Optimization of a high through-flow design turbine using response surface method

Physics of Fluids, Journal Year: 2024, Volume and Issue: 36(4)

Published: April 1, 2024

Enhancing the through-flow capability of turbine facilitates potential to decrease external dimension engine, leading a reduction in weight and an increase thrust-to-weight ratio. The optimization blade profile terms aerodynamic design is essential strategy improve overall performance high turbine. This study aims develop automated technique, utilizing response surface method (RSM), enable reliable prediction rapid performance. A parametric modeling devised generate profiles with continuous curvature throughout process. Box–Behnken experimental design, combination Reynolds-averaged Navier–Stokes numerical calculation, employed construct second-order polynomial RSM approximation model. process comprises two levels: improving reducing loss. optimized profile, Opt1, achieves substantial 13.19% improvement at cost 12.27% Thus, further performed minimize loss based on Opt1 scheme. Geometric constraints are applied most influential parameters affecting mitigate their impacts. Compared final Opt2, 31.83% negligible sacrifice 0.23% capability.

Language: Английский

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A deep learning approach for hydrofoil optimization of tidal turbines

Ocean Engineering, Journal Year: 2024, Volume and Issue: 305, P. 117996 - 117996

Published: April 25, 2024

Language: Английский

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Data-driven surrogate modelling of multistage Taylor cone–jet dynamics

Physics of Fluids, Journal Year: 2024, Volume and Issue: 36(5)

Published: May 1, 2024

The Taylor cone jet is an electrohydrodynamic flow typically induced by applying external electric field to a liquid within capillary, commonly utilized in colloidal thrusters. This generation involves complex multiphase and multiphysics process, with stability contingent upon specific operational parameters. window intrinsically linked rate applied voltage magnitude. High voltages can induce atomization instabilities, resulting the production of electrospray. Our study presents initially numerical investigation into process using computational fluid dynamics. Implemented OpenFOAM, our model utilizes volume-of-fluid approach coupled Maxwell's equations incorporate body forces incompressible Navier–Stokes equations. We employ leaky-dielectric model, subjecting interface between phases hydrodynamic surface tension stress (Maxwell stress). With this we studied droplet breakup heptane jet, for range operation 1.53–7.0 nL s−1 2.4–4.5 kV extraction. First, developed high-fidelity solution acceleration droplets. Second, integrate machine learning capable extending parametric windows operation. Additionally, explore influence extractor plates on propulsion systems. work offers exploration cone–jet transition novel, numerically accurate approaches. Subsequently, models, specifically artificial neural network one-dimensional convolutional network, predict jet's performance under conditions not previously evaluated computationally heavy models. Notably, demonstrate that outperforms type application data, achieving 2% size prediction accuracy.

Language: Английский

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Cavitation intensity prediction and optimization for a Venturi cavitation reactor using deep learning

Physics of Fluids, Journal Year: 2024, Volume and Issue: 36(11)

Published: Nov. 1, 2024

The Venturi reactor, widely used in process intensification through hydrodynamic cavitation technology, has proven highly effective various chemical and environmental applications. intensity of a is primarily influenced by shape parameters such as the convergent angle (β1), throat diameter (dth), length (lth), divergent (β2). However, impact these on not been sufficiently clarified. In this study, structural optimization reactor was accomplished integrating deep neural networks with particle swarm optimization. Cavitation Intensity Prediction Network model, which combines artificial numerical simulation, to establish nonlinear relationship between intensity. Partial dependence plots individual conditional expectation were utilized clarify influence each parameter. findings reveal that optimal 2.76 times greater than original design. Reducing β1 resulted swift conversion static pressure into dynamic pressure, but it also caused an uneven distribution fluid velocity. To reduce unevenness allow reach its peak, advantageous for generation, lth should be extended. dth directly efficiency converting key factor determining β2 indirectly impacted modulating space available development. insights gained from study may provide valuable guidance designing Venturis

Language: Английский

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Investigation and improvement of kT−kL−ω transition model for pressure gradient and inflow effects

Physics of Fluids, Journal Year: 2025, Volume and Issue: 37(1)

Published: Jan. 1, 2025

Based on kT−kL−ω model, the corrections for turbulence intensity and pressure gradient are proposed. The modeling work focuses local Tulocal dimensionless velocity λP. extended model is applied to a variety of benchmark transition test cases, validating its reliability universality. For zero-pressure-gradient flat plate, has shown some encouraging results: it accurately predicted Transition Onset Location (TOL) under various intensities Reynolds numbers. In addition, non-zero-pressure-gradient correctly reflected effect adverse separation. last validation case NLF(1)-0416 (natural-laminar-flow(1)-0416) airfoil, which wealth experimental data at AoA (angle attack). calculations that involve up 31 conditions, successfully TOL majority scenarios captured trend changes. results suggest better equipped handle simulation complex working conditions.

