1 Introduction Void fraction plays an important role in modeling of two phase flow at component scale In CTF code, during solving the conservation equations, the void fraction is calculated Then, the flow regime is defined based on value of void fraction For example, flow regimes are determined based on the range of void fraction in normal wall models as illustrated in Figure 2.8 of this thesis The normal wall flow regime map includes the following flow regimes:  Small-bubble defined by void fraction below 0.2  Small-to-large bubble (Slug) defined by void fraction in range (0.2, 0.5)  Churn/turbulent defined by void fraction in range (0.5 αcrit)  Annular/mist defined by void fraction greater αcrit Then each of the individual flow regimes of the normal wall map, the interfacial area, interfacial drag and interfacial heat transfer are defined differently Figure 2.8 CTF normal-wall flow regime maps (source [38]) 1.1 Thesis objectives Void fraction study on flow through a channel with heating wall is important in thermal hydraulics analysis with a lot of experiments and codes developments Thus, based on the material of the national projects (code DTDL.2011-G/82 and KC.05.26/11-15) it is proposed a motivation of the study with the objective to predict void fraction prediction in core of the VVER-1000/V392 nuclear reactor using best estimate approach The issues are proposed to study as following:  To adopt a procedure of void fraction prediction during transient using multi scale analysis based on the computer codes: MCNP5, RELAP5 and CTF;  To consider a combination of CTF and CFX (Ansys CFX) codes to improve void fraction predicted by CTF in specific timing within the transient period In the issues mentioned above, the consideration of utilization of CTF and CFX codes to improve void fraction prediction in core is a new one As usually, CTF is used to predict void fraction during transient time It is expected that CFX with meso scale for void fraction prediction will give an improvement to predict for steady state in specific timing 1.1.1 Studied object The void fraction in hot channel of VVER-1000/V392 reactor is predicted with different scales during 40 seconds of transient condition at the beginning of LOCAs with different break sizes 1.1.2 Scope study It is also limited the scope of the study due to complexity of the two phase flow The investigated two phase flow through core sub channels is vertical flow with the specific regime such as bubbly, slug, churn and annular 1.2 Thesis outline Thus, the thesis includes four chapters and the conclusion at the last The chapter mentions about introduction that leads to motivation of this study with following arguments:  Status of nuclear power in the World and Vietnam  Brief overview of nuclear safety  Core thermal hydraulics safety analysis in transient condition  VVER technologies understanding in Vietnam related to this study  Thesis objectives  Thesis outline Chapter presents the methodology that is related to multi scale analysis along with the code theories at different scale for RELAP5, CTF and CFX with emphasize to phase change models in several items below:  Multi scale approach to LWR thermal hydraulic simulation  System code RELAP5  Sub channel code CTF  Meso scale code CFX  Conclusions The verification and assessment of modeling used in these codes in this study versus experiment data are presented in chapter The system simulation results are compared with those in SAR documents (Belene project) The assessment of CTF code is implemented by simulation BM ENTEK experiment tests which is an International Standard Benchmark to investigate boiling flow through Russian fuel bundle of RBMK reactor The meso scale code CFX is verified with PSBT single sub channel which is also an International Standard Benchmark Therefore the contents of chapter are presented as following:  Brief information of VVER-1000/V392 nuclear reactor  Verification of RELAP5 simulation models for VVER1000/V392 reactor with SAR  Verification and assessment of CTF models with BM ENTEK experiment tests  Verification CFX models