Planning under uncertainty solving large-scale stochastic linear programs
Infanger, G. |
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.
Solving large scale traveling salesman problems by chaotic neurodynamics.
Hasegawa, Mikio; Ikeguch, Tohru; Aihara, Kazuyuki
2002-03-01
We propose a novel approach for solving large scale traveling salesman problems (TSPs) by chaotic dynamics. First, we realize the tabu search on a neural network, by utilizing the refractory effects as the tabu effects. Then, we extend it to a chaotic neural network version. We propose two types of chaotic searching methods, which are based on two different tabu searches. While the first one requires neurons of the order of n2 for an n-city TSP, the second one requires only n neurons. Moreover, an automatic parameter tuning method of our chaotic neural network is presented for easy application to various problems. Last, we show that our method with n neurons is applicable to large TSPs such as an 85,900-city problem and exhibits better performance than the conventional stochastic searches and the tabu searches.
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
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.
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.
Adaptive Optimization Techniques for Large-Scale Stochastic Planning
2011-06-28
cannot be kept longer than a few weeks. The decision maker must decide on blood - type substitutions that minimize the chance of future shortage. Because...optimal blood - type substitution is a large stochastic problem. Another application is managing water reservoirs. In this domain, an operator needs to decide...compatibility constraints among blood types , blood inventory management does not fit well the standard inventory control framework. In reservoir management
Li, Yongming; Ma, Zhiyao; Tong, Shaocheng
2017-09-01
The problem of adaptive fuzzy output-constrained tracking fault-tolerant control (FTC) is investigated for the large-scale stochastic nonlinear systems of pure-feedback form. The nonlinear systems considered in this paper possess the unstructured uncertainties, unknown interconnected terms and unknown nonaffine nonlinear faults. The fuzzy logic systems are employed to identify the unknown lumped nonlinear functions so that the problems of structured uncertainties can be solved. An adaptive fuzzy state observer is designed to solve the nonmeasurable state problem. By combining the barrier Lyapunov function theory, adaptive decentralized and stochastic control principles, a novel fuzzy adaptive output-constrained FTC approach is constructed. All the signals in the closed-loop system are proved to be bounded in probability and the system outputs are constrained in a given compact set. Finally, the applicability of the proposed controller is well carried out by a simulation example.
NASA Astrophysics Data System (ADS)
Macian-Sorribes, H.; Tilmant, A.; Pulido-Velazquez, M.
2017-02-01
The management of large-scale water resource systems with surface and groundwater resources requires considering stream-aquifer interactions. Optimization models applied to large-scale systems have either employed deterministic optimization (with perfect foreknowledge of future inflows, which hinders their applicability to real-life operations) or stochastic programming (in which stream-aquifer interaction is often neglected due to the computational burden associated with these methods). In this paper, stream-aquifer interaction is integrated in a stochastic programming framework by combining the Stochastic Dual Dynamic Programming (SDDP) optimization algorithm with the Embedded Multireservoir Model (EMM). The resulting extension of the SDDP algorithm, named Combined Surface-Groundwater SDDP (CSG-SDDP), is able to properly represent the stream-aquifer interaction within stochastic optimization models of large-scale surface-groundwater resource systems. The algorithm is applied to build a hydroeconomic model for the Jucar River Basin (Spain), in which stream-aquifer interactions are essential to the characterization of water resources. Besides the uncertainties regarding the economic characterization of the demand functions, the results show that the economic efficiency of the operating policies under the current system can be improved by better management of groundwater and surface resources.
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.
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
Solving Large-Scale Inverse Magnetostatic Problems using the Adjoint Method
Bruckner, Florian; Abert, Claas; Wautischer, Gregor; Huber, Christian; Vogler, Christoph; Hinze, Michael; Suess, Dieter
2017-01-01
An efficient algorithm for the reconstruction of the magnetization state within magnetic components is presented. The occurring inverse magnetostatic problem is solved by means of an adjoint approach, based on the Fredkin-Koehler method for the solution of the forward problem. Due to the use of hybrid FEM-BEM coupling combined with matrix compression techniques the resulting algorithm is well suited for large-scale problems. Furthermore the reconstruction of the magnetization state within a permanent magnet as well as an optimal design application are demonstrated. PMID:28098851
Solving Large-Scale Inverse Magnetostatic Problems using the Adjoint Method
NASA Astrophysics Data System (ADS)
Bruckner, Florian; Abert, Claas; Wautischer, Gregor; Huber, Christian; Vogler, Christoph; Hinze, Michael; Suess, Dieter
2017-01-01
An efficient algorithm for the reconstruction of the magnetization state within magnetic components is presented. The occurring inverse magnetostatic problem is solved by means of an adjoint approach, based on the Fredkin-Koehler method for the solution of the forward problem. Due to the use of hybrid FEM-BEM coupling combined with matrix compression techniques the resulting algorithm is well suited for large-scale problems. Furthermore the reconstruction of the magnetization state within a permanent magnet as well as an optimal design application are demonstrated.
NASA Astrophysics Data System (ADS)
Tong, Shaocheng; Xu, Yinyin; Li, Yongming
2015-06-01
This paper is concerned with the problem of adaptive fuzzy decentralised output-feedback control for a class of uncertain stochastic nonlinear pure-feedback large-scale systems with completely unknown functions, the mismatched interconnections and without requiring the states being available for controller design. With the help of fuzzy logic systems approximating the unknown nonlinear functions, a fuzzy state observer is designed estimating the unmeasured states. Therefore, the nonlinear filtered signals are incorporated into the backstepping recursive design, and an adaptive fuzzy decentralised output-feedback control scheme is developed. It is proved that the filter system converges to a small neighbourhood of the origin based on appropriate choice of the design parameters. Simulation studies are included illustrating the effectiveness of the proposed approach.
Lenormand, R.; Thiele, M.R.
1997-08-01
The paper describes the method and presents preliminary results for the calculation of homogenized relative permeabilities
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.
Three-Stage Tabu Search for Solving Large-Scale Flow Shop Scheduling Problems
NASA Astrophysics Data System (ADS)
Xu, Yuedong; Tian, Yajie; Sannomiya, Nobuo
Tabu search is a meta-heuristic approach designed skillfully for finding a suboptimal solution of combinatorial optimization problems. In this paper the tabu search with three stages is proposed for solving large-scale flow shop scheduling problems. In order to obtain a better suboptimal solution in a short computation time, three different candidate lists are used to determine the incumbent solution in the respective search stages. The candidate lists are constructed by restricting the moving of each job. Test problems with four kinds of job data are examined. Based on analyzing the relationship between the candidate list and the suboptimal solution for each job data, a common parameter is given to construct the candidate list during the search process. Comparison of the computation result is made with the genetic algorithm and the basic tabu search, from which it is shown that the proposed tabu search outperforms two others.
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
From Self-consistency to SOAR: Solving Large Scale NonlinearEigenvalue Problems
Bai, Zhaojun; Yang, Chao
2006-02-01
What is common among electronic structure calculation, design of MEMS devices, vibrational analysis of high speed railways, and simulation of the electromagnetic field of a particle accelerator? The answer: they all require solving large scale nonlinear eigenvalue problems. In fact, these are just a handful of examples in which solving nonlinear eigenvalue problems accurately and efficiently is becoming increasingly important. Recognizing the importance of this class of problems, an invited minisymposium dedicated to nonlinear eigenvalue problems was held at the 2005 SIAM Annual Meeting. The purpose of the minisymposium was to bring together numerical analysts and application scientists to showcase some of the cutting edge results from both communities and to discuss the challenges they are still facing. The minisymposium consisted of eight talks divided into two sessions. The first three talks focused on a type of nonlinear eigenvalue problem arising from electronic structure calculations. In this type of problem, the matrix Hamiltonian H depends, in a non-trivial way, on the set of eigenvectors X to be computed. The invariant subspace spanned by these eigenvectors also minimizes a total energy function that is highly nonlinear with respect to X on a manifold defined by a set of orthonormality constraints. In other applications, the nonlinearity of the matrix eigenvalue problem is restricted to the dependency of the matrix on the eigenvalues to be computed. These problems are often called polynomial or rational eigenvalue problems In the second session, Christian Mehl from Technical University of Berlin described numerical techniques for solving a special type of polynomial eigenvalue problem arising from vibration analysis of rail tracks excited by high-speed trains.
A large-scale stochastic spatiotemporal model for Aedes albopictus-borne chikungunya epidemiology
Chandra, Nastassya L.; Proestos, Yiannis; Lelieveld, Jos; Christophides, George K.; Parham, Paul E.
2017-01-01
Chikungunya is a viral disease transmitted to humans primarily via the bites of infected Aedes mosquitoes. The virus caused a major epidemic in the Indian Ocean in 2004, affecting millions of inhabitants, while cases have also been observed in Europe since 2007. We developed a stochastic spatiotemporal model of Aedes albopictus-borne chikungunya transmission based on our recently developed environmentally-driven vector population dynamics model. We designed an integrated modelling framework incorporating large-scale gridded climate datasets to investigate disease outbreaks on Reunion Island and in Italy. We performed Bayesian parameter inference on the surveillance data, and investigated the validity and applicability of the underlying biological assumptions. The model successfully represents the outbreak and measures of containment in Italy, suggesting wider applicability in Europe. In its current configuration, the model implies two different viral strains, thus two different outbreaks, for the two-stage Reunion Island epidemic. Characterisation of the posterior distributions indicates a possible relationship between the second larger outbreak on Reunion Island and the Italian outbreak. The model suggests that vector control measures, with different modes of operation, are most effective when applied in combination: adult vector intervention has a high impact but is short-lived, larval intervention has a low impact but is long-lasting, and quarantining infected territories, if applied strictly, is effective in preventing large epidemics. We present a novel approach in analysing chikungunya outbreaks globally using a single environmentally-driven mathematical model. Our study represents a significant step towards developing a globally applicable Ae. albopictus-borne chikungunya transmission model, and introduces a guideline for extending such models to other vector-borne diseases. PMID:28362820
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.
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…
NASA Astrophysics Data System (ADS)
Xiao, Jinyou; Zhou, Hang; Zhang, Chuanzeng; Xu, Chao
2017-02-01
This paper focuses on the development and engineering applications of a new resolvent sampling based Rayleigh-Ritz method (RSRR) for solving large-scale nonlinear eigenvalue problems (NEPs) in finite element analysis. There are three contributions. First, to generate reliable eigenspaces the resolvent sampling scheme is derived from Keldysh's theorem for holomorphic matrix functions following a more concise and insightful algebraic framework. Second, based on the new derivation a two-stage solution strategy is proposed for solving large-scale NEPs, which can greatly enhance the computational cost and accuracy of the RSRR. The effects of the user-defined parameters are studied, which provides a useful guide for real applications. Finally, the RSRR and the two-stage scheme is applied to solve two NEPs in the FE analysis of viscoelastic damping structures with up to 1 million degrees of freedom. The method is versatile, robust and suitable for parallelization, and can be easily implemented into other packages.
NASA Astrophysics Data System (ADS)
Xiao, Jinyou; Zhou, Hang; Zhang, Chuanzeng; Xu, Chao
2016-11-01
This paper focuses on the development and engineering applications of a new resolvent sampling based Rayleigh-Ritz method (RSRR) for solving large-scale nonlinear eigenvalue problems (NEPs) in finite element analysis. There are three contributions. First, to generate reliable eigenspaces the resolvent sampling scheme is derived from Keldysh's theorem for holomorphic matrix functions following a more concise and insightful algebraic framework. Second, based on the new derivation a two-stage solution strategy is proposed for solving large-scale NEPs, which can greatly enhance the computational cost and accuracy of the RSRR. The effects of the user-defined parameters are studied, which provides a useful guide for real applications. Finally, the RSRR and the two-stage scheme is applied to solve two NEPs in the FE analysis of viscoelastic damping structures with up to 1 million degrees of freedom. The method is versatile, robust and suitable for parallelization, and can be easily implemented into other packages.
Minimizing the stochasticity of halos in large-scale structure surveys
Hamaus, Nico; Desjacques, Vincent; Smith, Robert E.; Baldauf, Tobias; Seljak, Uros
2010-08-15
In recent work (Seljak, Hamaus, and Desjacques 2009) it was found that weighting central halo galaxies by halo mass can significantly suppress their stochasticity relative to the dark matter, well below the Poisson model expectation. This is useful for constraining relations between galaxies and the dark matter, such as the galaxy bias, especially in situations where sampling variance errors can be eliminated. In this paper we extend this study with the goal of finding the optimal mass-dependent halo weighting. We use N-body simulations to perform a general analysis of halo stochasticity and its dependence on halo mass. We investigate the stochasticity matrix, defined as C{sub ij{identical_to}}<({delta}{sub i}-b{sub i{delta}m})({delta}{sub j}-b{sub j{delta}m})>, where {delta}{sub m} is the dark matter overdensity in Fourier space, {delta}{sub i} the halo overdensity of the i-th halo mass bin, and b{sub i} the corresponding halo bias. In contrast to the Poisson model predictions we detect nonvanishing correlations between different mass bins. We also find the diagonal terms to be sub-Poissonian for the highest-mass halos. The diagonalization of this matrix results in one large and one low eigenvalue, with the remaining eigenvalues close to the Poisson prediction 1/n, where n is the mean halo number density. The eigenmode with the lowest eigenvalue contains most of the information and the corresponding eigenvector provides an optimal weighting function to minimize the stochasticity between halos and dark matter. We find this optimal weighting function to match linear mass weighting at high masses, while at the low-mass end the weights approach a constant whose value depends on the low-mass cut in the halo mass function. This weighting further suppresses the stochasticity as compared to the previously explored mass weighting. Finally, we employ the halo model to derive the stochasticity matrix and the scale-dependent bias from an analytical perspective. It is
Solving stochastic inflation for arbitrary potentials
Martin, Jerome; Musso, Marcello
2006-02-15
A perturbative method for solving the Langevin equation of inflationary cosmology in the presence of backreaction is presented. In the Gaussian approximation, the method permits an explicit calculation of the probability distribution of the inflaton field for an arbitrary potential, with or without the volume effects taken into account. The perturbative method is then applied to various concrete models, namely, large field, small field, hybrid, and running mass inflation. New results on the stochastic behavior of the inflaton field in those models are obtained. In particular, it is confirmed that the stochastic effects can be important in new inflation while it is demonstrated they are negligible in (vacuum dominated) hybrid inflation. The case of stochastic running mass inflation is discussed in some details and it is argued that quantum effects blur the distinction between the four classical versions of this model. It is also shown that the self-reproducing regime is likely to be important in this case.
Large-Scale Control and Distributed Computing Systems under Stochastic Structural Perturbations
1993-01-28
Stability of Lotka - Volterra Model Authors: G. S. Ladde and S. Sathananthan Journal: Mathematics and Computer Modelling, Vol. 16, No. 3, pp. 99-107, 1992. ...SUBTITLE LagScl oto n itiue . FUNDING NUMBERS Computing Systems Under Stochastic Structural Perturbatio •s 6. AUTHOR(S) 1. Dr. S. Sathananthan 98AL03...non- hereditary control and distributed systems under randomly varying structural pertur- bations. Three principal areas of research, namely, (i
A data-scalable randomized misfit approach for solving large-scale PDE-constrained inverse problems
NASA Astrophysics Data System (ADS)
Le, E. B.; Myers, A.; Bui-Thanh, T.; Nguyen, Q. P.
2017-06-01
A randomized misfit approach is presented for the efficient solution of large-scale PDE-constrained inverse problems with high-dimensional data. The purpose of this paper is to offer a theory-based framework for random projections in this inverse problem setting. The stochastic approximation to the misfit is analyzed using random projection theory. By expanding beyond mean estimator convergence, a practical characterization of randomized misfit convergence can be achieved. The theoretical results developed hold with any valid random projection in the literature. The class of feasible distributions is broad yet simple to characterize compared to previous stochastic misfit methods. This class includes very sparse random projections which provide additional computational benefit. A different proof for a variant of the Johnson-Lindenstrauss lemma is also provided. This leads to a different intuition for the { O}(\\varepsilon-2) factor in bounds for Johnson-Lindenstrauss results. The main contribution of this paper is a theoretical result showing the method guarantees a valid solution for small reduced misfit dimensions. The interplay between Johnson-Lindenstrauss theory and Morozov’s discrepancy principle is shown to be essential to the result. The computational cost savings for large-scale PDE-constrained problems with high-dimensional data is discussed. Numerical verification of the developed theory is presented for model problems of estimating a distributed parameter in an elliptic partial differential equation. Results with different random projections are presented to demonstrate the viability and accuracy of the proposed approach.
On stochastic control system design methods for weakly coupled large scale linear systems.
NASA Technical Reports Server (NTRS)
Kwong, R.; Chong, C.-Y.; Athans, M.
1972-01-01
This paper considers the problem of decentralized control of two weakly coupled linear stochastic systems, using quadratic performance indices. The basic idea is to have each controller control independently his own system, based upon noisy measurements of his own output. To compensate for the effects of weak coupling upon the resultant performance, fake white plant noise is introduced to each system. The appropriate intensity of the fake plant noise is obtained through the solution of an off-line deterministic matrix optimal control problem. The effects of this design method upon the overall coupled system performance are analyzed as a function of the degree of intersystem coupling.
Chen, Weiliang; De Schutter, Erik
2017-01-01
Stochastic, spatial reaction-diffusion simulations have been widely used in systems biology and computational neuroscience. However, the increasing scale and complexity of models and morphologies have exceeded the capacity of any serial implementation. This led to the development of parallel solutions that benefit from the boost in performance of modern supercomputers. In this paper, we describe an MPI-based, parallel operator-splitting implementation for stochastic spatial reaction-diffusion simulations with irregular tetrahedral meshes. The performance of our implementation is first examined and analyzed with simulations of a simple model. We then demonstrate its application to real-world research by simulating the reaction-diffusion components of a published calcium burst model in both Purkinje neuron sub-branch and full dendrite morphologies. Simulation results indicate that our implementation is capable of achieving super-linear speedup for balanced loading simulations with reasonable molecule density and mesh quality. In the best scenario, a parallel simulation with 2,000 processes runs more than 3,600 times faster than its serial SSA counterpart, and achieves more than 20-fold speedup relative to parallel simulation with 100 processes. In a more realistic scenario with dynamic calcium influx and data recording, the parallel simulation with 1,000 processes and no load balancing is still 500 times faster than the conventional serial SSA simulation. PMID:28239346
Chen, Weiliang; De Schutter, Erik
2017-01-01
Stochastic, spatial reaction-diffusion simulations have been widely used in systems biology and computational neuroscience. However, the increasing scale and complexity of models and morphologies have exceeded the capacity of any serial implementation. This led to the development of parallel solutions that benefit from the boost in performance of modern supercomputers. In this paper, we describe an MPI-based, parallel operator-splitting implementation for stochastic spatial reaction-diffusion simulations with irregular tetrahedral meshes. The performance of our implementation is first examined and analyzed with simulations of a simple model. We then demonstrate its application to real-world research by simulating the reaction-diffusion components of a published calcium burst model in both Purkinje neuron sub-branch and full dendrite morphologies. Simulation results indicate that our implementation is capable of achieving super-linear speedup for balanced loading simulations with reasonable molecule density and mesh quality. In the best scenario, a parallel simulation with 2,000 processes runs more than 3,600 times faster than its serial SSA counterpart, and achieves more than 20-fold speedup relative to parallel simulation with 100 processes. In a more realistic scenario with dynamic calcium influx and data recording, the parallel simulation with 1,000 processes and no load balancing is still 500 times faster than the conventional serial SSA simulation.
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.
Milovanov, A V
2001-04-01
The formulation of the fractional Fokker-Planck-Kolmogorov (FPK) equation [Physica D 76, 110 (1994)] has led to important advances in the description of the stochastic dynamics of Hamiltonian systems. Here, the long-time behavior of the basic transport processes obeying the fractional FPK equation is analyzed. A derivation of the large-scale turbulent transport coefficient for a Hamiltonian system with 11 / 2 degrees of freedom is proposed in connection with the fractal structure of the particle chaotic trajectories. The principal transport regimes (i.e., a diffusion-type process, ballistic motion, subdiffusion in the limit of the frozen Hamiltonian, and behavior associated with self-organized criticality) are obtained as partial cases of the generalized transport law. A comparison with recent numerical and experimental studies is given.
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)
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 man-induced large-scale conservation problems: the Spanish imperial eagle and power lines.
López-López, Pascual; Ferrer, Miguel; Madero, Agustín; Casado, Eva; McGrady, Michael
2011-03-02
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. 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 electricuted birds has been reduced in spite of the continuous growing of the wiring network. 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 species.
NASA Astrophysics Data System (ADS)
Gandolfo, Daniel; Rodriguez, Roger; Tuckwell, Henry C.
2017-03-01
We investigate the dynamics of large-scale interacting neural populations, composed of conductance based, spiking model neurons with modifiable synaptic connection strengths, which are possibly also subjected to external noisy currents. The network dynamics is controlled by a set of neural population probability distributions (PPD) which are constructed along the same lines as in the Klimontovich approach to the kinetic theory of plasmas. An exact non-closed, nonlinear, system of integro-partial differential equations is derived for the PPDs. As is customary, a closing procedure leads to a mean field limit. The equations we have obtained are of the same type as those which have been recently derived using rigorous techniques of probability theory. The numerical solutions of these so called McKean-Vlasov-Fokker-Planck equations, which are only valid in the limit of infinite size networks, actually shows that the statistical measures as obtained from PPDs are in good agreement with those obtained through direct integration of the stochastic dynamical system for large but finite size networks. Although numerical solutions have been obtained for networks of Fitzhugh-Nagumo model neurons, which are often used to approximate Hodgkin-Huxley model neurons, the theory can be readily applied to networks of general conductance-based model neurons of arbitrary dimension.
NASA Astrophysics Data System (ADS)
Gandolfo, Daniel; Rodriguez, Roger; Tuckwell, Henry C.
2017-01-01
We investigate the dynamics of large-scale interacting neural populations, composed of conductance based, spiking model neurons with modifiable synaptic connection strengths, which are possibly also subjected to external noisy currents. The network dynamics is controlled by a set of neural population probability distributions (PPD) which are constructed along the same lines as in the Klimontovich approach to the kinetic theory of plasmas. An exact non-closed, nonlinear, system of integro-partial differential equations is derived for the PPDs. As is customary, a closing procedure leads to a mean field limit. The equations we have obtained are of the same type as those which have been recently derived using rigorous techniques of probability theory. The numerical solutions of these so called McKean-Vlasov-Fokker-Planck equations, which are only valid in the limit of infinite size networks, actually shows that the statistical measures as obtained from PPDs are in good agreement with those obtained through direct integration of the stochastic dynamical system for large but finite size networks. Although numerical solutions have been obtained for networks of Fitzhugh-Nagumo model neurons, which are often used to approximate Hodgkin-Huxley model neurons, the theory can be readily applied to networks of general conductance-based model neurons of arbitrary dimension.
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.
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. PMID:26801020
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.
López-Marqués, Rosa L; Pérez-Castiñeira, José R; Buch-Pedersen, Morten J; Marco, Sergio; Rigaud, Jean-Louis; Palmgren, Michael G; Serrano, Aurelio
2005-10-01
Although several proton-pumping pyrophosphatases (H+-PPases) have been overexpressed in heterologous systems, purification of these recombinant integral membrane proteins in large amounts in order to study their structure-function relationships has proven to be a very difficult task. In this study we report a new method for large-scale production of pure and stable thermophilic H+-PPase from Thermotoga maritima. Following overexpression in yeast, a "Hot-Solve" procedure based on high-temperature solubilization and metal-affinity chromatography was used to obtain a highly purified detergent-solubilized TVP fraction with a yield around 1.5 mg of protein per litre of yeast culture. Electron microscopy showed the monodispersity of the purified protein and single particle analysis provided the first direct evidence of a dimeric structure for H+-PPases. We propose that the method developed could be useful for large-scale purification of other recombinant thermophilic membrane proteins.
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…
Oliveira, Rodrigo F.; Terrin, Anna; Di Benedetto, Giulietta; Cannon, Robert C.; Koh, Wonryull; Kim, MyungSook; Zaccolo, Manuela; Blackwell, Kim T.
2010-01-01
Cyclic AMP (cAMP) and its main effector Protein Kinase A (PKA) are critical for several aspects of neuronal function including synaptic plasticity. Specificity of synaptic plasticity requires that cAMP activates PKA in a highly localized manner despite the speed with which cAMP diffuses. Two mechanisms have been proposed to produce localized elevations in cAMP, known as microdomains: impeded diffusion, and high phosphodiesterase (PDE) activity. This paper investigates the mechanism of localized cAMP signaling using a computational model of the biochemical network in the HEK293 cell, which is a subset of pathways involved in PKA-dependent synaptic plasticity. This biochemical network includes cAMP production, PKA activation, and cAMP degradation by PDE activity. The model is implemented in NeuroRD: novel, computationally efficient, stochastic reaction-diffusion software, and is constrained by intracellular cAMP dynamics that were determined experimentally by real-time imaging using an Epac-based FRET sensor (H30). The model reproduces the high concentration cAMP microdomain in the submembrane region, distinct from the lower concentration of cAMP in the cytosol. Simulations further demonstrate that generation of the cAMP microdomain requires a pool of PDE4D anchored in the cytosol and also requires PKA-mediated phosphorylation of PDE4D which increases its activity. The microdomain does not require impeded diffusion of cAMP, confirming that barriers are not required for microdomains. The simulations reported here further demonstrate the utility of the new stochastic reaction-diffusion algorithm for exploring signaling pathways in spatially complex structures such as neurons. PMID:20661441
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 .
NASA Astrophysics Data System (ADS)
Mohamed, Nur Syarafina; Mamat, Mustafa; Rivaie, Mohd
2016-11-01
Conjugate gradient (CG) methods are one of the tools in optimization. Due to its low computational memory requirement, this method is used in solving several of nonlinear unconstrained optimization problems from designs, economics, physics and engineering. In this paper, a new modification of CG family coefficient (βk) is proposed and posses global convergence under exact line search direction. Numerical experimental results based on the number of iterations and central processing unit (CPU) time show that the new βk performs better than some other well known CG methods under some standard test functions.
NASA Astrophysics Data System (ADS)
Lin, Lin; Chen, Mohan; E, Weinan; He, Lixin; Lu, Jianfeng; Yang, Chao; Ying, Lexing
2013-03-01
The standard diagonalization based method for solving Kohn-Sham density functional theory (KSDFT) requires N eigenvectors for an O(N) * O(N) Kohn-Sham Hamiltonian matrix, with N being the number of electrons in the system. The computational cost for such procedure is expensive and scales as O(N3). We have developed a novel pole expansion plus selected inversion (PEXSI) method, in which KSDFT is solved by evaluating the selected elements of the inverse of a series of sparse symmetric matrices, and the overall algorithm scales at most O(N2) for all materials including metallic and insulating systems without any truncation. The PEXSI method can be used with orthogonal or nonorthogonal basis set, and the electron density, total energy, Helmholtz free energy and atomic force are calculated simultaneously and accurately without using the eigenvalues and eigenvectors. Combined with atomic orbital basis functions, the PEXSI method can be applied to study the electronic structure of boron nitride nanotube and carbon nanotube with more than 10,000 atoms on a single processor. U.S. Department of Energy DE-AC02-05CH11231
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.
