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This study aims to evaluate a new approach in modeling gully erosion susceptibility (GES) based on a deep learning neural network (DLNN) model and an ensemble particle swarm optimization (PSO) algorithm with DLNN (PSO-DLNN), comparing these approaches with common artificial neural network (ANN) and support vector machine (SVM) models in Shirahan watershed, Iran. For this purpose, 13 independent variables affecting GES in the study area, namely, altitude, slope, aspect, plan curvature, profile curvature, drainage density, distance from a river, land use, soil, lithology, rainfall, stream power index (SPI), and topographic wetness index (TWI), were prepared. A total of 132 gully erosion locations were identified during field visits. To implement the proposed model, the dataset was divided into the two categories of training (70%) and testing (30%). The results indicate that the area under the curve (AUC) value from receiver operating characteristic (ROC) considering the testing datasets of PSO-DLNN is 0.89, which indicates superb accuracy. The rest of the models are associated with optimal accuracy and have similar results to the PSO-DLNN model; the AUC values from ROC of DLNN, SVM, and ANN for the testing datasets are 0.87, 0.85, and 0.84, respectively. The efficiency of the proposed model in terms of prediction of GES was increased. Therefore, it can be concluded that the DLNN model and its ensemble with the PSO algorithm can be used as a novel and practical method to predict gully erosion susceptibility, which can help planners and managers to manage and reduce the risk of this phenomenon.
When it comes to monitoring of huge structures, main issues are limited time, high costs and how to deal with the big amount of data. In order to reduce and manage them, respectively, methods from the field of optimal design of experiments are useful and supportive. Having optimal experimental designs at hand before conducting any measurements is leading to a highly informative measurement concept, where the sensor positions are optimized according to minimal errors in the structures’ models. For the reduction of computational time a combined approach using Fisher Information Matrix and mean-squared error in a two-step procedure is proposed under the consideration of different error types. The error descriptions contain random/aleatoric and systematic/epistemic portions. Applying this combined approach on a finite element model using artificial acceleration time measurement data with artificially added errors leads to the optimized sensor positions. These findings are compared to results from laboratory experiments on the modeled structure, which is a tower-like structure represented by a hollow pipe as the cantilever beam. Conclusively, the combined approach is leading to a sound experimental design that leads to a good estimate of the structure’s behavior and model parameters without the need of preliminary measurements for model updating.
The amount of adsorbed styrene acrylate copolymer (SA) particles on cementitious surfaces at the early stage of hydration was quantitatively determined using three different methodological approaches: the depletion method, the visible spectrophotometry (VIS) and the thermo-gravimetry coupled with mass spectrometry (TG–MS). Considering the advantages and disadvantages of each method, including the respectively required sample preparation, the results for four polymer-modified cement pastes, varying in polymer content and cement fineness, were evaluated.
To some extent, significant discrepancies in the adsorption degrees were observed. There is a tendency that significantly lower amounts of adsorbed polymers were identified using TG-MS compared to values determined with the depletion method. Spectrophotometrically generated values were lying in between these extremes. This tendency was found for three of the four cement pastes examined and is originated in sample preparation and methodical limitations.
The main influencing factor is the falsification of the polymer concentration in the liquid phase during centrifugation. Interactions in the interface between sediment and supernatant are the cause. The newly developed method, using TG–MS for the quantification of SA particles, proved to be suitable for dealing with these revealed issues. Here, instead of the fluid phase, the sediment is examined with regard to the polymer content, on which the influence of centrifugation is considerably lower.
Acoustic travel-time TOMography (ATOM) allows the measurement and reconstruction of air temperature distributions. Due to limiting factors, such as the challenge of travel-time estimation of the early reflections in the room impulse response, which heavily depends on the position of transducers inside the measurement area, ATOM is applied mainly outdoors. To apply ATOM in buildings, this paper presents a numerical solution to optimize the positions of transducers. This optimization avoids reflection overlaps, leading to distinguishable travel-times in the impulse response reflectogram. To increase the accuracy of the measured temperature within tomographic voxels, an additional function is employed to the proposed numerical method to minimize the number of sound-path-free voxels, ensuring the best sound-ray coverage of the room. Subsequently, an experimental set-up has been performed to verify the proposed numerical method. The results indicate the positive impact of the optimal positions of transducers on the distribution of ATOM-temperatures.
