3D Particle Tracking Velocimetry Method: Advances and Error Analysis

A full three-dimensional particle tracking system was developed and tested. By using three separate CCDs placed at the vertices of an equilateral triangle, the threedimensional location of particles can be determined. Particle locations measured at two different times can then be used to create a three-component, three-dimensional velocity field. Key developments are: the ability to accurately process overlapping particle images, offset CCDs to significantly improve effective resolution, allowance for dim particle images, and a hybrid particle tracking technique ideal for three-dimensional flows when only two sets of images exist. An in-depth theoretical error analysis was performed which gives the important sources of error and their effect on the overall system. This error analysis was verified through a series of experiments, which utilized a test target with 100 small dots per square inch. For displacements of 2.54mm the mean errors were less than 2% and the 90% confidence limits were less than 5.2 μm in the plane perpendicular to the camera axis, and 66 μm in the direction of the camera axis. The system was used for flow measurements around a delta wing at an angle of attack. These measurements show the successful implementation of the system for three-dimensional flow velocimetry

On imploding cylindrical and spherical shock waves in a perfect gas

The problem of a cylindrically or spherically imploding and reflecting shock wave in a flow initially at rest is studied without the use of the strong-shock approximation. Dimensional arguments are first used to show that this flow admits a general solution where an infinitesimally weak shock from infinity strengthens as it converges towards the origin. For a perfect-gas equation of state, this solution depends only on the dimensionality of the flow and on the ratio of specific heats. The Guderley power-law result can then be interpreted as the leading-order, strong-shock approximation, valid near the origin at the implosion centre. We improve the Guderley solution by adding two further terms in the series expansion solution for both the incoming and the reflected shock waves. A series expansion, valid where the shock is still weak and very far from the origin, is also constructed. With an appropriate change of variables and using the exact shock-jump conditions, a numerical, characteristics-based solution is obtained describing the general shock motion from almost infinity to very close to the reflection point. Comparisons are made between the series expansions, the characteristics solution, and the results obtained using an Euler solver. These show that the addition of two terms to the Guderley solution significantly extends the range of validity of the strong-shock series expansion

Data management for heterogeneous research environments with CaosDB -- Experiences from an MPDL Open Source development project

Experimental and theoretical scientists in the turbulence department at the MPI-DS in Göttingen produce a large variety of heterogeneous data and analyze it in a number of different environments. In an MPDL project, the open source research data management software CaosDB was enhanced to meet these needs and hopefully those of other research groups as well. We will show the results of this process: automated integration of data from metadata-rich raw HDF 5 files and a new API with language bindings for Octave, C++ and Julia. Additionally, the user documentation was overhauled, programming tutorials published and perfomance bottlenecks identified. We will also share insights about "soft" measures to increase the overall utility of semantic data management: practical guidelines for scientists to produce truly FAIR data and workshops to empower scientists to work with CaosDB

Sparse 3D Point-cloud Map Upsampling and Noise Removal as a vSLAM Post-processing Step: Experimental Evaluation

The monocular vision-based simultaneous localization and mapping (vSLAM) is one of the most challenging problem in mobile robotics and computer vision. In this work we study the post-processing techniques applied to sparse 3D point-cloud maps, obtained by feature-based vSLAM algorithms. Map post-processing is split into 2 major steps: 1) noise and outlier removal and 2) upsampling. We evaluate different combinations of known algorithms for outlier removing and upsampling on datasets of real indoor and outdoor environments and identify the most promising combination. We further use it to convert a point-cloud map, obtained by the real UAV performing indoor flight to 3D voxel grid (octo-map) potentially suitable for path planning.Comment: 10 pages, 4 figures, camera-ready version of paper for "The 3rd International Conference on Interactive Collaborative Robotics (ICR 2018)