Performance Modeling of Hybrid MPI/OpenMP Scientific Applications on Large-scale Multicore Cluster Systems

KAUST Repository

Wu, Xingfu; Taylor, Valerie

2011-01-01

In this paper, we present a performance modeling framework based on memory bandwidth contention time and a parameterized communication model to predict the performance of OpenMP, MPI and hybrid applications with weak scaling on three large-scale multicore clusters: IBM POWER4, POWER5+ and Blue Gene/P, and analyze the performance of these MPI, OpenMP and hybrid applications. We use STREAM memory benchmarks to provide initial performance analysis and model validation of MPI and OpenMP applications on these multicore clusters because the measured sustained memory bandwidth can provide insight into the memory bandwidth that a system should sustain on scientific applications with the same amount of workload per core. In addition to using these benchmarks, we also use a weak-scaling hybrid MPI/OpenMP large-scale scientific application: Gyro kinetic Toroidal Code in magnetic fusion to validate our performance model of the hybrid application on these multicore clusters. The validation results for our performance modeling method show less than 7.77% error rate in predicting the performance of hybrid MPI/OpenMP GTC on up to 512 cores on these multicore clusters. © 2011 IEEE.

Performance Modeling of Hybrid MPI/OpenMP Scientific Applications on Large-scale Multicore Cluster Systems

KAUST Repository

Wu, Xingfu

2011-08-01

In this paper, we present a performance modeling framework based on memory bandwidth contention time and a parameterized communication model to predict the performance of OpenMP, MPI and hybrid applications with weak scaling on three large-scale multicore clusters: IBM POWER4, POWER5+ and Blue Gene/P, and analyze the performance of these MPI, OpenMP and hybrid applications. We use STREAM memory benchmarks to provide initial performance analysis and model validation of MPI and OpenMP applications on these multicore clusters because the measured sustained memory bandwidth can provide insight into the memory bandwidth that a system should sustain on scientific applications with the same amount of workload per core. In addition to using these benchmarks, we also use a weak-scaling hybrid MPI/OpenMP large-scale scientific application: Gyro kinetic Toroidal Code in magnetic fusion to validate our performance model of the hybrid application on these multicore clusters. The validation results for our performance modeling method show less than 7.77% error rate in predicting the performance of hybrid MPI/OpenMP GTC on up to 512 cores on these multicore clusters. © 2011 IEEE.

Do large-scale assessments measure students' ability to integrate scientific knowledge?

Science.gov (United States)

Lee, Hee-Sun

2010-03-01

Large-scale assessments are used as means to diagnose the current status of student achievement in science and compare students across schools, states, and countries. For efficiency, multiple-choice items and dichotomously-scored open-ended items are pervasively used in large-scale assessments such as Trends in International Math and Science Study (TIMSS). This study investigated how well these items measure secondary school students' ability to integrate scientific knowledge. This study collected responses of 8400 students to 116 multiple-choice and 84 open-ended items and applied an Item Response Theory analysis based on the Rasch Partial Credit Model. Results indicate that most multiple-choice items and dichotomously-scored open-ended items can be used to determine whether students have normative ideas about science topics, but cannot measure whether students integrate multiple pieces of relevant science ideas. Only when the scoring rubric is redesigned to capture subtle nuances of student open-ended responses, open-ended items become a valid and reliable tool to assess students' knowledge integration ability.

Decomposition and parallelization strategies for solving large-scale MDO problems

Energy Technology Data Exchange (ETDEWEB)

Grauer, M.; Eschenauer, H.A. [Research Center for Multidisciplinary Analyses and Applied Structural Optimization, FOMAAS, Univ. of Siegen (Germany)

2007-07-01

During previous years, structural optimization has been recognized as a useful tool within the discriptiones of engineering and economics. However, the optimization of large-scale systems or structures is impeded by an immense solution effort. This was the reason to start a joint research and development (R and D) project between the Institute of Mechanics and Control Engineering and the Information and Decision Sciences Institute within the Research Center for Multidisciplinary Analyses and Applied Structural Optimization (FOMAAS) on cluster computing for parallel and distributed solution of multidisciplinary optimization (MDO) problems based on the OpTiX-Workbench. Here the focus of attention will be put on coarsegrained parallelization and its implementation on clusters of workstations. A further point of emphasis was laid on the development of a parallel decomposition strategy called PARDEC, for the solution of very complex optimization problems which cannot be solved efficiently by sequential integrated optimization. The use of the OptiX-Workbench together with the FEM ground water simulation system FEFLOW is shown for a special water management problem. (orig.)

Advanced I/O for large-scale scientific applications

International Nuclear Information System (INIS)

Klasky, Scott; Schwan, Karsten; Oldfield, Ron A.; Lofstead, Gerald F. II

2010-01-01

As scientific simulations scale to use petascale machines and beyond, the data volumes generated pose a dual problem. First, with increasing machine sizes, the careful tuning of IO routines becomes more and more important to keep the time spent in IO acceptable. It is not uncommon, for instance, to have 20% of an application's runtime spent performing IO in a 'tuned' system. Careful management of the IO routines can move that to 5% or even less in some cases. Second, the data volumes are so large, on the order of 10s to 100s of TB, that trying to discover the scientifically valid contributions requires assistance at runtime to both organize and annotate the data. Waiting for offline processing is not feasible due both to the impact on the IO system and the time required. To reduce this load and improve the ability of scientists to use the large amounts of data being produced, new techniques for data management are required. First, there is a need for techniques for efficient movement of data from the compute space to storage. These techniques should understand the underlying system infrastructure and adapt to changing system conditions. Technologies include aggregation networks, data staging nodes for a closer parity to the IO subsystem, and autonomic IO routines that can detect system bottlenecks and choose different approaches, such as splitting the output into multiple targets, staggering output processes. Such methods must be end-to-end, meaning that even with properly managed asynchronous techniques, it is still essential to properly manage the later synchronous interaction with the storage system to maintain acceptable performance. Second, for the data being generated, annotations and other metadata must be incorporated to help the scientist understand output data for the simulation run as a whole, to select data and data features without concern for what files or other storage technologies were employed. All of these features should be attained while

Large-scale data analytics

CERN Document Server

Gkoulalas-Divanis, Aris

2014-01-01

Provides cutting-edge research in large-scale data analytics from diverse scientific areas Surveys varied subject areas and reports on individual results of research in the field Shares many tips and insights into large-scale data analytics from authors and editors with long-term experience and specialization in the field

Solving large scale unit dilemma in electricity system by applying commutative law

Science.gov (United States)

Legino, Supriadi; Arianto, Rakhmat

2018-03-01

The conventional system, pooling resources with large centralized power plant interconnected as a network. provides a lot of advantages compare to the isolated one include optimizing efficiency and reliability. However, such a large plant need a huge capital. In addition, more problems emerged to hinder the construction of big power plant as well as its associated transmission lines. By applying commutative law of math, ab = ba, for all a,b €-R, the problem associated with conventional system as depicted above, can be reduced. The idea of having small unit but many power plants, namely “Listrik Kerakyatan,” abbreviated as LK provides both social and environmental benefit that could be capitalized by using proper assumption. This study compares the cost and benefit of LK to those of conventional system, using simulation method to prove that LK offers alternative solution to answer many problems associated with the large system. Commutative Law of Algebra can be used as a simple mathematical model to analyze whether the LK system as an eco-friendly distributed generation can be applied to solve various problems associated with a large scale conventional system. The result of simulation shows that LK provides more value if its plants operate in less than 11 hours as peaker power plant or load follower power plant to improve load curve balance of the power system. The result of simulation indicates that the investment cost of LK plant should be optimized in order to minimize the plant investment cost. This study indicates that the benefit of economies of scale principle does not always apply to every condition, particularly if the portion of intangible cost and benefit is relatively high.

Scientific Approach to Improve Mathematical Problem Solving Skills Students of Grade V

Science.gov (United States)

Roheni; Herman, T.; Jupri, A.

2017-09-01

This study investigates the skills of elementary school students’ in problem solving through the Scientific Approach. The purpose of this study is to determine mathematical problem solving skills of students by using Scientific Approach is better than mathematical problem solving skills of students by using Direct Instruction. This study is using quasi-experimental method. Subject of this study is students in grade V in one of state elementary school in Cirebon Regency. Instrument that used in this study is mathematical problem solving skills. The result of this study showed that mathematical problem solving skills of students who learn by using Scientific Approach is more significant than using Direct Instruction. Base on result and analysis, the conclusion is that Scientific Approach can improve students’ mathematical problem solving skills.

Accelerating sustainability in large-scale facilities

CERN Multimedia

Marina Giampietro

2011-01-01

Scientific research centres and large-scale facilities are intrinsically energy intensive, but how can big science improve its energy management and eventually contribute to the environmental cause with new cleantech? CERN’s commitment to providing tangible answers to these questions was sealed in the first workshop on energy management for large scale scientific infrastructures held in Lund, Sweden, on the 13-14 October.   Participants at the energy management for large scale scientific infrastructures workshop. The workshop, co-organised with the European Spallation Source (ESS) and  the European Association of National Research Facilities (ERF), tackled a recognised need for addressing energy issues in relation with science and technology policies. It brought together more than 150 representatives of Research Infrastrutures (RIs) and energy experts from Europe and North America. “Without compromising our scientific projects, we can ...

Study of Scientific Problem-Solving Abilities Based on Scientific Knowledge about Atmosphere and Weather for Seventh Grade Students

Directory of Open Access Journals (Sweden)

Phoorin Thaengnoi

2017-06-01

Full Text Available The purposes of this research were: 1 to develop scientific problem-solving abilities test based on scientific knowledge about atmosphere and weather for seventh grade students and 2 to study the scientific problem-solving abilities of seventh grade students. The samples used in this study were 47 students who were studying in seventh grade in academic year 2015 of a school in Chai Nat province, Thailand. Purposive sampling was applied for identifying the samples. The research instrument of this study was the scientific problem-solving abilities test developed by the researcher. The research data was analyzed by comparing students’ scores with the criteria and considering students’ answers in each element of scientific problem-solving abilities. The results of the study were as follows: The scientific problem-solving abilities test composed of 2 parts. The first part was multiple-choice questions which was composed of 4 situations, a total of 20 questions. The Index of Item Objective Congruence of this part was varied in the range between 0.67 – 1.00. The difficulty and the discrimination level were in the range between 0.33 – 0.63 and 0.27 – 0.67, respectively. The reliability levels of this part was equal to 0.81. The second part of the test was subjective questions which composed of 2 situations, a total of 10 questions. The Index of Item Objective Congruence of this part was varied in the range between 0.67 – 1.00. The reliability level of this part was equal to 0.83. Besides, all questions in the test were covered all elements of scientific problem-solving abilities ; 1 identifying the problem 2 making the hypothesis 3 collecting data and knowledge to solve the problem 4 identifying problem-solving method and 5 predicting the characteristics of the results. The problem-solving abilities of the students revealed that 40.43% of students (n=19 were in a moderate level and 59.57% of students (n=28 were in a low level with the

Results of research and development in large-scale research centers as an innovation source for firms

International Nuclear Information System (INIS)

Theenhaus, R.

1978-01-01

The twelve large-scale research centres of the Federal Republic of Germany with their 16,000 employees represent a considerable scientific and technical potential. Cooperation with industry with regard to large-scale projects has already become very close and the know-how flow as well as the contributions to innovation connected therewith are largely established. The first successful steps to utilizing the results of basic research, of spin off and those within the frame of research and development as well as the fulfilling of services are encouraging. However, there is a number of detail problems which can only be solved between all parties concerned, in particular between industry and all large-scale research centres. (orig./RW) [de

Large-scale computation at PSI scientific achievements and future requirements

International Nuclear Information System (INIS)

Adelmann, A.; Markushin, V.

2008-11-01

Computational modelling and simulation are among the disciplines that have seen the most dramatic growth in capabilities in the 2Oth Century. Within the past two decades, scientific computing has become an important contributor to all scientific research programs. Computational modelling and simulation are particularly indispensable for solving research problems that are unsolvable by traditional theoretical and experimental approaches, hazardous to study, or time consuming or expensive to solve by traditional means. Many such research areas are found in PSI's research portfolio. Advances in computing technologies (including hardware and software) during the past decade have set the stage for a major step forward in modelling and simulation. We have now arrived at a situation where we have a number of otherwise unsolvable problems, where simulations are as complex as the systems under study. In 2008 the High-Performance Computing (HPC) community entered the petascale area with the heterogeneous Opteron/Cell machine, called Road Runner built by IBM for the Los Alamos National Laboratory. We are on the brink of a time where the availability of many hundreds of thousands of cores will open up new challenging possibilities in physics, algorithms (numerical mathematics) and computer science. However, to deliver on this promise, it is not enough to provide 'peak' performance in terms of peta-flops, the maximum theoretical speed a computer can attain. Most important, this must be translated into corresponding increase in the capabilities of scientific codes. This is a daunting problem that can only be solved by increasing investment in hardware, in the accompanying system software that enables the reliable use of high-end computers, in scientific competence i.e. the mathematical (parallel) algorithms that are the basis of the codes, and education. In the case of Switzerland, the white paper 'Swiss National Strategic Plan for High Performance Computing and Networking

Large-scale computation at PSI scientific achievements and future requirements

Energy Technology Data Exchange (ETDEWEB)

Adelmann, A.; Markushin, V

2008-11-15

Computational modelling and simulation are among the disciplines that have seen the most dramatic growth in capabilities in the 2Oth Century. Within the past two decades, scientific computing has become an important contributor to all scientific research programs. Computational modelling and simulation are particularly indispensable for solving research problems that are unsolvable by traditional theoretical and experimental approaches, hazardous to study, or time consuming or expensive to solve by traditional means. Many such research areas are found in PSI's research portfolio. Advances in computing technologies (including hardware and software) during the past decade have set the stage for a major step forward in modelling and simulation. We have now arrived at a situation where we have a number of otherwise unsolvable problems, where simulations are as complex as the systems under study. In 2008 the High-Performance Computing (HPC) community entered the petascale area with the heterogeneous Opteron/Cell machine, called Road Runner built by IBM for the Los Alamos National Laboratory. We are on the brink of a time where the availability of many hundreds of thousands of cores will open up new challenging possibilities in physics, algorithms (numerical mathematics) and computer science. However, to deliver on this promise, it is not enough to provide 'peak' performance in terms of peta-flops, the maximum theoretical speed a computer can attain. Most important, this must be translated into corresponding increase in the capabilities of scientific codes. This is a daunting problem that can only be solved by increasing investment in hardware, in the accompanying system software that enables the reliable use of high-end computers, in scientific competence i.e. the mathematical (parallel) algorithms that are the basis of the codes, and education. In the case of Switzerland, the white paper 'Swiss National Strategic Plan for High Performance Computing

Efficient Feature-Driven Visualization of Large-Scale Scientific Data

Energy Technology Data Exchange (ETDEWEB)

Lu, Aidong

2012-12-12

Very large, complex scientific data acquired in many research areas creates critical challenges for scientists to understand, analyze, and organize their data. The objective of this project is to expand the feature extraction and analysis capabilities to develop powerful and accurate visualization tools that can assist domain scientists with their requirements in multiple phases of scientific discovery. We have recently developed several feature-driven visualization methods for extracting different data characteristics of volumetric datasets. Our results verify the hypothesis in the proposal and will be used to develop additional prototype systems.

Solving Large-Scale Computational Problems Using Insights from Statistical Physics

Energy Technology Data Exchange (ETDEWEB)

Selman, Bart [Cornell University

2012-02-29

Many challenging problems in computer science and related fields can be formulated as constraint satisfaction problems. Such problems consist of a set of discrete variables and a set of constraints between those variables, and represent a general class of so-called NP-complete problems. The goal is to find a value assignment to the variables that satisfies all constraints, generally requiring a search through and exponentially large space of variable-value assignments. Models for disordered systems, as studied in statistical physics, can provide important new insights into the nature of constraint satisfaction problems. Recently, work in this area has resulted in the discovery of a new method for solving such problems, called the survey propagation (SP) method. With SP, we can solve problems with millions of variables and constraints, an improvement of two orders of magnitude over previous methods.

Solving Large Scale Crew Scheduling Problems in Practice

NARCIS (Netherlands)

E.J.W. Abbink (Erwin); L. Albino; T.A.B. Dollevoet (Twan); D. Huisman (Dennis); J. Roussado; R.L. Saldanha

2010-01-01

textabstractThis paper deals with large-scale crew scheduling problems arising at the Dutch railway operator, Netherlands Railways (NS). NS operates about 30,000 trains a week. All these trains need a driver and a certain number of guards. Some labor rules restrict the duties of a certain crew base

Structural problems of public participation in large-scale projects with environmental impact

International Nuclear Information System (INIS)

Bechmann, G.

1989-01-01

Four items are discussed showing that the problems involved through participation of the public in large-scale projects with environmental impact cannot be solved satisfactorily without suitable modification of the existing legal framework. The problematic items are: the status of the electric utilities as a quasi public enterprise; informal preliminary negotiations; the penetration of scientific argumentation into administrative decisions; the procedural concept. The paper discusses the fundamental issue of the problem-adequate design of the procedure and develops suggestions for a cooperative participation design. (orig./HSCH) [de

A Polar Rover for Large-Scale Scientific Surveys: Design, Implementation and Field Test Results

Directory of Open Access Journals (Sweden)

Yuqing He

2015-10-01

Full Text Available Exploration of polar regions is of great importance to scientific research. Unfortunately, due to the harsh environment, most of the regions on the Antarctic continent are still unreachable for humankind. Therefore, in 2011, the Chinese National Antarctic Research Expedition (CHINARE launched a project to design a rover to conduct large-scale scientific surveys on the Antarctic. The main challenges for the rover are twofold: one is the mobility, i.e., how to make a rover that could survive the harsh environment and safely move on the uneven, icy and snowy terrain; the other is the autonomy, in that the robot should be able to move at a relatively high speed with little or no human intervention so that it can explore a large region in a limit time interval under the communication constraints. In this paper, the corresponding techniques, especially the polar rover's design and autonomous navigation algorithms, are introduced in detail. Subsequently, an experimental report of the fields tests on the Antarctic is given to show some preliminary evaluation of the rover. Finally, experiences and existing challenging problems are summarized.

Exploiting Data Sparsity for Large-Scale Matrix Computations

KAUST Repository

Akbudak, Kadir

2018-02-24

Exploiting data sparsity in dense matrices is an algorithmic bridge between architectures that are increasingly memory-austere on a per-core basis and extreme-scale applications. The Hierarchical matrix Computations on Manycore Architectures (HiCMA) library tackles this challenging problem by achieving significant reductions in time to solution and memory footprint, while preserving a specified accuracy requirement of the application. HiCMA provides a high-performance implementation on distributed-memory systems of one of the most widely used matrix factorization in large-scale scientific applications, i.e., the Cholesky factorization. It employs the tile low-rank data format to compress the dense data-sparse off-diagonal tiles of the matrix. It then decomposes the matrix computations into interdependent tasks and relies on the dynamic runtime system StarPU for asynchronous out-of-order scheduling, while allowing high user-productivity. Performance comparisons and memory footprint on matrix dimensions up to eleven million show a performance gain and memory saving of more than an order of magnitude for both metrics on thousands of cores, against state-of-the-art open-source and vendor optimized numerical libraries. This represents an important milestone in enabling large-scale matrix computations toward solving big data problems in geospatial statistics for climate/weather forecasting applications.

Exploiting Data Sparsity for Large-Scale Matrix Computations

KAUST Repository

Akbudak, Kadir; Ltaief, Hatem; Mikhalev, Aleksandr; Charara, Ali; Keyes, David E.

2018-01-01

Exploiting data sparsity in dense matrices is an algorithmic bridge between architectures that are increasingly memory-austere on a per-core basis and extreme-scale applications. The Hierarchical matrix Computations on Manycore Architectures (HiCMA) library tackles this challenging problem by achieving significant reductions in time to solution and memory footprint, while preserving a specified accuracy requirement of the application. HiCMA provides a high-performance implementation on distributed-memory systems of one of the most widely used matrix factorization in large-scale scientific applications, i.e., the Cholesky factorization. It employs the tile low-rank data format to compress the dense data-sparse off-diagonal tiles of the matrix. It then decomposes the matrix computations into interdependent tasks and relies on the dynamic runtime system StarPU for asynchronous out-of-order scheduling, while allowing high user-productivity. Performance comparisons and memory footprint on matrix dimensions up to eleven million show a performance gain and memory saving of more than an order of magnitude for both metrics on thousands of cores, against state-of-the-art open-source and vendor optimized numerical libraries. This represents an important milestone in enabling large-scale matrix computations toward solving big data problems in geospatial statistics for climate/weather forecasting applications.

Improving Students’ Scientific Reasoning and Problem-Solving Skills by The 5E Learning Model

Directory of Open Access Journals (Sweden)

Sri Mulyani Endang Susilowati

2017-12-01

Full Text Available Biology learning in MA (Madrasah Aliyah Khas Kempek was still dominated by teacher with low students’ involvement. This study would analyze the effectiveness of the 5E (Engagement, Exploration, Explanation, Elaboration, Evaluation learning model in improving scientific knowledge and problems solving. It also explained the relationship between students’ scientific reasoning with their problem-solving abilities. This was a pre-experimental research with one group pre-test post-test. Sixty students of MA Khas Kempek from XI MIA 3 and XI MIA 4 involved in this study. The learning outcome of the students was collected by the test of reasoning and problem-solving. The results showed that the rises of students’ scientific reasoning ability were 69.77% for XI MIA 3 and 66.27% for XI MIA 4, in the medium category. The problem-solving skills were 63.40% for XI MIA 3, 61.67% for XI MIA 4, and classified in the moderate category. The simple regression test found a linear correlation between students’ scientific reasoning and problem-solving ability. This study affirms that reasoning ability is needed in problem-solving. It is found that application of 5E learning model was effective to improve scientific reasoning and problem-solving ability of students.

Examining the Relationship of Scientific Reasoning with Physics Problem Solving

Science.gov (United States)

Fabby, Carol; Koenig, Kathleen

2015-01-01

Recent research suggests students with more formal reasoning patterns are more proficient learners. However, little research has been done to establish a relationship between scientific reasoning and problem solving abilities by novices. In this exploratory study, we compared scientific reasoning abilities of students enrolled in a college level…

Performance Characteristics of Hybrid MPI/OpenMP Scientific Applications on a Large-Scale Multithreaded BlueGene/Q Supercomputer

KAUST Repository

Wu, Xingfu; Taylor, Valerie

2013-01-01

In this paper, we investigate the performance characteristics of five hybrid MPI/OpenMP scientific applications (two NAS Parallel benchmarks Multi-Zone SP-MZ and BT-MZ, an earthquake simulation PEQdyna, an aerospace application PMLB and a 3D particle-in-cell application GTC) on a large-scale multithreaded Blue Gene/Q supercomputer at Argonne National laboratory, and quantify the performance gap resulting from using different number of threads per node. We use performance tools and MPI profile and trace libraries available on the supercomputer to analyze and compare the performance of these hybrid scientific applications with increasing the number OpenMP threads per node, and find that increasing the number of threads to some extent saturates or worsens performance of these hybrid applications. For the strong-scaling hybrid scientific applications such as SP-MZ, BT-MZ, PEQdyna and PLMB, using 32 threads per node results in much better application efficiency than using 64 threads per node, and as increasing the number of threads per node, the FPU (Floating Point Unit) percentage decreases, and the MPI percentage (except PMLB) and IPC (Instructions per cycle) per core (except BT-MZ) increase. For the weak-scaling hybrid scientific application such as GTC, the performance trend (relative speedup) is very similar with increasing number of threads per node no matter how many nodes (32, 128, 512) are used. © 2013 IEEE.

Performance Characteristics of Hybrid MPI/OpenMP Scientific Applications on a Large-Scale Multithreaded BlueGene/Q Supercomputer

KAUST Repository

Wu, Xingfu

2013-07-01

In this paper, we investigate the performance characteristics of five hybrid MPI/OpenMP scientific applications (two NAS Parallel benchmarks Multi-Zone SP-MZ and BT-MZ, an earthquake simulation PEQdyna, an aerospace application PMLB and a 3D particle-in-cell application GTC) on a large-scale multithreaded Blue Gene/Q supercomputer at Argonne National laboratory, and quantify the performance gap resulting from using different number of threads per node. We use performance tools and MPI profile and trace libraries available on the supercomputer to analyze and compare the performance of these hybrid scientific applications with increasing the number OpenMP threads per node, and find that increasing the number of threads to some extent saturates or worsens performance of these hybrid applications. For the strong-scaling hybrid scientific applications such as SP-MZ, BT-MZ, PEQdyna and PLMB, using 32 threads per node results in much better application efficiency than using 64 threads per node, and as increasing the number of threads per node, the FPU (Floating Point Unit) percentage decreases, and the MPI percentage (except PMLB) and IPC (Instructions per cycle) per core (except BT-MZ) increase. For the weak-scaling hybrid scientific application such as GTC, the performance trend (relative speedup) is very similar with increasing number of threads per node no matter how many nodes (32, 128, 512) are used. © 2013 IEEE.

Topology Optimization of Large Scale Stokes Flow Problems

DEFF Research Database (Denmark)

Aage, Niels; Poulsen, Thomas Harpsøe; Gersborg-Hansen, Allan

2008-01-01

This note considers topology optimization of large scale 2D and 3D Stokes flow problems using parallel computations. We solve problems with up to 1.125.000 elements in 2D and 128.000 elements in 3D on a shared memory computer consisting of Sun UltraSparc IV CPUs.......This note considers topology optimization of large scale 2D and 3D Stokes flow problems using parallel computations. We solve problems with up to 1.125.000 elements in 2D and 128.000 elements in 3D on a shared memory computer consisting of Sun UltraSparc IV CPUs....

Escript: Open Source Environment For Solving Large-Scale Geophysical Joint Inversion Problems in Python

Science.gov (United States)

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.

Accelerating large-scale phase-field simulations with GPU

Directory of Open Access Journals (Sweden)

Xiaoming Shi

2017-10-01

Full Text Available A new package for accelerating large-scale phase-field simulations was developed by using GPU based on the semi-implicit Fourier method. The package can solve a variety of equilibrium equations with different inhomogeneity including long-range elastic, magnetostatic, and electrostatic interactions. Through using specific algorithm in Compute Unified Device Architecture (CUDA, Fourier spectral iterative perturbation method was integrated in GPU package. The Allen-Cahn equation, Cahn-Hilliard equation, and phase-field model with long-range interaction were solved based on the algorithm running on GPU respectively to test the performance of the package. From the comparison of the calculation results between the solver executed in single CPU and the one on GPU, it was found that the speed on GPU is enormously elevated to 50 times faster. The present study therefore contributes to the acceleration of large-scale phase-field simulations and provides guidance for experiments to design large-scale functional devices.

Political consultation and large-scale research

International Nuclear Information System (INIS)

Bechmann, G.; Folkers, H.

1977-01-01

Large-scale research and policy consulting have an intermediary position between sociological sub-systems. While large-scale research coordinates science, policy, and production, policy consulting coordinates science, policy and political spheres. In this very position, large-scale research and policy consulting lack of institutional guarantees and rational back-ground guarantee which are characteristic for their sociological environment. This large-scale research can neither deal with the production of innovative goods under consideration of rentability, nor can it hope for full recognition by the basis-oriented scientific community. Policy consulting knows neither the competence assignment of the political system to make decisions nor can it judge succesfully by the critical standards of the established social science, at least as far as the present situation is concerned. This intermediary position of large-scale research and policy consulting has, in three points, a consequence supporting the thesis which states that this is a new form of institutionalization of science: These are: 1) external control, 2) the organization form, 3) the theoretical conception of large-scale research and policy consulting. (orig.) [de

Adding intelligence to scientific data management

Science.gov (United States)

Campbell, William J.; Short, Nicholas M., Jr.; Treinish, Lloyd A.

1989-01-01

NASA plans to solve some of the problems of handling large-scale scientific data bases by turning to artificial intelligence (AI) are discussed. The growth of the information glut and the ways that AI can help alleviate the resulting problems are reviewed. The employment of the Intelligent User Interface prototype, where the user will generate his own natural language query with the assistance of the system, is examined. Spatial data management, scientific data visualization, and data fusion are discussed.

The Convergence of High Performance Computing and Large Scale Data Analytics

Science.gov (United States)

Duffy, D.; Bowen, M. K.; Thompson, J. H.; Yang, C. P.; Hu, F.; Wills, B.

2015-12-01

As the combinations of remote sensing observations and model outputs have grown, scientists are increasingly burdened with both the necessity and complexity of large-scale data analysis. Scientists are increasingly applying traditional high performance computing (HPC) solutions to solve their "Big Data" problems. While this approach has the benefit of limiting data movement, the HPC system is not optimized to run analytics, which can create problems that permeate throughout the HPC environment. To solve these issues and to alleviate some of the strain on the HPC environment, the NASA Center for Climate Simulation (NCCS) has created the Advanced Data Analytics Platform (ADAPT), which combines both HPC and cloud technologies to create an agile system designed for analytics. Large, commonly used data sets are stored in this system in a write once/read many file system, such as Landsat, MODIS, MERRA, and NGA. High performance virtual machines are deployed and scaled according to the individual scientist's requirements specifically for data analysis. On the software side, the NCCS and GMU are working with emerging commercial technologies and applying them to structured, binary scientific data in order to expose the data in new ways. Native NetCDF data is being stored within a Hadoop Distributed File System (HDFS) enabling storage-proximal processing through MapReduce while continuing to provide accessibility of the data to traditional applications. Once the data is stored within HDFS, an additional indexing scheme is built on top of the data and placed into a relational database. This spatiotemporal index enables extremely fast mappings of queries to data locations to dramatically speed up analytics. These are some of the first steps toward a single unified platform that optimizes for both HPC and large-scale data analysis, and this presentation will elucidate the resulting and necessary exascale architectures required for future systems.

The Roles of Sparse Direct Methods in Large-scale Simulations

Energy Technology Data Exchange (ETDEWEB)

Li, Xiaoye S.; Gao, Weiguo; Husbands, Parry J.R.; Yang, Chao; Ng, Esmond G.

2005-06-27

Sparse systems of linear equations and eigen-equations arise at the heart of many large-scale, vital simulations in DOE. Examples include the Accelerator Science and Technology SciDAC (Omega3P code, electromagnetic problem), the Center for Extended Magnetohydrodynamic Modeling SciDAC(NIMROD and M3D-C1 codes, fusion plasma simulation). The Terascale Optimal PDE Simulations (TOPS)is providing high-performance sparse direct solvers, which have had significant impacts on these applications. Over the past several years, we have been working closely with the other SciDAC teams to solve their large, sparse matrix problems arising from discretization of the partial differential equations. Most of these systems are very ill-conditioned, resulting in extremely poor convergence deployed our direct methods techniques in these applications, which achieved significant scientific results as well as performance gains. These successes were made possible through the SciDAC model of computer scientists and application scientists working together to take full advantage of terascale computing systems and new algorithms research.

The Roles of Sparse Direct Methods in Large-scale Simulations

International Nuclear Information System (INIS)

Li, Xiaoye S.; Gao, Weiguo; Husbands, Parry J.R.; Yang, Chao; Ng, Esmond G.

2005-01-01

Sparse systems of linear equations and eigen-equations arise at the heart of many large-scale, vital simulations in DOE. Examples include the Accelerator Science and Technology SciDAC (Omega3P code, electromagnetic problem), the Center for Extended Magnetohydrodynamic Modeling SciDAC(NIMROD and M3D-C1 codes, fusion plasma simulation). The Terascale Optimal PDE Simulations (TOPS)is providing high-performance sparse direct solvers, which have had significant impacts on these applications. Over the past several years, we have been working closely with the other SciDAC teams to solve their large, sparse matrix problems arising from discretization of the partial differential equations. Most of these systems are very ill-conditioned, resulting in extremely poor convergence deployed our direct methods techniques in these applications, which achieved significant scientific results as well as performance gains. These successes were made possible through the SciDAC model of computer scientists and application scientists working together to take full advantage of terascale computing systems and new algorithms research

Doing physics with scientific notebook a problem solving approach

CERN Document Server

Gallant, Joseph

2012-01-01

The goal of this book is to teach undergraduate students how to use Scientific Notebook (SNB) to solve physics problems. SNB software combines word processing and mathematics in standard notation with the power of symbolic computation. As its name implies, SNB can be used as a notebook in which students set up a math or science problem, write and solve equations, and analyze and discuss their results. Written by a physics teacher with over 20 years experience, this text includes topics that have educational value, fit within the typical physics curriculum, and show the benefits of using SNB.

Unified Access Architecture for Large-Scale Scientific Datasets

Science.gov (United States)

Karna, Risav

2014-05-01

Data-intensive sciences have to deploy diverse large scale database technologies for data analytics as scientists have now been dealing with much larger volume than ever before. While array databases have bridged many gaps between the needs of data-intensive research fields and DBMS technologies (Zhang 2011), invocation of other big data tools accompanying these databases is still manual and separate the database management's interface. We identify this as an architectural challenge that will increasingly complicate the user's work flow owing to the growing number of useful but isolated and niche database tools. Such use of data analysis tools in effect leaves the burden on the user's end to synchronize the results from other data manipulation analysis tools with the database management system. To this end, we propose a unified access interface for using big data tools within large scale scientific array database using the database queries themselves to embed foreign routines belonging to the big data tools. Such an invocation of foreign data manipulation routines inside a query into a database can be made possible through a user-defined function (UDF). UDFs that allow such levels of freedom as to call modules from another language and interface back and forth between the query body and the side-loaded functions would be needed for this purpose. For the purpose of this research we attempt coupling of four widely used tools Hadoop (hadoop1), Matlab (matlab1), R (r1) and ScaLAPACK (scalapack1) with UDF feature of rasdaman (Baumann 98), an array-based data manager, for investigating this concept. The native array data model used by an array-based data manager provides compact data storage and high performance operations on ordered data such as spatial data, temporal data, and matrix-based data for linear algebra operations (scidbusr1). Performances issues arising due to coupling of tools with different paradigms, niche functionalities, separate processes and output

Solving large-scale sparse eigenvalue problems and linear systems of equations for accelerator modeling

International Nuclear Information System (INIS)

Gene Golub; Kwok Ko

2009-01-01

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.

Dual Decomposition for Large-Scale Power Balancing

DEFF Research Database (Denmark)

Halvgaard, Rasmus; Jørgensen, John Bagterp; Vandenberghe, Lieven

2013-01-01

Dual decomposition is applied to power balancing of exible thermal storage units. The centralized large-scale problem is decomposed into smaller subproblems and solved locallyby each unit in the Smart Grid. Convergence is achieved by coordinating the units consumption through a negotiation...

Learning from large scale neural simulations

DEFF Research Database (Denmark)

Serban, Maria

2017-01-01

Large-scale neural simulations have the marks of a distinct methodology which can be fruitfully deployed to advance scientific understanding of the human brain. Computer simulation studies can be used to produce surrogate observational data for better conceptual models and new how...

Engineering management of large scale systems

Science.gov (United States)

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.

Parallel Tensor Compression for Large-Scale Scientific Data.

Energy Technology Data Exchange (ETDEWEB)

Kolda, Tamara G. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Ballard, Grey [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Austin, Woody Nathan [Univ. of Texas, Austin, TX (United States)

2015-10-01

As parallel computing trends towards the exascale, scientific data produced by high-fidelity simulations are growing increasingly massive. For instance, a simulation on a three-dimensional spatial grid with 512 points per dimension that tracks 64 variables per grid point for 128 time steps yields 8 TB of data. By viewing the data as a dense five way tensor, we can compute a Tucker decomposition to find inherent low-dimensional multilinear structure, achieving compression ratios of up to 10000 on real-world data sets with negligible loss in accuracy. So that we can operate on such massive data, we present the first-ever distributed memory parallel implementation for the Tucker decomposition, whose key computations correspond to parallel linear algebra operations, albeit with nonstandard data layouts. Our approach specifies a data distribution for tensors that avoids any tensor data redistribution, either locally or in parallel. We provide accompanying analysis of the computation and communication costs of the algorithms. To demonstrate the compression and accuracy of the method, we apply our approach to real-world data sets from combustion science simulations. We also provide detailed performance results, including parallel performance in both weak and strong scaling experiments.

On-demand Overlay Networks for Large Scientific Data Transfers

Energy Technology Data Exchange (ETDEWEB)

Ramakrishnan, Lavanya [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Guok, Chin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Jackson, Keith [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kissel, Ezra [Univ. of Delaware, Newark, DE (United States); Swany, D. Martin [Univ. of Delaware, Newark, DE (United States); Agarwal, Deborah [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2009-10-12

Large scale scientific data transfers are central to scientific processes. Data from large experimental facilities have to be moved to local institutions for analysis or often data needs to be moved between local clusters and large supercomputing centers. In this paper, we propose and evaluate a network overlay architecture to enable highthroughput, on-demand, coordinated data transfers over wide-area networks. Our work leverages Phoebus and On-demand Secure Circuits and AdvanceReservation System (OSCARS) to provide high performance wide-area network connections. OSCARS enables dynamic provisioning of network paths with guaranteed bandwidth and Phoebus enables the coordination and effective utilization of the OSCARS network paths. Our evaluation shows that this approach leads to improved end-to-end data transfer throughput with minimal overheads. The achievedthroughput using our overlay was limited only by the ability of the end hosts to sink the data.

Perceived Problem Solving Skills: As a Predictor of Prospective Teachers' Scientific Epistemological Beliefs

Science.gov (United States)

Temel, Senar

2016-01-01

This study aims to determine the level of perceived problem solving skills of prospective teachers and the relations between these skills and their scientific epistemological beliefs. The study was conducted in the fall semester of 2015-2016 academic year. Prospective teachers were applied Problem Solving Inventory which was developed by Heppner…

Using Relational Reasoning to Learn about Scientific Phenomena at Unfamiliar Scales

Science.gov (United States)

Resnick, Ilyse; Davatzes, Alexandra; Newcombe, Nora S.; Shipley, Thomas F.

2017-01-01

Many scientific theories and discoveries involve reasoning about extreme scales, removed from human experience, such as time in geology and size in nanoscience. Thus, understanding scale is central to science, technology, engineering, and mathematics. Unfortunately, novices have trouble understanding and comparing sizes of unfamiliar large and…

Robust large-scale parallel nonlinear solvers for simulations.

Energy Technology Data Exchange (ETDEWEB)

Bader, Brett William; Pawlowski, Roger Patrick; Kolda, Tamara Gibson (Sandia National Laboratories, Livermore, CA)

2005-11-01

This report documents research to develop robust and efficient solution techniques for solving large-scale systems of nonlinear equations. The most widely used method for solving systems of nonlinear equations is Newton's method. While much research has been devoted to augmenting Newton-based solvers (usually with globalization techniques), little has been devoted to exploring the application of different models. Our research has been directed at evaluating techniques using different models than Newton's method: a lower order model, Broyden's method, and a higher order model, the tensor method. We have developed large-scale versions of each of these models and have demonstrated their use in important applications at Sandia. Broyden's method replaces the Jacobian with an approximation, allowing codes that cannot evaluate a Jacobian or have an inaccurate Jacobian to converge to a solution. Limited-memory methods, which have been successful in optimization, allow us to extend this approach to large-scale problems. We compare the robustness and efficiency of Newton's method, modified Newton's method, Jacobian-free Newton-Krylov method, and our limited-memory Broyden method. Comparisons are carried out for large-scale applications of fluid flow simulations and electronic circuit simulations. Results show that, in cases where the Jacobian was inaccurate or could not be computed, Broyden's method converged in some cases where Newton's method failed to converge. We identify conditions where Broyden's method can be more efficient than Newton's method. We also present modifications to a large-scale tensor method, originally proposed by Bouaricha, for greater efficiency, better robustness, and wider applicability. Tensor methods are an alternative to Newton-based methods and are based on computing a step based on a local quadratic model rather than a linear model. The advantage of Bouaricha's method is that it can use any

A family of conjugate gradient methods for large-scale nonlinear equations.

Science.gov (United States)

Feng, Dexiang; Sun, Min; Wang, Xueyong

2017-01-01

In this paper, we present a family of conjugate gradient projection methods for solving large-scale nonlinear equations. At each iteration, it needs low storage and the subproblem can be easily solved. Compared with the existing solution methods for solving the problem, its global convergence is established without the restriction of the Lipschitz continuity on the underlying mapping. Preliminary numerical results are reported to show the efficiency of the proposed method.

A family of conjugate gradient methods for large-scale nonlinear equations

Directory of Open Access Journals (Sweden)

Dexiang Feng

2017-09-01

Full Text Available Abstract In this paper, we present a family of conjugate gradient projection methods for solving large-scale nonlinear equations. At each iteration, it needs low storage and the subproblem can be easily solved. Compared with the existing solution methods for solving the problem, its global convergence is established without the restriction of the Lipschitz continuity on the underlying mapping. Preliminary numerical results are reported to show the efficiency of the proposed method.

Large Scale Visual Recommendations From Street Fashion Images

OpenAIRE

Jagadeesh, Vignesh; Piramuthu, Robinson; Bhardwaj, Anurag; Di, Wei; Sundaresan, Neel

2014-01-01

We describe a completely automated large scale visual recommendation system for fashion. Our focus is to efficiently harness the availability of large quantities of online fashion images and their rich meta-data. Specifically, we propose four data driven models in the form of Complementary Nearest Neighbor Consensus, Gaussian Mixture Models, Texture Agnostic Retrieval and Markov Chain LDA for solving this problem. We analyze relative merits and pitfalls of these algorithms through extensive e...

Parallel Index and Query for Large Scale Data Analysis

Energy Technology Data Exchange (ETDEWEB)

Chou, Jerry; Wu, Kesheng; Ruebel, Oliver; Howison, Mark; Qiang, Ji; Prabhat,; Austin, Brian; Bethel, E. Wes; Ryne, Rob D.; Shoshani, Arie

2011-07-18

Modern scientific datasets present numerous data management and analysis challenges. State-of-the-art index and query technologies are critical for facilitating interactive exploration of large datasets, but numerous challenges remain in terms of designing a system for process- ing general scientific datasets. The system needs to be able to run on distributed multi-core platforms, efficiently utilize underlying I/O infrastructure, and scale to massive datasets. We present FastQuery, a novel software framework that address these challenges. FastQuery utilizes a state-of-the-art index and query technology (FastBit) and is designed to process mas- sive datasets on modern supercomputing platforms. We apply FastQuery to processing of a massive 50TB dataset generated by a large scale accelerator modeling code. We demonstrate the scalability of the tool to 11,520 cores. Motivated by the scientific need to search for inter- esting particles in this dataset, we use our framework to reduce search time from hours to tens of seconds.

Novel algorithm of large-scale simultaneous linear equations

International Nuclear Information System (INIS)

Fujiwara, T; Hoshi, T; Yamamoto, S; Sogabe, T; Zhang, S-L

2010-01-01

We review our recently developed methods of solving large-scale simultaneous linear equations and applications to electronic structure calculations both in one-electron theory and many-electron theory. This is the shifted COCG (conjugate orthogonal conjugate gradient) method based on the Krylov subspace, and the most important issue for applications is the shift equation and the seed switching method, which greatly reduce the computational cost. The applications to nano-scale Si crystals and the double orbital extended Hubbard model are presented.

The effect of Think Pair Share (TPS) using scientific approach on students’ self-confidence and mathematical problem-solving

Science.gov (United States)

Rifa’i, A.; Lestari, H. P.

2018-03-01

This study was designed to know the effects of Think Pair Share using Scientific Approach on students' self-confidence and mathematical problem-solving. Quasi-experimental with pre-test post-test non-equivalent group method was used as a basis for design this study. Self-confidence questionnaire and problem-solving test have been used for measurement of the two variables. Two classes of the first grade in religious senior high school (MAN) in Indonesia were randomly selected for this study. Teaching sequence and series from mathematics book at control group in the traditional way and at experiment group has been in TPS using scientific approach learning method. For data analysis regarding students’ problem-solving skill and self-confidence, One-Sample t-Test, Independent Sample t-Test, and Multivariate of Variance (MANOVA) were used. The results showed that (1) TPS using a scientific approach and traditional learning had positive effects (2) TPS using scientific approach learning in comparative with traditional learning had a more significant effect on students’ self-confidence and problem-solving skill.

Comparing the performance of SIMD computers by running large air pollution models

DEFF Research Database (Denmark)

Brown, J.; Hansen, Per Christian; Wasniewski, J.

1996-01-01

To compare the performance and use of three massively parallel SIMD computers, we implemented a large air pollution model on these computers. Using a realistic large-scale model, we gained detailed insight about the performance of the computers involved when used to solve large-scale scientific...... problems that involve several types of numerical computations. The computers used in our study are the Connection Machines CM-200 and CM-5, and the MasPar MP-2216...

Large-scale networks in engineering and life sciences

CERN Document Server

Findeisen, Rolf; Flockerzi, Dietrich; Reichl, Udo; Sundmacher, Kai

2014-01-01

This edited volume provides insights into and tools for the modeling, analysis, optimization, and control of large-scale networks in the life sciences and in engineering. Large-scale systems are often the result of networked interactions between a large number of subsystems, and their analysis and control are becoming increasingly important. The chapters of this book present the basic concepts and theoretical foundations of network theory and discuss its applications in different scientific areas such as biochemical reactions, chemical production processes, systems biology, electrical circuits, and mobile agents. The aim is to identify common concepts, to understand the underlying mathematical ideas, and to inspire discussions across the borders of the various disciplines.  The book originates from the interdisciplinary summer school “Large Scale Networks in Engineering and Life Sciences” hosted by the International Max Planck Research School Magdeburg, September 26-30, 2011, and will therefore be of int...

Seismic safety in conducting large-scale blasts

Science.gov (United States)

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.

3D large-scale calculations using the method of characteristics

International Nuclear Information System (INIS)

Dahmani, M.; Roy, R.; Koclas, J.

2004-01-01

An overview of the computational requirements and the numerical developments made in order to be able to solve 3D large-scale problems using the characteristics method will be presented. To accelerate the MCI solver, efficient acceleration techniques were implemented and parallelization was performed. However, for the very large problems, the size of the tracking file used to store the tracks can still become prohibitive and exceed the capacity of the machine. The new 3D characteristics solver MCG will now be introduced. This methodology is dedicated to solve very large 3D problems (a part or a whole core) without spatial homogenization. In order to eliminate the input/output problems occurring when solving these large problems, we define a new computing scheme that requires more CPU resources than the usual one, based on sweeps over large tracking files. The huge capacity of storage needed in some problems and the related I/O queries needed by the characteristics solver are replaced by on-the-fly recalculation of tracks at each iteration step. Using this technique, large 3D problems are no longer I/O-bound, and distributed CPU resources can be efficiently used. (author)

Scalability of Parallel Scientific Applications on the Cloud

Directory of Open Access Journals (Sweden)

Satish Narayana Srirama

2011-01-01

Full Text Available Cloud computing, with its promise of virtually infinite resources, seems to suit well in solving resource greedy scientific computing problems. To study the effects of moving parallel scientific applications onto the cloud, we deployed several benchmark applications like matrix–vector operations and NAS parallel benchmarks, and DOUG (Domain decomposition On Unstructured Grids on the cloud. DOUG is an open source software package for parallel iterative solution of very large sparse systems of linear equations. The detailed analysis of DOUG on the cloud showed that parallel applications benefit a lot and scale reasonable on the cloud. We could also observe the limitations of the cloud and its comparison with cluster in terms of performance. However, for efficiently running the scientific applications on the cloud infrastructure, the applications must be reduced to frameworks that can successfully exploit the cloud resources, like the MapReduce framework. Several iterative and embarrassingly parallel algorithms are reduced to the MapReduce model and their performance is measured and analyzed. The analysis showed that Hadoop MapReduce has significant problems with iterative methods, while it suits well for embarrassingly parallel algorithms. Scientific computing often uses iterative methods to solve large problems. Thus, for scientific computing on the cloud, this paper raises the necessity for better frameworks or optimizations for MapReduce.

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

Science.gov (United States)

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

2017-10-01

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

Assessment of climate change impacts on rainfall using large scale ...

Indian Academy of Sciences (India)

Many of the applied techniques in water resources management can be directly or indirectly influenced by ... is based on large scale climate signals data around the world. In order ... predictand relationships are often very complex. .... constraints to solve the optimization problem. ..... social, and environmental sustainability.

Resolute large scale mining company contribution to health services of

African Journals Online (AJOL)

Resolute large scale mining company contribution to health services of Lusu ... in terms of socio economic, health, education, employment, safe drinking water, ... The data were analyzed using Scientific Package for Social Science (SPSS).

Advancements in Large-Scale Data/Metadata Management for Scientific Data.

Science.gov (United States)

Guntupally, K.; Devarakonda, R.; Palanisamy, G.; Frame, M. T.

