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At least 181 records · Page 10

Inlet Development for a Rocket Based Combined Cycle, Single Stage to Orbit Vehicle Using Computational Fluid Dynamics

Design and analysis of the inlet for a rocket based combined cycle engine is discussed. Computational fluid dynamics was used in both the design and subsequent analysis. Reynolds averaged Navier-Stokes simulations were performed using both perfect gas and real gas assumptions. An inlet design that operates over the required Mach number range from 0 to 12 was produced. Performance data for cycle analysis was post processed using a stream thrust averaging technique. A detailed performance database for cycle analysis is presented. The effect ot vehicle forebody compression on air capture is also examined.

DeBonis, J. R.↗

Textbook Multigrid Efficiency for Computational Fluid Dynamics Simulations

Considerable progress over the past thirty years has been made in the development of large-scale computational fluid dynamics (CFD) solvers for the Euler and Navier-Stokes equations. Computations are used routinely to design the cruise shapes of transport aircraft through complex-geometry simulations involving the solution of 25-100 million equations; in this arena the number of wind-tunnel tests for a new design has been substantially reduced. However, simulations of the entire flight envelope of the vehicle, including maximum lift, buffet onset, flutter, and control effectiveness have not been as successful in eliminating the reliance on wind-tunnel testing. These simulations involve unsteady flows with more separation and stronger shock waves than at cruise. The main reasons limiting further inroads of CFD into the design process are: (1) the reliability of turbulence models; and (2) the time and expense of the numerical simulation. Because of the prohibitive resolution requirements of direct simulations at high Reynolds numbers, transition and turbulence modeling is expected to remain an issue for the near term. The focus of this paper addresses the latter problem by attempting to attain optimal efficiencies in solving the governing equations. Typically current CFD codes based on the use of multigrid acceleration techniques and multistage Runge-Kutta time-stepping schemes are able to converge lift and drag values for cruise configurations within approximately 1000 residual evaluations. An optimally convergent method is defined as having textbook multigrid efficiency (TME), meaning the solutions to the governing system of equations are attained in a computational work which is a small (less than 10) multiple of the operation count in the discretized system of equations (residual equations). In this paper, a distributed relaxation approach to achieving TME for Reynolds-averaged Navier-Stokes (RNAS) equations are discussed along with the foundations that form the basis of this approach. Because the governing equations are a set of coupled nonlinear conservation equations with discontinuities (shocks, slip lines, etc.) and singularities (flow- or grid-induced), the difficulties are many. This paper summarizes recent progress towards the attainment of TME in basic CFD simulations.

Brandt, Achi↗

Airborne Shaped Sonic Boom Demonstration Pressure Measurements with Computational Fluid Dynamics Comparisons

The Shaped Sonic Boom Demonstration project showed for the first time that by careful design of aircraft contour the resultant sonic boom can maintain a tailored shape, propagating through a real atmosphere down to ground level. In order to assess the propagation characteristics of the shaped sonic boom and to validate computational fluid dynamics codes, airborne measurements were taken of the pressure signatures in the near field by probing with an instrumented F-15B aircraft, and in the far field by overflying an instrumented L-23 sailplane. This paper describes each aircraft and their instrumentation systems, the airdata calibration, analysis of the near- and far-field airborne data, and shows the good to excellent agreement between computational fluid dynamics solutions and flight data. The flights of the Shaped Sonic Boom Demonstration aircraft occurred in two phases. Instrumentation problems were encountered during the first phase, and corrections and improvements were made to the instrumentation system for the second phase, which are documented in the paper. Piloting technique and observations are also given. These airborne measurements of the Shaped Sonic Boom Demonstration aircraft are a unique and important database that will be used to validate design tools for a new generation of quiet supersonic aircraft.

Haering, Edward A., Jr.↗

Aerodynamic design optimization using sensitivity analysis and computational fluid dynamics

A new and efficient method is presented for aerodynamic design optimization, which is based on a computational fluid dynamics (CFD)-sensitivity analysis algorithm. The method is applied to design a scramjet-afterbody configuration for an optimized axial thrust. The Euler equations are solved for the inviscid analysis of the flow, which in turn provides the objective function and the constraints. The CFD analysis is then coupled with the optimization procedure that uses a constrained minimization method. The sensitivity coefficients, i.e. gradients of the objective function and the constraints, needed for the optimization are obtained using a quasi-analytical method rather than the traditional brute force method of finite difference approximations. During the one-dimensional search of the optimization procedure, an approximate flow analysis (predicted flow) based on a first-order Taylor series expansion is used to reduce the computational cost. Finally, the sensitivity of the optimum objective function to various design parameters, which are kept constant during the optimization, is computed to predict new optimum solutions. The flow analysis of the demonstrative example are compared with the experimental data. It is shown that the method is more efficient than the traditional methods.

