EVALUATION OF THE IAEA 3-D PWR BENCHMARK PROBLEM USING NESTLE CODE Imelda Ariani* , Doddy Kastanya **
ABSTRAK EVALUATION OF THE IAEA 3-D PWR BENCHMARK PROBLEM USING NESTLE CODE. Sebagai bagian dari persiapan pembangunan dan pengoperasian PLTN di Indonesia, BATAN telah memulai kegiatan untuk meningkatkan kualitas sumber daya manusia yang dimilikinya. Sebagai tahap awal untuk persiapan itu, khususnya dalam bidang neutronik, telah disepakati bahwa beberapa pusat di BATAN melakukan perhitungan dengan menggunakan berbagai jenis kode komputer untuk menganalisis tiga buah problem yang berkaitan dengan perhitungan neutronik pada level lattice maupun teras. Makalah ini mempresentasikan hasil perhitungan problem yang kedua, yaitu perhitungan IAEA 3-D teras PWR dengan menggunakan kode komputer berbasis persamaan difusi dengan metoda nodal dan beda hingga. Kata kunci: simulasi teras PWR, difusi teori, metoda beda hingga, metoda nodal.
ABSTRACT EVALUATION OF THE IAEA 3-D PWR BENCHMARK PROBLEM USING NESTLE CODE. As part of the preparations for the eventual operation of a nuclear power plant in Indonesia, BATAN has organized some activities to improve the quality of its human resources, particularly in the neutronic field. As a preliminary step, it has been agreed that several centers which deal with the reactor neutronics will commit to perform calculations on three benchmark problems related to neutronics calculations in lattice and core levels. This paper presents the results of the second benchmark problem, i.e. the IAEA 3-D PWR, utilizing the NESTLE core simulator which is based on the diffusion theory with finite difference and nodal method solvers. Keywords: PWR core simulator, diffusion theory, finite difference method, nodal expansion method.
INTRODUCTION In preparation for the eventual operation of Indonesia’s first nuclear power plant in 2016, some activities are being organized to improve the quality of human resources at BATAN by providing them with appropriate tools and knowledge to handle this technology. Recent formation of a working group focusing on reactor *
Pusat Pengembangan Sistem Reaktor Maju – BATAN, Emails:
[email protected] Pusat Pendayagunaan IPTEK Nuklir – BATAN, Emails:
[email protected]
**
technology is one example of these activities. This working group is divided into three sub-groups, namely the neutronics, thermal hydraulics, and probabilistic safety analysis, where the members of each sub-group should have the expertise and practical experiences in the corresponding field. Before taking a giant leap to analyzing real nuclear power plant problems, the neutronics sub-group had decided to firstly put everyone at the same starting point. To accomplish this goal, some benchmark cases have been agreed upon and several research centers at BATAN have committed to performing the calculations. Results presented this paper are related to the calculations performed on the second benchmark problem in the set, i.e. the 3-D pressurized water reactor (PWR) core problem. Details on the specifications and the methodology to solve the problem are given in Sections 0 and 0. Section 0 discusses various results from solving this problem using the finite difference method (FDM) and the nodal expansion method (NEM). Conclusion of this study and recommendations for future research are summarized in Section 0. PROBLEM STATEMENT An IAEA 3-dimensional PWR problem is chosen as the second benchmark problem for the neutronic group. The problem specifies two-group cross sections for two different fuel assemblies and reflector regions. Rodded cross sections are also given. The core loading pattern is shown in Figure 1 while the corresponding cross sections are given in Table 1. There are 177 fuel assemblies in the core with 15 fuel assemblies across the core major axis. The radial assembly width is 20 cm. One layer of radial reflector region surrounds the fuel assemblies. The active core height is 340 cm and there is a 20 cm axial reflector region at the bottom and top of the core (see Figure 2). The purpose of this benchmark exercise is to calculate the core keff and power distribution using a diffusion equation-based neutronic code. The core keff and power distribution prediction from the code can then be compared with the reference solutions. Table 1: IAEA 3-D PWR two-group cross sections 1 Fuel 1 Fuel 1 + Rod Fuel 2 Reflector Reflector + Rod
1
D1 1.5 1.5 1.5 2.0 2.0
D2 0.4 0.4 0.4 0.3 0.3
Values taken from ANL-ID.11-A1 benchmark book
Σ a1 0.01 0.01 0.01 0.00 0.00
Σ a2 0.085 0.130 0.080 0.010 0.055
νΣ f1 0.0 0.0 0.0 0.0 0.0
νΣ f2 0.135 0.135 0.135 0.000 0.000
Σ s12 0.02 0.02 0.02 0.04 0.04
Figure 1. IAEA 3-D PWR radial quarter core loading pattern
80 cm
380 cm
20 cm
Figure 2. IAEA 3-D PWR axial core configuration.
