Adaptive response surface by kriging using pilot points for structural reliability analysis

Bennacer

Abdelrahmane

2021

AEF

The current study presents vulnerability and a reliability-mechanical approach which focuses on evaluating the seismic performance of reinforced concrete structures to determine the probability of failure. In this case, the performance function reflecting the non-linear behavior of the structure is modeled by a response surface to establish an analytical relationship between the random variables (strength of concrete and yield strength of steel) and mechanical responses of the structure (inter-floor displacement) obtained by the pushover results of finite element simulations. The push over analysis is executed by software SAP2000. The results acquired prove that properly designed frames will perform well under seismic loads. It is a comparative study of the behavior of the existing structure before and after reinforcement using the pushover method. The coupling indirect mechanical reliability by response surface avoids prohibitive calculation times. Finally, results of the proposed approach are compared with Monte Carlo Simulation. The comparative study shows that the structure is more reliable after the introduction of new shear walls.

Section: The Performance Functionmentioning

confidence: 99%

Vulnerability and Reliability Analysis of Existing Reinforced Concrete Buildings: Case Study

Bennacer

Abdelrahmane

2021

AEF

“…To do this, probabilistic mechanics has developed an arsenal of methods. Kernou et al [29][30][31] developed a New Approach in Reliability Analysis for, Excellent Predictive Quality of the Approximation Using Adaptive Kriging using pilot points for structural reliability analysis. Therefore, the coupling between probabilistic methods and finite element methods is a necessity.…”

Section: Introductionmentioning

confidence: 99%

Reliability Analysis and Comparative Study of Ordinary Concrete and High Performance Concrete Filled with Steel Tube under Axial Compression

Lydia

2022

JERA

Self Cite

Reliability and behaviour of composite columns is influenced by many factors. This paper presents a comparative study of the reliability and performance of square composite columns under axial compression, taking into account mechanical and geometric variability. The choice is opted for metal hollow profiles filled with ordinary concrete and high-performance concrete. In this study, a mechanic-reliability model to calculate the reliability index and the probability of failure of different columns is presented. The response surface method is used to accomplish this coupling in order to describe the uncertainties in a suitable model and to study their influence for a reliability assessment. The results show that the material and geometric characteristics of the columns have a significant influence on strength and reliability. The sensitivity of the random parameters of structural reliability is assessed from the proposed method.

“…Several authors have used this indicator to propose various refinement techniques based on the identification of the set of points that should be added to the design of experiments (DOE) of the kriging model in order to improve the prediction of the approximation. Li Yaohui and kernou [28][29] have introduced an efficient approach concerning the design of experiments for the kriging method to find the global optimum. In this field of global optimization, the best approximation of the objective function is the key to the success of the optimization procedure, where the region of interest is in the vicinity of the optimum outcome, and the approximation is improved by applying a sampling new points and credible termination rule.…”

Section: Introductionmentioning

confidence: 99%

Development of New Approach in Reliability Analysis for Excellent Predictive Quality of the Approximation Using Adaptive Kriging

Bouafia

2019

JERA

This study presents the results of a new approach for structural reliability analyses using adaptive kriging, confirmation simulation, and the pilot point method. Its main objective is to develop an efficient and accurate global approximation while controlling the computational cost and accuracy of prediction. The main contribution of research is to reduce computation time and successfully analyze complex problems with accurate results while ensuring excellent predictive quality of the approximation. For an excellent predictability of the kriging approximation, pilot point method and confirmation simulation are proposed. Simply, the predictive quality of the initial kriging approximation is improved by adding adaptive information, and the points are referred to as “pilot points” in areas where the kriging variance is maximized. Outcomes are confirmed with numerical simulations. The purpose is to select the minimum number of design experiments to ensure a good relative accuracy of the predictors with respect to the original models. Numerical examples show the efficiency of the proposed method compared to other structural reliability approaches.