- FW flow measurements are used to calculate reactor power but are prone to errors from nozzle fouling. - Heat balance techniques and performance modeling can diagnose fouling by comparing predicted vs actual parameters like turbine pressures and output. - Monitoring key parameters like turbine pressures and output over time through a performance program can identify capacity losses from undiscovered fouling.

2.  FW flow used to calculate NSSS heat input
 NSSS heat input with reactor heat balance
used to calculate reactor core thermal
power
 Calibrated flow nozzle used to measure FW
flow
 Calibration assumes clean flow section
 Fouling or deposits will result in errors in
flow measurement causing flow to read high

3.  Calculated reactor power would be higher
than true value with attendant loss in
plant capacity
 Methodology and heat balance techniques
to diagnose FW flow nozzle fouling and
quantifying capacity loss presented
 Recommendations provided to monitor
performance for FW flow nozzle fouling
 Steps to take for corrective action

4.  Reactor core thermal power cannot be
measured directly
 Determined indirectly through flow,
pressure, temperature measurements
 Errors in measurements could cause
derived value of reactor core thermal
power to read higher than actual value
 Result is loss in plant capacity

5.  From experience, most likely cause could
be error in FW flow measurement from
buildup of deposits in flow nozzle
 Several means for verifying loss in
capacity may be due to error in
determination of reactor core thermal
power
 Include monitoring and trending
parameters – stage pressures, electrical
output, control valve position, etc.

6.  Heat balance techniques invaluable
diagnostic tools
 Using performance modeling tools, heat
balances developed for entire cycle
 Used on routine basis to predict
performance and compared with plant
parameters for potential capacity losses
 Performance modeling tool used to
diagnose/evaluate BWR cycle in Fig. 1

9. 1. QFW = WFW x (hR – hFW)/3412141.63
2. QCRD = WCRD x (hR – hCRD)/3412141.63
3. QNSSS = QFW + QCRD
4. QCU = WCU x (hCUIN – hCUOUT)/3412141.63
5. QRAD = 1.85
6. QRRP = KWRRP/1000
7. CMWT = QFW + QCRD + QCU + QRAD - QRRP

10.  CMWT predominantly function of FW
thermal power QFW
 QFW affected by:
 FW flow
 Reactor outlet enthalpy hR
 Feedwater enthalpy hFW
 Fig. 3 shows base case turbine cycle
heat balance using performance
modeling tool

12.  Reactor outlet pressure is 1051.0 psia
 Reactor outlet moisture is 0.1%
 HP turbine bowl pressure is 908.0 psia
(assumes full-arc admission)
 HP turbine first stage shell pressure is
approximately 715.0 psia
 HP turbine extraction stage pressures are
457.5 and 166.3 psia
 FW flow is 7,266,000 lb/hr
 Feed pump discharge pressure is 1231.8 psia
 Feedwater temperature is 355.9 °F

13.  QFW decreases by 1%, from 1833.45 Mwt to
1815.12 Mwt
 HP turbine bowl pressure decreases by 1%,
from 908.0 psia to 899.0 psia
 HP turbine first stage shell pressure
decreases by 1%, from 715.4 psia to 707.8
psia

14.  HP turbine extraction stage pressures
decrease by 1%, from 457.5 psia to 452.8 psia
and, from 166.3 psia to 164.7 psia
 Feedwater temperature decreases by about
0.8 °F, from 355.9 °F to 355.1 °F.
 Generator output decreases by about 1%,
from 637 Mwe to 631 Mwe

16.  FW flow decreases by 0.43%, from 7,266,000
lb/hr to 7,234,701 lb/hr
 HP turbine bowl pressure decreases by 0.48%,
from 908.0 psia to about 903.6 psia
 HP turbine first stage shell pressure decreases by
0.49%, from 715.4 psia to 711.8 psia
 Extraction steam flow to HP heater decreases and
slightly more steam available to do work in LP
turbine
 Generator output decreases by about 1 Mwe, from
637 Mwe to 636 Mwe

18.  FW flow increases by 0.3%, from 7,266,000 lb/hr
to 7,287,628 lb/hr
 HP turbine bowl pressure increases by 0.1%, from
908.0 psia to 909.0 psia
 HP turbine first stage shell pressure increases by
0.29%, from 715.4 psia to 717.5 psia
 HP turbine extraction pressure increase by 0.14%,
from 457.5 psia to 458.14 psia
 Generator output decreases by approximately 0.5
Mwe

20.  Changes in FW flow have the greatest impact on
QFW, HP turbine bowl pressure, HP turbine first
stage shell pressure, HP turbine extraction
pressures and, generator output. A 1% reduction
in the feedwater flow results in a like change in
all these parameters
 For a constant QFW, a change in feedwater
temperature affects, to a lesser extent, FW flow,
HP turbine bowl pressure, HP turbine first stage
shell pressure and, generator output
 For a constant QFW, a large change in reactor
outlet moisture produces only small changes in
FW flow, HP turbine bowl pressure, HP turbine
first stage shell pressure and, generator output

21.  For sample cycle, critical parameters to
monitor for changes in FW flow are:
 Changes in HP turbine bowl pressure
 Changes in HP turbine first stage pressure
 Changes in HP turbine extraction stage
pressures
 Changes in generator output
 Changes in HP turbine bowl pressure are
the most important.

