Computational Fluid Dynamics Results Research Articles

Photocatalytic degradation of metformin on a rectangular baffled reactor: CFD modeling and validation investigation

Solar-irradiated photocatalysis is an advanced oxidation process (AOP) commonly used for water purification due to its excellent potential to break down a diverse range of persistent organic compounds into non-toxic byproducts. Reactor design is crucial in the photocatalysis process's efficiency, effectiveness, and scalability. Computational fluid dynamics (CFD) is an effective tool to study and comprehend reactor designs, reduce system cost, design time, and optimise reactor performance. This investigation focuses on designing and developing a rectangular baffled photocatalytic reactor that can effectively degrade metformin (MTF). The experimental study optimized the value of pH and catalyst dosage for efficient removal. The photoreactor demonstrated an efficiency of 58.14 % and was validated. The CFD results, including velocity profile and mass fraction of metformin, strongly agreed with the experimental results with an R2 value of 0.9826. The combination of various baffle sizes and spacing configurations was modeled and analyzed to develop a rectangular baffled photocatalytic reactor with maximum removal efficiency. The inclusion of baffles increased the flow path, improved mixing and enhanced the degrading efficiency. The investigation findings indicated the highest degradation efficiency of 78.03 % with the seven number of baffles.

#1967 Towards the design optimisation of catheters for paediatric dialysis using a bioengineering approach

Abstract Background and Aims Central venous lines (CVLs) used for haemodialysis (HD) in children are associated with a high complication rate, leading to inadequate dialysis and need for a line replacement in nearly 45% of children on HD. This high complication rate may be due to poor CVL configurations, designed without considering specific anatomical differences between children and adults. Using a bioengineering approach, we aim to provide a fluid dynamics characterization of different CVL models commonly used in children to establish an association between CVL design and clinical complications, and to improve CVL performance by optimising their design. Method Computational fluid dynamics (CFD) using modelling and simulations is a powerful engineering tool that use computers to study complex systems, applying mathematics, physics and computer science. Four models of CVLs of varying designs and sizes (6.5Fr, 8Fr, 10Fr and 14Fr) were scanned by microCT to reconstruct computational models. CFD analyses were set up to simulate blood flow within the CVLs under both ideal and realistic models of superior vena cava. A variety of flow rates, routinely used in clinical practice, were applied to study the whole range of working conditions. Haemodynamic features that cannot be measured in vivo such as high shear stresses and large areas of stagnation, were analysed. CFD findings were compared to clinical outcomes (n = 26 patients with 57 lines) and to the blood clots distribution of CVLs removed from patients (n = 8). Fluid dynamics characteristics of the CVLs studied were used to set up a preliminary design optimisation process of a 6.5F CVL model. Using sampling methods, a variety of CVL designs were created starting from the original model and results were compared. Results In all the simulated CVLs, the arterial lumens showed the highest stagnation and recirculation areas. The role of arterial tip configuration was negligible for the blood flows and the proximal side holes played a major role for blood aspiration being also subject to the highest levels of shear stress, regardless of the design. In all the anatomical models, blood velocity increased after catheter insertion (Fig. 1a) together with wall shear stresses. CFD results were in accordance with the clinical data which showed a higher recurrence rate of thrombosis for the 8Fr and 10Fr CVLs. Also, microCT of the CVLs removed due to complications confirmed presence of thrombosis at the catheter tips. Results suggest that shear stress is the parameter most strongly related to clinical complications. The preliminary design optimisation study was used to find the parameters which have the highest influence on the CVL performance. Preliminarily optimised designs of the 6.5F model showed a better haemodynamic performance, reducing stagnation areas (Fig. 1b). Conclusion Characterisation of the fluid dynamics of commercially available CVLs explains some of the clinical outcomes experienced by patients. Identification of potential design-related complications in CVLs has allowed to set up the optimisation process which will lead to new CVL designs with improved blood flow distribution and minimal damage to blood cells. Funding Kidney Research UK, PhD fellowship and MedTech grants.

