Neutronics performances of gas-cooled fast reactor for 300-600 MWt Output Power with Modified CANDLE burn-up scheme in radial direction

Gas-Cooled Fast Reactor-GFR is a Generation IV reactor that is helium-cooled and has a closed fuel cycle. Due to the target operation on 2022-2030, this reactor type still needs further research and development technologies. We investigated the neutronics performances of a GFR balance type core with some modification of CANDLE (Constant Axial shape of Neutron flux, nuclide densities and power shape During Life of Energy production) burn-up scheme in the radial direction. The output power varied from 300 to 600 MWt. The neutronics calculation was performed using SRAC 2002 with JENDL 4.0 nuclear data library. The analysis indicate the reactor could operate critically for ten years without refueling with burn-up level 20% HM.

Reconstructing the conductivity profile of a graphite block using inductance spectroscopy with data-driven techniques

The radial depth profile of the electrical conductivity of the graphite channels in the UK's advanced gas-cooled reactors (AGRs) can be reconstructed and estimated by solving a non-linear optimisation problem using the mutual inductance spectra of a set of coils. This process is slow, as it requires many iterations of a forward solver. Alternatively, a data-driven approach can be used to provide an initial estimate for the optimisation algorithm, reducing the amount of time it takes to solve the ill-posed inverse problem. Two data-driven approaches are compared: multi-variable polynomial regression (MVPR) and a convolutional neural network (CNN). The training data are generated using a finite element (FE) model and superimposed on a noise floor in the interval [20, 60] dB of the weakest amplitude point in the corresponding spectrum. A total of 5000 simulated datasets are generated for training. The results on smoothed test data show that the two models have a comparable mean percentage error norm of 17.8% for the convolutional neural network and 17.3% for multivariable polynomial regression. A further 500 unsmoothed profiles are tested in order to assess the performance of each algorithm on conductivity distributions where the conductivity of each layer is independent of another. The performance of both algorithms is then assessed on reactor-type test data. The results show that the two data-driven algorithms have a comparable performance when estimating the electrical conductivity depth profile of a typical reactor-type distribution, as well as vast deviations. More generally, it is thought that data-driven approaches for depth profiling of some electromagnetic quantity have the potential to be applied to other ill-posed inverse problems where speed is a priority.

Analytical Justifications As Part of the “Post-Fukushima” Upgrades Implementation on Zaporizhzhya NPP Unit 1

In accordance with a complex program to improve the safety of Ukrainian NPP units, a number of “Post-Fukushima” upgrades are being implemented. The upgrades were identified based on the results of “stress-tests” performed after the severe accident at the NPP Fukushima Daiichi (Japan) and aimed at preventing or managing a severe accident. As part of the implementation of upgrades for the possibility of installation and commissioning of new equipment, in accordance with regulatory documentation, is required confirmation that the upgrade will not lead to a degradation of the NPPs safety. For this purpose, the safety analysis report and analytical calculations, including thermal-hydraulic, probabilistic and radiation analysis, are developed. In this paper, on the example of “Post-Fukushima” upgrades, the practical experience of performing analytical calculations in order to justify the safety of Ukrainian NPP power units is described. As an example, Zaporizhzhya NPP Unit 1 (reactor facility type: VVER-1000/V320, reactor type: PWR VVER-1000, operational electric power: 1000 MW) was chosen, which is a pilot for the implementation of “Post-Fukushima” upgrades in Ukraine mainly. In this paper, on the example of “Post-Fukushima” upgrades, the practical experience of performing analytical calculations in order to justify the safety of pilot unit is described. Company ES Group and its employees took part in the implementation of most upgrades by supporting domestic and foreign companies, as well as the NPP operator, for the successful implementation of upgrades using the best technical solutions and modern calculation justifications.

Two-Dimensional Full Core Analysis of IFBA-Coated TRISO Fuel Particles in Very High Temperature Reactors

The Prismatic-core Advanced High Temperature Reactor (PAHTR) is a very high temperature reactor type which is one of promising reactor type technologies classified as Generation IV by the International Forum. The new technology designs are identified as being proliferation resistant, safe, economical, efficient, and long fuel cycle. In this paper, the continuous-energy Monte Carlo method is capable of capturing all of the necessary reactor physics parameters using high fidelity two dimensional model with Serpent Monte Carlo code, and applied for a large scale reactor core loaded with TRi-structural ISOtropic (TRISO) particle by taking into account the double heterogeneity effect. These analyses were performed for PAHTR reactor core that utilizes TRISO particles fuel embedded in graphite matrix by applying a new innovative idea of adding Integral Fuel Burnable Absorber (IFBA) as an additional coating layer with a designated thickness. Adding IFBA coating could lead to compressed excess reactivity at the Beginning of Cycle (BOC), and extended burnup cycle. The additional IFBA coating layer is placed in the outer surface of the fuel kernel and covered by the buffer layers that compose the TRISO fuel particle. Neutronic calculations were performed for both TRISO particle unit cell and for full core with homogenous distribution of IFBA coating.