Planning under uncertainty solving large-scale stochastic linear programs
Infanger, G. . Dept. of Operations Research Technische Univ., Vienna . 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.
ARPACK: Solving large scale eigenvalue problems
NASA Astrophysics Data System (ADS)
Lehoucq, Rich; Maschhoff, Kristi; Sorensen, Danny; Yang, Chao
2013-11-01
ARPACK is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems. The package is designed to compute a few eigenvalues and corresponding eigenvectors of a general n by n matrix A. It is most appropriate for large sparse or structured matrices A where structured means that a matrix-vector product w
Large scale stochastic spatio-temporal modelling with PCRaster
NASA Astrophysics Data System (ADS)
Karssenberg, Derek; Drost, Niels; Schmitz, Oliver; de Jong, Kor; Bierkens, Marc F. P.
2013-04-01
PCRaster is a software framework for building spatio-temporal models of land surface processes (http://www.pcraster.eu). Building blocks of models are spatial operations on raster maps, including a large suite of operations for water and sediment routing. These operations are available to model builders as Python functions. The software comes with Python framework classes providing control flow for spatio-temporal modelling, Monte Carlo simulation, and data assimilation (Ensemble Kalman Filter and Particle Filter). Models are built by combining the spatial operations in these framework classes. This approach enables modellers without specialist programming experience to construct large, rather complicated models, as many technical details of modelling (e.g., data storage, solving spatial operations, data assimilation algorithms) are taken care of by the PCRaster toolbox. Exploratory modelling is supported by routines for prompt, interactive visualisation of stochastic spatio-temporal data generated by the models. The high computational requirements for stochastic spatio-temporal modelling, and an increasing demand to run models over large areas at high resolution, e.g. in global hydrological modelling, require an optimal use of available, heterogeneous computing resources by the modelling framework. Current work in the context of the eWaterCycle project is on a parallel implementation of the modelling engine, capable of running on a high-performance computing infrastructure such as clusters and supercomputers. Model runs will be distributed over multiple compute nodes and multiple processors (GPUs and CPUs). Parallelization will be done by parallel execution of Monte Carlo realizations and sub regions of the modelling domain. In our approach we use multiple levels of parallelism, improving scalability considerably. On the node level we will use OpenCL, the industry standard for low-level high performance computing kernels. To combine multiple nodes we will use
Solving Large-scale Eigenvalue Problems in SciDACApplications
Yang, Chao
2005-06-29
Large-scale eigenvalue problems arise in a number of DOE applications. This paper provides an overview of the recent development of eigenvalue computation in the context of two SciDAC applications. We emphasize the importance of Krylov subspace methods, and point out its limitations. We discuss the value of alternative approaches that are more amenable to the use of preconditioners, and report the progression using the multi-level algebraic sub-structuring techniques to speed up eigenvalue calculation. In addition to methods for linear eigenvalue problems, we also examine new approaches to solving two types of non-linear eigenvalue problems arising from SciDAC applications.
Solving large scale structure in ten easy steps with COLA
Tassev, Svetlin; Zaldarriaga, Matias; Eisenstein, Daniel J. E-mail: matiasz@ias.edu
2013-06-01
We present the COmoving Lagrangian Acceleration (COLA) method: an N-body method for solving for Large Scale Structure (LSS) in a frame that is comoving with observers following trajectories calculated in Lagrangian Perturbation Theory (LPT). Unlike standard N-body methods, the COLA method can straightforwardly trade accuracy at small-scales in order to gain computational speed without sacrificing accuracy at large scales. This is especially useful for cheaply generating large ensembles of accurate mock halo catalogs required to study galaxy clustering and weak lensing, as those catalogs are essential for performing detailed error analysis for ongoing and future surveys of LSS. As an illustration, we ran a COLA-based N-body code on a box of size 100 Mpc/h with particles of mass ≈ 5 × 10{sup 9}M{sub s}un/h. Running the code with only 10 timesteps was sufficient to obtain an accurate description of halo statistics down to halo masses of at least 10{sup 11}M{sub s}un/h. This is only at a modest speed penalty when compared to mocks obtained with LPT. A standard detailed N-body run is orders of magnitude slower than our COLA-based code. The speed-up we obtain with COLA is due to the fact that we calculate the large-scale dynamics exactly using LPT, while letting the N-body code solve for the small scales, without requiring it to capture exactly the internal dynamics of halos. Achieving a similar level of accuracy in halo statistics without the COLA method requires at least 3 times more timesteps than when COLA is employed.
Solving large scale structure in ten easy steps with COLA
NASA Astrophysics Data System (ADS)
Tassev, Svetlin; Zaldarriaga, Matias; Eisenstein, Daniel J.
2013-06-01
We present the COmoving Lagrangian Acceleration (COLA) method: an N-body method for solving for Large Scale Structure (LSS) in a frame that is comoving with observers following trajectories calculated in Lagrangian Perturbation Theory (LPT). Unlike standard N-body methods, the COLA method can straightforwardly trade accuracy at small-scales in order to gain computational speed without sacrificing accuracy at large scales. This is especially useful for cheaply generating large ensembles of accurate mock halo catalogs required to study galaxy clustering and weak lensing, as those catalogs are essential for performing detailed error analysis for ongoing and future surveys of LSS. As an illustration, we ran a COLA-based N-body code on a box of size 100 Mpc/h with particles of mass ≈ 5 × 109Msolar/h. Running the code with only 10 timesteps was sufficient to obtain an accurate description of halo statistics down to halo masses of at least 1011Msolar/h. This is only at a modest speed penalty when compared to mocks obtained with LPT. A standard detailed N-body run is orders of magnitude slower than our COLA-based code. The speed-up we obtain with COLA is due to the fact that we calculate the large-scale dynamics exactly using LPT, while letting the N-body code solve for the small scales, without requiring it to capture exactly the internal dynamics of halos. Achieving a similar level of accuracy in halo statistics without the COLA method requires at least 3 times more timesteps than when COLA is employed.
He, Qiang; Hu, Xiangtao; Ren, Hong; Zhang, Hongqi
2015-11-01
A novel artificial fish swarm algorithm (NAFSA) is proposed for solving large-scale reliability-redundancy allocation problem (RAP). In NAFSA, the social behaviors of fish swarm are classified in three ways: foraging behavior, reproductive behavior, and random behavior. The foraging behavior designs two position-updating strategies. And, the selection and crossover operators are applied to define the reproductive ability of an artificial fish. For the random behavior, which is essentially a mutation strategy, the basic cloud generator is used as the mutation operator. Finally, numerical results of four benchmark problems and a large-scale RAP are reported and compared. NAFSA shows good performance in terms of computational accuracy and computational efficiency for large scale RAP. PMID:26474934
Tensor-Krylov methods for solving large-scale systems of nonlinear equations.
Bader, Brett William
2004-08-01
This paper develops and investigates iterative tensor methods for solving large-scale systems of nonlinear equations. Direct tensor methods for nonlinear equations have performed especially well on small, dense problems where the Jacobian matrix at the solution is singular or ill-conditioned, which may occur when approaching turning points, for example. This research extends direct tensor methods to large-scale problems by developing three tensor-Krylov methods that base each iteration upon a linear model augmented with a limited second-order term, which provides information lacking in a (nearly) singular Jacobian. The advantage of the new tensor-Krylov methods over existing large-scale tensor methods is their ability to solve the local tensor model to a specified accuracy, which produces a more accurate tensor step. The performance of these methods in comparison to Newton-GMRES and tensor-GMRES is explored on three Navier-Stokes fluid flow problems. The numerical results provide evidence that tensor-Krylov methods are generally more robust and more efficient than Newton-GMRES on some important and difficult problems. In addition, the results show that the new tensor-Krylov methods and tensor- GMRES each perform better in certain situations.
a Stochastic Approach to Multiobjective Optimization of Large-Scale Water Reservoir Networks
NASA Astrophysics Data System (ADS)
Bottacin-Busolin, A.; Worman, A. L.
2013-12-01
A main challenge for the planning and management of water resources is the development of multiobjective strategies for operation of large-scale water reservoir networks. The optimal sequence of water releases from multiple reservoirs depends on the stochastic variability of correlated hydrologic inflows and on various processes that affect water demand and energy prices. Although several methods have been suggested, large-scale optimization problems arising in water resources management are still plagued by the high dimensional state space and by the stochastic nature of the hydrologic inflows. In this work, the optimization of reservoir operation is approached using approximate dynamic programming (ADP) with policy iteration and function approximators. The method is based on an off-line learning process in which operating policies are evaluated for a number of stochastic inflow scenarios, and the resulting value functions are used to design new, improved policies until convergence is attained. A case study is presented of a multi-reservoir system in the Dalälven River, Sweden, which includes 13 interconnected reservoirs and 36 power stations. Depending on the late spring and summer peak discharges, the lowlands adjacent to Dalälven can often be flooded during the summer period, and the presence of stagnating floodwater during the hottest months of the year is the cause of a large proliferation of mosquitos, which is a major problem for the people living in the surroundings. Chemical pesticides are currently being used as a preventive countermeasure, which do not provide an effective solution to the problem and have adverse environmental impacts. In this study, ADP was used to analyze the feasibility of alternative operating policies for reducing the flood risk at a reasonable economic cost for the hydropower companies. To this end, mid-term operating policies were derived by combining flood risk reduction with hydropower production objectives. The performance
Quantifying the colour-dependent stochasticity of large-scale structure
NASA Astrophysics Data System (ADS)
Patej, Anna; Eisenstein, Daniel
2016-08-01
We address the question of whether massive red and blue galaxies trace the same large-scale structure at z ˜ 0.6 using the CMASS sample of galaxies from Data Release 12 of the Sloan Digital Sky Survey III. After splitting the catalogue into subsamples of red and blue galaxies using a simple colour cut, we measure the clustering of both subsamples and construct the correlation coefficient, r, using two statistics. The correlation coefficient quantifies the stochasticity between the two subsamples, which we examine over intermediate scales (20 ≲ R ≲ 100 h-1 Mpc). We find that on these intermediate scales, the correlation coefficient is consistent with 1; in particular, we find r > 0.95 taking into account both statistics and r > 0.974 using the favoured statistic.
Lenormand, R.; Thiele, M.R.
1997-08-01
The paper describes the method and presents preliminary results for the calculation of homogenized relative permeabilities
Behavioral stochastic resonance associated with large-scale synchronization of human brain activity
NASA Astrophysics Data System (ADS)
Kitajo, Keiichi; Yamanaka, Kentaro; Nozaki, Daichi; Ward, Lawrence M.; Yamamoto, Yoshiharu
2004-05-01
We demonstrate experimentally that enhanced detection of weak visual signals by addition of visual noise is accompanied by an increase in phase synchronization of EEG signals across widely-separated areas of the human brain. In our sensorimotor integration task, observers responded to a weak rectangular gray-level signal presented to their right eyes by pressing and releasing a button whenever they detected an increment followed by a decrement in brightness. Signal detection performance was optimized by presenting randomly-changing-gray-level noise separately to observers' left eyes using a mirror stereoscope. We measured brain electrical activity at the scalp by electroencephalograph (EEG), calculated the instantaneous phase for each EEG signal, and evaluated the degree of large-scale phase synchronization between pairs of EEG signals. Dynamic synchronization-desynchronization patterns were observed and we found evidence of noise-enhanced large-scale synchronization associated with detection of the brightness changes under conditions of noise-enhanced performance. Our results suggest that behavioral stochastic resonance might arise from noise-enhanced synchronization of neural activities across widespread brain regions.
Solving Large Scale Nonlinear Eigenvalue Problem in Next-Generation Accelerator Design
Liao, Ben-Shan; Bai, Zhaojun; Lee, Lie-Quan; Ko, Kwok; /SLAC
2006-09-28
A number of numerical methods, including inverse iteration, method of successive linear problem and nonlinear Arnoldi algorithm, are studied in this paper to solve a large scale nonlinear eigenvalue problem arising from finite element analysis of resonant frequencies and external Q{sub e} values of a waveguide loaded cavity in the next-generation accelerator design. They present a nonlinear Rayleigh-Ritz iterative projection algorithm, NRRIT in short and demonstrate that it is the most promising approach for a model scale cavity design. The NRRIT algorithm is an extension of the nonlinear Arnoldi algorithm due to Voss. Computational challenges of solving such a nonlinear eigenvalue problem for a full scale cavity design are outlined.
NASA Astrophysics Data System (ADS)
Lin, Chien-Min
Systematically numerical implementations for solving the large-scale electromagnetic problems of microstrip interconnects and rough surface scattering are explored and demonstrated in this dissertation by comparing with the traditional methods. Having circumvented the major difficulties of numerous storage and computational complexity, the proposed methods had validated themselves on the affordable computer platforms whenever both the analytical approaches and conventional numerical methods are not applicable. In use of the Method of Moments, an integro-differential equation is first formulated in terms of surface unknowns related to the boundary conditions. Following Garlerkin's procedures, a matrix equation with a finite discretization of N unknowns is constructed. In the full- wave analysis of microstrip interconnects, Complex Image Method is used to reduce the matrix fill-time while the Mixed-Potential Integral Equation with Rao, Wilton, and Glisson triangular discretization is concerned. The impedance matrix is decomposed into a pair of strong and weak interaction matrix accounting for the separation while the integral kernels are sufficiently approximated. Recalling the Fast Fourier Transform, the weak- interaction contributions are conferred in a canonical grid using the Taylor's series expansion. A Screening Window Wavelet Transform scheme is applied to the strong- interaction matrix for the data compression and high sparsity. Based on Multiresolution Analysis, the Matrix- Vector Multiplication can be efficiently performed by the Subband Filtering Scheme in the wavelet domain. Finally, the Banded or Sparse Matrix Iterative Approach in conjunction with the Conjugate Gradient iterative method is employed to solve for the matrix equation. In addition to investigating the validity of analytical theories, the proposed methods are corroborated to study the backscattering enhancement, conical diffraction, and Stokes parameters in remote sensing and induced surface
Towards large scale stochastic rainfall models for flood risk assessment in trans-national basins
NASA Astrophysics Data System (ADS)
Serinaldi, F.; Kilsby, C. G.
2012-04-01
While extensive research has been devoted to rainfall-runoff modelling for risk assessment in small and medium size watersheds, less attention has been paid, so far, to large scale trans-national basins, where flood events have severe societal and economic impacts with magnitudes quantified in billions of Euros. As an example, in the April 2006 flood events along the Danube basin at least 10 people lost their lives and up to 30 000 people were displaced, with overall damages estimated at more than half a billion Euros. In this context, refined analytical methods are fundamental to improve the risk assessment and, then, the design of structural and non structural measures of protection, such as hydraulic works and insurance/reinsurance policies. Since flood events are mainly driven by exceptional rainfall events, suitable characterization and modelling of space-time properties of rainfall fields is a key issue to perform a reliable flood risk analysis based on alternative precipitation scenarios to be fed in a new generation of large scale rainfall-runoff models. Ultimately, this approach should be extended to a global flood risk model. However, as the need of rainfall models able to account for and simulate spatio-temporal properties of rainfall fields over large areas is rather new, the development of new rainfall simulation frameworks is a challenging task involving that faces with the problem of overcoming the drawbacks of the existing modelling schemes (devised for smaller spatial scales), but keeping the desirable properties. In this study, we critically summarize the most widely used approaches for rainfall simulation. Focusing on stochastic approaches, we stress the importance of introducing suitable climate forcings in these simulation schemes in order to account for the physical coherence of rainfall fields over wide areas. Based on preliminary considerations, we suggest a modelling framework relying on the Generalized Additive Models for Location, Scale
NASA Astrophysics Data System (ADS)
Gross, Lutz; Altinay, Cihan; Fenwick, Joel; Smith, Troy
2014-05-01
inversion and appropriate solution schemes in escript. We will also give a brief introduction into escript's open framework for defining and solving geophysical inversion problems. Finally we will show some benchmark results to demonstrate the computational scalability of the inversion method across a large number of cores and compute nodes in a parallel computing environment. References: - L. Gross et al. (2013): Escript Solving Partial Differential Equations in Python Version 3.4, The University of Queensland, https://launchpad.net/escript-finley - L. Gross and C. Kemp (2013) Large Scale Joint Inversion of Geophysical Data using the Finite Element Method in escript. ASEG Extended Abstracts 2013, http://dx.doi.org/10.1071/ASEG2013ab306 - T. Poulet, L. Gross, D. Georgiev, J. Cleverley (2012): escript-RT: Reactive transport simulation in Python using escript, Computers & Geosciences, Volume 45, 168-176. http://dx.doi.org/10.1016/j.cageo.2011.11.005.
NASA Astrophysics Data System (ADS)
Noor-E-Alam, Md.; Doucette, John
2015-08-01
Grid-based location problems (GBLPs) can be used to solve location problems in business, engineering, resource exploitation, and even in the field of medical sciences. To solve these decision problems, an integer linear programming (ILP) model is designed and developed to provide the optimal solution for GBLPs considering fixed cost criteria. Preliminary results show that the ILP model is efficient in solving small to moderate-sized problems. However, this ILP model becomes intractable in solving large-scale instances. Therefore, a decomposition heuristic is proposed to solve these large-scale GBLPs, which demonstrates significant reduction of solution runtimes. To benchmark the proposed heuristic, results are compared with the exact solution via ILP. The experimental results show that the proposed method significantly outperforms the exact method in runtime with minimal (and in most cases, no) loss of optimality.
Solving stochastic epidemiological models using computer algebra
NASA Astrophysics Data System (ADS)
Hincapie, Doracelly; Ospina, Juan
2011-06-01
Mathematical modeling in Epidemiology is an important tool to understand the ways under which the diseases are transmitted and controlled. The mathematical modeling can be implemented via deterministic or stochastic models. Deterministic models are based on short systems of non-linear ordinary differential equations and the stochastic models are based on very large systems of linear differential equations. Deterministic models admit complete, rigorous and automatic analysis of stability both local and global from which is possible to derive the algebraic expressions for the basic reproductive number and the corresponding epidemic thresholds using computer algebra software. Stochastic models are more difficult to treat and the analysis of their properties requires complicated considerations in statistical mathematics. In this work we propose to use computer algebra software with the aim to solve epidemic stochastic models such as the SIR model and the carrier-borne model. Specifically we use Maple to solve these stochastic models in the case of small groups and we obtain results that do not appear in standard textbooks or in the books updated on stochastic models in epidemiology. From our results we derive expressions which coincide with those obtained in the classical texts using advanced procedures in mathematical statistics. Our algorithms can be extended for other stochastic models in epidemiology and this shows the power of computer algebra software not only for analysis of deterministic models but also for the analysis of stochastic models. We also perform numerical simulations with our algebraic results and we made estimations for the basic parameters as the basic reproductive rate and the stochastic threshold theorem. We claim that our algorithms and results are important tools to control the diseases in a globalized world.
NASA Astrophysics Data System (ADS)
Wang, J.; Cai, X.
2007-12-01
A water resources system can be defined as a large-scale spatial system, within which distributed ecological system interacts with the stream network and ground water system. Water resources management, the causative factors and hence the solutions to be developed have a significant spatial dimension. This motivates a modeling analysis of water resources management within a spatial analytical framework, where data is usually geo- referenced and in the form of a map. One of the important functions of Geographic information systems (GIS) is to identify spatial patterns of environmental variables. The role of spatial patterns in water resources management has been well established in the literature particularly regarding how to design better spatial patterns for satisfying the designated objectives of water resources management. Evolutionary algorithms (EA) have been demonstrated to be successful in solving complex optimization models for water resources management due to its flexibility to incorporate complex simulation models in the optimal search procedure. The idea of combining GIS and EA motivates the development and application of spatial evolutionary algorithms (SEA). SEA assimilates spatial information into EA, and even changes the representation and operators of EA. In an EA used for water resources management, the mathematical optimization model should be modified to account the spatial patterns; however, spatial patterns are usually implicit, and it is difficult to impose appropriate patterns to spatial data. Also it is difficult to express complex spatial patterns by explicit constraints included in the EA. The GIS can help identify the spatial linkages and correlations based on the spatial knowledge of the problem. These linkages are incorporated in the fitness function for the preference of the compatible vegetation distribution. Unlike a regular GA for spatial models, the SEA employs a special hierarchical hyper-population and spatial genetic operators
A Note on Solving Large-Scale Zero-One Programming Problems. Research Report 88-4.
ERIC Educational Resources Information Center
Adema, Jos J.
A heuristic for solving large-scale zero-one programming problems is provided. The heuristic is based on the modifications made by H. Crowder et al. (1983) to the standard branch-and-bound strategy. First, the initialization is modified. The modification is only useful if the objective function values for the continuous and the zero-one…
Gene Golub; Kwok Ko
2009-03-30
The solutions of sparse eigenvalue problems and linear systems constitute one of the key computational kernels in the discretization of partial differential equations for the modeling of linear accelerators. The computational challenges faced by existing techniques for solving those sparse eigenvalue problems and linear systems call for continuing research to improve on the algorithms so that ever increasing problem size as required by the physics application can be tackled. Under the support of this award, the filter algorithm for solving large sparse eigenvalue problems was developed at Stanford to address the computational difficulties in the previous methods with the goal to enable accelerator simulations on then the world largest unclassified supercomputer at NERSC for this class of problems. Specifically, a new method, the Hemitian skew-Hemitian splitting method, was proposed and researched as an improved method for solving linear systems with non-Hermitian positive definite and semidefinite matrices.
On large-scale nonlinear programming techniques for solving optimal control problems
Faco, J.L.D.
1994-12-31
The formulation of decision problems by Optimal Control Theory allows the consideration of their dynamic structure and parameters estimation. This paper deals with techniques for choosing directions in the iterative solution of discrete-time optimal control problems. A unified formulation incorporates nonlinear performance criteria and dynamic equations, time delays, bounded state and control variables, free planning horizon and variable initial state vector. In general they are characterized by a large number of variables, mostly when arising from discretization of continuous-time optimal control or calculus of variations problems. In a GRG context the staircase structure of the jacobian matrix of the dynamic equations is exploited in the choice of basic and super basic variables and when changes of basis occur along the process. The search directions of the bound constrained nonlinear programming problem in the reduced space of the super basic variables are computed by large-scale NLP techniques. A modified Polak-Ribiere conjugate gradient method and a limited storage quasi-Newton BFGS method are analyzed and modifications to deal with the bounds on the variables are suggested based on projected gradient devices with specific linesearches. Some practical models are presented for electric generation planning and fishery management, and the application of the code GRECO - Gradient REduit pour la Commande Optimale - is discussed.
Solving Large-Scale Computational Problems Using Insights from Statistical Physics
Selman, Bart
2012-02-29
Many challenging problems in computer science and related fields can be formulated as constraint satisfaction problems. Such problems consist of a set of discrete variables and a set of constraints between those variables, and represent a general class of so-called NP-complete problems. The goal is to find a value assignment to the variables that satisfies all constraints, generally requiring a search through and exponentially large space of variable-value assignments. Models for disordered systems, as studied in statistical physics, can provide important new insights into the nature of constraint satisfaction problems. Recently, work in this area has resulted in the discovery of a new method for solving such problems, called the survey propagation (SP) method. With SP, we can solve problems with millions of variables and constraints, an improvement of two orders of magnitude over previous methods.
Solving large-scale real-world telecommunication problems using a grid-based genetic algorithm
NASA Astrophysics Data System (ADS)
Luna, Francisco; Nebro, Antonio; Alba, Enrique; Durillo, Juan
2008-11-01
This article analyses the use of a grid-based genetic algorithm (GrEA) to solve a real-world instance of a problem from the telecommunication domain. The problem, known as automatic frequency planning (AFP), is used in a global system for mobile communications (GSM) networks to assign a number of fixed frequencies to a set of GSM transceivers located in the antennae of a cellular phone network. Real data instances of the AFP are very difficult to solve owing to the NP-hard nature of the problem, so combining grid computing and metaheuristics turns out to be a way to provide satisfactory solutions in a reasonable amount of time. GrEA has been deployed on a grid with up to 300 processors to solve an AFP instance of 2612 transceivers. The results not only show that significant running time reductions are achieved, but that the search capability of GrEA clearly outperforms that of the equivalent non-grid algorithm.
Wong, Kwai; D'Azevedo, Ed F; Hu, Harvy; Kail, Andrew A; Su, Shiquan
2015-01-01
We present a novel methodology to compute the transient thermal condi- tion of a set of objects in an open space environment. The governing energy equa- tion and the convective energy transfer are solved by the sparse iterative solvers. The average radiating energy on a set of surfaces is represented by a linear system of the radiosity equations, which is factorized by an out-of-core parallel Cholesky decomposition solver. The coupling and interplay of the direct radiosity solver us- ing GPUs and the CPU-based sparse solver are handled by a light weight software integrator called Interoperable Executive Library (IEL). IEL manages the distribu- tion of data and memory, coordinates communication among parallel processes, and also directs execution of the set of loosely coupled physics tasks as warranted by the thermal condition of the simulated object and its surrounding environment.
NASA Astrophysics Data System (ADS)
Wilson, Larry L.; Lettenmaier, Dennis P.; Skyllingstad, Eric
1992-02-01
A stochastic model of weather states and concurrent daily precipitation at multiple precipitation stations is described. Four algorithms are investigated for classification of daily weather states: k-means clustering, fuzzy clustering, principal components, and principal components coupled with k-means clustering. A semi-Markov model with a geometric distribution for within-class lengths of stay is used to describe the evolution of weather classes. A hierarchical modified Pólya urn model is used to simulate precipitation conditioned on the regional weather type. An information measure that considers both the probability of weather class occurrence and conditional precipitation probabilities is developed to quantify the extent to which each of the weather classification schemes discriminates the precipitation states (rain-no rain) at the precipitation stations. Evaluation of the four algorithms using the information measure shows that all methods performed equally well. The principal components method is chosen due to its ability to incorporate information from larger spatial fields. Precipitation amount distributions are assumed to be drawn from spatially correlated mixed exponential distributions, whose parameters varied by season and weather class. The model is implemented using National Meteorological Center historical atmospheric observations for the period 1964-1988 mapped to 5° × 5° grid cells over the eastern North Pacific, and three precipitation stations west of the Cascade mountain range in the state of Washington. Comparison of simulated weather class-station precipitation time series with observational data shows that the model preserved weather class statistics and mean daily precipitation quite well, especially for stations highest in the hierarchy. Precipitation amounts for the lowest precipitation station in the hierarchy, and for precipitation extremes, are not as well preserved.
NASA Astrophysics Data System (ADS)
Bui-Thanh, T.; Girolami, M.
2014-11-01
We consider the Riemann manifold Hamiltonian Monte Carlo (RMHMC) method for solving statistical inverse problems governed by partial differential equations (PDEs). The Bayesian framework is employed to cast the inverse problem into the task of statistical inference whose solution is the posterior distribution in infinite dimensional parameter space conditional upon observation data and Gaussian prior measure. We discretize both the likelihood and the prior using the H1-conforming finite element method together with a matrix transfer technique. The power of the RMHMC method is that it exploits the geometric structure induced by the PDE constraints of the underlying inverse problem. Consequently, each RMHMC posterior sample is almost uncorrelated/independent from the others providing statistically efficient Markov chain simulation. However this statistical efficiency comes at a computational cost. This motivates us to consider computationally more efficient strategies for RMHMC. At the heart of our construction is the fact that for Gaussian error structures the Fisher information matrix coincides with the Gauss-Newton Hessian. We exploit this fact in considering a computationally simplified RMHMC method combining state-of-the-art adjoint techniques and the superiority of the RMHMC method. Specifically, we first form the Gauss-Newton Hessian at the maximum a posteriori point and then use it as a fixed constant metric tensor throughout RMHMC simulation. This eliminates the need for the computationally costly differential geometric Christoffel symbols, which in turn greatly reduces computational effort at a corresponding loss of sampling efficiency. We further reduce the cost of forming the Fisher information matrix by using a low rank approximation via a randomized singular value decomposition technique. This is efficient since a small number of Hessian-vector products are required. The Hessian-vector product in turn requires only two extra PDE solves using the adjoint
A modified priority list-based MILP method for solving large-scale unit commitment problems
Ke, Xinda; Lu, Ning; Wu, Di; Kintner-Meyer, Michael CW
2015-07-26
This paper studies the typical pattern of unit commitment (UC) results in terms of generator’s cost and capacity. A method is then proposed to combine a modified priority list technique with mixed integer linear programming (MILP) for UC problem. The proposed method consists of two steps. At the first step, a portion of generators are predetermined to be online or offline within a look-ahead period (e.g., a week), based on the demand curve and generator priority order. For the generators whose on/off status is predetermined, at the second step, the corresponding binary variables are removed from the UC MILP problem over the operational planning horizon (e.g., 24 hours). With a number of binary variables removed, the resulted problem can be solved much faster using the off-the-shelf MILP solvers, based on the branch-and-bound algorithm. In the modified priority list method, scale factors are designed to adjust the tradeoff between solution speed and level of optimality. It is found that the proposed method can significantly speed up the UC problem with minor compromise in optimality by selecting appropriate scale factors.
Solving Man-Induced Large-Scale Conservation Problems: The Spanish Imperial Eagle and Power Lines
López-López, Pascual; Ferrer, Miguel; Madero, Agustín; Casado, Eva; McGrady, Michael
2011-01-01
Background Man-induced mortality of birds caused by electrocution with poorly-designed pylons and power lines has been reported to be an important mortality factor that could become a major cause of population decline of one of the world rarest raptors, the Spanish imperial eagle (Aquila adalberti). Consequently it has resulted in an increasing awareness of this problem amongst land managers and the public at large, as well as increased research into the distribution of electrocution events and likely mitigation measures. Methodology/Principal Findings We provide information of how mitigation measures implemented on a regional level under the conservation program of the Spanish imperial eagle have resulted in a positive shift of demographic trends in Spain. A 35 years temporal data set (1974–2009) on mortality of Spanish imperial eagle was recorded, including population censuses, and data on electrocution and non-electrocution of birds. Additional information was obtained from 32 radio-tracked young eagles and specific field surveys. Data were divided into two periods, before and after the approval of a regional regulation of power line design in 1990 which established mandatory rules aimed at minimizing or eliminating the negative impacts of power lines facilities on avian populations. Our results show how population size and the average annual percentage of population change have increased between the two periods, whereas the number of electrocuted birds has been reduced in spite of the continuous growing of the wiring network. Conclusions Our results demonstrate that solving bird electrocution is an affordable problem if political interest is shown and financial investment is made. The combination of an adequate spatial planning with a sustainable development of human infrastructures will contribute positively to the conservation of the Spanish imperial eagle and may underpin population growth and range expansion, with positive side effects on other endangered
Solving large-scale dynamic systems using band Lanczos method in Rockwell NASTRAN on CRAY X-MP
NASA Technical Reports Server (NTRS)
Gupta, V. K.; Zillmer, S. D.; Allison, R. E.
1986-01-01
The improved cost effectiveness using better models, more accurate and faster algorithms and large scale computing offers more representative dynamic analyses. The band Lanczos eigen-solution method was implemented in Rockwell's version of 1984 COSMIC-released NASTRAN finite element structural analysis computer program to effectively solve for structural vibration modes including those of large complex systems exceeding 10,000 degrees of freedom. The Lanczos vectors were re-orthogonalized locally using the Lanczos Method and globally using the modified Gram-Schmidt method for sweeping rigid-body modes and previously generated modes and Lanczos vectors. The truncated band matrix was solved for vibration frequencies and mode shapes using Givens rotations. Numerical examples are included to demonstrate the cost effectiveness and accuracy of the method as implemented in ROCKWELL NASTRAN. The CRAY version is based on RPK's COSMIC/NASTRAN. The band Lanczos method was more reliable and accurate and converged faster than the single vector Lanczos Method. The band Lanczos method was comparable to the subspace iteration method which was a block version of the inverse power method. However, the subspace matrix tended to be fully populated in the case of subspace iteration and not as sparse as a band matrix.
Richard V. Field, Jr.; Emery, John M.; Grigoriu, Mircea Dan
2015-05-19
The stochastic collocation (SC) and stochastic Galerkin (SG) methods are two well-established and successful approaches for solving general stochastic problems. A recently developed method based on stochastic reduced order models (SROMs) can also be used. Herein we provide a comparison of the three methods for some numerical examples; our evaluation only holds for the examples considered in the paper. The purpose of the comparisons is not to criticize the SC or SG methods, which have proven very useful for a broad range of applications, nor is it to provide overall ratings of these methods as compared to the SROM method.more » Furthermore, our objectives are to present the SROM method as an alternative approach to solving stochastic problems and provide information on the computational effort required by the implementation of each method, while simultaneously assessing their performance for a collection of specific problems.« less
Richard V. Field, Jr.; Emery, John M.; Grigoriu, Mircea Dan
2015-05-19
The stochastic collocation (SC) and stochastic Galerkin (SG) methods are two well-established and successful approaches for solving general stochastic problems. A recently developed method based on stochastic reduced order models (SROMs) can also be used. Herein we provide a comparison of the three methods for some numerical examples; our evaluation only holds for the examples considered in the paper. The purpose of the comparisons is not to criticize the SC or SG methods, which have proven very useful for a broad range of applications, nor is it to provide overall ratings of these methods as compared to the SROM method. Furthermore, our objectives are to present the SROM method as an alternative approach to solving stochastic problems and provide information on the computational effort required by the implementation of each method, while simultaneously assessing their performance for a collection of specific problems.
NASA Astrophysics Data System (ADS)
Tan, Zhiqiang; Xia, Junchao; Zhang, Bin W.; Levy, Ronald M.
2016-01-01
The weighted histogram analysis method (WHAM) including its binless extension has been developed independently in several different contexts, and widely used in chemistry, physics, and statistics, for computing free energies and expectations from multiple ensembles. However, this method, while statistically efficient, is computationally costly or even infeasible when a large number, hundreds or more, of distributions are studied. We develop a locally WHAM (local WHAM) from the perspective of simulations of simulations (SOS), using generalized serial tempering (GST) to resample simulated data from multiple ensembles. The local WHAM equations based on one jump attempt per GST cycle can be solved by optimization algorithms orders of magnitude faster than standard implementations of global WHAM, but yield similarly accurate estimates of free energies to global WHAM estimates. Moreover, we propose an adaptive SOS procedure for solving local WHAM equations stochastically when multiple jump attempts are performed per GST cycle. Such a stochastic procedure can lead to more accurate estimates of equilibrium distributions than local WHAM with one jump attempt per cycle. The proposed methods are broadly applicable when the original data to be "WHAMMED" are obtained properly by any sampling algorithm including serial tempering and parallel tempering (replica exchange). To illustrate the methods, we estimated absolute binding free energies and binding energy distributions using the binding energy distribution analysis method from one and two dimensional replica exchange molecular dynamics simulations for the beta-cyclodextrin-heptanoate host-guest system. In addition to the computational advantage of handling large datasets, our two dimensional WHAM analysis also demonstrates that accurate results similar to those from well-converged data can be obtained from simulations for which sampling is limited and not fully equilibrated.
NASA Astrophysics Data System (ADS)
Vorobiev, O.; Ezzedine, S. M.; Antoun, T.; Glenn, L.
2014-12-01
This work describes a methodology used for large scale modeling of wave propagation fromunderground explosions conducted at the Nevada Test Site (NTS) in two different geological settings:fractured granitic rock mass and in alluvium deposition. We show that the discrete nature of rockmasses as well as the spatial variability of the fabric of alluvium is very important to understand groundmotions induced by underground explosions. In order to build a credible conceptual model of thesubsurface we integrated the geological, geomechanical and geophysical characterizations conductedduring recent test at the NTS as well as historical data from the characterization during the undergroundnuclear test conducted at the NTS. Because detailed site characterization is limited, expensive and, insome instances, impossible we have numerically investigated the effects of the characterization gaps onthe overall response of the system. We performed several computational studies to identify the keyimportant geologic features specific to fractured media mainly the joints; and those specific foralluvium porous media mainly the spatial variability of geological alluvium facies characterized bytheir variances and their integral scales. We have also explored common key features to both geologicalenvironments such as saturation and topography and assess which characteristics affect the most theground motion in the near-field and in the far-field. Stochastic representation of these features based onthe field characterizations have been implemented in Geodyn and GeodynL hydrocodes. Both codeswere used to guide site characterization efforts in order to provide the essential data to the modelingcommunity. We validate our computational results by comparing the measured and computed groundmotion at various ranges. This work performed under the auspices of the U.S. Department of Energy by Lawrence LivermoreNational Laboratory under Contract DE-AC52-07NA27344.
NASA Astrophysics Data System (ADS)
Szatmári, Gábor; Barta, Károly; Pásztor, László
2015-04-01
Modelling of large-scale spatial variability of soil properties is a promising subject in soil science, as well as in general environmental research, since the resulted model(s) can be applied to solve various problems. In addition to "purely" map an environmental element, the spatial uncertainty of the map product can deduced, specific areas could be identified and/or delineated (contaminated or endangered regions, plots for fertilization, etc.). Geostatistics, which can be regarded as a subset of statistics specialized in analysis and interpretation of geographically referenced data, offer a huge amount of tools to solve these tasks. Numerous spatial modeling methods have been developed in the past decades based on the regionalized variable theory. One of these techniques is sequential stochastic simulation, which can be conditioned with universal kriging (also referred to as regression kriging). As opposed to universal kriging (UK), sequential simulation conditioned with universal kriging (SSUK) provides not just one but several alternative and equally probable "maps", i.e. realizations. The realizations reproduce the global statistics (e.g. sample histogram, variogram), i.e. they reflect/model the reality in a certain global (and not local!) sense. In this paper we present and test SSUK developed in R-code and its utilizations in a water erosion affected study area. Furthermore, we compare the results from UK and SSUK. For this purpose, two soil variables were selected: soil organic matter (SOM) content and rooting depth (RD). SSUK approach is illustrated with a legacy soil dataset from a study area endangered by water erosion in Central Hungary. Legacy soil data was collected in the end of the 1980s in the framework of the National Land Evaluation Programme. Spatially exhaustive covariates were derived from a digital elevation model and from the land-use-map of the study area. SSUK was built upon a UK prediction system for both variables and 200 realizations
Li, Tong; Gu, YuanTong
2014-04-15
As all-atom molecular dynamics method is limited by its enormous computational cost, various coarse-grained strategies have been developed to extend the length scale of soft matters in the modeling of mechanical behaviors. However, the classical thermostat algorithm in highly coarse-grained molecular dynamics method would underestimate the thermodynamic behaviors of soft matters (e.g. microfilaments in cells), which can weaken the ability of materials to overcome local energy traps in granular modeling. Based on all-atom molecular dynamics modeling of microfilament fragments (G-actin clusters), a new stochastic thermostat algorithm is developed to retain the representation of thermodynamic properties of microfilaments at extra coarse-grained level. The accuracy of this stochastic thermostat algorithm is validated by all-atom MD simulation. This new stochastic thermostat algorithm provides an efficient way to investigate the thermomechanical properties of large-scale soft matters.
NASA Astrophysics Data System (ADS)
Li, Tong; Gu, YuanTong
2014-04-01
As all-atom molecular dynamics method is limited by its enormous computational cost, various coarse-grained strategies have been developed to extend the length scale of soft matters in the modeling of mechanical behaviors. However, the classical thermostat algorithm in highly coarse-grained molecular dynamics method would underestimate the thermodynamic behaviors of soft matters (e.g. microfilaments in cells), which can weaken the ability of materials to overcome local energy traps in granular modeling. Based on all-atom molecular dynamics modeling of microfilament fragments (G-actin clusters), a new stochastic thermostat algorithm is developed to retain the representation of thermodynamic properties of microfilaments at extra coarse-grained level. The accuracy of this stochastic thermostat algorithm is validated by all-atom MD simulation. This new stochastic thermostat algorithm provides an efficient way to investigate the thermomechanical properties of large-scale soft matters.
ERIC Educational Resources Information Center
Mashood, K. K.; Singh, Vijay A.
2013-01-01
Research suggests that problem-solving skills are transferable across domains. This claim, however, needs further empirical substantiation. We suggest correlation studies as a methodology for making preliminary inferences about transfer. The correlation of the physics performance of students with their performance in chemistry and mathematics in…
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 . PMID:27122320
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 .
Thomas, Philipp; Straube, Arthur V; Grima, Ramon
2010-11-21
Chemical reactions inside cells occur in compartment volumes in the range of atto- to femtoliters. Physiological concentrations realized in such small volumes imply low copy numbers of interacting molecules with the consequence of considerable fluctuations in the concentrations. In contrast, rate equation models are based on the implicit assumption of infinitely large numbers of interacting molecules, or equivalently, that reactions occur in infinite volumes at constant macroscopic concentrations. In this article we compute the finite-volume corrections (or equivalently the finite copy number corrections) to the solutions of the rate equations for chemical reaction networks composed of arbitrarily large numbers of enzyme-catalyzed reactions which are confined inside a small subcellular compartment. This is achieved by applying a mesoscopic version of the quasisteady-state assumption to the exact Fokker-Planck equation associated with the Poisson representation of the chemical master equation. The procedure yields impressively simple and compact expressions for the finite-volume corrections. We prove that the predictions of the rate equations will always underestimate the actual steady-state substrate concentrations for an enzyme-reaction network confined in a small volume. In particular we show that the finite-volume corrections increase with decreasing subcellular volume, decreasing Michaelis-Menten constants, and increasing enzyme saturation. The magnitude of the corrections depends sensitively on the topology of the network. The predictions of the theory are shown to be in excellent agreement with stochastic simulations for two types of networks typically associated with protein methylation and metabolism.
NASA Astrophysics Data System (ADS)
Thomas, Philipp; Straube, Arthur V.; Grima, Ramon
2010-11-01
Chemical reactions inside cells occur in compartment volumes in the range of atto- to femtoliters. Physiological concentrations realized in such small volumes imply low copy numbers of interacting molecules with the consequence of considerable fluctuations in the concentrations. In contrast, rate equation models are based on the implicit assumption of infinitely large numbers of interacting molecules, or equivalently, that reactions occur in infinite volumes at constant macroscopic concentrations. In this article we compute the finite-volume corrections (or equivalently the finite copy number corrections) to the solutions of the rate equations for chemical reaction networks composed of arbitrarily large numbers of enzyme-catalyzed reactions which are confined inside a small subcellular compartment. This is achieved by applying a mesoscopic version of the quasisteady-state assumption to the exact Fokker-Planck equation associated with the Poisson representation of the chemical master equation. The procedure yields impressively simple and compact expressions for the finite-volume corrections. We prove that the predictions of the rate equations will always underestimate the actual steady-state substrate concentrations for an enzyme-reaction network confined in a small volume. In particular we show that the finite-volume corrections increase with decreasing subcellular volume, decreasing Michaelis-Menten constants, and increasing enzyme saturation. The magnitude of the corrections depends sensitively on the topology of the network. The predictions of the theory are shown to be in excellent agreement with stochastic simulations for two types of networks typically associated with protein methylation and metabolism.
Robust algorithms for solving stochastic partial differential equations
Werner, M.J.; Drummond, P.D.
1997-04-01
A robust semi-implicit central partial difference algorithm for the numerical solution of coupled stochastic parabolic partial differential equations (PDEs) is described. This can be used for calculating correlation functions of systems of interacting stochastic fields. Such field equations can arise in the description of Hamiltonian and open systems in the physics of nonlinear processes, and may include multiplicative noise sources. The algorithm can be used for studying the properties of nonlinear quantum or classical field theories. The general approach is outlined and applied to a specific example, namely the quantum statistical fluctuations of ultra-short optical pulses in X{sup 2} parametric waveguides. This example uses non-diagonal coherent state representation, and correctly predicts the sub-shot noise level spectral fluctuations observed in homodyne detection measurements. It is expected that the methods used will be applicable for higher-order correlation functions and other physical problems as well. A stochastic differencing technique for reducing sampling errors is also introduced. This involves solving nonlinear stochastic parabolic PDEs in combination with a reference process, which uses the Wigner representation in the example presented here. A computer implementation on MIMD parallel architectures is discussed. 27 refs., 4 figs.
NASA Astrophysics Data System (ADS)
Tanaka, S.; Hasegawa, K.; Okamoto, N.; Umegaki, R.; Wang, S.; Uemura, M.; Okamoto, A.; Koyamada, K.
2016-06-01
We propose a method for the precise 3D see-through imaging, or transparent visualization, of the large-scale and complex point clouds acquired via the laser scanning of 3D cultural heritage objects. Our method is based on a stochastic algorithm and directly uses the 3D points, which are acquired using a laser scanner, as the rendering primitives. This method achieves the correct depth feel without requiring depth sorting of the rendering primitives along the line of sight. Eliminating this need allows us to avoid long computation times when creating natural and precise 3D see-through views of laser-scanned cultural heritage objects. The opacity of each laser-scanned object is also flexibly controllable. For a laser-scanned point cloud consisting of more than 107 or 108 3D points, the pre-processing requires only a few minutes, and the rendering can be executed at interactive frame rates. Our method enables the creation of cumulative 3D see-through images of time-series laser-scanned data. It also offers the possibility of fused visualization for observing a laser-scanned object behind a transparent high-quality photographic image placed in the 3D scene. We demonstrate the effectiveness of our method by applying it to festival floats of high cultural value. These festival floats have complex outer and inner 3D structures and are suitable for see-through imaging.
Heydari, M.H.; Hooshmandasl, M.R.; Cattani, C.; Maalek Ghaini, F.M.
2015-02-15
Because of the nonlinearity, closed-form solutions of many important stochastic functional equations are virtually impossible to obtain. Thus, numerical solutions are a viable alternative. In this paper, a new computational method based on the generalized hat basis functions together with their stochastic operational matrix of Itô-integration is proposed for solving nonlinear stochastic Itô integral equations in large intervals. In the proposed method, a new technique for computing nonlinear terms in such problems is presented. The main advantage of the proposed method is that it transforms problems under consideration into nonlinear systems of algebraic equations which can be simply solved. Error analysis of the proposed method is investigated and also the efficiency of this method is shown on some concrete examples. The obtained results reveal that the proposed method is very accurate and efficient. As two useful applications, the proposed method is applied to obtain approximate solutions of the stochastic population growth models and stochastic pendulum problem.
Solving the Langevin equation with stochastic algebraically correlated noise
NASA Astrophysics Data System (ADS)
Płoszajczak, M.; Srokowski, T.
1997-05-01
The long time tail in the velocity and force autocorrelation function has been found recently in molecular dynamics simulations of peripheral collisions of ions. Simulation of those slowly decaying correlations in the stochastic transport theory requires the development of new methods of generating stochastic force of arbitrarily long correlation times. In this paper we propose a Markovian process, the multidimensional kangaroo process, which permits the description of various algebraically correlated stochastic processes.
A wavelet-based computational method for solving stochastic Itô–Volterra integral equations
Mohammadi, Fakhrodin
2015-10-01
This paper presents a computational method based on the Chebyshev wavelets for solving stochastic Itô–Volterra integral equations. First, a stochastic operational matrix for the Chebyshev wavelets is presented and a general procedure for forming this matrix is given. Then, the Chebyshev wavelets basis along with this stochastic operational matrix are applied for solving stochastic Itô–Volterra integral equations. Convergence and error analysis of the Chebyshev wavelets basis are investigated. To reveal the accuracy and efficiency of the proposed method some numerical examples are included.
NASA Astrophysics Data System (ADS)
Kozma, Robert; Hu, Sanqing
2015-12-01
For millennia, causality served as a powerful guiding principle to our understanding of natural processes, including the functioning of our body, mind, and brain. The target paper presents an impressive vista of the field of causality in brain networks, starting from philosophical issues, expanding on neuroscience effects, and addressing broad engineering and societal aspects as well. The authors conclude that the concept of stochastic causality is more suited to characterize the experimentally observed complex dynamical processes in large-scale brain networks, rather than the more traditional view of deterministic causality. We strongly support this conclusion and provide two additional examples that may enhance and complement this review: (i) a generalization of the Wiener-Granger Causality (WGC) to fit better the complexity of brain networks; (ii) employment of criticality as a key concept highly relevant to interpreting causality and non-locality in large-scale brain networks.
NASA Technical Reports Server (NTRS)
Doolin, B. F.
1975-01-01
Classes of large scale dynamic systems were discussed in the context of modern control theory. Specific examples discussed were in the technical fields of aeronautics, water resources and electric power.
PySP : modeling and solving stochastic mixed-integer programs in Python.
Woodruff, David L.; Watson, Jean-Paul
2010-08-01
Although stochastic programming is a powerful tool for modeling decision-making under uncertainty, various impediments have historically prevented its widespread use. One key factor involves the ability of non-specialists to easily express stochastic programming problems as extensions of deterministic models, which are often formulated first. A second key factor relates to the difficulty of solving stochastic programming models, particularly the general mixed-integer, multi-stage case. Intricate, configurable, and parallel decomposition strategies are frequently required to achieve tractable run-times. We simultaneously address both of these factors in our PySP software package, which is part of the COIN-OR Coopr open-source Python project for optimization. To formulate a stochastic program in PySP, the user specifies both the deterministic base model and the scenario tree with associated uncertain parameters in the Pyomo open-source algebraic modeling language. Given these two models, PySP provides two paths for solution of the corresponding stochastic program. The first alternative involves writing the extensive form and invoking a standard deterministic (mixed-integer) solver. For more complex stochastic programs, we provide an implementation of Rockafellar and Wets Progressive Hedging algorithm. Our particular focus is on the use of Progressive Hedging as an effective heuristic for approximating general multi-stage, mixed-integer stochastic programs. By leveraging the combination of a high-level programming language (Python) and the embedding of the base deterministic model in that language (Pyomo), we are able to provide completely generic and highly configurable solver implementations. PySP has been used by a number of research groups, including our own, to rapidly prototype and solve difficult stochastic programming problems.
NASA Astrophysics Data System (ADS)
Oladyshkin, S.; Schroeder, P.; Class, H.; Nowak, W.
2013-12-01
Predicting underground carbon dioxide (CO2) storage represents a challenging problem in a complex dynamic system. Due to lacking information about reservoir parameters, quantification of uncertainties may become the dominant question in risk assessment. Calibration on past observed data from pilot-scale test injection can improve the predictive power of the involved geological, flow, and transport models. The current work performs history matching to pressure time series from a pilot storage site operated in Europe, maintained during an injection period. Simulation of compressible two-phase flow and transport (CO2/brine) in the considered site is computationally very demanding, requiring about 12 days of CPU time for an individual model run. For that reason, brute-force approaches for calibration are not feasible. In the current work, we explore an advanced framework for history matching based on the arbitrary polynomial chaos expansion (aPC) and strict Bayesian principles. The aPC [1] offers a drastic but accurate stochastic model reduction. Unlike many previous chaos expansions, it can handle arbitrary probability distribution shapes of uncertain parameters, and can therefore handle directly the statistical information appearing during the matching procedure. We capture the dependence of model output on these multipliers with the expansion-based reduced model. In our study we keep the spatial heterogeneity suggested by geophysical methods, but consider uncertainty in the magnitude of permeability trough zone-wise permeability multipliers. Next combined the aPC with Bootstrap filtering (a brute-force but fully accurate Bayesian updating mechanism) in order to perform the matching. In comparison to (Ensemble) Kalman Filters, our method accounts for higher-order statistical moments and for the non-linearity of both the forward model and the inversion, and thus allows a rigorous quantification of calibrated model uncertainty. The usually high computational costs of
Stochastic pattern transitions in large scale swarms
NASA Astrophysics Data System (ADS)
Schwartz, Ira; Lindley, Brandon; Mier-Y-Teran, Luis
2013-03-01
We study the effects of time dependent noise and discrete, randomly distributed time delays on the dynamics of a large coupled system of self-propelling particles. Bifurcation analysis on a mean field approximation of the system reveals that the system possesses patterns with certain universal characteristics that depend on distinguished moments of the time delay distribution. We show both theoretically and numerically that although bifurcations of simple patterns, such as translations, change stability only as a function of the first moment of the time delay distribution, more complex bifurcating patterns depend on all of the moments of the delay distribution. In addition, we show that for sufficiently large values of the coupling strength and/or the mean time delay, there is a noise intensity threshold, dependent on the delay distribution width, that forces a transition of the swarm from a misaligned state into an aligned state. We show that this alignment transition exhibits hysteresis when the noise intensity is taken to be time dependent. Research supported by the Office of Naval Research
Large scale tracking algorithms.
