Current Tomography -- Localization of void fractions in conducting liquids by measuring the induced magnetic flux density

A novel concept of a measurement technology for the localization and determination of the size of gas bubbles is presented, which is intended to contribute to a further understanding of the dynamics of efficiency-reducing gas bubbles in electrolyzers. A simplified proof-of-concept (POC) model is used to numerically simulate the electric current flow through materials with significant differences in electrical conductivity. Through an automated approach, an extensive data set of electric current density and conductivity distributions is generated, complemented with determined magnetic flux densities in the surroundings of the POC cell at virtual sensor positions. The generated data set serves as testing data for various reconstruction approaches. Based on the measurable magnetic flux density, solving Biot-Savarts law inversely is demonstrated and discussed with a model-based solution of an optimization problem, of which the gas bubble locations are derived

scenery: Flexible Virtual Reality Visualization on the Java VM

Life science today involves computational analysis of a large amount and variety of data, such as volumetric data acquired by state-of-the-art microscopes, or mesh data from analysis of such data or simulations. Visualization is often the first step in making sense of data, and a crucial part of building and debugging analysis pipelines. It is therefore important that visualizations can be quickly prototyped, as well as developed or embedded into full applications. In order to better judge spatiotemporal relationships, immersive hardware, such as Virtual or Augmented Reality (VR/AR) headsets and associated controllers are becoming invaluable tools. In this work we introduce scenery, a flexible VR/AR visualization framework for the Java VM that can handle mesh and large volumetric data, containing multiple views, timepoints, and color channels. scenery is free and open-source software, works on all major platforms, and uses the Vulkan or OpenGL rendering APIs. We introduce scenery's main features and example applications, such as its use in VR for microscopy, in the biomedical image analysis software Fiji, or for visualizing agent-based simulations.Comment: Added IEEE DOI, version published at VIS 201

Hierarchical Shape-Adaptive Quantization for Geometry Compression

The compression of polygonal mesh geometry is still an active field of research as in 3d no theoretical bounds are known. This work proposes a geometry coding method based on predictive coding. Instead of using the vertex to vertex distance as distortion measurement, an approximation to the Hausdorffdistance is used resulting in additional degrees of freedom. These are exploited by a new adaptive quantization approach, which is independent of the encoding order. The achieved compression rates are similar to those of entropy based optimization but with a significantly faster compression performance

Incremental Raycasting of Piecewise Quadratic Surfaces on the GPU

To overcome the limitations of triangle and point based surfaces several authors have recently investigated surface representations that are based on higher order primitives. Among these are MPU, SLIM surfaces, dynamic skin surfaces and higher order isosurfaces. Up to now these representations were not suitable for interactive applications because of the lack of an efficient rendering algorithm. In this paper we close this gap for implicit surface representations of degree two by developing highly optimized GPU implementations of the raycasting algorithm. We investigate techniques for fast incremental raycasting and cover per fragment and per quadric backface culling. We apply the approaches to the rendering of SLIM surfaces, quadratic iso-surfaces over tetrahedral meshes and bilinear quadrilaterals. Compared to triangle based surface approximations of similar geometric error we achieve only slightly lower frame rates but with much higher visual quality due to the quadratic approximation power of the underlying surfaces