Refine
Document Type
- Article (57)
- Doctoral Thesis (26)
- Part of a Book (16)
- Master's Thesis (7)
- Book (4)
- Preprint (3)
- Conference Proceeding (2)
- Habilitation (2)
- Report (2)
- Bachelor Thesis (1)
Institute
- Institut für Strukturmechanik (ISM) (42)
- Junior-Professur Bildtheorie (17)
- Professur Bauphysik (8)
- Professur Sozialwissenschaftliche Stadtforschung (7)
- Junior-Professur Organisation und vernetzte Medien (6)
- Institut für Europäische Urbanistik (5)
- Professur Bauchemie und Polymere Werkstoffe (3)
- Professur Denkmalpflege und Baugeschichte (3)
- Professur Modellierung und Simulation - Konstruktion (3)
- Bauhaus-Institut für zukunftsweisende Infrastruktursysteme (b.is) (2)
- Freie Kunst (2)
- Professur Angewandte Mathematik (2)
- Professur Stadtplanung (2)
- Professur Werkstoffe des Bauens (2)
- Promotionsstudiengang Kunst und Design-Freie Kunst-Medienkunst (Ph.D) (2)
- Geschichte und Theorie der Kunst (1)
- Geschichte und Theorie der Visuellen Kommunikation (1)
- Graduiertenkolleg 1462 (1)
- Hochschule für Musik FRANZ LISZT (1)
- Kompetenzzentrum Medienanthropologie (KOMA) (1)
- Materialforschungs- und -prüfanstalt an der Bauhaus-Universität (1)
- Medienkunst/Mediengestaltung (1)
- Professur Baustatik und Bauteilfestigkeit (1)
- Professur Computer Vision in Engineering (1)
- Professur Content Management und Webtechnologien (1)
- Professur Entwerfen und Innenraumgestaltung (1)
- Professur Geschichte und Theorie der Kulturtechniken (1)
- Professur Immobilienwirtschaft und -management (1)
- Professur Intelligentes Technisches Design (1)
- Professur Medieninformatik (1)
- Professur Mediensoziologie (1)
- Professur Raumplanung und Raumforschung (1)
- Zentrale Einrichtungen, Büro des Präsidenten, Dezernate (1)
- bauhaus.institut für experimentelle Architektur (1)
Keywords
- OA-Publikationsfonds2020 (27)
- Maschinelles Lernen (17)
- Machine learning (12)
- Künstlerische Forschung (10)
- Erdbeben (7)
- Deep learning (5)
- Theater (5)
- big data (5)
- Medien (4)
- Raumklima (4)
Year of publication
- 2020 (123) (remove)
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.
In Germany, bridges have an average age of 40 years. A bridge consumes between 0.4% and 2% of its construction cost per year over its entire life cycle. This means that up to 80% of the construction cost are additionally needed for operation, inspection, maintenance, and destruction. Current practices rely either on paperbased inspections or on abstract specialist software. Every application in the inspection and maintenance sector uses its own data model for structures, inspections, defects, and maintenance. Due to this, data and properties have to be transferred manually, otherwise a converter is necessary for every data exchange between two applications. To overcome this issue, an adequate model standard for inspections, damage, and maintenance is necessary. Modern 3D models may serve as a single source of truth, which has been suggested in the Building Information Modeling (BIM) concept. Further, these models offer a clear visualization of the built infrastructure, and improve not only the planning and construction phases, but also the operation phase of construction projects. BIM is established mostly in the Architecture, Engineering, and Construction (AEC) sector to plan and construct new buildings. Currently, BIM does not cover the whole life cycle of a building, especially not inspection and maintenance. Creating damage models needs the building model first, because a defect is dependent on the building component, its properties and material. Hence, a building information model is necessary to obtain meaningful conclusions from damage information. This paper analyzes the requirements, which arise from practice, and the research that has been done in modeling damage and related information for bridges. With a look at damage categories and use cases related to inspection and maintenance, scientific literature is discussed and synthesized. Finally, research gaps and needs are identified and discussed.