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.
NASA Technical Reports Server (NTRS)
Vanderplaats, Garrett; Townsend, James C. (Technical Monitor)
2002-01-01
The purpose of this research under the NASA Small Business Innovative Research program was to develop algorithms and associated software to solve very large nonlinear, constrained optimization tasks. Key issues included efficiency, reliability, memory, and gradient calculation requirements. This report describes the general optimization problem, ten candidate methods, and detailed evaluations of four candidates. The algorithm chosen for final development is a modern recreation of a 1960s external penalty function method that uses very limited computer memory and computational time. Although of lower efficiency, the new method can solve problems orders of magnitude larger than current methods. The resulting BIGDOT software has been demonstrated on problems with 50,000 variables and about 50,000 active constraints. For unconstrained optimization, it has solved a problem in excess of 135,000 variables. The method includes a technique for solving discrete variable problems that finds a "good" design, although a theoretical optimum cannot be guaranteed. It is very scalable in that the number of function and gradient evaluations does not change significantly with increased problem size. Test cases are provided to demonstrate the efficiency and reliability of the methods and software.
Digital program for solving the linear stochastic optimal control and estimation problem
NASA Technical Reports Server (NTRS)
Geyser, L. C.; Lehtinen, B.
1975-01-01
A computer program is described which solves the linear stochastic optimal control and estimation (LSOCE) problem by using a time-domain formulation. The LSOCE problem is defined as that of designing controls for a linear time-invariant system which is disturbed by white noise in such a way as to minimize a performance index which is quadratic in state and control variables. The LSOCE problem and solution are outlined; brief descriptions are given of the solution algorithms, and complete descriptions of each subroutine, including usage information and digital listings, are provided. A test case is included, as well as information on the IBM 7090-7094 DCS time and storage requirements.
NASA Astrophysics Data System (ADS)
Tahvili, Sahar; Österberg, Jonas; Silvestrov, Sergei; Biteus, Jonas
2014-12-01
One of the most important factors in the operations of many cooperations today is to maximize profit and one important tool to that effect is the optimization of maintenance activities. Maintenance activities is at the largest level divided into two major areas, corrective maintenance (CM) and preventive maintenance (PM). When optimizing maintenance activities, by a maintenance plan or policy, we seek to find the best activities to perform at each point in time, be it PM or CM. We explore the use of stochastic simulation, genetic algorithms and other tools for solving complex maintenance planning optimization problems in terms of a suggested framework model based on discrete event simulation.
Tahvili, Sahar; Österberg, Jonas; Silvestrov, Sergei; Biteus, Jonas
2014-12-10
One of the most important factors in the operations of many cooperations today is to maximize profit and one important tool to that effect is the optimization of maintenance activities. Maintenance activities is at the largest level divided into two major areas, corrective maintenance (CM) and preventive maintenance (PM). When optimizing maintenance activities, by a maintenance plan or policy, we seek to find the best activities to perform at each point in time, be it PM or CM. We explore the use of stochastic simulation, genetic algorithms and other tools for solving complex maintenance planning optimization problems in terms of a suggested framework model based on discrete event simulation.
Using genetic algorithm to solve a new multi-period stochastic optimization model
NASA Astrophysics Data System (ADS)
Zhang, Xin-Li; Zhang, Ke-Cun
2009-09-01
This paper presents a new asset allocation model based on the CVaR risk measure and transaction costs. Institutional investors manage their strategic asset mix over time to achieve favorable returns subject to various uncertainties, policy and legal constraints, and other requirements. One may use a multi-period portfolio optimization model in order to determine an optimal asset mix. Recently, an alternative stochastic programming model with simulated paths was proposed by Hibiki [N. Hibiki, A hybrid simulation/tree multi-period stochastic programming model for optimal asset allocation, in: H. Takahashi, (Ed.) The Japanese Association of Financial Econometrics and Engineering, JAFFE Journal (2001) 89-119 (in Japanese); N. Hibiki A hybrid simulation/tree stochastic optimization model for dynamic asset allocation, in: B. Scherer (Ed.), Asset and Liability Management Tools: A Handbook for Best Practice, Risk Books, 2003, pp. 269-294], which was called a hybrid model. However, the transaction costs weren't considered in that paper. In this paper, we improve Hibiki's model in the following aspects: (1) The risk measure CVaR is introduced to control the wealth loss risk while maximizing the expected utility; (2) Typical market imperfections such as short sale constraints, proportional transaction costs are considered simultaneously. (3) Applying a genetic algorithm to solve the resulting model is discussed in detail. Numerical results show the suitability and feasibility of our methodology.
Large Scale Shape Optimization for Accelerator Cavities
Akcelik, Volkan; Lee, Lie-Quan; Li, Zenghai; Ng, Cho; Xiao, Li-Ling; Ko, Kwok; /SLAC
2011-12-06
We present a shape optimization method for designing accelerator cavities with large scale computations. The objective is to find the best accelerator cavity shape with the desired spectral response, such as with the specified frequencies of resonant modes, field profiles, and external Q values. The forward problem is the large scale Maxwell equation in the frequency domain. The design parameters are the CAD parameters defining the cavity shape. We develop scalable algorithms with a discrete adjoint approach and use the quasi-Newton method to solve the nonlinear optimization problem. Two realistic accelerator cavity design examples are presented.
Heydari, M.H.; Hooshmandasl, M.R.; Maalek Ghaini, F.M.; Cattani, C.
2014-08-01
In this paper, a new computational method based on the generalized hat basis functions is proposed for solving stochastic Itô–Volterra integral equations. In this way, a new stochastic operational matrix for generalized hat functions on the finite interval [0,T] is obtained. By using these basis functions and their stochastic operational matrix, such problems can be transformed into linear lower triangular systems of algebraic equations which can be directly solved by forward substitution. Also, the rate of convergence of the proposed method is considered and it has been shown that it is O(1/(n{sup 2}) ). Further, in order to show the accuracy and reliability of the proposed method, the new approach is compared with the block pulse functions method by some examples. The obtained results reveal that the proposed method is more accurate and efficient in comparison with the block pule functions method.
Fractals and cosmological large-scale structure
NASA Technical Reports Server (NTRS)
Luo, Xiaochun; Schramm, David N.
1992-01-01
Observations of galaxy-galaxy and cluster-cluster correlations as well as other large-scale structure can be fit with a 'limited' fractal with dimension D of about 1.2. This is not a 'pure' fractal out to the horizon: the distribution shifts from power law to random behavior at some large scale. If the observed patterns and structures are formed through an aggregation growth process, the fractal dimension D can serve as an interesting constraint on the properties of the stochastic motion responsible for limiting the fractal structure. In particular, it is found that the observed fractal should have grown from two-dimensional sheetlike objects such as pancakes, domain walls, or string wakes. This result is generic and does not depend on the details of the growth process.
A numerical method for solving a stochastic inverse problem for parameters.
Butler, T; Estep, D
2013-02-01
We review recent work (Briedt et al., 2011., 2012) on a new approach to the formulation and solution of the stochastic inverse parameter determination problem, i.e. determine the random variation of input parameters to a map that matches specified random variation in the output of the map, and then apply the various aspects of this method to the interesting Brusselator model. In this approach, the problem is formulated as an inverse problem for an integral equation using the Law of Total Probability. The solution method employs two steps: (1) we construct a systematic method for approximating set-valued inverse solutions and (2) we construct a computational approach to compute a measure-theoretic approximation of the probability measure on the input space imparted by the approximate set-valued inverse that solves the inverse problem. In addition to convergence analysis, we carry out an a posteriori error analysis on the computed probability distribution that takes into account all sources of stochastic and deterministic error. PMID:24347806
A numerical method for solving a stochastic inverse problem for parameters
Butler, T.; Estep, D.
2013-01-01
We review recent work (Briedt et al., 2011., 2012) on a new approach to the formulation and solution of the stochastic inverse parameter determination problem, i.e. determine the random variation of input parameters to a map that matches specified random variation in the output of the map, and then apply the various aspects of this method to the interesting Brusselator model. In this approach, the problem is formulated as an inverse problem for an integral equation using the Law of Total Probability. The solution method employs two steps: (1) we construct a systematic method for approximating set-valued inverse solutions and (2) we construct a computational approach to compute a measure-theoretic approximation of the probability measure on the input space imparted by the approximate set-valued inverse that solves the inverse problem. In addition to convergence analysis, we carry out an a posteriori error analysis on the computed probability distribution that takes into account all sources of stochastic and deterministic error. PMID:24347806
Very Large Scale Integration (VLSI).
ERIC Educational Resources Information Center
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…
Galaxy clustering on large scales.
Efstathiou, G
1993-06-01
I describe some recent observations of large-scale structure in the galaxy distribution. The best constraints come from two-dimensional galaxy surveys and studies of angular correlation functions. Results from galaxy redshift surveys are much less precise but are consistent with the angular correlations, provided the distortions in mapping between real-space and redshift-space are relatively weak. The galaxy two-point correlation function, rich-cluster two-point correlation function, and galaxy-cluster cross-correlation function are all well described on large scales ( greater, similar 20h-1 Mpc, where the Hubble constant, H0 = 100h km.s-1.Mpc; 1 pc = 3.09 x 10(16) m) by the power spectrum of an initially scale-invariant, adiabatic, cold-dark-matter Universe with Gamma = Omegah approximately 0.2. I discuss how this fits in with the Cosmic Background Explorer (COBE) satellite detection of large-scale anisotropies in the microwave background radiation and other measures of large-scale structure in the Universe.
Engineering management of large scale systems
NASA Technical Reports Server (NTRS)
Sanders, Serita; Gill, Tepper L.; Paul, Arthur S.
1989-01-01
The organization of high technology and engineering problem solving, has given rise to an emerging concept. Reasoning principles for integrating traditional engineering problem solving with system theory, management sciences, behavioral decision theory, and planning and design approaches can be incorporated into a methodological approach to solving problems with a long range perspective. Long range planning has a great potential to improve productivity by using a systematic and organized approach. Thus, efficiency and cost effectiveness are the driving forces in promoting the organization of engineering problems. Aspects of systems engineering that provide an understanding of management of large scale systems are broadly covered here. Due to the focus and application of research, other significant factors (e.g., human behavior, decision making, etc.) are not emphasized but are considered.
Large-Scale Visual Data Analysis
NASA Astrophysics Data System (ADS)
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.
A study of MLFMA for large-scale scattering problems
NASA Astrophysics Data System (ADS)
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.
Survey of decentralized control methods. [for large scale dynamic systems
NASA Technical Reports Server (NTRS)
Athans, M.
1975-01-01
An overview is presented of the types of problems that are being considered by control theorists in the area of dynamic large scale systems with emphasis on decentralized control strategies. Approaches that deal directly with decentralized decision making for large scale systems are discussed. It is shown that future advances in decentralized system theory are intimately connected with advances in the stochastic control problem with nonclassical information pattern. The basic assumptions and mathematical tools associated with the latter are summarized, and recommendations concerning future research are presented.
Palmer, Tim N; O'Shea, Michael
2015-01-01
How is the brain configured for creativity? What is the computational substrate for 'eureka' moments of insight? Here we argue that creative thinking arises ultimately from a synergy between low-energy stochastic and energy-intensive deterministic processing, and is a by-product of a nervous system whose signal-processing capability per unit of available energy has become highly energy optimised. We suggest that the stochastic component has its origin in thermal (ultimately quantum decoherent) noise affecting the activity of neurons. Without this component, deterministic computational models of the brain are incomplete. PMID:26528173
Palmer, Tim N.; O’Shea, Michael
2015-01-01
How is the brain configured for creativity? What is the computational substrate for ‘eureka’ moments of insight? Here we argue that creative thinking arises ultimately from a synergy between low-energy stochastic and energy-intensive deterministic processing, and is a by-product of a nervous system whose signal-processing capability per unit of available energy has become highly energy optimised. We suggest that the stochastic component has its origin in thermal (ultimately quantum decoherent) noise affecting the activity of neurons. Without this component, deterministic computational models of the brain are incomplete. PMID:26528173
NASA Astrophysics Data System (ADS)
Macian-Sorribes, Hector; Pulido-Velazquez, Manuel; Tilmant, Amaury
2015-04-01
Stochastic programming methods are better suited to deal with the inherent uncertainty of inflow time series in water resource management. However, one of the most important hurdles in their use in practical implementations is the lack of generalized Decision Support System (DSS) shells, usually based on a deterministic approach. The purpose of this contribution is to present a general-purpose DSS shell, named Explicit Stochastic Programming Advanced Tool (ESPAT), able to build and solve stochastic programming problems for most water resource systems. It implements a hydro-economic approach, optimizing the total system benefits as the sum of the benefits obtained by each user. It has been coded using GAMS, and implements a Microsoft Excel interface with a GAMS-Excel link that allows the user to introduce the required data and recover the results. Therefore, no GAMS skills are required to run the program. The tool is divided into four modules according to its capabilities: 1) the ESPATR module, which performs stochastic optimization procedures in surface water systems using a Stochastic Dual Dynamic Programming (SDDP) approach; 2) the ESPAT_RA module, which optimizes coupled surface-groundwater systems using a modified SDDP approach; 3) the ESPAT_SDP module, capable of performing stochastic optimization procedures in small-size surface systems using a standard SDP approach; and 4) the ESPAT_DET module, which implements a deterministic programming procedure using non-linear programming, able to solve deterministic optimization problems in complex surface-groundwater river basins. The case study of the Mijares river basin (Spain) is used to illustrate the method. It consists in two reservoirs in series, one aquifer and four agricultural demand sites currently managed using historical (XIV century) rights, which give priority to the most traditional irrigation district over the XX century agricultural developments. Its size makes it possible to use either the SDP or
Large scale cluster computing workshop
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
NASA Technical Reports Server (NTRS)
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.
Backscatter in Large-Scale Flows
NASA Astrophysics Data System (ADS)
Nadiga, Balu
2009-11-01
Downgradient mixing of potential-voriticity and its variants are commonly employed to model the effects of unresolved geostrophic turbulence on resolved scales. This is motivated by the (inviscid and unforced) particle-wise conservation of potential-vorticity and the mean forward or down-scale cascade of potential enstrophy in geostrophic turubulence. By examining the statistical distribution of the transfer of potential enstrophy from mean or filtered motions to eddy or sub-filter motions, we find that the mean forward cascade results from the forward-scatter being only slightly greater than the backscatter. Downgradient mixing ideas, do not recognize such equitable mean-eddy or large scale-small scale interactions and consequently model only the mean effect of forward cascade; the importance of capturing the effects of backscatter---the forcing of resolved scales by unresolved scales---are only beginning to be recognized. While recent attempts to model the effects of backscatter on resolved scales have taken a stochastic approach, our analysis suggests that these effects are amenable to being modeled deterministically.
Large Scale Nanolaminate Deformable Mirror
Papavasiliou, A; Olivier, S; Barbee, T; Miles, R; Chang, K
2005-11-30
This work concerns the development of a technology that uses Nanolaminate foils to form light-weight, deformable mirrors that are scalable over a wide range of mirror sizes. While MEMS-based deformable mirrors and spatial light modulators have considerably reduced the cost and increased the capabilities of adaptive optic systems, there has not been a way to utilize the advantages of lithography and batch-fabrication to produce large-scale deformable mirrors. This technology is made scalable by using fabrication techniques and lithography that are not limited to the sizes of conventional MEMS devices. Like many MEMS devices, these mirrors use parallel plate electrostatic actuators. This technology replicates that functionality by suspending a horizontal piece of nanolaminate foil over an electrode by electroplated nickel posts. This actuator is attached, with another post, to another nanolaminate foil that acts as the mirror surface. Most MEMS devices are produced with integrated circuit lithography techniques that are capable of very small line widths, but are not scalable to large sizes. This technology is very tolerant of lithography errors and can use coarser, printed circuit board lithography techniques that can be scaled to very large sizes. These mirrors use small, lithographically defined actuators and thin nanolaminate foils allowing them to produce deformations over a large area while minimizing weight. This paper will describe a staged program to develop this technology. First-principles models were developed to determine design parameters. Three stages of fabrication will be described starting with a 3 x 3 device using conventional metal foils and epoxy to a 10-across all-metal device with nanolaminate mirror surfaces.
Large-Scale Information Systems
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.
An Analysis of Two Schemes to Numerically Solve the Stochastic Collection Growth Equation.
NASA Astrophysics Data System (ADS)
de Almeida, Fausto Carlos; Dennett, Roger D.
1980-12-01
Two schemes for the numerical solution of the stochastic collection growth equation for cloud drops are compared. Their numerical approaches are different. One (the Berry/Reinhardt method) emphasizes accuracy; the other (the Bleck method) emphasizes speed. Our analysis shows that for applications where the number of solutions (time steps) does not exceed 104 the accuracy-oriented scheme is faster. For larger, repetitive applications, such as a comprehensive cloud model, an objective analysis can be made on the merits of exchanging accuracy for computational time.
Solving the problem of imaging resolution: stochastic multi-scale image fusion
NASA Astrophysics Data System (ADS)
Karsanina, Marina; Mallants, Dirk; Gilyazetdinova, Dina; Gerke, Kiril
2016-04-01
Structural features of porous materials define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, gas exchange between biologically active soil root zone and atmosphere, etc.) and solute transport. To characterize soil and rock microstructure X-ray microtomography is extremely useful. However, as any other imaging technique, this one also has a significant drawback - a trade-off between sample size and resolution. The latter is a significant problem for multi-scale complex structures, especially such as soils and carbonates. Other imaging techniques, for example, SEM/FIB-SEM or X-ray macrotomography can be helpful in obtaining higher resolution or wider field of view. The ultimate goal is to create a single dataset containing information from all scales or to characterize such multi-scale structure. In this contribution we demonstrate a general solution for merging multiscale categorical spatial data into a single dataset using stochastic reconstructions with rescaled correlation functions. The versatility of the method is demonstrated by merging three images representing macro, micro and nanoscale spatial information on porous media structure. Images obtained by X-ray microtomography and scanning electron microscopy were fused into a single image with predefined resolution. The methodology is sufficiently generic for implementation of other stochastic reconstruction techniques, any number of scales, any number of material phases, and any number of images for a given scale. The methodology can be further used to assess effective properties of fused porous media images or to compress voluminous spatial datasets for efficient data storage. Potential practical applications of this method are abundant in soil science, hydrology and petroleum engineering, as well as other geosciences. This work was partially supported by RSF grant 14-17-00658 (X-ray microtomography study of shale
NASA Astrophysics Data System (ADS)
Chen, Xianshun; Feng, Liang; Ong, Yew Soon
2012-07-01
In this article, we proposed a self-adaptive memeplex robust search (SAMRS) for finding robust and reliable solutions that are less sensitive to stochastic behaviours of customer demands and have low probability of route failures, respectively, in vehicle routing problem with stochastic demands (VRPSD). In particular, the contribution of this article is three-fold. First, the proposed SAMRS employs the robust solution search scheme (RS 3) as an approximation of the computationally intensive Monte Carlo simulation, thus reducing the computation cost of fitness evaluation in VRPSD, while directing the search towards robust and reliable solutions. Furthermore, a self-adaptive individual learning based on the conceptual modelling of memeplex is introduced in the SAMRS. Finally, SAMRS incorporates a gene-meme co-evolution model with genetic and memetic representation to effectively manage the search for solutions in VRPSD. Extensive experimental results are then presented for benchmark problems to demonstrate that the proposed SAMRS serves as an efficable means of generating high-quality robust and reliable solutions in VRPSD.
On the decentralized control of large-scale systems. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Chong, C.
1973-01-01
The decentralized control of stochastic large scale systems was considered. Particular emphasis was given to control strategies which utilize decentralized information and can be computed in a decentralized manner. The deterministic constrained optimization problem is generalized to the stochastic case when each decision variable depends on different information and the constraint is only required to be satisfied on the average. For problems with a particular structure, a hierarchical decomposition is obtained. For the stochastic control of dynamic systems with different information sets, a new kind of optimality is proposed which exploits the coupled nature of the dynamic system. The subsystems are assumed to be uncoupled and then certain constraints are required to be satisfied, either in a off-line or on-line fashion. For off-line coordination, a hierarchical approach of solving the problem is obtained. The lower level problems are all uncoupled. For on-line coordination, distinction is made between open loop feedback optimal coordination and closed loop optimal coordination.
Turbulent large-scale structure effects on wake meandering
NASA Astrophysics Data System (ADS)
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
Reinforcement Learning in Large Scale Systems Using State Generalization and Multi-Agent Techniques
NASA Astrophysics Data System (ADS)
Kimura, Hajime; Aoki, Kei; Kobayashi, Shigenobu
This paper introduces several problems in reinforcement learning of industrial applications, and shows some techniques to overcome it. Reinforcement learning is known as on-line learning of an input-output mapping through a process of trial and error interactions with its uncertain environment, however, the trial and error will cause fatal damages in real applications. We introduce a planning method, based on reinforcement learning in the simulator. It can be seen as a stochastic approximation of dynamic programming in Markov decision processes. But in large problems, simple grid-tiling to quantize state space for tabular Q-learning is still infeasible. We introduce a generalization technique to approximate value functions in continuous state space, and a multiagent architecture to solve large scale problems. The efficiency of these techniques are shown through experiments in a sewage water-flow control system.
Chou, Sheng-Kai; Jiau, Ming-Kai; Huang, Shih-Chia
2016-08-01
The growing ubiquity of vehicles has led to increased concerns about environmental issues. These concerns can be mitigated by implementing an effective carpool service. In an intelligent carpool system, an automated service process assists carpool participants in determining routes and matches. It is a discrete optimization problem that involves a system-wide condition as well as participants' expectations. In this paper, we solve the carpool service problem (CSP) to provide satisfactory ride matches. To this end, we developed a particle swarm carpool algorithm based on stochastic set-based particle swarm optimization (PSO). Our method introduces stochastic coding to augment traditional particles, and uses three terminologies to represent a particle: 1) particle position; 2) particle view; and 3) particle velocity. In this way, the set-based PSO (S-PSO) can be realized by local exploration. In the simulation and experiments, two kind of discrete PSOs-S-PSO and binary PSO (BPSO)-and a genetic algorithm (GA) are compared and examined using tested benchmarks that simulate a real-world metropolis. We observed that the S-PSO outperformed the BPSO and the GA thoroughly. Moreover, our method yielded the best result in a statistical test and successfully obtained numerical results for meeting the optimization objectives of the CSP.
Sidje, R B; Vo, H D
2015-11-01
The mathematical framework of the chemical master equation (CME) uses a Markov chain to model the biochemical reactions that are taking place within a biological cell. Computing the transient probability distribution of this Markov chain allows us to track the composition of molecules inside the cell over time, with important practical applications in a number of areas such as molecular biology or medicine. However the CME is typically difficult to solve, since the state space involved can be very large or even countably infinite. We present a novel way of using the stochastic simulation algorithm (SSA) to reduce the size of the finite state projection (FSP) method. Numerical experiments that demonstrate the effectiveness of the reduction are included.
Automating large-scale reactor systems
Kisner, R.A.
1985-01-01
This paper conveys a philosophy for developing automated large-scale control systems that behave in an integrated, intelligent, flexible manner. Methods for operating large-scale systems under varying degrees of equipment degradation are discussed, and a design approach that separates the effort into phases is suggested. 5 refs., 1 fig.
Sensitivity technologies for large scale simulation.
Collis, Samuel Scott; Bartlett, Roscoe Ainsworth; Smith, Thomas Michael; Heinkenschloss, Matthias; Wilcox, Lucas C.; Hill, Judith C.; Ghattas, Omar; Berggren, Martin Olof; Akcelik, Volkan; 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
Is the universe homogeneous on large scale?
NASA Astrophysics Data System (ADS)
Zhu, Xingfen; Chu, Yaoquan
Wether the distribution of matter in the universe is homogeneous or fractal on large scale is vastly debated in observational cosmology recently. Pietronero and his co-workers have strongly advocated that the fractal behaviour in the galaxy distribution extends to the largest scale observed (≍1000h-1Mpc) with the fractal dimension D ≍ 2. Most cosmologists who hold the standard model, however, insist that the universe be homogeneous on large scale. The answer of whether the universe is homogeneous or not on large scale should wait for the new results of next generation galaxy redshift surveys.
Relic vector field and CMB large scale anomalies
Chen, Xingang; Wang, Yi E-mail: yw366@cam.ac.uk
2014-10-01
We study the most general effects of relic vector fields on the inflationary background and density perturbations. Such effects are observable if the number of inflationary e-folds is close to the minimum requirement to solve the horizon problem. We show that this can potentially explain two CMB large scale anomalies: the quadrupole-octopole alignment and the quadrupole power suppression. We discuss its effect on the parity anomaly. We also provide analytical template for more detailed data comparison.
Large-scale regions of antimatter
Grobov, A. V. Rubin, S. G.
2015-07-15
Amodified mechanism of the formation of large-scale antimatter regions is proposed. Antimatter appears owing to fluctuations of a complex scalar field that carries a baryon charge in the inflation era.
Webster, Clayton G; Tran, Hoang A; Trenchea, Catalin S
2013-01-01
n this paper we show how stochastic collocation method (SCM) could fail to con- verge for nonlinear differential equations with random coefficients. First, we consider Navier-Stokes equation with uncertain viscosity and derive error estimates for stochastic collocation discretization. Our analysis gives some indicators on how the nonlinearity negatively affects the accuracy of the method. The stochastic collocation method is then applied to noisy Lorenz system. Simulation re- sults demonstrate that the solution of a nonlinear equation could be highly irregular on the random data and in such cases, stochastic collocation method cannot capture the correct solution.
Large-Scale Optimization for Bayesian Inference in Complex Systems
Willcox, Karen; Marzouk, Youssef
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 achieve their
Robust large-scale parallel nonlinear solvers for simulations.
Bader, Brett William; Pawlowski, Roger Patrick; Kolda, Tamara Gibson
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 existing linear solver, which makes it simple to write
Large-scale motions in the universe
Rubin, V.C.; Coyne, G.V.
1988-01-01
The present conference on the large-scale motions of the universe discusses topics on the problems of two-dimensional and three-dimensional structures, large-scale velocity fields, the motion of the local group, small-scale microwave fluctuations, ab initio and phenomenological theories, and properties of galaxies at high and low Z. Attention is given to the Pisces-Perseus supercluster, large-scale structure and motion traced by galaxy clusters, distances to galaxies in the field, the origin of the local flow of galaxies, the peculiar velocity field predicted by the distribution of IRAS galaxies, the effects of reionization on microwave background anisotropies, the theoretical implications of cosmological dipoles, and n-body simulations of universe dominated by cold dark matter.
Survey on large scale system control methods
NASA Technical Reports Server (NTRS)
Mercadal, Mathieu
1987-01-01
The problem inherent to large scale systems such as power network, communication network and economic or ecological systems were studied. The increase in size and flexibility of future spacecraft has put those dynamical systems into the category of large scale systems, and tools specific to the class of large systems are being sought to design control systems that can guarantee more stability and better performance. Among several survey papers, reference was found to a thorough investigation on decentralized control methods. Especially helpful was the classification made of the different existing approaches to deal with large scale systems. A very similar classification is used, even though the papers surveyed are somehow different from the ones reviewed in other papers. Special attention is brought to the applicability of the existing methods to controlling large mechanical systems like large space structures. Some recent developments are added to this survey.
Large-scale nanophotonic phased array.
Sun, Jie; Timurdogan, Erman; Yaacobi, Ami; Hosseini, Ehsan Shah; Watts, Michael R
2013-01-10
Electromagnetic phased arrays at radio frequencies are well known and have enabled applications ranging from communications to radar, broadcasting and astronomy. The ability to generate arbitrary radiation patterns with large-scale phased arrays has long been pursued. Although it is extremely expensive and cumbersome to deploy large-scale radiofrequency phased arrays, optical phased arrays have a unique advantage in that the much shorter optical wavelength holds promise for large-scale integration. However, the short optical wavelength also imposes stringent requirements on fabrication. As a consequence, although optical phased arrays have been studied with various platforms and recently with chip-scale nanophotonics, all of the demonstrations so far are restricted to one-dimensional or small-scale two-dimensional arrays. Here we report the demonstration of a large-scale two-dimensional nanophotonic phased array (NPA), in which 64 × 64 (4,096) optical nanoantennas are densely integrated on a silicon chip within a footprint of 576 μm × 576 μm with all of the nanoantennas precisely balanced in power and aligned in phase to generate a designed, sophisticated radiation pattern in the far field. We also show that active phase tunability can be realized in the proposed NPA by demonstrating dynamic beam steering and shaping with an 8 × 8 array. This work demonstrates that a robust design, together with state-of-the-art complementary metal-oxide-semiconductor technology, allows large-scale NPAs to be implemented on compact and inexpensive nanophotonic chips. In turn, this enables arbitrary radiation pattern generation using NPAs and therefore extends the functionalities of phased arrays beyond conventional beam focusing and steering, opening up possibilities for large-scale deployment in applications such as communication, laser detection and ranging, three-dimensional holography and biomedical sciences, to name just a few.
Sensitivity analysis for large-scale problems
NASA Technical Reports Server (NTRS)
Noor, Ahmed K.; Whitworth, Sandra L.
1987-01-01
The development of efficient techniques for calculating sensitivity derivatives is studied. The objective is to present a computational procedure for calculating sensitivity derivatives as part of performing structural reanalysis for large-scale problems. The scope is limited to framed type structures. Both linear static analysis and free-vibration eigenvalue problems are considered.
A Large Scale Computer Terminal Output Controller.
ERIC Educational Resources Information Center
Tucker, Paul Thomas
This paper describes the design and implementation of a large scale computer terminal output controller which supervises the transfer of information from a Control Data 6400 Computer to a PLATO IV data network. It discusses the cost considerations leading to the selection of educational television channels rather than telephone lines for…
Management of large-scale technology
NASA Technical Reports Server (NTRS)
Levine, A.
1985-01-01
Two major themes are addressed in this assessment of the management of large-scale NASA programs: (1) how a high technology agency was a decade marked by a rapid expansion of funds and manpower in the first half and almost as rapid contraction in the second; and (2) how NASA combined central planning and control with decentralized project execution.
Evaluating Large-Scale Interactive Radio Programmes
ERIC Educational Resources Information Center
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…
Foundational perspectives on causality in large-scale brain networks
NASA Astrophysics Data System (ADS)
Mannino, Michael; Bressler, Steven L.
2015-12-01
likelihood that a change in the activity of one neuronal population affects the activity in another. We argue that these measures access the inherently probabilistic nature of causal influences in the brain, and are thus better suited for large-scale brain network analysis than are DC-based measures. Our work is consistent with recent advances in the philosophical study of probabilistic causality, which originated from inherent conceptual problems with deterministic regularity theories. It also resonates with concepts of stochasticity that were involved in establishing modern physics. In summary, we argue that probabilistic causality is a conceptually appropriate foundation for describing neural causality in the brain.
Foundational perspectives on causality in large-scale brain networks.
Mannino, Michael; Bressler, Steven L
2015-12-01
likelihood that a change in the activity of one neuronal population affects the activity in another. We argue that these measures access the inherently probabilistic nature of causal influences in the brain, and are thus better suited for large-scale brain network analysis than are DC-based measures. Our work is consistent with recent advances in the philosophical study of probabilistic causality, which originated from inherent conceptual problems with deterministic regularity theories. It also resonates with concepts of stochasticity that were involved in establishing modern physics. In summary, we argue that probabilistic causality is a conceptually appropriate foundation for describing neural causality in the brain.
Population generation for large-scale simulation
NASA Astrophysics Data System (ADS)
Hannon, Andrew C.; King, Gary; Morrison, Clayton; Galstyan, Aram; Cohen, Paul
2005-05-01
Computer simulation is used to research phenomena ranging from the structure of the space-time continuum to population genetics and future combat.1-3 Multi-agent simulations in particular are now commonplace in many fields.4, 5 By modeling populations whose complex behavior emerges from individual interactions, these simulations help to answer questions about effects where closed form solutions are difficult to solve or impossible to derive.6 To be useful, simulations must accurately model the relevant aspects of the underlying domain. In multi-agent simulation, this means that the modeling must include both the agents and their relationships. Typically, each agent can be modeled as a set of attributes drawn from various distributions (e.g., height, morale, intelligence and so forth). Though these can interact - for example, agent height is related to agent weight - they are usually independent. Modeling relations between agents, on the other hand, adds a new layer of complexity, and tools from graph theory and social network analysis are finding increasing application.7, 8 Recognizing the role and proper use of these techniques, however, remains the subject of ongoing research. We recently encountered these complexities while building large scale social simulations.9-11 One of these, the Hats Simulator, is designed to be a lightweight proxy for intelligence analysis problems. Hats models a "society in a box" consisting of many simple agents, called hats. Hats gets its name from the classic spaghetti western, in which the heroes and villains are known by the color of the hats they wear. The Hats society also has its heroes and villains, but the challenge is to identify which color hat they should be wearing based on how they behave. There are three types of hats: benign hats, known terrorists, and covert terrorists. Covert terrorists look just like benign hats but act like terrorists. Population structure can make covert hat identification significantly more
Novel algorithm of large-scale simultaneous linear equations.
Fujiwara, T; Hoshi, T; Yamamoto, S; Sogabe, T; Zhang, S-L
2010-02-24
We review our recently developed methods of solving large-scale simultaneous linear equations and applications to electronic structure calculations both in one-electron theory and many-electron theory. This is the shifted COCG (conjugate orthogonal conjugate gradient) method based on the Krylov subspace, and the most important issue for applications is the shift equation and the seed switching method, which greatly reduce the computational cost. The applications to nano-scale Si crystals and the double orbital extended Hubbard model are presented.
Large-scale Advanced Propfan (LAP) program
NASA Technical Reports Server (NTRS)
Sagerser, D. A.; Ludemann, S. G.
1985-01-01
The propfan is an advanced propeller concept which maintains the high efficiencies traditionally associated with conventional propellers at the higher aircraft cruise speeds associated with jet transports. The large-scale advanced propfan (LAP) program extends the research done on 2 ft diameter propfan models to a 9 ft diameter article. The program includes design, fabrication, and testing of both an eight bladed, 9 ft diameter propfan, designated SR-7L, and a 2 ft diameter aeroelastically scaled model, SR-7A. The LAP program is complemented by the propfan test assessment (PTA) program, which takes the large-scale propfan and mates it with a gas generator and gearbox to form a propfan propulsion system and then flight tests this system on the wing of a Gulfstream 2 testbed aircraft.
Condition Monitoring of Large-Scale Facilities
NASA Technical Reports Server (NTRS)
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 instabilities of helical flows
NASA Astrophysics Data System (ADS)
Cameron, Alexandre; Alexakis, Alexandros; Brachet, Marc-Étienne
2016-10-01
Large-scale hydrodynamic instabilities of periodic helical flows of a given wave number K are investigated using three-dimensional Floquet numerical computations. In the Floquet formalism the unstable field is expanded in modes of different spacial periodicity. This allows us (i) to clearly distinguish large from small scale instabilities and (ii) to study modes of wave number q of arbitrarily large-scale separation q ≪K . Different flows are examined including flows that exhibit small-scale turbulence. The growth rate σ of the most unstable mode is measured as a function of the scale separation q /K ≪1 and the Reynolds number Re. It is shown that the growth rate follows the scaling σ ∝q if an AKA effect [Frisch et al., Physica D: Nonlinear Phenomena 28, 382 (1987), 10.1016/0167-2789(87)90026-1] is present or a negative eddy viscosity scaling σ ∝q2 in its absence. This holds both for the Re≪1 regime where previously derived asymptotic results are verified but also for Re=O (1 ) that is beyond their range of validity. Furthermore, for values of Re above a critical value ReSc beyond which small-scale instabilities are present, the growth rate becomes independent of q and the energy of the perturbation at large scales decreases with scale separation. The nonlinear behavior of these large-scale instabilities is also examined in the nonlinear regime where the largest scales of the system are found to be the most dominant energetically. These results are interpreted by low-order models.
Large-scale fibre-array multiplexing
Cheremiskin, I V; Chekhlova, T K
2001-05-31
The possibility of creating a fibre multiplexer/demultiplexer with large-scale multiplexing without any basic restrictions on the number of channels and the spectral spacing between them is shown. The operating capacity of a fibre multiplexer based on a four-fibre array ensuring a spectral spacing of 0.7 pm ({approx} 10 GHz) between channels is demonstrated. (laser applications and other topics in quantum electronics)
Large-scale neuromorphic computing systems
NASA Astrophysics Data System (ADS)
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.
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. PMID:27529195
Large scale processes in the solar nebula.
NASA Astrophysics Data System (ADS)
Boss, A. P.
Most proposed chondrule formation mechanisms involve processes occurring inside the solar nebula, so the large scale (roughly 1 to 10 AU) structure of the nebula is of general interest for any chrondrule-forming mechanism. Chondrules and Ca, Al-rich inclusions (CAIs) might also have been formed as a direct result of the large scale structure of the nebula, such as passage of material through high temperature regions. While recent nebula models do predict the existence of relatively hot regions, the maximum temperatures in the inner planet region may not be high enough to account for chondrule or CAI thermal processing, unless the disk mass is considerably greater than the minimum mass necessary to restore the planets to solar composition. Furthermore, it does not seem to be possible to achieve both rapid heating and rapid cooling of grain assemblages in such a large scale furnace. However, if the accretion flow onto the nebula surface is clumpy, as suggested by observations of variability in young stars, then clump-disk impacts might be energetic enough to launch shock waves which could propagate through the nebula to the midplane, thermally processing any grain aggregates they encounter, and leaving behind a trail of chondrules.
Large-scale brightenings associated with flares
NASA Technical Reports Server (NTRS)
Mandrini, Cristina H.; Machado, Marcos E.
1992-01-01
It is shown that large-scale brightenings (LSBs) associated with solar flares, similar to the 'giant arches' discovered by Svestka et al. (1982) in images obtained by the SSM HXIS hours after the onset of two-ribbon flares, can also occur in association with confined flares in complex active regions. For these events, a clear link between the LSB and the underlying flare is clearly evident from the active-region magnetic field topology. The implications of these findings are discussed within the framework of the interacting loops of flares and the giant arch phenomenology.
Large scale phononic metamaterials for seismic isolation
Aravantinos-Zafiris, N.; Sigalas, M. M.
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.
Large-scale dynamics and global warming
Held, I.M. )
1993-02-01
Predictions of future climate change raise a variety of issues in large-scale atmospheric and oceanic dynamics. Several of these are reviewed in this essay, including the sensitivity of the circulation of the Atlantic Ocean to increasing freshwater input at high latitudes; the possibility of greenhouse cooling in the southern oceans; the sensitivity of monsoonal circulations to differential warming of the two hemispheres; the response of midlatitude storms to changing temperature gradients and increasing water vapor in the atmosphere; and the possible importance of positive feedback between the mean winds and eddy-induced heating in the polar stratosphere.
Neutrinos and large-scale structure
Eisenstein, Daniel J.
2015-07-15
I review the use of cosmological large-scale structure to measure properties of neutrinos and other relic populations of light relativistic particles. With experiments to measure the anisotropies of the cosmic microwave anisotropies and the clustering of matter at low redshift, we now have securely measured a relativistic background with density appropriate to the cosmic neutrino background. Our limits on the mass of the neutrino continue to shrink. Experiments coming in the next decade will greatly improve the available precision on searches for the energy density of novel relativistic backgrounds and the mass of neutrinos.
Experimental Simulations of Large-Scale Collisions
NASA Technical Reports Server (NTRS)
Housen, Kevin R.
2002-01-01
This report summarizes research on the effects of target porosity on the mechanics of impact cratering. Impact experiments conducted on a centrifuge provide direct simulations of large-scale cratering on porous asteroids. The experiments show that large craters in porous materials form mostly by compaction, with essentially no deposition of material into the ejecta blanket that is a signature of cratering in less-porous materials. The ratio of ejecta mass to crater mass is shown to decrease with increasing crater size or target porosity. These results are consistent with the observation that large closely-packed craters on asteroid Mathilde appear to have formed without degradation to earlier craters.
Large-Scale PV Integration Study
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.
Local gravity and large-scale structure
NASA Technical Reports Server (NTRS)
Juszkiewicz, Roman; Vittorio, Nicola; Wyse, Rosemary F. G.
1990-01-01
The magnitude and direction of the observed dipole anisotropy of the galaxy distribution can in principle constrain the amount of large-scale power present in the spectrum of primordial density fluctuations. This paper confronts the data, provided by a recent redshift survey of galaxies detected by the IRAS satellite, with the predictions of two cosmological models with very different levels of large-scale power: the biased Cold Dark Matter dominated model (CDM) and a baryon-dominated model (BDM) with isocurvature initial conditions. Model predictions are investigated for the Local Group peculiar velocity, v(R), induced by mass inhomogeneities distributed out to a given radius, R, for R less than about 10,000 km/s. Several convergence measures for v(R) are developed, which can become powerful cosmological tests when deep enough samples become available. For the present data sets, the CDM and BDM predictions are indistinguishable at the 2 sigma level and both are consistent with observations. A promising discriminant between cosmological models is the misalignment angle between v(R) and the apex of the dipole anisotropy of the microwave background.
Development and Applications of a Modular Parallel Process for Large Scale Fluid/Structures Problems
NASA Technical Reports Server (NTRS)
Guruswamy, Guru P.; Byun, Chansup; Kwak, Dochan (Technical Monitor)
2001-01-01
A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel super computers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.
Development and Applications of a Modular Parallel Process for Large Scale Fluid/Structures Problems
NASA Technical Reports Server (NTRS)
Guruswamy, Guru P.; Kwak, Dochan (Technical Monitor)
2002-01-01
A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel supercomputers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.
Stochastic regularization operators on unstructured meshes
NASA Astrophysics Data System (ADS)
Jordi, Claudio; Doetsch, Joseph; Günther, Thomas; Schmelzbach, Cedric; Robertsson, Johan
2016-04-01
Most geophysical inverse problems require the solution of underdetermined systems of equations. In order to solve such inverse problems, appropriate regularization is required. Ideally, this regularization includes information on the expected model variability and spatial correlation. Based on geostatistical covariance functions, which can be adapted to the specific situation, stochastic regularization can be used to add auxiliary constraints to the given inverse problem. Stochastic regularization operators have been successfully applied to geophysical inverse problems formulated on regular grids. Here, we demonstrate the calculation of stochastic regularization operators for unstructured meshes. Unstructured meshes are advantageous with regards to incorporating arbitrary topography, undulating geological interfaces and complex acquisition geometries into the inversion. However, compared to regular grids, unstructured meshes have variable cell sizes, complicating the calculation of stochastic operators. The stochastic operators proposed here are based on a 2D exponential correlation function, allowing to predefine spatial correlation lengths. The regularization thus acts over an imposed correlation length rather than only taking into account neighbouring cells as in regular smoothing constraints. Correlation over a spatial length partly removes the effects of variable cell sizes of unstructured meshes on the regularization. Synthetic models having large-scale interfaces as well as small-scale stochastic variations are used to analyse the performance and behaviour of the stochastic regularization operators. The resulting inverted models obtained with stochastic regularization are compare against the results of standard regularization approaches (damping and smoothing). Besides using stochastic operators for regularization, we plan to incorporate the footprint of the stochastic operator in further applications such as the calculation of the cross-gradient functions
Large scale study of tooth enamel
Bodart, F.; Deconninck, G.; Martin, M.Th.
1981-04-01
Human tooth enamel contains traces of foreign elements. The presence of these elements is related to the history and the environment of the human body and can be considered as the signature of perturbations which occur during the growth of a tooth. A map of the distribution of these traces on a large scale sample of the population will constitute a reference for further investigations of environmental effects. One hundred eighty samples of teeth were first analysed using PIXE, backscattering and nuclear reaction techniques. The results were analysed using statistical methods. Correlations between O, F, Na, P, Ca, Mn, Fe, Cu, Zn, Pb and Sr were observed and cluster analysis was in progress. The techniques described in the present work have been developed in order to establish a method for the exploration of very large samples of the Belgian population.
Batteries for Large Scale Energy Storage
Soloveichik, Grigorii L.
2011-07-15
In recent years, with the deployment of renewable energy sources, advances in electrified transportation, and development in smart grids, the markets for large-scale stationary energy storage have grown rapidly. Electrochemical energy storage methods are strong candidate solutions due to their high energy density, flexibility, and scalability. This review provides an overview of mature and emerging technologies for secondary and redox flow batteries. New developments in the chemistry of secondary and flow batteries as well as regenerative fuel cells are also considered. Advantages and disadvantages of current and prospective electrochemical energy storage options are discussed. The most promising technologies in the short term are high-temperature sodium batteries with β”-alumina electrolyte, lithium-ion batteries, and flow batteries. Regenerative fuel cells and lithium metal batteries with high energy density require further research to become practical.
Large-scale databases of proper names.
Conley, P; Burgess, C; Hage, D
1999-05-01
Few tools for research in proper names have been available--specifically, there is no large-scale corpus of proper names. Two corpora of proper names were constructed, one based on U.S. phone book listings, the other derived from a database of Usenet text. Name frequencies from both corpora were compared with human subjects' reaction times (RTs) to the proper names in a naming task. Regression analysis showed that the Usenet frequencies contributed to predictions of human RT, whereas phone book frequencies did not. In addition, semantic neighborhood density measures derived from the HAL corpus were compared with the subjects' RTs and found to be a better predictor of RT than was frequency in either corpus. These new corpora are freely available on line for download. Potentials for these corpora range from using the names as stimuli in experiments to using the corpus data in software applications. PMID:10495803
Large Scale Quantum Simulations of Nuclear Pasta
NASA Astrophysics Data System (ADS)
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 < ρ < 0 . 10 fm-3, proton fractions 0 . 05
Large-scale simulations of reionization
Kohler, Katharina; Gnedin, Nickolay Y.; 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 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. PMID:26072893
Large scale structures in transitional pipe flow
NASA Astrophysics Data System (ADS)
Hellström, Leo; Ganapathisubramani, Bharathram; Smits, Alexander
2015-11-01
We present a dual-plane snapshot POD analysis of transitional pipe flow at a Reynolds number of 3440, based on the pipe diameter. The time-resolved high-speed PIV data were simultaneously acquired in two planes, a cross-stream plane (2D-3C) and a streamwise plane (2D-2C) on the pipe centerline. The two light sheets were orthogonally polarized, allowing particles situated in each plane to be viewed independently. In the snapshot POD analysis, the modal energy is based on the cross-stream plane, while the POD modes are calculated using the dual-plane data. We present results on the emergence and decay of the energetic large scale motions during transition to turbulence, and compare these motions to those observed in fully developed turbulent flow. Supported under ONR Grant N00014-13-1-0174 and ERC Grant No. 277472.
Challenges in large scale distributed computing: bioinformatics.
Disz, T.; Kubal, M.; Olson, R.; Overbeek, R.; Stevens, R.; Mathematics and Computer Science; Univ. of Chicago; The Fellowship for the Interpretation of Genomes
2005-01-01
The amount of genomic data available for study is increasing at a rate similar to that of Moore's law. This deluge of data is challenging bioinformaticians to develop newer, faster and better algorithms for analysis and examination of this data. The growing availability of large scale computing grids coupled with high-performance networking is challenging computer scientists to develop better, faster methods of exploiting parallelism in these biological computations and deploying them across computing grids. In this paper, we describe two computations that are required to be run frequently and which require large amounts of computing resource to complete in a reasonable time. The data for these computations are very large and the sequential computational time can exceed thousands of hours. We show the importance and relevance of these computations, the nature of the data and parallelism and we show how we are meeting the challenge of efficiently distributing and managing these computations in the SEED project.
The challenge of large-scale structure
NASA Astrophysics Data System (ADS)
Gregory, S. A.
1996-03-01
The tasks that I have assumed for myself in this presentation include three separate parts. The first, appropriate to the particular setting of this meeting, is to review the basic work of the founding of this field; the appropriateness comes from the fact that W. G. Tifft made immense contributions that are not often realized by the astronomical community. The second task is to outline the general tone of the observational evidence for large scale structures. (Here, in particular, I cannot claim to be complete. I beg forgiveness from any workers who are left out by my oversight for lack of space and time.) The third task is to point out some of the major aspects of the field that may represent the clues by which some brilliant sleuth will ultimately figure out how galaxies formed.
Grid sensitivity capability for large scale structures
NASA Technical Reports Server (NTRS)
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 Astrophysical Visualization on Smartphones
NASA Astrophysics Data System (ADS)
Becciani, U.; Massimino, P.; Costa, A.; Gheller, C.; Grillo, A.; Krokos, M.; Petta, C.
2011-07-01
Nowadays digital sky surveys and long-duration, high-resolution numerical simulations using high performance computing and grid systems produce multidimensional astrophysical datasets in the order of several Petabytes. Sharing visualizations of such datasets within communities and collaborating research groups is of paramount importance for disseminating results and advancing astrophysical research. Moreover educational and public outreach programs can benefit greatly from novel ways of presenting these datasets by promoting understanding of complex astrophysical processes, e.g., formation of stars and galaxies. We have previously developed VisIVO Server, a grid-enabled platform for high-performance large-scale astrophysical visualization. This article reviews the latest developments on VisIVO Web, a custom designed web portal wrapped around VisIVO Server, then introduces VisIVO Smartphone, a gateway connecting VisIVO Web and data repositories for mobile astrophysical visualization. We discuss current work and summarize future developments.
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.
The XMM Large Scale Structure Survey
NASA Astrophysics Data System (ADS)
Pierre, Marguerite
2005-10-01
We propose to complete, by an additional 5 deg2, the XMM-LSS Survey region overlying the Spitzer/SWIRE field. This field already has CFHTLS and Integral coverage, and will encompass about 10 deg2. The resulting multi-wavelength medium-depth survey, which complements XMM and Chandra deep surveys, will provide a unique view of large-scale structure over a wide range of redshift, and will show active galaxies in the full range of environments. The complete coverage by optical and IR surveys provides high-quality photometric redshifts, so that cosmological results can quickly be extracted. In the spirit of a Legacy survey, we will make the raw X-ray data immediately public. Multi-band catalogues and images will also be made available on short time scales.
Large-scale sequential quadratic programming algorithms
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.
Introducing Large-Scale Innovation in Schools
NASA Astrophysics Data System (ADS)
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.
Supporting large-scale computational science
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.
Supporting large-scale computational science
Musick, R., LLNL
1998-02-19
Business needs have driven the development of commercial database systems since their inception. As a result, there has been a strong focus on supporting many users, minimizing the potential corruption or loss of data, and maximizing performance metrics like transactions per second, or TPC-C and TPC-D results. It turns out that these optimizations have little to do with the needs of the scientific community, and in particular have little impact on improving the management and use of large-scale high-dimensional data. At the same time, there is an unanswered need in the scientific community for many of the benefits offered by a robust DBMS. For example, tying an ad-hoc query language such as SQL together with a visualization toolkit would be a powerful enhancement to current capabilities. Unfortunately, there has been little emphasis or discussion in the VLDB community on this mismatch over the last decade. The goal of the paper is to identify the specific issues that need to be resolved before large-scale scientific applications can make use of DBMS products. This topic is addressed in the context of an evaluation of commercial DBMS technology applied to the exploration of data generated by the Department of Energy`s Accelerated Strategic Computing Initiative (ASCI). The paper describes the data being generated for ASCI as well as current capabilities for interacting with and exploring this data. The attraction of applying standard DBMS technology to this domain is discussed, as well as the technical and business issues that currently make this an infeasible solution.
