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| number = ML14149A089 | | number = ML14149A089 | ||
| issue date = 05/21/2014 | | issue date = 05/21/2014 | ||
| title = | | title = NRR E-mail Capture - STP-GSI-191 Presentation | ||
| author name = Harrison A | | author name = Harrison A | ||
| author affiliation = South Texas Project Nuclear Operating Co | | author affiliation = South Texas Project Nuclear Operating Co | ||
| addressee name = Singal B | | addressee name = Singal B | ||
| addressee affiliation = NRC/NRR/DORL | | addressee affiliation = NRC/NRR/DORL | ||
| docket = 05000498, 05000499 | | docket = 05000498, 05000499 | ||
Line 14: | Line 14: | ||
| page count = 46 | | page count = 46 | ||
| project = TAC:MF2400, TAC:MF2401 | | project = TAC:MF2400, TAC:MF2401 | ||
| stage = Other | |||
}} | }} | ||
=Text= | =Text= | ||
{{#Wiki_filter: | {{#Wiki_filter:NRR-PMDA-ECapture Resource From: Harrison Albon <awharrison@STPEGS.COM> | ||
Sent: Wednesday, May 21, 2014 11:03 AM To: Singal, Balwant Cc: Kee, Ernie; Blossom, Steven; Murray, Michael | |||
==Subject:== | |||
STP Sensitivity Presentation Attachments: STP-GSI-191 Presentation May 222014.pdf | |||
: Balwant, Our presentation is attached. Also, Alion confirmed the SWRI presentation has no proprietary information. | |||
Wayne 1 | |||
}} | CASA Grande Sensitivity Studies May 22,2014 | ||
===Introductions=== | |||
* Presenters Mike Murray Wayne Harrison Ernie Kee David Morton Bruce Letellier 2 | |||
===Introductions=== | |||
* Contributors Steve Blossom Zahra Mohaghegh Seyed Reihani Jeremy Tejada Don Wakefield 3 | |||
Summary | |||
* Summarize approach to sensitivity analyses | |||
* Demonstrate the approach on several parameters | |||
* Review and explain counterintuitive results observed with certain parameters 4 | |||
Development Status and Potential Application o Development Status o NOT being proposed for NRC review/approval as part of the Risk-Informed Pilot Application o Will require appropriate validation and verification o Potential Applications o Facilitate evaluation of emergent plant conditions Facilitate identification/prioritization of compensatory actions Quantitative assessment may be required to formalize evaluation o Evaluation of plant modifications 5 | |||
Potential Application and Development Status, cont. | |||
o Current and Potential Features (Ref. ML14072A211) o One-way sensitivity, tornado plots (Step 6) o One-way sensitivity studies, UQ plots (Step 7) o One-way sensitivity: Spider Plots (Step 8) o Two-way (two at a time) sensitivity studies (Step 9) o Meta models (Step 10) (response surface correlation) | |||
To support multi-attribute sensitivity and simplified analysis of plant response o Compliance with standard software quality assurance o Importance o Helps show the relative importance of parameters o Helps to identify potential errors (counterintuitive results) and thereby contributes to analysis quality 6 | |||
CASA
Grande
Sensi-vity
Studies | |||
John Hasenbein David Morton Jeremy Tejada Alex Zolan May 22, 2014 7 | |||
Sensitivity Studies | |||
* Approach | |||
* Boron fuel limit | |||
* Fiber penetration function | |||
* Head loss studies 8 | |||
10-Step Sensitivity Analysis Process | |||
* Step 1: Define the Model | |||
* Step 2: Select Outputs of Interest | |||
* Step 3: Select Inputs of Interest | |||
* Step 4: Choose Nominal Values and Ranges for Inputs | |||
* Step 5: Estimate Model Outputs under Nominal Input Values | |||
* Step 6: One-Way Sensitivity Analysis: Sensitivity Plots & Tornado Diagrams | |||
* Step 7: One-Way Sensitivity Analysis: UQ Plots | |||
* Step 8: One-Way Sensitivity Analysis: Spider Plots | |||
* Step 9: Two-way Sensitivity Analysis: Two-way Sensitivity Plots | |||
* Step 10: Metamodels & Design of Experiments 9 | |||
Step 1: Define the Model | |||
* We wont detail CASA Grande here (Volume 3) | |||
* Use CASA Grande to estimate probability of sump failure and boron fiber limit failure, conditional on small, medium & large breaks | |||
* Estimate change in core damage frequency (CDF) in events/year due to GSI-191 issues using these failure probability estimates and corresponding frequencies | |||
* All results here are conditional on all pumps working 10 | |||
Step 2: Select Outputs of Interest | |||
* Change in core damage frequency (CDF) | |||
* Sometimes, we report ratio of CDF estimate for a scenario to CDF estimate for baseline and call this the risk ratio | |||
* Use stratified sampling on initiating frequency | |||
* Use IID replications within each cell of stratification | |||
* Use common random numbers across scenarios; i.e., use CRNs across specified changes in input parameters 11 | |||
Step 2: Outputs: Estimating CDF Indices and Sets: | |||
i = 1, . . . , F index for cells stratifying frequency replications k = 1, . . . , N index for set of pump states Events: | |||
SL, M L, LL small, medium, large LOCA P Sk pumps in state k Fi initiating frequency in cell i S sump failure B boron fiber limit failure CD core damage Parameters: | |||