2017-12-01

Scientific data often comes with complex and diverse metadata which are critical for data discovery and users. The Online Metadata Editor (OME) tool, which was developed by an Oak Ridge National Laboratory team, effectively manages diverse scientific datasets across several federal data centers, such as DOE's Atmospheric Radiation Measurement (ARM) Data Center and USGS's Core Science Analytics, Synthesis, and Libraries (CSAS&L) project. This presentation will focus mainly on recent developments and future strategies for refining OME tool within these centers. The ARM OME is a standard based tool (https://www.archive.arm.gov/armome) that allows scientists to create and maintain metadata about their data products. The tool has been improved with new workflows that help metadata coordinators and submitting investigators to submit and review their data more efficiently. The ARM Data Center's newly upgraded Data Discovery Tool (http://www.archive.arm.gov/discovery) uses rich metadata generated by the OME to enable search and discovery of thousands of datasets, while also providing a citation generator and modern order-delivery techniques like Globus (using GridFTP), Dropbox and THREDDS. The Data Discovery Tool also supports incremental indexing, which allows users to find new data as and when they are added. The USGS CSAS&L search catalog employs a custom version of the OME (https://www1.usgs.gov/csas/ome), which has been upgraded with high-level Federal Geographic Data Committee (FGDC) validations and the ability to reserve and mint Digital Object Identifiers (DOIs). The USGS's Science Data Catalog (SDC) (https://data.usgs.gov/datacatalog) allows users to discover a myriad of science data holdings through a web portal. Recent major upgrades to the SDC and ARM Data Discovery Tool include improved harvesting performance and migration using new search software, such as Apache Solr 6.0 for serving up data/metadata to scientific communities. Our presentation will highlight

Sparse deconvolution for the large-scale ill-posed inverse problem of impact force reconstruction

Science.gov (United States)

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.

Accelerating Relevance Vector Machine for Large-Scale Data on Spark

Directory of Open Access Journals (Sweden)

Liu Fang

2017-01-01

Full Text Available Relevance vector machine (RVM is a machine learning algorithm based on a sparse Bayesian framework, which performs well when running classification and regression tasks on small-scale datasets. However, RVM also has certain drawbacks which restricts its practical applications such as (1 slow training process, (2 poor performance on training large-scale datasets. In order to solve these problem, we propose Discrete AdaBoost RVM (DAB-RVM which incorporate ensemble learning in RVM at first. This method performs well with large-scale low-dimensional datasets. However, as the number of features increases, the training time of DAB-RVM increases as well. To avoid this phenomenon, we utilize the sufficient training samples of large-scale datasets and propose all features boosting RVM (AFB-RVM, which modifies the way of obtaining weak classifiers. In our experiments we study the differences between various boosting techniques with RVM, demonstrating the performance of the proposed approaches on Spark. As a result of this paper, two proposed approaches on Spark for different types of large-scale datasets are available.

Large scale electrolysers

International Nuclear Information System (INIS)

B Bello; M Junker

2006-01-01

Hydrogen production by water electrolysis represents nearly 4 % of the world hydrogen production. Future development of hydrogen vehicles will require large quantities of hydrogen. Installation of large scale hydrogen production plants will be needed. In this context, development of low cost large scale electrolysers that could use 'clean power' seems necessary. ALPHEA HYDROGEN, an European network and center of expertise on hydrogen and fuel cells, has performed for its members a study in 2005 to evaluate the potential of large scale electrolysers to produce hydrogen in the future. The different electrolysis technologies were compared. Then, a state of art of the electrolysis modules currently available was made. A review of the large scale electrolysis plants that have been installed in the world was also realized. The main projects related to large scale electrolysis were also listed. Economy of large scale electrolysers has been discussed. The influence of energy prices on the hydrogen production cost by large scale electrolysis was evaluated. (authors)

Large-scale inverse model analyses employing fast randomized data reduction

Science.gov (United States)

Lin, Youzuo; Le, Ellen B.; O'Malley, Daniel; Vesselinov, Velimir V.; Bui-Thanh, Tan

2017-08-01

When the number of observations is large, it is computationally challenging to apply classical inverse modeling techniques. We have developed a new computationally efficient technique for solving inverse problems with a large number of observations (e.g., on the order of 107 or greater). Our method, which we call the randomized geostatistical approach (RGA), is built upon the principal component geostatistical approach (PCGA). We employ a data reduction technique combined with the PCGA to improve the computational efficiency and reduce the memory usage. Specifically, we employ a randomized numerical linear algebra technique based on a so-called "sketching" matrix to effectively reduce the dimension of the observations without losing the information content needed for the inverse analysis. In this way, the computational and memory costs for RGA scale with the information content rather than the size of the calibration data. Our algorithm is coded in Julia and implemented in the MADS open-source high-performance computational framework (http://mads.lanl.gov). We apply our new inverse modeling method to invert for a synthetic transmissivity field. Compared to a standard geostatistical approach (GA), our method is more efficient when the number of observations is large. Most importantly, our method is capable of solving larger inverse problems than the standard GA and PCGA approaches. Therefore, our new model inversion method is a powerful tool for solving large-scale inverse problems. The method can be applied in any field and is not limited to hydrogeological applications such as the characterization of aquifer heterogeneity.

A Decomposition-Based Pricing Method for Solving a Large-Scale MILP Model for an Integrated Fishery

Directory of Open Access Journals (Sweden)

M. Babul Hasan

2007-01-01

The IFP can be decomposed into a trawler-scheduling subproblem and a fish-processing subproblem in two different ways by relaxing different sets of constraints. We tried conventional decomposition techniques including subgradient optimization and Dantzig-Wolfe decomposition, both of which were unacceptably slow. We then developed a decomposition-based pricing method for solving the large fishery model, which gives excellent computation times. Numerical results for several planning horizon models are presented.

Extreme Scale Computing for First-Principles Plasma Physics Research

Energy Technology Data Exchange (ETDEWEB)

Chang, Choogn-Seock [Princeton University

2011-10-12

World superpowers are in the middle of the “Computnik” race. US Department of Energy (and National Nuclear Security Administration) wishes to launch exascale computer systems into the scientific (and national security) world by 2018. The objective is to solve important scientific problems and to predict the outcomes using the most fundamental scientific laws, which would not be possible otherwise. Being chosen into the next “frontier” group can be of great benefit to a scientific discipline. An extreme scale computer system requires different types of algorithms and programming philosophy from those we have been accustomed to. Only a handful of scientific codes are blessed to be capable of scalable usage of today’s largest computers in operation at petascale (using more than 100,000 cores concurrently). Fortunately, a few magnetic fusion codes are competing well in this race using the “first principles” gyrokinetic equations.These codes are beginning to study the fusion plasma dynamics in full-scale realistic diverted device geometry in natural nonlinear multiscale, including the large scale neoclassical and small scale turbulence physics, but excluding some ultra fast dynamics. In this talk, most of the above mentioned topics will be introduced at executive level. Representative properties of the extreme scale computers, modern programming exercises to take advantage of them, and different philosophies in the data flows and analyses will be presented. Examples of the multi-scale multi-physics scientific discoveries made possible by solving the gyrokinetic equations on extreme scale computers will be described. Future directions into “virtual tokamak experiments” will also be discussed.

Republic Scientific-practical Conference 'The Youth Role in solving the most important issues of globalization process' Proceedings

International Nuclear Information System (INIS)

2015-01-01

Present collection comprises of materials of Republic Scientific-practical Conference 'The Youth Role in solving the most important issues of globalization process'. Present collection is intended for scientific and technical staff, postgraduates, and students of institutes of higher education.

C Versus Fortran-77 for Scientific Programming

Directory of Open Access Journals (Sweden)

Tom MacDonald

1992-01-01

Full Text Available The predominant programming language for numeric and scientific applications is Fortran-77 and supercomputers are primarily used to run large-scale numeric and scientific applications. Standard C* is not widely used for numerical and scientific programming, yet Standard C provides many desirable linguistic features not present in Fortran-77. Furthermore, the existence of a standard library and preprocessor eliminates the worst portability problems. A comparison of Standard C and Fortran-77 shows several key deficiencies in C that reduce its ability to adequately solve some numerical problems. Some of these problems have already been addressed by the C standard but others remain. Standard C with a few extensions and modifications could be suitable for all numerical applications and could become more popular in supercomputing environments.

Insufficiencies in solving global environmental problems by specialized scientific expertise

International Nuclear Information System (INIS)

Hartwig, S.G.; Kra, R.S.

1989-01-01

The most paradoxical and urgent problem faces the world today. We find ourselves between the horns of a dilemma. One horn represents the accelerating demand for energy, and the other, the irreversible degradation of our natural environment. There are two directions that we can take to solve our growing global crisis. The first step is to encourage scientific specialists to think in broader terms. The second necessary approach is to make decision makers aware of the complexity of the situation as well as the dangers of tunnel vision that experts often fall into. Therefore, to find a long-term holistic solution, decision makers, be they government officials or academics, must be, themselves, solution oriented and capable of directing scientists along broadened problem-solving pathways. Up till now, scientists have been required to research environmental problems, discover causal associations and determine effects. Contemporary scientists, in the truest sense of the meaning, are no longer generalists but are specialists in their own fields with great depth and accuracy of knowledge. However, experts of high standing may have difficulty visualizing adjacent sciences, which causes them to lose sight of topics peripheral to their main field of interest. The consequence of this can be that solutions to a problem will be sought only within particular and specialized areas, but it is, unfortunately, a fact of life that environmental problems do not come neatly packaged in scientific disciplines: they happen in their entirety, with all their synergistic implications. 5 refs., 5 figs

Scale-Up: Improving Large Enrollment Physics Courses

Science.gov (United States)

Beichner, Robert

1999-11-01

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

BILGO: Bilateral greedy optimization for large scale semidefinite programming

KAUST Repository

Hao, Zhifeng; Yuan, Ganzhao; Ghanem, Bernard

2013-01-01

Many machine learning tasks (e.g. metric and manifold learning problems) can be formulated as convex semidefinite programs. To enable the application of these tasks on a large-scale, scalability and computational efficiency are considered as desirable properties for a practical semidefinite programming algorithm. In this paper, we theoretically analyze a new bilateral greedy optimization (denoted BILGO) strategy in solving general semidefinite programs on large-scale datasets. As compared to existing methods, BILGO employs a bilateral search strategy during each optimization iteration. In such an iteration, the current semidefinite matrix solution is updated as a bilateral linear combination of the previous solution and a suitable rank-1 matrix, which can be efficiently computed from the leading eigenvector of the descent direction at this iteration. By optimizing for the coefficients of the bilateral combination, BILGO reduces the cost function in every iteration until the KKT conditions are fully satisfied, thus, it tends to converge to a global optimum. In fact, we prove that BILGO converges to the global optimal solution at a rate of O(1/k), where k is the iteration counter. The algorithm thus successfully combines the efficiency of conventional rank-1 update algorithms and the effectiveness of gradient descent. Moreover, BILGO can be easily extended to handle low rank constraints. To validate the effectiveness and efficiency of BILGO, we apply it to two important machine learning tasks, namely Mahalanobis metric learning and maximum variance unfolding. Extensive experimental results clearly demonstrate that BILGO can solve large-scale semidefinite programs efficiently.

BILGO: Bilateral greedy optimization for large scale semidefinite programming

KAUST Repository

Hao, Zhifeng

2013-10-03

Many machine learning tasks (e.g. metric and manifold learning problems) can be formulated as convex semidefinite programs. To enable the application of these tasks on a large-scale, scalability and computational efficiency are considered as desirable properties for a practical semidefinite programming algorithm. In this paper, we theoretically analyze a new bilateral greedy optimization (denoted BILGO) strategy in solving general semidefinite programs on large-scale datasets. As compared to existing methods, BILGO employs a bilateral search strategy during each optimization iteration. In such an iteration, the current semidefinite matrix solution is updated as a bilateral linear combination of the previous solution and a suitable rank-1 matrix, which can be efficiently computed from the leading eigenvector of the descent direction at this iteration. By optimizing for the coefficients of the bilateral combination, BILGO reduces the cost function in every iteration until the KKT conditions are fully satisfied, thus, it tends to converge to a global optimum. In fact, we prove that BILGO converges to the global optimal solution at a rate of O(1/k), where k is the iteration counter. The algorithm thus successfully combines the efficiency of conventional rank-1 update algorithms and the effectiveness of gradient descent. Moreover, BILGO can be easily extended to handle low rank constraints. To validate the effectiveness and efficiency of BILGO, we apply it to two important machine learning tasks, namely Mahalanobis metric learning and maximum variance unfolding. Extensive experimental results clearly demonstrate that BILGO can solve large-scale semidefinite programs efficiently.

A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems

Directory of Open Access Journals (Sweden)

Yingni Zhai

2014-10-01

Full Text Available Purpose: A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems (JSP is proposed.Design/methodology/approach: In the algorithm, a number of sub-problems are constructed by iteratively decomposing the large-scale JSP according to the process route of each job. And then the solution of the large-scale JSP can be obtained by iteratively solving the sub-problems. In order to improve the sub-problems' solving efficiency and the solution quality, a detection method for multi-bottleneck machines based on critical path is proposed. Therewith the unscheduled operations can be decomposed into bottleneck operations and non-bottleneck operations. According to the principle of “Bottleneck leads the performance of the whole manufacturing system” in TOC (Theory Of Constraints, the bottleneck operations are scheduled by genetic algorithm for high solution quality, and the non-bottleneck operations are scheduled by dispatching rules for the improvement of the solving efficiency.Findings: In the process of the sub-problems' construction, partial operations in the previous scheduled sub-problem are divided into the successive sub-problem for re-optimization. This strategy can improve the solution quality of the algorithm. In the process of solving the sub-problems, the strategy that evaluating the chromosome's fitness by predicting the global scheduling objective value can improve the solution quality.Research limitations/implications: In this research, there are some assumptions which reduce the complexity of the large-scale scheduling problem. They are as follows: The processing route of each job is predetermined, and the processing time of each operation is fixed. There is no machine breakdown, and no preemption of the operations is allowed. The assumptions should be considered if the algorithm is used in the actual job shop.Originality/value: The research provides an efficient scheduling method for the

A generic library for large scale solution of PDEs on modern heterogeneous architectures

DEFF Research Database (Denmark)

Glimberg, Stefan Lemvig; Engsig-Karup, Allan Peter

2012-01-01

Adapting to new programming models for modern multi- and many-core architectures requires code-rewriting and changing algorithms and data structures, in order to achieve good efficiency and scalability. We present a generic library for solving large scale partial differential equations (PDEs......), capable of utilizing heterogeneous CPU/GPU environments. The library can be used for fast proto-typing of PDE solvers, based on finite difference approximations of spatial derivatives in one, two, or three dimensions. In order to efficiently solve large scale problems, we keep memory consumption...... and memory access low, using a low-storage implementation of flexible-order finite difference operators. We will illustrate the use of library components by assembling such matrix-free operators to be used with one of the supported iterative solvers, such as GMRES, CG, Multigrid or Defect Correction...

Parallel Quasi Newton Algorithms for Large Scale Non Linear Unconstrained Optimization

International Nuclear Information System (INIS)

Rahman, M. A.; Basarudin, T.

1997-01-01

This paper discusses about Quasi Newton (QN) method to solve non-linear unconstrained minimization problems. One of many important of QN method is choice of matrix Hk. to be positive definite and satisfies to QN method. Our interest here is the parallel QN methods which will suite for the solution of large-scale optimization problems. The QN methods became less attractive in large-scale problems because of the storage and computational requirements. How ever, it is often the case that the Hessian is space matrix. In this paper we include the mechanism of how to reduce the Hessian update and hold the Hessian properties.One major reason of our research is that the QN method may be good in solving certain type of minimization problems, but it is efficiency degenerate when is it applied to solve other category of problems. For this reason, we use an algorithm containing several direction strategies which are processed in parallel. We shall attempt to parallelized algorithm by exploring different search directions which are generated by various QN update during the minimization process. The different line search strategies will be employed simultaneously in the process of locating the minimum along each direction.The code of algorithm will be written in Occam language 2 which is run on the transputer machine

Solving Large Clustering Problems with Meta-Heuristic Search

DEFF Research Database (Denmark)

Turkensteen, Marcel; Andersen, Kim Allan; Bang-Jensen, Jørgen

In Clustering Problems, groups of similar subjects are to be retrieved from data sets. In this paper, Clustering Problems with the frequently used Minimum Sum-of-Squares Criterion are solved using meta-heuristic search. Tabu search has proved to be a successful methodology for solving optimization...... problems, but applications to large clustering problems are rare. The simulated annealing heuristic has mainly been applied to relatively small instances. In this paper, we implement tabu search and simulated annealing approaches and compare them to the commonly used k-means approach. We find that the meta-heuristic...

Theory and algorithms for solving large-scale numerical problems. Application to the management of electricity production

International Nuclear Information System (INIS)

Chiche, A.

2012-01-01

This manuscript deals with large-scale optimization problems, and more specifically with solving the electricity unit commitment problem arising at EDF. First, we focused on the augmented Lagrangian algorithm. The behavior of that algorithm on an infeasible convex quadratic optimization problem is analyzed. It is shown that the algorithm finds a point that satisfies the shifted constraints with the smallest possible shift in the sense of the Euclidean norm and that it minimizes the objective on the corresponding shifted constrained set. The convergence to such a point is realized at a global linear rate, which depends explicitly on the augmentation parameter. This suggests us a rule for determining the augmentation parameter to control the speed of convergence of the shifted constraint norm to zero. This rule has the advantage of generating bounded augmentation parameters even when the problem is infeasible. As a by-product, the algorithm computes the smallest translation in the Euclidean norm that makes the constraints feasible. Furthermore, this work provides solution methods for stochastic optimization industrial problems decomposed on a scenario tree, based on the progressive hedging algorithm introduced by [Rockafellar et Wets, 1991]. We also focus on the convergence of that algorithm. On the one hand, we offer a counter-example showing that the algorithm could diverge if its augmentation parameter is iteratively updated. On the other hand, we show how to recover the multipliers associated with the non-dualized constraints defined on the scenario tree from those associated with the corresponding constraints of the scenario subproblems. Their convergence is also analyzed for convex problems. The practical interest of theses solutions techniques is corroborated by numerical experiments performed on the electric production management problem. We apply the progressive hedging algorithm to a realistic industrial problem. More precisely, we solve the French medium

State of the Art in Large-Scale Soil Moisture Monitoring

Science.gov (United States)

Ochsner, Tyson E.; Cosh, Michael Harold; Cuenca, Richard H.; Dorigo, Wouter; Draper, Clara S.; Hagimoto, Yutaka; Kerr, Yan H.; Larson, Kristine M.; Njoku, Eni Gerald; Small, Eric E.;

How the Internet Will Help Large-Scale Assessment Reinvent Itself

Directory of Open Access Journals (Sweden)

Randy Elliot Bennett

2001-02-01

Full Text Available Large-scale assessment in the United States is undergoing enormous pressure to change. That pressure stems from many causes. Depending upon the type of test, the issues precipitating change include an outmoded cognitive-scientific basis for test design; a mismatch with curriculum; the differential performance of population groups; a lack of information to help individuals improve; and inefficiency. These issues provide a strong motivation to reconceptualize both the substance and the business of large-scale assessment. At the same time, advances in technology, measurement, and cognitive science are providing the means to make that reconceptualization a reality. The thesis of this paper is that the largest facilitating factor will be technological, in particular the Internet. In the same way that it is already helping to revolutionize commerce, education, and even social interaction, the Internet will help revolutionize the business and substance of large-scale assessment.

Speedup predictions on large scientific parallel programs

International Nuclear Information System (INIS)

Williams, E.; Bobrowicz, F.

1985-01-01

How much speedup can we expect for large scientific parallel programs running on supercomputers. For insight into this problem we extend the parallel processing environment currently existing on the Cray X-MP (a shared memory multiprocessor with at most four processors) to a simulated N-processor environment, where N greater than or equal to 1. Several large scientific parallel programs from Los Alamos National Laboratory were run in this simulated environment, and speedups were predicted. A speedup of 14.4 on 16 processors was measured for one of the three most used codes at the Laboratory

Design study on sodium cooled large-scale reactor

International Nuclear Information System (INIS)

Murakami, Tsutomu; Hishida, Masahiko; Kisohara, Naoyuki

2004-07-01

In Phase 1 of the 'Feasibility Studies on Commercialized Fast Reactor Cycle Systems (F/S)', an advanced loop type reactor has been selected as a promising concept of sodium-cooled large-scale reactor, which has a possibility to fulfill the design requirements of the F/S. In Phase 2, design improvement for further cost reduction of establishment of the plant concept has been performed. This report summarizes the results of the design study on the sodium-cooled large-scale reactor performed in JFY2003, which is the third year of Phase 2. In the JFY2003 design study, critical subjects related to safety, structural integrity and thermal hydraulics which found in the last fiscal year has been examined and the plant concept has been modified. Furthermore, fundamental specifications of main systems and components have been set and economy has been evaluated. In addition, as the interim evaluation of the candidate concept of the FBR fuel cycle is to be conducted, cost effectiveness and achievability for the development goal were evaluated and the data of the three large-scale reactor candidate concepts were prepared. As a results of this study, the plant concept of the sodium-cooled large-scale reactor has been constructed, which has a prospect to satisfy the economic goal (construction cost: less than 200,000 yens/kWe, etc.) and has a prospect to solve the critical subjects. From now on, reflecting the results of elemental experiments, the preliminary conceptual design of this plant will be preceded toward the selection for narrowing down candidate concepts at the end of Phase 2. (author)

Design study on sodium-cooled large-scale reactor

International Nuclear Information System (INIS)

Shimakawa, Yoshio; Nibe, Nobuaki; Hori, Toru

2002-05-01

In Phase 1 of the 'Feasibility Study on Commercialized Fast Reactor Cycle Systems (F/S)', an advanced loop type reactor has been selected as a promising concept of sodium-cooled large-scale reactor, which has a possibility to fulfill the design requirements of the F/S. In Phase 2 of the F/S, it is planed to precede a preliminary conceptual design of a sodium-cooled large-scale reactor based on the design of the advanced loop type reactor. Through the design study, it is intended to construct such a plant concept that can show its attraction and competitiveness as a commercialized reactor. This report summarizes the results of the design study on the sodium-cooled large-scale reactor performed in JFY2001, which is the first year of Phase 2. In the JFY2001 design study, a plant concept has been constructed based on the design of the advanced loop type reactor, and fundamental specifications of main systems and components have been set. Furthermore, critical subjects related to safety, structural integrity, thermal hydraulics, operability, maintainability and economy have been examined and evaluated. As a result of this study, the plant concept of the sodium-cooled large-scale reactor has been constructed, which has a prospect to satisfy the economic goal (construction cost: less than 200,000yens/kWe, etc.) and has a prospect to solve the critical subjects. From now on, reflecting the results of elemental experiments, the preliminary conceptual design of this plant will be preceded toward the selection for narrowing down candidate concepts at the end of Phase 2. (author)

Hydrometeorological variability on a large french catchment and its relation to large-scale circulation across temporal scales

Science.gov (United States)

Massei, Nicolas; Dieppois, Bastien; Fritier, Nicolas; Laignel, Benoit; Debret, Maxime; Lavers, David; Hannah, David

2015-04-01

In the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations. In this work, we develop an approach associating large-scale/local-scale correlation, enmpirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations. The results showed that the large-scale/local-scale links were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach which integrated discrete wavelet multiresolution analysis for reconstructing local hydrometeorological processes (predictand : precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector) on a monthly time-step. This approach

Development of a large-scale general purpose two-phase flow analysis code

International Nuclear Information System (INIS)

Terasaka, Haruo; Shimizu, Sensuke

2001-01-01

A general purpose three-dimensional two-phase flow analysis code has been developed for solving large-scale problems in industrial fields. The code uses a two-fluid model to describe the conservation equations for two-phase flow in order to be applicable to various phenomena. Complicated geometrical conditions are modeled by FAVOR method in structured grid systems, and the discretization equations are solved by a modified SIMPLEST scheme. To reduce computing time a matrix solver for the pressure correction equation is parallelized with OpenMP. Results of numerical examples show that the accurate solutions can be obtained efficiently and stably. (author)

Finite-Time Stability of Large-Scale Systems with Interval Time-Varying Delay in Interconnection

Directory of Open Access Journals (Sweden)

T. La-inchua

2017-01-01

Full Text Available We investigate finite-time stability of a class of nonlinear large-scale systems with interval time-varying delays in interconnection. Time-delay functions are continuous but not necessarily differentiable. Based on Lyapunov stability theory and new integral bounding technique, finite-time stability of large-scale systems with interval time-varying delays in interconnection is derived. The finite-time stability criteria are delays-dependent and are given in terms of linear matrix inequalities which can be solved by various available algorithms. Numerical examples are given to illustrate effectiveness of the proposed method.

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

Science.gov (United States)

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

2018-03-01

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

An efficient method based on the uniformity principle for synthesis of large-scale heat exchanger networks

International Nuclear Information System (INIS)

Zhang, Chunwei; Cui, Guomin; Chen, Shang

2016-01-01

Highlights: • Two dimensionless uniformity factors are presented to heat exchange network. • The grouping of process streams reduces the computational complexity of large-scale HENS problems. • The optimal sub-network can be obtained by Powell particle swarm optimization algorithm. • The method is illustrated by a case study involving 39 process streams, with a better solution. - Abstract: The optimal design of large-scale heat exchanger networks is a difficult task due to the inherent non-linear characteristics and the combinatorial nature of heat exchangers. To solve large-scale heat exchanger network synthesis (HENS) problems, two dimensionless uniformity factors to describe the heat exchanger network (HEN) uniformity in terms of the temperature difference and the accuracy of process stream grouping are deduced. Additionally, a novel algorithm that combines deterministic and stochastic optimizations to obtain an optimal sub-network with a suitable heat load for a given group of streams is proposed, and is named the Powell particle swarm optimization (PPSO). As a result, the synthesis of large-scale heat exchanger networks is divided into two corresponding sub-parts, namely, the grouping of process streams and the optimization of sub-networks. This approach reduces the computational complexity and increases the efficiency of the proposed method. The robustness and effectiveness of the proposed method are demonstrated by solving a large-scale HENS problem involving 39 process streams, and the results obtained are better than those previously published in the literature.

Bonus algorithm for large scale stochastic nonlinear programming problems

CERN Document Server

Diwekar, Urmila

2015-01-01

This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power systems, and capacity expansion of energy systems. A generalized method for stochastic nonlinear programming based on a sampling based approach for uncertainty analysis and statistical reweighting to obtain probability information is demonstrated in this book. Stochastic optimization problems are difficult to solve since they involve dealing with optimization and uncertainty loops. There are two fundamental approaches used to solve such problems. The first being the decomposition techniques and the second method identifies problem specific structures and transforms the problem into a deterministic nonlinear programming problem. These techniques have significant limitations on either the objective function type or the underlying distributions for the uncertain variables. Moreover, these ...

Engineering large-scale agent-based systems with consensus

Science.gov (United States)

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.

Large-scale theoretical calculations in molecular science - design of a large computer system for molecular science and necessary conditions for future computers

Energy Technology Data Exchange (ETDEWEB)

Kashiwagi, H [Institute for Molecular Science, Okazaki, Aichi (Japan)

1982-06-01

A large computer system was designed and established for molecular science under the leadership of molecular scientists. Features of the computer system are an automated operation system and an open self-service system. Large-scale theoretical calculations have been performed to solve many problems in molecular science, using the computer system. Necessary conditions for future computers are discussed on the basis of this experience.

Large-scale theoretical calculations in molecular science - design of a large computer system for molecular science and necessary conditions for future computers

International Nuclear Information System (INIS)

Kashiwagi, H.

1982-01-01

A large computer system was designed and established for molecular science under the leadership of molecular scientists. Features of the computer system are an automated operation system and an open self-service system. Large-scale theoretical calculations have been performed to solve many problems in molecular science, using the computer system. Necessary conditions for future computers are discussed on the basis of this experience. (orig.)

Subgrid-scale models for large-eddy simulation of rotating turbulent channel flows

Science.gov (United States)

Silvis, Maurits H.; Bae, Hyunji Jane; Trias, F. Xavier; Abkar, Mahdi; Moin, Parviz; Verstappen, Roel

2017-11-01

We aim to design subgrid-scale models for large-eddy simulation of rotating turbulent flows. Rotating turbulent flows form a challenging test case for large-eddy simulation due to the presence of the Coriolis force. The Coriolis force conserves the total kinetic energy while transporting it from small to large scales of motion, leading to the formation of large-scale anisotropic flow structures. The Coriolis force may also cause partial flow laminarization and the occurrence of turbulent bursts. Many subgrid-scale models for large-eddy simulation are, however, primarily designed to parametrize the dissipative nature of turbulent flows, ignoring the specific characteristics of transport processes. We, therefore, propose a new subgrid-scale model that, in addition to the usual dissipative eddy viscosity term, contains a nondissipative nonlinear model term designed to capture transport processes, such as those due to rotation. We show that the addition of this nonlinear model term leads to improved predictions of the energy spectra of rotating homogeneous isotropic turbulence as well as of the Reynolds stress anisotropy in spanwise-rotating plane-channel flows. This work is financed by the Netherlands Organisation for Scientific Research (NWO) under Project Number 613.001.212.

Large-scale solar purchasing

International Nuclear Information System (INIS)

1999-01-01

The principal objective of the project was to participate in the definition of a new IEA task concerning solar procurement (''the Task'') and to assess whether involvement in the task would be in the interest of the UK active solar heating industry. The project also aimed to assess the importance of large scale solar purchasing to UK active solar heating market development and to evaluate the level of interest in large scale solar purchasing amongst potential large scale purchasers (in particular housing associations and housing developers). A further aim of the project was to consider means of stimulating large scale active solar heating purchasing activity within the UK. (author)

Generation Expansion Planning Considering Integrating Large-scale Wind Generation

DEFF Research Database (Denmark)

Zhang, Chunyu; Ding, Yi; Østergaard, Jacob

2013-01-01

necessitated the inclusion of more innovative and sophisticated approaches in power system investment planning. A bi-level generation expansion planning approach considering large-scale wind generation was proposed in this paper. The first phase is investment decision, while the second phase is production...... optimization decision. A multi-objective PSO (MOPSO) algorithm was introduced to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of the proposed bi-level planning approach and the MOPSO...

Scientific Reasoning and Its Relationship with Problem Solving: The Case of Upper Primary Science Teachers

Science.gov (United States)

Alshamali, Mahmoud A.; Daher, Wajeeh M.

2016-01-01

This study aimed at identifying the levels of scientific reasoning of upper primary stage (grades 4-7) science teachers based on their use of a problem-solving strategy. The study sample (N = 138; 32 % male and 68 % female) was randomly selected using stratified sampling from an original population of 437 upper primary school teachers. The…

Challenges in Managing Trustworthy Large-scale Digital Science

Science.gov (United States)

Evans, B. J. K.

2017-12-01

The increased use of large-scale international digital science has opened a number of challenges for managing, handling, using and preserving scientific information. The large volumes of information are driven by three main categories - model outputs including coupled models and ensembles, data products that have been processing to a level of usability, and increasingly heuristically driven data analysis. These data products are increasingly the ones that are usable by the broad communities, and far in excess of the raw instruments data outputs. The data, software and workflows are then shared and replicated to allow broad use at an international scale, which places further demands of infrastructure to support how the information is managed reliably across distributed resources. Users necessarily rely on these underlying "black boxes" so that they are productive to produce new scientific outcomes. The software for these systems depend on computational infrastructure, software interconnected systems, and information capture systems. This ranges from the fundamentals of the reliability of the compute hardware, system software stacks and libraries, and the model software. Due to these complexities and capacity of the infrastructure, there is an increased emphasis of transparency of the approach and robustness of the methods over the full reproducibility. Furthermore, with large volume data management, it is increasingly difficult to store the historical versions of all model and derived data. Instead, the emphasis is on the ability to access the updated products and the reliability by which both previous outcomes are still relevant and can be updated for the new information. We will discuss these challenges and some of the approaches underway that are being used to address these issues.

Imprint of thawing scalar fields on the large scale galaxy overdensity

Science.gov (United States)

Dinda, Bikash R.; Sen, Anjan A.

2018-04-01

We investigate the observed galaxy power spectrum for the thawing class of scalar field models taking into account various general relativistic corrections that occur on very large scales. We consider the full general relativistic perturbation equations for the matter as well as the dark energy fluid. We form a single autonomous system of equations containing both the background and the perturbed equations of motion which we subsequently solve for different scalar field potentials. First we study the percentage deviation from the Λ CDM model for different cosmological parameters as well as in the observed galaxy power spectra on different scales in scalar field models for various choices of scalar field potentials. Interestingly the difference in background expansion results from the enhancement of power from Λ CDM on small scales, whereas the inclusion of general relativistic (GR) corrections results in the suppression of power from Λ CDM on large scales. This can be useful to distinguish scalar field models from Λ CDM with future optical/radio surveys. We also compare the observed galaxy power spectra for tracking and thawing types of scalar field using some particular choices for the scalar field potentials. We show that thawing and tracking models can have large differences in observed galaxy power spectra on large scales and for smaller redshifts due to different GR effects. But on smaller scales and for larger redshifts, the difference is small and is mainly due to the difference in background expansion.

Solution approach for a large scale personnel transport system for a large company in Latin America

Energy Technology Data Exchange (ETDEWEB)

Garzón-Garnica, Eduardo-Arturo; Caballero-Morales, Santiago-Omar; Martínez-Flores, José-Luis

2017-07-01

The present paper focuses on the modelling and solution of a large-scale personnel transportation system in Mexico where many routes and vehicles are currently used to service 525 points. The routing system proposed can be applied to many cities in the Latin-American region. Design/methodology/approach: This system was modelled as a VRP model considering the use of real-world transit times, and the fact that routes start at the farthest point from the destination center. Experiments were performed on different sized sets of service points. As the size of the instances was increased, the performance of the heuristic method was assessed in comparison with the results of an exact algorithm, the results remaining very close between both. When the size of the instance was full-scale and the exact algorithm took too much time to solve the problem, then the heuristic algorithm provided a feasible solution. Supported by the validation with smaller scale instances, where the difference between both solutions was close to a 6%, the full –scale solution obtained with the heuristic algorithm was considered to be within that same range. Findings: The proposed modelling and solving method provided a solution that would produce significant savings in the daily operation of the routes. Originality/value: The urban distribution of the cities in Latin America is unique to other regions in the world. The general layout of the large cities in this region includes a small town center, usually antique, and a somewhat disordered outer region. The lack of a vehicle-centered urban planning poses distinct challenges for vehicle routing problems in the region. The use of a heuristic VRP combined with the results of an exact VRP, allowed the obtention of an improved routing plan specific to the requirements of the region.

Solution approach for a large scale personnel transport system for a large company in Latin America

International Nuclear Information System (INIS)

Garzón-Garnica, Eduardo-Arturo; Caballero-Morales, Santiago-Omar; Martínez-Flores, José-Luis

2017-01-01

The present paper focuses on the modelling and solution of a large-scale personnel transportation system in Mexico where many routes and vehicles are currently used to service 525 points. The routing system proposed can be applied to many cities in the Latin-American region. Design/methodology/approach: This system was modelled as a VRP model considering the use of real-world transit times, and the fact that routes start at the farthest point from the destination center. Experiments were performed on different sized sets of service points. As the size of the instances was increased, the performance of the heuristic method was assessed in comparison with the results of an exact algorithm, the results remaining very close between both. When the size of the instance was full-scale and the exact algorithm took too much time to solve the problem, then the heuristic algorithm provided a feasible solution. Supported by the validation with smaller scale instances, where the difference between both solutions was close to a 6%, the full –scale solution obtained with the heuristic algorithm was considered to be within that same range. Findings: The proposed modelling and solving method provided a solution that would produce significant savings in the daily operation of the routes. Originality/value: The urban distribution of the cities in Latin America is unique to other regions in the world. The general layout of the large cities in this region includes a small town center, usually antique, and a somewhat disordered outer region. The lack of a vehicle-centered urban planning poses distinct challenges for vehicle routing problems in the region. The use of a heuristic VRP combined with the results of an exact VRP, allowed the obtention of an improved routing plan specific to the requirements of the region.

Solution approach for a large scale personnel transport system for a large company in Latin America

Directory of Open Access Journals (Sweden)

Eduardo-Arturo Garzón-Garnica

2017-10-01

Full Text Available Purpose: The present paper focuses on the modelling and solution of a large-scale personnel transportation system in Mexico where many routes and vehicles are currently used to service 525 points. The routing system proposed can be applied to many cities in the Latin-American region. Design/methodology/approach: This system was modelled as a VRP model considering the use of real-world transit times, and the fact that routes start at the farthest point from the destination center. Experiments were performed on different sized sets of service points. As the size of the instances was increased, the performance of the heuristic method was assessed in comparison with the results of an exact algorithm, the results remaining very close between both.  When the size of the instance was full-scale and the exact algorithm took too much time to solve the problem, then the heuristic algorithm provided a feasible solution. Supported by the validation with smaller scale instances, where the difference between both solutions was close to a 6%, the full –scale solution obtained with the heuristic algorithm was considered to be within that same range. Findings: The proposed modelling and solving method provided a solution that would produce significant savings in the daily operation of the routes. Originality/value: The urban distribution of the cities in Latin America is unique to other regions in the world. The general layout of the large cities in this region includes a small town center, usually antique, and a somewhat disordered outer region. The lack of a vehicle-centered urban planning poses distinct challenges for vehicle routing problems in the region. The use of a heuristic VRP combined with the results of an exact VRP, allowed the obtention of an improved routing plan specific to the requirements of the region.

Large scale electronic structure calculations in the study of the condensed phase

NARCIS (Netherlands)

van Dam, H.J.J.; Guest, M.F.; Sherwood, P.; Thomas, J.M.H.; van Lenthe, J.H.; van Lingen, J.N.J.; Bailey, C.L.; Bush, I.J.

2006-01-01

We consider the role that large-scale electronic structure computations can now play in the modelling of the condensed phase. To structure our analysis, we consider four distict ways in which today's scientific targets can be re-scoped to take advantage of advances in computing resources: 1. time to

Bilevel Traffic Evacuation Model and Algorithm Design for Large-Scale Activities

Directory of Open Access Journals (Sweden)

Danwen Bao

2017-01-01

Full Text Available This paper establishes a bilevel planning model with one master and multiple slaves to solve traffic evacuation problems. The minimum evacuation network saturation and shortest evacuation time are used as the objective functions for the upper- and lower-level models, respectively. The optimizing conditions of this model are also analyzed. An improved particle swarm optimization (PSO method is proposed by introducing an electromagnetism-like mechanism to solve the bilevel model and enhance its convergence efficiency. A case study is carried out using the Nanjing Olympic Sports Center. The results indicate that, for large-scale activities, the average evacuation time of the classic model is shorter but the road saturation distribution is more uneven. Thus, the overall evacuation efficiency of the network is not high. For induced emergencies, the evacuation time of the bilevel planning model is shortened. When the audience arrival rate is increased from 50% to 100%, the evacuation time is shortened from 22% to 35%, indicating that the optimization effect of the bilevel planning model is more effective compared to the classic model. Therefore, the model and algorithm presented in this paper can provide a theoretical basis for the traffic-induced evacuation decision making of large-scale activities.

Partially acoustic dark matter, interacting dark radiation, and large scale structure

Energy Technology Data Exchange (ETDEWEB)

Chacko, Zackaria [Maryland Center for Fundamental Physics, Department of Physics, University of Maryland,Stadium Dr., College Park, MD 20742 (United States); Cui, Yanou [Maryland Center for Fundamental Physics, Department of Physics, University of Maryland,Stadium Dr., College Park, MD 20742 (United States); Department of Physics and Astronomy, University of California-Riverside,University Ave, Riverside, CA 92521 (United States); Perimeter Institute, 31 Caroline Street, North Waterloo, Ontario N2L 2Y5 (Canada); Hong, Sungwoo [Maryland Center for Fundamental Physics, Department of Physics, University of Maryland,Stadium Dr., College Park, MD 20742 (United States); Okui, Takemichi [Department of Physics, Florida State University,College Avenue, Tallahassee, FL 32306 (United States); Tsai, Yuhsinz [Maryland Center for Fundamental Physics, Department of Physics, University of Maryland,Stadium Dr., College Park, MD 20742 (United States)

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{sub 0} and the matter density perturbation σ{sub 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{sub 8} problem, while the presence of tightly coupled dark radiation ameliorates the H{sub 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

International Nuclear Information System (INIS)

Chacko, Zackaria; Cui, Yanou; Hong, Sungwoo; Okui, Takemichi; Tsai, Yuhsinz

2016-01-01

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.

Bayesian Inversion for Large Scale Antarctic Ice Sheet Flow

KAUST Repository

Ghattas, Omar

2015-01-07

The flow of ice from the interior of polar ice sheets is the primary contributor to projected sea level rise. One of the main difficulties faced in modeling ice sheet flow is the uncertain spatially-varying Robin boundary condition that describes the resistance to sliding at the base of the ice. Satellite observations of the surface ice flow velocity, along with a model of ice as a creeping incompressible shear-thinning fluid, can be used to infer this uncertain basal boundary condition. We cast this ill-posed inverse problem in the framework of Bayesian inference, which allows us to infer not only the basal sliding parameters, but also the associated uncertainty. To overcome the prohibitive nature of Bayesian methods for large-scale inverse problems, we exploit the fact that, despite the large size of observational data, they typically provide only sparse information on model parameters. We show results for Bayesian inversion of the basal sliding parameter field for the full Antarctic continent, and demonstrate that the work required to solve the inverse problem, measured in number of forward (and adjoint) ice sheet model solves, is independent of the parameter and data dimensions

Bayesian Inversion for Large Scale Antarctic Ice Sheet Flow

KAUST Repository

Ghattas, Omar

2015-01-01

The flow of ice from the interior of polar ice sheets is the primary contributor to projected sea level rise. One of the main difficulties faced in modeling ice sheet flow is the uncertain spatially-varying Robin boundary condition that describes the resistance to sliding at the base of the ice. Satellite observations of the surface ice flow velocity, along with a model of ice as a creeping incompressible shear-thinning fluid, can be used to infer this uncertain basal boundary condition. We cast this ill-posed inverse problem in the framework of Bayesian inference, which allows us to infer not only the basal sliding parameters, but also the associated uncertainty. To overcome the prohibitive nature of Bayesian methods for large-scale inverse problems, we exploit the fact that, despite the large size of observational data, they typically provide only sparse information on model parameters. We show results for Bayesian inversion of the basal sliding parameter field for the full Antarctic continent, and demonstrate that the work required to solve the inverse problem, measured in number of forward (and adjoint) ice sheet model solves, is independent of the parameter and data dimensions

Improved Monkey-King Genetic Algorithm for Solving Large Winner Determination in Combinatorial Auction

Science.gov (United States)

Li, Yuzhong

Using GA solve the winner determination problem (WDP) with large bids and items, run under different distribution, because the search space is large, constraint complex and it may easy to produce infeasible solution, would affect the efficiency and quality of algorithm. This paper present improved MKGA, including three operator: preprocessing, insert bid and exchange recombination, and use Monkey-king elite preservation strategy. Experimental results show that improved MKGA is better than SGA in population size and computation. The problem that traditional branch and bound algorithm hard to solve, improved MKGA can solve and achieve better effect.

Improved decomposition–coordination and discrete differential dynamic programming for optimization of large-scale hydropower system

International Nuclear Information System (INIS)

Li, Chunlong; Zhou, Jianzhong; Ouyang, Shuo; Ding, Xiaoling; Chen, Lu

2014-01-01

Highlights: • Optimization of large-scale hydropower system in the Yangtze River basin. • Improved decomposition–coordination and discrete differential dynamic programming. • Generating initial solution randomly to reduce generation time. • Proposing relative coefficient for more power generation. • Proposing adaptive bias corridor technology to enhance convergence speed. - Abstract: With the construction of major hydro plants, more and more large-scale hydropower systems are taking shape gradually, which brings up a challenge to optimize these systems. Optimization of large-scale hydropower system (OLHS), which is to determine water discharges or water levels of overall hydro plants for maximizing total power generation when subjecting to lots of constrains, is a high dimensional, nonlinear and coupling complex problem. In order to solve the OLHS problem effectively, an improved decomposition–coordination and discrete differential dynamic programming (IDC–DDDP) method is proposed in this paper. A strategy that initial solution is generated randomly is adopted to reduce generation time. Meanwhile, a relative coefficient based on maximum output capacity is proposed for more power generation. Moreover, an adaptive bias corridor technology is proposed to enhance convergence speed. The proposed method is applied to long-term optimal dispatches of large-scale hydropower system (LHS) in the Yangtze River basin. Compared to other methods, IDC–DDDP has competitive performances in not only total power generation but also convergence speed, which provides a new method to solve the OLHS problem

Research on unit commitment with large-scale wind power connected power system

Science.gov (United States)

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.

Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso.

Science.gov (United States)

Mazumder, Rahul; Hastie, Trevor

2012-03-01

We consider the sparse inverse covariance regularization problem or graphical lasso with regularization parameter λ. Suppose the sample covariance graph formed by thresholding the entries of the sample covariance matrix at λ is decomposed into connected components. We show that the vertex-partition induced by the connected components of the thresholded sample covariance graph (at λ) is exactly equal to that induced by the connected components of the estimated concentration graph, obtained by solving the graphical lasso problem for the same λ. This characterizes a very interesting property of a path of graphical lasso solutions. Furthermore, this simple rule, when used as a wrapper around existing algorithms for the graphical lasso, leads to enormous performance gains. For a range of values of λ, our proposal splits a large graphical lasso problem into smaller tractable problems, making it possible to solve an otherwise infeasible large-scale problem. We illustrate the graceful scalability of our proposal via synthetic and real-life microarray examples.

Influence of Family Processes, Motivation, and Beliefs about Intelligence on Creative Problem Solving of Scientifically Talented Individuals

Science.gov (United States)

Cho, Seokhee; Lin, Chia-Yi

2011-01-01

Predictive relationships among perceived family processes, intrinsic and extrinsic motivation, incremental beliefs about intelligence, confidence in intelligence, and creative problem-solving practices in mathematics and science were examined. Participants were 733 scientifically talented Korean students in fourth through twelfth grades as well as…

Do you kiss your mother with that mouth? An authentic large-scale undergraduate research experience in mapping the human oral microbiome.

Science.gov (United States)

Wang, Jack T H; Daly, Joshua N; Willner, Dana L; Patil, Jayee; Hall, Roy A; Schembri, Mark A; Tyson, Gene W; Hugenholtz, Philip

2015-05-01

Clinical microbiology testing is crucial for the diagnosis and treatment of community and hospital-acquired infections. Laboratory scientists need to utilize technical and problem-solving skills to select from a wide array of microbial identification techniques. The inquiry-driven laboratory training required to prepare microbiology graduates for this professional environment can be difficult to replicate within undergraduate curricula, especially in courses that accommodate large student cohorts. We aimed to improve undergraduate scientific training by engaging hundreds of introductory microbiology students in an Authentic Large-Scale Undergraduate Research Experience (ALURE). The ALURE aimed to characterize the microorganisms that reside in the healthy human oral cavity-the oral microbiome-by analyzing hundreds of samples obtained from student volunteers within the course. Students were able to choose from selective and differential culture media, Gram-staining, microscopy, as well as polymerase chain reaction (PCR) and 16S rRNA gene sequencing techniques, in order to collect, analyze, and interpret novel data to determine the collective oral microbiome of the student cohort. Pre- and postsurvey analysis of student learning gains across two iterations of the course (2012-2013) revealed significantly higher student confidence in laboratory skills following the completion of the ALURE (p < 0.05 using the Mann-Whitney U-test). Learning objectives on effective scientific communication were also met through effective student performance in laboratory reports describing the research outcomes of the project. The integration of undergraduate research in clinical microbiology has the capacity to deliver authentic research experiences and improve scientific training for large cohorts of undergraduate students.

XVIS: Visualization for the Extreme-Scale Scientific-Computation Ecosystem Final Scientific/Technical Report

Energy Technology Data Exchange (ETDEWEB)

Geveci, Berk [Kitware, Inc., Clifton Park, NY (United States); Maynard, Robert [Kitware, Inc., Clifton Park, NY (United States)

2017-10-27

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. The XVis project brought together collaborators from predominant DOE projects for visualization on accelerators and combining their respective features into a new visualization toolkit called VTK-m.

Large-scale road safety programmes in low- and middle-income countries: an opportunity to generate evidence.

Science.gov (United States)

Hyder, Adnan A; Allen, Katharine A; Peters, David H; Chandran, Aruna; Bishai, David

2013-01-01

The growing burden of road traffic injuries, which kill over 1.2 million people yearly, falls mostly on low- and middle-income countries (LMICs). Despite this, evidence generation on the effectiveness of road safety interventions in LMIC settings remains scarce. This paper explores a scientific approach for evaluating road safety programmes in LMICs and introduces such a road safety multi-country initiative, the Road Safety in 10 Countries Project (RS-10). By building on existing evaluation frameworks, we develop a scientific approach for evaluating large-scale road safety programmes in LMIC settings. This also draws on '13 lessons' of large-scale programme evaluation: defining the evaluation scope; selecting study sites; maintaining objectivity; developing an impact model; utilising multiple data sources; using multiple analytic techniques; maximising external validity; ensuring an appropriate time frame; the importance of flexibility and a stepwise approach; continuous monitoring; providing feedback to implementers, policy-makers; promoting the uptake of evaluation results; and understanding evaluation costs. The use of relatively new approaches for evaluation of real-world programmes allows for the production of relevant knowledge. The RS-10 project affords an important opportunity to scientifically test these approaches for a real-world, large-scale road safety evaluation and generate new knowledge for the field of road safety.

