Virtual Reactor Research Articles

Small Modular Reactors and Virtual Reactor

In February of this year, the Ministry of Science and ICT launched a call for proposals for the Global TOP Strategic Research Groups project with the slogan “Bold Challenges from Research Institutes, Innovative Steps Together.” The Global TOP Strategic Research Groups initiative aims to establish an open collaborative framework focused on national missions that transcends the boundaries of research institutes, supporting them to achieve significant outcomes befitting national research organizations. This feature aims to briefly introduce the research background and goals of one of the five selected strategic research groups: the “Development of an SMR Virtual Reactor Platform.” This initiative, led by the Korea Atomic Energy Research Institute (KAERI), the Korea Institute of Science and Technology Information (KISTI), and the Electronics and Telecommunications Research Institute (ETRI), will be conducted over five years, starting from June 2024.

DC fault current clearance coordinated control strategy for DC grid with hybrid MMC

For DC grid based on the hybrid modular multilevel converter (MMC), the traditional DC fault current clearance scheme takes a long time and greatly affects the active power transmission. A novel DC fault current clearance coordinated control strategy is proposed, which can quickly interrupt the fault current and reduce the impact of DC fault on the DC grid and AC system. For fault-line connected MMC (FLMMC), a negative DC voltage control is employed, which can improve the current attenuation speed and ensure reliable fault isolation. For non-fault-line connected MMC (NFLMMC), the active current-limiting control (ACLC) based on the virtual reactor is adopted, which can reduce the current flow to the fault location and further shorten fault isolation time. To reduce the impact on the AC system during the DC fault, a short-time active power support control is designed. Finally, a four-terminal DC grid simulation model is built based on the RT-LAB OP5600 real-time digital simulation platform. The simulation results show that the proposed coordinated control strategy for the DC grid can quickly clear DC fault current, shorten DC fault isolation time, and strengthen active power support capability.

Environmental and Economic Evaluation of the Sequential Combination of Coagulation–Flocculation with Different Electro-Fenton-Based Configurations for the Treatment of Raw Textile Wastewater

This study reports, for the first time, on the assessment of a multistage sequential system composed of coagulation–flocculation with different electro-Fenton-based configurations, followed by neutralization (N), for the treatment of raw textile wastewater heavily contaminated with acid black 194 dye and other pollutants. Electrochemical peroxidation (ECP-N), electro-Fenton (EF-N) and peroxi-coagulation (PC-N) were tested at laboratory scale and compared in terms of their efficiency for the removal of organic matter and color, current efficiency and energetic parameter, operating cost and environmental sustainability using life cycle analysis conducted in large-scale virtual reactors. The three electro-Fenton-based systems complied with current environmental standards (color removal > 87%, COD < 400 mg/L, among others) requiring different electrolysis times: ECP-N (52 min) < PC-N (120 min) < EF-N (160 min); energy consumptions: ECP-N (2.27 kWh/m3) < PC-N (4.28 kWh/m3) < EF-N (33.2 kWh/m3); operational costs: ECP-N (2.63 USD/m3) < EF-N (6.65 USD/m3) < PC-N (6.98 USD/m3); among others. Electricity (for ECP-N and EF-N) and reagents (for ECP-N and PC-N) were found as main environmental hotspots. ECP-N presented the lowest carbon footprint of 10.3 kg CO2-Eq/FU (<PC-N (26.3 kg CO2-Eq/FU) < EF-N (38.0 kg CO2-Eq/FU), had lower incidence in all the impact categories analyzed (ReCiPe-2016 at midpoint level) and can be considered technically, economically and environmentally sustainable for large-scale applications.

The effect of the decomposition of CH4 gas on polycrystalline SiC coating on SiC ceramics using Si vapor

We investigated the application of polycrystalline SiC coating on SiC ceramics using vapor from a Si melt as a Si source and C2H2 generated by decomposition of CH4 gas as a C source. First, the temperature distribution and gas flow in the furnace, the decomposition behavior of CH4 gas, and the production rate were calculated using the simulation software Virtual Reactor. Based on these numerical results, the structure of the furnace and its internal layout were decided. Next, SiC coating on SiC ceramics was performed with two different furnace layouts, and the generated SiC coating layer was evaluated by observation of the microstructure. With a CH4 gas flow rate of 50 sccm and a pressure inside the furnace of 0.5 atm, SiC coating with a coating rate of 26 μm h−1 was achieved.