fSL , fM L , fLL frequency (events/CY) of a small, medium, large LOCA P (P Sk ) probability mass of P Sk P (Fi ) probability mass of Fi P (SlLOCA, Fi , P Sk ) estimate of probability of S given LOCA = SL, M L, orLL, Fi , P Sk P (BlLOCA, Fi , P Sk ) estimate of probability of B given LOCA = SL, M L, orLL, Fi , P Sk RBASE non-GSI-191 core damage frequency (events/CY) | |||
RCD estimate of core damage frequency (events/CY) 12 | |||
Step 2: Outputs: Estimating CDF CDF = RCD RBASE X F X N | |||
= P (Fi )P (P Sk ) | |||
* i=1 k=1 h | |||
fSL | |||
* P (SlSL, Fi , P Sk ) + fSL | |||
* P (BlSL, Fi , P Sk ) | |||
+fM L | |||
* P (SlM L, Fi , P Sk ) + fM L | |||
* P (BlM L, Fi , P Sk ) | |||
i | |||
+fLL | |||
* P (SlLL, Fi , P Sk ) + fLL | |||
* P (BlLL, Fi , P Sk ) | |||
* We report results with: | |||
- fSL , fML , fLL from Volume 2s Table 4-1 | |||
- P(all pumps working)=1 | |||
- P(Fi ): Bounded Johnson fit to NUREG-1829 | |||
* We form a variance estimate for the above estimator 13 | |||
Step 3: Select Inputs of Interest | |||
* Amount of Latent Fiber in Pool: Existing dust/dirt in containment, based on plant measurement. Assumed to be in the pool at start of recirculation, uniformly mixed. During fill up, latent debris available to penetrate sump screen. | |||
* Boron Fiber Limit: Refers to threshold where boron precipitation occurs for cold leg breaks. Fiber limit comes from vendor testing that shows no pressure drop occurs with full chemical effects. Assume all fiber that penetrates sump screen deposits uniformly on core. | |||
* Debris Transport Fractions in ZOI: Refers to debris transport fractions involving three-zone ZOI. Each insulation type has characteristic ZOI divided in three sections to account for type of damage within each zone. | |||
14 | |||
Step 3: Select Inputs of Interest | |||
* Chemical Precipitation Temperature: CASA Grande assumes that, once a thin bed of fiber forms on strainer, chemical head loss factors apply when pool temperature reaches precipitation temperature. | |||
* Total Failure Fraction for Debris Outside the ZOI: CASA Grande uses table of total failure fractions applied to transport logic trees. Fraction of each type (fiber, paint and coatings, etc.) that passes to the pool are used to understand what is in the pool as a function of time during recirculation. | |||
* Chemical Head Loss Factor: Used as a multiplier on conventional head loss calculated in CASA Grande. Multiplier is applied if thin bed is formed and pool temperature is at or below precipitation temperature. | |||
15 | |||
Step 3: Select Inputs of Interest | |||
* Fiber Penetration Function: Fraction of fiber that bypasses the ECCS sump screen as a function of the amount of fiber on the screen. | |||
* Size of ZOI: ZOI defined as direct function (multiplier) of break size and nominal pipe diameter; e.g., for NUKON fiber, ZOI is 17 times break diameter. ZOI is spherical unless break is not DEGB, in which case it is hemispherical. Truncated by any concrete walls within the ZOI. | |||
* Time to Turn Off One Spray Pump: If three spray pumps start, then by procedure one is secured. Time to secure the pump is governed by operator acting on the conditional action step in procedure. | |||
16 | |||
Step 3: Select Inputs of Interest | |||
* Time to Hot Leg Injection: Similar to the spray pump turn off time, the time to switch one or more trains to hot leg injection operation is governed by procedure. | |||
* Strainer Buckling Limit: Limit is the differential pressure across ECCS strainer at which strainer is assumed to fail mechanically. This limit is based on engineering calculations that incorporate safety factor. | |||
* Water Volume in the Pool: Depending on break size, amount of water in pool, as opposed to amount in RCS and other areas in containment, varies. Smaller breaks tend to result in less pool volume than larger breaks. | |||
17 | |||
Step 3: Select Inputs of Interest | |||
* Debris Densities: Depends on amount and type of debris that arrives in pool. These densities are used in head loss correlations to calculate, for example, debris volume. | |||
* Time Dependent Temperature Profiles: Temperature of water in sump affects air release and vaporization during recirculation. Time-dependent temperature profile comes from coupled RELAP5-3D and MELCOR simulations depending on break size. | |||
* Spray Failure Fraction for Debris Outside ZOI: CASA Grande uses a table of failure fractions applied to transport logic trees. Fractions of each type of debris that passes to pool are used to understand what is in pool as function of time during recirculation. The spray failure fraction is fraction of failed coatings that wash to pool during spray operation. | |||
18 | |||
Step 4: Nominal Values and Ranges for Inputs Input
Parameter
Level
1
Level
2
Level
3
Level
4 | |||
Latent
Fiber
(63)
12.5
6.25
25
50 | |||
Boron
Fiber
Limit
(g/FA)
7.5
4
15
50 | |||
Debris
Transport
Inside
ZOI
Base
Low
High
| |||
Water
Volume
in
Pool
Base
-10%
+10%
| |||
Chemical
Precipita-on
Temp
(oF)
140o
160o
| |||
Total
Failure
Frac-on
Outside
ZOI
Base
Low
| |||
Chemical
Head
Loss
Factor
Base
+50%
| |||
Fiber
Penetra-on
Func-on
Base
High
| |||
ZOI
Size
Base
-33%
| |||
Turn
o
1
Spray
Pump
(min.)
20
1440
| |||
Hot
Leg
Injec-on
(min.)
345
450
| |||
Strainer
Buckling
Limit
(6.
