4,328 research outputs found
-vector meson elliptic flow () in collisions at GeV in STAR at RHIC
The first measurement of the - vector meson elliptic flow
at mid-rapidity ( 0.5) in centrality in
collisions at GeV from the STAR experiment at RHIC is
presented. The study is through the hadronic decay channel of
which has a branching ratio of 100 %. The analysis is being
carried out in two different methods. The results obtained in these
methods are consistent. Number of Constituent Quark (NCQ) scaling of of
meson with respect to other hadrons at intermediate is
observed. The favors scaling, supporting the
coalescence being the dominant mechanism of hadronization in the intermediate
region at RHIC.Comment: 4 pages, 6 figures, proceeding for the 6th International Conference
on Physics and Astrophysics of Quark Gluon Plasma (ICPAQGP 2010
A Model of Inter-Regional Trade in Grains with Storage
When there is spatial arbitrage between food markets, the price differential between the markets should equal the cost of transfer. This simple arbitrage rule has formed the basis of many empirical tests of the performance of developing countries’ food markets. Here, a more complex structure to regional food markets is hypothesised. By including commodity storage into a model of inter-regional trade, it is shown that, in an optimal dynamic program, trade is intermittent. The possibility of periods without trade casts doubt on the validity of using tests for correlation in market prices as indicators of market performance.Food markets, optimal control, storage, spatial equilibrium.
New directions for Artificial Intelligence (AI) methods in optimum design
Developments and applications of artificial intelligence (AI) methods in the design of structural systems is reviewed. Principal shortcomings in the current approach are emphasized, and the need for some degree of formalism in the development environment for such design tools is underscored. Emphasis is placed on efforts to integrate algorithmic computations in expert systems
SRAT-Distribution Voltage Sags and Reliability Assessment Tool
Interruptions to supply and sags of distribution system voltage are the main aspects causing customer complaints. There is a need for analysis of supply reliability and voltage sag to relate system performance with network structure and equipment design parameters. This analysis can also give prediction of voltage dips, as well as relating traditional reliability and momentary outage measures to the properties of protection systems and to network impedances. Existing reliability analysis software often requires substantial training, lacks automated facilities, and suffers from data availability. Thus it requires time-consuming manual intervention for the study of large networks. A user-friendly sag and reliability assessment tool (SRAT) has been developed based on existing impedance data, protection characteristics, and a model of failure probability. The new features included in SRAT are a) efficient reliability and sag assessments for a radial network with limited loops, b) reliability evaluation associated with realistic protection and restoration schemes, c) inclusion of momentary outages in the same model as permanent outage evaluation, d) evaluation of the sag transfer through meshed subtransmission network, and e) simplified probability distribution model determined from available faults records. Examples of the application of the tools to an Australian distribution network are used to illustrate the application of this model
Applications of artificial neural nets in structural mechanics
A brief introduction to the fundamental of Neural Nets is given, followed by two applications in structural optimization. In the first case, the feasibility of simulating with neural nets the many structural analyses performed during optimization iterations was studied. In the second case, the concept of using neural nets to capture design expertise was studied
An Assessment of Data Transfer Performance for Large-Scale Climate Data Analysis and Recommendations for the Data Infrastructure for CMIP6
We document the data transfer workflow, data transfer performance, and other
aspects of staging approximately 56 terabytes of climate model output data from
the distributed Coupled Model Intercomparison Project (CMIP5) archive to the
National Energy Research Supercomputing Center (NERSC) at the Lawrence Berkeley
National Laboratory required for tracking and characterizing extratropical
storms, a phenomena of importance in the mid-latitudes. We present this
analysis to illustrate the current challenges in assembling multi-model data
sets at major computing facilities for large-scale studies of CMIP5 data.
Because of the larger archive size of the upcoming CMIP6 phase of model
intercomparison, we expect such data transfers to become of increasing
importance, and perhaps of routine necessity. We find that data transfer rates
using the ESGF are often slower than what is typically available to US
residences and that there is significant room for improvement in the data
transfer capabilities of the ESGF portal and data centers both in terms of
workflow mechanics and in data transfer performance. We believe performance
improvements of at least an order of magnitude are within technical reach using
current best practices, as illustrated by the performance we achieved in
transferring the complete raw data set between two high performance computing
facilities. To achieve these performance improvements, we recommend: that
current best practices (such as the Science DMZ model) be applied to the data
servers and networks at ESGF data centers; that sufficient financial and human
resources be devoted at the ESGF data centers for systems and network
engineering tasks to support high performance data movement; and that
performance metrics for data transfer between ESGF data centers and major
computing facilities used for climate data analysis be established, regularly
tested, and published
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