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The assessment of wind-induced vibrations is considered vital for the design of long-span bridges. The aim of this research is to develop a methodological framework for robust and efficient prediction strategies for complex aerodynamic phenomena using hybrid models that employ numerical analyses as well as meta-models. Here, an approach to predict motion-induced aerodynamic forces is developed using artificial neural network (ANN). The ANN is implemented in the classical formulation and trained with a comprehensive dataset which is obtained from computational fluid dynamics forced vibration simulations. The input to the ANN is the response time histories of a bridge section, whereas the output is the motion-induced forces. The developed ANN has been tested for training and test data of different cross section geometries which provide promising predictions. The prediction is also performed for an ambient response input with multiple frequencies. Moreover, the trained ANN for aerodynamic forcing is coupled with the structural model to perform fully-coupled fluid--structure interaction analysis to determine the aeroelastic instability limit. The sensitivity of the ANN parameters to the model prediction quality and the efficiency has also been highlighted. The proposed methodology has wide application in the analysis and design of long-span bridges.
The automotive industry requires realistic virtual reality applications more than other domains to increase the efficiency of product development. Currently, the visual quality of virtual invironments resembles reality, but interaction within these environments is usually far from what is known in everyday life. Several realistic research approaches exist, however they are still not all-encompassing enough to be usable in industrial processes. This thesis realizes lifelike direct multi-hand and multi-finger interaction with arbitrary objects, and proposes algorithmic and technical improvements that also approach lifelike usability. In addition, the thesis proposes methods to measure the effectiveness and usability of such interaction techniques as well as discusses different types of grasping feedback that support the user during interaction. Realistic and reliable interaction is reached through the combination of robust grasping heuristics and plausible pseudophysical object reactions. The easy-to-compute grasping rules use the objects’ surface normals, and mimic human grasping behavior. The novel concept of Normal Proxies increases grasping stability and diminishes challenges induced by adverse normals. The intricate act of picking-up thin and tiny objects remains challenging for some users. These cases are further supported by the consideration of finger pinches, which are measured with a specialized finger tracking device. With regard to typical object constraints, realistic object motion is geometrically calculated as a plausible reaction on user input. The resulting direct finger-based
interaction technique enables realistic and intuitive manipulation of arbitrary objects. The thesis proposes two methods that prove and compare effectiveness and usability. An expert review indicates that experienced users quickly familiarize themselves with the technique. A quantitative and qualitative user study shows that direct finger-based interaction is preferred over indirect interaction in the context of functional car assessments. While controller-based interaction is more robust, the direct finger-based interaction provides greater realism, and becomes nearly as reliable when the pinch-sensitive mechanism is used. At present, the haptic channel is not used in industrial virtual reality applications. That is why it can be used for grasping feedback which improves the users’ understanding of the grasping situation. This thesis realizes a novel pressure-based tactile feedback at the fingertips. As an alternative, vibro-tactile feedback at the same location is realized as well as visual feedback by the coloring of grasp-involved finger segments. The feedback approaches are also compared within the user study, which reveals that grasping feedback is a requirement to judge grasp status and that tactile feedback improves interaction independent of the used display system. The considerably stronger vibrational tactile feedback can quickly become annoying during interaction. The interaction improvements and hardware enhancements make it possible to interact with virtual objects in a realistic and reliable manner. By addressing realism and reliability, this thesis paves the way for the virtual evaluation of human-object interaction, which is necessary for a broader application of virtual environments in the automotive industry and other domains.
Estimating the solubility of carbon dioxide in ionic liquids, using reliable models, is of paramount importance from both environmental and economic points of view. In this regard, the current research aims at evaluating the performance of two data-driven techniques, namely multilayer perceptron (MLP) and gene expression programming (GEP), for predicting the solubility of carbon dioxide (CO2) in ionic liquids (ILs) as the function of pressure, temperature, and four thermodynamical parameters of the ionic liquid. To develop the above techniques, 744 experimental data points derived from the literature including 13 ILs were used (80% of the points for training and 20% for validation). Two backpropagation-based methods, namely Levenberg–Marquardt (LM) and Bayesian Regularization (BR), were applied to optimize the MLP algorithm. Various statistical and graphical assessments were applied to check the credibility of the developed techniques. The results were then compared with those calculated using Peng–Robinson (PR) or Soave–Redlich–Kwong (SRK) equations of state (EoS). The highest coefficient of determination (R2 = 0.9965) and the lowest root mean square error (RMSE = 0.0116) were recorded for the MLP-LMA model on the full dataset (with a negligible difference to the MLP-BR model). The comparison of results from this model with the vastly applied thermodynamic equation of state models revealed slightly better performance, but the EoS approaches also performed well with R2 from 0.984 up to 0.996. Lastly, the newly established correlation based on the GEP model exhibited very satisfactory results with overall values of R2 = 0.9896 and RMSE = 0.0201.