H2O)
9.35
9.6
| |||
Debris
Density
(lbm/63)
Base
+25%
| |||
Temperature
Pro"les
(oF)
Base
-5%
| |||
Spray
Transport
Frac-on
6%
12% | |||
19 | |||
Step 5: Estimate Outputs Under Nominal Values of Inputs | |||
#
Sensi7vity
Measure
Expected
95%
CI
95%
CI
95%
CI
CI
HW
% | |||
Mean
CDF | |||
Direc7on
Half-Width
Low
Limit
Upper
Limit
of
Mean | |||
0
Baseline
None
1.817E-08
1.914E-09
1.626E-08
2.009E-08
10.53% | |||
20 | |||
Step 6: One-Way Sensitivity Analysis | |||
#
Expected
0.95-level
CI
HW
%
of | |||
Sensi7vity
Measure
Mean
CDF | |||
Direc7on
Mean | |||
0
Baseline
N/A
1.817E-08
10.53% | |||
1
Latent
Fiber
Low
(6.25
6^3)
Decrease
1.905E-08
10.12% | |||
2
Latent
Fiber
High
(25
6^3)
Increase
1.669E-08
10.61% | |||
3
Latent
Fiber
Very
High
(50
6^3)
Increase
3.394E-08
42.63% | |||
4
Boron
Low
(4.0
g/FA)
Increase
1.690E-06
67.79% | |||
5
Boron
Very
High
(50
g/FA)
Decrease
1.308E-08
10.80% | |||
6
Boron
High
(15
g/FA)
Decrease
1.329E-08
10.65% | |||
7
Debris
Transport
Inside
ZOI
High
Increase
7.896E-08
28.50% | |||
8
Debris
Transport
Inside
ZOI
Low
Decrease
1.241E-08
12.03% | |||
9
Chemical
Temp
High
Increase
1.905E-08
10.17% | |||
10
Debris
Transport
Outside
ZOI
Low
Decrease
1.770E-08
10.61% | |||
11
Chemical
Head
Loss
Factors
High
Increase
2.287E-08
8.85% | |||
12
Penetra-on:
Low
Envelope
of
Filtra-on
Func-on
Increase
1.552E-07
10.93% | |||
13
ZOI
Size
Small
Decrease
6.795E-09
12.18% | |||
14
Turn
O
1
Spray
Longer
Decrease
1.569E-08
11.23% | |||
15
Hot
Leg
Injec-on
Longer
Increase
1.962E-08
9.96% | |||
16
Strainer
Limit
Higher
Decrease
1.639E-08
10.99% | |||
17
Water
Volume
Low
Increase
2.001E-08
10.13% | |||
18
Water
Volume
High
Decrease
1.655E-08
10.73% | |||
19
Debris
Density
High
Increase
2.567E-08
9.17% | |||
20
Temperature
Pro"les
Low
Increase
1.963E-08
10.14% | |||
21
Debris
Transport
Outside
ZOI
High
Increase
1.798E-08
10.65% | |||
21 | |||
Step 6: One-Way Sensitivity Analysis Tornado
Diagram:
Total
CDF | |||
Ra-o
of
Risk
under
the
Scenarios
to
Risk
under
Nominal
Parameter
Values | |||
Decreasing
Risk
Increasing
Risk | |||
0.10
1.00
10.00
100.00
1,000.00 | |||
Boron
Fuel
Limit
(4.0
g/FA
-
50
g/FA) | |||
Penetra-on
Low
Envelope | |||
Debris
Transport
Inside
ZOI | |||
ZOI
Size
Small | |||
Scenario
Descrip-ons | |||
Latent
Fiber
(6.25
6^3
-
50
6^3) | |||
Debris
Density
High | |||
Decreased
Parameter
Values | |||
Chemical
Head
Loss
Factors
High | |||
Water
Volume
Increased
Parameter
Values | |||
Turn
O
1
Spray
Longer | |||
Strainer
Limit
Higher | |||
Temperature
Pro"les
Low | |||
Hot
Leg
Injec-on
Longer | |||
Chemical
Temp
High | |||
Total
Failure
%
Outside
ZOI
Low
(80%) | |||
Spray
Transport
%
Outside
ZOI
High
(12%) | |||
22 | |||
Step 6: One-Way Sensitivity Analysis CDF
(Total) | |||
1000.0 | |||
Mean
Risk | |||
Baseline | |||
100.0 | |||
Risk
Ra-os | |||
Increasing
Risk | |||
10.0 | |||
1.0 | |||
Decreasing
Risk | |||
0.1 | |||
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
8.0
8.5
9.0 | |||
Boron
Fuel
Limit
(g/FA) | |||
23 | |||
Step 6: One-Way Sensitivity Analysis CDF
(Vessel) | |||
1000.0 | |||
Mean
Risk | |||
100.0
Baseline | |||
Risk
Ra-os | |||
Decreasing
Risk
Increasing
Risk | |||
10.0 | |||
1.0 | |||
0.1 | |||
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
8.0
8.5
9.0 | |||
Boron
Fuel
Limit
(g/FA) | |||
24 | |||
Step 6: One-Way Sensitivity Analysis CDF
(Sump) | |||
10.0 | |||
Mean
Risk | |||
Baseline | |||
Decreasing
Risk
Increasing
Risk | |||
Risk
Ra-os
1.0 | |||
0.1 | |||
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
8.0
8.5
9.0 | |||
Boron
Fuel
Limit
(g/FA) | |||
25 | |||
Step 6: One-Way Sensitivity Analysis Filtration Function Envelope 1$ | |||
0.95$ | |||
0.9$ | |||
0.85$ | |||
Filtra'on* | |||
Test$1:$353gpm$ | |||
0.8$ | |||
Test$2:$353gpm$ | |||
0.75$ Test$3:$353gpm$ | |||
Test$5:$358gpm$ | |||
0.7$ | |||
Test$7:$220gpm$ | |||
0.65$ Fit$ | |||
Upper$Envelope$ | |||
0.6$ | |||
Lower$Envelope$ | |||
0.55$ | |||
0$ 500$ 1000$ 1500$ 2000$ 2500$ 3000$ 3500$ 4000$ | |||
Strainer*Mass*in*Grams* | |||
26 | |||
Step 6: One-Way Sensitivity Analysis CDF
(Total) | |||
100.0 | |||
Mean
Risk | |||
Increasing
Risk | |||
10.0 | |||
Risk
Ra-os | |||
1.0 | |||
Decreasing
Risk | |||
0.1 | |||
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0 | |||
Fiber
Envelope
(0-Lower,
1-Upper) | |||
27 | |||
Step 6: One-Way Sensitivity Analysis CDF
(Vessel) | |||
100.0 | |||
Mean
Risk | |||
Baseline | |||
10.0 | |||
Risk
Ra-os | |||
Increasing
Risk | |||
1.0 | |||
Decreasing
