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This dataset consists mainly of two subsets. The first subset includes measurements and simulation data conducted to validate the simulation tool ENVI-met. The measurements were conducted at the campus of the Bauhaus-University Weimar in Weimar, Germany and consisted of recording exterior air temperature, globe temperature, relative humidity, and wind velocity at 1.5 m at four points on four different days. After the measurements, the geometry of the campus was modelled and meshed; the simulations were conducted using the weather data of the measurements days with the aim of investigating the accuracy of the model.
The second data subset consists of ENVI-met simulation data of the potential of facade greening in improving the outdoor environment and the indoor air temperature during heatwaves in Central European cities. The data consist of the boundary conditions and the simulation output of two simulation models: with and without facade greening. The geometry of the models corresponded to a residential buildings district in Stuttgart, Germany. The simulation output consisted of exterior air temperature, mean radiant temperature, relative humidity, and wind velocity at 12 different probe points in the model in addition to the indoor air temperature of an exemplary building. The dataset presents both vertical profiles of the probed parameters as well as the time series output of the five-day simulation duration. Both data subsets correspond to the investigations presented in the co-submitted article [1].
In this thesis, a generic model for the post-failure behavior of concrete in tension is proposed. A mesoscale model of concrete representing the heterogeneous nature of concrete is formulated. The mesoscale model is composed of three phases: aggregate, mortar matrix, and the Interfacial Transition Zone between them. Both local and non-local formulations of the damage are implemented and the results are compared. Three homogenization schemes from the literature are employed to obtain the homogenized constitutive relationship for the macroscale model. Three groups of numerical examples are provided.
Personalisierte Lüftung (PL) kann die thermische Behaglichkeit sowie die Qualität der eingeatmeten Atemluft verbessern, in dem jedem Arbeitsplatz Frischluft separat zugeführt wird. In diesem Beitrag wird die Wirkung der PL auf die thermische Behaglichkeit der Nutzer unter sommerlichen Randbedingungen untersucht. Hierfür wurden zwei Ansätze zur Bewertung des Kühlungseffekts der PL untersucht: basierend auf (1) der äquivalenten Temperatur und (2) dem thermischen Empfinden. Grundlage der Auswertung sind in einer Klimakammer gemessene sowie numerisch simulierte Daten. Vor der Durchführung der Simulationen wurde das numerische Modell zunächst anhand der gemessenen Daten validiert. Die Ergebnisse zeigen, dass der Ansatz basierend auf dem thermischen Empfinden zur Evaluierung des Kühlungseffekts der PL sinnvoller sein kann, da bei diesem die komplexen physiologischen Faktoren besser berücksichtigt werden.
Turbomachinery plays an important role in many cases of energy generation or conversion. Therefore, turbomachinery is a promising approaching point for optimization in order to increase the efficiency of energy use. In recent years, the use of automated optimization strategies in combination with numerical simulation has become increasingly popular in many fields of engineering. The complex interactions between fluid and solid mechanics encountered in turbomachines on the one hand and the high computational expense needed to calculate the performance on the other hand, have, however, prevented a widespread use of these techniques in this field of engineering. The objective of this work was the development of a strategy for efficient metamodel based optimization of centrifugal compressor impellers. In this context, the main focus is the reduction of the required numerical expense. The central idea followed in this research was the incorporation of preliminary information acquired from low-fidelity computation methods and empirical correlations into the sampling process to identify promising regions of the parameter space. This information was then used to concentrate the numerically expensive high-fidelity computations of the fluid dynamic and structure mechanic performance of the impeller in these regions while still maintaining a good coverage of the whole parameter space. The development of the optimization strategy can be divided into three main tasks. Firstly, the available preliminary information had to be researched and rated. This research identified loss models based on one dimensional flow physics and empirical correlations as the best suited method to predict the aerodynamic performance. The loss models were calibrated using available performance data to obtain a high prediction quality. As no sufficiently exact models for the prediction of the mechanical loading of the impellercould be identified, a metamodel based on finite element computations was chosen for this estimation. The second task was the development of a sampling method which concentrates samples in regions of the parameter space where high quality designs are predicted by the preliminary information while maintaining a good overall coverage. As available methods like rejection sampling or Markov-chain Monte-Carlo methods did not meet the requirements in terms of sample distribution and input correlation, a new multi-fidelity sampling method called “Filtered Sampling“has been developed. The last task was the development of an automated computational workflow. This workflow encompasses geometry parametrization, geometry generation, grid generation and computation of the aerodynamic performance and the structure mechanic loading. Special emphasis was put into the development of a geometry parametrization strategy based on fluid mechanic considerations to prevent the generation of physically inexpedient designs. Finally, the optimization strategy, which utilizes the previously developed tools, was successfully employed to carry out three optimization tasks. The efficiency of the method was proven by the first and second testcase where an existing compressor design was optimized by the presented method. The results were comparable to optimizations which did not take preliminary information into account, while the required computational expense cloud be halved. In the third testcase, the method was applied to generate a new impeller design. In contrast to the previous examples, this optimization featuredlargervariationsoftheimpellerdesigns. Therefore, theapplicability of the method to parameter spaces with significantly varying designs could be proven, too.
