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

Science.gov (United States)

Shameldin, Ramez Ahmed; Bowling, Shannon R.

2010-01-01

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

A 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.

Large scale molecular simulations of nanotoxicity.

Science.gov (United States)

Jimenez-Cruz, Camilo A; Kang, Seung-gu; Zhou, Ruhong

2014-01-01

The widespread use of nanomaterials in biomedical applications has been accompanied by an increasing interest in understanding their interactions with tissues, cells, and biomolecules, and in particular, on how they might affect the integrity of cell membranes and proteins. In this mini-review, we present a summary of some of the recent studies on this important subject, especially from the point of view of large scale molecular simulations. The carbon-based nanomaterials and noble metal nanoparticles are the main focus, with additional discussions on quantum dots and other nanoparticles as well. The driving forces for adsorption of fullerenes, carbon nanotubes, and graphene nanosheets onto proteins or cell membranes are found to be mainly hydrophobic interactions and the so-called π-π stacking (between aromatic rings), while for the noble metal nanoparticles the long-range electrostatic interactions play a bigger role. More interestingly, there are also growing evidences showing that nanotoxicity can have implications in de novo design of nanomedicine. For example, the endohedral metallofullerenol Gd@C₈₂(OH)₂₂ is shown to inhibit tumor growth and metastasis by inhibiting enzyme MMP-9, and graphene is illustrated to disrupt bacteria cell membranes by insertion/cutting as well as destructive extraction of lipid molecules. These recent findings have provided a better understanding of nanotoxicity at the molecular level and also suggested therapeutic potential by using the cytotoxicity of nanoparticles against cancer or bacteria cells. © 2014 Wiley Periodicals, Inc.

Model-based plant-wide optimization of large-scale lignocellulosic bioethanol plants

DEFF Research Database (Denmark)

Prunescu, Remus Mihail; Blanke, Mogens; Jakobsen, Jon Geest

2017-01-01

Second generation biorefineries transform lignocellulosic biomass into chemicals with higher added value following a conversion mechanism that consists of: pretreatment, enzymatic hydrolysis, fermentation and purification. The objective of this study is to identify the optimal operational point...... with respect to maximum economic profit of a large scale biorefinery plant using a systematic model-based plantwide optimization methodology. The following key process parameters are identified as decision variables: pretreatment temperature, enzyme dosage in enzymatic hydrolysis, and yeast loading per batch...... in fermentation. The plant is treated in an integrated manner taking into account the interactions and trade-offs between the conversion steps. A sensitivity and uncertainty analysis follows at the optimal solution considering both model and feed parameters. It is found that the optimal point is more sensitive...

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

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

Science.gov (United States)

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

2015-12-01

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

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.

A modular approach to large-scale design optimization of aerospace systems

Science.gov (United States)

Hwang, John T.

Gradient-based optimization and the adjoint method form a synergistic combination that enables the efficient solution of large-scale optimization problems. Though the gradient-based approach struggles with non-smooth or multi-modal problems, the capability to efficiently optimize up to tens of thousands of design variables provides a valuable design tool for exploring complex tradeoffs and finding unintuitive designs. However, the widespread adoption of gradient-based optimization is limited by the implementation challenges for computing derivatives efficiently and accurately, particularly in multidisciplinary and shape design problems. This thesis addresses these difficulties in two ways. First, to deal with the heterogeneity and integration challenges of multidisciplinary problems, this thesis presents a computational modeling framework that solves multidisciplinary systems and computes their derivatives in a semi-automated fashion. This framework is built upon a new mathematical formulation developed in this thesis that expresses any computational model as a system of algebraic equations and unifies all methods for computing derivatives using a single equation. The framework is applied to two engineering problems: the optimization of a nanosatellite with 7 disciplines and over 25,000 design variables; and simultaneous allocation and mission optimization for commercial aircraft involving 330 design variables, 12 of which are integer variables handled using the branch-and-bound method. In both cases, the framework makes large-scale optimization possible by reducing the implementation effort and code complexity. The second half of this thesis presents a differentiable parametrization of aircraft geometries and structures for high-fidelity shape optimization. Existing geometry parametrizations are not differentiable, or they are limited in the types of shape changes they allow. This is addressed by a novel parametrization that smoothly interpolates aircraft

Optimization of Large-Scale Structural Systems

DEFF Research Database (Denmark)

Jensen, F. M.

solutions to small problems with one or two variables to the optimization of large structures such as bridges, ships and offshore structures. The methods used for salving these problems have evolved from being classical differential calculus and calculus of variation to very advanced numerical techniques...

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.

A new hybrid meta-heuristic algorithm for optimal design of large-scale dome structures

Science.gov (United States)

Kaveh, A.; Ilchi Ghazaan, M.

2018-02-01

In this article a hybrid algorithm based on a vibrating particles system (VPS) algorithm, multi-design variable configuration (Multi-DVC) cascade optimization, and an upper bound strategy (UBS) is presented for global optimization of large-scale dome truss structures. The new algorithm is called MDVC-UVPS in which the VPS algorithm acts as the main engine of the algorithm. The VPS algorithm is one of the most recent multi-agent meta-heuristic algorithms mimicking the mechanisms of damped free vibration of single degree of freedom systems. In order to handle a large number of variables, cascade sizing optimization utilizing a series of DVCs is used. Moreover, the UBS is utilized to reduce the computational time. Various dome truss examples are studied to demonstrate the effectiveness and robustness of the proposed method, as compared to some existing structural optimization techniques. The results indicate that the MDVC-UVPS technique is a powerful search and optimization method for optimizing structural engineering problems.

Final Report: Large-Scale Optimization for Bayesian Inference in Complex Systems

Energy Technology Data Exchange (ETDEWEB)

Ghattas, Omar [The University of Texas at Austin

2013-10-15

The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimiza- tion) Project focuses on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimiza- tion and inversion methods. Our research is directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. Our efforts are integrated in the context of a challenging testbed problem that considers subsurface reacting flow and transport. The MIT component of the SAGUARO Project addresses the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas-Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to- observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as "reduce then sample" and "sample then reduce." In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their speedups.

Thermal System Analysis and Optimization of Large-Scale Compressed Air Energy Storage (CAES

Directory of Open Access Journals (Sweden)

Zhongguang Fu

2015-08-01

Full Text Available As an important solution to issues regarding peak load and renewable energy resources on grids, large-scale compressed air energy storage (CAES power generation technology has recently become a popular research topic in the area of large-scale industrial energy storage. At present, the combination of high-expansion ratio turbines with advanced gas turbine technology is an important breakthrough in energy storage technology. In this study, a new gas turbine power generation system is coupled with current CAES technology. Moreover, a thermodynamic cycle system is optimized by calculating for the parameters of a thermodynamic system. Results show that the thermal efficiency of the new system increases by at least 5% over that of the existing system.

A fast and optimized dynamic economic load dispatch for large scale power systems

International Nuclear Information System (INIS)

Musse Mohamud Ahmed; Mohd Ruddin Ab Ghani; Ismail Hassan

2000-01-01

This paper presents Lagrangian Multipliers (LM) and Linear Programming (LP) based dynamic economic load dispatch (DELD) solution for large-scale power system operations. It is to minimize the operation cost of power generation. units subject to the considered constraints. After individual generator units are economically loaded and periodically dispatched, fast and optimized DELD has been achieved. DELD with period intervals has been taken into consideration The results found from the algorithm based on LM and LP techniques appear to be modest in both optimizing the operation cost and achieving fast computation. (author)

Process optimization of large-scale production of recombinant adeno-associated vectors using dielectric spectroscopy.

Science.gov (United States)

Negrete, Alejandro; Esteban, Geoffrey; Kotin, Robert M

2007-09-01

A well-characterized manufacturing process for the large-scale production of recombinant adeno-associated vectors (rAAV) for gene therapy applications is required to meet current and future demands for pre-clinical and clinical studies and potential commercialization. Economic considerations argue in favor of suspension culture-based production. Currently, the only feasible method for large-scale rAAV production utilizes baculovirus expression vectors and insect cells in suspension cultures. To maximize yields and achieve reproducibility between batches, online monitoring of various metabolic and physical parameters is useful for characterizing early stages of baculovirus-infected insect cells. In this study, rAAVs were produced at 40-l scale yielding ~1 x 10(15) particles. During the process, dielectric spectroscopy was performed by real time scanning in radio frequencies between 300 kHz and 10 MHz. The corresponding permittivity values were correlated with the rAAV production. Both infected and uninfected reached a maximum value; however, only infected cell cultures permittivity profile reached a second maximum value. This effect was correlated with the optimal harvest time for rAAV production. Analysis of rAAV indicated the harvesting time around 48 h post-infection (hpi), and 72 hpi produced similar quantities of biologically active rAAV. Thus, if operated continuously, the 24-h reduction in the production process of rAAV gives sufficient time for additional 18 runs a year corresponding to an extra production of ~2 x 10(16) particles. As part of large-scale optimization studies, this new finding will facilitate the bioprocessing scale-up of rAAV and other bioproducts.

Decentralized Large-Scale Power Balancing

DEFF Research Database (Denmark)

Halvgaard, Rasmus; Jørgensen, John Bagterp; Poulsen, Niels Kjølstad

2013-01-01

problem is formulated as a centralized large-scale optimization problem but is then decomposed into smaller subproblems that are solved locally by each unit connected to an aggregator. For large-scale systems the method is faster than solving the full problem and can be distributed to include an arbitrary...

Optimal Capacity Allocation of Large-Scale Wind-PV-Battery Units

Directory of Open Access Journals (Sweden)

Kehe Wu

2014-01-01

Full Text Available An optimal capacity allocation of large-scale wind-photovoltaic- (PV- battery units was proposed. First, an output power model was established according to meteorological conditions. Then, a wind-PV-battery unit was connected to the power grid as a power-generation unit with a rated capacity under a fixed coordinated operation strategy. Second, the utilization rate of renewable energy sources and maximum wind-PV complementation was considered and the objective function of full life cycle-net present cost (NPC was calculated through hybrid iteration/adaptive hybrid genetic algorithm (HIAGA. The optimal capacity ratio among wind generator, PV array, and battery device also was calculated simultaneously. A simulation was conducted based on the wind-PV-battery unit in Zhangbei, China. Results showed that a wind-PV-battery unit could effectively minimize the NPC of power-generation units under a stable grid-connected operation. Finally, the sensitivity analysis of the wind-PV-battery unit demonstrated that the optimization result was closely related to potential wind-solar resources and government support. Regions with rich wind resources and a reasonable government energy policy could improve the economic efficiency of their power-generation units.

LAMMPS strong scaling performance optimization on Blue Gene/Q

Energy Technology Data Exchange (ETDEWEB)

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

2014-11-12

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

Subspace Barzilai-Borwein Gradient Method for Large-Scale Bound Constrained Optimization

International Nuclear Information System (INIS)

Xiao Yunhai; Hu Qingjie

2008-01-01

An active set subspace Barzilai-Borwein gradient algorithm for large-scale bound constrained optimization is proposed. The active sets are estimated by an identification technique. The search direction consists of two parts: some of the components are simply defined; the other components are determined by the Barzilai-Borwein gradient method. In this work, a nonmonotone line search strategy that guarantees global convergence is used. Preliminary numerical results show that the proposed method is promising, and competitive with the well-known method SPG on a subset of bound constrained problems from CUTEr collection

Protein homology model refinement by large-scale energy optimization.

Science.gov (United States)

Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E; DiMaio, Frank; Baker, David

2018-03-20

Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.

Large-Scale Portfolio Optimization Using Multiobjective Evolutionary Algorithms and Preselection Methods

Directory of Open Access Journals (Sweden)

B. Y. Qu

2017-01-01

Full Text Available Portfolio optimization problems involve selection of different assets to invest in order to maximize the overall return and minimize the overall risk simultaneously. The complexity of the optimal asset allocation problem increases with an increase in the number of assets available to select from for investing. The optimization problem becomes computationally challenging when there are more than a few hundreds of assets to select from. To reduce the complexity of large-scale portfolio optimization, two asset preselection procedures that consider return and risk of individual asset and pairwise correlation to remove assets that may not potentially be selected into any portfolio are proposed in this paper. With these asset preselection methods, the number of assets considered to be included in a portfolio can be increased to thousands. To test the effectiveness of the proposed methods, a Normalized Multiobjective Evolutionary Algorithm based on Decomposition (NMOEA/D algorithm and several other commonly used multiobjective evolutionary algorithms are applied and compared. Six experiments with different settings are carried out. The experimental results show that with the proposed methods the simulation time is reduced while return-risk trade-off performances are significantly improved. Meanwhile, the NMOEA/D is able to outperform other compared algorithms on all experiments according to the comparative analysis.

Optimization theory for large systems

CERN Document Server

Lasdon, Leon S

2002-01-01

Important text examines most significant algorithms for optimizing large systems and clarifying relations between optimization procedures. Much data appear as charts and graphs and will be highly valuable to readers in selecting a method and estimating computer time and cost in problem-solving. Initial chapter on linear and nonlinear programming presents all necessary background for subjects covered in rest of book. Second chapter illustrates how large-scale mathematical programs arise from real-world problems. Appendixes. List of Symbols.

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.

Lightweight computational steering of very large scale molecular dynamics simulations

International Nuclear Information System (INIS)

Beazley, D.M.

1996-01-01

We present a computational steering approach for controlling, analyzing, and visualizing very large scale molecular dynamics simulations involving tens to hundreds of millions of atoms. Our approach relies on extensible scripting languages and an easy to use tool for building extensions and modules. The system is extremely easy to modify, works with existing C code, is memory efficient, and can be used from inexpensive workstations and networks. We demonstrate how we have used this system to manipulate data from production MD simulations involving as many as 104 million atoms running on the CM-5 and Cray T3D. We also show how this approach can be used to build systems that integrate common scripting languages (including Tcl/Tk, Perl, and Python), simulation code, user extensions, and commercial data analysis packages

Optimal Wind Energy Integration in Large-Scale Electric Grids

Science.gov (United States)

Albaijat, Mohammad H.

The major concern in electric grid operation is operating under the most economical and reliable fashion to ensure affordability and continuity of electricity supply. This dissertation investigates the effects of such challenges, which affect electric grid reliability and economic operations. These challenges are: 1. Congestion of transmission lines, 2. Transmission lines expansion, 3. Large-scale wind energy integration, and 4. Phaser Measurement Units (PMUs) optimal placement for highest electric grid observability. Performing congestion analysis aids in evaluating the required increase of transmission line capacity in electric grids. However, it is necessary to evaluate expansion of transmission line capacity on methods to ensure optimal electric grid operation. Therefore, the expansion of transmission line capacity must enable grid operators to provide low-cost electricity while maintaining reliable operation of the electric grid. Because congestion affects the reliability of delivering power and increases its cost, the congestion analysis in electric grid networks is an important subject. Consequently, next-generation electric grids require novel methodologies for studying and managing congestion in electric grids. We suggest a novel method of long-term congestion management in large-scale electric grids. Owing to the complication and size of transmission line systems and the competitive nature of current grid operation, it is important for electric grid operators to determine how many transmission lines capacity to add. Traditional questions requiring answers are "Where" to add, "How much of transmission line capacity" to add, and "Which voltage level". Because of electric grid deregulation, transmission lines expansion is more complicated as it is now open to investors, whose main interest is to generate revenue, to build new transmission lines. Adding a new transmission capacity will help the system to relieve the transmission system congestion, create

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

A Grouping Particle Swarm Optimizer with Personal-Best-Position Guidance for Large Scale Optimization.

Science.gov (United States)

Guo, Weian; Si, Chengyong; Xue, Yu; Mao, Yanfen; Wang, Lei; Wu, Qidi

2017-05-04

Particle Swarm Optimization (PSO) is a popular algorithm which is widely investigated and well implemented in many areas. However, the canonical PSO does not perform well in population diversity maintenance so that usually leads to a premature convergence or local optima. To address this issue, we propose a variant of PSO named Grouping PSO with Personal- Best-Position (Pbest) Guidance (GPSO-PG) which maintains the population diversity by preserving the diversity of exemplars. On one hand, we adopt uniform random allocation strategy to assign particles into different groups and in each group the losers will learn from the winner. On the other hand, we employ personal historical best position of each particle in social learning rather than the current global best particle. In this way, the exemplars diversity increases and the effect from the global best particle is eliminated. We test the proposed algorithm to the benchmarks in CEC 2008 and CEC 2010, which concern the large scale optimization problems (LSOPs). By comparing several current peer algorithms, GPSO-PG exhibits a competitive performance to maintain population diversity and obtains a satisfactory performance to the problems.

Comparison of prestellar core elongations and large-scale molecular cloud structures in the Lupus I region

Energy Technology Data Exchange (ETDEWEB)

Poidevin, Frédérick [UCL, KLB, Department of Physics and Astronomy, Gower Place, London WC1E 6BT (United Kingdom); Ade, Peter A. R.; Hargrave, Peter C.; Nutter, David [School of Physics and Astronomy, Cardiff University, Queens Buildings, The Parade, Cardiff CF24 3AA (United Kingdom); Angile, Francesco E.; Devlin, Mark J.; Klein, Jeffrey [Department of Physics and Astronomy, University of Pennsylvania, 209 South 33rd Street, Philadelphia, PA 19104 (United States); Benton, Steven J.; Netterfield, Calvin B. [Department of Physics, University of Toronto, 60 St. George Street, Toronto, ON M5S 1A7 (Canada); Chapin, Edward L. [XMM SOC, ESAC, Apartado 78, E-28691 Villanueva de la Canãda, Madrid (Spain); Fissel, Laura M.; Gandilo, Natalie N. [Department of Astronomy and Astrophysics, University of Toronto, 50 St. George Street, Toronto, ON M5S 3H4 (Canada); Fukui, Yasuo [Department of Physics, Nagoya University, Chikusa-ku, Nagoya, Aichi 464-8601 (Japan); Gundersen, Joshua O. [Department of Physics, University of Miami, 1320 Campo Sano Drive, Coral Gables, FL 33146 (United States); Korotkov, Andrei L. [Department of Physics, Brown University, 182 Hope Street, Providence, RI 02912 (United States); Matthews, Tristan G.; Novak, Giles [Department of Physics and Astronomy, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208 (United States); Moncelsi, Lorenzo; Mroczkowski, Tony K. [California Institute of Technology, 1200 East California Boulevard, Pasadena, CA 91125 (United States); Olmi, Luca, E-mail: fpoidevin@iac.es [Physics Department, University of Puerto Rico, Rio Piedras Campus, Box 23343, UPR station, San Juan, PR 00931 (United States); and others

2014-08-10

Turbulence and magnetic fields are expected to be important for regulating molecular cloud formation and evolution. However, their effects on sub-parsec to 100 parsec scales, leading to the formation of starless cores, are not well understood. We investigate the prestellar core structure morphologies obtained from analysis of the Herschel-SPIRE 350 μm maps of the Lupus I cloud. This distribution is first compared on a statistical basis to the large-scale shape of the main filament. We find the distribution of the elongation position angle of the cores to be consistent with a random distribution, which means no specific orientation of the morphology of the cores is observed with respect to the mean orientation of the large-scale filament in Lupus I, nor relative to a large-scale bent filament model. This distribution is also compared to the mean orientation of the large-scale magnetic fields probed at 350 μm with the Balloon-borne Large Aperture Telescope for Polarimetry during its 2010 campaign. Here again we do not find any correlation between the core morphology distribution and the average orientation of the magnetic fields on parsec scales. Our main conclusion is that the local filament dynamics—including secondary filaments that often run orthogonally to the primary filament—and possibly small-scale variations in the local magnetic field direction, could be the dominant factors for explaining the final orientation of each core.

Scalable Molecular Dynamics for Large Biomolecular Systems

Directory of Open Access Journals (Sweden)

Robert K. Brunner

2000-01-01

Full Text Available We present an optimized parallelization scheme for molecular dynamics simulations of large biomolecular systems, implemented in the production-quality molecular dynamics program NAMD. With an object-based hybrid force and spatial decomposition scheme, and an aggressive measurement-based predictive load balancing framework, we have attained speeds and speedups that are much higher than any reported in literature so far. The paper first summarizes the broad methodology we are pursuing, and the basic parallelization scheme we used. It then describes the optimizations that were instrumental in increasing performance, and presents performance results on benchmark simulations.

Modeling ramp compression experiments using large-scale molecular dynamics simulation.

Energy Technology Data Exchange (ETDEWEB)

Mattsson, Thomas Kjell Rene; Desjarlais, Michael Paul; Grest, Gary Stephen; Templeton, Jeremy Alan; Thompson, Aidan Patrick; Jones, Reese E.; Zimmerman, Jonathan A.; Baskes, Michael I. (University of California, San Diego); Winey, J. Michael (Washington State University); Gupta, Yogendra Mohan (Washington State University); Lane, J. Matthew D.; Ditmire, Todd (University of Texas at Austin); Quevedo, Hernan J. (University of Texas at Austin)

2011-10-01

Molecular dynamics simulation (MD) is an invaluable tool for studying problems sensitive to atomscale physics such as structural transitions, discontinuous interfaces, non-equilibrium dynamics, and elastic-plastic deformation. In order to apply this method to modeling of ramp-compression experiments, several challenges must be overcome: accuracy of interatomic potentials, length- and time-scales, and extraction of continuum quantities. We have completed a 3 year LDRD project with the goal of developing molecular dynamics simulation capabilities for modeling the response of materials to ramp compression. The techniques we have developed fall in to three categories (i) molecular dynamics methods (ii) interatomic potentials (iii) calculation of continuum variables. Highlights include the development of an accurate interatomic potential describing shock-melting of Beryllium, a scaling technique for modeling slow ramp compression experiments using fast ramp MD simulations, and a technique for extracting plastic strain from MD simulations. All of these methods have been implemented in Sandia's LAMMPS MD code, ensuring their widespread availability to dynamic materials research at Sandia and elsewhere.

a Stochastic Approach to Multiobjective Optimization of Large-Scale Water Reservoir Networks

Science.gov (United States)

Bottacin-Busolin, A.; Worman, A. L.

2013-12-01

A main challenge for the planning and management of water resources is the development of multiobjective strategies for operation of large-scale water reservoir networks. The optimal sequence of water releases from multiple reservoirs depends on the stochastic variability of correlated hydrologic inflows and on various processes that affect water demand and energy prices. Although several methods have been suggested, large-scale optimization problems arising in water resources management are still plagued by the high dimensional state space and by the stochastic nature of the hydrologic inflows. In this work, the optimization of reservoir operation is approached using approximate dynamic programming (ADP) with policy iteration and function approximators. The method is based on an off-line learning process in which operating policies are evaluated for a number of stochastic inflow scenarios, and the resulting value functions are used to design new, improved policies until convergence is attained. A case study is presented of a multi-reservoir system in the Dalälven River, Sweden, which includes 13 interconnected reservoirs and 36 power stations. Depending on the late spring and summer peak discharges, the lowlands adjacent to Dalälven can often be flooded during the summer period, and the presence of stagnating floodwater during the hottest months of the year is the cause of a large proliferation of mosquitos, which is a major problem for the people living in the surroundings. Chemical pesticides are currently being used as a preventive countermeasure, which do not provide an effective solution to the problem and have adverse environmental impacts. In this study, ADP was used to analyze the feasibility of alternative operating policies for reducing the flood risk at a reasonable economic cost for the hydropower companies. To this end, mid-term operating policies were derived by combining flood risk reduction with hydropower production objectives. The performance

Scaling Sparse Matrices for Optimization Algorithms

OpenAIRE

Gajulapalli Ravindra S; Lasdon Leon S

2006-01-01

To iteratively solve large scale optimization problems in various contexts like planning, operations, design etc., we need to generate descent directions that are based on linear system solutions. Irrespective of the optimization algorithm or the solution method employed for the linear systems, ill conditioning introduced by problem characteristics or the algorithm or both need to be addressed. In [GL01] we used an intuitive heuristic approach in scaling linear systems that improved performan...

A Novel Spatial-Temporal Voronoi Diagram-Based Heuristic Approach for Large-Scale Vehicle Routing Optimization with Time Constraints

Directory of Open Access Journals (Sweden)

Wei Tu

2015-10-01

Full Text Available Vehicle routing optimization (VRO designs the best routes to reduce travel cost, energy consumption, and carbon emission. Due to non-deterministic polynomial-time hard (NP-hard complexity, many VROs involved in real-world applications require too much computing effort. Shortening computing time for VRO is a great challenge for state-of-the-art spatial optimization algorithms. From a spatial-temporal perspective, this paper presents a spatial-temporal Voronoi diagram-based heuristic approach for large-scale vehicle routing problems with time windows (VRPTW. Considering time constraints, a spatial-temporal Voronoi distance is derived from the spatial-temporal Voronoi diagram to find near neighbors in the space-time searching context. A Voronoi distance decay strategy that integrates a time warp operation is proposed to accelerate local search procedures. A spatial-temporal feature-guided search is developed to improve unpromising micro route structures. Experiments on VRPTW benchmarks and real-world instances are conducted to verify performance. The results demonstrate that the proposed approach is competitive with state-of-the-art heuristics and achieves high-quality solutions for large-scale instances of VRPTWs in a short time. This novel approach will contribute to spatial decision support community by developing an effective vehicle routing optimization method for large transportation applications in both public and private sectors.

Optimal number of coarse-grained sites in different components of large biomolecular complexes.

Science.gov (United States)

Sinitskiy, Anton V; Saunders, Marissa G; Voth, Gregory A

2012-07-26

The computational study of large biomolecular complexes (molecular machines, cytoskeletal filaments, etc.) is a formidable challenge facing computational biophysics and biology. To achieve biologically relevant length and time scales, coarse-grained (CG) models of such complexes usually must be built and employed. One of the important early stages in this approach is to determine an optimal number of CG sites in different constituents of a complex. This work presents a systematic approach to this problem. First, a universal scaling law is derived and numerically corroborated for the intensity of the intrasite (intradomain) thermal fluctuations as a function of the number of CG sites. Second, this result is used for derivation of the criterion for the optimal number of CG sites in different parts of a large multibiomolecule complex. In the zeroth-order approximation, this approach validates the empirical rule of taking one CG site per fixed number of atoms or residues in each biomolecule, previously widely used for smaller systems (e.g., individual biomolecules). The first-order corrections to this rule are derived and numerically checked by the case studies of the Escherichia coli ribosome and Arp2/3 actin filament junction. In different ribosomal proteins, the optimal number of amino acids per CG site is shown to differ by a factor of 3.5, and an even wider spread may exist in other large biomolecular complexes. Therefore, the method proposed in this paper is valuable for the optimal construction of CG models of such complexes.

Large-Scale Systems Control Design via LMI Optimization

Czech Academy of Sciences Publication Activity Database

Rehák, Branislav

2015-01-01

Roč. 44, č. 3 (2015), s. 247-253 ISSN 1392-124X Institutional support: RVO:67985556 Keywords : Combinatorial linear matrix inequalities * large-scale system * decentralized control Subject RIV: BC - Control Systems Theory Impact factor: 0.633, year: 2015

Energy Decomposition Analysis Based on Absolutely Localized Molecular Orbitals for Large-Scale Density Functional Theory Calculations in Drug Design.

Science.gov (United States)

Phipps, M J S; Fox, T; Tautermann, C S; Skylaris, C-K

2016-07-12

We report the development and implementation of an energy decomposition analysis (EDA) scheme in the ONETEP linear-scaling electronic structure package. Our approach is hybrid as it combines the localized molecular orbital EDA (Su, P.; Li, H. J. Chem. Phys., 2009, 131, 014102) and the absolutely localized molecular orbital EDA (Khaliullin, R. Z.; et al. J. Phys. Chem. A, 2007, 111, 8753-8765) to partition the intermolecular interaction energy into chemically distinct components (electrostatic, exchange, correlation, Pauli repulsion, polarization, and charge transfer). Limitations shared in EDA approaches such as the issue of basis set dependence in polarization and charge transfer are discussed, and a remedy to this problem is proposed that exploits the strictly localized property of the ONETEP orbitals. Our method is validated on a range of complexes with interactions relevant to drug design. We demonstrate the capabilities for large-scale calculations with our approach on complexes of thrombin with an inhibitor comprised of up to 4975 atoms. Given the capability of ONETEP for large-scale calculations, such as on entire proteins, we expect that our EDA scheme can be applied in a large range of biomolecular problems, especially in the context of drug design.

Comparison of particle swarm optimization and dynamic programming for large scale hydro unit load dispatch

International Nuclear Information System (INIS)

Cheng Chuntian; Liao Shengli; Tang Zitian; Zhao Mingyan

2009-01-01

Dynamic programming (DP) is one of classic and sophisticated optimization methods that have successfully been applied to solve the problem of hydro unit load dispatch (HULD). However, DP will be faced with the curse of dimensionality with the increase of unit number and installed generating capacity of hydropower station. With the appearance of the huge hydropower station similar to the Three George with 26 generators of 700 MW, it is hard to apply the DP to large scale HULD problem. It is crucial to seek for other optimization techniques in order to improve the operation quality and efficiency. Different with the most of literature about power generation scheduling that focused on the comparisons of novel PSO algorithms with other techniques, the paper will pay emphasis on comparison study of PSO with DP based on a case hydropower station. The objective of study is to seek for an effective and feasible method for the large scale of hydropower station of the current and future in China. This paper first compares the performance of PSO and DP using a sample load curve of the Wujiangdu hydropower plant located in the upper stream of the Yangtze River in China and contained five units with the installed capacity of 1250 MW. Next, the effect of different load interval and unit number on the optimal results and efficiency of two methods has also been implemented. The comparison results show that the PSO is feasible for HULD. Furthermore, we simulated the effect of the magnitude of unit number and load capacity on the optimal results and cost time. The simulation comparisons show that PSO has a great advantage over DP in the efficiency and will be one of effective methods for HULD problem of huge hydropower stations.

Comparison of particle swarm optimization and dynamic programming for large scale hydro unit load dispatch

Energy Technology Data Exchange (ETDEWEB)

Cheng Chuntian, E-mail: ctcheng@dlut.edu.c [Department of Civil and Hydraulic Engineering, Dalian University of Technology, 116024 Dalian (China); Liao Shengli; Tang Zitian [Department of Civil and Hydraulic Engineering, Dalian University of Technology, 116024 Dalian (China); Zhao Mingyan [Department of Environmental Science and Engineering, Tsinghua University, 100084 Beijing (China)

2009-12-15

Dynamic programming (DP) is one of classic and sophisticated optimization methods that have successfully been applied to solve the problem of hydro unit load dispatch (HULD). However, DP will be faced with the curse of dimensionality with the increase of unit number and installed generating capacity of hydropower station. With the appearance of the huge hydropower station similar to the Three George with 26 generators of 700 MW, it is hard to apply the DP to large scale HULD problem. It is crucial to seek for other optimization techniques in order to improve the operation quality and efficiency. Different with the most of literature about power generation scheduling that focused on the comparisons of novel PSO algorithms with other techniques, the paper will pay emphasis on comparison study of PSO with DP based on a case hydropower station. The objective of study is to seek for an effective and feasible method for the large scale of hydropower station of the current and future in China. This paper first compares the performance of PSO and DP using a sample load curve of the Wujiangdu hydropower plant located in the upper stream of the Yangtze River in China and contained five units with the installed capacity of 1250 MW. Next, the effect of different load interval and unit number on the optimal results and efficiency of two methods has also been implemented. The comparison results show that the PSO is feasible for HULD. Furthermore, we simulated the effect of the magnitude of unit number and load capacity on the optimal results and cost time. The simulation comparisons show that PSO has a great advantage over DP in the efficiency and will be one of effective methods for HULD problem of huge hydropower stations.

Comparison of particle swarm optimization and dynamic programming for large scale hydro unit load dispatch

Energy Technology Data Exchange (ETDEWEB)

Chun-tian Cheng; Sheng-li Liao; Zi-Tian Tang [Dept. of Civil and Hydraulic Engineering, Dalian Univ. of Technology, 116024 Dalian (China); Ming-yan Zhao [Dept. of Environmental Science and Engineering, Tsinghua Univ., 100084 Beijing (China)

2009-12-15

Dynamic programming (DP) is one of classic and sophisticated optimization methods that have successfully been applied to solve the problem of hydro unit load dispatch (HULD). However, DP will be faced with the curse of dimensionality with the increase of unit number and installed generating capacity of hydropower station. With the appearance of the huge hydropower station similar to the Three George with 26 generators of 700 MW, it is hard to apply the DP to large scale HULD problem. It is crucial to seek for other optimization techniques in order to improve the operation quality and efficiency. Different with the most of literature about power generation scheduling that focused on the comparisons of novel PSO algorithms with other techniques, the paper will pay emphasis on comparison study of PSO with DP based on a case hydropower station. The objective of study is to seek for an effective and feasible method for the large scale of hydropower station of the current and future in China. This paper first compares the performance of PSO and DP using a sample load curve of the Wujiangdu hydropower plant located in the upper stream of the Yangtze River in China and contained five units with the installed capacity of 1250 MW. Next, the effect of different load interval and unit number on the optimal results and efficiency of two methods has also been implemented. The comparison results show that the PSO is feasible for HULD. Furthermore, we simulated the effect of the magnitude of unit number and load capacity on the optimal results and cost time. The simulation comparisons show that PSO has a great advantage over DP in the efficiency and will be one of effective methods for HULD problem of huge hydropower stations. (author)

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

Optimal Siting and Sizing of Energy Storage System for Power Systems with Large-scale Wind Power Integration

DEFF Research Database (Denmark)

Zhao, Haoran; Wu, Qiuwei; Huang, Shaojun

2015-01-01

This paper proposes algorithms for optimal sitingand sizing of Energy Storage System (ESS) for the operationplanning of power systems with large scale wind power integration.The ESS in this study aims to mitigate the wind powerfluctuations during the interval between two rolling Economic......Dispatches (EDs) in order to maintain generation-load balance.The charging and discharging of ESS is optimized consideringoperation cost of conventional generators, capital cost of ESSand transmission losses. The statistics from simulated systemoperations are then coupled to the planning process to determinethe...

Fast Bound Methods for Large Scale Simulation with Application for Engineering Optimization

Science.gov (United States)

Patera, Anthony T.; Peraire, Jaime; Zang, Thomas A. (Technical Monitor)

2002-01-01

In this work, we have focused on fast bound methods for large scale simulation with application for engineering optimization. The emphasis is on the development of techniques that provide both very fast turnaround and a certificate of Fidelity; these attributes ensure that the results are indeed relevant to - and trustworthy within - the engineering context. The bound methodology which underlies this work has many different instantiations: finite element approximation; iterative solution techniques; and reduced-basis (parameter) approximation. In this grant we have, in fact, treated all three, but most of our effort has been concentrated on the first and third. We describe these below briefly - but with a pointer to an Appendix which describes, in some detail, the current "state of the art."

An optimal beam alignment method for large-scale distributed space surveillance radar system

Science.gov (United States)

Huang, Jian; Wang, Dongya; Xia, Shuangzhi

2018-06-01

Large-scale distributed space surveillance radar is a very important ground-based equipment to maintain a complete catalogue for Low Earth Orbit (LEO) space debris. However, due to the thousands of kilometers distance between each sites of the distributed radar system, how to optimally implement the Transmitting/Receiving (T/R) beams alignment in a great space using the narrow beam, which proposed a special and considerable technical challenge in the space surveillance area. According to the common coordinate transformation model and the radar beam space model, we presented a two dimensional projection algorithm for T/R beam using the direction angles, which could visually describe and assess the beam alignment performance. Subsequently, the optimal mathematical models for the orientation angle of the antenna array, the site location and the T/R beam coverage are constructed, and also the beam alignment parameters are precisely solved. At last, we conducted the optimal beam alignment experiments base on the site parameters of Air Force Space Surveillance System (AFSSS). The simulation results demonstrate the correctness and effectiveness of our novel method, which can significantly stimulate the construction for the LEO space debris surveillance equipment.

Large-scale linear programs in planning and prediction.

Science.gov (United States)

2017-06-01

Large-scale linear programs are at the core of many traffic-related optimization problems in both planning and prediction. Moreover, many of these involve significant uncertainty, and hence are modeled using either chance constraints, or robust optim...

Large-scale building energy efficiency retrofit: Concept, model and control

International Nuclear Information System (INIS)

Wu, Zhou; Wang, Bo; Xia, Xiaohua

2016-01-01

BEER (Building energy efficiency retrofit) projects are initiated in many nations and regions over the world. Existing studies of BEER focus on modeling and planning based on one building and one year period of retrofitting, which cannot be applied to certain large BEER projects with multiple buildings and multi-year retrofit. In this paper, the large-scale BEER problem is defined in a general TBT (time-building-technology) framework, which fits essential requirements of real-world projects. The large-scale BEER is newly studied in the control approach rather than the optimization approach commonly used before. Optimal control is proposed to design optimal retrofitting strategy in terms of maximal energy savings and maximal NPV (net present value). The designed strategy is dynamically changing on dimensions of time, building and technology. The TBT framework and the optimal control approach are verified in a large BEER project, and results indicate that promising performance of energy and cost savings can be achieved in the general TBT framework. - Highlights: • Energy efficiency retrofit of many buildings is studied. • A TBT (time-building-technology) framework is proposed. • The control system of the large-scale BEER is modeled. • The optimal retrofitting strategy is obtained.

Large-scale conformational changes of Trypanosoma cruzi proline racemase predicted by accelerated molecular dynamics simulation.

Directory of Open Access Journals (Sweden)

César Augusto F de Oliveira

2011-10-01

Full Text Available Chagas' disease, caused by the protozoan parasite Trypanosoma cruzi (T. cruzi, is a life-threatening illness affecting 11-18 million people. Currently available treatments are limited, with unacceptable efficacy and safety profiles. Recent studies have revealed an essential T. cruzi proline racemase enzyme (TcPR as an attractive candidate for improved chemotherapeutic intervention. Conformational changes associated with substrate binding to TcPR are believed to expose critical residues that elicit a host mitogenic B-cell response, a process contributing to parasite persistence and immune system evasion. Characterization of the conformational states of TcPR requires access to long-time-scale motions that are currently inaccessible by standard molecular dynamics simulations. Here we describe advanced accelerated molecular dynamics that extend the effective simulation time and capture large-scale motions of functional relevance. Conservation and fragment mapping analyses identified potential conformational epitopes located in the vicinity of newly identified transient binding pockets. The newly identified open TcPR conformations revealed by this study along with knowledge of the closed to open interconversion mechanism advances our understanding of TcPR function. The results and the strategy adopted in this work constitute an important step toward the rationalization of the molecular basis behind the mitogenic B-cell response of TcPR and provide new insights for future structure-based drug discovery.