with PSBT sub channel experiment tests  Conclusions The tasks related to thesis objectives mentioned in chapter are solved in chapter with following steps:  Calculation Diagram  Power distribution calculation by MCNP5 code  LOCAs simulation by RELAP5 code  Transient simulation in LOCAs by CTF code  Steady state simulation specific timing of LOCAs by CFX code  Conclusions Overview of phase change models in code theories with different scales The chapter presented following issue: 2.1 Multi codes and multi scales approach to PWR thermal hydraulic simulation 2.1.1 Neutron codes and thermal hydraulics codes 2.1.2 The different scale of thermal hydraulic codes 2.1.3 The different thermal hydraulic modeling approaches 2.2 Phase change models in system code RELAP5 2.3 Phase change models in sub channel code CTF 2.3.1 Evaporation and condensation induced by thermal phase change 2.3.2 Evaporation and condensation induced by turbulent mixing and void drift 2.4 Phase change models in meso scale code CFX 2.4.1 Evaporation at the wall 2.4.2 Condensation model in bulk of liquid 2.5 Conclusions In summary, this chapter shows the detail of multi code and multi scale for PWR thermal hydraulics simulation, in especially for void fraction prediction The phase change of the codes used to predict void fraction in this thesis including RELAP5, CTF and CFX are briefly presented Verification and assessment of phase change models by numerical simulation The chapter presents the thesis’ study on verification and assessment of phase change models by numerical simulation codes with different scales such as RELAP5 for the whole system of VVER-1000/V392 reactor, CTF for ENTEK BM experiment and CFX for PSBT single channel Then the assessment of CFX and CTF for void prediction based on PSBT is presented In briefly conclusions, the findings and achievements of this chapter are presented below 3.1 Verification of RELAP5 simulation models for VVER1000/V392 reactor with SAR The purpose of this section is verification of RELAP5 modeling developed by this study for VVER-1000/V392 reactor Therefore, simulation results of this study are compared with those in SAR for LOCAs scenarios The comparisons focus on steady state results, timing of transient events and behavior of peaking temperature of cladding 3.2.2 Verification of modeling through steady-state study The results show that the steady-state calculations are matched and acceptable with design values in compare with SAR calculation in [35] since the deviation between these two values is within 4% Table 3.2 Comparison of steady-state of VVER-1000/V392 Parameter Dim Design value SAR results[35] Reactor thermal power Reactor outlet pressure Reactor inlet temperature Reactor outlet temperature Pressurizer (PRZ) level Steam Generator (SG) inlet pressure - primary side Total volumetric flow rate at reactor inlet SGs wide range level measurement Feed water temperature Maximum fuel temperature SGs pressure at steam collector outlet MW MPa o K o K M MPa 3000 15.7 ± 564.15+2-5 594.15±5 8.17 15.64 ± 0.3 3120 16.0 566.15 599.15 8.17 15.94 The present study 3120 15.8 561.8 591.8 8.18 15.75 m3/h 86000+2600 82200 86029 0.03% M 2.7 ± 0.05 2.65 2.63 2.59% o 493.15± 2078.15 6.27 ± 0.1 498.15 2189.15 6.37 493.15 1843.14 6.27 0.00% 0.84% 0.00% K K MPa o Deviation (Percent) 4.00% 0.64% 0.42% 0.40% 0.12% 0.70% 3.2.3 Verification through accident case study  The comparison results of chronological sequence of the main events for Event are given in Table 3.4 Table 3.4 chronological sequence of the Event from SAR [35] and this study Time, s 0.00 SAR results MCPL guillotine break at the reactor inlet And Loss of off-site power supply: - startup of DG and safety systems according to stepwise startup program (failure of one DG to start up and one DG is in repair) - Trip of the systems for normal operation; Time, s 0.00 The present study Dev MCPL guillotine break at the reactor inlet And Loss of off-site power supply: - startup of DG and safety systems according to stepwise startup program (failure of one DG to start up and one DG is in repair) - Trip