Universitätsbibliothek
Weimar Open Access

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.

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.

The production of a desired product needs an effective use of the experimental model. The present study proposes an extreme learning machine (ELM) and a support vector machine (SVM) integrated with the response surface methodology (RSM) to solve the complexity in optimization and prediction of the ethyl ester and methyl ester production process. The novel hybrid models of ELM-RSM and ELM-SVM are further used as a case study to estimate the yield of methyl and ethyl esters through a trans-esterification process from waste cooking oil (WCO) based on American Society for Testing and Materials (ASTM) standards. The results of the prediction phase were also compared with artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS), which were recently developed by the second author of this study. Based on the results, an ELM with a correlation coefficient of 0.9815 and 0.9863 for methyl and ethyl esters, respectively, had a high estimation capability compared with that for SVM, ANNs, and ANFIS. Accordingly, the maximum production yield was obtained in the case of using ELM-RSM of 96.86% for ethyl ester at a temperature of 68.48 °C, a catalyst value of 1.15 wt. %, mixing intensity of 650.07 rpm, and an alcohol to oil molar ratio (A/O) of 5.77; for methyl ester, the production yield was 98.46% at a temperature of 67.62 °C, a catalyst value of 1.1 wt. %, mixing intensity of 709.42 rpm, and an A/O of 6.09. Therefore, ELM-RSM increased the production yield by 3.6% for ethyl ester and 3.1% for methyl ester, compared with those for the experimental data.

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.

The building sector is responsible for a large share of human environmental impacts. Architects and planners are the key players for reducing the environmental impacts of buildings, as they define them to a large extent. Life Cycle Assessment (LCA) allows for the holistic environmental analysis of a building. However, it is currently not employed to improve the environmental performance of buildings during the design process, although the potential for optimization is greatest there. One main reason is the lack of an adequate means of applying LCA in the architectural design process. As such, the main objective of this thesis is to develop a method for environmental building design optimization that is applicable in the design process. The key concept proposed in this thesis is to combine LCA with parametric design, because it proved to have a high potential for design optimization. The research approach includes the analysis of the characteristics of LCA for buildings and the architectural design stages to identify the research gap, the establishment of a requirement catalogue, the development of a method based on a digital, parametric model, and an evaluation of the method. An analysis of currently available approaches for LCA of buildings indicates that they are either holistic but very complex or simple but not holistic. Furthermore, none of them provide the opportunity for optimization in the architectural design process, which is the main research gap. The requirements derived from the analysis have been summarized in the form of a catalogue. This catalogue can be used to evaluate both existing approaches and potential methods developed in the future. In this thesis, it served as guideline for the development of the parametric method – Parametric Life Cycle Assessment (PLCA). The unique main feature of PLCA is that embodied and operational environmental impact are calculated together. In combination with the self-contained workflow of the method, this provides the basis for holistic, time-efficient environmental design optimization. The application of PLCA to three examples indicated that all established mandatory requirements are met. In all cases, environmental impact could be significantly reduced. In comparison to conventional approaches, PLCA was shown to be much more time-efficient. PLCA allows architects to focus on their main task of designing the building, and finally makes LCA practically useful as one of several criteria for design optimization. With PLCA, the building design can be time-efficiently optimized from the beginning of the most influential early design stages, which has not been possible until now. PLCA provides a good starting point for further research. In the future, it could be extended by integrating the social and economic aspects of sustainability.