eCommons

 

Generative Methods for Urban Design and Rapid Solution Space Exploration

Other Titles

Author(s)

Abstract

Rapid population growth and climate change are driving urban renewal and urbanization at massive scales. New computational methods are needed to better support urban designers in developing sustainable, resilient, and livable urban environments. Despite the emergence of tools for mobility, public health, and environmental performance simulation, strategic urban design space exploration and multi-objective optimization of masterplans remain challenging due to a lack of generalizable methods for urban form generation. A variety of computational approaches have been proposed to facilitate the automatic generation of urban form. However, most of these developments have produced siloed tools and disconnected workflows. This research introduces a new generative urban design toolkit for rapid design space exploration and multi-objective optimization of masterplans that integrates with the Rhino/Grasshopper ecosystem of urban analysis and environmental performance simulation tools. We implement generative methods based on tensor fields. Tensor fields provide a generalized way to encode contextual constraints such as waterfront edges, terrain, view-axis, existing streets, landmarks, and non-geometric design inputs such as network directionality, desired densities of streets, amenities, buildings, and people as forces that the user can weigh. This allows users to generate various urban fabric configurations that resemble real-world cities with few inputs. Furthermore, this facilitates the sampling of complex parametric design solution spaces for multi-objective optimization while keeping dimensionality and computational overhead manageable. A series of case studies demonstrates flexibility, applicability and shows how modelers can identify design and environmental performance synergies that would be hard to find otherwise.

Journal / Series

Volume & Issue

Description

27 pages

Sponsorship

Date Issued

2021-08

Publisher

Keywords

computational design; Generative; masterplans; modeling; multi-objective optimization; tensor fields

Location

Effective Date

Expiration Date

Sector

Employer

Union

Union Local

NAICS

Number of Workers

Committee Chair

Dogan, Timur

Committee Co-Chair

Committee Member

Sabin, Jenny E.

Degree Discipline

Architecture

Degree Name

M.S., Architecture

Degree Level

Master of Science

Related Version

Related DOI

Related To

Related Part

Based on Related Item

Has Other Format(s)

Part of Related Item

Related To

Related Publication(s)

Link(s) to Related Publication(s)

References

Link(s) to Reference(s)

Previously Published As

Government Document

ISBN

ISMN

ISSN

Other Identifiers

Rights

Rights URI

Types

dissertation or thesis

Accessibility Feature

Accessibility Hazard

Accessibility Summary

Link(s) to Catalog Record