of the systems for normal operation; 0.03 0.04 1.90 7.00 17.0 30.0 40.00 60.00 63.00 117.00 500.00  Scram signal generation due to Pressure above the core is below 14.70 MPa Set point for connection of ECCS pumps is reached SCRAM signal generation Beginning of injection into the reactor from HA-1 Opening of valves in the pipelines connecting HA-2 to the core due to primary pressure decreases up to 1.50 MPa Connection of SG PHRS to SG 1, Beginning of injection from the ECCS pumps Bringing of SG 1, PHRS to full power Termination of boron solution injection into the reactor from HA-1 Beginning of supply from HA-2 End of the calculation 0.08 0.03 1.90 6.00 15.00 30.00 40.00 75.00 63.00 115.00 500.00 Scram signal generation due to Pressure above the core is below 14.70 MPa Set point for connection of ECCS pumps is reached SCRAM signal generation Beginning of injection into the reactor from HA-1 Opening of valves in the pipelines connecting HA-2 to the core due to primary pressure decreases up to 1.50 MPa Connection of SG PHRS to SG 1, 0.05 Beginning of injection from the ECCS pumps Bringing of SG 1, PHRS to full power Termination of boron solution injection into the reactor from HA-1 Beginning of supply from HA-2 End of the calculation 15 The comparison of peaking temperature (PCT) (a) 0.01 (b) Figure 3.4 (a) Cladding temperature from calculations, (b) Cladding temperature from SAR Figure 3.4 also show the study’s calculations are similar to SAR results in term of peaking cladding temperature and timing to cool down cladding temperature Therefore, the simulation model of this study is appropriate with reference model from the SAR 3.3 Verification and assessment of CTF models with BM ENTEK tests  Along channel void fraction distribution discussion Table 3.6 and Table 3.7 show the void fraction distribution calculation results versus experiment distribution along the channel Table 3.8 shows the deviation between void fraction distribution calculation results versus experiment distribution It is observed that CTF’s void fraction distribution predictions for base cases are good agreement with experiment distribution with mainly deviation around 0.03 of void The maximum deviations with value around 0.1 are occurred just one or two locations of the tests T04 and T08 Especially, for the five tests at MPa (T17, T18, T22, T24 and T25), the very good void fraction distribution calculations are agreed with experiment distribution with deviation not more than 0.03 void along the channel Table 3.6 Base case void fraction distribution calculations versus experiment for cases at 3MPa Z 0.385 0.948 1.573 2.322 2.947 4.01 4.823 5.448 6.135 6.76 T01x 0 0 0 0.027 0.178 0.493 0.635 T01c 0 0 0 0.003 0.155 0.591 0.706 T04x 0.006 0.015 0.002 0.002 0.043 0.136 0.299 0.472 T04c 0 0 0 0.022 0.157 0.459 0.584 T08x 0.003 0.01 0.001 0 0.206 0.621 0.756 0.83 0.86 T08c 0 0 0.088 0.574 0.759 0.842 0.877 T10x 0.001 0.006 0.006 0.165 0.398 0.541 0.652 0.74 T10c 0 0 0.067 0.342 0.608 0.723 0.771 T14x 0.002 0.001 0 0.24 0.484 0.594 0.646 0.718 T14c 0 0 0.183 0.441 0.588 0.673 0.714 (x = Experiment, c= Calculation) Table 3.7 Base case void fraction distribution calculations versus experiment for cases at 7MPa Z 0.385 0.948 1.573 2.322 2.947 4.01 4.823 T17x 0.004 0.006 0.009 0.002 0.017 T17c 0 0 0 T18x 0.003 0.009 0.089 0.275 0.405 T18c 0 0 0.005 0.179 0.381 T22x 0.001 0.018 0.015 0.085 0.22 0.446 0.579 T22c 0 0.03 0.134 0.496 0.616 T24x 0 0 0.1027 0.2814 T24c 0 0 0.076 0.25 T25x T25c 0 0 0 0.1548 0 0 0.001 0.123 5.448 6.135 6.76 0.033 0.079 0.194 0.056 0.17 0.485 0.553 0.612 0.503 0.585 0.628 0.654 0.733 0.79 0.694 0.75 0.781 0.3973 0.4834 0.5585 0.406 0.512 0.564 0.4021 0.5178 0.6398 0.364 0.591 0.67 Table 3.8 Deviation between void fraction distribution calculation results versus experiment Z D(T01)* Heat mode D(T04) Heat mode D(T08) Heat mode D(T10) Heat mode D(T14) Heat mode 0.385 spl spl -0.003 spl spl -0.002 spl 0.948 spl -0.006 spl -0.01 spl -0.001 spl -0.001 spl 1.573 spl -0.015 spl -0.001 spl -0.006 spl spl 2.322 spl spl spl spl subc 2.947 spl -0.002 spl spl -0.006 