An Interval Bound Algorithm of optimizing reactor core loading pattern by using reactivity interval schema

In order to research the performance of Pressurized Water Reactor (PWR) with 1/3 MOX fuel in the initial cycle, this paper serves Qinshan II reactor core as the reference core to design suitable MOX assemblies and study relevant core properties. The analyses documented within use assembly cross section calculation code CASMO-4 and core calculation code SIMULATE-3 studied by Studsvik. The purpose of this paper is to demonstrate that the Qinshan II reactor is capable of complying with the requirement for MOX fuel utilization without significant changes to the design of the plant. Several impacts on key physics parameters and safety analysis assumptions, introduced by MOX, are discussing in the paper.

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Application of Evolutionary Simulated Annealing Method to Design a Small 200 MWt Reactor Core

Nuclear Science and Technology ◽

10.53747/jnst.v10i4.11 ◽

2021 ◽

Vol 10 (4) ◽

pp. 16-23

Author(s):

Tran Viet Phu ◽

Tran Hoai Nam ◽

Hoang Van Khanh

Keyword(s):

Simulated Annealing ◽

Power Plant ◽

Nuclear Power ◽

Cycle Length ◽

Reactor Core ◽

Loading Pattern ◽

The Core ◽

Fuel Assemblies ◽

Full Power ◽

Annealing Method

This paper presents the application of an evolutionary simulated annealing (ESA) method to design a small 200 MWt reactor core. The core design is based on a reference ACPR50 reactor deployed in a floating nuclear power plant. The core consists of 37 typical 17x17 PWR fuel assemblies with three different U-235 enrichments of 4.45, 3.40 and 2.35 wt%. Core loading pattern (LP) has been optimized for obtaining the cycle length of 900 effective full power days, while minimizing the average U-235 enrichment and the radial power peaking factor. The optimization process was performed by coupling the ESA method with the COREBN module of the SRAC2006 system code.

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Machine Learning of the Reactor Core Loading Pattern Critical Parameters

Science and Technology of Nuclear Installations ◽

10.1155/2008/695153 ◽

2008 ◽

Vol 2008 ◽

pp. 1-6

Author(s):

Krešimir Trontl ◽

Dubravko Pevec ◽

Tomislav Šmuc

Keyword(s):

Machine Learning ◽

Nonlinear Modeling ◽

Reactor Core ◽

Computer Code ◽

Critical Parameters ◽

Support Vector ◽

Model Parameters ◽

Quadratic Optimization Problem ◽

Loading Pattern ◽

Pattern Modeling

The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm, and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper, we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employ a recently introduced machine learning technique, support vector regression (SVR), which is a data driven, kernel based, nonlinear modeling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem. The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modeling. We illustrate the performance of the solution and discuss its applicability, that is, complexity, speed, and accuracy.

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Multiobjective Core Reloading Pattern Optimization of PARR-1 Using Modified Genetic Algorithm Coupled with Monte Carlo Methods

Science and Technology of Nuclear Installations ◽

10.1155/2021/1802492 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Nadeem Shaukat ◽

Ammar Ahmad ◽

Bukhtiar Mohsin ◽

Rustam Khan ◽

Salah Ud-Din Khan ◽

...

Keyword(s):

Monte Carlo ◽

Nuclear Reactor ◽

Computational Cost ◽

Reactor Core ◽

Reactor Physics ◽

Irradiation Site ◽

Loading Pattern ◽

Intelligent Technique ◽

Safety Constraints ◽

The Given

In order to maximize both the life cycle and efficiency of a reactor core, it is essential to find the optimum loading pattern. In the case of research reactors, a loading pattern can also be optimized for flux at an irradiation site. Therefore, the development of a general-use methodology for core loading optimization would be very valuable. In this paper, general-use multiobjective core reloading pattern optimization is performed using modified genetic algorithms (MGA). The developed strategy can be applied for the constrained optimization of research and power reactor cores. For an optimal reactor core reloading design strategy, an intelligent technique GA is coupled with the Monte Carlo (MC) code SuperMC developed by the FDS team in China for nuclear reactor physics calculations. An optimal loading pattern can be depicted as a configuration that has the maximum keff and maximum thermal fluxes in the core of the given fuel inventory keeping in view the safety constraints such as limitation on power peaking factor. The optimized loading patterns for Pakistan Research Reactor-1 (PARR-1) have been recommended using the implemented strategy by considering the constraint optimization, i.e., to maximize the keff or maximum thermal neutron flux while maintaining low power peaking factor. It has been observed that the developed intelligent strategy performs these tasks with a reasonable computational cost.

