Open AccessAnalysis of the efficiency of obtaining reliable data when operating with number sets in simulation of bridges structural components
Author(s) -
Igor Maystrenko,
Tagir Zinnurov,
Dmitriy Erohin,
Tatiana Maystrenko
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/890/1/012030
Subject(s) - realization (probability) , reliability (semiconductor) , monte carlo method , stochastic simulation , computer science , sample size determination , random number generation , bridge (graph theory) , reliability engineering , sample (material) , algorithm , mathematical optimization , mathematics , engineering , statistics , power (physics) , medicine , physics , quantum mechanics , chemistry , chromatography
The issue of reducing the complexity of a multifactorial simulation experiment to an acceptable level is relevant. The simulation complexity is characterized by the computing capabilities of a PC while maintaining a given level of accuracy and certainty of the problem being solved. Many authors neglect the justification of the sample size, thereby reducing the experiment’s reliability. Loads are stochastic, therefore, in the calculations, they are determined by rated and design values. However, the Monte Carlo methods allow the specific realization of loads based on the distribution law chosen. Techniques for optimizing the multifactorial simulation experiment procedures have been proposed on a test example of adding permanent loads due to the bridge pavement layers. They allow excluding the procedure of building multidimensional laws of the final distribution of random parameters, while sequentially transforming them from input to output values. The minimum required simulation experiment size, which should exceed 7.5 10 6 realizations and is determined by the product of the number of tests N by the number of runs n , has been experimentally justified for the structural components of bridges.