Ingenieuranalyse von Erdbebenschäden: Das Bingöl (Türkei)‐Erdbeben vom 1. Mai 2003

Engineering analysis of earthquake damage: The Bingöl (Türkiye) earthquake of May 1, 2003. Through the engineering analysis of structural damage caused by the magnitude 6.6 Bingöl (Türkiye) earthquake on May 1, 2003, an attempt is made to work out the damage‐promotive factors. The damage analyses, instrumental site investigations, and the reinterpretation of structural behaviour concentrate on reinforced‐concrete buildings which were documented on site. At this, standardized school buildings take center stage, showing different grades of damage (slight damage to total collapse) even though they are of comparable character. A scheme to evaluate the causes of structural damage will be introduced which accounts for ground motion intensity, resonance effects between site und structure, directional effects of the seismic wave propagation, as well as for features of design and construction. Besides to phenomena and typical damage pattern which had been already be observed after other worldwide earthquakes, factors will be emphasized (possibly) contributing to the amplification of seismic ground motion. This in particular concerns topographical peculiarities which even seem to be insufficiently considered by actual code provisions. Furthermore, a reinforced‐concrete frame structure, typical for the regarded region, will be subjected to the nonlinear static “pushover” analysis in order to check the plausibility between recorded ground motion of the damaging mainshock and observed structural performance, the latter to be represented by the actual state of damage pattern. A methodical procedure will be presented which can be applied to derive statements on the structural vulnerability by stiffness‐dependent capacity curves. This being mainly based on material parameters and reinforcement detailing to be documented on site.     

Probabilistische Modellierung hochfester Stahlbetonstützen in Hochhäusern

Probabilistic Modelling of HPC Slender Columns in High‐Rise Buildings In Germany high strength concrete is used successfully since 1990. The extremely high compressive strength of this material allows considerable reduction in cross‐sectional dimensions of reinforced concrete columns and accordingly accomplishes highest architectural and functional requirements. This leads in many cases to extremely slender structures and therefore increases the risk of failure due to loss of stability. Because of the positive experience with high strength concrete up to now, the current study questions the initial conservative design provisions. In this context code procedures of DIN 1055‐3 and DIN 1045‐1 are compared with the results of probabilistic analysis and potential optimization will be indicated.     

Achieving Water Quality System Reliability Using Genetic Algorithms

This paper presents an efficient approach for obtaining wasteload allocation solutions that provide the optimal trade-off between treatment cost and reliability. This approach links a genetic algorithm (GA) with the first-order reliability method (FORM) for estimating the probability of system failure under a given wasteload allocation. The GA-FORM optimization approach is demonstrated for the case study of managing water quality in the Willamette River in Oregon. The objective function minimizes the sum of the treatment cost and the penalty associated with breaching a reliability target for meeting a water quality standard. The random variables used to generate the reliability estimates include streamflow, temperature, and reaeration coefficient values. The results obtained indicate that the GA-FORM approach is nearly as accurate as the approach that links the GA with Monte Carlo simulation and is far more efficient. The trade-off between total treatment cost and reliability becomes more pronounced at higher water quality standards and is most sensitive to the uncertainty in the reaeration coefficient. The sensitivity to the reaeration coefficient also increases at increased reliability levels.     

Forecasting Cyanobacterial Concentrations Using B-Spline Networks

Artificial neural networks have been used successfully in a number of areas of civil engineering, including hydrology and water resources engineering. In the vast majority of cases, multilayer perceptrons that are trained with the back-propagation algorithm are used. One of the major shortcomings of this approach is that it is difficult to elicit the knowledge about the input/output mapping that is stored in the trained networks. One way to overcome this problem is to use B-spline associative memory networks (AMNs), because their connection weights may be interpreted as a set of fuzzy membership functions and hence the relationship between the model inputs and outputs may be written as a set of fuzzy rules. In this paper, multilayer perceptrons and AMN models are compared, and their main advantages and disadvantages are discussed. The performance of both model types is compared in terms of prediction accuracy and model transparency for a particular water quality case study, the forecasting (4 weeks in advance) of concentrations of the cyanobacterium Anabaena spp. in the River Murray at Morgan, South Australia. The forecasts obtained using both model types are good. Neither model clearly outperforms the other, although the forecasts obtained when the B-spline AMN model is used may be considered slightly better overall. In addition, the B-spline AMN model provides more explicit information about the relationship between the model inputs and outputs. The fuzzy rules extracted from the B-spline AMN model indicate that incidences of Anabaena spp. are likely to occur after the passing of a flood hydrograph and when water temperatures are high.     

Tribologische Sub‐Mikrometer Schichten für Mikrosysteme

With increasing interest in microelectromechanical systems (MEMS) a high demand on performance and lifetime arises. One option to improve this reliability is the optimization of friction and wear behaviour. Therefore we present a selection of well established systems that were scaled to serve as microtribological coatings. Hard and superhard coatings like DLC, CN_x, cBN and Alumina were investigated and optimized. For a better understanding of the tribological processes and the occuring effects in microsystems we used the macroscopic pin on disc test as well as nanoscale characterization like AFM based nanoindentation and a newly developed tape abrasive wear test.