Methods of Scientific Research: Teaching Scientific Creativity at Scale

Science.gov (United States)

Robbins, Dennis; Ford, K. E. Saavik

2016-01-01

We present a scaling-up plan for AstroComNYC's Methods of Scientific Research (MSR), a course designed to improve undergraduate students' understanding of science practices. The course format and goals, notably the open-ended, hands-on, investigative nature of the curriculum are reviewed. We discuss how the course's interactive pedagogical techniques empower students to learn creativity within the context of experimental design and control of variables thinking. To date the course has been offered to a limited numbers of students in specific programs. The goals of broadly implementing MSR is to reach more students and early in their education—with the specific purpose of supporting and improving retention of students pursuing STEM careers. However, we also discuss challenges in preserving the effectiveness of the teaching and learning experience at scale.

Nearly incompressible fluids: Hydrodynamics and large scale inhomogeneity

International Nuclear Information System (INIS)

Hunana, P.; Zank, G. P.; Shaikh, D.

2006-01-01

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)

Moditored unsaturated soil transport processes as a support for large scale soil and water management

Science.gov (United States)

Vanclooster, Marnik

2010-05-01

The current societal demand for sustainable soil and water management is very large. The drivers of global and climate change exert many pressures on the soil and water ecosystems, endangering appropriate ecosystem functioning. The unsaturated soil transport processes play a key role in soil-water system functioning as it controls the fluxes of water and nutrients from the soil to plants (the pedo-biosphere link), the infiltration flux of precipitated water to groundwater and the evaporative flux, and hence the feed back from the soil to the climate system. Yet, unsaturated soil transport processes are difficult to quantify since they are affected by huge variability of the governing properties at different space-time scales and the intrinsic non-linearity of the transport processes. The incompatibility of the scales between the scale at which processes reasonably can be characterized, the scale at which the theoretical process correctly can be described and the scale at which the soil and water system need to be managed, calls for further development of scaling procedures in unsaturated zone science. It also calls for a better integration of theoretical and modelling approaches to elucidate transport processes at the appropriate scales, compatible with the sustainable soil and water management objective. Moditoring science, i.e the interdisciplinary research domain where modelling and monitoring science are linked, is currently evolving significantly in the unsaturated zone hydrology area. In this presentation, a review of current moditoring strategies/techniques will be given and illustrated for solving large scale soil and water management problems. This will also allow identifying research needs in the interdisciplinary domain of modelling and monitoring and to improve the integration of unsaturated zone science in solving soil and water management issues. A focus will be given on examples of large scale soil and water management problems in Europe.

An algebraic sub-structuring method for large-scale eigenvalue calculation

International Nuclear Information System (INIS)

Yang, C.; Gao, W.; Bai, Z.; Li, X.; Lee, L.; Husbands, P.; Ng, E.

2004-01-01

We examine sub-structuring methods for solving large-scale generalized eigenvalue problems from a purely algebraic point of view. We use the term 'algebraic sub-structuring' to refer to the process of applying matrix reordering and partitioning algorithms to divide a large sparse matrix into smaller submatrices from which a subset of spectral components are extracted and combined to provide approximate solutions to the original problem. We are interested in the question of which spectral components one should extract from each sub-structure in order to produce an approximate solution to the original problem with a desired level of accuracy. Error estimate for the approximation to the smallest eigenpair is developed. The estimate leads to a simple heuristic for choosing spectral components (modes) from each sub-structure. The effectiveness of such a heuristic is demonstrated with numerical examples. We show that algebraic sub-structuring can be effectively used to solve a generalized eigenvalue problem arising from the simulation of an accelerator structure. One interesting characteristic of this application is that the stiffness matrix produced by a hierarchical vector finite elements scheme contains a null space of large dimension. We present an efficient scheme to deflate this null space in the algebraic sub-structuring process

Hierarchical optimal control of large-scale nonlinear chemical processes.

Science.gov (United States)

Ramezani, Mohammad Hossein; Sadati, Nasser

2009-01-01

In this paper, a new approach is presented for optimal control of large-scale chemical processes. In this approach, the chemical process is decomposed into smaller sub-systems at the first level, and a coordinator at the second level, for which a two-level hierarchical control strategy is designed. For this purpose, each sub-system in the first level can be solved separately, by using any conventional optimization algorithm. In the second level, the solutions obtained from the first level are coordinated using a new gradient-type strategy, which is updated by the error of the coordination vector. The proposed algorithm is used to solve the optimal control problem of a complex nonlinear chemical stirred tank reactor (CSTR), where its solution is also compared with the ones obtained using the centralized approach. The simulation results show the efficiency and the capability of the proposed hierarchical approach, in finding the optimal solution, over the centralized method.

Recent developments in large-scale ozone generation with dielectric barrier discharges

Science.gov (United States)

Lopez, Jose L.

2014-10-01

Large-scale ozone generation for industrial applications has been entirely based on the creation of microplasmas or microdischarges created using dielectric barrier discharge (DBD) reactors. Although versions of DBD generated ozone have been in continuous use for over a hundred years especially in water treatment, recent changes in environmental awareness and sustainability have lead to a surge of ozone generating facilities throughout the world. As a result of this enhanced global usage of this environmental cleaning application various new discoveries have emerged in the science and technology of ozone generation. This presentation will describe some of the most recent breakthrough developments in large-scale ozone generation while further addressing some of the current scientific and engineering challenges of this technology.

Web-based visualization of very large scientific astronomy imagery

Science.gov (United States)

Bertin, E.; Pillay, R.; Marmo, C.

2015-04-01

Visualizing and navigating through large astronomy images from a remote location with current astronomy display tools can be a frustrating experience in terms of speed and ergonomics, especially on mobile devices. In this paper, we present a high performance, versatile and robust client-server system for remote visualization and analysis of extremely large scientific images. Applications of this work include survey image quality control, interactive data query and exploration, citizen science, as well as public outreach. The proposed software is entirely open source and is designed to be generic and applicable to a variety of datasets. It provides access to floating point data at terabyte scales, with the ability to precisely adjust image settings in real-time. The proposed clients are light-weight, platform-independent web applications built on standard HTML5 web technologies and compatible with both touch and mouse-based devices. We put the system to the test and assess the performance of the system and show that a single server can comfortably handle more than a hundred simultaneous users accessing full precision 32 bit astronomy data.

Integrated fringe projection 3D scanning system for large-scale metrology based on laser tracker

Science.gov (United States)

Du, Hui; Chen, Xiaobo; Zhou, Dan; Guo, Gen; Xi, Juntong

2017-10-01

Large scale components exist widely in advance manufacturing industry,3D profilometry plays a pivotal role for the quality control. This paper proposes a flexible, robust large-scale 3D scanning system by integrating a robot with a binocular structured light scanner and a laser tracker. The measurement principle and system construction of the integrated system are introduced. And a mathematical model is established for the global data fusion. Subsequently, a flexible and robust method and mechanism is introduced for the establishment of the end coordination system. Based on this method, a virtual robot noumenon is constructed for hand-eye calibration. And then the transformation matrix between end coordination system and world coordination system is solved. Validation experiment is implemented for verifying the proposed algorithms. Firstly, hand-eye transformation matrix is solved. Then a car body rear is measured for 16 times for the global data fusion algorithm verification. And the 3D shape of the rear is reconstructed successfully.

Energy transfers in large-scale and small-scale dynamos

Science.gov (United States)

Samtaney, Ravi; Kumar, Rohit; Verma, Mahendra

2015-11-01

We present the energy transfers, mainly energy fluxes and shell-to-shell energy transfers in small-scale dynamo (SSD) and large-scale dynamo (LSD) using numerical simulations of MHD turbulence for Pm = 20 (SSD) and for Pm = 0.2 on 10243 grid. For SSD, we demonstrate that the magnetic energy growth is caused by nonlocal energy transfers from the large-scale or forcing-scale velocity field to small-scale magnetic field. The peak of these energy transfers move towards lower wavenumbers as dynamo evolves, which is the reason for the growth of the magnetic fields at the large scales. The energy transfers U2U (velocity to velocity) and B2B (magnetic to magnetic) are forward and local. For LSD, we show that the magnetic energy growth takes place via energy transfers from large-scale velocity field to large-scale magnetic field. We observe forward U2U and B2B energy flux, similar to SSD.

Solving and Interpreting Large-scale Harvest Scheduling Problems by Duality and Decomposition

OpenAIRE

Berck, Peter; Bible, Thomas

1982-01-01

This paper presents a solution to the forest planning problem that takes advantage of both the duality of linear programming formulations currently being used for harvest scheduling and the characteristics of decomposition inherent in the forest land class-relationship. The subproblems of decomposition, defined as the dual, can be solved in a simple, recursive fashion. In effect, such a technique reduces the computational burden in terms of time and computer storage as compared to the traditi...

On distributed wavefront reconstruction for large-scale adaptive optics systems.

Science.gov (United States)

de Visser, Cornelis C; Brunner, Elisabeth; Verhaegen, Michel

2016-05-01

The distributed-spline-based aberration reconstruction (D-SABRE) method is proposed for distributed wavefront reconstruction with applications to large-scale adaptive optics systems. D-SABRE decomposes the wavefront sensor domain into any number of partitions and solves a local wavefront reconstruction problem on each partition using multivariate splines. D-SABRE accuracy is within 1% of a global approach with a speedup that scales quadratically with the number of partitions. The D-SABRE is compared to the distributed cumulative reconstruction (CuRe-D) method in open-loop and closed-loop simulations using the YAO adaptive optics simulation tool. D-SABRE accuracy exceeds CuRe-D for low levels of decomposition, and D-SABRE proved to be more robust to variations in the loop gain.

An inertia-free filter line-search algorithm for large-scale nonlinear programming

Energy Technology Data Exchange (ETDEWEB)

Chiang, Nai-Yuan; Zavala, Victor M.

2016-02-15

We present a filter line-search algorithm that does not require inertia information of the linear system. This feature enables the use of a wide range of linear algebra strategies and libraries, which is essential to tackle large-scale problems on modern computing architectures. The proposed approach performs curvature tests along the search step to detect negative curvature and to trigger convexification. We prove that the approach is globally convergent and we implement the approach within a parallel interior-point framework to solve large-scale and highly nonlinear problems. Our numerical tests demonstrate that the inertia-free approach is as efficient as inertia detection via symmetric indefinite factorizations. We also demonstrate that the inertia-free approach can lead to reductions in solution time because it reduces the amount of convexification needed.

Learning biology through connecting mathematics to scientific mechanisms: Student outcomes and teacher supports

Science.gov (United States)

Schuchardt, Anita

Integrating mathematics into science classrooms has been part of the conversation in science education for a long time. However, studies on student learning after incorporating mathematics in to the science classroom have shown mixed results. Understanding the mixed effects of including mathematics in science has been hindered by a historical focus on characteristics of integration tangential to student learning (e.g., shared elements, extent of integration). A new framework is presented emphasizing the epistemic role of mathematics in science. An epistemic role of mathematics missing from the current literature is identified: use of mathematics to represent scientific mechanisms, Mechanism Connected Mathematics (MCM). Building on prior theoretical work, it is proposed that having students develop mathematical equations that represent scientific mechanisms could elevate their conceptual understanding and quantitative problem solving. Following design and implementation of an MCM unit in inheritance, a large-scale quantitative analysis of pre and post implementation test results showed MCM students, compared to traditionally instructed students) had significantly greater gains in conceptual understanding of mathematically modeled scientific mechanisms, and their ability to solve complex quantitative problems. To gain insight into the mechanism behind the gain in quantitative problem solving, a small-scale qualitative study was conducted of two contrasting groups: 1) within-MCM instruction: competent versus struggling problem solvers, and 2) within-competent problem solvers: MCM instructed versus traditionally instructed. Competent MCM students tended to connect their mathematical inscriptions to the scientific phenomenon and to switch between mathematical and scientifically productive approaches during problem solving in potentially productive ways. The other two groups did not. To address concerns about teacher capacity presenting barriers to scalability of MCM

Technologies for Large Data Management in Scientific Computing

CERN Document Server

Pace, A

2014-01-01

In recent years, intense usage of computing has been the main strategy of investigations in several scientific research projects. The progress in computing technology has opened unprecedented opportunities for systematic collection of experimental data and the associated analysis that were considered impossible only few years ago. This paper focusses on the strategies in use: it reviews the various components that are necessary for an effective solution that ensures the storage, the long term preservation, and the worldwide distribution of large quantities of data that are necessary in a large scientific research project. The paper also mentions several examples of data management solutions used in High Energy Physics for the CERN Large Hadron Collider (LHC) experiments in Geneva, Switzerland which generate more than 30,000 terabytes of data every year that need to be preserved, analyzed, and made available to a community of several tenth of thousands scientists worldwide.

Large-scale computation in solid state physics - Recent developments and prospects

International Nuclear Information System (INIS)

DeVreese, J.T.

1985-01-01

During the past few years an increasing interest in large-scale computation is developing. Several initiatives were taken to evaluate and exploit the potential of ''supercomputers'' like the CRAY-1 (or XMP) or the CYBER-205. In the U.S.A., there first appeared the Lax report in 1982 and subsequently (1984) the National Science Foundation in the U.S.A. announced a program to promote large-scale computation at the universities. Also, in Europe several CRAY- and CYBER-205 systems have been installed. Although the presently available mainframes are the result of a continuous growth in speed and memory, they might have induced a discontinuous transition in the evolution of the scientific method; between theory and experiment a third methodology, ''computational science'', has become or is becoming operational

Exploiting large-scale correlations to detect continuous gravitational waves.

Science.gov (United States)

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.

Report of the Workshop on Petascale Systems Integration for LargeScale Facilities

Energy Technology Data Exchange (ETDEWEB)

Kramer, William T.C.; Walter, Howard; New, Gary; Engle, Tom; Pennington, Rob; Comes, Brad; Bland, Buddy; Tomlison, Bob; Kasdorf, Jim; Skinner, David; Regimbal, Kevin

2007-10-01

There are significant issues regarding Large Scale System integration that are not being addressed in other forums such as current research portfolios or vendor user groups. Unfortunately, the issues in the area of large-scale system integration often fall into a netherworld; not research, not facilities, not procurement, not operations, not user services. Taken together, these issues along with the impact of sub-optimal integration technology means the time required to deploy, integrate and stabilize large scale system may consume up to 20 percent of the useful life of such systems. Improving the state of the art for large scale systems integration has potential to increase the scientific productivity of these systems. Sites have significant expertise, but there are no easy ways to leverage this expertise among them . Many issues inhibit the sharing of information, including available time and effort, as well as issues with sharing proprietary information. Vendors also benefit in the long run from the solutions to issues detected during site testing and integration. There is a great deal of enthusiasm for making large scale system integration a full-fledged partner along with the other major thrusts supported by funding agencies in the definition, design, and use of a petascale systems. Integration technology and issues should have a full 'seat at the table' as petascale and exascale initiatives and programs are planned. The workshop attendees identified a wide range of issues and suggested paths forward. Pursuing these with funding opportunities and innovation offers the opportunity to dramatically improve the state of large scale system integration.

Improving Problem Solving Skill and Self Regulated Learning of Senior High School Students through Scientific Approach using Quantum Learning strategy

Directory of Open Access Journals (Sweden)

M Sudirman

2017-12-01

Full Text Available This research is quasi experiment with control group pretest-postest design. The sampel in this research using the techique of purposive sampling so the samples used were two classes of the 11th grade students of SMAN 14 Bandung in the academic year 2017/2018. The experiment group uses saintific approach using Quantum Learning strategy and control group uses saintific approach. In collecting the data the researcher will use the test of problem solving ability and self regulated learning as the instrument. The aims of this research are to:1find out the improvement of students mathematical problem solving through scientific approach using Quantum Learning study, 2 find out students self regulated learning through scientific approach using Quantum Learning.

Large-scale grid management

International Nuclear Information System (INIS)

Langdal, Bjoern Inge; Eggen, Arnt Ove

2003-01-01

The network companies in the Norwegian electricity industry now have to establish a large-scale network management, a concept essentially characterized by (1) broader focus (Broad Band, Multi Utility,...) and (2) bigger units with large networks and more customers. Research done by SINTEF Energy Research shows so far that the approaches within large-scale network management may be structured according to three main challenges: centralization, decentralization and out sourcing. The article is part of a planned series

Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy.

Science.gov (United States)

Penas, David R; González, Patricia; Egea, Jose A; Doallo, Ramón; Banga, Julio R

2017-01-21

The development of large-scale kinetic models is one of the current key issues in computational systems biology and bioinformatics. Here we consider the problem of parameter estimation in nonlinear dynamic models. Global optimization methods can be used to solve this type of problems but the associated computational cost is very large. Moreover, many of these methods need the tuning of a number of adjustable search parameters, requiring a number of initial exploratory runs and therefore further increasing the computation times. Here we present a novel parallel method, self-adaptive cooperative enhanced scatter search (saCeSS), to accelerate the solution of this class of problems. The method is based on the scatter search optimization metaheuristic and incorporates several key new mechanisms: (i) asynchronous cooperation between parallel processes, (ii) coarse and fine-grained parallelism, and (iii) self-tuning strategies. The performance and robustness of saCeSS is illustrated by solving a set of challenging parameter estimation problems, including medium and large-scale kinetic models of the bacterium E. coli, bakerés yeast S. cerevisiae, the vinegar fly D. melanogaster, Chinese Hamster Ovary cells, and a generic signal transduction network. The results consistently show that saCeSS is a robust and efficient method, allowing very significant reduction of computation times with respect to several previous state of the art methods (from days to minutes, in several cases) even when only a small number of processors is used. The new parallel cooperative method presented here allows the solution of medium and large scale parameter estimation problems in reasonable computation times and with small hardware requirements. Further, the method includes self-tuning mechanisms which facilitate its use by non-experts. We believe that this new method can play a key role in the development of large-scale and even whole-cell dynamic models.

Discriminant WSRC for Large-Scale Plant Species Recognition

Directory of Open Access Journals (Sweden)

Shanwen Zhang

2017-01-01

Full Text Available In sparse representation based classification (SRC and weighted SRC (WSRC, it is time-consuming to solve the global sparse representation problem. A discriminant WSRC (DWSRC is proposed for large-scale plant species recognition, including two stages. Firstly, several subdictionaries are constructed by dividing the dataset into several similar classes, and a subdictionary is chosen by the maximum similarity between the test sample and the typical sample of each similar class. Secondly, the weighted sparse representation of the test image is calculated with respect to the chosen subdictionary, and then the leaf category is assigned through the minimum reconstruction error. Different from the traditional SRC and its improved approaches, we sparsely represent the test sample on a subdictionary whose base elements are the training samples of the selected similar class, instead of using the generic overcomplete dictionary on the entire training samples. Thus, the complexity to solving the sparse representation problem is reduced. Moreover, DWSRC is adapted to newly added leaf species without rebuilding the dictionary. Experimental results on the ICL plant leaf database show that the method has low computational complexity and high recognition rate and can be clearly interpreted.

The fastclime Package for Linear Programming and Large-Scale Precision Matrix Estimation in R.

Science.gov (United States)

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 L 1 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 Biosphere-Atmosphere Experiment in Amazonia: Analyzing Regional Land Use Change Effects.

Science.gov (United States)

Michael Keller; Maria Assunção Silva-Dias; Daniel C. Nepstad; Meinrat O. Andreae

2004-01-01

The Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) is a multi-disciplinary, multinational scientific project led by Brazil. LBA researchers seek to understand Amazonia in its global context especially with regard to regional and global climate. Current development activities in Amazonia including deforestation, logging, cattle ranching, and agriculture...

Ethics of large-scale change

OpenAIRE

Arler, Finn

2006-01-01

  The subject of this paper is long-term large-scale changes in human society. Some very significant examples of large-scale change are presented: human population growth, human appropriation of land and primary production, the human use of fossil fuels, and climate change. The question is posed, which kind of attitude is appropriate when dealing with large-scale changes like these from an ethical point of view. Three kinds of approaches are discussed: Aldo Leopold's mountain thinking, th...

A Test of the Circumvention-of-Limits Hypothesis in Scientific Problem Solving: The Case of Geological Bedrock Mapping

Science.gov (United States)

Hambrick, David Z.; Libarkin, Julie C.; Petcovic, Heather L.; Baker, Kathleen M.; Elkins, Joe; Callahan, Caitlin N.; Turner, Sheldon P.; Rench, Tara A.; LaDue, Nicole D.

2012-01-01

Sources of individual differences in scientific problem solving were investigated. Participants representing a wide range of experience in geology completed tests of visuospatial ability and geological knowledge, and performed a geological bedrock mapping task, in which they attempted to infer the geological structure of an area in the Tobacco…

Hierarchical approach to optimization of parallel matrix multiplication on large-scale platforms

KAUST Repository

Hasanov, Khalid

2014-03-04

© 2014, Springer Science+Business Media New York. Many state-of-the-art parallel algorithms, which are widely used in scientific applications executed on high-end computing systems, were designed in the twentieth century with relatively small-scale parallelism in mind. Indeed, while in 1990s a system with few hundred cores was considered a powerful supercomputer, modern top supercomputers have millions of cores. In this paper, we present a hierarchical approach to optimization of message-passing parallel algorithms for execution on large-scale distributed-memory systems. The idea is to reduce the communication cost by introducing hierarchy and hence more parallelism in the communication scheme. We apply this approach to SUMMA, the state-of-the-art parallel algorithm for matrix–matrix multiplication, and demonstrate both theoretically and experimentally that the modified Hierarchical SUMMA significantly improves the communication cost and the overall performance on large-scale platforms.

Genetics problem solving and worldview

Science.gov (United States)

Dale, Esther

The research goal was to determine whether worldview relates to traditional and real-world genetics problem solving. Traditionally, scientific literacy emphasized content knowledge alone because it was sufficient to solve traditional problems. The contemporary definition of scientific literacy is, "The knowledge and understanding of scientific concepts and processes required for personal decision-making, participation in civic and cultural affairs and economic productivity" (NRC, 1996). An expanded definition of scientific literacy is needed to solve socioscientific issues (SSI), complex social issues with conceptual, procedural, or technological associations with science. Teaching content knowledge alone assumes that students will find the scientific explanation of a phenomenon to be superior to a non-science explanation. Formal science and everyday ways of thinking about science are two different cultures (Palmer, 1999). Students address this rift with cognitive apartheid, the boxing away of science knowledge from other types of knowledge (Jedege & Aikenhead, 1999). By addressing worldview, cognitive apartheid may decrease and scientific literacy may increase. Introductory biology students at the University of Minnesota during fall semester 2005 completed a written questionnaire-including a genetics content-knowledge test, four genetic dilemmas, the Worldview Assessment Instrument (WAI) and some items about demographics and religiosity. Six students responded to the interview protocol. Based on statistical analysis and interview data, this study concluded the following: (1) Worldview, in the form of metaphysics, relates to solving traditional genetic dilemmas. (2) Worldview, in the form of agency, relates to solving traditional genetics problems. (3) Thus, worldview must be addressed in curriculum, instruction, and assessment.

Large-scale ab initio configuration interaction calculations for light nuclei

International Nuclear Information System (INIS)

Maris, Pieter; Potter, Hugh; Vary, James P; Aktulga, H Metin; Ng, Esmond G; Yang Chao; Caprio, Mark A; Çatalyürek, Ümit V; Saule, Erik; Oryspayev, Dossay; Sosonkina, Masha; Zhou Zheng

2012-01-01

In ab-initio Configuration Interaction calculations, the nuclear wavefunction is expanded in Slater determinants of single-nucleon wavefunctions and the many-body Schrodinger equation becomes a large sparse matrix problem. The challenge is to reach numerical convergence to within quantified numerical uncertainties for physical observables using finite truncations of the infinite-dimensional basis space. We discuss strategies for constructing and solving the resulting large sparse matrix eigenvalue problems on current multicore computer architectures. Several of these strategies have been implemented in the code MFDn, a hybrid MPI/OpenMP Fortran code for ab-initio nuclear structure calculations that can scale to 100,000 cores and more. Finally, we will conclude with some recent results for 12 C including emerging collective phenomena such as rotational band structures using SRG evolved chiral N3LO interactions.

Urban Freight Management with Stochastic Time-Dependent Travel Times and Application to Large-Scale Transportation Networks

Directory of Open Access Journals (Sweden)

Shichao Sun

2015-01-01

Full Text Available This paper addressed the vehicle routing problem (VRP in large-scale urban transportation networks with stochastic time-dependent (STD travel times. The subproblem which is how to find the optimal path connecting any pair of customer nodes in a STD network was solved through a robust approach without requiring the probability distributions of link travel times. Based on that, the proposed STD-VRP model can be converted into solving a normal time-dependent VRP (TD-VRP, and algorithms for such TD-VRPs can also be introduced to obtain the solution. Numerical experiments were conducted to address STD-VRPTW of practical sizes on a real world urban network, demonstrated here on the road network of Shenzhen, China. The stochastic time-dependent link travel times of the network were calibrated by historical floating car data. A route construction algorithm was applied to solve the STD problem in 4 delivery scenarios efficiently. The computational results showed that the proposed STD-VRPTW model can improve the level of customer service by satisfying the time-window constraint under any circumstances. The improvement can be very significant especially for large-scale network delivery tasks with no more increase in cost and environmental impacts.

The scaling issue: scientific opportunities

Science.gov (United States)

Orbach, Raymond L.

2009-07-01

A brief history of the Leadership Computing Facility (LCF) initiative is presented, along with the importance of SciDAC to the initiative. The initiative led to the initiation of the Innovative and Novel Computational Impact on Theory and Experiment program (INCITE), open to all researchers in the US and abroad, and based solely on scientific merit through peer review, awarding sizeable allocations (typically millions of processor-hours per project). The development of the nation's LCFs has enabled available INCITE processor-hours to double roughly every eight months since its inception in 2004. The 'top ten' LCF accomplishments in 2009 illustrate the breadth of the scientific program, while the 75 million processor hours allocated to American business since 2006 highlight INCITE contributions to US competitiveness. The extrapolation of INCITE processor hours into the future brings new possibilities for many 'classic' scaling problems. Complex systems and atomic displacements to cracks are but two examples. However, even with increasing computational speeds, the development of theory, numerical representations, algorithms, and efficient implementation are required for substantial success, exhibiting the crucial role that SciDAC will play.

The scaling issue: scientific opportunities

International Nuclear Information System (INIS)

Orbach, Raymond L

2009-01-01

A brief history of the Leadership Computing Facility (LCF) initiative is presented, along with the importance of SciDAC to the initiative. The initiative led to the initiation of the Innovative and Novel Computational Impact on Theory and Experiment program (INCITE), open to all researchers in the US and abroad, and based solely on scientific merit through peer review, awarding sizeable allocations (typically millions of processor-hours per project). The development of the nation's LCFs has enabled available INCITE processor-hours to double roughly every eight months since its inception in 2004. The 'top ten' LCF accomplishments in 2009 illustrate the breadth of the scientific program, while the 75 million processor hours allocated to American business since 2006 highlight INCITE contributions to US competitiveness. The extrapolation of INCITE processor hours into the future brings new possibilities for many 'classic' scaling problems. Complex systems and atomic displacements to cracks are but two examples. However, even with increasing computational speeds, the development of theory, numerical representations, algorithms, and efficient implementation are required for substantial success, exhibiting the crucial role that SciDAC will play.

On the role of individual human abilities in the design of adaptive user interfaces for scientific problem solving environments

NARCIS (Netherlands)

Zudilova-Seinstra, E.V.

2007-01-01

A scientific problem solving environment should be built in such a way that users (scientists) might exploit underlying technologies without a specialised knowledge about available tools and resources. An adaptive user interface can be considered as an opportunity in addressing this challenge. This

Complex Formation Control of Large-Scale Intelligent Autonomous Vehicles

Directory of Open Access Journals (Sweden)

Ming Lei

2012-01-01

Full Text Available A new formation framework of large-scale intelligent autonomous vehicles is developed, which can realize complex formations while reducing data exchange. Using the proposed hierarchy formation method and the automatic dividing algorithm, vehicles are automatically divided into leaders and followers by exchanging information via wireless network at initial time. Then, leaders form formation geometric shape by global formation information and followers track their own virtual leaders to form line formation by local information. The formation control laws of leaders and followers are designed based on consensus algorithms. Moreover, collision-avoiding problems are considered and solved using artificial potential functions. Finally, a simulation example that consists of 25 vehicles shows the effectiveness of theory.

Parallel Computational Fluid Dynamics 2007 : Implementations and Experiences on Large Scale and Grid Computing

CERN Document Server

2009-01-01

At the 19th Annual Conference on Parallel Computational Fluid Dynamics held in Antalya, Turkey, in May 2007, the most recent developments and implementations of large-scale and grid computing were presented. This book, comprised of the invited and selected papers of this conference, details those advances, which are of particular interest to CFD and CFD-related communities. It also offers the results related to applications of various scientific and engineering problems involving flows and flow-related topics. Intended for CFD researchers and graduate students, this book is a state-of-the-art presentation of the relevant methodology and implementation techniques of large-scale computing.

Hi-Corrector: a fast, scalable and memory-efficient package for normalizing large-scale Hi-C data.

Science.gov (United States)

Li, Wenyuan; Gong, Ke; Li, Qingjiao; Alber, Frank; Zhou, Xianghong Jasmine

2015-03-15

Genome-wide proximity ligation assays, e.g. Hi-C and its variant TCC, have recently become important tools to study spatial genome organization. Removing biases from chromatin contact matrices generated by such techniques is a critical preprocessing step of subsequent analyses. The continuing decline of sequencing costs has led to an ever-improving resolution of the Hi-C data, resulting in very large matrices of chromatin contacts. Such large-size matrices, however, pose a great challenge on the memory usage and speed of its normalization. Therefore, there is an urgent need for fast and memory-efficient methods for normalization of Hi-C data. We developed Hi-Corrector, an easy-to-use, open source implementation of the Hi-C data normalization algorithm. Its salient features are (i) scalability-the software is capable of normalizing Hi-C data of any size in reasonable times; (ii) memory efficiency-the sequential version can run on any single computer with very limited memory, no matter how little; (iii) fast speed-the parallel version can run very fast on multiple computing nodes with limited local memory. The sequential version is implemented in ANSI C and can be easily compiled on any system; the parallel version is implemented in ANSI C with the MPI library (a standardized and portable parallel environment designed for solving large-scale scientific problems). The package is freely available at http://zhoulab.usc.edu/Hi-Corrector/. © The Author 2014. Published by Oxford University Press.

Large-scale multimedia modeling applications

International Nuclear Information System (INIS)

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

Application of Logic Models in a Large Scientific Research Program

Science.gov (United States)

O'Keefe, Christine M.; Head, Richard J.

2011-01-01

It is the purpose of this article to discuss the development and application of a logic model in the context of a large scientific research program within the Commonwealth Scientific and Industrial Research Organisation (CSIRO). CSIRO is Australia's national science agency and is a publicly funded part of Australia's innovation system. It conducts…

Algorithm and Application of Gcp-Independent Block Adjustment for Super Large-Scale Domestic High Resolution Optical Satellite Imagery

Science.gov (United States)

Sun, Y. S.; Zhang, L.; Xu, B.; Zhang, Y.

2018-04-01

The accurate positioning of optical satellite image without control is the precondition for remote sensing application and small/medium scale mapping in large abroad areas or with large-scale images. In this paper, aiming at the geometric features of optical satellite image, based on a widely used optimization method of constraint problem which is called Alternating Direction Method of Multipliers (ADMM) and RFM least-squares block adjustment, we propose a GCP independent block adjustment method for the large-scale domestic high resolution optical satellite image - GISIBA (GCP-Independent Satellite Imagery Block Adjustment), which is easy to parallelize and highly efficient. In this method, the virtual "average" control points are built to solve the rank defect problem and qualitative and quantitative analysis in block adjustment without control. The test results prove that the horizontal and vertical accuracy of multi-covered and multi-temporal satellite images are better than 10 m and 6 m. Meanwhile the mosaic problem of the adjacent areas in large area DOM production can be solved if the public geographic information data is introduced as horizontal and vertical constraints in the block adjustment process. Finally, through the experiments by using GF-1 and ZY-3 satellite images over several typical test areas, the reliability, accuracy and performance of our developed procedure will be presented and studied in this paper.

How scientific experiments are designed: Problem solving in a knowledge-rich, error-rich environment

Science.gov (United States)

Baker, Lisa M.

While theory formation and the relation between theory and data has been investigated in many studies of scientific reasoning, researchers have focused less attention on reasoning about experimental design, even though the experimental design process makes up a large part of real-world scientists' reasoning. The goal of this thesis was to provide a cognitive account of the scientific experimental design process by analyzing experimental design as problem-solving behavior (Newell & Simon, 1972). Three specific issues were addressed: the effect of potential error on experimental design strategies, the role of prior knowledge in experimental design, and the effect of characteristics of the space of alternate hypotheses on alternate hypothesis testing. A two-pronged in vivo/in vitro research methodology was employed, in which transcripts of real-world scientific laboratory meetings were analyzed as well as undergraduate science and non-science majors' design of biology experiments in the psychology laboratory. It was found that scientists use a specific strategy to deal with the possibility of error in experimental findings: they include "known" control conditions in their experimental designs both to determine whether error is occurring and to identify sources of error. The known controls strategy had not been reported in earlier studies with science-like tasks, in which participants' responses to error had consisted of replicating experiments and discounting results. With respect to prior knowledge: scientists and undergraduate students drew on several types of knowledge when designing experiments, including theoretical knowledge, domain-specific knowledge of experimental techniques, and domain-general knowledge of experimental design strategies. Finally, undergraduate science students generated and tested alternates to their favored hypotheses when the space of alternate hypotheses was constrained and searchable. This result may help explain findings of confirmation

Distributed constraint satisfaction for coordinating and integrating a large-scale, heterogenous enterprise

CERN Document Server

Eisenberg, C

2003-01-01

Market forces are continuously driving public and private organisations towards higher productivity, shorter process and production times, and fewer labour hours. To cope with these changes, organisations are adopting new organisational models of coordination and cooperation that increase their flexibility, consistency, efficiency, productivity and profit margins. In this thesis an organisational model of coordination and cooperation is examined using a real life example; the technical integration of a distributed large-scale project of an international physics collaboration. The distributed resource constraint project scheduling problem is modelled and solved with the methods of distributed constraint satisfaction. A distributed local search method, the distributed breakout algorithm (DisBO), is used as the basis for the coordination scheme. The efficiency of the local search method is improved by extending it with an incremental problem solving scheme with variable ordering. The scheme is implemented as cen...

EvArnoldi: A New Algorithm for Large-Scale Eigenvalue Problems.

Science.gov (United States)

Tal-Ezer, Hillel

2016-05-19

Eigenvalues and eigenvectors are an essential theme in numerical linear algebra. Their study is mainly motivated by their high importance in a wide range of applications. Knowledge of eigenvalues is essential in quantum molecular science. Solutions of the Schrödinger equation for the electrons composing the molecule are the basis of electronic structure theory. Electronic eigenvalues compose the potential energy surfaces for nuclear motion. The eigenvectors allow calculation of diople transition matrix elements, the core of spectroscopy. The vibrational dynamics molecule also requires knowledge of the eigenvalues of the vibrational Hamiltonian. Typically in these problems, the dimension of Hilbert space is huge. Practically, only a small subset of eigenvalues is required. In this paper, we present a highly efficient algorithm, named EvArnoldi, for solving the large-scale eigenvalues problem. The algorithm, in its basic formulation, is mathematically equivalent to ARPACK ( Sorensen , D. C. Implicitly Restarted Arnoldi/Lanczos Methods for Large Scale Eigenvalue Calculations ; Springer , 1997 ; Lehoucq , R. B. ; Sorensen , D. C. SIAM Journal on Matrix Analysis and Applications 1996 , 17 , 789 ; Calvetti , D. ; Reichel , L. ; Sorensen , D. C. Electronic Transactions on Numerical Analysis 1994 , 2 , 21 ) (or Eigs of Matlab) but significantly simpler.

Large-scale dynamo action due to α fluctuations in a linear shear flow

Science.gov (United States)

Sridhar, S.; Singh, Nishant K.

2014-12-01

We present a model of large-scale dynamo action in a shear flow that has stochastic, zero-mean fluctuations of the α parameter. This is based on a minimal extension of the Kraichnan-Moffatt model, to include a background linear shear and Galilean-invariant α-statistics. Using the first-order smoothing approximation we derive a linear integro-differential equation for the large-scale magnetic field, which is non-perturbative in the shearing rate S , and the α-correlation time τα . The white-noise case, τα = 0 , is solved exactly, and it is concluded that the necessary condition for dynamo action is identical to the Kraichnan-Moffatt model without shear; this is because white-noise does not allow for memory effects, whereas shear needs time to act. To explore memory effects we reduce the integro-differential equation to a partial differential equation, valid for slowly varying fields when τα is small but non-zero. Seeking exponential modal solutions, we solve the modal dispersion relation and obtain an explicit expression for the growth rate as a function of the six independent parameters of the problem. A non-zero τα gives rise to new physical scales, and dynamo action is completely different from the white-noise case; e.g. even weak α fluctuations can give rise to a dynamo. We argue that, at any wavenumber, both Moffatt drift and Shear always contribute to increasing the growth rate. Two examples are presented: (a) a Moffatt drift dynamo in the absence of shear and (b) a Shear dynamo in the absence of Moffatt drift.

Examination of the relationship between preservice science teachers' scientific reasoning and problem solving skills on basic mechanics

Science.gov (United States)

Yuksel, Ibrahim; Ates, Salih

2018-02-01

The purpose of this study is to determine relationship between scientific reasoning and mechanics problem solving skills of students in science education program. Scientific Reasoning Skills Test (SRST) and Basic Mechanics Knowledge Test (BMKT) were applied to 90 second, third and fourth grade students who took Scientific Reasoning Skills course at science teaching program of Gazi Faculty of Education for three successive fall semesters of 2014, 2015 and 2016 academic years. It was found a statistically significant positive (p = 0.038 <0.05) but a low correlation (r = 0.219) between SRST and BMKT. There were no significant relationship among Conservation Laws, Proportional Thinking, Combinational Thinking, Correlational Thinking, Probabilistic Thinking subskills of reasoning and BMKT. There were significant and positive correlation among Hypothetical Thinking and Identifying and Controlling Variables subskills of reasoning and BMKT. The findings of the study were compared with other studies in the field and discussed.

Some Problems of Industrial Scale-Up.

Science.gov (United States)

Jackson, A. T.

1985-01-01

Scientific ideas of the biological laboratory are turned into economic realities in industry only after several problems are solved. Economics of scale, agitation, heat transfer, sterilization of medium and air, product recovery, waste disposal, and future developments are discussed using aerobic respiration as the example in the scale-up…

Automating large-scale reactor systems

International Nuclear Information System (INIS)

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

Tools for Observation: Art and the Scientific Process

Science.gov (United States)

Pettit, E. C.; Coryell-Martin, M.; Maisch, K.

2015-12-01

Art can support the scientific process during different phases of a scientific discovery. Art can help explain and extend the scientific concepts for the general public; in this way art is a powerful tool for communication. Art can aid the scientist in processing and interpreting the data towards an understanding of the concepts and processes; in this way art is powerful - if often subconscious - tool to inform the process of discovery. Less often acknowledged, art can help engage students and inspire scientists during the initial development of ideas, observations, and questions; in this way art is a powerful tool to develop scientific questions and hypotheses. When we use art as a tool for communication of scientific discoveries, it helps break down barriers and makes science concepts less intimidating and more accessible and understandable for the learner. Scientists themselves use artistic concepts and processes - directly or indirectly - to help deepen their understanding. Teachers are following suit by using art more to stimulate students' creative thinking and problem solving. We show the value of teaching students to use the artistic "way of seeing" to develop their skills in observation, questioning, and critical thinking. In this way, art can be a powerful tool to engage students (from elementary to graduate) in the beginning phase of a scientific discovery, which is catalyzed by inquiry and curiosity. Through qualitative assessment of the Girls on Ice program, we show that many of the specific techniques taught by art teachers are valuable for science students to develop their observation skills. In particular, the concepts of contour drawing, squinting, gesture drawing, inverted drawing, and others can provide valuable training for student scientists. These art techniques encourage students to let go of preconceptions and "see" the world (the "data") in new ways they help students focus on both large-scale patterns and small-scale details.

Testing foreign language impact on engineering students' scientific problem-solving performance

Science.gov (United States)

Tatzl, Dietmar; Messnarz, Bernd

2013-12-01

This article investigates the influence of English as the examination language on the solution of physics and science problems by non-native speakers in tertiary engineering education. For that purpose, a statistically significant total number of 96 students in four year groups from freshman to senior level participated in a testing experiment in the Degree Programme of Aviation at the FH JOANNEUM University of Applied Sciences, Graz, Austria. Half of each test group were given a set of 12 physics problems described in German, the other half received the same set of problems described in English. It was the goal to test linguistic reading comprehension necessary for scientific problem solving instead of physics knowledge as such. The results imply that written undergraduate English-medium engineering tests and examinations may not require additional examination time or language-specific aids for students who have reached university-entrance proficiency in English as a foreign language.

Large-scale block adjustment without use of ground control points based on the compensation of geometric calibration for ZY-3 images

Science.gov (United States)

Yang, Bo; Wang, Mi; Xu, Wen; Li, Deren; Gong, Jianya; Pi, Yingdong

2017-12-01

The potential of large-scale block adjustment (BA) without ground control points (GCPs) has long been a concern among photogrammetric researchers, which is of effective guiding significance for global mapping. However, significant problems with the accuracy and efficiency of this method remain to be solved. In this study, we analyzed the effects of geometric errors on BA, and then developed a step-wise BA method to conduct integrated processing of large-scale ZY-3 satellite images without GCPs. We first pre-processed the BA data, by adopting a geometric calibration (GC) method based on the viewing-angle model to compensate for systematic errors, such that the BA input images were of good initial geometric quality. The second step was integrated BA without GCPs, in which a series of technical methods were used to solve bottleneck problems and ensure accuracy and efficiency. The BA model, based on virtual control points (VCPs), was constructed to address the rank deficiency problem caused by lack of absolute constraints. We then developed a parallel matching strategy to improve the efficiency of tie points (TPs) matching, and adopted a three-array data structure based on sparsity to relieve the storage and calculation burden of the high-order modified equation. Finally, we used the conjugate gradient method to improve the speed of solving the high-order equations. To evaluate the feasibility of the presented large-scale BA method, we conducted three experiments on real data collected by the ZY-3 satellite. The experimental results indicate that the presented method can effectively improve the geometric accuracies of ZY-3 satellite images. This study demonstrates the feasibility of large-scale mapping without GCPs.

International scientific seminar «Chronicle of Nature – a common database for scientific analysis and joint planning of scientific publications»

Directory of Open Access Journals (Sweden)

Juri P. Kurhinen

2016-05-01

Full Text Available Provides information about the results of the international scienti fic seminar «Сhronicle of Nature – a common database for scientific analysis and joint planning of scientific publications», held at Findland-Russian project «Linking environmental change to biodiversity change: large scale analysis оf Eurasia ecosystem».

Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron for Large Scale Classification of Protein Structures.

Science.gov (United States)

Arana-Daniel, Nancy; Gallegos, Alberto A; López-Franco, Carlos; Alanís, Alma Y; Morales, Jacob; López-Franco, Adriana

2016-01-01

With the increasing power of computers, the amount of data that can be processed in small periods of time has grown exponentially, as has the importance of classifying large-scale data efficiently. Support vector machines have shown good results classifying large amounts of high-dimensional data, such as data generated by protein structure prediction, spam recognition, medical diagnosis, optical character recognition and text classification, etc. Most state of the art approaches for large-scale learning use traditional optimization methods, such as quadratic programming or gradient descent, which makes the use of evolutionary algorithms for training support vector machines an area to be explored. The present paper proposes an approach that is simple to implement based on evolutionary algorithms and Kernel-Adatron for solving large-scale classification problems, focusing on protein structure prediction. The functional properties of proteins depend upon their three-dimensional structures. Knowing the structures of proteins is crucial for biology and can lead to improvements in areas such as medicine, agriculture and biofuels.

A Science-Technology-Society Paradigm and Cross River State Secondary School Students' Scientific Literacy: Problem Solving and Decision Making

Science.gov (United States)

Umoren, Grace

2007-01-01

The aim of this study was to investigate the effect of Science-Technology-Society (STS) curriculum on students' scientific literacy, problem solving and decision making. Four hundred and eighty (480) Senior Secondary two science and non-science students were randomly selected from intact classes in six secondary schools in Calabar Municipality of…

The Software Reliability of Large Scale Integration Circuit and Very Large Scale Integration Circuit

OpenAIRE

Artem Ganiyev; Jan Vitasek

2010-01-01

This article describes evaluation method of faultless function of large scale integration circuits (LSI) and very large scale integration circuits (VLSI). In the article there is a comparative analysis of factors which determine faultless of integrated circuits, analysis of already existing methods and model of faultless function evaluation of LSI and VLSI. The main part describes a proposed algorithm and program for analysis of fault rate in LSI and VLSI circuits.

Implicit solvers for large-scale nonlinear problems

International Nuclear Information System (INIS)

Keyes, David E; Reynolds, Daniel R; Woodward, Carol S

2006-01-01

Computational scientists are grappling with increasingly complex, multi-rate applications that couple such physical phenomena as fluid dynamics, electromagnetics, radiation transport, chemical and nuclear reactions, and wave and material propagation in inhomogeneous media. Parallel computers with large storage capacities are paving the way for high-resolution simulations of coupled problems; however, hardware improvements alone will not prove enough to enable simulations based on brute-force algorithmic approaches. To accurately capture nonlinear couplings between dynamically relevant phenomena, often while stepping over rapid adjustments to quasi-equilibria, simulation scientists are increasingly turning to implicit formulations that require a discrete nonlinear system to be solved for each time step or steady state solution. Recent advances in iterative methods have made fully implicit formulations a viable option for solution of these large-scale problems. In this paper, we overview one of the most effective iterative methods, Newton-Krylov, for nonlinear systems and point to software packages with its implementation. We illustrate the method with an example from magnetically confined plasma fusion and briefly survey other areas in which implicit methods have bestowed important advantages, such as allowing high-order temporal integration and providing a pathway to sensitivity analyses and optimization. Lastly, we overview algorithm extensions under development motivated by current SciDAC applications

HTS cables open the window for large-scale renewables

International Nuclear Information System (INIS)

Geschiere, A; Willen, D; Piga, E; Barendregt, P

2008-01-01

In a realistic approach to future energy consumption, the effects of sustainable power sources and the effects of growing welfare with increased use of electricity need to be considered. These factors lead to an increased transfer of electric energy over the networks. A dominant part of the energy need will come from expanded large-scale renewable sources. To use them efficiently over Europe, large energy transits between different countries are required. Bottlenecks in the existing infrastructure will be avoided by strengthening the network. For environmental reasons more infrastructure will be built underground. Nuon is studying the HTS technology as a component to solve these challenges. This technology offers a tremendously large power transport capacity as well as the possibility to reduce short circuit currents, making integration of renewables easier. Furthermore, power transport will be possible at lower voltage levels, giving the opportunity to upgrade the existing network while re-using it. This will result in large cost savings while reaching the future energy challenges. In a 6 km backbone structure in Amsterdam Nuon wants to install a 50 kV HTS Triax cable for a significant increase of the transport capacity, while developing its capabilities. Nevertheless several barriers have to be overcome

Data management strategies for multinational large-scale systems biology projects.

Science.gov (United States)

Wruck, Wasco; Peuker, Martin; Regenbrecht, Christian R A

2014-01-01

Good accessibility of publicly funded research data is essential to secure an open scientific system and eventually becomes mandatory [Wellcome Trust will Penalise Scientists Who Don't Embrace Open Access. The Guardian 2012]. By the use of high-throughput methods in many research areas from physics to systems biology, large data collections are increasingly important as raw material for research. Here, we present strategies worked out by international and national institutions targeting open access to publicly funded research data via incentives or obligations to share data. Funding organizations such as the British Wellcome Trust therefore have developed data sharing policies and request commitment to data management and sharing in grant applications. Increased citation rates are a profound argument for sharing publication data. Pre-publication sharing might be rewarded by a data citation credit system via digital object identifiers (DOIs) which have initially been in use for data objects. Besides policies and incentives, good practice in data management is indispensable. However, appropriate systems for data management of large-scale projects for example in systems biology are hard to find. Here, we give an overview of a selection of open-source data management systems proved to be employed successfully in large-scale projects.

