Refine
Document Type
- Article (1015) (remove)
Institute
- Professur Theorie und Geschichte der modernen Architektur (393)
- Institut für Strukturmechanik (ISM) (254)
- Professur Informatik im Bauwesen (130)
- Professur Stochastik und Optimierung (40)
- Professur Bauphysik (23)
- In Zusammenarbeit mit der Bauhaus-Universität Weimar (21)
- Professur Informatik in der Architektur (15)
- Junior-Professur Computational Architecture (12)
- Institut für Europäische Urbanistik (11)
- Professur Bauchemie und Polymere Werkstoffe (11)
Keywords
- Bauhaus-Kolloquium (395)
- Weimar (395)
- Angewandte Mathematik (186)
- Strukturmechanik (185)
- Architektur (168)
- 1986 (63)
- 1989 (60)
- Design (59)
- Bauhaus (55)
- Raum (55)
Rice husk ash (RHA) is classified as a highly reactive pozzolan. It has a very high silica content similar to that of silica fume (SF). Using less-expensive and locally available RHA as a mineral admixture in concrete brings ample benefits to the costs, the technical properties of concrete as well as to the environment. An experimental study of the effect of RHA blending on workability, strength and durability of high performance fine-grained concrete (HPFGC) is presented. The results show that the addition of RHA to HPFGC improved significantly compressive strength, splitting tensile strength and chloride penetration resistance. Interestingly, the ratio of compressive strength to splitting tensile strength of HPFGC was lower than that of ordinary concrete, especially for the concrete made with 20 % RHA. Compressive strength and splitting tensile strength of HPFGC containing RHA was similar and slightly higher, respectively, than for HPFGC containing SF. Chloride penetration resistance of HPFGC containing 10–15 % RHA was comparable with that of HPFGC containing 10 % SF.
Flow velocity is generally presumed to influence flood damage. However, this influence is hardly quantified and virtually no damage models take it into account. Therefore, the influences of flow velocity, water depth and combinations of these two impact parameters on various types of flood damage were investigated in five communities affected by the Elbe catchment flood in Germany in 2002. 2-D hydraulic models with high to medium spatial resolutions were used to calculate the impact parameters at the sites in which damage occurred. A significant influence of flow velocity on structural damage, particularly on roads, could be shown in contrast to a minor influence on monetary losses and business interruption. Forecasts of structural damage to road infrastructure should be based on flow velocity alone. The energy head is suggested as a suitable flood impact parameter for reliable forecasting of structural damage to residential buildings above a critical impact level of 2m of energy head or water depth. However, general consideration of flow velocity in flood damage modelling, particularly for estimating monetary loss, cannot be recommended.
We present StarWatch, our application for real-time analysis of radio astronomical data in Virtual Environment. Serving as an interface to radio astronomical databases or being applied to live data from the radio telescopes, the application supports various data filters measuring signal-to-noise ratio (SNR), Doppler's drift, degree of signal localization on celestial sphere and other useful tools for signal extraction and classification. Originally designed for the database of narrow band signals from SETI Institute (setilive.org), the application has been recently extended for the detection of wide band periodic signals, necessary for the search of pulsars. We will also address the detection of week signals possessing arbitrary waveforms and present several data filters suitable for this purpose.
Traditionally, buildings in the Inner Himalayan valleys of Bhutan were constructed from rammed earth in the western regions and quarry stone in the central and eastern regions. Whilst basic architectural design elements have been retained, the construction methods have however changed over recent decades alongside expectations for indoor thermal comfort. Nevertheless, despite the need for space heating, thermal building performance remains largely unknown. Furthermore, no dedicated climate data is available for building performance assessments. This paper establishes such climatological information for the capital Thimphu and presents an investigation of building physics properties of traditional and contemporary building types. In a one month field study 10 buildings were surveyed, looking at building air tightness, indoor climate, wall U-values and water absorption of typical wall construction materials. The findings highlight comparably high wall U-values of 1.0 to 1.5 W/m²K for both current and historic constructions. Furthermore, air tightness tests show that, due to poorly sealed joints between construction elements, windows and doors, many buildings have high infiltration rates, reaching up to 5 air changes per hour. However, the results also indicate an indoor climate moderating effect of more traditional earth construction techniques. Based on these survey findings basic improvements are being suggested.
