chf lut 2006 lookup table

Nuclear Engineering and Design 237 (2007) 19091922

The 2006 CHF look-u. Vahen

gineer., Chatong Unergy

ry 20

Abstract

CHF look F).for a vertical 8 mm water-cooled tube. The 2006 CHF look-up table is based on a database containing more than 30,000 data points and providesCHF values at 24 pressures, 20 mass fluxes, and 23 qualities, covering the full range of conditions of practical interest. In addition, the 2006 CHFlook-up table addresses several concerns with respect to previous CHF look-up tables raised in the literature. The major improvements of the 2006CHF look-up table are:

An enhan An increa A signific An increa An impro

A discusscharacterize 2007 Else

1. Introdu

The critheat transfeerators. Faiis exceedeincreased ojust for tubpredictioncomplex; nconditionsthe CHF in

CorresponEngineering,

E-mail ad

0029-5493/$doi:10.1016/jced quality of the database (improved screening procedures, removal of clearly identified outliers and duplicate data).sed number of data in the database (an addition of 33 recent data sets).antly improved prediction of CHF in the subcooled region and the limiting quality region.sed number of pressure and mass flux intervals (thus increasing the CHF entries by 20% compared to the 1995 CHF look-up table).ved smoothness of the look-up table (the smoothness was quantified by a smoothness index).

ion of the impact of these changes on the prediction accuracy and table smoothness is presented. The 2006 CHF look-up table isd by a significant improvement in accuracy and smoothness.vier B.V. All rights reserved.

ction

ical heat flux (CHF) normally limits the amount ofrred, both in nuclear fuel bundles and in steam gen-lure of the heated surface may occur once the CHFd. The number of empirical CHF correlations hasver the past 50 years and has reached well over 1000,es cooled by water. The present proliferation of CHFmethods clearly indicates that the CHF mechanism iso single theory or equation can be applied to all CHFof interest. The complexity involved in predictingcreases significantly when additional factors such as

ding author at: University of Ottawa, Department of MechanicalOttawa, Ont., Canada. Tel.: +1 6135843142.dress: [email protected] (D.C. Groeneveld).

transients, non-uniform flux distributions, and asymmetric crosssections are introduced. This has led to the development of theCHF look-up table.

The CHF look-up table is basically a normalized data bank,that predicts the CHF as a function of the coolant pres-sure (P), mass flux (G) and thermodynamic quality (X). Anupdated version of the CHF look-up table is appended to thispaper.

The CHF look-up table method has many advantages overother CHF prediction methods, e.g., (i) simple to use, (ii) noiteration required, (iii) wide range of application, (iv) based ona very large database, and (vi) eliminates the need to chooseamong many CHF prediction methods currently available fortubes cooled by water.

Although the CHF look-up table has been quite successfuland has been adopted widely, several concerns have been raised,including

see front matter 2007 Elsevier B.V. All rights reserved..nucengdes.2007.02.014D.C. Groeneveld a,b,, J.Q. Shan c, A.ZA. Durmayaz d, J. Yang a,b, S.C. Ca University of Ottawa, Department of Mechanical En

b Chalk River Laboratories, Atomic Energy of Canada Ltdc Department of Nuclear Engineering, Xian Jiao

d Istanbul Technical University, Institute of EReceived 2 May 2006; received in revised form 26 Februa

-up tables are used widely for the prediction of the critical heat flux (CHp tablesic b, L.K.H. Leung b,g a, A. Tanase aing, Ottawa, Ont., Canadalk River, Ont., Canada K0J 1J0niversity, P.R. China

, Istanbul, Turkey07; accepted 26 February 2007

The CHF look-up table is basically a normalized data bank

1910 D.C. Groeneveld et al. / Nuclear Engineering and Design 237 (2007) 19091922

Nomenclature

AECLCHFDGHHfgHinIDL, LhLQRLUTpqcrTX

Greek le

SubscripCHFexpinlim

Fluctuatflux andup tablerequired

Large vaespecialregion is

Predictioflow, CH

Lack orcoolings

An initiues for a giusing a limsubsequent8-mm watequalities. Sprogress atsity of Ottaever-increahereafter reet al., 1996points andtube at 21covering, r(zero flow(negative q

