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Record W2136582356 · doi:10.1061/9780784412947.093

Simultaneous Optimization of Pipe and Pavement Renewal Scheduling

2013· article· en· W2136582356 on OpenAlexaff
Yehuda Kleiner

Bibliographic record

VenueWorld Environmental and Water Resources Congress 2013 · 2013
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsScheduling (production processes)BreakageComputer sciencePipe network analysisEngineeringCivil engineeringOperations researchOperations management

Abstract

fetched live from OpenAlex

Most urban distribution water mains are located under paved streets or roads. Despite an obvious interdependence between pipe and pavement deterioration, this interdependence has not yet been considered in frameworks that would optimize both simultaneously, which is the issue addressed in this paper. The deterioration processes of both pipe and pavement are considered to be deterministic, and some assumptions are made about the interactions between pipe breakage frequency and pavement condition. Total life cycle costs of both pipe and pavement are computed as the discounted costs of an infinite series of perpetual renewal cycles. Genetic Algorithm (GA) is used to find the (near) least cost strategy for scheduling multiple pipes and pavements in a network.

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: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.426

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 head0.151
Teacher spread0.147 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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