Measurements of Decompression Wave Speed in Simulated Anthropogenic Carbon Dioxide Mixtures Containing Hydrogen
Bibliographic record
Abstract
In order to determine the material fracture resistance necessary to provide adequate control of ductile fracture propagation in a pipeline, a knowledge of the decompression wave speed following the quasi-instantaneous formation of an unstable, full-bore rupture is necessary. The thermodynamic and fluid dynamics background of such calculations is understood, but predictions based on specific equations of state (EOS) need to be validated against experimental measurements. A program of tests has been conducted using a specially constructed shock tube to determine the impact of impurities on the decompression wave speed in carbon dioxide (CO2), so that the results can be compared to two existing theoretical models. In this paper, data and analysis results are presented for three shock tube tests involving anthropogenic CO2 mixtures containing hydrogen as the primary impurity. The first mixture was intended to represent a typical scenario of precombustion carbon capture and storage (CCS) technology, where typically the concentration of CO2 is around 95–97% (mole). The second mixture represents a worst case scenario of this technology with high level of impurities (with CO2 concentration around 85%). The third test represents a typical chemical-looping combustion process. It was found that the extent of the plateau on the decompression wave speed curves in these tests depends on the location of the phase boundary crossing along the bubble-point curve. The closer the phase boundary crossing to the critical point, the shorter the plateau. This is primarily due to the change in magnitude of the drop in the speed of sound at phase boundary crossing. For the most part, the predictions of the plateau pressure by both of the EOS that were evaluated, GERG-2008 and Peng–Robinson (PR), are in good agreement with measurements by the shock tube. This by no means reflects overall good performance of either EOS, but was rather due to the fact that the isentropes intersected the phase envelope near the critical point, or that the concentration of H2 was relatively low, either in absolute terms or relative to other impurity constituents. Hence, its influence in causing inaccurate prediction of the plateau pressure is lessened. An example of pipeline material toughness required to arrest ductile fracture is presented which shows that predictions by GERG-2008 are more conservative and are therefore recommended.
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 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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".