During the past 10 years, further enhancements have beenmade to the CHF look-up table and its database, culminat-

thehanccy o

taba

lowiof 3

cludethesep tabing c

cepass flsuriwer

e]).entifi

al.,aminok-ure Piticalenta

ass flj1 +andAtomic Energy of Canada Limitedcritical heat flux (kW m2)inside diameter (m)mass flux (kg m2 s1)enthalpy (kJ kg1)latent heat (kJ kg1)inlet subcooling = (HHin)/Hfg (kJ kg1)inside diameterheated length (m)limiting quality regionlook-up tablepressure at CHF (kPa)critical heat flux (kW m2)fluid temperature (C)thermodynamic quality

ttersmoothness index

tspertaining to the CHFexperimentalinlet conditionslimiting quality as explained in Appendix A

ions in the value of the CHF with pressure, massquality. This can cause difficulties when using look-

ing inthe enaccura

2. Da

Fola totaland inall oflook-uscreen

(i) Acm

(ii) Enporis

(iii) Idetex

losu

cr

imm

(GPis inside safety analysis codes in which iteration is.riations in CHF between the adjacent table entries,

ly in the region of the so-called limiting quality (thisdiscussed in Appendix A).n of CHF at unattainable conditions (e.g., criticalF at qualities greater than 1.0).scarcity of data at certain conditions (e.g., high sub-and high flow, near zero flows).

al attempt to construct a standard table of CHF val-ven geometry was made by Doroshchuk et al. (1975),ited database of 5000 data points. This table, and alltables, contains normalized CHF values for a verticalr-cooled tube at various pressures, mass fluxes andince then, CHF table development work has been invarious institutions (e.g., CENG-Grenoble, Univer-

wa, IPPE-Obninsk, and AECL-Chalk River) using ansing database. The most recent CHF look-up table,ferred to as the 1995 CHF look-up table (Groeneveld) employed a database containing about 24,000 CHFprovides CHF values for an 8-mm ID, water-cooledpressures, 20 mass fluxes, and 23 critical qualities,espectively, ranges of 0.120 MPa, 08 Mg m2 s1refers to pool-boiling conditions) and 50 to 100%ualities refer to subcooled conditions).

with thwere laup tablslice. Tpressu

(iv) Identifisame dauthor

(v) Removgeneradata segive riment (

As can bresenting 2consideredderivation

3. Skeleto

The dertable to prvalues. Thslopes of Colating seletable value2006 CHF look-up table. This paper summarizesements and presents the improvements in predictionf the 2006 CHF look-up table.

se

ng the development of the 1995 CHF look-up table,3 new data sets containing 7545 data were acquiredd in the University of Ottawas CHF data bank. Notdata were used in the derivation of the new CHF

le. The database was first subjected to the followingriteria (summarized in Table 1):

table values for diameter (D), ratio L/D, pressure (P),ux (G) and quality (X).ng that the data satisfied the heat balance (reportedshould be approximately equal to [flow] [enthalpy

cation of outliers using the slice method (Durmayaz2004): the slice method was introduced to

e all the data behind each table entry in thep table. For each nominal look-up table pres-i and nominal mass flux Gj, a CHF versusquality plot was created showing all the exper-

l CHF values falling within the pressure andux ranges of (Pi1 + Pi)/2 < Pexp < (Pi+1 + Pi)/2 andGj)/2 < Gexp < (Gj+1 + Gj)/2 after normalization toGj and D = 8 mm. Data that did not obviously agreee bulk of the data and the previous CHF look-up tablebelled outliers and were excluded in the CHF look-e derivation process. Fig. 1 shows an example of ahe same slice approach was used for the CHF versus

re (P) and CHF versus mass flux (G) plots.cation of duplicate data using the slice method (theata sets may have been reported by more than one

).al of data sets which display a significant scatter andlly disagree with the bulk of the data. These badts may be due to soft inlet conditions, which canse to flow instabilities or a poorly performed experi-e.g., large uncertainties in instrumentation).

e seen from Table 1, a total of 8394 data points, rep-5% of the total number of CHF data available, wereunsuitable for use in the 2006 CHF look-up table

and were removed through the screening process.

n table

ivation of the CHF look-up table requires a skeletonovide the initial estimate of the CHF look-up tablee skeleton CHF values are used for evaluating theHF versus P, G or X. The slopes are used for extrap-cted CHF measurement to the surrounding look-up

s of P, G and X as was described by Groeneveld et al.

