scholarly journals Detection and Location of Damage on Pipelines

Author(s):  
Karen A. Moore ◽  
Robert Carrington ◽  
John Richardson

The U.S. Dept of Energy Idaho National Engineering and Environmental Laboratory (INEEL) has developed and successfully tested a real-time pipeline damage detection and location system. This system uses porous metal resistive traces applied to the pipe to detect and locate damage. The porous metal resistive traces are sprayed along the length of a pipeline. The unique nature and arrangement of the traces allows locating the damage in real time along miles of pipe. This system allows pipeline operators to detect damage when and where it is occurring, and the decision to shut down a transmission pipeline can be made with actual real-time data, instead of conservative estimates from visual inspection above the area.

Author(s):  
H. H. Shih ◽  
James Sprenke ◽  
David Trombley ◽  
John Cassidy ◽  
Tom Mero

The U.S. National Ocean Service (NOS) of NOAA maintains and operates a Physical Oceanography Real Time System (PORTS®) in the Nation’s major ports, harbors and bays. The traditional method of obtaining real-time data from bottom mounted instruments is via underwater cable link. However, this is vulnerable to damage and costly to install and maintain. This paper describes an approach utilizing acoustic and Iridium satellite links to report in real-time wave and current data. The system consists of an ocean bottom instrumentation platform and a U.S. Coast Guard Aid-to-Navigation buoy for data relay. The bottom platform contains a Nortek 1 MHz Acoustic Wave and Current profiler (AWAC) with an integrated Nortek Internal Processor (NIP), a LinkQuest omni-directional UWM2000H underwater acoustic transmitting modem, an ORE acoustic release-based recovery component, and a Teledyne-Benthos UAT-376/EL acoustic transponder. The surface buoy supports an omni-directional UWM2000H receiving modem, an Iridium antenna, and an electronic box containing an Iridium modem, a controller, battery packs, and temperature and voltage sensors. The AWAC measures current profiles along the vertical water column at 30-minute intervals and surface waves at hourly intervals. The NIP processes a set of user selected wave and current parameters and sends these data to the controller on the surface buoy through acoustic modems. The data are then transmitted via Iridium satellite to remote offices in real-time. Sample measurement results and reference data from a near-by Datawell’s Waverider directional wave buoy are presented. The Waverider is operated by the U.S. Army Corps of Engineers (USACE) and Scripps Institution of Oceanography (SIO). Several unique system design features and interesting wave phenomenon observed at the measurement site are discussed. The goal of this project is to demonstrate the performance of AWAC, NIP, shallow water acoustic modems, and Iridium satellite in real-time data telemetry.


Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 399-P
Author(s):  
ANN MARIE HASSE ◽  
RIFKA SCHULMAN ◽  
TORI CALDER

2021 ◽  
Vol 31 (6) ◽  
pp. 7-7
Author(s):  
Valerie A. Canady
Keyword(s):  

Author(s):  
Yu-Hsiang Wu ◽  
Jingjing Xu ◽  
Elizabeth Stangl ◽  
Shareka Pentony ◽  
Dhruv Vyas ◽  
...  

Abstract Background Ecological momentary assessment (EMA) often requires respondents to complete surveys in the moment to report real-time experiences. Because EMA may seem disruptive or intrusive, respondents may not complete surveys as directed in certain circumstances. Purpose This article aims to determine the effect of environmental characteristics on the likelihood of instances where respondents do not complete EMA surveys (referred to as survey incompletion), and to estimate the impact of survey incompletion on EMA self-report data. Research Design An observational study. Study Sample Ten adults hearing aid (HA) users. Data Collection and Analysis Experienced, bilateral HA users were recruited and fit with study HAs. The study HAs were equipped with real-time data loggers, an algorithm that logged the data generated by HAs (e.g., overall sound level, environment classification, and feature status including microphone mode and amount of gain reduction). The study HAs were also connected via Bluetooth to a smartphone app, which collected the real-time data logging data as well as presented the participants with EMA surveys about their listening environments and experiences. The participants were sent out to wear the HAs and complete surveys for 1 week. Real-time data logging was triggered when participants completed surveys and when participants ignored or snoozed surveys. Data logging data were used to estimate the effect of environmental characteristics on the likelihood of survey incompletion, and to predict participants' responses to survey questions in the instances of survey incompletion. Results Across the 10 participants, 715 surveys were completed and survey incompletion occurred 228 times. Mixed effects logistic regression models indicated that survey incompletion was more likely to happen in the environments that were less quiet and contained more speech, noise, and machine sounds, and in the environments wherein directional microphones and noise reduction algorithms were enabled. The results of survey response prediction further indicated that the participants could have reported more challenging environments and more listening difficulty in the instances of survey incompletion. However, the difference in the distribution of survey responses between the observed responses and the combined observed and predicted responses was small. Conclusion The present study indicates that EMA survey incompletion occurs systematically. Although survey incompletion could bias EMA self-report data, the impact is likely to be small.


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