Data and code of "Physics-informed neural networks for programmable origami metamaterials with controlled deployment"
Data and code of "Physics-informed neural networks for programmable origami metamaterials with controlled deployment" When you extract the compressed file, you will find the following four files: Experiement: Contains all experimental data, experimental codes, and experimental results. This includes raw measurement data, data processing scripts, experimental setup configurations, and processed results from physical origami metamaterial experiments. FEA: Contains all finite element analysis (FEA) related materials including simulation results and analysis codes. The directory is organized into two main categories: Multilayer: Includes FEA data, results, and codes for three geometric configurations - cone, cylinder, and zigzag structures Singlelayer: Includes FEA data, results, and codes for forward analysis, inverse_1, and inverse_2 problems PINN_Forward: Contains all codes, results, and data for 4 forward problem cases using physics-informed neural networks. This includes training scripts, trained models, validation data, and performance metrics for forward prediction of origami metamaterial behavior. PINN_Inverse_1: Contains all codes, results, and data for 4 inverse problem cases. This includes the implementation of inverse design algorithms, optimization routines, training data, and obtained solutions for metamaterial parameter identification. PINN_Inverse_2: Contains all codes, results, and data for 7 inverse problem cases specifically focused on energy programming. This includes advanced inverse design implementations for controlling deployment energy landscapes, optimization algorithms, and comprehensive results for programmable metamaterial design.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-08-29
- DOI
- https://doi.org/10.5281/zenodo.16991595
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00