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Für eine Abschätzung des Heizwärmebedarfs von Gebäuden und Quartieren können thermisch-energetische Simulationen eingesetzt werden. Grundlage dieser Simulationen sind geometrische und physikalische Gebäudemodelle. Die Erstellung des geometrischen Modells erfolgt in der Regel auf Basis von Bauplänen oder Vor-Ort-Begehungen, was mit einem großen Recherche- und Modellierungsaufwand verbunden ist. Spätere bauliche Veränderungen des Gebäudes müssen häufig manuell in das Modell eingearbeitet werden, was den Arbeitsaufwand zusätzlich erhöht. Das physikalische Modell stellt die Menge an Parametern und Randbedingungen dar, welche durch Materialeigenschaften, Lage und Umgebungs-einflüsse gegeben sind. Die Verknüpfung beider Modelle wird innerhalb der entsprechenden Simulations-software realisiert und ist meist nicht in andere Softwareprodukte überführbar. Mithilfe des Building Information Modeling (BIM) können Simulationsdaten sowohl konsistent gespeichert als auch über Schnittstellen mit entsprechenden Anwendungen ausgetauscht werden. Hierfür wird eine Methode vorgestellt, die thermisch-energetische Simulationen auf Basis des standardisierten Übergabe-formats Industry Foundation Classes (IFC) inklusive anschließender Auswertungen ermöglicht. Dabei werden geometrische und physikalische Parameter direkt aus einem über den gesamten Lebenszyklus aktuellen Gebäudemodell extrahiert und an die Simulation übergeben. Dies beschleunigt den Simulations-prozess hinsichtlich der Gebäudemodellierung und nach späteren baulichen Veränderungen. Die erarbeite-te Methode beruht hierbei auf einfachen Modellierungskonventionen bei der Erstellung des Bauwerksinformationsmodells und stellt eine vollständige Übertragbarkeit der Eingangs- und Ausgangswerte sicher.
Thermal building simulation based on BIM-models. Thermal energetic simulations are used for the estimation of the heating demand of buildings and districts. These simulations are based on building models containing geometrical and physical information. The creation of geometrical models is usually based on existing construction plans or in situ assessments which demand a comparatively big effort of investigation and modeling. Alterations, which are later applied to the structure, request manual changes of the related model, which increases the effort additionally. The physical model represents the total amount of parameters and boundary conditions that are influenced by material properties, location and environmental influences on the building. The link between both models is realized within the correspondent simulation soft-ware and is usually not transferable to other software products. By Applying Building Information Modeling (BIM) simulation data is stored consistently and an exchange to other software is enabled. Therefore, a method which allows a thermal energetic simulation based on the exchange format Industry Foundation Classes (IFC) including an evaluation is presented. All geometrical and physical information are extracted directly from the building model that is kept up-to-date during its life cycle and transferred to the simulation. This accelerates the simulation process regarding the geometrical modeling and adjustments after later changes of the building. The developed method is based on simple conventions for the creation of the building model and ensures a complete transfer of all simulation data.
Für eine Abschätzung des Heizwärmebedarfs von Gebäuden und Quartieren können thermisch-energetische Simulationen eingesetzt werden. Grundlage dieser Simulationen sind geometrische und physikalische Gebäudemodelle. Die Erstellung des geometrischen Modells erfolgt in der Regel auf Basis von Bauplänen oder Vor-Ort-Begehungen, was mit einem großen Recherche- und Modellierungsaufwand verbunden ist. Spätere bauliche Veränderungen des Gebäudes müssen häufig manuell in das Modell eingearbeitet werden, was den Arbeitsaufwand zusätzlich erhöht. Das physikalische Modell stellt die Menge an Parametern und Randbedingungen dar, welche durch Materialeigenschaften, Lage und Umgebungs-einflüsse gegeben sind. Die Verknüpfung beider Modelle wird innerhalb der entsprechenden Simulations-software realisiert und ist meist nicht in andere Softwareprodukte überführbar.
