Reactor Pressure Research Articles

Application of CFD and nodal expansion method for simulation and analysis of boron dilution accident

Nuclear power, as a low-carbon energy source, provides the steady and reliable electricity. In this power source, safe operation plays a significant role from the point of view of design and economic cost. While nuclear power plants are designed to be safe in their operation and safe in the event of any malfunction or accident, some accidents with considerable occurrence frequency should be considered to provide related safety system and operation. The malfunction of boron injection system is one of this accident affecting the chemical and neutronic characteristics of cooling fluid. The aim of this study is the simulation and analysis of the boron dilution accident as one of Design Basis Accident, by considering the heterogeneous distribution of boron. For this purpose, CFD methods were used for exact evaluation of the boron distribution in each fuel assembly. Also, cross-section correction module and core calculation module are respectively developed by a cell calculation code and nodal expansion method. These modules are employed to apply absorber effects including boron and control banks and calculate 3D relative power. The results reveal the effect of heterogeneous distribution of boron in reactor pressure vessel and non-uniform chemical characteristics of coolant across fuel channels.

Production of Novel Tubular Electrochemical Hydrogen Compressor

For most applications, especially transport, hydrogen needs to be compressed due to its low volumetric density. Conventionally, mechanical compressors are used for hydrogen compression, but they possess disadvantages such as high maintenance due to moving parts and a limited one-stage compression ratio. A promising technology to overcome those obstacles is electrochemical hydrogen compression, in which hydrogen is compressed in an electrochemical membrane reactor.To date, only planar electrochemical reactors for hydrogen compression have been investigated although tubular designs offer advantages in membrane area to reactor volume ratio, sealing options, pressure stability and reactor complexity. However, high contact and membrane resistances and scalable manufacturing processes are still challenges to be addressed for the advent of tubular electrochemical compressors in application.Herein we introduce a manufacturing process for tubular electrochemical hydrogen compression reactors. The developed cell comprises a catalyst coated porous tubular anode covered by a tubular proton exchange membrane, which was subsequently coated with the cathode catalyst layer. The porous anode was prepared via metal 3D printing. 3D printing enables tailored porosity and geometry by which mass transport is enhanced. The catalyst layer was applied by manual spray coating. Constant current experiments and electrochemical impedance spectroscopy were performed to characterize the as prepared tubular electrochemical compressor. The results revealed the importance of tailored contacting concepts and the optimization of components regarding water transport, as the efficiency of the process is dominated by contact and membrane resistances.

Supercritical CO2 Assisted Ni-P Electroless Plating of PET Components with Complex 3D Structures

There is an increasing demand of methodologies to metallize complex polymer materials for application in electronics such as wearable devices and robotic products. In various metallization methods, electroless plating is a powerful and promising approach to meet this demand. The present conventional electroless plating requires pretreatment steps to deposit catalyst onto surfaces of polymer materials, which results in damages to their surfaces and also deformation of their shape because of the usage of strong acidic solvents. Furthermore, the adhesion strength between the polymer material and the metal layer is insufficient. To overcome these problems, a catalyzation step using supercritical carbon dioxide (sc-CO2) as the solvent is proposed.[1] The sc-CO2-assisted catalyzation enables a deep impregnation of catalysts into the polymer material without the pretreatment step, and this enhances the adhesive properties of the deposited metal on the polymer. By the sc-CO2-assisted catalyzation, electroless Ni-P plating of polyethylene terephthalate (PET) is realized. [1] Metallization of polymer materials with complex 3D structures is a more attractive topic, but it is widely accepted to be more difficult than film structures. Also, application the electroless plating via sc-CO2-asssited catalyzation to 3D-structured polymer materials remains unexplored. In this presentation, we report Ni-P plating of PET samples having complex 3D structures by the sc-CO2-assisited catalyzation process.A PET based material with a concavo-convex structure was designed and fabricated by the processing machine as shown in Figs. 1(a)–(b). Sc-CO2-assisted catalyzation process was performed in a high pressure reactor[1] containing palladium (II) hexafluoroacetylacetonate (Pd(C5HF6O2)2) as the palladium catalyst source at 70 °C under 15 MPa for 2 h. After the catalyzation process, the reactor was cooled to room temperature while maintaining the pressure in the reactor, and then the pressure in the reactor was reduced to atmospheric pressure. The collected PET sample from the reactor was kept under ambient atmosphere for two weeks, and then it was subjected to electroless Ni-P plating at 70 ℃ for 10 min.Fig. 1(c) shows the PET sample obtained after the sc-CO2-assisted catalyzation process followed by the post-treatment process. The volume of the catalyzed PET sample was scarcely changed. On the other hand, the post-treatment processes performed under the different conditions were found to cause undesired swelling and white turbidity of the PET sample, presumably because of microbubbles derived from residual CO2 in the PET. Fig. 1(d) shows an image of Ni-P successfully metallized on the PET surface. The electrical resistance of the Ni-P/PET material was 8.7 Ω, which is acceptable for electronic device applications. From these results, we concluded that sc-CO2-assisted catalyzation is applicable to metallization of PET materials with complex 3D structures. Reference [1] P.-W. Cheng, C.-Y. Chen, T. Ichibayashi, T.-F.M. Chang, M. Sone, S. Nishimura, J. Supercrit. Fluids 180 (2022) 105455. Figure 1

