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At least 19 records

Flow-separation patterns on symmetric forebodies

Flow-visualization studies of ogival, parabolic, and conical forebodies were made in a comprehensive investigation of the various types of flow patterns. Schlieren, vapor-screen, oil-flow, and sublimation flow-visualization tests were conducted over an angle-of-attack range from 0 deg. to 88 deg., over a Reynolds-number range from 0.3X10(6) to 2.0X10(6) (based on base diameter), and over a Mach number range from 0.1 to 2. The principal effects of angle of attack, Reynolds number, and Mach number on the occurrence of vortices, the position of vortex shedding, the principal surface-flow-separation patterns, the magnitude of surface-flow angles, and the extent of laminar and turbulent flow for symmetric, asymmetric, and wake-like flow-separation regimes are presented. It was found that the two-dimensional cylinder analogy was helpful in a qualitative sense in analyzing both the surface-flow patterns and the external flow field. The oil-flow studies showed three types of primary separation patterns at the higher Reynolds numbers owing to the influence of boundary-layer transition. The effect of angle of attack and Reynolds number is to change the axial location of the onset and extent of the primary transitional and turbulent separation regions. Crossflow inflectional-instability vortices were observed on the windward surface at angles of attack from 5 deg. to 55 deg. Their effect is to promote early transition. At low angles of attack, near 10 deg., an unexpected laminar-separation bubble occurs over the forward half of the forebody. At high angles of attack, at which vortex asymmetry occurs, the results support the proposition that the principal cause of vortex asymmetry is the hydrodynamic instability of the inviscid flow field. On the other hand, boundary-layer asymmetries also occur, especially at transitional Reynolds numbers. The position of asymmetric vortex shedding moves forward with increasing angle of attack and with increasing Reynolds number, and moves rearward with increasing Mach number.

Keener, Earl R.↗

Oil-flow separation patterns on an ogive forebody

Oil flow patterns on a symmetric tangent ogive forebody having a fineness ratio of 3.5 are presented for angles of attack up to 88 deg at a transitional Reynolds number of 8 million (based on base diameter) and a Mach number of 0.25. Results show typical surface flow separation patterns, the magnitude of surface flow angles, and the extent of laminar and turbulent flow for symmetric, asymmetric, and wakelike flow regimes.

Keener, E. R.↗

Complex Flow Separation Pattern on Transonic Fan Airfoils Revealed by Flow Visualization

Modern turbofan engines employ a highly loaded fan stage with transonic or low-supersonic velocities in the blade-tip region. The fan blades are often prone to flutter at off-design conditions. Flutter is a highly undesirable and dangerous self-excited mode of blade oscillations that can result in high-cycle fatigue blade failure. The origins of blade flutter are not fully understood yet. The latest view is that the blade oscillations are triggered by high-frequency changes in the extent of the partially separated area on the airfoil suction side. There is a lack of experimental data describing the separated flow characteristics of modern airfoils for transonic fans.

Lepicovsky, Jan↗

Impact of particle arrays on phase separation composition patterns

We examine the symmetry-breaking effect of fixed constellations of particles on the surface-directed spinodal decomposition of binary blends in the presence of particles whose surfaces have a preferential affinity for one of the components. Our phase-field simulations indicate that the phase separation morphology in the presence of particle arrays can be tuned to have a continuous, droplet, lamellar, or hybrid morphology depending on the interparticle spacing, blend composition, and time. In particular, when the interparticle spacing is large compared to the spinodal wavelength, a transient target pattern composed of alternate rings of preferred and non-preferred phases emerges at early times, tending to adopt the symmetry of the particle configuration. We reveal that such target patterns stabilize for certain characteristic length, time, and composition scales characteristic of the pure phase-separating mixture. To illustrate the general range of phenomena exhibited by mixture-particle systems, we simulate the effects of single-particle, multi-particle, and cluster–particle systems having multiple geometrical configurations of the particle characteristic of pattern substrates on phase separation. Our simulations show that tailoring the particle configuration, or substrate pattern configuration, a relative fluid-particle composition should allow the desirable control of the phase separation morphology as in block copolymer materials, but where the scales accessible to this approach of organizing phase-separated fluids usually are significantly larger. Limited experiments confirm the trends observed in our simulations, which should provide some guidance in engineering patterned blend and other mixtures of technological interest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coarsening following a morphological instability in the one-sided model

We study the coarsening of the interfacial pattern separating two coexisting phases after the pattern becomes morphologically unstable. Shortly after the instability, the scale of the structure is given by the most unstable wave number in the linear regime. At later times, nonlinear interactions cause the structure to coarsen. Coarsening is studied by monitoring the time dependence of the two-dimensional power spectrum of the pattern, especially for wave vectors transverse to the direction of growth. Characteristic length scales of the pattern obtained from moments of the power spectrum are asymptotically linear in time. Furthermore, the power spectrum is seen to satisfy a scaling relation, in agreement with previous studies. A normal-velocity autocorrelation function is calculated and found to decay substantially over length scales that are of the order of the scale of the pattern. The issue of spatial anisotropy in the correlation functions is also discussed.

