Robust large-scale parallel nonlinear solvers for simulations.
Energy Technology Data Exchange (ETDEWEB)
Bader, Brett William; Pawlowski, Roger Patrick; Kolda, Tamara Gibson (Sandia National Laboratories, Livermore, CA)
2005-11-01
This report documents research to develop robust and efficient solution techniques for solving large-scale systems of nonlinear equations. The most widely used method for solving systems of nonlinear equations is Newton's method. While much research has been devoted to augmenting Newton-based solvers (usually with globalization techniques), little has been devoted to exploring the application of different models. Our research has been directed at evaluating techniques using different models than Newton's method: a lower order model, Broyden's method, and a higher order model, the tensor method. We have developed large-scale versions of each of these models and have demonstrated their use in important applications at Sandia. Broyden's method replaces the Jacobian with an approximation, allowing codes that cannot evaluate a Jacobian or have an inaccurate Jacobian to converge to a solution. Limited-memory methods, which have been successful in optimization, allow us to extend this approach to large-scale problems. We compare the robustness and efficiency of Newton's method, modified Newton's method, Jacobian-free Newton-Krylov method, and our limited-memory Broyden method. Comparisons are carried out for large-scale applications of fluid flow simulations and electronic circuit simulations. Results show that, in cases where the Jacobian was inaccurate or could not be computed, Broyden's method converged in some cases where Newton's method failed to converge. We identify conditions where Broyden's method can be more efficient than Newton's method. We also present modifications to a large-scale tensor method, originally proposed by Bouaricha, for greater efficiency, better robustness, and wider applicability. Tensor methods are an alternative to Newton-based methods and are based on computing a step based on a local quadratic model rather than a linear model. The advantage of Bouaricha's method is that it can use any
Network robustness under large-scale attacks
Zhou, Qing; Liu, Ruifang; Cui, Shuguang
2014-01-01
Network Robustness under Large-Scale Attacks provides the analysis of network robustness under attacks, with a focus on large-scale correlated physical attacks. The book begins with a thorough overview of the latest research and techniques to analyze the network responses to different types of attacks over various network topologies and connection models. It then introduces a new large-scale physical attack model coined as area attack, under which a new network robustness measure is introduced and applied to study the network responses. With this book, readers will learn the necessary tools to evaluate how a complex network responds to random and possibly correlated attacks.
Trinh, Hung-Cuong; Le, Duc-Hau; Kwon, Yung-Keun
2014-01-01
It has been a challenge in systems biology to unravel relationships between structural properties and dynamic behaviors of biological networks. A Cytoscape plugin named NetDS was recently proposed to analyze the robustness-related dynamics and feed-forward/feedback loop structures of biological networks. Despite such a useful function, limitations on the network size that can be analyzed exist due to high computational costs. In addition, the plugin cannot verify an intrinsic property which can be induced by an observed result because it has no function to simulate the observation on a large number of random networks. To overcome these limitations, we have developed a novel software tool, PANET. First, the time-consuming parts of NetDS were redesigned to be processed in parallel using the OpenCL library. This approach utilizes the full computing power of multi-core central processing units and graphics processing units. Eventually, this made it possible to investigate a large-scale network such as a human signaling network with 1,609 nodes and 5,063 links. We also developed a new function to perform a batch-mode simulation where it generates a lot of random networks and conducts robustness calculations and feed-forward/feedback loop examinations of them. This helps us to determine if the findings in real biological networks are valid in arbitrary random networks or not. We tested our plugin in two case studies based on two large-scale signaling networks and found interesting results regarding relationships between coherently coupled feed-forward/feedback loops and robustness. In addition, we verified whether or not those findings are consistently conserved in random networks through batch-mode simulations. Taken together, our plugin is expected to effectively investigate various relationships between dynamics and structural properties in large-scale networks. Our software tool, user manual and example datasets are freely available at http://panet-csc.sourceforge.net/.
Directory of Open Access Journals (Sweden)
Hung-Cuong Trinh
Full Text Available It has been a challenge in systems biology to unravel relationships between structural properties and dynamic behaviors of biological networks. A Cytoscape plugin named NetDS was recently proposed to analyze the robustness-related dynamics and feed-forward/feedback loop structures of biological networks. Despite such a useful function, limitations on the network size that can be analyzed exist due to high computational costs. In addition, the plugin cannot verify an intrinsic property which can be induced by an observed result because it has no function to simulate the observation on a large number of random networks. To overcome these limitations, we have developed a novel software tool, PANET. First, the time-consuming parts of NetDS were redesigned to be processed in parallel using the OpenCL library. This approach utilizes the full computing power of multi-core central processing units and graphics processing units. Eventually, this made it possible to investigate a large-scale network such as a human signaling network with 1,609 nodes and 5,063 links. We also developed a new function to perform a batch-mode simulation where it generates a lot of random networks and conducts robustness calculations and feed-forward/feedback loop examinations of them. This helps us to determine if the findings in real biological networks are valid in arbitrary random networks or not. We tested our plugin in two case studies based on two large-scale signaling networks and found interesting results regarding relationships between coherently coupled feed-forward/feedback loops and robustness. In addition, we verified whether or not those findings are consistently conserved in random networks through batch-mode simulations. Taken together, our plugin is expected to effectively investigate various relationships between dynamics and structural properties in large-scale networks. Our software tool, user manual and example datasets are freely available at http://panet-csc.sourceforge.net/.
Robust regression for large-scale neuroimaging studies.
Fritsch, Virgile; Da Mota, Benoit; Loth, Eva; Varoquaux, Gaël; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Brühl, Rüdiger; Butzek, Brigitte; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Lemaitre, Hervé; Mann, Karl; Nees, Frauke; Paus, Tomas; Schad, Daniel J; Schümann, Gunter; Frouin, Vincent; Poline, Jean-Baptiste; Thirion, Bertrand
2015-05-01
Multi-subject datasets used in neuroimaging group studies have a complex structure, as they exhibit non-stationary statistical properties across regions and display various artifacts. While studies with small sample sizes can rarely be shown to deviate from standard hypotheses (such as the normality of the residuals) due to the poor sensitivity of normality tests with low degrees of freedom, large-scale studies (e.g. >100 subjects) exhibit more obvious deviations from these hypotheses and call for more refined models for statistical inference. Here, we demonstrate the benefits of robust regression as a tool for analyzing large neuroimaging cohorts. First, we use an analytic test based on robust parameter estimates; based on simulations, this procedure is shown to provide an accurate statistical control without resorting to permutations. Second, we show that robust regression yields more detections than standard algorithms using as an example an imaging genetics study with 392 subjects. Third, we show that robust regression can avoid false positives in a large-scale analysis of brain-behavior relationships with over 1500 subjects. Finally we embed robust regression in the Randomized Parcellation Based Inference (RPBI) method and demonstrate that this combination further improves the sensitivity of tests carried out across the whole brain. Altogether, our results show that robust procedures provide important advantages in large-scale neuroimaging group studies.
Large scale petroleum reservoir simulation and parallel preconditioning algorithms research
Institute of Scientific and Technical Information of China (English)
SUN Jiachang; CAO Jianwen
2004-01-01
Solving large scale linear systems efficiently plays an important role in a petroleum reservoir simulator, and the key part is how to choose an effective parallel preconditioner. Properly choosing a good preconditioner has been beyond the pure algebraic field. An integrated preconditioner should include such components as physical background, characteristics of PDE mathematical model, nonlinear solving method, linear solving algorithm, domain decomposition and parallel computation. We first discuss some parallel preconditioning techniques, and then construct an integrated preconditioner, which is based on large scale distributed parallel processing, and reservoir simulation-oriented. The infrastructure of this preconditioner contains such famous preconditioning construction techniques as coarse grid correction, constraint residual correction and subspace projection correction. We essentially use multi-step means to integrate totally eight types of preconditioning components in order to give out the final preconditioner. Million-grid cell scale industrial reservoir data were tested on native high performance computers. Numerical statistics and analyses show that this preconditioner achieves satisfying parallel efficiency and acceleration effect.
Parallel Framework for Dimensionality Reduction of Large-Scale Datasets
Directory of Open Access Journals (Sweden)
Sai Kiranmayee Samudrala
2015-01-01
Full Text Available Dimensionality reduction refers to a set of mathematical techniques used to reduce complexity of the original high-dimensional data, while preserving its selected properties. Improvements in simulation strategies and experimental data collection methods are resulting in a deluge of heterogeneous and high-dimensional data, which often makes dimensionality reduction the only viable way to gain qualitative and quantitative understanding of the data. However, existing dimensionality reduction software often does not scale to datasets arising in real-life applications, which may consist of thousands of points with millions of dimensions. In this paper, we propose a parallel framework for dimensionality reduction of large-scale data. We identify key components underlying the spectral dimensionality reduction techniques, and propose their efficient parallel implementation. We show that the resulting framework can be used to process datasets consisting of millions of points when executed on a 16,000-core cluster, which is beyond the reach of currently available methods. To further demonstrate applicability of our framework we perform dimensionality reduction of 75,000 images representing morphology evolution during manufacturing of organic solar cells in order to identify how processing parameters affect morphology evolution.
Large-scale parallel genome assembler over cloud computing environment.
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.
Parallel cluster labeling for large-scale Monte Carlo simulations
Flanigan, M; Flanigan, M; Tamayo, P
1995-01-01
We present an optimized version of a cluster labeling algorithm previously introduced by the authors. This algorithm is well suited for large-scale Monte Carlo simulations of spin models using cluster dynamics on parallel computers with large numbers of processors. The algorithm divides physical space into rectangular cells which are assigned to processors and combines a serial local labeling procedure with a relaxation process across nearest-neighbor processors. By controlling overhead and reducing inter-processor communication this method attains good computational speed-up and efficiency. Large systems of up to 65536 X 65536 spins have been simulated at updating speeds of 11 nanosecs/site (90.7 million spin updates/sec) using state-of-the-art supercomputers. In the second part of the article we use the cluster algorithm to study the relaxation of magnetization and energy on large Ising models using Swendsen-Wang dynamics. We found evidence that exponential and power law factors are present in the relaxatio...
Institute of Scientific and Technical Information of China (English)
Zhang Yougang; Xu Bugong
2006-01-01
Decentralized robust stabilization problem of discrete-time fuzzy large-scale systems with parametric uncertainties is considered. This uncertain fuzzy large-scale system consists of N interconnected T-S fuzzy subsystems, and the parametric uncertainties are unknown but norm-bounded. Based on Lyapunov stability theory and decentralized control theory of large-scale system, the design schema of decentralized parallel distributed compensation (DPDC) fuzzy controllers to ensure the asymptotic stability of the whole fuzzy large-scale system is proposed. The existence conditions for these controllers take the forms of LMIs. Finally a numerical simulation example is given to show the utility of the method proposed.
Robust regression for large-scale neuroimaging studies.
2015-01-01
PUBLISHED Multi-subject datasets used in neuroimaging group studies have a complex structure, as they exhibit non-stationary statistical properties across regions and display various artifacts. While studies with small sample sizes can rarely be shown to deviate from standard hypotheses (such as the normality of the residuals) due to the poor sensitivity of normality tests with low degrees of freedom, large-scale studies (e.g. >100 subjects) exhibit more obvious deviations from these hypot...
Robust regression for large-scale neuroimaging studies.
BOKDE, ARUN
2015-01-01
PUBLISHED Multi-subject datasets used in neuroimaging group studies have a complex structure, as they exhibit non-stationary statistical properties across regions and display various artifacts. While studies with small sample sizes can rarely be shown to deviate from standard hypotheses (such as the normality of the residuals) due to the poor sensitivity of normality tests with low degrees of freedom, large-scale studies (e.g. >100 subjects) exhibit more obvious deviations from these hypot...
Concurrent Programming Using Actors: Exploiting Large-Scale Parallelism,
1985-10-07
ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK* Artificial Inteligence Laboratory AREA Is WORK UNIT NUMBERS 545 Technology Square...D-R162 422 CONCURRENT PROGRMMIZNG USING f"OS XL?ITP TEH l’ LARGE-SCALE PARALLELISH(U) NASI AC E Al CAMBRIDGE ARTIFICIAL INTELLIGENCE L. G AGHA ET AL...RESOLUTION TEST CHART N~ATIONAL BUREAU OF STANDA.RDS - -96 A -E. __ _ __ __’ .,*- - -- •. - MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL
Parallel Tensor Compression for Large-Scale Scientific Data.
Energy Technology Data Exchange (ETDEWEB)
Kolda, Tamara G. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Ballard, Grey [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Austin, Woody Nathan [Univ. of Texas, Austin, TX (United States)
2015-10-01
As parallel computing trends towards the exascale, scientific data produced by high-fidelity simulations are growing increasingly massive. For instance, a simulation on a three-dimensional spatial grid with 512 points per dimension that tracks 64 variables per grid point for 128 time steps yields 8 TB of data. By viewing the data as a dense five way tensor, we can compute a Tucker decomposition to find inherent low-dimensional multilinear structure, achieving compression ratios of up to 10000 on real-world data sets with negligible loss in accuracy. So that we can operate on such massive data, we present the first-ever distributed memory parallel implementation for the Tucker decomposition, whose key computations correspond to parallel linear algebra operations, albeit with nonstandard data layouts. Our approach specifies a data distribution for tensors that avoids any tensor data redistribution, either locally or in parallel. We provide accompanying analysis of the computation and communication costs of the algorithms. To demonstrate the compression and accuracy of the method, we apply our approach to real-world data sets from combustion science simulations. We also provide detailed performance results, including parallel performance in both weak and strong scaling experiments.
Parallel Index and Query for Large Scale Data Analysis
Energy Technology Data Exchange (ETDEWEB)
Chou, Jerry; Wu, Kesheng; Ruebel, Oliver; Howison, Mark; Qiang, Ji; Prabhat,; Austin, Brian; Bethel, E. Wes; Ryne, Rob D.; Shoshani, Arie
2011-07-18
Modern scientific datasets present numerous data management and analysis challenges. State-of-the-art index and query technologies are critical for facilitating interactive exploration of large datasets, but numerous challenges remain in terms of designing a system for process- ing general scientific datasets. The system needs to be able to run on distributed multi-core platforms, efficiently utilize underlying I/O infrastructure, and scale to massive datasets. We present FastQuery, a novel software framework that address these challenges. FastQuery utilizes a state-of-the-art index and query technology (FastBit) and is designed to process mas- sive datasets on modern supercomputing platforms. We apply FastQuery to processing of a massive 50TB dataset generated by a large scale accelerator modeling code. We demonstrate the scalability of the tool to 11,520 cores. Motivated by the scientific need to search for inter- esting particles in this dataset, we use our framework to reduce search time from hours to tens of seconds.
Final Report: Migration Mechanisms for Large-scale Parallel Applications
Energy Technology Data Exchange (ETDEWEB)
Jason Nieh
2009-10-30
Process migration is the ability to transfer a process from one machine to another. It is a useful facility in distributed computing environments, especially as computing devices become more pervasive and Internet access becomes more ubiquitous. The potential benefits of process migration, among others, are fault resilience by migrating processes off of faulty hosts, data access locality by migrating processes closer to the data, better system response time by migrating processes closer to users, dynamic load balancing by migrating processes to less loaded hosts, and improved service availability and administration by migrating processes before host maintenance so that applications can continue to run with minimal downtime. Although process migration provides substantial potential benefits and many approaches have been considered, achieving transparent process migration functionality has been difficult in practice. To address this problem, our work has designed, implemented, and evaluated new and powerful transparent process checkpoint-restart and migration mechanisms for desktop, server, and parallel applications that operate across heterogeneous cluster and mobile computing environments. A key aspect of this work has been to introduce lightweight operating system virtualization to provide processes with private, virtual namespaces that decouple and isolate processes from dependencies on the host operating system instance. This decoupling enables processes to be transparently checkpointed and migrated without modifying, recompiling, or relinking applications or the operating system. Building on this lightweight operating system virtualization approach, we have developed novel technologies that enable (1) coordinated, consistent checkpoint-restart and migration of multiple processes, (2) fast checkpointing of process and file system state to enable restart of multiple parallel execution environments and time travel, (3) process migration across heterogeneous
Development of parallel mathematical subroutine library and large scale numerical simulation
Energy Technology Data Exchange (ETDEWEB)
Shimizu, Futoshi [Japan Atomic Energy Research Inst., Tokyo (Japan)
1998-03-01
In recent years, parallel computers, namely parallel supercomputers and workstation clusters, come into use for large scale numerical simulations in the field of computational science. At present, since the parallel programming is difficult compared to using serial computers, development of efficient program in parallel computers can be easily achieved by incorporating the parallelized numerical subroutines. In Japan Atomic Energy Research Institute (JAERI), portable mathematical subroutine library using MPI (Message Passing Interface) or PVM (Parallel Virtual Machine) is being developed for distributed memory parallel computers. In this report, we present the overview of the parallel library and its application to the parallelization for tight-binding molecular dynamics. (author)
Hierarchical approach to optimization of parallel matrix multiplication on large-scale platforms
Hasanov, Khalid
2014-03-04
© 2014, Springer Science+Business Media New York. Many state-of-the-art parallel algorithms, which are widely used in scientific applications executed on high-end computing systems, were designed in the twentieth century with relatively small-scale parallelism in mind. Indeed, while in 1990s a system with few hundred cores was considered a powerful supercomputer, modern top supercomputers have millions of cores. In this paper, we present a hierarchical approach to optimization of message-passing parallel algorithms for execution on large-scale distributed-memory systems. The idea is to reduce the communication cost by introducing hierarchy and hence more parallelism in the communication scheme. We apply this approach to SUMMA, the state-of-the-art parallel algorithm for matrix–matrix multiplication, and demonstrate both theoretically and experimentally that the modified Hierarchical SUMMA significantly improves the communication cost and the overall performance on large-scale platforms.
Penas, David R; González, Patricia; Egea, Jose A; Doallo, Ramón; Banga, Julio R
2017-01-21
The development of large-scale kinetic models is one of the current key issues in computational systems biology and bioinformatics. Here we consider the problem of parameter estimation in nonlinear dynamic models. Global optimization methods can be used to solve this type of problems but the associated computational cost is very large. Moreover, many of these methods need the tuning of a number of adjustable search parameters, requiring a number of initial exploratory runs and therefore further increasing the computation times. Here we present a novel parallel method, self-adaptive cooperative enhanced scatter search (saCeSS), to accelerate the solution of this class of problems. The method is based on the scatter search optimization metaheuristic and incorporates several key new mechanisms: (i) asynchronous cooperation between parallel processes, (ii) coarse and fine-grained parallelism, and (iii) self-tuning strategies. The performance and robustness of saCeSS is illustrated by solving a set of challenging parameter estimation problems, including medium and large-scale kinetic models of the bacterium E. coli, bakerés yeast S. cerevisiae, the vinegar fly D. melanogaster, Chinese Hamster Ovary cells, and a generic signal transduction network. The results consistently show that saCeSS is a robust and efficient method, allowing very significant reduction of computation times with respect to several previous state of the art methods (from days to minutes, in several cases) even when only a small number of processors is used. The new parallel cooperative method presented here allows the solution of medium and large scale parameter estimation problems in reasonable computation times and with small hardware requirements. Further, the method includes self-tuning mechanisms which facilitate its use by non-experts. We believe that this new method can play a key role in the development of large-scale and even whole-cell dynamic models.
Advances in Parallelization for Large Scale Oct-Tree Mesh Generation
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.
A new asynchronous parallel algorithm for inferring large-scale gene regulatory networks.
Directory of Open Access Journals (Sweden)
Xiangyun Xiao
Full Text Available The reconstruction of gene regulatory networks (GRNs from high-throughput experimental data has been considered one of the most important issues in systems biology research. With the development of high-throughput technology and the complexity of biological problems, we need to reconstruct GRNs that contain thousands of genes. However, when many existing algorithms are used to handle these large-scale problems, they will encounter two important issues: low accuracy and high computational cost. To overcome these difficulties, the main goal of this study is to design an effective parallel algorithm to infer large-scale GRNs based on high-performance parallel computing environments. In this study, we proposed a novel asynchronous parallel framework to improve the accuracy and lower the time complexity of large-scale GRN inference by combining splitting technology and ordinary differential equation (ODE-based optimization. The presented algorithm uses the sparsity and modularity of GRNs to split whole large-scale GRNs into many small-scale modular subnetworks. Through the ODE-based optimization of all subnetworks in parallel and their asynchronous communications, we can easily obtain the parameters of the whole network. To test the performance of the proposed approach, we used well-known benchmark datasets from Dialogue for Reverse Engineering Assessments and Methods challenge (DREAM, experimentally determined GRN of Escherichia coli and one published dataset that contains more than 10 thousand genes to compare the proposed approach with several popular algorithms on the same high-performance computing environments in terms of both accuracy and time complexity. The numerical results demonstrate that our parallel algorithm exhibits obvious superiority in inferring large-scale GRNs.
2009-01-01
At the 19th Annual Conference on Parallel Computational Fluid Dynamics held in Antalya, Turkey, in May 2007, the most recent developments and implementations of large-scale and grid computing were presented. This book, comprised of the invited and selected papers of this conference, details those advances, which are of particular interest to CFD and CFD-related communities. It also offers the results related to applications of various scientific and engineering problems involving flows and flow-related topics. Intended for CFD researchers and graduate students, this book is a state-of-the-art presentation of the relevant methodology and implementation techniques of large-scale computing.
Truong, Cong-Doan; Tran, Tien-Dzung; Kwon, Yung-Keun
2016-12-23
Although there have been many studies revealing that dynamic robustness of a biological network is related to its modularity characteristics, no proper tool exists to investigate the relation between network dynamics and modularity. Accordingly, we developed a novel Cytoscape app called MORO, which can conveniently analyze the relationship between network modularity and robustness. We employed an existing algorithm to analyze the modularity of directed graphs and a Boolean network model for robustness calculation. In particular, to ensure the robustness algorithm's applicability to large-scale networks, we implemented it as a parallel algorithm by using the OpenCL library. A batch-mode simulation function was also developed to verify whether an observed relationship between modularity and robustness is conserved in a large set of randomly structured networks. The app provides various visualization modes to better elucidate topological relations between modules, and tabular results of centrality and gene ontology enrichment analyses of modules. We tested the proposed app to analyze large signaling networks and showed an interesting relationship between network modularity and robustness. Our app can be a promising tool which efficiently analyzes the relationship between modularity and robustness in large signaling networks.
Parallel Motion Simulation of Large-Scale Real-Time Crowd in a Hierarchical Environmental Model
Directory of Open Access Journals (Sweden)
Xin Wang
2012-01-01
Full Text Available This paper presents a parallel real-time crowd simulation method based on a hierarchical environmental model. A dynamical model of the complex environment should be constructed to simulate the state transition and propagation of individual motions. By modeling of a virtual environment where virtual crowds reside, we employ different parallel methods on a topological layer, a path layer and a perceptual layer. We propose a parallel motion path matching method based on the path layer and a parallel crowd simulation method based on the perceptual layer. The large-scale real-time crowd simulation becomes possible with these methods. Numerical experiments are carried out to demonstrate the methods and results.
2015-08-01
Atomic /Molecular Massively Parallel Simulator (LAMMPS) Software by N Scott Weingarten and James P Larentzos Approved for...0687 ● AUG 2015 US Army Research Laboratory Implementation of Shifted Periodic Boundary Conditions in the Large-Scale Atomic /Molecular...Shifted Periodic Boundary Conditions in the Large-Scale Atomic /Molecular Massively Parallel Simulator (LAMMPS) Software 5a. CONTRACT NUMBER 5b
Okou, Francis A.; Akhrif, Ouassima; Dessaint, Louis A.; Bouchard, Derrick
2013-05-01
This papter introduces a decentralized multivariable robust adaptive voltage and frequency regulator to ensure the stability of large-scale interconnnected generators. Interconnection parameters (i.e. load, line and transormer parameters) are assumed to be unknown. The proposed design approach requires the reformulation of conventiaonal power system models into a multivariable model with generator terminal voltages as state variables, and excitation and turbine valve inputs as control signals. This model, while suitable for the application of modern control methods, introduces problems with regards to current design techniques for large-scale systems. Interconnection terms, which are treated as perturbations, do not meet the common matching condition assumption. A new adaptive method for a certain class of large-scale systems is therefore introduces that does not require the matching condition. The proposed controller consists of nonlinear inputs that cancel some nonlinearities of the model. Auxiliary controls with linear and nonlinear components are used to stabilize the system. They compensate unknown parametes of the model by updating both the nonlinear component gains and excitation parameters. The adaptation algorithms involve the sigma-modification approach for auxiliary control gains, and the projection approach for excitation parameters to prevent estimation drift. The computation of the matrix-gain of the controller linear component requires the resolution of an algebraic Riccati equation and helps to solve the perturbation-mismatching problem. A realistic power system is used to assess the proposed controller performance. The results show that both stability and transient performance are considerably improved following a severe contingency.
Fonseca, Ricardo A; Fiúza, Frederico; Davidson, Asher; Tsung, Frank S; Mori, Warren B; Silva, Luís O
2013-01-01
A new generation of laser wakefield accelerators, 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 modeling for further understanding of the underlying physics and identification of optimal regimes, but large scale modeling of these scenarios is computationally heavy and requires 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 modeling of LWFA, demonstrating speedups of over 1 order of magni...
Directory of Open Access Journals (Sweden)
Jian Wang
2014-01-01
Full Text Available A large-scale parallel-unit seawater reverse osmosis desalination plant contains many reverse osmosis (RO units. If the operating conditions change, these RO units will not work at the optimal design points which are computed before the plant is built. The operational optimization problem (OOP of the plant is to find out a scheduling of operation to minimize the total running cost when the change happens. In this paper, the OOP is modelled as a mixed-integer nonlinear programming problem. A two-stage differential evolution algorithm is proposed to solve this OOP. Experimental results show that the proposed method is satisfactory in solution quality.
Accelerating Large Scale Image Analyses on Parallel, CPU-GPU Equipped Systems.
Teodoro, George; Kurc, Tahsin M; Pan, Tony; Cooper, Lee A D; Kong, Jun; Widener, Patrick; Saltz, Joel H
2012-05-01
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.
Energy Technology Data Exchange (ETDEWEB)
Quinlan, D; Barany, G; Panas, T
2007-08-30
Many forms of security analysis on large scale applications can be substantially automated but the size and complexity can exceed the time and memory available on conventional desktop computers. Most commercial tools are understandably focused on such conventional desktop resources. This paper presents research work on the parallelization of security analysis of both source code and binaries within our Compass tool, which is implemented using the ROSE source-to-source open compiler infrastructure. We have focused on both shared and distributed memory parallelization of the evaluation of rules implemented as checkers for a wide range of secure programming rules, applicable to desktop machines, networks of workstations and dedicated clusters. While Compass as a tool focuses on source code analysis and reports violations of an extensible set of rules, the binary analysis work uses the exact same infrastructure but is less well developed into an equivalent final tool.
Chen, Weiliang
2016-01-01
Stochastic, spatial reaction-diffusion simulations have been widely used in systems biology and computational neuroscience. However, the increasing scale and complexity of simulated models and morphologies have exceeded the capacity of any serial implementation. This led to development of parallel solutions that benefit from the boost in performance of modern large-scale supercomputers. In this paper, we describe an MPI-based, parallel Operator-Splitting implementation for stochastic spatial reaction-diffusion simulations with irregular tetrahedral meshes. The performance of our implementation is first examined and analyzed with simulations of a simple model. We then demonstrate its usage in real-world research by simulating the reaction-diffusion components of a published calcium burst model in both Purkinje neuron sub-branch and full dendrite morphologies. Simulation results indicate that our implementation is capable of achieving super-linear speedup for balanced loading simulations with reasonable molecul...
Robust linear equation dwell time model compatible with large scale discrete surface error matrix.
Dong, Zhichao; Cheng, Haobo; Tam, Hon-Yuen
2015-04-01
The linear equation dwell time model can translate the 2D convolution process of material removal during subaperture polishing into a more intuitional expression, and may provide relatively fast and reliable results. However, the accurate solution of this ill-posed equation is not so easy, and its practicability for a large scale surface error matrix is still limited. This study first solves this ill-posed equation by Tikhonov regularization and the least square QR decomposition (LSQR) method, and automatically determines an optional interval and a typical value for the damped factor of regularization, which are dependent on the peak removal rate of tool influence functions. Then, a constrained LSQR method is presented to increase the robustness of the damped factor, which can provide more consistent dwell time maps than traditional LSQR. Finally, a matrix segmentation and stitching method is used to cope with large scale surface error matrices. Using these proposed methods, the linear equation model becomes more reliable and efficient in practical engineering.
Hierarchical Modeling and Robust Synthesis for the Preliminary Design of Large Scale Complex Systems
Koch, Patrick N.
1997-01-01
Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis; Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration; and Noise modeling techniques for implementing robust preliminary design when approximate models are employed. Hierarchical partitioning and modeling techniques including intermediate responses, linking variables, and compatibility constraints are incorporated within a hierarchical compromise decision support problem formulation for synthesizing subproblem solutions for a partitioned system. Experimentation and approximation techniques are employed for concurrent investigations and modeling of partitioned subproblems. A modified composite experiment is introduced for fitting better predictive models across the ranges of the factors, and an approach for
DGDFT: A massively parallel method for large scale density functional theory calculations
Energy Technology Data Exchange (ETDEWEB)
Hu, Wei, E-mail: whu@lbl.gov; Yang, Chao, E-mail: cyang@lbl.gov [Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720 (United States); Lin, Lin, E-mail: linlin@math.berkeley.edu [Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720 (United States); Department of Mathematics, University of California, Berkeley, California 94720 (United States)
2015-09-28
We describe a massively parallel implementation of the recently developed discontinuous Galerkin density functional theory (DGDFT) method, for efficient large-scale Kohn-Sham DFT based electronic structure calculations. The DGDFT method uses adaptive local basis (ALB) functions generated on-the-fly during the self-consistent field iteration to represent the solution to the Kohn-Sham equations. The use of the ALB set provides a systematic way to improve the accuracy of the approximation. By using the pole expansion and selected inversion technique to compute electron density, energy, and atomic forces, we can make the computational complexity of DGDFT scale at most quadratically with respect to the number of electrons for both insulating and metallic systems. We show that for the two-dimensional (2D) phosphorene systems studied here, using 37 basis functions per atom allows us to reach an accuracy level of 1.3 × 10{sup −4} Hartree/atom in terms of the error of energy and 6.2 × 10{sup −4} Hartree/bohr in terms of the error of atomic force, respectively. DGDFT can achieve 80% parallel efficiency on 128,000 high performance computing cores when it is used to study the electronic structure of 2D phosphorene systems with 3500-14 000 atoms. This high parallel efficiency results from a two-level parallelization scheme that we will describe in detail.
Parallelization of a beam dynamics code and first large scale radio frequency quadrupole simulations
Directory of Open Access Journals (Sweden)
J. Xu
2007-01-01
Full Text Available The design and operation support of hadron (proton and heavy-ion linear accelerators require substantial use of beam dynamics simulation tools. The beam dynamics code TRACK has been originally developed at Argonne National Laboratory (ANL to fulfill the special requirements of the rare isotope accelerator (RIA accelerator systems. From the beginning, the code has been developed to make it useful in the three stages of a linear accelerator project, namely, the design, commissioning, and operation of the machine. To realize this concept, the code has unique features such as end-to-end simulations from the ion source to the final beam destination and automatic procedures for tuning of a multiple charge state heavy-ion beam. The TRACK code has become a general beam dynamics code for hadron linacs and has found wide applications worldwide. Until recently, the code has remained serial except for a simple parallelization used for the simulation of multiple seeds to study the machine errors. To speed up computation, the TRACK Poisson solver has been parallelized. This paper discusses different parallel models for solving the Poisson equation with the primary goal to extend the scalability of the code onto 1024 and more processors of the new generation of supercomputers known as BlueGene (BG/L. Domain decomposition techniques have been adapted and incorporated into the parallel version of the TRACK code. To demonstrate the new capabilities of the parallelized TRACK code, the dynamics of a 45 mA proton beam represented by 10^{8} particles has been simulated through the 325 MHz radio frequency quadrupole and initial accelerator section of the proposed FNAL proton driver. The results show the benefits and advantages of large-scale parallel computing in beam dynamics simulations.
Visual Data-Analytics of Large-Scale Parallel Discrete-Event Simulations
Energy Technology Data Exchange (ETDEWEB)
Ross, Caitlin; Carothers, Christopher D.; Mubarak, Misbah; Carns, Philip; Ross, Robert; Li, Jianping Kelvin; Ma, Kwan-Liu
2016-11-13
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 to 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
Secure Access Control and Large Scale Robust Representation for Online Multimedia Event Detection
Directory of Open Access Journals (Sweden)
Changyu Liu
2014-01-01
Full Text Available We developed an online multimedia event detection (MED system. However, there are a secure access control issue and a large scale robust representation issue when we want to integrate traditional event detection algorithms into the online environment. For the first issue, we proposed a tree proxy-based and service-oriented access control (TPSAC model based on the traditional role based access control model. Verification experiments were conducted on the CloudSim simulation platform, and the results showed that the TPSAC model is suitable for the access control of dynamic online environments. For the second issue, inspired by the object-bank scene descriptor, we proposed a 1000-object-bank (1000OBK event descriptor. Feature vectors of the 1000OBK were extracted from response pyramids of 1000 generic object detectors which were trained on standard annotated image datasets, such as the ImageNet dataset. A spatial bag of words tiling approach was then adopted to encode these feature vectors for bridging the gap between the objects and events. Furthermore, we performed experiments in the context of event classification on the challenging TRECVID MED 2012 dataset, and the results showed that the robust 1000OBK event descriptor outperforms the state-of-the-art approaches.
Secure access control and large scale robust representation for online multimedia event detection.
Liu, Changyu; Lu, Bin; Li, Huiling
2014-01-01
We developed an online multimedia event detection (MED) system. However, there are a secure access control issue and a large scale robust representation issue when we want to integrate traditional event detection algorithms into the online environment. For the first issue, we proposed a tree proxy-based and service-oriented access control (TPSAC) model based on the traditional role based access control model. Verification experiments were conducted on the CloudSim simulation platform, and the results showed that the TPSAC model is suitable for the access control of dynamic online environments. For the second issue, inspired by the object-bank scene descriptor, we proposed a 1000-object-bank (1000OBK) event descriptor. Feature vectors of the 1000OBK were extracted from response pyramids of 1000 generic object detectors which were trained on standard annotated image datasets, such as the ImageNet dataset. A spatial bag of words tiling approach was then adopted to encode these feature vectors for bridging the gap between the objects and events. Furthermore, we performed experiments in the context of event classification on the challenging TRECVID MED 2012 dataset, and the results showed that the robust 1000OBK event descriptor outperforms the state-of-the-art approaches.
Colin, Samuel
2015-01-01
The de Broglie-Bohm pilot-wave formulation of quantum theory allows the existence of physical states that violate the Born probability rule. Recent work has shown that in pilot-wave field theory on expanding space relaxation to the Born rule is suppressed for long-wavelength field modes, resulting in a large-scale power deficit {\\xi}(k) which for a radiation-dominated expansion is found to have a characteristic (approximate) inverse-tangent dependence on k. In this paper we show that the functional form of {\\xi}(k) is robust under changes in the initial nonequilibrium distribution as well as under the addition of an inflationary era at the end of the radiation-dominated phase. In both cases the predicted deficit {\\xi}(k) remains an inverse-tangent function of k. Furthermore, with the inflationary phase the dependence of the fitting parameters on the number of superposed pre-inflationary energy states is comparable to that found previously. Our results indicate that an inverse-tangent power deficit is likely t...
Suplatov, Dmitry; Popova, Nina; Zhumatiy, Sergey; Voevodin, Vladimir; Švedas, Vytas
2016-04-01
Rapid expansion of online resources providing access to genomic, structural, and functional information associated with biological macromolecules opens an opportunity to gain a deeper understanding of the mechanisms of biological processes due to systematic analysis of large datasets. This, however, requires novel strategies to optimally utilize computer processing power. Some methods in bioinformatics and molecular modeling require extensive computational resources. Other algorithms have fast implementations which take at most several hours to analyze a common input on a modern desktop station, however, due to multiple invocations for a large number of subtasks the full task requires a significant computing power. Therefore, an efficient computational solution to large-scale biological problems requires both a wise parallel implementation of resource-hungry methods as well as a smart workflow to manage multiple invocations of relatively fast algorithms. In this work, a new computer software mpiWrapper has been developed to accommodate non-parallel implementations of scientific algorithms within the parallel supercomputing environment. The Message Passing Interface has been implemented to exchange information between nodes. Two specialized threads - one for task management and communication, and another for subtask execution - are invoked on each processing unit to avoid deadlock while using blocking calls to MPI. The mpiWrapper can be used to launch all conventional Linux applications without the need to modify their original source codes and supports resubmission of subtasks on node failure. We show that this approach can be used to process huge amounts of biological data efficiently by running non-parallel programs in parallel mode on a supercomputer. The C++ source code and documentation are available from http://biokinet.belozersky.msu.ru/mpiWrapper .
Large-Scale, Parallel, Multi-Sensor Atmospheric Data Fusion Using Cloud Computing
Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.
2013-12-01
NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the 'A-Train' platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (MERRA), stratify the comparisons using a classification of the 'cloud scenes' from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Figure 1 shows the architecture of the full computational system, with SciReduce at the core. Multi-year datasets are automatically 'sharded' by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will
DGDFT: A Massively Parallel Method for Large Scale Density Functional Theory Calculations
Hu, Wei; Yang, Chao
2015-01-01
We describe a massively parallel implementation of the recently developed discontinuous Galerkin density functional theory (DGDFT) [J. Comput. Phys. 2012, 231, 2140] method, for efficient large-scale Kohn-Sham DFT based electronic structure calculations. The DGDFT method uses adaptive local basis (ALB) functions generated on-the-fly during the self-consistent field (SCF) iteration to represent the solution to the Kohn-Sham equations. The use of the ALB set provides a systematic way to improve the accuracy of the approximation. It minimizes the number of degrees of freedom required to represent the solution to the Kohn-Sham problem for a desired level of accuracy. In particular, DGDFT can reach the planewave accuracy with far fewer numbers of degrees of freedom. By using the pole expansion and selected inversion (PEXSI) technique to compute electron density, energy and atomic forces, we can make the computational complexity of DGDFT scale at most quadratically with respect to the number of electrons for both i...
Directory of Open Access Journals (Sweden)
Lorenzo L. Pesce
2013-01-01
Full Text Available Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determined the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons and processor pool sizes (1 to 256 processors. Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.
Oikawa, Takaaki; Sonoda, Jun; Sato, Motoyuki; Honma, Noriyasu; Ikegawa, Yutaka
Analysis of lightning electromagnetic field using the FDTD method have been studied in recent year. However, large-scale three-dimensional analysis on real environment have not been considered, because the FDTD method has huge computational cost on large-scale analysis. So we have proposed a three-dimensional moving window FDTD (MW-FDTD) method with parallel computation. Our method use few computational cost than the conventional FDTD method and the original MW-FDTD method. In this paper, we have studied about computation performance of MW-FDTD parallel computation and large-scale three-dimensional analysis of lightning electromagnetic field on a real terrain model using our MW-FDTD with parallel computation.
Wu, Hansheng
2016-09-01
The problem of decentralised robust stabilisation is considered for a class of uncertain large-scale time-delay interconnected dynamical systems. In the paper, the upper bounds of delayed state perturbations, uncertainties, interconnection terms, and external disturbances are assumed to be completely unknown, and the delays are assumed to be any non-negative constants. For such a class of uncertain large-scale time-delay interconnected systems, a new method is presented whereby a class of adaptation-free decentralised local robust state feedback controllers can be constructed. In addition, it is also shown that the solutions of uncertain large-scale time-delay interconnected systems can be guaranteed to be uniformly ultimately bounded. Finally, as an application to the practical mechanical systems, some simulations of a numerical example are provided to demonstrate the validity of the theoretical results.
Parallel Optimization of Polynomials for Large-scale Problems in Stability and Control
Kamyar, Reza
In this thesis, we focus on some of the NP-hard problems in control theory. Thanks to the converse Lyapunov theory, these problems can often be modeled as optimization over polynomials. To avoid the problem of intractability, we establish a trade off between accuracy and complexity. In particular, we develop a sequence of tractable optimization problems --- in the form of Linear Programs (LPs) and/or Semi-Definite Programs (SDPs) --- whose solutions converge to the exact solution of the NP-hard problem. However, the computational and memory complexity of these LPs and SDPs grow exponentially with the progress of the sequence - meaning that improving the accuracy of the solutions requires solving SDPs with tens of thousands of decision variables and constraints. Setting up and solving such problems is a significant challenge. The existing optimization algorithms and software are only designed to use desktop computers or small cluster computers --- machines which do not have sufficient memory for solving such large SDPs. Moreover, the speed-up of these algorithms does not scale beyond dozens of processors. This in fact is the reason we seek parallel algorithms for setting-up and solving large SDPs on large cluster- and/or super-computers. We propose parallel algorithms for stability analysis of two classes of systems: 1) Linear systems with a large number of uncertain parameters; 2) Nonlinear systems defined by polynomial vector fields. First, we develop a distributed parallel algorithm which applies Polya's and/or Handelman's theorems to some variants of parameter-dependent Lyapunov inequalities with parameters defined over the standard simplex. The result is a sequence of SDPs which possess a block-diagonal structure. We then develop a parallel SDP solver which exploits this structure in order to map the computation, memory and communication to a distributed parallel environment. Numerical tests on a supercomputer demonstrate the ability of the algorithm to
Efficient graph-based dynamic load-balancing for parallel large-scale agent-based traffic simulation
Xu, Y.; Cai, W.; Aydt, H.; Lees, M.; Tolk, A.; Diallo, S.Y.; Ryzhov, I.O.; Yilmaz, L.; Buckley, S.; Miller, J.A.
2014-01-01
One of the issues of parallelizing large-scale agent-based traffic simulations is partitioning and load-balancing. Traffic simulations are dynamic applications where the distribution of workload in the spatial domain constantly changes. Dynamic load-balancing at run-time has shown better efficiency
LDRD final report : robust analysis of large-scale combinatorial applications.
Energy Technology Data Exchange (ETDEWEB)
Carr, Robert D.; Morrison, Todd (University of Colorado, Denver, CO); Hart, William Eugene; Benavides, Nicolas L. (Santa Clara University, Santa Clara, CA); Greenberg, Harvey J. (University of Colorado, Denver, CO); Watson, Jean-Paul; Phillips, Cynthia Ann
2007-09-01
Discrete models of large, complex systems like national infrastructures and complex logistics frameworks naturally incorporate many modeling uncertainties. Consequently, there is a clear need for optimization techniques that can robustly account for risks associated with modeling uncertainties. This report summarizes the progress of the Late-Start LDRD 'Robust Analysis of Largescale Combinatorial Applications'. This project developed new heuristics for solving robust optimization models, and developed new robust optimization models for describing uncertainty scenarios.
Lin, Y.; O'Malley, D.; Vesselinov, V. V.
2015-12-01
Inverse modeling seeks model parameters given a set of observed state variables. However, for many practical problems due to the facts that the observed data sets are often large and model parameters are often numerous, conventional methods for solving the inverse modeling can be computationally expensive. We have developed a new, computationally-efficient Levenberg-Marquardt method for solving large-scale inverse modeling. Levenberg-Marquardt methods require the solution of a dense linear system of equations which can be prohibitively expensive to compute for large-scale inverse problems. Our novel method projects the original large-scale linear problem down to a Krylov subspace, such that the dimensionality of the measurements can be significantly reduced. Furthermore, instead of solving the linear system for every Levenberg-Marquardt damping parameter, we store the Krylov subspace computed when solving the first damping parameter and recycle it for all the following damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved by using these computational techniques. We apply this new inverse modeling method to invert for a random transitivity field. Our algorithm is fast enough to solve for the distributed model parameters (transitivity) at each computational node in the model domain. The inversion is also aided by the use regularization techniques. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). Julia is an advanced high-level scientific programing language that allows for efficient memory management and utilization of high-performance computational resources. By comparing with a Levenberg-Marquardt method using standard linear inversion techniques, our Levenberg-Marquardt method yields speed-up ratio of 15 in a multi-core computational environment and a speed-up ratio of 45 in a single-core computational environment. Therefore, our new inverse modeling method is a
Directory of Open Access Journals (Sweden)
Xiaoqing Wang
2016-01-01
Full Text Available Parallel analyses about the dynamic responses of a large-scale water conveyance tunnel under seismic excitation are presented in this paper. A full three-dimensional numerical model considering the water-tunnel-soil coupling is established and adopted to investigate the tunnel’s dynamic responses. The movement and sloshing of the internal water are simulated using the multi-material Arbitrary Lagrangian Eulerian (ALE method. Nonlinear fluid–structure interaction (FSI between tunnel and inner water is treated by using the penalty method. Nonlinear soil-structure interaction (SSI between soil and tunnel is dealt with by using the surface to surface contact algorithm. To overcome computing power limitations and to deal with such a large-scale calculation, a parallel algorithm based on the modified recursive coordinate bisection (MRCB considering the balance of SSI and FSI loads is proposed and used. The whole simulation is accomplished on Dawning 5000 A using the proposed MRCB based parallel algorithm optimized to run on supercomputers. The simulation model and the proposed approaches are validated by comparison with the added mass method. Dynamic responses of the tunnel are analyzed and the parallelism is discussed. Besides, factors affecting the dynamic responses are investigated. Better speedup and parallel efficiency show the scalability of the parallel method and the analysis results can be used to aid in the design of water conveyance tunnels.
Galassi, D.; Tamain, P.; Bufferand, H.; Ciraolo, G.; Ghendrih, Ph.; Baudoin, C.; Colin, C.; Fedorczak, N.; Nace, N.; Serre, E.
2017-03-01
The poloidal asymmetries of parallel flows in edge plasmas are investigated by the 3D fluid turbulence code TOKAM3X. A diverted COMPASS-like magnetic equilibrium is used for the simulations. The measurements and simulations of parallel Mach numbers are compared, and exhibit good qualitative agreement. Small-scale turbulent transport is observed to dominate near the low field side midplane, even though it co-exists with significant large-scale cross-field fluxes. Despite the turbulent nature of the plasma in the divertor region, simulations show the low effectiveness of turbulence for the cross-field transport towards the private flux region. Nevertheless, a complex pattern of fluxes associated with the average field components are found to cross the separatrix in the divertor region. Large-scale and small-scale turbulent E× B transport, along with the \
HPF: a data parallel programming interface for large-scale numerical simulations
Energy Technology Data Exchange (ETDEWEB)
Seo, Yoshiki; Suehiro, Kenji; Murai, Hitoshi [NEC Corp., Tokyo (Japan)
1998-03-01
HPF (High Performance Fortran) is a data parallel language designed for programming on distributed memory parallel systems. The first draft of HPF1.0 was defined in 1993 as a de facto standard language. Recently, relatively reliable HPF compilers have become available on several distributed memory parallel systems. Many projects to parallelize real world programs have started mainly in the U.S. and Europe, and the weak and strong points in the current HPF have been made clear. In this paper, major data transfer patterns required to parallelize numerical simulations, such as SHIFT, matrix transposition, reduction, GATHER/SCATTER and irregular communication, and the programming methods to implement them with HPF are described. The problems in the current HPF interface for developing efficient parallel programs and recent activities to deal with them is presented as well. (author)
Directory of Open Access Journals (Sweden)
Brian J.N. Wylie
2008-01-01
Full Text Available Developers of applications with large-scale computing requirements are currently presented with a variety of high-performance systems optimised for message-passing, however, effectively exploiting the available computing resources remains a major challenge. In addition to fundamental application scalability characteristics, application and system peculiarities often only manifest at extreme scales, requiring highly scalable performance measurement and analysis tools that are convenient to incorporate in application development and tuning activities. We present our experiences with a multigrid solver benchmark and state-of-the-art real-world applications for numerical weather prediction and computational fluid dynamics, on three quite different multi-thousand-processor supercomputer systems – Cray XT3/4, MareNostrum & Blue Gene/L – using the newly-developed SCALASCA toolset to quantify and isolate a range of significant performance issues.
MapReduce Based Parallel Neural Networks in Enabling Large Scale Machine Learning.
Liu, Yang; Yang, Jie; Huang, Yuan; Xu, Lixiong; Li, Siguang; Qi, Man
2015-01-01
Artificial neural networks (ANNs) have been widely used in pattern recognition and classification applications. However, ANNs are notably slow in computation especially when the size of data is large. Nowadays, big data has received a momentum from both industry and academia. To fulfill the potentials of ANNs for big data applications, the computation process must be speeded up. For this purpose, this paper parallelizes neural networks based on MapReduce, which has become a major computing model to facilitate data intensive applications. Three data intensive scenarios are considered in the parallelization process in terms of the volume of classification data, the size of the training data, and the number of neurons in the neural network. The performance of the parallelized neural networks is evaluated in an experimental MapReduce computer cluster from the aspects of accuracy in classification and efficiency in computation.
Energy Technology Data Exchange (ETDEWEB)
Bauerle, Matthew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2014-08-01
This project utilizes Graphics Processing Units (GPUs) to compute radiograph simulations for arbitrary objects. The generation of radiographs, also known as the forward projection imaging model, is computationally intensive and not widely utilized. The goal of this research is to develop a massively parallel algorithm that can compute forward projections for objects with a trillion voxels (3D pixels). To achieve this end, the data are divided into blocks that can each t into GPU memory. The forward projected image is also divided into segments to allow for future parallelization and to avoid needless computations.
Solving Large-Scale QAP Problems in Parallel with the Search
DEFF Research Database (Denmark)
Clausen, Jens; Brüngger, A.; Marzetta, A.
1998-01-01
Program libraries are one tool to make the cooperation between specialists from various fields successful: the separation of application-specific knowledge from application-independent tasks ensures portability, maintenance, extensibility, and flexibility. The current paper demonstrates the success...... in combining problem-specific knowledge for the quadratic assignment problem (QAP) with the raw computing power offered by contemporary parallel hardware by using the library of parallel search algorithms ZRAM. Solutions of previously unsolved large standard test-instances of the QAP are presented....
A General-purpose Framework for Parallel Processing of Large-scale LiDAR Data
Li, Z.; Hodgson, M.; Li, W.
2016-12-01
Light detection and ranging (LiDAR) technologies have proven efficiency to quickly obtain very detailed Earth surface data for a large spatial extent. Such data is important for scientific discoveries such as Earth and ecological sciences and natural disasters and environmental applications. However, handling LiDAR data poses grand geoprocessing challenges due to data intensity and computational intensity. Previous studies received notable success on parallel processing of LiDAR data to these challenges. However, these studies either relied on high performance computers and specialized hardware (GPUs) or focused mostly on finding customized solutions for some specific algorithms. We developed a general-purpose scalable framework coupled with sophisticated data decomposition and parallelization strategy to efficiently handle big LiDAR data. Specifically, 1) a tile-based spatial index is proposed to manage big LiDAR data in the scalable and fault-tolerable Hadoop distributed file system, 2) two spatial decomposition techniques are developed to enable efficient parallelization of different types of LiDAR processing tasks, and 3) by coupling existing LiDAR processing tools with Hadoop, this framework is able to conduct a variety of LiDAR data processing tasks in parallel in a highly scalable distributed computing environment. The performance and scalability of the framework is evaluated with a series of experiments conducted on a real LiDAR dataset using a proof-of-concept prototype system. The results show that the proposed framework 1) is able to handle massive LiDAR data more efficiently than standalone tools; and 2) provides almost linear scalability in terms of either increased workload (data volume) or increased computing nodes with both spatial decomposition strategies. We believe that the proposed framework provides valuable references on developing a collaborative cyberinfrastructure for processing big earth science data in a highly scalable environment.
MapReduce Based Parallel Neural Networks in Enabling Large Scale Machine Learning
Yang Liu; Jie Yang; Yuan Huang; Lixiong Xu; Siguang Li; Man Qi
2015-01-01
Artificial neural networks (ANNs) have been widely used in pattern recognition and classification applications. However, ANNs are notably slow in computation especially when the size of data is large. Nowadays, big data has received a momentum from both industry and academia. To fulfill the potentials of ANNs for big data applications, the computation process must be speeded up. For this purpose, this paper parallelizes neural networks based on MapReduce, which has become a major computing mo...
