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NASA NTRSDate not supplied

Uncertainty Quantification of CFD Model Assumptions Against Sonic Boom Noise Prediction of a Commercial Supersonic Transport

This paper presents the results of uncertainty modeling of sonic boom noise generation from commercial supersonic transport considering the Spalart-Allmaras (SA) turbulence modeling parameters as well as Mach number, angle of attack and altitude. Sample generation and analysis for this uncertainty model was performed by UQPCE, which is a software package developed at the NASA Langley Research Center. To build the uncertainty model, 42 cases of sonic boom noise calculation were performed. Computation of the ground noise can be briefly summarized in two steps. First, the near field pressure waveforms are sampled from CFD calculation using the NASA Langley’s FUN3D solver. Second, this information is passed to an atmospheric propagation code, sBOOM, which solves an augmented Burger’s equation and simulates how the near field waveforms will change while passing through the atmosphere. The ground signature is further processed to obtain the perceived loudness, PLdB. Having a high spatial resolution near the shockwave in the CFD calculation is critical in sonic boom noise prediction. Because the variation in the input parameters for the current uncertainty quantification (UQ) study is likely to lead to change in shock location, angle and strength, the grid adaptation for shock capturing is independently applied for each condition. The final mesh used in the CFD calculation consists of approximately 420 million cells. The pressure signatures are sampled at three, four and five body lengths away from the aircraft to make sure the three dimensional effects around the aircraft are resolved. The results of the UQ analysis shows that within the three aleatory variables, the angle of attack had the most impact against ground noise, followed by the altitude and the Mach number. Between the two SA model parameters, the Kármán constant (𝜅) was significantly more important than the turbulent Prandtl number (𝜎), but these two parameters were only marginally significant in the overall prediction variance in ground noise. The UQ procedure explained in this paper can be widely applied to other model parameters.

Uncertainty Quantification↗
NASA NTRSDate not supplied

Uncertainty Quantification of CFD Model Assumptions Against Sonic Boom Noise Prediction of a Commercial Supersonic Transport

This paper presents the results of uncertainty modeling of sonic boom noise generation from commercial supersonic transport considering the Spalart-Allmaras (SA) turbulence modeling parameters as well as Mach number, angle of attack and altitude. Sample generation and analysis for this uncertainty model was performed by UQPCE, which is a software package developed at the NASA Langley Research Center. To build the uncertainty model, 42 cases of sonic boom noise calculation were performed. Computation of the ground noise can be briefly summarized in two steps. First, the near field pressure waveforms are sampled from CFD calculation using the NASA Langley’s FUN3D solver. Second, this information is passed to an atmospheric propagation code, sBOOM, which solves an augmented Burger’s equation and simulates how the near field waveforms will change while passing through the atmosphere. The ground signature is further processed to obtain the perceived loudness, PLdB. Having a high spatial resolution near the shock wave in the CFD calculation is critical in sonic boom noise prediction. Because the variation in the input parameters for the current uncertainty quantification (UQ) study is likely to lead to change in shock location, angle and strength, the grid adaptation for shock capturing is independently applied for each condition. The final mesh used in the CFD calculation consists of approximately 420 million cells. The pressure signatures are sampled at three, four and five body lengths away from the aircraft to make sure the three dimensional effects around the aircraft are resolved. The results of the UQ analysis shows that within the three aleatory variables, the angle of attack had the most impact against ground noise, followed by the altitude and the Mach number. Between the two SA model parameters, the Kármán constant (𝜅) was significantly more important than the turbulent Prandtl number (𝜎), but these two parameters were only marginally significant in the overall prediction variance in ground noise. The UQ procedure explained in this paper can be widely applied to other model parameters.

Uncertainty Quantifications↗
NASA NTRS2023

Evaluation of Transport-Equation-Based Transition Models for High-Speed Boundary Layers Using OVERFLOW

Accurate modeling of laminar-turbulent transition is crucial for the design of hypersonic flight systems. However, the current transition models used in production CFD codes are insufficient for high-speed flows. Many extensions to low-speed models have been suggested; however, a thorough verification and validation effort is needed before these models can be used in design settings. Challenges include potentially missing details of the model implementation requirements and/or a complete specification of the input parameters needed to replicate the test findings. A meaningful assessment of the generalization capability of these models is also hindered by a lack of information regarding the specific flow configurations and associated grids employed for model calibration. As a key first step toward model verification, we present an independent assessment of two recently proposed models for high-speed transition, namely, a model within the SST-$\gamma$ framework and a model based on the SST-$\gamma-\nu_L$ equations. These models are implemented in the NASA OVERFLOW 2.3e solver and their performance in predicting first mode, second mode, and crossflow transition has been evaluated for several test cases in the supersonic and hypersonic regimes. Besides the test cases employed by the model developers, which could have also been used for model calibration, the present assessment includes supplementary configurations that contribute to an unbiased assessment of the models. The outcomes presented in this study indicate the potential for the models to be applied to high-speed flight configurations. Key steps toward future improvements to these models are also outlined.

