Computational Intelligence Applied in Optimal Design of Wooden Plane Trusses

Christofóro, André Luis; Moraes, Matheus Henrique Morato de; Fraga, Iuri Fazolin; Junior, Wanderlei Malaquias Pereira; Lahr, Francisco Antônio Rocco

doi:10.1590/1809-4430-eng.agric.v42nepe20210123/2022

Cited by 6 publications

(3 citation statements)

References 32 publications

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“…With the evolution of the sizing procedure from computational methods, structural optimization has become a viable tool, applied to various structural systems, including timber structures such as beams [30][31][32], frames [33], and trusses [29,[34][35][36].…”

Section: Introductionmentioning

confidence: 99%

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Comparative Analysis of the Mechanical Performance of Timber Flat Truss Typologies for Different Strength Classes via Optimization Algorithm

Moraes,

Fraga,

Menezes

et al. 2023

Buildings

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This study aimed to compare the mechanical performance of two truss typologies, the modified Fan and Howe trusses, using five different wood species: Cambará-rosa, Cupiúba, Angelim-pedra, Garapa, and Jatobá. The spans considered were 6, 9, 12, and 15 m, and the optimization algorithm used was a swarm intelligence algorithm to minimize the structure weight. The study found that wood is a sustainable and viable option for truss constructions, with different wood species having distinct mechanical properties that must be considered when designing the structure. The Howe truss typology presented lower results for the objective function in comparison with the modified Fan truss. The distribution of normal forces in the truss correlated with the characteristic strength in compression and tensile of the species. The Howe truss typology presented a larger amplitude in relation to the modified Fan truss typology in most of the conditions adopted for the Ultimate Limit State constraints. Constraints associated with deflection in the immediate condition were observed to limit the optimization process. The study used the matrix analysis method to evaluate internal efforts and nodal displacements in the trusses. In summary, this study demonstrates the importance of considering all constraints when dimensioning timber structures and the benefits of using different wood species for sustainable construction.

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Section: Introductionmentioning

confidence: 99%

“…Different swarm intelligence-based algorithms have been introduced in optimization algorithm applications, such as the Artificial Bee Colony (ABC), the Ant Colony Optimization (ACO) Algorithm, the Bat Algorithm (BA), Particle Swarm Optimization (PSO), and the Firefly Algorithm (FA). FA is widely used in structural optimization processes [29,34,[47][48][49].…”

mentioning

confidence: 99%

Comparative Analysis of the Mechanical Performance of Timber Flat Truss Typologies for Different Strength Classes via Optimization Algorithm

Moraes,

Fraga,

Menezes

et al. 2023

Buildings

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“…Cardoso et al [17] evaluated the static and dynamic wind effect applying structural optimization of concrete plane frames. Christoforo et al [18] and Moraes et al [19] applied optimization for wood truss roof structures.…”

Section: Introductionmentioning

confidence: 99%

Optimum design of precast and prestressed beams with focus on CO2 emission reduction

Moraes

Junior²,

Almeida

et al. 2022

Rev. IBRACON Estrut. Mater.

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Among the main contributors to CO2 emissions on the ozone layer, the construction industry contributes with a significant portion. This emission is generated largely by applying concrete construction systems and their variations. Therefore, it is important to use tools that allow the development of projects which mitigate the effects of harmful gas emissions into the atmosphere. Thus, this study applied an optimization algorithm called Firefly Algorithm (FA) to design precast and prestressed rectangular beams focusing on reducing CO2 emissions in the structural design phase. The Objective Function (OF) was defined as the total weight of CO2 emitted in each construction phase (production, transportation, and placement) and the structural design constraints are based on the design criteria established in ABNT NBR 6118. The problem optimization’s variables are geometric properties and mechanical beam's conditions, where the beam height, beam width, the proportion of height generates prestressing eccentricity, and the proportion of prestressing load were considered as design variables. Ten beams were analyzed, with different loadings, where each of these beams was submitted to the optimization process thirty times. For the proposed conditions, the ten beams had an average CO2 emission of 3282.59 kg, maximum and minimum carbon emission of 3630.52 kg and 2910.67 kg, respectively. The study resulted in a feasibility rate higher than 90%, showing that the optimization tool was efficient in the structural design phase focusing on sustainability. Concerning carbon emission, it is possible to verify a relationship between the increase of emission and the load since element with greater inertia tend to emit a greater amount of CO2. It was also possible to determine a regression between carbon emission and beam load.

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Improved differential evolution algorithm based convolutional neural network for emotional analysis of music data

Li,

Soradi-Zeid,

Yousefpour

et al. 2024

Applied Soft Computing

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Computational Intelligence Applied in Optimal Design of Wooden Plane Trusses

Cited by 6 publications

References 32 publications

Comparative Analysis of the Mechanical Performance of Timber Flat Truss Typologies for Different Strength Classes via Optimization Algorithm

Comparative Analysis of the Mechanical Performance of Timber Flat Truss Typologies for Different Strength Classes via Optimization Algorithm

Optimum design of precast and prestressed beams with focus on CO2 emission reduction

Improved differential evolution algorithm based convolutional neural network for emotional analysis of music data

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