Evidence map›Paper›PMID 41902162›Full record

ReviewSensors (Basel, Switzerland)2026

Nondestructive Inspection of Water Pipes: A Review.

Rileigh Nowroski, Piervincenzo Rizzo, Liam Byrne, Adeline Ziegler

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Rileigh NowroskiDepartment of Civil and Environmental Engineering, University of Pittsburgh, 3700 O'Hara Street, 742 Benedum Hall, Pittsburgh, PA 15261, USA.
Piervincenzo RizzoDepartment of Civil and Environmental Engineering, University of Pittsburgh, 3700 O'Hara Street, 742 Benedum Hall, Pittsburgh, PA 15261, USA.ORCID 0000-0002-7159-2221
Liam ByrneDepartment of Civil and Environmental Engineering, University of Pittsburgh, 3700 O'Hara Street, 742 Benedum Hall, Pittsburgh, PA 15261, USA.
Adeline ZieglerDepartment of Civil and Environmental Engineering, University of Pittsburgh, 3700 O'Hara Street, 742 Benedum Hall, Pittsburgh, PA 15261, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pipe networks assure the transportation of primary commodities such as water, oil, and natural gas. Quantitative and early detection of defects avoids costly consequences. Due to low cost of water, high-profile accidents, and economic downturns, the research and development of nondestructive evaluation (NDE) and structural health monitoring (SHM) technologies for freshwater mains and urban water networks have received less attention with respect to the gas and oil industries. Moreover, the technical challenges associated with the practical deployment of monitoring systems and the fact that most water pipelines are buried underground demand synergistic interaction across several disciplines, which may limit the transition from laboratory to real structures. This paper reviews the most prominent NDE/SHM technologies for freshwater pipes. The challenges that said infrastructures pose, as well as the methodologies that can be translated into SHM approaches, are highlighted. The scope of this review is to provide a holistic view of the physical principles, the success, and the technological challenges associated with the inspection and monitoring of freshwater pipelines.

Indexed as

nondestructive evaluationoptical methodspipe inspectionreview articlestress wavesstructural health monitoring

Identifiers

PMID41902162
PMCPMC13030724

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.