Visual Scalar Matrix Evaluation: An Application to Thermodynamics
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Date
2024
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Modeling and predicting thermodynamic properties of binary mixtures is crucial in chemical engineering. Understanding how the mixture behavior, represented as a scalar matrix, depends on properties of pure substances offers valuable insights into substance interactions. While there is robust support for pattern-based sorting of matrices in general, limited support exists for evaluating patterns against external attributes available in many fields. In this paper, we introduce an interactive software to detect and analyze block patterns in scalar matrices using annotated domain knowledge. Therefore, we revisit canonical matrix patterns, explore their translation to this application, and describe a workflow to fit the matrix ordering. Our interactive software allows users to explore hierarchical aggregation levels, rating them based on additional domain-specific data properties of various type. Using our tool, chemical engineers are able to identify and interpret cluster structures in their mixture data. These insights contribute to the development of improved prediction methods for thermodynamic properties, forming the foundation for modeling and simulation in chemical engineering.
Description
CCS Concepts: Human-centered computing → Heat maps; Dendrograms; Applied computing → Chemistry; Engineering
@inproceedings{10.2312:visgap.20241121,
booktitle = {VisGap - The Gap between Visualization Research and Visualization Software},
editor = {Gillmann, Christina and Krone, Michael and Reina, Guido and Wischgoll, Thomas},
title = {{Visual Scalar Matrix Evaluation: An Application to Thermodynamics}},
author = {Sohns, Jan-Tobias and Gond, Dominik and Jirasek, Fabian and Hasse, Hans and Leitte, Heike},
year = {2024},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-255-4},
DOI = {10.2312/visgap.20241121}
}