Methodology for the Selection of Trenchless Sewer Rehabilitation Technologies in Bogotá, Colombia

Abstract

Context: Operational and/or structural failures in sewer networks lead network operators to carry out rehabilitation tasks to maintain water transport conditions, which is why it is necessary to decide on the type of intervention to be performed, that is, i) a traditional open-ditch procedure, or ii) the use of trenchless rehabilitation technologies. Objective: This article focuses on the methodology developed and implemented in the SELECTOR program, whose purpose is to provide public service companies responsible for sewer service, as well as related professionals, with a decision tool that answers, from a technical perspective, which of the analyzed trenchless rehabilitation technologies (pipe bursting, cured-in-place pipe, slip lining, and spiral wound) is the most suitable for the rehabilitation of sewer networks. Method: To this effect, it is necessary ​​to consider all the influence parameters at the time of sewer rehabilitation, define the application ranges of these trenchless technologies, extract the differential variables, use fuzzy logic verbalization, determine the priority and relationship between the variables using the data mining technique known as decision trees, and develop the SELECTOR program by means of the Visual Studio 2017® platform. Results: The differential variables for decisions regarding the application of trenchless rehabilitation technologies in underground sewerage infrastructure projects were identified. A graphic summary of the decision model was made using the verbalization diagrams and the SELECTOR program, which allows processing the information of the sewerage networks individually and for a whole sewer rehabilitation project, detailing the intervention collector to collector. Conclusions: There are eight differential variables when deciding on sewer rehabilitation. Verbalization diagrams allow to compress the decision model and facilitate its programming, and automated decision models increase effectiveness and transparency in construction processes.