Unconventional frequency response analysis of PEM fuel cell based on high-order frequency response function and total harmonic distortion

Electrochemical impedance spectroscopy (EIS) is a commonly used technique for studying internal dynamics of the proton exchange membrane (PEM) fuel cell. However, due to its linear frequency response nature and reliance on the linear target hypothesis, EIS has limitations in analyzing the nonlinear behavior of the PEM fuel cell, which is the inherently nonlinear system. To overcome this issue, this paper employs an unconventional frequency analysis technique that utilizes the high-order frequency response function (FRF) and total harmonic distortion (THD) in a broad frequency range, to conduct the nonlinear frequency response analysis (NFRA) of the PEM fuel cell. In addition to the traditional electrochemical impedance based on the first-order harmonic response, the high-order harmonic response is also included. Based on this, the appropriate excitation amplitude is determined through a comprehensive examination of the impact of varying excitation amplitudes on the impedance, second-order FRF, and THD. Then, the impacts of operating conditions, such as reactant stoichiometry, humidity, temperature, and pressure, on the FRF and THD were investigated incorporating the dynamics losses computed using EIS and equivalent circuit model. Furthermore, the nonlinear frequency response is investigated under various fault conditions, such as flooding, membrane drying, and air starvation. The results demonstrate the heightened sensitivity of the NFRA method towards detecting changes in internal processes of the PEM fuel cell, which offers a multidimensional frequency-domain perspective, facilitating the study of the advanced diagnosis, system control, material optimization, and even other electrochemical energy sources.

Reconstruction error‐based fault detection of time series process data using generative adversarial auto‐encoders

AbstractFaults in time series process data are typically difficult to detect due to the complex temporal correlations of data samples. In this context, traditional unsupervised machine learning algorithms, such as principal component analysis, independent component analysis, and so forth, would yield only limited performance. Deep learning‐based methods have been employed in recent years to address these problems. Recently, generative adversarial networks have emerged as a promising generative modelling approach for learning data distributions. Inspired by the above, in this study, we present a novel reconstruction error‐based fault detection method for time series process data using generative adversarial auto‐encoder (GAAE) with Wasserstein loss, cycle consistency loss, and gradient penalty methods. The proposed method is designed to detect abnormal patterns in the time series data by training a GAAE to learn the underlying normal behaviour of the data. GAAEs help in effectively capturing the data's hidden distribution, and Wasserstein loss with gradient penalty is used to improve the accuracy of the latent space representation of the data, while the cycle consistency loss ensures consistency between the input and output data during the reconstruction process. Based on the extent of the reconstruction error metric of the GAAEs, we identify the potential faults in the process data stream. The proposed method is evaluated on two data process sets, namely, the Tennessee Eastman benchmark process dataset and the nuclear power flux real‐time dataset from a pressurized heavy water nuclear reactor, to validate the efficacy of the proposed approach.

