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Record W3104936069 · doi:10.11159/ffhmt20.134

Experimental and Numerical Study of a Latent Heat Thermal Energy Storage System Enhanced with Fins

2020· article· en· W3104936069 on OpenAlexvenueno aff
Saeed Tiari, Addison Hockins, S. Moretti

Bibliographic record

VenueProceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer · 2020
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsnot available
Fundersnot available
KeywordsThermal energy storageLatent heatMaterials scienceThermalEnergy storageHeat energyMechanicsHeat transferMechanical engineeringThermodynamicsEngineeringPhysics

Abstract

fetched live from OpenAlex

The lack of a dispatchable energy supply makes transitioning from fossil fuels to green energy alternatives such as solar and wind energy extremely difficult. One solution to remedy this problem is the introduction of a latent heat thermal energy storage (LHTES) unit into an energy system to continue to provide energy long after the original source is gone. LHTES units utilize phase change materials (PCM) as storage media that melt and solidify in the presence of thermal energy. LHTES units using only pure PCMs take a long time to charge and discharge due to PCM low thermal conductivity, making their application in energy systems more difficult. The introduction of thermal conductivity enhancement techniques such as fins, nanoparticles and metallic foam decreases charging and discharging time and increases the thermal efficiency of LHTES units The current study numerically and experimentally analyses a LHTES unit containing Rubitherm RT55 as the PCM and enhanced with fins. Different configurations of metallic fins were examined to maximize the heat transfer to the PCM. These configurations were compared to the operation of the LHTES unit without any enhancement. Both the charging and the discharging cycles of the LHTES unit were studied. The experimental results were compared to numerical simulations completed by ANSYS Fluent 17.0 commercial CFD package. Finding an optimal configuration of a LHTES unit containing PCM and fins allows such units to be integrated with an alternative energy system making the alternative energy more reliable and comparable to their fossil fuel counterpart. The PCM in this study is stored in a cylindrical container which was of 30.48 cm tall with an inner diameter of 19.05 cm, with a copper pipe that transports the heat transfer fluid at the center of the container. The system is initialized from room temperature (22 ) and is charged with water at 70 . Firstly, the numerical data was compared to the experimental to provide verification for the model. The comparison indicated that the numerical predictions were in good agreement with the experimental data. Two configurations of 10 annular fins and 20 annular fins attached to the central pipe were analysed numerically. These two cases were compared to a benchmark case using no fins. The no-fin case using 70 HTF took approximately 48 hours to charge. This benchmark was then compared to the finned cases. The 10-fin case took roughly 15 hours to charge, while the 20-fin case took 12 hours and 40 minutes to fully charge. The resulting percent decreases in charging times were 68.9% and 73.7%, respectively. When evaluating the discharging cycle of the heat exchanger, it was found that the case utilizing no fins took about 42.5 hours to completely discharge. The 10-fin case took 11 hours and 20 minutes, a 73.2% decrease in total charging time. The 20-fin case had the fastest discharge cycle, which was 8 hours and 50 minutes, a 79.1% decrease when compared to the no-fin case. A case can be made that gains in efficiency when using the 20-fin case are offset by the manufacturing cost and difficulty when creating and assembling the fin geometry.

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 score0.102
Threshold uncertainty score0.432

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 head0.033
GPT teacher head0.246
Teacher spread0.213 · 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".

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Citations1
Published2020
Admission routes1
Has abstractyes

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