Data Acquisition for Enhancing Human-Informed Topology Optimization

This thesis presents a survey application designed for the future development of HumanInformed Topology Optimization (HiTop) towards the deeper integration of optimization and real-world feasibility. Topology optimization produces high-performance designs by optimally distributing material, but its application in professional environments remains limited due to fabrication constraints and inflexible design workflows. To address this, the Carstensen Group developed HiTop, which integrates optimization algorithms with human experience, allowing engineers to modify the computer design based on their professional judgment. Thus, the future development of HiTop requires real-world data on human preferences. This project introduces a web-based survey app integrated with Qualtrics. It presents users with various design scenarios and computer-optimized designs, and records their modifications and reasoning. A preliminary survey collected responses from 13 professionals and engineering students. Preliminary findings suggest that engineers consistently focus on similar regions of interest, even when motivated by different reasons. However, the sample size is too small to make any statistically significant conclusions. While the platform mostly performed as intended, a bug related to data storage was discovered during analysis. The issue has since been resolved, and the tool is now fully functional and ready for broader deployment.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Civil and Environmental Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2025

Author dc:creator

• Wang, Zach

Advisor dc:contributor.advisor

• Carstensen, Josephine V.

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/162520

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/162520