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Record W3160230376 · doi:10.18280/ijdne.160201

Experimental Study of the Efficiency of a Solar Water Heater Construction from Recycled Plastic Bottles

2021· article· en· W3160230376 on OpenAlexvenueno aff
Besma Chekchek, Mohamed Salmi, Abdelhakim Boursas, Giulio Lorenzini, Hijaz Ahmad, Younes Menni, Houari Ameur, Merzaqa Merrah, Djamal Fridja

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2021
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsHeat exchangerMaterials scienceSolar energyWaste managementEnvironmental scienceThermalWater flowHalogen lampComposite materialEnvironmental engineeringMechanical engineeringEngineeringMeteorology

Abstract

fetched live from OpenAlex

A solar polymer heat exchanger is designed to heat water; its primary materials are plastic water bottles with a capacity of 1.5 liters. These materials were recycled to preserve the environment and to make use of it again. The thermal insulation properties are adopted for the characterization of polymeric materials. These properties concern the conservation of energy for the longest period of time and the absence of problems caused by rust and corrosion, which are usually encountered in traditional heat exchangers. The heat exchanger experiments start by tracking the flow of water inside the pipes by a valve. The water temperature and flow rates are determined at the inlet and outlet surfaces of the exchanger. The obtained results indicated an increase in water temperature exceeding 10℃ in an ideal spring day. The thermal efficiency of the solar collector was about 62% under the sunlight, and 44% in the laboratory where halogen lamps were used as an industrial light source.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.184

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 head0.006
GPT teacher head0.217
Teacher spread0.211 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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