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A categorical perspective towards aerodynamic models for aeroelastic analyses of bridge decks
(2019)
Reliable modelling in structural engineering is crucial for the serviceability and safety of structures. A huge variety of aerodynamic models for aeroelastic analyses of bridges poses natural questions on their complexity and thus, quality. Moreover, a direct comparison of aerodynamic models is typically either not possible or senseless, as the models can be based on very different physical assumptions. Therefore, to address the question of principal comparability and complexity of models, a more abstract approach, accounting for the effect of basic physical assumptions, is necessary.
This paper presents an application of a recently introduced category theory-based modelling approach to a diverse set of models from bridge aerodynamics. Initially, the categorical approach is extended to allow an adequate description of aerodynamic models. Complexity of the selected aerodynamic models is evaluated, based on which model comparability is established. Finally, the utility of the approach for model comparison and characterisation is demonstrated on an illustrative example from bridge aeroelasticity. The outcome of this study is intended to serve as an alternative framework for model comparison and impact future model assessment studies of mathematical models for engineering applications.
Die Zonenmethode nach Hertz ist ein vereinfachtes Verfahren zur Heißbemessung von Stahlbetonbauteilen. Um eine händische Bemessung zu ermöglichen, werden daher verschiedene Annahmen und Vereinfachungen getroffen. Insbesondere werden die thermischen Dehnungen vernachlässigt und das mechanische Verhalten durch einen verkleinerten Querschnitt mit konstanten Stoffeigenschaften beschrieben.
Ziel der vorliegenden Arbeit ist, dieses vereinfachte Verfahren in ein nichtlineares Verfahren zur Heißbemessung von Stahlbetondruckgliedern bei Brandbeanspruchung durch die Einheits-Temperaturzeitkurve zu überführen. Dazu werden die wesentlichen Annahmen der Zonenmethode überprüft und ein Vorschlag zur Weiterentwicklung vorgestellt. Dieser beruht im Wesentlichen auf der Modellierung der druckbeanspruchten Bewehrung. Diese weiterentwickelte Zonenmethode wird durch die Nachrechnung von Laborversuchen validiert und das Sicherheitsniveau durch eine vollprobabilistische Analyse und den Vergleich mit dem allgemeinen Verfahren bestimmt.
In the field of engineering, surrogate models are commonly used for approximating the behavior of a physical phenomenon in order to reduce the computational costs. Generally, a surrogate model is created based on a set of training data, where a typical method for the statistical design is the Latin hypercube sampling (LHS). Even though a space filling distribution of the training data is reached, the sampling process takes no information on the underlying behavior of the physical phenomenon into account and new data cannot be sampled in the same distribution if the approximation quality is not sufficient. Therefore, in this study we present a novel adaptive sampling method based on a specific surrogate model, the least-squares support vector regresson. The adaptive sampling method generates training data based on the uncertainty in local prognosis capabilities of the surrogate model - areas of higher uncertainty require more sample data. The approach offers a cost efficient calculation due to the properties of the least-squares support vector regression. The opportunities of the adaptive sampling method are proven in comparison with the LHS on different analytical examples. Furthermore, the adaptive sampling method is applied to the calculation of global sensitivity values according to Sobol, where it shows faster convergence than the LHS method. With the applications in this paper it is shown that the presented adaptive sampling method improves the estimation of global sensitivity values, hence reducing the overall computational costs visibly.
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
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.
As part of an international research project – funded by the European Union – capillary glasses for facades are being developed exploiting storage energy by means of fluids flowing through the capillaries. To meet highest visual demands, acrylate adhesives and EVA films are tested as possible bonding materials for the glass setup. Especially non-destructive methods (visual analysis, analysis of birefringent properties and computed tomographic data) are applied to evaluate failure patterns as well as the long-term behavior considering climatic influences. The experimental investigations are presented after different loading periods, providing information of failure developments. In addition, detailed information and scientific findings on the application of computed tomographic analyses are presented.
The aim of my research is to observe the variance of energy efficiency of a typical multi-story office building under the exposure of different climatic conditions. Energy efficiency requirements in building codes or energy standards are among the most important single measures for buildings’ energy efficiency. Therefore, this study can be set up for a better understanding of how energy efficiency of a building changes under the effect of adverse to moderate climatic conditions which possess a mentionable effect on the operation of a building.
This thesis is structured in three balanced and conceptual steps. Following the aim of the project, the virtual building model is to be analyzed under the effect of seven distinct climatic conditions namely work environment of New Delhi, Mumbai, Berlin, Lisbon, Copenhagen, Dubai and Montreal. Firstly, the task is to do a complete literature research based on the scope of similar researches and studying the problems in detail along with the theoritical background all the concepts which are implemented to get the numerical results. This chapter also comprises a detailed study of the climatic conditions of the above-mentioned cities. Different climatic traits like temperature variations, count of heating and cooling degree days, relative humidity, temperature range and comfort zonal charts for the specified cities are studied in detail. This study helps to understand the effect of these adverse to moderate climates on the operation of the building. On the second step, the virtual building model is prepared on a software platform named Revit Structures. This virtual building model is not necessarily a complete building, but it has the relevant functionalities of a real building. We perform the energy analysis and the heating and cooling analysis on this virtual building model to study the operational outcome of the building under different climatic conditions in detail. By the end of these above two tasks, two scenarios are observed. On one hand, we have a literature research and on the other hand we have the numerical results. Therefore, finally we present a comparative scenario based on the energy efficient performances of the building under such variant climatic conditions. This is followed by the prediction of thermal comfort level inside the building and it based on Fanger’s PMV Model. Understanding the literature and the numerical values in detail helps us to predict the index thermal comfort level inside the building.
The conclusion of this master thesis focuses mainly on the scopes of improvement of energy efficiency requirements in energy codes if any, differentiated according to specific locations. The initial aim of my hypothesis which is to study the impacts of climatic variations on the energy efficient performances of a building is fulfilled but as such topics have very deep and broad roots, the scope of further improvements is always predominant.
Durch Reifungs- und Strukturbildungsprozesse kann es bei silikatischen und alumosilikatischen Bindern zu Rissbildung bei behinderter Verformung, Festigkeitsverlust und somit Verlust der Dauerhaftigkeit kommen. Die Bewertung dieser Prozesse erfolgt an silikatischen Materialien mit einem Ausblick auf die alumosilikatischen Binder.
Durch Reifungs- und Strukturbildungsprozesse kann es bei silikatischen und alumosilikatischen Bindern zu Rissbildung bei behinderter Verformung, Festigkeitsverlust und somit Verlust der Dauerhaftigkeit kommen. Die Bewertung dieser Prozesse erfolgt an silikatischen Materialien mit einem Ausblick auf die alumosilikatischen Binder