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DEVELOPMENT OF A GENERATOR OF GLUED LAMINATED TIMBER ELEMENTS SECTIONS USING ARTIFICIAL INTELLIGENCE
Abstract
Within the current framework of approaching different directions of carbon emissions reduction policy, wood fits as an environmentally friendly building material with low production in terms of energy consumption. In this manner, timber combines its qualities such as high strength/weight ratio and rigidity/weight, low specific gravity, recovery/recycling that make it competitive with classic building materials with the demands of climate change green deal. One specific attention has to be given to the design and execution of civil structures in terms of geometric dimensioning of structures, which favors constant rectangular sections, easy to size. This article proposes the initialization of a generator of optimized geometries for glued laminated timber (GLT) structural elements that can provide in a reasonable time through artificial intelligence different solutions. Otherwise, this would have required the use of topological optimization by the finite element method with long analysis times. From a scientific point of view, this approach has been applied only on small part elements in order to solve specific problems of the artificial intelligence-optimized design chain. The results demonstrate the reduction of the amount of material, the improvement of production costs and the optimization of the mechanical behavior of the structural elements in glued laminated timber.
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References4
Mayencourt, P., & Mueller, C. (2019). Structural Optimization of Cross-laminated Timber Panels in One-way Bending. Structures, 18, Pages 48-59, DOI: 10.1016/j.istruc.2018.12.009
de Vito Jr., AF, Vicente, WM, & Xie, YM (2023). Topology optimization applied to the core of structural engineered wood product. Structures, 48, DOI: 10.1016/j.istruc.2023.01.036
Pech, S., Kandler, G., Lukacevic, M., & Fuss, J. (2019). Metamodel assisted optimization of glued laminated timber beams by using metaheuristic algorithms. Engineering Applications of Artificial Intelligence, 79, DOI: 10.1016/j.engappai.2018.12.010
Christoforo, A., de Moraes, M., Fraga, I., Pereira Junior, W., & Lahr, F. (2022). Computational Intelligence Applied in Optimal Design of Wooden Plane Trusses. Eng. agric., Special Issue: Artificial Intelligence, 42, DOI: 10.1590/1809-4430-Eng.Agric.v42nepe20210123/2022
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Number of times cited according to Crossref: 1
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