Numerical investigation of the segregation of turbulent emulsions

We study the segregation of emulsions in decaying turbulence using direct numerical simulations (DNS) in combination with the volume of fluid method (VOF). To this end, we generate emulsions in forced homogeneous isotropic turbulence and then turn the forcing off and activate gravitational acceleration. This allows us to study the segregation process in decaying turbulence and under gravity. We consider non-iso-density emulsions, where the dispersed phase is the lighter one. The segregation process is driven by both the minimization of the potential energy achieved by the sinking of the heavier phase, as well as the minimization of the surface energy achieved by coalescence. To study these two processes and their impacts on the segregation progress in detail, we consider different buoyancy forces and surface tension coefficients in our investigation, resulting in five different configurations. The surface tension coefficient also alters the droplet size distribution of the emulsion. Using the three-dimensional simulation results and the monitored data, we analyze the driving mechanisms and their impact on the segregation progress in detail. We propose a dimensionless number that reflects the energy release dominating the segregation. Moreover, we evaluate the time required for the rise of the lighter phase and study correlations with the varied parameters gravitational acceleration and surface tension coefficient

Turbulent Bubble-Laden Channel Flow of Power-Law Fluids: A Direct Numerical Simulation Study

The influence of non-Newtonian fluid behavior on the flow statistics of turbulent bubble-laden downflow in a vertical channel is investigated. A Direct Numerical Simulation (DNS) study is conducted for power-law fluids with power-law indexes of 0.7 (shear-thinning), 1 (Newtonian) and 1.3 (shear-thickening) in the liquid phase at a gas volume fraction of 6%. The flow is driven downward by a constant volumetric flow rate corresponding to a friction Reynolds number of Reτ≈127.3. The Eötvös number is varied between Eo=0.3125 and Eo=3.75 in order to investigate the influence of quasi-spherical as well as wobbling bubbles and thus the interplay of the bubble deformability with the power-law behavior of the liquid bulk. The resulting first- and second-order fluid statistics, i.e., the gas fraction, mean velocity and velocity fluctuation profiles across the channel, show clear trends in reply to varying power-law indexes. In addition, it was observed that the bubble oscillations increase with decreasing power-law index. In the channel core, the bubbles significantly increase the dissipation rate, which, in contrast to its behavior at the wall, shows similar orders of magnitude for all power-law indexes

EuProGigant Resilience Approach: A Concept for Strengthening Resilience in the Manufacturing Industry on the Shop Floor

Crises lead to adverse effects in the value creation ecosystem. In the long term, they lead to uncertainties that can destabilize the system. Resilience is getting more and more critical in connected, value-added ecosystems. Crises such as the Corona pandemic, the Suez Canal blockage, the chip crisis, and rising energy prices can cause sudden change in the market demand-supply equilibrium. Those can be expressed as calamities. This concept aims to create calamity-avoiding mechanisms in the manufacturing industry based on a common data infrastructure and smart use of data and services. Calamity-avoiding mechanisms are essential for unplannable and unknown disturbance factors connecting enterprise value creation networks in multiple layers. Resilience mechanisms must be distributed, decentralized, and interoperable to reduce the effect of self-reinforcement of calamities and enable self-orchestration functionalities. Gaia-X, the European initiative for creating a common and sovereign data infrastructure, offers data exchange based on the EU legal framework and is crucial for the (inter-)operability of the mechanisms. This paper presents the concept of such resilience mechanisms, the processing of data in the vertical plane (within a company), and the benefits at the horizontal level (across supply chains of companies). The concept is developed in the context of the EuProGigant project. It follows a bottom-up approach and starts with the Self-Descriptions (SD) of all assets on the shop floor. The resilience approach includes five key points: SDs, stress scenarios and stress mechanisms, system theory and control, anomaly detection services, and self-orchestration