ML060650429
| ML060650429 | |
| Person / Time | |
|---|---|
| Site: | Brunswick, PROJ0710  |
| Issue date: | 02/28/2006 |
| From: | General Electric Co |
| To: | Office of Nuclear Reactor Regulation |
| References | |
| DRF 0000-0048-4552, MFN 06-065 NEDO-33264, Rev 0 | |
| Download: ML060650429 (83) | |
Text
ENCLOSURE 2 MFN 06-065 GE Licensing Topical Report, NEDC-33264P, BSEP Noise Report Non-Proprietary Version IMPORTANT NOTICE This is a non-proprietary version of NEDC-3:3264P, which has the proprietary information removed. Portions of the enclosure that have been removed are indicated by an opena and closed bracket as shown here (( ))
GE Energy
) Nuclear 3901 Castle Hayne Rd Wilmington, NC 28401 NEDO-33264 Revision 0 Class I DRF 0000-0048-4552 February 2006 NON-PROPRIETARY VERSION LICENSING TOPICAL REPORT GENERAL ELECTRIC BOILING WATER REACTOR BRUNSWICK NUCLEAR POWER STATION UNIT 1 GE ANALYSIS OF OPRM NOISE Copyright 2006
NEDO-33264 NON-PROP:EUETARY VERSION IMPORTANT NOTICE REGARDING THE CONTENTS OF THIS REPORT Please Read Carefully A. Disclaimer The only undertakings of the General Electric Company (GE) respecting information in this document are contained in the contract between the company receiving this document and GE. Nothing contained in this document shall be construed as changing the applicable contract. The use of this information by anyone other than a customer authorized by GE to have this document, or for any purpose other than. that for which it is intended, is not authorized. With respect to any unauthorized use, GE makes no representation or warranty, and assumes no liability as to the completeness, accuracy or usefulness of the information contained in this document, or that its use may not infringe privately owned rights.
B. Non-Proprietary Information Notice This is a non-proprietary version of the document NEDC-33264P, which has the proprietary information removed. Portions of the document that have been removed are indicated by an open and closed double brackets as shown here (( )).
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NE-DO-33264 NON-PROP:RIETARY VERSION TABLE OF CONTENTS Page Executive Summary .............................. vii Acronyms, Definitions and Abbreviations ............ ................. viii 1.0 Introduction ............................. 1l 1.1 Background .............................. 1
1.2 Purpose and Scope
.............................. 2 1.3 Approach .............................. 2 2.0 Brunswick Noise Evaluation .3 2.1 OPRM Cell Evaluation ............................ 3 2.2 Calculation Procedure and Results ............................ 4 2.2.1 Data Preparation .4 2.2.2 Frequency Analysis - Unfiltered LPRM Data .6 2.2.3 Time Analysis - Unfiltered LPRM Data .7 2.2.4 Frequency Analysis - Filtered OPRM Data .8 2.2.5 Time Analysis - Filtered OPRM Data .9 2.2.6 Successive Confirmation Count Evaluation .1 2.2.7 Safety Significance .1 3.0 Conclusions .. 13 4.0 References .. 16 iii
NElDO-33264 NON-PROPRIETARY VERSION LIST OF FIGURES Figure Title Page Figure 1: LPRM Assignments for Brunskwi-.k 1 OPRM Channel 1.17 Figure 2: LPRM Assignments for Brunskwi k 1 OPRM Channel 2 .18 Figure 3: LPRM Assignments for Brunskwi -k 1 OPRM Channel 3 .... 19 Figure 4: LPRM Assignments for Brunskwi k 1 OPRM Channel 4 ........ 20 Figure 5: Frequency Content - Unfiltered LPRMs & Composite OPRM Ch I Cell 8 .21 Figure 6: Frequency Content - Unfiltered LPRMs & Composite OPRM Ch 3 Cell 8 .22 Figure 7: Time Series Analysis -High Count Window - Unfiltered LPRMs & Composite OPRM Ch I Cell 8 .22 Figure 8: Time Series Analysis - High Count Window - Unfiltered LPRMs & Composite OPRM Ch I Cell 9 ....... 24 Figure 9: Time Series Analysis - High Count Window - Unfiltered LPRMs & Composite OPRM Ch 3 Cell 8 ................ 25 Figure 10: Time Series Analysis - High Count Window - Unfiltered LPRMs & Composite OPRM Ch 3 Cell 13 ............ ..... ............. 2..6.......
26 Figure 11: Time Series Analysis - High Count Window - Unfiltered LPRMs & Composite OPRM Ch 3 Cell 14 . ........... 266.................
Figure 11: Time Series Analysis - High Count Window - Unfiltered LPRMs & Composite OPRM Ch 3 Cell 14 ............... 27 Figure 12: Time Series Analysis - High Count Window - Unfiltered LPRMs & Composite OPRM Ch 4 Cell 9 . ................... ... 28 Figure 13: Time Series Analysis - High Count Window - Unfiltered LPRMs & Composite OPRM Ch 4 Cell 14 ..................................... 29 Figure 14: Time Series Analysis - High Count Window - Unfiltered LPRMs & Composite OPRM Ch 4-Cell 19 . .................. - ..... 30 Figure 15: Time Series Analysis - High Count Window - Unfiltered LPRMs & Composite OPRM Ch 4 Cell 22 ............ 31 31...............
Figure 16: Time Series Analysis - High Coumt Window - Unfiltered LPRMs & Composite OPRM Ch 4 Cell 24 ............ 32 3.2................
