Band 87, Heft 3

CPR1000 severe accident management guideline (SAMG) is a product of the Westinghouse Owners Group (WOG) SAMG and the French SAMG (called GIAG) combination. It adopts the structure of WOG SAMG. However, it follows the approach of GIAG performing reactor coolant system (RCS) depressurization immediately after entering SAMG. This is a special feature of CPR1000 SAMG. The purpose of this paper is to evaluate this RCS depressurization strategy. The simulations of a station blackout (SBO) accident are performed for CPR1000 with RCS depressurization strategy adopted at both core exit temperature (CET) of 650 and 1100 °C together with opening different number of safety relief valves (SRV) using an integral severe accident analysis code. The optimized RCS depressurization strategy is provided to delay the reactor pressure vessel (RPV) failure time. And some comments are provided for future improvement.

During a nuclear or radiological emergency, timely implementation of precautionary urgent protective actions, urgent protective actions, early protective actions, and other response actions is inevitable for the protection of the public and the emergency workers. unmanned aerial vehicles commonly known as drones have numerous applications including their use in disaster management for support in early warning, provision of medical aid, monitoring, situational awareness, taking various protective and response actions, and post-accident assessment. In the current study, in comparison to drone applications in response to other disasters, their potential use in response to a nuclear or radiological emergency has been discussed. The drones use in mapping radiation and contamination levels in Fukushima nuclear power plant accidents have already proved their applications in a nuclear or radiological emergency. It is concluded that drones inherently complement the existing disaster management arrangements and have the potential for their use in strengthening arrangements for taking protective and response actions in case of a nuclear or radiological emergency.

It is investigated for the seismic consequences in the nuclear power plant (NPP) where the radiological hazard could be one of critical issues when the safety system is in failure. The artificial learning is done during the calculations of each time step. There are the simulations for the artificial neural networking (ANN) as the precision, sensitivity (recall value), specificity, and accuracy which are 21.48%, 50.53%, 25.47%, and 32.68% respectively. Likewise, the recurrent neural network (RNN) modeling has 23.64%, 54.53%, 25.56%, and 34.17% respectively. In the comparisons for ANN and RNN, the values of ANN’s parameters are lower than those of RNN in all values of precision, recall, specificity, and accuracy. As the designed factors for the nuclear matters increase, the estimations could be better in considering the conditional situations.

The reactor pressure vessel was contact sealed with a double-channel O-ring made of Inconel 718 alloy and nuclear power material SA508. The fretting wear characteristics of Inconel 718 O-tube and SA508 plate friction pair were tested by fretting wear testing machine to explore the failure mechanism of reactor pressure vessel seal system. The test conditions are as follows: normal temperature, normal loads of 10, 20, and 40 N, displacement amplitude of 600 μm, the number of cycles of 10,000, and frequency of 4 Hz. Results show that the coefficient of friction (COF) increased with increasing normal force. Significant material losses were detected during the relative sliding of the contact surface of SA508. A large number of abrasive dust accumulated at the edge of the contact zone, forming a large number of oxides. During the friction of Inconel 718 O-ring, plastic deformation occurred, and a plastic flow layer was formed. The plastic deformation flow at the contact point formed an adhesive connection point, producing adhesive wear and oxidative wear. The wear mechanism was characterized by the combination of oxidative wear and abrasive wear.

The fissile mass deduced from fast neutron multiplicity counting (FNMC) measurement is underestimated if the matrix self-absorption effect of the radioactive source is not taken into account. Based on the analysis of FNMC equations, a set of FNMC system was built to simulate and study the mass attribute of the hollow sphere (spherical shell) plutonium under different shapes and different masses conditions. Geant4 simulation shows that an appropriate parameter correction successfully removes the bias because of the matrix effect. Consequently, the self-multiplication factor, α coefficient and scattering crosstalk of the simulation result were corrected after analyzing the detection efficiency and multiplicity counting rate, and the corresponding polynomial fitting equation was obtained. The corrected mass deviation of samples was less than ±1% in this interval. The results show that the combination of the FNMC and parameter correction can accurately measure the sample mass attribute, which provides a new method for solving similar problems.

