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 sections1
D1 D2 ΣΣa1 ΣΣa2 νΣνΣf1 νΣνΣf2 ΣΣs12
Fuel 1 1.5 0.4 0.01 0.085 0.0 0.135 0.02
Fuel 1 + Rod 1.5 0.4 0.01 0.130 0.0 0.135 0.02
Fuel 2 1.5 0.4 0.01 0.080 0.0 0.135 0.02
Reflector 2.0 0.3 0.00 0.010 0.0 0.000 0.04
Reflector + Rod 2.0 0.3 0.00 0.055 0.0 0.000 0.04
1 Values taken from ANL-ID.11-A1 benchmark book
Figure 1. IAEA 3-D PWR radial quarter core loading pattern
Figure 2. IAEA 3-D PWR axial core configuration.
20 cm 380 cm
80 cm
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 : 500
Eigenvalue convergence : 1.e-6
Relative residual L2-norm : 1.e-5
Maximum relative residual : 5.e-4
Wielandt shift for initial iteration : 0.01 Wielandt shift for other iterations : 0.04 Nonlinear nodal update frequency : 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 : 3.285 seconds
Initialization time : 0.060 seconds
Coarse mesh finite difference time : 2.564 seconds
Nodal method time : 0.701 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.
Distance (cm) P o w e r 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
IAEA 3D Axial Power Distribution
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8
0 100 200 300 400
Distance from bottom core (cm)
Relative Power Fraction
1 2 3 4 5 6 7 8
A 0.7264 1.2742 1.4156 1.1884 0.6097 0.9524 0.9607 0.7798 B 1.2742 1.3899 1.4248 1.2856 1.0685 1.0543 0.9768 0.7600 C 1.4156 1.4248 1.3627 1.3065 1.1785 1.0888 1.0016 0.7152 D 1.1884 1.2856 1.3065 1.1751 0.9702 0.9238 0.8698
E 0.6097 1.0685 1.1785 0.9702 0.4766 0.7015 0.6150 F 0.9524 1.0543 1.0888 0.9238 0.7015 0.6017
G 0.9607 0.9768 1.0016 0.8698 0.6150 H 0.7798 0.7600 0.7152
Figure 3. Axial relative power distribution (reference).
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 non- linear 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 equation- based 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 Multi- Dimensional 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, Fixed- Source, and Transient Problem,” Idaho National Energy Laboratory (1994)
Table 2: NESTLE Benchmark Cases
Case Solution Method
#nodes per assembly
# axial nodes
Total # of nodes
Convergence Criteriaa
1 NEM 2 x 2 19 4579 [ε1=1e-6], [ε2,ε3=1e-5], [ε4=1e-4]
2 FDM 2 x 2 19 4579 [ε1=1e-6], [ε2,ε3=1e-5], [ε4=1e-4]
3 NEM 4 x 4 19 18316 [ε1=1e-6], [ε2,ε3=1e-5], [ε4=1e-4]
4 FDM 4 x 4 19 18316 [ε1=1e-6], [ε2,ε3=1e-5], [ε4=1e-4]
5 FDM 4 x 4 38 9158 [ε1=1e-6], [ε2,ε3=1e-5], [ε4=1e-4]
6 FDM 8 x 8 19 73264 [ε1=1e-6], [ε2,ε3=1e-5], [ε4=1e-4]
7 FDM 10 x 10 19 114475 [ε1=1e-6], [ε2,ε3=1e-5], [ε4=1e-4]
8 FDM 12 x 12 19 164844 [ε1=1e-6], [ε2,ε3=1e-5], [ε4=1e-4]
9 FDM 14 x 14 19 224371 [ε1=1e-6], [ε2,ε3=1e-5], [ε4=1e-4]
9 NEM 2 x 2 19 4579 [ε1=1e-5], [ε2,ε3=1e-4], [ε4=1e-4]
10 NEM 2 x 2 19 4579 Same as Case 1, NEM update frequency = 3
a 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
D i s t . ( c m ) R e f e r e n c e NESTLE f r o m P o w e r C a s e 1
b o t t o m P o w e r
10 0.350 0.3463 30 0.600 0.5973 50 0.859 0.8575 70 1.087 1.0862 90 1.276 1.2761 110 1.420 1.4206 130 1.514 1.5146 150 1.553 1.5548 170 1.538 1.5399 190 1.469 1.4706 210 1.348 1.3499 230 1.181 1.1827 250 0.975 0.9758 270 0.743 0.7440 290 0.538 0.5385 310 0.353 0.3519 330 0.195 0.1934
IAEA 3D Axial Power Distribution
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8
0 1 0 0 2 0 0 3 0 0 4 0 0
Distance from bottom core (cm)
Relative Power Fraction
Reference NESTLE Case 1
1 2 3 4 5 6 7 8
A 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
B 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
C 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
D 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
E 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
F 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
G 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
H 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.
