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Diese Studie beleuchtet die Ansteckungsgefahr mit Sars-CoV-2 im Öffentlichen Personennahverkehr (ÖPNV). Methodisch werden hierbei drei Ansätze zur Klärung dieser Aufgabenstellung verfolgt: 1) Eine Literaturstudie wurde durchgeführt, um dokumentierte Ansteckungsfälle im ÖPNV zu finden sowie typische Betriebsparameter der Fahrzeuge zu identifizieren. 2) Im Rahmen von in-situ Messungen im ÖPNV wurden Luft- und Wischproben auf Sars-CoV-2 sowie auf die ubiquitär vorkommenden Humanen Adenoviren (HAdV) als Kontrollviren untersucht. Zusätzlich wurden die Verläufe der CO2-Konzentration im Innenraum gemessen, die in Kombination mit der festgestellten Belegung der Verkehrsmittel Rückschlüsse auf die Frischluftrate zulassen. In einigen Fahrzeugen wurde die Partikelkonzentration als Marker für die mögliche Aerosolbelastung gemessen. 3) Mit einem zonal unterteilten Simulationsmodell wurde eine Parameterstudie für die verschiedenen Verkehrsmittel durchgeführt, die die Ist-Situation beleuchtet sowie technische Nachrüstlösungen und Verhaltensanpassungen der Fahrgäste bewertet. Aus dem ÖPNV wurden hierbei exemplarisch die S-Bahn, U-Bahn, Stadtbus und Straßenbahn sowie der U-Bahnsteig untersucht. Bei den in-situ Messungen wurde in keiner Probe das SARS-CoV-2 Virus nachgewiesen und die Verläufe der CO2-Konzentrationsmessungen zeigen überwiegend einen Betrieb bei hygienisch unbedenklicher Luftqualität nach den in definierten Kriterien. Simulationen zeigen, dass das persönliche Verhalten wie das Tragen einer Maske und technische Lösungen wie die Umluftfilterung zu einer geringeren Exposition führen.

As cities are sensitive to climate change, they must be prepared for its consequences. While high-performance urban climate models are the basis for prospective planning decisions, as of today, practice-oriented models are rare. Within the framework of the Urban Climate Under ChangeUC2 research programme, the new urban climate model PALM‑4U will be developed to simulate climate and air-pollution problems in urban areas. The joint projects KliMoPrax and UseUClim deal with both the model\'s practicability and usability, and, therefore, are to be conducted together with partners from German municipalities and industry, with user requirements identified and summarised for implementation into the new model. Furthermore, case studies on current and future municipal issues will be performed using the PALM‑4U model. At the conclusion of the project, the new model\'s practicability and usability are evaluated, with the results to be summarised in an evaluation report including recommendations on further model development for both current and future everyday municipal planning.

The concept of modular building performance simulation has been accredited with considerable potential to realize the vision of an integrated building simulation platform for several stakeholders. Current literature identifies missing technological advancement as the key obstacle for its realization. This work presents a methodology that incorporates the Functional Mock-up Interface, Semantic Web Technologies and Building Information Modeling to realize a modular building performance simulation. The approach is based on the specification of Functional Mock-up Units using a formal information model. This allows to set individual simulation modules in context with an overarching data framework in order to identify their role within a building performance simulation. Through the additional association to project-specific information in a digital representation of a building, an algorithm is able to automatically infer the simulation topology of an arbitrary number of contributing simulation modules by means of reasoning. An example demonstrates the feasibility and indicates the technological potential of the approach.

The emergence of building performance optimization is recognized as a way to achieve sustainable building designs. In this paper, the problem consists in minimizing simultaneously the emissions of greenhouse gases (GHG) related to building energy consumption and those related to building materials. This multi-objective optimization problem involves variables with different hierarchical levels, i.e. variables that can become obsolete depending on the value of the other variables. To solve it, NSGA-II is compared with an algorithm designed specifically to deal with hierarchical variables, namely sNSGA. Evaluation metrics such as convergence, diversity and hypervolume show that both algorithms handle hierarchical variables, but the analysis of the Pareto front confirms that in the present case, NSGA-II is better to identify optimal solutions than sNSGA. All the optimal solutions are made of buildings with wooden envelopes and relied either on heat pumps or on electrical heaters for proving heating.

In many industrial multi-physics engineering applications, models need to capture the heat transfer effects of spatial and temporal changes in conditions around the human body. For thermal comfort assessment, convection heat transfer coefficients (hc) form part of the heat balance equation of the human body. In many non-uniform flow conditions, due to the turbulently mixed or stratified environment, convection heat transfer varies significantly on the human body. Parametric, segment-wise applicable convection heat transfer correlations are seen as an alternative in order to bridge these scales and levels in space and time. Therefore, robust reduced-order convective heat transfer models are needed for predicting heat transfer between the human body and its surroundings. The main goal of this research is to develop a reduced order model database that provides the segment-wise convective heat transfer coefficients (hc) for typical indoor flow responses in multiple applicat ions. In this article, a new parametric approach was detailed for estimating segment-wise body convection heat transfer coefficients for sitting posture in vehicles. The methodology follows a new strategy, i.e., in this application domain, here a car cabin, primarily relevant parameters are identified which affect the convective heat exchange. Following the sensitivity analysis of numerous computational fluid dynamics simulations with varying conditions, we identify relevant primary variables and heat transfer coefficients correlations and test the model robustness accordingly. A database-driven approach is developed in order to make correlations accessible during simulations, for example addressing energy performance. Finally, the experimentally investigated heat transfer analysis around the human body is presented and later compared with numerically reproduced data.