Hu, Yuanan; Cheng, Hefa
2013-04-16
As heavy metals occur naturally in soils at measurable concentrations and their natural background contents have significant spatial variations, identification and apportionment of heavy metal pollution sources across large-scale regions is a challenging task. Stochastic models, including the recently developed conditional inference tree (CIT) and the finite mixture distribution model (FMDM), were applied to identify the sources of heavy metals found in the surface soils of the Pearl River Delta, China, and to apportion the contributions from natural background and human activities. Regression trees were successfully developed for the concentrations of Cd, Cu, Zn, Pb, Cr, Ni, As, and Hg in 227 soil samples from a region of over 7.2 × 10(4) km(2) based on seven specific predictors relevant to the source and behavior of heavy metals: land use, soil type, soil organic carbon content, population density, gross domestic product per capita, and the lengths and classes of the roads surrounding the sampling sites. The CIT and FMDM results consistently indicate that Cd, Zn, Cu, Pb, and Cr in the surface soils of the PRD were contributed largely by anthropogenic sources, whereas As, Ni, and Hg in the surface soils mostly originated from the soil parent materials.
Large Scale Nonlinear Programming.
1978-06-15
KEY WORDS (Conhinu. as, t.n.t.. aid. if nic••iary aid ld.ntify by block n,a,b.r) L. In,~~~ IP!CIE LARGE SCALE OPTIMIZATION APPLICATIONS OF NONLINEAR ... NONLINEAR PROGRAMMING by Garth P. McCormick 1. Introduction The general mathematical programming ( optimization ) problem can be stated in the following form...because the difficulty in solving a general nonlinear optimization problem has a~ much to do with the nature of the functions involved as it does with the
NASA Astrophysics Data System (ADS)
Browell, E. V.; Fenn, M. A.; Grant, W. B.; Avery, M. A.; Neuber, R.; McGee, T. J.; Trepte, C. R.; Butler, C. F.; Kooi, S. A.; Notari, A.; Hair, J. W.; Lait, L. R.
2003-12-01
Ozone cross sections were obtained from near the surface to above 30 km along the ground track of the NASA DC-8 on long-range flights across the Arctic during the 2003 SAGE-III (Stratospheric Aerosol and Gas Experiment) Ozone Loss and Validation Experiment (SOLVE-2). Extensive regions of lower than expected ozone were found inside the polar vortex below about 22 km at the start of the mission (January 9, 2003), and by the end of mission (February 12, 2003) ozone had decreased to less than 2.0 ppm in localized regions inside the vortex at about 19 km. These regions of particularly low ozone were associated with air masses that had seen extended periods of sunlight. Extensive structure was observed in the ozone field near the edge of the vortex on many flights, and on occasion, large filaments of extra-vortex air were observed inside the vortex. When the vortex divided into two separate vortices, the ozone field reflected the separation with extra-vortex air in between. The nadir ozone data showed strong evidence of downward transport in vicinity of jet streams, and these intrusions were observed to extend down to below 4 km in some cases. Directly under the vortex, large-scale descent of stratospheric air produced ozone levels exceeding 100 ppbv down to 5 km. This is the first time the entire ozone cross section was obtained during an airborne field experiment, and it will provide important new information on atmospheric dynamics and ozone chemistry in the Arctic. This experiment also provided a unique opportunity to compare ozone measurements from several different remote and in situ instruments. Ozone profiles were measured above and below the DC-8 with the airborne UV Differential Absorption Lidar (DIAL) system, and the Airborne Raman Ozone, Temperature, and Aerosol Lidar (AROTAL) measured ozone profiles above the aircraft. In situ ozone measurements were made at the DC-8 flight level, and ground-based lidar and ozonesonde measurements were made from Ny
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.
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.
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.
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.
2008-03-01
solve the problem of likelihood maximization. It is shown that maximizing likelihood under a certain dis- tribution corresponds to minimizing distance ...multinomial distribution and exponential distrib- ution correspond to Euclidean distance , logistic loss, KL- divergence and Itakura-Satio distance ...Given a graph G = (V, E , A) where A ∈ Rn×n, a distance function D, and a positive integer k, the optimized partitioning is given by the minimization
Large scale scientific computing
Deuflhard, P. ); Engquist, B. )
1987-01-01
This book presents papers on large scale scientific computing. It includes: Initial value problems of ODE's and parabolic PDE's; Boundary value problems of ODE's and elliptic PDE's; Hyperbolic PDE's; Inverse problems; Optimization and optimal control problems; and Algorithm adaptation on supercomputers.
Solving Parker's transport equation with stochastic differential equations on GPUs
NASA Astrophysics Data System (ADS)
Dunzlaff, P.; Strauss, R. D.; Potgieter, M. S.
2015-07-01
The numerical solution of transport equations for energetic charged particles in space is generally very costly in terms of time. Besides the use of multi-core CPUs and computer clusters in order to decrease the computation times, high performance calculations on graphics processing units (GPUs) have become available during the last years. In this work we introduce and describe a GPU-accelerated implementation of Parker's equation using Stochastic Differential Equations (SDEs) for the simulation of the transport of energetic charged particles with the CUDA toolkit, which is the focus of this work. We briefly discuss the set of SDEs arising from Parker's transport equation and their application to boundary value problems such as that of the Jovian magnetosphere. We compare the runtimes of the GPU code with a CPU version of the same algorithm. Compared to the CPU implementation (using OpenMP and eight threads) we find a performance increase of about a factor of 10-60, depending on the assumed set of parameters. Furthermore, we benchmark our simulation using the results of an existing SDE implementation of Parker's transport equation.
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
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)
Gad-El-Hak, Mohamed
"Extreme" events - including climatic events, such as hurricanes, tornadoes, and drought - can cause massive disruption to society, including large death tolls and property damage in the billions of dollars. Events in recent years have shown the importance of being prepared and that countries need to work together to help alleviate the resulting pain and suffering. This volume presents a review of the broad research field of large-scale disasters. It establishes a common framework for predicting, controlling and managing both manmade and natural disasters. There is a particular focus on events caused by weather and climate change. Other topics include air pollution, tsunamis, disaster modeling, the use of remote sensing and the logistics of disaster management. It will appeal to scientists, engineers, first responders and health-care professionals, in addition to graduate students and researchers who have an interest in the prediction, prevention or mitigation of large-scale disasters.
A method for solving stochastic equations by reduced order models and local approximations
Grigoriu, M.
2012-08-01
A method is proposed for solving equations with random entries, referred to as stochastic equations (SEs). The method is based on two recent developments. The first approximates the response surface giving the solution of a stochastic equation as a function of its random parameters by a finite set of hyperplanes tangent to it at expansion points selected by geometrical arguments. The second approximates the vector of random parameters in the definition of a stochastic equation by a simple random vector, referred to as stochastic reduced order model (SROM), and uses it to construct a SROM for the solution of this equation. The proposed method is a direct extension of these two methods. It uses SROMs to select expansion points, rather than selecting these points by geometrical considerations, and represents the solution by linear and/or higher order local approximations. The implementation and the performance of the method are illustrated by numerical examples involving random eigenvalue problems and stochastic algebraic/differential equations. The method is conceptually simple, non-intrusive, efficient relative to classical Monte Carlo simulation, accurate, and guaranteed to converge to the exact solution.
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.
Large scale traffic simulations
Nagel, K.; Barrett, C.L. |; Rickert, M. |
1997-04-01
Large scale microscopic (i.e. vehicle-based) traffic simulations pose high demands on computational speed in at least two application areas: (i) real-time traffic forecasting, and (ii) long-term planning applications (where repeated {open_quotes}looping{close_quotes} between the microsimulation and the simulated planning of individual person`s behavior is necessary). As a rough number, a real-time simulation of an area such as Los Angeles (ca. 1 million travellers) will need a computational speed of much higher than 1 million {open_quotes}particle{close_quotes} (= vehicle) updates per second. This paper reviews how this problem is approached in different projects and how these approaches are dependent both on the specific questions and on the prospective user community. The approaches reach from highly parallel and vectorizable, single-bit implementations on parallel supercomputers for Statistical Physics questions, via more realistic implementations on coupled workstations, to more complicated driving dynamics implemented again on parallel supercomputers. 45 refs., 9 figs., 1 tab.
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.
NASA Astrophysics Data System (ADS)
Miller, J. A.; Piscicelli, M.
2005-12-01
The momentum diffusion or Fokker-Planck operator describes, at least approximately, the evolution of a distribution of particles interacting with a collection of scattering centers. The interactions can range from Coulomb collisions with particles of the same or another species, to resonant interactions with linear plasma waves, to nonresonant collisions with randomly-moving large-scale (compared to the particle gyroradius) magnetic inhomogeneities. Consequently, this operator is a common feature in descriptions of particle transport and stochastic acceleration by electromagnetic turbulence in a wide variety of astrophysical and space plasma situations. An analytical solution of a kinetic equation involving this operator is intractable in practical instances, and hence numerical solutions must be employed. We demonstrate how to transform the kinetic equation into an equivalent system of Stratonovich Stochastic Differential Equations, and present a high-order adaptive Runge-Kutta algorithm for their solution. This technique can provide accurate solutions of a kinetic equation over long timescales, and is easily adapted to take into account nonstochastic processes. This work was supported by NASA grant NAG5-12794
Challenges for Large Scale Simulations
NASA Astrophysics Data System (ADS)
Troyer, Matthias
2010-03-01
With computational approaches becoming ubiquitous the growing impact of large scale computing on research influences both theoretical and experimental work. I will review a few examples in condensed matter physics and quantum optics, including the impact of computer simulations in the search for supersolidity, thermometry in ultracold quantum gases, and the challenging search for novel phases in strongly correlated electron systems. While only a decade ago such simulations needed the fastest supercomputers, many simulations can now be performed on small workstation clusters or even a laptop: what was previously restricted to a few experts can now potentially be used by many. Only part of the gain in computational capabilities is due to Moore's law and improvement in hardware. Equally impressive is the performance gain due to new algorithms - as I will illustrate using some recently developed algorithms. At the same time modern peta-scale supercomputers offer unprecedented computational power and allow us to tackle new problems and address questions that were impossible to solve numerically only a few years ago. While there is a roadmap for future hardware developments to exascale and beyond, the main challenges are on the algorithmic and software infrastructure side. Among the problems that face the computational physicist are: the development of new algorithms that scale to thousands of cores and beyond, a software infrastructure that lifts code development to a higher level and speeds up the development of new simulation programs for large scale computing machines, tools to analyze the large volume of data obtained from such simulations, and as an emerging field provenance-aware software that aims for reproducibility of the complete computational workflow from model parameters to the final figures. Interdisciplinary collaborations and collective efforts will be required, in contrast to the cottage-industry culture currently present in many areas of computational
Research on unit commitment with large-scale wind power connected power system
NASA Astrophysics Data System (ADS)
Jiao, Ran; Zhang, Baoqun; Chi, Zhongjun; Gong, Cheng; Ma, Longfei; Yang, Bing
2017-01-01
Large-scale integration of wind power generators into power grid brings severe challenges to power system economic dispatch due to its stochastic volatility. Unit commitment including wind farm is analyzed from the two parts of modeling and solving methods. The structures and characteristics can be summarized after classification has been done according to different objective function and constraints. Finally, the issues to be solved and possible directions of research and development in the future are discussed, which can adapt to the requirements of the electricity market, energy-saving power generation dispatching and smart grid, even providing reference for research and practice of researchers and workers in this field.
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.
GPELab, a Matlab toolbox to solve Gross-Pitaevskii equations II: Dynamics and stochastic simulations
NASA Astrophysics Data System (ADS)
Antoine, Xavier; Duboscq, Romain
2015-08-01
GPELab is a free Matlab toolbox for modeling and numerically solving large classes of systems of Gross-Pitaevskii equations that arise in the physics of Bose-Einstein condensates. The aim of this second paper, which follows (Antoine and Duboscq, 2014), is to first present the various pseudospectral schemes available in GPELab for computing the deterministic and stochastic nonlinear dynamics of Gross-Pitaevskii equations (Antoine, et al., 2013). Next, the corresponding GPELab functions are explained in detail. Finally, some numerical examples are provided to show how the code works for the complex dynamics of BEC problems.
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.
Solving multistage stochastic programming models of portfolio selection with outstanding liabilities
Edirisinghe, C.
1994-12-31
Models for portfolio selection in the presence of an outstanding liability have received significant attention, for example, models for pricing options. The problem may be described briefly as follows: given a set of risky securities (and a riskless security such as a bond), and given a set of cash flows, i.e., outstanding liability, to be met at some future date, determine an initial portfolio and a dynamic trading strategy for the underlying securities such that the initial cost of the portfolio is within a prescribed wealth level and the expected cash surpluses arising from trading is maximized. While the trading strategy should be self-financing, there may also be other restrictions such as leverage and short-sale constraints. Usually the treatment is limited to binomial evolution of uncertainty (of stock price), with possible extensions for developing computational bounds for multinomial generalizations. Posing as stochastic programming models of decision making, we investigate alternative efficient solution procedures under continuous evolution of uncertainty, for discrete time economies. We point out an important moment problem arising in the portfolio selection problem, the solution (or bounds) on which provides the basis for developing efficient computational algorithms. While the underlying stochastic program may be computationally tedious even for a modest number of trading opportunities (i.e., time periods), the derived algorithms may used to solve problems whose sizes are beyond those considered within stochastic optimization.
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.
Kadam, Shantanu; Vanka, Kumar
2013-02-15
Methods based on the stochastic formulation of chemical kinetics have the potential to accurately reproduce the dynamical behavior of various biochemical systems of interest. However, the computational expense makes them impractical for the study of real systems. Attempts to render these methods practical have led to the development of accelerated methods, where the reaction numbers are modeled by Poisson random numbers. However, for certain systems, such methods give rise to physically unrealistic negative numbers for species populations. The methods which make use of binomial variables, in place of Poisson random numbers, have since become popular, and have been partially successful in addressing this problem. In this manuscript, the development of two new computational methods, based on the representative reaction approach (RRA), has been discussed. The new methods endeavor to solve the problem of negative numbers, by making use of tools like the stochastic simulation algorithm and the binomial method, in conjunction with the RRA. It is found that these newly developed methods perform better than other binomial methods used for stochastic simulations, in resolving the problem of negative populations.
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.
Large-scale structural optimization
NASA Technical Reports Server (NTRS)
Sobieszczanski-Sobieski, J.
1983-01-01
Problems encountered by aerospace designers in attempting to optimize whole aircraft are discussed, along with possible solutions. Large scale optimization, as opposed to component-by-component optimization, is hindered by computational costs, software inflexibility, concentration on a single, rather than trade-off, design methodology and the incompatibility of large-scale optimization with single program, single computer methods. The software problem can be approached by placing the full analysis outside of the optimization loop. Full analysis is then performed only periodically. Problem-dependent software can be removed from the generic code using a systems programming technique, and then embody the definitions of design variables, objective function and design constraints. Trade-off algorithms can be used at the design points to obtain quantitative answers. Finally, decomposing the large-scale problem into independent subproblems allows systematic optimization of the problems by an organization of people and machines.
Large-scale circuit simulation
NASA Astrophysics Data System (ADS)
Wei, Y. P.
1982-12-01
The simulation of VLSI (Very Large Scale Integration) circuits falls beyond the capabilities of conventional circuit simulators like SPICE. On the other hand, conventional logic simulators can only give the results of logic levels 1 and 0 with the attendent loss of detail in the waveforms. The aim of developing large-scale circuit simulation is to bridge the gap between conventional circuit simulation and logic simulation. This research is to investigate new approaches for fast and relatively accurate time-domain simulation of MOS (Metal Oxide Semiconductors), LSI (Large Scale Integration) and VLSI circuits. New techniques and new algorithms are studied in the following areas: (1) analysis sequencing (2) nonlinear iteration (3) modified Gauss-Seidel method (4) latency criteria and timestep control scheme. The developed methods have been implemented into a simulation program PREMOS which could be used as a design verification tool for MOS circuits.
NASA Astrophysics Data System (ADS)
Vishniac, Ethan T.
2015-01-01
We show that a differentially rotating conducting fluid automatically creates a magnetic helicity flux with components along the rotation axis and in the direction of the local vorticity. This drives a rapid growth in the local density of current helicity, which in turn drives a large scale dynamo. The dynamo growth rate derived from this process is not constant, but depends inversely on the large scale magnetic field strength. This dynamo saturates when buoyant losses of magnetic flux compete with the large scale dynamo, providing a simple prediction for magnetic field strength as a function of Rossby number in stars. Increasing anisotropy in the turbulence produces a decreasing magnetic helicity flux, which explains the flattening of the B/Rossby number relation at low Rossby numbers. We also show that the kinetic helicity is always a subdominant effect. There is no kinematic dynamo in real stars.
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.
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
1993-01-01
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. PMID:11607400
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.
Large-scale autostereoscopic outdoor display
NASA Astrophysics Data System (ADS)
Reitterer, Jörg; Fidler, Franz; Saint Julien-Wallsee, Ferdinand; Schmid, Gerhard; Gartner, Wolfgang; Leeb, Walter; Schmid, Ulrich
2013-03-01
State-of-the-art autostereoscopic displays are often limited in size, effective brightness, number of 3D viewing zones, and maximum 3D viewing distances, all of which are mandatory requirements for large-scale outdoor displays. Conventional autostereoscopic indoor concepts like lenticular lenses or parallax barriers cannot simply be adapted for these screens due to the inherent loss of effective resolution and brightness, which would reduce both image quality and sunlight readability. We have developed a modular autostereoscopic multi-view laser display concept with sunlight readable effective brightness, theoretically up to several thousand 3D viewing zones, and maximum 3D viewing distances of up to 60 meters. For proof-of-concept purposes a prototype display with two pixels was realized. Due to various manufacturing tolerances each individual pixel has slightly different optical properties, and hence the 3D image quality of the display has to be calculated stochastically. In this paper we present the corresponding stochastic model, we evaluate the simulation and measurement results of the prototype display, and we calculate the achievable autostereoscopic image quality to be expected for our concept.
NASA Astrophysics Data System (ADS)
Cirpka, Olaf A.; Valocchi, Albert J.
2016-12-01
While stochastic subsurface hydrology has been tremendously successful in understanding how the spatial variability of hydraulic conductivity affects conservative solute transport in idealized settings, it has gained little impact in practice. This is the case because typical assumptions needed for the derivation of analytical expressions are too restrictive for practical applications and often geologically implausible, small-scale variation of hydraulic conductivity is by far not the only cause of uncertainty when considering the fate and remediation of pollutants, and the research community has not developed enough methods that can directly be used by practitioners. To overcome these shortcomings, we propose putting more emphasis on providing easy-to-use tools to generate realistic realizations of subsurface properties that are conditioned on all data measured at a site, extending the focus from hydraulic conductivity only to all parameters and processes relevant for reactive transport, making use of self-organizing principles of reactive transport to conceptually simplify the problem, and addressing conceptual uncertainty by stochastic methods.
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.
Cosmology with Large Scale Structure
NASA Astrophysics Data System (ADS)
Ho, Shirley; Cuesta, A.; Ross, A.; Seo, H.; DePutter, R.; Padmanabhan, N.; White, M.; Myers, A.; Bovy, J.; Blanton, M.; Hernandez, C.; Mena, O.; Percival, W.; Prada, F.; Ross, N. P.; Saito, S.; Schneider, D.; Skibba, R.; Smith, K.; Slosar, A.; Strauss, M.; Verde, L.; Weinberg, D.; Bachall, N.; Brinkmann, J.; da Costa, L. A.
2012-01-01
The Sloan Digital Sky Survey I-III surveyed 14,000 square degrees, and delivered over a trillion pixels of imaging data. I present cosmological results from this unprecedented data set which contains over a million galaxies distributed between redshift of 0.45 to 0.70. With such a large volume of data set, high precision cosmological constraints can be obtained given a careful control and understanding of observational systematics. I present a novel treatment of observational systematics and its application to the clustering signals from the data set. I will present cosmological constraints on dark components of the Universe and tightest constraints of the non-gaussianity of early Universe to date utilizing Large Scale Structure.
Large scale biomimetic membrane arrays.
Hansen, Jesper S; Perry, Mark; Vogel, Jörg; Groth, Jesper S; Vissing, Thomas; Larsen, Marianne S; Geschke, Oliver; Emneús, Jenny; Bohr, Henrik; Nielsen, Claus H
2009-10-01
To establish planar biomimetic membranes across large scale partition aperture arrays, we created a disposable single-use horizontal chamber design that supports combined optical-electrical measurements. Functional lipid bilayers could easily and efficiently be established across CO(2) laser micro-structured 8 x 8 aperture partition arrays with average aperture diameters of 301 +/- 5 microm. We addressed the electro-physical properties of the lipid bilayers established across the micro-structured scaffold arrays by controllable reconstitution of biotechnological and physiological relevant membrane peptides and proteins. Next, we tested the scalability of the biomimetic membrane design by establishing lipid bilayers in rectangular 24 x 24 and hexagonal 24 x 27 aperture arrays, respectively. The results presented show that the design is suitable for further developments of sensitive biosensor assays, and furthermore demonstrate that the design can conveniently be scaled up to support planar lipid bilayers in large square-centimeter partition arrays.
Angstmann, C.N.; Donnelly, I.C.; Henry, B.I.; Jacobs, B.A.; Langlands, T.A.M.; Nichols, J.A.
2016-02-15
We have introduced a new explicit numerical method, based on a discrete stochastic process, for solving a class of fractional partial differential equations that model reaction subdiffusion. The scheme is derived from the master equations for the evolution of the probability density of a sum of discrete time random walks. We show that the diffusion limit of the master equations recovers the fractional partial differential equation of interest. This limiting procedure guarantees the consistency of the numerical scheme. The positivity of the solution and stability results are simply obtained, provided that the underlying process is well posed. We also show that the method can be applied to standard reaction–diffusion equations. This work highlights the broader applicability of using discrete stochastic processes to provide numerical schemes for partial differential equations, including fractional partial differential equations.
Large-scale PACS implementation.
Carrino, J A; Unkel, P J; Miller, I D; Bowser, C L; Freckleton, M W; Johnson, T G
1998-08-01
The transition to filmless radiology is a much more formidable task than making the request for proposal to purchase a (Picture Archiving and Communications System) PACS. The Department of Defense and the Veterans Administration have been pioneers in the transformation of medical diagnostic imaging to the electronic environment. Many civilian sites are expected to implement large-scale PACS in the next five to ten years. This presentation will related the empirical insights gleaned at our institution from a large-scale PACS implementation. Our PACS integration was introduced into a fully operational department (not a new hospital) in which work flow had to continue with minimal impact. Impediments to user acceptance will be addressed. The critical components of this enormous task will be discussed. The topics covered during this session will include issues such as phased implementation, DICOM (digital imaging and communications in medicine) standard-based interaction of devices, hospital information system (HIS)/radiology information system (RIS) interface, user approval, networking, workstation deployment and backup procedures. The presentation will make specific suggestions regarding the implementation team, operating instructions, quality control (QC), training and education. The concept of identifying key functional areas is relevant to transitioning the facility to be entirely on line. Special attention must be paid to specific functional areas such as the operating rooms and trauma rooms where the clinical requirements may not match the PACS capabilities. The printing of films may be necessary for certain circumstances. The integration of teleradiology and remote clinics into a PACS is a salient topic with respect to the overall role of the radiologists providing rapid consultation. A Web-based server allows a clinician to review images and reports on a desk-top (personal) computer and thus reduce the number of dedicated PACS review workstations. This session
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
Morton, D.P.
1994-01-01
Handling uncertainty in natural inflow is an important part of a hydroelectric scheduling model. In a stochastic programming formulation, natural inflow may be modeled as a random vector with known distribution, but the size of the resulting mathematical program can be formidable. Decomposition-based algorithms take advantage of special structure and provide an attractive approach to such problems. We develop an enhanced Benders decomposition algorithm for solving multistage stochastic linear programs. The enhancements include warm start basis selection, preliminary cut generation, the multicut procedure, and decision tree traversing strategies. Computational results are presented for a collection of stochastic hydroelectric scheduling problems. Stochastic programming, Hydroelectric scheduling, Large-scale Systems.
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 Sequence Comparison.
Lal, Devi; Verma, Mansi
2017-01-01
There are millions of sequences deposited in genomic databases, and it is an important task to categorize them according to their structural and functional roles. Sequence comparison is a prerequisite for proper categorization of both DNA and protein sequences, and helps in assigning a putative or hypothetical structure and function to a given sequence. There are various methods available for comparing sequences, alignment being first and foremost for sequences with a small number of base pairs as well as for large-scale genome comparison. Various tools are available for performing pairwise large sequence comparison. The best known tools either perform global alignment or generate local alignments between the two sequences. In this chapter we first provide basic information regarding sequence comparison. This is followed by the description of the PAM and BLOSUM matrices that form the basis of sequence comparison. We also give a practical overview of currently available methods such as BLAST and FASTA, followed by a description and overview of tools available for genome comparison including LAGAN, MumMER, BLASTZ, and AVID.
Large Scale Homing in Honeybees
Pahl, Mario; Zhu, Hong; Tautz, Jürgen; Zhang, Shaowu
2011-01-01
Honeybee foragers frequently fly several kilometres to and from vital resources, and communicate those locations to their nest mates by a symbolic dance language. Research has shown that they achieve this feat by memorizing landmarks and the skyline panorama, using the sun and polarized skylight as compasses and by integrating their outbound flight paths. In order to investigate the capacity of the honeybees' homing abilities, we artificially displaced foragers to novel release spots at various distances up to 13 km in the four cardinal directions. Returning bees were individually registered by a radio frequency identification (RFID) system at the hive entrance. We found that homing rate, homing speed and the maximum homing distance depend on the release direction. Bees released in the east were more likely to find their way back home, and returned faster than bees released in any other direction, due to the familiarity of global landmarks seen from the hive. Our findings suggest that such large scale homing is facilitated by global landmarks acting as beacons, and possibly the entire skyline panorama. PMID:21602920
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.
Barnett, Jason; Watson, Jean -Paul; Woodruff, David L.
2016-11-27
Progressive hedging, though an effective heuristic for solving stochastic mixed integer programs (SMIPs), is not guaranteed to converge in this case. Here, we describe BBPH, a branch and bound algorithm that uses PH at each node in the search tree such that, given sufficient time, it will always converge to a globally optimal solution. Additionally, to providing a theoretically convergent “wrapper” for PH applied to SMIPs, computational results demonstrate that for some difficult problem instances branch and bound can find improved solutions after exploring only a few nodes.
Methane emissions on large scales
NASA Astrophysics Data System (ADS)
Beswick, K. M.; Simpson, T. W.; Fowler, D.; Choularton, T. W.; Gallagher, M. W.; Hargreaves, K. J.; Sutton, M. A.; Kaye, A.
with previous results from the area, indicating that this method of data analysis provided good estimates of large scale methane emissions.
