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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Validation of a Node-Centered Wall Function Model for the Unstructured Flow Code FUN3D

In this paper, the implementation of two wall function models in the Reynolds averaged Navier-Stokes (RANS) computational uid dynamics (CFD) code FUN3D is described. FUN3D is a node centered method for solving the three-dimensional Navier-Stokes equations on unstructured computational grids. The first wall function model, based on the work of Knopp et al., is used in conjunction with the one-equation turbulence model of Spalart-Allmaras. The second wall function model, also based on the work of Knopp, is used in conjunction with the two-equation k-! turbulence model of Menter. The wall function models compute the wall momentum and energy flux, which are used to weakly enforce the wall velocity and pressure flux boundary conditions in the mean flow momentum and energy equations. These wall conditions are implemented in an implicit form where the contribution of the wall function model to the Jacobian are also included. The boundary conditions of the turbulence transport equations are enforced explicitly (strongly) on all solid boundaries. The use of the wall function models is demonstrated on four test cases: a at plate boundary layer, a subsonic di user, a 2D airfoil, and a 3D semi-span wing. Where possible, different near-wall viscous spacing tactics are examined. Iterative residual convergence was obtained in most cases. Solution results are compared with theoretical and experimental data for several variations of grid spacing. In general, very good comparisons with data were achieved.

Carlson, Jan-Renee↗
NASA NTRS2015

Aeroacoustic Simulations of a Nose Landing Gear Using FUN3D on Pointwise Unstructured Grids

Numerical simulations have been performed for a partially-dressed, cavity-closed (PDCC) nose landing gear configuration that was tested in the University of Florida's open-jet acoustic facility known as the UFAFF. The unstructured-grid flow solver FUN3D is used to compute the unsteady flow field for this configuration. Mixed-element grids generated using the Pointwise(TradeMark) grid generation software are used for these simulations. Particular care is taken to ensure quality cells and proper resolution in critical areas of interest in an effort to minimize errors introduced by numerical artifacts. A hybrid Reynolds-averaged Navier-Stokes/large eddy simulation (RANS/LES) turbulence model is used for these simulations. Solutions are also presented for a wall function model coupled to the standard turbulence model. Time-averaged and instantaneous solutions obtained on these Pointwise grids are compared with the measured data and previous numerical solutions. The resulting CFD solutions are used as input to a Ffowcs Williams-Hawkings noise propagation code to compute the farfield noise levels in the flyover and sideline directions. The computed noise levels compare well with previous CFD solutions and experimental data.

Vatsa, Veer N.↗
NASA NTRS2016

Unstructured Grid Adaptation: Status, Potential Impacts, and Recommended Investments Toward CFD Vision 2030

Unstructured grid adaptation is a powerful tool to control discretization error for Computational Fluid Dynamics (CFD). It has enabled key increases in the accuracy, automation, and capacity of some fluid simulation applications. Slotnick et al. provides a number of case studies in the CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences to illustrate the current state of CFD capability and capacity. The authors forecast the potential impact of emerging High Performance Computing (HPC) environments forecast in the year 2030 and identify that mesh generation and adaptivity continue to be significant bottlenecks in the CFD work flow. These bottlenecks may persist because very little government investment has been targeted in these areas. To motivate investment, the impacts of improved grid adaptation technologies are identified. The CFD Vision 2030 Study roadmap and anticipated capabilities in complementary disciplines are quoted to provide context for the progress made in grid adaptation in the past fifteen years, current status, and a forecast for the next fifteen years with recommended investments. These investments are specific to mesh adaptation and impact other aspects of the CFD process. Finally, a strategy is identified to diffuse grid adaptation technology into production CFD work flows.

Park, Michael A.↗
NASA NTRS2017

Development of an Unstructured, Three-Dimensional Material Response Design Tool

A preliminary verification and validation of a new material response model is presented. This model, Icarus, is intended to serve as a design tool for the thermal protection systems of re-entry vehicles. Currently, the capability of the model is limited to simulating the pyrolysis of a material as a result of the radiative and convective surface heating imposed on the material from the surrounding high enthalpy gas. Since the major focus behind the development of Icarus has been model extensibility, the hope is that additional physics can be quickly added. The extensibility is critical since thermal protection systems are becoming increasing complex, e.g. woven carbon polymers. Additionally, as a three-dimensional, unstructured, finite-volume model, Icarus is capable of modeling complex geometries as well as multi-dimensional physics, which have been shown to be important in some scenarios and are not captured by one-dimensional models. In this paper, the mathematical and numerical formulation is presented followed by a discussion of the software architecture and some preliminary verification and validation studies.

