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Abstract
The optimization of civil engineering structures is critical for enhancing structural performance and material efficiency in engineering applications. Structural optimization approaches seek to determine the optimal design, by considering material performance, cost, and structural safety. The design approaches aim to reduce the built environment’s energy use and carbon emissions. This comprehensive review examines optimization techniques, including size, shape, topology, and multi-objective approaches, by integrating these methodologies. The trends and advancements that contribute to developing more efficient, cost-effective, and reliable structural designs were identified. The review also discusses emerging technologies, such as machine learning applications with different optimization techniques. Optimization of truss, frame, tensegrity, reinforced concrete, origami, pantographic, and adaptive structures are covered and discussed. Optimization techniques are explained, including metaheuristics, genetic algorithm, particle swarm, ant-colony, harmony search algorithm, and their applications with mentioned structure types. Linear and non-linear structures, including geometric and material nonlinearity, are distinguished. The role of optimization in active structures, structural design, seismic design, form-finding, and structural control is taken into account, and the most recent techniques and advancements are mentioned.
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Authors (4)
-
Hogr Hassan
-
Najmadeen Saeed Asst Prof.
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Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.32604/cmes.2025.059249
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Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
no. 142,
pages 933 - 971,
ISSN: 1526-1492 - Language:
- English
- Publication year:
- 2025
- Bibliographic description:
- Manguri A., Hassan H., Saeed N., Jankowski R.: Topology, Size, and Shape Optimization in Civil Engineering Structures: A Review// CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES -Vol. 142,iss. 2 (2025), s.933-971
- DOI:
- Digital Object Identifier (open in new tab) 10.32604/cmes.2025.059249
- Sources of funding:
-
- Free publication
- Verified by:
- Gdańsk University of Technology
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