-based observation point is performed. A possibility of the determination of the intensity and dimensions of a single large-scale irregularity near the boundary of the radio transparency frequency range of the ionosphere is demonstrated.

Evaluation of the reliability and validity for X16 balance testing scale for the elderly.

PubMed

Ju, Jingjuan; Jiang, Yu; Zhou, Peng; Li, Lin; Ye, Xiaolei; Wu, Hongmei; Shen, Bin; Zhang, Jialei; He, Xiaoding; Niu, Chunjin; Xia, Qinghua

2018-05-10

Balance performance is considered as an indicator of functional status in the elderly, a large scale population screening and evaluation in the community context followed by proper interventions would be of great significance at public health level. However, there has been no suitable balance testing scale available for large scale studies in the unique community context of urban China. A balance scale named X16 balance testing scale was developed, which was composed of 3 domains and 16 items. A total of 1985 functionally independent and active community-dwelling elderly adults' balance abilities were tested using the X16 scale. The internal consistency, split-half reliability, content validity, construct validity, discriminant validity of X16 balance testing scale were evaluated. Factor analysis was performed to identify alternative factor structure. The Eigenvalues of factors 1, 2, and 3 were 8.53, 1.79, and 1.21, respectively, and their cumulative contribution to the total variance reached 72.0%. These 3 factors mainly represented domains static balance, postural stability, and dynamic balance. The Cronbach alpha coefficient for the scale was 0.933. The Spearman correlation coefficients between items and its corresponding domains were ranged from 0.538 to 0.964. The correlation coefficients between each item and its corresponding domain were higher than the coefficients between this item and other domains. With the increase of age, the scores of balance performance, domains static balance, postural stability, and dynamic balance in the elderly declined gradually (P < 0.001). With the increase of age, the proportion of the elderly with intact balance performance decreased gradually (P < 0.001). The reliability and validity of the X16 balance testing scale is both adequate and acceptable. Due to its simple and quick use features, it is practical to be used repeatedly and routinely especially in community setting and on large scale screening.

A Ranking Approach on Large-Scale Graph With Multidimensional Heterogeneous Information.

PubMed

Wei, Wei; Gao, Bin; Liu, Tie-Yan; Wang, Taifeng; Li, Guohui; Li, Hang

2016-04-01

Graph-based ranking has been extensively studied and frequently applied in many applications, such as webpage ranking. It aims at mining potentially valuable information from the raw graph-structured data. Recently, with the proliferation of rich heterogeneous information (e.g., node/edge features and prior knowledge) available in many real-world graphs, how to effectively and efficiently leverage all information to improve the ranking performance becomes a new challenging problem. Previous methods only utilize part of such information and attempt to rank graph nodes according to link-based methods, of which the ranking performances are severely affected by several well-known issues, e.g., over-fitting or high computational complexity, especially when the scale of graph is very large. In this paper, we address the large-scale graph-based ranking problem and focus on how to effectively exploit rich heterogeneous information of the graph to improve the ranking performance. Specifically, we propose an innovative and effective semi-supervised PageRank (SSP) approach to parameterize the derived information within a unified semi-supervised learning framework (SSLF-GR), then simultaneously optimize the parameters and the ranking scores of graph nodes. Experiments on the real-world large-scale graphs demonstrate that our method significantly outperforms the algorithms that consider such graph information only partially.

Contribution of peculiar shear motions to large-scale structure

NASA Technical Reports Server (NTRS)

Mueler, Hans-Reinhard; Treumann, Rudolf A.

1994-01-01

Self-gravitating shear flow instability simulations in a cold dark matter-dominated expanding Einstein-de Sitter universe have been performed. When the shear flow speed exceeds a certain threshold, self-gravitating Kelvin-Helmoholtz instability occurs, forming density voids and excesses along the shear flow layer which serve as seeds for large-scale structure formation. A possible mechanism for generating shear peculiar motions are velocity fluctuations induced by the density perturbations of the postinflation era. In this scenario, short scales grow earlier than large scales. A model of this kind may contribute to the cellular structure of the luminous mass distribution in the universe.

Asynchronous Two-Level Checkpointing Scheme for Large-Scale Adjoints in the Spectral-Element Solver Nek5000

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schanen, Michel; Marin, Oana; Zhang, Hong

Adjoints are an important computational tool for large-scale sensitivity evaluation, uncertainty quantification, and derivative-based optimization. An essential component of their performance is the storage/recomputation balance in which efficient checkpointing methods play a key role. We introduce a novel asynchronous two-level adjoint checkpointing scheme for multistep numerical time discretizations targeted at large-scale numerical simulations. The checkpointing scheme combines bandwidth-limited disk checkpointing and binomial memory checkpointing. Based on assumptions about the target petascale systems, which we later demonstrate to be realistic on the IBM Blue Gene/Q system Mira, we create a model of the expected performance of our checkpointing approach and validatemore » it using the highly scalable Navier-Stokes spectralelement solver Nek5000 on small to moderate subsystems of the Mira supercomputer. In turn, this allows us to predict optimal algorithmic choices when using all of Mira. We also demonstrate that two-level checkpointing is significantly superior to single-level checkpointing when adjoining a large number of time integration steps. To our knowledge, this is the first time two-level checkpointing had been designed, implemented, tuned, and demonstrated on fluid dynamics codes at large scale of 50k+ cores.« less

An efficient implementation of 3D high-resolution imaging for large-scale seismic data with GPU/CPU heterogeneous parallel computing

NASA Astrophysics Data System (ADS)

Xu, Jincheng; Liu, Wei; Wang, Jin; Liu, Linong; Zhang, Jianfeng

2018-02-01

De-absorption pre-stack time migration (QPSTM) compensates for the absorption and dispersion of seismic waves by introducing an effective Q parameter, thereby making it an effective tool for 3D, high-resolution imaging of seismic data. Although the optimal aperture obtained via stationary-phase migration reduces the computational cost of 3D QPSTM and yields 3D stationary-phase QPSTM, the associated computational efficiency is still the main problem in the processing of 3D, high-resolution images for real large-scale seismic data. In the current paper, we proposed a division method for large-scale, 3D seismic data to optimize the performance of stationary-phase QPSTM on clusters of graphics processing units (GPU). Then, we designed an imaging point parallel strategy to achieve an optimal parallel computing performance. Afterward, we adopted an asynchronous double buffering scheme for multi-stream to perform the GPU/CPU parallel computing. Moreover, several key optimization strategies of computation and storage based on the compute unified device architecture (CUDA) were adopted to accelerate the 3D stationary-phase QPSTM algorithm. Compared with the initial GPU code, the implementation of the key optimization steps, including thread optimization, shared memory optimization, register optimization and special function units (SFU), greatly improved the efficiency. A numerical example employing real large-scale, 3D seismic data showed that our scheme is nearly 80 times faster than the CPU-QPSTM algorithm. Our GPU/CPU heterogeneous parallel computing framework significant reduces the computational cost and facilitates 3D high-resolution imaging for large-scale seismic data.

The Role of Reading Comprehension in Large-Scale Subject-Matter Assessments

ERIC Educational Resources Information Center

Zhang, Ting

2013-01-01

This study was designed with the overall goal of understanding how difficulties in reading comprehension are associated with early adolescents' performance in large-scale assessments in subject domains including science and civic-related social studies. The current study extended previous research by taking a cognition-centered approach based on…

Architecture and Programming Models for High Performance Intensive Computation

DTIC Science & Technology

2016-06-29

Applications Systems and Large-Scale-Big-Data & Large-Scale-Big-Computing (DDDAS- LS ). ICCS 2015, June 2015. Reykjavk, Ice- land. 2. Bo YT, Wang P, Guo ZL...The Mahali project,” Communications Magazine , vol. 52, pp. 111–133, Aug 2014. 14 DISTRIBUTION A: Distribution approved for public release. Response ID

Cohort Profile of the Goals Study: A Large-Scale Research of Physical Activity in Dutch Students

ERIC Educational Resources Information Center

de Groot, Renate H. M.; van Dijk, Martin L.; Kirschner, Paul A.

2015-01-01

The GOALS study (Grootschalig Onderzoek naar Activiteiten van Limburgse Scholieren [Large-scale Research of Activities in Dutch Students]) was set up to investigate possible associations between different forms of physical activity and inactivity with cognitive performance, academic achievement and mental well-being. It was conducted at a…

The Application of Large-Scale Hypermedia Information Systems to Training.

ERIC Educational Resources Information Center

Crowder, Richard; And Others

1995-01-01

Discusses the use of hypermedia in electronic information systems that support maintenance operations in large-scale industrial plants. Findings show that after establishing an information system, the same resource base can be used to train personnel how to use the computer system and how to perform operational and maintenance tasks. (Author/JMV)

Dynamics of the McDonnell Douglas Large Scale Dynamic Rig and Dynamic Calibration of the Rotor Balance

DOT National Transportation Integrated Search

1994-10-01

A shake test was performed on the Large Scale Dynamic Rig in the 40- by 80-Foot Wind Tunnel in support of the McDonnell Douglas Advanced Rotor Technology (MDART) Test Program. The shake test identifies the hub modes and the dynamic calibration matrix...

A Parallel Sliding Region Algorithm to Make Agent-Based Modeling Possible for a Large-Scale Simulation: Modeling Hepatitis C Epidemics in Canada.

PubMed

Wong, William W L; Feng, Zeny Z; Thein, Hla-Hla

2016-11-01

Agent-based models (ABMs) are computer simulation models that define interactions among agents and simulate emergent behaviors that arise from the ensemble of local decisions. ABMs have been increasingly used to examine trends in infectious disease epidemiology. However, the main limitation of ABMs is the high computational cost for a large-scale simulation. To improve the computational efficiency for large-scale ABM simulations, we built a parallelizable sliding region algorithm (SRA) for ABM and compared it to a nonparallelizable ABM. We developed a complex agent network and performed two simulations to model hepatitis C epidemics based on the real demographic data from Saskatchewan, Canada. The first simulation used the SRA that processed on each postal code subregion subsequently. The second simulation processed the entire population simultaneously. It was concluded that the parallelizable SRA showed computational time saving with comparable results in a province-wide simulation. Using the same method, SRA can be generalized for performing a country-wide simulation. Thus, this parallel algorithm enables the possibility of using ABM for large-scale simulation with limited computational resources.

Large-scale retrieval for medical image analytics: A comprehensive review.

PubMed

Li, Zhongyu; Zhang, Xiaofan; Müller, Henning; Zhang, Shaoting

2018-01-01

Over the past decades, medical image analytics was greatly facilitated by the explosion of digital imaging techniques, where huge amounts of medical images were produced with ever-increasing quality and diversity. However, conventional methods for analyzing medical images have achieved limited success, as they are not capable to tackle the huge amount of image data. In this paper, we review state-of-the-art approaches for large-scale medical image analysis, which are mainly based on recent advances in computer vision, machine learning and information retrieval. Specifically, we first present the general pipeline of large-scale retrieval, summarize the challenges/opportunities of medical image analytics on a large-scale. Then, we provide a comprehensive review of algorithms and techniques relevant to major processes in the pipeline, including feature representation, feature indexing, searching, etc. On the basis of existing work, we introduce the evaluation protocols and multiple applications of large-scale medical image retrieval, with a variety of exploratory and diagnostic scenarios. Finally, we discuss future directions of large-scale retrieval, which can further improve the performance of medical image analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Experimental feasibility study of the application of magnetic suspension techniques to large-scale aerodynamic test facilities

NASA Technical Reports Server (NTRS)

Zapata, R. N.; Humphris, R. R.; Henderson, K. C.

1974-01-01

Based on the premises that (1) magnetic suspension techniques can play a useful role in large-scale aerodynamic testing and (2) superconductor technology offers the only practical hope for building large-scale magnetic suspensions, an all-superconductor three-component magnetic suspension and balance facility was built as a prototype and was tested successfully. Quantitative extrapolations of design and performance characteristics of this prototype system to larger systems compatible with existing and planned high Reynolds number facilities have been made and show that this experimental technique should be particularly attractive when used in conjunction with large cryogenic wind tunnels.

Solutions of large-scale electromagnetics problems involving dielectric objects with the parallel multilevel fast multipole algorithm.

PubMed

Ergül, Özgür

2011-11-01

Fast and accurate solutions of large-scale electromagnetics problems involving homogeneous dielectric objects are considered. Problems are formulated with the electric and magnetic current combined-field integral equation and discretized with the Rao-Wilton-Glisson functions. Solutions are performed iteratively by using the multilevel fast multipole algorithm (MLFMA). For the solution of large-scale problems discretized with millions of unknowns, MLFMA is parallelized on distributed-memory architectures using a rigorous technique, namely, the hierarchical partitioning strategy. Efficiency and accuracy of the developed implementation are demonstrated on very large problems involving as many as 100 million unknowns.

Experimental feasibility study of the application of magnetic suspension techniques to large-scale aerodynamic test facilities. [cryogenic traonics wind tunnel

NASA Technical Reports Server (NTRS)

Zapata, R. N.; Humphris, R. R.; Henderson, K. C.

1975-01-01

Based on the premises that magnetic suspension techniques can play a useful role in large scale aerodynamic testing, and that superconductor technology offers the only practical hope for building large scale magnetic suspensions, an all-superconductor 3-component magnetic suspension and balance facility was built as a prototype and tested sucessfully. Quantitative extrapolations of design and performance characteristics of this prototype system to larger systems compatible with existing and planned high Reynolds number facilities at Langley Research Center were made and show that this experimental technique should be particularly attractive when used in conjunction with large cryogenic wind tunnels.

Exploring Cloud Computing for Large-scale Scientific Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Guang; Han, Binh; Yin, Jian

This paper explores cloud computing for large-scale data-intensive scientific applications. Cloud computing is attractive because it provides hardware and software resources on-demand, which relieves the burden of acquiring and maintaining a huge amount of resources that may be used only once by a scientific application. However, unlike typical commercial applications that often just requires a moderate amount of ordinary resources, large-scale scientific applications often need to process enormous amount of data in the terabyte or even petabyte range and require special high performance hardware with low latency connections to complete computation in a reasonable amount of time. To address thesemore » challenges, we build an infrastructure that can dynamically select high performance computing hardware across institutions and dynamically adapt the computation to the selected resources to achieve high performance. We have also demonstrated the effectiveness of our infrastructure by building a system biology application and an uncertainty quantification application for carbon sequestration, which can efficiently utilize data and computation resources across several institutions.« less

Design Sketches For Optical Crossbar Switches Intended For Large-Scale Parallel Processing Applications

NASA Astrophysics Data System (ADS)

Hartmann, Alfred; Redfield, Steve

1989-04-01

This paper discusses design of large-scale (1000x 1000) optical crossbar switching networks for use in parallel processing supercom-puters. Alternative design sketches for an optical crossbar switching network are presented using free-space optical transmission with either a beam spreading/masking model or a beam steering model for internodal communications. The performances of alternative multiple access channel communications protocol-unslotted and slotted ALOHA and carrier sense multiple access (CSMA)-are compared with the performance of the classic arbitrated bus crossbar of conventional electronic parallel computing. These comparisons indicate an almost inverse relationship between ease of implementation and speed of operation. Practical issues of optical system design are addressed, and an optically addressed, composite spatial light modulator design is presented for fabrication to arbitrarily large scale. The wide range of switch architecture, communications protocol, optical systems design, device fabrication, and system performance problems presented by these design sketches poses a serious challenge to practical exploitation of highly parallel optical interconnects in advanced computer designs.

Accelerating large-scale simulation of seismic wave propagation by multi-GPUs and three-dimensional domain decomposition

NASA Astrophysics Data System (ADS)

Okamoto, Taro; Takenaka, Hiroshi; Nakamura, Takeshi; Aoki, Takayuki

2010-12-01

We adopted the GPU (graphics processing unit) to accelerate the large-scale finite-difference simulation of seismic wave propagation. The simulation can benefit from the high-memory bandwidth of GPU because it is a "memory intensive" problem. In a single-GPU case we achieved a performance of about 56 GFlops, which was about 45-fold faster than that achieved by a single core of the host central processing unit (CPU). We confirmed that the optimized use of fast shared memory and registers were essential for performance. In the multi-GPU case with three-dimensional domain decomposition, the non-contiguous memory alignment in the ghost zones was found to impose quite long time in data transfer between GPU and the host node. This problem was solved by using contiguous memory buffers for ghost zones. We achieved a performance of about 2.2 TFlops by using 120 GPUs and 330 GB of total memory: nearly (or more than) 2200 cores of host CPUs would be required to achieve the same performance. The weak scaling was nearly proportional to the number of GPUs. We therefore conclude that GPU computing for large-scale simulation of seismic wave propagation is a promising approach as a faster simulation is possible with reduced computational resources compared to CPUs.

Scale interaction and arrangement in a turbulent boundary layer perturbed by a wall-mounted cylindrical element

NASA Astrophysics Data System (ADS)

Tang, Zhanqi; Jiang, Nan

2018-05-01

This study reports the modifications of scale interaction and arrangement in a turbulent boundary layer perturbed by a wall-mounted circular cylinder. Hot-wire measurements were executed at multiple streamwise and wall-normal wise locations downstream of the cylindrical element. The streamwise fluctuating signals were decomposed into large-, small-, and dissipative-scale signatures by corresponding cutoff filters. The scale interaction under the cylindrical perturbation was elaborated by comparing the small- and dissipative-scale amplitude/frequency modulation effects downstream of the cylinder element with the results observed in the unperturbed case. It was obtained that the large-scale fluctuations perform a stronger amplitude modulation on both the small and dissipative scales in the near-wall region. At the wall-normal positions of the cylinder height, the small-scale amplitude modulation coefficients are redistributed by the cylinder wake. The similar observation was noted in small-scale frequency modulation; however, the dissipative-scale frequency modulation seems to be independent of the cylindrical perturbation. The phase-relationship observation indicated that the cylindrical perturbation shortens the time shifts between both the small- and dissipative-scale variations (amplitude and frequency) and large-scale fluctuations. Then, the integral time scale dependence of the phase-relationship between the small/dissipative scales and large scales was also discussed. Furthermore, the discrepancy of small- and dissipative-scale time shifts relative to the large-scale motions was examined, which indicates that the small-scale amplitude/frequency leads the dissipative scales.

Enabling Diverse Software Stacks on Supercomputers using High Performance Virtual Clusters.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Younge, Andrew J.; Pedretti, Kevin; Grant, Ryan

While large-scale simulations have been the hallmark of the High Performance Computing (HPC) community for decades, Large Scale Data Analytics (LSDA) workloads are gaining attention within the scientific community not only as a processing component to large HPC simulations, but also as standalone scientific tools for knowledge discovery. With the path towards Exascale, new HPC runtime systems are also emerging in a way that differs from classical distributed com- puting models. However, system software for such capabilities on the latest extreme-scale DOE supercomputing needs to be enhanced to more appropriately support these types of emerging soft- ware ecosystems. In thismore » paper, we propose the use of Virtual Clusters on advanced supercomputing resources to enable systems to support not only HPC workloads, but also emerging big data stacks. Specifi- cally, we have deployed the KVM hypervisor within Cray's Compute Node Linux on a XC-series supercomputer testbed. We also use libvirt and QEMU to manage and provision VMs directly on compute nodes, leveraging Ethernet-over-Aries network emulation. To our knowledge, this is the first known use of KVM on a true MPP supercomputer. We investigate the overhead our solution using HPC benchmarks, both evaluating single-node performance as well as weak scaling of a 32-node virtual cluster. Overall, we find single node performance of our solution using KVM on a Cray is very efficient with near-native performance. However overhead increases by up to 20% as virtual cluster size increases, due to limitations of the Ethernet-over-Aries bridged network. Furthermore, we deploy Apache Spark with large data analysis workloads in a Virtual Cluster, ef- fectively demonstrating how diverse software ecosystems can be supported by High Performance Virtual Clusters.« less

Outlook and Challenges of Perovskite Solar Cells toward Terawatt-Scale Photovoltaic Module Technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Kai; Kim, Donghoe; Whitaker, James B

Rapid development of perovskite solar cells (PSCs) during the past several years has made this photovoltaic (PV) technology a serious contender for potential large-scale deployment on the terawatt scale in the PV market. To successfully transition PSC technology from the laboratory to industry scale, substantial efforts need to focus on scalable fabrication of high-performance perovskite modules with minimum negative environmental impact. Here, we provide an overview of the current research and our perspective regarding PSC technology toward future large-scale manufacturing and deployment. Several key challenges discussed are (1) a scalable process for large-area perovskite module fabrication; (2) less hazardous chemicalmore » routes for PSC fabrication; and (3) suitable perovskite module designs for different applications.« less

High-Stakes Accountability: Student Anxiety and Large-Scale Testing

ERIC Educational Resources Information Center

von der Embse, Nathaniel P.; Witmer, Sara E.

2014-01-01

This study examined the relationship between student anxiety about high-stakes testing and their subsequent test performance. The FRIEDBEN Test Anxiety Scale was administered to 1,134 11th-grade students, and data were subsequently collected on their statewide assessment performance. Test anxiety was a significant predictor of test performance…

An evaluation of multi-probe locality sensitive hashing for computing similarities over web-scale query logs.

PubMed

Cormode, Graham; Dasgupta, Anirban; Goyal, Amit; Lee, Chi Hoon

2018-01-01

Many modern applications of AI such as web search, mobile browsing, image processing, and natural language processing rely on finding similar items from a large database of complex objects. Due to the very large scale of data involved (e.g., users' queries from commercial search engines), computing such near or nearest neighbors is a non-trivial task, as the computational cost grows significantly with the number of items. To address this challenge, we adopt Locality Sensitive Hashing (a.k.a, LSH) methods and evaluate four variants in a distributed computing environment (specifically, Hadoop). We identify several optimizations which improve performance, suitable for deployment in very large scale settings. The experimental results demonstrate our variants of LSH achieve the robust performance with better recall compared with "vanilla" LSH, even when using the same amount of space.

Fire extinguishing tests -80 with methyl alcohol gasoline (in MIXED)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Holmstedt, G.; Ryderman, A.; Carlsson, B.

1980-01-01

Large scale tests and laboratory experiments were carried out for estimating the extinguishing effectiveness of three alcohol resistant aqueous film forming foams (AFFF), two alcohol resistant fluoroprotein foams and two detergent foams in various poolfires: gasoline, isopropyl alcohol, acetone, methyl-ethyl ketone, methyl alcohol and M15 (a gasoline, methyl alcohol, isobutene mixture). The scaling down of large scale tests for developing a reliable laboratory method was especially examined. The tests were performed with semidirect foam application, in pools of 50, 11, 4, 0.6, and 0.25 sq m. Burning time, temperature distribution in the liquid, and thermal radiation were determined. An M15more » fire can be extinguished with a detergent foam, but it is impossible to extinguish fires in polar solvents, such as methyl alcohol, acetone, and isopropyl alcohol with detergent foams, AFFF give the best results, and performances with small pools can hardly be correlated with results from large scale fires.« less

Investigating the Potential of Deep Neural Networks for Large-Scale Classification of Very High Resolution Satellite Images

NASA Astrophysics Data System (ADS)

Postadjian, T.; Le Bris, A.; Sahbi, H.; Mallet, C.

2017-05-01

Semantic classification is a core remote sensing task as it provides the fundamental input for land-cover map generation. The very recent literature has shown the superior performance of deep convolutional neural networks (DCNN) for many classification tasks including the automatic analysis of Very High Spatial Resolution (VHR) geospatial images. Most of the recent initiatives have focused on very high discrimination capacity combined with accurate object boundary retrieval. Therefore, current architectures are perfectly tailored for urban areas over restricted areas but not designed for large-scale purposes. This paper presents an end-to-end automatic processing chain, based on DCNNs, that aims at performing large-scale classification of VHR satellite images (here SPOT 6/7). Since this work assesses, through various experiments, the potential of DCNNs for country-scale VHR land-cover map generation, a simple yet effective architecture is proposed, efficiently discriminating the main classes of interest (namely buildings, roads, water, crops, vegetated areas) by exploiting existing VHR land-cover maps for training.

Compromising genetic diversity in the wild: Unmonitored large-scale release of plants and animals

Treesearch

Linda Laikre; Michael K. Schwartz; Robin S. Waples; Nils Ryman; F. W. Allendorf; C. S. Baker; D. P. Gregovich; M. M. Hansen; J. A. Jackson; K. C. Kendall; K. McKelvey; M. C. Neel; I. Olivieri; R. Short Bull; J. B. Stetz; D. A. Tallmon; C. D. Vojta; D. M. Waller

2010-01-01

Large-scale exploitation of wild animals and plants through fishing, hunting and logging often depends on augmentation through releases of translocated or captively raised individuals. Such releases are performed worldwide in vast numbers. Augmentation can be demographically and economically beneficial but can also cause four types of adverse genetic change to wild...

Large-Scale Investigation of the Role of Trait Activation Theory for Understanding Assessment Center Convergent and Discriminant Validity

ERIC Educational Resources Information Center

Lievens, Filip; Chasteen, Christopher S.; Day, Eric Anthony; Christiansen, Neil D.

2006-01-01

This study used trait activation theory as a theoretical framework to conduct a large-scale test of the interactionist explanation of the convergent and discriminant validity findings obtained in assessment centers. Trait activation theory specifies the conditions in which cross-situationally consistent and inconsistent candidate performances are…

A novel artificial fish swarm algorithm for solving large-scale reliability-redundancy application problem.

PubMed

He, Qiang; Hu, Xiangtao; Ren, Hong; Zhang, Hongqi

2015-11-01

A novel artificial fish swarm algorithm (NAFSA) is proposed for solving large-scale reliability-redundancy allocation problem (RAP). In NAFSA, the social behaviors of fish swarm are classified in three ways: foraging behavior, reproductive behavior, and random behavior. The foraging behavior designs two position-updating strategies. And, the selection and crossover operators are applied to define the reproductive ability of an artificial fish. For the random behavior, which is essentially a mutation strategy, the basic cloud generator is used as the mutation operator. Finally, numerical results of four benchmark problems and a large-scale RAP are reported and compared. NAFSA shows good performance in terms of computational accuracy and computational efficiency for large scale RAP. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Construction of large scale switch matrix by interconnecting integrated optical switch chips with EDFAs

NASA Astrophysics Data System (ADS)

Liao, Mingle; Wu, Baojian; Hou, Jianhong; Qiu, Kun

2018-03-01

Large scale optical switches are essential components in optical communication network. We aim to build up a large scale optical switch matrix by the interconnection of silicon-based optical switch chips using 3-stage CLOS structure, where EDFAs are needed to compensate for the insertion loss of the chips. The optical signal-to-noise ratio (OSNR) performance of the resulting large scale optical switch matrix is investigated for TE-mode light and the experimental results are in agreement with the theoretical analysis. We build up a 64 ×64 switch matrix by use of 16 ×16 optical switch chips and the OSNR and receiver sensibility can respectively be improved by 0.6 dB and 0.2 dB by optimizing the gain configuration of the EDFAs.

A Hybrid, Large-Scale Wireless Sensor Network for Real-Time Acquisition and Tracking

DTIC Science & Technology

2007-06-01

multicolor, Quantum Well Infrared Photodetector ( QWIP ), step-stare, large-format Focal Plane Array (FPA) is proposed and evaluated through performance...Photodetector ( QWIP ), step-stare, large-format Focal Plane Array (FPA) is proposed and evaluated through performance analysis. The thesis proposes...7 1. Multi-color IR Sensors - Operational Advantages ...........................8 2. Quantum-Well IR Photodetector ( QWIP

Ice Accretion Test Results for Three Large-Scale Swept-Wing Models in the NASA Icing Research Tunnel

NASA Technical Reports Server (NTRS)

Broeren, Andy; Potapczuk, Mark; Lee, Sam; Malone, Adam; Paul, Ben; Woodard, Brian

2016-01-01

The design and certification of modern transport airplanes for flight in icing conditions increasing relies on three-dimensional numerical simulation tools for ice accretion prediction. There is currently no publically available, high-quality, ice accretion database upon which to evaluate the performance of icing simulation tools for large-scale swept wings that are representative of modern commercial transport airplanes. The purpose of this presentation is to present the results of a series of icing wind tunnel test campaigns whose aim was to provide an ice accretion database for large-scale, swept wings.

COLAcode: COmoving Lagrangian Acceleration code

NASA Astrophysics Data System (ADS)

Tassev, Svetlin V.

2016-02-01

COLAcode is a serial particle mesh-based N-body code illustrating the COLA (COmoving Lagrangian Acceleration) method; it solves for Large Scale Structure (LSS) in a frame that is comoving with observers following trajectories calculated in Lagrangian Perturbation Theory (LPT). It differs from standard N-body code by trading accuracy at small-scales to gain computational speed without sacrificing accuracy at large scales. This is useful for generating large ensembles of accurate mock halo catalogs required to study galaxy clustering and weak lensing; such catalogs are needed to perform detailed error analysis for ongoing and future surveys of LSS.

Performance of an MPI-only semiconductor device simulator on a quad socket/quad core InfiniBand platform.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shadid, John Nicolas; Lin, Paul Tinphone

2009-01-01

This preliminary study considers the scaling and performance of a finite element (FE) semiconductor device simulator on a capacity cluster with 272 compute nodes based on a homogeneous multicore node architecture utilizing 16 cores. The inter-node communication backbone for this Tri-Lab Linux Capacity Cluster (TLCC) machine is comprised of an InfiniBand interconnect. The nonuniform memory access (NUMA) nodes consist of 2.2 GHz quad socket/quad core AMD Opteron processors. The performance results for this study are obtained with a FE semiconductor device simulation code (Charon) that is based on a fully-coupled Newton-Krylov solver with domain decomposition and multilevel preconditioners. Scaling andmore » multicore performance results are presented for large-scale problems of 100+ million unknowns on up to 4096 cores. A parallel scaling comparison is also presented with the Cray XT3/4 Red Storm capability platform. The results indicate that an MPI-only programming model for utilizing the multicore nodes is reasonably efficient on all 16 cores per compute node. However, the results also indicated that the multilevel preconditioner, which is critical for large-scale capability type simulations, scales better on the Red Storm machine than the TLCC machine.« less

A comparative study of all-vanadium and iron-chromium redox flow batteries for large-scale energy storage

NASA Astrophysics Data System (ADS)

Zeng, Y. K.; Zhao, T. S.; An, L.; Zhou, X. L.; Wei, L.

2015-12-01

The promise of redox flow batteries (RFBs) utilizing soluble redox couples, such as all vanadium ions as well as iron and chromium ions, is becoming increasingly recognized for large-scale energy storage of renewables such as wind and solar, owing to their unique advantages including scalability, intrinsic safety, and long cycle life. An ongoing question associated with these two RFBs is determining whether the vanadium redox flow battery (VRFB) or iron-chromium redox flow battery (ICRFB) is more suitable and competitive for large-scale energy storage. To address this concern, a comparative study has been conducted for the two types of battery based on their charge-discharge performance, cycle performance, and capital cost. It is found that: i) the two batteries have similar energy efficiencies at high current densities; ii) the ICRFB exhibits a higher capacity decay rate than does the VRFB; and iii) the ICRFB is much less expensive in capital costs when operated at high power densities or at large capacities.

Efficient parallelization of analytic bond-order potentials for large-scale atomistic simulations

NASA Astrophysics Data System (ADS)

Teijeiro, C.; Hammerschmidt, T.; Drautz, R.; Sutmann, G.

2016-07-01

Analytic bond-order potentials (BOPs) provide a way to compute atomistic properties with controllable accuracy. For large-scale computations of heterogeneous compounds at the atomistic level, both the computational efficiency and memory demand of BOP implementations have to be optimized. Since the evaluation of BOPs is a local operation within a finite environment, the parallelization concepts known from short-range interacting particle simulations can be applied to improve the performance of these simulations. In this work, several efficient parallelization methods for BOPs that use three-dimensional domain decomposition schemes are described. The schemes are implemented into the bond-order potential code BOPfox, and their performance is measured in a series of benchmarks. Systems of up to several millions of atoms are simulated on a high performance computing system, and parallel scaling is demonstrated for up to thousands of processors.

Large-scale derived flood frequency analysis based on continuous simulation

NASA Astrophysics Data System (ADS)

Dung Nguyen, Viet; Hundecha, Yeshewatesfa; Guse, Björn; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

There is an increasing need for spatially consistent flood risk assessments at the regional scale (several 100.000 km2), in particular in the insurance industry and for national risk reduction strategies. However, most large-scale flood risk assessments are composed of smaller-scale assessments and show spatial inconsistencies. To overcome this deficit, a large-scale flood model composed of a weather generator and catchments models was developed reflecting the spatially inherent heterogeneity. The weather generator is a multisite and multivariate stochastic model capable of generating synthetic meteorological fields (precipitation, temperature, etc.) at daily resolution for the regional scale. These fields respect the observed autocorrelation, spatial correlation and co-variance between the variables. They are used as input into catchment models. A long-term simulation of this combined system enables to derive very long discharge series at many catchment locations serving as a basic for spatially consistent flood risk estimates at the regional scale. This combined model was set up and validated for major river catchments in Germany. The weather generator was trained by 53-year observation data at 528 stations covering not only the complete Germany but also parts of France, Switzerland, Czech Republic and Australia with the aggregated spatial scale of 443,931 km2. 10.000 years of daily meteorological fields for the study area were generated. Likewise, rainfall-runoff simulations with SWIM were performed for the entire Elbe, Rhine, Weser, Donau and Ems catchments. The validation results illustrate a good performance of the combined system, as the simulated flood magnitudes and frequencies agree well with the observed flood data. Based on continuous simulation this model chain is then used to estimate flood quantiles for the whole Germany including upstream headwater catchments in neighbouring countries. This continuous large scale approach overcomes the several drawbacks reported in traditional approaches for the derived flood frequency analysis and therefore is recommended for large scale flood risk case studies.

Topological Properties of Some Integrated Circuits for Very Large Scale Integration Chip Designs

NASA Astrophysics Data System (ADS)

Swanson, S.; Lanzerotti, M.; Vernizzi, G.; Kujawski, J.; Weatherwax, A.

2015-03-01

This talk presents topological properties of integrated circuits for Very Large Scale Integration chip designs. These circuits can be implemented in very large scale integrated circuits, such as those in high performance microprocessors. Prior work considered basic combinational logic functions and produced a mathematical framework based on algebraic topology for integrated circuits composed of logic gates. Prior work also produced an historically-equivalent interpretation of Mr. E. F. Rent's work for today's complex circuitry in modern high performance microprocessors, where a heuristic linear relationship was observed between the number of connections and number of logic gates. This talk will examine topological properties and connectivity of more complex functionally-equivalent integrated circuits. The views expressed in this article are those of the author and do not reflect the official policy or position of the United States Air Force, Department of Defense or the U.S. Government.

A novel iron-lead redox flow battery for large-scale energy storage

NASA Astrophysics Data System (ADS)

Zeng, Y. K.; Zhao, T. S.; Zhou, X. L.; Wei, L.; Ren, Y. X.

2017-04-01

The redox flow battery (RFB) is one of the most promising large-scale energy storage technologies for the massive utilization of intermittent renewables especially wind and solar energy. This work presents a novel redox flow battery that utilizes inexpensive and abundant Fe(II)/Fe(III) and Pb/Pb(II) redox couples as redox materials. Experimental results show that both the Fe(II)/Fe(III) and Pb/Pb(II) redox couples have fast electrochemical kinetics in methanesulfonic acid, and that the coulombic efficiency and energy efficiency of the battery are, respectively, as high as 96.2% and 86.2% at 40 mA cm-2. Furthermore, the battery exhibits stable performance in terms of efficiencies and discharge capacities during the cycle test. The inexpensive redox materials, fast electrochemical kinetics and stable cycle performance make the present battery a promising candidate for large-scale energy storage applications.

An evaluation of multi-probe locality sensitive hashing for computing similarities over web-scale query logs

PubMed Central

2018-01-01

Many modern applications of AI such as web search, mobile browsing, image processing, and natural language processing rely on finding similar items from a large database of complex objects. Due to the very large scale of data involved (e.g., users’ queries from commercial search engines), computing such near or nearest neighbors is a non-trivial task, as the computational cost grows significantly with the number of items. To address this challenge, we adopt Locality Sensitive Hashing (a.k.a, LSH) methods and evaluate four variants in a distributed computing environment (specifically, Hadoop). We identify several optimizations which improve performance, suitable for deployment in very large scale settings. The experimental results demonstrate our variants of LSH achieve the robust performance with better recall compared with “vanilla” LSH, even when using the same amount of space. PMID:29346410

Supercapacitors specialities - Technology review

NASA Astrophysics Data System (ADS)

Münchgesang, Wolfram; Meisner, Patrick; Yushin, Gleb

2014-06-01

Commercial electrochemical capacitors (supercapacitors) are not limited to mobile electronics anymore, but have reached the field of large-scale applications, like smart grid, wind turbines, power for large scale ground, water and aerial transportation, energy-efficient industrial equipment and others. This review gives a short overview of the current state-of-the-art of electrochemical capacitors, their commercial applications and the impact of technological development on performance.

Supercapacitors specialities - Technology review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Münchgesang, Wolfram; Meisner, Patrick; Yushin, Gleb

2014-06-16

Commercial electrochemical capacitors (supercapacitors) are not limited to mobile electronics anymore, but have reached the field of large-scale applications, like smart grid, wind turbines, power for large scale ground, water and aerial transportation, energy-efficient industrial equipment and others. This review gives a short overview of the current state-of-the-art of electrochemical capacitors, their commercial applications and the impact of technological development on performance.

Infrastructure for Large-Scale Quality-Improvement Projects: Early Lessons from North Carolina Improving Performance in Practice

ERIC Educational Resources Information Center

Newton, Warren P.; Lefebvre, Ann; Donahue, Katrina E.; Bacon, Thomas; Dobson, Allen

2010-01-01

Introduction: Little is known regarding how to accomplish large-scale health care improvement. Our goal is to improve the quality of chronic disease care in all primary care practices throughout North Carolina. Methods: Methods for improvement include (1) common quality measures and shared data system; (2) rapid cycle improvement principles; (3)…

On the performance of exponential integrators for problems in magnetohydrodynamics

NASA Astrophysics Data System (ADS)

Einkemmer, Lukas; Tokman, Mayya; Loffeld, John

2017-02-01

Exponential integrators have been introduced as an efficient alternative to explicit and implicit methods for integrating large stiff systems of differential equations. Over the past decades these methods have been studied theoretically and their performance was evaluated using a range of test problems. While the results of these investigations showed that exponential integrators can provide significant computational savings, the research on validating this hypothesis for large scale systems and understanding what classes of problems can particularly benefit from the use of the new techniques is in its initial stages. Resistive magnetohydrodynamic (MHD) modeling is widely used in studying large scale behavior of laboratory and astrophysical plasmas. In many problems numerical solution of MHD equations is a challenging task due to the temporal stiffness of this system in the parameter regimes of interest. In this paper we evaluate the performance of exponential integrators on large MHD problems and compare them to a state-of-the-art implicit time integrator. Both the variable and constant time step exponential methods of EPIRK-type are used to simulate magnetic reconnection and the Kevin-Helmholtz instability in plasma. Performance of these methods, which are part of the EPIC software package, is compared to the variable time step variable order BDF scheme included in the CVODE (part of SUNDIALS) library. We study performance of the methods on parallel architectures and with respect to magnitudes of important parameters such as Reynolds, Lundquist, and Prandtl numbers. We find that the exponential integrators provide superior or equal performance in most circumstances and conclude that further development of exponential methods for MHD problems is warranted and can lead to significant computational advantages for large scale stiff systems of differential equations such as MHD.

Large-scale fortification of condiments and seasonings as a public health strategy: equity considerations for implementation.

PubMed

Zamora, Gerardo; Flores-Urrutia, Mónica Crissel; Mayén, Ana-Lucia

2016-09-01

Fortification of staple foods with vitamins and minerals is an effective approach to increase micronutrient intake and improve nutritional status. The specific use of condiments and seasonings as vehicles in large-scale fortification programs is a relatively new public health strategy. This paper underscores equity considerations for the implementation of large-scale fortification of condiments and seasonings as a public health strategy by examining nonexhaustive examples of programmatic experiences and pilot projects in various settings. An overview of conceptual elements in implementation research and equity is presented, followed by an examination of equity considerations for five implementation strategies: (1) enhancing the capabilities of the public sector, (2) improving the performance of implementing agencies, (3) strengthening the capabilities and performance of frontline workers, (3) empowering communities and individuals, and (4) supporting multiple stakeholders engaged in improving health. Finally, specific considerations related to intersectoral action are considered. Large-scale fortification of condiments and seasonings cannot be a standalone strategy and needs to be implemented with concurrent and coordinated public health strategies, which should be informed by a health equity lens. © 2016 New York Academy of Sciences.

Experimental performance evaluation of software defined networking (SDN) based data communication networks for large scale flexi-grid optical networks.

PubMed

Zhao, Yongli; He, Ruiying; Chen, Haoran; Zhang, Jie; Ji, Yuefeng; Zheng, Haomian; Lin, Yi; Wang, Xinbo

2014-04-21

Software defined networking (SDN) has become the focus in the current information and communication technology area because of its flexibility and programmability. It has been introduced into various network scenarios, such as datacenter networks, carrier networks, and wireless networks. Optical transport network is also regarded as an important application scenario for SDN, which is adopted as the enabling technology of data communication networks (DCN) instead of general multi-protocol label switching (GMPLS). However, the practical performance of SDN based DCN for large scale optical networks, which is very important for the technology selection in the future optical network deployment, has not been evaluated up to now. In this paper we have built a large scale flexi-grid optical network testbed with 1000 virtual optical transport nodes to evaluate the performance of SDN based DCN, including network scalability, DCN bandwidth limitation, and restoration time. A series of network performance parameters including blocking probability, bandwidth utilization, average lightpath provisioning time, and failure restoration time have been demonstrated under various network environments, such as with different traffic loads and different DCN bandwidths. The demonstration in this work can be taken as a proof for the future network deployment.

Large-scale structural optimization

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, J.

1983-01-01

Problems encountered by aerospace designers in attempting to optimize whole aircraft are discussed, along with possible solutions. Large scale optimization, as opposed to component-by-component optimization, is hindered by computational costs, software inflexibility, concentration on a single, rather than trade-off, design methodology and the incompatibility of large-scale optimization with single program, single computer methods. The software problem can be approached by placing the full analysis outside of the optimization loop. Full analysis is then performed only periodically. Problem-dependent software can be removed from the generic code using a systems programming technique, and then embody the definitions of design variables, objective function and design constraints. Trade-off algorithms can be used at the design points to obtain quantitative answers. Finally, decomposing the large-scale problem into independent subproblems allows systematic optimization of the problems by an organization of people and machines.

Workflow management in large distributed systems

NASA Astrophysics Data System (ADS)

Legrand, I.; Newman, H.; Voicu, R.; Dobre, C.; Grigoras, C.

2011-12-01

The MonALISA (Monitoring Agents using a Large Integrated Services Architecture) framework provides a distributed service system capable of controlling and optimizing large-scale, data-intensive applications. An essential part of managing large-scale, distributed data-processing facilities is a monitoring system for computing facilities, storage, networks, and the very large number of applications running on these systems in near realtime. All this monitoring information gathered for all the subsystems is essential for developing the required higher-level services—the components that provide decision support and some degree of automated decisions—and for maintaining and optimizing workflow in large-scale distributed systems. These management and global optimization functions are performed by higher-level agent-based services. We present several applications of MonALISA's higher-level services including optimized dynamic routing, control, data-transfer scheduling, distributed job scheduling, dynamic allocation of storage resource to running jobs and automated management of remote services among a large set of grid facilities.

A Study on Fast Gates for Large-Scale Quantum Simulation with Trapped Ions

PubMed Central

Taylor, Richard L.; Bentley, Christopher D. B.; Pedernales, Julen S.; Lamata, Lucas; Solano, Enrique; Carvalho, André R. R.; Hope, Joseph J.

2017-01-01

Large-scale digital quantum simulations require thousands of fundamental entangling gates to construct the simulated dynamics. Despite success in a variety of small-scale simulations, quantum information processing platforms have hitherto failed to demonstrate the combination of precise control and scalability required to systematically outmatch classical simulators. We analyse how fast gates could enable trapped-ion quantum processors to achieve the requisite scalability to outperform classical computers without error correction. We analyze the performance of a large-scale digital simulator, and find that fidelity of around 70% is realizable for π-pulse infidelities below 10−5 in traps subject to realistic rates of heating and dephasing. This scalability relies on fast gates: entangling gates faster than the trap period. PMID:28401945

A Study on Fast Gates for Large-Scale Quantum Simulation with Trapped Ions.

PubMed

Taylor, Richard L; Bentley, Christopher D B; Pedernales, Julen S; Lamata, Lucas; Solano, Enrique; Carvalho, André R R; Hope, Joseph J

2017-04-12

Large-scale digital quantum simulations require thousands of fundamental entangling gates to construct the simulated dynamics. Despite success in a variety of small-scale simulations, quantum information processing platforms have hitherto failed to demonstrate the combination of precise control and scalability required to systematically outmatch classical simulators. We analyse how fast gates could enable trapped-ion quantum processors to achieve the requisite scalability to outperform classical computers without error correction. We analyze the performance of a large-scale digital simulator, and find that fidelity of around 70% is realizable for π-pulse infidelities below 10 -5 in traps subject to realistic rates of heating and dephasing. This scalability relies on fast gates: entangling gates faster than the trap period.

A KPI-based process monitoring and fault detection framework for large-scale processes.

PubMed

Zhang, Kai; Shardt, Yuri A W; Chen, Zhiwen; Yang, Xu; Ding, Steven X; Peng, Kaixiang

2017-05-01

Large-scale processes, consisting of multiple interconnected subprocesses, are commonly encountered in industrial systems, whose performance needs to be determined. A common approach to this problem is to use a key performance indicator (KPI)-based approach. However, the different KPI-based approaches are not developed with a coherent and consistent framework. Thus, this paper proposes a framework for KPI-based process monitoring and fault detection (PM-FD) for large-scale industrial processes, which considers the static and dynamic relationships between process and KPI variables. For the static case, a least squares-based approach is developed that provides an explicit link with least-squares regression, which gives better performance than partial least squares. For the dynamic case, using the kernel representation of each subprocess, an instrument variable is used to reduce the dynamic case to the static case. This framework is applied to the TE benchmark process and the hot strip mill rolling process. The results show that the proposed method can detect faults better than previous methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Performance of distributed multiscale simulations

PubMed Central

Borgdorff, J.; Ben Belgacem, M.; Bona-Casas, C.; Fazendeiro, L.; Groen, D.; Hoenen, O.; Mizeranschi, A.; Suter, J. L.; Coster, D.; Coveney, P. V.; Dubitzky, W.; Hoekstra, A. G.; Strand, P.; Chopard, B.

2014-01-01

Multiscale simulations model phenomena across natural scales using monolithic or component-based code, running on local or distributed resources. In this work, we investigate the performance of distributed multiscale computing of component-based models, guided by six multiscale applications with different characteristics and from several disciplines. Three modes of distributed multiscale computing are identified: supplementing local dependencies with large-scale resources, load distribution over multiple resources, and load balancing of small- and large-scale resources. We find that the first mode has the apparent benefit of increasing simulation speed, and the second mode can increase simulation speed if local resources are limited. Depending on resource reservation and model coupling topology, the third mode may result in a reduction of resource consumption. PMID:24982258

Automated Decomposition of Model-based Learning Problems

NASA Technical Reports Server (NTRS)

Williams, Brian C.; Millar, Bill

1996-01-01

A new generation of sensor rich, massively distributed autonomous systems is being developed that has the potential for unprecedented performance, such as smart buildings, reconfigurable factories, adaptive traffic systems and remote earth ecosystem monitoring. To achieve high performance these massive systems will need to accurately model themselves and their environment from sensor information. Accomplishing this on a grand scale requires automating the art of large-scale modeling. This paper presents a formalization of [\\em decompositional model-based learning (DML)], a method developed by observing a modeler's expertise at decomposing large scale model estimation tasks. The method exploits a striking analogy between learning and consistency-based diagnosis. Moriarty, an implementation of DML, has been applied to thermal modeling of a smart building, demonstrating a significant improvement in learning rate.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rizzi, Silvio; Hereld, Mark; Insley, Joseph

In this work we perform in-situ visualization of molecular dynamics simulations, which can help scientists to visualize simulation output on-the-fly, without incurring storage overheads. We present a case study to couple LAMMPS, the large-scale molecular dynamics simulation code with vl3, our parallel framework for large-scale visualization and analysis. Our motivation is to identify effective approaches for covisualization and exploration of large-scale atomistic simulations at interactive frame rates.We propose a system of coupled libraries and describe its architecture, with an implementation that runs on GPU-based clusters. We present the results of strong and weak scalability experiments, as well as future researchmore » avenues based on our results.« less

Real-time simulation of large-scale floods

NASA Astrophysics Data System (ADS)

Liu, Q.; Qin, Y.; Li, G. D.; Liu, Z.; Cheng, D. J.; Zhao, Y. H.

2016-08-01

According to the complex real-time water situation, the real-time simulation of large-scale floods is very important for flood prevention practice. Model robustness and running efficiency are two critical factors in successful real-time flood simulation. This paper proposed a robust, two-dimensional, shallow water model based on the unstructured Godunov- type finite volume method. A robust wet/dry front method is used to enhance the numerical stability. An adaptive method is proposed to improve the running efficiency. The proposed model is used for large-scale flood simulation on real topography. Results compared to those of MIKE21 show the strong performance of the proposed model.

Spatial Structure of Large-Scale Plasma Density Perturbations HF-Induced in the Ionospheric F 2 Region

NASA Astrophysics Data System (ADS)

Frolov, V. L.; Komrakov, G. P.; Glukhov, Ya. V.; Andreeva, E. S.; Kunitsyn, V. E.; Kurbatov, G. A.

2016-07-01

We consider the experimental results obtained by studying the large-scale structure of the HF-disturbed ionospheric region. The experiments were performed using the SURA heating facility. The disturbed ionospheric region was sounded by signals radiated by GPS navigation satellite beacons as well as by signals of low-orbit satellites (radio tomography). The results of the experiments show that large-scale plasma density perturbations induced at altitudes higher than the F2 layer maximum can contribute significantly to the measured variations of the total electron density and can, with a certain arrangement of the reception points, be measured by the GPS sounding method.

Large scale preparation and crystallization of neuron-specific enolase.

PubMed

Ishioka, N; Isobe, T; Kadoya, T; Okuyama, T; Nakajima, T

1984-03-01

A simple method has been developed for the large scale purification of neuron-specific enolase [EC 4.2.1.11]. The method consists of ammonium sulfate fractionation of brain extract, and two subsequent column chromatography steps on DEAE Sephadex A-50. The chromatography was performed on a short (25 cm height) and thick (8.5 cm inside diameter) column unit that was specially devised for the large scale preparation. The purified enolase was crystallized in 0.05 M imidazole-HCl buffer containing 1.6 M ammonium sulfate (pH 6.39), with a yield of 0.9 g/kg of bovine brain tissue.

Cosmological measurements with general relativistic galaxy correlations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raccanelli, Alvise; Montanari, Francesco; Durrer, Ruth

We investigate the cosmological dependence and the constraining power of large-scale galaxy correlations, including all redshift-distortions, wide-angle, lensing and gravitational potential effects on linear scales. We analyze the cosmological information present in the lensing convergence and in the gravitational potential terms describing the so-called ''relativistic effects'', and we find that, while smaller than the information contained in intrinsic galaxy clustering, it is not negligible. We investigate how neglecting them does bias cosmological measurements performed by future spectroscopic and photometric large-scale surveys such as SKA and Euclid. We perform a Fisher analysis using the CLASS code, modified to include scale-dependent galaxymore » bias and redshift-dependent magnification and evolution bias. Our results show that neglecting relativistic terms, especially lensing convergence, introduces an error in the forecasted precision in measuring cosmological parameters of the order of a few tens of percent, in particular when measuring the matter content of the Universe and primordial non-Gaussianity parameters. The analysis suggests a possible substantial systematic error in cosmological parameter constraints. Therefore, we argue that radial correlations and integrated relativistic terms need to be taken into account when forecasting the constraining power of future large-scale number counts of galaxy surveys.« less

Large voltage modulation in superconducting quantum interference devices with submicron-scale step-edge junctions

NASA Astrophysics Data System (ADS)

Lam, Simon K. H.

2017-09-01

A promising direction to improve the sensitivity of a SQUID is to increase its junction's normal resistance value, Rn, as the SQUID modulation voltage scales linearly with Rn. As a first step to develop highly sensitive single layer SQUID, submicron scale YBCO grain boundary step edge junctions and SQUIDs with large Rn were fabricated and studied. The step-edge junctions were reduced to submicron scale to increase their Rn values using focus ion beam, FIB and the measurement of transport properties were performed from 4.3 to 77 K. The FIB induced deposition layer proves to be effective to minimize the Ga ion contamination during the FIB milling process. The critical current-normal resistance value of submicron junction at 4.3 K was found to be 1-3 mV, comparable to the value of the same type of junction in micron scale. The submicron junction Rn value is in the range of 35-100 Ω, resulting a large SQUID modulation voltage in a wide temperature range. This performance promotes further investigation of cryogen-free, high field sensitivity SQUID applications at medium low temperature, e.g. at 40-60 K.

Icing Simulation Research Supporting the Ice-Accretion Testing of Large-Scale Swept-Wing Models

NASA Technical Reports Server (NTRS)

Yadlin, Yoram; Monnig, Jaime T.; Malone, Adam M.; Paul, Bernard P.

2018-01-01

The work summarized in this report is a continuation of NASA's Large-Scale, Swept-Wing Test Articles Fabrication; Research and Test Support for NASA IRT contract (NNC10BA05 -NNC14TA36T) performed by Boeing under the NASA Research and Technology for Aerospace Propulsion Systems (RTAPS) contract. In the study conducted under RTAPS, a series of icing tests in the Icing Research Tunnel (IRT) have been conducted to characterize ice formations on large-scale swept wings representative of modern commercial transport airplanes. The outcome of that campaign was a large database of ice-accretion geometries that can be used for subsequent aerodynamic evaluation in other experimental facilities and for validation of ice-accretion prediction codes.

A Large-Scale Inquiry-Based Astronomy Intervention Project: Impact on Students' Content Knowledge Performance and Views of Their High School Science Classroom

ERIC Educational Resources Information Center

Fitzgerald, Michael; McKinnon, David H.; Danaia, Lena; Deehan, James

2016-01-01

In this paper, we present the results from a study of the impact on students involved in a large-scale inquiry-based astronomical high school education intervention in Australia. Students in this intervention were led through an educational design allowing them to undertake an investigative approach to understanding the lifecycle of stars more…

Classification Accuracy of Oral Reading Fluency and Maze in Predicting Performance on Large-Scale Reading Assessments

ERIC Educational Resources Information Center

Decker, Dawn M.; Hixson, Michael D.; Shaw, Amber; Johnson, Gloria

2014-01-01

The purpose of this study was to examine whether using a multiple-measure framework yielded better classification accuracy than oral reading fluency (ORF) or maze alone in predicting pass/fail rates for middle-school students on a large-scale reading assessment. Participants were 178 students in Grades 7 and 8 from a Midwestern school district.…

Development of Novel Therapeutics for Neglected Tropical Disease Leishmaniasis

DTIC Science & Technology

2015-10-01

Approved for public release; distribution unlimited We undertook planning of kick off coordination meeting. A low dose infection model of CL was validated...A large scale synthesis of PEN optimized and in vitro studies were performed revealed that PEN alters parasite lipidome. Further studies were...Pentalinonsterol, Leishmania, cutaneous leishmaniasis, treatment Accomplishments • Undertook planning of kick off coordination meeting • Large scale synthesis of

Newly invented biobased materials from low-carbon, diverted waste fibers: research methods, testing, and full-scale application in a case study structure

Treesearch

Julee A Herdt; John Hunt; Kellen Schauermann

2016-01-01

This project demonstrates newly invented, biobased construction materials developed by applying lowcarbon, biomass waste sources through the Authors’ engineered fiber processes and technology. If manufactured and applied large-scale the project inventions can divert large volumes of cellulose waste into high-performance, low embodied energy, environmental construction...

