Post-Surge Load Prediction for Multi-Stage Compressors via CFD Simulations
Bibliographic record
Abstract
A methodology is proposed and developed for the simulation of post-surge condition in a multi-stage compressor that is part of a gas generator system that also includes the combustor and turbine and ducts. Given the essentially one-dimensional nature of surge, the approach basically consists of coupling single blade passage multi-stage RANS CFD simulations of the compressor for with 1D equations modelling the behaviour of the other components applied as dynamic boundary conditions. This method allows for the simulation of the flow behaviour inside a multi-stage compressor during surge and, by extension, for the prediction at the design phase of the time variation of aerodynamic forces on the blades and of the pressure and temperature at bleed locations inside the compressor used for turbine cooling. The main advantages of this method over existing methods are its relatively modest computational time and resource requirements and the fact that it does not require any empirical data input beyond what is used in standard CFD simulations. The method is implemented in a commercial CFD code (ANSYS CFX) and applied to three compressor geometries with distinct features. Simulations on a low-speed (incompressible) three stage axial compressor allows for a validation with experimental data, which shows that the proposed methodology captures the surge behaviour of the system very well both qualitatively and quantitatively. This comparison also highlights the strong dependence of the surge cycle frequency on the volume of the downstream plenum (combustion chamber). Subsequently, the addition of a low-speed centrifugal compressor to the previous compressor is used to demonstrate the adaptability of the approach to a multi-stage axial-centrifugal configuration, yielding qualitatively realistic surge results. Finally, application of the method to an industrial transonic compressor geometry demonstrates the tool on a mixed flow-centrifugal compressor configuration operating in a highly compressible flow regime. A comparison of predicted versus measured shaft loading amplitude during surge is highly promising.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".