Evaluation of seismic torsional response of ductile RC buildings with soft first story

Hareen, Ch.B.V.; Mohan, S. C.

doi:10.1016/j.istruc.2020.12.031

Cited by 16 publications

(4 citation statements)

References 67 publications

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“…A verification report [64] compares the seismic responses of RC buildings from SeismoStruct simulations to experimental observations. Our current study on elastic 3D buildings employs similar methods to those detailed in the mentioned report [64] and study [65].…”

Section: Modelling and Analysis Of Buildingsmentioning

confidence: 99%

Utilizing Artificial Neural Networks and Random Forests to Forecast the Dynamic Amplification Factors of Non-Structural Components

Vyshnavi,

Challagulla,

Adamu

et al. 2023

Applied Sciences

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Soft stories in buildings are well-known to present structural vulnerabilities during seismic events, and the failure of non-structural components (NSCs) has been evident in past earthquakes, along with structural damage. This study seeks to investigate how the presence of a soft story in a building affects the criteria for elastic floor acceleration. The soft story is assumed to be at the top, middle, and bottom levels of the structure. To comprehend the behavior of NSCs, the researchers analyze the floor response spectra (FRSs) and component acceleration amplification. Remarkably, the results reveal that the position of the soft story strongly influences the floor response spectra, with structures featuring a middle soft story showing the most significant amplification of component acceleration. In constructing the FRSs, the component dynamic amplification factors (CDAFs) play a vital role as they accurately illustrate how NSCs amplify floor vibrations. Consequently, the study delves into exploring machine learning (ML) models like artificial neural networks (ANNs) and random forest (RF) to map the intricate relationship between CDAFs, the dynamic characteristics of the building, and the behavior of NSCs. Upon comparison of the two models, the random forest model emerges as the superior method in predicting the CDAFs.

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Section: Modelling and Analysis Of Buildingsmentioning

confidence: 99%

Utilizing Artificial Neural Networks and Random Forests to Forecast the Dynamic Amplification Factors of Non-Structural Components

Vyshnavi,

Challagulla,

Adamu

et al. 2023

Applied Sciences

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“…In 2021, the infill wall interaction amplifying the torsional response of buildings at the bottom story was discussed [15], and it was proved that the infill walls have altered the load-resisting path and effectively enhanced the load redistribution ability for the frames [16,17], depending on the construction sequences of the infilled frames [18]. Moreover, infill walls can contribute to a lateral strength increase of up to 60% compared to bare frames [19].…”

Section: Introductionmentioning

confidence: 99%

Effect of Infills on the Response Modification Factor for Infilled Reinforced Concrete Frame Buildings

Helmy,

Okail,

Zidan

2023

Civ Eng J

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RC frames with unreinforced masonry infill walls are the most common type of building. Unreinforced masonry walls are often not considered by engineers in the design process, although walls and frames interact during strong ground motion, leading to structural responses deviating radically from what is expected in the design. Under lateral load, reinforced concrete confining members (frames) act in tension or compression, depending on the direction of the lateral seismic pressures. Meanwhile, masonry walls act as diagonal struts prone to compression. This research aims to develop the effect of masonry infills and their distribution on the value of the resulting response modification factor. For this purpose, a parametric study was performed on five, seven, and ten-story' buildings modeled as bare and infilled frames. Infill ratio, panel aspect ratio, unidirectional eccentricity, and bidirectional eccentricities were the parameters investigated. Each proposed model's resulting response modification factor was compared to the value cited in different international codes. It was concluded that this value differs depending on several parameters and cannot be constant for a certain structural system. The novelty of this research is the deduction of a general equation to calculate the response modification factor as a function of the percentage of infills and the eccentricity, while presenting two different methods to calculate it. Doi: 10.28991/CEJ-2023-09-12-09 Full Text: PDF

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“…A transfer story has several types, for example, transfer beam (girder) [1], transfer slab (plate) [2][3][4][5][6][7], or transfer box [8], among which the transfer slab structure is quite popular due to being free from the limitation of the forms of the upper and lower structures and the flexible axes distribution of upper and lower stories. Due to the space requirement of subway station, the height of frame structure differs greatly from the first floor to the second floor, resulting in structural stiffness mutation and the formation of soft-story [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27]. Buildings with soft-story had a significantly higher proportion of serious damage than other conventional types of buildings after the earthquake in Hyogo-ken Nambu (1995) as well as in Mexico City (1985) [7].…”

Section: Introductionmentioning

confidence: 99%

“…Buildings with soft-story had a significantly higher proportion of serious damage than other conventional types of buildings after the earthquake in Hyogo-ken Nambu (1995) as well as in Mexico City (1985) [7]. The internal force of the vertical anti-lateral component of the structure is transferred downward by the horizontal conversion component, and the structure displays obvious vertical irregularity [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27]. The plate-column joints of this structure have complex forces under seismic loads; therefore, some scholars have carried out studies on such structures from the perspective of the joints [4][5][6][28][29][30][31][32][33][34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Experimental Study of Frame-Supported Shear Wall Structure of High-Rise Buildings with Transfer Slab in Metro Depot

Xia

Liu³

et al. 2022

Buildings

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Taking the frame-supported shear wall structure of a 102.1 m high metro depot as the test object, the structure has obvious vertical irregularity, and a quasi-static test was carried out on the structural model with the scale of 1/5. The damage development and strain of the structure were observed by applying displacement loads under different seismic actions, and the experimental phenomena and measured data were analyzed. The results show that the safety performance of the structure meets the seismic requirements of the MCE (Maximum considered earthquake) condition. Under the action of load, a reasonable damage mechanism is formed in which the components above the transfer story crack first and those below the transfer story crack later, which is in line with the design concept of “the performance objective of the bottom frame structure is higher than that of the upper shear wall structure”. The transfer plate is mainly subjected to shear deformation, the possible shear failure of the transfer plate should be avoided by reasonable design. Due to the large height difference between the first floor and the second floor, the structure may be adversely affected, so it is necessary to make the yielding floor appear in the bottom strengthening part above the transfer story. Under the SLE (Service level earthquake) and DBE (Design based earthquake) conditions, the bottom frame of the structure is mainly subjected to elastic deformation. Under the MCE (Maximum considered earthquake) condition, the bottom frame of the structure causes a lot of damage, increases energy consumption and decreases stiffness, which further proves that “the performance goal of the bottom frame structure is higher than that of the upper shear wall structure”.

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Evaluation of seismic torsional response of ductile RC buildings with soft first story

Cited by 16 publications

References 67 publications

Utilizing Artificial Neural Networks and Random Forests to Forecast the Dynamic Amplification Factors of Non-Structural Components

Utilizing Artificial Neural Networks and Random Forests to Forecast the Dynamic Amplification Factors of Non-Structural Components

Effect of Infills on the Response Modification Factor for Infilled Reinforced Concrete Frame Buildings

Experimental Study of Frame-Supported Shear Wall Structure of High-Rise Buildings with Transfer Slab in Metro Depot

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