Large scale shell model study of the evolution of mixed-symmetry states in chains of nuclei around 132Sn

NASA Astrophysics Data System (ADS)

Lo Iudice, N.; Bianco, D.; Andreozzi, F.; Porrino, A.; Knapp, F.

2012-10-01

Large scale shell model calculations based on a new diagonalization algorithm are performed in order to investigate the mixed symmetry states in chains of nuclei in the proximity of N=82. The resulting spectra and transitions are in agreement with the experiments and consistent with the scheme provided by the interacting boson model.

Large-Scale Brain Network Coupling Predicts Total Sleep Deprivation Effects on Cognitive Capacity

PubMed Central

Wang, Lubin; Zhai, Tianye; Zou, Feng; Ye, Enmao; Jin, Xiao; Li, Wuju; Qi, Jianlin; Yang, Zheng

2015-01-01

Interactions between large-scale brain networks have received most attention in the study of cognitive dysfunction of human brain. In this paper, we aimed to test the hypothesis that the coupling strength of large-scale brain networks will reflect the pressure for sleep and will predict cognitive performance, referred to as sleep pressure index (SPI). Fourteen healthy subjects underwent this within-subject functional magnetic resonance imaging (fMRI) study during rested wakefulness (RW) and after 36 h of total sleep deprivation (TSD). Self-reported scores of sleepiness were higher for TSD than for RW. A subsequent working memory (WM) task showed that WM performance was lower after 36 h of TSD. Moreover, SPI was developed based on the coupling strength of salience network (SN) and default mode network (DMN). Significant increase of SPI was observed after 36 h of TSD, suggesting stronger pressure for sleep. In addition, SPI was significantly correlated with both the visual analogue scale score of sleepiness and the WM performance. These results showed that alterations in SN-DMN coupling might be critical in cognitive alterations that underlie the lapse after TSD. Further studies may validate the SPI as a potential clinical biomarker to assess the impact of sleep deprivation. PMID:26218521

Cross-flow turbines: progress report on physical and numerical model studies at large laboratory scale

NASA Astrophysics Data System (ADS)

Wosnik, Martin; Bachant, Peter

2016-11-01

Cross-flow turbines show potential in marine hydrokinetic (MHK) applications. A research focus is on accurately predicting device performance and wake evolution to improve turbine array layouts for maximizing overall power output, i.e., minimizing wake interference, or taking advantage of constructive wake interaction. Experiments were carried with large laboratory-scale cross-flow turbines D O (1 m) using a turbine test bed in a large cross-section tow tank, designed to achieve sufficiently high Reynolds numbers for the results to be Reynolds number independent with respect to turbine performance and wake statistics, such that they can be reliably extrapolated to full scale and used for model validation. Several turbines of varying solidity were employed, including the UNH Reference Vertical Axis Turbine (RVAT) and a 1:6 scale model of the DOE-Sandia Reference Model 2 (RM2) turbine. To improve parameterization in array simulations, an actuator line model (ALM) was developed to provide a computationally feasible method for simulating full turbine arrays inside Navier-Stokes models. Results are presented for the simulation of performance and wake dynamics of cross-flow turbines and compared with experiments and body-fitted mesh, blade-resolving CFD. Supported by NSF-CBET Grant 1150797, Sandia National Laboratories.

Analytical Assessment of the Relationship between 100MWp Large-scale Grid-connected Photovoltaic Plant Performance and Meteorological Parameters

NASA Astrophysics Data System (ADS)

Sheng, Jie; Zhu, Qiaoming; Cao, Shijie; You, Yang

2017-05-01

This paper helps in study of the relationship between the photovoltaic power generation of large scale “fishing and PV complementary” grid-tied photovoltaic system and meteorological parameters, with multi-time scale power data from the photovoltaic power station and meteorological data over the same period of a whole year. The result indicates that, the PV power generation has the most significant correlation with global solar irradiation, followed by diurnal temperature range, sunshine hours, daily maximum temperature and daily average temperature. In different months, the maximum monthly average power generation appears in August, which related to the more global solar irradiation and longer sunshine hours in this month. However, the maximum daily average power generation appears in October, this is due to the drop in temperature brings about the improvement of the efficiency of PV panels. Through the contrast of monthly average performance ratio (PR) and monthly average temperature, it is shown that, the larger values of monthly average PR appears in April and October, while it is smaller in summer with higher temperature. The results concluded that temperature has a great influence on the performance ratio of large scale grid-tied PV power system, and it is important to adopt effective measures to decrease the temperature of PV plant properly.

On the Fidelity of Semi-distributed Hydrologic Model Simulations for Large Scale Catchment Applications

NASA Astrophysics Data System (ADS)

Ajami, H.; Sharma, A.; Lakshmi, V.

2017-12-01

Application of semi-distributed hydrologic modeling frameworks is a viable alternative to fully distributed hyper-resolution hydrologic models due to computational efficiency and resolving fine-scale spatial structure of hydrologic fluxes and states. However, fidelity of semi-distributed model simulations is impacted by (1) formulation of hydrologic response units (HRUs), and (2) aggregation of catchment properties for formulating simulation elements. Here, we evaluate the performance of a recently developed Soil Moisture and Runoff simulation Toolkit (SMART) for large catchment scale simulations. In SMART, topologically connected HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are equivalent cross sections (ECS) representative of a hillslope in first order sub-basins. Earlier investigations have shown that formulation of ECSs at the scale of a first order sub-basin reduces computational time significantly without compromising simulation accuracy. However, the implementation of this approach has not been fully explored for catchment scale simulations. To assess SMART performance, we set-up the model over the Little Washita watershed in Oklahoma. Model evaluations using in-situ soil moisture observations show satisfactory model performance. In addition, we evaluated the performance of a number of soil moisture disaggregation schemes recently developed to provide spatially explicit soil moisture outputs at fine scale resolution. Our results illustrate that the statistical disaggregation scheme performs significantly better than the methods based on topographic data. Future work is focused on assessing the performance of SMART using remotely sensed soil moisture observations using spatially based model evaluation metrics.

Large- and Very-Large-Scale Motions in Katabatic Flows Over Steep Slopes

NASA Astrophysics Data System (ADS)

Giometto, M. G.; Fang, J.; Salesky, S.; Parlange, M. B.

2016-12-01

Evidence of large- and very-large-scale motions populating the boundary layer in katabatic flows over steep slopes is presented via direct numerical simulations (DNSs). DNSs are performed at a modified Reynolds number (Rem = 967), considering four sloping angles (α = 60°, 70°, 80° and 90°). Large coherent structures prove to be strongly dependent on the inclination of the underlying surface. Spectra and co-spectra consistently show signatures of large-scale motions (LSMs), with streamwise extension on the order of the boundary layer thickness. A second low-wavenumber mode characterizes pre-multiplied spectra and co-spectra when the slope angle is below 70°, indicative of very-large-scale motions (VLSMs). In addition, conditional sampling and averaging shows how LSMs and VLSMs are induced by counter-rotating roll modes, in agreement with findings from canonical wall-bounded flows. VLSMs contribute to the stream-wise velocity variance and shear stress in the above-jet regions up to 30% and 45% respectively, whereas both LSMs and VLSMs are inactive in the near-wall regions.

Overview of large scale experiments performed within the LBB project in the Czech Republic

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kadecka, P.; Lauerova, D.

1997-04-01

During several recent years NRI Rez has been performing the LBB analyses of safety significant primary circuit pipings of NPPs in Czech and Slovak Republics. The analyses covered the NPPs with reactors WWER 440 Type 230 and 213 and WWER 1000 Type 320. Within the relevant LBB projects undertaken with the aim to prove the fulfilling of the requirements of LBB, a series of large scale experiments were performed. The goal of these experiments was to verify the properties of the components selected, and to prove the quality and/or conservatism of assessments used in the LBB-analyses. In this poster, amore » brief overview of experiments performed in Czech Republic under guidance of NRI Rez is presented.« less

Adaptive Fault-Tolerant Control of Uncertain Nonlinear Large-Scale Systems With Unknown Dead Zone.

PubMed

Chen, Mou; Tao, Gang

2016-08-01

In this paper, an adaptive neural fault-tolerant control scheme is proposed and analyzed for a class of uncertain nonlinear large-scale systems with unknown dead zone and external disturbances. To tackle the unknown nonlinear interaction functions in the large-scale system, the radial basis function neural network (RBFNN) is employed to approximate them. To further handle the unknown approximation errors and the effects of the unknown dead zone and external disturbances, integrated as the compounded disturbances, the corresponding disturbance observers are developed for their estimations. Based on the outputs of the RBFNN and the disturbance observer, the adaptive neural fault-tolerant control scheme is designed for uncertain nonlinear large-scale systems by using a decentralized backstepping technique. The closed-loop stability of the adaptive control system is rigorously proved via Lyapunov analysis and the satisfactory tracking performance is achieved under the integrated effects of unknown dead zone, actuator fault, and unknown external disturbances. Simulation results of a mass-spring-damper system are given to illustrate the effectiveness of the proposed adaptive neural fault-tolerant control scheme for uncertain nonlinear large-scale systems.

Detonation failure characterization of non-ideal explosives

NASA Astrophysics Data System (ADS)

Janesheski, Robert S.; Groven, Lori J.; Son, Steven

2012-03-01

Non-ideal explosives are currently poorly characterized, hence limiting the modeling of them. Current characterization requires large-scale testing to obtain steady detonation wave characterization for analysis due to the relatively thick reaction zones. Use of a microwave interferometer applied to small-scale confined transient experiments is being implemented to allow for time resolved characterization of a failing detonation. The microwave interferometer measures the position of a failing detonation wave in a tube that is initiated with a booster charge. Experiments have been performed with ammonium nitrate and various fuel compositions (diesel fuel and mineral oil). It was observed that the failure dynamics are influenced by factors such as chemical composition and confiner thickness. Future work is planned to calibrate models to these small-scale experiments and eventually validate the models with available large scale experiments. This experiment is shown to be repeatable, shows dependence on reactive properties, and can be performed with little required material.

Presenting an Approach for Conducting Knowledge Architecture within Large-Scale Organizations

PubMed Central

Varaee, Touraj; Habibi, Jafar; Mohaghar, Ali

2015-01-01

Knowledge architecture (KA) establishes the basic groundwork for the successful implementation of a short-term or long-term knowledge management (KM) program. An example of KA is the design of a prototype before a new vehicle is manufactured. Due to a transformation to large-scale organizations, the traditional architecture of organizations is undergoing fundamental changes. This paper explores the main strengths and weaknesses in the field of KA within large-scale organizations and provides a suitable methodology and supervising framework to overcome specific limitations. This objective was achieved by applying and updating the concepts from the Zachman information architectural framework and the information architectural methodology of enterprise architecture planning (EAP). The proposed solution may be beneficial for architects in knowledge-related areas to successfully accomplish KM within large-scale organizations. The research method is descriptive; its validity is confirmed by performing a case study and polling the opinions of KA experts. PMID:25993414

Seismic safety in conducting large-scale blasts

NASA Astrophysics Data System (ADS)

Mashukov, I. V.; Chaplygin, V. V.; Domanov, V. P.; Semin, A. A.; Klimkin, M. A.

2017-09-01

In mining enterprises to prepare hard rocks for excavation a drilling and blasting method is used. With the approach of mining operations to settlements the negative effect of large-scale blasts increases. To assess the level of seismic impact of large-scale blasts the scientific staff of Siberian State Industrial University carried out expertise for coal mines and iron ore enterprises. Determination of the magnitude of surface seismic vibrations caused by mass explosions was performed using seismic receivers, an analog-digital converter with recording on a laptop. The registration results of surface seismic vibrations during production of more than 280 large-scale blasts at 17 mining enterprises in 22 settlements are presented. The maximum velocity values of the Earth’s surface vibrations are determined. The safety evaluation of seismic effect was carried out according to the permissible value of vibration velocity. For cases with exceedance of permissible values recommendations were developed to reduce the level of seismic impact.

Presenting an Approach for Conducting Knowledge Architecture within Large-Scale Organizations.

PubMed

Varaee, Touraj; Habibi, Jafar; Mohaghar, Ali

2015-01-01

Knowledge architecture (KA) establishes the basic groundwork for the successful implementation of a short-term or long-term knowledge management (KM) program. An example of KA is the design of a prototype before a new vehicle is manufactured. Due to a transformation to large-scale organizations, the traditional architecture of organizations is undergoing fundamental changes. This paper explores the main strengths and weaknesses in the field of KA within large-scale organizations and provides a suitable methodology and supervising framework to overcome specific limitations. This objective was achieved by applying and updating the concepts from the Zachman information architectural framework and the information architectural methodology of enterprise architecture planning (EAP). The proposed solution may be beneficial for architects in knowledge-related areas to successfully accomplish KM within large-scale organizations. The research method is descriptive; its validity is confirmed by performing a case study and polling the opinions of KA experts.

A behavioral-level HDL description of SFQ logic circuits for quantitative performance analysis of large-scale SFQ digital systems

NASA Astrophysics Data System (ADS)

Matsuzaki, F.; Yoshikawa, N.; Tanaka, M.; Fujimaki, A.; Takai, Y.

2003-10-01

Recently many single flux quantum (SFQ) logic circuits containing several thousands of Josephson junctions have been designed successfully by using digital domain simulation based on the hard ware description language (HDL). In the present HDL-based design of SFQ circuits, a structure-level HDL description has been used, where circuits are made up of basic gate cells. However, in order to analyze large-scale SFQ digital systems, such as a microprocessor, more higher-level circuit abstraction is necessary to reduce the circuit simulation time. In this paper we have investigated the way to describe functionality of the large-scale SFQ digital circuits by a behavior-level HDL description. In this method, the functionality and the timing of the circuit block is defined directly by describing their behavior by the HDL. Using this method, we can dramatically reduce the simulation time of large-scale SFQ digital circuits.

Will COBE challenge the inflationary paradigm - Cosmic microwave background anisotropies versus large-scale streaming motions revisited

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gorski, K.M.

1991-03-01

The relation between cosmic microwave background (CMB) anisotropies and large-scale galaxy streaming motions is examined within the framework of inflationary cosmology. The minimal Sachs and Wolfe (1967) CMB anisotropies at large angular scales in the models with initial Harrison-Zel'dovich spectrum of inhomogeneity normalized to the local large-scale bulk flow, which are independent of the Hubble constant and specific nature of dark matter, are found to be within the anticipated ultimate sensitivity limits of COBE's Differential Microwave Radiometer experiment. For example, the most likely value of the quadrupole coefficient is predicted to be a2 not less than 7 x 10 tomore » the -6th, where equality applies to the limiting minimal model. If (1) COBE's DMR instruments perform well throughout the two-year period; (2) the anisotropy data are not marred by the systematic errors; (3) the large-scale motions retain their present observational status; (4) there is no statistical conspiracy in a sense of the measured bulk flow being of untypically high and the large-scale anisotropy of untypically low amplitudes; and (5) the low-order multipoles in the all-sky primordial fireball temperature map are not detected, the inflationary paradigm will have to be questioned. 19 refs.« less

On the influences of key modelling constants of large eddy simulations for large-scale compartment fires predictions

NASA Astrophysics Data System (ADS)

Yuen, Anthony C. Y.; Yeoh, Guan H.; Timchenko, Victoria; Cheung, Sherman C. P.; Chan, Qing N.; Chen, Timothy

2017-09-01

An in-house large eddy simulation (LES) based fire field model has been developed for large-scale compartment fire simulations. The model incorporates four major components, including subgrid-scale turbulence, combustion, soot and radiation models which are fully coupled. It is designed to simulate the temporal and fluid dynamical effects of turbulent reaction flow for non-premixed diffusion flame. Parametric studies were performed based on a large-scale fire experiment carried out in a 39-m long test hall facility. Several turbulent Prandtl and Schmidt numbers ranging from 0.2 to 0.5, and Smagorinsky constants ranging from 0.18 to 0.23 were investigated. It was found that the temperature and flow field predictions were most accurate with turbulent Prandtl and Schmidt numbers of 0.3, respectively, and a Smagorinsky constant of 0.2 applied. In addition, by utilising a set of numerically verified key modelling parameters, the smoke filling process was successfully captured by the present LES model.

Medical image classification based on multi-scale non-negative sparse coding.

PubMed

Zhang, Ruijie; Shen, Jian; Wei, Fushan; Li, Xiong; Sangaiah, Arun Kumar

2017-11-01

With the rapid development of modern medical imaging technology, medical image classification has become more and more important in medical diagnosis and clinical practice. Conventional medical image classification algorithms usually neglect the semantic gap problem between low-level features and high-level image semantic, which will largely degrade the classification performance. To solve this problem, we propose a multi-scale non-negative sparse coding based medical image classification algorithm. Firstly, Medical images are decomposed into multiple scale layers, thus diverse visual details can be extracted from different scale layers. Secondly, for each scale layer, the non-negative sparse coding model with fisher discriminative analysis is constructed to obtain the discriminative sparse representation of medical images. Then, the obtained multi-scale non-negative sparse coding features are combined to form a multi-scale feature histogram as the final representation for a medical image. Finally, SVM classifier is combined to conduct medical image classification. The experimental results demonstrate that our proposed algorithm can effectively utilize multi-scale and contextual spatial information of medical images, reduce the semantic gap in a large degree and improve medical image classification performance. Copyright © 2017 Elsevier B.V. All rights reserved.

Biology-Inspired Distributed Consensus in Massively-Deployed Sensor Networks

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin, Chunsheng

2005-01-01

Promises of ubiquitous control of the physical environment by large-scale wireless sensor networks open avenues for new applications that are expected to redefine the way we live and work. Most of recent research has concentrated on developing techniques for performing relatively simple tasks in small-scale sensor networks assuming some form of centralized control. The main contribution of this work is to propose a new way of looking at large-scale sensor networks, motivated by lessons learned from the way biological ecosystems are organized. Indeed, we believe that techniques used in small-scale sensor networks are not likely to scale to large networks; that such large-scale networks must be viewed as an ecosystem in which the sensors/effectors are organisms whose autonomous actions, based on local information, combine in a communal way to produce global results. As an example of a useful function, we demonstrate that fully distributed consensus can be attained in a scalable fashion in massively deployed sensor networks where individual motes operate based on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects.

Large-scale, high-performance and cloud-enabled multi-model analytics experiments in the context of the Earth System Grid Federation

NASA Astrophysics Data System (ADS)

Fiore, S.; Płóciennik, M.; Doutriaux, C.; Blanquer, I.; Barbera, R.; Williams, D. N.; Anantharaj, V. G.; Evans, B. J. K.; Salomoni, D.; Aloisio, G.

2017-12-01

The increased models resolution in the development of comprehensive Earth System Models is rapidly leading to very large climate simulations output that pose significant scientific data management challenges in terms of data sharing, processing, analysis, visualization, preservation, curation, and archiving.Large scale global experiments for Climate Model Intercomparison Projects (CMIP) have led to the development of the Earth System Grid Federation (ESGF), a federated data infrastructure which has been serving the CMIP5 experiment, providing access to 2PB of data for the IPCC Assessment Reports. In such a context, running a multi-model data analysis experiment is very challenging, as it requires the availability of a large amount of data related to multiple climate models simulations and scientific data management tools for large-scale data analytics. To address these challenges, a case study on climate models intercomparison data analysis has been defined and implemented in the context of the EU H2020 INDIGO-DataCloud project. The case study has been tested and validated on CMIP5 datasets, in the context of a large scale, international testbed involving several ESGF sites (LLNL, ORNL and CMCC), one orchestrator site (PSNC) and one more hosting INDIGO PaaS services (UPV). Additional ESGF sites, such as NCI (Australia) and a couple more in Europe, are also joining the testbed. The added value of the proposed solution is summarized in the following: it implements a server-side paradigm which limits data movement; it relies on a High-Performance Data Analytics (HPDA) stack to address performance; it exploits the INDIGO PaaS layer to support flexible, dynamic and automated deployment of software components; it provides user-friendly web access based on the INDIGO Future Gateway; and finally it integrates, complements and extends the support currently available through ESGF. Overall it provides a new "tool" for climate scientists to run multi-model experiments. At the time this contribution is being written, the proposed testbed represents the first implementation of a distributed large-scale, multi-model experiment in the ESGF/CMIP context, joining together server-side approaches for scientific data analysis, HPDA frameworks, end-to-end workflow management, and cloud computing.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gallarno, George; Rogers, James H; Maxwell, Don E

The high computational capability of graphics processing units (GPUs) is enabling and driving the scientific discovery process at large-scale. The world s second fastest supercomputer for open science, Titan, has more than 18,000 GPUs that computational scientists use to perform scientific simu- lations and data analysis. Understanding of GPU reliability characteristics, however, is still in its nascent stage since GPUs have only recently been deployed at large-scale. This paper presents a detailed study of GPU errors and their impact on system operations and applications, describing experiences with the 18,688 GPUs on the Titan supercom- puter as well as lessons learnedmore » in the process of efficient operation of GPUs at scale. These experiences are helpful to HPC sites which already have large-scale GPU clusters or plan to deploy GPUs in the future.« less

Designing a Large-Scale Multilevel Improvement Initiative: The Improving Performance in Practice Program

ERIC Educational Resources Information Center

Margolis, Peter A.; DeWalt, Darren A.; Simon, Janet E.; Horowitz, Sheldon; Scoville, Richard; Kahn, Norman; Perelman, Robert; Bagley, Bruce; Miles, Paul

2010-01-01

Improving Performance in Practice (IPIP) is a large system intervention designed to align efforts and motivate the creation of a tiered system of improvement at the national, state, practice, and patient levels, assisting primary-care physicians and their practice teams to assess and measurably improve the quality of care for chronic illness and…

Impact of spatial variability and sampling design on model performance

NASA Astrophysics Data System (ADS)

Schrape, Charlotte; Schneider, Anne-Kathrin; Schröder, Boris; van Schaik, Loes

2017-04-01

Many environmental physical and chemical parameters as well as species distributions display a spatial variability at different scales. In case measurements are very costly in labour time or money a choice has to be made between a high sampling resolution at small scales and a low spatial cover of the study area or a lower sampling resolution at the small scales resulting in local data uncertainties with a better spatial cover of the whole area. This dilemma is often faced in the design of field sampling campaigns for large scale studies. When the gathered field data are subsequently used for modelling purposes the choice of sampling design and resulting data quality influence the model performance criteria. We studied this influence with a virtual model study based on a large dataset of field information on spatial variation of earthworms at different scales. Therefore we built a virtual map of anecic earthworm distributions over the Weiherbach catchment (Baden-Württemberg in Germany). First of all the field scale abundance of earthworms was estimated using a catchment scale model based on 65 field measurements. Subsequently the high small scale variability was added using semi-variograms, based on five fields with a total of 430 measurements divided in a spatially nested sampling design over these fields, to estimate the nugget, range and standard deviation of measurements within the fields. With the produced maps, we performed virtual samplings of one up to 50 random points per field. We then used these data to rebuild the catchment scale models of anecic earthworm abundance with the same model parameters as in the work by Palm et al. (2013). The results of the models show clearly that a large part of the non-explained deviance of the models is due to the very high small scale variability in earthworm abundance: the models based on single virtual sampling points on average obtain an explained deviance of 0.20 and a correlation coefficient of 0.64. With increasing sampling points per field, we averaged the measured abundance of the sampling within each field to obtain a more representative value of the field average. Doubling the samplings per field strongly improved the model performance criteria (explained deviance 0.38 and correlation coefficient 0.73). With 50 sampling points per field the performance criteria were 0.91 and 0.97 respectively for explained deviance and correlation coefficient. The relationship between number of samplings and performance criteria can be described with a saturation curve. Beyond five samples per field the model improvement becomes rather small. With this contribution we wish to discuss the impact of data variability at sampling scale on model performance and the implications for sampling design and assessment of model results as well as ecological inferences.

Approximate kernel competitive learning.

PubMed

Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang

2015-03-01

Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.

The impact of pH inhomogeneities on CHO cell physiology and fed-batch process performance - two-compartment scale-down modelling and intracellular pH excursion.

PubMed

Brunner, Matthias; Braun, Philipp; Doppler, Philipp; Posch, Christoph; Behrens, Dirk; Herwig, Christoph; Fricke, Jens

2017-07-01

Due to high mixing times and base addition from top of the vessel, pH inhomogeneities are most likely to occur during large-scale mammalian processes. The goal of this study was to set-up a scale-down model of a 10-12 m 3 stirred tank bioreactor and to investigate the effect of pH perturbations on CHO cell physiology and process performance. Short-term changes in extracellular pH are hypothesized to affect intracellular pH and thus cell physiology. Therefore, batch fermentations, including pH shifts to 9.0 and 7.8, in regular one-compartment systems are conducted. The short-term adaption of the cells intracellular pH are showed an immediate increase due to elevated extracellular pH. With this basis of fundamental knowledge, a two-compartment system is established which is capable of simulating defined pH inhomogeneities. In contrast to state-of-the-art literature, the scale-down model is included parameters (e.g. volume of the inhomogeneous zone) as they might occur during large-scale processes. pH inhomogeneity studies in the two-compartment system are performed with simulation of temporary pH zones of pH 9.0. The specific growth rate especially during the exponential growth phase is strongly affected resulting in a decreased maximum viable cell density and final product titer. The gathered results indicate that even short-term exposure of cells to elevated pH values during large-scale processes can affect cell physiology and overall process performance. In particular, it could be shown for the first time that pH perturbations, which might occur during the early process phase, have to be considered in scale-down models of mammalian processes. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Performance Characterization of Global Address Space Applications: A Case Study with NWChem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hammond, Jeffrey R.; Krishnamoorthy, Sriram; Shende, Sameer

The use of global address space languages and one-sided communication for complex applications is gaining attention in the parallel computing community. However, lack of good evaluative methods to observe multiple levels of performance makes it difficult to isolate the cause of performance deficiencies and to understand the fundamental limitations of system and application design for future improvement. NWChem is a popular computational chemistry package which depends on the Global Arrays/ ARMCI suite for partitioned global address space functionality to deliver high-end molecular modeling capabilities. A workload characterization methodology was developed to support NWChem performance engineering on large-scale parallel platforms. Themore » research involved both the integration of performance instrumentation and measurement in the NWChem software, as well as the analysis of one-sided communication performance in the context of NWChem workloads. Scaling studies were conducted for NWChem on Blue Gene/P and on two large-scale clusters using different generation Infiniband interconnects and x86 processors. The performance analysis and results show how subtle changes in the runtime parameters related to the communication subsystem could have significant impact on performance behavior. The tool has successfully identified several algorithmic bottlenecks which are already being tackled by computational chemists to improve NWChem performance.« less

Experience with specifications applicable to certification. [of photovoltaic modules for large-scale application

NASA Technical Reports Server (NTRS)

Ross, R. G., Jr.

1982-01-01

The Jet Propulsion Laboratory has developed a number of photovoltaic test and measurement specifications to guide the development of modules toward the requirements of future large-scale applications. Experience with these specifications and the extensive module measurement and testing that has accompanied their use is examined. Conclusions are drawn relative to three aspects of product certification: performance measurement, endurance testing and safety evaluation.

Design of an omnidirectional single-point photodetector for large-scale spatial coordinate measurement

NASA Astrophysics Data System (ADS)

Xie, Hongbo; Mao, Chensheng; Ren, Yongjie; Zhu, Jigui; Wang, Chao; Yang, Lei

2017-10-01

In high precision and large-scale coordinate measurement, one commonly used approach to determine the coordinate of a target point is utilizing the spatial trigonometric relationships between multiple laser transmitter stations and the target point. A light receiving device at the target point is the key element in large-scale coordinate measurement systems. To ensure high-resolution and highly sensitive spatial coordinate measurement, a high-performance and miniaturized omnidirectional single-point photodetector (OSPD) is greatly desired. We report one design of OSPD using an aspheric lens, which achieves an enhanced reception angle of -5 deg to 45 deg in vertical and 360 deg in horizontal. As the heart of our OSPD, the aspheric lens is designed in a geometric model and optimized by LightTools Software, which enables the reflection of a wide-angle incident light beam into the single-point photodiode. The performance of home-made OSPD is characterized with working distances from 1 to 13 m and further analyzed utilizing developed a geometric model. The experimental and analytic results verify that our device is highly suitable for large-scale coordinate metrology. The developed device also holds great potential in various applications such as omnidirectional vision sensor, indoor global positioning system, and optical wireless communication systems.

Global-scale regionalization of hydrological model parameters using streamflow data from many small catchments

NASA Astrophysics Data System (ADS)

Beck, Hylke; de Roo, Ad; van Dijk, Albert; McVicar, Tim; Miralles, Diego; Schellekens, Jaap; Bruijnzeel, Sampurno; de Jeu, Richard

2015-04-01

Motivated by the lack of large-scale model parameter regionalization studies, a large set of 3328 small catchments (< 10000 km2) around the globe was used to set up and evaluate five model parameterization schemes at global scale. The HBV-light model was chosen because of its parsimony and flexibility to test the schemes. The catchments were calibrated against observed streamflow (Q) using an objective function incorporating both behavioral and goodness-of-fit measures, after which the catchment set was split into subsets of 1215 donor and 2113 evaluation catchments based on the calibration performance. The donor catchments were subsequently used to derive parameter sets that were transferred to similar grid cells based on a similarity measure incorporating climatic and physiographic characteristics, thereby producing parameter maps with global coverage. Overall, there was a lack of suitable donor catchments for mountainous and tropical environments. The schemes with spatially-uniform parameter sets (EXP2 and EXP3) achieved the worst Q estimation performance in the evaluation catchments, emphasizing the importance of parameter regionalization. The direct transfer of calibrated parameter sets from donor catchments to similar grid cells (scheme EXP1) performed best, although there was still a large performance gap between EXP1 and HBV-light calibrated against observed Q. The schemes with parameter sets obtained by simultaneously calibrating clusters of similar donor catchments (NC10 and NC58) performed worse than EXP1. The relatively poor Q estimation performance achieved by two (uncalibrated) macro-scale hydrological models suggests there is considerable merit in regionalizing the parameters of such models. The global HBV-light parameter maps and ancillary data are freely available via http://water.jrc.ec.europa.eu.

Edge-localized mode avoidance and pedestal structure in I-mode plasmas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walk, J. R., E-mail: jrwalk@psfc.mit.edu; Hughes, J. W.; Hubbard, A. E.

I-mode is a high-performance tokamak regime characterized by the formation of a temperature pedestal and enhanced energy confinement, without an accompanying density pedestal or drop in particle and impurity transport. I-mode operation appears to have naturally occurring suppression of large Edge-Localized Modes (ELMs) in addition to its highly favorable scalings of pedestal structure and overall performance. Extensive study of the ELMy H-mode has led to the development of the EPED model, which utilizes calculations of coupled peeling-ballooning MHD modes and kinetic-ballooning mode (KBM) stability limits to predict the pedestal structure preceding an ELM crash. We apply similar tools to themore » structure and ELM stability of I-mode pedestals. Analysis of I-mode discharges prepared with high-resolution pedestal data from the most recent C-Mod campaign reveals favorable pedestal scalings for extrapolation to large machines—pedestal temperature scales strongly with power per particle P{sub net}/n{sup ¯}{sub e}, and likewise pedestal pressure scales as the net heating power (consistent with weak degradation of confinement with heating power). Matched discharges in current, field, and shaping demonstrate the decoupling of energy and particle transport in I-mode, increasing fueling to span nearly a factor of two in density while maintaining matched temperature pedestals with consistent levels of P{sub net}/n{sup ¯}{sub e}. This is consistent with targets for increased performance in I-mode, elevating pedestal β{sub p} and global performance with matched increases in density and heating power. MHD calculations using the ELITE code indicate that I-mode pedestals are strongly stable to edge peeling-ballooning instabilities. Likewise, numerical modeling of the KBM turbulence onset, as well as scalings of the pedestal width with poloidal beta, indicates that I-mode pedestals are not limited by KBM turbulence—both features identified with the trigger for large ELMs, consistent with the observed suppression of large ELMs in I-mode.« less

Edge-localized mode avoidance and pedestal structure in I-mode plasmasa)

NASA Astrophysics Data System (ADS)

Walk, J. R.; Hughes, J. W.; Hubbard, A. E.; Terry, J. L.; Whyte, D. G.; White, A. E.; Baek, S. G.; Reinke, M. L.; Theiler, C.; Churchill, R. M.; Rice, J. E.; Snyder, P. B.; Osborne, T.; Dominguez, A.; Cziegler, I.

2014-05-01

I-mode is a high-performance tokamak regime characterized by the formation of a temperature pedestal and enhanced energy confinement, without an accompanying density pedestal or drop in particle and impurity transport. I-mode operation appears to have naturally occurring suppression of large Edge-Localized Modes (ELMs) in addition to its highly favorable scalings of pedestal structure and overall performance. Extensive study of the ELMy H-mode has led to the development of the EPED model, which utilizes calculations of coupled peeling-ballooning MHD modes and kinetic-ballooning mode (KBM) stability limits to predict the pedestal structure preceding an ELM crash. We apply similar tools to the structure and ELM stability of I-mode pedestals. Analysis of I-mode discharges prepared with high-resolution pedestal data from the most recent C-Mod campaign reveals favorable pedestal scalings for extrapolation to large machines—pedestal temperature scales strongly with power per particle Pnet/n ¯e, and likewise pedestal pressure scales as the net heating power (consistent with weak degradation of confinement with heating power). Matched discharges in current, field, and shaping demonstrate the decoupling of energy and particle transport in I-mode, increasing fueling to span nearly a factor of two in density while maintaining matched temperature pedestals with consistent levels of Pnet/n ¯e. This is consistent with targets for increased performance in I-mode, elevating pedestal βp and global performance with matched increases in density and heating power. MHD calculations using the ELITE code indicate that I-mode pedestals are strongly stable to edge peeling-ballooning instabilities. Likewise, numerical modeling of the KBM turbulence onset, as well as scalings of the pedestal width with poloidal beta, indicates that I-mode pedestals are not limited by KBM turbulence—both features identified with the trigger for large ELMs, consistent with the observed suppression of large ELMs in I-mode.

Parallel Visualization of Large-Scale Aerodynamics Calculations: A Case Study on the Cray T3E

NASA Technical Reports Server (NTRS)

Ma, Kwan-Liu; Crockett, Thomas W.

1999-01-01

This paper reports the performance of a parallel volume rendering algorithm for visualizing a large-scale, unstructured-grid dataset produced by a three-dimensional aerodynamics simulation. This dataset, containing over 18 million tetrahedra, allows us to extend our performance results to a problem which is more than 30 times larger than the one we examined previously. This high resolution dataset also allows us to see fine, three-dimensional features in the flow field. All our tests were performed on the Silicon Graphics Inc. (SGI)/Cray T3E operated by NASA's Goddard Space Flight Center. Using 511 processors, a rendering rate of almost 9 million tetrahedra/second was achieved with a parallel overhead of 26%.

Instrumentation Development for Large Scale Hypersonic Inflatable Aerodynamic Decelerator Characterization

NASA Technical Reports Server (NTRS)

Swanson, Gregory T.; Cassell, Alan M.

2011-01-01

Hypersonic Inflatable Aerodynamic Decelerator (HIAD) technology is currently being considered for multiple atmospheric entry applications as the limitations of traditional entry vehicles have been reached. The Inflatable Re-entry Vehicle Experiment (IRVE) has successfully demonstrated this technology as a viable candidate with a 3.0 m diameter vehicle sub-orbital flight. To further this technology, large scale HIADs (6.0 8.5 m) must be developed and tested. To characterize the performance of large scale HIAD technology new instrumentation concepts must be developed to accommodate the flexible nature inflatable aeroshell. Many of the concepts that are under consideration for the HIAD FY12 subsonic wind tunnel test series are discussed below.

Centrifuge impact cratering experiments: Scaling laws for non-porous targets

NASA Technical Reports Server (NTRS)

Schmidt, Robert M.

1987-01-01

This research is a continuation of an ongoing program whose objective is to perform experiments and to develop scaling relationships for large body impacts onto planetary surfaces. The development of the centrifuge technique has been pioneered by the present investigator and is used to provide experimental data for actual target materials of interest. With both powder and gas guns mounted on a rotor arm, it is possible to match various dimensionless similarity parameters, which have been shown to govern the behavior of large scale impacts. Current work is directed toward the determination of scaling estimates for nonporous targets. The results are presented in summary form.

Reversible Parallel Discrete-Event Execution of Large-scale Epidemic Outbreak Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perumalla, Kalyan S; Seal, Sudip K

2010-01-01

The spatial scale, runtime speed and behavioral detail of epidemic outbreak simulations together require the use of large-scale parallel processing. In this paper, an optimistic parallel discrete event execution of a reaction-diffusion simulation model of epidemic outbreaks is presented, with an implementation over themore » $$\\mu$$sik simulator. Rollback support is achieved with the development of a novel reversible model that combines reverse computation with a small amount of incremental state saving. Parallel speedup and other runtime performance metrics of the simulation are tested on a small (8,192-core) Blue Gene / P system, while scalability is demonstrated on 65,536 cores of a large Cray XT5 system. Scenarios representing large population sizes (up to several hundred million individuals in the largest case) are exercised.« less

A global classification of coastal flood hazard climates associated with large-scale oceanographic forcing.

PubMed

Rueda, Ana; Vitousek, Sean; Camus, Paula; Tomás, Antonio; Espejo, Antonio; Losada, Inigo J; Barnard, Patrick L; Erikson, Li H; Ruggiero, Peter; Reguero, Borja G; Mendez, Fernando J

2017-07-11

Coastal communities throughout the world are exposed to numerous and increasing threats, such as coastal flooding and erosion, saltwater intrusion and wetland degradation. Here, we present the first global-scale analysis of the main drivers of coastal flooding due to large-scale oceanographic factors. Given the large dimensionality of the problem (e.g. spatiotemporal variability in flood magnitude and the relative influence of waves, tides and surge levels), we have performed a computer-based classification to identify geographical areas with homogeneous climates. Results show that 75% of coastal regions around the globe have the potential for very large flooding events with low probabilities (unbounded tails), 82% are tide-dominated, and almost 49% are highly susceptible to increases in flooding frequency due to sea-level rise.

Advances in Parallelization for Large Scale Oct-Tree Mesh Generation

NASA Technical Reports Server (NTRS)

O'Connell, Matthew; Karman, Steve L.

2015-01-01

Despite great advancements in the parallelization of numerical simulation codes over the last 20 years, it is still common to perform grid generation in serial. Generating large scale grids in serial often requires using special "grid generation" compute machines that can have more than ten times the memory of average machines. While some parallel mesh generation techniques have been proposed, generating very large meshes for LES or aeroacoustic simulations is still a challenging problem. An automated method for the parallel generation of very large scale off-body hierarchical meshes is presented here. This work enables large scale parallel generation of off-body meshes by using a novel combination of parallel grid generation techniques and a hybrid "top down" and "bottom up" oct-tree method. Meshes are generated using hardware commonly found in parallel compute clusters. The capability to generate very large meshes is demonstrated by the generation of off-body meshes surrounding complex aerospace geometries. Results are shown including a one billion cell mesh generated around a Predator Unmanned Aerial Vehicle geometry, which was generated on 64 processors in under 45 minutes.

Implementation of a multi-threaded framework for large-scale scientific applications

DOE PAGES

Sexton-Kennedy, E.; Gartung, Patrick; Jones, C. D.; ...

2015-05-22

The CMS experiment has recently completed the development of a multi-threaded capable application framework. In this paper, we will discuss the design, implementation and application of this framework to production applications in CMS. For the 2015 LHC run, this functionality is particularly critical for both our online and offline production applications, which depend on faster turn-around times and a reduced memory footprint relative to before. These applications are complex codes, each including a large number of physics-driven algorithms. While the framework is capable of running a mix of thread-safe and 'legacy' modules, algorithms running in our production applications need tomore » be thread-safe for optimal use of this multi-threaded framework at a large scale. Towards this end, we discuss the types of changes, which were necessary for our algorithms to achieve good performance of our multithreaded applications in a full-scale application. Lastly performance numbers for what has been achieved for the 2015 run are presented.« less

Study of multi-functional precision optical measuring system for large scale equipment

NASA Astrophysics Data System (ADS)

Jiang, Wei; Lao, Dabao; Zhou, Weihu; Zhang, Wenying; Jiang, Xingjian; Wang, Yongxi

2017-10-01

The effective application of high performance measurement technology can greatly improve the large-scale equipment manufacturing ability. Therefore, the geometric parameters measurement, such as size, attitude and position, requires the measurement system with high precision, multi-function, portability and other characteristics. However, the existing measuring instruments, such as laser tracker, total station, photogrammetry system, mostly has single function, station moving and other shortcomings. Laser tracker needs to work with cooperative target, but it can hardly meet the requirement of measurement in extreme environment. Total station is mainly used for outdoor surveying and mapping, it is hard to achieve the demand of accuracy in industrial measurement. Photogrammetry system can achieve a wide range of multi-point measurement, but the measuring range is limited and need to repeatedly move station. The paper presents a non-contact opto-electronic measuring instrument, not only it can work by scanning the measurement path but also measuring the cooperative target by tracking measurement. The system is based on some key technologies, such as absolute distance measurement, two-dimensional angle measurement, automatically target recognition and accurate aiming, precision control, assembly of complex mechanical system and multi-functional 3D visualization software. Among them, the absolute distance measurement module ensures measurement with high accuracy, and the twodimensional angle measuring module provides precision angle measurement. The system is suitable for the case of noncontact measurement of large-scale equipment, it can ensure the quality and performance of large-scale equipment throughout the process of manufacturing and improve the manufacturing ability of large-scale and high-end equipment.

High-Performance Monitoring Architecture for Large-Scale Distributed Systems Using Event Filtering

NASA Technical Reports Server (NTRS)

Maly, K.

1998-01-01

Monitoring is an essential process to observe and improve the reliability and the performance of large-scale distributed (LSD) systems. In an LSD environment, a large number of events is generated by the system components during its execution or interaction with external objects (e.g. users or processes). Monitoring such events is necessary for observing the run-time behavior of LSD systems and providing status information required for debugging, tuning and managing such applications. However, correlated events are generated concurrently and could be distributed in various locations in the applications environment which complicates the management decisions process and thereby makes monitoring LSD systems an intricate task. We propose a scalable high-performance monitoring architecture for LSD systems to detect and classify interesting local and global events and disseminate the monitoring information to the corresponding end- points management applications such as debugging and reactive control tools to improve the application performance and reliability. A large volume of events may be generated due to the extensive demands of the monitoring applications and the high interaction of LSD systems. The monitoring architecture employs a high-performance event filtering mechanism to efficiently process the large volume of event traffic generated by LSD systems and minimize the intrusiveness of the monitoring process by reducing the event traffic flow in the system and distributing the monitoring computation. Our architecture also supports dynamic and flexible reconfiguration of the monitoring mechanism via its Instrumentation and subscription components. As a case study, we show how our monitoring architecture can be utilized to improve the reliability and the performance of the Interactive Remote Instruction (IRI) system which is a large-scale distributed system for collaborative distance learning. The filtering mechanism represents an Intrinsic component integrated with the monitoring architecture to reduce the volume of event traffic flow in the system, and thereby reduce the intrusiveness of the monitoring process. We are developing an event filtering architecture to efficiently process the large volume of event traffic generated by LSD systems (such as distributed interactive applications). This filtering architecture is used to monitor collaborative distance learning application for obtaining debugging and feedback information. Our architecture supports the dynamic (re)configuration and optimization of event filters in large-scale distributed systems. Our work represents a major contribution by (1) survey and evaluating existing event filtering mechanisms In supporting monitoring LSD systems and (2) devising an integrated scalable high- performance architecture of event filtering that spans several kev application domains, presenting techniques to improve the functionality, performance and scalability. This paper describes the primary characteristics and challenges of developing high-performance event filtering for monitoring LSD systems. We survey existing event filtering mechanisms and explain key characteristics for each technique. In addition, we discuss limitations with existing event filtering mechanisms and outline how our architecture will improve key aspects of event filtering.

Accelerating Large Scale Image Analyses on Parallel, CPU-GPU Equipped Systems

PubMed Central

Teodoro, George; Kurc, Tahsin M.; Pan, Tony; Cooper, Lee A.D.; Kong, Jun; Widener, Patrick; Saltz, Joel H.

2014-01-01

The past decade has witnessed a major paradigm shift in high performance computing with the introduction of accelerators as general purpose processors. These computing devices make available very high parallel computing power at low cost and power consumption, transforming current high performance platforms into heterogeneous CPU-GPU equipped systems. Although the theoretical performance achieved by these hybrid systems is impressive, taking practical advantage of this computing power remains a very challenging problem. Most applications are still deployed to either GPU or CPU, leaving the other resource under- or un-utilized. In this paper, we propose, implement, and evaluate a performance aware scheduling technique along with optimizations to make efficient collaborative use of CPUs and GPUs on a parallel system. In the context of feature computations in large scale image analysis applications, our evaluations show that intelligently co-scheduling CPUs and GPUs can significantly improve performance over GPU-only or multi-core CPU-only approaches. PMID:25419545

A practical overview and comparison of certain commercial forensic software tools for processing large-scale digital investigations

NASA Astrophysics Data System (ADS)

Kröger, Knut; Creutzburg, Reiner

2013-05-01

The aim of this paper is to show the usefulness of modern forensic software tools for processing large-scale digital investigations. In particular, we focus on the new version of Nuix 4.2 and compare it with AccessData FTK 4.2, X-Ways Forensics 16.9 and Guidance Encase Forensic 7 regarding its performance, functionality, usability and capability. We will show how these software tools work with large forensic images and how capable they are in examining complex and big data scenarios.

Improving Design Efficiency for Large-Scale Heterogeneous Circuits

NASA Astrophysics Data System (ADS)

Gregerson, Anthony

Despite increases in logic density, many Big Data applications must still be partitioned across multiple computing devices in order to meet their strict performance requirements. Among the most demanding of these applications is high-energy physics (HEP), which uses complex computing systems consisting of thousands of FPGAs and ASICs to process the sensor data created by experiments at particles accelerators such as the Large Hadron Collider (LHC). Designing such computing systems is challenging due to the scale of the systems, the exceptionally high-throughput and low-latency performance constraints that necessitate application-specific hardware implementations, the requirement that algorithms are efficiently partitioned across many devices, and the possible need to update the implemented algorithms during the lifetime of the system. In this work, we describe our research to develop flexible architectures for implementing such large-scale circuits on FPGAs. In particular, this work is motivated by (but not limited in scope to) high-energy physics algorithms for the Compact Muon Solenoid (CMS) experiment at the LHC. To make efficient use of logic resources in multi-FPGA systems, we introduce Multi-Personality Partitioning, a novel form of the graph partitioning problem, and present partitioning algorithms that can significantly improve resource utilization on heterogeneous devices while also reducing inter-chip connections. To reduce the high communication costs of Big Data applications, we also introduce Information-Aware Partitioning, a partitioning method that analyzes the data content of application-specific circuits, characterizes their entropy, and selects circuit partitions that enable efficient compression of data between chips. We employ our information-aware partitioning method to improve the performance of the hardware validation platform for evaluating new algorithms for the CMS experiment. Together, these research efforts help to improve the efficiency and decrease the cost of the developing large-scale, heterogeneous circuits needed to enable large-scale application in high-energy physics and other important areas.

Tracking of large-scale structures in turbulent channel with direct numerical simulation of low Prandtl number passive scalar

NASA Astrophysics Data System (ADS)

Tiselj, Iztok

2014-12-01

Channel flow DNS (Direct Numerical Simulation) at friction Reynolds number 180 and with passive scalars of Prandtl numbers 1 and 0.01 was performed in various computational domains. The "normal" size domain was ˜2300 wall units long and ˜750 wall units wide; size taken from the similar DNS of Moser et al. The "large" computational domain, which is supposed to be sufficient to describe the largest structures of the turbulent flows was 3 times longer and 3 times wider than the "normal" domain. The "very large" domain was 6 times longer and 6 times wider than the "normal" domain. All simulations were performed with the same spatial and temporal resolution. Comparison of the standard and large computational domains shows the velocity field statistics (mean velocity, root-mean-square (RMS) fluctuations, and turbulent Reynolds stresses) that are within 1%-2%. Similar agreement is observed for Pr = 1 temperature fields and can be observed also for the mean temperature profiles at Pr = 0.01. These differences can be attributed to the statistical uncertainties of the DNS. However, second-order moments, i.e., RMS temperature fluctuations of standard and large computational domains at Pr = 0.01 show significant differences of up to 20%. Stronger temperature fluctuations in the "large" and "very large" domains confirm the existence of the large-scale structures. Their influence is more or less invisible in the main velocity field statistics or in the statistics of the temperature fields at Prandtl numbers around 1. However, these structures play visible role in the temperature fluctuations at low Prandtl number, where high temperature diffusivity effectively smears the small-scale structures in the thermal field and enhances the relative contribution of large-scales. These large thermal structures represent some kind of an echo of the large scale velocity structures: the highest temperature-velocity correlations are not observed between the instantaneous temperatures and instantaneous streamwise velocities, but between the instantaneous temperatures and velocities averaged over certain time interval.

A Review of Large-Scale Fracture Experiments Relevant to Pressure Vessel Integrity Under Pressurized Thermal Shock Conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pugh, C.E.

2001-01-29

Numerous large-scale fracture experiments have been performed over the past thirty years to advance fracture mechanics methodologies applicable to thick-wall pressure vessels. This report first identifies major factors important to nuclear reactor pressure vessel (RPV) integrity under pressurized thermal shock (PTS) conditions. It then covers 20 key experiments that have contributed to identifying fracture behavior of RPVs and to validating applicable assessment methodologies. The experiments are categorized according to four types of specimens: (1) cylindrical specimens, (2) pressurized vessels, (3) large plate specimens, and (4) thick beam specimens. These experiments were performed in laboratories in six different countries. This reportmore » serves as a summary of those experiments, and provides a guide to references for detailed information.« less

DistributedFBA.jl: High-level, high-performance flux balance analysis in Julia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heirendt, Laurent; Thiele, Ines; Fleming, Ronan M. T.

Flux balance analysis and its variants are widely used methods for predicting steady-state reaction rates in biochemical reaction networks. The exploration of high dimensional networks with such methods is currently hampered by software performance limitations. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on a subset or all the reactions of large and huge-scale networks, on any number of threads or nodes. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on amore » subset or all the reactions of large and huge-scale networks, on any number of threads or nodes.« less

DistributedFBA.jl: High-level, high-performance flux balance analysis in Julia

DOE PAGES

Heirendt, Laurent; Thiele, Ines; Fleming, Ronan M. T.

2017-01-16

Flux balance analysis and its variants are widely used methods for predicting steady-state reaction rates in biochemical reaction networks. The exploration of high dimensional networks with such methods is currently hampered by software performance limitations. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on a subset or all the reactions of large and huge-scale networks, on any number of threads or nodes. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on amore » subset or all the reactions of large and huge-scale networks, on any number of threads or nodes.« less

Building and measuring a high performance network architecture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kramer, William T.C.; Toole, Timothy; Fisher, Chuck

2001-04-20

Once a year, the SC conferences present a unique opportunity to create and build one of the most complex and highest performance networks in the world. At SC2000, large-scale and complex local and wide area networking connections were demonstrated, including large-scale distributed applications running on different architectures. This project was designed to use the unique opportunity presented at SC2000 to create a testbed network environment and then use that network to demonstrate and evaluate high performance computational and communication applications. This testbed was designed to incorporate many interoperable systems and services and was designed for measurement from the very beginning.more » The end results were key insights into how to use novel, high performance networking technologies and to accumulate measurements that will give insights into the networks of the future.« less

Probabilistic double guarantee kidnapping detection in SLAM.

PubMed

Tian, Yang; Ma, Shugen

2016-01-01

For determining whether kidnapping has happened and which type of kidnapping it is while a robot performs autonomous tasks in an unknown environment, a double guarantee kidnapping detection (DGKD) method has been proposed. The good performance of DGKD in a relative small environment is shown. However, a limitation of DGKD is found in a large-scale environment by our recent work. In order to increase the adaptability of DGKD in a large-scale environment, an improved method called probabilistic double guarantee kidnapping detection is proposed in this paper to combine probability of features' positions and the robot's posture. Simulation results demonstrate the validity and accuracy of the proposed method.

Grindability measurements on low-rank fuels. [Prediction of large pulverizer performance from small scale test equipment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peipho, R.R.; Dougan, D.R.

1981-01-01

Experience has shown that the grinding characteristics of low rank coals are best determined by testing them in a pulverizer. Test results from a small MPS-32 Babcock and Wilcox pulverizer to predict large, full-scale pulverizer performance are presented. The MPS-32 apparatus, test procedure and evaluation of test results is described. The test data show that the Hardgrove apparatus and the ASTM test method must be used with great caution when considering low-rank fuels. The MPS-32 meets the needs for real-machine simulation but with some disadvantages. A smaller pulverizer is desirable. 1 ref.

HRLSim: a high performance spiking neural network simulator for GPGPU clusters.

PubMed

Minkovich, Kirill; Thibeault, Corey M; O'Brien, Michael John; Nogin, Aleksey; Cho, Youngkwan; Srinivasa, Narayan

2014-02-01

Modeling of large-scale spiking neural models is an important tool in the quest to understand brain function and subsequently create real-world applications. This paper describes a spiking neural network simulator environment called HRL Spiking Simulator (HRLSim). This simulator is suitable for implementation on a cluster of general purpose graphical processing units (GPGPUs). Novel aspects of HRLSim are described and an analysis of its performance is provided for various configurations of the cluster. With the advent of inexpensive GPGPU cards and compute power, HRLSim offers an affordable and scalable tool for design, real-time simulation, and analysis of large-scale spiking neural networks.

Visual analysis of inter-process communication for large-scale parallel computing.

PubMed

Muelder, Chris; Gygi, Francois; Ma, Kwan-Liu

2009-01-01

In serial computation, program profiling is often helpful for optimization of key sections of code. When moving to parallel computation, not only does the code execution need to be considered but also communication between the different processes which can induce delays that are detrimental to performance. As the number of processes increases, so does the impact of the communication delays on performance. For large-scale parallel applications, it is critical to understand how the communication impacts performance in order to make the code more efficient. There are several tools available for visualizing program execution and communications on parallel systems. These tools generally provide either views which statistically summarize the entire program execution or process-centric views. However, process-centric visualizations do not scale well as the number of processes gets very large. In particular, the most common representation of parallel processes is a Gantt char t with a row for each process. As the number of processes increases, these charts can become difficult to work with and can even exceed screen resolution. We propose a new visualization approach that affords more scalability and then demonstrate it on systems running with up to 16,384 processes.

Predicting the propagation of concentration and saturation fronts in fixed-bed filters.

PubMed

Callery, O; Healy, M G

2017-10-15

The phenomenon of adsorption is widely exploited across a range of industries to remove contaminants from gases and liquids. Much recent research has focused on identifying low-cost adsorbents which have the potential to be used as alternatives to expensive industry standards like activated carbons. Evaluating these emerging adsorbents entails a considerable amount of labor intensive and costly testing and analysis. This study proposes a simple, low-cost method to rapidly assess the potential of novel media for potential use in large-scale adsorption filters. The filter media investigated in this study were low-cost adsorbents which have been found to be capable of removing dissolved phosphorus from solution, namely: i) aluminum drinking water treatment residual, and ii) crushed concrete. Data collected from multiple small-scale column tests was used to construct a model capable of describing and predicting the progression of adsorbent saturation and the associated effluent concentration breakthrough curves. This model was used to predict the performance of long-term, large-scale filter columns packed with the same media. The approach proved highly successful, and just 24-36 h of experimental data from the small-scale column experiments were found to provide sufficient information to predict the performance of the large-scale filters for up to three months. Copyright © 2017 Elsevier Ltd. All rights reserved.

