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ATOMIC Simulations and Experimental Data for Basalt-like Compounds

This data consists of simulations and experimental measurements of laser-induced breakdown spectroscopy (LIBS). The simulations are produced by ATOMIC, a general purpose plasma modeling and kinetics code that has been designed to compute emission (or absorption) spectra from plasmas [2]. The makeup of the plasma was considered to be divided into some proportion water, some proportion Martian atmosphere (CO2), and some proportion target (from the rock or object impacted by the laser), where these proportions add to 1. Based on expert knowledge, the proportion of water was kept in the range [0.0,0.5] and the proportion of atmosphere was kept in the range [0.02, 0.9]. Our overall suite of simulations contains six sets of simulations that differ in which elements were considered to make up the target. Within each set, we used uniformly drawn temperatures and log mass densities within pre-specified ranges. The temperature range was [0.5,1.5] eV and the log (base 10) mass density range was [-7,-4]. The proportion of water, atmosphere, and target were drawn from a symmetric Dirichlet distribution, but draws in which the propor- tion of water or atmosphere exceeded the pre-specified limits were rejected from the design. Up to eleven constituent elements (Si, Al, Fe, Mg, Ca, O, Ti, Mn, Na, K, P) were considered for the target, as they are the most common elements found in basalt compounds and were used in [1]. For each run, the proportions of the constituent elements making up the target were drawn from a symmetric Dirichlet distribution. We ran 1,350 simulations that included nonzero proportions of all eleven elements. We also ran simulations which excluded some of these elements. In particular, we ran 1,000 simulations that only included nonzero proportions for the six most common elements (Si, Al, Fe, Mg, Ca, O). We also ran five sets, each with 500 simulations, that only included nonzero proportions for five of the six most common elements (but where all sets included O). Thus, we generated a total of 4,850 spectra representing basalt-like compounds in which the target was comprised of oxygen and between four and ten other elements. The ATOMIC code produced spectra over a range of 240nm - 880nm that roughly mimics the range collected by the ChemCam instrument on the Mars rover Curiosity. Each spectra had 32,000 wavelengths split across three spectrometer ranges (to mimic ChemCam). The experimental data, described in [1], measures a prepared basalt sample. All files are kept in directories whose names indicate the set of elements considered for the target with file names numbered to indicate the line in the design files used to produce the simulation. The designs are provided as text files with names indicating their purpose. The experimental data is provided as a CSV file which contains a header with measurement information, followed by a collection of 50 shots across a collection of wavelengths, along with the computed median and mean across shots.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Progress Toward Generation of a Navier-Stokes Database for a Harrier in Ground Effect

The Harrier YAV-8B aircraft is capable of vertical and short-field take-off and landing (V/STOL) by directing its four exhaust nozzles toward the ground, or conventional flight by rotating its nozzles into a horizontal position. The British Royal Air Force and the United States Marine Corps have used this aircraft for more than 30 years to provide a quick reaction time for troop support, and reduce the need for long runways. The success of this powered-lift (PL) vehicle has also prompted the more recent design of the Joint Strike Fighter (JSF). However there are significant safety issues that must be addressed when operating a PL vehicle in close proximity to the ground. Hot Gas Ingestion (HGI) by the inlets can result in a rapid loss of powered lift; and high-speed jet flows along the ground plane can induce low pressures underneath the vehicle, causing a 'suck-down' effect. Under these conditions, departure from controlled flight may occur. Moreover, unsteady ground vortices and jet fountains can affect the aircraft,s controllability and its proximity to ground troops. The viscous, time-dependent flow fields of PL vehicles are difficult to accurately and efficiently predict using Computational Fluid Dynamics (CFD). A number of researchers have used the time-dependent Reynolds-averaged Navier-Stokes (RANS) equations to compute flows for single and multiple jets in a cross-flow. A few have added some geometric complexity to the problem by computing flows for jet-augmented delta wings near a ground plane. Smith et.al. computed for the first time a single RANS solution about a simplified Harrier. This geometry included a fuselage, wing, leading edge root extension (LERX), inlets, and exhaust nozzles. All of these investigations cite two practical problems with computing these flows: 1) the need for improved solution accuracy; and, 2) the need for faster solution methods. We view the need for faster solution methods as key to improving the solution accuracy and making this class of computation more routine. One can hardly refine grids, explore the use of advanced turbulence models, and generate databases when it takes weeks of dedicated computer time for a single solution. Chaderjian, Ahmad, Pandya, and Murman have focused on reducing the time-to-solution for this very difficult and complex problem through process automation and exploitation of parallel computing. They began with the Harrier geometry reported, and added a deflected wing flap and empennage for greater realism. To date more than 80 solutions have been carried out. This paper will describe this process and progress made in reducing the time required to generate a simple longitudinal force and moment database for a Harrier in ground effect. It shows a typical snap-shot from an unsteady streakline animation, where fluid particles are colored by temperature. The ground vortex and a jet-fountain vortex are highlighted. It also shows a similar streakline image, where HGI occurs due to the vehicle in close proximity to the ground. It is show the mean lift coefficient as a function of angle of attack and height. The angle of attack range was 4 deg less than or = alpha less than or = 10 deg with an increment of 1 degree, and the height range was 10 ft less than or = h less than or = 30ft with an increment of 5 feet. This 35 solution database was extended to over 2500 cases using a monotone cubic-spline interpolation procedure. The suck-down effect (reduction of lift near the ground) is highlighted in the figure. The "cushion effect," the conventional reduction of lift as the vehicle moves out of ground effect, is also indicated. All 35 RANS solutions were obtained using 952 Silicon Graphics Origin 2000 and 3000 processors in dedicated mode for one week. Typically, 112 processors were assigned to each case. Some other cases used fewer processors to utilize all available CPUS. The final paper will report on the automation of the solution process, including: grid generation, job monitoring, solution completion criteria, and post processing. Moreover, improvements in parallel efficiency for a dual time-step algorithm for the RANS equations will also be presented. Results will be discussed in detail using unsteady streakline flow visualization to correlate unsteady flow structures with dominant aerodynamic frequencies. The stability derivatives, CL, and CL, will also be presented.

