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Year of publication
- 2018 (58) (remove)
Increasing structural robustness is the goal which is of interest for structural engineering community. The partial collapse of RC buildings is subject of this dissertation. Understanding the robustness of RC buildings will guide the development of safer structures against abnormal loading scenarios such as; explosions, earthquakes, fine, and/or long-term accumulation effects leading to deterioration or fatigue. Any of these may result in local immediate structural damage, that can propagate to the rest of the structure causing what is known by the disproportionate collapse.
This work handels collapse propagation through various analytical approaches which simplifies the mechanical description of damaged reinfoced concrete structures due to extreme acidental event.
Polymeric nanocomposites (PNCs) are considered for numerous nanotechnology such as: nano-biotechnology, nano-systems, nanoelectronics, and nano-structured materials. Commonly , they are formed by polymer (epoxy) matrix reinforced with a nanosized filler. The addition of rigid nanofillers to the epoxy matrix has offered great improvements in the fracture toughness without sacrificing other important thermo-mechanical properties. The physics of the fracture in PNCs is rather complicated and is influenced by different parameters. The presence of uncertainty in the predicted output is expected as a result of stochastic variance in the factors affecting the fracture mechanism. Consequently, evaluating the improved fracture toughness in PNCs is a challenging problem.
Artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) have been employed to predict the fracture energy of polymer/particle nanocomposites. The ANN and ANFIS models were constructed, trained, and tested based on a collection of 115 experimental datasets gathered from the literature. The performance evaluation indices of the developed ANN and ANFIS showed relatively small error, with high coefficients of determination (R2), and low root mean square error and mean absolute percentage error.
In the framework for uncertainty quantification of PNCs, a sensitivity analysis (SA) has been conducted to examine the influence of uncertain input parameters on the fracture toughness of polymer/clay nanocomposites (PNCs). The phase-field approach is employed to predict the macroscopic properties of the composite considering six uncertain input parameters. The efficiency, robustness, and repeatability are compared and evaluated comprehensively for five different SA methods.
The Bayesian method is applied to develop a methodology in order to evaluate the performance of different analytical models used in predicting the fracture toughness of polymeric particles nanocomposites. The developed method have considered the model and parameters uncertainties based on different reference data (experimental measurements) gained from the literature. Three analytical models differing in theory and assumptions were examined. The coefficients of variation of the model predictions to the measurements are calculated using the approximated optimal parameter sets. Then, the model selection probability is obtained with respect to the different reference data.
Stochastic finite element modeling is implemented to predict the fracture toughness of polymer/particle nanocomposites. For this purpose, 2D finite element model containing an epoxy matrix and rigid nanoparticles surrounded by an interphase zone is generated. The crack propagation is simulated by the cohesive segments method and phantom nodes. Considering the uncertainties in the input parameters, a polynomial chaos expansion (PCE) surrogate model is construed followed by a sensitivity analysis.
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.
Living heritage sites are strongly connected to their historical, geographical, socio-political and cultural context. A descriptive narrative of the evolutionary process of the living heritage site of a Sufi shrine is undertaken in this research. It focuses on the changing relationship between the spatial and socio-cultural aspects over time. The larger or macro regional context is interrelated to the micro architectural context. The tangible heritage is defined by and intimately tied to the intangible aspects of the heritage. It is these constituting macro and micro elements and their interrelationships particularly through space and architecture that the research thesis explores in its documentation and analysis.
The Sufi shrine in the South Asian Pakistani context is representative of a larger culture in the precolonial era. It is an expression of an indigenous modernity, belonging to a certain time period, place and community. The Sufi shrine as a building type has evolved from the precolonial time period, particularly starting at the golden ages of the Muslim Empire in the world (9th – 12th century), through the colonial age when western modernity arrived until the current neoliberal paradigm within the post independence period. Continued and evolved use of space, ritualistic performances, multiple social groups using the site are various elements whose documentation and analysis can establish the essential co-relations that contribute to continuity of its historical living. Physical and social relation of the historic site to its immediate settlement context is also a significant element that preserves the socio-cultural context.
The chosen case of the Shrine of Shah Abdul Latif Bhitai, situated in the small town of Bhitshah in the province of Sindh, Pakistan forms a unique example where the particular physical and socio-cultural environment forms the context within which the Sufi heritage lives and survives. It is well integrated within its context at multiple levels. What are these levels and how do the constituting elements integrate is a major subject of research? These form the background to defining some of the basic issues and questions addressed in this doctoral thesis.
