© All Rights Reserved.

Form Finding Lab.
Princeton University

Back to Home

Award: IMI Innovation Award – AR Masonry

  • News

We are thrilled to announce that our innovative work in masonry and augmented reality, in collaboration with SOM, was recognized last night in Washington, D.C., with the prestigious JBC Masonry Innovation Award from the International Masonry Institur. This award, named in honor of Joan B. Calambokidis—President of the International Masonry Institute (IMI) from 1995 to 2017—celebrates groundbreaking advancements in the field. It is a great privilege to have our efforts acknowledged at this level, and we look forward to continuing to push the boundaries of design and technology in masonry

More insights

Publication: Digital guidework for augmented thin-tile vaulting construction

Masonry vaults are among the most elegant and efficient structural forms, yet their construction has long been slowed down by costly falsework and guidework.
Our team explored a new path: augmented reality as digital guidework. Instead of rigid scaffolding, masons can now follow holographic projections that provide just the right amount of visual support—keeping builders in control of their analog craft.
In field tests, this approach improved productivity by ~30% while achieving remarkable accuracy (within 1% of the vault span). Looking ahead, interactive mixed-reality could further boost precision, speed, and even training opportunities.
This work shows how centuries-old craftsmanship and cutting-edge technology can merge to keep masonry vaulting not just viable, but visionary. Read more about our findings here https://lnkd.in/d4-KcCxS

Read more >

Publication: Design of purely compressive shells under vertical and horizontal loads through Machine Learning-driven form-finding

We are excited to share our latest research on advancing the design of shell structures under challenging loading conditions. Traditionally, form-finding methods for masonry vaults focus on vertical loads, but extreme wind or seismic forces introduce significant design and safety complexities.
Our new paper explores an alternative to computationally intensive optimisation steps in Membrane Equilibrium Analysis. Using machine learning regression techniques—XGBoost, Random Forests, and k-Nearest Neighbours—we identify optimal Airy Stress Function parameters to improve efficiency and maintain structural integrity.
Case study results show that these methods can reduce computational demands while achieving material-efficient designs, with k-Nearest Neighbours delivering the best performance in our tests.
Read more about our findings here: https://lnkd.in/eEnu8sEW

Read more >

Exhibit: Alternative Skies at the Venice Architecture Biennale, Italy

We’re pleased to share that our latest paper, “Numerical modeling of cantilevered bigon arm mechanics under gravity,” by Axel Larsson @axla.io and Sigrid Adriaenssens is now published Open Access in the Journal of the Mechanics and Physics of Solids (link in bio)

In this work, we investigate the stability regimes of reconfigurable bigon arms under gravitational loading—offering new insights into multi-stable structural systems.

Read more >