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Record W4396701015 · doi:10.11159/icsect24.140

Study of Salt Hydrate-based Phase Change Materials Integrated into Thermal Energy Storage System for Air Pre-cooling in Hot Climate

2024· article· en· W4396701015 on OpenAlexvenueno aff
Mahmoud Haggag, Usman Masood, Ahmed Hassan, Mohammad Shakeel Laghari

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicAdsorption and Cooling Systems
Canadian institutionsnot available
Fundersnot available
KeywordsThermal energy storageHydratePhase changeSalt (chemistry)Phase-change materialEnvironmental scienceMaterials sciencePhase (matter)Energy storagePetroleum engineeringThermalProcess engineeringThermodynamicsGeologyEngineeringChemistryPhysics

Abstract

fetched live from OpenAlex

The cooling of lightweight buildings is a major future challenge due to the consequences of global warming.Air conditioning (AC) systems are a major energy consumer, so even small improvements in AC performance can lead to significant energy savings.This numerical study investigates the use of thermal energy storage (TES) to improve AC performance in hot climates.TES is a technology that shows promise in meeting the rising energy demand while reducing greenhouse gas emissions.Latent heat thermal energy storage (LHTES) is a specific type of TES that aims to reduce the need for excessive cooling or heating in buildings.Researchers are currently exploring the use of phase change materials (PCMs) as potential LHTES materials to enhance energy efficiency in building systems.The primary objective of this paper is to explore the application of PCMs specifically salt hydrate (CaCl2.6H2O)with a melting range of 29-33°C in the pre-cooling of air, where they store night time ambient cooling and release it during the day to diminish peak cooling requirements.To accomplish this, a standard-size air-conditioning duct incorporated with the PCM enclosure has been modelled using ANSYS/Fluent.Results showed that a PCM-based air-pre-cooling model reduced peak cooling demand by 23% and air conditioning system capacity by 30%, achieving an 8.2°C drop in temperature at a velocity of 1 m/s.The findings of this study suggest that PCMbased TES systems are a promising technology for improving AC performance in hot environments.

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 score0.428
Threshold uncertainty score0.973

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 head0.008
GPT teacher head0.213
Teacher spread0.205 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the World Congress on Civil, Structural, and Environmental EngineeringSame topicAdsorption and Cooling SystemsFrench-language works237,207