Investigating the dependence of reactor core neutronic parameters on the accelerator related parameters such as source multiplication coefficient ( K s ), beam profile and electron beam energy ( E e ), have a significant impact on the design of future ADS reactors and the cost of their construction. Using the MCNPX code, core neutronic parameters were calculated for three eigenvalues levels ( k s ) such as axial and radial distributions of neutron flux, effective multiplication coefficient ( K eff ), photoneutron yield ( Y n / e ), net neutron multiplication ( M ), energy gain ( G ), energy constant gain ( G 0 ), power peaking factor ( P max / P ave ), and importance of neutron source ( φ *) for the tungsten target in the core of TRIGA reactor which was driven by an electron accelerator. According to the results, when K s increases safety margin and the required accelerator current ( I e ) decrease, but the parameters G and φ * increase. Also, using the parabolic spatial distribution for the electron source instead of the uniform spatial distribution, the parameters Y n / e , G and M increase. In addition, by increasing E e from 100 to 500 MeV, Y n / e and G are improved, and I e and accelerating power ( p acc ) decrease. Therefore, these results suggest that the dependence of reactor core neutronic parameters on accelerator related parameters is necessary to optimize the design cost of an ADS reactor.

Transmutation technology has been developed to address the issue of long-term safety of nuclear waste disposal in geological repository. Transuranic (TRU) transmutation in thermal neutron spectrum can be considered more beneficial at the present time due to the larger fission cross section of TRU elements than in fast neutron spectrum. This paper discusses preliminary study on TRU transmutation in Vodo-Vodyanoi Energetichesky Reactor (VVER)-1000 fuel assembly using MCNP6 code. The fuel assembly is configured by 312 fuel cells consist of 300 UO 2 fuel rods with 3.7 wt% 235 U and 12 UGD fuel rods containing a mixture of UO 2 with 3.6 wt% 235 U and 4.0 wt% Gd 2 O 3 . The calculation results show that the k inf value is higher with the increase in the TRU thickness at the beginning of cycle and at the end of cycle, which means that the addition of TRU will increase the fuel cycle length. The total temperature coefficient of reactivity is negative for all fuel assemblies both without TRU and with TRU. In general, the computed β eff values of the assembly with and without TRU addition are not significantly different. It shows that the coating of the TRU layer in the UGD fuel cell will not complicate the reactor control. The transmutation of TRU recycled from spent nuclear fuel in the VVER-1000 fuel assembly can be considered feasible from the viewpoint of excess reactivity and control safety characteristics. The total transmutation rate of ∼55.73% can be achieved with 239 Pu and 241 Am isotopes are taking the largest portion of transmuted nuclides.

This article mainly studies the positioning function of radioactive detection technology in process control for processing devices. The accuracy of 22 Na detection is not limited by the spatial area by comparing different illumination scenarios; the accuracy of inspection is independent of the accuracy of machining equipment; the accuracy of the detection is not affected by the conditions of the processed body. This study is of great significance for the future radioactive detection technology to make up for the lack of precision caused by the existing sensor technology on the spatial positioning of the processing device, the illumination environment and the material characteristics of the processed body, and for the process control research in the field of advanced manufacturing.

The precise simulation of the reactor core either in steady state or during transients is very important for the safety assessment of nuclear power plants. This requires accurate determination of the parameters that influence the reactor operation. Coupling neutronic and thermal hydraulic schemes are developed to calculate these parameters. In the present paper, a coupling scheme between MCNP6 and ANSYS-FLUENT17.2 codes is proposed to obtain accurate radial and axial temperature distribution and hence pin power distribution for VVER-1000 fuel assembly. The Performance of the developed coupling scheme is investigated in steady state calculations. An iterative process is associated with the exchange of data between codes to meet the convergence criteria. The results obtained demonstrate that the proposed coupling scheme is able to simulate the VVER-1000 fuel assembly accurately. It gives information about thermal and neutronic behavior of the assembly and allows the feedback effects to be accurately modeled. This work is a step forward to establish a consistent methodology to be used in transient calculations.

