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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

CDISC Remote Design Method to Simulate Aircraft Interference Effects for the CATNLF Flight Test

The Crossflow Attenuated Natural Laminar Flow (CATNLF) flight test is an experimental evaluation of a laminar flow design approach that will be conducted on a small transonic wing-like model suspended from the Centerline Instrumented Pylon (CLIP) underneath an F-15 vehicle. The upcoming flight test is anticipated to provide experimental data that may be useful for transition prediction code calibrations or laminar flow computational studies. For the computational results to be reliable, relevant aerodynamics must be included in the simulations. It has been shown that the F-15 vehicle produces a notable aerodynamic influence on the CATNLF test article, and that removing the F-15 vehicle from the simulation significantly alters the laminar flow behavior. Because the F-15 vehicle is not a publicly-releasable geometry, if the CATNLF flight test dataset is to be widely used by the community, an alternative method to ensure that the CATNLF test article flight configuration aerodynamics is properly modeled is required. The objective of this research is to use the CDISC aerodynamic design tool to perform a remote design of a surface that would replicate the aerodynamic influence on the CATNLF test article. This new design approach, referred to as the Equivalent Loading via Interference Surface Effects (ELISE), is presented in this paper, including the details on the design setup and results. The ELISE design successfully reproduced the F-15 influence on the CATNLF test article, with predicted transition location within an average of 4% chord of the full flight configuration. An off-design assessment is included for small perturbations in Mach and sideslip angle that suggest the ELISE design can cover a reasonable range of expected flight conditions with the same geometry. This paper is intended to explain the design approach, as well as show results that can be expected when utilizing the ELISE design method.

CDISC↗
NASA NTRSDate not supplied

CDISC Remote Design Method to Simulate Aircraft Interference Effects for the CATNLF Flight Test

The Crossflow Attenuated Natural Laminar Flow (CATNLF)flight test is an experimental evaluation of a laminar flow design approach that will be conducted on a small transonic wing-like model suspended from the Centerline Instrumented Pylon (CLIP) underneath an F-15 vehicle. The upcoming flight testis anticipated to provide experimental data that may be useful for transition prediction code calibrations or laminar flow computational studies. For the computational results to be reliable, relevant aerodynamics must be included in the simulations. It has been shown that the F-15 vehicle produces a notable aerodynamic influence on the CATNLF test article, and that removing the F-15 vehicle from the simulation significantly alters the laminar flow behavior. Because the F-15 vehicle is not a publicly-releasable geometry, if the CATNLF flight test dataset is to be widely used by the community, an alternative method to ensure that the CATNLF test article flight configuration aerodynamics is properly modeled is required. The objective of this research is to use the CDISC aerodynamic design tool to perform a remote design of a surface that would replicate the aerodynamic influence on the CATNLF test article. This new design approach, referred to as the Equivalent Loading via Interference Surface Effects (ELISE), is presented in this paper, including the details on the design setup and results. The ELISE design successfully reproduced theF-15 influence on the CATNLF test article, with predicted transition location within an average of 4% chord of the full flight configuration. An off-design assessment is included for small perturbations in Mach and sideslip angle that suggest the ELISE design can cover a reasonable range of expected flight conditions with the same geometry. This paper is intended to explain the design approach, as well as show results that can be expected when utilizing the ELISE design method.

