Elliptic supersonic jet morphology manipulation using sharp-tipped lobes

Elliptic nozzle geometry is attractive for mixing enhancement of supersonic jets. However, jet dynamics, such as flapping, gives rise to high-intensity tonal sound. We experimentally manipulate the supersonic elliptic jet morphology by using two sharp-tipped lobes. The lobes are placed on either end of the minor axis in an elliptic nozzle. The design Mach number and the aspect ratio of the elliptic nozzle and the lobed nozzle are 2.0 and 1.65. The supersonic jet is exhausted into ambient at almost perfectly expanded conditions. Time-resolved schlieren imaging, longitudinal and cross-sectional planar laser Mie-scattering imaging, planar Particle Image Velocimetry, and near-field microphone measurements are performed to assess the fluidic behavior of the two nozzles. Dynamic Mode and Proper Orthogonal Decomposition (DMD and POD) analysis are carried out on the schlieren and the Mie-scattering images. Mixing characteristics are extracted from the Mie-scattering images through the image processing routines. The flapping elliptic jet consists of two dominant DMD modes, while the lobed nozzle has only one dominant mode, and the flapping is suppressed. Microphone measurements show the associated noise reduction. The jet column bifurcates in the lobed nozzle enabling a larger surface contact area with the ambient fluid and higher mixing rates in the near-field of the nozzle exit. The jet width growth rate of the two-lobed nozzle is about twice as that of the elliptic jet in the near-field, and there is a 40\% reduction in the potential core length. Particle Image Velocimetry (PIV) contours substantiate the results.Comment: 19 pages, 16 figures. Revised version submitted to Physics of Fluids for peer review. URL of the Video files (Fig. 6 & Fig. 14) are given in the text files (see in '/anc/*.txt'

Development of Maximum Conical Shock Angle Limit for Osculating Cone Waveriders

Hypersonic waveriders are special shapes with leading edges coincident with the body's shock wave, yielding high lift-to-drag ratios. The waverider geometry results from streamline tracing using the solutions of a basic flow field such as the wedge or the cone for specified shock and base curves. The base and shock curves can be independently prescribed in the osculating cone method enabling a larger design space. Generally, low values of the conical shock angle (9-15 degrees) are used. The lack of any method to limit the maximum cone angle for osculating cone waverider motivates this study. Mathematical expressions are derived for geometrical conditions that result in successful osculating cone waverider generation. A power law curve and a Bezier curve are analyzed. Closed-form expressions for the maximum cone shock angle are obtained for the power law curve. A numerical procedure to solve the same for the Bezier curve is developed. The results, for a typical Mach number of 6.0, evidently show that the maximum cone shock angle for successful waverider generation is significantly lower than the maximum angle for attached shock solutions. The limiting conditions developed will be essential in constraining the waverider sample space for automated multiobjective optimization routines

A novel Artificial Neural Network-based streamline tracing strategy applied to hypersonic waverider design

Streamline tracing in conical hypersonic flows is essential for designing high-performance waverider and intake. Conventionally, the streamline equations are solved after obtaining the velocity field from the solution of the axisymmetric conical flow field. The hypersonic waverider shape is generated from the base conical flow field by repeatedly applying the streamline tracing approach along several planes. When exploring the design space for optimization of the waverider, streamline tracing can be computationally expensive. We provide a novel strategy where first the Taylor-Maccoll equations for the inviscid axisymmetric conical flowfield and the streamlines from the shock are solved for a wide range of cone angle and Mach number conditions resulting in an extensive database. The streamlines are parametrized by a third-order polynomial, and an Artificial Neural Network (ANN) is trained to predict the coefficients of the polynomial for arbitrary inputs of Mach number, cone angle, and streamline originating location on the shock . We apply this strategy to design a cone derived waverider and compare the geometry obtained with the standard conical waverider design method and the simplified waverider design method. The ANN technique is highly accurate, with a difference of 0.68% with the standard in the coordinates of the waverider. RANS computations show that the ANN derived waverider does not indicate severe flow spillage at the leading edge, which is observed in the waverider generated from the simplified method. The new ANN-based approach is 20 times faster than the conventional method

