ARCHITECTURAL ENGINEERING IN THE DIGITAL ERA: PARAMETRIC DESIGN AND STRUCTURAL RATIONALIZATION
Abstract
Architectural engineering in the digital era is increasingly shaped by parametric design methodologies that enable complex form generation and performance-driven optimization. Rapid advancements in computational tools have transformed design processes, yet a persistent gap remains between architectural exploration and structural rationalization, often resulting in inefficiencies and post-design adjustments. This study aims to develop an integrated computational framework that aligns parametric design with structural performance, ensuring that architectural forms are both innovative and structurally feasible. A computational design-based methodology was employed, combining parametric modeling, finite element analysis, and algorithmic optimization across representative architectural typologies. Iterative workflows were implemented to establish continuous feedback between geometric parameters and structural responses. Results indicate that integrated parametric-structural models achieve higher structural efficiency, reduced material consumption, and improved deformation control compared to conventional and non-integrated approaches. Statistical analysis confirms significant performance improvements, while case-based validation demonstrates strong alignment between simulated and expected structural behavior. Findings further reveal that real-time integration enhances design adaptability and decision-making efficiency. This study concludes that the integration of parametric design and structural rationalization represents a robust and scalable paradigm for contemporary architectural engineering, offering significant implications for sustainability, performance optimization, and interdisciplinary collaboration.
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References
Alexopoulos, M. J., Iliopoulou, T., Modé, P., Istrati, D., Koutsoyiannis, D., Królewicz, S., Graf, R., Kaczmarek, L., & R?czkowski, W. (2025). Flood risk assessment of cultural heritage sites near lakes via advanced hydrodynamic modeling and digital technologies. Results in Engineering, 28, 107977. https://doi.org/https://doi.org/10.1016/j.rineng.2025.107977
Ashraf, N., & Abdin, A. R. (2024). Biomimetic design synthesis and digital optimization of building shading skin: A novel conceptual framework for enhanced energy efficiency. Energy and Buildings, 323, 114824. https://doi.org/https://doi.org/10.1016/j.enbuild.2024.114824
Ceccarelli, U. (2024). Advancing Digital Architecture in the Metaverse: A Case Study of Pini Group’s Helmallery. Procedia Structural Integrity, 64, 2214–2221. https://doi.org/https://doi.org/10.1016/j.prostr.2024.09.346
Ceylan, S., ?ahin, P., Seçmen, S., Somer, M. E., & Süher, H. K. (2024). The contribution of digital tools to architectural design studio: A case study. Ain Shams Engineering Journal, 15(7), 102795. https://doi.org/https://doi.org/10.1016/j.asej.2024.102795
Chang, D., Wang, L., Xiang, Y., Zhu, X., & Lee, C.-H. (2025). Exploring human perception in interactive digital advertising: A Genetic-Kansei engineering approach with human-AI collaboration. Knowledge-Based Systems, 311, 113072. https://doi.org/https://doi.org/10.1016/j.knosys.2025.113072
Chen, C.-M., & Chen, X.-X. (2024). An associative text analyzer to facilitate effectiveness of exploring historical texts for digital humanities. Aslib Journal of Information Management, 78(1), 93–119. https://doi.org/https://doi.org/10.1108/AJIM-01-2024-0014
