SARS-CoV-2 (COVID-19) as an airborne respiratory disease led to a bunch of open questions: how teaching in classrooms is possible and how the risk of infection can be reduced, e.g., by the use of air purifier systems. In this study, the transmission of aerosols in a classroom is analyzed numerically and experimentally. The aerosol concentration in a classroom equipped with an air purifier system was measured with an aerosol spectrometer (optical particle sizer, TSI Incorporated) at different locations. The transient reduction of the aerosol concentration, which was artificially generated by an aerosol generator (di-ethyl hexyl sebacate-atomizer, detected particle size ranging from 0.3 to 10 μ m), was monitored. The experimental results were used to validate a numerical simulation model of the classroom using the Open Source Computational Fluid Dynamics code OpenFOAM® (version 6). With the numerical simulation model, different scenarios with infected persons in the room have been analyzed, showing that the air purifier system leads to a significant reduction of airborne particles in the room dependent on the location of the infected person. The system can support additional ventilation strategies with fresh air, especially in cold seasons.

We present a 3D code-coupling approach which has been specialized towards cardiovascular blood flow. For the first time, the prescribed geometry movement of the cardiovascular flow model KaHMo (Karlsruhe Heart Model) has been replaced by a myocardial composite model. Deformation is driven by fluid forces and myocardial response, i.e., both its contractile and constitutive behavior. Whereas the arbitrary Lagrangian-Eulerian formulation (ALE) of the Navier-Stokes equations is discretized by finite volumes (FVM), the solid mechanical finite elasticity equations are discretized by a finite element (FEM) approach. Taking advantage of specialized numerical solution strategies for non-matching fluid and solid domain meshes, an iterative data-exchange guarantees the interface equilibrium of the underlying governing equations. The focus of this work is on left-ventricular fluid-structure interaction based on patient-specific magnetic resonance imaging datasets. Multi-physical phenomena are described by temporal visualization and characteristic FSI numbers. The results gained show flow patterns that are in good agreement with previous observations. A deeper understanding of cavity deformation, blood flow, and their vital interaction can help to improve surgical treatment and clinical therapy planning.

The Karlsruhe Heart Model (KaHMo) is a patient-specific simulation tool for a three-dimensional blood flow evaluation inside the human heart. Whereas KaHMo MRT is based on geometry movement identified from MRT data, KaHMo FSI allows the consideration of structural properties and the analysis of FSI. Previous investigations by Oertel et al. have shown the ability of KaHMo to gain insight into different intra-ventricular fluid mechanics of both healthy and diseased hearts. However, the in vivo validation of the highly dynamic cavity flow pattern has been a challenging task in recent years. As a first step, the focus of this study is on an artificial ventricular experiment, derived from real heart anatomy. Fluid domain deformation and intra-ventricular flow dynamics are enforced by an outer surface pressure distribution. The pure geometrical representation of KaHMo MRT can now be complemented by constitutive properties, pressure forces, and interaction effects using KaHMo FSI's partitioned code-coupling approach. For the first time, fluid domain deformation and intra-ventricular flow of KaHMo FSI has been compared with experimental data. With a good overall agreement, the proof of KaHMo's validity represents an important step from feasibility study toward patient-specific analysis.

The mixing process in biogas plants is fundamental for effectiveness. Unfortunately, difficulties at full scale mean that research must usually be performed at lab‐scale and the results up‐scaled. This study presents a scale‐up strategy for the fluid flow in shear‐thinning non‐Newtonian fluids. Dimensional analysis was applied to connect the influencing parameters, i.e., geometric dimensions, rotational speed, and rheological properties, to key figures. By using the Reynolds and Hedström number, standards for adapting the rotational speed and rheological properties were defined as a function of the scale. A sliding‐mesh model was selected for numerical simulations of a plant with a paddle agitator at two different scales. The scale‐up approach leads to similar velocity fields, which result in equal normalized mixing times.

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A new approach for transportation of objects within production systems by automated throwing and capturing is investigated. This paper presents an implementation, consisting of a throwing robot and a capturing robot. The throwing robot uses a linear and the capturing robot a rotary axis. The throwing robot is capable of throwing cylinder-shaped objects onto a target point with high precision. The capturing robot there smoothly grips the cylinders during flight by means of a rotational movement. In order to synchronize the capturing robot and the cylinder's pose and velocity, its trajectory has to be modeled as well as the motion sequences of both robots. The throwing and capturing tasks are performed by the robots automatically without the use of any external sensor system.

The removal of droplets on surfaces by an (air-) flow is relevant, e.g., for cleaning processes or to prevent corrosion or damage of electronic devices. Still the condition for droplet movement is not fully understood. Droplets start to move downstream at a critical (air-) flow velocity vcrit. For increasing flow velocity, this process is related to a strong oscillation of the droplet. This oscillation is supposed to be a key mechanism for the onset of droplet movement in conjunction with the flow field around the droplet. We report on measurements in the wake of the adhering droplet by means of laser-Doppler velocity profile sensor and hot wire anemometry. Thanks to the excellent spatial and temporal resolution of laser-Doppler velocity profile sensor and its capability to measure bidirectional flows, a backflow region can be detected in the wake of the droplet. Therefore, it can be concluded that this backflow structure is the driving mechanism for the strong flow movement inside the droplet against channel flow direction found in previous work. Analyzing the frequency spectra of the flow velocity, it was found that the flow is also oscillating; frequency peaks are in the same range as for the contour oscillation. Based on frequency, diameter and flow velocity, a Strouhal number can be calculated. This Strouhal number is almost constant in the investigated regime of droplet volumes and is between 0.015 and 0.03. Therefore, it can be assumed that an aeroelastic self-excitation effect may be present that eventually leads to droplet movement. Graphic abstract