Experimental and numerical investigation on the flow field within a compact inlet duct

Vaccaro, John C.; Elimelech, Yossef; Chen, Yi; Sahni, Onkar; Jansen, Kenneth E.; Amitay, Michael

doi:10.1016/j.ijheatfluidflow.2013.08.004

Cited by 9 publications

(19 citation statements)

References 27 publications

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“…The present study expands on a previous investigation by the authors (Vaccaro et al, 2013) to include the effects of blowing on a short, diffusing, rectangular cross-sectional S-shaped duct in the compressible flow regime. A highly aggressive length-tohydraulic diameter ratio of 1.5 has been studied at a Mach number of 0.44, which corresponds to a hydraulic diameter based Reynolds number of 7.5 Â 10 5 .…”

Section: Introductionmentioning

confidence: 78%

“…This speed and duct geometry produced a maximum achievable Reynolds number based on exit hydraulic diameter, D, of 1.17 Â 10 6 . A detailed description of the test facility can be found in Vaccaro et al (2013). …”

Section: Wind Tunnel Facilitymentioning

confidence: 99%

“…The inlet duct geometry studied was identical to that of Vaccaro et al (2013). The offset inlet was a highly aggressive compact inlet with a length-to-hydraulic diameter ratio of 1.5 (Fig.…”

Section: Inlet Duct Geometrymentioning

confidence: 99%

“…This gave a total of forty measurement locations which were used to construct the AIP contour maps presented throughout this manuscript. A more detailed description can be found in Vaccaro et al (2013).…”

Section: Pressure Measurementsmentioning

confidence: 99%

“…The reader is referred to Vaccaro et al (2013) for a thorough description of the LaVision system and experimental set up. The flow field velocity components were computed by cross-correlating pairs of successive images with 50% overlap between the interrogation domains.…”

Section: Stereoscopic Particle Image Velocimetrymentioning

confidence: 99%

See 4 more Smart Citations

Experimental and numerical investigation on steady blowing flow control within a compact inlet duct

Vaccaro

Elimelech

Chen

et al. 2015

International Journal of Heat and Fluid Flow

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Section: Introductionmentioning

confidence: 78%

Section: Wind Tunnel Facilitymentioning

confidence: 99%

Section: Inlet Duct Geometrymentioning

confidence: 99%

Section: Pressure Measurementsmentioning

confidence: 99%

Section: Stereoscopic Particle Image Velocimetrymentioning

confidence: 99%

See 3 more Smart Citations

Experimental and numerical investigation on steady blowing flow control within a compact inlet duct

Vaccaro

Elimelech

Chen

et al. 2015

International Journal of Heat and Fluid Flow

Self Cite

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Design optimization of a compressor transition S-shaped duct using a teaching–learning-based optimization algorithm

Sharma

Baloni

2019

J Braz. Soc. Mech. Sci. Eng.

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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 teaching-learning-based optimization (MO-TLBO) algorithm in the area of S-shaped transition compressor duct. The present algorithm is applied for obtaining the optimum design of the S-shaped duct while minimizing the total pressure loss coefficient and non-uniformity index at the S-shaped duct outlet. These objectives are also optimized independently and as a multi-objective consideration as well. Because of the conflicting nature of the objective functions, a Pareto-optimal curve is also presented for a successful trade-off between the objectives. Pareto-optimal curve gives flexibility to the designer for selecting the best set of the parameters based on the objectives. Successful execution of the proposed MO-TLBO algorithm is examined by comparing the optimum results acquired by the multi-objective genetic algorithm and comparisons divulge that the TLBO algorithm can be successfully practiced to obtain the optimized design of compressor transition S-shaped duct. Optimized duct shows the reduction in total pressure loss and non-uniformity by 28.80% and 36.67%, respectively, despite the reduction of 14.74% in overall length.

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Design optimization of S-shaped compressor transition duct using particle swarm optimization algorithm

Sharma

Baloni

2020

SN Appl. Sci.

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A high-bypass turbofan engine transfers air from low-to the high-pressure compressor through an S-shaped transition duct. Minimization of the total pressure loss and maximization of uniform flow are key factors to ensure the maximum performance of the S-shaped transition duct. The conventional design approach is time-consuming and does not guarantee an optimal solution. Hence, the present article is based on the application of optimization for the S-shaped compressor transition duct. The optimization is carried out on the basis of shape parameters to minimize objectives namely pressure loss coefficient and non-uniformity with the reduction of length of the S-shaped transition duct. The 2-D axisymmetric approach of computational fluid dynamics is used as a design tool for performance evaluation with optimization techniques. The simulation model is validated with the available experimental results of the literature. The correlation between the response and independent variables is established with the help of the second-order polynomial response surface methodology. Further, individual optimization is carried out for single-objective consideration using particle swarm optimization and gray wolf optimization algorithms. As the results of single-objective optimization depict the conflicts between both objectives, later optimization using multi-objective particle swarm optimization and multi-objective gray wolf optimization algorithms is carried out. The performance metrics are obtained and compared. The 'TOPSIS' method is applied to get best solution out of multiple solutions. The optimized duct reduced pressure loss coefficient and non-uniformity index by 28.14% and 43.33% with a reduction of 6.37% of length compared to baseline S-shaped duct.

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Experimental and numerical investigation on the flow field within a compact inlet duct

Cited by 9 publications

References 27 publications

Experimental and numerical investigation on steady blowing flow control within a compact inlet duct

Experimental and numerical investigation on steady blowing flow control within a compact inlet duct

Design optimization of a compressor transition S-shaped duct using a teaching–learning-based optimization algorithm

Design optimization of S-shaped compressor transition duct using particle swarm optimization algorithm

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