Language: Английский

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Wind Turbine Optimization by Blade Element Momentum Method and Particle Swarm Optimization Technique

Journal of Engineering, Journal Year: 2025, Volume and Issue: 2025(1)

Published: Jan. 1, 2025

The aerodynamic efficiency of wind turbines is greatly influenced by the shape their airfoils. In this study, four airfoils were optimized to enhance performance a small horizontal axis turbine. optimization process involved adjusting thickness and camber using blade element momentum method particle swarm technique. goal was find most aerodynamically efficient airfoil based on thickness‐to‐camber ratio. compared select best one for three‐blade, 6‐m diameter turbine configuration. results showed that microturbine achieved better than baseline those other researchers. Notably, study also rigorously validated momentum–particle methodology through experimental methods, providing robust support our findings.

Language: Английский

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Aerodynamic investigation and flow loss control on a newly designed leading edge fillet in a high-load turbine

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 136617 - 136617

Published: May 1, 2025

Language: Английский

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Airfoil aerodynamic/stealth design based on conditional generative adversarial networks

Physics of Fluids, Journal Year: 2024, Volume and Issue: 36(7)

Published: July 1, 2024

Aerodynamic/stealth design is becoming an important factor in the advanced airfoil design. In this work, a supervised machine learning method proposed for aerodynamic and stealth integrated The conditional generative adversarial network (CGAN) constructed multidisciplinary of airfoil. Then, generator discriminator simply using deep neural have good robustness stability training. CGAN model also shows generalization capability test set, with less than 1% error fitting to profile data, generated airfoils are within 10% compared characteristics. addition, optimization results based on demonstrate that performance improvement would increase camber sharpen leading edge.

Language: Английский

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Design, optimization, and performance analysis of a subsonic high-through flow turbine

Physics of Fluids, Journal Year: 2024, Volume and Issue: 36(7)

Published: July 1, 2024

This paper presents the design method and numerical analysis results of a two-stage high-through flow (HTF) high-pressure turbine. Compared to conventional principles, HTF turbine proposed in this study is kind high coefficient scheme enables effectively increase output power thrust while maintaining same windward area. At speed, pressure ratio 3.8, with an adiabatic efficiency 91.46%. The coefficients first second stage are 0.76 0.86, respectively, loading 2.55 1.47. Detailed parameters, characteristics, aerodynamic performance presented paper. Based on preliminary result, was optimized for wide range operating conditions. computational fluid dynamics simulation show that compared traditional turbine, form changes from aft-loaded front-loaded. In addition, there certain tip leakage achieves efficiency, increasing rate, provides corresponding reference improving capacity.

Language: Английский

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Numerical simulations of self-sustained oscillation characteristics in cavity with high-Mach-number flow disturbances

Physics of Fluids, Journal Year: 2024, Volume and Issue: 36(8)

Published: Aug. 1, 2024

Oscillation characteristics in a cavity are investigated under real experimental conditions through unsteady numerical simulations of the time-evolving oscillatory damping high-Mach-number freestream over two-dimensional forward-facing cavity. The post-disturbance flow field is taken as initial condition. Temporal variations and wall resistance coefficient obtained. experiences underdamped behavior when subjected to disturbances. convergence oscillations influenced by volume, with significant reductions observed stagnation regions develop within During phase disturbance, each oscillation cycle consists gas injection jet phases. In former, external stagnates cavity, resulting gradual increase internal density pressure. High-temperature extend from into bow shocks approach wall, adversely affecting aerodynamic drag reduction thermal protection for aircrafts. phase, structure resembles opposing jet. As expelled, pressure decreases, forming cold that envelops cavity's surface. temperature boundary layer on surface pushed away thermal-protection drag-reduction effects. Transitions between phases induce instability states transition reaches its peak value; reverse results lowest coefficient.

Language: Английский

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