Risk
0.1 | |||
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0 | |||
Fiber
Envelope
(0-Lower,
1-Upper) | |||
28 | |||
Step 6: One-Way Sensitivity Analysis CDF
(Sump) | |||
10.0 | |||
Mean
Risk | |||
Baseline | |||
Risk
Ra-os | |||
Increasing
Risk | |||
1.0 | |||
Decreasing
Risk
0.1 | |||
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0 | |||
Fiber
Envelope
(0-Lower,
1-Upper) | |||
29 | |||
Step 6: One-Way Sensitivity Analysis | |||
* Alternative distributions used for chemical head loss factor: | |||
: 1. No chemical head loss | |||
: 2. Factors constant at 1x mean (S=2.25/M=2.50/L=3.00) | |||
: 3. Factors constant at 2x mean (S=3.50/M=4.00/L=5.00) | |||
: 4. Factors constant at 3x mean (S=4.75/M=5.50/L=7.00) | |||
: 5. Truncated exponential (S=6/M=3.5/L=2.25) at tail probability of 1E-5 | |||
: 6. Truncated exponential (S=3/M=2.5/L=2.25) at tail probability of 1E-5 | |||
: 7. Truncated normal (Mean, St Dev = 3x Mean) | |||
Means have base case values of (S=2.25/M=2.50/L=3.00) 30 | |||
Step 6: One-Way Sensitivity Analysis Total
CDF | |||
2.0 | |||
Min
Temp
140 | |||
1.8 | |||
No
Minimum
Temp | |||
1.6 | |||
Increasing
Risk
| |||
Ra-o
of
Total
CDF
to
Base
Case | |||
Baseline | |||
1.4 | |||
1.2 | |||
1.0 | |||
Decreasing
Risk | |||
0.8 | |||
0.6 | |||
0.4 | |||
0.2 | |||
0.0 | |||
Distribu-on
of
Chemical
Head
Loss
Factor | |||
31 | |||
Step 9: Two-Way Sensitivity Analysis CDF
(Total)
as
a
Func7on
of
Fiber
Penetra7on
Limit
and
Filtra7on
Func7on | |||
0
-
1.E-08 | |||
1.E-09-1.E-08 | |||
1.E-08-1.E-07 | |||
1.E-04 | |||
1.E-07-1.E-06 | |||
1.E-05 | |||
1.E-06-1.E-05
| |||
CDF | |||
1.E-05-1.E-04 | |||
1.E-06 | |||
1.E-07 | |||
0.000 | |||
Filtra7on
Func7on | |||
1.E-08
0.167 | |||
0.333 | |||
1.E-09 | |||
4.0
0.500 | |||
5.0 | |||
6.0 | |||
7.0
1.000 | |||
8.5 | |||
Fiber
Penetra7on
Limit
(g/FA) | |||
32 | |||
Step 9: Two-Way Sensitivity Analysis CDF
(Total)
as
a
Func7on
of
Fiber
Penetra7on
Limit
and
Filtra7on
Func7on | |||
0.000 | |||
0
-
1.E-08 | |||
1.E-09-1.E-08 | |||
1.E-08-1.E-07
| |||
CDF | |||
0.167 | |||
1.E-07-1.E-06 | |||
Filtra7on
Func7on | |||
1.E-06-1.E-05 | |||
0.333 | |||
1.E-05-1.E-04 | |||
0.500 | |||
1.000 | |||
4.0
5.0
6.0
7.0
8.5 | |||
Fiber
Penetra7on
Limit
(g/FA) | |||
33 | |||
Step 9: Two-Way Sensitivity Analysis CDF
(Vessel)
as
a
Func7on
of
Fiber
Penetra7on
Limit
and
Filtra7on
Func7on | |||
0.000 | |||
0
-
1.E-08 | |||
1.E-09-1.E-08 | |||
1.E-08-1.E-07
| |||
CDF
0.167 | |||
1.E-07-1.E-06 | |||
Filtra7on
Func7on | |||
1.E-06-1.E-05 | |||
1.E-05-1.E-04
0.333 | |||
0.500 | |||
1.000 | |||
4.0
5.0
6.0
7.0
8.5 | |||
Fiber
Penetra7on
Limit
(g/FA) | |||
34 | |||
Explaining Subtle Modeling Trends Bruce Letellier - Alion Science Jeremy Tejada - University of Texas Austin 35 | |||
Nonintuitive Trends | |||
* Extensive usage of CASA Grande for parameter studies reveals four (4) subtle nonintuitive trends in quantitative risk | |||
* Two issues were opened as Error Reports. Two issues were investigated during parameter study. All dispositioned using case study analysis: | |||
- ER01 - Unqualified Coatings Spray Fraction | |||
* Increasing the fraction of UC transport under spray leads to slight reduction in risk | |||
- ER03 - Fiber Inventory Mass Conservation | |||
* Over time, fiber mass increases slightly | |||
- PS01 - Latent Fiber Effect at T0 | |||
* Increasing latent fiber slightly decreases risk | |||
- PS02 - TimeStep Effect | |||
* Decreasing time step can significantly decrease risk 36 | |||
ER01 - Unqualified Coatings Spray Fraction | |||
* Parameter studies of transport fractions indicate that increasing the 6% | |||
spray washdown fraction to 12% for failed epoxy slightly reduces risk (1% Reduction). | |||
* Spreadsheet calculations for assumed inventory of failed coatings shows very definite reduction in SV for increased spray fraction from 6% | |||
to 25%. | |||
* Holds for both linear mass and volume weighting and for quadratic volume weighting. Simply competition between particulate properties. | |||
* SV is the amount of drag area per unit solid debris volume. SV is independent of porosity. More debris does not imply higher average SV. | |||
* A proper formalism would use total surface area rather than average surfacetovolume ratio so that more of anything always adds drag. | |||
37 | |||
ER01 - Unqualified Coatings Spray Fraction (example) | |||
Spherical Material Initial Initial Final Final Diam Density Mass (m1) Mass (m1) | |||
