Multiphase CFD Modelling of Mineral Separators Performance: Validation Against Tomography Data

The objective of this work is to use electrical resistance tomography (ERT) and computational fluid dynamic (CFD) modeling to investigate the flow field generated by a Scaba 6SRGT impeller in the agitation of the xanthan solution, as a pseudoplastic fluid with yield stress. ERT provides a non-destructive technique to measure, in three dimensions, the concentration fields inside the mixing tanks. Using ERT, the impeller flow pattern, the dimensions of the cavern formed and the mixing time in the agitation of xanthan solutions were evaluated. The sizes of cavern measured using ERT were in good agreement with that calculated using Elson's model (cylindrical model). ERT provides both overall mixing time using 1264 probes (316 probes for each plan) and local mixing time using 4 selected probes or pixels. The dimensionless mixing times obtained from ERT were correlated well with the Moo-Young correlation, confirming that increased impeller speeds decreases the mixing times. The 3D flow field generated by a Scaba 6SRGT impeller and tracer homogenization in the agitation of xanthan gum were also simulated using the commercial CFD package (FLUENT). The experimental torque measurements were used to validate the numerical simulations. The validated CFD model provided useful information regarding the impeller pumping capacity and flow pattern, the velocity profiles, the formation of cavern around the impeller, and the mixing time. CFD results show good qualitative as well as quantitative agreement with the experimental results and theory. The sizes of cavern measure using CFD were in good agreement with that calculated using Elson's model. The local mixing times predicted from CFD simulations agreed well with literature in a way that mixing times varied inversely with the cube root of the power consumed per unit volume of the solution. CFD under predicted the local mixing times measured using ERT by 11-47%.

Drag models, solids concentration and velocity distribution in a stirred tank

Aerated stirred vessels are commonly employed to enhance gas dispersion. However, the associated high energy consumption is a challenging feature, particularly when dealing with complex non‐Newtonian fluids. Coaxial mixers comprising a central impeller and a close‐clearance impeller have emerged as an energy‐efficient alternative that effectively intensifies gas dispersion. Hence, the objective of this study is to investigate the effect of aeration and agitation on the gas dispersion effectiveness of a coaxial mixer containing a yield‐pseudoplastic fluid. An anchor‐pitched blade turbine was employed to disperse air into a 1 wt.% xanthan gum solution, and the analysis primarily focused on characterizing the gas holdup and fluid flow behaviour. Gas holdup data were obtained experimentally using electrical resistance tomography (ERT), while computational fluid dynamics (CFD) simulations provided a detailed analysis of fluid flow patterns within the coaxial mixer. The rotational speed of the impeller exhibited a non‐monotonic effect on the gas holdup, and a significant influence of the interaction between variables was identified. For instance, the experimental data showed that the aeration effect varied with the anchor speed. Nevertheless, the variables' interaction effect was explained by the change in flow pattern observed numerically. Furthermore, the CFD results demonstrated that high gas holdup does not necessarily indicate intensified mixing. Therefore, combining experimental data and numerical simulations enables a more accurate characterization of mixing performance. These findings contribute to the understanding and improvement of mixing performance in such a complex system, which is crucial for designing efficient operations.

Scale-up strategy for bubble column slurry reactors using CFD simulations

While designing the power requirements of a ship, the most important factor to be considered is the ship resistance, or the sea drag forces acting on the ship. It is important to have an estimate of the ship resistance while designing the propulsion system since the power required to overcome the sea drag forces contribute to ‘losses’ in the propulsion system. There are three main methods to calculate ship resistance: Statistical methods like the Holtrop-Mennen (HM) method, numerical analysis or CFD (Computational Fluid Dynamics) simulations, and model testing, i.e. scaled model tests in towing tanks. At the start of the design stage, when only basic ship parameters are available, only statistical models like the HM method can be used. Numerical analysis/ CFD simulations and model tests can be performed only when the complete 3D design of the ship is completed. The present paper aims at predicting the calm water ship resistance using CFD simulations, using the Flow-3D software package. A case study of a roll-on/roll-off passenger (RoPax) ferry was investigated. Ship resistance was calculated at various ship speeds. Since the mesh affects the results in any CFD simulation, multiple meshes were used to check the mesh sensitivity. The results from the simulations were compared with the estimate from the HM method. The results from simulations agreed well with the HM method for low ship speeds. The difference in the results was considerably high compared to the HM method for higher ship speeds. The capability of Flow-3D to perform ship resistance analysis was demonstrated.

