EEpBeton - Development of a data-driven material model for real-time property prediction in concrete production and quality assurance

The production of concrete that does not have the properties required by the customer can result in economic losses and legal risks for the producer. For this reason, a prototype assistance system for concrete plant operators is to be developed as part of the project at the Department of Measurement and Control Technology. An important sub-goal is the creation of forecast models using machine learning methods for the 28-day compressive strength of concrete, which is an important parameter.

In order to obtain data, the concrete pilot plant of the cooperation partner will be re-instrumented and corresponding tests will be carried out, including measurements of relevant influencing variables and the recording of test specimen properties.

M.Sc. Farzad Rezazadeh Pilehdarboni

September 2021 - December 2023

State of Hesse LOEWE 3