Hierarchical Parallel Matrix Multiplication on Large-Scale Distributed Memory Platforms
Quintin, Jean-Noel
2013-10-01
Matrix multiplication is a very important computation kernel both in its own right as a building block of many scientific applications and as a popular representative for other scientific applications. Cannon\\'s algorithm which dates back to 1969 was the first efficient algorithm for parallel matrix multiplication providing theoretically optimal communication cost. However this algorithm requires a square number of processors. In the mid-1990s, the SUMMA algorithm was introduced. SUMMA overcomes the shortcomings of Cannon\\'s algorithm as it can be used on a nonsquare number of processors as well. Since then the number of processors in HPC platforms has increased by two orders of magnitude making the contribution of communication in the overall execution time more significant. Therefore, the state of the art parallel matrix multiplication algorithms should be revisited to reduce the communication cost further. This paper introduces a new parallel matrix multiplication algorithm, Hierarchical SUMMA (HSUMMA), which is a redesign of SUMMA. Our algorithm reduces the communication cost of SUMMA by introducing a two-level virtual hierarchy into the two-dimensional arrangement of processors. Experiments on an IBM BlueGene/P demonstrate the reduction of communication cost up to 2.08 times on 2048 cores and up to 5.89 times on 16384 cores. © 2013 IEEE.
Parallel Processing for Large-scale Fault Tree in Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Xinyan Wang
2013-05-01
Full Text Available Wireless sensor networks (WSN covers many kinds of technologies, such as technology of sensor, embedded system, wireless communication, etc. WSN is different from the traditional networks in size, communication distance and energy-constrained so as to develop new topology, protocol, quality of service (QoS, and so on. In order to solve the problem of self-organizing in the topology, this paper proposes a novel strategy which is based on communication delay between sensors. Firstly, the gateway selects some boundary nodes to connect. Secondly, the boundary nodes choose inner nodes. The rest may be deduced by analogy. Finally, a net-tree topology with multi-path routing is developed. The analyses of the topology show that net-tree has strong ability in self-organizing and extensible. However, the scale of system is usually very large and complexity so that it is hard to detect the failure nodes when the nodes fail. To solve the greater challenge, the paper proposes to adopt fault tree analysis. Fault tree is a commonly used method to analyze the reliability of a network or system. Based on the fault tree analysis, a parallel computing algorithm is represented to these faults in the net-tree. Firstly, two models for parallel processing are came up and we focus on the parallel processing algorithm based on the cut sets. Then, the speedup ratio is studied. Compare with the serial algorithm, the results of the experiment shows that the efficiency has been greatly improved.
Large-scale design of robust genetic circuits with multiple inputs and outputs for mammalian cells.
Weinberg, Benjamin H; Pham, N T Hang; Caraballo, Leidy D; Lozanoski, Thomas; Engel, Adrien; Bhatia, Swapnil; Wong, Wilson W
2017-05-01
Engineered genetic circuits for mammalian cells often require extensive fine-tuning to perform as intended. We present a robust, general, scalable system, called 'Boolean logic and arithmetic through DNA excision' (BLADE), to engineer genetic circuits with multiple inputs and outputs in mammalian cells with minimal optimization. The reliability of BLADE arises from its reliance on recombinases under the control of a single promoter, which integrates circuit signals on a single transcriptional layer. We used BLADE to build 113 circuits in human embryonic kidney and Jurkat T cells and devised a quantitative, vector-proximity metric to evaluate their performance. Of 113 circuits analyzed, 109 functioned (96.5%) as intended without optimization. The circuits, which are available through Addgene, include a 3-input, two-output full adder; a 6-input, one-output Boolean logic look-up table; circuits with small-molecule-inducible control; and circuits that incorporate CRISPR-Cas9 to regulate endogenous genes. BLADE enables execution of sophisticated cellular computation in mammalian cells, with applications in cell and tissue engineering.
Robust Periodic Hartree-Fock Exchange for Large-Scale Simulations Using Gaussian Basis Sets.
Guidon, Manuel; Hutter, Jürg; VandeVondele, Joost
2009-11-10
Hartree-Fock exchange with a truncated Coulomb operator has recently been discussed in the context of periodic plane-waves calculations [Spencer, J.; Alavi, A. Phys. Rev. B: Solid State, 2008, 77, 193110]. In this work, this approach is extended to Gaussian basis sets, leading to a stable and accurate procedure for evaluating Hartree-Fock exchange at the Γ-point. Furthermore, it has been found that standard hybrid functionals can be transformed into short-range functionals without loss of accuracy. The well-defined short-range nature of the truncated exchange operator can naturally be exploited in integral screening procedures and makes this approach interesting for both condensed phase and gas phase systems. The presented Hartree-Fock implementation is massively parallel and scales up to ten thousands of cores. This makes it feasible to perform highly accurate calculations on systems containing thousands of atoms or ten thousands of basis functions. The applicability of this scheme is demonstrated by calculating the cohesive energy of a LiH crystal close to the Hartree-Fock basis set limit and by performing an electronic structure calculation of a complete protein (rubredoxin) in solution with a large and flexible basis set.
Robustness of linkage strategy that leads to large-scale cooperation.
Inaba, Misato; Takahashi, Nobuyuki; Ohtsuki, Hisashi
2016-11-21
One of the most well-known models to characterize cooperation among unrelated individuals is Social dilemma (SD). However there is no consensus about how to solve the SD by itself. Since SDs are often embedded in other social interactions, including indirect reciprocity games (IR), human can coordinate their behaviors across multiple games. Such coordination is called 'linkage'. Recently linkage has been considered as a promising solution to resolve SDs, since excluding SD defectors (i.e. those who defected in SD) from indirectly reciprocal relationships functions as a costless sanction. A previous study performed mathematical modeling and revealed that a linkage strategy, which cooperates in SD and engages in the Standing strategy in IR based on the recipients' behaviors in both SD and IR, was an ESS against a non-linkage strategy which defects in SD and engages in the Standing strategy in IR based on recipients' behaviors only in IR (Panchanathan and Boyd, 2004). In order to investigate the robustness of the linkage strategy, we devised a non-linkage strategy, which cooperates in SD but does not link two games. First, we conducted a mathematical analysis and demonstrated that the linkage strategy was not an ESS against cooperating non-linkage strategy. Second, we conducted a series of agent-based computer simulations to examine how the strategies perform in situations in which various types of errors can occur. Our results showed that the linkage strategy was an ESS only when there are implementation errors in SD. However, the equilibrium of the linkage strategy was unstable when there are perception errors. Since we know that humans are not free from perception errors in their social life, future studies will need to show how perception errors can be overcome in order to provide support for the conclusion that linkage is a plausible solution to SDs. Copyright © 2016 Elsevier Ltd. All rights reserved.
Leveraging human oversight and intervention in large-scale parallel processing of open-source data
Casini, Enrico; Suri, Niranjan; Bradshaw, Jeffrey M.
2015-05-01
The popularity of cloud computing along with the increased availability of cheap storage have led to the necessity of elaboration and transformation of large volumes of open-source data, all in parallel. One way to handle such extensive volumes of information properly is to take advantage of distributed computing frameworks like Map-Reduce. Unfortunately, an entirely automated approach that excludes human intervention is often unpredictable and error prone. Highly accurate data processing and decision-making can be achieved by supporting an automatic process through human collaboration, in a variety of environments such as warfare, cyber security and threat monitoring. Although this mutual participation seems easily exploitable, human-machine collaboration in the field of data analysis presents several challenges. First, due to the asynchronous nature of human intervention, it is necessary to verify that once a correction is made, all the necessary reprocessing is done in chain. Second, it is often needed to minimize the amount of reprocessing in order to optimize the usage of resources due to limited availability. In order to improve on these strict requirements, this paper introduces improvements to an innovative approach for human-machine collaboration in the processing of large amounts of open-source data in parallel.
A Review on Large Scale Graph Processing Using Big Data Based Parallel Programming Models
Directory of Open Access Journals (Sweden)
Anuraj Mohan
2017-02-01
Full Text Available Processing big graphs has become an increasingly essential activity in various fields like engineering, business intelligence and computer science. Social networks and search engines usually generate large graphs which demands sophisticated techniques for social network analysis and web structure mining. Latest trends in graph processing tend towards using Big Data platforms for parallel graph analytics. MapReduce has emerged as a Big Data based programming model for the processing of massively large datasets. Apache Giraph, an open source implementation of Google Pregel which is based on Bulk Synchronous Parallel Model (BSP is used for graph analytics in social networks like Facebook. This proposed work is to investigate the algorithmic effects of the MapReduce and BSP model on graph problems. The triangle counting problem in graphs is considered as a benchmark and evaluations are made on the basis of time of computation on the same cluster, scalability in relation to graph and cluster size, resource utilization and the structure of the graph.
Energy Technology Data Exchange (ETDEWEB)
Lehoucq, Richard B.; Salinger, Andrew G.
1999-08-01
We present an approach for determining the linear stability of steady states of PDEs on massively parallel computers. Linearizing the transient behavior around a steady state leads to a generalized eigenvalue problem. The eigenvalues with largest real part are calculated using Arnoldi's iteration driven by a novel implementation of the Cayley transformation to recast the problem as an ordinary eigenvalue problem. The Cayley transformation requires the solution of a linear system at each Arnoldi iteration, which must be done iteratively for the algorithm to scale with problem size. A representative model problem of 3D incompressible flow and heat transfer in a rotating disk reactor is used to analyze the effect of algorithmic parameters on the performance of the eigenvalue algorithm. Successful calculations of leading eigenvalues for matrix systems of order up to 4 million were performed, identifying the critical Grashof number for a Hopf bifurcation.
An extensible operating system design for large-scale parallel machines.
Energy Technology Data Exchange (ETDEWEB)
Riesen, Rolf E.; Ferreira, Kurt Brian
2009-04-01
Running untrusted user-level code inside an operating system kernel has been studied in the 1990's but has not really caught on. We believe the time has come to resurrect kernel extensions for operating systems that run on highly-parallel clusters and supercomputers. The reason is that the usage model for these machines differs significantly from a desktop machine or a server. In addition, vendors are starting to add features, such as floating-point accelerators, multicore processors, and reconfigurable compute elements. An operating system for such machines must be adaptable to the requirements of specific applications and provide abstractions to access next-generation hardware features, without sacrificing performance or scalability.
Gallien, Sebastien; Kim, Sang Yoon; Domon, Bruno
2015-06-01
Targeted high-resolution and accurate mass analyses performed on fast sequencing mass spectrometers have opened new avenues for quantitative proteomics. More specifically, parallel reaction monitoring (PRM) implemented on quadrupole-orbitrap instruments exhibits exquisite selectivity to discriminate interferences from analytes. Furthermore, the instrument trapping capability enhances the sensitivity of the measurements. The PRM technique, applied to the analysis of limited peptide sets (typically 50 peptides or less) in a complex matrix, resulted in an improved detection and quantification performance as compared with the reference method of selected reaction monitoring performed on triple quadrupole instruments. However, the implementation of PRM for the analysis of large peptide numbers requires the adjustment of mass spectrometry acquisition parameters, which affects dramatically the quality of the generated data, and thus the overall output of an experiment. A newly designed data acquisition scheme enabled the analysis of moderate-to-large peptide numbers while retaining a high performance level. This new method, called internal standard triggered-parallel reaction monitoring (IS-PRM), relies on added internal standards and the on-the-fly adjustment of acquisition parameters to drive in real-time measurement of endogenous peptides. The acquisition time management was designed to maximize the effective time devoted to measure the analytes in a time-scheduled targeted experiment. The data acquisition scheme alternates between two PRM modes: a fast low-resolution "watch mode" and a "quantitative mode" using optimized parameters ensuring data quality. The IS-PRM method exhibited a highly effective use of the instrument time. Applied to the analysis of large peptide sets (up to 600) in complex samples, the method showed an unprecedented combination of scale and analytical performance, with limits of quantification in the low amol range. The successful analysis of
Joshi, Navin Chandra; Sun, Xudong; Wang, Haimin; Magara, Tetsuya; Moon, Y -J
2015-01-01
In this paper, we present observations and analysis of an interesting sigmoid formation, eruption and the associated flare that occurred on 2014 April 18 using multi-wavelength data sets. We discuss the possible role of the sigmoid eruption in triggering the flare, which consists of two different set of ribbons: parallel ribbons as well as a large-scale quasi-circular ribbon. Several observational evidence and nonlinear force-free field extrapolation results show the existence of a large-scale fan-spine type magnetic configuration with a sigmoid lying under a section of the fan dome. The event can be explained with the following two phases. During the pre-flare phase, we observed the formation and appearance of sigmoid via tether-cutting reconnection between the two sets of sheared fields under the fan dome. The second, main flare phase, features the eruption of the sigmoid, the subsequent flare with parallel ribbons, and a quasi-circular ribbon. We propose the following multi-stage successive reconnections s...
fast_protein_cluster: parallel and optimized clustering of large-scale protein modeling data.
Hung, Ling-Hong; Samudrala, Ram
2014-06-15
fast_protein_cluster is a fast, parallel and memory efficient package used to cluster 60 000 sets of protein models (with up to 550 000 models per set) generated by the Nutritious Rice for the World project. fast_protein_cluster is an optimized and extensible toolkit that supports Root Mean Square Deviation after optimal superposition (RMSD) and Template Modeling score (TM-score) as metrics. RMSD calculations using a laptop CPU are 60× faster than qcprot and 3× faster than current graphics processing unit (GPU) implementations. New GPU code further increases the speed of RMSD and TM-score calculations. fast_protein_cluster provides novel k-means and hierarchical clustering methods that are up to 250× and 2000× faster, respectively, than Clusco, and identify significantly more accurate models than Spicker and Clusco. fast_protein_cluster is written in C++ using OpenMP for multi-threading support. Custom streaming Single Instruction Multiple Data (SIMD) extensions and advanced vector extension intrinsics code accelerate CPU calculations, and OpenCL kernels support AMD and Nvidia GPUs. fast_protein_cluster is available under the M.I.T. license. (http://software.compbio.washington.edu/fast_protein_cluster) © The Author 2014. Published by Oxford University Press.
Efficient numerical methods for the large-scale, parallel solution of elastoplastic contact problems
Frohne, Jörg
2015-08-06
© 2016 John Wiley & Sons, Ltd. Quasi-static elastoplastic contact problems are ubiquitous in many industrial processes and other contexts, and their numerical simulation is consequently of great interest in accurately describing and optimizing production processes. The key component in these simulations is the solution of a single load step of a time iteration. From a mathematical perspective, the problems to be solved in each time step are characterized by the difficulties of variational inequalities for both the plastic behavior and the contact problem. Computationally, they also often lead to very large problems. In this paper, we present and evaluate a complete set of methods that are (1) designed to work well together and (2) allow for the efficient solution of such problems. In particular, we use adaptive finite element meshes with linear and quadratic elements, a Newton linearization of the plasticity, active set methods for the contact problem, and multigrid-preconditioned linear solvers. Through a sequence of numerical experiments, we show the performance of these methods. This includes highly accurate solutions of a three-dimensional benchmark problem and scaling our methods in parallel to 1024 cores and more than a billion unknowns.
Directory of Open Access Journals (Sweden)
Julián A García-Grajales
Full Text Available With the growing body of research on traumatic brain injury and spinal cord injury, computational neuroscience has recently focused its modeling efforts on neuronal functional deficits following mechanical loading. However, in most of these efforts, cell damage is generally only characterized by purely mechanistic criteria, functions of quantities such as stress, strain or their corresponding rates. The modeling of functional deficits in neurites as a consequence of macroscopic mechanical insults has been rarely explored. In particular, a quantitative mechanically based model of electrophysiological impairment in neuronal cells, Neurite, has only very recently been proposed. In this paper, we present the implementation details of this model: a finite difference parallel program for simulating electrical signal propagation along neurites under mechanical loading. Following the application of a macroscopic strain at a given strain rate produced by a mechanical insult, Neurite is able to simulate the resulting neuronal electrical signal propagation, and thus the corresponding functional deficits. The simulation of the coupled mechanical and electrophysiological behaviors requires computational expensive calculations that increase in complexity as the network of the simulated cells grows. The solvers implemented in Neurite--explicit and implicit--were therefore parallelized using graphics processing units in order to reduce the burden of the simulation costs of large scale scenarios. Cable Theory and Hodgkin-Huxley models were implemented to account for the electrophysiological passive and active regions of a neurite, respectively, whereas a coupled mechanical model accounting for the neurite mechanical behavior within its surrounding medium was adopted as a link between electrophysiology and mechanics. This paper provides the details of the parallel implementation of Neurite, along with three different application examples: a long myelinated axon
García-Grajales, Julián A; Rucabado, Gabriel; García-Dopico, Antonio; Peña, José-María; Jérusalem, Antoine
2015-01-01
With the growing body of research on traumatic brain injury and spinal cord injury, computational neuroscience has recently focused its modeling efforts on neuronal functional deficits following mechanical loading. However, in most of these efforts, cell damage is generally only characterized by purely mechanistic criteria, functions of quantities such as stress, strain or their corresponding rates. The modeling of functional deficits in neurites as a consequence of macroscopic mechanical insults has been rarely explored. In particular, a quantitative mechanically based model of electrophysiological impairment in neuronal cells, Neurite, has only very recently been proposed. In this paper, we present the implementation details of this model: a finite difference parallel program for simulating electrical signal propagation along neurites under mechanical loading. Following the application of a macroscopic strain at a given strain rate produced by a mechanical insult, Neurite is able to simulate the resulting neuronal electrical signal propagation, and thus the corresponding functional deficits. The simulation of the coupled mechanical and electrophysiological behaviors requires computational expensive calculations that increase in complexity as the network of the simulated cells grows. The solvers implemented in Neurite--explicit and implicit--were therefore parallelized using graphics processing units in order to reduce the burden of the simulation costs of large scale scenarios. Cable Theory and Hodgkin-Huxley models were implemented to account for the electrophysiological passive and active regions of a neurite, respectively, whereas a coupled mechanical model accounting for the neurite mechanical behavior within its surrounding medium was adopted as a link between electrophysiology and mechanics. This paper provides the details of the parallel implementation of Neurite, along with three different application examples: a long myelinated axon, a segmented
Energy Technology Data Exchange (ETDEWEB)
Thiess, Alexander R.
2011-12-19
In this thesis we present the development of the self-consistent, full-potential Korringa-Kohn-Rostoker (KKR) Green function method KKRnano for calculating the electronic properties, magnetic interactions, and total energy including all electrons on the basis of the density functional theory (DFT) on high-end massively parallelized high-performance computers for supercells containing thousands of atoms without sacrifice of accuracy. KKRnano was used for the following two applications. The first application is centered in the field of dilute magnetic semiconductors. In this field a new promising material combination was identified: gadolinium doped gallium nitride which shows ferromagnetic ordering of colossal magnetic moments above room temperature. It quickly turned out that additional extrinsic defects are inducing the striking properties. However, the question which kind of extrinsic defects are present in experimental samples is still unresolved. In order to shed light on this open question, we perform extensive studies of the most promising candidates: interstitial nitrogen and oxygen, as well as gallium vacancies. By analyzing the pairwise magnetic coupling among defects it is shown that nitrogen and oxygen interstitials cannot support thermally stable ferromagnetic order. Gallium vacancies, on the other hand, facilitate an important coupling mechanism. The vacancies are found to induce large magnetic moments on all surrounding nitrogen sites, which then couple ferromagnetically both among themselves and with the gadolinium dopants. Based on a statistical evaluation it can be concluded that already small concentrations of gallium vacancies can lead to a distinct long-range ferromagnetic ordering. Beyond this important finding we present further indications, from which we infer that gallium vacancies likely cause the striking ferromagnetic coupling of colossal magnetic moments in GaN:Gd. The second application deals with the phase-change material germanium
Directory of Open Access Journals (Sweden)
Hua Wang
2008-01-01
Full Text Available With the movement of magnetic resonance imaging (MRI technology towards higher field (and therefore frequency systems, the interaction of the fields generated by the system with patients, healthcare workers, and internally within the system is attracting more attention. Due to the complexity of the interactions, computational modeling plays an essential role in the analysis, design, and development of modern MRI systems. As a result of the large computational scale associated with most of the MRI models, numerical schemes that rely on a single computer processing unit often require a significant amount of memory and long computational times, which makes modeling of these problems quite inefficient. This paper presents dedicated message passing interface (MPI, OPENMP parallel computing solvers for finite-difference time-domain (FDTD, and quasistatic finite-difference (QSFD schemes. The FDTD and QSFD methods have been widely used to model/ analyze the induction of electric fields/ currents in voxel phantoms and MRI system components at high and low frequencies, respectively. The power of the optimized parallel computing architectures is illustrated by distinct, large-scale field calculation problems and shows significant computational advantages over conventional single processing platforms.
A modified parallel tree code for N-body simulation of the Large Scale Structure of the Universe
Becciani, U
2000-01-01
N-body codes to perform simulations of the origin and evolution of the Large Scale Structure of the Universe have improved significantly over the past decade both in terms of the resolution achieved and of reduction of the CPU time. However, state-of-the-art N-body codes hardly allow one to deal with particle numbers larger than a few 10^7, even on the largest parallel systems. In order to allow simulations with larger resolution, we have first re-considered the grouping strategy as described in Barnes (1990) (hereafter B90) and applied it with some modifications to our WDSH-PT (Work and Data SHaring - Parallel Tree) code. In the first part of this paper we will give a short description of the code adopting the Barnes and Hut algorithm \\cite{barh86} (hereafter BH), and in particular of the memory and work distribution strategy applied to describe the {\\it data distribution} on a CC-NUMA machine like the CRAY-T3E system. In the second part of the paper we describe the modification to the Barnes grouping strate...
DEFF Research Database (Denmark)
Knecht, Stefan; Jensen, Hans Jørgen Aagaard; Fleig, Timo
2010-01-01
We present a parallel implementation of a large-scale relativistic double-group configuration interaction CIprogram. It is applicable with a large variety of two- and four-component Hamiltonians. The parallel algorithm is based on a distributed data model in combination with a static load balanci...
Energy Technology Data Exchange (ETDEWEB)
Pask, J E; Sukumar, N; Guney, M; Hu, W
2011-02-28
Over the course of the past two decades, quantum mechanical calculations have emerged as a key component of modern materials research. However, the solution of the required quantum mechanical equations is a formidable task and this has severely limited the range of materials systems which can be investigated by such accurate, quantum mechanical means. The current state of the art for large-scale quantum simulations is the planewave (PW) method, as implemented in now ubiquitous VASP, ABINIT, and QBox codes, among many others. However, since the PW method uses a global Fourier basis, with strictly uniform resolution at all points in space, and in which every basis function overlaps every other at every point, it suffers from substantial inefficiencies in calculations involving atoms with localized states, such as first-row and transition-metal atoms, and requires substantial nonlocal communications in parallel implementations, placing critical limits on scalability. In recent years, real-space methods such as finite-differences (FD) and finite-elements (FE) have been developed to address these deficiencies by reformulating the required quantum mechanical equations in a strictly local representation. However, while addressing both resolution and parallel-communications problems, such local real-space approaches have been plagued by one key disadvantage relative to planewaves: excessive degrees of freedom (grid points, basis functions) needed to achieve the required accuracies. And so, despite critical limitations, the PW method remains the standard today. In this work, we show for the first time that this key remaining disadvantage of real-space methods can in fact be overcome: by building known atomic physics into the solution process using modern partition-of-unity (PU) techniques in finite element analysis. Indeed, our results show order-of-magnitude reductions in basis size relative to state-of-the-art planewave based methods. The method developed here is
DEFF Research Database (Denmark)
Knecht, Stefan; Jensen, Hans Jørgen Aagaard; Fleig, Timo
2008-01-01
is based on the message passing interface and a distributed data model in order to efficiently exploit key features of various modern computer architectures. We exemplify the nearly linear scalability of our parallel code in large-scale multireference configuration interaction (MRCI) calculations, and we...
Energy Technology Data Exchange (ETDEWEB)
1992-03-10
The first phase of the proposed work is largely completed on schedule. Scientists at the San Diego Supercomputer Center (SDSC) succeeded in putting a version of the Hamburg isopycnal coordinate ocean model (OPYC) onto the INTEL parallel computer. Due to the slow run speeds of the OPYC on the parallel machine, another ocean is being model used during the first part of phase 2. The model chosen is the Large Scale Geostrophic (LSG) model form the Max Planck Institute.
Institute of Scientific and Technical Information of China (English)
Wo Songlin; Shi Guodong; Zou Yun
2007-01-01
The decentralized robust guaranteed cost control problem is studied for a class ofinterconnected singular large-scale systems with time-delay and norm-bounded time-invariant parameter uncertainty under a given quadratic cost performance function. The problem that is addressed in this study is to design a decentralized robust guaranteed cost state feedback controller such that the closed-loop system is not only regular, impulse-free and stable, but also guarantees an adequate level of performance for all admissible uncertainties. A sufficient condition for the existence of the decentralized robust guaranteed cost state feedback controllers is proposed in terms of a linear matrix inequality (LMI) via LMI approach. When this condition is feasible, the desired state feedback decentralized robust guaranteed cost controller gain matrices can be obtained. Finally, an illustrative example is provided to demonstrate the effectiveness of the proposed approach.
Manfredi, Sabato
2016-06-01
Large-scale dynamic systems are becoming highly pervasive in their occurrence with applications ranging from system biology, environment monitoring, sensor networks, and power systems. They are characterised by high dimensionality, complexity, and uncertainty in the node dynamic/interactions that require more and more computational demanding methods for their analysis and control design, as well as the network size and node system/interaction complexity increase. Therefore, it is a challenging problem to find scalable computational method for distributed control design of large-scale networks. In this paper, we investigate the robust distributed stabilisation problem of large-scale nonlinear multi-agent systems (briefly MASs) composed of non-identical (heterogeneous) linear dynamical systems coupled by uncertain nonlinear time-varying interconnections. By employing Lyapunov stability theory and linear matrix inequality (LMI) technique, new conditions are given for the distributed control design of large-scale MASs that can be easily solved by the toolbox of MATLAB. The stabilisability of each node dynamic is a sufficient assumption to design a global stabilising distributed control. The proposed approach improves some of the existing LMI-based results on MAS by both overcoming their computational limits and extending the applicative scenario to large-scale nonlinear heterogeneous MASs. Additionally, the proposed LMI conditions are further reduced in terms of computational requirement in the case of weakly heterogeneous MASs, which is a common scenario in real application where the network nodes and links are affected by parameter uncertainties. One of the main advantages of the proposed approach is to allow to move from a centralised towards a distributed computing architecture so that the expensive computation workload spent to solve LMIs may be shared among processors located at the networked nodes, thus increasing the scalability of the approach than the network
Large Scale Earth’s Bow Shock with Northern IMF as Simulated by PIC Code in Parallel with MHD Model
Indian Academy of Sciences (India)
Suleiman Baraka
2016-06-01
In this paper, we propose a 3D kinetic model (particle-in-cell, PIC) for the description of the large scale Earth’s bow shock. The proposed version is stable and does not require huge or extensive computer resources. Because PIC simulations work with scaled plasma and field parameters, we also propose to validate our code by comparing its results with the available MHD simulations under same scaled solar wind (SW) and (IMF) conditions. We report new results from the two models. In both codes the Earth’s bow shock position is found to be $\\approx 14.8 R_{{\\rm E}}$ along the Sun–Earth line, and $\\approx 29 R_{{\\rm E}}$ on the dusk side. Those findings are consistent with past in situ observations. Both simulations reproduce the theoretical jump conditions at the shock. However, the PIC code density and temperature distributions are inflated and slightly shifted sunward when compared to the MHD results. Kinetic electron motions and reflected ions upstream may cause this sunward shift. Species distributions in the foreshock region are depicted within the transition of the shock (measured $\\approx$2$c/\\omega_{pi}$ for $ \\Theta_{Bn}=90^{\\circ}$ and $M_{{\\rm MS}} = 4.7 $) and in the downstream. The size of the foot jump in the magnetic field at the shock is measured to be ($1.7 c/ \\omega_{pi} $). In the foreshocked region, the thermal velocity is found equal to 213 km $s^{−1}$ at $15R_{{\\rm E}}$ and is equal to $63 km s^{-1}$ at $12 R_{{\\rm E}}$ (magnetosheath region). Despite the large cell size of the current version of the PIC code, it is powerful to retain macrostructure of planets magnetospheres in very short time, thus it can be used for pedagogical test purposes. It is also likely complementary with MHD to deepen our understanding of the large scale magnetosphere.
Institute of Scientific and Technical Information of China (English)
CHENMou; JIANGChang-sheng; CHENWen-hua
2004-01-01
A new decentralized robust control method is discussed for a class of nonlinear interconnected largescale system with unknown bounded disturbance and unknown nonlinear function term. A decentralized control law is proposed which combines the approximation method of neural network with sliding mode control. The decentralized controller consists of an equivalent controller and an adaptive sliding mode controller. The sliding mode controller is a robust controller used to reduce the track error of the control system. The neural networks are used to approximate the unknown nonlinear functions, meanwhile the approximation errors of the neural networks are applied to the weight value updated law to improve performance of the system. Finally, an example demonstrates the availability of the decentralized control method.
Flap/Lag Stall Flutter Control of Large-Scale Wind Turbine Blade Based on Robust H2 Controller
Directory of Open Access Journals (Sweden)
Tingrui Liu
2016-01-01
Full Text Available Flap/lag stall nonlinear flutter and active control of anisotropic composite wind turbine blade modeled as antisymmetric beam analysis have been investigated based on robust H2 controller. The blade is modeled as single-cell thin-walled beam structure, exhibiting flap bending moment-lag transverse shear deformation, and lag bending moment-flap transverse shear deformation, with constant pitch angle set. The stall flutter control of dynamic response characteristics of composite blade incorporating nonlinear aerodynamic model is investigated based on some structural and dynamic parameters. The aeroelastic partial differential equations are reduced by Galerkin method, with the aerodynamic forces decomposed by strip theory. Robust H2 optimal controller is developed to enhance the vibrational behavior and dynamic response to aerodynamic excitation under extreme wind conditions and stabilize structures that might be damaged in the absence of control. The effectiveness of the control algorithm is demonstrated in both amplitudes and frequencies by description of time responses, extended phase planes, and frequency spectrum analysis, respectively.
Large Scale Earth's Bow Shock with Northern IMF as simulated by PIC code in parallel with MHD model
Baraka, Suleiman M
2016-01-01
In this paper, we propose a 3D kinetic model (Particle-in-Cell PIC ) for the description of the large scale Earth's bow shock. The proposed version is stable and does not require huge or extensive computer resources. Because PIC simulations work with scaled plasma and field parameters, we also propose to validate our code by comparing its results with the available MHD simulations under same scaled Solar wind ( SW ) and ( IMF ) conditions. We report new results from the two models. In both codes the Earth's bow shock position is found to be ~14.8 RE along the Sun-Earth line, and ~ 29 RE on the dusk side. Those findings are consistent with past in situ observations. Both simulations reproduce the theoretical jump conditions at the shock. However, the PIC code density and temperature distributions are inflated and slightly shifted sunward when compared to the MHD results. Kinetic electron motions and reflected ions upstream may cause this sunward shift. Species distributions in the foreshock region are depicted...
Directory of Open Access Journals (Sweden)
M. Ramírez
2015-04-01
Full Text Available In this paper, the effect of fuzzy logic-based robust power system stabilizers on the improvement of the dynamics of a large-scale power system is investigated. The study is particularly focused on the Mexican Interconnected System and on adding damping to two critical inter-area system oscillation modes: the north-south mode and the western-peninsular mode. The fuzzy power system stabilizers (FPSSs applied here are based on a significantly reduced rule base, small number of tuning parameters, and simple control algorithm and architecture, which makes their design and implementation easier and suitable for practical applications. Non-linear time-domain simulations for a set of test cases and results from Prony Analysis verify the robustness of the designed FPSSs, as compared to conventional PSSs.
Sayadi, Taraneh; Schmid, Peter J.
2016-10-01
Many fluid flows of engineering interest, though very complex in appearance, can be approximated by low-order models governed by a few modes, able to capture the dominant behavior (dynamics) of the system. This feature has fueled the development of various methodologies aimed at extracting dominant coherent structures from the flow. Some of the more general techniques are based on data-driven decompositions, most of which rely on performing a singular value decomposition (SVD) on a formulated snapshot (data) matrix. The amount of experimentally or numerically generated data expands as more detailed experimental measurements and increased computational resources become readily available. Consequently, the data matrix to be processed will consist of far more rows than columns, resulting in a so-called tall-and-skinny (TS) matrix. Ultimately, the SVD of such a TS data matrix can no longer be performed on a single processor, and parallel algorithms are necessary. The present study employs the parallel TSQR algorithm of (Demmel et al. in SIAM J Sci Comput 34(1):206-239, 2012), which is further used as a basis of the underlying parallel SVD. This algorithm is shown to scale well on machines with a large number of processors and, therefore, allows the decomposition of very large datasets. In addition, the simplicity of its implementation and the minimum required communication makes it suitable for integration in existing numerical solvers and data decomposition techniques. Examples that demonstrate the capabilities of highly parallel data decomposition algorithms include transitional processes in compressible boundary layers without and with induced flow separation.
Energy Technology Data Exchange (ETDEWEB)
Hasenkamp, Daren; Sim, Alexander; Wehner, Michael; Wu, Kesheng
2010-09-30
Extensive computing power has been used to tackle issues such as climate changes, fusion energy, and other pressing scientific challenges. These computations produce a tremendous amount of data; however, many of the data analysis programs currently only run a single processor. In this work, we explore the possibility of using the emerging cloud computing platform to parallelize such sequential data analysis tasks. As a proof of concept, we wrap a program for analyzing trends of tropical cyclones in a set of virtual machines (VMs). This approach allows the user to keep their familiar data analysis environment in the VMs, while we provide the coordination and data transfer services to ensure the necessary input and output are directed to the desired locations. This work extensively exercises the networking capability of the cloud computing systems and has revealed a number of weaknesses in the current cloud system software. In our tests, we are able to scale the parallel data analysis job to a modest number of VMs and achieve a speedup that is comparable to running the same analysis task using MPI. However, compared to MPI based parallelization, the cloud-based approach has a number of advantages. The cloud-based approach is more flexible because the VMs can capture arbitrary software dependencies without requiring the user to rewrite their programs. The cloud-based approach is also more resilient to failure; as long as a single VM is running, it can make progress while as soon as one MPI node fails the whole analysis job fails. In short, this initial work demonstrates that a cloud computing system is a viable platform for distributed scientific data analyses traditionally conducted on dedicated supercomputing systems.
Institute of Scientific and Technical Information of China (English)
Ting Lei; Zhenhan Yao; Haitao Wang; Pengbo Wang
2006-01-01
In this paper, an adaptive boundary element method (BEM) is presented for solving 3-D elasticity problems. The numerical scheme is accelerated by the new version of fast multipole method (FMM) and parallelized on distributed memory architectures. The resulting solver is applied to the study of representative volume element (RVE)for short fiberreinforced composites with complex inclusion geometry. Numerical examples performed on a 32-processor cluster show that the proposed method is both accurate and efficient. And can solve problems of large size that are challenging to existing state-of-the-art domain methods.
Wang, Yaping; Nie, Jingxin; Yap, Pew-Thian; Li, Gang; Shi, Feng; Geng, Xiujuan; Guo, Lei; Shen, Dinggang
2014-01-01
Accurate and robust brain extraction is a critical step in most neuroimaging analysis pipelines. In particular, for the large-scale multi-site neuroimaging studies involving a significant number of subjects with diverse age and diagnostic groups, accurate and robust extraction of the brain automatically and consistently is highly desirable. In this paper, we introduce population-specific probability maps to guide the brain extraction of diverse subject groups, including both healthy and diseased adult human populations, both developing and aging human populations, as well as non-human primates. Specifically, the proposed method combines an atlas-based approach, for coarse skull-stripping, with a deformable-surface-based approach that is guided by local intensity information and population-specific prior information learned from a set of real brain images for more localized refinement. Comprehensive quantitative evaluations were performed on the diverse large-scale populations of ADNI dataset with over 800 subjects (55∼90 years of age, multi-site, various diagnosis groups), OASIS dataset with over 400 subjects (18∼96 years of age, wide age range, various diagnosis groups), and NIH pediatrics dataset with 150 subjects (5∼18 years of age, multi-site, wide age range as a complementary age group to the adult dataset). The results demonstrate that our method consistently yields the best overall results across almost the entire human life span, with only a single set of parameters. To demonstrate its capability to work on non-human primates, the proposed method is further evaluated using a rhesus macaque dataset with 20 subjects. Quantitative comparisons with popularly used state-of-the-art methods, including BET, Two-pass BET, BET-B, BSE, HWA, ROBEX and AFNI, demonstrate that the proposed method performs favorably with superior performance on all testing datasets, indicating its robustness and effectiveness. PMID:24489639
Wang, Yaping; Nie, Jingxin; Yap, Pew-Thian; Li, Gang; Shi, Feng; Geng, Xiujuan; Guo, Lei; Shen, Dinggang
2014-01-01
Accurate and robust brain extraction is a critical step in most neuroimaging analysis pipelines. In particular, for the large-scale multi-site neuroimaging studies involving a significant number of subjects with diverse age and diagnostic groups, accurate and robust extraction of the brain automatically and consistently is highly desirable. In this paper, we introduce population-specific probability maps to guide the brain extraction of diverse subject groups, including both healthy and diseased adult human populations, both developing and aging human populations, as well as non-human primates. Specifically, the proposed method combines an atlas-based approach, for coarse skull-stripping, with a deformable-surface-based approach that is guided by local intensity information and population-specific prior information learned from a set of real brain images for more localized refinement. Comprehensive quantitative evaluations were performed on the diverse large-scale populations of ADNI dataset with over 800 subjects (55 ∼ 90 years of age, multi-site, various diagnosis groups), OASIS dataset with over 400 subjects (18 ∼ 96 years of age, wide age range, various diagnosis groups), and NIH pediatrics dataset with 150 subjects (5 ∼ 18 years of age, multi-site, wide age range as a complementary age group to the adult dataset). The results demonstrate that our method consistently yields the best overall results across almost the entire human life span, with only a single set of parameters. To demonstrate its capability to work on non-human primates, the proposed method is further evaluated using a rhesus macaque dataset with 20 subjects. Quantitative comparisons with popularly used state-of-the-art methods, including BET, Two-pass BET, BET-B, BSE, HWA, ROBEX and AFNI, demonstrate that the proposed method performs favorably with superior performance on all testing datasets, indicating its robustness and effectiveness.
Directory of Open Access Journals (Sweden)
Yaping Wang
Full Text Available Accurate and robust brain extraction is a critical step in most neuroimaging analysis pipelines. In particular, for the large-scale multi-site neuroimaging studies involving a significant number of subjects with diverse age and diagnostic groups, accurate and robust extraction of the brain automatically and consistently is highly desirable. In this paper, we introduce population-specific probability maps to guide the brain extraction of diverse subject groups, including both healthy and diseased adult human populations, both developing and aging human populations, as well as non-human primates. Specifically, the proposed method combines an atlas-based approach, for coarse skull-stripping, with a deformable-surface-based approach that is guided by local intensity information and population-specific prior information learned from a set of real brain images for more localized refinement. Comprehensive quantitative evaluations were performed on the diverse large-scale populations of ADNI dataset with over 800 subjects (55 ∼ 90 years of age, multi-site, various diagnosis groups, OASIS dataset with over 400 subjects (18 ∼ 96 years of age, wide age range, various diagnosis groups, and NIH pediatrics dataset with 150 subjects (5 ∼ 18 years of age, multi-site, wide age range as a complementary age group to the adult dataset. The results demonstrate that our method consistently yields the best overall results across almost the entire human life span, with only a single set of parameters. To demonstrate its capability to work on non-human primates, the proposed method is further evaluated using a rhesus macaque dataset with 20 subjects. Quantitative comparisons with popularly used state-of-the-art methods, including BET, Two-pass BET, BET-B, BSE, HWA, ROBEX and AFNI, demonstrate that the proposed method performs favorably with superior performance on all testing datasets, indicating its robustness and effectiveness.
Directory of Open Access Journals (Sweden)
Volzer Thomas
2016-12-01
Full Text Available The use of elastic bodies within a multibody simulation became more and more important within the last years. To include the elastic bodies, described as a finite element model in multibody simulations, the dimension of the system of ordinary differential equations must be reduced by projection. For this purpose, in this work, the modal reduction method, a component mode synthesis based method and a moment-matching method are used. Due to the always increasing size of the non-reduced systems, the calculation of the projection matrix leads to a large demand of computational resources and cannot be done on usual serial computers with available memory. In this paper, the model reduction software Morembs++ is presented using a parallelization concept based on the message passing interface to satisfy the need of memory and reduce the runtime of the model reduction process. Additionally, the behaviour of the Block-Krylov-Schur eigensolver, implemented in the Anasazi package of the Trilinos project, is analysed with regard to the choice of the size of the Krylov base, the block size and the number of blocks. Besides, an iterative solver is considered within the CMS-based method.
A Scalable O(N) Algorithm for Large-Scale Parallel First-Principles Molecular Dynamics Simulations
Energy Technology Data Exchange (ETDEWEB)
Osei-Kuffuor, Daniel [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Fattebert, Jean-Luc [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2014-01-01
Traditional algorithms for first-principles molecular dynamics (FPMD) simulations only gain a modest capability increase from current petascale computers, due to their O(N^{3}) complexity and their heavy use of global communications. To address this issue, we are developing a truly scalable O(N) complexity FPMD algorithm, based on density functional theory (DFT), which avoids global communications. The computational model uses a general nonorthogonal orbital formulation for the DFT energy functional, which requires knowledge of selected elements of the inverse of the associated overlap matrix. We present a scalable algorithm for approximately computing selected entries of the inverse of the overlap matrix, based on an approximate inverse technique, by inverting local blocks corresponding to principal submatrices of the global overlap matrix. The new FPMD algorithm exploits sparsity and uses nearest neighbor communication to provide a computational scheme capable of extreme scalability. Accuracy is controlled by the mesh spacing of the finite difference discretization, the size of the localization regions in which the electronic orbitals are confined, and a cutoff beyond which the entries of the overlap matrix can be omitted when computing selected entries of its inverse. We demonstrate the algorithm's excellent parallel scaling for up to O(100K) atoms on O(100K) processors, with a wall-clock time of O(1) minute per molecular dynamics time step.
Knecht, Stefan; Jensen, Hans Jorgen Aa; Fleig, Timo
2008-01-07
We present a parallel implementation of a string-driven general active space configuration interaction program for nonrelativistic and scalar-relativistic electronic-structure calculations. The code has been modularly incorporated in the DIRAC quantum chemistry program package. The implementation is based on the message passing interface and a distributed data model in order to efficiently exploit key features of various modern computer architectures. We exemplify the nearly linear scalability of our parallel code in large-scale multireference configuration interaction (MRCI) calculations, and we discuss the parallel speedup with respect to machine-dependent aspects. The largest sample MRCI calculation includes 1.5x10(9) Slater determinants. Using the new code we determine for the first time the full short-range electronic potentials and spectroscopic constants for the ground state and for eight low-lying excited states of the weakly bound molecular system (Rb-Ba)+ with the spin-orbit-free Dirac formalism and using extensive uncontracted basis sets. The time required to compute to full convergence these electronic states for (Rb-Ba)+ in a single-point MRCI calculation correlating 18 electrons and using 16 cores was reduced from more than 10 days to less than 1 day.
Wu, X.
2011-07-18
The NAS Parallel Benchmarks (NPB) are well-known applications with fixed algorithms for evaluating parallel systems and tools. Multicore clusters provide a natural programming paradigm for hybrid programs, whereby OpenMP can be used with the data sharing with the multicores that comprise a node, and MPI can be used with the communication between nodes. In this paper, we use Scalar Pentadiagonal (SP) and Block Tridiagonal (BT) benchmarks of MPI NPB 3.3 as a basis for a comparative approach to implement hybrid MPI/OpenMP versions of SP and BT. In particular, we can compare the performance of the hybrid SP and BT with the MPI counterparts on large-scale multicore clusters, Intrepid (BlueGene/P) at Argonne National Laboratory and Jaguar (Cray XT4/5) at Oak Ridge National Laboratory. Our performance results indicate that the hybrid SP outperforms the MPI SP by up to 20.76 %, and the hybrid BT outperforms the MPI BT by up to 8.58 % on up to 10 000 cores on Intrepid and Jaguar. We also use performance tools and MPI trace libraries available on these clusters to further investigate the performance characteristics of the hybrid SP and BT. © 2011 The Author. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.
Wu, Xingfu
2011-03-29
The NAS Parallel Benchmarks (NPB) are well-known applications with the fixed algorithms for evaluating parallel systems and tools. Multicore supercomputers provide a natural programming paradigm for hybrid programs, whereby OpenMP can be used with the data sharing with the multicores that comprise a node and MPI can be used with the communication between nodes. In this paper, we use SP and BT benchmarks of MPI NPB 3.3 as a basis for a comparative approach to implement hybrid MPI/OpenMP versions of SP and BT. In particular, we can compare the performance of the hybrid SP and BT with the MPI counterparts on large-scale multicore supercomputers. Our performance results indicate that the hybrid SP outperforms the MPI SP by up to 20.76%, and the hybrid BT outperforms the MPI BT by up to 8.58% on up to 10,000 cores on BlueGene/P at Argonne National Laboratory and Jaguar (Cray XT4/5) at Oak Ridge National Laboratory. We also use performance tools and MPI trace libraries available on these supercomputers to further investigate the performance characteristics of the hybrid SP and BT.
Katta, Mohan A. V. S. K.; Khan, Aamir W.; Doddamani, Dadakhalandar; Thudi, Mahendar; Varshney, Rajeev K.
2015-01-01
Rapid popularity and adaptation of next generation sequencing (NGS) approaches have generated huge volumes of data. High throughput platforms like Illumina HiSeq produce terabytes of raw data that requires quick processing. Quality control of the data is an important component prior to the downstream analyses. To address these issues, we have developed a quality control pipeline, NGS-QCbox that scales up to process hundreds or thousands of samples. Raspberry is an in-house tool, developed in C language utilizing HTSlib (v1.2.1) (http://htslib.org), for computing read/base level statistics. It can be used as stand-alone application and can process both compressed and uncompressed FASTQ format files. NGS-QCbox integrates Raspberry with other open-source tools for alignment (Bowtie2), SNP calling (SAMtools) and other utilities (bedtools) towards analyzing raw NGS data at higher efficiency and in high-throughput manner. The pipeline implements batch processing of jobs using Bpipe (https://github.com/ssadedin/bpipe) in parallel and internally, a fine grained task parallelization utilizing OpenMP. It reports read and base statistics along with genome coverage and variants in a user friendly format. The pipeline developed presents a simple menu driven interface and can be used in either quick or complete mode. In addition, the pipeline in quick mode outperforms in speed against other similar existing QC pipeline/tools. The NGS-QCbox pipeline, Raspberry tool and associated scripts are made available at the URL https://github.com/CEG-ICRISAT/NGS-QCbox and https://github.com/CEG-ICRISAT/Raspberry for rapid quality control analysis of large-scale next generation sequencing (Illumina) data. PMID:26460497
Katta, Mohan A V S K; Khan, Aamir W; Doddamani, Dadakhalandar; Thudi, Mahendar; Varshney, Rajeev K
2015-01-01
Rapid popularity and adaptation of next generation sequencing (NGS) approaches have generated huge volumes of data. High throughput platforms like Illumina HiSeq produce terabytes of raw data that requires quick processing. Quality control of the data is an important component prior to the downstream analyses. To address these issues, we have developed a quality control pipeline, NGS-QCbox that scales up to process hundreds or thousands of samples. Raspberry is an in-house tool, developed in C language utilizing HTSlib (v1.2.1) (http://htslib.org), for computing read/base level statistics. It can be used as stand-alone application and can process both compressed and uncompressed FASTQ format files. NGS-QCbox integrates Raspberry with other open-source tools for alignment (Bowtie2), SNP calling (SAMtools) and other utilities (bedtools) towards analyzing raw NGS data at higher efficiency and in high-throughput manner. The pipeline implements batch processing of jobs using Bpipe (https://github.com/ssadedin/bpipe) in parallel and internally, a fine grained task parallelization utilizing OpenMP. It reports read and base statistics along with genome coverage and variants in a user friendly format. The pipeline developed presents a simple menu driven interface and can be used in either quick or complete mode. In addition, the pipeline in quick mode outperforms in speed against other similar existing QC pipeline/tools. The NGS-QCbox pipeline, Raspberry tool and associated scripts are made available at the URL https://github.com/CEG-ICRISAT/NGS-QCbox and https://github.com/CEG-ICRISAT/Raspberry for rapid quality control analysis of large-scale next generation sequencing (Illumina) data.
Directory of Open Access Journals (Sweden)
Mohan A V S K Katta
Full Text Available Rapid popularity and adaptation of next generation sequencing (NGS approaches have generated huge volumes of data. High throughput platforms like Illumina HiSeq produce terabytes of raw data that requires quick processing. Quality control of the data is an important component prior to the downstream analyses. To address these issues, we have developed a quality control pipeline, NGS-QCbox that scales up to process hundreds or thousands of samples. Raspberry is an in-house tool, developed in C language utilizing HTSlib (v1.2.1 (http://htslib.org, for computing read/base level statistics. It can be used as stand-alone application and can process both compressed and uncompressed FASTQ format files. NGS-QCbox integrates Raspberry with other open-source tools for alignment (Bowtie2, SNP calling (SAMtools and other utilities (bedtools towards analyzing raw NGS data at higher efficiency and in high-throughput manner. The pipeline implements batch processing of jobs using Bpipe (https://github.com/ssadedin/bpipe in parallel and internally, a fine grained task parallelization utilizing OpenMP. It reports read and base statistics along with genome coverage and variants in a user friendly format. The pipeline developed presents a simple menu driven interface and can be used in either quick or complete mode. In addition, the pipeline in quick mode outperforms in speed against other similar existing QC pipeline/tools. The NGS-QCbox pipeline, Raspberry tool and associated scripts are made available at the URL https://github.com/CEG-ICRISAT/NGS-QCbox and https://github.com/CEG-ICRISAT/Raspberry for rapid quality control analysis of large-scale next generation sequencing (Illumina data.
Robust control of a parallel hybrid drivetrain with a CVT
Energy Technology Data Exchange (ETDEWEB)
Mayer, T.; Schroeder, D. [Technical Univ. of Munich (Germany)
1996-09-01
In this paper the design of a robust control system for a parallel hybrid drivetrain is presented. The drivetrain is based on a continuously variable transmission (CVT) and is therefore a highly nonlinear multiple-input-multiple-output system (MIMO-System). Input-Output-Linearization offers the possibility of linearizing and of decoupling the system. Since for example the vehicle mass varies with the load and the efficiency of the gearbox depends strongly on the actual working point, an exact linearization of the plant will mostly fail. Therefore a robust control algorithm based on sliding mode is used to control the drivetrain.
Huang, Yi-Shao; Liu, Wel-Ping; Wu, Min; Wang, Zheng-Wu
2014-09-01
This paper presents a novel observer-based decentralized hybrid adaptive fuzzy control scheme for a class of large-scale continuous-time multiple-input multiple-output (MIMO) uncertain nonlinear systems whose state variables are unmeasurable. The scheme integrates fuzzy logic systems, state observers, and strictly positive real conditions to deal with three issues in the control of a large-scale MIMO uncertain nonlinear system: algorithm design, controller singularity, and transient response. Then, the design of the hybrid adaptive fuzzy controller is extended to address a general large-scale uncertain nonlinear system. It is shown that the resultant closed-loop large-scale system keeps asymptotically stable and the tracking error converges to zero. The better characteristics of our scheme are demonstrated by simulations. Copyright © 2014. Published by Elsevier Ltd.
JASMIN-based Massive Parallel Computing of Large Scale Groundwater Flow%基于JASMIN的地下水流大规模并行数值模拟
Institute of Scientific and Technical Information of China (English)
程汤培; 莫则尧; 邵景力
2013-01-01
针对具有精细网格剖分、长时间跨度特征的地下水流模拟中计算时间长、存储开销大等瓶颈问题,基于MODFLOW三维非稳定流计算方法,提出基于网格片的核心算法以及基于影像区的通信机制,并在JASMIN框架上研制了大规模地下水流并行数值模拟程序JOGFLOW.通过河南郑州市中牟县雁鸣湖水源地地下水流的模拟,对程序正确性和性能进行了验证；通过建立一个具有精细网格剖分的假想地下水概念模型对可扩展性进行测试.相对于32核的并行程序,在512以及1024个处理机上的并行效率分别可达77.2％和67.5％.数值模拟结果表明,JOGFLOW具有较好的计算性能与可扩展性,能够有效使用数百上千计算核心,支持千万量级以上网格剖分的地下水流模型的大规模并行计算.%To overcome prohibitive cost in computational time and memory requirement in simulating groundwater flow models with detailed spatial discretization and long time period,we present an efficient massive parallel-computing program JOGFLOW for large scale groundwater flow simulation.In the program,groundwater flow process in MODFLOW is re-implemented on JASMIN by designing patch-based algorithms as well as using communication method based on adding ghost cells to each patch.Accuracy and efficiency of JOGFLOW are demonstrated in modeling a field flow located at Yanming Lake in Zhengzhou of Henan province.Parallel scalability is measured by simulating a hypothetic groundwater flow problem with much detailed spatial discretization.Compared to 32 cores,the parallel efficiency reaches 77.2％ and 67.5％ on 512 and 1 024 processors,respectively.Numerical modeling demonstrates good performance and scalability of JOGFLOW,which enables to support groundwater flow simulation with tens of millions of computational cells through massive parallel computing on hundreds or thousands of CPU cores.
