The Impact Of Impurities In Plastic Pipes On Long-Term Performance

Engineering structures, such as the installation of plastic pipes, often have unexpected effects that may shorten their service life. In the past few decades, people have gained increasing understanding of the process of controlling these sudden failures. By improving the material's resistance to slow crack propagation (SCG) performance (such as from PE63 to PE100RC), pipeline performance has been significantly improved. There is still significant uncertainty in the use of non original grade materials, mainly due to the unknown effects of impurities found in recycled materials. The influence of impurities on lifetime related characteristics can be divided into three categories:

Different types of polymer impurities (such as PE in PP)

Impurities in similar polymers (such as PE-LD in PE-HD)

Non polymer impurities (such as inorganic particles, etc.)

In this case, this study investigates the influence of impurities by mixing the original grade polypropylene (v-PP) with actual recycled polypropylene (r-PP) into different compositions (v-PP/r-PP, expressed as%: 100/0, 90/10, 75/25, 50/50, 0/100). Subsequently, these materials were tested through pipeline hydrostatic pressure testing. It can be demonstrated that the impurity content is highly dependent on the final failure time (tf). In addition, in-depth analysis of the fractured pipeline samples showed a clear correlation between the maximum size of introduced inorganic impurities and tf. This indicates that based on the size of the introduced key impurities (amax), two seemingly identical pipeline samples may still have vastly different failure times in terms of recycled material content. The results indicate that it is not only necessary to understand the impact of the content and distribution of recyclable materials on the service life of pipelines, but more importantly, to understand the maximum impurity size. Therefore, pipeline manufacturers should carefully choose the recycling grade and only make the selection after understanding the raw material itself, processing, and physical sorting history.