Very sparse LSSVM reductions for large-scale data.
Mall, Raghvendra; Suykens, Johan A K
2015-05-01
Least squares support vector machines (LSSVMs) have been widely applied for classification and regression with comparable performance with SVMs. The LSSVM model lacks sparsity and is unable to handle large-scale data due to computational and memory constraints. A primal fixed-size LSSVM (PFS-LSSVM) introduce sparsity using Nyström approximation with a set of prototype vectors (PVs). The PFS-LSSVM model solves an overdetermined system of linear equations in the primal. However, this solution is not the sparsest. We investigate the sparsity-error tradeoff by introducing a second level of sparsity. This is done by means of L0 -norm-based reductions by iteratively sparsifying LSSVM and PFS-LSSVM models. The exact choice of the cardinality for the initial PV set is not important then as the final model is highly sparse. The proposed method overcomes the problem of memory constraints and high computational costs resulting in highly sparse reductions to LSSVM models. The approximations of the two models allow to scale the models to large-scale datasets. Experiments on real-world classification and regression data sets from the UCI repository illustrate that these approaches achieve sparse models without a significant tradeoff in errors.
Engineering large-scale agent-based systems with consensus
NASA Technical Reports Server (NTRS)
Bokma, A.; Slade, A.; Kerridge, S.; Johnson, K.
1994-01-01
The paper presents the consensus method for the development of large-scale agent-based systems. Systems can be developed as networks of knowledge based agents (KBA) which engage in a collaborative problem solving effort. The method provides a comprehensive and integrated approach to the development of this type of system. This includes a systematic analysis of user requirements as well as a structured approach to generating a system design which exhibits the desired functionality. There is a direct correspondence between system requirements and design components. The benefits of this approach are that requirements are traceable into design components and code thus facilitating verification. The use of the consensus method with two major test applications showed it to be successful and also provided valuable insight into problems typically associated with the development of large systems.
A low-dimensional model for large-scale coherent structures
NASA Astrophysics Data System (ADS)
Bai, Kunlun; Ji, Dandan; Brown, Eric
2015-11-01
We demonstrate a methodology to predict the dynamics of the large-scale coherent structures in turbulence using a simple low dimensional stochastic model proposed by Brown and Ahlers (Phys. Fluids, 2008). The model terms are derived from the Navier-Stokes equations, including a potential term depending on the geometry of the system. The model has previously described several dynamical modes of the large-scale circulation (LSC) in turbulent Rayleigh-Bénard convection. Here we test a model prediction for the existence of a new mode where the LSC stochastically changes direction to align with different diagonals of a cubic container. The model successfully predicts the switching rate of the LSC at different tilting conditions. The success of the prediction of the switching mode demonstrates that a low-dimensional turbulent model can quantitatively predict the existence and properties of different dynamical states that result from boundary geometry.
Large-Scale Statistics for Cu Electromigration
NASA Astrophysics Data System (ADS)
Hauschildt, M.; Gall, M.; Hernandez, R.
2009-06-01
Even after the successful introduction of Cu-based metallization, the electromigration failure risk has remained one of the important reliability concerns for advanced process technologies. The observation of strong bimodality for the electron up-flow direction in dual-inlaid Cu interconnects has added complexity, but is now widely accepted. The failure voids can occur both within the via ("early" mode) or within the trench ("late" mode). More recently, bimodality has been reported also in down-flow electromigration, leading to very short lifetimes due to small, slit-shaped voids under vias. For a more thorough investigation of these early failure phenomena, specific test structures were designed based on the Wheatstone Bridge technique. The use of these structures enabled an increase of the tested sample size close to 675000, allowing a direct analysis of electromigration failure mechanisms at the single-digit ppm regime. Results indicate that down-flow electromigration exhibits bimodality at very small percentage levels, not readily identifiable with standard testing methods. The activation energy for the down-flow early failure mechanism was determined to be 0.83±0.02 eV. Within the small error bounds of this large-scale statistical experiment, this value is deemed to be significantly lower than the usually reported activation energy of 0.90 eV for electromigration-induced diffusion along Cu/SiCN interfaces. Due to the advantages of the Wheatstone Bridge technique, we were also able to expand the experimental temperature range down to 150° C, coming quite close to typical operating conditions up to 125° C. As a result of the lowered activation energy, we conclude that the down-flow early failure mode may control the chip lifetime at operating conditions. The slit-like character of the early failure void morphology also raises concerns about the validity of the Blech-effect for this mechanism. A very small amount of Cu depletion may cause failure even before a
Non-Gaussianity and large-scale structure in a two-field inflationary model
Tseliakhovich, Dmitriy; Hirata, Christopher
2010-08-15
Single-field inflationary models predict nearly Gaussian initial conditions, and hence a detection of non-Gaussianity would be a signature of the more complex inflationary scenarios. In this paper we study the effect on the cosmic microwave background and on large-scale structure from primordial non-Gaussianity in a two-field inflationary model in which both the inflaton and curvaton contribute to the density perturbations. We show that in addition to the previously described enhancement of the galaxy bias on large scales, this setup results in large-scale stochasticity. We provide joint constraints on the local non-Gaussianity parameter f-tilde{sub NL} and the ratio {xi} of the amplitude of primordial perturbations due to the inflaton and curvaton using WMAP and Sloan Digital Sky Survey data.
NASA Astrophysics Data System (ADS)
Ebrahimi, F.; Blackman, E. G.
2016-06-01
For cylindrical differentially rotating plasmas, we study large-scale magnetic field generation from finite amplitude non-axisymmetric perturbations by comparing numerical simulations with quasi-linear analytic theory. When initiated with a vertical magnetic field of either zero or finite net flux, our global cylindrical simulations exhibit the magnetorotational instability (MRI) and large-scale dynamo growth of radially alternating mean fields, averaged over height and azimuth. This dynamo growth is explained by our analytic calculations of a non-axisymmetric fluctuation-induced electromotive force that is sustained by azimuthal shear of the fluctuating fields. The standard `Ω effect' (shear of the mean field by differential rotation) is unimportant. For the MRI case, we express the large-scale dynamo field as a function of differential rotation. The resulting radially alternating large-scale fields may have implications for angular momentum transport in discs and corona. To connect with previous work on large-scale dynamos with local linear shear and identify the minimum conditions needed for large-scale field growth, we also solve our equations in local Cartesian coordinates. We find that large-scale dynamo growth in a linear shear flow without rotation can be sustained by shear plus non-axisymmetric fluctuations - even if not helical, a seemingly previously unidentified distinction. The linear shear flow dynamo emerges as a more restricted version of our more general new global cylindrical calculations.
Large scale digital atlases in neuroscience
NASA Astrophysics Data System (ADS)
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.
Food appropriation through large scale land acquisitions
NASA Astrophysics Data System (ADS)
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 carbon fiber tests
NASA Technical Reports Server (NTRS)
Pride, R. A.
1980-01-01
A realistic release of carbon fibers was established by burning a minimum of 45 kg of carbon fiber composite aircraft structural components in each of five large scale, outdoor aviation jet fuel fire tests. This release was quantified by several independent assessments with various instruments developed specifically for these tests. The most likely values for the mass of single carbon fibers released ranged from 0.2 percent of the initial mass of carbon fiber for the source tests (zero wind velocity) to a maximum of 0.6 percent of the initial carbon fiber mass for dissemination tests (5 to 6 m/s wind velocity). Mean fiber lengths for fibers greater than 1 mm in length ranged from 2.5 to 3.5 mm. Mean diameters ranged from 3.6 to 5.3 micrometers which was indicative of significant oxidation. Footprints of downwind dissemination of the fire released fibers were measured to 19.1 km from the fire.
Large-scale clustering of cosmic voids
NASA Astrophysics Data System (ADS)
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.
Simulations of Large Scale Structures in Cosmology
NASA Astrophysics Data System (ADS)
Liao, Shihong
Large-scale structures are powerful probes for cosmology. Due to the long range and non-linear nature of gravity, the formation of cosmological structures is a very complicated problem. The only known viable solution is cosmological N-body simulations. In this thesis, we use cosmological N-body simulations to study structure formation, particularly dark matter haloes' angular momenta and dark matter velocity field. The origin and evolution of angular momenta is an important ingredient for the formation and evolution of haloes and galaxies. We study the time evolution of the empirical angular momentum - mass relation for haloes to offer a more complete picture about its origin, dependences on cosmological models and nonlinear evolutions. We also show that haloes follow a simple universal specific angular momentum profile, which is useful in modelling haloes' angular momenta. The dark matter velocity field will become a powerful cosmological probe in the coming decades. However, theoretical predictions of the velocity field rely on N-body simulations and thus may be affected by numerical artefacts (e.g. finite box size, softening length and initial conditions). We study how such numerical effects affect the predicted pairwise velocities, and we propose a theoretical framework to understand and correct them. Our results will be useful for accurately comparing N-body simulations to observational data of pairwise velocities.
Curvature constraints from large scale structure
NASA Astrophysics Data System (ADS)
Di Dio, Enea; Montanari, Francesco; Raccanelli, Alvise; Durrer, Ruth; Kamionkowski, Marc; Lesgourgues, Julien
2016-06-01
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 ΩK 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 spatial curvature parameter estimation. We show that constraints on the curvature parameter may be strongly biased if, in particular, cosmic magnification is not included in the analysis. Other relativistic effects turn out to be subdominant in the studied configuration. We analyze how the shift in the estimated best-fit value for the curvature and other cosmological parameters depends on the magnification bias parameter, and find that significant biases are to be expected if this term is not properly considered in the analysis.
Large scale molecular simulations of nanotoxicity.
Jimenez-Cruz, Camilo A; Kang, Seung-gu; Zhou, Ruhong
2014-01-01
The widespread use of nanomaterials in biomedical applications has been accompanied by an increasing interest in understanding their interactions with tissues, cells, and biomolecules, and in particular, on how they might affect the integrity of cell membranes and proteins. In this mini-review, we present a summary of some of the recent studies on this important subject, especially from the point of view of large scale molecular simulations. The carbon-based nanomaterials and noble metal nanoparticles are the main focus, with additional discussions on quantum dots and other nanoparticles as well. The driving forces for adsorption of fullerenes, carbon nanotubes, and graphene nanosheets onto proteins or cell membranes are found to be mainly hydrophobic interactions and the so-called π-π stacking (between aromatic rings), while for the noble metal nanoparticles the long-range electrostatic interactions play a bigger role. More interestingly, there are also growing evidences showing that nanotoxicity can have implications in de novo design of nanomedicine. For example, the endohedral metallofullerenol Gd@C₈₂(OH)₂₂ is shown to inhibit tumor growth and metastasis by inhibiting enzyme MMP-9, and graphene is illustrated to disrupt bacteria cell membranes by insertion/cutting as well as destructive extraction of lipid molecules. These recent findings have provided a better understanding of nanotoxicity at the molecular level and also suggested therapeutic potential by using the cytotoxicity of nanoparticles against cancer or bacteria cells.
Large scale mechanical metamaterials as seismic shields
NASA Astrophysics Data System (ADS)
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 wind turbine structures
NASA Technical Reports Server (NTRS)
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 wind turbine structures
NASA Astrophysics Data System (ADS)
Spera, David A.
1988-05-01
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 Stratospheric Transport Processes
NASA Technical Reports Server (NTRS)
Plumb, R. Alan
2001-01-01
The paper discusses the following: 1. The Brewer-Dobson circulation: tropical upwelling. 2. Mixing into polar vortices. 3. The latitudinal structure of "age" in the stratosphere. 4. The subtropical "tracer edges". 5. Transport in the lower troposphere. 6. Tracer modeling during SOLVE. 7. 3D modeling of "mean age". 8. Models and measurements II.
An informal paper on large-scale dynamic systems
NASA Technical Reports Server (NTRS)
Ho, Y. C.
1975-01-01
Large scale systems are defined as systems requiring more than one decision maker to control the system. Decentralized control and decomposition are discussed for large scale dynamic systems. Information and many-person decision problems are analyzed.
NASA Astrophysics Data System (ADS)
de J. Montoya G., G.; Sampaio, A. J. C.; de Almeida, F. C.
A comparison is made between the methods for solving the stochastic collection equation of Berry and Reinhardt, using 72 categories, and the method of moments as improved by Tzivion et al., using only 36 classes. The computations, carried out for different kernels and several initial mean drop radii, showed that the numerical acceleration inherent to the Bleck's method is also present in the approach of Tzivion et al., but in a weaker form. This acceleration depends on the type of kernel and, for cloud conditions allowing coalescence development, it remains between acceptable limits and decreases with time. When the method of moments is run for 72 categories, the numerical acceleration practically disappears. Although, in terms of mass storage, the requirements of both methods are the same, in terms of computational speed, this approach has advantages over Berry and Reinhardt's method for use in cloud models with detailed description of microphysical processes.
3D fast adaptive correlation imaging for large-scale gravity data based on GPU computation
NASA Astrophysics Data System (ADS)
Chen, Z.; Meng, X.; Guo, L.; Liu, G.
2011-12-01
In recent years, large scale gravity data sets have been collected and employed to enhance gravity problem-solving abilities of tectonics studies in China. Aiming at the large scale data and the requirement of rapid interpretation, previous authors have carried out a lot of work, including the fast gradient module inversion and Euler deconvolution depth inversion ,3-D physical property inversion using stochastic subspaces and equivalent storage, fast inversion using wavelet transforms and a logarithmic barrier method. So it can be say that 3-D gravity inversion has been greatly improved in the last decade. Many authors added many different kinds of priori information and constraints to deal with nonuniqueness using models composed of a large number of contiguous cells of unknown property and obtained good results. However, due to long computation time, instability and other shortcomings, 3-D physical property inversion has not been widely applied to large-scale data yet. In order to achieve 3-D interpretation with high efficiency and precision for geological and ore bodies and obtain their subsurface distribution, there is an urgent need to find a fast and efficient inversion method for large scale gravity data. As an entirely new geophysical inversion method, 3D correlation has a rapid development thanks to the advantage of requiring no a priori information and demanding small amount of computer memory. This method was proposed to image the distribution of equivalent excess masses of anomalous geological bodies with high resolution both longitudinally and transversely. In order to tranform the equivalence excess masses into real density contrasts, we adopt the adaptive correlation imaging for gravity data. After each 3D correlation imaging, we change the equivalence into density contrasts according to the linear relationship, and then carry out forward gravity calculation for each rectangle cells. Next, we compare the forward gravity data with real data, and
International space station. Large scale integration approach
NASA Astrophysics Data System (ADS)
Cohen, Brad
The International Space Station is the most complex large scale integration program in development today. The approach developed for specification, subsystem development, and verification lay a firm basis on which future programs of this nature can be based. International Space Station is composed of many critical items, hardware and software, built by numerous International Partners, NASA Institutions, and U.S. Contractors and is launched over a period of five years. Each launch creates a unique configuration that must be safe, survivable, operable, and support ongoing assembly (assemblable) to arrive at the assembly complete configuration in 2003. The approaches to integrating each of the modules into a viable spacecraft and continue the assembly is a challenge in itself. Added to this challenge are the severe schedule constraints and lack of an "Iron Bird", which prevents assembly and checkout of each on-orbit configuration prior to launch. This paper will focus on the following areas: 1) Specification development process explaining how the requirements and specifications were derived using a modular concept driven by launch vehicle capability. Each module is composed of components of subsystems versus completed subsystems. 2) Approach to stage (each stage consists of the launched module added to the current on-orbit spacecraft) specifications. Specifically, how each launched module and stage ensures support of the current and future elements of the assembly. 3) Verification approach, due to the schedule constraints, is primarily analysis supported by testing. Specifically, how are the interfaces ensured to mate and function on-orbit when they cannot be mated before launch. 4) Lessons learned. Where can we improve this complex system design and integration task?
Large Scale Flame Spread Environmental Characterization Testing
NASA Technical Reports Server (NTRS)
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
Li, Fangfei
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.
Schumacher, Kathryn M.; Chen, Richard Li-Yang; Cohn, Amy E. M.; Castaing, Jeremy
2016-04-15
Here, we consider the problem of determining the capacity to assign to each arc in a given network, subject to uncertainty in the supply and/or demand of each node. This design problem underlies many real-world applications, such as the design of power transmission and telecommunications networks. We first consider the case where a set of supply/demand scenarios are provided, and we must determine the minimum-cost set of arc capacities such that a feasible flow exists for each scenario. We briefly review existing theoretical approaches to solving this problem and explore implementation strategies to reduce run times. With this as amore » foundation, our primary focus is on a chance-constrained version of the problem in which α% of the scenarios must be feasible under the chosen capacity, where α is a user-defined parameter and the specific scenarios to be satisfied are not predetermined. We describe an algorithm which utilizes a separation routine for identifying violated cut-sets which can solve the problem to optimality, and we present computational results. We also present a novel greedy algorithm, our primary contribution, which can be used to solve for a high quality heuristic solution. We present computational analysis to evaluate the performance of our proposed approaches.« less
Nearly incompressible fluids: hydrodynamics and large scale inhomogeneity.
Hunana, P; Zank, G P; Shaikh, D
2006-08-01
incompressible equations for higher order fluctuation components are derived and it is shown that they converge to the usual homogeneous nearly incompressible equations in the limit of no large-scale background. We use a time and length scale separation procedure to obtain wave equations for the acoustic pressure and velocity perturbations propagating on fast-time-short-wavelength scales. On these scales, the pseudosound relation, used to relate density and pressure fluctuations, is also obtained. In both cases, the speed of propagation (sound speed) depends on background variables and therefore varies spatially. For slow-time scales, a simple pseudosound relation cannot be obtained and density and pressure fluctuations are implicitly related through a relation which can be solved only numerically. Subject to some simplifications, a generalized inhomogeneous pseudosound relation is derived. With this paper, we extend the theory of nearly incompressible hydrodynamics to flows, including the solar wind, which include large-scale inhomogeneities (in this case radially symmetric and in equilibrium). PMID:17025534
Cloud-based large-scale air traffic flow optimization
NASA Astrophysics Data System (ADS)
Cao, Yi
The ever-increasing traffic demand makes the efficient use of airspace an imperative mission, and this paper presents an effort in response to this call. Firstly, a new aggregate model, called Link Transmission Model (LTM), is proposed, which models the nationwide traffic as a network of flight routes identified by origin-destination pairs. The traversal time of a flight route is assumed to be the mode of distribution of historical flight records, and the mode is estimated by using Kernel Density Estimation. As this simplification abstracts away physical trajectory details, the complexity of modeling is drastically decreased, resulting in efficient traffic forecasting. The predicative capability of LTM is validated against recorded traffic data. Secondly, a nationwide traffic flow optimization problem with airport and en route capacity constraints is formulated based on LTM. The optimization problem aims at alleviating traffic congestions with minimal global delays. This problem is intractable due to millions of variables. A dual decomposition method is applied to decompose the large-scale problem such that the subproblems are solvable. However, the whole problem is still computational expensive to solve since each subproblem is an smaller integer programming problem that pursues integer solutions. Solving an integer programing problem is known to be far more time-consuming than solving its linear relaxation. In addition, sequential execution on a standalone computer leads to linear runtime increase when the problem size increases. To address the computational efficiency problem, a parallel computing framework is designed which accommodates concurrent executions via multithreading programming. The multithreaded version is compared with its monolithic version to show decreased runtime. Finally, an open-source cloud computing framework, Hadoop MapReduce, is employed for better scalability and reliability. This framework is an "off-the-shelf" parallel computing model
Large-Scale Spacecraft Fire Safety Tests
NASA Technical Reports Server (NTRS)
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
Reconstructing Information in Large-Scale Structure via Logarithmic Mapping
NASA Astrophysics Data System (ADS)
Szapudi, Istvan
We propose to develop a new method to extract information from large-scale structure data combining two-point statistics and non-linear transformations; before, this information was available only with substantially more complex higher-order statistical methods. Initially, most of the cosmological information in large-scale structure lies in two-point statistics. With non- linear evolution, some of that useful information leaks into higher-order statistics. The PI and group has shown in a series of theoretical investigations how that leakage occurs, and explained the Fisher information plateau at smaller scales. This plateau means that even as more modes are added to the measurement of the power spectrum, the total cumulative information (loosely speaking the inverse errorbar) is not increasing. Recently we have shown in Neyrinck et al. (2009, 2010) that a logarithmic (and a related Gaussianization or Box-Cox) transformation on the non-linear Dark Matter or galaxy field reconstructs a surprisingly large fraction of this missing Fisher information of the initial conditions. This was predicted by the earlier wave mechanical formulation of gravitational dynamics by Szapudi & Kaiser (2003). The present proposal is focused on working out the theoretical underpinning of the method to a point that it can be used in practice to analyze data. In particular, one needs to deal with the usual real-life issues of galaxy surveys, such as complex geometry, discrete sam- pling (Poisson or sub-Poisson noise), bias (linear, or non-linear, deterministic, or stochastic), redshift distortions, pro jection effects for 2D samples, and the effects of photometric redshift errors. We will develop methods for weak lensing and Sunyaev-Zeldovich power spectra as well, the latter specifically targetting Planck. In addition, we plan to investigate the question of residual higher- order information after the non-linear mapping, and possible applications for cosmology. Our aim will be to work out
Large-scale assembly of colloidal particles
NASA Astrophysics Data System (ADS)
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 Turbulent Structures in Supersonic Jets
NASA Technical Reports Server (NTRS)
Rao, Ram Mohan; Lundgren, Thomas S.
1997-01-01
Jet noise is a major concern in the design of commercial aircraft. Studies by various researchers suggest that aerodynamic noise is a major contributor to jet noise. Some of these studies indicate that most of the aerodynamic jet noise due to turbulent mixing occurs when there is a rapid variation in turbulent structure, i.e. rapidly growing or decaying vortices. The objective of this research was to simulate a compressible round jet to study the non-linear evolution of vortices and the resulting acoustic radiations. In particular, to understand the effect of turbulence structure on the noise. An ideal technique to study this problem is Direct Numerical Simulations (DNS), because it provides precise control on the initial and boundary conditions that lead to the turbulent structures studied. It also provides complete 3-dimensional time dependent data. Since the dynamics of a temporally evolving jet are not greatly different from those of a spatially evolving jet, a temporal jet problem was solved, using periodicity in the direction of the jet axis. This enables the application of Fourier spectral methods in the streamwise direction. Physically this means that turbulent structures in the jet are repeated in successive downstream cells instead of being gradually modified downstream into a jet plume. The DNS jet simulation helps us understand the various turbulent scales and mechanisms of turbulence generation in the evolution of a compressible round jet. These accurate flow solutions will be used in future research to estimate near-field acoustic radiation by computing the total outward flux across a surface and determine how it is related to the evolution of the turbulent solutions. Furthermore, these simulations allow us to investigate the sensitivity of acoustic radiations to inlet/boundary conditions, with possible appli(,a- tion to active noise suppression. In addition, the data generated can be used to compute, various turbulence quantities such as mean
Large Scale Turbulent Structures in Supersonic Jets
NASA Technical Reports Server (NTRS)
Rao, Ram Mohan; Lundgren, Thomas S.
1997-01-01
Jet noise is a major concern in the design of commercial aircraft. Studies by various researchers suggest that aerodynamic noise is a major contributor to jet noise. Some of these studies indicate that most of the aerodynamic jet noise due to turbulent mixing occurs when there is a rapid variation in turbulent structure, i.e. rapidly growing or decaying vortices. The objective of this research was to simulate a compressible round jet to study the non-linear evolution of vortices and the resulting acoustic radiations. In particular, to understand the effect of turbulence structure on the noise. An ideal technique to study this problem is Direct Numerical Simulations(DNS), because it provides precise control on the initial and boundary conditions that lead to the turbulent structures studied. It also provides complete 3-dimensional time dependent data. Since the dynamics of a temporally evolving jet are not greatly different from those, of a spatially evolving jet, a temporal jet problem was solved, using periodicity ill the direction of the jet axis. This enables the application of Fourier spectral methods in the streamwise direction. Physically this means that turbulent structures in the jet are repeated in successive downstream cells instead of being gradually modified downstream into a jet plume. The DNS jet simulation helps us understand the various turbulent scales and mechanisms of turbulence generation in the evolution of a compressible round jet. These accurate flow solutions will be used in future research to estimate near-field acoustic radiation by computing the total outward flux across a surface and determine how it is related to the evolution of the turbulent solutions. Furthermore, these simulations allow us to investigate the sensitivity of acoustic radiations to inlet/boundary conditions, with possible application to active noise suppression. In addition, the data generated can be used to compute various turbulence quantities such as mean velocities
Multitree Algorithms for Large-Scale Astrostatistics
NASA Astrophysics Data System (ADS)
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
Nonlinear large-scale optimization with WORHP
NASA Astrophysics Data System (ADS)
Nikolayzik, Tim; Büskens, Christof; Gerdts, Matthias
Nonlinear optimization has grown to a key technology in many areas of aerospace industry, e.g. satellite control, shape-optimization, aerodynamamics, trajectory planning, reentry prob-lems, interplanetary flights. One of the most extensive areas is the optimization of trajectories for aerospace applications. These problems typically are discretized optimal control problems, which leads to large sparse nonlinear optimization problems. In the end all these different problems from different areas can be described in the general formulation as a nonlinear opti-mization problem. WORHP is designed to solve nonlinear optimization problems with more then one million variables and one million constraints. WORHP uses a lot of different advanced techniques, e.g. reverse communication, to organize the optimization process as efficient and controllable by the user as possible. The solver has nine different interfaces, e.g. to MAT-LAB/SIMULINK and AMPL. Tests of WORHP had shown that WORHP is a very robust and promising solver. Several examples from space applications will be presented.
Large Scale, High Resolution, Mantle Dynamics Modeling
NASA Astrophysics Data System (ADS)
Geenen, T.; Berg, A. V.; Spakman, W.
2007-12-01
To model the geodynamic evolution of plate convergence, subduction and collision and to allow for a connection to various types of observational data, geophysical, geodetical and geological, we developed a 4D (space-time) numerical mantle convection code. The model is based on a spherical 3D Eulerian fem model, with quadratic elements, on top of which we constructed a 3D Lagrangian particle in cell(PIC) method. We use the PIC method to transport material properties and to incorporate a viscoelastic rheology. Since capturing small scale processes associated with localization phenomena require a high resolution, we spend a considerable effort on implementing solvers suitable to solve for models with over 100 million degrees of freedom. We implemented Additive Schwartz type ILU based methods in combination with a Krylov solver, GMRES. However we found that for problems with over 500 thousend degrees of freedom the convergence of the solver degraded severely. This observation is known from the literature [Saad, 2003] and results from the local character of the ILU preconditioner resulting in a poor approximation of the inverse of A for large A. The size of A for which ILU is no longer usable depends on the condition of A and on the amount of fill in allowed for the ILU preconditioner. We found that for our problems with over 5×105 degrees of freedom convergence became to slow to solve the system within an acceptable amount of walltime, one minute, even when allowing for considerable amount of fill in. We also implemented MUMPS and found good scaling results for problems up to 107 degrees of freedom for up to 32 CPU¡¯s. For problems with over 100 million degrees of freedom we implemented Algebraic Multigrid type methods (AMG) from the ML library [Sala, 2006]. Since multigrid methods are most effective for single parameter problems, we rebuild our model to use the SIMPLE method in the Stokes solver [Patankar, 1980]. We present scaling results from these solvers for 3D
Probes of large-scale structure in the universe
NASA Technical Reports Server (NTRS)
Suto, Yasushi; Gorski, Krzysztof; Juszkiewicz, Roman; Silk, Joseph
1988-01-01
A general formalism is developed which shows that the gravitational instability theory for the origin of the large-scale structure of the universe is now capable of critically confronting observational results on cosmic background radiation angular anisotropies, large-scale bulk motions, and large-scale clumpiness in the galaxy counts. The results indicate that presently advocated cosmological models will have considerable difficulty in simultaneously explaining the observational results.
Parallel block schemes for large scale least squares computations
Golub, G.H.; Plemmons, R.J.; Sameh, A.
1986-04-01
Large scale least squares computations arise in a variety of scientific and engineering problems, including geodetic adjustments and surveys, medical image analysis, molecular structures, partial differential equations and substructuring methods in structural engineering. In each of these problems, matrices often arise which possess a block structure which reflects the local connection nature of the underlying physical problem. For example, such super-large nonlinear least squares computations arise in geodesy. Here the coordinates of positions are calculated by iteratively solving overdetermined systems of nonlinear equations by the Gauss-Newton method. The US National Geodetic Survey will complete this year (1986) the readjustment of the North American Datum, a problem which involves over 540 thousand unknowns and over 6.5 million observations (equations). The observation matrix for these least squares computations has a block angular form with 161 diagnonal blocks, each containing 3 to 4 thousand unknowns. In this paper parallel schemes are suggested for the orthogonal factorization of matrices in block angular form and for the associated backsubstitution phase of the least squares computations. In addition, a parallel scheme for the calculation of certain elements of the covariance matrix for such problems is described. It is shown that these algorithms are ideally suited for multiprocessors with three levels of parallelism such as the Cedar system at the University of Illinois. 20 refs., 7 figs.
Scalable pattern recognition for large-scale scientific data mining
Kamath, C.; Musick, R.
1998-03-23
Our ability to generate data far outstrips our ability to explore and understand it. The true value of this data lies not in its final size or complexity, but rather in our ability to exploit the data to achieve scientific goals. The data generated by programs such as ASCI have such a large scale that it is impractical to manually analyze, explore, and understand it. As a result, useful information is overlooked, and the potential benefits of increased computational and data gathering capabilities are only partially realized. The difficulties that will be faced by ASCI applications in the near future are foreshadowed by the challenges currently facing astrophysicists in making full use of the data they have collected over the years. For example, among other difficulties, astrophysicists have expressed concern that the sheer size of their data restricts them to looking at very small, narrow portions at any one time. This narrow focus has resulted in the loss of ``serendipitous`` discoveries which have been so vital to progress in the area in the past. To solve this problem, a new generation of computational tools and techniques is needed to help automate the exploration and management of large scientific data. This whitepaper proposes applying and extending ideas from the area of data mining, in particular pattern recognition, to improve the way in which scientists interact with large, multi-dimensional, time-varying data.
HTS cables open the window for large-scale renewables
NASA Astrophysics Data System (ADS)
Geschiere, A.; Willén, D.; Piga, E.; Barendregt, P.
2008-02-01
In a realistic approach to future energy consumption, the effects of sustainable power sources and the effects of growing welfare with increased use of electricity need to be considered. These factors lead to an increased transfer of electric energy over the networks. A dominant part of the energy need will come from expanded large-scale renewable sources. To use them efficiently over Europe, large energy transits between different countries are required. Bottlenecks in the existing infrastructure will be avoided by strengthening the network. For environmental reasons more infrastructure will be built underground. Nuon is studying the HTS technology as a component to solve these challenges. This technology offers a tremendously large power transport capacity as well as the possibility to reduce short circuit currents, making integration of renewables easier. Furthermore, power transport will be possible at lower voltage levels, giving the opportunity to upgrade the existing network while re-using it. This will result in large cost savings while reaching the future energy challenges. In a 6 km backbone structure in Amsterdam Nuon wants to install a 50 kV HTS Triax cable for a significant increase of the transport capacity, while developing its capabilities. Nevertheless several barriers have to be overcome.
Large-scale magnetic fields, dark energy, and QCD
Urban, Federico R.; Zhitnitsky, Ariel R.
2010-08-15
Cosmological magnetic fields are being observed with ever increasing correlation lengths, possibly reaching the size of superclusters, therefore disfavoring the conventional picture of generation through primordial seeds later amplified by galaxy-bound dynamo mechanisms. In this paper we put forward a fundamentally different approach that links such large-scale magnetic fields to the cosmological vacuum energy. In our scenario the dark energy is due to the Veneziano ghost (which solves the U(1){sub A} problem in QCD). The Veneziano ghost couples through the triangle anomaly to the electromagnetic field with a constant which is unambiguously fixed in the standard model. While this interaction does not produce any physical effects in Minkowski space, it triggers the generation of a magnetic field in an expanding universe at every epoch. The induced energy of the magnetic field is thus proportional to cosmological vacuum energy: {rho}{sub EM{approx_equal}}B{sup 2{approx_equal}}(({alpha}/4{pi})){sup 2{rho}}{sub DE}, {rho}{sub DE} hence acting as a source for the magnetic energy {rho}{sub EM}. The corresponding numerical estimate leads to a magnitude in the nG range. There are two unique and distinctive predictions of our proposal: an uninterrupted active generation of Hubble size correlated magnetic fields throughout the evolution of the Universe; the presence of parity violation on the enormous scales 1/H, which apparently has been already observed in CMB. These predictions are entirely rooted into the standard model of particle physics.
Implicit solvers for large-scale nonlinear problems
Keyes, D E; Reynolds, D; Woodward, C S
2006-07-13
Computational scientists are grappling with increasingly complex, multi-rate applications that couple such physical phenomena as fluid dynamics, electromagnetics, radiation transport, chemical and nuclear reactions, and wave and material propagation in inhomogeneous media. Parallel computers with large storage capacities are paving the way for high-resolution simulations of coupled problems; however, hardware improvements alone will not prove enough to enable simulations based on brute-force algorithmic approaches. To accurately capture nonlinear couplings between dynamically relevant phenomena, often while stepping over rapid adjustments to quasi-equilibria, simulation scientists are increasingly turning to implicit formulations that require a discrete nonlinear system to be solved for each time step or steady state solution. Recent advances in iterative methods have made fully implicit formulations a viable option for solution of these large-scale problems. In this paper, we overview one of the most effective iterative methods, Newton-Krylov, for nonlinear systems and point to software packages with its implementation. We illustrate the method with an example from magnetically confined plasma fusion and briefly survey other areas in which implicit methods have bestowed important advantages, such as allowing high-order temporal integration and providing a pathway to sensitivity analyses and optimization. Lastly, we overview algorithm extensions under development motivated by current SciDAC applications.
Limitations and tradeoffs in synchronization of large-scale networks with uncertain links
NASA Astrophysics Data System (ADS)
Diwadkar, Amit; Vaidya, Umesh
2016-04-01
The synchronization of nonlinear systems connected over large-scale networks has gained popularity in a variety of applications, such as power grids, sensor networks, and biology. Stochastic uncertainty in the interconnections is a ubiquitous phenomenon observed in these physical and biological networks. We provide a size-independent network sufficient condition for the synchronization of scalar nonlinear systems with stochastic linear interactions over large-scale networks. This sufficient condition, expressed in terms of nonlinear dynamics, the Laplacian eigenvalues of the nominal interconnections, and the variance and location of the stochastic uncertainty, allows us to define a synchronization margin. We provide an analytical characterization of important trade-offs between the internal nonlinear dynamics, network topology, and uncertainty in synchronization. For nearest neighbour networks, the existence of an optimal number of neighbours with a maximum synchronization margin is demonstrated. An analytical formula for the optimal gain that produces the maximum synchronization margin allows us to compare the synchronization properties of various complex network topologies.
Limitations and tradeoffs in synchronization of large-scale networks with uncertain links
Diwadkar, Amit; Vaidya, Umesh
2016-01-01
The synchronization of nonlinear systems connected over large-scale networks has gained popularity in a variety of applications, such as power grids, sensor networks, and biology. Stochastic uncertainty in the interconnections is a ubiquitous phenomenon observed in these physical and biological networks. We provide a size-independent network sufficient condition for the synchronization of scalar nonlinear systems with stochastic linear interactions over large-scale networks. This sufficient condition, expressed in terms of nonlinear dynamics, the Laplacian eigenvalues of the nominal interconnections, and the variance and location of the stochastic uncertainty, allows us to define a synchronization margin. We provide an analytical characterization of important trade-offs between the internal nonlinear dynamics, network topology, and uncertainty in synchronization. For nearest neighbour networks, the existence of an optimal number of neighbours with a maximum synchronization margin is demonstrated. An analytical formula for the optimal gain that produces the maximum synchronization margin allows us to compare the synchronization properties of various complex network topologies. PMID:27067994
Suppression of a laminar kinematic dynamo by a prescribed large-scale shear
NASA Astrophysics Data System (ADS)
Sood, Aditi; Hollerbach, Rainer; Kim, Eun-jin
2016-10-01
We numerically solve the magnetic induction equation in a spherical shell geometry, with a kinematically prescribed axisymmetric flow that consists of a superposition of a small-scale helical flow and a large-scale shear flow. The small-scale flow is chosen to be a local analog of the classical Roberts cells, consisting of strongly helical vortex rolls. The large-scale flow is a shearing motion in either the radial or the latitudinal directions. In the absence of large-scale shear, the small-scale flow operates very effectively as a dynamo, in agreement with previous results. Adding increasingly large shear flows strongly suppresses the dynamo efficiency, indicating that shear is not always a favorable ingredient in dynamo action.
Performance modeling and analysis of consumer classes in large scale systems
NASA Astrophysics Data System (ADS)
Al-Shukri, Sh.; Lenin, R. B.; Ramaswamy, S.; Anand, A.; Narasimhan, V. L.; Abraham, J.; Varadan, Vijay
2009-03-01
Peer-to-Peer (P2P) networks have been used efficiently as building blocks as overlay networks for large-scale distributed network applications with Internet Protocol (IP) based bottom layer networks. With large scale Wireless Sensor Networks (WSNs) becoming increasingly realistic, it is important to overlay networks with WSNs in the bottom layer. The suitable mathematical (stochastic) model that can model the overlay network over WSNs is Queuing Networks with Multi-Class customers. In this paper, we discuss how these mathematical network models can be simulated using the object oriented simulation package OMNeT++. We discuss the Graphical User Interface (GUI) which is developed to accept the input parameter files and execute the simulation using this interface. We compare the simulation results with analytical formulas available in the literature for these mathematical models.
Safeguards instruments for Large-Scale Reprocessing Plants
Hakkila, E.A.; Case, R.S.; Sonnier, C.
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.
The Challenge of Large-Scale Literacy Improvement
ERIC Educational Resources Information Center
Levin, Ben
2010-01-01
This paper discusses the challenge of making large-scale improvements in literacy in schools across an entire education system. Despite growing interest and rhetoric, there are very few examples of sustained, large-scale change efforts around school-age literacy. The paper reviews 2 instances of such efforts, in England and Ontario. After…
NASA Astrophysics Data System (ADS)
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
Distribution probability of large-scale landslides in central Nepal
NASA Astrophysics Data System (ADS)
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.
Multi-period natural gas market modeling Applications, stochastic extensions and solution approaches
NASA Astrophysics Data System (ADS)
Egging, Rudolf Gerardus
This dissertation develops deterministic and stochastic multi-period mixed complementarity problems (MCP) for the global natural gas market, as well as solution approaches for large-scale stochastic MCP. The deterministic model is unique in the combination of the level of detail of the actors in the natural gas markets and the transport options, the detailed regional and global coverage, the multi-period approach with endogenous capacity expansions for transportation and storage infrastructure, the seasonal variation in demand and the representation of market power according to Nash-Cournot theory. The model is applied to several scenarios for the natural gas market that cover the formation of a cartel by the members of the Gas Exporting Countries Forum, a low availability of unconventional gas in the United States, and cost reductions in long-distance gas transportation. 1 The results provide insights in how different regions are affected by various developments, in terms of production, consumption, traded volumes, prices and profits of market participants. The stochastic MCP is developed and applied to a global natural gas market problem with four scenarios for a time horizon until 2050 with nineteen regions and containing 78,768 variables. The scenarios vary in the possibility of a gas market cartel formation and varying depletion rates of gas reserves in the major gas importing regions. Outcomes for hedging decisions of market participants show some significant shifts in the timing and location of infrastructure investments, thereby affecting local market situations. A first application of Benders decomposition (BD) is presented to solve a large-scale stochastic MCP for the global gas market with many hundreds of first-stage capacity expansion variables and market players exerting various levels of market power. The largest problem solved successfully using BD contained 47,373 variables of which 763 first-stage variables, however using BD did not result in
Numerical Technology for Large-Scale Computational Electromagnetics
Sharpe, R; Champagne, N; White, D; Stowell, M; Adams, R
2003-01-30
The key bottleneck of implicit computational electromagnetics tools for large complex geometries is the solution of the resulting linear system of equations. The goal of this effort was to research and develop critical numerical technology that alleviates this bottleneck for large-scale computational electromagnetics (CEM). The mathematical operators and numerical formulations used in this arena of CEM yield linear equations that are complex valued, unstructured, and indefinite. Also, simultaneously applying multiple mathematical modeling formulations to different portions of a complex problem (hybrid formulations) results in a mixed structure linear system, further increasing the computational difficulty. Typically, these hybrid linear systems are solved using a direct solution method, which was acceptable for Cray-class machines but does not scale adequately for ASCI-class machines. Additionally, LLNL's previously existing linear solvers were not well suited for the linear systems that are created by hybrid implicit CEM codes. Hence, a new approach was required to make effective use of ASCI-class computing platforms and to enable the next generation design capabilities. Multiple approaches were investigated, including the latest sparse-direct methods developed by our ASCI collaborators. In addition, approaches that combine domain decomposition (or matrix partitioning) with general-purpose iterative methods and special purpose pre-conditioners were investigated. Special-purpose pre-conditioners that take advantage of the structure of the matrix were adapted and developed based on intimate knowledge of the matrix properties. Finally, new operator formulations were developed that radically improve the conditioning of the resulting linear systems thus greatly reducing solution time. The goal was to enable the solution of CEM problems that are 10 to 100 times larger than our previous capability.
Polymer Physics of the Large-Scale Structure of Chromatin.
Bianco, Simona; Chiariello, Andrea Maria; Annunziatella, Carlo; Esposito, Andrea; Nicodemi, Mario
2016-01-01
We summarize the picture emerging from recently proposed models of polymer physics describing the general features of chromatin large scale spatial architecture, as revealed by microscopy and Hi-C experiments. PMID:27659986
Large-scale anisotropy of the cosmic microwave background radiation
NASA Technical Reports Server (NTRS)
Silk, J.; Wilson, M. L.
1981-01-01
Inhomogeneities in the large-scale distribution of matter inevitably lead to the generation of large-scale anisotropy in the cosmic background radiation. The dipole, quadrupole, and higher order fluctuations expected in an Einstein-de Sitter cosmological model have been computed. The dipole and quadrupole anisotropies are comparable to the measured values, and impose important constraints on the allowable spectrum of large-scale matter density fluctuations. A significant dipole anisotropy is generated by the matter distribution on scales greater than approximately 100 Mpc. The large-scale anisotropy is insensitive to the ionization history of the universe since decoupling, and cannot easily be reconciled with a galaxy formation theory that is based on primordial adiabatic density fluctuations.
Polymer Physics of the Large-Scale Structure of Chromatin.
Bianco, Simona; Chiariello, Andrea Maria; Annunziatella, Carlo; Esposito, Andrea; Nicodemi, Mario
2016-01-01
We summarize the picture emerging from recently proposed models of polymer physics describing the general features of chromatin large scale spatial architecture, as revealed by microscopy and Hi-C experiments.
Needs, opportunities, and options for large scale systems research
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.
Large scale anomalies in the microwave background: causation and correlation.
Aslanyan, Grigor; Easther, Richard
2013-12-27
Most treatments of large scale anomalies in the microwave sky are a posteriori, with unquantified look-elsewhere effects. We contrast these with physical models of specific inhomogeneities in the early Universe which can generate these apparent anomalies. Physical models predict correlations between candidate anomalies and the corresponding signals in polarization and large scale structure, reducing the impact of cosmic variance. We compute the apparent spatial curvature associated with large-scale inhomogeneities and show that it is typically small, allowing for a self-consistent analysis. As an illustrative example we show that a single large plane wave inhomogeneity can contribute to low-l mode alignment and odd-even asymmetry in the power spectra and the best-fit model accounts for a significant part of the claimed odd-even asymmetry. We argue that this approach can be generalized to provide a more quantitative assessment of potential large scale anomalies in the Universe.
Large-scale studies of marked birds in North America
Tautin, J.; Metras, L.; Smith, G.
1999-01-01
The first large-scale, co-operative, studies of marked birds in North America were attempted in the 1950s. Operation Recovery, which linked numerous ringing stations along the east coast in a study of autumn migration of passerines, and the Preseason Duck Ringing Programme in prairie states and provinces, conclusively demonstrated the feasibility of large-scale projects. The subsequent development of powerful analytical models and computing capabilities expanded the quantitative potential for further large-scale projects. Monitoring Avian Productivity and Survivorship, and Adaptive Harvest Management are current examples of truly large-scale programmes. Their exemplary success and the availability of versatile analytical tools are driving changes in the North American bird ringing programme. Both the US and Canadian ringing offices are modifying operations to collect more and better data to facilitate large-scale studies and promote a more project-oriented ringing programme. New large-scale programmes such as the Cornell Nest Box Network are on the horizon.
Large-scale motions in a plane wall jet
NASA Astrophysics Data System (ADS)
Gnanamanickam, Ebenezer; Jonathan, Latim; Shibani, Bhatt
2015-11-01
The dynamic significance of large-scale motions in turbulent boundary layers have been the focus of several recent studies, primarily focussing on canonical flows - zero pressure gradient boundary layers, flows within pipes and channels. This work presents an investigation into the large-scale motions in a boundary layer that is used as the prototypical flow field for flows with large-scale mixing and reactions, the plane wall jet. An experimental investigation is carried out in a plane wall jet facility designed to operate at friction Reynolds numbers Reτ > 1000 , which allows for the development of a significant logarithmic region. The streamwise turbulent intensity across the boundary layer is decomposed into small-scale (less than one integral length-scale δ) and large-scale components. The small-scale energy has a peak in the near-wall region associated with the near-wall turbulent cycle as in canonical boundary layers. However, eddies of large-scales are the dominating eddies having significantly higher energy, than the small-scales across almost the entire boundary layer even at the low to moderate Reynolds numbers under consideration. The large-scales also appear to amplitude and frequency modulate the smaller scales across the entire boundary layer.
NASA Technical Reports Server (NTRS)
Sobh, Nahil Atef
1992-01-01
A parallel Preconditioned Conjugate Gradient (PCG) iterative solver has been developed and implemented on the iPSC-860 scalable hypercube. This new implementation makes use of the Parallel Automated Runtime Toolkit at ICASE (PARTI) primitives to efficiently program irregular communications patterns that exist in general sparse matrices and in particular in the finite element sparse stiffness matrices. The iterative PCG has been used to solve the finite element equations that result from discretizing large scale aerospace structures. In particular, the static response of the High Speed Civil Transport (HSCT) finite element model is solved on the iPSC-860.
Cost Distribution of Environmental Flow Demands in a Large Scale Multi-Reservoir System
NASA Astrophysics Data System (ADS)
Marques, G.; Tilmant, A.
2014-12-01
This paper investigates the recovery of a prescribed flow regime through reservoir system reoperation, focusing on the associated costs and losses imposed on different power plants depending on flows, power plant and reservoir characteristics and systems topology. In large-scale reservoir systems such cost distribution is not trivial, and it should be properly evaluated to identify coordinated operating solutions that avoid penalizing a single reservoir. The methods combine an efficient stochastic dual dynamic programming algorithm for reservoir optimization subject to environmental flow targets with specific magnitude, duration and return period, which effects on fish recruitment are already known. Results indicate that the distribution of the effect of meeting the environmental flow demands throughout the reservoir cascade differs largely, and in some reservoirs power production and revenue are increased, while in others it is reduced. Most importantly, for the example system modeled here (10 reservoirs in the Parana River basin, Brazil) meeting the target environmental flows was possible without reducing the total energy produced in the year, at a cost of $25 Million/year in foregone hydropower revenues (3% reduction). Finally, the results and methods are useful in (a) quantifying the foregone hydropower and revenues resulting from meeting a specific environmental flow demand, (b) identifying the distribution and reallocation of the foregone hydropower and revenue across a large scale system, and (c) identifying optimal reservoir operating strategies to meet environmental flow demands in a large scale multi-reservoir system.
Towards a self-consistent halo model for the nonlinear large-scale structure
NASA Astrophysics Data System (ADS)
Schmidt, Fabian
2016-03-01
The halo model is a theoretically and empirically well-motivated framework for predicting the statistics of the nonlinear matter distribution in the Universe. However, current incarnations of the halo model suffer from two major deficiencies: (i) they do not enforce the stress-energy conservation of matter; (ii) they are not guaranteed to recover exact perturbation theory results on large scales. Here, we provide a formulation of the halo model (EHM) that remedies both drawbacks in a consistent way, while attempting to maintain the predictivity of the approach. In the formulation presented here, mass and momentum conservation are guaranteed on large scales, and results of the perturbation theory and the effective field theory can, in principle, be matched to any desired order on large scales. We find that a key ingredient in the halo model power spectrum is the halo stochasticity covariance, which has been studied to a much lesser extent than other ingredients such as mass function, bias, and profiles of halos. As written here, this approach still does not describe the transition regime between perturbation theory and halo scales realistically, which is left as an open problem. We also show explicitly that, when implemented consistently, halo model predictions do not depend on any properties of low-mass halos that are smaller than the scales of interest.
NASA Astrophysics Data System (ADS)
Aranson, Igor
2006-03-01
We consider two biological systems of active particles exhibiting large-scale collective behavior: microtubules interacting with molecular motors and hydrodynamically entrained swimming bacteria. Starting from a generic stochastic microscopic model of inelastically colliding polar rods with an anisotropic interaction kernel, we derive set of equations for the local rods concentration and orientation. Above certain critical density of rods the model exhibits orientational instability and onset of large-scale coherence. For the microtubules and molecular motors system we demonstrate that the orientational instability leads to the formation of vortices and asters seen in recent experiments. Similar approach is applied to colonies of swimming bacteria Bacillus subtilis confined in thin fluid film. The model is formulated in term of two-dimensional equations for local density and orientation of bacteria coupled to the low Reynolds number Navier-Stokes equation for the fluid flow velocity. The collective swimming of bacteria is represented by additional source term in the Navier-Stokes equation. We demonstrate that this system exhibits formation of dynamic large-scale patterns with the typical scale determined by the density of bacteria.
Large-scale-circulation dynamics of turbulent Rayleigh-Benard convection in a cubic container
NASA Astrophysics Data System (ADS)
Bai, Kunlun; Ji, Dandan; Brown, Eric
2014-11-01
We present measurements of the large-scale-circulation (LSC) in turbulent Rayleigh-Benard convection in a cubic container. The experiments cover the Rayleigh number ranging from 0 . 5 ×109 to 3 ×109 at Prandtl number 6.4. Using three rows of thermistors at different height of the container, the large-scale-circulation (LSC) can then be identified. It is found that the LSC prefers to lock at the corners of the container, and switches between them stochastically. The strength of LSC keeps as a constant during the switching which suggests those switching correspond to fluctuation driven crossings of a potential barrier in θ due to the side wall geometry as predicted by Brown and Ahlers (Phys. Fluids, 2008). The switching frequency is found to decrease as Ra increases. The measured LSC orientation and its switching will be compared to the model which predicts the effects of container geometry on large-scale coherent structure dynamics for arbitrary geometry.
