2,162 research outputs found

    Down Time Terms and Information Used for Assessment of Equipment Reliability and Maintenance Performance

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    Reliability and maintenance data is important for predictive analysis related to equipment downtime in the oil and gas industry. For example, downtime data together with equipment reliability data is vital for improving system designs, for optimizing maintenance and in estimating the potential for hazardous events that could harm both people and the environment. The quality is largely influenced by the repair time taxonomy, such as the measures used to define downtime linked to equipment failures. However, although it is important to achieve high quality from maintenance operations as part of this picture, these often seem to receive less focus compared to reliability aspects. Literature and experiences from, e.g., the OREDA project suggest several challenging issues, which we discuss in this chapter, e.g., for the interpretation of “MTTR.” Another challenge relates to the duration of maintenance activities. For example, while performing corrective maintenance on an item, one could also be working on several other items while being on site. This provides an opening for different ways of recording the mobilization time and repair time, which may then influence the data used for predictive analysis. Some relevant examples are included to illustrate some of the challenges posed, and some remedial actions are proposed

    The Surface Brightness Fluctuations and Globular Cluster Populations of M87 and its Companions

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    Using the surface brightness fluctuations in HST WFPC-2 images, we determine that M87, NGC 4486B, and NGC 4478 are all at a distance of ~16 Mpc, while NGC 4476 lies in the background at ~21 Mpc. We also examine the globular clusters of M87 using archived HST fields. We detect the bimodal color distribution, and find that the amplitude of the red peak relative to the blue peak is greatest near the center. This feature is in good agreement with the merger model of elliptical galaxy formation, where some of the clusters originated in progenitor galaxies while other formed during mergers.Comment: 5 pages, 2 figure

    A Search for Exozodiacal Clouds with Kepler

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    Planets embedded within dust disks may drive the formation of large scale clumpy dust structures by trapping dust into resonant orbits. Detection and subsequent modeling of the dust structures would help constrain the mass and orbit of the planet and the disk architecture, give clues to the history of the planetary system, and provide a statistical estimate of disk asymmetry for future exoEarth-imaging missions. Here we present the first search for these resonant structures in the inner regions of planetary systems by analyzing the light curves of hot Jupiter planetary candidates identified by the Kepler mission. We detect only one candidate disk structure associated with KOI 838.01 at the 3-sigma confidence level, but subsequent radial velocity measurements reveal that KOI 838.01 is a grazing eclipsing binary and the candidate disk structure is a false positive. Using our null result, we place an upper limit on the frequency of dense exozodi structures created by hot Jupiters. We find that at the 90% confidence level, less than 21% of Kepler hot Jupiters create resonant dust clumps that lead and trail the planet by ~90 degrees with optical depths >~5*10^-6, which corresponds to the resonant structure expected for a lone hot Jupiter perturbing a dynamically cold dust disk 50 times as dense as the zodiacal cloud.Comment: 22 pages, 6 figures, Accepted for publication in Ap
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