Volume 90, Issue 6

We use Serpent 2 as a contemporary Monte Carlo tool to simulate the effective neutron multiplication factor k eff of the historic Haigerloch B8 nuclear reactor designed by Heisenberg and Wirtz in February to April 1945. The device parameters are either measured in the Haigerloch replica, taken from the historic reports or adapted from literature. We obtain k eff  = 0.952 which coincides with previously calculated results reported in the literature, but which is larger than the historically reported measured value of k eff  = 0.85. In addition, we tune the design parameters in order to reveal the most important device characteristics. We find an optimized reactor set-up that, under the condition to use as little uranium and heavy water as possible, is characterized by an increase of the vessel diameter by 35 % which would have brought the reactor to criticality with the available amount of uranium fuel. We show that the bottleneck would have been the lack of a sufficient amount of heavy water which would have been almost two-and-a-half times the then available quantity to reach criticality.

The performance of the nuclear reactor responding to any unexpected variation in reactivity is very important for reactor safety. Positive reactivity insertion causes power excursion and could have a destructive impact on the reactor core. Uranium silicide is considered to be well known accident tolerant fuel for the light water reactors due to their high metal density and high thermal conductivity. The aim of this study is to examine the thermal-hydraulic behavior of material testing reactor using U 3 Si 2 fuel during reactivity insertion accident. The analysis is done for MTR-22 MW reactor with the U 3 O 8 original fuel and the U 3 Si 2 fuel using PARET; a neutronics-hydrodynamics-heat transfer code. The calculated parameters are the reactor power and the temperatures of clad and fuel as a function of time for the hot channel. The calculations show that a direct replacement of U 3 O 8 by U 3 Si 2 will not have effect on the reactor safety. The results show that in both cases the fuel integrity is maintained during the accident demonstrating the inherent safety features of the MTR reactor. Moreover, the maximum fuel temperature for U 3 Si 2 during the accident is lower than that of U 3 O 8 due to its higher thermal conductivity confirmed that it will perform better in severe accidents.

The development of a 10 MW research reactor core using high-density U 3 Si 2 –Al plate fuel is presented, focusing on enhancing neutronic safety through optimized core configuration and control element design. This study employs MCNP and CITATION codes to evaluate neutronic parameters, including Power Peaking Factor (PPF) and Stuck Rod Shutdown Margin (SRSM). By incorporating four symmetrical irradiation boxes in the core center, the PPF is reduced by approximately 5 %, distributing neutron flux more uniformly. A novel control assembly design with a thin D 2 O layer increases control rod worth ensuring SRSM <−1,000 pcm without additional absorber material. Reactivity feedback analysis confirms safe operation with negative coefficients for fuel temperature and moderator conditions (−1.56 pcm/°C for D 2 O −20.11 pcm/°C for combined moderator temperature and density with D 2 O). This approach enhances safety margins and extends cycle length, offering a novel solution for high-density fuel research reactors.

Oxidation of zirconium cladding with high temperature steam releases additional heat and hydrogen which worsen the situations and may jeopardise safety barriers inside the reactor core. This article proposes coating zirconium clad with thin chromium layers or using low oxidation material such as silicon carbide (SiC). The normal UO 2 fuel is also replaced with a high density material such as uranium nitride (UN) or uranium carbide (UC). VVER-1200 core is modeled and the previous scenarios are applied. The results indicated that SiC clad achieves a higher 5 % K eff and cycle length than normal zirconium clad, while chromium coated zirconium reduces K eff and cycle length by 5 %. The new fuel types UN and UC increase the fuel cycle by 40 and 42 % respectively. UN and UC fuel have higher production of plutonium and Neptonium-237 than normal UO 2 case. Optimization of UN fuel performance was analyzed by studying the effect of ratio 14 N/ 15 N on the cycle length. Kinetic parameters and temperature coefficient of reactivity for fuel and moderator are calculated for fuel types under consideration. Neutron flux and power mapping are evaluated and investigated for all fuel types.

To enhance computational efficiency in estimating the posterior failure probability of passive systems, this study proposes an innovative framework integrating inverse uncertainty quantification (IUQ) with adaptive metamodel-based subset importance sampling (AM-SIS). This approach leverages updated input parameter distributions for precise posterior failure probability assessment. Within the IUQ framework, Bayesian neural networks is employed to assist established Markov Chain Monte Carlo methods for posterior sampling, significantly reducing computational costs. The coupled IUQ-AM-SIS framework is validated on polynomial benchmark cases and the equal height difference passive containment cooling system (EHDPCCS), examining scenarios with single and double calibration parameters. Results demonstrate that integrating the AM-SIS method significantly improves computational efficiency for posterior failure probability estimation, particularly in low failure probability regimes.