Characterization of fusion boundary between low alloy steel and stainless steel cladding

The microstructure and hardness of fusion boundary (FB) and near FB of a low alloy steel (LAS) 16MND5 welding cladded with stainless steel 308L for nuclear reactor pressure vessel were investigated by using modern electron microscopes and nano-indenter. The wavy morphology of fusion line results in changes of nearby microstructures of both cladding 308L and substrate 16MND5 along the FB. The microstructure of the cladding 308L is composed of columnar grains adjacent most of the FB, but it is equiaxed grains at the valley of the wavy fusion line with large curvature. The microstructures of 16MND5 near the FB are ferrite at the wavy fusion line with large curvature, martensite at the wavy fusion line with small curvature, and transition mixed structure between them. A carbide-depleted zone adjacent to the FB was observed in the 16MND5 side, of which the hardness is lower than both FB and 16MND5 base metal. Three types of FB can be observed according to the width, being narrow or sharp FB, needle-like martensite FB, and partially-mixed zone FB. The FB includes high density of carbides of M7C3 and M3C, leading to a hardness peak at FB.

“Practical elimination” principle in the Akkuyu Nuclear Power Plant design

The paper considers the implementation of the “practical elimination” principle in the design of the Akkuyu NPP with VVER1200 reactors being under construction in Turkey. The “practical elimination” principle is defined as follows: for accident sequences or phenomena that contribute or lead to unacceptable radiological consequences for the public or the environment, it shall be shown with a high level of confidence that their occurrence is highly unlikely. “Practical elimination” is proved predominantly by results of a Level 2 probabilistic safety assessment. The implementation of the “practical elimination” principle was considered at the level of accident sequences leading to a large radioactive release. It has been shown that each accident sequence leading to an unacceptable release has the probability of occurrence below 4.45Е–8 per reactor per year, while their total probability not exceeding the value of 6.17Е–7 per reactor per year. For the phenomena inside the containment area during severe accidents, including hydrogen detonation, a large thermal explosion, direct containment heating, overpressure in the containment volume, and the containment damage at later stages due to the basement melting through, their “practical elimination” has been demonstrated. The paper also considers specific hard-to-assess scenarios of beyond design basis accidents, for which the applicability of the “practical elimination” principle is assessed as well: a major positive reactivity insertion, a rupture of the reactor pressure vessel and other largescale components, damage of fuel elements in the spent fuel pool, severe accidents with the containment bypass or containment failure, and severe accidents accompanied the means for mitigating with their consequences being unavailable. Criteria have been developed and used for the “practical elimination” assessment. A sensitivity analysis was undertaken as part of the Level 2 probabilistic safety assessment which has shown that estimated values slightly depend on the analytical assumptions, as well as on the random change in the parameters that the affect the progression of severe accidents.

Development of HELIOS/BIPR/PARCS/MCNP6 Computation Route for WWER RPV Neutron Fluence Analysis and Validation Against Ex-Vessel Detector Measurement Data

A computational route was developed for precise calculation of fast neutron fluence on a WWER-type reactor pressure vessel (RPV). The method is based on the transfer of neutronics data from HELIOS-2 lattice calculations and nodal diffusion neutronics data (power, density, and temperature) from BIPR7.1 and PARCS 3.36/PATHS core calculations into a three-dimensional (pinwise axially distributed) fixed neutron source for modeling of transport of fast neutrons from the reactor core to the outer surface of the RPV using MCNP6.2. Validation of the proposed computational method was carried out based on comparative analysis of MCNP6.2-predicted and neutron dosimetry–measured reaction rates [54Fe(n,p)54Мn, 93Nb(n,nʹ)93mNb, and 58Ni(n,р)58Со] on the outer surface of the Armenian Nuclear Power Plant (ANPP) Unit 2 RPV. Validation revealed that the MCNP6.2-predicted fast neutron fluence results are very sensitive to the ENDF-B neutron data. Particularly, MCNP6.2 with ENDF/B-VIII.0 significantly underpredicts (20% to 30%) fast neutron fluence while using ENDF/B-VII.1 data overpredicts it. Adding revised beta-released evaluations of 54Fe, 56Fe, 57Fe, and 16O from the International Nuclear Data Evaluation Network (INDEN) to ENDF/B-VIII.0 allows one to obtain reasonable agreement with measurement results for all types of measured reaction rates.

Origin of Suppressed Chain Transfer in Phosphinephenolato Ni(II)-Catalyzed Ethylene Polymerization.

