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Record W4410410527 · doi:10.1061/9780784486184.089

Mitigating Pipe Corrosion in Water Distribution Systems: Strategies for Sustainability and Resilience

2025· article· en· W4410410527 on OpenAlexaffabout
Misagh Khanlarian, Nafiseh Ebrahimi, Ehsan Roshani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsResilience (materials science)SustainabilityCorrosionEnvironmental scienceDistribution (mathematics)Computer scienceEnvironmental resource managementMaterials scienceMetallurgy

Abstract

fetched live from OpenAlex

The corrosion of metallic pipes in water distribution systems is a critical issue that impacts the integrity and efficiency of water supply networks. As global temperatures rise and precipitation patterns shift, the chemical composition of water and soil environments surrounding the pipes is altered, influencing corrosion processes. This research, as part of a larger initiative at the National Research Council Canada, aims to summarize recent findings and best practices from literature publications to enhance maintenance strategies for water distribution systems. By examining the latest advancements in corrosion prevention, monitoring technologies, and maintenance protocols, the broader research seeks to develop a comprehensive framework that municipalities and water management authorities can adopt to mitigate the adverse effects of environmental changes on corrosion. Additionally, these efforts aim to lower the carbon footprint of water distribution systems by reducing the need for energy-intensive repairs and replacements, promoting sustainability. This paper specifically focuses on identifying gaps in the study of corrosion in buried water pipes, particularly regarding laboratory experimentation, contributing to the overall goals of the broader research initiative. The most significant gaps in the lab experiments are their short duration and the lack of studies focusing on the combined effects of factors like pH and moisture content under controlled laboratory conditions that mimic real-world scenarios.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.606
Threshold uncertainty score0.189

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.214
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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