Properties of liquid clusters in large-scale molecular dynamics nucleation simulations

International Nuclear Information System (INIS)

Angélil, Raymond; Diemand, Jürg; Tanaka, Kyoko K.; Tanaka, Hidekazu

2014-01-01

We have performed large-scale Lennard-Jones molecular dynamics simulations of homogeneous vapor-to-liquid nucleation, with 10 9 atoms. This large number allows us to resolve extremely low nucleation rates, and also provides excellent statistics for cluster properties over a wide range of cluster sizes. The nucleation rates, cluster growth rates, and size distributions are presented in Diemand et al. [J. Chem. Phys. 139, 74309 (2013)], while this paper analyses the properties of the clusters. We explore the cluster temperatures, density profiles, potential energies, and shapes. A thorough understanding of the properties of the clusters is crucial to the formulation of nucleation models. Significant latent heat is retained by stable clusters, by as much as ΔkT = 0.1ε for clusters with size i = 100. We find that the clusters deviate remarkably from spherical—with ellipsoidal axis ratios for critical cluster sizes typically within b/c = 0.7 ± 0.05 and a/c = 0.5 ± 0.05. We examine cluster spin angular momentum, and find that it plays a negligible role in the cluster dynamics. The interfaces of large, stable clusters are thinner than planar equilibrium interfaces by 10%−30%. At the critical cluster size, the cluster central densities are between 5% and 30% lower than the bulk liquid expectations. These lower densities imply larger-than-expected surface areas, which increase the energy cost to form a surface, which lowers nucleation rates

A glimpse of fluid turbulence from the molecular scale

KAUST Repository

Komatsu, Teruhisa S.

2014-08-01

Large-scale molecular dynamics (MD) simulations of freely decaying turbulence in three-dimensional space are reported. Fluid components are defined from the microscopic states by eliminating thermal components from the coarse-grained fields. The energy spectrum of the fluid components is observed to scale reasonably well according to Kolmogorov scaling determined from the energy dissipation rate and the viscosity of the fluid, even though the Kolmogorov length is of the order of the molecular scale. © 2014 The Authors.

Challenges in analysing and visualizing large-scale molecular dynamics simulations: domain and defect formation in lung surfactant monolayers

International Nuclear Information System (INIS)

Mendez-Villuendas, E; Baoukina, S; Tieleman, D P

2012-01-01

Molecular dynamics simulations have rapidly grown in size and complexity, as computers have become more powerful and molecular dynamics software more efficient. Using coarse-grained models like MARTINI system sizes of the order of 50 nm × 50 nm × 50 nm can be simulated on commodity clusters on microsecond time scales. For simulations of biological membranes and monolayers mimicking lung surfactant this enables large-scale transformation and complex mixtures of lipids and proteins. Here we use a simulation of a monolayer with three phospholipid components, cholesterol, lung surfactant proteins, water, and ions on a ten microsecond time scale to illustrate some current challenges in analysis. In the simulation, phase separation occurs followed by formation of a bilayer fold in which lipids and lung surfactant protein form a highly curved structure in the aqueous phase. We use Voronoi analysis to obtain detailed physical properties of the different components and phases, and calculate local mean and Gaussian curvatures of the bilayer fold.

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.

Symplectic integrators for large scale molecular dynamics simulations: A comparison of several explicit methods

International Nuclear Information System (INIS)

Gray, S.K.; Noid, D.W.; Sumpter, B.G.

1994-01-01

We test the suitability of a variety of explicit symplectic integrators for molecular dynamics calculations on Hamiltonian systems. These integrators are extremely simple algorithms with low memory requirements, and appear to be well suited for large scale simulations. We first apply all the methods to a simple test case using the ideas of Berendsen and van Gunsteren. We then use the integrators to generate long time trajectories of a 1000 unit polyethylene chain. Calculations are also performed with two popular but nonsymplectic integrators. The most efficient integrators of the set investigated are deduced. We also discuss certain variations on the basic symplectic integration technique

A Novel Consensus-Based Particle Swarm Optimization-Assisted Trust-Tech Methodology for Large-Scale Global Optimization.

Science.gov (United States)

Zhang, Yong-Feng; Chiang, Hsiao-Dong

2017-09-01

A novel three-stage methodology, termed the "consensus-based particle swarm optimization (PSO)-assisted Trust-Tech methodology," to find global optimal solutions for nonlinear optimization problems is presented. It is composed of Trust-Tech methods, consensus-based PSO, and local optimization methods that are integrated to compute a set of high-quality local optimal solutions that can contain the global optimal solution. The proposed methodology compares very favorably with several recently developed PSO algorithms based on a set of small-dimension benchmark optimization problems and 20 large-dimension test functions from the CEC 2010 competition. The analytical basis for the proposed methodology is also provided. Experimental results demonstrate that the proposed methodology can rapidly obtain high-quality optimal solutions that can contain the global optimal solution. The scalability of the proposed methodology is promising.

LARGE-SCALE TOPOLOGICAL PROPERTIES OF MOLECULAR NETWORKS.

Energy Technology Data Exchange (ETDEWEB)

MASLOV,S.SNEPPEN,K.

2003-11-17

Bio-molecular networks lack the top-down design. Instead, selective forces of biological evolution shape them from raw material provided by random events such as gene duplications and single gene mutations. As a result individual connections in these networks are characterized by a large degree of randomness. One may wonder which connectivity patterns are indeed random, while which arose due to the network growth, evolution, and/or its fundamental design principles and limitations? Here we introduce a general method allowing one to construct a random null-model version of a given network while preserving the desired set of its low-level topological features, such as, e.g., the number of neighbors of individual nodes, the average level of modularity, preferential connections between particular groups of nodes, etc. Such a null-model network can then be used to detect and quantify the non-random topological patterns present in large networks. In particular, we measured correlations between degrees of interacting nodes in protein interaction and regulatory networks in yeast. It was found that in both these networks, links between highly connected proteins are systematically suppressed. This effect decreases the likelihood of cross-talk between different functional modules of the cell, and increases the overall robustness of a network by localizing effects of deleterious perturbations. It also teaches us about the overall computational architecture of such networks and points at the origin of large differences in the number of neighbors of individual nodes.

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.

Expectation propagation for large scale Bayesian inference of non-linear molecular networks from perturbation data.

Science.gov (United States)

Narimani, Zahra; Beigy, Hamid; Ahmad, Ashar; Masoudi-Nejad, Ali; Fröhlich, Holger

2017-01-01

Inferring the structure of molecular networks from time series protein or gene expression data provides valuable information about the complex biological processes of the cell. Causal network structure inference has been approached using different methods in the past. Most causal network inference techniques, such as Dynamic Bayesian Networks and ordinary differential equations, are limited by their computational complexity and thus make large scale inference infeasible. This is specifically true if a Bayesian framework is applied in order to deal with the unavoidable uncertainty about the correct model. We devise a novel Bayesian network reverse engineering approach using ordinary differential equations with the ability to include non-linearity. Besides modeling arbitrary, possibly combinatorial and time dependent perturbations with unknown targets, one of our main contributions is the use of Expectation Propagation, an algorithm for approximate Bayesian inference over large scale network structures in short computation time. We further explore the possibility of integrating prior knowledge into network inference. We evaluate the proposed model on DREAM4 and DREAM8 data and find it competitive against several state-of-the-art existing network inference methods.

Design specific joint optimization of masks and sources on a very large scale

Science.gov (United States)

Lai, K.; Gabrani, M.; Demaris, D.; Casati, N.; Torres, A.; Sarkar, S.; Strenski, P.; Bagheri, S.; Scarpazza, D.; Rosenbluth, A. E.; Melville, D. O.; Wächter, A.; Lee, J.; Austel, V.; Szeto-Millstone, M.; Tian, K.; Barahona, F.; Inoue, T.; Sakamoto, M.

2011-04-01

Joint optimization (JO) of source and mask together is known to produce better SMO solutions than sequential optimization of the source and the mask. However, large scale JO problems are very difficult to solve because the global impact of the source variables causes an enormous number of mask variables to be coupled together. This work presents innovation that minimize this runtime bottleneck. The proposed SMO parallelization algorithm allows separate mask regions to be processed efficiently across multiple CPUs in a high performance computing (HPC) environment, despite the fact that a truly joint optimization is being carried out with source variables that interact across the entire mask. Building on this engine a progressive deletion (PD) method was developed that can directly compute "binding constructs" for the optimization, i.e. our method can essentially determine the particular feature content which limits the process window attainable by the optimum source. This method allows us to minimize the uncertainty inherent to different clustering/ranking methods in seeking an overall optimum source that results from the use of heuristic metrics. An objective benchmarking of the effectiveness of different pattern sampling methods was performed during postoptimization analysis. The PD serves as a golden standard for us to develop optimum pattern clustering/ranking algorithms. With this work, it is shown that it is not necessary to exhaustively optimize the entire mask together with the source in order to identify these binding clips. If the number of clips to be optimized exceeds the practical limit of the parallel SMO engine one can starts with a pattern selection step to achieve high clip count compression before SMO. With this LSSO capability one can address the challenging problem of layout-specific design, or improve the technology source as cell layouts and sample layouts replace lithography test structures in the development cycle.

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 ...

The Modified HZ Conjugate Gradient Algorithm for Large-Scale Nonsmooth Optimization.

Science.gov (United States)

Yuan, Gonglin; Sheng, Zhou; Liu, Wenjie

2016-01-01

In this paper, the Hager and Zhang (HZ) conjugate gradient (CG) method and the modified HZ (MHZ) CG method are presented for large-scale nonsmooth convex minimization. Under some mild conditions, convergent results of the proposed methods are established. Numerical results show that the presented methods can be better efficiency for large-scale nonsmooth problems, and several problems are tested (with the maximum dimensions to 100,000 variables).

The Modified HZ Conjugate Gradient Algorithm for Large-Scale Nonsmooth Optimization.

Directory of Open Access Journals (Sweden)

Gonglin Yuan

Full Text Available In this paper, the Hager and Zhang (HZ conjugate gradient (CG method and the modified HZ (MHZ CG method are presented for large-scale nonsmooth convex minimization. Under some mild conditions, convergent results of the proposed methods are established. Numerical results show that the presented methods can be better efficiency for large-scale nonsmooth problems, and several problems are tested (with the maximum dimensions to 100,000 variables.

Reliability analysis of large scaled structures by optimization technique

International Nuclear Information System (INIS)

Ishikawa, N.; Mihara, T.; Iizuka, M.

1987-01-01

This paper presents a reliability analysis based on the optimization technique using PNET (Probabilistic Network Evaluation Technique) method for the highly redundant structures having a large number of collapse modes. This approach makes the best use of the merit of the optimization technique in which the idea of PNET method is used. The analytical process involves the minimization of safety index of the representative mode, subjected to satisfaction of the mechanism condition and of the positive external work. The procedure entails the sequential performance of a series of the NLP (Nonlinear Programming) problems, where the correlation condition as the idea of PNET method pertaining to the representative mode is taken as an additional constraint to the next analysis. Upon succeeding iterations, the final analysis is achieved when a collapse probability at the subsequent mode is extremely less than the value at the 1st mode. The approximate collapse probability of the structure is defined as the sum of the collapse probabilities of the representative modes classified by the extent of correlation. Then, in order to confirm the validity of the proposed method, the conventional Monte Carlo simulation is also revised by using the collapse load analysis. Finally, two fairly large structures were analyzed to illustrate the scope and application of the approach. (orig./HP)

SWAP-Assembler 2: Optimization of De Novo Genome Assembler at Large Scale

Energy Technology Data Exchange (ETDEWEB)

Meng, Jintao; Seo, Sangmin; Balaji, Pavan; Wei, Yanjie; Wang, Bingqiang; Feng, Shengzhong

2016-08-16

In this paper, we analyze and optimize the most time-consuming steps of the SWAP-Assembler, a parallel genome assembler, so that it can scale to a large number of cores for huge genomes with the size of sequencing data ranging from terabyes to petabytes. According to the performance analysis results, the most time-consuming steps are input parallelization, k-mer graph construction, and graph simplification (edge merging). For the input parallelization, the input data is divided into virtual fragments with nearly equal size, and the start position and end position of each fragment are automatically separated at the beginning of the reads. In k-mer graph construction, in order to improve the communication efficiency, the message size is kept constant between any two processes by proportionally increasing the number of nucleotides to the number of processes in the input parallelization step for each round. The memory usage is also decreased because only a small part of the input data is processed in each round. With graph simplification, the communication protocol reduces the number of communication loops from four to two loops and decreases the idle communication time. The optimized assembler is denoted as SWAP-Assembler 2 (SWAP2). In our experiments using a 1000 Genomes project dataset of 4 terabytes (the largest dataset ever used for assembling) on the supercomputer Mira, the results show that SWAP2 scales to 131,072 cores with an efficiency of 40%. We also compared our work with both the HipMER assembler and the SWAP-Assembler. On the Yanhuang dataset of 300 gigabytes, SWAP2 shows a 3X speedup and 4X better scalability compared with the HipMer assembler and is 45 times faster than the SWAP-Assembler. The SWAP2 software is available at https://sourceforge.net/projects/swapassembler.

Optimal defense resource allocation in scale-free networks

Science.gov (United States)

Zhang, Xuejun; Xu, Guoqiang; Xia, Yongxiang

2018-02-01

The robustness research of networked systems has drawn widespread attention in the past decade, and one of the central topics is to protect the network from external attacks through allocating appropriate defense resource to different nodes. In this paper, we apply a specific particle swarm optimization (PSO) algorithm to optimize the defense resource allocation in scale-free networks. Results reveal that PSO based resource allocation shows a higher robustness than other resource allocation strategies such as uniform, degree-proportional, and betweenness-proportional allocation strategies. Furthermore, we find that assigning less resource to middle-degree nodes under small-scale attack while more resource to low-degree nodes under large-scale attack is conductive to improving the network robustness. Our work provides an insight into the optimal defense resource allocation pattern in scale-free networks and is helpful for designing a more robust network.

Computational optimization of catalyst distributions at the nano-scale

International Nuclear Information System (INIS)

Ström, Henrik

2017-01-01

Highlights: • Macroscopic data sampled from a DSMC simulation contain statistical scatter. • Simulated annealing is evaluated as an optimization algorithm with DSMC. • Proposed method is more robust than a gradient search method. • Objective function uses the mass transfer rate instead of the reaction rate. • Combined algorithm is more efficient than a macroscopic overlay method. - Abstract: Catalysis is a key phenomenon in a great number of energy processes, including feedstock conversion, tar cracking, emission abatement and optimizations of energy use. Within heterogeneous, catalytic nano-scale systems, the chemical reactions typically proceed at very high rates at a gas–solid interface. However, the statistical uncertainties characteristic of molecular processes pose efficiency problems for computational optimizations of such nano-scale systems. The present work investigates the performance of a Direct Simulation Monte Carlo (DSMC) code with a stochastic optimization heuristic for evaluations of an optimal catalyst distribution. The DSMC code treats molecular motion with homogeneous and heterogeneous chemical reactions in wall-bounded systems and algorithms have been devised that allow optimization of the distribution of a catalytically active material within a three-dimensional duct (e.g. a pore). The objective function is the outlet concentration of computational molecules that have interacted with the catalytically active surface, and the optimization method used is simulated annealing. The application of a stochastic optimization heuristic is shown to be more efficient within the present DSMC framework than using a macroscopic overlay method. Furthermore, it is shown that the performance of the developed method is superior to that of a gradient search method for the current class of problems. Finally, the advantages and disadvantages of different types of objective functions are discussed.

Primal Interior-Point Method for Large Sparse Minimax Optimization

Czech Academy of Sciences Publication Activity Database

Lukšan, Ladislav; Matonoha, Ctirad; Vlček, Jan

2009-01-01

Roč. 45, č. 5 (2009), s. 841-864 ISSN 0023-5954 R&D Projects: GA AV ČR IAA1030405; GA ČR GP201/06/P397 Institutional research plan: CEZ:AV0Z10300504 Keywords : unconstrained optimization * large-scale optimization * minimax optimization * nonsmooth optimization * interior-point methods * modified Newton methods * variable metric methods * computational experiments Subject RIV: BA - General Mathematics Impact factor: 0.445, year: 2009 http://dml.cz/handle/10338.dmlcz/140034

Large Scale GW Calculations on the Cori System

Science.gov (United States)

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

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

Cooperative Coevolution with Formula-Based Variable Grouping for Large-Scale Global Optimization.

Science.gov (United States)

Wang, Yuping; Liu, Haiyan; Wei, Fei; Zong, Tingting; Li, Xiaodong

2017-08-09

For a large-scale global optimization (LSGO) problem, divide-and-conquer is usually considered an effective strategy to decompose the problem into smaller subproblems, each of which can then be solved individually. Among these decomposition methods, variable grouping is shown to be promising in recent years. Existing variable grouping methods usually assume the problem to be black-box (i.e., assuming that an analytical model of the objective function is unknown), and they attempt to learn appropriate variable grouping that would allow for a better decomposition of the problem. In such cases, these variable grouping methods do not make a direct use of the formula of the objective function. However, it can be argued that many real-world problems are white-box problems, that is, the formulas of objective functions are often known a priori. These formulas of the objective functions provide rich information which can then be used to design an effective variable group method. In this article, a formula-based grouping strategy (FBG) for white-box problems is first proposed. It groups variables directly via the formula of an objective function which usually consists of a finite number of operations (i.e., four arithmetic operations "[Formula: see text]", "[Formula: see text]", "[Formula: see text]", "[Formula: see text]" and composite operations of basic elementary functions). In FBG, the operations are classified into two classes: one resulting in nonseparable variables, and the other resulting in separable variables. In FBG, variables can be automatically grouped into a suitable number of non-interacting subcomponents, with variables in each subcomponent being interdependent. FBG can easily be applied to any white-box problem and can be integrated into a cooperative coevolution framework. Based on FBG, a novel cooperative coevolution algorithm with formula-based variable grouping (so-called CCF) is proposed in this article for decomposing a large-scale white-box problem

Molecular device computer: point of departure for large scale cellular automata

Energy Technology Data Exchange (ETDEWEB)

Carter, F L

1984-01-01

Switching is possible at the molecular size level because of the conformational changes that occur. Three of the most promising switching mechanisms include electron tunnelling in short periodic arrays, soliton switching and soliton valving. Assuming a 3-d architecture and molecular dimensions, memory and switching elements with densities of 10/sup 15/ to 10 /sup 18/ elements per cc are possible. The active elements are connected together conceptionally with molecular wires like polysulfur nitride (sn)/sub x/ and polyacetylene (ch)/sub x/. Simple cellular automata involving soliton propagation in conjugated systems would include soliton valves and cyclic configurations of valves. In the latter, soliton propagation becomes isomorphous with group operations giving rise to possible non-binary finite-state machines. The development of a molecular electron device (MED) synthetic capability in combination with the above devices would suggest that large 3-d arrays of parallel processors will be possible with automata, biological, and crystallographic implications. 41 references.

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

KAUST Repository

Hasanov, Khalid; Quintin, Jean-Noë l; Lastovetsky, Alexey

2014-01-01

-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

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)

The temperature of large dust grains in molecular clouds

Science.gov (United States)

Clark, F. O.; Laureijs, R. J.; Prusti, T.

1991-01-01

The temperature of the large dust grains is calculated from three molecular clouds ranging in visual extinction from 2.5 to 8 mag, by comparing maps of either extinction derived from star counts or gas column density derived from molecular observations to I(100). Both techniques show the dust temperature declining into clouds. The two techniques do not agree in absolute scale.

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.

LARGE-SCALE CO MAPS OF THE LUPUS MOLECULAR CLOUD COMPLEX

International Nuclear Information System (INIS)

Tothill, N. F. H.; Loehr, A.; Stark, A. A.; Lane, A. P.; Harnett, J. I.; Bourke, T. L.; Myers, P. C.; Parshley, S. C.; Wright, G. A.; Walker, C. K.

2009-01-01

Fully sampled degree-scale maps of the 13 CO 2-1 and CO 4-3 transitions toward three members of the Lupus Molecular Cloud Complex-Lupus I, III, and IV-trace the column density and temperature of the molecular gas. Comparison with IR extinction maps from the c2d project requires most of the gas to have a temperature of 8-10 K. Estimates of the cloud mass from 13 CO emission are roughly consistent with most previous estimates, while the line widths are higher, around 2 km s -1 . CO 4-3 emission is found throughout Lupus I, indicating widespread dense gas, and toward Lupus III and IV. Enhanced line widths at the NW end and along the edge of the B 228 ridge in Lupus I, and a coherent velocity gradient across the ridge, are consistent with interaction between the molecular cloud and an expanding H I shell from the Upper-Scorpius subgroup of the Sco-Cen OB Association. Lupus III is dominated by the effects of two HAe/Be stars, and shows no sign of external influence. Slightly warmer gas around the core of Lupus IV and a low line width suggest heating by the Upper-Centaurus-Lupus subgroup of Sco-Cen, without the effects of an H I shell.

Energy modeling and analysis for optimal grid integration of large-scale variable renewables using hydrogen storage in Japan

International Nuclear Information System (INIS)

Komiyama, Ryoichi; Otsuki, Takashi; Fujii, Yasumasa

2015-01-01

Although the extensive introduction of VRs (variable renewables) will play an essential role to resolve energy and environmental issues in Japan after the Fukushima nuclear accident, its large-scale integration would pose a technical challenge in the grid management; as one of technical countermeasures, hydrogen storage receives much attention, as well as rechargeable battery, for controlling the intermittency of VR power output. For properly planning renewable energy policies, energy system modeling is important to quantify and qualitatively understand its potential benefits and impacts. This paper analyzes the optimal grid integration of large-scale VRs using hydrogen storage in Japan by developing a high time-resolution optimal power generation mix model. Simulation results suggest that the installation of hydrogen storage is promoted by both its cost reduction and CO 2 regulation policy. In addition, hydrogen storage turns out to be suitable for storing VR energy in a long period of time. Finally, through a sensitivity analysis of rechargeable battery cost, hydrogen storage is economically competitive with rechargeable battery; the cost of both technologies should be more elaborately recognized for formulating effective energy policies to integrate massive VRs into the country's power system in an economical manner. - Highlights: • Authors analyze hydrogen storage coupled with VRs (variable renewables). • Simulation analysis is done by developing an optimal power generation mix model. • Hydrogen storage installation is promoted by its cost decline and CO 2 regulation. • Hydrogen storage is suitable for storing VR energy in a long period of time. • Hydrogen storage is economically competitive with rechargeable battery

Low-Complexity Transmit Antenna Selection and Beamforming for Large-Scale MIMO Communications

Directory of Open Access Journals (Sweden)

Kun Qian

2014-01-01

Full Text Available Transmit antenna selection plays an important role in large-scale multiple-input multiple-output (MIMO communications, but optimal large-scale MIMO antenna selection is a technical challenge. Exhaustive search is often employed in antenna selection, but it cannot be efficiently implemented in large-scale MIMO communication systems due to its prohibitive high computation complexity. This paper proposes a low-complexity interactive multiple-parameter optimization method for joint transmit antenna selection and beamforming in large-scale MIMO communication systems. The objective is to jointly maximize the channel outrage capacity and signal-to-noise (SNR performance and minimize the mean square error in transmit antenna selection and minimum variance distortionless response (MVDR beamforming without exhaustive search. The effectiveness of all the proposed methods is verified by extensive simulation results. It is shown that the required antenna selection processing time of the proposed method does not increase along with the increase of selected antennas, but the computation complexity of conventional exhaustive search method will significantly increase when large-scale antennas are employed in the system. This is particularly useful in antenna selection for large-scale MIMO communication systems.

Dynamic Reactive Power Compensation of Large Scale Wind Integrated Power System

DEFF Research Database (Denmark)

Rather, Zakir Hussain; Chen, Zhe; Thøgersen, Paul

2015-01-01

wind turbines especially wind farms with additional grid support functionalities like dynamic support (e,g dynamic reactive power support etc.) and ii) refurbishment of existing conventional central power plants to synchronous condensers could be one of the efficient, reliable and cost effective option......Due to progressive displacement of conventional power plants by wind turbines, dynamic security of large scale wind integrated power systems gets significantly compromised. In this paper we first highlight the importance of dynamic reactive power support/voltage security in large scale wind...... integrated power systems with least presence of conventional power plants. Then we propose a mixed integer dynamic optimization based method for optimal dynamic reactive power allocation in large scale wind integrated power systems. One of the important aspects of the proposed methodology is that unlike...

A primal-dual interior point method for large-scale free material optimization

DEFF Research Database (Denmark)

Weldeyesus, Alemseged Gebrehiwot; Stolpe, Mathias

2015-01-01

Free Material Optimization (FMO) is a branch of structural optimization in which the design variable is the elastic material tensor that is allowed to vary over the design domain. The requirements are that the material tensor is symmetric positive semidefinite with bounded trace. The resulting...... optimization problem is a nonlinear semidefinite program with many small matrix inequalities for which a special-purpose optimization method should be developed. The objective of this article is to propose an efficient primal-dual interior point method for FMO that can robustly and accurately solve large...... of iterations the interior point method requires is modest and increases only marginally with problem size. The computed optimal solutions obtain a higher precision than other available special-purpose methods for FMO. The efficiency and robustness of the method is demonstrated by numerical experiments on a set...

Large-scale integration of optimal combinations of PV, wind and wave power into the electricity supply

DEFF Research Database (Denmark)

Lund, Henrik

2006-01-01

This article presents the results of analyses of large-scale integration of wind power, photo voltaic (PV) and wave power into a Danish reference energy system. The possibility of integrating Renewable Energy Sources (RES) into the electricity supply is expressed in terms of the ability to avoid...... ancillary services are needed in order to secure the electricity supply system. The idea is to benefit from the different patterns in the fluctuations of different renewable sources. And the purpose is to identify optimal mixtures from a technical point of view. The optimal mixture seems to be when onshore...... wind power produces approximately 50% of the total electricity production from RES. Meanwhile, the mixture between PV and wave power seems to depend on the total amount of electricity production from RES. When the total RES input is below 20% of demand, PV should cover 40% and wave power only 10%. When...

Image-based Exploration of Large-Scale Pathline Fields

KAUST Repository

Nagoor, Omniah H.

2014-01-01

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

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...

Dynamic Modeling, Optimization, and Advanced Control for Large Scale Biorefineries

DEFF Research Database (Denmark)

Prunescu, Remus Mihail

with a complex conversion route. Computational fluid dynamics is used to model transport phenomena in large reactors capturing tank profiles, and delays due to plug flows. This work publishes for the first time demonstration scale real data for validation showing that the model library is suitable...

Performance evaluation of the DCMD desalination process under bench scale and large scale module operating conditions

KAUST Repository

Francis, Lijo

2014-04-01

The flux performance of different hydrophobic microporous flat sheet commercial membranes made of poly tetrafluoroethylene (PTFE) and poly propylene (PP) was tested for Red Sea water desalination using the direct contact membrane distillation (DCMD) process, under bench scale (high δT) and large scale module (low δT) operating conditions. Membranes were characterized for their surface morphology, water contact angle, thickness, porosity, pore size and pore size distribution. The DCMD process performance was optimized using a locally designed and fabricated module aiming to maximize the flux at different levels of operating parameters, mainly feed water and coolant inlet temperatures at different temperature differences across the membrane (δT). Water vapor flux of 88.8kg/m2h was obtained using a PTFE membrane at high δT (60°C). In addition, the flux performance was compared to the first generation of a new locally synthesized and fabricated membrane made of a different class of polymer under the same conditions. A total salt rejection of 99.99% and boron rejection of 99.41% were achieved under extreme operating conditions. On the other hand, a detailed water characterization revealed that low molecular weight non-ionic molecules (ppb level) were transported with the water vapor molecules through the membrane structure. The membrane which provided the highest flux was then tested under large scale module operating conditions. The average flux of the latter study (low δT) was found to be eight times lower than that of the bench scale (high δT) operating conditions.

Performance evaluation of the DCMD desalination process under bench scale and large scale module operating conditions

KAUST Repository

Francis, Lijo; Ghaffour, NorEddine; Alsaadi, Ahmad Salem; Nunes, Suzana Pereira; Amy, Gary L.

2014-01-01

The flux performance of different hydrophobic microporous flat sheet commercial membranes made of poly tetrafluoroethylene (PTFE) and poly propylene (PP) was tested for Red Sea water desalination using the direct contact membrane distillation (DCMD) process, under bench scale (high δT) and large scale module (low δT) operating conditions. Membranes were characterized for their surface morphology, water contact angle, thickness, porosity, pore size and pore size distribution. The DCMD process performance was optimized using a locally designed and fabricated module aiming to maximize the flux at different levels of operating parameters, mainly feed water and coolant inlet temperatures at different temperature differences across the membrane (δT). Water vapor flux of 88.8kg/m2h was obtained using a PTFE membrane at high δT (60°C). In addition, the flux performance was compared to the first generation of a new locally synthesized and fabricated membrane made of a different class of polymer under the same conditions. A total salt rejection of 99.99% and boron rejection of 99.41% were achieved under extreme operating conditions. On the other hand, a detailed water characterization revealed that low molecular weight non-ionic molecules (ppb level) were transported with the water vapor molecules through the membrane structure. The membrane which provided the highest flux was then tested under large scale module operating conditions. The average flux of the latter study (low δT) was found to be eight times lower than that of the bench scale (high δT) operating conditions.

Optimal charging scheduling for large-scale EV (electric vehicle) deployment based on the interaction of the smart-grid and intelligent-transport systems

International Nuclear Information System (INIS)

Luo, Yugong; Zhu, Tao; Wan, Shuang; Zhang, Shuwei; Li, Keqiang

2016-01-01

The widespread use of electric vehicles (EVs) is becoming an imminent trend. Research has been done on the scheduling of EVs from the perspective of the charging characteristic, improvement in the safety and economy of the power grid, or the traffic jams in the transport system caused by a large number of EVs driven to charging stations. There is a lack of systematic studies considering EVs, the power grid, and the transport system all together. In this paper, a novel optimal charging scheduling strategy for different types of EVs is proposed based on not only transport system information, such as road length, vehicle velocity and waiting time, but also grid system information, such as load deviation and node voltage. In addition, a charging scheduling simulation platform suitable for large-scale EV deployment is developed based on actual charging scenarios. The simulation results show that the improvements in both the transport system efficiency and the grid system operation can be obtained by using the optimal strategy, such as the node voltage drop is decreased, the power loss is reduced, and the load curve is optimized. - Highlights: • A novel optimal charging scheduling strategy is proposed for different electric vehicles (EVs). • A simulation platform suitable for large-scale EV deployment is established. • The traffic congestion near the charging and battery-switch stations is relieved. • The safety and economy problems of the distribution network are solved. • The peak-to-valley load of the distribution system is reduced.

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.

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.

Comparative Analysis of Different Protocols to Manage Large Scale Networks

OpenAIRE

Anil Rao Pimplapure; Dr Jayant Dubey; Prashant Sen

2013-01-01

In recent year the numbers, complexity and size is increased in Large Scale Network. The best example of Large Scale Network is Internet, and recently once are Data-centers in Cloud Environment. In this process, involvement of several management tasks such as traffic monitoring, security and performance optimization is big task for Network Administrator. This research reports study the different protocols i.e. conventional protocols like Simple Network Management Protocol and newly Gossip bas...

Novel material and structural design for large-scale marine protective devices

International Nuclear Information System (INIS)

Qiu, Ang; Lin, Wei; Ma, Yong; Zhao, Chengbi; Tang, Youhong

2015-01-01

Highlights: • Large-scale protective devices with different structural designs have been optimized. • Large-scale protective devices with novel material designs have been optimized. • Protective devices constructed of sandwich panels have the best anti-collision performance. • Protective devices with novel material design can reduce weight and construction cost. - Abstract: Large-scale protective devices must endure the impact of severe forces, large structural deformation, the increased stress and strain rate effects, and multiple coupling effects. In evaluation of the safety of conceptual design through simulation, several key parameters considered in this research are maximum impact force, energy dissipated by the impactor (e.g. a ship) and energy absorbed by the device and the impactor stroke. During impact, the main function of the ring beam structure is to resist and buffer the impact force between ship and bridge pile caps, which could guarantee that the magnitude of impact force meets the corresponding requirements. The means of improving anti-collision performance can be to increase the strength of the beam section or to exchange the steel material with novel fiber reinforced polymer laminates. The main function of the buoyancy tank is to absorb and transfer the ship’s kinetic energy through large plastic deformation, damage, or friction occurring within itself. The energy absorption effect can be improved by structure optimization or by the use of new sandwich panels. Structural and material optimization schemes are proposed on the basis of conceptual design in this research, and protective devices constructed of sandwich panels prove to have the best anti-collision performance

A resource of large-scale molecular markers for monitoring Agropyron cristatum chromatin introgression in wheat background based on transcriptome sequences.

Science.gov (United States)

Zhang, Jinpeng; Liu, Weihua; Lu, Yuqing; Liu, Qunxing; Yang, Xinming; Li, Xiuquan; Li, Lihui

2017-09-20

Agropyron cristatum is a wild grass of the tribe Triticeae and serves as a gene donor for wheat improvement. However, very few markers can be used to monitor A. cristatum chromatin introgressions in wheat. Here, we reported a resource of large-scale molecular markers for tracking alien introgressions in wheat based on transcriptome sequences. By aligning A. cristatum unigenes with the Chinese Spring reference genome sequences, we designed 9602 A. cristatum expressed sequence tag-sequence-tagged site (EST-STS) markers for PCR amplification and experimental screening. As a result, 6063 polymorphic EST-STS markers were specific for the A. cristatum P genome in the single-receipt wheat background. A total of 4956 randomly selected polymorphic EST-STS markers were further tested in eight wheat variety backgrounds, and 3070 markers displaying stable and polymorphic amplification were validated. These markers covered more than 98% of the A. cristatum genome, and the marker distribution density was approximately 1.28 cM. An application case of all EST-STS markers was validated on the A. cristatum 6 P chromosome. These markers were successfully applied in the tracking of alien A. cristatum chromatin. Altogether, this study provided a universal method of large-scale molecular marker development to monitor wild relative chromatin in wheat.

Large Deviations for Two-Time-Scale Diffusions, with Delays

International Nuclear Information System (INIS)

Kushner, Harold J.

2010-01-01

We consider the problem of large deviations for a two-time-scale reflected diffusion process, possibly with delays in the dynamical terms. The Dupuis-Ellis weak convergence approach is used. It is perhaps the most intuitive and simplest for the problems of concern. The results have applications to the problem of approximating optimal controls for two-time-scale systems via use of the averaged equation.

Simulation-optimization of large agro-hydrosystems using a decomposition approach

Science.gov (United States)

Schuetze, Niels; Grundmann, Jens

2014-05-01

In this contribution a stochastic simulation-optimization framework for decision support for optimal planning and operation of water supply of large agro-hydrosystems is presented. It is based on a decomposition solution strategy which allows for (i) the usage of numerical process models together with efficient Monte Carlo simulations for a reliable estimation of higher quantiles of the minimum agricultural water demand for full and deficit irrigation strategies at small scale (farm level), and (ii) the utilization of the optimization results at small scale for solving water resources management problems at regional scale. As a secondary result of several simulation-optimization runs at the smaller scale stochastic crop-water production functions (SCWPF) for different crops are derived which can be used as a basic tool for assessing the impact of climate variability on risk for potential yield. In addition, microeconomic impacts of climate change and the vulnerability of the agro-ecological systems are evaluated. The developed methodology is demonstrated through its application on a real-world case study for the South Al-Batinah region in the Sultanate of Oman where a coastal aquifer is affected by saltwater intrusion due to excessive groundwater withdrawal for irrigated agriculture.

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...

Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.

Science.gov (United States)

Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen

2017-02-01

Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too. Our solution (PSOMCS) is to use particle swarm optimization (PSO) along with the direct calculation of cMCSs from the stoichiometric matrix to obtain optimal designs satisfying multiple objectives. To illustrate the working of PSOMCS, we apply it to a toy network. Next we show its superiority by comparing its performance against other comparable methods on a medium sized E. coli core metabolic network. PSOMCS not only finds solutions comparable to previously published results but also it is orders of magnitude faster. Finally, we use PSOMCS to predict knockouts satisfying multiple objectives in a genome-scale metabolic model of E. coli and compare it with OptKnock and RobustKnock. PSOMCS finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. It can be used in identifying knockouts which will force optimal desired behaviors in large and genome scale metabolic networks. It will be even more useful as larger metabolic models of industrially relevant organisms become available.

EFFECTS OF LARGE-SCALE POULTRY FARMS ON AQUATIC MICROBIAL COMMUNITIES: A MOLECULAR INVESTIGATION.

Science.gov (United States)

The effects of large-scale poultry production operations on water quality and human health are largely unknown. Poultry litter is frequently applied as fertilizer to agricultural lands adjacent to large poultry farms. Run-off from the land introduces a variety of stressors into t...

