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Multiple-Criteria Decision Analysis Using TOPSIS: Sustainable Approach to Technical and Economic Evaluation of Rocks for Lining Canals

Mahrous A. M. AliMining and Petroleum Engineering Department, Faculty of Engineering-Qena, Al-Azhar University, Qena 83513, EgyptJong-Gwan KimDepartment of Energy and Resources Engineering, Chonnam National University, Gwangju 61186, KoreaZakaria H. AwadallahCivil Engineering Department, Faculty of Engineering, Al-Azhar University, Qena 83513, EgyptAhmed M. AbdoDepartment of Architecture, Faculty of Engineering, Al-Azhar University, Qena 83513, EgyptAbbas M. HassanDepartment of Architecture, Faculty of Engineering, Al-Azhar University, Qena 83513, Egypt
2021en
ABI

Abstract

One of the crucial projects underway in Egypt is the lining of watercourses to withstand the outflow of water through their beds and flanks. Various materials have been used in this project, including limestone, sandstone, basalt, and dolomite, along with other building materials. This study focused on the evaluation of rock characteristics to determine their suitability for the construction of a canal lining. All rock characteristics should be classified in terms of technical and economic concerns related to mining rock specifications, such as mechanical and physical properties, and evaluated according to their weights and ratings. As a rule of decision making, management stakeholders select the rock types. The primary purpose of canal linings is to reduce water loss due to seepage. Methodologically, we adopted the technique for order of preference by similarity to ideal solution (TOPSIS), and derived an improved TOPSIS method based on experimental testing. This study attempted the first application of TOPSIS to canal linings and relevant construction materials. The analysis shows that limestone L1 is the best rock-building material for canal linings in Upper Egypt. Limestone L1 has the shortest geometric distance from the positive ideal solution and the longest geometric distance from the negative ideal solution. The results provide decision makers with strategic indicators to select among different rock types based on the total points assigned to all rock specifications.

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