Vinals, Jorge↗

A combinatorial model for dentate gyrus sparse coding

The dentate gyrus forms a critical link between the entorhinal cortex and CA3 by providing a sparse version of the signal. Concurrent with this increase in sparsity, a widely accepted theory suggests the dentate gyrus performs pattern separation—similar inputs yield decorrelated outputs. Although an active region of study and theory, few logically rigorous arguments detail the dentate gyrus’s (DG) coding. We suggest a theoretically tractable, combinatorial model for this action. The model provides formal methods for a highly redundant, arbitrarily sparse, and decorrelated output signal.To explore the value of this model framework, we assess how suitable it is for two notable aspects of DG coding: how it can handle the highly structured grid cell representation in the input entorhinal cortex region and the presence of adult neurogenesis, which has been proposed to produce a heterogeneous code in the DG. We find tailoring the model to grid cell input yields expansion parameters consistent with the literature. In addition, the heterogeneous coding reflects activity gradation observed experimentally. Lastly, we connect this approach with more conventional binary threshold neural circuit models via a formal embedding.

60 APPLIED LIFE SCIENCES↗

Sea level side loads in high-area-ratio rocket engines

An empirical separation and side load model to obtain applied aerodynamic loads has been developed based on data obtained from full-scale J-2S (265K-pound-thrust engine with an area ratio of 40:1) engine and model testing. Experimental data include visual observations of the separation patterns that show the dynamic nature of the separation phenomenon. Comparisons between measured and applied side loads are made. Correlations relating the separation location to the applied side loads and the methods used to determine the separation location are given.

Nave, L. H.↗

Numerical simulation of unsteady, viscous, high-angle-of-attack flows using a partially flux-split algorithm

Viscous separated flow surrounding a hemisphere-cylinder body at angles of attack ranging up to 19 deg in transonic flow has been computed using an implicit, approximately-factored, partially flux-split algorithm. The resulting flowfield structures, including the vortical flow on the leeward side of the body and the three-dimensional separation patterns, have been investigated. The computed results show good qualitative and quantitative agreement with experimental data. Furthermore, visualization of the flowfield patterns has yielded insight into the behavior of the three-dimensional separated flow.

Ying, S. X.↗

HLPW-4/GMGW-3: Wall-Modeled LES and Lattice-Boltzmann Technology Focus Group Workshop Summary

A summary of the nine submissions to the Wall-Modeled LES and Lattice-Boltzmann(WMLESLB) Technical Focus Group (TFG) at the 4th High lift Prediction Workshop is provided. The focus of this TFG was to assess the current capabilities of WMLES and Lattice-Boltzmann methods on a complex high-lift configuration across a wide range of angles of attack. Preliminary analysis of the submitted data suggests that>250𝑀spatial degrees of freedom are needed to accurately predict pitching moments at high angles of attack due to large pressure gradients present on the outboard slat and main element for𝛼 >17◦(corrected for free-air).While some scatter is reported in pitching moments at the low-angles of attack (𝛼 <11◦) - likely caused by differences in flap separation possibly due to low Reynolds number effects - excellent agreement is observed between the submissions near the𝐶𝐿,max state. Objective superiority over steady state RANS can be seen in terms of lack of excess outboard separation; a majority of the good quality WMLES and LB submissions predict wedge-shaped separation patterns consistent with the experimental oil flow. Differences in the onset of stall mechanism in the free-air configuration for𝛼 >20◦is reported with two distinct topologies observed. Topology A is characterized by the onset of corner-flow separation which progressively grows to produce a pitch break in free-air with an angle of attack increase from𝛼=20.55◦to𝛼=21.47◦+𝜖where𝜖is a small perturbation (varying between submissions and likely to be within±0.3◦). Topology Bis characterized by boundary layer weakness emanating from the inboard side of the wing-pylon juncture substantially larger than any weakness in the wing-body juncture (due to corner-flow);submissions in this category do not show any tendency for occurrence of a pitch break for the free-air configuration within the vicinity of𝛼=21.47◦. The in-tunnel simulations submitted by3 participants using different discretizations, grids and closure models show excellent agreement with the experiment in terms of a) integrated loads, b) surface flow-topology, and c) mechanism for the onset of inboard stall. Further evidence is provided to demonstrate both qualitative and quantitative superiority of all 3 WMLES submissions over a single steady state RANS submission to the workshop.

