Algorithmic-Aided Approach for the Design and Evaluation of Curvilinear Steel Bar Structures of Unit Roofs

Abstract

Rationalization in structural design in the field of steel structures mostly consists inreducing structural material. The aim of this work was to develop an algorithmic-aided, original and practical approach to shaping curvilinear steel bar structures of modular roofs, enabling their optimization. The first stage of shaping consists in creating algorithms that define the structures of shelters made of four roof units. Algorithmic definitions of the structures made it possible to obtain many variants of the roof structures with the adopted preliminary criteria. In order to evaluate the effectiveness of the individual variants, the genetic optimizations of the structures’ forms were carried out. Assuming that the structures were loaded with self-weights, the cross-sections of the structures’ members were optimized with the permissible deflections, while the structures’ weights were the optimization criteria. This allowed us to eliminate the design variants unfavorable in terms of shape and weight. In contrast, the structures with the most advantageous properties were then optimized for weight under snow and wind loads. The research allowed us to notice how the shapes of the structures influenced their efficiency. The dual approach proposed for shaping, which takes advantage of the generative design and consistent flow of information during shaping, allowed us to achieve better solutions compared to the traditional approach.

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“…The optimization of structures involves finding the most cost-effective structural design by minimizing the amount of material required that, at the same time, meets the predefined criteria, such as strength, stability, and displacements within the structural design and safety standards. Although research on structural optimization dates back to the 1970s [5][6][7], only in the last two decades has there been significant progress in its development [8][9][10][11][12], largely due to the implementation of artificial intelligence techniques such as genetic algorithms. However, most of the research focuses on steel [13][14][15][16] and concrete [17][18][19][20] structures, with timber structures [21][22][23] largely ignored by the scientific community.…”

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“…Esta interfaz permite a los usuarios ampliar las funciones del software y crear herramientas personalizadas. Así mismo, Dynamo está siendo utilizado por los usuarios https://doi.org/10.37787/pakamuros-unj.v11i1.359 _______________________________________________________________________________________ como un plugin, o complemento, para Revit y permite generar geometrías matemáticas complejas mediante bloques de código y parámetros, permitiendo el cambio automático de estos parámetros desde el software BIM (Dzwierzynska & Lechwar, 2022;Kensek, 2014). Esto quiere decir que, en lugar de digitar un código, la interacción entre los usuarios y Dynamo, genera una secuencia de comandos manipulando elementos gráficos llamados nodos (Wehbe & Shahrour, 2019).…”

Characterization and Modelling of Manufacturing–Microstructure–Property–Mechanism Relationship for Advanced and Emerging Materials

“…In their study, Zhang et al [ 38 ] focused on the vibration characteristics of a laminated composite double cylindrical shell system (LCDCSS), coupled with a variable number of annular plates. Dzwierzynska and Lechwar [ 39 ] proposed an algorithmic-aided approach for the design and optimization of the curvilinear steel bar structures of unit roofs, and their structural analysis was further verified by an FEM analysis, taking both the permanent and environmental loads into account. With the help of a computational fluid dynamics (CFD) model, Li et al [ 40 ] simulated a high-pressure hydrogen flow through their newly proposed Tesla-type depressurization structure.…”