spl subc 4.01 spl -0.002 subc -0.118 subc -0.098 subc -0.057 nucb 4.823 -0.024 subc -0.021 subc -0.047 nucb -0.056 nucb -0.043 nucb 5.448 -0.023 subc 0.021 nucb 0.003 nucb 0.067 nucb -0.006 nucb 6.135 0.098 nucb 0.16 nucb 0.012 nucb 0.071 nucb 0.027 nucb 6.76 0.071 nucb 0.112 nucb 0.017 nucb 0.031 nucb -0.004 nucb D(T017) Heat mode D(T18) Heat mode D(T22) Heat mode D(T24) D(T25) Heat mode Z Heat mode 0.385 spl spl -0.001 spl spl spl 0.948 -0.004 spl -0.003 spl -0.018 spl spl spl 1.573 -0.006 spl spl -0.015 subc spl spl 2.322 spl -0.009 subc -0.055 subc subc spl 2.947 -0.009 spl -0.084 subc -0.086 nucb subc spl 4.01 -0.002 0.05 nucb nucb 0.001 subc 4.823 -0.017 0.037 nucb 5.448 -0.033 0.04 nucb 0.0087 nucb 6.135 -0.023 subc 0.032 nucb 0.017 nucb 0.0286 nucb 0.0732 nucb 6.76 -0.024 nucb 0.016 nucb -0.009 nucb 0.0055 nucb 0.0302 nucb spl subc subc -0.096 -0.024 0.018 nucb nucb nucb 0.0267 0.0314 nucb 0.0318 0.0381 D (T01) = (T01C-T01X), c = calculation, x = experiment subc nucb It is found that CTF tend to under prediction when experiment void fraction below 0.2 where the CTF’s modeling for normal wall flow regime map is small bubble At the nearly outlet of the channel where the experiment data are more above 0.2 corresponding to heat transfer in saturated mode, CTF tend to over prediction Thus, CTF boiling model is still needed to be improved for both sub cooled and nucleate boiling regimes in order to generate more void in sub cooled region and reduce void at nucleate boiling region 3.4 Verification CFX models with PSBT sub channel tests 3.4.6 Assessment of CFX and CTF modeling results in comparison with PSBT single channel It is clear that CFX give better void fraction prediction in small bubble flow regime corresponding with sub cooled heat transfer mode in CTF It is noticed that the Nusselt number correlation used in CFX models for this case is Ranz Marshall Table 3.24 CFX and CTF results comparisons versus experiment void fraction in small bubble and sub cooled region Run No Pressure (kg/cm2) Mass Flux (106kg/m2h) Power (kW) Inlet Temp (oC) Exp Void CFX CTF heat Mode 1.2231 150.2 10.87 60.0 299.3 0.013 0.012 0.001 subc 1.2211 150.1 10.91 90.0 295.4 0.038 0.075 0.074 subc 1.4321 100.5 5.01 59.9 209.3 0.045 0.008 0.005 subc 1.4323 100.5 5.03 59.9 229.2 0.047 0.062 0.085 subc 1.5221 75.5 5.02 49.9 219.2 0.047 0.062 0.086 subc 1.2221 150.1 10.88 69.8 299.4 0.048 0.039 0.004 subc 1.2421 150.2 5.02 59.8 268.9 0.053 0.072 0.047 subc 1.3221 125.0 11.10 59.9 294.4 0.053 0.085 0.054 subc 1.2233 150.2 10.89 59.9 309.6 0.060 0.078 0.025 subc 1.2121 150.1 14.80 79.9 309.5 0.063 0.075 0.028 subc 1.6221 50.5 5.01 50.0 189.2 0.075 0.049 0.103 subc 1.2212 150.1 10.88 90.0 299.4 0.079 0.103 0.109 subc 1.2234 150.1 10.92 60.1 314.6 0.080 0.125 0.077 subc D(CFX)* D(CTF) -0.001 -0.012 0.037 0.036 -0.037 -0.040 0.015 0.038 0.015 0.039 -0.009 -0.044 0.019 -0.006 0.032 0.001 0.018 -0.035 0.012 -0.035 -0.026 0.028 0.024 0.030 0.045 -0.003 1.1221 169.1 10.95 49.9 329.7 0.087 0.109 0.032 subc 1.4121 100.1 10.97 69.9 274.1 0.097 0.118 0.134 subc 1.1222 169.1 10.98 50.0 334.7 0.142 0.168 0.094 subc 1.4411 100.4 1.99 19.9 253.7 0.152 0.183 0.167 subc 1.4324 100.1 5.02 60.1 238.9 0.157 0.145 0.197 subc 1.2422 150.1 5.00 60.0 284.1 0.182 0.194 0.198 subc 0.022 -0.055 0.021 0.037 0.026 -0.048 0.031 0.015 -0.012 0.040 0.012 0.016 Table 3.25 shows the void fraction calculations by CTF and CFX versus experiment in saturated region with measured void fraction in range of small-to-large bubbles and pressure lower than 122 bar It is observed that CTF give the over prediction in this region while CFX give the under prediction It is noticed that Nusselt number correlation used in CFX models in this case is Warierr Table 3.25 Comparison of CFX and CTF results and experiment void fraction in saturated region Run No Pressure (kg/cm2) Mass Flux (106kg/m2h) Power (kW) Inlet Temp (oC) Exp Void CFX CTF heat Mode D(CFX)* D(CTF) 1.5222 75.0 5.00 50.0 243.9 0.411 0.429 0.452 nucb 0.018 0.041 1.4412 100.2 5.03 79.8 248.9 0.504 0.605 0.584 nucb 0.101 0.080 1.4326 100.1 5.02 60.1 268.8 