A new analytical wind turbine wake model considering the effects of coriolis force and yawed conditions

Wind turbine wakes significantly affect power production and impose higher loads on downstream turbines. Therefore, the development of accurate and efficient wake models is important for optimizing wind farm layouts and predicting wind turbine performance. This study introduces a novel analytical wake model for yawed wind turbines that incorporates the effects of the Coriolis force. The wake deflection in the far wake region is derived through the application of the principles of mass and momentum conservation. In the near wake, the deflection is assumed to be linear with distance. A Gaussian distribution is assumed for the velocity deficit within the wind turbine wake. Two approaches have been proposed to estimate the onset of the far wake region. While the first approach employs a simplified empirical formula, the second approach utilizes an iteration-based method. The proposed analytical wake model has been validated against computational fluid dynamics (CFD) results. Subsequently, the effects of several important parameters on the wake deflection have been systematically investigated. Overall, the simulation results showed a satisfactory agreement between the CFD results and those obtained from the proposed model. Furthermore, the study concluded that the Coriolis force can exert significant effects on wake deflection, particularly in the far wake region, confirming previous findings from numerical simulations. Due to its simplicity and computational efficiency, the proposed model can be readily used in several applications, including wind farm layout optimization, control and risk assessment.

Understanding two‐phase flow behaviour: CFD Assessment of silicone oil–air and water–air in an intermediate vertical pipe

AbstractThe study utilized computational fluid dynamics (CFD) simulations employing the volume of fluid (VOF) model to analyze silicone oil–air flows in a vertical pipe with a diameter of 67 mm. Various structured meshes ensured grid independence, and the k‐ε realizable model addressed turbulence. The analysis characterized bubbly to annular flows, involving the evaluation of flow patterns, radial void fractions, void fraction time series, probability density functions (PDFs), power spectral densities (PSDs), and mean void fractions. Results indicated a transition from bubbly to annular flow with increasing gas velocities and notable changes in radial void fraction profiles. Void fraction exhibited significant variations with distinct flow patterns at constant liquid velocity. PDFs identified flow regimes, and PSDs revealed frequency patterns. CFD results were validated against experiments, demonstrating good agreement. The validated CFD model was utilized to investigate radial gas velocities and pressure drops, revealing a shift from uniform velocity distributions to irregular patterns and a decrease in total pressure drop with an increase in gas superficial velocity. The model was also applied to a water‐air system to explore two‐phase flow behaviour. The impact of superficial gas velocity on flow patterns and radial void fractions was studied through numerical analysis and compared with the silicone oil‐air system. Results showed that at extreme gas velocities (0.06 and 5.53 m/s), silicone oil exhibited bubbly and annular flows, while water displayed cap bubbly and churn flows. The significant variation in radial void fraction at these velocities emphasized the impact of fluid properties.

Transient Performance Analysis of Centrifugal Left Ventricular Assist Devices Coupled With Windkessel Model: Large Eddy Simulations Study on Continuous and Pulsatile Flow Operation.

Computational fluid dynamics (CFD) simulations are widely used to develop and analyze blood-contacting medical devices such as left ventricular assist devices (LVADs). This work presents an analysis of the transient behavior of two centrifugal LVADs with different designs: HeartWare VAD and HeartMate3. A scale-resolving methodology is followed through Large Eddy Simulations, which allows for the visualization of turbulent structures. The three-dimensional (3D) LVAD models are coupled to a zero-dimensional (0D) 2-element Windkessel model, which accounts for the vascular resistance and compliance of the arterial system downstream of the device. Furthermore, both continuous- and pulsatile-flow operation modes are analyzed. For the pulsatile conditions, the artificial pulse of HeartMate3 is imposed, leading to a larger variation of performance variables in HeartWare VAD than in HeartMate3. Moreover, CFD results of pulsatile-flow simulations are compared to those obtained by accessing the quasi-steady maps of the pumps. The quasi-steady approach is a predictive tool used to provide a preliminary approximation of the pulsatile evolution of flow rate, pressure head, and power, by only imposing a speed pulse and vascular parameters. This preliminary quasi-steady solution can be useful for deciding the characteristics of the pulsatile speed law before running a transient CFD simulation, as the former entails a significant reduction in computational cost in comparison to the latter.

