| id |
acadia16_72 |
| authors |
Harrison, Paul |
| year |
2016 |
| title |
What Bricks Want: Machine Learning and Iterative Ruin |
| doi |
https://doi.org/10.52842/conf.acadia.2016.072
|
| source |
ACADIA // 2016: POSTHUMAN FRONTIERS: Data, Designers, and Cognitive Machines [Proceedings of the 36th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-77095-5] Ann Arbor 27-29 October, 2016, pp. 72-77 |
| summary |
Ruin has a bad name. Despite the obvious complications, failure provides a rich opportunity—how better to understand a building’s physicality than to watch it collapse? This paper offers a novel method to exploit failure through physical simulation and iterative machine learning. Using technology traditionally relegated to special effects, we can now understand collapse on a granular level: since modern-day physics engines track object-object collisions, they enable a close reading of the spatial preferences that underpin ruin. In the case of bricks, that preference is relatively simple—to fall. By idealizing bricks as rigid bodies, one can understand the effects of gravitational force on each individual brick in a masonry structure. These structures are sometimes able to ‘settle,’ resulting in a stable equilibrium state; in many cases, it means that they will simply collapse. Analyzing ruin in this way is informative, to be sure, but it proves most useful when applied in series. The evolutionary solver described in this paper closely monitors the performance of constituent bricks and ensures that the most successful structures are emulated by later generations. The tool consists of two parts: a user interface for design and the solver itself. Once the architect produces a potential design, the solver performs an evolutionary optimization; after a few hundred iterations, the end result is a structurally sound version of the unstable original. It is hoped that this hybrid of top-down and bottom-up design strategies offers an architecture that is ultimately strengthened by its contingencies. |
| keywords |
rigid body analysis, machine learning, multi-agent structural optimization, sensate systems |
| series |
ACADIA |
| type |
paper |
| email |
|
| full text |
 file.pdf (777,837 bytes) |
| references |
Content-type: text/plain
|
(2013)
 Aggregate Architecture: Simulation Models for Synthetic Non-convex Granulates
, Adaptive Architecture: Proceedings of the 33rd Annual Conference of the Association for Computer Aided Design in Architecture, edited by Philip Beesley, Omar Kahn, and Michael Stacey. Cambridge, ON: ACADIA. 301–310.
|
|
|
|
|
Dierichs, Karola, and Achim Menges (2012)
Material and Machine Computation of Designed Granular Matter: Rigid-Body Dynamics Simulations as a Design Tool for Robotically-Poured Aggregate Structures Consisting of Polygonal Concave Particles.
, Digital Physicality: Proceedings of the 30th eCAADe Conference, vol. 2, edited by Henri Achten, Jiri Pavlicek, Jaroslav Hulin, and Dana Matejovska. Prague: eCAADe. 711–719
|
|
|
|
|
Dillenburger, Benjamin, Markus Braach, and Ludger Hovestadt (2009)
Building Design as Individual Compromise Between Qualities and Costs: A General Approach for Automated Building Generation Under Permanent Cost and Quality Control
, Joining Languages, Cultures, and Visions–Proceedings of the 13th International CAAD Futures Conference, edited by Temy Tifadi and Tomás Dorta. Montreal, QC: CAAD. 458–471
|
|
|
|
|
Grodecki, Louis (1978)
Gothic Architecture
, New York: Harry N. Abrams
|
|
|
|
|
Heyman, Jacques (1999)
The Stone Skeleton: Structural Engineering of Masonry Architecture
, Cambridge, UK: Cambridge University Press
|
|
|
|
|
King, Ross (2000)
Brunelleschi’s Dome: The Story of the Great Cathedral in Florence
, London: Chatto & Windus
|
|
|
|
|
Meredith, Michael, and Hilary Sample (2013)
Everything All at Once: The Software, Videos and Architecture of MOS
, New York: Princeton Architectural Press
|
|
|
|
|
Raymond, Eric S. (1999)
The Cathedral and the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary
, Sebastopol, CA: O’Reilly Media
|
|
|
|
|
Rippmann, Matthias, Lorenz Lachauer, and Phillipe Block (2012)
Interactive Vault Design
, International Journal of Space Structures 27 (4): 219–230
|
|
|
|
|
Rosenman, M. A. (1996)
The Generation of Form Using an Evolutionary Approach
, Artificial Intelligence in Design ‘96, edited by John S. Gero and Fay Sudweeks. Boston, MA: Kluwer Academic Publishers. 643–662
|
|
|
|
|
von Buelow, Peter (2002)
Using Evolutionary Algorithms to Aid Designers of Architectural Structures
, Creative Evolutionary Systems, edited by Peter J. Bentley and David W. Corne. San Francisco, CA: Morgan Kaufmann. 315–336.
|
|
|
|
|
Wolfram, Steven (2002)
New Kind of Science
, Champaign, IL: Wolfram Media
|
|
|
|
| last changed |
2022/06/07 07:49 |
|
