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Record W2408466719 · doi:10.1061/9780784479889.030

Optimal Design of Water-Supply Pipe Systems Using Economic and Technical Analysis

2016· article· en· W2408466719 on OpenAlexaff
Mohammad Haji Gholizadeh, Amirmasoud Hamedi, Amir Niazi, Morteza Eazi

Bibliographic record

VenueWorld Environmental and Water Resources Congress 2016 · 2016
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsUniversity of Calgary
FundersFlorida International University
KeywordsWater supplyComputer scienceOptimal designPopulationResource (disambiguation)Risk analysis (engineering)SoftwareEconomic analysisWater resourcesOperations researchEnvironmental economicsEngineeringEnvironmental engineeringBusinessEconomics

Abstract

fetched live from OpenAlex

Optimal design of water distribution networks involves an evaluation of different aspects such as economic and technical analysis, mechanical and hydraulic issues, and population-based strategies. These objectives often conflict, to an extent that finding the optimal solution for one of those objectives reduces the other objective’s utility. This paper presents an approach to select an optimal design between three pre-specified scenarios that accounts for both economic and technical issues to supply the required water demand to customers, and also satisfy decision makers’ criteria and meet the design purposes for Darakeh neighborhood in Tehran, Iran. WaterGEMS software that contains powerful GIS-based solution for efficiently modeling, managing, and protecting valuable resource water, was used to find a management solution and design an optimal water-supply system. Consequently, based on economic and technical scoring, one of the considered scenarios was evaluated as the best option for the water distribution network of the study area.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.382

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 head0.007
GPT teacher head0.167
Teacher spread0.160 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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