0.531 0.483 0.555 nucb -0.048 0.024 1.4312 100.2 5.03 79.8 248.9 0.566 0.457 0.588 nucb -0.109 0.022 1.4122 99.8 10.90 69.8 304.5 0.636 0.388 0.592 nucb -0.248 -0.044 1.5223 75.6 5.03 49.9 263.8 0.647 0.568 0.637 nucb -0.079 -0.010 1.6312 50.6 1.96 20.1 238.9 0.680 0.763 0.716 nucb 0.083 0.036 1.4327 100.1 4.96 59.9 289.0 0.688 0.591 0.689 nucb -0.097 0.001 1.6212 50.4 5.00 79.8 199.3 0.711 0.529 0.717 nucb -0.182 0.006 1.6223 50.5 5.03 49.9 239.0 0.718 0.609 0.72 nucb -0.109 0.002 3.4.8 Improvement of CFX void fraction prediction in saturated region Table 3.28 shows the void fraction and temperature superheating calculated before and after calibration presented in columns “Void”, “Tsup” and “Void*”, “Tsup*”, respectively It is noticed that Nusselt number correlation used in CFX models in this case is Kim and Park 10 Table 3.28 Void fraction and temperature super heating before and after calibration Run Void Tsup Scaling 43.28 Exp Void 0.531 DeltaT * (K) 1.2 Void* 1.4 MA F 0.65 1.4326 0.428 1.4312 D(CFX) D(CFX)* 0.544 Tsup* (K) 28.5 -0.103 0.013 0.404 62.57 0.566 1.4 0.75 2.4 0.559 48.66 -0.163 -0.007 1.4122 0.411 37.23 0.636 1.4 0.9 2.9 0.584 21.51 -0.226 -0.052 1.5223 1.4327 0.526 39.21 0.647 0.567 43.49 0.688 1.4 0.6 3.0 0.638 19.95 -0.121 -0.009 1.4 0.8 1.0 0.721 17.76 -0.121 0.033 1.6223 0.714 35.21 0.718 1.4 0.82 3.2 0.737 27.97 -0.004 0.019 *D (CFX) = (Void – Exp Void), D (CFX) = (Void* - Exp Void) Conclusions It is summarized the overall conclusions for verification and assessment of phase change as following - The system code RELAP5 with capability of modeling of whole system related to heat removal from the core to ultimate heat sink is utilized to simulate the reactor VVER-1000/V392 and related systems With the purpose of verification of our RELAP5 modeling, a scenario of LBLOCA in the confident document, Safety Analysis Report (SAR) for Belene (Bulgaria) project is used to compare simulations results Based on the two following arguments: (a) the deviations of timing in chronological sequence of main events in Table 3.4 with maximum of 15 seconds; (b) the behavior of maximum of peak cladding temperature (PCT) in the first duration of 300 seconds with similar maximum values less than 1200 oC and timing of cool down around at 280 seconds as illustrated in Figure 3.4, it is shown that simulation results given by this study are good agreed with the results presented in SAR - With regard to void fraction prediction in the core, the system code RELAP5 is not confident tool in case of high equivalent diameter of channel This conclusion is exposed from two issues: (a) RELAP5 is 1D code, so that the average or hot channel in the core is simulated as a pipe, that means the geometry of the core is not simulated as reality and the flow regime map in modeling may be different from 11 the reality; (b) The phase change models at the wall as presented in formulas (2.6) and (2.7) are depended on temperature near wall - CTF boiling models tend to under predict void fraction in sub cooled region where void fraction below 0.2 and tend to over predict void fraction at nucleate boiling region where void fraction above 0.2 For BM ENTEK experiment, CTF give void fraction distribution predictions for most all base cases are good agreement with experiment distributions with mainly deviation within experiment measured accuracy for void fraction (0.03 of void) and the maximum deviations with 0.1 of void between CTF prediction and experiment occur at downstream of channel in some tests - CFX gives the good prediction when void fraction below 0.2, corresponding with sub cooled heat transfer mode in CTF, with deviations around 0.03 of void So that, results in sub cooled region it is recommended to use void fraction predicted by CFX instead of CTF - For the saturated region corresponding with small-to-large bubble flow regime, CTF tends to give over void prediction and CFX tends to give under void prediction, Then, it is considered CFX and CTF results as lower and upper bounds for void fraction prediction along the channel - The improvement CFX simulation