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Articles

Simulation of melt jet breakup experiments by JASMINE with an empirical correlation for melt particle size distribution

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Pages 1608-1621 | Received 10 Sep 2015, Accepted 21 Jan 2016, Published online: 04 Mar 2016

Figures & data

Figure 1. Modeling of melt jet breakup in JASMINE code [Citation9].

Figure 1. Modeling of melt jet breakup in JASMINE code [Citation9].

Figure 2. A simple non-local radiation heat transfer model.

Figure 2. A simple non-local radiation heat transfer model.

Figure 3. Treatment of settled particle groups.

Figure 3. Treatment of settled particle groups.

Table 1. Summary of conditions and results of selected ALPHA/GPM experiments [Citation12].

Figure 4. Analytical grid for ALPHA/GPM simulation (left: deep pool, right: shallow pool).

Figure 4. Analytical grid for ALPHA/GPM simulation (left: deep pool, right: shallow pool).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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.

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.

Figure 16. Analytical grid for FARO L14 (left) and L28/L31 (right) simulation.

Figure 16. Analytical grid for FARO L14 (left) and L28/L31 (right) simulation.

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).

Figure 18. FARO L14, L28, and L31: comparison with experimental data on debris size distribution.

Figure 18. FARO L14, L28, and L31: comparison with experimental data on debris size distribution.

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.

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