A Dynamic Optimization Strategy for the Operation of Large Scale Seawater Reverses Osmosis System

Directory of Open Access Journals (Sweden)

Aipeng Jiang

2014-01-01

Full Text Available In this work, an efficient strategy was proposed for efficient solution of the dynamic model of SWRO system. Since the dynamic model is formulated by a set of differential-algebraic equations, simultaneous strategies based on collocations on finite element were used to transform the DAOP into large scale nonlinear programming problem named Opt2. Then, simulation of RO process and storage tanks was carried element by element and step by step with fixed control variables. All the obtained values of these variables then were used as the initial value for the optimal solution of SWRO system. Finally, in order to accelerate the computing efficiency and at the same time to keep enough accuracy for the solution of Opt2, a simple but efficient finite element refinement rule was used to reduce the scale of Opt2. The proposed strategy was applied to a large scale SWRO system with 8 RO plants and 4 storage tanks as case study. Computing result shows that the proposed strategy is quite effective for optimal operation of the large scale SWRO system; the optimal problem can be successfully solved within decades of iterations and several minutes when load and other operating parameters fluctuate.

Phylogenetic distribution of large-scale genome patchiness

Directory of Open Access Journals (Sweden)

Hackenberg Michael

2008-04-01

Full Text Available Abstract Background The phylogenetic distribution of large-scale genome structure (i.e. mosaic compositional patchiness has been explored mainly by analytical ultracentrifugation of bulk DNA. However, with the availability of large, good-quality chromosome sequences, and the recently developed computational methods to directly analyze patchiness on the genome sequence, an evolutionary comparative analysis can be carried out at the sequence level. Results The local variations in the scaling exponent of the Detrended Fluctuation Analysis are used here to analyze large-scale genome structure and directly uncover the characteristic scales present in genome sequences. Furthermore, through shuffling experiments of selected genome regions, computationally-identified, isochore-like regions were identified as the biological source for the uncovered large-scale genome structure. The phylogenetic distribution of short- and large-scale patchiness was determined in the best-sequenced genome assemblies from eleven eukaryotic genomes: mammals (Homo sapiens, Pan troglodytes, Mus musculus, Rattus norvegicus, and Canis familiaris, birds (Gallus gallus, fishes (Danio rerio, invertebrates (Drosophila melanogaster and Caenorhabditis elegans, plants (Arabidopsis thaliana and yeasts (Saccharomyces cerevisiae. We found large-scale patchiness of genome structure, associated with in silico determined, isochore-like regions, throughout this wide phylogenetic range. Conclusion Large-scale genome structure is detected by directly analyzing DNA sequences in a wide range of eukaryotic chromosome sequences, from human to yeast. In all these genomes, large-scale patchiness can be associated with the isochore-like regions, as directly detected in silico at the sequence level.

Managing large-scale models: DBS

International Nuclear Information System (INIS)

1981-05-01

A set of fundamental management tools for developing and operating a large scale model and data base system is presented. Based on experience in operating and developing a large scale computerized system, the only reasonable way to gain strong management control of such a system is to implement appropriate controls and procedures. Chapter I discusses the purpose of the book. Chapter II classifies a broad range of generic management problems into three groups: documentation, operations, and maintenance. First, system problems are identified then solutions for gaining management control are disucssed. Chapters III, IV, and V present practical methods for dealing with these problems. These methods were developed for managing SEAS but have general application for large scale models and data bases

Large Scale Self-Organizing Information Distribution System

National Research Council Canada - National Science Library

Low, Steven

2005-01-01

This project investigates issues in "large-scale" networks. Here "large-scale" refers to networks with large number of high capacity nodes and transmission links, and shared by a large number of users...

MicroEcos: Micro-Scale Explorations of Large-Scale Late Pleistocene Ecosystems

Science.gov (United States)

Gellis, B. S.

2017-12-01

Pollen data can inform the reconstruction of early-floral environments by providing data for artistic representations of what early-terrestrial ecosystems looked like, and how existing terrestrial landscapes have evolved. For example, what did the Bighorn Basin look like when large ice sheets covered modern Canada, the Yellowstone Plateau had an ice cap, and the Bighorn Mountains were mantled with alpine glaciers? MicroEcos is an immersive, multimedia project that aims to strengthen human-nature connections through the understanding and appreciation of biological ecosystems. Collected pollen data elucidates flora that are visible in the fossil record - associated with the Late-Pleistocene - and have been illustrated and described in botanical literature. It aims to make scientific data accessible and interesting to all audiences through a series of interactive-digital sculptures, large-scale photography and field-based videography. While this project is driven by scientific data, it is rooted in deeply artistic and outreach-based practices, which include broad artistic practices, e.g.: digital design, illustration, photography, video and sound design. Using 3D modeling and printing technology MicroEcos centers around a series of 3D-printed models of the Last Canyon rock shelter on the Wyoming and Montana border, Little Windy Hill pond site in Wyoming's Medicine Bow National Forest, and Natural Trap Cave site in Wyoming's Big Horn Basin. These digital, interactive-3D sculpture provide audiences with glimpses of three-dimensional Late-Pleistocene environments, and helps create dialogue of how grass, sagebrush, and spruce based ecosystems form. To help audiences better contextualize how MicroEcos bridges notions of time, space, and place, modern photography and videography of the Last Canyon, Little Windy Hill and Natural Trap Cave sites surround these 3D-digital reconstructions.

Large scale three-dimensional topology optimisation of heat sinks cooled by natural convection

DEFF Research Database (Denmark)

Alexandersen, Joe; Sigmund, Ole; Aage, Niels

2016-01-01

the Bousinessq approximation. The fully coupled non-linear multiphysics system is solved using stabilised trilinear equal-order finite elements in a parallel framework allowing for the optimisation of large scale problems with order of 20-330 million state degrees of freedom. The flow is assumed to be laminar...... topologies verify prior conclusions regarding fin length/thickness ratios and Biot numbers, but also indicate that carefully tailored and complex geometries may improve cooling behaviour considerably compared to simple heat fin geometries. (C) 2016 Elsevier Ltd. All rights reserved....

Large scale structure and baryogenesis

International Nuclear Information System (INIS)

Kirilova, D.P.; Chizhov, M.V.

2001-08-01

We discuss a possible connection between the large scale structure formation and the baryogenesis in the universe. An update review of the observational indications for the presence of a very large scale 120h -1 Mpc in the distribution of the visible matter of the universe is provided. The possibility to generate a periodic distribution with the characteristic scale 120h -1 Mpc through a mechanism producing quasi-periodic baryon density perturbations during inflationary stage, is discussed. The evolution of the baryon charge density distribution is explored in the framework of a low temperature boson condensate baryogenesis scenario. Both the observed very large scale of a the visible matter distribution in the universe and the observed baryon asymmetry value could naturally appear as a result of the evolution of a complex scalar field condensate, formed at the inflationary stage. Moreover, for some model's parameters a natural separation of matter superclusters from antimatter ones can be achieved. (author)

Automatic management software for large-scale cluster system

International Nuclear Information System (INIS)

Weng Yunjian; Chinese Academy of Sciences, Beijing; Sun Gongxing

2007-01-01

At present, the large-scale cluster system faces to the difficult management. For example the manager has large work load. It needs to cost much time on the management and the maintenance of large-scale cluster system. The nodes in large-scale cluster system are very easy to be chaotic. Thousands of nodes are put in big rooms so that some managers are very easy to make the confusion with machines. How do effectively carry on accurate management under the large-scale cluster system? The article introduces ELFms in the large-scale cluster system. Furthermore, it is proposed to realize the large-scale cluster system automatic management. (authors)

Parallel Optimization of Polynomials for Large-scale Problems in Stability and Control

Science.gov (United States)

Kamyar, Reza

In this thesis, we focus on some of the NP-hard problems in control theory. Thanks to the converse Lyapunov theory, these problems can often be modeled as optimization over polynomials. To avoid the problem of intractability, we establish a trade off between accuracy and complexity. In particular, we develop a sequence of tractable optimization problems --- in the form of Linear Programs (LPs) and/or Semi-Definite Programs (SDPs) --- whose solutions converge to the exact solution of the NP-hard problem. However, the computational and memory complexity of these LPs and SDPs grow exponentially with the progress of the sequence - meaning that improving the accuracy of the solutions requires solving SDPs with tens of thousands of decision variables and constraints. Setting up and solving such problems is a significant challenge. The existing optimization algorithms and software are only designed to use desktop computers or small cluster computers --- machines which do not have sufficient memory for solving such large SDPs. Moreover, the speed-up of these algorithms does not scale beyond dozens of processors. This in fact is the reason we seek parallel algorithms for setting-up and solving large SDPs on large cluster- and/or super-computers. We propose parallel algorithms for stability analysis of two classes of systems: 1) Linear systems with a large number of uncertain parameters; 2) Nonlinear systems defined by polynomial vector fields. First, we develop a distributed parallel algorithm which applies Polya's and/or Handelman's theorems to some variants of parameter-dependent Lyapunov inequalities with parameters defined over the standard simplex. The result is a sequence of SDPs which possess a block-diagonal structure. We then develop a parallel SDP solver which exploits this structure in order to map the computation, memory and communication to a distributed parallel environment. Numerical tests on a supercomputer demonstrate the ability of the algorithm to

Foundational perspectives on causality in large-scale brain networks

Science.gov (United States)

Mannino, Michael; Bressler, Steven L.

2015-12-01

A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical

Algorithms for large scale singular value analysis of spatially variant tomography systems

International Nuclear Information System (INIS)

Cao-Huu, Tuan; Brownell, G.; Lachiver, G.

1996-01-01

The problem of determining the eigenvalues of large matrices occurs often in the design and analysis of modem tomography systems. As there is an interest in solving systems containing an ever-increasing number of variables, current research effort is being made to create more robust solvers which do not depend on some special feature of the matrix for convergence (e.g. block circulant), and to improve the speed of already known and understood solvers so that solving even larger systems in a reasonable time becomes viable. Our standard techniques for singular value analysis are based on sparse matrix factorization and are not applicable when the input matrices are large because the algorithms cause too much fill. Fill refers to the increase of non-zero elements in the LU decomposition of the original matrix A (the system matrix). So we have developed iterative solutions that are based on sparse direct methods. Data motion and preconditioning techniques are critical for performance. This conference paper describes our algorithmic approaches for large scale singular value analysis of spatially variant imaging systems, and in particular of PCR2, a cylindrical three-dimensional PET imager 2 built at the Massachusetts General Hospital (MGH) in Boston. We recommend the desirable features and challenges for the next generation of parallel machines for optimal performance of our solver

Large curvature and background scale independence in single-metric approximations to asymptotic safety

Energy Technology Data Exchange (ETDEWEB)

Morris, Tim R. [STAG Research Centre & Department of Physics and Astronomy, University of Southampton,Highfield, Southampton, SO17 1BJ (United Kingdom)

2016-11-25

In single-metric approximations to the exact renormalization group (RG) for quantum gravity, it has been not been clear how to treat the large curvature domain beyond the point where the effective cutoff scale k is less than the lowest eigenvalue of the appropriate modified Laplacian. We explain why this puzzle arises from background dependence, resulting in Wilsonian RG concepts being inapplicable. We show that when properly formulated over an ensemble of backgrounds, the Wilsonian RG can be restored. This in turn implies that solutions should be smooth and well defined no matter how large the curvature is taken. Even for the standard single-metric type approximation schemes, this construction can be rigorously derived by imposing a modified Ward identity (mWI) corresponding to rescaling the background metric by a constant factor. However compatibility in this approximation requires the space-time dimension to be six. Solving the mWI and flow equation simultaneously, new variables are then derived that are independent of overall background scale.

Solving large mixed linear models using preconditioned conjugate gradient iteration.

Science.gov (United States)

Strandén, I; Lidauer, M

1999-12-01

Continuous evaluation of dairy cattle with a random regression test-day model requires a fast solving method and algorithm. A new computing technique feasible in Jacobi and conjugate gradient based iterative methods using iteration on data is presented. In the new computing technique, the calculations in multiplication of a vector by a matrix were recorded to three steps instead of the commonly used two steps. The three-step method was implemented in a general mixed linear model program that used preconditioned conjugate gradient iteration. Performance of this program in comparison to other general solving programs was assessed via estimation of breeding values using univariate, multivariate, and random regression test-day models. Central processing unit time per iteration with the new three-step technique was, at best, one-third that needed with the old technique. Performance was best with the test-day model, which was the largest and most complex model used. The new program did well in comparison to other general software. Programs keeping the mixed model equations in random access memory required at least 20 and 435% more time to solve the univariate and multivariate animal models, respectively. Computations of the second best iteration on data took approximately three and five times longer for the animal and test-day models, respectively, than did the new program. Good performance was due to fast computing time per iteration and quick convergence to the final solutions. Use of preconditioned conjugate gradient based methods in solving large breeding value problems is supported by our findings.

Large-Scale Multi-Dimensional Document Clustering on GPU Clusters

Energy Technology Data Exchange (ETDEWEB)

Cui, Xiaohui [ORNL; Mueller, Frank [North Carolina State University; Zhang, Yongpeng [ORNL; Potok, Thomas E [ORNL

2010-01-01

Document clustering plays an important role in data mining systems. Recently, a flocking-based document clustering algorithm has been proposed to solve the problem through simulation resembling the flocking behavior of birds in nature. This method is superior to other clustering algorithms, including k-means, in the sense that the outcome is not sensitive to the initial state. One limitation of this approach is that the algorithmic complexity is inherently quadratic in the number of documents. As a result, execution time becomes a bottleneck with large number of documents. In this paper, we assess the benefits of exploiting the computational power of Beowulf-like clusters equipped with contemporary Graphics Processing Units (GPUs) as a means to significantly reduce the runtime of flocking-based document clustering. Our framework scales up to over one million documents processed simultaneously in a sixteennode GPU cluster. Results are also compared to a four-node cluster with higher-end GPUs. On these clusters, we observe 30X-50X speedups, which demonstrates the potential of GPU clusters to efficiently solve massive data mining problems. Such speedups combined with the scalability potential and accelerator-based parallelization are unique in the domain of document-based data mining, to the best of our knowledge.

Large scale network-centric distributed systems

CERN Document Server

Sarbazi-Azad, Hamid

2014-01-01

A highly accessible reference offering a broad range of topics and insights on large scale network-centric distributed systems Evolving from the fields of high-performance computing and networking, large scale network-centric distributed systems continues to grow as one of the most important topics in computing and communication and many interdisciplinary areas. Dealing with both wired and wireless networks, this book focuses on the design and performance issues of such systems. Large Scale Network-Centric Distributed Systems provides in-depth coverage ranging from ground-level hardware issu

Sustainability Risk Evaluation for Large-Scale Hydropower Projects with Hybrid Uncertainty

Directory of Open Access Journals (Sweden)

Weiyao Tang

2018-01-01

Full Text Available As large-scale hydropower projects are influenced by many factors, risk evaluations are complex. This paper considers a hydropower project as a complex system from the perspective of sustainability risk, and divides it into three subsystems: the natural environment subsystem, the eco-environment subsystem and the socioeconomic subsystem. Risk-related factors and quantitative dimensions of each subsystem are comprehensively analyzed considering uncertainty of some quantitative dimensions solved by hybrid uncertainty methods, including fuzzy (e.g., the national health degree, the national happiness degree, the protection of cultural heritage, random (e.g., underground water levels, river width, and fuzzy random uncertainty (e.g., runoff volumes, precipitation. By calculating the sustainability risk-related degree in each of the risk-related factors, a sustainable risk-evaluation model is built. Based on the calculation results, the critical sustainability risk-related factors are identified and targeted to reduce the losses caused by sustainability risk factors of the hydropower project. A case study at the under-construction Baihetan hydropower station is presented to demonstrate the viability of the risk-evaluation model and to provide a reference for the sustainable risk evaluation of other large-scale hydropower projects.

Large-Scale Outflows in Seyfert Galaxies

Science.gov (United States)

Colbert, E. J. M.; Baum, S. A.

1995-12-01

\\catcode`\\@=11 \\ialign{m @th#1hfil ##hfil \\crcr#2\\crcr\\sim\\crcr}}} \\catcode`\\@=12 Highly collimated outflows extend out to Mpc scales in many radio-loud active galaxies. In Seyfert galaxies, which are radio-quiet, the outflows extend out to kpc scales and do not appear to be as highly collimated. In order to study the nature of large-scale (>~1 kpc) outflows in Seyferts, we have conducted optical, radio and X-ray surveys of a distance-limited sample of 22 edge-on Seyfert galaxies. Results of the optical emission-line imaging and spectroscopic survey imply that large-scale outflows are present in >~{{1} /{4}} of all Seyferts. The radio (VLA) and X-ray (ROSAT) surveys show that large-scale radio and X-ray emission is present at about the same frequency. Kinetic luminosities of the outflows in Seyferts are comparable to those in starburst-driven superwinds. Large-scale radio sources in Seyferts appear diffuse, but do not resemble radio halos found in some edge-on starburst galaxies (e.g. M82). We discuss the feasibility of the outflows being powered by the active nucleus (e.g. a jet) or a circumnuclear starburst.

Are large-scale flow experiments informing the science and management of freshwater ecosystems?

Science.gov (United States)

Olden, Julian D.; Konrad, Christopher P.; Melis, Theodore S.; Kennard, Mark J.; Freeman, Mary C.; Mims, Meryl C.; Bray, Erin N.; Gido, Keith B.; Hemphill, Nina P.; Lytle, David A.; McMullen, Laura E.; Pyron, Mark; Robinson, Christopher T.; Schmidt, John C.; Williams, John G.

2013-01-01

Greater scientific knowledge, changing societal values, and legislative mandates have emphasized the importance of implementing large-scale flow experiments (FEs) downstream of dams. We provide the first global assessment of FEs to evaluate their success in advancing science and informing management decisions. Systematic review of 113 FEs across 20 countries revealed that clear articulation of experimental objectives, while not universally practiced, was crucial for achieving management outcomes and changing dam-operating policies. Furthermore, changes to dam operations were three times less likely when FEs were conducted primarily for scientific purposes. Despite the recognized importance of riverine flow regimes, four-fifths of FEs involved only discrete flow events. Over three-quarters of FEs documented both abiotic and biotic outcomes, but only one-third examined multiple taxonomic responses, thus limiting how FE results can inform holistic dam management. Future FEs will present new opportunities to advance scientifically credible water policies.

Renormalization-group flow of the effective action of cosmological large-scale structures

CERN Document Server

Floerchinger, Stefan

2017-01-01

Following an approach of Matarrese and Pietroni, we derive the functional renormalization group (RG) flow of the effective action of cosmological large-scale structures. Perturbative solutions of this RG flow equation are shown to be consistent with standard cosmological perturbation theory. Non-perturbative approximate solutions can be obtained by truncating the a priori infinite set of possible effective actions to a finite subspace. Using for the truncated effective action a form dictated by dissipative fluid dynamics, we derive RG flow equations for the scale dependence of the effective viscosity and sound velocity of non-interacting dark matter, and we solve them numerically. Physically, the effective viscosity and sound velocity account for the interactions of long-wavelength fluctuations with the spectrum of smaller-scale perturbations. We find that the RG flow exhibits an attractor behaviour in the IR that significantly reduces the dependence of the effective viscosity and sound velocity on the input ...

Automatic Optimization for Large-Scale Real-Time Coastal Water Simulation

Directory of Open Access Journals (Sweden)

Shunli Wang

2016-01-01

Full Text Available We introduce an automatic optimization approach for the simulation of large-scale coastal water. To solve the singular problem of water waves obtained with the traditional model, a hybrid deep-shallow-water model is estimated by using an automatic coupling algorithm. It can handle arbitrary water depth and different underwater terrain. As a certain feature of coastal terrain, coastline is detected with the collision detection technology. Then, unnecessary water grid cells are simplified by the automatic simplification algorithm according to the depth. Finally, the model is calculated on Central Processing Unit (CPU and the simulation is implemented on Graphics Processing Unit (GPU. We show the effectiveness of our method with various results which achieve real-time rendering on consumer-level computer.

SCALE INTERACTION IN A MIXING LAYER. THE ROLE OF THE LARGE-SCALE GRADIENTS

KAUST Repository

Fiscaletti, Daniele

2015-08-23

The interaction between scales is investigated in a turbulent mixing layer. The large-scale amplitude modulation of the small scales already observed in other works depends on the crosswise location. Large-scale positive fluctuations correlate with a stronger activity of the small scales on the low speed-side of the mixing layer, and a reduced activity on the high speed-side. However, from physical considerations we would expect the scales to interact in a qualitatively similar way within the flow and across different turbulent flows. Therefore, instead of the large-scale fluctuations, the large-scale gradients modulation of the small scales has been additionally investigated.

Dissecting the large-scale galactic conformity

Science.gov (United States)

Seo, Seongu

2018-01-01

Galactic conformity is an observed phenomenon that galaxies located in the same region have similar properties such as star formation rate, color, gas fraction, and so on. The conformity was first observed among galaxies within in the same halos (“one-halo conformity”). The one-halo conformity can be readily explained by mutual interactions among galaxies within a halo. Recent observations however further witnessed a puzzling connection among galaxies with no direct interaction. In particular, galaxies located within a sphere of ~5 Mpc radius tend to show similarities, even though the galaxies do not share common halos with each other ("two-halo conformity" or “large-scale conformity”). Using a cosmological hydrodynamic simulation, Illustris, we investigate the physical origin of the two-halo conformity and put forward two scenarios. First, back-splash galaxies are likely responsible for the large-scale conformity. They have evolved into red galaxies due to ram-pressure stripping in a given galaxy cluster and happen to reside now within a ~5 Mpc sphere. Second, galaxies in strong tidal field induced by large-scale structure also seem to give rise to the large-scale conformity. The strong tides suppress star formation in the galaxies. We discuss the importance of the large-scale conformity in the context of galaxy evolution.

Automatic Installation and Configuration for Large Scale Farms

CERN Document Server

Novák, J

2005-01-01

Since the early appearance of commodity hardware, the utilization of computers rose rapidly, and they became essential in all areas of life. Soon it was realized that nodes are able to work cooperatively, in order to solve new, more complex tasks. This conception got materialized in coherent aggregations of computers called farms and clusters. Collective application of nodes, being efficient and economical, was adopted in education, research and industry before long. But maintainance, especially in large scale, appeared as a problem to be resolved. New challenges needed new methods and tools. Development work has been started to build farm management applications and frameworks. In the first part of the thesis, these systems are introduced. After a general description of the matter, a comparative analysis of different approaches and tools illustrates the practical aspects of the theoretical discussion. CERN, the European Organization of Nuclear Research is the largest Particle Physics laboratory in the world....

Do You Kiss Your Mother with That Mouth? An Authentic Large-Scale Undergraduate Research Experience in Mapping the Human Oral Microbiome

Directory of Open Access Journals (Sweden)

Jack T.H. Wang

2015-02-01

Full Text Available Clinical microbiology testing is crucial for the diagnosis and treatment of community and hospital-acquired infections. Laboratory scientists need to utilize technical and problem-solving skills to select from a wide array of microbial identification techniques. The inquiry-driven laboratory training required to prepare microbiology graduates for this professional environment can be difficult to replicate within undergraduate curricula, especially in courses that accommodate large student cohorts. We aimed to improve undergraduate scientific training by engaging hundreds of introductory microbiology students in an Authentic Large-Scale Undergraduate Research Experience (ALURE. The ALURE aimed to characterize the microorganisms that reside in the healthy human oral cavity—the oral microbiome—by analyzing hundreds of samples obtained from student volunteers within the course. Students were able to choose from selective and differential culture media, Gram-staining, microscopy, as well as polymerase chain reaction (PCR and 16S rRNA gene sequencing techniques, in order to collect, analyze, and interpret novel data to determine the collective oral microbiome of the student cohort. Pre- and postsurvey analysis of student learning gains across two iterations of the course (2012–2013 revealed significantly higher student confidence in laboratory skills following the completion of the ALURE (p < 0.05 using the Mann-Whitney U-test. Learning objectives on effective scientific communication were also met through effective student performance in laboratory reports describing the research outcomes of the project. The integration of undergraduate research in clinical microbiology has the capacity to deliver authentic research experiences and improve scientific training for large cohorts of undergraduate students. Editor's Note:The ASM advocates that students must successfully demonstrate the ability to explain and practice safe laboratory techniques

Solving Man-Induced Large-Scale Conservation Problems: The Spanish Imperial Eagle and Power Lines

Science.gov (United States)

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

Large-scale perspective as a challenge

NARCIS (Netherlands)

Plomp, M.G.A.

2012-01-01

1. Scale forms a challenge for chain researchers: when exactly is something ‘large-scale’? What are the underlying factors (e.g. number of parties, data, objects in the chain, complexity) that determine this? It appears to be a continuum between small- and large-scale, where positioning on that

Algorithm 896: LSA: Algorithms for Large-Scale Optimization

Czech Academy of Sciences Publication Activity Database

Lukšan, Ladislav; Matonoha, Ctirad; Vlček, Jan

2009-01-01

Roč. 36, č. 3 (2009), 16-1-16-29 ISSN 0098-3500 R&D Pro jects: GA AV ČR IAA1030405; GA ČR GP201/06/P397 Institutional research plan: CEZ:AV0Z10300504 Keywords : algorithms * design * large-scale optimization * large-scale nonsmooth optimization * large-scale nonlinear least squares * large-scale nonlinear minimax * large-scale systems of nonlinear equations * sparse pro blems * partially separable pro blems * limited-memory methods * discrete Newton methods * quasi-Newton methods * primal interior-point methods Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.904, year: 2009

Scale interactions in a mixing layer – the role of the large-scale gradients

KAUST Repository

Fiscaletti, D.

2016-02-15

© 2016 Cambridge University Press. The interaction between the large and the small scales of turbulence is investigated in a mixing layer, at a Reynolds number based on the Taylor microscale of , via direct numerical simulations. The analysis is performed in physical space, and the local vorticity root-mean-square (r.m.s.) is taken as a measure of the small-scale activity. It is found that positive large-scale velocity fluctuations correspond to large vorticity r.m.s. on the low-speed side of the mixing layer, whereas, they correspond to low vorticity r.m.s. on the high-speed side. The relationship between large and small scales thus depends on position if the vorticity r.m.s. is correlated with the large-scale velocity fluctuations. On the contrary, the correlation coefficient is nearly constant throughout the mixing layer and close to unity if the vorticity r.m.s. is correlated with the large-scale velocity gradients. Therefore, the small-scale activity appears closely related to large-scale gradients, while the correlation between the small-scale activity and the large-scale velocity fluctuations is shown to reflect a property of the large scales. Furthermore, the vorticity from unfiltered (small scales) and from low pass filtered (large scales) velocity fields tend to be aligned when examined within vortical tubes. These results provide evidence for the so-called \\'scale invariance\\' (Meneveau & Katz, Annu. Rev. Fluid Mech., vol. 32, 2000, pp. 1-32), and suggest that some of the large-scale characteristics are not lost at the small scales, at least at the Reynolds number achieved in the present simulation.

Collaborative e-Science Experiments and Scientific Workflows

NARCIS (Netherlands)

Belloum, A.; Inda, M.A.; Vasunin, D.; Korkhov, V.; Zhao, Z.; Rauwerda, H.; Breit, T.M.; Bubak, M.; Hertzberger, L.O.

2011-01-01

Recent advances in Internet and grid technologies have greatly enhanced scientific experiments' life cycle. In addition to compute- and data-intensive tasks, large-scale collaborations involving geographically distributed scientists and e-infrastructure are now possible. Scientific workflows, which

Large-scale solar heat

Energy Technology Data Exchange (ETDEWEB)

Tolonen, J.; Konttinen, P.; Lund, P. [Helsinki Univ. of Technology, Otaniemi (Finland). Dept. of Engineering Physics and Mathematics

1998-12-31

In this project a large domestic solar heating system was built and a solar district heating system was modelled and simulated. Objectives were to improve the performance and reduce costs of a large-scale solar heating system. As a result of the project the benefit/cost ratio can be increased by 40 % through dimensioning and optimising the system at the designing stage. (orig.)

The shared and unique values of optical, fluorescence, thermal and microwave satellite data for estimating large-scale crop yields

Science.gov (United States)

Large-scale crop monitoring and yield estimation are important for both scientific research and practical applications. Satellite remote sensing provides an effective means for regional and global cropland monitoring, particularly in data-sparse regions that lack reliable ground observations and rep...

Probes of large-scale structure in the Universe

International Nuclear Information System (INIS)

Suto, Yasushi; Gorski, K.; Juszkiewicz, R.; Silk, J.

1988-01-01

Recent progress in observational techniques has made it possible to confront quantitatively various models for the large-scale structure of the Universe with detailed observational data. We develop a general formalism to show that the gravitational instability theory for the origin of large-scale structure is now capable of critically confronting observational results on cosmic microwave background radiation angular anisotropies, large-scale bulk motions and large-scale clumpiness in the galaxy counts. (author)

Methods Dealing with Complexity in Selecting Joint Venture Contractors for Large-Scale Infrastructure Projects

Directory of Open Access Journals (Sweden)

Ru Liang

2018-01-01

Full Text Available The magnitude of business dynamics has increased rapidly due to increased complexity, uncertainty, and risk of large-scale infrastructure projects. This fact made it increasingly tough to “go alone” into a contractor. As a consequence, joint venture contractors with diverse strengths and weaknesses cooperatively bid for bidding. Understanding project complexity and making decision on the optimal joint venture contractor is challenging. This paper is to study how to select joint venture contractors for undertaking large-scale infrastructure projects based on a multiattribute mathematical model. Two different methods are developed to solve the problem. One is based on ideal points and the other one is based on balanced ideal advantages. Both of the two methods consider individual difference in expert judgment and contractor attributes. A case study of Hong Kong-Zhuhai-Macao-Bridge (HZMB project in China is used to demonstrate how to apply these two methods and their advantages.

On the Phenomenology of an Accelerated Large-Scale Universe

Directory of Open Access Journals (Sweden)

Martiros Khurshudyan

2016-10-01

Full Text Available In this review paper, several new results towards the explanation of the accelerated expansion of the large-scale universe is discussed. On the other hand, inflation is the early-time accelerated era and the universe is symmetric in the sense of accelerated expansion. The accelerated expansion of is one of the long standing problems in modern cosmology, and physics in general. There are several well defined approaches to solve this problem. One of them is an assumption concerning the existence of dark energy in recent universe. It is believed that dark energy is responsible for antigravity, while dark matter has gravitational nature and is responsible, in general, for structure formation. A different approach is an appropriate modification of general relativity including, for instance, f ( R and f ( T theories of gravity. On the other hand, attempts to build theories of quantum gravity and assumptions about existence of extra dimensions, possible variability of the gravitational constant and the speed of the light (among others, provide interesting modifications of general relativity applicable to problems of modern cosmology, too. In particular, here two groups of cosmological models are discussed. In the first group the problem of the accelerated expansion of large-scale universe is discussed involving a new idea, named the varying ghost dark energy. On the other hand, the second group contains cosmological models addressed to the same problem involving either new parameterizations of the equation of state parameter of dark energy (like varying polytropic gas, or nonlinear interactions between dark energy and dark matter. Moreover, for cosmological models involving varying ghost dark energy, massless particle creation in appropriate radiation dominated universe (when the background dynamics is due to general relativity is demonstrated as well. Exploring the nature of the accelerated expansion of the large-scale universe involving generalized

Large-scale grid management; Storskala Nettforvaltning

Energy Technology Data Exchange (ETDEWEB)

Langdal, Bjoern Inge; Eggen, Arnt Ove

2003-07-01

The network companies in the Norwegian electricity industry now have to establish a large-scale network management, a concept essentially characterized by (1) broader focus (Broad Band, Multi Utility,...) and (2) bigger units with large networks and more customers. Research done by SINTEF Energy Research shows so far that the approaches within large-scale network management may be structured according to three main challenges: centralization, decentralization and out sourcing. The article is part of a planned series.

Efficient Computation of Sparse Matrix Functions for Large-Scale Electronic Structure Calculations: The CheSS Library.

Science.gov (United States)

Mohr, Stephan; Dawson, William; Wagner, Michael; Caliste, Damien; Nakajima, Takahito; Genovese, Luigi

2017-10-10

We present CheSS, the "Chebyshev Sparse Solvers" library, which has been designed to solve typical problems arising in large-scale electronic structure calculations using localized basis sets. The library is based on a flexible and efficient expansion in terms of Chebyshev polynomials and presently features the calculation of the density matrix, the calculation of matrix powers for arbitrary powers, and the extraction of eigenvalues in a selected interval. CheSS is able to exploit the sparsity of the matrices and scales linearly with respect to the number of nonzero entries, making it well-suited for large-scale calculations. The approach is particularly adapted for setups leading to small spectral widths of the involved matrices and outperforms alternative methods in this regime. By coupling CheSS to the DFT code BigDFT, we show that such a favorable setup is indeed possible in practice. In addition, the approach based on Chebyshev polynomials can be massively parallelized, and CheSS exhibits excellent scaling up to thousands of cores even for relatively small matrix sizes.

Information Power Grid: Distributed High-Performance Computing and Large-Scale Data Management for Science and Engineering

Science.gov (United States)

Johnston, William E.; Gannon, Dennis; Nitzberg, Bill

2000-01-01

) Coupling large-scale computing and data systems to scientific and engineering instruments (e.g., realtime interaction with experiments through real-time data analysis and interpretation presented to the experimentalist in ways that allow direct interaction with the experiment (instead of just with instrument control); (5) Highly interactive, augmented reality and virtual reality remote collaborations (e.g., Ames / Boeing Remote Help Desk providing field maintenance use of coupled video and NDI to a remote, on-line airframe structures expert who uses this data to index into detailed design databases, and returns 3D internal aircraft geometry to the field); (5) Single computational problems too large for any single system (e.g. the rotocraft reference calculation). Grids also have the potential to provide pools of resources that could be called on in extraordinary / rapid response situations (such as disaster response) because they can provide common interfaces and access mechanisms, standardized management, and uniform user authentication and authorization, for large collections of distributed resources (whether or not they normally function in concert). IPG development and deployment is addressing requirements obtained by analyzing a number of different application areas, in particular from the NASA Aero-Space Technology Enterprise. This analysis has focussed primarily on two types of users: the scientist / design engineer whose primary interest is problem solving (e.g. determining wing aerodynamic characteristics in many different operating environments), and whose primary interface to IPG will be through various sorts of problem solving frameworks. The second type of user is the tool designer: the computational scientists who convert physics and mathematics into code that can simulate the physical world. These are the two primary users of IPG, and they have rather different requirements. The results of the analysis of the needs of these two types of users provides a

Japanese large-scale interferometers

CERN Document Server

Kuroda, K; Miyoki, S; Ishizuka, H; Taylor, C T; Yamamoto, K; Miyakawa, O; Fujimoto, M K; Kawamura, S; Takahashi, R; Yamazaki, T; Arai, K; Tatsumi, D; Ueda, A; Fukushima, M; Sato, S; Shintomi, T; Yamamoto, A; Suzuki, T; Saitô, Y; Haruyama, T; Sato, N; Higashi, Y; Uchiyama, T; Tomaru, T; Tsubono, K; Ando, M; Takamori, A; Numata, K; Ueda, K I; Yoneda, H; Nakagawa, K; Musha, M; Mio, N; Moriwaki, S; Somiya, K; Araya, A; Kanda, N; Telada, S; Sasaki, M; Tagoshi, H; Nakamura, T; Tanaka, T; Ohara, K

2002-01-01

The objective of the TAMA 300 interferometer was to develop advanced technologies for kilometre scale interferometers and to observe gravitational wave events in nearby galaxies. It was designed as a power-recycled Fabry-Perot-Michelson interferometer and was intended as a step towards a final interferometer in Japan. The present successful status of TAMA is presented. TAMA forms a basis for LCGT (large-scale cryogenic gravitational wave telescope), a 3 km scale cryogenic interferometer to be built in the Kamioka mine in Japan, implementing cryogenic mirror techniques. The plan of LCGT is schematically described along with its associated R and D.

A Chess-Like Game for Teaching Engineering Students to Solve Large System of Simultaneous Linear Equations

Science.gov (United States)

Nguyen, Duc T.; Mohammed, Ahmed Ali; Kadiam, Subhash

2010-01-01

Solving large (and sparse) system of simultaneous linear equations has been (and continues to be) a major challenging problem for many real-world engineering/science applications [1-2]. For many practical/large-scale problems, the sparse, Symmetrical and Positive Definite (SPD) system of linear equations can be conveniently represented in matrix notation as [A] {x} = {b} , where the square coefficient matrix [A] and the Right-Hand-Side (RHS) vector {b} are known. The unknown solution vector {x} can be efficiently solved by the following step-by-step procedures [1-2]: Reordering phase, Matrix Factorization phase, Forward solution phase, and Backward solution phase. In this research work, a Game-Based Learning (GBL) approach has been developed to help engineering students to understand crucial details about matrix reordering and factorization phases. A "chess-like" game has been developed and can be played by either a single player, or two players. Through this "chess-like" open-ended game, the players/learners will not only understand the key concepts involved in reordering algorithms (based on existing algorithms), but also have the opportunities to "discover new algorithms" which are better than existing algorithms. Implementing the proposed "chess-like" game for matrix reordering and factorization phases can be enhanced by FLASH [3] computer environments, where computer simulation with animated human voice, sound effects, visual/graphical/colorful displays of matrix tables, score (or monetary) awards for the best game players, etc. can all be exploited. Preliminary demonstrations of the developed GBL approach can be viewed by anyone who has access to the internet web-site [4]!

Compiler Technology for Parallel Scientific Computation

Directory of Open Access Journals (Sweden)

Can Özturan

1994-01-01

Full Text Available There is a need for compiler technology that, given the source program, will generate efficient parallel codes for different architectures with minimal user involvement. Parallel computation is becoming indispensable in solving large-scale problems in science and engineering. Yet, the use of parallel computation is limited by the high costs of developing the needed software. To overcome this difficulty we advocate a comprehensive approach to the development of scalable architecture-independent software for scientific computation based on our experience with equational programming language (EPL. Our approach is based on a program decomposition, parallel code synthesis, and run-time support for parallel scientific computation. The program decomposition is guided by the source program annotations provided by the user. The synthesis of parallel code is based on configurations that describe the overall computation as a set of interacting components. Run-time support is provided by the compiler-generated code that redistributes computation and data during object program execution. The generated parallel code is optimized using techniques of data alignment, operator placement, wavefront determination, and memory optimization. In this article we discuss annotations, configurations, parallel code generation, and run-time support suitable for parallel programs written in the functional parallel programming language EPL and in Fortran.

Large-Scale Image Analytics Using Deep Learning

Science.gov (United States)

Ganguly, S.; Nemani, R. R.; Basu, S.; Mukhopadhyay, S.; Michaelis, A.; Votava, P.

2014-12-01

High resolution land cover classification maps are needed to increase the accuracy of current Land ecosystem and climate model outputs. Limited studies are in place that demonstrates the state-of-the-art in deriving very high resolution (VHR) land cover products. In addition, most methods heavily rely on commercial softwares that are difficult to scale given the region of study (e.g. continents to globe). Complexities in present approaches relate to (a) scalability of the algorithm, (b) large image data processing (compute and memory intensive), (c) computational cost, (d) massively parallel architecture, and (e) machine learning automation. In addition, VHR satellite datasets are of the order of terabytes and features extracted from these datasets are of the order of petabytes. In our present study, we have acquired the National Agricultural Imaging Program (NAIP) dataset for the Continental United States at a spatial resolution of 1-m. This data comes as image tiles (a total of quarter million image scenes with ~60 million pixels) and has a total size of ~100 terabytes for a single acquisition. Features extracted from the entire dataset would amount to ~8-10 petabytes. In our proposed approach, we have implemented a novel semi-automated machine learning algorithm rooted on the principles of "deep learning" to delineate the percentage of tree cover. In order to perform image analytics in such a granular system, it is mandatory to devise an intelligent archiving and query system for image retrieval, file structuring, metadata processing and filtering of all available image scenes. Using the Open NASA Earth Exchange (NEX) initiative, which is a partnership with Amazon Web Services (AWS), we have developed an end-to-end architecture for designing the database and the deep belief network (following the distbelief computing model) to solve a grand challenge of scaling this process across quarter million NAIP tiles that cover the entire Continental United States. The

Using of P2P Networks for Acceleration of RTE Tasks Solving

Directory of Open Access Journals (Sweden)

Adrian Iftene

2008-07-01

Full Text Available In the last years the computational Grids have become an important research area in large-scale scientific and engineering research. Our approach is based on Peer-to-peer (P2P networks, which are recognized as one of most used architectures in order to achieve scalability in key components of Grid systems. The main scope in using of a computational Grid was to improve the computational speed of systems that solve complex problems from Natural Language processing field. We will see how can be implemented a computational Grid using the P2P model, and how can be used SMB protocol for file transfer. After that we will see how we can use this computational Grid, in order to improve the computational speed of a system used in RTE competition [1], a new complex challenge from Natural Language processing field.

Reducing computational costs in large scale 3D EIT by using a sparse Jacobian matrix with block-wise CGLS reconstruction

International Nuclear Information System (INIS)

Yang, C L; Wei, H Y; Soleimani, M; Adler, A

2013-01-01

Electrical impedance tomography (EIT) is a fast and cost-effective technique to provide a tomographic conductivity image of a subject from boundary current–voltage data. This paper proposes a time and memory efficient method for solving a large scale 3D EIT inverse problem using a parallel conjugate gradient (CG) algorithm. The 3D EIT system with a large number of measurement data can produce a large size of Jacobian matrix; this could cause difficulties in computer storage and the inversion process. One of challenges in 3D EIT is to decrease the reconstruction time and memory usage, at the same time retaining the image quality. Firstly, a sparse matrix reduction technique is proposed using thresholding to set very small values of the Jacobian matrix to zero. By adjusting the Jacobian matrix into a sparse format, the element with zeros would be eliminated, which results in a saving of memory requirement. Secondly, a block-wise CG method for parallel reconstruction has been developed. The proposed method has been tested using simulated data as well as experimental test samples. Sparse Jacobian with a block-wise CG enables the large scale EIT problem to be solved efficiently. Image quality measures are presented to quantify the effect of sparse matrix reduction in reconstruction results. (paper)

Reducing computational costs in large scale 3D EIT by using a sparse Jacobian matrix with block-wise CGLS reconstruction.

Science.gov (United States)

Yang, C L; Wei, H Y; Adler, A; Soleimani, M

2013-06-01

Electrical impedance tomography (EIT) is a fast and cost-effective technique to provide a tomographic conductivity image of a subject from boundary current-voltage data. This paper proposes a time and memory efficient method for solving a large scale 3D EIT inverse problem using a parallel conjugate gradient (CG) algorithm. The 3D EIT system with a large number of measurement data can produce a large size of Jacobian matrix; this could cause difficulties in computer storage and the inversion process. One of challenges in 3D EIT is to decrease the reconstruction time and memory usage, at the same time retaining the image quality. Firstly, a sparse matrix reduction technique is proposed using thresholding to set very small values of the Jacobian matrix to zero. By adjusting the Jacobian matrix into a sparse format, the element with zeros would be eliminated, which results in a saving of memory requirement. Secondly, a block-wise CG method for parallel reconstruction has been developed. The proposed method has been tested using simulated data as well as experimental test samples. Sparse Jacobian with a block-wise CG enables the large scale EIT problem to be solved efficiently. Image quality measures are presented to quantify the effect of sparse matrix reduction in reconstruction results.

Large scale model testing

International Nuclear Information System (INIS)

Brumovsky, M.; Filip, R.; Polachova, H.; Stepanek, S.

1989-01-01

Fracture mechanics and fatigue calculations for WWER reactor pressure vessels were checked by large scale model testing performed using large testing machine ZZ 8000 (with a maximum load of 80 MN) at the SKODA WORKS. The results are described from testing the material resistance to fracture (non-ductile). The testing included the base materials and welded joints. The rated specimen thickness was 150 mm with defects of a depth between 15 and 100 mm. The results are also presented of nozzles of 850 mm inner diameter in a scale of 1:3; static, cyclic, and dynamic tests were performed without and with surface defects (15, 30 and 45 mm deep). During cyclic tests the crack growth rate in the elastic-plastic region was also determined. (author). 6 figs., 2 tabs., 5 refs

Adaptive Neural Networks Decentralized FTC Design for Nonstrict-Feedback Nonlinear Interconnected Large-Scale Systems Against Actuator Faults.

Science.gov (United States)

Li, Yongming; Tong, Shaocheng

The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small neighborhood of zero. Finally, numerical results of practical examples are presented to further demonstrate the effectiveness of the proposed control strategy.The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small

Why small-scale cannabis growers stay small: five mechanisms that prevent small-scale growers from going large scale.

Science.gov (United States)

Hammersvik, Eirik; Sandberg, Sveinung; Pedersen, Willy

2012-11-01

Over the past 15-20 years, domestic cultivation of cannabis has been established in a number of European countries. New techniques have made such cultivation easier; however, the bulk of growers remain small-scale. In this study, we explore the factors that prevent small-scale growers from increasing their production. The study is based on 1 year of ethnographic fieldwork and qualitative interviews conducted with 45 Norwegian cannabis growers, 10 of whom were growing on a large-scale and 35 on a small-scale. The study identifies five mechanisms that prevent small-scale indoor growers from going large-scale. First, large-scale operations involve a number of people, large sums of money, a high work-load and a high risk of detection, and thus demand a higher level of organizational skills than for small growing operations. Second, financial assets are needed to start a large 'grow-site'. Housing rent, electricity, equipment and nutrients are expensive. Third, to be able to sell large quantities of cannabis, growers need access to an illegal distribution network and knowledge of how to act according to black market norms and structures. Fourth, large-scale operations require advanced horticultural skills to maximize yield and quality, which demands greater skills and knowledge than does small-scale cultivation. Fifth, small-scale growers are often embedded in the 'cannabis culture', which emphasizes anti-commercialism, anti-violence and ecological and community values. Hence, starting up large-scale production will imply having to renegotiate or abandon these values. Going from small- to large-scale cannabis production is a demanding task-ideologically, technically, economically and personally. The many obstacles that small-scale growers face and the lack of interest and motivation for going large-scale suggest that the risk of a 'slippery slope' from small-scale to large-scale growing is limited. Possible political implications of the findings are discussed. Copyright

Distributed large-scale dimensional metrology new insights

CERN Document Server

Franceschini, Fiorenzo; Maisano, Domenico

2011-01-01

Focuses on the latest insights into and challenges of distributed large scale dimensional metrology Enables practitioners to study distributed large scale dimensional metrology independently Includes specific examples of the development of new system prototypes

VET workers problem-solving skills in technology-rich environments: European approach

OpenAIRE

Hämäläinen, Raija

2014-01-01

The European workplace is challenging VET adults problem-solving skills in technology-rich environments (TREs). So far, no international large-scale assessment data has been available for VET. The PIAAC data comprise the most comprehensive source of information on adults skills to date. The present study (N=50 369) focuses on gaining insight into the problem-solving skills in TREs of adults with a VET background. When examining the similarities and differences in VET adults problem-solving sk...

VET workers’ problem-solving skills in technology-rich environments: European approach

OpenAIRE

Hämäläinen, Raija; Cincinnato, Sebastiano; Malin, Antero; De Wever, Bram

2014-01-01

The European workplace is challenging VET adults’ problem-solving skills in technology-rich environments (TREs). So far, no international large-scale assessment data has been available for VET. The PIAAC data comprise the most comprehensive source of information on adults’ skills to date. The present study (N=50 369) focuses on gaining insight into the problem-solving skills in TREs of adults with a VET background. When examining the similarities and differences in VET adults’ problem-solving...

SCALE INTERACTION IN A MIXING LAYER. THE ROLE OF THE LARGE-SCALE GRADIENTS

KAUST Repository

Fiscaletti, Daniele; Attili, Antonio; Bisetti, Fabrizio; Elsinga, Gerrit E.

2015-01-01

from physical considerations we would expect the scales to interact in a qualitatively similar way within the flow and across different turbulent flows. Therefore, instead of the large-scale fluctuations, the large-scale gradients modulation of the small scales has been additionally investigated.

Recent Regional Climate State and Change - Derived through Downscaling Homogeneous Large-scale Components of Re-analyses

Science.gov (United States)

Von Storch, H.; Klehmet, K.; Geyer, B.; Li, D.; Schubert-Frisius, M.; Tim, N.; Zorita, E.

2015-12-01

Global re-analyses suffer from inhomogeneities, as they process data from networks under development. However, the large-scale component of such re-analyses is mostly homogeneous; additional observational data add in most cases to a better description of regional details and less so on large-scale states. Therefore, the concept of downscaling may be applied to homogeneously complementing the large-scale state of the re-analyses with regional detail - wherever the condition of homogeneity of the large-scales is fulfilled. Technically this can be done by using a regional climate model, or a global climate model, which is constrained on the large scale by spectral nudging. This approach has been developed and tested for the region of Europe, and a skillful representation of regional risks - in particular marine risks - was identified. While the data density in Europe is considerably better than in most other regions of the world, even here insufficient spatial and temporal coverage is limiting risk assessments. Therefore, downscaled data-sets are frequently used by off-shore industries. We have run this system also in regions with reduced or absent data coverage, such as the Lena catchment in Siberia, in the Yellow Sea/Bo Hai region in East Asia, in Namibia and the adjacent Atlantic Ocean. Also a global (large scale constrained) simulation has been. It turns out that spatially detailed reconstruction of the state and change of climate in the three to six decades is doable for any region of the world.The different data sets are archived and may freely by used for scientific purposes. Of course, before application, a careful analysis of the quality for the intended application is needed, as sometimes unexpected changes in the quality of the description of large-scale driving states prevail.