M. Genseberger (Menno)
2008-01-01
htmlabstractMost computational work in Jacobi-Davidson [9], an iterative method for large scale eigenvalue problems, is due to a so-called correction equation. In [5] a strategy for the approximate solution of the correction equation was proposed. This strategy is based on a domain decomposition
Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time
Directory of Open Access Journals (Sweden)
Hongtao Hu
2016-01-01
Full Text Available A parallel machine scheduling problem in plastic production is studied in this paper. In this problem, the processing time and arrival time are uncertain but lie in their respective intervals. In addition, each job must be processed together with a mold while jobs which belong to one family can share the same mold. Therefore, time changing mold is required for two consecutive jobs that belong to different families, which is known as sequence-dependent setup time. This paper aims to identify a robust schedule by min–max regret criterion. It is proved that the scenario incurring maximal regret for each feasible solution lies in finite extreme scenarios. A mixed integer linear programming formulation and an exact algorithm are proposed to solve the problem. Moreover, a modified artificial bee colony algorithm is developed to solve large-scale problems. The performance of the presented algorithm is evaluated through extensive computational experiments and the results show that the proposed algorithm surpasses the exact method in terms of objective value and computational time.
DEFF Research Database (Denmark)
Bache, Anja Margrethe
2010-01-01
WORLD FAMOUS ARCHITECTS CHALLENGE TODAY THE EXPOSURE OF CONCRETE IN THEIR ARCHITECTURE. IT IS MY HOPE TO BE ABLE TO COMPLEMENT THESE. I TRY TO DEVELOP NEW AESTHETIC POTENTIALS FOR THE CONCRETE AND CERAMICS, IN LARGE SCALES THAT HAS NOT BEEN SEEN BEFORE IN THE CERAMIC AREA. IT IS EXPECTED TO RESULT...
Chen, Mingyang; Stott, Amanda C; Li, Shenggang; Dixon, David A
2012-04-01
A robust metadata database called the Collaborative Chemistry Database Tool (CCDBT) for massive amounts of computational chemistry raw data has been designed and implemented. It performs data synchronization and simultaneously extracts the metadata. Computational chemistry data in various formats from different computing sources, software packages, and users can be parsed into uniform metadata for storage in a MySQL database. Parsing is performed by a parsing pyramid, including parsers written for different levels of data types and sets created by the parser loader after loading parser engines and configurations.
Cache-style Parallel Checkpointing for Large-scale Computing System%面向大规模计算系统的Cache式并行检查点
Institute of Scientific and Technical Information of China (English)
刘勇燕; 刘勇鹏; 冯华; 迟万庆
2011-01-01
Checkpointing is a typical technique for fault tolerance, whereas its scalability is limited by the overhead of file access. According to the multi-level file system architecture, the cache-style parallel checkpointing was introduced,which translates global coordinated checkpointing into local file operation by out-of-order pipelining of checkpoint flushing opportunity. The overhead of write-back is hidden effectively to increase the performance and the scalability of parallel checkpointing.%检查点机制是高性能并行计算系统中重要的容错手段,随着系统规模的增大,并行检查点的可扩展性受文件访问的制约.针对大规模并行计算系统的多级文件系统结构,提出了cache式并行检查点技术.它将全局同步并行检查点转化为局部文件操作,并利用多处理器结构进行乱序流水线式写回调度,将检查点的写回时机合理分布,从而有效地隐藏了检查点的写回开销,保证了并行检查点文件访问的高性能和高可扩展性.
一种基于PETSc的热传导方程大规模并行求解策略%Parallel-computing Strategy for Large-scale Heat Equation Based on PETSc
Institute of Scientific and Technical Information of China (English)
程汤培; 王群
2009-01-01
提出了一种大规模热传导方程并行求解的策略,采用了分布式内存和压缩矩阵技术解决超大规模稀疏矩阵的存储及其计算,整合了多种Krylov子空间方法和预条件子技术来并行求解大规模线性方程组,基于面向对象设计实现了具体应用与算法的低耦合.在Linux机群系统上进行了性能测试,程序具有良好的加速比和计算性能.%A parallel-computing strategy was presented to solve the large-scale heat equations.The distributed memory and compressed matrices technology was adopted for both the process of storage and evaluation of large-scale sparse matrices.All kinds of Krylov subspace methods and preconditioners were introduced to assemble and solve the linear systems of equations.The code implementation of this strategy was written in high-level abstractions based on object-o-riented technology which promotes code reuse, flexibility and helps to decouple issues of parallelism from algorithm choices.The experiments carried on Linux clusters demonstrate that this strategy has achieved desirable speedup and ef-ficiency.
In the fast lane: large-scale bacterial genome engineering.
Fehér, Tamás; Burland, Valerie; Pósfai, György
2012-07-31
The last few years have witnessed rapid progress in bacterial genome engineering. The long-established, standard ways of DNA synthesis, modification, transfer into living cells, and incorporation into genomes have given way to more effective, large-scale, robust genome modification protocols. Expansion of these engineering capabilities is due to several factors. Key advances include: (i) progress in oligonucleotide synthesis and in vitro and in vivo assembly methods, (ii) optimization of recombineering techniques, (iii) introduction of parallel, large-scale, combinatorial, and automated genome modification procedures, and (iv) rapid identification of the modifications by barcode-based analysis and sequencing. Combination of the brute force of these techniques with sophisticated bioinformatic design and modeling opens up new avenues for the analysis of gene functions and cellular network interactions, but also in engineering more effective producer strains. This review presents a summary of recent technological advances in bacterial genome engineering.
Energy Technology Data Exchange (ETDEWEB)
Ali, Ghafar; Yoo, Seung Hwa; Kum, Jong Min; Kim, Yong Nam; Cho, Sung Oh [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology (KAIST), 373-1 Guseong, Yuseong, Daejeon 305-701 (Korea, Republic of)
2011-06-17
We present a novel and straightforward approach to fabricate large-scale and robust free-standing TiO{sub 2} nanotube (TNT) membranes. Simply by blowing N{sub 2} gas onto as-anodized TNTs that are wetted with methanol, free-standing TNT membranes are produced. The approach also provides homogeneous and honeycomb-like Ti substrates after the detachment of TNT membranes. Through the second anodization of the honeycomb-like Ti substrates following the N{sub 2} blowing, TNT membranes comprising hexagonally close-packed and regularly ordered TNTs with clear open ends can be achieved. Characterization of the free-standing TNT membranes using Raman spectroscopy and a high-resolution transmission electron microscope reveals that anatase TiO{sub 2} and crystalline graphitic carbon are embedded in the bottom surface of the free-standing TNT membranes.
DEFF Research Database (Denmark)
Heller, Alfred
2001-01-01
The main objective of the research was to evaluate large-scale solar heating connected to district heating (CSDHP), to build up a simulation tool and to demonstrate the application of the simulation tool for design studies and on a local energy planning case. The evaluation was mainly carried out...... model is designed and validated on the Marstal case. Applying the Danish Reference Year, a design tool is presented. The simulation tool is used for proposals for application of alternative designs, including high-performance solar collector types (trough solar collectors, vaccum pipe collectors......). Simulation programs are proposed as control supporting tool for daily operation and performance prediction of central solar heating plants. Finaly the CSHP technolgy is put into persepctive with respect to alternatives and a short discussion on the barries and breakthrough of the technology are given....
Institute of Scientific and Technical Information of China (English)
江树刚; 张玉; 赵勋旺
2015-01-01
基于我国超级计算机平台,开展了大规模并行时域有限差分法(Finite-Difference Time-Domain FDTD)的性能和应用研究.在我国首台百万亿次"魔方"超级计算机、具有国产CPU的"神威蓝光"超级计算机和当前排名世界第一的"天河二号"超级计算机上就并行FDTD方法的并行性能进行了测试,并分别突破了10000 CPU核,100000 CPU核和300000 CPU核的并行规模.在不同测试规模下,该算法的并行效率均达到了50%以上,表明了本文并行算法具有良好的可扩展性.通过仿真分析多个微带天线阵的辐射特性和某大型飞机的散射特性,表明本文方法可以在不同架构的超级计算机上对复杂电磁问题进行精确高效电磁仿真.%The study of performance and applications of the large-scale parallel Finite-Difference Time-Domain (FDTD) method is carried out on the China-made supercomputer platforms. The parallel efficiency is tested on Magic Cube supercomputer that ranked the 10th fastest supercomputer in the world in Nov. 2008, Sunway BlueLight MPP supercomputer that is the first large scale parallel supercomputer with China-own-made CPUs, and Tianhe-2 supercomputer that ranked the 1st in the world currently, and the algorithm is implemented on the three supercomputers using maximum number of CPU cores of 10000, 100000 and 300000, respectively. The parallel efficiency reaches up to 50%, which indicates a good scalability of the method in this paper. Multiple microstrip antenna arrays and a large airplane are computed to demonstrate that the parallel FDTD can be applied for accurate and efficient simulation of complicated electromagnetic problems on supercomputer with different architectures.
Large Scale Metal Additive Techniques Review
Energy Technology Data Exchange (ETDEWEB)
Nycz, Andrzej [ORNL; Adediran, Adeola I [ORNL; Noakes, Mark W [ORNL; Love, Lonnie J [ORNL
2016-01-01
In recent years additive manufacturing made long strides toward becoming a main stream production technology. Particularly strong progress has been made in large-scale polymer deposition. However, large scale metal additive has not yet reached parity with large scale polymer. This paper is a review study of the metal additive techniques in the context of building large structures. Current commercial devices are capable of printing metal parts on the order of several cubic feet compared to hundreds of cubic feet for the polymer side. In order to follow the polymer progress path several factors are considered: potential to scale, economy, environment friendliness, material properties, feedstock availability, robustness of the process, quality and accuracy, potential for defects, and post processing as well as potential applications. This paper focuses on current state of art of large scale metal additive technology with a focus on expanding the geometric limits.
Large scale tracking algorithms
Energy Technology Data Exchange (ETDEWEB)
Hansen, Ross L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Love, Joshua Alan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Melgaard, David Kennett [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Karelitz, David B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pitts, Todd Alan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Zollweg, Joshua David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Anderson, Dylan Z. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Nandy, Prabal [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Whitlow, Gary L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bender, Daniel A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Byrne, Raymond Harry [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-01-01
Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For higher resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.
Large scale tracking algorithms.
Energy Technology Data Exchange (ETDEWEB)
Hansen, Ross L.; Love, Joshua Alan; Melgaard, David Kennett; Karelitz, David B.; Pitts, Todd Alan; Zollweg, Joshua David; Anderson, Dylan Z.; Nandy, Prabal; Whitlow, Gary L.; Bender, Daniel A.; Byrne, Raymond Harry
2015-01-01
Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For higher resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.
Large scale parallel document image processing
van der Zant, Tijn; Schomaker, Lambert; Valentijn, Edwin; Yanikoglu, BA; Berkner, K
2008-01-01
Building a system which allows to search a very large database of document images. requires professionalization of hardware and software, e-science and web access. In astrophysics there is ample experience dealing with large data sets due to an increasing number of measurement instruments. The probl
Large scale parallel document image processing
van der Zant, Tijn; Schomaker, Lambert; Valentijn, Edwin; Yanikoglu, BA; Berkner, K
2008-01-01
Building a system which allows to search a very large database of document images. requires professionalization of hardware and software, e-science and web access. In astrophysics there is ample experience dealing with large data sets due to an increasing number of measurement instruments. The
ELASTIC: A Large Scale Dynamic Tuning Environment
Directory of Open Access Journals (Sweden)
Andrea Martínez
2014-01-01
Full Text Available The spectacular growth in the number of cores in current supercomputers poses design challenges for the development of performance analysis and tuning tools. To be effective, such analysis and tuning tools must be scalable and be able to manage the dynamic behaviour of parallel applications. In this work, we present ELASTIC, an environment for dynamic tuning of large-scale parallel applications. To be scalable, the architecture of ELASTIC takes the form of a hierarchical tuning network of nodes that perform a distributed analysis and tuning process. Moreover, the tuning network topology can be configured to adapt itself to the size of the parallel application. To guide the dynamic tuning process, ELASTIC supports a plugin architecture. These plugins, called ELASTIC packages, allow the integration of different tuning strategies into ELASTIC. We also present experimental tests conducted using ELASTIC, showing its effectiveness to improve the performance of large-scale parallel applications.
Robust Visual Control of Parallel Robots under Uncertain Camera Orientation
Directory of Open Access Journals (Sweden)
Miguel A. Trujano
2012-10-01
Full Text Available This work presents a stability analysis and experimental assessment of a visual control algorithm applied to a redundant planar parallel robot under uncertainty in relation to camera orientation. The key feature of the analysis is a strict Lyapunov function that allows the conclusion of asymptotic stability without invoking the Barbashin-Krassovsky-LaSalle invariance theorem. The controller does not rely on velocity measurements and has a structure similar to a classic Proportional Derivative control algorithm. Experiments in a laboratory prototype show that uncertainty in camera orientation does not significantly degrade closed-loop performance.
Institute of Scientific and Technical Information of China (English)
王海兵
2011-01-01
通过重载MPI消息传递函数,在重载的MPI函数中调用MPE库中各日志记录函数,实现了大规模面向对象有限元程序自定义并行性能监测.对一个典型冲击动力学问题进行了16 CPU的并行有限元模拟,通过并行性能监测对其有限元并行算法进行了分析.%MPI functions in the large-scale object-oriented finite element software were overloaded to cany out user defined parallel performance profiling. Log functions in Multi-Processing Environment (MPE) library were inserted to MPI functions when the MPI functions were overloaded. A typical impact simulation has been carried out using 16 CPUs, and the simulation process was monitored. Parallel finite element algorithm which was used in the simulation has been evaluated by analyzing the monitor results.
CX: A Scalable, Robust Network for Parallel Computing
Directory of Open Access Journals (Sweden)
Peter Cappello
2002-01-01
Full Text Available CX, a network-based computational exchange, is presented. The system's design integrates variations of ideas from other researchers, such as work stealing, non-blocking tasks, eager scheduling, and space-based coordination. The object-oriented API is simple, compact, and cleanly separates application logic from the logic that supports interprocess communication and fault tolerance. Computations, of course, run to completion in the presence of computational hosts that join and leave the ongoing computation. Such hosts, or producers, use task caching and prefetching to overlap computation with interprocessor communication. To break a potential task server bottleneck, a network of task servers is presented. Even though task servers are envisioned as reliable, the self-organizing, scalable network of n- servers, described as a sibling-connected height-balanced fat tree, tolerates a sequence of n-1 server failures. Tasks are distributed throughout the server network via a simple "diffusion" process. CX is intended as a test bed for research on automated silent auctions, reputation services, authentication services, and bonding services. CX also provides a test bed for algorithm research into network-based parallel computation.
An Efficient and Robust Metacrawler with Parallel Activities
Directory of Open Access Journals (Sweden)
Vimal Bibhu
2010-05-01
Full Text Available This paper presents the Metacrawler, a fielded Web service that represents the next level up in the information ``food chain.'' The Metacrawler provides a single, central interface for Web document searching. Upon receiving a query, the Metacrawler posts the query to multiple search services in parallel, collates the returned references, and loads those references to verify their existence and to ensure that they contain relevant information. The Metacrawler is sufficiently lightweight to reside on a user's machine, which facilitates customization, privacy, sophisticated filtering of references, and more. Standard Web search services, though useful, are far from ideal. There are over a dozen of different search services currently in existence, each with a unique interface and adatabase covering a different portion of the Web. As a result, users are forced to repeatedly try and retry their queries across different services. Furthermore, the services return many responses that are irrelevant, outdated, or unavailable, forcing the user to manually sift through the responses searching for useful information.
Directory of Open Access Journals (Sweden)
Steinhaus Thomas
2007-01-01
Full Text Available A review of research into the burning behavior of large pool fires and fuel spill fires is presented. The features which distinguish such fires from smaller pool fires are mainly associated with the fire dynamics at low source Froude numbers and the radiative interaction with the fire source. In hydrocarbon fires, higher soot levels at increased diameters result in radiation blockage effects around the perimeter of large fire plumes; this yields lower emissive powers and a drastic reduction in the radiative loss fraction; whilst there are simplifying factors with these phenomena, arising from the fact that soot yield can saturate, there are other complications deriving from the intermittency of the behavior, with luminous regions of efficient combustion appearing randomly in the outer surface of the fire according the turbulent fluctuations in the fire plume. Knowledge of the fluid flow instabilities, which lead to the formation of large eddies, is also key to understanding the behavior of large-scale fires. Here modeling tools can be effectively exploited in order to investigate the fluid flow phenomena, including RANS- and LES-based computational fluid dynamics codes. The latter are well-suited to representation of the turbulent motions, but a number of challenges remain with their practical application. Massively-parallel computational resources are likely to be necessary in order to be able to adequately address the complex coupled phenomena to the level of detail that is necessary.
Gkoulalas-Divanis, Aris
2014-01-01
Provides cutting-edge research in large-scale data analytics from diverse scientific areas Surveys varied subject areas and reports on individual results of research in the field Shares many tips and insights into large-scale data analytics from authors and editors with long-term experience and specialization in the field
Institute of Scientific and Technical Information of China (English)
Chunqing HUANG; Lisang LIU; Xinggui WANG; Songjiao SHI
2007-01-01
A simple robust scheme of parallel force/position control is proposed in this paper to deal with two problems for non-planar constraint surface and nonlinear mechanical feature of environment: i) uncertainties in environment that are usually not available or difficult to be determined in most practical situations; ii) stability problem or/and integrator windup due to the integration of force error in the force dominance rule in parallel force/position control. It shows that this robust scheme is a good alternative for anti-windup. In the presence of environment uncertainties, global asymptotic stability of the resulting closed-loop system is guaranteed; it also shows robustness of the proposed controller to uncertain environment with complex characteristics. Finally, numerical simulation verifies results via contact task of a two rigid-links robot manipulator.
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
This paper presents a pressure observer based adaptive robust controller (POARC) for posture trajectory tracking of a parallel manipulator driven by three pneumatic muscles without pressure sensors. Due to model errors of the static forces and friction forces of pneumatic muscles, simplified average flow rate characteristics of valves, unknown disturbances of entire system,and unmeasured pressures, there exist rather severe parametric uncertainties, nonlinear uncertainties and dynamic uncertainties in modeling of the parallel manipulator. A nonlinear pressure observer is constructed to estimate unknown pressures on the basis of a single-input-single-output (SISO) decoupling model that is simplified from the actual multiple-input-multiple-output (MIMO)coupling model of the parallel manipulator. Then, an adaptive robust controller integrated with the pressure observer is developed to accomplish high precision posture trajectory tracking of the parallel manipulator. The experimental results indicate that the system with the proposed POARC not only achieves good control accuracy and smooth movement but also maintains robustness to disturbances.
Vishniac, Ethan T.
2015-01-01
We show that a differentially rotating conducting fluid automatically creates a magnetic helicity flux with components along the rotation axis and in the direction of the local vorticity. This drives a rapid growth in the local density of current helicity, which in turn drives a large scale dynamo. The dynamo growth rate derived from this process is not constant, but depends inversely on the large scale magnetic field strength. This dynamo saturates when buoyant losses of magnetic flux compete with the large scale dynamo, providing a simple prediction for magnetic field strength as a function of Rossby number in stars. Increasing anisotropy in the turbulence produces a decreasing magnetic helicity flux, which explains the flattening of the B/Rossby number relation at low Rossby numbers. We also show that the kinetic helicity is always a subdominant effect. There is no kinematic dynamo in real stars.
Large-scale circuit simulation
Wei, Y. P.
1982-12-01
The simulation of VLSI (Very Large Scale Integration) circuits falls beyond the capabilities of conventional circuit simulators like SPICE. On the other hand, conventional logic simulators can only give the results of logic levels 1 and 0 with the attendent loss of detail in the waveforms. The aim of developing large-scale circuit simulation is to bridge the gap between conventional circuit simulation and logic simulation. This research is to investigate new approaches for fast and relatively accurate time-domain simulation of MOS (Metal Oxide Semiconductors), LSI (Large Scale Integration) and VLSI circuits. New techniques and new algorithms are studied in the following areas: (1) analysis sequencing (2) nonlinear iteration (3) modified Gauss-Seidel method (4) latency criteria and timestep control scheme. The developed methods have been implemented into a simulation program PREMOS which could be used as a design verification tool for MOS circuits.
Robust Parallel Motion Estimation and Mapping with Stereo Cameras in Underground Infrastructure
Liu, Chun; Li, Zhengning; Zhou, Yuan
2016-06-01
Presently, we developed a novel robust motion estimation method for localization and mapping in underground infrastructure using a pre-calibrated rigid stereo camera rig. Localization and mapping in underground infrastructure is important to safety. Yet it's also nontrivial since most underground infrastructures have poor lighting condition and featureless structure. Overcoming these difficulties, we discovered that parallel system is more efficient than the EKF-based SLAM approach since parallel system divides motion estimation and 3D mapping tasks into separate threads, eliminating data-association problem which is quite an issue in SLAM. Moreover, the motion estimation thread takes the advantage of state-of-art robust visual odometry algorithm which is highly functional under low illumination and provides accurate pose information. We designed and built an unmanned vehicle and used the vehicle to collect a dataset in an underground garage. The parallel system was evaluated by the actual dataset. Motion estimation results indicated a relative position error of 0.3%, and 3D mapping results showed a mean position error of 13cm. Off-line process reduced position error to 2cm. Performance evaluation by actual dataset showed that our system is capable of robust motion estimation and accurate 3D mapping in poor illumination and featureless underground environment.
ROBUST PARALLEL MOTION ESTIMATION AND MAPPING WITH STEREO CAMERAS IN UNDERGROUND INFRASTRUCTURE
Directory of Open Access Journals (Sweden)
C. Liu
2016-06-01
Full Text Available Presently, we developed a novel robust motion estimation method for localization and mapping in underground infrastructure using a pre-calibrated rigid stereo camera rig. Localization and mapping in underground infrastructure is important to safety. Yet it’s also nontrivial since most underground infrastructures have poor lighting condition and featureless structure. Overcoming these difficulties, we discovered that parallel system is more efficient than the EKF-based SLAM approach since parallel system divides motion estimation and 3D mapping tasks into separate threads, eliminating data-association problem which is quite an issue in SLAM. Moreover, the motion estimation thread takes the advantage of state-of-art robust visual odometry algorithm which is highly functional under low illumination and provides accurate pose information. We designed and built an unmanned vehicle and used the vehicle to collect a dataset in an underground garage. The parallel system was evaluated by the actual dataset. Motion estimation results indicated a relative position error of 0.3%, and 3D mapping results showed a mean position error of 13cm. Off-line process reduced position error to 2cm. Performance evaluation by actual dataset showed that our system is capable of robust motion estimation and accurate 3D mapping in poor illumination and featureless underground environment.
Robust gain-scheduling for smart-structures in parallel robots
Algermissen, Stephan; Rose, Michael; Keimer, Ralf; Sinapius, Michael
2009-03-01
In the past years parallel robots demonstrated their capability in applications with high-dynamic trajectories. Smart-structures offer the potential to further increase the productivity of parallel robots by reducing disturbing vibrations caused by high dynamic loads effectively. To investigate parallel robots and their applications, including suitable control concepts for smart-structures, the Collaborative Research Center 562 was founded by the German Research Council (DFG). The latest prototype within this research center is called Triglide. It is a four degree of freedom (DOF) robot with three translational and one rotational DOF. It realizes an acceleration of 10 g* at the effector. In the structure of the robot six active rods and a tri-axial accelerometer are integrated to control effector vibrations in three translational DOF. The main challenge of this control application is the position dependent vibration behavior. A single robust controller is not able to gain satisfying performance within the entire workspace. Therefore a strategy for describing the vibration behavior by linearization at several operating points is developed. Behavior in-between is approximated by a linear approach. On a trajectory robust controllers in all operating points are smoothly switched by robust gain-scheduling. The scheduling parameters are fast varying and though a suitable stability proof is defined, based on Small-Gain approach. Several transformations enhance the results from Small-Gain Theorem and reduce the usual conservatism. Experimental data is used to show the improvements made.
Very Large Scale Integration (VLSI).
Yeaman, Andrew R. J.
Very Large Scale Integration (VLSI), the state-of-the-art production techniques for computer chips, promises such powerful, inexpensive computing that, in the future, people will be able to communicate with computer devices in natural language or even speech. However, before full-scale VLSI implementation can occur, certain salient factors must be…
Institute of Scientific and Technical Information of China (English)
王皞; 徐东生; 杨锐
2013-01-01
界面对钛合金的力学性能有至关重要的影响。界面行为的原子模拟涉及的原子数目庞大，必须借助大规模并行计算。本研究组开发了大规模并行分子动力学程序，并将其应用于钛合金中不同种类界面行为的模拟研究。本文以钛铝金属间化合物中的孪晶界和α钛中的特殊大角晶界为例，介绍研究组在钛合金晶界行为的计算模拟方面的近期研究成果。所模拟的体系尺寸达到微米级，所需 CPU 核数几十至几百不等。研究发现，钛铝模拟晶胞沿伪孪晶方向剪切变形时，等静压力下可产生 L11结构的伪孪晶形核长大，而等静张力下剪切可产生真孪晶的形核长大，提出钛铝中一种新的孪晶长大机制。在α钛中，特定取向的两个晶粒所形成的晶界与位错发生相互作用，裂纹形核依赖于加载外力的取向而发生在晶界处或硬取向晶粒内，从而可能导致疲劳断裂行为与加载取向相关。这些结果有助于理解钛合金的塑性变形行为，并为更高尺度的模拟研究提供了原子尺度细节。%The mechanical behavior of titanium alloys is often inlfuenced signiifcantly by interfaces. The atomistic investigation of interfaces corresponds with large numbers of atoms, hence requiring large-scale parallel simulations. A molecular dynamics code for such simulations is developed in our group, and used in the investigations of interfacial behaviors in titanium alloys. The present paper introduces our recent works on the simulations of interfacial behaviors in titanium alloys, with the coherent twin boundary in TiAl and a special large-angle grain boundary inα-titanium as two examples. The size of the simulated cells is around micrometers, using tens to hundreds of CPU cores. It is found that, in TiAl under shear along the pseudo-twin direction, pseudo-twin and true twin nucleates and grows under hydrostatic compression and tension respectively
Energy Technology Data Exchange (ETDEWEB)
Tolonen, J.; Konttinen, P.; Lund, P. [Helsinki Univ. of Technology, Otaniemi (Finland). Dept. of Engineering Physics and Mathematics
1998-12-31
In this project a large domestic solar heating system was built and a solar district heating system was modelled and simulated. Objectives were to improve the performance and reduce costs of a large-scale solar heating system. As a result of the project the benefit/cost ratio can be increased by 40 % through dimensioning and optimising the system at the designing stage. (orig.)
Testing gravity on Large Scales
Raccanelli Alvise
2013-01-01
We show how it is possible to test general relativity and different models of gravity via Redshift-Space Distortions using forthcoming cosmological galaxy surveys. However, the theoretical models currently used to interpret the data often rely on simplifications that make them not accurate enough for precise measurements. We will discuss improvements to the theoretical modeling at very large scales, including wide-angle and general relativistic corrections; we then show that for wide and deep...
Cross-coupling integral adaptive robust posture control of a pneumatic parallel platform
Institute of Scientific and Technical Information of China (English)
左赫; 陶国良
2016-01-01
A pneumatic parallel platform driven by an air cylinder and three circumambient pneumatic muscles was considered. Firstly, a mathematical model of the pneumatic servo system was developed for the MIMO nonlinear model-based controller designed. The pneumatic muscles were controlled by three proportional position valves, and the air cylinder was controlled by a proportional pressure valve. As the forward kinematics of this structure had no analytical solution, the control strategy should be designed in joint space. A cross-coupling integral adaptive robust controller (CCIARC) which combined cross-coupling control strategy and traditional adaptive robust control (ARC) theory was developed by back-stepping method to accomplish trajectory tracking control of the parallel platform. The cross-coupling part of the controller stabilized the length error in joint space as well as the synchronization error, and the adaptive robust control part attenuated the adverse effects of modelling error and disturbance. The force character of the pneumatic muscles was difficult to model precisely, so the on-line recursive least square estimation (RLSE) method was employed to modify the model compensation. The projector mapping method was used to condition the RLSE algorithm to bound the parameters estimated. An integral feedback part was added to the traditional robust function to reduce the negative influence of the slow time-varying characteristic of pneumatic muscles and enhance the ability of trajectory tracking. The stability of the controller designed was proved through Laypunov’s theory. Various contrast controllers were designed to testify the newly designed components of the CCIARC. Extensive experiments were conducted to illustrate the performance of the controller.
Balancing modern Power System with large scale of wind power
Basit, Abdul; Altin, Müfit; Hansen, Anca Daniela; Sørensen, Poul Ejnar
2014-01-01
Power system operators must ensure robust, secure and reliable power system operation even with a large scale integration of wind power. Electricity generated from the intermittent wind in large propor-tion may impact on the control of power system balance and thus deviations in the power system frequency in small or islanded power systems or tie line power flows in interconnected power systems. Therefore, the large scale integration of wind power into the power system strongly concerns the s...
Strings and large scale magnetohydrodynamics
Olesen, P
1995-01-01
From computer simulations of magnetohydrodynamics one knows that a turbulent plasma becomes very intermittent, with the magnetic fields concentrated in thin flux tubes. This situation looks very "string-like", so we investigate whether strings could be solutions of the magnetohydrodynamics equations in the limit of infinite conductivity. We find that the induction equation is satisfied, and we discuss the Navier-Stokes equation (without viscosity) with the Lorentz force included. We argue that the string equations (with non-universal maximum velocity) should describe the large scale motion of narrow magnetic flux tubes, because of a large reparametrization (gauge) invariance of the magnetic and electric string fields.
Japanese large-scale interferometers
Kuroda, K; Miyoki, S; Ishizuka, H; Taylor, C T; Yamamoto, K; Miyakawa, O; Fujimoto, M K; Kawamura, S; Takahashi, R; Yamazaki, T; Arai, K; Tatsumi, D; Ueda, A; Fukushima, M; Sato, S; Shintomi, T; Yamamoto, A; Suzuki, T; Saitô, Y; Haruyama, T; Sato, N; Higashi, Y; Uchiyama, T; Tomaru, T; Tsubono, K; Ando, M; Takamori, A; Numata, K; Ueda, K I; Yoneda, H; Nakagawa, K; Musha, M; Mio, N; Moriwaki, S; Somiya, K; Araya, A; Kanda, N; Telada, S; Sasaki, M; Tagoshi, H; Nakamura, T; Tanaka, T; Ohara, K
2002-01-01
The objective of the TAMA 300 interferometer was to develop advanced technologies for kilometre scale interferometers and to observe gravitational wave events in nearby galaxies. It was designed as a power-recycled Fabry-Perot-Michelson interferometer and was intended as a step towards a final interferometer in Japan. The present successful status of TAMA is presented. TAMA forms a basis for LCGT (large-scale cryogenic gravitational wave telescope), a 3 km scale cryogenic interferometer to be built in the Kamioka mine in Japan, implementing cryogenic mirror techniques. The plan of LCGT is schematically described along with its associated R and D.
Models of large scale structure
Energy Technology Data Exchange (ETDEWEB)
Frenk, C.S. (Physics Dept., Univ. of Durham (UK))
1991-01-01
The ingredients required to construct models of the cosmic large scale structure are discussed. Input from particle physics leads to a considerable simplification by offering concrete proposals for the geometry of the universe, the nature of the dark matter and the primordial fluctuations that seed the growth of structure. The remaining ingredient is the physical interaction that governs dynamical evolution. Empirical evidence provided by an analysis of a redshift survey of IRAS galaxies suggests that gravity is the main agent shaping the large-scale structure. In addition, this survey implies large values of the mean cosmic density, {Omega}> or approx.0.5, and is consistent with a flat geometry if IRAS galaxies are somewhat more clustered than the underlying mass. Together with current limits on the density of baryons from Big Bang nucleosynthesis, this lends support to the idea of a universe dominated by non-baryonic dark matter. Results from cosmological N-body simulations evolved from a variety of initial conditions are reviewed. In particular, neutrino dominated and cold dark matter dominated universes are discussed in detail. Finally, it is shown that apparent periodicities in the redshift distributions in pencil-beam surveys arise frequently from distributions which have no intrinsic periodicity but are clustered on small scales. (orig.).
Desjacques, Vincent; Schmidt, Fabian
2016-01-01
This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a pedagogical proof of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which includes the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in i...
Large scale biomimetic membrane arrays
DEFF Research Database (Denmark)
Hansen, Jesper Søndergaard; Perry, Mark; Vogel, Jörg
2009-01-01
To establish planar biomimetic membranes across large scale partition aperture arrays, we created a disposable single-use horizontal chamber design that supports combined optical-electrical measurements. Functional lipid bilayers could easily and efficiently be established across CO2 laser micro......-structured 8 x 8 aperture partition arrays with average aperture diameters of 301 +/- 5 mu m. We addressed the electro-physical properties of the lipid bilayers established across the micro-structured scaffold arrays by controllable reconstitution of biotechnological and physiological relevant membrane...... peptides and proteins. Next, we tested the scalability of the biomimetic membrane design by establishing lipid bilayers in rectangular 24 x 24 and hexagonal 24 x 27 aperture arrays, respectively. The results presented show that the design is suitable for further developments of sensitive biosensor assays...
Testing gravity on Large Scales
Directory of Open Access Journals (Sweden)
Raccanelli Alvise
2013-09-01
Full Text Available We show how it is possible to test general relativity and different models of gravity via Redshift-Space Distortions using forthcoming cosmological galaxy surveys. However, the theoretical models currently used to interpret the data often rely on simplifications that make them not accurate enough for precise measurements. We will discuss improvements to the theoretical modeling at very large scales, including wide-angle and general relativistic corrections; we then show that for wide and deep surveys those corrections need to be taken into account if we want to measure the growth of structures at a few percent level, and so perform tests on gravity, without introducing systematic errors. Finally, we report the results of some recent cosmological model tests carried out using those precise models.
Conference on Large Scale Optimization
Hearn, D; Pardalos, P
1994-01-01
On February 15-17, 1993, a conference on Large Scale Optimization, hosted by the Center for Applied Optimization, was held at the University of Florida. The con ference was supported by the National Science Foundation, the U. S. Army Research Office, and the University of Florida, with endorsements from SIAM, MPS, ORSA and IMACS. Forty one invited speakers presented papers on mathematical program ming and optimal control topics with an emphasis on algorithm development, real world applications and numerical results. Participants from Canada, Japan, Sweden, The Netherlands, Germany, Belgium, Greece, and Denmark gave the meeting an important international component. At tendees also included representatives from IBM, American Airlines, US Air, United Parcel Serice, AT & T Bell Labs, Thinking Machines, Army High Performance Com puting Research Center, and Argonne National Laboratory. In addition, the NSF sponsored attendance of thirteen graduate students from universities in the United States and abro...
Large Scale Correlation Clustering Optimization
Bagon, Shai
2011-01-01
Clustering is a fundamental task in unsupervised learning. The focus of this paper is the Correlation Clustering functional which combines positive and negative affinities between the data points. The contribution of this paper is two fold: (i) Provide a theoretic analysis of the functional. (ii) New optimization algorithms which can cope with large scale problems (>100K variables) that are infeasible using existing methods. Our theoretic analysis provides a probabilistic generative interpretation for the functional, and justifies its intrinsic "model-selection" capability. Furthermore, we draw an analogy between optimizing this functional and the well known Potts energy minimization. This analogy allows us to suggest several new optimization algorithms, which exploit the intrinsic "model-selection" capability of the functional to automatically recover the underlying number of clusters. We compare our algorithms to existing methods on both synthetic and real data. In addition we suggest two new applications t...
Topology Optimization of Large Scale Stokes Flow Problems
DEFF Research Database (Denmark)
Aage, Niels; Poulsen, Thomas Harpsøe; Gersborg-Hansen, Allan
2008-01-01
This note considers topology optimization of large scale 2D and 3D Stokes flow problems using parallel computations. We solve problems with up to 1.125.000 elements in 2D and 128.000 elements in 3D on a shared memory computer consisting of Sun UltraSparc IV CPUs.......This note considers topology optimization of large scale 2D and 3D Stokes flow problems using parallel computations. We solve problems with up to 1.125.000 elements in 2D and 128.000 elements in 3D on a shared memory computer consisting of Sun UltraSparc IV CPUs....
Accelerated large-scale multiple sequence alignment
Directory of Open Access Journals (Sweden)
Lloyd Scott
2011-12-01
Full Text Available Abstract Background Multiple sequence alignment (MSA is a fundamental analysis method used in bioinformatics and many comparative genomic applications. Prior MSA acceleration attempts with reconfigurable computing have only addressed the first stage of progressive alignment and consequently exhibit performance limitations according to Amdahl's Law. This work is the first known to accelerate the third stage of progressive alignment on reconfigurable hardware. Results We reduce subgroups of aligned sequences into discrete profiles before they are pairwise aligned on the accelerator. Using an FPGA accelerator, an overall speedup of up to 150 has been demonstrated on a large data set when compared to a 2.4 GHz Core2 processor. Conclusions Our parallel algorithm and architecture accelerates large-scale MSA with reconfigurable computing and allows researchers to solve the larger problems that confront biologists today. Program source is available from http://dna.cs.byu.edu/msa/.
A study of MLFMA for large-scale scattering problems
Hastriter, Michael Larkin
This research is centered in computational electromagnetics with a focus on solving large-scale problems accurately in a timely fashion using first principle physics. Error control of the translation operator in 3-D is shown. A parallel implementation of the multilevel fast multipole algorithm (MLFMA) was studied as far as parallel efficiency and scaling. The large-scale scattering program (LSSP), based on the ScaleME library, was used to solve ultra-large-scale problems including a 200lambda sphere with 20 million unknowns. As these large-scale problems were solved, techniques were developed to accurately estimate the memory requirements. Careful memory management is needed in order to solve these massive problems. The study of MLFMA in large-scale problems revealed significant errors that stemmed from inconsistencies in constants used by different parts of the algorithm. These were fixed to produce the most accurate data possible for large-scale surface scattering problems. Data was calculated on a missile-like target using both high frequency methods and MLFMA. This data was compared and analyzed to determine possible strategies to increase data acquisition speed and accuracy through multiple computation method hybridization.
Adaptive robust trajectory tracking control of a parallel manipulator driven by pneumatic cylinders
Directory of Open Access Journals (Sweden)
Ce Shang
2016-04-01
Full Text Available Due to the compressibility of air, non-linear characteristics, and parameter uncertainties of pneumatic elements, the position control of a pneumatic cylinder or parallel platform is still very difficult while comparing with the systems driven by electric or hydraulic power. In this article, based on the basic dynamic model and descriptions of thermal processes, a controller integrated with online parameter estimation is proposed to improve the performance of a pneumatic cylinder controlled by a proportional valve. The trajectory tracking error is significantly decreased by applying this method. Moreover, the algorithm is expanded to the problem of posture trajectory tracking for the three-revolute prismatic spherical pneumatic parallel manipulator. Lyapunov’s method is used to give the proof of stability of the controller. Using NI-CompactRio, NI-PXI, and Veristand platform as the realistic controller hardware and data interactive environment, the adaptive robust control algorithm is applied to the physical system successfully. Experimental results and data analysis showed that the posture error of the platform could be about 0.5%–0.7% of the desired trajectory amplitude. By integrating this method to the mechatronic system, the pneumatic servo solutions can be much more competitive in the industrial market of position and posture control.
Large scale cluster computing workshop
Energy Technology Data Exchange (ETDEWEB)
Dane Skow; Alan Silverman
2002-12-23
Recent revolutions in computer hardware and software technologies have paved the way for the large-scale deployment of clusters of commodity computers to address problems heretofore the domain of tightly coupled SMP processors. Near term projects within High Energy Physics and other computing communities will deploy clusters of scale 1000s of processors and be used by 100s to 1000s of independent users. This will expand the reach in both dimensions by an order of magnitude from the current successful production facilities. The goals of this workshop were: (1) to determine what tools exist which can scale up to the cluster sizes foreseen for the next generation of HENP experiments (several thousand nodes) and by implication to identify areas where some investment of money or effort is likely to be needed. (2) To compare and record experimences gained with such tools. (3) To produce a practical guide to all stages of planning, installing, building and operating a large computing cluster in HENP. (4) To identify and connect groups with similar interest within HENP and the larger clustering community.
Large Scale Magnetostrictive Valve Actuator
Richard, James A.; Holleman, Elizabeth; Eddleman, David
2008-01-01
Marshall Space Flight Center's Valves, Actuators and Ducts Design and Development Branch developed a large scale magnetostrictive valve actuator. The potential advantages of this technology are faster, more efficient valve actuators that consume less power and provide precise position control and deliver higher flow rates than conventional solenoid valves. Magnetostrictive materials change dimensions when a magnetic field is applied; this property is referred to as magnetostriction. Magnetostriction is caused by the alignment of the magnetic domains in the material s crystalline structure and the applied magnetic field lines. Typically, the material changes shape by elongating in the axial direction and constricting in the radial direction, resulting in no net change in volume. All hardware and testing is complete. This paper will discuss: the potential applications of the technology; overview of the as built actuator design; discuss problems that were uncovered during the development testing; review test data and evaluate weaknesses of the design; and discuss areas for improvement for future work. This actuator holds promises of a low power, high load, proportionally controlled actuator for valves requiring 440 to 1500 newtons load.
Eighth SIAM conference on parallel processing for scientific computing: Final program and abstracts
Energy Technology Data Exchange (ETDEWEB)
NONE
1997-12-31
This SIAM conference is the premier forum for developments in parallel numerical algorithms, a field that has seen very lively and fruitful developments over the past decade, and whose health is still robust. Themes for this conference were: combinatorial optimization; data-parallel languages; large-scale parallel applications; message-passing; molecular modeling; parallel I/O; parallel libraries; parallel software tools; parallel compilers; particle simulations; problem-solving environments; and sparse matrix computations.
Robust parallel iterative solvers for linear and least-squares problems, Final Technical Report
Energy Technology Data Exchange (ETDEWEB)
Saad, Yousef
2014-01-16
The primary goal of this project is to study and develop robust iterative methods for solving linear systems of equations and least squares systems. The focus of the Minnesota team is on algorithms development, robustness issues, and on tests and validation of the methods on realistic problems. 1. The project begun with an investigation on how to practically update a preconditioner obtained from an ILU-type factorization, when the coefficient matrix changes. 2. We investigated strategies to improve robustness in parallel preconditioners in a specific case of a PDE with discontinuous coefficients. 3. We explored ways to adapt standard preconditioners for solving linear systems arising from the Helmholtz equation. These are often difficult linear systems to solve by iterative methods. 4. We have also worked on purely theoretical issues related to the analysis of Krylov subspace methods for linear systems. 5. We developed an effective strategy for performing ILU factorizations for the case when the matrix is highly indefinite. The strategy uses shifting in some optimal way. The method was extended to the solution of Helmholtz equations by using complex shifts, yielding very good results in many cases. 6. We addressed the difficult problem of preconditioning sparse systems of equations on GPUs. 7. A by-product of the above work is a software package consisting of an iterative solver library for GPUs based on CUDA. This was made publicly available. It was the first such library that offers complete iterative solvers for GPUs. 8. We considered another form of ILU which blends coarsening techniques from Multigrid with algebraic multilevel methods. 9. We have released a new version on our parallel solver - called pARMS [new version is version 3]. As part of this we have tested the code in complex settings - including the solution of Maxwell and Helmholtz equations and for a problem of crystal growth.10. As an application of polynomial preconditioning we considered the
Handbook of Large-Scale Random Networks
Bollobas, Bela; Miklos, Dezso
2008-01-01
Covers various aspects of large-scale networks, including mathematical foundations and rigorous results of random graph theory, modeling and computational aspects of large-scale networks, as well as areas in physics, biology, neuroscience, sociology and technical areas
Large-Scale Information Systems
Energy Technology Data Exchange (ETDEWEB)
D. M. Nicol; H. R. Ammerlahn; M. E. Goldsby; M. M. Johnson; D. E. Rhodes; A. S. Yoshimura
2000-12-01
Large enterprises are ever more dependent on their Large-Scale Information Systems (LSLS), computer systems that are distinguished architecturally by distributed components--data sources, networks, computing engines, simulations, human-in-the-loop control and remote access stations. These systems provide such capabilities as workflow, data fusion and distributed database access. The Nuclear Weapons Complex (NWC) contains many examples of LSIS components, a fact that motivates this research. However, most LSIS in use grew up from collections of separate subsystems that were not designed to be components of an integrated system. For this reason, they are often difficult to analyze and control. The problem is made more difficult by the size of a typical system, its diversity of information sources, and the institutional complexities associated with its geographic distribution across the enterprise. Moreover, there is no integrated approach for analyzing or managing such systems. Indeed, integrated development of LSIS is an active area of academic research. This work developed such an approach by simulating the various components of the LSIS and allowing the simulated components to interact with real LSIS subsystems. This research demonstrated two benefits. First, applying it to a particular LSIS provided a thorough understanding of the interfaces between the system's components. Second, it demonstrated how more rapid and detailed answers could be obtained to questions significant to the enterprise by interacting with the relevant LSIS subsystems through simulated components designed with those questions in mind. In a final, added phase of the project, investigations were made on extending this research to wireless communication networks in support of telemetry applications.
Conundrum of the Large Scale Streaming
Malm, T M
1999-01-01
The etiology of the large scale peculiar velocity (large scale streaming motion) of clusters would increasingly seem more tenuous, within the context of the gravitational instability hypothesis. Are there any alternative testable models possibly accounting for such large scale streaming of clusters?
Flexibility in design of large-scale methanol plants
Institute of Scientific and Technical Information of China (English)
Esben Lauge Sφrensen; Helge Holm-Larsen; Haldor Topsφe A/S
2006-01-01
This paper presents a cost effective design for large-scale methanol production. It is demonstrated how recent technological progress can be utilised to design a methanol plant,which is inexpensive and easy to operate, while at the same time very robust towards variations in feed-stock composition and product specifications.
Institute of Scientific and Technical Information of China (English)
彭春华; 谢鹏; 陈臣
2014-01-01
ABSTRACT:With the increase of penetration of photovoltaic power, the randomness and volatility of photovoltaic power output would have a greater impact on power system optimization scheduling. To ensure the reliability of optimal scheduling, this paper applied box set robust optimization theory into power system optimization scheduling. To coordinate the contradiction between the reliability and economy of system scheduling, the concept of uncertainty budget was applied to achieve robust optimization in adjustable uncertain intervals, and to make up for the conservation deficiencies which box set robust optimization method has. The robust optimization model in adjustable uncertain intervals was established for power system to achieve coordination between reliability and economy. Based on the constructed optimization model, this paper derived an uncertainty budget decision- making method, which can effectively reduce the blindness in the uncertainty budgetary decision-making. Finally, differential evolution algorithm was employed to solve the dynamic optimization dispatch problems. The feasibility and rationality of the constituted model is verified by a testing example.%随着光伏电站接入电网的比例不断提高，光伏电站出力的随机性和波动性给电力系统优化调度带来较大影响。为保证优化调度的可靠性，提出将盒式集合鲁棒优化理论引入到含大规模光伏电站的电力系统优化调度中。同时为了协调系统调度中可靠性与经济性之间的矛盾，提出引入不确定性预算的概念以实现不确定区间可调节鲁棒优化，弥补盒式集合鲁棒优化偏于保守的不足，构建可靠性与经济性相协调的含光伏电站的电力系统不确定区间可调节鲁棒优化调度模型。并根据所构建的优化调度模型推导出一个不确定性预算决策方法，从而降低不确定性预算决策的盲目性。最后采用微分进化算法对提出的动态优
BFAST: an alignment tool for large scale genome resequencing.
Directory of Open Access Journals (Sweden)
Nils Homer
Full Text Available BACKGROUND: The new generation of massively parallel DNA sequencers, combined with the challenge of whole human genome resequencing, result in the need for rapid and accurate alignment of billions of short DNA sequence reads to a large reference genome. Speed is obviously of great importance, but equally important is maintaining alignment accuracy of short reads, in the 25-100 base range, in the presence of errors and true biological variation. METHODOLOGY: We introduce a new algorithm specifically optimized for this task, as well as a freely available implementation, BFAST, which can align data produced by any of current sequencing platforms, allows for user-customizable levels of speed and accuracy, supports paired end data, and provides for efficient parallel and multi-threaded computation on a computer cluster. The new method is based on creating flexible, efficient whole genome indexes to rapidly map reads to candidate alignment locations, with arbitrary multiple independent indexes allowed to achieve robustness against read errors and sequence variants. The final local alignment uses a Smith-Waterman method, with gaps to support the detection of small indels. CONCLUSIONS: We compare BFAST to a selection of large-scale alignment tools -- BLAT, MAQ, SHRiMP, and SOAP -- in terms of both speed and accuracy, using simulated and real-world datasets. We show BFAST can achieve substantially greater sensitivity of alignment in the context of errors and true variants, especially insertions and deletions, and minimize false mappings, while maintaining adequate speed compared to other current methods. We show BFAST can align the amount of data needed to fully resequence a human genome, one billion reads, with high sensitivity and accuracy, on a modest computer cluster in less than 24 hours. BFAST is available at (http://bfast.sourceforge.net.
Real-time simulation of large-scale floods
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.
Institute of Scientific and Technical Information of China (English)
袁静珍
2010-01-01
构建了一个面向互联网计算资源共享的并行程序设计环境IPPE(internet-based parallel programming environment).该环境使用Java语言开发,通过利用Java运行系统与Java并行通信类库,在IPPE环境下可以书写具有并行处理能力的Java应用程序.IPPE具有平台独立性、容易使用、负载均衡性、容错性等特点.IPPE环境的平台独立性与易用性得益于其基于Java的字节码技术与对象序列化技术,IPPE的负载均衡性得益于针对任务的自适应并行调度算法及子任务级的容错策略.通过运行两个典型的BanchMark并行程序,表明了IPPE环境的高效性与稳定性.
GPU-based large-scale visualization
Hadwiger, Markus
2013-11-19
Recent advances in image and volume acquisition as well as computational advances in simulation have led to an explosion of the amount of data that must be visualized and analyzed. Modern techniques combine the parallel processing power of GPUs with out-of-core methods and data streaming to enable the interactive visualization of giga- and terabytes of image and volume data. A major enabler for interactivity is making both the computational and the visualization effort proportional to the amount of data that is actually visible on screen, decoupling it from the full data size. This leads to powerful display-aware multi-resolution techniques that enable the visualization of data of almost arbitrary size. The course consists of two major parts: An introductory part that progresses from fundamentals to modern techniques, and a more advanced part that discusses details of ray-guided volume rendering, novel data structures for display-aware visualization and processing, and the remote visualization of large online data collections. You will learn how to develop efficient GPU data structures and large-scale visualizations, implement out-of-core strategies and concepts such as virtual texturing that have only been employed recently, as well as how to use modern multi-resolution representations. These approaches reduce the GPU memory requirements of extremely large data to a working set size that fits into current GPUs. You will learn how to perform ray-casting of volume data of almost arbitrary size and how to render and process gigapixel images using scalable, display-aware techniques. We will describe custom virtual texturing architectures as well as recent hardware developments in this area. We will also describe client/server systems for distributed visualization, on-demand data processing and streaming, and remote visualization. We will describe implementations using OpenGL as well as CUDA, exploiting parallelism on GPUs combined with additional asynchronous
Balancing modern Power System with large scale of wind power
DEFF Research Database (Denmark)
Basit, Abdul; Altin, Müfit; Hansen, Anca Daniela
2014-01-01
Power system operators must ensure robust, secure and reliable power system operation even with a large scale integration of wind power. Electricity generated from the intermittent wind in large propor-tion may impact on the control of power system balance and thus deviations in the power system...... to be analysed with improved analytical tools and techniques. This paper proposes techniques for the active power balance control in future power systems with the large scale wind power integration, where power balancing model provides the hour-ahead dispatch plan with reduced planning horizon and the real time...... frequency in small or islanded power systems or tie line power flows in interconnected power systems. Therefore, the large scale integration of wind power into the power system strongly concerns the secure and stable grid operation. To ensure the stable power system operation, the evolving power system has...
Large Scale Computations in Air Pollution Modelling
DEFF Research Database (Denmark)
Zlatev, Z.; Brandt, J.; Builtjes, P. J. H.
Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998......Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998...
Large Scale Computations in Air Pollution Modelling
DEFF Research Database (Denmark)
Zlatev, Z.; Brandt, J.; Builtjes, P. J. H.
Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998......Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998...