Large-scale derived flood frequency analysis based on continuous simulation
NASA Astrophysics Data System (ADS)
Dung Nguyen, Viet; Hundecha, Yeshewatesfa; Guse, Björn; Vorogushyn, Sergiy; Merz, Bruno
2016-04-01
There is an increasing need for spatially consistent flood risk assessments at the regional scale (several 100.000 km2), in particular in the insurance industry and for national risk reduction strategies. However, most large-scale flood risk assessments are composed of smaller-scale assessments and show spatial inconsistencies. To overcome this deficit, a large-scale flood model composed of a weather generator and catchments models was developed reflecting the spatially inherent heterogeneity. The weather generator is a multisite and multivariate stochastic model capable of generating synthetic meteorological fields (precipitation, temperature, etc.) at daily resolution for the regional scale. These fields respect the observed autocorrelation, spatial correlation and co-variance between the variables. They are used as input into catchment models. A long-term simulation of this combined system enables to derive very long discharge series at many catchment locations serving as a basic for spatially consistent flood risk estimates at the regional scale. This combined model was set up and validated for major river catchments in Germany. The weather generator was trained by 53-year observation data at 528 stations covering not only the complete Germany but also parts of France, Switzerland, Czech Republic and Australia with the aggregated spatial scale of 443,931 km2. 10.000 years of daily meteorological fields for the study area were generated. Likewise, rainfall-runoff simulations with SWIM were performed for the entire Elbe, Rhine, Weser, Donau and Ems catchments. The validation results illustrate a good performance of the combined system, as the simulated flood magnitudes and frequencies agree well with the observed flood data. Based on continuous simulation this model chain is then used to estimate flood quantiles for the whole Germany including upstream headwater catchments in neighbouring countries. This continuous large scale approach overcomes the several
Final Report: Large-Scale Optimization for Bayesian Inference in Complex Systems
Ghattas, Omar
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.
EINSTEIN'S SIGNATURE IN COSMOLOGICAL LARGE-SCALE STRUCTURE
Bruni, Marco; Hidalgo, Juan Carlos; Wands, David
2014-10-10
We show how the nonlinearity of general relativity generates a characteristic nonGaussian signal in cosmological large-scale structure that we calculate at all perturbative orders in a large-scale limit. Newtonian gravity and general relativity provide complementary theoretical frameworks for modeling large-scale structure in ΛCDM cosmology; a relativistic approach is essential to determine initial conditions, which can then be used in Newtonian simulations studying the nonlinear evolution of the matter density. Most inflationary models in the very early universe predict an almost Gaussian distribution for the primordial metric perturbation, ζ. However, we argue that it is the Ricci curvature of comoving-orthogonal spatial hypersurfaces, R, that drives structure formation at large scales. We show how the nonlinear relation between the spatial curvature, R, and the metric perturbation, ζ, translates into a specific nonGaussian contribution to the initial comoving matter density that we calculate for the simple case of an initially Gaussian ζ. Our analysis shows the nonlinear signature of Einstein's gravity in large-scale structure.
Cosmology from Cosmic Microwave Background and large- scale structure
NASA Astrophysics Data System (ADS)
Xu, Yongzhong
2003-10-01
This dissertation consists of a series of studies, constituting four published papers, involving the Cosmic Microwave Background and the large scale structure, which help constrain Cosmological parameters and potential systematic errors. First, we present a method for comparing and combining maps with different resolutions and beam shapes, and apply it to the Saskatoon, QMAP and COBE/DMR data sets. Although the Saskatoon and QMAP maps detect signal at the 21σ and 40σ, levels, respectively, their difference is consistent with pure noise, placing strong limits on possible systematic errors. In particular, we obtain quantitative upper limits on relative calibration and pointing errors. Splitting the combined data by frequency shows similar consistency between the Ka- and Q-bands, placing limits on foreground contamination. The visual agreement between the maps is equally striking. Our combined QMAP+Saskatoon map, nicknamed QMASK, is publicly available at www.hep.upenn.edu/˜xuyz/qmask.html together with its 6495 x 6495 noise covariance matrix. This thoroughly tested data set covers a large enough area (648 square degrees—at the time, the largest degree-scale map available) to allow a statistical comparison with LOBE/DMR, showing good agreement. By band-pass-filtering the QMAP and Saskatoon maps, we are also able to spatially compare them scale-by-scale to check for beam- and pointing-related systematic errors. Using the QMASK map, we then measure the cosmic microwave background (CMB) power spectrum on angular scales ℓ ˜ 30 200 (1° 6°), and we test it for non-Gaussianity using morphological statistics known as Minkowski functionals. We conclude that the QMASK map is neither a very typical nor a very exceptional realization of a Gaussian random field. At least about 20% of the 1000 Gaussian Monte Carlo maps differ more than the QMASK map from the mean morphological parameters of the Gaussian fields. Finally, we compute the real-space power spectrum and the
Classification of large-scale stellar spectra based on the non-linearly assembling learning machine
NASA Astrophysics Data System (ADS)
Liu, Zhongbao; Song, Lipeng; Zhao, Wenjuan
2016-02-01
An important problem to be solved of traditional classification methods is they cannot deal with large-scale classification because of very high time complexity. In order to solve above problem, inspired by the thinking of collaborative management, the non-linearly assembling learning machine (NALM) is proposed and used in the large-scale stellar spectral classification. In NALM, the large-scale dataset is firstly divided into several subsets, and then the traditional classifiers such as support vector machine (SVM) runs on the subset, finally, the classification results on each subset are assembled and the overall classification decision is obtained. In comparative experiments, we investigate the performance of NALM in the stellar spectral subclasses classification compared with SVM. We apply SVM and NALM respectively to classify the four subclasses of K-type spectra, three subclasses of F-type spectra and three subclasses of G-type spectra from Sloan Digital Sky Survey (SDSS). The comparative experiment results show that the performance of NALM is much better than SVM in view of the classification accuracy and the computation time.
Toward Improved Support for Loosely Coupled Large Scale Simulation Workflows
Boehm, Swen; Elwasif, Wael R; Naughton, III, Thomas J; Vallee, Geoffroy R
2014-01-01
High-performance computing (HPC) workloads are increasingly leveraging loosely coupled large scale simula- tions. Unfortunately, most large-scale HPC platforms, including Cray/ALPS environments, are designed for the execution of long-running jobs based on coarse-grained launch capabilities (e.g., one MPI rank per core on all allocated compute nodes). This assumption limits capability-class workload campaigns that require large numbers of discrete or loosely coupled simulations, and where time-to-solution is an untenable pacing issue. This paper describes the challenges related to the support of fine-grained launch capabilities that are necessary for the execution of loosely coupled large scale simulations on Cray/ALPS platforms. More precisely, we present the details of an enhanced runtime system to support this use case, and report on initial results from early testing on systems at Oak Ridge National Laboratory.
Do Large-Scale Topological Features Correlate with Flare Properties?
NASA Astrophysics Data System (ADS)
DeRosa, Marc L.; Barnes, Graham
2016-05-01
In this study, we aim to identify whether the presence or absence of particular topological features in the large-scale coronal magnetic field are correlated with whether a flare is confined or eruptive. To this end, we first determine the locations of null points, spine lines, and separatrix surfaces within the potential fields associated with the locations of several strong flares from the current and previous sunspot cycles. We then validate the topological skeletons against large-scale features in observations, such as the locations of streamers and pseudostreamers in coronagraph images. Finally, we characterize the topological environment in the vicinity of the flaring active regions and identify the trends involving their large-scale topologies and the properties of the associated flares.
Acoustic Studies of the Large Scale Ocean Circulation
NASA Technical Reports Server (NTRS)
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.
A relativistic signature in large-scale structure
NASA Astrophysics Data System (ADS)
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.
Coupling between convection and large-scale circulation
NASA Astrophysics Data System (ADS)
Becker, T.; Stevens, B. B.; Hohenegger, C.
2014-12-01
The ultimate drivers of convection - radiation, tropospheric humidity and surface fluxes - are altered both by the large-scale circulation and by convection itself. A quantity to which all drivers of convection contribute is moist static energy, or gross moist stability, respectively. Therefore, a variance analysis of the moist static energy budget in radiative-convective equilibrium helps understanding the interaction of precipitating convection and the large-scale environment. In addition, this method provides insights concerning the impact of convective aggregation on this coupling. As a starting point, the interaction is analyzed with a general circulation model, but a model intercomparison study using a hierarchy of models is planned. Effective coupling parameters will be derived from cloud resolving models and these will in turn be related to assumptions used to parameterize convection in large-scale models.
Human pescadillo induces large-scale chromatin unfolding.
Zhang, Hao; Fang, Yan; Huang, Cuifen; Yang, Xiao; Ye, Qinong
2005-06-01
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.
Magnetic Helicity and Large Scale Magnetic Fields: A Primer
NASA Astrophysics Data System (ADS)
Blackman, Eric G.
2015-05-01
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. Here I discuss how magnetic helicity has come to help us understand the saturation of and sustenance of large scale dynamos, the need for either local or global helicity fluxes to avoid dynamo quenching, and the associated observational consequences. I also discuss how magnetic helicity acts as a hindrance to turbulent diffusion of large scale fields, and thus a helper for fossil remnant large scale field origin models in some contexts. I briefly discuss the connection between large scale fields and accretion disk theory as well. The goal here is to provide a conceptual primer to help the reader efficiently penetrate the literature.
A survey on routing protocols for large-scale wireless sensor networks.
Li, Changle; Zhang, Hanxiao; Hao, Binbin; Li, Jiandong
2011-01-01
With the advances in micro-electronics, wireless sensor devices have been made much smaller and more integrated, and large-scale wireless sensor networks (WSNs) based the cooperation among the significant amount of nodes have become a hot topic. "Large-scale" means mainly large area or high density of a network. Accordingly the routing protocols must scale well to the network scope extension and node density increases. A sensor node is normally energy-limited and cannot be recharged, and thus its energy consumption has a quite significant effect on the scalability of the protocol. To the best of our knowledge, currently the mainstream methods to solve the energy problem in large-scale WSNs are the hierarchical routing protocols. In a hierarchical routing protocol, all the nodes are divided into several groups with different assignment levels. The nodes within the high level are responsible for data aggregation and management work, and the low level nodes for sensing their surroundings and collecting information. The hierarchical routing protocols are proved to be more energy-efficient than flat ones in which all the nodes play the same role, especially in terms of the data aggregation and the flooding of the control packets. With focus on the hierarchical structure, in this paper we provide an insight into routing protocols designed specifically for large-scale WSNs. According to the different objectives, the protocols are generally classified based on different criteria such as control overhead reduction, energy consumption mitigation and energy balance. In order to gain a comprehensive understanding of each protocol, we highlight their innovative ideas, describe the underlying principles in detail and analyze their advantages and disadvantages. Moreover a comparison of each routing protocol is conducted to demonstrate the differences between the protocols in terms of message complexity, memory requirements, localization, data aggregation, clustering manner and
Clearing and Labeling Techniques for Large-Scale Biological Tissues
Seo, Jinyoung; Choe, Minjin; Kim, Sung-Yon
2016-01-01
Clearing and labeling techniques for large-scale biological tissues enable simultaneous extraction of molecular and structural information with minimal disassembly of the sample, facilitating the integration of molecular, cellular and systems biology across different scales. Recent years have witnessed an explosive increase in the number of such methods and their applications, reflecting heightened interest in organ-wide clearing and labeling across many fields of biology and medicine. In this review, we provide an overview and comparison of existing clearing and labeling techniques and discuss challenges and opportunities in the investigations of large-scale biological systems. PMID:27239813
Corridors Increase Plant Species Richness at Large Scales
Damschen, Ellen I.; Haddad, Nick M.; Orrock,John L.; Tewksbury, Joshua J.; Levey, Douglas J.
2006-09-01
Habitat fragmentation is one of the largest threats to biodiversity. Landscape corridors, which are hypothesized to reduce the negative consequences of fragmentation, have become common features of ecological management plans worldwide. Despite their popularity, there is little evidence documenting the effectiveness of corridors in preserving biodiversity at large scales. Using a large-scale replicated experiment, we showed that habitat patches connected by corridors retain more native plant species than do isolated patches, that this difference increases over time, and that corridors do not promote invasion by exotic species. Our results support the use of corridors in biodiversity conservation.
Large-scale superfluid vortex rings at nonzero temperatures
NASA Astrophysics Data System (ADS)
Wacks, D. H.; Baggaley, A. W.; Barenghi, C. F.
2014-12-01
We numerically model experiments in which large-scale vortex rings—bundles of quantized vortex loops—are created in superfluid helium by a piston-cylinder arrangement. We show that the presence of a normal-fluid vortex ring together with the quantized vortices is essential to explain the coherence of these large-scale vortex structures at nonzero temperatures, as observed experimentally. Finally we argue that the interaction of superfluid and normal-fluid vortex bundles is relevant to recent investigations of superfluid turbulence.
NASA Technical Reports Server (NTRS)
Dahl, Milo D.; Hixon, Ray; Mankbadi, Reda R.
2003-01-01
An approximate technique is presented for the prediction of the large-scale turbulent structure sound source in a supersonic jet. A linearized Euler equations code is used to solve for the flow disturbances within and near a jet with a given mean flow. Assuming a normal mode composition for the wave-like disturbances, the linear radial profiles are used in an integration of the Navier-Stokes equations. This results in a set of ordinary differential equations representing the weakly nonlinear self-interactions of the modes along with their interaction with the mean flow. Solutions are then used to correct the amplitude of the disturbances that represent the source of large-scale turbulent structure sound in the jet.
Supercomputer optimizations for stochastic optimal control applications
NASA Technical Reports Server (NTRS)
Chung, Siu-Leung; Hanson, Floyd B.; Xu, Huihuang
1991-01-01
Supercomputer optimizations for a computational method of solving stochastic, multibody, dynamic programming problems are presented. The computational method is valid for a general class of optimal control problems that are nonlinear, multibody dynamical systems, perturbed by general Markov noise in continuous time, i.e., nonsmooth Gaussian as well as jump Poisson random white noise. Optimization techniques for vector multiprocessors or vectorizing supercomputers include advanced data structures, loop restructuring, loop collapsing, blocking, and compiler directives. These advanced computing techniques and superconducting hardware help alleviate Bellman's curse of dimensionality in dynamic programming computations, by permitting the solution of large multibody problems. Possible applications include lumped flight dynamics models for uncertain environments, such as large scale and background random aerospace fluctuations.
Stochastic competitive learning in complex networks.
Silva, Thiago Christiano; Zhao, Liang
2012-03-01
Competitive learning is an important machine learning approach which is widely employed in artificial neural networks. In this paper, we present a rigorous definition of a new type of competitive learning scheme realized on large-scale networks. The model consists of several particles walking within the network and competing with each other to occupy as many nodes as possible, while attempting to reject intruder particles. The particle's walking rule is composed of a stochastic combination of random and preferential movements. The model has been applied to solve community detection and data clustering problems. Computer simulations reveal that the proposed technique presents high precision of community and cluster detections, as well as low computational complexity. Moreover, we have developed an efficient method for estimating the most likely number of clusters by using an evaluator index that monitors the information generated by the competition process itself. We hope this paper will provide an alternative way to the study of competitive learning..
Large-Scale Machine Learning for Classification and Search
ERIC Educational Resources Information Center
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
ERIC Educational Resources Information Center
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…
The Large-Scale Structure of Scientific Method
ERIC Educational Resources Information Center
Kosso, Peter
2009-01-01
The standard textbook description of the nature of science describes the proposal, testing, and acceptance of a theoretical idea almost entirely in isolation from other theories. The resulting model of science is a kind of piecemeal empiricism that misses the important network structure of scientific knowledge. Only the large-scale description of…
Potential and issues in large scale flood inundation modelling
NASA Astrophysics Data System (ADS)
Di Baldassarre, Giuliano; Brandimarte, Luigia; Dottori, Francesco; Mazzoleni, Maurizio; Yan, Kun
2015-04-01
The last years have seen a growing research interest on large scale flood inundation modelling. Nowadays, modelling tools and datasets allow for analyzing flooding processes at regional, continental and even global scale with an increasing level of detail. As a result, several research works have already addressed this topic using different methodologies of varying complexity. The potential of these studies is certainly enormous. Large scale flood inundation modelling can provide valuable information in areas where few information and studies were previously available. They can provide a consistent framework for a comprehensive assessment of flooding processes in the river basins of world's large rivers, as well as impacts of future climate scenarios. To make the most of such a potential, we believe it is necessary, on the one hand, to understand strengths and limitations of the existing methodologies, and on the other hand, to discuss possibilities and implications of using large scale flood models for operational flood risk assessment and management. Where should researchers put their effort, in order to develop useful and reliable methodologies and outcomes? How the information coming from large scale flood inundation studies can be used by stakeholders? How should we use this information where previous higher resolution studies exist, or where official studies are available?
Global smoothing and continuation for large-scale molecular optimization
More, J.J.; Wu, Zhijun
1995-10-01
We discuss the formulation of optimization problems that arise in the study of distance geometry, ionic systems, and molecular clusters. We show that continuation techniques based on global smoothing are applicable to these molecular optimization problems, and we outline the issues that must be resolved in the solution of large-scale molecular optimization problems.
DESIGN OF LARGE-SCALE AIR MONITORING NETWORKS
The potential effects of air pollution on human health have received much attention in recent years. In the U.S. and other countries, there are extensive large-scale monitoring networks designed to collect data to inform the public of exposure risks to air pollution. A major crit...
International Large-Scale Assessments: What Uses, What Consequences?
ERIC Educational Resources Information Center
Johansson, Stefan
2016-01-01
Background: International large-scale assessments (ILSAs) are a much-debated phenomenon in education. Increasingly, their outcomes attract considerable media attention and influence educational policies in many jurisdictions worldwide. The relevance, uses and consequences of these assessments are often the focus of research scrutiny. Whilst some…
Large Scale Survey Data in Career Development Research
ERIC Educational Resources Information Center
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…
Current Scientific Issues in Large Scale Atmospheric Dynamics
NASA Technical Reports Server (NTRS)
Miller, T. L. (Compiler)
1986-01-01
Topics in large scale atmospheric dynamics are discussed. Aspects of atmospheric blocking, the influence of transient baroclinic eddies on planetary-scale waves, cyclogenesis, the effects of orography on planetary scale flow, small scale frontal structure, and simulations of gravity waves in frontal zones are discussed.
Large-scale drift and Rossby wave turbulence
NASA Astrophysics Data System (ADS)
Harper, K. L.; Nazarenko, S. V.
2016-08-01
We study drift/Rossby wave turbulence described by the large-scale limit of the Charney–Hasegawa–Mima equation. We define the zonal and meridional regions as Z:= \\{{k} :| {k}y| \\gt \\sqrt{3}{k}x\\} and M:= \\{{k} :| {k}y| \\lt \\sqrt{3}{k}x\\} respectively, where {k}=({k}x,{k}y) is in a plane perpendicular to the magnetic field such that k x is along the isopycnals and k y is along the plasma density gradient. We prove that the only types of resonant triads allowed are M≤ftrightarrow M+Z and Z≤ftrightarrow Z+Z. Therefore, if the spectrum of weak large-scale drift/Rossby turbulence is initially in Z it will remain in Z indefinitely. We present a generalised Fjørtoft’s argument to find transfer directions for the quadratic invariants in the two-dimensional {k}-space. Using direct numerical simulations, we test and confirm our theoretical predictions for weak large-scale drift/Rossby turbulence, and establish qualitative differences with cases when turbulence is strong. We demonstrate that the qualitative features of the large-scale limit survive when the typical turbulent scale is only moderately greater than the Larmor/Rossby radius.
Moon-based Earth Observation for Large Scale Geoscience Phenomena
NASA Astrophysics Data System (ADS)
Guo, Huadong; Liu, Guang; Ding, Yixing
2016-07-01
The capability of Earth observation for large-global-scale natural phenomena needs to be improved and new observing platform are expected. We have studied the concept of Moon as an Earth observation in these years. Comparing with manmade satellite platform, Moon-based Earth observation can obtain multi-spherical, full-band, active and passive information,which is of following advantages: large observation range, variable view angle, long-term continuous observation, extra-long life cycle, with the characteristics of longevity ,consistency, integrity, stability and uniqueness. Moon-based Earth observation is suitable for monitoring the large scale geoscience phenomena including large scale atmosphere change, large scale ocean change,large scale land surface dynamic change,solid earth dynamic change,etc. For the purpose of establishing a Moon-based Earth observation platform, we already have a plan to study the five aspects as follows: mechanism and models of moon-based observing earth sciences macroscopic phenomena; sensors' parameters optimization and methods of moon-based Earth observation; site selection and environment of moon-based Earth observation; Moon-based Earth observation platform; and Moon-based Earth observation fundamental scientific framework.
Large-scale drift and Rossby wave turbulence
NASA Astrophysics Data System (ADS)
Harper, K. L.; Nazarenko, S. V.
2016-08-01
We study drift/Rossby wave turbulence described by the large-scale limit of the Charney-Hasegawa-Mima equation. We define the zonal and meridional regions as Z:= \\{{k} :| {k}y| \\gt \\sqrt{3}{k}x\\} and M:= \\{{k} :| {k}y| \\lt \\sqrt{3}{k}x\\} respectively, where {k}=({k}x,{k}y) is in a plane perpendicular to the magnetic field such that k x is along the isopycnals and k y is along the plasma density gradient. We prove that the only types of resonant triads allowed are M≤ftrightarrow M+Z and Z≤ftrightarrow Z+Z. Therefore, if the spectrum of weak large-scale drift/Rossby turbulence is initially in Z it will remain in Z indefinitely. We present a generalised Fjørtoft’s argument to find transfer directions for the quadratic invariants in the two-dimensional {k}-space. Using direct numerical simulations, we test and confirm our theoretical predictions for weak large-scale drift/Rossby turbulence, and establish qualitative differences with cases when turbulence is strong. We demonstrate that the qualitative features of the large-scale limit survive when the typical turbulent scale is only moderately greater than the Larmor/Rossby radius.
A bibliographical surveys of large-scale systems
NASA Technical Reports Server (NTRS)
Corliss, W. R.
1970-01-01
A limited, partly annotated bibliography was prepared on the subject of large-scale system control. Approximately 400 references are divided into thirteen application areas, such as large societal systems and large communication systems. A first-author index is provided.
Resilience of Florida Keys coral communities following large scale disturbances
The decline of coral reefs in the Caribbean over the last 40 years has been attributed to multiple chronic stressors and episodic large-scale disturbances. This study assessed the resilience of coral communities in two different regions of the Florida Keys reef system between 199...
Lessons from Large-Scale Renewable Energy Integration Studies: Preprint
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.
Large-Scale Networked Virtual Environments: Architecture and Applications
ERIC Educational Resources Information Center
Lamotte, Wim; Quax, Peter; Flerackers, Eddy
2008-01-01
Purpose: Scalability is an important research topic in the context of networked virtual environments (NVEs). This paper aims to describe the ALVIC (Architecture for Large-scale Virtual Interactive Communities) approach to NVE scalability. Design/methodology/approach: The setup and results from two case studies are shown: a 3-D learning environment…
Large-scale data analysis using the Wigner function
NASA Astrophysics Data System (ADS)
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.
Ecosystem resilience despite large-scale altered hydro climatic conditions
Technology Transfer Automated Retrieval System (TEKTRAN)
Climate change is predicted to increase both drought frequency and duration, and when coupled with substantial warming, will establish a new hydroclimatological paradigm for many regions. Large-scale, warm droughts have recently impacted North America, Africa, Europe, Amazonia, and Australia result...
Large-scale societal changes and intentionality - an uneasy marriage.
Bodor, Péter; Fokas, Nikos
2014-08-01
Our commentary focuses on juxtaposing the proposed science of intentional change with facts and concepts pertaining to the level of large populations or changes on a worldwide scale. Although we find a unified evolutionary theory promising, we think that long-term and large-scale, scientifically guided - that is, intentional - social change is not only impossible, but also undesirable. PMID:25162863
Implicit solution of large-scale radiation diffusion problems
Brown, P N; Graziani, F; Otero, I; Woodward, C S
2001-01-04
In this paper, we present an efficient solution approach for fully implicit, large-scale, nonlinear radiation diffusion problems. The fully implicit approach is compared to a semi-implicit solution method. Accuracy and efficiency are shown to be better for the fully implicit method on both one- and three-dimensional problems with tabular opacities taken from the LEOS opacity library.
Mixing Metaphors: Building Infrastructure for Large Scale School Turnaround
ERIC Educational Resources Information Center
Peurach, Donald J.; Neumerski, Christine M.
2015-01-01
The purpose of this analysis is to increase understanding of the possibilities and challenges of building educational infrastructure--the basic, foundational structures, systems, and resources--to support large-scale school turnaround. Building educational infrastructure often exceeds the capacity of schools, districts, and state education…
Simulation and Analysis of Large-Scale Compton Imaging Detectors
Manini, H A; Lange, D J; Wright, D M
2006-12-27
We perform simulations of two types of large-scale Compton imaging detectors. The first type uses silicon and germanium detector crystals, and the second type uses silicon and CdZnTe (CZT) detector crystals. The simulations use realistic detector geometry and parameters. We analyze the performance of each type of detector, and we present results using receiver operating characteristics (ROC) curves.
US National Large-scale City Orthoimage Standard Initiative
Zhou, G.; Song, C.; Benjamin, S.; Schickler, W.
2003-01-01
The early procedures and algorithms for National digital orthophoto generation in National Digital Orthophoto Program (NDOP) were based on earlier USGS mapping operations, such as field control, aerotriangulation (derived in the early 1920's), the quarter-quadrangle-centered (3.75 minutes of longitude and latitude in geographic extent), 1:40,000 aerial photographs, and 2.5 D digital elevation models. However, large-scale city orthophotos using early procedures have disclosed many shortcomings, e.g., ghost image, occlusion, shadow. Thus, to provide the technical base (algorithms, procedure) and experience needed for city large-scale digital orthophoto creation is essential for the near future national large-scale digital orthophoto deployment and the revision of the Standards for National Large-scale City Digital Orthophoto in National Digital Orthophoto Program (NDOP). This paper will report our initial research results as follows: (1) High-precision 3D city DSM generation through LIDAR data processing, (2) Spatial objects/features extraction through surface material information and high-accuracy 3D DSM data, (3) 3D city model development, (4) Algorithm development for generation of DTM-based orthophoto, and DBM-based orthophoto, (5) True orthophoto generation by merging DBM-based orthophoto and DTM-based orthophoto, and (6) Automatic mosaic by optimizing and combining imagery from many perspectives.
Considerations for Managing Large-Scale Clinical Trials.
ERIC Educational Resources Information Center
Tuttle, Waneta C.; And Others
1989-01-01
Research management strategies used effectively in a large-scale clinical trial to determine the health effects of exposure to Agent Orange in Vietnam are discussed, including pre-project planning, organization according to strategy, attention to scheduling, a team approach, emphasis on guest relations, cross-training of personnel, and preparing…
CACHE Guidelines for Large-Scale Computer Programs.
ERIC Educational Resources Information Center
National Academy of Engineering, Washington, DC. Commission on Education.
The Computer Aids for Chemical Engineering Education (CACHE) guidelines identify desirable features of large-scale computer programs including running cost and running-time limit. Also discussed are programming standards, documentation, program installation, system requirements, program testing, and program distribution. Lists of types of…
Over-driven control for large-scale MR dampers
NASA Astrophysics Data System (ADS)
Friedman, A. J.; Dyke, S. J.; Phillips, B. M.
2013-04-01
As semi-active electro-mechanical control devices increase in scale for use in real-world civil engineering applications, their dynamics become increasingly complicated. Control designs that are able to take these characteristics into account will be more effective in achieving good performance. Large-scale magnetorheological (MR) dampers exhibit a significant time lag in their force-response to voltage inputs, reducing the efficacy of typical controllers designed for smaller scale devices where the lag is negligible. A new control algorithm is presented for large-scale MR devices that uses over-driving and back-driving of the commands to overcome the challenges associated with the dynamics of these large-scale MR dampers. An illustrative numerical example is considered to demonstrate the controller performance. Via simulations of the structure using several seismic ground motions, the merits of the proposed control strategy to achieve reductions in various response parameters are examined and compared against several accepted control algorithms. Experimental evidence is provided to validate the improved capabilities of the proposed controller in achieving the desired control force levels. Through real-time hybrid simulation (RTHS), the proposed controllers are also examined and experimentally evaluated in terms of their efficacy and robust performance. The results demonstrate that the proposed control strategy has superior performance over typical control algorithms when paired with a large-scale MR damper, and is robust for structural control applications.
The Role of Plausible Values in Large-Scale Surveys
ERIC Educational Resources Information Center
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 Environmental Influences on Aquatic Animal Health
In the latter portion of the 20th century, North America experienced numerous large-scale mortality events affecting a broad diversity of aquatic animals. Short-term forensic investigations of these events have sometimes characterized a causative agent or condition, but have rare...
Large-Scale Innovation and Change in UK Higher Education
ERIC Educational Resources Information Center
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…
Efficient On-Demand Operations in Large-Scale Infrastructures
ERIC Educational Resources Information Center
Ko, Steven Y.
2009-01-01
In large-scale distributed infrastructures such as clouds, Grids, peer-to-peer systems, and wide-area testbeds, users and administrators typically desire to perform "on-demand operations" that deal with the most up-to-date state of the infrastructure. However, the scale and dynamism present in the operating environment make it challenging to…
Assuring Quality in Large-Scale Online Course Development
ERIC Educational Resources Information Center
Parscal, Tina; Riemer, Deborah
2010-01-01
Student demand for online education requires colleges and universities to rapidly expand the number of courses and programs offered online while maintaining high quality. This paper outlines two universities respective processes to assure quality in large-scale online programs that integrate instructional design, eBook custom publishing, Quality…
Cosmic strings and the large-scale structure
NASA Technical Reports Server (NTRS)
Stebbins, Albert
1988-01-01
A possible problem for cosmic string models of galaxy formation is presented. If very large voids are common and if loop fragmentation is not much more efficient than presently believed, then it may be impossible for string scenarios to produce the observed large-scale structure with Omega sub 0 = 1 and without strong environmental biasing.
Extracting Useful Semantic Information from Large Scale Corpora of Text
ERIC Educational Resources Information Center
Mendoza, Ray Padilla, Jr.
2012-01-01
Extracting and representing semantic information from large scale corpora is at the crux of computer-assisted knowledge generation. Semantic information depends on collocation extraction methods, mathematical models used to represent distributional information, and weighting functions which transform the space. This dissertation provides a…
Improving the Utility of Large-Scale Assessments in Canada
ERIC Educational Resources Information Center
Rogers, W. Todd
2014-01-01
Principals and teachers do not use large-scale assessment results because the lack of distinct and reliable subtests prevents identifying strengths and weaknesses of students and instruction, the results arrive too late to be used, and principals and teachers need assistance to use the results to improve instruction so as to improve student…
Parallel high-order methods for deterministic and stochastic CFD and MHD problems
NASA Astrophysics Data System (ADS)
Lin, Guang
In computational fluid dynamics (CFD) and magneto-hydro-dynamics (MHD) applications there exist many sources of uncertainty, arising from imprecise material properties, random geometric roughness, noise in boundary/initial condition, transport coefficients, or external forcing. In this dissertation, stochastic perturbation analysis and stochastic simulations based on multi-element generalized polynomial chaos (ME-gPC) are employed synergistically, to solve large-scale stochastic CFD and MHD problems with many random inputs. Stochastic analytical solutions are obtained to serve in verifying the accuracy of the numerical results for small random inputs, but also in shedding light into the physical mechanisms and scaling laws associated with the structural changes of flow field due to random inputs. First, the Karhuen-Loeve (K-L) decomposition is presented; it is an efficient technique for modeling the random inputs. How to represent the covariance kernel for different boundary constrains is an important issue. A new covariance matrix for an one-dimensional fourth-order random process with four boundary constraints is derived analytically, and it is used to model random rough wedge surfaces subjected to supersonic flow. The algorithm of ME-gPC is presented next. ME-gPC is based on the decomposition of random space and spectral expansions. To efficiently solve complex stochastic fluid dynamical systems, e.g., stochastic compressible flows, the ME-gPC method is extended to multi-element probabilistic collocation method on sparse grids (ME-PCM) by coupling it with the probabilistic collocation projection. By using the sparse grid points, ME-PCM can handle random process with large number of random dimensions, with relative lower computational cost, compared to full tensor products. Several prototype problems in compressible and MHD flows are investigated by employing the aforementioned high-order stochastic numerical methods in conjunction with the stochastic
Cognitive Transfer Revisited: Can We Exploit New Media to Solve Old Problems on a Large Scale?
ERIC Educational Resources Information Center
Derry, Sharon J.; Hmelo-Silver, Cindy E.; Nagarajan, Anandi; Chernobilsky, Ellina; Beitzel, Brian D.
2006-01-01
The work we report in this special issue attempted to exploit the power of technology and cognitive theory to help make conceptual systems taught in large college courses truly useful in students' future lives. Facing evidence that traditional instructional models have not succeeded in this regard, we sought feasible course designs and…
Large-scale Individual-based Models of Pandemic Influenza Mitigation Strategies
NASA Astrophysics Data System (ADS)
Kadau, Kai; Germann, Timothy; Longini, Ira; Macken, Catherine
2007-03-01
We have developed a large-scale stochastic simulation model to investigate the spread of a pandemic strain of influenza virus through the U.S. population of 281 million people, to assess the likely effectiveness of various potential intervention strategies including antiviral agents, vaccines, and modified social mobility (including school closure and travel restrictions) [1]. The heterogeneous population structure and mobility is based on available Census and Department of Transportation data where available. Our simulations demonstrate that, in a highly mobile population, restricting travel after an outbreak is detected is likely to delay slightly the time course of the outbreak without impacting the eventual number ill. For large basic reproductive numbers R0, we predict that multiple strategies in combination (involving both social and medical interventions) will be required to achieve a substantial reduction in illness rates. [1] T. C. Germann, K. Kadau, I. M. Longini, and C. A. Macken, Proc. Natl. Acad. Sci. (USA) 103, 5935-5940 (2006).
NASA Astrophysics Data System (ADS)
Maneta, M. P.; Kimball, J. S.; Jencso, K. G.
2015-12-01
Managing the impact of climatic cycles on agricultural production, on land allocation, and on the state of active and projected water sources is challenging. This is because in addition to the uncertainties associated with climate projections, it is difficult to anticipate how farmers will respond to climatic change or to economic and policy incentives. Some sophisticated decision support systems available to water managers consider farmers' adaptive behavior but they are data intensive and difficult to apply operationally over large regions. Satellite-based observational technologies, in conjunction with models and assimilation methods, create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents at seasonal scales.We present an integrated modeling framework that can be driven by satellite remote sensing to enable robust regional assessment and prediction of climatic and policy impacts on agricultural production, water resources, and management decisions. The core of this framework is a widely used model of agricultural production and resource allocation adapted to be used in conjunction with remote sensing inputs to quantify the amount of land and water farmers allocate for each crop they choose to grow on a seasonal basis in response to reduced or enhanced access to water due to climatic or policy restrictions. A recursive Bayesian update method is used to adjust the model parameters by assimilating information on crop acreage, production, and crop evapotranspiration as a proxy for water use that can be estimated from high spatial resolution satellite remote sensing. The data assimilation framework blends new and old information to avoid over-calibration to the specific conditions of a single year and permits the updating of parameters to track gradual changes in the agricultural system.This integrated framework provides an operational means of monitoring and forecasting what crops will be grown and how farmers will allocate land and water under expected adverse conditions, and the resulting consequences for other water users. The Bayesian update framework constitutes an efficient method for the identification of the production function parameters and provides valuable information on the associated uncertainty of the forecasts.
NASA Astrophysics Data System (ADS)
Das, S.; Goswami, K.; Datta, B. N.
2016-05-01
Failure of structural systems under dynamic loading can be prevented via active vibration control which shifts the damped natural frequencies of the systems away from the dominant range of a loading spectrum. The damped natural frequencies and the dynamic load typically show significant variations in practice. A computationally efficient methodology based on quadratic partial eigenvalue assignment technique and optimization under uncertainty has been formulated in the present work that will rigorously account for these variations and result in economic and resilient design of structures. A novel scheme based on hierarchical clustering and importance sampling is also developed in this work for accurate and efficient estimation of probability of failure to guarantee the desired resilience level of the designed system. Finally the most robust set of feedback matrices is selected from the set of probabilistically characterized optimal closed-loop system to implement the new methodology for design of active controlled structures. Numerical examples are presented to illustrate the proposed methodology.
Using stochastically-generated subcolumns to represent cloud structure in a large-scale model
Pincus, R; Hemler, R; Klein, S A
2005-12-08
A new method for representing subgrid-scale cloud structure, in which each model column is decomposed into a set of subcolumns, has been introduced into the Geophysical Fluid Dynamics Laboratory's global climate model AM2. Each subcolumn in the decomposition is homogeneous but the ensemble reproduces the initial profiles of cloud properties including cloud fraction, internal variability (if any) in cloud condensate, and arbitrary overlap assumptions that describe vertical correlations. These subcolumns are used in radiation and diagnostic calculations, and have allowed the introduction of more realistic overlap assumptions. This paper describes the impact of these new methods for representing cloud structure in instantaneous calculations and long-term integrations. Shortwave radiation computed using subcolumns and the random overlap assumption differs in the global annual average by more than 4 W/m{sup 2} from the operational radiation scheme in instantaneous calculations; much of this difference is counteracted by a change in the overlap assumption to one in which overlap varies continuously with the separation distance between layers. Internal variability in cloud condensate, diagnosed from the mean condensate amount and cloud fraction, has about the same effect on radiative fluxes as does the ad hoc tuning accounting for this effect in the operational radiation scheme. Long simulations with the new model configuration show little difference from the operational model configuration, while statistical tests indicate that the model does not respond systematically to the sampling noise introduced by the approximate radiative transfer techniques introduced to work with the subcolumns.
Das, Sonjoy; Goswami, Kundan; Datta, Biswa N.
2014-12-10
Failure of structural systems under dynamic loading can be prevented via active vibration control which shifts the damped natural frequencies of the systems away from the dominant range of loading spectrum. The damped natural frequencies and the dynamic load typically show significant variations in practice. A computationally efficient methodology based on quadratic partial eigenvalue assignment technique and optimization under uncertainty has been formulated in the present work that will rigorously account for these variations and result in an economic and resilient design of structures. A novel scheme based on hierarchical clustering and importance sampling is also developed in this work for accurate and efficient estimation of probability of failure to guarantee the desired resilience level of the designed system. Numerical examples are presented to illustrate the proposed methodology.
NASA Astrophysics Data System (ADS)
Das, Sonjoy; Goswami, Kundan; Datta, Biswa N.
2014-12-01
Failure of structural systems under dynamic loading can be prevented via active vibration control which shifts the damped natural frequencies of the systems away from the dominant range of loading spectrum. The damped natural frequencies and the dynamic load typically show significant variations in practice. A computationally efficient methodology based on quadratic partial eigenvalue assignment technique and optimization under uncertainty has been formulated in the present work that will rigorously account for these variations and result in an economic and resilient design of structures. A novel scheme based on hierarchical clustering and importance sampling is also developed in this work for accurate and efficient estimation of probability of failure to guarantee the desired resilience level of the designed system. Numerical examples are presented to illustrate the proposed methodology.
Stochastic inflation lattice simulations - Ultra-large scale structure of the universe
NASA Technical Reports Server (NTRS)
Salopek, D. S.
1991-01-01
Non-Gaussian fluctuations for structure formation may arise in inflation from the nonlinear interaction of long wavelength gravitational and scalar fields. Long wavelength fields have spatial gradients, a (exp -1), small compared to the Hubble radius, and they are described in terms of classical random fields that are fed by short wavelength quantum noise. Lattice Langevin calculations are given for a toy model with a scalar field interacting with an exponential potential where one can obtain exact analytic solutions of the Fokker-Planck equation. For single scalar field models that are consistent with current microwave background fluctuations, the fluctuations are Gaussian. However, for scales much larger than our observable Universe, one expects large metric fluctuations that are non-Gaussian. This example illuminates non-Gaussian models involving multiple scalar fields which are consistent with current microwave background limits.
Constructing perturbation theory kernels for large-scale structure in generalized cosmologies
NASA Astrophysics Data System (ADS)
Taruya, Atsushi
2016-07-01
We present a simple numerical scheme for perturbation theory (PT) calculations of large-scale structure. Solving the evolution equations for perturbations numerically, we construct the PT kernels as building blocks of statistical calculations, from which the power spectrum and/or correlation function can be systematically computed. The scheme is especially applicable to the generalized structure formation including modified gravity, in which the analytic construction of PT kernels is intractable. As an illustration, we show several examples for power spectrum calculations in f (R ) gravity and Λ CDM models.
Wang, Jian; Wang, Xiaolong; Jiang, Aipeng; Jiangzhou, Shu; Li, Ping
2014-01-01
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. PMID:24701180
Wang, Xiaolong; Jiang, Aipeng; Jiangzhou, Shu; Li, Ping
2014-01-01
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. PMID:24701180
Wang, Jian; Wang, Xiaolong; Jiang, Aipeng; Jiangzhou, Shu; Li, Ping
2014-01-01
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.
Some notions of decentralization and coordination in large-scale dynamic systems
NASA Technical Reports Server (NTRS)
Chong, C. Y.
1975-01-01
Some notions of decentralization and coordination in the control of large-scale dynamic systems are discussed. Decentralization and coordination have always been important concepts in the study of large systems. Roughly speaking decentralization is the process of dividing a large problem into subproblems so that it can be handled more easily. Coordination is the manipulation of the subproblem so that the original problem is solved. The various types of decentralization and coordination that have been used to control dynamic systems are discussed. The emphasis was to distinguish between on-line and off-line operations to understand the results available by indicating the aspects of the problem which are decentralized.
Performance of Thorup's Shortest Path Algorithm for Large-Scale Network Simulation
NASA Astrophysics Data System (ADS)
Sakumoto, Yusuke; Ohsaki, Hiroyuki; Imase, Makoto
In this paper, we investigate the performance of Thorup's algorithm by comparing it to Dijkstra's algorithm for large-scale network simulations. One of the challenges toward the realization of large-scale network simulations is the efficient execution to find shortest paths in a graph with N vertices and M edges. The time complexity for solving a single-source shortest path (SSSP) problem with Dijkstra's algorithm with a binary heap (DIJKSTRA-BH) is O((M+N)log N). An sophisticated algorithm called Thorup's algorithm has been proposed. The original version of Thorup's algorithm (THORUP-FR) has the time complexity of O(M+N). A simplified version of Thorup's algorithm (THORUP-KL) has the time complexity of O(Mα(N)+N) where α(N) is the functional inverse of the Ackerman function. In this paper, we compare the performances (i.e., execution time and memory consumption) of THORUP-KL and DIJKSTRA-BH since it is known that THORUP-FR is at least ten times slower than Dijkstra's algorithm with a Fibonaccii heap. We find that (1) THORUP-KL is almost always faster than DIJKSTRA-BH for large-scale network simulations, and (2) the performances of THORUP-KL and DIJKSTRA-BH deviate from their time complexities due to the presence of the memory cache in the microprocessor.
Continuation and bifurcation analysis of large-scale dynamical systems with LOCA.
Salinger, Andrew Gerhard; Phipps, Eric Todd; Pawlowski, Roger Patrick
2010-06-01
Dynamical systems theory provides a powerful framework for understanding the behavior of complex evolving systems. However applying these ideas to large-scale dynamical systems such as discretizations of multi-dimensional PDEs is challenging. Such systems can easily give rise to problems with billions of dynamical variables, requiring specialized numerical algorithms implemented on high performance computing architectures with thousands of processors. This talk will describe LOCA, the Library of Continuation Algorithms, a suite of scalable continuation and bifurcation tools optimized for these types of systems that is part of the Trilinos software collection. In particular, we will describe continuation and bifurcation analysis techniques designed for large-scale dynamical systems that are based on specialized parallel linear algebra methods for solving augmented linear systems. We will also discuss several other Trilinos tools providing nonlinear solvers (NOX), eigensolvers (Anasazi), iterative linear solvers (AztecOO and Belos), preconditioners (Ifpack, ML, Amesos) and parallel linear algebra data structures (Epetra and Tpetra) that LOCA can leverage for efficient and scalable analysis of large-scale dynamical systems.
Iterative methods for large scale nonlinear and linear systems. Final report, 1994--1996
Walker, H.F.
1997-09-01
The major goal of this research has been to develop improved numerical methods for the solution of large-scale systems of linear and nonlinear equations, such as occur almost ubiquitously in the computational modeling of physical phenomena. The numerical methods of central interest have been Krylov subspace methods for linear systems, which have enjoyed great success in many large-scale applications, and newton-Krylov methods for nonlinear problems, which use Krylov subspace methods to solve approximately the linear systems that characterize Newton steps. Krylov subspace methods have undergone a remarkable development over the last decade or so and are now very widely used for the iterative solution of large-scale linear systems, particularly those that arise in the discretization of partial differential equations (PDEs) that occur in computational modeling. Newton-Krylov methods have enjoyed parallel success and are currently used in many nonlinear applications of great scientific and industrial importance. In addition to their effectiveness on important problems, Newton-Krylov methods also offer a nonlinear framework within which to transfer to the nonlinear setting any advances in Krylov subspace methods or preconditioning techniques, or new algorithms that exploit advanced machine architectures. This research has resulted in a number of improved Krylov and Newton-Krylov algorithms together with applications of these to important linear and nonlinear problems.
NASA Astrophysics Data System (ADS)
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.
Nogaret, Alain; Meliza, C. Daniel; Margoliash, Daniel; Abarbanel, Henry D. I.
2016-01-01
We report on the construction of neuron models by assimilating electrophysiological data with large-scale constrained nonlinear optimization. The method implements interior point line parameter search to determine parameters from the responses to intracellular current injections of zebra finch HVC neurons. We incorporated these parameters into a nine ionic channel conductance model to obtain completed models which we then use to predict the state of the neuron under arbitrary current stimulation. Each model was validated by successfully predicting the dynamics of the membrane potential induced by 20–50 different current protocols. The dispersion of parameters extracted from different assimilation windows was studied. Differences in constraints from current protocols, stochastic variability in neuron output, and noise behave as a residual temperature which broadens the global minimum of the objective function to an ellipsoid domain whose principal axes follow an exponentially decaying distribution. The maximum likelihood expectation of extracted parameters was found to provide an excellent approximation of the global minimum and yields highly consistent kinetics for both neurons studied. Large scale assimilation absorbs the intrinsic variability of electrophysiological data over wide assimilation windows. It builds models in an automatic manner treating all data as equal quantities and requiring minimal additional insight. PMID:27605157
Nogaret, Alain; Meliza, C Daniel; Margoliash, Daniel; Abarbanel, Henry D I
2016-01-01
We report on the construction of neuron models by assimilating electrophysiological data with large-scale constrained nonlinear optimization. The method implements interior point line parameter search to determine parameters from the responses to intracellular current injections of zebra finch HVC neurons. We incorporated these parameters into a nine ionic channel conductance model to obtain completed models which we then use to predict the state of the neuron under arbitrary current stimulation. Each model was validated by successfully predicting the dynamics of the membrane potential induced by 20-50 different current protocols. The dispersion of parameters extracted from different assimilation windows was studied. Differences in constraints from current protocols, stochastic variability in neuron output, and noise behave as a residual temperature which broadens the global minimum of the objective function to an ellipsoid domain whose principal axes follow an exponentially decaying distribution. The maximum likelihood expectation of extracted parameters was found to provide an excellent approximation of the global minimum and yields highly consistent kinetics for both neurons studied. Large scale assimilation absorbs the intrinsic variability of electrophysiological data over wide assimilation windows. It builds models in an automatic manner treating all data as equal quantities and requiring minimal additional insight. PMID:27605157
Real-time simulation of large-scale floods
NASA Astrophysics Data System (ADS)
Liu, Q.; Qin, Y.; Li, G. D.; Liu, Z.; Cheng, D. J.; Zhao, Y. H.
2016-08-01
According to the complex real-time water situation, the real-time simulation of large-scale floods is very important for flood prevention practice. Model robustness and running efficiency are two critical factors in successful real-time flood simulation. This paper proposed a robust, two-dimensional, shallow water model based on the unstructured Godunov- type finite volume method. A robust wet/dry front method is used to enhance the numerical stability. An adaptive method is proposed to improve the running efficiency. The proposed model is used for large-scale flood simulation on real topography. Results compared to those of MIKE21 show the strong performance of the proposed model.
Prototype Vector Machine for Large Scale Semi-Supervised Learning
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.
The Large Scale Synthesis of Aligned Plate Nanostructures
Zhou, Yang; Nash, Philip; Liu, Tian; Zhao, Naiqin; Zhu, Shengli
2016-01-01
We propose a novel technique for the large-scale synthesis of aligned-plate nanostructures that are self-assembled and self-supporting. The synthesis technique involves developing nanoscale two-phase microstructures through discontinuous precipitation followed by selective etching to remove one of the phases. The method may be applied to any alloy system in which the discontinuous precipitation transformation goes to completion. The resulting structure may have many applications in catalysis, filtering and thermal management depending on the phase selection and added functionality through chemical reaction with the retained phase. The synthesis technique is demonstrated using the discontinuous precipitation of a γ′ phase, (Ni, Co)3Al, followed by selective dissolution of the γ matrix phase. The production of the nanostructure requires heat treatments on the order of minutes and can be performed on a large scale making this synthesis technique of great economic potential. PMID:27439672
Electron drift in a large scale solid xenon
Yoo, J.; Jaskierny, W. F.
2015-08-21
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 ± 0.003 cm/μs while the drift speed in the solid phase (157 K) is 0.397 ± 0.006 cm/μs at 900 V/cm over 8.0 cm of uniform electric fields. Furthermore, it is demonstrated that a factor twomore » faster electron drift speed in solid phase xenon compared to that in liquid in a large scale solid xenon.« less
Electron drift in a large scale solid xenon
Yoo, J.; Jaskierny, W. F.
2015-08-21
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 ± 0.003 cm/μs while the drift speed in the solid phase (157 K) is 0.397 ± 0.006 cm/μs at 900 V/cm over 8.0 cm of uniform electric fields. Furthermore, 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.
Large scale meteorological influence during the Geysers 1979 field experiment
Barr, S.
1980-01-01
A series of meteorological field measurements conducted during July 1979 near Cobb Mountain in Northern California reveals evidence of several scales of atmospheric circulation consistent with the climatic pattern of the area. The scales of influence are reflected in the structure of wind and temperature in vertically stratified layers at a given observation site. Large scale synoptic gradient flow dominates the wind field above about twice the height of the topographic ridge. Below that there is a mixture of effects with evidence of a diurnal sea breeze influence and a sublayer of katabatic winds. The July observations demonstrate that weak migratory circulations in the large scale synoptic meteorological pattern have a significant influence on the day-to-day gradient winds and must be accounted for in planning meteorological programs including tracer experiments.
GAIA: A WINDOW TO LARGE-SCALE MOTIONS
Nusser, Adi; Branchini, Enzo; Davis, Marc E-mail: branchin@fis.uniroma3.it
2012-08-10
Using redshifts as a proxy for galaxy distances, estimates of the two-dimensional (2D) transverse peculiar velocities of distant galaxies could be obtained from future measurements of proper motions. We provide the mathematical framework for analyzing 2D transverse motions and show that they offer several advantages over traditional probes of large-scale motions. They are completely independent of any intrinsic relations between galaxy properties; hence, they are essentially free of selection biases. They are free from homogeneous and inhomogeneous Malmquist biases that typically plague distance indicator catalogs. They provide additional information to traditional probes that yield line-of-sight peculiar velocities only. Further, because of their 2D nature, fundamental questions regarding vorticity of large-scale flows can be addressed. Gaia, for example, is expected to provide proper motions of at least bright galaxies with high central surface brightness, making proper motions a likely contender for traditional probes based on current and future distance indicator measurements.
Lagrangian space consistency relation for large scale structure
Horn, Bart; Hui, Lam; Xiao, Xiao E-mail: lh399@columbia.edu
2015-09-01
Consistency relations, which relate the squeezed limit of an (N+1)-point correlation function to an N-point function, are non-perturbative symmetry statements that hold even if the associated high momentum modes are deep in the nonlinear regime and astrophysically complex. Recently, Kehagias and Riotto and Peloso and Pietroni discovered a consistency relation applicable to large scale structure. We show that this can be recast into a simple physical statement in Lagrangian space: that the squeezed correlation function (suitably normalized) vanishes. This holds regardless of whether the correlation observables are at the same time or not, and regardless of whether multiple-streaming is present. The simplicity of this statement suggests that an analytic understanding of large scale structure in the nonlinear regime may be particularly promising in Lagrangian space.
