Optimization of slender reinforced concrete columns subjected to biaxial bending using genetic algorithms

Pires, Susana; Silva, Maria Cecília Amorim Teixeira da

doi:10.1590/s1983-41952021000600010

Cited by 3 publications

(2 citation statements)

References 32 publications

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“…𝑓𝑓 𝑞𝑞 ≤ 𝑆𝑆 350 (16) Where 𝜓𝜓 𝐴𝐴 is the weighting coefficient for live load; 𝑇𝑇 1 is the time relative to cutting the strands; 𝑇𝑇 2 is the time relative to performing the cover or placing other dead loads in the system; and 𝑇𝑇 5 corresponds to the creep coefficient at each time informed.…”

Section: Deflection Verification (Sls)mentioning

confidence: 99%

“…Other applications in the field of structural engineering can be observed in Azad et al [10] applied an optimization process for steel trusses under dynamic excitation. Juliani and Gomes [15] optimized reinforced concrete (RC) frames, with genetic algorithms, such as Pires and Silva [16] which optimized slender RC columns subject to biaxial bending. Cardoso et al [17] evaluated the static and dynamic wind effect applying structural optimization of concrete plane frames.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Deflection Verification (Sls)mentioning

confidence: 99%

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.

View full text Add to dashboard Cite

show abstract

Strain regime induced by axial compression in slender reinforced concrete columns using different mathematical approaches

2023

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Metaheuristic-Based Practical Tool for Optimal Design of Reinforced Concrete Isolated Footings: Development and Application for Parametric Investigation

et al. 2022

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In the process of designing an economical structure, safety along with total cost must be balanced. This can be attained by design optimization, however the complex nature of the algorithms involved hinders its application. Further, there is a severe lack of research on the optimization of reinforced concrete (RC) isolated footings. Therefore, the main objective of this research is to develop a user-friendly tool for the optimization of RC isolated footings using advanced metaheuristic algorithms to make it more practical and convenient to adopt for design optimization. For this purpose, a spreadsheet-based interface is created in which input parameters from the original design can be entered to find the best option for the minimum cost design. The Evolutionary Algorithm (EA) and the Genetic Algorithm (GA) are used as metaheuristic techniques for optimization. The original design of four examples from the literature is compared with the optimized design obtained from the developed tool to demonstrate its efficiency. For the considered case studies, cost-saving of up to 44% has been obtained. Furthermore, a parametric investigation for the minimum cost objective using the GA has been performed through which a detailed analysis of geometric reinforcement and material strength variables is conducted. The results lead to the derivation of useful thumb rules for the economical design and proportioning of isolated footings.

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Optimization of slender reinforced concrete columns subjected to biaxial bending using genetic algorithms

Cited by 3 publications

References 32 publications

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

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

Strain regime induced by axial compression in slender reinforced concrete columns using different mathematical approaches

Metaheuristic-Based Practical Tool for Optimal Design of Reinforced Concrete Isolated Footings: Development and Application for Parametric Investigation

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