The contribution of generative design to efficiency in structural engineering: a case study
DOI:
https://doi.org/10.51372/gacetatecnica271.2Keywords:
generative design, structural engineering, structural optimization, efficiencyAbstract
Generative design is a design approach that uses algorithms and computational techniques to generate and optimize shapes and patterns. This methodology has the potential to revolutionize the structural design process by emerging as a disruptive tool in structural engineering, driving optimization and innovation in design. The importance of generative design in structural engineering lies in its ability to efficiently and sustainably optimize structures, which can reduce costs and construction time. The objective of this article is to identify the generative design parameters that affect the efficiency of structural design. The procedure includes a search in academic databases and the selection of relevant documents exploring its applications in various structural engineering contexts. The search led to a total of 128 documents between 2020 and 2024; applying inclusion and exclusion criteria based on task automation, generation of more efficient designs, and exploration of multiple design options reduced this to ten cases, of which five were exemplified. Finally, it was found that the parameters time, cost, quality, weight, strength, and energy efficiency are identified as key factors within structural design efficiency
Downloads
References
G. F. Azevedo, «BIM methodology implementation in structural design: Adaptation of procedures and information management», Journal of Civil Engineering and Environmental Sciences, vol. 8, n.o 1, pp. 093-099, oct. 2022, doi: https://dx.doi.org/10.17352/2455-488X.000058.
L. H. Oscar, L. C. Cerqueira, P. H. Cunha, y E. L. Qualharini, «Generative design in civil construction: a case study in Brazil», Front. Built Environ., vol. 9, jun. 2023, doi: 10.3389/fbuil.2023.1150767.
P. N. Angarita-Uscategui, L. Ovallos-Manosalva, y B. Y. Carballo-Rincón, «Análisis de la productividad de mano de obra para la construcción de una vivienda unifamiliar en el municipio de Ocaña, Norte de Santander», Revista Ingenio, vol. 15, n.o 1, Art. n.o 1, dic. 2018, doi: 10.22463/2011642X.3123.
K. J. Angulo Benavides, «Evaluación de la productividad del diseño estructural de edificaciones de concreto armado mediante el uso de dos software», bachelorThesis, Universidad Nacional de Chimborazo,2018, 2018. Accedido: 4 de mayo de 2024. [En línea]. Disponible en: http://dspace.unach.edu.ec/handle/51000/4756
J. Prokopenko, La gestión de la productividad: manual práctico. Oficina Internacional del Trabajo, 1989.
H. R. Thomas, Q. C. Korte, V. E. Sanvido, y M. K. Parfitt, «Conceptual Model for Measuring Productivity of Design and Engineering», Journal of Architectural Engineering, vol. 5, n.o 1, pp. 1-7, mar. 1999, doi: 10.1061/(ASCE)1076-0431(1999)5:1(1).
Y. Ebrahimy y S. Rokni, «Validity of Industry Benchmarks and Metrics for Engineering Productivity», pp. 1057-1063, abr. 2012, doi: 10.1061/41109(373)106.
L. Song, M. Allouche, y S. AbouRizk, «Measuring and Estimating Steel Drafting Productivity», pp. 1-9, abr. 2012, doi: 10.1061/40671(2003)9.
I. Kim, «Development and implementation of an engineering productivity measurement system (EPMS) for benchmarking», 2007, Accedido: 13 de mayo de 2024. [En línea]. Disponible en: http://hdl.handle.net/2152/3285
B. Malgıt, Ü. Işıkdağ, G. Bekdaş, y M. Yücel, «A generative design-to-BIM workflow for minimum weight plane truss design», Revista de la construcción, vol. 21, n.o 2, pp. 473-492, sep. 2022, doi: 10.7764/rdlc.21.2.473.
M. McKnight, «Generative Design: What it is? How is it being used? Why it’s a game changer», KnE Engineering, pp. 176-181, feb. 2017, doi: 10.18502/keg.v2i2.612.
L. Gradišar, R. Klinc, Ž. Turk, y M. Dolenc, «Generative Design Methodology and Framework Exploiting Designer-Algorithm Synergies», Buildings, vol. 12, n.o 12, Art. n.o 12, dic. 2022, doi: 10.3390/buildings12122194.