Der vorliegende Beitrag beschreibt die Problematik bei der Prognose verkehrsbedingter Schadstoff-Immissionen. Im Mittelpunkt steht die Entwicklung und der Aufbau einer Simulationsumgebung zur Evaluation von umweltorientierten Verkehrsmanagement-Strategien. Die Simulationsumgebung wird über die drei Felder Verkehr, Emission, Immission entwickelt und findet zunächst Anwendung in der Evaluation verkehrlicher Maßnahmen für die Friedberger Landstraße in Frankfurt am Main.
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.
In this work, molecular separation of aqueous-organic was simulated by using combined soft computing-mechanistic approaches. The considered separation system was a microporous membrane contactor for separation of benzoic acid from water by contacting with an organic phase containing extractor molecules. Indeed, extractive separation is carried out using membrane technology where complex of solute-organic is formed at the interface. The main focus was to develop a simulation methodology for prediction of concentration distribution of solute (benzoic acid) in the feed side of the membrane system, as the removal efficiency of the system is determined by concentration distribution of the solute in the feed channel. The pattern of Adaptive Neuro-Fuzzy Inference System (ANFIS) was optimized by finding the optimum membership function, learning percentage, and a number of rules. The ANFIS was trained using the extracted data from the CFD simulation of the membrane system. The comparisons between the predicted concentration distribution by ANFIS and CFD data revealed that the optimized ANFIS pattern can be used as a predictive tool for simulation of the process. The R2 of higher than 0.99 was obtained for the optimized ANFIS model. The main privilege of the developed methodology is its very low computational time for simulation of the system and can be used as a rigorous simulation tool for understanding and design of membrane-based systems.
Highlights are, Molecular separation using microporous membranes. Developing hybrid model based on ANFIS-CFD for the separation process, Optimization of ANFIS structure for prediction of separation process
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.
Entwicklung eines Sommerreferenzjahres zur Bestimmung der sommerlichen Überhitzung von Gebäuden
(2015)
Die Ableitung von sommer-fokussierten warmen Referenzjahren aus langjährigen Klimadaten erfolgt in Europa bisher nach unterschiedlichen, länderspezifischen Methoden, die sich in der Regel allein auf die Trockentemperatur beziehen und in der Auswahl eines zusammenhängenden realen Sommerhalbjahres resultieren. Simulationsergebnisse zur sommerlichen Überhitzung von natürlich belüfteten Gebäuden in Deutschland und Großbritannien zeigen jedoch für einige Wetterstationen weniger Überhitzung für Simulationen mit dem sommer-fokussierten Referenzjahr als für solche mit dem entsprechenden Testreferenzjahr (TRY) für den gleichen Ort. Dies gilt insbesondere dann, wenn einzelne Monate miteinander verglichen werden. Neben der Wahl eines kompletten Halbjahres, das sowohl extrem warme als auch vergleichsweise kühle Monate beinhalten kann, liegt dies vor allem begründet in der fehlenden Berücksichtigung der Solarstrahlung bei der Auswahl eines warmen Referenzjahres, die jedoch eine wichtige Rolle für sommerliche Überhitzungserscheinungen in Gebäuden spielt. Eine verlässliche, allgemein anerkannte Methode zur Erstellung von sommer-fokussierten Referenzjahren erscheint daher auch im Hinblick auf die rechtlichen Rahmenbedingungen in der Europäischen Union, die Strategien zur natürlichen Belüftung von Neubauten und Sanierungen begünstigen, erforderlich. Diese Arbeit präsentiert einen Ansatz zur Erstellung eines Sommerreferenzjahres (Summer Reference Year – SRY) aus dem TRY eines gegebenen Ortes und langjährigen Klimadaten. Die existierenden TRY-Daten werden hierbei skaliert, um den Bedingungen für Trockentemperatur und Solarstrahlung von nah-extremen Kandidatenjahren zu entsprechen, die separat über einen statistischen Ansatz ausgewählt werden. Anschließend werden Feuchttemperatur, Windgeschwindigkeit und Luftdruck des TRY durch lineare Korrelationen mit der Trockentemperatur angepasst, um die entsprechenden SRY-Daten zu erhalten. Der Vorteil dieser Methode liegt darin, dass das grundlegende Wettermuster des TRY erhalten bleibt und somit eine klare Relation zwischen SRY und TRY besteht, die eine Vergleichbarkeit von Simulationsergebnissen gewährleistet. Über vergleichende Gebäudesimulationen mit dem zugrundeliegenden TRY und langjährigen Klimadatensätzen kann nachgewiesen werden, dass sich das SRY zur Ermittlung sommerlicher Überhitzungserscheinungen in natürlich belüfteten Gebäuden eignet. Weiterhin kann gezeigt werden, dass das SRY im Gegensatz zur direkten Nutzung eines Kandidatenjahres für einen nah-extremen Sommer die Möglichkeit eines monatsscharfen Vergleichs mit dem TRY erlaubt und frei von wenig repräsentativen Besonderheiten ist, die in den entsprechenden Kandidatenjahren vorhanden sein können.
