Seismic Fragility Assessment of Reinforced Concrete High-Rise Buildings Using the Uncoupled Modal Response History Analysis (UMRHA)

Zain, Muhammad; Anwar, Naveed; Najam, Fawad Ahmed; Mehmood, Tahir

doi:10.1007/978-3-319-78187-7_16

Cited by 10 publications

(4 citation statements)

References 11 publications

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“…Field data containing structural information like the number of spans, beams, columns, the thickness of slabs, and location of stairs was collected by Ferreira from district Muzaffarabad for the existing RC school buildings and was verified with the structural drawings [ 44 ]. The databases containing building dimensions are tabulated in Table 1 [ 21 ]. The nonlinear incremental dynamic analysis was employed to determine the structural behaviour against the gradually scaled 20 past earthquake records depending upon the site history.…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…These curves can be beneficial for retrofitting the structures and planning for future possible earthquakes in highly seismic zones such as Pakistan. Fragility curves can be established using judgemental, empirical, or analytical procedures [ 20 , 21 ]. However, analytical techniques are the most commonly practiced methods using available past recorded earthquake data and structural details [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

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Machine Learning-Based Fragility Assessment of Reinforced Concrete Buildings

Rasheed¹,

Usman

Zain

et al. 2022

Computational Intelligence and Neuroscience

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In the past, large earthquakes caused the collapse of infrastructure and killed thousands of people in Pakistan, a seismically active region. Therefore, the seismic assessment of infrastructure is a dire need that can be done using the fragility analysis. This study focuses on the fragility analysis of school buildings in Muzaffarabad district, seismic zone-4 of Pakistan. Fragility curves were developed using incremental dynamic analysis (IDA); however, the numerical analysis is computationally time-consuming and expensive. Therefore, soft computing techniques such as Artificial Neural Network (ANN) and Gene Expression Programming (GEP) were employed as alternative methods to establish the fragility curves for the prediction of seismic performance. The optimized ANN model [5-25-1] was used. The feedforward backpropagation network was considered in this study. To achieve a reliable model, 70% of the data was selected for training and 15% for validation and 15% of data was used for testing the model. Similarly, the GEP model was also employed to predict the fragility curves. The results of both ANN and GEP were compared based on the coefficient of determination, R2. The ANN model accurately predicts the global drift values with R2 equal to 0.938 compared to the GEP model having R2 equal to 0.87.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Machine Learning-Based Fragility Assessment of Reinforced Concrete Buildings

Rasheed¹,

Usman

Zain

et al. 2022

Computational Intelligence and Neuroscience

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“…As indicated by the literature, fragility curves are widely employed to represent the vulnerability of buildings [5,6]. Tangible examples can be observed in the literature; for instance, Zain et al [7] developed the analytical fragility curves for a reinforced concrete building in Philippines by considering two damage states. It is pertinent to mention that the damage itself characterizes undesirable changes in a system that adversely affects a structure's behavior [8].…”

Section: Introductionmentioning

confidence: 99%

Seismic Vulnerability Assessment of School Buildings in Seismic Zone 4 of Pakistan

Zain

Usman

Farooq

et al. 2019

Advances in Civil Engineering

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Thick population density and its escalation propensity in seismically active regions of Pakistan has raised sincere concerns about the performance of building stock whose suboptimal performance and complete collapses led to a colossal number of casualties during the past earthquakes. The current research is inspired by the Kashmir earthquake of 2005 which consumed more than 80,000 lives, out of which, approximately 19,000 were children due to wide spread collapse of school buildings. A new database for existing reinforced concrete (RC) school buildings in seismic zone 4 of Pakistan has been developed using the surveyed information and presented briefly. The paper presents the statistics of the data collected through field surveys and professional interviews. It was found that the infrastructural authorities in the considered region developed some specific designs for school buildings, with varying architectural and structural configurations, which were eventually replicated throughout the area. In the current study, almost 2500 schools were surveyed for identifying versatile architectural and structural configurations, and subsequently, 19 different types had been identified, which were eventually used as representative stock for the schools in seismic zone 4 of Pakistan, Muzaffarabad district. The results of the study yield the brief of the collected data from the field and a consolidated methodology for establishing the analytical fragility relationships for one of the 19 structural configurations of the school buildings. A sample building from the collected data has been selected by considering the maximum number of students, and afterwards, the vulnerability is assessed by employing incremental dynamic analysis (IDA) which constitutes the presented methodology. Finally, the fragility curves are developed and presented for the said building type. The derived analytical fragility curves for the considered building type indicate its structural vulnerability and as a whole represent its satisfactory behavior. The vulnerability assessment process and the fragility development are described in an easy manner so that the domestic practicing engineers can readily become able to extend the application towards other school buildings in the region. The developed relationships can be employed for rational decision making so that essential disaster preparedness can be carried out by identifying any need for structural strengthening and interventions.

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A Systematic Review on Different Approaches Used in the Development of Fragility Curves for Buildings

Rajapaksha¹,

Siriwardana²

2022

Lecture Notes in Civil Engineering

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Seismic Fragility Assessment of Reinforced Concrete High-Rise Buildings Using the Uncoupled Modal Response History Analysis (UMRHA)

Cited by 10 publications

References 11 publications

Machine Learning-Based Fragility Assessment of Reinforced Concrete Buildings

Machine Learning-Based Fragility Assessment of Reinforced Concrete Buildings

Seismic Vulnerability Assessment of School Buildings in Seismic Zone 4 of Pakistan

A Systematic Review on Different Approaches Used in the Development of Fragility Curves for Buildings

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