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Record W2793376378 · doi:10.2166/aqua.2018.097

Probability of network disconnection of water distribution system for maintenance prioritization

2018· article· en· W2793376378 on OpenAlexafffund
Hieu Chi Phan, Ashutosh Sutra Dhar, Premkumar Thodi, Rehan Sadiq

Bibliographic record

VenueJournal of Water Supply Research and Technology—AQUA · 2018
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsCentre For Cold Ocean Resources EngineeringOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRedundancy (engineering)UnavailabilityReliability engineeringRobustness (evolution)Probability distributionTopology (electrical circuits)SupervisorComputer scienceFail-safeEngineeringMathematicsStatisticsElectrical engineering

Abstract

fetched live from OpenAlex

Abstract Unexpected pipe breaks in municipal water distribution systems may cause isolation of parts of the network or reduction of redundancy, leading to reduced system reliability. While a network with less redundancy implies less tolerance to further breaks, the isolation of nodes explicitly indicates unavailability of the system to service the nodes. This paper presents a method of measuring these topological changes using algebraic connectivity (AC). AC is a parameter that can be used to assess robustness and redundancy of a network. The changes in AC associated with pipe breaks are compared with the AC of intact networks to assess whether the removal of the pipe causes reduction of redundancy or isolation in the network. An AC of 1.5625 × 10−5 is calculated for an intake of a medium-sized water distribution network (WDN). The fluctuation in AC is used to assess the criticality of each pipe segment to the overall structure of the network. This study also evaluates the failure probability of the WDN, assuming that the network failure probability is equivalent to the probability of isolation of parts of the system due to pipe breaks. The breaks leading to the failure are identified using the method of the minimum cut-sets.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.229

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.020
GPT teacher head0.247
Teacher spread0.227 · 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 designBench or experimental
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

Citations9
Published2018
Admission routes2
Has abstractyes

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