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.
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
Computational Complexity, Efficiency and Accountability in Large Scale Teleprocessing Systems.
1980-12-01
COMPLEXITY, EFFICIENCY AND ACCOUNTABILITY IN LARGE SCALE TELEPROCESSING SYSTEMS DAAG29-78-C-0036 STANFORD UNIVERSITY JOHN T. GILL MARTIN E. BELLMAN...solve but easy to check. Ve have also suggested howy sucb random tapes can be simulated by determin- istically generating "pseudorandom" numbers by a
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.
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.
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.
Management of large-scale multimedia conferencing
NASA Astrophysics Data System (ADS)
Cidon, Israel; Nachum, Youval
1998-12-01
The goal of this work is to explore management strategies and algorithms for large-scale multimedia conferencing over a communication network. Since the use of multimedia conferencing is still limited, the management of such systems has not yet been studied in depth. A well organized and human friendly multimedia conference management should utilize efficiently and fairly its limited resources as well as take into account the requirements of the conference participants. The ability of the management to enforce fair policies and to quickly take into account the participants preferences may even lead to a conference environment that is more pleasant and more effective than a similar face to face meeting. We suggest several principles for defining and solving resource sharing problems in this context. The conference resources which are addressed in this paper are the bandwidth (conference network capacity), time (participants' scheduling) and limitations of audio and visual equipment. The participants' requirements for these resources are defined and translated in terms of Quality of Service requirements and the fairness criteria.
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.
Solving stochastic inverse elasticity problems via gradient-enhanced kernel PCA
NASA Astrophysics Data System (ADS)
Thimmisetty, C.; Zhao, W.; Chen, X.; Tong, C. H.; White, J. A.
2016-12-01
We study a class of inverse problems in which one wishes to determine the elastic properties of a subsurface formation based on deformation observations. This problem is challenging due to sparse observations, noisy measurements, and the highly heterogeneous nature of unknown underground structures. As a result, traditional deterministic inversion methods often fail to recover the unknown elastic properties with a complete description of their joint probabilistic distributions. Here, we consider a stochastic inversion problem where useful prior information about the geometry of the subsurface is given by a set of "snapshots" representing potential subsurface configurations generated by a machine-learning algorithm. Kernel principal component analysis is thus used to capture properties of the nonlinearly correlated observational data based on a smaller set of non-Gaussian "feature" random parameters. We then standardize these non-Gaussian feature parameters in terms of Gaussian random variables using Rosenblatt transformation and polynomial chaos expansion. In order to accelerate convergence of the stochastic inversion algorithm, one needs to obtain the gradient of a cost functional measuring the discrepancies between model solutions and deformation observations. Specially, the gradient information is incorporated into a Bayesian inference framework to determine the solution of the inverse problem via a variant of the MCMC algorithm. To compute the gradient information, a continuous self-adjoint model is derived and it is coupled with another two discretized adjoint models that are constructed by automatic differentiation toolkit TAPDENADE. We present numerical experiments involving a channelized formation to demonstrate the efficiency and robustness of the proposed inversion approach. This work was performed by Lawrence Livermore National Laboratory for the Department of Energy under contract number DE-AC52-07NA27344.
Large-scale simulations of complex physical systems
NASA Astrophysics Data System (ADS)
Belić, A.
2007-04-01
Scientific computing has become a tool as vital as experimentation and theory for dealing with scientific challenges of the twenty-first century. Large scale simulations and modelling serve as heuristic tools in a broad problem-solving process. High-performance computing facilities make possible the first step in this process - a view of new and previously inaccessible domains in science and the building up of intuition regarding the new phenomenology. The final goal of this process is to translate this newly found intuition into better algorithms and new analytical results. In this presentation we give an outline of the research themes pursued at the Scientific Computing Laboratory of the Institute of Physics in Belgrade regarding large-scale simulations of complex classical and quantum physical systems, and present recent results obtained in the large-scale simulations of granular materials and path integrals.
Large-scale simulations of complex physical systems
Belic, A.
2007-04-23
Scientific computing has become a tool as vital as experimentation and theory for dealing with scientific challenges of the twenty-first century. Large scale simulations and modelling serve as heuristic tools in a broad problem-solving process. High-performance computing facilities make possible the first step in this process - a view of new and previously inaccessible domains in science and the building up of intuition regarding the new phenomenology. The final goal of this process is to translate this newly found intuition into better algorithms and new analytical results.In this presentation we give an outline of the research themes pursued at the Scientific Computing Laboratory of the Institute of Physics in Belgrade regarding large-scale simulations of complex classical and quantum physical systems, and present recent results obtained in the large-scale simulations of granular materials and path integrals.
Large-Scale Reform Comes of Age
ERIC Educational Resources Information Center
Fullan, Michael
2009-01-01
This article reviews the history of large-scale education reform and makes the case that large-scale or whole system reform policies and strategies are becoming increasingly evident. The review briefly addresses the pre 1997 period concluding that while the pressure for reform was mounting that there were very few examples of deliberate or…
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.
NASA Astrophysics Data System (ADS)
Roldán, Édgar; Gupta, Shamik
2017-08-01
We study the dynamics of overdamped Brownian particles diffusing in conservative force fields and undergoing stochastic resetting to a given location at a generic space-dependent rate of resetting. We present a systematic approach involving path integrals and elements of renewal theory that allows us to derive analytical expressions for a variety of statistics of the dynamics such as (i) the propagator prior to first reset, (ii) the distribution of the first-reset time, and (iii) the spatial distribution of the particle at long times. We apply our approach to several representative and hitherto unexplored examples of resetting dynamics. A particularly interesting example for which we find analytical expressions for the statistics of resetting is that of a Brownian particle trapped in a harmonic potential with a rate of resetting that depends on the instantaneous energy of the particle. We find that using energy-dependent resetting processes is more effective in achieving spatial confinement of Brownian particles on a faster time scale than performing quenches of parameters of the harmonic potential.
Scaling and Criticality in Large-Scale Neuronal Activity
NASA Astrophysics Data System (ADS)
Linkenkaer-Hansen, K.
The human brain during wakeful rest spontaneously generates large-scale neuronal network oscillations at around 10 and 20 Hz that can be measured non-invasively using magnetoencephalography (MEG) or electroencephalography (EEG). In this chapter, spontaneous oscillations are viewed as the outcome of a self-organizing stochastic process. The aim is to introduce the general prerequisites for stochastic systems to evolve to the critical state and to explain their neurophysiological equivalents. I review the recent evidence that the theory of self-organized criticality (SOC) may provide a unifying explanation for the large variability in amplitude, duration, and recurrence of spontaneous network oscillations, as well as the high susceptibility to perturbations and the long-range power-law temporal correlations in their amplitude envelope.
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
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.
Decomposition and (importance) sampling techniques for multi-stage stochastic linear programs
Infanger, G.
1993-11-01
The difficulty of solving large-scale multi-stage stochastic linear programs arises from the sheer number of scenarios associated with numerous stochastic parameters. The number of scenarios grows exponentially with the number of stages and problems get easily out of hand even for very moderate numbers of stochastic parameters per stage. Our method combines dual (Benders) decomposition with Monte Carlo sampling techniques. We employ importance sampling to efficiently obtain accurate estimates of both expected future costs and gradients and right-hand sides of cuts. The method enables us to solve practical large-scale problems with many stages and numerous stochastic parameters per stage. We discuss the theory of sharing and adjusting cuts between different scenarios in a stage. We derive probabilistic lower and upper bounds, where we use importance path sampling for the upper bound estimation. Initial numerical results turned out to be promising.
Large Scale Metal Additive Techniques Review
Nycz, Andrzej; Adediran, Adeola I; Noakes, Mark W; Love, Lonnie J
2016-01-01
In recent years additive manufacturing made long strides toward becoming a main stream production technology. Particularly strong progress has been made in large-scale polymer deposition. However, large scale metal additive has not yet reached parity with large scale polymer. This paper is a review study of the metal additive techniques in the context of building large structures. Current commercial devices are capable of printing metal parts on the order of several cubic feet compared to hundreds of cubic feet for the polymer side. In order to follow the polymer progress path several factors are considered: potential to scale, economy, environment friendliness, material properties, feedstock availability, robustness of the process, quality and accuracy, potential for defects, and post processing as well as potential applications. This paper focuses on current state of art of large scale metal additive technology with a focus on expanding the geometric limits.
Large-scale 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.
The Large -scale Distribution of Galaxies
NASA Astrophysics Data System (ADS)
Flin, Piotr
A review of the Large-scale structure of the Universe is given. A connection is made with the titanic work by Johannes Kepler in many areas of astronomy and cosmology. A special concern is made to spatial distribution of Galaxies, voids and walls (cellular structure of the Universe). Finaly, the author is concluding that the large scale structure of the Universe can be observed in much greater scale that it was thought twenty years ago.
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
Large scale dynamics of protoplanetary discs
NASA Astrophysics Data System (ADS)
BÃ©thune, William
2017-08-01
Planets form in the gaseous and dusty disks orbiting young stars. These protoplanetary disks are dispersed in a few million years, being accreted onto the central star or evaporated into the interstellar medium. To explain the observed accretion rates, it is commonly assumed that matter is transported through the disk by turbulence, although the mechanism sustaining turbulence is uncertain. On the other side, irradiation by the central star could heat up the disk surface and trigger a photoevaporative wind, but thermal effects cannot account for the observed acceleration and collimation of the wind into a narrow jet perpendicular to the disk plane. Both issues can be solved if the disk is sensitive to magnetic fields. Weak fields lead to the magnetorotational instability, whose outcome is a state of sustained turbulence. Strong fields can slow down the disk, causing it to accrete while launching a collimated wind. However, the coupling between the disk and the neutral gas is done via electric charges, each of which is outnumbered by several billion neutral molecules. The imperfect coupling between the magnetic field and the neutral gas is described in terms of "non-ideal" effects, introducing new dynamical behaviors. This thesis is devoted to the transport processes happening inside weakly ionized and weakly magnetized accretion disks; the role of microphysical effects on the large-scale dynamics of the disk is of primary importance. As a first step, I exclude the wind and examine the impact of non-ideal effects on the turbulent properties near the disk midplane. I show that the flow can spontaneously organize itself if the ionization fraction is low enough; in this case, accretion is halted and the disk exhibits axisymmetric structures, with possible consequences on planetary formation. As a second step, I study the launching of disk winds via a global model of stratified disk embedded in a warm atmosphere. This model is the first to compute non-ideal effects from
Large scale simulations of Brownian suspensions
NASA Astrophysics Data System (ADS)
Viera, Marc Nathaniel
Particle suspensions occur in a wide variety of natural and engineering materials. Some examples are colloids, polymers, paints, and slurries. These materials exhibit complex behavior owing to the forces which act among the particles and are transmitted through the fluid medium. Depending on the application, particle sizes range from large macroscopic molecules of 100mum to smaller colloidal particles in the range of 10nm to 1mum. Particles of this size interact though interparticle forces such as electrostatic and van der Waals, as well as hydrodynamic forces transmitted through the fluid medium. Additionally, the particles are subjected to random thermal fluctuations in the fluid giving rise to Brownian motion. The central objective of our research is to develop efficient numerical algorithms for the large scale dynamic simulation of particle suspensions. While previous methods have incurred a computational cost of O(N3), where N is the number of particles, we have developed a novel algorithm capable of solving this problem in O(N ln N) operations. This has allowed us to perform dynamic simulations with up to 64,000 particles and Monte Carlo realizations of up to 1 million particles. Our algorithm follows a Stokesian dynamics formulation by evaluating many-body hydrodynamic interactions using a far-field multipole expansion combined with a near-field lubrication correction. The breakthrough O(N ln N) scaling is obtained by employing a Particle-Mesh-Ewald (PME) approach whereby near-field interactions are evaluated directly and far-field interactions are evaluated using a grid based velocity computed with FFT's. This approach is readily extended to include the effects of Brownian motion. For interacting particles, the fluctuation-dissipation theorem requires that the individual Brownian forces satisfy a correlation based on the N body resistance tensor R. The accurate modeling of these forces requires the computation of a matrix square root R 1/2 for matrices up
Large-scale cortical networks and cognition.
Bressler, S L
1995-03-01
The well-known parcellation of the mammalian cerebral cortex into a large number of functionally distinct cytoarchitectonic areas presents a problem for understanding the complex cortical integrative functions that underlie cognition. How do cortical areas having unique individual functional properties cooperate to accomplish these complex operations? Do neurons distributed throughout the cerebral cortex act together in large-scale functional assemblages? This review examines the substantial body of evidence supporting the view that complex integrative functions are carried out by large-scale networks of cortical areas. Pathway tracing studies in non-human primates have revealed widely distributed networks of interconnected cortical areas, providing an anatomical substrate for large-scale parallel processing of information in the cerebral cortex. Functional coactivation of multiple cortical areas has been demonstrated by neurophysiological studies in non-human primates and several different cognitive functions have been shown to depend on multiple distributed areas by human neuropsychological studies. Electrophysiological studies on interareal synchronization have provided evidence that active neurons in different cortical areas may become not only coactive, but also functionally interdependent. The computational advantages of synchronization between cortical areas in large-scale networks have been elucidated by studies using artificial neural network models. Recent observations of time-varying multi-areal cortical synchronization suggest that the functional topology of a large-scale cortical network is dynamically reorganized during visuomotor behavior.
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
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.
Comparative study of large-scale nonlinear optimization methods
Alemzadeh, S.A.
1987-01-01
Solving large-scale nonlinear optimization problems has been one of the active research areas for the last twenty years. Several heuristic algorithms with codes have been developed and implemented since 1966. This study explores the motivation and basic mathematical ideas leading to the development of MINOS-1.0, GRG-2,and MINOS-5.0 algorithms and their codes. The reliability, accuracy, and complexity of the algorithms and software depend upon their use of the gradient, Jacobian, and the Hessian. MINOS-1.0 and GRG-2 incorporate all of the input and output features, while MINOS-1.0 is not able to handle the nonlinearly constrained problems, and GRG-2 is not able to handle large-scale problems, MINOS-5.0 is a robust and an efficient software that incorporates all input, output features.
The large-scale distribution of galaxies
NASA Technical Reports Server (NTRS)
Geller, Margaret J.
1989-01-01
The spatial distribution of galaxies in the universe is characterized on the basis of the six completed strips of the Harvard-Smithsonian Center for Astrophysics redshift-survey extension. The design of the survey is briefly reviewed, and the results are presented graphically. Vast low-density voids similar to the void in Bootes are found, almost completely surrounded by thin sheets of galaxies. Also discussed are the implications of the results for the survey sampling problem, the two-point correlation function of the galaxy distribution, the possibility of detecting large-scale coherent flows, theoretical models of large-scale structure, and the identification of groups and clusters of galaxies.
Yazidi, Anis; Oommen, B John; Goodwin, Morten
2016-04-28
The purpose of this paper is to propose a solution to an extremely pertinent problem, namely, that of identifying unreliable sensors (in a domain of reliable and unreliable ones) without any knowledge of the ground truth. This fascinating paradox can be formulated in simple terms as trying to identify stochastic liars without any additional information about the truth. Though apparently impossible, we will show that it is feasible to solve the problem, a claim that is counter-intuitive in and of itself. One aspect of our contribution is to show how redundancy can be introduced, and how it can be effectively utilized in resolving this paradox. Legacy work and the reported literature (for example, in the so-called weighted majority algorithm) have merely addressed assessing the reliability of a sensor by comparing its reading to the ground truth either in an online or an offline manner. Unfortunately, the fundamental assumption of revealing the ground truth cannot be always guaranteed (or even expected) in many real life scenarios. While some extensions of the Condorcet jury theorem [9] can lead to a probabilistic guarantee on the quality of the fused process, they do not provide a solution to the unreliable sensor identification problem. The essence of our approach involves studying the agreement of each sensor with the rest of the sensors, and not comparing the reading of the individual sensors with the ground truth-as advocated in the literature. Under some mild conditions on the reliability of the sensors, we can prove that we can, indeed, filter out the unreliable ones. Our approach leverages the power of the theory of learning automata (LA) so as to gradually learn the identity of the reliable and unreliable sensors. To achieve this, we resort to a team of LA, where a distinct automaton is associated with each sensor. The solution provided here has been subjected to rigorous experimental tests, and the results presented are, in our opinion, both novel and
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.
Large-scale multimedia modeling applications
Droppo, J.G. Jr.; Buck, J.W.; Whelan, G.; Strenge, D.L.; Castleton, K.J.; Gelston, G.M.
1995-08-01
Over the past decade, the US Department of Energy (DOE) and other agencies have faced increasing scrutiny for a wide range of environmental issues related to past and current practices. A number of large-scale applications have been undertaken that required analysis of large numbers of potential environmental issues over a wide range of environmental conditions and contaminants. Several of these applications, referred to here as large-scale applications, have addressed long-term public health risks using a holistic approach for assessing impacts from potential waterborne and airborne transport pathways. Multimedia models such as the Multimedia Environmental Pollutant Assessment System (MEPAS) were designed for use in such applications. MEPAS integrates radioactive and hazardous contaminants impact computations for major exposure routes via air, surface water, ground water, and overland flow transport. A number of large-scale applications of MEPAS have been conducted to assess various endpoints for environmental and human health impacts. These applications are described in terms of lessons learned in the development of an effective approach for large-scale applications.
Evaluating Large-Scale Interactive Radio Programmes
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…
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.
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
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.
A New Large-Scale Global Optimization Method and Its Application to Lennard-Jones Problems
1992-11-01
stochastic methods. Computational results on Lennard - Jones problems show that the new method is considerably more successful than any other method that...our method does not find as good a solution as has been found by the best special purpose methods for Lennard - Jones problems. This illustrates the inherent difficulty of large scale global optimization.
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
Modeling Failure Propagation in Large-Scale Engineering Networks
NASA Astrophysics Data System (ADS)
Schläpfer, Markus; Shapiro, Jonathan L.
The simultaneous unavailability of several technical components within large-scale engineering systems can lead to high stress, rendering them prone to cascading events. In order to gain qualitative insights into the failure propagation mechanisms resulting from independent outages, we adopt a minimalistic model representing the components and their interdependencies by an undirected, unweighted network. The failure dynamics are modeled by an anticipated accelerated “wearout” process being dependent on the initial degree of a node and on the number of failed nearest neighbors. The results of the stochastic simulations imply that the influence of the network topology on the speed of the cascade highly depends on how the number of failed nearest neighbors shortens the life expectancy of a node. As a formal description of the decaying networks we propose a continuous-time mean field approximation, estimating the average failure rate of the nearest neighbors of a node based on the degree-degree distribution.
An iterative decoupling solution method for large scale Lyapunov equations
NASA Technical Reports Server (NTRS)
Athay, T. M.; Sandell, N. R., Jr.
1976-01-01
A great deal of attention has been given to the numerical solution of the Lyapunov equation. A useful classification of the variety of solution techniques are the groupings of direct, transformation, and iterative methods. The paper summarizes those methods that are at least partly favorable numerically, giving special attention to two criteria: exploitation of a general sparse system matrix structure and efficiency in resolving the governing linear matrix equation for different matrices. An iterative decoupling solution method is proposed as a promising approach for solving large-scale Lyapunov equation when the system matrix exhibits a general sparse structure. A Fortran computer program that realizes the iterative decoupling algorithm is also discussed.
A Modular Ring Architecture for Large Scale Neural Network Implementations
NASA Astrophysics Data System (ADS)
Jump, Lance B.; Ligomenides, Panos A.
1989-11-01
Constructing fully parallel, large scale, neural networks is complicated by the problems of providing for massive interconnectivity and of overcoming fan in/out limitations in area-efficient VLSI/WSI realizations. A modular, bus switched, neural ring architecture employing primitive ring (pRing) processors is proposed, which solves the fan in/out and connectivity problems by a dynamically reconfigurable communication ring that synchronously serves identical, radially connected, processing elements. It also allows cost versus performance trade-offs by the assignment of variable numbers of logical neurons to each physical processing element.
Large Scale Organization of a Near Wall Turbulent Boundary Layer
NASA Astrophysics Data System (ADS)
Stanislas, Michel; Dekou Tiomajou, Raoul Florent; Foucaut, Jean Marc
2016-11-01
This study lies in the context of large scale coherent structures investigation in a near wall turbulent boundary layer. An experimental database at high Reynolds numbers (Re θ = 9830 and Re θ = 19660) was obtained in the LML wind tunnel with stereo-PIV at 4 Hz and hot wire anemometry at 30 kHz. A Linear Stochastic Estimation procedure, is used to reconstruct a 3 component field resolved in space and time. Algorithms were developed to extract coherent structures from the reconstructed field. A sample of 3D view of the structures is depicted in Figure 1. Uniform momentum regions are characterized with their mean hydraulic diameter in the YZ plane, their life time and their contribution to Reynolds stresses. The vortical motions are characterized by their position, radius, circulation and vorticity in addition to their life time and their number computed at a fixed position from the wall. The spatial organization of the structures was investigated through a correlation of their respective indicative functions in the spanwise direction. The simplified large scale model that arise is compared to the ones available in the literature. Streamwise low (green) and high (yellow) uniform momentum regions with positive (red) and negative (blue) vortical motions. This work was supported by Campus International pour la Sécurité et l'Intermodalité des Transports.
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 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.
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)
Modeling Human Behavior at a Large Scale
2012-01-01
Discerning intentions in dynamic human action. Trends in Cognitive Sciences , 5(4):171 – 178, 2001. Shirli Bar-David, Israel Bar-David, Paul C. Cross, Sadie...Limits of predictability in human mobility. Science , 327(5968):1018, 2010. S.A. Stouffer. Intervening opportunities: a theory relating mobility and...Modeling Human Behavior at a Large Scale by Adam Sadilek Submitted in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy
Large-Scale Aerosol Modeling and Analysis
2008-09-30
aerosol species up to six days in advance anywhere on the globe. NAAPS and COAMPS are particularly useful for forecasts of dust storms in areas...impact cloud processes globally. With increasing dust storms due to climate change and land use changes in desert regions, the impact of the...bacteria in large-scale dust storms is expected to significantly impact warm ice cloud formation, human health, and ecosystems globally. In Niemi et al
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.
Economically viable large-scale hydrogen liquefaction
NASA Astrophysics Data System (ADS)
Cardella, U.; Decker, L.; Klein, H.
2017-02-01
The liquid hydrogen demand, particularly driven by clean energy applications, will rise in the near future. As industrial large scale liquefiers will play a major role within the hydrogen supply chain, production capacity will have to increase by a multiple of today’s typical sizes. The main goal is to reduce the total cost of ownership for these plants by increasing energy efficiency with innovative and simple process designs, optimized in capital expenditure. New concepts must ensure a manageable plant complexity and flexible operability. In the phase of process development and selection, a dimensioning of key equipment for large scale liquefiers, such as turbines and compressors as well as heat exchangers, must be performed iteratively to ensure technological feasibility and maturity. Further critical aspects related to hydrogen liquefaction, e.g. fluid properties, ortho-para hydrogen conversion, and coldbox configuration, must be analysed in detail. This paper provides an overview on the approach, challenges and preliminary results in the development of efficient as well as economically viable concepts for large-scale hydrogen liquefaction.
Large-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.
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.
NASA Astrophysics Data System (ADS)
Nigro, G.; Pongkitiwanichakul, P.; Cattaneo, F.; Tobias, S. M.
2017-01-01
We consider kinematic dynamo action in a sheared helical flow at moderate to high values of the magnetic Reynolds number (Rm). We find exponentially growing solutions which, for large enough shear, take the form of a coherent part embedded in incoherent fluctuations. We argue that at large Rm large-scale dynamo action should be identified by the presence of structures coherent in time, rather than those at large spatial scales. We further argue that although the growth rate is determined by small-scale processes, the period of the coherent structures is set by mean-field considerations.
Large-scale 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 planar lightwave circuits
NASA Astrophysics Data System (ADS)
Bidnyk, Serge; Zhang, Hua; Pearson, Matt; Balakrishnan, Ashok
2011-01-01
By leveraging advanced wafer processing and flip-chip bonding techniques, we have succeeded in hybrid integrating a myriad of active optical components, including photodetectors and laser diodes, with our planar lightwave circuit (PLC) platform. We have combined hybrid integration of active components with monolithic integration of other critical functions, such as diffraction gratings, on-chip mirrors, mode-converters, and thermo-optic elements. Further process development has led to the integration of polarization controlling functionality. Most recently, all these technological advancements have been combined to create large-scale planar lightwave circuits that comprise hundreds of optical elements integrated on chips less than a square inch in size.
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.
Colloquium: Large scale simulations on GPU clusters
NASA Astrophysics Data System (ADS)
Bernaschi, Massimo; Bisson, Mauro; Fatica, Massimiliano
2015-06-01
Graphics processing units (GPU) are currently used as a cost-effective platform for computer simulations and big-data processing. Large scale applications require that multiple GPUs work together but the efficiency obtained with cluster of GPUs is, at times, sub-optimal because the GPU features are not exploited at their best. We describe how it is possible to achieve an excellent efficiency for applications in statistical mechanics, particle dynamics and networks analysis by using suitable memory access patterns and mechanisms like CUDA streams, profiling tools, etc. Similar concepts and techniques may be applied also to other problems like the solution of Partial Differential Equations.
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.
Large-scale Heterogeneous Network Data Analysis
2012-07-31
Data for Multi-Player Influence Maximization on Social Networks.” KDD 2012 (Demo). Po-Tzu Chang , Yen-Chieh Huang, Cheng-Lun Yang, Shou-De Lin, Pu...Jen Cheng. “Learning-Based Time-Sensitive Re-Ranking for Web Search.” SIGIR 2012 (poster) Hung -Che Lai, Cheng-Te Li, Yi-Chen Lo, and Shou-De Lin...Exploiting and Evaluating MapReduce for Large-Scale Graph Mining.” ASONAM 2012 (Full, 16% acceptance ratio). Hsun-Ping Hsieh , Cheng-Te Li, and Shou
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.
Internationalization Measures in Large Scale Research Projects
NASA Astrophysics Data System (ADS)
Soeding, Emanuel; Smith, Nancy
2017-04-01
Internationalization measures in Large Scale Research Projects Large scale research projects (LSRP) often serve as flagships used by universities or research institutions to demonstrate their performance and capability to stakeholders and other interested parties. As the global competition among universities for the recruitment of the brightest brains has increased, effective internationalization measures have become hot topics for universities and LSRP alike. Nevertheless, most projects and universities are challenged with little experience on how to conduct these measures and make internationalization an cost efficient and useful activity. Furthermore, those undertakings permanently have to be justified with the Project PIs as important, valuable tools to improve the capacity of the project and the research location. There are a variety of measures, suited to support universities in international recruitment. These include e.g. institutional partnerships, research marketing, a welcome culture, support for science mobility and an effective alumni strategy. These activities, although often conducted by different university entities, are interlocked and can be very powerful measures if interfaced in an effective way. On this poster we display a number of internationalization measures for various target groups, identify interfaces between project management, university administration, researchers and international partners to work together, exchange information and improve processes in order to be able to recruit, support and keep the brightest heads to your project.
