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Record W4410508859 · doi:10.31031/pps.2023.05.000614

Factorial Design Heat and Mass Transfer of Counter-Current Water Cooling Tower as a Case Study of an Experimental Design Project

2023· article· en· W4410508859 on OpenAlexfundno aff
Isam Al Zubaidi

Bibliographic record

VenueProgress in Petrochemical Science · 2023
Typearticle
Languageen
FieldEngineering
TopicAdsorption and Cooling Systems
Canadian institutionsnot available
FundersUniversity of Regina
KeywordsCooling towerTowerCurrent (fluid)Heat transferWater coolingMass transferNuclear engineeringEngineeringEnvironmental scienceMechanical engineeringMechanicsElectrical engineeringStructural engineeringPhysics

Abstract

fetched live from OpenAlex

for the Heat Mass and Momentum Transfer.This project is to compare the effectiveness and cooling performance of the standard film fill packing material in a water cooling tower apparatus.The results showed that increasing the air and water flow rates can increase efficiency by approximately 10% and 13%, respectively.The cooling ranges and ideal ranges of the cooling tower were used to calculate efficiencies between 83-97% for the regular packing material.Other calculations were performed, including approach, heat and mass transfer coefficients, the heat emitted, mass and energy balance, factorial design analysis using Minitab, Solid Edge work, etc.Many operating variables were evaluated, such as the effect of packing material, flow rates of air and water, water inlet temperature to study the effect of these variable on the efficiency of water cooling towers, which can be used to optimize cooling tower performance in industrial settings.

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 score0.109
Threshold uncertainty score0.404

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 head0.048
GPT teacher head0.330
Teacher spread0.282 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

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