Bubble Size Measurements Research Articles

On the reliability of image analysis for bubble size distribution measurements in electrolyte solutions in stirred reactors

The translation of chemical processes from laboratory to industrial scale is crucial for the effective and sustainable implementation of new technologies. This transition presents significant challenges, particularly in multiphase systems where variations in physical chemistry can complicate scale-up efforts. A key aspect of this challenge is understanding bubble dynamics in gas-liquid systems, which are pivotal in processes such as hydrogen production and CO2 absorption. Bubble size significantly influences mass transfer rates and process efficiency, necessitating accurate measurement methods. A factorial design approach was employed to assess the sensitivity of results to key parameters. The findings provide quantitative guidelines for optimizing image analysis techniques and improving the accuracy of bubble size measurements in diverse operational conditions. This work advances the understanding of bubble dynamics in gas-liquid systems and offers practical insights for refining measurement techniques, ultimately supporting more effective scale-up of chemical processes.

The bubble size produced in a pilot HydroFloat® cell and its effects on flotation

Unlike a traditional mechanical flotation cell, Eriez’s HydroFloat® is a fluidized-bed flotation device that can recover much coarser and less liberated particles. This is a new flotation machine where the effects of parameters such as bubble size are yet to be established. To address this problem, JKMRC has built a pilot HydroFloat® rig which it deployed to a copper–gold plant in New South Wales, Australia. Tests were performed at a range of operating conditions and bubble size images were collected and analysed using a novel newly created bubble size measurement method. In conventional flotation, a finer bubble size increases flotation rates because it increases the probability of bubble-particle collision and attachment. In this pilot HydroFloat® test program, however, flotation performance was optimal at an intermediate bubble size. Using the comprehensive test program data, the operating parameters that significantly affect bubble size were established, and an empirical model to predict bubble size was developed.

Picosecond Imaging Of Bubbly Flows

Despite their ubiquity, bubbly flows are notoriously challenging to instrument. In high-void fractions, most optical measurement techniques fail due to intense scattering and occlusion. Ultrafast imaging with picosecond exposure times offers an opportunity, allowing measurements before scattering obscures the field of view. Furthermore, detecting the time of arrival of photons allows measurement of bubble sizes, even for those partially occluded. Through implementing the Optical Kerr Effect (OKE), using a 70 fs 800 nm pulsed laser and a Carbon Disulfide cell, images are acquired with an exposure of 2.9 ps. Gating these images with an optical delay stage further allows the decomposition of scenes with 33 fs time increments. Proof of concept is demonstrated by applying this approach to static scenes of submerged bubbles at low and high void fractions. The experimental temporal decomposition shows the arrival of photons that travel through different media (air, water, and glass) and those scattered within the turbid media. A new visualization is presented to display this breakdown concisely, the Temporally Tagged Shadowgraph (TTS), presenting the time of arrival with the context of position and surroundings. Bubble sizes are measured using this temporal information and through edge detection, with good agreement for single unoccluded bubbles. With polydisperse bubble plumes, time delay-based measurements tend to overestimate bubble diameter; however, this could also be due to greater uncertainty in edge detection with occlusion. This demonstrates the potential of Ultrafast Imaging when it comes to probing high-void fraction flows. By further shortening exposure times and improving the robustness of processing algorithms, the scope of applicability of this technique can be widened.

Population balance modeling-assisted prediction of oxygen mass transfer coefficients with optical measurements

Prediction of bubble size distributions (BSD) is challenging but necessary to develop a more advanced bubble population-based model for oxygen mass transfer with increased data quality while reducing the required experimental effort. In this paper, we experimentally investigated bubble sizes in a pilot-scale setup using a submersible in-situ flow-microscope. This technique enables bubble size measurements in dense bubbly flows and at airflow rates of up to 40 sL/min above the diffuser, where former measurement methods were limited to a range below 8 slpm with a comparable diffuser configuration. The data obtained were used to study coalescence and breakup behavior and to predict bubble size distributions using population balance modeling (PBM). We also investigated the prediction of the volumetric oxygen mass transfer coefficient based on measurement of bubble size at only one height in combination with PBM to provide reliable estimates of the apparent mass transfer rate with less experimental effort. A mass transfer rate estimate was obtained with deviations from the experimentally determined mass transfer rate of <10 %.