High-speed flow↗
NASA NTRS2021

Pretest Computational Assessment of Boundary Layer Transition in the NASA Juncture Flow Model with an NACA 0015-Based Wing

The first two phases of the NASA Juncture Flow experiment were carried out on a DLR-F6 swept-wing model and were designed to provide “CFD validation-quality” data toward the assessment and improvement of existing CFD turbulence models in predicting onset and extent of three-dimensional separated flow near the wing-juncture trailing-edge region. The next phase of experiments will involve an NACA 0015-based swept wing, as prior risk reduction experiments had indicated that this wing shape resulted in reduced separation near the juncture region than the DLR-F6 wing, thus providing a better option to evaluate the ability of CFD models to predict incipient turbulent separation. The NACA 0015 measurements will also include IR thermography to infer the variation of transition front with respect to an increasing angle of attack. The primary objective of this work is to computationally make a preliminary assessment of the transition front on both surfaces of the NACA 0015 wing at a crank-chord-based Reynolds number of 2.4 x 106 for four different angles of attack, (0°, 2.5°, 5°, and 7.5°) and to determine the dominant mechanisms responsible for transition. This assessment includes both RANS-based transition models from NASA’s OVERFLOW 2.3b flow solver and linear parabolized stability equations (PSE) stability analysis based on the Langley Stability and Transition Analysis code, LASTRAC. Linear PSE results indicate that the upper surface of the wing is dominated by Tollmien- Schlichting (TS) instabilities, and that the laminar flow region shrinks from about 50% chord to a very small region just downstream of the attachment line as the angle of attack is increased from 0° to 7.5°. Consequently, the transition fronts predicted by the Spalart- Allmaras-based amplification factor transport (AFT-2017b) equation model (which accounts for the TS instabilities alone) and the Menter’s shear-stress transport equation (SST2003)- based Langtry-Menter transition model with ability to account for both TS and crossflow effects (LM2015) compare well with those predicted using linear PSE. On the lower surface of the wing, stationary crossflow (CF) instabilities begin to appear on the inboard portion of the wing in addition to the TS-instabilities for the larger angles of attack (5° and 7.5°), further reducing the laminar flow extent within the inboard region. The LM2015 model that accounts for CF effects is able to replicate this trend but appears to predict a slightly earlier transition. The outcome of this effort will inform the experiment and, when the actual experimental data become available, provide further opportunity to assess and improve the various transition models.

CFD modeling↗
NASA NTRS2006

Validation of Multi-Dimensional Stirling Engine Design Codes: Measurements in the 90-Degree Turn Test Section

The work to be presented herein was motivated largely by a desire to improve the understanding of oscillatory fluid mechanics inside a Stirling engine. To this end, a CFD project was undertaken at Cleveland State University with the goal of accurately predicting the fluid dynamics within an engine or engine component. Along with the CFD efforts, a code validation project was undertaken at the University of Minnesota. The material covered herein consists of four main parts. In section 1, an experimental investigation of a small aspect ratio impinging jet is discussed. Included in this discussion is a description of the test facilities and instrumentation. A presentation of the collected data is given and comments are made. Next, in section 2, a parallel experimental investigation is presented in which the same geometry as that of section 1 is used, but the flow conditions are changed from steady unidirectional flow to sinusoidally oscillating flow. In section Two, collected data are presented and comments are made. In section 3, a comparison is made between the results of sections 1 and 2, namely, sinusoidally oscillating flow results are compared to steady, unidirectional flow results from the same geometry. Finally, in section 4, a comparison is made between experimentally collected data (the main subject of this work) and CFD generated results. Furthermore, in appendix A, an introductory description of the primary measurement tool used in the experimental process the hot wire anemometer is given for the unfamiliar. The anemometer calibration procedure is described in appendix B. A portfolio of data reduction and data processing codes is provided in appendix C and lastly, a DVD and a roadmap of its contents is provided in an appendix D. 1.0 Unidirectional Flow Investigations 1.1 Introduction This unidirectional experimental program was undertaken to complement an oscillatory flow investigation conducted at the University of Minnesota. The oscillatory investigation is discussed thoroughly in section 2. We defer the description of the motivation behind these experiments until the introduction of section 2. The work that is discussed in this thesis began (chronologically) with oscillatory flow visualization experiments. It was decided that it would be valuable and important to investigate the flow under unidirectional conditions in the same geometry as that of the oscillatory experiments. The thought was that the unidirectional case would be less complicated to model with a CFD program (a moving boundary would be replaced with a steady state boundary condition). Thus, a series of unidirectional experiments were carried out to capture the important features of the flow within the test section. The purpose of these experiments was to provide a data set for comparison to CFD generated velocity fields. Hot-wire anemometry data were taken and flow visualization was conducted as a standard for code validation. The flow geometry was simple, such that it could be easily gridded in a CFD program. However, the geometry provided separation and transition zones, shear layers and recirculation zones. These characteristics made the flow complex and challenging for CFD computation. We comment that the order of experiments that produced this report is as follows: experimental flow visualization under oscillatory flow conditions was carried out; this was followed by unidirectional flow visualization and hot wire anemometry; finally, oscillatory hot wire anemometry was conducted. We present the results out of chronological order for the following reason: the unidirectional results are easier

