risk-informed assessment of pwscc issue in candu feeder...
TRANSCRIPT
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›- Copyright -
›Risk-Informed Assessment of PWSCC Issue in CANDU Feeder Piping
›Xinjian Duan, Min Wang, Candu Energy Inc. ›Ming Li, Ontario Power Generation
17th International Conference on Environmental Degradation of Materials in Nuclear Power Systems-Water
Reactor, August 9-13, 2015, Ottawa, Ontario, Canada.
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Background
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PWSCC observed in PWR/BWR primary heat transport piping
Dissimilar Metal Weld (DMW)
CANDU feeder DMW: SA-106 Grade B to Alloy 600 with Alloy
82/182 filler material
Based on the EDY method, DMWs in some CANDU outlet
feeders are approaching high risk category to be susceptible to
PWSCC
Cracking inspection on DMWs is challenging due to high dose
and access limitations. As an alternative, demonstration of LBB
mode of failure is required.
oFor susceptible PWSCC, inspection is not required if LBB is demonstrated
oFor active PWSCC, inspection (scope and frequency) is required
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Objective
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Demonstrate LBB through a risk-informed methodology
(composite of the three methods)
oDeterministic LBB
oAFEA/XFEM flaw evaluation
oProbabilistic assessment
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Methodology
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›Deterministic LBB FFSG
SRP 3.6.3
›FLAW Evaluation AFEA/XFEM
›Probabilistic Assessment PRAISE-CANDU 1.0
Probabilistic
Assessment AFEA/XFEM
Flaw Evaluation
Deterministic
LBB
• Factor on Crack Length • Factor on Load • Factor on Leak Detection • Factor on time from leakage to rupture • Consequential leakage
• Realistic margin
on time from
leakage to
rupture
• Likelihood of
failure
• Effect of inspection
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Deterministic LBB
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›Key Inputs Geometry and material properties
Loads
oLoad Case 1 operational leakage calculation
oLoad Cases 2/3 for the stability evaluation
Leak detection limit: 25 kg/h based on operating procedure and OPEX
Leak rate model (SQUIRT), leak rate factor of 5 as per the FFSG requirement to take into account the uncertainties in leak rate calculation
Crack growth model (PWSCC and fatigue)
›Results LBB margins generally decreases with decreasing piping size
40/44 feeders satisfy the LBB requirements
4 feeder (two 2.5" + two 3") with reduced margins (3.7 – 4.8) on leak rate
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Advanced FEA (AFEA) or Extended FEM (XFEM)
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›Purpose Deterministic calculation
To grow the crack of a postulated inner surface crack
oConsidering the effect of Weld Residual Stresses (WRS)
oCalculating the natural or non-constrained crack shape
›Methodology AFEA: same as MRP-216
XFEM: new development
›Preliminary AFEA Results Sufficient time to credit operator action to the leakage
oTime from incipient leakage to orderly shutdown leakage (5×25 kg/h): 160 days
oTime from orderly shutdown leakage to immediate shutdown leakage (1800 kg/h): 58 days
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Weld Residual Stresses-Overview
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›Most uncertainty mechanical parameter
›Large experimental program to quantify this parameter
Sample Fabrication
oLiburdi Automation
Measurements
oNeutron Diffraction: Canadian Neutron Beam Centre and Rutherford
Appleton Lab
oX-ray Diffraction: Proto Manufacturing and Open University
oContour Method: Open University
FE Modeling
oCandu Energy Inc (Abaqus) and Carleton University (VrWeld)
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Probabilistic Assessment
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›Purpose
Provide additional technical basis for exempting inspection
Provide supplemental information for deterministic calculation (deterministic
LBB+AFEA/XFEM)
oQuantify low probability of rupture
›PFM Code – PRAISE-CANDU 1.0
Full compliance with CSA N286.7
Joint effort between Structural Integrity Associates and Candu Energy Inc.
State-of-the-art deterministic models and uncertainty treatment
›Advantages
Uncertainties: aleatory, epistemic, and combined aleatory and epistemic
Quantify the effect of crack initiation, inspection, and leak detection
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PRAISE-CANDU 1.0
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›Two-loop Architecture
Same as xLPR 1.0/2.0
Separation of uncertainties
o Aleatory uncertainty
o Epistemic uncertainty
o Aleatory + Epistemic
Important parameter/uncertainty study
›PC based, Monte Carlo only
o Computationally efficient
o Use of large number of CPUs
›Three Levels of Validations
o Benchmarking with other generally accepted and documented PFM codes
o Comparing PFM calculations with the rupture events of non-nuclear piping
o Phenomenon based validation
START
END
Epistemic
Loop Done?
