What do you want to explore or achieve most in this project? What is the vision behind the project? Is the use of data part of that?
Our goal was to make morphing materials design tools more assistive and informative during computer-aided design processes. Unlike conventional design practices that deal with static objects, morphing materials are transformative and actuatable, and these factors are often not captured accurately by conventional design tools. As a result, designers have to resort to physical prototyping even at the early stages of design processes, making it time-consuming to carry out a project. To overcome this issue, we take inspiration from the human mind’s ability that, given sufficient observations of similar events, we would eventually become capable of predicting what would happen next in an instant based on what we see. This process can be approximated by using machine learning as an analogy of the human mind and a dataset of morphing materials transformations as the observations. On the other hand, fast and accurate simulators are also experts in the targeted domain, thus can be more assistive and informative to both novice and expert users. In the future, we are hoping that with SimuLearn as a backend engine, morphing materials design tools would become the users’ collaborative partners as opposed to being passive tools.