Optimal vault problem -- form finding through 2D convex program

TL;DR

This paper introduces a convex optimization framework for designing minimal-volume, load-bearing vaults that efficiently transfer loads via pure compression, combining analytical and numerical methods for optimal structural solutions.

Contribution

It develops a dual convex programming approach for form finding of optimal vaults, including analytical solutions and a numerical grid-shell design method.

Findings

Optimal vaults minimize volume and compliance.

Convex duality reduces 3D vault design to 2D problems.

Numerical methods produce highly precise grid-shell approximations.

Abstract

This work puts forward a form finding problem of designing a least-volume vault that is a surface structure spanning over a plane region, which via pure compression transfers a vertically tracking load to the supporting boundary. Through a duality scheme, developed recently for the design of pre-stressed membranes, the optimal vault problem is reduced to a pair of mutually dual convex problems $(\mathcal{P})$, $(\mathcal{P}^*)$ formulated on the 2D reference region. The vault constructed upon solutions of those problems is proved to be both of minimum volume and minimum compliance; analytical examples of optimal vaults are given. Through a measure-theoretic approach, thus found optimal vaults are proved to solve the Prager problem of designing a 3D structure that by compression carries a transmissible load. The ground structure method applied to the convex problems furnishes a pair of discrete, conic quadratic programs $(\mathcal{P}_X)$, $(\mathcal{P}_X^*)$ leading to optimal design of grid-shells. By adopting the member-adding adaptive technique this pair is efficiently tackled numerically, which is demonstrated on a number of examples where highly precise grid-shell approximations of optimal vaults are found.