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.
Large-scale Intelligent Transporation Systems simulation
Ewing, T.; Canfield, T.; Hannebutte, U.; Levine, D.; Tentner, A.
1995-06-01
A prototype computer system has been developed which defines a high-level architecture for a large-scale, comprehensive, scalable simulation of an Intelligent Transportation System (ITS) capable of running on massively parallel computers and distributed (networked) computer systems. The prototype includes the modelling of instrumented ``smart`` vehicles with in-vehicle navigation units capable of optimal route planning and Traffic Management Centers (TMC). The TMC has probe vehicle tracking capabilities (display position and attributes of instrumented vehicles), and can provide 2-way interaction with traffic to provide advisories and link times. Both the in-vehicle navigation module and the TMC feature detailed graphical user interfaces to support human-factors studies. The prototype has been developed on a distributed system of networked UNIX computers but is designed to run on ANL`s IBM SP-X parallel computer system for large scale problems. A novel feature of our design is that vehicles will be represented by autonomus computer processes, each with a behavior model which performs independent route selection and reacts to external traffic events much like real vehicles. With this approach, one will be able to take advantage of emerging massively parallel processor (MPP) systems.
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.
Large-scale Globally Propagating Coronal Waves.
Warmuth, Alexander
Large-scale, globally propagating wave-like disturbances have been observed in the solar chromosphere and by inference in the corona since the 1960s. However, detailed analysis of these phenomena has only been conducted since the late 1990s. This was prompted by the availability of high-cadence coronal imaging data from numerous spaced-based instruments, which routinely show spectacular globally propagating bright fronts. Coronal waves, as these perturbations are usually referred to, have now been observed in a wide range of spectral channels, yielding a wealth of information. Many findings have supported the "classical" interpretation of the disturbances: fast-mode MHD waves or shocks that are propagating in the solar corona. However, observations that seemed inconsistent with this picture have stimulated the development of alternative models in which "pseudo waves" are generated by magnetic reconfiguration in the framework of an expanding coronal mass ejection. This has resulted in a vigorous debate on the physical nature of these disturbances. This review focuses on demonstrating how the numerous observational findings of the last one and a half decades can be used to constrain our models of large-scale coronal waves, and how a coherent physical understanding of these disturbances is finally emerging.
Efficient, large scale separation of coal macerals
Dyrkacz, G.R.; Bloomquist, C.A.A.
1988-01-01
The authors believe that the separation of macerals by continuous flow centrifugation offers a simple technique for the large scale separation of macerals. With relatively little cost (/approximately/ $10K), it provides an opportunity for obtaining quite pure maceral fractions. Although they have not completely worked out all the nuances of this separation system, they believe that the problems they have indicated can be minimized to pose only minor inconvenience. It cannot be said that this system completely bypasses the disagreeable tedium or time involved in separating macerals, nor will it by itself overcome the mental inertia required to make maceral separation an accepted necessary fact in fundamental coal science. However, they find their particular brand of continuous flow centrifugation is considerably faster than sink/float separation, can provide a good quality product with even one separation cycle, and permits the handling of more material than a conventional sink/float centrifuge separation.
Primer design for large scale sequencing.
Haas, S; Vingron, M; Poustka, A; Wiemann, S
1998-01-01
We have developed PRIDE, a primer design program that automatically designs primers in single contigs or whole sequencing projects to extend the already known sequence and to double strand single-stranded regions. The program is fully integrated into the Staden package (GAP4) and accessible with a graphical user interface. PRIDE uses a fuzzy logic-based system to calculate primer qualities. The computational performance of PRIDE is enhanced by using suffix trees to store the huge amount of data being produced. A test set of 110 sequencing primers and 11 PCR primer pairs has been designed on genomic templates, cDNAs and sequences containing repetitive elements to analyze PRIDE's success rate. The high performance of PRIDE, combined with its minimal requirement of user interaction and its fast algorithm, make this program useful for the large scale design of primers, especially in large sequencing projects. PMID:9611248
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 Organization of Glycosylation Networks
NASA Astrophysics Data System (ADS)
Kim, Pan-Jun; Lee, Dong-Yup; Jeong, Hawoong
2009-03-01
Glycosylation is a highly complex process to produce a diverse repertoire of cellular glycans that are frequently attached to proteins and lipids. Glycans participate in fundamental biological processes including molecular trafficking and clearance, cell proliferation and apoptosis, developmental biology, immune response, and pathogenesis. N-linked glycans found on proteins are formed by sequential attachments of monosaccharides with the help of a relatively small number of enzymes. Many of these enzymes can accept multiple N-linked glycans as substrates, thus generating a large number of glycan intermediates and their intermingled pathways. Motivated by the quantitative methods developed in complex network research, we investigate the large-scale organization of such N-glycosylation pathways in a mammalian cell. The uncovered results give the experimentally-testable predictions for glycosylation process, and can be applied to the engineering of therapeutic glycoproteins.
Large-scale optimization of neuron arbors
NASA Astrophysics Data System (ADS)
Cherniak, Christopher; Changizi, Mark; Won Kang, Du
1999-05-01
At the global as well as local scales, some of the geometry of types of neuron arbors-both dendrites and axons-appears to be self-organizing: Their morphogenesis behaves like flowing water, that is, fluid dynamically; waterflow in branching networks in turn acts like a tree composed of cords under tension, that is, vector mechanically. Branch diameters and angles and junction sites conform significantly to this model. The result is that such neuron tree samples globally minimize their total volume-rather than, for example, surface area or branch length. In addition, the arbors perform well at generating the cheapest topology interconnecting their terminals: their large-scale layouts are among the best of all such possible connecting patterns, approaching 5% of optimum. This model also applies comparably to arterial and river networks.
Large scale cryogenic fluid systems testing
NASA Technical Reports Server (NTRS)
1992-01-01
NASA Lewis Research Center's Cryogenic Fluid Systems Branch (CFSB) within the Space Propulsion Technology Division (SPTD) has the ultimate goal of enabling the long term storage and in-space fueling/resupply operations for spacecraft and reusable vehicles in support of space exploration. Using analytical modeling, ground based testing, and on-orbit experimentation, the CFSB is studying three primary categories of fluid technology: storage, supply, and transfer. The CFSB is also investigating fluid handling, advanced instrumentation, and tank structures and materials. Ground based testing of large-scale systems is done using liquid hydrogen as a test fluid at the Cryogenic Propellant Tank Facility (K-site) at Lewis' Plum Brook Station in Sandusky, Ohio. A general overview of tests involving liquid transfer, thermal control, pressure control, and pressurization is given.
Large scale preparation of pure phycobiliproteins.
Padgett, M P; Krogmann, D W
1987-01-01
This paper describes simple procedures for the purification of large amounts of phycocyanin and allophycocyanin from the cyanobacterium Microcystis aeruginosa. A homogeneous natural bloom of this organism provided hundreds of kilograms of cells. Large samples of cells were broken by freezing and thawing. Repeated extraction of the broken cells with distilled water released phycocyanin first, then allophycocyanin, and provides supporting evidence for the current models of phycobilisome structure. The very low ionic strength of the aqueous extracts allowed allophycocyanin release in a particulate form so that this protein could be easily concentrated by centrifugation. Other proteins in the extract were enriched and concentrated by large scale membrane filtration. The biliproteins were purified to homogeneity by chromatography on DEAE cellulose. Purity was established by HPLC and by N-terminal amino acid sequence analysis. The proteins were examined for stability at various pHs and exposures to visible light.
Primer design for large scale sequencing.
Haas, S; Vingron, M; Poustka, A; Wiemann, S
1998-06-15
We have developed PRIDE, a primer design program that automatically designs primers in single contigs or whole sequencing projects to extend the already known sequence and to double strand single-stranded regions. The program is fully integrated into the Staden package (GAP4) and accessible with a graphical user interface. PRIDE uses a fuzzy logic-based system to calculate primer qualities. The computational performance of PRIDE is enhanced by using suffix trees to store the huge amount of data being produced. A test set of 110 sequencing primers and 11 PCR primer pairs has been designed on genomic templates, cDNAs and sequences containing repetitive elements to analyze PRIDE's success rate. The high performance of PRIDE, combined with its minimal requirement of user interaction and its fast algorithm, make this program useful for the large scale design of primers, especially in large sequencing projects.
Large-scale synthesis of peptides.
Andersson, L; Blomberg, L; Flegel, M; Lepsa, L; Nilsson, B; Verlander, M
2000-01-01
Recent advances in the areas of formulation and delivery have rekindled the interest of the pharmaceutical community in peptides as drug candidates, which, in turn, has provided a challenge to the peptide industry to develop efficient methods for the manufacture of relatively complex peptides on scales of up to metric tons per year. This article focuses on chemical synthesis approaches for peptides, and presents an overview of the methods available and in use currently, together with a discussion of scale-up strategies. Examples of the different methods are discussed, together with solutions to some specific problems encountered during scale-up development. Finally, an overview is presented of issues common to all manufacturing methods, i.e., methods used for the large-scale purification and isolation of final bulk products and regulatory considerations to be addressed during scale-up of processes to commercial levels. Copyright 2000 John Wiley & Sons, Inc. Biopolymers (Pept Sci) 55: 227-250, 2000
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
Jovian large-scale stratospheric circulation
NASA Technical Reports Server (NTRS)
West, R. A.; Friedson, A. J.; Appleby, J. F.
1992-01-01
An attempt is made to diagnose the annual-average mean meridional residual Jovian large-scale stratospheric circulation from observations of the temperature and reflected sunlight that reveal the morphology of the aerosol heating. The annual mean solar heating, total radiative flux divergence, mass stream function, and Eliassen-Palm flux divergence are shown. The stratospheric radiative flux divergence is dominated the high latitudes by aerosol absorption. Between the 270 and 100 mbar pressure levels, where there is no aerosol heating in the model, the structure of the circulation at low- to midlatitudes is governed by the meridional variation of infrared cooling in association with the variation of zonal mean temperatures observed by IRIS. The principal features of the vertical velocity profile found by Gierasch et al. (1986) are recovered in the present calculation.
Large-scale parametric survival analysis.
Mittal, Sushil; Madigan, David; Cheng, Jerry Q; Burd, Randall S
2013-10-15
Survival analysis has been a topic of active statistical research in the past few decades with applications spread across several areas. Traditional applications usually consider data with only a small numbers of predictors with a few hundreds or thousands of observations. Recent advances in data acquisition techniques and computation power have led to considerable interest in analyzing very-high-dimensional data where the number of predictor variables and the number of observations range between 10(4) and 10(6). In this paper, we present a tool for performing large-scale regularized parametric survival analysis using a variant of the cyclic coordinate descent method. Through our experiments on two real data sets, we show that application of regularized models to high-dimensional data avoids overfitting and can provide improved predictive performance and calibration over corresponding low-dimensional models.
Large-Scale Parametric Survival Analysis†
Mittal, Sushil; Madigan, David; Cheng, Jerry; Burd, Randall S.
2013-01-01
Survival analysis has been a topic of active statistical research in the past few decades with applications spread across several areas. Traditional applications usually consider data with only small numbers of predictors with a few hundreds or thousands of observations. Recent advances in data acquisition techniques and computation power has led to considerable interest in analyzing very high-dimensional data where the number of predictor variables and the number of observations range between 104 – 106. In this paper, we present a tool for performing large-scale regularized parametric survival analysis using a variant of cyclic coordinate descent method. Through our experiments on two real data sets, we show that application of regularized models to high-dimensional data avoids overfitting and can provide improved predictive performance and calibration over corresponding low-dimensional models. PMID:23625862
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.
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.
Modeling the Internet's large-scale topology
Yook, Soon-Hyung; Jeong, Hawoong; Barabási, Albert-László
2002-01-01
Network generators that capture the Internet's large-scale topology are crucial for the development of efficient routing protocols and modeling Internet traffic. Our ability to design realistic generators is limited by the incomplete understanding of the fundamental driving forces that affect the Internet's evolution. By combining several independent databases capturing the time evolution, topology, and physical layout of the Internet, we identify the universal mechanisms that shape the Internet's router and autonomous system level topology. We find that the physical layout of nodes form a fractal set, determined by population density patterns around the globe. The placement of links is driven by competition between preferential attachment and linear distance dependence, a marked departure from the currently used exponential laws. The universal parameters that we extract significantly restrict the class of potentially correct Internet models and indicate that the networks created by all available topology generators are fundamentally different from the current Internet. PMID:12368484
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.
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.
Improving Recent Large-Scale Pulsar Surveys
NASA Astrophysics Data System (ADS)
Cardoso, Rogerio Fernando; Ransom, S.
2011-01-01
Pulsars are unique in that they act as celestial laboratories for precise tests of gravity and other extreme physics (Kramer 2004). There are approximately 2000 known pulsars today, which is less than ten percent of pulsars in the Milky Way according to theoretical models (Lorimer 2004). Out of these 2000 known pulsars, approximately ten percent are known millisecond pulsars, objects used for their period stability for detailed physics tests and searches for gravitational radiation (Lorimer 2008). As the field and instrumentation progress, pulsar astronomers attempt to overcome observational biases and detect new pulsars, consequently discovering new millisecond pulsars. We attempt to improve large scale pulsar surveys by examining three recent pulsar surveys. The first, the Green Bank Telescope 350MHz Drift Scan, a low frequency isotropic survey of the northern sky, has yielded a large number of candidates that were visually inspected and identified, resulting in over 34.000 thousands candidates viewed, dozens of detections of known pulsars, and the discovery of a new low-flux pulsar, PSRJ1911+22. The second, the PALFA survey, is a high frequency survey of the galactic plane with the Arecibo telescope. We created a processing pipeline for the PALFA survey at the National Radio Astronomy Observatory in Charlottesville- VA, in addition to making needed modifications upon advice from the PALFA consortium. The third survey examined is a new GBT 820MHz survey devoted to find new millisecond pulsars by observing the target-rich environment of unidentified sources in the FERMI LAT catalogue. By approaching these three pulsar surveys at different stages, we seek to improve the success rates of large scale surveys, and hence the possibility for ground-breaking work in both basic physics and astrophysics.
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.
Voids in the Large-Scale Structure
NASA Astrophysics Data System (ADS)
El-Ad, Hagai; Piran, Tsvi
1997-12-01
Voids are the most prominent feature of the large-scale structure of the universe. Still, their incorporation into quantitative analysis of it has been relatively recent, owing essentially to the lack of an objective tool to identify the voids and to quantify them. To overcome this, we present here the VOID FINDER algorithm, a novel tool for objectively quantifying voids in the galaxy distribution. The algorithm first classifies galaxies as either wall galaxies or field galaxies. Then, it identifies voids in the wall-galaxy distribution. Voids are defined as continuous volumes that do not contain any wall galaxies. The voids must be thicker than an adjustable limit, which is refined in successive iterations. In this way, we identify the same regions that would be recognized as voids by the eye. Small breaches in the walls are ignored, avoiding artificial connections between neighboring voids. We test the algorithm using Voronoi tesselations. By appropriate scaling of the parameters with the selection function, we apply it to two redshift surveys, the dense SSRS2 and the full-sky IRAS 1.2 Jy. Both surveys show similar properties: ~50% of the volume is filled by voids. The voids have a scale of at least 40 h-1 Mpc and an average -0.9 underdensity. Faint galaxies do not fill the voids, but they do populate them more than bright ones. These results suggest that both optically and IRAS-selected galaxies delineate the same large-scale structure. Comparison with the recovered mass distribution further suggests that the observed voids in the galaxy distribution correspond well to underdense regions in the mass distribution. This confirms the gravitational origin of the voids.
Braumann, Andreas; Kraft, Markus; Wagner, Wolfgang
2010-10-01
This paper is concerned with computational aspects of a multidimensional population balance model of a wet granulation process. Wet granulation is a manufacturing method to form composite particles, granules, from small particles and binders. A detailed numerical study of a stochastic particle algorithm for the solution of a five-dimensional population balance model for wet granulation is presented. Each particle consists of two types of solids (containing pores) and of external and internal liquid (located in the pores). Several transformations of particles are considered, including coalescence, compaction and breakage. A convergence study is performed with respect to the parameter that determines the number of numerical particles. Averaged properties of the system are computed. In addition, the ensemble is subdivided into practically relevant size classes and analysed with respect to the amount of mass and the particle porosity in each class. These results illustrate the importance of the multidimensional approach. Finally, the kinetic equation corresponding to the stochastic model is discussed.
Exploiting large-scale correlations to detect continuous gravitational waves.
Pletsch, Holger J; Allen, Bruce
2009-10-30
Fully coherent searches (over realistic ranges of parameter space and year-long observation times) for unknown sources of continuous gravitational waves are computationally prohibitive. Less expensive hierarchical searches divide the data into shorter segments which are analyzed coherently, then detection statistics from different segments are combined incoherently. The novel method presented here solves the long-standing problem of how best to do the incoherent combination. The optimal solution exploits large-scale parameter-space correlations in the coherent detection statistic. Application to simulated data shows dramatic sensitivity improvements compared with previously available (ad hoc) methods, increasing the spatial volume probed by more than 2 orders of magnitude at lower computational cost.
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.
Efficient multiobjective optimization scheme for large scale structures
NASA Astrophysics Data System (ADS)
Grandhi, Ramana V.; Bharatram, Geetha; Venkayya, V. B.
1992-09-01
This paper presents a multiobjective optimization algorithm for an efficient design of large scale structures. The algorithm is based on generalized compound scaling techniques to reach the intersection of multiple functions. Multiple objective functions are treated similar to behavior constraints. Thus, any number of objectives can be handled in the formulation. Pseudo targets on objectives are generated at each iteration in computing the scale factors. The algorithm develops a partial Pareto set. This method is computationally efficient due to the fact that it does not solve many single objective optimization problems in reaching the Pareto set. The computational efficiency is compared with other multiobjective optimization methods, such as the weighting method and the global criterion method. Trusses, plate, and wing structure design cases with stress and frequency considerations are presented to demonstrate the effectiveness of the method.
Large-Scale Numerical Simulations of Human Motion
NASA Technical Reports Server (NTRS)
Anderson, Frank C.; Ziegler, James M.; Pandy, Marcus G.; Whalen, Robert T.
1994-01-01
This paper examines the feasibility of using massively-parallel and vector-processing supercomputers to solve large-scale optimal control problems for human movement. Specifically, we compare the computational expense of determining the optimal controls for the single support phase of walking using a conventional serial machine (a Silicon Graphics Personal Iris 4D25 workstation), a MIMD parallel machine (an Intel iPSC/860 comprising 128 processors), and a parallel-vector-processing machine (a Cray Y-MP 8/864). With the human body modeled as a 14 degree-of-freedom linkage actuated by 46 musculotendinous units, computation of the optimal controls for walking could take up to 3 months of CPU time on the Iris. Both the Cray Y-MP and the Intel iPSC/860 are able to reduce this time to practical levels. The optimal control solution for walking can be found with about 77 hours of CPU time on the Cray, and with about 88 hours of CPU time on the Intel. Although the overall speeds of the Cray and the Intel were found to be similar, the unique capabilities of each machine are best suited to different parts of the optimal control algorithm used. The Intel performed best in the calculation of the derivatives of the performance criterion and the constraints. In contrast, the Cray performed best during parameter optimization of the controls. These results suggest that the ideal computer architecture for solving very large-scale optimal control problems is a hybrid system in which a vector-processing machine is integrated into the communication network of a MIMD parallel machine.
Statistical Measures of Large-Scale Structure
NASA Astrophysics Data System (ADS)
Vogeley, Michael; Geller, Margaret; Huchra, John; Park, Changbom; Gott, J. Richard
1993-12-01
\\inv Mpc} To quantify clustering in the large-scale distribution of galaxies and to test theories for the formation of structure in the universe, we apply statistical measures to the CfA Redshift Survey. This survey is complete to m_{B(0)}=15.5 over two contiguous regions which cover one-quarter of the sky and include ~ 11,000 galaxies. The salient features of these data are voids with diameter 30-50\\hmpc and coherent dense structures with a scale ~ 100\\hmpc. Comparison with N-body simulations rules out the ``standard" CDM model (Omega =1, b=1.5, sigma_8 =1) at the 99% confidence level because this model has insufficient power on scales lambda >30\\hmpc. An unbiased open universe CDM model (Omega h =0.2) and a biased CDM model with non-zero cosmological constant (Omega h =0.24, lambda_0 =0.6) match the observed power spectrum. The amplitude of the power spectrum depends on the luminosity of galaxies in the sample; bright (L>L(*) ) galaxies are more strongly clustered than faint galaxies. The paucity of bright galaxies in low-density regions may explain this dependence. To measure the topology of large-scale structure, we compute the genus of isodensity surfaces of the smoothed density field. On scales in the ``non-linear" regime, <= 10\\hmpc, the high- and low-density regions are multiply-connected over a broad range of density threshold, as in a filamentary net. On smoothing scales >10\\hmpc, the topology is consistent with statistics of a Gaussian random field. Simulations of CDM models fail to produce the observed coherence of structure on non-linear scales (>95% confidence level). The underdensity probability (the frequency of regions with density contrast delta rho //lineρ=-0.8) depends strongly on the luminosity of galaxies; underdense regions are significantly more common (>2sigma ) in bright (L>L(*) ) galaxy samples than in samples which include fainter galaxies.
Non-Gaussianity and Large Scale Structure in a two-field Inflationary model
Tseliakhovich, D.; Slosar, A.; Hirata, C.
2010-08-30
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*{sub NL} and the ratio {zeta} of the amplitude of primordial perturbations due to the inflaton and curvaton using WMAP and Sloan Digital Sky Survey data.
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 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 tides in general relativity
NASA Astrophysics Data System (ADS)
Ip, Hiu Yan; Schmidt, Fabian
2017-02-01
Density perturbations in cosmology, i.e. spherically symmetric adiabatic perturbations of a Friedmann-Lemaȋtre-Robertson-Walker (FLRW) spacetime, are locally exactly equivalent to a different FLRW solution, as long as their wavelength is much larger than the sound horizon of all fluid components. This fact is known as the "separate universe" paradigm. However, no such relation is known for anisotropic adiabatic perturbations, which correspond to an FLRW spacetime with large-scale tidal fields. Here, we provide a closed, fully relativistic set of evolutionary equations for the nonlinear evolution of such modes, based on the conformal Fermi (CFC) frame. We show explicitly that the tidal effects are encoded by the Weyl tensor, and are hence entirely different from an anisotropic Bianchi I spacetime, where the anisotropy is sourced by the Ricci tensor. In order to close the system, certain higher derivative terms have to be dropped. We show that this approximation is equivalent to the local tidal approximation of Hui and Bertschinger [1]. We also show that this very simple set of equations matches the exact evolution of the density field at second order, but fails at third and higher order. This provides a useful, easy-to-use framework for computing the fully relativistic growth of structure at second order.
Large scale 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.
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 structure of the sun's corona
NASA Astrophysics Data System (ADS)
Kundu, Mukul R.
Results concerning the large-scale structure of the solar corona obtained by observations at meter-decameter wavelengths are reviewed. Coronal holes observed on the disk at multiple frequencies show the radial and azimuthal geometry of the hole. At the base of the hole there is good correspondence to the chromospheric signature in He I 10,830 A, but at greater heights the hole may show departures from symmetry. Two-dimensional imaging of weak-type III bursts simultaneously with the HAO SMM coronagraph/polarimeter measurements indicate that these bursts occur along elongated features emanating from the quiet sun, corresponding in position angle to the bright coronal streamers. It is shown that the densest regions of streamers and the regions of maximum intensity of type II bursts coincide closely. Non-flare-associated type II/type IV bursts associated with coronal streamer disruption events are studied along with correlated type II burst emissions originating from distant centers on the sun.
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.
Large Scale EOF Analysis of Climate Data
NASA Astrophysics Data System (ADS)
Prabhat, M.; Gittens, A.; Kashinath, K.; Cavanaugh, N. R.; Mahoney, M.
2016-12-01
We present a distributed approach towards extracting EOFs from 3D climate data. We implement the method in Apache Spark, and process multi-TB sized datasets on O(1000-10,000) cores. We apply this method to latitude-weighted ocean temperature data from CSFR, a 2.2 terabyte-sized data set comprising ocean and subsurface reanalysis measurements collected at 41 levels in the ocean, at 6 hour intervals over 31 years. We extract the first 100 EOFs of this full data set and compare to the EOFs computed simply on the surface temperature field. Our analyses provide evidence of Kelvin and Rossy waves and components of large-scale modes of oscillation including the ENSO and PDO that are not visible in the usual SST EOFs. Further, they provide information on the the most influential parts of the ocean, such as the thermocline, that exist below the surface. Work is ongoing to understand the factors determining the depth-varying spatial patterns observed in the EOFs. We will experiment with weighting schemes to appropriately account for the differing depths of the observations. We also plan to apply the same distributed approach to analysis of analysis of 3D atmospheric climatic data sets, including multiple variables. Because the atmosphere changes on a quicker time-scale than the ocean, we expect that the results will demonstrate an even greater advantage to computing 3D EOFs in lieu of 2D EOFs.
Numerical Modeling for Large Scale Hydrothermal System
NASA Astrophysics Data System (ADS)
Sohrabi, Reza; Jansen, Gunnar; Malvoisin, Benjamin; Mazzini, Adriano; Miller, Stephen A.
2017-04-01
Moderate-to-high enthalpy systems are driven by multiphase and multicomponent processes, fluid and rock mechanics, and heat transport processes, all of which present challenges in developing realistic numerical models of the underlying physics. The objective of this work is to present an approach, and some initial results, for modeling and understanding dynamics of the birth of large scale hydrothermal systems. Numerical modeling of such complex systems must take into account a variety of coupled thermal, hydraulic, mechanical and chemical processes, which is numerically challenging. To provide first estimates of the behavior of this deep complex systems, geological structures must be constrained, and the fluid dynamics, mechanics and the heat transport need to be investigated in three dimensions. Modeling these processes numerically at adequate resolution and reasonable computation times requires a suite of tools that we are developing and/or utilizing to investigate such systems. Our long-term goal is to develop 3D numerical models, based on a geological models, which couples mechanics with the hydraulics and thermal processes driving hydrothermal system. Our first results from the Lusi hydrothermal system in East Java, Indonesia provide a basis for more sophisticated studies, eventually in 3D, and we introduce a workflow necessary to achieve these objectives. Future work focuses with the aim and parallelization suitable for High Performance Computing (HPC). Such developments are necessary to achieve high-resolution simulations to more fully understand the complex dynamics of hydrothermal systems.
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.
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.
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
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.
The School Principal's Role in Large-Scale Assessment
ERIC Educational Resources Information Center
Newton, Paul; Tunison, Scott; Viczko, Melody
2010-01-01
This paper reports on an interpretive study in which 25 elementary principals were asked about their assessment knowledge, the use of large-scale assessments in their schools, and principals' perceptions on their roles with respect to large-scale assessments. Principals in this study suggested that the current context of large-scale assessment and…
Synchronization of coupled large-scale Boolean networks
NASA Astrophysics Data System (ADS)
Li, Fangfei
2014-03-01
This paper investigates the complete synchronization and partial synchronization of two large-scale Boolean networks. First, the aggregation algorithm towards large-scale Boolean network is reviewed. Second, the aggregation algorithm is applied to study the complete synchronization and partial synchronization of large-scale Boolean networks. Finally, an illustrative example is presented to show the efficiency of the proposed results.
