Mixing Performance Research Articles

Improvement of mixing efficiency in twisted micromixers: The impact of cross-sectional shape and eccentricity ratio

Microfluidic mixers with twisted geometries show promise for high mixing efficiency, especially at elevated flow rates. However, there is a lack of understanding regarding the optimal geometrical parameters to enhance mixing across various Reynolds numbers. This study aimed to explore the influence of pitch number, cross-section geometry, and eccentricity ratio on the performance of the twisted micromixer. The flow field in these micromixers was solved numerically and the mixing index and pressure drop were calculated for Reynolds numbers of 1 to 400. Twisted micromixers with rectangular cross-sections and aspect ratios of 0.5 and 2 outperformed those with square cross-sections by up to 34% in mixing efficiency, exceeding 90% efficiency for Reynolds numbers from 1 to 400. Moreover, the eccentricity ratio (ER) was studied for the first time in twisted micromixers in this study and demonstrated a critical role in improving the mixing performance. For low to intermediate Reynolds numbers, the highest ER of 0.75 showed the best performance, while for high Reynolds numbers, an ER of 0.5 was optimal. These insights offer valuable direction for designing high-performance micromixers for advanced microfluidic systems.

Analyzing Homogeneity of Highly Viscous Polymer Suspensions in Change Can Mixers.

The mixing of highly viscous non-Newtonian suspensions is a critical process in various industrial applications. This computational fluid dynamics (CFD) study presents an in-depth analysis of non-isothermal mixing performance in change can mixers. The aim of the study was to identify parameters that significantly influence both distributive and dispersive mixing in these mixers, which are essential for optimizing industrial mixing processes. The study employed a numerical design of experiments (DOE) approach to identify the parameters that most significantly influence both distributive and dispersive mixing, as measured by the Kramer mixing index (MKramer) and the Ica Manas-Zloczower mixing index λMZ¯. The investigated parameters included mixing time, number of arms, arm size ratio, revolutions per minute (RPM), z-axis rotation, z-axis movement, and initial and mixing temperatures. The methodology involved employing the bootstrap forest algorithm for predicting the mixing indices, achieving an R2 of 0.949 for MKramer and an R2 of 0.836 for λMZ¯. The results indicate that the z-axis rotation has the greatest impact on both distributive and dispersive mixing. An increased number of arms negatively impacted λMZ, but had a small positive effect on MKramer. Surprisingly, in this study, neither the initial temperature of the material nor the mixing temperature significantly impacted the mixing performance. These findings highlight the relative importance of operational parameters over traditional temperature factors and provide a new perspective on mixing science.

Trends in the incorporation of nanomaterials in asphalt binders to improve rheological properties

Asphalt binders play a significant role in the performance of pavements. The current volume of traffic and loads on highways contribute to the occurrence of damages that affect the performance and lifespan of the asphalt mix. In this context, the development of optimized materials can help reduce damages and increase the lifespan of the pavement. One way to improve asphalt performance, that is, improving rheological, mechanical, and durability properties, is by incorporating nanomaterials. Through a systematic literature review and bibliometric analysis, this study aimed to verify the recent scientific scenario on the subject, aiming to identify trends and prospect content for future work. Thus, bibliometric indexes were analyzed, and the selected articles from the systematic search were summarized, which allowed the identification of the research objectives, the incorporated materials, and their optimal contents. Additionally, the asphalt matrices used, the tests performed, and the highlights regarding mechanical and rheological gains were identified. Finally, it was concluded that the study achieved its objective, contributing to decision-making in the prospecting of themes for future research.

