Computer Analysis of Dynamic Reliability of Some Concrete Beam Structure Exhibiting Random Damping

Abstract

An efficiency of the generalized tenth order stochastic perturbation technique in determination of the basic probabilistic characteristics of up to the fourth order of dynamic response of Euler-Bernoulli beams with Gaussian uncertain damping is verified in this work. This is done on civil engineering application of a two-bay reinforced concrete beam using the Stochastic Finite Element Method implementation and its contrast with traditional Monte-Carlo simulation based Finite Element Method study and also with the semi-analytical probabilistic approach. The special purpose numerical implementation of the entire Stochastic perturbation-based Finite Element Method has been entirely programmed in computer algebra system MAPLE 2019 using Runge-Kutta-Fehlberg method. Further usage of the proposed technique to analyze stochastic reliability of the given structure subjected to dynamic oscillatory excitation is also included and discussed here because of a complete lack of the additional detailed demands in the current European designing codes.

Structural Reliability Estimation of Steel Mast Exhibiting Random Mechanical and Environmental Parameters

“…Probabilistic analysis has been performed with the Stochastic Perturbation Technique (SPT), and independently using Monte-Carlo simulations (MCS) and semi-analytical method (SAM) also [7], [8]. The results obtained by SPT are marked with asterisk, these coming from the MCS -with a cross, while these obtained by SAM -with a diagonal box.…”

Performance Assessment of an Energy–Based Approximation Method for the Dynamic Capacity of RC Frames Subjected to Sudden Column Removal Scenarios

“…When designing a structure with respect to robustness, it must also be taken into consideration that progressive collapses caused by extreme events are low-probability high-consequence phenomena [1]. In order to be able to accurately predict the structural response, it is important to study the progressive collapse behavior using a probabilistic approach, as it has been found that there is a significant influence of many uncertainties on the structural behavior, e.g., randomness from material properties, which is neglected by most existing studies [30][31][32][33][34][35][36][37][38][39][40][41][42]. However, in the three widely used approaches in relation to the quantification of the structural robustness, i.e., deterministic-based method, probabilisticbased method, and risk-based method [30,43,44], both the probabilistic-based method and the risk-based method require a reliability analysis.…”

“…However, in the three widely used approaches in relation to the quantification of the structural robustness, i.e., deterministic-based method, probabilisticbased method, and risk-based method [30,43,44], both the probabilistic-based method and the risk-based method require a reliability analysis. Several approaches can be adopted in a probabilistic analysis in combination with the finite element method [35,41,42,45], such as the Monte Carlo simulation [42] and the Latin Hypercube sampling technique [45]. Moreover, considering that the EBM is an approximate approach, the quantitative assessment of the model uncertainty associated to the EBM becomes important when the EBM is applied to quantify the reliability or robustness of a RC building structure following a sudden column removal scenario.…”