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Record W4399654069 · doi:10.54097/qxtac480

Comparison of the Suitability between the Piston Solid Gravitational Energy Storage and Rechargeable Battery Energy Storage for Applications in the Industrial Process of Electricity Storage

2024· article· en· W4399654069 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.

Bibliographic record

VenueHighlights in Science Engineering and Technology · 2024
Typearticle
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEnergy storageProcess (computing)Process engineeringBattery (electricity)Computer data storageEnvironmental scienceWaste managementMaterials scienceComputer scienceEngineeringPhysicsPower (physics)Computer hardware

Abstract

fetched live from OpenAlex

Contemporarily, the electricity deficiency is a problem that should be faced and discussed for most countries. To solve this problem, the electricity should be used wisely. In this paper, the suitability between the Piston Solid Gravitational Energy (PSGES) and Rechargeable Battery Energy Storage (RBES) for applications in the electricity storage for both scenarios is compared. First, the development conditions, quantitative metrics including energy efficiency, energy density, response time of discharging, energy losses during the storage, duration of the storage, and levelized cost of the energy are discussed for each system. Then, quantitative metrics between these 2 systems are compared. The comparison results shows that the RBES used sodium-sulfur (NaS) has the highest competency compared with the rest systems. It has flexible discharge time, fast response time, high energy density and power density, relatively low levelized cost of the energy, and high efficiency. Thus, the RBES used NaS is the optimal solution for both scenarios.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score0.258

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.022
GPT teacher head0.277
Teacher spread0.255 · 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