Simon, Terrence W.↗
NASA NTRS1998

A Geometry Based Infra-Structure for Computational Analysis and Design

The computational steps traditionally taken for most engineering analysis suites (computational fluid dynamics (CFD), structural analysis, heat transfer and etc.) are: (1) Surface Generation -- usually by employing a Computer Assisted Design (CAD) system; (2) Grid Generation -- preparing the volume for the simulation; (3) Flow Solver -- producing the results at the specified operational point; (4) Post-processing Visualization -- interactively attempting to understand the results. For structural analysis, integrated systems can be obtained from a number of commercial vendors. These vendors couple directly to a number of CAD systems and are executed from within the CAD Graphical User Interface (GUI). It should be noted that the structural analysis problem is more tractable than CFD; there are fewer mesh topologies used and the grids are not as fine (this problem space does not have the length scaling issues of fluids). For CFD, these steps have worked well in the past for simple steady-state simulations at the expense of much user interaction. The data was transmitted between phases via files. In most cases, the output from a CAD system could go to Initial Graphics Exchange Specification (IGES) or Standard Exchange Program (STEP) files. The output from Grid Generators and Solvers do not really have standards though there are a couple of file formats that can be used for a subset of the gridding (i.e. PLOT3D data formats). The user would have to patch up the data or translate from one format to another to move to the next step. Sometimes this could take days. Specifically the problems with this procedure are:(1) File based -- Information flows from one step to the next via data files with formats specified for that procedure. File standards, when they exist, are wholly inadequate. For example, geometry from CAD systems (transmitted via IGES files) is defined as disjoint surfaces and curves (as well as masses of other information of no interest for the Grid Generator). This is particularly onerous for modern CAD systems based on solid modeling. The part was a proper solid and in the translation to IGES has lost this important characteristic. STEP is another standard for CAD data that exists and supports the concept of a solid. The problem with STEP is that a solid modeling geometry kernel is required to query and manipulate the data within this type of file. (2) 'Good' Geometry. A bottleneck in getting results from a solver is the construction of proper geometry to be fed to the grid generator. With 'good' geometry a grid can be constructed in tens of minutes (even with a complex configuration) using unstructured techniques. Adroit multi-block methods are not far behind. This means that a million node steady-state solution can be computed on the order of hours (using current high performance computers) starting from this 'good' geometry. Unfortunately, the geometry usually transmitted from the CAD system is not 'good' in the grid generator sense. The grid generator needs smooth closed solid geometry. It can take a week (or more) of interaction with the CAD output (sometimes by hand) before the process can begin. One way Communication. (3) One-way Communication -- All information travels on from one phase to the next. This makes procedures like node adaptation difficult when attempting to add or move nodes that sit on bounding surfaces (when the actual surface data has been lost after the grid generation phase). Until this process can be automated, more complex problems such as multi-disciplinary analysis or using the above procedure for design becomes prohibitive. There is also no way to easily deal with this system in a modular manner. One can only replace the grid generator, for example, if the software reads and writes the same files. Instead of the serial approach to analysis as described above, CAPRI takes a geometry centric approach. This makes the actual geometry (not a discretized version) accessible to all phases of the analysis. The connection to the geometry is made through an Application Programming Interface (API) and NOT a file system. This API isolates the top-level applications (grid generators, solvers and visualization components) from the geometry engine. Also this allows the replacement of one geometry kernel with another, without effecting these top-level applications. For example, if UniGraphics is used as the CAD package then Parasolid (UG's own geometry engine) can be used for all geometric queries so that no solid geometry information is lost in a translation. This is much better than STEP because when the data is queried, the same software is executed as used in the CAD system. Therefore, one analyzes the exact part that is in the CAD system. CAPRI uses the same idea as the commercial structural analysis codes but does not specify control. Software components of the CAD system are used, but the analysis suite, not the CAD operator, specifies the control of the software session. This also means that the license issues (may be) minimized and individuals need not have to know how to operate a CAD system in order to run the suite.

Haimes, Robert↗