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Heschl, Christian
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Official Name
Heschl, Christian
Alternative Name
Heschl, C
Main Affiliation
Akademische Titel
Prof.(FH) Dipl.-Ing. (FH) Dr.
Email
christian.heschl@fh-burgenland.at
Scopus Author ID
50161591800
Status
staff
Research Outputs
Now showing 1 - 10 of 34
- PublicationComputation of the temperature distribution in biomass boilers with reciprocating grate furnaces(2015-12)
; ; ;Nöhrer, Dietmar ;Inthavong, Kiao; Tu, Jiyuan148 1 - PublicationInnovative central building energy management(9th International Conference on Indoor Climate of Buildings, Štrbské pleso 2016, 2016-11-29)
; ; Paar, Klaus448 1 - PublicationCharacterization of non-invasive pipe flow temperature measurement(2017-10)
; ;Derler, Bernhard ;Seidl, Christian6 3 - PublicationTowards non-invasive temperature measurements in HVAC: A characterization and correction approach(IEEE, 2019-06)
; ; ; ; ;Sauter, ThiloTreytl, AlbertThe existing building stock within the European Union is responsible for a considerably huge amount of the total energy consumed. This has prompted legislative actions that focus on increasing the efficiency of Heating, Ventilation and Air Conditioning facilities by employing building automation and electronic monitoring systems. The fluid flow temperature in the hydraulic grid of a building is therefore an essential parameter to be measured, where clamp-on temperature sensors are often applied due to their simple and cost-effective installation. As the plumbing industry heads towards non-metal pipe materials with low thermal conductivity, the applicability of non- invasive measurement procedures diminishes. In this context, a characterization approach of non-invasive temperature measurements that is linked to a thermal resistance model is experimentally validated. Based on that, a correction algorithm to reduce the deviation between measured surface and the fluid flow temperature for steady state conditions is derived and tested. The presented approach provides sufficient characterization and correction performance, albeit several limitations have to be taken into consideration.423 1Scopus© Citations 1 - Publication
134 1 - PublicationOn the Influence of the Reynolds-Stress Anisotropy Tensor on the Prediction of Wall-Affected Three-Dimensional Room Airflows(2008-10)
; Sanz, WolfgangIt 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.64 215 - PublicationComplex glass facade modelling for Model Predictive Control of thermal loads: impact of the solar load identification on the state-space model accuracyAbove 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.
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