Recent breakthroughs in the generation of polar-functionalized and more sustainable degradable polyethylenes have been enabled by advanced phosphinephenolato Ni(II) catalysts. A key has been to overcome this type of catalysts' propensity for extensive chain transfer to enable formation of high-molecular-weight polyethylene chains. We elucidate the mechanistic origin of this paradigm shift by a combined experimental and theoretical study. Single-crystal X-ray structural analysis and cyclic voltammetry of a set of six different catalysts with variable electronics and sterics, combined with extensive pressure reactor polymerization studies, suggest that an attractive Ni-aryl interaction of a P-[2-(aryl)phenyl] is responsible for the suppression of chain transfer. This differs from the established picture of steric shielding found for other prominent late transition metal catalysts. Extensive density functional theory studies identify the relevant pathways of chain growth and chain transfer and show how this attractive interaction suppresses chain transfer.

Structural integrity analysis with crack propagation for reactor pressure vessel nozzles based on XFEM

Structural integrity analysis for reactor pressure vessel (RPV) nozzles has been a vital issue due to the irradiation embrittlement and especially the discontinuity of geometry in RPV nozzles, which may cause a higher stress concentration and influence the structural integrity of RPV nozzles. For the linear elastic fracture mechanics (LEFM) analysis of the RPV nozzle, a postulated crack with a specific crack depth is presumed to evaluate the stress intensity factors (SIFs) whose crack depth does not grow during LEFM analysis. Thus, this paper would discuss the crack propagation for the postulated crack with a specific crack depth under the different reference temperature of nil-ductility transition (RTNDT), and the SIFs on the specific crack depth are also calculated. In recent research, the extended finite element method (XFEM) was developed, which is based on the enrichment solution space to simplify the computational fracture mechanics with the crack propagation of various discontinuities, and can be used to evaluate the crack propagation of RPV nozzle with a specific crack depth under RTNDT of −23.89, −10.89, 0.89, 2.69, and 2.89 °C. To investigate the crack propagation and structural integrity of RPV nozzles, the finite element analysis of Taiwan domestic boiling water reactor (BWR) nozzles containing the postulated circular corner crack with depths of one-fourth and one-tenth thickness along the 45° path from the tip of the nozzle corner is engaged. The present result shows that the crack was growing when the RTNDT was 0.89 °C and. In addition, the XFEM calculation of the SIFs for the specific crack depth is similar to the LEFM results.

Optimization and evaluation of the distribution of Fischer-Tropsch products over a cobalt-based catalyst utilising design expert software

Modelling biomass to liquid via the Fischer-Tropsch synthesis (FTS) system allows researchers to investigate the most efficient parameters while running the system under optimal conditions. As part of the design of experiments (DOE) procedure, a special data simulation method based on response surface methodology (RSM) is utilized to thoroughly analyse the impact of operating circumstances. The objective of this study was to examine the factors that affect the production of C1, C2–C4, and C5+ in FTS process, and then optimize the critical factors utilising factorial design and response surface techniques. The parameters evaluated were reaction temperature, reaction pressure and the crystallite size of cobalt. The effects of these factors and their potential for synergy were explored simultaneously using multivariate DOE, with the yield of different hydrocarbon composition selectivity's as the measured responses. In the concept generation phase, optimization was based on the literature consulted, which proved to be an effective method for determining the optimization parameters. The detailed conceptual design included the generation of models using statistical methods and response surface models. Finally, the optimized design was validated using catalysts and parameters obtained during the optimization process, and this were compared to the output recorded in the theoretical modelling. The optimized parameters resulted in performance consistency, with the theoretical model for each group of hydrocarbons being validated by actual experiments. The established models were seen to characterize hydrocarbon distributions accurately and repeatedly over a wide range of reaction conditions (200–270 °C, 5–20 Bar, and 3–26 nm) using a cobalt-based catalyst. According to the detailed quantitative models developed, for higher C5+ production, 220 °C, 10 barg and 11 nm (cobalt crystallite) benchmark parameters were set to produce 19.3 % C1, 11.4 % C2–C4 and 69 % C5+ selectivity's. Comparative analysis showed a 1.9 %, 3.9 % and 0.3 % percentage difference between the theoretical output and the actual output of C1, C2–C4 and C5+, respectively.

