Minimizing Structural Vibrations via Guided Flow Matching Design Optimization
This work addresses passenger comfort in engineering systems by reducing vibrations, presenting an incremental improvement through a novel integration of generative and surrogate models for design optimization.
The paper tackles the problem of minimizing structural vibrations in engineering systems like vehicles by developing a design optimization approach using guided flow matching to place beadings in plate-like structures, resulting in diverse and manufacturable designs with reduced vibrations compared to random search, heuristic, and genetic methods.
Structural vibrations are a source of unwanted noise in engineering systems like cars, trains or airplanes. Minimizing these vibrations is crucial for improving passenger comfort. This work presents a novel design optimization approach based on guided flow matching for reducing vibrations by placing beadings (indentations) in plate-like structures. Our method integrates a generative flow matching model and a surrogate model trained to predict structural vibrations. During the generation process, the flow matching model pushes towards manufacturability while the surrogate model pushes to low-vibration solutions. The flow matching model and its training data implicitly define the design space, enabling a broader exploration of potential solutions as no optimization of manually-defined design parameters is required. We apply our method to a range of differentiable optimization objectives, including direct optimization of specific eigenfrequencies through careful construction of the objective function. Results demonstrate that our method generates diverse and manufacturable plate designs with reduced structural vibrations compared to designs from random search, a criterion-based design heuristic and genetic optimization. The code and data are available from https://github.com/ecker-lab/Optimizing_Vibrating_Plates.