REFERENCE SOLUTIONS The reference solutions were obtained using the PARCS code [0], a US core simulator developed by Purdue University. PARCS solves the two-group neutron diffusion equation utilizing the analytic nodal method (ANM). To solve the IAEA 3-D benchmark problem, PARCS employed 2x2 radial nodes per assembly, with the radial size of each node of 10 cm. The active core height (340 cm) was divided into 17 uniform axial meshes. The axial node size for bottom and top reflector regions were set to 20 cm each. A non-reentrant boundary condition (zero incoming current) was applied to the exterior radial and axial boundaries. A reflective boundary condition was employed at the interior radial boundaries. The following parameters were applied to the PARCS iteration scheme:
Maximum number of inner iteration Eigenvalue convergence Relative residual L2-norm Maximum relative residual Wielandt shift for initial iteration Wielandt shift for other iterations Nonlinear nodal update frequency
: : : : : : :
500 1.e-6 1.e-5 5.e-4 0.01 0.04 4
The CPU timing results were as follows. Note that the details/specifications on the computer/CPU on which the calculations were performed are unknown. Total execution time Initialization time Coarse mesh finite difference time Nodal method time
: : : :
3.285 0.060 2.564 0.701
seconds seconds seconds seconds
The core keff from the PARCS’ steady state, eigenvalue calculation was found to be 1.029096. The axial and radial assembly relative power distributions are shown in Figure 3 and Figure 4, respectively.
IAEA 3D Axial Power Distribution 1.8 Relative Power Fraction
Distance (cm) Power from bottom 10 0.350 30 0.600 50 0.859 70 1.087 90 1.276 110 1.420 130 1.514 150 1.553 170 1.538 190 1.469 210 1.348 230 1.181 250 0.975 270 0.743 290 0.538 310 0.353
1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 0
100
200
300
400
Distance from bottom core (cm)
Figure 3. Axial relative power distribution (reference).
A B C D E F G H
1 0.7264 1.2742 1.4156 1.1884 0.6097 0.9524 0.9607 0.7798
2 1.2742 1.3899 1.4248 1.2856 1.0685 1.0543 0.9768 0.7600
3 1.4156 1.4248 1.3627 1.3065 1.1785 1.0888 1.0016 0.7152
4 1.1884 1.2856 1.3065 1.1751 0.9702 0.9238 0.8698
5 0.6097 1.0685 1.1785 0.9702 0.4766 0.7015 0.6150
6 0.9524 1.0543 1.0888 0.9238 0.7015 0.6017
7 0.9607 0.9768 1.0016 0.8698 0.6150
8 0.7798 0.7600 0.7152
Figure 4. Assembly relative assembly power distribution (reference).