The workshop on iterative methods for large scale nonlinear problems
Walker, H.F.; Pernice, M.
1995-12-01
The aim of the workshop was to bring together researchers working on large scale applications with numerical specialists of various kinds. Applications that were addressed included reactive flows (combustion and other chemically reacting flows, tokamak modeling), porous media flows, cardiac modeling, chemical vapor deposition, image restoration, macromolecular modeling, and population dynamics. Numerical areas included Newton iterative (truncated Newton) methods, Krylov subspace methods, domain decomposition and other preconditioning methods, large scale optimization and optimal control, and parallel implementations and software. This report offers a brief summary of workshop activities and information about the participants. Interested readers are encouraged to look into an online proceedings available at http://www.usi.utah.edu/logan.proceedings. In this, the material offered here is augmented with hypertext abstracts that include links to locations such as speakers` home pages, PostScript copies of talks and papers, cross-references to related talks, and other information about topics addresses at the workshop.
The Large Scale Synthesis of Aligned Plate Nanostructures
NASA Astrophysics Data System (ADS)
Zhou, Yang; Nash, Philip; Liu, Tian; Zhao, Naiqin; Zhu, Shengli
2016-07-01
We propose a novel technique for the large-scale synthesis of aligned-plate nanostructures that are self-assembled and self-supporting. The synthesis technique involves developing nanoscale two-phase microstructures through discontinuous precipitation followed by selective etching to remove one of the phases. The method may be applied to any alloy system in which the discontinuous precipitation transformation goes to completion. The resulting structure may have many applications in catalysis, filtering and thermal management depending on the phase selection and added functionality through chemical reaction with the retained phase. The synthesis technique is demonstrated using the discontinuous precipitation of a γ‧ phase, (Ni, Co)3Al, followed by selective dissolution of the γ matrix phase. The production of the nanostructure requires heat treatments on the order of minutes and can be performed on a large scale making this synthesis technique of great economic potential.
Large Scale Deformation of the Western U.S. Cordillera
NASA Technical Reports Server (NTRS)
Bennett, Richard A.
2002-01-01
The overall objective of the work that was conducted was to understand the present-day large-scale deformations of the crust throughout the western United States and in so doing to improve our ability to assess the potential for seismic hazards in this region. To address this problem, we used a large collection of Global Positioning System (GPS) networks which spans the region to precisely quantify present-day large-scale crustal deformations in a single uniform reference frame. Our results can roughly be divided into an analysis of the GPS observations to infer the deformation field across and within the entire plate boundary zone and an investigation of the implications of this deformation field regarding plate boundary dynamics.
Large Scale Deformation of the Western US Cordillera
NASA Technical Reports Server (NTRS)
Bennett, Richard A.
2001-01-01
Destructive earthquakes occur throughout the western US Cordillera (WUSC), not just within the San Andreas fault zone. But because we do not understand the present-day large-scale deformations of the crust throughout the WUSC, our ability to assess the potential for seismic hazards in this region remains severely limited. To address this problem, we are using a large collection of Global Positioning System (GPS) networks which spans the WUSC to precisely quantify present-day large-scale crustal deformations in a single uniform reference frame. Our work can roughly be divided into an analysis of the GPS observations to infer the deformation field across and within the entire plate boundary zone and an investigation of the implications of this deformation field regarding plate boundary dynamics.
Startup of large-scale projects casts spotlight on IGCC
Swanekamp, R.
1996-06-01
With several large-scale plants cranking up this year, integrated coal gasification/combined cycle (IGCC) appears poised for growth. The technology may eventually help coal reclaim its former prominence in new plant construction, but developers worldwide are eyeing other feedstocks--such as petroleum coke or residual oil. Of the so-called advanced clean-coal technologies, integrated (IGCC) appears to be having a defining year. Of three large-scale demonstration plants in the US, one is well into startup, a second is expected to begin operating in the fall, and a third should startup by the end of the year; worldwide, over a dozen more projects are in the works. In Italy, for example, several large projects using petroleum coke or refinery residues as feedstocks are proceeding, apparently on a project-finance basis.
Considerations of large scale impact and the early Earth
NASA Technical Reports Server (NTRS)
Grieve, R. A. F.; Parmentier, E. M.
1985-01-01
Bodies which have preserved portions of their earliest crust indicate that large scale impact cratering was an important process in early surface and upper crustal evolution. Large impact basins form the basic topographic, tectonic, and stratigraphic framework of the Moon and impact was responsible for the characteristics of the second order gravity field and upper crustal seismic properties. The Earth's crustal evolution during the first 800 my of its history is conjectural. The lack of a very early crust may indicate that thermal and mechanical instabilities resulting from intense mantle convection and/or bombardment inhibited crustal preservation. Whatever the case, the potential effects of large scale impact have to be considered in models of early Earth evolution. Preliminary models of the evolution of a large terrestrial impact basin was derived and discussed in detail.
The large-scale anisotropy with the PAMELA calorimeter
NASA Astrophysics Data System (ADS)
Karelin, A.; Adriani, O.; Barbarino, G.; Bazilevskaya, G.; Bellotti, R.; Boezio, M.; Bogomolov, E.; Bongi, M.; Bonvicini, V.; Bottai, S.; Bruno, A.; Cafagna, F.; Campana, D.; Carbone, R.; Carlson, P.; Casolino, M.; Castellini, G.; De Donato, C.; De Santis, C.; De Simone, N.; Di Felice, V.; Formato, V.; Galper, A.; Koldashov, S.; Koldobskiy, S.; Krut'kov, S.; Kvashnin, A.; Leonov, A.; Malakhov, V.; Marcelli, L.; Martucci, M.; Mayorov, A.; Menn, W.; Mergé, M.; Mikhailov, V.; Mocchiutti, E.; Monaco, A.; Mori, N.; Munini, R.; Osteria, G.; Palma, F.; Panico, B.; Papini, P.; Pearce, M.; Picozza, P.; Ricci, M.; Ricciarini, S.; Sarkar, R.; Simon, M.; Scotti, V.; Sparvoli, R.; Spillantini, P.; Stozhkov, Y.; Vacchi, A.; Vannuccini, E.; Vasilyev, G.; Voronov, S.; Yurkin, Y.; Zampa, G.; Zampa, N.
2015-10-01
The large-scale anisotropy (or the so-called star-diurnal wave) has been studied using the calorimeter of the space-born experiment PAMELA. The cosmic ray anisotropy has been obtained for the Southern and Northern hemispheres simultaneously in the equatorial coordinate system for the time period 2006-2014. The dipole amplitude and phase have been measured for energies 1-20 TeV n-1.
Report on large scale molten core/magnesia interaction test
Chu, T.Y.; Bentz, J.H.; Arellano, F.E.; Brockmann, J.E.; Field, M.E.; Fish, J.D.
1984-08-01
A molten core/material interaction experiment was performed at the Large-Scale Melt Facility at Sandia National Laboratories. The experiment involved the release of 230 kg of core melt, heated to 2923/sup 0/K, into a magnesia brick crucible. Descriptions of the facility, the melting technology, as well as results of the experiment, are presented. Preliminary evaluations of the results indicate that magnesia brick can be a suitable material for core ladle construction.
Analysis plan for 1985 large-scale tests. Technical report
McMullan, F.W.
1983-01-01
The purpose of this effort is to assist DNA in planning for large-scale (upwards of 5000 tons) detonations of conventional explosives in the 1985 and beyond time frame. Primary research objectives were to investigate potential means to increase blast duration and peak pressures. This report identifies and analyzes several candidate explosives. It examines several charge designs and identifies advantages and disadvantages of each. Other factors including terrain and multiburst techniques are addressed as are test site considerations.
Simulating Weak Lensing by Large-Scale Structure
NASA Astrophysics Data System (ADS)
Vale, Chris; White, Martin
2003-08-01
We model weak gravitational lensing of light by large-scale structure using ray tracing through N-body simulations. The method is described with particular attention paid to numerical convergence. We investigate some of the key approximations in the multiplane ray-tracing algorithm. Our simulated shear and convergence maps are used to explore how well standard assumptions about weak lensing hold, especially near large peaks in the lensing signal.
The Phoenix series large scale LNG pool fire experiments.
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.
The Large-scale Structure of Scientific Method
NASA Astrophysics Data System (ADS)
Kosso, Peter
2009-01-01
The standard textbook description of the nature of science describes the proposal, testing, and acceptance of a theoretical idea almost entirely in isolation from other theories. The resulting model of science is a kind of piecemeal empiricism that misses the important network structure of scientific knowledge. Only the large-scale description of scientific method can reveal the global interconnectedness of scientific knowledge that is an essential part of what makes science scientific.
Space transportation booster engine thrust chamber technology, large scale injector
NASA Technical Reports Server (NTRS)
Schneider, J. A.
1993-01-01
The objective of the Large Scale Injector (LSI) program was to deliver a 21 inch diameter, 600,000 lbf thrust class injector to NASA/MSFC for hot fire testing. The hot fire test program would demonstrate the feasibility and integrity of the full scale injector, including combustion stability, chamber wall compatibility (thermal management), and injector performance. The 21 inch diameter injector was delivered in September of 1991.
Large-Scale Weather Disturbances in Mars’ Southern Extratropics
NASA Astrophysics Data System (ADS)
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
Multivariate Clustering of Large-Scale Scientific Simulation Data
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.
Multivariate Clustering of Large-Scale Simulation Data
Eliassi-Rad, T; Critchlow, T
2003-03-04
Simulations of complex scientific phenomena involve the execution of massively parallel computer programs. These simulation programs generate large-scale data sets over the spatiotemporal 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 space 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 the threshold 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 a cluster, it is desirable to associate each cluster with its correct spatial space. 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.
Onishchenko, O. G.; Horton, W.; Scullion, E.; Fedun, V.
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.
NASA Astrophysics Data System (ADS)
Onishchenko, O. G.; Pokhotelov, O. A.; Horton, W.; Scullion, E.; Fedun, V.
2015-12-01
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.
A Cloud Computing Platform for Large-Scale Forensic Computing
NASA Astrophysics Data System (ADS)
Roussev, Vassil; Wang, Liqiang; Richard, Golden; Marziale, Lodovico
The timely processing of massive digital forensic collections demands the use of large-scale distributed computing resources and the flexibility to customize the processing performed on the collections. This paper describes MPI MapReduce (MMR), an open implementation of the MapReduce processing model that outperforms traditional forensic computing techniques. MMR provides linear scaling for CPU-intensive processing and super-linear scaling for indexing-related workloads.
Supporting large scale applications on networks of workstations
NASA Technical Reports Server (NTRS)
Cooper, Robert; Birman, Kenneth P.
1989-01-01
Distributed applications on networks of workstations are an increasingly common way to satisfy computing needs. However, existing mechanisms for distributed programming exhibit poor performance and reliability as application size increases. Extension of the ISIS distributed programming system to support large scale distributed applications by providing hierarchical process groups is discussed. Incorporation of hierarchy in the program structure and exploitation of this to limit the communication and storage required in any one component of the distributed system is examined.
Geospatial Optimization of Siting Large-Scale Solar Projects
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.
Homogenization of Large-Scale Movement Models in Ecology
Garlick, M.J.; Powell, J.A.; Hooten, M.B.; McFarlane, L.R.
2011-01-01
A difficulty in using diffusion models to predict large scale animal population dispersal is that individuals move differently based on local information (as opposed to gradients) in differing habitat types. This can be accommodated by using ecological diffusion. However, real environments are often spatially complex, limiting application of a direct approach. Homogenization for partial differential equations has long been applied to Fickian diffusion (in which average individual movement is organized along gradients of habitat and population density). We derive a homogenization procedure for ecological diffusion and apply it to a simple model for chronic wasting disease in mule deer. Homogenization allows us to determine the impact of small scale (10-100 m) habitat variability on large scale (10-100 km) movement. The procedure generates asymptotic equations for solutions on the large scale with parameters defined by small-scale variation. The simplicity of this homogenization procedure is striking when compared to the multi-dimensional homogenization procedure for Fickian diffusion,and the method will be equally straightforward for more complex models. ?? 2010 Society for Mathematical Biology.
Dispersal Mutualism Incorporated into Large-Scale, Infrequent Disturbances.
Parker, V Thomas
2015-01-01
Because of their influence on succession and other community interactions, large-scale, infrequent natural disturbances also should play a major role in mutualistic interactions. Using field data and experiments, I test whether mutualisms have been incorporated into large-scale wildfire by whether the outcomes of a mutualism depend on disturbance. In this study a seed dispersal mutualism is shown to depend on infrequent, large-scale disturbances. A dominant shrubland plant (Arctostaphylos species) produces seeds that make up a persistent soil seed bank and requires fire to germinate. In post-fire stands, I show that seedlings emerging from rodent caches dominate sites experiencing higher fire intensity. Field experiments show that rodents (Perimyscus californicus, P. boylii) do cache Arctostaphylos fruit and bury most seed caches to a sufficient depth to survive a killing heat pulse that a fire might drive into the soil. While the rodent dispersal and caching behavior itself has not changed compared to other habitats, the environmental transformation caused by wildfire converts the caching burial of seed from a dispersal process to a plant fire adaptive trait, and provides the context for stimulating subsequent life history evolution in the plant host.
Large scale anisotropy of UHECRs for the Telescope Array
Kido, E.
2011-09-22
The origin of Ultra High Energy Cosmic Rays (UHECRs) is one of the most interesting questions in astroparticle physics. Despite of the efforts by other previous measurements, there is no consensus of both of the origin and the mechanism of UHECRs generation and propagation yet. In this context, Telescope Array (TA) experiment is expected to play an important role as the largest detector in the northern hemisphere which consists of an array of surface particle detectors (SDs) and fluorescence detectors (FDs) and other important calibration devices. We searched for large scale anisotropy using SD data of TA. UHECRs are expected to be restricted in GZK horizon when the composition of UHECRs is proton, so the observed arrival directions are expected to exhibit local large scale anisotropy if UHECR sources are some astrophysical objects. We used the SD data set from 11 May 2008 to 7 September 2010 to search for large-scale anisotropy. The discrimination power between LSS and isotropy is not enough yet, but the statistics in TA is expected to discriminate between those in about 95% confidence level on average in near future.
How Large Scales Flows May Influence Solar Activity
NASA Technical Reports Server (NTRS)
Hathaway, D. H.
2004-01-01
Large scale flows within the solar convection zone are the primary drivers of the Sun's magnetic activity cycle and play important roles in shaping the Sun's magnetic field. Differential rotation amplifies the magnetic field through its shearing action and converts poloidal field into toroidal field. Poleward meridional flow near the surface carries magnetic flux that reverses the magnetic poles at about the time of solar maximum. The deeper, equatorward meridional flow can carry magnetic flux back toward the lower latitudes where it erupts through the surface to form tilted active regions that convert toroidal fields into oppositely directed poloidal fields. These axisymmetric flows are themselves driven by large scale convective motions. The effects of the Sun's rotation on convection produce velocity correlations that can maintain both the differential rotation and the meridional circulation. These convective motions can also influence solar activity directly by shaping the magnetic field pattern. While considerable theoretical advances have been made toward understanding these large scale flows, outstanding problems in matching theory to observations still remain.
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. PMID:25731989
Large-scale flow experiments for managing river systems
Konrad, C.P.; Olden, J.D.; Lytle, D.A.; Melis, T.S.; Schmidt, J.C.; Bray, E.N.; Freeman, Mary C.; Gido, K.B.; Hemphill, N.P.; Kennard, M.J.; McMullen, L.E.; Mims, M.C.; Pyron, M.; Robinson, C.T.; Williams, J.G.
2011-01-01
Experimental manipulations of streamflow have been used globally in recent decades to mitigate the impacts of dam operations on river systems. Rivers are challenging subjects for experimentation, because they are open systems that cannot be isolated from their social context. We identify principles to address the challenges of conducting effective large-scale flow experiments. Flow experiments have both scientific and social value when they help to resolve specific questions about the ecological action of flow with a clear nexus to water policies and decisions. Water managers must integrate new information into operating policies for large-scale experiments to be effective. Modeling and monitoring can be integrated with experiments to analyze long-term ecological responses. Experimental design should include spatially extensive observations and well-defined, repeated treatments. Large-scale flow manipulations are only a part of dam operations that affect river systems. Scientists can ensure that experimental manipulations continue to be a valuable approach for the scientifically based management of river systems. ?? 2011 by American Institute of Biological Sciences. All rights reserved.
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.
A visualization framework for large-scale virtual astronomy
NASA Astrophysics Data System (ADS)
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.
Line segment extraction for large scale unorganized point clouds
NASA Astrophysics Data System (ADS)
Lin, Yangbin; Wang, Cheng; Cheng, Jun; Chen, Bili; Jia, Fukai; Chen, Zhonggui; Li, Jonathan
2015-04-01
Line segment detection in images is already a well-investigated topic, although it has received considerably less attention in 3D point clouds. Benefiting from current LiDAR devices, large-scale point clouds are becoming increasingly common. Most human-made objects have flat surfaces. Line segments that occur where pairs of planes intersect give important information regarding the geometric content of point clouds, which is especially useful for automatic building reconstruction and segmentation. This paper proposes a novel method that is capable of accurately extracting plane intersection line segments from large-scale raw scan points. The 3D line-support region, namely, a point set near a straight linear structure, is extracted simultaneously. The 3D line-support region is fitted by our Line-Segment-Half-Planes (LSHP) structure, which provides a geometric constraint for a line segment, making the line segment more reliable and accurate. We demonstrate our method on the point clouds of large-scale, complex, real-world scenes acquired by LiDAR devices. We also demonstrate the application of 3D line-support regions and their LSHP structures on urban scene abstraction.
Impact of Large-scale Geological Architectures On Recharge
NASA Astrophysics Data System (ADS)
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.
Dispersal Mutualism Incorporated into Large-Scale, Infrequent Disturbances
Parker, V. Thomas
2015-01-01
Because of their influence on succession and other community interactions, large-scale, infrequent natural disturbances also should play a major role in mutualistic interactions. Using field data and experiments, I test whether mutualisms have been incorporated into large-scale wildfire by whether the outcomes of a mutualism depend on disturbance. In this study a seed dispersal mutualism is shown to depend on infrequent, large-scale disturbances. A dominant shrubland plant (Arctostaphylos species) produces seeds that make up a persistent soil seed bank and requires fire to germinate. In post-fire stands, I show that seedlings emerging from rodent caches dominate sites experiencing higher fire intensity. Field experiments show that rodents (Perimyscus californicus, P. boylii) do cache Arctostaphylos fruit and bury most seed caches to a sufficient depth to survive a killing heat pulse that a fire might drive into the soil. While the rodent dispersal and caching behavior itself has not changed compared to other habitats, the environmental transformation caused by wildfire converts the caching burial of seed from a dispersal process to a plant fire adaptive trait, and provides the context for stimulating subsequent life history evolution in the plant host. PMID:26151560
Reliability assessment for components of large scale photovoltaic systems
NASA Astrophysics Data System (ADS)
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.
Dispersal Mutualism Incorporated into Large-Scale, Infrequent Disturbances.
Parker, V Thomas
2015-01-01
Because of their influence on succession and other community interactions, large-scale, infrequent natural disturbances also should play a major role in mutualistic interactions. Using field data and experiments, I test whether mutualisms have been incorporated into large-scale wildfire by whether the outcomes of a mutualism depend on disturbance. In this study a seed dispersal mutualism is shown to depend on infrequent, large-scale disturbances. A dominant shrubland plant (Arctostaphylos species) produces seeds that make up a persistent soil seed bank and requires fire to germinate. In post-fire stands, I show that seedlings emerging from rodent caches dominate sites experiencing higher fire intensity. Field experiments show that rodents (Perimyscus californicus, P. boylii) do cache Arctostaphylos fruit and bury most seed caches to a sufficient depth to survive a killing heat pulse that a fire might drive into the soil. While the rodent dispersal and caching behavior itself has not changed compared to other habitats, the environmental transformation caused by wildfire converts the caching burial of seed from a dispersal process to a plant fire adaptive trait, and provides the context for stimulating subsequent life history evolution in the plant host. PMID:26151560
Large-scale flow experiments for managing river systems
Konrad, Christopher P.; Olden, Julian D.; Lytle, David A.; Melis, Theodore S.; Schmidt, John C.; Bray, Erin N.; Freeman, Mary C.; Gido, Keith B.; Hemphill, Nina P.; Kennard, Mark J.; McMullen, Laura E.; Mims, Meryl C.; Pyron, Mark; Robinson, Christopher T.; Williams, John G.
2011-01-01
Experimental manipulations of streamflow have been used globally in recent decades to mitigate the impacts of dam operations on river systems. Rivers are challenging subjects for experimentation, because they are open systems that cannot be isolated from their social context. We identify principles to address the challenges of conducting effective large-scale flow experiments. Flow experiments have both scientific and social value when they help to resolve specific questions about the ecological action of flow with a clear nexus to water policies and decisions. Water managers must integrate new information into operating policies for large-scale experiments to be effective. Modeling and monitoring can be integrated with experiments to analyze long-term ecological responses. Experimental design should include spatially extensive observations and well-defined, repeated treatments. Large-scale flow manipulations are only a part of dam operations that affect river systems. Scientists can ensure that experimental manipulations continue to be a valuable approach for the scientifically based management of river systems.
Multiresolution comparison of precipitation datasets for large-scale models
NASA Astrophysics Data System (ADS)
Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.
2014-12-01
Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.
Large-scale data mining pilot project in human genome
Musick, R.; Fidelis, R.; Slezak, T.
1997-05-01
This whitepaper briefly describes a new, aggressive effort in large- scale data Livermore National Labs. The implications of `large- scale` will be clarified Section. In the short term, this effort will focus on several @ssion-critical questions of Genome project. We will adapt current data mining techniques to the Genome domain, to quantify the accuracy of inference results, and lay the groundwork for a more extensive effort in large-scale data mining. A major aspect of the approach is that we will be fully-staffed data warehousing effort in the human Genome area. The long term goal is strong applications- oriented research program in large-@e data mining. The tools, skill set gained will be directly applicable to a wide spectrum of tasks involving a for large spatial and multidimensional data. This includes applications in ensuring non-proliferation, stockpile stewardship, enabling Global Ecology (Materials Database Industrial Ecology), advancing the Biosciences (Human Genome Project), and supporting data for others (Battlefield Management, Health Care).
PARTICLE ACCELERATION BY COLLISIONLESS SHOCKS CONTAINING LARGE-SCALE MAGNETIC-FIELD VARIATIONS
Guo, F.; Jokipii, J. R.; Kota, J. E-mail: jokipii@lpl.arizona.ed
2010-12-10
Diffusive shock acceleration at collisionless shocks is thought to be the source of many of the energetic particles observed in space. Large-scale spatial variations of the magnetic field have been shown to be important in understanding observations. The effects are complex, so here we consider a simple, illustrative model. Here we solve numerically the Parker transport equation for a shock in the presence of large-scale sinusoidal magnetic-field variations. We demonstrate that the familiar planar-shock results can be significantly altered as a consequence of large-scale, meandering magnetic lines of force. Because the perpendicular diffusion coefficient {kappa}{sub perpendicular} is generally much smaller than the parallel diffusion coefficient {kappa}{sub ||}, the energetic charged particles are trapped and preferentially accelerated along the shock front in the regions where the connection points of magnetic field lines intersecting the shock surface converge, and thus create the 'hot spots' of the accelerated particles. For the regions where the connection points separate from each other, the acceleration to high energies will be suppressed. Further, the particles diffuse away from the 'hot spot' regions and modify the spectra of downstream particle distribution. These features are qualitatively similar to the recent Voyager observations in the Heliosheath. These results are potentially important for particle acceleration at shocks propagating in turbulent magnetized plasmas as well as those which contain large-scale nonplanar structures. Examples include anomalous cosmic rays accelerated by the solar wind termination shock, energetic particles observed in propagating heliospheric shocks, galactic cosmic rays accelerated by supernova blast waves, etc.
A Survey on Routing Protocols for Large-Scale Wireless Sensor Networks
Li, Changle; Zhang, Hanxiao; Hao, Binbin; Li, Jiandong
2011-01-01
With the advances in micro-electronics, wireless sensor devices have been made much smaller and more integrated, and large-scale wireless sensor networks (WSNs) based the cooperation among the significant amount of nodes have become a hot topic. “Large-scale” means mainly large area or high density of a network. Accordingly the routing protocols must scale well to the network scope extension and node density increases. A sensor node is normally energy-limited and cannot be recharged, and thus its energy consumption has a quite significant effect on the scalability of the protocol. To the best of our knowledge, currently the mainstream methods to solve the energy problem in large-scale WSNs are the hierarchical routing protocols. In a hierarchical routing protocol, all the nodes are divided into several groups with different assignment levels. The nodes within the high level are responsible for data aggregation and management work, and the low level nodes for sensing their surroundings and collecting information. The hierarchical routing protocols are proved to be more energy-efficient than flat ones in which all the nodes play the same role, especially in terms of the data aggregation and the flooding of the control packets. With focus on the hierarchical structure, in this paper we provide an insight into routing protocols designed specifically for large-scale WSNs. According to the different objectives, the protocols are generally classified based on different criteria such as control overhead reduction, energy consumption mitigation and energy balance. In order to gain a comprehensive understanding of each protocol, we highlight their innovative ideas, describe the underlying principles in detail and analyze their advantages and disadvantages. Moreover a comparison of each routing protocol is conducted to demonstrate the differences between the protocols in terms of message complexity, memory requirements, localization, data aggregation, clustering manner
A cooperative strategy for parameter estimation in large scale systems biology models
2012-01-01
Background Mathematical models play a key role in systems biology: they summarize the currently available knowledge in a way that allows to make experimentally verifiable predictions. Model calibration consists of finding the parameters that give the best fit to a set of experimental data, which entails minimizing a cost function that measures the goodness of this fit. Most mathematical models in systems biology present three characteristics which make this problem very difficult to solve: they are highly non-linear, they have a large number of parameters to be estimated, and the information content of the available experimental data is frequently scarce. Hence, there is a need for global optimization methods capable of solving this problem efficiently. Results A new approach for parameter estimation of large scale models, called Cooperative Enhanced Scatter Search (CeSS), is presented. Its key feature is the cooperation between different programs (“threads”) that run in parallel in different processors. Each thread implements a state of the art metaheuristic, the enhanced Scatter Search algorithm (eSS). Cooperation, meaning information sharing between threads, modifies the systemic properties of the algorithm and allows to speed up performance. Two parameter estimation problems involving models related with the central carbon metabolism of E. coli which include different regulatory levels (metabolic and transcriptional) are used as case studies. The performance and capabilities of the method are also evaluated using benchmark problems of large-scale global optimization, with excellent results. Conclusions The cooperative CeSS strategy is a general purpose technique that can be applied to any model calibration problem. Its capability has been demonstrated by calibrating two large-scale models of different characteristics, improving the performance of previously existing methods in both cases. The cooperative metaheuristic presented here can be easily extended
Large-Scale Analysis of Auditory Segregation Behavior Crowdsourced via a Smartphone App
Kumar, Sukhbinder; Griffiths, Timothy D.
2016-01-01
The human auditory system is adept at detecting sound sources of interest from a complex mixture of several other simultaneous sounds. The ability to selectively attend to the speech of one speaker whilst ignoring other speakers and background noise is of vital biological significance—the capacity to make sense of complex ‘auditory scenes’ is significantly impaired in aging populations as well as those with hearing loss. We investigated this problem by designing a synthetic signal, termed the ‘stochastic figure-ground’ stimulus that captures essential aspects of complex sounds in the natural environment. Previously, we showed that under controlled laboratory conditions, young listeners sampled from the university subject pool (n = 10) performed very well in detecting targets embedded in the stochastic figure-ground signal. Here, we presented a modified version of this cocktail party paradigm as a ‘game’ featured in a smartphone app (The Great Brain Experiment) and obtained data from a large population with diverse demographical patterns (n = 5148). Despite differences in paradigms and experimental settings, the observed target-detection performance by users of the app was robust and consistent with our previous results from the psychophysical study. Our results highlight the potential use of smartphone apps in capturing robust large-scale auditory behavioral data from normal healthy volunteers, which can also be extended to study auditory deficits in clinical populations with hearing impairments and central auditory disorders. PMID:27096165
On the rejection-based algorithm for simulation and analysis of large-scale reaction networks
Thanh, Vo Hong; Zunino, Roberto; Priami, Corrado
2015-06-28
Stochastic simulation for in silico studies of large biochemical networks requires a great amount of computational time. We recently proposed a new exact simulation algorithm, called the rejection-based stochastic simulation algorithm (RSSA) [Thanh et al., J. Chem. Phys. 141(13), 134116 (2014)], to improve simulation performance by postponing and collapsing as much as possible the propensity updates. In this paper, we analyze the performance of this algorithm in detail, and improve it for simulating large-scale biochemical reaction networks. We also present a new algorithm, called simultaneous RSSA (SRSSA), which generates many independent trajectories simultaneously for the analysis of the biochemical behavior. SRSSA improves simulation performance by utilizing a single data structure across simulations to select reaction firings and forming trajectories. The memory requirement for building and storing the data structure is thus independent of the number of trajectories. The updating of the data structure when needed is performed collectively in a single operation across the simulations. The trajectories generated by SRSSA are exact and independent of each other by exploiting the rejection-based mechanism. We test our new improvement on real biological systems with a wide range of reaction networks to demonstrate its applicability and efficiency.
Large-Scale Analysis of Auditory Segregation Behavior Crowdsourced via a Smartphone App.
Teki, Sundeep; Kumar, Sukhbinder; Griffiths, Timothy D
2016-01-01
The human auditory system is adept at detecting sound sources of interest from a complex mixture of several other simultaneous sounds. The ability to selectively attend to the speech of one speaker whilst ignoring other speakers and background noise is of vital biological significance-the capacity to make sense of complex 'auditory scenes' is significantly impaired in aging populations as well as those with hearing loss. We investigated this problem by designing a synthetic signal, termed the 'stochastic figure-ground' stimulus that captures essential aspects of complex sounds in the natural environment. Previously, we showed that under controlled laboratory conditions, young listeners sampled from the university subject pool (n = 10) performed very well in detecting targets embedded in the stochastic figure-ground signal. Here, we presented a modified version of this cocktail party paradigm as a 'game' featured in a smartphone app (The Great Brain Experiment) and obtained data from a large population with diverse demographical patterns (n = 5148). Despite differences in paradigms and experimental settings, the observed target-detection performance by users of the app was robust and consistent with our previous results from the psychophysical study. Our results highlight the potential use of smartphone apps in capturing robust large-scale auditory behavioral data from normal healthy volunteers, which can also be extended to study auditory deficits in clinical populations with hearing impairments and central auditory disorders. PMID:27096165
NASA Technical Reports Server (NTRS)
Nguyen, D. T.; Watson, Willie R. (Technical Monitor)
2005-01-01
The overall objectives of this research work are to formulate and validate efficient parallel algorithms, and to efficiently design/implement computer software for solving large-scale acoustic problems, arised from the unified frameworks of the finite element procedures. The adopted parallel Finite Element (FE) Domain Decomposition (DD) procedures should fully take advantages of multiple processing capabilities offered by most modern high performance computing platforms for efficient parallel computation. To achieve this objective. the formulation needs to integrate efficient sparse (and dense) assembly techniques, hybrid (or mixed) direct and iterative equation solvers, proper pre-conditioned strategies, unrolling strategies, and effective processors' communicating schemes. Finally, the numerical performance of the developed parallel finite element procedures will be evaluated by solving series of structural, and acoustic (symmetrical and un-symmetrical) problems (in different computing platforms). Comparisons with existing "commercialized" and/or "public domain" software are also included, whenever possible.
Jakob, Christian
2015-02-26
This report summarises an investigation into the relationship of tropical thunderstorms to the atmospheric conditions they are embedded in. The study is based on the use of radar observations at the Atmospheric Radiation Measurement site in Darwin run under the auspices of the DOE Atmospheric Systems Research program. Linking the larger scales of the atmosphere with the smaller scales of thunderstorms is crucial for the development of the representation of thunderstorms in weather and climate models, which is carried out by a process termed parametrisation. Through the analysis of radar and wind profiler observations the project made several fundamental discoveries about tropical storms and quantified the relationship of the occurrence and intensity of these storms to the large-scale atmosphere. We were able to show that the rainfall averaged over an area the size of a typical climate model grid-box is largely controlled by the number of storms in the area, and less so by the storm intensity. This allows us to completely rethink the way we represent such storms in climate models. We also found that storms occur in three distinct categories based on their depth and that the transition between these categories is strongly related to the larger scale dynamical features of the atmosphere more so than its thermodynamic state. Finally, we used our observational findings to test and refine a new approach to cumulus parametrisation which relies on the stochastic modelling of the area covered by different convective cloud types.
NASA Astrophysics Data System (ADS)
Konno, Yohko; Suzuki, Keiji
This paper describes an approach to development of a solution algorithm of a general-purpose for large scale problems using “Local Clustering Organization (LCO)” as a new solution for Job-shop scheduling problem (JSP). Using a performance effective large scale scheduling in the study of usual LCO, a solving JSP keep stability induced better solution is examined. In this study for an improvement of a performance of a solution for JSP, processes to a optimization by LCO is examined, and a scheduling solution-structure is extended to a new solution-structure based on machine-division. A solving method introduced into effective local clustering for the solution-structure is proposed as an extended LCO. An extended LCO has an algorithm which improves scheduling evaluation efficiently by clustering of parallel search which extends over plural machines. A result verified by an application of extended LCO on various scale of problems proved to conduce to minimizing make-span and improving on the stable performance.
Large-scale computation of incompressible viscous flow by least-squares finite element method
NASA Technical Reports Server (NTRS)
Jiang, Bo-Nan; Lin, T. L.; Povinelli, Louis A.
1993-01-01
The least-squares finite element method (LSFEM) based on the velocity-pressure-vorticity formulation is applied to large-scale/three-dimensional steady incompressible Navier-Stokes problems. This method can accommodate equal-order interpolations and results in symmetric, positive definite algebraic system which can be solved effectively by simple iterative methods. The first-order velocity-Bernoulli function-vorticity formulation for incompressible viscous flows is also tested. For three-dimensional cases, an additional compatibility equation, i.e., the divergence of the vorticity vector should be zero, is included to make the first-order system elliptic. The simple substitution of the Newton's method is employed to linearize the partial differential equations, the LSFEM is used to obtain discretized equations, and the system of algebraic equations is solved using the Jacobi preconditioned conjugate gradient method which avoids formation of either element or global matrices (matrix-free) to achieve high efficiency. To show the validity of this scheme for large-scale computation, we give numerical results for 2D driven cavity problem at Re = 10000 with 408 x 400 bilinear elements. The flow in a 3D cavity is calculated at Re = 100, 400, and 1,000 with 50 x 50 x 50 trilinear elements. The Taylor-Goertler-like vortices are observed for Re = 1,000.
LARGE-SCALE CO2 TRANSPORTATION AND DEEP OCEAN SEQUESTRATION
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.
Large-Scale Hybrid Motor Testing. Chapter 10
NASA Technical Reports Server (NTRS)
Story, George
2006-01-01
Hybrid rocket motors can be successfully demonstrated at a small scale virtually anywhere. There have been many suitcase sized portable test stands assembled for demonstration of hybrids. They show the safety of hybrid rockets to the audiences. These small show motors and small laboratory scale motors can give comparative burn rate data for development of different fuel/oxidizer combinations, however questions that are always asked when hybrids are mentioned for large scale applications are - how do they scale and has it been shown in a large motor? To answer those questions, large scale motor testing is required to verify the hybrid motor at its true size. The necessity to conduct large-scale hybrid rocket motor tests to validate the burn rate from the small motors to application size has been documented in several place^'^^.^. Comparison of small scale hybrid data to that of larger scale data indicates that the fuel burn rate goes down with increasing port size, even with the same oxidizer flux. This trend holds for conventional hybrid motors with forward oxidizer injection and HTPB based fuels. While the reason this is occurring would make a great paper or study or thesis, it is not thoroughly understood at this time. Potential causes include the fact that since hybrid combustion is boundary layer driven, the larger port sizes reduce the interaction (radiation, mixing and heat transfer) from the core region of the port. This chapter focuses on some of the large, prototype sized testing of hybrid motors. The largest motors tested have been AMROC s 250K-lbf thrust motor at Edwards Air Force Base and the Hybrid Propulsion Demonstration Program s 250K-lbf thrust motor at Stennis Space Center. Numerous smaller tests were performed to support the burn rate, stability and scaling concepts that went into the development of those large motors.
Statistical analysis of large-scale neuronal recording data
Reed, Jamie L.; Kaas, Jon H.
2010-01-01
Relating stimulus properties to the response properties of individual neurons and neuronal networks is a major goal of sensory research. Many investigators implant electrode arrays in multiple brain areas and record from chronically implanted electrodes over time to answer a variety of questions. Technical challenges related to analyzing large-scale neuronal recording data are not trivial. Several analysis methods traditionally used by neurophysiologists do not account for dependencies in the data that are inherent in multi-electrode recordings. In addition, when neurophysiological data are not best modeled by the normal distribution and when the variables of interest may not be linearly related, extensions of the linear modeling techniques are recommended. A variety of methods exist to analyze correlated data, even when data are not normally distributed and the relationships are nonlinear. Here we review expansions of the Generalized Linear Model designed to address these data properties. Such methods are used in other research fields, and the application to large-scale neuronal recording data will enable investigators to determine the variable properties that convincingly contribute to the variances in the observed neuronal measures. Standard measures of neuron properties such as response magnitudes can be analyzed using these methods, and measures of neuronal network activity such as spike timing correlations can be analyzed as well. We have done just that in recordings from 100-electrode arrays implanted in the primary somatosensory cortex of owl monkeys. Here we illustrate how one example method, Generalized Estimating Equations analysis, is a useful method to apply to large-scale neuronal recordings. PMID:20472395
Statistical Modeling of Large-Scale Scientific Simulation Data
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.
Infectious diseases in large-scale cat hoarding investigations.
Polak, K C; Levy, J K; Crawford, P C; Leutenegger, C M; Moriello, K A
2014-08-01
Animal hoarders accumulate animals in over-crowded conditions without adequate nutrition, sanitation, and veterinary care. As a result, animals rescued from hoarding frequently have a variety of medical conditions including respiratory infections, gastrointestinal disease, parasitism, malnutrition, and other evidence of neglect. The purpose of this study was to characterize the infectious diseases carried by clinically affected cats and to determine the prevalence of retroviral infections among cats in large-scale cat hoarding investigations. Records were reviewed retrospectively from four large-scale seizures of cats from failed sanctuaries from November 2009 through March 2012. The number of cats seized in each case ranged from 387 to 697. Cats were screened for feline leukemia virus (FeLV) and feline immunodeficiency virus (FIV) in all four cases and for dermatophytosis in one case. A subset of cats exhibiting signs of upper respiratory disease or diarrhea had been tested for infections by PCR and fecal flotation for treatment planning. Mycoplasma felis (78%), calicivirus (78%), and Streptococcus equi subspecies zooepidemicus (55%) were the most common respiratory infections. Feline enteric coronavirus (88%), Giardia (56%), Clostridium perfringens (49%), and Tritrichomonas foetus (39%) were most common in cats with diarrhea. The seroprevalence of FeLV and FIV were 8% and 8%, respectively. In the one case in which cats with lesions suspicious for dermatophytosis were cultured for Microsporum canis, 69/76 lesional cats were culture-positive; of these, half were believed to be truly infected and half were believed to be fomite carriers. Cats from large-scale hoarding cases had high risk for enteric and respiratory infections, retroviruses, and dermatophytosis. Case responders should be prepared for mass treatment of infectious diseases and should implement protocols to prevent transmission of feline or zoonotic infections during the emergency response and when
Improving Design Efficiency for Large-Scale Heterogeneous Circuits
NASA Astrophysics Data System (ADS)
Gregerson, Anthony
Despite increases in logic density, many Big Data applications must still be partitioned across multiple computing devices in order to meet their strict performance requirements. Among the most demanding of these applications is high-energy physics (HEP), which uses complex computing systems consisting of thousands of FPGAs and ASICs to process the sensor data created by experiments at particles accelerators such as the Large Hadron Collider (LHC). Designing such computing systems is challenging due to the scale of the systems, the exceptionally high-throughput and low-latency performance constraints that necessitate application-specific hardware implementations, the requirement that algorithms are efficiently partitioned across many devices, and the possible need to update the implemented algorithms during the lifetime of the system. In this work, we describe our research to develop flexible architectures for implementing such large-scale circuits on FPGAs. In particular, this work is motivated by (but not limited in scope to) high-energy physics algorithms for the Compact Muon Solenoid (CMS) experiment at the LHC. To make efficient use of logic resources in multi-FPGA systems, we introduce Multi-Personality Partitioning, a novel form of the graph partitioning problem, and present partitioning algorithms that can significantly improve resource utilization on heterogeneous devices while also reducing inter-chip connections. To reduce the high communication costs of Big Data applications, we also introduce Information-Aware Partitioning, a partitioning method that analyzes the data content of application-specific circuits, characterizes their entropy, and selects circuit partitions that enable efficient compression of data between chips. We employ our information-aware partitioning method to improve the performance of the hardware validation platform for evaluating new algorithms for the CMS experiment. Together, these research efforts help to improve the efficiency
Large-scale molten core/material interaction experiments
Chu, T.Y.
1984-01-01
The paper described the facility and melting technology for large-scale molten core/material interaction experiments being carried out at Sandia National Laboratories. The facility is largest of its kind anywhere. It is capable of producing core melts up to 500 kg at a temperature of 3000/sup 0/K. Results of a recent experiment involving the release of 230 kg of core melt into a magnesia brick crucible is discussed in detail. Data on thermal and mechanical responses of magnesia brick, heat flux partitioning, melt penetration, gas and aerosol generation are presented.
Laser Welding of Large Scale Stainless Steel Aircraft Structures
NASA Astrophysics Data System (ADS)
Reitemeyer, D.; Schultz, V.; Syassen, F.; Seefeld, T.; Vollertsen, F.
In this paper a welding process for large scale stainless steel structures is presented. The process was developed according to the requirements of an aircraft application. Therefore, stringers are welded on a skin sheet in a t-joint configuration. The 0.6 mm thickness parts are welded with a thin disc laser, seam length up to 1920 mm are demonstrated. The welding process causes angular distortions of the skin sheet which are compensated by a subsequent laser straightening process. Based on a model straightening process parameters matching the induced welding distortion are predicted. The process combination is successfully applied to stringer stiffened specimens.
Large-scale genotoxicity assessments in the marine environment.
Hose, J E
1994-12-01
There are a number of techniques for detecting genotoxicity in the marine environment, and many are applicable to large-scale field assessments. Certain tests can be used to evaluate responses in target organisms in situ while others utilize surrogate organisms exposed to field samples in short-term laboratory bioassays. Genotoxicity endpoints appear distinct from traditional toxicity endpoints, but some have chemical or ecotoxicologic correlates. One versatile end point, the frequency of anaphase aberrations, has been used in several large marine assessments to evaluate genotoxicity in the New York Bight, in sediment from San Francisco Bay, and following the Exxon Valdez oil spill.
Locally Biased Galaxy Formation and Large-Scale Structure
NASA Astrophysics Data System (ADS)
Narayanan, Vijay K.; Berlind, Andreas A.; Weinberg, David H.
2000-01-01
We examine the influence of the morphology-density relation and a wide range of simple models for biased galaxy formation on statistical measures of large-scale structure. We contrast the behavior of local biasing models, in which the efficiency of galaxy formation is determined by the density, geometry, or velocity dispersion of the local mass distribution, with that of nonlocal biasing models, in which galaxy formation is modulated coherently over scales larger than the galaxy correlation length. If morphological segregation of galaxies is governed by a local morphology-density relation, then the correlation function of E/S0 galaxies should be steeper and stronger than that of spiral galaxies on small scales, as observed, while on large scales the E/S0 and spiral galaxies should have correlation functions with the same shape but different amplitudes. Similarly, all of our local bias models produce scale-independent amplification of the correlation function and power spectrum in the linear and mildly nonlinear regimes; only a nonlocal biasing mechanism can alter the shape of the power spectrum on large scales. Moments of the biased galaxy distribution retain the hierarchical pattern of the mass moments, but biasing alters the values and scale dependence of the hierarchical amplitudes S3 and S4. Pair-weighted moments of the galaxy velocity distribution are sensitive to the details of the bias prescription even if galaxies have the same local velocity distribution as the underlying dark matter. The nonlinearity of the relation between galaxy density and mass density depends on the biasing prescription and the smoothing scale, and the scatter in this relation is a useful diagnostic of the physical parameters that determine the bias. While the assumption that galaxy formation is governed by local physics leads to some important simplifications on large scales, even local biasing is a multifaceted phenomenon whose impact cannot be described by a single parameter or
Why large-scale seasonal streamflow forecasts are feasible
NASA Astrophysics Data System (ADS)
Bierkens, M. F.; Candogan Yossef, N.; Van Beek, L. P.
2011-12-01
Seasonal forecasts of precipitation and temperature, using either statistical or dynamic prediction, have been around for almost 2 decades. The skill of these forecasts differ both in space and time, with highest skill in areas heavily influenced by SST anomalies such as El Nino or areas where land surface properties have a major impact on e.g. Monsoon strength, such as the vegetation cover of the Sahel region or the snow cover of the Tibetan plateau. However, the skill of seasonal forecasts is limited in most regions, with anomaly correlation coefficients varying between 0.2 and 0.5 for 1-3 month precipitation totals. This raises the question whether seasonal hydrological forecasting is feasible. Here, we make the case that it is. Using the example of statistical forecasts of NAO-strength and related precipitation anomalies over Europe, we show that the skill of large-scale streamflow forecasts is generally much higher than the precipitation forecasts itself, provided that the initial state of the system is accurately estimated. In the latter case, even the precipitation climatology can produce skillful results. This is due to the inertia of the hydrological system rooted in the storage of soil moisture, groundwater and snow pack, as corroborated by a recent study using snow observations for seasonal streamflow forecasting in the Western US. These examples seem to suggest that for accurate seasonal hydrological forecasting, correct state estimation is more important than accurate seasonal meteorological forecasts. However, large-scale estimation of hydrological states is difficult and validation of large-scale hydrological models often reveals large biases in e.g. streamflow estimates. Fortunately, as shown with a validation study of the global model PCR-GLOBWB, these biases are of less importance when seasonal forecasts are evaluated in terms of their ability to reproduce anomalous flows and extreme events, i.e. by anomaly correlations or categorical quantile
Towards large scale production and separation of carbon nanotubes
NASA Astrophysics Data System (ADS)
Alvarez, Noe T.
Since their discovery, carbon nanotubes (CNTs) have boosted the research and applications of nanotechnology; however, many applications of CNTs are inaccessible because they depend upon large-scale CNT production and separations. Type, chirality and diameter control of CNTs determine many of their physical properties, and such control is still not accesible. This thesis studies the fundamentals for scalable selective reactions of HiPCo CNTs as well as the early phase of routes to an inexpensive approach for large-scale CNT production. In the growth part, this thesis covers a complete wet-chemistry process of catalyst and catalyst support deposition for growth of vertically aligned (VA) CNTs. A wet-chemistry preparation process has significant importance for CNT synthesis through chemical vapor deposition (CVD). CVD is by far, the most suitable and inexpensive process for large-scale CNT production when compared to other common processes such as laser ablation and arc discharge. However, its potential has been limited by low-yielding and difficult preparation processes of catalyst and its support, therefore its competitiveness has been reduced. The wet-chemistry process takes advantage of current nanoparticle technology to deposit the catalyst and the catalyst support as a thin film of nanoparticles, making the protocol simple compared to electron beam evaporation and sputtering processes. In the CNT selective reactions part, this thesis studies UV irradiation of individually dispersed HiPCo CNTs that generates auto-selective reactions in the liquid phase with good control over their diameter and chirality. This technique is ideal for large-scale and continuous-process of separations of CNTs by diameter and type. Additionally, an innovative simple catalyst deposition through abrasion is demonstrated. Simple friction between the catalyst and the substrates deposit a high enough density of metal catalyst particles for successful CNT growth. This simple approach has
Quantum computation for large-scale image classification
NASA Astrophysics Data System (ADS)
Ruan, Yue; Chen, Hanwu; Tan, Jianing; Li, Xi
2016-10-01
Due to the lack of an effective quantum feature extraction method, there is currently no effective way to perform quantum image classification or recognition. In this paper, for the first time, a global quantum feature extraction method based on Schmidt decomposition is proposed. A revised quantum learning algorithm is also proposed that will classify images by computing the Hamming distance of these features. From the experimental results derived from the benchmark database Caltech 101, and an analysis of the algorithm, an effective approach to large-scale image classification is derived and proposed against the background of big data.
Generation of Large-Scale Winds in Horizontally Anisotropic Convection.
von Hardenberg, J; Goluskin, D; Provenzale, A; Spiegel, E A
2015-09-25
We simulate three-dimensional, horizontally periodic Rayleigh-Bénard convection, confined between free-slip horizontal plates and rotating about a distant 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. PMID:26451558
Large Scale Composite Manufacturing for Heavy Lift Launch Vehicles
NASA Technical Reports Server (NTRS)
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.
Search for Large Scale Anisotropies with the Pierre Auger Observatory
NASA Astrophysics Data System (ADS)
Bonino, R.; Pierre Auger Collaboration
The Pierre Auger Observatory studies the nature and the origin of Ultra High Energy Cosmic Rays (>3\\cdot1018 eV). Completed at the end of 2008, it has been continuously operating for more than six years. Using data collected from 1 January 2004 until 31 March 2009, we search for large scale anisotropies with two complementary analyses in different energy windows. No significant anisotropies are observed, resulting in bounds on the first harmonic amplitude at the 1% level at EeV energies.
Large-Scale periodic solar velocities: An observational study
NASA Technical Reports Server (NTRS)
Dittmer, P. H.
1977-01-01
Observations of large-scale solar velocities were made using the mean field telescope and Babcock magnetograph of the Stanford Solar Observatory. Observations were made in the magnetically insensitive ion line at 5124 A, with light from the center (limb) of the disk right (left) circularly polarized, so that the magnetograph measures the difference in wavelength between center and limb. Computer calculations are made of the wavelength difference produced by global pulsations for spherical harmonics up to second order and of the signal produced by displacing the solar image relative to polarizing optics or diffraction grating.
Evaluation of uncertainty in large-scale fusion metrology
NASA Astrophysics Data System (ADS)
Zhang, Fumin; Qu, Xinghua; Wu, Hongyan; Ye, Shenghua
2008-12-01
The expression system of uncertainty in conventional scale has been perfect, however, due to varies of error sources, it is still hard to obtain the uncertainty of large-scale instruments by common methods. In this paper, the uncertainty is evaluated by Monte Carlo simulation. The point-clouds created by this method are shown through computer visualization and point by point analysis is made. Thus, in fusion measurement, apart from the uncertainty of every instrument being expressed directly, the contribution every error source making for the whole uncertainty becomes easy to calculate. Finally, the application of this method in measuring tunnel component is given.
Large-scale sodium spray fire code validation (SOFICOV) test
Jeppson, D.W.; Muhlestein, L.D.
1985-01-01
A large-scale, sodium, spray fire code validation test was performed in the HEDL 850-m/sup 3/ Containment System Test Facility (CSTF) as part of the Sodium Spray Fire Code Validation (SOFICOV) program. Six hundred fifty eight kilograms of sodium spray was sprayed in an air atmosphere for a period of 2400 s. The sodium spray droplet sizes and spray pattern distribution were estimated. The containment atmosphere temperature and pressure response, containment wall temperature response and sodium reaction rate with oxygen were measured. These results are compared to post-test predictions using SPRAY and NACOM computer codes.
