Dynamic PRA of a Multi-unit Plant - RELAP5-3D...and 3 w/ invol. align of EDGS 8. Data Analysis •CD...
Transcript of Dynamic PRA of a Multi-unit Plant - RELAP5-3D...and 3 w/ invol. align of EDGS 8. Data Analysis •CD...
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
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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