Figure 17: Time Series Analysis - Low Count Window - Unfiltered LPRMs OPRM Ch 1 Cell 8 ... 33 Figure 18: Time Series Analysis - Low Count Window - Unfiltered LPRMs OPRM Ch I Cell 9 . 34 Figure 19: Time Series Analysis - Low Count Window - Unfiltered LPRMs OPRM Ch 3 Cell 8. 35 Figure 20: Time Series Analysis - Low Count Window - Unfiltered LPRMs OPRM Ch 3 Cell 13 .36 iv
NE DO-33264 NON-PROP:RIETARY VERSION Figure 21: Time Series Analysis - Low Count Window - Unfiltered LPRMs OPRM Ch 3 Cell 14 ...... 37 Figure 22: Time Series Analysis - Low Count Window - Unfiltered LPRMs OPRM Ch 4 Cell 9 ........ 38 Figure 23: Time Series Analysis - Low Count Window - Unfiltered LPRMs OPRM Ch 4 Cell 14 ...... 39 Figure 24: Time Series Analysis - Low Count Window - Unfiltered LPRMs OPRM Ch 4 Cell 19 ...... 40 Figure 25: Time Series Analysis - Low Count Window - Unfiltered LPRMs OPRM Ch 4 Cell 22 ...... 41 Figure 26: Time Series Analysis - Low Count Window - Unfiltered LPRMs OPRM Ch 4 Cell 24 ...... 42 Figure 27: Time Series Analysis - High Count Window - Unfiltered LPRMs (Normalized)
(All OPRM Cells) ..................................................................... 43 Figure 28: Time Series Analysis - Low Count Window - Unfiltered LPRMs (Nornalized)
(All OPRM Cells) ..................................................................... 44 Figure 29: Time Series Analysis - Full 5 Minute time Span - Unfiltered LPRMs (Normalized)
(All OPRM Cells) ...................................................................... 45 Figure 30: Frequency Content - Filtered OPRM Ch 1 Cell 8 .................................................................. 46 Figure 31: Time Series Analysis -High Count Window -Filtered OPRM Ch 1 Cell 8, Oscillation Signal and Counts ..................................................................... 47 Figure 32: Time Series Analysis -High Count Window -Filtered OPRM Ch 1 Cell 9 Oscillation Signal and Counts ...................................................................... 48 Figure 33: Time Series Analysis -High Count Window -Filtered OPRM Ch 3 Cell 8 Oscillation Signal and Counts ...................................................................... 49 Figure 34: Time Series Analysis -High Count Window -Filtered OPRM Ch 3 Cell 13 Oscillation Signal and Counts ..................................................................... 50 Figure 35: Time Series Analysis -High Count Window -Filtered OPRM Ch 3 Cell 14 Oscillation Signal and Counts ..................................................................... 51 Figure 36: Time Series Analysis -High Count Window -Filtered OPRM Ch 4 Cell 9 Oscillation Signal and Counts ..................................................................... 52 Figure 37: Time Series Analysis -High Count Window -Filtered OPRM Ch 4 Cell 14 Oscillation Signal and Counts ..................................................................... 53 Figure 38: Time Series Analysis -High Count Window -Filtered OPRM Ch 4 Cell 19 Oscillation Signal and Counts ...................................................................... 54 Figure 39: Time Series Analysis -High Count Window -Filtered OPRM Ch 4 Cell 22 Oscillation Signal and Counts ...................................................................... 55 Figure 40: Time Series Analysis -High Count Window -Filtered OPRM Ch 4 Cell 24 Oscillation Signal and Counts ...................................................................... 56 Figure 41: Time Series Analysis -Low Count Window -Filtered OPRM Ch 1 Cell 8 Oscillation Signal and Counts ...................................................................... 57 v
NE-DO-33264 NON-PROP:RIETARY VERSION Figure 42: Time Series Analysis -Low Count Window -Filtered OPRM Ch 1 Cell 9 Oscillation Signal and Counts ..................................................................... 58 Figure 43: Time Series Analysis -Low Count Window -Filtered OPRM Ch 3 Cell 8 Oscillation Signal and Counts ..................................................................... 59 Figure 44: Time Series Analysis -Low Count Window -Filtered OPRM Ch 3 Cell 1:3 Oscillation Signal and Counts .................................................................... 60 Figure 45: Time Series Analysis -Low Count Window -Filtered OPRM Ch 3 Cell 14 Oscillation Signal and Counts ..................................................................... 61 Figure 46: Time Series Analysis -Low Count Window -Filtered OPRM Ch 4 Cell 9 Oscillation Signal and Counts ..................................................................... 62 Figure 47: Time Series Analysis -Low Count Window -Filtered OPRM Ch 4 Cell 14 Oscillation Signal and Counts ..................................................................... 63 Figure 48: Time Series Analysis -Low Count Window -Filtered OPRM Ch 4 Cell 19 Oscillation Signal and Counts ..................................................................... 64 Figure 49: Time Series Analysis -Low Count Window -Filtered OPRM Ch 4 Cell 221 Oscillation Signal and Counts ..................................................................... 65 Figure 50: Time Series Analysis -Low Count Window -Filtered OPRM Ch 4 Cell 24 Oscillation Signal and Counts .................................................................... 66 Figure 51: Time Series Analysis - High Count Window - Filtered OPRM Data (All OPRM Cells) .................................................................... 67 Figure 52: Time Series Analysis - Low Count Window - Filtered OPRM Data (All OPRM Cells) .................................................................... 68 Figure 53: Time Series Analysis - Full 5 Minute time Span - Filtered OPRM Data (All OPRM Cells) .................................................................... 69 Figure 54: Time Series Analysis - High Count Window- Selected Plant Data ...................................... 70 vi
NEDO-33264 NON-PROPRIETARY VERSION EXECUTIVE
SUMMARY
The Detect and Suppress Solution - Confirmation Density (DSS-CD) stability solution has been installed at Brunswick Units 1 and 2 using NUMAC based Oscillation Power Range Monitor (OPRM) hardware. To evaluate the DSS-CD OPRM system performance data was collected and analyzed at rated EPU power at Brunswick 1, prior to placing the system in operation. The data indicates unexpected coherent periodic noise resulting in high counts (in excess of the setpoint) for multiple OPRM cells, in the absence of coupled thermal-hydraulic/neutronic instability. The cause of the coherent periodic noise is not known, but does not appear to be EPU related, or related to whether the reactor is operating at rated or off-rated power levels. Possible causes include reactor pressure or core flow variations that could potentially affect the flux in all parts of the reactor simultaneously.
This report shows that the observed coherent periodic noise pattern has no safety significance but could result in spurious alarms and trip if it occurred inside the OPRM scram enabled region.
The issue of spurious scram is addressed in DSS-CD Rev 5, section 3.3.1.6.