Large scale obscuration and related climate effects open literature bibliography
Russell, N.A.; Geitgey, J.; Behl, Y.K.; Zak, B.D.
1994-05-01
Large scale obscuration and related climate effects of nuclear detonations first became a matter of concern in connection with the so-called ``Nuclear Winter Controversy`` in the early 1980`s. Since then, the world has changed. Nevertheless, concern remains about the atmospheric effects of nuclear detonations, but the source of concern has shifted. Now it focuses less on global, and more on regional effects and their resulting impacts on the performance of electro-optical and other defense-related systems. This bibliography reflects the modified interest.
Large-Scale Compton Imaging for Wide-Area Surveillance
Lange, D J; Manini, H A; Wright, D M
2006-03-01
We study the performance of a large-scale Compton imaging detector placed in a low-flying aircraft, used to search wide areas for rad/nuc threat sources. In this paper we investigate the performance potential of equipping aerial platforms with gamma-ray detectors that have photon sensitivity up to a few MeV. We simulate the detector performance, and present receiver operating characteristics (ROC) curves for a benchmark scenario using a {sup 137}Cs source. The analysis uses a realistic environmental background energy spectrum and includes air attenuation.
Frequency domain multiplexing for large-scale bolometer arrays
Spieler, Helmuth
2002-05-31
The development of planar fabrication techniques for superconducting transition-edge sensors has brought large-scale arrays of 1000 pixels or more to the realm of practicality. This raises the problem of reading out a large number of sensors with a tractable number of connections. A possible solution is frequency-domain multiplexing. I summarize basic principles, present various circuit topologies, and discuss design trade-offs, noise performance, cross-talk and dynamic range. The design of a practical device and its readout system is described with a discussion of fabrication issues, practical limits and future prospects.
Quantum computation for large-scale image classification
NASA Astrophysics Data System (ADS)
Ruan, Yue; Chen, Hanwu; Tan, Jianing; Li, Xi
2016-07-01
Due to the lack of an effective quantum feature extraction method, there is currently no effective way to perform quantum image classification or recognition. In this paper, for the first time, a global quantum feature extraction method based on Schmidt decomposition is proposed. A revised quantum learning algorithm is also proposed that will classify images by computing the Hamming distance of these features. From the experimental results derived from the benchmark database Caltech 101, and an analysis of the algorithm, an effective approach to large-scale image classification is derived and proposed against the background of big data.
Radiative shocks on large scale lasers. Preliminary results
NASA Astrophysics Data System (ADS)
Leygnac, S.; Bouquet, S.; Stehle, C.; Barroso, P.; Batani, D.; Benuzzi, A.; Cathala, B.; Chièze, J.-P.; Fleury, X.; Grandjouan, N.; Grenier, J.; Hall, T.; Henry, E.; Koenig, M.; Lafon, J. P. J.; Malka, V.; Marchet, B.; Merdji, H.; Michaut, C.; Poles, L.; Thais, F.
2001-05-01
Radiative shocks, those structure is strongly influenced by the radiation field, are present in various astrophysical objects (circumstellar envelopes of variable stars, supernovae ...). Their modeling is very difficult and thus will take benefit from experimental informations. This approach is now possible using large scale lasers. Preliminary experiments have been performed with the nanosecond LULI laser at Ecole Polytechnique (France) in 2000. A radiative shock has been obtained in a low pressure xenon cell. The preparation of such experiments and their interpretation is performed using analytical calculations and numerical simulations.
Large-scale genotoxicity assessments in the marine environment.
Hose, J E
1994-12-01
There are a number of techniques for detecting genotoxicity in the marine environment, and many are applicable to large-scale field assessments. Certain tests can be used to evaluate responses in target organisms in situ while others utilize surrogate organisms exposed to field samples in short-term laboratory bioassays. Genotoxicity endpoints appear distinct from traditional toxicity endpoints, but some have chemical or ecotoxicologic correlates. One versatile end point, the frequency of anaphase aberrations, has been used in several large marine assessments to evaluate genotoxicity in the New York Bight, in sediment from San Francisco Bay, and following the Exxon Valdez oil spill. PMID:7713029
[National Strategic Promotion for Large-Scale Clinical Cancer Research].
Toyama, Senya
2016-04-01
The number of clinical research by clinical cancer study groups has been decreasing this year in Japan. They say the reason is the abolition of donations to the groups from the pharmaceutical companies after the Diovan scandal. But I suppose fundamental problem is that government-supported large-scale clinical cancer study system for evidence based medicine (EBM) has not been fully established. An urgent establishment of the system based on the national strategy is needed for the cancer patients and the public health promotion.
Enabling Large-Scale Biomedical Analysis in the Cloud
Lin, Ying-Chih; Yu, Chin-Sheng; Lin, Yen-Jen
2013-01-01
Recent progress in high-throughput instrumentations has led to an astonishing growth in both volume and complexity of biomedical data collected from various sources. The planet-size data brings serious challenges to the storage and computing technologies. Cloud computing is an alternative to crack the nut because it gives concurrent consideration to enable storage and high-performance computing on large-scale data. This work briefly introduces the data intensive computing system and summarizes existing cloud-based resources in bioinformatics. These developments and applications would facilitate biomedical research to make the vast amount of diversification data meaningful and usable. PMID:24288665
Large-scale deformation associated with ridge subduction
Geist, E.L.; Fisher, M.A.; Scholl, D. W.
1993-01-01
Continuum models are used to investigate the large-scale deformation associated with the subduction of aseismic ridges. Formulated in the horizontal plane using thin viscous sheet theory, these models measure the horizontal transmission of stress through the arc lithosphere accompanying ridge subduction. Modelling was used to compare the Tonga arc and Louisville ridge collision with the New Hebrides arc and d'Entrecasteaux ridge collision, which have disparate arc-ridge intersection speeds but otherwise similar characteristics. Models of both systems indicate that diffuse deformation (low values of the effective stress-strain exponent n) are required to explain the observed deformation. -from Authors
A multilevel optimization of large-scale dynamic systems
NASA Technical Reports Server (NTRS)
Siljak, D. D.; Sundareshan, M. K.
1976-01-01
A multilevel feedback control scheme is proposed for optimization of large-scale systems composed of a number of (not necessarily weakly coupled) subsystems. Local controllers are used to optimize each subsystem, ignoring the interconnections. Then, a global controller may be applied to minimize the effect of interconnections and improve the performance of the overall system. At the cost of suboptimal performance, this optimization strategy ensures invariance of suboptimality and stability of the systems under structural perturbations whereby subsystems are disconnected and again connected during operation.
Large-Scale Purification of Peroxisomes for Preparative Applications.
Cramer, Jana; Effelsberg, Daniel; Girzalsky, Wolfgang; Erdmann, Ralf
2015-09-01
This protocol is designed for large-scale isolation of highly purified peroxisomes from Saccharomyces cerevisiae using two consecutive density gradient centrifugations. Instructions are provided for harvesting up to 60 g of oleic acid-induced yeast cells for the preparation of spheroplasts and generation of organellar pellets (OPs) enriched in peroxisomes and mitochondria. The OPs are loaded onto eight continuous 36%-68% (w/v) sucrose gradients. After centrifugation, the peak peroxisomal fractions are determined by measurement of catalase activity. These fractions are subsequently pooled and subjected to a second density gradient centrifugation using 20%-40% (w/v) Nycodenz. PMID:26330621
Large-scale Direct Targeting for Drug Repositioning and Discovery.
Zheng, Chunli; Guo, Zihu; Huang, Chao; Wu, Ziyin; Li, Yan; Chen, Xuetong; Fu, Yingxue; Ru, Jinlong; Ali Shar, Piar; Wang, Yuan; Wang, Yonghua
2015-01-01
A system-level identification of drug-target direct interactions is vital to drug repositioning and discovery. However, the biological means on a large scale remains challenging and expensive even nowadays. The available computational models mainly focus on predicting indirect interactions or direct interactions on a small scale. To address these problems, in this work, a novel algorithm termed weighted ensemble similarity (WES) has been developed to identify drug direct targets based on a large-scale of 98,327 drug-target relationships. WES includes: (1) identifying the key ligand structural features that are highly-related to the pharmacological properties in a framework of ensemble; (2) determining a drug's affiliation of a target by evaluation of the overall similarity (ensemble) rather than a single ligand judgment; and (3) integrating the standardized ensemble similarities (Z score) by Bayesian network and multi-variate kernel approach to make predictions. All these lead WES to predict drug direct targets with external and experimental test accuracies of 70% and 71%, respectively. This shows that the WES method provides a potential in silico model for drug repositioning and discovery.
Strong CP Violation in Large Scale Magnetic Fields
Faccioli, P.; Millo, R.
2007-11-19
We explore the possibility of improving on the present experimental bounds on Strong CP violation, by studying processes in which the smallness of {theta} is compensated by the presence of some other very large scale. In particular, we study the response of the {theta} vacuum to large-scale magnetic fields, whose correlation lengths can be as large as the size of galaxy clusters. We find that, if strong interactions break CP, an external magnetic field would induce an electric vacuum polarization along the same direction. As a consequence, u,d-bar and d,u-bar quarks would accumulate in the opposite regions of the space, giving raise to an electric dipole moment. We estimate the magnitude of this effect both at T = 0 and for 0
Alignment of quasar polarizations with large-scale structures
NASA Astrophysics Data System (ADS)
Hutsemékers, D.; Braibant, L.; Pelgrims, V.; Sluse, D.
2014-12-01
We have measured the optical linear polarization of quasars belonging to Gpc scale quasar groups at redshift z ~ 1.3. Out of 93 quasars observed, 19 are significantly polarized. We found that quasar polarization vectors are either parallel or perpendicular to the directions of the large-scale structures to which they belong. Statistical tests indicate that the probability that this effect can be attributed to randomly oriented polarization vectors is on the order of 1%. We also found that quasars with polarization perpendicular to the host structure preferentially have large emission line widths while objects with polarization parallel to the host structure preferentially have small emission line widths. Considering that quasar polarization is usually either parallel or perpendicular to the accretion disk axis depending on the inclination with respect to the line of sight, and that broader emission lines originate from quasars seen at higher inclinations, we conclude that quasar spin axes are likely parallel to their host large-scale structures. Based on observations made with ESO Telescopes at the La Silla Paranal Observatory under program ID 092.A-0221.Table 1 is available in electronic form at http://www.aanda.org
Maestro: An Orchestration Framework for Large-Scale WSN Simulations
Riliskis, Laurynas; Osipov, Evgeny
2014-01-01
Contemporary wireless sensor networks (WSNs) have evolved into large and complex systems and are one of the main technologies used in cyber-physical systems and the Internet of Things. Extensive research on WSNs has led to the development of diverse solutions at all levels of software architecture, including protocol stacks for communications. This multitude of solutions is due to the limited computational power and restrictions on energy consumption that must be accounted for when designing typical WSN systems. It is therefore challenging to develop, test and validate even small WSN applications, and this process can easily consume significant resources. Simulations are inexpensive tools for testing, verifying and generally experimenting with new technologies in a repeatable fashion. Consequently, as the size of the systems to be tested increases, so does the need for large-scale simulations. This article describes a tool called Maestro for the automation of large-scale simulation and investigates the feasibility of using cloud computing facilities for such task. Using tools that are built into Maestro, we demonstrate a feasible approach for benchmarking cloud infrastructure in order to identify cloud Virtual Machine (VM)instances that provide an optimal balance of performance and cost for a given simulation. PMID:24647123
Ecohydrological modeling for large-scale environmental impact assessment.
Woznicki, Sean A; Nejadhashemi, A Pouyan; Abouali, Mohammad; Herman, Matthew R; Esfahanian, Elaheh; Hamaamin, Yaseen A; Zhang, Zhen
2016-02-01
Ecohydrological models are frequently used to assess the biological integrity of unsampled streams. These models vary in complexity and scale, and their utility depends on their final application. Tradeoffs are usually made in model scale, where large-scale models are useful for determining broad impacts of human activities on biological conditions, and regional-scale (e.g. watershed or ecoregion) models provide stakeholders greater detail at the individual stream reach level. Given these tradeoffs, the objective of this study was to develop large-scale stream health models with reach level accuracy similar to regional-scale models thereby allowing for impacts assessments and improved decision-making capabilities. To accomplish this, four measures of biological integrity (Ephemeroptera, Plecoptera, and Trichoptera taxa (EPT), Family Index of Biotic Integrity (FIBI), Hilsenhoff Biotic Index (HBI), and fish Index of Biotic Integrity (IBI)) were modeled based on four thermal classes (cold, cold-transitional, cool, and warm) of streams that broadly dictate the distribution of aquatic biota in Michigan. The Soil and Water Assessment Tool (SWAT) was used to simulate streamflow and water quality in seven watersheds and the Hydrologic Index Tool was used to calculate 171 ecologically relevant flow regime variables. Unique variables were selected for each thermal class using a Bayesian variable selection method. The variables were then used in development of adaptive neuro-fuzzy inference systems (ANFIS) models of EPT, FIBI, HBI, and IBI. ANFIS model accuracy improved when accounting for stream thermal class rather than developing a global model. PMID:26595397
Simulating the large-scale structure of HI intensity maps
NASA Astrophysics Data System (ADS)
Seehars, Sebastian; Paranjape, Aseem; Witzemann, Amadeus; Refregier, Alexandre; Amara, Adam; Akeret, Joel
2016-03-01
Intensity mapping of neutral hydrogen (HI) is a promising observational probe of cosmology and large-scale structure. We present wide field simulations of HI intensity maps based on N-body simulations of a 2.6 Gpc / h box with 20483 particles (particle mass 1.6 × 1011 Msolar / h). Using a conditional mass function to populate the simulated dark matter density field with halos below the mass resolution of the simulation (108 Msolar / h < Mhalo < 1013 Msolar / h), we assign HI to those halos according to a phenomenological halo to HI mass relation. The simulations span a redshift range of 0.35 lesssim z lesssim 0.9 in redshift bins of width Δ z ≈ 0.05 and cover a quarter of the sky at an angular resolution of about 7'. We use the simulated intensity maps to study the impact of non-linear effects and redshift space distortions on the angular clustering of HI. Focusing on the autocorrelations of the maps, we apply and compare several estimators for the angular power spectrum and its covariance. We verify that these estimators agree with analytic predictions on large scales and study the validity of approximations based on Gaussian random fields, particularly in the context of the covariance. We discuss how our results and the simulated maps can be useful for planning and interpreting future HI intensity mapping surveys.
Large scale floodplain mapping using a hydrogeomorphic method
NASA Astrophysics Data System (ADS)
Nardi, F.; Yan, K.; Di Baldassarre, G.; Grimaldi, S.
2013-12-01
Floodplain landforms are clearly distinguishable as respect to adjacent hillslopes being the trace of severe floods that shaped the terrain. As a result digital topography intrinsically contains the floodplain information, this works presents the results of the application of a DEM-based large scale hydrogeomorphic floodplain delineation method. The proposed approach, based on the integration of terrain analysis algorithms in a GIS framework, automatically identifies the potentially frequently saturated zones of riparian areas by analysing the maximum flood flow heights associated to stream network nodes as respect to surrounding uplands. Flow heights are estimated by imposing a Leopold's law that scales with the contributing area. Presented case studies include the floodplain map of large river basins for the entire Italian territory , that are also used for calibrating the Leopold scaling parameters, as well as additional large international river basins in different climatic and geomorphic characteristics posing the base for the use of such approach for global floodplain mapping. The proposed tool could be useful to detect the hydrological change since it can easily provide maps to verify the flood impact on human activities and vice versa how the human activities changed in floodplain areas at large scale.
Large-scale network-level processes during entrainment
Lithari, Chrysa; Sánchez-García, Carolina; Ruhnau, Philipp; Weisz, Nathan
2016-01-01
Visual rhythmic stimulation evokes a robust power increase exactly at the stimulation frequency, the so-called steady-state response (SSR). Localization of visual SSRs normally shows a very focal modulation of power in visual cortex and led to the treatment and interpretation of SSRs as a local phenomenon. Given the brain network dynamics, we hypothesized that SSRs have additional large-scale effects on the brain functional network that can be revealed by means of graph theory. We used rhythmic visual stimulation at a range of frequencies (4–30 Hz), recorded MEG and investigated source level connectivity across the whole brain. Using graph theoretical measures we observed a frequency-unspecific reduction of global density in the alpha band “disconnecting” visual cortex from the rest of the network. Also, a frequency-specific increase of connectivity between occipital cortex and precuneus was found at the stimulation frequency that exhibited the highest resonance (30 Hz). In conclusion, we showed that SSRs dynamically re-organized the brain functional network. These large-scale effects should be taken into account not only when attempting to explain the nature of SSRs, but also when used in various experimental designs. PMID:26835557
Scalable WIM: effective exploration in large-scale astrophysical environments.
Li, Yinggang; Fu, Chi-Wing; Hanson, Andrew J
2006-01-01
Navigating through large-scale virtual environments such as simulations of the astrophysical Universe is difficult. The huge spatial range of astronomical models and the dominance of empty space make it hard for users to travel across cosmological scales effectively, and the problem of wayfinding further impedes the user's ability to acquire reliable spatial knowledge of astronomical contexts. We introduce a new technique called the scalable world-in-miniature (WIM) map as a unifying interface to facilitate travel and wayfinding in a virtual environment spanning gigantic spatial scales: Power-law spatial scaling enables rapid and accurate transitions among widely separated regions; logarithmically mapped miniature spaces offer a global overview mode when the full context is too large; 3D landmarks represented in the WIM are enhanced by scale, positional, and directional cues to augment spatial context awareness; a series of navigation models are incorporated into the scalable WIM to improve the performance of travel tasks posed by the unique characteristics of virtual cosmic exploration. The scalable WIM user interface supports an improved physical navigation experience and assists pragmatic cognitive understanding of a visualization context that incorporates the features of large-scale astronomy.
Large-scale network-level processes during entrainment.
Lithari, Chrysa; Sánchez-García, Carolina; Ruhnau, Philipp; Weisz, Nathan
2016-03-15
Visual rhythmic stimulation evokes a robust power increase exactly at the stimulation frequency, the so-called steady-state response (SSR). Localization of visual SSRs normally shows a very focal modulation of power in visual cortex and led to the treatment and interpretation of SSRs as a local phenomenon. Given the brain network dynamics, we hypothesized that SSRs have additional large-scale effects on the brain functional network that can be revealed by means of graph theory. We used rhythmic visual stimulation at a range of frequencies (4-30 Hz), recorded MEG and investigated source level connectivity across the whole brain. Using graph theoretical measures we observed a frequency-unspecific reduction of global density in the alpha band "disconnecting" visual cortex from the rest of the network. Also, a frequency-specific increase of connectivity between occipital cortex and precuneus was found at the stimulation frequency that exhibited the highest resonance (30 Hz). In conclusion, we showed that SSRs dynamically re-organized the brain functional network. These large-scale effects should be taken into account not only when attempting to explain the nature of SSRs, but also when used in various experimental designs. PMID:26835557
Exploring Cloud Computing for Large-scale Scientific Applications
Lin, Guang; Han, Binh; Yin, Jian; Gorton, Ian
2013-06-27
This paper explores cloud computing for large-scale data-intensive scientific applications. Cloud computing is attractive because it provides hardware and software resources on-demand, which relieves the burden of acquiring and maintaining a huge amount of resources that may be used only once by a scientific application. However, unlike typical commercial applications that often just requires a moderate amount of ordinary resources, large-scale scientific applications often need to process enormous amount of data in the terabyte or even petabyte range and require special high performance hardware with low latency connections to complete computation in a reasonable amount of time. To address these challenges, we build an infrastructure that can dynamically select high performance computing hardware across institutions and dynamically adapt the computation to the selected resources to achieve high performance. We have also demonstrated the effectiveness of our infrastructure by building a system biology application and an uncertainty quantification application for carbon sequestration, which can efficiently utilize data and computation resources across several institutions.
Large-scale anisotropy in stably stratified rotating flows.
Marino, R; Mininni, P D; Rosenberg, D L; Pouquet, A
2014-08-01
We present results from direct numerical simulations of the Boussinesq equations in the presence of rotation and/or stratification, both in the vertical direction. The runs are forced isotropically and randomly at small scales and have spatial resolutions of up to 1024(3) grid points and Reynolds numbers of ≈1000. We first show that solutions with negative energy flux and inverse cascades develop in rotating turbulence, whether or not stratification is present. However, the purely stratified case is characterized instead by an early-time, highly anisotropic transfer to large scales with almost zero net isotropic energy flux. This is consistent with previous studies that observed the development of vertically sheared horizontal winds, although only at substantially later times. However, and unlike previous works, when sufficient scale separation is allowed between the forcing scale and the domain size, the kinetic energy displays a perpendicular (horizontal) spectrum with power-law behavior compatible with ∼k(⊥)(-5/3), including in the absence of rotation. In this latter purely stratified case, such a spectrum is the result of a direct cascade of the energy contained in the large-scale horizontal wind, as is evidenced by a strong positive flux of energy in the parallel direction at all scales including the largest resolved scales.
Large-scale anisotropy in stably stratified rotating flows
Marino, R.; Mininni, P. D.; Rosenberg, D. L.; Pouquet, A.
2014-08-28
We present results from direct numerical simulations of the Boussinesq equations in the presence of rotation and/or stratification, both in the vertical direction. The runs are forced isotropically and randomly at small scales and have spatial resolutions of up to $1024^3$ grid points and Reynolds numbers of $\\approx 1000$. We first show that solutions with negative energy flux and inverse cascades develop in rotating turbulence, whether or not stratification is present. However, the purely stratified case is characterized instead by an early-time, highly anisotropic transfer to large scales with almost zero net isotropic energy flux. This is consistent with previous studies that observed the development of vertically sheared horizontal winds, although only at substantially later times. However, and unlike previous works, when sufficient scale separation is allowed between the forcing scale and the domain size, the total energy displays a perpendicular (horizontal) spectrum with power law behavior compatible with $\\sim k_\\perp^{-5/3}$, including in the absence of rotation. In this latter purely stratified case, such a spectrum is the result of a direct cascade of the energy contained in the large-scale horizontal wind, as is evidenced by a strong positive flux of energy in the parallel direction at all scales including the largest resolved scales.
Large-scale anisotropy in stably stratified rotating flows
Marino, R.; Mininni, P. D.; Rosenberg, D. L.; Pouquet, A.
2014-08-28
We present results from direct numerical simulations of the Boussinesq equations in the presence of rotation and/or stratification, both in the vertical direction. The runs are forced isotropically and randomly at small scales and have spatial resolutions of up tomore » $1024^3$ grid points and Reynolds numbers of $$\\approx 1000$$. We first show that solutions with negative energy flux and inverse cascades develop in rotating turbulence, whether or not stratification is present. However, the purely stratified case is characterized instead by an early-time, highly anisotropic transfer to large scales with almost zero net isotropic energy flux. This is consistent with previous studies that observed the development of vertically sheared horizontal winds, although only at substantially later times. However, and unlike previous works, when sufficient scale separation is allowed between the forcing scale and the domain size, the total energy displays a perpendicular (horizontal) spectrum with power law behavior compatible with $$\\sim k_\\perp^{-5/3}$$, including in the absence of rotation. In this latter purely stratified case, such a spectrum is the result of a direct cascade of the energy contained in the large-scale horizontal wind, as is evidenced by a strong positive flux of energy in the parallel direction at all scales including the largest resolved scales.« less
Maestro: an orchestration framework for large-scale WSN simulations.
Riliskis, Laurynas; Osipov, Evgeny
2014-01-01
Contemporary wireless sensor networks (WSNs) have evolved into large and complex systems and are one of the main technologies used in cyber-physical systems and the Internet of Things. Extensive research on WSNs has led to the development of diverse solutions at all levels of software architecture, including protocol stacks for communications. This multitude of solutions is due to the limited computational power and restrictions on energy consumption that must be accounted for when designing typical WSN systems. It is therefore challenging to develop, test and validate even small WSN applications, and this process can easily consume significant resources. Simulations are inexpensive tools for testing, verifying and generally experimenting with new technologies in a repeatable fashion. Consequently, as the size of the systems to be tested increases, so does the need for large-scale simulations. This article describes a tool called Maestro for the automation of large-scale simulation and investigates the feasibility of using cloud computing facilities for such task. Using tools that are built into Maestro, we demonstrate a feasible approach for benchmarking cloud infrastructure in order to identify cloud Virtual Machine (VM)instances that provide an optimal balance of performance and cost for a given simulation. PMID:24647123
Large-scale magnetic fields in magnetohydrodynamic turbulence.
Alexakis, Alexandros
2013-02-22
High Reynolds number magnetohydrodynamic turbulence in the presence of zero-flux large-scale magnetic fields is investigated as a function of the magnetic field strength. For a variety of flow configurations, the energy dissipation rate [symbol: see text] follows the scaling [Symbol: see text] proportional U(rms)(3)/ℓ even when the large-scale magnetic field energy is twenty times larger than the kinetic energy. A further increase of the magnetic energy showed a transition to the [Symbol: see text] proportional U(rms)(2) B(rms)/ℓ scaling implying that magnetic shear becomes more efficient at this point at cascading the energy than the velocity fluctuations. Strongly helical configurations form nonturbulent helicity condensates that deviate from these scalings. Weak turbulence scaling was absent from the investigation. Finally, the magnetic energy spectra support the Kolmogorov spectrum k(-5/3) while kinetic energy spectra are closer to the Iroshnikov-Kraichnan spectrum k(-3/2) as observed in the solar wind.
The combustion behavior of large scale lithium titanate battery.
Huang, Peifeng; Wang, Qingsong; Li, Ke; Ping, Ping; Sun, Jinhua
2015-01-01
Safety problem is always a big obstacle for lithium battery marching to large scale application. However, the knowledge on the battery combustion behavior is limited. To investigate the combustion behavior of large scale lithium battery, three 50 Ah Li(Ni(x)Co(y)Mn(z))O2/Li(4)Ti(5)O(12) batteries under different state of charge (SOC) were heated to fire. The flame size variation is depicted to analyze the combustion behavior directly. The mass loss rate, temperature and heat release rate are used to analyze the combustion behavior in reaction way deeply. Based on the phenomenon, the combustion process is divided into three basic stages, even more complicated at higher SOC with sudden smoke flow ejected. The reason is that a phase change occurs in Li(Ni(x)Co(y)Mn(z))O2 material from layer structure to spinel structure. The critical temperatures of ignition are at 112-121 °C on anode tab and 139 to 147 °C on upper surface for all cells. But the heating time and combustion time become shorter with the ascending of SOC. The results indicate that the battery fire hazard increases with the SOC. It is analyzed that the internal short and the Li(+) distribution are the main causes that lead to the difference. PMID:25586064
Measuring Cosmic Expansion and Large Scale Structure with Destiny
NASA Technical Reports Server (NTRS)
Benford, Dominic J.; Lauer, Tod R.
2007-01-01
Destiny is a simple, direct, low cost mission to determine the properties of dark energy by obtaining a cosmologically deep supernova (SN) type Ia Hubble diagram and by measuring the large-scale mass power spectrum over time. Its science instrument is a 1.65m space telescope, featuring a near-infrared survey camera/spectrometer with a large field of view. During its first two years, Destiny will detect, observe, and characterize 23000 SN Ia events over the redshift interval 0.4
Exact-Differential Large-Scale Traffic Simulation
Hanai, Masatoshi; Suzumura, Toyotaro; Theodoropoulos, Georgios; Perumalla, Kalyan S
2015-01-01
Analyzing large-scale traffics by simulation needs repeating execution many times with various patterns of scenarios or parameters. Such repeating execution brings about big redundancy because the change from a prior scenario to a later scenario is very minor in most cases, for example, blocking only one of roads or changing the speed limit of several roads. In this paper, we propose a new redundancy reduction technique, called exact-differential simulation, which enables to simulate only changing scenarios in later execution while keeping exactly same results as in the case of whole simulation. The paper consists of two main efforts: (i) a key idea and algorithm of the exact-differential simulation, (ii) a method to build large-scale traffic simulation on the top of the exact-differential simulation. In experiments of Tokyo traffic simulation, the exact-differential simulation shows 7.26 times as much elapsed time improvement in average and 2.26 times improvement even in the worst case as the whole simulation.
Ecohydrological modeling for large-scale environmental impact assessment.
Woznicki, Sean A; Nejadhashemi, A Pouyan; Abouali, Mohammad; Herman, Matthew R; Esfahanian, Elaheh; Hamaamin, Yaseen A; Zhang, Zhen
2016-02-01
Ecohydrological models are frequently used to assess the biological integrity of unsampled streams. These models vary in complexity and scale, and their utility depends on their final application. Tradeoffs are usually made in model scale, where large-scale models are useful for determining broad impacts of human activities on biological conditions, and regional-scale (e.g. watershed or ecoregion) models provide stakeholders greater detail at the individual stream reach level. Given these tradeoffs, the objective of this study was to develop large-scale stream health models with reach level accuracy similar to regional-scale models thereby allowing for impacts assessments and improved decision-making capabilities. To accomplish this, four measures of biological integrity (Ephemeroptera, Plecoptera, and Trichoptera taxa (EPT), Family Index of Biotic Integrity (FIBI), Hilsenhoff Biotic Index (HBI), and fish Index of Biotic Integrity (IBI)) were modeled based on four thermal classes (cold, cold-transitional, cool, and warm) of streams that broadly dictate the distribution of aquatic biota in Michigan. The Soil and Water Assessment Tool (SWAT) was used to simulate streamflow and water quality in seven watersheds and the Hydrologic Index Tool was used to calculate 171 ecologically relevant flow regime variables. Unique variables were selected for each thermal class using a Bayesian variable selection method. The variables were then used in development of adaptive neuro-fuzzy inference systems (ANFIS) models of EPT, FIBI, HBI, and IBI. ANFIS model accuracy improved when accounting for stream thermal class rather than developing a global model.
Systematic renormalization of the effective theory of Large Scale Structure
NASA Astrophysics Data System (ADS)
Akbar Abolhasani, Ali; Mirbabayi, Mehrdad; Pajer, Enrico
2016-05-01
A perturbative description of Large Scale Structure is a cornerstone of our understanding of the observed distribution of matter in the universe. Renormalization is an essential and defining step to make this description physical and predictive. Here we introduce a systematic renormalization procedure, which neatly associates counterterms to the UV-sensitive diagrams order by order, as it is commonly done in quantum field theory. As a concrete example, we renormalize the one-loop power spectrum and bispectrum of both density and velocity. In addition, we present a series of results that are valid to all orders in perturbation theory. First, we show that while systematic renormalization requires temporally non-local counterterms, in practice one can use an equivalent basis made of local operators. We give an explicit prescription to generate all counterterms allowed by the symmetries. Second, we present a formal proof of the well-known general argument that the contribution of short distance perturbations to large scale density contrast δ and momentum density π(k) scale as k2 and k, respectively. Third, we demonstrate that the common practice of introducing counterterms only in the Euler equation when one is interested in correlators of δ is indeed valid to all orders.
Detecting differential protein expression in large-scale population proteomics
Ryu, Soyoung; Qian, Weijun; Camp, David G.; Smith, Richard D.; Tompkins, Ronald G.; Davis, Ronald W.; Xiao, Wenzhong
2014-06-17
Mass spectrometry-based high-throughput quantitative proteomics shows great potential in clinical biomarker studies, identifying and quantifying thousands of proteins in biological samples. However, methods are needed to appropriately handle issues/challenges unique to mass spectrometry data in order to detect as many biomarker proteins as possible. One issue is that different mass spectrometry experiments generate quite different total numbers of quantified peptides, which can result in more missing peptide abundances in an experiment with a smaller total number of quantified peptides. Another issue is that the quantification of peptides is sometimes absent, especially for less abundant peptides and such missing values contain the information about the peptide abundance. Here, we propose a Significance Analysis for Large-scale Proteomics Studies (SALPS) that handles missing peptide intensity values caused by the two mechanisms mentioned above. Our model has a robust performance in both simulated data and proteomics data from a large clinical study. Because varying patients’ sample qualities and deviating instrument performances are not avoidable for clinical studies performed over the course of several years, we believe that our approach will be useful to analyze large-scale clinical proteomics data.
The combustion behavior of large scale lithium titanate battery
Huang, Peifeng; Wang, Qingsong; Li, Ke; Ping, Ping; Sun, Jinhua
2015-01-01
Safety problem is always a big obstacle for lithium battery marching to large scale application. However, the knowledge on the battery combustion behavior is limited. To investigate the combustion behavior of large scale lithium battery, three 50 Ah Li(NixCoyMnz)O2/Li4Ti5O12 batteries under different state of charge (SOC) were heated to fire. The flame size variation is depicted to analyze the combustion behavior directly. The mass loss rate, temperature and heat release rate are used to analyze the combustion behavior in reaction way deeply. Based on the phenomenon, the combustion process is divided into three basic stages, even more complicated at higher SOC with sudden smoke flow ejected. The reason is that a phase change occurs in Li(NixCoyMnz)O2 material from layer structure to spinel structure. The critical temperatures of ignition are at 112–121°C on anode tab and 139 to 147°C on upper surface for all cells. But the heating time and combustion time become shorter with the ascending of SOC. The results indicate that the battery fire hazard increases with the SOC. It is analyzed that the internal short and the Li+ distribution are the main causes that lead to the difference. PMID:25586064
Large scale reconstruction of the solar coronal magnetic field
NASA Astrophysics Data System (ADS)
Amari, T.; Aly, J.-J.; Chopin, P.; Canou, A.; Mikic, Z.
2014-10-01
It is now becoming necessary to access the global magnetic structure of the solar low corona at a large scale in order to understand its physics and more particularly the conditions of energization of the magnetic fields and the multiple connections between distant active regions (ARs) which may trigger eruptive events in an almost coordinated way. Various vector magnetographs, either on board spacecraft or ground-based, currently allow to obtain vector synoptic maps, composite magnetograms made of multiple interactive ARs, and full disk magnetograms. We present a method recently developed for reconstructing the global solar coronal magnetic field as a nonlinear force-free magnetic field in spherical geometry, generalizing our previous results in Cartesian geometry. This method is implemented in the new code XTRAPOLS, which thus appears as an extension of our active region scale code XTRAPOL. We apply our method by performing a reconstruction at a specific time for which we dispose of a set of composite data constituted of a vector magnetogram provided by SDO/HMI, embedded in a larger full disk vector magnetogram provided by the same instrument, finally embedded in a synoptic map provided by SOLIS. It turns out to be possible to access the large scale structure of the corona and its energetic contents, and also the AR scale, at which we recover the presence of a twisted flux rope in equilibrium.
THE LARGE-SCALE MAGNETIC FIELDS OF THIN ACCRETION DISKS
Cao Xinwu; Spruit, Hendrik C. E-mail: henk@mpa-garching.mpg.de
2013-03-10
Large-scale magnetic field threading an accretion disk is a key ingredient in the jet formation model. The most attractive scenario for the origin of such a large-scale field is the advection of the field by the gas in the accretion disk from the interstellar medium or a companion star. However, it is realized that outward diffusion of the accreted field is fast compared with the inward accretion velocity in a geometrically thin accretion disk if the value of the Prandtl number P{sub m} is around unity. In this work, we revisit this problem considering the angular momentum of the disk to be removed predominantly by the magnetically driven outflows. The radial velocity of the disk is significantly increased due to the presence of the outflows. Using a simplified model for the vertical disk structure, we find that even moderately weak fields can cause sufficient angular momentum loss via a magnetic wind to balance outward diffusion. There are two equilibrium points, one at low field strengths corresponding to a plasma-beta at the midplane of order several hundred, and one for strong accreted fields, {beta} {approx} 1. We surmise that the first is relevant for the accretion of weak, possibly external, fields through the outer parts of the disk, while the latter one could explain the tendency, observed in full three-dimensional numerical simulations, of strong flux bundles at the centers of disk to stay confined in spite of strong magnetororational instability turbulence surrounding them.
Online education in a large scale rehabilitation institution.
Mazzoleni, M Cristina; Rognoni, Carla; Pagani, Marco; Imbriani, Marcello
2012-01-01
Large scale multiple venue institutions face problems when delivering educations to their healthcare staff. The present study is aimed at evaluating the feasibility of relying on e-learning for at least part of the training of the Salvatore Maugeri Foundation healthcare staff. The paper reports the results of the delivery of e-learning courses to the personnel during a span of time of 7 months in order to assess the attitude to online courses attendance, the proportion between administered online education and administered traditional education, the economic sustainability of the online education delivery process. 37% of the total healthcare staff have attended online courses and 46% of nurses have proved to be the very active. The ratio between total number of credits and total number of courses for online and traditional education are respectively 18268/5 and 20354/96. These results point out that eLearning is not at all a niche tool used (or usable) by a limited number of people. Economic sustainability, assessed via personnel work hour saving, has been demonstrated. When distance learning is appropriate, online education is an effective, sustainable, well accepted mean to support and promote healthcare staff's education in a large scale institution. PMID:22491113
High Speed Networking and Large-scale Simulation in Geodynamics
NASA Technical Reports Server (NTRS)
Kuang, Weijia; Gary, Patrick; Seablom, Michael; Truszkowski, Walt; Odubiyi, Jide; Jiang, Weiyuan; Liu, Dong
2004-01-01
Large-scale numerical simulation has been one of the most important approaches for understanding global geodynamical processes. In this approach, peta-scale floating point operations (pflops) are often required to carry out a single physically-meaningful numerical experiment. For example, to model convective flow in the Earth's core and generation of the geomagnetic field (geodynamo), simulation for one magnetic free-decay time (approximately 15000 years) with a modest resolution of 150 in three spatial dimensions would require approximately 0.2 pflops. If such a numerical model is used to predict geomagnetic secular variation over decades and longer, with e.g. an ensemble Kalman filter assimilation approach, approximately 30 (and perhaps more) independent simulations of similar scales would be needed for one data assimilation analysis. Obviously, such a simulation would require an enormous computing resource that exceeds the capacity of a single facility currently available at our disposal. One solution is to utilize a very fast network (e.g. 10Gb optical networks) and available middleware (e.g. Globus Toolkit) to allocate available but often heterogeneous resources for such large-scale computing efforts. At NASA GSFC, we are experimenting with such an approach by networking several clusters for geomagnetic data assimilation research. We shall present our initial testing results in the meeting.
Large-Scale Low-Boom Inlet Test Overview
NASA Technical Reports Server (NTRS)
Hirt, Stefanie
2011-01-01
This presentation provides a high level overview of the Large-Scale Low-Boom Inlet Test and was presented at the Fundamental Aeronautics 2011 Technical Conference. In October 2010 a low-boom supersonic inlet concept with flow control was tested in the 8'x6' supersonic wind tunnel at NASA Glenn Research Center (GRC). The primary objectives of the test were to evaluate the inlet stability and operability of a large-scale low-boom supersonic inlet concept by acquiring performance and flowfield validation data, as well as evaluate simple, passive, bleedless inlet boundary layer control options. During this effort two models were tested: a dual stream inlet intended to model potential flight hardware and a single stream design to study a zero-degree external cowl angle and to permit surface flow visualization of the vortex generator flow control on the internal centerbody surface. The tests were conducted by a team of researchers from NASA GRC, Gulfstream Aerospace Corporation, University of Illinois at Urbana-Champaign, and the University of Virginia
Large-scale Direct Targeting for Drug Repositioning and Discovery
Zheng, Chunli; Guo, Zihu; Huang, Chao; Wu, Ziyin; Li, Yan; Chen, Xuetong; Fu, Yingxue; Ru, Jinlong; Ali Shar, Piar; Wang, Yuan; Wang, Yonghua
2015-01-01
A system-level identification of drug-target direct interactions is vital to drug repositioning and discovery. However, the biological means on a large scale remains challenging and expensive even nowadays. The available computational models mainly focus on predicting indirect interactions or direct interactions on a small scale. To address these problems, in this work, a novel algorithm termed weighted ensemble similarity (WES) has been developed to identify drug direct targets based on a large-scale of 98,327 drug-target relationships. WES includes: (1) identifying the key ligand structural features that are highly-related to the pharmacological properties in a framework of ensemble; (2) determining a drug’s affiliation of a target by evaluation of the overall similarity (ensemble) rather than a single ligand judgment; and (3) integrating the standardized ensemble similarities (Z score) by Bayesian network and multi-variate kernel approach to make predictions. All these lead WES to predict drug direct targets with external and experimental test accuracies of 70% and 71%, respectively. This shows that the WES method provides a potential in silico model for drug repositioning and discovery. PMID:26155766
Topographically Engineered Large Scale Nanostructures for Plasmonic Biosensing
Xiao, Bo; Pradhan, Sangram K.; Santiago, Kevin C.; Rutherford, Gugu N.; Pradhan, Aswini K.
2016-01-01
We demonstrate that a nanostructured metal thin film can achieve enhanced transmission efficiency and sharp resonances and use a large-scale and high-throughput nanofabrication technique for the plasmonic structures. The fabrication technique combines the features of nanoimprint and soft lithography to topographically construct metal thin films with nanoscale patterns. Metal nanogratings developed using this method show significantly enhanced optical transmission (up to a one-order-of-magnitude enhancement) and sharp resonances with full width at half maximum (FWHM) of ~15nm in the zero-order transmission using an incoherent white light source. These nanostructures are sensitive to the surrounding environment, and the resonance can shift as the refractive index changes. We derive an analytical method using a spatial Fourier transformation to understand the enhancement phenomenon and the sensing mechanism. The use of real-time monitoring of protein-protein interactions in microfluidic cells integrated with these nanostructures is demonstrated to be effective for biosensing. The perpendicular transmission configuration and large-scale structures provide a feasible platform without sophisticated optical instrumentation to realize label-free surface plasmon resonance (SPR) sensing. PMID:27072067
Extending large-scale forest inventories to assess urban forests.
Corona, Piermaria; Agrimi, Mariagrazia; Baffetta, Federica; Barbati, Anna; Chiriacò, Maria Vincenza; Fattorini, Lorenzo; Pompei, Enrico; Valentini, Riccardo; Mattioli, Walter
2012-03-01
Urban areas are continuously expanding today, extending their influence on an increasingly large proportion of woods and trees located in or nearby urban and urbanizing areas, the so-called urban forests. Although these forests have the potential for significantly improving the quality the urban environment and the well-being of the urban population, data to quantify the extent and characteristics of urban forests are still lacking or fragmentary on a large scale. In this regard, an expansion of the domain of multipurpose forest inventories like National Forest Inventories (NFIs) towards urban forests would be required. To this end, it would be convenient to exploit the same sampling scheme applied in NFIs to assess the basic features of urban forests. This paper considers approximately unbiased estimators of abundance and coverage of urban forests, together with estimators of the corresponding variances, which can be achieved from the first phase of most large-scale forest inventories. A simulation study is carried out in order to check the performance of the considered estimators under various situations involving the spatial distribution of the urban forests over the study area. An application is worked out on the data from the Italian NFI.
The combustion behavior of large scale lithium titanate battery.
Huang, Peifeng; Wang, Qingsong; Li, Ke; Ping, Ping; Sun, Jinhua
2015-01-14
Safety problem is always a big obstacle for lithium battery marching to large scale application. However, the knowledge on the battery combustion behavior is limited. To investigate the combustion behavior of large scale lithium battery, three 50 Ah Li(Ni(x)Co(y)Mn(z))O2/Li(4)Ti(5)O(12) batteries under different state of charge (SOC) were heated to fire. The flame size variation is depicted to analyze the combustion behavior directly. The mass loss rate, temperature and heat release rate are used to analyze the combustion behavior in reaction way deeply. Based on the phenomenon, the combustion process is divided into three basic stages, even more complicated at higher SOC with sudden smoke flow ejected. The reason is that a phase change occurs in Li(Ni(x)Co(y)Mn(z))O2 material from layer structure to spinel structure. The critical temperatures of ignition are at 112-121 °C on anode tab and 139 to 147 °C on upper surface for all cells. But the heating time and combustion time become shorter with the ascending of SOC. The results indicate that the battery fire hazard increases with the SOC. It is analyzed that the internal short and the Li(+) distribution are the main causes that lead to the difference.
The combustion behavior of large scale lithium titanate battery
NASA Astrophysics Data System (ADS)
Huang, Peifeng; Wang, Qingsong; Li, Ke; Ping, Ping; Sun, Jinhua
2015-01-01
Safety problem is always a big obstacle for lithium battery marching to large scale application. However, the knowledge on the battery combustion behavior is limited. To investigate the combustion behavior of large scale lithium battery, three 50 Ah Li(NixCoyMnz)O2/Li4Ti5O12 batteries under different state of charge (SOC) were heated to fire. The flame size variation is depicted to analyze the combustion behavior directly. The mass loss rate, temperature and heat release rate are used to analyze the combustion behavior in reaction way deeply. Based on the phenomenon, the combustion process is divided into three basic stages, even more complicated at higher SOC with sudden smoke flow ejected. The reason is that a phase change occurs in Li(NixCoyMnz)O2 material from layer structure to spinel structure. The critical temperatures of ignition are at 112-121°C on anode tab and 139 to 147°C on upper surface for all cells. But the heating time and combustion time become shorter with the ascending of SOC. The results indicate that the battery fire hazard increases with the SOC. It is analyzed that the internal short and the Li+ distribution are the main causes that lead to the difference.
The effective field theory of cosmological large scale structures
Carrasco, John Joseph M.; Hertzberg, Mark P.; Senatore, Leonardo
2012-09-20
Large scale structure surveys will likely become the next leading cosmological probe. In our universe, matter perturbations are large on short distances and small at long scales, i.e. strongly coupled in the UV and weakly coupled in the IR. To make precise analytical predictions on large scales, we develop an effective field theory formulated in terms of an IR effective fluid characterized by several parameters, such as speed of sound and viscosity. These parameters, determined by the UV physics described by the Boltzmann equation, are measured from N-body simulations. We find that the speed of sound of the effective fluid is c^{2}_{s} ≈ 10^{–6}c^{2} and that the viscosity contributions are of the same order. The fluid describes all the relevant physics at long scales k and permits a manifestly convergent perturbative expansion in the size of the matter perturbations δ(k) for all the observables. As an example, we calculate the correction to the power spectrum at order δ(k)^{4}. As a result, the predictions of the effective field theory are found to be in much better agreement with observation than standard cosmological perturbation theory, already reaching percent precision at this order up to a relatively short scale k ≃ 0.24h Mpc^{–1}.
[Privacy and public benefit in using large scale health databases].
Yamamoto, Ryuichi
2014-01-01
In Japan, large scale heath databases were constructed in a few years, such as National Claim insurance and health checkup database (NDB) and Japanese Sentinel project. But there are some legal issues for making adequate balance between privacy and public benefit by using such databases. NDB is carried based on the act for elderly person's health care but in this act, nothing is mentioned for using this database for general public benefit. Therefore researchers who use this database are forced to pay much concern about anonymization and information security that may disturb the research work itself. Japanese Sentinel project is a national project to detecting drug adverse reaction using large scale distributed clinical databases of large hospitals. Although patients give the future consent for general such purpose for public good, it is still under discussion using insufficiently anonymized data. Generally speaking, researchers of study for public benefit will not infringe patient's privacy, but vague and complex requirements of legislation about personal data protection may disturb the researches. Medical science does not progress without using clinical information, therefore the adequate legislation that is simple and clear for both researchers and patients is strongly required. In Japan, the specific act for balancing privacy and public benefit is now under discussion. The author recommended the researchers including the field of pharmacology should pay attention to, participate in the discussion of, and make suggestion to such act or regulations.
Power suppression at large scales in string inflation
Cicoli, Michele; Downes, Sean; Dutta, Bhaskar E-mail: sddownes@physics.tamu.edu
2013-12-01
We study a possible origin of the anomalous suppression of the power spectrum at large angular scales in the cosmic microwave background within the framework of explicit string inflationary models where inflation is driven by a closed string modulus parameterizing the size of the extra dimensions. In this class of models the apparent power loss at large scales is caused by the background dynamics which involves a sharp transition from a fast-roll power law phase to a period of Starobinsky-like slow-roll inflation. An interesting feature of this class of string inflationary models is that the number of e-foldings of inflation is inversely proportional to the string coupling to a positive power. Therefore once the string coupling is tuned to small values in order to trust string perturbation theory, enough e-foldings of inflation are automatically obtained without the need of extra tuning. Moreover, in the less tuned cases the sharp transition responsible for the power loss takes place just before the last 50-60 e-foldings of inflation. We illustrate these general claims in the case of Fibre Inflation where we study the strength of this transition in terms of the attractor dynamics, finding that it induces a pivot from a blue to a redshifted power spectrum which can explain the apparent large scale power loss. We compute the effects of this pivot for example cases and demonstrate how magnitude and duration of this effect depend on model parameters.
NIC-based Reduction Algorithms for Large-scale Clusters
Petrini, F; Moody, A T; Fernandez, J; Frachtenberg, E; Panda, D K
2004-07-30
Efficient algorithms for reduction operations across a group of processes are crucial for good performance in many large-scale, parallel scientific applications. While previous algorithms limit processing to the host CPU, we utilize the programmable processors and local memory available on modern cluster network interface cards (NICs) to explore a new dimension in the design of reduction algorithms. In this paper, we present the benefits and challenges, design issues and solutions, analytical models, and experimental evaluations of a family of NIC-based reduction algorithms. Performance and scalability evaluations were conducted on the ASCI Linux Cluster (ALC), a 960-node, 1920-processor machine at Lawrence Livermore National Laboratory, which uses the Quadrics QsNet interconnect. We find NIC-based reductions on modern interconnects to be more efficient than host-based implementations in both scalability and consistency. In particular, at large-scale--1812 processes--NIC-based reductions of small integer and floating-point arrays provided respective speedups of 121% and 39% over the host-based, production-level MPI implementation.
Evaluating Unmanned Aerial Platforms for Cultural Heritage Large Scale Mapping
NASA Astrophysics Data System (ADS)
Georgopoulos, A.; Oikonomou, C.; Adamopoulos, E.; Stathopoulou, E. K.
2016-06-01
When it comes to large scale mapping of limited areas especially for cultural heritage sites, things become critical. Optical and non-optical sensors are developed to such sizes and weights that can be lifted by such platforms, like e.g. LiDAR units. At the same time there is an increase in emphasis on solutions that enable users to get access to 3D information faster and cheaper. Considering the multitude of platforms, cameras and the advancement of algorithms in conjunction with the increase of available computing power this challenge should and indeed is further investigated. In this paper a short review of the UAS technologies today is attempted. A discussion follows as to their applicability and advantages, depending on their specifications, which vary immensely. The on-board cameras available are also compared and evaluated for large scale mapping. Furthermore a thorough analysis, review and experimentation with different software implementations of Structure from Motion and Multiple View Stereo algorithms, able to process such dense and mostly unordered sequence of digital images is also conducted and presented. As test data set, we use a rich optical and thermal data set from both fixed wing and multi-rotor platforms over an archaeological excavation with adverse height variations and using different cameras. Dense 3D point clouds, digital terrain models and orthophotos have been produced and evaluated for their radiometric as well as metric qualities.
Halo detection via large-scale Bayesian inference
NASA Astrophysics Data System (ADS)
Merson, Alexander I.; Jasche, Jens; Abdalla, Filipe B.; Lahav, Ofer; Wandelt, Benjamin; Jones, D. Heath; Colless, Matthew
2016-08-01
We present a proof-of-concept of a novel and fully Bayesian methodology designed to detect haloes of different masses in cosmological observations subject to noise and systematic uncertainties. Our methodology combines the previously published Bayesian large-scale structure inference algorithm, HAmiltonian Density Estimation and Sampling algorithm (HADES), and a Bayesian chain rule (the Blackwell-Rao estimator), which we use to connect the inferred density field to the properties of dark matter haloes. To demonstrate the capability of our approach, we construct a realistic galaxy mock catalogue emulating the wide-area 6-degree Field Galaxy Survey, which has a median redshift of approximately 0.05. Application of HADES to the catalogue provides us with accurately inferred three-dimensional density fields and corresponding quantification of uncertainties inherent to any cosmological observation. We then use a cosmological simulation to relate the amplitude of the density field to the probability of detecting a halo with mass above a specified threshold. With this information, we can sum over the HADES density field realisations to construct maps of detection probabilities and demonstrate the validity of this approach within our mock scenario. We find that the probability of successful detection of haloes in the mock catalogue increases as a function of the signal to noise of the local galaxy observations. Our proposed methodology can easily be extended to account for more complex scientific questions and is a promising novel tool to analyse the cosmic large-scale structure in observations.
