Figures & data
Figure 1. Modeling of melt jet breakup in JASMINE code [Citation9].
![Figure 1. Modeling of melt jet breakup in JASMINE code [Citation9].](/cms/asset/ce0d4a80-da67-4706-8ae8-9df7099705c5/tnst_a_1146636_f0001_oc.jpg)
Table 1. Summary of conditions and results of selected ALPHA/GPM experiments [Citation12].
Table 2. Physical properties of the melt material used in the simulation [Citation3,Citation12,Citation28,Citation29].
Table 3. Model parameters in JASMINE code relevant to the present work.
Figure 5. Snapshots of GPM10 (ZAO, subcool) simulation, base case (time 1.5, 3, 7, and 12 s) (red/black dots are molten/frozen particles).
![Figure 5. Snapshots of GPM10 (ZAO, subcool) simulation, base case (time 1.5, 3, 7, and 12 s) (red/black dots are molten/frozen particles).](/cms/asset/3fd2fbde-f641-4b08-b7fc-3e00b523620f/tnst_a_1146636_f0005_oc.jpg)
Figure 6. GPM10 (ZAO, subcool): comparison with experimental data on melt jet leading edge progress (a), water temperature (b), and containment pressure (c).
![Figure 6. GPM10 (ZAO, subcool): comparison with experimental data on melt jet leading edge progress (a), water temperature (b), and containment pressure (c).](/cms/asset/28f370c6-959d-4380-a1a5-ae371fe1c88b/tnst_a_1146636_f0006_oc.jpg)
Figure 7. GPM10 (ZAO, subcool): sensitivity of model parameters on the re-agglomerate fraction (a) and heat transfer to water (b).
![Figure 7. GPM10 (ZAO, subcool): sensitivity of model parameters on the re-agglomerate fraction (a) and heat transfer to water (b).](/cms/asset/103297b3-1774-4587-b65e-339ce81d483d/tnst_a_1146636_f0007_oc.jpg)
Figure 8. Snapshots of GPM05 (ZAO, shallow pool) simulation, base case (time 1.5, 3, 7, and 12 s) (red/black dots are molten/frozen particles).
![Figure 8. Snapshots of GPM05 (ZAO, shallow pool) simulation, base case (time 1.5, 3, 7, and 12 s) (red/black dots are molten/frozen particles).](/cms/asset/8d76e0b2-0137-4999-9a8a-7e45c87d36df/tnst_a_1146636_f0008_oc.jpg)
Figure 9. GPM05 (ZAO, shallow pool): sensitivity of model parameters on the re-agglomerate fraction (a) and heat transfer to water (b).
![Figure 9. GPM05 (ZAO, shallow pool): sensitivity of model parameters on the re-agglomerate fraction (a) and heat transfer to water (b).](/cms/asset/ac7ab7ad-0cff-4046-835a-7cc11077f3a7/tnst_a_1146636_f0009_oc.jpg)
Figure 10. Snapshots of GPM12 (ZAO, saturation) simulation, Chtc = 4 (time 1.5, 3, 7, and 12 s) (red/black dots are molten/frozen particles).
![Figure 10. Snapshots of GPM12 (ZAO, saturation) simulation, Chtc = 4 (time 1.5, 3, 7, and 12 s) (red/black dots are molten/frozen particles).](/cms/asset/215b1b16-45d0-49eb-a468-8190a8db73fc/tnst_a_1146636_f0010_oc.jpg)
Figure 11. GPM12 (ZAO, saturation): sensitivity of model parameters on the re-agglomerate fraction (a) and heat transfer to water (b).
![Figure 11. GPM12 (ZAO, saturation): sensitivity of model parameters on the re-agglomerate fraction (a) and heat transfer to water (b).](/cms/asset/24ba933e-4572-4814-8911-3b99d2a44e40/tnst_a_1146636_f0011_oc.jpg)
Figure 12. GPM09 (SUS, subcool): sensitivity of model parameters on the re-agglomerate fraction (a) and heat transfer to water (b).
![Figure 12. GPM09 (SUS, subcool): sensitivity of model parameters on the re-agglomerate fraction (a) and heat transfer to water (b).](/cms/asset/6d68fab8-3742-4450-8577-1262c406878b/tnst_a_1146636_f0012_oc.jpg)
Figure 13. GPM08 (SUS, saturation): sensitivity of model parameters on the re-agglomerate fraction (a) and heat transfer to water (b).
![Figure 13. GPM08 (SUS, saturation): sensitivity of model parameters on the re-agglomerate fraction (a) and heat transfer to water (b).](/cms/asset/9e1e20bf-7df3-4f2d-aea7-4c9431c6e740/tnst_a_1146636_f0013_oc.jpg)
Figure 14. Comparison of the calculated containment pressure with experimental data for ALPHA/GPM. Calculation cases GPM10 and 05: base case, GPM12, 09, and 08: Chtc = 4.
![Figure 14. Comparison of the calculated containment pressure with experimental data for ALPHA/GPM. Calculation cases GPM10 and 05: base case, GPM12, 09, and 08: Chtc = 4.](/cms/asset/ef9a5591-eaea-4838-96f1-531d0e87775e/tnst_a_1146636_f0014_oc.jpg)
Figure 15. Comparison of calculated particle size distribution with experimental data for ALPHA/GPM. Calculation cases GPM10 and 05: base case, GPM12, 09, and 08: Chtc=4.
![Figure 15. Comparison of calculated particle size distribution with experimental data for ALPHA/GPM. Calculation cases GPM10 and 05: base case, GPM12, 09, and 08: Chtc=4.](/cms/asset/ef8e260b-be47-4a36-9cd7-0496d5ac82da/tnst_a_1146636_f0015_oc.jpg)
Table 4. Summary of conditions and results of selected FARO experiments [Citation13].
Figure 17. FARO L14, L28, and L31: comparison with experimental data on pressure (a), heat exchange (b), and agglomerate fraction (c).
![Figure 17. FARO L14, L28, and L31: comparison with experimental data on pressure (a), heat exchange (b), and agglomerate fraction (c).](/cms/asset/bece41d4-f8f0-41b6-877a-3c18e9a4e1a0/tnst_a_1146636_f0017_oc.jpg)
Figure 19. FARO L14, L28, and L31: impact of the modified models on the heat transfer: ‘nlrad-off’ non-local radiation model disabled, ‘mono’ mono-spectrum particle size at mass median diameter, ‘mono, Chtc = 1’ mono-spectrum particle size without heat transfer modification.
![Figure 19. FARO L14, L28, and L31: impact of the modified models on the heat transfer: ‘nlrad-off’ non-local radiation model disabled, ‘mono’ mono-spectrum particle size at mass median diameter, ‘mono, Chtc = 1’ mono-spectrum particle size without heat transfer modification.](/cms/asset/e82df673-b1c1-475a-9c6b-f3584781ac4b/tnst_a_1146636_f0019_oc.jpg)