Mathematical modelling and optimization of a large-scale combined cooling, heat, and power system that incorporates unit changeover and time-of-use electricity price

International Nuclear Information System (INIS)

Zhu, Qiannan; Luo, Xianglong; Zhang, Bingjian; Chen, Ying

2017-01-01

Highlights: • We propose a novel superstructure for the design and optimization of LSCCHP. • A multi-objective multi-period MINLP model is formulated. • The unit start-up cost and time-of-use electricity prices are involved. • Unit size discretization strategy is proposed to linearize the original MINLP model. • A case study is elaborated to demonstrate the effectiveness of the proposed method. - Abstract: Building energy systems, particularly large public ones, are major energy consumers and pollutant emission contributors. In this study, a superstructure of large-scale combined cooling, heat, and power system is constructed. The off-design unit, economic cost, and CO_2 emission models are also formulated. Moreover, a multi-objective mixed integer nonlinear programming model is formulated for the simultaneous system synthesis, technology selection, unit sizing, and operation optimization of large-scale combined cooling, heat, and power system. Time-of-use electricity price and unit changeover cost are incorporated into the problem model. The economic objective is to minimize the total annual cost, which comprises the operation and investment costs of large-scale combined cooling, heat, and power system. The environmental objective is to minimize the annual global CO_2 emission of large-scale combined cooling, heat, and power system. The augmented ε–constraint method is applied to achieve the Pareto frontier of the design configuration, thereby reflecting the set of solutions that represent optimal trade-offs between the economic and environmental objectives. Sensitivity analysis is conducted to reflect the impact of natural gas price on the combined cooling, heat, and power system. The synthesis and design of combined cooling, heat, and power system for an airport in China is studied to test the proposed synthesis and design methodology. The Pareto curve of multi-objective optimization shows that the total annual cost varies from 102.53 to 94.59 M

Optimization of Large-Scale Culture Conditions for the Production of Cordycepin with Cordyceps militaris by Liquid Static Culture

Directory of Open Access Journals (Sweden)

Chao Kang

2014-01-01

Full Text Available Cordycepin is one of the most important bioactive compounds produced by species of Cordyceps sensu lato, but it is hard to produce large amounts of this substance in industrial production. In this work, single factor design, Plackett-Burman design, and central composite design were employed to establish the key factors and identify optimal culture conditions which improved cordycepin production. Using these culture conditions, a maximum production of cordycepin was 2008.48 mg/L for 700 mL working volume in the 1000 mL glass jars and total content of cordycepin reached 1405.94 mg/bottle. This method provides an effective way for increasing the cordycepin production at a large scale. The strategies used in this study could have a wide application in other fermentation processes.

Scale economies and optimal size in the Swiss gas distribution sector

International Nuclear Information System (INIS)

Alaeifar, Mozhgan; Farsi, Mehdi; Filippini, Massimo

2014-01-01

This paper studies the cost structure of Swiss gas distribution utilities. Several econometric models are applied to a panel of 26 companies over 1996–2000. Our main objective is to estimate the optimal size and scale economies of the industry and to study their possible variation with respect to network characteristics. The results indicate the presence of unexploited scale economies. However, very large companies in the sample and companies with a disproportionate mixture of output and density present an exception. Furthermore, the estimated optimal size for majority of companies in the sample has shown a value far greater than the actual size, suggesting remarkable efficiency gains by reorganization of the industry. The results also highlight the effect of customer density on optimal size. Networks with higher density or greater complexity have a lower optimal size. - highlights: • Presence of unexploited scale economies for small and medium sized companies. • Scale economies vary considerably with customer density. • Higher density or greater complexity is associated with lower optimal size. • Optimal size varies across the companies through unobserved heterogeneity. • Firms with low density can gain more from expanding firm size

Large scale IRAM 30 m CO-observations in the giant molecular cloud complex W43

Science.gov (United States)

Carlhoff, P.; Nguyen Luong, Q.; Schilke, P.; Motte, F.; Schneider, N.; Beuther, H.; Bontemps, S.; Heitsch, F.; Hill, T.; Kramer, C.; Ossenkopf, V.; Schuller, F.; Simon, R.; Wyrowski, F.

2013-12-01

We aim to fully describe the distribution and location of dense molecular clouds in the giant molecular cloud complex W43. It was previously identified as one of the most massive star-forming regions in our Galaxy. To trace the moderately dense molecular clouds in the W43 region, we initiated W43-HERO, a large program using the IRAM 30 m telescope, which covers a wide dynamic range of scales from 0.3 to 140 pc. We obtained on-the-fly-maps in 13CO (2-1) and C18O (2-1) with a high spectral resolution of 0.1 km s-1 and a spatial resolution of 12''. These maps cover an area of ~1.5 square degrees and include the two main clouds of W43 and the lower density gas surrounding them. A comparison to Galactic models and previous distance calculations confirms the location of W43 near the tangential point of the Scutum arm at approximately 6 kpc from the Sun. The resulting intensity cubes of the observed region are separated into subcubes, which are centered on single clouds and then analyzed in detail. The optical depth, excitation temperature, and H2 column density maps are derived out of the 13CO and C18O data. These results are then compared to those derived from Herschel dust maps. The mass of a typical cloud is several 104 M⊙ while the total mass in the dense molecular gas (>102 cm-3) in W43 is found to be ~1.9 × 106 M⊙. Probability distribution functions obtained from column density maps derived from molecular line data and Herschel imaging show a log-normal distribution for low column densities and a power-law tail for high densities. A flatter slope for the molecular line data probability distribution function may imply that those selectively show the gravitationally collapsing gas. Appendices are available in electronic form at http://www.aanda.orgThe final datacubes (13CO and C18O) for the entire survey are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/560/A24

Quantum Monte Carlo for large chemical systems: implementing efficient strategies for peta scale platforms and beyond

International Nuclear Information System (INIS)

Scemama, Anthony; Caffarel, Michel; Oseret, Emmanuel; Jalby, William

2013-01-01

Various strategies to implement efficiently quantum Monte Carlo (QMC) simulations for large chemical systems are presented. These include: (i) the introduction of an efficient algorithm to calculate the computationally expensive Slater matrices. This novel scheme is based on the use of the highly localized character of atomic Gaussian basis functions (not the molecular orbitals as usually done), (ii) the possibility of keeping the memory footprint minimal, (iii) the important enhancement of single-core performance when efficient optimization tools are used, and (iv) the definition of a universal, dynamic, fault-tolerant, and load-balanced framework adapted to all kinds of computational platforms (massively parallel machines, clusters, or distributed grids). These strategies have been implemented in the QMC-Chem code developed at Toulouse and illustrated with numerical applications on small peptides of increasing sizes (158, 434, 1056, and 1731 electrons). Using 10-80 k computing cores of the Curie machine (GENCI-TGCC-CEA, France), QMC-Chem has been shown to be capable of running at the peta scale level, thus demonstrating that for this machine a large part of the peak performance can be achieved. Implementation of large-scale QMC simulations for future exa scale platforms with a comparable level of efficiency is expected to be feasible. (authors)

Optimization methodology for large scale fin geometry on the steel containment of a Public Acceptable Simple SMR (PASS)

International Nuclear Information System (INIS)

Kim, Do Yun; NO, Hee Cheon; Kim, Ho Sik

2015-01-01

Highlights: • Optimization methodology for fin geometry on the steel containment is established. • Optimum spacing is 7 cm in PASS containment. • Optimum thickness is 0.9–1.8 cm when a fin height is 10–25 cm. • Optimal fin geometry is determined in given fin height by overall effectiveness correlation. • 13% of material volume and 43% of containment volume are reduced by using fins. - Abstracts: Heat removal capability through a steel containment is important in accident situations to preserve the integrity of a nuclear power plant which adopts a steel containment concept. A heat transfer rate will be enhanced by using fins on the external surface of the steel containment. The fins, however, cause to increase flow resistance and to deteriorate the heat transfer rate at the same time. Therefore, this study investigates an optimization methodology of large scale fin geometry for a vertical base where a natural convection flow regime is turbulent. Rectangular plate fins adopted in the steel containment of a Public Acceptable Simple SMR (PASS) is used as a reference. The heat transfer rate through the fins is obtained from CFD tools. In order to optimize fin geometry, an overall effectiveness concept is introduced as a fin performance parameter. The optimizing procedure is starting from finding optimum spacing. Then, optimum thickness is calculated and finally optimal fin geometry is suggested. Scale analysis is conducted to show the existence of an optimum spacing which turns out to be 7 cm in case of PASS. Optimum thickness is obtained by the overall effectiveness correlation, which is derived from a total heat transfer coefficient correlation. The total heat transfer coefficient correlation of a vertical fin array is suggested considering both of natural convection and radiation. However, the optimum thickness is changed as a fin height varies. Therefore, optimal fin geometry is obtained as a function of a fin height. With the assumption that the heat

Derivation of Optimal Operating Rules for Large-scale Reservoir Systems Considering Multiple Trade-off

Science.gov (United States)

Zhang, J.; Lei, X.; Liu, P.; Wang, H.; Li, Z.

2017-12-01

Flood control operation of multi-reservoir systems such as parallel reservoirs and hybrid reservoirs often suffer from complex interactions and trade-off among tributaries and the mainstream. The optimization of such systems is computationally intensive due to nonlinear storage curves, numerous constraints and complex hydraulic connections. This paper aims to derive the optimal flood control operating rules based on the trade-off among tributaries and the mainstream using a new algorithm known as weighted non-dominated sorting genetic algorithm II (WNSGA II). WNSGA II could locate the Pareto frontier in non-dominated region efficiently due to the directed searching by weighted crowding distance, and the results are compared with those of conventional operating rules (COR) and single objective genetic algorithm (GA). Xijiang river basin in China is selected as a case study, with eight reservoirs and five flood control sections within four tributaries and the mainstream. Furthermore, the effects of inflow uncertainty have been assessed. Results indicate that: (1) WNSGA II could locate the non-dominated solutions faster and provide better Pareto frontier than the traditional non-dominated sorting genetic algorithm II (NSGA II) due to the weighted crowding distance; (2) WNSGA II outperforms COR and GA on flood control in the whole basin; (3) The multi-objective operating rules from WNSGA II deal with the inflow uncertainties better than COR. Therefore, the WNSGA II can be used to derive stable operating rules for large-scale reservoir systems effectively and efficiently.

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].

Time scale of diffusion in molecular and cellular biology

International Nuclear Information System (INIS)

Holcman, D; Schuss, Z

2014-01-01

Diffusion is the driver of critical biological processes in cellular and molecular biology. The diverse temporal scales of cellular function are determined by vastly diverse spatial scales in most biophysical processes. The latter are due, among others, to small binding sites inside or on the cell membrane or to narrow passages between large cellular compartments. The great disparity in scales is at the root of the difficulty in quantifying cell function from molecular dynamics and from simulations. The coarse-grained time scale of cellular function is determined from molecular diffusion by the mean first passage time of molecular Brownian motion to a small targets or through narrow passages. The narrow escape theory (NET) concerns this issue. The NET is ubiquitous in molecular and cellular biology and is manifested, among others, in chemical reactions, in the calculation of the effective diffusion coefficient of receptors diffusing on a neuronal cell membrane strewn with obstacles, in the quantification of the early steps of viral trafficking, in the regulation of diffusion between the mother and daughter cells during cell division, and many other cases. Brownian trajectories can represent the motion of a molecule, a protein, an ion in solution, a receptor in a cell or on its membrane, and many other biochemical processes. The small target can represent a binding site or an ionic channel, a hidden active site embedded in a complex protein structure, a receptor for a neurotransmitter on the membrane of a neuron, and so on. The mean time to attach to a receptor or activator determines diffusion fluxes that are key regulators of cell function. This review describes physical models of various subcellular microdomains, in which the NET coarse-grains the molecular scale to a higher cellular-level, thus clarifying the role of cell geometry in determining subcellular function. (topical review)

Time scale of diffusion in molecular and cellular biology

Science.gov (United States)

Holcman, D.; Schuss, Z.

2014-05-01

Diffusion is the driver of critical biological processes in cellular and molecular biology. The diverse temporal scales of cellular function are determined by vastly diverse spatial scales in most biophysical processes. The latter are due, among others, to small binding sites inside or on the cell membrane or to narrow passages between large cellular compartments. The great disparity in scales is at the root of the difficulty in quantifying cell function from molecular dynamics and from simulations. The coarse-grained time scale of cellular function is determined from molecular diffusion by the mean first passage time of molecular Brownian motion to a small targets or through narrow passages. The narrow escape theory (NET) concerns this issue. The NET is ubiquitous in molecular and cellular biology and is manifested, among others, in chemical reactions, in the calculation of the effective diffusion coefficient of receptors diffusing on a neuronal cell membrane strewn with obstacles, in the quantification of the early steps of viral trafficking, in the regulation of diffusion between the mother and daughter cells during cell division, and many other cases. Brownian trajectories can represent the motion of a molecule, a protein, an ion in solution, a receptor in a cell or on its membrane, and many other biochemical processes. The small target can represent a binding site or an ionic channel, a hidden active site embedded in a complex protein structure, a receptor for a neurotransmitter on the membrane of a neuron, and so on. The mean time to attach to a receptor or activator determines diffusion fluxes that are key regulators of cell function. This review describes physical models of various subcellular microdomains, in which the NET coarse-grains the molecular scale to a higher cellular-level, thus clarifying the role of cell geometry in determining subcellular function.

Newton Methods for Large Scale Problems in Machine Learning

Science.gov (United States)

Hansen, Samantha Leigh

2014-01-01

The focus of this thesis is on practical ways of designing optimization algorithms for minimizing large-scale nonlinear functions with applications in machine learning. Chapter 1 introduces the overarching ideas in the thesis. Chapters 2 and 3 are geared towards supervised machine learning applications that involve minimizing a sum of loss…

Grid sensitivity capability for large scale structures

Science.gov (United States)

Nagendra, Gopal K.; Wallerstein, David V.

1989-01-01

The considerations and the resultant approach used to implement design sensitivity capability for grids into a large scale, general purpose finite element system (MSC/NASTRAN) are presented. The design variables are grid perturbations with a rather general linking capability. Moreover, shape and sizing variables may be linked together. The design is general enough to facilitate geometric modeling techniques for generating design variable linking schemes in an easy and straightforward manner. Test cases have been run and validated by comparison with the overall finite difference method. The linking of a design sensitivity capability for shape variables in MSC/NASTRAN with an optimizer would give designers a powerful, automated tool to carry out practical optimization design of real life, complicated structures.

Mathematical programming methods for large-scale topology optimization problems

DEFF Research Database (Denmark)

Rojas Labanda, Susana

for mechanical problems, but has rapidly extended to many other disciplines, such as fluid dynamics and biomechanical problems. However, the novelty and improvements of optimization methods has been very limited. It is, indeed, necessary to develop of new optimization methods to improve the final designs......, and at the same time, reduce the number of function evaluations. Nonlinear optimization methods, such as sequential quadratic programming and interior point solvers, have almost not been embraced by the topology optimization community. Thus, this work is focused on the introduction of this kind of second...... for the classical minimum compliance problem. Two of the state-of-the-art optimization algorithms are investigated and implemented for this structural topology optimization problem. A Sequential Quadratic Programming (TopSQP) and an interior point method (TopIP) are developed exploiting the specific mathematical...

Large Scale Molecular Simulation of Nanoparticle-Biomolecule Interactions and their Implications in Nanomedicine

Science.gov (United States)

Zhou, Ruhong

Nanoscale particles have become promising materials in various biomedical applications, however, in order to stimulate and facilitate these applications, there is an urgent need for a better understanding of their biological effects and related molecular mechanism/physics as well. In this talk, I will discuss some of our recent works, mostly molecular modelling, on nanotoxicity and their implications in de novo design of nanomedicine. We show that carbon-based nanoparticles (carbon nanotubes, graphene nanosheets, and fullerenes) can interact and disrupt the structures and functions of many important proteins. The hydrophobic interactions between the carbon nanotubes and hydrophobic residues, particularly aromatic residues through the so-called π- π stacking interactions, are found to play key roles. Meanwhile, metallofullerenol Gd@C82(OH)22 is found to inhibit tumour growth and metastases with both experimental and theoretical approaches. Graphene and graphene oxide (GO) nanosheets show strong destructive interactions to E. coli cell membranes (antibacterial activity) and A β amyloid fibrils (anti-AD, Alzheimer's disease, capability) with unique molecular mechanisms, while on the other hand, they also show a strong supportive role in enzyme immobilisation such as lipases through lid opening. In particular, the lid opening is assisted by lipase's sophisticated interaction with GO, which allows the adsorbed lipase to enhance its enzyme activity. The lipase enzymatic activity can be further optimized through fine tuning of the GO surface hydrophobicity. These findings might provide a better understanding of ``nanotoxicity'' at the molecular level with implications in de novo nanomedicine design.

Scale-up and optimization of biohydrogen production reactor from laboratory-scale to industrial-scale on the basis of computational fluid dynamics simulation

Energy Technology Data Exchange (ETDEWEB)

Wang, Xu; Ding, Jie; Guo, Wan-Qian; Ren, Nan-Qi [State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, 202 Haihe Road, Nangang District, Harbin, Heilongjiang 150090 (China)

2010-10-15

The objective of conducting experiments in a laboratory is to gain data that helps in designing and operating large-scale biological processes. However, the scale-up and design of industrial-scale biohydrogen production reactors is still uncertain. In this paper, an established and proven Eulerian-Eulerian computational fluid dynamics (CFD) model was employed to perform hydrodynamics assessments of an industrial-scale continuous stirred-tank reactor (CSTR) for biohydrogen production. The merits of the laboratory-scale CSTR and industrial-scale CSTR were compared and analyzed on the basis of CFD simulation. The outcomes demonstrated that there are many parameters that need to be optimized in the industrial-scale reactor, such as the velocity field and stagnation zone. According to the results of hydrodynamics evaluation, the structure of industrial-scale CSTR was optimized and the results are positive in terms of advancing the industrialization of biohydrogen production. (author)

Hybrid Metaheuristic Approach for Nonlocal Optimization of Molecular Systems.

Science.gov (United States)

Dresselhaus, Thomas; Yang, Jack; Kumbhar, Sadhana; Waller, Mark P

2013-04-09

Accurate modeling of molecular systems requires a good knowledge of the structure; therefore, conformation searching/optimization is a routine necessity in computational chemistry. Here we present a hybrid metaheuristic optimization (HMO) algorithm, which combines ant colony optimization (ACO) and particle swarm optimization (PSO) for the optimization of molecular systems. The HMO implementation meta-optimizes the parameters of the ACO algorithm on-the-fly by the coupled PSO algorithm. The ACO parameters were optimized on a set of small difluorinated polyenes where the parameters exhibited small variance as the size of the molecule increased. The HMO algorithm was validated by searching for the closed form of around 100 molecular balances. Compared to the gradient-based optimized molecular balance structures, the HMO algorithm was able to find low-energy conformations with a 87% success rate. Finally, the computational effort for generating low-energy conformation(s) for the phenylalanyl-glycyl-glycine tripeptide was approximately 60 CPU hours with the ACO algorithm, in comparison to 4 CPU years required for an exhaustive brute-force calculation.

Risk-based optimization of pipe inspections in large underground networks with imprecise information

International Nuclear Information System (INIS)

Mancuso, A.; Compare, M.; Salo, A.; Zio, E.; Laakso, T.

2016-01-01

In this paper, we present a novel risk-based methodology for optimizing the inspections of large underground infrastructure networks in the presence of incomplete information about the network features and parameters. The methodology employs Multi Attribute Value Theory to assess the risk of each pipe in the network, whereafter the optimal inspection campaign is built with Portfolio Decision Analysis (PDA). Specifically, Robust Portfolio Modeling (RPM) is employed to identify Pareto-optimal portfolios of pipe inspections. The proposed methodology is illustrated by reporting a real case study on the large-scale maintenance optimization of the sewerage network in Espoo, Finland. - Highlights: • Risk-based approach to optimize pipe inspections on large underground networks. • Reasonable computational effort to select efficient inspection portfolios. • Possibility to accommodate imprecise expert information. • Feasibility of the approach shown by Espoo water system case study.

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)

Oil Reservoir Production Optimization using Optimal Control

DEFF Research Database (Denmark)

Völcker, Carsten; Jørgensen, John Bagterp; Stenby, Erling Halfdan

2011-01-01

Practical oil reservoir management involves solution of large-scale constrained optimal control problems. In this paper we present a numerical method for solution of large-scale constrained optimal control problems. The method is a single-shooting method that computes the gradients using the adjo...... reservoir using water ooding and smart well technology. Compared to the uncontrolled case, the optimal operation increases the Net Present Value of the oil field by 10%.......Practical oil reservoir management involves solution of large-scale constrained optimal control problems. In this paper we present a numerical method for solution of large-scale constrained optimal control problems. The method is a single-shooting method that computes the gradients using...

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.

SUPERGIANT SHELLS AND MOLECULAR CLOUD FORMATION IN THE LARGE MAGELLANIC CLOUD

Energy Technology Data Exchange (ETDEWEB)

Dawson, J. R.; Dickey, John M. [School of Mathematics and Physics, University of Tasmania, Sandy Bay Campus, Churchill Avenue, Sandy Bay, TAS 7005 (Australia); McClure-Griffiths, N. M. [Australia Telescope National Facility, CSIRO Astronomy and Space Science, Marsfield NSW 2122 (Australia); Wong, T. [Astronomy Department, University of Illinois, Urbana, IL 61801 (United States); Hughes, A. [Max-Planck-Institut fuer Astronomie, Koenigstuhl 17, D-69117, Heidelberg (Germany); Fukui, Y. [Department of Physics and Astrophysics, Nagoya University, Chikusa-ku, Nagoya (Japan); Kawamura, A., E-mail: joanne.dawson@utas.edu.au [National Astronomical Observatory of Japan, Tokyo 181-8588 (Japan)

2013-01-20

We investigate the influence of large-scale stellar feedback on the formation of molecular clouds in the Large Magellanic Cloud (LMC). Examining the relationship between H I and {sup 12}CO(J = 1-0) in supergiant shells (SGSs), we find that the molecular fraction in the total volume occupied by SGSs is not enhanced with respect to the rest of the LMC disk. However, the majority of objects ({approx}70% by mass) are more molecular than their local surroundings, implying that the presence of a supergiant shell does on average have a positive effect on the molecular gas fraction. Averaged over the full SGS sample, our results suggest that {approx}12%-25% of the molecular mass in supergiant shell systems was formed as a direct result of the stellar feedback that created the shells. This corresponds to {approx}4%-11% of the total molecular mass of the galaxy. These figures are an approximate lower limit to the total contribution of stellar feedback to molecular cloud formation in the LMC, and constitute one of the first quantitative measurements of feedback-triggered molecular cloud formation in a galactic system.

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.;

Control Algorithms for Large-scale Single-axis Photovoltaic Trackers

Directory of Open Access Journals (Sweden)

Dorian Schneider

2012-01-01

Full Text Available The electrical yield of large-scale photovoltaic power plants can be greatly improved by employing solar trackers. While fixed-tilt superstructures are stationary and immobile, trackers move the PV-module plane in order to optimize its alignment to the sun. This paper introduces control algorithms for single-axis trackers (SAT, including a discussion for optimal alignment and backtracking. The results are used to simulate and compare the electrical yield of fixed-tilt and SAT systems. The proposed algorithms have been field tested, and are in operation in solar parks worldwide.

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)

Molecular cloud-scale star formation in NGC 300

Energy Technology Data Exchange (ETDEWEB)

Faesi, Christopher M.; Lada, Charles J.; Forbrich, Jan [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Menten, Karl M. [Max Planck Institut für Radioastronomie, Auf dem Hügel 69, D-53121 Bonn (Germany); Bouy, Hervé [Centro de Astrobiología, (INTA-CSIC), Departamento de Astrofísica, POB 78, ESAC Campus, 28691 Villanueva dela Cañada (Spain)

2014-07-01

We present the results of a galaxy-wide study of molecular gas and star formation in a sample of 76 H II regions in the nearby spiral galaxy NGC 300. We have measured the molecular gas at 250 pc scales using pointed CO(J = 2-1) observations with the Atacama Pathfinder Experiment telescope. We detect CO in 42 of our targets, deriving molecular gas masses ranging from our sensitivity limit of ∼10{sup 5} M {sub ☉} to 7 × 10{sup 5} M {sub ☉}. We find a clear decline in the CO detection rate with galactocentric distance, which we attribute primarily to the decreasing radial metallicity gradient in NGC 300. We combine Galaxy Evolution Explorer far-ultraviolet, Spitzer 24 μm, and Hα narrowband imaging to measure the star formation activity in our sample. We have developed a new direct modeling approach for computing star formation rates (SFRs) that utilizes these data and population synthesis models to derive the masses and ages of the young stellar clusters associated with each of our H II region targets. We find a characteristic gas depletion time of 230 Myr at 250 pc scales in NGC 300, more similar to the results obtained for Milky Way giant molecular clouds than the longer (>2 Gyr) global depletion times derived for entire galaxies and kiloparsec-sized regions within them. This difference is partially due to the fact that our study accounts for only the gas and stars within the youngest star-forming regions. We also note a large scatter in the NGC 300 SFR-molecular gas mass scaling relation that is furthermore consistent with the Milky Way cloud results. This scatter likely represents real differences in giant molecular cloud physical properties such as the dense gas fraction.

Distributed and hierarchical control techniques for large-scale power plant systems

International Nuclear Information System (INIS)

Raju, G.V.S.; Kisner, R.A.

1985-08-01

In large-scale systems, integrated and coordinated control functions are required to maximize plant availability, to allow maneuverability through various power levels, and to meet externally imposed regulatory limitations. Nuclear power plants are large-scale systems. Prime subsystems are those that contribute directly to the behavior of the plant's ultimate output. The prime subsystems in a nuclear power plant include reactor, primary and intermediate heat transport, steam generator, turbine generator, and feedwater system. This paper describes and discusses the continuous-variable control system developed to supervise prime plant subsystems for optimal control and coordination

A new asynchronous parallel algorithm for inferring large-scale gene regulatory networks.

Directory of Open Access Journals (Sweden)

Xiangyun Xiao

Full Text Available The reconstruction of gene regulatory networks (GRNs from high-throughput experimental data has been considered one of the most important issues in systems biology research. With the development of high-throughput technology and the complexity of biological problems, we need to reconstruct GRNs that contain thousands of genes. However, when many existing algorithms are used to handle these large-scale problems, they will encounter two important issues: low accuracy and high computational cost. To overcome these difficulties, the main goal of this study is to design an effective parallel algorithm to infer large-scale GRNs based on high-performance parallel computing environments. In this study, we proposed a novel asynchronous parallel framework to improve the accuracy and lower the time complexity of large-scale GRN inference by combining splitting technology and ordinary differential equation (ODE-based optimization. The presented algorithm uses the sparsity and modularity of GRNs to split whole large-scale GRNs into many small-scale modular subnetworks. Through the ODE-based optimization of all subnetworks in parallel and their asynchronous communications, we can easily obtain the parameters of the whole network. To test the performance of the proposed approach, we used well-known benchmark datasets from Dialogue for Reverse Engineering Assessments and Methods challenge (DREAM, experimentally determined GRN of Escherichia coli and one published dataset that contains more than 10 thousand genes to compare the proposed approach with several popular algorithms on the same high-performance computing environments in terms of both accuracy and time complexity. The numerical results demonstrate that our parallel algorithm exhibits obvious superiority in inferring large-scale GRNs.

A new asynchronous parallel algorithm for inferring large-scale gene regulatory networks.

Science.gov (United States)

Xiao, Xiangyun; Zhang, Wei; Zou, Xiufen

2015-01-01

The reconstruction of gene regulatory networks (GRNs) from high-throughput experimental data has been considered one of the most important issues in systems biology research. With the development of high-throughput technology and the complexity of biological problems, we need to reconstruct GRNs that contain thousands of genes. However, when many existing algorithms are used to handle these large-scale problems, they will encounter two important issues: low accuracy and high computational cost. To overcome these difficulties, the main goal of this study is to design an effective parallel algorithm to infer large-scale GRNs based on high-performance parallel computing environments. In this study, we proposed a novel asynchronous parallel framework to improve the accuracy and lower the time complexity of large-scale GRN inference by combining splitting technology and ordinary differential equation (ODE)-based optimization. The presented algorithm uses the sparsity and modularity of GRNs to split whole large-scale GRNs into many small-scale modular subnetworks. Through the ODE-based optimization of all subnetworks in parallel and their asynchronous communications, we can easily obtain the parameters of the whole network. To test the performance of the proposed approach, we used well-known benchmark datasets from Dialogue for Reverse Engineering Assessments and Methods challenge (DREAM), experimentally determined GRN of Escherichia coli and one published dataset that contains more than 10 thousand genes to compare the proposed approach with several popular algorithms on the same high-performance computing environments in terms of both accuracy and time complexity. The numerical results demonstrate that our parallel algorithm exhibits obvious superiority in inferring large-scale GRNs.

Optimization of large-scale fabrication of dielectric elastomer transducers

DEFF Research Database (Denmark)

Hassouneh, Suzan Sager

Dielectric elastomers (DEs) have gained substantial ground in many different applications, such as wave energy harvesting, valves and loudspeakers. For DE technology to be commercially viable, it is necessary that any large-scale production operation is nondestructive, efficient and cheap. Danfoss......-strength laminates to perform as monolithic elements. For the front-to-back and front-to-front configurations, conductive elastomers were utilised. One approach involved adding the cheap and conductive filler, exfoliated graphite (EG) to a PDMS matrix to increase dielectric permittivity. The results showed that even...... as conductive adhesives were rejected. Dielectric properties below the percolation threshold were subsequently investigated, in order to conclude the study. In order to avoid destroying the network structure, carbon nanotubes (CNTs) were used as fillers during the preparation of the conductive elastomers...

[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.

Molecular computational elements encode large populations of small objects

Science.gov (United States)

Prasanna de Silva, A.; James, Mark R.; McKinney, Bernadine O. F.; Pears, David A.; Weir, Sheenagh M.

2006-10-01

Since the introduction of molecular computation, experimental molecular computational elements have grown to encompass small-scale integration, arithmetic and games, among others. However, the need for a practical application has been pressing. Here we present molecular computational identification (MCID), a demonstration that molecular logic and computation can be applied to a widely relevant issue. Examples of populations that need encoding in the microscopic world are cells in diagnostics or beads in combinatorial chemistry (tags). Taking advantage of the small size (about 1nm) and large `on/off' output ratios of molecular logic gates and using the great variety of logic types, input chemical combinations, switching thresholds and even gate arrays in addition to colours, we produce unique identifiers for members of populations of small polymer beads (about 100μm) used for synthesis of combinatorial libraries. Many millions of distinguishable tags become available. This method should be extensible to far smaller objects, with the only requirement being a `wash and watch' protocol. Our focus on converting molecular science into technology concerning analog sensors, turns to digital logic devices in the present work.

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

Science.gov (United States)

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

2018-01-24

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

First principles molecular dynamics without self-consistent field optimization

International Nuclear Information System (INIS)

Souvatzis, Petros; Niklasson, Anders M. N.

2014-01-01

We present a first principles molecular dynamics approach that is based on time-reversible extended Lagrangian Born-Oppenheimer molecular dynamics [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] in the limit of vanishing self-consistent field optimization. The optimization-free dynamics keeps the computational cost to a minimum and typically provides molecular trajectories that closely follow the exact Born-Oppenheimer potential energy surface. Only one single diagonalization and Hamiltonian (or Fockian) construction are required in each integration time step. The proposed dynamics is derived for a general free-energy potential surface valid at finite electronic temperatures within hybrid density functional theory. Even in the event of irregular functional behavior that may cause a dynamical instability, the optimization-free limit represents a natural starting guess for force calculations that may require a more elaborate iterative electronic ground state optimization. Our optimization-free dynamics thus represents a flexible theoretical framework for a broad and general class of ab initio molecular dynamics simulations

Large-scale Intelligent Transporation Systems simulation

Energy Technology Data Exchange (ETDEWEB)

Ewing, T.; Canfield, T.; Hannebutte, U.; Levine, D.; Tentner, A.

1995-06-01

A prototype computer system has been developed which defines a high-level architecture for a large-scale, comprehensive, scalable simulation of an Intelligent Transportation System (ITS) capable of running on massively parallel computers and distributed (networked) computer systems. The prototype includes the modelling of instrumented ``smart`` vehicles with in-vehicle navigation units capable of optimal route planning and Traffic Management Centers (TMC). The TMC has probe vehicle tracking capabilities (display position and attributes of instrumented vehicles), and can provide 2-way interaction with traffic to provide advisories and link times. Both the in-vehicle navigation module and the TMC feature detailed graphical user interfaces to support human-factors studies. The prototype has been developed on a distributed system of networked UNIX computers but is designed to run on ANL`s IBM SP-X parallel computer system for large scale problems. A novel feature of our design is that vehicles will be represented by autonomus computer processes, each with a behavior model which performs independent route selection and reacts to external traffic events much like real vehicles. With this approach, one will be able to take advantage of emerging massively parallel processor (MPP) systems.

A visual analytics system for optimizing the performance of large-scale networks in supercomputing systems

Directory of Open Access Journals (Sweden)

Takanori Fujiwara

2018-03-01

Full Text Available The overall efficiency of an extreme-scale supercomputer largely relies on the performance of its network interconnects. Several of the state of the art supercomputers use networks based on the increasingly popular Dragonfly topology. It is crucial to study the behavior and performance of different parallel applications running on Dragonfly networks in order to make optimal system configurations and design choices, such as job scheduling and routing strategies. However, in order to study these temporal network behavior, we would need a tool to analyze and correlate numerous sets of multivariate time-series data collected from the Dragonfly’s multi-level hierarchies. This paper presents such a tool–a visual analytics system–that uses the Dragonfly network to investigate the temporal behavior and optimize the communication performance of a supercomputer. We coupled interactive visualization with time-series analysis methods to help reveal hidden patterns in the network behavior with respect to different parallel applications and system configurations. Our system also provides multiple coordinated views for connecting behaviors observed at different levels of the network hierarchies, which effectively helps visual analysis tasks. We demonstrate the effectiveness of the system with a set of case studies. Our system and findings can not only help improve the communication performance of supercomputing applications, but also the network performance of next-generation supercomputers. Keywords: Supercomputing, Parallel communication network, Dragonfly networks, Time-series data, Performance analysis, Visual analytics

Structure–performance characterization for carbon molecular sieve membranes using molecular scale gas probes

KAUST Repository

Rungta, Meha

2015-04-01

© 2015 Elsevier Ltd. All rights reserved. Understanding the relationship between carbon molecular sieve (CMS) pore structure and corresponding gas separation performance enables optimization for a given gas separation application. The final pyrolysis temperature and starting polymer precursor are the two critical parameters in controlling CMS performance. This study considers structure and performance changes of CMS derived from a commercially available polymer precursor at different pyrolysis temperatures. As reviewed in this paper, most traditional characterization methods based on microscopy, X-ray diffraction, spectroscopy, sorption-based pore size distribution measurements etc. provide limited information for relating separation performance to the CMS morphology and structural changes. A useful alternative approach based on different sized gases as molecular scale probes of the CMS pore structure was successfully used here in conjunction with separation data to provide critical insights into the structure-performance relationships of the engineered CMS.

Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments

Directory of Open Access Journals (Sweden)

Renata De Paris

2015-01-01

Full Text Available Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand.

Assessment of economically optimal water management and geospatial potential for large-scale water storage

Science.gov (United States)

Weerasinghe, Harshi; Schneider, Uwe A.

2010-05-01

Assessment of economically optimal water management and geospatial potential for large-scale water storage Weerasinghe, Harshi; Schneider, Uwe A Water is an essential but limited and vulnerable resource for all socio-economic development and for maintaining healthy ecosystems. Water scarcity accelerated due to population expansion, improved living standards, and rapid growth in economic activities, has profound environmental and social implications. These include severe environmental degradation, declining groundwater levels, and increasing problems of water conflicts. Water scarcity is predicted to be one of the key factors limiting development in the 21st century. Climate scientists have projected spatial and temporal changes in precipitation and changes in the probability of intense floods and droughts in the future. As scarcity of accessible and usable water increases, demand for efficient water management and adaptation strategies increases as well. Addressing water scarcity requires an intersectoral and multidisciplinary approach in managing water resources. This would in return safeguard the social welfare and the economical benefit to be at their optimal balance without compromising the sustainability of ecosystems. This paper presents a geographically explicit method to assess the potential for water storage with reservoirs and a dynamic model that identifies the dimensions and material requirements under an economically optimal water management plan. The methodology is applied to the Elbe and Nile river basins. Input data for geospatial analysis at watershed level are taken from global data repositories and include data on elevation, rainfall, soil texture, soil depth, drainage, land use and land cover; which are then downscaled to 1km spatial resolution. Runoff potential for different combinations of land use and hydraulic soil groups and for mean annual precipitation levels are derived by the SCS-CN method. Using the overlay and decision tree algorithms

Stability of large-area molecular junctions

NARCIS (Netherlands)

Akkerman, Hylke B.; Kronemeijer, Auke J.; Harkema, Jan; van Hal, Paul A.; Smits, Edsger C. P.; de Leeuw, Dago M.; Blom, Paul W. M.

The stability of molecular junctions is crucial for any application of molecular electronics. Degradation of molecular junctions when exposed to ambient conditions is regularly observed. In this report the stability of large-area molecular junctions under ambient conditions for more than two years

Scaling Optimization of the SIESTA MHD Code

Science.gov (United States)

Seal, Sudip; Hirshman, Steven; Perumalla, Kalyan

2013-10-01

SIESTA is a parallel three-dimensional plasma equilibrium code capable of resolving magnetic islands at high spatial resolutions for toroidal plasmas. Originally designed to exploit small-scale parallelism, SIESTA has now been scaled to execute efficiently over several thousands of processors P. This scaling improvement was accomplished with minimal intrusion to the execution flow of the original version. First, the efficiency of the iterative solutions was improved by integrating the parallel tridiagonal block solver code BCYCLIC. Krylov-space generation in GMRES was then accelerated using a customized parallel matrix-vector multiplication algorithm. Novel parallel Hessian generation algorithms were integrated and memory access latencies were dramatically reduced through loop nest optimizations and data layout rearrangement. These optimizations sped up equilibria calculations by factors of 30-50. It is possible to compute solutions with granularity N/P near unity on extremely fine radial meshes (N > 1024 points). Grid separation in SIESTA, which manifests itself primarily in the resonant components of the pressure far from rational surfaces, is strongly suppressed by finer meshes. Large problem sizes of up to 300 K simultaneous non-linear coupled equations have been solved on the NERSC supercomputers. Work supported by U.S. DOE under Contract DE-AC05-00OR22725 with UT-Battelle, LLC.

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.