Radial bubble size distributions in a rising foam column

The diameter distribution of bubbles in foam is one of the most important features in foam-based separation processes like foam fractionation and froth flotation.In this study the bubble size at different radial positions of pneumatically produced foams without coalescence and coarsening of bubbles is investigated in a cylindrical column by employing an invasive sampling probe. It is shown that pronounced differences of the local Sauter-mean diameter of the bubbles can appear in radial direction. Oftentimes a parabolic profile with the largest mean bubble diameter in the center of the column is found. The difference of the Sauter-mean diameter between wall- and center region is in the order of up to 60%. Experiments on foams produced with different spargers, gas flow rates and liquid filling levels reveal that the actual degree of the inhomogeniety depends on the specific bubble size distribution that is produced by the sparger, and becomes more pronounced if the range of bubble diameters in the foam increases. As an explanation for the observations, hydrodynamic interactions in the liquid phase, as well as the behavior of different sized bubbles close to the liquid/foam interface are proposed.The observed existence of local differences of the bubble diameters can have a strong influence the dynamic behavior, like liquid drainage, and measurement methods of pneumatic foams. In particular it can limit the applicability of surface-based bubble size measurements.

Relation of bubble size, grade and recovery in the copper flotation systems

In recent years, studies have shown that bubble structure, which is affected by reagent types, dosages, and particle size, is closely related to flotation performance. In contrast to two-phase systems, there is very limited information regarding bubble size in three-phase systems. To this aim, we investigated the relationship between bubble size and flotation performance with two different copper ores. Firstly, the surface tension and bubble size measurements were carried out in two-phase systems with Methyl isobutyl carbinol, and Polypropylene glycol methyl ether. Then the bubble size measurements were performed in three-phase systems at laboratory and industrial scales. The results showed that surface tension decreased with higher frother amounts and higher pHs. Although remarkable decreases in bubble size were observed with increasing frother amount, a direct relationship between surface tension and bubble size was not observed. However, pH affected the behavior of the frother, resulting in smaller bubble sizes at pH 12 compared to pH 7. Similarly, the three-phase laboratory tests showed that higher amount of frother caused a reduction in the bubble size and the copper grade. Increasing the amount of collector also caused the bubble size and copper grade to decrease, but the frothers were more effective in bubble size reduction. Compared to the two-phase, in the three-phase study bubble size was notably bigger due to the presence of a collector and solid. In the plant scale, smaller bubble size and higher grade were obtained compared with the laboratory scale due to presence of cleaning circuit measurements. The froth phase properties were also affected by the ore types due to properties such as size and hydrophobicity of the various mineral species present.

Artificial neural network (ANN) modelling to estimate bubble size from macroscopic image and object features

Bubble size measurements in aerated systems such as froth flotation cells are critical for controlling gas dispersion. Commonly, bubbles are measured by obtaining representative photographs, which are then analyzed using segmentation and identification software tools. Recent developments have focused on enhancing these segmentation tools. However, the main challenges around complex bubble cluster segmentation remain unresolved, while the tools to tackle these challenges have become increasingly complex and computationally expensive. In this work, we propose an alternative solution, circumventing the need for image segmentation and bubble identification. An Artificial Neural Network (ANN) was trained to estimate the Sauter mean bubble size (D&lt;sub&gt;32&lt;/sub&gt;) based on macroscopic image features obtained with simple and inexpensive image analysis. The results showed excellent prediction accuracy, with a correlation coefficient, R, over 0.998 in the testing stage, and without bias in its error distribution. This machine learning tool paves the way for robust and fast estimation of bubble size under complex bubble images, without the need of image segmentation.

