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Energy Use in Water Distribution Systems: A Life Cycle Perspective

2019· other· en· W2998017130 on OpenAlexaff
Hirushie Karunathilake, Tharindu Prabatha, Shahnawaz Khan, Kasun Hewage

Bibliographic record

VenueEncyclopedia of Water · 2019
Typeother
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsEnvironmental economicsEnvironmental scienceSizingClimate changeEnergy (signal processing)Environmental resource managementWater cycleLife-cycle assessmentDistribution (mathematics)Computer scienceEnvironmental planningProduction (economics)EcologyEconomics

Abstract

fetched live from OpenAlex

Abstract Water distribution systems (WDSs) serve to deliver water from the source to intended consumers or endpoint applications, with the requisite quality and quantity. While these systems are a critically needed aspect of modern civilizations and their infrastructure, they also consume significant amounts of energy during their life cycle. The environmental impacts related to energy use have received global attention in recent times, with increasing concerns about anthropogenic climate change. Efforts are being made at all levels to reduce energy use in order to achieve the climate action targets set at regional, federal, and global levels. Water pumping to end users causes the highest energy use impacts in a WDS. The flow distances, component sizing and facility locations, flow rates, and other parameters need to be carefully managed in designing water distribution networks to minimize energy use and economic impacts. In attempting to develop more energy efficient WDSs, their energy use and impacts need to be contemplated from a holistic life cycle perspective.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.241
Threshold uncertainty score0.932

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 head0.005
GPT teacher head0.176
Teacher spread0.171 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2019
Admission routes1
Has abstractyes

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