Geometric optimization of Kenics-type static mixers: numerical analysis of thermal and dynamic performance

Static mixers play an important role in industry by facilitating mixing and heat transfer processes. This study investigates the effect of geometry on the thermal and dynamic performance of a Kenics-type static mixer by examining four different configurations. Numerical simulations using Fluent.20 software were used to analyze parameters such as Reynolds number (ranging from 0.1 to 80), pressure drop, shear rate, fluid temperature, and Nusselt number. The results highlight the critical importance of geometry in fluid dynamics, which affects thermal performance. Among the configurations studied, the third case, characterized by three cavities occupying the entire length of the helix, proved to be the most efficient. This research thus provides valuable insights into the dynamic and thermal characteristics of kinetic static mixers, underscoring the critical importance of geometry in optimizing overall performance. What's more, this performance improvement can be observed at different Reynolds numbers, resulting in improved mixing efficiency and reduced pressure losses. This study shows that the third geometric configuration outperforms the other proposed mixers, with a performance improvement of 99%.

Enhanced particle mixing performance of liquid-solid reactor under non-periodic chaotic stirring

This paper introduces the Chebyshev non-periodic chaotic stirring speed based on chaos theory. Additionally, it constructs the DEM-VOF coupled computational model to investigate non-periodic mixing within the reactor system. Numerical calculations are employed to compare and analyze Constant Stirring Speed (CSS) with Chebyshev Non-Periodic Chaotic Stirring Speed and its reverse (CRS, CRS-R). The results indicate that the number of particles deposited at the bottom of end diffusion decreases by 54.3 %. Moreover, it samples particle concentration per unit volume, resulting in a 70.3 % decrease in the Relative Concentration Standard Deviation (RCSD) of particles. Furthermore, it quantifies the mixing effect based on the distribution of distances between particles, leading to a 20.3 % increase in the Unit Block Mixing Index (UBMI). In conclusion, this study improves particle distribution characteristics by utilizing appropriate non-periodic variable speed intervals. Additionally, it provides technical support for production scenarios involving the mixing and dispersion of multiphase non-homogeneous systems.

A Preliminary Fuzzy Inference System for Predicting Atmospheric Ozone in an Intermountain Basin

High concentrations of ozone in the Uinta Basin, Utah, can occur after sufficient snowfall and a strong atmospheric anticyclone creates a persistent cold pool that traps emissions from oil and gas operations, where sustained photolysis of the precursors builds ozone to unhealthy concentrations. The basin’s winter-ozone system is well understood by domain experts and supported by archives of atmospheric observations. Rules of the system can be formulated in natural language (“sufficient snowfall and high pressure leads to high ozone”), lending itself to analysis with a fuzzy-logic inference system. This method encodes human expertise as machine intelligence in a more prescribed manner than more complex, black-box inference methods such as neural networks, increasing user trustworthiness of our model prototype before further optimization. Herein, we develop an ozone forecasting system, Clyfar, informed by an archive of meteorological and air-chemistry measurements. This prototype successfully demonstrates proof-of-concept despite rudimentary tuning. We describe our framework for predicting future ozone concentrations if input values are drawn from numerical weather prediction forecasts rather than observations as Clyfar initial conditions. We evaluate inferred values for one winter, finding our prototype demonstrates mixed performance but promise after optimization to deliver useful forecast guidance for decision-makers when forecast data are used as input. This early version model is the basis of ongoing optimization through machine learning.

The novel inorganic solidified foam prepared by direct foaming and its characteristics for preventing spontaneous combustion of coal

ABSTRACT To mitigate coal spontaneous combustion disasters caused due to air leakage in coal mines, inorganic solidified foam is widely employed to seal these areas. This study proposes a simplified method for preparing such foam by directly foaming a mixture of water, cement, fly ash, and foaming agent. This new inorganic solidified foam plugging material aims to enhance sealing effectiveness. The research investigates the foaming ability and stability characteristics of different types of surfactants, analyzing their compatibility with cement and fly ash. It identifies that lauramidopropyl surfactant (LX) exhibits the lowest viscosity in the cement-fly ash slurry mix, resulting in superior foaming performance. By studying effects of water-cement ratio and foaming agent concentration on the foaming performance of cement-fly ash slurry mix, it is found that when the water-cement ratio is 0.6 and the foaming agent concentration is 0.5%, the foaming performance of inorganic solidified foam is optimal, yield the highest foaming efficiency with a multiple of 4.33 times and compressive strength of 0.13 MPa, effectively bonding and reinforcing fractured coal bodies to sealing air leakage cracks efficiently. This study contributes to simplifying the preparation equipment and the application processes of inorganic solidified foam, making it more suitable for widespread application in the confined spaces of coal mines, providing a new technical approach for preventing and controlling coal spontaneous combustion in mines.