Visualizing and Evaluating Microbubbles in Multiphase Flow Applications

Accurate visualization of bubbles in multiphase flow is a crucial aspect of modeling heat transfer, mixing, and turbulence processes. It has many applications, including chemical processes, wastewater treatment, and aquaculture. A new software, Flow_Vis, based on experimental data visualization, has been developed to visualize the movement and size distribution of bubbles within multiphase flow. Images and videos recorded from an experimental rig designed to generate microbubbles were analyzed using the new software. The bubbles in the fluid were examined and found to move with different velocities due to their varying sizes. The software was used to measure bubble size distributions, and the obtained results were compared with experimental measurements, showing reasonable accuracy. The velocity measurements were also compared with literature values and found to be equally accurate.

A Multiscale Euler–Lagrange Model for High-Frequency Cavitation Noise Prediction

Abstract To simulate the microscale bubble distribution and its effect on high-frequency cavitation noise, we present a two-way transition and coupling Euler–Lagrange model. The model accounts for both cavity fission and environmental nucleation as sources of microscale bubbles, which are limited in the traditional mesh-based Euler models. We evaluate the model with the experimental data of truncated NACA0009 hydrofoil as well as the measured bubble size distributions, showing satisfactory results for velocity distribution, cavity patterns, and power law scalings of bubble size. Based on an acoustic analogy, we find that the model produces sound waves with smaller wavelengths and higher frequencies than the Euler model, which are mainly attributed to two factors: (1) microscale bubbles with high natural frequency and (2) intense multiple cavity collapse/rebound behavior. This model is promising for predicting the full-spectrum of cavitation noise.

The reionizing bubble size distribution around galaxies

ABSTRACT Lyman-alpha (Ly α) emission from galaxies is currently our most promising probe for constraining when and how reionization began, and thus when the first galaxies formed. At z &amp;gt; 7, the majority of galaxies detected with Ly α are in candidate overdensities. Here, we quantify the probability of these galaxies residing in large ionized bubbles. We create (1.6 Gpc)3 intergalactic medium (IGM) simulations: sufficient volume to robustly measure bubble size distributions around UV-bright galaxies and rare overdensities. We find ${M_{\small UV}}\lesssim -16$ galaxies and overdensities are ≳10–1000 × more likely to trace ionized bubbles compared to randomly selected positions. The brightest galaxies and strongest overdensities have bubble size distributions with highest characteristic size and least scatter. We compare two models: gradual reionization driven by numerous UV-faint galaxies versus rapid reionization by rarer brighter galaxies, producing larger bubbles at fixed neutral fraction. We demonstrate that recently observed z ∼ 7 overdensities are highly likely to trace large ionized bubbles, corroborated by their high Ly α detection rates. However, Ly α detections at z ≈ 8.7 in EGS and z = 10.6 in GN-z11 are unlikely to trace large bubbles in our fiducial model – 11 and 7 per cent probability of &amp;gt;1 proper Mpc bubbles, respectively. Ly α detections at such high redshifts could be explained by: a less neutral IGM than previously expected; larger ionized regions at fixed neutral fraction; or if intrinsic Ly α flux is unusually strong in these galaxies. We discuss how to test these scenarios with JWST and prospects for upcoming wide-area surveys to distinguish between reionization models.

Micro-CT imaging of a frozen bubble cluster: Sample holder development and image processing techniques

The significance of clusters in the flotation of coarse particles is well-known. This paper presents a novel technique for micro-computerized tomography (micro-CT) imaging of bubble clusters. A bubble cluster was collected using a customised arrangement and subsequently frozen to keep the cluster in a fixed position. A sample holder with a cooling chamber was designed and constructed to maintain the frozen state of the cluster during the micro-CT imaging process. The cooling chamber maintained a continuous flow of coolant at −10 °C across the sample, effectively preserving the frozen state of the bubble cluster during imaging. By utilizing this custom sample holder, high-quality imaging of the frozen bubble cluster sample was achieved. Image processing techniques enabled 3D visualization and quantitative analysis of the bubble cluster. The analysis includes measurements of cluster dimensions, particle and bubble sizes, volume distribution, and the percentage of particles in each size range within the cluster. These insights provide valuable information for understanding the underlying structure and characteristics of the bubble cluster, which cannot be obtained through the traditional photographic method.

