MétaCan
Menu
Back to cohort
Record W2899145948 · doi:10.14288/1.0371603

Development of a quantitative risk analysis approach to evaluate the economic performance of an industrial-scale biorefinery

2018· article· en· W2899145948 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOpen Collections · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Business Development Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsScale (ratio)Quantitative analysis (chemistry)BiorefineryEconomic analysisRisk analysis (engineering)BusinessEconomicsEngineeringAgricultural economicsGeographyWaste management

Abstract

fetched live from OpenAlex

The overall objective of this dissertation was to evaluate the economic performance of a commercial-scale biorefinery given the volatility in the market price of the final product and the variability in the biomass delivered cost. To this end, a risk analysis methodology comprised of five steps was developed: 1) construct the supply area geographical data base, 2) perform Monte Carlo simulation via the Integrated Biomass Supply Analysis and Logistics Multi-Crop model (IBSAL-MC) to produce the biomass delivered cost distribution, 3) conduct economic analysis by combining the biomass delivered cost distribution with the product market price to generate a ROI (return on investment) heat map, 4) repeat Steps 1 to 3 for an alternative scenario and 5) compare heat maps from different scenarios to quantify the effectiveness and incentive available for achieving an alternative scenario. The proposed methodology was applied to a cellulosic sugar plant under construction in Southwestern Ontario, Canada. Three biorefinery scenarios were considered including small-scale (175 dry tonnes (dt)/day), medium-scale (520 dt/day) and large-scale (860 dt/day). Results showed that the magnitude of the required logistical resources and their associated upfront and administrative costs hindered the biorefinery’s economic performance as its scale increased. The risk analysis approach was then applied to the small-scale scenario. Potential economic incentives for participating biomass producers were quantified as the participation rate increased from 20% to 30%, 40% and 50. While increasing farm participation rate was economically beneficial to the biorefinery, there were more economic benefits if the sugar market price was in a favourable range. When a farmers’ co-operative was introduced to the supply system, if the biorefinery could secure a long-term consumer of the produced sugar in the price range of $425-575/tonne, the farmers’ co-operative and other investors of the biomass project were both more likely to achieve an acceptable annual ROI that exceeds 10%.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.714

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.121
GPT teacher head0.285
Teacher spread0.165 · 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