This study addresses a critical challenge faced by the oil and gas industry: erosion of sand control screens used in well production operations. The objective is to evaluate sand screen erosion rates through experimental testing and computational modeling, with the goal of establishing practical solutions for improving sand screen performance and creating production plans that increase longevity. By examining erosion behavior under realistic conditions, this study aims to enhance the industry's ability to predict and manage sand screen erosion-related failures in harsh environments. Erosion testing was conducted on wire-wrap sand screen coupon samples with sand slurry approach velocities between 1.2 ft/s and 2.0 ft/s to simulate aggressive production conditions. Three measurement techniques, optical microscopy, maximum particle passed (MPP), and filter cut point (FCP), were used to assess sand screen gap changes before and after erosion. Additionally, computational fluid dynamics (CFD) simulations, incorporating the Discrete Phase Model (DPM), were performed to replicate the experimental conditions, capturing fluid flow dynamics, particle tracking, and erosion mechanisms. The CFD model was calibrated against experimental data to improve accuracy and refine erosion predictions. This combined approach enhances the assessment of erosion behavior and enables more reliable predictions of sand screen performance in harsh well environments that cannot be economically replicated in a laboratory. Experimental results showed predictable differences in erosion rates and screen gap expansion across different measurement methods. Optical microscopy and MPP exhibited agreement, while comparatively, FCP underestimated erosion, though all methods were found to have valuable insights. CFD simulations successfully captured the erosion trends observed in testing. The results indicate that experimental testing remains critical for accurate erosion assessment, while CFD provides valuable insights into erosion patterns and influencing factors. Trends suggest that screen erosion is influenced by factors such as particle concentration, flow velocity, and base pipe hole configurations, highlighting the importance of choosing an optimized screen design for each well application. This study provides a unique combination of experimental testing and CFD analysis to evaluate erosion in sand control screens, offering a more comprehensive understanding of erosion mechanisms. The findings contribute to the industry by validating a computational erosion prediction model that can be used while also identifying the limitations of both the model and current screen gap measurement techniques. This research enhances predictive capabilities for sand screen performance.

The hydrodynamics involved with the rise of air bubbles in shear‐thinning non‐Newtonian liquids in bubble columns was investigated using computational fluid dynamics (CFD). In bubble columns, the bubble size distribution (BSD) and gas holdup significantly affect the mass transfer rates and the reactor design. Consequently, the influence of superficial gas velocity, flow index, consistency index, sparger bubble size, and yield stress were analyzed on a local and global scale. The bubble sizes and the coalescence and breakage phenomena were incorporated using the homogeneous discrete method of the population balance model (PBM). The bubbles underwent coalescence during ascent and exhibited bimodal distribution. The radial homogeneity of the gas phase increased axially. Moreover, the zones of low liquid dynamic viscosity produced zones of a high gas holdup. Though the dual effect of viscosity on gas holdup was non‐existent, the gas holdup surged after 35.1 mPa s at the mid‐zone and remained constant thereafter. The noteworthy differences in simulation results put further emphasis upon the importance of sparger bubble size in CFD modelling. A decrease in the overall gas holdup and the axial air velocity with yield stress was observed. CFD simulation proved capable of providing results in reasonable agreement with experiments.

Optimization methods have been widely applied to the aerodynamic design of gas turbine blades. While applying optimization to high-fidelity computational fluid dynamics (CFD) simulations has proven capable of improving engineering design performance, a challenge has been overcoming the prolonged run-time due to the computationally expensive CFD runs. Reduced-order models and, more recently, machine learning methods have been increasingly used in gas turbine studies to predict performance metrics and operational characteristics, model turbulence, and optimize designs. The application of machine learning methods allows for utilizing existing knowledge and datasets from different sources, such as previous experiments, CFD, low-fidelity simulations, 1D or system-level studies. The present study investigates inserting a machine learning model that utilizes such data into a high-fidelity CFD driven optimization process, and hence effectively reduces the number of required evaluations of the CFD model. Artificial Neural Network (ANN) models were trained on data from over three thousand two-dimensional (2D) CFD analyses of turbine blade cross-sections. The trained ANN models were then used as surrogates in a nested optimization process alongside a full three-dimensional Navier–Stokes CFD simulation. The much lower evaluation cost of the ANN model allows for tens of thousands of design evaluations to guide the search of the best blade profiles to be used in the more expensive, high-fidelity CFD runs, improving the progress of the optimization while reducing the required computation time. It is estimated that the current workflow achieves a five-fold reduction in computational time in comparison to an optimization process that is based on three-dimensional (3D) CFD simulations alone. The methodology is demonstrated on the NASA/General Electric Energy Efficient Engine (E3) high pressure turbine blade and found Pareto front designs with improved blade efficiency and power over the baseline. Quantitative analysis of the optimization data reveals that some design parameters in the present study are more influential than others, such as the lean angle and tip scaling factor. Examining the optimized designs also provides insight into the physics, showing that the optimized designs have a lower amount of pressure drop near the trailing edge, but have an earlier onset of pressure drop on the suction side surface when compared to the baseline design, contributing to the observed improvements in efficiency and power.

