Electromagnetically-induced transparency (EIT) is observed and analyzed for the group velocity of a femtosecond light pulse interacting with GaAs/AlGaAs multiple quantum wells (MQWs) in a transient regime. The calculated slowdown factor of the group velocity inside the medium due to the dynamic refractive index change is approximately 2.10 x 10(3). We discuss the potential of EIT-induced slow light in GaAs/AlGaAs MQWs for ultrafast (approximately 210 GHz) all-optical information processing such as photon routing.

Au nanoparticles exhibited both negative and positive nonlinear absorptions with ground-state plasmon bleaching and free-carrier absorption that could be origins of the saturable and reverse-saturable optical properties. Au/Ag coreshells displayed only positive nonlinear absorption and reverse-saturable optical properties as a function of excitation intensity at the edge of surface-plasmon resonance, which implies no ground-state plasmon bleaching and the existence of two-photon absorption.

This paper presents an investigation of a circumferential feed-back channel located on shroud surface in rotor domain to find its effects on aerodynamic performance of a single-stage axial compressor, NASA Stage 37, using three-dimensional Reynolds-averaged Navier-Stokes equations. Validation of numerical results was performed using experimental data for both of single rotor and single-stage compressors. A parametric study of the feed-back channel was performed using various geometric parameters related to the locations and shapes of the channel inlet and outlet. The numerical results showed that a reference circumferential feed-back channel increased the stall margin by 26.8% with 0.14% reduction in the peak adiabatic efficiency, compared to the case without the feed-back channel.

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Inlet flow direction significantly affects the hydraulic performance of an axial-flow pump. Usually, the research papers ignore this phenomenon, resulting in discrepancies between simulation and experimental results. This study examines the influence of inflow direction in five cases (0%, 5%, 10%, 15%, and 30% pre-swirl intensities) to determine the relationship between the pre-swirl intensity and the hydraulic performance of the axial-flow pump. Based on this, changing the setting angle of the inlet guide vane (IGV) is proposed and thoroughly investigated to reduce the effect of inflow direction. In this study, the influence of clearances in IGV blades on hydraulic performance is also investigated in detail. Numerical simulations are performed using ANSYS–CFX and a shear stress transport reattachment modification (SST k-$$\omega$$ ω ) turbulence model with small y+ values at all walls. Specifically, the hydraulic performance curves and internal flow characteristics, including contours and streamlines, are assessed and analyzed. The inflow direction significantly impacts the hydraulic efficiency of the axial-flow pump. Increased pre-swirl intensity causes more loss in the IGV passage. The internal flow field and performance are not affected by the clearance at the hub and shroud of the IGV. However, the tip clearance of the impeller causes a decrease in hydraulic efficiency due to the tip leakage vortex. By adjusting the setting angle of the IGV, the efficiency and head gradually increase from a negative to a positive setting angle. Additionally, 30° is considered the critical setting angle for IGV.

In order to maximize the mixing performance of a micromixer with an integrated three-dimensional serpentine and split-and-recombination configuration, multi-objective optimizations were performed at two different Reynolds numbers, 1 and 120, based on numerical simulation. Numerical analyses of fluid flow and mixing in the micromixer were performed using three-dimensional Navier-Stokes equations and convection-diffusion equation. Three dimensionless design variables that were related to the geometry of the micromixer were selected as design variables for optimization. Mixing index at the exit and pressure drop through the micromixer were employed as two objective functions. A parametric study was carried out to explore the effects of the design variables on the objective functions. Latin hypercube sampling method as a design-of-experiment technique has been used to select design points in the design space. Surrogate modeling of the objective functions was performed by using radial basis neural network. Concave Pareto-optimal curves comprising of Pareto-optimal solutions that represents the trade-off between the objective functions were obtained using a multi-objective genetic algorithm at Re = 1 and 120. Through the optimizations, maximum enhancements of 18.8% and 6.0% in mixing index were achieved at Re = 1 and 120, respectively.

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