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MSPI DRIVING SAFER NUCLEAR POWER PLANT –

CALLAWAY ENERGY CENTER

Hongbing Jiang Tennessee Valley Authority

 Zhiping Li Ameren Missouri

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I. INSTRUCTION II. WHAT IS MSPI III. MSPI APPLICATION: A CASE STUDY III.A. Power Source Design III.B. Extra Decay Heat Removal Design III.C. Observations and Areas For

Improvement IV. MSPI OPTIMIZATION V. CONCLUSIONS

Outlines

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MSPI (Mitigating System Performance Index) assessing licensee performance.

Regulation : NRC ROP with Action Matrix

MSPI could reflect implicitly or explicitly the as-built, as-operated, as-maintained and as-planned plant with the predefined baselines,

MSPI driving safer NPP – Callaway Energy Center

I. INSTRUCTION

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Widely recognized Equation

UAI : Unavailability Index URI : Unreliability Index

NUREG-1816, NEI 99-02

II. WHAT IS MSPI

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Where：； Numeric Index (NI) Performance Limit Exceed (PLE)

II. WHAT IS MSPI

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II. WHAT IS MSPI

MSPI

NI

Non-Green (True)

Green(False)

Non-Green(True) (NI=T, MSPI=T)

(NI=T, MSPI=F)& RiskCap

Green(False)

(NI=F, MSPI=T)

& PLE(NI=F, MSPI=F)

Actual State

Indication State

True False

True (T, T) (T, F)

False (F, T) (F, F)

Truth Table of Recognition Overall View of MSPI

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In 2010, Callaway Nuclear Power Plant (4-loop, W-PWR, 3565 MWt)

(1) white for an EAC system (2) potential white for AFW system

Installed AEPS and motor-driven NSAFP modifications were completed in 2011

Safer nuclear power plantCDF was reduced to about half

before the Japanese FukushimaINPO 1 “excellent” rating

III. MSPI APPLICATION: A CASE STUDY

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Design features

Switchyard vs. Safety Bus SBO considerationLOOP consideration

III.A. Power Source Design

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SBO mitigation

Pump location reduced margin due to steam break initiator

III.B. Extra Decay Heat Removal Design

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time consuming to input data (text XML input) Only integer margins (decimal margin index) Only the maximum margin (margin combination)

threshold 1.05E-6 (1.00E-6) Excessively high UA hours (below 36 months) Shorter MT, more EAC FTR margin gain the margin one system, lose margin

another system Selection of low risk significant (≤1.0E-6)

components

III.C. Observations and Areas for Improvement

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The software, MSPI Analyzer, developed for MSPI application and optimization

III.C. Observations and Areas For Improvement

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“RISK WORTH” (X), which measures the risk increase in terms of CDF or MSPI change from one unavailability hour or one unreliability failure.

Potential MR, SDP applications (X, Birnbaum)

IV. MSPI OPTIMIZATION

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IV. MSPI OPTIMIZATION

The MSPI optimization function: 

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IV. MSPI OPTIMIZATION

Given (1) PRA parameters like CDF, FV, CCF, (2) operational data such as critical hours, estimated or actual component run time and demands and industry and plant specific baseline values,

The GREEN MSPI combination can be determined in advance.

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IV. MSPI OPTIMIZATION

(A)TRNA.X

(B)TRNB.X

(C) *DG.Xs

(D) *DG.Xl

(E) *DG.Xr

X 1.534E-09 1.534E-09 6.639E-07 6.528E-07 2.593E-06

Then the corresponding object function is

1.534E-09*A +1.534E-09*B + 6.639E-07*C + 6.528E-07*D + 2.593E-06*E <= 3.362E-06

TABLE III. Train Unavailability and Component Group Unreliability Risk Worth

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IV. MSPI OPTIMIZATION

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IV. MSPI OPTIMIZATION

Maximization of EAC Green Margin

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MSPI reflects implicitly or explicitly the as-built, as-operated, as-maintained and as-planned Nuclear Power Plants (NPP).

Overall, the MSPI index is not only able to, but also it can be the index for selecting better plant designs and.

Once the PRA and plant data are known, all green combinations can be determined in advance.

Better MSPI means safer plant operation, a plant is able to predefine strategy and make proactive decisions rather than response passively.

V. CONCLUSIONS