Chaderjian, Neal M.↗

Stabilization of gaze during circular locomotion in darkness. II. Contribution of velocity storage to compensatory eye and head nystagmus in the running monkey

1. Yaw eye in head (Eh) and head on body velocities (Hb) were measured in two monkeys that ran around the perimeter of a circular platform in darkness. The platform was stationary or could be counterrotated to reduce body velocity in space (Bs) while increasing gait velocity on the platform (Bp). The animals were also rotated while seated in a primate chair at eccentric locations to provide linear and angular accelerations similar to those experienced while running. 2. Both animals had head and eye nystagmus while running in darkness during which slow phase gaze velocity on the body (Gb) partially compensated for body velocity in space (Bs). The eyes, driven by the vestibuloocular reflex (VOR), supplied high-frequency characteristics, bringing Gb up to compensatory levels at the beginning and end of the slow phases. The head provided substantial gaze compensation during the slow phases, probably through the vestibulocollic reflex (VCR). Synchronous eye and head quick phases moved gaze in the direction of running. Head movements occurred consistently only when animals were running. This indicates that active body and limb motion may be essential for inducing the head-eye gaze synergy. 3. Gaze compensation was good when running in both directions in one animal and in one direction in the other animal. The animals had long VOR time constants in these directions. The VOR time constant was short to one side in one animal, and it had poor gaze compensation in this direction. Postlocomotory nystagmus was weaker after running in directions with a long VOR time constant than when the animals were passively rotated in darkness. We infer that velocity storage in the vestibular system had been activated to produce continuous Eh and Hb during running and to counteract postrotatory afterresponses. 4. Continuous compensatory gaze nystagmus was not produced by passive eccentric rotation with the head stabilized or free. This indicates that an aspect of active locomotion, most likely somatosensory feedback, was responsible for activating velocity storage. 5. Nystagmus was compared when an animal ran in darkness and in light. the beat frequency of eye and head nystagmus was lower, and the quick phases were larger in darkness. The duration of head and eye quick phases covaried. Eye quick phases were larger when animals ran in darkness than when they were passively rotated. The maximum velocity and duration of eye quick phases were the same in both conditions. 6. The platform was counterrotated under one monkey in darkness while it ran in the direction of its long vestibular time constant.(ABSTRACT TRUNCATED AT 400 WORDS).