Firoozi, A. A., & Firoozi, A. A. (2025). Digital integration in eco-construction 2.0: Advancing sustainability through technology. Sustainable Futures, 10, 101310. https://doi.org/https://doi.org/10.1016/j.sftr.2025.101310
Frangedaki, E., Sardone, L., Marano, G. C., & Lagaros, N. D. (2023). Optimisation-driven design in the architectural, engineering and construction industry. Proceedings of the Institution of Civil Engineers - Structures and Buildings, 176(12), 998–1009. https://doi.org/https://doi.org/10.1680/jstbu.22.00032
Goldbach, A.-K., & Lázaro, C. (2024). CAD-integrated parametric design and analysis of lightweight shell structures. Structures, 64, 106566. https://doi.org/https://doi.org/10.1016/j.istruc.2024.106566
Govindasamy, A., Rajeswari, D., Srinivasan, R., & Arivarasi, A. (2024). Cost-Effective digital twin Design for entertainment Enterprise’s through Machine learning. Entertainment Computing, 50, 100648. https://doi.org/https://doi.org/10.1016/j.entcom.2024.100648
Hadjadji, N., Toulan, N., & Dorra, M. (2024). Impact of digital architecture: The impact of digital technology on ecological formations and its effect on determinants of identity and culture in architectural design. Journal of Engineering Research, 12(3), 285–293. https://doi.org/https://doi.org/10.1016/j.jer.2023.09.004
Huang, Q., Zeng, W., Liu, J., Zhang, Z., Deng, J., Qiu, Z., Xu, L., Wei, Z., Lu, Q., Gong, L., Shi, C., & Zhong, X. (2025). Shaping the future of nuclear reactors with digital twins: Current developments and perspectives. Applied Energy, 402, 126922. https://doi.org/https://doi.org/10.1016/j.apenergy.2025.126922
Huang, Z., Fey, M., Liu, C., Beysel, E., Xu, X., & Brecher, C. (2023). Hybrid learning-based digital twin for manufacturing process: Modeling framework and implementation. Robotics and Computer-Integrated Manufacturing, 82, 102545. https://doi.org/https://doi.org/10.1016/j.rcim.2023.102545
Idrissi Kaitouni, S., Gargab, F.-Z., Es-sakali, N., Mghazli, M. O., El Mansouri, F., Jamil, A., & Ahachad, M. (2025). Digital workflow for nearly zero-energy high-rise office building design optimization at the district scale in Mediterranean context. Energy and Built Environment, 6(6), 1025–1038. https://doi.org/https://doi.org/10.1016/j.enbenv.2024.04.008
Jin, C., Lee, Y., Lee, S., & Hyun, C. (2024). Lightweighting Process of Digital Twin Information Models for Smart City Services. KSCE Journal of Civil Engineering, 28(4), 1304–1320. https://doi.org/https://doi.org/10.1007/s12205-024-2354-z
Jin, L., Zhai, X., Wang, K., Zhang, K., Wu, D., Nazir, A., Jiang, J., & Liao, W.-H. (2024). Big data, machine learning, and digital twin assisted additive manufacturing: A review. Materials & Design, 244, 113086. https://doi.org/https://doi.org/10.1016/j.matdes.2024.113086
Kobayashi, K., Daniell, J., & Alam, S. B. (2024). Improved generalization with deep neural operators for engineering systems: Path towards digital twin. Engineering Applications of Artificial Intelligence, 131, 107844. https://doi.org/https://doi.org/10.1016/j.engappai.2024.107844
Kondo, R. E., Andrade, W. J., de Mello Henequim, C., Lazzaretti, A. E., de Souza Britto, A., de Freitas Rocha Loures, E., Santos, E. A. P., & Reynoso-Meza, G. (2024). An industrial edge computing architecture for Local Digital Twin. Computers & Industrial Engineering, 193, 110257. https://doi.org/https://doi.org/10.1016/j.cie.2024.110257
Li, J. (2025). Green building design and energy efficiency improvement in architectural engineering. Results in Engineering, 27, 106973. https://doi.org/https://doi.org/10.1016/j.rineng.2025.106973
Li, L., Meng, Q., Li, S.-E., & Chen, Z. (2025). Rooted or expansive? The impact of digital-physical technological integration on corporate knowledge breadth. International Review of Economics & Finance, 104, 104602. https://doi.org/https://doi.org/10.1016/j.iref.2025.104602
