From bistable Geometry to acoustic Functionality: A Data-Driven study of Kresling origami bandgaps

The Kresling origami structure, a geometric construction with folding deformation characteristics, exhibits significant research potential in the domains of deformable structures and phononic crystals. This research presents a novel approach for precise bandgap modulation of Kresling origami structures through geometric design. Gradient Boosting Regression (GBR) and Lasso Regression (LR) are employed for the first time to predict bandgap frequencies, capturing the nonlinear relationship between geometric parameters and bandgaps. The models, trained on experimental and simulation data, provide reliable statistical support, significantly enhancing prediction accuracy, with a maximum sampling error of only 1.28%, while structural optimization efficiency is greatly improved. The findings indicate that the bandgap frequency can be precisely adjusted by modifying parameters like height, diameter, relative angle, and number of layers of the origami structure, hence enabling vibration isolation over a wide frequency range. The effectiveness of the regression models in handling complex nonlinear data was evaluated through prediction errors and bandgap analysis, with data-driven modeling providing theoretical and statistical support for the design optimization of Kresling origami structures.