MétaCan
Menu
Back to cohort
Record W2993090621 · doi:10.1002/est2.116

Improving clean energy greenhouse heating with solar thermal energy storage and phase change materials

2019· article· en· W2993090621 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnergy Storage · 2019
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsUniversity of Windsor
FundersAgricultural Adaptation Council
KeywordsTRNSYSPayback periodEnvironmental scienceGreenhouse gasThermal energy storagePhase-change materialProcess engineeringSolar energyNuclear engineeringZero-energy buildingEnergy consumptionEnergy storageThermal energyEnvironmental engineeringWaste managementThermalEngineeringMeteorologyElectrical engineeringThermodynamics

Abstract

fetched live from OpenAlex

Abstract Greenhouses consume a great deal of energy to heat their building envelopes. The strategic integration of solar energy and thermal energy storage (TES) can help to boost energy performance and reduce the carbon emission in the sector. In this paper, the benefits of adding phase change materials (PCM) to the water tank of a solar heating system have been evaluated using the Transient System Simulation (TRNSYS) program. Initially, the hourly heating load of a reference greenhouse was evaluated using TRNSYS software. The results were validated with natural gas consumption data. The validated simulation was then used to investigate the impact of PCM on the performance of a large‐scale solar energy system. Four system configurations were evaluated; no PCM materials in the tank, then 20%, 40%, and 60% of the water tank volume occupied by PCM. Energy performance improvements of 10% to 14% were observed by increasing the proportion of PCM amounts over the baseline conventional system. Finally, an economic study was conducted to investigate the cost feasibility of different PCM concentrations. It was shown that PCM price, cost of natural gas, and carbon tax are the principal influence factors on the payback period.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.060
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.236
Teacher spread0.216 · 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