NESTLE SOLUTIONS Background on NESTLE Code NESTLE1 [2], developed by North Carolina State University, is a FORTRAN 77 code that solves few-group neutron diffusion equation utilizing the nodal expansion method (NEM). NESTLE can solve the eigenvalue with criticality search, eigenvalue adjoint, external fixed-source steady state or external fixed-source/eigenvalue initiated transient problems. The code name NESTLE originates from the multi-problem solution capability, abbreviating Nodal Eigenvalue, Steady-state, Transient, Le core Evaluator. Core geometries modeled include Cartesian and hexagonal. Three-, two-, and one-dimensional models can be utilized with various symmetries. The non-linear iterative strategy associated with the NEM is employed. An advantage of the nonlinear iterative strategy is that NESTLE can be utilized to solve either the nodal or finite difference method (FDM) representation of the few-group neutron diffusion equation. For Cartesian geometry, the NEM is based upon quartic polynomial expansion functions; whereas, for hexagonal geometry, the NEM is based upon the semi-analytic nodal method utilizing trigonometric, hyperbolic trigonometric and polynomial expansion functions and the conformal mapping technique. Thermal hydraulic feedback is modeled employing a homogeneous equilibrium mixture (HEM) model, allowing two-phase flow to be treated. The thermal conditions predicted by the thermal hydraulic model are used to correct the cross sections for temperature and density effects. Cross sections are parameterized by color, control rod state and burnup, allowing fuel depletion to be modeled. Either a macroscopic or microscopic model may be employed. All cross sections are expressed in terms of a Taylor’s expansion in coolant density, coolant temperature, effective fuel temperature, and soluble poison number density. Memory management is accomplished utilizing a container array to facilitate efficient memory allocation. IAEA 3-D PWR Model in NESTLE Several cases were completed to examine the behavior of the solver in solving the IAEA 3-D PWR core model. Both FDM and NEM methodologies were examined. The sensitivity of the predictions to the mesh size selection was also studied. Iteration convergence criteria were varied to see their effects on the neutronic predictions and CPU timing. The complete descriptions of the changing variables in each case are shown in Table 2.
RESULT DISCUSSIONS Cases 1 and 3: Nodal Expansion Method (NEM) Case 1 is the closest match to the methodology used to obtain the reference solutions. Both case 1 and reference case utilized a nodal method with 2x2 nodes per assembly radial meshing (uniform node size of 10 cm x 10 cm x 20 cm). Similar stopping criteria were also employed. Excellent agreement in the core keff prediction is observed (less than 1 pcm difference). The assembly and axial relative power distributions also agree well with the reference values (Figure 5 and Figure 6). The maximum difference in the assembly power is 0.0018 with a root mean square (RMS) assembly power difference of 0.001 which is deemed to be good. A tilt in the assembly power comparison is also observed. NESTLE predicts slightly lower power values for assemblies closer to the peripheral. Conversely, higher power value predictions are observed at the assemblies closer to the center. The absolute difference in the peak assembly power is -0.0013 which is less than 0.1%. Case 1 is also the fastest in terms of CPU time (2.44 sec.). Overall, the comparisons between NESTLE’s predictions and the reference values are excellent. Case 3 is similar to Case 1, except for the size of the radial mesh. The node size is reduced by a factor of four (i.e. each node is now 2.5 cm x 2.5 cm x 20 cm). Case 3 results are practically the same as those for Case 1 (see Table 3). Hence, further mesh refinement for the NEM case is unnecessary. As expected, due to mesh refinement, the CPU time of Case 3 increases to around 13 seconds.
Cases 2, 4,5,6,7, 8, and 9: Finite Difference Method (FDM) Cases 2, 4 through 9 employ finite difference method instead of nodal expansion method to solve the diffusion equation. The purpose of these exercises is to prove the superiority of the nodal method versus finite difference method. Case 2 utilized identical conditions to Case 1, except for the methodology used in solving the diffusion equation. As expected, using the same node size as used by NEM, the FDM predictions of power distributions are in poor agreement with the reference values (see Figure 7). The maximum assembly power difference for Case 2 is around 0.17 with RMS difference of 0.1. These magnitudes of errors are considered unacceptable. To yield an acceptable solution set, the mesh size of FDM should be set to less than the limiting diffusion length (~ 1.8 cm for this specific case). The CPU time for Case 2 is 0.7 seconds, which is around one-third of the NEM case. To make FDM results more comparable to the NEM results, we performed mesh refinements in Cases 4 through 9. The assembly power distributions for Cases 4
through 8 are not shown in this paper to conserve space. Instead, global measures of power difference in terms of RMS power differences are shown in Table 3. It can be seen from Table 3 that the agreement in the power distribution improves as the mesh size is refined. However, even when the mesh size is reduced to 49 times smaller than the original size, the FDM still cannot produce power predictions which are comparable to the NEM results. As expected, the execution time grows rapidly as the FDM mesh is refined. The best FDM results obtained using a 1.428 cm x 1.428 cm x 20 cm (Case 9). The maximum assembly power difference for Case 9 is 0.017 which is still considered large in the PWR world. Further mesh refinement is not completed due to the memory limitation.