(kg/m3) (kg) (kg) 1 10 1490 100 100 2 150 1986 25 30 SV 512,000 1581 | |||
* Surfacetovolume ratio can decrease when the proportion of larger particles increases (volume increases faster than area) | |||
* True at STP for spray fractions because large inventory of 10m enamel has zero spray fraction (other particulates increase in proportion and SV decreases) 38 | |||
ER03 - Fiber Inventory Mass Conservation | |||
* Parameter studies and code verification exercises show that fiber inventory increases slightly over the 36h calculation | |||
* Explicit timeforward integration uses leading concentrations for each time step. | |||
Coarse resolution delivers artificial mass at each time step that accumulates above initial inventory. | |||
* Smaller time steps reduce this effect. | |||
39 | |||
PS01 - Latent Fiber Effect at T0 | |||
* Parameter studies of latent fiber quantity show that increasing latent fiber slightly decreases risk. | |||
* Fiber filtration and shedding model accounts for improved filtration with increasing debris load. | |||
* More latent fiber initializes slightly higher filtration at beginning of recirculation | |||
* User option added to allow some fraction of latent fiber to pass through the strainer. | |||
40 | |||
PS01 - Latent Fiber Effect at T0 (cont) | |||
Sensitivity Plot: Common Random Numbers 3.5E08 Mean Risk 3.0E08 Total Core Damage Frequency Increasing Risk 2.5E08 2.0E08 Decreasing Risk 1.5E08 1.0E08 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 Latent Fiber (ft3) 41 | |||
PS02 - Time-Step Effect | |||
* Reduction of time step from 5 min to 1 min found to reduce quantitative risk by a factor of 1.5. | |||
* Explict timeforward integration introduces numerical diffusion that advances debris to the strainer artificially rapidly. | |||
* NPSH related failures occur before reduction in temperature regains margin. | |||
* Possible nonconservatism may be introduced by improved filtration on the debris bed that protects core. | |||
No numerical evidence that this dominates. | |||
42 | |||
PS02 - TimeStep Effect Trend 43 | |||
Summary: | |||
* The four nonintuitive observations discussed here have been explained at a fundamental level | |||
* Changes in numerical approximations and physical descriptions can eliminate undesired behavior | |||
* Subtle trends revealed in model interactions | |||
* Essential to confirming or correcting engineering intuition | |||
* Sensitivity studies create essential QA opportunities to exercise physical models over full parameter ranges | |||
- Identify input errors | |||
- Identify code level errors 44 | |||
Conclusions | |||
* Summarized approach to sensitivity analyses | |||
* Demonstrated the approach on several parameters | |||
* Reviewed and explained counterintuitive results observed with certain parameters 45}} |
Latest revision as of 20:50, 5 February 2020
ML14149A089 | |
Person / Time | |
---|---|
Site: | South Texas |
Issue date: | 05/21/2014 |
From: | Harrison A South Texas |
To: | Balwant Singal Division of Operating Reactor Licensing |
References | |
STP-GSI-191, TAC MF2400, TAC MF2401 | |
Download: ML14149A089 (46) | |
Text
NRR-PMDA-ECapture Resource From: Harrison Albon <awharrison@STPEGS.COM>
Sent: Wednesday, May 21, 2014 11:03 AM To: Singal, Balwant Cc: Kee, Ernie; Blossom, Steven; Murray, Michael
Subject:
STP Sensitivity Presentation Attachments: STP-GSI-191 Presentation May 222014.pdf
- Balwant, Our presentation is attached. Also, Alion confirmed the SWRI presentation has no proprietary information.
Wayne 1
CASA Grande Sensitivity Studies May 22,2014
Introductions
- Presenters Mike Murray Wayne Harrison Ernie Kee David Morton Bruce Letellier 2
Introductions
- Contributors Steve Blossom Zahra Mohaghegh Seyed Reihani Jeremy Tejada Don Wakefield 3
Summary
- Summarize approach to sensitivity analyses
- Demonstrate the approach on several parameters
- Review and explain counterintuitive results observed with certain parameters 4
Development Status and Potential Application o Development Status o NOT being proposed for NRC review/approval as part of the Risk-Informed Pilot Application o Will require appropriate validation and verification o Potential Applications o Facilitate evaluation of emergent plant conditions Facilitate identification/prioritization of compensatory actions Quantitative assessment may be required to formalize evaluation o Evaluation of plant modifications 5
Potential Application and Development Status, cont.
