Numerical analysis of the shear strength of circular reinforced concrete columns subjected to cyclic lateral loads using linear genetic programming. Issue 7 (16th March 2020)
- Record Type:
- Journal Article
- Title:
- Numerical analysis of the shear strength of circular reinforced concrete columns subjected to cyclic lateral loads using linear genetic programming. Issue 7 (16th March 2020)
- Main Title:
- Numerical analysis of the shear strength of circular reinforced concrete columns subjected to cyclic lateral loads using linear genetic programming
- Authors:
- Rezvani Sharif, Mostafa
Sadri Tabaei Zavareh, Seyed Mohammad Reza - Abstract:
- Abstract : 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 proposedAbstract : 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. … (more)
- Is Part Of:
- Engineering computations. Volume 37:Issue 7(2020)
- Journal:
- Engineering computations
- Issue:
- Volume 37:Issue 7(2020)
- Issue Display:
- Volume 37, Issue 7 (2020)
- Year:
- 2020
- Volume:
- 37
- Issue:
- 7
- Issue Sort Value:
- 2020-0037-0007-0000
- Page Start:
- 2517
- Page End:
- 2537
- Publication Date:
- 2020-03-16
- Subjects:
- Prediction -- Shear strength -- Circular reinforced concrete columns -- Cyclic lateral loads -- Linear genetic programming
Computer-aided engineering -- Periodicals
Computer graphics -- Periodicals
620.00285 - Journal URLs:
- http://info.emeraldinsight.com/products/journals/journals.htm?id=ec ↗
http://www.emeraldinsight.com/journals.htm?issn=0264-4401 ↗
http://www.emeraldinsight.com/0264-4401.htm ↗
http://www.emeraldinsight.com/ ↗
http://firstsearch.oclc.org ↗ - DOI:
- 10.1108/EC-10-2018-0453 ↗
- Languages:
- English
- ISSNs:
- 0264-4401
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3758.580800
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 22055.xml