NASA Discipline Neuroscience↗

A Very Large Eddy Simulation of the Nonreacting Flow in a Single-Element Lean Direct Injection Combustor Using PRNS with a Nonlinear Subscale Model

Very large eddy simulation (VLES) of the nonreacting turbulent flow in a single-element lean direct injection (LDI) combustor has been successfully performed via the approach known as the partially resolved numerical simulation (PRNS/VLES) using a nonlinear subscale model. The grid is the same as the one used in a previous RANS simulation, which was considered as too coarse for a traditional LES simulation. In this study, we first carry out a steady RANS simulation to provide the initial flow field for the subsequent PRNS/VLES simulation. We have also carried out an unsteady RANS (URANS) simulation for the purpose of comparing its results with that of the PRNS/VLES simulation. In addition, these calculated results are compared with the experimental data. The present effort has demonstrated that the PRNS/VLES approach, while using a RANS type of grid, is able to reveal the dynamically important, unsteady large-scale turbulent structures occurring in the flow field of a single-element LDI combustor. The interactions of these coherent structures play a critical role in the dispersion of the fuel, hence, the mixing between the fuel and the oxidizer in a combustor.

Shih, Tsan-Hsing↗

Large Eddy Simulation of Transonic Flow Field in NASA Rotor 37

The current paper reports on numerical investigations on the flow characteristics in a transonic axial compressor, NASA Rotor 37. The flow field was used previously as a CFD blind test case conducted by American Society of Mechanical Engineers in 1994. Since the CFD blind-test exercise, many numerical studies on the flow field in the NASA Rotor 37 have been reported. Although steady improvements have been reported in both numerical procedure and turbulence closure, it is believed that all the important aspects of the flow field have not been fully explained with numerical studies based on the Reynolds Averaged Navier-Stokes (RANS) solution. Experimental data show large dip in total pressure distribution near the hub at downstream of the rotor at 100% rotor speed. Most original numerical solutions from the blind test exercise did not predict this total pressure deficit correctly. This total pressure deficit at the rotor exit was attributed to a hub corner flow separation by the author. Several subsequent numerical studies with different turbulence closure model also calculated this dip in total pressure rise. Also, several studies attributed this total pressure deficit to a small leakage flow coming from the hub in the test article. As the experimental study cannot be repeated, either explanation cannot be validated. The primary purpose of the current investigation is to investigate the transonic flow field with both RANS and a Large Eddy Simulation (LES). The RANS approach gives similar results presented at the original blind test exercise. Although the RANS calculates higher overall total pressure rise, the total pressure deficit near the hub is calculated correctly. The numerical solution shows that the total pressure deficit is due to a hub corner flow separation. The calculated pressure rise from the LES agrees better with the measured total pressure rise especially near the casing area where the passage shock interacts with the tip clearance vortex and flow becomes unsteady due to this interaction. The LES simulation also calculates the total pressure rise deficit near the hub and it agrees well with the measured data.

Hah, Chunill↗

Steady and Unsteady Flow Effects of Circumferential Grooves Casing Treatment in a Transonic Compressor Rotor

The current paper reports on an investigation of steady and unsteady flow effects of circumferential grooves casing treatment in a transonic compressor rotor. Circumferential grooves casing treatment is used mainly to increase stall margin in axial compressors with a relatively small decrease in aerodynamic efficiency. It is widely believed that flow mechanisms of circumferential grooves casing treatment near stall conditions are not yet well understood even though this treatment has been used widely in real engines. Numerical analysis based on steady Reynolds-averaged Navier-Stokes (RANS) has been the primary tool used to understand flow mechanism for circumferential grooves casing treatment. Although steady RANS explains some flow effects of circumferential grooves casing treatment, it does not calculate all the measured changes in the compressor characteristics. Therefore, design optimization of circumferential grooves with steady RANS has not been very successful. As a compressor operates toward the stall condition, the flow field becomes transient. Major sources of self-generated flow unsteadiness are shock oscillation and interaction between the passage shock and the tip leakage vortex. In the present paper, an unsteady Reynolds-averaged Navier-Stokes (URANS) approach is applied to study the effects of circumferential grooves in a transonic compressor. The results from URANS are compared with the results from RANS and measured data. The current investigation shows that there are significant unsteady flow effects on the performance of the circumferential grooves casing treatment. For the currently investigated rotor, the unsteady effects are of the same magnitude as the steady effects in terms of extending the compressor stall margin.

