PyKirigami: An interactive python simulator for Kirigami structures

In recent years, the concept of kirigami has been used in creating deployable structures for various scientific and technological applications. While high-fidelity Finite Element Analysis (FEA) is the standard for analyzing stress distributions and material deformation, it is computationally intensive and often ill-suited for the rapid exploration of vast kinematic configuration spaces. In this work, we develop PyKirigami, a lightweight, open-source Python framework for the efficient deployment simulation of kirigami structures. Unlike continuum mechanics solvers, PyKirigami models tessellations as articulated rigid-body networks, allowing for the real-time simulation of global deployment trajectories and volumetric transformations. The tool incorporates collision detection and interactive actuation, enabling users to validate folding paths and identify geometric locking states in both 2D and 3D topologies. This framework serves as a fast kinematic prototyping tool for kirigami structures, allowing researchers to verify deployment mechanics and self-contacts prior to performing detailed mechanical analysis or physical fabrication. Program summary Program Title: PyKirigami CPC Library link to program files: (to be added by Technical Editor) Developer’s repository link: https://github.com/andy-qhjiang/PyKirigami Licensing provisions: Apache-2.0 Programming language: Python External routines/libraries: NumPy, PyBullet Nature of problem: Validating the deployment of complex kirigami structures typically relies on computationally expensive Finite Element Analysis (FEA) or physical prototyping. Using FEA for purely kinematic exploration, specifically for checking folding paths, bistability, and self-collisions, is inefficient, particularly when iteratively searching through large design spaces or testing multiple actuation strategies. Solution method: PyKirigami bypasses the heavy computational load of continuum stress analysis by solving the non-smooth contact dynamics of an articulated rigid-body system. The software implements a graph-based topology parser that maps 2D input tessellations into a 3D constrained multi-body network. It utilizes an impulse-based dynamic solver (Projected Gauss–Seidel) to resolve joint constraints and contacts in real-time. This allows for the lightweight, interactive discovery of collision-free deployment trajectories, serving as a rapid verification step before high-fidelity analysis.