Production of needle cokes via mild condition co-pyrolysis of FCC-DO and PFPE

The conventional needle coke production process suffers from high reaction temperature and pressure, and therefore, alternative approaches for needle coke production with low energy consumption should be developed. The co-pyrolysis process of FCC decant oil (FCC-DO) and perfluoropolyether (PFPE) was suggested to prepare needle cokes under mild reaction conditions in this work. The characteristics of green pitches and cokes from the co-pyrolysis process were evaluated with XRD, FT-IR, TGA, EA and polarized images to prove the effectiveness of the PFPE-aided reaction in accelerating polymerization. The mixture of FCC-DO and 10 wt% of PFPE was heated to 420, 430, 440, and 450 °C and 1 bar in continuous nitrogen flow, and needle cokes could be successfully derived at a temperature of 440 °C and atmospheric pressure with the addition of PFPE, which are significantly milder conditions compared with prior studies on needle coke production. The reaction mechanism of co-pyrolysis was suggested with radical-based reactions that emerged during the thermal decomposition of PFPE. Furthermore, the electrical and thermal properties of the carbonized needle cokes indicated the superior structural, thermal, and chemical characteristics of PFPE-assisted reaction-derived needle cokes; the needle cokes obtained from PFPE co-pyrolysis showed a 23.5 % reduced CTE value and 7.2 times higher electrical conductivity compared with cokes from pure FCC-DO. Effective needle coke production at a low temperature and pressure could be achieved with a PFPE-assisted co-pyrolysis reaction, and we believe that this study could contribute to a novel method for preparing needle cokes with low energy consumption and extending the applicability of needle cokes by supplying high-quality and low-price needle cokes.

Enhancing coking resistance of ZSM-5 in the conversion of pine sawdust into oxygen-free bio-aromatic hydrocarbons through tandem catalytic hydropyrolysis/vapor-phase hydrotreatment

The conversion of biomass into bio-aromatic hydrocarbons is a crucial aspect of achieving sustainable development. However, inadequate deoxygenation not only reduces the yield of aromatics but also causes instability in the produced biofuels. In this study, a tandem hydropyrolysis/vapor phase hydrotreatment process was conducted in a two-stage pressurized fixed-bed reactor to produce oxygen-free bio-aromatic hydrocarbons from pine sawdust under 0.15 MPa H2 with ZSM-5. The experimental results indicated that oxygen-containing compounds generated during the hydropyrolysis of pine sawdust in the first-stage reactor, were completely hydrodeoxygenated in the second-stage reactor over ZSM-5. This resulted in a total bio-aromatic hydrocarbons yield of 109.6 mg/g, with 81.5% selectivity to monoaromatic hydrocarbons, including benzene, toluene, ethylbenzene, and xylenes (BTEXs). The optimization study revealed that the hydropyrolysis temperature, hydrodeoxygenation temperature, and catalyst-to-biomass mass ratio could be controlled at 550 °C, 450 °C, and 8:1, respectively. The tandem process, conducted under pressurized H2, showed the capability to inhibit the deactivation of ZSM-5, as the low deactivation rate (35.1%) was observed in 15 sequential experiments of pine sawdust with an accumulated catalyst-to-biomass mass ratio of 0.5. The catalytic tandem vapor-phase hydrotreatment strategy offers a promising approach to effectively produce bio-aromatic hydrocarbons from biomass.

CNN-based automated approach to crack-feature detection in steam cycle components

Periodic manual inspection by trained specialists is an important element of asset management in the nuclear industry. Detection of cracks caused by stress corrosion is an important element of remote visual inspection (RVI) in power plant steam generator components such as boilers, superheaters and reheaters. Challenges exist in the interpretation of RVI footage, such as high degree of concentration for reviewing lengthy and disorienting footage due to narrow field of view offered by endoscope. Deep learning is considered useful to automate crack detection process for improved efficiency and accuracy, and has enjoyed success in related applications. This article utilises a new application of automated crack feature detection in steam cycle components to demonstrate a transferrable data-driven framework for a variety of anomaly inspections in such structures. Specifically, a case study of superheater (a type of reactor pressure vessel head) anomaly inspection is presented to automatically detect regions of crack-like features in inspection footage with a good accuracy of 92.97 % using convolutional neural network (CNN), even in challenging cases. Due to the black-box nature of the CNN classification, the explicability of the classification results is discussed to enhance the trustworthiness of the detection system.