Das Erzeugen räumlicher Konfigurationen ist eine zentrale Aufgabe im architektonischen bzw. städtebaulichen Entwurfsprozess und hat zum Ziel, eine für Menschen angenehme Umwelt zu schaffen. Der Geometrie der entstehenden Räume kommt hierbei eine zentrale Rolle zu, da sie einen großen Einfluss auf das Empfinden und Verhalten der Menschen ausübt und nur noch mit großem Aufwand verändert werden kann, wenn sie einmal gebaut wurde. Die meisten Entscheidungen zur Festlegung der Geometrie von Räumen werden während eines sehr kurzen Zeitraums (Entwurfsphase) getroffen. Fehlentscheidungen die in dieser Phase getroffen werden haben langfristige Auswirkungen auf das Leben von Menschen, und damit auch Konsequenzen auf ökonomische und ökologische Aspekte.
Mittels computerbasierten Layoutsystemen lässt sich der Entwurf räumlicher Konfigurationen sinnvoll unterstützen, da sie es ermöglichen, in kürzester Zeit eine große Anzahl an Varianten zu erzeugen und zu überprüfen. Daraus ergeben sich zwei Vorteile. Erstens kann die große Menge an Varianten dazu beitragen, bessere Lösungen zu finden. Zweitens kann das Formalisieren von Bewertungskriterien zu einer größeren Objektivität und Transparenz bei der Lösungsfindung führen. Um den Entwurf räumlicher Konfigurationen optimal zu unterstützen, muss ein Layoutsystem in der Lage sein, ein möglichst großes Spektrum an Grundrissvarianten zu erzeugen (Vielfalt); und zahlreiche Möglichkeiten und Detaillierungsstufen zur Problembeschreibung (Flexibilität), sowie Mittel anzubieten, mit denen sich die Anforderungen an die räumliche Konfiguration adäquat beschreiben lassen (Relevanz). Bezüglich Letzterem spielen wahrnehmungs- und nutzungsbezogene Kriterien (wie z. B. Grad an Privatheit, Gefühl von Sicherheit, Raumwirkung, Orientierbarkeit, Potenzial zu sozialer Interaktion) eine wichtige Rolle.
Die bislang entwickelten Layoutsysteme weisen hinsichtlich Vielfalt, Flexibilität und Relevanz wesentliche Beschränkungen auf, welche auf eine ungeeignete Methode zur Repräsentation von Räumen zurückzuführen sind. Die in einem Layoutsystem verwendeten Raumrepräsentationsmethoden bestimmen die Möglichkeiten zur Formerzeugung und Problembeschreibung wesentlich. Sichtbarkeitsbasierte Raumrepräsentationen (Sichtfelder, Sichtachsen, Konvexe Räume) eignen sich in besonderer Weise zur Abbildung von Räumen in Layoutsystemen, da sie einerseits ein umfangreiches Repertoire zur Verfügung stellen, um räumliche Konfigurationen hinsichtlich wahrnehmungs- und nutzungsbezogener Kriterien zu beschreiben. Andererseits lassen sie sich vollständig aus der Geometrie der begrenzenden Oberflächen ableiten und sind nicht an bestimmte zur Formerzeugung verwendete geometrische Objekte gebunden.
