Data Acquisition for Enhancing Human-Informed Topology
Optimization
Name
Wang-zachw23-MEng-CEE-2025-thesis.pdf
Description
Thesis PDF
Size
1.26 MB
Format
Adobe PDF
Checksum (MD5)
9fa4ab8fb0df8d173eed4919d1d06710
Author(s)
Wang, Zach
Advisor(s)
Carstensen, Josephine V.
Date Issued
May 2025
Publisher
Massachusetts Institute of Technology
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
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