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Martin Niemann

dblp:275/9179 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Visualization and visual analytics · 50% Image and video processing · 50%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational science and engineering · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video processing
feature detection
0.412020
Detection and Visualization of Splat and Antisplat Events in Turbulent Flows · IEEE Trans. Vis. Comput. Graph. 2020
Visualization and visual analytics
flow visualization
0.412020
Detection and Visualization of Splat and Antisplat Events in Turbulent Flows · IEEE Trans. Vis. Comput. Graph. 2020
Computational science and engineering › fluid dynamics
turbulent flow analysis
0.112020
Detection and Visualization of Splat and Antisplat Events in Turbulent Flows · IEEE Trans. Vis. Comput. Graph. 2020

Methods — techniques the papers use, named apart from their topics

strain tensor analysis · 0.9lagrangian method · 0.9
YearPublicationVenuePosition
2020 Detection and Visualization of Splat and Antisplat Events in Turbulent Flows
abstract
Splat and antisplat events are a widely found phenomenon in three-dimensional turbulent flow fields. Splats are observed when fluid locally impinges on an impermeable surface transferring energy from the normal component to the tangential velocity components, while antisplats relate to the inverted situation. These events affect a variety of flow properties, such as the transfer of kinetic energy between velocity components and the transfer of heat, so that their investigation can provide new insight into these issues. Here, we propose the first Lagrangian method for the detection of splats and antisplats as features of an unsteady flow field. Our method utilizes the concept of strain tensors on flow-embedded flat surfaces to extract disjoint regions in which splat and antisplat events of arbitrary scale occur. We validate the method with artificial flow fields of increasing complexity. Subsequently, the method is used to analyze application data stemming from a direct numerical simulation of the turbulent flow over a backward facing step. Our results show that splat and antisplat events can be identified efficiently and reliably even in such a complex situation, demonstrating that the new method constitutes a well-suited tool for the analysis of turbulent flows.
Baldwin Nsonga, Martin Niemann, Jochen Fröhlich, Joachim Staib, Stefan Gumhold, Gerik Scheuermann
IEEE Trans. Vis. Comput. Graph.2