TTT↗

Dopamine-Mediated Polymer Coating Facilitates Area-Selective Atomic Layer Deposition

Area-selective atomic layer deposition (ALD) has the potential to significantly improve current fabrication approaches by introducing a bottom-up process in which robust and conformal thin films are selectively deposited onto patterned substrates. This bottom-up approach requires selective areas of the substrates to be masked to inhibit deposition. Spontaneous self-assembly and organization of a mask, incorporating adhesion and other functions, are particularly attractive for this role as they do not require a separate patterning step. In this work, we make use of the pH/light tunability of catechol adhesion to develop a catechol-functionalized polymer that exhibits tunable adhesion strengths on different materials based on their specific chemistry. Tunable selective deposition was shown between metal/metal oxide substrates by controlling the local pH. Moreover, by controlling the adhesion strength through UV light, the deposition of hafnium oxide (HfO 2 ) during ALD was successfully inhibited.

36 MATERIALS SCIENCE↗

High-Lift Common Research Model: RANS, HRLES and WMLES Perspectives for CLmax Prediction Using LAVA

A unified assessment of three turbulence treatments: Reynolds Averaged Navier-Stokes(RANS), Hybrid RANS/LES (HRLES) and Equilibrium Wall-Modelled Large Eddy Simulation(WMLES) is presented for the High-Lift Common Research Model (CRM-HL). For the free-air configuration, steady-state RANS simulations show very accurate drag polar predictions in the low-𝛼linear regime. However, strong grid sensitivity is reported near the maximum lift-state(𝐶𝐿max), with finer-grids showing larger errors and predicting erroneous flow topologies on the wing. Our RANS simulations show that several corrections for the Spalart-Allmaras (SA)turbulence model widely used in the community lead to more erroneous results compared to the baseline closure, without exception. Both scale-resolving methods (HRLES and WMLES)address these drawbacks and predict an outboard separation pattern on the main element that is in good agreement with the oil flow photographs taken from the QinetiQ wind tunnel experiments, when LES-appropriate grids and numerical discretizations are used. While RANS simulations with the baseline SA closure do not show any wing-root separation post𝐶𝐿max, both HRLES and WMLES show onset of corner flow separation with varying degrees of progression, along with a weak pitch break in the wing-contribution of the overall pitching moment. This post-𝐶𝐿max pitch break seen in the free-air simulations is weaker than the break observed in experiments, with a weaker break reported in WMLES for each iteration of grid-refinement. In-tunnel simulations using both SA-baseline RANS and WMLES show a much stronger post-𝐶𝐿max break with the WMLES predictions showing excellent agreement with the experiment in terms of both the flow-topology observed and the pressure-coefficients at various spanwise stations. Sensitivity to the tunnel wall boundary layer is characterized via comparisons between viscous and inviscid treatments for the tunnel walls. WMLES predictions show moderate sensitivity at the predicted inboard flow-state at 𝐶𝐿max along with the progression towards a post-𝐶𝐿max stall; however, this stalled state at 𝛼≈20◦(inside the tunnel) obtained with both tunnel wall treatments appears to be largely identical.

TTT↗

Transonic flow about a thick circular-arc airfoil

An experimental and theoretical study of transonic flow over a thick airfoil, prompted by a need for adequately documented experiments that could provide rigorous verification of viscous flow simulation computer codes, is reported. Special attention is given to the shock-induced separation phenomenon in the turbulent regime. Measurements presented include surface pressures, streamline and flow separation patterns, and shadowgraphs. For a limited range of free-stream Mach numbers the airfoil flow field is found to be unsteady. Dynamic pressure measurements and high-speed shadowgraph movies were taken to investigate this phenomenon. Comparisons of experimentally determined and numerically simulated steady flows using a new viscous-turbulent code are also included. The comparisons show the importance of including an accurate turbulence model. When the shock-boundary layer interaction is weak the turbulence model employed appears adequate, but when the interaction is strong, and extensive regions of separation are present, the model is inadequate and needs further development.

