2019
DOI: 10.1007/s40430-019-2072-5
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Design optimization of a compressor transition S-shaped duct using a teaching–learning-based optimization algorithm

Abstract: A high bypass turbofan aero-engine delivers compressed air from the low-pressure to the high-pressure compressor through a compressor transition duct. Weight and design space limitations impel to its S-shaped design. Despite that, the compressor transition duct has to guide the flow very carefully to the high-pressure compressor without disturbances and flow separations. Hence, the present paper is devoted to elaborate on the application of the proposed heuristic optimization technique known as multi-objective… Show more

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Cited by 6 publications
(2 citation statements)
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“…-Implementing non-axisymmetric end wall contouring on hub and shroud wall, a 19% length reduction of the baseline duct could be further possible along with a 2% reduction in loss. Sharma and Baloni [76] Teaching learning based optimization algorithm -The proposed design showed 28.80%, 36.67% reduction in pressure loss and non-uniformity respectively despite 14.74% length reduction.…”
Section: Authors Technique Remarkmentioning
confidence: 96%
“…-Implementing non-axisymmetric end wall contouring on hub and shroud wall, a 19% length reduction of the baseline duct could be further possible along with a 2% reduction in loss. Sharma and Baloni [76] Teaching learning based optimization algorithm -The proposed design showed 28.80%, 36.67% reduction in pressure loss and non-uniformity respectively despite 14.74% length reduction.…”
Section: Authors Technique Remarkmentioning
confidence: 96%
“…After optimizing the design, the radial drop length ratio of the transition duct had been increased by 11.6% compared with that of the prototype, the total pressure loss had been reduced by 36.9% and the parameter distribution at the outlet was more uniform. In 2019, Sharma et al 17 applied a multi-objective teaching–learning-based optimization algorithm to the s-shaped transition compressor duct. Compared with the prototype, the total pressure loss and non-uniformity of the optimized duct were reduced by 28.80% and 36.67%, respectively, despite the overall length being reduced by 14.74%.…”
Section: Introductionmentioning
confidence: 99%