results in saturated region by scaling bubble departure diameter and maximum area fraction for quenching effect brings a new approach to continue development of RPI boiling models for saturated region Void fraction prediction in hot channel of VVER-1000/V392 4.2 Power distribution calculation by MCNP5 code The calculation results are based on whole core geometry simulation and the number of neutron histories equal 2.107 (with relative variation for keff around 10-5) The relative power for each assembly in 1/6 of the core is presented in Figure 4.5 Thus, the hot channel is an assembly with identification of 30A9P corresponding to maximum relative factor of 1.72 This value of power distribution is appropriate because it is within the range of (1.6, 1.8) mentioned in [34] 12 Figure 4.5 The relative power distribution in the sixth of the whole core Figure 4.6 shows the axial channel distribution of relative power with the maximum peaking factor of 1.52 that is also appropriate with distribution for the first fuel cycle as mentioned in [34] Figure 4.6 Distribution of relative power along axial hot channel For the CTF heat flux modeling, it is also needed the distribution of power inside each rod of hot channel and this calculation results are also performed by MCNP5 Figure 4.7 shows the relative power distribution for each rod inside the hot channel with maximum peaking factor of 1.374 13 Figure 4.7 Distribution of relative power in the hot channel 4.4.1 VVER-1000/V392 void fraction prediction by RELAP5 and CTF Table 4.2 Case studies for void fraction prediction Case ID Description LB01001 LB01002 SB01003 SB01004 Large break LOCA coupled with SBO-1 Large break LOCA coupled with SBO-2 Small break LOCA coupled with SBO-1 Small break LOCA coupled with SBO-2 Break Area (m2) 0.11 0.095 0.07 0.05 Equivalent Diameter (m) Location of break 0.374 0.348 0.298 0.252 Cold Leg Cold Leg Cold Leg Cold Leg 14 (LB01001) (LB01002) (SB01003) (SB01004) Figure 4.13 Void fraction prediction by CTF and RELAP5 for SBLOCAs  Accuracy of void faction predictions - Geometry of flow in modeling Due to RELAP5 model of flow is 1D, so that the flow through hot channel including 312 fuel rods is simulated as the flow in a pipe with equivalent flow area of 0.02538 m2 as mentioned in Table 28 The conversion of geometry of flow in RELAP5 causes inaccuracy in flow regime in comparison with origin flow This issue affects to accuracy of void fraction In other hand CTF model of flow is 3D as illustrated in Figure 4.2 with P equal 12.75 mm and D equal 9.1 mm Therefore, the flow at scale of sub channel is modeled properly - Determine temperature of liquid near wall For the RELAP5 model, the temperature is averaging inside a control volume Therefore, the temperature of liquid near wall is the same at the center of the flow For example, with the flow area of 0.02538 m2 then the distance from center of flow to the wall is around cm For the CTF model of flow is based on sub channel geometry as in Figure 4.2, and then the distance from the center of flow to the wall is about 0.275 cm It is concluded that the physical models for phase change of RELAP5 and CTF presented in formulas (2.6), (2.7) and (2.8), (2.17), respectively, is depended on near wall liquid enthalpy (or temperature) CTF gives the near wall enthalpy better than RELAP5, 15 and then its calculation of phase change is more accuracy Besides, the conversion of flow is not implemented as in RELAP5, so that, the flow regime in CTF model is reliable Based on above arguments and the fact that CTF can predict void fraction with pressure of 3MPa and 7MPa with acceptable accuracy such as BM ENTEK tests [33], it is concluded that CTF gives better void fraction prediction results than RELAP5 4.5 Void fraction prediction of single channel by CFX code For the case identification such as SB01003-09-37, it is shown that this case is taken from case identification as in Table 4.2 (SB01003) with the timing of view at 09 second from beginning of transient and sub channel number of 37 as in Figure 4.11 Figure 4.11 the cross section of CTF modeling