Estimation and testing of single-step oxidation reactions for hydrogen and methane in low-oxygen, elevated pressure conditions

Advanced combustion concepts, such as moderate or intense low-oxygen dilution (MILD) combustion, offer a reduction in NOx emissions and increased thermal efficiency. MILD is characterised by low-oxygen, high-temperature conditions, where finite-rate chemistry effects are significant. Modelling this regime using reduced or single-step chemistry remains a challenge in part due to the finite-rate chemistry. This work proposes a generalised method for assigning Arrhenius coefficients of a single-step reaction using the outputs of a detailed mechanism. Assigning the typical chemical conservation equation to a progress variable, activation energy and pre-exponential factor for an Arrhenius kinetics global reaction are determined for hydrogen and methane across a number of conditions, with the proposed method extended to n-heptane as well. The temperature exponent in the modified Arrhenius equation is determined by minimising the ignition delay error between detailed and single-step simulations. Functional forms of each coefficient are calculated from a multivariate regression, dependent on initial temperature, pressure, and oxidant mole fraction. The predicted mechanisms are compared against the detailed kinetics in closed homogeneous batch reactors, with comparisons for hydrogen extended to both laminar opposed flow diffusion flames, and computational fluid dynamics (CFD) simulations. Ignition delay and equilibrium temperature are both well predicted for all three fuels in the batch reactors. Notably, the negative temperature coefficient behaviour of n-heptane is successfully recreated with the single-step mechanism. Temperature and heat release of hydrogen flames are well captured in both opposed flow laminar flames, and in turbulent CFD simulations. The computational time was also significantly reduced through the single-step mechanisms, resulting in ∼100 times reduction in compute time for CFD simulations. The function form of the Arrhenius coefficients shows promise for extension outside of the ranges and fuels analysed herein, and presents interesting phenomena for exploring how initial reactant temperature and pressure influence the effective activation energy of an oxidation process.

Converting waste tires into p-cymene through hydropyrolysis and selective gas-phase hydrogenation/dehydrogenation

The resource utilization and valorization of waste tires (WT) are of significant importance in reducing environmental pollution. To produce high-value p-cymene from WT, we propose a catalytic cascade process combining hydropyrolysis and catalytic gas-phase hydrotreating in a two-stage fixed-bed reactor. The effect of catalysts prepared with three different acidic supports on the hydrogenation/dehydrogenation of limonene, a compound derived from the hydropyrolysis of WT, was investigated. The p-cymene formation could be controlled by optimizing process parameters, including hydropyrolysis temperature, hydrogenation temperature, and catalyst-to-feedstock ratio (C/F). Experimental results indicated that, in the absence of a catalyst, limonene was the main product of WT depolymerization. Under optimized conditions (hydropyrolysis temperature of 425 ℃, hydrotreating temperature of 400 ℃, C/F of 10:1, and reaction pressure of 0.15 MPa), the highest relative content of p-cymene (79.1%) was obtained over the Pd/SBA-15 catalyst. This demonstrates that our proposed catalytic cascade process of hydropyrolysis and selective gas-phase hydrogenation/dehydrogenation can convert WT into p-cymene with high added value.

Experimental investigation of thermal stratification development in boiling water reactor suppression pools during reactor core isolation cooling system operation

The Reactor Core Isolation Cooling (RCIC) system provides make-up water to the reactor pressure vessel during isolation events by passing steam from the vessel through a turbine which drives a pump to return water to the vessel. Exemplary performance of the RCIC system during the Fukushima Daiichi nuclear accident of 2011 has promoted interest in its potential performance.To investigate the development of thermal stratification within suppression pools due to RCIC system exhaust, a facility was constructed to produce the highest-resolution 3-D temperature measurements available in a large water pool during pool mixing by steam injection.Thermal stratification was most strongly influenced by suppression chamber pressure. Increased steam flowrate promoted mixing, which delayed the onset of thermal stratification. Containment response is discussed with respect to thermal stratification, which delays the time of warm water ingestion and cavitation of the RCIC pump, and pool mixing, which reduces the containment pressurization rate.