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Rizzuto, Enrico; Narasimhan, Harikrishna
2012-01-01
More frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure combined with increased requirements to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of structures......, a theoretical and risk-based framework is presented which facilitates the quantification of robustness, and thus supports the formulation of pre-normative guidelines....
Large scale network-centric distributed systems
Sarbazi-Azad, Hamid
2014-01-01
A highly accessible reference offering a broad range of topics and insights on large scale network-centric distributed systems Evolving from the fields of high-performance computing and networking, large scale network-centric distributed systems continues to grow as one of the most important topics in computing and communication and many interdisciplinary areas. Dealing with both wired and wireless networks, this book focuses on the design and performance issues of such systems. Large Scale Network-Centric Distributed Systems provides in-depth coverage ranging from ground-level hardware issu
Running Large-Scale Air Pollution Models on Parallel Computers
DEFF Research Database (Denmark)
Georgiev, K.; Zlatev, Z.
2000-01-01
Proceedings of the 23rd NATO/CCMS International Technical Meeting on Air Pollution Modeling and Its Application, held 28 September - 2 October 1998, in Varna, Bulgaria.......Proceedings of the 23rd NATO/CCMS International Technical Meeting on Air Pollution Modeling and Its Application, held 28 September - 2 October 1998, in Varna, Bulgaria....
Debugging and Analysis of Large-Scale Parallel Programs
1989-09-01
vtT in ti, M maps a2 to v’ in t,,n, and j < k. 3. a, and a2 both access the same memory location m, M maps both a, and a 2 to vjm in tin, a, is an...lock is released. In addition to being independent of a particular protocol, our synchronization trac ing technique does not rely on a particular
Parallel Earthquake Simulations on Large-Scale Multicore Supercomputers
Wu, Xingfu
2011-01-01
Earthquakes are one of the most destructive natural hazards on our planet Earth. Hugh earthquakes striking offshore may cause devastating tsunamis, as evidenced by the 11 March 2011 Japan (moment magnitude Mw9.0) and the 26 December 2004 Sumatra (Mw9.1) earthquakes. Earthquake prediction (in terms of the precise time, place, and magnitude of a coming earthquake) is arguably unfeasible in the foreseeable future. To mitigate seismic hazards from future earthquakes in earthquake-prone areas, such as California and Japan, scientists have been using numerical simulations to study earthquake rupture propagation along faults and seismic wave propagation in the surrounding media on ever-advancing modern computers over past several decades. In particular, ground motion simulations for past and future (possible) significant earthquakes have been performed to understand factors that affect ground shaking in populated areas, and to provide ground shaking characteristics and synthetic seismograms for emergency preparation and design of earthquake-resistant structures. These simulation results can guide the development of more rational seismic provisions for leading to safer, more efficient, and economical50pt]Please provide V. Taylor author e-mail ID. structures in earthquake-prone regions.
Robust Fuzzy PD Method with Parallel Computed Fuel Ratio Estimation Applied to Automotive Engine
Directory of Open Access Journals (Sweden)
Farzin Piltan
2013-07-01
Full Text Available Both fuzzy logic and computed fuel ratio can compensate the steady-state error of proportional-derivative (PD method. This paper presents parallel computed fuel ratio compensation for fuzzy plus PID control management with application to internal combustion (IC engine. The asymptotic stability of fuzzy plus PID control methodology with first-order computed fuel ratio estimation in the parallel structure is proven. For the parallel structure, the finite time convergence with a super-twisting second-order sliding-mode is guaranteed.
Imaging HF-induced large-scale irregularities above HAARP
Djuth, Frank T.; Reinisch, Bodo W.; Kitrosser, David F.; Elder, John H.; Snyder, A. Lee; Sales, Gary S.
2006-02-01
The University of Massachusetts-Lowell digisonde is used with the HAARP high-frequency (HF), ionospheric modification facility to obtain radio images of artificially-produced, large-scale, geomagnetic field-aligned irregularities. F region irregularities generated with the HAARP beam pointed in the vertical and geomagnetic field-aligned directions are examined in a smooth background plasma. It is found that limited large-scale irregularity production takes place with vertical transmissions, whereas there is a dramatic increase in the number of source irregularities with the beam pointed parallel to the geomagnetic field. Strong irregularity production appears to be confined to within ~5° of the geomagnetic zenith and does not fill the volume occupied by the HF beam. A similar effect is observed in optical images of artificial airglow.
Accelerating sustainability in large-scale facilities
Marina Giampietro
2011-01-01
Scientific research centres and large-scale facilities are intrinsically energy intensive, but how can big science improve its energy management and eventually contribute to the environmental cause with new cleantech? CERN’s commitment to providing tangible answers to these questions was sealed in the first workshop on energy management for large scale scientific infrastructures held in Lund, Sweden, on the 13-14 October. Participants at the energy management for large scale scientific infrastructures workshop. The workshop, co-organised with the European Spallation Source (ESS) and the European Association of National Research Facilities (ERF), tackled a recognised need for addressing energy issues in relation with science and technology policies. It brought together more than 150 representatives of Research Infrastrutures (RIs) and energy experts from Europe and North America. “Without compromising our scientific projects, we can ...
DEFF Research Database (Denmark)
Dollerup, Niels; Jepsen, Michael S.; Damkilde, Lars
2013-01-01
of the precalculation step, which utilizes the principals of the well-known frontal method. The succeeding optimization algorithm is also significantly optimized, by applying a parallel implementation, which eliminates the exponential growth in computational time relative to the element numbers....
Large-Scale Analysis of Art Proportions
DEFF Research Database (Denmark)
Jensen, Karl Kristoffer
2014-01-01
While literature often tries to impute mathematical constants into art, this large-scale study (11 databases of paintings and photos, around 200.000 items) shows a different truth. The analysis, consisting of the width/height proportions, shows a value of rarely if ever one (square) and with majo......While literature often tries to impute mathematical constants into art, this large-scale study (11 databases of paintings and photos, around 200.000 items) shows a different truth. The analysis, consisting of the width/height proportions, shows a value of rarely if ever one (square...
Large-scale Complex IT Systems
Sommerville, Ian; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard
2011-01-01
This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that identifies the major challenges and issues in the development of large-scale complex, software-intensive systems. Central to this is the notion that we cannot separate software from the socio-technical environment in which it is used.
Topological Routing in Large-Scale Networks
DEFF Research Database (Denmark)
Pedersen, Jens Myrup; Knudsen, Thomas Phillip; Madsen, Ole Brun
2004-01-01
A new routing scheme, Topological Routing, for large-scale networks is proposed. It allows for efficient routing without large routing tables as known from traditional routing schemes. It presupposes a certain level of order in the networks, known from Structural QoS. The main issues in applying...... Topological Routing to large-scale networks are discussed. Hierarchical extensions are presented along with schemes for shortest path routing, fault handling and path restoration. Further reserach in the area is discussed and perspectives on the prerequisites for practical deployment of Topological Routing...
Topological Routing in Large-Scale Networks
DEFF Research Database (Denmark)
Pedersen, Jens Myrup; Knudsen, Thomas Phillip; Madsen, Ole Brun
A new routing scheme, Topological Routing, for large-scale networks is proposed. It allows for efficient routing without large routing tables as known from traditional routing schemes. It presupposes a certain level of order in the networks, known from Structural QoS. The main issues in applying...... Topological Routing to large-scale networks are discussed. Hierarchical extensions are presented along with schemes for shortest path routing, fault handling and path restoration. Further reserach in the area is discussed and perspectives on the prerequisites for practical deployment of Topological Routing...
Large scale topic modeling made practical
DEFF Research Database (Denmark)
Wahlgreen, Bjarne Ørum; Hansen, Lars Kai
2011-01-01
Topic models are of broad interest. They can be used for query expansion and result structuring in information retrieval and as an important component in services such as recommender systems and user adaptive advertising. In large scale applications both the size of the database (number of docume......Topic models are of broad interest. They can be used for query expansion and result structuring in information retrieval and as an important component in services such as recommender systems and user adaptive advertising. In large scale applications both the size of the database (number...... topics at par with a much larger case specific vocabulary....
DEFF Research Database (Denmark)
Dollerup, Niels; Jepsen, Michael S.; Frier, Christian;
2014-01-01
A robust and effective finite element based implementation of lower bound limit state analysis applying an interior point formulation is presented in this paper. The lower bound formulation results in a convex optimization problem consisting of a number of linear constraints from the equilibrium...... equations and a number of convex non-linear constraints from the yield criteria. The computational robustness has been improved by eliminating a large number of the equilibrium equations a priori leaving only the statical redundant variables as free optimization variables. The elimination of equilibrium...... equations is based on a optimized numbering of elements and stress variables based on the frontal method approach used in the standard finite element method. The optimized numbering secures sparsity in the formulation. The convex non-linear yield criteria are treated directly in the interior point...
Martínez Guardiola, Francisco Javier; Márquez Ruiz, Andrés; Gallego Rico, Sergi; Ortuño Sánchez, Manuel; Francés Monllor, Jorge; Beléndez Vázquez, Augusto; Pascual Villalobos, Inmaculada
2014-01-01
Parallel-aligned liquid crystal on silicon (PA-LCoS) displays have become the most attractive spatial light modulator device for a wide range of applications, due to their superior resolution and light efficiency, added to their phase-only capability. Recently we proposed a novel polarimetric method, based on Stokes polarimetry, enabling the characterization of their linear retardance and the magnitude of their associated phase fluctuations, if existent, as it happens in most of digital backp...
Large-scale multimedia modeling applications
Energy Technology Data Exchange (ETDEWEB)
Droppo, J.G. Jr.; Buck, J.W.; Whelan, G.; Strenge, D.L.; Castleton, K.J.; Gelston, G.M.
1995-08-01
Over the past decade, the US Department of Energy (DOE) and other agencies have faced increasing scrutiny for a wide range of environmental issues related to past and current practices. A number of large-scale applications have been undertaken that required analysis of large numbers of potential environmental issues over a wide range of environmental conditions and contaminants. Several of these applications, referred to here as large-scale applications, have addressed long-term public health risks using a holistic approach for assessing impacts from potential waterborne and airborne transport pathways. Multimedia models such as the Multimedia Environmental Pollutant Assessment System (MEPAS) were designed for use in such applications. MEPAS integrates radioactive and hazardous contaminants impact computations for major exposure routes via air, surface water, ground water, and overland flow transport. A number of large-scale applications of MEPAS have been conducted to assess various endpoints for environmental and human health impacts. These applications are described in terms of lessons learned in the development of an effective approach for large-scale applications.
Evaluating Large-Scale Interactive Radio Programmes
Potter, Charles; Naidoo, Gordon
2009-01-01
This article focuses on the challenges involved in conducting evaluations of interactive radio programmes in South Africa with large numbers of schools, teachers, and learners. It focuses on the role such large-scale evaluation has played during the South African radio learning programme's development stage, as well as during its subsequent…
Configuration management in large scale infrastructure development
Rijn, T.P.J. van; Belt, H. van de; Los, R.H.
2000-01-01
Large Scale Infrastructure (LSI) development projects such as the construction of roads, rail-ways and other civil engineering (water)works is tendered differently today than a decade ago. Traditional workflow requested quotes from construction companies for construction works where the works to be
Computing in Large-Scale Dynamic Systems
Pruteanu, A.S.
2013-01-01
Software applications developed for large-scale systems have always been difficult to de- velop due to problems caused by the large number of computing devices involved. Above a certain network size (roughly one hundred), necessary services such as code updating, topol- ogy discovery and data dissem
Sensitivity analysis for large-scale problems
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.
Large-scale perspective as a challenge
Plomp, M.G.A.
2012-01-01
1. Scale forms a challenge for chain researchers: when exactly is something ‘large-scale’? What are the underlying factors (e.g. number of parties, data, objects in the chain, complexity) that determine this? It appears to be a continuum between small- and large-scale, where positioning on that cont
Ensemble methods for large scale inverse problems
Heemink, A.W.; Umer Altaf, M.; Barbu, A.L.; Verlaan, M.
2013-01-01
Variational data assimilation, also sometimes simply called the ‘adjoint method’, is used very often for large scale model calibration problems. Using the available data, the uncertain parameters in the model are identified by minimizing a certain cost function that measures the difference between t
DEFF Research Database (Denmark)
Arler, Finn
2006-01-01
, which kind of attitude is appropriate when dealing with large-scale changes like these from an ethical point of view. Three kinds of approaches are discussed: Aldo Leopold's mountain thinking, the neoclassical economists' approach, and finally the so-called Concentric Circle Theories approach...
Inflation, large scale structure and particle physics
Indian Academy of Sciences (India)
S F King
2004-02-01
We review experimental and theoretical developments in inflation and its application to structure formation, including the curvation idea. We then discuss a particle physics model of supersymmetric hybrid inflation at the intermediate scale in which the Higgs scalar field is responsible for large scale structure, show how such a theory is completely natural in the framework extra dimensions with an intermediate string scale.
Large Scale Simulations of the Euler Equations on GPU Clusters
Liebmann, Manfred
2010-08-01
The paper investigates the scalability of a parallel Euler solver, using the Vijayasundaram method, on a GPU cluster with 32 Nvidia Geforce GTX 295 boards. The aim of this research is to enable large scale fluid dynamics simulations with up to one billion elements. We investigate communication protocols for the GPU cluster to compensate for the slow Gigabit Ethernet network between the GPU compute nodes and to maintain overall efficiency. A diesel engine intake-port and a nozzle, meshed in different resolutions, give good real world examples for the scalability tests on the GPU cluster. © 2010 IEEE.
Petascale computations for Large-scale Atomic and Molecular collisions
McLaughlin, Brendan M
2014-01-01
Petaflop architectures are currently being utilized efficiently to perform large scale computations in Atomic, Molecular and Optical Collisions. We solve the Schroedinger or Dirac equation for the appropriate collision problem using the R-matrix or R-matrix with pseudo-states approach. We briefly outline the parallel methodology used and implemented for the current suite of Breit-Pauli and DARC codes. Various examples are shown of our theoretical results compared with those obtained from Synchrotron Radiation facilities and from Satellite observations. We also indicate future directions and implementation of the R-matrix codes on emerging GPU architectures.
Reliability assessment for components of large scale photovoltaic systems
Ahadi, Amir; Ghadimi, Noradin; Mirabbasi, Davar
2014-10-01
Photovoltaic (PV) systems have significantly shifted from independent power generation systems to a large-scale grid-connected generation systems in recent years. The power output of PV systems is affected by the reliability of various components in the system. This study proposes an analytical approach to evaluate the reliability of large-scale, grid-connected PV systems. The fault tree method with an exponential probability distribution function is used to analyze the components of large-scale PV systems. The system is considered in the various sequential and parallel fault combinations in order to find all realistic ways in which the top or undesired events can occur. Additionally, it can identify areas that the planned maintenance should focus on. By monitoring the critical components of a PV system, it is possible not only to improve the reliability of the system, but also to optimize the maintenance costs. The latter is achieved by informing the operators about the system component's status. This approach can be used to ensure secure operation of the system by its flexibility in monitoring system applications. The implementation demonstrates that the proposed method is effective and efficient and can conveniently incorporate more system maintenance plans and diagnostic strategies.
Equivalent common path method in large-scale laser comparator
He, Mingzhao; Li, Jianshuang; Miao, Dongjing
2015-02-01
Large-scale laser comparator is main standard device that providing accurate, reliable and traceable measurements for high precision large-scale line and 3D measurement instruments. It mainly composed of guide rail, motion control system, environmental parameters monitoring system and displacement measurement system. In the laser comparator, the main error sources are temperature distribution, straightness of guide rail and pitch and yaw of measuring carriage. To minimize the measurement uncertainty, an equivalent common optical path scheme is proposed and implemented. Three laser interferometers are adjusted to parallel with the guide rail. The displacement in an arbitrary virtual optical path is calculated using three displacements without the knowledge of carriage orientations at start and end positions. The orientation of air floating carriage is calculated with displacements of three optical path and position of three retroreflectors which are precisely measured by Laser Tracker. A 4th laser interferometer is used in the virtual optical path as reference to verify this compensation method. This paper analyzes the effect of rail straightness on the displacement measurement. The proposed method, through experimental verification, can improve the measurement uncertainty of large-scale laser comparator.
Large Scale Implementations for Twitter Sentiment Classification
Directory of Open Access Journals (Sweden)
Andreas Kanavos
2017-03-01
Full Text Available Sentiment Analysis on Twitter Data is indeed a challenging problem due to the nature, diversity and volume of the data. People tend to express their feelings freely, which makes Twitter an ideal source for accumulating a vast amount of opinions towards a wide spectrum of topics. This amount of information offers huge potential and can be harnessed to receive the sentiment tendency towards these topics. However, since no one can invest an infinite amount of time to read through these tweets, an automated decision making approach is necessary. Nevertheless, most existing solutions are limited in centralized environments only. Thus, they can only process at most a few thousand tweets. Such a sample is not representative in order to define the sentiment polarity towards a topic due to the massive number of tweets published daily. In this work, we develop two systems: the first in the MapReduce and the second in the Apache Spark framework for programming with Big Data. The algorithm exploits all hashtags and emoticons inside a tweet, as sentiment labels, and proceeds to a classification method of diverse sentiment types in a parallel and distributed manner. Moreover, the sentiment analysis tool is based on Machine Learning methodologies alongside Natural Language Processing techniques and utilizes Apache Spark’s Machine learning library, MLlib. In order to address the nature of Big Data, we introduce some pre-processing steps for achieving better results in Sentiment Analysis as well as Bloom filters to compact the storage size of intermediate data and boost the performance of our algorithm. Finally, the proposed system was trained and validated with real data crawled by Twitter, and, through an extensive experimental evaluation, we prove that our solution is efficient, robust and scalable while confirming the quality of our sentiment identification.
Large-Scale Optimization for Bayesian Inference in Complex Systems
Energy Technology Data Exchange (ETDEWEB)
Willcox, Karen [MIT; Marzouk, Youssef [MIT
2013-11-12
The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimization) Project focused on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimization and inversion methods. The project was a collaborative effort among MIT, the University of Texas at Austin, Georgia Institute of Technology, and Sandia National Laboratories. The research was directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. The MIT--Sandia component of the SAGUARO Project addressed the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas--Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to-observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as ``reduce then sample'' and ``sample then reduce.'' In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to
Multivariate Clustering of Large-Scale Scientific Simulation Data
Energy Technology Data Exchange (ETDEWEB)
Eliassi-Rad, T; Critchlow, T
2003-06-13
Simulations of complex scientific phenomena involve the execution of massively parallel computer programs. These simulation programs generate large-scale data sets over the spatio-temporal space. Modeling such massive data sets is an essential step in helping scientists discover new information from their computer simulations. In this paper, we present a simple but effective multivariate clustering algorithm for large-scale scientific simulation data sets. Our algorithm utilizes the cosine similarity measure to cluster the field variables in a data set. Field variables include all variables except the spatial (x, y, z) and temporal (time) variables. The exclusion of the spatial dimensions is important since ''similar'' characteristics could be located (spatially) far from each other. To scale our multivariate clustering algorithm for large-scale data sets, we take advantage of the geometrical properties of the cosine similarity measure. This allows us to reduce the modeling time from O(n{sup 2}) to O(n x g(f(u))), where n is the number of data points, f(u) is a function of the user-defined clustering threshold, and g(f(u)) is the number of data points satisfying f(u). We show that on average g(f(u)) is much less than n. Finally, even though spatial variables do not play a role in building clusters, it is desirable to associate each cluster with its correct spatial region. To achieve this, we present a linking algorithm for connecting each cluster to the appropriate nodes of the data set's topology tree (where the spatial information of the data set is stored). Our experimental evaluations on two large-scale simulation data sets illustrate the value of our multivariate clustering and linking algorithms.
Jang, Ju-Seog; Shin, Dong-Hak
1997-03-01
For a flexible pattern recognition system that is robust to the input variations, a feature extraction approach is investigated. Two types of features are extracted: one is line orientations, and the other is the eigenvectors of the covariance matrix of the patterns that cannot be distinguished with the line orientation features alone. For the feature extraction, the Vander Lugt-type filters are used, which are recorded in a small spot of holographic recording medium by use of multiplexing techniques. A multilayer perceptron implemented in a computer is trained with a set of optically extracted features, so that it can recognize the input patterns that are not used in the training. Through preliminary experiments, where English character patterns composed of only straight line segments were tested, the feasibility of our approach is demonstrated.
The large-scale structure of vacuum
Albareti, F D; Maroto, A L
2014-01-01
The vacuum state in quantum field theory is known to exhibit an important number of fundamental physical features. In this work we explore the possibility that this state could also present a non-trivial space-time structure on large scales. In particular, we will show that by imposing the renormalized vacuum energy-momentum tensor to be conserved and compatible with cosmological observations, the vacuum energy of sufficiently heavy fields behaves at late times as non-relativistic matter rather than as a cosmological constant. In this limit, the vacuum state supports perturbations whose speed of sound is negligible and accordingly allows the growth of structures in the vacuum energy itself. This large-scale structure of vacuum could seed the formation of galaxies and clusters very much in the same way as cold dark matter does.
Growth Limits in Large Scale Networks
DEFF Research Database (Denmark)
Knudsen, Thomas Phillip
the fundamental technological resources in network technologies are analysed for scalability. Here several technological limits to continued growth are presented. The third step involves a survey of major problems in managing large scale networks given the growth of user requirements and the technological...... limitations. The rising complexity of network management with the convergence of communications platforms is shown as problematic for both automatic management feasibility and for manpower resource management. In the fourth step the scope is extended to include the present society with the DDN project as its...... main focus. Here the general perception of the nature and role in society of large scale networks as a fundamental infrastructure is analysed. This analysis focuses on the effects of the technical DDN projects and on the perception of network infrastructure as expressed by key decision makers...
Quantum Signature of Cosmological Large Scale Structures
Capozziello, S; De Siena, S; Illuminati, F; Capozziello, Salvatore; Martino, Salvatore De; Siena, Silvio De; Illuminati, Fabrizio
1998-01-01
We demonstrate that to all large scale cosmological structures where gravitation is the only overall relevant interaction assembling the system (e.g. galaxies), there is associated a characteristic unit of action per particle whose order of magnitude coincides with the Planck action constant $h$. This result extends the class of physical systems for which quantum coherence can act on macroscopic scales (as e.g. in superconductivity) and agrees with the absence of screening mechanisms for the gravitational forces, as predicted by some renormalizable quantum field theories of gravity. It also seems to support those lines of thought invoking that large scale structures in the Universe should be connected to quantum primordial perturbations as requested by inflation, that the Newton constant should vary with time and distance and, finally, that gravity should be considered as an effective interaction induced by quantization.
Process Principles for Large-Scale Nanomanufacturing.
Behrens, Sven H; Breedveld, Victor; Mujica, Maritza; Filler, Michael A
2017-06-07
Nanomanufacturing-the fabrication of macroscopic products from well-defined nanoscale building blocks-in a truly scalable and versatile manner is still far from our current reality. Here, we describe the barriers to large-scale nanomanufacturing and identify routes to overcome them. We argue for nanomanufacturing systems consisting of an iterative sequence of synthesis/assembly and separation/sorting unit operations, analogous to those used in chemicals manufacturing. In addition to performance and economic considerations, phenomena unique to the nanoscale must guide the design of each unit operation and the overall process flow. We identify and discuss four key nanomanufacturing process design needs: (a) appropriately selected process break points, (b) synthesis techniques appropriate for large-scale manufacturing, (c) new structure- and property-based separations, and (d) advances in stabilization and packaging.
Condition Monitoring of Large-Scale Facilities
Hall, David L.
1999-01-01
This document provides a summary of the research conducted for the NASA Ames Research Center under grant NAG2-1182 (Condition-Based Monitoring of Large-Scale Facilities). The information includes copies of view graphs presented at NASA Ames in the final Workshop (held during December of 1998), as well as a copy of a technical report provided to the COTR (Dr. Anne Patterson-Hine) subsequent to the workshop. The material describes the experimental design, collection of data, and analysis results associated with monitoring the health of large-scale facilities. In addition to this material, a copy of the Pennsylvania State University Applied Research Laboratory data fusion visual programming tool kit was also provided to NASA Ames researchers.
Large-scale structure of the Universe
Energy Technology Data Exchange (ETDEWEB)
Shandarin, S.F.; Doroshkevich, A.G.; Zel' dovich, Ya.B. (Inst. Prikladnoj Matematiki, Moscow, USSR)
1983-01-01
A review of theory of the large-scale structure of the Universe is given, including formation of clusters and superclusters of galaxies as well as large voids. Particular attention is paid to the theory of neutrino dominated Universe - the cosmological model where neutrinos with the rest mass of several tens eV dominate the mean density. Evolution of small perturbations is discussed, estimates of microwave backgorund radiation fluctuations is given for different angular scales. Adiabatic theory of the Universe structure formation, known as ''cake'' scenario and their successive fragmentation is given. This scenario is based on approximate nonlinear theory of gravitation instability. Results of numerical experiments, modeling the processes of large-scale structure formation are discussed.
Large-scale structure of the universe
Energy Technology Data Exchange (ETDEWEB)
Shandarin, S.F.; Doroshkevich, A.G.; Zel' dovich, Y.B.
1983-01-01
A survey is given of theories for the origin of large-scale structure in the universe: clusters and superclusters of galaxies, and vast black regions practically devoid of galaxies. Special attention is paid to the theory of a neutrino-dominated universe: a cosmology in which electron neutrinos with a rest mass of a few tens of electron volts would contribute the bulk of the mean density. The evolution of small perturbations is discussed, and estimates are made for the temperature anisotropy of the microwave background radiation on various angular scales. The nonlinear stage in the evolution of smooth irrotational perturbations in a low-pressure medium is described in detail. Numerical experiments simulating large-scale structure formation processes are discussed, as well as their interpretation in the context of catastrophe theory.
Wireless Secrecy in Large-Scale Networks
Pinto, Pedro C; Win, Moe Z
2011-01-01
The ability to exchange secret information is critical to many commercial, governmental, and military networks. The intrinsically secure communications graph (iS-graph) is a random graph which describes the connections that can be securely established over a large-scale network, by exploiting the physical properties of the wireless medium. This paper provides an overview of the main properties of this new class of random graphs. We first analyze the local properties of the iS-graph, namely the degree distributions and their dependence on fading, target secrecy rate, and eavesdropper collusion. To mitigate the effect of the eavesdroppers, we propose two techniques that improve secure connectivity. Then, we analyze the global properties of the iS-graph, namely percolation on the infinite plane, and full connectivity on a finite region. These results help clarify how the presence of eavesdroppers can compromise secure communication in a large-scale network.
Large-scale self-assembled zirconium phosphate smectic layers via a simple spray-coating process.
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
2014-04-07
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.
Measuring Bulk Flows in Large Scale Surveys
Feldman, H A; Feldman, Hume A.; Watkins, Richard
1993-01-01
We follow a formalism presented by Kaiser to calculate the variance of bulk flows in large scale surveys. We apply the formalism to a mock survey of Abell clusters \\'a la Lauer \\& Postman and find the variance in the expected bulk velocities in a universe with CDM, MDM and IRAS--QDOT power spectra. We calculate the velocity variance as a function of the 1--D velocity dispersion of the clusters and the size of the survey.
Statistical characteristics of Large Scale Structure
Demianski; Doroshkevich
2002-01-01
We investigate the mass functions of different elements of the Large Scale Structure -- walls, pancakes, filaments and clouds -- and the impact of transverse motions -- expansion and/or compression -- on their statistical characteristics. Using the Zel'dovich theory of gravitational instability we show that the mass functions of all structure elements are approximately the same and the mass of all elements is found to be concentrated near the corresponding mean mass. At high redshifts, both t...
Topologies for large scale photovoltaic power plants
Cabrera Tobar, Ana; Bullich Massagué, Eduard; Aragüés Peñalba, Mònica; Gomis Bellmunt, Oriol
2016-01-01
© 2016 Elsevier Ltd. All rights reserved. The concern of increasing renewable energy penetration into the grid together with the reduction of prices of photovoltaic solar panels during the last decade have enabled the development of large scale solar power plants connected to the medium and high voltage grid. Photovoltaic generation components, the internal layout and the ac collection grid are being investigated for ensuring the best design, operation and control of these power plants. This ...
Large-scale instabilities of helical flows
Cameron, Alexandre; Brachet, Marc-Étienne
2016-01-01
Large-scale hydrodynamic instabilities of periodic helical flows are investigated using $3$D Floquet numerical computations. A minimal three-modes analytical model that reproduce and explains some of the full Floquet results is derived. The growth-rate $\\sigma$ of the most unstable modes (at small scale, low Reynolds number $Re$ and small wavenumber $q$) is found to scale differently in the presence or absence of anisotropic kinetic alpha (\\AKA{}) effect. When an $AKA$ effect is present the scaling $\\sigma \\propto q\\; Re\\,$ predicted by the $AKA$ effect theory [U. Frisch, Z. S. She, and P. L. Sulem, Physica D: Nonlinear Phenomena 28, 382 (1987)] is recovered for $Re\\ll 1$ as expected (with most of the energy of the unstable mode concentrated in the large scales). However, as $Re$ increases, the growth-rate is found to saturate and most of the energy is found at small scales. In the absence of \\AKA{} effect, it is found that flows can still have large-scale instabilities, but with a negative eddy-viscosity sca...
Economically viable large-scale hydrogen liquefaction
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-Scale Visual Data Analysis
Johnson, Chris
2014-04-01
Modern high performance computers have speeds measured in petaflops and handle data set sizes measured in terabytes and petabytes. Although these machines offer enormous potential for solving very large-scale realistic computational problems, their effectiveness will hinge upon the ability of human experts to interact with their simulation results and extract useful information. One of the greatest scientific challenges of the 21st century is to effectively understand and make use of the vast amount of information being produced. Visual data analysis will be among our most most important tools in helping to understand such large-scale information. Our research at the Scientific Computing and Imaging (SCI) Institute at the University of Utah has focused on innovative, scalable techniques for large-scale 3D visual data analysis. In this talk, I will present state- of-the-art visualization techniques, including scalable visualization algorithms and software, cluster-based visualization methods and innovate visualization techniques applied to problems in computational science, engineering, and medicine. I will conclude with an outline for a future high performance visualization research challenges and opportunities.
Large-scale neuromorphic computing systems
Furber, Steve
2016-10-01
Neuromorphic computing covers a diverse range of approaches to information processing all of which demonstrate some degree of neurobiological inspiration that differentiates them from mainstream conventional computing systems. The philosophy behind neuromorphic computing has its origins in the seminal work carried out by Carver Mead at Caltech in the late 1980s. This early work influenced others to carry developments forward, and advances in VLSI technology supported steady growth in the scale and capability of neuromorphic devices. Recently, a number of large-scale neuromorphic projects have emerged, taking the approach to unprecedented scales and capabilities. These large-scale projects are associated with major new funding initiatives for brain-related research, creating a sense that the time and circumstances are right for progress in our understanding of information processing in the brain. In this review we present a brief history of neuromorphic engineering then focus on some of the principal current large-scale projects, their main features, how their approaches are complementary and distinct, their advantages and drawbacks, and highlight the sorts of capabilities that each can deliver to neural modellers.
Robust nonlinear PID-like fuzzy logic control of a planar parallel (2PRP-PPR) manipulator.
Londhe, P S; Singh, Yogesh; Santhakumar, M; Patre, B M; Waghmare, L M
2016-07-01
In this paper, a robust nonlinear proportional-integral-derivative (PID)-like fuzzy control scheme is presented and applied to complex trajectory tracking control of a 2PRP-PPR (P-prismatic, R-revolute) planar parallel manipulator (motion platform) with three degrees-of-freedom (DOF) in the presence of parameter uncertainties and external disturbances. The proposed control law consists of mainly two parts: first part uses a feed forward term to enhance the control activity and estimated perturbed term to compensate for the unknown effects namely external disturbances and unmodeled dynamics, and the second part uses a PID-like fuzzy logic control as a feedback portion to enhance the overall closed-loop stability of the system. Experimental results are presented to show the effectiveness of the proposed control scheme.
Energy Technology Data Exchange (ETDEWEB)
Sadjadi, Seyed Jafar [Department of Industrial Engineering, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of)], E-mail: sjsadjadi@iust.ac.ir; Soltani, R. [Department of Industrial Engineering, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of)
2009-11-15
We present a heuristic approach to solve a general framework of serial-parallel redundancy problem where the reliability of the system is maximized subject to some general linear constraints. The complexity of the redundancy problem is generally considered to be NP-Hard and the optimal solution is not normally available. Therefore, to evaluate the performance of the proposed method, a hybrid genetic algorithm is also implemented whose parameters are calibrated via Taguchi's robust design method. Then, various test problems are solved and the computational results indicate that the proposed heuristic approach could provide us some promising reliabilities, which are fairly close to optimal solutions in a reasonable amount of time.
RESTRUCTURING OF THE LARGE-SCALE SPRINKLERS
Directory of Open Access Journals (Sweden)
Paweł Kozaczyk
2016-09-01
Full Text Available One of the best ways for agriculture to become independent from shortages of precipitation is irrigation. In the seventies and eighties of the last century a number of large-scale sprinklers in Wielkopolska was built. At the end of 1970’s in the Poznan province 67 sprinklers with a total area of 6400 ha were installed. The average size of the sprinkler reached 95 ha. In 1989 there were 98 sprinklers, and the area which was armed with them was more than 10 130 ha. The study was conducted on 7 large sprinklers with the area ranging from 230 to 520 hectares in 1986÷1998. After the introduction of the market economy in the early 90’s and ownership changes in agriculture, large-scale sprinklers have gone under a significant or total devastation. Land on the State Farms of the State Agricultural Property Agency has leased or sold and the new owners used the existing sprinklers to a very small extent. This involved a change in crop structure, demand structure and an increase in operating costs. There has also been a threefold increase in electricity prices. Operation of large-scale irrigation encountered all kinds of barriers in practice and limitations of system solutions, supply difficulties, high levels of equipment failure which is not inclined to rational use of available sprinklers. An effect of a vision of the local area was to show the current status of the remaining irrigation infrastructure. The adopted scheme for the restructuring of Polish agriculture was not the best solution, causing massive destruction of assets previously invested in the sprinkler system.
Large-Scale PV Integration Study
Energy Technology Data Exchange (ETDEWEB)
Lu, Shuai; Etingov, Pavel V.; Diao, Ruisheng; Ma, Jian; Samaan, Nader A.; Makarov, Yuri V.; Guo, Xinxin; Hafen, Ryan P.; Jin, Chunlian; Kirkham, Harold; Shlatz, Eugene; Frantzis, Lisa; McClive, Timothy; Karlson, Gregory; Acharya, Dhruv; Ellis, Abraham; Stein, Joshua; Hansen, Clifford; Chadliev, Vladimir; Smart, Michael; Salgo, Richard; Sorensen, Rahn; Allen, Barbara; Idelchik, Boris
2011-07-29
This research effort evaluates the impact of large-scale photovoltaic (PV) and distributed generation (DG) output on NV Energy’s electric grid system in southern Nevada. It analyzes the ability of NV Energy’s generation to accommodate increasing amounts of utility-scale PV and DG, and the resulting cost of integrating variable renewable resources. The study was jointly funded by the United States Department of Energy and NV Energy, and conducted by a project team comprised of industry experts and research scientists from Navigant Consulting Inc., Sandia National Laboratories, Pacific Northwest National Laboratory and NV Energy.
Conformal Anomaly and Large Scale Gravitational Coupling
Salehi, H
2000-01-01
We present a model in which the breackdown of conformal symmetry of a quantum stress-tensor due to the trace anomaly is related to a cosmological effect in a gravitational model. This is done by characterizing the traceless part of the quantum stress-tensor in terms of the stress-tensor of a conformal invariant classical scalar field. We introduce a conformal frame in which the anomalous trace is identified with a cosmological constant. In this conformal frame we establish the Einstein field equations by connecting the quantum stress-tensor with the large scale distribution of matter in the universe.
Large Scale Quantum Simulations of Nuclear Pasta
Fattoyev, Farrukh J.; Horowitz, Charles J.; Schuetrumpf, Bastian
2016-03-01
Complex and exotic nuclear geometries collectively referred to as ``nuclear pasta'' are expected to naturally exist in the crust of neutron stars and in supernovae matter. Using a set of self-consistent microscopic nuclear energy density functionals we present the first results of large scale quantum simulations of pasta phases at baryon densities 0 . 03 pasta configurations. This work is supported in part by DOE Grants DE-FG02-87ER40365 (Indiana University) and DE-SC0008808 (NUCLEI SciDAC Collaboration).
Large scale wind power penetration in Denmark
DEFF Research Database (Denmark)
Karnøe, Peter
2013-01-01
he Danish electricity generating system prepared to adopt nuclear power in the 1970s, yet has become the world's front runner in wind power with a national plan for 50% wind power penetration by 2020. This paper deploys a sociotechnical perspective to explain the historical transformation of "net...... expertise evolves and contributes to the normalization and large-scale penetration of wind power in the electricity generating system. The analysis teaches us how technological paths become locked-in, but also indicates keys for locking them out....
Stabilization Algorithms for Large-Scale Problems
DEFF Research Database (Denmark)
Jensen, Toke Koldborg
2006-01-01
The focus of the project is on stabilization of large-scale inverse problems where structured models and iterative algorithms are necessary for computing approximate solutions. For this purpose, we study various iterative Krylov methods and their abilities to produce regularized solutions. Some......-curve. This heuristic is implemented as a part of a larger algorithm which is developed in collaboration with G. Rodriguez and P. C. Hansen. Last, but not least, a large part of the project has, in different ways, revolved around the object-oriented Matlab toolbox MOORe Tools developed by PhD Michael Jacobsen. New...
Nigro, G.; Pongkitiwanichakul, P.; Cattaneo, F.; Tobias, S. M.
2017-01-01
We consider kinematic dynamo action in a sheared helical flow at moderate to high values of the magnetic Reynolds number (Rm). We find exponentially growing solutions which, for large enough shear, take the form of a coherent part embedded in incoherent fluctuations. We argue that at large Rm large-scale dynamo action should be identified by the presence of structures coherent in time, rather than those at large spatial scales. We further argue that although the growth rate is determined by small-scale processes, the period of the coherent structures is set by mean-field considerations.
Large scale phononic metamaterials for seismic isolation
Energy Technology Data Exchange (ETDEWEB)
Aravantinos-Zafiris, N. [Department of Sound and Musical Instruments Technology, Ionian Islands Technological Educational Institute, Stylianou Typaldou ave., Lixouri 28200 (Greece); Sigalas, M. M. [Department of Materials Science, University of Patras, Patras 26504 (Greece)
2015-08-14
In this work, we numerically examine structures that could be characterized as large scale phononic metamaterials. These novel structures could have band gaps in the frequency spectrum of seismic waves when their dimensions are chosen appropriately, thus raising the belief that they could be serious candidates for seismic isolation structures. Different and easy to fabricate structures were examined made from construction materials such as concrete and steel. The well-known finite difference time domain method is used in our calculations in order to calculate the band structures of the proposed metamaterials.
Hiearchical Engine for Large Scale Infrastructure Simulation
Energy Technology Data Exchange (ETDEWEB)
2017-03-15
HELICS ls a new open-source, cyber-physlcal-energy co-simulation framework for electric power systems. HELICS Is designed to support very-large-scale (100,000+ federates) cosimulations with off-the-shelf power-system, communication, market, and end-use tools. Other key features Include cross platform operating system support, the integration of both eventdrlven (e.g., packetlzed communication) and time-series (e.g.,power flow) simulations, and the ability to co-Iterate among federates to ensure physical model convergence at each time step.
Colloquium: Large scale simulations on GPU clusters
Bernaschi, Massimo; Bisson, Mauro; Fatica, Massimiliano
2015-06-01
Graphics processing units (GPU) are currently used as a cost-effective platform for computer simulations and big-data processing. Large scale applications require that multiple GPUs work together but the efficiency obtained with cluster of GPUs is, at times, sub-optimal because the GPU features are not exploited at their best. We describe how it is possible to achieve an excellent efficiency for applications in statistical mechanics, particle dynamics and networks analysis by using suitable memory access patterns and mechanisms like CUDA streams, profiling tools, etc. Similar concepts and techniques may be applied also to other problems like the solution of Partial Differential Equations.
Internationalization Measures in Large Scale Research Projects
Soeding, Emanuel; Smith, Nancy
2017-04-01
Internationalization measures in Large Scale Research Projects Large scale research projects (LSRP) often serve as flagships used by universities or research institutions to demonstrate their performance and capability to stakeholders and other interested parties. As the global competition among universities for the recruitment of the brightest brains has increased, effective internationalization measures have become hot topics for universities and LSRP alike. Nevertheless, most projects and universities are challenged with little experience on how to conduct these measures and make internationalization an cost efficient and useful activity. Furthermore, those undertakings permanently have to be justified with the Project PIs as important, valuable tools to improve the capacity of the project and the research location. There are a variety of measures, suited to support universities in international recruitment. These include e.g. institutional partnerships, research marketing, a welcome culture, support for science mobility and an effective alumni strategy. These activities, although often conducted by different university entities, are interlocked and can be very powerful measures if interfaced in an effective way. On this poster we display a number of internationalization measures for various target groups, identify interfaces between project management, university administration, researchers and international partners to work together, exchange information and improve processes in order to be able to recruit, support and keep the brightest heads to your project.
Large-scale Globally Propagating Coronal Waves
Directory of Open Access Journals (Sweden)
Alexander Warmuth
2015-09-01
Full Text Available Large-scale, globally propagating wave-like disturbances have been observed in the solar chromosphere and by inference in the corona since the 1960s. However, detailed analysis of these phenomena has only been conducted since the late 1990s. This was prompted by the availability of high-cadence coronal imaging data from numerous spaced-based instruments, which routinely show spectacular globally propagating bright fronts. Coronal waves, as these perturbations are usually referred to, have now been observed in a wide range of spectral channels, yielding a wealth of information. Many findings have supported the “classical” interpretation of the disturbances: fast-mode MHD waves or shocks that are propagating in the solar corona. However, observations that seemed inconsistent with this picture have stimulated the development of alternative models in which “pseudo waves” are generated by magnetic reconfiguration in the framework of an expanding coronal mass ejection. This has resulted in a vigorous debate on the physical nature of these disturbances. This review focuses on demonstrating how the numerous observational findings of the last one and a half decades can be used to constrain our models of large-scale coronal waves, and how a coherent physical understanding of these disturbances is finally emerging.
Directory of Open Access Journals (Sweden)
Guohua Cui
2015-01-01
Full Text Available This paper proposes a redundantly actuated parallel manipulator 4-UPS-S that is applicable for orientation adjustment in the gathering process of solar power. A thorough analysis involving the kinematic issues is performed. Inverse kinematic problems are solved in the close-loop. The Jacobian matrix and some performance indexes are analytically derived. The multiobjective optimization model is established, and the determinacy optimization is completed on the basis of previous research works. Six-Sigma robust analysis is performed on the basis of the determinacy optimal solution. Results show that 4-UPS-S does not satisfy the quality requirement. Therefore, it is necessary to implement Six-Sigma robust optimization, and select optimial solution of robustness to complete the nondeterminacy optimization. The research results show that the proposed methodology has a simple operation and high optimization efficiency. The methodology commodiously obtains robustness parallel manipulator that satisfies the quality requirement.
LARGE-SCALE CO2 TRANSPORTATION AND DEEP OCEAN SEQUESTRATION
Energy Technology Data Exchange (ETDEWEB)
Hamid Sarv
1999-03-01
Technical and economical feasibility of large-scale CO{sub 2} transportation and ocean sequestration at depths of 3000 meters or grater was investigated. Two options were examined for transporting and disposing the captured CO{sub 2}. In one case, CO{sub 2} was pumped from a land-based collection center through long pipelines laid on the ocean floor. Another case considered oceanic tanker transport of liquid carbon dioxide to an offshore floating structure for vertical injection to the ocean floor. In the latter case, a novel concept based on subsurface towing of a 3000-meter pipe, and attaching it to the offshore structure was considered. Budgetary cost estimates indicate that for distances greater than 400 km, tanker transportation and offshore injection through a 3000-meter vertical pipe provides the best method for delivering liquid CO{sub 2} to deep ocean floor depressions. For shorter distances, CO{sub 2} delivery by parallel-laid, subsea pipelines is more cost-effective. Estimated costs for 500-km transport and storage at a depth of 3000 meters by subsea pipelines and tankers were 1.5 and 1.4 dollars per ton of stored CO{sub 2}, respectively. At these prices, economics of ocean disposal are highly favorable. Future work should focus on addressing technical issues that are critical to the deployment of a large-scale CO{sub 2} transportation and disposal system. Pipe corrosion, structural design of the transport pipe, and dispersion characteristics of sinking CO{sub 2} effluent plumes have been identified as areas that require further attention. Our planned activities in the next Phase include laboratory-scale corrosion testing, structural analysis of the pipeline, analytical and experimental simulations of CO{sub 2} discharge and dispersion, and the conceptual economic and engineering evaluation of large-scale implementation.
Statistical Modeling of Large-Scale Scientific Simulation Data
Energy Technology Data Exchange (ETDEWEB)
Eliassi-Rad, T; Baldwin, C; Abdulla, G; Critchlow, T
2003-11-15
With the advent of massively parallel computer systems, scientists are now able to simulate complex phenomena (e.g., explosions of a stars). Such scientific simulations typically generate large-scale data sets over the spatio-temporal space. Unfortunately, the sheer sizes of the generated data sets make efficient exploration of them impossible. Constructing queriable statistical models is an essential step in helping scientists glean new insight from their computer simulations. We define queriable statistical models to be descriptive statistics that (1) summarize and describe the data within a user-defined modeling error, and (2) are able to answer complex range-based queries over the spatiotemporal dimensions. In this chapter, we describe systems that build queriable statistical models for large-scale scientific simulation data sets. In particular, we present our Ad-hoc Queries for Simulation (AQSim) infrastructure, which reduces the data storage requirements and query access times by (1) creating and storing queriable statistical models of the data at multiple resolutions, and (2) evaluating queries on these models of the data instead of the entire data set. Within AQSim, we focus on three simple but effective statistical modeling techniques. AQSim's first modeling technique (called univariate mean modeler) computes the ''true'' (unbiased) mean of systematic partitions of the data. AQSim's second statistical modeling technique (called univariate goodness-of-fit modeler) uses the Andersen-Darling goodness-of-fit method on systematic partitions of the data. Finally, AQSim's third statistical modeling technique (called multivariate clusterer) utilizes the cosine similarity measure to cluster the data into similar groups. Our experimental evaluations on several scientific simulation data sets illustrate the value of using these statistical models on large-scale simulation data sets.
Large-Scale Astrophysical Visualization on Smartphones
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.
Clumps in large scale relativistic jets
Tavecchio, F; Celotti, A
2003-01-01
The relatively intense X-ray emission from large scale (tens to hundreds kpc) jets discovered with Chandra likely implies that jets (at least in powerful quasars) are still relativistic at that distances from the active nucleus. In this case the emission is due to Compton scattering off seed photons provided by the Cosmic Microwave Background, and this on one hand permits to have magnetic fields close to equipartition with the emitting particles, and on the other hand minimizes the requirements about the total power carried by the jet. The emission comes from compact (kpc scale) knots, and we here investigate what we can predict about the possible emission between the bright knots. This is motivated by the fact that bulk relativistic motion makes Compton scattering off the CMB photons efficient even when electrons are cold or mildly relativistic in the comoving frame. This implies relatively long cooling times, dominated by adiabatic losses. Therefore the relativistically moving plasma can emit, by Compton sc...
Large-scale parametric survival analysis.
Mittal, Sushil; Madigan, David; Cheng, Jerry Q; Burd, Randall S
2013-10-15
Survival analysis has been a topic of active statistical research in the past few decades with applications spread across several areas. Traditional applications usually consider data with only a small numbers of predictors with a few hundreds or thousands of observations. Recent advances in data acquisition techniques and computation power have led to considerable interest in analyzing very-high-dimensional data where the number of predictor variables and the number of observations range between 10(4) and 10(6). In this paper, we present a tool for performing large-scale regularized parametric survival analysis using a variant of the cyclic coordinate descent method. Through our experiments on two real data sets, we show that application of regularized models to high-dimensional data avoids overfitting and can provide improved predictive performance and calibration over corresponding low-dimensional models.
Curvature constraints from Large Scale Structure
Di Dio, Enea; Raccanelli, Alvise; Durrer, Ruth; Kamionkowski, Marc; Lesgourgues, Julien
2016-01-01
We modified the CLASS code in order to include relativistic galaxy number counts in spatially curved geometries; we present the formalism and study the effect of relativistic corrections on spatial curvature. The new version of the code is now publicly available. Using a Fisher matrix analysis, we investigate how measurements of the spatial curvature parameter $\\Omega_K$ with future galaxy surveys are affected by relativistic effects, which influence observations of the large scale galaxy distribution. These effects include contributions from cosmic magnification, Doppler terms and terms involving the gravitational potential. As an application, we consider angle and redshift dependent power spectra, which are especially well suited for model independent cosmological constraints. We compute our results for a representative deep, wide and spectroscopic survey, and our results show the impact of relativistic corrections on the spatial curvature parameter estimation. We show that constraints on the curvature para...
Large-scale simulations of reionization
Energy Technology Data Exchange (ETDEWEB)
Kohler, Katharina; /JILA, Boulder /Fermilab; Gnedin, Nickolay Y.; /Fermilab; Hamilton, Andrew J.S.; /JILA, Boulder
2005-11-01
We use cosmological simulations to explore the large-scale effects of reionization. Since reionization is a process that involves a large dynamic range--from galaxies to rare bright quasars--we need to be able to cover a significant volume of the universe in our simulation without losing the important small scale effects from galaxies. Here we have taken an approach that uses clumping factors derived from small scale simulations to approximate the radiative transfer on the sub-cell scales. Using this technique, we can cover a simulation size up to 1280h{sup -1} Mpc with 10h{sup -1} Mpc cells. This allows us to construct synthetic spectra of quasars similar to observed spectra of SDSS quasars at high redshifts and compare them to the observational data. These spectra can then be analyzed for HII region sizes, the presence of the Gunn-Peterson trough, and the Lyman-{alpha} forest.
Large-Scale Tides in General Relativity
Ip, Hiu Yan
2016-01-01
Density perturbations in cosmology, i.e. spherically symmetric adiabatic perturbations of a Friedmann-Lema\\^itre-Robertson-Walker (FLRW) spacetime, are locally exactly equivalent to a different FLRW solution, as long as their wavelength is much larger than the sound horizon of all fluid components. This fact is known as the "separate universe" paradigm. However, no such relation is known for anisotropic adiabatic perturbations, which correspond to an FLRW spacetime with large-scale tidal fields. Here, we provide a closed, fully relativistic set of evolutionary equations for the nonlinear evolution of such modes, based on the conformal Fermi (CFC) frame. We show explicitly that the tidal effects are encoded by the Weyl tensor, and are hence entirely different from an anisotropic Bianchi I spacetime, where the anisotropy is sourced by the Ricci tensor. In order to close the system, certain higher derivative terms have to be dropped. We show that this approximation is equivalent to the local tidal approximation ...
Grid sensitivity capability for large scale structures
Nagendra, Gopal K.; Wallerstein, David V.
1989-01-01
The considerations and the resultant approach used to implement design sensitivity capability for grids into a large scale, general purpose finite element system (MSC/NASTRAN) are presented. The design variables are grid perturbations with a rather general linking capability. Moreover, shape and sizing variables may be linked together. The design is general enough to facilitate geometric modeling techniques for generating design variable linking schemes in an easy and straightforward manner. Test cases have been run and validated by comparison with the overall finite difference method. The linking of a design sensitivity capability for shape variables in MSC/NASTRAN with an optimizer would give designers a powerful, automated tool to carry out practical optimization design of real life, complicated structures.
Large scale water lens for solar concentration.
Mondol, A S; Vogel, B; Bastian, G
2015-06-01
Properties of large scale water lenses for solar concentration were investigated. These lenses were built from readily available materials, normal tap water and hyper-elastic linear low density polyethylene foil. Exposed to sunlight, the focal lengths and light intensities in the focal spot were measured and calculated. Their optical properties were modeled with a raytracing software based on the lens shape. We have achieved a good match of experimental and theoretical data by considering wavelength dependent concentration factor, absorption and focal length. The change in light concentration as a function of water volume was examined via the resulting load on the foil and the corresponding change of shape. The latter was extracted from images and modeled by a finite element simulation.
Constructing sites on a large scale
DEFF Research Database (Denmark)
Braae, Ellen Marie; Tietjen, Anne
2011-01-01
for setting the design brief in a large scale urban landscape in Norway, the Jaeren region around the city of Stavanger. In this paper, we first outline the methodological challenges and then present and discuss the proposed method based on our teaching experiences. On this basis, we discuss aspects...... within the development of our urban landscapes. At the same time, urban and landscape designers are confronted with new methodological problems. Within a strategic transformation perspective, the formulation of the design problem or brief becomes an integrated part of the design process. This paper...... discusses new design (education) methods based on a relational concept of urban sites and design processes. Within this logic site survey is not simply a pre-design activity nor is it a question of comprehensive analysis. Site survey is an integrated part of the design process. By means of active site...