Ultraselective carbon hollow fiber membrane for H2 extraction from blended natural gas

Blending hydrogen into natural gas (H2NG) pipelines is a feasible solution for low-cost hydrogen delivery while purifying H2 at end-use remains challenging due to its high pressure and low H2 concentration. Herein, biomass-derived carbon hollow fiber membranes (CHFMs) with ultrahigh H2/CH4 separation factor of 4149.0 under a simulated H2NG (10 mol% H2/90 mol% CH4) at 30 bar were reported, and the separation performance maintained within 150 h in a dynamic durability test. Furthermore, the CHFMs showed good stability under fluctuating temperature feeds (up to 100 °C). To evaluate the feasibility of the CHFMs for H2 extraction from H2NG, a three-stage membrane system was designed based on the mixed gas separation performances. It suggested that 99.99 mol% H2 can be achieved with a 90 % recovery, and the specific H2 purification cost was 0.245 $/Nm3 for a 1.8 × 105 Nm3/h production scale, which provides the possibility of hydrogen extraction from H2NG pipelines.

Mass transfer and mixing performance in jet-to-counterflow micromixer

As an important component of the fine organic microreaction system, micromixers can realize efficient mixing of different fluids within a short distance. In spite of great progress in micromixer design for high mixing performance over the last decade, micromixers are limited by the narrowness of channels, making it impossible to operate at high throughputs. Here, we propose a novel jet-to-counterflow (JTC) micromixer, which is based on the offset fluctuation jet mechanism to build a jet-to-counterflow zone and an annular liquid film zone to promote the rapid and efficient mixing of fluids. Micro-PIV and dye visualization experiments are used to investigate the internal flow behaviors and mixing performance of the JTC micromixer. The results show that in the “jet-to-counterflow mixing zone”, the jet undergoes the transition of three flow regimes i.e. “no offset jet − stable offset jet − fluctuating offset jet” with the increase of Re under the effects of wall effect and fluid inertia. When Re = 100, the fluctuating offset jet enhances the internal perturbation, which promotes the mixing index of the micromixer within 3 mm up to 78 %. In addition, the fluctuating offset jet intensifies the disturbance of the fluid flow in the annular liquid film zone, which further enhances the fluid mixing. A mixing efficiency of 97 % is achieved in mixing experiments over flow rates ranging from 0.075 – 37.66 mL/min−1. Our results demonstrate that fluctuating offset jet can be used to enhance microfluidic internal perturbation and mixing, which provide new insights into the design of novel micromixers.

Towards Low NOx Emissions Performance of A 65KW Recuperated Gas Turbine Operated on 100% Hydrogen

Abstract This work supports the development of a low NOx emission 65 kW natural gas turbine capable of operating on 100% hydrogen. This gas turbine has been demonstrated to operate from cold start to full load on up to 30% hydrogen mixed into natural gas with single digit ppm NOx emissions. To reach operation on 100% hydrogen, injectors specifically designed to 1) avoid challenges with flashback and 2) be field retrofittable were developed and tested. Successful operation of the engine from cold start to full load on 100% hydrogen was demonstrated. To support the development, a chemical reactor network (CRN) is used in conjunction with experimental injector mixing characterization. A strategy to account for variation in mixing performance was developed and utilized with the CRN to connect NOx emissions to the injector mixing performance. Measured fuel concentration profiles and the CRN model was used to infer the effects of mixing on NOx emission. The results illustrate how NOx emissions are directly influenced by local fuel rich regions found at the injector outlet. The CRN model can thus be used to screen injector designs and infer NOx performance and will be used to guide the development of injectors for hydrogen that can attain desired fuel distributions, concentrations, and velocities. The results affirm the direction needed to attain improved mixing and to operate at overall leaner conditions made possible by the stabilizing features inherent to hydrogen.

