Towards an automatic optimization framework for performance oriented precast concrete design
- The aim of the project LeBeDigital is to present opportunities of digitalization for concrete applications and show a way towards a performance oriented material design.
Due to the high complexity of the manufacturing process of concrete and the range of parameters affecting the effective composite properties, a global optimization is challenging.
Currently, most optimization is only carried out on a narrow scope related to the respective players, e.g. a mix optimization for a target strength, or a design optimization for minimum weight, using a given mix. To enable a path toward a full global optimization
requires a reproducible chain of data, accessible for all contributors.
We propose a framework based on an ontology, which automatically combines experimental data with numerical simulations. This not only simplifies experimental knowledge transfer, but allows the model calibration and the resulting simulation predictions to be
reproducible and interpretable. In addition to anThe aim of the project LeBeDigital is to present opportunities of digitalization for concrete applications and show a way towards a performance oriented material design.
Due to the high complexity of the manufacturing process of concrete and the range of parameters affecting the effective composite properties, a global optimization is challenging.
Currently, most optimization is only carried out on a narrow scope related to the respective players, e.g. a mix optimization for a target strength, or a design optimization for minimum weight, using a given mix. To enable a path toward a full global optimization
requires a reproducible chain of data, accessible for all contributors.
We propose a framework based on an ontology, which automatically combines experimental data with numerical simulations. This not only simplifies experimental knowledge transfer, but allows the model calibration and the resulting simulation predictions to be
reproducible and interpretable. In addition to an optimized set of parameters, this setup allows to study the quality and uncertainty of the data and models, as well as giving information about optimal experiments to improve the data set.
We will present the proposed optimization workflow, using the example of a precast concrete element. The contribution will focus on the workflow and challenges of an interoperable FEM formulation.…