Supporting large-scale computational science
Energy Technology Data Exchange (ETDEWEB)
Musick, R
1998-10-01
A study has been carried out to determine the feasibility of using commercial database management systems (DBMSs) to support large-scale computational science. Conventional wisdom in the past has been that DBMSs are too slow for such data. Several events over the past few years have muddied the clarity of this mindset: 1. 2. 3. 4. Several commercial DBMS systems have demonstrated storage and ad-hoc quer access to Terabyte data sets. Several large-scale science teams, such as EOSDIS [NAS91], high energy physics [MM97] and human genome [Kin93] have adopted (or make frequent use of) commercial DBMS systems as the central part of their data management scheme. Several major DBMS vendors have introduced their first object-relational products (ORDBMSs), which have the potential to support large, array-oriented data. In some cases, performance is a moot issue. This is true in particular if the performance of legacy applications is not reduced while new, albeit slow, capabilities are added to the system. The basic assessment is still that DBMSs do not scale to large computational data. However, many of the reasons have changed, and there is an expiration date attached to that prognosis. This document expands on this conclusion, identifies the advantages and disadvantages of various commercial approaches, and describes the studies carried out in exploring this area. The document is meant to be brief, technical and informative, rather than a motivational pitch. The conclusions within are very likely to become outdated within the next 5-7 years, as market forces will have a significant impact on the state of the art in scientific data management over the next decade.
Introducing Large-Scale Innovation in Schools
Sotiriou, Sofoklis; Riviou, Katherina; Cherouvis, Stephanos; Chelioti, Eleni; Bogner, Franz X.
2016-08-01
Education reform initiatives tend to promise higher effectiveness in classrooms especially when emphasis is given to e-learning and digital resources. Practical changes in classroom realities or school organization, however, are lacking. A major European initiative entitled Open Discovery Space (ODS) examined the challenge of modernizing school education via a large-scale implementation of an open-scale methodology in using technology-supported innovation. The present paper describes this innovation scheme which involved schools and teachers all over Europe, embedded technology-enhanced learning into wider school environments and provided training to teachers. Our implementation scheme consisted of three phases: (1) stimulating interest, (2) incorporating the innovation into school settings and (3) accelerating the implementation of the innovation. The scheme's impact was monitored for a school year using five indicators: leadership and vision building, ICT in the curriculum, development of ICT culture, professional development support, and school resources and infrastructure. Based on about 400 schools, our study produced four results: (1) The growth in digital maturity was substantial, even for previously high scoring schools. This was even more important for indicators such as vision and leadership" and "professional development." (2) The evolution of networking is presented graphically, showing the gradual growth of connections achieved. (3) These communities became core nodes, involving numerous teachers in sharing educational content and experiences: One out of three registered users (36 %) has shared his/her educational resources in at least one community. (4) Satisfaction scores ranged from 76 % (offer of useful support through teacher academies) to 87 % (good environment to exchange best practices). Initiatives such as ODS add substantial value to schools on a large scale.
Large-scale sequential quadratic programming algorithms
Energy Technology Data Exchange (ETDEWEB)
Eldersveld, S.K.
1992-09-01
The problem addressed is the general nonlinear programming problem: finding a local minimizer for a nonlinear function subject to a mixture of nonlinear equality and inequality constraints. The methods studied are in the class of sequential quadratic programming (SQP) algorithms, which have previously proved successful for problems of moderate size. Our goal is to devise an SQP algorithm that is applicable to large-scale optimization problems, using sparse data structures and storing less curvature information but maintaining the property of superlinear convergence. The main features are: 1. The use of a quasi-Newton approximation to the reduced Hessian of the Lagrangian function. Only an estimate of the reduced Hessian matrix is required by our algorithm. The impact of not having available the full Hessian approximation is studied and alternative estimates are constructed. 2. The use of a transformation matrix Q. This allows the QP gradient to be computed easily when only the reduced Hessian approximation is maintained. 3. The use of a reduced-gradient form of the basis for the null space of the working set. This choice of basis is more practical than an orthogonal null-space basis for large-scale problems. The continuity condition for this choice is proven. 4. The use of incomplete solutions of quadratic programming subproblems. Certain iterates generated by an active-set method for the QP subproblem are used in place of the QP minimizer to define the search direction for the nonlinear problem. An implementation of the new algorithm has been obtained by modifying the code MINOS. Results and comparisons with MINOS and NPSOL are given for the new algorithm on a set of 92 test problems.
A Large-Scale 3D Object Recognition dataset
DEFF Research Database (Denmark)
Sølund, Thomas; Glent Buch, Anders; Krüger, Norbert
2016-01-01
This paper presents a new large scale dataset targeting evaluation of local shape descriptors and 3d object recognition algorithms. The dataset consists of point clouds and triangulated meshes from 292 physical scenes taken from 11 different views; a total of approximately 3204 views. Each...... geometric groups; concave, convex, cylindrical and flat 3D object models. The object models have varying amount of local geometric features to challenge existing local shape feature descriptors in terms of descriptiveness and robustness. The dataset is validated in a benchmark which evaluates the matching...... performance of 7 different state-of-the-art local shape descriptors. Further, we validate the dataset in a 3D object recognition pipeline. Our benchmark shows as expected that local shape feature descriptors without any global point relation across the surface have a poor matching performance with flat...
Synchronization control for large-scale network systems
Wu, Yuanqing; Su, Hongye; Shi, Peng; Wu, Zheng-Guang
2017-01-01
This book provides recent advances in analysis and synthesis of Large-scale network systems (LSNSs) with sampled-data communication and non-identical nodes. In its first chapter of the book presents an introduction to Synchronization of LSNSs and Algebraic Graph Theory as well as an overview of recent developments of LSNSs with sampled data control or output regulation control. The main text of the book is organized into two main parts - Part I: LSNSs with sampled-data communication and Part II: LSNSs with non-identical nodes. This monograph provides up-to-date advances and some recent developments in the analysis and synthesis issues for LSNSs with sampled-data communication and non-identical nodes. It describes the constructions of the adaptive reference generators in the first stage and the robust regulators in the second stage. Examples are presented to show the effectiveness of the proposed design techniques.
Large scale simulations of the great 1906 San Francisco earthquake
Nilsson, S.; Petersson, A.; Rodgers, A.; Sjogreen, B.; McCandless, K.
2006-12-01
As part of a multi-institutional simulation effort, we present large scale computations of the ground motion during the great 1906 San Francisco earthquake using a new finite difference code called WPP. The material data base for northern California provided by USGS together with the rupture model by Song et al. is demonstrated to lead to a reasonable match with historical data. In our simulations, the computational domain covered 550 km by 250 km of northern California down to 40 km depth, so a 125 m grid size corresponds to about 2.2 Billion grid points. To accommodate these large grids, the simulations were run on 512-1024 processors on one of the supercomputers at Lawrence Livermore National Lab. A wavelet compression algorithm enabled storage of time-dependent volumetric data. Nevertheless, the first 45 seconds of the earthquake still generated 1.2 TByte of disk space and the 3-D post processing was done in parallel.
Planning under uncertainty solving large-scale stochastic linear programs
Energy Technology Data Exchange (ETDEWEB)
Infanger, G. (Stanford Univ., CA (United States). Dept. of Operations Research Technische Univ., Vienna (Austria). Inst. fuer Energiewirtschaft)
1992-12-01
For many practical problems, solutions obtained from deterministic models are unsatisfactory because they fail to hedge against certain contingencies that may occur in the future. Stochastic models address this shortcoming, but up to recently seemed to be intractable due to their size. Recent advances both in solution algorithms and in computer technology now allow us to solve important and general classes of practical stochastic problems. We show how large-scale stochastic linear programs can be efficiently solved by combining classical decomposition and Monte Carlo (importance) sampling techniques. We discuss the methodology for solving two-stage stochastic linear programs with recourse, present numerical results of large problems with numerous stochastic parameters, show how to efficiently implement the methodology on a parallel multi-computer and derive the theory for solving a general class of multi-stage problems with dependency of the stochastic parameters within a stage and between different stages.
Large scale stochastic spatio-temporal modelling with PCRaster
Karssenberg, Derek; Drost, Niels; Schmitz, Oliver; de Jong, Kor; Bierkens, Marc F. P.
2013-04-01
software from the eScience Technology Platform (eSTeP), developed at the Netherlands eScience Center. This will allow us to scale up to hundreds of machines, with thousands of compute cores. A key requirement is not to change the user experience of the software. PCRaster operations and the use of the Python framework classes should work in a similar manner on machines ranging from a laptop to a supercomputer. This enables a seamless transfer of models from small machines, where model development is done, to large machines used for large-scale model runs. Domain specialists from a large range of disciplines, including hydrology, ecology, sedimentology, and land use change studies, currently use the PCRaster Python software within research projects. Applications include global scale hydrological modelling and error propagation in large-scale land use change models. The software runs on MS Windows, Linux operating systems, and OS X.
High speed and large scale scientific computing
Gentzsch, W; Joubert, GR
2010-01-01
Over the years parallel technologies have completely transformed main stream computing. This book deals with the issues related to the area of cloud computing and discusses developments in grids, applications and information processing, as well as e-science. It is suitable for computer scientists, IT engineers and IT managers.
Cold flows and large scale tides
van de Weygaert, R.; Hoffman, Y.
1999-01-01
Within the context of the general cosmological setting it has remained puzzling that the local Universe is a relatively cold environment, in the sense of small-scale peculiar velocities being relatively small. Indeed, it has since long figured as an important argument for the Universe having a low Ω, or if the Universe were to have a high Ω for the existence of a substantial bias between the galaxy and the matter distribution. Here we investigate the dynamical impact of neighbouring matter concentrations on local small-scale characteristics of cosmic flows. While regions where huge nearby matter clumps represent a dominating component in the local dynamics and kinematics may experience a faster collapse on behalf of the corresponding tidal influence, the latter will also slow down or even prevent a thorough mixing and virialization of the collapsing region. By means of N-body simulations starting from constrained realizations of regions of modest density surrounded by more pronounced massive structures, we have explored the extent to which the large scale tidal fields may indeed suppress the `heating' of the small-scale cosmic velocities. Amongst others we quantify the resulting cosmic flows through the cosmic Mach number. This allows us to draw conclusions about the validity of estimates of global cosmological parameters from local cosmic phenomena and the necessity to take into account the structure and distribution of mass in the local Universe.
Large scale mechanical metamaterials as seismic shields
Miniaci, Marco; Krushynska, Anastasiia; Bosia, Federico; Pugno, Nicola M.
2016-08-01
Earthquakes represent one of the most catastrophic natural events affecting mankind. At present, a universally accepted risk mitigation strategy for seismic events remains to be proposed. Most approaches are based on vibration isolation of structures rather than on the remote shielding of incoming waves. In this work, we propose a novel approach to the problem and discuss the feasibility of a passive isolation strategy for seismic waves based on large-scale mechanical metamaterials, including for the first time numerical analysis of both surface and guided waves, soil dissipation effects, and adopting a full 3D simulations. The study focuses on realistic structures that can be effective in frequency ranges of interest for seismic waves, and optimal design criteria are provided, exploring different metamaterial configurations, combining phononic crystals and locally resonant structures and different ranges of mechanical properties. Dispersion analysis and full-scale 3D transient wave transmission simulations are carried out on finite size systems to assess the seismic wave amplitude attenuation in realistic conditions. Results reveal that both surface and bulk seismic waves can be considerably attenuated, making this strategy viable for the protection of civil structures against seismic risk. The proposed remote shielding approach could open up new perspectives in the field of seismology and in related areas of low-frequency vibration damping or blast protection.
Large-scale autostereoscopic outdoor display
Reitterer, Jörg; Fidler, Franz; Saint Julien-Wallsee, Ferdinand; Schmid, Gerhard; Gartner, Wolfgang; Leeb, Walter; Schmid, Ulrich
2013-03-01
State-of-the-art autostereoscopic displays are often limited in size, effective brightness, number of 3D viewing zones, and maximum 3D viewing distances, all of which are mandatory requirements for large-scale outdoor displays. Conventional autostereoscopic indoor concepts like lenticular lenses or parallax barriers cannot simply be adapted for these screens due to the inherent loss of effective resolution and brightness, which would reduce both image quality and sunlight readability. We have developed a modular autostereoscopic multi-view laser display concept with sunlight readable effective brightness, theoretically up to several thousand 3D viewing zones, and maximum 3D viewing distances of up to 60 meters. For proof-of-concept purposes a prototype display with two pixels was realized. Due to various manufacturing tolerances each individual pixel has slightly different optical properties, and hence the 3D image quality of the display has to be calculated stochastically. In this paper we present the corresponding stochastic model, we evaluate the simulation and measurement results of the prototype display, and we calculate the achievable autostereoscopic image quality to be expected for our concept.
Management of large-scale multimedia conferencing
Cidon, Israel; Nachum, Youval
1998-12-01
The goal of this work is to explore management strategies and algorithms for large-scale multimedia conferencing over a communication network. Since the use of multimedia conferencing is still limited, the management of such systems has not yet been studied in depth. A well organized and human friendly multimedia conference management should utilize efficiently and fairly its limited resources as well as take into account the requirements of the conference participants. The ability of the management to enforce fair policies and to quickly take into account the participants preferences may even lead to a conference environment that is more pleasant and more effective than a similar face to face meeting. We suggest several principles for defining and solving resource sharing problems in this context. The conference resources which are addressed in this paper are the bandwidth (conference network capacity), time (participants' scheduling) and limitations of audio and visual equipment. The participants' requirements for these resources are defined and translated in terms of Quality of Service requirements and the fairness criteria.
Large-scale wind turbine structures
Spera, David A.
1988-01-01
The purpose of this presentation is to show how structural technology was applied in the design of modern wind turbines, which were recently brought to an advanced stage of development as sources of renewable power. Wind turbine structures present many difficult problems because they are relatively slender and flexible; subject to vibration and aeroelastic instabilities; acted upon by loads which are often nondeterministic; operated continuously with little maintenance in all weather; and dominated by life-cycle cost considerations. Progress in horizontal-axis wind turbines (HAWT) development was paced by progress in the understanding of structural loads, modeling of structural dynamic response, and designing of innovative structural response. During the past 15 years a series of large HAWTs was developed. This has culminated in the recent completion of the world's largest operating wind turbine, the 3.2 MW Mod-5B power plane installed on the island of Oahu, Hawaii. Some of the applications of structures technology to wind turbine will be illustrated by referring to the Mod-5B design. First, a video overview will be presented to provide familiarization with the Mod-5B project and the important components of the wind turbine system. Next, the structural requirements for large-scale wind turbines will be discussed, emphasizing the difficult fatigue-life requirements. Finally, the procedures used to design the structure will be presented, including the use of the fracture mechanics approach for determining allowable fatigue stresses.
Large-scale tides in general relativity
Ip, Hiu Yan; Schmidt, Fabian
2017-02-01
Density perturbations in cosmology, i.e. spherically symmetric adiabatic perturbations of a Friedmann-Lemaȋtre-Robertson-Walker (FLRW) spacetime, are locally exactly equivalent to a different FLRW solution, as long as their wavelength is much larger than the sound horizon of all fluid components. This fact is known as the "separate universe" paradigm. However, no such relation is known for anisotropic adiabatic perturbations, which correspond to an FLRW spacetime with large-scale tidal fields. Here, we provide a closed, fully relativistic set of evolutionary equations for the nonlinear evolution of such modes, based on the conformal Fermi (CFC) frame. We show explicitly that the tidal effects are encoded by the Weyl tensor, and are hence entirely different from an anisotropic Bianchi I spacetime, where the anisotropy is sourced by the Ricci tensor. In order to close the system, certain higher derivative terms have to be dropped. We show that this approximation is equivalent to the local tidal approximation of Hui and Bertschinger [1]. We also show that this very simple set of equations matches the exact evolution of the density field at second order, but fails at third and higher order. This provides a useful, easy-to-use framework for computing the fully relativistic growth of structure at second order.
Large scale probabilistic available bandwidth estimation
Thouin, Frederic; Rabbat, Michael
2010-01-01
The common utilization-based definition of available bandwidth and many of the existing tools to estimate it suffer from several important weaknesses: i) most tools report a point estimate of average available bandwidth over a measurement interval and do not provide a confidence interval; ii) the commonly adopted models used to relate the available bandwidth metric to the measured data are invalid in almost all practical scenarios; iii) existing tools do not scale well and are not suited to the task of multi-path estimation in large-scale networks; iv) almost all tools use ad-hoc techniques to address measurement noise; and v) tools do not provide enough flexibility in terms of accuracy, overhead, latency and reliability to adapt to the requirements of various applications. In this paper we propose a new definition for available bandwidth and a novel framework that addresses these issues. We define probabilistic available bandwidth (PAB) as the largest input rate at which we can send a traffic flow along a pa...
Gravitational redshifts from large-scale structure
Croft, Rupert A C
2013-01-01
The recent measurement of the gravitational redshifts of galaxies in galaxy clusters by Wojtak et al. has opened a new observational window on dark matter and modified gravity. By stacking clusters this determination effectively used the line of sight distortion of the cross-correlation function of massive galaxies and lower mass galaxies to estimate the gravitational redshift profile of clusters out to 4 Mpc/h. Here we use a halo model of clustering to predict the distortion due to gravitational redshifts of the cross-correlation function on scales from 1 - 100 Mpc/h. We compare our predictions to simulations and use the simulations to make mock catalogues relevant to current and future galaxy redshift surveys. Without formulating an optimal estimator, we find that the full BOSS survey should be able to detect gravitational redshifts from large-scale structure at the ~4 sigma level. Upcoming redshift surveys will greatly increase the number of galaxies useable in such studies and the BigBOSS and Euclid exper...
Food appropriation through large scale land acquisitions
Rulli, Maria Cristina; D'Odorico, Paolo
2014-05-01
The increasing demand for agricultural products and the uncertainty of international food markets has recently drawn the attention of governments and agribusiness firms toward investments in productive agricultural land, mostly in the developing world. The targeted countries are typically located in regions that have remained only marginally utilized because of lack of modern technology. It is expected that in the long run large scale land acquisitions (LSLAs) for commercial farming will bring the technology required to close the existing crops yield gaps. While the extent of the acquired land and the associated appropriation of freshwater resources have been investigated in detail, the amount of food this land can produce and the number of people it could feed still need to be quantified. Here we use a unique dataset of land deals to provide a global quantitative assessment of the rates of crop and food appropriation potentially associated with LSLAs. We show how up to 300-550 million people could be fed by crops grown in the acquired land, should these investments in agriculture improve crop production and close the yield gap. In contrast, about 190-370 million people could be supported by this land without closing of the yield gap. These numbers raise some concern because the food produced in the acquired land is typically exported to other regions, while the target countries exhibit high levels of malnourishment. Conversely, if used for domestic consumption, the crops harvested in the acquired land could ensure food security to the local populations.
Large-scale clustering of cosmic voids
Chan, Kwan Chuen; Hamaus, Nico; Desjacques, Vincent
2014-11-01
We study the clustering of voids using N -body simulations and simple theoretical models. The excursion-set formalism describes fairly well the abundance of voids identified with the watershed algorithm, although the void formation threshold required is quite different from the spherical collapse value. The void cross bias bc is measured and its large-scale value is found to be consistent with the peak background split results. A simple fitting formula for bc is found. We model the void auto-power spectrum taking into account the void biasing and exclusion effect. A good fit to the simulation data is obtained for voids with radii ≳30 Mpc h-1 , especially when the void biasing model is extended to 1-loop order. However, the best-fit bias parameters do not agree well with the peak-background results. Being able to fit the void auto-power spectrum is particularly important not only because it is the direct observable in galaxy surveys, but also our method enables us to treat the bias parameters as nuisance parameters, which are sensitive to the techniques used to identify voids.
Large scale digital atlases in neuroscience
Hawrylycz, M.; Feng, D.; Lau, C.; Kuan, C.; Miller, J.; Dang, C.; Ng, L.
2014-03-01
Imaging in neuroscience has revolutionized our current understanding of brain structure, architecture and increasingly its function. Many characteristics of morphology, cell type, and neuronal circuitry have been elucidated through methods of neuroimaging. Combining this data in a meaningful, standardized, and accessible manner is the scope and goal of the digital brain atlas. Digital brain atlases are used today in neuroscience to characterize the spatial organization of neuronal structures, for planning and guidance during neurosurgery, and as a reference for interpreting other data modalities such as gene expression and connectivity data. The field of digital atlases is extensive and in addition to atlases of the human includes high quality brain atlases of the mouse, rat, rhesus macaque, and other model organisms. Using techniques based on histology, structural and functional magnetic resonance imaging as well as gene expression data, modern digital atlases use probabilistic and multimodal techniques, as well as sophisticated visualization software to form an integrated product. Toward this goal, brain atlases form a common coordinate framework for summarizing, accessing, and organizing this knowledge and will undoubtedly remain a key technology in neuroscience in the future. Since the development of its flagship project of a genome wide image-based atlas of the mouse brain, the Allen Institute for Brain Science has used imaging as a primary data modality for many of its large scale atlas projects. We present an overview of Allen Institute digital atlases in neuroscience, with a focus on the challenges and opportunities for image processing and computation.
Developing Large-Scale Bayesian Networks by Composition
National Aeronautics and Space Administration — In this paper, we investigate the use of Bayesian networks to construct large-scale diagnostic systems. In particular, we consider the development of large-scale...
Distributed large-scale dimensional metrology new insights
Franceschini, Fiorenzo; Maisano, Domenico
2011-01-01
Focuses on the latest insights into and challenges of distributed large scale dimensional metrology Enables practitioners to study distributed large scale dimensional metrology independently Includes specific examples of the development of new system prototypes
CROW for large scale macromolecular simulations.
Hodoscek, Milan; Borstnik, Urban; Janezic, Dusanka
2002-01-01
CROW (Columns and Rows Of Workstations - http://www.sicmm.org/crow/) is a parallel computer cluster based on the Beowulf (http://www.beowulf.org/) idea, modified to support a larger number of processors. Its architecture is based on point-to-point network architecture, which does not require the use of any network switching equipment in the system. Thus, the cost is lower, and there is no degradation in network performance even for a larger number of processors.
Sensitivity technologies for large scale simulation.
Energy Technology Data Exchange (ETDEWEB)
Collis, Samuel Scott; Bartlett, Roscoe Ainsworth; Smith, Thomas Michael; Heinkenschloss, Matthias (Rice University, Houston, TX); Wilcox, Lucas C. (Brown University, Providence, RI); Hill, Judith C. (Carnegie Mellon University, Pittsburgh, PA); Ghattas, Omar (Carnegie Mellon University, Pittsburgh, PA); Berggren, Martin Olof (University of UppSala, Sweden); Akcelik, Volkan (Carnegie Mellon University, Pittsburgh, PA); Ober, Curtis Curry; van Bloemen Waanders, Bart Gustaaf; Keiter, Eric Richard
2005-01-01
Sensitivity analysis is critically important to numerous analysis algorithms, including large scale optimization, uncertainty quantification,reduced order modeling, and error estimation. Our research focused on developing tools, algorithms and standard interfaces to facilitate the implementation of sensitivity type analysis into existing code and equally important, the work was focused on ways to increase the visibility of sensitivity analysis. We attempt to accomplish the first objective through the development of hybrid automatic differentiation tools, standard linear algebra interfaces for numerical algorithms, time domain decomposition algorithms and two level Newton methods. We attempt to accomplish the second goal by presenting the results of several case studies in which direct sensitivities and adjoint methods have been effectively applied, in addition to an investigation of h-p adaptivity using adjoint based a posteriori error estimation. A mathematical overview is provided of direct sensitivities and adjoint methods for both steady state and transient simulations. Two case studies are presented to demonstrate the utility of these methods. A direct sensitivity method is implemented to solve a source inversion problem for steady state internal flows subject to convection diffusion. Real time performance is achieved using novel decomposition into offline and online calculations. Adjoint methods are used to reconstruct initial conditions of a contamination event in an external flow. We demonstrate an adjoint based transient solution. In addition, we investigated time domain decomposition algorithms in an attempt to improve the efficiency of transient simulations. Because derivative calculations are at the root of sensitivity calculations, we have developed hybrid automatic differentiation methods and implemented this approach for shape optimization for gas dynamics using the Euler equations. The hybrid automatic differentiation method was applied to a first
Sensitivity technologies for large scale simulation.
Energy Technology Data Exchange (ETDEWEB)
Collis, Samuel Scott; Bartlett, Roscoe Ainsworth; Smith, Thomas Michael; Heinkenschloss, Matthias (Rice University, Houston, TX); Wilcox, Lucas C. (Brown University, Providence, RI); Hill, Judith C. (Carnegie Mellon University, Pittsburgh, PA); Ghattas, Omar (Carnegie Mellon University, Pittsburgh, PA); Berggren, Martin Olof (University of UppSala, Sweden); Akcelik, Volkan (Carnegie Mellon University, Pittsburgh, PA); Ober, Curtis Curry; van Bloemen Waanders, Bart Gustaaf; Keiter, Eric Richard
2005-01-01
Sensitivity analysis is critically important to numerous analysis algorithms, including large scale optimization, uncertainty quantification,reduced order modeling, and error estimation. Our research focused on developing tools, algorithms and standard interfaces to facilitate the implementation of sensitivity type analysis into existing code and equally important, the work was focused on ways to increase the visibility of sensitivity analysis. We attempt to accomplish the first objective through the development of hybrid automatic differentiation tools, standard linear algebra interfaces for numerical algorithms, time domain decomposition algorithms and two level Newton methods. We attempt to accomplish the second goal by presenting the results of several case studies in which direct sensitivities and adjoint methods have been effectively applied, in addition to an investigation of h-p adaptivity using adjoint based a posteriori error estimation. A mathematical overview is provided of direct sensitivities and adjoint methods for both steady state and transient simulations. Two case studies are presented to demonstrate the utility of these methods. A direct sensitivity method is implemented to solve a source inversion problem for steady state internal flows subject to convection diffusion. Real time performance is achieved using novel decomposition into offline and online calculations. Adjoint methods are used to reconstruct initial conditions of a contamination event in an external flow. We demonstrate an adjoint based transient solution. In addition, we investigated time domain decomposition algorithms in an attempt to improve the efficiency of transient simulations. Because derivative calculations are at the root of sensitivity calculations, we have developed hybrid automatic differentiation methods and implemented this approach for shape optimization for gas dynamics using the Euler equations. The hybrid automatic differentiation method was applied to a first
Accelerating Satellite Image Based Large-Scale Settlement Detection with GPU
Energy Technology Data Exchange (ETDEWEB)
Patlolla, Dilip Reddy [ORNL; Cheriyadat, Anil M [ORNL; Weaver, Jeanette E [ORNL; Bright, Eddie A [ORNL
2012-01-01
Computer vision algorithms for image analysis are often computationally demanding. Application of such algorithms on large image databases\\---- such as the high-resolution satellite imagery covering the entire land surface, can easily saturate the computational capabilities of conventional CPUs. There is a great demand for vision algorithms running on high performance computing (HPC) architecture capable of processing petascale image data. We exploit the parallel processing capability of GPUs to present a GPU-friendly algorithm for robust and efficient detection of settlements from large-scale high-resolution satellite imagery. Feature descriptor generation is an expensive, but a key step in automated scene analysis. To address this challenge, we present GPU implementations for three different feature descriptors\\-- multiscale Historgram of Oriented Gradients (HOG), Gray Level Co-Occurrence Matrix (GLCM) Contrast and local pixel intensity statistics. We perform extensive experimental evaluations of our implementation using diverse and large image datasets. Our GPU implementation of the feature descriptor algorithms results in speedups of 220 times compared to the CPU version. We present an highly efficient settlement detection system running on a multiGPU architecture capable of extracting human settlement regions from a city-scale sub-meter spatial resolution aerial imagery spanning roughly 1200 sq. kilometers in just 56 seconds with detection accuracy close to 90\\%. This remarkable speedup gained by our vision algorithm maintaining high detection accuracy clearly demonstrates that such computational advancements clearly hold the solution for petascale image analysis challenges.
Large Scale Flame Spread Environmental Characterization Testing
Clayman, Lauren K.; Olson, Sandra L.; Gokoghi, Suleyman A.; Brooker, John E.; Ferkul, Paul V.; Kacher, Henry F.
2013-01-01
Under the Advanced Exploration Systems (AES) Spacecraft Fire Safety Demonstration Project (SFSDP), as a risk mitigation activity in support of the development of a large-scale fire demonstration experiment in microgravity, flame-spread tests were conducted in normal gravity on thin, cellulose-based fuels in a sealed chamber. The primary objective of the tests was to measure pressure rise in a chamber as sample material, burning direction (upward/downward), total heat release, heat release rate, and heat loss mechanisms were varied between tests. A Design of Experiments (DOE) method was imposed to produce an array of tests from a fixed set of constraints and a coupled response model was developed. Supplementary tests were run without experimental design to additionally vary select parameters such as initial chamber pressure. The starting chamber pressure for each test was set below atmospheric to prevent chamber overpressure. Bottom ignition, or upward propagating burns, produced rapid acceleratory turbulent flame spread. Pressure rise in the chamber increases as the amount of fuel burned increases mainly because of the larger amount of heat generation and, to a much smaller extent, due to the increase in gaseous number of moles. Top ignition, or downward propagating burns, produced a steady flame spread with a very small flat flame across the burning edge. Steady-state pressure is achieved during downward flame spread as the pressure rises and plateaus. This indicates that the heat generation by the flame matches the heat loss to surroundings during the longer, slower downward burns. One heat loss mechanism included mounting a heat exchanger directly above the burning sample in the path of the plume to act as a heat sink and more efficiently dissipate the heat due to the combustion event. This proved an effective means for chamber overpressure mitigation for those tests producing the most total heat release and thusly was determined to be a feasible mitigation
Synchronization of coupled large-scale Boolean networks
Energy Technology Data Exchange (ETDEWEB)
Li, Fangfei, E-mail: li-fangfei@163.com [Department of Mathematics, East China University of Science and Technology, No. 130, Meilong Road, Shanghai, Shanghai 200237 (China)
2014-03-15
This paper investigates the complete synchronization and partial synchronization of two large-scale Boolean networks. First, the aggregation algorithm towards large-scale Boolean network is reviewed. Second, the aggregation algorithm is applied to study the complete synchronization and partial synchronization of large-scale Boolean networks. Finally, an illustrative example is presented to show the efficiency of the proposed results.
Synchronization of coupled large-scale Boolean networks
Li, Fangfei
2014-03-01
This paper investigates the complete synchronization and partial synchronization of two large-scale Boolean networks. First, the aggregation algorithm towards large-scale Boolean network is reviewed. Second, the aggregation algorithm is applied to study the complete synchronization and partial synchronization of large-scale Boolean networks. Finally, an illustrative example is presented to show the efficiency of the proposed results.
Large scale tracking of stem cells using sparse coding and coupled graphs
DEFF Research Database (Denmark)
Vestergaard, Jacob Schack; Dahl, Anders Lindbjerg; Holm, Peter
Stem cell tracking is an inherently large scale problem. The challenge is to identify and track hundreds or thousands of cells over a time period of several weeks. This requires robust methods that can leverage the knowledge of specialists on the field. The tracking pipeline presented here consists...
Scaltritti, Michele; Balota, David A.
2013-01-01
This present study examined accuracy and response latency of letter processing as a function of position within a horizontal array. In a series of 4 Experiments, target-strings were briefly (33 ms for Experiment 1 to 3, 83 ms for Experiment 4) displayed and both forward and backward masked. Participants then made a two alternative forced choice. The two alternative responses differed just in one element of the string, and position of mismatch was systematically manipulated. In Experiment 1, words of different lengths (from 3 to 6 letters) were presented in separate blocks. Across different lengths, there was a robust advantage in performance when the alternative response was different for the letter occurring at the first position, compared to when the difference occurred at any other position. Experiment 2 replicated this finding with the same materials used in Experiment 1, but with words of different lengths randomly intermixed within blocks. Experiment 3 provided evidence of the first position advantage with legal nonwords and strings of consonants, but did not provide any first position advantage for non-alphabetic symbols. The lack of a first position advantage for symbols was replicated in Experiment 4, where target-strings were displayed for a longer duration (83 ms). Taken together these results suggest that the first position advantage is a phenomenon that occurs specifically and selectively for letters, independent of lexical constraints. We argue that the results are consistent with models that assume a processing advantage for coding letters in the first position, and are inconsistent with the commonly held assumption in visual word recognition models that letters are equally processed in parallel independent of letter position. PMID:24012723
Watanabe, Eriko; Ishikawa, Mami; Ohta, Maiko; Kodate, Kashiko
2005-09-01
Face recognition is used in a wide range of security systems, such as monitoring credit card use, searching for individuals with street cameras via Internet and maintaining immigration control. There are still many technical subjects under study. For instance, the number of images that can be stored is limited under the current system, and the rate of recognition must be improved to account for photo shots taken at different angles under various conditions. We implemented a fully automatic Fast Face Recognition Optical Correlator (FARCO) system by using a 1000 frame/s optical parallel correlator designed and assembled by us. Operational speed for the 1: N (i.e. matching a pair of images among N, where N refers to the number of images in the database) identification experiment (4000 face images) amounts to less than 1.5 seconds, including the pre/post processing. From trial 1: N identification experiments using FARCO, we acquired low error rates of 2.6% False Reject Rate and 1.3% False Accept Rate. By making the most of the high-speed data-processing capability of this system, much more robustness can be achieved for various recognition conditions when large-category data are registered for a single person. We propose a face recognition algorithm for the FARCO while employing a temporal image sequence of moving images. Applying this algorithm to a natural posture, a two times higher recognition rate scored compared with our conventional system. The system has high potential for future use in a variety of purposes such as search for criminal suspects by use of street and airport video cameras, registration of babies at hospitals or handling of an immeasurable number of images in a database.
High Fidelity Simulations of Large-Scale Wireless Networks
Energy Technology Data Exchange (ETDEWEB)
Onunkwo, Uzoma [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Benz, Zachary [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-11-01
The worldwide proliferation of wireless connected devices continues to accelerate. There are 10s of billions of wireless links across the planet with an additional explosion of new wireless usage anticipated as the Internet of Things develops. Wireless technologies do not only provide convenience for mobile applications, but are also extremely cost-effective to deploy. Thus, this trend towards wireless connectivity will only continue and Sandia must develop the necessary simulation technology to proactively analyze the associated emerging vulnerabilities. Wireless networks are marked by mobility and proximity-based connectivity. The de facto standard for exploratory studies of wireless networks is discrete event simulations (DES). However, the simulation of large-scale wireless networks is extremely difficult due to prohibitively large turnaround time. A path forward is to expedite simulations with parallel discrete event simulation (PDES) techniques. The mobility and distance-based connectivity associated with wireless simulations, however, typically doom PDES and fail to scale (e.g., OPNET and ns-3 simulators). We propose a PDES-based tool aimed at reducing the communication overhead between processors. The proposed solution will use light-weight processes to dynamically distribute computation workload while mitigating communication overhead associated with synchronizations. This work is vital to the analytics and validation capabilities of simulation and emulation at Sandia. We have years of experience in Sandia’s simulation and emulation projects (e.g., MINIMEGA and FIREWHEEL). Sandia’s current highly-regarded capabilities in large-scale emulations have focused on wired networks, where two assumptions prevent scalable wireless studies: (a) the connections between objects are mostly static and (b) the nodes have fixed locations.
Large scale dynamics of protoplanetary discs
BÃ©thune, William
2017-08-01
Planets form in the gaseous and dusty disks orbiting young stars. These protoplanetary disks are dispersed in a few million years, being accreted onto the central star or evaporated into the interstellar medium. To explain the observed accretion rates, it is commonly assumed that matter is transported through the disk by turbulence, although the mechanism sustaining turbulence is uncertain. On the other side, irradiation by the central star could heat up the disk surface and trigger a photoevaporative wind, but thermal effects cannot account for the observed acceleration and collimation of the wind into a narrow jet perpendicular to the disk plane. Both issues can be solved if the disk is sensitive to magnetic fields. Weak fields lead to the magnetorotational instability, whose outcome is a state of sustained turbulence. Strong fields can slow down the disk, causing it to accrete while launching a collimated wind. However, the coupling between the disk and the neutral gas is done via electric charges, each of which is outnumbered by several billion neutral molecules. The imperfect coupling between the magnetic field and the neutral gas is described in terms of "non-ideal" effects, introducing new dynamical behaviors. This thesis is devoted to the transport processes happening inside weakly ionized and weakly magnetized accretion disks; the role of microphysical effects on the large-scale dynamics of the disk is of primary importance. As a first step, I exclude the wind and examine the impact of non-ideal effects on the turbulent properties near the disk midplane. I show that the flow can spontaneously organize itself if the ionization fraction is low enough; in this case, accretion is halted and the disk exhibits axisymmetric structures, with possible consequences on planetary formation. As a second step, I study the launching of disk winds via a global model of stratified disk embedded in a warm atmosphere. This model is the first to compute non-ideal effects from
Large-Scale Spacecraft Fire Safety Tests
Urban, David; Ruff, Gary A.; Ferkul, Paul V.; Olson, Sandra; Fernandez-Pello, A. Carlos; T'ien, James S.; Torero, Jose L.; Cowlard, Adam J.; Rouvreau, Sebastien; Minster, Olivier; Toth, Balazs; Legros, Guillaume; Eigenbrod, Christian; Smirnov, Nickolay; Fujita, Osamu; Jomaas, Grunde
2014-01-01
An international collaborative program is underway to address open issues in spacecraft fire safety. Because of limited access to long-term low-gravity conditions and the small volume generally allotted for these experiments, there have been relatively few experiments that directly study spacecraft fire safety under low-gravity conditions. Furthermore, none of these experiments have studied sample sizes and environment conditions typical of those expected in a spacecraft fire. The major constraint has been the size of the sample, with prior experiments limited to samples of the order of 10 cm in length and width or smaller. This lack of experimental data forces spacecraft designers to base their designs and safety precautions on 1-g understanding of flame spread, fire detection, and suppression. However, low-gravity combustion research has demonstrated substantial differences in flame behavior in low-gravity. This, combined with the differences caused by the confined spacecraft environment, necessitates practical scale spacecraft fire safety research to mitigate risks for future space missions. To address this issue, a large-scale spacecraft fire experiment is under development by NASA and an international team of investigators. This poster presents the objectives, status, and concept of this collaborative international project (Saffire). The project plan is to conduct fire safety experiments on three sequential flights of an unmanned ISS re-supply spacecraft (the Orbital Cygnus vehicle) after they have completed their delivery of cargo to the ISS and have begun their return journeys to earth. On two flights (Saffire-1 and Saffire-3), the experiment will consist of a flame spread test involving a meter-scale sample ignited in the pressurized volume of the spacecraft and allowed to burn to completion while measurements are made. On one of the flights (Saffire-2), 9 smaller (5 x 30 cm) samples will be tested to evaluate NASAs material flammability screening tests
Large-scale GW software development
Kim, Minjung; Mandal, Subhasish; Mikida, Eric; Jindal, Prateek; Bohm, Eric; Jain, Nikhil; Kale, Laxmikant; Martyna, Glenn; Ismail-Beigi, Sohrab
Electronic excitations are important in understanding and designing many functional materials. In terms of ab initio methods, the GW and Bethe-Saltpeter Equation (GW-BSE) beyond DFT methods have proved successful in describing excited states in many materials. However, the heavy computational loads and large memory requirements have hindered their routine applicability by the materials physics community. We summarize some of our collaborative efforts to develop a new software framework designed for GW calculations on massively parallel supercomputers. Our GW code is interfaced with the plane-wave pseudopotential ab initio molecular dynamics software ``OpenAtom'' which is based on the Charm++ parallel library. The computation of the electronic polarizability is one of the most expensive parts of any GW calculation. We describe our strategy that uses a real-space representation to avoid the large number of fast Fourier transforms (FFTs) common to most GW methods. We also describe an eigendecomposition of the plasmon modes from the resulting dielectric matrix that enhances efficiency. This work is supported by NSF through Grant ACI-1339804.
Large Scale CW ECRH Systems: Some considerations
Directory of Open Access Journals (Sweden)
Turkin Y.
2012-09-01
Full Text Available Electron Cyclotron Resonance Heating (ECRH is a key component in the heating arsenal for the next step fusion devices like W7-X and ITER. These devices are equipped with superconducting coils and are designed to operate steady state. ECRH must thus operate in CW-mode with a large flexibility to comply with various physics demands such as plasma start-up, heating and current drive, as well as configurationand MHD - control. The request for many different sophisticated applications results in a growing complexity, which is in conflict with the request for high availability, reliability, and maintainability. ‘Advanced’ ECRH-systems must, therefore, comply with both the complex physics demands and operational robustness and reliability. The W7-X ECRH system is the first CW- facility of an ITER relevant size and is used as a test bed for advanced components. Proposals for future developments are presented together with improvements of gyrotrons, transmission components and launchers.
Python for large-scale electrophysiology
Directory of Open Access Journals (Sweden)
Martin A Spacek
2009-01-01
Full Text Available Electrophysiology is increasingly moving towards highly parallel recording techniques which generate large data sets. We record extracellularly in vivo in cat and rat visual cortex with 54 channel silicon polytrodes, under time-locked visual stimulation, from localized neuronal populations within a cortical column. To help deal with the complexity of generating and analyzing these data, we used the Python programming language to develop three software projects: one for temporally precise visual stimulus generation (dimstim; one for electrophysiological waveform visualization and spike sorting (spyke; and one for spike train and stimulus analysis (neuropy. All three are open source and available for download (http://swindale.ecc.ubc.ca/code. The requirements and solutions for these projects differed greatly, yet we found Python to be well suited for all three. Here we present our software as a showcase of the extensive capabilities of Python in neuroscience.
Python for large-scale electrophysiology.
Spacek, Martin; Blanche, Tim; Swindale, Nicholas
2008-01-01
Electrophysiology is increasingly moving towards highly parallel recording techniques which generate large data sets. We record extracellularly in vivo in cat and rat visual cortex with 54-channel silicon polytrodes, under time-locked visual stimulation, from localized neuronal populations within a cortical column. To help deal with the complexity of generating and analysing these data, we used the Python programming language to develop three software projects: one for temporally precise visual stimulus generation ("dimstim"); one for electrophysiological waveform visualization and spike sorting ("spyke"); and one for spike train and stimulus analysis ("neuropy"). All three are open source and available for download (http://swindale.ecc.ubc.ca/code). The requirements and solutions for these projects differed greatly, yet we found Python to be well suited for all three. Here we present our software as a showcase of the extensive capabilities of Python in neuroscience.
Large-scale assembly of colloidal particles
Yang, Hongta
This study reports a simple, roll-to-roll compatible coating technology for producing three-dimensional highly ordered colloidal crystal-polymer composites, colloidal crystals, and macroporous polymer membranes. A vertically beveled doctor blade is utilized to shear align silica microsphere-monomer suspensions to form large-area composites in a single step. The polymer matrix and the silica microspheres can be selectively removed to create colloidal crystals and self-standing macroporous polymer membranes. The thickness of the shear-aligned crystal is correlated with the viscosity of the colloidal suspension and the coating speed, and the correlations can be qualitatively explained by adapting the mechanisms developed for conventional doctor blade coating. Five important research topics related to the application of large-scale three-dimensional highly ordered macroporous films by doctor blade coating are covered in this study. The first topic describes the invention in large area and low cost color reflective displays. This invention is inspired by the heat pipe technology. The self-standing macroporous polymer films exhibit brilliant colors which originate from the Bragg diffractive of visible light form the three-dimensional highly ordered air cavities. The colors can be easily changed by tuning the size of the air cavities to cover the whole visible spectrum. When the air cavities are filled with a solvent which has the same refractive index as that of the polymer, the macroporous polymer films become completely transparent due to the index matching. When the solvent trapped in the cavities is evaporated by in-situ heating, the sample color changes back to brilliant color. This process is highly reversible and reproducible for thousands of cycles. The second topic reports the achievement of rapid and reversible vapor detection by using 3-D macroporous photonic crystals. Capillary condensation of a condensable vapor in the interconnected macropores leads to the
Large scale structure from viscous dark matter
Blas, Diego; Floerchinger, Stefan; Garny, Mathias; Tetradis, Nikolaos; Wiedemann, Urs Achim
2015-11-01
Cosmological perturbations of sufficiently long wavelength admit a fluid dynamic description. We consider modes with wavevectors below a scale km for which the dynamics is only mildly non-linear. The leading effect of modes above that scale can be accounted for by effective non-equilibrium viscosity and pressure terms. For mildly non-linear scales, these mainly arise from momentum transport within the ideal and cold but inhomogeneous fluid, while momentum transport due to more microscopic degrees of freedom is suppressed. As a consequence, concrete expressions with no free parameters, except the matching scale km, can be derived from matching evolution equations to standard cosmological perturbation theory. Two-loop calculations of the matter power spectrum in the viscous theory lead to excellent agreement with N-body simulations up to scales k=0.2 h/Mpc. The convergence properties in the ultraviolet are better than for standard perturbation theory and the results are robust with respect to variations of the matching scale.
Large scale structure from viscous dark matter
Blas, Diego; Garny, Mathias; Tetradis, Nikolaos; Wiedemann, Urs Achim
2015-01-01
Cosmological perturbations of sufficiently long wavelength admit a fluid dynamic description. We consider modes with wavevectors below a scale $k_m$ for which the dynamics is only mildly non-linear. The leading effect of modes above that scale can be accounted for by effective non-equilibrium viscosity and pressure terms. For mildly non-linear scales, these mainly arise from momentum transport within the ideal and cold but inhomogeneous fluid, while momentum transport due to more microscopic degrees of freedom is suppressed. As a consequence, concrete expressions with no free parameters, except the matching scale $k_m$, can be derived from matching evolution equations to standard cosmological perturbation theory. Two-loop calculations of the matter power spectrum in the viscous theory lead to excellent agreement with $N$-body simulations up to scales $k=0.2 \\, h/$Mpc. The convergence properties in the ultraviolet are better than for standard perturbation theory and the results are robust with respect to varia...
Energy Technology Data Exchange (ETDEWEB)
Kuebler, R.; Fisch, M.N. [Steinbeis-Transferzentrum Energie-, Gebaeude- und Solartechnik, Stuttgart (Germany)
1998-12-31
The aim of this project is the preparation of the ``Large-Scale Solar Heating`` programme for an Europe-wide development of subject technology. The following demonstration programme was judged well by the experts but was not immediately (1996) accepted for financial subsidies. In November 1997 the EU-commission provided 1,5 million ECU which allowed the realisation of an updated project proposal. By mid 1997 a small project was approved, that had been requested under the lead of Chalmes Industriteteknik (CIT) in Sweden and is mainly carried out for the transfer of technology. (orig.) [Deutsch] Ziel dieses Vorhabens ist die Vorbereitung eines Schwerpunktprogramms `Large Scale Solar Heating`, mit dem die Technologie europaweit weiterentwickelt werden sollte. Das daraus entwickelte Demonstrationsprogramm wurde von den Gutachtern positiv bewertet, konnte jedoch nicht auf Anhieb (1996) in die Foerderung aufgenommen werden. Im November 1997 wurden von der EU-Kommission dann kurzfristig noch 1,5 Mio ECU an Foerderung bewilligt, mit denen ein aktualisierter Projektvorschlag realisiert werden kann. Bereits Mitte 1997 wurde ein kleineres Vorhaben bewilligt, das unter Federfuehrung von Chalmers Industriteknik (CIT) in Schweden beantragt worden war und das vor allem dem Technologietransfer dient. (orig.)
Multitree Algorithms for Large-Scale Astrostatistics
March, William B.; Ozakin, Arkadas; Lee, Dongryeol; Riegel, Ryan; Gray, Alexander G.
2012-03-01
this number every week, resulting in billions of objects. At such scales, even linear-time analysis operations present challenges, particularly since statistical analyses are inherently interactive processes, requiring that computations complete within some reasonable human attention span. The quadratic (or worse) runtimes of straightforward implementations become quickly unbearable. Examples of applications. These analysis subroutines occur ubiquitously in astrostatistical work. We list just a few examples. The need to cross-match objects across different catalogs has led to various algorithms, which at some point perform an AllNN computation. 2-point and higher-order spatial correlations for the basis of spatial statistics, and are utilized in astronomy to compare the spatial structures of two datasets, such as an observed sample and a theoretical sample, for example, forming the basis for two-sample hypothesis testing. Friends-of-friends clustering is often used to identify halos in data from astrophysical simulations. Minimum spanning tree properties have also been proposed as statistics of large-scale structure. Comparison of the distributions of different kinds of objects requires accurate density estimation, for which KDE is the overall statistical method of choice. The prediction of redshifts from optical data requires accurate regression, for which kernel regression is a powerful method. The identification of objects of various types in astronomy, such as stars versus galaxies, requires accurate classification, for which KDA is a powerful method. Overview. In this chapter, we will briefly sketch the main ideas behind recent fast algorithms which achieve, for example, linear runtimes for pairwise-distance problems, or similarly dramatic reductions in computational growth. In some cases, the runtime orders for these algorithms are mathematically provable statements, while in others we have only conjectures backed by experimental observations for the time being
Stability Criteria for Large-Scale Linear Systems with Structured Uncertainties
Institute of Scientific and Technical Information of China (English)
Cao Dengqing
1996-01-01
The robust stability analysis for large-scale linear systems with structured timevarying uncertainties is investigated in this paper. By using the scalar Lyapunov functions and the properties of M-matrix and nonnegative matrix, stability robustness measures are proposed. The robust stability criteria obtained are applied to derive an algebric criterion which is expressed directly in terms of plant parameters and is shown to be less conservative than the existing ones. A numerical example is given to demonstrate the stability criteria obtained and to compare them with the previous ones.
Analysis using large-scale ringing data
Directory of Open Access Journals (Sweden)
Baillie, S. R.
2004-06-01
survival and recruitment estimates from the French CES scheme to assess the relative contributions of survival and recruitment to overall population changes. He develops a novel approach to modelling survival rates from such multi–site data by using within–year recaptures to provide a covariate of between–year recapture rates. This provided parsimonious models of variation in recapture probabilities between sites and years. The approach provides promising results for the four species investigated and can potentially be extended to similar data from other CES/MAPS schemes. The final paper by Blandine Doligez, David Thomson and Arie van Noordwijk (Doligez et al., 2004 illustrates how large-scale studies of population dynamics can be important for evaluating the effects of conservation measures. Their study is concerned with the reintroduction of White Stork populations to the Netherlands where a re–introduction programme started in 1969 had resulted in a breeding population of 396 pairs by 2000. They demonstrate the need to consider a wide range of models in order to account for potential age, time, cohort and “trap–happiness” effects. As the data are based on resightings such trap–happiness must reflect some form of heterogeneity in resighting probabilities. Perhaps surprisingly, the provision of supplementary food did not influence survival, but it may havehad an indirect effect via the alteration of migratory behaviour. Spatially explicit modelling of data gathered at many sites inevitably results in starting models with very large numbers of parameters. The problem is often complicated further by having relatively sparse data at each site, even where the total amount of data gathered is very large. Both Julliard (2004 and Doligez et al. (2004 give explicit examples of problems caused by needing to handle very large numbers of parameters and show how they overcame them for their particular data sets. Such problems involve both the choice of appropriate
Large-scale functional purification of recombinant HIV-1 capsid.
Directory of Open Access Journals (Sweden)
Magdeleine Hung
Full Text Available During human immunodeficiency virus type-1 (HIV-1 virion maturation, capsid proteins undergo a major rearrangement to form a conical core that protects the viral nucleoprotein complexes. Mutations in the capsid sequence that alter the stability of the capsid core are deleterious to viral infectivity and replication. Recently, capsid assembly has become an attractive target for the development of a new generation of anti-retroviral agents. Drug screening efforts and subsequent structural and mechanistic studies require gram quantities of active, homogeneous and pure protein. Conventional means of laboratory purification of Escherichia coli expressed recombinant capsid protein rely on column chromatography steps that are not amenable to large-scale production. Here we present a function-based purification of wild-type and quadruple mutant capsid proteins, which relies on the inherent propensity of capsid protein to polymerize and depolymerize. This method does not require the packing of sizable chromatography columns and can generate double-digit gram quantities of functionally and biochemically well-behaved proteins with greater than 98% purity. We have used the purified capsid protein to characterize two known assembly inhibitors in our in-house developed polymerization assay and to measure their binding affinities. Our capsid purification procedure provides a robust method for purifying large quantities of a key protein in the HIV-1 life cycle, facilitating identification of the next generation anti-HIV agents.
