Evidence map›Paper›PMID 40808097›Full record

ArticlePolymers2025

Microwave Based Non-Destructive Testing for Detecting Cold Welding Defects in Thermal Fusion Welded High-Density Polyethylene Pipes.

Zhen Wang, Chaoming Zhu, Jinping Pan, Ran Huang, Lianjiang Tan

Abstract read
In one paragraph

Article in Polymers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zhen WangSchool of Materials Science and Engineering, Shanghai Institute of Technology, Shanghai 201418, China.ORCID 0009-0006-5905-6537
Chaoming ZhuJiaxing Special Equipment Inspection Institute, Jiaxing 314051, China.
Jinping PanJiaxing Special Equipment Inspection Institute, Jiaxing 314051, China.
Ran HuangCollege of Biomedical Engineering, & Yiwu Research Institute, & Zhuhai Fudan Innovation Institute, Fudan University, Shanghai 200433, China.ORCID 0000-0001-7778-0920
Lianjiang TanSchool of Materials Science and Engineering, Shanghai Institute of Technology, Shanghai 201418, China.

Funding

National Key Research and Development Program China 2022YFC2009500
6 · The paper itself

Abstract

High-density polyethylene (HDPE) pipes are widely used in urban natural gas pipeline systems due to their excellent mechanical and chemical properties. However, welding joints are critical weak points in these pipelines, and defects, such as cold welding-caused by reduced temperature or/and insufficient pressure-pose significant safety risks. Traditional non-destructive testing (NDT) methods face challenges in detecting cold welding defects due to the polymer's complex structure and characteristics. This study presents a microwave-based NDT system for detecting cold welding defects in thermal fusion welds of HDPE pipes. The system uses a focusing antenna with a resonant cavity, connected to a vector network analyzer (VNA), to measure changes in microwave parameters caused by cold welding defects in thermal fusion welds. Experiments conducted on HDPE pipes welded at different temperatures demonstrated the system's effectiveness in identifying areas with a lack of fusion. Mechanical and microstructural analyses, including tensile tests and scanning electron microscopy (SEM), confirmed that cold welding defects lead to reduced mechanical properties and lower material density. The proposed microwave NDT method offers a sensitive, efficient approach for detecting cold welds in HDPE pipelines, enhancing pipeline integrity and safety.

Indexed as

cold welding defectshigh-density polyethylene pipesmicrowave non-destructive testingthermal fusion welds

Identifiers

PMID40808097
PMCPMC12349315

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.