In der vorliegenden Arbeit wird ein Layoutsystem entwickelt, welches auf diesen Raumrepräsentationen basiert. Es wird ein Evaluationsmechanismus (EM) entwickelt, welcher es ermöglicht, beliebige zweidimensionale räumliche Konfigurationen hinsichtlich wahrnehmungs- und nutzungsrelevanter Kriterien zu bewerten. Hierzu wurde eine Methodik entwickelt, die es ermöglicht automatisch Raumbereiche (O-Spaces und P-Spaces) zu identifizieren, welche bestimmte Eigenschaften haben (z.B. sichtbare Fläche, Kompaktheit des Sichtfeldes, Tageslicht) und bestimmte Relationen zueinander (wie gegenseitige Sichtbarkeit, visuelle und physische Distanz) aufweisen. Der EM wurde mit Generierungsmechanismen (GM) gekoppelt, um zu prüfen, ob dieser sich eignet, um in großen Variantenräumen nach geeigneten räumlichen Konfigurationen zu suchen. Die Ergebnisse dieser Experimente zeigen, dass die entwickelte Methodik einen vielversprechenden Ansatz zur automatisierten Erzeugung von räumlichen Konfigurationen darstellt: Erstens ist der EM vollständig vom GM getrennt, wodurch es möglich ist, verschiedene GM in einem Entwurfssystem zu verwenden und somit den Variantenraum zu vergrößern (Vielfalt). Zweitens erlaubt der EM die Anforderungen an eine räumliche Konfiguration flexibel zu beschreiben (unterschiedliche Maßstäbe, unterschiedlicher Detaillierungsgrad). Letztlich erlauben die verwendeten Repräsentationsmethoden eine Problembeschreibung vorzunehmen, die stark an der Wirkung des Raumes auf den Menschen orientiert ist (Relevanz).
Die in der Arbeit entwickelte Methodik leistet einen wichtigen Beitrag zur Verbesserung evidenzbasierter Entwurfsprozesse, da sie eine Brücke zwischen der nutzerorientierten Bewertung von räumlichen Konfigurationen und deren Erzeugung schlägt.
The structure and development of cities can be seen and evaluated from different points of view. By replicating the growth or shrinkage of a city using historical maps depicting different time states, we can obtain momentary snapshots of the dynamic mechanisms of the city. An examination of how these snapshots change over the course of time and a comparison of the different static time states reveals the various interdependencies of population density, technical infrastructure and the availability of public transport facilities. Urban infrastructure and facilities are not distributed evenly across the city – rather they are subject to different patterns and speeds of spread over the course of time and follow different spatial and temporal regularities. The reasons and underlying processes that cause the transition from one state to another result from the same recurring but varyingly pronounced hidden forces and their complex interactions. Such forces encompass a variety of economic, social, cultural and ecological conditions whose respective weighting defines the development of a city in general. Urban development is, however, not solely a product of the different spatial distribution of economic, legal or social indicators but also of the distribution of infrastructure. But to what extent is the development of a city affected by the changing provision of infrastructure? As
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.
Temporary changes in precipitation may lead to sustained and severe drought or massive floods in different parts of the world. Knowing the variation in precipitation can effectively help the water resources decision-makers in water resources management. Large-scale circulation drivers have a considerable impact on precipitation in different parts of the world. In this research, the impact of El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO) on seasonal precipitation over Iran was investigated. For this purpose, 103 synoptic stations with at least 30 years of data were utilized. The Spearman correlation coefficient between the indices in the previous 12 months with seasonal precipitation was calculated, and the meaningful correlations were extracted. Then, the month in which each of these indices has the highest correlation with seasonal precipitation was determined. Finally, the overall amount of increase or decrease in seasonal precipitation due to each of these indices was calculated. Results indicate the Southern Oscillation Index (SOI), NAO, and PDO have the most impact on seasonal precipitation, respectively. Additionally, these indices have the highest impact on the precipitation in winter, autumn, spring, and summer, respectively. SOI has a diverse impact on winter precipitation compared to the PDO and NAO, while in the other seasons, each index has its special impact on seasonal precipitation. Generally, all indices in different phases may decrease the seasonal precipitation up to 100%. However, the seasonal precipitation may increase more than 100% in different seasons due to the impact of these indices. The results of this study can be used effectively in water resources management and especially in dam operation.