Yes
No
Sample Epistemic
Random Variables
Aleatory Loop
Done?
Yes
No
Sample Aleatory
Random Variables
Deterministic
Models
Time Loop
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PRAISE-CANDU Benchmarking on PWSCC
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1E-08
1E-07
1E-06
1E-05
1E-04
1E-03
1E-02
1E-01
1E+00
0 5 10 15 20 25
P(L
OC
A)
Time (years)
PRAISE-CANDU
WinPRAISE
0
0.2
0.4
0.6
0.8
1
0 10 20 30 40 50 60P
rob
ab
ilit
y o
f R
up
ture
Time (years)
95 percentile: PRAISE-CANDU 1.0
95 percentile: xLPR 1.0
Mean: PRAISE-CANDU 1.0
Mean: xLPR 1.0
›Excellent Agreement with
WinPRAISE
xLPR 1.0
PRAISE-CANDU vs WinPRAISE PRAISE-CANDU vs xLPR 1.0
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PWSCC Initiation Model 1
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›Amzallag et al (1999)
i: temperature index, exp(-Qi/RT)
i: stress index, pn
im: material index
A: model coefficient, including heat-to-heat and within-heat uncertainties
QI: activation energy, calibrated to be 193 kJ/mol
pn: applied stress
𝑡𝐼1
𝑖𝑖𝑖𝑚
𝑡𝐼 =1
𝐴𝑖𝑚𝑝𝑛e𝑄𝐼 R𝑇 for 𝑝 > 𝑡ℎ
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Results
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The rupture probability is low, < 1.410-8
HAZ (Alloy 600) has higher rupture probability than weld center
(Alloy 82)
1E-09
1E-08
1E-07
1E-06
1E-05
1E-04
1E-03
1E-02
1E-01
1E+00
0 5 10 15 20 25
Pro
ba
bil
ity
Time (a)
P(Init) P(TW) P(LOCA)
1E-09
1E-08
1E-07
1E-06
1E-05
1E-04
1E-03
1E-02
1E-01
1E+00
0 5 10 15 20 25
Pro
ba
bil
ity
Time (a)
P(Init) P(TW) P(LOCA)
Weld Center (Alloy 82) HAZ (Alloy 600)
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Effect of Activation Energy
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Activation Energy, QI = 0, i.e., multipel pre-existing initial cracks
The rupture probability is low, < 1.010-4
1E-09
1E-08
1E-07
1E-06
1E-05
1E-04
1E-03
1E-02
1E-01
1E+00
0 5 10 15 20 25
P(L
OC
A)
Time (a)
QI = 193 kJ/mol QI = 0
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Effect of Leak Detection Limit
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25 kg/h vs. 50 kg/h, 125 kg/h, no leak detection
Rupture probability increases
1E-09
1E-08
1E-07
1E-06
1E-05
1E-04
1E-03
1E-02
1E-01
1E+00
0 5 10 15 20 25
P(L
OC
A)
Time (years)
No leak detection
OLRL = 125 kg/h
OLRL = 50 kg/h
OLRL = 25kg/h
Power Law Model
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Effect of In-Service Inspection
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No inspection vs. inspection every 3 years with good POD
Rupture probability slightly decreases
1E-09
1E-08
1E-07
1E-06
1E-05
1E-04
1E-03
1E-02
0 5 10 15 20 25
P(L
OC
A)
Time (years)
No Inspection Good POD
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Parameter Ranking
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Activation energy (activation energy 193 vs 0 KJ/mol ), leak
detection capability (25 vs 125 kg/h) and welding residual stress
are top three factors .
0
4
8
12
16
20Im
po
rta
nce
Factors
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Uncertainty Separation
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Forty billion (40×109) Monte Carlo simulations
Uncertainty of mean residual stress being epistemic uncertainty
Rupture probability: 5.9510-8 at 95th percentile vs. 1.4010-8 at
mean value
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Conclusions
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A tiered composite RI-informed LBB assessment has been
developed and applied to PWSCC issue on feeder DMW. The
results have been conditional accepted by the regulator.
Deterministic LBB assessment demonstrates 90% DMWs satisfy
the LBB requirements.
AFEA demonstrates sufficient margins on time from leak to
rupture for the remaining 10% DMWs.
Probabilistic assessment demonstrates the probability of rupture
is low.
The sensitivity study shows the PWSCC initiation model, leak
detection capability, and WRS are important, while the in-service
inspection has little impact on the rupture probability.
The uncertainty can be separated through two-loop PFM code,
PRAISE-CANDU 1.0 for prioritizing the resources.
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Acknowledgement
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CANDU Owners Group and Ontario Power Generation for the
funding the work.