Modelling lower-limb peripheral arterial disease using clinically available datasets: impact of inflow boundary conditions on hemodynamic indices for restenosis prediction

Background and ObjectivesThe integration of hemodynamic markers as risk factors in restenosis prediction models for lower-limb peripheral arteries is hindered by fragmented clinical datasets. Computed tomography (CT) scans enable vessel geometry reconstruction and can be obtained at different times than the Doppler ultrasound (DUS) images, which provide information on blood flow velocity. Computational fluid dynamics (CFD) simulations allow the computation of near-wall hemodynamic indices, whose accuracy depends on the prescribed inlet boundary condition (BC), derived from the DUS images. This study aims to: (i) investigate the impact of different DUS-derived velocity waveforms on CFD results; (ii) test whether the same vessel areas, subjected to altered hemodynamics, can be detected independently of the applied inlet BC; (iii) suggest suitable DUS images to obtain reliable CFD results. MethodsCFD simulations were conducted on three patients treated with bypass surgery, using patient-specific DUS-derived inlet BCs recorded at either the same or different time points than the CT scan. The impact of the chosen inflow condition on bypass hemodynamics was assessed in terms of wall shear stress (WSS)-derived quantities. Patient-specific critical thresholds for the hemodynamic indices were applied to identify critical luminal areas and compare the results with a reference obtained with a DUS image acquired in close temporal proximity to the CT scan. ResultsThe main findings indicate that: (i) DUS-derived inlet velocity waveforms acquired at different time points than the CT scan led to statistically significantly different CFD results (p<0.001); (ii) the same luminal surface areas, exposed to low time-averaged WSS, could be identified independently of the applied inlet BCs; (iii) similar outcomes were observed for the other hemodynamic indices if the prescribed inlet velocity waveform had the same shape and comparable systolic acceleration time to the one recorded in close temporal proximity to the CT scan. ConclusionsDespite a lack of standardised data collection for diseased lower-limb peripheral arteries, an accurate estimation of luminal areas subjected to altered near-wall hemodynamics is possible independently of the applied inlet BC. This holds if the applied inlet waveform shares some characteristics – derivable from the DUS report – as one matching the acquisition time of the CT scan.

3D numerical simulations of mixed convective heat transfer and correlation development for a thermal manikin head

The head represents 10 % of the body's total surface area. Unprotected, it accounts for a significant portion of overall heat loss when exposed to cold conditions. This study was motivated by a need to clarify how the human head interacts with its environment in terms of heat exchange. Accurate estimations of heat transfer coefficients on the human head are essential for conducting thermal comfort and safety analyses in buildings. In this study, a thermal head resembling a real male human head is utilized to investigate heat transfer between the body and the surrounding environment. A three-dimensional computational fluid dynamics (CFD) model is proposed to simulate steady-state dry heat loss from the human head within a chamber. This model provides predictions for heat flux, temperature, and velocity distribution surrounding the head. A straightforward correlation, derived from numerical and experimental findings, is introduced to forecast the average Nusselt number for the head under combined natural and forced convection. This correlation, relying on dimensionless parameters (Grashof, Reynolds, and Prandtl numbers), offers enhanced accuracy, simplicity, and fewer terms. The predicted average Nusselt numbers from the proposed correlation for mixed convection closely match CFD and experimental results, with relative percentage differences within ±2 %, signifying excellent accuracy across a broader range of flow conditions, including temperature differences and air velocities. Additionally, the study explores the impact of head diameter on overall heat transfer.

Investigation of the asymmetric flow structure in a hydrocyclone

AbstractThe flow field of a hydrocyclone was investigated using both computational fluid dynamics (CFD) and particle image velocimetry (PIV). A refractive index matching method was employed to improve the precision of the PIV measurements. The CFD results are in good agreement with PIV measurements. Detailed analysis reveals significant axial asymmetry in the velocity components, with the radial velocity component exhibiting notable disparities. This observation is supported by quantitative data comparing different sections of the hydrocyclone. It is further found that the asymmetry might be mainly attributed to the secondary vortexes with the single inlet of the hydrocyclone. And the secondary vortexes, superimposed on the primary flow rather than existing on its own, spiral downwards from near the inlet towards the underflow orifice. It is hypothesized that specific boundary effects and pressure gradients play a pivotal role in the formation of secondary flows. This assumption is grounded on both theoretical considerations and empirical observations, suggesting that these factors significantly influence the flow dynamics within the hydrocyclone. The insights gained from our measurement methodology and enhanced understanding of secondary flows within hydrocyclones are not only poised to serve as valuable references for fellow researchers but also have the potential to inform the design and operational optimization of hydrocyclones for improved efficiency and performance.