Hah, Chunill↗

Development of the Glenn Heat-Transfer (Glenn-HT) Computer Code to Enable Time-Filtered Navier-Stokes (TFNS) Simulations and Application to Film Cooling on a Flat Plate Through Long Cooling Tubes

Computational fluid dynamics (CFD) analysis using Reynolds-averaged Navier-Stokes (RANS) formulation for turbomachinery-related flows has enabled improved engine component designs. RANS methodology has limitations that are related to its inability to accurately describe the spectrum of flow phenomena encountered in engines. Examples of flows that are difficult to compute accurately with RANS include phenomena such as laminar/turbulent transition, turbulent mixing due to mixing of streams, and separated flows. Large eddy simulation (LES) can improve accuracy but at a considerably higher cost. In recent years, hybrid schemes that take advantage of both unsteady RANS and LES have been proposed. This study investigated an alternative scheme, the time-filtered Navier-Stokes (TFNS) method applied to compressible flows. The method developed by Shih and Liu was implemented in the Glenn-Heat-Transfer (Glenn-HT) code and applied to film-cooling flows. In this report the method and its implementation is briefly described. The film effectiveness results obtained for film cooling from a row of 30deg holes with a pitch of 3.0 diameters emitting air at a nominal density ratio of unity and two blowing ratios of 0.5 and 1.0 are shown. Flow features under those conditions are also described.

Ameri, Ali↗

Development of the Glenn-HT Computer Code to Enable Time-Filtered Navier-Stokes (TFNS) Simulations and Application to Film Cooling on a Flat Plate Through Long Cooling Tubes

Computational fluid dynamics (CFD) analysis using Reynolds-averaged Navier-Stokes (RANS) formulation for turbomachinery-related flows has enabled improved engine component designs. RANS methodology has limitations which are related to its inability to accurately describe the spectrum of flow phenomena encountered in engines. Examples of flows that are difficult to compute accurately with RANS include phenomena such as laminarturbulent transition, turbulent mixing due to mixing of streams, and separated flows. Large eddy simulation (LES) can improve accuracy but at a considerably higher cost. In recent years, hybrid schemes which take advantage of both unsteady RANS and LES have been proposed. This study investigated an alternative scheme, the time-filtered Navier-Stokes (TFNS) method applied to compressible flows. The method developed by Shih and Liu was implemented in the Glenn-HT code and applied to film cooling flows. In this report the method and its implementation is briefly described. The film effectiveness results obtained for film cooling from a row of 30 holes with a pitch of 3.0 diameters emitting air at a nominal density ratio of unity and four blowing ratios of 0.5, 1.0, 1.5 and 2.0 are shown. Flow features under those conditions are also described.

infrared↗

Development of the Glenn-Heat-Transfer (Glenn-HT) Computer Code to Enable Time-Filtered Navier Stokes (TFNS) Simulations and Application to Film Cooling on a Flat Plate Through Long Cooling Tubes

Computational fluid dynamics (CFD) analysis using Reynolds-averaged Navier-Stokes (RANS) formulation for turbomachinery-related flows has enabled improved engine component designs. RANS methodology has limitations that are related to its inability to accurately describe the spectrum of flow phenomena encountered in engines. Examples of flows that are difficult to compute accurately with RANS include phenomena such as laminar/turbulent transition, turbulent mixing due to mixing of streams, and separated flows. Large eddy simulation (LES) can improve accuracy but at a considerably higher cost. In recent years, hybrid schemes that take advantage of both unsteady RANS and LES have been proposed. This study investigated an alternative scheme, the time-filtered Navier-Stokes (TFNS) method applied to compressible flows. The method developed by Shih and Liu was implemented in the Glenn-Heat-Transfer (Glenn-HT) code and applied to film-cooling flows. In this report the method and its implementation is briefly described. The film effectiveness results obtained for film cooling from a row of 30deg holes with a pitch of 3.0 diameters emitting air at a nominal density ratio of unity and two blowing ratios of 0.5 and 1.0 are shown. Flow features under those conditions are also described.

heat transfer↗

An Investigation of Transonic Resonance in a Mach 2.2 Round Convergent-Divergent Nozzle

