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Record W7046431282

Development and modeling of a lab-scale integrated copper-chlorine cycle for hydrogen production

2021· dissertation· en· W7046431282 on OpenAlexaboutno aff

Bibliographic record

Venuee-scholar@UOIT (University of Ontario Institute of Technology) · 2021
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsHydrogen productionDistillationThermochemical cycleExergyPressure swing adsorptionMultiple-effect distillationHydrogenAir separation
DOInot available

Abstract

fetched live from OpenAlex

Hydrogen is one of the most important energy carriers, clean fuels, and storage media in the upcoming future. Hydrogen production through the thermochemical copper-chlorine (Cu-Cl) cycle is one of the most promising methods of nuclear hydrogen production on a large scale. Researchers at the University of Ontario Institute of Technology (UOIT) have designed and developed a lab-scale integrated Cu-Cl cycle for producing hydrogen. This study aims to develop the thermodynamic, hydrodynamic, electrochemical, and heat and mass transfer models for the experimental Cu-Cl cycle to evaluate the performance of the cycle and its components. Also, an exergoeonomic and optimization study is performed for a more cost-effective approach and revealing optimal design conditions. The results of this study will be useful as a benchmark for the lab-scale Cu-Cl cycle performance assessment accounting for actual large-scale implementation. In practical operation of the Cu-Cl cycle, besides the main steps of hydrolysis, thermolysis, electrolysis and drying, the depleted anolyte (consumed anolyte at the electrolyzer) needs to be recycled to be concentrated sufficiently for the electrochemical process. Recycling of the oxidized anolyte through the separation processes is achieved by distillation of anolyte, drying unit, separation cell, pressure swing distillation unit (PSDU), and CuCl2 concentrator. The overall exergy efficiency of the integrated lab-scale Cu-Cl cycle is found to be 33.4%. The estimated cost of produced hydrogen from the scaled-up facilities with a capacity of 1000 kg/day H2 is about 3.91 $/kg H2. In the hydrolysis reactor, with an increase of St/Cu ratio (from 5 to 17 and 30), the maximum exergetic efficiency of the system occurs at the lower reactor operating temperature (from 450℃ to 388℃ and 380℃, respectively). From the hydrodynamic study of CuCl/HCl(aq) electrolyzer, the cells close to the anolyte or catholyte input ports possess a higher voltage efficiency than other cells for the X-shape bipolar modules, resulting in less decomposition potential. In the PSDU, both heat and mass transfer model results predict the same values for the low and high pressure packing column height of 1.7 m and 2 m, respectively.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.226
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 source (direct Gemma or distilled Codex), 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

Citations0
Published2021
Admission routes1
Has abstractyes

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