Discrete function theory in higher-dimensional setting has been in active development since many years. However, available results focus on studying discrete setting for such canonical domains as half-space, while the case of bounded domains generally remained unconsidered. Therefore, this paper presents the extension of the higher-dimensional function theory to the case of arbitrary bounded domains in Rn. On this way, discrete Stokes’ formula, discrete Borel–Pompeiu formula, as well as discrete Hardy spaces for general bounded domains are constructed. Finally, several discrete Hilbert problems are considered.
This article focuses on further developments of the background-oriented schlieren (BOS) technique to visualize convective indoor air flow, which is usually defined by very small density gradients. Since the light rays deflect when passing through fluids with different densities, BOS can detect the resulting refractive index gradients as integration along a line of sight. In this paper, the BOS technique is used to yield a two-dimensional visualization of small density gradients. The novelty of the described method is the implementation of a highly sensitive BOS setup to visualize the ascending thermal plume from a heated thermal manikin with temperature differences of minimum 1 K. To guarantee steady boundary conditions, the thermal manikin was seated in a climate laboratory. For the experimental investigations, a high-resolution DLSR camera was used capturing a large field of view with sufficient detail accuracy. Several parameters such as various backgrounds, focal lengths, room air temperatures, and distances between the object of investigation, camera, and structured background were tested to find the most suitable parameters to visualize convective indoor air flow. Besides these measurements, this paper presents the analyzing method using cross-correlation algorithms and finally the results of visualizing the convective indoor air flow with BOS. The highly sensitive BOS setup presented in this article complements the commonly used invasive methods that highly influence weak air flows.
The evolution of urbanism under dictatorship forms the core of the current research. This thesis is part of a research network at Bauhaus-Universität Weimar, which studies the 20th century's urbanism under different dictatorships. The network has provided a cross-cultural and cross-border environment and has enabled the author to communicate with other like-minded researchers. The 2015 published book of this group 'Urbanism and Dictatorship: A European Perspective' strengthens the foundation of this research's theoretical and methodological framework.
This thesis investigates urban policies and plans leading to the advancement of urbanization and the transformation of urban space in Iran during the second Pahlavi (1941-1979) when the country faced a milestone in its history: Nationalization of the Iranian oil industry. By reflecting the influence of economic and socio‐political determinants of the time on urbanism and the urbanization process, this work intends to critically trace the effect of dictatorship on evolved urbanism before and after the oil nationalization in 1951.
The research on the second Pahlavi's urbanism has been limitedly addressed and has only recently expanded. Most of the conducted studies date back to less than a decade ago and could not incorporate all the episodes of the second Pahlavi urbanism. These works have often investigated urbanism and architecture by focusing merely on the physical features and urban products in different years regardless of the importance of urbanism as a tool in the service of hegemony. In other words, the majority of the available literature does not intend to address the socio-economic and political roots of urban transformations and by questioning 'what has been built?' investigates the individual urban projects and plans designed by individual designers without interlinking these projects to the state's urban planning program and tracing the beneficiaries of those projects or questioning 'built for whom?'
Moreover, some chapters of this modern urbanism have rarely been investigated. For instance, scant research has looked into the works of foreign designers and consultants involved in the projects such as Peter Georg Ahrens or Constantinos A. Doxiadis. Similarly, the urbanism of the first decade of the second Pahlavi, including the government of Mossadegh, has mainly been overlooked.
Therefore, by critically analyzing the state's urban planning program and the process of urbanization in Iran during the second Pahlavi, this research aims to bridge the literature gap and to unravel the effect of the power structure on urban planning and products while seeking to find a pattern behind the regime's policies.
