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Stp quaterly meeting 1015-rev+2.0
1. University of New Mexico
CHLE (T3,4,5) & Bench test (SNC-001) Update
STP Quarterly Progress Meeting
10/15/2013
Seung-Jun Kim, Ph.D.
2. University of New Mexico
Overview
•
Summary of CHLE tests (T1,2,3,4 and T5)
– Objectives
– Operating condition, system configurations
– Preliminary results/ analysis
•
Comparative Test matrix with CHLE tests
–
–
–
–
Prototypical temperature & aluminum condition (LOCA) vs. non-prototypical LCOA temperature &
aluminum (100times more than prototypical) condition: T125 vs T34
NEI-bed vs. blender-bed: T2 vs. T5 or T3/T4
Al precipitation effect vs. zinc source effect : T3 vs. T4
MB LOCA vs. LB LOCA : T1 vs. T2
•
Comprehensive analysis for all CHLE tests result T1,2,3,4 and 5
– Precipitation map analysis to predict aluminum precipitation
•
SNC-001 Bench test Results
– Al corrosion/ release rate result
– Passivation of Al release from the SNC test result
– Proposed new Al release correlation (with passivation)
2
3. University of New Mexico
Background and Objectives
• UNM’s CHLE tests were designed simulate the corrosion product in
the tank, corrosion product transfer from tank to column, corrosion
induced head loss behavior over the 10 or 30 day testing periods.
• 10-day or 30-day chemical effect test simulating LB-LOCA (T2,T5),
MB-LOCA (T1), and non prototypical LOCA (T3,T4) with conditions
found at South Texas Project Nuclear Operating Company (STPNOC)
were conducted to assess the generic safety issue (GSI) 191
chemical effects
• The objectives of those 5 tests were to create conditions that
captured the prototypical or non-prototypical temperature profile,
corrosion materials, and chemistry conditions in ECCS system, and
evaluated the corrosion induced head loss on blender-processed
beds and NEI-processed beds over the testing period.
3
4. University of New Mexico
CHLE loop schematic diagram
Head loss modules (3 identical columns)
Corrosion tank module
4
5. University of New Mexico
Experimental set-up
• Corrosion tank module
– Corrosion materials (Al, Zn, GS coupons, fiberglass,
concrete) were loaded
– Tank temperature was controlled by the set temperature
profile (LB-LOCA, MB-LOCA, non-prototypical condition)
– Solution in tank was well mixed with recirculating loop
• Head loss modules
– 3 identical columns were linked to tank
– Each column was loaded with blender-processed bed or
NEI-processed bed
– Pressure drops (head loss) were measured at each column
5
7. University of New Mexico
Test conditions
T1
T2
T3
T4
T5
Corrosion
materials
Al scaffolding
Fiberglass
Al scaffolding
Fiberglass
GS, Zn
coupons
Concrete
Al coupons
Fiberglass
GS, Zn
coupons
Concrete
Al coupons
Fiberglass
Al scaffolding
Fiberglass
GS, Zn
coupons
Concrete
AV (ft/s)
0.01
0.01
0.01
0.01
0.01
pH
7.22
7.32
7.22
7.22
7.25
Temperature
profile
MB-LOCA
LB-LOCA
Nonprototypical
Nonprototypical
LB-LOCA
Testing period
30-day
30-day
10-day
10-day
10-day
Bed prep.
NEI (1)
NEI (2)
NEI (3)
NEI (1)
NEI (2)
NEI (3)
Blender(1)
NEI(2)
Blender(3)
Blender(1)
NEI(2)
Blender(3)
Blender (1)
Blender (2)
Blender (3)
7
8. University of New Mexico
Comparative Test matrix with CHLE tests
1. Prototypical temperature & aluminum condition (LOCA) vs. non-prototypical LCOA
temperature & aluminum (100times more than prototypical) condition: T125 vs T34
–
–
T1,2, and 5 followed the prototypical LOCA temperature profile with prototypical aluminum material
turbidity kept decreasing over the testing
T3 and T4 temperature condition designed to generate aggressive corrosion product by maintaining
80C for first 5 days turbidity decreased for first 5 days and started increasing after day 6
2. NEI-bed vs. blender-bed: T2 vs. T5 or T3/T4
–
–
T2 (NEI) vs T5 (blender) showed that blender bed (100’’ of water) indicated significant head loss
compared to NEI bed (2’’ of water)
T3 and T4 also showed that a blender bed is much more sensitive than an NEI bed in the same
operating condition
3. Al precipitation effect vs. zinc source effect : T3 vs. T4
–
–
When zinc sources are present, initial high turbidity was observed and head loss increased along
with certain time.
