The Genesis of IDARC and Advances in Macromodeling for Nonlinear Analysis of RC Structures

Kunnath, Sashi K.

doi:10.1007/978-3-319-06394-2_3

Cited by 10 publications

(11 citation statements)

References 6 publications

(3 reference statements)

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“…For predicting the life of the miniature FeSMA BRBs under mainshock-aftershock sequences or long-duration earthquakes, it is necessary to define a factor that could quantify the contributions of these effects. The frequently used one is the modified Park-Ang damage index, DI [47]:…”

Section: Unified Measure Of Damagementioning

confidence: 99%

Experimental tests and numerical simulations of miniature buckling-restrained braces using iron-shape memory alloy bar

Wang,

Jiang,

Qiu

et al. 2024

Smart Mater. Struct.

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Miniature buckling-restrained braces (BRBs) have a concise configuration and clear working mechanism. Owing to stable and full hysteresis, miniature BRBs are emerging as favorable energy-dissipating fuse elements in seismic applications. This paper proposes using iron-shape memory alloy (FeSMA) in lieu of conventional steel as the yielding core and focuses on the cyclic behavior. Four specimens, corresponding to four loading protocols, were fabricated and tested. According to experimental data, the miniature FeSMA BRBs exhibited full hysteresis, which is characterized by large damping, noticeable isotropic and kinematic hardening behavior and appreciable post-yield stiffness ratio. The cumulative plastic deformations meet the requirement by ANSI/AISC 341-16. Further, high fidelity finite element models, which explicitly considered damage and fracture rules, were established for numerical simulations. Good agreement can be found between the experimental data and numerical simulations, in terms of failure modes, fracture locations and global hysteresis.

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Section: Unified Measure Of Damagementioning

confidence: 99%

Experimental tests and numerical simulations of miniature buckling-restrained braces using iron-shape memory alloy bar

Wang,

Jiang,

Qiu

et al. 2024

Smart Mater. Struct.

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“…In order to describe the structural response, a global damage index was proposed by Park and Ang [59]. In this study, the modified Park and Ang damage index, as developed by Kunnath et al [60], is employed. The general local damage measure is defined for each element as follows:…”

Section: Mdof Systemsmentioning

confidence: 99%

Evaluation of Ground Motion Damage Potential with Consideration of Compound Intensity Measures Using Principal Component Analysis and Canonical Correlation Analysis

Liu,

2024

Buildings

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The primary motivation of this study is to develop a compound intensity measure (IM) to evaluate ground motion damage potential based on principal component analysis (PCA) and canonical correlation analysis (CCA). To illustrate this, this study examines the correlation among intragroup IMs and intergroup IMs, as well as the correlation between various IMs and response variables. A compound IM, which can be obtained by a linear combination of ten IMs in the log-scale, is utilized to measure the ground motion damage potential. Elastoplastic, bilinear and hysteretic models are utilized to determine peak deformation and hysteretic energy as the response variables of Single-Degree-of-Freedom (SDOF) systems. On the basis of the SDOF systems, the overall structural damage index is obtained by a nonlinear time–history analysis for two reinforced concrete moment frame systems. It is clear that the developed compound IM shows significantly high-level correlation with structural response. The better the correlations, the more one can measure the earthquake damage potential. A single IM alone inadequately characterizes structural damage, highlighting the necessity of multiple IMs to estimate the possibility of structural damage.

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“…The three-story RC structure was modeled using the sophisticated finite element method (FEM)based tool INSPECT INelastic Seismic Performance Evaluation Computational Tool (INSPECT), a graphical user interface of IDARC-2D to analyze the response of structures to nonlinear time history (AlHamaydeh et al, 2016;Kunnath et al, 1992). In this analysis, the beams are represented by continuous flexural springs, where flexural deformation is considered.…”

Section: Numerical Model Of the Rc Structurementioning

confidence: 99%

“…The viscous damping ratio was assumed to be uniformly distributed, with a value of 5%. This approach allowed for a more accurate representation of the nonlinear behavior of the structures and provided important information on the response of the structures to seismic loads (Kunnath et al, 1992). Figure 2 (a, b and c) represents the 2D RC structure with cross-section details.…”

Section: Numerical Model Of the Rc Structurementioning

confidence: 99%

Prediction of storey drift for reinforced concrete structures subjected to pulse-like ground motions using machine learning classification models

Wani,

Vemuri,

Chenna

2023

IJSI

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PurposeNear-fault pulse-like ground motions have distinct and very severe effects on reinforced concrete (RC) structures. However, there is a paucity of recorded data from Near-Fault Ground Motions (NFGMs), and thus forecasting the dynamic seismic response of structures, using conventional techniques, under such intense ground motions has remained a challenge.Design/methodology/approachThe present study utilizes a 2D finite element model of an RC structure subjected to near-fault pulse-like ground motions with a focus on the storey drift ratio (SDR) as the key demand parameter. Five machine learning classifiers (MLCs), namely decision tree, k-nearest neighbor, random forest, support vector machine and Naïve Bayes classifier , were evaluated to classify the damage states of the RC structure.FindingsThe results such as confusion matrix, accuracy and mean square error indicate that the Naïve Bayes classifier model outperforms other MLCs with 80.0% accuracy. Furthermore, three MLC models with accuracy greater than 75% were trained using a voting classifier to enhance the performance score of the models. Finally, a sensitivity analysis was performed to evaluate the model's resilience and dependability.Originality/valueThe objective of the current study is to predict the nonlinear storey drift demand for low-rise RC structures using machine learning techniques, instead of labor-intensive nonlinear dynamic analysis.

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The Genesis of IDARC and Advances in Macromodeling for Nonlinear Analysis of RC Structures

Cited by 10 publications

References 6 publications

Experimental tests and numerical simulations of miniature buckling-restrained braces using iron-shape memory alloy bar

Experimental tests and numerical simulations of miniature buckling-restrained braces using iron-shape memory alloy bar

Evaluation of Ground Motion Damage Potential with Consideration of Compound Intensity Measures Using Principal Component Analysis and Canonical Correlation Analysis

Prediction of storey drift for reinforced concrete structures subjected to pulse-like ground motions using machine learning classification models

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