Measurements of Decompression Wave Speed in Pure Carbon Dioxide and Comparison With Predictions by Equation of State
Bibliographic record
Abstract
Carbon dioxide capture and storage (CCS) is one of the technologies that have been proposed to reduce emissions of carbon dioxide (CO2) to the atmosphere. CCS will require the transportation of the CO2 from the “capture” locations to the “storage” locations via large-scale pipeline projects. One of the key requirements for the design and operation of pipelines in all jurisdictions is fracture control. Supercritical CO2 is a particularly challenging fluid from this point of view, because its thermodynamic characteristics are such that a very high driving force for fracture can be sustained for a long time. Even though CO2 is not flammable, it is an asphyxiating gas that is denser than air, and can collect in low-lying areas. Additionally, it is well known that any pipeline rupture, regardless of the nature of the fluid it is transporting, has a damaging reputational, commercial, logistic, and end user impact. Therefore, it is as important to control fracture in a CO2 pipeline as in one transporting a flammable fluid. With materials specified appropriately for the prevention of brittle failure, the key element is the control of propagating ductile (or tearing) fracture. The determination of the required toughness for the arrest of ductile fracture requires knowledge of the decompression behavior of the contained fluid, which in turn requires accurate knowledge of its thermodynamic characteristics along the decompression isentrope. While thermodynamic models based on appropriate EOS (equations of state) are available that will, in principle, allow determination of the decompression wave speed, they, in general, have not been fully validated for very rapid transients following a rupture. This paper presents experimental results of the decompression wave speed obtained from shock tube tests conducted on pure CO2 from different initial conditions, and comparison with predictions by models based on GERG-2008, Peng-Robinson, and BWRS equations of state (EOS). These tests were conducted as a baseline before introducing various impurities.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".