Advances in Structural Systems for Tall Buildings: Emerging Developments for Contemporary Urban Giants

Ali, Mir M.; Moon, Kyoung Sun

doi:10.3390/buildings8080104

Cited by 81 publications

(50 citation statements)

References 22 publications

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“…Step 3: To determine the optimized structure of C-ANN, various structures of C-ANN were developed and validated using R 2 , RMSE, and MAE. The optimized C-ANN structure was selected based on the maximum values of R 2 and minimum values of RMSE and MAE.…”

Section: Methodological Flow Chartmentioning

confidence: 99%

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Investigation and Optimization of the C-ANN Structure in Predicting the Compressive Strength of Foamed Concrete

Dao

et al. 2020

Materials

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Development of Foamed Concrete (FC) and incessant increases in fabrication technology have paved the way for many promising civil engineering applications. Nevertheless, the design of FC requires a large number of experiments to determine the appropriate Compressive Strength (CS). Employment of machine learning algorithms to take advantage of the existing experiments database has been attempted, but model performance can still be improved. In this study, the performance of an Artificial Neural Network (ANN) was fully analyzed to predict the 28 days CS of FC. Monte Carlo simulations (MCS) were used to statistically analyze the convergence of the modeled results under the effect of random sampling strategies and the network structures selected. Various statistical measures such as Coefficient of Determination (R2), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE) were used for validation of model performance. The results show that ANN is a highly efficient predictor of the CS of FC, achieving a maximum R2 value of 0.976 on the training part and an R2 of 0.972 on the testing part, using the optimized C-ANN-[3–4–5–1] structure, which compares with previous published studies. In addition, a sensitivity analysis using Partial Dependence Plots (PDP) over 1000 MCS was also performed to interpret the relationship between the input parameters and 28 days CS of FC. Dry density was found as the variable with the highest impact to predict the CS of FC. The results presented could facilitate and enhance the use of C-ANN in other civil engineering-related problems.

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Section: Methodological Flow Chartmentioning

confidence: 99%

“…Over the past decades, large-scale, super-tall, or mega-tall buildings have been increasingly constructed over the world [1,2]. This fact raises a number of fundamental engineering problems, crucial to be solved, such as self-weight, large foundation sizes, and earthquake resistance [3,4].…”

Section: Introductionmentioning

confidence: 99%

Investigation and Optimization of the C-ANN Structure in Predicting the Compressive Strength of Foamed Concrete

Dao

et al. 2020

Materials

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“…Structural systems for high‐rise buildings have evolved from the relatively simple systems, such as frame system, shear wall system, wall‐frame system, and core tube system, towards more complex hybrid systems for super high‐rise buildings . The complex hybrid structural system for super high‐rise buildings often consists of core tubes, mega columns, and outrigger trusses.…”

Section: Osp Frameworkmentioning

confidence: 99%

Optimal multi‐type sensor placement for monitoring high‐rise buildings under bidirectional long‐period ground motions

Zhao

2020

Struct Control Health Monit

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Summary Towards a complete and accurate seismic assessment of a super high‐rise building under bidirectional long‐period ground motions, this study proposes an optimal multi‐type sensor placement framework for the best reconstruction of structural responses and ground motions based on a full‐scale 3D finite element (FE) model of the building. The selected locations and types of sensors are capable of not only capturing the coupled bending‐torsional vibration but also providing an unbiased estimation of the unmeasured responses of seismic‐vulnerable components and bidirectional ground motions. A Kalman filtering algorithm‐based data fusion technique is employed to deal with the measurement data from multi‐type sensors. With the target of achieving the best reconstruction, an optimal sensor placement (OSP) configuration, which minimizes the reconstruction error, is achieved through a sequential sensor placement algorithm. To assess the feasibility of the proposed OSP framework and the accuracy of reconstructed responses and ground motions, a numerical study is also performed on the full‐scale 3D FE model of a super high‐rise building. The torsional effects of the building under bidirectional long‐period ground motions are assessed by comparison with the results without considering the torsional effect. The numerical results show that the proposed framework is feasible and the reconstructed responses and ground motions are accurate and that the torsional effects cannot be neglected in the seismic assessment of the building.

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“…columns, beams, walls and slabs) capable of resisting loads. Tall buildings are generally composed of three structural sub-systems: a lateral load resisting system (LLRS), which predominantly resists wind and earthquake loads, a vertical load resisting system (VLRS), which predominantly resists gravity loads, and a foundation system, which transfers all of the loads to the ground (Ali and Moon, 2018). Due to the high influence of lateral loads on the structural design of tall buildings, this paper classifies structural systems of tall buildings based on their lateral load-resisting systems.…”

Section: Structural Systemsmentioning

confidence: 99%

Towards a design framework for the structural systems of tall buildings that considers embodied greenhouse gas emissions

Helal¹,

Stephan²,

Crawford³

2019

Structures and Architecture: Bridging the Gap and Crossing Borders

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proposed an influential design framework for the structural systems of tall buildings titled premium-for-height. Khan argued that the challenge of a structural engineer is to design structural systems that minimise the increase in structural material weight per gross floor area with increasing building height. However, in meeting the challenges of climate change and urbanisation, minimising the embodied environmental flows of tall buildings must also be a priority in structural design frameworks. This paper proposes to expand the premium-for-height framework for tall buildings by considering the embodied greenhouse gas emissions of structural systems using a hybrid life cycle inventory analysis method. Advanced structural analysis and a comprehensive consideration of building parameters are also proposed. To demonstrate the use and potential of the framework, embodied greenhouse gas emissions of six case study tall buildings are analysed. The results are discussed and recommendations are made to improve the reliability of the more comprehensive framework.

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Advances in Structural Systems for Tall Buildings: Emerging Developments for Contemporary Urban Giants

Cited by 81 publications

References 22 publications

Investigation and Optimization of the C-ANN Structure in Predicting the Compressive Strength of Foamed Concrete

Investigation and Optimization of the C-ANN Structure in Predicting the Compressive Strength of Foamed Concrete

Optimal multi‐type sensor placement for monitoring high‐rise buildings under bidirectional long‐period ground motions

Towards a design framework for the structural systems of tall buildings that considers embodied greenhouse gas emissions

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