Topology, Size, and Shape Optimization in Civil Engineering Structures: A Review
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| Veröffentlicht in: | Computer Modeling in Engineering & Sciences vol. 142, no. 2 (2025), p. 933 |
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Tech Science Press
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| 001 | 3200122770 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1526-1492 | ||
| 022 | |a 1526-1506 | ||
| 024 | 7 | |a 10.32604/cmes.2025.059249 |2 doi | |
| 035 | |a 3200122770 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Manguri, Ahmed | |
| 245 | 1 | |a Topology, Size, and Shape Optimization in Civil Engineering Structures: A Review | |
| 260 | |b Tech Science Press |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 653 | |a Built environment | ||
| 653 | |a Reinforced concrete | ||
| 653 | |a Structural safety | ||
| 653 | |a Genetic algorithms | ||
| 653 | |a Shape optimization | ||
| 653 | |a Optimization techniques | ||
| 653 | |a Civil engineering | ||
| 653 | |a Search algorithms | ||
| 653 | |a Emissions | ||
| 653 | |a Structural design | ||
| 653 | |a Machine learning | ||
| 653 | |a Design optimization | ||
| 653 | |a Energy consumption | ||
| 653 | |a Tensegrity | ||
| 653 | |a Topology optimization | ||
| 653 | |a Seismic design | ||
| 653 | |a Heuristic methods | ||
| 653 | |a Smart structures | ||
| 653 | |a Nonlinearity | ||
| 700 | 1 | |a Hogr Hassan | |
| 700 | 1 | |a Najmadeen Saeed | |
| 700 | 1 | |a Jankowski, Robert | |
| 773 | 0 | |t Computer Modeling in Engineering & Sciences |g vol. 142, no. 2 (2025), p. 933 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3200122770/abstract/embedded/H09TXR3UUZB2ISDL?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3200122770/fulltextPDF/embedded/H09TXR3UUZB2ISDL?source=fedsrch |