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ARTICLES

Convergence analysis of coarse mesh finite difference method applied to two-group three-dimensional neutron diffusion problem

Pages 926-936 | Received 02 May 2012, Accepted 04 Jul 2012, Published online: 21 Aug 2012

Figures & data

Figure 1. Flowchart of CMFD global–local iteration.

Figure 1. Flowchart of CMFD global–local iteration.

Figure 2. Sensitivity of convergence rate to core size (2-N CMFD; 2-G 3D model EVP).

Figure 2. Sensitivity of convergence rate to core size (2-N CMFD; 2-G 3D model EVP).

Figure 3. Convergence rate vs. mesh size (2-N CMFD; 2-G 3D model problem).

Figure 3. Convergence rate vs. mesh size (2-N CMFD; 2-G 3D model problem).

Figure 4. Sensitivity of 1-N CMFD convergence rate to mesh size and relaxation parameter with 2-G 3D model EVP (Shin's CCF; Jacobi-style Jin update, single sweep). (a) Convergence rate vs. mesh size and (b) convergence rate vs. relaxation parameter.

Figure 4. Sensitivity of 1-N CMFD convergence rate to mesh size and relaxation parameter with 2-G 3D model EVP (Shin's CCF; Jacobi-style Jin update, single sweep). (a) Convergence rate vs. mesh size and (b) convergence rate vs. relaxation parameter.

Figure 5. Sensitivity of 1-N CMFD convergence rate to sweep strategy for the 2-G 3D model EVP (Shin's CCF).

Figure 5. Sensitivity of 1-N CMFD convergence rate to sweep strategy for the 2-G 3D model EVP (Shin's CCF).

Figure 6. Sensitivity of 1-N CMFD convergence rate to CCF form (Jacobi/G–S-style double sweeps, R–B ordering).

Figure 6. Sensitivity of 1-N CMFD convergence rate to CCF form (Jacobi/G–S-style double sweeps, R–B ordering).

Figure 7. Sensitivity of 1-N CMFD convergence rate to CCF form (Shin's form B: CCF update after all the local 1-N sweeps).

Figure 7. Sensitivity of 1-N CMFD convergence rate to CCF form (Shin's form B: CCF update after all the local 1-N sweeps).

Table 1. Cross section data for 2-G problem.

Table 2. List of test cases (3D cubic core with uniform meshes).

Table 3. Parameters for 1-N CMFD strategy.

Figure 8. PARCS quarter-core model for NEACRP A1 case (A: 100 steps, C: 200 steps).

Figure 8. PARCS quarter-core model for NEACRP A1 case (A: 100 steps, C: 200 steps).

Figure 9. Jacobi vs. G–S Jin update (Joo's CCF, triple sweeps).

Figure 9. Jacobi vs. G–S Jin update (Joo's CCF, triple sweeps).

Table 4. Summary of NEACRP A1 calculation (Joo's CCF, G–S Jin update, R–B ordering).

Figure 10. Convergence rate of 1-N/2-N CMFD (Joo's CCF, G–S Jin update).

Figure 10. Convergence rate of 1-N/2-N CMFD (Joo's CCF, G–S Jin update).

Figure 11. Convergence of single-sweep 1-N CMFD for NEACRP A1 steady state (Joo's CCF, G–S Jin update, R–B ordering). (a) Error reduction vs. relaxation parameter and (b) CCF convergence of node (k = 9, l = 40).

Figure 11. Convergence of single-sweep 1-N CMFD for NEACRP A1 steady state (Joo's CCF, G–S Jin update, R–B ordering). (a) Error reduction vs. relaxation parameter and (b) CCF convergence of node (k = 9, l = 40).

Table 5. Summary of NEACRP A1 steady state with single-sweep 1-N CMFD (Joo's CCF, G–S Jin update, R–B ordering).

Table 6. Summary of NEACRP A1 steady state with double-sweep 1-N CMFD (Joo's CCF, G–S Jin update, R–B ordering).

Table 7. Summary of NEACRP A1 steady state with triple-sweep 1-N CMFD (Joo's CCF, G–S Jin update, R–B ordering).

Figure 12. Convergence of 1-N CMFD for NEACRP A1 steady state (Joo's CCF, G–S Jin update, R–B ordering).

Figure 12. Convergence of 1-N CMFD for NEACRP A1 steady state (Joo's CCF, G–S Jin update, R–B ordering).

Table 8. Summary of NEACRP steady state calculations (Joo's CCF; triple sweeps (1-N CMFD), G–S Jin update, R–B ordering, under-relaxation 0.8).

Table 9. Summary of NEACRP transient calculations (Joo's CCF; triple sweeps (1-N CMFD), G–S Jin update, R–B ordering, under-relaxation 0.8).

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