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Record W4323047846 · doi:10.18280/mmep.100118

Numerical Investigation of a Photovoltaic Thermal System Performance under Irbid-Jordan Climate Conditions

2023· article· en· W4323047846 on OpenAlexvenueno aff
Isam Qasem, Ahmed A. Hussien, Mohamad Okour, Khalideh Al bkoor Alrawashdeh, M. Q. Al‐Odat

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2023
Typearticle
Languageen
FieldEnergy
TopicSolar Thermal and Photovoltaic Systems
Canadian institutionsnot available
Fundersnot available
KeywordsPhotovoltaic systemThermalEnvironmental scienceMaterials scienceEngineering physicsMeteorologyGeographyEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

The performance of a photovoltaic/thermal (PVT) system in Irbid -Jordan climate conditions is numerically investigated using TRNSYS Software.The PVT system is designed to produce both electricity and hot water simultaneously.In this research work, a PVT system is tested in Irbid, which is located in the northern region of Jordan (32.50 N, 35.90 E).The effects of the factors that affected the performance of PVT were theoretically studied.They included global solar radiation, water temperature, mass flow rate, wind speed, and tilted angle.The type of PV cell under consideration is polycrystalline (Po-Si).The results show that the maximum electrical efficiency was 18% and the thermal efficiency was 42%.The optimum tilt angle for thermal efficiency was nearly 28°, while electrical efficiency was 44%.The mass flow rate of water under which the thermal and electrical efficiencies are at their maximum is equal to 20 kg/hr.Also, the results reveal that as the temperature of the city water decreases, the electrical efficiency rises and the thermal efficiency drops.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.660

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 head0.029
GPT teacher head0.211
Teacher spread0.182 · 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 designSimulation or modeling
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

Citations1
Published2023
Admission routes1
Has abstractyes

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