Analysis of In-Cylinder Flow in a Small-Bore Spark-Ignition Engine Using Computational Fluid Dynamics Simulations and Zero-Dimensional-Based Modeling

Abstract The evolution of in-cylinder flow involves large- and small-scale structures during the intake and compression strokes, significantly influencing the fuel–air mixing and combustion processes. Extensive research has been conducted to investigate the flow evolution in medium- to large-sized engines using laser-based diagnostic methods, computational fluid dynamics (CFD) simulations, and zero-dimensional (0D) based modeling. In the present study, we provide a detailed analysis of the evolution of flow fields in a small-bore spark ignition (SI) engine with a displacement volume of 110 cm3. This analysis employs a unique methodology, where CFD simulation is performed and validated using measured particle image velocimetry (PIV) data. Subsequently, the validated CFD results are utilized to develop and validate a 0D-based model as it is computationally more efficient. The validated CFD simulation and 0D-based model are then used to evaluate the quantified strength of the flow by calculating the tumble ratio and turbulent kinetic energy (TKE). The streamlines and velocity vectors of the flow fields obtained from CFD simulations are utilized to explain the evolution of these parameters during intake and compression strokes. The study is further extended to analyze the effect of engine speed on the evolution of flow fields. With an increase in engine speed, relatively higher values of tumble ratio and TKE at the end of the compression stroke are observed, which is expected to improve the fuel–air mixing and combustion efficiency.

Simulation of Transient Temperature and Clearance after Shutdown of Aeroengine Based on CFD and FEA Coupled Models

It is crucial to comprehend the heat soak phenomenon, which may result in a significant temperature increase after the shutdown followed by a gradual decrease. This could bring potential risks for the engine including oil coking. The temperature change of engine components dictates the clearance after shutdown, while startup strategies are primarily based on this. A simulation strategy, utilizing computational fluid dynamics (CFD) and finite element analysis (FEA) coupled models, is suggested to investigate the transient temperature and clearance after shutdown. The maximum temperature deviation between the simulation result and experimental data are less than 6%. Flow parameters, including velocity and mass flow rate obtained from the CFD result, were applied as boundaries of the FEA model. Based on the FEA model, transient temperature calculations were also conducted for 20 hours after shutdown. The results indicate that the FEA model demonstrates good agreement with the CFD simulation, with a maximum deviation of less than 5% and at only 0.2% of the simulation time. After the engine shuts down, the stator’s temperature change rate is faster than that of the rotor due to better cooling conditions and relatively small heat capacity. Consequently, the seal clearance increases in the initial period after shutdown and then decreases to a minimum value. The nondimensional minimum clearance can be 0.8 times the cold state value at the location of the high-pressure turbine seal.

Reduction of Disk Friction Loss by Applying a Fin to the Back of a Centrifugal Impeller

Abstract It is well known that the ratio of disk friction loss of low specific speed pumps is large. When the specific speed is 100 min−1, m3/min, m or less, the disk friction loss increases remarkably. In this study, focusing on the clearance flow from the diffuser outlet to the impeller outlet (This is called the outward flow) behind the centrifugal pump, a fin was installed on outer diameter side of the rotating wall on the back side of a centrifugal pump as a countermeasure, and the influence of changes in velocity distribution near the wall on disk friction loss was investigated by torque measurements, velocity measurement, and computational fluid dynamics (CFD) analysis. As a result, it was clarified that disk friction loss is decreasing by installing the fin in both torque measurements and CFD results, because the clearance flow is separated by fin and circumferential velocity is increased in the wake region of the fin in both measurements and CFD. In addition, it was clarified that disk friction coefficient (normalized torque) can be expressed as a function of the inlet swirl ratio and Reynolds number. Also, prediction equation is derived for each shape (with and without fin). According to the equation, it was found that disk friction loss reduction effect by installing a fin becomes larger when Reynolds number and the inlet swirl ratio are small.