D.C. Groeneveld et al. / Nuclear Engineering and Design 237 (2007) 19091922 1911

Table 1Data selection criteria for look-up table derivation

Parameter 1995 selection criteria 2006 selection

# of data in the database 25,630 33,175# of data sets in the database 49 82D (mm) 3 < D < 25 3 < D < 25P (kPa) 100 < P < 20,000 100 < P < 21,00G (kg m2 s1) 0 < G < 8000 SameX XCHF < 1.0 SameInlet temperature (C) Tin > 0.01 SameL/D, Xin < 0 L/D > 80 L/D > 50 for XcL/D, Xin > 0 Not accepted L/D > 100Heat balance Error > 5% Error > 5%

Other data removal criteria Duplicates DuplicatesOutliers as ide

Bad data sets removed Mayinger (1967), Era et al., 1967,Bertoletti (1964)

Bertoletti (196

# of data accepted for LUT derivation 23,114 24,781

(1996). The skeleton table also provides the default CHF valuesat conditions where no experimental data are available.

The skeleton table is primarily based on the 1995 CHF look-up table but with corrections to the subcooled region. Thesecorrections were necessary because the skeleton table for the1995 CHF look-up table was primarily based on the Kattoequation (1992), which was subsequently found to contain dis-continuities or trend reversals at certain conditions as shown inFig. 1.

Values ipredicted u

Fig. 1. CHF vexperimentalafter normaliz

factor derivvalues for Greplaced wequation, bslicing the2004).

For 0 0, L/D > 25 for Xcr < 0 2214154619

1284ntified by the slice method 326

4), Ladislau, 1978 522

Total of above: 8394

ed by Ivey and Morris (1962). The skeleton table> 300 kg m2 s1 and X < 0 are either maintained or

ith the predicted values by Hall and Mudawar (2000)ased on a visual observation of the plots produced bylook-up table and the data trends (Durmayaz et al.,

G < 500 kg m2 s1 and X < 0, the table CHF valueshed using a linear interpolation between those at zero0 kg m2 s1. This provides a smooth transition.

ed to the 1995 look-up table three additional pres-nd 21 MPa) and one mass flux (750 kg m2 s1) weree look-up table. The skeleton CHF values for condi-nd 4 MPa pressures and of 750 kg m2 s1 mass fluxed from linear interpolation. The skeleton CHF val-Pa were interpolated using the CHF versus pressureZuber equation, which was found to approximately

CHF versus P trends for flow boiling (Groeneveld et

ion of the CHF look-up tableary building blocks for the CHF look-up table ared database, described in Section 2, and the skeletonibed in Section 3. The following steps were taken intable derivation process:

5 CHF look-up table, modified as described in thesection, was used as the skeleton table.nded database was screened as described in Section

ct of tube diameter on CHF is accounted for using thecorrection factor: CHFD/CHFD = 8 mm = (D/8)1/2

ange of 3 < D < 25 mm. Outside this range the diam-ct appears to be absent (Wong, 1994).h set of look-up table conditions (each combi-f Px, Gy and Xz), all experimental data falling

the range Px1 < Pexp < Px+1, Gy1 < Gexp < Gy+1


Table 2Impact of polynomial order on prediction accuracy and smoothness

Polynomial o let conditions Smoothness index

Error (%) Avg. () rms (%)Avg. rms

1 0.35 8.23 0.090 11.52 0.78 8.11 0.101 10.83 1.00 8.32 0.107 11.64 0.98 8.32 0.116 13.15 0.99 8.28 0.138 15.7

and XzCHF po(Pexp Pusing thpoint w[1 {(P(Gy+1 ing Px, Gall correreplace t

The updlar variatioranges: preattributed tent data sesuch as heSharp variboundariesable and remployed.procedureThe princinomials tothree polynthe CHF vimprovemeorder polynlook-up tabfirst-ordernificant losindex andSection 5.2