Prediction of the groundwater nitrate concentration is of utmost importance for pollution control and water resource management. This research aims to model the spatial groundwater nitrate concentration in the Marvdasht watershed, Iran, based on several artificial intelligence methods of support vector machine (SVM), Cubist, random forest (RF), and Bayesian artificial neural network (Baysia-ANN) machine learning models. For this purpose, 11 independent variables affecting groundwater nitrate changes include elevation, slope, plan curvature, profile curvature, rainfall, piezometric depth, distance from the river, distance from residential, Sodium (Na), Potassium (K), and topographic wetness index (TWI) in the study area were prepared. Nitrate levels were also measured in 67 wells and used as a dependent variable for modeling. Data were divided into two categories of training (70%) and testing (30%) for modeling. The evaluation criteria coefficient of determination (R2), mean absolute error (MAE), root mean square error (RMSE), and Nash–Sutcliffe efficiency (NSE) were used to evaluate the performance of the models used. The results of modeling the susceptibility of groundwater nitrate concentration showed that the RF (R2 = 0.89, RMSE = 4.24, NSE = 0.87) model is better than the other Cubist (R2 = 0.87, RMSE = 5.18, NSE = 0.81), SVM (R2 = 0.74, RMSE = 6.07, NSE = 0.74), Bayesian-ANN (R2 = 0.79, RMSE = 5.91, NSE = 0.75) models. The results of groundwater nitrate concentration zoning in the study area showed that the northern parts of the case study have the highest amount of nitrate, which is higher in these agricultural areas than in other areas. The most important cause of nitrate pollution in these areas is agriculture activities and the use of groundwater to irrigate these crops and the wells close to agricultural areas, which has led to the indiscriminate use of chemical fertilizers by irrigation or rainwater of these fertilizers is washed and penetrates groundwater and pollutes the aquifer.
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.
Piping erosion is one form of water erosion that leads to significant changes in the landscape and environmental degradation. In the present study, we evaluated piping erosion modeling in the Zarandieh watershed of Markazi province in Iran based on random forest (RF), support vector machine (SVM), and Bayesian generalized linear models (Bayesian GLM) machine learning algorithms. For this goal, due to the importance of various geo-environmental and soil properties in the evolution and creation of piping erosion, 18 variables were considered for modeling the piping erosion susceptibility in the Zarandieh watershed. A total of 152 points of piping erosion were recognized in the study area that were divided into training (70%) and validation (30%) for modeling. The area under curve (AUC) was used to assess the effeciency of the RF, SVM, and Bayesian GLM. Piping erosion susceptibility results indicated that all three RF, SVM, and Bayesian GLM models had high efficiency in the testing step, such as the AUC shown with values of 0.9 for RF, 0.88 for SVM, and 0.87 for Bayesian GLM. Altitude, pH, and bulk density were the variables that had the greatest influence on the piping erosion susceptibility in the Zarandieh watershed. This result indicates that geo-environmental and soil chemical variables are accountable for the expansion of piping erosion in the Zarandieh watershed.
While Public-Private Partnership (PPP) is widely adopted across various sectors, it raises a question on its meagre utilisation in the housing sector. This paper, therefore, gauges the perspective of the stakeholders in the building industry towards the application of PPP in various building sectors together with housing. It assesses the performance reliability of PPP for housing by learning possible take-aways from other sectors. The role of key stakeholders in the industry becomes highly responsible for an informed understanding and decision-making. To this end, a two-tier investigation was conducted including surveys and expert interviews, with several stakeholders in the PPP industry in Europe, involving the public sector, private sector, consultants, as well as other community/user representatives.
The survey results demonstrated the success rate with PPPs, major factors important for PPPs such as profitability or end-user acceptability, the prevalent practices and trends in the PPP world, and the majority of support expressed in favour of the suitability of PPP for housing. The interviews added more detailed dimensions to the understanding of the PPP industry, its functioning and enabling the formation of a comprehensive outlook. The results present the perspective, approaches, and experiences of stakeholders over PPP practices, current trends and scenarios and their take on PPP in housing. It shall aid in understanding the challenges prevalent in the PPP approach for implementation in housing and enable the policymakers and industry stakeholders to make provisions for higher uptake to accelerate housing provision.
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.
Experimente lernen, Techniken tauschen. Ein spekulatives Handbuch
Das spekulative Handbuch bietet vielfältige Techniken für ein radikales Lernen und Vermitteln. Es umfasst konkrete Anleitungen, Erfahrungen und theoretische Überlegungen. Die Texte beteiligen sich an der Konzeption einer Vermittlung, die das gemeinsame Experimentieren (wieder) einführt.