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).
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;
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
Using Multimedia in Large-Scale Computer-Based Testing Programs.
ERIC Educational Resources Information Center
Bennett, R. E.; Goodman, M.; Hessinger, J.; Kahn, H.; Ligget, J.; Marshall, G.; Zack, J.
1999-01-01
Discusses the use of multimedia in large-scale computer-based testing programs to measure problem solving and related cognitive constructs more effectively. Considers the incorporation of dynamic stimuli such as audio, video, and animation, and gives examples in history, physical education, and the sciences. (Author/LRW)
Large-Scale Events: New Ways of Working Across the Organization.
ERIC Educational Resources Information Center
Brigham, Steven E.
1996-01-01
Eight approaches to organizational change and problem solving that use large-scale events and involve a broad range of stakeholders are described, and their applications to college administration are discussed. They include future searches; open space technology; interactive design method; home-grown events such as retreats; great teaching…
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
Schumacher, Kathryn M.; Chen, Richard Li-Yang; Cohn, Amy E. M.; ...
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
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 a 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.
Large-scale Fractal Motion of Clouds
2017-09-27
waters surrounding the island.) The “swallowed” gulps of clear island air get carried along within the vortices, but these are soon mixed into the surrounding clouds. Landsat is unique in its ability to image both the small-scale eddies that mix clear and cloudy air, down to the 30 meter pixel size of Landsat, but also having a wide enough field-of-view, 180 km, to reveal the connection of the turbulence to large-scale flows such as the subtropical oceanic gyres. Landsat 7, with its new onboard digital recorder, has extended this capability away from the few Landsat ground stations to remote areas such as Alejandro Island, and thus is gradually providing a global dynamic picture of evolving human-scale phenomena. For more details on von Karman vortices, refer to climate.gsfc.nasa.gov/~cahalan. Image and caption courtesy Bob Cahalan, NASA GSFC Instrument: Landsat 7 - ETM+ Credit: NASA/GSFC/Landsat NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Join us on Facebook
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 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
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
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
Large-scale Stratospheric Transport Processes
NASA Technical Reports Server (NTRS)
Plumb, R. Alan
2003-01-01
The PI has undertaken a theoretical analysis of the existence and nature of compact tracer-tracer relationships of the kind observed in the stratosphere, augmented with three-dimensional model simulations of stratospheric tracers (the latter being an extension of modeling work the group did during the SOLVE experiment). This work achieves a rigorous theoretical basis for the existence and shape of these relationships, as well as a quantitative theory of their width and evolution, in terms of the joint tracer-tracer PDF distribution. A paper on this work is almost complete and will soon be submitted to Rev. Geophys. We have analyzed lower stratospheric water in simulations with an isentropic-coordinate version of the MATCH transport model which we recently helped to develop. The three-dimensional structure of lower stratospheric water, in particular, attracted our attention: dry air is, below about 400K potential temperature, localized in the regions of the west Pacific and equatorial South America. We have been analyzing air trajectories to determine how air passes through the tropopause cold trap. This work is now being completed, and a paper will be submitted to Geophys. Res. Lett. before the end of summer. We are continuing to perform experiments with the 'MATCH' CTM, in both sigma- and entropy-coordinate forms. We earlier found (in collaboration with Dr Natalie Mahowald, and as part of an NSF-funded project) that switching to isentropic coordinates made a substantial improvement to the simulation of the age of stratospheric air. We are now running experiments with near-tropopause sources in both versions of the model, to see if and to what extent the simulation of stratosphere-troposphere transport is dependent on the model coordinate. Personnel Research is supervised by the PI, Prof. Alan Plumb. Mr William Heres conducts the tracer modeling work and performs other modeling tasks. Two graduate students, Ms Irene Lee and Mr Michael Ring, have been participating
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.
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
Limitations and tradeoffs in synchronization of large-scale networks with uncertain links.
Diwadkar, Amit; Vaidya, Umesh
2016-04-12
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
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.
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.
Visual attention mitigates information loss in small- and large-scale neural codes
Sprague, Thomas C; Saproo, Sameer; Serences, John T
2015-01-01
Summary The visual system transforms complex inputs into robust and parsimonious neural codes that efficiently guide behavior. Because neural communication is stochastic, the amount of encoded visual information necessarily decreases with each synapse. This constraint requires processing sensory signals in a manner that protects information about relevant stimuli from degradation. Such selective processing – or selective attention – is implemented via several mechanisms, including neural gain and changes in tuning properties. However, examining each of these effects in isolation obscures their joint impact on the fidelity of stimulus feature representations by large-scale population codes. Instead, large-scale activity patterns can be used to reconstruct representations of relevant and irrelevant stimuli, providing a holistic understanding about how neuron-level modulations collectively impact stimulus encoding. PMID:25769502
Effect of primordial magnetic field on seeds for large scale structure
Yamazaki, Dai Great; Hanayama, Hidekazu; Ichiki, Kiyotomo; Umezu, Ken-ichi
2006-12-15
Magnetic field plays a very important role in many astronomical phenomena at various scales of the universe. It is no exception in the early universe. Since the energy density, pressure, and tension of the primordial magnetic field affect gravitational collapses of plasma, the formation of seeds for large-scale structures should be influenced by them. Here we numerically investigate the effects of stochastic primordial magnetic field on the seeds of large-scale structures in the universe in detail. We found that the amplitude ratio between the density spectra with and without PMF (vertical bar P(k)/P{sub 0}(k) vertical bar at k>0.2 Mpc{sup -1}) lies between 75% and 130% at present for the range of PMF strengths 0.5nG
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.
Using Web-Based Testing for Large-Scale Assessment.
ERIC Educational Resources Information Center
Hamilton, Laura S.; Klein, Stephen P.; Lorie, William
This paper describes an approach to large-scale assessment that uses tests that are delivered to students over the Internet and that are tailored (adapted) to each student's own level of proficiency. A brief background on large-scale assessment is followed by a description of this new technology and an example. Issues that need to be investigated…
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
Adaptive and Optimal Control of Stochastic Dynamical Systems
2015-09-14
control and stochastic differential games . Stochastic linear-quadratic, continuous time, stochastic control problems are solved for systems with noise...control problems for systems with arbitrary correlated n 15. SUBJECT TERMS Adaptive control, optimal control, stochastic differential games 16. SECURITY...explicit results have been obtained for problems of stochastic control and stochastic differential games . Stochastic linear- quadratic, continuous time
CytoModeler: a tool for bridging large-scale network analysis and dynamic quantitative modeling
Xia, Tian; Van Hemert, John; Dickerson, Julie A.
2011-01-01
Summary: CytoModeler is an open-source Java application based on the Cytoscape platform. It integrates large-scale network analysis and quantitative modeling by combining omics analysis on the Cytoscape platform, access to deterministic and stochastic simulators, and static and dynamic network context visualizations of simulation results. Availability: Implemented in Java, CytoModeler runs with Cytoscape 2.6 and 2.7. Binaries, documentation and video walkthroughs are freely available at http://vrac.iastate.edu/~jlv/cytomodeler/. Contact: julied@iastate.edu; netscape@iastate.edu Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:21511714
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
Organised convection embedded in a large-scale flow
NASA Astrophysics Data System (ADS)
Naumann, Ann Kristin; Stevens, Bjorn; Hohenegger, Cathy
2017-04-01
In idealised simulations of radiative convective equilibrium, convection aggregates spontaneously from randomly distributed convective cells into organized mesoscale convection despite homogeneous boundary conditions. Although these simulations apply very idealised setups, the process of self-aggregation is thought to be relevant for the development of tropical convective systems. One feature that idealised simulations usually neglect is the occurrence of a large-scale background flow. In the tropics, organised convection is embedded in a large-scale circulation system, which advects convection in along-wind direction and alters near surface convergence in the convective areas. A large-scale flow also modifies the surface fluxes, which are expected to be enhanced upwind of the convective area if a large-scale flow is applied. Convective clusters that are embedded in a large-scale flow therefore experience an asymmetric component of the surface fluxes, which influences the development and the pathway of a convective cluster. In this study, we use numerical simulations with explicit convection and add a large-scale flow to the established setup of radiative convective equilibrium. We then analyse how aggregated convection evolves when being exposed to wind forcing. The simulations suggest that convective line structures are more prevalent if a large-scale flow is present and that convective clusters move considerably slower than advection by the large-scale flow would suggest. We also study the asymmetric component of convective aggregation due to enhanced surface fluxes, and discuss the pathway and speed of convective clusters as a function of the large-scale wind speed.
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.
Sparse deconvolution for the large-scale ill-posed inverse problem of impact force reconstruction
NASA Astrophysics Data System (ADS)
Qiao, Baijie; Zhang, Xingwu; Gao, Jiawei; Liu, Ruonan; Chen, Xuefeng
2017-01-01
Most previous regularization methods for solving the inverse problem of force reconstruction are to minimize the l2-norm of the desired force. However, these traditional regularization methods such as Tikhonov regularization and truncated singular value decomposition, commonly fail to solve the large-scale ill-posed inverse problem in moderate computational cost. In this paper, taking into account the sparse characteristic of impact force, the idea of sparse deconvolution is first introduced to the field of impact force reconstruction and a general sparse deconvolution model of impact force is constructed. Second, a novel impact force reconstruction method based on the primal-dual interior point method (PDIPM) is proposed to solve such a large-scale sparse deconvolution model, where minimizing the l2-norm is replaced by minimizing the l1-norm. Meanwhile, the preconditioned conjugate gradient algorithm is used to compute the search direction of PDIPM with high computational efficiency. Finally, two experiments including the small-scale or medium-scale single impact force reconstruction and the relatively large-scale consecutive impact force reconstruction are conducted on a composite wind turbine blade and a shell structure to illustrate the advantage of PDIPM. Compared with Tikhonov regularization, PDIPM is more efficient, accurate and robust whether in the single impact force reconstruction or in the consecutive impact force reconstruction.
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.
Modified gravity and large scale flows, a review
NASA Astrophysics Data System (ADS)
Mould, Jeremy
2017-02-01
Large scale flows have been a challenging feature of cosmography ever since galaxy scaling relations came on the scene 40 years ago. The next generation of surveys will offer a serious test of the standard cosmology.
Learning networks for sustainable, large-scale improvement.
McCannon, C Joseph; Perla, Rocco J
2009-05-01
Large-scale improvement efforts known as improvement networks offer structured opportunities for exchange of information and insights into the adaptation of clinical protocols to a variety of settings.
Amplification of large-scale magnetic field in nonhelical magnetohydrodynamics
NASA Astrophysics Data System (ADS)
Kumar, Rohit; Verma, Mahendra K.
2017-09-01
It is typically assumed that the kinetic and magnetic helicities play a crucial role in the growth of large-scale dynamo. In this paper, we demonstrate that helicity is not essential for the amplification of large-scale magnetic field. For this purpose, we perform nonhelical magnetohydrodynamic (MHD) simulation, and show that the large-scale magnetic field can grow in nonhelical MHD when random external forcing is employed at scale 1/10 the box size. The energy fluxes and shell-to-shell transfer rates computed using the numerical data show that the large-scale magnetic energy grows due to the energy transfers from the velocity field at the forcing scales.
An Adaptive Multiscale Finite Element Method for Large Scale Simulations
2015-09-28
the method . Using the above definitions , the weak statement of the non-linear local problem at the kth 4 DISTRIBUTION A: Distribution approved for...AFRL-AFOSR-VA-TR-2015-0305 An Adaptive Multiscale Finite Element Method for Large Scale Simulations Carlos Duarte UNIVERSITY OF ILLINOIS CHAMPAIGN...14-07-2015 4. TITLE AND SUBTITLE An Adaptive Multiscale Generalized Finite Element Method for Large Scale Simulations 5a. CONTRACT NUMBER 5b
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.
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.
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.
Chaotic dynamics of large-scale structures in a turbulent wake
NASA Astrophysics Data System (ADS)
Varon, Eliott; Eulalie, Yoann; Edwige, Stephie; Gilotte, Philippe; Aider, Jean-Luc
2017-03-01
The dynamics of a three-dimensional (3D) bimodal turbulent wake downstream of a square-back Ahmed body are experimentally studied in a wind tunnel through high-frequency wall-pressure probes mapping the rear of the model and a horizontal two-dimensional (2D) velocity field. The barycenters of the pressure distribution over the rear part of the model and the intensity recirculation are found highly correlated. Both described the most energetic large-scale structures dynamics, confirming the relation between the large-scale recirculation bubble and its wall-pressure footprint. Focusing on the pressure, its barycenter trajectory has a stochastic behavior but its low-frequency dynamics exhibit the same characteristics as a weak strange chaotic attractor system, with two well-defined attractors. The low-frequency dynamics associated to the large-scale structures are then analyzed. The largest Lyapunov exponent is first estimated, leading to a low positive value characteristic of strange attractors and weak chaotic systems. Afterwards, analyzing the autocorrelation function of the timeseries, we compute the correlation dimension, larger than two. The signal is finally transformed and analyzed as a telegraph signal, showing that its dynamics correspond to a quasirandom telegraph signal. This is the first demonstration that the low-frequency dynamics of a turbulent 3D wake are not a purely stochastic process but rather a weak chaotic process exhibiting strange attractors. From the flow control point of view, it also opens the path to more simple closed-loop flow-control strategies aiming at the stabilization of the wake and the control of the dynamics of the wake barycenter.
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.
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
Metabolic network alignment in large scale by network compression.
Ay, Ferhat; Dang, Michael; Kahveci, Tamer
2012-03-21
alignments that are comparable to existing algorithms and can do this with practical resource utilization for large scale networks that existing algorithms could not handle. As an example of our method's performance in practice, the alignment of organism-wide metabolic networks of human (1615 reactions) and mouse (1600 reactions) was performed under three minutes by only using a single level of compression.
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.
Recursive architecture for large-scale adaptive system
NASA Astrophysics Data System (ADS)
Hanahara, Kazuyuki; Sugiyama, Yoshihiko
1994-09-01
'Large scale' is one of major trends in the research and development of recent engineering, especially in the field of aerospace structural system. This term expresses the large scale of an artifact in general, however, it also implies the large number of the components which make up the artifact in usual. Considering a large scale system which is especially used in remote space or deep-sea, such a system should be adaptive as well as robust by itself, because its control as well as maintenance by human operators are not easy due to the remoteness. An approach to realizing this large scale, adaptive and robust system is to build the system as an assemblage of components which are respectively adaptive by themselves. In this case, the robustness of the system can be achieved by using a large number of such components and suitable adaptation as well as maintenance strategies. Such a system gathers many research's interest and their studies such as decentralized motion control, configurating algorithm and characteristics of structural elements are reported. In this article, a recursive architecture concept is developed and discussed towards the realization of large scale system which consists of a number of uniform adaptive components. We propose an adaptation strategy based on the architecture and its implementation by means of hierarchically connected processing units. The robustness and the restoration from degeneration of the processing unit are also discussed. Two- and three-dimensional adaptive truss structures are conceptually designed based on the recursive architecture.
The Influence of Large-scale Environments on Galaxy Properties
NASA Astrophysics Data System (ADS)
Wei, Yu-qing; Wang, Lei; Dai, Cai-ping
2017-07-01
The star formation properties of galaxies and their dependence on environments play an important role for understanding the formation and evolution of galaxies. Using the galaxy sample of the Sloan Digital Sky Survey (SDSS), different research groups have studied the physical properties of galaxies and their large-scale environments. Here, using the filament catalog from Tempel et al. and the galaxy catalog of large-scale structure classification from Wang et al., and taking the influence of the galaxy morphology, high/low local density environment, and central (satellite) galaxy into consideration, we have found that the properties of galaxies are correlated with their residential large-scale environments: the SSFR (specific star formation rate) and SFR (star formation rate) strongly depend on the large-scale environment for spiral galaxies and satellite galaxies, but this dependence is very weak for elliptical galaxies and central galaxies, and the influence of large-scale environments on galaxies in low density region is more sensitive than that in high density region. The above conclusions remain valid even for the galaxies with the same mass. In addition, the SSFR distributions derived from the catalogs of Tempel et al. and Wang et al. are not entirely consistent.
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.
Segment-Based Predominant Learning Swarm Optimizer for Large-Scale Optimization.
Yang, Qiang; Chen, Wei-Neng; Gu, Tianlong; Zhang, Huaxiang; Deng, Jeremiah D; Li, Yun; Zhang, Jun
2016-10-24
Large-scale optimization has become a significant yet challenging area in evolutionary computation. To solve this problem, this paper proposes a novel segment-based predominant learning swarm optimizer (SPLSO) swarm optimizer through letting several predominant particles guide the learning of a particle. First, a segment-based learning strategy is proposed to randomly divide the whole dimensions into segments. During update, variables in different segments are evolved by learning from different exemplars while the ones in the same segment are evolved by the same exemplar. Second, to accelerate search speed and enhance search diversity, a predominant learning strategy is also proposed, which lets several predominant particles guide the update of a particle with each predominant particle responsible for one segment of dimensions. By combining these two learning strategies together, SPLSO evolves all dimensions simultaneously and possesses competitive exploration and exploitation abilities. Extensive experiments are conducted on two large-scale benchmark function sets to investigate the influence of each algorithmic component and comparisons with several state-of-the-art meta-heuristic algorithms dealing with large-scale problems demonstrate the competitive efficiency and effectiveness of the proposed optimizer. Further the scalability of the optimizer to solve problems with dimensionality up to 2000 is also verified.
Deschaine, L.M.
2008-07-01
The global impact to human health and the environment from large scale chemical / radionuclide releases is well documented. Examples are the wide spread release of radionuclides from the Chernobyl nuclear reactors, the mobilization of arsenic in Bangladesh, the formation of Environmental Protection Agencies in the United States, Canada and Europe, and the like. The fiscal costs of addressing and remediating these issues on a global scale are astronomical, but then so are the fiscal and human health costs of ignoring them. An integrated methodology for optimizing the response(s) to these issues is needed. This work addresses development of optimal policy design for large scale, complex, environmental issues. It discusses the development, capabilities, and application of a hybrid system of algorithms that optimizes the environmental response. It is important to note that 'optimization' does not singularly refer to cost minimization, but to the effective and efficient balance of cost, performance, risk, management, and societal priorities along with uncertainty analysis. This tool integrates all of these elements into a single decision framework. It provides a consistent approach to designing optimal solutions that are tractable, traceable, and defensible. The system is modular and scalable. It can be applied either as individual components or in total. By developing the approach in a complex systems framework, a solution methodology represents a significant improvement over the non-optimal 'trial and error' approach to environmental response(s). Subsurface environmental processes are represented by linear and non-linear, elliptic and parabolic equations. The state equations solved using numerical methods include multi-phase flow (water, soil gas, NAPL), and multicomponent transport (radionuclides, heavy metals, volatile organics, explosives, etc.). Genetic programming is used to generate the simulators either when simulation models do not exist, or to extend the
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.
Seismic safety in conducting large-scale blasts
NASA Astrophysics Data System (ADS)
Mashukov, I. V.; Chaplygin, V. V.; Domanov, V. P.; Semin, A. A.; Klimkin, M. A.
2017-09-01
In mining enterprises to prepare hard rocks for excavation a drilling and blasting method is used. With the approach of mining operations to settlements the negative effect of large-scale blasts increases. To assess the level of seismic impact of large-scale blasts the scientific staff of Siberian State Industrial University carried out expertise for coal mines and iron ore enterprises. Determination of the magnitude of surface seismic vibrations caused by mass explosions was performed using seismic receivers, an analog-digital converter with recording on a laptop. The registration results of surface seismic vibrations during production of more than 280 large-scale blasts at 17 mining enterprises in 22 settlements are presented. The maximum velocity values of the Earth’s surface vibrations are determined. The safety evaluation of seismic effect was carried out according to the permissible value of vibration velocity. For cases with exceedance of permissible values recommendations were developed to reduce the level of seismic impact.
PKI security in large-scale healthcare networks.
Mantas, Georgios; Lymberopoulos, Dimitrios; Komninos, Nikos
2012-06-01
During the past few years a lot of PKI (Public Key Infrastructures) infrastructures have been proposed for healthcare networks in order to ensure secure communication services and exchange of data among healthcare professionals. However, there is a plethora of challenges in these healthcare PKI infrastructures. Especially, there are a lot of challenges for PKI infrastructures deployed over large-scale healthcare networks. In this paper, we propose a PKI infrastructure to ensure security in a large-scale Internet-based healthcare network connecting a wide spectrum of healthcare units geographically distributed within a wide region. Furthermore, the proposed PKI infrastructure facilitates the trust issues that arise in a large-scale healthcare network including multi-domain PKI infrastructures.
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.
Large-scale velocity structures in turbulent thermal convection.
Qiu, X L; Tong, P
2001-09-01
A systematic study of large-scale velocity structures in turbulent thermal convection is carried out in three different aspect-ratio cells filled with water. Laser Doppler velocimetry is used to measure the velocity profiles and statistics over varying Rayleigh numbers Ra and at various spatial positions across the whole convection cell. Large velocity fluctuations are found both in the central region and near the cell boundary. Despite the large velocity fluctuations, the flow field still maintains a large-scale quasi-two-dimensional structure, which rotates in a coherent manner. This coherent single-roll structure scales with Ra and can be divided into three regions in the rotation plane: (1) a thin viscous boundary layer, (2) a fully mixed central core region with a constant mean velocity gradient, and (3) an intermediate plume-dominated buffer region. The experiment reveals a unique driving mechanism for the large-scale coherent rotation in turbulent convection.
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.
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.
Large Scale Processes and Extreme Floods in Brazil
NASA Astrophysics Data System (ADS)
Ribeiro Lima, C. H.; AghaKouchak, A.; Lall, U.
2016-12-01
Persistent large scale anomalies in the atmospheric circulation and ocean state have been associated with heavy rainfall and extreme floods in water basins of different sizes across the world. Such studies have emerged in the last years as a new tool to improve the traditional, stationary based approach in flood frequency analysis and flood prediction. Here we seek to advance previous studies by evaluating the dominance of large scale processes (e.g. atmospheric rivers/moisture transport) over local processes (e.g. local convection) in producing floods. We consider flood-prone regions in Brazil as case studies and the role of large scale climate processes in generating extreme floods in such regions is explored by means of observed streamflow, reanalysis data and machine learning methods. The dynamics of the large scale atmospheric circulation in the days prior to the flood events are evaluated based on the vertically integrated moisture flux and its divergence field, which are interpreted in a low-dimensional space as obtained by machine learning techniques, particularly supervised kernel principal component analysis. In such reduced dimensional space, clusters are obtained in order to better understand the role of regional moisture recycling or teleconnected moisture in producing floods of a given magnitude. The convective available potential energy (CAPE) is also used as a measure of local convection activities. We investigate for individual sites the exceedance probability in which large scale atmospheric fluxes dominate the flood process. Finally, we analyze regional patterns of floods and how the scaling law of floods with drainage area responds to changes in the climate forcing mechanisms (e.g. local vs large scale).
Dynamics of large-scale instabilities in conductors electrically exploded in strong magnetic fields
NASA Astrophysics Data System (ADS)
Datsko, I. M.; Chaikovsky, S. A.; Labetskaya, N. A.; Oreshkin, V. I.; Ratakhin, N. A.
2014-11-01
The growth of large-scale instabilities during the propagation of a nonlinear magnetic diffusion wave through a conductor was studied experimentally. The experiment was carried out using the MIG terawatt pulsed power generator at a peak current up to 2.5 MA with 100 ns rise time. It was observed that instabilities with a wavelength of 150 μm developed on the surface of the conductor hollow part within 160 ns after the onset of current flow, whereas the surface of the solid rod remained almost unperturbed. A system of equations describing the propagation of a nonlinear diffusion wave through a conductor and the growth of thermal instabilities has been solved numerically. It has been revealed that the development of large- scale instabilities is obviously related to the propagation of a nonlinear magnetic diffusion wave.
The evolution of large-scale magnetic fields in the ionosphere of Venus
NASA Technical Reports Server (NTRS)
Cravens, T. E.; Shinagawa, H.; Nagy, A. F.
1984-01-01
Large-scale magnetic fields are often observed in the ionosphere of Venus by the magnetometer on the Pioneer Venus Orbiter, especially near the subsolar point or when the solar wind dynamic pressure is high. An equation for the time evolution of the magnetic field is derived which includes both a term representing the time rate of change of the field due to the convection of magnetic flux by plasma motions, and a magnetic diffusion/dissipation term. The ionospheric plasma velocities required by these equations were obtained by numerically solving the momentum equation. Numerical solutions to the magnetic field equation indicate that large-scale magnetic fields, which are not being actively maintained, decay with time scales ranging from tens of minutes to several hours. The vertical convection of magnetic flux enables magnetic field structures deep within the ionosphere to persist longer than would otherwise be expected. This vertical convection also explains the shape of these structures.
NASA Astrophysics Data System (ADS)
Jong Choi, Tae; Ahn, Chang Wook
2017-02-01
A new differential evolution (DE) algorithm is presented in this paper. The proposed algorithm monitors the evolutionary progress of each individual and assigns appropriate control parameters depends on whether the individual is successfully evolved or not. We conducted the performance evaluation on CEC 2014 benchmark problems and confirmed that the proposed algorithm outperformed than the conventional DE algorithm. In addition, we apply the proposed DE algorithm as an optimization technique of training large scale multilayer perceptron. We conducted the performance evaluation on an artificial neural network that has approximately 1,000 weights and confirmed again that the proposed algorithm performed better than the conventional DE algorithm. As a result, we proposed a new DE algorithm that has better optimization performance for solving large-scale global optimization problems.
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.
An inertia-free filter line-search algorithm for large-scale nonlinear programming
Chiang, Nai-Yuan; Zavala, Victor M.
2016-02-15
We present a filter line-search algorithm that does not require inertia information of the linear system. This feature enables the use of a wide range of linear algebra strategies and libraries, which is essential to tackle large-scale problems on modern computing architectures. The proposed approach performs curvature tests along the search step to detect negative curvature and to trigger convexification. We prove that the approach is globally convergent and we implement the approach within a parallel interior-point framework to solve large-scale and highly nonlinear problems. Our numerical tests demonstrate that the inertia-free approach is as efficient as inertia detection via symmetric indefinite factorizations. We also demonstrate that the inertia-free approach can lead to reductions in solution time because it reduces the amount of convexification needed.
[Issues of large scale tissue culture of medicinal plant].
Lv, Dong-Mei; Yuan, Yuan; Zhan, Zhi-Lai
2014-09-01
In order to increase the yield and quality of the medicinal plant and enhance the competitive power of industry of medicinal plant in our country, this paper analyzed the status, problem and countermeasure of the tissue culture of medicinal plant on large scale. Although the biotechnology is one of the most efficient and promising means in production of medicinal plant, it still has problems such as stability of the material, safety of the transgenic medicinal plant and optimization of cultured condition. Establishing perfect evaluation system according to the characteristic of the medicinal plant is the key measures to assure the sustainable development of the tissue culture of medicinal plant on large scale.
