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Structural optimization design of multi ribbed composite wall of building components under seismic load based on random optimization algorithm and resilience model

Autorzy
Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The multi ribbed composite wall structure is also known as the multi ribbed wall panel light frame structure. This structure is suitable for housing construction in the residential field. The special structural failure process and mode of multi ribbed composite walls are different from traditional walls. To fully utilize the excellent structural performance in building construction and improve the seismic performance of the building, based on the transformation principle of subset optimization algorithm for optimization problems, a constrained subset simulation optimization algorithm suitable for optimizing the maximum displacement angle of multi ribbed composite wall panels is designed. The Bayesian algorithm is used to construct a restoring force model for multi ribbed composite wall panels. The constrained subset simulation optimization algorithm and resilience model are used to optimize the seismic performance of 4-layer multi ribbed composite wall panels. The results show that the section height and the equivalent slant support width of the continuous column for the 4-story multi ribbed composite wall panel change from discrete distribution to aggregation with the increase of iteration. Finally, the sampling is stable in the 9th floor. At this time, the section height of the continuous column is 230 mm, and the equivalent slant support width is 525. After optimization, the failure probability of both extreme displacement angle states has decreased. When the peak ground acceleration is 1.0 g, the optimized second limit state failure probability is less than 100%. When the peak ground acceleration value is between 0.2 g and 0.6 g, both limit states show a rapid upward trend. The constrained subset simulation optimization algorithm and Bayesian quantitative resilience model proposed in the research can effectively optimize the seismic performance of multi ribbed composite walls.
Słowa kluczowe
Rocznik
Strony
447--460
Opis fizyczny
Bibliogr. 15 poz., il., tab.
Twórcy
autor
  • Department of Real Estate and Engineering Management, Liaoning Urban Construction Technical College, Shenyang, China
autor
  • Department of Real Estate and Engineering Management, Liaoning Urban Construction Technical College, Shenyang, China
Bibliografia
  • [1] S. Durdyev, S. R. Mohandes, S. Tokbolat, H. Sadeghi, and T. Zayed, “Examining the OHS of green building construction projects: a hybrid fuzzy-based approach”, Journal of Cleaner Production, vol. 338, pp. 590-602, 2022, doi: 10.1016/j.jclepro.2022.130590.
  • [2] Y.P. Liu, J.J. Li,W. Q. Chen, L.L. Song, and S.Q. Dai, “Quantifying urban mass gain and loss by a GIS-based material stocks and flows analysis”, Journal of Industrial Ecology, vol. 26, no. 3, pp. 1051-1060, 2022, doi:10.1111/jiec.13252.
  • [3] M. Tomczak and P. Jaskowski, “Harmonizing construction processes in repetitive construction projects with multiple buildings”, Automation in Construction, vol. 139, pp. 266-288, 2022, doi: 10.1016/j.autcon.2022.104266.
  • [4] Q. Lin, S. C. Li, and Y.F. Zhu, “Analysis of hysteresis rule of energy-saving block and invisible multi-ribbed frame composite wall”, Structural Engineering and Mechanics, vol. 77, no. 2, pp. 261-272, 2021, doi: 10.12989/sem.2021.77.2.261.
  • [5] J. Sun, L. Yuan, and P.F. Wang, “Residual bearing capacity of infilled frame of multi-ribbed composite wall after high temperature”, Construction and Building Materials, vol. 214, pp. 196-206, 2019, doi: 10.1016/j.conbuildmat.2019.04.112.
  • [6] Z.A.B. Ismail, “Thermal comfort practices for precast concrete building construction projects: towards BIM and IOT integration”, Engineering Construction and Architectural Management, vol. 29, no. 3, pp. 1504-1521, 2022, doi: 10.1108/ECAM-09-2020-0767.
  • [7] S. Han, Z. Lei, U. Hermann, A. Bouferguene, and M. Al-Hussein, “4D-based automation of heavy lift planning in industrial construction projects”, Canadian Journal of Civil Engineering, vol. 48, no. 9, pp. 1115-1129, 2021, doi: 10.1139/cjce-2019-0825.
  • [8] M. Li, G.F. Jia, Z.B. Cheng, and Z. Shi, “Generative adversarial network guided topology optimization of doi: 10.1016/j.compstruct.2020.113254.
  • [9] H. Ezaldeen, S.K. Bisoy, R. Misra, and R. Alatrash, “Semantics-aware context-based learner modelling using normalized PSO for personalized e-learning”, Journal of Web Engineering, vol. 21, no. 4, pp. 1187-1224, 2022, doi: 10.13052/jwe1540-9589.2148.
  • [10] L. Cao, W.Y. Zhang, X. Kan, and W. Yao, “A novel adaptive mutation PSO optimized SVM algorithm for sEMG-based gesture recognition”, Scientific Programming, vol. 2021, pp. 823-836, 2021, doi: 10.1155/2021/9988823.
  • [11] G. Datola, M. Bottero, E. De Angelis, and F. Romagnoli, “Operationalising resilience: a methodological framework for assessing urban resilience through System Dynamics Model”, Ecological Modelling, vol. 465, art. no. 109851, 2022, doi: 10.1016/j.ecolmodel.2021.109851.
  • [12] S. Oslund, C. Washington, A. So, T.T. Chen, and H. Ji, “Multiview robust adversarial stickers for arbitrary objects in the physical world”, Journal of Computational and Cognitive Engineering, vol. 1, no. 4, pp. 152-158, 2022, doi: 10.47852/bonviewJCCE2202322.
  • [13] M. Ünver, M. Olgun, and E. Türkarslan, “Cosine and cotangent similarity measures based on Choquet integral for Spherical fuzzy sets and applications to pattern recognition”, Journal of Computational and Cognitive Engineering, vol. 1, no. 1, pp. 21-31, 2022, doi: 10.47852/bonviewJCCE2022010105.
  • [14] D. Aikhuele, “Development of a statistical reliability-based model for data1, Revised: data2 the estimation and optimization of a spur gear system”, Journal of Computational and Cognitive Engineering, vol. 2, no. 2, pp. 168-174, 2022, doi: 10.47852/bonviewJCCE2202153.
  • [15] P. Szeptyński and L. Mikulski, “Preliminary optimization technique in the design of steel girders according to Eurocode 3”, Archives of Civil Engineering, vol. 69, no. 1, pp. 71-89, 2023, doi: 10.24425/ace.2023.144160.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a96a1074-da18-4b6f-a65f-3ffec5450397
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