Optimization of large scale food production using Lean Manufacturing principles

DEFF Research Database (Denmark)

Engelund, Eva Høy; Friis, Alan; Breum, Gitte

2009-01-01

This paper discusses how the production principles of Lean Manufacturing (Lean) can be applied in a large-scale meal production. Lean principles are briefly presented, followed by a field study of how a kitchen at a Danish hospital has implemented Lean in the daily production. In the kitchen...... not be negatively affected by the rationalisation of production procedures. The field study shows that Lean principles can be applied in meal production and can result in increased production efficiency and systematic improvement of product quality without negative effects on the working environment. The results...... show that Lean can be applied and used to manage the production of meals in the kitchen....

Parallelizing Gene Expression Programming Algorithm in Enabling Large-Scale Classification

Directory of Open Access Journals (Sweden)

Lixiong Xu

2017-01-01

Full Text Available As one of the most effective function mining algorithms, Gene Expression Programming (GEP algorithm has been widely used in classification, pattern recognition, prediction, and other research fields. Based on the self-evolution, GEP is able to mine an optimal function for dealing with further complicated tasks. However, in big data researches, GEP encounters low efficiency issue due to its long time mining processes. To improve the efficiency of GEP in big data researches especially for processing large-scale classification tasks, this paper presents a parallelized GEP algorithm using MapReduce computing model. The experimental results show that the presented algorithm is scalable and efficient for processing large-scale classification tasks.

Iodine oxides in large-scale THAI tests

International Nuclear Information System (INIS)

Funke, F.; Langrock, G.; Kanzleiter, T.; Poss, G.; Fischer, K.; Kühnel, A.; Weber, G.; Allelein, H.-J.

2012-01-01

Highlights: ► Iodine oxide particles were produced from gaseous iodine and ozone. ► Ozone replaced the effect of ionizing radiation in the large-scale THAI facility. ► The mean diameter of the iodine oxide particles was about 0.35 μm. ► Particle formation was faster than the chemical reaction between iodine and ozone. ► Deposition of iodine oxide particles was slow in the absence of other aerosols. - Abstract: The conversion of gaseous molecular iodine into iodine oxide aerosols has significant relevance in the understanding of the fission product iodine volatility in a LWR containment during severe accidents. In containment, the high radiation field caused by fission products released from the reactor core induces radiolytic oxidation into iodine oxides. To study the characteristics and the behaviour of iodine oxides in large scale, two THAI tests Iod-13 and Iod-14 were performed, simulating radiolytic oxidation of molecular iodine by reaction of iodine with ozone, with ozone injected from an ozone generator. The observed iodine oxides form submicron particles with mean volume-related diameters of about 0.35 μm and show low deposition rates in the THAI tests performed in the absence of other nuclear aerosols. Formation of iodine aerosols from gaseous precursors iodine and ozone is fast as compared to their chemical interaction. The current approach in empirical iodine containment behaviour models in severe accidents, including the radiolytic production of I 2 -oxidizing agents followed by the I 2 oxidation itself, is confirmed by these THAI tests.

Analysis of the electricity demand of Greece for optimal planning of a large-scale hybrid renewable energy system

Science.gov (United States)

Tyralis, Hristos; Karakatsanis, Georgios; Tzouka, Katerina; Mamassis, Nikos

2015-04-01

The Greek electricity system is examined for the period 2002-2014. The demand load data are analysed at various time scales (hourly, daily, seasonal and annual) and they are related to the mean daily temperature and the gross domestic product (GDP) of Greece for the same time period. The prediction of energy demand, a product of the Greek Independent Power Transmission Operator, is also compared with the demand load. Interesting results about the change of the electricity demand scheme after the year 2010 are derived. This change is related to the decrease of the GDP, during the period 2010-2014. The results of the analysis will be used in the development of an energy forecasting system which will be a part of a framework for optimal planning of a large-scale hybrid renewable energy system in which hydropower plays the dominant role. Acknowledgement: This research was funded by the Greek General Secretariat for Research and Technology through the research project Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO; grant number 5145)

Optimizing Implementation of Obesity Prevention Programs: A Qualitative Investigation Within a Large-Scale Randomized Controlled Trial.

Science.gov (United States)

Kozica, Samantha L; Teede, Helena J; Harrison, Cheryce L; Klein, Ruth; Lombard, Catherine B

2016-01-01

The prevalence of obesity in rural and remote areas is elevated in comparison to urban populations, highlighting the need for interventions targeting obesity prevention in these settings. Implementing evidence-based obesity prevention programs is challenging. This study aimed to investigate factors influencing the implementation of obesity prevention programs, including adoption, program delivery, community uptake, and continuation, specifically within rural settings. Nested within a large-scale randomized controlled trial, a qualitative exploratory approach was adopted, with purposive sampling techniques utilized, to recruit stakeholders from 41 small rural towns in Australia. In-depth semistructured interviews were conducted with clinical health professionals, health service managers, and local government employees. Open coding was completed independently by 2 investigators and thematic analysis undertaken. In-depth interviews revealed that obesity prevention programs were valued by the rural workforce. Program implementation is influenced by interrelated factors across: (1) contextual factors and (2) organizational capacity. Key recommendations to manage the challenges of implementing evidence-based programs focused on reducing program delivery costs, aided by the provision of a suite of implementation and evaluation resources. Informing the scale-up of future prevention programs, stakeholders highlighted the need to build local rural capacity through developing supportive university partnerships, generating local program ownership and promoting active feedback to all program partners. We demonstrate that the rural workforce places a high value on obesity prevention programs. Our results inform the future scale-up of obesity prevention programs, providing an improved understanding of strategies to optimize implementation of evidence-based prevention programs. © 2015 National Rural Health Association.

Large-Scale Multiantenna Multisine Wireless Power Transfer

Science.gov (United States)

Huang, Yang; Clerckx, Bruno

2017-11-01

Wireless Power Transfer (WPT) is expected to be a technology reshaping the landscape of low-power applications such as the Internet of Things, Radio Frequency identification (RFID) networks, etc. Although there has been some progress towards multi-antenna multi-sine WPT design, the large-scale design of WPT, reminiscent of massive MIMO in communications, remains an open challenge. In this paper, we derive efficient multiuser algorithms based on a generalizable optimization framework, in order to design transmit sinewaves that maximize the weighted-sum/minimum rectenna output DC voltage. The study highlights the significant effect of the nonlinearity introduced by the rectification process on the design of waveforms in multiuser systems. Interestingly, in the single-user case, the optimal spatial domain beamforming, obtained prior to the frequency domain power allocation optimization, turns out to be Maximum Ratio Transmission (MRT). In contrast, in the general weighted sum criterion maximization problem, the spatial domain beamforming optimization and the frequency domain power allocation optimization are coupled. Assuming channel hardening, low-complexity algorithms are proposed based on asymptotic analysis, to maximize the two criteria. The structure of the asymptotically optimal spatial domain precoder can be found prior to the optimization. The performance of the proposed algorithms is evaluated. Numerical results confirm the inefficiency of the linear model-based design for the single and multi-user scenarios. It is also shown that as nonlinear model-based designs, the proposed algorithms can benefit from an increasing number of sinewaves.

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

Large deviations and portfolio optimization

Science.gov (United States)

Sornette, Didier

Risk control and optimal diversification constitute a major focus in the finance and insurance industries as well as, more or less consciously, in our everyday life. We present a discussion of the characterization of risks and of the optimization of portfolios that starts from a simple illustrative model and ends by a general functional integral formulation. A major item is that risk, usually thought of as one-dimensional in the conventional mean-variance approach, has to be addressed by the full distribution of losses. Furthermore, the time-horizon of the investment is shown to play a major role. We show the importance of accounting for large fluctuations and use the theory of Cramér for large deviations in this context. We first treat a simple model with a single risky asset that exemplifies the distinction between the average return and the typical return and the role of large deviations in multiplicative processes, and the different optimal strategies for the investors depending on their size. We then analyze the case of assets whose price variations are distributed according to exponential laws, a situation that is found to describe daily price variations reasonably well. Several portfolio optimization strategies are presented that aim at controlling large risks. We end by extending the standard mean-variance portfolio optimization theory, first within the quasi-Gaussian approximation and then using a general formulation for non-Gaussian correlated assets in terms of the formalism of functional integrals developed in the field theory of critical phenomena.

Integral criteria for large-scale multiple fingerprint solutions

Science.gov (United States)

Ushmaev, Oleg S.; Novikov, Sergey O.

2004-08-01

We propose the definition and analysis of the optimal integral similarity score criterion for large scale multmodal civil ID systems. Firstly, the general properties of score distributions for genuine and impostor matches for different systems and input devices are investigated. The empirical statistics was taken from the real biometric tests. Then we carry out the analysis of simultaneous score distributions for a number of combined biometric tests and primary for ultiple fingerprint solutions. The explicit and approximate relations for optimal integral score, which provides the least value of the FRR while the FAR is predefined, have been obtained. The results of real multiple fingerprint test show good correspondence with the theoretical results in the wide range of the False Acceptance and the False Rejection Rates.

Optimal Scale Edge Detection Utilizing Noise within Images

Directory of Open Access Journals (Sweden)

Adnan Khashman

2003-04-01

Full Text Available Edge detection techniques have common problems that include poor edge detection in low contrast images, speed of recognition and high computational cost. An efficient solution to the edge detection of objects in low to high contrast images is scale space analysis. However, this approach is time consuming and computationally expensive. These expenses can be marginally reduced if an optimal scale is found in scale space edge detection. This paper presents a new approach to detecting objects within images using noise within the images. The novel idea is based on selecting one optimal scale for the entire image at which scale space edge detection can be applied. The selection of an ideal scale is based on the hypothesis that "the optimal edge detection scale (ideal scale depends on the noise within an image". This paper aims at providing the experimental evidence on the relationship between the optimal scale and the noise within images.

A method of orbital analysis for large-scale first-principles simulations

Energy Technology Data Exchange (ETDEWEB)

Ohwaki, Tsukuru [Advanced Materials Laboratory, Nissan Research Center, Nissan Motor Co., Ltd., 1 Natsushima-cho, Yokosuka, Kanagawa 237-8523 (Japan); Otani, Minoru [Nanosystem Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki 305-8568 (Japan); Ozaki, Taisuke [Research Center for Simulation Science (RCSS), Japan Advanced Institute of Science and Technology (JAIST), 1-1 Asahidai, Nomi, Ishikawa 923-1292 (Japan)

2014-06-28

An efficient method of calculating the natural bond orbitals (NBOs) based on a truncation of the entire density matrix of a whole system is presented for large-scale density functional theory calculations. The method recovers an orbital picture for O(N) electronic structure methods which directly evaluate the density matrix without using Kohn-Sham orbitals, thus enabling quantitative analysis of chemical reactions in large-scale systems in the language of localized Lewis-type chemical bonds. With the density matrix calculated by either an exact diagonalization or O(N) method, the computational cost is O(1) for the calculation of NBOs associated with a local region where a chemical reaction takes place. As an illustration of the method, we demonstrate how an electronic structure in a local region of interest can be analyzed by NBOs in a large-scale first-principles molecular dynamics simulation for a liquid electrolyte bulk model (propylene carbonate + LiBF{sub 4})

A method of orbital analysis for large-scale first-principles simulations

International Nuclear Information System (INIS)

Ohwaki, Tsukuru; Otani, Minoru; Ozaki, Taisuke

2014-01-01

An efficient method of calculating the natural bond orbitals (NBOs) based on a truncation of the entire density matrix of a whole system is presented for large-scale density functional theory calculations. The method recovers an orbital picture for O(N) electronic structure methods which directly evaluate the density matrix without using Kohn-Sham orbitals, thus enabling quantitative analysis of chemical reactions in large-scale systems in the language of localized Lewis-type chemical bonds. With the density matrix calculated by either an exact diagonalization or O(N) method, the computational cost is O(1) for the calculation of NBOs associated with a local region where a chemical reaction takes place. As an illustration of the method, we demonstrate how an electronic structure in a local region of interest can be analyzed by NBOs in a large-scale first-principles molecular dynamics simulation for a liquid electrolyte bulk model (propylene carbonate + LiBF 4 )

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

Science.gov (United States)

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

2017-11-01

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

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

A Matter of Time: Faster Percolator Analysis via Efficient SVM Learning for Large-Scale Proteomics.

Science.gov (United States)

Halloran, John T; Rocke, David M

2018-05-04

Percolator is an important tool for greatly improving the results of a database search and subsequent downstream analysis. Using support vector machines (SVMs), Percolator recalibrates peptide-spectrum matches based on the learned decision boundary between targets and decoys. To improve analysis time for large-scale data sets, we update Percolator's SVM learning engine through software and algorithmic optimizations rather than heuristic approaches that necessitate the careful study of their impact on learned parameters across different search settings and data sets. We show that by optimizing Percolator's original learning algorithm, l 2 -SVM-MFN, large-scale SVM learning requires nearly only a third of the original runtime. Furthermore, we show that by employing the widely used Trust Region Newton (TRON) algorithm instead of l 2 -SVM-MFN, large-scale Percolator SVM learning is reduced to nearly only a fifth of the original runtime. Importantly, these speedups only affect the speed at which Percolator converges to a global solution and do not alter recalibration performance. The upgraded versions of both l 2 -SVM-MFN and TRON are optimized within the Percolator codebase for multithreaded and single-thread use and are available under Apache license at bitbucket.org/jthalloran/percolator_upgrade .

Enhanced nonlinearity interval mapping scheme for high-performance simulation-optimization of watershed-scale BMP placement

Science.gov (United States)

Zou, Rui; Riverson, John; Liu, Yong; Murphy, Ryan; Sim, Youn

2015-03-01

Integrated continuous simulation-optimization models can be effective predictors of a process-based responses for cost-benefit optimization of best management practices (BMPs) selection and placement. However, practical application of simulation-optimization model is computationally prohibitive for large-scale systems. This study proposes an enhanced Nonlinearity Interval Mapping Scheme (NIMS) to solve large-scale watershed simulation-optimization problems several orders of magnitude faster than other commonly used algorithms. An efficient interval response coefficient (IRC) derivation method was incorporated into the NIMS framework to overcome a computational bottleneck. The proposed algorithm was evaluated using a case study watershed in the Los Angeles County Flood Control District. Using a continuous simulation watershed/stream-transport model, Loading Simulation Program in C++ (LSPC), three nested in-stream compliance points (CP)—each with multiple Total Maximum Daily Loads (TMDL) targets—were selected to derive optimal treatment levels for each of the 28 subwatersheds, so that the TMDL targets at all the CP were met with the lowest possible BMP implementation cost. Genetic Algorithm (GA) and NIMS were both applied and compared. The results showed that the NIMS took 11 iterations (about 11 min) to complete with the resulting optimal solution having a total cost of 67.2 million, while each of the multiple GA executions took 21-38 days to reach near optimal solutions. The best solution obtained among all the GA executions compared had a minimized cost of 67.7 million—marginally higher, but approximately equal to that of the NIMS solution. The results highlight the utility for decision making in large-scale watershed simulation-optimization formulations.

Cytology of DNA Replication Reveals Dynamic Plasticity of Large-Scale Chromatin Fibers.

Science.gov (United States)

Deng, Xiang; Zhironkina, Oxana A; Cherepanynets, Varvara D; Strelkova, Olga S; Kireev, Igor I; Belmont, Andrew S

2016-09-26

In higher eukaryotic interphase nuclei, the 100- to >1,000-fold linear compaction of chromatin is difficult to reconcile with its function as a template for transcription, replication, and repair. It is challenging to imagine how DNA and RNA polymerases with their associated molecular machinery would move along the DNA template without transient decondensation of observed large-scale chromatin "chromonema" fibers [1]. Transcription or "replication factory" models [2], in which polymerases remain fixed while DNA is reeled through, are similarly difficult to conceptualize without transient decondensation of these chromonema fibers. Here, we show how a dynamic plasticity of chromatin folding within large-scale chromatin fibers allows DNA replication to take place without significant changes in the global large-scale chromatin compaction or shape of these large-scale chromatin fibers. Time-lapse imaging of lac-operator-tagged chromosome regions shows no major change in the overall compaction of these chromosome regions during their DNA replication. Improved pulse-chase labeling of endogenous interphase chromosomes yields a model in which the global compaction and shape of large-Mbp chromatin domains remains largely invariant during DNA replication, with DNA within these domains undergoing significant movements and redistribution as they move into and then out of adjacent replication foci. In contrast to hierarchical folding models, this dynamic plasticity of large-scale chromatin organization explains how localized changes in DNA topology allow DNA replication to take place without an accompanying global unfolding of large-scale chromatin fibers while suggesting a possible mechanism for maintaining epigenetic programming of large-scale chromatin domains throughout DNA replication. Copyright © 2016 Elsevier Ltd. All rights reserved.

Crystallisation of a Lennard-Jones fluid by large scale molecular dynamics simulation

International Nuclear Information System (INIS)

Snook, I.

1998-01-01

Full text: The evolution of the structure of a large system of atoms interacting via a Lennard-Jones pair potential was simulated by the use of the Molecular Dynamics computer simulation technique. The system was initially equilibrated in the one phase region of the phase diagram at a temperature above critical then a temperature quench was performed which placed the system in a region were the single fluid phase was unstable. Quenches to below the triple point temperature gave rise to crystallisation The mechanism and final morphology is shown to depend strongly on the starting conditions e.g. the starting density

Mesoderm Lineage 3D Tissue Constructs Are Produced at Large-Scale in a 3D Stem Cell Bioprocess.

Science.gov (United States)

Cha, Jae Min; Mantalaris, Athanasios; Jung, Sunyoung; Ji, Yurim; Bang, Oh Young; Bae, Hojae

2017-09-01

Various studies have presented different approaches to direct pluripotent stem cell differentiation such as applying defined sets of exogenous biochemical signals and genetic/epigenetic modifications. Although differentiation to target lineages can be successfully regulated, such conventional methods are often complicated, laborious, and not cost-effective to be employed to the large-scale production of 3D stem cell-based tissue constructs. A 3D-culture platform that could realize the large-scale production of mesoderm lineage tissue constructs from embryonic stem cells (ESCs) is developed. ESCs are cultured using our previously established 3D-bioprocess platform which is amenable to mass-production of 3D ESC-based tissue constructs. Hepatocarcinoma cell line conditioned medium is introduced to the large-scale 3D culture to provide a specific biomolecular microenvironment to mimic in vivo mesoderm formation process. After 5 days of spontaneous differentiation period, the resulting 3D tissue constructs are composed of multipotent mesodermal progenitor cells verified by gene and molecular expression profiles. Subsequently the optimal time points to trigger terminal differentiation towards cardiomyogenesis or osteogenesis from the mesodermal tissue constructs is found. A simple and affordable 3D ESC-bioprocess that can reach the scalable production of mesoderm origin tissues with significantly improved correspondent tissue properties is demonstrated. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Non-smooth optimization methods for large-scale problems: applications to mid-term power generation planning

International Nuclear Information System (INIS)

Emiel, G.

2008-01-01

This manuscript deals with large-scale non-smooth optimization that may typically arise when performing Lagrangian relaxation of difficult problems. This technique is commonly used to tackle mixed-integer linear programming - or large-scale convex problems. For example, a classical approach when dealing with power generation planning problems in a stochastic environment is to perform a Lagrangian relaxation of the coupling constraints of demand. In this approach, a master problem coordinates local subproblems, specific to each generation unit. The master problem deals with a separable non-smooth dual function which can be maximized with, for example, bundle algorithms. In chapter 2, we introduce basic tools of non-smooth analysis and some recent results regarding incremental or inexact instances of non-smooth algorithms. However, in some situations, the dual problem may still be very hard to solve. For instance, when the number of dualized constraints is very large (exponential in the dimension of the primal problem), explicit dualization may no longer be possible or the update of dual variables may fail. In order to reduce the dual dimension, different heuristics were proposed. They involve a separation procedure to dynamically select a restricted set of constraints to be dualized along the iterations. This relax-and-cut type approach has shown its numerical efficiency in many combinatorial problems. In chapter 3, we show Primal-dual convergence of such strategy when using an adapted sub-gradient method for the dual step and under minimal assumptions on the separation procedure. Another limit of Lagrangian relaxation may appear when the dual function is separable in highly numerous or complex sub-functions. In such situation, the computational burden of solving all local subproblems may be preponderant in the whole iterative process. A natural strategy would be here to take full advantage of the dual separable structure, performing a dual iteration after having

A Pilot-Scale System for Carbon Molecular Sieve Hollow Fiber Membrane Manufacturing

KAUST Repository

Karvan, O.

2012-12-21

Carbon molecular sieve (CMS) membranes offer advantages over traditional polymeric membrane materials, but scale-up of manufacturing systems has not received much attention. In the recent decade, there has been a dramatic increase in fundamental research on these materials with a variety of applications being studied. The results from a pilot-scale CMS production system are presented. This system was designed based on extensive laboratory research, and hollow fiber membranes produced in this system show similar performance compared to membranes produced using a smaller bench-scale system. After optimizing the system design, a 93% recovery of the precursor fibers for use in membrane module preparation were obtained. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimization of the plasma parameters for the high current and uniform large-scale pulse arc ion source of the VEST-NBI system

International Nuclear Information System (INIS)

Jung, Bongki; Park, Min; Heo, Sung Ryul; Kim, Tae-Seong; Jeong, Seung Ho; Chang, Doo-Hee; Lee, Kwang Won; In, Sang-Ryul

2016-01-01

Highlights: • High power magnetic bucket-type arc plasma source for the VEST NBI system is developed with modifications based on the prototype plasma source for KSTAR. • Plasma parameters in pulse duration are measured to characterize the plasma source. • High plasma density and good uniformity is achieved at the low operating pressure below 1 Pa. • Required ion beam current density is confirmed by analysis of plasma parameters and results of a particle balance model. - Abstract: A large-scale hydrogen arc plasma source was developed at the Korea Atomic Energy Research Institute for a high power pulsed NBI system of VEST which is a compact spherical tokamak at Seoul national university. One of the research target of VEST is to study innovative tokamak operating scenarios. For this purpose, high current density and uniform large-scale pulse plasma source is required to satisfy the target ion beam power efficiently. Therefore, optimizing the plasma parameters of the ion source such as the electron density, temperature, and plasma uniformity is conducted by changing the operating conditions of the plasma source. Furthermore, ion species of the hydrogen plasma source are analyzed using a particle balance model to increase the monatomic fraction which is another essential parameter for increasing the ion beam current density. Conclusively, efficient operating conditions are presented from the results of the optimized plasma parameters and the extractable ion beam current is calculated.

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.

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...

Large scale aggregate microarray analysis reveals three distinct molecular subclasses of human preeclampsia.

Science.gov (United States)

Leavey, Katherine; Bainbridge, Shannon A; Cox, Brian J

2015-01-01

Preeclampsia (PE) is a life-threatening hypertensive pathology of pregnancy affecting 3-5% of all pregnancies. To date, PE has no cure, early detection markers, or effective treatments short of the removal of what is thought to be the causative organ, the placenta, which may necessitate a preterm delivery. Additionally, numerous small placental microarray studies attempting to identify "PE-specific" genes have yielded inconsistent results. We therefore hypothesize that preeclampsia is a multifactorial disease encompassing several pathology subclasses, and that large cohort placental gene expression analysis will reveal these groups. To address our hypothesis, we utilized known bioinformatic methods to aggregate 7 microarray data sets across multiple platforms in order to generate a large data set of 173 patient samples, including 77 with preeclampsia. Unsupervised clustering of these patient samples revealed three distinct molecular subclasses of PE. This included a "canonical" PE subclass demonstrating elevated expression of known PE markers and genes associated with poor oxygenation and increased secretion, as well as two other subclasses potentially representing a poor maternal response to pregnancy and an immunological presentation of preeclampsia. Our analysis sheds new light on the heterogeneity of PE patients, and offers up additional avenues for future investigation. Hopefully, our subclassification of preeclampsia based on molecular diversity will finally lead to the development of robust diagnostics and patient-based treatments for this disorder.

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

Science.gov (United States)

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

2018-02-01

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

Experiment-scale molecular simulation study of liquid crystal thin films

Science.gov (United States)

Nguyen, Trung Dac; Carrillo, Jan-Michael Y.; Matheson, Michael A.; Brown, W. Michael

2014-03-01

Supercomputers have now reached a performance level adequate for studying thin films with molecular detail at the relevant scales. By exploiting the power of GPU accelerators on Titan, we have been able to perform simulations of characteristic liquid crystal films that provide remarkable qualitative agreement with experimental images. We have demonstrated that key features of spinodal instability can only be observed with sufficiently large system sizes, which were not accessible with previous simulation studies. Our study emphasizes the capability and significance of petascale simulations in providing molecular-level insights in thin film systems as well as other interfacial phenomena.

Large-scale Patterns of 14C Age of Bulk Organic Carbon and Various Molecular Components in Grassland Soils

Science.gov (United States)

Jia, J.; Liu, Z.; Cao, Z.; Chen, L.; He, J. S.; Haghipour, N.; Wacker, L.; Eglinton, T. I.; Feng, X.

2017-12-01

Unraveling the fate of organic carbon (OC) in soils is essential to understanding the impact of global changes on the global carbon cycle. Previous studies have shown that while various soil OC components have different decomposability, chemically labile OC can have old 14C ages. However, few studies have compared the 14C age of various soil OC components on a large scale, which may provide important information on the link between the age or turnover of soil OC components to their sources, molecular structures as well as environmental variables. In this project, a suite of soil profiles were sampled along a large-scale transect of temperate and alpine grasslands across the Tibetan and Mongolian Plateaus in China with contrasting climatic, vegetation and soil properties. Bulk OC and source-specific compounds (including fatty acids (FAs), diacids (DAs) and lignin phenols) were radiocarbon-dated to investigate the age and turnover dynamics of different OC pools and the mechanisms controlling their stability. Our results show that lignin phenols displayed a large 14C variability. Short-chain (C16, 18) FAs sourced from vascular plants as well as microorganisms were younger than plant-derived long-chain FAs and DAs, indicating that short-chain FAs were easier to be decomposed or newly synthesized. In the temperate grasslands, long-chain DAs were younger than FAs, while the opposite trend was observed in the alpine grasslands. Preliminary correlation analysis suggests that the age of short-chain FAs were mainly influenced by clay contents and climate, while reactive minerals, clay or silt particles were important factors in the stabilization of long-chain FAs, DAs and lignin phenols. Overall, our study provided a unique 14 C dataset of soil OC components in grasslands, which will provide important constraints on soil carbon turnover in future investigations.

Limitations and tradeoffs in synchronization of large-scale networks with uncertain links

Science.gov (United States)

Diwadkar, Amit; Vaidya, Umesh

2016-01-01

The synchronization of nonlinear systems connected over large-scale networks has gained popularity in a variety of applications, such as power grids, sensor networks, and biology. Stochastic uncertainty in the interconnections is a ubiquitous phenomenon observed in these physical and biological networks. We provide a size-independent network sufficient condition for the synchronization of scalar nonlinear systems with stochastic linear interactions over large-scale networks. This sufficient condition, expressed in terms of nonlinear dynamics, the Laplacian eigenvalues of the nominal interconnections, and the variance and location of the stochastic uncertainty, allows us to define a synchronization margin. We provide an analytical characterization of important trade-offs between the internal nonlinear dynamics, network topology, and uncertainty in synchronization. For nearest neighbour networks, the existence of an optimal number of neighbours with a maximum synchronization margin is demonstrated. An analytical formula for the optimal gain that produces the maximum synchronization margin allows us to compare the synchronization properties of various complex network topologies. PMID:27067994

Mapping spatial patterns of denitrifiers at large scales (Invited)

Science.gov (United States)

Philippot, L.; Ramette, A.; Saby, N.; Bru, D.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.

2010-12-01

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.

Less is more: regularization perspectives on large scale machine learning

CERN Multimedia

CERN. Geneva

2017-01-01

Deep learning based techniques provide a possible solution at the expanse of theoretical guidance and, especially, of computational requirements. It is then a key challenge for large scale machine learning to devise approaches guaranteed to be accurate and yet computationally efficient. In this talk, we will consider a regularization perspectives on machine learning appealing to classical ideas in linear algebra and inverse problems to scale-up dramatically nonparametric methods such as kernel methods, often dismissed because of prohibitive costs. Our analysis derives optimal theoretical guarantees while providing experimental results at par or out-performing state of the art approaches.

Exploring quantum control landscapes: Topology, features, and optimization scaling

International Nuclear Information System (INIS)

Moore, Katharine W.; Rabitz, Herschel

2011-01-01

Quantum optimal control experiments and simulations have successfully manipulated the dynamics of systems ranging from atoms to biomolecules. Surprisingly, these collective works indicate that the effort (i.e., the number of algorithmic iterations) required to find an optimal control field appears to be essentially invariant to the complexity of the system. The present work explores this matter in a series of systematic optimizations of the state-to-state transition probability on model quantum systems with the number of states N ranging from 5 through 100. The optimizations occur over a landscape defined by the transition probability as a function of the control field. Previous theoretical studies on the topology of quantum control landscapes established that they should be free of suboptimal traps under reasonable physical conditions. The simulations in this work include nearly 5000 individual optimization test cases, all of which confirm this prediction by fully achieving optimal population transfer of at least 99.9% on careful attention to numerical procedures to ensure that the controls are free of constraints. Collectively, the simulation results additionally show invariance of required search effort to system dimension N. This behavior is rationalized in terms of the structural features of the underlying control landscape. The very attractive observed scaling with system complexity may be understood by considering the distance traveled on the control landscape during a search and the magnitude of the control landscape slope. Exceptions to this favorable scaling behavior can arise when the initial control field fluence is too large or when the target final state recedes from the initial state as N increases.

Molecular scale

Directory of Open Access Journals (Sweden)

Christopher H. Childers

2016-03-01

Full Text Available This manuscript demonstrates the molecular scale cure rate dependence of di-functional epoxide based thermoset polymers cured with amines. A series of cure heating ramp rates were used to determine the influence of ramp rate on the glass transition temperature (Tg and sub-Tg transitions and the average free volume hole size in these systems. The networks were comprised of 3,3′-diaminodiphenyl sulfone (33DDS and diglycidyl ether of bisphenol F (DGEBF and were cured at ramp rates ranging from 0.5 to 20 °C/min. Differential scanning calorimetry (DSC and NIR spectroscopy were used to explore the cure ramp rate dependence of the polymer network growth, whereas broadband dielectric spectroscopy (BDS and free volume hole size measurements were used to interrogate networks’ molecular level structural variations upon curing at variable heating ramp rates. It was found that although the Tg of the polymer matrices was similar, the NIR and DSC measurements revealed a strong correlation for how these networks grow in relation to the cure heating ramp rate. The free volume analysis and BDS results for the cured samples suggest differences in the molecular architecture of the matrix polymers due to cure heating rate dependence.

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.

Large scale nuclear structure studies

International Nuclear Information System (INIS)

Faessler, A.

1985-01-01

Results of large scale nuclear structure studies are reported. The starting point is the Hartree-Fock-Bogoliubov solution with angular momentum and proton and neutron number projection after variation. This model for number and spin projected two-quasiparticle excitations with realistic forces yields in sd-shell nuclei similar good results as the 'exact' shell-model calculations. Here the authors present results for a pf-shell nucleus 46 Ti and results for the A=130 mass region where they studied 58 different nuclei with the same single-particle energies and the same effective force derived from a meson exchange potential. They carried out a Hartree-Fock-Bogoliubov variation after mean field projection in realistic model spaces. In this way, they determine for each yrast state the optimal mean Hartree-Fock-Bogoliubov field. They apply this method to 130 Ce and 128 Ba using the same effective nucleon-nucleon interaction. (Auth.)

Scheduling of power generation a large-scale mixed-variable model

CERN Document Server

Prékopa, András; Strazicky, Beáta; Deák, István; Hoffer, János; Németh, Ágoston; Potecz, Béla

2014-01-01

The book contains description of a real life application of modern mathematical optimization tools in an important problem solution for power networks. The objective is the modelling and calculation of optimal daily scheduling of power generation, by thermal power plants,  to satisfy all demands at minimum cost, in such a way that the  generation and transmission capacities as well as the demands at the nodes of the system appear in an integrated form. The physical parameters of the network are also taken into account. The obtained large-scale mixed variable problem is relaxed in a smart, practical way, to allow for fast numerical solution of the problem.

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.)

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

An industrial perspective on bioreactor scale-down: what we can learn from combined large-scale bioprocess and model fluid studies.

Science.gov (United States)

Noorman, Henk

2011-08-01

For industrial bioreactor design, operation, control and optimization, the scale-down approach is often advocated to efficiently generate data on a small scale, and effectively apply suggested improvements to the industrial scale. In all cases it is important to ensure that the scale-down conditions are representative of the real large-scale bioprocess. Progress is hampered by limited detailed and local information from large-scale bioprocesses. Complementary to real fermentation studies, physical aspects of model fluids such as air-water in large bioreactors provide useful information with limited effort and cost. Still, in industrial practice, investments of time, capital and resources often prohibit systematic work, although, in the end, savings obtained in this way are trivial compared to the expenses that result from real process disturbances, batch failures, and non-flyers with loss of business opportunity. Here we try to highlight what can be learned from real large-scale bioprocess in combination with model fluid studies, and to provide suitable computation tools to overcome data restrictions. Focus is on a specific well-documented case for a 30-m(3) bioreactor. Areas for further research from an industrial perspective are also indicated. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Large-scale exploration and analysis of drug combinations.

Science.gov (United States)

Li, Peng; Huang, Chao; Fu, Yingxue; Wang, Jinan; Wu, Ziyin; Ru, Jinlong; Zheng, Chunli; Guo, Zihu; Chen, Xuetong; Zhou, Wei; Zhang, Wenjuan; Li, Yan; Chen, Jianxin; Lu, Aiping; Wang, Yonghua

2015-06-15

Drug combinations are a promising strategy for combating complex diseases by improving the efficacy and reducing corresponding side effects. Currently, a widely studied problem in pharmacology is to predict effective drug combinations, either through empirically screening in clinic or pure experimental trials. However, the large-scale prediction of drug combination by a systems method is rarely considered. We report a systems pharmacology framework to predict drug combinations (PreDCs) on a computational model, termed probability ensemble approach (PEA), for analysis of both the efficacy and adverse effects of drug combinations. First, a Bayesian network integrating with a similarity algorithm is developed to model the combinations from drug molecular and pharmacological phenotypes, and the predictions are then assessed with both clinical efficacy and adverse effects. It is illustrated that PEA can predict the combination efficacy of drugs spanning different therapeutic classes with high specificity and sensitivity (AUC = 0.90), which was further validated by independent data or new experimental assays. PEA also evaluates the adverse effects (AUC = 0.95) quantitatively and detects the therapeutic indications for drug combinations. Finally, the PreDC database includes 1571 known and 3269 predicted optimal combinations as well as their potential side effects and therapeutic indications. The PreDC database is available at http://sm.nwsuaf.edu.cn/lsp/predc.php. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Half dozen of one, six billion of the other: What can small- and large-scale molecular systems biology learn from one another?

Science.gov (United States)

Mellis, Ian A; Raj, Arjun

2015-10-01

Small-scale molecular systems biology, by which we mean the understanding of a how a few parts work together to control a particular biological process, is predicated on the assumption that cellular regulation is arranged in a circuit-like structure. Results from the omics revolution have upset this vision to varying degrees by revealing a high degree of interconnectivity, making it difficult to develop a simple, circuit-like understanding of regulatory processes. We here outline the limitations of the small-scale systems biology approach with examples from research into genetic algorithms, genetics, transcriptional network analysis, and genomics. We also discuss the difficulties associated with deriving true understanding from the analysis of large data sets and propose that the development of new, intelligent, computational tools may point to a way forward. Throughout, we intentionally oversimplify and talk about things in which we have little expertise, and it is likely that many of our arguments are wrong on one level or another. We do believe, however, that developing a true understanding via molecular systems biology will require a fundamental rethinking of our approach, and our goal is to provoke thought along these lines. © 2015 Mellis and Raj; Published by Cold Spring Harbor Laboratory Press.

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

Large-scale modeling of rain fields from a rain cell deterministic model

Science.gov (United States)

FéRal, Laurent; Sauvageot, Henri; Castanet, Laurent; Lemorton, JoëL.; Cornet, FréDéRic; Leconte, Katia

2006-04-01

A methodology to simulate two-dimensional rain rate fields at large scale (1000 × 1000 km2, the scale of a satellite telecommunication beam or a terrestrial fixed broadband wireless access network) is proposed. It relies on a rain rate field cellular decomposition. At small scale (˜20 × 20 km2), the rain field is split up into its macroscopic components, the rain cells, described by the Hybrid Cell (HYCELL) cellular model. At midscale (˜150 × 150 km2), the rain field results from the conglomeration of rain cells modeled by HYCELL. To account for the rain cell spatial distribution at midscale, the latter is modeled by a doubly aggregative isotropic random walk, the optimal parameterization of which is derived from radar observations at midscale. The extension of the simulation area from the midscale to the large scale (1000 × 1000 km2) requires the modeling of the weather frontal area. The latter is first modeled by a Gaussian field with anisotropic covariance function. The Gaussian field is then turned into a binary field, giving the large-scale locations over which it is raining. This transformation requires the definition of the rain occupation rate over large-scale areas. Its probability distribution is determined from observations by the French operational radar network ARAMIS. The coupling with the rain field modeling at midscale is immediate whenever the large-scale field is split up into midscale subareas. The rain field thus generated accounts for the local CDF at each point, defining a structure spatially correlated at small scale, midscale, and large scale. It is then suggested that this approach be used by system designers to evaluate diversity gain, terrestrial path attenuation, or slant path attenuation for different azimuth and elevation angle directions.

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.

Multi-Agent System Supporting Automated Large-Scale Photometric Computations

Directory of Open Access Journals (Sweden)

Adam Sȩdziwy

2016-02-01

Full Text Available The technologies related to green energy, smart cities and similar areas being dynamically developed in recent years, face frequently problems of a computational nature rather than a technological one. The example is the ability of accurately predicting the weather conditions for PV farms or wind turbines. Another group of issues is related to the complexity of the computations required to obtain an optimal setup of a solution being designed. In this article, we present the case representing the latter group of problems, namely designing large-scale power-saving lighting installations. The term “large-scale” refers to an entire city area, containing tens of thousands of luminaires. Although a simple power reduction for a single street, giving limited savings, is relatively easy, it becomes infeasible for tasks covering thousands of luminaires described by precise coordinates (instead of simplified layouts. To overcome this critical issue, we propose introducing a formal representation of a computing problem and applying a multi-agent system to perform design-related computations in parallel. The important measure introduced in the article indicating optimization progress is entropy. It also allows for terminating optimization when the solution is satisfying. The article contains the results of real-life calculations being made with the help of the presented approach.

