| Summary: | 碩士 === 國立臺灣科技大學 === 營建工程系 === 97 === In the traditional reinforce concrete design, a lot of initial values of parameters are set based on the engineers' experience, such as diameter of the pillar, deep of beam, amount of reinforcing bar, etc. Since the design parameters affect the performance and the engineers usually take a conservative approach, the overall design may not necessarily be optimal.
For example, increasing the reinforcing bar amount can raise strength of RC pillar. Opposite to concrete, reinforcing bars are much expensive. Without appropriate design, even using the same number of reinforcing bars can not raise the strength. It is not economical. It is not easy to find appropriate design parameters in the large search space. This study considers diameter of pillar, number of reinforcing bars, concrete’s strength and reinforcing bar strength as a parameter to calculate economical design parameters and conforms with the design rules. The proposed methods include Genetic Algorithm and Particle Swarm Optimization Algorithm.
This study is to apply two algorithms to find the optimal beam design which is based on ACI design rule, and a pillar design which is based on AASHTO design rule. The goal is to find the optimal design parameters and conforms with the design rules. This research also compares the result of two models.
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