Hot-wire and acoustic measurements were taken for a round convergent nozzle and a round convergent-divergent (C-D) nozzle at a jet Mach number of 0.61. The C-D nozzle had a design Mach number of 2.2. Compared to the convergent nozzle jet flow, the Mach 2.2 nozzle jet flow produced excess broadband noise (EBBN). It also produced a transonic resonance tone at 1200 Herz. Computational simulations were performed for both nozzle flows. A steady Reynolds-Averaged Navier-Stokes simulation was performed for the convergent nozzle jet flow. For the Mach 2.2 nozzle flow, a steady RANS simulation, an unsteady RANS (URANS) simulation, and an unsteady Detached Eddy Simulation (DES) were performed. The RANS simulation of the convergent nozzle showed good agreement with the hot-wire velocity and turbulence measurements, though the decay of the potential core was over-predicted. The RANS simulation of the Mach 2.2 nozzle showed poor agreement with the experimental data, and more closely resembled an ideally-expanded jet. The URANS simulation also showed qualitative agreement with the hot-wire data, but predicted a transonic resonance at 1145 Herz. The DES showed good agreement with the hot-wire velocity and turbulence data. The DES also produced a transonic tone at 1135 Herz. The DES solution showed that the destabilization of the shock-induced separation region inside the nozzle produced increased levels of turbulence intensity. This is likely the source of the EBBN.

DES↗

Revisiting Turbulence Model Validation for High-Mach Number Axisymmetric Compression Corner Flows

Two axisymmetric shock-wave/boundary-layer interaction (SWBLI) cases are used to benchmark one- and two-equation Reynolds-averaged Navier-Stokes (RANS) turbulence models. This validation exercise was executed in the philosophy of the NASA Turbulence Modeling Resource and the AIAA Turbulence Model Benchmarking Working Group. Both SWBLI cases are from the experiments of Kussoy and Horstman for axisymmetric compression corner geometries with SWBLI inducing flares of 20 and 30 degrees, respectively. The freestream Mach number was approximately 7. The RANS closures examined are the Spalart-Allmaras one-equation model and the Menter family of kappa − omega two equation models including the Baseline and Shear Stress Transport formulations. The Wind-US and CFL3D RANS solvers are employed to simulate the SWBLI cases. Comparisons of RANS solutions to experimental data are made for a boundary layer survey plane just upstream of the SWBLI region. In the SWBLI region, comparisons of surface pressure and heat transfer are made. The effects of inflow modeling strategy, grid resolution, grid orthogonality, turbulent Prandtl number, and code-to-code variations are also addressed.

Shock Wave↗

Development of a High-Order Space-Time Matrix-Free Adjoint Solver

The growth in computational power and algorithm development in the past few decades has granted the science and engineering community the ability to simulate flows over complex geometries, thus making Computational Fluid Dynamics (CFD) tools indispensable in analysis and design. Currently, one of the pacing items limiting the utility of CFD for general problems is the prediction of unsteady turbulent ows.1{3 Reynolds-averaged Navier-Stokes (RANS) methods, which predict a time-invariant mean flowfield, struggle to provide consistent predictions when encountering even mild separation, such as the side-of-body separation at a wing-body junction. NASA's Transformative Tools and Technologies project is developing both numerical methods and physical modeling approaches to improve the prediction of separated flows. A major focus of this e ort is efficient methods for resolving the unsteady fluctuations occurring in these flows to provide valuable engineering data of the time-accurate flow field for buffet analysis, vortex shedding, etc. This approach encompasses unsteady RANS (URANS), large-eddy simulations (LES), and hybrid LES-RANS approaches such as Detached Eddy Simulations (DES). These unsteady approaches are inherently more expensive than traditional engineering RANS approaches, hence every e ort to mitigate this cost must be leveraged. Arguably, the most cost-effective approach to improve the efficiency of unsteady methods is the optimal placement of the spatial and temporal degrees of freedom (DOF) using solution-adaptive methods.

Adjoint↗

Assimilation of Global Radar Backscatter and Radiometer Brightness Temperature Observations to Improve Soil Moisture and Land Evaporation Estimates

Active radar backscatter (s◦) observations from the Advanced Scatterometer (ASCAT) and passive radiometer brightness temperature (TB) observations from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated either individually or jointly into the Global Land Evaporation Amsterdam Model (GLEAM) to improve its simulations of soil moisture and land evaporation. To enable s◦ and TB assimilation, GLEAM is coupled to the Water Cloud Model and the L-band Microwave Emission from the Biosphere (L-MEB) model. The innovations, i.e. differences between observations and simulations, are mapped onto the model soil moisture states through an Ensemble Kalman Filter. The validation of surface (0-10 cm) soil moisture simulations over the period 2010-2014 against in situ measurements from the International Soil Moisture Network (ISMN) shows that assimilating s◦ or TB alone improves the average correlation of seasonal anomalies (Ran) from 0.514 to 0.547 and 0.548, respectively. The joint assimilation further improves Ran to 0.559. Associated enhancements in daily evaporative flux simulations by GLEAM are validated based on measurements from 22 FLUXNET stations. Again, the singular assimilation improves Ran from 0.502 to 0.536 and 0.533, respectively for s◦ and TB, whereas the best performance is observed for the joint assimilation (Ran = 0.546). These results demonstrate the complementary value of assimilating radar backscatter observations together with brightness temperatures for improving estimates of hydrological variables, as their joint assimilation outperforms the assimilation of each observation type separately.