Optimized molecular reconstruction procedure combining hybrid reverse Monte Carlo and molecular dynamics

Energy Technology Data Exchange (ETDEWEB)

Bousige, Colin; Boţan, Alexandru; Coasne, Benoît, E-mail: coasne@mit.edu [Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); UMI 3466 CNRS-MIT, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); Ulm, Franz-Josef [Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); Pellenq, Roland J.-M. [Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); UMI 3466 CNRS-MIT, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); CINaM, CNRS/Aix Marseille Université, Campus de Luminy, 13288 Marseille Cedex 09 (France)

2015-03-21

We report an efficient atom-scale reconstruction method that consists of combining the Hybrid Reverse Monte Carlo algorithm (HRMC) with Molecular Dynamics (MD) in the framework of a simulated annealing technique. In the spirit of the experimentally constrained molecular relaxation technique [Biswas et al., Phys. Rev. B 69, 195207 (2004)], this modified procedure offers a refined strategy in the field of reconstruction techniques, with special interest for heterogeneous and disordered solids such as amorphous porous materials. While the HRMC method generates physical structures, thanks to the use of energy penalties, the combination with MD makes the method at least one order of magnitude faster than HRMC simulations to obtain structures of similar quality. Furthermore, in order to ensure the transferability of this technique, we provide rational arguments to select the various input parameters such as the relative weight ω of the energy penalty with respect to the structure optimization. By applying the method to disordered porous carbons, we show that adsorption properties provide data to test the global texture of the reconstructed sample but are only weakly sensitive to the presence of defects. In contrast, the vibrational properties such as the phonon density of states are found to be very sensitive to the local structure of the sample.

Molecular-Scale Electronics: From Concept to Function.

Science.gov (United States)

Xiang, Dong; Wang, Xiaolong; Jia, Chuancheng; Lee, Takhee; Guo, Xuefeng

2016-04-13

Creating functional electrical circuits using individual or ensemble molecules, often termed as "molecular-scale electronics", not only meets the increasing technical demands of the miniaturization of traditional Si-based electronic devices, but also provides an ideal window of exploring the intrinsic properties of materials at the molecular level. This Review covers the major advances with the most general applicability and emphasizes new insights into the development of efficient platform methodologies for building reliable molecular electronic devices with desired functionalities through the combination of programmed bottom-up self-assembly and sophisticated top-down device fabrication. First, we summarize a number of different approaches of forming molecular-scale junctions and discuss various experimental techniques for examining these nanoscale circuits in details. We then give a full introduction of characterization techniques and theoretical simulations for molecular electronics. Third, we highlight the major contributions and new concepts of integrating molecular functionalities into electrical circuits. Finally, we provide a critical discussion of limitations and main challenges that still exist for the development of molecular electronics. These analyses should be valuable for deeply understanding charge transport through molecular junctions, the device fabrication process, and the roadmap for future practical molecular electronics.

Optimized theory for simple and molecular fluids.

Science.gov (United States)

Marucho, M; Montgomery Pettitt, B

2007-03-28

An optimized closure approximation for both simple and molecular fluids is presented. A smooth interpolation between Perkus-Yevick and hypernetted chain closures is optimized by minimizing the free energy self-consistently with respect to the interpolation parameter(s). The molecular version is derived from a refinement of the method for simple fluids. In doing so, a method is proposed which appropriately couples an optimized closure with the variant of the diagrammatically proper integral equation recently introduced by this laboratory [K. M. Dyer et al., J. Chem. Phys. 123, 204512 (2005)]. The simplicity of the expressions involved in this proposed theory has allowed the authors to obtain an analytic expression for the approximate excess chemical potential. This is shown to be an efficient tool to estimate, from first principles, the numerical value of the interpolation parameters defining the aforementioned closure. As a preliminary test, representative models for simple fluids and homonuclear diatomic Lennard-Jones fluids were analyzed, obtaining site-site correlation functions in excellent agreement with simulation data.

PathlinesExplorer — Image-based exploration of large-scale pathline fields

KAUST Repository

Nagoor, Omniah H.

2015-10-25

PathlinesExplorer is a novel image-based tool, which has been designed to visualize large scale pathline fields on a single computer [7]. PathlinesExplorer integrates explorable images (EI) technique [4] with order-independent transparency (OIT) method [2]. What makes this method different is that it allows users to handle large data on a single workstation. Although it is a view-dependent method, PathlinesExplorer combines both exploration and modification of visual aspects without re-accessing the original huge data. Our approach is based on constructing a per-pixel linked list data structure in which each pixel contains a list of pathline segments. With this view-dependent method, it is possible to filter, color-code, and explore large-scale flow data in real-time. In addition, optimization techniques such as early-ray termination and deferred shading are applied, which further improves the performance and scalability of our approach.

Large-scale structure of the Taurus molecular complex. II. Analysis of velocity fluctuations and turbulence. III. Methods for turbulence

International Nuclear Information System (INIS)

Kleiner, S.C.; Dickman, R.L.

1985-01-01

The velocity autocorrelation function (ACF) of observed spectral line centroid fluctuations is noted to effectively reproduce the actual ACF of turbulent gas motions within an interstellar cloud, thereby furnishing a framework for the study of the large scale velocity structure of the Taurus dark cloud complex traced by the present C-13O J = 1-0 observations of this region. The results obtained are discussed in the context of recent suggestions that widely observed correlations between molecular cloud widths and cloud sizes indicate the presence of a continuum of turbulent motions within the dense interstellar medium. Attention is then given to a method for the quantitative study of these turbulent motions, involving the mapping of a source in an optically thin spectral line and studying the spatial correlation properties of the resulting velocity centroid map. 61 references

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

Distributed weighted least-squares estimation with fast convergence for large-scale systems☆

Science.gov (United States)

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods. PMID:25641976

Distributed weighted least-squares estimation with fast convergence for large-scale systems.

Science.gov (United States)

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods.

Output regulation of large-scale hydraulic networks with minimal steady state power consumption

NARCIS (Netherlands)

Jensen, Tom Nørgaard; Wisniewski, Rafał; De Persis, Claudio; Kallesøe, Carsten Skovmose

2014-01-01

An industrial case study involving a large-scale hydraulic network is examined. The hydraulic network underlies a district heating system, with an arbitrary number of end-users. The problem of output regulation is addressed along with a optimization criterion for the control. The fact that the

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

Science.gov (United States)

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

2015-01-01

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

Topology optimization for nano-scale heat transfer

DEFF Research Database (Denmark)

Evgrafov, Anton; Maute, Kurt; Yang, Ronggui

2009-01-01

We consider the problem of optimal design of nano-scale heat conducting systems using topology optimization techniques. At such small scales the empirical Fourier's law of heat conduction no longer captures the underlying physical phenomena because the mean-free path of the heat carriers, phonons...... in our case, becomes comparable with, or even larger than, the feature sizes of considered material distributions. A more accurate model at nano-scales is given by kinetic theory, which provides a compromise between the inaccurate Fourier's law and precise, but too computationally expensive, atomistic...

Resolving the Circumstellar Environment of the Galactic B[e] Supergiant Star MWC 137 from Large to Small Scales

Energy Technology Data Exchange (ETDEWEB)

Kraus, Michaela; Nickeler, Dieter H. [Astronomický ústav, Akademie věd České republiky, v.v.i., Fričova 298, 251 65 Ondřejov (Czech Republic); Liimets, Tiina [Tartu Observatory, 61602 Tõravere, Tartumaa (Estonia); Cappa, Cristina E.; Duronea, Nicolas U. [Instituto Argentino de Radioastronomía, CONICET, CCT-La Plata, C.C.5., 1894, Villa Elisa (Argentina); Cidale, Lydia S.; Arias, Maria L. [Facultad de Ciencias Astronómicas y Geofísicas, Universidad Nacional de La Plata, Paseo del Bosque s/n, 1900, La Plata (Argentina); Gunawan, Diah S.; Maravelias, Grigoris; Curé, Michel [Instituto de Física y Astronomía, Facultad de Ciencias, Universidad de Valparaíso, Av. Gran Bretaña 1111, Casilla 5030, Valparaíso (Chile); Oksala, Mary E. [California Lutheran University, Department of Physics, Thousand Oaks, CA 91360 (United States); Fernandes, Marcelo Borges [Observatório Nacional, Rua General José Cristino 77, 20921-400 São Cristovão, Rio de Janeiro (Brazil); Santander-García, Miguel, E-mail: michaela.kraus@asu.cas.cz [Observatorio Astronómico Nacional (IGN), C/Alfonso XII 3, E-28014, Madrid (Spain)

2017-11-01

The Galactic object MWC 137 has been suggested to belong to the group of B[e] supergiants. However, with its large-scale optical bipolar ring nebula and high-velocity jet and knots, it is a rather atypical representative of this class. We performed multiwavelength observations spreading from the optical to the radio regimes. Based on optical imaging and long-slit spectroscopic data, we found that the northern parts of the large-scale nebula are predominantly blueshifted, while the southern regions appear mostly redshifted. We developed a geometrical model consisting of two double cones. Although various observational features can be approximated with such a scenario, the observed velocity pattern is more complex. Using near-infrared integral-field unit spectroscopy, we studied the hot molecular gas in the vicinity of the star. The emission from the hot CO gas arises in a small-scale disk revolving around the star on Keplerian orbits. Although the disk itself cannot be spatially resolved, its emission is reflected by the dust arranged in arc-like structures and the clumps surrounding MWC 137 on small scales. In the radio regime, we mapped the cold molecular gas in the outskirts of the optical nebula. We found that large amounts of cool molecular gas and warm dust embrace the optical nebula in the east, south, and west. No cold gas or dust was detected in the north and northwestern regions. Despite the new insights into the nebula kinematics gained from our studies, the real formation scenario of the large-scale nebula remains an open issue.

Resolving the Circumstellar Environment of the Galactic B[e] Supergiant Star MWC 137 from Large to Small Scales

International Nuclear Information System (INIS)

Kraus, Michaela; Nickeler, Dieter H.; Liimets, Tiina; Cappa, Cristina E.; Duronea, Nicolas U.; Cidale, Lydia S.; Arias, Maria L.; Gunawan, Diah S.; Maravelias, Grigoris; Curé, Michel; Oksala, Mary E.; Fernandes, Marcelo Borges; Santander-García, Miguel

2017-01-01

The Galactic object MWC 137 has been suggested to belong to the group of B[e] supergiants. However, with its large-scale optical bipolar ring nebula and high-velocity jet and knots, it is a rather atypical representative of this class. We performed multiwavelength observations spreading from the optical to the radio regimes. Based on optical imaging and long-slit spectroscopic data, we found that the northern parts of the large-scale nebula are predominantly blueshifted, while the southern regions appear mostly redshifted. We developed a geometrical model consisting of two double cones. Although various observational features can be approximated with such a scenario, the observed velocity pattern is more complex. Using near-infrared integral-field unit spectroscopy, we studied the hot molecular gas in the vicinity of the star. The emission from the hot CO gas arises in a small-scale disk revolving around the star on Keplerian orbits. Although the disk itself cannot be spatially resolved, its emission is reflected by the dust arranged in arc-like structures and the clumps surrounding MWC 137 on small scales. In the radio regime, we mapped the cold molecular gas in the outskirts of the optical nebula. We found that large amounts of cool molecular gas and warm dust embrace the optical nebula in the east, south, and west. No cold gas or dust was detected in the north and northwestern regions. Despite the new insights into the nebula kinematics gained from our studies, the real formation scenario of the large-scale nebula remains an open issue.

Optimizing porphyrins for dye sensitized solar cells using large-scale ab initio calculations

DEFF Research Database (Denmark)

Ørnsø, Kristian Baruël; Pedersen, Christian S.; García Lastra, Juan Maria

2014-01-01

different side and anchoring groups. Based on the calculated frontier orbital energies and optical gaps we quantify the energy level alignment with the TiO2 conduction band and different redox mediators. An analysis of the energy level-structure relationship reveals a significant structural diversity among...... the dyes with the highest level alignment quality, demonstrating the large degree of flexibility in porphyrin dye design. As a specific example of dye optimization, we show that the level alignment of the high efficiency record dye YD2-o-C8 [Yella et al., Science, 2011, 334, 629-634] can be significantly...

Algorithm 873: LSTRS: MATLAB Software for Large-Scale Trust-Region Subproblems and Regularization

DEFF Research Database (Denmark)

Rojas Larrazabal, Marielba de la Caridad; Santos, Sandra A.; Sorensen, Danny C.

2008-01-01

A MATLAB 6.0 implementation of the LSTRS method is resented. LSTRS was described in Rojas, M., Santos, S.A., and Sorensen, D.C., A new matrix-free method for the large-scale trust-region subproblem, SIAM J. Optim., 11(3):611-646, 2000. LSTRS is designed for large-scale quadratic problems with one...... at each step. LSTRS relies on matrix-vector products only and has low and fixed storage requirements, features that make it suitable for large-scale computations. In the MATLAB implementation, the Hessian matrix of the quadratic objective function can be specified either explicitly, or in the form...... of a matrix-vector multiplication routine. Therefore, the implementation preserves the matrix-free nature of the method. A description of the LSTRS method and of the MATLAB software, version 1.2, is presented. Comparisons with other techniques and applications of the method are also included. A guide...

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.

PubChemQC Project: A Large-Scale First-Principles Electronic Structure Database for Data-Driven Chemistry.

Science.gov (United States)

Nakata, Maho; Shimazaki, Tomomi

2017-06-26

Large-scale molecular databases play an essential role in the investigation of various subjects such as the development of organic materials, in silico drug design, and data-driven studies with machine learning. We have developed a large-scale quantum chemistry database based on first-principles methods. Our database currently contains the ground-state electronic structures of 3 million molecules based on density functional theory (DFT) at the B3LYP/6-31G* level, and we successively calculated 10 low-lying excited states of over 2 million molecules via time-dependent DFT with the B3LYP functional and the 6-31+G* basis set. To select the molecules calculated in our project, we referred to the PubChem Project, which was used as the source of the molecular structures in short strings using the InChI and SMILES representations. Accordingly, we have named our quantum chemistry database project "PubChemQC" ( http://pubchemqc.riken.jp/ ) and placed it in the public domain. In this paper, we show the fundamental features of the PubChemQC database and discuss the techniques used to construct the data set for large-scale quantum chemistry calculations. We also present a machine learning approach to predict the electronic structure of molecules as an example to demonstrate the suitability of the large-scale quantum chemistry database.

Numerical computation of molecular integrals via optimized (vectorized) FORTRAN code

International Nuclear Information System (INIS)

Scott, T.C.; Grant, I.P.; Saunders, V.R.

1997-01-01

The calculation of molecular properties based on quantum mechanics is an area of fundamental research whose horizons have always been determined by the power of state-of-the-art computers. A computational bottleneck is the numerical calculation of the required molecular integrals to sufficient precision. Herein, we present a method for the rapid numerical evaluation of molecular integrals using optimized FORTRAN code generated by Maple. The method is based on the exploitation of common intermediates and the optimization can be adjusted to both serial and vectorized computations. (orig.)

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

Energy Technology Data Exchange (ETDEWEB)

Schanen, Michel; Marin, Oana; Zhang, Hong; Anitescu, Mihai

2016-01-01

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

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...

An Optimal Parametrization of Turbulent Scales

Science.gov (United States)

Thalabard, S.

2015-12-01

To numerically capture the large-scale dynamics of atmospheric flows, geophysicists need to rely on reasonable parametrizations of the energy transfers to and from the non-resolved small scale eddies, mediated through turbulence. The task is notoriously not trivial, and is typically solved by ingenious but ad-hoc elaborations on the concept of eddy viscosities. The difficulty is tied into the intrinsic Non-Gaussianity of turbulence, a feature that may explain why standard Quasi-Normal cumulant discard statistical closure strategies can fail dramatically, an example being the development of negative energy spectra in Millionshtchikov's 1941 Quasi-Normal (QN) theory. While Orszag's 1977 Eddy Damped Quasi Normal Markovian closure (EDQNM) provides an ingenious patch to the issue, the reason why the QN theory fails so badly is not so clear. Are closures necessarily either trivial or ad-hoc, when proxies for true ensemble averages are taken to be Gaussian ? The purpose of the talk is to answer negatively, using the lights of a new ``optimal closure framework'' recently exposed by [Turkington,2013]. For turbulence problems, the optimal closure allows a consistent use of a Gaussian Ansatz (and corresponding vanishing third cumulant) that also retains an intrinsic damping. The key to this apparent paradox lies in a clear distinction between the true ensemble averages and their proxies, most easily grasped provided one uses the Liouville equation as a starting point, rather than the cumulant hierarchy. Schematically said, closure is achieved by minimizing a lack-of-fit residual, which retains the intrinsic features of the true dynamics. The optimal closure is not restricted to the Gaussian modeling. Yet, for the sake of clarity, I will discuss the optimal closure on a problem where it can be entirely implemented, and compared to DNS : the relaxation of an arbitrarily far from equilibrium energy shell towards the Gibbs equilibrium for truncated Euler dynamics. Predictive

Distributed parallel cooperative coevolutionary multi-objective large-scale immune algorithm for deployment of wireless sensor networks

DEFF Research Database (Denmark)

Cao, Bin; Zhao, Jianwei; Yang, Po

2018-01-01

-objective evolutionary algorithms the Cooperative Coevolutionary Generalized Differential Evolution 3, the Cooperative Multi-objective Differential Evolution and the Nondominated Sorting Genetic Algorithm III, the proposed algorithm addresses the deployment optimization problem efficiently and effectively.......Using immune algorithms is generally a time-intensive process especially for problems with a large number of variables. In this paper, we propose a distributed parallel cooperative coevolutionary multi-objective large-scale immune algorithm that is implemented using the message passing interface...... (MPI). The proposed algorithm is composed of three layers: objective, group and individual layers. First, for each objective in the multi-objective problem to be addressed, a subpopulation is used for optimization, and an archive population is used to optimize all the objectives. Second, the large...

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)

On the strong influence of molecular interactions over large distances

Science.gov (United States)

Pfennig, Andreas

2018-03-01

Molecular-dynamics simulations of liquid water show deterministic chaos, i.e. an intentionally introduced molecular position shift of an individual molecule increases exponentially by a factor of 10 in 0.23 ps. This is a Lyaponov instability. As soon as it reaches molecular scale, the direction of the resulting shift in molecular motions is unpredictable. The influence of any individual distant particle on an observed molecule will be minute, but the effect will quickly increase to molecular scale and beyond due to this exponential growth. Consequently, any individual particle in the universe will affect the behavior of any molecule within at most 33 ps after the interaction reaches it. A larger distance of the faraway particle does not decrease the influence on an observed molecule, but the effect reaches molecular scale only some ps later. Thus in evaluating the interactions, nearby and faraway molecules have to be equally accounted for. The consequences of this quickly reacting network of interactions on universal scale are fundamental. Even in a strictly deterministic view, molecular behavior is principally unpredictable, and thus has to be regarded random. Corresponding statements apply for any particles interacting. This result leads to a fundamental rethinking of the structure of interactions of molecules and particles as well as the behavior of reality.

Optimal Experimental Design for Large-Scale Bayesian Inverse Problems

KAUST Repository

Ghattas, Omar

2014-01-01

We develop a Bayesian framework for the optimal experimental design of the shock tube experiments which are being carried out at the KAUST Clean Combustion Research Center. The unknown parameters are the pre-exponential parameters and the activation

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 ...

Preface: Special Topic on Frontiers in Molecular Scale Electronics

Science.gov (United States)

Evers, Ferdinand; Venkataraman, Latha

2017-03-01

The electronic, mechanical, and thermoelectric properties of molecular scale devices have fascinated scientists across several disciplines in natural sciences and engineering. The interest is partially technological, driven by the fast miniaturization of integrated circuits that now have reached characteristic features at the nanometer scale. Equally important, a very strong incentive also exists to elucidate the fundamental aspects of structure-function relations for nanoscale devices, which utilize molecular building blocks as functional units. Thus motivated, a rich research field has established itself, broadly termed "Molecular Electronics," that hosts a plethora of activities devoted to this goal in chemistry, physics, and electrical engineering. This Special Topic on Frontiers of Molecular Scale Electronics captures recent theoretical and experimental advances in the field.

Networking for large-scale science: infrastructure, provisioning, transport and application mapping

International Nuclear Information System (INIS)

Rao, Nageswara S; Carter, Steven M; Wu Qishi; Wing, William R; Zhu Mengxia; Mezzacappa, Anthony; Veeraraghavan, Malathi; Blondin, John M

2005-01-01

Large-scale science computations and experiments require unprecedented network capabilities in the form of large bandwidth and dynamically stable connections to support data transfers, interactive visualizations, and monitoring and steering operations. A number of component technologies dealing with the infrastructure, provisioning, transport and application mappings must be developed and/or optimized to achieve these capabilities. We present a brief account of the following technologies that contribute toward achieving these network capabilities: (a) DOE UltraScienceNet and NSF CHEETAH network testbeds that provide on-demand and scheduled dedicated network connections; (b) experimental results on transport protocols that achieve close to 100% utilization on dedicated 1Gbps wide-area channels; (c) a scheme for optimally mapping a visualization pipeline onto a network to minimize the end-to-end delays; and (d) interconnect configuration and protocols that provides multiple Gbps flows from Cray X1 to external hosts

Networking for large-scale science: infrastructure, provisioning, transport and application mapping

Energy Technology Data Exchange (ETDEWEB)

Rao, Nageswara S [Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Carter, Steven M [Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Wu Qishi [Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Wing, William R [Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Zhu Mengxia [Department of Computer Science, Louisiana State University, Baton Rouge, LA 70803 (United States); Mezzacappa, Anthony [Physics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Veeraraghavan, Malathi [Department of Computer Science, University of Virginia, Charlottesville, VA 22904 (United States); Blondin, John M [Department of Physics, North Carolina State University, Raleigh, NC 27695 (United States)

2005-01-01

Large-scale science computations and experiments require unprecedented network capabilities in the form of large bandwidth and dynamically stable connections to support data transfers, interactive visualizations, and monitoring and steering operations. A number of component technologies dealing with the infrastructure, provisioning, transport and application mappings must be developed and/or optimized to achieve these capabilities. We present a brief account of the following technologies that contribute toward achieving these network capabilities: (a) DOE UltraScienceNet and NSF CHEETAH network testbeds that provide on-demand and scheduled dedicated network connections; (b) experimental results on transport protocols that achieve close to 100% utilization on dedicated 1Gbps wide-area channels; (c) a scheme for optimally mapping a visualization pipeline onto a network to minimize the end-to-end delays; and (d) interconnect configuration and protocols that provides multiple Gbps flows from Cray X1 to external hosts.

Design and Optimization of Fast Switching Valves for Large Scale Digital Hydraulic Motors

DEFF Research Database (Denmark)

Roemer, Daniel Beck

The present thesis is on the design, analysis and optimization of fast switching valves for digital hydraulic motors with high power ratings. The need for such high power motors origins in the potential use of hydrostatic transmissions in wind turbine drive trains, as digital hydraulic machines...... have been shown to improve the overall efficiency and efficient operation range compared to traditional hydraulic machines. Digital hydraulic motors uses electronically controlled independent seat valves connected to the pressure chambers, which must be fast acting and exhibit low pressure losses...... to enable efficient operation. These valves are complex components to design, as multiple design aspects are present in these integrated valve units, with conflicting objectives and interdependencies. A preliminary study on a small scale single-cylinder digital hydraulic pump has initially been conducted...

Large scale mapping of groundwater resources using a highly integrated set of tools

DEFF Research Database (Denmark)

Søndergaard, Verner; Auken, Esben; Christiansen, Anders Vest

large areas with information from an optimum number of new investigation boreholes, existing boreholes, logs and water samples to get an integrated and detailed description of the groundwater resources and their vulnerability.Development of more time efficient and airborne geophysical data acquisition...... platforms (e.g. SkyTEM) have made large-scale mapping attractive and affordable in the planning and administration of groundwater resources. The handling and optimized use of huge amounts of geophysical data covering large areas has also required a comprehensive database, where data can easily be stored...

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

An efficient and novel computation method for simulating diffraction patterns from large-scale coded apertures on large-scale focal plane arrays

Science.gov (United States)

Shrekenhamer, Abraham; Gottesman, Stephen R.

2012-10-01

A novel and memory efficient method for computing diffraction patterns produced on large-scale focal planes by largescale Coded Apertures at wavelengths where diffraction effects are significant has been developed and tested. The scheme, readily implementable on portable computers, overcomes the memory limitations of present state-of-the-art simulation codes such as Zemax. The method consists of first calculating a set of reference complex field (amplitude and phase) patterns on the focal plane produced by a single (reference) central hole, extending to twice the focal plane array size, with one such pattern for each Line-of-Sight (LOS) direction and wavelength in the scene, and with the pattern amplitude corresponding to the square-root of the spectral irradiance from each such LOS direction in the scene at selected wavelengths. Next the set of reference patterns is transformed to generate pattern sets for other holes. The transformation consists of a translational pattern shift corresponding to each hole's position offset and an electrical phase shift corresponding to each hole's position offset and incoming radiance's direction and wavelength. The set of complex patterns for each direction and wavelength is then summed coherently and squared for each detector to yield a set of power patterns unique for each direction and wavelength. Finally the set of power patterns is summed to produce the full waveband diffraction pattern from the scene. With this tool researchers can now efficiently simulate diffraction patterns produced from scenes by large-scale Coded Apertures onto large-scale focal plane arrays to support the development and optimization of coded aperture masks and image reconstruction algorithms.

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.

Cost optimization of wind turbines for large-scale offshore wind farms

International Nuclear Information System (INIS)

Fuglsang, P.; Thomsen, K.

1998-02-01

This report contains a preliminary investigation of site specific design of off-shore wind turbines for a large off-shore wind farm project at Roedsand that is currently being proposed by ELKRAFT/SEAS. The results were found using a design tool for wind turbines that involve numerical optimization and aeroelastic calculations of response. The wind climate was modeled in detail and a cost function was used to estimate costs from manufacture and installation. Cost of energy is higher for off-shore installations. A comparison of an off-shore wind farm site with a typical stand alone on-shore site showed an increase of the annual production of 28% due to the difference in wind climate. Extreme loads and blade fatigue loads were nearly identical, however,fatigue loads on other main components increased significantly. Optimizations were carried out to find the optimum overall off-shore wind turbine design. A wind turbine for the off-shore wind farm should be different compared with a stand-alone on-shore wind turbine. The overall design changed were increased swept area and rated power combined with reduced rotor speed and tower height. Cost was reduced by 12% for the final 5D/14D off-shore wind turbine from 0.306 DKr/kWh to 0.270 DKr/kWh. These figures include capital costs from manufacture and installation but not on-going costs from maintenance. These results make off-shore wind farms more competitive and comparable to the reference on-shore stand-alone wind turbine. A corresponding reduction of cost of energy could not be found for the stand alone on-shore wind turbine. Furthermore the fatigue loads on wind turbines in on-shore wind farms will increase and cost of energy will increase in favor of off-shore wind farms. (au) EFP-95; EU-JOULE-3; 21 tabs., 7 ills., 8 refs

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.

Optimal Experimental Design for Large-Scale Bayesian Inverse Problems

KAUST Repository

Ghattas, Omar

2014-01-06

We develop a Bayesian framework for the optimal experimental design of the shock tube experiments which are being carried out at the KAUST Clean Combustion Research Center. The unknown parameters are the pre-exponential parameters and the activation energies in the reaction rate expressions. The control parameters are the initial mixture composition and the temperature. The approach is based on first building a polynomial based surrogate model for the observables relevant to the shock tube experiments. Based on these surrogates, a novel MAP based approach is used to estimate the expected information gain in the proposed experiments, and to select the best experimental set-ups yielding the optimal expected information gains. The validity of the approach is tested using synthetic data generated by sampling the PC surrogate. We finally outline a methodology for validation using actual laboratory experiments, and extending experimental design methodology to the cases where the control parameters are noisy.

Meta-Heuristics in Short Scale Construction: Ant Colony Optimization and Genetic Algorithm.

Science.gov (United States)

Schroeders, Ulrich; Wilhelm, Oliver; Olaru, Gabriel

2016-01-01

The advent of large-scale assessment, but also the more frequent use of longitudinal and multivariate approaches to measurement in psychological, educational, and sociological research, caused an increased demand for psychometrically sound short scales. Shortening scales economizes on valuable administration time, but might result in inadequate measures because reducing an item set could: a) change the internal structure of the measure, b) result in poorer reliability and measurement precision, c) deliver measures that cannot effectively discriminate between persons on the intended ability spectrum, and d) reduce test-criterion relations. Different approaches to abbreviate measures fare differently with respect to the above-mentioned problems. Therefore, we compare the quality and efficiency of three item selection strategies to derive short scales from an existing long version: a Stepwise COnfirmatory Factor Analytical approach (SCOFA) that maximizes factor loadings and two metaheuristics, specifically an Ant Colony Optimization (ACO) with a tailored user-defined optimization function and a Genetic Algorithm (GA) with an unspecific cost-reduction function. SCOFA compiled short versions were highly reliable, but had poor validity. In contrast, both metaheuristics outperformed SCOFA and produced efficient and psychometrically sound short versions (unidimensional, reliable, sensitive, and valid). We discuss under which circumstances ACO and GA produce equivalent results and provide recommendations for conditions in which it is advisable to use a metaheuristic with an unspecific out-of-the-box optimization function.

Large-scale molecular dynamics simulations of self-assembling systems.

Science.gov (United States)

Klein, Michael L; Shinoda, Wataru

2008-08-08

Relentless increases in the size and performance of multiprocessor computers, coupled with new algorithms and methods, have led to novel applications of simulations across chemistry. This Perspective focuses on the use of classical molecular dynamics and so-called coarse-grain models to explore phenomena involving self-assembly in complex fluids and biological systems.

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.

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.

RGCA: A Reliable GPU Cluster Architecture for Large-Scale Internet of Things Computing Based on Effective Performance-Energy Optimization.

Science.gov (United States)

Fang, Yuling; Chen, Qingkui; Xiong, Neal N; Zhao, Deyu; Wang, Jingjuan

2017-08-04

This paper aims to develop a low-cost, high-performance and high-reliability computing system to process large-scale data using common data mining algorithms in the Internet of Things (IoT) computing environment. Considering the characteristics of IoT data processing, similar to mainstream high performance computing, we use a GPU (Graphics Processing Unit) cluster to achieve better IoT services. Firstly, we present an energy consumption calculation method (ECCM) based on WSNs. Then, using the CUDA (Compute Unified Device Architecture) Programming model, we propose a Two-level Parallel Optimization Model (TLPOM) which exploits reasonable resource planning and common compiler optimization techniques to obtain the best blocks and threads configuration considering the resource constraints of each node. The key to this part is dynamic coupling Thread-Level Parallelism (TLP) and Instruction-Level Parallelism (ILP) to improve the performance of the algorithms without additional energy consumption. Finally, combining the ECCM and the TLPOM, we use the Reliable GPU Cluster Architecture (RGCA) to obtain a high-reliability computing system considering the nodes' diversity, algorithm characteristics, etc. The results show that the performance of the algorithms significantly increased by 34.1%, 33.96% and 24.07% for Fermi, Kepler and Maxwell on average with TLPOM and the RGCA ensures that our IoT computing system provides low-cost and high-reliability services.

Localization Algorithm Based on a Spring Model (LASM for Large Scale Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Shuai Li

2008-03-01

Full Text Available A navigation method for a lunar rover based on large scale wireless sensornetworks is proposed. To obtain high navigation accuracy and large exploration area, highnode localization accuracy and large network scale are required. However, thecomputational and communication complexity and time consumption are greatly increasedwith the increase of the network scales. A localization algorithm based on a spring model(LASM method is proposed to reduce the computational complexity, while maintainingthe localization accuracy in large scale sensor networks. The algorithm simulates thedynamics of physical spring system to estimate the positions of nodes. The sensor nodesare set as particles with masses and connected with neighbor nodes by virtual springs. Thevirtual springs will force the particles move to the original positions, the node positionscorrespondingly, from the randomly set positions. Therefore, a blind node position can bedetermined from the LASM algorithm by calculating the related forces with the neighbornodes. The computational and communication complexity are O(1 for each node, since thenumber of the neighbor nodes does not increase proportionally with the network scale size.Three patches are proposed to avoid local optimization, kick out bad nodes and deal withnode variation. Simulation results show that the computational and communicationcomplexity are almost constant despite of the increase of the network scale size. The time consumption has also been proven to remain almost constant since the calculation steps arealmost unrelated with the network scale size.

Maximum length scale in density based topology optimization

DEFF Research Database (Denmark)

Lazarov, Boyan Stefanov; Wang, Fengwen

2017-01-01

The focus of this work is on two new techniques for imposing maximum length scale in topology optimization. Restrictions on the maximum length scale provide designers with full control over the optimized structure and open possibilities to tailor the optimized design for broader range...... of manufacturing processes by fulfilling the associated technological constraints. One of the proposed methods is based on combination of several filters and builds on top of the classical density filtering which can be viewed as a low pass filter applied to the design parametrization. The main idea...

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

Science.gov (United States)

Hua, H.

2016-12-01

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

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

Science.gov (United States)

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

2016-04-01

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

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

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.

Large-scale sequential quadratic programming algorithms

Energy Technology Data Exchange (ETDEWEB)

Eldersveld, S.K.

1992-09-01

The problem addressed is the general nonlinear programming problem: finding a local minimizer for a nonlinear function subject to a mixture of nonlinear equality and inequality constraints. The methods studied are in the class of sequential quadratic programming (SQP) algorithms, which have previously proved successful for problems of moderate size. Our goal is to devise an SQP algorithm that is applicable to large-scale optimization problems, using sparse data structures and storing less curvature information but maintaining the property of superlinear convergence. The main features are: 1. The use of a quasi-Newton approximation to the reduced Hessian of the Lagrangian function. Only an estimate of the reduced Hessian matrix is required by our algorithm. The impact of not having available the full Hessian approximation is studied and alternative estimates are constructed. 2. The use of a transformation matrix Q. This allows the QP gradient to be computed easily when only the reduced Hessian approximation is maintained. 3. The use of a reduced-gradient form of the basis for the null space of the working set. This choice of basis is more practical than an orthogonal null-space basis for large-scale problems. The continuity condition for this choice is proven. 4. The use of incomplete solutions of quadratic programming subproblems. Certain iterates generated by an active-set method for the QP subproblem are used in place of the QP minimizer to define the search direction for the nonlinear problem. An implementation of the new algorithm has been obtained by modifying the code MINOS. Results and comparisons with MINOS and NPSOL are given for the new algorithm on a set of 92 test problems.

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

Mapping the distribution of the denitrifier community at large scales (Invited)

Science.gov (United States)

Philippot, L.; Bru, D.; Ramette, A.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.

2010-12-01

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 740 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.

Large-scale matrix-handling subroutines 'ATLAS'

International Nuclear Information System (INIS)

Tsunematsu, Toshihide; Takeda, Tatsuoki; Fujita, Keiichi; Matsuura, Toshihiko; Tahara, Nobuo

1978-03-01

Subroutine package ''ATLAS'' has been developed for handling large-scale matrices. The package is composed of four kinds of subroutines, i.e., basic arithmetic routines, routines for solving linear simultaneous equations and for solving general eigenvalue problems and utility routines. The subroutines are useful in large scale plasma-fluid simulations. (auth.)

Temperature Scaling Law for Quantum Annealing Optimizers.

Science.gov (United States)

Albash, Tameem; Martin-Mayor, Victor; Hen, Itay

2017-09-15

Physical implementations of quantum annealing unavoidably operate at finite temperatures. We point to a fundamental limitation of fixed finite temperature quantum annealers that prevents them from functioning as competitive scalable optimizers and show that to serve as optimizers annealer temperatures must be appropriately scaled down with problem size. We derive a temperature scaling law dictating that temperature must drop at the very least in a logarithmic manner but also possibly as a power law with problem size. We corroborate our results by experiment and simulations and discuss the implications of these to practical annealers.

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.)

Energy conserving, linear scaling Born-Oppenheimer molecular dynamics.

Science.gov (United States)

Cawkwell, M J; Niklasson, Anders M N

2012-10-07

Born-Oppenheimer molecular dynamics simulations with long-term conservation of the total energy and a computational cost that scales linearly with system size have been obtained simultaneously. Linear scaling with a low pre-factor is achieved using density matrix purification with sparse matrix algebra and a numerical threshold on matrix elements. The extended Lagrangian Born-Oppenheimer molecular dynamics formalism [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] yields microcanonical trajectories with the approximate forces obtained from the linear scaling method that exhibit no systematic drift over hundreds of picoseconds and which are indistinguishable from trajectories computed using exact forces.

