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In this work, a novel type of polyester urethane urea (PEUU) foam is introduced. The foam was produced by reactive foaming using a mixture of poly(1,10–decamethylene adipate) diol and poly(1,4–butylene adipate) diol, 4,4′-diphenylmethane diisocyanate, 1,4–butanediol, diethanolamine and water as blowing agent. As determined by differential scanning calorimetry, the melting of the ester-based phases occurred at temperatures in between 25 °C and 61 °C, while the crystallization transition spread from 48 °C to 20 °C. The mechanical properties of the foam were simulated with the hyperplastic models Neo-Hookean and Ogden, whereby the latter showed a better agreement with the experimental data as evidenced by a Pearson correlation coefficient R² above 0.99. Once thermomechanically treated, the foam exhibited a maximum actuation of 13.7% in heating-cooling cycles under a constant external load. In turn, thermal cycling under load-free conditions resulted in an actuation of more than 10%. Good thermal insulation properties were demonstrated by thermal conductivities of 0.039 W·(m·K)−1 in the pristine state and 0.052 W·(m·K)−1 in a state after compression by 50%, respectively. Finally, three demonstrators were developed, which closed an aperture or opened it again simply by changing the temperature. The self-sufficient material behavior is particularly promising in the construction industry, where programmable air slots offer the prospect of a dynamic insulation system for an adaptive building envelope.

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The current pandemic of the SARS-CoV-2 virus requires measures to reduce the risk of infection. In addition to the usual hygiene measures, air cleaners are a recommended solution to decrease the viral load in rooms. Suitable technologies range from pure filters to inactivating units, such as cold plasma or UVC irradiation. Such inactivating air cleaners, partly combined with filter technology, are available on the market in various designs, dimensions and technical specifications. Since it is not always clear whether they may produce undesirable by-products, and the suitability for particular applications cannot be assessed on the basis of the principle of operation, the effectivity of six inactivating devices was investigated in a near-real environment. The investigations were based on a standard method published by the VDI. The procedure was extended in such a way that a permanent virus source was simulated, which corresponds to the presence of a person suffering from COVID-19 in a room. The study addresses the difference of the mere presence of viruses to the determination of the virulence. As a result, a deep understanding is provided between the behavior of a virus as a pure aerosolized particle and its real infectivity in order to enable the assessment of suitable air cleaners.

This paper presents the Modelica Thermal Model Generation Tool. The aim of this tool is to enable the user to set up a geometrically correct thermal model for complex geometries that allows predicting the impact of heated/heating devices and their location both in terms of airflow pattern and radiation distribution. Using a geometry file exported from CAD software, the tool distributes wall facets, air nodes and computes the long-wave radiant view factor matrix for obstructed and unobstructed surfaces. This information is exported as ready to use Modelica code. The zonal model VEPZO is used to model airflow within a domain (enclosed space). This model allows predicting airflow and air temperature distribution in space on a coarse mesh and thus computes faster than classical CFD computations. Walls are subdivided on the same grid as the zonal model is set upon. For each wall facet, the Modelica Thermal Model Generation Tool computes the view factors to the other facets in the domain. Comparison of simulated results with test data and application of the Modelica Thermal Model Generation Tool for a room with radiant heating and for the cooling of an aircraft cockpit are presented in this paper.

A big challenge for energy savings performance contracting projects is the transparent and reliable determination of the energy consumption before and after retrofitting. This process, the so called “measurement and verification” (M&V) process, can be performed by means of calibrating simulation models with measured data, e.g. the energy bill data. There are guidelines for reporting and conducting this procedure. According to reports from case studies, it seems that they are carried out using several different approaches. The main goal of this work is to develop a consistent, practical approach for the M&V process. The approach supports visual inspection methods, parametric studies, and optimization methods. The visual inspection method can help to understand characteristics of a specific building depending on an input parameter change via graphs. However, the visual inspection method requires an extensive effort for this trial and error process and it is strongly dependent upon the users’ experience. The automated parametric study can be applied both for calibration and sensitivity analysis of uncertain parameters. The big challenge for the practical use is the need for automating the process due to an enormous number of simulation cases and the required skills in applied statistics. Optimization algorithms quickly provide the user with a quantitatively best solution. However, they do not analyze the actual problems and therefore do not contribute to an understanding of the system under consideration. Furthermore, results should be examined carefully because the optimization may produce mathematically correct but physically meaningless results. Due to the present advantages and disadvantages of these methods, a calibration tool including all three methods would be desirable in order to predict the impact of energy efficient retrofitting projects.Methodologische Herangehensweise für die Kalibrierung von Gebäudesimulationsmodellen im “Measurement M&V Verification“‐Prozess. Eine große Herausforderung bei Energiespar‐Contracting‐Projekten ist die transparente und zuverlässige Bestimmung der Energieeinsparung vor und nach der Sanierung. Der sogenannte “Measurement & Verification“ (M&V)‐Prozess kann mittels der Kalibrierung von Simulationsmodellen mit gemessenen Daten, z. B. den Berechnungsdaten von Energieversorgern, durchgeführt werden. Es gibt mehrere Leitfäden für die Vorgehensweise bei solchen M&V‐Prozessen, Projektberichten von Fallstudien zufolge wird die Kalibrierung der Gebäudesimulationsmodelle jedoch mit recht unterschiedlichen Ansätzen bewerkstelligt. Ziel dieser Arbeit ist es, einen einheitlichen, praxistauglichen methodischen Ansatz für den M&V‐Prozess zu entwickeln. In dem hier vorgestellten neuen Ansatz können sowohl Methoden der visuellen Untersuchung, parametrische Studien als auch Optimierungsverfahren angewendet werden. Die Methoden der visuellen Untersuchung können in erster Linie dazu beitragen, Eigenschaften eines bestimmten Gebäudes zu verstehen. Der große Nachteil dabei ist, dass sie auf einer “Trial and Error“‐Vorgehensweise beruht. Somit ist sie mit hohem Zeitaufwand verbunden und die Qualität des Ergebnisses hängt stark von der durchführenden Person ab. Automatisierte parametrische Studien werden bislang in erster Linie für Sensitivitätsanalysen durchgeführt. Eine Übertragung dieser Methode auf die Modellkalibrierung erscheint jedoch im genannten Kontext vielversprechend. Die große Herausforderung für eine praktische Anwendung ist hierbei, einen hohen Automatisierungsgrad zu erreichen, da eine sehr große Anzahl von Simulationsfällen ausgewertet werden muss. Darüber hinaus erfordert sie vom Anwender vertiefte Fachkompetenzen im Bereich Statistik. Optimierungsverfahren erlauben es, schnell zu quantitativ besseren Lösungen zu gelangen. Deren Nachteil ist jedoch, dass sie keine Analyse des Systems vornehmen und dadurch kaum zu einem besseren Systemverständnis beitragen. Zudem sollten die Ergebnisse eines Optimierungsprozesses sorgfältig geprüft werden, da daraus zwar mathematisch korrekte, aber unter Umständen physikalisch bedeutungslose Systemvarianten resultieren können. Aufgrund der bekannten Vor‐ und Nachteile dieser Methoden wäre ein Kalibrierungswerkzeug wünschenswert, welches alle drei Verfahren in der Praxis nutzbar macht, um die Wirkung energieeffizienter Sanierungsprojekte besser vorhersagen zu können.