Research Projects
There are 4 results.
InSite - Monitoring and evaluation of innovative demonstration buildings
In the "Stadt der Zukunft" and "Smart City Initiative" programmes, a large number of demonstration projects have been implemented in recent years. To be able to evaluate the developed innovations in a uniform and comparable form and to make the knowledge gained accessible to implementers, InSite subjects 10 selected objects from these programmes to energy and ecological monitoring as well as sociological surveys over a period of 24 months. The interpreted results are publicly available as a published study and as an interactive online platform.
LenA circular houses - Demonstration of the circular architecture design process for circular andreuse building based on the lighthouse project LenA
The main objective is to research and demonstrate the positive climate impact of reuse in the construction industry. Through this (re)use of components, products and material groups, large shares of the emissions generated by the construction industry can be avoided and contribute to the targeted climate neutrality. Another aspect is to design the connections of the components in such a way that they can be deconstructed and reused.
Earthen building 2.0: Earthen building of the future - The art of craftsmanship based on engineering approaches
The exploratory project investigates the suitability of fiber optic sensors for the long-term monitoring of the deformation behavior of rammed earth wall elements under moisture and temperature fluctuations (shrinkage) as well as loads (creep). The experimental findings will be integrated into a finite element model to simulate failure behavior under load.
AI4FM - Artificial Intelligence for Facility Management
AI-based anomaly and fault detection in buildings. Digital twins of buildings with simulation models for testing and optimizing rule-based fault detection methods. Mining of the recorded time-series data from existing Building Management Systems to train Machine Learning models for fault detection.