180,079 research outputs found
Analysis and Estimation of the Maximum Switch Current during Battery System Reconfiguration
Batteries are interconnected in series and/or parallel to meet wide-range power or energy demands in various industrial applications. To pursue the benefits of multiple connection structures in one system, reconfigurable battery systems (RBSs) have recently emerged for safe and efficient operation, extended energy storage and delivery, etc. Switches are the essential elements to enable the battery system reconfiguration, but selecting appropriate switches for RBS designs has not been systematically investigated. To bridge this gap, analytical expressions are derived in this paper to estimate the maximum switch current and its upper limit to facilitate the selection of RBS switches. An RBS prototype based on H-bridges is set up and experimental results verify the effectiveness and advantage of the proposed estimation method. These analytical expressions, relying only on resistances of batteries and switches, are readily applicable to practical RBS design and much more efficient than conducting numerous circuit experiments, simulation tests, or circuit analyses, especially for large-scale systems. Moreover, the analysis framework and estimation method proposed for series-parallel mutual conversion can be adaptively extended to other complex system reconfigurations to facilitate various RBS designs
CMS Monte Carlo production in the WLCG computing Grid
Monte Carlo production in CMS has received a major boost in performance and
scale since the past CHEP06 conference. The production system has been re-engineered in order
to incorporate the experience gained in running the previous system and to integrate production
with the new CMS event data model, data management system and data processing framework.
The system is interfaced to the two major computing Grids used by CMS, the LHC Computing
Grid (LCG) and the Open Science Grid (OSG).
Operational experience and integration aspects of the new CMS Monte Carlo production
system is presented together with an analysis of production statistics. The new system
automatically handles job submission, resource monitoring, job queuing, job distribution
according to the available resources, data merging, registration of data into the data
bookkeeping, data location, data transfer and placement systems. Compared to the previous
production system automation, reliability and performance have been considerably improved. A
more efficient use of computing resources and a better handling of the inherent Grid unreliability
have resulted in an increase of production scale by about an order of magnitude, capable of
running in parallel at the order of ten thousand jobs and yielding more than two million events
per day
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