A New Method Based On Modified Shuffled Frog Leaping Algorithm In Order To Solve Nonlinear Large Scale Problem

Directory of Open Access Journals (Sweden)

Aliasghar Baziar

2015-03-01

Full Text Available Abstract In order to handle large scale problems this study has used shuffled frog leaping algorithm. This algorithm is an optimization method based on natural memetics that uses a new two-phase modification to it to have a better search in the problem space. The suggested algorithm is evaluated by comparing to some well known algorithms using several benchmark optimization problems. The simulation results have clearly shown the superiority of this algorithm over other well-known methods in the area.

Trends in large-scale testing of reactor structures

International Nuclear Information System (INIS)

Blejwas, T.E.

2003-01-01

Large-scale tests of reactor structures have been conducted at Sandia National Laboratories since the late 1970s. This paper describes a number of different large-scale impact tests, pressurization tests of models of containment structures, and thermal-pressure tests of models of reactor pressure vessels. The advantages of large-scale testing are evident, but cost, in particular limits its use. As computer models have grown in size, such as number of degrees of freedom, the advent of computer graphics has made possible very realistic representation of results - results that may not accurately represent reality. A necessary condition to avoiding this pitfall is the validation of the analytical methods and underlying physical representations. Ironically, the immensely larger computer models sometimes increase the need for large-scale testing, because the modeling is applied to increasing more complex structural systems and/or more complex physical phenomena. Unfortunately, the cost of large-scale tests is a disadvantage that will likely severely limit similar testing in the future. International collaborations may provide the best mechanism for funding future programs with large-scale tests. (author)

Modeling and solving a large-scale generation expansion planning problem under uncertainty

Energy Technology Data Exchange (ETDEWEB)

Jin, Shan; Ryan, Sarah M. [Iowa State University, Department of Industrial and Manufacturing Systems Engineering, Ames (United States); Watson, Jean-Paul [Sandia National Laboratories, Discrete Math and Complex Systems Department, Albuquerque (United States); Woodruff, David L. [University of California Davis, Graduate School of Management, Davis (United States)

2011-11-15

We formulate a generation expansion planning problem to determine the type and quantity of power plants to be constructed over each year of an extended planning horizon, considering uncertainty regarding future demand and fuel prices. Our model is expressed as a two-stage stochastic mixed-integer program, which we use to compute solutions independently minimizing the expected cost and the Conditional Value-at-Risk; i.e., the risk of significantly larger-than-expected operational costs. We introduce stochastic process models to capture demand and fuel price uncertainty, which are in turn used to generate trees that accurately represent the uncertainty space. Using a realistic problem instance based on the Midwest US, we explore two fundamental, unexplored issues that arise when solving any stochastic generation expansion model. First, we introduce and discuss the use of an algorithm for computing confidence intervals on obtained solution costs, to account for the fact that a finite sample of scenarios was used to obtain a particular solution. Second, we analyze the nature of solutions obtained under different parameterizations of this method, to assess whether the recommended solutions themselves are invariant to changes in costs. The issues are critical for decision makers who seek truly robust recommendations for generation expansion planning. (orig.)

[Review of occupational hazard census and large-scale surveys in sixty years in China].

Science.gov (United States)

Li, Tao; Li, Chao-lin; Wang, Huan-qiang

2010-11-01

To compare and analyze the all previous censuses and large-scale surveys on occupational hazard in China, draw lessons from the past, and try to provide references for the development of census or surveys on the occupational hazard in the new period. A literature retrieval had been performed mainly on the occupational hazard census and large-scale surveys since the founding of People's Republic of China. Only the survey items carried on a national scale were selected. Some keywords were drawn from these items such as survey time, survey scope, industries, occupational diseases and the rate of examination, organization and technical director, methods and so on. The outcomes and experiences were summarized. Since the founding of People's Republic of China, there were seven occupational hazard census and large-scale surveys carried in China, three of them were about silicosis or pneumoconiosis, two of them were about poison and carcinogens, one was about noise, another one was about the township industrial enterprises. Leadership attention was the fundamental guarantee of the success of the survey, sound occupational health management organizations were the base, collaborative relationship with each other was an import factor, and only the interdisciplinary team, scientific design, quality control and incentive mechanism could assure the quality of the survey. The survey should be designed and carried out according to industries.

TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild

KAUST Repository

Mü ller, Matthias; Bibi, Adel Aamer; Giancola, Silvio; Al-Subaihi, Salman; Ghanem, Bernard

2018-01-01

Despite the numerous developments in object tracking, further development of current tracking algorithms is limited by small and mostly saturated datasets. As a matter of fact, data-hungry trackers based on deep-learning currently rely on object detection datasets due to the scarcity of dedicated large-scale tracking datasets. In this work, we present TrackingNet, the first large-scale dataset and benchmark for object tracking in the wild. We provide more than 30K videos with more than 14 million dense bounding box annotations. Our dataset covers a wide selection of object classes in broad and diverse context. By releasing such a large-scale dataset, we expect deep trackers to further improve and generalize. In addition, we introduce a new benchmark composed of 500 novel videos, modeled with a distribution similar to our training dataset. By sequestering the annotation of the test set and providing an online evaluation server, we provide a fair benchmark for future development of object trackers. Deep trackers fine-tuned on a fraction of our dataset improve their performance by up to 1.6% on OTB100 and up to 1.7% on TrackingNet Test. We provide an extensive benchmark on TrackingNet by evaluating more than 20 trackers. Our results suggest that object tracking in the wild is far from being solved.

TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild

KAUST Repository

Müller, Matthias

2018-03-28

Despite the numerous developments in object tracking, further development of current tracking algorithms is limited by small and mostly saturated datasets. As a matter of fact, data-hungry trackers based on deep-learning currently rely on object detection datasets due to the scarcity of dedicated large-scale tracking datasets. In this work, we present TrackingNet, the first large-scale dataset and benchmark for object tracking in the wild. We provide more than 30K videos with more than 14 million dense bounding box annotations. Our dataset covers a wide selection of object classes in broad and diverse context. By releasing such a large-scale dataset, we expect deep trackers to further improve and generalize. In addition, we introduce a new benchmark composed of 500 novel videos, modeled with a distribution similar to our training dataset. By sequestering the annotation of the test set and providing an online evaluation server, we provide a fair benchmark for future development of object trackers. Deep trackers fine-tuned on a fraction of our dataset improve their performance by up to 1.6% on OTB100 and up to 1.7% on TrackingNet Test. We provide an extensive benchmark on TrackingNet by evaluating more than 20 trackers. Our results suggest that object tracking in the wild is far from being solved.

The Associative Basis of Scientific Creativity: A Model Proposal

Directory of Open Access Journals (Sweden)

Esra Kanli

2014-06-01

Full Text Available Creativity is accepted as an important part of scientific skills. Scientific creativity proceeds from a need or urge to solve a problem, and in-volves the production of original and useful ideas or products. Existing scientific creativity theories and tests do not feature the very im-portant thinking processes, such as analogical and associative thinking, which can be consid-ered crucial in creative scientific problem solv-ing. Current study’s aim is to provide an alter-native model and explicate the associative basis of scientific creativity. Emerging from the re-viewed theoretical framework, Scientific Asso-ciations Model is proposed. This model claims that, similarity and mediation constitutes the basis of creativity and focuses on three compo-nents namely; associative thinking, analogical thinking (analogical reasoning & analogical problem solving and insight which are consid-ered to be main elements of scientific associa-tive thinking.

Investigation of the Contamination Control in a Cleaning Room with a Moving AGV by 3D Large-Scale Simulation

Directory of Open Access Journals (Sweden)

Qing-He Yao

2013-01-01

Full Text Available The motions of the airflow induced by the movement of an automatic guided vehicle (AGV in a cleanroom are numerically studied by large-scale simulation. For this purpose, numerical experiments scheme based on domain decomposition method is designed. Compared with the related past research, the high Reynolds number is treated by large-scale computation in this work. A domain decomposition Lagrange-Galerkin method is employed to approximate the Navier-Stokes equations and the convection diffusion equation; the stiffness matrix is symmetric and an incomplete balancing preconditioned conjugate gradient (PCG method is employed to solve the linear algebra system iteratively. The end wall effects are readily viewed, and the necessity of the extension to 3 dimensions is confirmed. The effect of the high efficiency particular air (HEPA filter on contamination control is studied and the proper setting of the speed of the clean air flow is also investigated. More details of the recirculation zones are revealed by the 3D large-scale simulation.

Large Scale Computations in Air Pollution Modelling

DEFF Research Database (Denmark)

Zlatev, Z.; Brandt, J.; Builtjes, P. J. H.

Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998......Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998...

Paul Scherrer Institute Scientific and Technical Report 2000. Volume VI: Large Research Facilities

International Nuclear Information System (INIS)

Foroughi, Fereydoun; Bercher, Renate; Buechli, Carmen; Zumkeller, Lotty

2001-01-01

The PSI Department Large Research Facilities (GFA) joins the efforts to provide an excellent research environment to Swiss and foreign research groups on the experimental facilities driven by our high intensity proton accelerator complex. Its divisions care for the running, maintenance and enhancement of the accelerator complex, the primary proton beamlines, the targets and the secondary beams as well as the neutron spallation source SINQ. The division for technical support and coordination provides for technical support to the research facility complementary to the basic logistic available from the department for logistics and marketing. Besides running the facilities, the staff of the department is also involved in theoretical and experimental research projects. Some of them address basic scientific questions mainly concerning the properties of micro- or nanostructured materials: experiments as well as large scale computer simulations of molecular dynamics were performed to investigate nonclassical materials properties. Others are related to improvements or extensions of the capabilities of our facilities. We also report on intriguing results from applications of the neutron capture radiography, the prompt gamma activation method and the isotope production facility at SINQ

Paul Scherrer Institute Scientific and Technical Report 2000. Volume VI: Large Research Facilities

Energy Technology Data Exchange (ETDEWEB)

Foroughi, Fereydoun; Bercher, Renate; Buechli, Carmen; Zumkeller, Lotty [eds.

2001-07-01

The PSI Department Large Research Facilities (GFA) joins the efforts to provide an excellent research environment to Swiss and foreign research groups on the experimental facilities driven by our high intensity proton accelerator complex. Its divisions care for the running, maintenance and enhancement of the accelerator complex, the primary proton beamlines, the targets and the secondary beams as well as the neutron spallation source SINQ. The division for technical support and coordination provides for technical support to the research facility complementary to the basic logistic available from the department for logistics and marketing. Besides running the facilities, the staff of the department is also involved in theoretical and experimental research projects. Some of them address basic scientific questions mainly concerning the properties of micro- or nanostructured materials: experiments as well as large scale computer simulations of molecular dynamics were performed to investigate nonclassical materials properties. Others are related to improvements or extensions of the capabilities of our facilities. We also report on intriguing results from applications of the neutron capture radiography, the prompt gamma activation method and the isotope production facility at SINQ.

Addressing Criticisms of Large-Scale Marine Protected Areas

Science.gov (United States)

Ban, Natalie C; Fernandez, Miriam; Friedlander, Alan M; García-Borboroglu, Pablo; Golbuu, Yimnang; Guidetti, Paolo; Harris, Jean M; Hawkins, Julie P; Langlois, Tim; McCauley, Douglas J; Pikitch, Ellen K; Richmond, Robert H; Roberts, Callum M

2018-01-01

Abstract Designated large-scale marine protected areas (LSMPAs, 100,000 or more square kilometers) constitute over two-thirds of the approximately 6.6% of the ocean and approximately 14.5% of the exclusive economic zones within marine protected areas. Although LSMPAs have received support among scientists and conservation bodies for wilderness protection, regional ecological connectivity, and improving resilience to climate change, there are also concerns. We identified 10 common criticisms of LSMPAs along three themes: (1) placement, governance, and management; (2) political expediency; and (3) social–ecological value and cost. Through critical evaluation of scientific evidence, we discuss the value, achievements, challenges, and potential of LSMPAs in these arenas. We conclude that although some criticisms are valid and need addressing, none pertain exclusively to LSMPAs, and many involve challenges ubiquitous in management. We argue that LSMPAs are an important component of a diversified management portfolio that tempers potential losses, hedges against uncertainty, and enhances the probability of achieving sustainably managed oceans. PMID:29731514

Large-Scale 3D Printing: The Way Forward

Science.gov (United States)

Jassmi, Hamad Al; Najjar, Fady Al; Ismail Mourad, Abdel-Hamid

2018-03-01

Research on small-scale 3D printing has rapidly evolved, where numerous industrial products have been tested and successfully applied. Nonetheless, research on large-scale 3D printing, directed to large-scale applications such as construction and automotive manufacturing, yet demands a great a great deal of efforts. Large-scale 3D printing is considered an interdisciplinary topic and requires establishing a blended knowledge base from numerous research fields including structural engineering, materials science, mechatronics, software engineering, artificial intelligence and architectural engineering. This review article summarizes key topics of relevance to new research trends on large-scale 3D printing, particularly pertaining (1) technological solutions of additive construction (i.e. the 3D printers themselves), (2) materials science challenges, and (3) new design opportunities.

Liquid metal fast breeder reactor steam generator survey of the consequences of large scale sodium water reaction

International Nuclear Information System (INIS)

Vambenepe, G.

1978-01-01

The ''Retona'' three-dimensional hydrodynamic computing code is being developed by Electricity de France to survey the consequences, on the very plant, of a large scale sodium water reaction in liquid metal steam generators. In this communication, the heat-exchanger geometry is schematized and the problem solving process briefly described under assumed simplifying hypotheses. The application of the results to the Creusot-Loire steam generator selected for Super-Phenix are given as an example. (author)

The XChemExplorer graphical workflow tool for routine or large-scale protein–ligand structure determination

Science.gov (United States)

Krojer, Tobias; Talon, Romain; Pearce, Nicholas; Douangamath, Alice; Brandao-Neto, Jose; Dias, Alexandre; Marsden, Brian

2017-01-01

XChemExplorer (XCE) is a data-management and workflow tool to support large-scale simultaneous analysis of protein–ligand complexes during structure-based ligand discovery (SBLD). The user interfaces of established crystallo­graphic software packages such as CCP4 [Winn et al. (2011 ▸), Acta Cryst. D67, 235–242] or PHENIX [Adams et al. (2010 ▸), Acta Cryst. D66, 213–221] have entrenched the paradigm that a ‘project’ is concerned with solving one structure. This does not hold for SBLD, where many almost identical structures need to be solved and analysed quickly in one batch of work. Functionality to track progress and annotate structures is essential. XCE provides an intuitive graphical user interface which guides the user from data processing, initial map calculation, ligand identification and refinement up until data dissemination. It provides multiple entry points depending on the need of each project, enables batch processing of multiple data sets and records metadata, progress and annotations in an SQLite database. XCE is freely available and works on any Linux and Mac OS X system, and the only dependency is to have the latest version of CCP4 installed. The design and usage of this tool are described here, and its usefulness is demonstrated in the context of fragment-screening campaigns at the Diamond Light Source. It is routinely used to analyse projects comprising 1000 data sets or more, and therefore scales well to even very large ligand-design projects. PMID:28291762

The XChemExplorer graphical workflow tool for routine or large-scale protein-ligand structure determination.

Science.gov (United States)

Krojer, Tobias; Talon, Romain; Pearce, Nicholas; Collins, Patrick; Douangamath, Alice; Brandao-Neto, Jose; Dias, Alexandre; Marsden, Brian; von Delft, Frank

2017-03-01

XChemExplorer (XCE) is a data-management and workflow tool to support large-scale simultaneous analysis of protein-ligand complexes during structure-based ligand discovery (SBLD). The user interfaces of established crystallographic software packages such as CCP4 [Winn et al. (2011), Acta Cryst. D67, 235-242] or PHENIX [Adams et al. (2010), Acta Cryst. D66, 213-221] have entrenched the paradigm that a `project' is concerned with solving one structure. This does not hold for SBLD, where many almost identical structures need to be solved and analysed quickly in one batch of work. Functionality to track progress and annotate structures is essential. XCE provides an intuitive graphical user interface which guides the user from data processing, initial map calculation, ligand identification and refinement up until data dissemination. It provides multiple entry points depending on the need of each project, enables batch processing of multiple data sets and records metadata, progress and annotations in an SQLite database. XCE is freely available and works on any Linux and Mac OS X system, and the only dependency is to have the latest version of CCP4 installed. The design and usage of this tool are described here, and its usefulness is demonstrated in the context of fragment-screening campaigns at the Diamond Light Source. It is routinely used to analyse projects comprising 1000 data sets or more, and therefore scales well to even very large ligand-design projects.

Internet computer coaches for introductory physics problem solving

Science.gov (United States)

Xu Ryan, Qing

The ability to solve problems in a variety of contexts is becoming increasingly important in our rapidly changing technological society. Problem-solving is a complex process that is important for everyday life and crucial for learning physics. Although there is a great deal of effort to improve student problem solving skills throughout the educational system, national studies have shown that the majority of students emerge from such courses having made little progress toward developing good problem-solving skills. The Physics Education Research Group at the University of Minnesota has been developing Internet computer coaches to help students become more expert-like problem solvers. During the Fall 2011 and Spring 2013 semesters, the coaches were introduced into large sections (200+ students) of the calculus based introductory mechanics course at the University of Minnesota. This dissertation, will address the research background of the project, including the pedagogical design of the coaches and the assessment of problem solving. The methodological framework of conducting experiments will be explained. The data collected from the large-scale experimental studies will be discussed from the following aspects: the usage and usability of these coaches; the usefulness perceived by students; and the usefulness measured by final exam and problem solving rubric. It will also address the implications drawn from this study, including using this data to direct future coach design and difficulties in conducting authentic assessment of problem-solving.

Growth Limits in Large Scale Networks

DEFF Research Database (Denmark)

Knudsen, Thomas Phillip

limitations. The rising complexity of network management with the convergence of communications platforms is shown as problematic for both automatic management feasibility and for manpower resource management. In the fourth step the scope is extended to include the present society with the DDN project as its......The Subject of large scale networks is approached from the perspective of the network planner. An analysis of the long term planning problems is presented with the main focus on the changing requirements for large scale networks and the potential problems in meeting these requirements. The problems...... the fundamental technological resources in network technologies are analysed for scalability. Here several technological limits to continued growth are presented. The third step involves a survey of major problems in managing large scale networks given the growth of user requirements and the technological...

Large scale reflood test

International Nuclear Information System (INIS)

Hirano, Kemmei; Murao, Yoshio

1980-01-01

The large-scale reflood test with a view to ensuring the safety of light water reactors was started in fiscal 1976 based on the special account act for power source development promotion measures by the entrustment from the Science and Technology Agency. Thereafter, to establish the safety of PWRs in loss-of-coolant accidents by joint international efforts, the Japan-West Germany-U.S. research cooperation program was started in April, 1980. Thereupon, the large-scale reflood test is now included in this program. It consists of two tests using a cylindrical core testing apparatus for examining the overall system effect and a plate core testing apparatus for testing individual effects. Each apparatus is composed of the mock-ups of pressure vessel, primary loop, containment vessel and ECCS. The testing method, the test results and the research cooperation program are described. (J.P.N.)

Size matters: the ethical, legal, and social issues surrounding large-scale genetic biobank initiatives

Directory of Open Access Journals (Sweden)

Klaus Lindgaard Hoeyer

2012-04-01

Full Text Available During the past ten years the complex ethical, legal and social issues (ELSI typically surrounding large-scale genetic biobank research initiatives have been intensely debated in academic circles. In many ways genetic epidemiology has undergone a set of changes resembling what in physics has been called a transition into Big Science. This article outlines consequences of this transition and suggests that the change in scale implies challenges to the roles of scientists and public alike. An overview of key issues is presented, and it is argued that biobanks represent not just scientific endeavors with purely epistemic objectives, but also political projects with social implications. As such, they demand clever maneuvering among social interests to succeed.

Anisotropy of the Cosmic Microwave Background Radiation on Large and Medium Angular Scales

Science.gov (United States)

Houghton, Anthony; Timbie, Peter

1998-01-01

This grant has supported work at Brown University on measurements of the 2.7 K Cosmic Microwave Background Radiation (CMB). The goal has been to characterize the spatial variations in the temperature of the CMB in order to understand the formation of large-scale structure in the universe. We have concurrently pursued two measurements using millimeter-wave telescopes carried aloft by scientific balloons. Both systems operate over a range of wavelengths, chosen to allow spectral removal of foreground sources such as the atmosphere, Galaxy, etc. The angular resolution of approx. 25 arcminutes is near the angular scale at which the most structure is predicted by current models to be visible in the CMB angular power spectrum. The main goal is to determine the angular scale of this structure; in turn we can infer the density parameter, Omega, for the universe as well as other cosmological parameters, such as the Hubble constant.

Large-scale model of flow in heterogeneous and hierarchical porous media

Science.gov (United States)

Chabanon, Morgan; Valdés-Parada, Francisco J.; Ochoa-Tapia, J. Alberto; Goyeau, Benoît

2017-11-01

Heterogeneous porous structures are very often encountered in natural environments, bioremediation processes among many others. Reliable models for momentum transport are crucial whenever mass transport or convective heat occurs in these systems. In this work, we derive a large-scale average model for incompressible single-phase flow in heterogeneous and hierarchical soil porous media composed of two distinct porous regions embedding a solid impermeable structure. The model, based on the local mechanical equilibrium assumption between the porous regions, results in a unique momentum transport equation where the global effective permeability naturally depends on the permeabilities at the intermediate mesoscopic scales and therefore includes the complex hierarchical structure of the soil. The associated closure problem is numerically solved for various configurations and properties of the heterogeneous medium. The results clearly show that the effective permeability increases with the volume fraction of the most permeable porous region. It is also shown that the effective permeability is sensitive to the dimensionality spatial arrangement of the porous regions and in particular depends on the contact between the impermeable solid and the two porous regions.

Application of parallel computing techniques to a large-scale reservoir simulation

International Nuclear Information System (INIS)

Zhang, Keni; Wu, Yu-Shu; Ding, Chris; Pruess, Karsten

2001-01-01

Even with the continual advances made in both computational algorithms and computer hardware used in reservoir modeling studies, large-scale simulation of fluid and heat flow in heterogeneous reservoirs remains a challenge. The problem commonly arises from intensive computational requirement for detailed modeling investigations of real-world reservoirs. This paper presents the application of a massive parallel-computing version of the TOUGH2 code developed for performing large-scale field simulations. As an application example, the parallelized TOUGH2 code is applied to develop a three-dimensional unsaturated-zone numerical model simulating flow of moisture, gas, and heat in the unsaturated zone of Yucca Mountain, Nevada, a potential repository for high-level radioactive waste. The modeling approach employs refined spatial discretization to represent the heterogeneous fractured tuffs of the system, using more than a million 3-D gridblocks. The problem of two-phase flow and heat transfer within the model domain leads to a total of 3,226,566 linear equations to be solved per Newton iteration. The simulation is conducted on a Cray T3E-900, a distributed-memory massively parallel computer. Simulation results indicate that the parallel computing technique, as implemented in the TOUGH2 code, is very efficient. The reliability and accuracy of the model results have been demonstrated by comparing them to those of small-scale (coarse-grid) models. These comparisons show that simulation results obtained with the refined grid provide more detailed predictions of the future flow conditions at the site, aiding in the assessment of proposed repository performance

Large Scale Cosmological Anomalies and Inhomogeneous Dark Energy

Directory of Open Access Journals (Sweden)

Leandros Perivolaropoulos

2014-01-01

Full Text Available A wide range of large scale observations hint towards possible modifications on the standard cosmological model which is based on a homogeneous and isotropic universe with a small cosmological constant and matter. These observations, also known as “cosmic anomalies” include unexpected Cosmic Microwave Background perturbations on large angular scales, large dipolar peculiar velocity flows of galaxies (“bulk flows”, the measurement of inhomogenous values of the fine structure constant on cosmological scales (“alpha dipole” and other effects. The presence of the observational anomalies could either be a large statistical fluctuation in the context of ΛCDM or it could indicate a non-trivial departure from the cosmological principle on Hubble scales. Such a departure is very much constrained by cosmological observations for matter. For dark energy however there are no significant observational constraints for Hubble scale inhomogeneities. In this brief review I discuss some of the theoretical models that can naturally lead to inhomogeneous dark energy, their observational constraints and their potential to explain the large scale cosmic anomalies.

Large-scale patterns in Rayleigh-Benard convection

International Nuclear Information System (INIS)

Hardenberg, J. von; Parodi, A.; Passoni, G.; Provenzale, A.; Spiegel, E.A.

2008-01-01

Rayleigh-Benard convection at large Rayleigh number is characterized by the presence of intense, vertically moving plumes. Both laboratory and numerical experiments reveal that the rising and descending plumes aggregate into separate clusters so as to produce large-scale updrafts and downdrafts. The horizontal scales of the aggregates reported so far have been comparable to the horizontal extent of the containers, but it has not been clear whether that represents a limitation imposed by domain size. In this work, we present numerical simulations of convection at sufficiently large aspect ratio to ascertain whether there is an intrinsic saturation scale for the clustering process when that ratio is large enough. From a series of simulations of Rayleigh-Benard convection with Rayleigh numbers between 10 5 and 10 8 and with aspect ratios up to 12π, we conclude that the clustering process has a finite horizontal saturation scale with at most a weak dependence on Rayleigh number in the range studied

Large scale Brownian dynamics of confined suspensions of rigid particles

Science.gov (United States)

Sprinkle, Brennan; Balboa Usabiaga, Florencio; Patankar, Neelesh A.; Donev, Aleksandar

2017-12-01

We introduce methods for large-scale Brownian Dynamics (BD) simulation of many rigid particles of arbitrary shape suspended in a fluctuating fluid. Our method adds Brownian motion to the rigid multiblob method [F. Balboa Usabiaga et al., Commun. Appl. Math. Comput. Sci. 11(2), 217-296 (2016)] at a cost comparable to the cost of deterministic simulations. We demonstrate that we can efficiently generate deterministic and random displacements for many particles using preconditioned Krylov iterative methods, if kernel methods to efficiently compute the action of the Rotne-Prager-Yamakawa (RPY) mobility matrix and its "square" root are available for the given boundary conditions. These kernel operations can be computed with near linear scaling for periodic domains using the positively split Ewald method. Here we study particles partially confined by gravity above a no-slip bottom wall using a graphical processing unit implementation of the mobility matrix-vector product, combined with a preconditioned Lanczos iteration for generating Brownian displacements. We address a major challenge in large-scale BD simulations, capturing the stochastic drift term that arises because of the configuration-dependent mobility. Unlike the widely used Fixman midpoint scheme, our methods utilize random finite differences and do not require the solution of resistance problems or the computation of the action of the inverse square root of the RPY mobility matrix. We construct two temporal schemes which are viable for large-scale simulations, an Euler-Maruyama traction scheme and a trapezoidal slip scheme, which minimize the number of mobility problems to be solved per time step while capturing the required stochastic drift terms. We validate and compare these schemes numerically by modeling suspensions of boomerang-shaped particles sedimented near a bottom wall. Using the trapezoidal scheme, we investigate the steady-state active motion in dense suspensions of confined microrollers, whose

Solving very large scattering problems using a parallel PWTD-enhanced surface integral equation solver

KAUST Repository

Liu, Yang

2013-07-01

The computational complexity and memory requirements of multilevel plane wave time domain (PWTD)-accelerated marching-on-in-time (MOT)-based surface integral equation (SIE) solvers scale as O(NtNs(log 2)Ns) and O(Ns 1.5); here N t and Ns denote numbers of temporal and spatial basis functions discretizing the current [Shanker et al., IEEE Trans. Antennas Propag., 51, 628-641, 2003]. In the past, serial versions of these solvers have been successfully applied to the analysis of scattering from perfect electrically conducting as well as homogeneous penetrable targets involving up to Ns ≈ 0.5 × 106 and Nt ≈ 10 3. To solve larger problems, parallel PWTD-enhanced MOT solvers are called for. Even though a simple parallelization strategy was demonstrated in the context of electromagnetic compatibility analysis [M. Lu et al., in Proc. IEEE Int. Symp. AP-S, 4, 4212-4215, 2004], by and large, progress in this area has been slow. The lack of progress can be attributed wholesale to difficulties associated with the construction of a scalable PWTD kernel. © 2013 IEEE.

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

Science.gov (United States)

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

2017-12-01

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

Characterizing Temperature Variability and Associated Large Scale Meteorological Patterns Across South America

Science.gov (United States)

Detzer, J.; Loikith, P. C.; Mechoso, C. R.; Barkhordarian, A.; Lee, H.

2017-12-01

South America's climate varies considerably owing to its large geographic range and diverse topographical features. Spanning the tropics to the mid-latitudes and from high peaks to tropical rainforest, the continent experiences an array of climate and weather patterns. Due to this considerable spatial extent, assessing temperature variability at the continent scale is particularly challenging. It is well documented in the literature that temperatures have been increasing across portions of South America in recent decades, and while there have been many studies that have focused on precipitation variability and change, temperature has received less scientific attention. Therefore, a more thorough understanding of the drivers of temperature variability is critical for interpreting future change. First, k-means cluster analysis is used to identify four primary modes of temperature variability across the continent, stratified by season. Next, composites of large scale meteorological patterns (LSMPs) are calculated for months assigned to each cluster. Initial results suggest that LSMPs, defined using meteorological variables such as sea level pressure (SLP), geopotential height, and wind, are able to identify synoptic scale mechanisms important for driving temperature variability at the monthly scale. Some LSMPs indicate a relationship with known recurrent modes of climate variability. For example, composites of geopotential height suggest that the Southern Annular Mode is an important, but not necessarily dominant, component of temperature variability over southern South America. This work will be extended to assess the drivers of temperature extremes across South America.

Manufacturing test of large scale hollow capsule and long length cladding in the large scale oxide dispersion strengthened (ODS) martensitic steel

International Nuclear Information System (INIS)

Narita, Takeshi; Ukai, Shigeharu; Kaito, Takeji; Ohtsuka, Satoshi; Fujiwara, Masayuki

2004-04-01

Mass production capability of oxide dispersion strengthened (ODS) martensitic steel cladding (9Cr) has being evaluated in the Phase II of the Feasibility Studies on Commercialized Fast Reactor Cycle System. The cost for manufacturing mother tube (raw materials powder production, mechanical alloying (MA) by ball mill, canning, hot extrusion, and machining) is a dominant factor in the total cost for manufacturing ODS ferritic steel cladding. In this study, the large-sale 9Cr-ODS martensitic steel mother tube which is made with a large-scale hollow capsule, and long length claddings were manufactured, and the applicability of these processes was evaluated. Following results were obtained in this study. (1) Manufacturing the large scale mother tube in the dimension of 32 mm OD, 21 mm ID, and 2 m length has been successfully carried out using large scale hollow capsule. This mother tube has a high degree of accuracy in size. (2) The chemical composition and the micro structure of the manufactured mother tube are similar to the existing mother tube manufactured by a small scale can. And the remarkable difference between the bottom and top sides in the manufactured mother tube has not been observed. (3) The long length cladding has been successfully manufactured from the large scale mother tube which was made using a large scale hollow capsule. (4) For reducing the manufacturing cost of the ODS steel claddings, manufacturing process of the mother tubes using a large scale hollow capsules is promising. (author)

Amplification of large-scale magnetic field in nonhelical magnetohydrodynamics

KAUST Repository

Kumar, Rohit

2017-08-11

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.

Large scale analysis of signal reachability.

Science.gov (United States)

Todor, Andrei; Gabr, Haitham; Dobra, Alin; Kahveci, Tamer

2014-06-15

Major disorders, such as leukemia, have been shown to alter the transcription of genes. Understanding how gene regulation is affected by such aberrations is of utmost importance. One promising strategy toward this objective is to compute whether signals can reach to the transcription factors through the transcription regulatory network (TRN). Due to the uncertainty of the regulatory interactions, this is a #P-complete problem and thus solving it for very large TRNs remains to be a challenge. We develop a novel and scalable method to compute the probability that a signal originating at any given set of source genes can arrive at any given set of target genes (i.e., transcription factors) when the topology of the underlying signaling network is uncertain. Our method tackles this problem for large networks while providing a provably accurate result. Our method follows a divide-and-conquer strategy. We break down the given network into a sequence of non-overlapping subnetworks such that reachability can be computed autonomously and sequentially on each subnetwork. We represent each interaction using a small polynomial. The product of these polynomials express different scenarios when a signal can or cannot reach to target genes from the source genes. We introduce polynomial collapsing operators for each subnetwork. These operators reduce the size of the resulting polynomial and thus the computational complexity dramatically. We show that our method scales to entire human regulatory networks in only seconds, while the existing methods fail beyond a few tens of genes and interactions. We demonstrate that our method can successfully characterize key reachability characteristics of the entire transcriptions regulatory networks of patients affected by eight different subtypes of leukemia, as well as those from healthy control samples. All the datasets and code used in this article are available at bioinformatics.cise.ufl.edu/PReach/scalable.htm. © The Author 2014

Re-thinking china's densified biomass fuel policies: Large or small scale?

International Nuclear Information System (INIS)

Shan, Ming; Li, Dingkai; Jiang, Yi; Yang, Xudong

2016-01-01

Current policies and strategies related to the utilization of densified biomass fuel (DBF) in China are mainly focused on medium- or large-scale manufacturing modes, which cannot provide feasible solutions to solve the household energy problems in China's rural areas. To simplify commercial processes related to the collection of DBF feedstock and the production and utilization of fuel, a novel village-scale DBF approach is proposed. Pilot demonstration projects have shown the feasibility and flexibility of this new approach in realizing sustainable development in rural China. Effective utilization of DBF in rural China will lead to gains for global, regional, and local energy savings, environmental protection, sustainable development, and related social benefits. It could also benefit other developing countries for better utilization of biomass as a viable household energy source. This proposal therefore delivers the possibility of reciprocal gains, and as such deserves the attention of policy makers and various stakeholders. - Highlights: •A field survey of Chinese densified biomass fuel (DBF) development is conducted. •The current situation and problems related to China's DBF industry are analyzed. •A novel and viable village-scale DBF utilization mode is proposed. •Further actions are suggested to boost the utilization of DBF in rural China.

Dynamic state estimation techniques for large-scale electric power systems

International Nuclear Information System (INIS)

Rousseaux, P.; Pavella, M.

1991-01-01

This paper presents the use of dynamic type state estimators for energy management in electric power systems. Various dynamic type estimators have been developed, but have never been implemented. This is primarily because of dimensionality problems posed by the conjunction of an extended Kalman filter with a large scale power system. This paper precisely focuses on how to circumvent the high dimensionality, especially prohibitive in the filtering step, by using a decomposition-aggregation hierarchical scheme; to appropriately model the power system dynamics, the authors introduce new state variables in the prediction step and rely on a load forecasting method. The combination of these two techniques succeeds in solving the overall dynamic state estimation problem not only in a tractable and realistic way, but also in compliance with real-time computational requirements. Further improvements are also suggested, bound to the specifics of the high voltage electric transmission systems

FFTLasso: Large-Scale LASSO in the Fourier Domain

KAUST Repository

Bibi, Adel Aamer

2017-11-09

In this paper, we revisit the LASSO sparse representation problem, which has been studied and used in a variety of different areas, ranging from signal processing and information theory to computer vision and machine learning. In the vision community, it found its way into many important applications, including face recognition, tracking, super resolution, image denoising, to name a few. Despite advances in efficient sparse algorithms, solving large-scale LASSO problems remains a challenge. To circumvent this difficulty, people tend to downsample and subsample the problem (e.g. via dimensionality reduction) to maintain a manageable sized LASSO, which usually comes at the cost of losing solution accuracy. This paper proposes a novel circulant reformulation of the LASSO that lifts the problem to a higher dimension, where ADMM can be efficiently applied to its dual form. Because of this lifting, all optimization variables are updated using only basic element-wise operations, the most computationally expensive of which is a 1D FFT. In this way, there is no need for a linear system solver nor matrix-vector multiplication. Since all operations in our FFTLasso method are element-wise, the subproblems are completely independent and can be trivially parallelized (e.g. on a GPU). The attractive computational properties of FFTLasso are verified by extensive experiments on synthetic and real data and on the face recognition task. They demonstrate that FFTLasso scales much more effectively than a state-of-the-art solver.

FFTLasso: Large-Scale LASSO in the Fourier Domain

KAUST Repository

Bibi, Adel Aamer; Itani, Hani; Ghanem, Bernard

2017-01-01

In this paper, we revisit the LASSO sparse representation problem, which has been studied and used in a variety of different areas, ranging from signal processing and information theory to computer vision and machine learning. In the vision community, it found its way into many important applications, including face recognition, tracking, super resolution, image denoising, to name a few. Despite advances in efficient sparse algorithms, solving large-scale LASSO problems remains a challenge. To circumvent this difficulty, people tend to downsample and subsample the problem (e.g. via dimensionality reduction) to maintain a manageable sized LASSO, which usually comes at the cost of losing solution accuracy. This paper proposes a novel circulant reformulation of the LASSO that lifts the problem to a higher dimension, where ADMM can be efficiently applied to its dual form. Because of this lifting, all optimization variables are updated using only basic element-wise operations, the most computationally expensive of which is a 1D FFT. In this way, there is no need for a linear system solver nor matrix-vector multiplication. Since all operations in our FFTLasso method are element-wise, the subproblems are completely independent and can be trivially parallelized (e.g. on a GPU). The attractive computational properties of FFTLasso are verified by extensive experiments on synthetic and real data and on the face recognition task. They demonstrate that FFTLasso scales much more effectively than a state-of-the-art solver.

Superconducting materials for large scale applications

International Nuclear Information System (INIS)

Dew-Hughes, D.

1975-01-01

Applications of superconductors capable of carrying large current densities in large-scale electrical devices are examined. Discussions are included on critical current density, superconducting materials available, and future prospects for improved superconducting materials. (JRD)

Large-scale influences in near-wall turbulence.

Science.gov (United States)

Hutchins, Nicholas; Marusic, Ivan

2007-03-15

Hot-wire data acquired in a high Reynolds number facility are used to illustrate the need for adequate scale separation when considering the coherent structure in wall-bounded turbulence. It is found that a large-scale motion in the log region becomes increasingly comparable in energy to the near-wall cycle as the Reynolds number increases. Through decomposition of fluctuating velocity signals, it is shown that this large-scale motion has a distinct modulating influence on the small-scale energy (akin to amplitude modulation). Reassessment of DNS data, in light of these results, shows similar trends, with the rate and intensity of production due to the near-wall cycle subject to a modulating influence from the largest-scale motions.

Sufficient Descent Conjugate Gradient Methods for Solving Convex Constrained Nonlinear Monotone Equations

Directory of Open Access Journals (Sweden)

San-Yang Liu

2014-01-01

Full Text Available Two unified frameworks of some sufficient descent conjugate gradient methods are considered. Combined with the hyperplane projection method of Solodov and Svaiter, they are extended to solve convex constrained nonlinear monotone equations. Their global convergence is proven under some mild conditions. Numerical results illustrate that these methods are efficient and can be applied to solve large-scale nonsmooth equations.

Linking the Scales of Scientific inquiry and Watershed Management: A Focus on Green Infrastructure

Science.gov (United States)

Golden, H. E.; Hoghooghi, N.

2017-12-01

Urbanization modifies the hydrologic cycle, resulting in potentially deleterious downstream water quality and quantity effects. However, the cumulative interacting effects of water storage, transport, and biogeochemical processes occurring within other land cover and use types of the same watershed can render management explicitly targeted to limit the negative outcomes from urbanization ineffective. For example, evidence indicates that green infrastructure, or low impact development (LID), practices can attenuate the adverse water quality and quantity effects of urbanizing systems. However, the research providing this evidence has been conducted at local scales (e.g., plots, small homogeneous urban catchments) that isolate the measurable effects of such approaches. Hence, a distinct disconnect exists between the scale of scientific inquiry and the scale of management and decision-making practices. Here we explore the oft-discussed yet rarely directly addressed scientific and management conundrum: How do we scale our well-documented scientific knowledge of the water quantity and quality responses to LID practices measured and modeled at local scales to that of "actual" management scales? We begin by focusing on LID practices in mixed land cover watersheds. We present key concepts that have emerged from LID research at the local scale, considerations for scaling this research to watersheds, recent advances and findings in scaling the effects of LID practices on water quality and quantity at watershed scales, and the use of combined novel measurements and models for these scaling efforts. We underscore these concepts with a case study that evaluates the effects of three LID practices using simulation modeling across a mixed land cover watershed. This synthesis and case study highlight that scientists are making progress toward successfully tailoring fundamental research questions with decision-making goals in mind, yet we still have a long road ahead.

Optimizing Prediction Using Bayesian Model Averaging: Examples Using Large-Scale Educational Assessments.

Science.gov (United States)

Kaplan, David; Lee, Chansoon

2018-01-01

This article provides a review of Bayesian model averaging as a means of optimizing the predictive performance of common statistical models applied to large-scale educational assessments. The Bayesian framework recognizes that in addition to parameter uncertainty, there is uncertainty in the choice of models themselves. A Bayesian approach to addressing the problem of model uncertainty is the method of Bayesian model averaging. Bayesian model averaging searches the space of possible models for a set of submodels that satisfy certain scientific principles and then averages the coefficients across these submodels weighted by each model's posterior model probability (PMP). Using the weighted coefficients for prediction has been shown to yield optimal predictive performance according to certain scoring rules. We demonstrate the utility of Bayesian model averaging for prediction in education research with three examples: Bayesian regression analysis, Bayesian logistic regression, and a recently developed approach for Bayesian structural equation modeling. In each case, the model-averaged estimates are shown to yield better prediction of the outcome of interest than any submodel based on predictive coverage and the log-score rule. Implications for the design of large-scale assessments when the goal is optimal prediction in a policy context are discussed.

PKI security in large-scale healthcare networks.

Science.gov (United States)

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.

Nanomedicine: Problem Solving to Treat Cancer

Science.gov (United States)

Hemling, Melissa A.; Sammel, Lauren M.; Zenner, Greta; Payne, Amy C.; Crone, Wendy C.

2006-01-01

Many traditional classroom science and technology activities often ask students to complete prepackaged labs that ensure that everyone arrives at the same "scientifically accurate" solution or theory, which ignores the important problem-solving and creative aspects of scientific research and technological design. Students rarely have the…

A new proposed approach for future large-scale de-carbonization coal-fired power plants

International Nuclear Information System (INIS)

Xu, Gang; Liang, Feifei; Wu, Ying; Yang, Yongping; Zhang, Kai; Liu, Wenyi

2015-01-01

The post-combustion CO 2 capture technology provides a feasible and promising method for large-scale CO 2 capture in coal-fired power plants. However, the large-scale CO 2 capture in conventionally designed coal-fired power plants is confronted with various problems, such as the selection of the steam extraction point and steam parameter mismatch. To resolve these problems, an improved design idea for the future coal-fired power plant with large-scale de-carbonization is proposed. A main characteristic of the proposed design is the adoption of a back-pressure steam turbine, which extracts the suitable steam for CO 2 capture and ensures the stability of the integrated system. A new let-down steam turbine generator is introduced to retrieve the surplus energy from the exhaust steam of the back-pressure steam turbine when CO 2 capture is cut off. Results show that the net plant efficiency of the improved design is 2.56% points higher than that of the conventional one when CO 2 capture ratio reaches 80%. Meanwhile, the net plant efficiency of the improved design maintains the same level to that of the conventional design when CO 2 capture is cut off. Finally, the match between the extracted steam and the heat demand of the reboiler is significantly increased, which solves the steam parameter mismatch problem. The techno-economic analysis indicates that the proposed design is a cost-effective approach for the large-scale CO 2 capture in coal-fired power plants. - Highlights: • Problems caused by CO 2 capture in the power plant are deeply analyzed. • An improved design idea for coal-fired power plants with CO 2 capture is proposed. • Thermodynamic, exergy and techno-economic analyses are quantitatively conducted. • Energy-saving effects are found in the proposed coal-fired power plant design idea

Emerging large-scale solar heating applications

International Nuclear Information System (INIS)

Wong, W.P.; McClung, J.L.

2009-01-01

Currently the market for solar heating applications in Canada is dominated by outdoor swimming pool heating, make-up air pre-heating and domestic water heating in homes, commercial and institutional buildings. All of these involve relatively small systems, except for a few air pre-heating systems on very large buildings. Together these applications make up well over 90% of the solar thermal collectors installed in Canada during 2007. These three applications, along with the recent re-emergence of large-scale concentrated solar thermal for generating electricity, also dominate the world markets. This paper examines some emerging markets for large scale solar heating applications, with a focus on the Canadian climate and market. (author)

Emerging large-scale solar heating applications

Energy Technology Data Exchange (ETDEWEB)

Wong, W.P.; McClung, J.L. [Science Applications International Corporation (SAIC Canada), Ottawa, Ontario (Canada)

2009-07-01

Currently the market for solar heating applications in Canada is dominated by outdoor swimming pool heating, make-up air pre-heating and domestic water heating in homes, commercial and institutional buildings. All of these involve relatively small systems, except for a few air pre-heating systems on very large buildings. Together these applications make up well over 90% of the solar thermal collectors installed in Canada during 2007. These three applications, along with the recent re-emergence of large-scale concentrated solar thermal for generating electricity, also dominate the world markets. This paper examines some emerging markets for large scale solar heating applications, with a focus on the Canadian climate and market. (author)

Dispositional Insight Scale: Development and Validation of a Tool That Measures Propensity toward Insight in Problem Solving

Science.gov (United States)

Ovington, Linda A.; Saliba, Anthony J.; Goldring, Jeremy

2016-01-01

This article reports the development of a brief self-report measure of dispositional insight problem solving, the Dispositional Insight Scale (DIS). From a representative Australian database, 1,069 adults (536 women and 533 men) completed an online questionnaire. An exploratory and confirmatory factor analysis revealed a 5-item scale, with all…

Solving the equality generalized traveling salesman problem using the Lin–Kernighan–Helsgaun Algorithm

DEFF Research Database (Denmark)

Helsgaun, Keld

2015-01-01

instances in a well-known library of benchmark instances, GTSPLIB, could be solved to optimality in a reasonable time. In addition, it was possible to solve a series of new very-large-scale instances with up to 17,180 clusters and 85,900 vertices. Optima for these instances are not known...... be downloaded in source code....

Large-Scale Studies on the Transferability of General Problem-Solving Skills and the Pedagogic Potential of Physics

Science.gov (United States)

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…

Web tools for large-scale 3D biological images and atlases

Directory of Open Access Journals (Sweden)

Husz Zsolt L

2012-06-01

Full Text Available Abstract Background Large-scale volumetric biomedical image data of three or more dimensions are a significant challenge for distributed browsing and visualisation. Many images now exceed 10GB which for most users is too large to handle in terms of computer RAM and network bandwidth. This is aggravated when users need to access tens or hundreds of such images from an archive. Here we solve the problem for 2D section views through archive data delivering compressed tiled images enabling users to browse through very-large volume data in the context of a standard web-browser. The system provides an interactive visualisation for grey-level and colour 3D images including multiple image layers and spatial-data overlay. Results The standard Internet Imaging Protocol (IIP has been extended to enable arbitrary 2D sectioning of 3D data as well a multi-layered images and indexed overlays. The extended protocol is termed IIP3D and we have implemented a matching server to deliver the protocol and a series of Ajax/Javascript client codes that will run in an Internet browser. We have tested the server software on a low-cost linux-based server for image volumes up to 135GB and 64 simultaneous users. The section views are delivered with response times independent of scale and orientation. The exemplar client provided multi-layer image views with user-controlled colour-filtering and overlays. Conclusions Interactive browsing of arbitrary sections through large biomedical-image volumes is made possible by use of an extended internet protocol and efficient server-based image tiling. The tools open the possibility of enabling fast access to large image archives without the requirement of whole image download and client computers with very large memory configurations. The system was demonstrated using a range of medical and biomedical image data extending up to 135GB for a single image volume.

Large-scale regions of antimatter

International Nuclear Information System (INIS)

Grobov, A. V.; Rubin, S. G.

2015-01-01

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

Large-scale regions of antimatter

Energy Technology Data Exchange (ETDEWEB)

Grobov, A. V., E-mail: alexey.grobov@gmail.com; Rubin, S. G., E-mail: sgrubin@mephi.ru [National Research Nuclear University MEPhI (Russian Federation)

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 TeraShake Computational Platform for Large-Scale Earthquake Simulations

Science.gov (United States)

Cui, Yifeng; Olsen, Kim; Chourasia, Amit; Moore, Reagan; Maechling, Philip; Jordan, Thomas

Geoscientific and computer science researchers with the Southern California Earthquake Center (SCEC) are conducting a large-scale, physics-based, computationally demanding earthquake system science research program with the goal of developing predictive models of earthquake processes. The computational demands of this program continue to increase rapidly as these researchers seek to perform physics-based numerical simulations of earthquake processes for larger meet the needs of this research program, a multiple-institution team coordinated by SCEC has integrated several scientific codes into a numerical modeling-based research tool we call the TeraShake computational platform (TSCP). A central component in the TSCP is a highly scalable earthquake wave propagation simulation program called the TeraShake anelastic wave propagation (TS-AWP) code. In this chapter, we describe how we extended an existing, stand-alone, wellvalidated, finite-difference, anelastic wave propagation modeling code into the highly scalable and widely used TS-AWP and then integrated this code into the TeraShake computational platform that provides end-to-end (initialization to analysis) research capabilities. We also describe the techniques used to enhance the TS-AWP parallel performance on TeraGrid supercomputers, as well as the TeraShake simulations phases including input preparation, run time, data archive management, and visualization. As a result of our efforts to improve its parallel efficiency, the TS-AWP has now shown highly efficient strong scaling on over 40K processors on IBM’s BlueGene/L Watson computer. In addition, the TSCP has developed into a computational system that is useful to many members of the SCEC community for performing large-scale earthquake simulations.