Supermassive Black Hole Binaries in High Performance Massively Parallel Direct N-body Simulations on Large GPU Clusters

NASA Astrophysics Data System (ADS)

Spurzem, R.; Berczik, P.; Zhong, S.; Nitadori, K.; Hamada, T.; Berentzen, I.; Veles, A.

2012-07-01

Astrophysical Computer Simulations of Dense Star Clusters in Galactic Nuclei with Supermassive Black Holes are presented using new cost-efficient supercomputers in China accelerated by graphical processing cards (GPU). We use large high-accuracy direct N-body simulations with Hermite scheme and block-time steps, parallelised across a large number of nodes on the large scale and across many GPU thread processors on each node on the small scale. A sustained performance of more than 350 Tflop/s for a science run on using simultaneously 1600 Fermi C2050 GPUs is reached; a detailed performance model is presented and studies for the largest GPU clusters in China with up to Petaflop/s performance and 7000 Fermi GPU cards. In our case study we look at two supermassive black holes with equal and unequal masses embedded in a dense stellar cluster in a galactic nucleus. The hardening processes due to interactions between black holes and stars, effects of rotation in the stellar system and relativistic forces between the black holes are simultaneously taken into account. The simulation stops at the complete relativistic merger of the black holes.

High-Throughput Microbore UPLC-MS Metabolic Phenotyping of Urine for Large-Scale Epidemiology Studies.

PubMed

Gray, Nicola; Lewis, Matthew R; Plumb, Robert S; Wilson, Ian D; Nicholson, Jeremy K

2015-06-05

A new generation of metabolic phenotyping centers are being created to meet the increasing demands of personalized healthcare, and this has resulted in a major requirement for economical, high-throughput metabonomic analysis by liquid chromatography-mass spectrometry (LC-MS). Meeting these new demands represents an emerging bioanalytical problem that must be solved if metabolic phenotyping is to be successfully applied to large clinical and epidemiological sample sets. Ultraperformance (UP)LC-MS-based metabolic phenotyping, based on 2.1 mm i.d. LC columns, enables comprehensive metabolic phenotyping but, when employed for the analysis of thousands of samples, results in high solvent usage. The use of UPLC-MS employing 1 mm i.d. columns for metabolic phenotyping rather than the conventional 2.1 mm i.d. methodology shows that the resulting optimized microbore method provided equivalent or superior performance in terms of peak capacity, sensitivity, and robustness. On average, we also observed, when using the microbore scale separation, an increase in response of 2-3 fold over that obtained with the standard 2.1 mm scale method. When applied to the analysis of human urine, the 1 mm scale method showed no decline in performance over the course of 1000 analyses, illustrating that microbore UPLC-MS represents a viable alternative to conventional 2.1 mm i.d. formats for routine large-scale metabolic profiling studies while also resulting in a 75% reduction in solvent usage. The modest increase in sensitivity provided by this methodology also offers the potential to either reduce sample consumption or increase the number of metabolite features detected with confidence due to the increased signal-to-noise ratios obtained. Implementation of this miniaturized UPLC-MS method of metabolic phenotyping results in clear analytical, economic, and environmental benefits for large-scale metabolic profiling studies with similar or improved analytical performance compared to conventional UPLC-MS.

Enhancements for a Dynamic Data Warehousing and Mining System for Large-Scale Human Social Cultural Behavioral (HSBC) Data

DTIC Science & Technology

2016-09-26

Intelligent Automation Incorporated Enhancements for a Dynamic Data Warehousing and Mining ...Enhancements for a Dynamic Data Warehousing and Mining System for N00014-16-P-3014 Large-Scale Human Social Cultural Behavioral (HSBC) Data 5b. GRANT NUMBER...Representative Media Gallery View. We perform Scraawl’s NER algorithm to the text associated with YouTube post, which classifies the named entities into

Large scale static tests of a tilt-nacelle V/STOL propulsion/attitude control system

NASA Technical Reports Server (NTRS)

1978-01-01

The concept of a combined V/STOL propulsion and aircraft attitude control system was subjected to large scale engine tests. The tilt nacelle/attitude control vane package consisted of the T55 powered Hamilton Standard Q-Fan demonstrator. Vane forces, moments, thermal and acoustic characteristics as well as the effects on propulsion system performance were measured under conditions simulating hover in and out of ground effect.

Stereotype Threat, Inquiring about Test Takers' Race and Gender, and Performance on Low-Stakes Tests in a Large-Scale Assessment. Research Report. ETS RR-15-02

ERIC Educational Resources Information Center

Stricker, Lawrence J.; Rock, Donald A.; Bridgeman, Brent

2015-01-01

This study explores stereotype threat on low-stakes tests used in a large-scale assessment, math and reading tests in the Education Longitudinal Study of 2002 (ELS). Issues identified in laboratory research (though not observed in studies of high-stakes tests) were assessed: whether inquiring about their race and gender is related to the…

Distributed Storage Inverter and Legacy Generator Integration Plus Renewables Solution for Microgrids

DTIC Science & Technology

2015-07-01

Reactive kVAR Kilo Watts kW Lithium Ion Li Ion Lithium-Titanate Oxide nLTO Natural gas NG Performance Objectives PO Photovoltaic PV Power ...cloud covered) periods. The demonstration features a large (relative to the overall system power requirements) photovoltaic solar array, whose inverter...microgrid with less expensive power storage instead of large scale energy storage and that the renewable energy with small-scale power storage can

Development of a Two-Stage Microalgae Dewatering Process – A Life Cycle Assessment Approach

PubMed Central

Soomro, Rizwan R.; Zeng, Xianhai; Lu, Yinghua; Lin, Lu; Danquah, Michael K.

2016-01-01

Even though microalgal biomass is leading the third generation biofuel research, significant effort is required to establish an economically viable commercial-scale microalgal biofuel production system. Whilst a significant amount of work has been reported on large-scale cultivation of microalgae using photo-bioreactors and pond systems, research focus on establishing high performance downstream dewatering operations for large-scale processing under optimal economy is limited. The enormous amount of energy and associated cost required for dewatering large-volume microalgal cultures has been the primary hindrance to the development of the needed biomass quantity for industrial-scale microalgal biofuels production. The extremely dilute nature of large-volume microalgal suspension and the small size of microalgae cells in suspension create a significant processing cost during dewatering and this has raised major concerns towards the economic success of commercial-scale microalgal biofuel production as an alternative to conventional petroleum fuels. This article reports an effective framework to assess the performance of different dewatering technologies as the basis to establish an effective two-stage dewatering system. Bioflocculation coupled with tangential flow filtration (TFF) emerged a promising technique with total energy input of 0.041 kWh, 0.05 kg CO2 emissions and a cost of $ 0.0043 for producing 1 kg of microalgae biomass. A streamlined process for operational analysis of two-stage microalgae dewatering technique, encompassing energy input, carbon dioxide emission, and process cost, is presented. PMID:26904075

Clinical Scales Do Not Reliably Identify Acute Ischemic Stroke Patients With Large-Artery Occlusion.

PubMed

Turc, Guillaume; Maïer, Benjamin; Naggara, Olivier; Seners, Pierre; Isabel, Clothilde; Tisserand, Marie; Raynouard, Igor; Edjlali, Myriam; Calvet, David; Baron, Jean-Claude; Mas, Jean-Louis; Oppenheim, Catherine

2016-06-01

It remains debated whether clinical scores can help identify acute ischemic stroke patients with large-artery occlusion and hence improve triage in the era of thrombectomy. We aimed to determine the accuracy of published clinical scores to predict large-artery occlusion. We assessed the performance of 13 clinical scores to predict large-artery occlusion in consecutive patients with acute ischemic stroke undergoing clinical examination and magnetic resonance or computed tomographic angiography ≤6 hours of symptom onset. When no cutoff was published, we used the cutoff maximizing the sum of sensitivity and specificity in our cohort. We also determined, for each score, the cutoff associated with a false-negative rate ≤10%. Of 1004 patients (median National Institute of Health Stroke Scale score, 7; range, 0-40), 328 (32.7%) had an occlusion of the internal carotid artery, M1 segment of the middle cerebral artery, or basilar artery. The highest accuracy (79%; 95% confidence interval, 77-82) was observed for National Institute of Health Stroke Scale score ≥11 and Rapid Arterial Occlusion Evaluation Scale score ≥5. However, these cutoffs were associated with false-negative rates >25%. Cutoffs associated with an false-negative rate ≤10% were 5, 1, and 0 for National Institute of Health Stroke Scale, Rapid Arterial Occlusion Evaluation Scale, and Cincinnati Prehospital Stroke Severity Scale, respectively. Using published cutoffs for triage would result in a loss of opportunity for ≥20% of patients with large-artery occlusion who would be inappropriately sent to a center lacking neurointerventional facilities. Conversely, using cutoffs reducing the false-negative rate to 10% would result in sending almost every patient to a comprehensive stroke center. Our findings, therefore, suggest that intracranial arterial imaging should be performed in all patients with acute ischemic stroke presenting within 6 hours of symptom onset. © 2016 American Heart Association, Inc.

High-Performance Computing Unlocks Innovation at NREL - Video Text Version

Science.gov Websites

scales, data visualizations and large-scale modeling provide insights and test new ideas. But this type most energy-efficient data center in the world. NREL and Hewlett-Packard won an R&D 100 award-the

Large-scale high-throughput computer-aided discovery of advanced materials using cloud computing

NASA Astrophysics Data System (ADS)

Bazhirov, Timur; Mohammadi, Mohammad; Ding, Kevin; Barabash, Sergey

Recent advances in cloud computing made it possible to access large-scale computational resources completely on-demand in a rapid and efficient manner. When combined with high fidelity simulations, they serve as an alternative pathway to enable computational discovery and design of new materials through large-scale high-throughput screening. Here, we present a case study for a cloud platform implemented at Exabyte Inc. We perform calculations to screen lightweight ternary alloys for thermodynamic stability. Due to the lack of experimental data for most such systems, we rely on theoretical approaches based on first-principle pseudopotential density functional theory. We calculate the formation energies for a set of ternary compounds approximated by special quasirandom structures. During an example run we were able to scale to 10,656 CPUs within 7 minutes from the start, and obtain results for 296 compounds within 38 hours. The results indicate that the ultimate formation enthalpy of ternary systems can be negative for some of lightweight alloys, including Li and Mg compounds. We conclude that compared to traditional capital-intensive approach that requires in on-premises hardware resources, cloud computing is agile and cost-effective, yet scalable and delivers similar performance.

Experimental study of detonation of large-scale powder-droplet-vapor mixtures

NASA Astrophysics Data System (ADS)

Bai, C.-H.; Wang, Y.; Xue, K.; Wang, L.-F.

2018-05-01

Large-scale experiments were carried out to investigate the detonation performance of a 1600-m3 ternary cloud consisting of aluminum powder, fuel droplets, and vapor, which were dispersed by a central explosive in a cylindrically stratified configuration. High-frame-rate video cameras and pressure gauges were used to analyze the large-scale explosive dispersal of the mixture and the ensuing blast wave generated by the detonation of the cloud. Special attention was focused on the effect of the descending motion of the charge on the detonation performance of the dispersed ternary cloud. The charge was parachuted by an ensemble of apparatus from the designated height in order to achieve the required terminal velocity when the central explosive was detonated. A descending charge with a terminal velocity of 32 m/s produced a cloud with discernably increased concentration compared with that dispersed from a stationary charge, the detonation of which hence generates a significantly enhanced blast wave beyond the scaled distance of 6 m/kg^{1/3}. The results also show the influence of the descending motion of the charge on the jetting phenomenon and the distorted shock front.

Discrete Event Modeling and Massively Parallel Execution of Epidemic Outbreak Phenomena

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perumalla, Kalyan S; Seal, Sudip K

2011-01-01

In complex phenomena such as epidemiological outbreaks, the intensity of inherent feedback effects and the significant role of transients in the dynamics make simulation the only effective method for proactive, reactive or post-facto analysis. The spatial scale, runtime speed, and behavioral detail needed in detailed simulations of epidemic outbreaks make it necessary to use large-scale parallel processing. Here, an optimistic parallel execution of a new discrete event formulation of a reaction-diffusion simulation model of epidemic propagation is presented to facilitate in dramatically increasing the fidelity and speed by which epidemiological simulations can be performed. Rollback support needed during optimistic parallelmore » execution is achieved by combining reverse computation with a small amount of incremental state saving. Parallel speedup of over 5,500 and other runtime performance metrics of the system are observed with weak-scaling execution on a small (8,192-core) Blue Gene / P system, while scalability with a weak-scaling speedup of over 10,000 is demonstrated on 65,536 cores of a large Cray XT5 system. Scenarios representing large population sizes exceeding several hundreds of millions of individuals in the largest cases are successfully exercised to verify model scalability.« less

A novel computational approach towards the certification of large-scale boson sampling

NASA Astrophysics Data System (ADS)

Huh, Joonsuk

Recent proposals of boson sampling and the corresponding experiments exhibit the possible disproof of extended Church-Turning Thesis. Furthermore, the application of boson sampling to molecular computation has been suggested theoretically. Till now, however, only small-scale experiments with a few photons have been successfully performed. The boson sampling experiments of 20-30 photons are expected to reveal the computational superiority of the quantum device. A novel theoretical proposal for the large-scale boson sampling using microwave photons is highly promising due to the deterministic photon sources and the scalability. Therefore, the certification protocol of large-scale boson sampling experiments should be presented to complete the exciting story. We propose, in this presentation, a computational protocol towards the certification of large-scale boson sampling. The correlations of paired photon modes and the time-dependent characteristic functional with its Fourier component can show the fingerprint of large-scale boson sampling. This work was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education, Science and Technology(NRF-2015R1A6A3A04059773), the ICT R&D program of MSIP/IITP [2015-019, Fundamental Research Toward Secure Quantum Communication] and Mueunjae Institute for Chemistry (MIC) postdoctoral fellowship.

Correlated motion of protein subdomains and large-scale conformational flexibility of RecA protein filament

NASA Astrophysics Data System (ADS)

Yu, Garmay; A, Shvetsov; D, Karelov; D, Lebedev; A, Radulescu; M, Petukhov; V, Isaev-Ivanov

2012-02-01

Based on X-ray crystallographic data available at Protein Data Bank, we have built molecular dynamics (MD) models of homologous recombinases RecA from E. coli and D. radiodurans. Functional form of RecA enzyme, which is known to be a long helical filament, was approximated by a trimer, simulated in periodic water box. The MD trajectories were analyzed in terms of large-scale conformational motions that could be detectable by neutron and X-ray scattering techniques. The analysis revealed that large-scale RecA monomer dynamics can be described in terms of relative motions of 7 subdomains. Motion of C-terminal domain was the major contributor to the overall dynamics of protein. Principal component analysis (PCA) of the MD trajectories in the atom coordinate space showed that rotation of C-domain is correlated with the conformational changes in the central domain and N-terminal domain, that forms the monomer-monomer interface. Thus, even though C-terminal domain is relatively far from the interface, its orientation is correlated with large-scale filament conformation. PCA of the trajectories in the main chain dihedral angle coordinate space implicates a co-existence of a several different large-scale conformations of the modeled trimer. In order to clarify the relationship of independent domain orientation with large-scale filament conformation, we have performed analysis of independent domain motion and its implications on the filament geometry.

Allometry indicates giant eyes of giant squid are not exceptional.

PubMed

Schmitz, Lars; Motani, Ryosuke; Oufiero, Christopher E; Martin, Christopher H; McGee, Matthew D; Gamarra, Ashlee R; Lee, Johanna J; Wainwright, Peter C

2013-02-18

The eyes of giant and colossal squid are among the largest eyes in the history of life. It was recently proposed that sperm whale predation is the main driver of eye size evolution in giant squid, on the basis of an optical model that suggested optimal performance in detecting large luminous visual targets such as whales in the deep sea. However, it is poorly understood how the eye size of giant and colossal squid compares to that of other aquatic organisms when scaling effects are considered. We performed a large-scale comparative study that included 87 squid species and 237 species of acanthomorph fish. While squid have larger eyes than most acanthomorphs, a comparison of relative eye size among squid suggests that giant and colossal squid do not have unusually large eyes. After revising constants used in a previous model we found that large eyes perform equally well in detecting point targets and large luminous targets in the deep sea. The eyes of giant and colossal squid do not appear exceptionally large when allometric effects are considered. It is probable that the giant eyes of giant squid result from a phylogenetically conserved developmental pattern manifested in very large animals. Whatever the cause of large eyes, they appear to have several advantages for vision in the reduced light of the deep mesopelagic zone.

A Short History of Performance Assessment: Lessons Learned.

ERIC Educational Resources Information Center

Madaus, George F.; O'Dwyer, Laura M.

1999-01-01

Places performance assessment in the context of high-stakes uses, describes underlying technologies, and outlines the history of performance testing from 210 B.C.E. to the present. Historical issues of fairness, efficiency, cost, and infrastructure influence contemporary efforts to use performance assessments in large-scale, high-stakes testing…

Wafer scale fabrication of carbon nanotube thin film transistors with high yield

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tian, Boyuan; Liang, Xuelei, E-mail: liangxl@pku.edu.cn, E-mail: ssxie@iphy.ac.cn; Yan, Qiuping

Carbon nanotube thin film transistors (CNT-TFTs) are promising candidates for future high performance and low cost macro-electronics. However, most of the reported CNT-TFTs are fabricated in small quantities on a relatively small size substrate. The yield of large scale fabrication and the performance uniformity of devices on large size substrates should be improved before the CNT-TFTs reach real products. In this paper, 25 200 devices, with various geometries (channel width and channel length), were fabricated on 4-in. size ridged and flexible substrates. Almost 100% device yield were obtained on a rigid substrate with high out-put current (>8 μA/μm), high on/off current ratiomore » (>10{sup 5}), and high mobility (>30 cm{sup 2}/V·s). More importantly, uniform performance in 4-in. area was achieved, and the fabrication process can be scaled up. The results give us more confidence for the real application of the CNT-TFT technology in the near future.« less

Sachem: a chemical cartridge for high-performance substructure search.

PubMed

Kratochvíl, Miroslav; Vondrášek, Jiří; Galgonek, Jakub

2018-05-23

Structure search is one of the valuable capabilities of small-molecule databases. Fingerprint-based screening methods are usually employed to enhance the search performance by reducing the number of calls to the verification procedure. In substructure search, fingerprints are designed to capture important structural aspects of the molecule to aid the decision about whether the molecule contains a given substructure. Currently available cartridges typically provide acceptable search performance for processing user queries, but do not scale satisfactorily with dataset size. We present Sachem, a new open-source chemical cartridge that implements two substructure search methods: The first is a performance-oriented reimplementation of substructure indexing based on the OrChem fingerprint, and the second is a novel method that employs newly designed fingerprints stored in inverted indices. We assessed the performance of both methods on small, medium, and large datasets containing 1, 10, and 94 million compounds, respectively. Comparison of Sachem with other freely available cartridges revealed improvements in overall performance, scaling potential and screen-out efficiency. The Sachem cartridge allows efficient substructure searches in databases of all sizes. The sublinear performance scaling of the second method and the ability to efficiently query large amounts of pre-extracted information may together open the door to new applications for substructure searches.

Exploiting multi-scale parallelism for large scale numerical modelling of laser wakefield accelerators

NASA Astrophysics Data System (ADS)

Fonseca, R. A.; Vieira, J.; Fiuza, F.; Davidson, A.; Tsung, F. S.; Mori, W. B.; Silva, L. O.

2013-12-01

A new generation of laser wakefield accelerators (LWFA), supported by the extreme accelerating fields generated in the interaction of PW-Class lasers and underdense targets, promises the production of high quality electron beams in short distances for multiple applications. Achieving this goal will rely heavily on numerical modelling to further understand the underlying physics and identify optimal regimes, but large scale modelling of these scenarios is computationally heavy and requires the efficient use of state-of-the-art petascale supercomputing systems. We discuss the main difficulties involved in running these simulations and the new developments implemented in the OSIRIS framework to address these issues, ranging from multi-dimensional dynamic load balancing and hybrid distributed/shared memory parallelism to the vectorization of the PIC algorithm. We present the results of the OASCR Joule Metric program on the issue of large scale modelling of LWFA, demonstrating speedups of over 1 order of magnitude on the same hardware. Finally, scalability to over ˜106 cores and sustained performance over ˜2 P Flops is demonstrated, opening the way for large scale modelling of LWFA scenarios.

Utilization of Large Scale Surface Models for Detailed Visibility Analyses

NASA Astrophysics Data System (ADS)

Caha, J.; Kačmařík, M.

2017-11-01

This article demonstrates utilization of large scale surface models with small spatial resolution and high accuracy, acquired from Unmanned Aerial Vehicle scanning, for visibility analyses. The importance of large scale data for visibility analyses on the local scale, where the detail of the surface model is the most defining factor, is described. The focus is not only the classic Boolean visibility, that is usually determined within GIS, but also on so called extended viewsheds that aims to provide more information about visibility. The case study with examples of visibility analyses was performed on river Opava, near the Ostrava city (Czech Republic). The multiple Boolean viewshed analysis and global horizon viewshed were calculated to determine most prominent features and visibility barriers of the surface. Besides that, the extended viewshed showing angle difference above the local horizon, which describes angular height of the target area above the barrier, is shown. The case study proved that large scale models are appropriate data source for visibility analyses on local level. The discussion summarizes possible future applications and further development directions of visibility analyses.

Similarity spectra analysis of high-performance jet aircraft noise.

PubMed

Neilsen, Tracianne B; Gee, Kent L; Wall, Alan T; James, Michael M

2013-04-01

Noise measured in the vicinity of an F-22A Raptor has been compared to similarity spectra found previously to represent mixing noise from large-scale and fine-scale turbulent structures in laboratory-scale jet plumes. Comparisons have been made for three engine conditions using ground-based sideline microphones, which covered a large angular aperture. Even though the nozzle geometry is complex and the jet is nonideally expanded, the similarity spectra do agree with large portions of the measured spectra. Toward the sideline, the fine-scale similarity spectrum is used, while the large-scale similarity spectrum provides a good fit to the area of maximum radiation. Combinations of the two similarity spectra are shown to match the data in between those regions. Surprisingly, a combination of the two is also shown to match the data at the farthest aft angle. However, at high frequencies the degree of congruity between the similarity and the measured spectra changes with engine condition and angle. At the higher engine conditions, there is a systematically shallower measured high-frequency slope, with the largest discrepancy occurring in the regions of maximum radiation.

Rotation and scale change invariant point pattern relaxation matching by the Hopfield neural network

NASA Astrophysics Data System (ADS)

Sang, Nong; Zhang, Tianxu

1997-12-01

Relaxation matching is one of the most relevant methods for image matching. The original relaxation matching technique using point patterns is sensitive to rotations and scale changes. We improve the original point pattern relaxation matching technique to be invariant to rotations and scale changes. A method that makes the Hopfield neural network perform this matching process is discussed. An advantage of this is that the relaxation matching process can be performed in real time with the neural network's massively parallel capability to process information. Experimental results with large simulated images demonstrate the effectiveness and feasibility of the method to perform point patten relaxation matching invariant to rotations and scale changes and the method to perform this matching by the Hopfield neural network. In addition, we show that the method presented can be tolerant to small random error.

Dynamics of large scale impacts on Venus and Earth

NASA Technical Reports Server (NTRS)

Okeefe, John D.; Ahrens, Thomas J.

1993-01-01

Large scale impacts are a key aspect of the accretion and growth of the planets, the evolution of their atmospheres, and the viability of their life forms. We have performed an extensive series of numerical calculations that examined the mechanics of impacts over a broad range of conditions and are now extending these to account for the effects of the planetary atmosphere. We have examined the effects of large scale impacts in which the trapping and compression of an atmosphere during impact is a significant factor in the transfer of energy to the atmosphere. The various energy transfer regimes and where conventional drag and trapping and subsequent compression of atmosphere between the bolide and planetary surface are significant are shown.

Guided growth of large-scale, horizontally aligned arrays of single-walled carbon nanotubes and their use in thin-film transistors.

PubMed

Kocabas, Coskun; Hur, Seung-Hyun; Gaur, Anshu; Meitl, Matthew A; Shim, Moonsub; Rogers, John A

2005-11-01

A convenient process for generating large-scale, horizontally aligned arrays of pristine, single-walled carbon nanotubes (SWNTs) is described. The approach uses guided growth, by chemical vapor deposition (CVD), of SWNTs on miscut single-crystal quartz substrates. Studies of the growth reveal important relationships between the density and alignment of the tubes, the CVD conditions, and the morphology of the quartz. Electrodes and dielectrics patterned on top of these arrays yield thin-film transistors that use the SWNTs as effective thin-film semiconductors. The ability to build high-performance devices of this type suggests significant promise for large-scale aligned arrays of SWNTs in electronics, sensors, and other applications.

Large-scale self-assembled zirconium phosphate smectic layers via a simple spray-coating process

NASA Astrophysics Data System (ADS)

Wong, Minhao; Ishige, Ryohei; White, Kevin L.; Li, Peng; Kim, Daehak; Krishnamoorti, Ramanan; Gunther, Robert; Higuchi, Takeshi; Jinnai, Hiroshi; Takahara, Atsushi; Nishimura, Riichi; Sue, Hung-Jue

2014-04-01

The large-scale assembly of asymmetric colloidal particles is used in creating high-performance fibres. A similar concept is extended to the manufacturing of thin films of self-assembled two-dimensional crystal-type materials with enhanced and tunable properties. Here we present a spray-coating method to manufacture thin, flexible and transparent epoxy films containing zirconium phosphate nanoplatelets self-assembled into a lamellar arrangement aligned parallel to the substrate. The self-assembled mesophase of zirconium phosphate nanoplatelets is stabilized by epoxy pre-polymer and exhibits rheology favourable towards large-scale manufacturing. The thermally cured film forms a mechanically robust coating and shows excellent gas barrier properties at both low- and high humidity levels as a result of the highly aligned and overlapping arrangement of nanoplatelets. This work shows that the large-scale ordering of high aspect ratio nanoplatelets is easier to achieve than previously thought and may have implications in the technological applications for similar materials.

Chronic, Wireless Recordings of Large Scale Brain Activity in Freely Moving Rhesus Monkeys

PubMed Central

Schwarz, David A.; Lebedev, Mikhail A.; Hanson, Timothy L.; Dimitrov, Dragan F.; Lehew, Gary; Meloy, Jim; Rajangam, Sankaranarayani; Subramanian, Vivek; Ifft, Peter J.; Li, Zheng; Ramakrishnan, Arjun; Tate, Andrew; Zhuang, Katie; Nicolelis, Miguel A.L.

2014-01-01

Advances in techniques for recording large-scale brain activity contribute to both the elucidation of neurophysiological principles and the development of brain-machine interfaces (BMIs). Here we describe a neurophysiological paradigm for performing tethered and wireless large-scale recordings based on movable volumetric three-dimensional (3D) multielectrode implants. This approach allowed us to isolate up to 1,800 units per animal and simultaneously record the extracellular activity of close to 500 cortical neurons, distributed across multiple cortical areas, in freely behaving rhesus monkeys. The method is expandable, in principle, to thousands of simultaneously recorded channels. It also allows increased recording longevity (5 consecutive years), and recording of a broad range of behaviors, e.g. social interactions, and BMI paradigms in freely moving primates. We propose that wireless large-scale recordings could have a profound impact on basic primate neurophysiology research, while providing a framework for the development and testing of clinically relevant neuroprostheses. PMID:24776634

Economically viable large-scale hydrogen liquefaction

NASA Astrophysics Data System (ADS)

Cardella, U.; Decker, L.; Klein, H.

2017-02-01

The liquid hydrogen demand, particularly driven by clean energy applications, will rise in the near future. As industrial large scale liquefiers will play a major role within the hydrogen supply chain, production capacity will have to increase by a multiple of today’s typical sizes. The main goal is to reduce the total cost of ownership for these plants by increasing energy efficiency with innovative and simple process designs, optimized in capital expenditure. New concepts must ensure a manageable plant complexity and flexible operability. In the phase of process development and selection, a dimensioning of key equipment for large scale liquefiers, such as turbines and compressors as well as heat exchangers, must be performed iteratively to ensure technological feasibility and maturity. Further critical aspects related to hydrogen liquefaction, e.g. fluid properties, ortho-para hydrogen conversion, and coldbox configuration, must be analysed in detail. This paper provides an overview on the approach, challenges and preliminary results in the development of efficient as well as economically viable concepts for large-scale hydrogen liquefaction.

Large-area photogrammetry based testing of wind turbine blades

NASA Astrophysics Data System (ADS)

Poozesh, Peyman; Baqersad, Javad; Niezrecki, Christopher; Avitabile, Peter; Harvey, Eric; Yarala, Rahul

2017-03-01

An optically based sensing system that can measure the displacement and strain over essentially the entire area of a utility-scale blade leads to a measurement system that can significantly reduce the time and cost associated with traditional instrumentation. This paper evaluates the performance of conventional three dimensional digital image correlation (3D DIC) and three dimensional point tracking (3DPT) approaches over the surface of wind turbine blades and proposes a multi-camera measurement system using dynamic spatial data stitching. The potential advantages for the proposed approach include: (1) full-field measurement distributed over a very large area, (2) the elimination of time-consuming wiring and expensive sensors, and (3) the need for large-channel data acquisition systems. There are several challenges associated with extending the capability of a standard 3D DIC system to measure entire surface of utility scale blades to extract distributed strain, deflection, and modal parameters. This paper only tries to address some of the difficulties including: (1) assessing the accuracy of the 3D DIC system to measure full-field distributed strain and displacement over the large area, (2) understanding the geometrical constraints associated with a wind turbine testing facility (e.g. lighting, working distance, and speckle pattern size), (3) evaluating the performance of the dynamic stitching method to combine two different fields of view by extracting modal parameters from aligned point clouds, and (4) determining the feasibility of employing an output-only system identification to estimate modal parameters of a utility scale wind turbine blade from optically measured data. Within the current work, the results of an optical measurement (one stereo-vision system) performed on a large area over a 50-m utility-scale blade subjected to quasi-static and cyclic loading are presented. The blade certification and testing is typically performed using International Electro-Technical Commission standard (IEC 61400-23). For static tests, the blade is pulled in either flap-wise or edge-wise directions to measure deflection or distributed strain at a few limited locations of a large-sized blade. Additionally, the paper explores the error associated with using a multi-camera system (two stereo-vision systems) in measuring 3D displacement and extracting structural dynamic parameters on a mock set up emulating a utility-scale wind turbine blade. The results obtained in this paper reveal that the multi-camera measurement system has the potential to identify the dynamic characteristics of a very large structure.

Paying for performance: Performance incentives increase desire for the reward object.

PubMed

Hur, Julia D; Nordgren, Loran F

2016-09-01

The current research examines how exposure to performance incentives affects one's desire for the reward object. We hypothesized that the flexible nature of performance incentives creates an attentional fixation on the reward object (e.g., money), which leads people to become more desirous of the rewards. Results from 5 laboratory experiments and 1 large-scale field study provide support for this prediction. When performance was incentivized with monetary rewards, participants reported being more desirous of money (Study 1), put in more effort to earn additional money in an ensuing task (Study 2), and were less willing to donate money to charity (Study 4). We replicated the result with nonmonetary rewards (Study 5). We also found that performance incentives increased attention to the reward object during the task, which in part explains the observed effects (Study 6). A large-scale field study replicated these findings in a real-world setting (Study 7). One laboratory experiment failed to replicate (Study 3). (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Quantitative Missense Variant Effect Prediction Using Large-Scale Mutagenesis Data.

PubMed

Gray, Vanessa E; Hause, Ronald J; Luebeck, Jens; Shendure, Jay; Fowler, Douglas M

2018-01-24

Large datasets describing the quantitative effects of mutations on protein function are becoming increasingly available. Here, we leverage these datasets to develop Envision, which predicts the magnitude of a missense variant's molecular effect. Envision combines 21,026 variant effect measurements from nine large-scale experimental mutagenesis datasets, a hitherto untapped training resource, with a supervised, stochastic gradient boosting learning algorithm. Envision outperforms other missense variant effect predictors both on large-scale mutagenesis data and on an independent test dataset comprising 2,312 TP53 variants whose effects were measured using a low-throughput approach. This dataset was never used for hyperparameter tuning or model training and thus serves as an independent validation set. Envision prediction accuracy is also more consistent across amino acids than other predictors. Finally, we demonstrate that Envision's performance improves as more large-scale mutagenesis data are incorporated. We precompute Envision predictions for every possible single amino acid variant in human, mouse, frog, zebrafish, fruit fly, worm, and yeast proteomes (https://envision.gs.washington.edu/). Copyright © 2017 Elsevier Inc. All rights reserved.

Optimization and large scale computation of an entropy-based moment closure

NASA Astrophysics Data System (ADS)

Kristopher Garrett, C.; Hauck, Cory; Hill, Judith

2015-12-01

We present computational advances and results in the implementation of an entropy-based moment closure, MN, in the context of linear kinetic equations, with an emphasis on heterogeneous and large-scale computing platforms. Entropy-based closures are known in several cases to yield more accurate results than closures based on standard spectral approximations, such as PN, but the computational cost is generally much higher and often prohibitive. Several optimizations are introduced to improve the performance of entropy-based algorithms over previous implementations. These optimizations include the use of GPU acceleration and the exploitation of the mathematical properties of spherical harmonics, which are used as test functions in the moment formulation. To test the emerging high-performance computing paradigm of communication bound simulations, we present timing results at the largest computational scales currently available. These results show, in particular, load balancing issues in scaling the MN algorithm that do not appear for the PN algorithm. We also observe that in weak scaling tests, the ratio in time to solution of MN to PN decreases.

Optimization and large scale computation of an entropy-based moment closure

DOE PAGES

Hauck, Cory D.; Hill, Judith C.; Garrett, C. Kristopher

2015-09-10

We present computational advances and results in the implementation of an entropy-based moment closure, M N, in the context of linear kinetic equations, with an emphasis on heterogeneous and large-scale computing platforms. Entropy-based closures are known in several cases to yield more accurate results than closures based on standard spectral approximations, such as P N, but the computational cost is generally much higher and often prohibitive. Several optimizations are introduced to improve the performance of entropy-based algorithms over previous implementations. These optimizations include the use of GPU acceleration and the exploitation of the mathematical properties of spherical harmonics, which aremore » used as test functions in the moment formulation. To test the emerging high-performance computing paradigm of communication bound simulations, we present timing results at the largest computational scales currently available. Lastly, these results show, in particular, load balancing issues in scaling the M N algorithm that do not appear for the P N algorithm. We also observe that in weak scaling tests, the ratio in time to solution of M N to P N decreases.« less

Strategic partnering to improve community health worker programming and performance: features of a community-health system integrated approach.

PubMed

Naimoli, Joseph F; Perry, Henry B; Townsend, John W; Frymus, Diana E; McCaffery, James A

2015-09-01

There is robust evidence that community health workers (CHWs) in low- and middle-income (LMIC) countries can improve their clients' health and well-being. The evidence on proven strategies to enhance and sustain CHW performance at scale, however, is limited. Nevertheless, CHW stakeholders need guidance and new ideas, which can emerge from the recognition that CHWs function at the intersection of two dynamic, overlapping systems - the formal health system and the community. Although each typically supports CHWs, their support is not necessarily strategic, collaborative or coordinated. We explore a strategic community health system partnership as one approach to improving CHW programming and performance in countries with or intending to mount large-scale CHW programmes. To identify the components of the approach, we drew on a year-long evidence synthesis exercise on CHW performance, synthesis records, author consultations, documentation on large-scale CHW programmes published after the synthesis and other relevant literature. We also established inclusion and exclusion criteria for the components we considered. We examined as well the challenges and opportunities associated with implementing each component. We identified a minimum package of four strategies that provide opportunities for increased cooperation between communities and health systems and address traditional weaknesses in large-scale CHW programmes, and for which implementation is feasible at sub-national levels over large geographic areas and among vulnerable populations in the greatest need of care. We postulate that the CHW performance benefits resulting from the simultaneous implementation of all four strategies could outweigh those that either the health system or community could produce independently. The strategies are (1) joint ownership and design of CHW programmes, (2) collaborative supervision and constructive feedback, (3) a balanced package of incentives, and (4) a practical monitoring system incorporating data from communities and the health system. We believe that strategic partnership between communities and health systems on a minimum package of simultaneously implemented strategies offers the potential for accelerating progress in improving CHW performance at scale. Comparative, retrospective and prospective research can confirm the potential of these strategies. More experience and evidence on strategic partnership can contribute to our understanding of how to achieve sustainable progress in health with equity.

Simulations of hypervelocity impacts for asteroid deflection studies

NASA Astrophysics Data System (ADS)

Heberling, T.; Ferguson, J. M.; Gisler, G. R.; Plesko, C. S.; Weaver, R.

2016-12-01

The possibility of kinetic-impact deflection of threatening near-earth asteroids will be tested for the first time in the proposed AIDA (Asteroid Impact Deflection Assessment) mission, involving two independent spacecraft, NASAs DART (Double Asteroid Redirection Test) and ESAs AIM (Asteroid Impact Mission). The impact of the DART spacecraft onto the secondary of the binary asteroid 65803 Didymos, at a speed of 5 to 7 km/s, is expected to alter the mutual orbit by an observable amount. The velocity imparted to the secondary depends on the geometry and dynamics of the impact, and especially on the momentum enhancement factor, conventionally called beta. We use the Los Alamos hydrocodes Rage and Pagosa to estimate beta in laboratory-scale benchmark experiments and in the large-scale asteroid deflection test. Simulations are performed in two- and three-dimensions, using a variety of equations of state and strength models for both the lab-scale and large-scale cases. This work is being performed as part of a systematic benchmarking study for the AIDA mission that includes other hydrocodes.

Heavy hydrocarbon main injector technology

NASA Technical Reports Server (NTRS)

Fisher, S. C.; Arbit, H. A.

1988-01-01

One of the key components of the Advanced Launch System (ALS) is a large liquid rocket, booster engine. To keep the overall vehicle size and cost down, this engine will probably use liquid oxygen (LOX) and a heavy hydrocarbon, such as RP-1, as propellants and operate at relatively high chamber pressures to increase overall performance. A technology program (Heavy Hydrocarbon Main Injector Technology) is being studied. The main objective of this effort is to develop a logic plan and supporting experimental data base to reduce the risk of developing a large scale (approximately 750,000 lb thrust), high performance main injector system. The overall approach and program plan, from initial analyses to large scale, two dimensional combustor design and test, and the current status of the program are discussed. Progress includes performance and stability analyses, cold flow tests of injector model, design and fabrication of subscale injectors and calorimeter combustors for performance, heat transfer, and dynamic stability tests, and preparation of hot fire test plans. Related, current, high pressure, LOX/RP-1 injector technology efforts are also briefly discussed.

Towards building high performance medical image management system for clinical trials

NASA Astrophysics Data System (ADS)

Wang, Fusheng; Lee, Rubao; Zhang, Xiaodong; Saltz, Joel

2011-03-01

Medical image based biomarkers are being established for therapeutic cancer clinical trials, where image assessment is among the essential tasks. Large scale image assessment is often performed by a large group of experts by retrieving images from a centralized image repository to workstations to markup and annotate images. In such environment, it is critical to provide a high performance image management system that supports efficient concurrent image retrievals in a distributed environment. There are several major challenges: high throughput of large scale image data over the Internet from the server for multiple concurrent client users, efficient communication protocols for transporting data, and effective management of versioning of data for audit trails. We study the major bottlenecks for such a system, propose and evaluate a solution by using a hybrid image storage with solid state drives and hard disk drives, RESTfulWeb Services based protocols for exchanging image data, and a database based versioning scheme for efficient archive of image revision history. Our experiments show promising results of our methods, and our work provides a guideline for building enterprise level high performance medical image management systems.

An economy of scale system's mensuration of large spacecraft

NASA Technical Reports Server (NTRS)

Deryder, L. J.

1981-01-01

The systems technology and cost particulars of using multipurpose platforms versus several sizes of bus type free flyer spacecraft to accomplish the same space experiment missions. Computer models of these spacecraft bus designs were created to obtain data relative to size, weight, power, performance, and cost. To answer the question of whether or not large scale does produce economy, the dominant cost factors were determined and the programmatic effect on individual experiment costs were evaluated.

Large-scale broadband absorber based on metallic tungsten nanocone structure

NASA Astrophysics Data System (ADS)

Wang, Jiaxing; Liang, Yuzhang; Huo, Pengcheng; Wang, Daopeng; Tan, Jun; Xu, Ting

2017-12-01

We report a broadband tungsten absorber based on a nanocone metallic resonant structure fabricated by self-assembly nanosphere lithography. In experimental demonstration, the fabricated absorber has more than 90% average absorption efficiency and shows superior angular tolerance in the entire visible and near-infrared spectral region. We envision that this large-scale nanostructured broadband optical absorber would find great potential in the applications of high performance optoelectronic platforms and solar-thermal energy harvesting systems.

Cache Coherence Protocols for Large-Scale Multiprocessors

DTIC Science & Technology

1990-09-01

and is compared with the other protocols for large-scale machines. In later analysis, this coherence method is designated by the acronym OCPD , which...private read misses 2 6 6 ( OCPD ) private write misses 2 6 6 Table 4.2: Transaction Types and Costs. the performance of the memory system. These...methodologies. Figure 4-2 shows the processor utiliza- tions of the Weather program, with special code in the dyn-nic post-mortem sched- 94 OCPD DlrINB

Supporting large scale applications on networks of workstations

NASA Technical Reports Server (NTRS)

Cooper, Robert; Birman, Kenneth P.

1989-01-01

Distributed applications on networks of workstations are an increasingly common way to satisfy computing needs. However, existing mechanisms for distributed programming exhibit poor performance and reliability as application size increases. Extension of the ISIS distributed programming system to support large scale distributed applications by providing hierarchical process groups is discussed. Incorporation of hierarchy in the program structure and exploitation of this to limit the communication and storage required in any one component of the distributed system is examined.

Cedar-a large scale multiprocessor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gajski, D.; Kuck, D.; Lawrie, D.

1983-01-01

This paper presents an overview of Cedar, a large scale multiprocessor being designed at the University of Illinois. This machine is designed to accommodate several thousand high performance processors which are capable of working together on a single job, or they can be partitioned into groups of processors where each group of one or more processors can work on separate jobs. Various aspects of the machine are described including the control methodology, communication network, optimizing compiler and plans for construction. 13 references.

Performance evaluation of the bioreactor landfill in treatment and stabilisation of mechanically biologically treated municipal solid waste.

PubMed

Lakshmikanthan, P; Sivakumar Babu, G L

2017-03-01

The potential of bioreactor landfills to treat mechanically biologically treated municipal solid waste is analysed in this study. Developing countries like India and China have begun to investigate bioreactor landfills for municipal solid waste management. This article describes the impacts of leachate recirculation on waste stabilisation, landfill gas generation, leachate characteristics and long-term waste settlement. A small-scale and large-scale anaerobic cell were filled with mechanically biologically treated municipal solid waste collected from a landfill site at the outskirts of Bangalore, India. Leachate collected from the same landfill site was recirculated at the rate of 2-5 times a month on a regular basis for 370 days. The total quantity of gas generated was around 416 L in the large-scale reactor and 21 L in the small-scale reactor, respectively. Differential settlements ranging from 20%-26% were observed at two different locations in the large reactor, whereas 30% of settlement was observed in the small reactor. The biological oxygen demand/chemical oxygen demand (COD) ratio indicated that the waste in the large reactor was stabilised at the end of 1 year. The performance of the bioreactor with respect to the reactor size, temperature, landfill gas and leachate quality was analysed and it was found that the bioreactor landfill is efficient in the treatment and stabilising of mechanically biologically treated municipal solid waste.

paraGSEA: a scalable approach for large-scale gene expression profiling

PubMed Central

Peng, Shaoliang; Yang, Shunyun

2017-01-01

Abstract More studies have been conducted using gene expression similarity to identify functional connections among genes, diseases and drugs. Gene Set Enrichment Analysis (GSEA) is a powerful analytical method for interpreting gene expression data. However, due to its enormous computational overhead in the estimation of significance level step and multiple hypothesis testing step, the computation scalability and efficiency are poor on large-scale datasets. We proposed paraGSEA for efficient large-scale transcriptome data analysis. By optimization, the overall time complexity of paraGSEA is reduced from O(mn) to O(m+n), where m is the length of the gene sets and n is the length of the gene expression profiles, which contributes more than 100-fold increase in performance compared with other popular GSEA implementations such as GSEA-P, SAM-GS and GSEA2. By further parallelization, a near-linear speed-up is gained on both workstations and clusters in an efficient manner with high scalability and performance on large-scale datasets. The analysis time of whole LINCS phase I dataset (GSE92742) was reduced to nearly half hour on a 1000 node cluster on Tianhe-2, or within 120 hours on a 96-core workstation. The source code of paraGSEA is licensed under the GPLv3 and available at http://github.com/ysycloud/paraGSEA. PMID:28973463

On the validity of self-report assessment of cognitive abilities: Attentional control scale associations with cognitive performance, emotional adjustment, and personality.

PubMed

Williams, Paula G; Rau, Holly K; Suchy, Yana; Thorgusen, Sommer R; Smith, Timothy W

2017-05-01

Individual differences in attentional control involve the ability to voluntarily direct, shift, and sustain attention. In studies of the role of attentional control in emotional adjustment, social relationships, and vulnerability to the effects of stress, self-report questionnaires are commonly used to measure this construct. Yet, convincing evidence of the association between self-report scales and actual cognitive performance has not been demonstrated. Across 2 independent samples, we examined associations between self-reported attentional control (Attentional Control Scale; ACS), self-reported emotional adjustment, Five-Factor Model personality traits (NEO Personality Inventory-Revised) and performance measures of attentional control. Study 1 examined behavioral performance on the Attention Network Test (ANT; Fan, McCandliss, Sommer, Raz, & Posner, 2002) and the Modified Switching Task (MST; Suchy & Kosson, 2006) in a large sample (n = 315) of healthy young adults. Study 2 (n = 78) examined behavioral performance on standardized neuropsychological tests of attention, including Conner's Continuous Performance Test-II and subtests from the Wechsler Adult Intelligence Scales, Third Edition (WAIS-III; Psychological Corporation, 1997) and Delis-Kaplan Executive Function System (D-KEFS; Delis, Kaplan, & Kramer, 2001). Results indicated that the ACS was largely unrelated to behavioral performance measures of attentional control but was significantly associated with emotional adjustment, neuroticism, and conscientiousness. These findings suggest that although self-reported attentional control may be a useful construct, researchers using the ACS should exercise caution in interpreting it as a proxy for actual cognitive ability or performance. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Tools for Large-Scale Mobile Malware Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bierma, Michael

Analyzing mobile applications for malicious behavior is an important area of re- search, and is made di cult, in part, by the increasingly large number of appli- cations available for the major operating systems. There are currently over 1.2 million apps available in both the Google Play and Apple App stores (the respec- tive o cial marketplaces for the Android and iOS operating systems)[1, 2]. Our research provides two large-scale analysis tools to aid in the detection and analysis of mobile malware. The rst tool we present, Andlantis, is a scalable dynamic analysis system capa- ble of processing over 3000more » Android applications per hour. Traditionally, Android dynamic analysis techniques have been relatively limited in scale due to the compu- tational resources required to emulate the full Android system to achieve accurate execution. Andlantis is the most scalable Android dynamic analysis framework to date, and is able to collect valuable forensic data, which helps reverse-engineers and malware researchers identify and understand anomalous application behavior. We discuss the results of running 1261 malware samples through the system, and provide examples of malware analysis performed with the resulting data. While techniques exist to perform static analysis on a large number of appli- cations, large-scale analysis of iOS applications has been relatively small scale due to the closed nature of the iOS ecosystem, and the di culty of acquiring appli- cations for analysis. The second tool we present, iClone, addresses the challenges associated with iOS research in order to detect application clones within a dataset of over 20,000 iOS applications.« less

Realtime monitoring of bridge scour using remote monitoring technology

DOT National Transportation Integrated Search

2011-02-01

The research performed in this project focuses on the application of instruments including accelerometers : and tiltmeters to monitor bridge scour. First, two large scale laboratory experiments were performed. One : experiment is the simulation of a ...

HEPCloud, a New Paradigm for HEP Facilities: CMS Amazon Web Services Investigation

DOE PAGES

Holzman, Burt; Bauerdick, Lothar A. T.; Bockelman, Brian; ...

2017-09-29

Historically, high energy physics computing has been performed on large purpose-built computing systems. These began as single-site compute facilities, but have evolved into the distributed computing grids used today. Recently, there has been an exponential increase in the capacity and capability of commercial clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is a growing interest among the cloud providers to demonstrate the capability to perform large-scale scientific computing. In this paper, we discuss results from the CMS experiment using the Fermilab HEPCloud facility, which utilized bothmore » local Fermilab resources and virtual machines in the Amazon Web Services Elastic Compute Cloud. We discuss the planning, technical challenges, and lessons learned involved in performing physics workflows on a large-scale set of virtualized resources. Additionally, we will discuss the economics and operational efficiencies when executing workflows both in the cloud and on dedicated resources.« less

HEPCloud, a New Paradigm for HEP Facilities: CMS Amazon Web Services Investigation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Holzman, Burt; Bauerdick, Lothar A. T.; Bockelman, Brian

Historically, high energy physics computing has been performed on large purpose-built computing systems. These began as single-site compute facilities, but have evolved into the distributed computing grids used today. Recently, there has been an exponential increase in the capacity and capability of commercial clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is a growing interest among the cloud providers to demonstrate the capability to perform large-scale scientific computing. In this paper, we discuss results from the CMS experiment using the Fermilab HEPCloud facility, which utilized bothmore » local Fermilab resources and virtual machines in the Amazon Web Services Elastic Compute Cloud. We discuss the planning, technical challenges, and lessons learned involved in performing physics workflows on a large-scale set of virtualized resources. Additionally, we will discuss the economics and operational efficiencies when executing workflows both in the cloud and on dedicated resources.« less

Large-Scale Wind-Tunnel Tests and Evaluation of the Low-Speed Performance of a 35 deg Sweptback Wing Jet Transport Model Equipped with a Blowing Boundary-Layer-Control Flap and Leading-Edge Slat

NASA Technical Reports Server (NTRS)

Hickey, David H.; Aoyagi, Kiyoshi

1960-01-01

A wind-tunnel investigation was conducted to determine the effect of trailing-edge flaps with blowing-type boundary-layer control and leading-edge slats on the low-speed performance of a large-scale jet transport model with four engines and a 35 deg. sweptback wing of aspect ratio 7. Two spanwise extents and several deflections of the trailing-edge flap were tested. Results were obtained with a normal leading-edge and with full-span leading-edge slats. Three-component longitudinal force and moment data and boundary-layer-control flow requirements are presented. The test results are analyzed in terms of possible improvements in low-speed performance. The effect on performance of the source of boundary-layer-control air flow is considered in the analysis.

Computational Issues in Damping Identification for Large Scale Problems

NASA Technical Reports Server (NTRS)

Pilkey, Deborah L.; Roe, Kevin P.; Inman, Daniel J.

1997-01-01

Two damping identification methods are tested for efficiency in large-scale applications. One is an iterative routine, and the other a least squares method. Numerical simulations have been performed on multiple degree-of-freedom models to test the effectiveness of the algorithm and the usefulness of parallel computation for the problems. High Performance Fortran is used to parallelize the algorithm. Tests were performed using the IBM-SP2 at NASA Ames Research Center. The least squares method tested incurs high communication costs, which reduces the benefit of high performance computing. This method's memory requirement grows at a very rapid rate meaning that larger problems can quickly exceed available computer memory. The iterative method's memory requirement grows at a much slower pace and is able to handle problems with 500+ degrees of freedom on a single processor. This method benefits from parallelization, and significant speedup can he seen for problems of 100+ degrees-of-freedom.

Carbon and Carbon Hybrid Materials as Anodes for Sodium-Ion Batteries.

PubMed

Zhong, Xiongwu; Wu, Ying; Zeng, Sifan; Yu, Yan

2018-02-12

Sodium-ion batteries (SIBs) have attracted much attention for application in large-scale grid energy storage owing to the abundance and low cost of sodium sources. However, low energy density and poor cycling life hinder practical application of SIBs. Recently, substantial efforts have been made to develop electrode materials to push forward large-scale practical applications. Carbon materials can be directly used as anode materials, and they show excellent sodium storage performance. Additionally, designing and constructing carbon hybrid materials is an effective strategy to obtain high-performance anodes for SIBs. In this review, we summarize recent research progress on carbon and carbon hybrid materials as anodes for SIBs. Nanostructural design to enhance the sodium storage performance of anode materials is discussed, and we offer some insight into the potential directions of and future high-performance anode materials for SIBs. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Large-scale performance evaluation of Accu-Chek inform II point-of-care glucose meters.

PubMed

Jeong, Tae-Dong; Cho, Eun-Jung; Ko, Dae-Hyun; Lee, Woochang; Chun, Sail; Hong, Ki-Sook; Min, Won-Ki

2016-12-01

The aim of this study was to report the experience of large-scale performance evaluation of 238 Accu-Chek Inform II point-of-care (POC) glucose meters in a single medical setting. The repeatability of 238 POC devices, the within-site imprecision of 12 devices, and the linearity of 49 devices were evaluated using glucose control solutions. The glucose results of 24 POC devices and central laboratory were compared using patient samples. Mean concentration of control solutions was 2.39 mmol/L for Level 1 and 16.52 mmol/L for Level 2. The pooled repeatability coefficient of variation (CV) of the 238 devices was 2.0% for Level 1 and 1.6% for Level 2. The pooled within-site imprecision CV and reproducibility CV of the 12 devices were 2.7% and 2.7% for Level 1, and 1.9%, and 1.9% for Level 2, respectively. The test results of all 49 devices were linear within analytical measurement range from 1.55-31.02 mmol/L. The correlation coefficient for individual POC devices ranged from 0.9967-0.9985. The total correlation coefficient for the 24 devices was 0.998. The Accu-Chek Inform II POC blood glucose meters performed well in terms of precision, linearity, and correlation evaluations. Consensus guidelines for the large-scale performance evaluations of POC devices are required.

Role of substrate quality on IC performance and yields

NASA Technical Reports Server (NTRS)

Thomas, R. N.

1981-01-01

The development of silicon and gallium arsenide crystal growth for the production of large diameter substrates are discussed. Large area substrates of significantly improved compositional purity, dopant distribution and structural perfection on a microscopic as well as macroscopic scale are important requirements. The exploratory use of magnetic fields to suppress convection effects in Czochralski crystal growth is addressed. The growth of large crystals in space appears impractical at present however the efforts to improve substrate quality could benefit from the experiences gained in smaller scale growth experiments conducted in the zero gravity environment of space.

Using stroboscopic flow imaging to validate large-scale computational fluid dynamics simulations

NASA Astrophysics Data System (ADS)

Laurence, Ted A.; Ly, Sonny; Fong, Erika; Shusteff, Maxim; Randles, Amanda; Gounley, John; Draeger, Erik

2017-02-01

The utility and accuracy of computational modeling often requires direct validation against experimental measurements. The work presented here is motivated by taking a combined experimental and computational approach to determine the ability of large-scale computational fluid dynamics (CFD) simulations to understand and predict the dynamics of circulating tumor cells in clinically relevant environments. We use stroboscopic light sheet fluorescence imaging to track the paths and measure the velocities of fluorescent microspheres throughout a human aorta model. Performed over complex physiologicallyrealistic 3D geometries, large data sets are acquired with microscopic resolution over macroscopic distances.