Baysal, Oktay↗

Flight, Wind-Tunnel, and Computational Fluid Dynamics Comparison for Cranked Arrow Wing (F-16XL-1) at Subsonic and Transonic Speeds

Geometrical, flight, computational fluid dynamics (CFD), and wind-tunnel studies for the F-16XL-1 airplane are summarized over a wide range of test conditions. Details are as follows: (1) For geometry, the upper surface of the airplane and the numerical surface description compare reasonably well. (2) For flight, CFD, and wind-tunnel surface pressures, the comparisons are generally good at low angles of attack at both subsonic and transonic speeds, however, local differences are present. In addition, the shock location at transonic speeds from wind-tunnel pressure contours is near the aileron hinge line and generally is in correlative agreement with flight results. (3) For boundary layers, flight profiles were predicted reasonably well for attached flow and underneath the primary vortex but not for the secondary vortex. Flight data indicate the presence of an interaction of the secondary vortex system and the boundary layer and the boundary-layer measurements show the secondary vortex located more outboard than predicted. (4) Predicted and measured skin friction distributions showed qualitative agreement for a two vortex system. (5) Web-based data-extraction and computational-graphical tools have proven useful in expediting the preceding comparisons. (6) Data fusion has produced insightful results for a variety of visualization-based data sets.

John E Lamar↗

A Transported Livengood–Wu Integral Model for Knock Prediction in Computational Fluid Dynamics Simulation

This work describes the development of a transported Livengood–Wu (L–W) integral model for computational fluid dynamics (CFD) simulation to predict autoignition and engine knock tendency. The currently employed L–W integral model considers both single-stage and two-stage ignition processes, thus can be generally applied to different fuels such as paraffin, olefin, aromatics, and alcohol. The model implementation is first validated in simulations of homogeneous charge compression ignition (HCCI) combustion for three different fuels, showing good accuracy in prediction of autoignition timing for fuels with either single-stage or two-stage ignition characteristics. Then, the L–W integral model is coupled with G-equation model to indicate end-gas autoignition and knock tendency in CFD simulations of a direct-injection spark-ignition engine. This modeling approach is about 10 times more efficient than the ones that based on detailed chemistry calculation and pressure oscillation analysis. Two fuels with same Research Octane Number (RON) but different octane sensitivity are studied, namely, Co-Optima alkylate and Co-Optima E30. Feed-forward neural network model in conjunction with multivariable minimization technique is used to generate fuel surrogates with targets of matched RON, octane sensitivity, and ethanol content. The CFD model is validated against experimental data in terms of pressure traces and heat release rate for both fuels under a wide range of operating conditions. The knock tendency—indicated by the fuel energy contained in the autoignited region—of the two fuels at different load conditions correlates well with the experimental results and the fuel octane sensitivity, implying the current knock modeling approach can capture the octane sensitivity effect and can be applied to further investigation on composition of octane sensitivity.

33 ADVANCED PROPULSION SYSTEMS↗

A compendium of computational fluid dynamics at the Langley Research Center

Through numerous summary examples, the scope and general nature of the computational fluid dynamics (CFD) effort at Langley is identified. These summaries will help inform researchers in CFD and line management at Langley of the overall effort. In addition to the inhouse efforts, out of house CFD work supported by Langley through industrial contracts and university grants are included. Researchers were encouraged to include summaries of work in preliminary and tentative states of development as well as current research approaching definitive results.

Source record↗

Computational Fluid Dynamics (CFD) Simulation of Hypersonic Turbine-Based Combined-Cycle (TBCC) Inlet Mode Transition

Methods of computational fluid dynamics were applied to simulate the aerodynamics within the turbine flowpath of a turbine-based combined-cycle propulsion system during inlet mode transition at Mach 4. Inlet mode transition involved the rotation of a splitter cowl to close the turbine flowpath to allow the full operation of a parallel dual-mode ramjet/scramjet flowpath. Steady-state simulations were performed at splitter cowl positions of 0deg, -2deg, -4deg, and -5.7deg, at which the turbine flowpath was closed half way. The simulations satisfied one objective of providing a greater understanding of the flow during inlet mode transition. Comparisons of the simulation results with wind-tunnel test data addressed another objective of assessing the applicability of the simulation methods for simulating inlet mode transition. The simulations showed that inlet mode transition could occur in a stable manner and that accurate modeling of the interactions among the shock waves, boundary layers, and porous bleed regions was critical for evaluating the inlet static and total pressures, bleed flow rates, and bleed plenum pressures. The simulations compared well with some of the wind-tunnel data, but uncertainties in both the windtunnel data and simulations prevented a formal evaluation of the accuracy of the simulation methods.