Large-Scale Analysis of Art Proportions

DEFF Research Database (Denmark)

Jensen, Karl Kristoffer

2014-01-01

While literature often tries to impute mathematical constants into art, this large-scale study (11 databases of paintings and photos, around 200.000 items) shows a different truth. The analysis, consisting of the width/height proportions, shows a value of rarely if ever one (square) and with majo......While literature often tries to impute mathematical constants into art, this large-scale study (11 databases of paintings and photos, around 200.000 items) shows a different truth. The analysis, consisting of the width/height proportions, shows a value of rarely if ever one (square...

The Expanded Large Scale Gap Test

Science.gov (United States)

1987-03-01

NSWC TR 86-32 DTIC THE EXPANDED LARGE SCALE GAP TEST BY T. P. LIDDIARD D. PRICE RESEARCH AND TECHNOLOGY DEPARTMENT ’ ~MARCH 1987 Ap~proved for public...arises, to reduce the spread in the LSGT 50% gap value.) The worst charges, such as those with the highest or lowest densities, the largest re-pressed...Arlington, VA 22217 PE 62314N INS3A 1 RJ14E31 7R4TBK 11 TITLE (Include Security CIlmsilficatiorn The Expanded Large Scale Gap Test . 12. PEIRSONAL AUTHOR() T

Scientific Services on the Cloud

Science.gov (United States)

Chapman, David; Joshi, Karuna P.; Yesha, Yelena; Halem, Milt; Yesha, Yaacov; Nguyen, Phuong

Scientific Computing was one of the first every applications for parallel and distributed computation. To this date, scientific applications remain some of the most compute intensive, and have inspired creation of petaflop compute infrastructure such as the Oak Ridge Jaguar and Los Alamos RoadRunner. Large dedicated hardware infrastructure has become both a blessing and a curse to the scientific community. Scientists are interested in cloud computing for much the same reason as businesses and other professionals. The hardware is provided, maintained, and administrated by a third party. Software abstraction and virtualization provide reliability, and fault tolerance. Graduated fees allow for multi-scale prototyping and execution. Cloud computing resources are only a few clicks away, and by far the easiest high performance distributed platform to gain access to. There may still be dedicated infrastructure for ultra-scale science, but the cloud can easily play a major part of the scientific computing initiative.

Large Scale Computing and Storage Requirements for Nuclear Physics Research

Energy Technology Data Exchange (ETDEWEB)

Gerber, Richard A.; Wasserman, Harvey J.

2012-03-02

IThe National Energy Research Scientific Computing Center (NERSC) is the primary computing center for the DOE Office of Science, serving approximately 4,000 users and hosting some 550 projects that involve nearly 700 codes for a wide variety of scientific disciplines. In addition to large-scale computing resources NERSC provides critical staff support and expertise to help scientists make the most efficient use of these resources to advance the scientific mission of the Office of Science. In May 2011, NERSC, DOE’s Office of Advanced Scientific Computing Research (ASCR) and DOE’s Office of Nuclear Physics (NP) held a workshop to characterize HPC requirements for NP research over the next three to five years. The effort is part of NERSC’s continuing involvement in anticipating future user needs and deploying necessary resources to meet these demands. The workshop revealed several key requirements, in addition to achieving its goal of characterizing NP computing. The key requirements include: 1. Larger allocations of computational resources at NERSC; 2. Visualization and analytics support; and 3. Support at NERSC for the unique needs of experimental nuclear physicists. This report expands upon these key points and adds others. The results are based upon representative samples, called “case studies,” of the needs of science teams within NP. The case studies were prepared by NP workshop participants and contain a summary of science goals, methods of solution, current and future computing requirements, and special software and support needs. Participants were also asked to describe their strategy for computing in the highly parallel, “multi-core” environment that is expected to dominate HPC architectures over the next few years. The report also includes a section with NERSC responses to the workshop findings. NERSC has many initiatives already underway that address key workshop findings and all of the action items are aligned with NERSC strategic plans.

Large-Scale Covariability Between Aerosol and Precipitation Over the 7-SEAS Region: Observations and Simulations

Science.gov (United States)

Huang, Jingfeng; Hsu, N. Christina; Tsay, Si-Chee; Zhang, Chidong; Jeong, Myeong Jae; Gautam, Ritesh; Bettenhausen, Corey; Sayer, Andrew M.; Hansell, Richard A.; Liu, Xiaohong;

Large scale and big data processing and management

CERN Document Server

Sakr, Sherif

2014-01-01

Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments.The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-bas

Large scale cluster computing workshop

International Nuclear Information System (INIS)

Dane Skow; Alan Silverman

2002-01-01

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 Agriculture and Outgrower Schemes in Ethiopia

DEFF Research Database (Denmark)

Wendimu, Mengistu Assefa

, the impact of large-scale agriculture and outgrower schemes on productivity, household welfare and wages in developing countries is highly contentious. Chapter 1 of this thesis provides an introduction to the study, while also reviewing the key debate in the contemporary land ‘grabbing’ and historical large...... sugarcane outgrower scheme on household income and asset stocks. Chapter 5 examines the wages and working conditions in ‘formal’ large-scale and ‘informal’ small-scale irrigated agriculture. The results in Chapter 2 show that moisture stress, the use of untested planting materials, and conflict over land...... commands a higher wage than ‘formal’ large-scale agriculture, while rather different wage determination mechanisms exist in the two sectors. Human capital characteristics (education and experience) partly explain the differences in wages within the formal sector, but play no significant role...

Economically viable large-scale hydrogen liquefaction

Science.gov (United States)

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.

Three-Dimensional Thermo Fluid Analysis of Large Scale Electric Motor

Directory of Open Access Journals (Sweden)

Debasish Biswas

2000-01-01

Full Text Available In the present work, the flow and temperature fields in large scale rotating electric motor are studied by solving the Navier–Stokes equations along with the temperature equation on the basis of finite difference method. All the equations are written in terms of relative velocity with respect to the rotating frame of reference. Generalized coordinate system is used so that sufficient grid resolution could be achieved in the body surface boundary layer region. Differential terms with respect to time are approximated by forward differences, diffusion terms are approximated by the implicit Euler form, convection terms in the Navier–Stokes equations are approximated by the third order upwind difference scheme. The results of calculation led to a good understanding of the flow behavior, namely, the rotating cavity flow in between the supporting bar of the motor, the flow stagnation and region of temperature rise due to flow stagnation, etc. Also the measured average temperature of the motor coil wall is predicted quite satisfactorily.

Large Neighborhood Search

DEFF Research Database (Denmark)

Pisinger, David; Røpke, Stefan

2010-01-01

Heuristics based on large neighborhood search have recently shown outstanding results in solving various transportation and scheduling problems. Large neighborhood search methods explore a complex neighborhood by use of heuristics. Using large neighborhoods makes it possible to find better...... candidate solutions in each iteration and hence traverse a more promising search path. Starting from the large neighborhood search method,we give an overview of very large scale neighborhood search methods and discuss recent variants and extensions like variable depth search and adaptive large neighborhood...

Large scale chromatographic separations using continuous displacement chromatography (CDC)

International Nuclear Information System (INIS)

Taniguchi, V.T.; Doty, A.W.; Byers, C.H.

1988-01-01

A process for large scale chromatographic separations using a continuous chromatography technique is described. The process combines the advantages of large scale batch fixed column displacement chromatography with conventional analytical or elution continuous annular chromatography (CAC) to enable large scale displacement chromatography to be performed on a continuous basis (CDC). Such large scale, continuous displacement chromatography separations have not been reported in the literature. The process is demonstrated with the ion exchange separation of a binary lanthanide (Nd/Pr) mixture. The process is, however, applicable to any displacement chromatography separation that can be performed using conventional batch, fixed column chromatography

Remote collaboration system based on large scale simulation

International Nuclear Information System (INIS)

Kishimoto, Yasuaki; Sugahara, Akihiro; Li, J.Q.

2008-01-01

Large scale simulation using super-computer, which generally requires long CPU time and produces large amount of data, has been extensively studied as a third pillar in various advanced science fields in parallel to theory and experiment. Such a simulation is expected to lead new scientific discoveries through elucidation of various complex phenomena, which are hardly identified only by conventional theoretical and experimental approaches. In order to assist such large simulation studies for which many collaborators working at geographically different places participate and contribute, we have developed a unique remote collaboration system, referred to as SIMON (simulation monitoring system), which is based on client-server system control introducing an idea of up-date processing, contrary to that of widely used post-processing. As a key ingredient, we have developed a trigger method, which transmits various requests for the up-date processing from the simulation (client) running on a super-computer to a workstation (server). Namely, the simulation running on a super-computer actively controls the timing of up-date processing. The server that has received the requests from the ongoing simulation such as data transfer, data analyses, and visualizations, etc. starts operations according to the requests during the simulation. The server makes the latest results available to web browsers, so that the collaborators can monitor the results at any place and time in the world. By applying the system to a specific simulation project of laser-matter interaction, we have confirmed that the system works well and plays an important role as a collaboration platform on which many collaborators work with one another

Large Scale Processes and Extreme Floods in Brazil

Science.gov (United States)

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).

Computing in Large-Scale Dynamic Systems

NARCIS (Netherlands)

Pruteanu, A.S.

2013-01-01

Software applications developed for large-scale systems have always been difficult to de- velop due to problems caused by the large number of computing devices involved. Above a certain network size (roughly one hundred), necessary services such as code updating, topol- ogy discovery and data

Integrating scientific knowledge into large-scale restoration programs: the CALFED Bay-Delta Program experience

Science.gov (United States)

Taylor, K.A.; Short, A.

2009-01-01

Integrating science into resource management activities is a goal of the CALFED Bay-Delta Program, a multi-agency effort to address water supply reliability, ecological condition, drinking water quality, and levees in the Sacramento-San Joaquin Delta of northern California. Under CALFED, many different strategies were used to integrate science, including interaction between the research and management communities, public dialogues about scientific work, and peer review. This paper explores ways science was (and was not) integrated into CALFED's management actions and decision systems through three narratives describing different patterns of scientific integration and application in CALFED. Though a collaborative process and certain organizational conditions may be necessary for developing new understandings of the system of interest, we find that those factors are not sufficient for translating that knowledge into management actions and decision systems. We suggest that the application of knowledge may be facilitated or hindered by (1) differences in the objectives, approaches, and cultures of scientists operating in the research community and those operating in the management community and (2) other factors external to the collaborative process and organization.

Fires in large scale ventilation systems

International Nuclear Information System (INIS)

Gregory, W.S.; Martin, R.A.; White, B.W.; Nichols, B.D.; Smith, P.R.; Leslie, I.H.; Fenton, D.L.; Gunaji, M.V.; Blythe, J.P.

1991-01-01

This paper summarizes the experience gained simulating fires in large scale ventilation systems patterned after ventilation systems found in nuclear fuel cycle facilities. The series of experiments discussed included: (1) combustion aerosol loading of 0.61x0.61 m HEPA filters with the combustion products of two organic fuels, polystyrene and polymethylemethacrylate; (2) gas dynamic and heat transport through a large scale ventilation system consisting of a 0.61x0.61 m duct 90 m in length, with dampers, HEPA filters, blowers, etc.; (3) gas dynamic and simultaneous transport of heat and solid particulate (consisting of glass beads with a mean aerodynamic diameter of 10μ) through the large scale ventilation system; and (4) the transport of heat and soot, generated by kerosene pool fires, through the large scale ventilation system. The FIRAC computer code, designed to predict fire-induced transients in nuclear fuel cycle facility ventilation systems, was used to predict the results of experiments (2) through (4). In general, the results of the predictions were satisfactory. The code predictions for the gas dynamics, heat transport, and particulate transport and deposition were within 10% of the experimentally measured values. However, the code was less successful in predicting the amount of soot generation from kerosene pool fires, probably due to the fire module of the code being a one-dimensional zone model. The experiments revealed a complicated three-dimensional combustion pattern within the fire room of the ventilation system. Further refinement of the fire module within FIRAC is needed. (orig.)

AlpArray - technical strategies for large-scale European co-operation in broadband seismology

Science.gov (United States)

Brisbourne, A.; Clinton, J.; Hetenyi, G.; Pequegnat, C.; Wilde-Piorko, M.; Villasenor, A.; Comelli, P.; AlpArray Working Group

2012-04-01

AlpArray is a new initiative to study the greater Alpine area with a large-scale broadband seismological network. The interested parties (currently 32 institutes in 12 countries) plan to combine their existing infrastructures into an all-out transnational effort that includes data acquisition, processing, imaging and interpretation. The experiment will encompass the greater Alpine area, from the Black Forest in the north to the Northern Apennines in the south and from the Pannonian Basin in the east to the French Massif Central in the west. We aim to cover this region with high-quality broadband seismometers by combining the ~400 existing permanent stations with an additional 400+ instruments from mobile pools. In this way, we plan to achieve homogeneous and high resolution coverage while also deploying densely spaced stations along swaths across key parts of the Alpine chain. These efforts on land will be combined with deployments of ocean bottom seismometers in the Mediterranean Sea. Significant progress has already been made in outlining the scientific goals and funding strategy. A brief overview of these aspects of the initiative will be presented here. However, we will concentrate on the technical aspects: How efficient large-scale integration of existing infrastructures can be achieved. Existing permanent station coverage within the greater Alpine area has been collated and assessed for data availability, allowing strategies to be developed for network densification to ensure a robust backbone network: An anticipated deployment strategy has been drawn up to optimise array coverage and data quality. The augmented backbone network will be supplemented by more densely spaced temporary arrays targeting more specific scientific questions. For these temporary arrays, a strategy document has been produced to outline standards for station installation, data acquisition, processing, archival and dissemination. All these operations are of course vital. However, data

Large-scale Complex IT Systems

OpenAIRE

Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

2011-01-01

This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that identifies the major challen...

Large-scale complex IT systems

OpenAIRE

Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

2012-01-01

12 pages, 2 figures This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that ident...

First Mile Challenges for Large-Scale IoT

KAUST Repository

Bader, Ahmed; Elsawy, Hesham; Gharbieh, Mohammad; Alouini, Mohamed-Slim; Adinoyi, Abdulkareem; Alshaalan, Furaih

2017-01-01

The Internet of Things is large-scale by nature. This is not only manifested by the large number of connected devices, but also by the sheer scale of spatial traffic intensity that must be accommodated, primarily in the uplink direction. To that end

Sensitivity technologies for large scale simulation

International Nuclear Information System (INIS)

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

On scaling of scientific knowledge production in U.S. metropolitan areas

NARCIS (Netherlands)

Nomaler, Önder; Frenken, Koen; Heimeriks, Gaston

2014-01-01

Using data on all scientific publications from the Scopus database, we find a superlinear scaling effect for U.S. metropolitan areas as indicated by the increase of per capita publication output with city size. We also find that the variance of residuals is much higher for mid-sized cities (100,000

Prospects for large scale electricity storage in Denmark

DEFF Research Database (Denmark)

Krog Ekman, Claus; Jensen, Søren Højgaard

2010-01-01

In a future power systems with additional wind power capacity there will be an increased need for large scale power management as well as reliable balancing and reserve capabilities. Different technologies for large scale electricity storage provide solutions to the different challenges arising w...

Adaptive Fuzzy Output-Constrained Fault-Tolerant Control of Nonlinear Stochastic Large-Scale Systems With Actuator Faults.

Science.gov (United States)

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.

The prospect of modern thermomechanics in structural integrity calculations of large-scale pressure vessels

Science.gov (United States)

Fekete, Tamás

2018-05-01

Structural integrity calculations play a crucial role in designing large-scale pressure vessels. Used in the electric power generation industry, these kinds of vessels undergo extensive safety analyses and certification procedures before deemed feasible for future long-term operation. The calculations are nowadays directed and supported by international standards and guides based on state-of-the-art results of applied research and technical development. However, their ability to predict a vessel's behavior under accidental circumstances after long-term operation is largely limited by the strong dependence of the analysis methodology on empirical models that are correlated to the behavior of structural materials and their changes during material aging. Recently a new scientific engineering paradigm, structural integrity has been developing that is essentially a synergistic collaboration between a number of scientific and engineering disciplines, modeling, experiments and numerics. Although the application of the structural integrity paradigm highly contributed to improving the accuracy of safety evaluations of large-scale pressure vessels, the predictive power of the analysis methodology has not yet improved significantly. This is due to the fact that already existing structural integrity calculation methodologies are based on the widespread and commonly accepted 'traditional' engineering thermal stress approach, which is essentially based on the weakly coupled model of thermomechanics and fracture mechanics. Recently, a research has been initiated in MTA EK with the aim to review and evaluate current methodologies and models applied in structural integrity calculations, including their scope of validity. The research intends to come to a better understanding of the physical problems that are inherently present in the pool of structural integrity problems of reactor pressure vessels, and to ultimately find a theoretical framework that could serve as a well

A multiple-scale power series method for solving nonlinear ordinary differential equations

Directory of Open Access Journals (Sweden)

Chein-Shan Liu

2016-02-01

Full Text Available The power series solution is a cheap and effective method to solve nonlinear problems, like the Duffing-van der Pol oscillator, the Volterra population model and the nonlinear boundary value problems. A novel power series method by considering the multiple scales $R_k$ in the power term $(t/R_k^k$ is developed, which are derived explicitly to reduce the ill-conditioned behavior in the data interpolation. In the method a huge value times a tiny value is avoided, such that we can decrease the numerical instability and which is the main reason to cause the failure of the conventional power series method. The multiple scales derived from an integral can be used in the power series expansion, which provide very accurate numerical solutions of the problems considered in this paper.

A Decentralized Multivariable Robust Adaptive Voltage and Speed Regulator for Large-Scale Power Systems

Science.gov (United States)

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.

Evolution of scaling emergence in large-scale spatial epidemic spreading.

Science.gov (United States)

Wang, Lin; Li, Xiang; Zhang, Yi-Qing; Zhang, Yan; Zhang, Kan

2011-01-01

Zipf's law and Heaps' law are two representatives of the scaling concepts, which play a significant role in the study of complexity science. The coexistence of the Zipf's law and the Heaps' law motivates different understandings on the dependence between these two scalings, which has still hardly been clarified. In this article, we observe an evolution process of the scalings: the Zipf's law and the Heaps' law are naturally shaped to coexist at the initial time, while the crossover comes with the emergence of their inconsistency at the larger time before reaching a stable state, where the Heaps' law still exists with the disappearance of strict Zipf's law. Such findings are illustrated with a scenario of large-scale spatial epidemic spreading, and the empirical results of pandemic disease support a universal analysis of the relation between the two laws regardless of the biological details of disease. Employing the United States domestic air transportation and demographic data to construct a metapopulation model for simulating the pandemic spread at the U.S. country level, we uncover that the broad heterogeneity of the infrastructure plays a key role in the evolution of scaling emergence. The analyses of large-scale spatial epidemic spreading help understand the temporal evolution of scalings, indicating the coexistence of the Zipf's law and the Heaps' law depends on the collective dynamics of epidemic processes, and the heterogeneity of epidemic spread indicates the significance of performing targeted containment strategies at the early time of a pandemic disease.

Large-Scale Structure and Hyperuniformity of Amorphous Ices

Science.gov (United States)

Martelli, Fausto; Torquato, Salvatore; Giovambattista, Nicolas; Car, Roberto

2017-09-01

We investigate the large-scale structure of amorphous ices and transitions between their different forms by quantifying their large-scale density fluctuations. Specifically, we simulate the isothermal compression of low-density amorphous ice (LDA) and hexagonal ice to produce high-density amorphous ice (HDA). Both HDA and LDA are nearly hyperuniform; i.e., they are characterized by an anomalous suppression of large-scale density fluctuations. By contrast, in correspondence with the nonequilibrium phase transitions to HDA, the presence of structural heterogeneities strongly suppresses the hyperuniformity and the system becomes hyposurficial (devoid of "surface-area fluctuations"). Our investigation challenges the largely accepted "frozen-liquid" picture, which views glasses as structurally arrested liquids. Beyond implications for water, our findings enrich our understanding of pressure-induced structural transformations in glasses.

Human-Assisted Machine Information Exploitation: a crowdsourced investigation of information-based problem solving

Science.gov (United States)

Kase, Sue E.; Vanni, Michelle; Caylor, Justine; Hoye, Jeff

2017-05-01

The Human-Assisted Machine Information Exploitation (HAMIE) investigation utilizes large-scale online data collection for developing models of information-based problem solving (IBPS) behavior in a simulated time-critical operational environment. These types of environments are characteristic of intelligence workflow processes conducted during human-geo-political unrest situations when the ability to make the best decision at the right time ensures strategic overmatch. The project takes a systems approach to Human Information Interaction (HII) by harnessing the expertise of crowds to model the interaction of the information consumer and the information required to solve a problem at different levels of system restrictiveness and decisional guidance. The design variables derived from Decision Support Systems (DSS) research represent the experimental conditions in this online single-player against-the-clock game where the player, acting in the role of an intelligence analyst, is tasked with a Commander's Critical Information Requirement (CCIR) in an information overload scenario. The player performs a sequence of three information processing tasks (annotation, relation identification, and link diagram formation) with the assistance of `HAMIE the robot' who offers varying levels of information understanding dependent on question complexity. We provide preliminary results from a pilot study conducted with Amazon Mechanical Turk (AMT) participants on the Volunteer Science scientific research platform.

Measuring health-related problem solving among African Americans with multiple chronic conditions: application of Rasch analysis.

Science.gov (United States)

Fitzpatrick, Stephanie L; Hill-Briggs, Felicia

2015-10-01

Identification of patients with poor chronic disease self-management skills can facilitate treatment planning, determine effectiveness of interventions, and reduce disease complications. This paper describes the use of a Rasch model, the Rating Scale Model, to examine psychometric properties of the 50-item Health Problem-Solving Scale (HPSS) among 320 African American patients with high risk for cardiovascular disease. Items on the positive/effective HPSS subscales targeted patients at low, moderate, and high levels of positive/effective problem solving, whereas items on the negative/ineffective problem solving subscales mostly targeted those at moderate or high levels of ineffective problem solving. Validity was examined by correlating factor scores on the measure with clinical and behavioral measures. Items on the HPSS show promise in the ability to assess health-related problem solving among high risk patients. However, further revisions of the scale are needed to increase its usability and validity with large, diverse patient populations in the future.

Study of Large-Scale Wave Structure and Development of Equatorial Plasma Bubbles Using the C/NOFS Satellite

Science.gov (United States)

2012-10-31

scientific journals. The papers are listed below in chronological order. Kelley, M.C., F.S. Rodrigues, J.J. Makela, R. Tsunoda, P.A. Roddy, D.E. Hunton...source region be located on the dip equator. To illustrate, Figure 6 presents a sequence of satellite OLR maps, which were taken over Peru on 19-20...to large-scale wave structure and equatorial spread F, presented at the International Symposium for Equatorial Aeronomy, Paracas, Peru , March 2012

MARVIN: Distributed reasoning over large-scale Semantic Web data

NARCIS (Netherlands)

Oren, E.; Kotoulas, S.; Anadiotis, G.; Siebes, R.M.; ten Teije, A.C.M.; van Harmelen, F.A.H.

2009-01-01

Many Semantic Web problems are difficult to solve through common divide-and-conquer strategies, since they are hard to partition. We present Marvin, a parallel and distributed platform for processing large amounts of RDF data, on a network of loosely coupled peers. We present our divide-conquer-swap

Interactive exploration of large-scale time-varying data using dynamic tracking graphs

KAUST Repository

Widanagamaachchi, W.

2012-10-01

Exploring and analyzing the temporal evolution of features in large-scale time-varying datasets is a common problem in many areas of science and engineering. One natural representation of such data is tracking graphs, i.e., constrained graph layouts that use one spatial dimension to indicate time and show the "tracks" of each feature as it evolves, merges or disappears. However, for practical data sets creating the corresponding optimal graph layouts that minimize the number of intersections can take hours to compute with existing techniques. Furthermore, the resulting graphs are often unmanageably large and complex even with an ideal layout. Finally, due to the cost of the layout, changing the feature definition, e.g. by changing an iso-value, or analyzing properly adjusted sub-graphs is infeasible. To address these challenges, this paper presents a new framework that couples hierarchical feature definitions with progressive graph layout algorithms to provide an interactive exploration of dynamically constructed tracking graphs. Our system enables users to change feature definitions on-the-fly and filter features using arbitrary attributes while providing an interactive view of the resulting tracking graphs. Furthermore, the graph display is integrated into a linked view system that provides a traditional 3D view of the current set of features and allows a cross-linked selection to enable a fully flexible spatio-temporal exploration of data. We demonstrate the utility of our approach with several large-scale scientific simulations from combustion science. © 2012 IEEE.

Assessing large-scale weekly cycles in meteorological variables: a review

Directory of Open Access Journals (Sweden)

A. Sanchez-Lorenzo

2012-07-01

Full Text Available Several studies have claimed to have found significant weekly cycles of meteorological variables appearing over large domains, which can hardly be related to urban effects exclusively. Nevertheless, there is still an ongoing scientific debate whether these large-scale weekly cycles exist or not, and some other studies fail to reproduce them with statistical significance. In addition to the lack of the positive proof for the existence of these cycles, their possible physical explanations have been controversially discussed during the last years. In this work we review the main results about this topic published during the recent two decades, including a summary of the existence or non-existence of significant weekly weather cycles across different regions of the world, mainly over the US, Europe and Asia. In addition, some shortcomings of common statistical methods for analyzing weekly cycles are listed. Finally, a brief summary of supposed causes of the weekly cycles, focusing on the aerosol-cloud-radiation interactions and their impact on meteorological variables as a result of the weekly cycles of anthropogenic activities, and possible directions for future research, is presented.

Double inflation: A possible resolution of the large-scale structure problem

International Nuclear Information System (INIS)

Turner, M.S.; Villumsen, J.V.; Vittorio, N.; Silk, J.; Juszkiewicz, R.

1986-11-01

A model is presented for the large-scale structure of the universe in which two successive inflationary phases resulted in large small-scale and small large-scale density fluctuations. This bimodal density fluctuation spectrum in an Ω = 1 universe dominated by hot dark matter leads to large-scale structure of the galaxy distribution that is consistent with recent observational results. In particular, large, nearly empty voids and significant large-scale peculiar velocity fields are produced over scales of ∼100 Mpc, while the small-scale structure over ≤ 10 Mpc resembles that in a low density universe, as observed. Detailed analytical calculations and numerical simulations are given of the spatial and velocity correlations. 38 refs., 6 figs

Large-scale fracture mechancis testing -- requirements and possibilities

International Nuclear Information System (INIS)

Brumovsky, M.

1993-01-01

Application of fracture mechanics to very important and/or complicated structures, like reactor pressure vessels, brings also some questions about the reliability and precision of such calculations. These problems become more pronounced in cases of elastic-plastic conditions of loading and/or in parts with non-homogeneous materials (base metal and austenitic cladding, property gradient changes through material thickness) or with non-homogeneous stress fields (nozzles, bolt threads, residual stresses etc.). For such special cases some verification by large-scale testing is necessary and valuable. This paper discusses problems connected with planning of such experiments with respect to their limitations, requirements to a good transfer of received results to an actual vessel. At the same time, an analysis of possibilities of small-scale model experiments is also shown, mostly in connection with application of results between standard, small-scale and large-scale experiments. Experience from 30 years of large-scale testing in SKODA is used as an example to support this analysis. 1 fig

Ethics of large-scale change

DEFF Research Database (Denmark)

Arler, Finn

2006-01-01

, which kind of attitude is appropriate when dealing with large-scale changes like these from an ethical point of view. Three kinds of approaches are discussed: Aldo Leopold's mountain thinking, the neoclassical economists' approach, and finally the so-called Concentric Circle Theories approach...

Solving large-scale PDE-constrained Bayesian inverse problems with Riemann manifold Hamiltonian Monte Carlo

Science.gov (United States)

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

Ultra-Scale Visualization: Research and Education

International Nuclear Information System (INIS)

Ma, K-L; Ross, Robert; Huang Jian; Humphreys, Greg; Max, Nelson; Moreland, Kenneth; Owens, John D; Shen, H-W

2007-01-01

Understanding the science behind large-scale simulations and high-throughput experiments requires extracting meaning from data sets of hundreds of terabytes or more. Visualization is the most intuitive means for scientists to understand data at this scale, and the most effective way to communicate their findings with others. Even though visualization technology has matured over the past twenty years, it is still limited by the extent and scale of the data that it can be applied to, and also by the functionalities that were mostly designed for single-user, single-variable, and single-space investigation. The Institute for Ultra-Scale Visualization (IUSV), funded by the DOE SciDAC-2 program, has the mission to advance visualization technologies to enable knowledge discovery and dissemination for peta-scale applications. By working with the SciDAC application projects, Centers for Enabling Technology, and other Institutes, IUSV aims to lead the research innovation that can create new visualization capabilities needed for gleaning insights from data at petascale and beyond to solve forefront scientific problems. This paper outlines what we see as some of the biggest research challenges facing the visualization community, and how we can approach education and outreach to put successful research in the hands of scientists

The Landscape Evolution Observatory: a large-scale controllable infrastructure to study coupled Earth-surface processes

Science.gov (United States)

Pangle, Luke A.; DeLong, Stephen B.; Abramson, Nate; Adams, John; Barron-Gafford, Greg A.; Breshears, David D.; Brooks, Paul D.; Chorover, Jon; Dietrich, William E.; Dontsova, Katerina; Durcik, Matej; Espeleta, Javier; Ferré, T.P.A.; Ferriere, Regis; Henderson, Whitney; Hunt, Edward A.; Huxman, Travis E.; Millar, David; Murphy, Brendan; Niu, Guo-Yue; Pavao-Zuckerman, Mitch; Pelletier, Jon D.; Rasmussen, Craig; Ruiz, Joaquin; Saleska, Scott; Schaap, Marcel; Sibayan, Michael; Troch, Peter A.; Tuller, Markus; van Haren, Joost; Zeng, Xubin

2015-01-01

Zero-order drainage basins, and their constituent hillslopes, are the fundamental geomorphic unit comprising much of Earth's uplands. The convergent topography of these landscapes generates spatially variable substrate and moisture content, facilitating biological diversity and influencing how the landscape filters precipitation and sequesters atmospheric carbon dioxide. In light of these significant ecosystem services, refining our understanding of how these functions are affected by landscape evolution, weather variability, and long-term climate change is imperative. In this paper we introduce the Landscape Evolution Observatory (LEO): a large-scale controllable infrastructure consisting of three replicated artificial landscapes (each 330 m2 surface area) within the climate-controlled Biosphere 2 facility in Arizona, USA. At LEO, experimental manipulation of rainfall, air temperature, relative humidity, and wind speed are possible at unprecedented scale. The Landscape Evolution Observatory was designed as a community resource to advance understanding of how topography, physical and chemical properties of soil, and biological communities coevolve, and how this coevolution affects water, carbon, and energy cycles at multiple spatial scales. With well-defined boundary conditions and an extensive network of sensors and samplers, LEO enables an iterative scientific approach that includes numerical model development and virtual experimentation, physical experimentation, data analysis, and model refinement. We plan to engage the broader scientific community through public dissemination of data from LEO, collaborative experimental design, and community-based model development.

Interior Point Method for Solving Fuzzy Number Linear Programming Problems Using Linear Ranking Function

Directory of Open Access Journals (Sweden)

Yi-hua Zhong

2013-01-01

Full Text Available Recently, various methods have been developed for solving linear programming problems with fuzzy number, such as simplex method and dual simplex method. But their computational complexities are exponential, which is not satisfactory for solving large-scale fuzzy linear programming problems, especially in the engineering field. A new method which can solve large-scale fuzzy number linear programming problems is presented in this paper, which is named a revised interior point method. Its idea is similar to that of interior point method used for solving linear programming problems in crisp environment before, but its feasible direction and step size are chosen by using trapezoidal fuzzy numbers, linear ranking function, fuzzy vector, and their operations, and its end condition is involved in linear ranking function. Their correctness and rationality are proved. Moreover, choice of the initial interior point and some factors influencing the results of this method are also discussed and analyzed. The result of algorithm analysis and example study that shows proper safety factor parameter, accuracy parameter, and initial interior point of this method may reduce iterations and they can be selected easily according to the actual needs. Finally, the method proposed in this paper is an alternative method for solving fuzzy number linear programming problems.

Comparison Between Overtopping Discharge in Small and Large Scale Models

DEFF Research Database (Denmark)

Helgason, Einar; Burcharth, Hans F.

2006-01-01

The present paper presents overtopping measurements from small scale model test performed at the Haudraulic & Coastal Engineering Laboratory, Aalborg University, Denmark and large scale model tests performed at the Largde Wave Channel,Hannover, Germany. Comparison between results obtained from...... small and large scale model tests show no clear evidence of scale effects for overtopping above a threshold value. In the large scale model no overtopping was measured for waveheights below Hs = 0.5m as the water sunk into the voids between the stones on the crest. For low overtopping scale effects...

Measuring scientific reasoning through behavioral analysis in a computer-based problem solving exercise

Science.gov (United States)

Mead, C.; Horodyskyj, L.; Buxner, S.; Semken, S. C.; Anbar, A. D.

2016-12-01

Developing scientific reasoning skills is a common learning objective for general-education science courses. However, effective assessments for such skills typically involve open-ended questions or tasks, which must be hand-scored and may not be usable online. Using computer-based learning environments, reasoning can be assessed automatically by analyzing student actions within the learning environment. We describe such an assessment under development and present pilot results. In our content-neutral instrument, students solve a problem by collecting and interpreting data in a logical, systematic manner. We then infer reasoning skill automatically based on student actions. Specifically, students investigate why Earth has seasons, a scientifically simple but commonly misunderstood topic. Students are given three possible explanations and asked to select a set of locations on a world map from which to collect temperature data. They then explain how the data support or refute each explanation. The best approaches will use locations in both the Northern and Southern hemispheres to argue that the contrasting seasonality of the hemispheres supports only the correct explanation. We administered a pilot version to students at the beginning of an online, introductory science course (n = 223) as an optional extra credit exercise. We were able to categorize students' data collection decisions as more and less logically sound. Students who choose the most logical measurement locations earned higher course grades, but not significantly higher. This result is encouraging, but not definitive. In the future, we will clarify our results in two ways. First, we plan to incorporate more open-ended interactions into the assessment to improve the resolving power of this tool. Second, to avoid relying on course grades, we will independently measure reasoning skill with one of the existing hand-scored assessments (e.g., Critical Thinking Assessment Test) to cross-validate our new

Needs, opportunities, and options for large scale systems research

Energy Technology Data Exchange (ETDEWEB)

Thompson, G.L.

1984-10-01

The Office of Energy Research was recently asked to perform a study of Large Scale Systems in order to facilitate the development of a true large systems theory. It was decided to ask experts in the fields of electrical engineering, chemical engineering and manufacturing/operations research for their ideas concerning large scale systems research. The author was asked to distribute a questionnaire among these experts to find out their opinions concerning recent accomplishments and future research directions in large scale systems research. He was also requested to convene a conference which included three experts in each area as panel members to discuss the general area of large scale systems research. The conference was held on March 26--27, 1984 in Pittsburgh with nine panel members, and 15 other attendees. The present report is a summary of the ideas presented and the recommendations proposed by the attendees.

Large-scale structure of the Universe

International Nuclear Information System (INIS)

Doroshkevich, A.G.

1978-01-01

The problems, discussed at the ''Large-scale Structure of the Universe'' symposium are considered on a popular level. Described are the cell structure of galaxy distribution in the Universe, principles of mathematical galaxy distribution modelling. The images of cell structures, obtained after reprocessing with the computer are given. Discussed are three hypothesis - vortical, entropic, adiabatic, suggesting various processes of galaxy and galaxy clusters origin. A considerable advantage of the adiabatic hypothesis is recognized. The relict radiation, as a method of direct studying the processes taking place in the Universe is considered. The large-scale peculiarities and small-scale fluctuations of the relict radiation temperature enable one to estimate the turbance properties at the pre-galaxy stage. The discussion of problems, pertaining to studying the hot gas, contained in galaxy clusters, the interactions within galaxy clusters and with the inter-galaxy medium, is recognized to be a notable contribution into the development of theoretical and observational cosmology

Large Scale Computing and Storage Requirements for Basic Energy Sciences Research

Energy Technology Data Exchange (ETDEWEB)

Gerber, Richard; Wasserman, Harvey

2011-03-31

The National Energy Research Scientific Computing Center (NERSC) is the leading scientific computing facility supporting research within the Department of Energy's Office of Science. NERSC provides high-performance computing (HPC) resources to approximately 4,000 researchers working on about 400 projects. In addition to hosting large-scale computing facilities, NERSC provides the support and expertise scientists need to effectively and efficiently use HPC systems. In February 2010, NERSC, DOE's Office of Advanced Scientific Computing Research (ASCR) and DOE's Office of Basic Energy Sciences (BES) held a workshop to characterize HPC requirements for BES research through 2013. The workshop was part of NERSC's legacy of anticipating users future needs and deploying the necessary resources to meet these demands. Workshop participants reached a consensus on several key findings, in addition to achieving the workshop's goal of collecting and characterizing computing requirements. The key requirements for scientists conducting research in BES are: (1) Larger allocations of computational resources; (2) Continued support for standard application software packages; (3) Adequate job turnaround time and throughput; and (4) Guidance and support for using future computer architectures. This report expands upon these key points and presents others. Several 'case studies' are included as significant representative samples of the needs of science teams within BES. Research teams scientific goals, computational methods of solution, current and 2013 computing requirements, and special software and support needs are summarized in these case studies. Also included are researchers strategies for computing in the highly parallel, 'multi-core' environment that is expected to dominate HPC architectures over the next few years. NERSC has strategic plans and initiatives already underway that address key workshop findings. This report includes a

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY17.

Energy Technology Data Exchange (ETDEWEB)

Moreland, Kenneth D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pugmire, David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Rogers, David [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Childs, Hank [Univ. of Oregon, Eugene, OR (United States); Ma, Kwan-Liu [Univ. of California, Davis, CA (United States); Geveci, Berk [Kitware, Inc., Clifton Park, NY (United States)

2017-10-01

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

Emerging Nanophotonic Applications Explored with Advanced Scientific Parallel Computing

Science.gov (United States)

Meng, Xiang

The domain of nanoscale optical science and technology is a combination of the classical world of electromagnetics and the quantum mechanical regime of atoms and molecules. Recent advancements in fabrication technology allows the optical structures to be scaled down to nanoscale size or even to the atomic level, which are far smaller than the wavelength they are designed for. These nanostructures can have unique, controllable, and tunable optical properties and their interactions with quantum materials can have important near-field and far-field optical response. Undoubtedly, these optical properties can have many important applications, ranging from the efficient and tunable light sources, detectors, filters, modulators, high-speed all-optical switches; to the next-generation classical and quantum computation, and biophotonic medical sensors. This emerging research of nanoscience, known as nanophotonics, is a highly interdisciplinary field requiring expertise in materials science, physics, electrical engineering, and scientific computing, modeling and simulation. It has also become an important research field for investigating the science and engineering of light-matter interactions that take place on wavelength and subwavelength scales where the nature of the nanostructured matter controls the interactions. In addition, the fast advancements in the computing capabilities, such as parallel computing, also become as a critical element for investigating advanced nanophotonic devices. This role has taken on even greater urgency with the scale-down of device dimensions, and the design for these devices require extensive memory and extremely long core hours. Thus distributed computing platforms associated with parallel computing are required for faster designs processes. Scientific parallel computing constructs mathematical models and quantitative analysis techniques, and uses the computing machines to analyze and solve otherwise intractable scientific challenges. In

Image-based Exploration of Large-Scale Pathline Fields

KAUST Repository

Nagoor, Omniah H.

2014-05-27

While real-time applications are nowadays routinely used in visualizing large nu- merical simulations and volumes, handling these large-scale datasets requires high-end graphics clusters or supercomputers to process and visualize them. However, not all users have access to powerful clusters. Therefore, it is challenging to come up with a visualization approach that provides insight to large-scale datasets on a single com- puter. Explorable images (EI) is one of the methods that allows users to handle large data on a single workstation. Although it is a view-dependent method, it combines both exploration and modification of visual aspects without re-accessing the original huge data. In this thesis, we propose a novel image-based method that applies the concept of EI in visualizing large flow-field pathlines data. The goal of our work is to provide an optimized image-based method, which scales well with the dataset size. Our approach is based on constructing a per-pixel linked list data structure in which each pixel contains a list of pathlines segments. With this view-dependent method it is possible to filter, color-code and explore large-scale flow data in real-time. In addition, optimization techniques such as early-ray termination and deferred shading are applied, which further improves the performance and scalability of our approach.

Solved problems in electrochemistry

International Nuclear Information System (INIS)

Piron, D.L.

2004-01-01

This book presents calculated solutions to problems in fundamental and applied electrochemistry. It uses industrial data to illustrate scientific concepts and scientific knowledge to solve practical problems. It is subdivided into three parts. The first uses modern basic concepts, the second studies the scientific basis for electrode and electrolyte thermodynamics (including E-pH diagrams and the minimum energy involved in transformations) and the kinetics of rate processes (including the energy lost in heat and in parasite reactions). The third part treats larger problems in electrolysis and power generation, as well as in corrosion and its prevention. Each chapter includes three sections: the presentation of useful principles; some twenty problems with their solutions; and, a set of unsolved problems

Performance of Air Pollution Models on Massively Parallel Computers

DEFF Research Database (Denmark)

Brown, John; Hansen, Per Christian; Wasniewski, Jerzy

1996-01-01

To compare the performance and use of three massively parallel SIMD computers, we implemented a large air pollution model on the computers. Using a realistic large-scale model, we gain detailed insight about the performance of the three computers when used to solve large-scale scientific problems...

Homogenization of Large-Scale Movement Models in Ecology

Science.gov (United States)

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.

Problem-Solving: Scaling the "Brick Wall"

Science.gov (United States)

Benson, Dave

2011-01-01

Across the primary and secondary phases, pupils are encouraged to use and apply their knowledge, skills, and understanding of mathematics to solve problems in a variety of forms, ranging from single-stage word problems to the challenge of extended rich tasks. Amongst many others, Cockcroft (1982) emphasised the importance and relevance of…

The role of large-scale, extratropical dynamics in climate change

Energy Technology Data Exchange (ETDEWEB)

Shepherd, T.G. [ed.

1994-02-01

The climate modeling community has focused recently on improving our understanding of certain processes, such as cloud feedbacks and ocean circulation, that are deemed critical to climate-change prediction. Although attention to such processes is warranted, emphasis on these areas has diminished a general appreciation of the role played by the large-scale dynamics of the extratropical atmosphere. Lack of interest in extratropical dynamics may reflect the assumption that these dynamical processes are a non-problem as far as climate modeling is concerned, since general circulation models (GCMs) calculate motions on this scale from first principles. Nevertheless, serious shortcomings in our ability to understand and simulate large-scale dynamics exist. Partly due to a paucity of standard GCM diagnostic calculations of large-scale motions and their transports of heat, momentum, potential vorticity, and moisture, a comprehensive understanding of the role of large-scale dynamics in GCM climate simulations has not been developed. Uncertainties remain in our understanding and simulation of large-scale extratropical dynamics and their interaction with other climatic processes, such as cloud feedbacks, large-scale ocean circulation, moist convection, air-sea interaction and land-surface processes. To address some of these issues, the 17th Stanstead Seminar was convened at Bishop`s University in Lennoxville, Quebec. The purpose of the Seminar was to promote discussion of the role of large-scale extratropical dynamics in global climate change. Abstracts of the talks are included in this volume. On the basis of these talks, several key issues emerged concerning large-scale extratropical dynamics and their climatic role. Individual records are indexed separately for the database.

The role of large-scale, extratropical dynamics in climate change

International Nuclear Information System (INIS)

Shepherd, T.G.

1994-02-01

The climate modeling community has focused recently on improving our understanding of certain processes, such as cloud feedbacks and ocean circulation, that are deemed critical to climate-change prediction. Although attention to such processes is warranted, emphasis on these areas has diminished a general appreciation of the role played by the large-scale dynamics of the extratropical atmosphere. Lack of interest in extratropical dynamics may reflect the assumption that these dynamical processes are a non-problem as far as climate modeling is concerned, since general circulation models (GCMs) calculate motions on this scale from first principles. Nevertheless, serious shortcomings in our ability to understand and simulate large-scale dynamics exist. Partly due to a paucity of standard GCM diagnostic calculations of large-scale motions and their transports of heat, momentum, potential vorticity, and moisture, a comprehensive understanding of the role of large-scale dynamics in GCM climate simulations has not been developed. Uncertainties remain in our understanding and simulation of large-scale extratropical dynamics and their interaction with other climatic processes, such as cloud feedbacks, large-scale ocean circulation, moist convection, air-sea interaction and land-surface processes. To address some of these issues, the 17th Stanstead Seminar was convened at Bishop's University in Lennoxville, Quebec. The purpose of the Seminar was to promote discussion of the role of large-scale extratropical dynamics in global climate change. Abstracts of the talks are included in this volume. On the basis of these talks, several key issues emerged concerning large-scale extratropical dynamics and their climatic role. Individual records are indexed separately for the database

Large scale breeder reactor plant prototype mechanical pump conceptual design study

Energy Technology Data Exchange (ETDEWEB)

1976-07-01

This report includes engineering memorandums, drawings, key feature descriptions, and other data. Some of the reports, such as manufacturability and some stress analysis, were done by consultants for Byron Jackson. Review of this report indicates that the design is feasible. The pump can be manufactured to system and specification requirements. The overall length and weight of some pieces will require special consideration, but is within the scope of equipment and technology available today. The fabricated parts are large and heavy, but can be manufactured and machined. Only the high temperature is unique to this size, since previous sodium pumps were smaller. Nondestructive tests as required by the Code are described and are feasible. The performance test of the prototype has been studied thoroughly. It is feasible for a cold water test. There are some problem areas. However, all of them can be solved. Development needs include building and testing a small scale model.

Deep Hashing Based Fusing Index Method for Large-Scale Image Retrieval

Directory of Open Access Journals (Sweden)

Lijuan Duan

2017-01-01

Full Text Available Hashing has been widely deployed to perform the Approximate Nearest Neighbor (ANN search for the large-scale image retrieval to solve the problem of storage and retrieval efficiency. Recently, deep hashing methods have been proposed to perform the simultaneous feature learning and the hash code learning with deep neural networks. Even though deep hashing has shown the better performance than traditional hashing methods with handcrafted features, the learned compact hash code from one deep hashing network may not provide the full representation of an image. In this paper, we propose a novel hashing indexing method, called the Deep Hashing based Fusing Index (DHFI, to generate a more compact hash code which has stronger expression ability and distinction capability. In our method, we train two different architecture’s deep hashing subnetworks and fuse the hash codes generated by the two subnetworks together to unify images. Experiments on two real datasets show that our method can outperform state-of-the-art image retrieval applications.

Status: Large-scale subatmospheric cryogenic systems

International Nuclear Information System (INIS)

Peterson, T.

1989-01-01

In the late 1960's and early 1970's an interest in testing and operating RF cavities at 1.8K motivated the development and construction of four large (300 Watt) 1.8K refrigeration systems. in the past decade, development of successful superconducting RF cavities and interest in obtaining higher magnetic fields with the improved Niobium-Titanium superconductors has once again created interest in large-scale 1.8K refrigeration systems. The L'Air Liquide plant for Tore Supra is a recently commissioned 300 Watt 1.8K system which incorporates new technology, cold compressors, to obtain the low vapor pressure for low temperature cooling. CEBAF proposes to use cold compressors to obtain 5KW at 2.0K. Magnetic refrigerators of 10 Watt capacity or higher at 1.8K are now being developed. The state of the art of large-scale refrigeration in the range under 4K will be reviewed. 28 refs., 4 figs., 7 tabs

Fast and accurate solution for the SCUC problem in large-scale power systems using adapted binary programming and enhanced dual neural network

International Nuclear Information System (INIS)

Shafie-khah, M.; Moghaddam, M.P.; Sheikh-El-Eslami, M.K.; Catalão, J.P.S.

