[Federal Register Volume 86, Number 75 (Wednesday, April 21, 2021)]
[Notices]
[Pages 20744-20745]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2021-08177]


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NUCLEAR REGULATORY COMMISSION

[NRC-2021-0048]


Role of Artificial Intelligence Tools in U.S. Commercial Nuclear 
Power Operations

AGENCY: Nuclear Regulatory Commission.

ACTION: Request for comment.

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SUMMARY: The U.S. Nuclear Regulatory Commission (NRC) is requesting 
public comment on the current state of commercial nuclear power 
operations relative to the use of artificial intelligence (AI) and 
machine learning (ML) tools.

DATES: Submit comments by May 21, 2021. Comments received after this 
date will be considered if it is practical to do so, but the Commission 
is able to ensure consideration only for comments received on or before 
this date.

ADDRESSES: You may submit comments by any of the following methods; 
however, the NRC encourages electronic comment submission through the 
Federal Rulemaking website:
     Federal Rulemaking Website: Go to https://www.regulations.gov and search for Docket ID NRC-2021-0048. Address 
questions about Docket IDs in Regulations.gov to Stacy Schumann; 
telephone: 301-415-0624; email: [email protected]. For technical 
questions, contact the individual listed in the FOR FURTHER INFORMATION 
CONTACT section of this document.
     Mail comments to: Office of Administration, Mail Stop: 
TWFN-7-A60M, U.S. Nuclear Regulatory Commission, Washington, DC 20555-
0001, ATTN: Program Management, Announcements and Editing Staff.
    For additional direction on obtaining information and submitting 
comments, see ``Obtaining Information and Submitting Comments'' in the 
SUPPLEMENTARY INFORMATION section of this document.

FOR FURTHER INFORMATION CONTACT: John C. Lane, Office of Nuclear 
Regulatory Research, U.S. Nuclear Regulatory Commission, Washington, DC 
20555-0001, telephone: 301-415-2476, email: [email protected].

SUPPLEMENTARY INFORMATION:

I. Obtaining Information and Submitting Comments

A. Obtaining Information

    Please refer to Docket ID NRC-2021-0048 when contacting the NRC 
about the availability of information for this action. You may obtain 
publicly available information related to this action by any of the 
following methods:
     Federal Rulemaking Website: Go to https://www.regulations.gov and search for Docket ID NRC-2021-0048.
     NRC's Agencywide Documents Access and Management System 
(ADAMS): You may obtain publicly available documents online in the 
ADAMS Public Documents collection at https://www.nrc.gov/reading-rm/adams.html. To begin the search, select ``Begin Web-based ADAMS 
Search.'' For problems with ADAMS, please contact the NRC's Public 
Document Room (PDR) reference staff at 1-800-397-4209, at 301-415-4737, 
or by email to [email protected]. The AI/ML general solicitation 
request for comment is also available in ADAMS under Accession No. 
ML21085A611.
     Attention: The PDR, where you may examine and order copies 
of public documents, is currently closed. You may submit your request 
to the PDR via email at [email protected] or call 1-800-397-4209 or 
301-415-4737, between 8:00 a.m. and 4:00 p.m. (EST), Monday through 
Friday, except Federal holidays.

B. Submitting Comments

    The NRC encourages electronic comment submission through the 
Federal Rulemaking website (https://www.regulations.gov). Please 
include Docket ID NRC-2021-0048 in your comment submission.
    The NRC cautions you not to include identifying or contact 
information that you do not want to be publicly disclosed in your 
comment submission. The NRC will post all comment submissions at 
https://www.regulations.gov as well as enter the comment submissions 
into ADAMS. The NRC does not routinely edit comment submissions to 
remove identifying or contact information.
    If you are requesting or aggregating comments from other persons 
for submission to the NRC, then you should inform those persons not to 
include identifying or contact information that they do not want to be 
publicly disclosed in their comment submission. Your request should 
state that the NRC does not routinely edit comment submissions to 
remove such information before making the comment submissions available 
to the public or entering the comment into ADAMS.