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)

SPECTRAL LINE SURVEY TOWARD MOLECULAR CLOUDS IN THE LARGE MAGELLANIC CLOUD

Energy Technology Data Exchange (ETDEWEB)

Nishimura, Yuri; Watanabe, Yoshimasa; Yamamoto, Satoshi [Department of Physics, the University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-0033 (Japan); Shimonishi, Takashi [Frontier Research Institute for Interdisciplinary Sciences, Tohoku University, Aramakiazaaoba 6-3, Aoba-ku, Sendai, Miyagi, 980-8578 (Japan); Sakai, Nami [RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198 (Japan); Aikawa, Yuri [Center for Computational Sciences, The University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki 305-8577 (Japan); Kawamura, Akiko [National Astronomical Observatory of Japan, Osawa, Mitaka, Tokyo, 181-8588 (Japan)

2016-02-20

Spectral line survey observations of seven molecular clouds in the Large Magellanic Cloud (LMC) have been conducted in the 3 mm band with the Mopra 22 m telescope to reveal chemical compositions in low metallicity conditions. Spectral lines of fundamental species such as CS, SO, CCH, HCN, HCO{sup +}, and HNC are detected in addition to those of CO and {sup 13}CO, while CH{sub 3}OH is not detected in any source and N{sub 2}H{sup +} is marginally detected in two sources. The molecular-cloud scale (10 pc scale) chemical composition is found to be similar among the seven sources regardless of different star formation activities, and hence, it represents the chemical composition characteristic of the LMC without influences by star formation activities. In comparison with chemical compositions of Galactic sources, the characteristic features are (1) deficient N-bearing molecules, (2) abundant CCH, and (3) deficient CH{sub 3}OH. Feature (1) is due to a lower elemental abundance of nitrogen in the LMC, whereas features (2) and (3) seem to originate from extended photodissociation regions and warmer temperature in cloud peripheries due to a lower abundance of dust grains in the low metallicity condition. In spite of general resemblance of chemical abundances among the seven sources, the CS/HCO{sup +} and SO/HCO{sup +} ratios are found to be slightly higher in a quiescent molecular cloud. An origin of this trend is discussed in relation to possible depletion of sulfur along the molecular cloud formation.

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.

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.

Enabling High Performance Large Scale Dense Problems through KBLAS

KAUST Repository

Abdelfattah, Ahmad

2014-05-04

KBLAS (KAUST BLAS) is a small library that provides highly optimized BLAS routines on systems accelerated with GPUs. KBLAS is entirely written in CUDA C, and targets NVIDIA GPUs with compute capability 2.0 (Fermi) or higher. The current focus is on level-2 BLAS routines, namely the general matrix vector multiplication (GEMV) kernel, and the symmetric/hermitian matrix vector multiplication (SYMV/HEMV) kernel. KBLAS provides these two kernels in all four precisions (s, d, c, and z), with support to multi-GPU systems. Through advanced optimization techniques that target latency hiding and pushing memory bandwidth to the limit, KBLAS outperforms state-of-the-art kernels by 20-90% improvement. Competitors include CUBLAS-5.5, MAGMABLAS-1.4.0, and CULAR17. The SYMV/HEMV kernel from KBLAS has been adopted by NVIDIA, and should appear in CUBLAS-6.0. KBLAS has been used in large scale simulations of multi-object adaptive optics.

Large-scale production of Fischer-Tropsch diesel from biomass. Optimal gasification and gas cleaning systems

International Nuclear Information System (INIS)

Boerrigter, H.; Van der Drift, A.

2004-12-01

The paper is presented in the form of copies of overhead sheets. The contents concern definitions, an overview of Integrated biomass gasification and Fischer Tropsch (FT) systems (state-of-the-art, gas cleaning and biosyngas production, experimental demonstration and conclusions), some aspects of large-scale systems (motivation, biomass import) and an outlook

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.

High-Resiliency and Auto-Scaling of Large-Scale Cloud Computing for OCO-2 L2 Full Physics Processing

Science.gov (United States)

Hua, H.; Manipon, G.; Starch, M.; Dang, L. B.; Southam, P.; Wilson, B. D.; Avis, C.; Chang, A.; Cheng, C.; Smyth, M.; McDuffie, J. L.; Ramirez, P.

2015-12-01

Next generation science data systems are needed to address the incoming flood of data from new missions such as SWOT and NISAR where data volumes and data throughput rates are order of magnitude larger than present day missions. Additionally, traditional means of procuring hardware on-premise are already limited due to facilities capacity constraints for these new missions. Existing missions, such as OCO-2, may also require high turn-around time for processing different science scenarios where on-premise and even traditional HPC computing environments may not meet the high processing needs. We present our experiences on deploying a hybrid-cloud computing science data system (HySDS) for the OCO-2 Science Computing Facility to support large-scale processing of their Level-2 full physics data products. We will explore optimization approaches to getting best performance out of hybrid-cloud computing as well as common issues that will arise when dealing with large-scale computing. Novel approaches were utilized to do processing on Amazon's spot market, which can potentially offer ~10X costs savings but with an unpredictable computing environment based on market forces. We will present how we enabled high-tolerance computing in order to achieve large-scale computing as well as operational cost savings.

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.

Development of the Fragment Molecular Orbital Method for Calculating Nonlocal Excitations in Large Molecular Systems.

Science.gov (United States)

Fujita, Takatoshi; Mochizuki, Yuji

2018-04-19

We developed the fragment-based method for calculating nonlocal excitations in large molecular systems. This method is based on the multilayer fragment molecular orbital method and the configuration interaction single (CIS) wave function using localized molecular orbitals. The excited-state wave function for the whole system is described as a superposition of configuration state functions (CSFs) for intrafragment excitations and for interfragment charge-transfer excitations. The formulation and calculations of singlet excited-state Hamiltonian matrix elements in the fragment CSFs are presented in detail. The efficient approximation schemes for calculating the matrix elements are also presented. The computational efficiency and the accuracy were evaluated using the molecular dimers and molecular aggregates. We confirmed that absolute errors of 50 meV (relative to the conventional calculations) are achievable for the molecular systems in their equilibrium geometries. The perturbative electron correlation correction to the CIS excitation energies is also demonstrated. The present theory can compute a large number of excited states in large molecular systems; in addition, it allows for the systematic derivation of a model exciton Hamiltonian. These features are useful for studying excited-state dynamics in condensed molecular systems based on the ab initio electronic structure theory.

Time delay effects on large-scale MR damper based semi-active control strategies

International Nuclear Information System (INIS)

Cha, Y-J; Agrawal, A K; Dyke, S J

2013-01-01

This paper presents a detailed investigation on the robustness of large-scale 200 kN MR damper based semi-active control strategies in the presence of time delays in the control system. Although the effects of time delay on stability and performance degradation of an actively controlled system have been investigated extensively by many researchers, degradation in the performance of semi-active systems due to time delay has yet to be investigated. Since semi-active systems are inherently stable, instability problems due to time delay are unlikely to arise. This paper investigates the effects of time delay on the performance of a building with a large-scale MR damper, using numerical simulations of near- and far-field earthquakes. The MR damper is considered to be controlled by four different semi-active control algorithms, namely (i) clipped-optimal control (COC), (ii) decentralized output feedback polynomial control (DOFPC), (iii) Lyapunov control, and (iv) simple-passive control (SPC). It is observed that all controllers except for the COC are significantly robust with respect to time delay. On the other hand, the clipped-optimal controller should be integrated with a compensator to improve the performance in the presence of time delay. (paper)

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

Large-scale atomistic simulations of nanostructured materials based on divide-and-conquer density functional theory

Directory of Open Access Journals (Sweden)

Vashishta P.

2011-05-01

Full Text Available A linear-scaling algorithm based on a divide-and-conquer (DC scheme is designed to perform large-scale molecular-dynamics simulations, in which interatomic forces are computed quantum mechanically in the framework of the density functional theory (DFT. This scheme is applied to the thermite reaction at an Al/Fe2O3 interface. It is found that mass diffusion and reaction rate at the interface are enhanced by a concerted metal-oxygen flip mechanism. Preliminary simulations are carried out for an aluminum particle in water based on the conventional DFT, as a target system for large-scale DC-DFT simulations. A pair of Lewis acid and base sites on the aluminum surface preferentially catalyzes hydrogen production in a low activation-barrier mechanism found in the simulations

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

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

Science.gov (United States)

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

2012-02-01

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

Structure–performance characterization for carbon molecular sieve membranes using molecular scale gas probes

KAUST Repository

Rungta, Meha; Xu, Liren; Koros, William J.

2015-01-01

© 2015 Elsevier Ltd. All rights reserved. Understanding the relationship between carbon molecular sieve (CMS) pore structure and corresponding gas separation performance enables optimization for a given gas separation application. The final

Optimizing Distributed Machine Learning for Large Scale EEG Data Set

Directory of Open Access Journals (Sweden)

M Bilal Shaikh

2017-06-01

Full Text Available Distributed Machine Learning (DML has gained its importance more than ever in this era of Big Data. There are a lot of challenges to scale machine learning techniques on distributed platforms. When it comes to scalability, improving the processor technology for high level computation of data is at its limit, however increasing machine nodes and distributing data along with computation looks as a viable solution. Different frameworks   and platforms are available to solve DML problems. These platforms provide automated random data distribution of datasets which miss the power of user defined intelligent data partitioning based on domain knowledge. We have conducted an empirical study which uses an EEG Data Set collected through P300 Speller component of an ERP (Event Related Potential which is widely used in BCI problems; it helps in translating the intention of subject w h i l e performing any cognitive task. EEG data contains noise due to waves generated by other activities in the brain which contaminates true P300Speller. Use of Machine Learning techniques could help in detecting errors made by P300 Speller. We are solving this classification problem by partitioning data into different chunks and preparing distributed models using Elastic CV Classifier. To present a case of optimizing distributed machine learning, we propose an intelligent user defined data partitioning approach that could impact on the accuracy of distributed machine learners on average. Our results show better average AUC as compared to average AUC obtained after applying random data partitioning which gives no control to user over data partitioning. It improves the average accuracy of distributed learner due to the domain specific intelligent partitioning by the user. Our customized approach achieves 0.66 AUC on individual sessions and 0.75 AUC on mixed sessions, whereas random / uncontrolled data distribution records 0.63 AUC.

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.

PHIBSS: Unified Scaling Relations of Gas Depletion Time and Molecular Gas Fractions

Science.gov (United States)

Tacconi, L. J.; Genzel, R.; Saintonge, A.; Combes, F.; García-Burillo, S.; Neri, R.; Bolatto, A.; Contini, T.; Förster Schreiber, N. M.; Lilly, S.; Lutz, D.; Wuyts, S.; Accurso, G.; Boissier, J.; Boone, F.; Bouché, N.; Bournaud, F.; Burkert, A.; Carollo, M.; Cooper, M.; Cox, P.; Feruglio, C.; Freundlich, J.; Herrera-Camus, R.; Juneau, S.; Lippa, M.; Naab, T.; Renzini, A.; Salome, P.; Sternberg, A.; Tadaki, K.; Übler, H.; Walter, F.; Weiner, B.; Weiss, A.

2018-02-01

This paper provides an update of our previous scaling relations between galaxy-integrated molecular gas masses, stellar masses, and star formation rates (SFRs), in the framework of the star formation main sequence (MS), with the main goal of testing for possible systematic effects. For this purpose our new study combines three independent methods of determining molecular gas masses from CO line fluxes, far-infrared dust spectral energy distributions, and ∼1 mm dust photometry, in a large sample of 1444 star-forming galaxies between z = 0 and 4. The sample covers the stellar mass range log(M */M ⊙) = 9.0–11.8, and SFRs relative to that on the MS, δMS = SFR/SFR(MS), from 10‑1.3 to 102.2. Our most important finding is that all data sets, despite the different techniques and analysis methods used, follow the same scaling trends, once method-to-method zero-point offsets are minimized and uncertainties are properly taken into account. The molecular gas depletion time t depl, defined as the ratio of molecular gas mass to SFR, scales as (1 + z)‑0.6 × (δMS)‑0.44 and is only weakly dependent on stellar mass. The ratio of molecular to stellar mass μ gas depends on (1+z{)}2.5× {(δ {MS})}0.52× {({M}* )}-0.36, which tracks the evolution of the specific SFR. The redshift dependence of μ gas requires a curvature term, as may the mass dependences of t depl and μ gas. We find no or only weak correlations of t depl and μ gas with optical size R or surface density once one removes the above scalings, but we caution that optical sizes may not be appropriate for the high gas and dust columns at high z. Based on observations of an IRAM Legacy Program carried out with the NOEMA, operated by the Institute for Radio Astronomy in the Millimetre Range (IRAM), which is funded by a partnership of INSU/CNRS (France), MPG (Germany), and IGN (Spain).

Improved flexibility with large-scale variable renewable power in cities through optimal demand side management and power-to-heat conversion

International Nuclear Information System (INIS)

Salpakari, Jyri; Mikkola, Jani; Lund, Peter D.

2016-01-01

Highlights: • New models for optimal control of shiftable loads and power-to-heat conversion. • Full technical and economic potential with optimal controls. • Detailed time series of shiftable loads based on empirical data. • Case study of Helsinki (Finland) with over 90% share of district heating. • Positive net present values in cost-optimal operation. - Abstract: Solar and wind power are potential carbon-free energy solutions for urban areas, but they are also subject to large variability. At the same time, urban areas offer promising flexibility solutions for balancing variable renewable power. This paper presents models for optimal control of power-to-heat conversion to heating systems and shiftable loads in cities to incorporate large variable renewable power schemes. The power-to-heat systems comprise heat pumps, electric boilers, and thermal storage. The control strategies comprise optimal matching of load and production, and cost-optimal market participation with investment analysis. All analyses are based on hourly data. The models are applied to a case study in Helsinki, Finland. For a scheme providing ca. 50% of all electricity in the city through self-consumption of variable renewables, power-to-heat with thermal storage could absorb all the surplus production. A significant reduction in the net load magnitude was obtained with shiftable loads. Investments to both power-to-heat and load shifting with electric heating and commercial refrigeration have a positive net present value if the resources are controlled cost-optimally.

Large-scale enzymatic production of natural flavour esters in organic solvent with continuous water removal.

Science.gov (United States)

Gubicza, L; Kabiri-Badr, A; Keoves, E; Belafi-Bako, K

2001-11-30

A new, large-scale process was developed for the enzymatic production of low molecular weight flavour esters in organic solvent. Solutions for the elimination of substrate and product inhibitions are presented. The excess water produced during the process was continuously removed by hetero-azeotropic distillation and esters were produced at yields of over 90%.

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)

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.

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.

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.

Max-Min SINR in Large-Scale Single-Cell MU-MIMO: Asymptotic Analysis and Low Complexity Transceivers

KAUST Repository

Sifaou, Houssem

2016-12-28

This work focuses on the downlink and uplink of large-scale single-cell MU-MIMO systems in which the base station (BS) endowed with M antennas communicates with K single-antenna user equipments (UEs). Particularly, we aim at reducing the complexity of the linear precoder and receiver that maximize the minimum signal-to-interference-plus-noise ratio subject to a given power constraint. To this end, we consider the asymptotic regime in which M and K grow large with a given ratio. Tools from random matrix theory (RMT) are then used to compute, in closed form, accurate approximations for the parameters of the optimal precoder and receiver, when imperfect channel state information (modeled by the generic Gauss-Markov formulation form) is available at the BS. The asymptotic analysis allows us to derive the asymptotically optimal linear precoder and receiver that are characterized by a lower complexity (due to the dependence on the large scale components of the channel) and, possibly, by a better resilience to imperfect channel state information. However, the implementation of both is still challenging as it requires fast inversions of large matrices in every coherence period. To overcome this issue, we apply the truncated polynomial expansion (TPE) technique to the precoding and receiving vector of each UE and make use of RMT to determine the optimal weighting coefficients on a per- UE basis that asymptotically solve the max-min SINR problem. Numerical results are used to validate the asymptotic analysis in the finite system regime and to show that the proposed TPE transceivers efficiently mimic the optimal ones, while requiring much lower computational complexity.

Optimal design of robust piezoelectric microgrippers undergoing large displacements

DEFF Research Database (Denmark)

Ruiz, D.; Sigmund, Ole

2018-01-01

Topology optimization combined with optimal design of electrodes is used to design piezoelectric microgrippers. Fabrication at micro-scale presents an important challenge: due to non-symmetrical lamination of the structures, out-of-plane bending spoils the behaviour of the grippers. Suppression...

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...

SYNTHESIS AND CHARACTERIZATION OF NEW STABILIZERS WITH OPTIMAL MOLECULAR WEIGHT

Institute of Scientific and Technical Information of China (English)

Jiang-qing Pan

2001-01-01

Over 2 × l08 tons of polymers are produced every year, and a large portion of polymers faces the degradation problem. There are many effective methods to protect polymers against degradation and the addition of stabilizers to polymer remains the most convenient and effective way of enhancing polymer life and performance. In this article, a series of effective stabilizers with optimal molecular weight (MW), including common, monomeric and polymeric stabilizers (antioxidant and light stabilizer) were synthesized using isocyanation, controlled isocyanation, hydrosilylation, epoxide addition, macroreaction of stabilizing functional compounds and polymerization of monomeric stabilizers. The sructure and performance of these new stabilizers were characterized by using IR, NMR, MS, UV-spectra, XPS and elemental analysis. The current development of stabilizer synthesis was also reviewed.``

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.

Robust Optimal Adaptive Control Method with Large Adaptive Gain

Science.gov (United States)

Nguyen, Nhan T.

2009-01-01

In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

Connecting the molecular scale to the continuum scale for diffusion processes in smectite-rich porous media.

Science.gov (United States)

Bourg, Ian C; Sposito, Garrison

2010-03-15

In this paper, we address the manner in which the continuum-scale diffusive properties of smectite-rich porous media arise from their molecular- and pore-scale features. Our starting point is a successful model of the continuum-scale apparent diffusion coefficient for water tracers and cations, which decomposes it as a sum of pore-scale terms describing diffusion in macropore and interlayer "compartments." We then apply molecular dynamics (MD) simulations to determine molecular-scale diffusion coefficients D(interlayer) of water tracers and representative cations (Na(+), Cs(+), Sr(2+)) in Na-smectite interlayers. We find that a remarkably simple expression relates D(interlayer) to the pore-scale parameter δ(nanopore) ≤ 1, a constrictivity factor that accounts for the lower mobility in interlayers as compared to macropores: δ(nanopore) = D(interlayer)/D(0), where D(0) is the diffusion coefficient in bulk liquid water. Using this scaling expression, we can accurately predict the apparent diffusion coefficients of tracers H(2)0, Na(+), Sr(2+), and Cs(+) in compacted Na-smectite-rich materials.

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...

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 ...

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.)

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

Optimized method for manufacturing large aspheric surfaces

Science.gov (United States)

Zhou, Xusheng; Li, Shengyi; Dai, Yifan; Xie, Xuhui

2007-12-01

Aspheric optics are being used more and more widely in modern optical systems, due to their ability of correcting aberrations, enhancing image quality, enlarging the field of view and extending the range of effect, while reducing the weight and volume of the system. With optical technology development, we have more pressing requirement to large-aperture and high-precision aspheric surfaces. The original computer controlled optical surfacing (CCOS) technique cannot meet the challenge of precision and machining efficiency. This problem has been thought highly of by researchers. Aiming at the problem of original polishing process, an optimized method for manufacturing large aspheric surfaces is put forward. Subsurface damage (SSD), full aperture errors and full band of frequency errors are all in control of this method. Lesser SSD depth can be gained by using little hardness tool and small abrasive grains in grinding process. For full aperture errors control, edge effects can be controlled by using smaller tools and amendment model with material removal function. For full band of frequency errors control, low frequency errors can be corrected with the optimized material removal function, while medium-high frequency errors by using uniform removing principle. With this optimized method, the accuracy of a K9 glass paraboloid mirror can reach rms 0.055 waves (where a wave is 0.6328μm) in a short time. The results show that the optimized method can guide large aspheric surface manufacturing effectively.

NaviCell: a web-based environment for navigation, curation and maintenance of large molecular interaction maps.

Science.gov (United States)

Kuperstein, Inna; Cohen, David P A; Pook, Stuart; Viara, Eric; Calzone, Laurence; Barillot, Emmanuel; Zinovyev, Andrei

2013-10-07

Molecular biology knowledge can be formalized and systematically represented in a computer-readable form as a comprehensive map of molecular interactions. There exist an increasing number of maps of molecular interactions containing detailed and step-wise description of various cell mechanisms. It is difficult to explore these large maps, to organize discussion of their content and to maintain them. Several efforts were recently made to combine these capabilities together in one environment, and NaviCell is one of them. NaviCell is a web-based environment for exploiting large maps of molecular interactions, created in CellDesigner, allowing their easy exploration, curation and maintenance. It is characterized by a combination of three essential features: (1) efficient map browsing based on Google Maps; (2) semantic zooming for viewing different levels of details or of abstraction of the map and (3) integrated web-based blog for collecting community feedback. NaviCell can be easily used by experts in the field of molecular biology for studying molecular entities of interest in the context of signaling pathways and crosstalk between pathways within a global signaling network. NaviCell allows both exploration of detailed molecular mechanisms represented on the map and a more abstract view of the map up to a top-level modular representation. NaviCell greatly facilitates curation, maintenance and updating the comprehensive maps of molecular interactions in an interactive and user-friendly fashion due to an imbedded blogging system. NaviCell provides user-friendly exploration of large-scale maps of molecular interactions, thanks to Google Maps and WordPress interfaces, with which many users are already familiar. Semantic zooming which is used for navigating geographical maps is adopted for molecular maps in NaviCell, making any level of visualization readable. In addition, NaviCell provides a framework for community-based curation of maps.

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.

High performance nanostructured Silicon heterojunction for water splitting on large scales

KAUST Repository

Bonifazi, Marcella

2017-11-02

In past years the global demand for energy has been increasing steeply, as well as the awareness that new sources of clean energy are essential. Photo-electrochemical devices (PEC) for water splitting applications have stirred great interest, and different approach has been explored to improve the efficiency of these devices and to avoid optical losses at the interfaces with water. These include engineering materials and nanostructuring the device\\'s surfaces [1]-[2]. Despite the promising initial results, there are still many drawbacks that needs to be overcome to reach large scale production with optimized performances [3]. We present a new device that relies on the optimization of the nanostructuring process that exploits suitably disordered surfaces. Additionally, this device could harvest light on both sides to efficiently gain and store the energy to keep the photocatalytic reaction active.

High performance nanostructured Silicon heterojunction for water splitting on large scales

KAUST Repository

Bonifazi, Marcella; Fu, Hui-chun; He, Jr-Hau; Fratalocchi, Andrea

2017-01-01

In past years the global demand for energy has been increasing steeply, as well as the awareness that new sources of clean energy are essential. Photo-electrochemical devices (PEC) for water splitting applications have stirred great interest, and different approach has been explored to improve the efficiency of these devices and to avoid optical losses at the interfaces with water. These include engineering materials and nanostructuring the device's surfaces [1]-[2]. Despite the promising initial results, there are still many drawbacks that needs to be overcome to reach large scale production with optimized performances [3]. We present a new device that relies on the optimization of the nanostructuring process that exploits suitably disordered surfaces. Additionally, this device could harvest light on both sides to efficiently gain and store the energy to keep the photocatalytic reaction active.

Research on Optimal Observation Scale for Damaged Buildings after Earthquake Based on Optimal Feature Space

Science.gov (United States)

Chen, J.; Chen, W.; Dou, A.; Li, W.; Sun, Y.

2018-04-01

A new information extraction method of damaged buildings rooted in optimal feature space is put forward on the basis of the traditional object-oriented method. In this new method, ESP (estimate of scale parameter) tool is used to optimize the segmentation of image. Then the distance matrix and minimum separation distance of all kinds of surface features are calculated through sample selection to find the optimal feature space, which is finally applied to extract the image of damaged buildings after earthquake. The overall extraction accuracy reaches 83.1 %, the kappa coefficient 0.813. The new information extraction method greatly improves the extraction accuracy and efficiency, compared with the traditional object-oriented method, and owns a good promotional value in the information extraction of damaged buildings. In addition, the new method can be used for the information extraction of different-resolution images of damaged buildings after earthquake, then to seek the optimal observation scale of damaged buildings through accuracy evaluation. It is supposed that the optimal observation scale of damaged buildings is between 1 m and 1.2 m, which provides a reference for future information extraction of damaged buildings.

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

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

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)

Workflow management in large distributed systems

International Nuclear Information System (INIS)

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

2011-01-01

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

Workflow management in large distributed systems

Science.gov (United States)

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

2011-12-01

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

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.

New scale-down methodology from commercial to lab scale to optimize plant-derived soft gel capsule formulations on a commercial scale.

Science.gov (United States)

Oishi, Sana; Kimura, Shin-Ichiro; Noguchi, Shuji; Kondo, Mio; Kondo, Yosuke; Shimokawa, Yoshiyuki; Iwao, Yasunori; Itai, Shigeru

2018-01-15

A new scale-down methodology from commercial rotary die scale to laboratory scale was developed to optimize a plant-derived soft gel capsule formulation and eventually manufacture superior soft gel capsules on a commercial scale, in order to reduce the time and cost for formulation development. Animal-derived and plant-derived soft gel film sheets were prepared using an applicator on a laboratory scale and their physicochemical properties, such as tensile strength, Young's modulus, and adhesive strength, were evaluated. The tensile strength of the animal-derived and plant-derived soft gel film sheets was 11.7 MPa and 4.41 MPa, respectively. The Young's modulus of the animal-derived and plant-derived soft gel film sheets was 169 MPa and 17.8 MPa, respectively, and both sheets showed a similar adhesion strength of approximately 4.5-10 MPa. Using a D-optimal mixture design, plant-derived soft gel film sheets were prepared and optimized by varying their composition, including variations in the mass of κ-carrageenan, ι-carrageenan, oxidized starch and heat-treated starch. The physicochemical properties of the sheets were evaluated to determine the optimal formulation. Finally, plant-derived soft gel capsules were manufactured using the rotary die method and the prepared soft gel capsules showed equivalent or superior physical properties compared with pre-existing soft gel capsules. Therefore, we successfully developed a new scale-down methodology to optimize the formulation of plant-derived soft gel capsules on a commercial scale. Copyright © 2017 Elsevier B.V. All rights reserved.

A 3D Sphere Culture System Containing Functional Polymers for Large-Scale Human Pluripotent Stem Cell Production

Directory of Open Access Journals (Sweden)

Tomomi G. Otsuji

2014-05-01

Full Text Available Utilizing human pluripotent stem cells (hPSCs in cell-based therapy and drug discovery requires large-scale cell production. However, scaling up conventional adherent cultures presents challenges of maintaining a uniform high quality at low cost. In this regard, suspension cultures are a viable alternative, because they are scalable and do not require adhesion surfaces. 3D culture systems such as bioreactors can be exploited for large-scale production. However, the limitations of current suspension culture methods include spontaneous fusion between cell aggregates and suboptimal passaging methods by dissociation and reaggregation. 3D culture systems that dynamically stir carrier beads or cell aggregates should be refined to reduce shearing forces that damage hPSCs. Here, we report a simple 3D sphere culture system that incorporates mechanical passaging and functional polymers. This setup resolves major problems associated with suspension culture methods and dynamic stirring systems and may be optimal for applications involving large-scale hPSC production.

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.

Optimization of a Fluorescence-Based Assay for Large-Scale Drug Screening against Babesia and Theileria Parasites.

Science.gov (United States)

Rizk, Mohamed Abdo; El-Sayed, Shimaa Abd El-Salam; Terkawi, Mohamed Alaa; Youssef, Mohamed Ahmed; El Said, El Said El Shirbini; Elsayed, Gehad; El-Khodery, Sabry; El-Ashker, Maged; Elsify, Ahmed; Omar, Mosaab; Salama, Akram; Yokoyama, Naoaki; Igarashi, Ikuo

2015-01-01

A rapid and accurate assay for evaluating antibabesial drugs on a large scale is required for the discovery of novel chemotherapeutic agents against Babesia parasites. In the current study, we evaluated the usefulness of a fluorescence-based assay for determining the efficacies of antibabesial compounds against bovine and equine hemoparasites in in vitro cultures. Three different hematocrits (HCTs; 2.5%, 5%, and 10%) were used without daily replacement of the medium. The results of a high-throughput screening assay revealed that the best HCT was 2.5% for bovine Babesia parasites and 5% for equine Babesia and Theileria parasites. The IC50 values of diminazene aceturate obtained by fluorescence and microscopy did not differ significantly. Likewise, the IC50 values of luteolin, pyronaridine tetraphosphate, nimbolide, gedunin, and enoxacin did not differ between the two methods. In conclusion, our fluorescence-based assay uses low HCT and does not require daily replacement of culture medium, making it highly suitable for in vitro large-scale drug screening against Babesia and Theileria parasites that infect cattle and horses.

Optimization of a Fluorescence-Based Assay for Large-Scale Drug Screening against Babesia and Theileria Parasites.

Directory of Open Access Journals (Sweden)

Mohamed Abdo Rizk

Full Text Available A rapid and accurate assay for evaluating antibabesial drugs on a large scale is required for the discovery of novel chemotherapeutic agents against Babesia parasites. In the current study, we evaluated the usefulness of a fluorescence-based assay for determining the efficacies of antibabesial compounds against bovine and equine hemoparasites in in vitro cultures. Three different hematocrits (HCTs; 2.5%, 5%, and 10% were used without daily replacement of the medium. The results of a high-throughput screening assay revealed that the best HCT was 2.5% for bovine Babesia parasites and 5% for equine Babesia and Theileria parasites. The IC50 values of diminazene aceturate obtained by fluorescence and microscopy did not differ significantly. Likewise, the IC50 values of luteolin, pyronaridine tetraphosphate, nimbolide, gedunin, and enoxacin did not differ between the two methods. In conclusion, our fluorescence-based assay uses low HCT and does not require daily replacement of culture medium, making it highly suitable for in vitro large-scale drug screening against Babesia and Theileria parasites that infect cattle and horses.

Molecular scale modeling of polymer imprint nanolithography.

Science.gov (United States)

Chandross, Michael; Grest, Gary S

2012-01-10

We present the results of large-scale molecular dynamics simulations of two different nanolithographic processes, step-flash imprint lithography (SFIL), and hot embossing. We insert rigid stamps into an entangled bead-spring polymer melt above the glass transition temperature. After equilibration, the polymer is then hardened in one of two ways, depending on the specific process to be modeled. For SFIL, we cross-link the polymer chains by introducing bonds between neighboring beads. To model hot embossing, we instead cool the melt to below the glass transition temperature. We then study the ability of these methods to retain features by removing the stamps, both with a zero-stress removal process in which stamp atoms are instantaneously deleted from the system as well as a more physical process in which the stamp is pulled from the hardened polymer at fixed velocity. We find that it is necessary to coat the stamp with an antifriction coating to achieve clean removal of the stamp. We further find that a high density of cross-links is necessary for good feature retention in the SFIL process. The hot embossing process results in good feature retention at all length scales studied as long as coated, low surface energy stamps are used.

Stochastically Estimating Modular Criticality in Large-Scale Logic Circuits Using Sparsity Regularization and Compressive Sensing

Directory of Open Access Journals (Sweden)

Mohammed Alawad

2015-03-01

Full Text Available This paper considers the problem of how to efficiently measure a large and complex information field with optimally few observations. Specifically, we investigate how to stochastically estimate modular criticality values in a large-scale digital circuit with a very limited number of measurements in order to minimize the total measurement efforts and time. We prove that, through sparsity-promoting transform domain regularization and by strategically integrating compressive sensing with Bayesian learning, more than 98% of the overall measurement accuracy can be achieved with fewer than 10% of measurements as required in a conventional approach that uses exhaustive measurements. Furthermore, we illustrate that the obtained criticality results can be utilized to selectively fortify large-scale digital circuits for operation with narrow voltage headrooms and in the presence of soft-errors rising at near threshold voltage levels, without excessive hardware overheads. Our numerical simulation results have shown that, by optimally allocating only 10% circuit redundancy, for some large-scale benchmark circuits, we can achieve more than a three-times reduction in its overall error probability, whereas if randomly distributing such 10% hardware resource, less than 2% improvements in the target circuit’s overall robustness will be observed. Finally, we conjecture that our proposed approach can be readily applied to estimate other essential properties of digital circuits that are critical to designing and analyzing them, such as the observability measure in reliability analysis and the path delay estimation in stochastic timing analysis. The only key requirement of our proposed methodology is that these global information fields exhibit a certain degree of smoothness, which is universally true for almost any physical phenomenon.

Insights into the Molecular Pathogenesis of Activated B-Cell-like Diffuse Large B-Cell Lymphoma and Its Therapeutic Implications

Directory of Open Access Journals (Sweden)

Georg Lenz

2015-05-01

Full Text Available Within the last couple of years, the understanding of the molecular mechanisms that drive the pathogenesis of diffuse large B-cell lymphoma (DLBCL has significantly improved. Large-scale gene expression profiling studies have led to the discovery of several molecularly defined subtypes that are characterized by specific oncogene addictions and significant differences in their outcome. Next generation sequencing efforts combined with RNA interference screens frequently identify crucial oncogenes that lead to constitutive activation of various signaling pathways that drive lymphomagenesis. This review summarizes our current understanding of the molecular pathogenesis of the activated B-cell-like (ABC DLBCL subtype that is characterized by poor prognosis. A special emphasis is put on findings that might impact therapeutic strategies of affected patients.

Insights into the Molecular Pathogenesis of Activated B-Cell-like Diffuse Large B-Cell Lymphoma and Its Therapeutic Implications

Energy Technology Data Exchange (ETDEWEB)

Lenz, Georg [Translational Oncology, Department of Medicine A, Albert-Schweitzer Campus 1, University Hospital Münster, 48149 Münster (Germany); Cluster of Excellence EXC 1003, Cells in Motion, 48149 Münster (Germany)

2015-05-22

Within the last couple of years, the understanding of the molecular mechanisms that drive the pathogenesis of diffuse large B-cell lymphoma (DLBCL) has significantly improved. Large-scale gene expression profiling studies have led to the discovery of several molecularly defined subtypes that are characterized by specific oncogene addictions and significant differences in their outcome. Next generation sequencing efforts combined with RNA interference screens frequently identify crucial oncogenes that lead to constitutive activation of various signaling pathways that drive lymphomagenesis. This review summarizes our current understanding of the molecular pathogenesis of the activated B-cell-like (ABC) DLBCL subtype that is characterized by poor prognosis. A special emphasis is put on findings that might impact therapeutic strategies of affected patients.

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)

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 massively parallel algorithm for the solution of constrained equations of motion with applications to large-scale, long-time molecular dynamics simulations

Energy Technology Data Exchange (ETDEWEB)

Fijany, A. [Jet Propulsion Lab., Pasadena, CA (United States); Coley, T.R. [Virtual Chemistry, Inc., San Diego, CA (United States); Cagin, T.; Goddard, W.A. III [California Institute of Technology, Pasadena, CA (United States)

1997-12-31

Successful molecular dynamics (MD) simulation of large systems (> million atoms) for long times (> nanoseconds) requires the integration of constrained equations of motion (CEOM). Constraints are used to eliminate high frequency degrees of freedom (DOF) and to allow the use of rigid bodies. Solving the CEOM allows for larger integration time-steps and helps focus the simulation on the important collective dynamics of chemical, biological, and materials systems. We explore advances in multibody dynamics which have resulted in O(N) algorithms for propagating the CEOM. However, because of their strictly sequential nature, the computational time required by these algorithms does not scale down with increased numbers of processors. We then present the new constraint force algorithm for solving the CEOM and show that this algorithm is fully parallelizable, leading to a computational cost of O(N/P+IogP) for N DOF on P processors.

Media optimization for elevated molecular weight and mass production of pigment-free pullulan.

Science.gov (United States)

Yu, Xiaoliu; Wang, Yulei; Wei, Gongyuan; Dong, Yingying

2012-07-01

In this study, an Aureobasidium pullulans SZU 1001 mutant, deficient in pigment production, was screened by complex UV and γ-ray mutagenesis. Medium composition optimization for increased pullulan molecular weight and production was conducted using this mutant. Six nutrients: yeast extract, (NH4)2SO4, K2HPO4, NaCl, MgSO4·7H2O and CaCl2 were detected within pullulan production in flasks. It is shown that NaCl and K2HPO4 have significant influences on molecular weight of pullulan, while yeast extract and (NH4)2SO4 significantly affect pullulan yield. To achieve a higher molecular weight and more efficient pullulan production, a response surface methodology approach was introduced to predict an optimal nutrient combination. A molecular weight of 5.74 × 10(6) and pullulan yield on glucose of 51.30% were obtained under batch pullulan fermentation with the optimized media, which increased molecular weight and pullulan production by 97.25% and 11.04%, respectively compared with the control media. Copyright © 2012 Elsevier Ltd. All rights reserved.

Nanoscale heterostructures with molecular-scale single-crystal metal wires.

Science.gov (United States)

Kundu, Paromita; Halder, Aditi; Viswanath, B; Kundu, Dipan; Ramanath, Ganpati; Ravishankar, N

2010-01-13

Creating nanoscale heterostructures with molecular-scale (synthesis of nanoscale heterostructures with single-crystal molecular-scale Au nanowires attached to different nanostructure substrates. Our method involves the formation of Au nanoparticle seeds by the reduction of rocksalt AuCl nanocubes heterogeneously nucleated on the substrates and subsequent nanowire growth by oriented attachment of Au nanoparticles from the solution phase. Nanoscale heterostructures fabricated by such site-specific nucleation and growth are attractive for many applications including nanoelectronic device wiring, catalysis, and sensing.

[SIAM conference on optimization

Energy Technology Data Exchange (ETDEWEB)

1992-05-10

Abstracts are presented of 63 papers on the following topics: large-scale optimization, interior-point methods, algorithms for optimization, problems in control, network optimization methods, and parallel algorithms for optimization problems.

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

Science.gov (United States)

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

2017-10-01

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

A large-scale, higher-level, molecular phylogenetic study of the insect order Lepidoptera (moths and butterflies.

Directory of Open Access Journals (Sweden)

Jerome C Regier

Full Text Available Higher-level relationships within the Lepidoptera, and particularly within the species-rich subclade Ditrysia, are generally not well understood, although recent studies have yielded progress. We present the most comprehensive molecular analysis of lepidopteran phylogeny to date, focusing on relationships among superfamilies.483 taxa spanning 115 of 124 families were sampled for 19 protein-coding nuclear genes, from which maximum likelihood tree estimates and bootstrap percentages were obtained using GARLI. Assessment of heuristic search effectiveness showed that better trees and higher bootstrap percentages probably remain to be discovered even after 1000 or more search replicates, but further search proved impractical even with grid computing. Other analyses explored the effects of sampling nonsynonymous change only versus partitioned and unpartitioned total nucleotide change; deletion of rogue taxa; and compositional heterogeneity. Relationships among the non-ditrysian lineages previously inferred from morphology were largely confirmed, plus some new ones, with strong support. Robust support was also found for divergences among non-apoditrysian lineages of Ditrysia, but only rarely so within Apoditrysia. Paraphyly for Tineoidea is strongly supported by analysis of nonsynonymous-only signal; conflicting, strong support for tineoid monophyly when synonymous signal was added back is shown to result from compositional heterogeneity.Support for among-superfamily relationships outside the Apoditrysia is now generally strong. Comparable support is mostly lacking within Apoditrysia, but dramatically increased bootstrap percentages for some nodes after rogue taxon removal, and concordance with other evidence, strongly suggest that our picture of apoditrysian phylogeny is approximately correct. This study highlights the challenge of finding optimal topologies when analyzing hundreds of taxa. It also shows that some nodes get strong support only when

A large-scale molecular dynamics study of the divacancy defect in graphene

International Nuclear Information System (INIS)

Leyssale, Jean-Marc; Vignoles, Gerard L.

