This paper presents a non-intrusive measurement technique for the simultaneous assessment of the three-dimensional (3D) velocity and temperature fields in thermal convection. The technique is based on the combination of tomographic particle image velocimetry and particle image thermometry. Thermochromic liquid crystal particles serve simultaneously as both flow tracers and thermometers. The velocity fields were measured in a volume of 62 500 cm 3 and the temperature fields in a subvolume of 20 000 cm 3 . Turbulent Rayleigh-Bénard convection in a water-glycol mixture at Ra = 7.0 × 10 9 and Pr = 18 was used as a model system to measure the instantaneous 3D velocity and temperature fields at the same time. Uncertainties of σ v ⩽ 0.66 mm s −1 for the velocity and σ t ⩽ 0.095 K for the temperature measurement were estimated corresponding to dynamic ranges of 24 and 21 levels, respectively. Correlating the measured temperature and velocity fields, it is shown that the obtained large-scale structure reflects a region of warm rising fluid which is well-known from the literature.
The dispersion of aerosols originating from one source, the ‘index’ passenger, within the cabin of the aircraft Do728 is studied experimentally using an aerosol-exhaling thermal manikin and in Reynolds-averaged Navier–Stokes simulations (RANS). The overall aim of the present study is the experimental determination of the aerosol spreading for the state-of-the-art mixing ventilation (MV) and to evaluate the potential of alternative ventilation concepts for controlling the aerosol spreading in RANS. For MV, the experiments showed that the ratio of inhaled to exhaled aerosol particles drops below 0.06% (volume ratio) for distances larger than two seat rows from the source. However, within a single row, the observed ratio is higher. Further, the dispersion is much weaker for a standing than for a seated index passenger. High air exchange rates and a well-guided flow prevent a dispersion of the aerosols in high concentrations over larger distances. Additionally, the positive effect of a mask and an increased air flow rate, and especially their combination are shown. In the complementary conducted RANS, the advantages of floor-based cabin displacement ventilation (CDV) which is alternative ventilation concept to MV, regarding spreading lengths and the dwell time of the aerosols in the cabin were determined. The obtained results also underline the importance of the flow field for the aerosol dispersion. Further, additional unsteady RANS (URANS) simulations of the short-term process of the initial aerosol cloud formation highlighted that the momentum decay of the breathing and the evaporation processes take place within a few seconds only.
This paper presents a new framework for particle tracking based on a Gaussian Mixture Model (GMM). It is an extension of the state-of-the-art iterative reconstruction of individual particles by a continuous modeling of the particle trajectories considering the position and velocity as coupled quantities. The proposed approach includes an initialization and a processing step. In the first step, the velocities at the initial points are determined after iterative reconstruction of individual particles of the first four images to be able to generate the tracks between these initial points. From there on, the tracks are extended in the processing step by searching for and including new points obtained from consecutive images based on continuous modeling of the particle trajectories with a Gaussian Mixture Model. The presented tracking procedure allows to extend existing trajectories interactively with low computing effort and to store them in a compact representation using little memory space. To demonstrate the performance and the functionality of this new particle tracking approach, it is successfully applied to a synthetic turbulent pipe flow, to the problem of observing particles corresponding to a Brownian motion (e.g., motion of cells), as well as to problems where the motion is guided by boundary forces, e.g., in the case of particle tracking velocimetry of turbulent Rayleigh–Bénard convection.
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