Calculation of the Neutron Parameters for Accelerator-Driven Subcritical Reactors

In this paper, the accelerator-driven subcritical reactor (ADSR) is simulated based on structure of the TRIGA-Mark II reactor. A proton beam is accelerated and interacts on the lead target. Two cases of using lead are considered here: firstly, solid lead is referred to as spallation neutron target and water as the coolant; secondly, molten lead is considered both as a target and as a coolant. The proton beam in the energy range from 115 MeV to 2000 MeV interacts with the lead to create neutrons. The neutron parameters as neutron yield Yn/p, neutron multiplication factor k, the radial and axial distributions of the neutron flux in the core have been calculated by using MCNPX program. The results show that the neutron yield increases as the energies of the proton beam increases. When using the lead target, the differences between the neutron yield are from 4.2% to 14.2% depending on the energies of the proton beam. The proportion of uranium in the mixtures should be around 24% to produce an effective neutron multiplier factor greater than 0.9. The neutron fluxes are much higher than the same calculations for the TRIGA-Mark II reactor model using tungsten target and light water coolant.

Numerical modelling of modular high-temperature gas-cooled reactors with thorium fuel

The volumetric homogenization method for the simplified modelling of modular high-temperature gas-cooled reactor core with thorium-uranium fuel is presented in the paper. The method significantly reduces the complexity of the 3D numerical model. Hence, the computation time associated with the time-consuming Monte Carlo modelling of neutron transport is considerably reduced. Example results comprise the time evolutions of the effective neutron multiplication factor and fissionable isotopes (233U, 235U, 239Pu, 241Pu) for a few configurations of the initial reactor core.

Application of genetic algorithms in optimization of SFR nuclear reactor design

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.

Analyzing the Neutron Parameters in the Accelerator Driven Subcritical Reactor Using the Mixture of Molten Pb-Bi as Both Target and Coolant

In this paper, the Accelerator Driven Subcritical Reactor (ADSR) was simulated based on the structure of the TRIGA-Mark II reactor by the MCNPX program. The proton beam interacts on the Pb-Bi molten target with various energy levels from 0.5 GeV to 2.0 GeV. The important neutron parameters to evaluate the operability of ADSR were calculated as: the neutron yields according to various thicknesses of the target and according to the energy of the incident proton beam; the effective neutron multiplication factor for various fuel mixtures, along with its stability for some fuel mixtures; the axial and radial distributions of the neutron flux along with the height and radius of the core. The obtained results had shown a good agreement in using Pb-Bi molten as the interaction target and coolant for ADSR.

Optimisation of used nuclear fuel canister loading using a neural network and genetic algorithm

This paper presents an approach for the optimisation of geological disposal canister loadings, combining high resolution simulations of used nuclear fuel characteristics with an articial neural network and a genetic algorithm. The used nuclear fuels (produced in an open fuel cycle without reprocessing) considered in this work come from a Swiss Pressurised Water Reactor, taking into account their realistic lifetime in the reactor core and cooling periods, up to their disposal in the final geological repository. The case of 212 representative used nuclear fuel assemblies is analysed, assuming a loading of 4 fuel assemblies per canister, and optimizing two safety parameters: the fuel decay heat (DH) and the canister effective neutron multiplication factor k$$_{\mathrm{eff}}$$ eff . In the present approach, a neural network is trained as a surrogate model to evaluate the k$$_{\mathrm{eff}}$$ eff value to substitute the time-consuming-code Monte Carlo transport & depletion SERPENT for specific canister loading calculations. A genetic algorithm is then developed to optimise simultaneously the canister k$$_{\mathrm{eff}}$$ eff and DH values. The k$$_{\mathrm{eff}}$$ eff computed during the optimisation algorithm is using the previously developed artificial neural network. The optimisation algorithm allows (1) to minimize the number of canisters, given assumed limits for both DH and k$$_{\mathrm{eff}}$$ eff quantities and (2) to minimize DH and k$$_{\mathrm{eff}}$$ eff differences among canisters. This study represents a proof-of-principle of the neural network and genetic algorithm capabilities, and will be applied in the future to a larger number of cases.