When aluminum precipitation occurred, turbidity started increasing, and head loss increase was also
observed in some cases.
4. MB LOCA vs. LB LOCA : T1 vs. T2
–
With NEI-processed bed condition, the head loss increase and turbidity trend for both MB, LB LOCA
condition looks similar. No big difference observed.
8
9. University of New Mexico
1. Prototypical temperature & aluminum condition (LOCA)
vs. non-prototypical LCOA temperature & aluminum
(100times more than prototypical) condition: T125 vs T34
9
10. University of New Mexico
Turbidity measurement to detect the precipitated
particles in solution
T1
T2
T5
In T1,2 and 5, turbidity never increased during the testing periods
no particle formation but particle filtration or segmentation
T3
T4
In T3 and T4, turbidity
decreased and after day 6-7
started increased
Potential of aluminum
precipitation due to
supersaturation
10
11. University of New Mexico
Head loss
T2
140
T5
Column_1(Blender)
Column_2(Blender)
Column_3(Blender)
120
100
o
Normalized Head loss at 20 C [''H2O]
T1
80
60
40
20
0
0
1
2
3
4
5
6
7
8
9
Time [Day]
Head loss with NEI-bed (T12) was small but head loss (T5) with blender-bed was much higher.
However, the head losses resulted from the initial release (zinc), no al precipitation effect
T3
T4
In T3, two increases in head loss were
found, first increase was attributed to
“zinc source effect” and second
increase was “Al precipitation effect”.
In T4 head loss increased as turbidity
increased (Al precipitation effect)
11
20. University of New Mexico
Al precipitation map with CHLE tests data
13.0
12.5
12.0
Non-precipitation region
pH+p[Al]T
11.5
11.0
Precipitation region
10.5
Solubility by VMINTEQ
UNM, T5 test result
UNM, T4 test result
UNM, T3 test result
UNM, T2 test result
UNM, T1 test result
10.0
9.5
Day 7 in T3
Day 6 in T4
9.0
20
30
40
50
60
70
80
90
100
o
Temperature ( C)
Precipitation line based on turbidity
20
22. University of New Mexico
4. SNC-001 Bench test result and proposed new Al release
correlation (with passivation)
22
23. University of New Mexico
Objectives
• Current bench test is consisted of baseline Al release data
evaluating temp-effect, pH-effect with TSP in solution at
different time(5h ~ 5day)
• The result clearly demonstrated passivation or inhibiting
effect over time.
• Previous WCAP correlation is only function of Temp, and pH,
but time variable was not incorporated in their model,
which leads to not capture passivation effect on Al release
• In this study, new correlation is proposed and validated
with SNC bench test data.
• In future, this proposed correlation will be further validated
with other literature data and CHLE data
23
24. University of New Mexico
Al release bench test with TSP in solution
Series
pH Adjustment
Target pH
Temperature, °C
1100
TSP
7.34
85
1200
NaOH
7.34
85
1300
TSP
6.84
85
1400
TSP
7.84
85
1500
TSP
7.34
70
1600
TSP
7.34
55
Average test coupon surface
= 0.00146 m2
24
25. University of New Mexico
Al release [mg/m2] with time
14000.0
12000.0
10000.0
8000.0
6000.0
4000.0
2000.0
0.0
0
1000
2000
3000
4000
5000
6000
“Al release increased rapidly over the first 24 hours
and stop release due to passivation (inhibiting effect on al release)”
7000
8000
25
26. University of New Mexico
WCAP-16530 (Eq. 6-2)
Release = f(Temp., pH)
“At intermediate times (i.e., less than 30 days), Equation 6-2 will underpredict
the release rate. Hence, the cumulative 30-day integrated aluminum product
release predicted by this equation should be used for screen testing, even if an
intermediate time period is being simulated. If a cumulative value at an
intermediate time is desired, individual plants must justify the derivation of
that value.”
WCAP-16530 page 96
26
27. University of New Mexico
WCAP always overpredict even at intermediate
time (i.e., less than 30 day)
meausred release vs. WCAP release
70000.0
60000.0
Al release [mg/m2]
50000.0
40000.0
30000.0
20000.0
10000.0
0.0
0
1000
2000
3000
4000
5000
6000
7000
8000
time [min]
1100 meausred al release [mg/m2]
1100 WCAP cal. Al release [mg/m2]
27
28. University of New Mexico
A proposed Al release equation with boric-TSP in
solution
• Using multi-variable nonlinear regression scheme, following regression
parameters were determined within the adjusted R-square value of 0.95.