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NEDO-33264 NON-PROPRIETARY VERSION ACRONYMS, DEFINITIONS AND ABBREVIATIONS Term Definition DSS-CD Detect and Suppress Solution - Confirmation Density FFT Fast Fourier Transform Hz Hertz LPRM Local Power Range Monitor NUMAC Nuclear Measurement and Control System OPRM Oscillation Power Range Monitor SCC Successive Confirmation Count Tmin Minimum Period for Oscillation Detection (seconds) viii
NEDO-33264 NON-PROP3JUETARY VERSION
1.0 INTRODUCTION
1.1 BACKGROUND
The Detect and Suppress Solution - Confirmation Density (DSS-CD) stability solution has been installed at Brunswick using NUMAC based Oscillation Power Range Monitor (OPRM) hardware. The OPRM is a 4-channel system. Each channel is designed to detect coupled thermal-hydraulic/neutronic instability by monitoring the signals of multiple OPRM cells (-24 cells/channel) throughout the core. Each OPRM cell consists of 3 or 4 Local Power Range Monitor (LPRM) detector inputs from specified radial and axial locations. A typical OPRM cell may have inputs from A, B, C and D level detectors, but can be limited to fewer levels (e.g., 2 detectors at the C level and 2 at the D level). In the DSS-CD stability solution design (Reference 1), each channel monitors different aspects (period and amplitude) of oscillatory behavior to detect either core-wide or regional mode instability, and issues a channel trip signal if the following two conditions are satisfied:
a) Confirmation Density: The number of oscillation counts reaches or exceeds 10 in at least 5 OPRM cells concurrently. The OPRM cell confirmation count is incremented by one count when two successive periods are within a period tolerance of 100 msec and the oscillation base period is in the expected range for instability events (successive oscillation peaks or minima occurring between 0.8 to 4 seconds of each other). The oscillation counter resets to zero if these conditions are not satisfied.
b) Amplitude Discrimination: The normalized filtered oscillation amplitude of any OPRM cell at or above 10 Successive Confirmation Count (SCC) reaches or exceeds the amplitude discriminator level of 1.03.
The current installed DSS-CD system at Brunswick is an earlier design version, based on Reference 2, which does not include the amplitude discriminator detection feature.
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NEDO-33264 NON-PROPRIETARY VERSION 1.2 PURPOSE AND SCOPE Data has been collected at rated power at Brunswick to evaluate the DSS-CD OPRM system performance prior to placing the system in a plant operational mode. The raw data indicates unexpected concurrent oscillations that exceed the count trip setpoint for multiple OPRM cells, even though there is no evidence of coupled thermal-hydraulic/neutronic instability (i.e., the oscillation amplitude does not grow and is in the expected neutron noise level). This report presents the results of an evaluation to determine the safety and operational significance of the observed periodic noise pattern.
1.3 APPROACH Time and frequency domain analyses of unfiltered LPRM data and filtered OPEM data are performed and results are compared to expected performance.
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NE DO-33264 NON-PROPRIETARY VERSION 2.0 BRUNSWICK NOISE EVALUATION 2.1 OPRM CELL EVALUATION Data was collected and analyzed for a large number of the OPRM cells (shown in Table 1) at Brunswick Unit 1 on 5/12/04 from 6:31 to 6:36 AM when the OPRM equipment was registering a large number counts. The reactor was at approximately 100% rated EPU power (2923 MWt) and rated flow during this time. An illustration of the LPRM to OPRM cell assignment is shown in Figures 1, 2, 3 and 4, and the cells (and their LPRM components) for which data was taken and analyzed in this report are shown as filled in circles.
Table 1: List of Analyzed OPRM Cells OPRM Cell Identification Cell LPRM Assignments Channel Cell Detector P1 Detector #2 Detector #3 Detector #4 1 8 20-37A 28-37B 28-29B 20-29A 1 9 28-37B 36-37C 36-29C 28-29B 3 8 20-37D 28-37D 28-29A 20-29C 3 13 20-29C 28-29A 28-21B 20-21B 3 14 28-29A 36-29A 36-21D 28-21B 4 9 28-37A 36-37D 36-29B 28-29C 4 14 28-29C 36-29B 36-21B 28-21C 4 19 28-21C 36-21B 36-13D 28-13A 4 22 20-13B 28-13A 28-05A 20-O05B 4 24 36-13D 44-13C X 36-05D (Note 1)
Note 1: Only 3 LPRMs allocated for this corner cell.
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NEDO-33264 NON-PROPRIETARY VERSION It is believed that analysis of this large number of cells provides good evidence of the nature of the phenomenon that is causing the high OPRM counts.
For each OPRM cell, the data set that was analyzed consisted of the following:
- 2) Filtered (Processed) normalized OPRM readings
- 3) Counts and Base Period measured by the OPRM equipment The data was taken at a sample rate of 20 samples per sec (i.e., 50 ms interval), so for the 5 minutes of data in the data set there were 6000 samples for each variable. The data contained spans of time where the SCC for multiple OIPRM cells was high (which could lead to false trips),
and also where the counts were low and do not lead to false alarms. For each cell, both frequency and time domain analyses were performed for the unfiltered (raw) signals of each individual LPRMs that provide input to cells, and for the combination of the LPRM inputs to the OPRM cell. These frequency and time analyses were performed for the normalized filtered OPRM inputs, over the same time span. Unfiltered and filtered time domain responses were compared for various time spans including those when there were high measured counts and those when there were not.
2.2 CALCULATION PROCEDURE AND RESULTS 2.2.1 Data Preparation The raw unfiltered data for all LPRMs in each of the cells listed in Table 1 was analyzed.
During this time period, the overall reactor power was constant, but key plant parameters were measured and correlated to the observed OPRM noise. The data analysis was done in the following parts:
- 1. Individual LPRM data analyses a) The 6000 data values (20 samples/sec for 5 minutes) for each of the LPRM detectors were used for the individual detector time analyses.
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NE.DO-33264 NON-PROPRUETARY VERSION b) The average value for each LPRM detector was determined and the variation of each individual reading from the average was calculated. The resulting 6000 data variation values for the individual LPRM detectors were used for the individual detector frequency analyses.
- 2. OPRM analyses from Composed Unfiltered LPRM data c) The average of the 4 individual LPRM detector signals in each cell were determined for each time step. This provided 6000 data values representing the raw unfiltered OPRM signal for each cell. These data were used for the unfiltered OPRM signal time analyses for each cell. The cell readings were also normalized, so that the unfiltered noise in all OPRM cells could be compared and analyzed.
d) The average of the 6000 unfiltered OPRM cell signals was determined for each cell and the variation of each individual reading from the average was calculated. The resulting 6000 data variation values were used for frequency analysis of each cellos unfiltered OPRM signal.