GLEAM↗

Effect of Spatial Filtering in Implicit Large-Eddy Simulations of Separated Flows

The relatively high Reynolds number of turbulent flows encountered in various applications puts these problems well beyond the reach of direct numerical simulation (DNS) at present. Meanwhile, lower-fidelity Reynolds-averaged Navier-Stokes (RANS) calculations are known to be not accurate enough in complex problems, such as smooth-body flow separation and other flows involving highly-unsteady phenomena. Hence, given the current infeasibility of DNS and the unsatisfactory performance of RANS, intermediate techniques such as large-eddy simulation (LES) and hybrid RANS-LES, whose fidelity lie between RANS and DNS, have received much attention for application to various problems of practical importance. Modeling of the effect of missing scales on resolved scales, also known as subgrid-scale (SGS) modeling, is an important subject for LES. SGS models can be broadly categorized as explicit or implicit approaches. The explicit approach is based on an SGS model that explicitly appears in the governing equations expressed in the form of so-called “filtered Navier-Stokes equations”, which describe the evolution of the turbulence scales resolved by the LES grid. The effect of the scales unresolved by the grid is represented by the SGS model. The implicit modeling approach, on the other hand, does not employ an explicit model but instead treats the intrinsic dissipation of the numerical discretization scheme as an implicit SGS model. An LES without an explicit SGS model is commonly termed as an implicit LES (ILES). The relative merits of one SGS modeling approach over another is a subject of ongoing debate. We have opted to employ an ILES methodology, based on high-order compact finite-difference and spatial filtering schemes, in our recent investigations of separated flow problems [1, 2]. Further discussion of our preference of ILES over explicit LES is provided in Uzun and Malik [2]. The spatial filtering operation, described in the next section, is treated as an implicit SGS model for the ILES. Some observations made during the course of our recent investigations, which pointed out to excessive numerical dissipation in certain parts of the flowfield, prompted us to take a closer look at the potential effect of the spatial filter on ILES predictions. This technical note is therefore devoted to spatial filter effects in the context of a high Reynolds number, transonic shock-induced separated flow.

Ali Uzun↗

Simulation and Modeling of Hypersonic Turbulent Boundary Layers Subject to Favorable Pressure Gradients due to Streamline Curvature

Direct numerical simulations (DNS) of favorable-pressure-gradient turbulent boundary layers are presented for a nominal freestream Mach number of 5, with the objective of assessing the limitations of the currently available Reynolds-averaged Navier-Stokes (RANS) models.The wall geometry and flow conditions of the DNS are representative of the experimental data for a Mach 4.9 turbulent boundary layer that was tested on a two-dimensional planar convexwall model in the high-speed blow-down wind tunnel located at the National Aerothermochemistry Laboratory at Texas A&M University. The favorable pressure gradient is induced bythe streamwise surface curvature. The DNS results will be compared with experimental measurements and RANS computations for the same flow conditions and wall geometry. The DNS datasets will also be analyzed to provide an improved physical understanding of hypersonic boundary-layer turbulence subject to mechanical nonequilibrium, including the validity of Morkovin’s hypothesis and the various available compressibility transformations, as well as to obtain turbulence statistics that are relevant to RANS modeling, including the distribution ofeddy viscosity, the budgets of turbulent kinetic energy and Reynolds stresses, and the velocity-temperature correlations. The RANS predictions will be obtained by using both the commonly used one- and two-equation models that assume a constant turbulent Prandtl number and an algebraic, variable Prandtl number model for the turbulent energy flux.

turbulent boundary layers↗

Simulation and Modeling of Hypersonic Turbulent Boundary Layers Subject to Favorable Pressure Gradients due to Streamline Curvature

