Wyniki wyszukiwania - Biblioteka Nauki

1

Analysis of the BEAVRS PWR benchmark using SCALE and PARCS

100%

Darnowski P. , Pawluczyk M.

Nukleonika

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2019

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tom Vol. 64, No. 3

87--96

EN

This paper presents an analysis of the Benchmark for Evaluation And Validation of Reactor Simulations (BEAVRS) performed using SCALE 6.1.2 and PARCS 3.2 computer codes. The benchmark specifi cation contains a detailed design, operational data and measurements for a real 4-loop Westinghouse pressurized water reactor (PWR). The lattice physics simulations were prepared using TRITON depletion sequence and NEWT neutron transport solver (SCALE package). The 238-neutron group library based on evaluated nuclear data fi le – ENDF/B-VII nuclear data libraries was applied. A set of branch and burnup calculations was prepared, and group constants in the form of PMAXS fi les were generated with GenPMAXS. The full-core models were prepared using the PARCS nodal-diffusion core simulator. The PMAXS libraries were used with PARCS to investigate the core operation. The hot zero power measurement data, including control rod worths and critical boron concentrations, were compared using simulations, and satisfactory results were achieved. The fi rst fuel cycle was simulated, and acceptable agreement with boron letdown curve and measurements were obtained. Finally, conclusions and recommendations for future research were presented.

2

Application of genetic algorithms in optimization of SFR nuclear reactor design

80%

Żurkowski W. , Sawicki P. , Kubiński W. , Darnowski P.

Nukleonika

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2021

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tom Vol. 66, No. 4

139--145

EN

This work presents a demonstrational application of genetic algorithms (GAs) to solve sample optimization problems in the generation IV nuclear reactor core design. The new software was developed implementing novel GAs, and it was applied to show their capabilities by presenting an example solution of two selected problems to check whether GAs can be used successfully in reactor engineering as an optimization tool. The 3600 MWth oxide core, which was based on the OECD/NEA sodium-cooled fast reactor (SFR) benchmark, was used a reference design [1]. The first problem was the optimization of the fuel isotopic inventory in terms of minimizing the volume share of long-lived actinides, while maximizing the effective neutron multiplication factor. The second task was the optimization of the boron shield distribution around the reactor core to minimize the sodium void reactivity effect (SVRE). Neutron transport and fuel depletion simulations were performed using Monte Carlo neutron transport code SERPENT2. The simulation resulted in an optimized fuel mixture composition for the selected parameters, which demonstrates the functionality of the algorithm. The results show the efficiency and universality of GAs in multidimensional optimization problems in nuclear engineering.

3

Relation between thermal conductivity and coordination number for fibre-reinforced composite with random distribution of fibres

80%

Darnowski P. , Furmański P. , Domański R.

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tom Vol. 40, no 1

21--48

EN

Transverse effective thermal conductivity of the random unidirectional fibre-reinforced composite was studied. The geometry was circular with random patterns formed using random sequential addition method. Composite geometries for different volume fraction and fibre radii were generated and their effective thermal conductivities (ETC) were calculated. Influence of fibre-matrix conductivity ratio on composite ETC was investigated for high and low values. Patterns were described by a set of coordination numbers (CN) and correlations between ETC and CN were constructed. The correlations were compared with available formulae presented in literature. Additionally, symmetry of the conductivity tensor for the studied geometries of fibres was analysed.

4

Optimization of the loading pattern of the PWR core using genetic algorithms and multi-purpose fitness function

80%

Kubiński W. , Darnowski P. , Chęć K.

Nukleonika

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2021

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tom Vol. 66, No. 4

147--151

EN

The study demonstrates an application of genetic algorithms (GAs) in the optimization of the first core loading pattern. The Massachusetts Institute of Technology (MIT) BEAVRS pressurized water reactor (PWR) model was applied with PARCS nodal-diffusion core simulator coupled with GA numerical tool to perform pattern selection. In principle, GAs have been successfully used in many nuclear engineering problems such as core geometry optimization and fuel confi guration. In many cases, however, these analyses focused on optimizing only a single parameter, such as the effective neutron multiplication factor (keff), and often limited to the simplified core model. On the contrary, the GAs developed in this work are equipped with multiple-purpose fitness function (FF) and allow the optimization of more than one parameter at the same time, and these were applied to a realistic full-core problem. The main parameters of interest in this study were the total power peaking factor (PPF) and the length of the fuel cycle. The basic purpose of this study was to improve the economics by finding longer fuel cycle with more uniform power/flux distribution. Proper FFs were developed, tested, and implemented and their results were compared with the reference BEAVRS first fuel cycle. In the two analysed test scenarios, it was possible to extend the fi rst fuel cycle while maintaining lower or similar PPF, in comparison with the BEAVRS core, but for the price of increased initial reactivity.