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Fuel Loading Pattern Optimization with Constraint on Fuel Assembly Inventory Using Quantum-Inspired Evolutionary Algorithm

E3S Web of Conferences ◽

10.1051/e3sconf/20184201007 ◽

2018 ◽

Vol 42 ◽

pp. 01007 ◽

Cited By ~ 1

Author(s):

M. Rizki Oktavian ◽

Alexander Agung ◽

Andang Widi Harto

Keyword(s):

Fuel Assembly ◽

Evolutionary Algorithm ◽

Cycle Length ◽

Reactor Core ◽

Combinatorial Problem ◽

Weight Factor ◽

Fuel Loading ◽

Loading Pattern ◽

Fitness Value ◽

Fuel Assemblies

Nuclear fuel management was done by optimizing fuel loading pattern in a reactor core. Practically, performing fuel loading pattern optimization was difficult because of its combinatorial problem complexity which needed to be solved. Therefore, Quantum-inspired Evolutionary Algorithm (QEA) which could solve the combinatorial problem faster than conventional method was used. The main purpose of this research was to obtain an optimum fuel loading pattern of KSNP-1000 reactor core without altering fuel assembly inventories. KSNP-1000 core was modeled in SRAC code package using PIJ module for fuel pins and fuel assemblies’ lattices and CITATION module for fuel assemblies’ pattern in a quarter core symmetry. Optimization problem adaptation using QEA was made by presenting 52 fuel assemblies in Q-bit individuals with the length of 8 Q-bits. Q-bits were converted to corresponding bit values and then given weight which would be used as consideration to optimize the pattern. The optimization program was coupled with the SRAC neutronic code to obtain the values of effective multiplication factor (keff) and power peaking factor (PPF). The optimization was calculated based on fitness value which was a function of keff and PPF values with the particular weight factor. Using a rotation gate angle of Δθ=0.02π and a weight factor of w=0,041, fuel loading pattern optimization was done on 360 days burnup level. The optimization resulted in keff and PPF value of 1.11233 and 1.944 respectively. By calculating keff value on various burnup levels for the chosen core loading pattern, reactor cycle length obtained was 659 days with PPF at BOC was 2.19. Compared to the standard KSNP-1000 core which had 560 days of cycle length, the optimized core configuration increased 17.67% in cycle length.

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Conceptual Design of CANDU-SCWR With Thermal-Hydraulics Coupling

18th International Conference on Nuclear Engineering: Volume 2 ◽

10.1115/icone18-29373 ◽

2010 ◽

Cited By ~ 1

Author(s):

Ping Yang ◽

Liangzhi Cao ◽

Hongchun Wu ◽

Changhui Wang

Keyword(s):

Power Distribution ◽

Average Power ◽

Reactor Core ◽

Coolant Temperature ◽

Loading Pattern ◽

Burnable Poison ◽

Management Scheme ◽

Fuel Bundle ◽

Hydraulic Coupling ◽

Operation Pressure

A CANDU-SCWR core is designed by using a 3D neutronics/thermal-hydraulic coupling method. In the fuel channel design, a typical 43-element fuel bundle is used, the coolant and the moderator are supercritical water and heavy water respectively. The thickness of the moderator is optimized to ensure the negative coolant coefficient during operation. With 1220 MW electric power, the reactor core is designed with a diameter of 4.8m and length of 4.95m, and there are totally 300 fuel channels, each of which consists of 10 fuel bundles. The inlet coolant temperature is set to be 350 °C °C and the operation pressure is 25 MPa. In order to flatten the radial power distribution, the loading pattern of the equilibrium cycle is optimized, and an optimized fuel management scheme is used with three batches refueling, burnable poison Dy2O3 is used to flatten the power peaking. The numerical results show that the average power density is 42.75 W/cm3, while the maximum linear element rate (LER) is 575W/cm. The average discharged burnup of the equilibrium is 48.3GWD/tU, and a high average outlet coolant temperature of 625 °C is achieved with a maximum cladding surface temperature less than 850 °C. Besides, the coolant temperature coefficient is negative throughout the cycle.

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Point Defect Absorption and Dislocation Loop Formation at Grain Boundaries in Hvem-Irradiated Zr and Its Alloys:1. Influence of Solute Addition

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s042482010011862x ◽

1985 ◽

Vol 43 ◽

pp. 350-351

Author(s):

R.A. Herring ◽

M. Griffiths ◽

M.H Loretto ◽

R.E. Smallman

Keyword(s):

Grain Boundary ◽

Grain Boundaries ◽

Point Defect ◽

Reactor Core ◽

Solute Concentration ◽

Nuclear Industry ◽

Dislocation Loops ◽

Loop Formation ◽

Component Material ◽

Impurity Interaction

Because Zr is used in the nuclear industry to sheath fuel and as structural component material within the reactor core, it is important to understand Zr's point defect properties. In the present work point defect-impurity interaction has been assessed by measuring the influence of grain boundaries on the width of the zone denuded of dislocation loops in a series of irradiated Zr alloys. Electropolished Zr and its alloys have been irradiated using an AEI EM7 HVEM at 1 MeV, ∼675 K and ∼10-6 torr vacuum pressure. During some HVEM irradiations it has been seen that there is a difference in the loop nucleation and growth behaviour adjacent to the grain boundary as compared with the mid-grain region. The width of the region influenced by the presence of the grain boundary should be a function of the irradiation temperature, dose rate, solute concentration and crystallographic orientation.

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