Mcdevitt, J. B.↗

CRCNS22 Learning Rules in the Hippocampus and their Mapping to Neuromorphic Systems (Final Technical Report)

Large scale biologically-realistic computational models are key to investigating the interplay between structure and function in nervous systems, thus paving the way to new clinical methods and neuro-inspired computing solutions. This project focuses on the hippocampus, in particular the CA3-CA1 regions, due to their role in associative learning and memory, pattern separation and completion, and spatial navigation. Investigations into the neuronal organization and learning rule(s) of this circuit can shed light into how declarative memories are formed, stored, recalled and forgotten and inform computational, experimental and clinical neuroscience work. Our project aims at developing a novel data-driven methodology supported by a broad heterogeneous base of neuroscience experimental knowledge and inspired from advances in computer science and engineering. Specifically, this work will benchmark existing and new learning rules within a full-scale spiking neural network simulation of the CA3-CA1 region. The model will be based on an open-source repository, called the Hippocampome, which contains neuronal morphologies, firing patterns, synapse probabilities, and most other required parameters for all known neuron types in the rodent hippocampal formation. The model will be first trained in a supervised fashion for associative memory tasks using backpropagation through time traditionally used in computer science, enhanced with a new technique called the surrogate gradient method. This optimization method will be used to obtain a global loss minimization, but it is not biologically inspired as it assumes the use of data not locally available to the synapses. However, we propose its use as a benchmarking tool, to compare the training performance of local biologically plausible and hardware-mappable learning rules at scale. New rules or combinations will be proposed and tested as needed, based on the obtained results. Progress in this area will also drive the development of novel hardware-mappable algorithms for continual lifelong learning and categorization of new events from few presented examples. This project goes beyond the existing state-of-the-art by looking at large scale realistic neuronal circuits as networks trainable via global optimization methods such as surrogate gradient descent. The objective function of the brain that supports learning is largely unknown, but it is likely that it operates through local learning rules. Studying network trajectories around local minima as proposed in this work represents a useful strategy for understanding whether a network is training by using a specific (set of) learning rule(s). Starting from a completely untrained network is a challenging test since it is difficult to determine how the learning rule affects the trajectory of the network. This interdisciplinary project will help understand what rule governs learning in these regions or if multiple learning rules are involved. The work will develop a robust methodology to measure if the network is converging to the target solution, oscillating around it, or diverging away.

59 BASIC BIOLOGICAL SCIENCES↗

A Shallow-Water Model for Convective Self-Aggregation

Randomly distributed convective storms can self-aggregate in the absence of large-scale forcings. Here we present a 1D shallow-water model to study the convective self-aggregation. This model simulates the dynamics of the planetary boundary layer and represents convection as a triggered process. Once triggered, convection lasts for finite time and occupies finite length. Here we show that the model can successfully simulate self-aggregation, and that the results are robust to a wide range of parameter values. In the simulations, convection excites gravity waves. The gravity waves then form a standing wave pattern, separating the domain into convectively active and inactive regions. We analyze the available potential energy (APE) budget and show that convection generates APE, providing energy for self-aggregation. By performing dimensional analysis, we develop a scaling theory for the size of convective aggregation, which is set by the gravity wave speed, damping time scale, and number density of convective storms. This paper provides a simple modeling framework to further study convective self-aggregation.

54 ENVIRONMENTAL SCIENCES↗

Reynolds number and Mach number effect on space shuttle configurations

Analytical studies have been conducted concerning the lee-surface flow phenomena over a space shuttle orbiter model based on the experimental data obtained during September, 1971 through August, 1972. Lee-surface peak heating phenomena and flow separation patterns were analyzed. Major results of analyses are briefly presented.

Zakkay, V.↗

Surface flow visualization requirements for testing in NTF

Surface flow visualization is required to be correlated at all the facilities to allow the following: (1) an understanding of the chordwise and spanwise extent of laminar flow; (2) the change in shock location for various trip configurations; (3) the effectiveness of the chosen boundary layer trip (since its specifications will change as a function of Reynolds number); and (4) a comparison of the separation patterns at the buffet conditions. A requirement to tunnel-to-tunnel correlation testing involving the NTF is pointed out. A specification for a surface flow visualization system to be used in the NTF is defined. Recognition of the special limitations in the NTF including physical and visual accessibility, high operating cost, flow contamination requirements, as well as the need for on-line review of the results to develop the final trip configurations in a timely manner, leads to the listed requirements.

Bengelink, R. L.↗