Lin, X., Chen, W., Zhou, Z., Li, J., Zhao, Y., & Zhang, X. (2025). A five-dimensional digital twin framework driven by large language models-enhanced RL for CNC systems. Robotics and Computer-Integrated Manufacturing, 95, 103009. https://doi.org/https://doi.org/10.1016/j.rcim.2025.103009
Liu, C., Wang, W., Wang, Z., Ding, B., Wu, Z., & Feng, J. (2024). Data-driven modeling and fast adjustment for digital coded metasurfaces database: Application in adaptive electromagnetic energy harvesting. Applied Energy, 365, 123303. https://doi.org/https://doi.org/10.1016/j.apenergy.2024.123303
Mavromatidis, L. (2025). Constructal thermodynamics and its semantic ontology in autopoietic, digital, and computational architectural and urban space open systems. BioSystems, 249, 105404. https://doi.org/https://doi.org/10.1016/j.biosystems.2025.105404
Mehranfar, M., Braun, A., & Borrmann, A. (2024). From dense point clouds to semantic digital models: End-to-end AI-based automation procedure for Manhattan-world structures. Automation in Construction, 162, 105392. https://doi.org/https://doi.org/10.1016/j.autcon.2024.105392
Opoku, D.-G. J., Perera, S., Osei-Kyei, R., Rashidi, M., Bamdad, K., & Famakinwa, T. (2024). Digital twin for indoor condition monitoring in living labs: University library case study. Automation in Construction, 157, 105188. https://doi.org/https://doi.org/10.1016/j.autcon.2023.105188
Ronga, D., Mongelli, G., Faehn, E., Girard, P., & Virazel, A. (2025). Analog to digital memory modeling for test. Microprocessors and Microsystems, 118, 105189. https://doi.org/https://doi.org/10.1016/j.micpro.2025.105189
Rumanti, A. A., Daryanto, Y., Amelia, M., Rizaldi, A. S., Zulkarnain, I., & Andrawina, L. (2025). The role of organizational and stakeholder factors in strengthening digital literacy and communication for edu-tourism. Journal of Open Innovation: Technology, Market, and Complexity, 11(3), 100618. https://doi.org/https://doi.org/10.1016/j.joitmc.2025.100618
Shahruddin, S., Sonet, U. N., Azmi, A., & Zainordin, N. (2024). Traversing the complexity of digital construction and beyond through soft skills: experiences of Malaysian architects. Engineering, Construction and Architectural Management, 32(11), 7373–7398. https://doi.org/https://doi.org/10.1108/ECAM-01-2024-0147
Shehadeh, A., Alshboul, O., Aburamadan, R., Arar, M., Abuhazeem, S., Khazaleh, K., Cotella, V. A., & Moghayedi, A. (2025). Integrating climate resilience and digital twin technologies in housing: A comparative analysis and sustainable design proposal for Jordan and South Africa. Results in Engineering, 28, 108409. https://doi.org/https://doi.org/10.1016/j.rineng.2025.108409
Sifat, M. M. H., Das, S. K., & Choudhury, S. M. (2024). Design, development, and optimization of a conceptual framework of digital twin electric grid using systems engineering approach. Electric Power Systems Research, 226, 109958. https://doi.org/https://doi.org/10.1016/j.epsr.2023.109958
Tran, T., Nguyen, Q., Luu, T., Tran, M., Kua, J., Hoang, T., & Dien, M. (2025). Empowering robotic training with kinesthetic learning and digital twins in human–centric industrial systems. Journal of Industrial Information Integration, 43, 100743. https://doi.org/https://doi.org/10.1016/j.jii.2024.100743
Vijay, M. M., Kumar, O. P., Francis, S. A. J., Stalin, A. D., & Vincent, S. (2024). Enhancing high-speed digital systems: MVL circuit design with CNTFET and RRAM. Journal of King Saud University - Computer and Information Sciences, 36(4), 102033. https://doi.org/https://doi.org/10.1016/j.jksuci.2024.102033
