Conditional Assessment of Uncertain Parameters Using Palm Probabilistic Approach and Kriging Interpolation

Author(s):  
Mohamed Anass El Yamani ◽  
Saiida Lazaar
2015 ◽  
Vol 32 (7) ◽  
pp. 2020-2045 ◽  
Author(s):  
Mohamed Amine Ben Souf ◽  
Mohamed Ichchou ◽  
Olivier Bareille ◽  
Noureddine Bouhaddi ◽  
Mohamed Haddar

Purpose – The purpose of this paper is to develop a new formulation using spectral approach, which can predict the wave behavior to uncertain parameters in mid and high frequencies. Design/methodology/approach – The work presented is based on a hybridization of a spectral method called the “wave finite element (WFE)” method and a non-intrusive probabilistic approach called the “polynomial chaos expansion (PCE).” The WFE formulation for coupled structures is detailed in this paper. The direct connection with the conventional finite element method allows to identify the diffusion relation for a straight waveguide containing a mechanical or geometric discontinuity. Knowing that the uncertainties play a fundamental role in mid and high frequencies, the PCE is applied to identify uncertainty propagation in periodic structures with periodic uncertain parameters. The approach proposed allows the evaluation of the dispersion of kinematic and energetic parameters. Findings – The authors have found that even though this approach was originally designed to deal with uncertainty propagation in structures it can be competitive with its low time consumption. The Latin Hypercube Sampling (LHS) is also employed to minimize CPU time. Originality/value – The approach proposed is quite new and very simple to apply to any periodic structures containing variabilities in its mechanical parameters. The Stochastic Wave Finite Element can predict the dynamic behavior from wave sensitivity of any uncertain media. The approach presented is validated for two different cases: coupled waveguides with and without section modes. The presented results are verified vs Monte Carlo simulations.


Author(s):  
Alice Cicirello ◽  
Robin S. Langley

The response of engineering structures is often sensitive to uncertainty in the system properties. The information on the uncertain parameters is frequently incomplete, limited to experts’ opinion, based on previous knowledge, or a combination of those. There have been recent advances in building mathematical models of structures, which combine nonparametric probabilistic and parametric (probabilistic or nonprobabilistic) models of uncertainty. Here, several strategies for establishing the response of random systems whose uncertainties are described by parametric probabilistic and nonprobabilistic approaches in combination with a nonparametric probabilistic approach are presented. The proposed strategies are illustrated by analyzing a built-up plate structure.


2018 ◽  
Vol 4 (1) ◽  
pp. 165
Author(s):  
Herry Prabowo ◽  
Mochamad Hilmy

The assessment of the service life of concrete structures using the durability design approach is widely accepted nowadays. It is really encouraged that a simulation model can resemble the real performance of concrete during the service life. This paper investigates the concrete carbonation through probabilistic analysis. Data regarding Indonesian construction practice were taken from Indonesian National Standard (SNI). Meanwhile, data related to Indonesian weather condition for instance humidity and temperature are taken from local Meteorological, Climatological, and Geophysical Agency from 2004 until 2016. Hopefully the results can be a starting point for durability of concrete research in Indonesia.


2020 ◽  
Vol 22 (4) ◽  
pp. 983-990
Author(s):  
Konrad Mnich

AbstractIn this work we analyze the behavior of a nonlinear dynamical system using a probabilistic approach. We focus on the coexistence of solutions and we check how the changes in the parameters of excitation influence the dynamics of the system. For the demonstration we use the Duffing oscillator with the tuned mass absorber. We mention the numerous attractors present in such a system and describe how they were found with the method based on the basin stability concept.


2017 ◽  
Vol 12 (30) ◽  
pp. 90-97
Author(s):  
Yu.G. Klykov ◽  
◽  
R.N. Maksimov ◽  
A.I. Rakaev ◽  
L.V. Soroker ◽  
...  

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