The main body of this work is concentrated on studying the history of urbanism in Iran, of which collecting data and descriptions played a crucial role. To prevent the limitations associated with singular methods, this research's methodology is based on methodological triangulation (Denzin, 2017). With the triangulation scheme, the data is gathered by combining different qualitative and quantitative methods such as the library, archival and media research, online resources, non-participatory observation, and photography. For the empirical part, the city of Tehran is selected as the case study. Moreover, individual non-structured interviews with the locals were conducted to gain more insights regarding urban projects.
The contribution explores the migratory situation on the Balkans and more specifically in the so-called Refugee District in Belgrade from a spatial perspective. By visualizing the areas of tensions in the Refugee District, the city of Belgrade, Serbia and Europe it aims to disentangle the political and socio-spatial levels that lead to the stuck situation of in-betweenness at the gates of the European Union.
das Theater der sorge ist konzipiert als 3-Phasen-modell:
in der 1. Phase geht es um die hersTellung einer laborsituation, in der präfigurative lebens-, denk- und arbeitsformen in diskursiver und spielerischer weise präsentisch erprobt und in konstituierende Prozesse übertragen werden können;
in der 2. Phase geht es um die gemeinschaftliche Konzeption, Vorbereitung und durchführung einer das labor abschließenden öffentlichen auFsTellung, die auf den kollektiven erfahrungen und ergebnissen der
labore basiert. dadurch können gesellschaftliche resonanzen erzeugt und die konstituierenden Prozesse vorläufig instituiert werden.
in der 3.Phase geht es dann darum, Vorbereitung: alle inhaltlichen erkenntnisse und ästhetischen Versuche in eine wiederholbare Theaterinszenierung / Performance zu überführen. die nötigen Voraussetzungen und bedingungen für diese von uns Vorstellungen genannten Formate sind für die hier verhandelte Fragestellung nicht von bedeutung – respektive würden sie den vorhandenen rahmen überschreiten – daher sparen wir diesen Komplex an dieser stelle aus.
Neuartige Sanitärsysteme zielen auf eine ressourcenorientierte Verwertung von Abwasser ab. Erreicht werden soll dies durch die separate Erfassung von Abwasserteilströmen. In den Fachöffentlichkeiten der Wasserwirtschaft und Raumplanung werden neuartige Sanitärsysteme als ein geeigneter Ansatz für die zukünftige
Sicherung der Abwasserentsorgung in ländlichen Räumen betrachtet. Die Praxistauglichkeit dieser Systeme wurde zwar in Forschungsprojekten nachgewiesen, bisher erschweren jedoch für Abwasserentsorger vielfältige Risiken die Einführung einer ressourcenorientierten Abwasserbewirtschaftung. Ausgehend von einer Untersuchung der Kontexte bei der Umsetzung eines neuartigen Sanitärsystems im ländlichen Raum Thüringens wird in diesem Beitrag der Frage nachgegangen, wie auf Landesebene mit dem abwasserwirtschaftlichen Instrumentarium die Einführung von ressourcenorientierten Systemansätzen unterstützt werden kann. Zentrale Elemente des Beitrags sind die Darstellung der wesentlichen Transformationsrisiken in Bezug auf die Einführung innovativer Lösungsansätze, eine Erläuterung der spezifischen abwasserwirtschaftlichen Instrumente sowie die Darlegung von Steuerungsansätzen,mit denen die Einführung von neuartigen Sanitärsystemen gefördert werden kann. Im Ergebnis wird die Realisierbarkeit von neuartigen Sanitärsystemen durch den strategischen Einsatz des Instrumentariums deutlich, gleichwohl die Wasserwirtschaft durch die Erweiterung der bisherigen Systemgrenzen auf die Kooperation mit anderen Bereichen der Daseinsvorsorge angewiesen ist.