Wang, S., Lin, D., & Sun, L. (2023). Human-cyber-physical system for post-digital design and construction of lightweight timber structures. Automation in Construction, 154, 105033. https://doi.org/https://doi.org/10.1016/j.autcon.2023.105033
Wang, T., Liu, Z., Wang, L., Li, M., & Wang, X. V. (2025). A design framework for high-fidelity human-centric digital twin of collaborative work cell in Industry 5.0. Journal of Manufacturing Systems, 80, 140–156. https://doi.org/https://doi.org/10.1016/j.jmsy.2025.02.018
Wang, W., Xu, K., Song, S., Bao, Y., & Xiang, C. (2024). From BIM to digital twin in BIPV: A review of current knowledge. Sustainable Energy Technologies and Assessments, 67, 103855. https://doi.org/https://doi.org/10.1016/j.seta.2024.103855
Wang, X., Yang, X., Duan, J., Xu, L., Khan, M. I., Tao, C., & Huang, Y. (2025). A digital twin integrated smart-liner for visualization monitoring of oil and gas pipeline infrastructure. Applied Energy, 400, 126558. https://doi.org/https://doi.org/10.1016/j.apenergy.2025.126558
Wu, S., Lu, W.-Z., Qin, C., Wen, B., Wu, D., & Xiang, Y. (2023). A goal-oriented planning approach for two-dimensional cutting components in architectural design: Coupling BIM and Parametric design (PD). Journal of Building Engineering, 76, 107156. https://doi.org/https://doi.org/10.1016/j.jobe.2023.107156
Xie, H., Xin, M., Lu, C., & Xu, J. (2023). Knowledge map and forecast of digital twin in the construction industry: State-of-the-art review using scientometric analysis. Journal of Cleaner Production, 383, 135231. https://doi.org/https://doi.org/10.1016/j.jclepro.2022.135231
Xiong, Q., Yang, J., Zhang, X., Deng, Y., Gui, Y., & Guo, X. (2025). The influence of digital transformation on the total factor productivity of enterprises: the intermediate role of human-machine cooperation. Journal of Innovation & Knowledge, 10(4), 100736. https://doi.org/https://doi.org/10.1016/j.jik.2025.100736
Xu, P., Zhao, P., Liu, Y., & Liu, N. (2024). Reciprocal frame (RF) architecture design based on statistical analysis of geometrical form parameters from built cases and parametric simulations. Construction and Building Materials, 447, 138082. https://doi.org/https://doi.org/10.1016/j.conbuildmat.2024.138082
Yazdani Sarvestani, H., Patel, J., Shashoua, A., Ravanbakhsh, H., Taheri, S., Gholipour, J., & Ashrafi, B. (2024). Digital precision in engineered ceramics: Tailoring toughness and flexibility through interlocking strategies. Journal of the European Ceramic Society, 44(10), 6000–6012. https://doi.org/https://doi.org/10.1016/j.jeurceramsoc.2024.03.035
Ying, C., El-Hamalawi, A., Chen, S., & Han, D. (2025). Digital reconstruction and geometrical model updating of large-scale bridge structures: a case study of Baijusi bridge. Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction, 178(3), 167–177. https://doi.org/https://doi.org/10.1680/jsmic.24.00012
Zhao, W., & Hohman, A. (2025). Resurrecting Antonio Sant’Elia’s futurist vision: A journey through digital modeling and virtual reality. Digital Applications in Archaeology and Cultural Heritage, 39, e00473. https://doi.org/https://doi.org/10.1016/j.daach.2025.e00473
Zhao, X., He, D., Fang, Z., Chen, H., Zhang, Y., Zeng, L., Pan, H., & Zhang, Z. (2025). Digital twin-enhanced self-powered sensing anomaly detection system for intelligent rail transportation. Nano Energy, 144, 111338. https://doi.org/https://doi.org/10.1016/j.nanoen.2025.111338
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Copyright (c) 2026 Veronika Widi Prabawasari, Haruto Takahashi, Faizal Baharuddin, Anna Schneider
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