Serpent and MCB Comparison for Neutronics Calculations of the European Lead-Cooled Fast Reactor

As part of the GENIV systems, the European Lead-cooled Fast Reactor (ELFR) is one of the most promising candidates to be part of the European energy framework in the near future. Alike most of the GENIV systems, the ELFR is still under development and having reliable computational tools, that allow fast and accurate results, becomes in an important task in the modelling and simulation levels. In this work, the Serpent code, which is a continuous Monte Carlo code suitable for reactor physic calculations, is used for the modelling of the ELFR system. The results were compared with the reference data which were obtained with the MCB Monte Carlo code. In order to verify the ELFR Serpent model, several neutronic parameters were compared with the reference: the effective neutron multiplication factor (keff), the Doppler constant, the reactivity effect of the coolant density, the effective delayed neutron fraction and the effective prompt neutron lifetime. In addition, the axial and radial power distributions were also obtained and verified, and a good approximation between Serpent and MCB values was obtained.

The Study of the 22Ne(α,γ)26Mg Reaction at LUNA

The 22Ne(α,γ)26Mg reaction is the competitor of the 22Ne(α,γ)25Mg reaction, an effective neutron source for element synthesis through s-process in massive and AGB stars. Currently the ratio between the rates of these two reactions is poorly constrained because of the high uncertainty affecting the 22Ne(α,γ)26Mg reaction rate. Indeed a wide range of values for the 395 keV resonance strength (10−15 - 10−9 eV) is reported in literature, all of them from indirect measurements. The present study represents the first direct measurement which was performed at the ultra-low background LUNA laboratory. An high efficiency detector was installed at the gas target beamline of LUNA 400kV accelerator and the 99% enriched in 22Ne neon gas was irradiated with a 399.9 keV α-beam. No significant signal was detected in the 22Ne(α,γ)26Mg region of interest, thus an upper limit for the 395 keV resonance strength was estimated. A new campaign was completed in August 2019 with an improved setup and some details are reported here.

Development of SiO2 based doped with LiF, Cr2O3, CoO4 and B2O3 glasses for gamma and fast neutron shielding

In this study, the fast neutron and gamma-ray absorption capacities of the new glasses have been investigated, which are obtained by doping CoO,CdWO4,Bi2O3, Cr2O3, ZnO, LiF,B2O3 and PbO compounds to SiO2 based glasses. GEANT4 and FLUKA Monte Carlo simulation codes have been used in the planning of the samples. The glasses were produced using a well-known melt-quenching technique. The effective neutron removal cross-sections, mean free paths, half-value layer, and transmission numbers of the fabricated glasses have been calculated through both GEANT4 and FLUKA Monte Carlo simulation codes. Experimental neutron absorbed dose measurements have been carried out. It was found that GS4 glass has the best neutron protection capacity among the produced glasses. In addition to neutron shielding properties, the gamma-ray attenuation capacities, were calculated using newly developed Phy-X/PSD software. The gamma-ray shielding properties of GS1 and GS2 are found to be equivalent to Pb-based glass.

Experimental methods for determining the effective neutron multiplication factor of the “Yalina-Thermal” subcritical assembly

To study the kinetics of subcritical systems and determine the optimal conditions for the transmutation of longlived radioactive waste in the neutron spectrum of ADS-systems the “Yalina” research nuclear facility was created at Joint Institute for Power and Nuclear Research – Sosny (Minsk, Belarus). The main safety indicator of a subcritical system (active zone reactivity) was measured for a “Yalina-Thermal” assembly via three independent methods: inverse multiplication, probabilistic and impulse ones. For the inverse multiplication method, the neutron flux density was monitored during assembly loading. For a fuel load of 285 EK-10 rods the neutron multiplication was M = 22.3±0.6, and the effective neutron multiplication coefficient was keff = 0.9551± 0.0016. The probabilistic method (Feynman-alpha method), based on measuring fluctuations in the neutron density level within a system with a fission chain reaction, gave the ratio of the variance to the average counting rate value D/n = 1.779±0.005, which corresponds to keff = 0.9597 ±0.0003. The pulse method is aimed at studying the neutron flux behavior of after the neutron pulse injection into the breeding system. Measurements were held with the same setup, used in the Feynman-alpha method. The measured decay constant of instantaneous neutrons is α = –670±0.7 1/s, which corresponds to keff = 0.9560±0.0001. The effective multiplication factor keff of the subcritical assembly “Yalina-Thermal”, obtained via three different independent methods, is around average value of keff = 0.9569 ± 0.0018. The methods considered can be used for subcritical level monitoring for ADS-systems and research nuclear facilities.