Wavelet Analysis of Near-Field Ground Motions from the Mw 7.6 1999 Chi-Chi Earthquake in Taiwan

Wani, Faisal Mehraj; Moid, Mohammed Mujtaba; Reddy, Kanigiri Chandrakanth; Vemuri, Jayaprakash; Chenna, Rajaram

doi:10.1007/978-981-19-3371-4_28

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…Moreover, advanced techniques, such as the continuous wavelet transforms, aid in identifying the seismic activity simulatenously in both the time and the frequency domain. The results from (Wani et al ., 2022) confirm wavelet plunges for a short period of time for NFGMs with pulse-like (PL) features.…”

Section: Introductionmentioning

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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Section: Introductionmentioning

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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“…Ground motion with a fling step results in larger inter-storey drift for lower stories as the T p /T ratio approaches unity, whereas ground motion with forward directivity produces higher inter-storey drift for moderate and high stories when the T p /T ratio is less than 1. Additionally, a recent study (Wani et al. , 2022b) employed continuous wavelet transform for NFGMs for the 1999 Chi-Chi earthquake, to identify the seismic activity due to PL characteristics of ground motion, which is hidden in the time-domain plots.…”

Section: Introductionmentioning

confidence: 99%

Influence of near-fault ground motion characteristics and the relative geographical positioning of sites on the seismic response of RC structures

Wani

Vemuri

Chenna³

2023

IJSI

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PurposeThe objective of the study is to examine the response of reinforced concrete (RC) structures subjected to Near-Fault Ground Motions (NFGM) and highlight the importance of considering various factors including the influence of the relative geographical position of near-fault sites that can affect the structural response during an earthquake.Design/methodology/approachIn this paper, the response of a four-storey RC building subjected to NFGMs with varied characteristics like hanging wall and footwall in conjunction with directivity and the effect of pulse-like ground motions with rupture direction are investigated to understand the combined influence of these factors on the behavior of the structure. Furthermore, the capacity and demand of the structural element are investigated for computing the performance ratio.FindingsResults from this study indicate that the most unfavorable combinations for structural damage due to near-fault ground motion are the hanging wall with forward rupture, the fault normal component of ground motions, and pulse-like ground motions with forward directivity.Originality/valueThe results from this study provide valuable insight into the response of RC structures subjected to NFGM and highlight the importance of considering various factors that can affect the structural response during an earthquake. Moreover, the computation of capacity and demand of the critical beam indicates exceedance of desired limits, resulting in the early deterioration of the structural elements. Finally, the analytical analysis from the present study confirms that the hanging wall with forward ruptures, pulse-like motions, and fling steps are the most unfavorable combinations for seismic structural damage.

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Time–Frequency Analysis of Strong Ground Motions from the 1989 Loma Prieta Earthquake

Nerella,

Wani,

Ganne

et al. 2024

Lecture Notes in Mechanical Engineering

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Wavelet Analysis of Near-Field Ground Motions from the Mw 7.6 1999 Chi-Chi Earthquake in Taiwan

Cited by 3 publications

References 8 publications

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

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

Influence of near-fault ground motion characteristics and the relative geographical positioning of sites on the seismic response of RC structures

Time–Frequency Analysis of Strong Ground Motions from the 1989 Loma Prieta Earthquake

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