Reliability-based design optimization of reinforced concrete structures with elastomeric isolators

Léger, Numa; Rizzian, Luca; Marchi, Mariapia

doi:10.1016/j.proeng.2017.09.216

Cited by 10 publications

(6 citation statements)

References 11 publications

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“…If, instead, the protection system is designed to fully engage under the lower level event, the bridge is susceptible to excessive defor-mation through the isolation system and, therefore, significant damage or even the possibility of collapse under a stronger earthquake. Ideally, a bridge protection system based on isolation and damping should have a positive impact on the seismic performance at the different hazard levels (Rizzian, Léger & Marchi, 2017). In a context of structure design based on the performance approach, multi-objective optimization allows to take into consideration the achievement of several objectives simultaneously (Dezfuli & Alam, 2013).…”

Section: Multi-objective Optimizationmentioning

confidence: 99%

Multi-objective optimization of elastomeric bearings to improve seismic performance of old bridges using eigen analysis and genetic algorithms

Abbadi

Lamdouar

2022

srees

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Old bridges present several seismic vulnerabilities and were designed before the emergence of seismic codes. In this context, partial seismic isolation has given a special attention to improve their seismic performance. In particular, elastomeric bearings are the simplest and least expensive mean for this, enabling to resist both non-seismic actions and earthquake loads. In order to assess the initial structural performance and the improvement done by the isolation, this paper attempts to combine multi objective optimization using genetic algorithms with linear and non-linear analysis using FE program OpenSees. A prior screening of the columns states is settled and then a multi objective optimization of a population of standard sized bearings meeting non-seismic and stability requirements is established to optimize the linear and non-linear behavior of the structure, finding the best compromise between displacements and forces at the columns

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Section: Multi-objective Optimizationmentioning

confidence: 99%

Multi-objective optimization of elastomeric bearings to improve seismic performance of old bridges using eigen analysis and genetic algorithms

Abbadi

Lamdouar

2022

srees

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“…Shayanfar et al [11] estimated the corrosion occurrence in RC structures using reliability based particle swarm optimization. Léger et al [12] performed an RBDO of RC structures with elastomeric isolators using adaptive sparse polynomial chaos expansion. Zou et al [13] formulated a reliability-based performance design optimization for seismic retrofit of RC buildings with fiber-reinforced polymer composites.…”

Section: Introductionmentioning

confidence: 99%

Reliability Based Design Optimization of Reinforced Concrete Frames Using Genetic Algorithm

Asghshahr

2021

Period. Polytech. Civil Eng.

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This paper introduces a new framework for reliability based design optimization (RBDO) of the reinforced concrete (RC) frames. This framework is constructed based on the genetic algorithm (GA) and finite element reliability analysis (FERA) to optimize the frame weight by selecting appropriate sections for structural elements under deterministic and probabilistic constraints. Modulus of elasticity of the concrete and steel bar, dead load, live load, and earthquake equivalent load are considered as random variables. Deterministic constraints include the code design requirements that must be satisfied for all the frame elements according to the nominal values of the aforementioned random variables. On the other hand, this framework provides the minimum required reliability index as the probabilistic constraint. The first-order reliability method (FORM) using the Newton-type recursive relationship will be used to compute the reliability index. The maximum inter-story drift is considered as an engineering demand parameter to define the limit-state function in FORM analysis. To implement the proposed framework, a mid-rise five-story RC frame is selected as an example. Based on the analysis results, increasing the minimum reliability index from 6 to 7 causes an 11 % increase in the weight of the selected RC frame as an objective function. So, we can obtain a trade-off between the optimized frame weight and the required reliability index utilizing the developed framework. Furthermore, the high values of the reliability index for the frame demonstrate the conservative nature of code requirements for interstory drift limitations based on the linear static analysis method.

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“…Popular surrogate models available in literature include polynomial chaos expansion [28,29], Kriging [30][31][32][33], analysis of variance decomposition [34][35][36][37], neural network [38,39] and support vector machine [40,41]. Use of surrogate models within the RBDO framework can be found in [5,6,[42][43][44].…”

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confidence: 99%

Threshold shift method for reliability-based design optimization

Goswami

Chakraborty

Chowdhury

et al. 2019

Struct Multidisc Optim

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We present a novel approach, referred to as the threshold shift method (TSM), for reliability based design optimization (RBDO). The proposed approach is similar in spirit with the sequential optimization and reliability analysis (SORA) method where the RBDO problem is decoupled into an optimization and a reliability analysis problem. However, unlike SORA that utilizes shift-vector to shift the design variables within a constraint (independently), in TSM we propose to shift the threshold of the constraints. We argue that modifying a constraint, either by shifting the design variables (SORA) or by shifting the threshold of the constraints (TSM), influences the other constraints of the system. Therefore, we propose to determine the thresholds for all the constraints by solving a single optimization problem. Additionally, the proposed TSM is equipped with an active-constraint determination scheme. To make the method scalable, a practical algorithm for TSM that utilizes two surrogate models is proposed. Unlike the conventional RBDO methods, the proposed approach has the ability to handle highly non-linear probabilistic constraints. The performance of the proposed approach is examined on six benchmark problems selected from the literature. The proposed approach yields excellent results outperforming other popular methods in literature. As for the computational efficiency, the proposed approach is found to be highly efficient, indicating it's future application to other real-life problems.Keywords RBDO · threshold shift method · PC-Kriging · uncertainty IntroductionUncertainty is an eternal companion of all structural systems. In a system, uncertainty can originate from both, uncertain parameters within the model as well as the limitations in the model itself. These uncertainties, if ignored, may result in to catastrophic failures. Therefore, it is necessary to consider the effect of uncertainty in an optimization process. In literature, there exist two methodologies to incorporate uncertainty into the framework of optimization, namely the robust design optimization (RDO) [1-3] and the reliability-based design optimization (RBDO) [4][5][6][7][8][9]. In this study, we focus on RBDO. * These authors have equal contributions

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Reliability-based design optimization of reinforced concrete structures with elastomeric isolators

Cited by 10 publications

References 11 publications

Multi-objective optimization of elastomeric bearings to improve seismic performance of old bridges using eigen analysis and genetic algorithms

Multi-objective optimization of elastomeric bearings to improve seismic performance of old bridges using eigen analysis and genetic algorithms

Reliability Based Design Optimization of Reinforced Concrete Frames Using Genetic Algorithm

Threshold shift method for reliability-based design optimization

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