We investigate the thermal conductivity in the armchair and zigzag MoS2 nanoribbons, by combining the non-equilibrium Green's function approach and the first-principles method. A strong orientation dependence is observed in the thermal conductivity. Particularly, the thermal conductivity for the armchair MoS2 nanoribbon is about 673.6 Wm−1 K−1 in the armchair nanoribbon, and 841.1 Wm−1 K−1 in the zigzag nanoribbon at room temperature. By calculating the Caroli transmission, we disclose the underlying mechanism for this strong orientation dependence to be the fewer phonon transport channels in the armchair MoS2 nanoribbon in the frequency range of [150, 200] cm−1. Through the scaling of the phonon dispersion, we further illustrate that the thermal conductivity calculated for the MoS2 nanoribbon is esentially in consistent with the superior thermal conductivity found for graphene.
In this study, an application of evolutionary multi-objective optimization algorithms on the optimization of sandwich structures is presented. The solution strategy is known as Elitist Non-Dominated Sorting Evolution Strategy (ENSES) wherein Evolution Strategies (ES) as Evolutionary Algorithm (EA) in the elitist Non-dominated Sorting Genetic algorithm (NSGA-II) procedure. Evolutionary algorithm seems a compatible approach to resolve multi-objective optimization problems because it is inspired by natural evolution, which closely linked to Artificial Intelligence (AI) techniques and elitism has shown an important factor for improving evolutionary multi-objective search. In order to evaluate the notion of performance by ENSES, the well-known study case of sandwich structures are reconsidered. For Case 1, the goals of the multi-objective optimization are minimization of the deflection and the weight of the sandwich structures. The length, the core and skin thicknesses are the design variables of Case 1. For Case 2, the objective functions are the fabrication cost, the beam weight and the end deflection of the sandwich structures. There are four design variables i.e., the weld height, the weld length, the beam depth and the beam width in Case 2. Numerical results are presented in terms of Paretooptimal solutions for both evaluated cases.
Processes underlying crowding in visual letter recognition were examined by investigating effects of training. Experiment 1 revealed that training reduces crowding mainly for trained strings. This was corroborated in Experiment 2, where no training effects were obvious after 3 days of training when strings changed from trial to trial. Experiment 3 specified that after a short amount of training, learning effects remained specific to trained strings and also to the trained retinal eccentricity and the interletter spacing used in training. Transfer to other than trained conditions was observed only after further training. Experiment 4 showed that transfer occurred earlier when words were used as stimuli. These results thus demonstrate that part of crowding results from the absence of higher level representations of the stimulus. Such representations can be acquired through learning visual properties of the stimulus.
The laser beam is a small, flexible and fast polishing tool. With laser radiation it is possible to finish many outlines or geometries on quartz glass surfaces in the shortest possible time. It’s a fact that the temperature developing while polishing determines the reachable surface smoothing and, as a negative result, causes material tensions. To find out which parameters are important for the laser polishing process and the surface roughness respectively and to estimate material tensions, temperature simulations and extensive polishing experiments took place. During these experiments starting and machining parameters were changed and temperatures were measured contact-free. The accuracy of thermal and mechanical simulation was improved in the case of advanced FE-analysis.
The laser beam is a small, flexible and fast polishing tool. With laser radiation it is possible to finish many outlines or geometries on quartz glass surfaces in the shortest possible time. It's a fact that the temperature developing while polishing determines the reachable surface smoothing and, as a negative result, causes material tensions. To find out which parameters are important for the laser polishing process and the surface roughness respectively and to estimate material tensions, temperature simulations and extensive polishing experiments took place. During these experiments starting and machining parameters were changed and temperatures were measured contact-free.
Cyber security has become a major concern for users and businesses alike. Cyberstalking and harassment have been identified as a growing anti-social problem. Besides detecting cyberstalking and harassment, there is the need to gather digital evidence, often by the victim. To this end, we provide an overview of and discuss relevant technological means, in particular coming from text analytics as well as machine learning, that are capable to address the above challenges. We present a framework for the detection of text-based cyberstalking and the role and challenges of some core techniques such as author identification, text classification and personalisation. We then discuss PAN, a network and evaluation initiative that focusses on digital text forensics, in particular author identification.