The CLASSgal code for relativistic cosmological large scale structure
NASA Astrophysics Data System (ADS)
Di Dio, Enea; Montanari, Francesco; Lesgourgues, Julien; Durrer, Ruth
2013-11-01
We present accurate and efficient computations of large scale structure observables, obtained with a modified version of the CLASS code which is made publicly available. This code includes all relativistic corrections and computes both the power spectrum Cl(z1,z2) and the corresponding correlation function ξ(θ,z1,z2) of the matter density and the galaxy number fluctuations in linear perturbation theory. For Gaussian initial perturbations, these quantities contain the full information encoded in the large scale matter distribution at the level of linear perturbation theory. We illustrate the usefulness of our code for cosmological parameter estimation through a few simple examples.
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 Graph Processing Analysis using Supercomputer Cluster
NASA Astrophysics Data System (ADS)
Vildario, Alfrido; Fitriyani; Nugraha Nurkahfi, Galih
2017-01-01
Graph implementation is widely use in various sector such as automotive, traffic, image processing and many more. They produce graph in large-scale dimension, cause the processing need long computational time and high specification resources. This research addressed the analysis of implementation large-scale graph using supercomputer cluster. We impelemented graph processing by using Breadth-First Search (BFS) algorithm with single destination shortest path problem. Parallel BFS implementation with Message Passing Interface (MPI) used supercomputer cluster at High Performance Computing Laboratory Computational Science Telkom University and Stanford Large Network Dataset Collection. The result showed that the implementation give the speed up averages more than 30 times and eficiency almost 90%.
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
The Evolution of Baryons in Cosmic Large Scale Structure
NASA Astrophysics Data System (ADS)
Snedden, Ali; Arielle Phillips, Lara; Mathews, Grant James; Coughlin, Jared; Suh, In-Saeng; Bhattacharya, Aparna
2015-01-01
The environments of galaxies play a critical role in their formation and evolution. We study these environments using cosmological simulations with star formation and supernova feedback included. From these simulations, we parse the large scale structure into clusters, filaments and voids using a segmentation algorithm adapted from medical imaging. We trace the star formation history, gas phase and metal evolution of the baryons in the intergalactic medium as function of structure. We find that our algorithm reproduces the baryon fraction in the intracluster medium and that the majority of star formation occurs in cold, dense filaments. We present the consequences this large scale environment has for galactic halos and galaxy evolution.
Large scale purification of RNA nanoparticles by preparative ultracentrifugation.
Jasinski, Daniel L; Schwartz, Chad T; Haque, Farzin; Guo, Peixuan
2015-01-01
Purification of large quantities of supramolecular RNA complexes is of paramount importance due to the large quantities of RNA needed and the purity requirements for in vitro and in vivo assays. Purification is generally carried out by liquid chromatography (HPLC), polyacrylamide gel electrophoresis (PAGE), or agarose gel electrophoresis (AGE). Here, we describe an efficient method for the large-scale purification of RNA prepared by in vitro transcription using T7 RNA polymerase by cesium chloride (CsCl) equilibrium density gradient ultracentrifugation and the large-scale purification of RNA nanoparticles by sucrose gradient rate-zonal ultracentrifugation or cushioned sucrose gradient rate-zonal ultracentrifugation.
Robust stochastic optimization for reservoir operation
NASA Astrophysics Data System (ADS)
Pan, Limeng; Housh, Mashor; Liu, Pan; Cai, Ximing; Chen, Xin
2015-01-01
Optimal reservoir operation under uncertainty is a challenging engineering problem. Application of classic stochastic optimization methods to large-scale problems is limited due to computational difficulty. Moreover, classic stochastic methods assume that the estimated distribution function or the sample inflow data accurately represents the true probability distribution, which may be invalid and the performance of the algorithms may be undermined. In this study, we introduce a robust optimization (RO) approach, Iterative Linear Decision Rule (ILDR), so as to provide a tractable approximation for a multiperiod hydropower generation problem. The proposed approach extends the existing LDR method by accommodating nonlinear objective functions. It also provides users with the flexibility of choosing the accuracy of ILDR approximations by assigning a desired number of piecewise linear segments to each uncertainty. The performance of the ILDR is compared with benchmark policies including the sampling stochastic dynamic programming (SSDP) policy derived from historical data. The ILDR solves both the single and multireservoir systems efficiently. The single reservoir case study results show that the RO method is as good as SSDP when implemented on the original historical inflows and it outperforms SSDP policy when tested on generated inflows with the same mean and covariance matrix as those in history. For the multireservoir case study, which considers water supply in addition to power generation, numerical results show that the proposed approach performs as well as in the single reservoir case study in terms of optimal value and distributional robustness.
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..
The fastclime Package for Linear Programming and Large-Scale Precision Matrix Estimation in R
Pang, Haotian; Liu, Han; Vanderbei, Robert
2014-01-01
We develop an R package fastclime for solving a family of regularized linear programming (LP) problems. Our package efficiently implements the parametric simplex algorithm, which provides a scalable and sophisticated tool for solving large-scale linear programs. As an illustrative example, one use of our LP solver is to implement an important sparse precision matrix estimation method called CLIME (Constrained L1 Minimization Estimator). Compared with existing packages for this problem such as clime and flare, our package has three advantages: (1) it efficiently calculates the full piecewise-linear regularization path; (2) it provides an accurate dual certificate as stopping criterion; (3) it is completely coded in C and is highly portable. This package is designed to be useful to statisticians and machine learning researchers for solving a wide range of problems. PMID:25620890
The fastclime Package for Linear Programming and Large-Scale Precision Matrix Estimation in R.
Pang, Haotian; Liu, Han; Vanderbei, Robert
2014-02-01
We develop an R package fastclime for solving a family of regularized linear programming (LP) problems. Our package efficiently implements the parametric simplex algorithm, which provides a scalable and sophisticated tool for solving large-scale linear programs. As an illustrative example, one use of our LP solver is to implement an important sparse precision matrix estimation method called CLIME (Constrained L1 Minimization Estimator). Compared with existing packages for this problem such as clime and flare, our package has three advantages: (1) it efficiently calculates the full piecewise-linear regularization path; (2) it provides an accurate dual certificate as stopping criterion; (3) it is completely coded in C and is highly portable. This package is designed to be useful to statisticians and machine learning researchers for solving a wide range of problems.
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…
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.
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…
Firebrands and spotting ignition in large-scale fires
Eunmo Koo; Patrick J. Pagni; David R. Weise; John P. Woycheese
2010-01-01
Spotting ignition by lofted firebrands is a significant mechanism of fire spread, as observed in many largescale fires. The role of firebrands in fire propagation and the important parameters involved in spot fire development are studied. Historical large-scale fires, including wind-driven urban and wildland conflagrations and post-earthquake fires are given as...
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…
Measurement, Sampling, and Equating Errors in Large-Scale Assessments
ERIC Educational Resources Information Center
Wu, Margaret
2010-01-01
In large-scale assessments, such as state-wide testing programs, national sample-based assessments, and international comparative studies, there are many steps involved in the measurement and reporting of student achievement. There are always sources of inaccuracies in each of the steps. It is of interest to identify the source and magnitude of…
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.
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...
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...
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...
Developing and Understanding Methods for Large-Scale Nonlinear Optimization
2006-07-24
algorithms for large-scale uncon- strained and constrained optimization problems, including limited-memory methods for problems with -2- many thousands...34Published in peer-reviewed journals" E. Eskow, B. Bader, R. Byrd, S. Crivelli, T. Head-Gordon, V. Lamberti and R. Schnabel, "An optimization approach to the
Probabilistic Cuing in Large-Scale Environmental Search
ERIC Educational Resources Information Center
Smith, Alastair D.; Hood, Bruce M.; Gilchrist, Iain D.
2010-01-01
Finding an object in our environment is an important human ability that also represents a critical component of human foraging behavior. One type of information that aids efficient large-scale search is the likelihood of the object being in one location over another. In this study we investigated the conditions under which individuals respond to…
Feasibility of large-scale aquatic microcosms. Final report
Pease, T.; Wyman, R.L.; Logan, D.T.; Logan, C.M.; Lispi, D.R.
1982-02-01
Microcosms have been used to study a number of fundamental ecological principles and more recently to investigate the effects of man-made perturbations on ecosystems. In this report the feasibility of using large-scale microcosms to access aquatic impacts of power generating facilities is evaluated. Aquatic problems of concern to utilities are outlined, and various research approaches, including large and small microcosms, bioassays, and other laboratory experiments, are discussed. An extensive critical review and synthesis of the literature on recent microcosm research, which includes a comparison of the factors influencing physical, chemical, and biological processes in small vs large microcosms and in microcosms vs nature, led the authors to conclude that large-scale microcosms offer several advantages over other study techniques for particular types of problems. A hypothetical large-scale facility simulating a lake ecosystem is presented to illustrate the size, cost, and complexity of such facilities. The rationale for designing a lake-simulating large-scale microcosm is presented.
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…
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…
Research directions in large scale systems and decentralized control
NASA Technical Reports Server (NTRS)
Tenney, R. R.
1980-01-01
Control theory provides a well established framework for dealing with automatic decision problems and a set of techniques for automatic decision making which exploit special structure, but it does not deal well with complexity. The potential exists for combining control theoretic and knowledge based concepts into a unified approach. The elements of control theory are diagrammed, including modern control and large scale systems.
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…
Ecosystem resilience despite large-scale altered hydro climatic conditions
USDA-ARS?s Scientific Manuscript database
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...
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…
Large-Scale Assessments and Educational Policies in Italy
ERIC Educational Resources Information Center
Damiani, Valeria
2016-01-01
Despite Italy's extensive participation in most large-scale assessments, their actual influence on Italian educational policies is less easy to identify. The present contribution aims at highlighting and explaining reasons for the weak and often inconsistent relationship between international surveys and policy-making processes in Italy.…
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…
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 Assessments and Educational Policies in Italy
ERIC Educational Resources Information Center
Damiani, Valeria
2016-01-01
Despite Italy's extensive participation in most large-scale assessments, their actual influence on Italian educational policies is less easy to identify. The present contribution aims at highlighting and explaining reasons for the weak and often inconsistent relationship between international surveys and policy-making processes in Italy.…
Large scale fire whirls: Can their formation be predicted?
J. Forthofer; Bret Butler
2010-01-01
Large scale fire whirls have not traditionally been recognized as a frequent phenomenon on wildland fires. However, there are anecdotal data suggesting that they can and do occur with some regularity. This paper presents a brief summary of this information and an analysis of the causal factors leading to their formation.
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...
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…
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…
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…
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…
Individual Skill Differences and Large-Scale Environmental Learning
ERIC Educational Resources Information Center
Fields, Alexa W.; Shelton, Amy L.
2006-01-01
Spatial skills are known to vary widely among normal individuals. This project was designed to address whether these individual differences are differentially related to large-scale environmental learning from route (ground-level) and survey (aerial) perspectives. Participants learned two virtual environments (route and survey) with limited…
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…
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…
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.
Large-scale Eucalyptus energy farms and power cogeneration
Robert C. Noroña
1983-01-01
A thorough evaluation of all factors possibly affecting a large-scale planting of eucalyptus is foremost in determining the cost effectiveness of the planned operation. Seven basic areas of concern must be analyzed:1. Species Selection 2. Site Preparation 3. Planting 4. Weed Control 5....
Probabilistic Cuing in Large-Scale Environmental Search
ERIC Educational Resources Information Center
Smith, Alastair D.; Hood, Bruce M.; Gilchrist, Iain D.
2010-01-01
Finding an object in our environment is an important human ability that also represents a critical component of human foraging behavior. One type of information that aids efficient large-scale search is the likelihood of the object being in one location over another. In this study we investigated the conditions under which individuals respond to…
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.
The large scale microwave background anisotropy in decaying particle cosmology
Panek, M.
1987-06-01
We investigate the large-scale anisotropy of the microwave background radiation in cosmological models with decaying particles. The observed value of the quadrupole moment combined with other constraints gives an upper limit on the redshift of the decay z/sub d/ < 3-5. 12 refs., 2 figs.
Large-scale search for dark-matter axions
Kinion, D; van Bibber, K
2000-08-30
We review the status of two ongoing large-scale searches for axions which may constitute the dark matter of our Milky Way halo. The experiments are based on the microwave cavity technique proposed by Sikivie, and marks a ''second-generation'' to the original experiments performed by the Rochester-Brookhaven-Fermilab collaboration, and the University of Florida group.
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...
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…
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)…
Large-scale silicon optical switches for optical interconnection
NASA Astrophysics Data System (ADS)
Qiao, Lei; Tang, Weijie; Chu, Tao
2016-11-01
Large-scale optical switches are greatly demanded in building optical interconnections in data centers and high performance computers (HPCs). Silicon optical switches have advantages of being compact and CMOS process compatible, which can be easily monolithically integrated. However, there are difficulties to construct large ports silicon optical switches. One of them is the non-uniformity of the switch units in large scale silicon optical switches, which arises from the fabrication error and causes confusion in finding the unit optimum operation points. In this paper, we proposed a method to detect the optimum operating point in large scale switch with limited build-in power monitors. We also propose methods for improving the unbalanced crosstalk of cross/bar states in silicon electro-optical MZI switches and insertion losses. Our recent progress in large scale silicon optical switches, including 64 × 64 thermal-optical and 32 × 32 electro-optical switches will be introduced. To the best our knowledge, both of them are the largest scale silicon optical switches in their sections, respectively. The switches were fabricated on 340-nm SOI substrates with CMOS 180- nm processes. The crosstalk of the 32 × 32 electro-optic switch was -19.2dB to -25.1 dB, while the value of the 64 × 64 thermal-optic switch was -30 dB to -48.3 dB.
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…
Large-Scale Assessment and English Language Learners with Disabilities
ERIC Educational Resources Information Center
Liu, Kristin K.; Ward, Jenna M.; Thurlow, Martha L.; Christensen, Laurene L.
2017-01-01
This article highlights a set of principles and guidelines, developed by a diverse group of specialists in the field, for appropriately including English language learners (ELLs) with disabilities in large-scale assessments. ELLs with disabilities make up roughly 9% of the rapidly increasing ELL population nationwide. In spite of the small overall…
Large-scale silviculture experiments of western Oregon and Washington.
Nathan J. Poage; Paul D. Anderson
2007-01-01
We review 12 large-scale silviculture experiments (LSSEs) in western Washington and Oregon with which the Pacific Northwest Research Station of the USDA Forest Service is substantially involved. We compiled and arrayed information about the LSSEs as a series of matrices in a relational database, which is included on the compact disc published with this report and...
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…
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…
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…
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 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.
Large-scale screening by the automated Wassermann reaction
Wagstaff, W.; Firth, R.; Booth, J. R.; Bowley, C. C.
1969-01-01
In view of the drawbacks in the use of the Kahn test for large-scale screening of blood donors, mainly those of human error through work overload and fatiguability, an attempt was made to adapt an existing automated complement-fixation technique for this purpose. This paper reports the successful results of that adaptation. PMID:5776559
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…
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…
Large scale structure of the sun's radio corona
NASA Technical Reports Server (NTRS)
Kundu, M. R.
1986-01-01
Results of studies of large scale structures of the corona at long radio wavelengths are presented, using data obtained with the multifrequency radioheliograph of the Clark Lake Radio Observatory. It is shown that features corresponding to coronal streamers and coronal holes are readily apparent in the Clark Lake maps.
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...
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).
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.
Projection-aided videometric method for shape measurement of large-scale bulk material stockpile.
Zhang, Xiaohu; Ou, Jianliang; Yuan, Yun; Shang, Yang; Yu, Qifeng
2011-09-10
Large-scale stockpiles are a common means for the storage of bulk material and their shape measurement is a prerequisite for effective transportation and logistics management. This paper proposes a projection-aided videometric method that is based on stereo vision and makes use of projections and epipolar geometry constraints to solve the correspondence problem. A prototype measuring system was developed that can work in real time and achieve measuring accuracy of 0.71 mm in terms of the flatness deviation and 0.54 mm in terms of the depth error, as proven by the experimental results.
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
Bubble, bubble, flow and Hubble: large scale galaxy flow from cosmological bubble collisions
Larjo, Klaus; Levi, Thomas S. E-mail: tslevi@phas.ubc.ca
2010-08-01
We study large scale structure in the cosmology of Coleman-de Luccia bubble collisions. Within a set of controlled approximations we calculate the effects on galaxy motion seen from inside a bubble which has undergone such a collision. We find that generically bubble collisions lead to a coherent bulk flow of galaxies on some part of our sky, the details of which depend on the initial conditions of the collision and redshift to the galaxy in question. With other parameters held fixed the effects weaken as the amount of inflation inside our bubble grows, but can produce measurable flows past the number of efolds required to solve the flatness and horizon 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.
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.
1987-10-01
AUTHOR(*) S. CONTRACT OR GRANT NUMBER(*) Richard L. Henneman and William B. Rouse MDA903-2- C -Ol45 9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM...n measure Qf c Rlity. The literature review [ Henneman and I’ Rouse 1986] also suggested that an appropriate dependent measure of complexity is the... Henneman , R.L., and W.B. Rouse. Measures of human performance in fault diagnosis tasks. j= Kansactions on Sysems, Man and C .7Xkiat i’. its, SMC-14, (1):99
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…
Models and Algorithms Involving Very Large Scale Stochastic Mixed-Integer Programs
2011-02-28
give rise to a non - convex and discontinuous recourse function that may be difficult to optimize . As a result of this project, there have been... convex , the master problem in (3.1.6)-(3.1.9) is a non - convex mixed-integer program, and as indicated in [C.1], this approach is not scalable without...the first stage would result in a Benders’ master program which is non - convex , leading to a problem that is not any easier than (3.1.5). Nevertheless
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.
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.
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.
Stochastic inflation lattice simulations: Ultra-large scale structure of the universe
Salopek, D.S.
1990-11-01
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 {alpha}{sup {minus}1} {triangledown} 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-Guassian. This example illuminates non-Gaussian models involving multiple scalar fields which are consistent with current microwave background limits. 21 refs., 3 figs.
Using large scale structure to measure fNL , gNL and τNL
NASA Astrophysics Data System (ADS)
Ferraro, Simone; Smith, Kendrick M.
2015-02-01
Primordial non-Gaussianity of local type is known to produce a scale-dependent contribution to the galaxy bias. Several classes of multifield inflationary models predict non-Gaussian bias which is stochastic, in the sense that dark matter and halos do not trace each other perfectly on large scales. In this work, we forecast the ability of next-generation large-scale structure surveys to constrain common types of primordial non-Gaussianity like fNL, gNL and τNL using halo bias, including stochastic contributions. We provide fitting functions for statistical errors on these parameters which can be used for rapid forecasting or survey optimization. A next-generation survey with volume V =25 h-3 Gpc3 , median redshift z =0.7 and mean bias bg=2.5 can achieve σ (fNL)=6 , σ (gNL)=105 and σ (τNL)=103 if no mass information is available. If halo masses are available, we show that optimally weighting the halo field in order to reduce sample variance can achieve σ (fNL)=1.5 , σ (gNL)=104 and σ (τNL)=100 if halos with mass down to Mmin=1011h-1M⊙ are resolved, outperforming Planck by a factor of 4 on fNL and nearly an order of magnitude on gNL and τNL. Finally, we study the effect of photometric redshift errors and discuss degeneracies between different non-Gaussian parameters, as well as the impact of marginalizing Gaussian bias and shot noise.
Primordial non-Gaussianity in the bispectra of large-scale structure
Tasinato, Gianmassimo; Tellarini, Matteo; Ross, Ashley J.; Wands, David E-mail: matteo.tellarini@port.ac.uk E-mail: david.wands@port.ac.uk
2014-03-01
The statistics of large-scale structure in the Universe can be used to probe non-Gaussianity of the primordial density field, complementary to existing constraints from the cosmic microwave background. In particular, the scale dependence of halo bias, which affects the halo distribution at large scales, represents a promising tool for analyzing primordial non-Gaussianity of local form. Future observations, for example, may be able to constrain the trispectrum parameter g{sub NL} that is difficult to study and constrain using the CMB alone. We investigate how galaxy and matter bispectra can distinguish between the two non-Gaussian parameters f{sub NL} and g{sub NL}, whose effects give nearly degenerate contributions to the power spectra. We use a generalization of the univariate bias approach, making the hypothesis that the number density of halos forming at a given position is a function of the local matter density contrast and of its local higher-order statistics. Using this approach, we calculate the halo-matter bispectra and analyze their properties. We determine a connection between the sign of the halo bispectrum on large scales and the parameter g{sub NL}. We also construct a combination of halo and matter bispectra that is sensitive to f{sub NL}, with little contamination from g{sub NL}. We study both the case of single and multiple sources to the primordial gravitational potential, discussing how to extend the concept of stochastic halo bias to the case of bispectra. We use a specific halo mass-function to calculate numerically the bispectra in appropriate squeezed limits, confirming our theoretical findings.
NASA Astrophysics Data System (ADS)
Nogaret, Alain; Meliza, C. Daniel; Margoliash, Daniel; Abarbanel, Henry D. I.
2016-09-01
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.
Numerical study of large-scale vorticity generation in shear-flow turbulence.
Käpylä, Petri J; Mitra, Dhrubaditya; Brandenburg, Axel
2009-01-01
Simulations of stochastically forced shear-flow turbulence in a shearing-periodic domain are used to study the spontaneous generation of large-scale flow patterns in the direction perpendicular to the plane of the shear. Based on an analysis of the resulting large-scale velocity correlations it is argued that the mechanism behind this phenomenon could be the mean-vorticity dynamo effect pioneered by Elperin, Kleeorin, and Rogachevskii [Phys. Rev. E 68, 016311 (2003)]. This effect is based on the anisotropy of the eddy viscosity tensor. One of its components may be able to replenish cross-stream mean flows by acting upon the streamwise component of the mean flow. Shear, in turn, closes the loop by acting upon the cross-stream mean flow to produce stronger streamwise mean flows. The diagonal component of the eddy viscosity is found to be of the order of the rms turbulent velocity divided by the wave number of the energy-carrying eddies.
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
Isospin symmetry breaking and large-scale shell-model calculations with the Sakurai-Sugiura method
NASA Astrophysics Data System (ADS)
Mizusaki, Takahiro; Kaneko, Kazunari; Sun, Yang; Tazaki, Shigeru
2015-05-01
Recently isospin symmetry breaking for mass 60-70 region has been investigated based on large-scale shell-model calculations in terms of mirror energy differences (MED), Coulomb energy differences (CED) and triplet energy differences (TED). Behind these investigations, we have encountered a subtle problem in numerical calculations for odd-odd N = Z nuclei with large-scale shell-model calculations. Here we focus on how to solve this subtle problem by the Sakurai-Sugiura (SS) method, which has been recently proposed as a new diagonalization method and has been successfully applied to nuclear shell-model calculations.
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.
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
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.
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.
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
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.
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.
Large-scale linear nonparallel support vector machine solver.
Tian, Yingjie; Ping, Yuan
2014-02-01
Twin support vector machines (TWSVMs), as the representative nonparallel hyperplane classifiers, have shown the effectiveness over standard SVMs from some aspects. However, they still have some serious defects restricting their further study and real applications: (1) They have to compute and store the inverse matrices before training, it is intractable for many applications where data appear with a huge number of instances as well as features; (2) TWSVMs lost the sparseness by using a quadratic loss function making the proximal hyperplane close enough to the class itself. This paper proposes a Sparse Linear Nonparallel Support Vector Machine, termed as L1-NPSVM, to deal with large-scale data based on an efficient solver-dual coordinate descent (DCD) method. Both theoretical analysis and experiments indicate that our method is not only suitable for large scale problems, but also performs as good as TWSVMs and SVMs.
NASA Technical Reports Server (NTRS)
Swanson, Gregory T.; Cassell, Alan M.
2011-01-01
Hypersonic Inflatable Aerodynamic Decelerator (HIAD) technology is currently being considered for multiple atmospheric entry applications as the limitations of traditional entry vehicles have been reached. The Inflatable Re-entry Vehicle Experiment (IRVE) has successfully demonstrated this technology as a viable candidate with a 3.0 m diameter vehicle sub-orbital flight. To further this technology, large scale HIADs (6.0 8.5 m) must be developed and tested. To characterize the performance of large scale HIAD technology new instrumentation concepts must be developed to accommodate the flexible nature inflatable aeroshell. Many of the concepts that are under consideration for the HIAD FY12 subsonic wind tunnel test series are discussed below.
Long gradient mode and large-scale structure observables
NASA Astrophysics Data System (ADS)
Allahyari, Alireza; Firouzjaee, Javad T.
2017-03-01
We extend the study of long-mode perturbations to other large-scale observables such as cosmic rulers, galaxy-number counts, and halo bias. The long mode is a pure gradient mode that is still outside an observer's horizon. We insist that gradient-mode effects on observables vanish. It is also crucial that the expressions for observables are relativistic. This allows us to show that the effects of a gradient mode on the large-scale observables vanish identically in a relativistic framework. To study the potential modulation effect of the gradient mode on halo bias, we derive a consistency condition to the first order in gradient expansion. We find that the matter variance at a fixed physical scale is not modulated by the long gradient mode perturbations when the consistency condition holds. This shows that the contribution of long gradient modes to bias vanishes in this framework.
LARGE SCALE PURIFICATION OF PROTEINASES FROM CLOSTRIDIUM HISTOLYTICUM FILTRATES
Conklin, David A.; Webster, Marion E.; Altieri, Patricia L.; Berman, Sanford; Lowenthal, Joseph P.; Gochenour, Raymond B.
1961-01-01
Conklin, David A. (Walter Reed Army Institute of Research, Washington, D. C.), Marion E. Webster, Patricia L. Altieri, Sanford Berman, Joseph P. Lowenthal, and Raymond B. Gochenour. Large scale purification of proteinases from Clostridium histolyticum filtrates. J. Bacteriol. 82:589–594. 1961.—A method for the large scale preparation and partial purification of Clostridium histolyticum proteinases by fractional precipitation with ammonium sulfate is described. Conditions for adequate separation and purification of the δ-proteinase and the gelatinase were obtained. Collagenase, on the other hand, was found distributed in four to five fractions and little increase in purity was achieved as compared to the crude ammonium sulfate precipitates. PMID:13880849
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
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 MOTIONS IN THE PERSEUS GALAXY CLUSTER
Simionescu, A.; Werner, N.; Urban, O.; Allen, S. W.; Fabian, A. C.; Sanders, J. S.; Mantz, A.; Nulsen, P. E. J.; Takei, Y.