Large Scale Structure in the Epoch of Reionization
Koekemoer, Anton; Mould, Jeremy; Cooke, Jeffrey; Wyithe, Stuart; Lidman, Christopher; Trenti, Michele; Abbott, Tim; Kunder, Andrea; Barone-Nugent, Robert; Tescari, Edoardo; Katsianis, Antonios
2014-02-01
We propose to capitalize on the high red sensitivity and large field of view of DECam to detect the brightest and rarest galaxies at z=6-7. Our 2012 results show the signature of large scale structure with wavenumber of order 0.1 inverse Mpc in line with expectations of primordial non-gaussianity. But the signal to noise in one deep field from two nights' data is insufficient for a robust conclusion. Ten nights' data will do the job. These data will also constrain the galaxy contribution to reionization by enabling a tighter constraint on the full galaxy luminosity function, including the faint end. The observations will be executed with a cadence and depth that will enable the detection of super-luminous supernovae at z=6-7. Super-luminous supernovae are a recently observed class of supernovae that are 10-100x more luminous than typical supernovae. This class includes pair- instability supernovae that are a rare, third type of supernova explosion in which only 3 events are known. The proposed observations will greatly extend the current reach of supernovae research, examining their occurrence rate and properties near the epoch of reionization.
Large scale photovoltaic field trials. Second technical report: monitoring phase
Energy Technology Data Exchange (ETDEWEB)
NONE
2007-09-15
This report provides an update on the Large-Scale Building Integrated Photovoltaic Field Trials (LS-BIPV FT) programme commissioned by the Department of Trade and Industry (Department for Business, Enterprise and Industry; BERR). It provides detailed profiles of the 12 projects making up this programme, which is part of the UK programme on photovoltaics and has run in parallel with the Domestic Field Trial. These field trials aim to record the experience and use the lessons learnt to raise awareness of, and confidence in, the technology and increase UK capabilities. The projects involved: the visitor centre at the Gaia Energy Centre in Cornwall; a community church hall in London; council offices in West Oxfordshire; a sports science centre at Gloucester University; the visitor centre at Cotswold Water Park; the headquarters of the Insolvency Service; a Welsh Development Agency building; an athletics centre in Birmingham; a research facility at the University of East Anglia; a primary school in Belfast; and Barnstable civic centre in Devon. The report describes the aims of the field trials, monitoring issues, performance, observations and trends, lessons learnt and the results of occupancy surveys.
Development of large-scale structure in the Universe
Ostriker, J P
1991-01-01
This volume grew out of the 1988 Fermi lectures given by Professor Ostriker, and is concerned with cosmological models that take into account the large scale structure of the universe. He starts with homogeneous isotropic models of the universe and then, by considering perturbations, he leads us to modern cosmological theories of the large scale, such as superconducting strings. This will be an excellent companion for all those interested in the cosmology and the large scale nature of the universe.
Large-scale climatic anomalies affect marine predator foraging behaviour and demography
Bost, Charles A.; Cotté, Cedric; Terray, Pascal; Barbraud, Christophe; Bon, Cécile; Delord, Karine; Gimenez, Olivier; Handrich, Yves; Naito, Yasuhiko; Guinet, Christophe; Weimerskirch, Henri
2015-10-01
Determining the links between the behavioural and population responses of wild species to environmental variations is critical for understanding the impact of climate variability on ecosystems. Using long-term data sets, we show how large-scale climatic anomalies in the Southern Hemisphere affect the foraging behaviour and population dynamics of a key marine predator, the king penguin. When large-scale subtropical dipole events occur simultaneously in both subtropical Southern Indian and Atlantic Oceans, they generate tropical anomalies that shift the foraging zone southward. Consequently the distances that penguins foraged from the colony and their feeding depths increased and the population size decreased. This represents an example of a robust and fast impact of large-scale climatic anomalies affecting a marine predator through changes in its at-sea behaviour and demography, despite lack of information on prey availability. Our results highlight a possible behavioural mechanism through which climate variability may affect population processes.
Non-parametric co-clustering of large scale sparse bipartite networks on the GPU
DEFF Research Database (Denmark)
Hansen, Toke Jansen; Mørup, Morten; Hansen, Lars Kai
2011-01-01
Co-clustering is a problem of both theoretical and practical importance, e.g., market basket analysis and collaborative filtering, and in web scale text processing. We state the co-clustering problem in terms of non-parametric generative models which can address the issue of estimating the number...... of row and column clusters from a hypothesis space of an infinite number of clusters. To reach large scale applications of co-clustering we exploit that parameter inference for co-clustering is well suited for parallel computing. We develop a generic GPU framework for efficient inference on large scale......-life large scale collaborative filtering data and web scale text corpora, demonstrating that latent mesoscale structures extracted by the co-clustering problem as formulated by the Infinite Relational Model (IRM) are consistent across consecutive runs with different initializations and also relevant...
Imprint of non-linear effects on HI intensity mapping on large scales
Umeh, Obinna
2016-01-01
Intensity mapping of the HI brightness temperature provides a unique way of tracing large-scale structures of the Universe up to the largest possible scales. This is achieved by using a low angular resolution radio telescopes to detect emission line from cosmic neutral Hydrogen in the post-reionization Universe. We consider how non-linear effects associated with the HI bias and redshift space distortions contribute to the clustering of cosmic neutral Hydrogen on large scales. We use general relativistic perturbation theory techniques to derive for the first time the full expression for the HI brightness temperature up to third order in perturbation theory without making any plane-parallel approximation. We use this result to show how mode coupling at nonlinear order due to nonlinear bias parameters and redshift space distortions leads to about 10\\% modulation of the HI power spectrum on large scales.
Design of Large-Scale Sensory Data Processing System Based on Cloud Computing
Directory of Open Access Journals (Sweden)
Bing Tang
2012-04-01
Full Text Available In large-scale Wireless Sensor Networks (WSNs, with limited computing power and storage capacity of sensor nodes, there is an urgent demand of high performance sensory data processing. This study studies the interconnection of wireless sensor networks and cloud-based storage and computing infrastructure. It proposes the idea of distributed databases to store sensory data and MapReduce programming model for large-scale sensory data parallel processing. In our prototype of large-scale sensory data processing system, Hadoop Distributed File System (HDFS and HBase are used for sensory data storage, and Hadoop MapReduce is used for data processing application execution framework. The design and implementation of this system are described in detail. The simulation of environment temperature surveillance application is used to verify the feasibility and reasonableness of the system, which also proves that it significantly improves the data processing capability of WSNs.
Imprint of non-linear effects on HI intensity mapping on large scales
Umeh, Obinna
2017-06-01
Intensity mapping of the HI brightness temperature provides a unique way of tracing large-scale structures of the Universe up to the largest possible scales. This is achieved by using a low angular resolution radio telescopes to detect emission line from cosmic neutral Hydrogen in the post-reionization Universe. We use general relativistic perturbation theory techniques to derive for the first time the full expression for the HI brightness temperature up to third order in perturbation theory without making any plane-parallel approximation. We use this result and the renormalization prescription for biased tracers to study the impact of nonlinear effects on the power spectrum of HI brightness temperature both in real and redshift space. We show how mode coupling at nonlinear order due to nonlinear bias parameters and redshift space distortion terms modulate the power spectrum on large scales. The large scale modulation may be understood to be due to the effective bias parameter and effective shot noise.
Large Scale, High Resolution, Mantle Dynamics Modeling
Geenen, T.; Berg, A. V.; Spakman, W.
2007-12-01
spherical models. We also applied the above mentioned method to a high resolution (~ 1 km) 2D mantle convection model with temperature, pressure and phase dependent rheology including several phase transitions. We focus on a model of a subducting lithospheric slab which is subject to strong folding at the bottom of the mantle's D" region which includes the postperovskite phase boundary. For a detailed description of this model we refer to poster [Mantel convection models of the D" region, U17] [Saad, 2003] Saad, Y. (2003). Iterative methods for sparse linear systems. [Sala, 2006] Sala. M (2006) An Object-Oriented Framework for the Development of Scalable Parallel Multilevel Preconditioners. ACM Transactions on Mathematical Software, 32 (3), 2006 [Patankar, 1980] Patankar, S. V.(1980) Numerical Heat Transfer and Fluid Flow, Hemisphere, Washington.
Alignment between galaxies and large-scale structure
Institute of Scientific and Technical Information of China (English)
A. Faltenbacher; Cheng Li; Simon D. M. White; Yi-Peng Jing; Shu-De Mao; Jie Wang
2009-01-01
Based on the Sloan Digital Sky Survey DR6 (SDSS) and the Millennium Simulation (MS), we investigate the alignment between galaxies and large-scale struc-ture. For this purpose, we develop two new statistical tools, namely the alignment cor-relation function and the cos(20)-statistic. The former is a two-dimensional extension of the traditional two-point correlation function and the latter is related to the ellipticity correlation function used for cosmic shear measurements. Both are based on the cross correlation between a sample of galaxies with orientations and a reference sample which represents the large-scale structure. We apply the new statistics to the SDSS galaxy cat-alog. The alignment correlation function reveals an overabundance of reference galaxies along the major axes of red, luminous (L L*) galaxies out to projected separations of 60 h-1Mpc. The signal increases with central galaxy luminosity. No alignment signal is detected for blue galaxies. The cos(2θ)-statistic yields very similar results. Starting from a MS semi-analytic galaxy catalog, we assign an orientation to each red, luminous and central galaxy, based on that of the central region of the host halo (with size similar to that of the stellar galaxy). As an alternative, we use the orientation of the host halo itself. We find a mean projected misalignment between a halo and its central region of ~ 25°. The misalignment decreases slightly with increasing luminosity of the central galaxy. Using the orientations and luminosities of the semi-analytic galaxies, we repeat our alignment analysis on mock surveys of the MS. Agreement with the SDSS results is good if the central orientations are used. Predictions using the halo orientations as proxies for cen-tral galaxy orientations overestimate the observed alignment by more than a factor of 2. Finally, the large volume of the MS allows us to generate a two-dimensional map of the alignment correlation function, which shows the reference galaxy
Directory of Open Access Journals (Sweden)
Hui He
2013-01-01
Full Text Available It is of great significance to research the early warning system for large-scale network security incidents. It can improve the network system’s emergency response capabilities, alleviate the cyber attacks’ damage, and strengthen the system’s counterattack ability. A comprehensive early warning system is presented in this paper, which combines active measurement and anomaly detection. The key visualization algorithm and technology of the system are mainly discussed. The large-scale network system’s plane visualization is realized based on the divide and conquer thought. First, the topology of the large-scale network is divided into some small-scale networks by the MLkP/CR algorithm. Second, the sub graph plane visualization algorithm is applied to each small-scale network. Finally, the small-scale networks’ topologies are combined into a topology based on the automatic distribution algorithm of force analysis. As the algorithm transforms the large-scale network topology plane visualization problem into a series of small-scale network topology plane visualization and distribution problems, it has higher parallelism and is able to handle the display of ultra-large-scale network topology.
He, Hui; Fan, Guotao; Ye, Jianwei; Zhang, Weizhe
2013-01-01
It is of great significance to research the early warning system for large-scale network security incidents. It can improve the network system's emergency response capabilities, alleviate the cyber attacks' damage, and strengthen the system's counterattack ability. A comprehensive early warning system is presented in this paper, which combines active measurement and anomaly detection. The key visualization algorithm and technology of the system are mainly discussed. The large-scale network system's plane visualization is realized based on the divide and conquer thought. First, the topology of the large-scale network is divided into some small-scale networks by the MLkP/CR algorithm. Second, the sub graph plane visualization algorithm is applied to each small-scale network. Finally, the small-scale networks' topologies are combined into a topology based on the automatic distribution algorithm of force analysis. As the algorithm transforms the large-scale network topology plane visualization problem into a series of small-scale network topology plane visualization and distribution problems, it has higher parallelism and is able to handle the display of ultra-large-scale network topology.
Safeguards instruments for Large-Scale Reprocessing Plants
Energy Technology Data Exchange (ETDEWEB)
Hakkila, E.A. [Los Alamos National Lab., NM (United States); Case, R.S.; Sonnier, C. [Sandia National Labs., Albuquerque, NM (United States)
1993-06-01
Between 1987 and 1992 a multi-national forum known as LASCAR (Large Scale Reprocessing Plant Safeguards) met to assist the IAEA in development of effective and efficient safeguards for large-scale reprocessing plants. The US provided considerable input for safeguards approaches and instrumentation. This paper reviews and updates instrumentation of importance in measuring plutonium and uranium in these facilities.
Electrodialysis system for large-scale enantiomer separation
Ent, van der E.M.; Thielen, T.P.H.; Cohen Stuart, M.A.; Padt, van der A.; Keurentjes, J.T.F.
2001-01-01
In contrast to analytical methods, the range of technologies currently applied for large-scale enantiomer separations is not very extensive. Therefore, a new system has been developed for large-scale enantiomer separations that can be regarded as the scale-up of a capillary electrophoresis system. I
Electrodialysis system for large-scale enantiomer separation
Ent, van der E.M.; Thielen, T.P.H.; Cohen Stuart, M.A.; Padt, van der A.; Keurentjes, J.T.F.
2001-01-01
In contrast to analytical methods, the range of technologies currently applied for large-scale enantiomer separations is not very extensive. Therefore, a new system has been developed for large-scale enantiomer separations that can be regarded as the scale-up of a capillary electrophoresis system.
Prospects for large scale electricity storage in Denmark
DEFF Research Database (Denmark)
Krog Ekman, Claus; Jensen, Søren Højgaard
2010-01-01
In a future power systems with additional wind power capacity there will be an increased need for large scale power management as well as reliable balancing and reserve capabilities. Different technologies for large scale electricity storage provide solutions to the different challenges arising w...
Scalable multi-objective control for large scale water resources systems under uncertainty
Giuliani, Matteo; Quinn, Julianne; Herman, Jonathan; Castelletti, Andrea; Reed, Patrick
2016-04-01
The use of mathematical models to support the optimal management of environmental systems is rapidly expanding over the last years due to advances in scientific knowledge of the natural processes, efficiency of the optimization techniques, and availability of computational resources. However, undergoing changes in climate and society introduce additional challenges for controlling these systems, ultimately motivating the emergence of complex models to explore key causal relationships and dependencies on uncontrolled sources of variability. In this work, we contribute a novel implementation of the evolutionary multi-objective direct policy search (EMODPS) method for controlling environmental systems under uncertainty. The proposed approach combines direct policy search (DPS) with hierarchical parallelization of multi-objective evolutionary algorithms (MOEAs) and offers a threefold advantage: the DPS simulation-based optimization can be combined with any simulation model and does not add any constraint on modeled information, allowing the use of exogenous information in conditioning the decisions. Moreover, the combination of DPS and MOEAs prompts the generation or Pareto approximate set of solutions for up to 10 objectives, thus overcoming the decision biases produced by cognitive myopia, where narrow or restrictive definitions of optimality strongly limit the discovery of decision relevant alternatives. Finally, the use of large-scale MOEAs parallelization improves the ability of the designed solutions in handling the uncertainty due to severe natural variability. The proposed approach is demonstrated on a challenging water resources management problem represented by the optimal control of a network of four multipurpose water reservoirs in the Red River basin (Vietnam). As part of the medium-long term energy and food security national strategy, four large reservoirs have been constructed on the Red River tributaries, which are mainly operated for hydropower
Large-scale simulations of layered double hydroxide nanocomposite materials
Thyveetil, Mary-Ann
Layered double hydroxides (LDHs) have the ability to intercalate a multitude of anionic species. Atomistic simulation techniques such as molecular dynamics have provided considerable insight into the behaviour of these materials. We review these techniques and recent algorithmic advances which considerably improve the performance of MD applications. In particular, we discuss how the advent of high performance computing and computational grids has allowed us to explore large scale models with considerable ease. Our simulations have been heavily reliant on computational resources on the UK's NGS (National Grid Service), the US TeraGrid and the Distributed European Infrastructure for Supercomputing Applications (DEISA). In order to utilise computational grids we rely on grid middleware to launch, computationally steer and visualise our simulations. We have integrated the RealityGrid steering library into the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) 1 . which has enabled us to perform re mote computational steering and visualisation of molecular dynamics simulations on grid infrastruc tures. We also use the Application Hosting Environment (AHE) 2 in order to launch simulations on remote supercomputing resources and we show that data transfer rates between local clusters and super- computing resources can be considerably enhanced by using optically switched networks. We perform large scale molecular dynamics simulations of MgiAl-LDHs intercalated with either chloride ions or a mixture of DNA and chloride ions. The systems exhibit undulatory modes, which are suppressed in smaller scale simulations, caused by the collective thermal motion of atoms in the LDH layers. Thermal undulations provide elastic properties of the system including the bending modulus, Young's moduli and Poisson's ratios. To explore the interaction between LDHs and DNA. we use molecular dynamics techniques to per form simulations of double stranded, linear and plasmid DNA up
Ergul, Ozgur
2014-01-01
The Multilevel Fast Multipole Algorithm (MLFMA) for Solving Large-Scale Computational Electromagnetic Problems provides a detailed and instructional overview of implementing MLFMA. The book: Presents a comprehensive treatment of the MLFMA algorithm, including basic linear algebra concepts, recent developments on the parallel computation, and a number of application examplesCovers solutions of electromagnetic problems involving dielectric objects and perfectly-conducting objectsDiscusses applications including scattering from airborne targets, scattering from red
The Internet As a Large-Scale Complex System
Park, Kihong; Willinger, Walter
2005-06-01
The Internet may be viewed as a "complex system" with diverse features and many components that can give rise to unexpected emergent phenomena, revealing much about its own engineering. This book brings together chapter contributions from a workshop held at the Santa Fe Institute in March 2001. This volume captures a snapshot of some features of the Internet that may be fruitfully approached using a complex systems perspective, meaning using interdisciplinary tools and methods to tackle the subject area. The Internet penetrates the socioeconomic fabric of everyday life; a broader and deeper grasp of the Internet may be needed to meet the challenges facing the future. The resulting empirical data have already proven to be invaluable for gaining novel insights into the network's spatio-temporal dynamics, and can be expected to become even more important when tryin to explain the Internet's complex and emergent behavior in terms of elementary networking-based mechanisms. The discoveries of fractal or self-similar network traffic traces, power-law behavior in network topology and World Wide Web connectivity are instances of unsuspected, emergent system traits. Another important factor at the heart of fair, efficient, and stable sharing of network resources is user behavior. Network systems, when habited by selfish or greedy users, take on the traits of a noncooperative multi-party game, and their stability and efficiency are integral to understanding the overall system and its dynamics. Lastly, fault-tolerance and robustness of large-scale network systems can exhibit spatial and temporal correlations whose effective analysis and management may benefit from rescaling techniques applied in certain physical and biological systems. The present book will bring together several of the leading workers involved in the analysis of complex systems with the future development of the Internet.
Large-scale HTS bulks for magnetic application
Energy Technology Data Exchange (ETDEWEB)
Werfel, Frank N., E-mail: werfel@t-online.de [Adelwitz Technologiezentrum GmbH (ATZ), Rittergut Adelwitz 16, 04886 Arzberg-Adelwitz (Germany); Floegel-Delor, Uta; Riedel, Thomas; Goebel, Bernd; Rothfeld, Rolf; Schirrmeister, Peter; Wippich, Dieter [Adelwitz Technologiezentrum GmbH (ATZ), Rittergut Adelwitz 16, 04886 Arzberg-Adelwitz (Germany)
2013-01-15
Highlights: ► ATZ Company has constructed about 130 HTS magnet systems. ► Multi-seeded YBCO bulks joint the way for large-scale application. ► Levitation platforms demonstrate “superconductivity” to a great public audience (100 years anniversary). ► HTS magnetic bearings show forces up to 1 t. ► Modular HTS maglev vacuum cryostats are tested for train demonstrators in Brazil, China and Germany. -- Abstract: ATZ Company has constructed about 130 HTS magnet systems using high-Tc bulk magnets. A key feature in scaling-up is the fabrication of YBCO melts textured multi-seeded large bulks with three to eight seeds. Except of levitation, magnetization, trapped field and hysteresis, we review system engineering parameters of HTS magnetic linear and rotational bearings like compactness, cryogenics, power density, efficiency and robust construction. We examine mobile compact YBCO bulk magnet platforms cooled with LN{sub 2} and Stirling cryo-cooler for demonstrator use. Compact cryostats for Maglev train operation contain 24 pieces of 3-seed bulks and can levitate 2500–3000 N at 10 mm above a permanent magnet (PM) track. The effective magnetic distance of the thermally insulated bulks is 2 mm only; the stored 2.5 l LN{sub 2} allows more than 24 h operation without refilling. 34 HTS Maglev vacuum cryostats are manufactured tested and operate in Germany, China and Brazil. The magnetic levitation load to weight ratio is more than 15, and by group assembling the HTS cryostats under vehicles up to 5 t total loads levitated above a magnetic track is achieved.
Large Scale Computing and Storage Requirements for Nuclear Physics Research
Energy Technology Data Exchange (ETDEWEB)
Gerber, Richard A.; Wasserman, Harvey J.
2012-03-02
IThe National Energy Research Scientific Computing Center (NERSC) is the primary computing center for the DOE Office of Science, serving approximately 4,000 users and hosting some 550 projects that involve nearly 700 codes for a wide variety of scientific disciplines. In addition to large-scale computing resources NERSC provides critical staff support and expertise to help scientists make the most efficient use of these resources to advance the scientific mission of the Office of Science. In May 2011, NERSC, DOE’s Office of Advanced Scientific Computing Research (ASCR) and DOE’s Office of Nuclear Physics (NP) held a workshop to characterize HPC requirements for NP research over the next three to five years. The effort is part of NERSC’s continuing involvement in anticipating future user needs and deploying necessary resources to meet these demands. The workshop revealed several key requirements, in addition to achieving its goal of characterizing NP computing. The key requirements include: 1. Larger allocations of computational resources at NERSC; 2. Visualization and analytics support; and 3. Support at NERSC for the unique needs of experimental nuclear physicists. This report expands upon these key points and adds others. The results are based upon representative samples, called “case studies,” of the needs of science teams within NP. The case studies were prepared by NP workshop participants and contain a summary of science goals, methods of solution, current and future computing requirements, and special software and support needs. Participants were also asked to describe their strategy for computing in the highly parallel, “multi-core” environment that is expected to dominate HPC architectures over the next few years. The report also includes a section with NERSC responses to the workshop findings. NERSC has many initiatives already underway that address key workshop findings and all of the action items are aligned with NERSC strategic plans.
Large-scale electrohydrodynamic organic nanowire printing, lithography, and electronics
Lee, Tae-Woo
2014-03-01
Although the many merits of organic nanowires (NWs), a reliable process for controllable and large-scale assembly of highly-aligned NW parallel arrays based on ``individual control (IC)'' of NWs must be developed since inorganic NWs are mainly grown vertically on substrates and thus have been transferred to the target substrates by any of several non-individually controlled (non-IC) methods such as contact-printing technologies with unidirectional massive alignment, and the random dispersion method with disordered alignment. Controlled alignment and patterning of individual semiconducting NWs at a desired position in a large area is a major requirement for practical electronic device applications. Large-area, high-speed printing of highly-aligned individual NWs that allows control of the exact numbers of wires, and dimensions and their orientations, and its use in high-speed large-area nanolithography is a significant challenge for practical applications. Here we use a high-speed electrohydrodynamic organic nanowire printer to print large-area organic semiconducting nanowire arrays directly on device substrates in an accurately individually-controlled manner; this method also enables sophisticated large-area nanowire lithography for nano-electronics. We achieve an unprecedented high maximum field-effect mobility up to 9.7 cm2 .V-1 .s-1 with extremely low contact resistance (<5.53 Ω . cm) even in nano-channel transistors based on single-stranded semiconducting NWs. We also demonstrate complementary inverter circuit arrays consist of well-aligned p-type and n-type organic semiconducting NWs. Extremely fast nanolithography using printed semiconducting nanowire arrays provide a very simple, reliable method of fabricating large-area and flexible nano-electronics.
Distribution probability of large-scale landslides in central Nepal
Timilsina, Manita; Bhandary, Netra P.; Dahal, Ranjan Kumar; Yatabe, Ryuichi
2014-12-01
Large-scale landslides in the Himalaya are defined as huge, deep-seated landslide masses that occurred in the geological past. They are widely distributed in the Nepal Himalaya. The steep topography and high local relief provide high potential for such failures, whereas the dynamic geology and adverse climatic conditions play a key role in the occurrence and reactivation of such landslides. The major geoscientific problems related with such large-scale landslides are 1) difficulties in their identification and delineation, 2) sources of small-scale failures, and 3) reactivation. Only a few scientific publications have been published concerning large-scale landslides in Nepal. In this context, the identification and quantification of large-scale landslides and their potential distribution are crucial. Therefore, this study explores the distribution of large-scale landslides in the Lesser Himalaya. It provides simple guidelines to identify large-scale landslides based on their typical characteristics and using a 3D schematic diagram. Based on the spatial distribution of landslides, geomorphological/geological parameters and logistic regression, an equation of large-scale landslide distribution is also derived. The equation is validated by applying it to another area. For the new area, the area under the receiver operating curve of the landslide distribution probability in the new area is 0.699, and a distribution probability value could explain > 65% of existing landslides. Therefore, the regression equation can be applied to areas of the Lesser Himalaya of central Nepal with similar geological and geomorphological conditions.
Organised convection embedded in a large-scale flow
Naumann, Ann Kristin; Stevens, Bjorn; Hohenegger, Cathy
2017-04-01
In idealised simulations of radiative convective equilibrium, convection aggregates spontaneously from randomly distributed convective cells into organized mesoscale convection despite homogeneous boundary conditions. Although these simulations apply very idealised setups, the process of self-aggregation is thought to be relevant for the development of tropical convective systems. One feature that idealised simulations usually neglect is the occurrence of a large-scale background flow. In the tropics, organised convection is embedded in a large-scale circulation system, which advects convection in along-wind direction and alters near surface convergence in the convective areas. A large-scale flow also modifies the surface fluxes, which are expected to be enhanced upwind of the convective area if a large-scale flow is applied. Convective clusters that are embedded in a large-scale flow therefore experience an asymmetric component of the surface fluxes, which influences the development and the pathway of a convective cluster. In this study, we use numerical simulations with explicit convection and add a large-scale flow to the established setup of radiative convective equilibrium. We then analyse how aggregated convection evolves when being exposed to wind forcing. The simulations suggest that convective line structures are more prevalent if a large-scale flow is present and that convective clusters move considerably slower than advection by the large-scale flow would suggest. We also study the asymmetric component of convective aggregation due to enhanced surface fluxes, and discuss the pathway and speed of convective clusters as a function of the large-scale wind speed.
Probabilistic cartography of the large-scale structure
Leclercq, Florent; Lavaux, Guilhem; Wandelt, Benjamin
2015-01-01
The BORG algorithm is an inference engine that derives the initial conditions given a cosmological model and galaxy survey data, and produces physical reconstructions of the underlying large-scale structure by assimilating the data into the model. We present the application of BORG to real galaxy catalogs and describe the primordial and late-time large-scale structure in the considered volumes. We then show how these results can be used for building various probabilistic maps of the large-scale structure, with rigorous propagation of uncertainties. In particular, we study dynamic cosmic web elements and secondary effects in the cosmic microwave background.
Large scale and big data processing and management
Sakr, Sherif
2014-01-01
Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments.The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-bas
Big data Mining Using Very-Large-Scale Data Processing Platforms
Directory of Open Access Journals (Sweden)
Ms. K. Deepthi
2016-02-01
Full Text Available Big Data consists of large-volume, complex, growing data sets with multiple, heterogenous sources. With the tremendous development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. The MapReduce programming mode which has parallel processing ability to analyze the large-scale network. MapReduce is a programming model that allows easy development of scalable parallel applications to process big data on large clusters of commodity machines. Google’s MapReduce or its open-source equivalent Hadoop is a powerful tool for building such applications.
Accelerating large-scale protein structure alignments with graphics processing units
Directory of Open Access Journals (Sweden)
Pang Bin
2012-02-01
Full Text Available Abstract Background Large-scale protein structure alignment, an indispensable tool to structural bioinformatics, poses a tremendous challenge on computational resources. To ensure structure alignment accuracy and efficiency, efforts have been made to parallelize traditional alignment algorithms in grid environments. However, these solutions are costly and of limited accessibility. Others trade alignment quality for speedup by using high-level characteristics of structure fragments for structure comparisons. Findings We present ppsAlign, a parallel protein structure Alignment framework designed and optimized to exploit the parallelism of Graphics Processing Units (GPUs. As a general-purpose GPU platform, ppsAlign could take many concurrent methods, such as TM-align and Fr-TM-align, into the parallelized algorithm design. We evaluated ppsAlign on an NVIDIA Tesla C2050 GPU card, and compared it with existing software solutions running on an AMD dual-core CPU. We observed a 36-fold speedup over TM-align, a 65-fold speedup over Fr-TM-align, and a 40-fold speedup over MAMMOTH. Conclusions ppsAlign is a high-performance protein structure alignment tool designed to tackle the computational complexity issues from protein structural data. The solution presented in this paper allows large-scale structure comparisons to be performed using massive parallel computing power of GPU.
Optimization of nanofountain probe microfabrication enables large-scale nanopatterning
Safi, Asmahan; Kang, Wonmo; Czapleski, David; Divan, Ralu; Moldovan, Nicolae; Espinosa, Horacio D.
2013-12-01
A technological gap in nanomanufacturing has prevented the translation of many nanomaterial discoveries into real-world commercialized products. Bridging this gap requires a paradigm shift in methods for fabricating nanoscale devices in a reliable and repeatable fashion. Here we present the optimized fabrication of a robust and scalable nanoscale delivery platform, the nanofountain probe (NFP), for parallel direct-write of functional materials. Microfabrication of a new generation of NFP was realized with the aim of increasing the uniformity of the device structure. Optimized probe geometry was integrated into the design and fabrication process by modifying the precursor mask dimensions and by using an isotropic selective dry etching of the outer shell that defines the protrusion area. Probes with well-conserved sharp tips and controlled protrusion lengths were obtained. Sealing effectiveness of the channels was optimized. A conformal tetraethyl orthosilicate based oxide layer increased the sealing efficacy while minimizing the required thickness. A compensation scheme based on the residual stresses in each layer was implemented to minimize bending of the cantilever after releasing the device. The device was tested by patterning ferritin catalyst arrays on silicon dioxide with sub-100 nm resolution. The optimized probes increased the control over the parallel patterning resolution which enables manufacturing of ordered arrays of nanomaterials.
The theory of large-scale ocean circulation
National Research Council Canada - National Science Library
Samelson, R. M
2011-01-01
"This is a concise but comprehensive introduction to the basic elements of the theory of large-scale ocean circulation for advanced students and researchers"-- "Mounting evidence that human activities...
Learning networks for sustainable, large-scale improvement.
McCannon, C Joseph; Perla, Rocco J
2009-05-01
Large-scale improvement efforts known as improvement networks offer structured opportunities for exchange of information and insights into the adaptation of clinical protocols to a variety of settings.
Personalized Opportunistic Computing for CMS at Large Scale
CERN. Geneva
2015-01-01
**Douglas Thain** is an Associate Professor of Computer Science and Engineering at the University of Notre Dame, where he designs large scale distributed computing systems to power the needs of advanced science and...
An Evaluation Framework for Large-Scale Network Structures
DEFF Research Database (Denmark)
Pedersen, Jens Myrup; Knudsen, Thomas Phillip; Madsen, Ole Brun
2004-01-01
An evaluation framework for large-scale network structures is presented, which facilitates evaluations and comparisons of different physical network structures. A number of quantitative and qualitative parameters are presented, and their importance to networks discussed. Choosing a network...
Modified gravity and large scale flows, a review
Mould, Jeremy
2017-02-01
Large scale flows have been a challenging feature of cosmography ever since galaxy scaling relations came on the scene 40 years ago. The next generation of surveys will offer a serious test of the standard cosmology.
Some perspective on the Large Scale Scientific Computation Research
Institute of Scientific and Technical Information of China (English)
DU Qiang
2004-01-01
@@ The "Large Scale Scientific Computation (LSSC) Research"project is one of the State Major Basic Research projects funded by the Chinese Ministry of Science and Technology in the field ofinformation science and technology.
Some perspective on the Large Scale Scientific Computation Research
Institute of Scientific and Technical Information of China (English)
DU; Qiang
2004-01-01
The "Large Scale Scientific Computation (LSSC) Research"project is one of the State Major Basic Research projects funded by the Chinese Ministry of Science and Technology in the field ofinformation science and technology.……
PetroChina to Expand Dushanzi Refinery on Large Scale
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
@@ A large-scale expansion project for PetroChina Dushanzi Petrochemical Company has been given the green light, a move which will make it one of the largest refineries and petrochemical complexes in the country.
Needs, opportunities, and options for large scale systems research
Energy Technology Data Exchange (ETDEWEB)
Thompson, G.L.
1984-10-01
The Office of Energy Research was recently asked to perform a study of Large Scale Systems in order to facilitate the development of a true large systems theory. It was decided to ask experts in the fields of electrical engineering, chemical engineering and manufacturing/operations research for their ideas concerning large scale systems research. The author was asked to distribute a questionnaire among these experts to find out their opinions concerning recent accomplishments and future research directions in large scale systems research. He was also requested to convene a conference which included three experts in each area as panel members to discuss the general area of large scale systems research. The conference was held on March 26--27, 1984 in Pittsburgh with nine panel members, and 15 other attendees. The present report is a summary of the ideas presented and the recommendations proposed by the attendees.
Traffic Flow Prediction Model for Large-Scale Road Network Based on Cloud Computing
Directory of Open Access Journals (Sweden)
Zhaosheng Yang
2014-01-01
Full Text Available To increase the efficiency and precision of large-scale road network traffic flow prediction, a genetic algorithm-support vector machine (GA-SVM model based on cloud computing is proposed in this paper, which is based on the analysis of the characteristics and defects of genetic algorithm and support vector machine. In cloud computing environment, firstly, SVM parameters are optimized by the parallel genetic algorithm, and then this optimized parallel SVM model is used to predict traffic flow. On the basis of the traffic flow data of Haizhu District in Guangzhou City, the proposed model was verified and compared with the serial GA-SVM model and parallel GA-SVM model based on MPI (message passing interface. The results demonstrate that the parallel GA-SVM model based on cloud computing has higher prediction accuracy, shorter running time, and higher speedup.
Comparison Between Overtopping Discharge in Small and Large Scale Models
DEFF Research Database (Denmark)
Helgason, Einar; Burcharth, Hans F.
2006-01-01
small and large scale model tests show no clear evidence of scale effects for overtopping above a threshold value. In the large scale model no overtopping was measured for waveheights below Hs = 0.5m as the water sunk into the voids between the stones on the crest. For low overtopping scale effects...... are presented as the small-scale model underpredicts the overtopping discharge....
Efficient algorithms for collaborative decision making for large scale settings
DEFF Research Database (Denmark)
Assent, Ira
2011-01-01
Collaborative decision making is a successful approach in settings where data analysis and querying can be done interactively. In large scale systems with huge data volumes or many users, collaboration is often hindered by impractical runtimes. Existing work on improving collaboration focuses...... to bring about more effective and more efficient retrieval systems that support the users' decision making process. We sketch promising research directions for more efficient algorithms for collaborative decision making, especially for large scale systems....
Large-scale simulations of error-prone quantum computation devices
Energy Technology Data Exchange (ETDEWEB)
Trieu, Doan Binh
2009-07-01
The theoretical concepts of quantum computation in the idealized and undisturbed case are well understood. However, in practice, all quantum computation devices do suffer from decoherence effects as well as from operational imprecisions. This work assesses the power of error-prone quantum computation devices using large-scale numerical simulations on parallel supercomputers. We present the Juelich Massively Parallel Ideal Quantum Computer Simulator (JUMPIQCS), that simulates a generic quantum computer on gate level. It comprises an error model for decoherence and operational errors. The robustness of various algorithms in the presence of noise has been analyzed. The simulation results show that for large system sizes and long computations it is imperative to actively correct errors by means of quantum error correction. We implemented the 5-, 7-, and 9-qubit quantum error correction codes. Our simulations confirm that using error-prone correction circuits with non-fault-tolerant quantum error correction will always fail, because more errors are introduced than being corrected. Fault-tolerant methods can overcome this problem, provided that the single qubit error rate is below a certain threshold. We incorporated fault-tolerant quantum error correction techniques into JUMPIQCS using Steane's 7-qubit code and determined this threshold numerically. Using the depolarizing channel as the source of decoherence, we find a threshold error rate of (5.2{+-}0.2) x 10{sup -6}. For Gaussian distributed operational over-rotations the threshold lies at a standard deviation of 0.0431{+-}0.0002. We can conclude that quantum error correction is especially well suited for the correction of operational imprecisions and systematic over-rotations. For realistic simulations of specific quantum computation devices we need to extend the generic model to dynamic simulations, i.e. time-dependent Hamiltonian simulations of realistic hardware models. We focus on today's most advanced
Vector dissipativity theory for large-scale impulsive dynamical systems
Directory of Open Access Journals (Sweden)
Haddad Wassim M.
2004-01-01
Full Text Available Modern complex large-scale impulsive systems involve multiple modes of operation placing stringent demands on controller analysis of increasing complexity. In analyzing these large-scale systems, it is often desirable to treat the overall impulsive system as a collection of interconnected impulsive subsystems. Solution properties of the large-scale impulsive system are then deduced from the solution properties of the individual impulsive subsystems and the nature of the impulsive system interconnections. In this paper, we develop vector dissipativity theory for large-scale impulsive dynamical systems. Specifically, using vector storage functions and vector hybrid supply rates, dissipativity properties of the composite large-scale impulsive systems are shown to be determined from the dissipativity properties of the impulsive subsystems and their interconnections. Furthermore, extended Kalman-Yakubovich-Popov conditions, in terms of the impulsive subsystem dynamics and interconnection constraints, characterizing vector dissipativeness via vector system storage functions, are derived. Finally, these results are used to develop feedback interconnection stability results for large-scale impulsive dynamical systems using vector Lyapunov functions.
Large Scale Meteorological Pattern of Extreme Rainfall in Indonesia
Kuswanto, Heri; Grotjahn, Richard; Rachmi, Arinda; Suhermi, Novri; Oktania, Erma; Wijaya, Yosep
2014-05-01
Extreme Weather Events (EWEs) cause negative impacts socially, economically, and environmentally. Considering these facts, forecasting EWEs is crucial work. Indonesia has been identified as being among the countries most vulnerable to the risk of natural disasters, such as floods, heat waves, and droughts. Current forecasting of extreme events in Indonesia is carried out by interpreting synoptic maps for several fields without taking into account the link between the observed events in the 'target' area with remote conditions. This situation may cause misidentification of the event leading to an inaccurate prediction. Grotjahn and Faure (2008) compute composite maps from extreme events (including heat waves and intense rainfall) to help forecasters identify such events in model output. The composite maps show large scale meteorological patterns (LSMP) that occurred during historical EWEs. Some vital information about the EWEs can be acquired from studying such maps, in addition to providing forecaster guidance. Such maps have robust mid-latitude meteorological patterns (for Sacramento and California Central Valley, USA EWEs). We study the performance of the composite approach for tropical weather condition such as Indonesia. Initially, the composite maps are developed to identify and forecast the extreme weather events in Indramayu district- West Java, the main producer of rice in Indonesia and contributes to about 60% of the national total rice production. Studying extreme weather events happening in Indramayu is important since EWEs there affect national agricultural and fisheries activities. During a recent EWE more than a thousand houses in Indramayu suffered from serious flooding with each home more than one meter underwater. The flood also destroyed a thousand hectares of rice plantings in 5 regencies. Identifying the dates of extreme events is one of the most important steps and has to be carried out carefully. An approach has been applied to identify the
Real-Time Large Scale 3d Reconstruction by Fusing Kinect and Imu Data
Huai, J.; Zhang, Y.; Yilmaz, A.
2015-08-01
Kinect-style RGB-D cameras have been used to build large scale dense 3D maps for indoor environments. These maps can serve many purposes such as robot navigation, and augmented reality. However, to generate dense 3D maps of large scale environments is still very challenging. In this paper, we present a mapping system for 3D reconstruction that fuses measurements from a Kinect and an inertial measurement unit (IMU) to estimate motion. Our major achievements include: (i) Large scale consistent 3D reconstruction is realized by volume shifting and loop closure; (ii) The coarse-to-fine iterative closest point (ICP) algorithm, the SIFT odometry, and IMU odometry are combined to robustly and precisely estimate pose. In particular, ICP runs routinely to track the Kinect motion. If ICP fails in planar areas, the SIFT odometry provides incremental motion estimate. If both ICP and the SIFT odometry fail, e.g., upon abrupt motion or inadequate features, the incremental motion is estimated by the IMU. Additionally, the IMU also observes the roll and pitch angles which can reduce long-term drift of the sensor assembly. In experiments on a consumer laptop, our system estimates motion at 8Hz on average while integrating color images to the local map and saving volumes of meshes concurrently. Moreover, it is immune to tracking failures, and has smaller drift than the state-of-the-art systems in large scale reconstruction.
Energy Technology Data Exchange (ETDEWEB)
NONE
2008-10-15
Large-scale research facilities are of inestimable strategic value for science and research and, hence, for the Dutch knowledge economy. In July 2007, the Dutch Minister of Education, Culture and Science set up the National Roadmap Committee for Large-Scale Research Facilities, whose main task was to advise him as to which large-scale research facilities the Netherlands should construct or participate in within an international context. In the present advisory report, the Committee presents 25 large-scale research facilities whose construction or operation the Committee believes is important for the robustness and innovativeness of the Dutch science system. [Dutch] Grootschalige onderzoeksfaciliteiten zijn van onschatbaar strategisch belang voor onderzoek en wetenschap en daarmee voor de Nederlandse kenniseconomie. De Minister van OCW heeft in juli 2007 de Commissie Nationale Roadmap Grootschalige Onderzoeksfaciliteiten ingesteld met het primaire doel hem te adviseren welke grootschalige onderzoeksfaciliteiten geschikt zijn om in Nederland zelf te bouwen of om in een internationale context aan mee te doen. De Commissie presenteert in dit advies 25 grootschalige onderzoeksfaciliteiten waarvan naar het oordeel van de Commissie de bouw en exploitatie van belang zijn voor de vitaliteit en het innovatief vermogen van het Nederlandse wetenschap systeem.
Fox, Geoffrey C; Messina, Guiseppe C
2014-01-01
A clear illustration of how parallel computers can be successfully appliedto large-scale scientific computations. This book demonstrates how avariety of applications in physics, biology, mathematics and other scienceswere implemented on real parallel computers to produce new scientificresults. It investigates issues of fine-grained parallelism relevant forfuture supercomputers with particular emphasis on hypercube architecture. The authors describe how they used an experimental approach to configuredifferent massively parallel machines, design and implement basic systemsoftware, and develop
Large Scale Computing and Storage Requirements for High Energy Physics
Energy Technology Data Exchange (ETDEWEB)
Gerber, Richard A.; Wasserman, Harvey
2010-11-24
The National Energy Research Scientific Computing Center (NERSC) is the leading scientific computing facility for the Department of Energy's Office of Science, providing high-performance computing (HPC) resources to more than 3,000 researchers working on about 400 projects. NERSC provides large-scale computing resources and, crucially, the support and expertise needed for scientists to make effective use of them. In November 2009, NERSC, DOE's Office of Advanced Scientific Computing Research (ASCR), and DOE's Office of High Energy Physics (HEP) held a workshop to characterize the HPC resources needed at NERSC to support HEP research through the next three to five years. The effort is part of NERSC's legacy of anticipating users needs and deploying resources to meet those demands. The workshop revealed several key points, in addition to achieving its goal of collecting and characterizing computing requirements. The chief findings: (1) Science teams need access to a significant increase in computational resources to meet their research goals; (2) Research teams need to be able to read, write, transfer, store online, archive, analyze, and share huge volumes of data; (3) Science teams need guidance and support to implement their codes on future architectures; and (4) Projects need predictable, rapid turnaround of their computational jobs to meet mission-critical time constraints. This report expands upon these key points and includes others. It also presents a number of case studies as representative of the research conducted within HEP. Workshop participants were asked to codify their requirements in this case study format, summarizing their science goals, methods of solution, current and three-to-five year computing requirements, and software and support needs. Participants were also asked to describe their strategy for computing in the highly parallel, multi-core environment that is expected to dominate HPC architectures over the next few years
Large-scale-vortex dynamos in planar rotating convection
Guervilly, Céline; Jones, Chris A
2016-01-01
Several recent studies have demonstrated how large-scale vortices may arise spontaneously in rotating planar convection. Here we examine the dynamo properties of such flows in rotating Boussinesq convection. For moderate values of the magnetic Reynolds number ($100 \\lesssim Rm \\lesssim 550$, with $Rm$ based on the box depth and the convective velocity), a large-scale (i.e. system-size) magnetic field is generated. The amplitude of the magnetic energy oscillates in time, out of phase with the oscillating amplitude of the large-scale vortex. The dynamo mechanism relies on those components of the flow that have length scales lying between that of the large-scale vortex and the typical convective cell size; smaller-scale flows are not required. The large-scale vortex plays a crucial role in the magnetic induction despite being essentially two-dimensional. For larger magnetic Reynolds numbers, the dynamo is small scale, with a magnetic energy spectrum that peaks at the scale of the convective cells. In this case, ...
Stochastic variability of large-scale oceanic flows above topography anomalies
Venaille, Antoine; Molines, J -M; Barnier, B
2011-01-01
Large-scale oceanic currents show large fluctuations at decadal, centennial and even millennial time scales. Here, we describe a new stochastic variability mechanism which is genuinely internal to the ocean, i.e. not due to fluctuations in atmospheric forcing. The key ingredient is the existence of closed contours of bottom topography surrounded by a stirring region of enhanced eddy activity. This configuration leads to the formation of a robust but highly variable vortex above the topography anomaly. The vortex dynamics integrates the white noise forcing of oceanic eddies into a red noise signal for the large scale volume transport of the vortex. The fluctuations of the transport of the Zapiola anticyclone (100 Sv) in the Argentine basin are argued to be an example of such eddy-driven stochastic variability, on the basis of a 310 years long simulation of a comprehensive ocean model run driven by a repeated-year forcing.
An inertia-free filter line-search algorithm for large-scale nonlinear programming
Energy Technology Data Exchange (ETDEWEB)
Chiang, Nai-Yuan; Zavala, Victor M.
2016-02-15
We present a filter line-search algorithm that does not require inertia information of the linear system. This feature enables the use of a wide range of linear algebra strategies and libraries, which is essential to tackle large-scale problems on modern computing architectures. The proposed approach performs curvature tests along the search step to detect negative curvature and to trigger convexification. We prove that the approach is globally convergent and we implement the approach within a parallel interior-point framework to solve large-scale and highly nonlinear problems. Our numerical tests demonstrate that the inertia-free approach is as efficient as inertia detection via symmetric indefinite factorizations. We also demonstrate that the inertia-free approach can lead to reductions in solution time because it reduces the amount of convexification needed.
Large-Scale Cosmic-Ray Anisotropy as a Probe of Interstellar Turbulence
Giacinti, Gwenael
2016-01-01
We calculate the large-scale cosmic-ray (CR) anisotropies predicted for a range of Goldreich-Sridhar (GS) and isotropic models of interstellar turbulence, and compare them with IceTop data. In general, the predicted CR anisotropy is not a pure dipole; the cold spots reported at 400 TeV and 2 PeV are consistent with a GS model that contains a smooth deficit of parallel-propagating waves and a broad resonance function, although some other possibilities cannot, as yet, be ruled out. In particular, isotropic fast magnetosonic wave turbulence can match the observations at high energy, but cannot accommodate an energy-dependence in the shape of the CR anisotropy. Our findings suggest that improved data on the large-scale CR anisotropy could provide a valuable probe of the properties - notably the power-spectrum - of the local interstellar turbulence.
Seismic safety in conducting large-scale blasts
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.
Acoustic Studies of the Large Scale Ocean Circulation
Menemenlis, Dimitris
1999-01-01
Detailed knowledge of ocean circulation and its transport properties is prerequisite to an understanding of the earth's climate and of important biological and chemical cycles. Results from two recent experiments, THETIS-2 in the Western Mediterranean and ATOC in the North Pacific, illustrate the use of ocean acoustic tomography for studies of the large scale circulation. The attraction of acoustic tomography is its ability to sample and average the large-scale oceanic thermal structure, synoptically, along several sections, and at regular intervals. In both studies, the acoustic data are compared to, and then combined with, general circulation models, meteorological analyses, satellite altimetry, and direct measurements from ships. Both studies provide complete regional descriptions of the time-evolving, three-dimensional, large scale circulation, albeit with large uncertainties. The studies raise serious issues about existing ocean observing capability and provide guidelines for future efforts.
Human pescadillo induces large-scale chromatin unfolding
Institute of Scientific and Technical Information of China (English)
ZHANG Hao; FANG Yan; HUANG Cuifen; YANG Xiao; YE Qinong
2005-01-01
The human pescadillo gene encodes a protein with a BRCT domain. Pescadillo plays an important role in DNA synthesis, cell proliferation and transformation. Since BRCT domains have been shown to induce chromatin large-scale unfolding, we tested the role of Pescadillo in regulation of large-scale chromatin unfolding. To this end, we isolated the coding region of Pescadillo from human mammary MCF10A cells. Compared with the reported sequence, the isolated Pescadillo contains in-frame deletion from amino acid 580 to 582. Targeting the Pescadillo to an amplified, lac operator-containing chromosome region in the mammalian genome results in large-scale chromatin decondensation. This unfolding activity maps to the BRCT domain of Pescadillo. These data provide a new clue to understanding the vital role of Pescadillo.
Transport of Large Scale Poloidal Flux in Black Hole Accretion
Beckwith, Kris; Krolik, Julian H
2009-01-01
We perform a global, three-dimensional GRMHD simulation of an accretion torus embedded in a large scale vertical magnetic field orbiting a Schwarzschild black hole. This simulation investigates how a large scale vertical field evolves within a turbulent accretion disk and whether global magnetic field configurations suitable for launching jets and winds can develop. We identify a ``coronal mechanism'' of magnetic flux motion, which dominates the global flux evolution. In this coronal mechanism, magnetic stresses driven by orbital shear create large-scale half-loops of magnetic field that stretch radially inward and then reconnect, leading to discontinuous jumps in the location of magnetic flux. This mechanism is supplemented by a smaller amount of flux advection in the accretion flow proper. Because the black hole in this case does not rotate, the magnetic flux on the horizon determines the mean magnetic field strength in the funnel around the disk axis; this field strength is regulated by a combination of th...
Large Scale Anomalies of the Cosmic Microwave Background with Planck
DEFF Research Database (Denmark)
Frejsel, Anne Mette
This thesis focuses on the large scale anomalies of the Cosmic Microwave Background (CMB) and their possible origins. The investigations consist of two main parts. The first part is on statistical tests of the CMB, and the consistency of both maps and power spectrum. We find that the Planck data...... is very consistent, while the WMAP 9 year release appears more contaminated by non-CMB residuals than the 7 year release. The second part is concerned with the anomalies of the CMB from two approaches. One is based on an extended inflationary model as the origin of one specific large scale anomaly, namely....... Here we find evidence that the Planck CMB maps contain residual radiation in the loop areas, which can be linked to some of the large scale CMB anomalies: the point-parity asymmetry, the alignment of quadrupole and octupole and the dipolemodulation....
Large Scale Magnetohydrodynamic Dynamos from Cylindrical Differentially Rotating Flows
Ebrahimi, F
2015-01-01
For cylindrical differentially rotating plasmas threaded with a uniform vertical magnetic field, we study large-scale magnetic field generation from finite amplitude perturbations using analytic theory and direct numerical simulations. Analytically, we impose helical fluctuations, a seed field, and a background flow and use quasi-linear theory for a single mode. The predicted large-scale field growth agrees with numerical simulations in which the magnetorotational instability (MRI) arises naturally. The vertically and azimuthally averaged toroidal field is generated by a fluctuation-induced EMF that depends on differential rotation. Given fluctuations, the method also predicts large-scale field growth for MRI-stable rotation profiles and flows with no rotation but shear.
A relativistic signature in large-scale structure
Bartolo, Nicola; Bertacca, Daniele; Bruni, Marco; Koyama, Kazuya; Maartens, Roy; Matarrese, Sabino; Sasaki, Misao; Verde, Licia; Wands, David
2016-09-01
In General Relativity, the constraint equation relating metric and density perturbations is inherently nonlinear, leading to an effective non-Gaussianity in the dark matter density field on large scales-even if the primordial metric perturbation is Gaussian. Intrinsic non-Gaussianity in the large-scale dark matter overdensity in GR is real and physical. However, the variance smoothed on a local physical scale is not correlated with the large-scale curvature perturbation, so that there is no relativistic signature in the galaxy bias when using the simplest model of bias. It is an open question whether the observable mass proxies such as luminosity or weak lensing correspond directly to the physical mass in the simple halo bias model. If not, there may be observables that encode this relativistic signature.
