Condition Prediction for Chemical Grouting Rehabilitation of Sewer Networks

Different techniques have been used to maintain and rehabilitate pipes and manholes of the sewer networks in the province of Quebec, including several trenchless rehabilitation techniques in the past two decades. In an effort to predict the future performance of trenchless rehabilitations, this paper presents condition prediction models for chemical grouting rehabilitation of both pipelines and manholes in the city of Laval, Quebec, Canada. The models were developed using regression analysis, based on gathered and analyzed closed circuit television (CCTV) inspection reports for the Laval city sewer network. Different defects in the chemical grouting rehabilitated sewer mains and manholes in this city are presented. The developed regression models are capable of predicting the structural and operational conditions; they are also utilized to generate deterioration curves over time for chemical grouting rehabilitation of sewer pipes and manholes based on basic governing factors such as pipe material and rehabilitation age. Models were validated using a set of data that was randomly selected and set aside. Models validation based on the value of coefficient of multiple determinations (R2) ranged between 80 and 97%. The developed models could be used by municipalities for forecasting chemical grouting rehabilitation for network components' conditions, planning inspections, and in decision making regarding budget allocations.