journal article·2021-12

Long-term field performance of a composite pipe repair under constant hydrostatic pressure

H.S. da Costa Mattos, J.M.L. Reis, F.C. Amorim, J.F.S. Brandao, L.D.M. Lana, V.A. Perrut

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Abstract

Abstract The popularity of composite repair systems for underwater and underground pipelines has soared in recent times. The long-term performance of these repair systems must be verified under field conditions to gain confidence for any future applications. This article presents a result of long-term high-pressure hydrostatic tests of a composite repair system for metallic pipes with 1 in. through-wall (Type-B) corrosion defects. The samples are kept in a testing field at constant pressure in an open place close to the sea (Guanabara Bay, Rio de Janeiro Brazil) for years until potential failure due to environmental ageing and degradation. The hydrostatic testing of pipes repaired with different composite repair systems was performed after five years to monitor the pressure states for 24 h in the pipes. The results suggest a considerable pressure fluctuation during the measurement cycle. This fluctuation was then explained through a state law that correlates pressure and temperature for the water inside the specimen. This study shows, both experimentally and theoretically, that without an adequate pressure control, normal environment temperature variation may induce a huge pressure oscillation inside the specimen due to the water compressibility. The model predictions are in excellent agreement with experiments. These outcomes would assist further measure and control the static pressure inside the specimens, which will be tested in the future giving valuable information about the long-term performance of the composite repair system.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Structural Integrity and Reliability Analysis · Corrosion Behavior and Inhibition · Geotechnical Engineering and Underground Structures

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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