2014-01-01

We report on the dynamical behavior of single divacancy defects in large graphene sheets as studied by extensive classical molecular dynamics (MD) simulations at high temperatures and static calculations. In the first part of the paper, the ability of the used interatomic potential to properly render the stability and dynamics (energy barriers) of such defects is validated against electronic structure calculations from the literature. Then, results from MD simulations are presented. In agreement with recent TEM studies, some mobility is observed through a series of Stone-Wales-like bond rotations involving the 5-8-5, 555-777, and 5555-6-7777 reconstructions. Although these three structures are by far the most probable structures of the DV defect, not less than 18 other full reconstructions, including the experimentally observed 55-66-77 defect, were occasionally observed in the ∼1.5 μs of MD trajectories analyzed in this work. Most of these additional reconstructions have moderate formation energies and can be formed by a bond rotation mechanism from one of the aforementioned structures, with a lower activation energy than the one required to form a Stone-Wales defect in graphene. Therefore their future experimental observation is highly probable. The results presented here also suggest that the barrier to a conventional Stone-Wales transformation (the formation of two pentagon/heptagon pairs from four hexagons) can be significantly reduced in the vicinity of an existing defect, strengthening a recently proposed melting mechanism for graphene based on the aggregation of Stone-Wales defects. From a structural point of view, in addition to pentagons, heptagons, and octagons, these new DV reconstructions can also contain four- and nine-member rings and show a particularly large spatial extent of up to 13 rings (42 atoms) against three (14 atoms) for the original 5-8-5 defect. (authors)

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.

Quantitative Determination of Organic Semiconductor Microstructure from the Molecular to Device Scale

KAUST Repository

Rivnay, Jonathan; Mannsfeld, Stefan C. B.; Miller, Chad E.; Salleo, Alberto; Toney, Michael F.

2012-01-01

A study was conducted to demonstrate quantitative determination of organic semiconductor microstructure from the molecular to device scale. The quantitative determination of organic semiconductor microstructure from the molecular to device scale

A method to generate fully multi-scale optimal interpolation by combining efficient single process analyses, illustrated by a DINEOF analysis spiced with a local optimal interpolation

Directory of Open Access Journals (Sweden)

J.-M. Beckers

2014-10-01

Full Text Available We present a method in which the optimal interpolation of multi-scale processes can be expanded into a succession of simpler interpolations. First, we prove how the optimal analysis of a superposition of two processes can be obtained by different mathematical formulations involving iterations and analysis focusing on a single process. From the different mathematical equivalent formulations, we then select the most efficient ones by analyzing the behavior of the different possibilities in a simple and well-controlled test case. The clear guidelines deduced from this experiment are then applied to a real situation in which we combine large-scale analysis of hourly Spinning Enhanced Visible and Infrared Imager (SEVIRI satellite images using data interpolating empirical orthogonal functions (DINEOF with a local optimal interpolation using a Gaussian covariance. It is shown that the optimal combination indeed provides the best reconstruction and can therefore be exploited to extract the maximum amount of useful information from the original data.

Particle swarm optimization with scale-free interactions.

Directory of Open Access Journals (Sweden)

Chen Liu

Full Text Available The particle swarm optimization (PSO algorithm, in which individuals collaborate with their interacted neighbors like bird flocking to search for the optima, has been successfully applied in a wide range of fields pertaining to searching and convergence. Here we employ the scale-free network to represent the inter-individual interactions in the population, named SF-PSO. In contrast to the traditional PSO with fully-connected topology or regular topology, the scale-free topology used in SF-PSO incorporates the diversity of individuals in searching and information dissemination ability, leading to a quite different optimization process. Systematic results with respect to several standard test functions demonstrate that SF-PSO gives rise to a better balance between the convergence speed and the optimum quality, accounting for its much better performance than that of the traditional PSO algorithms. We further explore the dynamical searching process microscopically, finding that the cooperation of hub nodes and non-hub nodes play a crucial role in optimizing the convergence process. Our work may have implications in computational intelligence and complex networks.

Multi-Scale Modelling of Deformation and Fracture in a Biomimetic Apatite-Protein Composite: Molecular-Scale Processes Lead to Resilience at the μm-Scale.

Directory of Open Access Journals (Sweden)

Dirk Zahn

Full Text Available Fracture mechanisms of an enamel-like hydroxyapatite-collagen composite model are elaborated by means of molecular and coarse-grained dynamics simulation. Using fully atomistic models, we uncover molecular-scale plastic deformation and fracture processes initiated at the organic-inorganic interface. Furthermore, coarse-grained models are developed to investigate fracture patterns at the μm-scale. At the meso-scale, micro-fractures are shown to reduce local stress and thus prevent material failure after loading beyond the elastic limit. On the basis of our multi-scale simulation approach, we provide a molecular scale rationalization of this phenomenon, which seems key to the resilience of hierarchical biominerals, including teeth and bone.

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

Progresses in application of computational ?uid dynamic methods to large scale wind turbine aerodynamics?

Institute of Scientific and Technical Information of China (English)

Zhenyu ZHANG; Ning ZHAO; Wei ZHONG; Long WANG; Bofeng XU

2016-01-01

The computational ?uid dynamics (CFD) methods are applied to aerody-namic problems for large scale wind turbines. The progresses including the aerodynamic analyses of wind turbine pro?les, numerical ?ow simulation of wind turbine blades, evalu-ation of aerodynamic performance, and multi-objective blade optimization are discussed. Based on the CFD methods, signi?cant improvements are obtained to predict two/three-dimensional aerodynamic characteristics of wind turbine airfoils and blades, and the vorti-cal structure in their wake ?ows is accurately captured. Combining with a multi-objective genetic algorithm, a 1.5 MW NH-1500 optimized blade is designed with high e?ciency in wind energy conversion.

Optimization of MIMO Systems Capacity Using Large Random Matrix Methods

Directory of Open Access Journals (Sweden)

Philippe Loubaton

2012-11-01

Full Text Available This paper provides a comprehensive introduction of large random matrix methods for input covariance matrix optimization of mutual information of MIMO systems. It is first recalled informally how large system approximations of mutual information can be derived. Then, the optimization of the approximations is discussed, and important methodological points that are not necessarily covered by the existing literature are addressed, including the strict concavity of the approximation, the structure of the argument of its maximum, the accuracy of the large system approach with regard to the number of antennas, or the justification of iterative water-filling optimization algorithms. While the existing papers have developed methods adapted to a specific model, this contribution tries to provide a unified view of the large system approximation approach.

Discrete-time optimal control and games on large intervals

CERN Document Server

Zaslavski, Alexander J

2017-01-01

Devoted to the structure of approximate solutions of discrete-time optimal control problems and approximate solutions of dynamic discrete-time two-player zero-sum games, this book presents results on properties of approximate solutions in an interval that is independent lengthwise, for all sufficiently large intervals. Results concerning the so-called turnpike property of optimal control problems and zero-sum games in the regions close to the endpoints of the time intervals are the main focus of this book. The description of the structure of approximate solutions on sufficiently large intervals and its stability will interest graduate students and mathematicians in optimal control and game theory, engineering, and economics. This book begins with a brief overview and moves on to analyze the structure of approximate solutions of autonomous nonconcave discrete-time optimal control Lagrange problems.Next the structures of approximate solutions of autonomous discrete-time optimal control problems that are discret...

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

Identifying gene-environment interactions in schizophrenia: contemporary challenges for integrated, large-scale investigations.

Science.gov (United States)

van Os, Jim; Rutten, Bart P; Myin-Germeys, Inez; Delespaul, Philippe; Viechtbauer, Wolfgang; van Zelst, Catherine; Bruggeman, Richard; Reininghaus, Ulrich; Morgan, Craig; Murray, Robin M; Di Forti, Marta; McGuire, Philip; Valmaggia, Lucia R; Kempton, Matthew J; Gayer-Anderson, Charlotte; Hubbard, Kathryn; Beards, Stephanie; Stilo, Simona A; Onyejiaka, Adanna; Bourque, Francois; Modinos, Gemma; Tognin, Stefania; Calem, Maria; O'Donovan, Michael C; Owen, Michael J; Holmans, Peter; Williams, Nigel; Craddock, Nicholas; Richards, Alexander; Humphreys, Isla; Meyer-Lindenberg, Andreas; Leweke, F Markus; Tost, Heike; Akdeniz, Ceren; Rohleder, Cathrin; Bumb, J Malte; Schwarz, Emanuel; Alptekin, Köksal; Üçok, Alp; Saka, Meram Can; Atbaşoğlu, E Cem; Gülöksüz, Sinan; Gumus-Akay, Guvem; Cihan, Burçin; Karadağ, Hasan; Soygür, Haldan; Cankurtaran, Eylem Şahin; Ulusoy, Semra; Akdede, Berna; Binbay, Tolga; Ayer, Ahmet; Noyan, Handan; Karadayı, Gülşah; Akturan, Elçin; Ulaş, Halis; Arango, Celso; Parellada, Mara; Bernardo, Miguel; Sanjuán, Julio; Bobes, Julio; Arrojo, Manuel; Santos, Jose Luis; Cuadrado, Pedro; Rodríguez Solano, José Juan; Carracedo, Angel; García Bernardo, Enrique; Roldán, Laura; López, Gonzalo; Cabrera, Bibiana; Cruz, Sabrina; Díaz Mesa, Eva Ma; Pouso, María; Jiménez, Estela; Sánchez, Teresa; Rapado, Marta; González, Emiliano; Martínez, Covadonga; Sánchez, Emilio; Olmeda, Ma Soledad; de Haan, Lieuwe; Velthorst, Eva; van der Gaag, Mark; Selten, Jean-Paul; van Dam, Daniella; van der Ven, Elsje; van der Meer, Floor; Messchaert, Elles; Kraan, Tamar; Burger, Nadine; Leboyer, Marion; Szoke, Andrei; Schürhoff, Franck; Llorca, Pierre-Michel; Jamain, Stéphane; Tortelli, Andrea; Frijda, Flora; Vilain, Jeanne; Galliot, Anne-Marie; Baudin, Grégoire; Ferchiou, Aziz; Richard, Jean-Romain; Bulzacka, Ewa; Charpeaud, Thomas; Tronche, Anne-Marie; De Hert, Marc; van Winkel, Ruud; Decoster, Jeroen; Derom, Catherine; Thiery, Evert; Stefanis, Nikos C; Sachs, Gabriele; Aschauer, Harald; Lasser, Iris; Winklbaur, Bernadette; Schlögelhofer, Monika; Riecher-Rössler, Anita; Borgwardt, Stefan; Walter, Anna; Harrisberger, Fabienne; Smieskova, Renata; Rapp, Charlotte; Ittig, Sarah; Soguel-dit-Piquard, Fabienne; Studerus, Erich; Klosterkötter, Joachim; Ruhrmann, Stephan; Paruch, Julia; Julkowski, Dominika; Hilboll, Desiree; Sham, Pak C; Cherny, Stacey S; Chen, Eric Y H; Campbell, Desmond D; Li, Miaoxin; Romeo-Casabona, Carlos María; Emaldi Cirión, Aitziber; Urruela Mora, Asier; Jones, Peter; Kirkbride, James; Cannon, Mary; Rujescu, Dan; Tarricone, Ilaria; Berardi, Domenico; Bonora, Elena; Seri, Marco; Marcacci, Thomas; Chiri, Luigi; Chierzi, Federico; Storbini, Viviana; Braca, Mauro; Minenna, Maria Gabriella; Donegani, Ivonne; Fioritti, Angelo; La Barbera, Daniele; La Cascia, Caterina Erika; Mulè, Alice; Sideli, Lucia; Sartorio, Rachele; Ferraro, Laura; Tripoli, Giada; Seminerio, Fabio; Marinaro, Anna Maria; McGorry, Patrick; Nelson, Barnaby; Amminger, G Paul; Pantelis, Christos; Menezes, Paulo R; Del-Ben, Cristina M; Gallo Tenan, Silvia H; Shuhama, Rosana; Ruggeri, Mirella; Tosato, Sarah; Lasalvia, Antonio; Bonetto, Chiara; Ira, Elisa; Nordentoft, Merete; Krebs, Marie-Odile; Barrantes-Vidal, Neus; Cristóbal, Paula; Kwapil, Thomas R; Brietzke, Elisa; Bressan, Rodrigo A; Gadelha, Ary; Maric, Nadja P; Andric, Sanja; Mihaljevic, Marina; Mirjanic, Tijana

2014-07-01

Recent years have seen considerable progress in epidemiological and molecular genetic research into environmental and genetic factors in schizophrenia, but methodological uncertainties remain with regard to validating environmental exposures, and the population risk conferred by individual molecular genetic variants is small. There are now also a limited number of studies that have investigated molecular genetic candidate gene-environment interactions (G × E), however, so far, thorough replication of findings is rare and G × E research still faces several conceptual and methodological challenges. In this article, we aim to review these recent developments and illustrate how integrated, large-scale investigations may overcome contemporary challenges in G × E research, drawing on the example of a large, international, multi-center study into the identification and translational application of G × E in schizophrenia. While such investigations are now well underway, new challenges emerge for G × E research from late-breaking evidence that genetic variation and environmental exposures are, to a significant degree, shared across a range of psychiatric disorders, with potential overlap in phenotype. © The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Large-area landslide susceptibility with optimized slope-units

Science.gov (United States)

Alvioli, Massimiliano; Marchesini, Ivan; Reichenbach, Paola; Rossi, Mauro; Ardizzone, Francesca; Fiorucci, Federica; Guzzetti, Fausto

2017-04-01

A Slope-Unit (SU) is a type of morphological terrain unit bounded by drainage and divide lines that maximize the within-unit homogeneity and the between-unit heterogeneity across distinct physical and geographical boundaries [1]. Compared to other terrain subdivisions, SU are morphological terrain unit well related to the natural (i.e., geological, geomorphological, hydrological) processes that shape and characterize natural slopes. This makes SU easily recognizable in the field or in topographic base maps, and well suited for environmental and geomorphological analysis, in particular for landslide susceptibility (LS) modelling. An optimal subdivision of an area into a set of SU depends on multiple factors: size and complexity of the study area, quality and resolution of the available terrain elevation data, purpose of the terrain subdivision, scale and resolution of the phenomena for which SU are delineated. We use the recently developed r.slopeunits software [2,3] for the automatic, parametric delineation of SU within the open source GRASS GIS based on terrain elevation data and a small number of user-defined parameters. The software provides subdivisions consisting of SU with different shapes and sizes, as a function of the input parameters. In this work, we describe a procedure for the optimal selection of the user parameters through the production of a large number of realizations of the LS model. We tested the software and the optimization procedure in a 2,000 km2 area in Umbria, Central Italy. For LS zonation we adopt a logistic regression model implemented in an well-known software [4,5], using about 50 independent variables. To select the optimal SU partition for LS zonation, we want to define a metric which is able to quantify simultaneously: (i) slope-unit internal homogeneity (ii) slope-unit external heterogeneity (iii) landslide susceptibility model performance. To this end, we define a comprehensive objective function S, as the product of three

Accelerating large-scale protein structure alignments with graphics processing units

Directory of Open Access Journals (Sweden)

Pang Bin

2012-02-01

Full Text Available Abstract Background Large-scale protein structure alignment, an indispensable tool to structural bioinformatics, poses a tremendous challenge on computational resources. To ensure structure alignment accuracy and efficiency, efforts have been made to parallelize traditional alignment algorithms in grid environments. However, these solutions are costly and of limited accessibility. Others trade alignment quality for speedup by using high-level characteristics of structure fragments for structure comparisons. Findings We present ppsAlign, a parallel protein structure Alignment framework designed and optimized to exploit the parallelism of Graphics Processing Units (GPUs. As a general-purpose GPU platform, ppsAlign could take many concurrent methods, such as TM-align and Fr-TM-align, into the parallelized algorithm design. We evaluated ppsAlign on an NVIDIA Tesla C2050 GPU card, and compared it with existing software solutions running on an AMD dual-core CPU. We observed a 36-fold speedup over TM-align, a 65-fold speedup over Fr-TM-align, and a 40-fold speedup over MAMMOTH. Conclusions ppsAlign is a high-performance protein structure alignment tool designed to tackle the computational complexity issues from protein structural data. The solution presented in this paper allows large-scale structure comparisons to be performed using massive parallel computing power of GPU.

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

Optimized Placement of Wind Turbines in Large-Scale Offshore Wind Farm using Particle Swarm Optimization Algorithm

DEFF Research Database (Denmark)

Hou, Peng; Hu, Weihao; Soltani, Mohsen

2015-01-01

With the increasing size of wind farm, the impact of the wake effect on wind farm energy yields become more and more evident. The arrangement of the wind turbines’ (WT) locations will influence the capital investment and contribute to the wake losses which incur the reduction of energy production....... As a consequence, the optimized placement of the wind turbines may be done by considering the wake effect as well as the components cost within the wind farm. In this paper, a mathematical model which includes the variation of both wind direction and wake deficit is proposed. The problem is formulated by using...... Levelized Production Cost (LPC) as the objective function. The optimization procedure is performed by Particle Swarm Optimization (PSO) algorithm with the purpose of maximizing the energy yields while minimizing the total investment. The simulation results indicate that the proposed method is effective...

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...

Large scale PV plants - also in Denmark. Project report

Energy Technology Data Exchange (ETDEWEB)

Ahm, P [PA Energy, Malling (Denmark); Vedde, J [SiCon. Silicon and PV consulting, Birkeroed (Denmark)

2011-04-15

Large scale PV (LPV) plants, plants with a capacity of more than 200 kW, has since 2007 constituted an increasing share of the global PV installations. In 2009 large scale PV plants with cumulative power more that 1,3 GWp were connected to the grid. The necessary design data for LPV plants in Denmark are available or can be found, although irradiance data could be improved. There seems to be very few institutional barriers for LPV projects, but as so far no real LPV projects have been processed, these findings have to be regarded as preliminary. The fast growing number of very large scale solar thermal plants for district heating applications supports these findings. It has further been investigated, how to optimize the lay-out of LPV plants. Under the Danish irradiance conditions with several winter months with very low solar height PV installations on flat surfaces will have to balance the requirements of physical space - and cost, and the loss of electricity production due to shadowing effects. The potential for LPV plants in Denmark are found in three main categories: PV installations on flat roof of large commercial buildings, PV installations on other large scale infrastructure such as noise barriers and ground mounted PV installations. The technical potential for all three categories is found to be significant and in the range of 50 - 250 km2. In terms of energy harvest PV plants will under Danish conditions exhibit an overall efficiency of about 10 % in conversion of the energy content of the light compared to about 0,3 % for biomass. The theoretical ground area needed to produce the present annual electricity consumption of Denmark at 33-35 TWh is about 300 km2 The Danish grid codes and the electricity safety regulations mention very little about PV and nothing about LPV plants. It is expected that LPV plants will be treated similarly to big wind turbines. A number of LPV plant scenarios have been investigated in detail based on real commercial offers and

A Temporal Domain Decomposition Algorithmic Scheme for Large-Scale Dynamic Traffic Assignment

Directory of Open Access Journals (Sweden)

Eric J. Nava

2012-03-01

This paper presents a temporal decomposition scheme for large spatial- and temporal-scale dynamic traffic assignment, in which the entire analysis period is divided into Epochs. Vehicle assignment is performed sequentially in each Epoch, thus improving the model scalability and confining the peak run-time memory requirement regardless of the total analysis period. A proposed self-turning scheme adaptively searches for the run-time-optimal Epoch setting during iterations regardless of the characteristics of the modeled network. Extensive numerical experiments confirm the promising performance of the proposed algorithmic schemes.

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

Optimizing rice yields while minimizing yield-scaled global warming potential.

Science.gov (United States)

Pittelkow, Cameron M; Adviento-Borbe, Maria A; van Kessel, Chris; Hill, James E; Linquist, Bruce A

2014-05-01

To meet growing global food demand with limited land and reduced environmental impact, agricultural greenhouse gas (GHG) emissions are increasingly evaluated with respect to crop productivity, i.e., on a yield-scaled as opposed to area basis. Here, we compiled available field data on CH4 and N2 O emissions from rice production systems to test the hypothesis that in response to fertilizer nitrogen (N) addition, yield-scaled global warming potential (GWP) will be minimized at N rates that maximize yields. Within each study, yield N surplus was calculated to estimate deficit or excess N application rates with respect to the optimal N rate (defined as the N rate at which maximum yield was achieved). Relationships between yield N surplus and GHG emissions were assessed using linear and nonlinear mixed-effects models. Results indicate that yields increased in response to increasing N surplus when moving from deficit to optimal N rates. At N rates contributing to a yield N surplus, N2 O and yield-scaled N2 O emissions increased exponentially. In contrast, CH4 emissions were not impacted by N inputs. Accordingly, yield-scaled CH4 emissions decreased with N addition. Overall, yield-scaled GWP was minimized at optimal N rates, decreasing by 21% compared to treatments without N addition. These results are unique compared to aerobic cropping systems in which N2 O emissions are the primary contributor to GWP, meaning yield-scaled GWP may not necessarily decrease for aerobic crops when yields are optimized by N fertilizer addition. Balancing gains in agricultural productivity with climate change concerns, this work supports the concept that high rice yields can be achieved with minimal yield-scaled GWP through optimal N application rates. Moreover, additional improvements in N use efficiency may further reduce yield-scaled GWP, thereby strengthening the economic and environmental sustainability of rice systems. © 2013 John Wiley & Sons Ltd.

Kernel optimization for short-range molecular dynamics

Science.gov (United States)

Hu, Changjun; Wang, Xianmeng; Li, Jianjiang; He, Xinfu; Li, Shigang; Feng, Yangde; Yang, Shaofeng; Bai, He

2017-02-01

To optimize short-range force computations in Molecular Dynamics (MD) simulations, multi-threading and SIMD optimizations are presented in this paper. With respect to multi-threading optimization, a Partition-and-Separate-Calculation (PSC) method is designed to avoid write conflicts caused by using Newton's third law. Serial bottlenecks are eliminated with no additional memory usage. The method is implemented by using the OpenMP model. Furthermore, the PSC method is employed on Intel Xeon Phi coprocessors in both native and offload models. We also evaluate the performance of the PSC method under different thread affinities on the MIC architecture. In the SIMD execution, we explain the performance influence in the PSC method, considering the "if-clause" of the cutoff radius check. The experiment results show that our PSC method is relatively more efficient compared to some traditional methods. In double precision, our 256-bit SIMD implementation is about 3 times faster than the scalar version.

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

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

Science.gov (United States)

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

2009-01-01

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

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.)

GRAPHICS-IMAGE MIXED METHOD FOR LARGE-SCALE BUILDINGS RENDERING

Directory of Open Access Journals (Sweden)

Y. Zhou

2018-05-01

Full Text Available Urban 3D model data is huge and unstructured, LOD and Out-of-core algorithm are usually used to reduce the amount of data that drawn in each frame to improve the rendering efficiency. When the scene is large enough, even the complex optimization algorithm is difficult to achieve better results. Based on the traditional study, a novel idea was developed. We propose a graphics and image mixed method for large-scale buildings rendering. Firstly, the view field is divided into several regions, the graphics-image mixed method used to render the scene on both screen and FBO, then blending the FBO with scree. The algorithm is tested on the huge CityGML model data in the urban areas of New York which contained 188195 public building models, and compared with the Cesium platform. The experiment result shows the system was running smoothly. The experimental results confirm that the algorithm can achieve more massive building scene roaming under the same hardware conditions, and can rendering the scene without vision loss.

Including investment risk in large-scale power market models

DEFF Research Database (Denmark)

Lemming, Jørgen Kjærgaard; Meibom, P.

2003-01-01

Long-term energy market models can be used to examine investments in production technologies, however, with market liberalisation it is crucial that such models include investment risks and investor behaviour. This paper analyses how the effect of investment risk on production technology selection...... can be included in large-scale partial equilibrium models of the power market. The analyses are divided into a part about risk measures appropriate for power market investors and a more technical part about the combination of a risk-adjustment model and a partial-equilibrium model. To illustrate...... the analyses quantitatively, a framework based on an iterative interaction between the equilibrium model and a separate risk-adjustment module was constructed. To illustrate the features of the proposed modelling approach we examined how uncertainty in demand and variable costs affects the optimal choice...

Large-scale Estimates of Leaf Area Index from Active Remote Sensing Laser Altimetry

Science.gov (United States)

Hopkinson, C.; Mahoney, C.

2016-12-01

Leaf area index (LAI) is a key parameter that describes the spatial distribution of foliage within forest canopies which in turn control numerous relationships between the ground, canopy, and atmosphere. The retrieval of LAI has demonstrated success by in-situ (digital) hemispherical photography (DHP) and airborne laser scanning (ALS) data; however, field and ALS acquisitions are often spatially limited (100's km2) and costly. Large-scale (>1000's km2) retrievals have been demonstrated by optical sensors, however, accuracies remain uncertain due to the sensor's inability to penetrate the canopy. The spaceborne Geoscience Laser Altimeter System (GLAS) provides a possible solution in retrieving large-scale derivations whilst simultaneously penetrating the canopy. LAI retrieved by multiple DHP from 6 Australian sites, representing a cross-section of Australian ecosystems, were employed to model ALS LAI, which in turn were used to infer LAI from GLAS data at 5 other sites. An optimally filtered GLAS dataset was then employed in conjunction with a host of supplementary data to build a Random Forest (RF) model to infer predictions (and uncertainties) of LAI at a 250 m resolution across the forested regions of Australia. Predictions were validated against ALS-based LAI from 20 sites (R2=0.64, RMSE=1.1 m2m-2); MODIS-based LAI were also assessed against these sites (R2=0.30, RMSE=1.78 m2m-2) to demonstrate the strength of GLAS-based predictions. The large-scale nature of current predictions was also leveraged to demonstrate large-scale relationships of LAI with other environmental characteristics, such as: canopy height, elevation, and slope. The need for such wide-scale quantification of LAI is key in the assessment and modification of forest management strategies across Australia. Such work also assists Australia's Terrestrial Ecosystem Research Network, in fulfilling their government issued mandates.

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

A Framing Link Based Tabu Search Algorithm for Large-Scale Multidepot Vehicle Routing Problems

Directory of Open Access Journals (Sweden)

Xuhao Zhang

2014-01-01

Full Text Available A framing link (FL based tabu search algorithm is proposed in this paper for a large-scale multidepot vehicle routing problem (LSMDVRP. Framing links are generated during continuous great optimization of current solutions and then taken as skeletons so as to improve optimal seeking ability, speed up the process of optimization, and obtain better results. Based on the comparison between pre- and postmutation routes in the current solution, different parts are extracted. In the current optimization period, links involved in the optimal solution are regarded as candidates to the FL base. Multiple optimization periods exist in the whole algorithm, and there are several potential FLs in each period. If the update condition is satisfied, the FL base is updated, new FLs are added into the current route, and the next period starts. Through adjusting the borderline of multidepot sharing area with dynamic parameters, the authors define candidate selection principles for three kinds of customer connections, respectively. Link split and the roulette approach are employed to choose FLs. 18 LSMDVRP instances in three groups are studied and new optimal solution values for nine of them are obtained, with higher computation speed and reliability.

A glimpse of fluid turbulence from the molecular scale

KAUST Repository

Komatsu, Teruhisa S.; Matsumoto, Shigenori; Shimada, Takashi; Ito, Nobuyasu

2014-01-01

. The energy spectrum of the fluid components is observed to scale reasonably well according to Kolmogorov scaling determined from the energy dissipation rate and the viscosity of the fluid, even though the Kolmogorov length is of the order of the molecular

Exact and Optimal Quantum Mechanics/Molecular Mechanics Boundaries.

Science.gov (United States)

Sun, Qiming; Chan, Garnet Kin-Lic

2014-09-09

Motivated by recent work in density matrix embedding theory, we define exact link orbitals that capture all quantum mechanical (QM) effects across arbitrary quantum mechanics/molecular mechanics (QM/MM) boundaries. Exact link orbitals are rigorously defined from the full QM solution, and their number is equal to the number of orbitals in the primary QM region. Truncating the exact set yields a smaller set of link orbitals optimal with respect to reproducing the primary region density matrix. We use the optimal link orbitals to obtain insight into the limits of QM/MM boundary treatments. We further analyze the popular general hybrid orbital (GHO) QM/MM boundary across a test suite of molecules. We find that GHOs are often good proxies for the most important optimal link orbital, although there is little detailed correlation between the detailed GHO composition and optimal link orbital valence weights. The optimal theory shows that anions and cations cannot be described by a single link orbital. However, expanding to include the second most important optimal link orbital in the boundary recovers an accurate description. The second optimal link orbital takes the chemically intuitive form of a donor or acceptor orbital for charge redistribution, suggesting that optimal link orbitals can be used as interpretative tools for electron transfer. We further find that two optimal link orbitals are also sufficient for boundaries that cut across double bonds. Finally, we suggest how to construct "approximately" optimal link orbitals for practical QM/MM calculations.

The future of nanofabrication and molecular scale devices in nanomedicine.

Science.gov (United States)

Freitas, R A

2002-01-01

Nanotechnology is engineering and manufacturing at the molecular scale, and the application of nanotechnology to medicine is called nanomedicine. Nanomedicine subsumes three mutually overlapping and progressively more powerful molecular technologies. First, nanoscale-structured materials and devices that can be fabricated today hold great promise for advanced diagnostics and biosensors, targeted drug delivery and smart drugs, and immunoisolation therapies. Second, biotechnology offers the benefits of molecular medicine via genomics, proteomics, and artificial engineered microbes. Third, in the longer term, molecular machine systems and medical nanorobots will allow instant pathogen diagnosis and extermination, chromosome replacement and individual cell surgery in vivo, and the efficient augmentation and improvement of natural physiological function. Current research is exploring the fabrication of designed nanostructures, nanoactuators and nanomotors, microscopic energy sources, and nanocomputers at the molecular scale, along with the means to assemble them into larger systems, economically and in great numbers.

Finite element analysis and genetic algorithm optimization design for the actuator placement on a large adaptive structure

Science.gov (United States)

Sheng, Lizeng

The dissertation focuses on one of the major research needs in the area of adaptive/intelligent/smart structures, the development and application of finite element analysis and genetic algorithms for optimal design of large-scale adaptive structures. We first review some basic concepts in finite element method and genetic algorithms, along with the research on smart structures. Then we propose a solution methodology for solving a critical problem in the design of a next generation of large-scale adaptive structures---optimal placements of a large number of actuators to control thermal deformations. After briefly reviewing the three most frequently used general approaches to derive a finite element formulation, the dissertation presents techniques associated with general shell finite element analysis using flat triangular laminated composite elements. The element used here has three nodes and eighteen degrees of freedom and is obtained by combining a triangular membrane element and a triangular plate bending element. The element includes the coupling effect between membrane deformation and bending deformation. The membrane element is derived from the linear strain triangular element using Cook's transformation. The discrete Kirchhoff triangular (DKT) element is used as the plate bending element. For completeness, a complete derivation of the DKT is presented. Geometrically nonlinear finite element formulation is derived for the analysis of adaptive structures under the combined thermal and electrical loads. Next, we solve the optimization problems of placing a large number of piezoelectric actuators to control thermal distortions in a large mirror in the presence of four different thermal loads. We then extend this to a multi-objective optimization problem of determining only one set of piezoelectric actuator locations that can be used to control the deformation in the same mirror under the action of any one of the four thermal loads. A series of genetic algorithms

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

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...

Breaking Computational Barriers: Real-time Analysis and Optimization with Large-scale Nonlinear Models via Model Reduction

Energy Technology Data Exchange (ETDEWEB)

Carlberg, Kevin Thomas [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Quantitative Modeling and Analysis; Drohmann, Martin [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Quantitative Modeling and Analysis; Tuminaro, Raymond S. [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Computational Mathematics; Boggs, Paul T. [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Quantitative Modeling and Analysis; Ray, Jaideep [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Quantitative Modeling and Analysis; van Bloemen Waanders, Bart Gustaaf [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Optimization and Uncertainty Estimation

2014-10-01

Model reduction for dynamical systems is a promising approach for reducing the computational cost of large-scale physics-based simulations to enable high-fidelity models to be used in many- query (e.g., Bayesian inference) and near-real-time (e.g., fast-turnaround simulation) contexts. While model reduction works well for specialized problems such as linear time-invariant systems, it is much more difficult to obtain accurate, stable, and efficient reduced-order models (ROMs) for systems with general nonlinearities. This report describes several advances that enable nonlinear reduced-order models (ROMs) to be deployed in a variety of time-critical settings. First, we present an error bound for the Gauss-Newton with Approximated Tensors (GNAT) nonlinear model reduction technique. This bound allows the state-space error for the GNAT method to be quantified when applied with the backward Euler time-integration scheme. Second, we present a methodology for preserving classical Lagrangian structure in nonlinear model reduction. This technique guarantees that important properties--such as energy conservation and symplectic time-evolution maps--are preserved when performing model reduction for models described by a Lagrangian formalism (e.g., molecular dynamics, structural dynamics). Third, we present a novel technique for decreasing the temporal complexity --defined as the number of Newton-like iterations performed over the course of the simulation--by exploiting time-domain data. Fourth, we describe a novel method for refining projection-based reduced-order models a posteriori using a goal-oriented framework similar to mesh-adaptive h -refinement in finite elements. The technique allows the ROM to generate arbitrarily accurate solutions, thereby providing the ROM with a 'failsafe' mechanism in the event of insufficient training data. Finally, we present the reduced-order model error surrogate (ROMES) method for statistically quantifying reduced- order

Optimizing basin-scale coupled water quantity and water quality management with stochastic dynamic programming

DEFF Research Database (Denmark)

Davidsen, Claus; Liu, Suxia; Mo, Xingguo

2015-01-01

Few studies address water quality in hydro-economic models, which often focus primarily on optimal allocation of water quantities. Water quality and water quantity are closely coupled, and optimal management with focus solely on either quantity or quality may cause large costs in terms of the oth......-er component. In this study, we couple water quality and water quantity in a joint hydro-economic catchment-scale optimization problem. Stochastic dynamic programming (SDP) is used to minimize the basin-wide total costs arising from water allocation, water curtailment and water treatment. The simple water...... quality module can handle conservative pollutants, first order depletion and non-linear reactions. For demonstration purposes, we model pollutant releases as biochemical oxygen demand (BOD) and use the Streeter-Phelps equation for oxygen deficit to compute the resulting min-imum dissolved oxygen...

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.

Research and development of system to utilize photovoltaic energy. Study on large-scale PV power supply system; Taiyoko hatsuden riyo system no kenkyu kaihatsu. Taiyo energy kyokyu system no chosa kenkyu

Energy Technology Data Exchange (ETDEWEB)

Tatsuta, M [New Energy and Industrial Technology Development Organization, Tokyo (Japan)

1994-12-01

This paper reports the study results on large-scale PV power supply systems in fiscal 1994. (1) On optimization of large-scale systems, the conceptual design of the model system was carried out which supposes a large-scale integrated PV power generation system in desert area. As a result, a pair of 250kW generation system was designed as minimum one consisting power unit. Its frame and construction method were designed considering weather conditions in the inland of China. (2) On optimization of large-scale transmission systems, as large-scale power transmission systems for PV power generation, the following were studied: AC aerial transmission, DC aerial transmission, superconducting transmission, hydrogen gas pipeline, and LH2 tanker transport. (3) On the influence of large-scale systems, it was estimated that emission control is expected by substituting PV power generation for coal fired power generation, the negative influence on natural environment cannot be supposed, and the favorable economic effect is expected as influence on social environment. 4 tabs.

Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach

International Nuclear Information System (INIS)

Wei, F.; Wu, Q.H.; Jing, Z.X.; Chen, J.J.; Zhou, X.X.

2016-01-01

This paper proposes a comprehensive framework including a multi-objective interval optimization model and evidential reasoning (ER) approach to solve the unit sizing problem of small-scale integrated energy systems, with uncertain wind and solar energies integrated. In the multi-objective interval optimization model, interval variables are introduced to tackle the uncertainties of the optimization problem. Aiming at simultaneously considering the cost and risk of a business investment, the average and deviation of life cycle cost (LCC) of the integrated energy system are formulated. In order to solve the problem, a novel multi-objective optimization algorithm, MGSOACC (multi-objective group search optimizer with adaptive covariance matrix and chaotic search), is developed, employing adaptive covariance matrix to make the search strategy adaptive and applying chaotic search to maintain the diversity of group. Furthermore, ER approach is applied to deal with multiple interests of an investor at the business decision making stage and to determine the final unit sizing solution from the Pareto-optimal solutions. This paper reports on the simulation results obtained using a small-scale direct district heating system (DH) and a small-scale district heating and cooling system (DHC) optimized by the proposed framework. The results demonstrate the superiority of the multi-objective interval optimization model and ER approach in tackling the unit sizing problem of integrated energy systems considering the integration of uncertian wind and solar energies. - Highlights: • Cost and risk of investment in small-scale integrated energy systems are considered. • A multi-objective interval optimization model is presented. • A novel multi-objective optimization algorithm (MGSOACC) is proposed. • The evidential reasoning (ER) approach is used to obtain the final optimal solution. • The MGSOACC and ER can tackle the unit sizing problem efficiently.

