MétaCan
Menu
Back to cohort
Record W4400236645 · doi:10.11159/ehst24.155

Feasibility Assessment of Integrating Concentrating Solar Collectors with Gas Turbines in Low Direct Normal Irradiance Areas

2024· article· en· W4400236645 on OpenAlexaff
Navid Mahdavi, William David Lubitz, Shohel Mahmud, Syeda Humaira Tasnim

Bibliographic record

VenueProceedings of the International Conference of Energy Harvesting, Storage, and Transfer · 2024
Typearticle
Languageen
FieldEnergy
TopicSolar Thermal and Photovoltaic Systems
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsIrradianceSolar irradianceEnvironmental scienceSolar energyMeteorologyEngineeringElectrical engineeringOpticsPhysics

Abstract

fetched live from OpenAlex

The feasibility of integrating parabolic trough collectors (PTCs) with micro gas turbines (MGTs) in regions characterized by low Direct Normal Irradiance (DNI) was explored in this study.A transient simulation model was developed using MATLAB and typical meteorological year data to assess the impacts of varying DNI levels on the performance and efficiency of the system.The primary focus was on how the thermal efficiency of gas turbine cycles at different locations is influenced by the yearly average DNI.The findings revealed that by using the minimum annual average DNI difference as a reference, a reliable comparison and estimation of the gas turbine's thermal efficiency can be achieved.This approach confirmed a significant correlation between estimated and simulated thermal efficiencies, illustrating that the integration of PTCs with MGTs can substantially enhance system efficiency even in areas with low DNI.The robustness of this method highlights its potential as a predictive tool for optimizing the performance of hybrid solar-gas turbine systems across various geographical 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)0.000
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 score0.292
Threshold uncertainty score1.000

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 head0.022
GPT teacher head0.246
Teacher spread0.224 · 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

Explore more

Same venueProceedings of the International Conference of Energy Harvesting, Storage, and TransferSame topicSolar Thermal and Photovoltaic SystemsFrench-language works237,207