CDISC↗
NASA NTRSDate not supplied

Exploring data-driven modeling of boundary layer transition

Prediction of laminar-turbulent transition in boundary layer flows is an important component of predicting the aerodynamic performance of a number of aerospace configurations. According to the CFD Vision 2030 [1], transition modeling represents acriticalarea in CFD simulation capability that will remain a pacing item for the foreseeable future. The fact thattransition can take placevia either one of a myriad possible paths adds to the challenges inreliable transition predictions, despite a limited knowledge of the relevant input parameters. In the low disturbance environments typical of flight applications, transition is often initiated by small amplitude disturbances in the form of linear instability waves of the laminar boundary layer. These disturbances amplify linearly at first and eventually undergo a sequence of nonlinear interactions that result in transition to turbulence. Because the nonlinear phase is rather rapid, the amplification of boundary layer instabilities is governed by the linearstability theory over a majority of the distance leading up to the onset of transition. Semi-empirical transition correlations based on the linear stability theory have been successful in explaining the observed trends in transition location within a broad class of flows. However, the application of stability theory is highly non-robust and often requires a significant domain expertise. Recent work at the NASA Langley Research Center has beenaimed at bridging the gap between physics based transition analyses such as those based on linear stability theory and practical applications that require transition prediction by users that may not be well versed in transition physics. The applications of deep learning have been at the center of these efforts. This presentation will focus on the progress achieved thus far, highlighting the applications of neural networks to selectedtransition scenarios across a range of Mach numbers and flow configuration, as well as the lessons learnedand remaining challengeswithrespect to the selection of training data and neural networks architectures, hyperparameter tuning, and the physical insights distilled from the otherwise black-box models.

M. R. Malik↗
NASA NTRS2019

Effect of Out-Gassing on the Onset of Hypersonic Boundary Layer Transition

Prediction and control of the onset of transition and the associated variation in aerothermodynamic parameters in high-speed flows is key to optimize the performance and design of Thermal Protection Systems (TPS) of next-generation aerospace vehicles [1]. Boundary Layer Transition (BLT) characteristics can influence the surface heating budget determining the TPS thickness and consequently its weight penalty. Ablative heatshields are designed to alleviate the high heat flux at the surface through pyrolysis of their polymeric matrix and subsequent fiber ablation [2]. Pyrolysis leads to out-gassing and non-uniform ablation lead to surface roughness, both of which are known to influence the transition process. An ablator impacts BLT through three main routes: gas injecting into the boundary layer from the wall, changing the surface heat transfer due to wall-flow chemical reactions, and modifying surface roughness [3]. In preparation to Mars 2020 mission post-flight analysis, the predictive transition capability has been initiated toward hard-coupling porous material response analysis and aerothermal environment calculation.

Karimi, Mona↗
NASA NTRS1989

Prediction of transitional (laminar-turbulent) hypersonic flows using the parabolized Navier-Stokes equations

Hypersonic transitional flow predictions have been made using the parabolized Navier-Stokes equations with an algebraic transition/turbulence model by appropriately modulating the turbulent viscosity with the available intermittency functions for incompressible and compressible flows. A comparison between the predictions with and without a low Reynolds number correction has also been made. The predictions are compared with the available experimental data and with the theory over a range of Mach number. A simple Re(theta)/M(delta) criterion is shown to satisfactorily predict the meridional variation of the onset location of transition on a cone at a small angle of attack, whereas none of the correlations discussed can do that. Various available correlations are discussed vis-a-vis the predictions as to the locations of the onset and the end of transition.

Kaul, Upender K.↗
NASA NTRSDate not supplied

Exploring the Langtry-Menter Transition Model for High Speed Applications Using FUN3D

A series of Reynolds-averaged Navier-Stokes (RANS) simulations were performed using the FUN3D flow solver to explore the capabilities of the Langtry-Menter Shear-Stress Transport (LM-SST) transition model for predicting transition for aircraft inlet applications. Two geometries were simulated: a zero-pressure-gradient flat plate and an axisymmetric cone exposed to hypersonic flow. In addition to the transition-sensitized LM-SST model investigations, simulations were run with the one-equation Spalart-Allmaras (SA) and the two-equation Menter Shear-Stress Transport (SST-V) RANS models in fully turbulent mode to identify the natural RANS model transition behavior as a function of Mach number when executed in fully turbulent mode. The flat plate simulations showed that (1) the transition model was able to predict rapid transition at a freestream Mach number of 0.2, which is expected but (2) the predicted transition location moved downstream as the freestream Mach number was increased for the simulations that used the SST-V turbulence model. The latter is significant as it is usually assumed that one- and two-equation turbulence models will produce fully turbulent flow very near the boundary layer origin. The flat plate simulation freestream Mach number trend was confirmed with simulations using the Wind-US code, which also saw a similar trend when employing the SA turbulence model. For the axisymmetric cone simulations, the transition location was highly sensitive to the inflow turbulence levels. This is significant as the prediction of the transition location is crucial when trying to predict inlet performance, especially for hypersonic vehicle applications. It was also noted that the predicted transition location for the cone when using the SST-V turbulence model agreed well with the predicted transition location from the equivalent zero-pressure-gradient flat plate case.

