In the context of digitalization in the industry, a variety of technologies has been developed for system integration and enhanced team collaboration in the Architecture, Engineering and Construction (AEC) industry. Multidisciplinary design requirements are characterized by a high degree of complexity. Early design methods often rely on implicit or experiential design knowledge, whereas contemporary digital design tools mostly reflect domain-specific silo thinking with time-consuming iterative design processes. Yet, the early design stages hold the greatest potential for design optimization. This paper presents a framework of a multidisciplinary computational integration platform for early design stages that enables integration of AEC domain-specific methods from architecture, engineering, mathematics and computer science. The platform couples a semantic integrative mixed reality sketching application to a shape inference machine-learning based algorithm to link methods for different computation, simulation and digital fabrication tasks. A proof of concept of the proposed framework is presented for the use case of a freeform geometry wall. Future research will explore the potential of the framework to be extended to larger building projects with the aim to connect the method into BIM-processes.


Reisinger, J., Rasoulzadeh, S., Kovacs, B. I., Ferschin, P., Vasylevska, K., Hensel, M. U., Kovacic, I., & Wimmer, M. (2023). Integrating AEC Domain-Specific Multidisciplinary Knowledge for Informed and Interactive Feedback in Early Design Stages. In S. Skatulla & H. Beushausen (Eds.), Advances in Information Technology in Civil and Building Engineering: Proceedings of ICCCBE 2022 - Volume 2 (pp. 153–170). Springer. https://doi.org/10.1007/978-3-031-32515-1_12