MTA-NF-006 - Revision history

Colton Smith: Revision 0 Reviewed by Monica Hurley

2026-03-24T13:31:35Z

Revision 0 Reviewed by Monica Hurley

@@ Line 1: / Line 1: @@
 {{DISPLAYTITLE:Reduce Fuel-Related Operating Costs Through Statistics-Driven Innovations - MTA-NF-006}}
 {{MTATemplate||
 | Date |12/15/2020
@@ Line 7: / Line 8: @@
 NEI TIP Award Submittal #63; Securing Fuel Cost Competitiveness with Statistics-Driven Innovations (ID: 13343443)
-Boron-Induced Offset Anomaly (BOA), version 4.0 (EPRI [https://www.epri.com/research/products/3002012131 3002012131])
+Boron-induced Offset Anomaly (BOA) v4.1 (EPRI [https://www.epri.com/research/products/000000003002032069 3002032069])
-| Industry SME | EPRI – Ruwan Ratnayake
+| Industry SME | EPRI Fuel Reliability Program
 Contact: NuclearPlantMod@epri.com
 | Previous Implementation | Please contact EPRI for implementation examples and contacts.
 | Implementation Enablers | N/A
 | Applicability | All reactor types
 All geographic regions
@@ Line 28: / Line 22: @@
 Statistical approaches to the enhanced use of fuel‑cycle predictive capabilities may allow for the elimination or reduction of several fuel‑related activities, such as low power physics testing (LPPT) rod worth measurement, moderator temperature coefficient (MTC) testing, and fuel cleaning. Elimination of these tasks saves resources (i.e., manpower, equipment and time) and may also reduce outage critical path time.
-The statistical methodology takes credit for the accuracy of core predictive tools, rather than confirming core performance through testing and restoring margins through cleaning. LPPT rod worth testing and MTC testing are both intended to verify that the reactivity changes in the core occur as designed. Fuel cleaning is a mitigation strategy to reduce crud‑induced power shift (CIPS) during operation. The high accuracy of modern core predictive tools and methods can replace or reduce the need for testing and provide a basis for extending cleaning intervals. Statistical approaches are used to provide technical justifications for eliminating these activities. The statistical methods require comparison of startup testing data (e.g., rod position data) and core life data (e.g., reactivity and moderator temperature data) to ensure predictive codes are reliable and accurate enough to eliminate LPPT rod worth measurement and MTC testing. In addition to eliminating these tests, the potential need for fuel cleaning may be reduced by implementing EPRI’s Boron‑Induced Offset Anomaly (BOA) Risk Assessment Tool Version 4.0. This tool has enhanced capability to predict crud‑related fuel performance risks for zinc addition that can be used to assess the potential for reductions in cleaning.
+The statistical methodology takes credit for the accuracy of core predictive tools, rather than confirming core performance through testing and restoring margins through cleaning. LPPT rod worth testing and MTC testing are both intended to verify that the reactivity changes in the core occur as designed. Fuel cleaning is a mitigation strategy to reduce crud‑induced power shift (CIPS) during operation. The high accuracy of modern core predictive tools and methods can replace or reduce the need for testing and provide a basis for extending cleaning intervals. Statistical approaches are used to provide technical justifications for eliminating these activities. The statistical methods require comparison of startup testing data (e.g., rod position data) and core life data (e.g., reactivity and moderator temperature data) to ensure predictive codes are reliable and accurate enough to eliminate LPPT rod worth measurement and MTC testing. In addition to eliminating these tests, the potential need for fuel cleaning may be reduced by implementing EPRI’s [https://www.epri.com/research/products/000000003002032069 Boron‑Induced Offset Anomaly (BOA) Risk Assessment Tool Version 4.1]. This tool has enhanced capability to predict crud‑related fuel performance risks for zinc addition that can be used to assess the potential for reductions in cleaning.
 The statistical methodology has been implemented in pressurized water reactors (PWRs), but elements of the approach could be applied to boiling water reactors (BWRs) as well, depending on availability of fuel cycle data. BWR implementation may differ from PWR implementation but should follow the same fundamental principles.
@@ Line 56: / Line 50: @@
 Due to the elimination of LPPT rod worth measurement and MTC testing, boron measurements may need to be relied on more heavily for verifying that the core performs as designed. This may require additional conservatism for the boron measurements.

