Band 87, Heft 1

The aim of this review is to present a summary of the published papers of the heat transfer and pressure drop characteristics for single-phase flow in helically coiled tubes. The effect of geometrical parameters such as curvature ratio, coil pitch and working conditions such as Reynolds number, Dean number, flow rate and flow arrangement on heat transfer and pressure drop in helically coiled tubes are determined in the light of the experimental, numerical and analytical studies in the literature. Also, the effect of using nanofluids in comparison with conventional fluids, using enhanced surfaces such as corrugated, micro-finned, dimpled with regards to smooth surfaces and wire coil insert usage in helically coiled tubes are discussed. The correlations proposed for determination of Nusselt number and friction factor in helically coiled tubes are presented in detail separately under laminar and turbulent flow regimes. The studies show that usage of helically coiled tube merely gives higher heat transfer rate and pressure drop in comparison to straight one, additionally, the heat transfer performance increases with the inclusion of the combination of other passive heat transfer enhancement methods to helically coiled tube. Moreover, the subject of single-phase flow in helically coiled tubes is ascertained to be worth researching due to the fact that there are limited number of studies and is still no empirical or analytical model/correlation in the case of using enhanced surfaces and wire coil insert. Forthcoming researches on this issue in the near future will be considered as pioneer ones in literature.

An integrated gamma ray scanning system has been designed and built to extend that localizes and quantifies highly enriched uranium sample. The detection mechanisms of the two modes (segmented gamma scanner and tomographic gamma scanning) are analyzed respectively. Moreover, the parameters influence of speed and the deviation of the measurement accuracy are analyzed for the uranium sample. In view of these problems, the system has improved by the optimization processing, which include the optimization of the collimator opening for detector, the crosstalk and the time step. Finally, the experiment were investigated and discussed in detail. The single measurement time of the system can reduce to about 30 min with an error of less than ±5%, so the measurement accuracy and the speed are enhanced effectively. The system has broad application prospects in the fields of nuclear safety, radioactive recyclables and non-destructive measurement of nuclear waste.

The paper demonstrates the CFD capability to predict the effect of rod bowing on CHF. The applicability and performance of the models are validated based on the Weatherhead experimental data for vertical pipe and NUPEC PWR subchannel and bundle test (PSBT) International Benchmark for rod bundle. The capability of the existing CFD method in predicting CHF is studied both qualitatively and quantitatively. Based on the validated method, the effect of the bowed rod on CHF is evaluated. The bow is assumed to occur at the midspan between two spacer grids in the region where DNB is predicted to occur. The results indicate that rod bowing has a deleterious effect on CHF, but this adverse bowing effect is dependent on the closure (i.e., the ratio of the change of the fuel rod gap to the nominal gap). There is no effect on CHF for closure between 0 and 50%, but adverse effect on CHF for closure larger than 50%, even more considerable effect as the closure increases to larger than 85%. The findings can be used to assist in designing the test fuel rod before the rod bowing CHF experiment.

The purpose of this work was to perform a thermal–hydraulic numerical analysis of a nanofluid as the coolant in a typical MTR (material testing reactor) core. Numerical simulation was carried out for turbulent flow of water based nanofluid of different concentrations of Al 2 O 3 nanoparticles through a sub-channel of a typical MTR core subjected to cosine shape heat flux at various values of Reynolds number using the Ansys-Fluent computer code. The optimum performance of the studied nanofluid as a coolant in MTR core was determined by the determination of the conditions under which the total entropy generation due to both heat transfer and fluid flow had a minimum value. The results showed that this condition was at Re = 4.8 × 10 4 . The studied range of Reynolds number (Re) and particle concentration ( ϕ ) were 2.5 × 10 4  ≤ Re ≤ 5.6 × 10 4 and 0% ≤  ϕ  ≤ 9% respectively. Results for local and average heat transfer and flow characteristics were presented. For the studied range of Reynolds number and particle concentration, four new correlations were developed. Two correlations relating Nusselt number and friction coefficient with the parameters Re and ϕ whereas the other two correlations were one relating Nusselt number with Reynolds and Prandtl numbers and the other relating the friction coefficient with Reynolds number.

