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    This study introduces a visual analytics tool for analyzing spatial sensitivity in 3D simulations. It helps understand how parameters influence outcomes across different regions, improving simulation insights.

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    Area of Science:

    • Computer Science
    • Scientific Visualization
    • Computational Science

    Background:

    • Traditional sensitivity analyses often compute a single global value per parameter.
    • Analyzing localized sensitivities in 3D spatial simulations is crucial for many applications.
    • Multi-field data arises when analyzing spatial sensitivity for multiple simulation parameters.

    Purpose of the Study:

    • To develop an interactive visual analytics solution for analyzing multi-field spatial sensitivity data.
    • To enable investigation of parameter influence across specific spatial regions and their interplays.
    • To address the challenge of visualizing and analyzing complex multi-field sensitivity data.

    Main Methods:

    • Proposing an interactive visual analytics system for multi-field sensitivity data.
    • Utilizing data-driven space-filling curves to linearize 3D data and avoid occlusion.
    • Employing a combination of Horizon Graphs and line charts for visualizing spatial sensitivity values.
    • Validating the approach with synthetic and real-world ensemble data.

    Main Results:

    • The developed system effectively visualizes and analyzes spatial variations in parameter sensitivity.
    • It allows for the investigation of how individual parameters influence simulation outcomes in different spatial regions.
    • The approach facilitates understanding the interplay between multiple simulation parameters.

    Conclusions:

    • The proposed visual analytics solution provides an effective method for analyzing localized sensitivities in 3D spatial simulations.
    • This approach enhances the understanding of parameter influence and their spatial distribution.
    • The tool is valuable for applications requiring detailed sensitivity analysis of complex simulation ensembles.