Experimental and Computational Analysis of Additive Manufactured Augmented Backside Liner Cooling Surfaces for Use in Micro-Gas Turbines
Bibliographic record
Abstract
Abstract Augmented backside cooling refers to the enhancement of the backside convection of a combustor liner using extended heat transfer surfaces to fully utilize the cooling air by maximizing the heat transfer to pumping ratio characteristic. Although film cooling has and still is widely used in the gas turbine industry, augmented backside cooling has been in development for decades now. The reason for this is to reduce the amount of air used for liner cooling and to also reduce the emissions caused by using film cooling in the primary zones. In the case of micro-gas turbines, emissions are of even greater importance, since the regulations for such engines will most likely become stricter in the following years due to a global effort to reduce emissions. Furthermore, the liners investigated in this paper are for a 10 kWe micro-turbine, destine for various potential markets, such as combined heat and power for houses, electric vehicle hybrids and even small unmanned aerial vehicles. The majority of these markets require long service intervals, which in turn requires the combustor liners to be under the least amount of thermal stress possible. The desire to also increase combustor inlet temperatures with the use of recuperated exhaust gases, which in turn increase the overall system efficiency, limits the cooling effectiveness of the inlet air. Due to all these reasons, an advanced form of augmented backside cooling would be of substantial significance in such a system. Currently, some very simple designs are used in the form of straight plain fins, transverse strips, or other similar geometries, but the creation of high heat transfer efficiency surfaces in such small sizes becomes very difficult with traditional subtractive manufacturing methods. When using additive manufacturing though these types of surfaces are not an issue. This paper covers the comparison of experimental results with conjugate heat transfer computational fluid dynamics (CFD) models and empirical heat balance models for two different additively manufactured (AM) liner cooling geometries and an AM blank liner. The two cooling fin geometries include a rotating plain fin and an offset strip fin. The liners were tested in an AM-built reverse flow radial swirl stabilized combustion chamber at a variety of operating conditions. During the experiments, the surfaces were compared using a thermal camera to record the outer liner temperature, which was viewed through a quartz outer casing. The experimental results showed that the cooling surfaces were effective at reducing the liner temperatures with minimal pressure losses for multiple operating points. Those results were then compared against the conjugate heat transfer CFD models and the empirical calculations used to design the surfaces initially. From this comparison, it was noticed both the CFD and empirical calculations under-predicted the wall temperatures. This is thought to be due to inaccuracies in the predicted flame temperatures and the assumed emissivity values used to calibrate the thermal imaging camera. Further uncertainties arise from the assumption of a constant air and hot gas temperature and mass flow along the cooling surfaces and the lack of data for the surface roughness of the parts.
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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) | 0.001 | 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".