PSAM 16 Conference Paper Overview
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Lead Author: Ahmad Al Rashdan
| Mapping inspection procedure requirements into data metrics for automation-assisted inspection preparation |
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| In the nuclear industry, regulatory compliance activities constitute an appreciable portion of a nuclear plant's data collection and analysis efforts, and therefore represent a significant portion of a nuclear utility operations and maintenance budget, with regulatory inspections as a major component. These inspections involve many different types of information needed by the U.S. Nuclear Regulatory Commission’s (NRC) Reactor Oversight Program. The Department of Energy’s Light Water Reactor Sustainability (LWRS) program launched an effort to automate data collection and analysis for regulatory inspection preparation. The effort would also assess the ability of automation technologies to provide potentially more efficient means for nuclear utilities to verify and demonstrate regulatory compliance. A key aspect of automating this process is to convert plant performance related to each of the inspection requirements into quantifiable data metrics. The development of those data metrics is discussed using the NRC problem identification and resolution inspection as a use case. |
Paper AH327 Preview
Author and Presentation Info
Presentation only, a full paper is not available.
Lead Author Name: Ahmad Al Rashdan (ahmad.alrashdan@inl.gov)
Bio: Ahmad Al Rashdan, Ph.D., is currently a senior research and development scientist at INL. Dr. Al Rashdan holds a Ph.D. in nuclear engineering from Texas A&M University, a M.Sc. in information technology and automation systems from Esslingen University of Applied Science in Germany, and a B.Sc. in mechanical engineering from Jordan University of Science and Technology in Jordan. He has more than 15 years of industrial and research experience. His experience includes automated work processes using AI methods and advanced analytics, online condition monitoring of nuclear systems, control-systems design and development, anomalies detection, and automated modeling and simulation. Dr. Al Rashdan is an active contributor to and organizer of several DOE events and scientific conferences. He authored or co-authored more than 60 technical reports and journal papers and 7 patent applications and is a senior member of the IEEE and a member of the American Nuclear Society.
Country: United States of America
Company: Idaho National Laboratory
Job Title: Senior Research and Development Scientist
Bio: Ahmad Al Rashdan, Ph.D., is currently a senior research and development scientist at INL. Dr. Al Rashdan holds a Ph.D. in nuclear engineering from Texas A&M University, a M.Sc. in information technology and automation systems from Esslingen University of Applied Science in Germany, and a B.Sc. in mechanical engineering from Jordan University of Science and Technology in Jordan. He has more than 15 years of industrial and research experience. His experience includes automated work processes using AI methods and advanced analytics, online condition monitoring of nuclear systems, control-systems design and development, anomalies detection, and automated modeling and simulation. Dr. Al Rashdan is an active contributor to and organizer of several DOE events and scientific conferences. He authored or co-authored more than 60 technical reports and journal papers and 7 patent applications and is a senior member of the IEEE and a member of the American Nuclear Society.
Country: United States of America
Company: Idaho National Laboratory
Job Title: Senior Research and Development Scientist