Transition Model↗
NASA NTRS2023

Exploring the Langtry-Menter Transition Model for High Speed Applications Using FUN3D

A series of Reynolds-averaged Navier-Stokes (RANS) simulations were performed using the FUN3D flow solver to explore the capabilities of the Langtry-Menter Shear-Stress Transport (LM-SST) transition model for predicting transition for aircraft inlet applications. Two geometries were simulated: a zeropressure-gradient flat plate and an axisymmetric cone exposed to hypersonic flow. In addition to the transition-sensitized LM-SST model investigations, simulations were run with the one-equation SpalartAllmaras (SA) and the two-equation Menter Shear-Stress Transport (SST-V) RANS models in fully turbulent mode to identify the natural RANS model transition behavior as a function of Mach number when executed in fully turbulent mode. The flat plate simulations showed that (1) the transition model was able to predict rapid transition at a freestream Mach number of 0.2, which is expected but (2) the predicted transition location moved downstream as the freestream Mach number was increased for the simulations that used the SST-V turbulence model. The latter is significant as it is usually assumed that one- and two-equation turbulence models will produce fully turbulent flow very near the boundary layer origin. The flat plate simulation freestream Mach number trend was confirmed with simulations using the Wind-US code, which also saw a similar trend when employing the SA turbulence model. For the axisymmetric cone simulations, the transition location was highly sensitive to the inflow turbulence levels. This is significant as the prediction of the transition location is crucial when trying to predict inlet performance, especially for hypersonic vehicle applications. It was also noted that the predicted transition location for the cone when using the SST-V turbulence model agreed well with the predicted transition location from the equivalent zero-pressure-gradient cold wall flat plate case.

Transition Model↗
NASA NTRS1987

Stability theory applications to laminar-flow control

In order to design Laminar Flow Control (LFC) configurations, reliable methods are needed for boundary-layer transition predictions. Among the available methods, there are correlations based upon R sub e, shape factors, Goertler number and crossflow Reynolds number. The most advanced transition prediction method is based upon linear stability theory in the form of the e sup N method which has proven to be successful in predicting transition in two- and three-dimensional boundary layers. When transition occurs in a low disturbance environment, the e sup N method provides a viable design tool for transition prediction and LFC in both 2-D and 3-D subsonic/supersonic flows. This is true for transition dominated by either TS, crossflow, or Goertler instability. If Goertler/TS or crossflow/TS interaction is present, the e sup N will fail to predict transition. However, there is no evidence of such interaction at low amplitudes of Goertler and crossflow vortices.

Malik, Mujeeb R.↗
NASA NTRS2020

Tuning Neural Network Models for Improved Prediction of Boundary Layer Transition

Boundary layer transition can strongly impact flight vehicle performance as it influences surface skin friction and aerodynamic heating, making accurate transition prediction a key to designing next generation aircraft. Artificial neural networks (ANNs) have shown promise toward predicting laminar-turbulent transition based on linear stability correlations. The computational efficiency of ANNs and the substantially reduced user involvement in relation to direct computations based on the linear stability theory (LST) makes them an attractive methodology for integrating the LST based correlations in computational fluid dynamics codes. Tollmien-Schlichting (TS) waves correspond to the dominant transition mechanism in 2D or weakly 3D subsonic boundary layers, such as those encountered in general aviation applications. Improvements to neural network model accuracy in predicting the amplification rates of TS instability waves have been investigated by leveraging recent machine learning developments in conjunction with surrogate optimization techniques and via suitable augmentation of the data used to train the networks. The optimized models trained on the modified dataset reduced the average transition location errors on different airfoils at several flow conditions by 51% of the original manually-tuned network’s errors on the same flow cases. The actual transition locations were derived from the Langley Stability and Transition Analysis Code (LASTRAC).