CFD analysis of coolant mixing in VVER-1000/V320 reactor pressure vessel

This study presents a code-to-code and model-to-model comparison of coolant mixing in the VVER-1000/V320 Kozloduy Unit 6 nuclear power plant using Computational Fluid Dynamics (CFD). Four different CFD codes were used to simulate coolant mixing in the reactor vessel, namely ANSYS Fluent, ANSYS CFX, TrioCFD, and STAR-CCM+. Two different approaches were used to model the upper plenum, while a single simplified model was used for the reactor pressure vessel. The simulations were performed for VVER-1000 coolant transient benchmark (V1000CT-2) mixing exercise. The results were compared between the different CFD codes and models to assess the accuracy and consistency of the simulations with the available experimental data. Overall, the results showed good agreement between the different CFD codes and models, with minor differences observed in some cases. The simplified models were found to be sufficient for predicting the overall coolant mixing patterns observed in the reactor vessel, provided additional insights into the local flow structures and mixing characteristics. This study demonstrates the applicability and reliability of CFD simulations for coolant mixing analysis in VVER-1000/V320 nuclear power plants.

Transient full core analysis of PWR with multi-scale and multi-physics approach

Steam line break accident (SLB) in the nuclear reactor is one of the representative Non-LOCA accidents in which thermal-hydraulics and neutron kinetics are strongly coupled each other. Thus, the multi-scale and multi-physics approach is applied in this study in order to examine a realistic safety margin. An entire reactor coolant system is modelled by system scale node, whereas sub-channel scale resolution is applied for the region of interest such as the reactor core. Fuel performance code is extended to consider full core pin-wise fuel behaviour. The MARU platform is developed for easy integration of the codes to be coupled. An initial stage of the steam line break accident is simulated on the MARU platform. As cold coolant is injected from the cold leg into the reactor pressure vessel, the power increases due to the moderator feedback. Three-dimensional coolant and fuel behaviour are qualitatively visualized for easy comprehension. Moreover, quantitative investigation is added by focusing on the enhancement of safety margin by means of comparing the minimum departure from nucleate boiling ratio (MDNBR). Three factors contributing to the increase of the MDNBR are proposed: Various geometric parameters, realistic power distribution by neutron kinetics code, Radial coolant mixing including sub-channel physics model.

Numerical study of the flow and heat transfer characteristics in a scale model of the vessel cooling system for the HTTR

The reactor cavity cooling system (RCCS) is a passive reactor safety system commonly present in the designs of High-Temperature Gas-cooled Reactors (HTGR) that removes heat from the reactor pressure vessel by means of natural convection and radiation. It is one of the factors responsible for ensuring that the reactor does not melt down under any plausible accident scenario. For the simulation of accident scenarios, which are transient phenomena unfolding over a span of up to several days, intermediate fidelity methods and system codes must be employed to limit the models’ execution time. These models can quantify radiation heat transfer well, but heat transfer caused by natural convection must be quantified with the use of correlations for the heat transfer coefficient. It is difficult to obtain reliable correlations for HTGR RCCS heat transfer coefficients experimentally due to such a system’s size. They could, however, be obtained from high-fidelity steady-state simulations of RCCSs. The Rayleigh number in RCCSs is too high for using a Direct Numerical Simulation (DNS) technique; thus, a Reynolds-Averaged Navier–Stokes (RANS) approach must be employed. There are many RANS models, each performing best under different geometry and fluid flow conditions. To find the most suitable one for simulating an RCCS, the RANS models need to be validated. This work benchmarks various RANS models against three experiments performed on the HTTR RCCS Mockup by the Japanese Atomic Energy Agency (JAEA) in 1993. This facility is a 1/6 scale model of a vessel cooling system (VCS) for the High Temperature Engineering Test Reactor (HTTR), which is operated by JAEA. Multiple RANS models were evaluated on a simplified 2d-axisymmetric geometry. They were found to reproduce the experimental temperature profiles with errors of up to 22% for the lowest temperature benchmark and 15% for the higher temperature benchmarks. The results highlight that the pragmatic turbulence models need to be validated for high Rayleigh natural convection-driven flows and improved accordingly, more publicly available experimental data of RCCS resembling experiments is needed and indicate that a 2d-axisymmetric geometry approximation is likely insufficient to capture all the relevant phenomena in RCCS simulations.