Large-Scale Hybrid Motor Testing. Chapter 10

NASA Technical Reports Server (NTRS)

Story, George

2006-01-01

Hybrid rocket motors can be successfully demonstrated at a small scale virtually anywhere. There have been many suitcase sized portable test stands assembled for demonstration of hybrids. They show the safety of hybrid rockets to the audiences. These small show motors and small laboratory scale motors can give comparative burn rate data for development of different fuel/oxidizer combinations, however questions that are always asked when hybrids are mentioned for large scale applications are - how do they scale and has it been shown in a large motor? To answer those questions, large scale motor testing is required to verify the hybrid motor at its true size. The necessity to conduct large-scale hybrid rocket motor tests to validate the burn rate from the small motors to application size has been documented in several place^'^^.^. Comparison of small scale hybrid data to that of larger scale data indicates that the fuel burn rate goes down with increasing port size, even with the same oxidizer flux. This trend holds for conventional hybrid motors with forward oxidizer injection and HTPB based fuels. While the reason this is occurring would make a great paper or study or thesis, it is not thoroughly understood at this time. Potential causes include the fact that since hybrid combustion is boundary layer driven, the larger port sizes reduce the interaction (radiation, mixing and heat transfer) from the core region of the port. This chapter focuses on some of the large, prototype sized testing of hybrid motors. The largest motors tested have been AMROC s 250K-lbf thrust motor at Edwards Air Force Base and the Hybrid Propulsion Demonstration Program s 250K-lbf thrust motor at Stennis Space Center. Numerous smaller tests were performed to support the burn rate, stability and scaling concepts that went into the development of those large motors.

High performance cellular level agent-based simulation with FLAME for the GPU.

PubMed

Richmond, Paul; Walker, Dawn; Coakley, Simon; Romano, Daniela

2010-05-01

Driven by the availability of experimental data and ability to simulate a biological scale which is of immediate interest, the cellular scale is fast emerging as an ideal candidate for middle-out modelling. As with 'bottom-up' simulation approaches, cellular level simulations demand a high degree of computational power, which in large-scale simulations can only be achieved through parallel computing. The flexible large-scale agent modelling environment (FLAME) is a template driven framework for agent-based modelling (ABM) on parallel architectures ideally suited to the simulation of cellular systems. It is available for both high performance computing clusters (www.flame.ac.uk) and GPU hardware (www.flamegpu.com) and uses a formal specification technique that acts as a universal modelling format. This not only creates an abstraction from the underlying hardware architectures, but avoids the steep learning curve associated with programming them. In benchmarking tests and simulations of advanced cellular systems, FLAME GPU has reported massive improvement in performance over more traditional ABM frameworks. This allows the time spent in the development and testing stages of modelling to be drastically reduced and creates the possibility of real-time visualisation for simple visual face-validation.

Computational study of 3-D hot-spot initiation in shocked insensitive high-explosive

NASA Astrophysics Data System (ADS)

Najjar, F. M.; Howard, W. M.; Fried, L. E.; Manaa, M. R.; Nichols, A., III; Levesque, G.

2012-03-01

High-explosive (HE) material consists of large-sized grains with micron-sized embedded impurities and pores. Under various mechanical/thermal insults, these pores collapse generating hightemperature regions leading to ignition. A hydrodynamic study has been performed to investigate the mechanisms of pore collapse and hot spot initiation in TATB crystals, employing a multiphysics code, ALE3D, coupled to the chemistry module, Cheetah. This computational study includes reactive dynamics. Two-dimensional high-resolution large-scale meso-scale simulations have been performed. The parameter space is systematically studied by considering various shock strengths, pore diameters and multiple pore configurations. Preliminary 3-D simulations are undertaken to quantify the 3-D dynamics.

Cross-axis synchronous flow-through coil planet centrifuge for large-scale preparative counter-current chromatography. III. Performance of large-bore coils in slow planetary motion.

PubMed

Ito, Y; Zhang, T Y

1988-11-25

A preparative capability of the present cross-axis synchronous flow-through coil planet centrifuge was demonstrated with 0.5 cm I.D. multilayer coils. Results of the model studies with short coils indicated that the optimal separations are obtained at low revolutional speeds of 100-200 rpm in both central and lateral coil positions. Preparative separations were successfully performed on 2.5-10 g quantities of test samples in a pair of multilayer coils connected in series with a total capacity of 2.5 l. The sample loading capacity will be scaled up in several folds by increasing the column width.

Ecological Regional Analysis Applied to Campus Sustainability Performance

ERIC Educational Resources Information Center

Weber, Shana; Newman, Julie; Hill, Adam

2017-01-01

Purpose: Sustainability performance in higher education is often evaluated at a generalized large scale. It remains unknown to what extent campus efforts address regional sustainability needs. This study begins to address this gap by evaluating trends in performance through the lens of regional environmental characteristics.…

Novel Miscanthus Germplasm-Based Value Chains: A Life Cycle Assessment

PubMed Central

Wagner, Moritz; Kiesel, Andreas; Hastings, Astley; Iqbal, Yasir; Lewandowski, Iris

2017-01-01

In recent years, considerable progress has been made in miscanthus research: improvement of management practices, breeding of new genotypes, especially for marginal conditions, and development of novel utilization options. The purpose of the current study was a holistic analysis of the environmental performance of such novel miscanthus-based value chains. In addition, the relevance of the analyzed environmental impact categories was assessed. A Life Cycle Assessment was conducted to analyse the environmental performance of the miscanthus-based value chains in 18 impact categories. In order to include the substitution of a reference product, a system expansion approach was used. In addition, a normalization step was applied. This allowed the relevance of these impact categories to be evaluated for each utilization pathway. The miscanthus was cultivated on six sites in Europe (Aberystwyth, Adana, Moscow, Potash, Stuttgart and Wageningen) and the biomass was utilized in the following six pathways: (1) small-scale combustion (heat)—chips; (2) small-scale combustion (heat)—pellets; (3) large-scale combustion (CHP)—biomass baled for transport and storage; (4) large-scale combustion (CHP)—pellets; (5) medium-scale biogas plant—ensiled miscanthus biomass; and (6) large-scale production of insulation material. Thus, in total, the environmental performance of 36 site × pathway combinations was assessed. The comparatively high normalized results of human toxicity, marine, and freshwater ecotoxicity, and freshwater eutrophication indicate the relevance of these impact categories in the assessment of miscanthus-based value chains. Differences between the six sites can almost entirely be attributed to variations in biomass yield. However, the environmental performance of the utilization pathways analyzed varied widely. The largest differences were shown for freshwater and marine ecotoxicity, and freshwater eutrophication. The production of insulation material had the lowest impact on the environment, with net benefits in all impact categories expect three (marine eutrophication, human toxicity, agricultural land occupation). This performance can be explained by the multiple use of the biomass, first as material and subsequently as an energy carrier, and by the substitution of an emission-intensive reference product. The results of this study emphasize the importance of assessing all environmental impacts when selecting appropriate utilization pathways. PMID:28642784

A dynamic regularized gradient model of the subgrid-scale stress tensor for large-eddy simulation

NASA Astrophysics Data System (ADS)

Vollant, A.; Balarac, G.; Corre, C.

2016-02-01

Large-eddy simulation (LES) solves only the large scales part of turbulent flows by using a scales separation based on a filtering operation. The solution of the filtered Navier-Stokes equations requires then to model the subgrid-scale (SGS) stress tensor to take into account the effect of scales smaller than the filter size. In this work, a new model is proposed for the SGS stress model. The model formulation is based on a regularization procedure of the gradient model to correct its unstable behavior. The model is developed based on a priori tests to improve the accuracy of the modeling for both structural and functional performances, i.e., the model ability to locally approximate the SGS unknown term and to reproduce enough global SGS dissipation, respectively. LES is then performed for a posteriori validation. This work is an extension to the SGS stress tensor of the regularization procedure proposed by Balarac et al. ["A dynamic regularized gradient model of the subgrid-scale scalar flux for large eddy simulations," Phys. Fluids 25(7), 075107 (2013)] to model the SGS scalar flux. A set of dynamic regularized gradient (DRG) models is thus made available for both the momentum and the scalar equations. The second objective of this work is to compare this new set of DRG models with direct numerical simulations (DNS), filtered DNS in the case of classic flows simulated with a pseudo-spectral solver and with the standard set of models based on the dynamic Smagorinsky model. Various flow configurations are considered: decaying homogeneous isotropic turbulence, turbulent plane jet, and turbulent channel flows. These tests demonstrate the stable behavior provided by the regularization procedure, along with substantial improvement for velocity and scalar statistics predictions.

Scaling earthquake ground motions for performance-based assessment of buildings

USGS Publications Warehouse

Huang, Y.-N.; Whittaker, A.S.; Luco, N.; Hamburger, R.O.

2011-01-01

The impact of alternate ground-motion scaling procedures on the distribution of displacement responses in simplified structural systems is investigated. Recommendations are provided for selecting and scaling ground motions for performance-based assessment of buildings. Four scaling methods are studied, namely, (1)geometric-mean scaling of pairs of ground motions, (2)spectrum matching of ground motions, (3)first-mode-period scaling to a target spectral acceleration, and (4)scaling of ground motions per the distribution of spectral demands. Data were developed by nonlinear response-history analysis of a large family of nonlinear single degree-of-freedom (SDOF) oscillators that could represent fixed-base and base-isolated structures. The advantages and disadvantages of each scaling method are discussed. The relationship between spectral shape and a ground-motion randomness parameter, is presented. A scaling procedure that explicitly considers spectral shape is proposed. ?? 2011 American Society of Civil Engineers.

A first large-scale flood inundation forecasting model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schumann, Guy J-P; Neal, Jeffrey C.; Voisin, Nathalie

2013-11-04

At present continental to global scale flood forecasting focusses on predicting at a point discharge, with little attention to the detail and accuracy of local scale inundation predictions. Yet, inundation is actually the variable of interest and all flood impacts are inherently local in nature. This paper proposes a first large scale flood inundation ensemble forecasting model that uses best available data and modeling approaches in data scarce areas and at continental scales. The model was built for the Lower Zambezi River in southeast Africa to demonstrate current flood inundation forecasting capabilities in large data-scarce regions. The inundation model domainmore » has a surface area of approximately 170k km2. ECMWF meteorological data were used to force the VIC (Variable Infiltration Capacity) macro-scale hydrological model which simulated and routed daily flows to the input boundary locations of the 2-D hydrodynamic model. Efficient hydrodynamic modeling over large areas still requires model grid resolutions that are typically larger than the width of many river channels that play a key a role in flood wave propagation. We therefore employed a novel sub-grid channel scheme to describe the river network in detail whilst at the same time representing the floodplain at an appropriate and efficient scale. The modeling system was first calibrated using water levels on the main channel from the ICESat (Ice, Cloud, and land Elevation Satellite) laser altimeter and then applied to predict the February 2007 Mozambique floods. Model evaluation showed that simulated flood edge cells were within a distance of about 1 km (one model resolution) compared to an observed flood edge of the event. Our study highlights that physically plausible parameter values and satisfactory performance can be achieved at spatial scales ranging from tens to several hundreds of thousands of km2 and at model grid resolutions up to several km2. However, initial model test runs in forecast mode revealed that it is crucial to account for basin-wide hydrological response time when assessing lead time performances notwithstanding structural limitations in the hydrological model and possibly large inaccuracies in precipitation data.« less

An unbalanced spectra classification method based on entropy

NASA Astrophysics Data System (ADS)

Liu, Zhong-bao; Zhao, Wen-juan

2017-05-01

How to solve the problem of distinguishing the minority spectra from the majority of the spectra is quite important in astronomy. In view of this, an unbalanced spectra classification method based on entropy (USCM) is proposed in this paper to deal with the unbalanced spectra classification problem. USCM greatly improves the performances of the traditional classifiers on distinguishing the minority spectra as it takes the data distribution into consideration in the process of classification. However, its time complexity is exponential with the training size, and therefore, it can only deal with the problem of small- and medium-scale classification. How to solve the large-scale classification problem is quite important to USCM. It can be easily obtained by mathematical computation that the dual form of USCM is equivalent to the minimum enclosing ball (MEB), and core vector machine (CVM) is introduced, USCM based on CVM is proposed to deal with the large-scale classification problem. Several comparative experiments on the 4 subclasses of K-type spectra, 3 subclasses of F-type spectra and 3 subclasses of G-type spectra from Sloan Digital Sky Survey (SDSS) verify USCM and USCM based on CVM perform better than kNN (k nearest neighbor) and SVM (support vector machine) in dealing with the problem of rare spectra mining respectively on the small- and medium-scale datasets and the large-scale datasets.

Quantitative Large-Scale Three-Dimensional Imaging of Human Kidney Biopsies: A Bridge to Precision Medicine in Kidney Disease.

PubMed

Winfree, Seth; Dagher, Pierre C; Dunn, Kenneth W; Eadon, Michael T; Ferkowicz, Michael; Barwinska, Daria; Kelly, Katherine J; Sutton, Timothy A; El-Achkar, Tarek M

2018-06-05

Kidney biopsy remains the gold standard for uncovering the pathogenesis of acute and chronic kidney diseases. However, the ability to perform high resolution, quantitative, molecular and cellular interrogation of this precious tissue is still at a developing stage compared to other fields such as oncology. Here, we discuss recent advances in performing large-scale, three-dimensional (3D), multi-fluorescence imaging of kidney biopsies and quantitative analysis referred to as 3D tissue cytometry. This approach allows the accurate measurement of specific cell types and their spatial distribution in a thick section spanning the entire length of the biopsy. By uncovering specific disease signatures, including rare occurrences, and linking them to the biology in situ, this approach will enhance our understanding of disease pathogenesis. Furthermore, by providing accurate quantitation of cellular events, 3D cytometry may improve the accuracy of prognosticating the clinical course and response to therapy. Therefore, large-scale 3D imaging and cytometry of kidney biopsy is poised to become a bridge towards personalized medicine for patients with kidney disease. © 2018 S. Karger AG, Basel.

Van der Waals epitaxial growth and optoelectronics of large-scale WSe2/SnS2 vertical bilayer p-n junctions.

PubMed

Yang, Tiefeng; Zheng, Biyuan; Wang, Zhen; Xu, Tao; Pan, Chen; Zou, Juan; Zhang, Xuehong; Qi, Zhaoyang; Liu, Hongjun; Feng, Yexin; Hu, Weida; Miao, Feng; Sun, Litao; Duan, Xiangfeng; Pan, Anlian

2017-12-04

High-quality two-dimensional atomic layered p-n heterostructures are essential for high-performance integrated optoelectronics. The studies to date have been largely limited to exfoliated and restacked flakes, and the controlled growth of such heterostructures remains a significant challenge. Here we report the direct van der Waals epitaxial growth of large-scale WSe 2 /SnS 2 vertical bilayer p-n junctions on SiO 2 /Si substrates, with the lateral sizes reaching up to millimeter scale. Multi-electrode field-effect transistors have been integrated on a single heterostructure bilayer. Electrical transport measurements indicate that the field-effect transistors of the junction show an ultra-low off-state leakage current of 10 -14 A and a highest on-off ratio of up to 10 7 . Optoelectronic characterizations show prominent photoresponse, with a fast response time of 500 μs, faster than all the directly grown vertical 2D heterostructures. The direct growth of high-quality van der Waals junctions marks an important step toward high-performance integrated optoelectronic devices and systems.

Sign: large-scale gene network estimation environment for high performance computing.

PubMed

Tamada, Yoshinori; Shimamura, Teppei; Yamaguchi, Rui; Imoto, Seiya; Nagasaki, Masao; Miyano, Satoru

2011-01-01

Our research group is currently developing software for estimating large-scale gene networks from gene expression data. The software, called SiGN, is specifically designed for the Japanese flagship supercomputer "K computer" which is planned to achieve 10 petaflops in 2012, and other high performance computing environments including Human Genome Center (HGC) supercomputer system. SiGN is a collection of gene network estimation software with three different sub-programs: SiGN-BN, SiGN-SSM and SiGN-L1. In these three programs, five different models are available: static and dynamic nonparametric Bayesian networks, state space models, graphical Gaussian models, and vector autoregressive models. All these models require a huge amount of computational resources for estimating large-scale gene networks and therefore are designed to be able to exploit the speed of 10 petaflops. The software will be available freely for "K computer" and HGC supercomputer system users. The estimated networks can be viewed and analyzed by Cell Illustrator Online and SBiP (Systems Biology integrative Pipeline). The software project web site is available at http://sign.hgc.jp/ .

Performance of the first Japanese large-scale facility for radon inhalation experiments with small animals.

PubMed

Ishimori, Yuu; Mitsunobu, Fumihiro; Yamaoka, Kiyonori; Tanaka, Hiroshi; Kataoka, Takahiro; Sakoda, Akihiro

2011-07-01

A radon test facility for small animals was developed in order to increase the statistical validity of differences of the biological response in various radon environments. This paper illustrates the performances of that facility, the first large-scale facility of its kind in Japan. The facility has a capability to conduct approximately 150 mouse-scale tests at the same time. The apparatus for exposing small animals to radon has six animal chamber groups with five independent cages each. Different radon concentrations in each animal chamber group are available. Because the first target of this study is to examine the in vivo behaviour of radon and its effects, the major functions to control radon and to eliminate thoron were examined experimentally. Additionally, radon progeny concentrations and their particle size distributions in the cages were also examined experimentally to be considered in future projects.

PetIGA: A framework for high-performance isogeometric analysis

DOE PAGES

Dalcin, Lisandro; Collier, Nathaniel; Vignal, Philippe; ...

2016-05-25

We present PetIGA, a code framework to approximate the solution of partial differential equations using isogeometric analysis. PetIGA can be used to assemble matrices and vectors which come from a Galerkin weak form, discretized with Non-Uniform Rational B-spline basis functions. We base our framework on PETSc, a high-performance library for the scalable solution of partial differential equations, which simplifies the development of large-scale scientific codes, provides a rich environment for prototyping, and separates parallelism from algorithm choice. We describe the implementation of PetIGA, and exemplify its use by solving a model nonlinear problem. To illustrate the robustness and flexibility ofmore » PetIGA, we solve some challenging nonlinear partial differential equations that include problems in both solid and fluid mechanics. Lastly, we show strong scaling results on up to 4096 cores, which confirm the suitability of PetIGA for large scale simulations.« less

The Case for Modular Redundancy in Large-Scale High Performance Computing Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Engelmann, Christian; Ong, Hong Hoe; Scott, Stephen L

2009-01-01

Recent investigations into resilience of large-scale high-performance computing (HPC) systems showed a continuous trend of decreasing reliability and availability. Newly installed systems have a lower mean-time to failure (MTTF) and a higher mean-time to recover (MTTR) than their predecessors. Modular redundancy is being used in many mission critical systems today to provide for resilience, such as for aerospace and command \\& control systems. The primary argument against modular redundancy for resilience in HPC has always been that the capability of a HPC system, and respective return on investment, would be significantly reduced. We argue that modular redundancy can significantly increasemore » compute node availability as it removes the impact of scale from single compute node MTTR. We further argue that single compute nodes can be much less reliable, and therefore less expensive, and still be highly available, if their MTTR/MTTF ratio is maintained.« less

Users matter : multi-agent systems model of high performance computing cluster users.

DOE Office of Scientific and Technical Information (OSTI.GOV)

North, M. J.; Hood, C. S.; Decision and Information Sciences

2005-01-01

High performance computing clusters have been a critical resource for computational science for over a decade and have more recently become integral to large-scale industrial analysis. Despite their well-specified components, the aggregate behavior of clusters is poorly understood. The difficulties arise from complicated interactions between cluster components during operation. These interactions have been studied by many researchers, some of whom have identified the need for holistic multi-scale modeling that simultaneously includes network level, operating system level, process level, and user level behaviors. Each of these levels presents its own modeling challenges, but the user level is the most complex duemore » to the adaptability of human beings. In this vein, there are several major user modeling goals, namely descriptive modeling, predictive modeling and automated weakness discovery. This study shows how multi-agent techniques were used to simulate a large-scale computing cluster at each of these levels.« less

Finite difference and Runge-Kutta methods for solving vibration problems

NASA Astrophysics Data System (ADS)

Lintang Renganis Radityani, Scolastika; Mungkasi, Sudi

2017-11-01

The vibration of a storey building can be modelled into a system of second order ordinary differential equations. If the number of floors of a building is large, then the result is a large scale system of second order ordinary differential equations. The large scale system is difficult to solve, and if it can be solved, the solution may not be accurate. Therefore, in this paper, we seek for accurate methods for solving vibration problems. We compare the performance of numerical finite difference and Runge-Kutta methods for solving large scale systems of second order ordinary differential equations. The finite difference methods include the forward and central differences. The Runge-Kutta methods include the Euler and Heun methods. Our research results show that the central finite difference and the Heun methods produce more accurate solutions than the forward finite difference and the Euler methods do.

Coastal ocean forecasting with an unstructured grid model in the southern Adriatic and northern Ionian seas

NASA Astrophysics Data System (ADS)

Federico, Ivan; Pinardi, Nadia; Coppini, Giovanni; Oddo, Paolo; Lecci, Rita; Mossa, Michele

2017-01-01

SANIFS (Southern Adriatic Northern Ionian coastal Forecasting System) is a coastal-ocean operational system based on the unstructured grid finite-element three-dimensional hydrodynamic SHYFEM model, providing short-term forecasts. The operational chain is based on a downscaling approach starting from the large-scale system for the entire Mediterranean Basin (MFS, Mediterranean Forecasting System), which provides initial and boundary condition fields to the nested system. The model is configured to provide hydrodynamics and active tracer forecasts both in open ocean and coastal waters of southeastern Italy using a variable horizontal resolution from the open sea (3-4 km) to coastal areas (50-500 m). Given that the coastal fields are driven by a combination of both local (also known as coastal) and deep-ocean forcings propagating along the shelf, the performance of SANIFS was verified both in forecast and simulation mode, first (i) on the large and shelf-coastal scales by comparing with a large-scale survey CTD (conductivity-temperature-depth) in the Gulf of Taranto and then (ii) on the coastal-harbour scale (Mar Grande of Taranto) by comparison with CTD, ADCP (acoustic doppler current profiler) and tide gauge data. Sensitivity tests were performed on initialization conditions (mainly focused on spin-up procedures) and on surface boundary conditions by assessing the reliability of two alternative datasets at different horizontal resolution (12.5 and 6.5 km). The SANIFS forecasts at a lead time of 1 day were compared with the MFS forecasts, highlighting that SANIFS is able to retain the large-scale dynamics of MFS. The large-scale dynamics of MFS are correctly propagated to the shelf-coastal scale, improving the forecast accuracy (+17 % for temperature and +6 % for salinity compared to MFS). Moreover, the added value of SANIFS was assessed on the coastal-harbour scale, which is not covered by the coarse resolution of MFS, where the fields forecasted by SANIFS reproduced the observations well (temperature RMSE equal to 0.11 °C). Furthermore, SANIFS simulations were compared with hourly time series of temperature, sea level and velocity measured on the coastal-harbour scale, showing a good agreement. Simulations in the Gulf of Taranto described a circulation mainly characterized by an anticyclonic gyre with the presence of cyclonic vortexes in shelf-coastal areas. A surface water inflow from the open sea to Mar Grande characterizes the coastal-harbour scale.

LAMMPS strong scaling performance optimization on Blue Gene/Q

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coffman, Paul; Jiang, Wei; Romero, Nichols A.

2014-11-12

LAMMPS "Large-scale Atomic/Molecular Massively Parallel Simulator" is an open-source molecular dynamics package from Sandia National Laboratories. Significant performance improvements in strong-scaling and time-to-solution for this application on IBM's Blue Gene/Q have been achieved through computational optimizations of the OpenMP versions of the short-range Lennard-Jones term of the CHARMM force field and the long-range Coulombic interaction implemented with the PPPM (particle-particle-particle mesh) algorithm, enhanced by runtime parameter settings controlling thread utilization. Additionally, MPI communication performance improvements were made to the PPPM calculation by re-engineering the parallel 3D FFT to use MPICH collectives instead of point-to-point. Performance testing was done using anmore » 8.4-million atom simulation scaling up to 16 racks on the Mira system at Argonne Leadership Computing Facility (ALCF). Speedups resulting from this effort were in some cases over 2x.« less

Base Station Placement Algorithm for Large-Scale LTE Heterogeneous Networks.

PubMed

Lee, Seungseob; Lee, SuKyoung; Kim, Kyungsoo; Kim, Yoon Hyuk

2015-01-01

Data traffic demands in cellular networks today are increasing at an exponential rate, giving rise to the development of heterogeneous networks (HetNets), in which small cells complement traditional macro cells by extending coverage to indoor areas. However, the deployment of small cells as parts of HetNets creates a key challenge for operators' careful network planning. In particular, massive and unplanned deployment of base stations can cause high interference, resulting in highly degrading network performance. Although different mathematical modeling and optimization methods have been used to approach various problems related to this issue, most traditional network planning models are ill-equipped to deal with HetNet-specific characteristics due to their focus on classical cellular network designs. Furthermore, increased wireless data demands have driven mobile operators to roll out large-scale networks of small long term evolution (LTE) cells. Therefore, in this paper, we aim to derive an optimum network planning algorithm for large-scale LTE HetNets. Recently, attempts have been made to apply evolutionary algorithms (EAs) to the field of radio network planning, since they are characterized as global optimization methods. Yet, EA performance often deteriorates rapidly with the growth of search space dimensionality. To overcome this limitation when designing optimum network deployments for large-scale LTE HetNets, we attempt to decompose the problem and tackle its subcomponents individually. Particularly noting that some HetNet cells have strong correlations due to inter-cell interference, we propose a correlation grouping approach in which cells are grouped together according to their mutual interference. Both the simulation and analytical results indicate that the proposed solution outperforms the random-grouping based EA as well as an EA that detects interacting variables by monitoring the changes in the objective function algorithm in terms of system throughput performance.

A High-Performance Sintered Iron Electrode for Rechargeable Alkaline Batteries to Enable Large-Scale Energy Storage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Chenguang; Manohar, Aswin K.; Narayanan, S. R.

Iron-based alkaline rechargeable batteries such as iron-air and nickel-iron batteries are particularly attractive for large-scale energy storage because these batteries can be relatively inexpensive, environment- friendly, and also safe. Therefore, our study has focused on achieving the essential electrical performance and cycling properties needed for the widespread use of iron-based alkaline batteries in stationary and distributed energy storage applications.We have demonstrated for the first time, an advanced sintered iron electrode capable of 3500 cycles of repeated charge and discharge at the 1-hour rate and 100% depth of discharge in each cycle, and an average Coulombic efficiency of over 97%. Suchmore » a robust and efficient rechargeable iron electrode is also capable of continuous discharge at rates as high as 3C with no noticeable loss in utilization. We have shown that the porosity, pore size and thickness of the sintered electrode can be selected rationally to optimize specific capacity, rate capability and robustness. As a result, these advances in the electrical performance and durability of the iron electrode enables iron-based alkaline batteries to be a viable technology solution for meeting the dire need for large-scale electrical energy storage.« less

A High-Performance Sintered Iron Electrode for Rechargeable Alkaline Batteries to Enable Large-Scale Energy Storage

DOE PAGES

Yang, Chenguang; Manohar, Aswin K.; Narayanan, S. R.

2017-01-07

Iron-based alkaline rechargeable batteries such as iron-air and nickel-iron batteries are particularly attractive for large-scale energy storage because these batteries can be relatively inexpensive, environment- friendly, and also safe. Therefore, our study has focused on achieving the essential electrical performance and cycling properties needed for the widespread use of iron-based alkaline batteries in stationary and distributed energy storage applications.We have demonstrated for the first time, an advanced sintered iron electrode capable of 3500 cycles of repeated charge and discharge at the 1-hour rate and 100% depth of discharge in each cycle, and an average Coulombic efficiency of over 97%. Suchmore » a robust and efficient rechargeable iron electrode is also capable of continuous discharge at rates as high as 3C with no noticeable loss in utilization. We have shown that the porosity, pore size and thickness of the sintered electrode can be selected rationally to optimize specific capacity, rate capability and robustness. As a result, these advances in the electrical performance and durability of the iron electrode enables iron-based alkaline batteries to be a viable technology solution for meeting the dire need for large-scale electrical energy storage.« less

Molecular diagnosis of Plasmodium ovale by photo-induced electron transfer fluorogenic primers: PET-PCR

PubMed Central

Akerele, David; Ljolje, Dragan; Talundzic, Eldin; Udhayakumar, Venkatachalam

2017-01-01

Accurate diagnosis of malaria infections continues to be challenging and elusive, especially in the detection of submicroscopic infections. Developing new malaria diagnostic tools that are sensitive enough to detect low-level infections, user friendly, cost effective and capable of performing large scale diagnosis, remains critical. We have designed novel self-quenching photo-induced electron transfer (PET) fluorogenic primers for the detection of P. ovale by real-time PCR. In our study, a total of 173 clinical samples, consisting of different malaria species, were utilized to test this novel PET-PCR primer. The sensitivity and specificity were calculated using nested-PCR as the reference test. The novel primer set demonstrated a sensitivity of 97.5% and a specificity of 99.2% (95% CI 85.2–99.8% and 95.2–99.9% respectively). Furthermore, the limit of detection for P. ovale was found to be 1 parasite/μl. The PET-PCR assay is a new molecular diagnostic tool with comparable performance to other commonly used PCR methods. It is relatively easy to perform, and amiable to large scale malaria surveillance studies and malaria control and elimination programs. Further field validation of this novel primer will be helpful to ascertain the utility for large scale malaria screening programs. PMID:28640824

Molecular diagnosis of Plasmodium ovale by photo-induced electron transfer fluorogenic primers: PET-PCR.

PubMed

Akerele, David; Ljolje, Dragan; Talundzic, Eldin; Udhayakumar, Venkatachalam; Lucchi, Naomi W

2017-01-01

Accurate diagnosis of malaria infections continues to be challenging and elusive, especially in the detection of submicroscopic infections. Developing new malaria diagnostic tools that are sensitive enough to detect low-level infections, user friendly, cost effective and capable of performing large scale diagnosis, remains critical. We have designed novel self-quenching photo-induced electron transfer (PET) fluorogenic primers for the detection of P. ovale by real-time PCR. In our study, a total of 173 clinical samples, consisting of different malaria species, were utilized to test this novel PET-PCR primer. The sensitivity and specificity were calculated using nested-PCR as the reference test. The novel primer set demonstrated a sensitivity of 97.5% and a specificity of 99.2% (95% CI 85.2-99.8% and 95.2-99.9% respectively). Furthermore, the limit of detection for P. ovale was found to be 1 parasite/μl. The PET-PCR assay is a new molecular diagnostic tool with comparable performance to other commonly used PCR methods. It is relatively easy to perform, and amiable to large scale malaria surveillance studies and malaria control and elimination programs. Further field validation of this novel primer will be helpful to ascertain the utility for large scale malaria screening programs.

Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

PubMed

Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

2011-07-01

In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Review of the Need for a Large-scale Test Facility for Research on the Effects of Extreme Winds on Structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

R. G. Little

1999-03-01

The Idaho National Engineering and Environmental Laboratory (INEEL), through the US Department of Energy (DOE), has proposed that a large-scale wind test facility (LSWTF) be constructed to study, in full-scale, the behavior of low-rise structures under simulated extreme wind conditions. To determine the need for, and potential benefits of, such a facility, the Idaho Operations Office of the DOE requested that the National Research Council (NRC) perform an independent assessment of the role and potential value of an LSWTF in the overall context of wind engineering research. The NRC established the Committee to Review the Need for a Large-scale Testmore » Facility for Research on the Effects of Extreme Winds on Structures, under the auspices of the Board on Infrastructure and the Constructed Environment, to perform this assessment. This report conveys the results of the committee's deliberations as well as its findings and recommendations. Data developed at large-scale would enhanced the understanding of how structures, particularly light-frame structures, are affected by extreme winds (e.g., hurricanes, tornadoes, sever thunderstorms, and other events). With a large-scale wind test facility, full-sized structures, such as site-built or manufactured housing and small commercial or industrial buildings, could be tested under a range of wind conditions in a controlled, repeatable environment. At this time, the US has no facility specifically constructed for this purpose. During the course of this study, the committee was confronted by three difficult questions: (1) does the lack of a facility equate to a need for the facility? (2) is need alone sufficient justification for the construction of a facility? and (3) would the benefits derived from information produced in an LSWTF justify the costs of producing that information? The committee's evaluation of the need and justification for an LSWTF was shaped by these realities.« less

Food waste impact on municipal solid waste angle of internal friction.

PubMed

Cho, Young Min; Ko, Jae Hac; Chi, Liqun; Townsend, Timothy G

2011-01-01

The impact of food waste content on the municipal solid waste (MSW) friction angle was studied. Using reconstituted fresh MSW specimens with different food waste content (0%, 40%, 58%, and 80%), 48 small-scale (100-mm-diameter) direct shear tests and 12 large-scale (430 mm × 430 mm) direct shear tests were performed. A stress-controlled large-scale direct shear test device allowing approximately 170-mm sample horizontal displacement was designed and used. At both testing scales, the mobilized internal friction angle of MSW decreased considerably as food waste content increased. As food waste content increased from 0% to 40% and from 40% to 80%, the mobilized internal friction angles (estimated using the mobilized peak (ultimate) shear strengths of the small-scale direct shear tests) decreased from 39° to 31° and from 31° to 7°, respectively, while those of large-scale tests decreased from 36° to 26° and from 26° to 15°, respectively. Most friction angle measurements produced in this study fell within the range of those previously reported for MSW. Copyright © 2010 Elsevier Ltd. All rights reserved.

Water surface assisted synthesis of large-scale carbon nanotube film for high-performance and stretchable supercapacitors.

PubMed

Yu, Minghao; Zhang, Yangfan; Zeng, Yinxiang; Balogun, Muhammad-Sadeeq; Mai, Kancheng; Zhang, Zishou; Lu, Xihong; Tong, Yexiang

2014-07-16

A kind of multiwalled carbon-nanotube (MWCNT)/polydimethylsiloxane (PDMS) film with excellent conductivity and mechanical properties is developed using a facile and large-scale water surface assisted synthesis method. The film can act as a conductive support for electrochemically active PANI nano fibers. A device based on these PANI/MWCNT/PDMS electrodes shows good and stable capacitive behavior, even under static and dynamic stretching conditions. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Real Time Text Analysis

NASA Astrophysics Data System (ADS)

Senthilkumar, K.; Ruchika Mehra Vijayan, E.

2017-11-01

This paper aims to illustrate real time analysis of large scale data. For practical implementation we are performing sentiment analysis on live Twitter feeds for each individual tweet. To analyze sentiments we will train our data model on sentiWordNet, a polarity assigned wordNet sample by Princeton University. Our main objective will be to efficiency analyze large scale data on the fly using distributed computation. Apache Spark and Apache Hadoop eco system is used as distributed computation platform with Java as development language

Large scale obscuration and related climate effects open literature bibliography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Russell, N.A.; Geitgey, J.; Behl, Y.K.

1994-05-01

Large scale obscuration and related climate effects of nuclear detonations first became a matter of concern in connection with the so-called ``Nuclear Winter Controversy`` in the early 1980`s. Since then, the world has changed. Nevertheless, concern remains about the atmospheric effects of nuclear detonations, but the source of concern has shifted. Now it focuses less on global, and more on regional effects and their resulting impacts on the performance of electro-optical and other defense-related systems. This bibliography reflects the modified interest.

Astrophysical N-body Simulations Using Hierarchical Tree Data Structures

NASA Astrophysics Data System (ADS)

Warren, M. S.; Salmon, J. K.

The authors report on recent large astrophysical N-body simulations executed on the Intel Touchstone Delta system. They review the astrophysical motivation and the numerical techniques and discuss steps taken to parallelize these simulations. The methods scale as O(N log N), for large values of N, and also scale linearly with the number of processors. The performance sustained for a duration of 67 h, was between 5.1 and 5.4 Gflop/s on a 512-processor system.

Scale-Up: Improving Large Enrollment Physics Courses

NASA Astrophysics Data System (ADS)

Beichner, Robert

1999-11-01

The Student-Centered Activities for Large Enrollment University Physics (SCALE-UP) project is working to establish a learning environment that will promote increased conceptual understanding, improved problem-solving performance, and greater student satisfaction, while still maintaining class sizes of approximately 100. We are also addressing the new ABET engineering accreditation requirements for inquiry-based learning along with communication and team-oriented skills development. Results of studies of our latest classroom design, plans for future classroom space, and the current iteration of instructional materials will be discussed.

Photographic images captured while sampling for bald eagles near the Davis Pond freshwater diversion structure in Barataria Bay, Louisiana (2009-10)

USGS Publications Warehouse

Jenkins, Jill A.; Jeske, Clinton W.; Allain, Larry K.

2011-01-01

The implementation of freshwater diversions in large-scale coastal restoration schemes presents several scientific and management considerations. Large-scale environmental restructuring necessitates aquatic biomonitoring, and during such field studies, photographs that document animals and habitat may be captured. Among the biomonitoring studies performed in conjunction with the Davis Pond freshwater diversion structure south of New Orleans, Louisiana, only postdiversion study images are readily available, and these are presented here.

The Role of Free Stream Turbulence on the Aerodynamic Performance of a Wind Turbine Blade

NASA Astrophysics Data System (ADS)

Maldonado, Victor; Thormann, Adrien; Meneveau, Charles; Castillo, Luciano

2014-11-01

Effects of free stream turbulence with large integral scale on the aerodynamic performance of an S809 airfoil-based wind turbine blade at low Reynolds number are studied using wind tunnel experiments. A constant chord (2-D) S809 airfoil wind turbine blade model with an operating Reynolds number of 208,000 based on chord length was tested for a range of angles of attack representative of fully attached and stalled flow as encountered in typical wind turbine operation. The smooth-surface blade was subjected to a quasi-laminar free stream with very low free-stream turbulence as well as to elevated free-stream turbulence generated by an active grid. This turbulence contained large-scale eddies with levels of free-stream turbulence intensity of up to 6.14% and an integral length scale of about 60% of chord-length. The pressure distribution was acquired using static pressure taps and the lift was subsequently computed by numerical integration. The wake velocity deficit was measured utilizing hot-wire anemometry to compute the drag coefficient also via integration. In addition, the mean flow was quantified using 2-D particle image velocimetry (PIV) over the suction surface of the blade. Results indicate that turbulence, even with very large-scale eddies comparable in size to the chord-length, significantly improves the aerodynamic performance of the blade by increasing the lift coefficient and overall lift-to-drag ratio, L/D for all angles tested except zero degrees.

The use of data from national and other large-scale user experience surveys in local quality work: a systematic review.

PubMed

Haugum, Mona; Danielsen, Kirsten; Iversen, Hilde Hestad; Bjertnaes, Oyvind

2014-12-01

An important goal for national and large-scale surveys of user experiences is quality improvement. However, large-scale surveys are normally conducted by a professional external surveyor, creating an institutionalized division between the measurement of user experiences and the quality work that is performed locally. The aim of this study was to identify and describe scientific studies related to the use of national and large-scale surveys of user experiences in local quality work. Ovid EMBASE, Ovid MEDLINE, Ovid PsycINFO and the Cochrane Database of Systematic Reviews. Scientific publications about user experiences and satisfaction about the extent to which data from national and other large-scale user experience surveys are used for local quality work in the health services. Themes of interest were identified and a narrative analysis was undertaken. Thirteen publications were included, all differed substantially in several characteristics. The results show that large-scale surveys of user experiences are used in local quality work. The types of follow-up activity varied considerably from conducting a follow-up analysis of user experience survey data to information sharing and more-systematic efforts to use the data as a basis for improving the quality of care. This review shows that large-scale surveys of user experiences are used in local quality work. However, there is a need for more, better and standardized research in this field. The considerable variation in follow-up activities points to the need for systematic guidance on how to use data in local quality work. © The Author 2014. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.

bigSCale: an analytical framework for big-scale single-cell data.

PubMed

Iacono, Giovanni; Mereu, Elisabetta; Guillaumet-Adkins, Amy; Corominas, Roser; Cuscó, Ivon; Rodríguez-Esteban, Gustavo; Gut, Marta; Pérez-Jurado, Luis Alberto; Gut, Ivo; Heyn, Holger

2018-06-01

Single-cell RNA sequencing (scRNA-seq) has significantly deepened our insights into complex tissues, with the latest techniques capable of processing tens of thousands of cells simultaneously. Analyzing increasing numbers of cells, however, generates extremely large data sets, extending processing time and challenging computing resources. Current scRNA-seq analysis tools are not designed to interrogate large data sets and often lack sensitivity to identify marker genes. With bigSCale, we provide a scalable analytical framework to analyze millions of cells, which addresses the challenges associated with large data sets. To handle the noise and sparsity of scRNA-seq data, bigSCale uses large sample sizes to estimate an accurate numerical model of noise. The framework further includes modules for differential expression analysis, cell clustering, and marker identification. A directed convolution strategy allows processing of extremely large data sets, while preserving transcript information from individual cells. We evaluated the performance of bigSCale using both a biological model of aberrant gene expression in patient-derived neuronal progenitor cells and simulated data sets, which underlines the speed and accuracy in differential expression analysis. To test its applicability for large data sets, we applied bigSCale to assess 1.3 million cells from the mouse developing forebrain. Its directed down-sampling strategy accumulates information from single cells into index cell transcriptomes, thereby defining cellular clusters with improved resolution. Accordingly, index cell clusters identified rare populations, such as reelin ( Reln )-positive Cajal-Retzius neurons, for which we report previously unrecognized heterogeneity associated with distinct differentiation stages, spatial organization, and cellular function. Together, bigSCale presents a solution to address future challenges of large single-cell data sets. © 2018 Iacono et al.; Published by Cold Spring Harbor Laboratory Press.

Criterion Validity and Practical Utility of the Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF) in Assessments of Police Officer Candidates.

PubMed

Tarescavage, Anthony M; Corey, David M; Gupton, Herbert M; Ben-Porath, Yossef S

2015-01-01

Minnesota Multiphasic Personality Inventory-2-Restructured Form scores for 145 male police officer candidates were compared with supervisor ratings of field performance and problem behaviors during their initial probationary period. Results indicated that the officers produced meaningfully lower and less variant substantive scale scores compared to the general population. After applying a statistical correction for range restriction, substantive scale scores from all domains assessed by the inventory demonstrated moderate to large correlations with performance criteria. The practical significance of these results was assessed with relative risk ratio analyses that examined the utility of specific cutoffs on scales demonstrating associations with performance criteria.

Performance Status and Change--Measuring Education System Effectiveness with Data from PISA 2000-2009

ERIC Educational Resources Information Center

Lenkeit, Jenny; Caro, Daniel H.

2014-01-01

Reports of international large-scale assessments tend to evaluate and compare education system performance based on absolute scores. And policymakers refer to high-performing and economically prosperous education systems to enhance their own systemic features. But socioeconomic differences between systems compromise the plausibility of those…

Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance.

PubMed

Keerativittayayut, Ruedeerat; Aoki, Ryuta; Sarabi, Mitra Taghizadeh; Jimura, Koji; Nakahara, Kiyoshi

2018-06-18

Although activation/deactivation of specific brain regions have been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here we investigated time-varying functional connectivity patterns across the human brain in periods of 30-40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding. © 2018, Keerativittayayut et al.

Why build a virtual brain? Large-scale neural simulations as jump start for cognitive computing

NASA Astrophysics Data System (ADS)

Colombo, Matteo

2017-03-01

Despite the impressive amount of financial resources recently invested in carrying out large-scale brain simulations, it is controversial what the pay-offs are of pursuing this project. One idea is that from designing, building, and running a large-scale neural simulation, scientists acquire knowledge about the computational performance of the simulating system, rather than about the neurobiological system represented in the simulation. It has been claimed that this knowledge may usher in a new era of neuromorphic, cognitive computing systems. This study elucidates this claim and argues that the main challenge this era is facing is not the lack of biological realism. The challenge lies in identifying general neurocomputational principles for the design of artificial systems, which could display the robust flexibility characteristic of biological intelligence.

Large Scale GW Calculations on the Cori System

NASA Astrophysics Data System (ADS)

Deslippe, Jack; Del Ben, Mauro; da Jornada, Felipe; Canning, Andrew; Louie, Steven

The NERSC Cori system, powered by 9000+ Intel Xeon-Phi processors, represents one of the largest HPC systems for open-science in the United States and the world. We discuss the optimization of the GW methodology for this system, including both node level and system-scale optimizations. We highlight multiple large scale (thousands of atoms) case studies and discuss both absolute application performance and comparison to calculations on more traditional HPC architectures. We find that the GW method is particularly well suited for many-core architectures due to the ability to exploit a large amount of parallelism across many layers of the system. This work was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division, as part of the Computational Materials Sciences Program.

A holistic approach for large-scale derived flood frequency analysis

NASA Astrophysics Data System (ADS)

Dung Nguyen, Viet; Apel, Heiko; Hundecha, Yeshewatesfa; Guse, Björn; Sergiy, Vorogushyn; Merz, Bruno

2017-04-01

Spatial consistency, which has been usually disregarded because of the reported methodological difficulties, is increasingly demanded in regional flood hazard (and risk) assessments. This study aims at developing a holistic approach for deriving flood frequency at large scale consistently. A large scale two-component model has been established for simulating very long-term multisite synthetic meteorological fields and flood flow at many gauged and ungauged locations hence reflecting the spatially inherent heterogeneity. The model has been applied for the region of nearly a half million km2 including Germany and parts of nearby countries. The model performance has been multi-objectively examined with a focus on extreme. By this continuous simulation approach, flood quantiles for the studied region have been derived successfully and provide useful input for a comprehensive flood risk study.

On the Large-Scaling Issues of Cloud-based Applications for Earth Science Dat

NASA Astrophysics Data System (ADS)

Hua, H.

2016-12-01

Next generation science data systems are needed to address the incoming flood of data from new missions such as NASA's SWOT and NISAR where its SAR data volumes and data throughput rates are order of magnitude larger than present day missions. Existing missions, such as OCO-2, may also require high turn-around time for processing different science scenarios where on-premise and even traditional HPC computing environments may not meet the high processing needs. Additionally, traditional means of procuring hardware on-premise are already limited due to facilities capacity constraints for these new missions. Experiences have shown that to embrace efficient cloud computing approaches for large-scale science data systems requires more than just moving existing code to cloud environments. At large cloud scales, we need to deal with scaling and cost issues. We present our experiences on deploying multiple instances of our hybrid-cloud computing science data system (HySDS) to support large-scale processing of Earth Science data products. We will explore optimization approaches to getting best performance out of hybrid-cloud computing as well as common issues that will arise when dealing with large-scale computing. Novel approaches were utilized to do processing on Amazon's spot market, which can potentially offer 75%-90% costs savings but with an unpredictable computing environment based on market forces.

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

Verdon-Kidd, D.; Kiem, A. S.

2008-10-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and/or Indian Ocean Dipole (IOD) are associated with a shift in the relative frequency of wet and dry synoptic types. Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

A laser-sheet flow visualization technique for the large wind tunnels of the National Full-Scale Aerodynamics Complex

NASA Technical Reports Server (NTRS)

Reinath, M. S.; Ross, J. C.

1990-01-01

A flow visualization technique for the large wind tunnels of the National Full Scale Aerodynamics Complex (NFAC) is described. The technique uses a laser sheet generated by the NFAC Long Range Laser Velocimeter (LRLV) to illuminate a smoke-like tracer in the flow. The LRLV optical system is modified slightly, and a scanned mirror is added to generate the sheet. These modifications are described, in addition to the results of an initial performance test conducted in the 80- by 120-Foot Wind Tunnel. During this test, flow visualization was performed in the wake region behind a truck as part of a vehicle drag reduction study. The problems encountered during the test are discussed, in addition to the recommended improvements needed to enhance the performance of the technique for future applications.

Conceptual modelling of E. coli in urban stormwater drains, creeks and rivers

NASA Astrophysics Data System (ADS)

Jovanovic, Dusan; Hathaway, Jon; Coleman, Rhys; Deletic, Ana; McCarthy, David T.

2017-12-01

Accurate estimation of faecal microorganism levels in water systems, such as stormwater drains, creeks and rivers, is needed for appropriate assessment of impacts on receiving water bodies and the risks to human health. The underlying hypothesis for this work is that a single conceptual model (the MicroOrganism Prediction in Urban Stormwater model - i.e. MOPUS) can adequately simulate microbial dynamics over a variety of water systems and wide range of scales; something which has not been previously tested. Additionally, the application of radar precipitation data for improvement of the model performance at these scales via more accurate areal averaged rainfall intensities was tested. Six comprehensive Escherichia coli (E. coli) datasets collected from five catchments in south-eastern Australia and one catchment in Raleigh, USA, were used to calibrate the model. The MOPUS rainfall-runoff model performed well at all scales (Nash-Sutcliffe E for instantaneous flow rates between 0.70 and 0.93). Sensitivity analysis showed that wet weather urban stormwater flows can be modelled with only three of the five rainfall runoff model parameters: routing coefficient (K), effective imperviousness (IMP) and time of concentration (TOC). The model's performance for representing instantaneous E. coli fluctuations ranged from 0.17 to 0.45 in catchments drained via pipe or open creek, and was the highest for a large riverine catchment (0.64); performing similarly, if not better, than other microbial models in literature. The model could also capture the variability in event mean concentrations (E = 0.17-0.57) and event loads (E = 0.32-0.97) at all scales. Application of weather radar-derived rainfall inputs caused lower overall performance compared to using gauged rainfall inputs in representing both flow and E. coli levels in urban drain catchments, with the performance improving with increasing catchment size and being comparable to the models that use gauged rainfall inputs at the large riverine catchment. These results demonstrate the potential of the MOPUS model and its ability to be applied to a wide range of catchment scales, including large riverine systems.

Large-scale Advanced Prop-fan (LAP) technology assessment report

NASA Technical Reports Server (NTRS)

Degeorge, C. L.

1988-01-01

The technologically significant findings and accomplishments of the Large Scale Advanced Prop-Fan (LAP) program in the areas of aerodynamics, aeroelasticity, acoustics and materials and fabrication are described. The extent to which the program goals related to these disciplines were achieved is discussed, and recommendations for additional research are presented. The LAP program consisted of the design, manufacture and testing of a near full-scale Prop-Fan or advanced turboprop capable of operating efficiently at speeds to Mach .8. An aeroelastically scaled model of the LAP was also designed and fabricated. The goal of the program was to acquire data on Prop-Fan performance that would indicate the technology readiness of Prop-Fans for practical applications in commercial and military aviation.

Role of optometry school in single day large scale school vision testing

PubMed Central

Anuradha, N; Ramani, Krishnakumar

2015-01-01

Background: School vision testing aims at identification and management of refractive errors. Large-scale school vision testing using conventional methods is time-consuming and demands a lot of chair time from the eye care professionals. A new strategy involving a school of optometry in single day large scale school vision testing is discussed. Aim: The aim was to describe a new approach of performing vision testing of school children on a large scale in a single day. Materials and Methods: A single day vision testing strategy was implemented wherein 123 members (20 teams comprising optometry students and headed by optometrists) conducted vision testing for children in 51 schools. School vision testing included basic vision screening, refraction, frame measurements, frame choice and referrals for other ocular problems. Results: A total of 12448 children were screened, among whom 420 (3.37%) were identified to have refractive errors. 28 (1.26%) children belonged to the primary, 163 to middle (9.80%), 129 (4.67%) to secondary and 100 (1.73%) to the higher secondary levels of education respectively. 265 (2.12%) children were referred for further evaluation. Conclusion: Single day large scale school vision testing can be adopted by schools of optometry to reach a higher number of children within a short span. PMID:25709271

Validity of Scores for a Developmental Writing Scale Based on Automated Scoring

ERIC Educational Resources Information Center

Attali, Yigal; Powers, Donald

2009-01-01

A developmental writing scale for timed essay-writing performance was created on the basis of automatically computed indicators of writing fluency, word choice, and conventions of standard written English. In a large-scale data collection effort that involved a national sample of more than 12,000 students from 4th, 6th, 8th, 10th, and 12th grade,…

Parallel Clustering Algorithm for Large-Scale Biological Data Sets

PubMed Central

Wang, Minchao; Zhang, Wu; Ding, Wang; Dai, Dongbo; Zhang, Huiran; Xie, Hao; Chen, Luonan; Guo, Yike; Xie, Jiang

2014-01-01

Backgrounds Recent explosion of biological data brings a great challenge for the traditional clustering algorithms. With increasing scale of data sets, much larger memory and longer runtime are required for the cluster identification problems. The affinity propagation algorithm outperforms many other classical clustering algorithms and is widely applied into the biological researches. However, the time and space complexity become a great bottleneck when handling the large-scale data sets. Moreover, the similarity matrix, whose constructing procedure takes long runtime, is required before running the affinity propagation algorithm, since the algorithm clusters data sets based on the similarities between data pairs. Methods Two types of parallel architectures are proposed in this paper to accelerate the similarity matrix constructing procedure and the affinity propagation algorithm. The memory-shared architecture is used to construct the similarity matrix, and the distributed system is taken for the affinity propagation algorithm, because of its large memory size and great computing capacity. An appropriate way of data partition and reduction is designed in our method, in order to minimize the global communication cost among processes. Result A speedup of 100 is gained with 128 cores. The runtime is reduced from serval hours to a few seconds, which indicates that parallel algorithm is capable of handling large-scale data sets effectively. The parallel affinity propagation also achieves a good performance when clustering large-scale gene data (microarray) and detecting families in large protein superfamilies. PMID:24705246

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

DOE PAGES

Bicer, Tekin; Gursoy, Doga; Andrade, Vincent De; ...

2017-01-28

Here, synchrotron light source and detector technologies enable scientists to perform advanced experiments. These scientific instruments and experiments produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used data acquisition technique at light sources is Computed Tomography, which can generate tens of GB/s depending on x-ray range. A large-scale tomographic dataset, such as mouse brain, may require hours of computation time with a medium size workstation. In this paper, we present Trace, a data-intensive computing middleware we developed for implementation and parallelization of iterative tomographic reconstruction algorithms. Tracemore » provides fine-grained reconstruction of tomography datasets using both (thread level) shared memory and (process level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations we have done on the replicated reconstruction objects and evaluate them using a shale and a mouse brain sinogram. Our experimental evaluations show that the applied optimizations and parallelization techniques can provide 158x speedup (using 32 compute nodes) over single core configuration, which decreases the reconstruction time of a sinogram (with 4501 projections and 22400 detector resolution) from 12.5 hours to less than 5 minutes per iteration.« less

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bicer, Tekin; Gursoy, Doga; Andrade, Vincent De

Here, synchrotron light source and detector technologies enable scientists to perform advanced experiments. These scientific instruments and experiments produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used data acquisition technique at light sources is Computed Tomography, which can generate tens of GB/s depending on x-ray range. A large-scale tomographic dataset, such as mouse brain, may require hours of computation time with a medium size workstation. In this paper, we present Trace, a data-intensive computing middleware we developed for implementation and parallelization of iterative tomographic reconstruction algorithms. Tracemore » provides fine-grained reconstruction of tomography datasets using both (thread level) shared memory and (process level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations we have done on the replicated reconstruction objects and evaluate them using a shale and a mouse brain sinogram. Our experimental evaluations show that the applied optimizations and parallelization techniques can provide 158x speedup (using 32 compute nodes) over single core configuration, which decreases the reconstruction time of a sinogram (with 4501 projections and 22400 detector resolution) from 12.5 hours to less than 5 minutes per iteration.« less

Benchmarking of protein descriptor sets in proteochemometric modeling (part 2): modeling performance of 13 amino acid descriptor sets

PubMed Central

2013-01-01

Background While a large body of work exists on comparing and benchmarking descriptors of molecular structures, a similar comparison of protein descriptor sets is lacking. Hence, in the current work a total of 13 amino acid descriptor sets have been benchmarked with respect to their ability of establishing bioactivity models. The descriptor sets included in the study are Z-scales (3 variants), VHSE, T-scales, ST-scales, MS-WHIM, FASGAI, BLOSUM, a novel protein descriptor set (termed ProtFP (4 variants)), and in addition we created and benchmarked three pairs of descriptor combinations. Prediction performance was evaluated in seven structure-activity benchmarks which comprise Angiotensin Converting Enzyme (ACE) dipeptidic inhibitor data, and three proteochemometric data sets, namely (1) GPCR ligands modeled against a GPCR panel, (2) enzyme inhibitors (NNRTIs) with associated bioactivities against a set of HIV enzyme mutants, and (3) enzyme inhibitors (PIs) with associated bioactivities on a large set of HIV enzyme mutants. Results The amino acid descriptor sets compared here show similar performance (<0.1 log units RMSE difference and <0.1 difference in MCC), while errors for individual proteins were in some cases found to be larger than those resulting from descriptor set differences ( > 0.3 log units RMSE difference and >0.7 difference in MCC). Combining different descriptor sets generally leads to better modeling performance than utilizing individual sets. The best performers were Z-scales (3) combined with ProtFP (Feature), or Z-Scales (3) combined with an average Z-Scale value for each target, while ProtFP (PCA8), ST-Scales, and ProtFP (Feature) rank last. Conclusions While amino acid descriptor sets capture different aspects of amino acids their ability to be used for bioactivity modeling is still – on average – surprisingly similar. Still, combining sets describing complementary information consistently leads to small but consistent improvement in modeling performance (average MCC 0.01 better, average RMSE 0.01 log units lower). Finally, performance differences exist between the targets compared thereby underlining that choosing an appropriate descriptor set is of fundamental for bioactivity modeling, both from the ligand- as well as the protein side. PMID:24059743

``Large''- vs Small-scale friction control in turbulent channel flow

NASA Astrophysics Data System (ADS)

Canton, Jacopo; Örlü, Ramis; Chin, Cheng; Schlatter, Philipp

2017-11-01

We reconsider the ``large-scale'' control scheme proposed by Hussain and co-workers (Phys. Fluids 10, 1049-1051 1998 and Phys. Rev. Fluids, 2, 62601 2017), using new direct numerical simulations (DNS). The DNS are performed in a turbulent channel at friction Reynolds number Reτ of up to 550 in order to eliminate low-Reynolds-number effects. The purpose of the present contribution is to re-assess this control method in the light of more modern developments in the field, in particular also related to the discovery of (very) large-scale motions. The goals of the paper are as follows: First, we want to better characterise the physics of the control, and assess what external contribution (vortices, forcing, wall motion) are actually needed. Then, we investigate the optimal parameters and, finally, determine which aspects of this control technique actually scale in outer units and can therefore be of use in practical applications. In addition to discussing the mentioned drag-reduction effects, the present contribution will also address the potential effect of the naturally occurring large-scale motions on frictional drag, and give indications on the physical processes for potential drag reduction possible at all Reynolds numbers.