Cases 10 and 11: Slight Variations of NEM Cases 10 and 11 are similar to Case 1. In Case 10, the convergence criteria were relaxed by one order of magnitude. As expected, the CPU time decreases as more relaxed criteria were employed (Table 3). The core keff and power distribution agreements degrade slightly compared to Case 1 results. In Case 11, the frequency of the NEM update is changed from 5 to 3. The choice of the frequency of the NEM update impacts the execution time. In Case 11, changing the NEM frequency update from 5 to 3 reduces the CPU time slightly without impacting the overall solutions. CONCLUSIONS AND RECOMMENDATIONS The evaluation of the second benchmark problem chosen for the neutronic reactor technology group has been completed. The IAEA 3-D PWR problem was examined using a nodal based diffusion theory code called NESTLE. The NEM-based NESTLE’s predictions of core keff and power distributions agree well with the reference values. Further studies confirmed the superiority of the NEM over the FDM. For the current problem, the FDM cannot predict power distributions with acceptable agreement even when the mesh size was refined into much smaller mesh size than the original size (49 times smaller). The nodal method produces higher fidelity results with a shorter CPU time. Therefore, the usage or development of a diffusion equationbased core simulator code with a finite difference method is not recommended. ACKNOWLEDGMENT The authors would like to thank Mr. Tagor Sembiring for sharing the PARCS values for the IAEA 3-D benchmark problem.
REFERENCES 1. H.G. JOO, et.al., PARCS (Purdue Advanced Reactor Core Simulator), A MultiDimensional Two-Group Reactor Kinetics Code Based on the Nonlinear Analytic Nodal Method, Technical Report, PU/NE-98-26 (1998) 2. P.J. TURINSKY, et.al., “NESTLE, A Few-Group Neutron Diffusion Equation Solver utilizing the Nodal Expansion Method for Eigenvalue, Adjoint, FixedSource, and Transient Problem,” Idaho National Energy Laboratory (1994)
Table 2: NESTLE Benchmark Cases
Case
Solution Method
#nodes per assembly
# axial nodes
Total # of nodes
1 2 3 4 5 6 7 8 9 9
NEM FDM NEM FDM FDM FDM FDM FDM FDM NEM
2x2 2x2 4x4 4x4 4x4 8x8 10 x 10 12 x 12 14 x 14 2x2
19 19 19 19 38 19 19 19 19 19
4579 4579 18316 18316 9158 73264 114475 164844 224371 4579
10
NEM
2x2
19
4579
Convergence Criteriaa [ε1 =1e-6], [ε2, ε3 =1e-5], [ε4 =1e-4] [ε1 =1e-6], [ε2, ε3 =1e-5], [ε4 =1e-4] [ε1 =1e-6], [ε2, ε3 =1e-5], [ε4 =1e-4] [ε1 =1e-6], [ε2, ε3 =1e-5], [ε4 =1e-4] [ε1 =1e-6], [ε2, ε3 =1e-5], [ε4 =1e-4] [ε1 =1e-6], [ε2, ε3 =1e-5], [ε4 =1e-4] [ε1 =1e-6], [ε2, ε3 =1e-5], [ε4 =1e-4] [ε1 =1e-6], [ε2, ε3 =1e-5], [ε4 =1e-4] [ε1 =1e-6], [ε2, ε3 =1e-5], [ε4 =1e-4] [ε1 =1e-5], [ε2, ε3 =1e-4], [ε4 =1e-4] Same as Case 1, NEM update frequency = 3