for the selected part of the whole bundle Based on conclusion in chapter 3, it is recommended that for the case that CTF give void fractions lower than 0.2, it is used CFX results instead of CTF For the saturated region with small-to-large bubble regime, it is considered that CTF and CFX results are considered as upper and lower bounds, respectively Table 4.7 Void fraction prediction by CTF and CFX at downstream of channel at z = 3.48m Case ID SB01003-16-15 CTF bundle 0.062 CTF Boiling Mode nucb CTF single 0.094 CFX 0.1319 16 SB01003-16-30 SB01003-14-34 SB01003-20-15 LB01002-20-18 LB01002-15-30 LB01002-20-20 SB01003-09-37 LB01002-30-30 0.146 0.173 0.153 0.424 0.395 0.442 0.429 0.609 nucb nucb nucb nucb nucb nucb nucb nucb 0.101 0.152 0.2 0.356 0.361 0.438 0.444 0.64 0.1371 0.1964 0.2195 0.2979 0.32 0.3954 0.4064 0.6433 Figure 4.18 Axial sub channel void fraction prediction by CFX and CTF 4.6 Void fraction prediction for a bundle of channel by CFX code As conclusions in section 3.5 chapter 3, the results of CTF in small bubble flow corresponding with heat transfer mode of sub cooled region are recommended to be replaced by CFX results and for saturated region CTF and CFX predictions are considered as lower and upper bound curves Therefore, to illustrate this argument, it is selected sub cooled and saturated domains for each case as presented in Table 4.8 and 4.9, respectively 17 Table 4.8 Sub cooled selected regions for CFX investigation Sub cooled selected region Inlet (m) Outlet (m) Inlet void 0.0 Inlet Pressure (bar) 101.712 Mass flow (kg/s) 3.86 LB01001-06 0.926 1.647 LB01002-07 1.236 SB01003-14 SB01004-30 Power (kW) 438.944 Inlet temp (oC) 300.486 1.956 0.0 106.812 4.94 416.674 301.539 2.265 2.986 0.018 89.841 3.9 94.057 300.396 1.544 2.265 0.0 75.489 2.64 52.142 287.685 Table 4.9 Saturated selected regions for CFX investigation Saturated selected region Inlet (m) Outlet (m) Inlet void 0.707 Inlet Pressure (bar) 101.168 Mass flow (kg/s) 3.89 LB01001-06 3.089 3.53 LB01002-07 3.089 SB01003-14 SB01004-30 Power (kW) 95.701 Inlet temp (oC) 311.852 3.53 0.467 106.215 4.92 77.111 315.459 3.089 3.53 0.1 89.708 3.89 21.658 303.952 3.089 3.53 0.129 75.302 2.69 11.833 290.812 The left pictures of Figure 4.21 present CTF’ void fraction prediction and improvement results by CFX calculation for cases LB01001-06, LB01002-07, SB01003-14 and SB01004-30 The right pictures of Figure 4.21 show the upper and lower bounds for void fraction given by CTF and CFX calculation results It is noticed that CTF give higher prediction than CFX as mentioned in sections 3.4 and 3.5 in chapter 18 Figure 4.21 Improvement by CFX in left pictures and upper and lower bounds in right pictures 4.7 Conclusions 19 In summary of the work done in this chapter, several of the main issues from study of void fraction prediction for hot channel in the core of VVER-1000/V392 are presented as below - It is well implemented the simulation of VVER-V392 reactor by system code RELAP5 with power distribution provided by neutron code MNCP5 for the first fuel cycle using the model which is validated as mentioned in chapter - CTF and CFX can be used to predict void fraction in the core based on reference to each other With the void fraction below 0.2 and heat transfer mode in CTF is sub cooled boing, CTF tends to give under prediction and in this case it is used CFX results instead of CTF due to CFX gives better prediction with accuracy around ±0.03 of void - Due to CTF tends to over prediction of void fraction in nucleate boiling mode So that, in saturated boiling region, CTF and CFX void fraction predictions can be used as upper bound and lower bound curves Conclusions As mentioned in chapter 1, the main objective of the thesis is numerical investigation of void fraction in the core of VVER1000/V392 reactor with the goal as following:  To adopt a procedure of void fraction prediction during transient using multi scale analysis based on the computer codes: MCNP5, RELAP5 and CTF;  To consider a combination of CTF and Ansys CFX codes to improve void fraction predicted by CTF in specific timing