A Machine Learning Framework for Assessing Seismic Hazard Safety of Reinforced Concrete Buildings
(2020)
Although averting a seismic disturbance and its physical, social, and economic disruption is practically impossible, using the advancements in computational science and numerical modeling shall equip humanity to predict its severity, understand the outcomes, and equip for post-disaster management. Many buildings exist amidst the developed metropolitan areas, which are senile and still in service. These buildings were also designed before establishing national seismic codes or without the introduction of construction regulations. In that case, risk reduction is significant for developing alternatives and designing suitable models to enhance the existing structure’s performance. Such models will be able to classify risks and casualties related to possible earthquakes through emergency preparation. Thus, it is crucial to recognize structures that are susceptible to earthquake vibrations and need to be prioritized for retrofitting. However, each building’s behavior under seismic actions cannot be studied through performing structural analysis, as it might be unrealistic because of the rigorous computations, long period, and substantial expenditure. Therefore, it calls for a simple, reliable, and accurate process known as Rapid Visual Screening (RVS), which serves as a primary screening platform, including an optimum number of seismic parameters and predetermined performance damage conditions for structures. In this study, the damage classification technique was studied, and the efficacy of the Machine Learning (ML) method in damage prediction via a Support Vector Machine (SVM) model was explored. The ML model is trained and tested separately on damage data from four different earthquakes, namely Ecuador, Haiti, Nepal, and South Korea. Each dataset consists of varying numbers of input data and eight performance modifiers. Based on the study and the results, the ML model using SVM classifies the given input data into the belonging classes and accomplishes the performance on hazard safety evaluation of buildings.
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.
Radikale Planung
(2020)
Smart Cities and Mobility Stations: Lessons learned from the Smarter Together in Vienna and Munich
(2020)
With an increasing urban population and urban problems arising from this unplanned growth, several projects aimed at promoting sustainable urban development have emerged. Smart mobility strategies, such as shared mobility and mobility stations, represent some of the solutions to promote changes in travel behavior. Despite its beneficial impacts, however, the implementation of such infrastructure is criticized for not contributing to current urban issues, as well as often disregarding knowledge about urban space and its functioning.
In this context, the Smarter Together, a joint research and innovation project funded through the European Union program H2020, was implemented. The project selected three lighthouse cities to test and upscale innovative solutions: Vienna, Munich, and Lyon.
This master thesis presents the main characteristics of the mobility stations systems implemented in Vienna and Munich in the scope of the project Smarter Together. Its main goal is to share what can be learned from their experiences while approaching critically the concept of smart cities. This master thesis identifies important aspects to take into account when planning, implementing, and operating mobility stations, and provides an understanding of smart cities and smart mobility that goes beyond the adoption of technology. Several methods were combined for the development of this master thesis, such as quantitative secondary data, observational studies, application of survey forms, explorative expert interviews, and literature review.
This work has demonstrated that the Smarter Together has a cutting-edge scope and contributed greatly to research and innovation, by creating living laboratories to test the application of technology in the urban environment. However, from the perspective of the mobility stations assessment, many caveats were made. In short, many lessons could be learned and are presented throughout this work aiming at contributing to the improvement of the mobility stations implemented in the project areas in Munich and Vienna, as well as for inspiring other cities in Europe and worldwide.
Unmanned aircraft systems (UAS) show large potential for the construction industry. Their use in condition assessment has increased significantly, due to technological and computational progress. UAS play a crucial role in developing a digital maintenance strategy for infrastructure, saving cost and effort, while increasing safety and reliability. Part of that strategy are automated visual UAS inspections of the building’s condition. The resulting images can automatically be analyzed to identify and localize damages to the structure that have to be monitored. Further interest in parts of a structure can arise from events like accidents or collisions. Areas of low interest exist, where low resolution monitoring is sufficient.
From different requirements for resolution, different levels of detail can be derived. They require special image acquisition parameters that differ mainly in the distance between camera and structure. Areas with a higher level of detail require a smaller distance to the object, producing more images. This work proposes a multi-scale flight path planning procedure, enabling higher resolution requirements for areas of special interest, while reducing the number of required images to a minimum. Careful selection of the camera positions maintains the complete coverage of the structure, while achieving the required resolution in all areas. The result is an efficient UAS inspection, reducing effort for the maintenance of infrastructure.