Large scale CMB anomalies from thawing cosmic strings
NASA Astrophysics Data System (ADS)
Ringeval, Christophe; Yamauchi, Daisuke; Yokoyama, Jun'ichi; Bouchet, François R.
2016-02-01
Cosmic strings formed during inflation are expected to be either diluted over super-Hubble distances, i.e., invisible today, or to have crossed our past light cone very recently. We discuss the latter situation in which a few strings imprint their signature in the Cosmic Microwave Background (CMB) Anisotropies after recombination. Being almost frozen in the Hubble flow, these strings are quasi static and evade almost all of the previously derived constraints on their tension while being able to source large scale anisotropies in the CMB sky. Using a local variance estimator on thousand of numerically simulated Nambu-Goto all sky maps, we compute the expected signal and show that it can mimic a dipole modulation at large angular scales while being negligible at small angles. Interestingly, such a scenario generically produces one cold spot from the thawing of a cosmic string loop. Mixed with anisotropies of inflationary origin, we find that a few strings of tension GU = Script O(1) × 10-6 match the amplitude of the dipole modulation reported in the Planck satellite measurements and could be at the origin of other large scale anomalies.
Very large-scale motions in a turbulent pipe flow
NASA Astrophysics Data System (ADS)
Lee, Jae Hwa; Jang, Seong Jae; Sung, Hyung Jin
2011-11-01
Direct numerical simulation of a turbulent pipe flow with ReD=35000 was performed to investigate the spatially coherent structures associated with very large-scale motions. The corresponding friction Reynolds number, based on pipe radius R, is R+=934, and the computational domain length is 30 R. The computed mean flow statistics agree well with previous DNS data at ReD=44000 and 24000. Inspection of the instantaneous fields and two-point correlation of the streamwise velocity fluctuations showed that the very long meandering motions exceeding 25R exist in logarithmic and wake regions, and the streamwise length scale is almost linearly increased up to y/R ~0.3, while the structures in the turbulent boundary layer only reach up to the edge of the log-layer. Time-resolved instantaneous fields revealed that the hairpin packet-like structures grow with continuous stretching along the streamwise direction and create the very large-scale structures with meandering in the spanwise direction, consistent with the previous conceptual model of Kim & Adrian (1999). This work was supported by the Creative Research Initiatives of NRF/MEST of Korea (No. 2011-0000423).
IP over optical multicasting for large-scale video delivery
NASA Astrophysics Data System (ADS)
Jin, Yaohui; Hu, Weisheng; Sun, Weiqiang; Guo, Wei
2007-11-01
In the IPTV systems, multicasting will play a crucial role in the delivery of high-quality video services, which can significantly improve bandwidth efficiency. However, the scalability and the signal quality of current IPTV can barely compete with the existing broadcast digital TV systems since it is difficult to implement large-scale multicasting with end-to-end guaranteed quality of service (QoS) in packet-switched IP network. China 3TNet project aimed to build a high performance broadband trial network to support large-scale concurrent streaming media and interactive multimedia services. The innovative idea of 3TNet is that an automatic switched optical networks (ASON) with the capability of dynamic point-to-multipoint (P2MP) connections replaces the conventional IP multicasting network in the transport core, while the edge remains an IP multicasting network. In this paper, we will introduce the network architecture and discuss challenges in such IP over Optical multicasting for video delivery.
A study of synthetic large scales in turbulent boundary layers
NASA Astrophysics Data System (ADS)
Duvvuri, Subrahmanyam; Luhar, Mitul; Barnard, Casey; Sheplak, Mark; McKeon, Beverley
2013-11-01
Synthetic spanwise-constant spatio-temporal disturbances are excited in a turbulent boundary layer through a spatially impulsive patch of dynamic wall-roughness. The downstream flow response is studied through hot wire anemometry, pressure measurements at the wall and direct measurements of wall-shear-stress made using a novel micro-machined capacitive floating element sensor. These measurements are phase-locked to the input perturbation to recover the synthetic large-scale motion and characterize its structure and wall signature. The phase relationship between the synthetic large scale and small scale activity provides further insights into the apparent amplitude modulation effect between them, and the dynamics of wall-bounded turbulent flows in general. Results from these experiments will be discussed in the context of the critical-layer behavior revealed by the resolvent analysis of McKeon & Sharma (J Fluid Mech, 2010), and compared with similar earlier work by Jacobi & McKeon (J Fluid Mech, 2011). Model predictions are shown to be in broad agreement with experiments. The support of AFOSR grant #FA 9550-12-1-0469, Resnick Institute Graduate Research Fellowship (S.D.) and Sandia Graduate Fellowship (C.B.) are gratefully acknowledged.
Large-scale mapping of mutations affecting zebrafish development
Geisler, Robert; Rauch, Gerd-Jörg; Geiger-Rudolph, Silke; Albrecht, Andrea; van Bebber, Frauke; Berger, Andrea; Busch-Nentwich, Elisabeth; Dahm, Ralf; Dekens, Marcus PS; Dooley, Christopher; Elli, Alexandra F; Gehring, Ines; Geiger, Horst; Geisler, Maria; Glaser, Stefanie; Holley, Scott; Huber, Matthias; Kerr, Andy; Kirn, Anette; Knirsch, Martina; Konantz, Martina; Küchler, Axel M; Maderspacher, Florian; Neuhauss, Stephan C; Nicolson, Teresa; Ober, Elke A; Praeg, Elke; Ray, Russell; Rentzsch, Brit; Rick, Jens M; Rief, Eva; Schauerte, Heike E; Schepp, Carsten P; Schönberger, Ulrike; Schonthaler, Helia B; Seiler, Christoph; Sidi, Samuel; Söllner, Christian; Wehner, Anja; Weiler, Christian; Nüsslein-Volhard, Christiane
2007-01-01
Background Large-scale mutagenesis screens in the zebrafish employing the mutagen ENU have isolated several hundred mutant loci that represent putative developmental control genes. In order to realize the potential of such screens, systematic genetic mapping of the mutations is necessary. Here we report on a large-scale effort to map the mutations generated in mutagenesis screening at the Max Planck Institute for Developmental Biology by genome scanning with microsatellite markers. Results We have selected a set of microsatellite markers and developed methods and scoring criteria suitable for efficient, high-throughput genome scanning. We have used these methods to successfully obtain a rough map position for 319 mutant loci from the Tübingen I mutagenesis screen and subsequent screening of the mutant collection. For 277 of these the corresponding gene is not yet identified. Mapping was successful for 80 % of the tested loci. By comparing 21 mutation and gene positions of cloned mutations we have validated the correctness of our linkage group assignments and estimated the standard error of our map positions to be approximately 6 cM. Conclusion By obtaining rough map positions for over 300 zebrafish loci with developmental phenotypes, we have generated a dataset that will be useful not only for cloning of the affected genes, but also to suggest allelism of mutations with similar phenotypes that will be identified in future screens. Furthermore this work validates the usefulness of our methodology for rapid, systematic and inexpensive microsatellite mapping of zebrafish mutations. PMID:17212827
Large-scale climatic control on European precipitation
NASA Astrophysics Data System (ADS)
Lavers, David; Prudhomme, Christel; Hannah, David
2010-05-01
Precipitation variability has a significant impact on society. Sectors such as agriculture and water resources management are reliant on predictable and reliable precipitation supply with extreme variability having potentially adverse socio-economic impacts. Therefore, understanding the climate drivers of precipitation is of human relevance. This research examines the strength, location and seasonality of links between precipitation and large-scale Mean Sea Level Pressure (MSLP) fields across Europe. In particular, we aim to evaluate whether European precipitation is correlated with the same atmospheric circulation patterns or if there is a strong spatial and/or seasonal variation in the strength and location of centres of correlations. The work exploits time series of gridded ERA-40 MSLP on a 2.5˚×2.5˚ grid (0˚N-90˚N and 90˚W-90˚E) and gridded European precipitation from the Ensemble project on a 0.5°×0.5° grid (36.25˚N-74.25˚N and 10.25˚W-24.75˚E). Monthly Spearman rank correlation analysis was performed between MSLP and precipitation. During winter, a significant MSLP-precipitation correlation dipole pattern exists across Europe. Strong negative (positive) correlation located near the Icelandic Low and positive (negative) correlation near the Azores High pressure centres are found in northern (southern) Europe. These correlation dipoles resemble the structure of the North Atlantic Oscillation (NAO). The reversal in the correlation dipole patterns occurs at the latitude of central France, with regions to the north (British Isles, northern France, Scandinavia) having a positive relationship with the NAO, and regions to the south (Italy, Portugal, southern France, Spain) exhibiting a negative relationship with the NAO. In the lee of mountain ranges of eastern Britain and central Sweden, correlation with North Atlantic MSLP is reduced, reflecting a reduced influence of westerly flow on precipitation generation as the mountains act as a barrier to moist
Climatological context for large-scale coral bleaching
NASA Astrophysics Data System (ADS)
Barton, A. D.; Casey, K. S.
2005-12-01
Large-scale coral bleaching was first observed in 1979 and has occurred throughout virtually all of the tropics since that time. Severe bleaching may result in the loss of live coral and in a decline of the integrity of the impacted coral reef ecosystem. Despite the extensive scientific research and increased public awareness of coral bleaching, uncertainties remain about the past and future of large-scale coral bleaching. In order to reduce these uncertainties and place large-scale coral bleaching in the longer-term climatological context, specific criteria and methods for using historical sea surface temperature (SST) data to examine coral bleaching-related thermal conditions are proposed by analyzing three, 132 year SST reconstructions: ERSST, HadISST1, and GISST2.3b. These methodologies are applied to case studies at Discovery Bay, Jamaica (77.27°W, 18.45°N), Sombrero Reef, Florida, USA (81.11°W, 24.63°N), Academy Bay, Galápagos, Ecuador (90.31°W, 0.74°S), Pearl and Hermes Reef, Northwest Hawaiian Islands, USA (175.83°W, 27.83°N), Midway Island, Northwest Hawaiian Islands, USA (177.37°W, 28.25°N), Davies Reef, Australia (147.68°E, 18.83°S), and North Male Atoll, Maldives (73.35°E, 4.70°N). The results of this study show that (1) The historical SST data provide a useful long-term record of thermal conditions in reef ecosystems, giving important insight into the thermal history of coral reefs and (2) While coral bleaching and anomalously warm SSTs have occurred over much of the world in recent decades, case studies in the Caribbean, Northwest Hawaiian Islands, and parts of other regions such as the Great Barrier Reef exhibited SST conditions and cumulative thermal stress prior to 1979 that were comparable to those conditions observed during the strong, frequent coral bleaching events since 1979. This climatological context and knowledge of past environmental conditions in reef ecosystems may foster a better understanding of how coral reefs will
Large-Scale Graphene Film Deposition for Monolithic Device Fabrication
NASA Astrophysics Data System (ADS)
Al-shurman, Khaled
Since 1958, the concept of integrated circuit (IC) has achieved great technological developments and helped in shrinking electronic devices. Nowadays, an IC consists of more than a million of compacted transistors. The majority of current ICs use silicon as a semiconductor material. According to Moore's law, the number of transistors built-in on a microchip can be double every two years. However, silicon device manufacturing reaches its physical limits. To explain, there is a new trend to shrinking circuitry to seven nanometers where a lot of unknown quantum effects such as tunneling effect can not be controlled. Hence, there is an urgent need for a new platform material to replace Si. Graphene is considered a promising material with enormous potential applications in many electronic and optoelectronics devices due to its superior properties. There are several techniques to produce graphene films. Among these techniques, chemical vapor deposition (CVD) offers a very convenient method to fabricate films for large-scale graphene films. Though CVD method is suitable for large area growth of graphene, the need for transferring a graphene film to silicon-based substrates is required. Furthermore, the graphene films thus achieved are, in fact, not single crystalline. Also, graphene fabrication utilizing Cu and Ni at high growth temperature contaminates the substrate that holds Si CMOS circuitry and CVD chamber as well. So, lowering the deposition temperature is another technological milestone for the successful adoption of graphene in integrated circuits fabrication. In this research, direct large-scale graphene film fabrication on silicon based platform (i.e. SiO2 and Si3N4) at low temperature was achieved. With a focus on low-temperature graphene growth, hot-filament chemical vapor deposition (HF-CVD) was utilized to synthesize graphene film using 200 nm thick nickel film. Raman spectroscopy was utilized to examine graphene formation on the bottom side of the Ni film
Penetration of Large Scale Electric Field to Inner Magnetosphere
NASA Astrophysics Data System (ADS)
Chen, S. H.; Fok, M. C. H.; Sibeck, D. G.; Wygant, J. R.; Spence, H. E.; Larsen, B.; Reeves, G. D.; Funsten, H. O.
2015-12-01
The direct penetration of large scale global electric field to the inner magnetosphere is a critical element in controlling how the background thermal plasma populates within the radiation belts. These plasma populations provide the source of particles and free energy needed for the generation and growth of various plasma waves that, at critical points of resonances in time and phase space, can scatter or energize radiation belt particles to regulate the flux level of the relativistic electrons in the system. At high geomagnetic activity levels, the distribution of large scale electric fields serves as an important indicator of how prevalence of strong wave-particle interactions extend over local times and radial distances. To understand the complex relationship between the global electric fields and thermal plasmas, particularly due to the ionospheric dynamo and the magnetospheric convection effects, and their relations to the geomagnetic activities, we analyze the electric field and cold plasma measurements from Van Allen Probes over more than two years period and simulate a geomagnetic storm event using Coupled Inner Magnetosphere-Ionosphere Model (CIMI). Our statistical analysis of the measurements from Van Allan Probes and CIMI simulations of the March 17, 2013 storm event indicate that: (1) Global dawn-dusk electric field can penetrate the inner magnetosphere inside the inner belt below L~2. (2) Stronger convections occurred in the dusk and midnight sectors than those in the noon and dawn sectors. (3) Strong convections at multiple locations exist at all activity levels but more complex at higher activity levels. (4) At the high activity levels, strongest convections occur in the midnight sectors at larger distances from the Earth and in the dusk sector at closer distances. (5) Two plasma populations of distinct ion temperature isotropies divided at L-Shell ~2, indicating distinct heating mechanisms between inner and outer radiation belts. (6) CIMI
Large-scale dimension densities for heart rate variability analysis
NASA Astrophysics Data System (ADS)
Raab, Corinna; Wessel, Niels; Schirdewan, Alexander; Kurths, Jürgen
2006-04-01
In this work, we reanalyze the heart rate variability (HRV) data from the 2002 Computers in Cardiology (CiC) Challenge using the concept of large-scale dimension densities and additionally apply this technique to data of healthy persons and of patients with cardiac diseases. The large-scale dimension density (LASDID) is estimated from the time series using a normalized Grassberger-Procaccia algorithm, which leads to a suitable correction of systematic errors produced by boundary effects in the rather large scales of a system. This way, it is possible to analyze rather short, nonstationary, and unfiltered data, such as HRV. Moreover, this method allows us to analyze short parts of the data and to look for differences between day and night. The circadian changes in the dimension density enable us to distinguish almost completely between real data and computer-generated data from the CiC 2002 challenge using only one parameter. In the second part we analyzed the data of 15 patients with atrial fibrillation (AF), 15 patients with congestive heart failure (CHF), 15 elderly healthy subjects (EH), as well as 18 young and healthy persons (YH). With our method we are able to separate completely the AF (ρlsμ=0.97±0.02) group from the others and, especially during daytime, the CHF patients show significant differences from the young and elderly healthy volunteers (CHF, 0.65±0.13 ; EH, 0.54±0.05 ; YH, 0.57±0.05 ; p<0.05 for both comparisons). Moreover, for the CHF patients we find no circadian changes in ρlsμ (day, 0.65±0.13 ; night, 0.66±0.12 ; n.s.) in contrast to healthy controls (day, 0.54±0.05 ; night, 0.61±0.05 ; p=0.002 ). Correlation analysis showed no statistical significant relation between standard HRV and circadian LASDID, demonstrating a possibly independent application of our method for clinical risk stratification.
Modelling large-scale halo bias using the bispectrum
NASA Astrophysics Data System (ADS)
Pollack, Jennifer E.; Smith, Robert E.; Porciani, Cristiano
2012-03-01
We study the relation between the density distribution of tracers for large-scale structure and the underlying matter distribution - commonly termed bias - in the Λ cold dark matter framework. In particular, we examine the validity of the local model of biasing at quadratic order in the matter density. This model is characterized by parameters b1 and b2. Using an ensemble of N-body simulations, we apply several statistical methods to estimate the parameters. We measure halo and matter fluctuations smoothed on various scales. We find that, whilst the fits are reasonably good, the parameters vary with smoothing scale. We argue that, for real-space measurements, owing to the mixing of wavemodes, no smoothing scale can be found for which the parameters are independent of smoothing. However, this is not the case in Fourier space. We measure halo and halo-mass power spectra and from these construct estimates of the effective large-scale bias as a guide for b1. We measure the configuration dependence of the halo bispectra Bhhh and reduced bispectra Qhhh for very large-scale k-space triangles. From these data, we constrain b1 and b2, taking into account the full bispectrum covariance matrix. Using the lowest order perturbation theory, we find that for Bhhh the best-fitting parameters are in reasonable agreement with one another as the triangle scale is varied, although the fits become poor as smaller scales are included. The same is true for Qhhh. The best-fitting values were found to depend on the discreteness correction. This led us to consider halo-mass cross-bispectra. The results from these statistics supported our earlier findings. We then developed a test to explore whether the inconsistency in the recovered bias parameters could be attributed to missing higher order corrections in the models. We prove that low-order expansions are not sufficiently accurate to model the data, even on scales k1˜ 0.04 h Mpc-1. If robust inferences concerning bias are to be drawn
Applications of large-scale density functional theory in biology.
Cole, Daniel J; Hine, Nicholas D M
2016-10-01
Density functional theory (DFT) has become a routine tool for the computation of electronic structure in the physics, materials and chemistry fields. Yet the application of traditional DFT to problems in the biological sciences is hindered, to a large extent, by the unfavourable scaling of the computational effort with system size. Here, we review some of the major software and functionality advances that enable insightful electronic structure calculations to be performed on systems comprising many thousands of atoms. We describe some of the early applications of large-scale DFT to the computation of the electronic properties and structure of biomolecules, as well as to paradigmatic problems in enzymology, metalloproteins, photosynthesis and computer-aided drug design. With this review, we hope to demonstrate that first principles modelling of biological structure-function relationships are approaching a reality. PMID:27494095
Large scale Hugoniot material properties for Danby Marble
Rinehart, E.J.
1993-11-01
This paper presents the results of simulation experiments of nuclear underground testing carried out using the HYDROPLUS methodology for yield verifications of non-standard tests. The objective of this test series was to demonstrate the accuracy of stress and velocity measurements in hard, low porosity rock, to obtain comparisons of large-scale material properties with those obtained from laboratory testing of the same material, and to address the problems posed by a material having a clear precursor wave preceding the main shock wave. The test series consisted of three individual experimental tests. The first established material properties of the Danby marble selected for use in the experiments. The second and third tests looked at stress and velocity gage errors obtained when gages were placed in boreholes and grouted into place.
Large-scale structure in f(T) gravity
Li Baojiu; Sotiriou, Thomas P.; Barrow, John D.
2011-05-15
In this work we study the cosmology of the general f(T) gravity theory. We express the modified Einstein equations using covariant quantities, and derive the gauge-invariant perturbation equations in covariant form. We consider a specific choice of f(T), designed to explain the observed late-time accelerating cosmic expansion without including an exotic dark energy component. Our numerical solution shows that the extra degree of freedom of such f(T) gravity models generally decays as one goes to smaller scales, and consequently its effects on scales such as galaxies and galaxies clusters are small. But on large scales, this degree of freedom can produce large deviations from the standard {Lambda}CDM scenario, leading to severe constraints on the f(T) gravity models as an explanation to the cosmic acceleration.
Shock waves in the large scale structure of the universe
NASA Astrophysics Data System (ADS)
Ryu, Dongsu
Cosmological shock waves result from the supersonic flow motions induced by hierarchical formation of nonlinear structures in the universe. Like most astrophysical shocks, they are collisionless shocks which form in the tenuous intergalactic plasma via collective electromagnetic interactions between particles and electromagnetic fields. The gravitational energy released during the structure formation is transferred by these shocks to the intergalactic gas in several different forms. In addition to the gas entropy, cosmic rays are produced via diffusive shock acceleration, magnetic fields are generated via the Biermann battery mechanism and Weibel instability as well as the Bell-Lucek mechanism, and vorticity is generated at curved shocks. Here we review the properties, roles, and consequences of the shock waves in the context of the large scale structure of the universe.
Shock Waves in the Large Scale Structure of the Universe
NASA Astrophysics Data System (ADS)
Ryu, Dongsu
2008-04-01
Cosmological shock waves result from the supersonic flow motions induced by hierarchical formation of nonlinear structures in the universe. Like most astrophysical shocks, they are collisionless shocks which form in the tenuous intergalactic plasma via collective electromagnetic interactions between particles and electromagnetic fields. The gravitational energy released during the structure formation is transferred by these shocks to the intergalactic gas in several different forms: in addition to the gas entropy, cosmic rays are produced via diffusive shock acceleration, magnetic fields are generated via the Biermann battery mechanism and Weibel instability, and vorticity is generated at curved shocks. Here I review the properties, roles, and consequences of the shock waves in the context of the large scale structure of the universe.
Large scale simulations of the great 1906 San Francisco earthquake
NASA Astrophysics Data System (ADS)
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.
Performance evaluation of large-scale photovoltaic systems
Fuentes, M.K.; Fernandez, J.P.
1984-05-01
Over the past several years, the US Department of Energy has fielded a number of large-scale photovoltaic (PV) systems as initial experiments for assessing the performance of various PV designs. The array power and power conditioning subsystem (PCS) data have been analyzed from the following six sites: Sky Harbor Airport, Dallas-Fort Worth Airport, Newman Power Station, Lovington Shopping Center, Beverly High School, and the Oklahoma Center for Science and Arts. For all these systems, the peak power was determined to be within 67% of the rated peak. The differences between the actual peak power and rated peak power has been attributed to a number of factors, includ-module failures and array degradation. The peak PCS efficiencies range from 88% to 93%.
Identification of Extremely Large Scale Structures in SDSS-III
NASA Astrophysics Data System (ADS)
Sankhyayan, Shishir; Bagchi, J.; Sarkar, P.; Sahni, V.; Jacob, J.
2016-10-01
We have initiated the search and detailed study of large scale structures present in the universe using galaxy redshift surveys. In this process, we take the volume-limited sample of galaxies from Sloan Digital Sky Survey III and find very large structures even beyond the redshift of 0.2. One of the structures is even greater than 600 Mpc which raises a question on the homogeneity scale of the universe. The shapes of voids-structures (adjacent to each other) seem to be correlated, which supports the physical existence of the observed structures. The other observational supports include galaxy clusters' and QSO distribution's correlation with the density peaks of the volume limited sample of galaxies.
Large-scale coherent structures as drivers of combustion instability
Schadow, K.C.; Gutmark, E.; Parr, T.P.; Parr, D.M.; Wilson, K.J.
1987-06-01
The role of flow coherent structures as drivers of combustion instabilities in a dump combustor was studied. Results of nonreacting tests in air and water flows as well as combustion experiments in a diffusion flame and dump combustor are discussed to provide insight into the generation process of large-scale structures in the combustor flow and their interaction with the combustion process. It is shown that the flow structures, or vortices, are formed by interaction between the flow instabilities and the chamber acoustic resonance. When these vortices dominate the reacting flow, the combustion is confined to their cores, leading to periodic heat release, which may result in the driving of high amplitude pressure oscillations. These oscillations are typical to the occurrence of combustion instabilities for certain operating conditions. The basic understanding of the interaction between flow dynamics and the combustion process opens up the possibility for rational control of combustion-induced pressure oscillations. 42 references.
Policy Driven Development: Flexible Policy Insertion for Large Scale Systems.
Demchak, Barry; Krüger, Ingolf
2012-07-01
The success of a software system depends critically on how well it reflects and adapts to stakeholder requirements. Traditional development methods often frustrate stakeholders by creating long latencies between requirement articulation and system deployment, especially in large scale systems. One source of latency is the maintenance of policy decisions encoded directly into system workflows at development time, including those involving access control and feature set selection. We created the Policy Driven Development (PDD) methodology to address these development latencies by enabling the flexible injection of decision points into existing workflows at runtime, thus enabling policy composition that integrates requirements furnished by multiple, oblivious stakeholder groups. Using PDD, we designed and implemented a production cyberinfrastructure that demonstrates policy and workflow injection that quickly implements stakeholder requirements, including features not contemplated in the original system design. PDD provides a path to quickly and cost effectively evolve such applications over a long lifetime. PMID:25383258
Possible implications of large scale radiation processing of food
NASA Astrophysics Data System (ADS)
Zagórski, Z. P.
Large scale irradiation has been discussed in terms of the participation of processing cost in the final value of the improved product. Another factor has been taken into account and that is the saturation of the market with the new product. In the case of succesful projects the participation of irradiation cost is low, and the demand for the better product is covered. A limited availability of sources makes the modest saturation of the market difficult with all food subjected to correct radiation treatment. The implementation of the preservation of food needs a decided selection of these kinds of food which comply to all conditions i.e. of acceptance by regulatory bodies, real improvement of quality and economy. The last condition prefers the possibility of use of electron beams of low energy. The best fullfilment of conditions for succesful processing is observed in the group of dry food, in expensive spices in particular.
Large scale protein separations: engineering aspects of chromatography.
Chisti, Y; Moo-Young, M
1990-01-01
The engineering considerations common to large scale chromatographic purification of proteins are reviewed. A discussion of the industrial chromatography fundamentals is followed by aspects which affect the scale of separation. The separation column geometry, the effect of the main operational parameters on separation performance, and the physical characteristics of column packing are treated. Throughout, the emphasis is on ion exchange and size exclusion techniques which together constitute the major portion of commercial chromatographic protein purifications. In all cases, the state of current technology is examined and areas in need of further development are noted. The physico-chemical advances now underway in chromatographic separation of biopolymers would ensure a substantially enhanced role for these techniques in industrial production of products of new biotechnology.
Towards Online Multiresolution Community Detection in Large-Scale Networks
Huang, Jianbin; Sun, Heli; Liu, Yaguang; Song, Qinbao; Weninger, Tim
2011-01-01
The investigation of community structure in networks has aroused great interest in multiple disciplines. One of the challenges is to find local communities from a starting vertex in a network without global information about the entire network. Many existing methods tend to be accurate depending on a priori assumptions of network properties and predefined parameters. In this paper, we introduce a new quality function of local community and present a fast local expansion algorithm for uncovering communities in large-scale networks. The proposed algorithm can detect multiresolution community from a source vertex or communities covering the whole network. Experimental results show that the proposed algorithm is efficient and well-behaved in both real-world and synthetic networks. PMID:21887325
Atypical Behavior Identification in Large Scale Network Traffic
Best, Daniel M.; Hafen, Ryan P.; Olsen, Bryan K.; Pike, William A.
2011-10-23
Cyber analysts are faced with the daunting challenge of identifying exploits and threats within potentially billions of daily records of network traffic. Enterprise-wide cyber traffic involves hundreds of millions of distinct IP addresses and results in data sets ranging from terabytes to petabytes of raw data. Creating behavioral models and identifying trends based on those models requires data intensive architectures and techniques that can scale as data volume increases. Analysts need scalable visualization methods that foster interactive exploration of data and enable identification of behavioral anomalies. Developers must carefully consider application design, storage, processing, and display to provide usability and interactivity with large-scale data. We present an application that highlights atypical behavior in enterprise network flow records. This is accomplished by utilizing data intensive architectures to store the data, aggregation techniques to optimize data access, statistical techniques to characterize behavior, and a visual analytic environment to render the behavioral trends, highlight atypical activity, and allow for exploration.
Performance Health Monitoring of Large-Scale Systems
Rajamony, Ram
2014-11-20
This report details the progress made on the ASCR funded project Performance Health Monitoring for Large Scale Systems. A large-scale application may not achieve its full performance potential due to degraded performance of even a single subsystem. Detecting performance faults, isolating them, and taking remedial action is critical for the scale of systems on the horizon. PHM aims to develop techniques and tools that can be used to identify and mitigate such performance problems. We accomplish this through two main aspects. The PHM framework encompasses diagnostics, system monitoring, fault isolation, and performance evaluation capabilities that indicates when a performance fault has been detected, either due to an anomaly present in the system itself or due to contention for shared resources between concurrently executing jobs. Software components called the PHM Control system then build upon the capabilities provided by the PHM framework to mitigate degradation caused by performance problems.
Computational solutions to large-scale data management and analysis.
Schadt, Eric E; Linderman, Michael D; Sorenson, Jon; Lee, Lawrence; Nolan, Garry P
2010-09-01
Today we can generate hundreds of gigabases of DNA and RNA sequencing data in a week for less than US$5,000. The astonishing rate of data generation by these low-cost, high-throughput technologies in genomics is being matched by that of other technologies, such as real-time imaging and mass spectrometry-based flow cytometry. Success in the life sciences will depend on our ability to properly interpret the large-scale, high-dimensional data sets that are generated by these technologies, which in turn requires us to adopt advances in informatics. Here we discuss how we can master the different types of computational environments that exist - such as cloud and heterogeneous computing - to successfully tackle our big data problems.
Scalable parallel distance field construction for large-scale applications
Yu, Hongfeng; Xie, Jinrong; Ma, Kwan -Liu; Kolla, Hemanth; Chen, Jacqueline H.
2015-10-01
Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. Anew distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking overtime, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate its efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. In conclusion, our work greatly extends the usability of distance fields for demanding applications.
Large-scale testing of structural clay tile infilled frames
Flanagan, R.D.; Bennett, R.M.
1993-03-18
A summary of large-scale cyclic static tests of structural clay tile infilled frames is given. In-plane racking tests examined the effects of varying frame stiffness, varying infill size, infill offset from frame centerline, and single and double wythe infill construction. Out-of-plane tests examined infilled frame response to inertial loadings and inter-story drift loadings. Sequential in-plane and out-of-plane loadings were performed to determine the effects of orthogonal damage and degradation on both strength and stiffness. A combined out-of-plane inertial and in-plane racking test was conducted to investigate the interaction of multi-directional loading. To determine constitutive properties of the infills, prism compression, mortar compression and various unit tile tests were performed.
Hierarchical features of large-scale cortical connectivity
NASA Astrophysics Data System (ADS)
da F. Costa, L.; Sporns, O.
2005-12-01
The analysis of complex networks has revealed patterns of organization in a variety of natural and artificial systems, including neuronal networks of the brain at multiple scales. In this paper, we describe a novel analysis of the large-scale connectivity between regions of the mammalian cerebral cortex, utilizing a set of hierarchical measurements proposed recently. We examine previously identified functional clusters of brain regions in macaque visual cortex and cat cortex and find significant differences between such clusters in terms of several hierarchical measures, revealing differences in how these clusters are embedded in the overall cortical architecture. For example, the ventral cluster of visual cortex maintains structurally more segregated, less divergent connections than the dorsal cluster, which may point to functionally different roles of their constituent brain regions.
Scalable Parallel Distance Field Construction for Large-Scale Applications.
Yu, Hongfeng; Xie, Jinrong; Ma, Kwan-Liu; Kolla, Hemanth; Chen, Jacqueline H
2015-10-01
Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. A new distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking over time, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate its efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. Our work greatly extends the usability of distance fields for demanding applications. PMID:26357251
Large scale anisotropy studies with the Pierre Auger Observatory
NASA Astrophysics Data System (ADS)
Bonino, R.
2012-11-01
Completed at the end of 2008, the Pierre Auger Observatory has been continuously operating for more than seven years. We present here the analysis techniques and the results about the search for large scale anisotropies in the sky distribution of cosmic rays, reporting both the phase and the amplitude measurements of the first harmonic modulation in right ascension in different energy ranges above 2.5×1017 eV. Thanks to the collected statistics, a sensitivity of 1% at EeV energies can be reached. No significant anisotropies have been observed, upper limits on the amplitudes have been derived and are here compared with the results of previous experiments and with some theoretical expectations.
Distributed Coordinated Control of Large-Scale Nonlinear Networks
Kundu, Soumya; Anghel, Marian
2015-11-08
We provide a distributed coordinated approach to the stability analysis and control design of largescale nonlinear dynamical systems by using a vector Lyapunov functions approach. In this formulation the large-scale system is decomposed into a network of interacting subsystems and the stability of the system is analyzed through a comparison system. However finding such comparison system is not trivial. In this work, we propose a sum-of-squares based completely decentralized approach for computing the comparison systems for networks of nonlinear systems. Moreover, based on the comparison systems, we introduce a distributed optimal control strategy in which the individual subsystems (agents) coordinate with their immediate neighbors to design local control policies that can exponentially stabilize the full system under initial disturbances.We illustrate the control algorithm on a network of interacting Van der Pol systems.
Distributed Coordinated Control of Large-Scale Nonlinear Networks
Kundu, Soumya; Anghel, Marian
2015-11-08
We provide a distributed coordinated approach to the stability analysis and control design of largescale nonlinear dynamical systems by using a vector Lyapunov functions approach. In this formulation the large-scale system is decomposed into a network of interacting subsystems and the stability of the system is analyzed through a comparison system. However finding such comparison system is not trivial. In this work, we propose a sum-of-squares based completely decentralized approach for computing the comparison systems for networks of nonlinear systems. Moreover, based on the comparison systems, we introduce a distributed optimal control strategy in which the individual subsystems (agents) coordinatemore » with their immediate neighbors to design local control policies that can exponentially stabilize the full system under initial disturbances.We illustrate the control algorithm on a network of interacting Van der Pol systems.« less
Automated Sequence Preprocessing in a Large-Scale Sequencing Environment
Wendl, Michael C.; Dear, Simon; Hodgson, Dave; Hillier, LaDeana
1998-01-01
A software system for transforming fragments from four-color fluorescence-based gel electrophoresis experiments into assembled sequence is described. It has been developed for large-scale processing of all trace data, including shotgun and finishing reads, regardless of clone origin. Design considerations are discussed in detail, as are programming implementation and graphic tools. The importance of input validation, record tracking, and use of base quality values is emphasized. Several quality analysis metrics are proposed and applied to sample results from recently sequenced clones. Such quantities prove to be a valuable aid in evaluating modifications of sequencing protocol. The system is in full production use at both the Genome Sequencing Center and the Sanger Centre, for which combined weekly production is ∼100,000 sequencing reads per week. PMID:9750196
Large scale rigidity-based flexibility analysis of biomolecules
Streinu, Ileana
2016-01-01
KINematics And RIgidity (KINARI) is an on-going project for in silico flexibility analysis of proteins. The new version of the software, Kinari-2, extends the functionality of our free web server KinariWeb, incorporates advanced web technologies, emphasizes the reproducibility of its experiments, and makes substantially improved tools available to the user. It is designed specifically for large scale experiments, in particular, for (a) very large molecules, including bioassemblies with high degree of symmetry such as viruses and crystals, (b) large collections of related biomolecules, such as those obtained through simulated dilutions, mutations, or conformational changes from various types of dynamics simulations, and (c) is intended to work as seemlessly as possible on the large, idiosyncratic, publicly available repository of biomolecules, the Protein Data Bank. We describe the system design, along with the main data processing, computational, mathematical, and validation challenges underlying this phase of the KINARI project. PMID:26958583
A large-scale crop protection bioassay data set.
Gaulton, Anna; Kale, Namrata; van Westen, Gerard J P; Bellis, Louisa J; Bento, A Patrícia; Davies, Mark; Hersey, Anne; Papadatos, George; Forster, Mark; Wege, Philip; Overington, John P
2015-01-01
ChEMBL is a large-scale drug discovery database containing bioactivity information primarily extracted from scientific literature. Due to the medicinal chemistry focus of the journals from which data are extracted, the data are currently of most direct value in the field of human health research. However, many of the scientific use-cases for the current data set are equally applicable in other fields, such as crop protection research: for example, identification of chemical scaffolds active against a particular target or endpoint, the de-convolution of the potential targets of a phenotypic assay, or the potential targets/pathways for safety liabilities. In order to broaden the applicability of the ChEMBL database and allow more widespread use in crop protection research, an extensive data set of bioactivity data of insecticidal, fungicidal and herbicidal compounds and assays was collated and added to the database.
U-shaped Vortex Structures in Large Scale Cloud Cavitation
NASA Astrophysics Data System (ADS)
Cao, Yantao; Peng, Xiaoxing; Xu, Lianghao; Hong, Fangwen
2015-12-01
The control of cloud cavitation, especially large scale cloud cavitation(LSCC), is always a hot issue in the field of cavitation research. However, there has been little knowledge on the evolution of cloud cavitation since it is associated with turbulence and vortex flow. In this article, the structure of cloud cavitation shed by sheet cavitation around different hydrofoils and a wedge were observed in detail with high speed camera (HSC). It was found that the U-shaped vortex structures always existed in the development process of LSCC. The results indicated that LSCC evolution was related to this kind of vortex structures, and it may be a universal character for LSCC. Then vortex strength of U-shaped vortex structures in a cycle was analyzed with numerical results.
Statistics of Caustics in Large-Scale Structure Formation
NASA Astrophysics Data System (ADS)
Feldbrugge, Job L.; Hidding, Johan; van de Weygaert, Rien
2016-10-01
The cosmic web is a complex spatial pattern of walls, filaments, cluster nodes and underdense void regions. It emerged through gravitational amplification from the Gaussian primordial density field. Here we infer analytical expressions for the spatial statistics of caustics in the evolving large-scale mass distribution. In our analysis, following the quasi-linear Zel'dovich formalism and confined to the 1D and 2D situation, we compute number density and correlation properties of caustics in cosmic density fields that evolve from Gaussian primordial conditions. The analysis can be straightforwardly extended to the 3D situation. We moreover, are currently extending the approach to the non-linear regime of structure formation by including higher order Lagrangian approximations and Lagrangian effective field theory.
Large-scale structure non-Gaussianities with modal methods
NASA Astrophysics Data System (ADS)
Schmittfull, Marcel
2016-10-01
Relying on a separable modal expansion of the bispectrum, the implementation of a fast estimator for the full bispectrum of a 3d particle distribution is presented. The computational cost of accurate bispectrum estimation is negligible relative to simulation evolution, so the bispectrum can be used as a standard diagnostic whenever the power spectrum is evaluated. As an application, the time evolution of gravitational and primordial dark matter bispectra was measured in a large suite of N-body simulations. The bispectrum shape changes characteristically when the cosmic web becomes dominated by filaments and halos, therefore providing a quantitative probe of 3d structure formation. Our measured bispectra are determined by ~ 50 coefficients, which can be used as fitting formulae in the nonlinear regime and for non-Gaussian initial conditions. We also compare the measured bispectra with predictions from the Effective Field Theory of Large Scale Structures (EFTofLSS).
Large scale animal cell cultivation for production of cellular biologicals.
van Wezel, A L; van der Velden-de Groot, C A; de Haan, H H; van den Heuvel, N; Schasfoort, R
1985-01-01
Through the developments in molecular biology the interest for large scale animal cell cultivation has sharply increased during the last 5 years. At our laboratory, four different cultivation systems were studied, all of which are homogeneous culture systems, as they lend themselves best for scaling up and for the control of culture conditions. The four different systems which were compared are: batch culture, continuous chemostat, continuous recycling and continuous perfusion culture system, both for cells growing in suspension and for anchorage dependent cells in microcarrier culture. Our results indicate that for the production of virus vaccines and cells the batch and recycling culture system are most suitable. Disadvantages of the continued chemostat culture system are: the system is only applicable for cells growing in suspension; relatively low concentrations of cells and cellular products are obtained. The continuous perfusion system appears to be very suitable for the production of cellular components and also for the production of viruses which do not give cell lysis.
Nonzero Density-Velocity Consistency Relations for Large Scale Structures.
Rizzo, Luca Alberto; Mota, David F; Valageas, Patrick
2016-08-19
We present exact kinematic consistency relations for cosmological structures that do not vanish at equal times and can thus be measured in surveys. These rely on cross correlations between the density and velocity, or momentum, fields. Indeed, the uniform transport of small-scale structures by long-wavelength modes, which cannot be detected at equal times by looking at density correlations only, gives rise to a shift in the amplitude of the velocity field that could be measured. These consistency relations only rely on the weak equivalence principle and Gaussian initial conditions. They remain valid in the nonlinear regime and for biased galaxy fields. They can be used to constrain nonstandard cosmological scenarios or the large-scale galaxy bias. PMID:27588842
Large-scale dynamic compaction of natural salt
Hansen, F.D.; Ahrens, E.H.
1996-05-01
A large-scale dynamic compaction demonstration of natural salt was successfully completed. About 40 m{sup 3} of salt were compacted in three, 2-m lifts by dropping a 9,000-kg weight from a height of 15 m in a systematic pattern to achieve desired compaction energy. To enhance compaction, 1 wt% water was added to the relatively dry mine-run salt. The average compacted mass fractional density was 0.90 of natural intact salt, and in situ nitrogen permeabilities averaged 9X10{sup -14}m{sup 2}. This established viability of dynamic compacting for placing salt shaft seal components. The demonstration also provided compacted salt parameters needed for shaft seal system design and performance assessments of the Waste Isolation Pilot Plant.
Lightweight computational steering of very large scale molecular dynamics simulations
Beazley, D.M.; Lomdahl, P.S.
1996-09-01
We present a computational steering approach for controlling, analyzing, and visualizing very large scale molecular dynamics simulations involving tens to hundreds of millions of atoms. Our approach relies on extensible scripting languages and an easy to use tool for building extensions and modules. The system is extremely easy to modify, works with existing C code, is memory efficient, and can be used from inexpensive workstations and networks. We demonstrate how we have used this system to manipulate data from production MD simulations involving as many as 104 million atoms running on the CM-5 and Cray T3D. We also show how this approach can be used to build systems that integrate common scripting languages (including Tcl/Tk, Perl, and Python), simulation code, user extensions, and commercial data analysis packages.
Hydrokinetic approach to large-scale cardiovascular blood flow
NASA Astrophysics Data System (ADS)
Melchionna, Simone; Bernaschi, Massimo; Succi, Sauro; Kaxiras, Efthimios; Rybicki, Frank J.; Mitsouras, Dimitris; Coskun, Ahmet U.; Feldman, Charles L.
2010-03-01
We present a computational method for commodity hardware-based clinical cardiovascular diagnosis based on accurate simulation of cardiovascular blood flow. Our approach leverages the flexibility of the Lattice Boltzmann method to implementation on high-performance, commodity hardware, such as Graphical Processing Units. We developed the procedure for the analysis of real-life cardiovascular blood flow case studies, namely, anatomic data acquisition, geometry and mesh generation, flow simulation and data analysis and visualization. We demonstrate the usefulness of our computational tool through a set of large-scale simulations of the flow patterns associated with the arterial tree of a patient which involves two hundred million computational cells. The simulations show evidence of a very rich and heterogeneous endothelial shear stress pattern (ESS), a quantity of recognized key relevance to the localization and progression of major cardiovascular diseases, such as atherosclerosis, and set the stage for future studies involving pulsatile flows.
Applications of large-scale density functional theory in biology.
Cole, Daniel J; Hine, Nicholas D M
2016-10-01
Density functional theory (DFT) has become a routine tool for the computation of electronic structure in the physics, materials and chemistry fields. Yet the application of traditional DFT to problems in the biological sciences is hindered, to a large extent, by the unfavourable scaling of the computational effort with system size. Here, we review some of the major software and functionality advances that enable insightful electronic structure calculations to be performed on systems comprising many thousands of atoms. We describe some of the early applications of large-scale DFT to the computation of the electronic properties and structure of biomolecules, as well as to paradigmatic problems in enzymology, metalloproteins, photosynthesis and computer-aided drug design. With this review, we hope to demonstrate that first principles modelling of biological structure-function relationships are approaching a reality.
Large-scale volcano-ground ice interactions on Mars
NASA Technical Reports Server (NTRS)
Squyres, Steven W.; Wilhelms, Don E.; Moosman, Ann C.
1987-01-01
In the present investigation of Martian volcano-ground ice interaction processes, a numerical model is developed that encompasses conductive heat transport, surface radiation, heat transfer to the atmosphere, and H2O phase-changes in an ice-rich permafrost over which lave flows erupt, followed by the intrusion of sills. An examination is made of the two large scale interaction regions formed near Aeolis Mensae and near the volcano Hadriaca Patera, northeast of Hellas. The inferred channel discharges are compared to discharge rates calculated for lava-ground ice interactions, showing that meltwater (probably accumulated under the surface) was rapidly released at a discharge rate that was limited by soil permeability. The volcano-ground ice interactions have been an important Martian geologic process, and could account for the palagonites constituting the Martian dust.
Large-Scale All-Dielectric Metamaterial Perfect Reflectors
Moitra, Parikshit; Slovick, Brian A.; li, Wei; Kravchencko, Ivan I.; Briggs, Dayrl P.; Krishnamurthy, S.; Valentine, Jason
2015-05-08
All-dielectric metamaterials offer a potential low-loss alternative to plasmonic metamaterials at optical frequencies. In this paper, we take advantage of the low absorption loss as well as the simple unit cell geometry to demonstrate large-scale (centimeter-sized) all-dielectric metamaterial perfect reflectors made from silicon cylinder resonators. These perfect reflectors, operating in the telecommunications band, were fabricated using self-assembly based nanosphere lithography. In spite of the disorder originating from the self-assembly process, the average reflectance of the metamaterial perfect reflectors is 99.7% at 1530 nm, surpassing the reflectance of metallic mirrors. Moreover, the spectral separation of the electric and magnetic resonances can be chosen to achieve the required reflection bandwidth while maintaining a high tolerance to disorder. Finally, the scalability of this design could lead to new avenues of manipulating light for low-loss and large-area photonic applications.
Large-Scale All-Dielectric Metamaterial Perfect Reflectors
Moitra, Parikshit; Slovick, Brian A.; li, Wei; Kravchencko, Ivan I.; Briggs, Dayrl P.; Krishnamurthy, S.; Valentine, Jason
2015-05-08
All-dielectric metamaterials offer a potential low-loss alternative to plasmonic metamaterials at optical frequencies. In this paper, we take advantage of the low absorption loss as well as the simple unit cell geometry to demonstrate large-scale (centimeter-sized) all-dielectric metamaterial perfect reflectors made from silicon cylinder resonators. These perfect reflectors, operating in the telecommunications band, were fabricated using self-assembly based nanosphere lithography. In spite of the disorder originating from the self-assembly process, the average reflectance of the metamaterial perfect reflectors is 99.7% at 1530 nm, surpassing the reflectance of metallic mirrors. Moreover, the spectral separation of the electric and magnetic resonances canmore » be chosen to achieve the required reflection bandwidth while maintaining a high tolerance to disorder. Finally, the scalability of this design could lead to new avenues of manipulating light for low-loss and large-area photonic applications.« less
Scoring Large Scale Affinity Purification Mass Spectrometry Datasets with MIST
Verschueren, Erik; Von Dollen, John; Cimermancic, Peter; Gulbahce, Natali; Sali, Andrej; Krogan, Nevan
2015-01-01
High-throughput Affinity Purification Mass Spectrometry (AP-MS) experiments can identify a large number of protein interactions but only a fraction of these interactions are biologically relevant. Here, we describe a comprehensive computational strategy to process raw AP-MS data, perform quality controls and prioritize biologically relevant bait-prey pairs in a set of replicated AP-MS experiments with Mass spectrometry interaction STatistics (MiST). The MiST score is a linear combination of prey quantity (abundance), abundance invariability across repeated experiments (reproducibility), and prey uniqueness relative to other baits (specificity); We describe how to run the full MiST analysis pipeline in an R environment and discuss a number of configurable options that allow the lay user to convert any large-scale AP-MS data into an interpretable, biologically relevant protein-protein interaction network. PMID:25754993
A large-scale crop protection bioassay data set.
Gaulton, Anna; Kale, Namrata; van Westen, Gerard J P; Bellis, Louisa J; Bento, A Patrícia; Davies, Mark; Hersey, Anne; Papadatos, George; Forster, Mark; Wege, Philip; Overington, John P
2015-01-01
ChEMBL is a large-scale drug discovery database containing bioactivity information primarily extracted from scientific literature. Due to the medicinal chemistry focus of the journals from which data are extracted, the data are currently of most direct value in the field of human health research. However, many of the scientific use-cases for the current data set are equally applicable in other fields, such as crop protection research: for example, identification of chemical scaffolds active against a particular target or endpoint, the de-convolution of the potential targets of a phenotypic assay, or the potential targets/pathways for safety liabilities. In order to broaden the applicability of the ChEMBL database and allow more widespread use in crop protection research, an extensive data set of bioactivity data of insecticidal, fungicidal and herbicidal compounds and assays was collated and added to the database. PMID:26175909
Computational solutions to large-scale data management and analysis
Schadt, Eric E.; Linderman, Michael D.; Sorenson, Jon; Lee, Lawrence; Nolan, Garry P.
2011-01-01
Today we can generate hundreds of gigabases of DNA and RNA sequencing data in a week for less than US$5,000. The astonishing rate of data generation by these low-cost, high-throughput technologies in genomics is being matched by that of other technologies, such as real-time imaging and mass spectrometry-based flow cytometry. Success in the life sciences will depend on our ability to properly interpret the large-scale, high-dimensional data sets that are generated by these technologies, which in turn requires us to adopt advances in informatics. Here we discuss how we can master the different types of computational environments that exist — such as cloud and heterogeneous computing — to successfully tackle our big data problems. PMID:20717155
Complex modular structure of large-scale brain networks
NASA Astrophysics Data System (ADS)
Valencia, M.; Pastor, M. A.; Fernández-Seara, M. A.; Artieda, J.; Martinerie, J.; Chavez, M.
2009-06-01
Modular structure is ubiquitous among real-world networks from related proteins to social groups. Here we analyze the modular organization of brain networks at a large scale (voxel level) extracted from functional magnetic resonance imaging signals. By using a random-walk-based method, we unveil the modularity of brain webs and show modules with a spatial distribution that matches anatomical structures with functional significance. The functional role of each node in the network is studied by analyzing its patterns of inter- and intramodular connections. Results suggest that the modular architecture constitutes the structural basis for the coexistence of functional integration of distant and specialized brain areas during normal brain activities at rest.
