Development of Smart Membrane for Leak Detection in Pipeline Article Swipe

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Trung Van Nguyen · YOU? · · 2016 · Open Access · · DOI: https://doi.org/10.7939/r3x34n775

Pipelines are the most important liquid and gas transportation methods in various industries. They help to reduce the cost and to minimize the environmental impacts. However, the public maintains high resistance to pipeline’s developments because they are exposed to the consequents of pipeline’s leakages. Thus, pipeline operators must aim at zero leakage in their systems for publics’ safety and also for gaining public support. However, leaks are inevitable due to various reasons, and pipeline operators can only reduce leak consequences by early detections. As a result, many leak detection systems (LDSs) have been developed. According to the study of Afzal, most of those systems suffered from both technical and economical problems when applied to complex pipeline systems. These LDSs systems are optimized to detect different leaks and also to minimize the costly false alarms; thus, they overlook small leaks, i.e. pinhole leaks. This thesis introduces a new LDS that will solve both technical and economic problems. The system includes a flexible membrane with a sensor printed on its surface. This membrane will be wrapped around the 36” pipe to capture the release products. Also, its sensor will detect the membrane’s strain created by these products and send the signal to pipeline operators. For the system to be sensitive and cost effective, the membrane had to be optimized to achieve the longest lengths with the predefined thicknesses. Since this technology will be incorporated into to the protective wraps, the optimization procedure will use the material properties and the popular thicknesses of the protective wraps. To achieve the optimum design, the sensors’ geometry was optimized first. Then, they were printed on a flexible membrane using a low-cost printer, conductive ink, and resistive ink. The sensors were designed as a half Wheatstone bridge because this setup gave the highest signal outputs under different loading conditions. The sensors were studied using the four points bending test, and the gauge factors were determined to be 4 and 7.85 for the conductive ink and resistive ink, respectively. Based on this information, a prototype of the membrane was manufactured. This prototype was subjected to the dimple test to evaluate its workability and to compare with the FEA model. Also, the full FEA model of the membrane with the sensor was created. This model was used to optimize the length and thickness of the membrane. The optimum design was achieved when the printed sensor can generate a signal with a signal-to-noise ratio (S/N) of 30 dB under deformation. The simulation indicated that the elastomer membrane with the length of 8.5 ft and thickness of 0.03” can detect pinhole leak on the 36” pipe in 0.8 seconds.

Type

article

Language

en

Landing Page

https://doi.org/10.7939/r3x34n775

OA Status

green

References

10

Related Works

20

OpenAlex ID

https://openalex.org/W3097925073

Raw OpenAlex JSON

OpenAlex ID

https://openalex.org/W3097925073

Canonical identifier for this work in OpenAlex

DOI

https://doi.org/10.7939/r3x34n775

Digital Object Identifier

Title

Development of Smart Membrane for Leak Detection in Pipeline

Work title

Type

article

OpenAlex work type

Language

en

Primary language

Publication year

2016

Year of publication

Publication date

2016-01-01

Full publication date if available

Authors

Trung Van Nguyen

List of authors in order

Landing page

https://doi.org/10.7939/r3x34n775

Publisher landing page

Open access

Yes

Whether a free full text is available

OA status

green

Open access status per OpenAlex

OA URL

https://doi.org/10.7939/r3x34n775

Direct OA link when available

Concepts

Leak, Pipeline (software), Leak detection, Computer science, Petroleum engineering, Environmental science, Engineering, Environmental engineering, Operating system

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Cited by

0

Total citation count in OpenAlex

References (count)

10

Number of works referenced by this work

Related works (count)

20

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