Mithilfe des Building Information Modeling (BIM) können Simulationsdaten sowohl konsistent gespeichert als auch über Schnittstellen mit entsprechenden Anwendungen ausgetauscht werden. Hierfür wird eine Methode vorgestellt, die thermisch-energetische Simulationen auf Basis des standardisierten Übergabe-formats Industry Foundation Classes (IFC) inklusive anschließender Auswertungen ermöglicht. Dabei werden geometrische und physikalische Parameter direkt aus einem über den gesamten Lebenszyklus aktuellen Gebäudemodell extrahiert und an die Simulation übergeben. Dies beschleunigt den Simulations-prozess hinsichtlich der Gebäudemodellierung und nach späteren baulichen Veränderungen. Die erarbeite-te Methode beruht hierbei auf einfachen Modellierungskonventionen bei der Erstellung des Bauwerksinformationsmodells und stellt eine vollständige Übertragbarkeit der Eingangs- und Ausgangswerte sicher.
Thermal building simulation based on BIM-models. Thermal energetic simulations are used for the estimation of the heating demand of buildings and districts. These simulations are based on building models containing geometrical and physical information. The creation of geometrical models is usually based on existing construction plans or in situ assessments which demand a comparatively big effort of investigation and modeling. Alterations, which are later applied to the structure, request manual changes of the related model, which increases the effort additionally. The physical model represents the total amount of parameters and boundary conditions that are influenced by material properties, location and environmental influences on the building. The link between both models is realized within the correspondent simulation soft-ware and is usually not transferable to other software products.
By Applying Building Information Modeling (BIM) simulation data is stored consistently and an exchange to other software is enabled. Therefore, a method which allows a thermal energetic simulation based on the exchange format Industry Foundation Classes (IFC) including an evaluation is presented. All geometrical and physical information are extracted directly from the building model that is kept up-to-date during its life cycle and transferred to the simulation. This accelerates the simulation process regarding the geometrical modeling and adjustments after later changes of the building. The developed method is based on simple conventions for the creation of the building model and ensures a complete transfer of all simulation data.
The spread of breathing air when playing wind instruments and singing was investigated and visualized using two methods: (1) schlieren imaging with a schlieren mirror and (2) background-oriented schlieren (BOS). These methods visualize airflow by visualizing density gradients in transparent media. The playing of professional woodwind and brass instrument players, as well as professional classical trained singers were investigated to estimate the spread distances of the breathing air. For a better comparison and consistent measurement series, a single high note, a single low note, and an extract of a musical piece were investigated. Additionally, anemometry was used to determine the velocity of the spreading breathing air and the extent to which it was quantifiable. The results showed that the ejected airflow from the examined instruments and singers did not exceed a spreading range of 1.2 m into the room. However, differences in the various instruments have to be considered to assess properly the spread of the breathing air. The findings discussed below help to estimate the risk of cross-infection for wind instrument players and singers and to develop efficacious safety precautions, which is essential during critical health periods such as the current COVID-19 pandemic.
Overheating is a major problem in many modern buildings due to the utilization of lightweight constructions with low heat storing capacity. A possible answer to this problem is the emplacement of phase change materials (PCM), thereby increasing the thermal mass of a building. These materials change their state of aggregation within a defined temperature range. Useful PCM for buildings show a phase transition from solid to liquid and vice versa. The thermal mass of the materials is increased by the latent heat. A modified gypsum plaster and a salt mixture were chosen as two materials for the study of their impact on room temperature reduction. For realistic investigations, test rooms were erected where measurements were carried out under different conditions such as temporary air change, alternate internal heat gains or clouding. The experimental data was finally reproduced by dint of a mathematical model.
This study aims to develop an approach to couple a computational fluid dynamics (CFD) solver to the University of California, Berkeley (UCB) thermal comfort model to accurately evaluate thermal comfort. The coupling was made using an iterative JavaScript to automatically transfer data for each individual segment of the human body back and forth between the CFD solver and the UCB model until reaching convergence defined by a stopping criterion. The location from which data are transferred to the UCB model was determined using a new approach based on the temperature difference between subsequent points on the temperature profile curve in the vicinity of the body surface. This approach was used because the microclimate surrounding the human body differs in thickness depending on the body segment and the surrounding environment. To accurately simulate the thermal environment, the numerical model was validated beforehand using experimental data collected in a climate chamber equipped with a thermal manikin. Furthermore, an example of the practical implementations of this coupling is reported in this paper through radiant floor cooling simulation cases, in which overall and local thermal sensation and comfort were investigated using the coupled UCB model.