The work described here concentrates on under-expanded, axisym-metric turbulent jets issuing into quiescent conditions. Under-expanded turbulent jets are applicable to most aircraft propulsion applications that use convergent nozzles. Experimental studies used laser doppler velocimetry (LDV) and pitot probe measurements along the jet centreline. These measurements were made for two nozzle pressure ratios (2·5 and 4·0) and at various streamwise positions up to 10 nozzle diameters downstream of the nozzle exit plane. A computational fluid dynamics (CFD) model was developed using the Fluent code and utilised the RNG K-ε two-equation turbulence model. A mesh resolution of approximately one hundredth of nozzle exit diameter was found to be sufficient to establish a mesh independent solution.Comparison of the jet centreline axial velocity (LDV data) and pressure ratio (pitot probe data) showed good agreement with the CFD model. The correct number of shock cells had been predicted and the shock strength agreed well between the experiments and numerical model. The CFD model was, however, found to over-predict the shock cell length resulting in a longer supersonic core. There was some evidence, based on analysis of the LDV measurements that indicates the presence of swirl and jet unsteadiness, which could contribute to a shortening of the shock cell length. These effects were not modelled in the CFD. Correlation between the LDV and pitot probe measurements was generally good, however, there was some evidence that probe interference may have caused the premature decay of the jet. Overall, this work has indicated the good agreement between a CFD simulation using the RNG k-ε turbulence model and experimental data when applied to the prediction of the flowfield generated by under-expanded turbulent jets. The suitability of the LDV technique to jet flows with velocities up to 500ms-1has also been demonstrated.

Computational fluid dynamics (CFD) models are powerful computational tools to simulate urban-landscape scale atmospheric dispersion events. They are proven to be very useful for security management and emergency response. Essential inputs to CFD models include landscape characteristics, which are often captured by various GIS data layers. While it is logical to couple GIS and CFD models to take advantage of available GIS data and the visualization and cartographic rendering capabilities of GIS, the integration of the two tools have been minimal. In this paper, we took the first step to evaluate the use of GIS data in CFD modeling. Specifically, we explore how efficient is to use GIS data in CFD models and how sensitive the CFD results are to different GIS data formats. Using campus topography and building data, and the FEFLO-URBAN CFD model, we performed atmospheric release simulations using topographic data in contour and raster formats. We found that using raster format was quite efficient and contour data required significant effort. Though the simulation outputs from the two data formats were not identical, their overall outcomes were similar and did not post alarming discrepancies. We concluded that using GIS data have tremendous potential for CFD modeling.

A liquid-gas two-phase computational fluid dynamics (CFD) model was developed to simulate flow field and gas hold-up in a pilot-scale oxidation ditch (OD). The volume of fluid (VOF) model and the mass flow inlet boundary condition for gas injection were introduced in this model. The simulated values of the flow velocities and the gas hold-up were verified by experimental measurements in the pilot-scale OD. The results showed that the gas hold-up at test-site 3, immediately downstream of the surface aerator, was the highest among all three test-sites. Most of the gas existed in the upper portion of the ditch and was close to the inner side of the channel. Based on the liquid-gas two-phase CFD model, three operating conditions with different setting height ratios of the submerged impellers were simulated. The simulated results suggested that the setting heights of the submerged impellers have significant impacts on the flow velocity distribution. Lowering the setting height could increase the flow velocity in the pilot-scale OD. An optimal setting height ratio of 0.273 was proposed, which would be beneficial for minimizing sludge sedimentation, especially near the inner side of the curve bend.

The hydrodynamics of gas-liquid two-phase flow in a single-use bioreactor were investigated in detail both experimentally and numerically. Electrical resistance tomography (ERT) and dynamic gas disengagement (DGD) combined with computational fluid dynamics (CFD) were employed to assess the effect of the volumetric gas flow rate and impeller speed on the gas-liquid flow field, local and global gas holdup values, and Sauter mean bubble diameter. From the results obtained from DGD coupled with ERT, the bubble sizes were determined. The experimental data indicated that the total gas holdup values increased with increasing both the rotational speed of impeller and volumetric gas flow rate. Moreover, the analysis of the flow field generated inside the aerated stirred bioreactor was conducted using CFD results. Overall, a more uniform distribution of the gas holdup was obtained at impeller speeds≥100rpm for volumetric gas flow rates≥1.6×10-5m3/s.

