MétaCan
Menu
Back to cohort
Record W2278882138 · doi:10.1504/ijpse.2015.071428

Energy and exergy analyses of power generation via an integrated biomass post-firing combined-cycle

2015· article· en· W2278882138 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

VenueInternational Journal of Process Systems Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsExergyCombined cycleExergy efficiencyEnvironmental scienceGas compressorBiomass (ecology)CombustorOverall pressure ratioNatural gasCondenser (optics)Electricity generationWaste managementNuclear engineeringEngineeringTurbinePower (physics)ChemistryCombustionThermodynamicsMechanical engineeringGeology

Abstract

fetched live from OpenAlex

Biomass energy recently has received much attention due to its renewability and relatively low environment impact, both of which suggest it has good prospects as are placement for fossil fuels in the future. Furthermore, biomass gasification reduces problems associated with direct burning of biomass, and the producer gas from the gasification process can be utilised in various power generation systems. In this article, a biomass post-firing combined cycle is proposed and energy and exergy analyses are reported for the cycle. The cycle energy and exergy efficiencies are both determined peak at specific compressor pressure ratio, and increasing the compressor pressure ratio reduces the mass of air per mass of steam in the cycle and, correspondingly, the gas turbine size. With increasing compressor pressure ratio and decreasing gas turbine inlet temperature, the quantity of natural gas required relative to biomass is observed to decrease, while the exergy loss and exergy destruction rates are seen to increase. Furthermore, as the gas inlet temperature to the heat recovery steam generator rises, the exergy destruction rate increases and the exergy loss rate decreases. The highest exergy efficiency is exhibited by the gas turbine and the lowest by the combustor and the condenser.

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 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 score0.120
Threshold uncertainty score0.673

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 communication0.0000.001
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 head0.018
GPT teacher head0.256
Teacher spread0.238 · 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