2012-10-01
By combining large-scale mosaics of ROSAT PSPC, XMM-Newton, and Suzaku X-ray observations, we present evidence for large-scale motions in the intracluster medium of the nearby, X-ray bright Perseus Cluster. These motions are suggested by several alternating and interleaved X-ray bright, low-temperature, low-entropy arcs located along the east-west axis, at radii ranging from {approx}10 kpc to over a Mpc. Thermodynamic features qualitatively similar to these have previously been observed in the centers of cool-core clusters, and were successfully modeled as a consequence of the gas sloshing/swirling motions induced by minor mergers. Our observations indicate that such sloshing/swirling can extend out to larger radii than previously thought, on scales approaching the virial radius.
The CLASSgal code for relativistic cosmological large scale structure
Dio, Enea Di; Montanari, Francesco; Durrer, Ruth; Lesgourgues, Julien E-mail: Francesco.Montanari@unige.ch E-mail: Ruth.Durrer@unige.ch
2013-11-01
We present accurate and efficient computations of large scale structure observables, obtained with a modified version of the CLASS code which is made publicly available. This code includes all relativistic corrections and computes both the power spectrum C{sub ℓ}(z{sub 1},z{sub 2}) and the corresponding correlation function ξ(θ,z{sub 1},z{sub 2}) of the matter density and the galaxy number fluctuations in linear perturbation theory. For Gaussian initial perturbations, these quantities contain the full information encoded in the large scale matter distribution at the level of linear perturbation theory. We illustrate the usefulness of our code for cosmological parameter estimation through a few simple examples.
Turbulent amplification of large-scale magnetic fields
NASA Technical Reports Server (NTRS)
Montgomery, D.; Chen, H.
1984-01-01
Previously-introduced methods for analytically estimating the effects of small-scale turbulent fluctuations on large-scale dynamics are extended to fully three-dimensional magnetohydrodynamics. The problem becomes algebraically tractable in the presence of sufficiently large spectral gaps. The calculation generalizes 'alpha dynamo' calculations, except that the velocity fluctuations and magnetic fluctuations are treated on an independent and equal footing. Earlier expressions for the 'alpha coefficients' of turbulent magnetic field amplification are recovered as a special case.
Concurrent Programming Using Actors: Exploiting Large-Scale Parallelism,
1985-10-07
ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK* Artificial Inteligence Laboratory AREA Is WORK UNIT NUMBERS 545 Technology Square...D-R162 422 CONCURRENT PROGRMMIZNG USING f"OS XL?ITP TEH l’ LARGE-SCALE PARALLELISH(U) NASI AC E Al CAMBRIDGE ARTIFICIAL INTELLIGENCE L. G AGHA ET AL...RESOLUTION TEST CHART N~ATIONAL BUREAU OF STANDA.RDS - -96 A -E. __ _ __ __’ .,*- - -- •. - MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL
Host Immunity via Mutable Virtualized Large-Scale Network Containers
2016-07-25
migrate to different IP addresses multiple 6mes. We implement a virtual machine based system prototype and evaluate it using state-of-the-a1t scanning...entire !Pv4 address space within 5 Host Immunity via Mutable Virtualized Large-Scale Network Containers 45 minutes from a single machine . Second, when...that the attacker will be trapped into one decoy instead of the real server. We implement a virtual machine (VM)-based prototype that integrates
Developing and Understanding Methods for Large Scale Nonlinear Optimization
2001-12-01
development of new algorithms for large-scale uncon- strained and constrained optimization problems, including limited-memory methods for problems with...analysis of tensor and SQP methods for singular con- strained optimization", to appear in SIAM Journal on Optimization. Published in peer-reviewed...Mathematica, Vol III, Journal der Deutschen Mathematiker-Vereinigung, 1998. S. Crivelli, B. Bader, R. Byrd, E. Eskow, V. Lamberti , R.Schnabel and T
Wiggly cosmic strings, neutrinos and large-scale structure
NASA Astrophysics Data System (ADS)
Vachaspati, Tanmay
1993-04-01
We discuss the cosmic string scenario of large-scale structure formation in light of the result that the strings are not smooth but instead have a lot of sub-structure or wiggles on them. It appears from the results of Albrecht and Stebbins that the scenario works best if the universe is dominated by massive neutrinos or some other form of hot dark matter. Some unique features of the scenario, such as the generation of primordial magnetic fields, are also described.
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.
Multimodel Design of Large Scale Systems with Multiple Decision Makers.
1982-08-01
virtue. 5- , Lead me from darkneu to light. - Lead me from death to eternal Life. ( Vedic Payer) p. I, MULTIMODEL DESIGN OF LARGE SCALE SYSTEMS WITH...guidance during the course of *: this research . He would also like to thank Professors W. R. Perkins, P. V. Kokotovic, T. Basar, and T. N. Trick for...thesis concludes with Chapter 7 where we summarize the results obtained, outline the main contributions, and indicate directions for future research . 7- I
Critical Problems in Very Large Scale Computer Systems
1990-03-31
MAY I i9cu( CRITICAL PROBLEMS IN VERY LARGE SCALE COMPUTER SYSTEMS Semiannual Technical Report for the Period October 1, 1989 to...suitability for supporting popular models of parallel computation . During the reporting period they have developed an interface definition. A simulator has...queries in computational geometry . Range queries are a fundamental problem in computational geometry with applications to computer graphics and
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.
Large Scale Airflow Perturbations and Resultant Dune Dynamics
NASA Astrophysics Data System (ADS)
Smith, Alexander B.; Jackson, Derek W. T.; Cooper, J. Andrew G.; Beyers, Meiring
2017-04-01
Large-scale atmospheric turbulence can have a large impact on the regional wind regime effecting dune environments. Depending on the incident angle of mesoscale airflow, local topographic steering can also alter wind conditions and subsequent aeolian dynamics. This research analyses the influence of large-scale airflow perturbations occurring at the Maspalomas dunefield located on the southern coast of Gran Canaria, Spain. These perturbations in turn significantly influence the morphometry and migration rates of barchan dunes, monitored at the study site through time. The main meteorological station on Gran Canaria records highly uni-modal NNE wind conditions; however, simultaneously measured winds are highly variable around the island, showing a high degree of steering. Large Eddy Simulations (LES) were used to identify large-scale airflow perturbations around the island of Gran Canaria during NNE, N, and NNW incident flow directions. Results indicate that approaching surface airflow bifurcates around the island's coastline before converging at the lee coast. Winds in areas located around the islands lateral coast are controlled by these diverging flow patterns, whereas lee-side areas are influenced primarily by the islands upwind canyon topography leading to highly turbulent flow. Characteristic turbulent eddies show a complex wind environment at Maspalomas with winds diverging-converging up to 180° between the eastern and western sections of the dunefield. Multi-directional flow conditions lead to highly altered dune dynamics including the production of temporary slip faces on the stoss slopes, rapid reduction in crest height and slope length, and development of bi-crested dunes. This indicates a distinct bi-modality of airflow conditions that control the geomorphic evolution of the dunefield. Variability in wind conditions is not evident in the long-term meteorological records on the island, indicating the significance of large scale atmospheric steering on
A Holistic Management Architecture for Large-Scale Adaptive Networks
2007-09-01
MANAGEMENT ARCHITECTURE FOR LARGE-SCALE ADAPTIVE NETWORKS by Michael R. Clement September 2007 Thesis Advisor: Alex Bordetsky Second Reader...TECHNOLOGY MANAGEMENT from the NAVAL POSTGRADUATE SCHOOL September 2007 Author: Michael R. Clement Approved by: Dr. Alex ...achieve in life is by His will. Ad Majorem Dei Gloriam. To my parents, my family, and Caitlin: For supporting me, listening to me when I got
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.
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
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.
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 Density Estimation of Blue and Fin Whales (LSD)
2014-09-30
1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Large Scale Density Estimation of Blue and Fin Whales ...estimating blue and fin whale density that is effective over large spatial scales and is designed to cope with spatial variation in animal density utilizing...a density estimation methodology for quantifying blue and fin whale abundance from passive acoustic data recorded on sparse hydrophone arrays in the
Large-scale controls on convective extreme precipitation
NASA Astrophysics Data System (ADS)
Loriaux, Jessica M.; Lenderink, Geert; Pier Siebesma, A.
2017-04-01
The influence of large-scale conditions on extreme precipitation is not yet understood well enough. We will present the results of Loriaux et al. (2017), in which we investigate the role of large-scale dynamics and environmental conditions on precipitation and on the precipitation response to climate change. To this end, we have set up a composite LES case for convective precipitation using strong large-scale forcing based on idealized profiles for the highest 10 percentiles of peak intensities over the Netherlands, as described by Loriaux et al. (2016). In this setting, we have performed sensitivity analyses for atmospheric stability, large-scale moisture convergence, and relative humidity, and compared present-day climate to a warmer future climate. The results suggest that amplification of the moisture convergence and destabilization of the atmosphere both lead to an increase in precipitation, but due to different effects; Atmospheric stability mainly influences the precipitation intensity, while the moisture convergence mainly controls the precipitation area fraction. Extreme precipitation intensities show qualitatively similar sensitivities to atmospheric stability and moisture convergence. Precipitation increases with RH due to an increase in area fraction, despite a decrease in intensity. The precipitation response to the climate perturbation shows a stronger response for the precipitation intensity than the overall precipitation, with no clear dependency of changes in atmospheric stability, moisture convergence and relative humidity. The difference in response between the precipitation intensity and overall precipitation is caused by a decrease in the precipitation area fraction from present-day to future climate. In other words, our climate perturbation indicates that with warming, it will rain more intensely but in less places. Loriaux, J.M., G. Lenderink, and A.P. Siebesma, 2016, doi: 10.1002/2015JD024274 Loriaux, J.M., G. Lenderink, and A.P. Siebesma
On a Game of Large-Scale Projects Competition
NASA Astrophysics Data System (ADS)
Nikonov, Oleg I.; Medvedeva, Marina A.
2009-09-01
The paper is devoted to game-theoretical control problems motivated by economic decision making situations arising in realization of large-scale projects, such as designing and putting into operations the new gas or oil pipelines. A non-cooperative two player game is considered with payoff functions of special type for which standard existence theorems and algorithms for searching Nash equilibrium solutions are not applicable. The paper is based on and develops the results obtained in [1]-[5].
Measuring large scale space perception in literary texts
NASA Astrophysics Data System (ADS)
Rossi, Paolo
2007-07-01
A center and radius of “perception” (in the sense of environmental cognition) can be formally associated with a written text and operationally defined. Simple algorithms for their computation are presented, and indicators for anisotropy in large scale space perception are introduced. The relevance of these notions for the analysis of literary and historical records is briefly discussed and illustrated with an example taken from medieval historiography.
Semantic Concept Discovery for Large Scale Zero Shot Event Detection
2015-07-25
NO. 0704-0188 3. DATES COVERED (From - To) - UU UU UU UU 18-08-2015 Approved for public release; distribution is unlimited. Semantic Concept Discovery ...Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 zero shot event detection, semantic concept discovery REPORT DOCUMENTATION PAGE 11...Mellon University 5000 Forbes Avenue Pittsburgh, PA 15213 -3815 ABSTRACT Semantic Concept Discovery for Large-Scale Zero-Shot Event Detection Report
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.
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.
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
Large-scale quantization from local correlations in space plasmas
NASA Astrophysics Data System (ADS)
Livadiotis, George; McComas, David J.
2014-05-01
This study examines the large-scale quantization that can characterize the phase space of certain physical systems. Plasmas are such systems where large-scale quantization, ħ*, is caused by Debye shielding that structures correlations between particles. The value of ħ* is constant—some 12 orders of magnitude larger than the Planck constant—across a wide range of space plasmas, from the solar wind in the inner heliosphere to the distant plasma in the inner heliosheath and the local interstellar medium. This paper develops the foundation and advances the understanding of the concept of plasma quantization; in particular, we (i) show the analogy of plasma to Planck quantization, (ii) show the key points of plasma quantization, (iii) construct some basic quantum mechanical concepts for the large-scale plasma quantization, (iv) investigate the correlation between plasma parameters that implies plasma quantization, when it is approximated by a relation between the magnetosonic energy and the plasma frequency, (v) analyze typical space plasmas throughout the heliosphere and show the constancy of plasma quantization over many orders of magnitude in plasma parameters, (vi) analyze Advanced Composition Explorer (ACE) solar wind measurements to develop another measurement of the value of ħ*, and (vii) apply plasma quantization to derive unknown plasma parameters when some key observable is missing.
Large-scale investigation of genomic markers for severe periodontitis.
Suzuki, Asami; Ji, Guijin; Numabe, Yukihiro; Ishii, Keisuke; Muramatsu, Masaaki; Kamoi, Kyuichi
2004-09-01
The purpose of the present study was to investigate the genomic markers for periodontitis, using large-scale single-nucleotide polymorphism (SNP) association studies comparing healthy volunteers and patients with periodontitis. Genomic DNA was obtained from 19 healthy volunteers and 22 patients with severe periodontitis, all of whom were Japanese. The subjects were genotyped at 637 SNPs in 244 genes on a large scale, using the TaqMan polymerase chain reaction (PCR) system. Statistically significant differences in allele and genotype frequencies were analyzed with Fisher's exact test. We found statistically significant differences (P < 0.01) between the healthy volunteers and patients with severe periodontitis in the following genes; gonadotropin-releasing hormone 1 (GNRH1), phosphatidylinositol 3-kinase regulatory 1 (PIK3R1), dipeptidylpeptidase 4 (DPP4), fibrinogen-like 2 (FGL2), and calcitonin receptor (CALCR). These results suggest that SNPs in the GNRH1, PIK3R1, DPP4, FGL2, and CALCR genes are genomic markers for severe periodontitis. Our findings indicate the necessity of analyzing SNPs in genes on a large scale (i.e., genome-wide approach), to identify genomic markers for periodontitis.
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.
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).
A model of plasma heating by large-scale flow
NASA Astrophysics Data System (ADS)
Pongkitiwanichakul, P.; Cattaneo, F.; Boldyrev, S.; Mason, J.; Perez, J. C.
2015-12-01
In this work, we study the process of energy dissipation triggered by a slow large-scale motion of a magnetized conducting fluid. Our consideration is motivated by the problem of heating the solar corona, which is believed to be governed by fast reconnection events set off by the slow motion of magnetic field lines anchored in the photospheric plasma. To elucidate the physics governing the disruption of the imposed laminar motion and the energy transfer to small scales, we propose a simplified model where the large-scale motion of magnetic field lines is prescribed not at the footpoints but rather imposed volumetrically. As a result, the problem can be treated numerically with an efficient, highly accurate spectral method, allowing us to use a resolution and statistical ensemble exceeding those of the previous work. We find that, even though the large-scale deformations are slow, they eventually lead to reconnection events that drive a turbulent state at smaller scales. The small-scale turbulence displays many of the universal features of field-guided magnetohydrodynamic turbulence like a well-developed inertial range spectrum. Based on these observations, we construct a phenomenological model that gives the scalings of the amplitude of the fluctuations and the energy-dissipation rate as functions of the input parameters. We find good agreement between the numerical results and the predictions of the model.
Large-scale biodiversity patterns in freshwater phytoplankton.
Stomp, Maayke; Huisman, Jef; Mittelbach, Gary G; Litchman, Elena; Klausmeier, Christopher A
2011-11-01
Our planet shows striking gradients in the species richness of plants and animals, from high biodiversity in the tropics to low biodiversity in polar and high-mountain regions. Recently, similar patterns have been described for some groups of microorganisms, but the large-scale biogeographical distribution of freshwater phytoplankton diversity is still largely unknown. We examined the species diversity of freshwater phytoplankton sampled from 540 lakes and reservoirs distributed across the continental United States and found strong latitudinal, longitudinal, and altitudinal gradients in phytoplankton biodiversity, demonstrating that microorganisms can show substantial geographic variation in biodiversity. Detailed analysis using structural equation models indicated that these large-scale biodiversity gradients in freshwater phytoplankton diversity were mainly driven by local environmental factors, although there were residual direct effects of latitude, longitude, and altitude as well. Specifically, we found that phytoplankton species richness was an increasing saturating function of lake chlorophyll a concentration, increased with lake surface area and possibly increased with water temperature, resembling effects of productivity, habitat area, and temperature on diversity patterns commonly observed for macroorganisms. In turn, these local environmental factors varied along latitudinal, longitudinal, and altitudinal gradients. These results imply that changes in land use or climate that affect these local environmental factors are likely to have major impacts on large-scale biodiversity patterns of freshwater phytoplankton.
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.
Channel capacity of next generation large scale MIMO systems
NASA Astrophysics Data System (ADS)
Alshammari, A.; Albdran, S.; Matin, M.
2016-09-01
Information rate that can be transferred over a given bandwidth is limited by the information theory. Capacity depends on many factors such as the signal to noise ratio (SNR), channel state information (CSI) and the spatial correlation in the propagation environment. It is very important to increase spectral efficiency in order to meet the growing demand for wireless services. Thus, Multiple input multiple output (MIMO) technology has been developed and applied in most of the wireless standards and it has been very successful in increasing capacity and reliability. As the demand is still increasing, attention now is shifting towards large scale multiple input multiple output (MIMO) which has a potential of bringing orders of magnitude of improvement in spectral and energy efficiency. It has been shown that users channels decorrelate after increasing the number of antennas. As a result, inter-user interference can be avoided since energy can be focused on precise directions. This paper investigates the limits of channel capacity for large scale MIMO. We study the relation between spectral efficiency and the number of antenna N. We use time division duplex (TDD) system in order to obtain CSI using training sequence in the uplink. The same CSI is used for the downlink because the channel is reciprocal. Spectral efficiency is measured for channel model that account for small scale fading while ignoring the effect of large scale fading. It is shown the spectral efficiency can be improved significantly when compared to single antenna systems in ideal circumstances.
Sparse approximation through boosting for learning large scale kernel machines.
Sun, Ping; Yao, Xin
2010-06-01
Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subset of original data points also known as basis vectors, which are usually chosen one by one with a forward selection procedure based on some selection criteria. The computational complexity of several resultant algorithms scales as O(NM(2)) in time and O(NM) in memory, where N is the number of training points and M is the number of basis vectors as well as the steps of forward selection. For some large scale data sets, to obtain a better solution, we are sometimes required to include more basis vectors, which means that M is not trivial in this situation. However, the limited computational resource (e.g., memory) prevents us from including too many vectors. To handle this dilemma, we propose to add an ensemble of basis vectors instead of only one at each forward step. The proposed method, closely related to gradient boosting, could decrease the required number M of forward steps significantly and thus a large fraction of computational cost is saved. Numerical experiments on three large scale regression tasks and a classification problem demonstrate the effectiveness of the proposed approach.
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.
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.
[A large-scale accident in Alpine terrain].
Wildner, M; Paal, P
2015-02-01
Due to the geographical conditions, large-scale accidents amounting to mass casualty incidents (MCI) in Alpine terrain regularly present rescue teams with huge challenges. Using an example incident, specific conditions and typical problems associated with such a situation are presented. The first rescue team members to arrive have the elementary tasks of qualified triage and communication to the control room, which is required to dispatch the necessary additional support. Only with a clear "concept", to which all have to adhere, can the subsequent chaos phase be limited. In this respect, a time factor confounded by adverse weather conditions or darkness represents enormous pressure. Additional hazards are frostbite and hypothermia. If priorities can be established in terms of urgency, then treatment and procedure algorithms have proven successful. For evacuation of causalities, a helicopter should be strived for. Due to the low density of hospitals in Alpine regions, it is often necessary to distribute the patients over a wide area. Rescue operations in Alpine terrain have to be performed according to the particular conditions and require rescue teams to have specific knowledge and expertise. The possibility of a large-scale accident should be considered when planning events. With respect to optimization of rescue measures, regular training and exercises are rational, as is the analysis of previous large-scale Alpine accidents.
Large scale structure in universes dominated by cold dark matter
NASA Technical Reports Server (NTRS)
Bond, J. Richard
1986-01-01
The theory of Gaussian random density field peaks is applied to a numerical study of the large-scale structure developing from adiabatic fluctuations in models of biased galaxy formation in universes with Omega = 1, h = 0.5 dominated by cold dark matter (CDM). The angular anisotropy of the cross-correlation function demonstrates that the far-field regions of cluster-scale peaks are asymmetric, as recent observations indicate. These regions will generate pancakes or filaments upon collapse. One-dimensional singularities in the large-scale bulk flow should arise in these CDM models, appearing as pancakes in position space. They are too rare to explain the CfA bubble walls, but pancakes that are just turning around now are sufficiently abundant and would appear to be thin walls normal to the line of sight in redshift space. Large scale streaming velocities are significantly smaller than recent observations indicate. To explain the reported 700 km/s coherent motions, mass must be significantly more clustered than galaxies with a biasing factor of less than 0.4 and a nonlinear redshift at cluster scales greater than one for both massive neutrino and cold models.
Learning Short Binary Codes for Large-scale Image Retrieval.
Liu, Li; Yu, Mengyang; Shao, Ling
2017-03-01
Large-scale visual information retrieval has become an active research area in this big data era. Recently, hashing/binary coding algorithms prove to be effective for scalable retrieval applications. Most existing hashing methods require relatively long binary codes (i.e., over hundreds of bits, sometimes even thousands of bits) to achieve reasonable retrieval accuracies. However, for some realistic and unique applications, such as on wearable or mobile devices, only short binary codes can be used for efficient image retrieval due to the limitation of computational resources or bandwidth on these devices. In this paper, we propose a novel unsupervised hashing approach called min-cost ranking (MCR) specifically for learning powerful short binary codes (i.e., usually the code length shorter than 100 b) for scalable image retrieval tasks. By exploring the discriminative ability of each dimension of data, MCR can generate one bit binary code for each dimension and simultaneously rank the discriminative separability of each bit according to the proposed cost function. Only top-ranked bits with minimum cost-values are then selected and grouped together to compose the final salient binary codes. Extensive experimental results on large-scale retrieval demonstrate that MCR can achieve comparative performance as the state-of-the-art hashing algorithms but with significantly shorter codes, leading to much faster large-scale retrieval.
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. Copyright © 2015 Elsevier Inc. All rights reserved.
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.
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.
Alteration of Large-Scale Chromatin Structure by Estrogen Receptor
Nye, Anne C.; Rajendran, Ramji R.; Stenoien, David L.; Mancini, Michael A.; Katzenellenbogen, Benita S.; Belmont, Andrew S.
2002-01-01
The estrogen receptor (ER), a member of the nuclear hormone receptor superfamily important in human physiology and disease, recruits coactivators which modify local chromatin structure. Here we describe effects of ER on large-scale chromatin structure as visualized in live cells. We targeted ER to gene-amplified chromosome arms containing large numbers of lac operator sites either directly, through a lac repressor-ER fusion protein (lac rep-ER), or indirectly, by fusing lac repressor with the ER interaction domain of the coactivator steroid receptor coactivator 1. Significant decondensation of large-scale chromatin structure, comparable to that produced by the ∼150-fold-stronger viral protein 16 (VP16) transcriptional activator, was produced by ER in the absence of estradiol using both approaches. Addition of estradiol induced a partial reversal of this unfolding by green fluorescent protein-lac rep-ER but not by wild-type ER recruited by a lac repressor-SRC570-780 fusion protein. The chromatin decondensation activity did not require transcriptional activation by ER nor did it require ligand-induced coactivator interactions, and unfolding did not correlate with histone hyperacetylation. Ligand-induced coactivator interactions with helix 12 of ER were necessary for the partial refolding of chromatin in response to estradiol using the lac rep-ER tethering system. This work demonstrates that when tethered or recruited to DNA, ER possesses a novel large-scale chromatin unfolding activity. PMID:11971975
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.
Equivalent common path method in large-scale laser comparator
NASA Astrophysics Data System (ADS)
He, Mingzhao; Li, Jianshuang; Miao, Dongjing
2015-02-01
Large-scale laser comparator is main standard device that providing accurate, reliable and traceable measurements for high precision large-scale line and 3D measurement instruments. It mainly composed of guide rail, motion control system, environmental parameters monitoring system and displacement measurement system. In the laser comparator, the main error sources are temperature distribution, straightness of guide rail and pitch and yaw of measuring carriage. To minimize the measurement uncertainty, an equivalent common optical path scheme is proposed and implemented. Three laser interferometers are adjusted to parallel with the guide rail. The displacement in an arbitrary virtual optical path is calculated using three displacements without the knowledge of carriage orientations at start and end positions. The orientation of air floating carriage is calculated with displacements of three optical path and position of three retroreflectors which are precisely measured by Laser Tracker. A 4th laser interferometer is used in the virtual optical path as reference to verify this compensation method. This paper analyzes the effect of rail straightness on the displacement measurement. The proposed method, through experimental verification, can improve the measurement uncertainty of large-scale laser comparator.
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 generation by inhomogeneous helicity.
Yokoi, N; Brandenburg, A
2016-03-01
The effect of kinetic helicity (velocity-vorticity correlation) on turbulent momentum transport is investigated. The turbulent kinetic helicity (pseudoscalar) enters the Reynolds stress (mirror-symmetric tensor) expression in the form of a helicity gradient as the coupling coefficient for the mean vorticity and/or the angular velocity (axial vector), which suggests the possibility of mean-flow generation in the presence of inhomogeneous helicity. This inhomogeneous helicity effect, which was previously confirmed at the level of a turbulence- or closure-model simulation, is examined with the aid of direct numerical simulations of rotating turbulence with nonuniform helicity sustained by an external forcing. The numerical simulations show that the spatial distribution of the Reynolds stress is in agreement with the helicity-related term coupled with the angular velocity, and that a large-scale flow is generated in the direction of angular velocity. Such a large-scale flow is not induced in the case of homogeneous turbulent helicity. This result confirms the validity of the inhomogeneous helicity effect in large-scale flow generation and suggests that a vortex dynamo is possible even in incompressible turbulence where there is no baroclinicity effect.
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.