A. S. Birkemo y S. M. K. Samarakoon, «Application of generative design for structural optimization at the conceptual design phase», WIT Transactions on The Built Environment, pp. 139-153, nov. 2021, doi: 10.2495/BIM210121.
J. L. Rodríguez, «Generative Design for Constructability improvements with BIM|Lean approach», Master thesis: Bologna Process Level II Master Dissertation, Univerza v Ljubljani Fakulteta za gradbeništvo in geodezijo, Ljubljana, 2021. [En línea]. Disponible en: https://bimaplus.org/wp-content/uploads/2021/10/2021-JoseHernandez-Dissertation.pdf
L. García, M. Domínguez, y M. del M. Espinosa, «Diseño generativo: el estado del arte», Técnica Industrial, n.o 327, pp. 44-49, nov. 2020, doi: 10.23800/10417.
J. Cui y M. X. Tang, «Towards generative systems for supporting product design», International Journal of Design Engineering, vol. 7, n.o 1, pp. 1-16, ene. 2017, doi: 10.1504/IJDE.2017.085639.
E. Gascón Alvarez, N. L. Stamler, C. T. Mueller, y L. K. Norford, «Shape optimization of chilled concrete ceilings – Reduced embodied carbon and enhanced operational performance», Building and Environment, vol. 221, p. 109330, ago. 2022, doi: 10.1016/j.buildenv.2022.109330.
J. Saadi y M. Yang, «Observations on the implications of generative design tools on design process and designer behaviour», Proceedings of the Design Society, vol. 3, pp. 2805-2814, jul. 2023, doi: 10.1017/pds.2023.281.
W. Liao, X. Lu, Y. Fei, Y. Gu, y Y. Huang, «Generative AI design for building structures», Automation in Construction, vol. 157, p. 105187, ene. 2024, doi: 10.1016/j.autcon.2023.105187.
S. BuHamdan, A. Alwisy, y A. Bouferguene, «Generative systems in the architecture, engineering and construction industry: A systematic review and analysis», International Journal of Architectural Computing, vol. 19, n.o 3, pp. 226-249, sep. 2021, doi: 10.1177/1478077120934126.
S. Abrishami, J. S. Goulding, F. P. Rahimian, y A. Ganah, «Integration of BIM and generative design to exploit AEC conceptual design innovation», Journal of Information Technology in Construction (ITcon), vol. 19, n.o 21, pp. 350-359, sep. 2014.
A. Leitão, R. Fernandes, y L. Santos, «Pushing the Envelope: Stretching the Limits of Generative Design», en Blucher Design Proceedings, Blucher Proceedings, ene. 2015, pp. 235-238. doi: 10.5151/despro-sigradi2013-0043.
J. H. Holland, «Genetic Algorithms and Adaptation», en Adaptive Control of Ill-Defined Systems, O. G. Selfridge, E. L. Rissland, y M. A. Arbib, Eds., Boston, MA: Springer US, 1984, pp. 317-333. doi: 10.1007/978-1-4684-8941-5_21.
N. Rane, «Transforming Structural Engineering through ChatGPT and Similar Generative Artificial Intelligence: Roles, Challenges, and Opportunities», SSRN, sep. 2023, doi: 10.2139/ssrn.4603242.
M. Soori y F. K. G. Jough, «Artificial Intelligent in Optimization of Steel Moment Frame Structures: A Review», International Journal of Structural and Construction Engineering, vol. 18, n.o 3, pp. 141-158, mar. 2024.
M. Afzal, R. Y. M. Li, M. F. Ayyub, M. Shoaib, y M. Bilal, «Towards BIM-Based Sustainable Structural Design Optimization: A Systematic Review and Industry Perspective», Sustainability, vol. 15, n.o 20, Art. n.o 20, ene. 2023, doi: 10.3390/su152015117.
G. Díaz et al., «Aplicaciones del diseño generativo en la ingeniería estructural», Revista ingeniería de construcción, vol. 36, n.o 1, pp. 29-47, abr. 2021, doi: 10.4067/S0718-50732021000100029.
J. L. Pardal-Refoyo, «Los artículos de revisión. Orientaciones para los autores y revisores», Revista ORL, vol. 14, n.o 3, Art. n.o 3, sep. 2023, doi: 10.14201/orl.31646.
