Refine
Has Fulltext
- yes (26) (remove)
Institute
- Institut für Strukturmechanik (ISM) (6)
- Institut für Europäische Urbanistik (3)
- Professur Bauphysik (3)
- Bauhaus-Institut für zukunftsweisende Infrastruktursysteme (b.is) (2)
- Professur Stahl- und Hybridbau (2)
- Erdbebenzentrum (1)
- Fakultät Kunst und Gestaltung (1)
- Junior-Professur Bildtheorie (1)
- Junior-Professur Komplexe Tragwerke (1)
- Junior-Professur Organisation und vernetzte Medien (1)
Keywords
- OA-Publikationsfonds2022 (26) (remove)
This dataset presents the numerical analysis of the heat and moisture transport through a facade equipped with a living wall system designated for greywater treatment. While such greening systems provide many environmental benefits, they involve pumping large quantities of water onto the wall assembly, which can increase the risk of moisture in the wall as well as impaired energetic performance due to increased thermal conductivity with increased moisture content in the building materials. This dataset was acquired through numerical simulation using the coupling of two simulation tools, namely Envi-Met and Delphin. This coupling was used to include the complex role the plants play in shaping the near-wall environmental parameters in the hygrothermal simulations. Four different wall assemblies were investigated, each assembly was assessed twice: with and without the living wall. The presented data include the input and output parameters of the simulations, which were presented in the co-submitted article [1].
Multi-criteria decision analysis (MCDA) is an established methodology to support the decision-making of multi-objective problems. For conducting an MCDA, in most cases, a set of objectives (SOO) is required, which consists of a hierarchical structure comprised of objectives, criteria, and indicators. The development of an SOO is usually based on moderated development processes requiring high organizational and cognitive effort from all stakeholders involved. This article proposes elementary interactions as a key paradigm of an algorithm-driven development process for an SOO that requires little moderation efforts. Elementary interactions are self-contained information requests that may be answered with little cognitive effort. The pairwise comparison of elements in the well-known analytical hierarchical process (AHP) is an example of an elementary interaction. Each elementary interaction in the development process presented contributes to the stepwise development of an SOO. Based on the hypothesis that an SOO may be developed exclusively using elementary interactions (EIs), a concept for a multi-user platform is proposed. Essential components of the platform are a Model Aggregator, an Elementary Interaction Stream Generator, a Participant Manager, and a Discussion Forum. While the latter component serves the professional exchange of the participants, the first three components are intended to be automatable by algorithms. The platform concept proposed has been evaluated partly in an explorative validation study demonstrating the general functionality of the algorithms outlined. In summary, the platform concept suggested demonstrates the potential to ease SOO development processes as the platform concept does not restrict the application domain; it is intended to work with little administration moderation efforts, and it supports the further development of an existing SOO in the event of changes in external conditions. The algorithm-driven development of SOOs proposed in this article may ease the development of MCDA applications and, thus, may have a positive effect on the spread of MCDA applications.
Das Fahrrad ist ein Medium sozialer Veränderung. Seine vielfältigen utopischen Potenziale ergeben sich nicht zuletzt aus seinen ebenso vielfältigen und häufig übersehenen medialen Qualitäten: Es vermittelt, es verbindet, es übersetzt; es modifiziert Wahrnehmung und Organisation von Raum und Zeit, von Körpern und von Sozialität. Umgekehrt kann auch das medienwissenschaftliche Denken fahrradmedial verändert werden. Das Fahrrad ist nicht nur Medium des sozialen und ökologischen Wandels: Radfahren eröffnet Perspektiven, verändert Räume, lässt neue Relationen entstehen und teilt Handlungsmacht neu auf.
Fahrradutopien denkt vom Fahrrad aus und ergänzt dabei bestehende Ansätze zur Mobilitätsforschung um medienkulturwissenschaftliche Perspektiven. Die Beiträge verbinden Medienwissenschaften und Forschungen zu Fahrradaktivismus mit der Liebe zum Radfahren. Fokussiert werden Fahrradfilme und -vlogs, Verkehr und Infrastrukturen, Virtuelle Realität und Fahrrad, Fahrradkollektive und Fahrradfeminismus.
Der Aufruf, die Begriffe Stadt und Kritik in das Zentrum einer Debatte zu stellen, bietet die große Chance, uns weit über begriffliche Klärungen unseres gemeinsamen Arbeitsgegenstands hinaus – die ja auch für sich selbst sehr fruchtbar sein können – über die Funktion zu verständigen, die wir in der Gesellschaft ausüben, wenn wir räumliche Planung praktizieren, erforschen und lehren. Da in der Bundesrepublik nicht nur ein großer Bedarf, sondern auch eine beträchtliche Nachfrage nach öffentlicher Planung besteht und die planungsbezogenen Wissenschaften sich eines insgesamt stabilen institutionellen Standes erfreuen, laufen wir Gefahr, die gesellschaftspolitische Legitimation von Berufsfeld und Wissenschaft zu vernachlässigen, sie als gegeben zu behandeln. Wir müssen uns ja kaum rechtfertigen.