Given that living heritage sites are unique due to their particular association to the context, the case study method was used to gain deeper insight and understanding on the topic.
Am 22. Januar 2017 wurde die Beraterin des amerikanischen Präsidenten, Kellyanne Conway, in einem Meet the Press-Interview gefragt, warum der Pressesprecher des Präsidenten kurz zuvor eine »nachweisliche Lüge« bezüglich der Zahl der in Washington zur Amtseinführung Trumps zusammengekommenen Menschen geäußert habe. Conway antwortete: »Our press secretary, Sean Spicer, gave alternative facts […]«. Das war nicht nur eine Manifestation oder Überbietung von Orwellianischem »Newspeak«. Es war ein Moment, in dem sich ein Bruch mit dem in der westlichen Kultur bislang allgemein anerkannten Paradigma, worin die Faktizität von Daten – seien es Bilder, Zahlen, Aussagen – gründet, offen aussprach. Es war sozusagen ein ironischer Moment der Wahrheit – ironisch, weil dieser Moment einen Höhepunkt des »Post-Truth«-Zeitalters darstellte.
Doch welche Wahrheit? Dass es dazu unterschiedliche und zum Teil kontroverse Auffassungen gibt, zeigen die verschiedenen Deutungen und Instrumentalisierungen, die dieser Moment der Wahrheit in der Folge erfuhr. Der Debattenteil der letzten Ausgabe der Zeitschrift für Medien- und Kulturforschung hat bereits einen Teil dieser Kontroverse um die Deutung des Phänomens von »fake news« und »alternative facts« dokumentiert. Der Schwerpunkt der vorliegenden Ausgabe setzt diese Kontroverse fort, und zwar deswegen, weil die Kultur- und Medienwissenschaft in mehrfacher Weise vom Ereignis »alternativer Fakten« und den sich anschließenden Kontroversen um ihre Bewertung herausgefordert wird. Sehr schnell wurde nämlich klar, dass die Antwort auf die Frage, welche Wahrheit sich in jenem Moment kundtat, als die Welt aus dem (sich dabei merklich verziehenden) Munde von Kellyanne Conway vom Wunder der Existenz alternativer Fakten erfuhr, nicht einfach nur banal war. So banal wie die Tatsache, dass ein infantiler Narzissmus zur Richtschnur für die Konstruktion der offiziellen amerikanischen Regierungsversion von Wirklichkeit geworden ist, ein Narzissmus, der das, was ist (und wofür es zureichende Gründe gibt), zugunsten dessen verwirft, von dem er möchte, dass es stattdessen sei.
SEEING HISTORY - THE AUGMENTED ARCHIVE erforscht – in Theorie und Praxis – die Medialitäten des Archivs in Zeiten des Übergangs vom Speichermedium hin zum Modus des Übertragens. Am Beispiel Ägyptens seit den politischen Umwälzungen 2011 wird ein neues Archivsystem entwickelt, das mit Hilfe von Augmented Reality Technologie - d.h. der virtuellen Erweiterung des Realraums von mobiler Videotechnik durch Metainformationen - das umfassendste bestehende Videoarchiv zur ägyptischen Revolution im Stadtraum Kairos per GPS-Kodierung zur Verfügung stellt.
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.
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.
A broadband soil dielectric spectra retrieval approach ( 1 MHz– 2 GHz) has been implemented for a layered half space. The inversion kernel consists of a two-port transmission line forward model in the frequency domain and a constitutive material equation based on a power law soil mixture rule (Complex Refractive Index Model - CRIM). The spatially-distributed retrieval of broadband dielectric spectra was achieved with a global optimization approach based on a Shuffled Complex Evolution (SCE) algorithm using the full set of the scattering parameters. For each layer, the broadband dielectric spectra were retrieved with the corresponding parameters thickness, porosity, water saturation and electrical conductivity of the aqueous pore solution. For the validation of the approach, a coaxial transmission line cell measured with a network analyzer was used. The possibilities and limitations of the inverse parameter estimation were numerically analyzed in four scenarios. Expected and retrieved layer thicknesses, soil properties and broadband dielectric spectra in each scenario were in reasonable agreement. Hence, the model is suitable for an estimation of in-homogeneous material parameter distributions. Moreover, the proposed frequency domain approach allows an automatic adaptation of layer number and thickness or regular grids in time and/or space.
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.