- 3. OPRM analyses from Filtered OPRM data e) The 6000 data values for each of the filtered and normalized OPRM cell signals were used for the filtered OPRM signal time analyses for each cell. This normalized data also allowed comparison and analysis of the filtered noise in all OPRM cells.
0 The average for each of the 4 filtered and normalized OPRM cell signals was determined and the variation of each individual reading from the average was calculated. The resulting 6000 data variation values were used for the filtered and normalized OPRM signal frequency analyses for each cell.
g) The 6000 data values for each of the OPRM cell oscillation confirmation counts were used to determine time spans of high and low counts in order to compare the raw and filtered OPRM cell signals and confirm the observed counts. The measured oscillation period was also used to evaluate and analyze the measured counts.
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NEDO-33264 NON-PROPIUETARY VERSION
- 4. Plant data analysis h) Supporting plant data (APRM power, Core dP, Reactor Pressure) was taken. at half the speed of but in the same time frame as the LPRM/OPRM data. This plant data was used to determine if there was a correlation between the observed OPRM performance and key plant variables.
2.2.2 Frequency Analysis - Unfiltered LI'RM Data A frequency domain analysis using Fast Fourier Transform (FFT) method was performed using MathCAD 2001 Professional version. The Fourier analysis plots amplitude as a function of frequency, and is used to identify peaks at various frequencies. Since data was analyzed at 20 samples per sec, only frequencies up to 10 Hz could be evaluated.
Frequency analysis evaluation was done for data described in Section 2.2.1, Items b, d, and f.
(( )) Sample results for individual LPRM signals from OPRM Channel I Cell 8 and Channel 3 cell 8 are shown in Figure 5 and Figure 6. ((
)) The composite of the OPRM!Channel 1 Cell 8 and Channel 3 cell 8, made up by averaging the individual unfiltered LPRM signals for each of those cells, is also shown in Figures 5 and 6. ((
)) The frequency analysis does not show at what time the oscillations sta.t, how long they last, and whether the oscillations seen on various LPRM and OPRM signals are correlated.
For such an evaluation, a time analysis is required.
((
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))
2.2.3 Time Analysis - Unfiltered LPRM Data A time domain analysis was performed using MathCAD. In MathCAD, the time analysis plot can be any length of time. However, to dete;rmine a correlation between the noise from various LPRMs, a short time frame is required. Two short time frames were chosen, one for the time that contained the maximum counts and the other for a time frame where the counis were low.
For the "high-count" time frame a 10 second window (185 to 195 seconds from da:a start) was chosen to span the time from zero counts to maximum observed OPRM cell count of 12, and to include the time when the trip setpoint of 10C was reached. For the "low-count" time frame a 30 second window (0 to 30 seconds from data start) was chosen in which neither of the OPRM cells had a confirmed count of only 1 or 2.
Time analysis evaluation was done for data described in Section 2.2.1, Items a, c, and e. Results are shown in Figure 7 for individual unfiltered LPRM detector signals and the composite (or average) unfiltered OPRM signal for the cell 8 Ch. 1 in the high-count time window. Results for all the other cells are shown in Figures 8 - 16. ((
11 Results for individual unfiltered LPRM detector signals in the low-count time window are shown in Figure 17 to 26. ((
))
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NEDO-33264 NON-PROPRUETARY VERSION A comparison of the time series analysis for all the OPRM cells is shown in Figure 27 for the high count time window, and Figure 28 for the low count time window. In these plots the average unfiltered OPRM data (( )) is plotted as a function of time for each OPRRM cell. This provides a simple way to visually determine the degree of coherence between the unfiltered OPRM signals.
(( )) Noise measured by all analyzed OPRMs, including those with LPRMs in the middle of the core (:For example OPRM Channel 3 Cell 13) and at the edges of the core (for example OPRM Channel 4 Cell 24)
)) (Figure 27) ((
))(Figure 28). ((
According to the data, ((
)) (Figure 27) clearly show that the noise is sufficiently periodic to register as confirmed counts. In the low-count time window, Figure 28 shows that the noise is also spatially coherent but the oscillation are not sufficiently periodic to register as accumulating confirmed counts. A plot of the normalized unfiltered OPRM time series data, for the entire 5 minutes is shown in Figure 29.
2.2.4 Frequency Analysis - Filtered OPILM Data A frequency analysis similar to that described in Section 2.3.2 for the unfiltered LPRM data was also performed on the filtered and normalized OPRM data. The OPRM signal is filtered using a Butterworth filter with a corner frequency of 1 Hz to eliminate high frequency noise components at the plant. Results are shown in Figure 30 for Ch I Cell 8, and these are representative of all cells. ((
)) The results showed that fcr the filtered Page 8 of 70
NEDO-33264 NON-PROPRIETARY VERSION OPRM signals most of the power was in the low frequency region (< I Hz) just as for the unfiltered OPRM signals (Figure 6). ((
))
2.2.5 Time Analysis - Filtered OPRM Data A time domain analysis similar to that described in 2.3.3 for the unfiltered OPRM data was performed for the filtered and normalized O0'RM data. The results for the filtered data for each cell in the high-count time window are shown in Figure 31a - 40a as a comparison with the unfiltered data. In these figures the unfiltered OPRM data was normalized to I to facilitate comparison with the filtered OPRM data, which is already normalized. ((
)) However, the peaks and valleys for the filtered data occurred at a later time than the unfiltered data because of time shift due to OPRM filtering. The observed delay time of - 14 second is in line with the expected delay for the frequency of the oscillations and filter cut-off frequency.
According to the data, (( ))in the high-count time window (( )). The data also shows that the noise is quite periodic over a large part of the high-count time window, ((
The OPRM registers a count if the period is between 0.8 and 4.0 seconds, and if the period tolerance (magnitude of the difference in peak-to-peak times between successive oszillations) is less than 0.1 seconds. A plot of how the counts accumulate, along with the measured oscillation period, is shown for each OPRM cell in Figures 3 lb - 40b. The data clearly shows that the noise is sufficiently periodic (within the design limits) over a sufficiently long time to register as confirmed counts that can accumulate to values greater than the confirmed high count setpoint of
- 10. Note that in this time frame the oscillation period magnitude is well within the wide limits for measuring counts. ((
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NEDO-33264 NON-PROPIUETARY VERSION Also because of the coherence of the noise, all OPRMs register high counts at the same time.
