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Record W4392872822 · doi:10.14447/jnmes.v27i1.a07

Mathematical Modelling of Billboard Type Central Solar Receiver for Domestic Application

2024· article· en· W4392872822 on OpenAlexvenueno aff
Kaustubh G. Kulkarni, Sanjay N. Havaldar, Pradip K. Tamkhade, Amit D. Desale, Sandeep P. Nalavade

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2024
Typearticle
Languageen
FieldEnergy
TopicSolar Thermal and Photovoltaic Systems
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

The central tower solar receiver system is comprised of a number of small tracing mirrors that focus the beam radiation onto a huge tower in the centre.The tracing mirrors are placed as well as adjusted in such a manner that the light is always reflected at the top of the tower.The major goal of this study is to carry out a mathematical assessment of the central tower solar receiver where solar load calculation and heat transfer analysis has been carried out.Solar load is calculated for the location of Pune, India.Mathematical modelling is performed for the solar central receiver system Results of the mathematical modelling reveal that the estimated average sunshine hour for the year ranges from 10.9 hours in the month of December to 12.9 hours in the month of July.The maximum incident beam radiation of 1050.9 w/m2 has been estimated in the month of April at 1200 hour.After computing the variables, the matrix equation can be generated and the system can calculate the energy under the first-order differential equation.The system's thermal efficiency can be computed once the maximum temperature of the heat transfer fluid, ambient air as well as copper tube is known.

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 score0.423
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.030
GPT teacher head0.270
Teacher spread0.240 · 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
Published2024
Admission routes1
Has abstractyes

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