• Matlab and Orgin were utilized for MVN regression.
28
30. University of New Mexico
Measured release vs. UNM's release calculation
14000.0
12000.0
Al release [mh/m2]
10000.0
8000.0
6000.0
4000.0
2000.0
0.0
0
1000
2000
3000
4000
5000
6000
7000
8000
Time[min]
1100 measured al release [mg/m2]
1100 UNM prediction al release [mg/m2]
1300-measured
1300 UNM-predictio
1400-measured
1400-UNM-predictio
1500-measured
1500-UNM-prediction
1600-measured
1600-UNM-predictio
30
31. University of New Mexico
T4 CHLE test
•
•
•
•
Water volume in CHLE tank is 300 gallon (1135 liter)
ICP results are given
Total Al area = 2.787 m2
Al release is calculated below
Day
0
1
2
3
4
5
Al (mg/L)
0.2
4
5.1
5
4.9
4.9
Al (mg)
Al release
[mg/m2]
227
4540
5788.5
5675
5561.5
5561.5
81
1629
2077
2036
1995
1995
31
32. University of New Mexico
Al release prediction with proposed correlation for CHLE-T4
Measured Al release vs. predicted al release over the first 5 days of
T4 at Temp=80 C, pH=7.22
2500
Al release [mg/m2]
2000
1500
1000
500
0
0
1000
2000
3000
4000
5000
6000
7000
8000
Time [Min]
T4 Measured al release(mg/m2)
proposed correlation's predictio for T4 al release (mg/m2)
32
35. University of New Mexico
Aluminum oxide layer thickness from XPS
T3 aluminum oxide layer ~ 15 nm
T4 aluminum oxide layer ~ 2.3 nm
Maybe zinc effect …
35
36. University of New Mexico
Al release rate vs. Al release
• Al Release rate : mg/m2-min
• Al Release per unit area : mg/m2
• In long-term corrosion, release rate might be accurate
and misleading user.
• Release per unit area is more clear method to describe
how much Al corroded or release into solution
• In this study, all data and comparison will be made
based on the Al release [mg/m2] as a reference unit.
36
38. University of New Mexico
Temperature effect on Al release [mg/m2]
38
39. University of New Mexico
Flow sweep test with NEI vs. blender
40
1.6
Head Loss in Blender Bed ("H2O)
Superficial Velocity (ft/s)
1.4
Superficial Velocity (ft/s)
0.06
0.10
0.8
0.6
0.02
0.4
0.08
Head Loss ("H2O)
0.04
Superficial velocity (ft/s)
1.0
20
0.06
0.04
10
0.02
0.2
0.0
0
20
40
60
80
Time (Minutes)
100
120
0.00
140
0
0.00
0
20
40
60
80
100
120
140
160
180
Time (Mins)
39
Superficial velocity (ft/s)
30
1.2
Head Loss ("H2O)
0.12
Head Loss in NEI Bed("H2O)
40. University of New Mexico
Al concentration and Turbidity
6
0.8
Al Concentration [mg/L]
Turbidity [NTU]
0.6
4
3
0.4
2
Turbidity [NTU]
Concenturation of Al [mg/L]
5
0.2
Scale [Al(OH)3,?,?, etc.,]
1
0
0
1
Rapid Al Release
2
3
4
5
6
7
8
Time [Days]
Al Saturated (no release)
9
10
11
0.0
12
Al
Al3+
Al supersaturated
Possible precipitating
Corrosion / Release (ICP result)
40
41. University of New Mexico
Ergun Correlation
Ergun Correlation (1952)
- Kozeny-Carman equation(1956)
- Valid in laminar flow
41
42. University of New Mexico
NEI bed behavior with analytic model
1.8
1.6
Average head Loss in NEI ("H2O)
Assume that inertial term become negligible
when the flow are in laminar region
NEI Bed sweep test indicate good example of
the relationship between U & HL
Head Loss ("H2O)
1.4
1.2
1.0
0.8
0.6
“a” value for analytic equation for NEI-bed can
be determined from the experimental upward
flow sweep test result.
0.4
0.2
0.0
0.00
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
Superficial Velocity (ft/s)
42