Since the OPRM system logic requires 5 or more cells in 2 of the 4 channels to trip, the OPRM system would trip on confirmed counts if it was in an armed state. In actuality the OPRM system is not armed at rated operation, so the question of system trip is not germane for this set of data. However similar coherent noise has also been observed in power-flow operating regions where the OPRM system is armed, so the conclusions from analysis of this data are also applicable to the regions where the OPRM is armed and operational. The current DSS-CD algorithm also requires that the magnitude of the oscillation be above 3%, and since in this case the magnitude was less than 3% (see Figure 27), the OPRM would not have scrammed if the amplitude discriminator had been implemented and this noise occurred in the region where the OPRM was armed. However, it is clear that the presence of the coherent noise increases the chance of spurious OPRM scram, and such spurious scram events have been observed.
The data shows that the oscillations do not grow which is as expected since the noise data was taken at rated power where there is no instability concern. So the measured high counts is a coherent noise and spurious scram concern and not a reactor instability or plant safety concern.
A plot of the filtered and unfiltered OPRM data in the low-count window for all analyzed OPRM cells is shown in Figures 41a - 50a, and a plot of the counts in this time period is shown in Figures 41b - 50b. ((
)) So this noise signature would not result in spurious trips.
A comparison of the time series analysis for the filtered data from all the OPRM cells in the high-count window and low-count window is shown in Figures 51 and 52 respectively. ((
)) shown in Figures 27 and 28. A plot of the filtered OPRM time data, for the entire 5 minutes is shown in Figure 53.
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NEDO-33264 NON-PROPRIETARY VERSION 2.2.6 Successive Confirmation Count Evaluation
((
)) When changing from Option III to DSS-CD, the minimum oscillation period (Tmin) was reduced from 1.2 seconds to 0.80 second.
This change has made the oscillation detection algorithm sensitive to noise signatures with lower time period, and there is some mechanism that is producing coherent noise which is sufficiently periodic and lasts for a sufficiently long time at these frequencies to cause spurious high count trips. It is worth noting that for the data analyzed in this report, the concurrent multiple OPRM high confirmation count events at power would not have been detected by Option III as a result of the higher Tmin value. So for the analyzed data, the spurious trip on high counis would not have occurred with the Option III Tmin value. However, since the cause of the coherent oscillations is not known, it is possible that high counts ((
))
2.2.7 Safety Significance It is clear that the observed high oscillation count event at rated power condition is not a thermal-hydraulic instability event because the calculated decay ratio at power is approximately 0.2 and the reactor is completely stable. The tim.- analysis shows that during the time of coherent multiple OPRM cell high confirmation count level, the oscillation magnitude did not grow.
Oscillations with amplitude growth, that could challenge reactor stability, did not occur. The observed oscillations were due only to periodic and coherent noise. The periodic nature of the coherent oscillations were observed to last for several seconds (sufficient to trip the count setpoint), and then dissipated. The exact cause for this short-lived and relatively infrequent phenomenon cannot be established at this time based on the available plant data. A time plot of the APRM flux power (%), reactor pressure (psig) and core dP (psid) for the high-count and low-count window is shown in Figure 54. Visually, there appears to be no significant correlation between the reactor pressure or core dP and the observed coherent OPRM noise. ((
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)) However, the data indicates that these oscillations cannot challenge reactor stability. Since there is no amplitude growth associated with this relatively short and infrequent phenomenon, neutron flux variations remain at the typical noise level, which does not represent any added safety risk. The power fluctuations that may affect the fuel are associated with the heat flux and are an order of magnitude smaller than the neutron flux noise amplitude. Therefore, this coherent periodic noise phenomenon has no significant impact on plant safety, but can result in spurious trips.
If the coherent noise phenomenon occurs during a real thermal hydraulic instability event, it would tend to cause reactor scram before instability conditions are reached. This would be an operational concern, but would be conservative from the plant safety point of view.
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3.0 CONCLUSION
S Analysis of Brunswick 1 OPRM noise data has confirmed the presence of coherent periodic noise that could impact OPRM performance. Although the analysis was performed at rated power where the OPRM is not armed, this noise has been observed to occur in other power-flow regions where the OPRM is armed. Results similar to those described in this report were also obtained when data taken in the OPRM aimed region at 60% power, during a Brunswick 2 power-down operation on 6/25/04, was analyzed. Consequently, the conclusions of the analysis shown in this report are applicable to evaluate the general impact of the observed coherent reactor noise on OPRM performance. Following are the main conclusions:
- 1. There is a coherent -1 Hz periodic noise that affects multiple LPRMs synchronously for times lasting up to approximately 6 seconds in this data set. The LPRMs individually (and collectively through the OPRM) oscillate coherently at a frequency of about 1 Hz. This makes all the OPRM cells in all channels register high counts in excess of the setpoint at about the same time, causing a high-count trip. The current standard DSS-CD design also includes an amplitude discriminator, so with that feature OPRM would scram only if in addition to the high count trip, the oscillation amplitude exceeded the 3% amplitude setpoint.
- 2. The decay ratio at rated power was estimated to be 0.2, so the reactor is in a very stable state.
Moreover, no growth of oscillations was observed. So the simultaneous high counts in all cells are a measure of periodic coherent noise oscillations and not an indication of reactor thermal-hydraulic instability. If the coherent noise phenomenon occurs during a real thermal hydraulic instability event when the OPRM is armed, it would tend to cause reactor scram before instability conditions are reached. This would be an operational conceni, but would be conservative from the plant safety point of view.
- 3. The cause of the periodic coherent noise is not known. Possible causes include reactor pressure or core flow variations that could potentially affect the flux in all parts of the reactor simultaneously. ((
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)) Similar high counts have also been observed at a number of plants that have implemented Option III, so the phenomenon does not appear to be related to EPU or differences between Option III and DSS-CD. ((
1))
- 4. ((
- 5. For the analyzed data set, a high count of 12 was observed, but since the source of the coherent periodic noise is not known, it is possible that spurious counts higher than this would be observed at some time during power operation at Brunswick.
- 6. The observed coherent high confirmation count period was in the range of 0.9 to 1.1 seconds.
Such oscillations would not have been detected with the Option III stability solution because the value of Tmin, the minimum period for oscillation detection, was set to 1.2 seconds for Option III. However, since the cause of the coherent oscillations is not known, it is possible that high counts may also be measured for higher DSS-CD Tmin values.
