Reliability Analysis of Reinforced Concrete Buildings: Comparison between FORM and ISM

Abdelouafi, El Ghoulbzouri; Kissi, Benaissa; Khamlichi, Abdellatif

doi:10.1016/j.proeng.2015.08.006

Cited by 15 publications

(12 citation statements)

References 22 publications

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“…During solving the objectives set in the research probabilistic-statistical methods were used [1,2,7,[18][19][20][21][22][23][24][25][26][27], methods of system and economic analysis [16], as well as experimental methods pertaining to testing of full-scale structures [8,14,15].…”

Section: Methodsmentioning

confidence: 99%

“…Serious attention has always been paid to the issue of operational integrity assessment of building structures and enhancement of their quality [1][2][3][4][5][6][7]. This objective is especially relevant during implementation of quality control of precast reinforced concrete (RC) structures [1,2,[8][9][10][11][12][13][14], which comprise the basis of modern construction in Russia due to complexity of climatic conditions.…”

Section: Introductionmentioning

confidence: 99%

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Cost efficiency assessment of automated quality control of precast structures

et al. 2018

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Abstract. Relevance of the research is conditioned by the necessity to enhance the factory quality control of reinforced concrete structures based on integral assessment of their reliability. The current system of selective quality control of precast concrete structures does not provide reliability assurance of the whole lot of products. The present research aims to develop operational procedure and consider economic feasibility of automated quality control of precast RC structures. Quality control is performed each shift according to the developed software system based on probabilistic methods considering statistic variability of the controlled parameters. The critical criterion of operational integrity of structures is integral assessment of the reliability indicators. The following theoretical research methods were used in the study: probabilistic-statistical, methods of system and economic analysis. Validity of the obtained results and economic feasibility were proved by experimental studies including fullscale tests.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cost efficiency assessment of automated quality control of precast structures

et al. 2018

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“…In practice, the estimated parameters Θ M may differ from the true value Θ. erefore, it is necessary to investigate the influences of these parameters on the optimal CSADDT plan. With this aim, we compare the different V-optimal two-stress CSADDT plans obtained under various combinations of these parameters, 3 , and ε 4 denote the estimation errors for μ α , σ 2 α , β, and σ 2 B . Ten different combinations of errors are studied according to the L 9 (3 4 ) orthogonal array (see the four first columns of Table 10).…”

Section: Sensitivity Analysismentioning

confidence: 99%

“…us, this may lead to using concrete with a composition that differs from that recommended in EN 206. is alternative is acceptable if the new concrete is at least as good as the concrete defined in the standard, under the specific exposure class for which we want to qualify the performance of the new concrete. is approach called "performance-based" [2], based on the demonstration of the performance's equivalency, has gained large success in many fields [3]. is demonstration can be made through three different ways: by using durability indicators, performance tests [4], or a proven physical model.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Accelerated Destructive Degradation Testing of Cementitious Materials for Their Performances Qualification under Aggressive Environments: The Case of Carbonation

Yan

Bigaud

Chaibati

et al. 2020

Mathematical Problems in Engineering

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In order to guarantee the performance or to qualify the risk of nonperformance of cementitious materials over time, a significant number of experimental data obtained from tests mimicking various degradation mechanisms are required. The slowness of the materials’ degradation under environmental service conditions is an issue, and thus, acceleration strategies are required to obtain reliable and comprehensive results in a shorter time. The objective of this research work is to provide a generic framework for the design of optimal accelerated destructive degradation tests (ADDTs) for cementitious materials qualification. The definition of the optimal design of experiments depends on the capacity to capture the influence of data variability and uncertainty from any sources; they are extracted either from physical models or from experimental tests. In this research, the evolution of carbonation depth is characterized with the Wiener process formalism and the random effects related to the material heterogeneity are taken into account. Once the process parameters are estimated through the maximum likelihood estimation (MLE), associated with the expectation-maximization (EM) algorithm, we provide a step-by-step and detailed method to investigate the optimal design of ADDTs. The latter is defined as the one for which we can estimate durability indicators such as mean-time-to-failure with the best accuracy based on three criteria (D-V-A optimality) considering constraints of time, total number of samples, or limited costs. The optimal total sample size for the accelerated carbonation test and the optimal sample size allocation proportions for each stress level are determined, and the effects of the stress level on the objective functions and of test time duration constraint are also discussed. A comparison of the relative efficiency of optimal three-level versus optimal two-level ADDT completes this work.

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“…In FORM for structural reliability analysis, by the firstorder Taylor series, the limit-state function is approximated at the design point in the standard Gauss space of transformed independent random variables [9,10]. In this space, reliability analysis is usually converted into an optimization problem to solve the reliability index [8].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Reliability Analysis for Spacecraft Docking Lock with Random and Interval Uncertainty

Zhang

Qiu

Wang

2017

International Journal of Aerospace Engineering

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This paper presents a novel procedure based on first-order reliability method (FORM) for structural reliability analysis with hybrid variables, that is, random and interval variables. This method can significantly improve the computational efficiency for the abovementioned hybrid reliability analysis (HRA), while generally providing sufficient precision. In the proposed procedure, the hybrid problem is reduced to standard reliability problem with the polar coordinates, where an n-dimensional limit-state function is defined only in terms of two random variables. Firstly, the linear Taylor series is used to approximate the limit-state function around the design point. Subsequently, with the approximation of the n-dimensional limit-state function, the new bidimensional limit state is established by the polar coordinate transformation. And the probability density functions (PDFs) of the two variables can be obtained by the PDFs of random variables and bounds of interval variables. Then, the interval of failure probability is efficiently calculated by the integral method. At last, one simple problem with explicit expressions and one engineering application of spacecraft docking lock are employed to demonstrate the effectiveness of the proposed methods.

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Reliability Analysis of Reinforced Concrete Buildings: Comparison between FORM and ISM

Cited by 15 publications

References 22 publications

Cost efficiency assessment of automated quality control of precast structures

Cost efficiency assessment of automated quality control of precast structures

Optimization of Accelerated Destructive Degradation Testing of Cementitious Materials for Their Performances Qualification under Aggressive Environments: The Case of Carbonation

Hybrid Reliability Analysis for Spacecraft Docking Lock with Random and Interval Uncertainty

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