Personalized ventilation (PV) is a mean of delivering conditioned outdoor air into the breathing zone of the occupants. This study aims to qualitatively investigate the personalized flows using two methods of visualization: (1) schlieren imaging using a large schlieren mirror and (2) thermography using an infrared camera. While the schlieren imaging was used to render the velocity and mass transport of the supplied flow, thermography was implemented to visualize the air temperature distribution induced by the PV. Both studies were conducted using a thermal manikin to simulate an occupant facing a PV outlet. As a reference, the flow supplied by an axial fan and a cased axial fan was visualized with the schlieren system as well and compared to the flow supplied by PV. Schlieren visualization results indicate that the steady, low-turbulence flow supplied by PV was able to penetrate the thermal convective boundary layer encasing the manikin's body, providing clean air for inhalation. Contrarily, the axial fan diffused the supplied air over a large target area with high turbulence intensity; it only disturbed the convective boundary layer rather than destroying it. The cased fan supplied a flow with a reduced target area which allowed supplying more air into the breathing zone compared to the fan. The results of thermography visualization showed that the supplied cool air from PV penetrated the corona-shaped thermal boundary layer. Furthermore, the supplied air cooled the surface temperature of the face, which indicates the large impact of PV on local thermal sensation and comfort.
A new large‐field, high‐sensitivity, single‐mirror coincident schlieren optical instrument has been installed at the Bauhaus‐Universität Weimar for the purpose of indoor air research. Its performance is assessed by the non‐intrusive measurement of the thermal plume of a heated manikin. The schlieren system produces excellent qualitative images of the manikin's thermal plume and also quantitative data, especially schlieren velocimetry of the plume's velocity field that is derived from the digital cross‐correlation analysis of a large time sequence of schlieren images. The quantitative results are compared with thermistor and hot‐wire anemometer data obtained at discrete points in the plume. Good agreement is obtained, once the differences between path‐averaged schlieren data and planar anemometry data are reconciled.
The performance of ductless personalized ventilation (DPV) was compared to the performance of a typical desk fan since they are both stand-alone systems that allow the users to personalize their indoor environment. The two systems were evaluated using a validated computational fluid dynamics (CFD) model of an office room occupied by two users. To investigate the impact of DPV and the fan on the inhaled air quality, two types of contamination sources were modelled in the domain: an active source and a passive source. Additionally, the influence of the compared systems on thermal comfort was assessed using the coupling of CFD with the comfort model developed by the University of California, Berkeley (UCB model). Results indicated that DPV performed generally better than the desk fan. It provided better thermal comfort and showed a superior performance in removing the exhaled contaminants. However, the desk fan performed better in removing the contaminants emitted from a passive source near the floor level. This indicates that the performance of DPV and desk fans depends highly on the location of the contamination source. Moreover, the simulations showed that both systems increased the spread of exhaled contamination when used by the source occupant.
Performance assessment of a ductless personalized ventilation system using a validated CFD model
(2018)
The aim of this study is twofold: to validate a computational fluid dynamics (CFD) model, and then to use the validated model to evaluate the performance of a ductless personalized ventilation (DPV) system. To validate the numerical model, a series of measurements was conducted in a climate chamber equipped with a thermal manikin. Various turbulence models, settings, and options were tested; simulation results were compared to the measured data to determine the turbulence model and solver settings that achieve the best agreement between the measured and simulated values. Subsequently, the validated CFD model was then used to evaluate the thermal environment and indoor air quality in a room equipped with a DPV system combined with displacement ventilation. Results from the numerical model were then used to quantify thermal sensation and comfort using the UC Berkeley thermal comfort model.
Occupant needs with regard to residential buildings are not well known due to a lack of representative scientific studies. To improve the lack of data, a large scale study was carried out using a Post Occupancy Evaluation of 1,416 building occupants. Several criteria describing the needs of occupants were evaluated with regard to their subjective level of relevance. Additionally, we investigated the degree to which deficiencies subjectively exist, and the degree to which occupants were able to accept them. From the data obtained, a hierarchy of criteria was created. It was found that building occupants ranked the physiological needs of air quality and thermal comfort the highest. Health hazards such as mould and contaminated building materials were unacceptable for occupants, while other deficiencies were more likely to be tolerated. Occupant satisfaction was also investigated. We found that most occupants can be classified as satisfied, although some differences do exist between different populations. To explain the relationship between the constructs of what we call relevance, acceptance, deficiency and satisfaction, we then created an explanatory model. Using correlation and regression analysis, the validity of the model was then confirmed by applying the collected data. The results of the study are both relevant in shaping further research and in providing guidance on how to maximize tenant satisfaction in real estate management.