Novel, low energy, pre-combustion carbon capture feasibility study = Estudio de factibilidad de novedoso proceso de captura de carbono pre-combustion
Bibliographic record
Abstract
This research is focused on obtaining an important reduction in greenhouse gas (GHG) emissions resulting from the use of fossil fuels by increasing the efficiency of pre-combustion carbon capture. It examines a new, low-risk, approach that uses conventional water gas shift reactors and acid gas removal technology in a unusual arrangement, within an Integrated Gasification Combined Cycle power plant (IGCC). Timmins (2010) proposed a flowsheet of this nature and it is this flowsheet that is used as the starting point for this research project. Process simulation in UniSim Design R390 is conducted to validate the viability of such a flowsheet and to investigate optimal plant configuration. The modelling output is compared to US DOE baseline studies for competing technologies (2010).The physical solvent, Selexol, is used for cardon dioxide (CO2) absorption as recommended by researchers as the most energy efficient amongst the range of physical and chemical solvents investigated. There are mainly two thermodynamic models required to meet all of the needs of this complex process. Most of the process is modelled with the Peng-Robinson equation of state but the Selexol absorber and desorber is modelled using the non-random-two-liquid model (NRTL) for the liquid phase and the ideal gas law for the vapour phase. A beseline flowsheet model is successfully modelled that could be attached to an IGCC plant to enable it to continue producing electric power whilst capturing 90% of the carbon derived from the fuel. The model is used for process development, and for energy efficiency evaluation. Every major item of capital equipment has been included, modelled and sized to produce a cost analysis and additionallly, the model output was used for a preliminary life cycle analysis (LCA). From the results produced in this study, the proposed process appears to be a feasible, energy-efficient, alternative technology for incorporating carbon capture within an IGCC flowsheet.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".