Please use this identifier to cite or link to this item:
http://arks.princeton.edu/ark:/88435/dsp01p5547v56w
Title: | Castings and Mass Timber: A case study of a modernized traditional construction technique |
Authors: | Skepasts, Mark |
Advisors: | Adriaenssens, Sigrid |
Department: | Civil and Environmental Engineering |
Certificate Program: | Applications of Computing Program |
Class Year: | 2022 |
Abstract: | Timber engineering has gained increased popularity in the Architecture, Engineering and Construction industry. More people see a lot of benefits with wood construction, from prefabrication to sustainability. Moreover, with the increase in computational software, we see wood present in complex 3D structures – such as discrete gridshell and tree structures. The research attempts to shed light on efficient cast connections that connect timber members in complex 3D forms. Specifically, the Thesis is a case study on a discrete timber gridshell. It attempts to define a cast connection solution that is efficient and economical. Castings are most effective when solving complex 3d shapes and when their geometry can repeat throughout a structure. Thus, this Thesis attempts to regularity throughout gridshell nodes. More explicitly, the angle at which the members approach the node as there are discrepancies in these angles throughout the structure. Through computational analysis and custom algorithms, this thesis studies the feasibility of repeated cast connections throughout this structure. Although no concrete solutions are formed at the end of this research, it opens doors for further study and conversation on casting, mass timber and complex 3D forms. |
URI: | http://arks.princeton.edu/ark:/88435/dsp01p5547v56w |
Type of Material: | Princeton University Senior Theses |
Language: | en |
Appears in Collections: | Civil and Environmental Engineering, 2000-2024 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
SKEPASTS-MARK-THESIS.pdf | 3.39 MB | Adobe PDF | Request a copy |
Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.