ε1 = outer iteration criteria on eigenvalue ε2 = outer iteration criteria on L2 -norm of relative residual of outer iterative equation ε3 = out er iteration stopping criteria of the diffusion equation ε4 = inner iteration stopping criteria on L2 -norm of relative error reduction a
A
B
C
D
E
F
G
H
1
2
3
4
5
6
7
8
0.7264
1.2742
1.4156
1.1884
0.6097
0.9524
0.9607
0.7798
0.7264
1.2760
1.4169
1.1897
0.6094
0.9526
0.9601
0.7785
0.0000
-0.0018
-0.0013
-0.0013
0.0003
-0.0002
0.0006
0.0013
1.2742
1.3899
1.4248
1.2856
1.0685
1.0543
0.9768
0.7600
1.2760
1.3914
1.4261
1.2866
1.0693
1.0542
0.9761
0.7587
-0.0018
-0.0015
-0.0013
-0.0010
-0.0008
0.0001
0.0007
0.0013
1.4156
1.4248
1.3627
1.3065
1.1785
1.0888
1.0016
0.7152
1.4169
1.4261
1.3638
1.3074
1.1788
1.0886
1.0008
0.7136
-0.0013
-0.0013
-0.0011
-0.0009
-0.0003
0.0002
0.0008
0.0016
1.1884
1.2856
1.3065
1.1751
0.9702
0.9238
0.8698
1.1897
1.2866
1.3074
1.1757
0.9706
0.9235
0.8685
-0.0013
-0.0010
-0.0009
-0.0006
-0.0004
0.0003
0.0013
0.6097
1.0685
1.1785
0.9702
0.4766
0.7015
0.6150
0.6094
1.0693
1.1788
0.9706
0.4760
0.7013
0.6136
0.0003
-0.0008
-0.0003
-0.0004
0.0006
0.0002
0.0014
0.9524
1.0543
1.0888
0.9238
0.7015
0.6017
0.9526
1.0542
1.0886
0.9235
0.7013
0.6004
-0.0002
0.0001
0.0002
0.0003
0.0002
0.0013
0.9607
0.9768
1.0016
0.8698
0.6150
0.9601
0.9761
1.0008
0.8685
0.6136
0.0006
0.0007
0.0008
0.0013
0.0014
0.7798
0.7600
0.7152
Reference
0.7785
0.7587
0.7136
NESTLE - Case 1
0.0013
0.0013
0.0016
Difference
Figure 5. NESTLE-Case 1 Assembly Power Distribution. D i s t . ( c m ) R e f e r e n c e NESTLE Power
bottom
10 30 50 70 90 110 130 150 170 190 210 230 250 270 290 310 330
Case 1
IAEA 3D Axial Power Distribution
Power
0.350 0.600 0.859 1.087 1.276 1.420 1.514 1.553 1.538 1.469 1.348 1.181 0.975 0.743 0.538 0.353 0.195
0.3463 0.5973 0.8575 1.0862 1.2761 1.4206 1.5146 1.5548 1.5399 1.4706 1.3499 1.1827 0.9758 0.7440 0.5385 0.3519 0.1934
1.8 Relative Power Fraction
from
1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 0
100
200
300
Distance from bottom core (cm) Reference
NESTLE Case 1
Figure 6. NESTLE-Case 1 Axial Power Distribution
400
A
1
2
3
4
5
6
7
8
0.7264 0.7356
1.2742 1.4485
1.4156 1.5652
1.1884 1.3178
0.6097 0.5801
0.9524 0.9706
0.9607 0.9100
0.7798 0.6571
-0.0092
-0.1743
-0.1496
-0.1294
0.0296
-0.0182
0.0507
0.1227
B
1.2742 1.4485 -0.1743
1.3899 1.5604 -0.1705
1.4248 1.5743 -0.1495
1.2856 1.4045 -0.1189
1.0685 1.1406 -0.0721
1.0543 1.0618 -0.0075
0.9768 0.9210 0.0558
0.7600 0.6364 0.1236
C
1.4156 1.5652
1.4248 1.5743
1.3627 1.4798
1.3065 1.4030
1.1785 1.2226
1.0888 1.0755
1.0016 0.9419
