New empirical formulations for indirect estimation of peak-confined compressive strength and strain of circular RC columns using LGP method

Rostami, Mohamad Fazel; Sadrossadat, Ehsan; Ghorbani, Behnam; Kazemi, Seyed Morteza

doi:10.1007/s00366-018-0577-7

Cited by 14 publications

(10 citation statements)

References 26 publications

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“…An analytical based formula has also been optimized and its constant values are modified; therefore, a new model has been produced. Although the application of ANNs was successful in determining the shear strength factor, the generated ANN-based models are black-box and this is their great defect criticized by researchers (Rostami et al, 2018;Sadrossadat et al, 2013).…”

Section: Ec 377mentioning

confidence: 99%

“…LGP, gene expression programming, multi-expression programming and Cartesian GP (Brameier and Banzhaf, 2001;Oltean and Grosan, 2003;Brameier and Banzhaf, 2007;Ghorbani et al, 2018). Amongst all, LGP can be considered as the most common linear-based GP method used in data-mining and solving engineering approximation problems (Rostami et al, 2018).…”

Section: Linear Genetic Programmingmentioning

confidence: 99%

“…To tackle this, Numerical analysis of the shear strength 2517 experimental explorations represent the fact that strengthening RC columns with an appropriate amount of transverse reinforcement such as steel hoops or spirals will perfectly increase their shear strength, owing to the higher tensile strength of steel bars (Mander et al, 1988;Sadrossadat et al, 2018a). Transverse reinforcement enhances the shear strength of RC columns through confining the concrete core and longitudinal reinforcement and also by individually resisting under applied shear forces (Sadrossadat et al, 2018a;Rostami et al, 2018). There are several parameters influencing the shear strength of RC columns, e.g.…”

Section: Introductionmentioning

confidence: 99%

“…These methods apply assumptions to simplify the problem. However, the development of an accurate theory or assumption to fully describe the system behavior and its characteristics might be too difficult, complicated or impossible because of the lack of sufficient information and evidence about the problem (Rostami et al, 2018). The empirical and semi-empirical based models are mainly produced based on observed or experimental data.…”

Section: Introductionmentioning

confidence: 99%

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Numerical analysis of the shear strength of circular reinforced concrete columns subjected to cyclic lateral loads using linear genetic programming

Sharif

Zavareh

2020

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Purpose The shear strength of reinforced concrete (RC) columns under cyclic lateral loading is a crucial concern, particularly, in the seismic design of RC structures. Considering the costly procedure of testing methods for measuring the real value of the shear strength factor and the existence of several parameters impacting the system behavior, numerical modeling techniques have been very much appreciated by engineers and researchers. This study aims to propose a new model for estimation of the shear strength of cyclically loaded circular RC columns through a robust computational intelligence approach, namely, linear genetic programming (LGP). Design/methodology/approach LGP is a data-driven self-adaptive algorithm recently used for classification, pattern recognition and numerical modeling of engineering problems. A reliable database consisting of 64 experimental data is collected for the development of shear strength LGP models here. The obtained models are evaluated from both engineering and accuracy perspectives by means of several indicators and supplementary studies and the optimal model is presented for further purposes. Additionally, the capability of LGP is examined to be used as an alternative approach for the numerical analysis of engineering problems. Findings A new predictive model is proposed for the estimation of the shear strength of cyclically loaded circular RC columns using the LGP approach. To demonstrate the capability of the proposed model, the analysis results are compared to those obtained by some well-known models recommended in the existing literature. The results confirm the potential of the LGP approach for numerical analysis of engineering problems in addition to the fact that the obtained LGP model outperforms existing models in estimation and predictability. Originality/value This paper mainly represents the capability of the LGP approach as a robust alternative approach among existing analytical and numerical methods for modeling and analysis of relevant engineering approximation and estimation problems. The authors are confident that the shear strength model proposed can be used for design and pre-design aims. The authors also declare that they have no conflict of interest.

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Section: Ec 377mentioning

confidence: 99%

Section: Linear Genetic Programmingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Numerical analysis of the shear strength of circular reinforced concrete columns subjected to cyclic lateral loads using linear genetic programming

Sharif

Zavareh

2020

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“…The program can represent an empirical model to be used for approximation of a response function, and the explicit expression [25], or even algorithms [26], can be entirely attained for optimization. With the high accuracy, approximation models generated by GP have already been used for solving various design optimization problems [18,21,[27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Metaheuristic Approaches to Solve a Complex Aircraft Performance Optimization Problem

2019

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The increasing demands for travelling comfort and reduction of carbon dioxide emissions have been considered substantially in the stage of conceptual aircraft design. However, the design of a modern aircraft is a multidisciplinary process, which requires the coordination of information from several specific disciplines, such as structures, aerodynamics, control, etc. To address this problem with adequate accuracy, the multidisciplinary analysis and optimization (MAO) method is usually applied as a systematic and robust approach to solve such complex design issues arising from industries. Since MAO method is tedious and computationally expensive, genetic programming (GP)-based metamodeling techniques incorporating MAO are proposed as an effective approach to minimize the wing stiffness of a large aircraft subject to aerodynamic, aeroelastic and stability constraints in the conceptual design phase. Based on the linear small-disturbance theory, the state-space equation is employed for stability analysis. In the process of multidisciplinary analysis, aeroelastic response simulations are performed using Nastran. To construct metamodels representing the responses of the interests with high accuracy as well as less computational burden, optimal Latin hypercube design of experiments (DoE) is applied to determine the optimized distribution of sampling points. Following that, parametric optimization is carried out on metamodels to obtain the optimal wing geometry shape, elastic axis positions and stiffness distribution, and then the solution is verified by finite element simulations. Finally, the superiority of the GP-based metamodel technique over genetic algorithm is demonstrated by multidisciplinary design optimization of a representative beam-frame wing structure in terms of accuracy and efficiency. The results also show that GP metamodel-based strategy for solving MAO problems can provide valuable insights to tailoring parameters for the effective design of a large aircraft in the conceptual phase.

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Predictive modeling of the lateral drift capacity of circular reinforced concrete columns using an evolutionary algorithm

Sharif

Zavareh

2019

Engineering with Computers

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New empirical formulations for indirect estimation of peak-confined compressive strength and strain of circular RC columns using LGP method

Cited by 14 publications

References 26 publications

Numerical analysis of the shear strength of circular reinforced concrete columns subjected to cyclic lateral loads using linear genetic programming

Numerical analysis of the shear strength of circular reinforced concrete columns subjected to cyclic lateral loads using linear genetic programming

Metaheuristic Approaches to Solve a Complex Aircraft Performance Optimization Problem

Predictive modeling of the lateral drift capacity of circular reinforced concrete columns using an evolutionary algorithm

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