Research Outputs
Computation of the temperature distribution in biomass boilers with reciprocating grate furnaces
Precipitation of Coarse Fly Ash Particles in Wood Chip Boilers - A Comparison of Experimental and Numerical Investigations
Messtechnische Erfassung des hygrothermischen Verhaltens unterschiedlicher Estrichmischungen bei definierten Randbedingungen
Complex glass facade modelling for Model Predictive Control of thermal loads: impact of the solar load identification on the state-space model accuracy
Above and beyond improving the efficiency of the building envelope and the energy supply system, the demand-side flexibility in terms of load shifting and peak reduction are vital factors in further increasing the share of volatile renewable energy sources. The thermal activation of building components, like floors and ceilings, enables the cost-effective potential for short-term energy storage to fulfil these requirements. In order to exploit the storage capabilities of active building systems, a reliable model predicted control (MPC) approach is required. However, primarily if a large glass façade element is utilised, the appropriate modelling of solar loads is critical for an effective MPC operation. Hence, based on a dynamic building simulation tool, a characteristic map for the solar load prediction of a glass façade system in combination of external venetian blinds was generated to enhance the state-space model approach for the MPC algorithm. The comparison with a conventional state-space model approach shows the integration of a detailed characteristic map can only marginally improve the prediction accuracy. The additional information required from the glass façade manufacturer and the associated simulation effort is not of substantial value. In contrast, the conventional grey box model enables an entirely datadriven parameter identification, without the manufacturers’ data. Furthermore, the MPC optimisation procedure, searching for the best control strategy, can be more efficient (solver-based optimisation), with shorter computing turnaround times.
On the Influence of the Reynolds-Stress Anisotropy Tensor on the Prediction of Wall-Affected Three-Dimensional Room Airflows
It is well known that the turbulence anisotropy has a remarkable influence on the flow of three dimensional wall jets. So the accurate simulation of room airflows with air supplies mounted just below the ceiling requires a highlevel turbulence closure. Therefore in this paper the potential for the improvement of room airflow prediction by using different Reynolds stress models and a new nonlinear eddy viscosity turbulence model are discussed. For this purpose detailed three dimensional PIV measurement results of the velocity distribution and the Reynolds stress in a symmetrical model room are compared with the calculations using different turbulence models.