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Are you our next PhD in Fault Detection and Diagnosis of HVAC system?
The Department offers a BSc in Building Science (Bouwkunde) and MSc programmes in Architecture, Building and Planning and Construction Management and Engineering. Education and research in the Department focus on the development and use of technology for the design and construction of a comfortable, healthy and sustainable built environment. The Department’s philosophy is “Beyond Building”, which reflects our multidisciplinary, integral and innovative approach in the construction, evaluation and improvement of buildings and urban areas. Our research is based on fundamental scientific insights and methods and their application for the built environment.
The research will be embedded in the group “Building Services (BS)” of the unit Building Physics & Services (BPS). Research and teaching at this unit aim at creating and maintaining a sustainable, healthy, comfortable and productive indoor and outdoor environment. The focus lies on energy aspects and processes including heat and mass transfer in the indoor and outdoor built environment, indoor and outdoor air quality, lighting, heating, ventilation and air-conditioning. The unit has about 90 scientific staff (including 70 PhD researchers) and ample physical laboratory facilities (supported by 6 technicians). The multidisciplinary staffing of the unit enables the afore mentioned approach and makes the unit rather unique.
Technological developments in the field of sensors, energy meters and data transport and storage make it possible to monitor the performance of buildings in real time, such as the energy consumed and produced, the indoor environment parameters and the performance and aging of installations (condition measurement). These developments can help to make buildings more efficient and sustainable by using smart systems. These systems should be able to: Permanently monitor, track, analyse and adjust energy consumption; To test the energy efficiency of the building, to detect efficiency losses of technical building systems, and to inform the manager of the facilities or technical installations about the possibilities to improve this.
The current building management systems cannot comply with this. Automated error detection and control can only be based on the analysis of data flows from the installation, building use (user data), the building (data from the building management system) and on data flows from the supply side. Such an analysis can only be achieved scalable by applying data analysis and machine learning/artificial intelligence methods to the data streams. There are no standards for modular diagnostic tools, and integration with installation design, GBS, and maintenance and management tools is absent. It is important to be able to link the available data from the GBS with the functional description of the schemes and to do this modularly to make the complexity manageable. Installation technical knowledge must be linked to energy data modelling techniques and to data analytics and machine learning techniques. The task will be the development of error diagnostic plugins based on hybrid models and data analysis techniques (combination of artificial intelligence and physical models).Functie-eisen
To complement this environment and for the specific project mentioned above, we are looking for an outstanding candidate that meets the following requirements:
The project is expected to start in June 2021. More information about the project may be obtained from prof.ir. Wim Zeiler, w.zeiler[at]bwk.tue.nl, www.bwk.tue.nl/bwk/zeiler
For information about terms of employment, click here or contact HRServices.BE[at]tue.nl.
Please visit www.tue.nl/jobs to find out more about working at TU/e!
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