Filip Sadlo’s research while affiliated with Heidelberg University and other places

In this paper, we present Gaia Sky, a free and open-source multiplatform 3D Universe system, developed since 2014 in the Data Processing and Analysis Consortium framework of ESA's Gaia mission. Gaia's data release 2 represents the largest catalog of the stars of our Galaxy, comprising 1.3 billion star positions, with parallaxes, proper motions, magnitudes, and colors. In this mission, Gaia Sky is the central tool for off-the-shelf visualization of these data, and for aiding production of outreach material. With its capabilities to effectively handle these data, to enable seamless navigation along the high dynamic range of distances, and at the same time to provide advanced visualization techniques including relativistic aberration and gravitational wave effects, currently no actively maintained cross-platform, modern, and open alternative exists.

Jet-streams, their core lines and their role in atmospheric dynamics have been subject to considerable meteorological research since the first half of the twentieth century. Yet, until today no consistent automated feature detection approach has been proposed to identify jet-stream core lines from 3D wind fields. Such 3D core lines can facilitate meteorological analyses previously not possible. Although jet-stream cores can be manually analyzed by meteorologists in 2D as height ridges in the wind speed field, to the best of our knowledge no automated ridge detection approach has been applied to jet-stream core detection. In this work, we -a team of visualization scientists and meteorologists- propose a method that exploits directional information in the wind field to extract core lines in a robust and numerically less involved manner than traditional 3D ridge detection. For the first time, we apply the extracted 3D core lines to meteorological analysis, considering real-world case studies and demonstrating our method's benefits for weather forecasting and meteorological research.

An escape map is the partial mapping from seed points to exit points of streamlines in a bounded domain. The escape map is piecewise continuous, and a topological segmentation of the domain boundary yields the regions and curve segments on which it is continuous. Escape maps have recently been introduced in the context of studying the connectivity of coronal holes. Computation of escape maps faces the problem of exponentially diverging streamlines, where standard adaptive streamsurface methods can fail. As a tool to detect such places and to guide escape map computation, a technique based on isoclines has recently been proposed (Machado et al., IEEE Trans. Vis. Comput. Graph. 20(12):2604–2613, 2014). We show in this paper that, in the case of a divergence-free vector field, boundary switch connectors can be used as a purely topological alternative, which to the best of our knowledge is the first practical application of boundary switch connectors. We provide a systematic approach to the topological segmentation of 3D domain boundaries for divergence-free vector fields. Finally, we explore an alternative approach based on streamtubes and targeted at robustness in escape map computation. Simulation results as well as a synthetic vector field are used for validation.

We present a novel approach for the visualization of fracture processes in peridynamics simulations. In peridynamics simulation, materials are represented by material points linked with bonds, providing complex fracture behavior. Our approach first extracts the cracks from each time step by means of height ridge extraction. To avoid deterioration of the structures, we propose an approach to extract ridges from these data without resampling. The extracted crack geometries are then combined into a spatiotemporal structure, with special focus on temporal coherence and robustness. We then show how this structure can be used for various visualization approaches to reveal fracture dynamics, with a focus on physical mechanisms. We evaluate our approach and demonstrate its utility by means of different data sets.

In single-phase flow visualization, research focuses on the analysis of vector field properties. In two-phase flow, in contrast, analysis of the phase components is typically of major interest. So far, visualization research of two-phase flow concentrated on proper interface reconstruction and the analysis thereof. In this paper, we present a novel visualization technique that enables the investigation of complex two-phase flow phenomena with respect to the physics of breakup and coalescence of inclusions. On the one hand, we adapt dimensionless quantities for a localized analysis of phase instability and breakup, and provide detailed inspection of breakup dynamics with emphasis on oscillation and its interplay with rotational motion. On the other hand, we present a parametric tightly linked space-time visualization approach for an effective interactive representation of the overall dynamics. We demonstrate the utility of our approach using several two-phase CFD datasets.

Traditional vector field visualization has a close focus on velocity, and is typically constrained to the dynamics of massless particles. In this paper, we present a novel approach to the analysis of the force-induced dynamics of inertial particles. These forces can arise from acceleration fields such as gravitation, but also be dependent on the particle dynamics itself, as in the case of magnetism. Compared to massless particles, the velocity of an inertial particle is not determined solely by its position and time in a vector field. In contrast, its initial velocity can be arbitrary and impacts the dynamics over its entire lifetime. This leads to a four-dimensional problem for 2D setups, and a six-dimensional problem for the 3D case. Our approach avoids this increase in dimensionality and tackles the visualization by an integrated topological analysis approach. We demonstrate the utility of our approach using a synthetic time-dependent acceleration field, a system of magnetic dipoles, and N-body systems both in 2D and 3D.