Figure 6. NESTLE-Case 1 Axial Power Distribution
1 2 3 4 5 6 7 8 A 0.7264 1.2742 1.4156 1.1884 0.6097 0.9524 0.9607 0.7798 0.7356 1.4485 1.5652 1.3178 0.5801 0.9706 0.9100 0.6571 -0.0092 -0.1743 -0.1496 -0.1294 0.0296 -0.0182 0.0507 0.1227 B 1.2742 1.3899 1.4248 1.2856 1.0685 1.0543 0.9768 0.7600 1.4485 1.5604 1.5743 1.4045 1.1406 1.0618 0.9210 0.6364 -0.1743 -0.1705 -0.1495 -0.1189 -0.0721 -0.0075 0.0558 0.1236 C 1.4156 1.4248 1.3627 1.3065 1.1785 1.0888 1.0016 0.7152 1.5652 1.5743 1.4798 1.4030 1.2226 1.0755 0.9419 0.5457 -0.1496 -0.1495 -0.1171 -0.0965 -0.0441 0.0133 0.0597 0.1695 D 1.1884 1.2856 1.3065 1.1751 0.9702 0.9238 0.8698
1.3178 1.4045 1.4030 1.2481 1.0083 0.8970 0.7382 -0.1294 -0.1189 -0.0965 -0.0730 -0.0381 0.0268 0.1316 E 0.6097 1.0685 1.1785 0.9702 0.4766 0.7015 0.6150 0.5801 1.1406 1.2226 1.0083 0.4243 0.6719 0.4724 0.0296 -0.0721 -0.0441 -0.0381 0.0523 0.0296 0.1426 F 0.9524 1.0543 1.0888 0.9238 0.7015 0.6017
0.9706 1.0618 1.0755 0.8970 0.6719 0.4716 -0.0182 -0.0075 0.0133 0.0268 0.0296 0.1301 G 0.9607 0.9768 1.0016 0.8698 0.6150
0.9100 0.9210 0.9419 0.7382 0.4724 0.0507 0.0558 0.0597 0.1316 0.1426
H 0.7798 0.7600 0.7152 Reference
0.6571 0.6364 0.5457 NESTLE
0.1227 0.1236 0.1695 Difference
1 2 3 4 5 6 7 8
A 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
B 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
C 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
D 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
E 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
F 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
G 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
H 0.7798 0.7600 0.7152 Reference
0.7687 0.7485 0.6993 NESTLE-Case 9
0.0111 0.0115 0.0159 Difference
Figure 7. NESTLE-Case 2 Assembly Power Distribution.
Figure 8. NESTLE-Case 9 Assembly Power Distribution
Table 3. Summary of IAEA 3-D PWR Benchmark
Case Keff
difference (pcm)1
RMS Assembly Power Diff.2
Maximum Assembly Power Diff.
CPU Time (seconds)3
1 -0. 6 0.0010 0.0018 2.44
2 3.5 0.1003 0.1743 0.70
3 0.0 0.0012 0.0023 13.60
4 -37.9 0.0610 0.1041 4.83
5 -45.4 0.0608 0.1039 9.45
6 -17.2 0.0238 0.0404 26.73
7 -12.1 0.0167 0.0285 53.56
8 -8.8 0.0125 0.0213 90.52
9 -7.0 0.0098 0.0167 148.16
10 -0.8 0.0011 0.0020 1.78
11 -0.6 0.0010 0.0018 2.02
Notes:
1keff difference (pcm) =
( keffreference− k
effcase) × 105
2Root Mean Square power is defined as:
( )
N P P
N
n
n case n
∑
ref=
−
= 1
2 , ,
RMS
3CPU times were obtained using 2.66 GHz Pentium 4 PC
DISKUSI
MUKHLIS
1. Sejauh mana kesiapan kita dari Batan untuk menjawab tantangan yang diajukan oleh Dirjen PLN ke BATAN untuk PLTN?
2. Reaktor jenis apa yang bisa dibangun di Indonesia ?
3. Apakah bahan bakar yang digunakan sudah produk sendiri? Kalau tidak apa kelemahan dan kekurangannya?
IMELDA ARIANI
1. 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.
2. 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.
3. 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
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.
2. 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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