4.6 Article

Eco-Friendly Design of Reinforced Concrete Retaining Walls: Multi-objective Optimization with Harmony Search Applications

Journal

SUSTAINABILITY
Volume 12, Issue 15, Pages -

Publisher

MDPI
DOI: 10.3390/su12156087

Keywords

reinforced concrete; retaining walls; harmony search algorithm; CO(2)emission; optimization

Funding

  1. National Research Foundation of Korea (NRF) - Korea government (MSIT) [2020R1A2C1A01011131]
  2. Energy Cloud R&D Program through the National Research Foundation of Korea (NRF) - Ministry of Science, ICT [2019M3F2A1073164]

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In this study, considering the eco-friendly design necessities of reinforced concrete structures, the acquirement of minimizing both the cost and the CO(2)emission of the reinforced concrete retaining walls in conjunction with ensuring stability conditions has been investigated using harmony search algorithm. Optimization analyses were conducted with the use of two different objective functions to discover the contribution rate of variants to the cost and CO(2)emission individually. Besides this, the integrated relationship of cost and CO(2)emission was also identified by multi-objective analysis in order to identify an eco-friendly and cost-effective design. The height of the stem and the width of the foundation were treated as design variables. Several optimization cases were fictionalized in relation with the change of the depth of excavation, the amount of the surcharge applied at the top of the wall system at the backfill side, the unit weight of the backfill soil, the costs, and CO(2)emission amounts of both the concrete and the reinforcement bars. Consequently, the results of the optimization analyses were arranged to discover the possibility of supplying an eco-friendly design of retaining walls with the minimization of both cost and gas emission depending upon the comparison of outcomes of the identified objective functions. The proposed approach is effective to find both economic and ecological results according to hand calculations and flower pollination algorithm.

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