Computational optimization for the deposition of bioconvection thin Oldroyd-B nanofluid with entropy generation

The behavior of an Oldroyd-B nanoliquid film sprayed on a stretching cylinder is investigated. The system also contains gyrotactic microorganisms with heat and mass transfer flow. Similarity transformations are used to make the governing equations non-dimensional ordinary differential equations and subsequently are solved through an efficient and powerful analytic technique namely homotopy analysis method (HAM). The roles of all dimensionless profiles and spray rate have been investigated. Velocity decreases with the magnetic field strength and Oldroyd-B nanofluid parameter. Temperature is increased with increasing the Brownian motion parameter while it is decreased with the increasing values of Prandtl and Reynolds numbers. Nanoparticle’s concentration is enhanced with the higher values of Reynolds number and activation energy parameter. Gyrotactic microorganism density increases with bioconvection Rayleigh number while it decreases with Peclet number. The film size naturally increases with the spray rate in a nonlinear way. A close agreement is achieved by comparing the present results with the published results.

Aeroelastic scaling of flying demonstrator: flutter matching

The traditional approach for the design of aeroelastically scaled models assumes that either there exists flow similarity between the full-size aircraft and the model, or that flow non-similarities have a negligible effect. However, when trying to reproduce the behavior of an airliner that flies at transonic conditions using a scaled model that flies at nearly-incompressible flow conditions, this assumption is no longer valid and both flutter speed and static aerodynamic loading are subject to large discrepancies. To address this issue, we present an optimization-based approach for wing planform design that matches the scaled flutter speeds and modes of the reference aircraft when the Mach number cannot be matched. This is achieved by minimizing the squared error between the full-size and scaled aerodynamic models. This method is validated using the Common Research Model wing at the reference aircraft Mach number. The error in flutter speed is computed using the same wing at model conditions, which are in the nearly-incompressible regime. Starting from the baseline wing, its planform is optimized to match the reference response despite different conditions, achieving a reduction of the error in the predicted flutter speed from 7.79% to 2.13%.

Research on the Application of Partial Similarity for a 1-1/2 Axial Compressor

In this paper, a method based on the partial similarity principle is presented to improve the aerodynamic design with low cost and high accuracy for a 1-1/2 axial compressor. By means of this method, during the process of a similar design, the machine Mach number and flowrate coefficient are maintained. The flow similarity between the prototype and its large-scaled alternative was observed, according to a detailed analysis of flow fields of rotor and stator. As well, the relative discrepancies of isentropic efficiency and pressure ratio between two models are 1.25% and 0.4% at design point, respectively. Besides, their performance curves agreed very well in the whole operating range. Moreover, it was also found that the flow similarity between the two models can be maintained under unsteady working conditions. Thereafter, in order to investigate the impact of stability optimization method on the similarity principle, casing treatment with single circumferential groove was applied to these two models. The flow similarity was still maintained and the flowrate near the stall was reduced about 1.1% with negligible deterioration of the overall performance.

Performance Analysis and Improvement of a Centrifugal Compressor Based on Partial Similarity Principle

In this paper, with the help of partial similarity principle, aerodynamic performance of a centrifugal compressor in a turbocharger unit is analyzed and improved based on a low-speed large-scaled model. In order to achieve flow similarity between the scaled compressor and the prototype, tip clearance and diffuser outlet diameter have been modified further. It is observed from the numerical results that the relative error between the scaled compressor and the prototype is less than 0.8%. It means that the flow field of the scaled compressor is similar to the prototype though the Reynolds number is neglected during the scaling process. Furthermore, the large-scaled impeller has been improved by analyzing the numerical results, and then, the improved impeller is scaled down back to the smaller one by using the partial similarity principle, which geometric dimensions have the same level as those of the prototype but performance is improved obviously. Meanwhile, the experiment results are used to validate the method.