Large Scale Anomalies of the Cosmic Microwave Background with Planck
DEFF Research Database (Denmark)
Frejsel, Anne Mette
This thesis focuses on the large scale anomalies of the Cosmic Microwave Background (CMB) and their possible origins. The investigations consist of two main parts. The first part is on statistical tests of the CMB, and the consistency of both maps and power spectrum. We find that the Planck data...... is very consistent, while the WMAP 9 year release appears more contaminated by non-CMB residuals than the 7 year release. The second part is concerned with the anomalies of the CMB from two approaches. One is based on an extended inflationary model as the origin of one specific large scale anomaly, namely....... Here we find evidence that the Planck CMB maps contain residual radiation in the loop areas, which can be linked to some of the large scale CMB anomalies: the point-parity asymmetry, the alignment of quadrupole and octupole and the dipolemodulation....
Large-scale networks in engineering and life sciences
Findeisen, Rolf; Flockerzi, Dietrich; Reichl, Udo; Sundmacher, Kai
2014-01-01
This edited volume provides insights into and tools for the modeling, analysis, optimization, and control of large-scale networks in the life sciences and in engineering. Large-scale systems are often the result of networked interactions between a large number of subsystems, and their analysis and control are becoming increasingly important. The chapters of this book present the basic concepts and theoretical foundations of network theory and discuss its applications in different scientific areas such as biochemical reactions, chemical production processes, systems biology, electrical circuits, and mobile agents. The aim is to identify common concepts, to understand the underlying mathematical ideas, and to inspire discussions across the borders of the various disciplines. The book originates from the interdisciplinary summer school “Large Scale Networks in Engineering and Life Sciences” hosted by the International Max Planck Research School Magdeburg, September 26-30, 2011, and will therefore be of int...
A. Townsend Peterson; Daniel A. Kluza
2005-01-01
Large-scale assessments of the distribution and diversity of birds have been challenged by the need for a robust methodology for summarizing or predicting species' geographic distributions (e.g. Beard et al. 1999, Manel et al. 1999, Saveraid et al. 2001). Methodologies used in such studies have at times been inappropriate, or even more frequently limited in their...
Large-scale hydrology in Europe : observed patterns and model performance
Energy Technology Data Exchange (ETDEWEB)
Gudmundsson, Lukas
2011-06-15
In a changing climate, terrestrial water storages are of great interest as water availability impacts key aspects of ecosystem functioning. Thus, a better understanding of the variations of wet and dry periods will contribute to fully grasp processes of the earth system such as nutrient cycling and vegetation dynamics. Currently, river runoff from small, nearly natural, catchments is one of the few variables of the terrestrial water balance that is regularly monitored with detailed spatial and temporal coverage on large scales. River runoff, therefore, provides a foundation to approach European hydrology with respect to observed patterns on large scales, with regard to the ability of models to capture these.The analysis of observed river flow from small catchments, focused on the identification and description of spatial patterns of simultaneous temporal variations of runoff. These are dominated by large-scale variations of climatic variables but also altered by catchment processes. It was shown that time series of annual low, mean and high flows follow the same atmospheric drivers. The observation that high flows are more closely coupled to large scale atmospheric drivers than low flows, indicates the increasing influence of catchment properties on runoff under dry conditions. Further, it was shown that the low-frequency variability of European runoff is dominated by two opposing centres of simultaneous variations, such that dry years in the north are accompanied by wet years in the south.Large-scale hydrological models are simplified representations of our current perception of the terrestrial water balance on large scales. Quantification of the models strengths and weaknesses is the prerequisite for a reliable interpretation of simulation results. Model evaluations may also enable to detect shortcomings with model assumptions and thus enable a refinement of the current perception of hydrological systems. The ability of a multi model ensemble of nine large-scale
Large-scale synthesis of YSZ nanopowder by Pechini method
Indian Academy of Sciences (India)
Morteza Hajizadeh-Oghaz; Reza Shoja Razavi; Mohammadreza Loghman Estarki
2014-08-01
Yttria–stabilized zirconia nanopowders were synthesized on a relatively large scale using Pechini method. In the present paper, nearly spherical yttria-stabilized zirconia nanopowders with tetragonal structure were synthesized by Pechini process from zirconium oxynitrate hexahydrate, yttrium nitrate, citric acid and ethylene glycol. The phase and structural analyses were accomplished by X-ray diffraction; morphological analysis was carried out by field emission scanning electron microscopy and transmission electron microscopy. The results revealed nearly spherical yttria–stabilized zirconia powder with tetragonal crystal structure and chemical purity of 99.1% by inductively coupled plasma optical emission spectroscopy on a large scale.
Practical Large Scale Syntheses of New Drug Candidates
Institute of Scientific and Technical Information of China (English)
Hui-Yin; Li
2001-01-01
This presentation will be focus on Practical large scale syntheses of lead compounds and drug candidates from three major therapeutic areas from DuPont Pharmaceuticals Research Laboratory: 1). DMP777-a selective, non-toxic, orally active human elastase inhibitor; 2). DMP754-a potent glycoprotein IIb/IIIa antagonist; 3). R-Wafarin-the pure enantiomeric form of wafarin. The key technology used for preparation these drug candidates is asymmetric hydrogenation under very mild reaction conditions, which produced very high quality final products at large scale (＞99% de, ＞99 A% and ＞99 wt%). Some practical and GMP aspects of process development will be also discussed.……
Statistical equilibria of large scales in dissipative hydrodynamic turbulence
Dallas, Vassilios; Alexakis, Alexandros
2015-01-01
We present a numerical study of the statistical properties of three-dimensional dissipative turbulent flows at scales larger than the forcing scale. Our results indicate that the large scale flow can be described to a large degree by the truncated Euler equations with the predictions of the zero flux solutions given by absolute equilibrium theory, both for helical and non-helical flows. Thus, the functional shape of the large scale spectra can be predicted provided that scales sufficiently larger than the forcing length scale but also sufficiently smaller than the box size are examined. Deviations from the predictions of absolute equilibrium are discussed.
Fatigue Analysis of Large-scale Wind turbine
Directory of Open Access Journals (Sweden)
Zhu Yongli
2017-01-01
Full Text Available The paper does research on top flange fatigue damage of large-scale wind turbine generator. It establishes finite element model of top flange connection system with finite element analysis software MSC. Marc/Mentat, analyzes its fatigue strain, implements load simulation of flange fatigue working condition with Bladed software, acquires flange fatigue load spectrum with rain-flow counting method, finally, it realizes fatigue analysis of top flange with fatigue analysis software MSC. Fatigue and Palmgren-Miner linear cumulative damage theory. The analysis result indicates that its result provides new thinking for flange fatigue analysis of large-scale wind turbine generator, and possesses some practical engineering value.
Large-Scale Inverse Problems and Quantification of Uncertainty
Biegler, Lorenz; Ghattas, Omar
2010-01-01
Large-scale inverse problems and associated uncertainty quantification has become an important area of research, central to a wide range of science and engineering applications. Written by leading experts in the field, Large-scale Inverse Problems and Quantification of Uncertainty focuses on the computational methods used to analyze and simulate inverse problems. The text provides PhD students, researchers, advanced undergraduate students, and engineering practitioners with the perspectives of researchers in areas of inverse problems and data assimilation, ranging from statistics and large-sca
[Issues of large scale tissue culture of medicinal plant].
Lv, Dong-Mei; Yuan, Yuan; Zhan, Zhi-Lai
2014-09-01
In order to increase the yield and quality of the medicinal plant and enhance the competitive power of industry of medicinal plant in our country, this paper analyzed the status, problem and countermeasure of the tissue culture of medicinal plant on large scale. Although the biotechnology is one of the most efficient and promising means in production of medicinal plant, it still has problems such as stability of the material, safety of the transgenic medicinal plant and optimization of cultured condition. Establishing perfect evaluation system according to the characteristic of the medicinal plant is the key measures to assure the sustainable development of the tissue culture of medicinal plant on large scale.
Generation Expansion Planning Considering Integrating Large-scale Wind Generation
DEFF Research Database (Denmark)
Zhang, Chunyu; Ding, Yi; Østergaard, Jacob
2013-01-01
Generation expansion planning (GEP) is the problem of finding the optimal strategy to plan the Construction of new generation while satisfying technical and economical constraints. In the deregulated and competitive environment, large-scale integration of wind generation (WG) in power system has...... necessitated the inclusion of more innovative and sophisticated approaches in power system investment planning. A bi-level generation expansion planning approach considering large-scale wind generation was proposed in this paper. The first phase is investment decision, while the second phase is production...
The fractal octahedron network of the large scale structure
Battaner, E
1998-01-01
In a previous article, we have proposed that the large scale structure network generated by large scale magnetic fields could consist of a network of octahedra only contacting at their vertexes. Assuming such a network could arise at different scales producing a fractal geometry, we study here its properties, and in particular how a sub-octahedron network can be inserted within an octahedron of the large network. We deduce that the scale of the fractal structure would range from $\\approx$100 Mpc, i.e. the scale of the deepest surveys, down to about 10 Mpc, as other smaller scale magnetic fields were probably destroyed in the radiation dominated Universe.
Large-scale streaming motions and microwave background anisotropies
Energy Technology Data Exchange (ETDEWEB)
Martinez-Gonzalez, E.; Sanz, J.L. (Cantabria Universidad, Santander (Spain))
1989-12-01
The minimal microwave background radiation is calculated on each angular scale implied by the existence of large-scale streaming motions. These minimal anisotropies, due to the Sachs-Wolfe effect, are obtained for different experiments, and give quite different results from those found in previous work. They are not in conflict with present theories of galaxy formation. Upper limits are imposed on the scale at which large-scale streaming motions can occur by extrapolating results from present double-beam-switching experiments. 17 refs.
Distributed chaos tuned to large scale coherent motions in turbulence
Bershadskii, A
2016-01-01
It is shown, using direct numerical simulations and laboratory experiments data, that distributed chaos is often tuned to large scale coherent motions in anisotropic inhomogeneous turbulence. The examples considered are: fully developed turbulent boundary layer (range of coherence: $14 < y^{+} < 80$), turbulent thermal convection (in a horizontal cylinder), and Cuette-Taylor flow. Two ways of the tuning have been described: one via fundamental frequency (wavenumber) and another via subharmonic (period doubling). For the second way the large scale coherent motions are a natural component of distributed chaos. In all considered cases spontaneous breaking of space translational symmetry is accompanied by reflexional symmetry breaking.
Large-scale liquid scintillation detectors for solar neutrinos
Energy Technology Data Exchange (ETDEWEB)
Benziger, Jay B.; Calaprice, Frank P. [Princeton University Princeton, Princeton, NJ (United States)
2016-04-15
Large-scale liquid scintillation detectors are capable of providing spectral yields of the low energy solar neutrinos. These detectors require > 100 tons of liquid scintillator with high optical and radiopurity. In this paper requirements for low-energy neutrino detection by liquid scintillation are specified and the procedures to achieve low backgrounds in large-scale liquid scintillation detectors for solar neutrinos are reviewed. The designs, operations and achievements of Borexino, KamLAND and SNO+ in measuring the low-energy solar neutrino fluxes are reviewed. (orig.)
Optimal Dispatching of Large-scale Water Supply System
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
This paper deals with the use of optimal control techniques in large-scale water distribution networks. According to the network characteristics and actual state of the water supply system in China, the implicit model, which may be solved by utilizing the hierarchical optimization method, is established. In special, based on the analyses of the water supply system containing variable-speed pumps, a software tool has been developed successfully. The application of this model to the city of Shenyang (China) is compared to experiential strategy. The results of this study show that the developed model is a very promising optimization method to control the large-scale water supply systems.
Reliability Evaluation considering Structures of a Large Scale Wind Farm
DEFF Research Database (Denmark)
Shin, Je-Seok; Cha, Seung-Tae; Wu, Qiuwei
2012-01-01
evaluation on wind farm is necessarily required. Also, because large scale offshore wind farm has a long repair time and a high repair cost as well as a high investment cost, it is essential to take into account the economic aspect. One of methods to efficiently build and to operate wind farm is to construct......Wind energy is one of the most widely used renewable energy resources. Wind power has been connected to the grid as large scale wind farm which is made up of dozens of wind turbines, and the scale of wind farm is more increased recently. Due to intermittent and variable wind source, reliability...
Practical Large Scale Syntheses of New Drug Candidates
Institute of Scientific and Technical Information of China (English)
Hui-Yin Li
2001-01-01
@@ This presentation will be focus on Practical large scale syntheses of lead compounds and drug candidates from three major therapeutic areas from DuPont Pharmaceuticals Research Laboratory: 1). DMP777-a selective, non-toxic, orally active human elastase inhibitor; 2). DMP754-a potent glycoprotein IIb/IIIa antagonist; 3). R-Wafarin-the pure enantiomeric form of wafarin. The key technology used for preparation these drug candidates is asymmetric hydrogenation under very mild reaction conditions, which produced very high quality final products at large scale (＞99% de, ＞99 A% and ＞99 wt%). Some practical and GMP aspects of process development will be also discussed.
Fast paths in large-scale dynamic road networks
Nannicini, Giacomo; Barbier, Gilles; Krob, Daniel; Liberti, Leo
2007-01-01
Efficiently computing fast paths in large scale dynamic road networks (where dynamic traffic information is known over a part of the network) is a practical problem faced by several traffic information service providers who wish to offer a realistic fast path computation to GPS terminal enabled vehicles. The heuristic solution method we propose is based on a highway hierarchy-based shortest path algorithm for static large-scale networks; we maintain a static highway hierarchy and perform each query on the dynamically evaluated network.
Directory of Open Access Journals (Sweden)
I. Kalashnikova
2014-11-01
Full Text Available This paper describes a new parallel, scalable and robust finite-element based solver for the first-order Stokes momentum balance equations for ice flow. The solver, known as Albany/FELIX, is constructed using the component-based approach to building application codes, in which mature, modular libraries developed as a part of the Trilinos project are combined using abstract interfaces and Template-Based Generic Programming, resulting in a final code with access to dozens of algorithmic and advanced analysis capabilities. Following an overview of the relevant partial differential equations and boundary conditions, the numerical methods chosen to discretize the ice flow equations are described, along with their implementation. The results of several verification studies of the model accuracy are presented using: (1 new test cases derived using the method of manufactured solutions, and (2 canonical ice sheet modeling benchmarks. Model accuracy and convergence with respect to mesh resolution is then studied on problems involving a realistic Greenland ice sheet geometry discretized using structured and unstructured meshes. Also explored as a part of this study is the effect of vertical mesh resolution on the solution accuracy and solver performance. The robustness and scalability of our solver on these problems is demonstrated. Lastly, we show that good scalability can be achieved by preconditioning the iterative linear solver using a new algebraic multilevel preconditioner, constructed based on the idea of semi-coarsening.
Walker, J. M.; Bordoni, S.
2016-12-01
This study introduces a robust, objective definition for onset and withdrawal of the South Asian summer monsoon (SASM), based on the large-scale atmospheric moisture budget. The change point index (CHP) allows precise characterization of the different stages and timescales of the large-scale SASM and is also highly correlated with the commonly used local operational index, the monsoon onset over Kerala. The onset and withdrawal dates defined by CHP, which capture the expected seasonal transitions in rainfall and winds, correspond with regime changes in the large-scale SASM water vapor budget between negative and positive net precipitation. Analysis of climatological composites reveals that the seasonal transitions in SASM sector mean precipitation and circulation bear close resemblance to those of the zonal mean Hadley circulation. Computing the CHP index at grid points within the SASM domain yields a robust definition of local onset and withdrawal dates, which are well correlated with the large-scale index on interannual timescales, providing insight into the regional variability associated with the large-scale SASM.
GroFi: Large-scale fiber placement research facility
Directory of Open Access Journals (Sweden)
Christian Krombholz
2016-03-01
and processes for large-scale composite components. Due to the use of coordinated and simultaneously working layup units a high exibility of the research platform is achieved. This allows the investigation of new materials, technologies and processes on both, small coupons, but also large components such as wing covers or fuselage skins.
Large-scale search for dark-matter axions
Energy Technology Data Exchange (ETDEWEB)
Hagmann, C.A., LLNL; Kinion, D.; Stoeffl, W.; Van Bibber, K.; Daw, E.J. [Massachusetts Inst. of Tech., Cambridge, MA (United States); McBride, J. [Massachusetts Inst. of Tech., Cambridge, MA (United States); Peng, H. [Massachusetts Inst. of Tech., Cambridge, MA (United States); Rosenberg, L.J. [Massachusetts Inst. of Tech., Cambridge, MA (United States); Xin, H. [Massachusetts Inst. of Tech., Cambridge, MA (United States); Laveigne, J. [Florida Univ., Gainesville, FL (United States); Sikivie, P. [Florida Univ., Gainesville, FL (United States); Sullivan, N.S. [Florida Univ., Gainesville, FL (United States); Tanner, D.B. [Florida Univ., Gainesville, FL (United States); Moltz, D.M. [Lawrence Berkeley Lab., CA (United States); Powell, J. [Lawrence Berkeley Lab., CA (United States); Clarke, J. [Lawrence Berkeley Lab., CA (United States); Nezrick, F.A. [Fermi National Accelerator Lab., Batavia, IL (United States); Turner, M.S. [Fermi National Accelerator Lab., Batavia, IL (United States); Golubev, N.A. [Russian Academy of Sciences, Moscow (Russia); Kravchuk, L.V. [Russian Academy of Sciences, Moscow (Russia)
1998-01-01
Early results from a large-scale search for dark matter axions are presented. In this experiment, axions constituting our dark-matter halo may be resonantly converted to monochromatic microwave photons in a high-Q microwave cavity permeated by a strong magnetic field. Sensitivity at the level of one important axion model (KSVZ) has been demonstrated.
Temporal Variation of Large Scale Flows in the Solar Interior
Indian Academy of Sciences (India)
Sarbani Basu; H. M. Antia
2000-09-01
We attempt to detect short-term temporal variations in the rotation rate and other large scale velocity fields in the outer part of the solar convection zone using the ring diagram technique applied to Michelson Doppler Imager (MDI) data. The measured velocity field shows variations by about 10 m/s on the scale of few days.
Large-scale Homogenization of Bulk Materials in Mammoth Silos
Schott, D.L.
2004-01-01
This doctoral thesis concerns the large-scale homogenization of bulk materials in mammoth silos. The objective of this research was to determine the best stacking and reclaiming method for homogenization in mammoth silos. For this purpose a simulation program was developed to estimate the homogeniza
Quantized pressure control in large-scale nonlinear hydraulic networks
Persis, Claudio De; Kallesøe, Carsten Skovmose; Jensen, Tom Nørgaard
2010-01-01
It was shown previously that semi-global practical pressure regulation at designated points of a large-scale nonlinear hydraulic network is guaranteed by distributed proportional controllers. For a correct implementation of the control laws, each controller, which is located at these designated poin
Main Achievements of Cotton Large-scale Transformation System
Institute of Scientific and Technical Information of China (English)
LI Fu-guang; LIU Chuan-liang; WU Zhi-xia; ZHANG Chao-jun; ZHANG Xue-yan
2008-01-01
@@ Cotton large-scale transformation methods system was established based on innovation of cotton transformation methods.It obtains 8000 transgenic cotton plants per year by combining Agrobacteriurn turnefaciens-mediated,pollen-tube pathway and biolistic methods together efficiently.More than 1000 transgenie lines are selected from the transgenic plants with molecular assistant breeding and conventional breeding methods.
Segmentation by Large Scale Hypothesis Testing - Segmentation as Outlier Detection
DEFF Research Database (Denmark)
Darkner, Sune; Dahl, Anders Lindbjerg; Larsen, Rasmus
2010-01-01
locally. We propose a method based on large scale hypothesis testing with a consistent method for selecting an appropriate threshold for the given data. By estimating the background distribution we characterize the segment of interest as a set of outliers with a certain probability based on the estimated...
Large Scale Survey Data in Career Development Research
Diemer, Matthew A.
2008-01-01
Large scale survey datasets have been underutilized but offer numerous advantages for career development scholars, as they contain numerous career development constructs with large and diverse samples that are followed longitudinally. Constructs such as work salience, vocational expectations, educational expectations, work satisfaction, and…
Large-scale coastal impact induced by a catastrophic storm
DEFF Research Database (Denmark)
Fruergaard, Mikkel; Andersen, Thorbjørn Joest; Johannessen, Peter N
breaching. Our results demonstrate that violent, millennial-scale storms can trigger significant large-scale and long-term changes on barrier coasts, and that coastal changes assumed to take place over centuries or even millennia may occur in association with a single extreme storm event....
Regeneration and propagation of reed grass for large-scale ...
African Journals Online (AJOL)
전서범
2012-01-26
Jan 26, 2012 ... containing different sucrose concentrations; this experiment found that 60 g L-1 ... All these uses of reeds require the large-scale rege- ... numbers of plant in a small space within a short time ... callus stock and grown in vitro were used in this study. .... presence of 4-FA were converted to friable and light-.
Dual Decomposition for Large-Scale Power Balancing
DEFF Research Database (Denmark)
Halvgaard, Rasmus; Jørgensen, John Bagterp; Vandenberghe, Lieven
2013-01-01
Dual decomposition is applied to power balancing of exible thermal storage units. The centralized large-scale problem is decomposed into smaller subproblems and solved locallyby each unit in the Smart Grid. Convergence is achieved by coordinating the units consumption through a negotiation...
Large-Scale Assessment and English Language Learners with Disabilities
Liu, Kristin K.; Ward, Jenna M.; Thurlow, Martha L.; Christensen, Laurene L.
2017-01-01
This article highlights a set of principles and guidelines, developed by a diverse group of specialists in the field, for appropriately including English language learners (ELLs) with disabilities in large-scale assessments. ELLs with disabilities make up roughly 9% of the rapidly increasing ELL population nationwide. In spite of the small overall…
Large scale radial stability density of Hill's equation
Broer, Henk; Levi, Mark; Simo, Carles
2013-01-01
This paper deals with large scale aspects of Hill's equation (sic) + (a + bp(t)) x = 0, where p is periodic with a fixed period. In particular, the interest is the asymptotic radial density of the stability domain in the (a, b)-plane. It turns out that this density changes discontinuously in a certa
Water Implications of Large-Scale Land Acquisitions in Ghana
Directory of Open Access Journals (Sweden)
Timothy Olalekan Williams
2012-06-01
The paper offers recommendations which can help the government to achieve its stated objective of developing a "policy framework and guidelines for large-scale land acquisitions by both local and foreign investors for biofuels that will protect the interests of investors and the welfare of Ghanaian farmers and landowners".
Evaluating Large-scale National Public Management Reforms
DEFF Research Database (Denmark)
Breidahl, Karen Nielsen; Gjelstrup, Gunnar; Hansen, Morten Balle
This article explores differences and similarities between two evaluations of large-scale administrative reforms which were carried out in the 2000s: The evaluation of the Norwegian NAV reform (EVANAV) and the evaluation of the Danish Local Government Reform (LGR). We provide a comparative analys...
A Chain Perspective on Large-scale Number Systems
Grijpink, J.H.A.M.
2012-01-01
As large-scale number systems gain significance in social and economic life (electronic communication, remote electronic authentication), the correct functioning and the integrity of public number systems take on crucial importance. They are needed to uniquely indicate people, objects or phenomena i
Main Achievements of Cotton Large-scale Transformation System
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Cotton large-scale transformation methods system was established based on innovation of cotton transformation methods.It obtains 8000 transgenic cotton plants per year by combining Agrobacterium tumefaciens-mediated,pollen-tube pathway and biolistic methods together efficiently.More than
Newton Methods for Large Scale Problems in Machine Learning
Hansen, Samantha Leigh
2014-01-01
The focus of this thesis is on practical ways of designing optimization algorithms for minimizing large-scale nonlinear functions with applications in machine learning. Chapter 1 introduces the overarching ideas in the thesis. Chapters 2 and 3 are geared towards supervised machine learning applications that involve minimizing a sum of loss…
Large-Scale Machine Learning for Classification and Search
Liu, Wei
2012-01-01
With the rapid development of the Internet, nowadays tremendous amounts of data including images and videos, up to millions or billions, can be collected for training machine learning models. Inspired by this trend, this thesis is dedicated to developing large-scale machine learning techniques for the purpose of making classification and nearest…
Cost Overruns in Large-scale Transportation Infrastructure Projects
DEFF Research Database (Denmark)
Cantarelli, Chantal C; Flyvbjerg, Bent; Molin, Eric J. E
2010-01-01
Managing large-scale transportation infrastructure projects is difficult due to frequent misinformation about the costs which results in large cost overruns that often threaten the overall project viability. This paper investigates the explanations for cost overruns that are given in the literature...
Ultra-Large-Scale Systems: Scale Changes Everything
2008-03-06
Statistical Mechanics, Complexity Networks Are Everywhere Recurring “scale free” structure • internet & yeast protein structures Analogous dynamics...Design • Design Representation and Analysis • Assimilation • Determining and Managing Requirements 43 Ultra-Large-Scale Systems Linda Northrop: March
The Role of Plausible Values in Large-Scale Surveys
Wu, Margaret
2005-01-01
In large-scale assessment programs such as NAEP, TIMSS and PISA, students' achievement data sets provided for secondary analysts contain so-called "plausible values." Plausible values are multiple imputations of the unobservable latent achievement for each student. In this article it has been shown how plausible values are used to: (1) address…
Large-scale data analysis using the Wigner function
Earnshaw, R. A.; Lei, C.; Li, J.; Mugassabi, S.; Vourdas, A.
2012-04-01
Large-scale data are analysed using the Wigner function. It is shown that the 'frequency variable' provides important information, which is lost with other techniques. The method is applied to 'sentiment analysis' in data from social networks and also to financial data.
Lessons from Large-Scale Renewable Energy Integration Studies: Preprint
Energy Technology Data Exchange (ETDEWEB)
Bird, L.; Milligan, M.
2012-06-01
In general, large-scale integration studies in Europe and the United States find that high penetrations of renewable generation are technically feasible with operational changes and increased access to transmission. This paper describes other key findings such as the need for fast markets, large balancing areas, system flexibility, and the use of advanced forecasting.
VESPA: Very large-scale Evolutionary and Selective Pressure Analyses
Directory of Open Access Journals (Sweden)
Andrew E. Webb
2017-06-01
Full Text Available Background Large-scale molecular evolutionary analyses of protein coding sequences requires a number of preparatory inter-related steps from finding gene families, to generating alignments and phylogenetic trees and assessing selective pressure variation. Each phase of these analyses can represent significant challenges, particularly when working with entire proteomes (all protein coding sequences in a genome from a large number of species. Methods We present VESPA, software capable of automating a selective pressure analysis using codeML in addition to the preparatory analyses and summary statistics. VESPA is written in python and Perl and is designed to run within a UNIX environment. Results We have benchmarked VESPA and our results show that the method is consistent, performs well on both large scale and smaller scale datasets, and produces results in line with previously published datasets. Discussion Large-scale gene family identification, sequence alignment, and phylogeny reconstruction are all important aspects of large-scale molecular evolutionary analyses. VESPA provides flexible software for simplifying these processes along with downstream selective pressure variation analyses. The software automatically interprets results from codeML and produces simplified summary files to assist the user in better understanding the results. VESPA may be found at the following website: http://www.mol-evol.org/VESPA.
High-Throughput, Large-Scale SNP Genotyping: Bioinformatics Considerations
Margetic, Nino
2004-01-01
In order to provide a high-throughput, large-scale genotyping facility at the national level we have developed a set of inter-dependent information systems. A combination of commercial, publicly-available and in-house developed tools links a series of data repositories based both on flat files and relational databases providing an almost complete semi-automated pipeline.
Chain Analysis for large-scale Communication systems
Grijpink, Jan
2010-01-01
The chain concept is introduced to explain how large-scale information infrastructures so often fail and sometimes even backfire. Next, the assessment framework of the doctrine of Chain-computerisation and its chain analysis procedure are outlined. In this procedure chain description precedes assess
Large-Scale Machine Learning for Classification and Search
Liu, Wei
2012-01-01
With the rapid development of the Internet, nowadays tremendous amounts of data including images and videos, up to millions or billions, can be collected for training machine learning models. Inspired by this trend, this thesis is dedicated to developing large-scale machine learning techniques for the purpose of making classification and nearest…
Newton Methods for Large Scale Problems in Machine Learning
Hansen, Samantha Leigh
2014-01-01
The focus of this thesis is on practical ways of designing optimization algorithms for minimizing large-scale nonlinear functions with applications in machine learning. Chapter 1 introduces the overarching ideas in the thesis. Chapters 2 and 3 are geared towards supervised machine learning applications that involve minimizing a sum of loss…
Participatory Design of Large-Scale Information Systems
DEFF Research Database (Denmark)
Simonsen, Jesper; Hertzum, Morten
2008-01-01
In this article we discuss how to engage in large-scale information systems development by applying a participatory design (PD) approach that acknowledges the unique situated work practices conducted by the domain experts of modern organizations. We reconstruct the iterative prototyping approach...
How large-scale subsidence affects stratocumulus transitions (discussion paper)
Van der Dussen, J.J.; De Roode, S.R.; Siebesma, A.P.
2015-01-01
Some climate modeling results suggest that the Hadley circulation might weaken in a future climate, causing a subsequent reduction in the large-scale subsidence velocity in the subtropics. In this study we analyze the cloud liquid water path (LWP) budget from large-eddy simulation (LES) results of
Large-Scale Innovation and Change in UK Higher Education
Brown, Stephen
2013-01-01
This paper reflects on challenges universities face as they respond to change. It reviews current theories and models of change management, discusses why universities are particularly difficult environments in which to achieve large scale, lasting change and reports on a recent attempt by the UK JISC to enable a range of UK universities to employ…
Measurement, Sampling, and Equating Errors in Large-Scale Assessments
Wu, Margaret
2010-01-01
In large-scale assessments, such as state-wide testing programs, national sample-based assessments, and international comparative studies, there are many steps involved in the measurement and reporting of student achievement. There are always sources of inaccuracies in each of the steps. It is of interest to identify the source and magnitude of…
A Chain Perspective on Large-scale Number Systems
Grijpink, J.H.A.M.
2012-01-01
As large-scale number systems gain significance in social and economic life (electronic communication, remote electronic authentication), the correct functioning and the integrity of public number systems take on crucial importance. They are needed to uniquely indicate people, objects or phenomena i
Large-Scale Innovation and Change in UK Higher Education
Brown, Stephen
2013-01-01
This paper reflects on challenges universities face as they respond to change. It reviews current theories and models of change management, discusses why universities are particularly difficult environments in which to achieve large scale, lasting change and reports on a recent attempt by the UK JISC to enable a range of UK universities to employ…
Primordial non-Gaussianity from the large scale structure
Desjacques, Vincent
2010-01-01
Primordial non-Gaussianity is a potentially powerful discriminant of the physical mechanisms that generated the cosmological fluctuations observed today. Any detection of non-Gaussianity would have profound implications for our understanding of cosmic structure formation. In this paper, we review past and current efforts in the search for primordial non-Gaussianity in the large scale structure of the Universe.
Planck intermediate results XLII. Large-scale Galactic magnetic fields
DEFF Research Database (Denmark)
Adam, R.; Ade, P. A. R.; Alves, M. I. R.
2016-01-01
Recent models for the large-scale Galactic magnetic fields in the literature have been largely constrained by synchrotron emission and Faraday rotation measures. We use three different but representative models to compare their predicted polarized synchrotron and dust emission with that measured...
Electric vehicles and large-scale integration of wind power
DEFF Research Database (Denmark)
Liu, Wen; Hu, Weihao; Lund, Henrik
2013-01-01
was 6.5% in 2009 and which has the plan to develop large-scale wind power. The results show that electric vehicles (EVs) have the ability to balance the electricity demand and supply and to further the wind power integration. In the best case, the energy system with EV can increase wind power...
Large scale solar district heating. Evaluation, modelling and designing - Appendices
Energy Technology Data Exchange (ETDEWEB)
Heller, A.
2000-07-01
The appendices present the following: A) Cad-drawing of the Marstal CSHP design. B) Key values - large-scale solar heating in Denmark. C) Monitoring - a system description. D) WMO-classification of pyranometers (solarimeters). E) The computer simulation model in TRNSYS. F) Selected papers from the author. (EHS)
New Visions for Large Scale Networks: Research and Applications
Networking and Information Technology Research and Development, Executive Office of the President — This paper documents the findings of the March 12-14, 2001 Workshop on New Visions for Large-Scale Networks: Research and Applications. The workshops objectives were...
Directory of Open Access Journals (Sweden)
Silvio Picano
1992-01-01
Full Text Available We present detailed experimental work involving a commercially available large scale shared memory multiple instruction stream-multiple data stream (MIMD parallel computer having a software controlled cache coherence mechanism. To make effective use of such an architecture, the programmer is responsible for designing the program's structure to match the underlying multiprocessors capabilities. We describe the techniques used to exploit our multiprocessor (the BBN TC2000 on a network simulation program, showing the resulting performance gains and the associated programming costs. We show that an efficient implementation relies heavily on the user's ability to explicitly manage the memory system.
Tsukahara, Hiroshi; Iwano, Kaoru; Mitsumata, Chiharu; Ishikawa, Tadashi; Ono, Kanta
2016-10-01
We implement low communication frequency three-dimensional fast Fourier transform algorithms on micromagnetics simulator for calculations of a magnetostatic field which occupies a significant portion of large-scale micromagnetics simulation. This fast Fourier transform algorithm reduces the frequency of all-to-all communications from six to two times. Simulation times with our simulator show high scalability in parallelization, even if we perform the micromagnetics simulation using 32 768 physical computing cores. This low communication frequency fast Fourier transform algorithm enables world largest class micromagnetics simulations to be carried out with over one billion calculation cells.
Using Agent Base Models to Optimize Large Scale Network for Large System Inventories
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.
Large-Scale Cosmic-Ray Anisotropy as a Probe of Interstellar Turbulence
2016-01-01
We calculate the large-scale cosmic-ray (CR) anisotropies predicted for a range of Goldreich-Sridhar (GS) and isotropic models of interstellar turbulence, and compare them with IceTop data. In general, the predicted CR anisotropy is not a pure dipole; the cold spots reported at 400 TeV and 2 PeV are consistent with a GS model that contains a smooth deficit of parallel-propagating waves and a broad resonance function, although some other possibilities cannot, as yet, be ruled out. In particula...
Alignments of dark matter halos with large-scale tidal fields: mass and redshift dependence
Chen, Sijie; Mo, H J; Shi, Jingjing
2016-01-01
Large scale tidal field estimated directly from the distribution of dark matter halos is used to investigate how halo shapes and spin vectors are aligned with the cosmic web. The major, intermediate and minor axes of halos are aligned with the corresponding tidal axes, and halo spin axes tend to be parallel with the intermediate axes and perpendicular to the major axes of tidal field. The strengths of these alignments generally increase with halo mass and redshift, but the dependencies are only through the peak height, {\
Developing A Large-Scale, Collaborative, Productive Geoscience Education Network
Manduca, C. A.; Bralower, T. J.; Egger, A. E.; Fox, S.; Ledley, T. S.; Macdonald, H.; Mcconnell, D. A.; Mogk, D. W.; Tewksbury, B. J.
2012-12-01
Over the past 15 years, the geoscience education community has grown substantially and developed broad and deep capacity for collaboration and dissemination of ideas. While this community is best viewed as emergent from complex interactions among changing educational needs and opportunities, we highlight the role of several large projects in the development of a network within this community. In the 1990s, three NSF projects came together to build a robust web infrastructure to support the production and dissemination of on-line resources: On The Cutting Edge (OTCE), Earth Exploration Toolbook, and Starting Point: Teaching Introductory Geoscience. Along with the contemporaneous Digital Library for Earth System Education, these projects engaged geoscience educators nationwide in exploring professional development experiences that produced lasting on-line resources, collaborative authoring of resources, and models for web-based support for geoscience teaching. As a result, a culture developed in the 2000s in which geoscience educators anticipated that resources for geoscience teaching would be shared broadly and that collaborative authoring would be productive and engaging. By this time, a diverse set of examples demonstrated the power of the web infrastructure in supporting collaboration, dissemination and professional development . Building on this foundation, more recent work has expanded both the size of the network and the scope of its work. Many large research projects initiated collaborations to disseminate resources supporting educational use of their data. Research results from the rapidly expanding geoscience education research community were integrated into the Pedagogies in Action website and OTCE. Projects engaged faculty across the nation in large-scale data collection and educational research. The Climate Literacy and Energy Awareness Network and OTCE engaged community members in reviewing the expanding body of on-line resources. Building Strong
Sparse deconvolution for the large-scale ill-posed inverse problem of impact force reconstruction
Qiao, Baijie; Zhang, Xingwu; Gao, Jiawei; Liu, Ruonan; Chen, Xuefeng
2017-01-01
Most previous regularization methods for solving the inverse problem of force reconstruction are to minimize the l2-norm of the desired force. However, these traditional regularization methods such as Tikhonov regularization and truncated singular value decomposition, commonly fail to solve the large-scale ill-posed inverse problem in moderate computational cost. In this paper, taking into account the sparse characteristic of impact force, the idea of sparse deconvolution is first introduced to the field of impact force reconstruction and a general sparse deconvolution model of impact force is constructed. Second, a novel impact force reconstruction method based on the primal-dual interior point method (PDIPM) is proposed to solve such a large-scale sparse deconvolution model, where minimizing the l2-norm is replaced by minimizing the l1-norm. Meanwhile, the preconditioned conjugate gradient algorithm is used to compute the search direction of PDIPM with high computational efficiency. Finally, two experiments including the small-scale or medium-scale single impact force reconstruction and the relatively large-scale consecutive impact force reconstruction are conducted on a composite wind turbine blade and a shell structure to illustrate the advantage of PDIPM. Compared with Tikhonov regularization, PDIPM is more efficient, accurate and robust whether in the single impact force reconstruction or in the consecutive impact force reconstruction.
Phenomenology of two-dimensional stably stratified turbulence under large-scale forcing
Kumar, Abhishek; Sukhatmae, Jai
2016-01-01
In this paper we characterize the scaling of energy spectra, and the interscale transfer of energy and enstrophy, for strongly, moderately and weakly stably stratified two-dimensional (2D) turbulence under large-scale random forcing. In the strongly stratified case, a large-scale vertically sheared horizontal flow (VSHF) co-exists with small scale turbulence. The VSHF consists of internal gravity waves and the turbulent flow has a kinetic energy (KE) spectrum that follows an approximate $k^{-3}$ scaling with zero KE flux and a robust positive enstrophy flux. The spectrum of the turbulent potential energy (PE) also approximately follows a $k^{-3}$ power-law and its flux is directed to small scales. For moderate stratification, there is no VSHF and the KE of the turbulent flow exhibits Bolgiano-Obukhov scaling that transitions from a shallow $k^{-11/5}$ form at large scales, to a steeper approximate $k^{-3}$ scaling at small scales. The entire range of scales shows a strong forward enstrophy flux, and interesti...
Final Report: Large-Scale Optimization for Bayesian Inference in Complex Systems
Energy Technology Data Exchange (ETDEWEB)
Ghattas, Omar [The University of Texas at Austin
2013-10-15
The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimiza- tion) Project focuses on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimiza- tion and inversion methods. Our research is directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. Our efforts are integrated in the context of a challenging testbed problem that considers subsurface reacting flow and transport. The MIT component of the SAGUARO Project addresses the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas-Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to- observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as "reduce then sample" and "sample then reduce." In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their speedups.
Large-scale flow generation by inhomogeneous helicity
Yokoi, Nobumitsu
2015-01-01
The effect of kinetic helicity (velocity--vorticity correlation) on turbulent momentum transport is investigated. The turbulent kinetic helicity (pseudoscalar) enters into the Reynolds stress (mirrorsymmetric tensor) expression in the form of a helicity gradient as the coupling coefficient for the mean vorticity and/or the angular velocity (axial vector), which suggests the possibility of mean-flow generation in the presence of inhomogeneous helicity. This inhomogeneous helicity effect, which was previously confirmed at the level of a turbulence- or closure-model simulation, is examined with the aid of direct numerical simulations of rotating turbulence with non-uniform helicity sustained by an external forcing. The numerical simulations show that the spatial distribution of the Reynolds stress is in agreement with the helicity-related term coupled with the angular velocity, and that a large-scale flow is generated in the direction of angular velocity. Such a large-scale flow is not induced in the case of hom...
Series Design of Large-Scale NC Machine Tool
Institute of Scientific and Technical Information of China (English)
TANG Zhi
2007-01-01
Product system design is a mature concept in western developed countries. It has been applied in war industry during the last century. However, up until now, functional combination is still the main method for product system design in China. Therefore, in terms of a concept of product generation and product interaction we are in a weak position compared with the requirements of global markets. Today, the idea of serial product design has attracted much attention in the design field and the definition of product generation as well as its parameters has already become the standard in serial product designs. Although the design of a large-scale NC machine tool is complicated, it can be further optimized by the precise exercise of object design by placing the concept of platform establishment firmly into serial product design. The essence of a serial product design has been demonstrated by the design process of a large-scale NC machine tool.
Evaluation of Large-scale Public Sector Reforms
DEFF Research Database (Denmark)
Breidahl, Karen Nielsen; Gjelstrup, Gunnar; Hansen, Hanne Foss
2017-01-01
Research on the evaluation of large-scale public sector reforms is rare. This article sets out to fill that gap in the evaluation literature and argues that it is of vital importance. The impact of such reforms is considerable. Furthermore they change the context in which evaluations of other...... and more delimited policy areas take place. In our analysis we apply four governance perspectives (rational-instrumental, rational-interest based, institutional-cultural and a chaos perspective) in a comparative analysis of the evaluations of two large-scale public sector reforms in Denmark and Norway. We...... compare the evaluation process (focus and purpose), the evaluators and the organization of the evaluation as well as the utilization of the evaluation results. The analysis uncovers several significant findings including how the initial organization of the evaluation show strong impact on the utilization...
Magnetic Helicity and Large Scale Magnetic Fields: A Primer
Blackman, Eric G
2014-01-01
Magnetic fields of laboratory, planetary, stellar, and galactic plasmas commonly exhibit significant order on large temporal or spatial scales compared to the otherwise random motions within the hosting system. Such ordered fields can be measured in the case of planets, stars, and galaxies, or inferred indirectly by the action of their dynamical influence, such as jets. Whether large scale fields are amplified in situ or a remnant from previous stages of an object's history is often debated for objects without a definitive magnetic activity cycle. Magnetic helicity, a measure of twist and linkage of magnetic field lines, is a unifying tool for understanding large scale field evolution for both mechanisms of origin. Its importance stems from its two basic properties: (1) magnetic helicity is typically better conserved than magnetic energy; and (2) the magnetic energy associated with a fixed amount of magnetic helicity is minimized when the system relaxes this helical structure to the largest scale available. H...
Bayesian large-scale structure inference and cosmic web analysis
Leclercq, Florent
2015-01-01
Surveys of the cosmic large-scale structure carry opportunities for building and testing cosmological theories about the origin and evolution of the Universe. This endeavor requires appropriate data assimilation tools, for establishing the contact between survey catalogs and models of structure formation. In this thesis, we present an innovative statistical approach for the ab initio simultaneous analysis of the formation history and morphology of the cosmic web: the BORG algorithm infers the primordial density fluctuations and produces physical reconstructions of the dark matter distribution that underlies observed galaxies, by assimilating the survey data into a cosmological structure formation model. The method, based on Bayesian probability theory, provides accurate means of uncertainty quantification. We demonstrate the application of BORG to the Sloan Digital Sky Survey data and describe the primordial and late-time large-scale structure in the observed volume. We show how the approach has led to the fi...
Constraining cosmological ultra-large scale structure using numerical relativity
Braden, Jonathan; Peiris, Hiranya V; Aguirre, Anthony
2016-01-01
Cosmic inflation, a period of accelerated expansion in the early universe, can give rise to large amplitude ultra-large scale inhomogeneities on distance scales comparable to or larger than the observable universe. The cosmic microwave background (CMB) anisotropy on the largest angular scales is sensitive to such inhomogeneities and can be used to constrain the presence of ultra-large scale structure (ULSS). We numerically evolve nonlinear inhomogeneities present at the beginning of inflation in full General Relativity to assess the CMB quadrupole constraint on the amplitude of the initial fluctuations and the size of the observable universe relative to a length scale characterizing the ULSS. To obtain a statistically significant number of simulations, we adopt a toy model in which inhomogeneities are injected along a preferred direction. We compute the likelihood function for the CMB quadrupole including both ULSS and the standard quantum fluctuations produced during inflation. We compute the posterior given...
Ultra-large scale cosmology with next-generation experiments
Alonso, David; Ferreira, Pedro G; Maartens, Roy; Santos, Mario G
2015-01-01
Future surveys of large-scale structure will be able to measure perturbations on the scale of the cosmological horizon, and so could potentially probe a number of novel relativistic effects that are negligibly small on sub-horizon scales. These effects leave distinctive signatures in the power spectra of clustering observables and, if measurable, would open a new window on relativistic cosmology. We quantify the size and detectability of the effects for a range of future large-scale structure surveys: spectroscopic and photometric galaxy redshift surveys, intensity mapping surveys of neutral hydrogen, and continuum surveys of radio galaxies. Our forecasts show that next-generation experiments, reaching out to redshifts z ~ 4, will not be able to detect previously-undetected general-relativistic effects from the single-tracer power spectra alone, although they may be able to measure the lensing magnification in the auto-correlation. We also perform a rigorous joint forecast for the detection of primordial non-...
First Mile Challenges for Large-Scale IoT
Bader, Ahmed
2017-03-16
The Internet of Things is large-scale by nature. This is not only manifested by the large number of connected devices, but also by the sheer scale of spatial traffic intensity that must be accommodated, primarily in the uplink direction. To that end, cellular networks are indeed a strong first mile candidate to accommodate the data tsunami to be generated by the IoT. However, IoT devices are required in the cellular paradigm to undergo random access procedures as a precursor to resource allocation. Such procedures impose a major bottleneck that hinders cellular networks\\' ability to support large-scale IoT. In this article, we shed light on the random access dilemma and present a case study based on experimental data as well as system-level simulations. Accordingly, a case is built for the latent need to revisit random access procedures. A call for action is motivated by listing a few potential remedies and recommendations.
Supermassive black holes, large scale structure and holography
Mongan, T R
2013-01-01
A holographic analysis of large scale structure in the universe estimates the mass of supermassive black holes at the center of large scale structures with matter density varying inversely as the square of the distance from their center. The estimate is consistent with two important test cases involving observations of the supermassive black hole with mass 3.6\\times10^{-6} times the galactic mass in Sagittarius A^{*} near the center of our Milky Way and the 2\\times10^{9} solar mass black hole in the quasar ULAS J112001.48+064124.3 at redshift z=7.085. It is also consistent with upper bounds on central black hole masses in globular clusters M15, M19 and M22 developed using the Jansky Very Large Array in New Mexico.
Optimization of Survivability Analysis for Large-Scale Engineering Networks
Poroseva, S V
2012-01-01
Engineering networks fall into the category of large-scale networks with heterogeneous nodes such as sources and sinks. The survivability analysis of such networks requires the analysis of the connectivity of the network components for every possible combination of faults to determine a network response to each combination of faults. From the computational complexity point of view, the problem belongs to the class of exponential time problems at least. Partially, the problem complexity can be reduced by mapping the initial topology of a complex large-scale network with multiple sources and multiple sinks onto a set of smaller sub-topologies with multiple sources and a single sink connected to the network of sources by a single link. In this paper, the mapping procedure is applied to the Florida power grid.
Large-scale innovation and change in UK higher education
Directory of Open Access Journals (Sweden)
Stephen Brown
2013-09-01
Full Text Available This paper reflects on challenges universities face as they respond to change. It reviews current theories and models of change management, discusses why universities are particularly difficult environments in which to achieve large scale, lasting change and reports on a recent attempt by the UK JISC to enable a range of UK universities to employ technology to deliver such changes. Key lessons that emerged from these experiences are reviewed covering themes of pervasiveness, unofficial systems, project creep, opposition, pressure to deliver, personnel changes and technology issues. The paper argues that collaborative approaches to project management offer greater prospects of effective large-scale change in universities than either management-driven top-down or more champion-led bottom-up methods. It also argues that while some diminution of control over project outcomes is inherent in this approach, this is outweighed by potential benefits of lasting and widespread adoption of agreed changes.
Distant galaxy clusters in the XMM Large Scale Structure survey
Willis, J P; Bremer, M N; Pierre, M; Adami, C; Ilbert, O; Maughan, B; Maurogordato, S; Pacaud, F; Valtchanov, I; Chiappetti, L; Thanjavur, K; Gwyn, S; Stanway, E R; Winkworth, C
2012-01-01
(Abridged) Distant galaxy clusters provide important tests of the growth of large scale structure in addition to highlighting the process of galaxy evolution in a consistently defined environment at large look back time. We present a sample of 22 distant (z>0.8) galaxy clusters and cluster candidates selected from the 9 deg2 footprint of the overlapping X-ray Multi Mirror (XMM) Large Scale Structure (LSS), CFHTLS Wide and Spitzer SWIRE surveys. Clusters are selected as extended X-ray sources with an accompanying overdensity of galaxies displaying optical to mid-infrared photometry consistent with z>0.8. Nine clusters have confirmed spectroscopic redshifts in the interval 0.80.8 clusters.
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.
The complexity nature of large-scale software systems
Institute of Scientific and Technical Information of China (English)
Yan Dong; Qi Guo-Ning; Gu Xin-Jian
2006-01-01
In software engineering, class diagrams are often used to describe the system's class structures in Unified Modelling Language (UML). A class diagram, as a graph, is a collection of static declarative model elements, such as classes, interfaces, and the relationships of their connections with each other. In this paper, class graphs are examined within several Java software systems provided by Sun and IBM, and some new features are found. For a large-scale Java software system, its in-degree distribution tends to an exponential distribution, while its out-degree and degree distributions reveal the power-law behaviour. And then a directed preferential-random model is established to describe the corresponding degree distribution features and evolve large-scale Java software systems.
Electron drift in a large scale solid xenon
Yoo, J
2015-01-01
A study of charge drift in a large scale optically transparent solid xenon is reported. A pulsed high power xenon light source is used to liberate electrons from a photocathode. The drift speeds of the electrons are measured using a 8.7\\,cm long electrode in both the liquid and solid phase of xenon. In the liquid phase (163\\,K), the drift speed is 0.193 $\\pm$ 0.003 cm/$\\mu$s while the drift speed in the solid phase (157\\,K) is 0.397 $\\pm$ 0.006 cm/$\\mu$s at 900 V/cm over 8.0\\,cm of uniform electric fields. Therefore, it is demonstrated that a factor two faster electron drift speed in solid phase xenon compared to that in liquid in a large scale solid xenon.
Prototype Vector Machine for Large Scale Semi-Supervised Learning
Energy Technology Data Exchange (ETDEWEB)
Zhang, Kai; Kwok, James T.; Parvin, Bahram
2009-04-29
Practicaldataminingrarelyfalls exactlyinto the supervisedlearning scenario. Rather, the growing amount of unlabeled data poses a big challenge to large-scale semi-supervised learning (SSL). We note that the computationalintensivenessofgraph-based SSLarises largely from the manifold or graph regularization, which in turn lead to large models that are dificult to handle. To alleviate this, we proposed the prototype vector machine (PVM), a highlyscalable,graph-based algorithm for large-scale SSL. Our key innovation is the use of"prototypes vectors" for effcient approximation on both the graph-based regularizer and model representation. The choice of prototypes are grounded upon two important criteria: they not only perform effective low-rank approximation of the kernel matrix, but also span a model suffering the minimum information loss compared with the complete model. We demonstrate encouraging performance and appealing scaling properties of the PVM on a number of machine learning benchmark data sets.
Large-Scale Agriculture and Outgrower Schemes in Ethiopia
DEFF Research Database (Denmark)
Wendimu, Mengistu Assefa
As a result of the growing demand for food, feed and industrial raw materials in the first decade of this century, and the usually welcoming policies regarding investors amongst the governments of developing countries, there has been a renewed interest in agriculture and an increase in large...... to ‘land grabbing’ for large-scale farming (i.e. outgrower schemes and contract farming could modernise agricultural production while allowing smallholders to maintain their land ownership), to integrate them into global agro-food value chains and to increase their productivity and welfare. However......, the impact of large-scale agriculture and outgrower schemes on productivity, household welfare and wages in developing countries is highly contentious. Chapter 1 of this thesis provides an introduction to the study, while also reviewing the key debate in the contemporary land ‘grabbing’ and historical large...