Machine Learning↗
NASA NTRS1958

Heat Transfer in the Turbulent Incompressible Boundary Layer: Effect of Location of Transition and Prediction of Heat Transfer in a Known Transition Region - IV

The effect of the location of transition on the heat transfer to the turbulent incompressible boundary layer is analyzed. The analysis indicates that considerably higher heat-transfer rates may occur for some distance downstream if the transition is very late. The results of a limited experimental investigation are in substantial agreement with the results of the analysis. If the extent of the transition region is known, the analysis also allows adequate prediction of heat-transfer coefficients within the transition region. The nature of this analysis is such that it should predict local shear coefficients in the transition region equally well.

Reynolds, W. C.↗
DOE OSTI2024

Predicting Critical Transitions in Multiscale Data

Predicting the dynamics of complex nonlinear systems remains a challenging problem both in dynamical systems theory as well as real world science and engineering applications. Data-driven methods utilizing the latest advances in machine learning (ML) provide a promising new paradigm for this task. Our work centered on Reservoir Computing (RC), which has shown itself to be capable of skillfully predicting chaotic dynamics in multiscale systems. In the first part of the work, the focus is on how to improve predictions of critical transitions in a class of slow-fast metastable systems in which the equations are known. An additional goal was to determine whether a relationship exists between RC and Koopman operator theory, to improve the efficiency and broaden the applicability of the approach. In the second part of this work, a variation on the RC model known as Reconstructive Reservoir Computing (RRC) is applied to real-world data to identify anomalies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Predicting Atomistic Transitions with Transformers

Accurate knowledge of the atomistic transition pathways in materials and material surfaces is crucial for many material science problems. However, conventional simulation techniques used to find these transitions are extremely computationally intensive. Even with large-scale, accelerated material simulations, the computational cost constrains the applicable domain in practice. Machine learning models, with the potential to learn the complex emergent behaviors governing atomistic transitions as a fast surrogate model, have great promise to predict transitions with a vastly reduced computational cost. Here, we demonstrate how transformers can be trained to predict atomistic transitions in nano-clusters. We show how we evaluate physical validity of the predictions and how a multitude of additional, different microstates can be generated by slightly varying the data provided to the model.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Numerical prediction of transition of the F-16 wing at supersonic speeds

A parametric study is being conducted as an effort to numerically predict the extent of natural laminar flow (NLF) on finite swept wings at supersonic speeds. This study is one aspect of a High Speed Research Program (HSRP) to gain an understanding of the technical requirements for high-speed aircraft flight. The parameters that are being addressed in this study are Reynolds number, angle of attack, and leading-edge wing sweep. These parameters were analyzed through the use of an advanced Computational Fluid Dynamics (CFD) flow solver, specifically the ARC 3-D Compressible Navier-Stokes (CNS) flow solver. From the CNS code, pressure coefficients (Cp) are obtained for the various cases. These Cp's are then used to compute the boundary-layer profiles through the use of the 'Kaups and Cebeci' compressible 2-D boundary layer code. Finally, the boundary-layer parameters are processed into a 3-D compressible boundary layer stability code (COSAL) to predict transition. The parametric study then consisted of four geometries which addressed the effects of sweep, and three angles of attack from zero to ten degrees to yield a total of 12 cases. The above process was substantially automated through a procedure that was developed by the work conducted under this study. This automation procedure then yields a 3-D graphical measure of the extent of laminar flow by predicting the transition location of laminar to turbulent flow.