II. Discussion

    The NRC is exploring the potential for advanced computational and 
predictive capabilities involving AI and ML in the various phases of 
nuclear power generation operational experience and plant management. 
The NRC is soliciting comments on the state of practice, benefits, and 
future trends related to the advanced computational tools and 
techniques in predictive reliability and predictive safety assessments 
in the commercial nuclear power industry.

III. Specific Request for Comment

    The NRC requests comments from the public, the nuclear industry and 
other stakeholders, as well as other interested individuals and 
organizations. The focus of this request is to gather information that 
will provide the NRC staff with a better understanding of current usage 
and future trends in AI and ML in the commercial nuclear power 
industry.

IV. Requested Information and Comments

    AI and ML are emerging, analytical tools, which, if used properly, 
show promise in their ability to improve reactor safety, yet offer 
economic savings. The NRC requests comments on issues listed below in 
this solicitation to enhance the NRC's understanding of the short- and 
long-term applications of AI

[[Page 20745]]

and ML in nuclear power industry operations and management, as well as 
potential pitfalls and challenges associated with their application.
    1. What is status of the commercial nuclear power industry 
development or use of AI/ML tools to improve aspects of nuclear plant 
design, operations or maintenance or decommissioning? What tools are 
being used or developed? When are the tools currently under development 
expected to be put into use?
    2. What areas of commercial nuclear reactor operation and 
management will benefit the most, and the least, from the 
implementation of AI/ML? Possible examples include, but are not limited 
to, inspection support, incident response, power generation, 
cybersecurity, predictive maintenance, safety/risk assessment, system 
and component performance monitoring, operational/maintenance 
efficiency and shutdown management.
    3. What are the potential benefits to commercial nuclear power 
operations of incorporating AI/ML in terms of (a) design or operational 
automation, (b) preventive maintenance trending, and (c) improved 
reactor operations staff productivity?
    4. What AI/ML methods are either currently being used or will be in 
the near future in commercial nuclear plant management and operations? 
Example of possible AI/ML methods include, but are not limited to, 
artificial neural networks, decision trees, random forests, support 
vector machines, clustering algorithms, dimensionality reduction 
algorithms, data mining and content analytics tools, gaussian 
processes, Bayesian methods, natural language processing, and image 
digitization.
    5. What are the advantages or disadvantages of a high-level, top-
down strategic goal for developing and implementing AI/ML across a wide 
spectrum of general applications versus an ad-hoc, case-by-case 
targeted approach?
    6. With respect to AI/ML, what phase of technology adoption is the 
commercial nuclear power industry currently experiencing and why? The 
current technology adoption model characterizes phases into categories 
such as: the innovator phase, the early adopter phase, the early 
majority phase, the late majority phase, and the laggard phase.
    7. What challenges are involved in balancing the costs associated 
with the development and application of AI/ML tools, against plant 
operational and engineering benefits when integrating AI/ML into 
operational decision-making and workflow management?
    8. What is the general level of AI/ML expertise in the commercial 
nuclear power industry (e.g. expert, well-versed/skilled, or beginner)?
    9. How will AI/ML effect the commercial nuclear power industry in 
terms of efficiency, costs, and competitive positioning in comparison 
to other power generation sources?
    10. Does AI/ML have the potential to improve the efficiency and/or 
effectiveness of nuclear regulatory oversight or otherwise affect 
regulatory costs associated with safety oversight? If so, in what ways?
    11. AI/ML typically necessitates the creation, transfer and 
evaluation of very large amounts of data. What concerns, if any, exist 
regarding data security in relation to proprietary nuclear plant 
operating experience and design information that may be stored in 
remote, offsite networks?

    Dated: April 15, 2021.

    For the Nuclear Regulatory Commission.
Mehdi Reisi Fard,
Chief, Performance and Reliability Branch, Division of Risk Analysis, 
Office of Nuclear Regulatory Research.
[FR Doc. 2021-08177 Filed 4-20-21; 8:45 am]
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