- 7. The NUMAC OPRM appears to correctly filter and normalize the signal. The comer frequency (- 1 Hz) attenuates the amplitude of the oscillation but does not affect the ability of the OPRM instrument to count the oscillations. There is a good correlation between the counts from filtered OPRM data and the counts from unfiltered LPRM data combined according to the OPRM assignments.
- 8. There is no evidence of oscillation growth during the coherent periodic high oscillation count event, and the oscillation amplitude is approximately at the normal noise level. For the current data set the noise amplitude is approximately 2% which is less than Ihe standard Page 14of70
NEDO-33264 NON-PROPIUETARY VERSION DSS-CD amplitude setpoint of 3%. So this noise magnitude incident upon an arnned OPRM with the amplitude discriminator would not have resulted in a scram, even though the high-count setpoint was exceeded, since exceeding both the high count and noise amplitude setpoints is required for scram. ((
)) It is noted that the protection against high OPRM counts is reduced when the noise at the LPRMs is periodic and coherent, so it is clear that the chance of spurious OPRM scram. when such noise is present, is higher than it would have been if the noise were random.
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NEDO-33264 NON-PROPMIETARY VERSION
4.0 REFERENCES
I. NEDC-33075P Revision 5, Licensing Topical Report, General Electric Boiling Water Reactor Detect and Suppress Solution - Confirmation Density, November 2005.
- 2. NEDC-33075P Revision 3, Licensing Topical Report, General Electric Boiling Water Reactor Detect and Suppress Solution -- Confirmation Density, January 2004.
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NEDO-33264 NON-PROPRIETARY VERSION Figure 1: LPRM Asshinments for Brunskwick 1 OPRM Channcl I LO N
cr, 0 _ _ _ _
4 12 20 28 36 44 Page 17 of 70
NEDO-33264 NON-PROPRIETARY VERSION Fig!ure 2: LPRM Assillnments for Brunskwick I OPRM Channel 2 LO 4 8 2S499W CNI C))( 2 <3 (12 15 .
cv,e 4 12 20 28 36 42'1 Page 18 of 70
NE.DO-33264 NON-PROPRIETARY VERSION Figure 3: LPRM Assig~nments for Brunskivick 1 OPRM Channel 3 LO N-!
.15766 04 4 122 412 2() 28 36 4,it Page 19 of 70
NEDO-33264 NON-PROPPIETARY VERSION Fi sure 4: LPRM Assignments for Brtinskwick 1 OPRM Channel 4 v) 3 4 12 0 28 36 44 Page 20 of 70
NEDO-33264 NON-PROPRIETARY VERSION Figiure 5: Frequency Content - Unfiltered LPRMs & Composite OPRM Ch I Cell 8 1]
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NEDO-33264 NON-PROPRIETARY VERSION Figure 6: Frequency Content - Unfiltered LPRMs & Composite OPRM Ch :3 Cell 8
((
))
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NEDO-33264 NON-PROPIUETARY VERSION Figzure 7: Time Series Analysis -High Count Window - Unfiltered LPRMs & Composite OPRM Ch 1 Cell 8 I]
1]
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NEDO-33264 NON-PROPRIETARY VERSION Filuire 8: Time Series Analysis - High Colint Window - Unfiltered LPRMs & Composite OPRMT Ch I Cell 9 11 Page 24 of 70
NUDO-33264 NON-PROPRIETARY VERSION Fiiure 9: Time Series Analvsis - High Coint Window - Unfiltered LPRMs & Composite OPRMI Ch 3 Cell 8
((
1]
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NE DO-33264 NON-PROPRIETARY VERSION Figure 10: Time Series Analysis - IIigh Count Window - Unfiltered LPRMs & Composite OPRY[ Ch 3 Cell 13 r]
II Pa.ge 26 of 70
NE:DO-33264 NON-PROPRUETARY VERSION Figzure 11: Time Series Analvsis - Hligh Count Wllindow - Unfiltered LPRMs & Composite OPRM: Ch 3 Cell 14
))
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NEIDO-33264 NON-PROP:RIETARY VERSION Fiiure 12: Time Series Analysis - High C'ount Window - Unfiltered LPRINls & Composite OPRM Ch 4 Cell 9
((
))
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NEDO-33264 NON-PROPRIETARY VERSION Figuiire 13: Time Scrics Analvsis - Ilif!h Count Window - Unfiltcred LPR~ls & Compositc OPRM, Ch 4 Cell 14
((
))
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NEDO-33264 NON-PROPRIETARY VERSION Figure 14: Timc Series Analysis - flifah Count Window - Unfiltered LPR~ls & Composite OPRM1 Ch 4 Cell 19
((
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NEDO-33264 NON-PROPRIETARY VERSION Fia!urc 15: Time Serics Analvsis - High Count Vindow - Unfiltcred LPR~ls & -Composite OPRM Ch 4 Cell 22
))
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NEDO-33264 NON-PROPRIETARY VERSION Figuirc 16: Time Series Analvsis - lligh Count Window - Unfiltered LPRMs & Composite OPRM: Ch 4 Cell 24
((
))
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NIEDO-33264 NON-PROPRIETARY VERSION Figl~re 17: Time Series Anmlysis - Low Count Window - Unfiltered LPll'Ms OPRM Ch 1 Cell 8
((
1]
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NEDO-33264 NON-PROPIUETARY VERSION Figure 18: Time Series Annlvsis - Low Count WVindow - Unfiltered LPRMs OPRM Ch I Cell 9
((
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NEDO-33264 NON-PROPRIETARY VERSION Fifiurc 19: Time Series Analvsis - Low Count Window - Unfiltered LPRIls OPRMT Ch 3 Cell 8 II Page 35 of 70
NEDO-33264 NON-PROPRIETARY VERSION Figlure 20: Time Series Analvsis - Low Count Window - Unfiltered LPRMs OPRM Ch 3 Cell 13
((
II]
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NEDO-33264 NON-PROPRIETARY VERSION Figtire 21: Time Series Anzilvsis - Low Count Window - Unfiltered LPRMs OPRM Ch 3 Cell 14 Page 37 of 70
NEDO-33264 NON-PROPRIETARY VERSION Fi2ure 22: Time Series Annlvsis - Low Count Window - Unfiltered LPRMs OPRNM Ch 4 Cell 9 Page 38 of 70
NEDO-33264 NON-PROPRIETARY VERSION Figure 23: Time Series Analvsis -Low Count Window - Unfiltered LPRMs OPRM. Ch 4 Ccll 14 I'l Pege 39 of 70
NE;DO-33264 NON-PROPRIETARY VERSION Figiure 24: Time Series Analvsis - Low Count Window - Unfiltered LPRMs OPRM: Ch 4 Ccll 19
((
1]
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NEDO-33264 NON-PROPPJETARY VERSION Figuire 25: Time Series Analvsis - Low Count Window - Unfiltered LPRIls OPRM Ch 4 Cell 22 1]
