SUMMARYThe unsteady compressible flow equations are solved using a stabilized finite‐element formulation with C0 elements. In 2D, the performance of three‐noded linear and six‐noded quadratic triangular elements is compared. In 3D, the relative performance is evaluated for 6‐noded linear and 18‐noded quadratic wedge elements. Results are compared for the solutions to Euler, laminar, and turbulent flows at different Mach numbers for several flow problems. The finite‐element meshes considered for comparison have same location of nodes for the linear and quadratic interpolations. For the turbulent flow, the Spalart–Allmaras model is used for closure. It is found that the quadratic elements yield better performance than the linear elements. This is attributed to accurate representation of the stabilization terms that involve second‐order derivatives in the formulation. When these terms are dropped from the formulation with quadratic interpolation, the numerical results are similar to those obtained with linear interpolation. The absence of these terms result in added numerical diffusion that seems to give the effect of a relatively reduced Reynolds number. For the same location of nodes, the computations with the linear triangular and wedge elements are approximately 20% and 100% faster than those with quadratic triangular and wedge elements, respectively. However, if the same quadrature rule for numerical integration is used for both interpolations, the computations with quadratic elements are approximately 20% and 45% faster in 2D and 3D, respectively. Copyright © 2014 John Wiley & Sons, Ltd.

Numerical simulation of the flow in a two-dimensional mixed compression intake is carried out by solving unsteady viscous compressible equations using a stabilized finite element method. The effect of bleed in starting/unstarting of the intake and controlling the buzz instability is investigated in detail. Higher bleed leads to an increase in the ability of the intake to sustain larger back-pressure for stable operation. The amount of bleed and its location is varied to understand its effect on the performance of the intake. Two kinds of unsteady oscillations are observed: 'little' and 'big' buzz. The frequency of the both kinds of buzz oscillations is found to be super-harmonic of the fundamental acoustic frequency of intake modeled as an open-closed organ pipe. The frequency as well as amplitudes of the big buzz cycles is larger than those of the little buzz. The little-and big-buzz are found to occur for low-and high-subcritical state of the intake and are very similar to Ferri and Dailey criteria, respectively. Buzz is eliminated when relatively high bleed is implemented, both, upstream and downstream of the throat. The effect of rate of change of back-pressure on the start/unstart of the intake is investigated. Two situations are considered. The first case is that of an intake where the back-pressure remains below the critical value. It is found that the intake remains started if the change in back-pressure is gradual. However, it unstarts if the back-pressure is changed relatively rapidly. The second set of simulations is an attempt to model the situation where the back-pressure at the exit of the intake exceeds the critical value and a logic is incorporated in the feed back loop of the fuel modulation to start the intake. Low rate of change of pressure is unsuccessful in starting the intake. Relatively high rates result in either a quick starting of the intake or a slow unstart. and forth in the convergent portion leading to high unsteadiness in the flow. It involves periodic filling and discharge of the plenum chamber, complex shock-boundary layer interaction, shear layer/slip stream-boundary layer interaction, transient shock movement and flow separation. It adversely affects the mass flow entering the engine and may lead to combustion instability, engine surge and flame out. It can also lead to deterioration of the performance of propulsion system, thus causing catastrophic loss in thrust.The buzz instability was first reported by Oswatitsch [3]. The tests were conducted for supersonic missile flights for Mach number in the range of 2.5-3.0. He observed buzz during his experiments, but disregarded it on the basis that a sub-critical range of operation is impractical and, therefore, not important. Later (1945)(1946)(1947)(1948)(1949)(1950)(1951)(1952)(1953)(1954)(1955), buzz was observed in many of the extensive experiments that were conducted at NASA, Langley on external compression inlets. Ferri and Nucci [4] conducted detailed experiments on an axisymmetrical external compression air intake. The occur...

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The Large Eddy Simulations (LES) modeling of turbulence effects is computationally expensive even when not all scales are resolved, especially in the presence of deep turbulence effects in the atmosphere. Machine learning techniques provide a novel way to propagate the effects from inner- to outer-scale in atmospheric turbulence spectrum and to accelerate its characterization on long-distance laser propagation. We simulated the turbulent flow of atmospheric air in an idealized box with a temperature difference between the lower and upper surfaces of about 27 degrees Celsius with the LES method. The volume was voxelized, and several quantities, such as the velocity, temperature, and the pressure were obtained at regularly spaced grid points. These values were binned and converted into symbols that were concatenated along the length of the box to create a ‘text’ that was used to train a long short-term memory (LSTM) neural network and propose a way to use a naive Bayes model. LSTMs are used in speech recognition, and handwriting recognition tasks and naïve Bayes is used extensively in text categorization. The trained LSTM and the naïve Bayes models were used to generate instances of turbulent-like flows. Errors are quantified, and portrait as a difference that enables our studies to track error quantities passed through stochastic generative machine learning models — considering that our LES studies have a high state of the art high-fidelity approximation solutions of the Navier-Stokes. In the present work, LES solutions are imitated and compare against generative machine learning models.