Constrained Form-Finding of Tension-Compression Structures using Automatic Differentiation
Abstract
This paper proposes a computational approach to form-find pin-jointed, bar structures subjected to combinations of tension and compression forces. The generated equilibrium states can meet force and geometric constraints via gradient-based optimization. We achieve this by extending the combinatorial equilibrium modeling (CEM) framework in three important ways. First, we introduce a new topological object, the auxiliary trail, to expand the range of structures that can be form-found with the framework. Then, we leverage automatic differentiation (AD) to obtain an exact value of the gradient of the sequential and iterative calculations of the CEM form-finding algorithm, instead of a numerical approximation. Finally, we encapsulate our research developments into an open-source design tool written in Python that is usable across different CAD platforms and operating systems. After studying four different structures -- a self-stressed planar tensegrity, a tree canopy, a curved bridge, and a spiral staircase -- we demonstrate that our approach enables the solution of constrained form-finding problems on a diverse range of structures more efficiently than in previous work.
Cite
@article{arxiv.2111.02607,
title = {Constrained Form-Finding of Tension-Compression Structures using Automatic Differentiation},
author = {Rafael Pastrana and Patrick Ole Ohlbrock and Thomas Oberbichler and Pierluigi D'Acunto and Stefana Parascho},
journal= {arXiv preprint arXiv:2111.02607},
year = {2022}
}