Dynamic PRA of a Multi-unit Plant

IRUG Meeting – Idaho Falls, April 18th 2019

D. Mandelli, C. Parisi, A. Alfonsi, D. Maljovec, S. St Germain, R. Boring, S. Ewing, C. Smith, C. Rabiti

diego.mandelli@inl.gov

Simula'on*based*modeling*

Human*reliability**modeling*

Reduced*order*

modeling*

Data*mining*

Multi-Unit Analysis: Overview

• Analysis summary:– TH modeling of PWRs and Spent Fuel Pools (SFPs)– Human reliability models (HUNTER)– Dynamic PRA– Modeling of control logic at the site level– Heavy use of Reduced Order Models (ROMs)– Data analysis of large and complex dataset

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• Objectives: perform an integral multi-unit plant analysis using a simulation-based approach– Timing/sequencing of events among units– Large variety of interdependencies

RELAP5-3D

RAVEN

Initiating Event: Seismic Induced SBOUnit 2 CST

@ 20%

PWR1(100%)

Swing EDG (EDGS)

operating on Unit 2 3

Unit 3 CST @ 0%

Switchyardsdisabled

PWR2mid-loop

PWR3(108%)

High heat load for SFP3

EDGsdisabled

SFP LOCA

Unit 1

Unit 2 Unit 3

Recovery Crew

Aux FW cross-tie

CST cross-tie

EDGS AC cross-tie

Plant and Recovery Actions• Unit dependencies:

– Plant electrical system (EDGS) and AC cross-tie– AFW and CST cross-ties– Plant recovery crew, Emergency Portable Equipment (EPE)

• 3 formulated recovery strategies:– Sequence of unit recovery based on a prioritization scheme

• Depending on unit status• One unit at a time

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– Sequence might change depending on accident progression

• e.g., erroneous alignment of EDGS

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Accident Progression: Example

RISMC Multi-Unit Modeling• 23 stochastic variables:

– Timing of events– Recovery actions– Human interventions

• Site deterministic model: – RAVEN Ensemble model

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• HRA methods:– HUNTER: sub-task modeling– THERP: EDGS erroneous alignment

• Plant model:– RAVEN external model– Handle plant and recovery control logic– Human reliability models included– Determine timing of events for all 6 models

given values of 23 sampled parameters

Plant Model

PWR1

SFP1

PWR2

SFP2

PWR3

SFP3

RAVEN Ensemble Model

23 stochastic variables

Status of PWRs and

SFPs

Plant Model

PWR1

SFP1

PWR2

SFP2

PWR3

SFP3

RAVEN Ensemble Model

23 stochastic variables

Outcome

ROM Modeling• Multi-unit analysis issues:

– Large computational cost– High probability of simulation crash

• Solution: employ ROMs 1. Sample code response 2. Choose and train ROM3. Validate ROM response

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• ROM employed: KNN– Prediction performed by considering K neighbor samples– K is chosen based on validation results (3-fold validation process)

• Training samples size chosen based on convergence prediction

Multi-Unit PRA• Approach: Monte-Carlo

– 1.1 M samples• For each simulation the outcome of each model/ROM is collected

– OK or failed• Such a large coupling among units strongly affects timing and sequencing of

events – Valid even from a probabilistic point of view– Here classical tools show their limitations

Strategy 1 and 2 Strategy 3 w/

invol. align of EDGS Strategy 3

Strategy 3

Strategy 1, 2 and 3 w/ invol. align of EDGS

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Data Analysis• CD probability is typically determined for a single model (PWR or SFP)

• At a plant level, a probability value is associated to a Plant Damage State (PDS)

• A PDS is a 6-dimensional vector:– Each vector element describes the status of a model (OK or CD)– Vector elements are highly correlated– 26 = 64 PDSs allowed

• Approach:1. Group simulation runs based on their own PDS2. Evaluate probability associated to each PDS and rank PDSs based on

their probability values.3. Identify commonalities that characterize each PDS

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Results• 14 out of 64 PDSs were actually generated

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Results

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PWR3 can be recovered only within 50 min after SBO condition

CST is intact + multiple recovery actions available

Results

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SFP LOCAs are present but recovery actions are able to mitigate them

SFP LOCAs are modeled through 2 stoch. params:• SFP Loca time• SFP Loca size

Results

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smal

lm

ed

larg

e

Limit recovery time

SFP

reco

very

tim

e` Recovery strategy 3Very early AC x-tie

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Results

Results

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Recovery strategy 3 Involuntary alignment of EDGS

EDGS involuntary alignment time

EPE on Unit 3 EPE on Unit 1

Summary• First step toward a simulation-based approach to analyze multi-unit

plants

• Focus on recovery actions– No additional failures were introduced in the analysis

• Scope– Identify optimal recovery actions

• Future work– Extend analysis to Level 2 analysis

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