The behavior of the nuclear reactor in response to any sudden change in reactivity is very important for reactor control. Positive reactivity insertions causes power excursion and could have a destructive impact on the reactor core. The aim of the study is to investigate the safety features of a material test reactor (MTR) during reactivity transient with emphasis on the capability of the mathematical modeling using programming language. Therefore a mathematical model using Python3.6; high-level programming language is developed to solve the point kinetic equations taking into account Doppler and moderator feedback effects. The model is validated with AIREKMOD_RR; point kinetic computer code for reactivity transient analysis in nuclear research reactors. The results of the Python model demonstrate the inherent safety features of the MTR reactor. Also, there is good agreement between the results of the Python model and AIREKMOD_RR code, illustrating the efficiency of the Python model in simulating the behavior of the reactor core under reactivity transient.

The inverse kinetics problem in reactor physics is a standard formalism to unfold reactivity on the basis of registered power (flux) profile. The classical inverse point kinetics framework has been retrofitted herein to comprise thermal reactivity feedback effects. The instantaneous fuel and coolant temperatures are thus computed by way of the exponential time-differencing scheme and the corresponding thermal reactivity feedback is plugged into the inverse kinetics module. The core external reactivity is therefore unfolded employing only two consecutive time-steps of the power (flux) profile. A history independent yet straightforward numerical routine is accrued enjoying noticeable robustness with regards to the time-step resolution.

In this research, the analysis methodology for Kuosheng BWR/6 nuclear power plant (NPP) decommissioning is established by using NRCDose3 code. NRCDose3 code includes XOQDOQ, GASPAR II, and LADTAP II programs that can assess atmospheric dispersion factor, gaseous radioactive effluents and offsite doses, and liquid radioactive releases and offsite doses, respectively. Therefore, this analysis methodology of NRCDose3 assesses the offsite doses of the gaseous radioactive effluents and liquid radioactive releases for Kuosheng NPP decommissioning. According to the analysis results, the results of NRCDose3 are consistent with Kuosheng NPP data.

The neutronics performance and safety characteristics of Uranium mononitride (UN) fuel for System-Integrated Modular Advanced Reactor (SMART) has been investigated to discern the potential for non-proliferation, waste, and accident tolerance benefits of UN fuel. The neutronic evaluation of UN fuel for SMART reactor has been carried out under normal operation using OpenMC and compared with Uranium dioxide (UO 2 ) in terms of fuel cycle length, reactivity coefficients, Fuel depletion (burnup), thermal flux, and fission product activity. The power peaking factor (PPF) has been compared at the beginning of the fuel cycle (BOC), mid of the fuel cycle (MOC), and at the end of the fuel cycle (EOC). Results indicate that the UN fuel can be operated beyond the designed fuel cycle length of the SMART reactor, which induces the positive reactivity at the end of the fuel cycle of about 4625 pcm. However, the UO 2 showed negative reactivity after three years. The total fission product activity at the end of the fuel cycle (3.5 years) for UO 2 and UN has been founded 1.003 × 10 20  Bq and 1.023 × 10 20  Bq, respectively.

Power upgrade in nuclear reactors has been identified as one of the least costly options. This article focuses on how to further increase the thermal power and the possibility of using internally and externally cooled (I&EC) fuels instead of the solid fuels in the core of a Small Modular Reactor (SMR). In hence, The NuScale is chosen as the reference SMR. The core of NuScale is designed based on the use of a new 12 × 12 I&EC fuel assembly. This study is conducted throughout neutronic/thermal-hydraulic analysis. And many essential neutronic and thermal-hydraulic parameters such as variations of effective multiplication factor as a function of the pitch, neutron flux, power peaking factors, DNBRs and maximum temperature of the fuel were obtained. As one of the most important results of the analysis, I&EC fuel shows a sufficient margin available on DNBR and fuel pellet temperature compared with cylindrical solid fuel. The margin amount seems accommodating a 183% power-uprate seems viable. Also, the fuels axial temperature at different power levels were analyzed, and it was found that the proposed fuel at high power levels has a low peak temperature.