Direct numerical simulations (DNS) of favorable-pressure-gradient turbulent boundary layers are presented for a nominal freestream Mach number of 5, with the objective of assessing the limitations of the currently available Reynolds-averaged Navier-Stokes (RANS) models. The favorable pressure gradient is induced by the streamwise curvature of the two-dimensional, planar, convex measurement surface used during experiments at the Texas A&M University. The DNS data shows good comparison with the measured velocity profiles, strain rates, and some, but not all, of the Reynolds-stress components. The discrepancies between the predicted and the measured wall-normal as well as shear stress components are primarily attributed to the lower than actual values inferred from typical PIV measurements of turbulent boundary layers. The DNS data shows a zero or slightly negative Reynolds shear stress in the outer part of the boundary-layer, which is indicative of the decaying turbulent motion under a strong favorable pressure gradient. The DNS data is also compared with the results of RANS computations based on commonly used zero, one, and two equation eddy-viscosity models. The RANS models yield reasonable comparisons with the DNS-based skin friction under zero and weak pressure gradients, but significant discrepancies under a strong pressure gradient. The k-w SST model provided the best overall predictions of skin friction, except in the region where the flow transitions from a favorable to an adverse pressure gradient. While the RANS models examined herein also give good predictions of the Reynolds shear stress under a sufficiently weak pressure gradient, none of those models are able to appropriately capture the reduction in the Reynolds stresses when the flow was subjected to a strong pressure gradient. An a priori assessment of the turbulent heat-flux prediction based on the assumption of a constant turbulent Prandtl number with the DNS data shows that while the constant turbulent Prandtl number model is effective in predicting the wall-normal component of turbulent heat flux, it does not capture the turbulent heat transfer in the streamwise direction for all the pressure gradient cases. The failure of the constant turbulent Prandtl number model highlights a requirement for more advanced models of the turbulent heat flux.

turbulent boundary layers↗

Multiphysics Computational Analysis of a Perforated Plate Cooling Flow

A multiphysics analysis of a film cooling flow was conducted using a computational fluid dynamics (CFD) solver in conjunction with a conjugate heat transfer (CHT) solver. The film cooling problem consisted of a square nozzle producing a heated subsonic jet over a perforated plate with three sections of 45 cooling holes each. Results from the multiphysics analysis were compared to a CFD-only approach and experimental results. Reynolds-averaged Navier-Stokes (RANS) computations were employed first, with and without the CHT solver. The multiphysics approach provided much closer agreement with experimentally measured plate temperatures than the CFD-only approach. Comparisons of computed velocities and temperatures were also made with experimental data. Hybrid RANS-large eddy simulation calculations employing the Delayed Detached Eddy Simulation (DDES) approach were also conducted within the multiphysics framework. The DDES approach was unable to resolve turbulent structures in the near wall regions. Hence, the RANS part of the DDES model was used in near wall regions, and produced surface temperatures along with velocity and temperature profiles close to the wall that were very similar to the RANS results. The DDES approach did resolve structures in the outer portion of the boundary layer especially near the end of the plate where the boundary layer was thicker. The key result was the improved surface temperatures produced by the multiphysics approach employing CHT over the fluid-only approach.

Computational Fluid Dynamics↗

Development of Physics-Based Transition Models for Unstructured-Mesh CFD Codes Using Deep Learning Models

Predicting transition locations over a vehicle surface is of fundamental importance for many engineering applications. With the transition information, the Reynolds-averaged Navier-Stokes (RANS) computations can turn on the turbulence model at the right locations so that drag, lift and other aerodynamic quantities can be accurately predicted. In contrast to the popularity of RANS-based transition modeling in which transition onset is governed by the turbulence equations, physics-based transition models that account for instability waves within the boundary layer, thus more compliant to flow physics, only gained more attention in recent years. This paper describes the development of a new physics-based transition model based on either the linear stability theory (LST) or parabolized stability equations (PSE). The model is designed to communicate with a structured or unstructured-mesh RANS solver back and forth in order to more accurately compute transition fronts over a three-dimensional body. In the developed model, the Python suite of interface codes in conjunction with the LASTRAC software can be executed autonomously to produce transition onset locations for a given laminar or RANS-computed transitional state. In addition, as a proof of concept, the tool set consists of a deep learning neural network model that has been designed and trained to predict instability wave evolutions inside the boundary layer for various instability wave mechanisms across a selected speed range. A machine-learned intelligent profile interpolation model has also been devised to enable reliable instability-wave spectra predictions with just a few points in the mean flow profiles.

Transition Modeling↗