Kord Smith Art DiGiovine Dan Hagrman Scott Palmtag. Studsvik Scandpower. CASMO User s Group May 2003

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Transcription:

Kord Smith Art DiGiovine Dan Hagrman Scott Palmtag CASMO User s Group May 2003

TFU-related data is required input for: -CASMO-4 - SIMULATE-3 - SIMULATE-3K and SIMULATE-3R (implicit in XIMAGE and GARDEL) Fuel temperature modeling in CMS is intended to be best estimate and should be consistent for all CMS codes.

Historically, many customers have used vendor-supplied fuel temperature data which has lead to inconsistencies. Vendor data is often driven by considerations of being conservative rather than accurate. Vendor fuel temperature correlations may be designed for safety/mechanical analysis, not for core-follow or transient analysis. Inaccurate data leads to poor CMS predictions of axial offset in Xenon transients, power coefficients, coastdown reactivity, etc.

Studsvik s INTERPIN code was originally developed to support transient fuel pin analyses at the Studsvik R2 test reactor: rod pressurization fission gas release pellet/clad mechanical interaction Fuel temperature predictions are a natural by-product of fuel performance analysis In 1991, Studsvik introduced a new steady-state fuel temperature code, INTERPIN-CS, to automatically generate temperature data needed in CMS (SEG.TFU and TAB.TFU tables)

Fuel/cladding conductivity vs. temperature and burnup Fuel/cladding thermal expansion Pellet densification, cracking, swelling, relocation Fission gas migration (radial and axial) Fuel/cladding gap conductance (convection, conduction, emission) Clad stress/strain Clad/coolant heat transfer

Fuel Pin Changes with Burnup Attempt to separate densification, swelling and conductance effects on fuel centerline temperature Fuel conductivity vs. burnup based on recent Halden measured fuel centerline temperature data: Pins with various gap sizes Pins with various fission gas inventories See 26 th CUGM presentations by Hagrman and Dean

Fuel conductivity vs. burnup: in INTERPIN-CS decreases ~10% in INTERPIN-3 decreases ~ 40% (more important now with prevalence of high burnup cores) Gaseous convection between fuel and cladding when gap is closed: INTERPIN-CS decreases substantially with fission gas inventory INTERPIN-3 nearly independent of fission gas inventory Net effect of changes are that fuel temperatures increase at high burnup in INTERPIN-3 (INTERPIN-CS temperatures are ~ constant at high burnup)

Assumptions: All fuel pins have the same temperature Fuel temperature is independent of burnup Radial temperature distribution is spatially flat within a fuel pin

CASMO-4 generates nuclear data as a function of instantaneous and historical fuel temperature TFU depletions/branches produce data for temperature coefficients and history effects (automatically included in default case matrix) Average and pin-to-pin temperature variations are not very important

Reactivity Difference (900K-800K) 0.005 0.004 0.003 0.002 0.001 0.000-0.001-0.002-0.003-0.004-0.005 Depletion History 0 10 20 30 40 50 Burnup (MWd/kg) Higher temperature leads to more Pu-239 production and less U-235 depletion

SEG.TFU and TAB.TFU data tables are used to compute the difference between average fuel temperature and coolant temperature (usually as a function of fuel pin power density and burnup) Node-wise coolant temperatures added to compute actual node-averaged fuel temperature SIMULATE-3 accounts for fuel temperature and history effects on a node-wise basis since all nodes do not have the same fuel temperature

Legend INTERPIN-3 INTERPIN-CS SIMULATE-3 needs proper Doppler feedback to model pseudo-steady-state conditions

-1% Axial Flux Imbalance -2% -3% -4% 0 100 200 300 400 500 Time (hours)

10% Axial Flux Imbalance 5% 0% -5% -10% -15% -20% 0 100 200 300 400 500 IP3 Vendor 1 Vendor 2 Time (hours)

40 Axial Flux Imbalance (% I) 30 20 10 0-10 -20-30 -40 INTERPIN-CS INTERPIN-3 Measured SIMULATE-3 (old tfu data) SIMULATE-3 (INTERPIN-CS data) Measured 0 10 20 30 40 50 60 70 80 Elapsed Time (hrs) INTERPIN-3 data needed for analysis of Xenon transients

Measured INTERPIN-CS INTERPIN-3

Nine Mile Point Unit 2 Model TFUAVE Doppler Power HTFU Power Defect Defect Coefficient (K) (% k/k) (% k/k) (% k/k) (% k/k /%P) IPCS 777-0.734-4.991 Reference -0.377 IP3 836-0.894-5.137 0.077-0.384 Difference 59-0.160-0.146 0.077 1.9%

Solve time-dependent radial heat conduction equations for each node, using slightly simpler physical model than used in INTERPIN-3 Consistent: Conductivity vs. burnup (Wiesenack) Conductivity vs. temperature (MATPRO) Radial profile of fission rate (CASMO-4) Gas conduction properties (ideal gas) Different: Gap closure model Solid contact conductance (no contact pressure calculation) Assume no bulk fission gas release (no high temperature historical effects) Net result on fuel temperatures Steady-state temperatures are ~same in INTERPIN-3 and S3K

Truth is a RACER Monte Carlo Calculation using 10 radial rings to approximate quadratic temperature profile Doppler reactivity: k k kk 2 1 5 T2 T1 x Flat Quadratic 450-900K -108-101 450-1350K -111-105 900-1350K -114-108 1 2 / 10 Proper treatment of radial temperature profile lowers Doppler reactivity by ~ 6%. Profile effect is small relative to library uncertainties (~ 10%)

Traditional weighted temperature model: T 0.30T 0.70T eff center surf 1350 900 6.74 0.3x2250 0.7x450 0.3x1350 0.7x450 4.63 4.63/ 6.74 0.68 Surface/center weighting model overestimates temperature profile effect (-40% vs. -6%)

Effective Fuel Temperature model is not recommended in S3K (Physical average temperature is default) Internal gap conductance model is default in S3K Users can input their own conductance tables vs. temperature and exposure Be careful of consistency between vendorassumed conductivity and conductance models

~ No change in BOL temperature ~ 80K increase in MOL temperature ~ 100K increase in EOL temperature More Doppler feedback at high burnup 15% increase in PWR power coefficient Xenon transients are more accurate (more damping)

SSP recommends INTERPIN-3 data to be used consistently throughout CMS for best results. Carefully check vendor-supplied fuel temperature data to make sure they are appropriate for your analysis.