Clusters and Large-Scale Structure: the Synchrotron Keys
Rudnick, L; Andernach, H; Battaglia, N; Brown, S; Brunetti, Gf; Burns, J; Clarke, T; Dolag, K; Farnsworth, D; Giovannini, G; Hallman, E; Johnston-Hollit, M; Jones, T W; Kang, H; Kassim, N; Kravtsov, A; Lazio, J; Lonsdale, C; McNamara, B; Myers, S; Owen, F; Pfrommer, C; Ryu, D; Sarazin, C; Subrahmanyan, R; Taylor, G; Taylor, R
2009-01-01
For over four decades, synchrotron-radiating sources have played a series of pathfinding roles in the study of galaxy clusters and large scale structure. Such sources are uniquely sensitive to the turbulence and shock structures of large-scale environments, and their cosmic rays and magnetic fields often play important dynamic and thermodynamic roles. They provide essential complements to studies at other wavebands. Over the next decade, they will fill essential gaps in both cluster astrophysics and the cosmological growth of structure in the universe, especially where the signatures of shocks and turbulence, or even the underlying thermal plasma itself, are otherwise undetectable. Simultaneously, synchrotron studies offer a unique tool for exploring the fundamental question of the origins of cosmic magnetic fields. This work will be based on the new generation of m/cm-wave radio telescopes now in construction, as well as major advances in the sophistication of 3-D MHD simulations.
Cluster Galaxy Dynamics and the Effects of Large Scale Environment
White, Martin; Smit, Renske
2010-01-01
We use a high-resolution N-body simulation to study how the influence of large-scale structure in and around clusters causes correlated signals in different physical probes and discuss some implications this has for multi-physics probes of clusters. We pay particular attention to velocity dispersions, matching galaxies to subhalos which are explicitly tracked in the simulation. We find that not only do halos persist as subhalos when they fall into a larger host, groups of subhalos retain their identity for long periods within larger host halos. The highly anisotropic nature of infall into massive clusters, and their triaxiality, translates into an anisotropic velocity ellipsoid: line-of-sight galaxy velocity dispersions for any individual halo show large variance depending on viewing angle. The orientation of the velocity ellipsoid is correlated with the large-scale structure, and thus velocity outliers correlate with outliers caused by projection in other probes. We quantify this orientation uncertainty and ...
Quantum noise in large-scale coherent nonlinear photonic circuits
Santori, Charles; Beausoleil, Raymond G; Tezak, Nikolas; Hamerly, Ryan; Mabuchi, Hideo
2014-01-01
A semiclassical simulation approach is presented for studying quantum noise in large-scale photonic circuits incorporating an ideal Kerr nonlinearity. A netlist-based circuit solver is used to generate matrices defining a set of stochastic differential equations, in which the resonator field variables represent random samplings of the Wigner quasi-probability distributions. Although the semiclassical approach involves making a large-photon-number approximation, tests on one- and two-resonator circuits indicate satisfactory agreement between the semiclassical and full-quantum simulation results in the parameter regime of interest. The semiclassical model is used to simulate random errors in a large-scale circuit that contains 88 resonators and hundreds of components in total, and functions as a 4-bit ripple counter. The error rate as a function of on-state photon number is examined, and it is observed that the quantum fluctuation amplitudes do not increase as signals propagate through the circuit, an important...
Measuring large scale space perception in literary texts
Rossi, Paolo
2007-07-01
A center and radius of “perception” (in the sense of environmental cognition) can be formally associated with a written text and operationally defined. Simple algorithms for their computation are presented, and indicators for anisotropy in large scale space perception are introduced. The relevance of these notions for the analysis of literary and historical records is briefly discussed and illustrated with an example taken from medieval historiography.
The Phoenix series large scale LNG pool fire experiments.
Energy Technology Data Exchange (ETDEWEB)
Simpson, Richard B.; Jensen, Richard Pearson; Demosthenous, Byron; Luketa, Anay Josephine; Ricks, Allen Joseph; Hightower, Marion Michael; Blanchat, Thomas K.; Helmick, Paul H.; Tieszen, Sheldon Robert; Deola, Regina Anne; Mercier, Jeffrey Alan; Suo-Anttila, Jill Marie; Miller, Timothy J.
2010-12-01
The increasing demand for natural gas could increase the number and frequency of Liquefied Natural Gas (LNG) tanker deliveries to ports across the United States. Because of the increasing number of shipments and the number of possible new facilities, concerns about the potential safety of the public and property from an accidental, and even more importantly intentional spills, have increased. While improvements have been made over the past decade in assessing hazards from LNG spills, the existing experimental data is much smaller in size and scale than many postulated large accidental and intentional spills. Since the physics and hazards from a fire change with fire size, there are concerns about the adequacy of current hazard prediction techniques for large LNG spills and fires. To address these concerns, Congress funded the Department of Energy (DOE) in 2008 to conduct a series of laboratory and large-scale LNG pool fire experiments at Sandia National Laboratories (Sandia) in Albuquerque, New Mexico. This report presents the test data and results of both sets of fire experiments. A series of five reduced-scale (gas burner) tests (yielding 27 sets of data) were conducted in 2007 and 2008 at Sandia's Thermal Test Complex (TTC) to assess flame height to fire diameter ratios as a function of nondimensional heat release rates for extrapolation to large-scale LNG fires. The large-scale LNG pool fire experiments were conducted in a 120 m diameter pond specially designed and constructed in Sandia's Area III large-scale test complex. Two fire tests of LNG spills of 21 and 81 m in diameter were conducted in 2009 to improve the understanding of flame height, smoke production, and burn rate and therefore the physics and hazards of large LNG spills and fires.
Energy Technology Data Exchange (ETDEWEB)
Onishchenko, O. G., E-mail: onish@ifz.ru [Institute of Physics of the Earth, 10 B. Gruzinskaya, 123242 Moscow, Russian Federation and Space Research Institute, 84/32 Profsouznaya str., 117997 Moscow (Russian Federation); Pokhotelov, O. A., E-mail: pokh@ifz.ru [Institute of Physics of the Earth, 10 B. Gruzinskaya, 123242 Moscow (Russian Federation); Horton, W., E-mail: wendell.horton@gmail.com [Institute for Fusion Studies and Applied Research Laboratory, University of Texas at Austin, Austin, Texas 78713 (United States); Scullion, E., E-mail: scullie@tcd.ie [School of Physics, Trinity College Dublin, Dublin 2 (Ireland); Fedun, V., E-mail: v.fedun@sheffield.ac.uk [Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S13JD (United Kingdom)
2015-12-15
The new type of large-scale vortex structures of dispersionless Alfvén waves in collisionless plasma is investigated. It is shown that Alfvén waves can propagate in the form of Alfvén vortices of finite characteristic radius and characterised by magnetic flux ropes carrying orbital angular momentum. The structure of the toroidal and radial velocity, fluid and magnetic field vorticity, the longitudinal electric current in the plane orthogonal to the external magnetic field are discussed.
UAV Data Processing for Large Scale Topographical Mapping
Tampubolon, W.; Reinhardt, W.
2014-06-01
Large scale topographical mapping in the third world countries is really a prominent challenge in geospatial industries nowadays. On one side the demand is significantly increasing while on the other hand it is constrained by limited budgets available for mapping projects. Since the advent of Act Nr.4/yr.2011 about Geospatial Information in Indonesia, large scale topographical mapping has been on high priority for supporting the nationwide development e.g. detail spatial planning. Usually large scale topographical mapping relies on conventional aerial survey campaigns in order to provide high resolution 3D geospatial data sources. Widely growing on a leisure hobby, aero models in form of the so-called Unmanned Aerial Vehicle (UAV) bring up alternative semi photogrammetric aerial data acquisition possibilities suitable for relatively small Area of Interest (AOI) i.e. Indonesia this area size can be used as a mapping unit since it usually concentrates on the basis of sub district area (kecamatan) level. In this paper different camera and processing software systems will be further analyzed for identifying the best optimum UAV data acquisition campaign components in combination with the data processing scheme. The selected AOI is covering the cultural heritage of Borobudur Temple as one of the Seven Wonders of the World. A detailed accuracy assessment will be concentrated within the object feature of the temple at the first place. Feature compilation involving planimetric objects (2D) and digital terrain models (3D) will be integrated in order to provide Digital Elevation Models (DEM) as the main interest of the topographic mapping activity. By doing this research, incorporating the optimum amount of GCPs in the UAV photo data processing will increase the accuracy along with its high resolution in 5 cm Ground Sampling Distance (GSD). Finally this result will be used as the benchmark for alternative geospatial data acquisition in the future in which it can support
Hierarchical Engine for Large-scale Infrastructure Co-Simulation
Energy Technology Data Exchange (ETDEWEB)
2017-04-24
HELICS is designed to support very-large-scale (100,000+ federates) cosimulations with off-the-shelf power-system, communication, market, and end-use tools. Other key features include cross platform operating system support, the integration of both event driven (e.g., packetized communication) and time-series (e.g., power flow) simulations, and the ability to co-iterate among federates to ensure physical model convergence at each time step.
Large scale-small scale duality and cosmological constant
Darabi, F
1999-01-01
We study a model of quantum cosmology originating from a classical model of gravitation where a self interacting scalar field is coupled to gravity with the metric undergoing a signature transition. We show that there are dual classical signature changing solutions, one at large scales and the other at small scales. It is possible to fine-tune the physics in both scales with an infinitesimal effective cosmological constant.
Information Tailoring Enhancements for Large-Scale Social Data
2016-09-26
Social Data Final Report Reporting Period: September 22, 2015 – September 16, 2016 Contract No. N00014-15-P-5138 Sponsored by ONR...Report September 22, 20 15 - September 16, 20 16 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Information Tailoring Enhancements for Large-Scale Social ...goals of(i) further enhancing capability to analyze unstructured social media data at scale and rapidly, and (ii) improving IAI social media software
Large-scale prediction of drug-target relationships
DEFF Research Database (Denmark)
Kuhn, Michael; Campillos, Mónica; González, Paula
2008-01-01
, but also provides a more global view on drug-target relations. Here we review recent attempts to apply large-scale computational analyses to predict novel interactions of drugs and targets from molecular and cellular features. In this context, we quantify the family-dependent probability of two proteins...... to bind the same ligand as function of their sequence similarity. We finally discuss how phenotypic data could help to expand our understanding of the complex mechanisms of drug action....
One-dimensional adhesion model for large scale structures
Directory of Open Access Journals (Sweden)
Kayyunnapara Thomas Joseph
2010-05-01
Full Text Available We discuss initial value problems and initial boundary value problems for some systems of partial differential equations appearing in the modelling for the large scale structure formation in the universe. We restrict the initial data to be bounded measurable and locally bounded variation function and use Volpert product to justify the product which appear in the equation. For more general initial data in the class of generalized functions of Colombeau, we construct the solution in the sense of association.
Multimodel Design of Large Scale Systems with Multiple Decision Makers.
1982-08-01
virtue. 5- , Lead me from darkneu to light. - Lead me from death to eternal Life. ( Vedic Payer) p. I, MULTIMODEL DESIGN OF LARGE SCALE SYSTEMS WITH...BFI-S2L) is stable for all e in H. To avoid mathematical complications, the feedback matrices of (2.31) are restricted to be of the form, S(e)= Fli + 0...control values used during all past sampling intervals. This information pattern, though not of ouch practical importance, is mathematically con
A Large-Scale Study of Online Shopping Behavior
Nalchigar, Soroosh; Weber, Ingmar
2012-01-01
The continuous growth of electronic commerce has stimulated great interest in studying online consumer behavior. Given the significant growth in online shopping, better understanding of customers allows better marketing strategies to be designed. While studies of online shopping attitude are widespread in the literature, studies of browsing habits differences in relation to online shopping are scarce. This research performs a large scale study of the relationship between Internet browsing hab...
Foundations of Large-Scale Multimedia Information Management and Retrieval
Chang, Edward Y
2011-01-01
"Foundations of Large-Scale Multimedia Information Management and Retrieval - Mathematics of Perception" covers knowledge representation and semantic analysis of multimedia data and scalability in signal extraction, data mining, and indexing. The book is divided into two parts: Part I - Knowledge Representation and Semantic Analysis focuses on the key components of mathematics of perception as it applies to data management and retrieval. These include feature selection/reduction, knowledge representation, semantic analysis, distance function formulation for measuring similarity, and
Large-Scale Integrated Carbon Nanotube Gas Sensors
Kim, Joondong
2012-01-01
Carbon nanotube (CNT) is a promising one-dimensional nanostructure for various nanoscale electronics. Additionally, nanostructures would provide a significant large surface area at a fixed volume, which is an advantage for high-responsive gas sensors. However, the difficulty in fabrication processes limits the CNT gas sensors for the large-scale production. We review the viable scheme for large-area application including the CNT gas sensor fabrication and reaction mechanism with a practical d...
Turbulent large-scale structure effects on wake meandering
Muller, Y.-A.; Masson, C.; Aubrun, S.
2015-06-01
This work studies effects of large-scale turbulent structures on wake meandering using Large Eddy Simulations (LES) over an actuator disk. Other potential source of wake meandering such as the instablility mechanisms associated with tip vortices are not treated in this study. A crucial element of the efficient, pragmatic and successful simulations of large-scale turbulent structures in Atmospheric Boundary Layer (ABL) is the generation of the stochastic turbulent atmospheric flow. This is an essential capability since one source of wake meandering is these large - larger than the turbine diameter - turbulent structures. The unsteady wind turbine wake in ABL is simulated using a combination of LES and actuator disk approaches. In order to dedicate the large majority of the available computing power in the wake, the ABL ground region of the flow is not part of the computational domain. Instead, mixed Dirichlet/Neumann boundary conditions are applied at all the computational surfaces except at the outlet. Prescribed values for Dirichlet contribution of these boundary conditions are provided by a stochastic turbulent wind generator. This allows to simulate large-scale turbulent structures - larger than the computational domain - leading to an efficient simulation technique of wake meandering. Since the stochastic wind generator includes shear, the turbulence production is included in the analysis without the necessity of resolving the flow near the ground. The classical Smagorinsky sub-grid model is used. The resulting numerical methodology has been implemented in OpenFOAM. Comparisons with experimental measurements in porous-disk wakes have been undertaken, and the agreements are good. While temporal resolution in experimental measurements is high, the spatial resolution is often too low. LES numerical results provide a more complete spatial description of the flow. They tend to demonstrate that inflow low frequency content - or large- scale turbulent structures - is
Large Scale Density Estimation of Blue and Fin Whales (LSD)
2015-09-30
1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Large Scale Density Estimation of Blue and Fin Whales ...sensors, or both. The goal of this research is to develop and implement a new method for estimating blue and fin whale density that is effective over...develop and implement a density estimation methodology for quantifying blue and fin whale abundance from passive acoustic data recorded on sparse
Large-Scale Weather Disturbances in Mars’ Southern Extratropics
Hollingsworth, Jeffery L.; Kahre, Melinda A.
2015-11-01
Between late autumn and early spring, Mars’ middle and high latitudes within its atmosphere support strong mean thermal gradients between the tropics and poles. Observations from both the Mars Global Surveyor (MGS) and Mars Reconnaissance Orbiter (MRO) indicate that this strong baroclinicity supports intense, large-scale eastward traveling weather systems (i.e., transient synoptic-period waves). These extratropical weather disturbances are key components of the global circulation. Such wave-like disturbances act as agents in the transport of heat and momentum, and generalized scalar/tracer quantities (e.g., atmospheric dust, water-vapor and ice clouds). The character of large-scale, traveling extratropical synoptic-period disturbances in Mars' southern hemisphere during late winter through early spring is investigated using a moderately high-resolution Mars global climate model (Mars GCM). This Mars GCM imposes interactively lifted and radiatively active dust based on a threshold value of the surface stress. The model exhibits a reasonable "dust cycle" (i.e., globally averaged, a dustier atmosphere during southern spring and summer occurs). Compared to their northern-hemisphere counterparts, southern synoptic-period weather disturbances and accompanying frontal waves have smaller meridional and zonal scales, and are far less intense. Influences of the zonally asymmetric (i.e., east-west varying) topography on southern large-scale weather are examined. Simulations that adapt Mars’ full topography compared to simulations that utilize synthetic topographies emulating key large-scale features of the southern middle latitudes indicate that Mars’ transient barotropic/baroclinic eddies are highly influenced by the great impact basins of this hemisphere (e.g., Argyre and Hellas). The occurrence of a southern storm zone in late winter and early spring appears to be anchored to the western hemisphere via orographic influences from the Tharsis highlands, and the Argyre
Experimental simulation of microinteractions in large scale explosions
Energy Technology Data Exchange (ETDEWEB)
Chen, X.; Luo, R.; Yuen, W.W.; Theofanous, T.G. [California Univ., Santa Barbara, CA (United States). Center for Risk Studies and Safety
1998-01-01
This paper presents data and analysis of recent experiments conducted in the SIGMA-2000 facility to simulate microinteractions in large scale explosions. Specifically, the fragmentation behavior of a high temperature molten steel drop under high pressure (beyond critical) conditions are investigated. The current data demonstrate, for the first time, the effect of high pressure in suppressing the thermal effect of fragmentation under supercritical conditions. The results support the microinteractions idea, and the ESPROSE.m prediction of fragmentation rate. (author)
Systematic Literature Review of Agile Scalability for Large Scale Projects
Directory of Open Access Journals (Sweden)
Hina saeeda
2015-09-01
Full Text Available In new methods, “agile” has come out as the top approach in software industry for the development of the soft wares. With different shapes agile is applied for handling the issues such as low cost, tight time to market schedule continuously changing requirements, Communication & Coordination, team size and distributed environment. Agile has proved to be successful in the small and medium size project, however, it have several limitations when applied on large size projects. The purpose of this study is to know agile techniques in detail, finding and highlighting its restrictions for large size projects with the help of systematic literature review. The systematic literature review is going to find answers for the Research questions: 1 How to make agile approaches scalable and adoptable for large projects?2 What are the existing methods, approaches, frameworks and practices support agile process in large scale projects? 3 What are limitations of existing agile approaches, methods, frameworks and practices with reference to large scale projects? This study will identify the current research problems of the agile scalability for large size projects by giving a detail literature review of the identified problems, existed work for providing solution to these problems and will find out limitations of the existing work for covering the identified problems in the agile scalability. All the results gathered will be summarized statistically based on these finding remedial work will be planned in future for handling the identified limitations of agile approaches for large scale projects.
Critical thinking, politics on a large scale and media democracy
Directory of Open Access Journals (Sweden)
José Antonio IBÁÑEZ-MARTÍN
2015-06-01
Full Text Available The first approximation to the social current reality offers us numerous motives for the worry. The spectacle of violence and of immorality can scare us easily. But more worrying still it is to verify that the horizon of conviviality, peace and wellbeing that Europe had been developing from the Treaty of Rome of 1957 has compromised itself seriously for the economic crisis. Today we are before an assault to the democratic politics, which is qualified, on the part of the media democracy, as an exhausted system, which is required to be changed into a new and great politics, a politics on a large scale. The article analyses the concept of a politics on a large scale, primarily attending to Nietzsche, and noting its union with the great philosophy and the great education. The study of the texts of Nietzsche leads us to the conclusion of how in them we often find an interesting analysis of the problems and a misguided proposal for solutions. We cannot think to suggest solutions to all the problems, but we outline various proposals about changes of political activity, that reasonably are defended from the media democracy. In conclusion, we point out that a politics on a large scale requires statesmen, able to suggest modes of life in common that can structure a long-term coexistence.
Large Scale Magnetic Fields: Density Power Spectrum in Redshift Space
Indian Academy of Sciences (India)
Rajesh Gopal; Shiv K. Sethi
2003-09-01
We compute the density redshift-space power spectrum in the presence of tangled magnetic fields and compare it with existing observations. Our analysis shows that if these magnetic fields originated in the early universe then it is possible to construct models for which the shape of the power spectrum agrees with the large scale slope of the observed power spectrum. However requiring compatibility with observed CMBR anisotropies, the normalization of the power spectrum is too low for magnetic fields to have significant impact on the large scale structure at present. Magnetic fields of a more recent origin generically give density power spectrum ∝ 4 which doesn’t agree with the shape of the observed power spectrum at any scale. Magnetic fields generate curl modes of the velocity field which increase both the quadrupole and hexadecapole of the redshift space power spectrum. For curl modes, the hexadecapole dominates over quadrupole. So the presence of curl modes could be indicated by an anomalously large hexadecapole, which has not yet been computed from observation. It appears difficult to construct models in which tangled magnetic fields could have played a major role in shaping the large scale structure in the present epoch. However if they did, one of the best ways to infer their presence would be from the redshift space effects in the density power spectrum.
A visualization framework for large-scale virtual astronomy
Fu, Chi-Wing
Motivated by advances in modern positional astronomy, this research attempts to digitally model the entire Universe through computer graphics technology. Our first challenge is space itself. The gigantic size of the Universe makes it impossible to put everything into a typical graphics system at its own scale. The graphics rendering process can easily fail because of limited computational precision, The second challenge is that the enormous amount of data could slow down the graphics; we need clever techniques to speed up the rendering. Third, since the Universe is dominated by empty space, objects are widely separated; this makes navigation difficult. We attempt to tackle these problems through various techniques designed to extend and optimize the conventional graphics framework, including the following: power homogeneous coordinates for large-scale spatial representations, generalized large-scale spatial transformations, and rendering acceleration via environment caching and object disappearance criteria. Moreover, we implemented an assortment of techniques for modeling and rendering a variety of astronomical bodies, ranging from the Earth up to faraway galaxies, and attempted to visualize cosmological time; a method we call the Lightcone representation was introduced to visualize the whole space-time of the Universe at a single glance. In addition, several navigation models were developed to handle the large-scale navigation problem. Our final results include a collection of visualization tools, two educational animations appropriate for planetarium audiences, and state-of-the-art-advancing rendering techniques that can be transferred to practice in digital planetarium systems.
Impact of Large-scale Geological Architectures On Recharge
Troldborg, L.; Refsgaard, J. C.; Engesgaard, P.; Jensen, K. H.
Geological and hydrogeological data constitutes the basis for assessment of ground- water flow pattern and recharge zones. The accessibility and applicability of hard ge- ological data is often a major obstacle in deriving plausible conceptual models. Nev- ertheless focus is often on parameter uncertainty caused by the effect of geological heterogeneity due to lack of hard geological data, thus neglecting the possibility of alternative conceptualizations of the large-scale geological architecture. For a catchment in the eastern part of Denmark we have constructed different geologi- cal models based on different conceptualization of the major geological trends and fa- cies architecture. The geological models are equally plausible in a conceptually sense and they are all calibrated to well head and river flow measurements. Comparison of differences in recharge zones and subsequently well protection zones emphasize the importance of assessing large-scale geological architecture in hydrological modeling on regional scale in a non-deterministic way. Geostatistical modeling carried out in a transitional probability framework shows the possibility of assessing multiple re- alizations of large-scale geological architecture from a combination of soft and hard geological information.
Image-based Exploration of Large-Scale Pathline Fields
Nagoor, Omniah H.
2014-05-27
While real-time applications are nowadays routinely used in visualizing large nu- merical simulations and volumes, handling these large-scale datasets requires high-end graphics clusters or supercomputers to process and visualize them. However, not all users have access to powerful clusters. Therefore, it is challenging to come up with a visualization approach that provides insight to large-scale datasets on a single com- puter. Explorable images (EI) is one of the methods that allows users to handle large data on a single workstation. Although it is a view-dependent method, it combines both exploration and modification of visual aspects without re-accessing the original huge data. In this thesis, we propose a novel image-based method that applies the concept of EI in visualizing large flow-field pathlines data. The goal of our work is to provide an optimized image-based method, which scales well with the dataset size. Our approach is based on constructing a per-pixel linked list data structure in which each pixel contains a list of pathlines segments. With this view-dependent method it is possible to filter, color-code and explore large-scale flow data in real-time. In addition, optimization techniques such as early-ray termination and deferred shading are applied, which further improves the performance and scalability of our approach.
Large-scale magnetic topologies of early M dwarfs
Donati, JF; Petit, P; Delfosse, X; Forveille, T; Aurière, M; Cabanac, R; Dintrans, B; Fares, R; Gastine, T; Jardine, MM; Lignières, F; Paletou, F; Velez, J Ramirez; Théado, S
2008-01-01
We present here additional results of a spectropolarimetric survey of a small sample of stars ranging from spectral type M0 to M8 aimed at investigating observationally how dynamo processes operate in stars on both sides of the full convection threshold (spectral type M4). The present paper focuses on early M stars (M0--M3), i.e. above the full convection threshold. Applying tomographic imaging techniques to time series of rotationally modulated circularly polarised profiles collected with the NARVAL spectropolarimeter, we determine the rotation period and reconstruct the large-scale magnetic topologies of 6 early M dwarfs. We find that early-M stars preferentially host large-scale fields with dominantly toroidal and non-axisymmetric poloidal configurations, along with significant differential rotation (and long-term variability); only the lowest-mass star of our subsample is found to host an almost fully poloidal, mainly axisymmetric large-scale field ressembling those found in mid-M dwarfs. This abrupt chan...
Multiresolution comparison of precipitation datasets for large-scale models
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.
Searching for Large Scale Structure in Deep Radio Surveys
Baleisis, A; Loan, A J; Wall, J V; Baleisis, Audra; Lahav, Ofer; Loan, Andrew J.; Wall, Jasper V.
1997-01-01
(Abridged Abstract) We calculate the expected amplitude of the dipole and higher spherical harmonics in the angular distribution of radio galaxies. The median redshift of radio sources in existing catalogues is z=1, which allows us to study large scale structure on scales between those accessible to present optical and infrared surveys, and that of the Cosmic Microwave Background (CMB). The dipole is due to 2 effects which turn out to be of comparable magnitude: (i) our motion with respect to the CMB, and (ii) large scale structure, parameterised here by a family of Cold Dark Matter power-spectra. We make specific predictions for the Green Bank (87GB) and Parkes-MIT-NRAO (PMN) catalogues. For these relatively sparse catalogues both the motion and large scale structure dipole effects are expected to be smaller than the Poisson shot-noise. However, we detect dipole and higher harmonics in the combined 87GB-PMN catalogue which are far larger than expected. We attribute this to a 2 % flux mismatch between the two...
Geospatial Optimization of Siting Large-Scale Solar Projects
Energy Technology Data Exchange (ETDEWEB)
Macknick, J.; Quinby, T.; Caulfield, E.; Gerritsen, M.; Diffendorfer, J.; Haines, S.
2014-03-01
Recent policy and economic conditions have encouraged a renewed interest in developing large-scale solar projects in the U.S. Southwest. However, siting large-scale solar projects is complex. In addition to the quality of the solar resource, solar developers must take into consideration many environmental, social, and economic factors when evaluating a potential site. This report describes a proof-of-concept, Web-based Geographical Information Systems (GIS) tool that evaluates multiple user-defined criteria in an optimization algorithm to inform discussions and decisions regarding the locations of utility-scale solar projects. Existing siting recommendations for large-scale solar projects from governmental and non-governmental organizations are not consistent with each other, are often not transparent in methods, and do not take into consideration the differing priorities of stakeholders. The siting assistance GIS tool we have developed improves upon the existing siting guidelines by being user-driven, transparent, interactive, capable of incorporating multiple criteria, and flexible. This work provides the foundation for a dynamic siting assistance tool that can greatly facilitate siting decisions among multiple stakeholders.
Star formation associated with a large-scale infrared bubble
Xu, Jin-Long
2014-01-01
Using the data from the Galactic Ring Survey (GRS) and Galactic Legacy Infrared Mid-Plane Survey Extraordinaire (GLIMPSE), we performed a study for a large-scale infrared bubble with a size of about 16 pc at a distance of 2.0 kpc. We present the 12CO J=1-0, 13CO J=1-0 and C18O J=1-0 observations of HII region G53.54-0.01 (Sh2-82) obtained at the the Purple Mountain Observation (PMO) 13.7 m radio telescope to investigate the detailed distribution of associated molecular material. The large-scale infrared bubble shows a half-shell morphology at 8 um. H II regions G53.54-0.01, G53.64+0.24, and G54.09-0.06 are situated on the bubble. Comparing the radio recombination line velocities and associated 13CO J=1-0 components of the three H II regions, we found that the 8 um emission associated with H II region G53.54-0.01 should belong to the foreground emission, and only overlap with the large-scale infrared bubble in the line of sight. Three extended green objects (EGOs, the candidate massive young stellar objects), ...
Large scale structure around a z=2.1 cluster
Hung, Chao-Ling; Chiang, Yi-Kuan; Capak, Peter; Cowley, Michael J; Darvish, Behnam; Kacprzak, Glenn G; Kovac, K; Lilly, Simon J; Nanayakkara, Themiya; Spitler, Lee R; Tran, Kim-Vy H; Yuan, Tiantian
2016-01-01
The most prodigious starburst galaxies are absent in massive galaxy clusters today, but their connection with large scale environments is less clear at $z\\gtrsim2$. We present a search of large scale structure around a galaxy cluster core at $z=2.095$ using a set of spectroscopically confirmed galaxies. We find that both color-selected star-forming galaxies (SFGs) and dusty star-forming galaxies (DSFGs) show significant overdensities around the $z=2.095$ cluster. A total of 8 DSFGs (including 3 X-ray luminous active galactic nuclei, AGNs) and 34 SFGs are found within a 10 arcmin radius (corresponds to $\\sim$15 cMpc at $z\\sim2.1$) from the cluster center and within a redshift range of $\\Delta z=0.02$, which leads to galaxy overdensities of $\\delta_{\\rm DSFG}\\sim12.3$ and $\\delta_{\\rm SFG}\\sim2.8$. The cluster core and the extended DSFG- and SFG-rich structure together demonstrate an active cluster formation phase, in which the cluster is accreting a significant amount of material from large scale structure whi...
BILGO: Bilateral greedy optimization for large scale semidefinite programming
Hao, Zhifeng
2013-10-03
Many machine learning tasks (e.g. metric and manifold learning problems) can be formulated as convex semidefinite programs. To enable the application of these tasks on a large-scale, scalability and computational efficiency are considered as desirable properties for a practical semidefinite programming algorithm. In this paper, we theoretically analyze a new bilateral greedy optimization (denoted BILGO) strategy in solving general semidefinite programs on large-scale datasets. As compared to existing methods, BILGO employs a bilateral search strategy during each optimization iteration. In such an iteration, the current semidefinite matrix solution is updated as a bilateral linear combination of the previous solution and a suitable rank-1 matrix, which can be efficiently computed from the leading eigenvector of the descent direction at this iteration. By optimizing for the coefficients of the bilateral combination, BILGO reduces the cost function in every iteration until the KKT conditions are fully satisfied, thus, it tends to converge to a global optimum. In fact, we prove that BILGO converges to the global optimal solution at a rate of O(1/k), where k is the iteration counter. The algorithm thus successfully combines the efficiency of conventional rank-1 update algorithms and the effectiveness of gradient descent. Moreover, BILGO can be easily extended to handle low rank constraints. To validate the effectiveness and efficiency of BILGO, we apply it to two important machine learning tasks, namely Mahalanobis metric learning and maximum variance unfolding. Extensive experimental results clearly demonstrate that BILGO can solve large-scale semidefinite programs efficiently.
Diverse Scene Stitching from a Large-Scale Aerial Video Dataset
Directory of Open Access Journals (Sweden)
Tao Yang
2015-05-01
Full Text Available Diverse scene stitching is a challenging task in aerial video surveillance. This paper presents a hybrid stitching method based on the observation that aerial videos captured in real surveillance settings are neither totally ordered nor completely unordered. Often, human operators apply continuous monitoring of the drone to revisit the same area of interest. This monitoring mechanism yields to multiple short, successive video clips that overlap in either time or space. We exploit this property and treat the aerial image stitching problem as temporal sequential grouping and spatial cross-group retrieval. We develop an effective graph-based framework that can robustly conduct the grouping, retrieval and stitching tasks. To evaluate the proposed approach, we experiment on the large-scale VIRATaerial surveillance dataset, which is challenging for its heterogeneity in image quality and diversity of the scene. Quantitative and qualitative comparisons with state-of-the-art algorithms show the efficiency and robustness of our technique.
Banerjee, Amartya S; Hu, Wei; Yang, Chao; Pask, John E
2016-01-01
The Discontinuous Galerkin (DG) electronic structure method employs an adaptive local basis set to solve the equations of density functional theory in a discontinuous Galerkin framework. The methodology is implemented in the Discontinuous Galerkin Density Functional Theory (DGDFT) code for large-scale parallel electronic structure calculations. In DGDFT, the basis is generated on-the-fly to capture the local material physics, and can systematically attain chemical accuracy with only a few tens of degrees of freedom per atom. Hence, DGDFT combines the key advantage of planewave basis sets in terms of systematic improvability with that of localized basis sets in reducing basis size. A central issue for large-scale calculations, however, is the computation of the electron density from the discretized Hamiltonian in an efficient and scalable manner. We show in this work how Chebyshev polynomial filtered subspace iteration (CheFSI) can be used to address this issue and push the envelope in large-scale materials si...
MeshSLAM: Robust Localization and Large-Scale Mapping in Barren Terrain Project
National Aeronautics and Space Administration — Robots need to know their location to map of their surroundings but without global positioning data they need a map to identify their surroundings and estimate...
MeshSLAM: Robust Localization and Large-Scale Mapping in Barren Terrain Project
National Aeronautics and Space Administration — Robots need to know their location to map of their surroundings but without global positioning data they need a map to identify their surroundings and estimate their...
2012-01-11
involve filtered versions of the control input and system state in the update laws nor does it involve a least-squares exponential forgetting factor...including receptors for glycine, serotonin type 2 and 3, N- methyl-d-aspartate (NMDA), α-2 adrenoreceptors, α-amino-3-hydroxy-5-methyl-4- isoxazo
Robust node estimation and topology discovery for large-scale networks
Alouini, Mohamed-Slim
2017-02-23
Various examples are provided for node estimation and topology discovery for networks. In one example, a method includes receiving a packet having an identifier from a first node; adding the identifier to another transmission packet based on a comparison between the first identifier and existing identifiers associated with the other packet; adjusting a transmit probability based on the comparison; and transmitting the other packet based on a comparison between the transmit probability and a probability distribution. In another example, a system includes a network device that can adds an identifier received in a packet to a list including existing identifiers and adjust a transmit probability based on a comparison between the identifiers; and transmit another packet based on a comparison between the transmit probability and a probability distribution. In another example, a method includes determining a quantity of sensor devices based on a plurality of identifiers received in a packet.
Foundational perspectives on causality in large-scale brain networks
Mannino, Michael; Bressler, Steven L.
2015-12-01
A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical
Foundational perspectives on causality in large-scale brain networks.
Mannino, Michael; Bressler, Steven L
2015-12-01
A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical
Challenges of Modeling Flood Risk at Large Scales
Guin, J.; Simic, M.; Rowe, J.
2009-04-01
algorithm propagates the flows for each simulated event. The model incorporates a digital terrain model (DTM) at 10m horizontal resolution, which is used to extract flood plain cross-sections such that a one-dimensional hydraulic model can be used to estimate extent and elevation of flooding. In doing so the effect of flood defenses in mitigating floods are accounted for. Finally a suite of vulnerability relationships have been developed to estimate flood losses for a portfolio of properties that are exposed to flood hazard. Historical experience indicates that a for recent floods in Great Britain more than 50% of insurance claims occur outside the flood plain and these are primarily a result of excess surface flow, hillside flooding, flooding due to inadequate drainage. A sub-component of the model addresses this issue by considering several parameters that best explain the variability of claims off the flood plain. The challenges of modeling such a complex phenomenon at a large scale largely dictate the choice of modeling approaches that need to be adopted for each of these model components. While detailed numerically-based physical models exist and have been used for conducting flood hazard studies, they are generally restricted to small geographic regions. In a probabilistic risk estimation framework like our current model, a blend of deterministic and statistical techniques have to be employed such that each model component is independent, physically sound and is able to maintain the statistical properties of observed historical data. This is particularly important because of the highly non-linear behavior of the flooding process. With respect to vulnerability modeling, both on and off the flood plain, the challenges include the appropriate scaling of a damage relationship when applied to a portfolio of properties. This arises from the fact that the estimated hazard parameter used for damage assessment, namely maximum flood depth has considerable uncertainty. The
On the Phenomenology of an Accelerated Large-Scale Universe
Directory of Open Access Journals (Sweden)
Martiros Khurshudyan
2016-10-01
Full Text Available In this review paper, several new results towards the explanation of the accelerated expansion of the large-scale universe is discussed. On the other hand, inflation is the early-time accelerated era and the universe is symmetric in the sense of accelerated expansion. The accelerated expansion of is one of the long standing problems in modern cosmology, and physics in general. There are several well defined approaches to solve this problem. One of them is an assumption concerning the existence of dark energy in recent universe. It is believed that dark energy is responsible for antigravity, while dark matter has gravitational nature and is responsible, in general, for structure formation. A different approach is an appropriate modification of general relativity including, for instance, f ( R and f ( T theories of gravity. On the other hand, attempts to build theories of quantum gravity and assumptions about existence of extra dimensions, possible variability of the gravitational constant and the speed of the light (among others, provide interesting modifications of general relativity applicable to problems of modern cosmology, too. In particular, here two groups of cosmological models are discussed. In the first group the problem of the accelerated expansion of large-scale universe is discussed involving a new idea, named the varying ghost dark energy. On the other hand, the second group contains cosmological models addressed to the same problem involving either new parameterizations of the equation of state parameter of dark energy (like varying polytropic gas, or nonlinear interactions between dark energy and dark matter. Moreover, for cosmological models involving varying ghost dark energy, massless particle creation in appropriate radiation dominated universe (when the background dynamics is due to general relativity is demonstrated as well. Exploring the nature of the accelerated expansion of the large-scale universe involving generalized
Nonlinear evolution of large-scale structure in the universe
Energy Technology Data Exchange (ETDEWEB)
Frenk, C.S.; White, S.D.M.; Davis, M.
1983-08-15
Using N-body simulations we study the nonlinear development of primordial density perturbation in an Einstein--de Sitter universe. We compare the evolution of an initial distribution without small-scale density fluctuations to evolution from a random Poisson distribution. These initial conditions mimic the assumptions of the adiabatic and isothermal theories of galaxy formation. The large-scale structures which form in the two cases are markedly dissimilar. In particular, the correlation function xi(r) and the visual appearance of our adiabatic (or ''pancake'') models match better the observed distribution of galaxies. This distribution is characterized by large-scale filamentary structure. Because the pancake models do not evolve in a self-similar fashion, the slope of xi(r) steepens with time; as a result there is a unique epoch at which these models fit the galaxy observations. We find the ratio of cutoff length to correlation length at this time to be lambda/sub min//r/sub 0/ = 5.1; its expected value in a neutrino dominated universe is 4(..cap omega..h)/sup -1/ (H/sub 0/ = 100h km s/sup -1/ Mpc/sup -1/). At early epochs these models predict a negligible amplitude for xi(r) and could explain the lack of measurable clustering in the Ly..cap alpha.. absorption lines of high-redshift quasars. However, large-scale structure in our models collapses after z = 2. If this collapse precedes galaxy formation as in the usual pancake theory, galaxies formed uncomfortably recently. The extent of this problem may depend on the cosmological model used; the present series of experiments should be extended in the future to include models with ..cap omega..<1.
Modeling Large Scale Circuits Using Massively Parallel Descrete-Event Simulation
2013-06-01
in VHDL and Verilog . Using the Synopsys Design Compiler and scripts provided by the OpenSPARC code base, we were able to generate gate level...efficiently used in a simulation model. This process is described in Figure 1. 3.2.1 Source. The OpenSPARC T2 design is provided in Verilog Register Transfer...one flat netlist. This file format is still completely valid Verilog code. The module is defined with connection arguments and the netlist of its
Solving Large-Scale QAP Problems in Parallel with the Search
DEFF Research Database (Denmark)
Clausen, Jens; Brüngger, A.; Marzetta, A.
1998-01-01
Program libraries are one tool to make the cooperation between specialists from various fields successful: the separation of application-specific knowledge from application-independent tasks ensures portability, maintenance, extensibility, and flexibility. The current paper demonstrates the success...
Design techniques for large scale linear measurement systems
Energy Technology Data Exchange (ETDEWEB)
Candy, J.V.
1979-03-01
Techniques to design measurement schemes for systems modeled by large scale linear time invariant systems, i.e., physical systems modeled by a large number (> 5) of ordinary differential equations, are described. The techniques are based on transforming the physical system model to a coordinate system facilitating the design and then transforming back to the original coordinates. An example of a three-stage, four-species, extraction column used in the reprocessing of spent nuclear fuel elements is presented. The basic ideas are briefly discussed in the case of noisy measurements. An example using a plutonium nitrate storage vessel (reprocessing) with measurement uncertainty is also presented.
Large scale PV plants - also in Denmark. Project report
Energy Technology Data Exchange (ETDEWEB)
Ahm, P. (PA Energy, Malling (Denmark)); Vedde, J. (SiCon. Silicon and PV consulting, Birkeroed (Denmark))
2011-04-15
Large scale PV (LPV) plants, plants with a capacity of more than 200 kW, has since 2007 constituted an increasing share of the global PV installations. In 2009 large scale PV plants with cumulative power more that 1,3 GWp were connected to the grid. The necessary design data for LPV plants in Denmark are available or can be found, although irradiance data could be improved. There seems to be very few institutional barriers for LPV projects, but as so far no real LPV projects have been processed, these findings have to be regarded as preliminary. The fast growing number of very large scale solar thermal plants for district heating applications supports these findings. It has further been investigated, how to optimize the lay-out of LPV plants. Under the Danish irradiance conditions with several winter months with very low solar height PV installations on flat surfaces will have to balance the requirements of physical space - and cost, and the loss of electricity production due to shadowing effects. The potential for LPV plants in Denmark are found in three main categories: PV installations on flat roof of large commercial buildings, PV installations on other large scale infrastructure such as noise barriers and ground mounted PV installations. The technical potential for all three categories is found to be significant and in the range of 50 - 250 km2. In terms of energy harvest PV plants will under Danish conditions exhibit an overall efficiency of about 10 % in conversion of the energy content of the light compared to about 0,3 % for biomass. The theoretical ground area needed to produce the present annual electricity consumption of Denmark at 33-35 TWh is about 300 km2 The Danish grid codes and the electricity safety regulations mention very little about PV and nothing about LPV plants. It is expected that LPV plants will be treated similarly to big wind turbines. A number of LPV plant scenarios have been investigated in detail based on real commercial offers and
Using Large Scale Test Results for Pedagogical Purposes
DEFF Research Database (Denmark)
Dolin, Jens
2012-01-01
The use and influence of large scale tests (LST), both national and international, has increased dramatically within the last decade. This process has revealed a tension between the legitimate need for information about the performance of the educational system and teachers to inform policy...... wash back effects known from other research but gave additionally some insight in teachers’ attitudes towards LSTs. To account for these findings results from another research project - the Validation of PISA – will be included. This project analyzed how PISA has influenced the Danish educational...
Cosmological parameters from large scale structure - geometric versus shape information
Hamann, Jan; Lesgourgues, Julien; Rampf, Cornelius; Wong, Yvonne Y Y
2010-01-01
The matter power spectrum as derived from large scale structure (LSS) surveys contains two important and distinct pieces of information: an overall smooth shape and the imprint of baryon acoustic oscillations (BAO). We investigate the separate impact of these two types of information on cosmological parameter estimation, and show that for the simplest cosmological models, the broad-band shape information currently contained in the SDSS DR7 halo power spectrum (HPS) is by far superseded by geometric information derived from the baryonic features. An immediate corollary is that contrary to popular beliefs, the upper limit on the neutrino mass m_\
Practical Optimal Control of Large-scale Water Distribution Network
Institute of Scientific and Technical Information of China (English)
Lv Mou(吕谋); Song Shuang
2004-01-01
According to the network characteristics and actual state of the water supply system in China, the implicit model, which can be solved by the hierarchical optimization method, was established. In special, based on the analyses of the water supply system containing variable-speed pumps, a software has been developed successfully. The application of this model to the city of Hangzhou (China) was compared to experiential strategy. The results of this study showed that the developed model is a promising optimization method to control the large-scale water supply systems.
Controlled growth of large-scale silver nanowires
Institute of Scientific and Technical Information of China (English)
Xiao Cong-Wen; Yang Hai-Tao; Shen Cheng-Min; Li Zi-An; Zhang Huai-Ruo; Liu Fei; Yang Tian-Zhong; Chen Shu-Tang; Gao Hong-Jun
2005-01-01
Large-scale silver nanowires with controlled aspect ratio were synthesized via reducing silver nitrate with 1, 2-propanediol in the presence of poly (vinyl pyrrolidone) (PVP). Scanning electron microscopy, transmission electron microscopy and x-ray powder diffraction were employed to characterize these silver nanowires. The diameter of the silver nanowires can be readily controlled in the range of 100 to 400 nm by varying the experimental conditions. X-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy results show that there exists no chemical bond between the silver and the nitrogen atoms. The interaction between PVP and silver nanowires is mainly through the oxygen atom in the carbonyl group.
Accurate emulators for large-scale computer experiments
Haaland, Ben; 10.1214/11-AOS929
2012-01-01
Large-scale computer experiments are becoming increasingly important in science. A multi-step procedure is introduced to statisticians for modeling such experiments, which builds an accurate interpolator in multiple steps. In practice, the procedure shows substantial improvements in overall accuracy, but its theoretical properties are not well established. We introduce the terms nominal and numeric error and decompose the overall error of an interpolator into nominal and numeric portions. Bounds on the numeric and nominal error are developed to show theoretically that substantial gains in overall accuracy can be attained with the multi-step approach.
Large-scale computing techniques for complex system simulations
Dubitzky, Werner; Schott, Bernard
2012-01-01
Complex systems modeling and simulation approaches are being adopted in a growing number of sectors, including finance, economics, biology, astronomy, and many more. Technologies ranging from distributed computing to specialized hardware are explored and developed to address the computational requirements arising in complex systems simulations. The aim of this book is to present a representative overview of contemporary large-scale computing technologies in the context of complex systems simulations applications. The intention is to identify new research directions in this field and
Application of methanol synthesis reactor to large-scale plants
Institute of Scientific and Technical Information of China (English)
LOU Ren; XU Rong-liang; LOU Shou-lin
2006-01-01
The developing status of world large-scale methanol production technology is analyzed and Linda's JW low-pressure methanol synthesis reactor with uniform temperature is described. JW serial reactors have been successfully introduced in and applied in Harbin Gasification Plant and the productivity has been increased by 50% and now nine sets of equipments are successfully running in Harbin Gasification Plant,Jiangsu Xinya, Shandong Kenli,Henan Zhongyuan, Handan Xinyangguang,' Shanxi Weihua and Inner Mongolia Tianye. Now it has manufacturing the reactors of 300,000 t/a for Liaoning Dahua. Some solutions for the structure problems of 1000 ～5000 t/d methanol synthesis rectors are put forward.
Large-scale magnetic fields from inflation in teleparallel gravity
Bamba, Kazuharu; Luo, Ling-Wei
2013-01-01
Generation of large-scale magnetic fields in inflationary cosmology is studied in teleparallelism, where instead of the scalar curvature in general relativity, the torsion scalar describes the gravity theory. In particular, we investigate a coupling of the electromagnetic field to the torsion scalar during inflation, which leads to the breaking of conformal invariance of the electromagnetic field. We demonstrate that for a power-law type coupling, the current magnetic field strength of $\\sim 10^{-9}$ G on 1 Mpc scale can be generated, if the backreaction effects and strong coupling problem are not taken into consideration.
An Evaluation Framework for Large-Scale Network Structures
DEFF Research Database (Denmark)
Pedersen, Jens Myrup; Knudsen, Thomas Phillip; Madsen, Ole Brun
2004-01-01
structure is a matter of trade-offs between different desired properties, and given a specific case with specific known or expected demands and constraints, the parameters presented will be weighted differently. The decision of such a weighting is supported by a discussion of each parameter. The paper......An evaluation framework for large-scale network structures is presented, which facilitates evaluations and comparisons of different physical network structures. A number of quantitative and qualitative parameters are presented, and their importance to networks discussed. Choosing a network...
Large scale solar cooling plants in America, Asia and Europe
Energy Technology Data Exchange (ETDEWEB)
Holter, Christian; Olsacher, Nicole [S.O.L.I.D. GmbH, Graz (Austria)
2010-07-01
Large scale solar cooling plants with an area between 120 - 1600 m{sup 2} are representative examples to illustrate S.O.L.I.D.'s experiences. The selected three reference solar cooling plants are located on three different continents: America, Asia and Europe. Every region has different framework conditions and its unforeseen challenges but professional experience and innovative ideas form the basis that each plant is operating well and satisfying the customer's demand. This verifies that solar cooling already is a proven technology. (orig.)
Simple Method for Large-Scale Fabrication of Plasmonic Structures
Makarov, Sergey V; Mukhin, Ivan S; Shishkin, Ivan I; Mozharov, Alexey M; Krasnok, Alexander E; Belov, Pavel A
2015-01-01
A novel method for single-step, lithography-free, and large-scale laser writing of nanoparticle-based plasmonic structures has been developed. Changing energy of femtosecond laser pulses and thickness of irradiated gold film it is possible to vary diameter of the gold nanoparticles, while the distance between them can be varied by laser scanning parameters. This method has an advantage over the most previously demonstrated methods in its simplicity and versatility, while the quality of the structures is good enough for many applications. In particular, resonant light absorbtion/scattering and surface-enhanced Raman scattering have been demonstrated on the fabricated nanostructures.
Large Scale Composite Manufacturing for Heavy Lift Launch Vehicles
Stavana, Jacob; Cohen, Leslie J.; Houseal, Keth; Pelham, Larry; Lort, Richard; Zimmerman, Thomas; Sutter, James; Western, Mike; Harper, Robert; Stuart, Michael
2012-01-01
Risk reduction for the large scale composite manufacturing is an important goal to produce light weight components for heavy lift launch vehicles. NASA and an industry team successfully employed a building block approach using low-cost Automated Tape Layup (ATL) of autoclave and Out-of-Autoclave (OoA) prepregs. Several large, curved sandwich panels were fabricated at HITCO Carbon Composites. The aluminum honeycomb core sandwich panels are segments of a 1/16th arc from a 10 meter cylindrical barrel. Lessons learned highlight the manufacturing challenges required to produce light weight composite structures such as fairings for heavy lift launch vehicles.
An iterative decoupling solution method for large scale Lyapunov equations
Athay, T. M.; Sandell, N. R., Jr.
1976-01-01
A great deal of attention has been given to the numerical solution of the Lyapunov equation. A useful classification of the variety of solution techniques are the groupings of direct, transformation, and iterative methods. The paper summarizes those methods that are at least partly favorable numerically, giving special attention to two criteria: exploitation of a general sparse system matrix structure and efficiency in resolving the governing linear matrix equation for different matrices. An iterative decoupling solution method is proposed as a promising approach for solving large-scale Lyapunov equation when the system matrix exhibits a general sparse structure. A Fortran computer program that realizes the iterative decoupling algorithm is also discussed.
Large-Scale Self-Consistent Nuclear Mass Calculations
Stoitsov, M V; Dobaczewski, J; Nazarewicz, W
2006-01-01
The program of systematic large-scale self-consistent nuclear mass calculations that is based on the nuclear density functional theory represents a rich scientific agenda that is closely aligned with the main research directions in modern nuclear structure and astrophysics, especially the radioactive nuclear beam physics. The quest for the microscopic understanding of the phenomenon of nuclear binding represents, in fact, a number of fundamental and crucial questions of the quantum many-body problem, including the proper treatment of correlations and dynamics in the presence of symmetry breaking. Recent advances and open problems in the field of nuclear mass calculations are presented and discussed.
Generation of large-scale winds in horizontally anisotropic convection
von Hardenberg, J; Provenzale, A; Spiegel, E A
2015-01-01
We simulate three-dimensional, horizontally periodic Rayleigh-B\\'enard convection between free-slip horizontal plates, rotating about a horizontal axis. When both the temperature difference between the plates and the rotation rate are sufficiently large, a strong horizontal wind is generated that is perpendicular to both the rotation vector and the gravity vector. The wind is turbulent, large-scale, and vertically sheared. Horizontal anisotropy, engendered here by rotation, appears necessary for such wind generation. Most of the kinetic energy of the flow resides in the wind, and the vertical turbulent heat flux is much lower on average than when there is no wind.
Large-Scale Agriculture and Outgrower Schemes in Ethiopia
DEFF Research Database (Denmark)
Wendimu, Mengistu Assefa
, whereas Chapter 4 indicates that sugarcane outgrowers’ easy access to credit and technology and their high productivity compared to the plantation does not necessarily improve their income and asset stocks particularly when participation in outgrower schemes is mandatory, the buyer has monopsony market...... commands a higher wage than ‘formal’ large-scale agriculture, while rather different wage determination mechanisms exist in the two sectors. Human capital characteristics (education and experience) partly explain the differences in wages within the formal sector, but play no significant role...