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

2019 2019 2018 2018 2017 2017 0.0 0.0 0.2 0.2 0.4 0.4 0.6 0.6 0.8 0.8 1.0 1.0

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    Publication
    System efficiency of PVT-collector driven heat pumps
    (EDP Sciences, 2019)
    Hengel, Franz 
    ;
    Heschl, Christian 
    ;
    Inschlag, Franz 
    ;
    Klanatsky, Peter 
    Standard heat pump (HP) systems with horizontal ground heat exchangers (HGHE) are commonly designed based on arbitrary knowledge gained over time and the use of the rule of thumb. Where an undersizing of the HGHE occurs, the HP efficiencies are lowered. Undersizing could result as a consequence of underestimating the soils thermal conductivity. Therefore, this paper considers the combined photovoltaic and solar thermal (PVT) collectors as an extension to standard HP heating systems with a HGHE in single-family houses with the possibility of improving the COP of the HP at a later stage and effortlessly. With the implemented hydronic scheme, the PVT-collector is also used to regenerate the soil around the ground to increase the temperature level of the heat source resulting in improved performance. However, the efficiency potential of the PV-Cells due to active cooling of the modules is analyzed. The results show an increase of the seasonal performance factor (SPF) of 4.1 % and higher electric energy output of 4.4% due to active cooling of the PV-Cells while energy consumption of the regeneration pump is covered.
      437  934
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    Publication
    Exponential pattern recognition for deriving air change rates from CO2 data
    (Institute of Electrical and Electronics Engineers (IEEE), 2017)
    Wenig, Florian 
    ;
    Klanatsky, Peter 
    ;
    Heschl, Christian 
    ;
    Mateis, Cristinel 
    ;
    Dejan, Nickovic 
    A novel procedure for automated determination of air change rates from measured indoor CO2 concentrations is proposed. The suggested approach builds upon a new algorithm to detect exponential build-up and decay patterns in CO2 concentration time series. The feasibility of the concept is proved with a test run on synthetic data that shows a good reproduction of the previously defined air change distribution. The demonstration continues with test runs on CO2 datasets measured in the kitchen and the sleeping room of two residential buildings. The derived air change rates were within the expected distributions and ranges in both cases when natural or mechanical ventilation was used.
      255  53540Scopus© Citations 3