A cooperative strategy for parameter estimation in large scale systems biology models.

PubMed

Villaverde, Alejandro F; Egea, Jose A; Banga, Julio R

2012-06-22

Mathematical models play a key role in systems biology: they summarize the currently available knowledge in a way that allows to make experimentally verifiable predictions. Model calibration consists of finding the parameters that give the best fit to a set of experimental data, which entails minimizing a cost function that measures the goodness of this fit. Most mathematical models in systems biology present three characteristics which make this problem very difficult to solve: they are highly non-linear, they have a large number of parameters to be estimated, and the information content of the available experimental data is frequently scarce. Hence, there is a need for global optimization methods capable of solving this problem efficiently. A new approach for parameter estimation of large scale models, called Cooperative Enhanced Scatter Search (CeSS), is presented. Its key feature is the cooperation between different programs ("threads") that run in parallel in different processors. Each thread implements a state of the art metaheuristic, the enhanced Scatter Search algorithm (eSS). Cooperation, meaning information sharing between threads, modifies the systemic properties of the algorithm and allows to speed up performance. Two parameter estimation problems involving models related with the central carbon metabolism of E. coli which include different regulatory levels (metabolic and transcriptional) are used as case studies. The performance and capabilities of the method are also evaluated using benchmark problems of large-scale global optimization, with excellent results. The cooperative CeSS strategy is a general purpose technique that can be applied to any model calibration problem. Its capability has been demonstrated by calibrating two large-scale models of different characteristics, improving the performance of previously existing methods in both cases. The cooperative metaheuristic presented here can be easily extended to incorporate other global and local search solvers and specific structural information for particular classes of problems.

A cooperative strategy for parameter estimation in large scale systems biology models

PubMed Central

2012-01-01

Background Mathematical models play a key role in systems biology: they summarize the currently available knowledge in a way that allows to make experimentally verifiable predictions. Model calibration consists of finding the parameters that give the best fit to a set of experimental data, which entails minimizing a cost function that measures the goodness of this fit. Most mathematical models in systems biology present three characteristics which make this problem very difficult to solve: they are highly non-linear, they have a large number of parameters to be estimated, and the information content of the available experimental data is frequently scarce. Hence, there is a need for global optimization methods capable of solving this problem efficiently. Results A new approach for parameter estimation of large scale models, called Cooperative Enhanced Scatter Search (CeSS), is presented. Its key feature is the cooperation between different programs (“threads”) that run in parallel in different processors. Each thread implements a state of the art metaheuristic, the enhanced Scatter Search algorithm (eSS). Cooperation, meaning information sharing between threads, modifies the systemic properties of the algorithm and allows to speed up performance. Two parameter estimation problems involving models related with the central carbon metabolism of E. coli which include different regulatory levels (metabolic and transcriptional) are used as case studies. The performance and capabilities of the method are also evaluated using benchmark problems of large-scale global optimization, with excellent results. Conclusions The cooperative CeSS strategy is a general purpose technique that can be applied to any model calibration problem. Its capability has been demonstrated by calibrating two large-scale models of different characteristics, improving the performance of previously existing methods in both cases. The cooperative metaheuristic presented here can be easily extended to incorporate other global and local search solvers and specific structural information for particular classes of problems. PMID:22727112

Partially Filled Aperture Interferometric Telescopes: Achieving Large Aperture and Coronagraphic Performance

NASA Astrophysics Data System (ADS)

Moretto, G.; Kuhn, J.; Langlois, M.; Berdugyna, S.; Tallon, M.

2017-09-01

Telescopes larger than currently planned 30-m class instruments must break the mass-aperture scaling relationship of the Keck-generation of multi-segmented telescopes. Partially filled aperture, but highly redundant baseline interferometric instruments may achieve both large aperture and high dynamic range. The PLANETS FOUNDATION group has explored hybrid telescope-interferometer concepts for narrow-field optical systems that exhibit coronagraphic performance over narrow fields-of-view. This paper describes how the Colossus and Exo-Life Finder telescope designs achieve 10x lower moving masses than current Extremely Large Telescopes.

Structural Similitude and Scaling Laws

NASA Technical Reports Server (NTRS)

Simitses, George J.

1998-01-01

Aircraft and spacecraft comprise the class of aerospace structures that require efficiency and wisdom in design, sophistication and accuracy in analysis and numerous and careful experimental evaluations of components and prototype, in order to achieve the necessary system reliability, performance and safety. Preliminary and/or concept design entails the assemblage of system mission requirements, system expected performance and identification of components and their connections as well as of manufacturing and system assembly techniques. This is accomplished through experience based on previous similar designs, and through the possible use of models to simulate the entire system characteristics. Detail design is heavily dependent on information and concepts derived from the previous steps. This information identifies critical design areas which need sophisticated analyses, and design and redesign procedures to achieve the expected component performance. This step may require several independent analysis models, which, in many instances, require component testing. The last step in the design process, before going to production, is the verification of the design. This step necessitates the production of large components and prototypes in order to test component and system analytical predictions and verify strength and performance requirements under the worst loading conditions that the system is expected to encounter in service. Clearly then, full-scale testing is in many cases necessary and always very expensive. In the aircraft industry, in addition to full-scale tests, certification and safety necessitate large component static and dynamic testing. Such tests are extremely difficult, time consuming and definitely absolutely necessary. Clearly, one should not expect that prototype testing will be totally eliminated in the aircraft industry. It is hoped, though, that we can reduce full-scale testing to a minimum. Full-scale large component testing is necessary in other industries as well, Ship building, automobile and railway car construction all rely heavily on testing. Regardless of the application, a scaled-down (by a large factor) model (scale model) which closely represents the structural behavior of the full-scale system (prototype) can prove to be an extremely beneficial tool. This possible development must be based on the existence of certain structural parameters that control the behavior of a structural system when acted upon by static and/or dynamic loads. If such structural parameters exist, a scaled-down replica can be built, which will duplicate the response of the full-scale system. The two systems are then said to be structurally similar. The term, then, that best describes this similarity is structural similitude. Similarity of systems requires that the relevant system parameters be identical and these systems be governed by a unique set of characteristic equations. Thus, if a relation or equation of variables is written for a system, it is valid for all systems which are similar to it. Each variable in a model is proportional to the corresponding variable of the prototype. This ratio, which plays an essential role in predicting the relationship between the model and its prototype, is called the scale factor.

New design for interfacing computers to the Octopus network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sloan, L.J.

1977-03-14

The Lawrence Livermore Laboratory has several large-scale computers which are connected to the Octopus network. Several difficulties arise in providing adequate resources along with reliable performance. To alleviate some of these problems a new method of bringing large computers into the Octopus environment is proposed.

Dust Sensor with Large Detection Area Using Polyimide Film and Piezoelectric Elements

NASA Astrophysics Data System (ADS)

Kobayashi, M.; Okudaira, O.; Kurosawa, K.; Okamoto, T.; Matsui, T.

2016-10-01

We describe the development of dust particles sensor in space with large area (1m × 1m scale). The sensor has just a thin film of polyimide attached with small tips of piezoelectric elements. We performed experiments to characterize the sensor.

Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers.

PubMed

Jordan, Jakob; Ippen, Tammo; Helias, Moritz; Kitayama, Itaru; Sato, Mitsuhisa; Igarashi, Jun; Diesmann, Markus; Kunkel, Susanne

2018-01-01

State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems.

Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers

PubMed Central

Jordan, Jakob; Ippen, Tammo; Helias, Moritz; Kitayama, Itaru; Sato, Mitsuhisa; Igarashi, Jun; Diesmann, Markus; Kunkel, Susanne

2018-01-01

State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems. PMID:29503613

Linking climate projections to performance: A yield-based decision scaling assessment of a large urban water resources system

NASA Astrophysics Data System (ADS)

Turner, Sean W. D.; Marlow, David; Ekström, Marie; Rhodes, Bruce G.; Kularathna, Udaya; Jeffrey, Paul J.

2014-04-01

Despite a decade of research into climate change impacts on water resources, the scientific community has delivered relatively few practical methodological developments for integrating uncertainty into water resources system design. This paper presents an application of the "decision scaling" methodology for assessing climate change impacts on water resources system performance and asks how such an approach might inform planning decisions. The decision scaling method reverses the conventional ethos of climate impact assessment by first establishing the climate conditions that would compel planners to intervene. Climate model projections are introduced at the end of the process to characterize climate risk in such a way that avoids the process of propagating those projections through hydrological models. Here we simulated 1000 multisite synthetic monthly streamflow traces in a model of the Melbourne bulk supply system to test the sensitivity of system performance to variations in streamflow statistics. An empirical relation was derived to convert decision-critical flow statistics to climatic units, against which 138 alternative climate projections were plotted and compared. We defined the decision threshold in terms of a system yield metric constrained by multiple performance criteria. Our approach allows for fast and simple incorporation of demand forecast uncertainty and demonstrates the reach of the decision scaling method through successful execution in a large and complex water resources system. Scope for wider application in urban water resources planning is discussed.

Free Global Dsm Assessment on Large Scale Areas Exploiting the Potentialities of the Innovative Google Earth Engine Platform

NASA Astrophysics Data System (ADS)

Nascetti, A.; Di Rita, M.; Ravanelli, R.; Amicuzi, M.; Esposito, S.; Crespi, M.

2017-05-01

The high-performance cloud-computing platform Google Earth Engine has been developed for global-scale analysis based on the Earth observation data. In particular, in this work, the geometric accuracy of the two most used nearly-global free DSMs (SRTM and ASTER) has been evaluated on the territories of four American States (Colorado, Michigan, Nevada, Utah) and one Italian Region (Trentino Alto- Adige, Northern Italy) exploiting the potentiality of this platform. These are large areas characterized by different terrain morphology, land covers and slopes. The assessment has been performed using two different reference DSMs: the USGS National Elevation Dataset (NED) and a LiDAR acquisition. The DSMs accuracy has been evaluated through computation of standard statistic parameters, both at global scale (considering the whole State/Region) and in function of the terrain morphology using several slope classes. The geometric accuracy in terms of Standard deviation and NMAD, for SRTM range from 2-3 meters in the first slope class to about 45 meters in the last one, whereas for ASTER, the values range from 5-6 to 30 meters. In general, the performed analysis shows a better accuracy for the SRTM in the flat areas whereas the ASTER GDEM is more reliable in the steep areas, where the slopes increase. These preliminary results highlight the GEE potentialities to perform DSM assessment on a global scale.

Adapting Wave-front Algorithms to Efficiently Utilize Systems with Deep Communication Hierarchies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kerbyson, Darren J.; Lang, Michael; Pakin, Scott

2011-09-30

Large-scale systems increasingly exhibit a differential between intra-chip and inter-chip communication performance especially in hybrid systems using accelerators. Processorcores on the same socket are able to communicate at lower latencies, and with higher bandwidths, than cores on different sockets either within the same node or between nodes. A key challenge is to efficiently use this communication hierarchy and hence optimize performance. We consider here the class of applications that contains wavefront processing. In these applications data can only be processed after their upstream neighbors have been processed. Similar dependencies result between processors in which communication is required to pass boundarymore » data downstream and whose cost is typically impacted by the slowest communication channel in use. In this work we develop a novel hierarchical wave-front approach that reduces the use of slower communications in the hierarchy but at the cost of additional steps in the parallel computation and higher use of on-chip communications. This tradeoff is explored using a performance model. An implementation using the Reverse-acceleration programming model on the petascale Roadrunner system demonstrates a 27% performance improvement at full system-scale on a kernel application. The approach is generally applicable to large-scale multi-core and accelerated systems where a differential in system communication performance exists.« less

Adapting wave-front algorithms to efficiently utilize systems with deep communication hierarchies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kerbyson, Darren J; Lang, Michael; Pakin, Scott

2009-01-01

Large-scale systems increasingly exhibit a differential between intra-chip and inter-chip communication performance. Processor-cores on the same socket are able to communicate at lower latencies, and with higher bandwidths, than cores on different sockets either within the same node or between nodes. A key challenge is to efficiently use this communication hierarchy and hence optimize performance. We consider here the class of applications that contain wave-front processing. In these applications data can only be processed after their upstream neighbors have been processed. Similar dependencies result between processors in which communication is required to pass boundary data downstream and whose cost ismore » typically impacted by the slowest communication channel in use. In this work we develop a novel hierarchical wave-front approach that reduces the use of slower communications in the hierarchy but at the cost of additional computation and higher use of on-chip communications. This tradeoff is explored using a performance model and an implementation on the Petascale Roadrunner system demonstrates a 27% performance improvement at full system-scale on a kernel application. The approach is generally applicable to large-scale multi-core and accelerated systems where a differential in system communication performance exists.« less

Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition.

PubMed

Wang, Runchun; Thakur, Chetan Singh; Cohen, Gregory; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, Andre

2017-06-01

We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAs) for performing massively parallel real-time pattern recognition. NEF is a framework that is capable of synthesising large-scale cognitive systems from subnetworks and we have previously presented an FPGA implementation of the NEF that successfully performs nonlinear mathematical computations. That work was developed based on a compact digital neural core, which consists of 64 neurons that are instantiated by a single physical neuron using a time-multiplexing approach. We have now scaled this approach up to build a pattern recognition system by combining identical neural cores together. As a proof of concept, we have developed a handwritten digit recognition system using the MNIST database and achieved a recognition rate of 96.55%. The system is implemented on a state-of-the-art FPGA and can process 5.12 million digits per second. The architecture and hardware optimisations presented offer high-speed and resource-efficient means for performing high-speed, neuromorphic, and massively parallel pattern recognition and classification tasks.

Advanced Model for Extreme Lift and Improved Aeroacoustics (AMELIA)

NASA Technical Reports Server (NTRS)

Lichtwardt, Jonathan; Paciano, Eric; Jameson, Tina; Fong, Robert; Marshall, David

2012-01-01

With the very recent advent of NASA's Environmentally Responsible Aviation Project (ERA), which is dedicated to designing aircraft that will reduce the impact of aviation on the environment, there is a need for research and development of methodologies to minimize fuel burn, emissions, and reduce community noise produced by regional airliners. ERA tackles airframe technology, propulsion technology, and vehicle systems integration to meet performance objectives in the time frame for the aircraft to be at a Technology Readiness Level (TRL) of 4-6 by the year of 2020 (deemed N+2). The proceeding project that investigated similar goals to ERA was NASA's Subsonic Fixed Wing (SFW). SFW focused on conducting research to improve prediction methods and technologies that will produce lower noise, lower emissions, and higher performing subsonic aircraft for the Next Generation Air Transportation System. The work provided in this investigation was a NASA Research Announcement (NRA) contract #NNL07AA55C funded by Subsonic Fixed Wing. The project started in 2007 with a specific goal of conducting a large-scale wind tunnel test along with the development of new and improved predictive codes for the advanced powered-lift concepts. Many of the predictive codes were incorporated to refine the wind tunnel model outer mold line design. The large scale wind tunnel test goal was to investigate powered lift technologies and provide an experimental database to validate current and future modeling techniques. Powered-lift concepts investigated were Circulation Control (CC) wing in conjunction with over-the-wing mounted engines to entrain the exhaust to further increase the lift generated by CC technologies alone. The NRA was a five-year effort; during the first year the objective was to select and refine CESTOL concepts and then to complete a preliminary design of a large-scale wind tunnel model for the large scale test. During the second, third, and fourth years the large-scale wind tunnel model design would be completed, manufactured, and calibrated. During the fifth year the large scale wind tunnel test was conducted. This technical memo will describe all phases of the Advanced Model for Extreme Lift and Improved Aeroacoustics (AMELIA) project and provide a brief summary of the background and modeling efforts involved in the NRA. The conceptual designs considered for this project and the decision process for the selected configuration adapted for a wind tunnel model will be briefly discussed. The internal configuration of AMELIA, and the internal measurements chosen in order to satisfy the requirements of obtaining a database of experimental data to be used for future computational model validations. The external experimental techniques that were employed during the test, along with the large-scale wind tunnel test facility are covered in great detail. Experimental measurements in the database include forces and moments, and surface pressure distributions, local skin friction measurements, boundary and shear layer velocity profiles, far-field acoustic data and noise signatures from turbofan propulsion simulators. Results and discussion of the circulation control performance, over-the-wing mounted engines, and the combined performance are also discussed in great detail.

Stormbow: A Cloud-Based Tool for Reads Mapping and Expression Quantification in Large-Scale RNA-Seq Studies

PubMed Central

Zhao, Shanrong; Prenger, Kurt; Smith, Lance

2013-01-01

RNA-Seq is becoming a promising replacement to microarrays in transcriptome profiling and differential gene expression study. Technical improvements have decreased sequencing costs and, as a result, the size and number of RNA-Seq datasets have increased rapidly. However, the increasing volume of data from large-scale RNA-Seq studies poses a practical challenge for data analysis in a local environment. To meet this challenge, we developed Stormbow, a cloud-based software package, to process large volumes of RNA-Seq data in parallel. The performance of Stormbow has been tested by practically applying it to analyse 178 RNA-Seq samples in the cloud. In our test, it took 6 to 8 hours to process an RNA-Seq sample with 100 million reads, and the average cost was $3.50 per sample. Utilizing Amazon Web Services as the infrastructure for Stormbow allows us to easily scale up to handle large datasets with on-demand computational resources. Stormbow is a scalable, cost effective, and open-source based tool for large-scale RNA-Seq data analysis. Stormbow can be freely downloaded and can be used out of box to process Illumina RNA-Seq datasets. PMID:25937948

Stormbow: A Cloud-Based Tool for Reads Mapping and Expression Quantification in Large-Scale RNA-Seq Studies.

PubMed

Zhao, Shanrong; Prenger, Kurt; Smith, Lance

2013-01-01

RNA-Seq is becoming a promising replacement to microarrays in transcriptome profiling and differential gene expression study. Technical improvements have decreased sequencing costs and, as a result, the size and number of RNA-Seq datasets have increased rapidly. However, the increasing volume of data from large-scale RNA-Seq studies poses a practical challenge for data analysis in a local environment. To meet this challenge, we developed Stormbow, a cloud-based software package, to process large volumes of RNA-Seq data in parallel. The performance of Stormbow has been tested by practically applying it to analyse 178 RNA-Seq samples in the cloud. In our test, it took 6 to 8 hours to process an RNA-Seq sample with 100 million reads, and the average cost was $3.50 per sample. Utilizing Amazon Web Services as the infrastructure for Stormbow allows us to easily scale up to handle large datasets with on-demand computational resources. Stormbow is a scalable, cost effective, and open-source based tool for large-scale RNA-Seq data analysis. Stormbow can be freely downloaded and can be used out of box to process Illumina RNA-Seq datasets.

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets.

PubMed

Bicer, Tekin; Gürsoy, Doğa; Andrade, Vincent De; Kettimuthu, Rajkumar; Scullin, William; Carlo, Francesco De; Foster, Ian T

2017-01-01

Modern synchrotron light sources and detectors produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used imaging techniques that generates data at tens of gigabytes per second is computed tomography (CT). Although CT experiments result in rapid data generation, the analysis and reconstruction of the collected data may require hours or even days of computation time with a medium-sized workstation, which hinders the scientific progress that relies on the results of analysis. We present Trace, a data-intensive computing engine that we have developed to enable high-performance implementation of iterative tomographic reconstruction algorithms for parallel computers. Trace provides fine-grained reconstruction of tomography datasets using both (thread-level) shared memory and (process-level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations that we apply to the replicated reconstruction objects and evaluate them using tomography datasets collected at the Advanced Photon Source. Our experimental evaluations show that our optimizations and parallelization techniques can provide 158× speedup using 32 compute nodes (384 cores) over a single-core configuration and decrease the end-to-end processing time of a large sinogram (with 4501 × 1 × 22,400 dimensions) from 12.5 h to <5 min per iteration. The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.

The influence of cognitive load on spatial search performance.

PubMed

Longstaffe, Kate A; Hood, Bruce M; Gilchrist, Iain D

2014-01-01

During search, executive function enables individuals to direct attention to potential targets, remember locations visited, and inhibit distracting information. In the present study, we investigated these executive processes in large-scale search. In our tasks, participants searched a room containing an array of illuminated locations embedded in the floor. The participants' task was to press the switches at the illuminated locations on the floor so as to locate a target that changed color when pressed. The perceptual salience of the search locations was manipulated by having some locations flashing and some static. Participants were more likely to search at flashing locations, even when they were explicitly informed that the target was equally likely to be at any location. In large-scale search, attention was captured by the perceptual salience of the flashing lights, leading to a bias to explore these targets. Despite this failure of inhibition, participants were able to restrict returns to previously visited locations, a measure of spatial memory performance. Participants were more able to inhibit exploration to flashing locations when they were not required to remember which locations had previously been visited. A concurrent digit-span memory task further disrupted inhibition during search, as did a concurrent auditory attention task. These experiments extend a load theory of attention to large-scale search, which relies on egocentric representations of space. High cognitive load on working memory leads to increased distractor interference, providing evidence for distinct roles for the executive subprocesses of memory and inhibition during large-scale search.

Cortical circuitry implementing graphical models.

PubMed

Litvak, Shai; Ullman, Shimon

2009-11-01

In this letter, we develop and simulate a large-scale network of spiking neurons that approximates the inference computations performed by graphical models. Unlike previous related schemes, which used sum and product operations in either the log or linear domains, the current model uses an inference scheme based on the sum and maximization operations in the log domain. Simulations show that using these operations, a large-scale circuit, which combines populations of spiking neurons as basic building blocks, is capable of finding close approximations to the full mathematical computations performed by graphical models within a few hundred milliseconds. The circuit is general in the sense that it can be wired for any graph structure, it supports multistate variables, and it uses standard leaky integrate-and-fire neuronal units. Following previous work, which proposed relations between graphical models and the large-scale cortical anatomy, we focus on the cortical microcircuitry and propose how anatomical and physiological aspects of the local circuitry may map onto elements of the graphical model implementation. We discuss in particular the roles of three major types of inhibitory neurons (small fast-spiking basket cells, large layer 2/3 basket cells, and double-bouquet neurons), subpopulations of strongly interconnected neurons with their unique connectivity patterns in different cortical layers, and the possible role of minicolumns in the realization of the population-based maximum operation.

Crater size estimates for large-body terrestrial impact

NASA Technical Reports Server (NTRS)

Schmidt, Robert M.; Housen, Kevin R.

1988-01-01

Calculating the effects of impacts leading to global catastrophes requires knowledge of the impact process at very large size scales. This information cannot be obtained directly but must be inferred from subscale physical simulations, numerical simulations, and scaling laws. Schmidt and Holsapple presented scaling laws based upon laboratory-scale impact experiments performed on a centrifuge (Schmidt, 1980 and Schmidt and Holsapple, 1980). These experiments were used to develop scaling laws which were among the first to include gravity dependence associated with increasing event size. At that time using the results of experiments in dry sand and in water to provide bounds on crater size, they recognized that more precise bounds on large-body impact crater formation could be obtained with additional centrifuge experiments conducted in other geological media. In that previous work, simple power-law formulae were developed to relate final crater diameter to impactor size and velocity. In addition, Schmidt (1980) and Holsapple and Schmidt (1982) recognized that the energy scaling exponent is not a universal constant but depends upon the target media. Recently, Holsapple and Schmidt (1987) includes results for non-porous materials and provides a basis for estimating crater formation kinematics and final crater size. A revised set of scaling relationships for all crater parameters of interest are presented. These include results for various target media and include the kinematics of formation. Particular attention is given to possible limits brought about by very large impactors.

Advances in the manufacture of MIP nanoparticles.

PubMed

Poma, Alessandro; Turner, Anthony P F; Piletsky, Sergey A

2010-12-01

Molecularly imprinted polymers (MIPs) are prepared by creating a three-dimensional polymeric matrix around a template molecule. After the matrix is removed, complementary cavities with respect to shape and functional groups remain. MIPs have been produced for applications in in vitro diagnostics, therapeutics and separations. However, this promising technology still lacks widespread application because of issues related to large-scale production and optimization of the synthesis. Recent developments in the area of MIP nanoparticles might offer solutions to several problems associated with performance and application. This review discusses various approaches used in the preparation of MIP nanoparticles, focusing in particular on the issues associated with large-scale manufacture and implications for the performance of synthesized nanomaterials. Copyright © 2010 Elsevier Ltd. All rights reserved.

The Immigrant's University: A Study of Academic Performance and the Experiences of Recent Immigrant Groups at the University of California

ERIC Educational Resources Information Center

Douglass, John Aubrey; Thomson, Gregg

2010-01-01

One of the major characteristics of globalization is the large influx of immigrant groups moving largely from underdeveloped regions to developed economies. California offers one of the most robust examples of a large-scale, postmodern demographic transition that includes a great racial, ethnic, and cultural diversity of immigrant groups, many of…

A Combined Eulerian-Lagrangian Data Representation for Large-Scale Applications.

PubMed

Sauer, Franz; Xie, Jinrong; Ma, Kwan-Liu

2017-10-01

The Eulerian and Lagrangian reference frames each provide a unique perspective when studying and visualizing results from scientific systems. As a result, many large-scale simulations produce data in both formats, and analysis tasks that simultaneously utilize information from both representations are becoming increasingly popular. However, due to their fundamentally different nature, drawing correlations between these data formats is a computationally difficult task, especially in a large-scale setting. In this work, we present a new data representation which combines both reference frames into a joint Eulerian-Lagrangian format. By reorganizing Lagrangian information according to the Eulerian simulation grid into a "unit cell" based approach, we can provide an efficient out-of-core means of sampling, querying, and operating with both representations simultaneously. We also extend this design to generate multi-resolution subsets of the full data to suit the viewer's needs and provide a fast flow-aware trajectory construction scheme. We demonstrate the effectiveness of our method using three large-scale real world scientific datasets and provide insight into the types of performance gains that can be achieved.

A scalable PC-based parallel computer for lattice QCD

NASA Astrophysics Data System (ADS)

Fodor, Z.; Katz, S. D.; Pappa, G.

2003-05-01

A PC-based parallel computer for medium/large scale lattice QCD simulations is suggested. The Eo¨tvo¨s Univ., Inst. Theor. Phys. cluster consists of 137 Intel P4-1.7GHz nodes. Gigabit Ethernet cards are used for nearest neighbor communication in a two-dimensional mesh. The sustained performance for dynamical staggered (wilson) quarks on large lattices is around 70(110) GFlops. The exceptional price/performance ratio is below $1/Mflop.

Multi-scale pixel-based image fusion using multivariate empirical mode decomposition.

PubMed

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P; McDonald-Maier, Klaus D

2015-05-08

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences.

Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition

PubMed Central

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P.; McDonald-Maier, Klaus D.

2015-01-01

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences. PMID:26007714

Java Performance for Scientific Applications on LLNL Computer Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kapfer, C; Wissink, A

2002-05-10

Languages in use for high performance computing at the laboratory--Fortran (f77 and f90), C, and C++--have many years of development behind them and are generally considered the fastest available. However, Fortran and C do not readily extend to object-oriented programming models, limiting their capability for very complex simulation software. C++ facilitates object-oriented programming but is a very complex and error-prone language. Java offers a number of capabilities that these other languages do not. For instance it implements cleaner (i.e., easier to use and less prone to errors) object-oriented models than C++. It also offers networking and security as part ofmore » the language standard, and cross-platform executables that make it architecture neutral, to name a few. These features have made Java very popular for industrial computing applications. The aim of this paper is to explain the trade-offs in using Java for large-scale scientific applications at LLNL. Despite its advantages, the computational science community has been reluctant to write large-scale computationally intensive applications in Java due to concerns over its poor performance. However, considerable progress has been made over the last several years. The Java Grande Forum [1] has been promoting the use of Java for large-scale computing. Members have introduced efficient array libraries, developed fast just-in-time (JIT) compilers, and built links to existing packages used in high performance parallel computing.« less

Liquid Oxygen Propellant Densification Production and Performance Test Results With a Large-Scale Flight-Weight Propellant Tank for the X33 RLV

NASA Technical Reports Server (NTRS)

Tomsik, Thomas M.; Meyer, Michael L.

2010-01-01

This paper describes in-detail a test program that was initiated at the Glenn Research Center (GRC) involving the cryogenic densification of liquid oxygen (LO2). A large scale LO2 propellant densification system rated for 200 gpm and sized for the X-33 LO2 propellant tank, was designed, fabricated and tested at the GRC. Multiple objectives of the test program included validation of LO2 production unit hardware and characterization of densifier performance at design and transient conditions. First, performance data is presented for an initial series of LO2 densifier screening and check-out tests using densified liquid nitrogen. The second series of tests show performance data collected during LO2 densifier test operations with liquid oxygen as the densified product fluid. An overview of LO2 X-33 tanking operations and load tests with the 20,000 gallon Structural Test Article (STA) are described. Tank loading testing and the thermal stratification that occurs inside of a flight-weight launch vehicle propellant tank were investigated. These operations involved a closed-loop recirculation process of LO2 flow through the densifier and then back into the STA. Finally, in excess of 200,000 gallons of densified LO2 at 120 oR was produced with the propellant densification unit during the demonstration program, an achievement that s never been done before in the realm of large-scale cryogenic tests.

Sex Differences in Arithmetical Performance Scores: Central Tendency and Variability

ERIC Educational Resources Information Center

Martens, R.; Hurks, P. P. M.; Meijs, C.; Wassenberg, R.; Jolles, J.

2011-01-01

The present study aimed to analyze sex differences in arithmetical performance in a large-scale sample of 390 children (193 boys) frequenting grades 1-9. Past research in this field has focused primarily on average performance, implicitly assuming homogeneity of variance, for which support is scarce. This article examined sex differences in…

Unimanual Performance across the Age Span

ERIC Educational Resources Information Center

Bryden, P.J.; Roy, E.A.

2005-01-01

The purpose of the current investigation was to examine the age-related changes in the performance of the two hands on the Annett pegboard (Annett, 1970). The current study was part of a large-scale study investigating the development of unimanual and bimanual performance. Three hundred and two right-handed individuals participated in the present…

Rater Severity in Large-Scale Assessment: Is It Invariant?

ERIC Educational Resources Information Center

McQueen, Joy; Congdon, Peter J.

A study was conducted to investigate the stability of rater severity over an extended rating period. Multifaceted Rasch analysis was applied to ratings of writing performances of 8,285 primary school (elementary) students. Each performance was rated on two performance dimensions by two trained raters over a period of 7 rating days. Performances…

ATLAS and LHC computing on CRAY

NASA Astrophysics Data System (ADS)

Sciacca, F. G.; Haug, S.; ATLAS Collaboration

2017-10-01

Access and exploitation of large scale computing resources, such as those offered by general purpose HPC centres, is one important measure for ATLAS and the other Large Hadron Collider experiments in order to meet the challenge posed by the full exploitation of the future data within the constraints of flat budgets. We report on the effort of moving the Swiss WLCG T2 computing, serving ATLAS, CMS and LHCb, from a dedicated cluster to the large Cray systems at the Swiss National Supercomputing Centre CSCS. These systems do not only offer very efficient hardware, cooling and highly competent operators, but also have large backfill potentials due to size and multidisciplinary usage and potential gains due to economy at scale. Technical solutions, performance, expected return and future plans are discussed.

Dopaminergic modulation of hemodynamic signal variability and the functional connectome during cognitive performance.

PubMed

Alavash, Mohsen; Lim, Sung-Joo; Thiel, Christiane; Sehm, Bernhard; Deserno, Lorenz; Obleser, Jonas

2018-05-15

Dopamine underlies important aspects of cognition, and has been suggested to boost cognitive performance. However, how dopamine modulates the large-scale cortical dynamics during cognitive performance has remained elusive. Using functional MRI during a working memory task in healthy young human listeners, we investigated the effect of levodopa (l-dopa) on two aspects of cortical dynamics, blood oxygen-level-dependent (BOLD) signal variability and the functional connectome of large-scale cortical networks. We here show that enhanced dopaminergic signaling modulates the two potentially interrelated aspects of large-scale cortical dynamics during cognitive performance, and the degree of these modulations is able to explain inter-individual differences in l-dopa-induced behavioral benefits. Relative to placebo, l-dopa increased BOLD signal variability in task-relevant temporal, inferior frontal, parietal and cingulate regions. On the connectome level, however, l-dopa diminished functional integration across temporal and cingulo-opercular regions. This hypo-integration was expressed as a reduction in network efficiency and modularity in more than two thirds of the participants and to different degrees. Hypo-integration co-occurred with relative hyper-connectivity in paracentral lobule and precuneus, as well as posterior putamen. Both, l-dopa-induced BOLD signal variability modulation and functional connectome modulations proved predictive of an individual's l-dopa-induced benefits in behavioral performance, namely response speed and perceptual sensitivity. Lastly, l-dopa-induced modulations of BOLD signal variability were correlated with l-dopa-induced modulation of nodal connectivity and network efficiency. Our findings underline the role of dopamine in maintaining the dynamic range of, and communication between, cortical systems, and their explanatory power for inter-individual differences in benefits from dopamine during cognitive performance. Copyright © 2018 Elsevier Inc. All rights reserved.

Spiking neural network simulation: memory-optimal synaptic event scheduling.

PubMed

Stewart, Robert D; Gurney, Kevin N

2011-06-01

Spiking neural network simulations incorporating variable transmission delays require synaptic events to be scheduled prior to delivery. Conventional methods have memory requirements that scale with the total number of synapses in a network. We introduce novel scheduling algorithms for both discrete and continuous event delivery, where the memory requirement scales instead with the number of neurons. Superior algorithmic performance is demonstrated using large-scale, benchmarking network simulations.

Crash test and evaluation of temporary wood sign support system for large guide signs.

DOT National Transportation Integrated Search

2016-07-01

The objective of this research task was to evaluate the impact performance of a temporary wood sign support : system for large guide signs. It was desired to use existing TxDOT sign hardware in the design to the extent possible. : The full-scale cras...

Performance Assessment of a Large Scale Pulsejet- Driven Ejector System

NASA Technical Reports Server (NTRS)

Paxson, Daniel E.; Litke, Paul J.; Schauer, Frederick R.; Bradley, Royce P.; Hoke, John L.

2006-01-01

Unsteady thrust augmentation was measured on a large scale driver/ejector system. A 72 in. long, 6.5 in. diameter, 100 lb(sub f) pulsejet was tested with a series of straight, cylindrical ejectors of varying length, and diameter. A tapered ejector configuration of varying length was also tested. The objectives of the testing were to determine the dimensions of the ejectors which maximize thrust augmentation, and to compare the dimensions and augmentation levels so obtained with those of other, similarly maximized, but smaller scale systems on which much of the recent unsteady ejector thrust augmentation studies have been performed. An augmentation level of 1.71 was achieved with the cylindrical ejector configuration and 1.81 with the tapered ejector configuration. These levels are consistent with, but slightly lower than the highest levels achieved with the smaller systems. The ejector diameter yielding maximum augmentation was 2.46 times the diameter of the pulsejet. This ratio closely matches those of the small scale experiments. For the straight ejector, the length yielding maximum augmentation was 10 times the diameter of the pulsejet. This was also nearly the same as the small scale experiments. Testing procedures are described, as are the parametric variations in ejector geometry. Results are discussed in terms of their implications for general scaling of pulsed thrust ejector systems

Large-scale exact diagonalizations reveal low-momentum scales of nuclei

NASA Astrophysics Data System (ADS)

Forssén, C.; Carlsson, B. D.; Johansson, H. T.; Sääf, D.; Bansal, A.; Hagen, G.; Papenbrock, T.

2018-03-01

Ab initio methods aim to solve the nuclear many-body problem with controlled approximations. Virtually exact numerical solutions for realistic interactions can only be obtained for certain special cases such as few-nucleon systems. Here we extend the reach of exact diagonalization methods to handle model spaces with dimension exceeding 1010 on a single compute node. This allows us to perform no-core shell model (NCSM) calculations for 6Li in model spaces up to Nmax=22 and to reveal the 4He+d halo structure of this nucleus. Still, the use of a finite harmonic-oscillator basis implies truncations in both infrared (IR) and ultraviolet (UV) length scales. These truncations impose finite-size corrections on observables computed in this basis. We perform IR extrapolations of energies and radii computed in the NCSM and with the coupled-cluster method at several fixed UV cutoffs. It is shown that this strategy enables information gain also from data that is not fully UV converged. IR extrapolations improve the accuracy of relevant bound-state observables for a range of UV cutoffs, thus making them profitable tools. We relate the momentum scale that governs the exponential IR convergence to the threshold energy for the first open decay channel. Using large-scale NCSM calculations we numerically verify this small-momentum scale of finite nuclei.

Soil moisture and biogeochemical factors influence the distribution of annual Bromus species

Treesearch

Jayne Belnap; John M. Stark; Benjamin M. Rau; Edith B. Allen; Susan Phillips

2016-01-01

Abiotic factors have a strong influence on where annual Bromus species are found. At the large regional scale, temperature and precipitation extremes determine the boundaries of Bromus occurrence. At the more local scale, soil characteristics and climate influence distribution, cover, and performance. In hot, dry, summer-rainfall-dominated deserts (Sonoran, Chihuahuan...

The Role of Scheduling in Observing Teacher-Child Interactions

ERIC Educational Resources Information Center

Cash, Anne H.; Pianta, Robert C.

2014-01-01

Observational assessment is being used on a large scale to evaluate the quality of interactions between teachers and children in classroom environments. When one performs observations at scale, features of the protocol such as the scheduling of observations can potentially influence observed scores. In this study interactions were observed for 88…

Charter Operators Spell Out Barriers to "Scaling Up"

ERIC Educational Resources Information Center

Zehr, Mary Ann

2011-01-01

The pace at which the highest-performing charter-management organizations (CMOs) are "scaling up" is being determined largely by how rapidly they can develop and hire strong leaders and acquire physical space, and by the level of support they receive for growth from city or state policies, say leaders from some charter organizations…

Effect of Wall Shear Stress on Corrosion Inhibitor Film Performance

NASA Astrophysics Data System (ADS)

Canto Maya, Christian M.

In oil and gas production, internal corrosion of pipelines causes the highest incidence of recurring failures. Ensuring the integrity of ageing pipeline infrastructure is an increasingly important requirement. One of the most widely applied methods to reduce internal corrosion rates is the continuous injection of chemicals in very small quantities, called corrosion inhibitors. These chemical substances form thin films at the pipeline internal surface that reduce the magnitude of the cathodic and/or anodic reactions. However, the efficacy of such corrosion inhibitor films can be reduced by different factors such as multiphase flow, due to enhanced shear stress and mass transfer effects, loss of inhibitor due to adsorption on other interfaces such as solid particles, bubbles and droplets entrained by the bulk phase, and due to chemical interaction with other incompatible substances present in the stream. The first part of the present project investigated the electrochemical behavior of two organic corrosion inhibitors (a TOFA/DETA imidazolinium, and an alkylbenzyl dimethyl ammonium chloride), with and without an inorganic salt (sodium thiosulfate), and the resulting enhancement. The second part of the work explored the performance of corrosion inhibitor under multiphase (gas/liquid, solid/liquid) flow. The effect of gas/liquid multiphase flow was investigated using small and large scale apparatus. The small scale tests were conducted using a glass cell and a submersed jet impingement attachment with three different hydrodynamic patterns (water jet, CO 2 bubbles impact, and water vapor cavitation). The large scale experiments were conducted applying different flow loops (hilly terrain and standing slug systems). Measurements of weight loss, linear polarization resistance (LPR), and adsorption mass (using an electrochemical quartz crystal microbalance, EQCM) were used to quantify the effect of wall shear stress on the performance and integrity of corrosion inhibitor films. Different scenarios were evaluated in this section of the work, such as the loss of corrosion inhibitor due to the formation of foam, and the effect of different substrates on the adsorption of corrosion inhibitor. Erosion/corrosion effects due to solids carried by a multiphase flow were investigated both on a small and large scale. Small scale experiments were performed in order to determine whether the corrosion inhibitor concentration was diminished because of adsorption onto the large surface area of entrained solid particles. The large scale experiments were done to evaluate the effect of mechanical erosion corrosion on inhibitor film performance, and vice versa. The analysis of the results obtained by electrochemical characterization shows that the adsorption mechanism having a corrosion inhibitor competing with water molecules for a place on the steel surface is an accurate approach to describe this phenomenon. From the experimental results obtained in the multiphase part of this research project, it can be concluded that the performance of corrosion inhibitor films is not significantly impacted by mechanical forces alone; even under the worst case scenarios tested here (standing slug and erosion/corrosion). Reduction of inhibitor performance was found to be primarily due to the loss of inhibitor due to consumption by adsorption particularly when a gas phase was present, leading to foam formation.

SVM and SVM Ensembles in Breast Cancer Prediction.

PubMed

Huang, Min-Wei; Chen, Chih-Wen; Lin, Wei-Chao; Ke, Shih-Wen; Tsai, Chih-Fong

2017-01-01

Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers.

SVM and SVM Ensembles in Breast Cancer Prediction

PubMed Central

Huang, Min-Wei; Chen, Chih-Wen; Lin, Wei-Chao; Ke, Shih-Wen; Tsai, Chih-Fong

2017-01-01

Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers. PMID:28060807

Applications of large-scale density functional theory in biology

NASA Astrophysics Data System (ADS)

Cole, Daniel J.; Hine, Nicholas D. M.

2016-10-01

Density functional theory (DFT) has become a routine tool for the computation of electronic structure in the physics, materials and chemistry fields. Yet the application of traditional DFT to problems in the biological sciences is hindered, to a large extent, by the unfavourable scaling of the computational effort with system size. Here, we review some of the major software and functionality advances that enable insightful electronic structure calculations to be performed on systems comprising many thousands of atoms. We describe some of the early applications of large-scale DFT to the computation of the electronic properties and structure of biomolecules, as well as to paradigmatic problems in enzymology, metalloproteins, photosynthesis and computer-aided drug design. With this review, we hope to demonstrate that first principles modelling of biological structure-function relationships are approaching a reality.

A multidisciplinary approach to the development of low-cost high-performance lightwave networks

NASA Technical Reports Server (NTRS)

Maitan, Jacek; Harwit, Alex

1991-01-01

Our research focuses on high-speed distributed systems. We anticipate that our results will allow the fabrication of low-cost networks employing multi-gigabit-per-second data links for space and military applications. The recent development of high-speed low-cost photonic components and new generations of microprocessors creates an opportunity to develop advanced large-scale distributed information systems. These systems currently involve hundreds of thousands of nodes and are made up of components and communications links that may fail during operation. In order to realize these systems, research is needed into technologies that foster adaptability and scaleability. Self-organizing mechanisms are needed to integrate a working fabric of large-scale distributed systems. The challenge is to fuse theory, technology, and development methodologies to construct a cost-effective, efficient, large-scale system.

Transparent and Flexible Large-scale Graphene-based Heater

NASA Astrophysics Data System (ADS)

Kang, Junmo; Lee, Changgu; Kim, Young-Jin; Choi, Jae-Boong; Hong, Byung Hee

2011-03-01

We report the application of transparent and flexible heater with high optical transmittance and low sheet resistance using graphene films, showing outstanding thermal and electrical properties. The large-scale graphene films were grown on Cu foil by chemical vapor deposition methods, and transferred to transparent substrates by multiple stacking. The wet chemical doping process enhanced the electrical properties, showing a sheet resistance as low as 35 ohm/sq with 88.5 % transmittance. The temperature response usually depends on the dimension and the sheet resistance of the graphene-based heater. We show that a 4x4 cm2 heater can reach 80& circ; C within 40 seconds and large-scale (9x9 cm2) heater shows uniformly heating performance, which was measured using thermocouple and infra-red camera. These heaters would be very useful for defogging systems and smart windows.

A numerical projection technique for large-scale eigenvalue problems

NASA Astrophysics Data System (ADS)

Gamillscheg, Ralf; Haase, Gundolf; von der Linden, Wolfgang

2011-10-01

We present a new numerical technique to solve large-scale eigenvalue problems. It is based on the projection technique, used in strongly correlated quantum many-body systems, where first an effective approximate model of smaller complexity is constructed by projecting out high energy degrees of freedom and in turn solving the resulting model by some standard eigenvalue solver. Here we introduce a generalization of this idea, where both steps are performed numerically and which in contrast to the standard projection technique converges in principle to the exact eigenvalues. This approach is not just applicable to eigenvalue problems encountered in many-body systems but also in other areas of research that result in large-scale eigenvalue problems for matrices which have, roughly speaking, mostly a pronounced dominant diagonal part. We will present detailed studies of the approach guided by two many-body models.

A Fine-Grained Pipelined Implementation for Large-Scale Matrix Inversion on FPGA

NASA Astrophysics Data System (ADS)

Zhou, Jie; Dou, Yong; Zhao, Jianxun; Xia, Fei; Lei, Yuanwu; Tang, Yuxing

Large-scale matrix inversion play an important role in many applications. However to the best of our knowledge, there is no FPGA-based implementation. In this paper, we explore the possibility of accelerating large-scale matrix inversion on FPGA. To exploit the computational potential of FPGA, we introduce a fine-grained parallel algorithm for matrix inversion. A scalable linear array processing elements (PEs), which is the core component of the FPGA accelerator, is proposed to implement this algorithm. A total of 12 PEs can be integrated into an Altera StratixII EP2S130F1020C5 FPGA on our self-designed board. Experimental results show that a factor of 2.6 speedup and the maximum power-performance of 41 can be achieved compare to Pentium Dual CPU with double SSE threads.

Improved uniformity in high-performance organic photovoltaics enabled by (3-aminopropyl)triethoxysilane cathode functionalization.

PubMed

Luck, Kyle A; Shastry, Tejas A; Loser, Stephen; Ogien, Gabriel; Marks, Tobin J; Hersam, Mark C

2013-12-28

Organic photovoltaics have the potential to serve as lightweight, low-cost, mechanically flexible solar cells. However, losses in efficiency as laboratory cells are scaled up to the module level have to date impeded large scale deployment. Here, we report that a 3-aminopropyltriethoxysilane (APTES) cathode interfacial treatment significantly enhances performance reproducibility in inverted high-efficiency PTB7:PC71BM organic photovoltaic cells, as demonstrated by the fabrication of 100 APTES-treated devices versus 100 untreated controls. The APTES-treated devices achieve a power conversion efficiency of 8.08 ± 0.12% with histogram skewness of -0.291, whereas the untreated controls achieve 7.80 ± 0.26% with histogram skewness of -1.86. By substantially suppressing the interfacial origins of underperforming cells, the APTES treatment offers a pathway for fabricating large-area modules with high spatial performance uniformity.

Source localization in electromyography using the inverse potential problem

NASA Astrophysics Data System (ADS)

van den Doel, Kees; Ascher, Uri M.; Pai, Dinesh K.

2011-02-01

We describe an efficient method for reconstructing the activity in human muscles from an array of voltage sensors on the skin surface. MRI is used to obtain morphometric data which are segmented into muscle tissue, fat, bone and skin, from which a finite element model for volume conduction is constructed. The inverse problem of finding the current sources in the muscles is solved using a careful regularization technique which adds a priori information, yielding physically reasonable solutions from among those that satisfy the basic potential problem. Several regularization functionals are considered and numerical experiments on a 2D test model are performed to determine which performs best. The resulting scheme leads to numerical difficulties when applied to large-scale 3D problems. We clarify the nature of these difficulties and provide a method to overcome them, which is shown to perform well in the large-scale problem setting.

Scalable parallel elastic-plastic finite element analysis using a quasi-Newton method with a balancing domain decomposition preconditioner

NASA Astrophysics Data System (ADS)

Yusa, Yasunori; Okada, Hiroshi; Yamada, Tomonori; Yoshimura, Shinobu

2018-04-01

A domain decomposition method for large-scale elastic-plastic problems is proposed. The proposed method is based on a quasi-Newton method in conjunction with a balancing domain decomposition preconditioner. The use of a quasi-Newton method overcomes two problems associated with the conventional domain decomposition method based on the Newton-Raphson method: (1) avoidance of a double-loop iteration algorithm, which generally has large computational complexity, and (2) consideration of the local concentration of nonlinear deformation, which is observed in elastic-plastic problems with stress concentration. Moreover, the application of a balancing domain decomposition preconditioner ensures scalability. Using the conventional and proposed domain decomposition methods, several numerical tests, including weak scaling tests, were performed. The convergence performance of the proposed method is comparable to that of the conventional method. In particular, in elastic-plastic analysis, the proposed method exhibits better convergence performance than the conventional method.

Fault-tolerant Control of a Cyber-physical System

NASA Astrophysics Data System (ADS)

Roxana, Rusu-Both; Eva-Henrietta, Dulf

2017-10-01

Cyber-physical systems represent a new emerging field in automatic control. The fault system is a key component, because modern, large scale processes must meet high standards of performance, reliability and safety. Fault propagation in large scale chemical processes can lead to loss of production, energy, raw materials and even environmental hazard. The present paper develops a multi-agent fault-tolerant control architecture using robust fractional order controllers for a (13C) cryogenic separation column cascade. The JADE (Java Agent DEvelopment Framework) platform was used to implement the multi-agent fault tolerant control system while the operational model of the process was implemented in Matlab/SIMULINK environment. MACSimJX (Multiagent Control Using Simulink with Jade Extension) toolbox was used to link the control system and the process model. In order to verify the performance and to prove the feasibility of the proposed control architecture several fault simulation scenarios were performed.

Low Cost Manufacturing of Composite Cryotanks

NASA Technical Reports Server (NTRS)

Meredith, Brent; Palm, Tod; Deo, Ravi; Munafo, Paul M. (Technical Monitor)

2002-01-01

This viewgraph presentation reviews research and development of cryotank manufacturing conducted by Northrup Grumman. The objectives of the research and development included the development and validation of manufacturing processes and technology for fabrication of large scale cryogenic tanks, the establishment of a scale-up and facilitization plan for full scale cryotanks, the development of non-autoclave composite manufacturing processes, the fabrication of subscale tank joints for element tests, the performance of manufacturing risk reduction trials for the subscale tank, and the development of full-scale tank manufacturing concepts.

Really Large Scale Computer Graphic Projection Using Lasers and Laser Substitutes

NASA Astrophysics Data System (ADS)

Rother, Paul

1989-07-01

This paper reflects on past laser projects to display vector scanned computer graphic images onto very large and irregular surfaces. Since the availability of microprocessors and high powered visible lasers, very large scale computer graphics projection have become a reality. Due to the independence from a focusing lens, lasers easily project onto distant and irregular surfaces and have been used for amusement parks, theatrical performances, concert performances, industrial trade shows and dance clubs. Lasers have been used to project onto mountains, buildings, 360° globes, clouds of smoke and water. These methods have proven successful in installations at: Epcot Theme Park in Florida; Stone Mountain Park in Georgia; 1984 Olympics in Los Angeles; hundreds of Corporate trade shows and thousands of musical performances. Using new ColorRayTM technology, the use of costly and fragile lasers is no longer necessary. Utilizing fiber optic technology, the functionality of lasers can be duplicated for new and exciting projection possibilities. The use of ColorRayTM technology has enjoyed worldwide recognition in conjunction with Pink Floyd and George Michaels' world wide tours.

A prototype automatic phase compensation module

NASA Technical Reports Server (NTRS)

Terry, John D.

1992-01-01

The growing demands for high gain and accurate satellite communication systems will necessitate the utilization of large reflector systems. One area of concern of reflector based satellite communication is large scale surface deformations due to thermal effects. These distortions, when present, can degrade the performance of the reflector system appreciable. This performance degradation is manifested by a decrease in peak gain, and increase in sidelobe level, and pointing errors. It is essential to compensate for these distortion effects and to maintain the required system performance in the operating space environment. For this reason the development of a technique to offset the degradation effects is highly desirable. Currently, most research is direct at developing better material for the reflector. These materials have a lower coefficient of linear expansion thereby reducing the surface errors. Alternatively, one can minimize the distortion effects of these large scale errors by adaptive phased array compensation. Adaptive phased array techniques have been studied extensively at NASA and elsewhere. Presented in this paper is a prototype automatic phase compensation module designed and built at NASA Lewis Research Center which is the first stage of development for an adaptive array compensation module.

Intercomparison of methods of coupling between convection and large-scale circulation: 2. Comparison over nonuniform surface conditions

DOE PAGES

Daleu, C. L.; Plant, R. S.; Woolnough, S. J.; ...

2016-03-18

As part of an international intercomparison project, the weak temperature gradient (WTG) and damped gravity wave (DGW) methods are used to parameterize large-scale dynamics in a set of cloud-resolving models (CRMs) and single column models (SCMs). The WTG or DGW method is implemented using a configuration that couples a model to a reference state defined with profiles obtained from the same model in radiative-convective equilibrium. We investigated the sensitivity of each model to changes in SST, given a fixed reference state. We performed a systematic comparison of the WTG and DGW methods in different models, and a systematic comparison ofmore » the behavior of those models using the WTG method and the DGW method. The sensitivity to the SST depends on both the large-scale parameterization method and the choice of the cloud model. In general, SCMs display a wider range of behaviors than CRMs. All CRMs using either the WTG or DGW method show an increase of precipitation with SST, while SCMs show sensitivities which are not always monotonic. CRMs using either the WTG or DGW method show a similar relationship between mean precipitation rate and column-relative humidity, while SCMs exhibit a much wider range of behaviors. DGW simulations produce large-scale velocity profiles which are smoother and less top-heavy compared to those produced by the WTG simulations. Lastly, these large-scale parameterization methods provide a useful tool to identify the impact of parameterization differences on model behavior in the presence of two-way feedback between convection and the large-scale circulation.« less

Automated AFM for small-scale and large-scale surface profiling in CMP applications

NASA Astrophysics Data System (ADS)

Zandiatashbar, Ardavan; Kim, Byong; Yoo, Young-kook; Lee, Keibock; Jo, Ahjin; Lee, Ju Suk; Cho, Sang-Joon; Park, Sang-il

2018-03-01

As the feature size is shrinking in the foundries, the need for inline high resolution surface profiling with versatile capabilities is increasing. One of the important areas of this need is chemical mechanical planarization (CMP) process. We introduce a new generation of atomic force profiler (AFP) using decoupled scanners design. The system is capable of providing small-scale profiling using XY scanner and large-scale profiling using sliding stage. Decoupled scanners design enables enhanced vision which helps minimizing the positioning error for locations of interest in case of highly polished dies. Non-Contact mode imaging is another feature of interest in this system which is used for surface roughness measurement, automatic defect review, and deep trench measurement. Examples of the measurements performed using the atomic force profiler are demonstrated.