o Current and Potential Features (Ref. ML14072A211) o One-way sensitivity, tornado plots (Step 6) o One-way sensitivity studies, UQ plots (Step 7) o One-way sensitivity: Spider Plots (Step 8) o Two-way (two at a time) sensitivity studies (Step 9) o Meta models (Step 10) (response surface correlation)
To support multi-attribute sensitivity and simplified analysis of plant response o Compliance with standard software quality assurance o Importance o Helps show the relative importance of parameters o Helps to identify potential errors (counterintuitive results) and thereby contributes to analysis quality 6
CASA Grande Sensi-vity Studies
John Hasenbein David Morton Jeremy Tejada Alex Zolan May 22, 2014 7
Sensitivity Studies
- Approach
- Boron fuel limit
- Fiber penetration function
- Head loss studies 8
10-Step Sensitivity Analysis Process
- Step 1: Define the Model
- Step 2: Select Outputs of Interest
- Step 3: Select Inputs of Interest
- Step 4: Choose Nominal Values and Ranges for Inputs
- Step 5: Estimate Model Outputs under Nominal Input Values
- Step 6: One-Way Sensitivity Analysis: Sensitivity Plots & Tornado Diagrams
- Step 7: One-Way Sensitivity Analysis: UQ Plots
- Step 8: One-Way Sensitivity Analysis: Spider Plots
- Step 9: Two-way Sensitivity Analysis: Two-way Sensitivity Plots
- Step 10: Metamodels & Design of Experiments 9
Step 1: Define the Model
- We wont detail CASA Grande here (Volume 3)
- Use CASA Grande to estimate probability of sump failure and boron fiber limit failure, conditional on small, medium & large breaks
- Estimate change in core damage frequency (CDF) in events/year due to GSI-191 issues using these failure probability estimates and corresponding frequencies
- All results here are conditional on all pumps working 10
Step 2: Select Outputs of Interest
- Change in core damage frequency (CDF)
- Sometimes, we report ratio of CDF estimate for a scenario to CDF estimate for baseline and call this the risk ratio
- Use stratified sampling on initiating frequency
- Use IID replications within each cell of stratification
- Use common random numbers across scenarios; i.e., use CRNs across specified changes in input parameters 11
Step 2: Outputs: Estimating CDF Indices and Sets:
i = 1, . . . , F index for cells stratifying frequency replications k = 1, . . . , N index for set of pump states Events:
SL, M L, LL small, medium, large LOCA P Sk pumps in state k Fi initiating frequency in cell i S sump failure B boron fiber limit failure CD core damage Parameters:
fSL , fM L , fLL frequency (events/CY) of a small, medium, large LOCA P (P Sk ) probability mass of P Sk P (Fi ) probability mass of Fi P (SlLOCA, Fi , P Sk ) estimate of probability of S given LOCA = SL, M L, orLL, Fi , P Sk P (BlLOCA, Fi , P Sk ) estimate of probability of B given LOCA = SL, M L, orLL, Fi , P Sk RBASE non-GSI-191 core damage frequency (events/CY)
RCD estimate of core damage frequency (events/CY) 12
Step 2: Outputs: Estimating CDF CDF = RCD RBASE X F X N
= P (Fi )P (P Sk )
- i=1 k=1 h
fSL
- P (SlSL, Fi , P Sk ) + fSL
- P (BlSL, Fi , P Sk )
+fM L
- P (SlM L, Fi , P Sk ) + fM L
- P (BlM L, Fi , P Sk )
i
+fLL
- P (SlLL, Fi , P Sk ) + fLL
- P (BlLL, Fi , P Sk )
- We report results with:
- fSL , fML , fLL from Volume 2s Table 4-1
- P(all pumps working)=1
- P(Fi ): Bounded Johnson fit to NUREG-1829
- We form a variance estimate for the above estimator 13
Step 3: Select Inputs of Interest
- Amount of Latent Fiber in Pool: Existing dust/dirt in containment, based on plant measurement. Assumed to be in the pool at start of recirculation, uniformly mixed. During fill up, latent debris available to penetrate sump screen.
- Boron Fiber Limit: Refers to threshold where boron precipitation occurs for cold leg breaks. Fiber limit comes from vendor testing that shows no pressure drop occurs with full chemical effects. Assume all fiber that penetrates sump screen deposits uniformly on core.
- Debris Transport Fractions in ZOI: Refers to debris transport fractions involving three-zone ZOI. Each insulation type has characteristic ZOI divided in three sections to account for type of damage within each zone.
14
Step 3: Select Inputs of Interest
- Chemical Precipitation Temperature: CASA Grande assumes that, once a thin bed of fiber forms on strainer, chemical head loss factors apply when pool temperature reaches precipitation temperature.
- Total Failure Fraction for Debris Outside the ZOI: CASA Grande uses table of total failure fractions applied to transport logic trees. Fraction of each type (fiber, paint and coatings, etc.) that passes to the pool are used to understand what is in the pool as a function of time during recirculation.
- Chemical Head Loss Factor: Used as a multiplier on conventional head loss calculated in CASA Grande. Multiplier is applied if thin bed is formed and pool temperature is at or below precipitation temperature.
15
Step 3: Select Inputs of Interest
- Fiber Penetration Function: Fraction of fiber that bypasses the ECCS sump screen as a function of the amount of fiber on the screen.
- Size of ZOI: ZOI defined as direct function (multiplier) of break size and nominal pipe diameter; e.g., for NUKON fiber, ZOI is 17 times break diameter. ZOI is spherical unless break is not DEGB, in which case it is hemispherical. Truncated by any concrete walls within the ZOI.
- Time to Turn Off One Spray Pump: If three spray pumps start, then by procedure one is secured. Time to secure the pump is governed by operator acting on the conditional action step in procedure.
16
Step 3: Select Inputs of Interest
- Time to Hot Leg Injection: Similar to the spray pump turn off time, the time to switch one or more trains to hot leg injection operation is governed by procedure.
- Strainer Buckling Limit: Limit is the differential pressure across ECCS strainer at which strainer is assumed to fail mechanically. This limit is based on engineering calculations that incorporate safety factor.
- Water Volume in the Pool: Depending on break size, amount of water in pool, as opposed to amount in RCS and other areas in containment, varies. Smaller breaks tend to result in less pool volume than larger breaks.
17
Step 3: Select Inputs of Interest
- Debris Densities: Depends on amount and type of debris that arrives in pool. These densities are used in head loss correlations to calculate, for example, debris volume.
- Time Dependent Temperature Profiles: Temperature of water in sump affects air release and vaporization during recirculation. Time-dependent temperature profile comes from coupled RELAP5-3D and MELCOR simulations depending on break size.
- Spray Failure Fraction for Debris Outside ZOI: CASA Grande uses a table of failure fractions applied to transport logic trees. Fractions of each type of debris that passes to pool are used to understand what is in pool as function of time during recirculation. The spray failure fraction is fraction of failed coatings that wash to pool during spray operation.