Im Seminarraum, in Workshops, auf Festivals, in Fluren, Parks und der Stadt finden Lernen und Verlernen statt. Texte und Anleitungen u. a. zu: Filmessays, Collagen, Banküberfällen, der Universität der Toten, wildem Schreiben, konzeptuellem speed Dating, neurodiversem Lernen, Format-Denken, dem Theater der Sorge, dem Schreiblabor, dem Körperstreik.
Experimente lernen, Techniken tauschen
Ein spekulatives Handbuch
Das spekulative Handbuch bietet vielfältige Techniken für ein radikales Lernen und Vermitteln. Es umfasst konkrete Anleitungen, Erfahrungen und theoretische Überlegungen. Die Texte beteiligen sich an der Konzeption einer Vermittlung, die das gemeinsame Experimentieren (wieder) einführt.
Im Seminarraum, in Workshops, auf Festivals, in Fluren, Parks und der Stadt finden Lernen und Verlernen statt. Texte und Anleitungen u. a. zu: Filmessays, Collagen, Banküberfällen, der Universität der Toten, wildem Schreiben, konzeptuellem speed Dating, neurodiversem Lernen, Format-Denken, dem Theater der Sorge, dem Schreiblabor, dem Körperstreik.
Die Ruine der Barfüßerkirche in Erfurt stellt eine der letzten Erinnerungen an die Zerstörungen der Stadt im Zweiten Weltkrieg dar. Sie wird bis heute temporär und saisonal kulturell genutzt. Im Rahmen eines Studienprojektes im Sommersemester 2019 wurden an der Bauhaus-Universität Weimar, betreut durch die Professur Denkmalpflege und Baugeschichte und unterstützt vom Initiativkreis Barfüßerkirche, Nutzungskonzepte für ein Museum für Mittelalterkunst und für einen Tagungsort untersucht. Der vorliegende Band dokumentiert die 14 studentischen Entwürfe, die für ein Weiterbauen an der Barfüßerkirche entstanden sind.
The "Stapelhaus": Experimental building project on the campus of the Bauhaus-Universität Weimar
(2020)
The project is a cooperation between the bauhaus.ifex and MFPA Weimar and is intended to develop step by step as an experimental student village. Special focus is given to sustainability and construction using different building materials. For the construction of the first room module, CemCel was chosen as a new, lightweight and fibre-based building material.
Die derzeitige Wohnungskrise hat eine sozial-ökologische Kernproblematik. Dabei ist die sozial ungerechte und ökologisch problematische Verteilung von Wohnfläche meist unsichtbar und wird weder in wissenschaftlichen noch in aktivistischen Kontexten ausreichend als Frage der Flächengerechtigkeit problematisiert. Denn Wohnraum und Fläche in einer Stadt sind keine endlos verfügbaren Güter: Wenn einige Menschen auf viel Raum leben, bleibt für andere Menschen weniger Fläche übrig. Und die Menschen, die am wenigstens für eine Verknappung von Wohnraum verantwortlich sind, leiden am meisten darunter. Dieser Artikel arbeitet zunächst den Begriff der Wohnflächengerechtigkeit heraus, wobei auf die Ungleichverteilung von Wohnfläche und deren gesellschaftliche Implikationen unter derzeitigen Wohnungsverteilungsmechanismen Bezug genommen wird. Anschließend wird der Verbrauch von (Wohn-)Fläche aus ökologischer Perspektive problematisiert. Der Artikel diskutiert scheinbare und transformationsorientierte Lösungs- und Handlungsansätze. Abschließend fordert er in der kritischen Stadtforschung und in aktivistischen Kontexten eine stärkere Debatte um eine Wohnflächengerechtigkeit, deren Verwirklichung gleichermaßen eine soziale wie ökologische Dimension hat.
Die zu beobachtenden kürzeren Produktlebenszyklen und eine schnellere Marktdurchdringung von Produkttechnologien erfordern adaptive und leistungsfähige Produktionsanlagen. Die Adaptivität ermöglicht eine Anpassung der Produktionsanlage an neue Produkte, und die Leistungsfähigkeit der Anlage stellt sicher, dass ausreichend Produkte in kurzer Zeit und zu geringen Kosten hergestellt werden können. Durch eine Modularisierung der Produktionsanlage kann die Adaptivität erreicht werden. Jedoch erfordert heutzutage jede Adaption manuellen Aufwand, z.B. zur Anpassung von proprietären Signalen oder zur Anpassung übergeordneter Funktionen. Dadurch sinkt die Leistungsfähigkeit der Anlage.
