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Machine Intelligence Review Analysis Condition Logs Entries (MIRACLE)

February 2022

MIRACLE is an artificial intelligence tool for automated condition report review and analysis. It uses natural language processing and machine learning techniques to rapidly scan through reports, analyzing their information to make in fractions of a second key decisions that are currently performed in hours by plant staff. In addition to making the process much more efficient, MIRACLE reduces human error and, therefore, further improves the industry’s excellent safety record.

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Route-Operable Unmanned Navigation of Drones (ROUNDS)

November 2020

The LWRS Program recognizes the potential for drones to automate rounds in a nuclear power plant and developed a cost-effective method for drones to navigate a course inside a building or other structures where strong GPS signals are absent. Self-navigation is achieved by determining the drone’s location from the visual angle of QR cod​e​s placed along the desired course, then dynamically adjusting trajectory accordingly. ​

November 2019

The Light Water Reactor Sustainability (LWRS) Program conducts research to develop technologies and other solutions to improve the economics and reliability, sustain the safety, and extend the operation of our nation’s fleet of nuclear power plants. It has two objectives with respect to long-term operations: (1) to provide science and technology-based solutions to industry to overcome the current labor-intensive business model and associated practices; and (2) to manage the aging of systems, structures, and components (SSCs) so nuclear power plants can continue to operate safely and cost effectively.

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LWRS Program collaborates with Palo Verde

December 2018

The LWRS Program collaborates with Palo Verde to support control room modernization in a nuclear power plant, addressing equipment issues and the benefit of improved performance with people who operate and maintain the plant. One goal is to make the plants more economically competitive while maintaining safety and reliability.

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Palo Verde Nuclear Generating Station control room modernization

July 2018

Using animated 3D modeling technology, this video presents a fly-through tour of a proposed concept for a modernized control room for the Palo Verde Nuclear Generating Station, depicting how the current analog-based control boards are transformed into modern digital operator control stations.

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Human Systems Simulation Laboratory Demonstration (HSSL)

June 2018

The HSSL is a complete virtual nuclear control room created to safely test new technologies before they are implemented in commercial reactor control rooms. LWRS Program researchers use the HSSL to conduct human factors engineering research and development in order to enhance plant safety and human-system performance.

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Concrete testing

October 2016​

This video highlights the launch of a long-term concrete aging study for the Materials Research Pathway performed by the University of Tennessee and Oak Ridge National Laboratory.

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Wireless component position indication

July 2015

Simulating an error-prone manual valve alignment task in a nuclear power plant, this video illustrates how new technology for wireless component position indication can monitor the results of valve manipulations, detect positioning errors, and instruct the operators to correct such errors before they result in operational events, thus preventing nuclear safety challenges and loss of generation.
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Online power plant health monitoring

February 2015

The LWRS Program has been instrumental in developing and validating diagnostic and prognostic models for on-line monitoring of active components in nuclear power plants. This work was done in collaboration with the Electric Power Research Institute (EPRI) in support of its Fleet-Wide Plant Health Monitoring (FW-PHM) monitoring platform.

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Advanced Outage Control Center Prairie

December 2014

The LWRS Program produced a concept video on a modernized outage control center for a nuclear plant, which optimizes technology and human interaction. This work is founded on human factors studies of how to more effectively integrate informational and collaborative digital technologies into the critical tasks of processing volumes of real-time outage information for timely-effective decision-making. (This video has no sound)