Investigation of flow behaviour in the nozzle of a Pelton wheel: Effects and analysis of influencing parameters

The performance of a Pelton wheel is influenced by the jet created by the nozzle. Therefore, a Computational Fluid Dynamics (CFD) simulation was proposed. In this study, the significant output parameters (outlet velocity, outlet pressure, and tangential force component) and input parameters (different pressure and spear locations) were examined. In addition, the influencing parameters and their contributing percentages to the performance of the Pelton wheel were calculated using different optimisation techniques such as Taguchi Design of Experiments (DoE), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Grey Relational Analysis (GRA) and Criteria Importance Through Intercriteria Correlation (CRITIC). The effect of input factors on the output response was examined with DoE, and the results show that the inlet pressure had the most significant impact (97.38%, 99.18%, and 97.38%, respectively, for all different spear sites with a 99% confidence level). In terms of preference values, the TOPSIS and GRA results are comparable (best ranks for simulation runs #24 and #25 and least ranks for simulations #2 and #3, respectively). The CRITIC results for the pressure parameter are in good agreement with the Taguchi ANOVA analysis. The last spear location (5 mm after the nozzle outlet), with an inlet pressure of 413685 Pa generated the best result when employing the TOPSIS and GRA techniques. The outlet pressure of the nozzle was found to have a significant impact on the flow pattern of the Pelton Wheel based on the analysis of the CRITIC, Taguchi, and CFD results.

Modeling scalability of impurity precipitation in downstream biomanufacturing.

Precipitation during the viral inactivation, neutralization and depth filtration step of a monoclonal antibody (mAb) purification process can provide quantifiable and potentially significant impurity reduction. However, robust commercial implementation of this unit operation is limited due to the lack of a representative scale-down model to characterize the removal of impurities. The objective of this work is to compare isoelectric impurity precipitation behavior for a monoclonal antibody product across scales, from benchtop to pilot manufacturing. Scaling parameters such as agitation and vessel geometry were investigated, with the precipitate amount and particle size distribution (PSD) characterized via turbidity and flow imaging microscopy. Qualitative analysis of the data shows that maintaining a consistent energy dissipation rate (EDR) could be used for approximate scaling of vessel geometry and agitator speeds in the absence of more detailed simulation. For a more rigorous approach, however, agitation was simulated via computational fluid dynamics (CFD) and these results were applied alongside a population balance model to simulate the trajectory of the size distribution of precipitate. CFD results were analyzed within a framework of a two-compartment mixing model comprising regions of high- and low-energy agitation, with material exchange between the two. Rate terms accounting for particle formation, growth and breakage within each region were defined, accounting for dependence on turbulence. This bifurcated model was successful in capturing the variability in particle sizes over time across scales. Such an approach enhances the mechanistic understanding of impurity precipitation and provides additional tools for model-assisted prediction for process scaling.

Flow fields prediction for data-driven model of 5 × 5 fuel rod bundles based on POD-RBFNN surrogate model

The fuel rod bundles are a crucial component of nuclear reactors. Research the flow characteristics of the fuel rod bundles can be computationally expensive, despite some progress made in the past few decades. In this paper, the fast prediction of flow fields for 5 × 5 fuel rod bundles is implemented based on a data-driven algorithm. First, a refined model of the 5 × 5 fuel rod bundles with spacer grid is established, and meshes are generated using a hybrid meshes technology. Then, the flow characteristics of the 5 × 5 fuel rod bundles are extensively analyzed using Computational Fluid Dynamics (CFD) methods. A comparison between the CFD results and experimental data reveals a strong agreement, thereby validating our research findings. Subsequently, a reduced-order model (ROM) called the proper orthogonal decomposition (POD)-radial basis function neural network (RBFNN) surrogate model is proposed. the POD algorithm is utilized to extracting the dominant flow modes, and the RBFNN is employed to predict the POD mode coefficients of non-sample points. By linearly combining the predicted POD mode coefficients with the POD modes, rapid prediction of flow fields for non-sample points can be achieved. Compared to the full-scale CFD simulations, it finds that the proposed POD-RBFNN surrogate model not only significantly improved efficiency, but also maintained a high level of predictive accuracy. It is believed that the research results hold important value for CFD calculations within nuclear reactor cores.