Cummings, Russell M.↗
NASA NTRS1998

Mach Number Effects on Turbine Blade Transition Length Prediction

The effect of a Mach number correction on a model for predicting the length of transition was investigated. The transition length decreases as the turbulent spot production rate increases. Much of the data for predicting the spot production rate comes from low speed flow experiments. Recent data and analysis showed that the spot production rate is affected by Mach number. The degree of agreement between analysis and data for turbine blade heat transfer without film cooling is strongly dependent of accurately predicting the length of transition. Consequently, turbine blade heat transfer data sets were used to validate a transition length turbulence model. A method for modifying models for the length of transition to account for Mach number effects is presented. The modification was made to two transition length models. The modified models were incorporated into the two-dimensional Navier-Stokes code, RVCQ3D. Comparisons were made between predicted and measured midspan surface heat transfer for stator and rotor turbine blades. The results showed that accounting for Mach number effects significantly improved the agreement with the experimental data.

Boyle, R. J.↗
NASA NTRS1987

Prediction of transition on a flat plate under the influence of free-stream turbulence using low-Reynolds-number two-equation turbulence models

The prediction characteristics and capabilities of two popular two-equation low-Reynolds-number turbulence models (Jones, Launder 1972; Lam, Bremhorst 1981) have been evaluated with respect to the prediction of transition of a flat plate under the influence of free-stream turbulence. The sensitivity of the predictions to free-stream turbulence intensity, initial starting location of the calculation, and the assumed initial starting profiles for k and epsilon has been determined and presented. Although both models predict the correct qualitative characteristics of transition, they also exhibit significant quantitative deficiencies with regard to both the predicted location and the length of transition. A modification to the production term in the turbulent kinetic energy equation is proposed which is based on a simple stability criterion and correlated to the free-stream turbulence level. The modification becomes inactive in the fully turbulent regime, but is shown to improve both the qualitative and quantitative characteristics of the transition predictions.

Schmidt, Rodney C.↗
NASA NTRS1993

Relationship between transition and modes of instability in supersonic boundary layers

The relationship between the predicted transition location and the first and second modes of instability in two-dimensional supersonic boundary-layer flow on a flat plate is examined. Linear stability theory and the N-factor criterion are used to predict transition location. The effect of heat transfer is also studied; the results demonstrate that the transition reversal phenomenon can be explained by the opposite effect of cooling on the first and second modes of instability. Compressibility of destabilizing at free-stream Mach numbers of 2 to 3.5. The predicted transition location is due to the oblique first modes of instability, up to free-stream Mach numbers between 6 and 6.5. At higher Mach numbers, the predicted transition location is due to a combination of two-dimensional first and second modes of instability.

