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Division Spotlight
Robotics & Remote Systems
The Mission of the Robotics and Remote Systems Division is to promote the development and application of immersive simulation, robotics, and remote systems for hazardous environments for the purpose of reducing hazardous exposure to individuals, reducing environmental hazards and reducing the cost of performing work.
Meeting Spotlight
2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Latest News
NWMO to select Canadian repository site this year
Canada’s Nuclear Waste Management Organization, a not-for-profit organization responsible for the long-term management of the country’s intermediate- and high-level radioactive waste, is set to select a site for a deep geologic repository by the end of the year.
Ahmad Al Rashdan, Shawn St. Germain
Nuclear Technology | Volume 205 | Number 8 | August 2019 | Pages 1062-1074
Rapid Communication – Special section on Big Data for Nuclear Power Plants | doi.org/10.1080/00295450.2019.1610637
Articles are hosted by Taylor and Francis Online.
The operations and maintenance monitoring of nuclear power plants (NPPs) in the United States is reliant on manual activities supplying information to a human decision-making process. Several manually collected labor-intensive processes generate information that is not typically used beyond the intended target for collecting that information. The industry has recognized the benefits of both reducing labor-intensive tasks by automating them and increasing the fidelity of the information collected to enable advanced remote monitoring of NPPs using data-driven decision making. This requires developing new means to acquire data from the various data sources of an NPP. While some sources already exist in a digital form, others are collected manually, summarized through conclusive statements, or not collected at all. This paper describes 15 sources of data at an NPP and methods to migrate the data collection from a manual and analog data form to an automated and digital data form that increases the data fidelity in time and space. Three states of data collection methods are described for each data source. The states describe a base state for how the data are currently being collected, a modern state for a more efficient method of collecting data that has not yet been implemented, and a state of the art for an advanced method of collecting data that is not yet ready for deployment.