Artificial Intelligence for Hybrid Modeling in Fluid Catalytic Cracking (FCC)

This study reports a novel hybrid model for the prediction of six critical process variables of importance in an industrial-scale FCC (fluid catalytic cracking) riser reactor: vacuum gas oil (VGO) conversion, outlet riser temperature, light cycle oil (LCO), gasoline, light gases, and coke yields. The proposed model is developed via the integration of a computational particle-fluid dynamics (CPFD) methodology with artificial intelligence (AI). The adopted methodology solves the first principle model (FPM) equations numerically using the CPFD Barracuda Virtual Reactor 22.0® software. Based on 216 of these CPFD simulations, the performance of an industrial-scale FCC riser reactor unit was assessed using VGO catalytic cracking kinetics developed at CREC-UWO. The dataset obtained with CPFD is employed for the training and testing of a machine learning (ML) algorithm. This algorithm is based on a multiple output feedforward neural network (FNN) selected to allow one to establish correlations between the riser reactor feeding conditions and its outcoming parameters, with a 0.83 averaged regression coefficient and an overall RMSE of 1.93 being obtained. This research underscores the value of integrating CPFD simulations with ML to optimize industrial processes and enhance their predictive accuracy, offering significant advancements in FCC riser reactor unit operations.

Challenges in high-fidelity thermal–hydraulic simulation of SFR cores: Insights and PACA-S4FR solutions

Numerical simulations in studying thermal–hydraulic behavior in sodium-cooled fast reactors (SFR) have gained attention for their safety and cost advantages. While low-fidelity numerical simulations commonly used in industry have the advantage of lower computational costs, they face challenges in accurately representing intricate flow phenomena. On the other hand, high-fidelity numerical simulations offer excellent characterization of turbulence but demand significant computational resources. The emergence of exascale supercomputers has provided opportunities and challenges for large-scale high-fidelity numerical simulations. In this paper, firstly, we review the research progress of thermal–hydraulic numerical simulations of SFR cores using both low-fidelity and high-fidelity methods. Secondly, we estimate the computational and storage requirements for high-fidelity numerical simulations of SFR core based on calculations performed on China Experimental Fast Reactor (CEFR). Subsequently, we analyze the challenges of conducting high-fidelity thermal–hydraulic simulations of the entire SFR core, including large-scale mesh generation, appropriate numerical discretization methods, efficient simulation acceleration techniques, coupled simulations, and the complexities of validation and verification processes. Finally, we present the research progress of PACA-S4FR, a high-fidelity thermal–hydraulic simulation software in the China Virtual Reactor (CVR1.0) project, along with the ongoing efforts to address challenges in high-fidelity simulations. This paper contributes to advancing the comprehension of SFR core thermal hydraulics, potentially aiding in safety and performance enhancements in SFR.

Challenges of high-fidelity virtual reactor for exascale computing and research progress of China Virtual Reactor

The virtual reactor is a sophisticated software system deployed on supercomputers to simulate physics process or predict component behaviors inside real reactors. It highly relies on advanced modeling and coupling methods, high performance computing and advanced verification and validation (V&V) techniques, which is another important method for reactor engineering design and mechanism research besides experiment. With the advent of exascale computer, it becomes mainstream trend to develop full-core high-fidelity simulation research under the help of exascale computing technology. This paper first summarizes the challenges of developing high-fidelity virtual reactor simulation in exascale computing. The challenges of high-fidelity virtual reactor simulation are introduced from four aspects: science-based modeling methods, high-resolution mesh model, scientific numerical methods , and multiphysics and multiscale coupling. Based on the architecture of exascale computer, the challenges of parallel optimization of virtual reactor for exascale computing are introduced. Furthermore, this paper introduces the recent research progress of China Virtual Reactor (CVR), which is about the parallel optimization for Chinese exascale computers and the functional extensions for achieving full-core high-fidelity simulation. The recent research progress of CVR includes multiscale simulation software of materials, fuel performance simulation software, thermal-hydraulic simulation software, full-core high-resolution meshing tool, and optimization of basic sparse operators.

Full-Loop Study of a Pilot-Scale Dual Fluidized Bed Cold Flow System: Hydrodynamic Simulation

Computational particle fluid dynamics (CPFD) simulations of three-dimensional cold-flow gas-solid flow were performed for a pilot-scale dual-circulating fluidized bed (DCFB) using Barracuda Virtual Reactor® 17.4.0. This DCFB system is a fluidized bed gasifier used in a calcium-loop gasification process to produce a hydrogen-rich gas with CO2 capture. The effects of different bubble bed inlet airflow rates and different solid inventories on the full-loop pressure distribution and particle concentration distribution were compared. The increase in the bubble bed inlet airflow rate significantly increases the pressure in the bubble bed and lift pipe, and the increase in the solids inventory significantly increases the pressure where the solids are tightly packed. For long-term operation, the appropriate combination of parameters should be found to maintain a stable particle seal at the loopseals.