A study of particle motion in Kwerk-type twisted blades: Effect of configuration on particle mixing performance by CFD–DEM

Static mixers could promote the particle mixing in industries. Experimental and numerical investigations of particle mixing and flow characteristics in the riser with static mixers are carried out. The instantaneous microscopic characteristics and energy loss in Kwerk-type static mixer (K-KSM) are evaluated by Computational Fluid Dynamics coupled with Discrete Element Method (CFD–DEM). A more suitable calculation method is proposed, which utilizes particle coordinates and the coordination number of central particles to calculate the instantaneous mixing degree of particles (PK). The PK, Residence Time Distribution (RTD) and collision correlation are analyzed at different superficial gas velocities (Ug) and mass flow rates (Ms). The results show that the performance of K-KSM is superior to that of KSM under current conditions. Back mixing and aggregation phenomena are eliminated at Ug > 5 m/s and Ms < 1.73 g/s, and the recommended regimes are Ug ≥ 6.0 m/s and Ms < 1.5 g/s.

A novel static mixer for blending hydrogen into natural gas pipelines

A novel static mixer is designed specifically to blend hydrogen into natural gas pipelines, and its effectiveness is validated by numerical simulation method. Firstly, the structural model of the proposed static mixer model for hydrogen-methane blending is introduced, and the evaluation indicators are defined. Secondly, the computational fluid dynamic model for the mixing process is established based on the Large Eddy Simulation(LES) method, and the accuracy of the numerical results is validated against the experimental data of a benchmark gas mixing model. Subsequently, using LES, effects structural parameters (angle and height of trapezoidal baffle, number of mixing elements, and spacing and installation distance of mixing elements) and flow parameters (main flow velocity and hydrogen blending ratio) on the mixing homogeneity and pressure drop of the static mixer are investigated systematically to explore the optimal design and operational conditions. The numerical results showed that the static mixer can significantly improve the mixing efficiency of hydrogen and natural gas with acceptable pressure loss. In the range of flow conditions concerned, a best performance of mixing could be obtained by installing the mixer at a distance of 3D (D is the diameter of the natural gas pipeline) downstream the blending point, setting the spacing between mixing elements as 1D and employing four mixing elements. Finally, the underlying physics of mass transportation are analyzed based on the vortex structures generated by the mixer.

A comprehensive study on active mixer performance using liquid metal droplets: an experimental approach

In this experimental study, we delve into the performance of an active mixer that utilizes liquid metal droplets. Our mixer configuration follows an innovative Y-type design, where two liquid metal-based pumping mechanisms operate within the minichannel inlet branches. By applying alternating current voltage to both sides of the liquid metal, we induce a surface tension gradient, propelling the fluid from the reservoirs toward the minichannel. Notably, the two entering liquids are distinctly colored, allowing us to quantify mixing using a Mixing Index (MI) definition and image processing techniques. Our investigation centers on four key variables governing mixer performance: applied voltage, liquid metal droplet diameter, input angle between the branches, and minichannel width. Given the experimental nature of our research, we employ a central composite design method within the framework of design of experiments (DoE). From our obtained experimental results, we establish correlations between MI and the other variables. Our examination of the four mentioned parameters revealed that liquid metal droplet diameter exerts the most significant influence on the mixing index. Following this, in descending order of impact, we find applied voltage, input angle, and channel width. In the optimal dimensions of our mixer, we achieve a remarkable maximum MI of 0.867.

Development and evaluation of mixing performance of new type pitched paddle impeller (HR1000) for wastewater treatment

AbstractSATAKE MultiMix Corporation developed a new type of pitched paddle impeller for low power consumption turbulent mixing for wastewater treatment and its performance was evaluated by measuring power consumption, mixing time, and particle suspension. The power number of the new impeller was lower than that of the existing pitched paddle, which could be constructed by modifying the correlation equation. For the same power consumption per unit volume, the mixing performance was almost the same as that of other axial flow impellers. The particle suspension performance was also the same as that of other axial flow impellers.

