Abstract
Applicability of the Probability Density Evolution Method (PDEM) for realizing evolution of the probability density for the wind turbines has rather strict bounds on the basic number of the random variables involved in the model. The efficiency of most of the Advanced Monte Carlo (AMC) methods, i.e. Importance Sampling (IS) or Subset Simulation (SS), will be deteriorated on problems with many random variables. The problem with PDEM is that a multidimensional integral has to be carried out over the space defined by the random variables of the system. The numerical procedure requires discretization of the integral domain; this becomes increasingly difficult as the dimensions of the integral domain increase. On the other hand efficiency of the AMC methods is closely dependent on the design points of the problem. Presence of many random variables may increase the number of the design points, hence affects the efficiency of the AMC methods. The idea of the paper is to propose new schemes which allow reduction of the basic random variables of the turbulence such that PDEM and Advanced Monte Carlo (AMC) methods, i.e. subset simulation, are applicable on it.
Original language | English |
---|---|
Title of host publication | Reliability and Optimization of Structural Systems : Proceedings of the 16th working conference on the international federation of information processing (IFIP) working group 7.5 on reliability and optimization of structural systems |
Editors | A. Der Kiureghian, A. Hajian |
Number of pages | 8 |
Publisher | American University of Armenia Press, Yrevan, Armenia |
Publication date | 2012 |
Pages | 151-158 |
ISBN (Print) | 978-0-9657429-0-0 |
Publication status | Published - 2012 |
Event | Reliability and Optimization of Structural System: IFIP WG 7.5 working group conference - Yerevan, Armenia Duration: 24 Jun 2012 → 27 Jun 2012 Conference number: 16 |
Conference
Conference | Reliability and Optimization of Structural System |
---|---|
Number | 16 |
Country/Territory | Armenia |
City | Yerevan |
Period | 24/06/2012 → 27/06/2012 |
Keywords
- Reduction
- Random Variables
- Wind Field
- Probability Density Evolution Method (PDEM)