Large Scale Bacterial Colony Screening of Diversified FRET Biosensors
Litzlbauer, Julia; Schifferer, Martina; Ng, David; Fabritius, Arne; Thestrup, Thomas; Griesbeck, Oliver
2015-01-01
Biosensors based on Förster Resonance Energy Transfer (FRET) between fluorescent protein mutants have started to revolutionize physiology and biochemistry. However, many types of FRET biosensors show relatively small FRET changes, making measurements with these probes challenging when used under sub-optimal experimental conditions. Thus, a major effort in the field currently lies in designing new optimization strategies for these types of sensors. Here we describe procedures for optimizing FRET changes by large scale screening of mutant biosensor libraries in bacterial colonies. We describe optimization of biosensor expression, permeabilization of bacteria, software tools for analysis, and screening conditions. The procedures reported here may help in improving FRET changes in multiple suitable classes of biosensors. PMID:26061878
Recovery Act - Large Scale SWNT Purification and Solubilization
Michael Gemano; Dr. Linda B. McGown
2010-10-07
The goal of this Phase I project was to establish a quantitative foundation for development of binary G-gels for large-scale, commercial processing of SWNTs and to develop scientific insight into the underlying mechanisms of solubilization, selectivity and alignment. In order to accomplish this, we performed systematic studies to determine the effects of G-gel composition and experimental conditions that will enable us to achieve our goals that include (1) preparation of ultra-high purity SWNTs from low-quality, commercial SWNT starting materials, (2) separation of MWNTs from SWNTs, (3) bulk, non-destructive solubilization of individual SWNTs in aqueous solution at high concentrations (10-100 mg/mL) without sonication or centrifugation, (4) tunable enrichment of subpopulations of the SWNTs based on metallic vs. semiconductor properties, diameter, or chirality and (5) alignment of individual SWNTs.
Large-scale electric fields in the earth's magnetosphere
NASA Technical Reports Server (NTRS)
Stern, D. P.
1977-01-01
Studies of the earth's magnetosphere have indicated that a large-scale electric field E plays a central role in its electrodynamics and in the flow and acceleration of charged particles there; while many observations relevant to E have accumulated, quite a few basic problems involving the origin and structure of this field remain unsolved. The ultimate source of E is presumably the flow of the solar wind past the earth, but the mechanism by which E arises is still unclear, and several independent sources may contribute to it, some of them being of a rather transient nature. This review attempts to sum up the main observed facts and theoretical concepts related to E.
Battery technologies for large-scale stationary energy storage.
Soloveichik, Grigorii L
2011-01-01
In recent years, with the deployment of renewable energy sources, advances in electrified transportation, and development in smart grids, the markets for large-scale stationary energy storage have grown rapidly. Electrochemical energy storage methods are strong candidate solutions due to their high energy density, flexibility, and scalability. This review provides an overview of mature and emerging technologies for secondary and redox flow batteries. New developments in the chemistry of secondary and flow batteries as well as regenerative fuel cells are also considered. Advantages and disadvantages of current and prospective electrochemical energy storage options are discussed. The most promising technologies in the short term are high-temperature sodium batteries with β″-alumina electrolyte, lithium-ion batteries, and flow batteries. Regenerative fuel cells and lithium metal batteries with high energy density require further research to become practical. PMID:22432629
Black hole jets without large-scale net magnetic flux
NASA Astrophysics Data System (ADS)
Parfrey, Kyle; Giannios, Dimitrios; Beloborodov, Andrei M.
2015-01-01
We propose a scenario for launching relativistic jets from rotating black holes, in which small-scale magnetic flux loops, sustained by disc turbulence, are forced to inflate and open by differential rotation between the black hole and the accretion flow. This mechanism does not require a large-scale net magnetic flux in the accreting plasma. Estimates suggest that the process could operate effectively in many systems, and particularly naturally and efficiently when the accretion flow is retrograde. We present the results of general-relativistic force-free electrodynamic simulations demonstrating the time evolution of the black hole's magnetosphere, the cyclic formation of jets, and the effect of magnetic reconnection. The jets are highly variable on time-scales ˜10-103rg/c, where rg is the black hole's gravitational radius. The reconnecting current sheets observed in the simulations may be responsible for the hard X-ray emission from accreting black holes.
Optimal Wind Energy Integration in Large-Scale Electric Grids
NASA Astrophysics Data System (ADS)
Albaijat, Mohammad H.
The major concern in electric grid operation is operating under the most economical and reliable fashion to ensure affordability and continuity of electricity supply. This dissertation investigates the effects of such challenges, which affect electric grid reliability and economic operations. These challenges are: 1. Congestion of transmission lines, 2. Transmission lines expansion, 3. Large-scale wind energy integration, and 4. Phaser Measurement Units (PMUs) optimal placement for highest electric grid observability. Performing congestion analysis aids in evaluating the required increase of transmission line capacity in electric grids. However, it is necessary to evaluate expansion of transmission line capacity on methods to ensure optimal electric grid operation. Therefore, the expansion of transmission line capacity must enable grid operators to provide low-cost electricity while maintaining reliable operation of the electric grid. Because congestion affects the reliability of delivering power and increases its cost, the congestion analysis in electric grid networks is an important subject. Consequently, next-generation electric grids require novel methodologies for studying and managing congestion in electric grids. We suggest a novel method of long-term congestion management in large-scale electric grids. Owing to the complication and size of transmission line systems and the competitive nature of current grid operation, it is important for electric grid operators to determine how many transmission lines capacity to add. Traditional questions requiring answers are "Where" to add, "How much of transmission line capacity" to add, and "Which voltage level". Because of electric grid deregulation, transmission lines expansion is more complicated as it is now open to investors, whose main interest is to generate revenue, to build new transmission lines. Adding a new transmission capacity will help the system to relieve the transmission system congestion, create
Large Scale Deformation of the Western U.S. Cordillera
NASA Technical Reports Server (NTRS)
Bennett, Richard A.
2002-01-01
Over the past couple of years, with support from NASA, we used a large collection of data from GPS, VLBI, SLR, and DORIS networks which span the Western U.S. Cordillera (WUSC) to precisely quantify present-day large-scale crustal deformations in a single uniform reference frame. Our work was roughly divided into an analysis of these space geodetic observations to infer the deformation field across and within the entire plate boundary zone, and an investigation of the implications of this deformation field regarding plate boundary dynamics. Following the determination of the first generation WUSC velocity solution, we placed high priority on the dissemination of the velocity estimates. With in-kind support from the Smithsonian Astrophysical Observatory, we constructed a web-site which allows anyone to access the data, and to determine their own velocity reference frame.
Large Scale Deformation of the Western U.S. Cordillera
NASA Technical Reports Server (NTRS)
Bennett, Richard A.
2002-01-01
Over the past couple of years, with support from NASA, we used a large collection of data from GPS, VLBI, SLR, and DORIS networks which span the Westem U.S. Cordillera (WUSC) to precisely quantify present-day large-scale crustal deformations in a single uniform reference frame. Our work was roughly divided into an analysis of these space geodetic observations to infer the deformation field across and within the entire plate boundary zone, and an investigation of the implications of this deformation field regarding plate boundary dynamics. Following the determination of the first generation WUSC velocity solution, we placed high priority on the dissemination of the velocity estimates. With in-kind support from the Smithsonian Astrophysical Observatory, we constructed a web-site which allows anyone to access the data, and to determine their own velocity reference frame.
Large-scale quantum networks based on graphs
NASA Astrophysics Data System (ADS)
Epping, Michael; Kampermann, Hermann; Bruß, Dagmar
2016-05-01
Society relies and depends increasingly on information exchange and communication. In the quantum world, security and privacy is a built-in feature for information processing. The essential ingredient for exploiting these quantum advantages is the resource of entanglement, which can be shared between two or more parties. The distribution of entanglement over large distances constitutes a key challenge for current research and development. Due to losses of the transmitted quantum particles, which typically scale exponentially with the distance, intermediate quantum repeater stations are needed. Here we show how to generalise the quantum repeater concept to the multipartite case, by describing large-scale quantum networks, i.e. network nodes and their long-distance links, consistently in the language of graphs and graph states. This unifying approach comprises both the distribution of multipartite entanglement across the network, and the protection against errors via encoding. The correspondence to graph states also provides a tool for optimising the architecture of quantum networks.
Innovation cycle for small- and large-scale change.
Scott, Kathy; Steinbinder, Amy
2009-01-01
In today's complex healthcare systems, transformation requires 2 major efforts: (1) a fundamental changes in the underlying beliefs and assumptions that perpetuate the current system and (2) a fundamental redesign of the multiplicity of diverse and complex subsystems that result in unpredictable aggregate behavior and outcomes. Through an Intelligent Complex Adaptive System framework combined with an innovation process a transformation process and cycle was created for a large healthcare system that resulted in both small- and large-scale changes. This process not only challenges the underlying beliefs and assumptions but also creates new possibilities and prototypes for care delivery through a change-management process that is inclusive and honors the contributions of the entire team.
Large-scale structure of time evolving citation networks
NASA Astrophysics Data System (ADS)
Leicht, E. A.; Clarkson, G.; Shedden, K.; Newman, M. E. J.
2007-09-01
In this paper we examine a number of methods for probing and understanding the large-scale structure of networks that evolve over time. We focus in particular on citation networks, networks of references between documents such as papers, patents, or court cases. We describe three different methods of analysis, one based on an expectation-maximization algorithm, one based on modularity optimization, and one based on eigenvector centrality. Using the network of citations between opinions of the United States Supreme Court as an example, we demonstrate how each of these methods can reveal significant structural divisions in the network and how, ultimately, the combination of all three can help us develop a coherent overall picture of the network's shape.
Measuring Large-Scale Social Networks with High Resolution
Stopczynski, Arkadiusz; Sekara, Vedran; Sapiezynski, Piotr; Cuttone, Andrea; Madsen, Mette My; Larsen, Jakob Eg; Lehmann, Sune
2014-01-01
This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years—the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1 000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. The paper is concluded with early results from data analysis, illustrating the importance of multi-channel high-resolution approach to data collection. PMID:24770359
Large-scale coastal evolution of Louisiana's barrier islands
List, Jeffrey H.; Jaffe, Bruce E.; Sallenger,, Asbury H., Jr.
1991-01-01
The prediction of large-scale coastal change is an extremely important, but distant goal. Here we describe some of our initial efforts in this direction, using historical bathymetric information along a 150 km reach of the rapidly evolving barrier island coast of Louisiana. Preliminary results suggest that the relative sea level rise rate, though extremely high in the area, has played a secondary role in coastal erosion over the last 100 years, with longshore transport of sand-sized sediment being the primary cause. Prediction of future conditions is hampered by a general lack of erosion processes understanding; however, an examination of the changing volumes of sand stored in a large ebb-tidal delta system suggests a continued high rate of shoreline retreat driven by the longshore re-distribution of sand.
Large-Scale Quantitative Analysis of Painting Arts
NASA Astrophysics Data System (ADS)
Kim, Daniel; Son, Seung-Woo; Jeong, Hawoong
2014-12-01
Scientists have made efforts to understand the beauty of painting art in their own languages. As digital image acquisition of painting arts has made rapid progress, researchers have come to a point where it is possible to perform statistical analysis of a large-scale database of artistic paints to make a bridge between art and science. Using digital image processing techniques, we investigate three quantitative measures of images - the usage of individual colors, the variety of colors, and the roughness of the brightness. We found a difference in color usage between classical paintings and photographs, and a significantly low color variety of the medieval period. Interestingly, moreover, the increment of roughness exponent as painting techniques such as chiaroscuro and sfumato have advanced is consistent with historical circumstances.
Are Critical Phenomena Relevant to Large-Scale Evolution?
NASA Astrophysics Data System (ADS)
Sole, Ricard V.; Bascompte, Jordi
1996-02-01
Recent theoretical studies, based on the theory of self-organized critical systems, seem to suggest that the dynamical patterns of macroevolution could belong to such class of critical phenomena. Two basic approaches have been proposed: the Kauffman-Johnsen model (based on the use of coupled fitness landscapes) and the Bak-Sneppen model. Both are reviewed here. These models are oversimplified pictures of biological evolution, but the (possible) validity of them is based on the concept of universality, i.e. that apparently very different systems sharing some few common properties should also behave in a very similar way. In this paper we explore the current evidence from the fossil record, showing that some properties that are suggestive of critical dynamics would also be the result of random phenomema. Some general properties of the large-scale pattern of evolution, which should be reproduced by these models, are discussed.
Disaster triage systems for large-scale catastrophic events.
Bostick, Nathan A; Subbarao, Italo; Burkle, Frederick M; Hsu, Edbert B; Armstrong, John H; James, James J
2008-09-01
Large-scale catastrophic events typically result in a scarcity of essential medical resources and accordingly necessitate the implementation of triage management policies to minimize preventable morbidity and mortality. Accomplishing this goal requires a reconceptualization of triage as a population-based systemic process that integrates care at all points of interaction between patients and the health care system. This system identifies at minimum 4 orders of contact: first order, the community; second order, prehospital; third order, facility; and fourth order, regional level. Adopting this approach will ensure that disaster response activities will occur in a comprehensive fashion that minimizes the patient care burden at each subsequent order of intervention and reduces the overall need to ration care. The seamless integration of all orders of intervention within this systems-based model of disaster-specific triage, coordinated through health emergency operations centers, can ensure that disaster response measures are undertaken in a manner that is effective, just, and equitable. PMID:18769264
The effect of large-scale eddies on climatic change.
NASA Technical Reports Server (NTRS)
Stone, P. H.
1973-01-01
A parameterization for the fluxes of sensible heat by large-scale eddies developed in an earlier paper is incorporated into a model for the mean temperature structure of an atmosphere including only these fluxes and the radiative fluxes. The climatic changes in this simple model are then studied in order to assess the strength of the dynamical feedback and to gain insight into how dynamical parameters may change in more sophisticated climatic models. The model shows the following qualitative changes: (1) an increase in the solar constant leads to increased static stability, decreased dynamic stability, and stronger horizontal and vertical winds; (2) an increase in the amount of atmospheric absorption leads to decreased static and dynamic stability, and stronger horizontal and vertical winds; and (3) an increase in rotation rate leads to greater static and dynamic stability, weaker horizontal winds, and stronger vertical winds.
Policy Driven Development: Flexible Policy Insertion for Large Scale Systems
Demchak, Barry; Krüger, Ingolf
2014-01-01
The success of a software system depends critically on how well it reflects and adapts to stakeholder requirements. Traditional development methods often frustrate stakeholders by creating long latencies between requirement articulation and system deployment, especially in large scale systems. One source of latency is the maintenance of policy decisions encoded directly into system workflows at development time, including those involving access control and feature set selection. We created the Policy Driven Development (PDD) methodology to address these development latencies by enabling the flexible injection of decision points into existing workflows at runtime, thus enabling policy composition that integrates requirements furnished by multiple, oblivious stakeholder groups. Using PDD, we designed and implemented a production cyberinfrastructure that demonstrates policy and workflow injection that quickly implements stakeholder requirements, including features not contemplated in the original system design. PDD provides a path to quickly and cost effectively evolve such applications over a long lifetime. PMID:25383258
Large-Scale Quantitative Analysis of Painting Arts
Kim, Daniel; Son, Seung-Woo; Jeong, Hawoong
2014-01-01
Scientists have made efforts to understand the beauty of painting art in their own languages. As digital image acquisition of painting arts has made rapid progress, researchers have come to a point where it is possible to perform statistical analysis of a large-scale database of artistic paints to make a bridge between art and science. Using digital image processing techniques, we investigate three quantitative measures of images – the usage of individual colors, the variety of colors, and the roughness of the brightness. We found a difference in color usage between classical paintings and photographs, and a significantly low color variety of the medieval period. Interestingly, moreover, the increment of roughness exponent as painting techniques such as chiaroscuro and sfumato have advanced is consistent with historical circumstances. PMID:25501877
Successful Physician Training Program for Large Scale EMR Implementation
Stevens, L.A.; Mailes, E.S.; Goad, B.A.; Longhurst, C.A.
2015-01-01
Summary End-user training is an essential element of electronic medical record (EMR) implementation and frequently suffers from minimal institutional investment. In addition, discussion of successful EMR training programs for physicians is limited in the literature. The authors describe a successful physician-training program at Stanford Children’s Health as part of a large scale EMR implementation. Evaluations of classroom training, obtained at the conclusion of each class, revealed high physician satisfaction with the program. Free-text comments from learners focused on duration and timing of training, the learning environment, quality of the instructors, and specificity of training to their role or department. Based upon participant feedback and institutional experience, best practice recommendations, including physician engagement, curricular design, and assessment of proficiency and recognition, are suggested for future provider EMR training programs. The authors strongly recommend the creation of coursework to group providers by common workflow. PMID:25848415
Battery technologies for large-scale stationary energy storage.
Soloveichik, Grigorii L
2011-01-01
In recent years, with the deployment of renewable energy sources, advances in electrified transportation, and development in smart grids, the markets for large-scale stationary energy storage have grown rapidly. Electrochemical energy storage methods are strong candidate solutions due to their high energy density, flexibility, and scalability. This review provides an overview of mature and emerging technologies for secondary and redox flow batteries. New developments in the chemistry of secondary and flow batteries as well as regenerative fuel cells are also considered. Advantages and disadvantages of current and prospective electrochemical energy storage options are discussed. The most promising technologies in the short term are high-temperature sodium batteries with β″-alumina electrolyte, lithium-ion batteries, and flow batteries. Regenerative fuel cells and lithium metal batteries with high energy density require further research to become practical.
Large-scale asymmetric synthesis of a cathepsin S inhibitor.
Lorenz, Jon C; Busacca, Carl A; Feng, XuWu; Grinberg, Nelu; Haddad, Nizar; Johnson, Joe; Kapadia, Suresh; Lee, Heewon; Saha, Anjan; Sarvestani, Max; Spinelli, Earl M; Varsolona, Rich; Wei, Xudong; Zeng, Xingzhong; Senanayake, Chris H
2010-02-19
A potent reversible inhibitor of the cysteine protease cathepsin-S was prepared on large scale using a convergent synthetic route, free of chromatography and cryogenics. Late-stage peptide coupling of a chiral urea acid fragment with a functionalized aminonitrile was employed to prepare the target, using 2-hydroxypyridine as a robust, nonexplosive replacement for HOBT. The two key intermediates were prepared using a modified Strecker reaction for the aminonitrile and a phosphonation-olefination-rhodium-catalyzed asymmetric hydrogenation sequence for the urea. A palladium-catalyzed vinyl transfer coupled with a Claisen reaction was used to produce the aldehyde required for the side chain. Key scale up issues, safety calorimetry, and optimization of all steps for multikilogram production are discussed. PMID:20102230
Applications of large-scale density functional theory in biology
NASA Astrophysics Data System (ADS)
Cole, Daniel J.; Hine, Nicholas D. M.
2016-10-01
Density functional theory (DFT) has become a routine tool for the computation of electronic structure in the physics, materials and chemistry fields. Yet the application of traditional DFT to problems in the biological sciences is hindered, to a large extent, by the unfavourable scaling of the computational effort with system size. Here, we review some of the major software and functionality advances that enable insightful electronic structure calculations to be performed on systems comprising many thousands of atoms. We describe some of the early applications of large-scale DFT to the computation of the electronic properties and structure of biomolecules, as well as to paradigmatic problems in enzymology, metalloproteins, photosynthesis and computer-aided drug design. With this review, we hope to demonstrate that first principles modelling of biological structure-function relationships are approaching a reality.
Thermophoretically induced large-scale deformations around microscopic heat centers
NASA Astrophysics Data System (ADS)
Puljiz, Mate; Orlishausen, Michael; Köhler, Werner; Menzel, Andreas M.
2016-05-01
Selectively heating a microscopic colloidal particle embedded in a soft elastic matrix is a situation of high practical relevance. For instance, during hyperthermic cancer treatment, cell tissue surrounding heated magnetic colloidal particles is destroyed. Experiments on soft elastic polymeric matrices suggest a very long-ranged, non-decaying radial component of the thermophoretically induced displacement fields around the microscopic heat centers. We theoretically confirm this conjecture using a macroscopic hydrodynamic two-fluid description. Both thermophoretic and elastic effects are included in this theory. Indeed, we find that the elasticity of the environment can cause the experimentally observed large-scale radial displacements in the embedding matrix. Additional experiments confirm the central role of elasticity. Finally, a linearly decaying radial component of the displacement field in the experiments is attributed to the finite size of the experimental sample. Similar results are obtained from our theoretical analysis under modified boundary conditions.
Large scale land use cartography of special areas
Amico, F.D.; Maccarone, D.; Pandiscia, G.V.
1996-11-01
On 06 October 1993 an aerial remote sensing mission has been done on the {open_quote}Mounts of the Sila{close_quotes} area, using a DAEDALUS ATM multispectral scanner, in the framework of the TELAER project, supported by I.A.S.M. (Istituto per l`Assistenza e lo Sviluppo del Mezzogiorno). The study area is inside the National Park of Calabria, well known for its coniferous forests. The collected imagery were used to produce a large scale land use cartography, on the scale of 1 to 5000, extracting information on natural and anthropical vegetation from the multispectral images, with the aid of stereo photos acquired simultaneously. 5 refs., 1 fig., 1 tab.
Large-scale identification of yeast integral membrane protein interactions
Miller, John P.; Lo, Russell S.; Ben-Hur, Asa; Desmarais, Cynthia; Stagljar, Igor; Noble, William Stafford; Fields, Stanley
2005-01-01
We carried out a large-scale screen to identify interactions between integral membrane proteins of Saccharomyces cerevisiae by using a modified split-ubiquitin technique. Among 705 proteins annotated as integral membrane, we identified 1,985 putative interactions involving 536 proteins. To ascribe confidence levels to the interactions, we used a support vector machine algorithm to classify interactions based on the assay results and protein data derived from the literature. Previously identified and computationally supported interactions were used to train the support vector machine, which identified 131 interactions of highest confidence, 209 of the next highest confidence, 468 of the next highest, and the remaining 1,085 of low confidence. This study provides numerous putative interactions among a class of proteins that have been difficult to analyze on a high-throughput basis by other approaches. The results identify potential previously undescribed components of established biological processes and roles for integral membrane proteins of ascribed functions. PMID:16093310
Large-Scale Advanced Prop-Fan (LAP) blade design
NASA Technical Reports Server (NTRS)
Violette, John A.; Sullivan, William E.; Turnberg, Jay E.
1984-01-01
This report covers the design analysis of a very thin, highly swept, propeller blade to be used in the Large-Scale Advanced Prop-Fan (LAP) test program. The report includes: design requirements and goals, a description of the blade configuration which meets requirements, a description of the analytical methods utilized/developed to demonstrate compliance with the requirements, and the results of these analyses. The methods described include: finite element modeling, predicted aerodynamic loads and their application to the blade, steady state and vibratory response analyses, blade resonant frequencies and mode shapes, bird impact analysis, and predictions of stalled and unstalled flutter phenomena. Summarized results include deflections, retention loads, stress/strength comparisons, foreign object damage resistance, resonant frequencies and critical speed margins, resonant vibratory mode shapes, calculated boundaries of stalled and unstalled flutter, and aerodynamic and acoustic performance calculations.
Nonzero Density-Velocity Consistency Relations for Large Scale Structures
NASA Astrophysics Data System (ADS)
Rizzo, Luca Alberto; Mota, David F.; Valageas, Patrick
2016-08-01
We present exact kinematic consistency relations for cosmological structures that do not vanish at equal times and can thus be measured in surveys. These rely on cross correlations between the density and velocity, or momentum, fields. Indeed, the uniform transport of small-scale structures by long-wavelength modes, which cannot be detected at equal times by looking at density correlations only, gives rise to a shift in the amplitude of the velocity field that could be measured. These consistency relations only rely on the weak equivalence principle and Gaussian initial conditions. They remain valid in the nonlinear regime and for biased galaxy fields. They can be used to constrain nonstandard cosmological scenarios or the large-scale galaxy bias.
Scalable Parallel Distance Field Construction for Large-Scale Applications.
Yu, Hongfeng; Xie, Jinrong; Ma, Kwan-Liu; Kolla, Hemanth; Chen, Jacqueline H
2015-10-01
Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. A new distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking over time, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate its efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. Our work greatly extends the usability of distance fields for demanding applications.
In situ vitrification large-scale operational acceptance test analysis
Buelt, J.L.; Carter, J.G.
1986-05-01
A thermal treatment process is currently under study to provide possible enhancement of in-place stabilization of transuranic and chemically contaminated soil sites. The process is known as in situ vitrification (ISV). In situ vitrification is a remedial action process that destroys solid and liquid organic contaminants and incorporates radionuclides into a glass-like material that renders contaminants substantially less mobile and less likely to impact the environment. A large-scale operational acceptance test (LSOAT) was recently completed in which more than 180 t of vitrified soil were produced in each of three adjacent settings. The LSOAT demonstrated that the process conforms to the functional design criteria necessary for the large-scale radioactive test (LSRT) to be conducted following verification of the performance capabilities of the process. The energy requirements and vitrified block size, shape, and mass are sufficiently equivalent to those predicted by the ISV mathematical model to confirm its usefulness as a predictive tool. The LSOAT demonstrated an electrode replacement technique, which can be used if an electrode fails, and techniques have been identified to minimize air oxidation, thereby extending electrode life. A statistical analysis was employed during the LSOAT to identify graphite collars and an insulative surface as successful cold cap subsidence techniques. The LSOAT also showed that even under worst-case conditions, the off-gas system exceeds the flow requirements necessary to maintain a negative pressure on the hood covering the area being vitrified. The retention of simulated radionuclides and chemicals in the soil and off-gas system exceeds requirements so that projected emissions are one to two orders of magnitude below the maximum permissible concentrations of contaminants at the stack.
Sheltering in buildings from large-scale outdoor releases
Chan, W.R.; Price, P.N.; Gadgil, A.J.
2004-06-01
Intentional or accidental large-scale airborne toxic release (e.g. terrorist attacks or industrial accidents) can cause severe harm to nearby communities. Under these circumstances, taking shelter in buildings can be an effective emergency response strategy. Some examples where shelter-in-place was successful at preventing injuries and casualties have been documented [1, 2]. As public education and preparedness are vital to ensure the success of an emergency response, many agencies have prepared documents advising the public on what to do during and after sheltering [3, 4, 5]. In this document, we will focus on the role buildings play in providing protection to occupants. The conclusions to this article are: (1) Under most circumstances, shelter-in-place is an effective response against large-scale outdoor releases. This is particularly true for release of short duration (a few hours or less) and chemicals that exhibit non-linear dose-response characteristics. (2) The building envelope not only restricts the outdoor-indoor air exchange, but can also filter some biological or even chemical agents. Once indoors, the toxic materials can deposit or sorb onto indoor surfaces. All these processes contribute to the effectiveness of shelter-in-place. (3) Tightening of building envelope and improved filtration can enhance the protection offered by buildings. Common mechanical ventilation system present in most commercial buildings, however, should be turned off and dampers closed when sheltering from an outdoor release. (4) After the passing of the outdoor plume, some residuals will remain indoors. It is therefore important to terminate shelter-in-place to minimize exposure to the toxic materials.
High Fidelity Simulations of Large-Scale Wireless Networks
Onunkwo, Uzoma; Benz, Zachary
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.
The Large-scale Component of Mantle Convection
NASA Astrophysics Data System (ADS)
Cserepes, L.
Circulation in the Earth's mantle occurs on multiple spatial scales: this review dis- cusses the character of its large-scale or global components. Direct and strong evi- dence concerning the global flow comes, first of all, from the pattern of plate motion. Further indirect observational data which can be transformed into flow velocities by the equation of motion are the internal density heterogeneities revealed by seismic to- mography, and the geoid can also be used as an observational constraint. Due to their limited spatial resolution, global tomographic data automatically filter out the small- scale features and are therefore relevant to the global flow pattern. Flow solutions obtained from tomographic models, using the plate motion as boundary condition, re- veal that subduction is the downwelling of the global mantle circulation and that the deep-rooted upwellings are concentrated in 2-3 superplumes. Spectral analysis of the tomographic heterogeneities shows that the power of global flow appears dominantly in the lowest spherical harmonic orders 2-5. Theoretical convection calculations con- tribute substantially to the understanding of global flow. If basal heating of the mantle is significant, numerical models can reproduce the basic 2 to 5 cell pattern of con- vection even without the inclusion of surface plates. If plates are superimposed on the solution with their present arrangement and motion, the dominance of these low spherical harmonic orders is more pronounced. The cells are not necessarily closed, rather they show chaotic time-dependence, but they are normally bordered by long downwelling features, and they have usually a single superplume in the cell interior. Swarms of small plumes can develop in the large cells, especially when convection is partially layered due to an internal boundary such as the 670 km discontinuity (source of small plumes). These small plumes are usually tilted by the background large-scale flow which shows that they are
Nanomaterials processing toward large-scale flexible/stretchable electronics
NASA Astrophysics Data System (ADS)
Takahashi, Toshitake
In recent years, there has been tremendous progress in large-scale mechanically flexible electronics, where electrical components are fabricated on non-crystalline substrates such as plastics and glass. These devices are currently serving as the basis for various applications such as flat-panel displays, smart cards, and wearable electronics. In this thesis, a promising approach using chemically synthesized nanomaterials is explored to overcome various obstacles current technology faces in this field. Here, we use chemically synthesized semiconducting nanowires (NWs) including group IV (Si, Ge), III-V (InAs) and II-IV (CdS, CdSe) NWs, and semiconductor-enriched SWNTs (99 % purity), and developed reliable, controllable, and more importantly uniform assembly methods on 4-inch wafer-scale flexible substrates in the form of either parallel NW arrays or SWNT random networks, which act as the active components in thin film transistors (TFTs). Thusly obtained TFTs composed of nanomaterials show respectable electrical and optical properties such as 1) cut-off frequency, ft ~ 1 GHz and maximum frequency of oscillation, fmax ~ 1.8 GHz from InAs parallel NW array TFTs with channel length of ~ 1.5 μm, 2) photodetectors covering visible wavelengths (500-700 nm) using compositionally graded CdSxSe1-x (0 < x < 1) parallel NW arrays, and 3) carrier mobility of ~ 20 cm2/Vs, which is an order of magnitude larger than conventional TFT materials such as a-Si and organic semiconductors, without sacrificing current on/off ratio (Ion/Ioff ~ 104) from SWNT network TFTs. The capability to uniformly assemble nanomaterials over large-scale flexible substrates enables us to use them for more sophisticated applications. Artificial electronic skin (e-skin) is demonstrated by laminating pressure sensitive rubber on top of nanomaterial-based active matrix backplanes. Furthermore, an x-ray imaging device is also achieved by combining organic photodiodes with this backplane technology.
Large scale, urban decontamination; developments, historical examples and lessons learned
Demmer, R.L.
2007-07-01
Recent terrorist threats and actions have lead to a renewed interest in the technical field of large scale, urban environment decontamination. One of the driving forces for this interest is the prospect for the cleanup and removal of radioactive dispersal device (RDD or 'dirty bomb') residues. In response, the United States Government has spent many millions of dollars investigating RDD contamination and novel decontamination methodologies. The efficiency of RDD cleanup response will be improved with these new developments and a better understanding of the 'old reliable' methodologies. While an RDD is primarily an economic and psychological weapon, the need to cleanup and return valuable or culturally significant resources to the public is nonetheless valid. Several private companies, universities and National Laboratories are currently developing novel RDD cleanup technologies. Because of its longstanding association with radioactive facilities, the U. S. Department of Energy National Laboratories are at the forefront in developing and testing new RDD decontamination methods. However, such cleanup technologies are likely to be fairly task specific; while many different contamination mechanisms, substrate and environmental conditions will make actual application more complicated. Some major efforts have also been made to model potential contamination, to evaluate both old and new decontamination techniques and to assess their readiness for use. There are a number of significant lessons that can be gained from a look at previous large scale cleanup projects. Too often we are quick to apply a costly 'package and dispose' method when sound technological cleaning approaches are available. Understanding historical perspectives, advanced planning and constant technology improvement are essential to successful decontamination. (authors)
Tools for Large-Scale Mobile Malware Analysis
Bierma, Michael
2014-01-01
Analyzing mobile applications for malicious behavior is an important area of re- search, and is made di cult, in part, by the increasingly large number of appli- cations available for the major operating systems. There are currently over 1.2 million apps available in both the Google Play and Apple App stores (the respec- tive o cial marketplaces for the Android and iOS operating systems)[1, 2]. Our research provides two large-scale analysis tools to aid in the detection and analysis of mobile malware. The rst tool we present, Andlantis, is a scalable dynamic analysis system capa- ble of processing over 3000 Android applications per hour. Traditionally, Android dynamic analysis techniques have been relatively limited in scale due to the compu- tational resources required to emulate the full Android system to achieve accurate execution. Andlantis is the most scalable Android dynamic analysis framework to date, and is able to collect valuable forensic data, which helps reverse-engineers and malware researchers identify and understand anomalous application behavior. We discuss the results of running 1261 malware samples through the system, and provide examples of malware analysis performed with the resulting data. While techniques exist to perform static analysis on a large number of appli- cations, large-scale analysis of iOS applications has been relatively small scale due to the closed nature of the iOS ecosystem, and the di culty of acquiring appli- cations for analysis. The second tool we present, iClone, addresses the challenges associated with iOS research in order to detect application clones within a dataset of over 20,000 iOS applications.
Large-scale mass distribution in the Illustris simulation
NASA Astrophysics Data System (ADS)
Haider, M.; Steinhauser, D.; Vogelsberger, M.; Genel, S.; Springel, V.; Torrey, P.; Hernquist, L.
2016-04-01
Observations at low redshifts thus far fail to account for all of the baryons expected in the Universe according to cosmological constraints. A large fraction of the baryons presumably resides in a thin and warm-hot medium between the galaxies, where they are difficult to observe due to their low densities and high temperatures. Cosmological simulations of structure formation can be used to verify this picture and provide quantitative predictions for the distribution of mass in different large-scale structure components. Here we study the distribution of baryons and dark matter at different epochs using data from the Illustris simulation. We identify regions of different dark matter density with the primary constituents of large-scale structure, allowing us to measure mass and volume of haloes, filaments and voids. At redshift zero, we find that 49 per cent of the dark matter and 23 per cent of the baryons are within haloes more massive than the resolution limit of 2 × 108 M⊙. The filaments of the cosmic web host a further 45 per cent of the dark matter and 46 per cent of the baryons. The remaining 31 per cent of the baryons reside in voids. The majority of these baryons have been transported there through active galactic nuclei feedback. We note that the feedback model of Illustris is too strong for heavy haloes, therefore it is likely that we are overestimating this amount. Categorizing the baryons according to their density and temperature, we find that 17.8 per cent of them are in a condensed state, 21.6 per cent are present as cold, diffuse gas, and 53.9 per cent are found in the state of a warm-hot intergalactic medium.
Large-scale quantum photonic circuits in silicon
NASA Astrophysics Data System (ADS)
Harris, Nicholas C.; Bunandar, Darius; Pant, Mihir; Steinbrecher, Greg R.; Mower, Jacob; Prabhu, Mihika; Baehr-Jones, Tom; Hochberg, Michael; Englund, Dirk
2016-08-01
Quantum information science offers inherently more powerful methods for communication, computation, and precision measurement that take advantage of quantum superposition and entanglement. In recent years, theoretical and experimental advances in quantum computing and simulation with photons have spurred great interest in developing large photonic entangled states that challenge today's classical computers. As experiments have increased in complexity, there has been an increasing need to transition bulk optics experiments to integrated photonics platforms to control more spatial modes with higher fidelity and phase stability. The silicon-on-insulator (SOI) nanophotonics platform offers new possibilities for quantum optics, including the integration of bright, nonclassical light sources, based on the large third-order nonlinearity (χ(3)) of silicon, alongside quantum state manipulation circuits with thousands of optical elements, all on a single phase-stable chip. How large do these photonic systems need to be? Recent theoretical work on Boson Sampling suggests that even the problem of sampling from e30 identical photons, having passed through an interferometer of hundreds of modes, becomes challenging for classical computers. While experiments of this size are still challenging, the SOI platform has the required component density to enable low-loss and programmable interferometers for manipulating hundreds of spatial modes. Here, we discuss the SOI nanophotonics platform for quantum photonic circuits with hundreds-to-thousands of optical elements and the associated challenges. We compare SOI to competing technologies in terms of requirements for quantum optical systems. We review recent results on large-scale quantum state evolution circuits and strategies for realizing high-fidelity heralded gates with imperfect, practical systems. Next, we review recent results on silicon photonics-based photon-pair sources and device architectures, and we discuss a path towards
Making Large-Scale Networks from fMRI Data
Schmittmann, Verena D.; Jahfari, Sara; Borsboom, Denny; Savi, Alexander O.; Waldorp, Lourens J.
2015-01-01
Pairwise correlations are currently a popular way to estimate a large-scale network (> 1000 nodes) from functional magnetic resonance imaging data. However, this approach generally results in a poor representation of the true underlying network. The reason is that pairwise correlations cannot distinguish between direct and indirect connectivity. As a result, pairwise correlation networks can lead to fallacious conclusions; for example, one may conclude that a network is a small-world when it is not. In a simulation study and an application to resting-state fMRI data, we compare the performance of pairwise correlations in large-scale networks (2000 nodes) against three other methods that are designed to filter out indirect connections. Recovery methods are evaluated in four simulated network topologies (small world or not, scale-free or not) in scenarios where the number of observations is very small compared to the number of nodes. Simulations clearly show that pairwise correlation networks are fragmented into separate unconnected components with excessive connectedness within components. This often leads to erroneous estimates of network metrics, like small-world structures or low betweenness centrality, and produces too many low-degree nodes. We conclude that using partial correlations, informed by a sparseness penalty, results in more accurate networks and corresponding metrics than pairwise correlation networks. However, even with these methods, the presence of hubs in the generating network can be problematic if the number of observations is too small. Additionally, we show for resting-state fMRI that partial correlations are more robust than correlations to different parcellation sets and to different lengths of time-series. PMID:26325185
Modeling temporal relationships in large scale clinical associations
Hanauer, David A; Ramakrishnan, Naren
2013-01-01
Objective We describe an approach for modeling temporal relationships in a large scale association analysis of electronic health record data. The addition of temporal information can inform hypothesis generation and help to explain the relationships. We applied this approach on a dataset containing 41.2 million time-stamped International Classification of Diseases, Ninth Revision (ICD-9) codes from 1.6 million patients. Methods We performed two independent analyses including a pairwise association analysis using a χ2 test and a temporal analysis using a binomial test. Data were visualized using network diagrams and reviewed for clinical significance. Results We found nearly 400 000 highly associated pairs of ICD-9 codes with varying numbers of strong temporal associations ranging from ≥1 day to ≥10 years apart. Most of the findings were not considered clinically novel, although some, such as an association between Helicobacter pylori infection and diabetes, have recently been reported in the literature. The temporal analysis in our large cohort, however, revealed that diabetes usually preceded the diagnoses of H pylori, raising questions about possible cause and effect. Discussion Such analyses have significant limitations, some of which are due to known problems with ICD-9 codes and others to potentially incomplete data even at a health system level. Nevertheless, large scale association analyses with temporal modeling can help provide a mechanism for novel discovery in support of hypothesis generation. Conclusions Temporal relationships can provide an additional layer of meaning in identifying and interpreting clinical associations. PMID:23019240
Nonlinear random response of large-scale sparse finite element plate bending problems
NASA Astrophysics Data System (ADS)
Chokshi, Swati
Acoustic fatigue is one of the major design considerations for skin panels exposed to high levels of random pressure at subsonic/supersonic/hypersonic speeds. The nonlinear large deflection random response of the single-bay panels aerospace structures subjected to random excitations at various sound pressure levels (SPLs) is investigated. The nonlinear responses of plate analyses are limited to determine the root-mean-square displacement under uniformly distributed pressure random loads. Efficient computational technologies like sparse storage schemes and parallel computation are proposed and incorporated to solve large-scale, nonlinear large deflection random vibration problems for both types of loading cases: (1) synchronized in time and (2) unsynchronized and statistically uncorrelated in time. For the first time, large scale plate bending problems subjected to unsynchronized load are solved using parallel computing capabilities to account for computational burden due to the simulation of the unsynchronized random pressure fluctuations. The main focus of the research work is placed upon computational issues involved in the nonlinear modal methodologies. A nonlinear FEM method in time domain is incorporated with the Monte Carlo simulation and sparse computational technologies, including the efficient sparse Subspace Eigen-solutions are presented and applied to accurately determine the random response with a refined, large finite element mesh for the first time. Sparse equation solver and sparse matrix operations embedded inside the subspace Eigen-solution algorithms are also exploited. The approach uses the von-Karman nonlinear strain-displacement relations and the classical plate theory. In the proposed methodologies, the solution for a small number (say less than 100) of lowest linear, sparse Eigen-pairs need to be solved for only once, in order to transform nonlinear large displacements from the conventional structural degree-of-freedom (dof) into the modal
EvArnoldi: A New Algorithm for Large-Scale Eigenvalue Problems.
Tal-Ezer, Hillel
2016-05-19
Eigenvalues and eigenvectors are an essential theme in numerical linear algebra. Their study is mainly motivated by their high importance in a wide range of applications. Knowledge of eigenvalues is essential in quantum molecular science. Solutions of the Schrödinger equation for the electrons composing the molecule are the basis of electronic structure theory. Electronic eigenvalues compose the potential energy surfaces for nuclear motion. The eigenvectors allow calculation of diople transition matrix elements, the core of spectroscopy. The vibrational dynamics molecule also requires knowledge of the eigenvalues of the vibrational Hamiltonian. Typically in these problems, the dimension of Hilbert space is huge. Practically, only a small subset of eigenvalues is required. In this paper, we present a highly efficient algorithm, named EvArnoldi, for solving the large-scale eigenvalues problem. The algorithm, in its basic formulation, is mathematically equivalent to ARPACK ( Sorensen , D. C. Implicitly Restarted Arnoldi/Lanczos Methods for Large Scale Eigenvalue Calculations ; Springer , 1997 ; Lehoucq , R. B. ; Sorensen , D. C. SIAM Journal on Matrix Analysis and Applications 1996 , 17 , 789 ; Calvetti , D. ; Reichel , L. ; Sorensen , D. C. Electronic Transactions on Numerical Analysis 1994 , 2 , 21 ) (or Eigs of Matlab) but significantly simpler. PMID:27015379
Efficient Large-Scale Structure From Motion by Fusing Auxiliary Imaging Information.
Cui, Hainan; Shen, Shuhan; Gao, Wei; Hu, Zhanyi
2015-11-01
One of the potentially effective means for large-scale 3D scene reconstruction is to reconstruct the scene in a global manner, rather than incrementally, by fully exploiting available auxiliary information on the imaging condition, such as camera location by Global Positioning System (GPS), orientation by inertial measurement unit (or compass), focal length from EXIF, and so on. However, such auxiliary information, though informative and valuable, is usually too noisy to be directly usable. In this paper, we present an approach by taking advantage of such noisy auxiliary information to improve structure from motion solving. More specifically, we introduce two effective iterative global optimization algorithms initiated with such noisy auxiliary information. One is a robust rotation averaging algorithm to deal with contaminated epipolar graph, the other is a robust scene reconstruction algorithm to deal with noisy GPS data for camera centers initialization. We found that by exclusively focusing on the estimated inliers at the current iteration, the optimization process initialized by such noisy auxiliary information could converge well and efficiently. Our proposed method is evaluated on real images captured by unmanned aerial vehicle, StreetView car, and conventional digital cameras. Extensive experimental results show that our method performs similarly or better than many of the state-of-art reconstruction approaches, in terms of reconstruction accuracy and completeness, but is more efficient and scalable for large-scale image data sets.
Modeling haboob dust storms in large-scale weather and climate models
NASA Astrophysics Data System (ADS)
Pantillon, Florian; Knippertz, Peter; Marsham, John H.; Panitz, Hans-Jürgen; Bischoff-Gauss, Ingeborg
2016-03-01
Recent field campaigns have shown that haboob dust storms, formed by convective cold pool outflows, contribute a significant fraction of dust uplift over the Sahara and Sahel in summer. However, in situ observations are sparse and haboobs are frequently concealed by clouds in satellite imagery. Furthermore, most large-scale weather and climate models lack haboobs, because they do not explicitly represent convection. Here a 1 year long model run with explicit representation of convection delivers the first full seasonal cycle of haboobs over northern Africa. Using conservative estimates, the model suggests that haboobs contribute one fifth of the annual dust-generating winds over northern Africa, one fourth between May and October, and one third over the western Sahel during this season. A simple parameterization of haboobs has recently been developed for models with parameterized convection, based on the downdraft mass flux of convection schemes. It is applied here to two model runs with different horizontal resolutions and assessed against the explicit run. The parameterization succeeds in capturing the geographical distribution of haboobs and their seasonal cycle over the Sahara and Sahel. It can be tuned to the different horizontal resolutions, and different formulations are discussed with respect to the frequency of extreme events. The results show that the parameterization is reliable and may solve a major and long-standing issue in simulating dust storms in large-scale weather and climate models.
Opportunities for Breakthroughs in Large-Scale Computational Simulation and Design
NASA Technical Reports Server (NTRS)
Alexandrov, Natalia; Alter, Stephen J.; Atkins, Harold L.; Bey, Kim S.; Bibb, Karen L.; Biedron, Robert T.; Carpenter, Mark H.; Cheatwood, F. McNeil; Drummond, Philip J.; Gnoffo, Peter A.
2002-01-01
Opportunities for breakthroughs in the large-scale computational simulation and design of aerospace vehicles are presented. Computational fluid dynamics tools to be used within multidisciplinary analysis and design methods are emphasized. The opportunities stem from speedups and robustness improvements in the underlying unit operations associated with simulation (geometry modeling, grid generation, physical modeling, analysis, etc.). Further, an improved programming environment can synergistically integrate these unit operations to leverage the gains. The speedups result from reducing the problem setup time through geometry modeling and grid generation operations, and reducing the solution time through the operation counts associated with solving the discretized equations to a sufficient accuracy. The opportunities are addressed only at a general level here, but an extensive list of references containing further details is included. The opportunities discussed are being addressed through the Fast Adaptive Aerospace Tools (FAAST) element of the Advanced Systems Concept to Test (ASCoT) and the third Generation Reusable Launch Vehicles (RLV) projects at NASA Langley Research Center. The overall goal is to enable greater inroads into the design process with large-scale simulations.
2015-01-01
Given the large number of crystal structures and NMR ensembles that have been solved to date, classical molecular dynamics (MD) simulations have become powerful tools in the atomistic study of the kinetics and thermodynamics of biomolecular systems on ever increasing time scales. By virtue of the high-dimensional conformational state space that is explored, the interpretation of large-scale simulations faces difficulties not unlike those in the big data community. We address this challenge by introducing a method called clustering based feature selection (CB-FS) that employs a posterior analysis approach. It combines supervised machine learning (SML) and feature selection with Markov state models to automatically identify the relevant degrees of freedom that separate conformational states. We highlight the utility of the method in the evaluation of large-scale simulations and show that it can be used for the rapid and automated identification of relevant order parameters involved in the functional transitions of two exemplary cell-signaling proteins central to human disease states. PMID:25516725
Efficient Large-Scale Structure From Motion by Fusing Auxiliary Imaging Information.
Cui, Hainan; Shen, Shuhan; Gao, Wei; Hu, Zhanyi
2015-11-01
One of the potentially effective means for large-scale 3D scene reconstruction is to reconstruct the scene in a global manner, rather than incrementally, by fully exploiting available auxiliary information on the imaging condition, such as camera location by Global Positioning System (GPS), orientation by inertial measurement unit (or compass), focal length from EXIF, and so on. However, such auxiliary information, though informative and valuable, is usually too noisy to be directly usable. In this paper, we present an approach by taking advantage of such noisy auxiliary information to improve structure from motion solving. More specifically, we introduce two effective iterative global optimization algorithms initiated with such noisy auxiliary information. One is a robust rotation averaging algorithm to deal with contaminated epipolar graph, the other is a robust scene reconstruction algorithm to deal with noisy GPS data for camera centers initialization. We found that by exclusively focusing on the estimated inliers at the current iteration, the optimization process initialized by such noisy auxiliary information could converge well and efficiently. Our proposed method is evaluated on real images captured by unmanned aerial vehicle, StreetView car, and conventional digital cameras. Extensive experimental results show that our method performs similarly or better than many of the state-of-art reconstruction approaches, in terms of reconstruction accuracy and completeness, but is more efficient and scalable for large-scale image data sets. PMID:26111397
NASA Astrophysics Data System (ADS)
Kennedy, Scott Warren
A steady decline in the cost of wind turbines and increased experience in their successful operation have brought this technology to the forefront of viable alternatives for large-scale power generation. Methodologies for understanding the costs and benefits of large-scale wind power development, however, are currently limited. In this thesis, a new and widely applicable technique for estimating the social benefit of large-scale wind power production is presented. The social benefit is based upon wind power's energy and capacity services and the avoidance of environmental damages. The approach uses probabilistic modeling techniques to account for the stochastic interaction between wind power availability, electricity demand, and conventional generator dispatch. A method for including the spatial smoothing effect of geographically dispersed wind farms is also introduced. The model has been used to analyze potential offshore wind power development to the south of Long Island, NY. If natural gas combined cycle (NGCC) and integrated gasifier combined cycle (IGCC) are the alternative generation sources, wind power exhibits a negative social benefit due to its high capacity cost and the relatively low emissions of these advanced fossil-fuel technologies. Environmental benefits increase significantly if charges for CO2 emissions are included. Results also reveal a diminishing social benefit as wind power penetration increases. The dependence of wind power benefits on natural gas and coal prices is also discussed. In power systems with a high penetration of wind generated electricity, the intermittent availability of wind power may influence hourly spot prices. A price responsive electricity demand model is introduced that shows a small increase in wind power value when consumers react to hourly spot prices. The effectiveness of this mechanism depends heavily on estimates of the own- and cross-price elasticities of aggregate electricity demand. This work makes a valuable
NASA Astrophysics Data System (ADS)
Helman, E. Udi
This dissertation conducts research into the large-scale simulation of oligopolistic competition in wholesale electricity markets. The dissertation has two parts. Part I is an examination of the structure and properties of several spatial, or network, equilibrium models of oligopolistic electricity markets formulated as mixed linear complementarity problems (LCP). Part II is a large-scale application of such models to the electricity system that encompasses most of the United States east of the Rocky Mountains, the Eastern Interconnection. Part I consists of Chapters 1 to 6. The models developed in this part continue research into mixed LCP models of oligopolistic electricity markets initiated by Hobbs [67] and subsequently developed by Metzler [87] and Metzler, Hobbs and Pang [88]. Hobbs' central contribution is a network market model with Cournot competition in generation and a price-taking spatial arbitrage firm that eliminates spatial price discrimination by the Cournot firms. In one variant, the solution to this model is shown to be equivalent to the "no arbitrage" condition in a "pool" market, in which a Regional Transmission Operator optimizes spot sales such that the congestion price between two locations is exactly equivalent to the difference in the energy prices at those locations (commonly known as locational marginal pricing). Extensions to this model are presented in Chapters 5 and 6. One of these is a market model with a profit-maximizing arbitrage firm. This model is structured as a mathematical program with equilibrium constraints (MPEC), but due to the linearity of its constraints, can be solved as a mixed LCP. Part II consists of Chapters 7 to 12. The core of these chapters is a large-scale simulation of the U.S. Eastern Interconnection applying one of the Cournot competition with arbitrage models. This is the first oligopolistic equilibrium market model to encompass the full Eastern Interconnection with a realistic network representation (using
Renormalizing a viscous fluid model for large scale structure formation
NASA Astrophysics Data System (ADS)
Führer, Florian; Rigopoulos, Gerasimos
2016-02-01
Using the Stochastic Adhesion Model (SAM) as a simple toy model for cosmic structure formation, we study renormalization and the removal of the cutoff dependence from loop integrals in perturbative calculations. SAM shares the same symmetry with the full system of continuity+Euler equations and includes a viscosity term and a stochastic noise term, similar to the effective theories recently put forward to model CDM clustering. We show in this context that if the viscosity and noise terms are treated as perturbative corrections to the standard eulerian perturbation theory, they are necessarily non-local in time. To ensure Galilean Invariance higher order vertices related to the viscosity and the noise must then be added and we explicitly show at one-loop that these terms act as counter terms for vertex diagrams. The Ward Identities ensure that the non-local-in-time theory can be renormalized consistently. Another possibility is to include the viscosity in the linear propagator, resulting in exponential damping at high wavenumber. The resulting local-in-time theory is then renormalizable to one loop, requiring less free parameters for its renormalization.