A censura aos meios de comunicação durante a ditadura militar : um olhar dos alunos do 9º ano

Orientador : Eguimara Selma BrancoArtigo (especialização) - Universidade Federal do Paraná, Setor de Educação Profissional e Tecnológica, Curso de Especialização em Mídias Integradas na Educação.Inclui referência

Artificial neural network-based streamline tracing strategy applied to hypersonic waverider design

Streamline tracing in hypersonic flows is essential for designing a high-performance waverider and intake. Conventionally, the streamline equations are solved after obtaining the velocity field over a basic flow field from simplified flow differential equations or three-dimensional computational fluid dynamics. The hypersonic waverider shape is generated by repeatedly applying the streamline tracing approach along several planes. This approach is computationally expensive for iterative waverider optimization. We provide a novel strategy where an Artificial Neural Network (ANN) is trained to directly predict the streamlines without solving the differential equations. We consider the standard simple cone-derived waverider using Taylor–Maccoll equations for the conical flow field as a template for the study. First, the streamlines from the shock are solved for a wide range of cone angle and Mach number conditions resulting in an extensive database. The streamlines are parameterized by a third-order polynomial, and an ANN is trained to predict the coefficients of the polynomial for arbitrary inputs of Mach number, cone angle, and streamline originating locations. We apply this strategy to design a cone-derived waverider and compare the geometry obtained with the standard conical waverider design method and the simplified waverider design method. The ANN technique is highly accurate, with a difference of 0.68% from the standard method in the coordinates of the waverider. The performance of the three waveriders is compared using Reynolds averaged Navier–Stokes simulations. The ANN-derived waverider does not indicate severe flow spillage at the leading edge. The new ANN-based approach is 20 times faster than the standard method

Passive scalar mixing studies to identify the mixing length in a supersonic confined jet

Supersonic jet with a co-flow, closely bounded by walls is known as supersonic confined jet. Supersonic confined jet is encountered in practical devices like the supersonic ejector. Mixing of the primary and the secondary fluid inside the confined passage is complex. From a design perspective, it is necessary to have an accurate knowledge of the mixing length (L-MIX). Tracers that do not actively participate in the flow behavior but rather mark the fluids such that they faithfully follow the fluid motion are known as passive scalars. Passive scalars help in the understanding the progression of mixing amidst interacting flows. In this work, we have performed passive scalar mixing studies in a supersonic confined jet for different operating conditions using an existing low area ratio (AR = 3.7) rectangular supersonic gaseous ejector. Air is used as the working fluid in both the primary and the secondary flow. The design Mach number of the primary flow nozzle (M-PD = 1.5-3.0) and the total pressure of the primary flow (P-OP = 4.89-9.89 bar) are varied during the experiments. Using the planar laser-induced fluorescence (PLIF) technique and acetone as the passive scalar, L-MIX is determined. A 266 nm Nd-YAG laser with a repetition rate of 8 Hz is used to excite the acetone molecules in the flow field, and the emitted fluorescence is captured by an ICCD camera. A new method is proposed to study the passive scalar distribution from the acetone PLIF images through digital image processing. Spatial Scalar Fluctuations Intensity (SSFI or psi ) is a parameter defined at every transverse section along the flow direction. Based on the variation of psi along the jet, the location of L-MIX can be identified. L-MIX is defined as the length from the supersonic nozzle exit where psi first attains a value of 0.05. For the first time, L-MIX is quantified in a supersonic confined jet. L-MIX values are observed to be in the range of 3H to 6H for the cases under study, where H is the height of the confined passage. The behavior of L-MIX is closely dependent on the nozzle operating conditions. The values of L-MIX are found to be reduced by 17.67% for the over-expanded flows and increased by 15.76% for the under-expanded flows from the perfectly expanded condition. This study also provides other supersonic confined jet characteristics like the potential core length (L-PC) and the shock cell spacing (S-x) of the primary supersonic jet. Compared to the supersonic free jet, values of L-PC and S-x are found to be different in the supersonic confined jet