18
Step 4: Nominal Values and Ranges for Inputs Input Parameter Level 1 Level 2 Level 3 Level 4
Latent Fiber (63) 12.5 6.25 25 50
Boron Fiber Limit (g/FA) 7.5 4 15 50
Debris Transport Inside ZOI Base Low High
Water Volume in Pool Base -10% +10%
Chemical Precipita-on Temp (oF) 140o 160o
Total Failure Frac-on Outside ZOI Base Low
Chemical Head Loss Factor Base +50%
Fiber Penetra-on Func-on Base High
ZOI Size Base -33%
Turn o 1 Spray Pump (min.) 20 1440
Hot Leg Injec-on (min.) 345 450
Strainer Buckling Limit (6. H2O) 9.35 9.6
Debris Density (lbm/63) Base +25%
Temperature Pro"les (oF) Base -5%
Spray Transport Frac-on 6% 12%
19
Step 5: Estimate Outputs Under Nominal Values of Inputs
- Sensi7vity Measure Expected 95% CI 95% CI 95% CI CI HW %
Mean CDF
Direc7on Half-Width Low Limit Upper Limit of Mean
0 Baseline None 1.817E-08 1.914E-09 1.626E-08 2.009E-08 10.53%
20
Step 6: One-Way Sensitivity Analysis
- Expected 0.95-level CI HW % of
Sensi7vity Measure Mean CDF
Direc7on Mean
0 Baseline N/A 1.817E-08 10.53%
1 Latent Fiber Low (6.25 6^3) Decrease 1.905E-08 10.12%
2 Latent Fiber High (25 6^3) Increase 1.669E-08 10.61%
3 Latent Fiber Very High (50 6^3) Increase 3.394E-08 42.63%
4 Boron Low (4.0 g/FA) Increase 1.690E-06 67.79%
5 Boron Very High (50 g/FA) Decrease 1.308E-08 10.80%
6 Boron High (15 g/FA) Decrease 1.329E-08 10.65%
7 Debris Transport Inside ZOI High Increase 7.896E-08 28.50%
8 Debris Transport Inside ZOI Low Decrease 1.241E-08 12.03%
9 Chemical Temp High Increase 1.905E-08 10.17%
10 Debris Transport Outside ZOI Low Decrease 1.770E-08 10.61%
11 Chemical Head Loss Factors High Increase 2.287E-08 8.85%
12 Penetra-on: Low Envelope of Filtra-on Func-on Increase 1.552E-07 10.93%
13 ZOI Size Small Decrease 6.795E-09 12.18%
14 Turn O 1 Spray Longer Decrease 1.569E-08 11.23%
15 Hot Leg Injec-on Longer Increase 1.962E-08 9.96%
16 Strainer Limit Higher Decrease 1.639E-08 10.99%
17 Water Volume Low Increase 2.001E-08 10.13%
18 Water Volume High Decrease 1.655E-08 10.73%
19 Debris Density High Increase 2.567E-08 9.17%
20 Temperature Pro"les Low Increase 1.963E-08 10.14%
21 Debris Transport Outside ZOI High Increase 1.798E-08 10.65%
21
Step 6: One-Way Sensitivity Analysis Tornado Diagram: Total CDF
Ra-o of Risk under the Scenarios to Risk under Nominal Parameter Values
Decreasing Risk Increasing Risk
0.10 1.00 10.00 100.00 1,000.00
Boron Fuel Limit (4.0 g/FA - 50 g/FA)
Penetra-on Low Envelope
Debris Transport Inside ZOI
ZOI Size Small
Scenario Descrip-ons
Latent Fiber (6.25 6^3 - 50 6^3)
Debris Density High
Decreased Parameter Values
Chemical Head Loss Factors High
Water Volume Increased Parameter Values
Turn O 1 Spray Longer
Strainer Limit Higher
Temperature Pro"les Low
Hot Leg Injec-on Longer
Chemical Temp High
Total Failure % Outside ZOI Low (80%)
Spray Transport % Outside ZOI High (12%)
22
Step 6: One-Way Sensitivity Analysis CDF (Total)
1000.0
Mean Risk
Baseline
100.0
Risk Ra-os
Increasing Risk
10.0
1.0
Decreasing Risk
0.1
3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0
Boron Fuel Limit (g/FA)
23
Step 6: One-Way Sensitivity Analysis CDF (Vessel)
1000.0
Mean Risk
100.0 Baseline
Risk Ra-os
Decreasing Risk Increasing Risk
10.0
1.0
0.1
3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0
Boron Fuel Limit (g/FA)
24
Step 6: One-Way Sensitivity Analysis CDF (Sump)
10.0
Mean Risk
Baseline
Decreasing Risk Increasing Risk
Risk Ra-os 1.0
0.1
3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0
Boron Fuel Limit (g/FA)
25
Step 6: One-Way Sensitivity Analysis Filtration Function Envelope 1$
0.95$
0.9$
0.85$
Filtra'on*
Test$1:$353gpm$
0.8$
Test$2:$353gpm$
0.75$ Test$3:$353gpm$
Test$5:$358gpm$
0.7$
Test$7:$220gpm$
0.65$ Fit$
Upper$Envelope$
0.6$
Lower$Envelope$
0.55$
0$ 500$ 1000$ 1500$ 2000$ 2500$ 3000$ 3500$ 4000$
Strainer*Mass*in*Grams*
26
Step 6: One-Way Sensitivity Analysis CDF (Total)
100.0
Mean Risk
Increasing Risk
10.0
Risk Ra-os
1.0
Decreasing Risk
0.1
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Fiber Envelope (0-Lower, 1-Upper)
27
Step 6: One-Way Sensitivity Analysis CDF (Vessel)
100.0
Mean Risk
Baseline
10.0
Risk Ra-os
Increasing Risk
1.0
Decreasing Risk 0.1
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Fiber Envelope (0-Lower, 1-Upper)
28
Step 6: One-Way Sensitivity Analysis CDF (Sump)
10.0
Mean Risk
Baseline
Risk Ra-os
Increasing Risk
1.0
Decreasing Risk 0.1
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Fiber Envelope (0-Lower, 1-Upper)
29
Step 6: One-Way Sensitivity Analysis
- Alternative distributions used for chemical head loss factor:
- 1. No chemical head loss
- 2. Factors constant at 1x mean (S=2.25/M=2.50/L=3.00)
- 3. Factors constant at 2x mean (S=3.50/M=4.00/L=5.00)
- 4. Factors constant at 3x mean (S=4.75/M=5.50/L=7.00)
- 5. Truncated exponential (S=6/M=3.5/L=2.25) at tail probability of 1E-5
- 6. Truncated exponential (S=3/M=2.5/L=2.25) at tail probability of 1E-5
- 7. Truncated normal (Mean, St Dev = 3x Mean)
Means have base case values of (S=2.25/M=2.50/L=3.00) 30
Step 6: One-Way Sensitivity Analysis Total CDF
2.0
Min Temp 140
1.8
No Minimum Temp
1.6
Increasing Risk
Ra-o of Total CDF to Base Case
Baseline
1.4
1.2
1.0
Decreasing Risk
0.8
0.6
0.4