This work investigates a scalable building performance simulation (BPS) based on a modular setup deploying the recently developed functional mock-up interface standard. A procedure for the realization of such an approach is presented and a prototypical implementation is described. One of the key obstacles of the modular simulation is identified to be the collocation of simulation modules, which is addressed using a knowledge-based method enabled through ontology. The procedure allows to automatically derive a simulation topology based on the information about the interfacing variables for varying levels of detail. Also information from other sources such as building information models is incorporated. The feasibility of the proposed method is demonstrated by deploying it in test cases of a single-zone and a multi-zone BPS as well as a zonal airflow simulation.

With the increasing detail of thermal comfort studies, models need to represent the effects of spatial and temporal changes in conditions around the human body. Convection heat transfer varies significantly on the human body due to local airflow patterns. In many non-uniform flow scenarios different modes of convection show up depending on the airflow conditions. For example, flows through displacement ventilation or by mixing ventilation are commonly encountered in buildings and all result in substantially different convection regimes. Furthermore, the models are relevant for a number of areas such as automotive, aircraft and railway industries where local and dynamic effects under non-uniform conditions become significant. Therefore, there is a need to develop reduced order models that predict the convective heat transfer coefficients locally in non-uniform indoor flow conditions. The main aim of this research is to develop a reduced order model database that approximates the convective heat transfer coefficients (hc) of different body segments for typical indoor flow responses in multiple applications. Each application constitutes a definite structure in the database. This paper presents a first prototype of the developed reduced order database model where displacement ventilation flow regimes in rooms are detailed. The computational fluid dynamics (CFD) methodology is used to model airflow and heat transfer and also further to computationally evaluate the convective heat transfer coefficients for different body segments by temperature gradient analysis. In order to obtain local hc a parametric multi-segmented human manikin model with 48 body segments has been developed. Benchmark validations and regression models development are demonstrated through an example application, taken from the displacement ventilation structure. Finally, discussions and the applicability of the displacement ventilation subdomain models are detailed.

Der Beitrag untersucht globale und lokale Effekte asymmetrischer kurzwelliger und langwelliger Strahlung in Gebaudemodellen mit komplexen 3D-Geometrien. Das neu entwickelte Simulationsverfahren berechnet die thermische Last auf Personen durch nicht-uniforme Umgebungstemperaturen und solare Strahlung in Innenraumen. Das Berechnungsverfahren nutzt dabei eine effiziente Strahlverfolgung und Sichtfaktorberechnung mittels programmierbarer Grafik-Hardware. Dadurch werden aufwendige geometriebasierte Strahlverfolgungsalgorithmen auf Arbeitsplatzrechnern fur die Praxis ermoglicht. Hierzu wird der temperaturabhangige langwellige Strahlungsaustausch berechnet, sowie die Eintrage kurzwelliger diffuser und direkter Solarstrahlung. Zur Gesamtbewertung wird die in der Norm definierte langwellige Strahlungstemperatur Tumrt mit den Eintragen kurzwelliger Strahlung zu Tmrt erweitert. Zur lokalen Auswertung aller Strahlungseintrage werden virtuelle “Proben“ modelliert, wie z. B. Globe-Thermometer, und an ausgewahlten Raumpositionen in ein Gebaudemodell integriert. Fur eine genauere Analyse der lokalen thermischen Randbedingungen werden detaillierte virtuelle Menschmodelle verwendet. Die Strahlungstemperaturen werden pro Flachenelement durch richtungsabhangige Grosen ermittelt, da insbesondere asymmetrische Bestrahlung als Einflussfaktor auf die Behaglichkeit in Innenraumen gilt. Efficient radiation simulation for thermal comfort. The presented work analyses the local effects of asymmetric shortwave and longwave radiation in complex 3D building models. The new simulation tool provides thermal loads caused by non-uniform radiant temperatures and solar irradiation in indoor environments. The method implements efficient raytracing and viewfactor calculation on programmable graphic processing units. Therefor temperature based longwave radiation exchange and heat gains from direct and diffuse solar radiation are computed. Models of globe- thermometers are placed in selected room positions, in order to investigate local radiation impacts. Accurate analysis of local thermal conditions is enabled by detailed virtual manikin models. Radiant temperatures are evaluated by means of directional quantities, since asymmetric radiation is known to effect thermal comfort.

In the design of future electric vehicles, the air conditioning of the passenger compartment is considered as the largest auxiliary consumer. To test new climate control concepts and quantify their effectiveness in terms of user acceptance, energy efficiency and driving range, corresponding methods and tools are needed. This includes the numerical, experimental and subject-supported study regarding human thermal comfort.

Research and development in the fields of building technologies and community energy systems have caused in recent years a transition away from stand-alone components towards dynamically interacting systems. However, the precise modeling and simulation of such complex cyber-physical systems proves challenging for the established simulation tools. This paper illustrates the applicability of co-simulation and model exchange concepts based on the Functional Mock-up Interface (FMI) specification for the simulation of buildings and community energy systems by comparing several state-of-the-art approaches. The presented applications thereby demonstrate the suitability and relevance of such modular and flexible simulation concepts for these fields. At the same time the importance of a common simulation interface is emphasized, which allows the reuse of individual components for a diverse range of applications.