In the Space Syntax community, the standard tool for computing all kinds of spatial graph network measures is depthmapX (Turner, 2004; Varoudis, 2012). The process of evaluating many design variants of networks is relatively complicated, since they need to be drawn in a separated CAD system, exported and imported in depthmapX via dxf file format. This procedure disables a continuous integration into a design process. Furthermore, the standalone character of depthmapX makes it impossible to use its network centrality calculation for optimization processes. To overcome this limitations, we present in this paper the first steps of experimenting with a Grasshopper component (reference omitted until final version) that can access the functions of depthmapX and integrate them into Grasshopper/Rhino3D. Here the component is implemented in a way that it can be used directly for an evolutionary algorithm (EA) implemented in a Python scripting component in Grasshopper
Following restructuring of power industry, electricity supply to end-use customers has undergone fundamental changes. In the restructured power system, some of the responsibilities of the vertically integrated distribution companies have been assigned to network managers and retailers. Under the new situation, retailers are in charge of providing electrical energy to electricity consumers who have already signed contract with them. Retailers usually provide the required energy at a variable price, from wholesale electricity markets, forward contracts with energy producers, or distributed energy generators, and sell it at a fixed retail price to its clients. Different strategies are implemented by retailers to reduce the potential financial losses and risks associated with the uncertain nature of wholesale spot electricity market prices and electrical load of the consumers. In this paper, the strategic behavior of retailers in implementing forward contracts, distributed energy sources, and demand-response programs with the aim of increasing their profit and reducing their risk, while keeping their retail prices as low as possible, is investigated. For this purpose, risk management problem of the retailer companies collaborating with wholesale electricity markets, is modeled through bi-level programming approach and a comprehensive framework for retail electricity pricing, considering customers’ constraints, is provided in this paper. In the first level of the proposed bi-level optimization problem, the retailer maximizes its expected profit for a given risk level of profit variability, while in the second level, the customers minimize their consumption costs. The proposed programming problem is modeled as Mixed Integer programming (MIP) problem and can be efficiently solved using available commercial solvers. The simulation results on a test case approve the effectiveness of the proposed demand-response program based on dynamic pricing approach on reducing the retailer’s risk and increasing its profit.
In this paper, the decision-making problem of the retailers under dynamic pricing approach for demand response integration have been investigated. The retailer was supposed to rely on forward contracts, DGs, and spot electricity market to supply the required active and reactive power of its customers. To verify the effectiveness of the proposed model, four schemes for retailer’s scheduling problem are considered and the resulted profit under each scheme are analyzed and compared. The simulation results on a test case indicate that providing more options for the retailer to buy the required power of its customers and increase its flexibility in buying energy from spot electricity market reduces the retailers’ risk and increases its profit. From the customers’ perspective also the retailers’accesstodifferentpowersupplysourcesmayleadtoareductionintheretailelectricityprices. Since the retailer would be able to decrease its electricity selling price to the customers without losing its profitability, with the aim of attracting more customers. Inthiswork,theconditionalvalueatrisk(CVaR)measureisusedforconsideringandquantifying riskinthedecision-makingproblems. Amongallthepossibleoptioninfrontoftheretailertooptimize its profit and risk, demand response programs are the most beneficial option for both retailer and its customers. The simulation results on the case study prove that implementing dynamic pricing approach on retail electricity prices to integrate demand response programs can successfully provoke customers to shift their flexible demand from peak-load hours to mid-load and low-load hours. Comparing the simulation results of the third and fourth schemes evidences the impact of DRPs and customers’ load shifting on the reduction of retailer’s risk, as well as the reduction of retailer’s payment to contract holders, DG owners, and spot electricity market. Furthermore, the numerical results imply on the potential of reducing average retail prices up to 8%, under demand response activation. Consequently, it provides a win–win solution for both retailer and its customers.
Structural optimization has gained considerable attention in the design of structural engineering structures, especially in the preliminary phase.
This study introduces an unconventional approach for structural optimization by utilizing the Energy method with Integral Material Behavior (EIM), based on the Lagrange’s principle of minimum potential energy. An automated two-level optimization search process is proposed, which integrates the EIM, as an alternative method for nonlinear
structural analysis, and the bilevel optimization. The proposed procedure secures the equilibrium through minimizing the potential energy on one level, and on a higher level, a design objective function. For this, the most robust strategy of bilevel optimization, the nested method is used. The function of the potential energy is investigated along with its instabilities for physical nonlinear analysis through principle examples, by which the advantages and limitations using this method are reviewed. Furthermore, optimization algorithms are discussed.
A numerical fully functional code is developed for nonlinear cross section,
element and 2D frame analysis, utilizing different finite elements and is verified
against existing EIM programs. As a proof of concept, the method is applied on selected
examples using this code on cross section and element level. For the former one a
comparison is made with standard procedure, by employing the equilibrium equations
within the constrains. The validation of the element level was proven by a theoretical
solution of an arch bridge and finally, a truss bridge is optimized. Most of the
principle examples are chosen to be adequate for the everyday engineering practice, to
demonstrate the effectiveness of the proposed method.
This study implies that with further development, this method could become just as
competitive as the conventional structural optimization techniques using the Finite
Element Method.