TY - JOUR
T1 - Automatic and optimal rebar layout in reinforced concrete structure by decomposed optimization algorithms
AU - Liu, Jiepeng
AU - Li, Sheng
AU - Xu, Chengran
AU - Wu, Zhou
AU - Ao, Nian
AU - Chen, Y. Frank
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/6
Y1 - 2021/6
N2 - In structural designs, the rebar layout often relies on the empirical knowledge from engineers, resulting in higher labor cost, low efficiency, and low accuracy. This paper focuses on automatically designing collision-free rebar layout in Reinforced Concrete (RC) structures. Due to a great number of rebars with various sizes and shapes, the rebar layout task easily suffers from congestions and collisions. An improved method by decomposing the original layout task into simple subtasks is proposed, and each rebar layout subtask is modeled as an optimal trajectory planning problem with collision-free constraints. The Particle Swarm Optimization (PSO), Differential Evolution (DE), and Neighborhood Field Optimization (NFO) algorithms are respectively utilized in the decomposed method to complete subtasks. The PSO, DE, and NFO algorithms are verified on beam-column joints in a RC structure; and the performance with respect to computation time and path length is evaluated. The experimental results show that the decomposed optimization is effective for automatic rebar layout and the PSO is the best algorithm.
AB - In structural designs, the rebar layout often relies on the empirical knowledge from engineers, resulting in higher labor cost, low efficiency, and low accuracy. This paper focuses on automatically designing collision-free rebar layout in Reinforced Concrete (RC) structures. Due to a great number of rebars with various sizes and shapes, the rebar layout task easily suffers from congestions and collisions. An improved method by decomposing the original layout task into simple subtasks is proposed, and each rebar layout subtask is modeled as an optimal trajectory planning problem with collision-free constraints. The Particle Swarm Optimization (PSO), Differential Evolution (DE), and Neighborhood Field Optimization (NFO) algorithms are respectively utilized in the decomposed method to complete subtasks. The PSO, DE, and NFO algorithms are verified on beam-column joints in a RC structure; and the performance with respect to computation time and path length is evaluated. The experimental results show that the decomposed optimization is effective for automatic rebar layout and the PSO is the best algorithm.
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U2 - 10.1016/j.autcon.2021.103655
DO - 10.1016/j.autcon.2021.103655
M3 - Article
AN - SCOPUS:85102134225
SN - 0926-5805
VL - 126
JO - Automation in Construction
JF - Automation in Construction
M1 - 103655
ER -