Slater, John W.↗

Towards a generalized computational fluid dynamics technique for all Mach numbers

Currently there exists no single unified approach for efficiently and accurately solving computational fluid dynamics (CFD) problems across the Mach number regime, from truly low speed incompressible flows to hypersonic speeds. There are several CFD codes that have evolved into sophisticated prediction tools with a wide variety of features including multiblock capabilities, generalized chemistry and thermodynamics models among other features. However, as these codes evolve, the demand placed on the end user also increases simply because of the myriad of features that are incorporated into these codes. In order for a user to be able to solve a wide range of problems, several codes may be needed requiring the user to be familiar with the intricacies of each code and their rather complicated input files. Moreover, the cost of training users and maintaining several codes becomes prohibitive. The objective of the current work is to extend the compressible, characteristic-based, thermochemical nonequilibrium Navier-Stokes code GASP to very low speed flows and simultaneously improve convergence at all speeds. Before this work began, the practical speed range of GASP was Mach numbers on the order of 0.1 and higher. In addition, a number of new techniques have been developed for more accurate physical and numerical modeling. The primary focus has been on the development of optimal preconditioning techniques for the Euler and the Navier-Stokes equations with general finite-rate chemistry models and both equilibrium and nonequilibrium thermodynamics models. We began with the work of Van Leer, Lee, and Roe for inviscid, one-dimensional perfect gases and extended their approach to include three-dimensional reacting flows. The basic steps required to accomplish this task were a transformation to stream-aligned coordinates, the formulation of the preconditioning matrix, incorporation into both explicit and implicit temporal integration schemes, and modification of the numerical flux formulae. In addition, we improved the convergence rate of the implicit time integration schemes in GASP through the use of inner iteration strategies and the use of the GMRES (General Minimized Resisual) which belongs to the class of algorithms referred to as Krylov subspace iteration. Finally, we significantly improved the practical utility of GASP through the addition of mesh sequencing, a technique in which computations begin on a coarse grid and get interpolated onto successively finer grids. The fluid dynamic problems of interest to the propulsion community involve complex flow physics spanning different velocity regimes and possibly involving chemical reactions. This class of problems results in widely disparate time scales causing numerical stiffness. Even in the absence of chemical reactions, eigenvalue stiffness manifests itself at transonic and very low speed flows which can be quantified by the large condition number of the system and evidenced by slow convergence rates. This results in the need for thorough numerical analysis and subsequent implementation of sophisticated numerical techniques for these difficult yet practical problems. As a result of this work, we have been able to extend the range of applicability of compressible codes to very low speed inviscid flows (M = .001) and reacting flows.

Walters, R. W.↗

Application of an automated machine learning-genetic algorithm (AutoML-GA) coupled with computational fluid dynamics simulations for rapid engine design optimization

In recent years, the use of machine learning-based surrogate models for computational fluid dynamics (CFD) simulations has emerged as a promising technique for reducing the computational cost associated with engine design optimization. However, such methods still suffer from drawbacks. One main disadvantage is that the default machine learning (ML) hyperparameters are often severely suboptimal for a given problem. This has often been addressed by manually trying out different hyperparameter settings, but this solution is ineffective in case of a high-dimensional hyperparameter space. Besides this problem, the amount of data needed for training is also not known a priori. In response to these issues that need to be addressed, the present work describes and validates an automated active learning approach, AutoML-GA, for surrogate-based optimization of internal combustion engines. In this approach, a Bayesian optimization technique is used to find the best machine learning hyperparameters based on an initial dataset obtained from a small number of CFD simulations. Subsequently, a genetic algorithm is employed to locate the design optimum on the ML surrogate surface. In the vicinity of the design optimum, the solution is refined by repeatedly running CFD simulations at the projected optima and adding the newly obtained data to the training dataset. It is demonstrated that AutoML-GA leads to a better optimum with a lower number of CFD simulations, compared to the use of default hyperparameters. The proposed framework offers the advantage of being a more hands-off approach that can be readily utilized by researchers and engineers in industry who do not have extensive machine learning expertise.