Aqueous foams in microgravity, measuring bubble sizes

Aqueous foams in microgravity, measuring bubble sizes

Quantification and correlation analysis of bubble characteristics and heat transfer performance in direct contact heat exchanger

In this work, a combination of morphological processing and watershed algorithm is proposed to measure bubble size, based on which an improved frame difference method is proposed to obtain bubble velocities with an F1 score of 0.96. Empirical equations for the boiling properties of flow in immiscible fluids and their influencing factors are developed. Correlation equations for the Nusselt (Nu) number and Colburn (j) factor are developed, with mean deviations of 5.42% and 5.47%, respectively. The results show that the increase in bubble rise rate and the trend of bubble growth become slower with the increase in the flow rate of the dispersed phase. In contrast, the temperature of the continuous phase has a negative correlation on the bubble growth and almost no effect on the bubble velocity. In addition, the heat transfer coefficient, which increases with the increase of the flow rate of the dispersed phase, has a negative correlation with the initial temperature difference. The main objective of this study is to provide a new method for measuring bubble parameters during direct contact boiling heat transfer and to provide new ideas for studying direct contact boiling heat transfer.

A comparative study on the measurement of surface bubble size distributions in dry aqueous foams using optical methods

The measurement of bubble sizes in aqueous foams based on images of the surface is a typical method used in laboratory and industrial scales. In this article the relationship between the size distribution of the facet areas and the bubble size of wall-touching bubbles is investigated. To achieve this an invasive sampling approach is used for in-situ collection of wall-touching bubbles in dry foams, while the surface is imaged in parallel. Bubble and facet size distributions are obtained using automated image processing. It is shown that sharp peaks in the bubble size distribution will appear smoother in the facet size distribution. This results in an overestimation of polydispersity by the surface measurements. Furthermore, it is observed that the mean equivalent diameter of the facets is on average 6% smaller than the bubble diameter obtained using the sampling method. An approach proposed by Wang and Neethling (2009) gives a good approximation of the relation between facet and bubble size and can be used to reduce potential uncertainties in surface based bubble size measurements.

Passive acoustic measurement of bubble size and number from a bubble chain

Experiments and matching simulations are presented on the passive-acoustic emissions of a chain of bubbles, with the aim of deducing both the bubble size and number of bubbles from the emitted sound. It is well known that bubble-acoustic interactions cause shifts in frequency from those predicted for single bubbles, complicating the goal of measuring bubble size by measuring frequency, and also affecting the collective resonances of bubbles driven by ultrasound. A horizontal line of identical bubbles was held fixed in space, eliminating uncertainties in earlier studies due to the variable shape and location of freely rising bubbles. At one end of the line, a first, identical bubble naturally emitted a pulse of sound on formation from an underwater nozzle, exciting the rest of the bubbles into a coupled acoustic emission. It was found that a theoretically predicted relation between frequency and the number of bubbles, which can be derived from the coupled equations of motion, permitted an accurate fit to the data. Measurements of two independent spectral peaks unambiguously determined the two unknowns of bubble size and bubble number. However, experiments diverge from theory and simulations for greater than six bubbles, which are speculated may be explicable by network theory.

Measurement of bubble size and froth velocity using convolutional neural networks

Bubble size and froth velocity are the most important froth characteristics used for evaluating and controlling flotation systems. Bubble size is often measured using watershed and edge detection algorithms. These algorithms typically result in the over-segmentation of big bubbles or the under-segmentation of small ones. Froth velocity is usually determined by processing successive images using various techniques such as pixel tracing, block matching, and bubble tracking. Most of these algorithms perform well but are quite slow. Pre-trained convolutional neural networks are more accurate and simpler models for image classification and feature extraction. In this research, a new approach based on using a pre-trained convolutional neural network to measure bubble size and froth velocity from froth flotation images is proposed. The results demonstrate that pre-trained convolutional neural networks can serve as a more reliable and faster approach than classical image processing algorithms for analyzing froth images.