within the transient period It is concluded that both above issues are solved in this study The procedure of void fraction prediction during transient using multi scale are presented in chapter based on verification and validation of boiling models for different scale codes which is implemented in chapter As mentioned in chapter 1, a utilization of CTF and CFX codes to improve void fraction predicted CTF is new issue for void fraction prediction in the core As results of the thesis, the issue of void fraction prediction in core is improved by the utilization of CTF and CFX codes with reference to each other CTF give the void prediction during transient time and its results in specific moment is 20 improved by reference with CFX In the sub cooled region with low void (void below 0.2 defined by CTF) the CFX result is used and in the saturated boiling region (defined by CTF with void normally between 0.2 and 0.5) then void fraction prediction curves calculated by CTF and CFX is considered as upper and lower bounds It is summarized the thesis results as below 5.1 New findings and achievements from the thesis  Proposal of a reality of best estimate approach in void fraction prediction by utilization of multi codes and multi scale including MCNP5, RELAP5, CTF and CFX for analysis of void fraction behavior in the core during transient  For system analysis by RELAP5 code for VVER-1000/V392, it is found that temperature near heated wall is not defined with enough accuracy if simulation of a whole fuel assembly as hot channel, so that the phase change models in RELAP5 not give appropriate value of void fraction  From verification and validation of CTF results with ENTEK BM experiment, it is observed that CTF tends to give under prediction of void in the region of sub cooled boiling and flow regime in small bubble (αg < 0.2) and CTF tends to give over prediction of void in nucleate boiling region, corresponding with small-to-large bubble in flow regime  From verification with PSBT single sub channel experiment, CFX with models setup proposed by this thesis is converged with RMS of 1e-6 and stabilized in term of average void fraction prediction with physical sensitivity study For the sub cooled boiling region corresponding with small bubble of flow regime (αg < 0.2), CFX gives the appropriate void fraction prediction with accuracy around ±0.03 of void  In saturated boiling region, the wall boiling model built in CFX is incorrectly partitioned heat flux to corresponding parts in convective, quenching and evaporative This issue causes CFX gives under prediction of void fraction in saturated boiling region It is proposed a calibration for bubble departure diameter and maximum area fraction to improve void fraction prediction by CFX in saturated region 21  It is established a procedure of utilization of CTF and CFX for void fraction prediction as following: (a) at sub cooled region, corresponding with small bubble flow regime, CFX results is used; (b) in saturated boiling region, CTF and CFX void fraction curves along the channel is used as upper bound and lower bound to predict void fraction in the core 5.2 Proposal of future work Utilization of CFD codes for investigation of void fraction in the core is still a challenge This comes from complexity of boiling phenomena and the lack of experiment with similar PWR condition to verification and validation CFD models Based on study in the thesis, several following issues are proposed to study  Study on modification of RPI wall boiling model built in CFX (and FLUENT) in saturated boiling region Due to the fact that, in saturated boiling model, liquid temperature is the same saturated one everywhere, even near wall, so that evaporation and quenching phenomena can be dominated  Implement more experiment in similar PWR conditions which provides with void fraction distribution that can be used to validate evaporation and condensation models in CFX  Study on more accuracy of void fraction prediction of CFX based on condensation models such as the correlation of Nusselt number in different boiling conditions 22