Applyinconditionsthe limitingresulting inmaintain thintermediachanges atest look-upof the LQRtable value

uently to avoid a fluctuation in CHF with pressure andux. Fig. 2 illustrates the intended change in the look-uprior to applying the additional smoothing.final CHF look-up table is included as Appendix B. Four

of shading have been applied to highlight regions of uncer-The unshaded entries represent areas that were derivedy froaintyon s

tionsilabapolt con

as thm grftenl flowliquithe

s areegiod. FiR, werveass flntermrder Constant local conditions Constant in

No. of data Error (%) No. of dataAvg. rms

24,781 3.50 38.34 24,78124,781 5.53 38.27 24,78124,781 6.94 38.42 24,78124,781 6.60 37.24 24,78124,781 6.44 36.54 24,781

1 < Xexp < Xz+1 were selected. Each experimentalint was corrected for the differences in pressurex), mass flux (Gexp Gy) and quality (Xexp Xz),e slopes of the skeleton table. The correctedas given a weight, which was proportional toexp Px)(Gexp Gy)(Xexp Xz)}/{(Px+1 Px)Gy)(Xz+1 Xz)} for each of the quadrants surround-y and Xz and the weighted averaged CHF value for

cted data surrounding each table entry was used tohe skeleton CHF value.

ated CHF table is not smooth and displays an irregu-n (without any physical basis) in the three parametricssure, mass flux and quality. These fluctuations areo data scatter, systematic differences between differ-ts, and possible effects of second-order parametersated length, surface conditions and flow instability.ations in CHF were also observed at some of thebetween regions where experimental data are avail-

egions where correlations and extrapolations werePrior to finalizing the look-up table, a smoothing

developed by Huang and Cheng (1994) was applied.ple of the smoothing method is to fit three poly-six table entries in each parametric direction. Theomials intersect each other at the table entry, wherealue is then adjusted. This resulted in a significantnt in the smoothness of the look-up table. A third-omial was used for the smoothing of the 1995 CHFle. However, recent comparisons have shown that a

polynomial results in a smoother table with no sig-s in prediction accuracy, see Table 2 (the smoothnessroot-mean-square (rms) values will be discussed in

subseqmass fltable p

Thelevelstainty.directluncertbasedpredicare ava

of extrsmall alargemediuwere o

criticaof thewhereregionother ravoidethe LQbe obsand msome i).g the smoothing process to the table entries at allsuppressed the discontinuity at the boundaries ofquality region (LQR), as described in Appendix A,

non-representative trend to the experimental data. Toe physical trend of the table entries at the LQR, an

te table was created that maintained the more abruptthe boundaries of the LQR, extrapolated to the near-table qualities. Also between the maximum qualityand X = 0.9 a gradual change towards the skeleton

s was applied. Some smoothing needed to applied Fig. 2. Illustrm the experimental data and hence have the least. The light grey regions represent calculated valueselected prediction methods that provide reasonableat neighboring conditions where experimental data

le. The uncertainty in this region depends on the levelation from data-based regions. It is expected to beditions slightly beyond the range of data but becomese extrapolation is further beyond this range. Theay regions represent conditions where CHF valuesimpossible to obtain, including (i) conditions wheremay exist, and (ii) coolant enthalpies where the bulk

d starts to become solid (Tbulk < 0.01) and (iii) G = 0concept of flow quality becomes imaginary. Thoseincluded only to improve interpolation accuracy of

ns. Extrapolation into medium gray region should benally the entries having a black background representhere rapid changes in CHF versus quality curve can

d. Note that the LQR does not occur at all pressuresuxes. Because of space limitations CHF values atediate pressures are not shown in Appendix B.ation of derivation of 2006 CHF look-up table values at the LQR.