Material Response Model↗
NASA NTRS2017

Development of a Three-Dimensional, Unstructured Material Response Design Tool

A preliminary verification and validation of a new material response model is presented. This model, Icarus, is intended to serve as a design tool for the thermal protection systems of re-entry vehicles. Currently, the capability of the model is limited to simulating the pyrolysis of a material as a result of the radiative and convective surface heating imposed on the material from the surrounding high enthalpy gas. Since the major focus behind the development of Icarus has been model extensibility, the hope is that additional physics can be quickly added. This extensibility is critical since thermal protection systems are becoming increasing complex, e.g. woven carbon polymers. Additionally, as a three-dimensional, unstructured, finite-volume model, Icarus is capable of modeling complex geometries. In this paper, the mathematical and numerical formulation is presented followed by a discussion of the software architecture and some preliminary verification and validation studies.

Thermal Protection System↗
NASA NTRS2019

Using Power Diagrams to Build Optimal Unstructured Meshes for C-Grid Models

The Model for Prediction Across Scales (MPAS) for Ocean (-O), Sea-Ice (-SI) and Land-Ice (-LI), in addition to the Coastal Ocean Marine Prediction Across Scales (COMPAS) are two novel general circulation models designed to resolve coupled ocean-ice dynamics over variable spatial scales using non-uniform unstructured grids. Both models are based on a conservative mimetic finite-difference/volume formulation (TRiSK), in which staggered momentum, vorticity and mass-based degrees- of-freedom are distributed over an orthogonal 'primal-dual' mesh.

Engwirda, Darren↗
NASA NTRS2018

Model-Invariant Hybrid RANS-LES Computations on Unstructured Meshes

Hybrid RANS-LES computations combine the bene ts of RANS and LES so that LES is used in regions where the accuracy of RANS deteriorates. The numerous hybrid approaches are limited by the speci cation of the LES-RANS interface, which can cause nonphysical results such as log-layer mismatch and low shear stress. The hybrid RANS-LES approach based on the concept of model invariance, mitigates these problems, enabling seamless blending of the RANS and LES regions while forming the basis for interpreting the results in the interface region. This hybrid formulation was implemented in the NASA FUN3D unstructured code and computations for ow in a channel at Reynolds number of 3300 (based on the channel half width h and the bulk in ow velocity u(infinity) were carried out. An isotropic stochastic turbulence generator was implemented to generate in ow turbulence. The present approach was able to eliminate the log-layer mismatch and predict the shear stress fairly well. Thus, the model-invariant hybrid formulation coupled with the isotropic turbulence in ow generation serves as a physically meaningful way of performing hybrid RANS-LES computations.

Sreekanth, R.↗
NASA NTRS2019

Geometry Modeling for Unstructured Mesh Adaptation

The quantification and control of discretization error is critical to obtaining reliable simulation results. Adaptive mesh techniques have the potential to automate discretization error control, but have made limited impact on production analysis workflow. Recent progress has matured a number of independent implementations of flow solvers, error estimation methods, and anisotropic mesh adaptation mechanics. However, the poor integration of initial mesh generation and adaptive mesh mechanics to typical sources of geometry has hindered adoption of adaptive mesh techniques, where these geometries are often created in Mechanical Computer- Aided Design (MCAD) systems. The difficulty of this coupling is compounded by two factors: the inherent complexity of the model (e.g., large range of scales, bodies in proximity, details not required for analysis) and unintended geometry construction artifacts (e.g., translation, uneven parameterization, degeneracy, self-intersection, sliver faces, gaps, large tolerances be- tween topological elements, local high curvature to enforce continuity). Manual preparation of geometry is commonly employed to enable fixed-grid and adaptive-grid workflows by reducing the severity and negative impacts of these construction artifacts, but manual process interaction inhibits workflow automation. Techniques to permit the use of complex geometry models and reduce the impact of geometry construction artifacts on unstructured grid workflows are models from the AIAA Sonic Boom and High Lift Prediction are shown to demonstrate the utility of the current approach.

Park, Michael A.↗
NASA NTRSDate not supplied

Comparing Unstructured Adaptive Mesh Solutions for the High Lift Common Research Model Airfoil

Discretization error is a common source of uncertainty in Computational Fluid Dynamics (CFD) analyses. Traditional means of controlling discretization error through fixed-mesh refinement studies has proven to be difficult particularly when modeling complex geometries and flow fields. One reason for this is that mesh generation in today’s production CFD workflow is often a labor intensive process that is heavily dependent on user judgment. Unstructured mesh adaptation is known to be an efficient way to control discretization errors in CFD. Adaptive methods replace user based decision making with automated processes that optimize a mesh to reduce discretization error. This paper compares the application of multiple solution adaptive techniques in combination with multiple flow solvers to solve for the flow field about a 2D airfoil section of the NASA High-Lift Common Research Model (HL-CRM). By driving the adaptive mesh processes to a similar level of mesh convergence, the ability to achieve consistent results between multiple adaptive techniques and flow solvers is demonstrated. Mesh convergence for the various adaptive mesh approaches is compared identifying potential areas for improvement and providing mesh generation guidance for future workshops.