Owoyele, Opeoluwa↗

A computational fluid dynamics algorithm on a massively parallel computer

The implementation and performance of a finite-difference algorithm for the compressible Navier-Stokes equations in two or three dimensions on the Connection Machine are described. This machine is a single-instruction multiple-data machine with up to 65536 physical processors. The implicit portion of the algorithm is of particular interest. Running times and megadrop rates are given for two- and three-dimensional problems. Included are comparisons with the standard codes on a Cray X-MP/48.

Jespersen, Dennis C.↗

Influence of computational fluid dynamics on experimental aerospace facilities: A fifteen year projection

An assessment was made of the impact of developments in computational fluid dynamics (CFD) on the traditional role of aerospace ground test facilities over the next fifteen years. With improvements in CFD and more powerful scientific computers projected over this period it is expected to have the capability to compute the flow over a complete aircraft at a unit cost three orders of magnitude lower than presently possible. Over the same period improvements in ground test facilities will progress by application of computational techniques including CFD to data acquisition, facility operational efficiency, and simulation of the light envelope; however, no dramatic change in unit cost is expected as greater efficiency will be countered by higher energy and labor costs.

Source record↗

A survey of grid generation techniques in computational fluid dynamics

The use of numerically-generated body-conforming coordinate systems has become well-established in computational fluid dynamics, allowing general codes to be written which can treat boundaries of arbitrary shape. There is now a rapidly increasing interest in the dynamic coupling of the grid with the physical solution so that the grid lines continually move to achieve concentration in regions of strong variation of the physical solution and alignment with shocks, flame fronts, etc. Such adaptive coordinate systems have been developed using a variety of techniques for sensing and reacting to the developing regions of concentration and/or alignment. This paper reviews the techniques and applications of these dynamically adaptive systems and other systems.

Thompson, J. F.↗

Computational fluid dynamics of airfoils and wings

It is pointed out that transonic flow is one of the fields where computational fluid dynamics turns out to be most effective. Codes for the design and analysis of supercritical airfoils and wings have become standard tools of the aircraft industry. The present investigation is concerned with mathematical models and theorems which account for some of the progress that has been made. The most successful aerodynamics codes are those for the analysis of flow at off-design conditions where weak shock waves appear. A major breakthrough was achieved by Murman and Cole (1971), who conceived of a retarded difference scheme which incorporates artificial viscosity to capture shocks in the supersonic zone. This concept has been used to develop codes for the analysis of transonic flow past a swept wing. Attention is given to the trailing edge and the boundary layer, entropy inequalities and wave drag, shockless airfoils, and the inverse swept wing code.

Garabedian, P.↗

Current capabilities and future directions in computational fluid dynamics

A summary of significant findings is given, followed by specific recommendations for future directions of emphasis for computational fluid dynamics development. The discussion is organized into three application areas: external aerodynamics, hypersonics, and propulsion - and followed by a turbulence modeling synopsis.

Source record↗

Research on Computational Fluid Dynamics and Turbulence

Preconditioning matrices for Chebyshev derivative operators in several space dimensions; the Jacobi matrix technique in computational fluid dynamics; and Chebyshev techniques for periodic problems are discussed.

Source record↗

An evaluation of three two-dimensional computational fluid dynamics codes including low Reynolds numbers and transonic Mach numbers

Full-potential, Euler, and Navier-Stokes computational fluid dynamics (CFD) codes were evaluated for use in analyzing the flow field about airfoils sections operating at Mach numbers from 0.20 to 0.60 and Reynolds numbers from 500,000 to 2,000,000. The potential code (LBAUER) includes weakly coupled integral boundary layer equations for laminar and turbulent flow with simple transition and separation models. The Navier-Stokes code (ARC2D) uses the thin-layer formulation of the Reynolds-averaged equations with an algebraic turbulence model. The Euler code (ISES) includes strongly coupled integral boundary layer equations and advanced transition and separation calculations with the capability to model laminar separation bubbles and limited zones of turbulent separation. The best experiment/CFD correlation was obtained with the Euler code because its boundary layer equations model the physics of the flow better than the other two codes. An unusual reversal of boundary layer separation with increasing angle of attack, following initial shock formation on the upper surface of the airfoil, was found in the experiment data. This phenomenon was not predicted by the CFD codes evaluated.

Hicks, Raymond M.↗