Jet mixing optimization using a flexible nozzle, distributed actuators, and machine learning

In this paper, we introduce the first jet nozzle allowing simultaneous shape variation and distributed active control, termed “Smart Nozzle” in the sequel. Our Smart Nozzle manipulates the jet with an adjustable flexible shape via 12 equidistant stepper motors and 12 equidistantly placed inward-pointing minijets. The mixing performance is evaluated with a 7 × 7 array of Pitot tubes at the end of the potential core. The experimental investigation is carried out in three steps. First, we perform an aerodynamic characterization of the unforced round jet flow. Second, we investigate the mixing performance under five representative nozzle geometries, including round, elliptical, triangular, squared, and hexagonal shapes. The greatest mixing area is achieved with the square shape. Third, the symmetric forcing parameters are optimized for each specified nozzle shape with a machine learning algorithm. The best mixing enhancement for a symmetric active control is obtained by the squared shape, which results in a 1.93-fold mixing area increase as compared to the unforced case. Symmetrically unconstrained forcing achieves a nearly 4.5-fold mixing area increase. The Smart Nozzle demonstrates the feasibility of novel flow control techniques that combine shape variation and active control, leveraging the capabilities of machine learning optimization algorithms.

Evaluation of surface texturing on chrome-coated cylinder liners via deterministic mixed lubrication simulation

This study investigates the mixed lubrication performance of various surface texture configurations in the piston ring/cylinder liner conjunction of a two-stroke internal combustion engine using a deterministic mixed lubrication model. The numerical model simultaneously solves the Reynolds equation with mass-conserving cavitation to calculate inter-asperity hydrodynamic pressures and an elastic, perfectly plastic, rough contact model to determine contact pressures at each asperity interaction. Gaussian Mixture Model clustering was employed to enhance surface characterization. The deterministic simulation approach considers the full-scale representation of the cylinder liner topography to accurately capture the influence of surface features on the hydrodynamic support and friction under mixed lubrication conditions. The investigated cylinder liners were initially hard-chrome-coated and honed, resulting in a stochastic arrangement of surface pores, and then deterministic patterns of surface pockets were created by micro electrodischarge machining (EDM). Surface measurements were performed using laser interferometry, providing input for the mixed lubrication simulations. The study also explored the virtual removal of ridges formed around the pockets by the EDM technique. Key findings indicate that the stochastic texture outperformed the hybrid texture (stochastic + deterministic) in the boundary and mixed lubrication regimes, showing higher hydrodynamic support at low separations but increased hydrodynamic shear stresses at higher speeds. Conversely, deterministic textures exhibited a significant decrease in average hydrodynamic shear stress at high velocities. These results highlight the critical role of surface texture in tribological behavior and suggest that localized textures on cylinder liners can potentially optimize engine performance. The study recommends further exploration of a broader range of texture geometries, densities, and distribution patterns to enhance engine design strategies.

Effects of axisymmetric confinement on vortical structures emanating from round turbulent jets

Confined jets occur in many engineering applications including combustion chambers, jet pumps, and chemical reactors. The effects of axisymmetric confinement on the vortical structures identified in a turbulent jet are investigated using large eddy simulation at a Reynolds number of 30 000 (based on nozzle exit conditions) and expansion ratio (chamber-to-nozzle diameter ratio) of five. The results obtained from the confined jet are compared with those of a free jet under the same nozzle exit flow conditions. A prominent recirculation zone forms between the expanding jet and the confining wall, resulting in early shear layer distortion and a shorter interaction length in the confined jet (0.85 jet diameters) compared to the free jet (1.15 jet diameters). Using the λ2 criterion for vortex identification, two dominant structural modes are identified in the near-exit region of the free jet: ring and helical modes. However, in the confined jet, the helical mode is absent, and the turbulent confined fluid accelerates the breakup of the ring vortices. The interaction of the secondary line vortices with the breaking structures leads to the formation of new hairpin-like vortices, which also contribute to further vortex breakup. These results explain the enhanced mixing performance of confined jets as the mixing is directly tied to the breakup of large vortical structures. Proper orthogonal decomposition modes are also presented to identify the structures/events with the highest contribution to the total turbulent kinetic energy in both flow fields.