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NEDO-33264 NON-PROPRIETARY VERSION Figiure 26: Time Series Analysis - Low Count Window - Unfiltered LPRMs OPRM Clh 4 Cell 24
((
1]
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NE;DO-33264 NON-PROPIUETARY VERSION Fioure 27: Time Series Analvsis - High Count Vindow - Unfiltered LPRMs (Normalized)
(All CIPRM Cells)
((
1]
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NEDO-33264 NON-PROPRIETARY VERSION Figuirc 28: Time Series Analysis - Low Count Window - Unfiltered LPRMs (Normalized)
(All OPRM Cells)
))
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NE;DO-33264 NON-PROPRUETARY VERSION Finure 29: Time Series Annhvsis - Full 5; Minute time Span - IJUnfiltered LPRlNfs (Normnlized)
(A.ll OPRM Cells)
((
1]
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NEDO-33264 NON-PROPRIETARY VERSION Fif'urc 30: Frequencv Content - Filtered OPRM Ch 1 Cell 8
((
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NEDO-33264 NON-PROPFJETARY VERSION Fifiurc 31: Time Series Analysis -Bigh Count Window -Filtered OPRM Ch I Cell 8S Oscillation Signal and Counts I]
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NEDO-33264 NON-PROPFIETARY VERSION Fifgure 32: Time Series Analysis -1Eigh Count Window -Filtered OPRM Ch 1 Cell 9 Oscillation Signal and Counts
((
11 Page 48 of 70
NEDO-33264 NON-PROPIUETARY VERSION Fiiure 33: Time Series Analvsis -fliah Count Windolw -Filtered OPRMLCh 3 Cell 8 Oscillation Signal and Counts 1]
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NEDO-33264 NON-PROPIUETARY VERSION Fig!urc 34: Time Series Analysis -High Count Window -Filtered OPRM Ch 3 Cell 13 Oscillation Sijnal and Counts
))
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NEDO-33264 NON-PROPRIETARY VERSION Finurc 35: Time Series Analysis -1High Count Window -Filtered OPRM Ch 3 Cell 14 Oscillation Signal and Counts
))
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NEDO-33264 NON-PROPPIETARY VERSION Fifiure 36: Time Series Andlvsis -Tlish Count Window -Filtered OPRM Ch 4 Cell 9 Oscillation Signal and Counts 1]
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NEDO-33264 NON-PROPIUETARY VERSION Fi!urc 37: Time Series Analysis -High Count Window -Filtered OPRMI Ch 4 Ccll 14 Oscillation Signal and Counts 1]
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NEDO-33264 NON-PROPRIETARY VERSION Figurc 38: Time Series Analvsis -Hich Count Window-Filtered OPRM Ch 4 Cell 19 Oscillation Signal and Counts 1]
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NEDO-33264 NON-PROPRIETARY VERSION Figiure 39: Time Series Analvsis -High Count Window -Filtered OPRM Ch 4 Cell 22 Oscillation Signal and Counts
((
1]
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NE:DO-33264 NON-PROPIUETARY VERSION Fig!ure 40: Time Series Analvsis -High Count Window -Filtered OPRM Ch 4 Cell 24 Oscillation Signal and Counts r]
1]
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NEDO-33264 NON-PROPRIETARY VERSION Ficiure 41: Time Series Analysis -Low Count Window -F iltered OPRM 'Ch1 Cell 8 Oscillation Signal and Counts
((
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NE.DO-33264 NON-PROPIUETARY VERSION Fi~llrc 42: Timc Series Analvsis -Low Coint "Window -Filtered OPRM Ch 1 Cell 9 Oscillation Signal and Counts 1]
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NEDO-33264 NON-PROPRUETARY VERSION Fifiurc 43: Time Series Analvsis -Low Count Window -Filtered OPRMI Ch 3 Cell 8 Oscillation Sigfnal and Counts
((
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NEDO-33264 NON-PROPRIETARY VERSION Figure 44: Time Series Analysis -L-ow Count Window -Filtered OPRM Ch 3 Cell 13 Oscillation Signal and Counts 11 Page 60 of 70
NEDO-33264 NON-PROPRIETARY VERSION Figure 45: Time Series Analysis -Low Count Window -Filtered OPRM Clh 3 Cell 14 Oscillation Signal and Counts
((
- I Page 61 of 70
NEDO-33264 NON-PROPRIETARY VERSION Figure 46: Time Series Analvsis -Low Count Window -Filtrerd OPRM Ch 4 Cell 9 Oscillation Sipnal and Counts 11 Page 62 of 70
NEDO-33264 NON-PROPRIETARY VERSION Figure 47: Time Series Analysis -Low Count Window -Filtered OPRM Clh 4 Cell 14 Oscillation Signal and Counts E]
1]
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NE.DO-33264 NON-PROPRIETARY VERSION Figire 48: Time Series Analvsis -Low Count Window -F iltered OPRM Clh 4 Cell 19 Oscillation Siinal and Counts
((
1]
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NE;DO-33264 NON-PROPRIETARY VERSION Figure 49: Time Series Analysis -Low Count Window -Filtered OPRM Ch 4 Cell 22 Oscillation Signal and Counts 11 Page 65 of 70
NEDO-33264 NON-PROPIUETARY VERSION Figure 50: Time Series Analvsis -Low Count Window -Filtered OPRM Clh 4 Cell 24 Oscillation Sipnal and Counts 1]
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NE.DO-33264 NON-PROPIUETARY VERSION Fiaurc 51: Timc Serics Annlysis - Tlinh Count W'indow - Filtered OPR fl Data (All OPRM Cells)
TI Page 67 of 70
NEDO-33264 NON-PROPIUETARY VERSION Fitire 52: Timc Series Annlvsis - Tlo Count Wlin(onw - Filtere( OPR lDattn (All CIPRM Cclls)
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NEDO-33264 NON-PROPRUETARY VERSION Fiflurc 53: Timc Series Analvsis - Full 5 Minuitc time Span - Filtered O1lRI\Dnti (All OPRMI Cells)
((
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NEDO-33264 NON-PROPRUETARY VERSION Fiaurc 54: Time Series Annlvsik - High Count Window - Selected Plant Dnta I))
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ENCLOSURE 3 MFN 06-065 Affidavit
General Electric Company AFFIDAVIT I, George B. Stramback, state as follows:
(1) I am Manager, Regulatory Services, General Electric Company ("GE") and have been delegated the function of reviewing the information described in paragraph (2) which is sought to be withheld, and have been authorized to apply for its withholding.
