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EN
In the optimization of technical systems focused on a specific functional purpose (reliability, safety, and availability) with the use of simulation methods, an important parameter is the digital simulation time of the research subject. With the complexity of the issue, the digital simulation time increases. The aim of the article is to present a method (combination of parallel computing and variance reduction techniques) of reducing the computer simulation time of the research technical object. An example of the application of the developed method was presented as a result of an experiment conducted for decision making and control processes aimed at optimizing the process of operating overhead cranes in critical conditions. In this paper, selecting parallel batch jobs computation and stratified sampling, we exponentially decreased the simulation time, finding fast and practical solutions and eliminating the time constraint in the search of solutions.
EN
Effects of spatial fluctuations of soil parameters are considered in a new context – considering variability of soil parameters in conjunction with non-uniform stress fields, which can locally amplify (or suppress) subsoil inhomogeneities. In this way, several design situations for the Coulomb frictional material with random tan(φ(x)) reveal a reduction of variance, which is less significant than for the standard volume averaging. When looking for an 'effective' random variable [tan(φ)]a – that is, a random variable, which is equivalent to the random field tan(φ(x)) – the Vanmarcke averaging by simple volume integrals is insufficient; it systematically overestimates effects of variance reduction, thus causing potentially unsafe situations. The new proposed approach is coherent, formally defined and more realistic.
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