A. Vuotto, V. Di Césare, y N. Pallotta, «Fortalezas y debilidades de las principales bases de datos de información científica desde una perspectiva bibliométrica», Palabra clave, vol. 10, n.o 1, p. e101, oct. 2020, doi: 10.24215/18539912e101.
M. Amezcua, «La Búsqueda Bibliográfica en diez pasos», Index de Enfermería, vol. 24, n.o 1-2, pp. 14-14, jun. 2015, doi: 10.4321/S1132-12962015000100028.
G. A. S. Tajes, J. M. Salgado, F. A. N. D´agostino, y N. A. Vizioli, «Búsqueda de información científica en ciencias de la salud: conceptos, herramientas y valoración de los resultados.», Revista ConCiencia, vol. 8, n.o 2, Art. n.o 2, jul. 2023, doi: 10.32654/ConCiencia.8-2.1.
A. Kralj y D. Skejić, «Generative Design of Structural Steel Joints», Advances in Civil and Architectural Engineering, vol. 12, n.o 23, Art. n.o 23, 2021.
European Committee for Standardization (CEN) 2014, «Eurocode 3: Design of Steel Structures - Part 1-8: Design of Joints (EN 1993-1-8:2005+AC:2009)».
M. Wilhelmsen, «Structural Optimization of Pile Foundation with the use of Generative Design and Machine Learning.», Master thesis, NTNU, 2020. Accedido: 6 de mayo de 2024. [En línea]. Disponible en: https://ntnuopen.ntnu.no/ntnu-xmlui/handle/11250/2779991
D. Henríquez, R. F. Herrera, y J. C. Vielma, «Method for Designing Prequalified Connections Using Generative Design», Buildings, vol. 12, n.o 10, Art. n.o 10, oct. 2022, doi: 10.3390/buildings12101579.
F. Alkhatib, N. Kasim, S. Qaidi, H. M. Najm, y M. M. Sabri Sabri, «Wind-resistant structural optimization of irregular tall building using CFD and improved genetic algorithm for sustainable and cost-effective design», Front. Energy Res., vol. 10, oct. 2022, doi: 10.3389/fenrg.2022.1017813.
E. Duong, «Automation of Steel Shear Connection Design using Generative Design», Master of Science, University of Alberta, 2023. doi: 10.7939/r3-82y2-6e12.
F. Alsakka, A. Haddad, F. Ezzedine, G. Salami, M. Dabaghi, y F. Hamzeh, «Generative design for more economical and environmentally sustainable reinforced concrete structures», Journal of Cleaner Production, vol. 387, p. 135829, feb. 2023, doi: 10.1016/j.jclepro.2022.135829.
F. Ljubinković, J. Conde, H. Gervásio, y L. S. da Silva, «A methodology to assess structural design efficiency», Structures, vol. 58, p. 105366, dic. 2023, doi: 10.1016/j.istruc.2023.105366.
Y. Feng, Y. Fei, Y. Lin, W. Liao, y X. Lu, «Intelligent Generative Design for Shear Wall Cross-Sectional Size Using Rule-Embedded Generative Adversarial Network», Journal of Structural Engineering, vol. 149, n.o 11, p. 04023161, nov. 2023, doi: 10.1061/JSENDH.STENG-12206.
K.-H. Chang y C.-Y. Cheng, «Learning to Simulate and Design for Structural Engineering».
J.-H. Jeong y H. Jo, «Deep reinforcement learning for automated design of reinforced concrete structures», Computer-Aided Civil and Infrastructure Engineering, vol. 36, n.o 12, pp. 1508-1529, 2021, doi: 10.1111/mice.12773.
Published
How to Cite
Issue
Section
Copyright (c) 2026 Copyright will be assigned automatically to Gino Giuseppe Pannillo Majano, Juan Carlos Vielma Pérez when this is published.

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The opinions expressed by the authors do not necessarily reflect the position of the editor of the publication or UCLA. The total or partial reproduction of the texts published here is authorized, provided that the complete source and electronic address of this journal is cited. Authors have the right to use their articles for any purpose as long as it is done nonprofit. The authors can post on the internet or any other media the final approved version of their work.


.png)



