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Record W4399361818 · doi:10.5772/geet.26

Design and Simulations of Solar-Based Hydrogen Production System via Methane Decomposition

2024· article· en· W4399361818 on OpenAlexaff
Ali R. Al Shehhi, Ibrahim M. Gadala, Mohamed S. Gadala

Bibliographic record

VenueGreen Energy and Environmental Technology · 2024
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMethaneHydrogen productionDecompositionProduction (economics)Environmental scienceHydrogenAstrobiologyProcess engineeringChemistryEngineeringPhysicsEconomicsOrganic chemistry

Abstract

fetched live from OpenAlex

A solar-based hydrogen production system is analyzed and studied with the intention of optimizing the parameters involved in oil refining industry and the environment of the United Arab Emirates. Methane decomposition in molten salt media using a concentrated solar power system was adopted, since the temperature range required in the system design is achievable with this method. The System Advisor Model software was used in this study with three cases to optimize the system using the levelized cost of heat concept. In Case 1, a levelized cost of heat of 9.32 ¢/kWh was achieved using an optimized system with a CSP-RTUVR-2014 receiver and a Luz LS-3 collector. The design of Cases 1 and 2 exhibited pressure drops along the system of just 10 bar, significantly lower than the 50 bar of Case 3. Similarly, designs of Cases 1 and 2 resulted in maximum receiver thermal losses of around 7 MW, whereas Case 3 yielded 14 MW loss. Analysis of the best-suited molten salt option showed that HITEC solar salt was better than HITEC XL and standard HITEC. A regression analysis was carried out to examine the pressure drop responses since it is a key variable affecting the integrity of the solar system. It was observed that the receiver mass flow rate is the main contributing cause of pressure drop. Through careful operator control of receiver mass flow rate, premature failures of the solar system caused by the pressure drop can be avoided.

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 score0.099
Threshold uncertainty score0.754

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 head0.007
GPT teacher head0.202
Teacher spread0.195 · 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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