New probes of Cosmic Microwave Background large-scale anomalies
NASA Astrophysics Data System (ADS)
Aiola, Simone
Fifty years of Cosmic Microwave Background (CMB) data played a crucial role in constraining the parameters of the LambdaCDM model, where Dark Energy, Dark Matter, and Inflation are the three most important pillars not yet understood. Inflation prescribes an isotropic universe on large scales, and it generates spatially-correlated density fluctuations over the whole Hubble volume. CMB temperature fluctuations on scales bigger than a degree in the sky, affected by modes on super-horizon scale at the time of recombination, are a clean snapshot of the universe after inflation. In addition, the accelerated expansion of the universe, driven by Dark Energy, leaves a hardly detectable imprint in the large-scale temperature sky at late times. Such fundamental predictions have been tested with current CMB data and found to be in tension with what we expect from our simple LambdaCDM model. Is this tension just a random fluke or a fundamental issue with the present model? In this thesis, we present a new framework to probe the lack of large-scale correlations in the temperature sky using CMB polarization data. Our analysis shows that if a suppression in the CMB polarization correlations is detected, it will provide compelling evidence for new physics on super-horizon scale. To further analyze the statistical properties of the CMB temperature sky, we constrain the degree of statistical anisotropy of the CMB in the context of the observed large-scale dipole power asymmetry. We find evidence for a scale-dependent dipolar modulation at 2.5sigma. To isolate late-time signals from the primordial ones, we test the anomalously high Integrated Sachs-Wolfe effect signal generated by superstructures in the universe. We find that the detected signal is in tension with the expectations from LambdaCDM at the 2.5sigma level, which is somewhat smaller than what has been previously argued. To conclude, we describe the current status of CMB observations on small scales, highlighting the
NASA Astrophysics Data System (ADS)
Baars, Woutijn J.; Hutchins, Nicholas; Marusic, Ivan
2015-11-01
Interactions between small- and large-scale motions are inherent in the near-wall dynamics of wall-bounded flows. We here examine the scale-interaction embedded within the streamwise velocity component. Data were acquired using hot-wire anemometry in ZPG turbulent boundary layers, for Reynolds numbers ranging from Reτ ≡ δUτ / ν ~ 2800 to 22800. After first decomposing velocity signals into contributions from small- and large-scales, we then represent the time-varying small-scale energy with time series of its instantaneous amplitude and instantaneous frequency, via a wavelet-based method. Features of the scale-interaction are inferred from isocorrelation maps, formed by correlating the large-scale velocity with its concurrent small-scale amplitude and frequency. Below the onset of the log-region, the physics constitutes aspects of amplitude modulation and frequency modulation. Time shifts, associated with the correlation extrema--representing the lead/lag of the small-scale signatures relative to the large-scales--are shown to be governed by inner-scaling. Wall-normal trends of time shifts are explained by considering the arrangement of scales in the log- and intermittent-regions, and how they relate to stochastic top-down and bottom-up processes.
NASA Astrophysics Data System (ADS)
Ni, Chuen-Fa; Li, Shu-Guang; Liu, Chien-Jung; Hsu, Shaohua Marko
2010-02-01
SummaryThis study presents a hybrid spectral method (HSM) to estimate flow uncertainty in large-scale highly nonstationary groundwater systems. Taking advantages of spectral theories in solving unmodeled small-scale variability in hydraulic conductivity, the proposed HSM integrates analytical and numerical spectral solutions in the calculation procedures to estimate flow uncertainty. More specifically, the HSM involves two major computational steps after the mean flow equation is solved. The first step is to apply an analytical-based approximate spectral method (ASM) to predict nonstationary flow variances for entire modeling area. The perturbation-based numerical method, nonstationary spectral method (NSM), is then employed in the second step to correct the regional solution in local areas, where the variance dynamics is considered to be highly nonstationary (e.g., around inner boundaries or strong sources/sinks). The boundary conditions for the localized numerical solutions are based on the ASM closed form solutions at boundary nodes. Since the regional closed form solution is instantaneous and the more expensive perturbation-based numerical analysis is only applied locally around the strong stresses, the proposed HSM can be very efficient, making it possible to model strongly nonstationary variance dynamics with complex flow situations in large-scale groundwater systems. In this study the analytical-based ASM solutions was first assessed to quantify the solution accuracy under transient and inner boundary flow conditions. This study then illustrated the HSM accuracy and effectiveness with two synthetic examples. The HSM solutions were systematically compared with the corresponding numerical solutions of NSM and Monte Carlo simulation (MCS), and the analytical-based solutions of ASM. The simulation results have revealed that the HSM is computationally efficient and can provide accurate variance estimations for highly nonstationary large-scale groundwater flow
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
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.
On the rejection-based algorithm for simulation and analysis of large-scale reaction networks
NASA Astrophysics Data System (ADS)
Thanh, Vo Hong; Zunino, Roberto; Priami, Corrado
2015-06-01
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.
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
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
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.
Test Problems for Large-Scale Multiobjective and Many-Objective Optimization.
Cheng, Ran; Jin, Yaochu; Olhofer, Markus; Sendhoff, Bernhard
2016-08-26
The interests in multiobjective and many-objective optimization have been rapidly increasing in the evolutionary computation community. However, most studies on multiobjective and many-objective optimization are limited to small-scale problems, despite the fact that many real-world multiobjective and many-objective optimization problems may involve a large number of decision variables. As has been evident in the history of evolutionary optimization, the development of evolutionary algorithms (EAs) for solving a particular type of optimization problems has undergone a co-evolution with the development of test problems. To promote the research on large-scale multiobjective and many-objective optimization, we propose a set of generic test problems based on design principles widely used in the literature of multiobjective and many-objective optimization. In order for the test problems to be able to reflect challenges in real-world applications, we consider mixed separability between decision variables and nonuniform correlation between decision variables and objective functions. To assess the proposed test problems, six representative evolutionary multiobjective and many-objective EAs are tested on the proposed test problems. Our empirical results indicate that although the compared algorithms exhibit slightly different capabilities in dealing with the challenges in the test problems, none of them are able to efficiently solve these optimization problems, calling for the need for developing new EAs dedicated to large-scale multiobjective and many-objective optimization.
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.
Partially acoustic dark matter, interacting dark radiation, and large scale structure
Chacko, Zackaria; Cui, Yanou; Hong, Sungwoo; Okui, Takemichi; Tsai, Yuhsinz
2016-12-21
The standard paradigm of collisionless cold dark matter is in tension with measurements on large scales. In particular, the best fit values of the Hubble rate H_{0} and the matter density perturbation σ_{8} inferred from the cosmic microwave background seem inconsistent with the results from direct measurements. We show that both problems can be solved in a framework in which dark matter consists of two distinct components, a dominant component and a subdominant component. The primary component is cold and collisionless. The secondary component is also cold, but interacts strongly with dark radiation, which itself forms a tightly coupled fluid. The growth of density perturbations in the subdominant component is inhibited by dark acoustic oscillations due to its coupling to the dark radiation, solving the σ_{8} problem, while the presence of tightly coupled dark radiation ameliorates the H_{0} problem. The subdominant component of dark matter and dark radiation continue to remain in thermal equilibrium until late times, inhibiting the formation of a dark disk. We present an example of a simple model that naturally realizes this scenario in which both constituents of dark matter are thermal WIMPs. Our scenario can be tested by future stage-IV experiments designed to probe the CMB and large scale structure.
Partially acoustic dark matter, interacting dark radiation, and large scale structure
Chacko, Zackaria; Cui, Yanou; Hong, Sungwoo; ...
2016-12-21
The standard paradigm of collisionless cold dark matter is in tension with measurements on large scales. In particular, the best fit values of the Hubble rate H0 and the matter density perturbation σ8 inferred from the cosmic microwave background seem inconsistent with the results from direct measurements. We show that both problems can be solved in a framework in which dark matter consists of two distinct components, a dominant component and a subdominant component. The primary component is cold and collisionless. The secondary component is also cold, but interacts strongly with dark radiation, which itself forms a tightly coupled fluid.more » The growth of density perturbations in the subdominant component is inhibited by dark acoustic oscillations due to its coupling to the dark radiation, solving the σ8 problem, while the presence of tightly coupled dark radiation ameliorates the H0 problem. The subdominant component of dark matter and dark radiation continue to remain in thermal equilibrium until late times, inhibiting the formation of a dark disk. We present an example of a simple model that naturally realizes this scenario in which both constituents of dark matter are thermal WIMPs. Our scenario can be tested by future stage-IV experiments designed to probe the CMB and large scale structure.« less
Residues cluster-based segmentation and outlier-detection method for large-scale phase unwrapping.
Yu, Hanwen; Li, Zhenfang; Bao, Zheng
2011-10-01
2-D phase unwrapping is an important technique in many applications. However, with the growth of image scale, how to tile and splice the image effectively has become a new challenge. In this paper, the phase unwrapping problem is abstracted as solving a large-scale system of inconsistent linear equations. With the difficulties of large-scale phase unwrapping analyzed, L(0)-norm criterion is found to have potentials in efficient image tiling and splicing. Making use of the clustering characteristic of residue distribution, a tiling strategy is proposed for L(0)-norm criterion. Unfortunately, L(0)-norm is an NP-hard problem, which is very difficult to find an exact solution in a polynomial time. In order to effectively solve this problem, equations corresponding to branch cuts of L(0)-norm in the inconsistent equation system mentioned earlier are considered as outliers, and then an outlier-detection-based phase unwrapping method is proposed. Through this method, a highly accurate approximate solution to this NP-hard problem is achieved. A set of experimental results shows that the proposed approach can avoid the inconsistency between local and global phase unwrapping solutions caused by image tiling.
Partially acoustic dark matter, interacting dark radiation, and large scale structure
NASA Astrophysics Data System (ADS)
Chacko, Zackaria; Cui, Yanou; Hong, Sungwoo; Okui, Takemichi; Tsai, Yuhsinz
2016-12-01
The standard paradigm of collisionless cold dark matter is in tension with measurements on large scales. In particular, the best fit values of the Hubble rate H 0 and the matter density perturbation σ 8 inferred from the cosmic microwave background seem inconsistent with the results from direct measurements. We show that both problems can be solved in a framework in which dark matter consists of two distinct components, a dominant component and a subdominant component. The primary component is cold and collisionless. The secondary component is also cold, but interacts strongly with dark radiation, which itself forms a tightly coupled fluid. The growth of density perturbations in the subdominant component is inhibited by dark acoustic oscillations due to its coupling to the dark radiation, solving the σ 8 problem, while the presence of tightly coupled dark radiation ameliorates the H 0 problem. The subdominant component of dark matter and dark radiation continue to remain in thermal equilibrium until late times, inhibiting the formation of a dark disk. We present an example of a simple model that naturally realizes this scenario in which both constituents of dark matter are thermal WIMPs. Our scenario can be tested by future stage-IV experiments designed to probe the CMB and large scale structure.
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.
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.
Modeling the spreading of large-scale wildland fires
Mohamed Drissi
2015-01-01
The objective of the present study is twofold. First, the last developments and validation results of a hybrid model designed to simulate fire patterns in heterogeneous landscapes are presented. The model combines the features of a stochastic small-world network model with those of a deterministic semi-physical model of the interaction between burning and non-burning...
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.
The Large-Scale Current System During Auroral Substorms
NASA Astrophysics Data System (ADS)
Gjerloev, Jesper
2015-04-01
The substorm process has been discussed for more than four decades and new empirical large-scale models continue to be published. The continued activity implies both the importance and the complexity of the problem. We recently published a new model of the large-scale substorm current system (Gjerloev and Hoffman, JGR, 2014). Based on data from >100 ground magnetometers (obtained from SuperMAG), 116 isolated substorms, global auroral images (obtained by the Polar VIS Earth Camera) and a careful normalization technique we derived an empirical model of the ionospheric equivalent current system. Our model yield some unexpected features that appear inconsistent with the classical single current wedge current system. One of these features is a distinct latitudinal shift of the westward electrojet (WEJ) current between the pre- and post-midnight region and we find evidence that these two WEJ regions are quasi disconnected. This, and other observational facts, led us to propose a modified 3D current system configuration that consists of 2 wedge type systems: a current wedge in the pre-midnight region (bulge current wedge), and another current wedge system in the post-midnight region (oval current wedge). The two wedge systems are shifted in latitude but overlap in local time in the midnight region. Our model is at considerable variance with previous global models and conceptual schematics of the large-scale substorm current system. We speculate that the data coverage, the methodologies and the techniques used in these previous global studies are the cause of the differences in solutions. In this presentation we present our model, compare with other published models and discuss possible causes for the differences.
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 smart passive system for civil engineering applications
NASA Astrophysics Data System (ADS)
Jung, Hyung-Jo; Jang, Dong-Doo; Lee, Heon-Jae; Cho, Sang-Won
2008-03-01
The smart passive system consisting of a magnetorheological (MR) damper and an electromagnetic induction (EMI) part has been recently proposed. An EMI part can generate the input current for an MR damper from vibration of a structure according to Faraday's law of electromagnetic induction. The control performance of the smart passive system has been demonstrated mainly by numerical simulations. It was verified from the numerical results that the system could be effective to reduce the structural responses in the cases of civil engineering structures such as buildings and bridges. On the other hand, the experimental validation of the system is not sufficiently conducted yet. In this paper, the feasibility of the smart passive system to real-scale structures is investigated. To do this, the large-scale smart passive system is designed, manufactured, and tested. The system consists of the large-capacity MR damper, which has a maximum force level of approximately +/-10,000N, a maximum stroke level of +/-35mm and the maximum current level of 3 A, and the large-scale EMI part, which is designed to generate sufficient induced current for the damper. The applicability of the smart passive system to large real-scale structures is examined through a series of shaking table tests. The magnitudes of the induced current of the EMI part with various sinusoidal excitation inputs are measured. According to the test results, the large-scale EMI part shows the possibility that it could generate the sufficient current or power for changing the damping characteristics of the large-capacity MR damper.
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
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
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.
Analysis Plan for 1985 Large-Scale Tests.
1983-01-01
KEY WORDS (Continue on reverse side it necessary mnd Identify by block number) Large-Scale Blasting Agents Multiburst ANFO S:,ock Waves 20. ABSTRACT...CONSIDERATIONS 6 1.5 MULTIBURST TECHNIQUES 6 1.6 TEST SITE CONSIDERATIONS 6 2 CANDIDATE EXPLOSIVES 8 2.1 INTRODUCTION 82.2 ANFO 8 2.2.1 Bulk (Loose) ANFO 11...2.2.2 Bagged ANFO 13 2.3 APEX 1360 15 2.4 NITRIC ACID AND NITROPROPANE 17 2.5 NITROPROPANENITRATE (NPN) 19 2.6 DBA - 22M 21 2.7 HARDENING EMULSION 22 2.8
Large-Scale Patterns of Filament Channels and Filaments
NASA Astrophysics Data System (ADS)
Mackay, Duncan
2016-07-01
In this review the properties and large-scale patterns of filament channels and filaments will be considered. Initially, the global formation locations of filament channels and filaments are discussed, along with their hemispheric pattern. Next, observations of the formation of filament channels and filaments are described where two opposing views are considered. Finally, the wide range of models that have been constructed to consider the formation of filament channels and filaments over long time-scales are described, along with the origin of the hemispheric pattern of filaments.
Design of a large-scale CFB boiler
Darling, S.; Li, S.
1997-12-31
Many CFB boilers sized 100--150 MWe are in operation, and several others sized 150--250 MWe are in operation or under construction. The next step for CFB technology is the 300--400 MWe size range. This paper will describe Foster Wheeler`s large-scale CFB boiler experience and the design for a 300 MWe CFB boiler. The authors will show how the design incorporates Foster Wheeler`s unique combination of extensive utility experience and CFB boiler experience. All the benefits of CFB technology which include low emissions, fuel flexibility, low maintenance and competitive cost are now available in the 300--400 MWe size range.
Large-scale normal fluid circulation in helium superflows
NASA Astrophysics Data System (ADS)
Galantucci, Luca; Sciacca, Michele; Barenghi, Carlo F.
2017-01-01
We perform fully coupled numerical simulations of helium II pure superflows in a channel, with vortex-line density typical of experiments. Peculiar to our model is the computation of the back-reaction of the superfluid vortex motion on the normal fluid and the presence of solid boundaries. We recover the uniform vortex-line density experimentally measured employing second sound resonators and we show that pure superflow in helium II is associated with a large-scale circulation of the normal fluid which can be detected using existing particle-tracking visualization techniques.
On decentralized control of large-scale systems
NASA Technical Reports Server (NTRS)
Siljak, D. D.
1978-01-01
A scheme is presented for decentralized control of large-scale linear systems which are composed of a number of interconnected subsystems. By ignoring the interconnections, local feedback controls are chosen to optimize each decoupled subsystem. Conditions are provided to establish compatibility of the individual local controllers and achieve stability of the overall system. Besides computational simplifications, the scheme is attractive because of its structural features and the fact that it produces a robust decentralized regulator for large dynamic systems, which can tolerate a wide range of nonlinearities and perturbations among the subsystems.
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.
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.
Large-Scale Measurement of Absolute Protein Glycosylation Stoichiometry.
Sun, Shisheng; Zhang, Hui
2015-07-07
Protein glycosylation is one of the most important protein modifications. Glycosylation site occupancy alteration has been implicated in human diseases and cancers. However, current glycoproteomic methods focus on the identification and quantification of glycosylated peptides and glycosylation sites but not glycosylation occupancy or glycoform stoichiometry. Here we describe a method for large-scale determination of the absolute glycosylation stoichiometry using three independent relative ratios. Using this method, we determined 117 absolute N-glycosylation occupancies in OVCAR-3 cells. Finally, we investigated the possible functions and the determinants for partial glycosylation.
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 intermittency in the atmospheric boundary layer.
Kholmyansky, M; Moriconi, L; Tsinober, A
2007-08-01
We find actual evidence, relying upon vorticity time series taken in a high-Reynolds-number atmospheric experiment, that to a very good approximation the surface boundary layer flow may be described, in a statistical sense and under certain regimes, as an advected ensemble of homogeneous turbulent systems, characterized by a log-normal distribution of fluctuating intensities. Our analysis suggests that the usual direct numerical simulations of homogeneous and isotropic turbulence, performed at moderate Reynolds numbers, may play an important role in the study of turbulent boundary layer flows, if supplemented with appropriate statistical information concerned with the structure of large-scale fluctuations.
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.
Simplified DGS procedure for large-scale genome structural study.
Jung, Yong-Chul; Xu, Jia; Chen, Jun; Kim, Yeong; Winchester, David; Wang, San Ming
2009-11-01
Ditag genome scanning (DGS) uses next-generation DNA sequencing to sequence the ends of ditag fragments produced by restriction enzymes. These sequences are compared to known genome sequences to determine their structure. In order to use DGS for large-scale genome structural studies, we have substantially revised the original protocol by replacing the in vivo genomic DNA cloning with in vitro adaptor ligation, eliminating the ditag concatemerization steps, and replacing the 454 sequencer with Solexa or SOLiD sequencers for ditag sequence collection. This revised protocol further increases genome coverage and resolution and allows DGS to be used to analyze multiple genomes simultaneously.
UAV Data Processing for Large Scale Topographical Mapping
NASA Astrophysics Data System (ADS)
Tampubolon, W.; Reinhardt, W.
2014-06-01
Large scale topographical mapping in the third world countries is really a prominent challenge in geospatial industries nowadays. On one side the demand is significantly increasing while on the other hand it is constrained by limited budgets available for mapping projects. Since the advent of Act Nr.4/yr.2011 about Geospatial Information in Indonesia, large scale topographical mapping has been on high priority for supporting the nationwide development e.g. detail spatial planning. Usually large scale topographical mapping relies on conventional aerial survey campaigns in order to provide high resolution 3D geospatial data sources. Widely growing on a leisure hobby, aero models in form of the so-called Unmanned Aerial Vehicle (UAV) bring up alternative semi photogrammetric aerial data acquisition possibilities suitable for relatively small Area of Interest (AOI) i.e. <5,000 hectares. For detail spatial planning purposes in Indonesia this area size can be used as a mapping unit since it usually concentrates on the basis of sub district area (kecamatan) level. In this paper different camera and processing software systems will be further analyzed for identifying the best optimum UAV data acquisition campaign components in combination with the data processing scheme. The selected AOI is covering the cultural heritage of Borobudur Temple as one of the Seven Wonders of the World. A detailed accuracy assessment will be concentrated within the object feature of the temple at the first place. Feature compilation involving planimetric objects (2D) and digital terrain models (3D) will be integrated in order to provide Digital Elevation Models (DEM) as the main interest of the topographic mapping activity. By doing this research, incorporating the optimum amount of GCPs in the UAV photo data processing will increase the accuracy along with its high resolution in 5 cm Ground Sampling Distance (GSD). Finally this result will be used as the benchmark for alternative geospatial
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.
Clusters as cornerstones of large-scale structure.
NASA Astrophysics Data System (ADS)
Gottlöber, S.; Retzlaff, J.; Turchaninov, V.
1997-04-01
Galaxy clusters are one of the best tracers of large-scale structure in the Universe on scales well above 100 Mpc. The authors investigate here the clustering properties of a redshift sample of Abell/ACO clusters and compare the observational sample with mock samples constructed from N-body simulations on the basis of four different cosmological models. The authors discuss the power spectrum, the Minkowski functionals and the void statistics of these samples and conclude, that the SCDM and TCDM models are ruled out whereas the ACDM and BSI models are in agreement with the observational data.
Artificial intelligence and large scale computation: A physics perspective
NASA Astrophysics Data System (ADS)
Hogg, Tad; Huberman, B. A.
1987-12-01
We study the macroscopic behavior of computation and examine both emergent collective phenomena and dynamical aspects with an emphasis on software issues, which are at the core of large scale distributed computation and artificial intelligence systems. By considering large systems, we exhibit novel phenomena which cannot be foreseen from examination of their smaller counterparts. We review both the symbolic and connectionist views of artificial intelligence, provide a number of examples which display these phenomena, and resort to statistical mechanics, dynamical systems theory and the theory of random graphs to elicit the range of possible behaviors.
Potential for geophysical experiments in large scale tests
Dieterich, J.H.
1981-07-01
Potential research applications for large-specimen geophysical experiments include measurements of scale dependence of physical parameters and examination of interactions with heterogeneities, especially flaws such as cracks. In addition, increased specimen size provides opportunities for improved recording resolution and greater control of experimental variables. Large-scale experiments using a special purpose low stress (<40 MPa) bi-axial apparatus demonstrate that a minimum fault length is required to generate confined shear instabilities along pre-existing faults. Experimental analysis of source interactions for simulated earthquakes consisting of confined shear instabilities on a fault with gouge appears to require large specimens (approx.1m) and high confining pressures (>100 MPa).
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.
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.
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.
Water-based scintillators for large-scale liquid calorimetry
Winn, D.R.; Raftery, D.
1985-02-01
We have investigated primary and secondary solvent intermediates in search of a recipe to create a bulk liquid scintillator with water as the bulk solvent and common fluors as the solutes. As we are not concerned with energy resolution below 1 MeV in large-scale experiments, light-output at the 10% level of high-quality organic solvent based scintillators is acceptable. We have found encouraging performance from industrial surfactants as primary solvents for PPO and POPOP. This technique may allow economical and environmentally safe bulk scintillator for kiloton-sized high energy calorimetry.
Large scale mortality of nestling ardeids caused by nematode infection.
Wiese, J H; Davidson, W R; Nettles, V F
1977-10-01
During the summer of 1976, an epornitic of verminous peritonitis caused by Eustrongylides ignotus resulted in large scale mortality of young herons and egrets on Pea Patch Island, Delaware. Mortality was highest (84%) in snowy egret nestlings ( Egretta thula ) and less severe in great egrets ( Casmerodius albus ), Louisiana herons ( Hydranassa tricolor ), little blue herons ( Florida caerulea ), and black crowned night herons ( Nycticorax nycticorax ). Most deaths occured within the first 4 weeks after hatching. Migration of E. ignotus resulted in multiple perforations of the visceral organs, escape of intestinal contents into the body cavity and subsequent bacterial peritonitis. Killifish ( Fundulus heteroclitus ) served as the source of infective larvae.
The large-scale structure of the solar wind
NASA Technical Reports Server (NTRS)
Wolfe, J. H.
1972-01-01
The large-scale structure of the solar wind is reviewed on the basis of experimental space measurements acquired over approximately the last decade. The observations cover the fading portion of the last solar cycle up through the maximum of the present cycle. The character of the interplanetary medium is considered from the viewpoint of the temporal behavior of the solar wind over increasingly longer time intervals, the average properties of the various solar wind parameters and their interrelationships. Interplanetary-terrestrial relationships and the expected effects of heliographic lattitude and radial distance are briefly discussed.
Structure and function of large-scale brain systems.
Koziol, Leonard F; Barker, Lauren A; Joyce, Arthur W; Hrin, Skip
2014-01-01
This article introduces the functional neuroanatomy of large-scale brain systems. Both the structure and functions of these brain networks are presented. All human behavior is the result of interactions within and between these brain systems. This system of brain function completely changes our understanding of how cognition and behavior are organized within the brain, replacing the traditional lesion model. Understanding behavior within the context of brain network interactions has profound implications for modifying abstract constructs such as attention, learning, and memory. These constructs also must be understood within the framework of a paradigm shift, which emphasizes ongoing interactions within a dynamically changing environment.
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.
Decentrally stabilizable linear and bilinear large-scale systems
NASA Technical Reports Server (NTRS)
Siljak, D. D.; Vukcevic, M. B.
1977-01-01
Two classes of large-scale systems are identified, which can always be stabilized by decentralized feedback control. For the class of systems composed of interconnected linear subsystems, we can choose local controllers for the subsystems to achieve stability of the overall system. The same linear feedback scheme can be used to stabilize a class of linear systems with bilinear interconnections. In this case, however, the scheme is used to establish a finite region of stability for the overall system. The stabilization algorithm is applied to the design of a control system for the Large-Space Telescope.
Large-scale structure from wiggly cosmic strings
NASA Astrophysics Data System (ADS)
Vachaspati, Tanmay; Vilenkin, Alexander
1991-08-01
Recent simulations of the evolution of cosmic strings indicate the presence of small-scale structure on the strings. It is shown that wakes produced by such 'wiggly' cosmic strings can result in the efficient formation of large-scale structure and large streaming velocities in the universe without significantly affecting the microwave-background isotropy. It is also argued that the motion of strings will lead to the generation of a primordial magnetic field. The most promising version of this scenario appears to be the one in which the universe is dominated by light neutrinos.
Large-scale genotoxicity assessments in the marine environment.
Hose, J E
1994-01-01
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
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
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. 31 refs., 2 tabs.
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.
Brief Mental Training Reorganizes Large-Scale Brain Networks
Tang, Yi-Yuan; Tang, Yan; Tang, Rongxiang; Lewis-Peacock, Jarrod A.
2017-01-01
Emerging evidences have shown that one form of mental training—mindfulness meditation, can improve attention, emotion regulation and cognitive performance through changing brain activity and structural connectivity. However, whether and how the short-term mindfulness meditation alters large-scale brain networks are not well understood. Here, we applied a novel data-driven technique, the multivariate pattern analysis (MVPA) to resting-state fMRI (rsfMRI) data to identify changes in brain activity patterns and assess the neural mechanisms induced by a brief mindfulness training—integrative body–mind training (IBMT), which was previously reported in our series of randomized studies. Whole brain rsfMRI was performed on an undergraduate group who received 2 weeks of IBMT with 30 min per session (5 h training in total). Classifiers were trained on measures of functional connectivity in this fMRI data, and they were able to reliably differentiate (with 72% accuracy) patterns of connectivity from before vs. after the IBMT training. After training, an increase in positive functional connections (60 connections) were detected, primarily involving bilateral superior/middle occipital gyrus, bilateral frontale operculum, bilateral superior temporal gyrus, right superior temporal pole, bilateral insula, caudate and cerebellum. These results suggest that brief mental training alters the functional connectivity of large-scale brain networks at rest that may involve a portion of the neural circuitry supporting attention, cognitive and affective processing, awareness and sensory integration and reward processing. PMID:28293180
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
Development of Large-Scale Functional Brain Networks in Children
Supekar, Kaustubh; Musen, Mark; Menon, Vinod
2009-01-01
The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7–9 y) and 22 young-adults (ages 19–22 y). Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar “small-world” organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism. PMID:19621066
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}.