mesh adaptation high-lift 2D airfoil↗
NASA NTRSDate not supplied

Comparing Unstructured Adaptive Mesh Solutions for the High Lift Common Research Model Airfoil

Discretization error is a common source of uncertainty in Computational Fluid Dynamics (CFD) analyses. Traditional means of controlling discretization error through fixed-mesh refinement studies has proven to be difficult particularly when modeling complex geometries and flow fields. One reason for this is that mesh generation in today’s production CFD workflow is often a labor intensive process that is heavily dependent on user judgment. Unstructured mesh adaptation is known to be an efficient way to control discretization errors in CFD. Adaptive methods replace user based decision making with automated processes that optimize a mesh to reduce discretization error. This paper compares the application of multiple solution adaptive techniques in combination with multiple flow solvers to solve for the flow field about a 2D airfoil section of the NASA High-Lift Common Research Model (HL-CRM). By driving the adaptive mesh processes to a similar level of mesh convergence, the ability to achieve consistent results between multiple adaptive techniques and flow solvers is demonstrated. Mesh convergence for the various adaptive mesh approaches is compared identifying potential areas for improvement and providing mesh generation guidance for future workshops.

mesh adaptation↗
NASA NTRSDate not supplied

Structured Overset and Unstructured Grid Simulations for the Third AIAA Sonic Boom Prediction Workshop

Predictions using the Launch Ascent and Vehicle Aerodynamics (LAVA) Unstructured and Structured Curvilinear solvers for the Biconvex and C608 geometries are compared in support of the 3rd AIAA Sonic Boom Prediction workshop. Description of the mesh generation techniques and numerical methods are provided along with a comparison of nearfield and far-field predictions with available experimental data as well as other workshop sub-missions. Strong consistency was observed between the Biconvex and C608 nearfield predictions across the two solvers used for this study, as well as validation and verification data. Additionally, near-field and farfield ground signature results using a combination of a truncated computational fluid dynamics (CFD) domain coupled to a mid-field space marching method and propagated to the ground using sBOOM will be discussed. This approach is shown to provide an efficient way to propagate near-field pressure signatures to the ground with the same accuracy as the near-field CFD coupled to sBOOM, but at less computational cost.

CST↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

Towards an Automated Unstructured Grid Adaptation Workflow with VULCAN

Early work is presented for an unstructured grid adaptation workflow with VULCAN and refine. Anisotropic simplex grids are iteratively adapted to match a Riemannian metric tensor field describing desired mesh spacing. The Riemannian metric tensor field is obtained from Hessians of CFD solution output scalar sensor fields; both Mach number and static temperature sensor fields are explored. In addition, we describe a Newton-method-based solver recently implemented in VULCAN utilizing Jacobian-Free-Newton-Krylov that can be used to increase flow solver automation on early grids in the adadptation process. Hypersonic flow solutions are presented on a high Reynolds number flat plate and wall heat flux is compared against a highly resolved structured solution. Additionally, complex shock boundary-layer interaction is explored in a high Mach number compression corner and complex 3D flow phenomena are evaluated on the Boundary Layer Transition (BOLT) vehicle.

Matthew O'Connell↗
NASA NTRS2022

Scraping Unstructured Data to Explore the Relationship between Rainfall Anomalies and Vector-Borne Disease Outbreaks

According to the World Health Organization (WHO), vector-borne diseases such as malaria and dengue account for 17% of all infectious disease cases and lead to more than 700,000 deaths per year. Tracking and predicting the spread of vector-borne diseases is a vital task that could save hundreds of thousands of lives annually. Oftentimes, the first reports of vector-borne disease outbreaks occur through emails and online reporting systems long before they are officially documented. Tracking and predicting the emergence and spread of vector-borne disease outbreaks requires extracting data from these unstructured sources in combination with historical weather and climate data to understand the underlying background triggers and disease dynamics. In this work, we develop a data extraction pipeline for the online outbreak reporting website ProMED-mail that utilizes a web scraper, transformer neural network summarizer, and named entity recognizer to obtain a dataset of malaria, dengue, zika, and chikungunya outbreaks over the last 30 years. This scraped dataset was further analyzed in association with global rainfall anomalies derived from NASA’s Integrated Multi-satellitE Retrievals for GPM [Global Precipitation Mission] (IMERG) dataset. This preliminary analysis was to understand the effect of global rainfall patterns on the spread of vector-borne diseases. Analysis of the ProMED-mail and GPM data shows that vector-borne disease outbreaks are clustered towards the tropics and outbreaks are often amplified during the rainy seasons. Our scraped dataset can be a valuable tool in creating comprehensive georeferenced disease records for modeling and predicting future outbreaks.

