Early building design using multi-objective data approaches

During the design process in architecture, building performance and human experience are increasingly understood through computation. Within this context, this dissertation considers how data science and interactive optimization techniques can be combined to make simulation a more effective component of a natural early design process. It focuses on conceptual design, since technical principles should be considered when global decisions are made concerning the massing, structural system, and other design aspects that affect performance. In this early stage, designers might simulate structure, energy, daylighting, thermal comfort, acoustics, cost, and other quantifiable objectives. While parametric simulations offer the possibility of using a design space exploration framework to make decisions, their resulting feedback must be synthesized together, along with non-quantifiable design goals.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Architecture

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2019

Author dc:creator

• Brown, Nathan C.(Nathan Collin)

Advisor dc:contributor.advisor

• Caitlin T. Mueller.

• Architecture.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/123573

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/123573