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Record W2756402846 · doi:10.5006/c2017-09104

Modeling Lead and Copper Corrosion and Solubility in Municipal Water Distribution Systems

2017· article· en· W2756402846 on OpenAlexaboutno aff
Robert J. Ferguson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsnot available
Fundersnot available
KeywordsCopperCorrosionSolubilityLead (geology)MetallurgyErosion corrosion of copper water tubesMaterials scienceLead–acid batteryEnvironmental scienceChemistryGeologyThermodynamicsBattery (electricity)

Abstract

fetched live from OpenAlex

Abstract Lead and copper in municipal water systems present a major health hazard in addition to the infrastructure loss associated with corrosion releasing them into the distribution system. Soluble lead and copper became a legal as well as economic concern with the implementation of the Lead and Copper rule in the United States in 1991 and its subsequent expansion. Similar regulations where implemented in Canada during the same time period. The regulations set action limits for the metals at 15 μg/L for Pb and 1.3 mg/L for Cu. Lead and copper in municipal systems can result from soluble lead in copper in the water source, corrosion releasing soluble ions into the water, and the dissolution of corrosion product and other lead and/or copper deposits. The dissolution process can be increased, or limited, by changes in water chemistry due to seasonal variations, changing water sources, or changes in treatment. In some cases, treatment directed towards minimizing corrosion as a source of lead and copper, can actually increase the solubility of the ions. This paper describes a two fold approach to computer modeling of lead and copper corrosion, and the maximum solubility of lead and copper in the municipal water. The methods outlined can be used to: Model lead and copper corrosion in a distribution system.Model the maximum solubility of lead and copper as an indicator of the waters ability to dissolve deposits, and transport soluble Pb and Cu ions through the system.Predict the impact of changing water sources upon lead and copper levels in the system.Predict the impact of treatments, including pH adjustment upon lead and copper in the system. Examples are provided based upon a recent, well publicized, water change that resulted in high lead levels in a municipal water system. The method outlined was used to evaluate a municipal water, and compare traditional indices, maximum lead and copper solubility, and predicted corrosion rates, to the river water that replaced it.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.242
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2017
Admission routes1
Has abstractyes

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