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Interactive Visual Analysis of Structure-borne Noise Data.

Rainer Splechtna, Denis Gracanin, Goran Todorovic

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    This summary is machine-generated.

    This study introduces an interactive visualization method for analyzing complex automotive noise simulation data. It helps engineers quickly identify critical noise sources, improving design efficiency and reducing development costs.

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    Area of Science:

    • Automotive Engineering
    • Data Visualization
    • Computational Mechanics

    Background:

    • Numerical simulations are crucial in automotive design but face challenges with high-dimensional and complex data.
    • Early detection of noise sources is vital for cost and time reduction in product development.

    Purpose of the Study:

    • To develop an interactive visual analysis approach for high-dimensional spectral data from automotive noise simulations.
    • To facilitate design improvements by identifying and analyzing critical noise sources in structure-borne noise.

    Main Methods:

    • Interactive visualization with linked views exploring noise, vibration, and harshness (NVH) data.
    • Simultaneous analysis in both frequency and spatial domains with synchronized updates.
    • Novel drill-down view, split boxplots, and synchronized 3D geometry views for detailed analysis and comparison.

    Main Results:

    • Successfully identified critical noise sources within an internal combustion engine simulation.
    • Enabled engineers to iterate over design optimizations more rapidly.
    • Improved understanding of the analyzed noise and vibration phenomena.

    Conclusions:

    • The proposed interactive visualization approach effectively aids in analyzing complex noise simulation data.
    • This method accelerates the design optimization process for automotive engineers.
    • Enhanced system understanding and early issue detection are key benefits.