Web scraping↗
NASA NTRS2021

Physical Characteristics of Unstructured Coronal Clouds

Active regions in the inner solar corona, when observed in X-ray emission, consist of bright, hot loops surrounded by unstructured clouds. The emission from the clouds extends to a height of≈4–5×104km at temperatures of ≈2–3 MK. These “hot clouds” are variable, but persist for many days and do not appear to connect directly to the active region streamers or other large-scale structures observed higher in the corona. We present an observational analysis of these diffuse structures to establish basic plasma parameters such as magnetic field strength, particle density, and temperature. The values ofβ, the ratio of the plasma pressure to the magnetic field pressure, were found to be generally less than unity, though often approaching unity in the upper portions of the active region, where the hot clouds are located. The magnetic field may therefore only partially confine these regions and inhibit flare-like instabilities that could otherwise be driven by gradients of plasma pressure and current density.

The Sun↗
NASA NTRSDate not supplied

Wall-Modeled Large Eddy Simulation Method for Unstructured-Grid Navier-Stokes Solvers

This paper reports on the implementation and assessment of a Wall-Modeled Large-Eddy Simulation (WMLES) methodology in an unstructured-grid, node-centered flow solver, FUN3D that is developed and supported at the NASA Langley Research Center. Finite-volume (FV) and finite-element (FE) discretization schemes considered in the study provide formal second-order spatial accuracy. Large-Eddy Simulations (LES) resolve large-scale turbulent-flow features and filter out small-scale effects using the Vreman subgrid-scale model. At solid-wall boundaries, a shear-stress model is employed to provide a proper boundary-flux closure. The nonlinear equations are integrated in time using either an optimized backward difference formula or an implicit multistage Runge-Kutta temporal scheme. The implicit equations at each time step are solved by strong nonlinear iteration schemes. WMLES demonstrations are shown for two high-lift configurations, namely, the McDonnell Douglas 30P30N multielement airfoil and a NASA High-Lift Common Research Model. Results show that the WMLES approaches implemented in the FV and FE discretization methods produce consistent solutions and are capable of capturing key aerodynamic characteristics and flow structures for high-lift configurations at a wide range of angles of attack including maximum-lift conditions. In the 30P30N example, correct trends in the variations of integrated aerodynamic forces and moments, surface pressure distributions, and boundary-layer profiles are captured as the Reynolds number is increased.

CFD; turbulence modeling; High-Lift flow simulatio↗
NASA NTRS2021

Australian tidal currents – assessment of a barotropic model (COMPAS v1.3.0 rev6631) with an unstructured grid

While the variations of tidal range are large and fairly well known across Australia (less than 1 m near Perth but more than 14 m in King Sound), the properties of the tidal currents are not. We describe a new regional model of Australian tides and assess it against a validation dataset comprising tidal height and velocity constituents at 615 tide gauge sites and 95 current meter sites. The model is a barotropic implementation of COMPAS, an unstructured-grid primitive-equation model that is forced at the open boundaries by TPXO9v1. The mean absolute error (MAE) of the modelled M2 height amplitude is 8.8 cm, or 12 % of the 73 cm mean observed amplitude. The MAE of phase (10°), however, is significant, so the M2 mean magnitude of vector error (MMVE, 18.2 cm) is significantly greater. The root sum square over the eight major constituents is 26 % of the observed amplitude. We conclude that while the model has skill at height in all regions, there is definitely room for improvement (especially at some specific locations). For the M2 major axis velocity amplitude, the MAE across the 95 current meter sites, where the observed amplitude ranges from 0.1 to 156 cm s −1 , is 6.9 cm s −1 , or 22 % of the 31.7 cm s −1 observed mean. This nationwide average result is encouraging, but it conceals a very large regional variation. Relative errors of the tidal current amplitudes on the narrow shelves of New South Wales (NSW) and Western Australia exceed 100 %, but tidal currents are weak and negligible there compared to non-tidal currents, so the tidal errors are of little practical significance. Looking nationwide, we show that the model has predictive value for much of the 79 % of Australia's shelf seas where tides are a major component of the total velocity variability. In descending order this includes the Bass Strait, the Kimberley to Arnhem Land, and southern Great Barrier Reef regions. There is limited observational evidence to confirm that the model is also valuable for currents in other regions across northern Australia. We plan to commence publishing “unofficial” tidal current predictions for chosen regions in the near future based on both our COMPAS model and the validation dataset we have assembled.

Tidal currents↗