Numerical simulation of fluidization: Driven by challenges

In the century-long development of fluidization technology, simulation methods have evolved in response to scientific and engineering demands, which in turn have produced advances in technology. Faced with the profound global challenges of climate change and sustainable development, fluidization has found new applications in carbon capture and utilization, non-energy uses of fossil fuels, production of functional materials, and the continuous production of drugs and fine chemicals. Revolutionary research and development tools, such as digital virtual reactors and even factories, are highly desirable for the effective and efficient conceptualization, scaling-up, and optimization of the processes and equipment in these sophisticated applications, and require unprecedented advances in the accuracy and speed of simulations. After a short review of the existing simulation methods for fluidization, this article focuses on how such advances could be achieved through the organic integration of multiscale modeling, scalable algorithms, and supercomputing. Gallery of representative simulation studies on fluidization. • Inherent logic and driving force behind the development of modeling and simulation. • Importance of multi-scale modeling, scalable algorithms and supercomputing for future. • Integration of simulation with AI, VR, big data and robot scientists for new applications.

Image Processing and Measurement of the Bubble Properties in a Bubbling Fluidized Bed Reactor

The efficiency of a fluidized bed reactor depends on the bed fluid dynamic behavior, which is significantly influenced by the bubble properties. This work investigates the bubble properties of a bubbling fluidized bed reactor using computational particle fluid dynamic (CPFD) simulations and electrical capacitance tomography (ECT) measurements. The two-dimensional images (along the reactor horizontal and vertical planes) of the fluidized bed are obtained from the CPFD simulations at different operating conditions. The CPFD model was developed in a commercial CPFD software Barracuda Virtual Reactor 20.0.1. The bubble behavior and bed fluidization behavior are characterized form the bubble properties: average bubble diameter, bubble rise velocity, and bubble frequency. The bubble properties were determined by processing the extracted images with script developed in MATLAB. The CPFD simulation results are compared with experimental data (obtained from the ECT sensors) and correlations in the literature. The results from the CPFD model and experimental measurement depicted that the average bubble diameter increased with an increase in superficial gas velocities up to 4.2 Umf and decreased with a further increase in gas velocities due to the onset of large bubbles (potential slugging regime). The bubble rise velocity increased as it moved from the lower region to the bed surface. The Fourier transform of the transient solid volume fraction illustrated that multiple bubbles pass the plane with varying amplitude and frequency in the range of 1–6 Hz. Further, the bubble frequency increased with an increase in superficial gas velocity up to 2.5Umf and decreased with a further increase in gas velocity. The CPFD model and method employed in this work can be useful for studying the influence of bubble properties on conversion efficiency of a gasification reactor operating at high temperatures.

CPFD study of volatile liquid injection in a dense gas–solid fluidized bed

This study uses the Eulerian-Lagrangian multiphase particle-in-cell (MP-PIC) approach, adopted in the computational particle fluid dynamics (CPFD) code, Barracuda Virtual Reactor®, to simulate the injection of a gas–liquid spray into a gas–solid fluidized bed. The model accounts for evaporation of volatile liquid in the form of individually moving droplets and thin films distributed on the surface of the solid bed particles. Comparison with previously reported temperature measurements for varying spray nozzle gas-to-liquid ratios suggests that the model is capable of predicting the overall features of the gas temperature distributions within the injection region at injection velocities of less than 50 m/s. Locally observed discrepancies between experimental and simulated temperature profiles are likely related to the presence of wet particle agglomerates in the spray region, as suggested by a developed energy dissipation model that, combined with the MP-PIC model, predicts the location and extent of agglomeration in the fluidized bed.

Computational modeling of high pressure bubbling fluidized bed hydrodynamics using ilmenite particles

The multiphase particle-in-cell approach was used to model the hydrodynamics of five different ilmenite particle size distributions in a high pressure cylindrical fluidized bed. The model was created using the commercial software Barracuda Virtual Reactor® and validated against previously obtained experimental data. Simulations for minimum fluidization velocity were dependent on the model input close pack factor, with a value of 0.58 resulting in the best fit with an average absolute deviation (AARD) of 3.9%. Afterwards, trends in bed expansion with fluidization ratio and pressure were well represented by the model, but consistently under predicting by an average of 4.8%. The model also predicted bubble size distribution with change in relation to fluidization ratio, pressure, and elevation. The calculated mean bubble diameter deviated by 18.7% from the experimental results, and the Mori & Wen correlation for bubble growth was adapted to the simulated data resulting in an AARD of 22%.