5. Look-up table prediction accuracy and smoothness

5.1. Predic

There arof the CHF(i.e., constaconditionsMethod (i)method (Dbalance me

The CHsimplest topoint in quCHF look-diameter usG, and X. Nfollows:

CHF(Dexp

= CHF(

The CHobtained vifollowing s

Estimateassume C

Calculatflux and

X = HH

= 4G

Note thaquality, w

The firstup tablecorrected

qpred(De

= CH

Re-evaluvalue anCHF.

Continueconvergi

The prethe databasevaluated fon either co

rror hof datetc.).

istoge 200

ofhowors o

95 Cimp

bcoo(Xli

nleto 6.7the imtion 3ductto sin F

cantlse eintsompa, bu.eparmethreeection criteria have been effective in removing suspect

error distribution based on the constant inlet-flow condi-pproach for the 2006 CHF look-up table with respect tore, mass flux and critical quality are shown in Fig. 4. Slightatic errors are present at low pressures and very low andass velocities and high qualities. A more detailed exam-showed that the high errors were primarily at pressures

an 250 kPa and mass velocities less than 750 kg m2 s1.atter among these low flow and low-pressure data is veryue to possible flow instability at these conditions. Table 3the impact on prediction errors after excluding these datae error analysis. The rms error at constant inlet-flow con-for the 2006 CHF look-up table reduces from 7.10 to

.tion accuracy

e two methods for assessing the prediction accuracylook-up table: (i) based on constant local conditionsnt critical quality), and (ii) based on constant inlet(i.e., constant inlet temperature or inlet enthalpy).is sometimes referred to as the direct substitution

SM), while method (ii) is also referred to as the heatthod (HBM).F prediction based on constant local conditions is theapply. The predicted CHF for each experimental dataestion (Dexp, Pexp, Gexp, Xexp) is first found using theup table at local flow conditions for a tube of 8-mming direct interpolation between matrix values of P,ext, the CHF is corrected for the diameter effect as

, Pexp,Gexp, Xexp)

D = 8, Pexp,Gexp, Xexp)(

Dexp8

)1/2(5.1)

F prediction based on constant inlet conditions isa iteration with the heat-balance equation using theteps:

the heat flux (if unsure how to make an estimate,HF = 500 kW m2)

e the quality based on the estimated heat flux, massinlet subcooling: Hf(Pexp)

fg(Pexp)qest

expHfg(Pexp)Lh,expDexp

Hin,exp(Tin,exp)Hfg(Pexp)

(5.2)

t the quality as defined above is the thermodynamichich will be negative for subcooled conditions.estimate of CHF is calculated from the CHF look-at local flow conditions (D = 8 mm, Pexp, Gexp, X)for diameter

xp, Pexp,Gexp, X)

F(8, Pexp,Gexp, X)(

Dexp8

)1/2(5.3)

ate the quality using the average of the predictedd the previous heat flux value, and again find the

this iteration process until the heat flux value startsng to a single value.

diction errors are calculated for each data point frome. The mean (arithmetic average) and rms errors areor data subsets and for the complete database basednstant local quality and constant inlet condition. The

Fig. 3. Edata (%70%,

error hthat thDetailstable sage errthe 19

Thefor suregionstant i10.88 tdue toin SecThe retainingshownsignifi

Thedata pobeen c21 MP0.03%

A sslicethan ththe seldata.

Thetions apressusystemhigh minationless thThe sclarge dshowsfrom thditions5.86%istograms of the 1995 and 2006 CHF look-up tables for all selecteda is for each error band of 100 to 90%, 90 to 80%, 80 to

rams in Fig. 3 based on the enlarged database show6 look-up table has a more peaked error distribution.

the error distributions are presented in Table 3. Thes that using the enhanced database, the rms and aver-f the 2006 CHF look-up table are less than those for

HF look-up table.rovement in prediction accuracy is most pronouncedled conditions (X < 0) and in the limiting qualitym < X < X

lim) where the rms errors based on con-

conditions decrease from 11.13 to 7.08% and from1%, respectively. The reductions in error forX < 0 areprovements to the skeleton table forX < 0 (described) by reducing the dependence on the Katto equation

ion in error in the LQR is primarily due to the main-ome degree a sharper variation in CHF values as wasig. 2. The rms error in Region III was also reducedy: from 11.34 to 8.01%.rror comparisons are based on the total number of(i.e., 25,217). The 2006 CHF look-up table has alsoared to additional data obtained at pressures up tot adding the extra data affects the errors by less than

ate error analysis of the outliers (as identified by theod, see Fig. 1) showed that their rms errors are moretimes those of the above table. This indicates that