Numerical simulation study of liquid–liquid mixing of high-viscosity fluids under laminar flow in a reverse flow multi-stage Tesla valve

In this study, computational fluid dynamics was employed to conduct a numerical simulation of the mixing performance and flow characteristics of two highly viscous liquids under laminar flow conditions within a reversed Tesla valve. Scalar transport techniques are employed to analyze the efficiency of liquid–liquid mixing in high-viscosity fluids. The focus of this study is to investigate the optimal mixing behavior between different parameters. Results indicate that an increase in Reynolds number leads to intensified Dean vortices, thereby promoting liquid–liquid mixing efficiency. Additionally, the mixing coefficient shows a negative correlation with Schmidt number (Sc), with a diminishing impact on the mixing coefficient when Sc ≥ 104. This is attributed to the dominance of fluid flow in controlling mixing within the channel at higher Schmidt numbers. Furthermore, this study compares the influence of valve angles (α) and stage numbers (n) on the mixing coefficient under identical Reynolds and Schmidt number conditions. As the number of Tesla valve stages increases, fluid acceleration within the pipeline is enhanced. Moreover, larger valve angles result in increased lengths of the curved section, leading to higher mixing efficiency. Therefore, to enhance mixing efficiency, it is recommended to increase the valve angle and the number of stages in the Tesla valve.

Characterization of chaotic mixing effects in hydrometallurgical leaching process based on deep learning

Traditional stirring methods in the wet metallurgy leaching process suffer from low efficiency, high consumption, and low output, leading to increased production costs and energy consumption. Therefore, this study evaluates reactor performance using deep learning and introduces variable-speed stirring to enhance laminar mixing and reduce stirring reactor power consumption. An S-Type acceleration and deceleration control algorithm is constructed to ensure that stepper motors do not experience step loss, stalling, or overshoot when the frequency changes abruptly. A deep learning tracking model based on dual cameras is established to dynamically track tracer particles inside the stirring reactor, and a Euclidean distance evaluation method is proposed to characterize and evaluate the mixing performance of the stirring reactor. Experimental results demonstrate that the use of complex function variable-speed stirring and shortening the variable-speed cycle both contribute to improving mixing efficiency. Under a variable-speed cycle of 5 seconds, chaotic speed increases mixing efficiency by 53.1% compared to constant speed. This study provides a theoretical basis for optimizing the wet metallurgy leaching process.

Mathematical model of the process of mixing semi-liquid feeds in a device with a propeller

The article considers the issues of using a propeller apparatus for mixing semi-liquid feed mixtures in a mixer with an eccentrically positioned working body in the form of a propeller (screw). Until now, when studying the mixing process, little attention has been paid to the transporting ability of the working body in the form of a propeller agitator. When preparing wet mixtures, agitators with a vertically positioned shaft, which is located in the center of a vertical cylindrical tank, are widely used. When installing the working body horizontally, the propeller having a pumping effect (axial movement), can be used not only for mixing, but also for unloading the finished feed mixture, as well as moving it through pipes over short distances. The existing models of the mixing process do not take into account its stochastic nature. Methods of mathematical description of mixing processes considering the prevailing axial movement of the flow are scarcely developed. The proposed mathematical models make it possible to determine the mixer's performance and the required mixing power. The research was aimed at increasing the effectiveness of preparing a feed mixture in a horizontal mixer of propeller type with an eccentrically positioned working body (screw) and saving energy costs along with raising the productivity. The object of the study was a mixing chamber with eccentrically located working bodies of various diameters (0.2, 0.25 and 0.35 m). During the experiments, the productivity required to drive the motor shaft was determined. It has been experimentally established that increasing the agitator rotation speed from 200 to 400 min-1 with a propeller diameter from 0.2 to 0.35 m and a feed mixture humidity of 84 % leads to an increase in power consumption to 3.5 kW and mixer productivity to 12 m3/h, and the degree of uniformity of feed mixtures is up to 98 %.