Towards integrated performance-driven generative design tools

By Kristina Shea, R. Aish, M. Gourtovaia. 2004

347 citations recorded by the source corpus.

Subfields: Architecture, Building and Construction, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/2603ce24086ffa48a2639b5bc0d1910c18876dc2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Architecture

1. Ikjin Lee
2. Sangeun Oh
3. Seongsin Kim
4. Namwoo Kang
5. Yongsu Jung

In Mechanical Engineering

1. Ikjin Lee
2. Sangeun Oh
3. Seongsin Kim
4. Namwoo Kang
5. Yongsu Jung

Citations in the corpus

• Computational design in architecture: Defining parametric, generative, and algorithmic design (2020, background): “GD includes such processes and other algorithmic approaches, as mentioned by (Bernal et al., 2015; Bukhari, 2011; Chase, 2005; Fasoulaki, 2008; Humppi and Österlund, 2016; Leitão et al., 2014; McCormack et al., 2004; Mitchell, 1975; Oxman, 2008; Shea et al., 2005).”
• Deep Generative Design: Integration of Topology Optimization and Generative Models (2019, methodology): “The generative design is one of the design exploration methods performed by typically varying design geometry parametrically and assessing the performance of output designs [18,19].”