2014-01-01

Highlights: • A novel hybrid method based on decomposition of SCUC into QP and BP problems is proposed. • An adapted binary programming and an enhanced dual neural network model are applied. • The proposed EDNN is exactly convergent to the global optimal solution of QP. • An AC power flow procedure is developed for including contingency/security issues. • It is suited for large-scale systems, providing both accurate and fast solutions. - Abstract: This paper presents a novel hybrid method for solving the security constrained unit commitment (SCUC) problem. The proposed formulation requires much less computation time in comparison with other methods while assuring the accuracy of the results. Furthermore, the framework provided here allows including an accurate description of warmth-dependent startup costs, valve point effects, multiple fuel costs, forbidden zones of operation, and AC load flow bounds. To solve the nonconvex problem, an adapted binary programming method and enhanced dual neural network model are utilized as optimization tools, and a procedure for AC power flow modeling is developed for including contingency/security issues, as new contributions to earlier studies. Unlike classical SCUC methods, the proposed method allows to simultaneously solve the unit commitment problem and comply with the network limits. In addition to conventional test systems, a real-world large-scale power system with 493 units has been used to fully validate the effectiveness of the novel hybrid method proposed

Large-scale weakly supervised object localization via latent category learning.

Science.gov (United States)

Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

2015-04-01

Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.

Observing the World Through Your Own Lenses – The Role of Perceived Adaptability for Epistemological Beliefs About the Development of Scientific Knowledge

Directory of Open Access Journals (Sweden)

Ronny Scherer

2018-06-01

Full Text Available Students are exposed to vast amounts of information and knowledge that is rapidly changing. This exposure requires them to be adaptive, that is, to constantly adjust their thinking, behavior, and even their affect to successfully solve information-rich and knowledge-lean problems. Considering these developments, the purpose of the present study is twofold: First, it is aimed at exploring the link between students’ beliefs about their adaptability in an ever-changing world and their beliefs about the changing nature of scientific knowledge, thus linking two educationally relevant belief systems. Second, this study further explores validity issues related to the well-established and commonly used “Epistemological Beliefs about the Development of Scientific Knowledge (EBDE” scale. Performing structural equation modeling on a large-scale data set of 1,662 Norwegian tenth-grade students, we estimated the correlations among different aspects of adaptability (i.e., cognitive-behavioral and affective-emotional adaptability and EBDE. Moving beyond these correlations, we tested whether students’ perceived adaptability had an impact on the functioning of EBDE items by means of moderated factor analysis. Our analyses revealed that adaptability was associated with sophisticated EBDE in science, and the EB scale functioned differently with respect to different adaptability scores. The results of this study indicate that students perceive the development of scientific knowledge through the lenses of their own adaptability. Furthermore, the differential functioning of the EBDE scale challenges its validity.

Computational investigation of large-scale vortex interaction with flexible bodies

Science.gov (United States)

Connell, Benjamin; Yue, Dick K. P.

2003-11-01

The interaction of large-scale vortices with flexible bodies is examined with particular interest paid to the energy and momentum budgets of the system. Finite difference direct numerical simulation of the Navier-Stokes equations on a moving curvilinear grid is coupled with a finite difference structural solver of both a linear membrane under tension and linear Euler-Bernoulli beam. The hydrodynamics and structural dynamics are solved simultaneously using an iterative procedure with the external structural forcing calculated from the hydrodynamics at the surface and the flow-field velocity boundary condition given by the structural motion. We focus on an investigation into the canonical problem of a vortex-dipole impinging on a flexible membrane. It is discovered that the structural properties of the membrane direct the interaction in terms of the flow evolution and the energy budget. Pressure gradients associated with resonant membrane response are shown to sustain the oscillatory motion of the vortex pair. Understanding how the key mechanisms in vortex-body interactions are guided by the structural properties of the body is a prerequisite to exploiting these mechanisms.

Computer-supported analysis of scientific measurements

NARCIS (Netherlands)

de Jong, Hidde

1998-01-01

In the past decade, large-scale databases and knowledge bases have become available to researchers working in a range of scientific disciplines. In many cases these databases and knowledge bases contain measurements of properties of physical objects which have been obtained in experiments or at

An Novel Architecture of Large-scale Communication in IOT

Science.gov (United States)

Ma, Wubin; Deng, Su; Huang, Hongbin

2018-03-01

In recent years, many scholars have done a great deal of research on the development of Internet of Things and networked physical systems. However, few people have made the detailed visualization of the large-scale communications architecture in the IOT. In fact, the non-uniform technology between IPv6 and access points has led to a lack of broad principles of large-scale communications architectures. Therefore, this paper presents the Uni-IPv6 Access and Information Exchange Method (UAIEM), a new architecture and algorithm that addresses large-scale communications in the IOT.

Benefits of transactive memory systems in large-scale development

OpenAIRE

Aivars, Sablis

2016-01-01

Context. Large-scale software development projects are those consisting of a large number of teams, maybe even spread across multiple locations, and working on large and complex software tasks. That means that neither a team member individually nor an entire team holds all the knowledge about the software being developed and teams have to communicate and coordinate their knowledge. Therefore, teams and team members in large-scale software development projects must acquire and manage expertise...

Study of a large scale neutron measurement channel

International Nuclear Information System (INIS)

Amarouayache, Anissa; Ben Hadid, Hayet.

1982-12-01

A large scale measurement channel allows the processing of the signal coming from an unique neutronic sensor, during three different running modes: impulses, fluctuations and current. The study described in this note includes three parts: - A theoretical study of the large scale channel and its brief description are given. The results obtained till now in that domain are presented. - The fluctuation mode is thoroughly studied and the improvements to be done are defined. The study of a fluctuation linear channel with an automatic commutation of scales is described and the results of the tests are given. In this large scale channel, the method of data processing is analogical. - To become independent of the problems generated by the use of a an analogical processing of the fluctuation signal, a digital method of data processing is tested. The validity of that method is improved. The results obtained on a test system realized according to this method are given and a preliminary plan for further research is defined [fr

Quantifying expert consensus against the existence of a secret, large-scale atmospheric spraying program

Science.gov (United States)

Shearer, Christine; West, Mick; Caldeira, Ken; Davis, Steven J.

2016-08-01

Nearly 17% of people in an international survey said they believed the existence of a secret large-scale atmospheric program (SLAP) to be true or partly true. SLAP is commonly referred to as ‘chemtrails’ or ‘covert geoengineering’, and has led to a number of websites purported to show evidence of widespread chemical spraying linked to negative impacts on human health and the environment. To address these claims, we surveyed two groups of experts—atmospheric chemists with expertize in condensation trails and geochemists working on atmospheric deposition of dust and pollution—to scientifically evaluate for the first time the claims of SLAP theorists. Results show that 76 of the 77 scientists (98.7%) that took part in this study said they had not encountered evidence of a SLAP, and that the data cited as evidence could be explained through other factors, including well-understood physics and chemistry associated with aircraft contrails and atmospheric aerosols. Our goal is not to sway those already convinced that there is a secret, large-scale spraying program—who often reject counter-evidence as further proof of their theories—but rather to establish a source of objective science that can inform public discourse.

Capabilities of the Large-Scale Sediment Transport Facility

Science.gov (United States)

2016-04-01

pump flow meters, sediment trap weigh tanks , and beach profiling lidar. A detailed discussion of the original LSTF features and capabilities can be...ERDC/CHL CHETN-I-88 April 2016 Approved for public release; distribution is unlimited. Capabilities of the Large-Scale Sediment Transport...describes the Large-Scale Sediment Transport Facility (LSTF) and recent upgrades to the measurement systems. The purpose of these upgrades was to increase

Spatiotemporal property and predictability of large-scale human mobility

Science.gov (United States)

Zhang, Hai-Tao; Zhu, Tao; Fu, Dongfei; Xu, Bowen; Han, Xiao-Pu; Chen, Duxin

2018-04-01

Spatiotemporal characteristics of human mobility emerging from complexity on individual scale have been extensively studied due to the application potential on human behavior prediction and recommendation, and control of epidemic spreading. We collect and investigate a comprehensive data set of human activities on large geographical scales, including both websites browse and mobile towers visit. Numerical results show that the degree of activity decays as a power law, indicating that human behaviors are reminiscent of scale-free random walks known as Lévy flight. More significantly, this study suggests that human activities on large geographical scales have specific non-Markovian characteristics, such as a two-segment power-law distribution of dwelling time and a high possibility for prediction. Furthermore, a scale-free featured mobility model with two essential ingredients, i.e., preferential return and exploration, and a Gaussian distribution assumption on the exploration tendency parameter is proposed, which outperforms existing human mobility models under scenarios of large geographical scales.

Probabilities and Predictions: Modeling the Development of Scientific Problem-Solving Skills

Science.gov (United States)

2005-01-01

The IMMEX (Interactive Multi-Media Exercises) Web-based problem set platform enables the online delivery of complex, multimedia simulations, the rapid collection of student performance data, and has already been used in several genetic simulations. The next step is the use of these data to understand and improve student learning in a formative manner. This article describes the development of probabilistic models of undergraduate student problem solving in molecular genetics that detailed the spectrum of strategies students used when problem solving, and how the strategic approaches evolved with experience. The actions of 776 university sophomore biology majors from three molecular biology lecture courses were recorded and analyzed. Each of six simulations were first grouped by artificial neural network clustering to provide individual performance measures, and then sequences of these performances were probabilistically modeled by hidden Markov modeling to provide measures of progress. The models showed that students with different initial problem-solving abilities choose different strategies. Initial and final strategies varied across different sections of the same course and were not strongly correlated with other achievement measures. In contrast to previous studies, we observed no significant gender differences. We suggest that instructor interventions based on early student performances with these simulations may assist students to recognize effective and efficient problem-solving strategies and enhance learning. PMID:15746978

Problems of large-scale vertically-integrated aquaculture

Energy Technology Data Exchange (ETDEWEB)

Webber, H H; Riordan, P F

1976-01-01

The problems of vertically-integrated aquaculture are outlined; they are concerned with: species limitations (in the market, biological and technological); site selection, feed, manpower needs, and legal, institutional and financial requirements. The gaps in understanding of, and the constraints limiting, large-scale aquaculture are listed. Future action is recommended with respect to: types and diversity of species to be cultivated, marketing, biotechnology (seed supply, disease control, water quality and concerted effort), siting, feed, manpower, legal and institutional aids (granting of water rights, grants, tax breaks, duty-free imports, etc.), and adequate financing. The last of hard data based on experience suggests that large-scale vertically-integrated aquaculture is a high risk enterprise, and with the high capital investment required, banks and funding institutions are wary of supporting it. Investment in pilot projects is suggested to demonstrate that large-scale aquaculture can be a fully functional and successful business. Construction and operation of such pilot farms is judged to be in the interests of both the public and private sector.

Large-scale computing with Quantum Espresso

International Nuclear Information System (INIS)

Giannozzi, P.; Cavazzoni, C.

2009-01-01

This paper gives a short introduction to Quantum Espresso: a distribution of software for atomistic simulations in condensed-matter physics, chemical physics, materials science, and to its usage in large-scale parallel computing.

Highly parallel machines and future of scientific computing

International Nuclear Information System (INIS)

Singh, G.S.

1992-01-01

Computing requirement of large scale scientific computing has always been ahead of what state of the art hardware could supply in the form of supercomputers of the day. And for any single processor system the limit to increase in the computing power was realized a few years back itself. Now with the advent of parallel computing systems the availability of machines with the required computing power seems a reality. In this paper the author tries to visualize the future large scale scientific computing in the penultimate decade of the present century. The author summarized trends in parallel computers and emphasize the need for a better programming environment and software tools for optimal performance. The author concludes this paper with critique on parallel architectures, software tools and algorithms. (author). 10 refs., 2 tabs

VESPA: Very large-scale Evolutionary and Selective Pressure Analyses

Directory of Open Access Journals (Sweden)

Andrew E. Webb

2017-06-01

Full Text Available Background Large-scale molecular evolutionary analyses of protein coding sequences requires a number of preparatory inter-related steps from finding gene families, to generating alignments and phylogenetic trees and assessing selective pressure variation. Each phase of these analyses can represent significant challenges, particularly when working with entire proteomes (all protein coding sequences in a genome from a large number of species. Methods We present VESPA, software capable of automating a selective pressure analysis using codeML in addition to the preparatory analyses and summary statistics. VESPA is written in python and Perl and is designed to run within a UNIX environment. Results We have benchmarked VESPA and our results show that the method is consistent, performs well on both large scale and smaller scale datasets, and produces results in line with previously published datasets. Discussion Large-scale gene family identification, sequence alignment, and phylogeny reconstruction are all important aspects of large-scale molecular evolutionary analyses. VESPA provides flexible software for simplifying these processes along with downstream selective pressure variation analyses. The software automatically interprets results from codeML and produces simplified summary files to assist the user in better understanding the results. VESPA may be found at the following website: http://www.mol-evol.org/VESPA.

RESTRUCTURING OF THE LARGE-SCALE SPRINKLERS

Directory of Open Access Journals (Sweden)

Paweł Kozaczyk

2016-09-01

Full Text Available One of the best ways for agriculture to become independent from shortages of precipitation is irrigation. In the seventies and eighties of the last century a number of large-scale sprinklers in Wielkopolska was built. At the end of 1970’s in the Poznan province 67 sprinklers with a total area of 6400 ha were installed. The average size of the sprinkler reached 95 ha. In 1989 there were 98 sprinklers, and the area which was armed with them was more than 10 130 ha. The study was conducted on 7 large sprinklers with the area ranging from 230 to 520 hectares in 1986÷1998. After the introduction of the market economy in the early 90’s and ownership changes in agriculture, large-scale sprinklers have gone under a significant or total devastation. Land on the State Farms of the State Agricultural Property Agency has leased or sold and the new owners used the existing sprinklers to a very small extent. This involved a change in crop structure, demand structure and an increase in operating costs. There has also been a threefold increase in electricity prices. Operation of large-scale irrigation encountered all kinds of barriers in practice and limitations of system solutions, supply difficulties, high levels of equipment failure which is not inclined to rational use of available sprinklers. An effect of a vision of the local area was to show the current status of the remaining irrigation infrastructure. The adopted scheme for the restructuring of Polish agriculture was not the best solution, causing massive destruction of assets previously invested in the sprinkler system.

A Nonlinear Multiobjective Bilevel Model for Minimum Cost Network Flow Problem in a Large-Scale Construction Project

Directory of Open Access Journals (Sweden)

Jiuping Xu

2012-01-01

Full Text Available The aim of this study is to deal with a minimum cost network flow problem (MCNFP in a large-scale construction project using a nonlinear multiobjective bilevel model with birandom variables. The main target of the upper level is to minimize both direct and transportation time costs. The target of the lower level is to minimize transportation costs. After an analysis of the birandom variables, an expectation multiobjective bilevel programming model with chance constraints is formulated to incorporate decision makers’ preferences. To solve the identified special conditions, an equivalent crisp model is proposed with an additional multiobjective bilevel particle swarm optimization (MOBLPSO developed to solve the model. The Shuibuya Hydropower Project is used as a real-world example to verify the proposed approach. Results and analysis are presented to highlight the performances of the MOBLPSO, which is very effective and efficient compared to a genetic algorithm and a simulated annealing algorithm.

Large-scale synthesis of YSZ nanopowder by Pechini method

Indian Academy of Sciences (India)

Administrator

structure and chemical purity of 99⋅1% by inductively coupled plasma optical emission spectroscopy on a large scale. Keywords. Sol–gel; yttria-stabilized zirconia; large scale; nanopowder; Pechini method. 1. Introduction. Zirconia has attracted the attention of many scientists because of its tremendous thermal, mechanical ...

The Phoenix series large scale LNG pool fire experiments.

Energy Technology Data Exchange (ETDEWEB)

Simpson, Richard B.; Jensen, Richard Pearson; Demosthenous, Byron; Luketa, Anay Josephine; Ricks, Allen Joseph; Hightower, Marion Michael; Blanchat, Thomas K.; Helmick, Paul H.; Tieszen, Sheldon Robert; Deola, Regina Anne; Mercier, Jeffrey Alan; Suo-Anttila, Jill Marie; Miller, Timothy J.

2010-12-01

The increasing demand for natural gas could increase the number and frequency of Liquefied Natural Gas (LNG) tanker deliveries to ports across the United States. Because of the increasing number of shipments and the number of possible new facilities, concerns about the potential safety of the public and property from an accidental, and even more importantly intentional spills, have increased. While improvements have been made over the past decade in assessing hazards from LNG spills, the existing experimental data is much smaller in size and scale than many postulated large accidental and intentional spills. Since the physics and hazards from a fire change with fire size, there are concerns about the adequacy of current hazard prediction techniques for large LNG spills and fires. To address these concerns, Congress funded the Department of Energy (DOE) in 2008 to conduct a series of laboratory and large-scale LNG pool fire experiments at Sandia National Laboratories (Sandia) in Albuquerque, New Mexico. This report presents the test data and results of both sets of fire experiments. A series of five reduced-scale (gas burner) tests (yielding 27 sets of data) were conducted in 2007 and 2008 at Sandia's Thermal Test Complex (TTC) to assess flame height to fire diameter ratios as a function of nondimensional heat release rates for extrapolation to large-scale LNG fires. The large-scale LNG pool fire experiments were conducted in a 120 m diameter pond specially designed and constructed in Sandia's Area III large-scale test complex. Two fire tests of LNG spills of 21 and 81 m in diameter were conducted in 2009 to improve the understanding of flame height, smoke production, and burn rate and therefore the physics and hazards of large LNG spills and fires.

Geospatial Optimization of Siting Large-Scale Solar Projects

Energy Technology Data Exchange (ETDEWEB)

Macknick, Jordan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Quinby, Ted [National Renewable Energy Lab. (NREL), Golden, CO (United States); Caulfield, Emmet [Stanford Univ., CA (United States); Gerritsen, Margot [Stanford Univ., CA (United States); Diffendorfer, Jay [U.S. Geological Survey, Boulder, CO (United States); Haines, Seth [U.S. Geological Survey, Boulder, CO (United States)

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.

Comprehensive large-scale assessment of intrinsic protein disorder.

Science.gov (United States)

Walsh, Ian; Giollo, Manuel; Di Domenico, Tomás; Ferrari, Carlo; Zimmermann, Olav; Tosatto, Silvio C E

2015-01-15

Intrinsically disordered regions are key for the function of numerous proteins. Due to the difficulties in experimental disorder characterization, many computational predictors have been developed with various disorder flavors. Their performance is generally measured on small sets mainly from experimentally solved structures, e.g. Protein Data Bank (PDB) chains. MobiDB has only recently started to collect disorder annotations from multiple experimental structures. MobiDB annotates disorder for UniProt sequences, allowing us to conduct the first large-scale assessment of fast disorder predictors on 25 833 different sequences with X-ray crystallographic structures. In addition to a comprehensive ranking of predictors, this analysis produced the following interesting observations. (i) The predictors cluster according to their disorder definition, with a consensus giving more confidence. (ii) Previous assessments appear over-reliant on data annotated at the PDB chain level and performance is lower on entire UniProt sequences. (iii) Long disordered regions are harder to predict. (iv) Depending on the structural and functional types of the proteins, differences in prediction performance of up to 10% are observed. The datasets are available from Web site at URL: http://mobidb.bio.unipd.it/lsd. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Large-scale Agricultural Land Acquisitions in West Africa | IDRC ...

International Development Research Centre (IDRC) Digital Library (Canada)

This project will examine large-scale agricultural land acquisitions in nine West African countries -Burkina Faso, Guinea-Bissau, Guinea, Benin, Mali, Togo, Senegal, Niger, and Côte d'Ivoire. ... They will use the results to increase public awareness and knowledge about the consequences of large-scale land acquisitions.

Large-scale motions in the universe: a review

International Nuclear Information System (INIS)

Burstein, D.

1990-01-01

The expansion of the universe can be retarded in localised regions within the universe both by the presence of gravity and by non-gravitational motions generated in the post-recombination universe. The motions of galaxies thus generated are called 'peculiar motions', and the amplitudes, size scales and coherence of these peculiar motions are among the most direct records of the structure of the universe. As such, measurements of these properties of the present-day universe provide some of the severest tests of cosmological theories. This is a review of the current evidence for large-scale motions of galaxies out to a distance of ∼5000 km s -1 (in an expanding universe, distance is proportional to radial velocity). 'Large-scale' in this context refers to motions that are correlated over size scales larger than the typical sizes of groups of galaxies, up to and including the size of the volume surveyed. To orient the reader into this relatively new field of study, a short modern history is given together with an explanation of the terminology. Careful consideration is given to the data used to measure the distances, and hence the peculiar motions, of galaxies. The evidence for large-scale motions is presented in a graphical fashion, using only the most reliable data for galaxies spanning a wide range in optical properties and over the complete range of galactic environments. The kinds of systematic errors that can affect this analysis are discussed, and the reliability of these motions is assessed. The predictions of two models of large-scale motion are compared to the observations, and special emphasis is placed on those motions in which our own Galaxy directly partakes. (author)

VET Workers' Problem-Solving Skills in Technology-Rich Environments: European Approach

Science.gov (United States)

Hämäläinen, Raija; Cincinnato, Sebastiano; Malin, Antero; De Wever, Bram

2014-01-01

The European workplace is challenging VET adults' problem-solving skills in technology-rich environments (TREs). So far, no international large-scale assessment data has been available for VET. The PIAAC data comprise the most comprehensive source of information on adults' skills to date. The present study (N = 50 369) focuses on gaining insight…

A route to explosive large-scale magnetic reconnection in a super-ion-scale current sheet

Directory of Open Access Journals (Sweden)

K. G. Tanaka

2009-01-01

Full Text Available How to trigger magnetic reconnection is one of the most interesting and important problems in space plasma physics. Recently, electron temperature anisotropy (αeo=Te⊥/Te|| at the center of a current sheet and non-local effect of the lower-hybrid drift instability (LHDI that develops at the current sheet edges have attracted attention in this context. In addition to these effects, here we also study the effects of ion temperature anisotropy (αio=Ti⊥/Ti||. Electron anisotropy effects are known to be helpless in a current sheet whose thickness is of ion-scale. In this range of current sheet thickness, the LHDI effects are shown to weaken substantially with a small increase in thickness and the obtained saturation level is too low for a large-scale reconnection to be achieved. Then we investigate whether introduction of electron and ion temperature anisotropies in the initial stage would couple with the LHDI effects to revive quick triggering of large-scale reconnection in a super-ion-scale current sheet. The results are as follows. (1 The initial electron temperature anisotropy is consumed very quickly when a number of minuscule magnetic islands (each lateral length is 1.5~3 times the ion inertial length form. These minuscule islands do not coalesce into a large-scale island to enable large-scale reconnection. (2 The subsequent LHDI effects disturb the current sheet filled with the small islands. This makes the triggering time scale to be accelerated substantially but does not enhance the saturation level of reconnected flux. (3 When the ion temperature anisotropy is added, it survives through the small island formation stage and makes even quicker triggering to happen when the LHDI effects set-in. Furthermore the saturation level is seen to be elevated by a factor of ~2 and large-scale reconnection is achieved only in this case. Comparison with two-dimensional simulations that exclude the LHDI effects confirms that the saturation level

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

Science.gov (United States)

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

2017-12-01

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

More on Generalizations and Modifications of Iterative Methods for Solving Large Sparse Indefinite Linear Systems

Directory of Open Access Journals (Sweden)

Jen-Yuan Chen

2014-01-01

Full Text Available Continuing from the works of Li et al. (2014, Li (2007, and Kincaid et al. (2000, we present more generalizations and modifications of iterative methods for solving large sparse symmetric and nonsymmetric indefinite systems of linear equations. We discuss a variety of iterative methods such as GMRES, MGMRES, MINRES, LQ-MINRES, QR MINRES, MMINRES, MGRES, and others.

Large-scale structure observables in general relativity

International Nuclear Information System (INIS)

Jeong, Donghui; Schmidt, Fabian

2015-01-01

We review recent studies that rigorously define several key observables of the large-scale structure of the Universe in a general relativistic context. Specifically, we consider (i) redshift perturbation of cosmic clock events; (ii) distortion of cosmic rulers, including weak lensing shear and magnification; and (iii) observed number density of tracers of the large-scale structure. We provide covariant and gauge-invariant expressions of these observables. Our expressions are given for a linearly perturbed flat Friedmann–Robertson–Walker metric including scalar, vector, and tensor metric perturbations. While we restrict ourselves to linear order in perturbation theory, the approach can be straightforwardly generalized to higher order. (paper)

Fatigue Analysis of Large-scale Wind turbine

Directory of Open Access Journals (Sweden)

Zhu Yongli

2017-01-01

Full Text Available The paper does research on top flange fatigue damage of large-scale wind turbine generator. It establishes finite element model of top flange connection system with finite element analysis software MSC. Marc/Mentat, analyzes its fatigue strain, implements load simulation of flange fatigue working condition with Bladed software, acquires flange fatigue load spectrum with rain-flow counting method, finally, it realizes fatigue analysis of top flange with fatigue analysis software MSC. Fatigue and Palmgren-Miner linear cumulative damage theory. The analysis result indicates that its result provides new thinking for flange fatigue analysis of large-scale wind turbine generator, and possesses some practical engineering value.

Real-time simulation of large-scale floods

Science.gov (United States)

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

2016-08-01

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

A large-scale peer teaching programme - acceptance and benefit.

Science.gov (United States)

Schuetz, Elisabeth; Obirei, Barbara; Salat, Daniela; Scholz, Julia; Hann, Dagmar; Dethleffsen, Kathrin

2017-08-01

The involvement of students in the embodiment of university teaching through peer-assisted learning formats is commonly applied. Publications on this topic exclusively focus on strictly defined situations within the curriculum and selected target groups. This study, in contrast, presents and evaluates a large-scale structured and quality-assured peer teaching programme, which offers diverse and targeted courses throughout the preclinical part of the medical curriculum. The large-scale peer teaching programme consists of subject specific and interdisciplinary tutorials that address all scientific, physiological and anatomic subjects of the preclinical curriculum as well as tutorials with contents exceeding the formal curriculum. In the study year 2013/14 a total of 1,420 lessons were offered as part of the programme. Paper-based evaluations were conducted over the full range of courses. Acceptance and benefit of this peer teaching programme were evaluated in a retrospective study covering the period 2012 to 2014. Usage of tutorials by students who commenced their studies in 2012/13 (n=959) was analysed from 2012 till 2014. Based on the results of 13 first assessments in the preclinical subjects anatomy, biochemistry and physiology, the students were assigned to one of five groups. These groups were compared according to participation in the tutorials. To investigate the benefit of tutorials of the peer teaching programme, the results of biochemistry re-assessments of participants and non-participants of tutorials in the years 2012 till 2014 (n=188, 172 and 204, respectively) were compared using Kolmogorov-Smirnov- and Chi-square tests as well as the effect size Cohen's d. Almost 70 % of the students attended the voluntary additional programme during their preclinical studies. The students participating in the tutorials had achieved different levels of proficiency in first assessments. The acceptance of different kinds of tutorials appears to correlate with their

A solution to the economic dispatch using EP based SA algorithm on large scale power system

Energy Technology Data Exchange (ETDEWEB)

Christober Asir Rajan, C. [Department of EEE, Pondicherry Engineering College, Pondicherry 605 014 (India)

2010-07-15

This paper develops a new approach for solving the Economic Load Dispatch (ELD) using an integrated algorithm based on Evolutionary Programming (EP) and Simulated Annealing (SA) on large scale power system. Classical methods employed for solving Economic Load Dispatch are calculus-based. For generator units having quadratic fuel cost functions, the classical techniques ignore or flatten out the portions of the incremental fuel cost curves and so may be have difficulties in the determination of the global optimum solution for non-differentiable fuel cost functions. To overcome these problems, the intelligent techniques, namely, Evolutionary Programming and Simulated Annealing are employed. The above said optimization techniques are capable of determining the global or near global optimum dispatch solutions. The validity and effectiveness of the proposed integrated algorithm has been tested with 66-bus Indian utility system, IEEE 5-bus, 30-bus, 118-bus system. And the test results are compared with the results obtained from other methods. Numerical results show that the proposed integrated algorithm can provide accurate solutions within reasonable time for any type of fuel cost functions. (author)

Large-scale numerical simulations of plasmas

International Nuclear Information System (INIS)

Hamaguchi, Satoshi

2004-01-01

The recent trend of large scales simulations of fusion plasma and processing plasmas is briefly summarized. Many advanced simulation techniques have been developed for fusion plasmas and some of these techniques are now applied to analyses of processing plasmas. (author)

Performance Health Monitoring of Large-Scale Systems

Energy Technology Data Exchange (ETDEWEB)

Rajamony, Ram [IBM Research, Austin, TX (United States)

2014-11-20

This report details the progress made on the ASCR funded project Performance Health Monitoring for Large Scale Systems. A large-­scale application may not achieve its full performance potential due to degraded performance of even a single subsystem. Detecting performance faults, isolating them, and taking remedial action is critical for the scale of systems on the horizon. PHM aims to develop techniques and tools that can be used to identify and mitigate such performance problems. We accomplish this through two main aspects. The PHM framework encompasses diagnostics, system monitoring, fault isolation, and performance evaluation capabilities that indicates when a performance fault has been detected, either due to an anomaly present in the system itself or due to contention for shared resources between concurrently executing jobs. Software components called the PHM Control system then build upon the capabilities provided by the PHM framework to mitigate degradation caused by performance problems.

The Effects of Topology on Throughput Capacity of Large Scale Wireless Networks

Directory of Open Access Journals (Sweden)

Qiuming Liu

2017-03-01

Full Text Available In this paper, we jointly consider the inhomogeneity and spatial dimension in large scale wireless networks. We study the effects of topology on the throughput capacity. This problem is inherently difficult since it is complex to handle the interference caused by simultaneous transmission. To solve this problem, we, according to the inhomogeneity of topology, divide the transmission into intra-cluster transmission and inter-cluster transmission. For the intra-cluster transmission, a spheroidal percolation model is constructed. The spheroidal percolation model guarantees a constant rate when a power control strategy is adopted. We also propose a cube percolation mode for the inter-cluster transmission. Different from the spheroidal percolation model, a constant transmission rate can be achieved without power control. For both transmissions, we propose a routing scheme with five phases. By comparing the achievable rate of each phase, we get the rate bottleneck, which is the throughput capacity of the network.

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

Science.gov (United States)

Ramapriyan, Hampapuram; Isaac, David; Yang, Wenli; Morse, Steve

2005-01-01

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

Towards a Scalable and Adaptive Application Support Platform for Large-Scale Distributed E-Sciences in High-Performance Network Environments

Energy Technology Data Exchange (ETDEWEB)

Wu, Chase Qishi [New Jersey Inst. of Technology, Newark, NJ (United States); Univ. of Memphis, TN (United States); Zhu, Michelle Mengxia [Southern Illinois Univ., Carbondale, IL (United States)

2016-06-06

The advent of large-scale collaborative scientific applications has demonstrated the potential for broad scientific communities to pool globally distributed resources to produce unprecedented data acquisition, movement, and analysis. System resources including supercomputers, data repositories, computing facilities, network infrastructures, storage systems, and display devices have been increasingly deployed at national laboratories and academic institutes. These resources are typically shared by large communities of users over Internet or dedicated networks and hence exhibit an inherent dynamic nature in their availability, accessibility, capacity, and stability. Scientific applications using either experimental facilities or computation-based simulations with various physical, chemical, climatic, and biological models feature diverse scientific workflows as simple as linear pipelines or as complex as a directed acyclic graphs, which must be executed and supported over wide-area networks with massively distributed resources. Application users oftentimes need to manually configure their computing tasks over networks in an ad hoc manner, hence significantly limiting the productivity of scientists and constraining the utilization of resources. The success of these large-scale distributed applications requires a highly adaptive and massively scalable workflow platform that provides automated and optimized computing and networking services. This project is to design and develop a generic Scientific Workflow Automation and Management Platform (SWAMP), which contains a web-based user interface specially tailored for a target application, a set of user libraries, and several easy-to-use computing and networking toolkits for application scientists to conveniently assemble, execute, monitor, and control complex computing workflows in heterogeneous high-performance network environments. SWAMP will enable the automation and management of the entire process of scientific

Phenomenology of two-dimensional stably stratified turbulence under large-scale forcing

KAUST Repository

Kumar, Abhishek; Verma, Mahendra K.; Sukhatme, Jai

2017-01-01

In this paper, we characterise the scaling of energy spectra, and the interscale transfer of energy and enstrophy, for strongly, moderately and weakly stably stratified two-dimensional (2D) turbulence, restricted in a vertical plane, under large-scale random forcing. In the strongly stratified case, a large-scale vertically sheared horizontal flow (VSHF) coexists with small scale turbulence. The VSHF consists of internal gravity waves and the turbulent flow has a kinetic energy (KE) spectrum that follows an approximate k−3 scaling with zero KE flux and a robust positive enstrophy flux. The spectrum of the turbulent potential energy (PE) also approximately follows a k−3 power-law and its flux is directed to small scales. For moderate stratification, there is no VSHF and the KE of the turbulent flow exhibits Bolgiano–Obukhov scaling that transitions from a shallow k−11/5 form at large scales, to a steeper approximate k−3 scaling at small scales. The entire range of scales shows a strong forward enstrophy flux, and interestingly, large (small) scales show an inverse (forward) KE flux. The PE flux in this regime is directed to small scales, and the PE spectrum is characterised by an approximate k−1.64 scaling. Finally, for weak stratification, KE is transferred upscale and its spectrum closely follows a k−2.5 scaling, while PE exhibits a forward transfer and its spectrum shows an approximate k−1.6 power-law. For all stratification strengths, the total energy always flows from large to small scales and almost all the spectral indicies are well explained by accounting for the scale-dependent nature of the corresponding flux.

Phenomenology of two-dimensional stably stratified turbulence under large-scale forcing

KAUST Repository

Kumar, Abhishek

2017-01-11

In this paper, we characterise the scaling of energy spectra, and the interscale transfer of energy and enstrophy, for strongly, moderately and weakly stably stratified two-dimensional (2D) turbulence, restricted in a vertical plane, under large-scale random forcing. In the strongly stratified case, a large-scale vertically sheared horizontal flow (VSHF) coexists with small scale turbulence. The VSHF consists of internal gravity waves and the turbulent flow has a kinetic energy (KE) spectrum that follows an approximate k−3 scaling with zero KE flux and a robust positive enstrophy flux. The spectrum of the turbulent potential energy (PE) also approximately follows a k−3 power-law and its flux is directed to small scales. For moderate stratification, there is no VSHF and the KE of the turbulent flow exhibits Bolgiano–Obukhov scaling that transitions from a shallow k−11/5 form at large scales, to a steeper approximate k−3 scaling at small scales. The entire range of scales shows a strong forward enstrophy flux, and interestingly, large (small) scales show an inverse (forward) KE flux. The PE flux in this regime is directed to small scales, and the PE spectrum is characterised by an approximate k−1.64 scaling. Finally, for weak stratification, KE is transferred upscale and its spectrum closely follows a k−2.5 scaling, while PE exhibits a forward transfer and its spectrum shows an approximate k−1.6 power-law. For all stratification strengths, the total energy always flows from large to small scales and almost all the spectral indicies are well explained by accounting for the scale-dependent nature of the corresponding flux.

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

Science.gov (United States)

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

2018-04-01

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

Large-scale preparation of hollow graphitic carbon nanospheres

International Nuclear Information System (INIS)

Feng, Jun; Li, Fu; Bai, Yu-Jun; Han, Fu-Dong; Qi, Yong-Xin; Lun, Ning; Lu, Xi-Feng

2013-01-01

Hollow graphitic carbon nanospheres (HGCNSs) were synthesized on large scale by a simple reaction between glucose and Mg at 550 °C in an autoclave. Characterization by X-ray diffraction, Raman spectroscopy and transmission electron microscopy demonstrates the formation of HGCNSs with an average diameter of 10 nm or so and a wall thickness of a few graphenes. The HGCNSs exhibit a reversible capacity of 391 mAh g −1 after 60 cycles when used as anode materials for Li-ion batteries. -- Graphical abstract: Hollow graphitic carbon nanospheres could be prepared on large scale by the simple reaction between glucose and Mg at 550 °C, which exhibit superior electrochemical performance to graphite. Highlights: ► Hollow graphitic carbon nanospheres (HGCNSs) were prepared on large scale at 550 °C ► The preparation is simple, effective and eco-friendly. ► The in situ yielded MgO nanocrystals promote the graphitization. ► The HGCNSs exhibit superior electrochemical performance to graphite.

First Mile Challenges for Large-Scale IoT

KAUST Repository

Bader, Ahmed

2017-03-16

The Internet of Things is large-scale by nature. This is not only manifested by the large number of connected devices, but also by the sheer scale of spatial traffic intensity that must be accommodated, primarily in the uplink direction. To that end, cellular networks are indeed a strong first mile candidate to accommodate the data tsunami to be generated by the IoT. However, IoT devices are required in the cellular paradigm to undergo random access procedures as a precursor to resource allocation. Such procedures impose a major bottleneck that hinders cellular networks\\' ability to support large-scale IoT. In this article, we shed light on the random access dilemma and present a case study based on experimental data as well as system-level simulations. Accordingly, a case is built for the latent need to revisit random access procedures. A call for action is motivated by listing a few potential remedies and recommendations.

Parallel supercomputing: Advanced methods, algorithms, and software for large-scale linear and nonlinear problems

Energy Technology Data Exchange (ETDEWEB)

Carey, G.F.; Young, D.M.

1993-12-31

The program outlined here is directed to research on methods, algorithms, and software for distributed parallel supercomputers. Of particular interest are finite element methods and finite difference methods together with sparse iterative solution schemes for scientific and engineering computations of very large-scale systems. Both linear and nonlinear problems will be investigated. In the nonlinear case, applications with bifurcation to multiple solutions will be considered using continuation strategies. The parallelizable numerical methods of particular interest are a family of partitioning schemes embracing domain decomposition, element-by-element strategies, and multi-level techniques. The methods will be further developed incorporating parallel iterative solution algorithms with associated preconditioners in parallel computer software. The schemes will be implemented on distributed memory parallel architectures such as the CRAY MPP, Intel Paragon, the NCUBE3, and the Connection Machine. We will also consider other new architectures such as the Kendall-Square (KSQ) and proposed machines such as the TERA. The applications will focus on large-scale three-dimensional nonlinear flow and reservoir problems with strong convective transport contributions. These are legitimate grand challenge class computational fluid dynamics (CFD) problems of significant practical interest to DOE. The methods developed and algorithms will, however, be of wider interest.

Thermal power generation projects ``Large Scale Solar Heating``; EU-Thermie-Projekte ``Large Scale Solar Heating``

Energy Technology Data Exchange (ETDEWEB)

Kuebler, R.; Fisch, M.N. [Steinbeis-Transferzentrum Energie-, Gebaeude- und Solartechnik, Stuttgart (Germany)

1998-12-31

The aim of this project is the preparation of the ``Large-Scale Solar Heating`` programme for an Europe-wide development of subject technology. The following demonstration programme was judged well by the experts but was not immediately (1996) accepted for financial subsidies. In November 1997 the EU-commission provided 1,5 million ECU which allowed the realisation of an updated project proposal. By mid 1997 a small project was approved, that had been requested under the lead of Chalmes Industriteteknik (CIT) in Sweden and is mainly carried out for the transfer of technology. (orig.) [Deutsch] Ziel dieses Vorhabens ist die Vorbereitung eines Schwerpunktprogramms `Large Scale Solar Heating`, mit dem die Technologie europaweit weiterentwickelt werden sollte. Das daraus entwickelte Demonstrationsprogramm wurde von den Gutachtern positiv bewertet, konnte jedoch nicht auf Anhieb (1996) in die Foerderung aufgenommen werden. Im November 1997 wurden von der EU-Kommission dann kurzfristig noch 1,5 Mio ECU an Foerderung bewilligt, mit denen ein aktualisierter Projektvorschlag realisiert werden kann. Bereits Mitte 1997 wurde ein kleineres Vorhaben bewilligt, das unter Federfuehrung von Chalmers Industriteknik (CIT) in Schweden beantragt worden war und das vor allem dem Technologietransfer dient. (orig.)

Temperament and problem solving in a population of adolescent guide dogs.

Science.gov (United States)

Bray, Emily E; Sammel, Mary D; Seyfarth, Robert M; Serpell, James A; Cheney, Dorothy L

2017-09-01

It is often assumed that measures of temperament within individuals are more correlated to one another than to measures of problem solving. However, the exact relationship between temperament and problem-solving tasks remains unclear because large-scale studies have typically focused on each independently. To explore this relationship, we tested 119 prospective adolescent guide dogs on a battery of 11 temperament and problem-solving tasks. We then summarized the data using both confirmatory factor analysis and exploratory principal components analysis. Results of confirmatory analysis revealed that a priori separation of tests as measuring either temperament or problem solving led to weak results, poor model fit, some construct validity, and no predictive validity. In contrast, results of exploratory analysis were best summarized by principal components that mixed temperament and problem-solving traits. These components had both construct and predictive validity (i.e., association with success in the guide dog training program). We conclude that there is complex interplay between tasks of "temperament" and "problem solving" and that the study of both together will be more informative than approaches that consider either in isolation.

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

Science.gov (United States)

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

2018-01-01

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

Photorealistic large-scale urban city model reconstruction.

Science.gov (United States)

Poullis, Charalambos; You, Suya

2009-01-01

The rapid and efficient creation of virtual environments has become a crucial part of virtual reality applications. In particular, civil and defense applications often require and employ detailed models of operations areas for training, simulations of different scenarios, planning for natural or man-made events, monitoring, surveillance, games, and films. A realistic representation of the large-scale environments is therefore imperative for the success of such applications since it increases the immersive experience of its users and helps reduce the difference between physical and virtual reality. However, the task of creating such large-scale virtual environments still remains a time-consuming and manual work. In this work, we propose a novel method for the rapid reconstruction of photorealistic large-scale virtual environments. First, a novel, extendible, parameterized geometric primitive is presented for the automatic building identification and reconstruction of building structures. In addition, buildings with complex roofs containing complex linear and nonlinear surfaces are reconstructed interactively using a linear polygonal and a nonlinear primitive, respectively. Second, we present a rendering pipeline for the composition of photorealistic textures, which unlike existing techniques, can recover missing or occluded texture information by integrating multiple information captured from different optical sensors (ground, aerial, and satellite).

Prototype Vector Machine for Large Scale Semi-Supervised Learning

Energy Technology Data Exchange (ETDEWEB)

Zhang, Kai; Kwok, James T.; Parvin, Bahram

2009-04-29

Practicaldataminingrarelyfalls exactlyinto the supervisedlearning scenario. Rather, the growing amount of unlabeled data poses a big challenge to large-scale semi-supervised learning (SSL). We note that the computationalintensivenessofgraph-based SSLarises largely from the manifold or graph regularization, which in turn lead to large models that are dificult to handle. To alleviate this, we proposed the prototype vector machine (PVM), a highlyscalable,graph-based algorithm for large-scale SSL. Our key innovation is the use of"prototypes vectors" for effcient approximation on both the graph-based regularizer and model representation. The choice of prototypes are grounded upon two important criteria: they not only perform effective low-rank approximation of the kernel matrix, but also span a model suffering the minimum information loss compared with the complete model. We demonstrate encouraging performance and appealing scaling properties of the PVM on a number of machine learning benchmark data sets.

Problem Solving-Based Experiment untuk Meningkatkan Keterampilan Penalaran Ilmiah Mahasiswa Fisika

Directory of Open Access Journals (Sweden)

Muhamad Gina Nugraha

2017-12-01

Full Text Available Abstract As one of the foundations in the development of technology, physics must be supported by experimental activities that are able to develop a scientist's skills, such as scientific reasoning skills. Experiments with cookbook methods that have been conducted in various experimental activities are considered not able to maximize the potential of students because it does not provide wide opportunities for students to explore. One of the solutions to develop the scientific reasoning skills of physics students is the problem solving-based experiment approach. The research was conducted by one group pretest-posstest design to 20 physics students as research sample. The research instrument used is the scientific reasoning instrument test developed by Lawson which is known as Lawson Classroom Test of Scientific Reasoning (LCTSR and student work sheet instrument (LKM containing problems in daily life and questions about: tools and materials, prediction, exploration, measurement, analysis and conclusions. The results show all aspects of scientific reasoning being measured, i.e. 1 conservation of matter and volume, 2 proportional thinking, 3 identification and control of variables, 4 probabilistic thinking, 5 correlative thinking, and 6 hypothetic-deductive thinking has increased. Based on the result of research can be concluded that the problem solving-based experiment can improve the scientific reasoning skills of physics students. Keywords: Problem solving, experiment, scientific reasoning skills Abstrak Fisika sebagai salah satu pondasi ilmu dalam perkembangan teknologi harus didukung dengan kegiatan eksperimen yang mampu menumbuhkembangkan keterampilan seorang ilmuwan, diantaranya keterampilan penalaran ilmiah dalam menyikapi fenomena alam. Eksperimen dengan metode cookbook yang selama ini menjamur dalam berbagai kegiatan eksperimen dipandang tidak mampu memaksimalkan potensi mahasiswa karena tidak memberikan kesempatan yang luas kepada

Data and performance profiles applying an adaptive truncation criterion, within linesearch-based truncated Newton methods, in large scale nonconvex optimization

Directory of Open Access Journals (Sweden)

Andrea Caliciotti

2018-04-01

Full Text Available In this paper, we report data and experiments related to the research article entitled “An adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale nonconvex optimization” by Caliciotti et al. [1]. In particular, in Caliciotti et al. [1], large scale unconstrained optimization problems are considered by applying linesearch-based truncated Newton methods. In this framework, a key point is the reduction of the number of inner iterations needed, at each outer iteration, to approximately solving the Newton equation. A novel adaptive truncation criterion is introduced in Caliciotti et al. [1] to this aim. Here, we report the details concerning numerical experiences over a commonly used test set, namely CUTEst (Gould et al., 2015 [2]. Moreover, comparisons are reported in terms of performance profiles (Dolan and Moré, 2002 [3], adopting different parameters settings. Finally, our linesearch-based scheme is compared with a renowned trust region method, namely TRON (Lin and Moré, 1999 [4].

Can I solve my structure by SAD phasing? Planning an experiment, scaling data and evaluating the useful anomalous correlation and anomalous signal.

Science.gov (United States)

Terwilliger, Thomas C; Bunkóczi, Gábor; Hung, Li Wei; Zwart, Peter H; Smith, Janet L; Akey, David L; Adams, Paul D

2016-03-01

A key challenge in the SAD phasing method is solving a structure when the anomalous signal-to-noise ratio is low. Here, algorithms and tools for evaluating and optimizing the useful anomalous correlation and the anomalous signal in a SAD experiment are described. A simple theoretical framework [Terwilliger et al. (2016), Acta Cryst. D72, 346-358] is used to develop methods for planning a SAD experiment, scaling SAD data sets and estimating the useful anomalous correlation and anomalous signal in a SAD data set. The phenix.plan_sad_experiment tool uses a database of solved and unsolved SAD data sets and the expected characteristics of a SAD data set to estimate the probability that the anomalous substructure will be found in the SAD experiment and the expected map quality that would be obtained if the substructure were found. The phenix.scale_and_merge tool scales unmerged SAD data from one or more crystals using local scaling and optimizes the anomalous signal by identifying the systematic differences among data sets, and the phenix.anomalous_signal tool estimates the useful anomalous correlation and anomalous signal after collecting SAD data and estimates the probability that the data set can be solved and the likely figure of merit of phasing.

The Development of Complex Problem Solving in Adolescence: A Latent Growth Curve Analysis

Science.gov (United States)

Frischkorn, Gidon T.; Greiff, Samuel; Wüstenberg, Sascha

2014-01-01

Complex problem solving (CPS) as a cross-curricular competence has recently attracted more attention in educational psychology as indicated by its implementation in international educational large-scale assessments such as the Programme for International Student Assessment. However, research on the development of CPS is scarce, and the few…

Bayesian hierarchical model for large-scale covariance matrix estimation.

Science.gov (United States)

Zhu, Dongxiao; Hero, Alfred O

2007-12-01

Many bioinformatics problems implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy due to "overfitting." We cast the large-scale covariance matrix estimation problem into the Bayesian hierarchical model framework, and introduce dependency between covariance parameters. We demonstrate the advantages of our approaches over the traditional approaches using simulations and OMICS data analysis.

