Randomness in Robotically Fabricated Micro-Acoustic Patterns

Abstract

Randomness can introduce degrees of variation as part of a highly controlled design process, which can be of particular significance in the context of acoustic performance in architecture. This paper presents research into robotic fabrication of surfaces with acoustic micro-patterns that can change the acoustic response of space. It explores the design affordances for acoustically efficient 1:10 scale model prototypes, from parametric modeling to scale model production to physical evaluation. Acoustic reflective properties of surface patterns are investigated for scattering coefficients, in order to derive statistical data on acoustic properties of these surfaces, and to deduce design rules. The robotic subtractive process particularly invests variations and disturbances to originally coded fabrication sequences that lead to different pattern outcomes. Changes to protocols and workflows change the equations of design through shuffling of multiple criteria: from multiple sequences in a production process to intuitive impacts of the designer on a preset tooling and workpath; from computational design code to acoustic effect.