Batten Chair Speaker Series: Dr. Timashev, Nobel Prize Recipient
The Batten Chair in Systems Engineering is honored to invite everyone to the inaugural presentation of the Batten Chair in Systems Engineering Speaker Series.
We are proud to have Professor Sviatoslav Timashev as the first presenter in the series. Dr. Timashev holds a Research Professorship in the Engineering Management and Systems Engineering department at ODU, and is affiliated with the Russain Academy of Sciences, and the Ural Federal University. He is a member of the Intergovernmental Panel on Climate Change that was awarded the Nobel Prize in 2007 (See https://www.odu.edu/news/2016/7/timashev_appointment#.WEWwQ3fGxBw for additional details).
Dr. Timashev is collaborating with Dr. Gheorghe and other faculty in the Batten College of Engineering and Technology to develop expertise in the area of predictive maintenance.
The paper describes the methodology developed by the authors of a holistic innovative approach to ILI data generation and data management, which dramatically increases ILI inspection capabilities [9]. This methodology to a large extent decreases the existing uncertainties, minimizes scatter of the input parameters and thereby, makes predictions based on ILI data less conservative. As a result, all this permits generating safe solutions and avoiding dangerous errors in predictions which involve assessment of pipeline inspection frequency and safety margin.
According to the API 1163 Standard, the ILI measurement results are characterized by three parameters of statistical nature: tolerance, certainty, and the confidence level. Tolerance is the range with which an anomaly dimension or characteristic is sized or characterized. Certainty is the probability that a reported anomaly characteristic is within a stated tolerance. Confidence level (CL) is a statistical term used to describe the mathematical certainty with which a statement is made. CL indicates the confidence with which the tolerance and certainty levels are satisfied. The paper discusses the statistical sources of these probabilities and how they should be interpreted and handled.
Paper contains recommendations on how to approach different practical problems and illustrates each case with real life examples.
Posted By: Andres Sousa-Poza
Date: Mon Dec 05 14:23:08 EST 2016