Das Ziel dieser Arbeit ist es, die Interoperabilität in Bezug auf die Informationsverwendung in modularen Produktionsanlagen zu gewährleisten. Dazu werden Informationen durch semantische Modelle beschrieben. Damit wird ein einheitlicher Informationszugriff ermöglicht, und übergeordnete Funktionen erhalten Zugriff auf alle Informationen der Produktionsmodule, unabhängig von dem Typ, dem Hersteller und dem Alter des Moduls. Dadurch entfällt der manuelle Aufwand bei Anpassungen des modularen Produktionssystems, wodurch die Leistungsfähigkeit der Anlage gesteigert und Stillstandszeiten reduziert werden.
Nach dem Ermitteln der Anforderungen an einen Modellierungsformalismus wurden potentielle Formalismen mit den Anforderungen abgeglichen. OWL DL stellte sich als geeigneter Formalismus heraus und wurde für die Erstellung des semantischen Modells in dieser Arbeit verwendet. Es wurde exemplarisch ein semantisches Modell für die drei Anwendungsfälle Interaktion, Orchestrierung und Diagnose erstellt. Durch einen Vergleich der Modellierungselemente von unterschiedlichen Anwendungsfällen wurde die Allgemeingültigkeit des Modells bewertet. Dabei wurde gezeigt, dass die Erreichung eines allgemeinen Modells für technische Anwendungsfälle möglich ist und lediglich einige Hundert Begriffe benötigt.
Zur Evaluierung der erstellten Modelle wurde ein wandlungsfähiges Produktionssystem der SmartFactoryOWL verwendet, an dem die Anwendungsfälle umgesetzt wurden. Dazu wurde eine Laufzeitumgebung erstellt, die die semantischen Modelle der einzelnen Module zu einem Gesamtmodell vereint, Daten aus der Anlage in das Modell überträgt und eine Schnittstelle für die Services bereitstellt. Die Services realisieren übergeordnete Funktionen und verwenden die Informationen des semantischen Modells. In allen drei Anwendungsfällen wurden die semantischen Modelle korrekt zusammengefügt und mit den darin enthaltenen Informationen konnte die Aufgabe des jeweiligen Anwendungsfalles ohne zusätzlichen manuellen Aufwand gelöst werden.
This paper proposes a practice-theoretical journalism research approach for an alternate and innovative perspective of digital journalism’s current empirical challenges. The practice-theoretical approach is introduced by demonstrating its explanatory power in relation to demarcation problems, technological changes, economic challenges and challenges to journalism’s legitimacy. Its respective advantages in dealing with these problems are explained and then compared to established journalism theories. The particular relevance of the theoretical perspective is due to (1) its central decision to observe journalistic practices, (2) the transgression of conventional journalistic boundaries, (3) the denaturalization of journalistic norms and laws, (4) the explicit consideration of a material, socio-technical dimension of journalism, (5) a focus on the conflicting relationship between journalistic practices and media management practices, and (6) prioritizing order generation over stability.
Why Do Digital Native News Media Fail? An Investigation of Failure in the Early Start-Up Phase
(2020)
Digital native news media have great potential for improving journalism. Theoretically, they can be the sites where new products, novel revenue streams and alternative ways of organizing digital journalism are discovered, tested, and advanced. In practice, however, the situation appears to be more complicated. Besides the normal pressures facing new businesses, entrepreneurs in digital news are faced with specific challenges. Against the background of general and journalism specific entrepreneurship literature, and in light of a practice–theoretical approach, this qualitative case study research on 15 German digital native news media outlets empirically investigates what barriers curb their innovative capacity in the early start-up phase. In the new media organizations under study here, there are—among other problems—a high degree of homogeneity within founding teams, tensions between journalistic and economic practices, insufficient user orientation, as well as a tendency for organizations to be underfinanced. The patterns of failure investigated in this study can raise awareness, help news start-ups avoid common mistakes before actually entering the market, and help industry experts and investors to realistically estimate the potential of new ventures within the digital news industry.
