Metamaterials created through artificial intelligence (AI) models are a new way to engineer materials with a wide range of properties. Variational autoencoder (VAE) is an AI model that allows engineers to quickly design materials with specific properties from the latent space. The motivation for this paper is learning how to use AI as a tool for future architectural engineers. Creating new meta materials with complex geometry allows architectural engineers to design sustainable buildings and cities with strong materials. The methods of this paper describe the research that has been done, including running codes for different AI models and utilizing VAE model for generating materials. The results look at the output generated by the code and its application towards various fields including architectural engineering is discussed. The discussions observe the importance of using AI as a tool for faster decision making. The conclusions discuss the future of AI.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Natarajan, Priyalakshmi

Subject

• Innovation
• Learning
• Project-Based Learning
• Infrastructure

Publisher

• Worcester Polytechnic Institute

Identifier

• 112581
• E-project-080223-133037

Advisor

• Towner, Walter Thomas
• Cheng, Lin

Year

• 2023

UN Sustainable Development Goals

• 9 - Industry, Innovation and Infrastructure

Date created

• 2023-08-02

Resource type

• Major Qualifying Project

Major

• Architectural Engineering

Source

• E-project-080223-133037

Rights statement

• In Copyright

Last modified

• 2023-08-22