0.7152 0.5457 0.1695
-0.1496
-0.1495
-0.1171
-0.0965
-0.0441
0.0133
0.0597
D
1.1884 1.3178 -0.1294
1.2856 1.4045 -0.1189
1.3065 1.4030 -0.0965
1.1751 1.2481 -0.0730
0.9702 1.0083 -0.0381
0.9238 0.8970 0.0268
0.8698 0.7382 0.1316
E
0.6097 0.5801
1.0685 1.1406
1.1785 1.2226
0.9702 1.0083
0.4766 0.4243
0.7015 0.6719
0.6150 0.4724 0.1426
0.0296
-0.0721
-0.0441
-0.0381
0.0523
0.0296
F
0.9524 0.9706 -0.0182
1.0543 1.0618 -0.0075
1.0888 1.0755 0.0133
0.9238 0.8970 0.0268
0.7015 0.6719 0.0296
0.6017 0.4716 0.1301
G
0.9607 0.9100
0.9768 0.9210
1.0016 0.9419
0.8698 0.7382
0.6150 0.4724
0.0507
0.0558
0.0597
0.1316
0.1426
0.7798 0.6571 0.1227
0.7600 0.6364 0.1236
0.7152 0.5457 0.1695
H
Reference NESTLE Difference
Figure 7. NESTLE-Case 2 Assembly Power Distribution. A
B
C
D
E
F
G
H
1
2
3
4
5
6
7
8
0.7264
1.2742
1.4156
1.1884
0.6097
0.9524
0.9607
0.7798
0.7313
1.2909
1.4305
1.2008
0.6098
0.9536
0.9556
0.7687
-0.0049
-0.0167
-0.0149
-0.0124
-0.0001
-0.0012
0.0051
0.0111
1.2742
1.3899
1.4248
1.2856
1.0685
1.0543
0.9768
0.7600
1.2909
1.4060
1.4400
1.2967
1.0751
1.0540
0.9710
0.7485
-0.0167
-0.0161
-0.0152
-0.0111
-0.0066
0.0003
0.0058
0.0115
1.4156
1.4248
1.3627
1.3065
1.1785
1.0888
1.0016
0.7152
1.4305
1.4400
1.3770
1.3164
1.1826
1.0869
0.9945
0.6993
-0.0149
-0.0152
-0.0143
-0.0099
-0.0041
0.0019
0.0071
0.0159
1.1884
1.2856
1.3065
1.1751
0.9702
0.9238
0.8698
1.2008
1.2967
1.3164
1.1817
0.9735
0.9203
0.8571
-0.0124
-0.0111
-0.0099
-0.0066
-0.0033
0.0035
0.0127
0.6097
1.0685
1.1785
0.9702
0.4766
0.7015
0.6150
0.6098
1.0751
1.1826
0.9735
0.4733
0.6974
0.6011
-0.0001
-0.0066
-0.0041
-0.0033
0.0033
0.0041
0.0139
0.9524
1.0543
1.0888
0.9238
0.7015
0.6017
0.9536
1.0540
1.0869
0.9203
0.6974
0.5886
-0.0012
0.0003
0.0019
0.0035
0.0041
0.0131
0.9607
0.9768
1.0016
0.8698
0.6150
0.9556
0.9710
0.9945
0.8571
0.6011
0.0051
0.0058
0.0071
0.0127
0.0139
0.7798
0.7600
0.7152
Reference
0.7687
0.7485
0.6993
NESTLE-Case 9
0.0111
0.0115
0.0159
Difference
Figure 8. NESTLE-Case 9 Assembly Power Distribution
Table 3. Summary of IAEA 3-D PWR Benchmark Keff difference (pcm)1
Case 1 2 3 4 5 6 7 8 9 10 11
-0. 6 3.5 0.0 -37.9 -45.4 -17.2 -12.1 -8.8 -7.0 -0.8 -0.6
RMS Assembly Power Diff. 2 0.0010 0.1003 0.0012 0.0610 0.0608 0.0238 0.0167 0.0125 0.0098 0.0011 0.0010
Maximum CPU Time Assembly Power (seconds)3 Diff. 0.0018 2.44 0.1743 0.70 0.0023 13.60 0.1041 4.83 0.1039 9.45 0.0404 26.73 0.0285 53.56 0.0213 90.52 0.0167 148.16 0.0020 1.78 0.0018 2.02
Notes: 1
keff difference (pcm) =
(k
reference eff
case )× 10 5 − k eff
∑ (P N
2
Root Mean Square power is defined as: RMS = 3
n =1
ref , n
− Pcase, n )2 N
CPU times were obtained using 2.66 GHz Pentium 4 PC
DISKUSI MUKHLIS 1. 2. 3.
