Optimization of a novel impulse gas turbine nozzle and blades design utilizing Taguchi method for micro-scale power generation
Bibliographic record
Abstract
This study is conducted to optimize the nozzle and blade of a compact non-combustion impulse gas turbine driven by the pressurized gas line with Computational Fluid Dynamics (CFD) approach and Taguchi method. For nozzle, throat diameter, nozzle inlet and outlet diameter and convergent-divergent length were investigated. Meanwhile, number of blades, blade radius, blade curvature angle, blade thickness and surface roughness were evaluated for blade. An L25 orthogonal array was chosen for both optimizations. Once optimized, the corresponding operating envelope was identified and compared against the original turbine. When operating at flow rate of 1.2MMSCFD and pressure of 69 bar, the turbine with optimized nozzle produces a maximum power output of 4383.59W at 5500 rpm, while with optimized blades produce 2058.64W at 5000 rpm. Combining optimized nozzle and blades produced 4928.64W at 6000 rpm. These produced powers are significantly higher than the original turbine maximum power of 1743.81W at 4500 rpm. This indicates potential performance enhancement of the turbine by optimizing its blade and nozzle geometry which is useful for its implementation on the offshore platform. To fully utilize this potential enhancement, the electric generator attached to the turbine shall be fine-tuned to have peak power at the optimum rpm band of the optimized turbine.
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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 | 0.001 | 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 | 0.001 |
| 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".