Shear Failure Capacity Prediction of Concrete Beam–Column Joints in Terms of ANFIS and GMDH

Naderpour, Hosein; Mirrashid, Masoomeh

doi:10.1061/(asce)sc.1943-5576.0000417

Cited by 48 publications

(14 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…e use of only one damage index such as interstory drift could be unrealistic considering that there are several parameters such as forces and responses in elements, which results in damage to the structure simultaneity. Naderpour and Mirrashid [9] investigated maximum shear capacity for reinforced concrete (RC) beam-column joints by using group method of data handling (GMDH) and adaptive neurofuzzy inference system (ANFIS). During earthquake, insufficient separation gap between adjacent buildings may cause serious damages.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Multidimensional Fragility Analysis for a NEES Frame Structure by Integrating a New Energy Damage Index: Cumulative Plastic Strain

Wang

2019

Advances in Civil Engineering

View full text Add to dashboard Cite

Cumulative plastic strain (CPS) damage index is proposed in this study for seismic fragility analysis by integrating the force analogy method into the energy balance equation, and CPS can be defined as the ratio of the demand of plastic dissipation energy to its capacity. The cumulative plastic strain can indicate the structural damage cumulative effect under earthquakes, which makes it especially suitable to be selected as the damage index for the structural component. Threshold values of cumulative plastic strain for different performance limit state (PLS) levels are obtained through the degree of consistency of interstory drift-based fragility curves and CPS-based fragility curves. Regarding the multidimensional fragility evaluation, CPS and the floor acceleration will be selected as the quantification indices for performance limit state of the structural component and nonstructural component, respectively. The probabilistic seismic demand model (PSDM) following multivariate logarithmic normal distribution will be developed, and taking PLS uncertainty and correlation into consideration, multidimensional PLS function is constructed to identify the structural failure domain. A full-scale 2-bay 2-story frame structure for the Network for Earthquake Engineering Simulation (NEES) project is employed as the case study structure to demonstrate the proposed theory. Nonlinear dynamic time-history analysis is carried out for the structure to obtain its maximum responses under earthquakes. Consequently, the multidimensional fragility curves can be derived on the basis of CPS. Besides, the influence of PLS threshold value, engineering demand parameter (EDP) correlation, and PLS correlation on the multidimensional fragility is investigated. Results show that (1) CPS damage index can fully consider the cumulative effect of damage under earthquakes, which makes up for the deficiency of the interstory drift damage index in this aspect, (2) the multidimensional fragility framework can deal with the PLS correlation and EDP correlation simultaneously, which will generate a more precise seismic damage assessment result, and (3) multidimensional fragility is sensitive to PLS threshold values and PLS correlation parameters.

show abstract

Section: Introductionmentioning

confidence: 99%

[Retracted] Multidimensional Fragility Analysis for a NEES Frame Structure by Integrating a New Energy Damage Index: Cumulative Plastic Strain

Wang

2019

Advances in Civil Engineering

View full text Add to dashboard Cite

show abstract

“…Ni, Lu, & Lu, 2017;Seuba, Deville, Guizard, & Stevenson, 2016;Sha, Radzieński, Cao, & Ostachowicz, 2019;Wu, Zeng, Huang, & Song, 2017;Yang & Frangopol, 2018;Yazdanipour & Pourgol-Mohammad, 2016;Ye, Hong, Zhang, Zhu, & Fuh, 2018) Logistic regressions (Bissacot et al, 2016;Egnew et al, 2018;Gauthier, Hétu, & Allard, 2015;Jang et al, 2018;Regan, Canturk, Slavkovsky, Niezrecki, & Inalpolat, 2016;Wazen, Fernandes, Aoki, & De Souza, 2013;W. Zhang et al, 2015) Neuro-Fuzzy (Adoko, Gokceoglu, Wu, & Zuo, 2013;Aydin & Kisi, 2015;Guruprasad & Behera, 2015;Hasheminejad, Sohankar, & Hajiannia, 2018;Naderpour & Mirrashid, 2019;Nanda, Das, Das, & Das, 2015;Tran, Nguyen, & Seo, 2019) Conclusions Deep learning methods are fast-evolving. Some of them have advanced to be specialized in a particular application domain.…”

Section: Annmentioning

confidence: 99%

Structural Damage Diagnosis and Prediction Using Machine Learning and Deep Learning Models: Comprehensive Review of Advances<strong> </strong>

Mosavi¹

2019

Preprint

View full text Add to dashboard Cite

The loss of integrity and adverse effect on mechanical properties can be concluded as attributing miro/macro-mechanics damage in structures, especially in composite structures. Damage as a progressive degradation of material continuity in engineering predictions for any aspects of initiation and propagation requires to be identified by a trustworthy mechanism to guarantee the safety of structures. Besides the materials design, structural integrity and health are usually prone to be monitored clearly. One of the most powerful methods for the detection of damage is machine learning (ML). This paper presents the state of the art of ML methods and their applications in structural damage and prediction. Popular ML methods are identified and the performance and future trends are discussed.

show abstract

“…Furthermore, Ahmadi et al [4] studied the seismic failure probability and vulnerability assessment of steel-concrete composite structures. Shear failure capacity prediction of concrete beam-column joints and classification of failure modes in ductile and non-ductile concrete joints were also studied [28,29]. Haji et al [14] performed an experimental study on influence of proposed FRP-strengthening techniques on RC circular short columns considering different types of damage index.…”

Section: Introductionmentioning

confidence: 99%

Reliability assessment of RC frames rehabilitated by eccentrically braces having vertical shear link

2020

View full text Add to dashboard Cite

A considerable number of existing reinforced concrete (RC) structures need to seismic rehabilitation due to several reasons such as being designed just based on gravity loading and/or having an unsatisfactory level of ductility. One of the types of steel bracing can be referred to eccentrically braced frames with a vertical link. This system has some advantages such as an increase in ductility, stiffness and lateral strength, the ability to adapt to the architecture, and also the minimum weight added to the structure. In this study, reliability analysis assessment of two existing 3-, and 9-story RC frames in two cases including original and rehabilitated with an eccentrically braced frame having a vertical link is presented. Two limit states are defined as: maximum roof displacement and maximum inter-story displacement. The seismic behavior of frames was assessed by nonlinear static pushover analysis with finite element program OpenSees in two performance levels, including collapse prevention and life safety. Five random variables represented the variability in resistance of concrete material, bars and steel profiles yield stress, beams height, columns dimension, and also bars cross-section. Sensitivity analysis was carried out to recognize the effect of random variables on the reliability index. The reliability analysis was performed by two different methods: Hasofer-Lind and Monte Carlo with 25, 100, 1000, 10,000 and 100,000 simulated samples by considering two distributions including Normal and Log-Normal. Finally, a comparison between two common reliability methods was carried out in order to select the most appropriate method for performing the best seismic performance reliability analysis of RC frames rehabilitated by the proposed system.

show abstract

Shear Failure Capacity Prediction of Concrete Beam–Column Joints in Terms of ANFIS and GMDH

Cited by 48 publications

References 31 publications

[Retracted] Multidimensional Fragility Analysis for a NEES Frame Structure by Integrating a New Energy Damage Index: Cumulative Plastic Strain

[Retracted] Multidimensional Fragility Analysis for a NEES Frame Structure by Integrating a New Energy Damage Index: Cumulative Plastic Strain

Structural Damage Diagnosis and Prediction Using Machine Learning and Deep Learning Models: Comprehensive Review of Advances<strong> </strong>

Reliability assessment of RC frames rehabilitated by eccentrically braces having vertical shear link

Contact Info

Product

Resources

About