Geissler, Achim
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Gravity ventilation for interior bathrooms
Based on the extensive experience of a building cooperative with interior bathroom gravity (shaft) ventilation in existing apartment buildings, the replacement buildings constructed at the same location are also equipped with gravity ventilation. The aim of the project described here is to demonstrate the possibilities and limitations of gravity ventilation in one of the new replacement buildings by means of monitoring. Detailed monitoring over a complete year recorded the behaviour and effectiveness of the gravity ventilation in all seasons. In winter, gravity ventilation leads to higher air change rates in interior bathrooms than in summer. In general, humidity can be removed with gravity ventilation except in summer, when after a shower the bathroom door stays closed for 24 h. In summer when the indoor and ambient temperature is the same the gravity ventilation does not work. In this case, the interior bathroom should be ventilated by the main apartment ventilation, e.g., while the bathroom door and other room doors and windows are open at the same time. In summer, doors and windows are often open and the gravity ventilation summer problem can be viewed as negligible. Therefore, gravity ventilation is a good alternative to other ventilation systems in interior bathrooms.
In‐situ U‐Wert‐Messung – Teil 1: Vergleich von Verfahren und Einflüsse in Heizkammerversuchen
U-Wert-Messungen vor Ort eigenen sich für opake Bauteile unbekannter Konstruktion, bei denen eine zerstörungsfreie Aussage zu den thermischen Eigenschaften, z. B. für Sanierungsmaßnahmen erforderlich ist. In-situ U-Wert-Messungen sind Gegenstand zweier abgeschlossener Forschungsprojekte aus Deutschland und der Schweiz. Im vorliegenden Teil 1 werden die Ergebnisse des Projektes „LivingLab – Gebäudeperformance“ an der Bergischen Universität Wuppertal vorgestellt.
Determine the heat demand of existing buildings with machine learning
The renovation rate of existing buildings plays a major role in the Swiss Energy Strategy 2050+. To increase this rate, there must be a simple and cost-effective method to determine the heat demand of existing buildings. In this paper, the generation of such a method, based on the Swiss cantonal building energy certificate (GEAK) database with the help of machine learning (ML), is studied. The aim of the project was to develop a ML model which allows the heat demand of existing buildings to be determined quickly with a minimal set of parameters. The comparison of the GEAK building envelope class for single family houses calculated with the new ML model and the original GEAK classes shows that approximately 62 % have the same class, 32 % differ by one class and 6 % by two classes. The ML model is a good starting point for further refinements and developments.
In‐situ U‐Wert‐Messung – Teil 2: Vergleich von Messgeräten und Anwendung vor Ort
U-Wert-Messungen vor Ort (in situ) eignen sich für Gebäude, bei denen die Konstruktion unbekannt ist und eine zerstörungsfreie, sichere Aussage zu den thermischen Eigenschaften getroffen werden soll. Diese Veröffentlichung berichtet von einem Forschungsprojekt aus der Schweiz, in dessen Rahmen eine Anwendungshilfe für die in situ U-Wert-Messung erstellt wird. Grundlage sind U-Wert-Messungen mit am Markt erhältlichen Messgeräten, die auf eine breite Anwendung zielen. Die In-situ-Messungen werden durch vergleichende Messungen im Labor und Simulationen ergänzt.
Prebound, Rebound, Performance Gap. Was stimmt nicht zwischen dem Energiebedarf und dem Energieverbrauch von Wohngebäuden?
- Gemessener Verbrauch und berechneter Heizwärmebedarf bei 33 unsanierten Bestandsgebäuden - Anwendung SIA 380/1 für unsanierte Bestandsgebäude - Vorschläge zur Anpassung einzelner Faktoren in der Berechnung
Potential-estimation of thermal micro-grids in urban areas based on heat load and building clustering
As a result of climate change, fossil heating systems must be replaced with renewable systems. The question arises whether it makes sense for each building to have its own new heating system or whether a thermal micro-grid is possible. In this paper a model is presented which allows to aggregate buildings into thermal micro-grid clusters. All gas-heated residential buildings of Basel (Switzerland) are marked via geo-data. The heat demand of each building is determined depending on the year of construction and is then converted into the heat load. Each building then is grouped into thermal micro-grids according to a given grid load limit. The thermal micro-grids generated in this way are marked in color, so that the potential of any given city district can be easily and quickly identified. If the grid load limit is increased, the number of possible micro-grids increases, also.