Urban and building energy simulation models are usually driven by typical meteorological year (TMY) weather data often in a TMY2 or EPW format. However, the locations where these historical datasets were collected (usually airports) generally do not represent the local, site specific micro-climates that cities develop. In this paper, a humid sub-tropical climate context has been considered. An idealised “urban unit model” of 250 m radius is being presented as a method of adapting commonly available weather data files to the local micro-climate. This idealised “urban unit model” is based on the main thermal and morphological characteristics of nine sites with residential/institutional (university) use in Hangzhou, China. The area of the urban unit was determined by the region of influence on the air temperature signal at the centre of the unit. Air temperature and relative humidity were monitored and the characteristics of the surroundings assessed (eg green-space, blue-space, built form). The “urban unit model” was then implemented into micro-climatic simulations using a Computational Fluid Dynamics – Surface Energy Balance analysis tool (ENVI-met, Version 4). The “urban unit model” approach used here in the simulations delivered results with performance evaluation indices comparable to previously published work (for air temperature; RMSE <1, index of agreement d > 0.9). The micro-climatic simulation results were then used to adapt the air temperature and relative humidity of the TMY file for Hangzhou to represent the local, site specific morphology under three different weather forcing cases, (ie cloudy/rainy weather (Group 1), clear sky, average weather conditions (Group 2) and clear sky, hot weather (Group 3)). Following model validation, two scenarios (domestic and non-domestic building use) were developed to assess building heating and cooling loads against the business as usual case of using typical meteorological year data files. The final “urban weather projections” obtained from the simulations with the “urban unit model” were used to compare the degree days amongst the reference TMY file, the TMY file with a bulk UHI offset and the TMY file adapted for the site-specific micro-climate (TMY-UWP). The comparison shows that Heating Degree Days (HDD) of the TMY file (1598 days) decreased by 6 % in the “TMY + UHI” case and 13 % in the “TMY-UWP” case showing that the local specific micro-climate is attributed with an additional 7 % (ie from 6 to 13 %) reduction in relation to the bulk UHI effect in the city. The Cooling Degree Days (CDD) from the “TMY + UHI” file are 17 % more than the reference TMY (207 days) and the use of the “TMY-UWP” file results to an additional 14 % increase in comparison with the “TMY + UHI” file (ie from 17 to 31 %). This difference between the TMY-UWP and the TMY + UHI files is a reflection of the thermal characteristics of the specific urban morphology of the studied sites compared to the wider city. A dynamic thermal simulation tool (TRNSYS) was used to calculate the heating and cooling load demand change in a domestic and a non-domestic building scenario. The heating and cooling loads calculated with the adapted TMY-UWP file show that in both scenarios there is an increase by approximately 20 % of the cooling load and a 20 % decrease of the heating load. If typical COP values for a reversible air-conditioning system are 2.0 for heating and 3.5 for cooling then the total electricity consumption estimated with the use of the “urbanised” TMY-UWP file will be decreased by 11 % in comparison with the “business as usual” (ie reference TMY) case. Overall, it was found that the proposed method is appropriate for urban and building energy performance simulations in humid sub-tropical climate cities such as Hangzhou, addressing some of the shortfalls of current simulation weather data sets such as the TMY.