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Record W2175970799 · doi:10.1109/sege.2013.6707904

Configurations for multiple thermal energy storages in thermal networks

2013· article· en· W2175970799 on OpenAlexafffund
Behnaz Rezaie, Bale V. Reddy, Marc A. Rosen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Thermodynamics and Statistical Mechanics
Canadian institutionsOntario Tech University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHeat exchangerSeries (stratigraphy)ThermalThermal energy storageGridEnergy (signal processing)Thermal energyEnergy storageComputer scienceMechanical engineeringEngineeringThermodynamicsPhysicsMathematicsGeometryGeology

Abstract

fetched live from OpenAlex

In practice, there are some conditions, depending on space availability, economics, project requirements, insulation, storing media type and other issues, for which it may be advantageous to utilize several thermal energy storages (TESs) instead of one in thermal networks like district energy systems. Here, various configurations for multiple TESs are proposed and investigated. Significant parameters for a TES, or a set of TESs, include discharging temperature and recovered energy. First, one TES is investigated to determine the final temperature and energy recovery. Next, characteristics for various configurations of multiple TESs are developed as functions of TES characteristics (e.g., charging and discharging temperatures and energy quantities). Series, parallel and general grid (simultaneous series and parallel) TES configurations are considered. In the parallel configuration, the TESs behave independently. This suggests that with the TES can consist of different storage media types and sizes, and that there is no restriction on initial temperature of the TES. In the series configuration, the situation is different because the TESs are connected directly or indirectly through a heat exchanger. If there is no heat exchanger between the TESs, the TES storage media should be the same, because the outlet of one TES is the inlet to the next one in the series. The initial temperature of the second TES must be smaller than the discharge temperature of the first. There is no restriction on the TES size for series configurations. The general grid configuration is observed to exhibit characteristics of both series and parallel configurations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.947
Threshold uncertainty score1.000

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)0.0010.000

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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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.

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

Citations2
Published2013
Admission routes2
Has abstractyes

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