Nuclear reactor dynamics are nonlinear and time-varying, so the power level control is a challenging problem in nuclear power plants (NPPs) to ensure both its operation stability and efficiency. An important measure to improve the safety of the reactor core of NPP is the implementation of robust control for the core by adjusting the inserted reactivity of the control rods. Thus in the present paper, fractional-order PID (FOPID) controller is developed as it is well known for its simplicity and robustness against disturbances. A Genetic Algorithm (GA) is used to determine FOPID controller parameters to achieve the desired power level for the generation III+ reactor VVER-1000. Implementing the GA, a suitable objective function is proposed to search for the optimal FOPID parameters. The nonlinear model of the VVER-1000 nuclear reactor is presented based on the point kinetic equations with six delayed neutron groups and temperature feedback from lumped fuel and coolant temperatures. Two cases for the VVER-1000 reactor are investigated; the changes in the power loads and the control rod withdrawal that leads to reactivity disturbance. Moreover, the uncertainties that result from model parameters perturbation are added to examine the controller robustness. The simulation results show that the proposed optimized FOPID controller can track the desired power level of the VVER-1000 reactor and robustly cope with any load changes, disturbances, or any parameters uncertainties. Also, it proves the superiority of the proposed optimized FOPID controller over other PID controllers in ensuring the safe and effective operation of the VVER-1000 reactor.

Exposure of radioactivity applications should be handled reliably in repositories, radiotherapy rooms, and research centers built with cement-based composites which is generally used as an engineering barrier. The design of certain materials for radioactive exposure requires special handling considering the degradation mechanism of host composite environment and barrier capability. In this study, celestite (SrSO 4 ) minerals having favoring properties for shielding ability was used as aggregates in barrier composites. Strontium mineral-based aggregates were partially replaced with conventional concrete aggregates at different ratios. The high rate X-ray shielding ability and mechanical performance of developed composites were holistically investigated in the presence of real-case radiation. The use of celestite mineral resulted in higher performance both in mechanical and shielding capability of X-rays at a certain level. Microstructural findings also revealed that interface properties of composite paste and celestite minerals were compatible up to 30% of celestite aggregate replacement.

In this work, both hardware and software modifications in a typical research reactor protection system (RPS) is proposed. The reactor cooling pumps are tripped based on vibrations safety signals of the pumps while the reactor SCRAM signal is initiated based on low flow rate and pressure drop across the reactor core which is a direct result of pumps trip. The main objective of this work is to develop reactor SCRAM signal based of core cooling pumps vibration signals. The early shutdown of the reactor based on pumps vibration signals is of significant importance not only in cooling the decay power of the reactor core after shutdown but also to prevent pumps failure. In the hardware model, the core cooling pumps vibration signals are feed to RPS to initiate reactor SCRAM signal. In the software model, a modular artificial neural network (ANN) is used in modeling the vibration monitoring of the research reactor (ETRR-2). The input and the output signals of the vibration transducer are used as a source data for training the neural network model. The type of the network used in this methodology is the supervised Multilayer Feed-Forward Neural Networks with the back-propagation (BP) algorithm. Vibration analysis programs are used in research reactors (RRs) to identify faults in machinery, plan machinery repairs, and keep machinery functioning for as long as possible without failure. The vibration severity limits are determined based on the International Organization for Standardization (ISO) 10816. The ANNs were designed using two different methods; one is by using hardware application contained two out of three voting and dynamic modules for trip signal by using ANNs. The current model classifies the vibration signals into five ranges low, good, satisfactory, unsatisfactory, and unacceptable vibration. The ANN is trained to detect the signal and vote to take the correct and safe action. The results demonstrate that the ANN can help in taking predictive actions for the safe core coolant pumps operation.