The latest earthquakes have proven that several existing buildings, particularly in developing countries, are not secured from damages of earthquake. A variety of statistical and machine-learning approaches have been proposed to identify vulnerable buildings for the prioritization of retrofitting. The present work aims to investigate earthquake susceptibility through the combination of six building performance variables that can be used to obtain an optimal prediction of the damage state of reinforced concrete buildings using artificial neural network (ANN). In this regard, a multi-layer perceptron network is trained and optimized using a database of 484 damaged buildings from the Düzce earthquake in Turkey. The results demonstrate the feasibility and effectiveness of the selected ANN approach to classify concrete structural damage that can be used as a preliminary assessment technique to identify vulnerable buildings in disaster risk-management programs.
Die im Jahr 2020 in Deutschland praktizierte Siedlungs- und Wohnungspolitik erhält in Anbetracht ihrer Auswirkungen auf die soziale und ökologische Lage einen bitteren Beigeschmack. Arm und Reich triften weiter auseinander und einer zielgerichteten ökologischen Transformation der Art und Weise, wie Stadtentwicklung und Wohnungspolitik gestaltet werden,stehen noch immer historisch und systemisch bedingte Pfadabhängigkeiten im Weg. Diese werden nur durch eine integrierte Betrachtung sozialer und ökonomischer Aspekte sichtbar und deuten auf eine der ursprünglichen Fragen linker Gesellschaftsforschung hin: Die Auseinandersetzung mit dem Verhältnis von Eigentum und Gerechtigkeit.
Im Ergebnis stehen drei wesentliche Befunde: Der Diskurs zum Schutz des Klimas und der Biodiversität berührt direkt die Parameter Dichte, Nutzungsmischung und Flächeninanspruchnahme; zweitens steigt letztere relativ mit erhöhtem, individuell verfügbaren Kapital und insbesondere im selbstgenutztem Eigentum gegenüber Mietwohnungen; und drittens wächst der Eigentumsanteil mit fortschreitender Finanzialisierung des Wohnungsmarktes, sodass das Risiko sozialer und ökologischer Krisen sich verschärft.
Marine Makroalgen besitzen vielversprechende Eigenschaften und Inhaltsstoffe für die Verwendung als Energieträger, Nahrungsmittel oder als Ausgangsstoff für Pharmazeutika. Dass die Quantität und Qualität der in natürlicher Umgebung wachsenden Makroalgen schwankt, reduziert jedoch deren Verwertbarkeit und erschwert die Erschließung hochpreisiger Marktsegmente. Zudem ist eine Ausweitung der Zucht in marinen und küstennahen Aquakulturen in Europa gegenwärtig wenig aussichtsreich, da vielversprechende Areale bereits zum Fischfang oder als Erholungs- bzw. Naturschutzgebiete ausgewiesen sind. Im Rahmen dieser Arbeit wird demzufolge ein geschlossenes Photobioreaktorsystem zur Makroalgenkultivierung entwickelt, welches eine umfassende Kontrolle der abiotischen Kultivierungsparameter und eine effektive Aufbereitung des Kulturmediums vorsieht, um eine standortunabhängige Algenproduktion zu ermöglichen. Zur Bilanzierung des Gesamtkonzeptes einer Kultivierung und Verwertung (stofflich oder energetisch) werden die spezifischen Wachstumsraten und Methanbildungspotentiale der Algenarten Ulva intestinalis, Fucus vesiculosus und Palmaria palmata in praktischen Versuchen ermittelt.
Im Ergebnis wird für den gegenwärtigen Entwicklungsstand der Kultivierungsanlage eine positive Bilanz für die stoffliche Verwertung der Algenart Ulva intestinalis und eine negative Bilanz für die energetische Verwertung aller untersuchten Algenarten erzielt. Wird ein Optimalszenario betrachtet, indem die Besatzdichten und Wachstumsraten der Algen in der Zucht erhöht werden, bleibt die Energiebilanz negativ. Allerdings summieren sich die finanzielle Einnahmen durch einen Verkauf der Algen als Produkt auf jährlich 460.869€ für Ulva intestinalis, 4.010€ für Fucus vesiculosus und 16.913€ für Palmaria palmata. Im Ergebnis ist insbesondere eine stoffliche Verwertung der gezüchteten Grünalge Ulva intestinalis anzustreben und die Produktivität der Zuchtanlage im Sinne des Optimalszenarios zu steigern.