Virtual Catalytic Reactor Laboratory

A virtual catalytic reactor laboratory (VCRL) experiment, which can be used in most browsers, is described. Students select feed conditions and use the VCRL to take data for a gas-phase catalytic reaction and fit kinetic parameters to a Langmuir-Hinshelwood rate expression. The VCRL contains instructions, equipment descriptions, an animated start-up procedure, a video tour of a physical laboratory, screencasts about nonlinear regression, a means to submit answers online, and an instructor portal.

Virtual reactor laboratory integrated with cyber security from Bangladesh perspective

This paper intends to present the current status of the education and training program of BAEC TRIGA Research Reactor (BTRR) as well as the prospect of Virtual Reactor Laboratory (VRL) as a tool to impart training and education. VRL has been proposed based on BTRR and its feasibility with regard to imparting training and education programs of research reactor has been assessed. As education and training are key utilizations of BTRR, this VRL will widen the scope of harnessing maximum benefits out of such utilizations. Since nuclear security is a paramount concern, aspects of cyber security has been considered in the proposed VRL. In order to maintain a high degree of privacy of the BTRR facility, different levels of cyber security have been embedded along with the VRL to control the unknown access to the system. VRL can provide an impetus in developing skilled workforce for Rooppur Nuclear Power Plant (RNPP), other proposed nuclear power plants, nuclear installations and broaden the outlook of teachers, students and researchers in nuclear science and technology through distant learning method.

Multiphase Particle in Cell Simulations of Fluidized Beds: Studies on Bubble Rise Velocity and Minimum Fluidization Velocity

AbstractMultiphase particle in a cell simulation of fluidized beds for different Geldart group particles (A, B and D) were investigated. The minimum fluidization velocities predicted by the Barracuda Virtual Reactor® were compared and contrasted by theoretical predictions with the Wen‐Yu model. The optimal drag force coefficients based on the Wen‐Yu model for MP‐PIC simulations was further evaluated for different particle sizes and densities for Group A catalysts. A neural network model was constructed for the optimal model constants as a function of the explanatory variables for group A catalysts. This work illustrates the importance of choosing the correct value for the drag force coefficients to obtain realistic simulation results for fluidized beds. This work clearly demonstrates that the Barracuda simulation results are very sensitive to the value of the Wen‐Yu parameter. Using multiphase particle in cell simulations in conjunction with a neural network model can be directly used in further studies as a rapid tool to get the correct values for realistic drag force coefficients based on the Wen‐Yu model.

HVdc Reactor Reduction Method Based on Virtual Reactor Fault Current Limiting Control of MMC

A large high-voltage direct current (HVdc) reactor is required in modular multilevel converter (MMC) projects to realize dc fault current limiting (FCL). This condition may result in adverse effects on MMC control dynamics and oscillation and instability of HVdc systems. In this article, a virtual reactor (VR) control strategy is proposed to reduce a fixed large HVdc reactor. The VR characteristic of MMCs is revealed and analyzed as a controlled reactor, and the inductance of this reactor can be directly controlled by the discharge degree of submodule capacitors. A virtual reactor fault current limiting (VRFCL) control strategy in which VR can effectively limit dc fault current and substitute the fixed HVdc reactor is proposed accordingly. Simulation and experimental results verify the proposed control strategy. The adoption of the proposed strategy can eliminate the undesirable effect caused by an HVdc reactor, and the sub-module (SM) capacitor voltage can be reserved well. In addition, fault clearance time and fault energy dissipation can be reduced. The proposed VRFCL control is beneficial for MMCs to safely ride through dc fault in a continuous operation manner.