Masad, Jamal A.↗
NASA NTRS1998

Prediction of Transitional Flows in the Low Pressure Turbine

Current turbulence models tend to give too early and too short a length of flow transition to turbulence, and hence fail to predict flow separation induced by the adverse pressure gradients and streamline flow curvatures. Our discussion will focus on the development and validation of transition models. The baseline data for model comparisons are the T3 series, which include a range of free-stream turbulence intensity and cover zero-pressure gradient to aft-loaded turbine pressure gradient flows. The method will be based on the conditioned N-S equations and a transport equation for the intermittency factor. First, several of the most popular 2-equation models in predicting flow transition are examined: k-e [Launder-Sharina], k-w [Wilcox], Lien-Leschiziner and SST [Menter] models. All models fail to predict the onset and the length of transition, even for the simplest flat plate with zero-pressure gradient(T3A). Although the predicted onset position of transition can be varied by providing different inlet turbulent energy dissipation rates, the appropriate inlet conditions for turbulence quantities should be adjusted to match the decay of the free-stream turbulence. Arguably, one may adjust the low-Reynolds-number part of the model to predict transition. This approach has so far not been very successful. However, we have found that the low-Reynolds-number model of Launder and Sharma [1974], which is an improved version of Jones and Launder [1972] gave the best overall performance. The Launder and Sharma model was designed to capture flow re-laminarization (a reverse of flow transition), but tends to give rise to a too early and too fast transition in comparison with the physical transition. The three test cases were for flows with zero pressure gradient but with different free-stream turbulent intensities. The same can be said about the model when considering flows subject to pressure gradient(T3C1). To capture the effects of transition using existing turbulence models, one approach is to make use of the concept of the intermittency to predict the flow transition. It was originally based on the intermittency distribution of Narasimha [1957], and then gradually evolved into a transport equation for the intermittency factor. Gostelow and associates [1994,1995] have made some improvements to Narasimha's method in an attempt to account for both favorable and adverse pressure gradients. Their approach is based on a linear, explicit combination of laminar and turbulent solutions. This approach fails to predict the overshoot of the skin friction on a flat plate near the end of transition zone, even though the length of transition is well predicted. The major flaw of Gostelow's approach is that it assumes the non-turbulent part being the laminar solution and the turbulent part being the turbulent solution and they do not interact across the transitional region. The technique in condition averaging the flow equations in intermittent flows was first introduced by Libby [1975] and Dopazo [1977] and further refined by Dick and associates [1988, 1996]. This approach employs two sets of transport equations for the non-turbulent part and the other for the turbulent part. The advantage of this approach is that it allows the interaction of non-turbulent and turbulent velocities through the introduction of additional source terms in the continuity and momentum equations for the non-turbulent and turbulent velocities. However, the strong coupling of the two sets of equations has caused some numerical difficulties, which requires special attention. The prediction of the skin friction can be improved by this approach via the implicit coupling of non-turbulent and turbulent velocity flelds. Another improvement of the interrmittency model can be further made by allowing the intermittency to vary in the cross-stream direction. This is one step prior to testing any proposal for the transport equation for the intermittency factor. Instead of solving the transport equation for the intermittency factor, the distribution for the intermittency factor is prescribed by Klebanoff's empirical formula [1955]. The skin friction is very well predicted by this new modification, including the overshoot of the profile near the end of the transition zone. The outcome of this study is very encouraging since it indicates that the proper description of the intermittency distribution is the key to the success of the model prediction. This study will be used to guide us on the modelling of the intermittency transport equation.

Huang, George↗
NASA NTRSDate not supplied

Aerodynamic Design Optimization for Natural Laminar Flow Airfoils

Natural laminar flow technology is a passive laminar flow control (LFC) strategy that seeks to delay the onset of boundary-layer transition (BLT) through shape optimization to reduce the drag of the aerodynamic vehicle. Adjoint-based design optimization for LFC is proposed in an integrated multidisciplinary framework, which includes the computational fluid dynamics (CFD), geometry and grid deformation, and linear stability analysis (LSA) for transition prediction. In particular, the BLT location is predicted using the dual N-factor method that is based on a linear stability theory (LST) eigenvalue problem. The dual N-factor criterion accounts for the amplification of planar Tollmien-Schlichting (TS) and stationary crossflow (CF) boundary-layer instabilities to predict the transition location in three-dimensional boundary-layer flows. The adjoint-based shape optimization procedure is based on an iteratively coupled CFD and LSA methodology to converge the transition location and flow solutions, as well as to calculate the sensitivities of the aerodynamic metrics of interest with respect to the flow and shape design parameters. The RAE 2822 airfoil at 0 and 30 degrees yaw angles, an angle of attack of 0.72 degrees, and subsonic conditions (M∞ = 0.19, Rec = 5.6 × 106 ) are used as baseline configurations for design optimization. The angle of attack and the vertical displacement of free-form-deformation control points are used as design variables to reduce the drag coefficient while reaching a specified lift coefficient. The optimized unswept airfoil designs achieve a 30% drag reduction accompanied by a downstream shift of the transition locations over both suction and pressure sides of the airfoil. The initial design iterations for the swept case also show a favorable trend in the drag reduction with transition delay over both sides.

Transition↗