Aerosol deposition and emission from a United States Pharmacopeia‐induction port when using a pressurized metered‐dose inhaler with and without a valved holding chamber

AbstractThe testing of pharmaceutical aerosols includes measuring the aerodynamic particle size distribution, which is usually performed on cascade impactors. In the next generation impactor (NGI), the aerosol dose is introduced through an induction port (IP), being separated into different aerodynamic diameter ranges by seven stages and a micro‐orifice collector. The IP plays an important role in estimating the oropharyngeal deposition fraction. While the IP retains mainly large particles, it also tends to retain particles in the respirable range. In this work, the deposition of particles in the IP of an NGI is studied, both experimentally and through computational fluid dynamic (CFD) simulations. Experimental tests are conducted both with the pressurized metered‐dose inhaler (pMDI) alone and in conjunction with a cylindrical valved holding chamber (VHC). For each case, the total mass deposition that occurs in the VHC, IP, and NGI stages is measured, as well as the mass median aerodynamic diameter of the aerosol leaving the IP. The CFD simulations show minimal variations in results regardless of the injection method due to the relatively low velocity and spray angle of the pMDI‐generated aerosol. If the flap‐valve is removed from the VHC, significant particle deposition occurs upstream or within the valve region, with downstream air recirculation contributing to small particle deposition. Based on the CFD results, a correlation is proposed to accurately predict the particle escape fraction of the IP and VHC, which allows estimation of the tannin distribution of particles collected in the NGI stages, especially those corresponding to the range of respirable particles.

A numerical framework to investigate isotropic turbulent inflow interacting with an airfoil’s leading edge

This paper presents a numerical framework to study the interaction of isotropic turbulence with airfoils. Specifically, the developed numerical framework is used to investigate the distortion of the turbulent structures interacting with an airfoil’s leading edge. For turbulence modeling, Large Eddy Simulation (LES) is used. The isotropic turbulent inflow for the Computational Fluid Dynamics (CFD) simulations is synthetically generated using the turbulent digital filter method. The case studied with the numerical framework is a NACA 0012 airfoil with a chord-based Reynolds number of Rec=2×105 and an angle of attack of α=5°. The numerical simulation results are compared to high-speed particle image velocimetry (PIV) measurements performed for a NACA 0012 airfoil at the equivalent chord-based Reynolds number and turbulent inflow conditions. The CFD results of the numerical framework compare well with the experiments in terms of velocity spectra and RMS values upstream of the airfoil’s leading edge. The spectra and correlations of the velocity field generated by the turbulent digital filter demonstrate its ability to generate isotropic turbulent inflow. Instantaneous velocity fields show that the airfoil suppresses large-scale turbulent structures of the incoming turbulent flow. The size of the incoming turbulent structures decreases as they approach the leading edge due to the presence of the airfoil. The pre-multiplied spectra of the different velocity components show that downstream of the airfoil’s leading edge, the turbulent structures are stretched in the streamwise direction. The streamwise turbulent integral length scales and the velocity RMS values upstream of the airfoil’s leading edge indicate that the velocity components most affected by distortion are the streamwise and wall-normal components.

Performance characterization of a laminar gas inlet

Abstract. Aircraft-based measurements enable large-scale characterization of gas-phase atmospheric composition, but these measurements are complicated by the challenges of sampling from high-speed flow. Under such sampling conditions, the sample flow will likely experience turbulence, accelerating and mixing of potential contamination of the gas-phase from the condensed-phase components on walls, and reduced vapor transmission due to losses to the inner walls of the sampling line. While a significant amount of research has gone into understanding aerosol sampling efficiency for aircraft inlets, a similar research investment has not been made for gas sampling. Here, we analyze the performance of a forward-facing laminar flow gas inlet to establish its performance as a function of operating conditions, including ambient pressure, freestream velocities, and sampling conditions. Using computational fluid dynamics (CFD) modeling we simulate flow inside and outside the inlet to determine the extent of freestream turbulent interaction with the sample flow and its implication for gas sample transport. The CFD results of flow features in the inlet are compared against measurements of air speed and turbulent intensity from full-sized high-speed wind tunnel experiments. These comparisons suggest that the Reynolds-averaged Navier–Stokes (RANS) CFD simulations using the shear stress transport (SST) modeling approach provide the most reasonable prediction of the turbulence characteristics of the inlet.

