%0 Conference Paper %1 10148302 %A Kretzschmar, Vanessa %A Scheuermann, Gerik %A Stommel, Markus %A Gillmann, Christina %B 2023 IEEE 16th Pacific Visualization Symposium (PacificVis) %D 2023 %K imported %P 107-111 %R 10.1109/PacificVis56936.2023.00019 %T A Visual Analytics Inspired Approach to Correlate and Understand Multiple Mechanical Tensor Fields %X We develop an interactive approach for analyzing multi-field tensor data from simulations in close collaboration with domain scientists. Our approach is based on extensive application analysis and built around a multi-field clustering addressing multiple user-defined quantities which were required by the domain scientists. Established techniques like linked views complement the approach to support reasoning while offering an overview and detailed insight into the multi-field tensor data. Further, we include an evaluation containing a real-world use case and a user study with domain scientists to demonstrate the usefulness compared to existing tools.

@inproceedings{10148302, abstract = {We develop an interactive approach for analyzing multi-field tensor data from simulations in close collaboration with domain scientists. Our approach is based on extensive application analysis and built around a multi-field clustering addressing multiple user-defined quantities which were required by the domain scientists. Established techniques like linked views complement the approach to support reasoning while offering an overview and detailed insight into the multi-field tensor data. Further, we include an evaluation containing a real-world use case and a user study with domain scientists to demonstrate the usefulness compared to existing tools.}, added-at = {2024-12-10T10:56:34.000+0100}, author = {Kretzschmar, Vanessa and Scheuermann, Gerik and Stommel, Markus and Gillmann, Christina}, biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/2a1bcd2b3371309dc5bf0f43668ee2e14/scadsfct}, booktitle = {2023 IEEE 16th Pacific Visualization Symposium (PacificVis)}, doi = {10.1109/PacificVis56936.2023.00019}, interhash = {5a67a8290841a7e330800db9fff995d0}, intrahash = {a1bcd2b3371309dc5bf0f43668ee2e14}, issn = {2165-8773}, keywords = {imported}, month = {April}, pages = {107-111}, timestamp = {2024-12-10T10:56:34.000+0100}, title = {A Visual Analytics Inspired Approach to Correlate and Understand Multiple Mechanical Tensor Fields}, year = 2023 }