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Generative Crossed Timber System
Fall 2021
Selected Project
Chris MacDonnell, Ziwei Shen, Yuwen Zhou

Generative Crossed Timber System


The project “Generative Crossed Timber System” creates an open-ended timber system that can form different architectural elements by applying the notion of generative design, the materiality of wood, and digital fabrication. This project was named the best in student design in Fast Company’s 2022 Innovation by Design Awards.

Project Development

A cross-referencing method—which includes geometry study, material study, fabrication tests, and structural analysis—was developed by this research collective to serve as the driving force of this project. The feedback among each approach provides guidelines for future research and practice. The geometry study shaped the form-searching process and provided theoretical support for the unit design. It provided greater understanding of the physical properties of different geometries and connection methods. The material study focused on material dimension, grain orientation, stiffness, and elastic properties.

Three key elements of the final design came from the fabrication test: 1) the milling speed of the current robot setup limits the scale of final structure, 2) the dimension limitation and maximum load of the robot affects the form and size of the unit, and 3) the accuracy of the robotic fabrication and the bending behavior of wood material during the change of air humidity required more tolerance to be considered during the unit design process. The final design was also guided by the feedback of the structural analysis, which centered around the structural performance.

The final form consists of 81 pieces of pine lumber that are only connected by notches of different dimensions. The single size of each piece is 1”x 7” x 28”. The column-like structure can be re-formed to other architectural elements by rearranging the units and can be extended to other scales by aggregating through the opened notches.

Author and Image Credit

Chris MacDonnell, Ziwei Shen, Yuwen Zhou.


Ehsan Baharlou