The Neglected Situation: Assessment Performance and Interaction in Context

ERIC Educational Resources Information Center

Maddox, Bryan

2015-01-01

Informed by Goffman's influential essay on "The neglected situation" this paper examines the contextual and interactive dimensions of performance in large-scale educational assessments. The paper applies Goffman's participation framework and associated theory in linguistic anthropology to examine how testing situations are framed and…

Perceived Stress, Energy Drink Consumption, and Academic Performance among College Students

ERIC Educational Resources Information Center

Pettit, Michele L.; DeBarr, Kathy A.

2011-01-01

Objective: This study explored relationships regarding perceived stress, energy drink consumption, and academic performance among college students. Participants: Participants included 136 undergraduates attending a large southern plains university. Methods: Participants completed surveys including items from the Perceived Stress Scale and items to…

Scaling properties of the Arctic sea ice Deformation from Buoy Dispersion Analysis

NASA Astrophysics Data System (ADS)

Weiss, J.; Rampal, P.; Marsan, D.; Lindsay, R.; Stern, H.

2007-12-01

A temporal and spatial scaling analysis of Arctic sea ice deformation is performed over time scales from 3 hours to 3 months and over spatial scales from 300 m to 300 km. The deformation is derived from the dispersion of pairs of drifting buoys, using the IABP (International Arctic Buoy Program) buoy data sets. This study characterizes the deformation of a very large solid plate -the Arctic sea ice cover- stressed by heterogeneous forcing terms like winds and ocean currents. It shows that the sea ice deformation rate depends on the scales of observation following specific space and time scaling laws. These scaling properties share similarities with those observed for turbulent fluids, especially for the ocean and the atmosphere. However, in our case, the time scaling exponent depends on the spatial scale, and the spatial exponent on the temporal scale, which implies a time/space coupling. An analysis of the exponent values shows that Arctic sea ice deformation is very heterogeneous and intermittent whatever the scales, i.e. it cannot be considered as viscous-like, even at very large time and/or spatial scales. Instead, it suggests a deformation accommodated by a multi-scale fracturing/faulting processes.

Deep convolutional neural network based antenna selection in multiple-input multiple-output system

NASA Astrophysics Data System (ADS)

Cai, Jiaxin; Li, Yan; Hu, Ying

2018-03-01

Antenna selection of wireless communication system has attracted increasing attention due to the challenge of keeping a balance between communication performance and computational complexity in large-scale Multiple-Input MultipleOutput antenna systems. Recently, deep learning based methods have achieved promising performance for large-scale data processing and analysis in many application fields. This paper is the first attempt to introduce the deep learning technique into the field of Multiple-Input Multiple-Output antenna selection in wireless communications. First, the label of attenuation coefficients channel matrix is generated by minimizing the key performance indicator of training antenna systems. Then, a deep convolutional neural network that explicitly exploits the massive latent cues of attenuation coefficients is learned on the training antenna systems. Finally, we use the adopted deep convolutional neural network to classify the channel matrix labels of test antennas and select the optimal antenna subset. Simulation experimental results demonstrate that our method can achieve better performance than the state-of-the-art baselines for data-driven based wireless antenna selection.

Static analysis techniques for semiautomatic synthesis of message passing software skeletons

DOE PAGES

Sottile, Matthew; Dagit, Jason; Zhang, Deli; ...

2015-06-29

The design of high-performance computing architectures demands performance analysis of large-scale parallel applications to derive various parameters concerning hardware design and software development. The process of performance analysis and benchmarking an application can be done in several ways with varying degrees of fidelity. One of the most cost-effective ways is to do a coarse-grained study of large-scale parallel applications through the use of program skeletons. The concept of a “program skeleton” that we discuss in this article is an abstracted program that is derived from a larger program where source code that is determined to be irrelevant is removed formore » the purposes of the skeleton. In this work, we develop a semiautomatic approach for extracting program skeletons based on compiler program analysis. Finally, we demonstrate correctness of our skeleton extraction process by comparing details from communication traces, as well as show the performance speedup of using skeletons by running simulations in the SST/macro simulator.« less

Externally induced frontoparietal synchronization modulates network dynamics and enhances working memory performance.

PubMed

Violante, Ines R; Li, Lucia M; Carmichael, David W; Lorenz, Romy; Leech, Robert; Hampshire, Adam; Rothwell, John C; Sharp, David J

2017-03-14

Cognitive functions such as working memory (WM) are emergent properties of large-scale network interactions. Synchronisation of oscillatory activity might contribute to WM by enabling the coordination of long-range processes. However, causal evidence for the way oscillatory activity shapes network dynamics and behavior in humans is limited. Here we applied transcranial alternating current stimulation (tACS) to exogenously modulate oscillatory activity in a right frontoparietal network that supports WM. Externally induced synchronization improved performance when cognitive demands were high. Simultaneously collected fMRI data reveals tACS effects dependent on the relative phase of the stimulation and the internal cognitive processing state. Specifically, synchronous tACS during the verbal WM task increased parietal activity, which correlated with behavioral performance. Furthermore, functional connectivity results indicate that the relative phase of frontoparietal stimulation influences information flow within the WM network. Overall, our findings demonstrate a link between behavioral performance in a demanding WM task and large-scale brain synchronization.

Externally induced frontoparietal synchronization modulates network dynamics and enhances working memory performance

PubMed Central

Violante, Ines R; Li, Lucia M; Carmichael, David W; Lorenz, Romy; Leech, Robert; Hampshire, Adam; Rothwell, John C; Sharp, David J

2017-01-01

Cognitive functions such as working memory (WM) are emergent properties of large-scale network interactions. Synchronisation of oscillatory activity might contribute to WM by enabling the coordination of long-range processes. However, causal evidence for the way oscillatory activity shapes network dynamics and behavior in humans is limited. Here we applied transcranial alternating current stimulation (tACS) to exogenously modulate oscillatory activity in a right frontoparietal network that supports WM. Externally induced synchronization improved performance when cognitive demands were high. Simultaneously collected fMRI data reveals tACS effects dependent on the relative phase of the stimulation and the internal cognitive processing state. Specifically, synchronous tACS during the verbal WM task increased parietal activity, which correlated with behavioral performance. Furthermore, functional connectivity results indicate that the relative phase of frontoparietal stimulation influences information flow within the WM network. Overall, our findings demonstrate a link between behavioral performance in a demanding WM task and large-scale brain synchronization. DOI: http://dx.doi.org/10.7554/eLife.22001.001 PMID:28288700

Modal interactions between a large-wavelength inclined interface and small-wavelength multimode perturbations in a Richtmyer-Meshkov instability

NASA Astrophysics Data System (ADS)

McFarland, Jacob A.; Reilly, David; Black, Wolfgang; Greenough, Jeffrey A.; Ranjan, Devesh

2015-07-01

The interaction of a small-wavelength multimodal perturbation with a large-wavelength inclined interface perturbation is investigated for the reshocked Richtmyer-Meshkov instability using three-dimensional simulations. The ares code, developed at Lawrence Livermore National Laboratory, was used for these simulations and a detailed comparison of simulation results and experiments performed at the Georgia Tech Shock Tube facility is presented first for code validation. Simulation results are presented for four cases that vary in large-wavelength perturbation amplitude and the presence of secondary small-wavelength multimode perturbations. Previously developed measures of mixing and turbulence quantities are presented that highlight the large variation in perturbation length scales created by the inclined interface and the multimode complex perturbation. Measures are developed for entrainment, and turbulence anisotropy that help to identify the effects of and competition between each perturbations type. It is shown through multiple measures that before reshock the flow processes a distinct memory of the initial conditions that is present in both large-scale-driven entrainment measures and small-scale-driven mixing measures. After reshock the flow develops to a turbulentlike state that retains a memory of high-amplitude but not low-amplitude large-wavelength perturbations. It is also shown that the high-amplitude large-wavelength perturbation is capable of producing small-scale mixing and turbulent features similar to the small-wavelength multimode perturbations.

Cloud Computing for Complex Performance Codes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Appel, Gordon John; Hadgu, Teklu; Klein, Brandon Thorin

This report describes the use of cloud computing services for running complex public domain performance assessment problems. The work consisted of two phases: Phase 1 was to demonstrate complex codes, on several differently configured servers, could run and compute trivial small scale problems in a commercial cloud infrastructure. Phase 2 focused on proving non-trivial large scale problems could be computed in the commercial cloud environment. The cloud computing effort was successfully applied using codes of interest to the geohydrology and nuclear waste disposal modeling community.

Bursting process of large- and small-scale structures in turbulent boundary layer perturbed by a cylinder roughness element

NASA Astrophysics Data System (ADS)

Tang, Zhanqi; Jiang, Nan; Zheng, Xiaobo; Wu, Yanhua

2016-05-01

Hot-wire measurements on a turbulent boundary layer flow perturbed by a wall-mounted cylinder roughness element (CRE) are carried out in this study. The cylindrical element protrudes into the logarithmic layer, which is similar to those employed in turbulent boundary layers by Ryan et al. (AIAA J 49:2210-2220, 2011. doi: 10.2514/1.j051012) and Zheng and Longmire (J Fluid Mech 748:368-398, 2014. doi: 10.1017/jfm.2014.185) and in turbulent channel flow by Pathikonda and Christensen (AIAA J 53:1-10, 2014. doi: 10.2514/1.j053407). The similar effects on both the mean velocity and Reynolds stress are observed downstream of the CRE perturbation. The series of hot-wire data are decomposed into large- and small-scale fluctuations, and the characteristics of large- and small-scale bursting process are observed, by comparing the bursting duration, period and frequency between CRE-perturbed case and unperturbed case. It is indicated that the CRE perturbation performs the significant impact on the large- and small-scale structures, but within the different impact scenario. Moreover, the large-scale bursting process imposes a modulation on the bursting events of small-scale fluctuations and the overall trend of modulation is not essentially sensitive to the present CRE perturbation, even the modulation extent is modified. The conditionally averaging fluctuations are also plotted, which further confirms the robustness of the bursting modulation in the present experiments.

The TeraShake Computational Platform for Large-Scale Earthquake Simulations

NASA Astrophysics Data System (ADS)

Cui, Yifeng; Olsen, Kim; Chourasia, Amit; Moore, Reagan; Maechling, Philip; Jordan, Thomas

Geoscientific and computer science researchers with the Southern California Earthquake Center (SCEC) are conducting a large-scale, physics-based, computationally demanding earthquake system science research program with the goal of developing predictive models of earthquake processes. The computational demands of this program continue to increase rapidly as these researchers seek to perform physics-based numerical simulations of earthquake processes for larger meet the needs of this research program, a multiple-institution team coordinated by SCEC has integrated several scientific codes into a numerical modeling-based research tool we call the TeraShake computational platform (TSCP). A central component in the TSCP is a highly scalable earthquake wave propagation simulation program called the TeraShake anelastic wave propagation (TS-AWP) code. In this chapter, we describe how we extended an existing, stand-alone, wellvalidated, finite-difference, anelastic wave propagation modeling code into the highly scalable and widely used TS-AWP and then integrated this code into the TeraShake computational platform that provides end-to-end (initialization to analysis) research capabilities. We also describe the techniques used to enhance the TS-AWP parallel performance on TeraGrid supercomputers, as well as the TeraShake simulations phases including input preparation, run time, data archive management, and visualization. As a result of our efforts to improve its parallel efficiency, the TS-AWP has now shown highly efficient strong scaling on over 40K processors on IBM’s BlueGene/L Watson computer. In addition, the TSCP has developed into a computational system that is useful to many members of the SCEC community for performing large-scale earthquake simulations.

Channel optimization of high-intensity laser beams in millimeter-scale plasmas.

PubMed

Ceurvorst, L; Savin, A; Ratan, N; Kasim, M F; Sadler, J; Norreys, P A; Habara, H; Tanaka, K A; Zhang, S; Wei, M S; Ivancic, S; Froula, D H; Theobald, W

2018-04-01

Channeling experiments were performed at the OMEGA EP facility using relativistic intensity (>10^{18}W/cm^{2}) kilojoule laser pulses through large density scale length (∼390-570 μm) laser-produced plasmas, demonstrating the effects of the pulse's focal location and intensity as well as the plasma's temperature on the resulting channel formation. The results show deeper channeling when focused into hot plasmas and at lower densities, as expected. However, contrary to previous large-scale particle-in-cell studies, the results also indicate deeper penetration by short (10 ps), intense pulses compared to their longer-duration equivalents. This new observation has many implications for future laser-plasma research in the relativistic regime.

Channel optimization of high-intensity laser beams in millimeter-scale plasmas

NASA Astrophysics Data System (ADS)

Ceurvorst, L.; Savin, A.; Ratan, N.; Kasim, M. F.; Sadler, J.; Norreys, P. A.; Habara, H.; Tanaka, K. A.; Zhang, S.; Wei, M. S.; Ivancic, S.; Froula, D. H.; Theobald, W.

2018-04-01

Channeling experiments were performed at the OMEGA EP facility using relativistic intensity (>1018W/cm 2 ) kilojoule laser pulses through large density scale length (˜390 -570 μ m ) laser-produced plasmas, demonstrating the effects of the pulse's focal location and intensity as well as the plasma's temperature on the resulting channel formation. The results show deeper channeling when focused into hot plasmas and at lower densities, as expected. However, contrary to previous large-scale particle-in-cell studies, the results also indicate deeper penetration by short (10 ps), intense pulses compared to their longer-duration equivalents. This new observation has many implications for future laser-plasma research in the relativistic regime.

SIGN SINGULARITY AND FLARES IN SOLAR ACTIVE REGION NOAA 11158

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sorriso-Valvo, L.; De Vita, G.; Kazachenko, M. D.

Solar Active Region NOAA 11158 has hosted a number of strong flares, including one X2.2 event. The complexity of current density and current helicity are studied through cancellation analysis of their sign-singular measure, which features power-law scaling. Spectral analysis is also performed, revealing the presence of two separate scaling ranges with different spectral index. The time evolution of parameters is discussed. Sudden changes of the cancellation exponents at the time of large flares and the presence of correlation with Extreme-Ultra-Violet and X-ray flux suggest that eruption of large flares can be linked to the small-scale properties of the current structures.

Analysis of Discrete-Source Damage Progression in a Tensile Stiffened Composite Panel

NASA Technical Reports Server (NTRS)

Wang, John T.; Lotts, Christine G.; Sleight, David W.

1999-01-01

This paper demonstrates the progressive failure analysis capability in NASA Langley s COMET-AR finite element analysis code on a large-scale built-up composite structure. A large-scale five stringer composite panel with a 7-in. long discrete source damage was analyzed from initial loading to final failure including the geometric and material nonlinearities. Predictions using different mesh sizes, different saw cut modeling approaches, and different failure criteria were performed and assessed. All failure predictions have a reasonably good correlation with the test result.

A 100,000 Scale Factor Radar Range.

PubMed

Blanche, Pierre-Alexandre; Neifeld, Mark; Peyghambarian, Nasser

2017-12-19

The radar cross section of an object is an important electromagnetic property that is often measured in anechoic chambers. However, for very large and complex structures such as ships or sea and land clutters, this common approach is not practical. The use of computer simulations is also not viable since it would take many years of computational time to model and predict the radar characteristics of such large objects. We have now devised a new scaling technique to overcome these difficulties, and make accurate measurements of the radar cross section of large items. In this article we demonstrate that by reducing the scale of the model by a factor 100,000, and using near infrared wavelength, the radar cross section can be determined in a tabletop setup. The accuracy of the method is compared to simulations, and an example of measurement is provided on a 1 mm highly detailed model of a ship. The advantages of this scaling approach is its versatility, and the possibility to perform fast, convenient, and inexpensive measurements.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rubel, Oliver; Loring, Burlen; Vay, Jean -Luc

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analyticsmore » to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://bitbucket.org/berkeleylab/warpiv. The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material https://extras.computer.org/extra/mcg2016030022s1.pdf provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.« less

Hybrid Reynolds-Averaged/Large Eddy Simulation of the Flow in a Model SCRamjet Cavity Flameholder

NASA Technical Reports Server (NTRS)

Baurle, R. A.

2016-01-01

Steady-state and scale-resolving simulations have been performed for flow in and around a model scramjet combustor flameholder. Experimental data available for this configuration include velocity statistics obtained from particle image velocimetry. Several turbulence models were used for the steady-state Reynolds-averaged simulations which included both linear and non-linear eddy viscosity models. The scale-resolving simulations used a hybrid Reynolds-averaged/large eddy simulation strategy that is designed to be a large eddy simulation everywhere except in the inner portion (log layer and below) of the boundary layer. Hence, this formulation can be regarded as a wall-modeled large eddy simulation. This e ort was undertaken to not only assess the performance of the hybrid Reynolds-averaged / large eddy simulation modeling approach in a flowfield of interest to the scramjet research community, but to also begin to understand how this capability can best be used to augment standard Reynolds-averaged simulations. The numerical errors were quantified for the steady-state simulations, and at least qualitatively assessed for the scale-resolving simulations prior to making any claims of predictive accuracy relative to the measurements. The steady-state Reynolds-averaged results displayed a high degree of variability when comparing the flameholder fuel distributions obtained from each turbulence model. This prompted the consideration of applying the higher-fidelity scale-resolving simulations as a surrogate "truth" model to calibrate the Reynolds-averaged closures in a non-reacting setting prior to their use for the combusting simulations. In general, the Reynolds-averaged velocity profile predictions at the lowest fueling level matched the particle imaging measurements almost as well as was observed for the non-reacting condition. However, the velocity field predictions proved to be more sensitive to the flameholder fueling rate than was indicated in the measurements.

WarpIV: In situ visualization and analysis of ion accelerator simulations

DOE PAGES

Rubel, Oliver; Loring, Burlen; Vay, Jean -Luc; ...

2016-05-09

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analyticsmore » to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://bitbucket.org/berkeleylab/warpiv. The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material https://extras.computer.org/extra/mcg2016030022s1.pdf provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.« less

GoFFish: A Sub-Graph Centric Framework for Large-Scale Graph Analytics1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simmhan, Yogesh; Kumbhare, Alok; Wickramaarachchi, Charith

2014-08-25

Large scale graph processing is a major research area for Big Data exploration. Vertex centric programming models like Pregel are gaining traction due to their simple abstraction that allows for scalable execution on distributed systems naturally. However, there are limitations to this approach which cause vertex centric algorithms to under-perform due to poor compute to communication overhead ratio and slow convergence of iterative superstep. In this paper we introduce GoFFish a scalable sub-graph centric framework co-designed with a distributed persistent graph storage for large scale graph analytics on commodity clusters. We introduce a sub-graph centric programming abstraction that combines themore » scalability of a vertex centric approach with the flexibility of shared memory sub-graph computation. We map Connected Components, SSSP and PageRank algorithms to this model to illustrate its flexibility. Further, we empirically analyze GoFFish using several real world graphs and demonstrate its significant performance improvement, orders of magnitude in some cases, compared to Apache Giraph, the leading open source vertex centric implementation. We map Connected Components, SSSP and PageRank algorithms to this model to illustrate its flexibility. Further, we empirically analyze GoFFish using several real world graphs and demonstrate its significant performance improvement, orders of magnitude in some cases, compared to Apache Giraph, the leading open source vertex centric implementation.« less

A comprehensive evaluation of two MODIS evapotranspiration products over the conterminous United States: using point and gridded FLUXNET and water balance ET

USGS Publications Warehouse

Velpuri, Naga M.; Senay, Gabriel B.; Singh, Ramesh K.; Bohms, Stefanie; Verdin, James P.

2013-01-01

Remote sensing datasets are increasingly being used to provide spatially explicit large scale evapotranspiration (ET) estimates. Extensive evaluation of such large scale estimates is necessary before they can be used in various applications. In this study, two monthly MODIS 1 km ET products, MODIS global ET (MOD16) and Operational Simplified Surface Energy Balance (SSEBop) ET, are validated over the conterminous United States at both point and basin scales. Point scale validation was performed using eddy covariance FLUXNET ET (FLET) data (2001–2007) aggregated by year, land cover, elevation and climate zone. Basin scale validation was performed using annual gridded FLUXNET ET (GFET) and annual basin water balance ET (WBET) data aggregated by various hydrologic unit code (HUC) levels. Point scale validation using monthly data aggregated by years revealed that the MOD16 ET and SSEBop ET products showed overall comparable annual accuracies. For most land cover types, both ET products showed comparable results. However, SSEBop showed higher performance for Grassland and Forest classes; MOD16 showed improved performance in the Woody Savanna class. Accuracy of both the ET products was also found to be comparable over different climate zones. However, SSEBop data showed higher skill score across the climate zones covering the western United States. Validation results at different HUC levels over 2000–2011 using GFET as a reference indicate higher accuracies for MOD16 ET data. MOD16, SSEBop and GFET data were validated against WBET (2000–2009), and results indicate that both MOD16 and SSEBop ET matched the accuracies of the global GFET dataset at different HUC levels. Our results indicate that both MODIS ET products effectively reproduced basin scale ET response (up to 25% uncertainty) compared to CONUS-wide point-based ET response (up to 50–60% uncertainty) illustrating the reliability of MODIS ET products for basin-scale ET estimation. Results from this research would guide the additional parameter refinement required for the MOD16 and SSEBop algorithms in order to further improve their accuracy and performance for agro-hydrologic applications.

Visual Analysis of Cloud Computing Performance Using Behavioral Lines.

PubMed

Muelder, Chris; Zhu, Biao; Chen, Wei; Zhang, Hongxin; Ma, Kwan-Liu

2016-02-29

Cloud computing is an essential technology to Big Data analytics and services. A cloud computing system is often comprised of a large number of parallel computing and storage devices. Monitoring the usage and performance of such a system is important for efficient operations, maintenance, and security. Tracing every application on a large cloud system is untenable due to scale and privacy issues. But profile data can be collected relatively efficiently by regularly sampling the state of the system, including properties such as CPU load, memory usage, network usage, and others, creating a set of multivariate time series for each system. Adequate tools for studying such large-scale, multidimensional data are lacking. In this paper, we present a visual based analysis approach to understanding and analyzing the performance and behavior of cloud computing systems. Our design is based on similarity measures and a layout method to portray the behavior of each compute node over time. When visualizing a large number of behavioral lines together, distinct patterns often appear suggesting particular types of performance bottleneck. The resulting system provides multiple linked views, which allow the user to interactively explore the data by examining the data or a selected subset at different levels of detail. Our case studies, which use datasets collected from two different cloud systems, show that this visual based approach is effective in identifying trends and anomalies of the systems.

HiQuant: Rapid Postquantification Analysis of Large-Scale MS-Generated Proteomics Data.

PubMed

Bryan, Kenneth; Jarboui, Mohamed-Ali; Raso, Cinzia; Bernal-Llinares, Manuel; McCann, Brendan; Rauch, Jens; Boldt, Karsten; Lynn, David J

2016-06-03

Recent advances in mass-spectrometry-based proteomics are now facilitating ambitious large-scale investigations of the spatial and temporal dynamics of the proteome; however, the increasing size and complexity of these data sets is overwhelming current downstream computational methods, specifically those that support the postquantification analysis pipeline. Here we present HiQuant, a novel application that enables the design and execution of a postquantification workflow, including common data-processing steps, such as assay normalization and grouping, and experimental replicate quality control and statistical analysis. HiQuant also enables the interpretation of results generated from large-scale data sets by supporting interactive heatmap analysis and also the direct export to Cytoscape and Gephi, two leading network analysis platforms. HiQuant may be run via a user-friendly graphical interface and also supports complete one-touch automation via a command-line mode. We evaluate HiQuant's performance by analyzing a large-scale, complex interactome mapping data set and demonstrate a 200-fold improvement in the execution time over current methods. We also demonstrate HiQuant's general utility by analyzing proteome-wide quantification data generated from both a large-scale public tyrosine kinase siRNA knock-down study and an in-house investigation into the temporal dynamics of the KSR1 and KSR2 interactomes. Download HiQuant, sample data sets, and supporting documentation at http://hiquant.primesdb.eu .

MODFLOW-LGR: Practical application to a large regional dataset

NASA Astrophysics Data System (ADS)

Barnes, D.; Coulibaly, K. M.

2011-12-01

In many areas of the US, including southwest Florida, large regional-scale groundwater models have been developed to aid in decision making and water resources management. These models are subsequently used as a basis for site-specific investigations. Because the large scale of these regional models is not appropriate for local application, refinement is necessary to analyze the local effects of pumping wells and groundwater related projects at specific sites. The most commonly used approach to date is Telescopic Mesh Refinement or TMR. It allows the extraction of a subset of the large regional model with boundary conditions derived from the regional model results. The extracted model is then updated and refined for local use using a variable sized grid focused on the area of interest. MODFLOW-LGR, local grid refinement, is an alternative approach which allows model discretization at a finer resolution in areas of interest and provides coupling between the larger "parent" model and the locally refined "child." In the present work, these two approaches are tested on a mining impact assessment case in southwest Florida using a large regional dataset (The Lower West Coast Surficial Aquifer System Model). Various metrics for performance are considered. They include: computation time, water balance (as compared to the variable sized grid), calibration, implementation effort, and application advantages and limitations. The results indicate that MODFLOW-LGR is a useful tool to improve local resolution of regional scale models. While performance metrics, such as computation time, are case-dependent (model size, refinement level, stresses involved), implementation effort, particularly when regional models of suitable scale are available, can be minimized. The creation of multiple child models within a larger scale parent model makes it possible to reuse the same calibrated regional dataset with minimal modification. In cases similar to the Lower West Coast model, where a model is larger than optimal for direct application as a parent grid, a combination of TMR and LGR approaches should be used to develop a suitable parent grid.

Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments.

PubMed

Ionescu, Catalin; Papava, Dragos; Olaru, Vlad; Sminchisescu, Cristian

2014-07-01

We introduce a new dataset, Human3.6M, of 3.6 Million accurate 3D Human poses, acquired by recording the performance of 5 female and 6 male subjects, under 4 different viewpoints, for training realistic human sensing systems and for evaluating the next generation of human pose estimation models and algorithms. Besides increasing the size of the datasets in the current state-of-the-art by several orders of magnitude, we also aim to complement such datasets with a diverse set of motions and poses encountered as part of typical human activities (taking photos, talking on the phone, posing, greeting, eating, etc.), with additional synchronized image, human motion capture, and time of flight (depth) data, and with accurate 3D body scans of all the subject actors involved. We also provide controlled mixed reality evaluation scenarios where 3D human models are animated using motion capture and inserted using correct 3D geometry, in complex real environments, viewed with moving cameras, and under occlusion. Finally, we provide a set of large-scale statistical models and detailed evaluation baselines for the dataset illustrating its diversity and the scope for improvement by future work in the research community. Our experiments show that our best large-scale model can leverage our full training set to obtain a 20% improvement in performance compared to a training set of the scale of the largest existing public dataset for this problem. Yet the potential for improvement by leveraging higher capacity, more complex models with our large dataset, is substantially vaster and should stimulate future research. The dataset together with code for the associated large-scale learning models, features, visualization tools, as well as the evaluation server, is available online at http://vision.imar.ro/human3.6m.

Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961-2000

NASA Astrophysics Data System (ADS)

Sanchez-Gomez, Emilia; Somot, S.; Déqué, M.

2009-10-01

One of the main concerns in regional climate modeling is to which extent limited-area regional climate models (RCM) reproduce the large-scale atmospheric conditions of their driving general circulation model (GCM). In this work we investigate the ability of a multi-model ensemble of regional climate simulations to reproduce the large-scale weather regimes of the driving conditions. The ensemble consists of a set of 13 RCMs on a European domain, driven at their lateral boundaries by the ERA40 reanalysis for the time period 1961-2000. Two sets of experiments have been completed with horizontal resolutions of 50 and 25 km, respectively. The spectral nudging technique has been applied to one of the models within the ensemble. The RCMs reproduce the weather regimes behavior in terms of composite pattern, mean frequency of occurrence and persistence reasonably well. The models also simulate well the long-term trends and the inter-annual variability of the frequency of occurrence. However, there is a non-negligible spread among the models which is stronger in summer than in winter. This spread is due to two reasons: (1) we are dealing with different models and (2) each RCM produces an internal variability. As far as the day-to-day weather regime history is concerned, the ensemble shows large discrepancies. At daily time scale, the model spread has also a seasonal dependence, being stronger in summer than in winter. Results also show that the spectral nudging technique improves the model performance in reproducing the large-scale of the driving field. In addition, the impact of increasing the number of grid points has been addressed by comparing the 25 and 50 km experiments. We show that the horizontal resolution does not affect significantly the model performance for large-scale circulation.

Evaluating the performance of a soil moisture data assimilation system for agricultural drought monitoring

USDA-ARS?s Scientific Manuscript database

Despite considerable interest in the application of land surface data assimilation systems (LDAS) for agricultural drought applications, relatively little is known about the large-scale performance of such systems and, thus, the optimal methodological approach for implementing them. To address this ...

Performance Analysis, Design Considerations, and Applications of Extreme-Scale In Situ Infrastructures

DOE PAGES

Ayachit, Utkarsh; Bauer, Andrew; Duque, Earl P. N.; ...

2016-11-01

A key trend facing extreme-scale computational science is the widening gap between computational and I/O rates, and the challenge that follows is how to best gain insight from simulation data when it is increasingly impractical to save it to persistent storage for subsequent visual exploration and analysis. One approach to this challenge is centered around the idea of in situ processing, where visualization and analysis processing is performed while data is still resident in memory. Our paper examines several key design and performance issues related to the idea of in situ processing at extreme scale on modern platforms: Scalability, overhead,more » performance measurement and analysis, comparison and contrast with a traditional post hoc approach, and interfacing with simulation codes. We illustrate these principles in practice with studies, conducted on large-scale HPC platforms, that include a miniapplication and multiple science application codes, one of which demonstrates in situ methods in use at greater than 1M-way concurrency.« less

Keeping on Track: Performance Profiles of Low Performers in Academic Educational Tracks

ERIC Educational Resources Information Center

Reed, Helen C.; van Wesel, Floryt; Ouwehand, Carolijn; Jolles, Jelle

2015-01-01

In countries with high differentiation between academic and vocational education, an individual's future prospects are strongly determined by the educational track to which he or she is assigned. This large-scale, cross-sectional study focuses on low-performing students in academic tracks who face being moved to a vocational track. If more is…

Experimental and analytical investigations to improve low-speed performance and stability and control characteristics of supersonic cruise fighter vehicles

NASA Technical Reports Server (NTRS)

Graham, A. B.

1977-01-01

Small- and large-scale models of supersonic cruise fighter vehicles were used to determine the effectiveness of airframe/propulsion integration concepts for improved low-speed performance and stability and control characteristics. Computer programs were used for engine/airframe sizing studies to yield optimum vehicle performance.

Large-scale runoff generation - parsimonious parameterisation using high-resolution topography

NASA Astrophysics Data System (ADS)

Gong, L.; Halldin, S.; Xu, C.-Y.

2011-08-01

World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting at very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TRG only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the HydroSHEDS dataset with a resolution of 3" (around 90 m at the equator). The TRG algorithm was validated against the VIC algorithm in a common model framework in 3 river basins in different climates. The TRG algorithm performed equally well or marginally better than the VIC algorithm with one less parameter to be calibrated. The TRG algorithm also lacked equifinality problems and offered a realistic spatial pattern for runoff generation and evaporation.

Large-scale runoff generation - parsimonious parameterisation using high-resolution topography

NASA Astrophysics Data System (ADS)

Gong, L.; Halldin, S.; Xu, C.-Y.

2010-09-01

World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting a very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TGR only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the HydroSHEDS dataset with a resolution of 3'' (around 90 m at the equator). The TRG algorithm was validated against the VIC algorithm in a common model framework in 3 river basins in different climates. The TRG algorithm performed equally well or marginally better than the VIC algorithm with one less parameter to be calibrated. The TRG algorithm also lacked equifinality problems and offered a realistic spatial pattern for runoff generation and evaporation.

Profiling and Improving I/O Performance of a Large-Scale Climate Scientific Application

NASA Technical Reports Server (NTRS)

Liu, Zhuo; Wang, Bin; Wang, Teng; Tian, Yuan; Xu, Cong; Wang, Yandong; Yu, Weikuan; Cruz, Carlos A.; Zhou, Shujia; Clune, Tom;

Performing a Large-Scale Modal Test on the B2 Stand Crane at NASA's Stennis Space Center

NASA Technical Reports Server (NTRS)

Stasiunas, Eric C.; Parks, Russel A.; Sontag, Brendan D.

2018-01-01

A modal test of NASA's Space Launch System (SLS) Core Stage is scheduled to occur at the Stennis Space Center B2 test stand. A derrick crane with a 150-ft long boom, located at the top of the stand, will be used to suspend the Core Stage in order to achieve defined boundary conditions. During this suspended modal test, it is expected that dynamic coupling will occur between the crane and the Core Stage. Therefore, a separate modal test was performed on the B2 crane itself, in order to evaluate the varying dynamic characteristics and correlate math models of the crane. Performing a modal test on such a massive structure was challenging and required creative test setup and procedures, including implementing both AC and DC accelerometers, and performing both classical hammer and operational modal analysis. This paper describes the logistics required to perform this large-scale test, as well as details of the test setup, the modal test methods used, and an overview and application of the results.

Performing a Large-Scale Modal Test on the B2 Stand Crane at NASA's Stennis Space Center

NASA Technical Reports Server (NTRS)

Stasiunas, Eric C.; Parks, Russel A.

2018-01-01

A modal test of NASA’s Space Launch System (SLS) Core Stage is scheduled to occur prior to propulsion system verification testing at the Stennis Space Center B2 test stand. A derrick crane with a 180-ft long boom, located at the top of the stand, will be used to suspend the Core Stage in order to achieve defined boundary conditions. During this suspended modal test, it is expected that dynamic coupling will occur between the crane and the Core Stage. Therefore, a separate modal test was performed on the B2 crane itself, in order to evaluate the varying dynamic characteristics and correlate math models of the crane. Performing a modal test on such a massive structure was challenging and required creative test setup and procedures, including implementing both AC and DC accelerometers, and performing both classical hammer and operational modal analysis. This paper describes the logistics required to perform this large-scale test, as well as details of the test setup, the modal test methods used, and an overview of the results.

Stuttering, Induced Fluency, and Natural Fluency: A Hierarchical Series of Activation Likelihood Estimation Meta-Analyses

PubMed Central

Budde, Kristin S.; Barron, Daniel S.; Fox, Peter T.

2015-01-01

Developmental stuttering is a speech disorder most likely due to a heritable form of developmental dysmyelination impairing the function of the speech-motor system. Speech-induced brain-activation patterns in persons who stutter (PWS) are anomalous in various ways; the consistency of these aberrant patterns is a matter of ongoing debate. Here, we present a hierarchical series of coordinate-based meta-analyses addressing this issue. Two tiers of meta-analyses were performed on a 17-paper dataset (202 PWS; 167 fluent controls). Four large-scale (top-tier) meta-analyses were performed, two for each subject group (PWS and controls). These analyses robustly confirmed the regional effects previously postulated as “neural signatures of stuttering” (Brown 2005) and extended this designation to additional regions. Two smaller-scale (lower-tier) meta-analyses refined the interpretation of the large-scale analyses: 1) a between-group contrast targeting differences between PWS and controls (stuttering trait); and 2) a within-group contrast (PWS only) of stuttering with induced fluency (stuttering state). PMID:25463820

Continuous Flow Polymer Synthesis toward Reproducible Large-Scale Production for Efficient Bulk Heterojunction Organic Solar Cells.

PubMed

Pirotte, Geert; Kesters, Jurgen; Verstappen, Pieter; Govaerts, Sanne; Manca, Jean; Lutsen, Laurence; Vanderzande, Dirk; Maes, Wouter

2015-10-12

Organic photovoltaics (OPV) have attracted great interest as a solar cell technology with appealing mechanical, aesthetical, and economies-of-scale features. To drive OPV toward economic viability, low-cost, large-scale module production has to be realized in combination with increased top-quality material availability and minimal batch-to-batch variation. To this extent, continuous flow chemistry can serve as a powerful tool. In this contribution, a flow protocol is optimized for the high performance benzodithiophene-thienopyrroledione copolymer PBDTTPD and the material quality is probed through systematic solar-cell evaluation. A stepwise approach is adopted to turn the batch process into a reproducible and scalable continuous flow procedure. Solar cell devices fabricated using the obtained polymer batches deliver an average power conversion efficiency of 7.2 %. Upon incorporation of an ionic polythiophene-based cathodic interlayer, the photovoltaic performance could be enhanced to a maximum efficiency of 9.1 %. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Biometric identification: a holistic perspective

NASA Astrophysics Data System (ADS)

Nadel, Lawrence D.

2007-04-01

Significant advances continue to be made in biometric technology. However, the global war on terrorism and our increasingly electronic society have created the societal need for large-scale, interoperable biometric capabilities that challenge the capabilities of current off-the-shelf technology. At the same time, there are concerns that large-scale implementation of biometrics will infringe our civil liberties and offer increased opportunities for identity theft. This paper looks beyond the basic science and engineering of biometric sensors and fundamental matching algorithms and offers approaches for achieving greater performance and acceptability of applications enabled with currently available biometric technologies. The discussion focuses on three primary biometric system aspects: performance and scalability, interoperability, and cost benefit. Significant improvements in system performance and scalability can be achieved through careful consideration of the following elements: biometric data quality, human factors, operational environment, workflow, multibiometric fusion, and integrated performance modeling. Application interoperability hinges upon some of the factors noted above as well as adherence to interface, data, and performance standards. However, there are times when the price of conforming to such standards can be decreased local system performance. The development of biometric performance-based cost benefit models can help determine realistic requirements and acceptable designs.

Large Scale Laser Crystallization of Solution-based Alumina-doped Zinc Oxide (AZO) Nanoinks for Highly Transparent Conductive Electrode

PubMed Central

Nian, Qiong; Callahan, Michael; Saei, Mojib; Look, David; Efstathiadis, Harry; Bailey, John; Cheng, Gary J.

2015-01-01

A new method combining aqueous solution printing with UV Laser crystallization (UVLC) and post annealing is developed to deposit highly transparent and conductive Aluminum doped Zinc Oxide (AZO) films. This technique is able to rapidly produce large area AZO films with better structural and optoelectronic properties than most high vacuum deposition, suggesting a potential large-scale manufacturing technique. The optoelectronic performance improvement attributes to UVLC and forming gas annealing (FMG) induced grain boundary density decrease and electron traps passivation at grain boundaries. The physical model and computational simulation developed in this work could be applied to thermal treatment of many other metal oxide films. PMID:26515670

Modeling sediment yield in small catchments at event scale: Model comparison, development and evaluation

NASA Astrophysics Data System (ADS)

Tan, Z.; Leung, L. R.; Li, H. Y.; Tesfa, T. K.

2017-12-01

Sediment yield (SY) has significant impacts on river biogeochemistry and aquatic ecosystems but it is rarely represented in Earth System Models (ESMs). Existing SY models focus on estimating SY from large river basins or individual catchments so it is not clear how well they simulate SY in ESMs at larger spatial scales and globally. In this study, we compare the strengths and weaknesses of eight well-known SY models in simulating annual mean SY at about 400 small catchments ranging in size from 0.22 to 200 km2 in the US, Canada and Puerto Rico. In addition, we also investigate the performance of these models in simulating event-scale SY at six catchments in the US using high-quality hydrological inputs. The model comparison shows that none of the models can reproduce the SY at large spatial scales but the Morgan model performs the better than others despite its simplicity. In all model simulations, large underestimates occur in catchments with very high SY. A possible pathway to reduce the discrepancies is to incorporate sediment detachment by landsliding, which is currently not included in the models being evaluated. We propose a new SY model that is based on the Morgan model but including a landsliding soil detachment scheme that is being developed. Along with the results of the model comparison and evaluation, preliminary findings from the revised Morgan model will be presented.

Los Alamos Explosives Performance Key to Stockpile Stewardship

ScienceCinema

Dattelbaum, Dana

2018-02-14

As the U.S. Nuclear Deterrent ages, one essential factor in making sure that the weapons will continue to perform as designed is understanding the fundamental properties of the high explosives that are part of a nuclear weapons system. As nuclear weapons go through life extension programs, some changes may be advantageous, particularly through the addition of what are known as "insensitive" high explosives that are much less likely to accidentally detonate than the already very safe "conventional" high explosives that are used in most weapons. At Los Alamos National Laboratory explosives research includes a wide variety of both large- and small-scale experiments that include small contained detonations, gas and powder gun firings, larger outdoor detonations, large-scale hydrodynamic tests, and at the Nevada Nuclear Security Site, underground sub-critical experiments.

A Large number of fast cosmological simulations

NASA Astrophysics Data System (ADS)

Koda, Jun; Kazin, E.; Blake, C.

2014-01-01

Mock galaxy catalogs are essential tools to analyze large-scale structure data. Many independent realizations of mock catalogs are necessary to evaluate the uncertainties in the measurements. We perform 3600 cosmological simulations for the WiggleZ Dark Energy Survey to obtain the new improved Baron Acoustic Oscillation (BAO) cosmic distance measurements using the density field "reconstruction" technique. We use 1296^3 particles in a periodic box of 600/h Mpc on a side, which is the minimum requirement from the survey volume and observed galaxies. In order to perform such large number of simulations, we developed a parallel code using the COmoving Lagrangian Acceleration (COLA) method, which can simulate cosmological large-scale structure reasonably well with only 10 time steps. Our simulation is more than 100 times faster than conventional N-body simulations; one COLA simulation takes only 15 minutes with 216 computing cores. We have completed the 3600 simulations with a reasonable computation time of 200k core hours. We also present the results of the revised WiggleZ BAO distance measurement, which are significantly improved by the reconstruction technique.

Scalable clustering algorithms for continuous environmental flow cytometry.

PubMed

Hyrkas, Jeremy; Clayton, Sophie; Ribalet, Francois; Halperin, Daniel; Armbrust, E Virginia; Howe, Bill

2016-02-01

Recent technological innovations in flow cytometry now allow oceanographers to collect high-frequency flow cytometry data from particles in aquatic environments on a scale far surpassing conventional flow cytometers. The SeaFlow cytometer continuously profiles microbial phytoplankton populations across thousands of kilometers of the surface ocean. The data streams produced by instruments such as SeaFlow challenge the traditional sample-by-sample approach in cytometric analysis and highlight the need for scalable clustering algorithms to extract population information from these large-scale, high-frequency flow cytometers. We explore how available algorithms commonly used for medical applications perform at classification of such a large-scale, environmental flow cytometry data. We apply large-scale Gaussian mixture models to massive datasets using Hadoop. This approach outperforms current state-of-the-art cytometry classification algorithms in accuracy and can be coupled with manual or automatic partitioning of data into homogeneous sections for further classification gains. We propose the Gaussian mixture model with partitioning approach for classification of large-scale, high-frequency flow cytometry data. Source code available for download at https://github.com/jhyrkas/seaflow_cluster, implemented in Java for use with Hadoop. hyrkas@cs.washington.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

High-Resiliency and Auto-Scaling of Large-Scale Cloud Computing for OCO-2 L2 Full Physics Processing

NASA Astrophysics Data System (ADS)

Hua, H.; Manipon, G.; Starch, M.; Dang, L. B.; Southam, P.; Wilson, B. D.; Avis, C.; Chang, A.; Cheng, C.; Smyth, M.; McDuffie, J. L.; Ramirez, P.

2015-12-01

Next generation science data systems are needed to address the incoming flood of data from new missions such as SWOT and NISAR where data volumes and data throughput rates are order of magnitude larger than present day missions. Additionally, traditional means of procuring hardware on-premise are already limited due to facilities capacity constraints for these new missions. Existing missions, such as OCO-2, may also require high turn-around time for processing different science scenarios where on-premise and even traditional HPC computing environments may not meet the high processing needs. We present our experiences on deploying a hybrid-cloud computing science data system (HySDS) for the OCO-2 Science Computing Facility to support large-scale processing of their Level-2 full physics data products. We will explore optimization approaches to getting best performance out of hybrid-cloud computing as well as common issues that will arise when dealing with large-scale computing. Novel approaches were utilized to do processing on Amazon's spot market, which can potentially offer ~10X costs savings but with an unpredictable computing environment based on market forces. We will present how we enabled high-tolerance computing in order to achieve large-scale computing as well as operational cost savings.

Large-scale parallel genome assembler over cloud computing environment.

PubMed

Das, Arghya Kusum; Koppa, Praveen Kumar; Goswami, Sayan; Platania, Richard; Park, Seung-Jong

2017-06-01

The size of high throughput DNA sequencing data has already reached the terabyte scale. To manage this huge volume of data, many downstream sequencing applications started using locality-based computing over different cloud infrastructures to take advantage of elastic (pay as you go) resources at a lower cost. However, the locality-based programming model (e.g. MapReduce) is relatively new. Consequently, developing scalable data-intensive bioinformatics applications using this model and understanding the hardware environment that these applications require for good performance, both require further research. In this paper, we present a de Bruijn graph oriented Parallel Giraph-based Genome Assembler (GiGA), as well as the hardware platform required for its optimal performance. GiGA uses the power of Hadoop (MapReduce) and Giraph (large-scale graph analysis) to achieve high scalability over hundreds of compute nodes by collocating the computation and data. GiGA achieves significantly higher scalability with competitive assembly quality compared to contemporary parallel assemblers (e.g. ABySS and Contrail) over traditional HPC cluster. Moreover, we show that the performance of GiGA is significantly improved by using an SSD-based private cloud infrastructure over traditional HPC cluster. We observe that the performance of GiGA on 256 cores of this SSD-based cloud infrastructure closely matches that of 512 cores of traditional HPC cluster.

Design of coated standing nanowire array solar cell performing beyond the planar efficiency limits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zeng, Yang; Ye, Qinghao; Shen, Wenzhong, E-mail: wzshen@sjtu.edu.cn

2016-05-28

The single standing nanowire (SNW) solar cells have been proven to perform beyond the planar efficiency limits in both open-circuit voltage and internal quantum efficiency due to the built-in concentration and the shifting of the absorption front. However, the expandability of these nano-scale units to a macro-scale photovoltaic device remains unsolved. The main difficulty lies in the simultaneous preservation of an effective built-in concentration in each unit cell and a broadband high absorption capability of their array. Here, we have provided a detailed theoretical guideline for realizing a macro-scale solar cell that performs furthest beyond the planar limits. The keymore » lies in a complementary design between the light-trapping of the single SNWs and that of the photonic crystal slab formed by the array. By tuning the hybrid HE modes of the SNWs through the thickness of a coaxial dielectric coating, the optimized coated SNW array can sustain an absorption rate over 97.5% for a period as large as 425 nm, which, together with the inherited carrier extraction advantage, leads to a cell efficiency increment of 30% over the planar limit. This work has demonstrated the viability of a large-size solar cell that performs beyond the planar limits.« less

Scaling properties of sea ice deformation from buoy dispersion analysis

NASA Astrophysics Data System (ADS)

Rampal, P.; Weiss, J.; Marsan, D.; Lindsay, R.; Stern, H.

2008-03-01

A temporal and spatial scaling analysis of Arctic sea ice deformation is performed over timescales from 3 h to 3 months and over spatial scales from 300 m to 300 km. The deformation is derived from the dispersion of pairs of drifting buoys, using the IABP (International Arctic Buoy Program) buoy data sets. This study characterizes the deformation of a very large solid plate (the Arctic sea ice cover) stressed by heterogeneous forcing terms like winds and ocean currents. It shows that the sea ice deformation rate depends on the scales of observation following specific space and time scaling laws. These scaling properties share similarities with those observed for turbulent fluids, especially for the ocean and the atmosphere. However, in our case, the time scaling exponent depends on the spatial scale, and the spatial exponent on the temporal scale, which implies a time/space coupling. An analysis of the exponent values shows that Arctic sea ice deformation is very heterogeneous and intermittent whatever the scales, i.e., it cannot be considered as viscous-like, even at very large time and/or spatial scales. Instead, it suggests a deformation accommodated by a multiscale fracturing/faulting processes.

A priori and a posteriori investigations for developing large eddy simulations of multi-species turbulent mixing under high-pressure conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Borghesi, Giulio; Bellan, Josette, E-mail: josette.bellan@jpl.nasa.gov; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109-8099

2015-03-15

A Direct Numerical Simulation (DNS) database was created representing mixing of species under high-pressure conditions. The configuration considered is that of a temporally evolving mixing layer. The database was examined and analyzed for the purpose of modeling some of the unclosed terms that appear in the Large Eddy Simulation (LES) equations. Several metrics are used to understand the LES modeling requirements. First, a statistical analysis of the DNS-database large-scale flow structures was performed to provide a metric for probing the accuracy of the proposed LES models as the flow fields obtained from accurate LESs should contain structures of morphology statisticallymore » similar to those observed in the filtered-and-coarsened DNS (FC-DNS) fields. To characterize the morphology of the large-scales structures, the Minkowski functionals of the iso-surfaces were evaluated for two different fields: the second-invariant of the rate of deformation tensor and the irreversible entropy production rate. To remove the presence of the small flow scales, both of these fields were computed using the FC-DNS solutions. It was found that the large-scale structures of the irreversible entropy production rate exhibit higher morphological complexity than those of the second invariant of the rate of deformation tensor, indicating that the burden of modeling will be on recovering the thermodynamic fields. Second, to evaluate the physical effects which must be modeled at the subfilter scale, an a priori analysis was conducted. This a priori analysis, conducted in the coarse-grid LES regime, revealed that standard closures for the filtered pressure, the filtered heat flux, and the filtered species mass fluxes, in which a filtered function of a variable is equal to the function of the filtered variable, may no longer be valid for the high-pressure flows considered in this study. The terms requiring modeling are the filtered pressure, the filtered heat flux, the filtered pressure work, and the filtered species mass fluxes. Improved models were developed based on a scale-similarity approach and were found to perform considerably better than the classical ones. These improved models were also assessed in an a posteriori study. Different combinations of the standard models and the improved ones were tested. At the relatively small Reynolds numbers achievable in DNS and at the relatively small filter widths used here, the standard models for the filtered pressure, the filtered heat flux, and the filtered species fluxes were found to yield accurate results for the morphology of the large-scale structures present in the flow. Analysis of the temporal evolution of several volume-averaged quantities representative of the mixing layer growth, and of the cross-stream variation of homogeneous-plane averages and second-order correlations, as well as of visualizations, indicated that the models performed equivalently for the conditions of the simulations. The expectation is that at the much larger Reynolds numbers and much larger filter widths used in practical applications, the improved models will have much more accurate performance than the standard one.« less

Experience in using commercial clouds in CMS

NASA Astrophysics Data System (ADS)

Bauerdick, L.; Bockelman, B.; Dykstra, D.; Fuess, S.; Garzoglio, G.; Girone, M.; Gutsche, O.; Holzman, B.; Hufnagel, D.; Kim, H.; Kennedy, R.; Mason, D.; Spentzouris, P.; Timm, S.; Tiradani, A.; Vaandering, E.; CMS Collaboration

2017-10-01

Historically high energy physics computing has been performed on large purpose-built computing systems. In the beginning there were single site computing facilities, which evolved into the Worldwide LHC Computing Grid (WLCG) used today. The vast majority of the WLCG resources are used for LHC computing and the resources are scheduled to be continuously used throughout the year. In the last several years there has been an explosion in capacity and capability of commercial and academic computing clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is a growing interest amongst the cloud providers to demonstrate the capability to perform large scale scientific computing. In this presentation we will discuss results from the CMS experiment using the Fermilab HEPCloud Facility, which utilized both local Fermilab resources and Amazon Web Services (AWS). The goal was to work with AWS through a matching grant to demonstrate a sustained scale approximately equal to half of the worldwide processing resources available to CMS. We will discuss the planning and technical challenges involved in organizing the most IO intensive CMS workflows on a large-scale set of virtualized resource provisioned by the Fermilab HEPCloud. We will describe the data handling and data management challenges. Also, we will discuss the economic issues and cost and operational efficiency comparison to our dedicated resources. At the end we will consider the changes in the working model of HEP computing in a domain with the availability of large scale resources scheduled at peak times.

Experience in using commercial clouds in CMS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bauerdick, L.; Bockelman, B.; Dykstra, D.

Historically high energy physics computing has been performed on large purposebuilt computing systems. In the beginning there were single site computing facilities, which evolved into the Worldwide LHC Computing Grid (WLCG) used today. The vast majority of the WLCG resources are used for LHC computing and the resources are scheduled to be continuously used throughout the year. In the last several years there has been an explosion in capacity and capability of commercial and academic computing clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is amore » growing interest amongst the cloud providers to demonstrate the capability to perform large scale scientific computing. In this presentation we will discuss results from the CMS experiment using the Fermilab HEPCloud Facility, which utilized both local Fermilab resources and Amazon Web Services (AWS). The goal was to work with AWS through a matching grant to demonstrate a sustained scale approximately equal to half of the worldwide processing resources available to CMS. We will discuss the planning and technical challenges involved in organizing the most IO intensive CMS workflows on a large-scale set of virtualized resource provisioned by the Fermilab HEPCloud. We will describe the data handling and data management challenges. Also, we will discuss the economic issues and cost and operational efficiency comparison to our dedicated resources. At the end we will consider the changes in the working model of HEP computing in a domain with the availability of large scale resources scheduled at peak times.« less

Cl-Assisted Large Scale Synthesis of Cm-Scale Buckypapers of Fe₃C-Filled Carbon Nanotubes with Pseudo-Capacitor Properties: The Key Role of SBA-16 Catalyst Support as Synthesis Promoter.

PubMed

Boi, Filippo S; He, Yi; Wen, Jiqiu; Wang, Shanling; Yan, Kai; Zhang, Jingdong; Medranda, Daniel; Borowiec, Joanna; Corrias, Anna

2017-10-23

We show a novel chemical vapour deposition (CVD) approach, in which the large-scale fabrication of ferromagnetically-filled cm-scale buckypapers is achieved through the deposition of a mesoporous supported catalyst (SBA-16) on a silicon substrate. We demonstrate that SBA-16 has the crucial role of promoting the growth of carbon nanotubes (CNTs) on a horizontal plane with random orientation rather than in a vertical direction, therefore allowing a facile fabrication of cm-scale CNTs buckypapers free from the onion-crust by-product observed on the buckypaper-surface in previous reports. The morphology and composition of the obtained CNTs-buckypapers are analyzed in detail by scanning electron microscopy (SEM), Energy Dispersive X-ray (EDX), transmission electron microscopy (TEM), high resolution TEM (HRTEM), and thermogravimetric analysis (TGA), while structural analysis is performed by Rietveld Refinement of XRD data. The room temperature magnetic properties of the produced buckypapers are also investigated and reveal the presence of a high coercivity of 650 Oe. Additionally, the electrochemical performances of these buckypapers are demonstrated and reveal a behavior that is compatible with that of a pseudo-capacitor (resistive-capacitor) with better performances than those presented in other previously studied layered-buckypapers of Fe-filled CNTs, obtained by pyrolysis of dichlorobenzene-ferrocene mixtures. These measurements indicate that these materials show promise for applications in energy storage systems as flexible electrodes.

