Techno-economic assessment of CO2 quality effect on its storage and transport
Bibliographic record
Abstract
This paper presents and overview of the current FP7 European Commission CO2QUEST project involving the collaboration of 12 industry and academic partners in Europe, China and Canada aimed at addressing fundamentally important and urgent issues regarding the impact of the typical CO2 streams impurities captured from fossil fuel power plants on its safe and economic transportation and storage. The work programme, spanning 36 months, focuses on the development of state-of-the-art mathematical models, backed, by laboratory and industrial-scale experimentation using unique EC-funded test facilities to perform a comprehensive techno-economic, risk-based assessment of the impact of the CO2 stream impurities on the phase behaviour and the physico-chemical reactions governing the pipeline and storage site integrities. The above involves the determination of the important CO2 mixtures that have the most profound impact upon the pipeline pressure drop, compressor power requirements, pipeline propensity to ductile and brittle facture propagation, corrosion of the pipeline and well bore materials, geochemical interactions within the well bore and storage site, and the ensuing health and environmental hazards. Based on a cost/benefit analysis and whole system approach, the results will in turn be used to provide recommendations for tolerance levels, mixing protocols and control measures for pipeline networks and storage infrastructure thus contributing to the development of relevant standards for the safe design and operation of CCS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".