Visualization and parallel I/O at extreme scale

International Nuclear Information System (INIS)

Ross, R B; Peterka, T; Shen, H-W; Hong, Y; Ma, K-L; Yu, H; Moreland, K

2008-01-01

In our efforts to solve ever more challenging problems through computational techniques, the scale of our compute systems continues to grow. As we approach petascale, it becomes increasingly important that all the resources in the system be used as efficiently as possible, not just the floating-point units. Because of hardware, software, and usability challenges, storage resources are often one of the most poorly used and performing components of today's compute systems. This situation can be especially true in the case of the analysis phases of scientific workflows. In this paper we discuss the impact of large-scale data on visual analysis operations and examine a collection of approaches to I/O in the visual analysis process. First we examine the performance of volume rendering on a leadership-computing platform and assess the relative cost of I/O, rendering, and compositing operations. Next we analyze the performance implications of eliminating preprocessing from this example workflow. Then we describe a technique that uses data reorganization to improve access times for data-intensive volume rendering

Creating Large Scale Database Servers

International Nuclear Information System (INIS)

Becla, Jacek

2001-01-01

The BaBar experiment at the Stanford Linear Accelerator Center (SLAC) is designed to perform a high precision investigation of the decays of the B-meson produced from electron-positron interactions. The experiment, started in May 1999, will generate approximately 300TB/year of data for 10 years. All of the data will reside in Objectivity databases accessible via the Advanced Multi-threaded Server (AMS). To date, over 70TB of data have been placed in Objectivity/DB, making it one of the largest databases in the world. Providing access to such a large quantity of data through a database server is a daunting task. A full-scale testbed environment had to be developed to tune various software parameters and a fundamental change had to occur in the AMS architecture to allow it to scale past several hundred terabytes of data. Additionally, several protocol extensions had to be implemented to provide practical access to large quantities of data. This paper will describe the design of the database and the changes that we needed to make in the AMS for scalability reasons and how the lessons we learned would be applicable to virtually any kind of database server seeking to operate in the Petabyte region

Creating Large Scale Database Servers

Energy Technology Data Exchange (ETDEWEB)

Becla, Jacek

2001-12-14

The BaBar experiment at the Stanford Linear Accelerator Center (SLAC) is designed to perform a high precision investigation of the decays of the B-meson produced from electron-positron interactions. The experiment, started in May 1999, will generate approximately 300TB/year of data for 10 years. All of the data will reside in Objectivity databases accessible via the Advanced Multi-threaded Server (AMS). To date, over 70TB of data have been placed in Objectivity/DB, making it one of the largest databases in the world. Providing access to such a large quantity of data through a database server is a daunting task. A full-scale testbed environment had to be developed to tune various software parameters and a fundamental change had to occur in the AMS architecture to allow it to scale past several hundred terabytes of data. Additionally, several protocol extensions had to be implemented to provide practical access to large quantities of data. This paper will describe the design of the database and the changes that we needed to make in the AMS for scalability reasons and how the lessons we learned would be applicable to virtually any kind of database server seeking to operate in the Petabyte region.

Large-scale pool fires

Directory of Open Access Journals (Sweden)

Steinhaus Thomas

2007-01-01

Full Text Available A review of research into the burning behavior of large pool fires and fuel spill fires is presented. The features which distinguish such fires from smaller pool fires are mainly associated with the fire dynamics at low source Froude numbers and the radiative interaction with the fire source. In hydrocarbon fires, higher soot levels at increased diameters result in radiation blockage effects around the perimeter of large fire plumes; this yields lower emissive powers and a drastic reduction in the radiative loss fraction; whilst there are simplifying factors with these phenomena, arising from the fact that soot yield can saturate, there are other complications deriving from the intermittency of the behavior, with luminous regions of efficient combustion appearing randomly in the outer surface of the fire according the turbulent fluctuations in the fire plume. Knowledge of the fluid flow instabilities, which lead to the formation of large eddies, is also key to understanding the behavior of large-scale fires. Here modeling tools can be effectively exploited in order to investigate the fluid flow phenomena, including RANS- and LES-based computational fluid dynamics codes. The latter are well-suited to representation of the turbulent motions, but a number of challenges remain with their practical application. Massively-parallel computational resources are likely to be necessary in order to be able to adequately address the complex coupled phenomena to the level of detail that is necessary.

Decentralised stabilising controllers for a class of large-scale linear ...

Indian Academy of Sciences (India)

subsystems resulting from a new aggregation-decomposition technique. The method has been illustrated through a numerical example of a large-scale linear system consisting of three subsystems each of the fourth order. Keywords. Decentralised stabilisation; large-scale linear systems; optimal feedback control; algebraic ...

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY15 Q4.

Energy Technology Data Exchange (ETDEWEB)

Moreland, Kenneth D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sewell, Christopher [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Childs, Hank [Univ. of Oregon, Eugene, OR (United States); Ma, Kwan-Liu [Univ. of California, Davis, CA (United States); Geveci, Berk [Kitware, Inc., Clifton Park, NY (United States); Meredith, Jeremy [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2015-12-01

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Mid-year report FY17 Q2

Energy Technology Data Exchange (ETDEWEB)

Moreland, Kenneth D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pugmire, David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Rogers, David [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Childs, Hank [Univ. of Oregon, Eugene, OR (United States); Ma, Kwan-Liu [Univ. of California, Davis, CA (United States); Geveci, Berk [Kitware Inc., Clifton Park, NY (United States)

2017-05-01

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem. Mid-year report FY16 Q2

Energy Technology Data Exchange (ETDEWEB)

Moreland, Kenneth D.; Sewell, Christopher (LANL); Childs, Hank (U of Oregon); Ma, Kwan-Liu (UC Davis); Geveci, Berk (Kitware); Meredith, Jeremy (ORNL)

2016-05-01

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

Large Scale Computing and Storage Requirements for High Energy Physics

International Nuclear Information System (INIS)

Gerber, Richard A.; Wasserman, Harvey

2010-01-01

The National Energy Research Scientific Computing Center (NERSC) is the leading scientific computing facility for the Department of Energy's Office of Science, providing high-performance computing (HPC) resources to more than 3,000 researchers working on about 400 projects. NERSC provides large-scale computing resources and, crucially, the support and expertise needed for scientists to make effective use of them. In November 2009, NERSC, DOE's Office of Advanced Scientific Computing Research (ASCR), and DOE's Office of High Energy Physics (HEP) held a workshop to characterize the HPC resources needed at NERSC to support HEP research through the next three to five years. The effort is part of NERSC's legacy of anticipating users needs and deploying resources to meet those demands. The workshop revealed several key points, in addition to achieving its goal of collecting and characterizing computing requirements. The chief findings: (1) Science teams need access to a significant increase in computational resources to meet their research goals; (2) Research teams need to be able to read, write, transfer, store online, archive, analyze, and share huge volumes of data; (3) Science teams need guidance and support to implement their codes on future architectures; and (4) Projects need predictable, rapid turnaround of their computational jobs to meet mission-critical time constraints. This report expands upon these key points and includes others. It also presents a number of case studies as representative of the research conducted within HEP. Workshop participants were asked to codify their requirements in this case study format, summarizing their science goals, methods of solution, current and three-to-five year computing requirements, and software and support needs. Participants were also asked to describe their strategy for computing in the highly parallel, multi-core environment that is expected to dominate HPC architectures over the next few years. The report includes

Large Scale Survey Data in Career Development Research

Science.gov (United States)

Diemer, Matthew A.

2008-01-01

Large scale survey datasets have been underutilized but offer numerous advantages for career development scholars, as they contain numerous career development constructs with large and diverse samples that are followed longitudinally. Constructs such as work salience, vocational expectations, educational expectations, work satisfaction, and…

Large-scale multielectrode recording and stimulation of neural activity

International Nuclear Information System (INIS)

Sher, A.; Chichilnisky, E.J.; Dabrowski, W.; Grillo, A.A.; Grivich, M.; Gunning, D.; Hottowy, P.; Kachiguine, S.; Litke, A.M.; Mathieson, K.; Petrusca, D.

2007-01-01

Large circuits of neurons are employed by the brain to encode and process information. How this encoding and processing is carried out is one of the central questions in neuroscience. Since individual neurons communicate with each other through electrical signals (action potentials), the recording of neural activity with arrays of extracellular electrodes is uniquely suited for the investigation of this question. Such recordings provide the combination of the best spatial (individual neurons) and temporal (individual action-potentials) resolutions compared to other large-scale imaging methods. Electrical stimulation of neural activity in turn has two very important applications: it enhances our understanding of neural circuits by allowing active interactions with them, and it is a basis for a large variety of neural prosthetic devices. Until recently, the state-of-the-art in neural activity recording systems consisted of several dozen electrodes with inter-electrode spacing ranging from tens to hundreds of microns. Using silicon microstrip detector expertise acquired in the field of high-energy physics, we created a unique neural activity readout and stimulation framework that consists of high-density electrode arrays, multi-channel custom-designed integrated circuits, a data acquisition system, and data-processing software. Using this framework we developed a number of neural readout and stimulation systems: (1) a 512-electrode system for recording the simultaneous activity of as many as hundreds of neurons, (2) a 61-electrode system for electrical stimulation and readout of neural activity in retinas and brain-tissue slices, and (3) a system with telemetry capabilities for recording neural activity in the intact brain of awake, naturally behaving animals. We will report on these systems, their various applications to the field of neurobiology, and novel scientific results obtained with some of them. We will also outline future directions

Similitude and scaling of large structural elements: Case study

Directory of Open Access Journals (Sweden)

M. Shehadeh

2015-06-01

Full Text Available Scaled down models are widely used for experimental investigations of large structures due to the limitation in the capacities of testing facilities along with the expenses of the experimentation. The modeling accuracy depends upon the model material properties, fabrication accuracy and loading techniques. In the present work the Buckingham π theorem is used to develop the relations (i.e. geometry, loading and properties between the model and a large structural element as that is present in the huge existing petroleum oil drilling rigs. The model is to be designed, loaded and treated according to a set of similitude requirements that relate the model to the large structural element. Three independent scale factors which represent three fundamental dimensions, namely mass, length and time need to be selected for designing the scaled down model. Numerical prediction of the stress distribution within the model and its elastic deformation under steady loading is to be made. The results are compared with those obtained from the full scale structure numerical computations. The effect of scaled down model size and material on the accuracy of the modeling technique is thoroughly examined.

Large-scale Assessment Yields Evidence of Minimal Use of Reasoning Skills in Traditionally Taught Classes

Science.gov (United States)

Thacker, Beth

2017-01-01

Large-scale assessment data from Texas Tech University yielded evidence that most students taught traditionally in large lecture classes with online homework and predominantly multiple choice question exams, when asked to answer free-response (FR) questions, did not support their answers with logical arguments grounded in physics concepts. In addition to a lack of conceptual understanding, incorrect and partially correct answers lacked evidence of the ability to apply even lower level reasoning skills in order to solve a problem. Correct answers, however, did show evidence of at least lower level thinking skills as coded using a rubric based on Bloom's taxonomy. With the introduction of evidence-based instruction into the labs and recitations of the large courses and in a small, completely laboratory-based, hands-on course, the percentage of correct answers with correct explanations increased. The FR format, unlike other assessment formats, allowed assessment of both conceptual understanding and the application of thinking skills, clearly pointing out weaknesses not revealed by other assessment instruments, and providing data on skills beyond conceptual understanding for course and program assessment. Supported by National Institutes of Health (NIH) Challenge grant #1RC1GM090897-01.

Large-scale preparation of hollow graphitic carbon nanospheres

Energy Technology Data Exchange (ETDEWEB)

Feng, Jun; Li, Fu [Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials, Ministry of Education, Shandong University, Jinan 250061 (China); Bai, Yu-Jun, E-mail: byj97@126.com [Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials, Ministry of Education, Shandong University, Jinan 250061 (China); State Key laboratory of Crystal Materials, Shandong University, Jinan 250100 (China); Han, Fu-Dong; Qi, Yong-Xin; Lun, Ning [Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials, Ministry of Education, Shandong University, Jinan 250061 (China); Lu, Xi-Feng [Lunan Institute of Coal Chemical Engineering, Jining 272000 (China)

2013-01-15

Hollow graphitic carbon nanospheres (HGCNSs) were synthesized on large scale by a simple reaction between glucose and Mg at 550 Degree-Sign C in an autoclave. Characterization by X-ray diffraction, Raman spectroscopy and transmission electron microscopy demonstrates the formation of HGCNSs with an average diameter of 10 nm or so and a wall thickness of a few graphenes. The HGCNSs exhibit a reversible capacity of 391 mAh g{sup -1} after 60 cycles when used as anode materials for Li-ion batteries. -- Graphical abstract: Hollow graphitic carbon nanospheres could be prepared on large scale by the simple reaction between glucose and Mg at 550 Degree-Sign C, which exhibit superior electrochemical performance to graphite. Highlights: Black-Right-Pointing-Pointer Hollow graphitic carbon nanospheres (HGCNSs) were prepared on large scale at 550 Degree-Sign C Black-Right-Pointing-Pointer The preparation is simple, effective and eco-friendly. Black-Right-Pointing-Pointer The in situ yielded MgO nanocrystals promote the graphitization. Black-Right-Pointing-Pointer The HGCNSs exhibit superior electrochemical performance to graphite.

Large-scale impact cratering on the terrestrial planets

International Nuclear Information System (INIS)

Grieve, R.A.F.

1982-01-01

The crater densities on the earth and moon form the basis for a standard flux-time curve that can be used in dating unsampled planetary surfaces and constraining the temporal history of endogenic geologic processes. Abundant evidence is seen not only that impact cratering was an important surface process in planetary history but also that large imapact events produced effects that were crucial in scale. By way of example, it is noted that the formation of multiring basins on the early moon was as important in defining the planetary tectonic framework as plate tectonics is on the earth. Evidence from several planets suggests that the effects of very-large-scale impacts go beyond the simple formation of an impact structure and serve to localize increased endogenic activity over an extended period of geologic time. Even though no longer occurring with the frequency and magnitude of early solar system history, it is noted that large scale impact events continue to affect the local geology of the planets. 92 references

Optical interconnect for large-scale systems

Science.gov (United States)

Dress, William

2013-02-01

This paper presents a switchless, optical interconnect module that serves as a node in a network of identical distribution modules for large-scale systems. Thousands to millions of hosts or endpoints may be interconnected by a network of such modules, avoiding the need for multi-level switches. Several common network topologies are reviewed and their scaling properties assessed. The concept of message-flow routing is discussed in conjunction with the unique properties enabled by the optical distribution module where it is shown how top-down software control (global routing tables, spanning-tree algorithms) may be avoided.

Implementation of exterior complex scaling in B-splines to solve atomic and molecular collision problems

International Nuclear Information System (INIS)

McCurdy, C William; MartIn, Fernando

2004-01-01

B-spline methods are now well established as widely applicable tools for the evaluation of atomic and molecular continuum states. The mathematical technique of exterior complex scaling has been shown, in a variety of other implementations, to be a powerful method with which to solve atomic and molecular scattering problems, because it allows the correct imposition of continuum boundary conditions without their explicit analytic application. In this paper, an implementation of exterior complex scaling in B-splines is described that can bring the well-developed technology of B-splines to bear on new problems, including multiple ionization and breakup problems, in a straightforward way. The approach is demonstrated for examples involving the continuum motion of nuclei in diatomic molecules as well as electronic continua. For problems involving electrons, a method based on Poisson's equation is presented for computing two-electron integrals over B-splines under exterior complex scaling

[A large-scale accident in Alpine terrain].

Science.gov (United States)

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.

Three-M in Word Problem Solving

Science.gov (United States)

Hajra, Sayonita Ghosh; Kofman, Victoria

2018-01-01

We describe three activities that help undergraduates (pre-service teachers) to develop scientific vocabulary on measurable attributes and units of measurement. Measurable attributes are important features in understanding a word problem and solving the problem. These activities help students comprehend word problems better by identifying…

Hierarchical Cantor set in the large scale structure with torus geometry

Energy Technology Data Exchange (ETDEWEB)

Murdzek, R. [Physics Department, ' Al. I. Cuza' University, Blvd. Carol I, Nr. 11, Iassy 700506 (Romania)], E-mail: rmurdzek@yahoo.com

2008-12-15

The formation of large scale structures is considered within a model with string on toroidal space-time. Firstly, the space-time geometry is presented. In this geometry, the Universe is represented by a string describing a torus surface. Thereafter, the large scale structure of the Universe is derived from the string oscillations. The results are in agreement with the cellular structure of the large scale distribution and with the theory of a Cantorian space-time.

Commercial applications of large-scale Research and Development computer simulation technologies

International Nuclear Information System (INIS)

Kuok Mee Ling; Pascal Chen; Wen Ho Lee

1998-01-01

The potential commercial applications of two large-scale R and D computer simulation technologies are presented. One such technology is based on the numerical solution of the hydrodynamics equations, and is embodied in the two-dimensional Eulerian code EULE2D, which solves the hydrodynamic equations with various models for the equation of state (EOS), constitutive relations and fracture mechanics. EULE2D is an R and D code originally developed to design and analyze conventional munitions for anti-armor penetrations such as shaped charges, explosive formed projectiles, and kinetic energy rods. Simulated results agree very well with actual experiments. A commercial application presented here is the design and simulation of shaped charges for oil and gas well bore perforation. The other R and D simulation technology is based on the numerical solution of Maxwell's partial differential equations of electromagnetics in space and time, and is implemented in the three-dimensional code FDTD-SPICE, which solves Maxwell's equations in the time domain with finite-differences in the three spatial dimensions and calls SPICE for information when nonlinear active devices are involved. The FDTD method has been used in the radar cross-section modeling of military aircrafts and many other electromagnetic phenomena. The coupling of FDTD method with SPICE, a popular circuit and device simulation program, provides a powerful tool for the simulation and design of microwave and millimeter-wave circuits containing nonlinear active semiconductor devices. A commercial application of FDTD-SPICE presented here is the simulation of a two-element active antenna system. The simulation results and the experimental measurements are in excellent agreement. (Author)

Systems Engineering and Safety Issues in Scientific Facilities Subject to Ionizing Radiations

Directory of Open Access Journals (Sweden)

Pierre Bonnal

2013-10-01

Full Text Available The conception and development of large-scale scientific facilities emitting ionizing radiations rely more on project management practices in use in the process industry than on systems engineering practices. This paper aims to highlight possible reasons for this present situation and to propose some ways to enhance systems engineering so that the specific radiation safety requirements are considered and integrated in the approach. To do so, we have reviewed lessons learned from the management of large-scale scientific projects and more specifically that of the Large Hadron Collider project at CERN. It is shown that project management and systems engineering practices are complementary and can beneficially be assembled in an integrated and lean managerial framework that grants the appropriate amount of focus to safety and radiation safety aspects.

Towards a Database System for Large-scale Analytics on Strings

KAUST Repository

Sahli, Majed A.

2015-07-23

Recent technological advances are causing an explosion in the production of sequential data. Biological sequences, web logs and time series are represented as strings. Currently, strings are stored, managed and queried in an ad-hoc fashion because they lack a standardized data model and query language. String queries are computationally demanding, especially when strings are long and numerous. Existing approaches cannot handle the growing number of strings produced by environmental, healthcare, bioinformatic, and space applications. There is a trade- off between performing analytics efficiently and scaling to thousands of cores to finish in reasonable times. In this thesis, we introduce a data model that unifies the input and output representations of core string operations. We define a declarative query language for strings where operators can be pipelined to form complex queries. A rich set of core string operators is described to support string analytics. We then demonstrate a database system for string analytics based on our model and query language. In particular, we propose the use of a novel data structure augmented by efficient parallel computation to strike a balance between preprocessing overheads and query execution times. Next, we delve into repeated motifs extraction as a core string operation for large-scale string analytics. Motifs are frequent patterns used, for example, to identify biological functionality, periodic trends, or malicious activities. Statistical approaches are fast but inexact while combinatorial methods are sound but slow. We introduce ACME, a combinatorial repeated motifs extractor. We study the spatial and temporal locality of motif extraction and devise a cache-aware search space traversal technique. ACME is the only method that scales to gigabyte- long strings, handles large alphabets, and supports interesting motif types with minimal overhead. While ACME is cache-efficient, it is limited by being serial. We devise a lightweight

Could HPS Improve Problem-Solving?

Science.gov (United States)

Coelho, Ricardo Lopes

2013-05-01

It is generally accepted nowadays that History and Philosophy of Science (HPS) is useful in understanding scientific concepts, theories and even some experiments. Problem-solving strategies are a significant topic, since students' careers depend on their skill to solve problems. These are the reasons for addressing the question of whether problem solving could be improved by means of HPS. Three typical problems in introductory courses of mechanics—the inclined plane, the simple pendulum and the Atwood machine—are taken as the object of the present study. The solving strategies of these problems in the eighteenth and nineteenth century constitute the historical component of the study. Its philosophical component stems from the foundations of mechanics research literature. The use of HPS leads us to see those problems in a different way. These different ways can be tested, for which experiments are proposed. The traditional solving strategies for the incline and pendulum problems are adequate for some situations but not in general. The recourse to apparent weights in the Atwood machine problem leads us to a new insight and a solving strategy for composed Atwood machines. Educational implications also concern the development of logical thinking by means of the variety of lines of thought provided by HPS.

Large-scale Motion of Solar Filaments

Indian Academy of Sciences (India)

tribpo

Large-scale Motion of Solar Filaments. Pavel Ambrož, Astronomical Institute of the Acad. Sci. of the Czech Republic, CZ-25165. Ondrejov, The Czech Republic. e-mail: pambroz@asu.cas.cz. Alfred Schroll, Kanzelhöehe Solar Observatory of the University of Graz, A-9521 Treffen,. Austria. e-mail: schroll@solobskh.ac.at.

Sensitivity analysis for large-scale problems

Science.gov (United States)

Noor, Ahmed K.; Whitworth, Sandra L.

1987-01-01

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

The Cosmology Large Angular Scale Surveyor

Science.gov (United States)

Harrington, Kathleen; Marriage, Tobias; Ali, Aamir; Appel, John; Bennett, Charles; Boone, Fletcher; Brewer, Michael; Chan, Manwei; Chuss, David T.; Colazo, Felipe;

Prehospital Acute Stroke Severity Scale to Predict Large Artery Occlusion: Design and Comparison With Other Scales.

Science.gov (United States)

Hastrup, Sidsel; Damgaard, Dorte; Johnsen, Søren Paaske; Andersen, Grethe

2016-07-01

We designed and validated a simple prehospital stroke scale to identify emergent large vessel occlusion (ELVO) in patients with acute ischemic stroke and compared the scale to other published scales for prediction of ELVO. A national historical test cohort of 3127 patients with information on intracranial vessel status (angiography) before reperfusion therapy was identified. National Institutes of Health Stroke Scale (NIHSS) items with the highest predictive value of occlusion of a large intracranial artery were identified, and the most optimal combination meeting predefined criteria to ensure usefulness in the prehospital phase was determined. The predictive performance of Prehospital Acute Stroke Severity (PASS) scale was compared with other published scales for ELVO. The PASS scale was composed of 3 NIHSS scores: level of consciousness (month/age), gaze palsy/deviation, and arm weakness. In derivation of PASS 2/3 of the test cohort was used and showed accuracy (area under the curve) of 0.76 for detecting large arterial occlusion. Optimal cut point ≥2 abnormal scores showed: sensitivity=0.66 (95% CI, 0.62-0.69), specificity=0.83 (0.81-0.85), and area under the curve=0.74 (0.72-0.76). Validation on 1/3 of the test cohort showed similar performance. Patients with a large artery occlusion on angiography with PASS ≥2 had a median NIHSS score of 17 (interquartile range=6) as opposed to PASS <2 with a median NIHSS score of 6 (interquartile range=5). The PASS scale showed equal performance although more simple when compared with other scales predicting ELVO. The PASS scale is simple and has promising accuracy for prediction of ELVO in the field. © 2016 American Heart Association, Inc.

Analysis using large-scale ringing data

Directory of Open Access Journals (Sweden)

Baillie, S. R.

2004-06-01

Full Text Available Birds are highly mobile organisms and there is increasing evidence that studies at large spatial scales are needed if we are to properly understand their population dynamics. While classical metapopulation models have rarely proved useful for birds, more general metapopulation ideas involving collections of populations interacting within spatially structured landscapes are highly relevant (Harrison, 1994. There is increasing interest in understanding patterns of synchrony, or lack of synchrony, between populations and the environmental and dispersal mechanisms that bring about these patterns (Paradis et al., 2000. To investigate these processes we need to measure abundance, demographic rates and dispersal at large spatial scales, in addition to gathering data on relevant environmental variables. There is an increasing realisation that conservation needs to address rapid declines of common and widespread species (they will not remain so if such trends continue as well as the management of small populations that are at risk of extinction. While the knowledge needed to support the management of small populations can often be obtained from intensive studies in a few restricted areas, conservation of widespread species often requires information on population trends and processes measured at regional, national and continental scales (Baillie, 2001. While management prescriptions for widespread populations may initially be developed from a small number of local studies or experiments, there is an increasing need to understand how such results will scale up when applied across wider areas. There is also a vital role for monitoring at large spatial scales both in identifying such population declines and in assessing population recovery. Gathering data on avian abundance and demography at large spatial scales usually relies on the efforts of large numbers of skilled volunteers. Volunteer studies based on ringing (for example Constant Effort Sites [CES

Collaborative Visualization for Large-Scale Accelerator Electromagnetic Modeling (Final Report)

International Nuclear Information System (INIS)

Schroeder, William J.

2011-01-01

This report contains the comprehensive summary of the work performed on the SBIR Phase II, Collaborative Visualization for Large-Scale Accelerator Electromagnetic Modeling at Kitware Inc. in collaboration with Stanford Linear Accelerator Center (SLAC). The goal of the work was to develop collaborative visualization tools for large-scale data as illustrated in the figure below. The solutions we proposed address the typical problems faced by geographicallyand organizationally-separated research and engineering teams, who produce large data (either through simulation or experimental measurement) and wish to work together to analyze and understand their data. Because the data is large, we expect that it cannot be easily transported to each team member's work site, and that the visualization server must reside near the data. Further, we also expect that each work site has heterogeneous resources: some with large computing clients, tiled (or large) displays and high bandwidth; others sites as simple as a team member on a laptop computer. Our solution is based on the open-source, widely used ParaView large-data visualization application. We extended this tool to support multiple collaborative clients who may locally visualize data, and then periodically rejoin and synchronize with the group to discuss their findings. Options for managing session control, adding annotation, and defining the visualization pipeline, among others, were incorporated. We also developed and deployed a Web visualization framework based on ParaView that enables the Web browser to act as a participating client in a collaborative session. The ParaView Web Visualization framework leverages various Web technologies including WebGL, JavaScript, Java and Flash to enable interactive 3D visualization over the web using ParaView as the visualization server. We steered the development of this technology by teaming with the SLAC National Accelerator Laboratory. SLAC has a computationally-intensive problem

Collaborative Visualization for Large-Scale Accelerator Electromagnetic Modeling (Final Report)

Energy Technology Data Exchange (ETDEWEB)

William J. Schroeder

2011-11-13

This report contains the comprehensive summary of the work performed on the SBIR Phase II, Collaborative Visualization for Large-Scale Accelerator Electromagnetic Modeling at Kitware Inc. in collaboration with Stanford Linear Accelerator Center (SLAC). The goal of the work was to develop collaborative visualization tools for large-scale data as illustrated in the figure below. The solutions we proposed address the typical problems faced by geographicallyand organizationally-separated research and engineering teams, who produce large data (either through simulation or experimental measurement) and wish to work together to analyze and understand their data. Because the data is large, we expect that it cannot be easily transported to each team member's work site, and that the visualization server must reside near the data. Further, we also expect that each work site has heterogeneous resources: some with large computing clients, tiled (or large) displays and high bandwidth; others sites as simple as a team member on a laptop computer. Our solution is based on the open-source, widely used ParaView large-data visualization application. We extended this tool to support multiple collaborative clients who may locally visualize data, and then periodically rejoin and synchronize with the group to discuss their findings. Options for managing session control, adding annotation, and defining the visualization pipeline, among others, were incorporated. We also developed and deployed a Web visualization framework based on ParaView that enables the Web browser to act as a participating client in a collaborative session. The ParaView Web Visualization framework leverages various Web technologies including WebGL, JavaScript, Java and Flash to enable interactive 3D visualization over the web using ParaView as the visualization server. We steered the development of this technology by teaming with the SLAC National Accelerator Laboratory. SLAC has a computationally

A Low Collision and High Throughput Data Collection Mechanism for Large-Scale Super Dense Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Chunyang Lei

2016-07-01

Full Text Available Super dense wireless sensor networks (WSNs have become popular with the development of Internet of Things (IoT, Machine-to-Machine (M2M communications and Vehicular-to-Vehicular (V2V networks. While highly-dense wireless networks provide efficient and sustainable solutions to collect precise environmental information, a new channel access scheme is needed to solve the channel collision problem caused by the large number of competing nodes accessing the channel simultaneously. In this paper, we propose a space-time random access method based on a directional data transmission strategy, by which collisions in the wireless channel are significantly decreased and channel utility efficiency is greatly enhanced. Simulation results show that our proposed method can decrease the packet loss rate to less than 2 % in large scale WSNs and in comparison with other channel access schemes for WSNs, the average network throughput can be doubled.

A Low Collision and High Throughput Data Collection Mechanism for Large-Scale Super Dense Wireless Sensor Networks.

Science.gov (United States)

Lei, Chunyang; Bie, Hongxia; Fang, Gengfa; Gaura, Elena; Brusey, James; Zhang, Xuekun; Dutkiewicz, Eryk

2016-07-18

Super dense wireless sensor networks (WSNs) have become popular with the development of Internet of Things (IoT), Machine-to-Machine (M2M) communications and Vehicular-to-Vehicular (V2V) networks. While highly-dense wireless networks provide efficient and sustainable solutions to collect precise environmental information, a new channel access scheme is needed to solve the channel collision problem caused by the large number of competing nodes accessing the channel simultaneously. In this paper, we propose a space-time random access method based on a directional data transmission strategy, by which collisions in the wireless channel are significantly decreased and channel utility efficiency is greatly enhanced. Simulation results show that our proposed method can decrease the packet loss rate to less than 2 % in large scale WSNs and in comparison with other channel access schemes for WSNs, the average network throughput can be doubled.

Fast Simulation of Large-Scale Floods Based on GPU Parallel Computing

OpenAIRE

Qiang Liu; Yi Qin; Guodong Li

2018-01-01

Computing speed is a significant issue of large-scale flood simulations for real-time response to disaster prevention and mitigation. Even today, most of the large-scale flood simulations are generally run on supercomputers due to the massive amounts of data and computations necessary. In this work, a two-dimensional shallow water model based on an unstructured Godunov-type finite volume scheme was proposed for flood simulation. To realize a fast simulation of large-scale floods on a personal...

Managing Risk and Uncertainty in Large-Scale University Research Projects

Science.gov (United States)

Moore, Sharlissa; Shangraw, R. F., Jr.

2011-01-01

Both publicly and privately funded research projects managed by universities are growing in size and scope. Complex, large-scale projects (over $50 million) pose new management challenges and risks for universities. This paper explores the relationship between project success and a variety of factors in large-scale university projects. First, we…

Parallel clustering algorithm for large-scale biological data sets.

Science.gov (United States)

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

2014-01-01

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

Large Scale Simulation of Hydrogen Dispersion by a Stabilized Balancing Domain Decomposition Method

Directory of Open Access Journals (Sweden)

Qing-He Yao

2014-01-01

Full Text Available The dispersion behaviour of leaking hydrogen in a partially open space is simulated by a balancing domain decomposition method in this work. An analogy of the Boussinesq approximation is employed to describe the connection between the flow field and the concentration field. The linear systems of Navier-Stokes equations and the convection diffusion equation are symmetrized by a pressure stabilized Lagrange-Galerkin method, and thus a balancing domain decomposition method is enabled to solve the interface problem of the domain decomposition system. Numerical results are validated by comparing with the experimental data and available numerical results. The dilution effect of ventilation is investigated, especially at the doors, where flow pattern is complicated and oscillations appear in the past research reported by other researchers. The transient behaviour of hydrogen and the process of accumulation in the partially open space are discussed, and more details are revealed by large scale computation.

Coarse-Grain Bandwidth Estimation Scheme for Large-Scale Network

Science.gov (United States)

Cheung, Kar-Ming; Jennings, Esther H.; Sergui, John S.

2013-01-01

A large-scale network that supports a large number of users can have an aggregate data rate of hundreds of Mbps at any time. High-fidelity simulation of a large-scale network might be too complicated and memory-intensive for typical commercial-off-the-shelf (COTS) tools. Unlike a large commercial wide-area-network (WAN) that shares diverse network resources among diverse users and has a complex topology that requires routing mechanism and flow control, the ground communication links of a space network operate under the assumption of a guaranteed dedicated bandwidth allocation between specific sparse endpoints in a star-like topology. This work solved the network design problem of estimating the bandwidths of a ground network architecture option that offer different service classes to meet the latency requirements of different user data types. In this work, a top-down analysis and simulation approach was created to size the bandwidths of a store-and-forward network for a given network topology, a mission traffic scenario, and a set of data types with different latency requirements. These techniques were used to estimate the WAN bandwidths of the ground links for different architecture options of the proposed Integrated Space Communication and Navigation (SCaN) Network. A new analytical approach, called the "leveling scheme," was developed to model the store-and-forward mechanism of the network data flow. The term "leveling" refers to the spreading of data across a longer time horizon without violating the corresponding latency requirement of the data type. Two versions of the leveling scheme were developed: 1. A straightforward version that simply spreads the data of each data type across the time horizon and doesn't take into account the interactions among data types within a pass, or between data types across overlapping passes at a network node, and is inherently sub-optimal. 2. Two-state Markov leveling scheme that takes into account the second order behavior of

Improving extreme-scale problem solving: assessing electronic brainstorming effectiveness in an industrial setting.

Science.gov (United States)

Dornburg, Courtney C; Stevens, Susan M; Hendrickson, Stacey M L; Davidson, George S

2009-08-01

An experiment was conducted to compare the effectiveness of individual versus group electronic brainstorming to address difficult, real-world challenges. Although industrial reliance on electronic communications has become ubiquitous, empirical and theoretical understanding of the bounds of its effectiveness have been limited. Previous research using short-term laboratory experiments have engaged small groups of students in answering questions irrelevant to an industrial setting. The present experiment extends current findings beyond the laboratory to larger groups of real-world employees addressing organization-relevant challenges during the course of 4 days. Employees and contractors at a national laboratory participated, either in a group setting or individually, in an electronic brainstorm to pose solutions to a real-world problem. The data demonstrate that (for this design) individuals perform at least as well as groups in producing quantity of electronic ideas, regardless of brainstorming duration. However, when judged with respect to quality along three dimensions (originality, feasibility, and effectiveness), the individuals significantly (p industrial reliance on electronic problem-solving groups should be tempered, and large nominal groups may be more appropriate corporate problem-solving vehicles.

Oligopolistic competition in wholesale electricity markets: Large-scale simulation and policy analysis using complementarity models

Science.gov (United States)

Helman, E. Udi

This dissertation conducts research into the large-scale simulation of oligopolistic competition in wholesale electricity markets. The dissertation has two parts. Part I is an examination of the structure and properties of several spatial, or network, equilibrium models of oligopolistic electricity markets formulated as mixed linear complementarity problems (LCP). Part II is a large-scale application of such models to the electricity system that encompasses most of the United States east of the Rocky Mountains, the Eastern Interconnection. Part I consists of Chapters 1 to 6. The models developed in this part continue research into mixed LCP models of oligopolistic electricity markets initiated by Hobbs [67] and subsequently developed by Metzler [87] and Metzler, Hobbs and Pang [88]. Hobbs' central contribution is a network market model with Cournot competition in generation and a price-taking spatial arbitrage firm that eliminates spatial price discrimination by the Cournot firms. In one variant, the solution to this model is shown to be equivalent to the "no arbitrage" condition in a "pool" market, in which a Regional Transmission Operator optimizes spot sales such that the congestion price between two locations is exactly equivalent to the difference in the energy prices at those locations (commonly known as locational marginal pricing). Extensions to this model are presented in Chapters 5 and 6. One of these is a market model with a profit-maximizing arbitrage firm. This model is structured as a mathematical program with equilibrium constraints (MPEC), but due to the linearity of its constraints, can be solved as a mixed LCP. Part II consists of Chapters 7 to 12. The core of these chapters is a large-scale simulation of the U.S. Eastern Interconnection applying one of the Cournot competition with arbitrage models. This is the first oligopolistic equilibrium market model to encompass the full Eastern Interconnection with a realistic network representation (using

Multimode Resource-Constrained Multiple Project Scheduling Problem under Fuzzy Random Environment and Its Application to a Large Scale Hydropower Construction Project

Science.gov (United States)

Xu, Jiuping

2014-01-01

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method. PMID:24550708

Multimode resource-constrained multiple project scheduling problem under fuzzy random environment and its application to a large scale hydropower construction project.

Science.gov (United States)

Xu, Jiuping; Feng, Cuiying

2014-01-01

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method.

Scientific developments ISFD3

Science.gov (United States)

Schropp, M.H.I.; Soong, T.W.

2006-01-01

Highlights, trends, and consensus from the 63 papers submitted to the Scientific Developments theme of the Third International Symposium on Flood Defence (ISFD) are presented. Realizing that absolute protection against flooding can never be guaranteed, trends in flood management have shifted: (1) from flood protection to flood-risk management, (2) from reinforcing structural protection to lowering flood levels, and (3) to sustainable management through integrated problem solving. Improved understanding of watershed responses, climate changes, applications of GIS and remote-sensing technologies, and advanced analytical tools appeared to be the driving forces for renewing flood-risk management strategies. Technical competence in integrating analytical tools to form the basin wide management systems are demonstrated by several large, transnation models. However, analyses from social-economic-environmental points of view are found lag in general. ?? 2006 Taylor & Francis Group.

Adaptive visualization for large-scale graph

International Nuclear Information System (INIS)

Nakamura, Hiroko; Shinano, Yuji; Ohzahata, Satoshi

2010-01-01

We propose an adoptive visualization technique for representing a large-scale hierarchical dataset within limited display space. A hierarchical dataset has nodes and links showing the parent-child relationship between the nodes. These nodes and links are described using graphics primitives. When the number of these primitives is large, it is difficult to recognize the structure of the hierarchical data because many primitives are overlapped within a limited region. To overcome this difficulty, we propose an adaptive visualization technique for hierarchical datasets. The proposed technique selects an appropriate graph style according to the nodal density in each area. (author)

Stabilization Algorithms for Large-Scale Problems

DEFF Research Database (Denmark)

Jensen, Toke Koldborg

2006-01-01

The focus of the project is on stabilization of large-scale inverse problems where structured models and iterative algorithms are necessary for computing approximate solutions. For this purpose, we study various iterative Krylov methods and their abilities to produce regularized solutions. Some......-curve. This heuristic is implemented as a part of a larger algorithm which is developed in collaboration with G. Rodriguez and P. C. Hansen. Last, but not least, a large part of the project has, in different ways, revolved around the object-oriented Matlab toolbox MOORe Tools developed by PhD Michael Jacobsen. New...

The scientific status of fusion

International Nuclear Information System (INIS)

Crandall, D.H.

1989-01-01

The development of fusion energy has been a large-scale scientific undertaking of broad interest. The magnetic plasma containment in tokamaks and the laser-drive ignition of microfusion capsules appear to be scientifically feasible sources of energy. These concepts are bounded by questions of required intensity in magnetid field and plasma currents or in drive energy and, for both concepts, by issues of plasma stability and energy transport. The basic concept and the current scientific issues are described for magnetic fusion and for the interesting, but likely infeasible, muon-catalyzed fusion concept. Inertial fusion is mentioned, qualitatively, to complete the context. For magnetic fusion, the required net energy production within the plasma may be accomplished soon, but the more useful goal of self-sustained plasma ignition requires a new device of somewhat uncertain (factor of 2) cost and size. (orig.)

Designing a solution to enable agency-academic scientific collaboration for disasters

Directory of Open Access Journals (Sweden)

Lindley A. Mease

2017-06-01

Full Text Available As large-scale environmental disasters become increasingly frequent and more severe globally, people and organizations that prepare for and respond to these crises need efficient and effective ways to integrate sound science into their decision making. Experience has shown that integrating nongovernmental scientific expertise into disaster decision making can improve the quality of the response, and is most effective if the integration occurs before, during, and after a crisis, not just during a crisis. However, collaboration between academic, government, and industry scientists, decision makers, and responders is frequently difficult because of cultural differences, misaligned incentives, time pressures, and legal constraints. Our study addressed this challenge by using the Deep Change Method, a design methodology developed by Stanford ChangeLabs, which combines human-centered design, systems analysis, and behavioral psychology. We investigated underlying needs and motivations of government agency staff and academic scientists, mapped the root causes underlying the relationship failures between these two communities based on their experiences, and identified leverage points for shifting deeply rooted perceptions that impede collaboration. We found that building trust and creating mutual value between multiple stakeholders before crises occur is likely to increase the effectiveness of problem solving. We propose a solution, the Science Action Network, which is designed to address barriers to scientific collaboration by providing new mechanisms to build and improve trust and communication between government administrators and scientists, industry representatives, and academic scientists. The Science Action Network has the potential to ensure cross-disaster preparedness and science-based decision making through novel partnerships and scientific coordination.

Designing a solution to enable agency-academic scientific collaboration for disasters

Science.gov (United States)

Mease, Lindley A.; Gibbs-Plessl, Theodora; Erickson, Ashley; Ludwig, Kristin A.; Reddy, Christopher M.; Lubchenco, Jane

2017-01-01

As large-scale environmental disasters become increasingly frequent and more severe globally, people and organizations that prepare for and respond to these crises need efficient and effective ways to integrate sound science into their decision making. Experience has shown that integrating nongovernmental scientific expertise into disaster decision making can improve the quality of the response, and is most effective if the integration occurs before, during, and after a crisis, not just during a crisis. However, collaboration between academic, government, and industry scientists, decision makers, and responders is frequently difficult because of cultural differences, misaligned incentives, time pressures, and legal constraints. Our study addressed this challenge by using the Deep Change Method, a design methodology developed by Stanford ChangeLabs, which combines human-centered design, systems analysis, and behavioral psychology. We investigated underlying needs and motivations of government agency staff and academic scientists, mapped the root causes underlying the relationship failures between these two communities based on their experiences, and identified leverage points for shifting deeply rooted perceptions that impede collaboration. We found that building trust and creating mutual value between multiple stakeholders before crises occur is likely to increase the effectiveness of problem solving. We propose a solution, the Science Action Network, which is designed to address barriers to scientific collaboration by providing new mechanisms to build and improve trust and communication between government administrators and scientists, industry representatives, and academic scientists. The Science Action Network has the potential to ensure cross-disaster preparedness and science-based decision making through novel partnerships and scientific coordination.

Evaluating cloud processes in large-scale models: Of idealized case studies, parameterization testbeds and single-column modelling on climate time-scales

Science.gov (United States)

Neggers, Roel

2016-04-01

Boundary-layer schemes have always formed an integral part of General Circulation Models (GCMs) used for numerical weather and climate prediction. The spatial and temporal scales associated with boundary-layer processes and clouds are typically much smaller than those at which GCMs are discretized, which makes their representation through parameterization a necessity. The need for generally applicable boundary-layer parameterizations has motivated many scientific studies, which in effect has created its own active research field in the atmospheric sciences. Of particular interest has been the evaluation of boundary-layer schemes at "process-level". This means that parameterized physics are studied in isolated mode from the larger-scale circulation, using prescribed forcings and excluding any upscale interaction. Although feedbacks are thus prevented, the benefit is an enhanced model transparency, which might aid an investigator in identifying model errors and understanding model behavior. The popularity and success of the process-level approach is demonstrated by the many past and ongoing model inter-comparison studies that have been organized by initiatives such as GCSS/GASS. A red line in the results of these studies is that although most schemes somehow manage to capture first-order aspects of boundary layer cloud fields, there certainly remains room for improvement in many areas. Only too often are boundary layer parameterizations still found to be at the heart of problems in large-scale models, negatively affecting forecast skills of NWP models or causing uncertainty in numerical predictions of future climate. How to break this parameterization "deadlock" remains an open problem. This presentation attempts to give an overview of the various existing methods for the process-level evaluation of boundary-layer physics in large-scale models. This includes i) idealized case studies, ii) longer-term evaluation at permanent meteorological sites (the testbed approach

Large scale CMB anomalies from thawing cosmic strings

Energy Technology Data Exchange (ETDEWEB)

Ringeval, Christophe [Centre for Cosmology, Particle Physics and Phenomenology, Institute of Mathematics and Physics, Louvain University, 2 Chemin du Cyclotron, 1348 Louvain-la-Neuve (Belgium); Yamauchi, Daisuke; Yokoyama, Jun' ichi [Research Center for the Early Universe (RESCEU), Graduate School of Science, The University of Tokyo, Tokyo 113-0033 (Japan); Bouchet, François R., E-mail: christophe.ringeval@uclouvain.be, E-mail: yamauchi@resceu.s.u-tokyo.ac.jp, E-mail: yokoyama@resceu.s.u-tokyo.ac.jp, E-mail: bouchet@iap.fr [Institut d' Astrophysique de Paris, UMR 7095-CNRS, Université Pierre et Marie Curie, 98bis boulevard Arago, 75014 Paris (France)

2016-02-01

Cosmic strings formed during inflation are expected to be either diluted over super-Hubble distances, i.e., invisible today, or to have crossed our past light cone very recently. We discuss the latter situation in which a few strings imprint their signature in the Cosmic Microwave Background (CMB) Anisotropies after recombination. Being almost frozen in the Hubble flow, these strings are quasi static and evade almost all of the previously derived constraints on their tension while being able to source large scale anisotropies in the CMB sky. Using a local variance estimator on thousand of numerically simulated Nambu-Goto all sky maps, we compute the expected signal and show that it can mimic a dipole modulation at large angular scales while being negligible at small angles. Interestingly, such a scenario generically produces one cold spot from the thawing of a cosmic string loop. Mixed with anisotropies of inflationary origin, we find that a few strings of tension GU = O(1) × 10{sup −6} match the amplitude of the dipole modulation reported in the Planck satellite measurements and could be at the origin of other large scale anomalies.

Environmental Impacts of Large Scale Biochar Application Through Spatial Modeling

Science.gov (United States)

Huber, I.; Archontoulis, S.

2017-12-01

In an effort to study the environmental (emissions, soil quality) and production (yield) impacts of biochar application at regional scales we coupled the APSIM-Biochar model with the pSIMS parallel platform. So far the majority of biochar research has been concentrated on lab to field studies to advance scientific knowledge. Regional scale assessments are highly needed to assist decision making. The overall objective of this simulation study was to identify areas in the USA that have the most gain environmentally from biochar's application, as well as areas which our model predicts a notable yield increase due to the addition of biochar. We present the modifications in both APSIM biochar and pSIMS components that were necessary to facilitate these large scale model runs across several regions in the United States at a resolution of 5 arcminutes. This study uses the AgMERRA global climate data set (1980-2010) and the Global Soil Dataset for Earth Systems modeling as a basis for creating its simulations, as well as local management operations for maize and soybean cropping systems and different biochar application rates. The regional scale simulation analysis is in progress. Preliminary results showed that the model predicts that high quality soils (particularly those common to Iowa cropping systems) do not receive much, if any, production benefit from biochar. However, soils with low soil organic matter ( 0.5%) do get a noteworthy yield increase of around 5-10% in the best cases. We also found N2O emissions to be spatial and temporal specific; increase in some areas and decrease in some other areas due to biochar application. In contrast, we found increases in soil organic carbon and plant available water in all soils (top 30 cm) due to biochar application. The magnitude of these increases (% change from the control) were larger in soil with low organic matter (below 1.5%) and smaller in soils with high organic matter (above 3%) and also dependent on biochar

The art and science of problem solving

DEFF Research Database (Denmark)

Vidal, Rene Victor Valqui

2005-01-01

In this paper we will document that real-life problem solving in complex situations demands both rational (scientific) and intuitive (artistic) thinking. First, the concepts of art and science will be discussed; differences and similarities will be enhanced. Thereafter the concept of group problem...... solving facilitation both as science and art will be presented. A case study related to examination's planning will be discussed to illustrate the main concepts in practice. In addition, other cases studies will also be shortly presented....

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

International Nuclear Information System (INIS)

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

2013-01-01

A new generation of laser wakefield accelerators (LWFA), supported by the extreme accelerating fields generated in the interaction of PW-Class lasers and underdense targets, promises the production of high quality electron beams in short distances for multiple applications. Achieving this goal will rely heavily on numerical modelling to further understand the underlying physics and identify optimal regimes, but large scale modelling of these scenarios is computationally heavy and requires the efficient use of state-of-the-art petascale supercomputing systems. We discuss the main difficulties involved in running these simulations and the new developments implemented in the OSIRIS framework to address these issues, ranging from multi-dimensional dynamic load balancing and hybrid distributed/shared memory parallelism to the vectorization of the PIC algorithm. We present the results of the OASCR Joule Metric program on the issue of large scale modelling of LWFA, demonstrating speedups of over 1 order of magnitude on the same hardware. Finally, scalability to over ∼10 6 cores and sustained performance over ∼2 P Flops is demonstrated, opening the way for large scale modelling of LWFA scenarios. (paper)

Balancing modern Power System with large scale of wind power

DEFF Research Database (Denmark)

Basit, Abdul; Altin, Müfit; Hansen, Anca Daniela

2014-01-01

Power system operators must ensure robust, secure and reliable power system operation even with a large scale integration of wind power. Electricity generated from the intermittent wind in large propor-tion may impact on the control of power system balance and thus deviations in the power system...... frequency in small or islanded power systems or tie line power flows in interconnected power systems. Therefore, the large scale integration of wind power into the power system strongly concerns the secure and stable grid operation. To ensure the stable power system operation, the evolving power system has...... to be analysed with improved analytical tools and techniques. This paper proposes techniques for the active power balance control in future power systems with the large scale wind power integration, where power balancing model provides the hour-ahead dispatch plan with reduced planning horizon and the real time...