Constraints on the Origin of Cosmic Rays above 1018 eV from Large-scale Anisotropy Searches in Data of the Pierre Auger Observatory

NASA Astrophysics Data System (ADS)

Pierre Auger Collaboration; Abreu, P.; Aglietta, M.; Ahlers, M.; Ahn, E. J.; Albuquerque, I. F. M.; Allard, D.; Allekotte, I.; Allen, J.; Allison, P.; Almela, A.; Alvarez Castillo, J.; Alvarez-Muñiz, J.; Alves Batista, R.; Ambrosio, M.; Aminaei, A.; Anchordoqui, L.; Andringa, S.; Antiči'c, T.; Aramo, C.; Arganda, E.; Arqueros, F.; Asorey, H.; Assis, P.; Aublin, J.; Ave, M.; Avenier, M.; Avila, G.; Badescu, A. M.; Balzer, M.; Barber, K. B.; Barbosa, A. F.; Bardenet, R.; Barroso, S. L. C.; Baughman, B.; Bäuml, J.; Baus, C.; Beatty, J. J.; Becker, K. H.; Bellétoile, A.; Bellido, J. A.; BenZvi, S.; Berat, C.; Bertou, X.; Biermann, P. L.; Billoir, P.; Blanco, F.; Blanco, M.; Bleve, C.; Blümer, H.; Boháčová, M.; Boncioli, D.; Bonifazi, C.; Bonino, R.; Borodai, N.; Brack, J.; Brancus, I.; Brogueira, P.; Brown, W. C.; Bruijn, R.; Buchholz, P.; Bueno, A.; Buroker, L.; Burton, R. E.; Caballero-Mora, K. S.; Caccianiga, B.; Caramete, L.; Caruso, R.; Castellina, A.; Catalano, O.; Cataldi, G.; Cazon, L.; Cester, R.; Chauvin, J.; Cheng, S. H.; Chiavassa, A.; Chinellato, J. A.; Chirinos Diaz, J.; Chudoba, J.; Cilmo, M.; Clay, R. W.; Cocciolo, G.; Collica, L.; Coluccia, M. R.; Conceição, R.; Contreras, F.; Cook, H.; Cooper, M. J.; Coppens, J.; Cordier, A.; Coutu, S.; Covault, C. E.; Creusot, A.; Criss, A.; Cronin, J.; Curutiu, A.; Dagoret-Campagne, S.; Dallier, R.; Daniel, B.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; De Domenico, M.; De Donato, C.; de Jong, S. J.; De La Vega, G.; de Mello Junior, W. J. M.; de Mello Neto, J. R. T.; De Mitri, I.; de Souza, V.; de Vries, K. D.; del Peral, L.; del Río, M.; Deligny, O.; Dembinski, H.; Dhital, N.; Di Giulio, C.; Díaz Castro, M. L.; Diep, P. N.; Diogo, F.; Dobrigkeit, C.; Docters, W.; D'Olivo, J. C.; Dong, P. N.; Dorofeev, A.; dos Anjos, J. C.; Dova, M. T.; D'Urso, D.; Dutan, I.; Ebr, J.; Engel, R.; Erdmann, M.; Escobar, C. O.; Espadanal, J.; Etchegoyen, A.; Facal San Luis, P.; Falcke, H.; Fang, K.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Ferguson, A. P.; Fick, B.; Figueira, J. M.; Filevich, A.; Filipčič, A.; Fliescher, S.; Fracchiolla, C. E.; Fraenkel, E. D.; Fratu, O.; Fröhlich, U.; Fuchs, B.; Gaior, R.; Gamarra, R. F.; Gambetta, S.; García, B.; Garcia Roca, S. T.; Garcia-Gamez, D.; Garcia-Pinto, D.; Garilli, G.; Gascon Bravo, A.; Gemmeke, H.; Ghia, P. L.; Giller, M.; Gitto, J.; Glass, H.; Gold, M. S.; Golup, G.; Gomez Albarracin, F.; Gómez Berisso, M.; Gómez Vitale, P. F.; Gonçalves, P.; Gonzalez, J. G.; Gookin, B.; Gorgi, A.; Gouffon, P.; Grashorn, E.; Grebe, S.; Griffith, N.; Grillo, A. F.; Guardincerri, Y.; Guarino, F.; Guedes, G. P.; Hansen, P.; Harari, D.; Harrison, T. A.; Harton, J. L.; Haungs, A.; Hebbeker, T.; Heck, D.; Herve, A. E.; Hill, G. C.; Hojvat, C.; Hollon, N.; Holmes, V. C.; Homola, P.; Hörandel, J. R.; Horvath, P.; Hrabovský, M.; Huber, D.; Huege, T.; Insolia, A.; Ionita, F.; Italiano, A.; Jansen, S.; Jarne, C.; Jiraskova, S.; Josebachuili, M.; Kadija, K.; Kampert, K. H.; Karhan, P.; Kasper, P.; Katkov, I.; Kégl, B.; Keilhauer, B.; Keivani, A.; Kelley, J. L.; Kemp, E.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Knapp, J.; Koang, D.-H.; Kotera, K.; Krohm, N.; Krömer, O.; Kruppke-Hansen, D.; Kuempel, D.; Kulbartz, J. K.; Kunka, N.; La Rosa, G.; Lachaud, C.; LaHurd, D.; Latronico, L.; Lauer, R.; Lautridou, P.; Le Coz, S.; Leão, M. S. A. B.; Lebrun, D.; Lebrun, P.; Leigui de Oliveira, M. A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; López, R.; Lopez Agüera, A.; Louedec, K.; Lozano Bahilo, J.; Lu, L.; Lucero, A.; Ludwig, M.; Lyberis, H.; Maccarone, M. C.; Macolino, C.; Maldera, S.; Maller, J.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Marin, J.; Marin, V.; Maris, I. C.; Marquez Falcon, H. R.; Marsella, G.; Martello, D.; Martin, L.; Martinez, H.; Martínez Bravo, O.; Martraire, D.; Masías Meza, J. J.; Mathes, H. J.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Maurel, D.; Maurizio, D.; Mazur, P. O.; Medina-Tanco, G.; Melissas, M.; Melo, D.; Menichetti, E.; Menshikov, A.; Mertsch, P.; Messina, S.; Meurer, C.; Meyhandan, R.; Mi'canovi'c, S.; Micheletti, M. I.; Minaya, I. A.; Miramonti, L.; Molina-Bueno, L.; Mollerach, S.; Monasor, M.; Monnier Ragaigne, D.; Montanet, F.; Morales, B.; Morello, C.; Moreno, E.; Moreno, J. C.; Mostafá, M.; Moura, C. A.; Muller, M. A.; Müller, G.; Münchmeyer, M.; Mussa, R.; Navarra, G.; Navarro, J. L.; Navas, S.; Necesal, P.; Nellen, L.; Nelles, A.; Neuser, J.; Nhung, P. T.; Niechciol, M.; Niemietz, L.; Nierstenhoefer, N.; Nitz, D.; Nosek, D.; Nožka, L.; Oehlschläger, J.; Olinto, A.; Ortiz, M.; Pacheco, N.; Pakk Selmi-Dei, D.; Palatka, M.; Pallotta, J.; Palmieri, N.; Parente, G.; Parizot, E.; Parra, A.; Pastor, S.; Paul, T.; Pech, M.; Peķala, J.; Pelayo, R.; Pepe, I. M.; Perrone, L.; Pesce, R.; Petermann, E.; Petrera, S.; Petrolini, A.; Petrov, Y.; Pfendner, C.; Piegaia, R.; Pierog, T.; Pieroni, P.; Pimenta, M.; Pirronello, V.; Platino, M.; Plum, M.; Ponce, V. H.; Pontz, M.; Porcelli, A.; Privitera, P.; Prouza, M.; Quel, E. J.; Querchfeld, S.; Rautenberg, J.; Ravel, O.; Ravignani, D.; Revenu, B.; Ridky, J.; Riggi, S.; Risse, M.; Ristori, P.; Rivera, H.; Rizi, V.; Roberts, J.; Rodrigues de Carvalho, W.; Rodriguez, G.; Rodriguez Cabo, I.; Rodriguez Martino, J.; Rodriguez Rojo, J.; Rodríguez-Frías, M. D.; Ros, G.; Rosado, J.; Rossler, T.; Roth, M.; Rouillé-d'Orfeuil, B.; Roulet, E.; Rovero, A. C.; Rühle, C.; Saftoiu, A.; Salamida, F.; Salazar, H.; Salesa Greus, F.; Salina, G.; Sánchez, F.; Santo, C. E.; Santos, E.; Santos, E. M.; Sarazin, F.; Sarkar, B.; Sarkar, S.; Sato, R.; Scharf, N.; Scherini, V.; Schieler, H.; Schiffer, P.; Schmidt, A.; Scholten, O.; Schoorlemmer, H.; Schovancova, J.; Schovánek, P.; Schröder, F.; Schuster, D.; Sciutto, S. J.; Scuderi, M.; Segreto, A.; Settimo, M.; Shadkam, A.; Shellard, R. C.; Sidelnik, I.; Sigl, G.; Silva Lopez, H. H.; Sima, O.; 'Smiałkowski, A.; Šmída, R.; Snow, G. R.; Sommers, P.; Sorokin, J.; Spinka, H.; Squartini, R.; Srivastava, Y. N.; Stanic, S.; Stapleton, J.; Stasielak, J.; Stephan, M.; Stutz, A.; Suarez, F.; Suomijärvi, T.; Supanitsky, A. D.; Šuša, T.; Sutherland, M. S.; Swain, J.; Szadkowski, Z.; Szuba, M.; Tapia, A.; Tartare, M.; Taşcău, O.; Tcaciuc, R.; Thao, N. T.; Thomas, D.; Tiffenberg, J.; Timmermans, C.; Tkaczyk, W.; Todero Peixoto, C. J.; Toma, G.; Tomankova, L.; Tomé, B.; Tonachini, A.; Torralba Elipe, G.; Travnicek, P.; Tridapalli, D. B.; Tristram, G.; Trovato, E.; Tueros, M.; Ulrich, R.; Unger, M.; Urban, M.; Valdés Galicia, J. F.; Valiño, I.; Valore, L.; van Aar, G.; van den Berg, A. M.; van Velzen, S.; van Vliet, A.; Varela, E.; Vargas Cárdenas, B.; Vázquez, J. R.; Vázquez, R. A.; Veberič, D.; Verzi, V.; Vicha, J.; Videla, M.; Villaseñor, L.; Wahlberg, H.; Wahrlich, P.; Wainberg, O.; Walz, D.; Watson, A. A.; Weber, M.; Weidenhaupt, K.; Weindl, A.; Werner, F.; Westerhoff, S.; Whelan, B. J.; Widom, A.; Wieczorek, G.; Wiencke, L.; Wilczyńska, B.; Wilczyński, H.; Will, M.; Williams, C.; Winchen, T.; Wommer, M.; Wundheiler, B.; Yamamoto, T.; Yapici, T.; Younk, P.; Yuan, G.; Yushkov, A.; Zamorano Garcia, B.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zaw, I.; Zepeda, A.; Zhou, J.; Zhu, Y.; Zimbres Silva, M.; Ziolkowski, M.

2013-01-01

A thorough search for large-scale anisotropies in the distribution of arrival directions of cosmic rays detected above 1018 eV at the Pierre Auger Observatory is reported. For the first time, these large-scale anisotropy searches are performed as a function of both the right ascension and the declination and expressed in terms of dipole and quadrupole moments. Within the systematic uncertainties, no significant deviation from isotropy is revealed. Upper limits on dipole and quadrupole amplitudes are derived under the hypothesis that any cosmic ray anisotropy is dominated by such moments in this energy range. These upper limits provide constraints on the production of cosmic rays above 1018 eV, since they allow us to challenge an origin from stationary galactic sources densely distributed in the galactic disk and emitting predominantly light particles in all directions.

Vibration-based structural health monitoring of the aircraft large component

NASA Astrophysics Data System (ADS)

Pavelko, V.; Kuznetsov, S.; Nevsky, A.; Marinbah, M.

2017-10-01

In the presented paper there are investigated the basic problems of the local system of SHM of large scale aircraft component. Vibration-based damage detection is accepted as a basic condition, and main attention focused to a low-cost solution that would be attractive for practice. The conditions of small damage detection in the full scale structural component at low-frequency excitation were defined in analytical study and modal FEA. In experimental study the dynamic test of the helicopter Mi-8 tail beam was performed at harmonic excitation with frequency close to first natural frequency of the beam. The index of correlation coefficient deviation (CCD) was used for extraction of the features due to embedded pseudo-damage. It is shown that the problem of vibration-based detection of a small damage in the large scale structure at low-frequency excitation can be solved successfully.

A study of rotor and platform design trade-offs for large-scale floating vertical axis wind turbines

NASA Astrophysics Data System (ADS)

Griffith, D. Todd; Paquette, Joshua; Barone, Matthew; Goupee, Andrew J.; Fowler, Matthew J.; Bull, Diana; Owens, Brian

2016-09-01

Vertical axis wind turbines are receiving significant attention for offshore siting. In general, offshore wind offers proximity to large populations centers, a vast & more consistent wind resource, and a scale-up opportunity, to name a few beneficial characteristics. On the other hand, offshore wind suffers from high levelized cost of energy (LCOE) and in particular high balance of system (BoS) costs owing to accessibility challenges and limited project experience. To address these challenges associated with offshore wind, Sandia National Laboratories is researching large-scale (MW class) offshore floating vertical axis wind turbines (VAWTs). The motivation for this work is that floating VAWTs are a potential transformative technology solution to reduce offshore wind LCOE in deep-water locations. This paper explores performance and cost trade-offs within the design space for floating VAWTs between the configurations for the rotor and platform.

A review of sensing technologies for small and large-scale touch panels

NASA Astrophysics Data System (ADS)

Akhtar, Humza; Kemao, Qian; Kakarala, Ramakrishna

2017-06-01

A touch panel is an input device for human computer interaction. It consists of a network of sensors, a sampling circuit and a micro controller for detecting and locating a touch input. Touch input can come from either finger or stylus depending upon the type of touch technology. These touch panels provide an intuitive and collaborative workspace so that people can perform various tasks with the use of their fingers instead of traditional input devices like keyboard and mouse. Touch sensing technology is not new. At the time of this writing, various technologies are available in the market and this paper reviews the most common ones. We review traditional designs and sensing algorithms for touch technology. We also observe that due to its various strengths, capacitive touch will dominate the large-scale touch panel industry in years to come. In the end, we discuss the motivation for doing academic research on large-scale panels.

Sub-Selective Quantization for Learning Binary Codes in Large-Scale Image Search.

PubMed

Li, Yeqing; Liu, Wei; Huang, Junzhou

2018-06-01

Recently with the explosive growth of visual content on the Internet, large-scale image search has attracted intensive attention. It has been shown that mapping high-dimensional image descriptors to compact binary codes can lead to considerable efficiency gains in both storage and performing similarity computation of images. However, most existing methods still suffer from expensive training devoted to large-scale binary code learning. To address this issue, we propose a sub-selection based matrix manipulation algorithm, which can significantly reduce the computational cost of code learning. As case studies, we apply the sub-selection algorithm to several popular quantization techniques including cases using linear and nonlinear mappings. Crucially, we can justify the resulting sub-selective quantization by proving its theoretic properties. Extensive experiments are carried out on three image benchmarks with up to one million samples, corroborating the efficacy of the sub-selective quantization method in terms of image retrieval.

The island coalescence problem: Scaling of reconnection in extended fluid models including higher-order moments

DOE PAGES

Ng, Jonathan; Huang, Yi -Min; Hakim, Ammar; ...

2015-11-05

As modeling of collisionless magnetic reconnection in most space plasmas with realistic parameters is beyond the capability of today's simulations, due to the separation between global and kinetic length scales, it is important to establish scaling relations in model problems so as to extrapolate to realistic scales. Furthermore, large scale particle-in-cell simulations of island coalescence have shown that the time averaged reconnection rate decreases with system size, while fluid systems at such large scales in the Hall regime have not been studied. Here, we perform the complementary resistive magnetohydrodynamic (MHD), Hall MHD, and two fluid simulations using a ten-moment modelmore » with the same geometry. In contrast to the standard Harris sheet reconnection problem, Hall MHD is insufficient to capture the physics of the reconnection region. Additionally, motivated by the results of a recent set of hybrid simulations which show the importance of ion kinetics in this geometry, we evaluate the efficacy of the ten-moment model in reproducing such results.« less

Foster Wheeler's Solutions for Large Scale CFB Boiler Technology: Features and Operational Performance of Łagisza 460 MWe CFB Boiler

NASA Astrophysics Data System (ADS)

Hotta, Arto

During recent years, once-through supercritical (OTSC) CFB technology has been developed, enabling the CFB technology to proceed to medium-scale (500 MWe) utility projects such as Łagisza Power Plant in Poland owned by Poludniowy Koncern Energetyczny SA. (PKE), with net efficiency nearly 44%. Łagisza power plant is currently under commissioning and has reached full load operation in March 2009. The initial operation shows very good performance and confirms, that the CFB process has no problems with the scaling up to this size. Also the once-through steam cycle utilizing Siemens' vertical tube Benson technology has performed as predicted in the CFB process. Foster Wheeler has developed the CFB design further up to 800 MWe with net efficiency of ≥45%.

A Glance at Microsatellite Motifs from 454 Sequencing Reads of Watermelon Genomic DNA

USDA-ARS?s Scientific Manuscript database

A single 454 (Life Sciences Sequencing Technology) run of Charleston Gray watermelon (Citrullus lanatus var. lanatus) genomic DNA was performed and sequence data were assembled. A large scale identification of simple sequence repeat (SSR) was performed and SSR sequence data were used for the develo...

Enhancements for a Dynamic Data Warehousing and Mining System for Large-scale HSCB Data

DTIC Science & Technology

2016-05-27

Page | 1 . . . . . . . . . . . . . . . . . . . Intelligent Automation Incorporated Enhancements for a Dynamic Data...301.294.4241, osavas@i-a-i.com) 1 Work Performed within This Reporting Period .................................................... 2 1.1 Top K User and...5 3 Work to be Performed in the Next Reporting Period

Performance Comparison of the Digital Neuromorphic Hardware SpiNNaker and the Neural Network Simulation Software NEST for a Full-Scale Cortical Microcircuit Model

PubMed Central

van Albada, Sacha J.; Rowley, Andrew G.; Senk, Johanna; Hopkins, Michael; Schmidt, Maximilian; Stokes, Alan B.; Lester, David R.; Diesmann, Markus; Furber, Steve B.

2018-01-01

The digital neuromorphic hardware SpiNNaker has been developed with the aim of enabling large-scale neural network simulations in real time and with low power consumption. Real-time performance is achieved with 1 ms integration time steps, and thus applies to neural networks for which faster time scales of the dynamics can be neglected. By slowing down the simulation, shorter integration time steps and hence faster time scales, which are often biologically relevant, can be incorporated. We here describe the first full-scale simulations of a cortical microcircuit with biological time scales on SpiNNaker. Since about half the synapses onto the neurons arise within the microcircuit, larger cortical circuits have only moderately more synapses per neuron. Therefore, the full-scale microcircuit paves the way for simulating cortical circuits of arbitrary size. With approximately 80, 000 neurons and 0.3 billion synapses, this model is the largest simulated on SpiNNaker to date. The scale-up is enabled by recent developments in the SpiNNaker software stack that allow simulations to be spread across multiple boards. Comparison with simulations using the NEST software on a high-performance cluster shows that both simulators can reach a similar accuracy, despite the fixed-point arithmetic of SpiNNaker, demonstrating the usability of SpiNNaker for computational neuroscience applications with biological time scales and large network size. The runtime and power consumption are also assessed for both simulators on the example of the cortical microcircuit model. To obtain an accuracy similar to that of NEST with 0.1 ms time steps, SpiNNaker requires a slowdown factor of around 20 compared to real time. The runtime for NEST saturates around 3 times real time using hybrid parallelization with MPI and multi-threading. However, achieving this runtime comes at the cost of increased power and energy consumption. The lowest total energy consumption for NEST is reached at around 144 parallel threads and 4.6 times slowdown. At this setting, NEST and SpiNNaker have a comparable energy consumption per synaptic event. Our results widen the application domain of SpiNNaker and help guide its development, showing that further optimizations such as synapse-centric network representation are necessary to enable real-time simulation of large biological neural networks. PMID:29875620

Low-Cost and Large-Area Electronics, Roll-to-Roll Processing and Beyond

NASA Astrophysics Data System (ADS)

Wiesenhütter, Katarzyna; Skorupa, Wolfgang

In the following chapter, the authors conduct a literature survey of current advances in state-of-the-art low-cost, flexible electronics. A new emerging trend in the design of modern semiconductor devices dedicated to scaling-up, rather than reducing, their dimensions is presented. To realize volume manufacturing, alternative semiconductor materials with superior performance, fabricated by innovative processing methods, are essential. This review provides readers with a general overview of the material and technology evolution in the area of macroelectronics. Herein, the term macroelectronics (MEs) refers to electronic systems that can cover a large area of flexible media. In stark contrast to well-established micro- and nano-scale semiconductor devices, where property improvement is associated with downscaling the dimensions of the functional elements, in macroelectronic systems their overall size defines the ultimate performance (Sun and Rogers in Adv. Mater. 19:1897-1916, 2007). The major challenges of large-scale production are discussed. Particular attention has been focused on describing advanced, short-term heat treatment approaches, which offer a range of advantages compared to conventional annealing methods. There is no doubt that large-area, flexible electronic systems constitute an important research topic for the semiconductor industry. The ability to fabricate highly efficient macroelectronics by inexpensive processes will have a significant impact on a range of diverse technology sectors. A new era "towards semiconductor volume manufacturing…" has begun.

Simulating Daily and Sub-daily Water Flow in Large, Semi-arid Watershed Using SWAT: A Case Study of Nueces River Basin, Texas

NASA Astrophysics Data System (ADS)

Bassam, S.; Ren, J.

2015-12-01

Runoff generated during heavy rainfall imposes quick, but often intense, changes in the flow of streams, which increase the chance of flash floods in the vicinity of the streams. Understanding the temporal response of streams to heavy rainfall requires a hydrological model that considers meteorological, hydrological, and geological components of the streams and their watersheds. SWAT is a physically-based, semi-distributed model that is capable of simulating water flow within watersheds with both long-term, i.e. annually and monthly, and short-term (daily and sub-daily) time scales. However, the capability of SWAT in sub-daily water flow modeling within large watersheds has not been studied much, compare to long-term and daily time scales. In this study we are investigating the water flow in a large, semi-arid watershed, Nueces River Basin (NRB) with the drainage area of 16950 mi2 located in South Texas, with daily and sub-daily time scales. The objectives of this study are: (1) simulating the response of streams to heavy, and often quick, rainfall, (2) evaluating SWAT performance in sub-daily modeling of water flow within a large watershed, and (3) examining means for model performance improvement during model calibration and verification based on results of sensitivity and uncertainty analysis. The results of this study can provide important information for water resources planning during flood seasons.

Physical activity correlates with neurological impairment and disability in multiple sclerosis.

PubMed

Motl, Robert W; Snook, Erin M; Wynn, Daniel R; Vollmer, Timothy

2008-06-01

This study examined the correlation of physical activity with neurological impairment and disability in persons with multiple sclerosis (MS). Eighty individuals with MS wore an accelerometer for 7 days and completed the Symptom Inventory (SI), Performance Scales (PS), and Expanded Disability Status Scale. There were large negative correlations between the accelerometer and SI (r = -0.56; rho = -0.58) and Expanded Disability Status Scale (r = -0.60; rho = -0.69) and a moderate negative correlation between the accelerometer and PS (r = -0.39; rho = -0.48) indicating that physical activity was associated with reduced neurological impairment and disability. Such findings provide a preliminary basis for using an accelerometer and the SI and PS as outcome measures in large-scale prospective and experimental examinations of the effect of physical activity behavior on disability and dependence in MS.

Job Management and Task Bundling

NASA Astrophysics Data System (ADS)

Berkowitz, Evan; Jansen, Gustav R.; McElvain, Kenneth; Walker-Loud, André

2018-03-01

High Performance Computing is often performed on scarce and shared computing resources. To ensure computers are used to their full capacity, administrators often incentivize large workloads that are not possible on smaller systems. Measurements in Lattice QCD frequently do not scale to machine-size workloads. By bundling tasks together we can create large jobs suitable for gigantic partitions. We discuss METAQ and mpi_jm, software developed to dynamically group computational tasks together, that can intelligently backfill to consume idle time without substantial changes to users' current workflows or executables.

Determining the Influence of Groundwater Composition on the Performance of Arsenic Adsorption Columns Using Rapid Small-Scale Column Tests

NASA Astrophysics Data System (ADS)

Aragon, A. R.; Siegel, M.

2004-12-01

The USEPA has established a more stringent drinking water standard for arsenic, reducing the maximum contaminant level (MCL) from 50 μ g/L to 10 μ g/L. This will affect many small communities in the US that lack the appropriate treatment infrastructure and funding to reduce arsenic to such levels. For such communities, adsorption systems are the preferred technology based on ease of operation and relatively lower costs. The performance of adsorption media for the removal of arsenic from drinking water is dependent on site-specific water quality. At certain concentrations, co-occurring solutes will compete effectively with arsenic for sorption sites, potentially reducing the sorption capacity of the media. Due to the site-specific nature of water quality and variations in media properties, pilot scale studies are typically carried out to ensure that a proposed treatment technique is cost effective before installation of a full-scale system. Sandia National Laboratories is currently developing an approach to utilize rapid small-scale columns in lieu of pilot columns to test innovative technologies that could significantly reduce the cost of treatment in small communities. Rapid small-scale column tests (RSSCTs) were developed to predict full-scale treatment of organic contaminants by adsorption onto granular activated carbon (GAC). This process greatly reduced the time and costs required to verify performance of GAC adsorption columns. In this study, the RSSCT methodology is used to predict the removal of inorganic arsenic using mixed metal oxyhydroxide adsorption media. The media are engineered and synthesized from materials that control arsenic behavior in natural and disturbed systems. We describe the underlying theory and application of RSSCTs for the performance evaluation of novel media in several groundwater compositions. Results of small-scale laboratory columns are being used to predict the performance of pilot-scale systems and ultimately to design full-scale systems. RSSCTs will be performed on a suite of water compositions representing the variety of water supplies in the United States that are affected by the new drinking water standard. Ultimately, this approach will be used to carry out inexpensive short-term pilot studies at a large number of sites where large-scale pilots are not economically feasible. Sandia National Laboratories is a multi-program laboratory operated by Sandia Corporation, a Lockheed Martin company, for the United States Department of Energy's National Nuclear Security Administration under Contract DE-AC04-94AL85000.

Meta-analysis of prediction model performance across multiple studies: Which scale helps ensure between-study normality for the C-statistic and calibration measures?

PubMed

Snell, Kym Ie; Ensor, Joie; Debray, Thomas Pa; Moons, Karel Gm; Riley, Richard D

2017-01-01

If individual participant data are available from multiple studies or clusters, then a prediction model can be externally validated multiple times. This allows the model's discrimination and calibration performance to be examined across different settings. Random-effects meta-analysis can then be used to quantify overall (average) performance and heterogeneity in performance. This typically assumes a normal distribution of 'true' performance across studies. We conducted a simulation study to examine this normality assumption for various performance measures relating to a logistic regression prediction model. We simulated data across multiple studies with varying degrees of variability in baseline risk or predictor effects and then evaluated the shape of the between-study distribution in the C-statistic, calibration slope, calibration-in-the-large, and E/O statistic, and possible transformations thereof. We found that a normal between-study distribution was usually reasonable for the calibration slope and calibration-in-the-large; however, the distributions of the C-statistic and E/O were often skewed across studies, particularly in settings with large variability in the predictor effects. Normality was vastly improved when using the logit transformation for the C-statistic and the log transformation for E/O, and therefore we recommend these scales to be used for meta-analysis. An illustrated example is given using a random-effects meta-analysis of the performance of QRISK2 across 25 general practices.

Patterns of resting state connectivity in human primary visual cortical areas: a 7T fMRI study.

PubMed

Raemaekers, Mathijs; Schellekens, Wouter; van Wezel, Richard J A; Petridou, Natalia; Kristo, Gert; Ramsey, Nick F

2014-01-01

The nature and origin of fMRI resting state fluctuations and connectivity are still not fully known. More detailed knowledge on the relationship between resting state patterns and brain function may help to elucidate this matter. We therefore performed an in depth study of how resting state fluctuations map to the well known architecture of the visual system. We investigated resting state connectivity at both a fine and large scale within and across visual areas V1, V2 and V3 in ten human subjects using a 7Tesla scanner. We found evidence for several coexisting and overlapping connectivity structures at different spatial scales. At the fine-scale level we found enhanced connectivity between the same topographic locations in the fieldmaps of V1, V2 and V3, enhanced connectivity to the contralateral functional homologue, and to a lesser extent enhanced connectivity between iso-eccentric locations within the same visual area. However, by far the largest proportion of the resting state fluctuations occurred within large-scale bilateral networks. These large-scale networks mapped to some extent onto the architecture of the visual system and could thereby obscure fine-scale connectivity. In fact, most of the fine-scale connectivity only became apparent after the large-scale network fluctuations were filtered from the timeseries. We conclude that fMRI resting state fluctuations in the visual cortex may in fact be a composite signal of different overlapping sources. Isolating the different sources could enhance correlations between BOLD and electrophysiological correlates of resting state activity. © 2013 Elsevier Inc. All rights reserved.

Spectral enstrophy budget in a shear-less flow with turbulent/non-turbulent interface

NASA Astrophysics Data System (ADS)

Cimarelli, Andrea; Cocconi, Giacomo; Frohnapfel, Bettina; De Angelis, Elisabetta

2015-12-01

A numerical analysis of the interaction between decaying shear free turbulence and quiescent fluid is performed by means of global statistical budgets of enstrophy, both, at the single-point and two point levels. The single-point enstrophy budget allows us to recognize three physically relevant layers: a bulk turbulent region, an inhomogeneous turbulent layer, and an interfacial layer. Within these layers, enstrophy is produced, transferred, and finally destroyed while leading to a propagation of the turbulent front. These processes do not only depend on the position in the flow field but are also strongly scale dependent. In order to tackle this multi-dimensional behaviour of enstrophy in the space of scales and in physical space, we analyse the spectral enstrophy budget equation. The picture consists of an inviscid spatial cascade of enstrophy from large to small scales parallel to the interface moving towards the interface. At the interface, this phenomenon breaks, leaving place to an anisotropic cascade where large scale structures exhibit only a cascade process normal to the interface thus reducing their thickness while retaining their lengths parallel to the interface. The observed behaviour could be relevant for both the theoretical and the modelling approaches to flow with interacting turbulent/nonturbulent regions. The scale properties of the turbulent propagation mechanisms highlight that the inviscid turbulent transport is a large-scale phenomenon. On the contrary, the viscous diffusion, commonly associated with small scale mechanisms, highlights a much richer physics involving small lengths, normal to the interface, but at the same time large scales, parallel to the interface.

Evaluation of interpolation techniques for the creation of gridded daily precipitation (1 × 1 km2); Cyprus, 1980-2010

NASA Astrophysics Data System (ADS)

Camera, Corrado; Bruggeman, Adriana; Hadjinicolaou, Panos; Pashiardis, Stelios; Lange, Manfred A.

2014-01-01

High-resolution gridded daily data sets are essential for natural resource management and the analyses of climate changes and their effects. This study aims to evaluate the performance of 15 simple or complex interpolation techniques in reproducing daily precipitation at a resolution of 1 km2 over topographically complex areas. Methods are tested considering two different sets of observation densities and different rainfall amounts. We used rainfall data that were recorded at 74 and 145 observational stations, respectively, spread over the 5760 km2 of the Republic of Cyprus, in the Eastern Mediterranean. Regression analyses utilizing geographical copredictors and neighboring interpolation techniques were evaluated both in isolation and combined. Linear multiple regression (LMR) and geographically weighted regression methods (GWR) were tested. These included a step-wise selection of covariables, as well as inverse distance weighting (IDW), kriging, and 3D-thin plate splines (TPS). The relative rank of the different techniques changes with different station density and rainfall amounts. Our results indicate that TPS performs well for low station density and large-scale events and also when coupled with regression models. It performs poorly for high station density. The opposite is observed when using IDW. Simple IDW performs best for local events, while a combination of step-wise GWR and IDW proves to be the best method for large-scale events and high station density. This study indicates that the use of step-wise regression with a variable set of geographic parameters can improve the interpolation of large-scale events because it facilitates the representation of local climate dynamics.

Evaluation of Large-scale Data to Detect Irregularity in Payment for Medical Services. An Extended Use of Benford's Law.

PubMed

Park, Junghyun A; Kim, Minki; Yoon, Seokjoon

2016-05-17

Sophisticated anti-fraud systems for the healthcare sector have been built based on several statistical methods. Although existing methods have been developed to detect fraud in the healthcare sector, these algorithms consume considerable time and cost, and lack a theoretical basis to handle large-scale data. Based on mathematical theory, this study proposes a new approach to using Benford's Law in that we closely examined the individual-level data to identify specific fees for in-depth analysis. We extended the mathematical theory to demonstrate the manner in which large-scale data conform to Benford's Law. Then, we empirically tested its applicability using actual large-scale healthcare data from Korea's Health Insurance Review and Assessment (HIRA) National Patient Sample (NPS). For Benford's Law, we considered the mean absolute deviation (MAD) formula to test the large-scale data. We conducted our study on 32 diseases, comprising 25 representative diseases and 7 DRG-regulated diseases. We performed an empirical test on 25 diseases, showing the applicability of Benford's Law to large-scale data in the healthcare industry. For the seven DRG-regulated diseases, we examined the individual-level data to identify specific fees to carry out an in-depth analysis. Among the eight categories of medical costs, we considered the strength of certain irregularities based on the details of each DRG-regulated disease. Using the degree of abnormality, we propose priority action to be taken by government health departments and private insurance institutions to bring unnecessary medical expenses under control. However, when we detect deviations from Benford's Law, relatively high contamination ratios are required at conventional significance levels.

Solution of matrix equations using sparse techniques

NASA Technical Reports Server (NTRS)

Baddourah, Majdi

1994-01-01

The solution of large systems of matrix equations is key to the solution of a large number of scientific and engineering problems. This talk describes the sparse matrix solver developed at Langley which can routinely solve in excess of 263,000 equations in 40 seconds on one Cray C-90 processor. It appears that for large scale structural analysis applications, sparse matrix methods have a significant performance advantage over other methods.

Large eddy simulations of compressible magnetohydrodynamic turbulence

NASA Astrophysics Data System (ADS)

Grete, Philipp

2017-02-01

Supersonic, magnetohydrodynamic (MHD) turbulence is thought to play an important role in many processes - especially in astrophysics, where detailed three-dimensional observations are scarce. Simulations can partially fill this gap and help to understand these processes. However, direct simulations with realistic parameters are often not feasible. Consequently, large eddy simulations (LES) have emerged as a viable alternative. In LES the overall complexity is reduced by simulating only large and intermediate scales directly. The smallest scales, usually referred to as subgrid-scales (SGS), are introduced to the simulation by means of an SGS model. Thus, the overall quality of an LES with respect to properly accounting for small-scale physics crucially depends on the quality of the SGS model. While there has been a lot of successful research on SGS models in the hydrodynamic regime for decades, SGS modeling in MHD is a rather recent topic, in particular, in the compressible regime. In this thesis, we derive and validate a new nonlinear MHD SGS model that explicitly takes compressibility effects into account. A filter is used to separate the large and intermediate scales, and it is thought to mimic finite resolution effects. In the derivation, we use a deconvolution approach on the filter kernel. With this approach, we are able to derive nonlinear closures for all SGS terms in MHD: the turbulent Reynolds and Maxwell stresses, and the turbulent electromotive force (EMF). We validate the new closures both a priori and a posteriori. In the a priori tests, we use high-resolution reference data of stationary, homogeneous, isotropic MHD turbulence to compare exact SGS quantities against predictions by the closures. The comparison includes, for example, correlations of turbulent fluxes, the average dissipative behavior, and alignment of SGS vectors such as the EMF. In order to quantify the performance of the new nonlinear closure, this comparison is conducted from the subsonic (sonic Mach number M s ≈ 0.2) to the highly supersonic (M s ≈ 20) regime, and against other SGS closures. The latter include established closures of eddy-viscosity and scale-similarity type. In all tests and over the entire parameter space, we find that the proposed closures are (significantly) closer to the reference data than the other closures. In the a posteriori tests, we perform large eddy simulations of decaying, supersonic MHD turbulence with initial M s ≈ 3. We implemented closures of all types, i.e. of eddy-viscosity, scale-similarity and nonlinear type, as an SGS model and evaluated their performance in comparison to simulations without a model (and at higher resolution). We find that the models need to be calculated on a scale larger than the grid scale, e.g. by an explicit filter, to have an influence on the dynamics at all. Furthermore, we show that only the proposed nonlinear closure improves higher-order statistics.

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses

PubMed Central

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-01-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. PMID:24462600

Research on precision grinding technology of large scale and ultra thin optics

NASA Astrophysics Data System (ADS)

Zhou, Lian; Wei, Qiancai; Li, Jie; Chen, Xianhua; Zhang, Qinghua

2018-03-01

The flatness and parallelism error of large scale and ultra thin optics have an important influence on the subsequent polishing efficiency and accuracy. In order to realize the high precision grinding of those ductile elements, the low deformation vacuum chuck was designed first, which was used for clamping the optics with high supporting rigidity in the full aperture. Then the optics was planar grinded under vacuum adsorption. After machining, the vacuum system was turned off. The form error of optics was on-machine measured using displacement sensor after elastic restitution. The flatness would be convergenced with high accuracy by compensation machining, whose trajectories were integrated with the measurement result. For purpose of getting high parallelism, the optics was turned over and compensation grinded using the form error of vacuum chuck. Finally, the grinding experiment of large scale and ultra thin fused silica optics with aperture of 430mm×430mm×10mm was performed. The best P-V flatness of optics was below 3 μm, and parallelism was below 3 ″. This machining technique has applied in batch grinding of large scale and ultra thin optics.

A Matter of Time: Faster Percolator Analysis via Efficient SVM Learning for Large-Scale Proteomics.

PubMed

Halloran, John T; Rocke, David M

2018-05-04

Percolator is an important tool for greatly improving the results of a database search and subsequent downstream analysis. Using support vector machines (SVMs), Percolator recalibrates peptide-spectrum matches based on the learned decision boundary between targets and decoys. To improve analysis time for large-scale data sets, we update Percolator's SVM learning engine through software and algorithmic optimizations rather than heuristic approaches that necessitate the careful study of their impact on learned parameters across different search settings and data sets. We show that by optimizing Percolator's original learning algorithm, l 2 -SVM-MFN, large-scale SVM learning requires nearly only a third of the original runtime. Furthermore, we show that by employing the widely used Trust Region Newton (TRON) algorithm instead of l 2 -SVM-MFN, large-scale Percolator SVM learning is reduced to nearly only a fifth of the original runtime. Importantly, these speedups only affect the speed at which Percolator converges to a global solution and do not alter recalibration performance. The upgraded versions of both l 2 -SVM-MFN and TRON are optimized within the Percolator codebase for multithreaded and single-thread use and are available under Apache license at bitbucket.org/jthalloran/percolator_upgrade .

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses.

PubMed

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-06-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. Copyright © 2014 Elsevier Inc. All rights reserved.

Online Low-Rank Representation Learning for Joint Multi-subspace Recovery and Clustering.

PubMed

Li, Bo; Liu, Risheng; Cao, Junjie; Zhang, Jie; Lai, Yu-Kun; Liua, Xiuping

2017-10-06

Benefiting from global rank constraints, the lowrank representation (LRR) method has been shown to be an effective solution to subspace learning. However, the global mechanism also means that the LRR model is not suitable for handling large-scale data or dynamic data. For large-scale data, the LRR method suffers from high time complexity, and for dynamic data, it has to recompute a complex rank minimization for the entire data set whenever new samples are dynamically added, making it prohibitively expensive. Existing attempts to online LRR either take a stochastic approach or build the representation purely based on a small sample set and treat new input as out-of-sample data. The former often requires multiple runs for good performance and thus takes longer time to run, and the latter formulates online LRR as an out-ofsample classification problem and is less robust to noise. In this paper, a novel online low-rank representation subspace learning method is proposed for both large-scale and dynamic data. The proposed algorithm is composed of two stages: static learning and dynamic updating. In the first stage, the subspace structure is learned from a small number of data samples. In the second stage, the intrinsic principal components of the entire data set are computed incrementally by utilizing the learned subspace structure, and the low-rank representation matrix can also be incrementally solved by an efficient online singular value decomposition (SVD) algorithm. The time complexity is reduced dramatically for large-scale data, and repeated computation is avoided for dynamic problems. We further perform theoretical analysis comparing the proposed online algorithm with the batch LRR method. Finally, experimental results on typical tasks of subspace recovery and subspace clustering show that the proposed algorithm performs comparably or better than batch methods including the batch LRR, and significantly outperforms state-of-the-art online methods.

The Convergence of High Performance Computing and Large Scale Data Analytics

NASA Astrophysics Data System (ADS)

Duffy, D.; Bowen, M. K.; Thompson, J. H.; Yang, C. P.; Hu, F.; Wills, B.

2015-12-01

As the combinations of remote sensing observations and model outputs have grown, scientists are increasingly burdened with both the necessity and complexity of large-scale data analysis. Scientists are increasingly applying traditional high performance computing (HPC) solutions to solve their "Big Data" problems. While this approach has the benefit of limiting data movement, the HPC system is not optimized to run analytics, which can create problems that permeate throughout the HPC environment. To solve these issues and to alleviate some of the strain on the HPC environment, the NASA Center for Climate Simulation (NCCS) has created the Advanced Data Analytics Platform (ADAPT), which combines both HPC and cloud technologies to create an agile system designed for analytics. Large, commonly used data sets are stored in this system in a write once/read many file system, such as Landsat, MODIS, MERRA, and NGA. High performance virtual machines are deployed and scaled according to the individual scientist's requirements specifically for data analysis. On the software side, the NCCS and GMU are working with emerging commercial technologies and applying them to structured, binary scientific data in order to expose the data in new ways. Native NetCDF data is being stored within a Hadoop Distributed File System (HDFS) enabling storage-proximal processing through MapReduce while continuing to provide accessibility of the data to traditional applications. Once the data is stored within HDFS, an additional indexing scheme is built on top of the data and placed into a relational database. This spatiotemporal index enables extremely fast mappings of queries to data locations to dramatically speed up analytics. These are some of the first steps toward a single unified platform that optimizes for both HPC and large-scale data analysis, and this presentation will elucidate the resulting and necessary exascale architectures required for future systems.

The impact of nudging coefficient for the initialization on the atmospheric flow field and the photochemical ozone concentration of Seoul, Korea

NASA Astrophysics Data System (ADS)

Choi, Hyun-Jung; Lee, Hwa Woon; Sung, Kyoung-Hee; Kim, Min-Jung; Kim, Yoo-Keun; Jung, Woo-Sik

In order to incorporate correctly the large or local scale circulation in the model, a nudging term is introduced into the equation of motion. Nudging effects should be included properly in the model to reduce the uncertainties and improve the air flow field. To improve the meteorological components, the nudging coefficient should perform the adequate influence on complex area for the model initialization technique which related to data reliability and error suppression. Several numerical experiments have been undertaken in order to evaluate the effects on air quality modeling by comparing the performance of the meteorological result with variable nudging coefficient experiment. All experiments are calculated by the upper wind conditions (synoptic or asynoptic condition), respectively. Consequently, it is important to examine the model response to nudging effect of wind and mass information. The MM5-CMAQ model was used to assess the ozone differences in each case, during the episode day in Seoul, Korea and we revealed that there were large differences in the ozone concentration for each run. These results suggest that for the appropriate simulation of large or small-scale circulations, nudging considering the synoptic and asynoptic nudging coefficient does have a clear advantage over dynamic initialization, so appropriate limitation of these nudging coefficient values on its upper wind conditions is necessary before making an assessment. The statistical verifications showed that adequate nudging coefficient for both wind and temperature data throughout the model had a consistently positive impact on the atmospheric and air quality field. On the case dominated by large-scale circulation, a large nudging coefficient shows a minor improvement in the atmospheric and air quality field. However, when small-scale convection is present, the large nudging coefficient produces consistent improvement in the atmospheric and air quality field.

Investigations of grain size dependent sediment transport phenomena on multiple scales

NASA Astrophysics Data System (ADS)

Thaxton, Christopher S.

Sediment transport processes in coastal and fluvial environments resulting from disturbances such as urbanization, mining, agriculture, military operations, and climatic change have significant impact on local, regional, and global environments. Primarily, these impacts include the erosion and deposition of sediment, channel network modification, reduction in downstream water quality, and the delivery of chemical contaminants. The scale and spatial distribution of these effects are largely attributable to the size distribution of the sediment grains that become eligible for transport. An improved understanding of advective and diffusive grain-size dependent sediment transport phenomena will lead to the development of more accurate predictive models and more effective control measures. To this end, three studies were performed that investigated grain-size dependent sediment transport on three different scales. Discrete particle computer simulations of sheet flow bedload transport on the scale of 0.1--100 millimeters were performed on a heterogeneous population of grains of various grain sizes. The relative transport rates and diffusivities of grains under both oscillatory and uniform, steady flow conditions were quantified. These findings suggest that boundary layer formalisms should describe surface roughness through a representative grain size that is functionally dependent on the applied flow parameters. On the scale of 1--10m, experiments were performed to quantify the hydrodynamics and sediment capture efficiency of various baffles installed in a sediment retention pond, a commonly used sedimentation control measure in watershed applications. Analysis indicates that an optimum sediment capture effectiveness may be achieved based on baffle permeability, pond geometry and flow rate. Finally, on the scale of 10--1,000m, a distributed, bivariate watershed terain evolution module was developed within GRASS GIS. Simulation results for variable grain sizes and for distributed rainfall infiltration and land cover matched observations. Although a unique set of governing equations applies to each scale, an improved physics-based understanding of small and medium scale behavior may yield more accurate parameterization of key variables used in large scale predictive models.

A Bayesian hierarchical latent trait model for estimating rater bias and reliability in large-scale performance assessment

PubMed Central

2018-01-01

We propose a novel approach to modelling rater effects in scoring-based assessment. The approach is based on a Bayesian hierarchical model and simulations from the posterior distribution. We apply it to large-scale essay assessment data over a period of 5 years. Empirical results suggest that the model provides a good fit for both the total scores and when applied to individual rubrics. We estimate the median impact of rater effects on the final grade to be ± 2 points on a 50 point scale, while 10% of essays would receive a score at least ± 5 different from their actual quality. Most of the impact is due to rater unreliability, not rater bias. PMID:29614129

Channel optimization of high-intensity laser beams in millimeter-scale plasmas

DOE PAGES

Ceurvorst, L.; Savin, A.; Ratan, N.; ...

2018-04-20

Channeling experiments were performed at the OMEGA EP facility using relativistic intensity (> 10 18 W/cm 2) kilojoule laser pulses through large density scale length (~ 390-570 μm) laser-produced plasmas, demonstrating the effects of the pulse’s focal location and intensity as well as the plasma’s temperature on the resulting channel formation. The results show deeper channeling when focused into hot plasmas and at lower densities as expected. However, contrary to previous large scale particle-in-cell studies, the results also indicate deeper penetration by short (10 ps), intense pulses compared to their longer duration equivalents. To conclude, this new observation has manymore » implications for future laser-plasma research in the relativistic regime.« less

Scaling up digital circuit computation with DNA strand displacement cascades.

PubMed

Qian, Lulu; Winfree, Erik

2011-06-03

To construct sophisticated biochemical circuits from scratch, one needs to understand how simple the building blocks can be and how robustly such circuits can scale up. Using a simple DNA reaction mechanism based on a reversible strand displacement process, we experimentally demonstrated several digital logic circuits, culminating in a four-bit square-root circuit that comprises 130 DNA strands. These multilayer circuits include thresholding and catalysis within every logical operation to perform digital signal restoration, which enables fast and reliable function in large circuits with roughly constant switching time and linear signal propagation delays. The design naturally incorporates other crucial elements for large-scale circuitry, such as general debugging tools, parallel circuit preparation, and an abstraction hierarchy supported by an automated circuit compiler.

Channel optimization of high-intensity laser beams in millimeter-scale plasmas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ceurvorst, L.; Savin, A.; Ratan, N.

Channeling experiments were performed at the OMEGA EP facility using relativistic intensity (> 10 18 W/cm 2) kilojoule laser pulses through large density scale length (~ 390-570 μm) laser-produced plasmas, demonstrating the effects of the pulse’s focal location and intensity as well as the plasma’s temperature on the resulting channel formation. The results show deeper channeling when focused into hot plasmas and at lower densities as expected. However, contrary to previous large scale particle-in-cell studies, the results also indicate deeper penetration by short (10 ps), intense pulses compared to their longer duration equivalents. To conclude, this new observation has manymore » implications for future laser-plasma research in the relativistic regime.« less

Global Magnetohydrodynamic Modeling of the Solar Corona

NASA Technical Reports Server (NTRS)

Linker, Jon A.; Wagner, William (Technical Monitor)

2001-01-01

The solar corona, the hot, tenuous outer atmosphere of the Sun, exhibits many fascinating phenomena on a wide range of scales. One of the ways that the Sun can affect us here at Earth is through the large-scale structure of the corona and the dynamical phenomena associated with it, as it is the corona that extends outward as the solar wind and encounters the Earth's magnetosphere. The goal of our research sponsored by NASA's Supporting Research and Technology Program in Solar Physics is to develop increasingly realistic models of the large-scale solar corona, so that we can understand the underlying properties of the coronal magnetic field that lead to the observed structure and evolution of the corona. We describe the work performed under this contract.

Solving large scale structure in ten easy steps with COLA

NASA Astrophysics Data System (ADS)

Tassev, Svetlin; Zaldarriaga, Matias; Eisenstein, Daniel J.

2013-06-01

We present the COmoving Lagrangian Acceleration (COLA) method: an N-body method for solving for Large Scale Structure (LSS) in a frame that is comoving with observers following trajectories calculated in Lagrangian Perturbation Theory (LPT). Unlike standard N-body methods, the COLA method can straightforwardly trade accuracy at small-scales in order to gain computational speed without sacrificing accuracy at large scales. This is especially useful for cheaply generating large ensembles of accurate mock halo catalogs required to study galaxy clustering and weak lensing, as those catalogs are essential for performing detailed error analysis for ongoing and future surveys of LSS. As an illustration, we ran a COLA-based N-body code on a box of size 100 Mpc/h with particles of mass ≈ 5 × 109Msolar/h. Running the code with only 10 timesteps was sufficient to obtain an accurate description of halo statistics down to halo masses of at least 1011Msolar/h. This is only at a modest speed penalty when compared to mocks obtained with LPT. A standard detailed N-body run is orders of magnitude slower than our COLA-based code. The speed-up we obtain with COLA is due to the fact that we calculate the large-scale dynamics exactly using LPT, while letting the N-body code solve for the small scales, without requiring it to capture exactly the internal dynamics of halos. Achieving a similar level of accuracy in halo statistics without the COLA method requires at least 3 times more timesteps than when COLA is employed.

Resolving the Circumstellar Environment of the Galactic B[e] Supergiant Star MWC 137 from Large to Small Scales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kraus, Michaela; Nickeler, Dieter H.; Liimets, Tiina

The Galactic object MWC 137 has been suggested to belong to the group of B[e] supergiants. However, with its large-scale optical bipolar ring nebula and high-velocity jet and knots, it is a rather atypical representative of this class. We performed multiwavelength observations spreading from the optical to the radio regimes. Based on optical imaging and long-slit spectroscopic data, we found that the northern parts of the large-scale nebula are predominantly blueshifted, while the southern regions appear mostly redshifted. We developed a geometrical model consisting of two double cones. Although various observational features can be approximated with such a scenario, themore » observed velocity pattern is more complex. Using near-infrared integral-field unit spectroscopy, we studied the hot molecular gas in the vicinity of the star. The emission from the hot CO gas arises in a small-scale disk revolving around the star on Keplerian orbits. Although the disk itself cannot be spatially resolved, its emission is reflected by the dust arranged in arc-like structures and the clumps surrounding MWC 137 on small scales. In the radio regime, we mapped the cold molecular gas in the outskirts of the optical nebula. We found that large amounts of cool molecular gas and warm dust embrace the optical nebula in the east, south, and west. No cold gas or dust was detected in the north and northwestern regions. Despite the new insights into the nebula kinematics gained from our studies, the real formation scenario of the large-scale nebula remains an open issue.« less

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

Verdon-Kidd, D. C.; Kiem, A. S.

2009-04-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and/or the Southern Annular Mode (SAM) are associated with a shift in the relative frequency of wet and dry synoptic types on an annual to inter-annual timescale. In addition, the relative frequency of synoptic types is shown to vary on a multi-decadal timescale, associated with changes in the Inter-decadal Pacific Oscillation (IPO). Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

Evolutionary conservatism and convergence both lead to striking similarity in ecology, morphology and performance across continents in frogs.

PubMed

Moen, Daniel S; Irschick, Duncan J; Wiens, John J

2013-12-22

Many clades contain ecologically and phenotypically similar species across continents, yet the processes generating this similarity are largely unstudied, leaving fundamental questions unanswered. Is similarity in morphology and performance across assemblages caused by evolutionary convergence or by biogeographic dispersal of evolutionarily conserved ecotypes? Does convergence to new ecological conditions erase evidence of past adaptation? Here, we analyse ecology, morphology and performance in frog assemblages from three continents (Asia, Australia and South America), assessing the importance of dispersal and convergent evolution in explaining similarity across regions. We find three striking results. First, species using the same microhabitat type are highly similar in morphology and performance across both clades and continents. Second, some species on different continents owe their similarity to dispersal and evolutionary conservatism (rather than evolutionary convergence), even over vast temporal and spatial scales. Third, in one case, an ecologically specialized ancestor radiated into diverse ecotypes that have converged with those on other continents, largely erasing traces of past adaptation to their ancestral ecology. Overall, our study highlights the roles of both evolutionary conservatism and convergence in explaining similarity in species traits over large spatial and temporal scales and demonstrates a statistical framework for addressing these questions in other systems.

Evolutionary conservatism and convergence both lead to striking similarity in ecology, morphology and performance across continents in frogs

PubMed Central

Moen, Daniel S.; Irschick, Duncan J.; Wiens, John J.

2013-01-01

Many clades contain ecologically and phenotypically similar species across continents, yet the processes generating this similarity are largely unstudied, leaving fundamental questions unanswered. Is similarity in morphology and performance across assemblages caused by evolutionary convergence or by biogeographic dispersal of evolutionarily conserved ecotypes? Does convergence to new ecological conditions erase evidence of past adaptation? Here, we analyse ecology, morphology and performance in frog assemblages from three continents (Asia, Australia and South America), assessing the importance of dispersal and convergent evolution in explaining similarity across regions. We find three striking results. First, species using the same microhabitat type are highly similar in morphology and performance across both clades and continents. Second, some species on different continents owe their similarity to dispersal and evolutionary conservatism (rather than evolutionary convergence), even over vast temporal and spatial scales. Third, in one case, an ecologically specialized ancestor radiated into diverse ecotypes that have converged with those on other continents, largely erasing traces of past adaptation to their ancestral ecology. Overall, our study highlights the roles of both evolutionary conservatism and convergence in explaining similarity in species traits over large spatial and temporal scales and demonstrates a statistical framework for addressing these questions in other systems. PMID:24174109

Effects of multiple-scale driving on turbulence statistics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoo, Hyunju; Cho, Jungyeon, E-mail: hyunju527@gmail.com, E-mail: jcho@cnu.ac.kr

2014-01-01

Turbulence is ubiquitous in astrophysical fluids such as the interstellar medium and the intracluster medium. In turbulence studies, it is customary to assume that fluid is driven on a single scale. However, in astrophysical fluids, there can be many different driving mechanisms that act on different scales. If there are multiple energy-injection scales, the process of energy cascade and turbulence dynamo will be different compared with the case of the single energy-injection scale. In this work, we perform three-dimensional incompressible/compressible magnetohydrodynamic turbulence simulations. We drive turbulence in Fourier space in two wavenumber ranges, 2≤k≤√12 (large scale) and 15 ≲ kmore » ≲ 26 (small scale). We inject different amount of energy in each range by changing the amplitude of forcing in the range. We present the time evolution of the kinetic and magnetic energy densities and discuss the turbulence dynamo in the presence of energy injections at two scales. We show how kinetic, magnetic, and density spectra are affected by the two-scale energy injections and we discuss the observational implications. In the case ε {sub L} < ε {sub S}, where ε {sub L} and ε {sub S} are energy-injection rates at the large and small scales, respectively, our results show that even a tiny amount of large-scale energy injection can significantly change the properties of turbulence. On the other hand, when ε {sub L} ≳ ε {sub S}, the small-scale driving does not influence the turbulence statistics much unless ε {sub L} ∼ ε {sub S}.« less

Using HLM to Explore the Effects of Perceptions of Learning Environments and Assessments on Students' Test Performance

ERIC Educational Resources Information Center

Chu, Man-Wai; Babenko, Oksana; Cui, Ying; Leighton, Jacqueline P.