Table 3Error statistics of the 1995 and 2006 CHF look-up tables

Data selection (# of data) All selected(25,217)

Except P < 250,G < 750 (24,552)

X < 0 only(1845)

Region I: X < Xlimor no LQR (19,856)

Region II: LQR,Xlim < X < X

lim

(4565)

Region III:X > Xlim(796)

1995 CHF look-up tableAvg. error, X = C 7.63 7.27 2.95 6.10 13.81 9.40rms error X = C 42.96 42.10 18.00 37.42 58.89 57.28Avg. error, Hin = C 0.75 0.62 2.93 0.505 1.37 1.383rms error, Hin = C 9.18 8.66 11.13 8.62 10.88 11.34Smoothness index 0.098Smoothness rms 0.132

2006 CHF look-up tableAvg. error, X = C 4.09 5.81 0.85 2.31 14.53 12.4rms error X = C 38.92 37.21 14.74 31.13 60.8 47.52Avg. error, Hin = C 0.08 0.48 0.10 0.07 1.14 2.28rms error, Hin = C 7.10 5.86 7.08 7.15 6.71 8.01Smoothness index 0.095Smoothness rms 0.133

Fig. 4. Error distributions for the 2006 CHF look-up table with respect to P, G and X.


5.2. Smoot

Fig. 5 cCHF look-sonably sm2006 CHFout in thedifficult tojudge whicto quantifyapproach w

Since thG, and X arindexes wetable smoohas Pi, Gj,. . ., J; andtables is simof the relatpoint.

qcr (Pi,G

= 13

[(Fig. 5. Comparison of the 1995 CHF look-up table and the 2006 CHF

hness

ompares 3-D representations of the 1995 and 2006up tables for three pressures. Both tables appear rea-ooth. The only obvious non-smooth trend for thelook-up table was the LQR, which was smoothed1995 CHF look-up table. Aside from the LQR it issee which region is smoother, making it difficult toh of the two tables is smoother. Hence it was decidedthe smoothness using the following approach (thisas not applied to the transition at the LQR boundary).e grid numbers in these CHF look-up tables for P,e roughly the same, as a first approximation, the gridre used as the normalized parameters for the look-upthness assessment. Assuming that the look-up tableand Xm as its grid points, with i = 1, 2, . . ., I; j = 1, 2,m = 1, 2, . . ., M, the local smoothness of the look-up

ply presented by the average of the absolute valueive slope differences at each direction of a local grid

j, Xm)1qcr

qcr

i

)+

(

1qcr

qcr

i

)

+(

1qcr

qcr

j

)+

(

1qcr

qcr

j

)

+

where +backwardat its correentire looksmoothnes

qcr =

The rms

rmsqcr =

Table 3smoothnespared to thtable.look-up table (left: 1995; right: 2006).

(

1qcr

qcr

m

)+

(

1qcr

qcr

m

)

]Pi,Gj,Xm

(5.4)

refers to the forward slope, and refers to theslope, qcr is the CHF, and qcr is the average CHFsponding interval. The smoothness index for the

-up table is defined as the overall average of the locals at all internal grid points.I1i=2J1

j=2M1

m=2 qcr (Pi,Gj,Xm)(I 2)(J 2)(M 2) (5.5)

of the smoothness is calculated in a similar manner:I1i=2J1

j=2M1

m=2 [qcr (Pi,Gj,Xm) qcr ]2(I 2)(J 2)(M 2)

(5.6)

shows that the smoothness index and the rms of thes for the 2006 CHF look-up table are improved com-e corresponding values for the 1995 CHF look-up


6. Conclusions and nal remarks

The tube CHF database has been expanded since the deriva-tion of the 1995 CHF look-up table with 33 additional data setscontaining 7545 new data points.

The screening process of the CHF data has been enhancedsignificantly resulting in a larger fraction (25%) of data beingexcluded from the table development.