Improving efficiency of the nuclear power plants has always been of interest for researchers. Recently, Nanofluid technology are developed to increase the heat extraction from a hot surface. Throughout this work, the thermal hydraulic behavior of Nanofluid was experimentally investigated and theoretically predicted. For this purpose, an experimental apparatus (setup) was designed and constructed to study the effect of the kind of Nanomaterial and the concentration of nanoparticles. Two kinds of Nanomaterial, Carbon Nano Tubes (CNTs) and Copper Oxide (CuO) were used. In an experimental investigation of CNTs, two nanoparticles concentration was used; 0.05 and 0.1% vol. CNTs/Water. CuO nanofluid was investigated experimentally with 0.1, 0.2, 0.3, 0.4, and 0.5% vol.CuO/Water. These concentrations of nanofluid were investigated at a constant mass flow rate and different heat fluxes, (1000, 3000 and 5000 W/m 2 ). The test rig was modeled theoretically using ANSYS FLUENT 17.2 code and validated to predict the thermal hydraulic performance of the Nanofluid. The five concentrations of CNTs and CuO nanofluids were theoretically investigated. It was found that the measured wall surface temperatures of CNTs and CuO nanoparticles decreased remarkably as heat flux decreased and the nanoparticles concentrations increased. There was an increase in forced thermal efficiency of nanofluids as compared to base fluid. The experimental results showed a maximum heat transfer coefficient enhancement of 26.55% for a nanofluid prepared with 0.1% vol. CNTs and 20.6% with 0.5% vol. CuO. A good agreement was detected after comparing experimental results with the investigated model.

In this work, a three-dimensional study is conducted for silicon ingot irradiation facility in a typical MTR reactor. The silicon ingot heat generation is allowed to change around its nominal value in the range of 0.25, 0.5, 0.75, 1.0, and 1.25 W/g. The dimensionless clearance ratio ζ between the ingot and the outer casing is changed for values of 0.01, 0.05, 0.1, 0.15, and 0.2. The computational fluid dynamics code ANSYS FLUENT is employed to carry out these calculations. The temperature profile inside the silicon ingot during irradiation is of significant importance for uniform doping. Therefore, the impact of Rayleigh number and dimensionless clearance ratio ζ on the radial and axial temperature profiles through the ingot is reported. A best estimate correlation for the silicon irradiation facility global Nusselt number in terms of Rayleigh and dimensionless clearance ratio is presented. The dimensionless clearance ratio ζ value of 0.05 gives the best thermal hydraulic performance. Comparison with the available experimental correlations in the literature shows good agreement.

Sodium Iodide doped with Thallium NaI(Tl) scintillation detectors have potential for the development of an active dosimeter for photon radiation. We aim to show that the photon dosimetry response for NaI(Tl) scintillation detector may be optimized by employing the Particle Swarm optimization algorithm, when the selective data sampling is applied for the detector readout. In this work, Sodium Iodide doped with Thallium NaI(Tl) scintillation detector is considered due to being highly sensitive to gamma radiation, and one of the affordable room temperature detectors. In this research, we intend to measure the dosimetry response of the NaI(Tl) detector for various gamma sources, as an example, by measuring the ambient dose equivalent H*(10) for different gamma radioactive sources. Furthermore, we demonstrate that the photon dosimetry response may be well optimized for various energies, especially at lower energies, by increasing the energy interval number in data sampling over the NaI(Tl) scintillation detector readout with the help of an optimization algorithm. The simulation software Geant4 has been used for determining the NaI(Tl) scintillation detector readout. To this end, experimental ambient dose equivalent measurements for gamma radiation sources are compared with the theoretical results. As three and six energy intervals are considered for the selective data sampling along with an optimization algorithm based on NaI(Tl) detector output, the error percentage will be less than 20 and 10%, respectively.