Sejauh mana kesiapan kita dari Batan untuk menjawab tantangan yang diajukan oleh Dirjen PLN ke BATAN untuk PLTN? Reaktor jenis apa yang bisa dibangun di Indonesia ? Apakah bahan bakar yang digunakan sudah produk sendiri? Kalau tidak apa kelemahan dan kekurangannya?
IMELDA ARIANI 1.
2.
3.
Berhubung saya baru saja (beberapa bulan) berkecimpung di Batan, saya tidak ingin gegabah untuk menjawab pertanyaan yang mewakili Batan. Bapak Bakri Arbie dan Bapak Ferhat Aziz dapat membantu menjawab pertanyaan tersebut. Secar umum kesiapan membangun PLTN membutuhkan usaha yang sangat besar dan siap/tidaknya membangun PLTN terkadang bukan satu-satunya penentu jadi/tidaknya PLTN dibangun. Amerika Serikat misalnya yang telah puluhan tahun menikmati energi dari nuklir masih kesulitan mendapatkan “public acceptance” untuk membangun PLTN baru. Sebagai strategi pengganti AS memperpanjang izin operasi PLTN yang sudah ada sampai 2030-an. Sehingga opsi nuklir masih bertahan. Berdasarkan pengamatan reaktor berskala kecil bertenaga nuklir agak tidak menguntungkan dari segi ekonomi. Namun faktor-faktor yang lain harus juga dipertimbangkan. Geografi, kebutuhan, sumber yang lain, dll. akan mempengaruhi jenis reaktor nuklir yang dipilih. Jawabannya akan tergantung dari jenis reaktor apa yang nantinya dipilih.
BAKRI ARBIE 1. Analisis 3 problem, maksudnya apa saja? 2. Saya familiar dengan WIMS. Bagaimana approach Nestle Code untuk Lattice calculation group energy yang dipakai, auto-inner iteration approach? IMELDA ARIANI 1.
Sebenarnya tidak ada 3 masalah dalam presentasi ini. Tujuan pengembangan kode komputer kami adalah untuk membuat suatu PWR core simulator yang lebih akurat (dibanding kode komputer yang bisa digunakan di Batan sekarang
2.
ini) dan cepat, untuk nantinya dipakai sebagai alat optimasi pola penyusunan bahan bakar (loading pattern optimization) dan juga mungkin dicoupled dengan kode komputer thermal hidrolik sistem reaktor (misalnya RELAP) untuk analisa lainnya. Nestle code memerlukan latice data seperti kode komputer neutronik teras lainnya, yaitu dalam bentuk homogenized assembly cross section yang bergantung pada disain assembly (enrichment, penempatan burnable absorber, pola susun pin, dll.). Suhu bahan bakar, suhu pendingin dan densitas soluble absorber, batang kendali, dll. WIMS dapat digunakan untuk menghitung latice cross section data seperti di atas. Saya belum pernah menggunakan WIMS, namun berdasarkan literatur yang saya baca WIMS tampaknya agak kurang fleksible /praktis. Lattice code yang umum digunakan di Amerika Serikat adalah HELIOS dan CASMO yang memang sangat praktis dan bagus untuk Lattice calculation untuk PWR/BWR outer-inner iteration algorithm sudah ditampilkan di presentasi ini.
DAFTAR RIWAYAT HIDUP 1. Nama
: Imelda Ariani
2. Tempat/Tanggal Lahir
: Gombong, 27 November 1974
3. Instansi
: Pusat Pengembangan Sistem Reaktor Maju BATAN
4. Pekerjaan / Jabatan
:
5. Riwayat Pendidikan
:
• S1 North Carolina State University, USA • S2 North Carolina State University, USA 6. Pengalaman Kerja
:
• 2000-2003, Electric Power Research Center, Raleigh, North Carolina, USA • 2004-sekarang, P2SRM-BATAN 7. Organisasi Profesional
:
• American Nuclear Society • Sigma XI Research Society
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