Jacob Sommer: 1 revision imported

2026-03-05T01:37:56Z

1 revision imported

← Older revision	Revision as of 01:37, 5 March 2026
(No difference)

10.142.237.162: /* Risks */

2026-03-03T20:59:00Z

Risks

New page

{{DISPLAYTITLE:Reduce Fuel-Related Operating Costs Through Statistics-Driven Innovations - MTA-NF-006}}
{{MTATemplate||
| Date |12/15/2020
| Functional Area Where Benefits Will Be Realized | Nuclear Fuels
Engineering
| Reference Implementation Guidance |
2020 NEI TIP Award Submittal #63; Securing Fuel Cost Competitiveness with Statistics-Driven Innovations (ID: 13343443)

Boron-Induced Offset Anomaly (BOA), version 4.0 (EPRI [https://www.epri.com/research/products/3002012131 3002012131])
| Industry SME | EPRI – Ruwan Ratnayake
Contact: NuclearPlantMod@epri.com
| Previous Implementation | Please contact EPRI for implementation examples and contacts.
| Implementation Enablers | N/A
| SWEEP Score |
* Cost – Level 3 – Implementation costs should be less than $1 million.
* Savings – Level 2 – Savings are expected to be between $1 million and $5 million per year.
* Payback – Level 2 – Payback will be achieved on the first implementation of the statistics methodology, which will occur during an outage. Thus, payback period is expected to be between 1 – 5 years.
* Licensing Readiness – Level 3 – This technology has already been implemented at nuclear sites. However, licensees may have to prepare a LAR depending on the provisions of their Technical Specifications.
* Technology Readiness – Level 3 – This methodology has already been implemented at nuclear sites.
* Implementation proficiency – Level 3 – The implementation of the statistics‑driven innovations does not require knowledge in implementing digital technologies.
| Applicability | All reactor types
All geographic regions
| Keywords | Nuclear fuels; statistics; operating costs
| Business Case Analysis Cross-Reference | N/A
}}

==Description==
Statistical approaches to the enhanced use of fuel‑cycle predictive capabilities may allow for the elimination or reduction of several fuel‑related activities, such as low power physics testing (LPPT) rod worth measurement, moderator temperature coefficient (MTC) testing, and fuel cleaning. Elimination of these tasks saves resources (i.e., manpower, equipment and time) and may also reduce outage critical path time.

The statistical methodology takes credit for the accuracy of core predictive tools, rather than confirming core performance through testing and restoring margins through cleaning. LPPT rod worth testing and MTC testing are both intended to verify that the reactivity changes in the core occur as designed. Fuel cleaning is a mitigation strategy to reduce crud‑induced power shift (CIPS) during operation. The high accuracy of modern core predictive tools and methods can replace or reduce the need for testing and provide a basis for extending cleaning intervals. Statistical approaches are used to provide technical justifications for eliminating these activities. The statistical methods require comparison of startup testing data (e.g., rod position data) and core life data (e.g., reactivity and moderator temperature data) to ensure predictive codes are reliable and accurate enough to eliminate LPPT rod worth measurement and MTC testing. In addition to eliminating these tests, the potential need for fuel cleaning may be reduced by implementing EPRI’s Boron‑Induced Offset Anomaly (BOA) Risk Assessment Tool Version 4.0. This tool has enhanced capability to predict crud‑related fuel performance risks for zinc addition that can be used to assess the potential for reductions in cleaning.

The statistical methodology has been implemented in pressurized water reactors (PWRs), but elements of the approach could be applied to boiling water reactors (BWRs) as well, depending on availability of fuel cycle data. BWR implementation may differ from PWR implementation but should follow the same fundamental principles.

==Benefits==
===Benefits Estimate===
Level 2 – Savings are expected to be between $1 million and $5 million per year. These savings reflect elimination of testing and reduction of cleaning over the life of a plant. Additional savings can be realized from reduced outage critical path.

===Benefits Description===
* Reduced fuel‑related operating costs through eliminated tests and reduced fuel cleanings.
* Potential reduction in critical‑path outage time from eliminated tests and reduced fuel cleanings.
* Improved fuel reliability and safety due to reductions in unnecessary or excessive fuel cleaning. Reduced fuel cleaning decreases the chance of fuel damage during the cleaning process and also results in lower dose rates and radioactive waste inventory.
* Improved safety by avoiding test conditions. Tests require plants to operate in abnormal conditions that place additional burden on operators. Elimination of tests also decreases the potential for test performance errors that can result in operational and regulatory issues.

==Costs and Schedule==
===Cost===
Level 3 – Implementation costs should be less than $1 million and include the labor associated with incorporating the methodology and any licensing actions.

===Schedule===
Implementation schedule depends on whether a License Amendment Request (LAR) is required. Implementation and planning is expected to take less than six months if no LAR is required, and six months to one year if a LAR is required.

===Scope Context===
Per unit

==Risks==
The statistical methodology requires historical data from previous fuel cycles. Lack of this data would prevent implementation.

Due to the elimination of LPPT rod worth measurement and MTC testing, boron measurements may need to be relied on more heavily for verifying that the core performs as designed. This may require additional conservatism for the boron measurements.