Design Suggestions for I-Shaped Knee Connections with Conditional Variational Autoencoder

Abstract

Conditional variational autoencoder (CVAE) are used throughout the literature in the sense of performance-based generative design. One main advantage is the possibility of an inverse problem formulation, allowing the exploration of design possibilities/variations. This allows for a more dynamic design, including performance and code-based parameters as a preselection criterion, conditioning the overall design solutions. The work in the presented paper takes this general idea of CVAEs and applies it to connection design, e.g., welded knee connections from I-shaped sections. All created data sets used for the training of the models are based on component-based finite element simulations (CBFEM), performed with the software IDEA StatiCa Connection and the built-in Python API. The overall focus of this paper is specifically set on data creation/post-processing, its manipulation and incorporation in a forward and inverse design loop to demonstrate its possibilities in a more dynamic and intuitive design process compared to the classical workflow.