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Record W4402563322 · doi:10.1016/j.egyr.2024.09.013

Analysis of in-bin low-temperature and high-temperature grain drying in Alberta: Specific energy, carbon costs and policy implications

2024· article· en· W4402563322 on OpenAlexafffundabout
Shubham Subrot Panigrahi, Lorne Grieger, C. B. Singh

Bibliographic record

VenueEnergy Reports · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Drying and Modeling
Canadian institutionsGenome PrairieLethbridge CollegeUniversity of Lethbridge
FundersAlberta Wheat Commission
KeywordsBinCarbon fibersMaterials scienceEnvironmental scienceActivation energyChemistryComposite materialEngineeringPhysical chemistryMechanical engineering

Abstract

fetched live from OpenAlex

Optimizing grain drying process is pivotal for both economic viability and environmental sustainability. In cold countries, supplemental heating is paramount but instigates the issue of carbon release at the same time. To curve the emission, a carbon levy has been imposed that varies with fuel types. However, there is limited knowledge of the impact of field-adaptable technologies utilizing commercialized fuels on the optimal execution of grain drying. To explore this, a comprehensive three-year on-farm grain drying study was conducted in the province of Alberta, Canada. This comparative analysis centered on three critical aspects, i.e., specific energy consumption, greenhouse gas emissions (GHGs), and operating costs. Furthermore, the research extended its projections into the year 2030, accounting for the impact of gradual carbon levies on natural gas, propane, and diesel fuel systems. showed that indirect heaters in in-bin systems were 38 % more energy-efficient than direct heaters due to better airflow and higher initial grain temperatures, while indirect heaters with diesel burners exhibited 27.8 % lower burner turndown ratios and 35.4 % higher energy consumption than natural gas counterparts. In high-temperature drying, natural gas consumption decreased as supply air temperatures rose, with double-flow dryer showing the lowest energy consumption (6.3±1.9 GJ/t) in comparison to mixed-flow and cross-flow dryer due to waste heat recovery. Heaters and Dryers operated at varying load capacities, indicated 126–135 % increase in natural gas cost with carbon levy by 2030. Achieving lower specific energy consumption in grain drying requires precise burner and process control, along with maintenance, offering valuable guidance for producers. • Indirect heaters were 38 % efficient than direct heaters in this study. • Diesel fuel in indirect heaters was 35.4 % less efficient than natural gas. • Natural gas will see 126–135 % increment in drying cost by 2030. • Grain drying rate could be higher or lower than fuel consumption rate. • Adjusting burner load is crucial for lowest energy consumption.

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 score0.880
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.007
GPT teacher head0.219
Teacher spread0.212 · 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

Citations0
Published2024
Admission routes3
Has abstractyes

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