22.  For sample cycle, heat balances were
developed using the performance
modeling tool
 Heat balances relied upon detailed
design, performance test and plant
information
 Extensive plant performance logs
were reviewed at various reactor core
thermal power levels

23.  Using regression techniques, most
probable values of FW flow, feedwater
temperature and HP turbine first stage
bowl pressure were determined at the
licensed reactor core thermal power of
1850 Mwt
 These values were used for base case
shown in Fig. 3
 Figures 7, 8 and 9 show the plots

27.  Assume, for the sample cycle, fouling
of FW flow nozzles is suspected and
independent FW flow measurements
show a FW flow of 7,188,000 lb/hr
compared to a flow of 7,263,000 lb/hr
using the plant flow nozzles
 The FW temperature measured
independently was 356.6 F compared
to 356.1 F from plant instrumentation

28.  Fig. 10 shows reactor heat balance for FW
flow of 7,188,000 lb/hr
 Calculated reactor core thermal power
corresponding to this flow is 1828.41 Mwt
 Heat input to the turbine cycle is 1824.35
Mwt.
 Using this data, along with other plant data,
predicted performance is shown in Fig. 11.
 Predicted HP turbine bowl pressure was 900.2
psia and predicted generator output was
about 631 Mwe.

31.  Corresponding to FW flow of 7,263,000
lb/hr from plant FW flow nozzles, calculated
reactor core thermal power was 1848.34
Mwt and heat input to turbine cycle was
1844.27 Mwt.
 Using this data, along with rest of data
same as that for FW flow of 7,188,000 lb/hr,
performance of the cycle predicted.
 Figure 12 shows reactor heat balance and
Fig. 13 shows turbine cycle performance.

34.  Predicted generator output was 638.2
Mwe and predicted HP turbine bowl
pressure was 909.2 psia
 From plant records, actual HP turbine
bowl pressure was about 904.0 psia
and actual generator output was about
634 Mwe
 Corresponding to the actual recorded
output of 634 Mwe, model predicted a
FW flow of 7,219,304 lb/hr

35.  Calculated reactor core thermal power was
1836.31 Mwt and heat input to the turbine
cycle was 1832.25 Mwt
 Predicted HP turbine bowl pressure was 904.0
psia, which was in agreement with plant value
 Figures 14 and 15 show predicted
performance
 It might be concluded that fouling of the FW
flow nozzles is about 0.6% and associated
loss in output is about 4 Mwe

38.  If fouling is suspected, following technique may
be used for approximating the degree of fouling
and associated loss of capacity:
 Assume that plant performance logs show a FW
flow of 7,191,000 lb/hr, HP turbine bowl
pressure of 894.0 psia and generator output of
632 Mwe
 From the regression analysis discussed earlier,
most probable FW flow is 7,266,000 lb/hr and,
probable HP turbine bowl pressure is 908.0 psia
at the licensed reactor core thermal power of
1850 Mwt

39.  Corresponding to measured FW flow of 7,191,000
lb/hr, expected HP turbine bowl pressure should
have been (7,191,000/7,266,000) x 908 = 898.6
psia
 Since actual bowl pressure is 894.0 psia, the most
probable FW flow is (894/908.0) x 7,266,000 =
7,153,969 lb/hr
 Suspected degree of FW fouling is then
(7,191,000-7,153,969)/7,153,969 = 0.52%
 Expected generator output at the flow of 7,191,000
lb/hr is 632/(1-0.0052) = 635.3 Mwe
 Estimated loss in capacity due to fouling = 635.3 –
632 = 3.3 Mwe

40.  Heat balance techniques invaluable in
diagnosing fouling of FW flow nozzles and
in quantifying the associated capacity
losses
 Using performance modeling tools,
accurate models may be constructed for
analysis of plant data and, performance
predictions
 Success of heat balance methodology to
diagnose and quantify FW flow nozzle
fouling dependent upon ability to monitor
key parameters and use of performance
modeling tools, on a routine basis

41.  For sample cycle discussed in the paper, most
important parameters to monitor for evidence
of FW flow nozzle fouling are HP turbine bowl
pressure, HP turbine first stage pressure, HP
turbine extraction pressures and generator
output
 Other plant parameters such as pressures,
temperatures for feedwater heaters are not
as critical in calculations as HP turbine bowl,
first stage shell and extraction pressures,
generator output and condenser pressure

42.  Establish routine performance monitoring
program to monitor FW flow, FW temperature,
reactor core thermal power, feedwater thermal
power, HP turbine bowl pressure, HP turbine
first stage pressure, HP turbine extraction
pressures and, generator output
 Using performance modeling tools, develop an
accurate heat balance model using design,
acceptance/performance test and other plant
data

43.  Develop correlations between critical
parameters identified in the routine
performance monitoring program
 Use the model for performance
calculations using plant data from the
routine performance monitoring program
 Compare with the correlations to check
for potential FW flow nozzle fouling and,
to quantify the associated capacity loss