Das vorliegende Gutachten befasst sich mit der Innovationslandschaft des deutschen Journalismus. Innovation wird als eine essenzielle Voraussetzung verstanden, um tragfähige Lösungsansätze für die gegenwärtigen Probleme des Journa-lismus zu entwickeln. Im Mittelpunkt des Gutachtens steht die Frage, wie Innovationspolitik im Journalismus – d. h. die Unterstützung von Innovation durch die öffentliche Hand – funktionstüchtig ausgestaltet werden kann. Dabei wird dem Innovationssysteme-Ansatz gefolgt, welcher Probleme, Barrieren und Hemmnisse identifiziert, die der Innovationsfähigkeit des Journalismus in Deutschland grundlegend im Wege stehen.
The thesis concerns a work of urban history intended not to describe the city but rather to interpret it. By doing so, I have interpreted the city by means of the role played by the so-called ‘great property’ in the European city-making process during the last three decades of the 20th century, specifically focused on the concrete case of military properties in Italy. I have also considered the role played by other kinds of great properties, i.e. industries and railway, which previously acted in the production of the built environment in a different way respect to the military one. As all of them have as common denominator the fact of being ‘capital in land’, I analysed great industrial and railway properties in order to extrapolate a methodology which helped me to interpret the relationship between military properties and city-making process in Europe in the late 20th century.
I have analysed the relationship between the capital in land and the city-making process on the ground of the understanding the interrelation between the great property, the urban development, and the agents involved in the urban and territorial planning. Here I have showed that urban planning is not the decisive factor influencing the citymaking process, but instead the power held by the capital in land. I have found that is the great property the trigger of the creation of new ‘areas of centrality’ intended as large areas for consumerism. As far as the role played by great property is concerned, I have also discovered that it has evolved over time. Originally, industrial and railway properties have been regenerated into a wide range of new profit-driven spaces; successively, I have found out that most of the regeneration of military premises aimed to materialise areas of centrality. The way of interpreting this factor has been based on focusing my attention on the military premises in Italy: I have classified their typology when they have been built and, most importantly, when they have been regenerated into new areas of centrality.
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.
The purpose of this study is to develop self-contained methods for obtaining smooth meshes which are compatible with isogeometric analysis (IGA). The study contains three main parts. We start by developing a better understanding of shapes and splines through the study of an image-related problem. Then we proceed towards obtaining smooth volumetric meshes of the given voxel-based images. Finally, we treat the smoothness issue on the multi-patch domains with C1 coupling. Following are the highlights of each part.
First, we present a B-spline convolution method for boundary representation of voxel-based images. We adopt the filtering technique to compute the B-spline coefficients and gradients of the images effectively. We then implement the B-spline convolution for developing a non-rigid images registration method. The proposed method is in some sense of “isoparametric”, for which all the computation is done within the B-splines framework. Particularly, updating the images by using B-spline composition promote smooth transformation map between the images. We show the possible medical applications of our method by applying it for registration of brain images.
Secondly, we develop a self-contained volumetric parametrization method based on the B-splines boundary representation. We aim to convert a given voxel-based data to a matching C1 representation with hierarchical cubic splines. The concept of the osculating circle is employed to enhance the geometric approximation, where it is done by a single template and linear transformations (scaling, translations, and rotations) without the need for solving an optimization problem. Moreover, we use the Laplacian smoothing and refinement techniques to avoid irregular meshes and to improve mesh quality. We show with several examples that the method is capable of handling complex 2D and 3D configurations. In particular, we parametrize the 3D Stanford bunny which contains irregular shapes and voids.
Finally, we propose the B´ezier ordinates approach and splines approach for C1 coupling. In the first approach, the new basis functions are defined in terms of the B´ezier Bernstein polynomials. For the second approach, the new basis is defined as a linear combination of C0 basis functions. The methods are not limited to planar or bilinear mappings. They allow the modeling of solutions to fourth order partial differential equations (PDEs) on complex geometric domains, provided that the given patches are G1
continuous. Both methods have their advantages. In particular, the B´ezier approach offer more degree of freedoms, while the spline approach is more computationally efficient. In addition, we proposed partial degree elevation to overcome the C1-locking issue caused by the over constraining of the solution space. We demonstrate the potential of the resulting C1 basis functions for application in IGA which involve fourth order PDEs such as those appearing in Kirchhoff-Love shell models, Cahn-Hilliard phase field application, and biharmonic problems.