0.2
0.0
Distribu-on of Chemical Head Loss Factor
31
Step 9: Two-Way Sensitivity Analysis CDF (Total) as a Func7on of Fiber Penetra7on Limit and Filtra7on Func7on
0 - 1.E-08
1.E-09-1.E-08
1.E-08-1.E-07
1.E-04
1.E-07-1.E-06
1.E-05
1.E-06-1.E-05
1.E-05-1.E-04
1.E-06
1.E-07
0.000
Filtra7on Func7on
1.E-08 0.167
0.333
1.E-09
4.0 0.500
5.0
6.0
7.0 1.000
8.5
Fiber Penetra7on Limit (g/FA)
32
Step 9: Two-Way Sensitivity Analysis CDF (Total) as a Func7on of Fiber Penetra7on Limit and Filtra7on Func7on
0.000
0 - 1.E-08
1.E-09-1.E-08
1.E-08-1.E-07
0.167
1.E-07-1.E-06
Filtra7on Func7on
1.E-06-1.E-05
0.333
1.E-05-1.E-04
0.500
1.000
4.0 5.0 6.0 7.0 8.5
Fiber Penetra7on Limit (g/FA)
33
Step 9: Two-Way Sensitivity Analysis CDF (Vessel) as a Func7on of Fiber Penetra7on Limit and Filtra7on Func7on
0.000
0 - 1.E-08
1.E-09-1.E-08
1.E-08-1.E-07
CDF 0.167
1.E-07-1.E-06
Filtra7on Func7on
1.E-06-1.E-05
1.E-05-1.E-04 0.333
0.500
1.000
4.0 5.0 6.0 7.0 8.5
Fiber Penetra7on Limit (g/FA)
34
Explaining Subtle Modeling Trends Bruce Letellier - Alion Science Jeremy Tejada - University of Texas Austin 35
Nonintuitive Trends
- Extensive usage of CASA Grande for parameter studies reveals four (4) subtle nonintuitive trends in quantitative risk
- Two issues were opened as Error Reports. Two issues were investigated during parameter study. All dispositioned using case study analysis:
- ER01 - Unqualified Coatings Spray Fraction
- ER03 - Fiber Inventory Mass Conservation
- Over time, fiber mass increases slightly
- PS01 - Latent Fiber Effect at T0
- Increasing latent fiber slightly decreases risk
- PS02 - TimeStep Effect
- Decreasing time step can significantly decrease risk 36
ER01 - Unqualified Coatings Spray Fraction
- Parameter studies of transport fractions indicate that increasing the 6%
spray washdown fraction to 12% for failed epoxy slightly reduces risk (1% Reduction).
- Spreadsheet calculations for assumed inventory of failed coatings shows very definite reduction in SV for increased spray fraction from 6%
to 25%.
- Holds for both linear mass and volume weighting and for quadratic volume weighting. Simply competition between particulate properties.
- SV is the amount of drag area per unit solid debris volume. SV is independent of porosity. More debris does not imply higher average SV.
- A proper formalism would use total surface area rather than average surfacetovolume ratio so that more of anything always adds drag.
37
ER01 - Unqualified Coatings Spray Fraction (example)
Spherical Material Initial Initial Final Final Diam Density Mass (m1) Mass (m1)
(kg/m3) (kg) (kg) 1 10 1490 100 100 2 150 1986 25 30 SV 512,000 1581
- Surfacetovolume ratio can decrease when the proportion of larger particles increases (volume increases faster than area)
- True at STP for spray fractions because large inventory of 10m enamel has zero spray fraction (other particulates increase in proportion and SV decreases) 38
ER03 - Fiber Inventory Mass Conservation
- Parameter studies and code verification exercises show that fiber inventory increases slightly over the 36h calculation
- Explicit timeforward integration uses leading concentrations for each time step.
Coarse resolution delivers artificial mass at each time step that accumulates above initial inventory.
- Smaller time steps reduce this effect.
39
PS01 - Latent Fiber Effect at T0
- Parameter studies of latent fiber quantity show that increasing latent fiber slightly decreases risk.
- Fiber filtration and shedding model accounts for improved filtration with increasing debris load.
- More latent fiber initializes slightly higher filtration at beginning of recirculation
- User option added to allow some fraction of latent fiber to pass through the strainer.
40
PS01 - Latent Fiber Effect at T0 (cont)
Sensitivity Plot: Common Random Numbers 3.5E08 Mean Risk 3.0E08 Total Core Damage Frequency Increasing Risk 2.5E08 2.0E08 Decreasing Risk 1.5E08 1.0E08 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 Latent Fiber (ft3) 41
PS02 - Time-Step Effect
- Reduction of time step from 5 min to 1 min found to reduce quantitative risk by a factor of 1.5.
- Explict timeforward integration introduces numerical diffusion that advances debris to the strainer artificially rapidly.
- NPSH related failures occur before reduction in temperature regains margin.
- Possible nonconservatism may be introduced by improved filtration on the debris bed that protects core.
No numerical evidence that this dominates.
42
PS02 - TimeStep Effect Trend 43
Summary:
- The four nonintuitive observations discussed here have been explained at a fundamental level
- Changes in numerical approximations and physical descriptions can eliminate undesired behavior
- Subtle trends revealed in model interactions
- Essential to confirming or correcting engineering intuition
- Sensitivity studies create essential QA opportunities to exercise physical models over full parameter ranges
- Identify input errors
- Identify code level errors 44
Conclusions
- Summarized approach to sensitivity analyses
- Demonstrated the approach on several parameters
- Reviewed and explained counterintuitive results observed with certain parameters 45