Modeling and CFD simulation of photocatalytic removal of tetracycline by ZnO/PbBiO2Cl nanocomposite catalyst

In this work, the photocatalytic degradation process under visible light in a batch photoreactor was investigated using computational fluid dynamics (CFD). The removal of tetracycline (TC) by the ZnO/PbBiO2Cl photocatalyst was modeled using the single organic species model based on Langmuir-Hinshelwood kinetics. In addition, the hydrodynamic behavior of the two-phase flow inside the photoreactor was simulated using the Eulerian-Lagrangian approach. In this study, the kinetic of the degradation reaction, velocity field of suspension, and concentration of TC were investigated. Based on the CFD results, it has been determined that a rotational velocity of 250 rpm in the reactor is the optimal speed that leads to the highest homogeneity (approximately 95 %) in suspension. Therefore, more light is absorbed by performing experiments in high-quality mixing, and maximum degradation can be achieved. The kinetic study showed that the degradation rate follows pseudo-first-order kinetics. The effect of different weight percentages of PbBiO2Cl and various loading of ZnO/PbBO2Cl on the degradation rate was also examined. The results showed that the 0.5 g/l of ZnO/PbBO2Cl (40 %) is the optimal amount. The degradation reaction kinetic constant was also calculated about 200 × 10−4 min−1. Finally, the obtained modeling results demonstrate excellent agreement with the experimental data.

Fast reconstruction of boiler numerical physical field based on proper orthogonal decomposition and conditional deep convolutional generative adversarial networks

ABSTRACT Obtaining real-time physical field data inside the boiler furnace is crucial for combustion diagnostics and optimization. In this work, we propose a fast reconstruction technique for the physical fields in a tangentially-fired coal boiler. The method combines the Proper Orthogonal Decomposition (POD) and Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) based on the boiler physical field obtained by computational fluid dynamics (CFD). Firstly, CFD simulations are performed using data from the boiler Distributed Control System (DCS). After verifying the CFD results, we expanded the simulation to 105 operational condition cases sample sets. Then, the physical fields of the sample set undergo POD to determine the appropriate number of POD bases, thereby ensuring the accuracy of the reconstruction. Finally, the cDCGAN method is employed to establish the correlation between the POD bases and the operational conditions of the boiler. Results show that the POD-cDCGAN method achieves rapid and accurate reconstruction of temperature and velocity fields, with mean relative error (MRE) below 1.5% and root relative squared error (RRSE) below 5.7%. The reconstruction time is reduced to 10.57s, significantly faster than direct CFD methods. The POD-cDCGAN method offers an efficient approach for online operational diagnosis and digital twin construction of boiler equipment.

A novel framework for predicting active flow control by combining deep reinforcement learning and masked deep neural network

Active flow control (AFC) through deep reinforcement learning (DRL) is computationally demanding. To address this, a masked deep neural network (MDNN), aiming to replace the computational fluid dynamics (CFD) environment, is developed to predict unsteady flow fields under the influence of arbitrary object motion. Then, a novel DRL-MDNN framework that combines the MDNN-based environment with the DRL algorithm is proposed. To validate the reliability of the framework, a blind test in a pulsating baffle system is designed. Vibration damping is considered to be the objective, and a traditional DRL-CFD framework is constructed for comparison. After training, a spatiotemporal evolution of 200 time steps under the influence of arbitrary object motion is predicted by the MDNN. The details of the flow field are compared with the CFD results, and a relative error within 5% is achieved, which satisfies the accuracy of serving as an interactive environment for DRL algorithms. The DRL-MDNN and traditional DRL-CFD frameworks are then applied to the pulsating baffle system to find the optimal control strategy. The results indicate that both frameworks achieve similar control performance, reducing vibration by 90%. Considering the resources expended in establishing the database, the computational resource consumption of the DRL-MDNN framework is reduced by 95%, and the interactive response time during each episode is decreased by 98.84% compared to the traditional DRL-CFD framework.