Multi-physics coupling simulation in virtual reactors

Nuclear power stations involve a range of complex and interacting multi-physical processes. With the rapid development of high-performance computing technology, accurate multi-physics simulation in virtual reactors has drawn more and more attention in industry and academia. Great efforts have been made toward the simulation of multi-physics coupling processes in reactors. The interpretations of many terms that describe multi-physics simulation vary in different literatures. We organize and discuss some important terms relevant to the multi-physics coupling simulation. We compare the three most frequently used multi-physics coupling strategies: the operator splitting, Picard iteration, and Jacobian-Free Newton–Krylov methods. We summarize three main viewpoints on the degree of coupling of the three strategies (loose, tight, or full coupling). Then we review the coupling software and corresponding coupling strategies in some representative virtual reactor projects. We present the research focuses of Spider coupling platform. The Spider is developed in the China Virtual Reactor (CVR) project. The multi-physics phenomena are considered in the CVR project from three scales: fuel scale, reactor core scale, and system scale. Both loose and tight coupling strategies are supported in the Spider platform.

CPFD simulation of petcoke and SRF co–firing in a full–scale cement calciner

Computational particle fluid dynamics (CPFD) simulation is carried out to study the effect of petcoke and solid recovered fuel (SRF) co–firing in a full–scale cement calciner. The simulations are conducted using the Multi–Phase Particle–In–Cell (MP–PIC) approach with the Barracuda Virtual Reactor® 17.3.1 solver. The results from the CPFD simulation are compared with extensive field measurements of gas temperature and composition at several points in different calciner cross–sections. In the simulation, the SRF particles are divided into three components of plastic, biomass, and inert. The plastic particles go through drying, melting and decomposition while the conversion of biomass particles involves drying, devolatilization, and char oxidation. The predicted concentrations of O2 and CO2 are in good agreement with the measurements, while the gas temperature is overpredicted, especially in the lower calciner vessel. However, the trends of changes in the gas temperature are well–captured. The converted fuel fraction and calcination factor are predicted with an acceptable degree of accuracy. The simulation results show that large biomass particles in SRF tend to leave the calciner without complete conversion. Furthermore, a recirculation pattern for SRF particles is observed in the lower calciner vessel and the conical section, leading to high conversion degree of this fuel.

Experimental and CPFD study of gas–solid flow in a cold pilot calciner

Experimental characterization and computational fluid particle dynamics (CPFD) simulations of a cold pilot–scale cement calciner were carried out to investigate the dispersion and heating of cold cement raw meal particles in the hot gas flow. During the experiments, the gas velocity and temperature were measured at different locations upstream and downstream of the place where the particles were fed to the calciner. The simulations were carried out using Eulerian–Lagrangian approach together with the Multi–Phase Particle–In–Cell (MP–PIC) method, based on the commercially available Barracuda Virtual Reactor® 17.1.0 software. For the particle–free flow, it was shown that the grid–independent velocity profiles predicted from the simulations are in proper agreement with the measured values. For the particle–laden flow, the simulation results from two drag models of EMMS and Gidaspow were compared with the gas temperature measurements and visual observations. The simulation results from the Gidaspow model exhibited an over–prediction of the amount of falling particles to the upstream regions. Both drag models exhibited a local minimum temperature region at a location slightly different from the measured one in a cross–section close to the particle feed position. For the Gidaspow model, a second low gas temperature region was observed at the opposite position of the particle feed that was not detected by the measurements. Overall, it is concluded that the Barracuda Virtual Reactor® software is able to capture the particle dispersion and gas–solid interactions in the studied pilot–scale calciner and the EMMS drag model is more reliable for prediction of the gas–solid flow.

Efficient visualization of high-resolution virtual nuclear reactor

High-resolution virtual reactors will enable scientists to simulate and analyze almost every aspect of the performance of existing nuclear reactor designs in unprecedented detail. However, high-quality visualizations of full-core nuclear reactor simulation data with high (pin-by-pin) spatial resolution require both time- and memory-consuming processing of large-scale combinatorial solid geometries with complicated constructions. This paper presents an efficient approach for performing this task using a novel solid-model-oriented rendering pipeline. The proposed method depends on the repeated structures within the reactor model, homogeneous material properties of the solid entity, and visibility of that entity in the current view, coupled to an efficient multiscale-driven visualization framework. Virtual reactor datasets are maintained as solid representations of the simulation models until the rendering stage. The proposed method can guide the production and reduction of mesh geometry directly according to statistics gathered during rendering. In combination with a level-of-detail representation of the solid geometry set, the reactor visualization can be accelerated because of the effective runtime reduction of large-scale cells. The results and performance of the method are demonstrated for the large-scale data visualization of the full-core pin-mode virtual reactor of the Chinese Daya Bay nuclear power station that comprises 757,839 solid units. The example is rendered successfully within a common user’s resource-limited computing environment, respecting the limited budget for CPU and memory.