A multi‐objective structural optimization method for serviceability design of tall buildings
Structural optimization design aims to identify optimal design variables corresponding to a minimum objective function with constraints on performance requirements. To this end, many optimization frameworks have been proposed to determine optimal structural systems that are subjected to seismic and...
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| Published in | The structural design of tall and special buildings Vol. 32; no. 17 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
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Oxford
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10.12.2023
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| Abstract | Structural optimization design aims to identify optimal design variables corresponding to a minimum objective function with constraints on performance requirements. To this end, many optimization frameworks have been proposed to determine optimal structural systems that are subjected to seismic and wind hazards in isolation. However, some modern tall buildings are sensitive to seismic and wind excitation owing to their complex structural systems and geographic regions. Therefore, a proper structural optimization method for such buildings is required to ensure that the expected performance is achieved in a multi‐hazard scenario. This study proposes a multi‐objective serviceability design optimization methodology for buildings in multi‐hazard seismic and wind environments by combining optimality criteria and the nondominated sorting genetic algorithm II (NSGA‐II). Seismic and wind effects can be instantaneously updated due to changes in the structural dynamic properties during the optimal design process. A neural‐network‐based surrogate model with self‐updating is proposed to predict the structural natural frequency so that the overall computation time of the optimization process can be reduced. The proposed method was used to optimize a 50‐story frame‐tube building and was compared against the general genetic algorithm and general NSGA‐II to verify the feasibility and effectiveness. |
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| AbstractList | Structural optimization design aims to identify optimal design variables corresponding to a minimum objective function with constraints on performance requirements. To this end, many optimization frameworks have been proposed to determine optimal structural systems that are subjected to seismic and wind hazards in isolation. However, some modern tall buildings are sensitive to seismic and wind excitation owing to their complex structural systems and geographic regions. Therefore, a proper structural optimization method for such buildings is required to ensure that the expected performance is achieved in a multi‐hazard scenario. This study proposes a multi‐objective serviceability design optimization methodology for buildings in multi‐hazard seismic and wind environments by combining optimality criteria and the nondominated sorting genetic algorithm II (NSGA‐II). Seismic and wind effects can be instantaneously updated due to changes in the structural dynamic properties during the optimal design process. A neural‐network‐based surrogate model with self‐updating is proposed to predict the structural natural frequency so that the overall computation time of the optimization process can be reduced. The proposed method was used to optimize a 50‐story frame‐tube building and was compared against the general genetic algorithm and general NSGA‐II to verify the feasibility and effectiveness. |
| Author | Xiao, Zhi‐Bin Huang, Ming‐Feng Wang, Chun‐He Lin, Wei |
| Author_xml | – sequence: 1 givenname: Ming‐Feng orcidid: 0000-0002-3741-7550 surname: Huang fullname: Huang, Ming‐Feng organization: Institute of Structural Engineering Zhejiang University Hangzhou China, Center for Balance Architecture Zhejiang University Hangzhou China – sequence: 2 givenname: Chun‐He surname: Wang fullname: Wang, Chun‐He organization: Institute of Structural Engineering Zhejiang University Hangzhou China – sequence: 3 givenname: Wei surname: Lin fullname: Lin, Wei organization: Center for Balance Architecture Zhejiang University Hangzhou China – sequence: 4 givenname: Zhi‐Bin surname: Xiao fullname: Xiao, Zhi‐Bin organization: Center for Balance Architecture Zhejiang University Hangzhou China |
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| SubjectTerms | Algorithms Building design Design optimization Genetic algorithms Objective function Optimality criteria Resonant frequencies Seismic hazard Sorting algorithms Tall buildings Tube building Weather hazards Wind Wind effects |
| Title | A multi‐objective structural optimization method for serviceability design of tall buildings |
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