The seismic vulnerability assessment of existing reinforced concrete (RC) buildings is a significant source of disaster mitigation plans and rescue services. Different countries evolved various Rapid Visual Screening (RVS) techniques and methodologies to deal with the devastating consequences of earthquakes on the structural characteristics of buildings and human casualties. Artificial intelligence (AI) methods, such as machine learning (ML) algorithm-based methods, are increasingly used in various scientific and technical applications. The investigation toward using these techniques in civil engineering applications has shown encouraging results and reduced human intervention, including uncertainties and biased judgment. In this study, several known non-parametric algorithms are investigated toward RVS using a dataset employing different earthquakes. Moreover, the methodology encourages the possibility of examining the buildings’ vulnerability based on the factors related to the buildings’ importance and exposure. In addition, a web-based application built on Django is introduced. The interface is designed with the idea to ease the seismic vulnerability investigation in real-time. The concept was validated using two case studies, and the achieved results showed the proposed approach’s potential efficiency
This dataset consists mainly of two subsets. The first subset includes measurements and simulation data conducted to validate the simulation tool ENVI-met. The measurements were conducted at the campus of the Bauhaus-University Weimar in Weimar, Germany and consisted of recording exterior air temperature, globe temperature, relative humidity, and wind velocity at 1.5 m at four points on four different days. After the measurements, the geometry of the campus was modelled and meshed; the simulations were conducted using the weather data of the measurements days with the aim of investigating the accuracy of the model.
The second data subset consists of ENVI-met simulation data of the potential of facade greening in improving the outdoor environment and the indoor air temperature during heatwaves in Central European cities. The data consist of the boundary conditions and the simulation output of two simulation models: with and without facade greening. The geometry of the models corresponded to a residential buildings district in Stuttgart, Germany. The simulation output consisted of exterior air temperature, mean radiant temperature, relative humidity, and wind velocity at 12 different probe points in the model in addition to the indoor air temperature of an exemplary building. The dataset presents both vertical profiles of the probed parameters as well as the time series output of the five-day simulation duration. Both data subsets correspond to the investigations presented in the co-submitted article [1].
Design-related reassessment of structures integrating Bayesian updating of model safety factors
(2022)
In the semi-probabilistic approach of structural design, the partial safety factors are defined by considering some degree of uncertainties to actions and resistance, associated with the parameters’ stochastic nature. However, uncertainties for individual structures can be better examined by incorporating measurement data provided by sensors from an installed health monitoring scheme. In this context, the current study proposes an approach to revise the partial safety factor for existing structures on the action side, γE by integrating Bayesian model updating. A simple numerical example of a beam-like structure with artificially generated measurement data is used such that the influence of different sensor setups and data uncertainties on revising the safety factors can be investigated. It is revealed that the health monitoring system can reassess the current capacity reserve of the structure by updating the design safety factors, resulting in a better life cycle assessment of structures. The outcome is furthermore verified by analysing a real life small railway steel bridge ensuring the applicability of the proposed method to practical applications.
One of the most important renewable energy technologies used nowadays are wind power turbines. In this paper, we are interested in identifying the operating status of wind turbines, especially rotor blades, by means of multiphysical models. It is a state-of-the-art technology to test mechanical structures with ultrasonic-based methods. However, due to the density and the required high resolution, the testing is performed with high-frequency waves, which cannot penetrate the structure in depth. Therefore, there is a need to adopt techniques in the fields of multiphysical model-based inversion schemes or data-driven structural health monitoring. Before investing effort in the development of such approaches, further insights and approaches are necessary to make the techniques applicable to structures such as wind power plants (blades). Among the expected developments, further accelerations of the so-called “forward codes” for a more efficient implementation of the wave equation could be envisaged. Here, we employ electromagnetic waves for the early detection of cracks. Because in many practical situations, it is not possible to apply techniques from tomography (characterized by multiple sources and sensor pairs), we focus here on the question of whether the existence of cracks can be determined by using only one source for the sent waves.
The fracture of microcapsules is an important issue to release the healing agent for healing the cracks in encapsulation-based self-healing concrete. The capsular clustering generated from the concrete mixing process is considered one of the critical factors in the fracture mechanism. Since there is a lack of studies in the literature regarding this issue, the design of self-healing concrete cannot be made without an appropriate modelling strategy. In this paper, the effects of microcapsule size and clustering on the fractured microcapsules are studied computationally. A simple 2D computational modelling approach is developed based on the eXtended Finite Element Method (XFEM) and cohesive surface technique. The proposed model shows that the microcapsule size and clustering have significant roles in governing the load-carrying capacity and the crack propagation pattern and determines whether the microcapsule will be fractured or debonded from the concrete matrix. The higher the microcapsule circumferential contact length, the higher the load-carrying capacity. When it is lower than 25% of the microcapsule circumference, it will result in a greater possibility for the debonding of the microcapsule from the concrete. The greater the core/shell ratio (smaller shell thickness), the greater the likelihood of microcapsules being fractured.
Atlas der Datenkörper. Körperbilder in Kunst, Design und Wissenschaft im Zeitalter digitaler Medien
(2022)
Digitale Technologien und soziale Medien verändern die Selbst- und Körperwahrnehmung und verzerren, verstärken oder produzieren dabei spezifische Körperbilder. Die Beiträger*innen kartographieren diese Phänomene, fragen nach ihrer medialen Existenzweise sowie nach den Möglichkeiten ihrer Kritik. Dabei begegnen sie ihrer Neuartigkeit mit einer transdisziplinären Herangehensweise. Aus sowohl der Perspektive künstlerischer und gestalterischer Forschung als auch der Kunst-, Kultur- und Medienwissenschaft sowie der Psychologie und Neurowissenschaft wird die Landschaft rezenter Körperbilder und Techniken einer digitalen Körperlichkeit untersucht.