The 2006 CHF look-up table is a significant improvementover the 1995 CHF look-up table; the rms errors were reducedand the smoothness of the look-up table was improved. Thelargest improvements in prediction accuracy was obtained inthe subcooled CHF region where local subcooling trend nowagrees better with the HallMudawar equation, and in the lim-iting quality region where the smoothing has been removed.The rms errors decreased by approximately 4% in theseregions.

Despite the large number of CHF studies performed indirectly heated tubes during the past 50 years, significant gapsin the data remain, where CHF predictions are based on extrapo-lation and mrequired to

Acknowled

The finaCHF look-of previousAECL, AN

Appendix

The lima fast decreLQR usualTo illustratal. (1970) aversus qualThe annula

Fig. A1. Schematic representation of the limiting quality region.

tulated (e.g. Bennet et al., 1967) that in region I the primarymechanism responsible for CHF occurrence is droplet entrain-ment from the thick liquid film. This mechanism is quite effectivein reducing the film thickness thus depleting the annular film

te uneryhe enom apora

ns thrredersu

g etnd,

ariessityd. Thher

nsidt slo

ered

dixodels predictions. Additional CHF experiments arefill these gaps.

gements

ncial assistance for the development of the new 2006up table was provided by NSERC. The developmentversions of the CHF look-up table was supported bySL, EPRI, CEA and the IAEA.

A. Limiting quality region

iting quality phenomenon (LQR) is characterized byase in CHF with an increase of steam quality. Thely occurs in the intermediate steam quality region.e the limiting quality phenomenon, Doroshchuk etnd Bennet et al. (1967) divided the critical heat fluxity curve into three regions as is illustrated in Fig. A1.r flow regime occurs in all three regions, but it is pos-

flow raby a vfrom trate frthe evaexplaiis refeCHF v

PenLQR aboundUnivermethopoint wwas co

the nexconsid

Appentil the film breaks down. Region III in characterizedthin liquid film which is replenished by depositiontraiment laden vapor stream. Since the entrainmentthin liquid film is virtually zero, CHF occurs whention rate (q/Hfg) exceeds the deposition rate, which

e low CHFs in region III. The intermediate region IIto as the limiting quality region because of the steeps X slope.al. (2004) reviewed the available literature on theusing the UofO data bank, he tabulated the LQR. A similar approach was recently undertaken at theof Ottawa using Durmayazs et al. (2004) slicee boundaries were defined as shown in Fig. A1(b): the

e the slope first showed a significant change (qcrXlim)ered typical of the start of the LQR while the point ofpe change combined with a low CHF (qcrXlim) wasthe end of the LQR.

B. 2006 CHF look-up table


Reference

Bennet, A.W.Studies ofT319T33

Bertoletti, S.,Doroshchuk,

burnout iAmsterda

Doroshchuk, Vin Uniform

Durmayaz, Aheat-fluxProceedinin Nuclea

Gaspsfer D0 kg/s4.eld, Dup tabeld, Dgrado

cal heD., Mooled.X.C.,al exps. Nus

, Hewitt, G.F., Kearsey, H.A., Keeys, R.K.F., Pulling, D.J., 1967.burnout in boiling heat transfer. Trans. Instrum. Chem. Eng. 45,3.1964. Heat Transfer to SteamWater Mixtures, CISE R-78.V.E., Lantsman, F.P., Levitan, L.L., 1970. A peculiar type of

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., Groeneveld, D.C., Cheng, S.C., 2004. Assessment of critical-look-up tables, experimental data and selected correlations. In:gs of the Sixth International Conference on Simulation Methodsr Engineering, October 1215, Montreal.

Era, A.,Tranat 7R-18

Groenevlook

GroenevVinocriti

Hall, D.subc2640

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The 2006 CHF look-up tableIntroductionDatabaseSkeleton tableDerivation of the CHF look-up tableLook-up table prediction accuracy and smoothnessPrediction accuracySmoothness

Conclusions and final remarksAcknowledgementsLimiting quality region2006 CHF look-up tableReferences

chf lut 2006 lookup table

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