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EN
The ever-increasing demand for electricity and the need for conventional sources to cooperate with renewable ones generates the need to increase the efficiency and safety of the generation sources. Therefore, it is necessary to find a way to operate existing facilities more efficiently with full detection of emerging faults. These are the requirements of Polish, European and International law, which demands that energy facilities operate with the highest efficiency and meet a number of restrictive requirements. In order to improve the operation of steam power plants of electric generating stations, thermal-fluid diagnostics have been traditionally used, and in this paper a three-hull steam turbine, having a high-pressure, a medium-pressure and a low-pressure part, has been selected for analysis. The turbine class is of the order of 200 MW electric. Genetic algorithms (GA) were used in the process of creating the diagnostic model. So far, they have been used for diagnostic purposes in gas turbines, and no work has been found in the literature using GA for the diagnostic process of such complex objects as steam turbines located in professional manufacturing facilities. The use of genetic algorithms allowed rapid acquisition of global extremes, that is efficiency and power of the unit. The result of the work undertaken is the possibility to carry out a full diagnostic process, meaning detection, localization and identification of single and double degradations. In this way 100 % of the main faults are found, but there are sometimes additional ones, and these are not perfectly identified especially for single time detection. Thus, the results showed that with a very high success rate the simulated damage to the geometrical elements of the steam turbine under study is found.
PL
W pracy przedstawiono problem doboru minimalnej masy startowej rakiety trójstopniowej. Do optymalizacji masy rakiety wykorzystano algorytm genetyczny.
EN
This paper presents optimisation of three-stage rocket lift-off mass by use of genetic algorithm.
EN
Aftershocks which followed the 1995 Egion earthquake of magnitude ML=6.2 were used to detrminea preliminary P-wave velocity structure of the upper crust in a region of the western part of the Gulf of Corinth, western Greece. 680 selected P-wave arrival times from 108 aftershocks recorded by the seismic network PATENT of the University of Patras and the temporary EGION network were inverted for the P-wave velocity distribution with respect to two classes of models: horizontal homogenous layers and a single laterly heterogeneous half a space. Travel time data were inverted both in a standard way using the damped least-square approach and using Cauchyrobust norm and genetic algorithm optimization method in the framework of the Bayesian inversion scheme. Although the main features of P-wave distribution obtained by both approaches are similar, the differences were found to be up to a few percents even in a well resolved area. Generally, the models obtained by genetic algorithm provide smaller residua then those calculated by means of the damped least-squares. It has also been found that the main shock of 15 June and most of considered aftershocks occurred in the region of an increased velocity (about 0.4km/s) as compared to the average velocity of an adjacent area.
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