During the Coronavirus disease 2019 pandemic, short-range virus transmission has been observed to have a higher risk of causing infection than long-range virus transmission. However, the roles played by the inhalation and large droplet routes cannot be distinguished in practice. A recent analytical study revealed the predominance of short-range inhalation over the large droplet spray route as causes of respiratory infections. In the current study, short-range exposure was analyzed via computational fluid dynamics (CFD) simulations using a discrete phase model. Detailed facial membranes, including eyes, nostrils, and a mouth, were considered. In CFD simulations, there is no need for a spherical approximation of the human head for estimating deposition nor the “anisokinetic aerosol sampling” approximation for estimating inhalation in the analytical model. We considered two scenarios (with two spheres [Scenario 1] and two human manikins [Scenario 2]), source-target distances of 0.2 to 2 m, and droplet diameters of 3 to 1,500 µm. The overall CFD exposure results agree well with data previously obtained from a simple analytical model. The CFD results confirm the predominance of the short-range inhalation route beyond 0.2 m for expiratory droplets smaller than 50 µm during talking and coughing. A critical droplet size of 87.5 µm was found to differentiate droplet behaviors. The number of droplets deposited on the target head exceeded those exposed to facial membranes, which implies a risk of exposure through the immediate surface route over a short range.Electronic Supplementary Material (ESM)the Supplementary Materials are available in the online version of this article at 10.1007/s12273-022-0968-y.

A “credible” computational fluid dynamics (CFD) model has the potential to provide a meaningful evaluation of safety in medical devices. One major challenge in establishing “model credibility” is to determine the required degree of similarity between the model and experimental results for the model to be considered sufficiently validated. This study proposes a “threshold-based” validation approach that provides a well-defined acceptance criteria, which is a function of how close the simulation and experimental results are to the safety threshold, for establishing the model validity. The validation criteria developed following the threshold approach is not only a function of Comparison Error, E (which is the difference between experiments and simulations) but also takes in to account the risk to patient safety because of E. The method is applicable for scenarios in which a safety threshold can be clearly defined (e.g., the viscous shear-stress threshold for hemolysis in blood contacting devices). The applicability of the new validation approach was tested on the FDA nozzle geometry. The context of use (COU) was to evaluate if the instantaneous viscous shear stress in the nozzle geometry at Reynolds numbers (Re) of 3500 and 6500 was below the commonly accepted threshold for hemolysis. The CFD results (“S”) of velocity and viscous shear stress were compared with inter-laboratory experimental measurements (“D”). The uncertainties in the CFD and experimental results due to input parameter uncertainties were quantified following the ASME V&V 20 standard. The CFD models for both Re = 3500 and 6500 could not be sufficiently validated by performing a direct comparison between CFD and experimental results using the Student’s t-test. However, following the threshold-based approach, a Student’s t-test comparing |S-D| and |Threshold-S| showed that relative to the threshold, the CFD and experimental datasets for Re = 3500 were statistically similar and the model could be considered sufficiently validated for the COU. However, for Re = 6500, at certain locations where the shear stress is close the hemolysis threshold, the CFD model could not be considered sufficiently validated for the COU. Our analysis showed that the model could be sufficiently validated either by reducing the uncertainties in experiments, simulations, and the threshold or by increasing the sample size for the experiments and simulations. The threshold approach can be applied to all types of computational models and provides an objective way of determining model credibility and for evaluating medical devices.

To evaluate manoeuvring performance of merchant ships, the mathematical modeling group (MMG) or computational fluid dynamics (CFD) simulations are used. However, it is difficult to use the MMG to evaluate the manoeuvring performance of fishing vessels, thus research using CFD simulations is necessary. Also, since the course-changing and turning ability is crucial in fishing operations, a rudder design suitable for fishing vessels is necessary. This study designs a rudder using National Advisory Committee for Aeronautics (NACA) airfoil sections and evaluates its manoeuvring performance. A CFD model is used to evaluate the manoeuvring performance of the fishing vessel, and turning and zig-zag tests are conducted. The effectiveness of using CFD simulations based on Reynolds averaged Navier-Stokes equations to assess the manoeuvring performance of fishing vessels was validated. No significant difference was found in the manoeuvring performance for hull forms and rudder designs for course-changing ability. However, the original hull form showed superior turning performance. Among five rudders with varying aspect ratios and shapes, the rudder with 5.5% aspect ratio had the best turning performance. Regarding the rudder design for fishing vessels, NACA airfoil was employed, and a rudder aspect ratio of 5.5% based on the immersed hull side area is recommended.