Double‐sensor conductivity probe applied in a flotation system

AbstractThis study proposed a new approach for measuring bubble size distribution, bubble mean diameter, Sauter mean bubble diameter, and gas holdup using a double‐sensor conductivity probe in an air/water two‐phase system bubble column. The results for the two‐phase system were compared and calibrated using analyses from bubble images taken by a digital camera from the side of the column wall. Good agreement was observed between the two techniques. The same double‐sensor conductivity was used in an air/water/solids three‐phase system. The conductivity probe captured the change in bubble dynamic behaviour inside the pulp phase; however, the presence of the solids made it more challenging to measure. As a result, the VisioFroth commercial package, using images taken from the top of the froth layer, could be used in conjunction with the double‐sensor conductivity probe to show the dynamic evolution of mineralized bubbles from the pulp zone to the froth zone in a flotation process.

The Role of Stereological Assumptions in Bubble Size Estimations and Their Implications for Assessing Critical Coalescence Concentrations

Accurate measurement of bubble size is critical for assessing flotation performance. However, the 3D nature of bubbles, in contrast to the 2D nature of photographs obtained using a bubble viewer apparatus, may lead to distortions related to stereological assumptions. This study aimed to quantify the impact of these stereological effects on bubble size measurements in frother characterisations. Our results showed that different assumptions regarding bubble shape and volume resulted in variations in bubble size calculations of up to 10%. Furthermore, these stereological effects were propagated to the calculation of the critical coalescence concentration, leading to uncertainties of up to 14% depending on the type of frother. These findings emphasise the importance of considering stereological effects and selecting an appropriate calculation method when measuring bubble size for flotation and reagent assessments.

Applied Online Bubble Size Distribution Measurement in a Pilot Flotation Cell Based on Image Analysis

The distribution of bubble size in the pulp is a parameter directly related to the flotation kinetics, but its measurement is complex to determine due to the presence of particles and cluster of bubbles. The existing equipment for the measurement of bubble size (McGill and UCT), which operate manually and batch, requires specialized operators in image analysis. On the other hand, the McGill technique has not been directly validated with bubble swarms and only 10% of the sampled bubbles are analyzed. These aspects have limited the technology transfer and sustainability in the measurement of bubble size. To solve the problems presented, a device based on the McGill technique was designed and implemented. Furthermore, algorithms were implemented to increase the statistical significance of the measurement of bubbles per image. The validation consisted of a comparison of the degree of detection using the software manually and automatically (undetected remaining bubbles). As a result, it is possible to predict the bubble size distributions with an error of less than 5% and derivations close to 0.1 [mm] in the determination of D32, using an average of 100 images. In conclusion, the new device and algorithms improve the accuracy of BSD measurements, helping to optimize the process, predict, control flotation kinetics, and be used as a troubleshooting tool. The new device and algorithms improve the accuracy of BSD measurements, helping to optimize the process, predict, control flotation kinetics, and be used as a troubleshooting tool.

Flotation froth image segmentation using Mask R-CNN

Automatic control of the flotation circuits needs online information from froth indicators, such as froth texture, motion speed, shape, and number and size distribution of bubbles. In principle, these indicators may be extracted with a machine vision system. This paper presents a real-time image analysis system based on Mask R-CNN for flotation froth segmentation and bubble size measurement. The main objectives were detection of bubbles in flotation froth, measurement of the size distribution of the bubbles, and detection of non-loaded bubbles in the froth. Application of the classical image segmentation methods in an industrial copper flotation plant showed considerable errors in bubble identification and sizing. The accuracy of the proposed method in bubble detection and sizing was evaluated using manually segmented images. The proposed method could detect bubbles with an accuracy of 92.82%, which is a considerable improvement to classical image segmentation methods. The proposed system is installed, tested, and verified in an industrial copper flotation process.