Electrochemistry of single molecules and biomolecules, molecular scale nanostructures, and low-dimensional systems

DEFF Research Database (Denmark)

Nazmutdinov, Renat R.; Zinkicheva, Tamara T.; Zinkicheva, Tamara T.

2018-01-01

Electrochemistry at ultra-small scales, where even the single molecule or biomolecule can be characterized and manipulated, is on the way to a consolidated status. At the same time molecular electrochemistry is expanding into other areas of sophisticated nano- and molecular scale systems includin...... molecular scale metal and semiconductor nanoparticles (NPs) and other nanostructures, e.g. nanotubes, “nanoflowers” etc.. The new structures offer both new electronic properties and highly confined novel charge transfer environments....

Optimizing CyberShake Seismic Hazard Workflows for Large HPC Resources

Science.gov (United States)

Callaghan, S.; Maechling, P. J.; Juve, G.; Vahi, K.; Deelman, E.; Jordan, T. H.

2014-12-01

The CyberShake computational platform is a well-integrated collection of scientific software and middleware that calculates 3D simulation-based probabilistic seismic hazard curves and hazard maps for the Los Angeles region. Currently each CyberShake model comprises about 235 million synthetic seismograms from about 415,000 rupture variations computed at 286 sites. CyberShake integrates large-scale parallel and high-throughput serial seismological research codes into a processing framework in which early stages produce files used as inputs by later stages. Scientific workflow tools are used to manage the jobs, data, and metadata. The Southern California Earthquake Center (SCEC) developed the CyberShake platform using USC High Performance Computing and Communications systems and open-science NSF resources.CyberShake calculations were migrated to the NSF Track 1 system NCSA Blue Waters when it became operational in 2013, via an interdisciplinary team approach including domain scientists, computer scientists, and middleware developers. Due to the excellent performance of Blue Waters and CyberShake software optimizations, we reduced the makespan (a measure of wallclock time-to-solution) of a CyberShake study from 1467 to 342 hours. We will describe the technical enhancements behind this improvement, including judicious introduction of new GPU software, improved scientific software components, increased workflow-based automation, and Blue Waters-specific workflow optimizations.Our CyberShake performance improvements highlight the benefits of scientific workflow tools. The CyberShake workflow software stack includes the Pegasus Workflow Management System (Pegasus-WMS, which includes Condor DAGMan), HTCondor, and Globus GRAM, with Pegasus-mpi-cluster managing the high-throughput tasks on the HPC resources. The workflow tools handle data management, automatically transferring about 13 TB back to SCEC storage.We will present performance metrics from the most recent Cyber

Optimal separable bases and molecular collisions

International Nuclear Information System (INIS)

Poirier, L.W.

1997-12-01

A new methodology is proposed for the efficient determination of Green's functions and eigenstates for quantum systems of two or more dimensions. For a given Hamiltonian, the best possible separable approximation is obtained from the set of all Hilbert space operators. It is shown that this determination itself, as well as the solution of the resultant approximation, are problems of reduced dimensionality for most systems of physical interest. Moreover, the approximate eigenstates constitute the optimal separable basis, in the sense of self-consistent field theory. These distorted waves give rise to a Born series with optimized convergence properties. Analytical results are presented for an application of the method to the two-dimensional shifted harmonic oscillator system. The primary interest however, is quantum reactive scattering in molecular systems. For numerical calculations, the use of distorted waves corresponds to numerical preconditioning. The new methodology therefore gives rise to an optimized preconditioning scheme for the efficient calculation of reactive and inelastic scattering amplitudes, especially at intermediate energies. This scheme is particularly suited to discrete variable representations (DVR's) and iterative sparse matrix methods commonly employed in such calculations. State to state and cumulative reactive scattering results obtained via the optimized preconditioner are presented for the two-dimensional collinear H + H 2 → H 2 + H system. Computational time and memory requirements for this system are drastically reduced in comparison with other methods, and results are obtained for previously prohibitive energy regimes

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...

SQDFT: Spectral Quadrature method for large-scale parallel O(N) Kohn-Sham calculations at high temperature

Science.gov (United States)

Suryanarayana, Phanish; Pratapa, Phanisri P.; Sharma, Abhiraj; Pask, John E.

2018-03-01

We present SQDFT: a large-scale parallel implementation of the Spectral Quadrature (SQ) method for O(N) Kohn-Sham Density Functional Theory (DFT) calculations at high temperature. Specifically, we develop an efficient and scalable finite-difference implementation of the infinite-cell Clenshaw-Curtis SQ approach, in which results for the infinite crystal are obtained by expressing quantities of interest as bilinear forms or sums of bilinear forms, that are then approximated by spatially localized Clenshaw-Curtis quadrature rules. We demonstrate the accuracy of SQDFT by showing systematic convergence of energies and atomic forces with respect to SQ parameters to reference diagonalization results, and convergence with discretization to established planewave results, for both metallic and insulating systems. We further demonstrate that SQDFT achieves excellent strong and weak parallel scaling on computer systems consisting of tens of thousands of processors, with near perfect O(N) scaling with system size and wall times as low as a few seconds per self-consistent field iteration. Finally, we verify the accuracy of SQDFT in large-scale quantum molecular dynamics simulations of aluminum at high temperature.

Optimization of large bore gas engine

International Nuclear Information System (INIS)

Laiminger, S.

1999-01-01

This doctoral thesis is concerned with the experimental part of combustion optimization of a large bore gas engine. Nevertheless there was a very close co-operation with the simultaneous numeric simulation. The terms of reference were a systematic investigation of the optimization potential of the current combustion mode with the objective target to get a higher brake efficiency and lower NO x emissions. In a second part a new combustion mode for fuels containing H 2 , for fuels with very low heating value and for special fuels should be developed. The optimization contained all relevant components of the engine to achieve a stable and well suited combustion with short duration even with very lean mixture. After the optimization the engine was running stable with substantial lower NO x emissions. It was world-wide the first time when a gas medium-sized engine could reach a total electrical efficiency of more than 40 percent. Finally a combustion mode for gaseous fuels containing H 2 was developed. The engine is running now with direct ignition and with prechamber ignition. Both modes reach approximately the same efficiency and thermodynamic stability. (author)

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...

Towards Development of Clustering Applications for Large-Scale Comparative Genotyping and Kinship Analysis Using Y-Short Tandem Repeats.

Science.gov (United States)

Seman, Ali; Sapawi, Azizian Mohd; Salleh, Mohd Zaki

2015-06-01

Y-chromosome short tandem repeats (Y-STRs) are genetic markers with practical applications in human identification. However, where mass identification is required (e.g., in the aftermath of disasters with significant fatalities), the efficiency of the process could be improved with new statistical approaches. Clustering applications are relatively new tools for large-scale comparative genotyping, and the k-Approximate Modal Haplotype (k-AMH), an efficient algorithm for clustering large-scale Y-STR data, represents a promising method for developing these tools. In this study we improved the k-AMH and produced three new algorithms: the Nk-AMH I (including a new initial cluster center selection), the Nk-AMH II (including a new dominant weighting value), and the Nk-AMH III (combining I and II). The Nk-AMH III was the superior algorithm, with mean clustering accuracy that increased in four out of six datasets and remained at 100% in the other two. Additionally, the Nk-AMH III achieved a 2% higher overall mean clustering accuracy score than the k-AMH, as well as optimal accuracy for all datasets (0.84-1.00). With inclusion of the two new methods, the Nk-AMH III produced an optimal solution for clustering Y-STR data; thus, the algorithm has potential for further development towards fully automatic clustering of any large-scale genotypic data.

Network synchronization: optimal and pessimal scale-free topologies

International Nuclear Information System (INIS)

Donetti, Luca; Hurtado, Pablo I; Munoz, Miguel A

2008-01-01

By employing a recently introduced optimization algorithm we construct optimally synchronizable (unweighted) networks for any given scale-free degree distribution. We explore how the optimization process affects degree-degree correlations and observe a generic tendency toward disassortativity. Still, we show that there is not a one-to-one correspondence between synchronizability and disassortativity. On the other hand, we study the nature of optimally un-synchronizable networks, that is, networks whose topology minimizes the range of stability of the synchronous state. The resulting 'pessimal networks' turn out to have a highly assortative string-like structure. We also derive a rigorous lower bound for the Laplacian eigenvalue ratio controlling synchronizability, which helps understanding the impact of degree correlations on network synchronizability

Large-Scale Recurrent Neural Network Based Modelling of Gene Regulatory Network Using Cuckoo Search-Flower Pollination Algorithm.

Science.gov (United States)

Mandal, Sudip; Khan, Abhinandan; Saha, Goutam; Pal, Rajat K

2016-01-01

The accurate prediction of genetic networks using computational tools is one of the greatest challenges in the postgenomic era. Recurrent Neural Network is one of the most popular but simple approaches to model the network dynamics from time-series microarray data. To date, it has been successfully applied to computationally derive small-scale artificial and real-world genetic networks with high accuracy. However, they underperformed for large-scale genetic networks. Here, a new methodology has been proposed where a hybrid Cuckoo Search-Flower Pollination Algorithm has been implemented with Recurrent Neural Network. Cuckoo Search is used to search the best combination of regulators. Moreover, Flower Pollination Algorithm is applied to optimize the model parameters of the Recurrent Neural Network formalism. Initially, the proposed method is tested on a benchmark large-scale artificial network for both noiseless and noisy data. The results obtained show that the proposed methodology is capable of increasing the inference of correct regulations and decreasing false regulations to a high degree. Secondly, the proposed methodology has been validated against the real-world dataset of the DNA SOS repair network of Escherichia coli. However, the proposed method sacrifices computational time complexity in both cases due to the hybrid optimization process.

Prospects of luminescence based molecular scale logic gates and logic circuits

International Nuclear Information System (INIS)

Speiser, Shammai

2016-01-01

In recent years molecular electronics has emerged as a rapidly growing research field. The aim of this review is to introduce this subject as a whole with special emphasis on molecular scale potential devices and applications. As a particular example we will discuss all optical molecular scale logic gates and logic circuits based on molecular fluorescence and electronic excitation transfer processes. Charge and electronic energy transfers (ET and EET) are well-studied examples whereby different molecules can signal their state from one (the donor, D) to the other (the acceptor, A). We show how a half-adder logic circuit can be implemented on one molecule that can communicate its logic output as input to another half-adder molecule. This is achieved as an electronic energy transfer from a donor to an acceptor, thus implementing a molecular full adder. We discuss a specific pair, the rhodamine–azulene, for which there is considerable spectroscopic data, but the scheme is general enough to allow a wide choice of D and A pairs. We present results based on this pair, in which, for the first time, an all optical half-adder and full-adder logic circuits are implemented. - Highlights: • Molecular scale logic • Photoquenching • Full adder

Prospects of luminescence based molecular scale logic gates and logic circuits

Energy Technology Data Exchange (ETDEWEB)

Speiser, Shammai, E-mail: speiser@technion.ac.il

2016-01-15

In recent years molecular electronics has emerged as a rapidly growing research field. The aim of this review is to introduce this subject as a whole with special emphasis on molecular scale potential devices and applications. As a particular example we will discuss all optical molecular scale logic gates and logic circuits based on molecular fluorescence and electronic excitation transfer processes. Charge and electronic energy transfers (ET and EET) are well-studied examples whereby different molecules can signal their state from one (the donor, D) to the other (the acceptor, A). We show how a half-adder logic circuit can be implemented on one molecule that can communicate its logic output as input to another half-adder molecule. This is achieved as an electronic energy transfer from a donor to an acceptor, thus implementing a molecular full adder. We discuss a specific pair, the rhodamine–azulene, for which there is considerable spectroscopic data, but the scheme is general enough to allow a wide choice of D and A pairs. We present results based on this pair, in which, for the first time, an all optical half-adder and full-adder logic circuits are implemented. - Highlights: • Molecular scale logic • Photoquenching • Full adder.

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.

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

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.

A substrate-optimized electrophoretic mobility shift assay for ADAM12

DEFF Research Database (Denmark)

Kotzsch, Alexander; Skovgaard, Tine; Buus, Uwe

2014-01-01

long been investigated as pharmaceutical drug targets; however, due to lack of potency and in vivo side effects, none of the small-molecule inhibitors discovered so far has made it beyond clinical testing. Ongoing research on novel selective inhibitors of ADAMs requires reliable biochemical assays...... to validate molecular probes from large-scale screening efforts. Here we describe an electrophoretic mobility shift assay for ADAM12 based on the identification of an optimized peptide substrate that is characterized by excellent performance and reproducibility....

New Distributed Multipole Methods for Accurate Electrostatics for Large-Scale Biomolecular Simultations

Science.gov (United States)

Sagui, Celeste

2006-03-01

An accurate and numerically efficient treatment of electrostatics is essential for biomolecular simulations, as this stabilizes much of the delicate 3-d structure associated with biomolecules. Currently, force fields such as AMBER and CHARMM assign ``partial charges'' to every atom in a simulation in order to model the interatomic electrostatic forces, so that the calculation of the electrostatics rapidly becomes the computational bottleneck in large-scale simulations. There are two main issues associated with the current treatment of classical electrostatics: (i) how does one eliminate the artifacts associated with the point-charges (e.g., the underdetermined nature of the current RESP fitting procedure for large, flexible molecules) used in the force fields in a physically meaningful way? (ii) how does one efficiently simulate the very costly long-range electrostatic interactions? Recently, we have dealt with both of these challenges as follows. In order to improve the description of the molecular electrostatic potentials (MEPs), a new distributed multipole analysis based on localized functions -- Wannier, Boys, and Edminston-Ruedenberg -- was introduced, which allows for a first principles calculation of the partial charges and multipoles. Through a suitable generalization of the particle mesh Ewald (PME) and multigrid method, one can treat electrostatic multipoles all the way to hexadecapoles all without prohibitive extra costs. The importance of these methods for large-scale simulations will be discussed, and examplified by simulations from polarizable DNA models.

Optimization of a Fluorescence-Based Assay for Large-Scale Drug Screening against Babesia and Theileria Parasites

OpenAIRE

Rizk, Mohamed Abdo; El-Sayed, Shimaa Abd El-Salam; Terkawi, Mohamed Alaa; Youssef, Mohamed Ahmed; El Said, El Said El Shirbini; Elsayed, Gehad; El-Khodery, Sabry; El-Ashker, Maged; Elsify, Ahmed; Omar, Mosaab; Salama, Akram; Yokoyama, Naoaki; Igarashi, Ikuo

2015-01-01

A rapid and accurate assay for evaluating antibabesial drugs on a large scale is required for the discovery of novel chemotherapeutic agents against Babesia parasites. In the current study, we evaluated the usefulness of a fluorescence-based assay for determining the efficacies of antibabesial compounds against bovine and equine hemoparasites in in vitro cultures. Three different hematocrits (HCTs; 2.5%, 5%, and 10%) were used without daily replacement of the medium. The results of a high-thr...

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.

Comparison of Multi-Scale Digital Elevation Models for Defining Waterways and Catchments Over Large Areas

Science.gov (United States)

Harris, B.; McDougall, K.; Barry, M.

2012-07-01

Digital Elevation Models (DEMs) allow for the efficient and consistent creation of waterways and catchment boundaries over large areas. Studies of waterway delineation from DEMs are usually undertaken over small or single catchment areas due to the nature of the problems being investigated. Improvements in Geographic Information Systems (GIS) techniques, software, hardware and data allow for analysis of larger data sets and also facilitate a consistent tool for the creation and analysis of waterways over extensive areas. However, rarely are they developed over large regional areas because of the lack of available raw data sets and the amount of work required to create the underlying DEMs. This paper examines definition of waterways and catchments over an area of approximately 25,000 km2 to establish the optimal DEM scale required for waterway delineation over large regional projects. The comparative study analysed multi-scale DEMs over two test areas (Wivenhoe catchment, 543 km2 and a detailed 13 km2 within the Wivenhoe catchment) including various data types, scales, quality, and variable catchment input parameters. Historic and available DEM data was compared to high resolution Lidar based DEMs to assess variations in the formation of stream networks. The results identified that, particularly in areas of high elevation change, DEMs at 20 m cell size created from broad scale 1:25,000 data (combined with more detailed data or manual delineation in flat areas) are adequate for the creation of waterways and catchments at a regional scale.

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.

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

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

WAMS Based Intelligent Operation and Control of Modern Power System with large Scale Renewable Energy Penetration

DEFF Research Database (Denmark)

Rather, Zakir Hussain

security limits. Under such scenario, progressive displacement of conventional generation by wind generation is expected to eventually lead a complex power system with least presence of central power plants. Consequently the support from conventional power plants is expected to reach its all-time low...... system voltage control responsibility from conventional power plants to wind turbines. With increased wind penetration and displaced conventional central power plants, dynamic voltage security has been identified as one of the challenging issue for large scale wind integration. To address the dynamic...... security issue, a WAMS based systematic voltage control scheme for large scale wind integrated power system has been proposed. Along with the optimal reactive power compensation, the proposed scheme considers voltage support from wind farms (equipped with voltage support functionality) and refurbished...

First Joint Workshop on Energy Management for Large-Scale Research Infrastructures

CERN Document Server

2011-01-01

  CERN, ERF (European Association of National Research Facilities) and ESS (European Spallation Source) announce the first Joint Workshop on Energy Management for Large-Scale Research Infrastructures. The event will take place on 13-14 October 2011 at the ESS office in Sparta - Lund, Sweden.   The workshop will bring together international experts on energy and representatives from laboratories and future projects all over the world in order to identify the challenges and best practice in respect of energy efficiency and optimization, solutions and implementation as well as to review the challenges represented by potential future technical solutions and the tools for effective collaboration. Further information at: http://ess-scandinavia.eu/general-information

Network synchronization: optimal and pessimal scale-free topologies

Energy Technology Data Exchange (ETDEWEB)

Donetti, Luca [Departamento de Electronica y Tecnologia de Computadores and Instituto de Fisica Teorica y Computacional Carlos I, Facultad de Ciencias, Universidad de Granada, 18071 Granada (Spain); Hurtado, Pablo I; Munoz, Miguel A [Departamento de Electromagnetismo y Fisica de la Materia and Instituto Carlos I de Fisica Teorica y Computacional Facultad de Ciencias, Universidad de Granada, 18071 Granada (Spain)], E-mail: mamunoz@onsager.ugr.es

2008-06-06

By employing a recently introduced optimization algorithm we construct optimally synchronizable (unweighted) networks for any given scale-free degree distribution. We explore how the optimization process affects degree-degree correlations and observe a generic tendency toward disassortativity. Still, we show that there is not a one-to-one correspondence between synchronizability and disassortativity. On the other hand, we study the nature of optimally un-synchronizable networks, that is, networks whose topology minimizes the range of stability of the synchronous state. The resulting 'pessimal networks' turn out to have a highly assortative string-like structure. We also derive a rigorous lower bound for the Laplacian eigenvalue ratio controlling synchronizability, which helps understanding the impact of degree correlations on network synchronizability.

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.

Optimal Information Extraction of Laser Scanning Dataset by Scale-Adaptive Reduction

Science.gov (United States)

Zang, Y.; Yang, B.

2018-04-01

3D laser technology is widely used to collocate the surface information of object. For various applications, we need to extract a good perceptual quality point cloud from the scanned points. To solve the problem, most of existing methods extract important points based on a fixed scale. However, geometric features of 3D object come from various geometric scales. We propose a multi-scale construction method based on radial basis function. For each scale, important points are extracted from the point cloud based on their importance. We apply a perception metric Just-Noticeable-Difference to measure degradation of each geometric scale. Finally, scale-adaptive optimal information extraction is realized. Experiments are undertaken to evaluate the effective of the proposed method, suggesting a reliable solution for optimal information extraction of object.

OPTIMAL INFORMATION EXTRACTION OF LASER SCANNING DATASET BY SCALE-ADAPTIVE REDUCTION

Directory of Open Access Journals (Sweden)

Y. Zang

2018-04-01

Full Text Available 3D laser technology is widely used to collocate the surface information of object. For various applications, we need to extract a good perceptual quality point cloud from the scanned points. To solve the problem, most of existing methods extract important points based on a fixed scale. However, geometric features of 3D object come from various geometric scales. We propose a multi-scale construction method based on radial basis function. For each scale, important points are extracted from the point cloud based on their importance. We apply a perception metric Just-Noticeable-Difference to measure degradation of each geometric scale. Finally, scale-adaptive optimal information extraction is realized. Experiments are undertaken to evaluate the effective of the proposed method, suggesting a reliable solution for optimal information extraction of object.

A large-scale superhydrophobic surface-enhanced Raman scattering (SERS) platform fabricated via capillary force lithography and assembly of Ag nanocubes for ultratrace molecular sensing.

Science.gov (United States)

Tan, Joel Ming Rui; Ruan, Justina Jiexin; Lee, Hiang Kwee; Phang, In Yee; Ling, Xing Yi

2014-12-28

An analytical platform with an ultratrace detection limit in the atto-molar (aM) concentration range is vital for forensic, industrial and environmental sectors that handle scarce/highly toxic samples. Superhydrophobic surface-enhanced Raman scattering (SERS) platforms serve as ideal platforms to enhance detection sensitivity by reducing the random spreading of aqueous solution. However, the fabrication of superhydrophobic SERS platforms is generally limited due to the use of sophisticated and expensive protocols and/or suffers structural and signal inconsistency. Herein, we demonstrate a high-throughput fabrication of a stable and uniform superhydrophobic SERS platform for ultratrace molecular sensing. Large-area box-like micropatterns of the polymeric surface are first fabricated using capillary force lithography (CFL). Subsequently, plasmonic properties are incorporated into the patterned surfaces by decorating with Ag nanocubes using the Langmuir-Schaefer technique. To create a stable superhydrophobic SERS platform, an additional 25 nm Ag film is coated over the Ag nanocube-decorated patterned template followed by chemical functionalization with perfluorodecanethiol. Our resulting superhydrophobic SERS platform demonstrates excellent water-repellency with a static contact angle of 165° ± 9° and a consequent analyte concentration factor of 59-fold, as compared to its hydrophilic counterpart. By combining the analyte concentration effect of superhydrophobic surfaces with the intense electromagnetic "hot spots" of Ag nanocubes, our superhydrophobic SERS platform achieves an ultra-low detection limit of 10(-17) M (10 aM) for rhodamine 6G using just 4 μL of analyte solutions, corresponding to an analytical SERS enhancement factor of 10(13). Our fabrication protocol demonstrates a simple, cost- and time-effective approach for the large-scale fabrication of a superhydrophobic SERS platform for ultratrace molecular detection.

Design of optimal laser pulses to control molecular rovibrational ...

Indian Academy of Sciences (India)

Optimal control theory in combination with time-dependent quantum dynamics is employed to design laser ... area of quantum computing,22 use of molecular states of various systems ..... frequency) and ωv=0, j=1→v=1, j=0, along with small con- tributions from ... discussed here for three rovibrational excitation pro- cesses.

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...

Synthesis of Polyimides in Molecular-Scale Confinement for Low-Density Hybrid Nanocomposites.

Science.gov (United States)

Isaacson, Scott G; Fostvedt, Jade I; Koerner, Hilmar; Baur, Jeffery W; Lionti, Krystelle; Volksen, Willi; Dubois, Geraud; Dauskardt, Reinhold H

2017-11-08

In this work, we exploit a confinement-induced molecular synthesis and a resulting bridging mechanism to create confined polyimide thermoset nanocomposites that couple molecular confinement-enhanced toughening with an unprecedented combination of high-temperature properties at low density. We describe a synthesis strategy that involves the infiltration of individual polymer chains through a nanoscale porous network while simultaneous imidization reactions increase the molecular backbone stiffness. In the extreme limit where the confinement length scale is much smaller than the polymer's molecular size, confinement-induced molecular mechanisms give rise to exceptional mechanical properties. We find that polyimide oligomers can undergo cross-linking reactions even in such molecular-scale confinement, increasing the molecular weight of the organic phase and toughening the nanocomposite through a confinement-induced energy dissipation mechanism. This work demonstrates that the confinement-induced molecular bridging mechanism can be extended to thermoset polymers with multifunctional properties, such as excellent thermo-oxidative stability and high service temperatures (>350 °C).

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

Microelectromechanical systems integrating molecular spin crossover actuators

Energy Technology Data Exchange (ETDEWEB)

Manrique-Juarez, Maria D. [LCC, CNRS and Université de Toulouse, UPS, INP, F-31077 Toulouse (France); LAAS, CNRS and Université de Toulouse, INSA, UPS, F-31077 Toulouse (France); Rat, Sylvain; Salmon, Lionel; Molnár, Gábor; Bousseksou, Azzedine, E-mail: liviu.nicu@laas.fr, E-mail: azzedine.bousseksou@lcc-toulouse.fr [LCC, CNRS and Université de Toulouse, UPS, INP, F-31077 Toulouse (France); Mathieu, Fabrice; Saya, Daisuke; Séguy, Isabelle; Leïchlé, Thierry; Nicu, Liviu, E-mail: liviu.nicu@laas.fr, E-mail: azzedine.bousseksou@lcc-toulouse.fr [LAAS, CNRS and Université de Toulouse, INSA, UPS, F-31077 Toulouse (France)

2016-08-08

Silicon MEMS cantilevers coated with a 200 nm thin layer of the molecular spin crossover complex [Fe(H{sub 2}B(pz){sub 2}){sub 2}(phen)] (H{sub 2}B(pz){sub 2} = dihydrobis(pyrazolyl)borate and phen = 1,10-phenantroline) were actuated using an external magnetic field and their resonance frequency was tracked by means of integrated piezoresistive detection. The light-induced spin-state switching of the molecules from the ground low spin to the metastable high spin state at 10 K led to a well-reproducible shift of the cantilever's resonance frequency (Δf{sub r} = −0.52 Hz). Control experiments at different temperatures using coated as well as uncoated devices along with simple calculations support the assignment of this effect to the spin transition. This latter translates into changes in mechanical behavior of the cantilever due to the strong spin-state/lattice coupling. A guideline for the optimization of device parameters is proposed so as to efficiently harness molecular scale movements for large-scale mechanical work, thus paving the road for nanoelectromechanical systems (NEMS) actuators based on molecular materials.

Genetic Spot Optimization for Peak Power Estimation in Large VLSI Circuits

Directory of Open Access Journals (Sweden)

Michael S. Hsiao

2002-01-01

Full Text Available Estimating peak power involves optimization of the circuit's switching function. The switching of a given gate is not only dependent on the output capacitance of the node, but also heavily dependent on the gate delays in the circuit, since multiple switching events can result from uneven circuit delay paths in the circuit. Genetic spot expansion and optimization are proposed in this paper to estimate tight peak power bounds for large sequential circuits. The optimization spot shifts and expands dynamically based on the maximum power potential (MPP of the nodes under optimization. Four genetic spot optimization heuristics are studied for sequential circuits. Experimental results showed an average of 70.7% tighter peak power bounds for large sequential benchmark circuits was achieved in short execution times.

Centralized manure digestion. Selection of locations and estimation of costs of large-scale manure storage application

International Nuclear Information System (INIS)

1995-03-01

A study to assess the possibilities and the consequences of the use of existing Dutch large scale manure silos at centralised anaerobic digestion plants (CAD-plants) for manure and energy-rich organic wastes is carried out. Reconstruction of these large scale manure silos into digesters for a CAD-plant is not self-evident due to the high height/diameter ratio of these silos and the extra investments that have to be made for additional facilities for roofing, insulation, mixing and heating. From the results of an inventory and selection of large scale manure silos with a storage capacity above 1,500 m 3 it appeared that there are 21 locations in The Netherlands that can be qualified for realisation of a CAD plant with a processing capacity of 100 m 3 biomass (80% manure, 20% additives) per day. These locations are found in particular at the 'shortage-areas' for manure fertilisation in the Dutch provinces Groningen and Drenthe. Three of these 21 locations with large scale silos are considered to be the most suitable for realisation of a large scale CAD-plant. The selection is based on an optimal scale for a CAD-plant of 300 m 3 material (80% manure, 20% additives) to be processed per day and the most suitable consuming markets for the biogas produced at the CAD-plant. The three locations are at Middelharnis, Veendam, and Klazinaveen. Applying the conditions as used in this study and accounting for all costs for transport of manure, additives and end-product including the costs for the storage facilities, a break-even operation might be realised at a minimum income for the additives of approximately 50 Dutch guilders per m 3 (including TAV). This income price is considerably lower than the prevailing costs for tipping or processing of organic wastes in The Netherlands. This study revealed that a break-even exploitation of a large scale CAD-plant for the processing of manure with energy-rich additives is possible. (Abstract Truncated)

Robustizing Circuit Optimization using Huber Functions

DEFF Research Database (Denmark)

Bandler, John W.; Biernacki, Radek M.; Chen, Steve H.

1993-01-01

The authors introduce a novel approach to 'robustizing' microwave circuit optimization using Huber functions, both two-sided and one-sided. They compare Huber optimization with l/sub 1/, l/sub 2/, and minimax methods in the presence of faults, large and small measurement errors, bad starting poin......, a preliminary optimization by selecting a small number of dominant variables. It is demonstrated, through multiplexer optimization, that the one-sided Huber function can be more effective and efficient than minimax in overcoming a bad starting point.......The authors introduce a novel approach to 'robustizing' microwave circuit optimization using Huber functions, both two-sided and one-sided. They compare Huber optimization with l/sub 1/, l/sub 2/, and minimax methods in the presence of faults, large and small measurement errors, bad starting points......, and statistical uncertainties. They demonstrate FET statistical modeling, multiplexer optimization, analog fault location, and data fitting. They extend the Huber concept by introducing a 'one-sided' Huber function for large-scale optimization. For large-scale problems, the designer often attempts, by intuition...

Traffic Flow Prediction Model for Large-Scale Road Network Based on Cloud Computing

Directory of Open Access Journals (Sweden)

Zhaosheng Yang

2014-01-01

Full Text Available To increase the efficiency and precision of large-scale road network traffic flow prediction, a genetic algorithm-support vector machine (GA-SVM model based on cloud computing is proposed in this paper, which is based on the analysis of the characteristics and defects of genetic algorithm and support vector machine. In cloud computing environment, firstly, SVM parameters are optimized by the parallel genetic algorithm, and then this optimized parallel SVM model is used to predict traffic flow. On the basis of the traffic flow data of Haizhu District in Guangzhou City, the proposed model was verified and compared with the serial GA-SVM model and parallel GA-SVM model based on MPI (message passing interface. The results demonstrate that the parallel GA-SVM model based on cloud computing has higher prediction accuracy, shorter running time, and higher speedup.

Particle physics and polyedra proximity calculation for hazard simulations in large-scale industrial plants

Science.gov (United States)

Plebe, Alice; Grasso, Giorgio

2016-12-01

This paper describes a system developed for the simulation of flames inside an open-source 3D computer graphic software, Blender, with the aim of analyzing in virtual reality scenarios of hazards in large-scale industrial plants. The advantages of Blender are of rendering at high resolution the very complex structure of large industrial plants, and of embedding a physical engine based on smoothed particle hydrodynamics. This particle system is used to evolve a simulated fire. The interaction of this fire with the components of the plant is computed using polyhedron separation distance, adopting a Voronoi-based strategy that optimizes the number of feature distance computations. Results on a real oil and gas refining industry are presented.

Concepts and Plans towards fast large scale Monte Carlo production for the ATLAS Experiment

Science.gov (United States)

Ritsch, E.; Atlas Collaboration

2014-06-01

The huge success of the physics program of the ATLAS experiment at the Large Hadron Collider (LHC) during Run 1 relies upon a great number of simulated Monte Carlo events. This Monte Carlo production takes the biggest part of the computing resources being in use by ATLAS as of now. In this document we describe the plans to overcome the computing resource limitations for large scale Monte Carlo production in the ATLAS Experiment for Run 2, and beyond. A number of fast detector simulation, digitization and reconstruction techniques are being discussed, based upon a new flexible detector simulation framework. To optimally benefit from these developments, a redesigned ATLAS MC production chain is presented at the end of this document.

Cost Optimal Elastic Auto-Scaling in Cloud Infrastructure

Science.gov (United States)

Mukhopadhyay, S.; Sidhanta, S.; Ganguly, S.; Nemani, R. R.

2014-12-01

Today, elastic scaling is critical part of leveraging cloud. Elastic scaling refers to adding resources only when it is needed and deleting resources when not in use. Elastic scaling ensures compute/server resources are not over provisioned. Today, Amazon and Windows Azure are the only two platform provider that allow auto-scaling of cloud resources where servers are automatically added and deleted. However, these solution falls short of following key features: A) Requires explicit policy definition such server load and therefore lacks any predictive intelligence to make optimal decision; B) Does not decide on the right size of resource and thereby does not result in cost optimal resource pool. In a typical cloud deployment model, we consider two types of application scenario: A. Batch processing jobs → Hadoop/Big Data case B. Transactional applications → Any application that process continuous transactions (Requests/response) In reference of classical queuing model, we are trying to model a scenario where servers have a price and capacity (size) and system can add delete servers to maintain a certain queue length. Classical queueing models applies to scenario where number of servers are constant. So we cannot apply stationary system analysis in this case. We investigate the following questions 1. Can we define Job queue and use the metric to define such a queue to predict the resource requirement in a quasi-stationary way? Can we map that into an optimal sizing problem? 2. Do we need to get into a level of load (CPU/Data) on server level to characterize the size requirement? How do we learn that based on Job type?

Plasmonic nanoparticle lithography: Fast resist-free laser technique for large-scale sub-50 nm hole array fabrication

Science.gov (United States)

Pan, Zhenying; Yu, Ye Feng; Valuckas, Vytautas; Yap, Sherry L. K.; Vienne, Guillaume G.; Kuznetsov, Arseniy I.

2018-05-01

Cheap large-scale fabrication of ordered nanostructures is important for multiple applications in photonics and biomedicine including optical filters, solar cells, plasmonic biosensors, and DNA sequencing. Existing methods are either expensive or have strict limitations on the feature size and fabrication complexity. Here, we present a laser-based technique, plasmonic nanoparticle lithography, which is capable of rapid fabrication of large-scale arrays of sub-50 nm holes on various substrates. It is based on near-field enhancement and melting induced under ordered arrays of plasmonic nanoparticles, which are brought into contact or in close proximity to a desired material and acting as optical near-field lenses. The nanoparticles are arranged in ordered patterns on a flexible substrate and can be attached and removed from the patterned sample surface. At optimized laser fluence, the nanohole patterning process does not create any observable changes to the nanoparticles and they have been applied multiple times as reusable near-field masks. This resist-free nanolithography technique provides a simple and cheap solution for large-scale nanofabrication.

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.

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.

Optimization and analysis of large chemical kinetic mechanisms using the solution mapping method - Combustion of methane

Science.gov (United States)

Frenklach, Michael; Wang, Hai; Rabinowitz, Martin J.

1992-01-01

A method of systematic optimization, solution mapping, as applied to a large-scale dynamic model is presented. The basis of the technique is parameterization of model responses in terms of model parameters by simple algebraic expressions. These expressions are obtained by computer experiments arranged in a factorial design. The developed parameterized responses are then used in a joint multiparameter multidata-set optimization. A brief review of the mathematical background of the technique is given. The concept of active parameters is discussed. The technique is applied to determine an optimum set of parameters for a methane combustion mechanism. Five independent responses - comprising ignition delay times, pre-ignition methyl radical concentration profiles, and laminar premixed flame velocities - were optimized with respect to thirteen reaction rate parameters. The numerical predictions of the optimized model are compared to those computed with several recent literature mechanisms. The utility of the solution mapping technique in situations where the optimum is not unique is also demonstrated.

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.

Minimum scale controlled topology optimization and experimental test of a micro thermal actuator

DEFF Research Database (Denmark)

Heo, S.; Yoon, Gil Ho; Kim, Y.Y.

2008-01-01

This paper is concerned with the optimal topology design, fabrication and test of a micro thermal actuator. Because the minimum scale was controlled during the design optimization process, the production yield rate of the actuator was improved considerably; alternatively, the optimization design ...... tested. The test showed that control over the minimum length scale in the design process greatly improves the yield rate and reduces the performance deviation....... without scale control resulted in a very low yield rate. Using the minimum scale controlling topology design method developed earlier by the authors, micro thermal actuators were designed and fabricated through a MEMS process. Moreover, both their performance and production yield were experimentally...

Optimization and scale up of microfluidic nanolipomer production method for preclinical and potential clinical trials.

Science.gov (United States)

Gdowski, Andrew; Johnson, Kaitlyn; Shah, Sunil; Gryczynski, Ignacy; Vishwanatha, Jamboor; Ranjan, Amalendu

2018-02-12

synthesized and easily scaled up through a high flow microfluidic system with optimal characteristics. The process of developing nanolipomers using this methodology is significant as the same optimized parameters used for small batches could be translated into manufacturing large scale batches for clinical trials through parallel flow systems.

Microsecond atomic-scale molecular dynamics simulations of polyimides

NARCIS (Netherlands)

Lyulin, S.V.; Gurtovenko, A.A.; Larin, S.V.; Nazarychev, V.M.; Lyulin, A.V.

2013-01-01

We employ microsecond atomic-scale molecular dynamics simulations to get insight into the structural and thermal properties of heat-resistant bulk polyimides. As electrostatic interactions are essential for the polyimides considered, we propose a two-step equilibration protocol that includes long

Off-Policy Reinforcement Learning: Optimal Operational Control for Two-Time-Scale Industrial Processes.

Science.gov (United States)

Li, Jinna; Kiumarsi, Bahare; Chai, Tianyou; Lewis, Frank L; Fan, Jialu

2017-12-01

Industrial flow lines are composed of unit processes operating on a fast time scale and performance measurements known as operational indices measured at a slower time scale. This paper presents a model-free optimal solution to a class of two time-scale industrial processes using off-policy reinforcement learning (RL). First, the lower-layer unit process control loop with a fast sampling period and the upper-layer operational index dynamics at a slow time scale are modeled. Second, a general optimal operational control problem is formulated to optimally prescribe the set-points for the unit industrial process. Then, a zero-sum game off-policy RL algorithm is developed to find the optimal set-points by using data measured in real-time. Finally, a simulation experiment is employed for an industrial flotation process to show the effectiveness of the proposed method.

Parallel low-memory quasi-Newton optimization algorithm for molecular structure