CFD Modelling of Heat Soak-Back Phenomenon Inside a Gas Turbine Combustor
Bibliographic record
Abstract
The heat soak-back occurring in engines under post-shutdown conditions is a well-known phenomenon. This behavior is caused by the transmission of accumulated heat from hot parts or cavities during idle operation (such as turbines, contention rings, etc.) to colder ones (combustion chamber, injectors, etc.) when the airflow inside the engine approaches nullity. Then stagnant fluids in components such as the injectors (mainly TDE) and bearings become exposed to this heat which spreads by conduction, radiation and natural convection through the engine, and potentially leading fuel or oil to decompose and to form a build-up of carbon through a phenomenon called “coking”. Heat soak-back to engine components on shutdown, due to the thermal inertia of heated turbine parts, has the potential to cause deposits to build up in fuel injectors which can over time block the injectors. Blocked or partially blocked injectors must then be removed from the engine, inspected and sent for cleaning. Both soak-back and coking phenomenon have already been investigated by some motorists through experimental and structural (FEA) studies [1]. To the author’s knowledge however, no CFD model considering the airflow has yet been discussed, mainly because of the computing resources and the time it requires to simulate this unsteady phenomenon. As part of the present study and in order to fill in the gap on the availability of numerical data in the open literature for the heat soak-back occurring in a gas turbine combustor, the following investigation implies CFD simulation to predict the thermal behavior and magnitude of such a soak-back and its potential consequence on the fuel passages. A previous CFD simulation done by the authors showed that the use of a radiation model was required to provide some very reasonable results. As a follow up, the work to be presented in this paper will provide a more complete numerical soak-back procedure that can be used to predict the thermal behavior inside the combustor of a just shutdown gas turbine engine. Prior to the heat soak-back analysis, a non-premixed combustion model is run to simulate idle condition. Then these more realistic results for idle are used as initial conditions for the analysis of the transient heat dissipation occurring after shutdown. The following work includes a quick description of the experimental setup, and an introduction to the operational conditions for a simplified test rig. The full numerical procedure is then described. An analysis highlights the improved ability of the numerical model in predicting when the coking temperatures are reached using the adopted modeling techniques. It is observed that results obtained by the present model compare well with the experimental data to validate the simulation of this not so obvious natural convection phenomenon for a better understanding of this transient problem.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".