Effects of NP Shapes on Non-Newtonian Bio-Nanofluid Flow in Suction/Blowing Process with Convective Condition: Sisko Model

The present mathematical simulation deals with the study of heat transfer characteristics of the shape of gold nanoparticles (Au-NPs) on blood flow past an exponentially stretching sheet using Sisko nanofluid taking into account the Biot number effect. Influences of non-linear thermal radiation and suction/injection are considered. The one-phase model is used to describe the Sisko nanofluid flow. Similarity variables are performed to convert the non-linear PDEs into ordinary ones. These equations together with initial and boundary conditions are provided in a non-dimensional form and then resolved numerically utilizing the fourth–fifth-order Runge–Kutta–Fehlberg (RKF45) technique. The attitude of diverse flow quantities is investigated and examined via the study of parameters like the Au-NP volume fraction, the non-linear stretching parameter, and the Biot number. It is found that the Biot number improves the heat transfer rate markedly. In the blowing case, the blade-shaped Au-NPs show the highest heat transfer rate; in the suction case, the contrary is observed for spherical Au-NPs.

Monin–Obukhov Similarity Theory for Modeling of Wind Turbine Wakes under Atmospheric Stable Conditions: Breakdown and Modifications

Monin–Obukhov similarity theory (MOST) overestimates the mean vertical velocity gradient in some atmospheric stable conditions, i.e., Richardson number R f < 0 . 25 . To obtain a given hub-height inflow velocity for a certain roughness length, this overestimated velocity gradient underpredicts the friction wind speed and the turbulence intensity, potentially influencing wake modeling of a wind turbine. This work investigates the side effects of the breakdown of MOST on wake modeling under stable conditions and makes some modifications to the flow similarity functions to eliminate these side effects. Based on a field measurement in a wind farm, we first show that MOST predicts a larger velocity gradient for the atmospheric stability parameter ζ > 0 . 1 and proposes new flow similarity functions without constraining R f to limit the overestimated velocity gradient. Next, different turbulence models based on MOST and a modified one based on the new similarity functions are investigated through numerical simulations. These turbulence models are combined with the actuator disk model (AD) and Reynolds-averaged Navier–Stokes equations (RANS) to model wind turbine wakes under stable conditions. As compared to measurements, numerical results show that turbulence models based on MOST result in a larger wake deficit and a slower wake recovery rate with a root-mean-squared error (RSME) of wake deficit in the range of 0.07 to 0.20. This overestimated wake effect is improved by applying the new similarity functions, and the RSME of wake deficit is reduced by 0.05 on average.

Monin-Obukhov Similarity Theory for Modeling of Wind Turbine Wakes under Atmospheric Stable Conditions: Breakdown and Modifications

Monin-Obukhov similarity theory (MOST) overestimates wind shear in some atmospheric stable conditions, i.e. Richardson number $R_f&lt;0.25$. The overestimated wind shear that leads to an under-predicted friction wind speed and a lower ambient turbulence intensity for a given hub-height reference wind speed and a given roughness length, could influence wake modeling of a wind turbine. This work investigates the side effects of the breakdown of MOST on wake modeling under stable conditions and makes some modifications to the flow similarity functions to eliminate these side effects. Based on a field measurement in a wind farm, we firstly show that MOST predicts a larger wind shear for the atmospheric stability parameter $\zeta&gt;0.1$ and proposes new flow similarity functions without constraining $R_f$ to limit the overestimated wind shear by MOST. Next, different turbulence models based on MOST and a modified one based on the new similarity functions are investigated through numerical simulations. These turbulence models are combined with the actuator disk model (AD) and Reynolds-averaged Navier&ndash;Stokes equations (RANS) to model wind turbine wakes under stable conditions. As compared to measurements, numerical results show that turbulence models based on MOST result in larger wake deficits and slower wake recovery rate with a square root of the mean-squared-error (RSME) of wake deficit in the range of 0.07-0.18. This overestimated wake effect is improved by applying the new similarity functions and the RSME of wake deficit is averagely reduced by 0.05. Finally, we check the role of the under-predicted turbulence intensity playing in the larger wake deficit predicted by models based MOST. Additional numerical simulations using the modified turbulence model are carried out, in which the roughness length is reduced to impose a hub-height ambient turbulence intensity equivalent to the MOST case. Simulation results show that reducing turbulence intensity enhances wake effects, however, it cannot reproduce the large wake deficit predicted by models based on MOST, which suggests that the overestimated wake effect by MOST could be also related to the overestimated wind shear.