Feng Yang , Jingcai Liu , Ting Lin , Changxin Nai , Yuqiang Liu , Panpan Qiu , Ya Xu , Can Qian
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引用次数: 0
Abstract
This study utilized electrical defects detection, correlation analysis, and regression analysis to conduct a prediction about the generation of defects in high-density polyethylene geomembranes (HDPE GMBs) in landfills. The findings revealed that the average defect density of 108 landfills was 15 defects/ha, and the average defect area was 122 cm2/ha. Four out of the 11 potential indicators, namely construction unit qualification, HDPE GMB thickness, drainage media type, and drainage system structure, had a significant impact on the density of installation and total defects. Prediction models of installation and total defects, using the four key indicators as independent variables, could reasonably predict the occurrence of initial defects. The model supports the accurate prediction of landfill risk and the identification of high-risk sites, which is crucial for hierarchical classification management and risk control.
期刊介绍:
The range of products and their applications has expanded rapidly over the last decade with geotextiles and geomembranes being specified world wide. This rapid growth is paralleled by a virtual explosion of technology. Current reference books and even manufacturers' sponsored publications tend to date very quickly and the need for a vehicle to bring together and discuss the growing body of technology now available has become evident.
Geotextiles and Geomembranes fills this need and provides a forum for the dissemination of information amongst research workers, designers, users and manufacturers. By providing a growing fund of information the journal increases general awareness, prompts further research and assists in the establishment of international codes and regulations.