Glass fabrication

  • Rima Ajlouni

Abstract

In architecture, the prevalence of computational design and digital fabrication has led to an increase in exploration of casting modulated geometry using fabricated molds. However, the use of mold making strategies are often limited to casting materials that conform easily to mold geometry (i.e. concrete, plaster, resin, ceramics, etc.). It is rarely that fabrication strategies are used to explore materials with challenging behavioral properties such as glass. As a result, glass in its non-flat form has been underutilized in contemporary architecture. Because of its complicated physical behavior and the technical difficulties associated with the fabrication processes, architecture education often avoids exploring such medium. One key challenge with casting glass using fabricated refractory molds relates to understanding the behavior of glass under certain physical conditions and temperature profiles. If such parameters are not anticipated, the geometry of the final casted elements can be substantially different from the design intentions. This research argues that computation can be used to predict glass forming behavior under different temperature profiles, which can inform the design and fabrication processes. The goal is to highlight the importance of integrating the complexities of the physical reality into the design and fabrication processes, especially within the context of the educational experience. To contribute to this creative discourse this paper explores the limits of precision from computation to fabrication as it relates to casting glass. The objective is to design and test an algorithm for predicting edge/corner geometry of casted glass under different temperature profiles. Physical experiments are used to evaluate and recalibrate the prediction algorithm. Results show that the digital predictions are within acceptable tolerance and can be enhanced using data from physical experiments.

Published
2019-05-18
How to Cite
Ajlouni, R. (2019). Glass fabrication. ARCC Conference Repository, 1(1). Retrieved from https://www.arcc-repository.org/index.php/repository/article/view/667