The properties of geometrically modelling computational schemes for building structures


For launching a project on a structural object, the calculation of building structures stands as one of the most important stages of project development. In order to correctly analyse structural behaviour, determine the stress-strain state and solve design or inspection problems, the designer is forced to adequately formalize the actual structure turning it into a faultless computational scheme. Virtual testing is one of the main features of the single graphical-information model. Interoperable systems for three-dimensional modelling and analysis, calculation and design ensure smooth data transfer between the physical and computational model. Modern object-modelling techniques and integrated analysis systems allow achieving the defined goal. The article deals with the forms of data exchange, the developmental features of the designed and computational (analysis) BIM model, the integrated design process of CAD/CAE as well as the conversion problems of the physical and computational model.

First published online 14 January 2021

Keyword : BIM, CAD, physical model, analysis model, software integration

How to Cite
Popov, V., Kriksunov, E., & Grigorjeva, T. (2020). The properties of geometrically modelling computational schemes for building structures. Engineering Structures and Technologies, 12(1), 32-38.
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Dec 31, 2020
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Eastman, C. M., Sacks, R., Liston, K., & Teicholz, P. (2011). BIM handbook - a guide to Building Information Modeling for owners, managers, designers, engineers, and contractors (2nd ed.). John Wiley & Sons.

El-Diraby, T., Krijnen, T., & Papagelis, M. (2017). BIM-based collaborative design and socio-technical analytics of green buildings. Automation in Construction, 82, 59–74.

Ford, S., Aouad, G., Brandon, P., Brown, F., Child, T., Cooper, G., Kirkham, J., Oxman, R., & Young, B. (1994). The object oriented modelling of building design concepts. Building and Environment, 29(4), 411–419.

Hasan, A. M. M., Torky, A. A., & Rashed, Y. F. (2019). Geometrically accurate structural analysis models in BIM-centered software. Automation in Construction, 104, 299–321.

Hoekstra, J. (2003). Big Buzz for BIM. Architecture, 92(7), 79–82.

Jeong, Y.-S., Sacks, R., Kaner, I., & Eastman, C. M. (2009). Benchmark tests for BIM data exchanges of precast concrete. Automation in Construction, 18(4), 469–484.

Kouhestani, S., & Nik-Bakht, M. (2020). IFC-based process mining for design authoring. Automation in Construction, 112, 103069.

Miettinen, R., & Paavola, S. (2014). Beyond the BIM utopia: Approaches to the development and implementation of building information modeling. Automation in Construction, 43, 84–91.

Migilinskas, D., Popov, V., Juocevičius, V., & Ustinovičius, L. (2013). The benefits, obstacles and problems of practical BIM implementation. Procedia Engineering, 57, 767–774.

Oraskari, J., & Törmä, S. (2015). RDF-based signature algorithms for computing differences of IFC models. Automation in Construction, 57, 213–221.

Popovas, V., Jarmolajevas, A., & Grigorjeva, T. (2003). Šiuolaiknės automatizuoto projektavimo sistemos. Nauja statyba, 6–7, 26–29, 40–41 (in Lithuanian).

Popovas, V., Ustinovičius, L., & Mikalauskas, S. (2004, May). Technique for computer aided evaluation of economic indicators of a construction project. In The 8th International Conference “Modern Building Materials, Structures and Techniques”: Selected papers (Vol. 1., pp. 242–248). Vilnius, Lithuania. Technika.

Popov, V., & Grigorjeva, T. (2007). Statybinių konstrukcijų projektavimas taikant integruotas kompiuterinio projektavimo sistemas. Pažangioji statyba: pranešimų medžiaga (pp. 30–39). Technologija (in Lithuanian).

Popov, V., & Grigorjeva, T. (2010). Integrated automated design of building structures. Engineering Structures and Technologies, 2(1), 31–37.

Succar, B. (2009). Building information modelling framework: A research and delivery foundation for industry stakeholders. Automation in Construction, 18(3), 357–375.

Tang, P., Akinci, B., Lipman, R., Lytle, A., & Huber, D. (2010). Automatic reconstruction of as-built building information models from laser-scanned point clouds: a review of related techniques. Automation in Construction, 19(7), 829–843.

Zhu, Y. (2015). Ontology to support multi-objective integrated analyses for sustainable construction: A conceptual framework. In R. R. A. Issa & I. Mutis (Eds.), Ontology in the AEC industry: A decade of research and development in architecture, engineering, and construction (pp. 73–95). ASCE.

Watson, A. (2011). Digital buildings – challenges and opportunities. Advanced Engineering Informatics, 25(4), 573–581.