A three-tube intertwined heat exchanger design featuring simplicity, robustness, and efficient heat-transfer properties. The design is derived from the twined tube heat exchanger design with the addition of a third tube in the shell section. To meet the required heat load, multiple modules can be configured within a shell area. An experimentally validated twined tube heat exchanger computational fluid dynamics model is utilized to perform the thermal-hydraulic analysis on the full-scale numerical simulation for single-phase forced convection. The thermal-hydraulic performance parameters of the three-tube intertwined heat exchanger are evaluated for mass fluxes varying from 163 kg/m 2  s to 279 kg/m 2  s. The results are compared with those of the straight tube and twined tube heat exchanger configurations. The three-tube intertwined heat exchanger demonstrates a 55 % higher performance factor than the straight tube heat exchanger and 16 % higher than the twined tube heat exchanger. The three-tube intertwined heat exchanger exhibits a performance factor of 2.49, higher than the straight tube and twined tube heat exchangers. Moreover, without compromising the performance, this design facilitates enhanced heat duty for the same geometrical and process parameters as the twined tube heat exchanger. The design could be deployed in the advanced nuclear reactors.

Neural networks (NNs) and deep learning have revolutionized several fields, and nuclear safety analysis is no exception. The proper operation of nuclear reactor safety systems is crucial and is designed to meet strict safety requirements. Such systems are expected to withstand certain postulated accidents known as design basis accidents (DBAs), which include the loss of coolant accident (LOCA). As the LOCA involves complex fluid mechanics and heat transfer, the pattern recognition abilities of NNs allow for excellent prediction capabilities and the bypassing of otherwise tedious conventional analysis methods. This work investigates the deep learning techniques through long short-term memory (LSTM) architecture, for its ability to deal with time-series problems which include LOCAs. The utilized model is taught to estimate the size of pipe breaks within the cooling system based off of the corresponding pressure drops. A range of 0.5 %–100 % break-size-time-variant parameters were collected using the WSC Inc. 1,400 MWe generic pressurized water reactor (GPWR) simulator, using two circulation loops. Neural networks were trained on parameters such as loop temperature, pressure, containment pressure and Boron concentration. The performance of the LSTM model showed a mean absolute error (MAE) of 5.185, mean squared error (MSE) of 76.50, root mean squared error (RMSE) of 7.953, R 2 of 0.888 and Accuracy of 80.684 % within a tolerance of 15 % across 100 runs.

According to the characteristics of multi-variable control object in small modular reactors control system, a design method of control system is presented in this paper. Firstly, the nonlinear differential equations of the system are constructed according to the principle of mechanism modeling, and then the transfer function of the system is obtained by linearization. Then, the coupling characteristics of the system are analyzed by using Gershgorin Circle Theorem in modern frequency domain analysis method. On this basis, the inverse Nyquist array method is used to decouple the two key channels of reaction-exit temperature channel and feed-water valve-steam pressure in small modular reactors. Then the PI correction network is designed by frequency response method. In order to fully verify the performance of the decoupling controller, the system is verified based on linear model and nonlinear model respectively, and the pre-compensation matrix processing strategy under variable load conditions is proposed. Simulation results show that this method can significantly reduce the coupling degree between the two channels, and the performance of the control system after decoupling is significantly improved compared with that before decoupling.

Se is one of the radionuclides focused on in the safety evaluation of deep geological disposal repositories for high-level wastes, and elements with different valence states have different chemical properties and adsorption behaviors, which directly affects their adsorption efficiency and mechanism on bentonite. This study investigated the adsorption behavior of selenium in different valence states (Se(IV) and Se(VI)) on sodium bentonite through batch static adsorption experiments to assess its potential application in deep geological disposal repositories. The results indicate that the adsorption distribution coefficients ( K d ) of Se(IV) and Se(VI) on sodium-based bentonite decrease first, then increase, and finally decrease again with increasing pH. However, the adsorption of Se(IV) is less affected by ionic strength, while the adsorption of Se(VI) decreases with increasing ionic strength, temperature, and initial concentration. The adsorption of Se(IV) is an entropy-increasing, non-spontaneous, and endothermic chemical process influenced by environmental pH, which can be described by the Langmuir isotherm model and the pseudo-second-order kinetic model; the adsorption of Se(VI) is a pH-dependent, entropy-decreasing, spontaneous, and exothermic physical process, which can be described by the Langmuir isotherm model and the pseudo-first-order kinetic model. Both exhibit weak competitive adsorption on sodium-based bentonite, and the electrostatic repulsive forces between the negatively charged Se species and the sodium-based bentonite surface inhibit adsorption. FTIR and XRD spectral analyses show no significant changes in functional group characteristics before and after adsorption. The research results are of great significance for understanding the behavior of nuclides during geological migration.