Optimum Cost Prediction of Reinforced Concrete Cantilever Retaining Walls

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Date

2023

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Mdpi

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Civil Engineering
(2000)
The Atılım University Department of Civil Engineering was founded in 2000 as a pioneer for the Departments of Civil Engineering among the foundation schools of Ankara. It offers education in English. The Department of Civil Engineering has an academic staff qualified in all areas of the education offered. In addition to a high level of academic learning that benefits from learning opportunities through practice at its seven laboratories, the Department also offers a Cooperative Education program conducted in cooperation with renowned organizations in the construction sector. Accredited by MÜDEK (Association of Evaluation and Accreditation of Engineering Programs) (in 2018), our Department has been granted the longest period of accreditation to ever achieve through the association (six years). The accreditation is recognized by ENAEE (European Network for Accreditation of Engineering Education), and other international accreditation boards.

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Abstract

Reinforced concrete cantilever retaining walls (RCCRWs) are widely used in civil engineering projects as a common type of retaining structure. The design of these structures focuses on ensuring safety against various failure scenarios and compliance with standard building code requirements. This research aims to enhance the design process of RCCRWs by developing a specific code and optimizing it through a metaheuristic-based algorithm. In this study, the cost prediction of RCCRWs is also investigated through a parametric study involving key variables such as wall height, seismic zone, backfill material properties, and backfill inclination angle. To achieve this, non-linear regression analysis is employed to establish an empirical correlation, enabling cost estimation for optimized RCCRWs. The resulting prediction equation is simple to use, requiring only limited inputs. Therefore, it can be applied during the initial stages of a project, making a valuable contribution in determining approximate costs for RCCRW projects.

Description

Akis, Ebru/0000-0001-8417-2405

Keywords

cost prediction, optimization, optimum design, regression analyses, reinforced concrete cantilever walls

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Volume

13

Issue

10

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