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.
Müller et al. (Mon,) studied this question.