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One of the most important parameters in a burning chamber - in power stations, in waste to energy plants - is the temperature. This temperature is in the range of 700-1500 °C - one of the most advanced measuring methods being the acoustic pyrometry with the possibility of producing temperature mapping in one level of the burning chamber - comparable to computer tomography. The results of these measurements discussed in the presentation can be used - to fulfil the legal requirements in the FRG or in the EU - to equalise the temperature in one level of the burning chamber to optimise the steam production (better efficiency of the plant) and to minimise the production of temperature controlled flue gas components (NO, CO a. o.) - to control the SNCR-process if used.
The Solar-Institute Jülich (SIJ) has initiated the construction of the first and only German solar tower power plant and is now involved in the accompanying research. The power plant for experimental and demonstration purposes in the town of Jülich started supplying electric energy in the beginning of 2008. The central receiver plant features as central innovation an open volumetric receiver, consisting of porous ceramic elements that simultaneously absorb the concentrated sunlight and transfer the heat to ambient air passing through the pores so that an average temperature of 680°C is reached. The subsequent steam cycle generates up to 1.5 MWe. A main field of research at the SIJ is the optimization of the absorber structures. To analyze the capability of new absorber specimens a special test facility was developed and set up in the laboratory. A high-performance near-infrared radiator offers for single test samples a variable and repeatable beam with a power of up to 320 kW/m² peak. The temperatures achieved on the absorber surface can reach more than 1000°C. To suck ambient air through the open absorber - like on the tower - it is mounted on a special blower system. An overview about the test facility and some recent results will be presented.
Textile reinforced concrete. Part I: Process model for collaborative research and development
(2003)
The adsorption of fluor-carbon complexes on GaAs(110) studied by electron energy loss spectroscopy
(1986)
With proven impact of statistical fracture analysis on fracture classifications, it is desirable to minimize the manual work and to maximize repeatability of this approach. We address this with an algorithm that reduces the manual effort to segmentation, fragment identification and reduction. The fracture edge detection and heat map generation are performed automatically. With the same input, the algorithm always delivers the same output. The tool transforms one intact template consecutively onto each fractured specimen by linear least square optimization, detects the fragment edges in the template and then superimposes them to generate a fracture probability heat map.
We hypothesized that the algorithm runs faster than the manual evaluation and with low (< 5 mm) deviation. We tested the hypothesis in 10 fractured proximal humeri and found that it performs with good accuracy (2.5 mm ± 2.4 mm averaged Euclidean distance) and speed (23 times faster). When applied to a distal humerus, a tibia plateau, and a scaphoid fracture, the run times were low (1–2 min), and the detected edges correct by visual judgement. In the geometrically complex acetabulum, at a run time of 78 min some outliers were considered acceptable. An automatically generated fracture probability heat map based on 50 proximal humerus fractures matches the areas of high risk of fracture reported in medical literature.
Such automation of the fracture analysis method is advantageous and could be extended to reduce the manual effort even further.