2014-01-01

The study examines the role that perceptions or impressions of learning environments and assessments play in students' performance on a large-scale standardized test. Hierarchical linear modeling (HLM) was used to test aspects of the Learning Errors and Formative Feedback model to determine how much variation in students' performance was explained…

Reading Fluency as a Predictor of Reading Proficiency in Low-Performing, High-Poverty Schools

ERIC Educational Resources Information Center

Baker, Scott K.; Smolkowski, Keith; Katz, Rachell; Fien, Hank; Seeley, John R.; Kame'enui, Edward J.; Beck, Carrie Thomas

2008-01-01

The purpose of this study was to examine oral reading fluency (ORF) in the context of a large-scale federal reading initiative conducted in low performing, high poverty schools. The objectives were to (a) investigate the relation between ORF and comprehensive reading tests, (b) examine whether slope of performance over time on ORF predicted…

Using Hybrid Techniques for Generating Watershed-scale Flood Models in an Integrated Modeling Framework

NASA Astrophysics Data System (ADS)

Saksena, S.; Merwade, V.; Singhofen, P.

2017-12-01

There is an increasing global trend towards developing large scale flood models that account for spatial heterogeneity at watershed scales to drive the future flood risk planning. Integrated surface water-groundwater modeling procedures can elucidate all the hydrologic processes taking part during a flood event to provide accurate flood outputs. Even though the advantages of using integrated modeling are widely acknowledged, the complexity of integrated process representation, computation time and number of input parameters required have deterred its application to flood inundation mapping, especially for large watersheds. This study presents a faster approach for creating watershed scale flood models using a hybrid design that breaks down the watershed into multiple regions of variable spatial resolution by prioritizing higher order streams. The methodology involves creating a hybrid model for the Upper Wabash River Basin in Indiana using Interconnected Channel and Pond Routing (ICPR) and comparing the performance with a fully-integrated 2D hydrodynamic model. The hybrid approach involves simplification procedures such as 1D channel-2D floodplain coupling; hydrologic basin (HUC-12) integration with 2D groundwater for rainfall-runoff routing; and varying spatial resolution of 2D overland flow based on stream order. The results for a 50-year return period storm event show that hybrid model (NSE=0.87) performance is similar to the 2D integrated model (NSE=0.88) but the computational time is reduced to half. The results suggest that significant computational efficiency can be obtained while maintaining model accuracy for large-scale flood models by using hybrid approaches for model creation.

High Performance Semantic Factoring of Giga-Scale Semantic Graph Databases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joslyn, Cliff A.; Adolf, Robert D.; Al-Saffar, Sinan

2010-10-04

As semantic graph database technology grows to address components ranging from extant large triple stores to SPARQL endpoints over SQL-structured relational databases, it will become increasingly important to be able to bring high performance computational resources to bear on their analysis, interpretation, and visualization, especially with respect to their innate semantic structure. Our research group built a novel high performance hybrid system comprising computational capability for semantic graph database processing utilizing the large multithreaded architecture of the Cray XMT platform, conventional clusters, and large data stores. In this paper we describe that architecture, and present the results of our deployingmore » that for the analysis of the Billion Triple dataset with respect to its semantic factors.« less

Microfluidic desalination techniques and their potential applications.

PubMed

Roelofs, S H; van den Berg, A; Odijk, M

2015-09-07

In this review we discuss recent developments in the emerging research field of miniaturized desalination. Traditionally desalination is performed to convert salt water into potable water and research is focused on improving performance of large-scale desalination plants. Microfluidic desalination offers several new opportunities in comparison to macro-scale desalination, such as providing a platform to increase fundamental knowledge of ion transport on the nano- and microfluidic scale and new microfluidic sample preparation methods. This approach has also lead to the development of new desalination techniques, based on micro/nanofluidic ion-transport phenomena, which are potential candidates for up-scaling to (portable) drinking water devices. This review assesses microfluidic desalination techniques on their applications and is meant to contribute to further implementation of microfluidic desalination techniques in the lab-on-chip community.

Assessing the performance of multi-purpose channel management measures at increasing scales

NASA Astrophysics Data System (ADS)

Wilkinson, Mark; Addy, Steve

2016-04-01

In addition to hydroclimatic drivers, sediment deposition from high energy river systems can reduce channel conveyance capacity and lead to significant increases in flood risk. There is an increasing recognition that we need to work with the interplay of natural hydrological and morphological processes in order to attenuate flood flows and manage sediment (both coarse and fine). This typically includes both catchment (e.g. woodland planting, wetlands) and river (e.g. wood placement, floodplain reconnection) restoration approaches. The aim of this work was to assess at which scales channel management measures (notably wood placement and flood embankment removal) are most appropriate for flood and sediment management in high energy upland river systems. We present research findings from two densely instrumented research sites in Scotland which regularly experience flood events and have associated coarse sediment problems. We assessed the performance of a range of novel trial measures for three different scales: wooded flow restrictors and gully tree planting at the small scale (<1 km2), floodplain tree planting and engineered log jams at the intermediate scale (5-60 km2), and flood embankment lowering at the large scale (350 km2). Our results suggest that at the smallest scale, care is needed in the installation of flow restrictors. It was found for some restrictors that vertical erosion can occur if the tributary channel bed is disturbed. Preliminary model evidence suggested they have a very limited impact on channel discharge and flood peak delay owing to the small storage areas behind the structures. At intermediate scales, the ability to trap sediment by engineered log jams was limited. Of the 45 engineered log jams installed, around half created a small geomorphic response and only 5 captured a significant amount of coarse material (during one large flood event). As scale increases, the chance of damage or loss of wood placement is greatest. Monitoring highlights the importance of structure design (porosity and degree of channel blockage) and placement in zones of high sediment transport to optimise performance. At the large scale, well designed flood embankment lowering can improve connectivity to the floodplain during low to medium return period events. However, ancillary works to stabilise the bank failed thus emphasising the importance of letting natural processes readjust channel morphology and hydrological connections to the floodplain. Although these trial measures demonstrated limited effects, this may be in part owing to restrictions in the range of hydroclimatological conditions during the study period and further work is needed to assess the performance under more extreme conditions. This work will contribute to refining guidance for managing channel coarse sediment problems in the future which in turn could help mitigate flooding using natural approaches.

Impact of Data Placement on Resilience in Large-Scale Object Storage Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carns, Philip; Harms, Kevin; Jenkins, John

Distributed object storage architectures have become the de facto standard for high-performance storage in big data, cloud, and HPC computing. Object storage deployments using commodity hardware to reduce costs often employ object replication as a method to achieve data resilience. Repairing object replicas after failure is a daunting task for systems with thousands of servers and billions of objects, however, and it is increasingly difficult to evaluate such scenarios at scale on realworld systems. Resilience and availability are both compromised if objects are not repaired in a timely manner. In this work we leverage a high-fidelity discrete-event simulation model tomore » investigate replica reconstruction on large-scale object storage systems with thousands of servers, billions of objects, and petabytes of data. We evaluate the behavior of CRUSH, a well-known object placement algorithm, and identify configuration scenarios in which aggregate rebuild performance is constrained by object placement policies. After determining the root cause of this bottleneck, we then propose enhancements to CRUSH and the usage policies atop it to enable scalable replica reconstruction. We use these methods to demonstrate a simulated aggregate rebuild rate of 410 GiB/s (within 5% of projected ideal linear scaling) on a 1,024-node commodity storage system. We also uncover an unexpected phenomenon in rebuild performance based on the characteristics of the data stored on the system.« less

Scalable 96-well Plate Based iPSC Culture and Production Using a Robotic Liquid Handling System.

PubMed

Conway, Michael K; Gerger, Michael J; Balay, Erin E; O'Connell, Rachel; Hanson, Seth; Daily, Neil J; Wakatsuki, Tetsuro

2015-05-14

Continued advancement in pluripotent stem cell culture is closing the gap between bench and bedside for using these cells in regenerative medicine, drug discovery and safety testing. In order to produce stem cell derived biopharmaceutics and cells for tissue engineering and transplantation, a cost-effective cell-manufacturing technology is essential. Maintenance of pluripotency and stable performance of cells in downstream applications (e.g., cell differentiation) over time is paramount to large scale cell production. Yet that can be difficult to achieve especially if cells are cultured manually where the operator can introduce significant variability as well as be prohibitively expensive to scale-up. To enable high-throughput, large-scale stem cell production and remove operator influence novel stem cell culture protocols using a bench-top multi-channel liquid handling robot were developed that require minimal technician involvement or experience. With these protocols human induced pluripotent stem cells (iPSCs) were cultured in feeder-free conditions directly from a frozen stock and maintained in 96-well plates. Depending on cell line and desired scale-up rate, the operator can easily determine when to passage based on a series of images showing the optimal colony densities for splitting. Then the necessary reagents are prepared to perform a colony split to new plates without a centrifugation step. After 20 passages (~3 months), two iPSC lines maintained stable karyotypes, expressed stem cell markers, and differentiated into cardiomyocytes with high efficiency. The system can perform subsequent high-throughput screening of new differentiation protocols or genetic manipulation designed for 96-well plates. This technology will reduce the labor and technical burden to produce large numbers of identical stem cells for a myriad of applications.

Validation of large-scale, monochromatic UV disinfection systems for drinking water using dyed microspheres.

PubMed

Blatchley, E R; Shen, C; Scheible, O K; Robinson, J P; Ragheb, K; Bergstrom, D E; Rokjer, D

2008-02-01

Dyed microspheres have been developed as a new method for validation of ultraviolet (UV) reactor systems. When properly applied, dyed microspheres allow measurement of the UV dose distribution delivered by a photochemical reactor for a given operating condition. Prior to this research, dyed microspheres had only been applied to a bench-scale UV reactor. The goal of this research was to extend the application of dyed microspheres to large-scale reactors. Dyed microsphere tests were conducted on two prototype large-scale UV reactors at the UV Validation and Research Center of New York (UV Center) in Johnstown, NY. All microsphere tests were conducted under conditions that had been used previously in biodosimetry experiments involving two challenge bacteriophage: MS2 and Qbeta. Numerical simulations based on computational fluid dynamics and irradiance field modeling were also performed for the same set of operating conditions used in the microspheres assays. Microsphere tests on the first reactor illustrated difficulties in sample collection and discrimination of microspheres against ambient particles. Changes in sample collection and work-up were implemented in tests conducted on the second reactor that allowed for improvements in microsphere capture and discrimination against the background. Under these conditions, estimates of the UV dose distribution from the microspheres assay were consistent with numerical simulations and the results of biodosimetry, using both challenge organisms. The combined application of dyed microspheres, biodosimetry, and numerical simulation offers the potential to provide a more in-depth description of reactor performance than any of these methods individually, or in combination. This approach also has the potential to substantially reduce uncertainties in reactor validation, thereby leading to better understanding of reactor performance, improvements in reactor design, and decreases in reactor capital and operating costs.

Linux OS Jitter Measurements at Large Node Counts using a BlueGene/L

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, Terry R; Tauferner, Mr. Andrew; Inglett, Mr. Todd

2010-01-01

We present experimental results for a coordinated scheduling implementation of the Linux operating system. Results were collected on an IBM Blue Gene/L machine at scales up to 16K nodes. Our results indicate coordinated scheduling was able to provide a dramatic improvement in scaling performance for two applications characterized as bulk synchronous parallel programs.

Providing Test Performance Feedback That Bridges Assessment and Instruction: The Case of Two Standardized English Language Tests in Japan

ERIC Educational Resources Information Center

Sawaki, Yasuyo; Koizumi, Rie

2017-01-01

This small-scale qualitative study considers feedback and results reported for two major large-scale English language tests administered in Japan: the Global Test of English Communication for Students (GTECfS) and the Eiken Test in Practical English Proficiency (Eiken). Specifically, it examines current score-reporting practices in student and…

Enabling Large-Scale Biomedical Analysis in the Cloud

PubMed Central

Lin, Ying-Chih; Yu, Chin-Sheng; Lin, Yen-Jen

2013-01-01

Recent progress in high-throughput instrumentations has led to an astonishing growth in both volume and complexity of biomedical data collected from various sources. The planet-size data brings serious challenges to the storage and computing technologies. Cloud computing is an alternative to crack the nut because it gives concurrent consideration to enable storage and high-performance computing on large-scale data. This work briefly introduces the data intensive computing system and summarizes existing cloud-based resources in bioinformatics. These developments and applications would facilitate biomedical research to make the vast amount of diversification data meaningful and usable. PMID:24288665

Iris indexing based on local intensity order pattern

NASA Astrophysics Data System (ADS)

Emerich, Simina; Malutan, Raul; Crisan, Septimiu; Lefkovits, Laszlo

2017-03-01

In recent years, iris biometric systems have increased in popularity and have been proven that are capable of handling large-scale databases. The main advantage of these systems is accuracy and reliability. A proper iris patterns classification is expected to reduce the matching time in huge databases. This paper presents an iris indexing technique based on Local Intensity Order Pattern. The performance of the present approach is evaluated on UPOL database and is compared with other recent systems designed for iris indexing. The results illustrate the potential of the proposed method for large scale iris identification.

Dynamic Smagorinsky model on anisotropic grids

NASA Technical Reports Server (NTRS)

Scotti, A.; Meneveau, C.; Fatica, M.

1996-01-01

Large Eddy Simulation (LES) of complex-geometry flows often involves highly anisotropic meshes. To examine the performance of the dynamic Smagorinsky model in a controlled fashion on such grids, simulations of forced isotropic turbulence are performed using highly anisotropic discretizations. The resulting model coefficients are compared with a theoretical prediction (Scotti et al., 1993). Two extreme cases are considered: pancake-like grids, for which two directions are poorly resolved compared to the third, and pencil-like grids, where one direction is poorly resolved when compared to the other two. For pancake-like grids the dynamic model yields the results expected from the theory (increasing coefficient with increasing aspect ratio), whereas for pencil-like grids the dynamic model does not agree with the theoretical prediction (with detrimental effects only on smallest resolved scales). A possible explanation of the departure is attempted, and it is shown that the problem may be circumvented by using an isotropic test-filter at larger scales. Overall, all models considered give good large-scale results, confirming the general robustness of the dynamic and eddy-viscosity models. But in all cases, the predictions were poor for scales smaller than that of the worst resolved direction.

Combined climate and carbon-cycle effects of large-scale deforestation

PubMed Central

Bala, G.; Caldeira, K.; Wickett, M.; Phillips, T. J.; Lobell, D. B.; Delire, C.; Mirin, A.

2007-01-01

The prevention of deforestation and promotion of afforestation have often been cited as strategies to slow global warming. Deforestation releases CO2 to the atmosphere, which exerts a warming influence on Earth's climate. However, biophysical effects of deforestation, which include changes in land surface albedo, evapotranspiration, and cloud cover also affect climate. Here we present results from several large-scale deforestation experiments performed with a three-dimensional coupled global carbon-cycle and climate model. These simulations were performed by using a fully three-dimensional model representing physical and biogeochemical interactions among land, atmosphere, and ocean. We find that global-scale deforestation has a net cooling influence on Earth's climate, because the warming carbon-cycle effects of deforestation are overwhelmed by the net cooling associated with changes in albedo and evapotranspiration. Latitude-specific deforestation experiments indicate that afforestation projects in the tropics would be clearly beneficial in mitigating global-scale warming, but would be counterproductive if implemented at high latitudes and would offer only marginal benefits in temperate regions. Although these results question the efficacy of mid- and high-latitude afforestation projects for climate mitigation, forests remain environmentally valuable resources for many reasons unrelated to climate. PMID:17420463

Combined climate and carbon-cycle effects of large-scale deforestation.

PubMed

Bala, G; Caldeira, K; Wickett, M; Phillips, T J; Lobell, D B; Delire, C; Mirin, A

2007-04-17

The prevention of deforestation and promotion of afforestation have often been cited as strategies to slow global warming. Deforestation releases CO(2) to the atmosphere, which exerts a warming influence on Earth's climate. However, biophysical effects of deforestation, which include changes in land surface albedo, evapotranspiration, and cloud cover also affect climate. Here we present results from several large-scale deforestation experiments performed with a three-dimensional coupled global carbon-cycle and climate model. These simulations were performed by using a fully three-dimensional model representing physical and biogeochemical interactions among land, atmosphere, and ocean. We find that global-scale deforestation has a net cooling influence on Earth's climate, because the warming carbon-cycle effects of deforestation are overwhelmed by the net cooling associated with changes in albedo and evapotranspiration. Latitude-specific deforestation experiments indicate that afforestation projects in the tropics would be clearly beneficial in mitigating global-scale warming, but would be counterproductive if implemented at high latitudes and would offer only marginal benefits in temperate regions. Although these results question the efficacy of mid- and high-latitude afforestation projects for climate mitigation, forests remain environmentally valuable resources for many reasons unrelated to climate.

Combined Climate and Carbon-Cycle Effects of Large-Scale Deforestation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bala, G; Caldeira, K; Wickett, M

2006-10-17

The prevention of deforestation and promotion of afforestation have often been cited as strategies to slow global warming. Deforestation releases CO{sub 2} to the atmosphere, which exerts a warming influence on Earth's climate. However, biophysical effects of deforestation, which include changes in land surface albedo, evapotranspiration, and cloud cover also affect climate. Here we present results from several large-scale deforestation experiments performed with a three-dimensional coupled global carbon-cycle and climate model. These are the first such simulations performed using a fully three-dimensional model representing physical and biogeochemical interactions among land, atmosphere, and ocean. We find that global-scale deforestation has amore » net cooling influence on Earth's climate, since the warming carbon-cycle effects of deforestation are overwhelmed by the net cooling associated with changes in albedo and evapotranspiration. Latitude-specific deforestation experiments indicate that afforestation projects in the tropics would be clearly beneficial in mitigating global-scale warming, but would be counterproductive if implemented at high latitudes and would offer only marginal benefits in temperate regions. While these results question the efficacy of mid- and high-latitude afforestation projects for climate mitigation, forests remain environmentally valuable resources for many reasons unrelated to climate.« less

High performance computing applications in neurobiological research

NASA Technical Reports Server (NTRS)

Ross, Muriel D.; Cheng, Rei; Doshay, David G.; Linton, Samuel W.; Montgomery, Kevin; Parnas, Bruce R.

1994-01-01

The human nervous system is a massively parallel processor of information. The vast numbers of neurons, synapses and circuits is daunting to those seeking to understand the neural basis of consciousness and intellect. Pervading obstacles are lack of knowledge of the detailed, three-dimensional (3-D) organization of even a simple neural system and the paucity of large scale, biologically relevant computer simulations. We use high performance graphics workstations and supercomputers to study the 3-D organization of gravity sensors as a prototype architecture foreshadowing more complex systems. Scaled-down simulations run on a Silicon Graphics workstation and scale-up, three-dimensional versions run on the Cray Y-MP and CM5 supercomputers.

Bridging the scales in atmospheric composition simulations using a nudging technique

NASA Astrophysics Data System (ADS)

D'Isidoro, Massimo; Maurizi, Alberto; Russo, Felicita; Tampieri, Francesco

2010-05-01

Studying the interaction between climate and anthropogenic activities, specifically those concentrated in megacities/hot spots, requires the description of processes in a very wide range of scales from local, where anthropogenic emissions are concentrated to global where we are interested to study the impact of these sources. The description of all the processes at all scales within the same numerical implementation is not feasible because of limited computer resources. Therefore, different phenomena are studied by means of different numerical models that can cover different range of scales. The exchange of information from small to large scale is highly non-trivial though of high interest. In fact uncertainties in large scale simulations are expected to receive large contribution from the most polluted areas where the highly inhomogeneous distribution of sources connected to the intrinsic non-linearity of the processes involved can generate non negligible departures between coarse and fine scale simulations. In this work a new method is proposed and investigated in a case study (August 2009) using the BOLCHEM model. Monthly simulations at coarse (0.5° European domain, run A) and fine (0.1° Central Mediterranean domain, run B) horizontal resolution are performed using the coarse resolution as boundary condition for the fine one. Then another coarse resolution run (run C) is performed, in which the high resolution fields remapped on to the coarse grid are used to nudge the concentrations on the Po Valley area. The nudging is applied to all gas and aerosol species of BOLCHEM. Averaged concentrations and variances over Po Valley and other selected areas for O3 and PM are computed. It is observed that although the variance of run B is markedly larger than that of run A, the variance of run C is smaller because the remapping procedure removes large portion of variance from run B fields. Mean concentrations show some differences depending on species: in general mean values of run C lie between run A and run B. A propagation of the signal outside the nudging region is observed, and is evaluated in terms of differences between coarse resolution (with and without nudging) and fine resolution simulations.

Nudging and predictability in regional climate modelling: investigation in a nested quasi-geostrophic model

NASA Astrophysics Data System (ADS)

Omrani, Hiba; Drobinski, Philippe; Dubos, Thomas

2010-05-01

In this work, we consider the effect of indiscriminate and spectral nudging on the large and small scales of an idealized model simulation. The model is a two layer quasi-geostrophic model on the beta-plane driven at its boundaries by the « global » version with periodic boundary condition. This setup mimics the configuration used for regional climate modelling. The effect of large-scale nudging is studied by using the "perfect model" approach. Two sets of experiments are performed: (1) the effect of nudging is investigated with a « global » high resolution two layer quasi-geostrophic model driven by a low resolution two layer quasi-geostrophic model. (2) similar simulations are conducted with the two layer quasi-geostrophic Limited Area Model (LAM) where the size of the LAM domain comes into play in addition to the first set of simulations. The study shows that the indiscriminate nudging time that minimizes the error at both the large and small scales is reached for a nudging time close to the predictability time, for spectral nudging, the optimum nudging time should tend to zero since the best large scale dynamics is supposed to be given by the driving large-scale fields are generally given at much lower frequency than the model time step(e,g, 6-hourly analysis) with a basic interpolation between the fields, the optimum nudging time differs from zero, however remaining smaller than the predictability time.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daleu, C. L.; Plant, R. S.; Woolnough, S. J.

As part of an international intercomparison project, the weak temperature gradient (WTG) and damped gravity wave (DGW) methods are used to parameterize large-scale dynamics in a set of cloud-resolving models (CRMs) and single column models (SCMs). The WTG or DGW method is implemented using a configuration that couples a model to a reference state defined with profiles obtained from the same model in radiative-convective equilibrium. We investigated the sensitivity of each model to changes in SST, given a fixed reference state. We performed a systematic comparison of the WTG and DGW methods in different models, and a systematic comparison ofmore » the behavior of those models using the WTG method and the DGW method. The sensitivity to the SST depends on both the large-scale parameterization method and the choice of the cloud model. In general, SCMs display a wider range of behaviors than CRMs. All CRMs using either the WTG or DGW method show an increase of precipitation with SST, while SCMs show sensitivities which are not always monotonic. CRMs using either the WTG or DGW method show a similar relationship between mean precipitation rate and column-relative humidity, while SCMs exhibit a much wider range of behaviors. DGW simulations produce large-scale velocity profiles which are smoother and less top-heavy compared to those produced by the WTG simulations. Lastly, these large-scale parameterization methods provide a useful tool to identify the impact of parameterization differences on model behavior in the presence of two-way feedback between convection and the large-scale circulation.« less

Overview of physical dosimetry methods for triage application integrated in the new European network RENEB.

PubMed

Trompier, François; Burbidge, Christopher; Bassinet, Céline; Baumann, Marion; Bortolin, Emanuela; De Angelis, Cinzia; Eakins, Jonathan; Della Monaca, Sara; Fattibene, Paola; Quattrini, Maria Cristina; Tanner, Rick; Wieser, Albrecht; Woda, Clemens

2017-01-01

In the EC-funded project RENEB (Realizing the European Network in Biodosimetry), physical methods applied to fortuitous dosimetric materials are used to complement biological dosimetry, to increase dose assessment capacity for large-scale radiation/nuclear accidents. This paper describes the work performed to implement Optically Stimulated Luminescence (OSL) and Electron Paramagnetic Resonance (EPR) dosimetry techniques. OSL is applied to electronic components and EPR to touch-screen glass from mobile phones. To implement these new approaches, several blind tests and inter-laboratory comparisons (ILC) were organized for each assay. OSL systems have shown good performances. EPR systems also show good performance in controlled conditions, but ILC have also demonstrated that post-irradiation exposure to sunlight increases the complexity of the EPR signal analysis. Physically-based dosimetry techniques present high capacity, new possibilities for accident dosimetry, especially in the case of large-scale events. Some of the techniques applied can be considered as operational (e.g. OSL on Surface Mounting Devices [SMD]) and provide a large increase of measurement capacity for existing networks. Other techniques and devices currently undergoing validation or development in Europe could lead to considerable increases in the capacity of the RENEB accident dosimetry network.

Absolute pitch among students at the Shanghai Conservatory of Music: a large-scale direct-test study.

PubMed

Deutsch, Diana; Li, Xiaonuo; Shen, Jing

2013-11-01

This paper reports a large-scale direct-test study of absolute pitch (AP) in students at the Shanghai Conservatory of Music. Overall note-naming scores were very high, with high scores correlating positively with early onset of musical training. Students who had begun training at age ≤5 yr scored 83% correct not allowing for semitone errors and 90% correct allowing for semitone errors. Performance levels were higher for white key pitches than for black key pitches. This effect was greater for orchestral performers than for pianists, indicating that it cannot be attributed to early training on the piano. Rather, accuracy in identifying notes of different names (C, C#, D, etc.) correlated with their frequency of occurrence in a large sample of music taken from the Western tonal repertoire. There was also an effect of pitch range, so that performance on tones in the two-octave range beginning on Middle C was higher than on tones in the octave below Middle C. In addition, semitone errors tended to be on the sharp side. The evidence also ran counter to the hypothesis, previously advanced by others, that the note A plays a special role in pitch identification judgments.

Evolution of scaling emergence in large-scale spatial epidemic spreading.

PubMed

Wang, Lin; Li, Xiang; Zhang, Yi-Qing; Zhang, Yan; Zhang, Kan

2011-01-01

Zipf's law and Heaps' law are two representatives of the scaling concepts, which play a significant role in the study of complexity science. The coexistence of the Zipf's law and the Heaps' law motivates different understandings on the dependence between these two scalings, which has still hardly been clarified. In this article, we observe an evolution process of the scalings: the Zipf's law and the Heaps' law are naturally shaped to coexist at the initial time, while the crossover comes with the emergence of their inconsistency at the larger time before reaching a stable state, where the Heaps' law still exists with the disappearance of strict Zipf's law. Such findings are illustrated with a scenario of large-scale spatial epidemic spreading, and the empirical results of pandemic disease support a universal analysis of the relation between the two laws regardless of the biological details of disease. Employing the United States domestic air transportation and demographic data to construct a metapopulation model for simulating the pandemic spread at the U.S. country level, we uncover that the broad heterogeneity of the infrastructure plays a key role in the evolution of scaling emergence. The analyses of large-scale spatial epidemic spreading help understand the temporal evolution of scalings, indicating the coexistence of the Zipf's law and the Heaps' law depends on the collective dynamics of epidemic processes, and the heterogeneity of epidemic spread indicates the significance of performing targeted containment strategies at the early time of a pandemic disease.

Attribution of Large-Scale Climate Patterns to Seasonal Peak-Flow and Prospects for Prediction Globally

NASA Astrophysics Data System (ADS)

Lee, Donghoon; Ward, Philip; Block, Paul

2018-02-01

Flood-related fatalities and impacts on society surpass those from all other natural disasters globally. While the inclusion of large-scale climate drivers in streamflow (or high-flow) prediction has been widely studied, an explicit link to global-scale long-lead prediction is lacking, which can lead to an improved understanding of potential flood propensity. Here we attribute seasonal peak-flow to large-scale climate patterns, including the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO), using streamflow station observations and simulations from PCR-GLOBWB, a global-scale hydrologic model. Statistically significantly correlated climate patterns and streamflow autocorrelation are subsequently applied as predictors to build a global-scale season-ahead prediction model, with prediction performance evaluated by the mean squared error skill score (MSESS) and the categorical Gerrity skill score (GSS). Globally, fair-to-good prediction skill (20% ≤ MSESS and 0.2 ≤ GSS) is evident for a number of locations (28% of stations and 29% of land area), most notably in data-poor regions (e.g., West and Central Africa). The persistence of such relevant climate patterns can improve understanding of the propensity for floods at the seasonal scale. The prediction approach developed here lays the groundwork for further improving local-scale seasonal peak-flow prediction by identifying relevant global-scale climate patterns. This is especially attractive for regions with limited observations and or little capacity to develop flood early warning systems.

Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python.

PubMed

Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

2014-01-01

In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

Translational bioinformatics in the cloud: an affordable alternative

PubMed Central

2010-01-01

With the continued exponential expansion of publicly available genomic data and access to low-cost, high-throughput molecular technologies for profiling patient populations, computational technologies and informatics are becoming vital considerations in genomic medicine. Although cloud computing technology is being heralded as a key enabling technology for the future of genomic research, available case studies are limited to applications in the domain of high-throughput sequence data analysis. The goal of this study was to evaluate the computational and economic characteristics of cloud computing in performing a large-scale data integration and analysis representative of research problems in genomic medicine. We find that the cloud-based analysis compares favorably in both performance and cost in comparison to a local computational cluster, suggesting that cloud computing technologies might be a viable resource for facilitating large-scale translational research in genomic medicine. PMID:20691073

Large-Scale Astrophysical Visualization on Smartphones

NASA Astrophysics Data System (ADS)

Becciani, U.; Massimino, P.; Costa, A.; Gheller, C.; Grillo, A.; Krokos, M.; Petta, C.

2011-07-01

Nowadays digital sky surveys and long-duration, high-resolution numerical simulations using high performance computing and grid systems produce multidimensional astrophysical datasets in the order of several Petabytes. Sharing visualizations of such datasets within communities and collaborating research groups is of paramount importance for disseminating results and advancing astrophysical research. Moreover educational and public outreach programs can benefit greatly from novel ways of presenting these datasets by promoting understanding of complex astrophysical processes, e.g., formation of stars and galaxies. We have previously developed VisIVO Server, a grid-enabled platform for high-performance large-scale astrophysical visualization. This article reviews the latest developments on VisIVO Web, a custom designed web portal wrapped around VisIVO Server, then introduces VisIVO Smartphone, a gateway connecting VisIVO Web and data repositories for mobile astrophysical visualization. We discuss current work and summarize future developments.

Los Alamos Explosives Performance Key to Stockpile Stewardship

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dattelbaum, Dana

2014-11-03

As the U.S. Nuclear Deterrent ages, one essential factor in making sure that the weapons will continue to perform as designed is understanding the fundamental properties of the high explosives that are part of a nuclear weapons system. As nuclear weapons go through life extension programs, some changes may be advantageous, particularly through the addition of what are known as "insensitive" high explosives that are much less likely to accidentally detonate than the already very safe "conventional" high explosives that are used in most weapons. At Los Alamos National Laboratory explosives research includes a wide variety of both large- andmore » small-scale experiments that include small contained detonations, gas and powder gun firings, larger outdoor detonations, large-scale hydrodynamic tests, and at the Nevada Nuclear Security Site, underground sub-critical experiments.« less

Large-eddy simulation of turbulent flow with a surface-mounted two-dimensional obstacle

NASA Technical Reports Server (NTRS)

Yang, Kyung-Soo; Ferziger, Joel H.

1993-01-01

In this paper, we perform a large eddy simulation (LES) of turbulent flow in a channel containing a two-dimensional obstacle on one wall using a dynamic subgrid-scale model (DSGSM) at Re = 3210, based on bulk velocity above the obstacle and obstacle height; the wall layers are fully resolved. The low Re enables us to perform a DNS (Case 1) against which to validate the LES results. The LES with the DSGSM is designated Case 2. In addition, an LES with the conventional fixed model constant (Case 3) is conducted to allow identification of improvements due to the DSGSM. We also include LES at Re = 82,000 (Case 4) using conventional Smagorinsky subgrid-scale model and a wall-layer model. The results will be compared with the experiment of Dimaczek et al.

Environmental performance evaluation of large-scale municipal solid waste incinerators using data envelopment analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, H.-W.; Chang, N.-B., E-mail: nchang@mail.ucf.ed; Chen, J.-C.

2010-07-15

Limited to insufficient land resources, incinerators are considered in many countries such as Japan and Germany as the major technology for a waste management scheme capable of dealing with the increasing demand for municipal and industrial solid waste treatment in urban regions. The evaluation of these municipal incinerators in terms of secondary pollution potential, cost-effectiveness, and operational efficiency has become a new focus in the highly interdisciplinary area of production economics, systems analysis, and waste management. This paper aims to demonstrate the application of data envelopment analysis (DEA) - a production economics tool - to evaluate performance-based efficiencies of 19more » large-scale municipal incinerators in Taiwan with different operational conditions. A 4-year operational data set from 2002 to 2005 was collected in support of DEA modeling using Monte Carlo simulation to outline the possibility distributions of operational efficiency of these incinerators. Uncertainty analysis using the Monte Carlo simulation provides a balance between simplifications of our analysis and the soundness of capturing the essential random features that complicate solid waste management systems. To cope with future challenges, efforts in the DEA modeling, systems analysis, and prediction of the performance of large-scale municipal solid waste incinerators under normal operation and special conditions were directed toward generating a compromised assessment procedure. Our research findings will eventually lead to the identification of the optimal management strategies for promoting the quality of solid waste incineration, not only in Taiwan, but also elsewhere in the world.« less

From lab to full-scale ultrafiltration in microalgae harvesting

NASA Astrophysics Data System (ADS)

Wenten, I. G.; Steven, S.; Dwiputra, A.; Khoiruddin; Hakim, A. N.

2017-07-01

Ponding system is generally used for microalgae cultivation. However, selection of appropriate technology for the harvesting process is challenging due to the low cell density of cultivated microalgae from the ponding system and the large volume of water to be handled. One of the promising technologies for microalgae harvesting is ultrafiltration (UF). In this study, the performance of UF during harvesting of microalgae in a lab- and a full-scale test is investigated. The performances of both scales are compared and analyzed to provide an understanding of several aspects which affect the yield produced from lab and actual conditions. Furthermore, a unique self-standing non-modular UF is introduced in the full-scale test. The non-modular UF exhibits several advantages, such as simple piping and connection, single pump for filtration and backwashing, and smaller footprint. With those advantages, the non-modular UF could be a promising technology for microalgae harvesting in industrial-scale.

Direct and inverse energy cascades in a forced rotating turbulence experiment

NASA Astrophysics Data System (ADS)

Campagne, Antoine; Gallet, Basile; Moisy, Frédéric; Cortet, Pierre-Philippe

2014-12-01

We present experimental evidence for a double cascade of kinetic energy in a statistically stationary rotating turbulence experiment. Turbulence is generated by a set of vertical flaps, which continuously injects velocity fluctuations towards the center of a rotating water tank. The energy transfers are evaluated from two-point third-order three-component velocity structure functions, which we measure using stereoscopic particle image velocimetry in the rotating frame. Without global rotation, the energy is transferred from large to small scales, as in classical three-dimensional turbulence. For nonzero rotation rates, the horizontal kinetic energy presents a double cascade: a direct cascade at small horizontal scales and an inverse cascade at large horizontal scales. By contrast, the vertical kinetic energy is always transferred from large to small horizontal scales, a behavior reminiscent of the dynamics of a passive scalar in two-dimensional turbulence. At the largest rotation rate, the flow is nearly two-dimensional, and a pure inverse energy cascade is found for the horizontal energy. To describe the scale-by-scale energy budget, we consider a generalization of the Kármán-Howarth-Monin equation to inhomogeneous turbulent flows, in which the energy input is explicitly described as the advection of turbulent energy from the flaps through the surface of the control volume where the measurements are performed.

An innovative large scale integration of silicon nanowire-based field effect transistors

NASA Astrophysics Data System (ADS)

Legallais, M.; Nguyen, T. T. T.; Mouis, M.; Salem, B.; Robin, E.; Chenevier, P.; Ternon, C.

2018-05-01

Since the early 2000s, silicon nanowire field effect transistors are emerging as ultrasensitive biosensors while offering label-free, portable and rapid detection. Nevertheless, their large scale production remains an ongoing challenge due to time consuming, complex and costly technology. In order to bypass these issues, we report here on the first integration of silicon nanowire networks, called nanonet, into long channel field effect transistors using standard microelectronic process. A special attention is paid to the silicidation of the contacts which involved a large number of SiNWs. The electrical characteristics of these FETs constituted by randomly oriented silicon nanowires are also studied. Compatible integration on the back-end of CMOS readout and promising electrical performances open new opportunities for sensing applications.

Dynamic Time Expansion and Compression Using Nonlinear Waveguides

DOEpatents

Findikoglu, Alp T.; Hahn, Sangkoo F.; Jia, Quanxi

2004-06-22

Dynamic time expansion or compression of a small amplitude input signal generated with an initial scale is performed using a nonlinear waveguide. A nonlinear waveguide having a variable refractive index is connected to a bias voltage source having a bias signal amplitude that is large relative to the input signal to vary the reflective index and concomitant speed of propagation of the nonlinear waveguide and an electrical circuit for applying the small amplitude signal and the large amplitude bias signal simultaneously to the nonlinear waveguide. The large amplitude bias signal with the input signal alters the speed of propagation of the small-amplitude signal with time in the nonlinear waveguide to expand or contract the initial time scale of the small-amplitude input signal.

Dynamic time expansion and compression using nonlinear waveguides

DOEpatents

Findikoglu, Alp T [Los Alamos, NM; Hahn, Sangkoo F [Los Alamos, NM; Jia, Quanxi [Los Alamos, NM

2004-06-22

Dynamic time expansion or compression of a small-amplitude input signal generated with an initial scale is performed using a nonlinear waveguide. A nonlinear waveguide having a variable refractive index is connected to a bias voltage source having a bias signal amplitude that is large relative to the input signal to vary the reflective index and concomitant speed of propagation of the nonlinear waveguide and an electrical circuit for applying the small-amplitude signal and the large amplitude bias signal simultaneously to the nonlinear waveguide. The large amplitude bias signal with the input signal alters the speed of propagation of the small-amplitude signal with time in the nonlinear waveguide to expand or contract the initial time scale of the small-amplitude input signal.

Performance evaluation of Space Shuttle SRB parachutes from air drop and scaled model wind tunnel tests. [Solid Rocket Booster recovery system

NASA Technical Reports Server (NTRS)

Moog, R. D.; Bacchus, D. L.; Utreja, L. R.

1979-01-01

The aerodynamic performance characteristics have been determined for the Space Shuttle Solid Rocket Booster drogue, main, and pilot parachutes. The performance evaluation on the 20-degree conical ribbon parachutes is based primarily on air drop tests of full scale prototype parachutes. In addition, parametric wind tunnel tests were performed and used in parachute configuration development and preliminary performance assessments. The wind tunnel test data are compared to the drop test results and both sets of data are used to determine the predicted performance of the Solid Rocket Booster flight parachutes. Data from other drop tests of large ribbon parachutes are also compared with the Solid Rocket Booster parachute performance characteristics. Parameters assessed include full open terminal drag coefficients, reefed drag area, opening characteristics, clustering effects, and forebody interference.

Automated Essay Scoring versus Human Scoring: A Correlational Study

ERIC Educational Resources Information Center

Wang, Jinhao; Brown, Michelle Stallone

2008-01-01

The purpose of the current study was to analyze the relationship between automated essay scoring (AES) and human scoring in order to determine the validity and usefulness of AES for large-scale placement tests. Specifically, a correlational research design was used to examine the correlations between AES performance and human raters' performance.…

Large-Scale Studies on the Transferability of General Problem-Solving Skills and the Pedagogic Potential of Physics

ERIC Educational Resources Information Center

Mashood, K. K.; Singh, Vijay A.

2013-01-01

Research suggests that problem-solving skills are transferable across domains. This claim, however, needs further empirical substantiation. We suggest correlation studies as a methodology for making preliminary inferences about transfer. The correlation of the physics performance of students with their performance in chemistry and mathematics in…

Criterion-Referenced Job Proficiency Testing: A Large Scale Application. Research Report 1193.

ERIC Educational Resources Information Center

Maier, Milton H.; Hirshfeld, Stephen F.

The Army Skill Qualification Tests (SQT's) were designed to determine levels of competence in performance of the tasks crucial to an enlisted soldier's occupational specialty. SQT's are performance-based, criterion-referenced measures which offer two advantages over traditional proficiency and achievement testing programs: test content can be made…

Infrared Multiphoton Dissociation for Quantitative Shotgun Proteomics

PubMed Central

Ledvina, Aaron R.; Lee, M. Violet; McAlister, Graeme C.; Westphall, Michael S.; Coon, Joshua J.

2012-01-01

We modified a dual-cell linear ion trap mass spectrometer to perform infrared multiphoton dissociation (IRMPD) in the low pressure trap of a dual-cell quadrupole linear ion trap (dual cell QLT) and perform large-scale IRMPD analyses of complex peptide mixtures. Upon optimization of activation parameters (precursor q-value, irradiation time, and photon flux), IRMPD subtly, but significantly outperforms resonant excitation CAD for peptides identified at a 1% false-discovery rate (FDR) from a yeast tryptic digest (95% confidence, p = 0.019). We further demonstrate that IRMPD is compatible with the analysis of isobaric-tagged peptides. Using fixed QLT RF amplitude allows for the consistent retention of reporter ions, but necessitates the use of variable IRMPD irradiation times, dependent upon precursor mass-to-charge (m/z). We show that IRMPD activation parameters can be tuned to allow for effective peptide identification and quantitation simultaneously. We thus conclude that IRMPD performed in a dual-cell ion trap is an effective option for the large-scale analysis of both unmodified and isobaric-tagged peptides. PMID:22480380

Accelerating three-dimensional FDTD calculations on GPU clusters for electromagnetic field simulation.

PubMed

Nagaoka, Tomoaki; Watanabe, Soichi

2012-01-01

Electromagnetic simulation with anatomically realistic computational human model using the finite-difference time domain (FDTD) method has recently been performed in a number of fields in biomedical engineering. To improve the method's calculation speed and realize large-scale computing with the computational human model, we adapt three-dimensional FDTD code to a multi-GPU cluster environment with Compute Unified Device Architecture and Message Passing Interface. Our multi-GPU cluster system consists of three nodes. The seven GPU boards (NVIDIA Tesla C2070) are mounted on each node. We examined the performance of the FDTD calculation on multi-GPU cluster environment. We confirmed that the FDTD calculation on the multi-GPU clusters is faster than that on a multi-GPU (a single workstation), and we also found that the GPU cluster system calculate faster than a vector supercomputer. In addition, our GPU cluster system allowed us to perform the large-scale FDTD calculation because were able to use GPU memory of over 100 GB.

Hybrid-optimization strategy for the communication of large-scale Kinetic Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Wu, Baodong; Li, Shigang; Zhang, Yunquan; Nie, Ningming

2017-02-01

The parallel Kinetic Monte Carlo (KMC) algorithm based on domain decomposition has been widely used in large-scale physical simulations. However, the communication overhead of the parallel KMC algorithm is critical, and severely degrades the overall performance and scalability. In this paper, we present a hybrid optimization strategy to reduce the communication overhead for the parallel KMC simulations. We first propose a communication aggregation algorithm to reduce the total number of messages and eliminate the communication redundancy. Then, we utilize the shared memory to reduce the memory copy overhead of the intra-node communication. Finally, we optimize the communication scheduling using the neighborhood collective operations. We demonstrate the scalability and high performance of our hybrid optimization strategy by both theoretical and experimental analysis. Results show that the optimized KMC algorithm exhibits better performance and scalability than the well-known open-source library-SPPARKS. On 32-node Xeon E5-2680 cluster (total 640 cores), the optimized algorithm reduces the communication time by 24.8% compared with SPPARKS.

Ion conducting membranes for aqueous flow battery systems.

PubMed

Yuan, Zhizhang; Zhang, Huamin; Li, Xianfeng

2018-06-07

Flow batteries, aqueous flow batteries in particular, are the most promising candidates for stationary energy storage to realize the wide utilization of renewable energy sources. To meet the requirement of large-scale energy storage, there has been a growing interest in aqueous flow batteries, especially in novel redox couples and flow-type systems. However, the development of aqueous flow battery technologies is at an early stage and their performance can be further improved. As a key component of a flow battery, the membrane has a significant effect on battery performance. Currently, the membranes used in aqueous flow battery technologies are very limited. In this feature article, we first cover the application of porous membranes in vanadium flow battery technology, and then the membranes in most recently reported aqueous flow battery systems. Meanwhile, we hope that this feature article will inspire more efforts to design and prepare membranes with outstanding performance and stability, and then accelerate the development of flow batteries for large scale energy storage applications.

Energy extraction from a large-scale microbial fuel cell system treating municipal wastewater

NASA Astrophysics Data System (ADS)

Ge, Zheng; Wu, Liao; Zhang, Fei; He, Zhen

2015-11-01

Development of microbial fuel cell (MFC) technology must address the challenges associated with energy extraction from large-scale MFC systems consisting of multiple modules. Herein, energy extraction is investigated with a 200-L MFC system (effective volume of 100 L for this study) treating actual municipal wastewater. A commercially available energy harvesting device (BQ 25504) is used successfully to convert 0.8-2.4 V from the MFCs to 5 V for charging ultracapacitors and running a DC motor. Four different types of serial connection containing different numbers of MFC modules are examined for energy extraction and conversion efficiency. The connection containing three rows of the MFCs has exhibited the best performance with the highest power output of ∼114 mW and the conversion efficiency of ∼80%. The weak performance of one-row MFCs negatively affects the overall performance of the connected MFCs in terms of both energy production and conversion. Those results indicate that an MFC system with balanced performance among individual modules will be critical to energy extraction. Future work will focus on application of the extracted energy to support MFC operation.

Scale growth of structures in the turbulent boundary layer with a rod-roughened wall

NASA Astrophysics Data System (ADS)

Lee, Jin; Kim, Jung Hoon; Lee, Jae Hwa

2016-01-01

Direct numerical simulation of a turbulent boundary layer over a rod-roughened wall is performed with a long streamwise domain to examine the streamwise-scale growth mechanism of streamwise velocity fluctuating structures in the presence of two-dimensional (2-D) surface roughness. An instantaneous analysis shows that there is a slightly larger population of long structures with a small helix angle (spanwise inclinations relative to streamwise) and a large spanwise width over the rough-wall compared to that over a smooth-wall. Further inspection of time-evolving instantaneous fields clearly exhibits that adjacent long structures combine to form a longer structure through a spanwise merging process over the rough-wall; moreover, spanwise merging for streamwise scale growth is expected to occur frequently over the rough-wall due to the large spanwise scales generated by the 2-D roughness. Finally, we examine the influence of a large width and a small helix angle of the structures over the rough-wall with regard to spatial two-point correlation. The results show that these factors can increase the streamwise coherence of the structures in a statistical sense.

Just enough inflation: power spectrum modifications at large scales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cicoli, Michele; Downes, Sean; Dutta, Bhaskar

2014-12-01

We show that models of 'just enough' inflation, where the slow-roll evolution lasted only 50- 60 e-foldings, feature modifications of the CMB power spectrum at large angular scales. We perform a systematic analytic analysis in the limit of a sudden transition between any possible non-slow-roll background evolution and the final stage of slow-roll inflation. We find a high degree of universality since most common backgrounds like fast-roll evolution, matter or radiation-dominance give rise to a power loss at large angular scales and a peak together with an oscillatory behaviour at scales around the value of the Hubble parameter at themore » beginning of slow-roll inflation. Depending on the value of the equation of state parameter, different pre-inflationary epochs lead instead to an enhancement of power at low ℓ, and so seem disfavoured by recent observational hints for a lack of CMB power at ℓ∼< 40. We also comment on the importance of initial conditions and the possibility to have multiple pre-inflationary stages.« less

Validity of the two-level model for Viterbi decoder gap-cycle performance

NASA Technical Reports Server (NTRS)

Dolinar, S.; Arnold, S.

1990-01-01

A two-level model has previously been proposed for approximating the performance of a Viterbi decoder which encounters data received with periodically varying signal-to-noise ratio. Such cyclically gapped data is obtained from the Very Large Array (VLA), either operating as a stand-alone system or arrayed with Goldstone. This approximate model predicts that the decoder error rate will vary periodically between two discrete levels with the same period as the gap cycle. It further predicts that the length of the gapped portion of the decoder error cycle for a constraint length K decoder will be about K-1 bits shorter than the actual duration of the gap. The two-level model for Viterbi decoder performance with gapped data is subjected to detailed validation tests. Curves showing the cyclical behavior of the decoder error burst statistics are compared with the simple square-wave cycles predicted by the model. The validity of the model depends on a parameter often considered irrelevant in the analysis of Viterbi decoder performance, the overall scaling of the received signal or the decoder's branch-metrics. Three scaling alternatives are examined: optimum branch-metric scaling and constant branch-metric scaling combined with either constant noise-level scaling or constant signal-level scaling. The simulated decoder error cycle curves roughly verify the accuracy of the two-level model for both the case of optimum branch-metric scaling and the case of constant branch-metric scaling combined with constant noise-level scaling. However, the model is not accurate for the case of constant branch-metric scaling combined with constant signal-level scaling.

Comparison of fall prediction by the Hessisch Oldendorf Fall Risk Scale and the Fall Risk Scale by Huhn in neurological rehabilitation: an observational study.

PubMed

Hermann, Olena; Schmidt, Simone B; Boltzmann, Melanie; Rollnik, Jens D

2018-05-01

To calculate scale performance of the newly developed Hessisch Oldendorf Fall Risk Scale (HOSS) for classifying fallers and non-fallers in comparison with the Risk of Falling Scale by Huhn (FSH), a frequently used assessment tool. A prospective observational trail was conducted. The study was performed in a large specialized neurological rehabilitation facility. The study population ( n = 690) included neurological and neurosurgery patients during neurological rehabilitation with varying levels of disability. Around the half of the study patients were independent and dependent in the activities of daily living (ADL), respectively. Fall risk of each patient was assessed by HOSS and FSH within the first seven days after admission. Event of fall during rehabilitation was compared with HOSS and FSH scores as well as the according fall risk. Scale performance including sensitivity and specificity was calculated for both scales. A total of 107 (15.5%) patients experienced at least one fall. In general, fallers were characterized by an older age, a prolonged length of stay, and a lower Barthel Index (higher dependence in the ADL) on admission than non-fallers. The verification of fall prediction for both scales showed a sensitivity of 83% and a specificity of 64% for the HOSS scale, and a sensitivity of 98% with a specificity of 12% for the FSH scale, respectively. The HOSS shows an adequate sensitivity, a higher specificity and therefore a better scale performance than the FSH. Thus, the HOSS might be superior to existing assessments.

Performance of the Italian version of the subjective well-being under neuroleptic (SWN) scale in schizophrenic outpatients.

PubMed

Balestrieri, M; Giaroli, G; Mazzi, M; Bellantuono, C

2006-05-01

Several studies indicate that subjective experience toward antipsychotic drugs (APs) in schizophrenic patients is a key factor in ensuring a smooth recovery from the illness. The principal aim of this study was to establish the psychometric performance of the Subjective Well-being Under Neuroleptic (SWN) scale in its Italian version and to assess, through the SWN scale, the subjective experience of stabilized psychotic outpatients in maintenance with APs. The original short version of SWN, consisting of 20 items, was back translated, and a focus group was also conducted to better improve the comprehension of the scale. The results showed a good performance of the Italian version of the SWN as documented by the internal consistency (Cronbach's alpha; 0.85). A satisfactory subjective experience was reported in the sample of schizophrenic outpatients interviewed (SWN mean total score: 84.95, SD: 17.5). The performance of the SWN scale in the present study was very similar to that reported by Naber et al. in the original validation study. Large multi-center studies are needed to better establish differences in the subjective experience of schizophrenic patients treated with first- and second-generation APs.

Psychometric properties of the feedback orientation scale among South African salespersons.

PubMed

Lilford, Neil; Caruana, Albert; Pitt, Leyland

2014-02-01

Feedback to employees is an important management tool, and the literature demonstrates that it has a positive effect on learning, motivation, and job performance. This study investigates in a non-U.S. context the psychometric properties of the Feedback Orientation Scale. Data were gathered from a sample of 202 salespersons from a large South African firm within the industrial fuels and lubricants sector. Confirmatory Factor Analysis provided evidence for the intended dimensionality, reliability, and convergent and discriminant validity of the scale.

One-step synthesis of large-scale graphene film doped with gold nanoparticles at liquid-air interface for electrochemistry and Raman detection applications.

PubMed

Zhang, Panpan; Huang, Ying; Lu, Xin; Zhang, Siyu; Li, Jingfeng; Wei, Gang; Su, Zhiqiang

2014-07-29

We demonstrated a facile one-step synthesis strategy for the preparation of a large-scale reduced graphene oxide multilayered film doped with gold nanoparticles (RGO/AuNP film) and applied this film as functional nanomaterials for electrochemistry and Raman detection applications. The related applications of the fabricated RGO/AuNP film in electrochemical nonenzymatic H2O2 biosensor, electrochemical oxygen reduction reaction (ORR), and surface-enhanced Raman scattering (SERS) detection were investigated. Electrochemical data indicate that the H2O2 biosensor fabricated by RGO/AuNP film shows a wide linear range, low limitation of detection, high selectivity, and long-term stability. In addition, it was proved that the created RGO/AuNP film also exhibits excellent ORR electrochemical catalysis performance. The created RGO/AuNP film, when serving as SERS biodetection platform, presents outstanding performances in detecting 4-aminothiophenol with an enhancement factor of approximately 5.6 × 10(5) as well as 2-thiouracil sensing with a low concentration to 1 μM. It is expected that this facile strategy for fabricating large-scale graphene film doped with metallic nanoparticles will spark inspirations in preparing functional nanomaterials and further extend their applications in drug delivery, wastewater purification, and bioenergy.

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

PubMed Central

Azad, Ariful; Ouzounis, Christos A; Kyrpides, Nikos C; Buluç, Aydin

2018-01-01

Abstract Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times and memory demands. Here, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ∼70 million nodes with ∼68 billion edges in ∼2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license. PMID:29315405

Scaling and biomechanics of surface attachment in climbing animals

PubMed Central

Labonte, David; Federle, Walter

2015-01-01

Attachment devices are essential adaptations for climbing animals and valuable models for synthetic adhesives. A major unresolved question for both natural and bioinspired attachment systems is how attachment performance depends on size. Here, we discuss how contact geometry and mode of detachment influence the scaling of attachment forces for claws and adhesive pads, and how allometric data on biological systems can yield insights into their mechanism of attachment. Larger animals are expected to attach less well to surfaces, due to their smaller surface-to-volume ratio, and because it becomes increasingly difficult to distribute load uniformly across large contact areas. In order to compensate for this decrease of weight-specific adhesion, large animals could evolve overproportionally large pads, or adaptations that increase attachment efficiency (adhesion or friction per unit contact area). Available data suggest that attachment pad area scales close to isometry within clades, but pad efficiency in some animals increases with size so that attachment performance is approximately size-independent. The mechanisms underlying this biologically important variation in pad efficiency are still unclear. We suggest that switching between stress concentration (easy detachment) and uniform load distribution (strong attachment) via shear forces is one of the key mechanisms enabling the dynamic control of adhesion during locomotion. PMID:25533088