99,631 research outputs found
Quench characteristics of a Cu-Stabilized 2G HTS conductor
No full textThe prospect of medium/high field superconducting magnets using 2G HTS tapes is approaching to reality with continued enhancement in the performance of these conductors. Direct measurements of 1d adiabatic quench initiation and propagation of a Cu-stabilized 2G conductor have been carried out with spatial-temporal recording of temperature and voltage following the deposition of various local heat pulses to the conductor at different temperatures between 40K and 64K carrying different transport currents. It was found that the stabilizer-free 2G tape maintains the unique characteristics previously measured in non-stabilized tape of increasing MPZ with transport current and higher quench energy at lower temperatures. The minimum quench energy, minimum propagation zone (MPZ) length are determined as a function of temperature and transport current. The change in MPZ size is investigated with measured temperature dependent E-J characteristics. The results add more detail to help understand the unique characteristics of increasing MPZ with transport current and lower temperatures
Abstraction Refinement Guided by a Learnt Probabilistic Model
Full text linkThe core challenge in designing an effective static program analysis is to find a good program abstraction -- one that retains only details relevant to a given query. In this paper, we present a new approach for automatically finding such an abstraction. Our approach uses a pessimistic strategy, which can optionally use guidance from a probabilistic model. Our approach applies to parametric static analyses implemented in Datalog, and is based on counterexample-guided abstraction refinement. For each untried abstraction, our probabilistic model provides a probability of success, while the size of the abstraction provides an estimate of its cost in terms of analysis time. Combining these two metrics, probability and cost, our refinement algorithm picks an optimal abstraction. Our probabilistic model is a variant of the Erdos-Renyi random graph model, and it is tunable by what we call hyperparameters. We present a method to learn good values for these hyperparameters, by observing past runs of the analysis on an existing codebase. We evaluate our approach on an object sensitive pointer analysis for Java programs, with two client analyses (PolySite and Downcast)
Geometric Nonlinear Analysis of Cable Structures with a Two-Node Cable Element by Generalized Displacement Control Method
No full textWind-Induced Aerostatic Instability of Cable-Supported Bridges by a Two-Stage Geometric Nonlinear Analysis
No full textTransmission of Vibrations from High Speed Trains Through Viaducts and Foundations to the Ground
No full textAerodynamic Instability of Cable-Stayed Bridges Considering the Initial Deformed Shape Due to Dead Loads
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On super form factors of half-BPS operators in N=4 super Yang-Mills
Full text linkOpen Access, (c) The Authors. Article funded by SCOAP3. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits any use, distribution and reproduction in any medium, provided the original author(s) and source are credited
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