(2) The information sought to be withheld is contained in the GE proprietary report NEDC-33264P, Brunswick Nuclear Power Station Unit 1 GE Analysis of OPRM Noise, Class III (GE Proprietary Information), dated February 2006. The proprietary information is delineated by a double underline inside double square brackets.
Figures and large equation objects are identified with double square brackets before and after the object. In each case, the superscript notation(3 ) refers to Paragraph (3) of this affidavit, which provides the basis for the proprietary determination.
(3) In making this application for withholding of proprietary information of which it is the owner, GE relies upon the exemption from disclosure set forth in the Freedom of Information Act ("FOIA"), 5 USC Sec. 552(b)(4), and the Trade Secrets Act, 18 USC Sec. 1905, and NRC regulations 10 CFR 9.17(a)(4), and 2.390(a)(4) for "trade secrets" (Exemption 4). The material for which exemption from disclosure is here sought also qualify under the narrower definition of "trade secret", within the meanings assigned to those terms for purposes of FOIA Exemption 4 in, respectively, Critical Mass Energy Project v. Nuclear Regulatory Commission.
975F2d871 (DC Cir. 1992), and Public Citizen Health Research Groun v. FDA, 704F2dl280 (DC Cir. 1983).
(4) Some examples of categories of information which fit into the definition of proprietary information are:
- a. Information that discloses a process, method, or apparatus, including supporting data and analyses, where prevention of its use by General Electric's competitors without license from General Electric constitutes a competitive economic advantage over other companies;
- b. Information which, if used by a competitor, would reduce his expenditure of resources or improve his competitive position in the design, manufacture, shipment, installation, assurance of quality, or licensing of a similar product;
- c. Information which reveals aspects of past, present, or future General Electric customer-funded development plans and programs, resulting in. potential products to General Electric; GBS-06-02-af Brunswick I NEDC-33264P OPRM Noise Anlaysis.doc Affidavit Page I
- d. Information which discloses patentable subject matter for which it may be desirable to obtain patent protection.
The information sought to be withheld is considered to be proprietary for the reasons set forth in paragraphs (4)a., and (4)b, above.
(5) To address 10 CFR 2.390 (b) (4), the information sought to be withheld is being submitted to NRC in confidence. The information is of a sort customarily held in confidence by GE, and is in fact so held. The information sought to be withheld has, to the best of my knowledge and belief, consistently been held in confidence by GE, no public disclosure has been made, and it is not available in public sources. All disclosures to third parties including any required transmittals to NRC, have been made, or must be made, pursuant to regulatory provisions or proprietary agreements which provide for maintenance of the information in confidence. Its initial designation as proprietary information, and the subsequent steps taken to prevent its unauthorized disclosure, are as set fbrth in paragraphs (6) and (7) following.
(6) Initial approval of proprietary treatment of a document is made by the manager of the originating component, the person most likely to be acquainted with the value and sensitivity of the information in relation to industry knowledge. Access to such documents within GE is limited on a "need to know" basis.
(7) The procedure for approval of external release of such a document typically requires review by the staff manager, project manager, principal scientist or other equivalent authority, by the manager of the cognizant marketing function (or his delegate), and by the Legal Operation, for technical content, competitive effect, and determination of the accuracy of the proprietary designation. Disclosures outside GE are limited to regulatory bodies, customers, and potential customers, and their agents, suppliers, and licensees, and others with a legitimate need for the information, and then only in accordance with appropriate regulatory provisions or proprietary agreements.
(8) The information identified in paragraph (2), above, is classified as proprietary because it contains detailed results of analytical models, methods and processes, including computer codes, which GE has developed, and applied to perform stability evaluations for the BWR. The development of the detection and suppression capability of the APRM-based detection algorithm for the BWR was achieved at a significant cost, in excess of 1/4million dollars, to GE.
The development of the evaluation process along with the interpretation and application of the analytical results is derived from the extensive experience database that constitutes a major GE asset.
(9) Public disclosure of the information sought to be withheld is likely to cause substantial harm to GE's competitive position and foreclose or reduce the availability of profit-making opportunities. The information is part of GE's comprehensive BWR safety and technology base, and its commercial value extends GBS-06-02-af Brunswick I NEDC-33264P OPRM Noise Anlaysis.doc Affidavit Page 2
beyond the original development cost. The value of the technology base goes beyond the extensive physical database and analytical methodology and includes development of the expertise to determine and apply the appropriate evaluation process. In addition, the technology base includes the value derived from providing analyses done with NRC-approved methods.
The research, development, engineering, analytical and NRC review costs comprise a substantial investment of time and money by GE.
The precise value of the expertise to devise an evaluation process and. apply the correct analytical methodology is difficult to quantify, but it clearly is substantial.
GE's competitive advantage will be lost if its competitors are able to use the results of the GE experience to normalize or verify their own process or if they are able to claim an equivalent understanding by demonstrating that they can arrive at the same or similar conclusions.
The value of this information to GE would be lost if the information were disclosed to the public. Making such information available to competitors without their having been required to undertake a similar expenditure of resources would unfairly provide competitors with a windfall, and deprive GE of the opportunity to exercise its competitive advantage to seek an adequate return on its large investment in developing these very valuable analytical tools.
I declare under penalty of pejury that. the foregoing affidavit and the matters stated therein are true and correct to the best of my knowledge, information, and belief.
Executed on this d of A t, 2006.
SGeofB. Stramback General Electric Company GBS-06-02-af Brunswick I NEDC-33264P OPRM Noise Anlaysis.doc Affidavit Page 3