The development of energy-efficient solutions for large-scale fermenters demands a deep and comprehensive understanding of hydrodynamic and heat and mass transfer processes. Despite a wide variety of research dedicated to measurements of mass transfer intensity in bubble flows, this research subject faces new challenges due to the topical development of new innovative bioreactor designs. In order to understand the fluid dynamics of the gas–liquid medium, researchers need to develop verified CFD models describing flows in the bioreactor loop using a progressive physical and mathematical apparatus. In the current paper, we represent the results of evaluating the key performance indicator of the bioreactor, namely the volumetric mass transfer coefficient (${\mathrm{k}}_{\mathrm{L}}\mathrm{a}$) known as a parameter of dominant importance for the design, operation, scale-up, and optimization of bioreactors, using the developed thermometry method. The thermometry method under consideration was examined within a series of experiments, and a comparative analysis was provided for a number of various regimes also being matched with the classical approaches. The methodology, experiment results, and data verification are given, which allow the evaluation of the effectiveness and prediction of the fluid flows dynamics in bioreactors circuits and ultimately the operational capabilities of the fermenter line.

Multiphase biophysical media are known to be complex structures with continuous high demand to the scientific community for understanding the relationships and ratios between factors affecting the type, dynamics and nature of its structural changes on their impact degree on the media itself. Among the plentiful list of such factors the following do worth mentioning: the lifetime of a particle, turbulence factors and a number of others, each requiring careful analysis, assessment of the contribution degree and, importantly, correct accounting. The present study is focused on such a factor affecting mass transfer intensity change as surface tension through its relationship with the interfacial area: the latter is the site of mass exchange between the gas and liquid phases, and modifications in surface tension values can significantly impact the characteristics of this area, hence altering the rate of mass transfer. By controlling surface tension, one can effectively modulate the size and stability of particles, namely bubbles or droplets, which in turn changes the interfacial area available for mass transfer. The total interfacial area, which is the cumulative surface area of all bubbles, serves as the site for mass transfer. The impact of the surface tension coefficient variation into gas–liquid mass transfer characteristics is analyzed both for the case of water and model liquid. The latter means the potential contribution of surface-active substances was a part of research scope since it was applied to recreate conditions similar to the cultural liquid when microorganisms that produce surfactants are grown. The proposed new methodology assumes calculating interfacial area through the segmentation of images captured by a high-speed camera, thus we can gain a profoundly enhanced understanding of the relationship between surface tension and mass transfer. The precise visual data and subsequent computation of the interfacial area provide deeper insights into the dynamics of bubble formation and the effects of surface tension on bubble size and distribution. As a result, this method has significantly improved our capacity to investigate and optimize mass transfer processes in multiphase biophysical systems. Both analytical approach and results interpretation not only influence affirmatively on deep understanding of natural mechanisms in biophysical media, but also might serve their best for potential application, e.g. in the context of the development of biotechnological industries based on fermentation processes for protein production.

The paper presents the results of experimental study on melting simulator of the fuel coating pin cladding made of alloy Pb (44.5 %)-Bi (55.5 %) and the flow of the melt on the surface of the heated rod. Experiments were conducted for different parameters: heat release, initial temperature, linear size, and the cladding thickness. All experiments provided the video of the process of formation and relocation of the melt, and the cladding temperature and mass loss rate were measured. The paper presents analysis of melt formation and relocation on the fuel rod imitator surface.

Bubble multiphase systems are crucial in industries such as biotechnology, medicine, oil and gas, and water treatment. Optical data analysis provides critical insights into bubble characteristics, such as the shape and size, complementing physical sensor data. Existing detection techniques rely on classical computer vision algorithms and neural network models. While neural networks achieve a higher accuracy, they require extensive annotated datasets, and classical methods often struggle with complex systems due to their lower accuracy. This study proposes a novel framework to address these limitations. Using Superformula parameter regression, we introduce an advanced border detection method for accurately identifying gas inclusions and complex-shaped objects in multiphase environments. The framework also includes a new approach for generating realistic artificial bubble images based on physical flow conditions, leveraging the Superformula to create extensive, labeled datasets without manual annotation. Tested on real bubble flows in mass transfer equipment, the algorithms enable bubble classification by shape and size, enhance detection accuracy, and reduce development time for neural network solutions. This work provides a robust method for object detection and dataset generation in multiphase systems, paving the way for more precise modeling and analysis.

Our study investigates how non-spherical bubble shapes influence gas–liquid mass transfer across the bubble interface. An analytical shape descriptor, namely Superformula, is used to parametrically define the bubble interface, enabling efficient CFD simulations over a range of Reynolds ($Re$) and Eötvös ($Eo$) numbers. By prescribing the bubble geometry analytically, we avoid expensive interface-capturing simulations and directly compute the concentration field without transient boundary shape pre-equilibration. The represented approach is computationally efficient and captures the impact of bubble shape and flow parameters on the dissolved gas concentration gradients in the surrounding liquid. Results show that bubble deformation alters the distribution of dissolved gas around the bubble and the overall mass transfer rate, with higher $Re$ enhancing convective transport and higher $Eo$ (more deformed bubbles), leading to anisotropic concentration boundary layers. The developed framework not only advances a fundamental understanding of bubble-driven mass transfer mechanisms but also directly addresses industrial needs, particularly in optimizing oxygen delivery within bioreactors contour and similar aerated processes. The proposed efficient modeling strategy provides a basis for developing fast surrogate tools in hybrid modeling frameworks, where high-fidelity CFD insights are incorporated into larger-scale multiphase process simulations.

Methods of calculating the motion of melt over the surface of fuel element in accident conditions are presented. The calculation is performed using mathematical modeling methods. The results of...