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At least 505 records · Page 28

Nonlinear simulation of a flexible aircraft in maneuvering flight

A mathematical model integrating nonlinear rigid-body flight mechanics and linear aeroelastic dynamics is examined; the equations of motion for an elastic aircraft in accelerated flight are developed using Lagrangian mechanics. This approach is used to construct a simulation model of an F/A-18 (configured with tip missiles) which includes angular/elastic inertial coupling (IC). In general, the elastic modes significantly affected by IC were aerodynamically decoupled from the rest of the model. The affected modes were those which induced changes in total aircraft mass distribution. The elastic effect is noticeable if deformation-induced mass distribution changes are significant with respect to modal mass and modal frequencies. A modal parameter is presented which characterizes the level of IC between elastic momentum and rigid-body angular momentum.

Buttrill, Carey S.↗

Adaptive Filtering Using Recurrent Neural Networks

A method for adaptive (or, optionally, nonadaptive) filtering has been developed for estimating the states of complex process systems (e.g., chemical plants, factories, or manufacturing processes at some level of abstraction) from time series of measurements of system inputs and outputs. The method is based partly on the fundamental principles of the Kalman filter and partly on the use of recurrent neural networks. The standard Kalman filter involves an assumption of linearity of the mathematical model used to describe a process system. The extended Kalman filter accommodates a nonlinear process model but still requires linearization about the state estimate. Both the standard and extended Kalman filters involve the often unrealistic assumption that process and measurement noise are zero-mean, Gaussian, and white. In contrast, the present method does not involve any assumptions of linearity of process models or of the nature of process noise; on the contrary, few (if any) assumptions are made about process models, noise models, or the parameters of such models. In this regard, the method can be characterized as one of nonlinear, nonparametric filtering. The method exploits the unique ability of neural networks to approximate nonlinear functions. In a given case, the process model is limited mainly by limitations of the approximation ability of the neural networks chosen for that case. Moreover, despite the lack of assumptions regarding process noise, the method yields minimum- variance filters. In that they do not require statistical models of noise, the neural- network-based state filters of this method are comparable to conventional nonlinear least-squares estimators.

Parlos, Alexander G.↗

Simulations of Turbulent Momentum and Scalar Transport in Confined Swirling Coaxial Jets

This paper presents the numerical simulations of confined three dimensional coaxial water jets. The objectives are to validate the newly proposed nonlinear turbulence models of momentum and scalar transport, and to evaluate the newly introduced scalar APDF and DWFDF equation along with its Eulerian implementation in the National Combustion Code (NCC). Simulations conducted include the steady RANS, the unsteady RANS (URANS), and the time-filtered Navier-Stokes (TFNS) with and without invoking the APDF or DWFDF equation. When the APDF or DWFDF equation is invoked, the simulations are of a hybrid nature, i.e., the transport equations of energy and species are replaced by the APDF or DWFDF equation. Results of simulations are compared with the available experimental data. Some positive impacts of the nonlinear turbulence models and the Eulerian scalar APDF and DWFDF approach are observed.

Shih, Tsan-Hsing↗

Linear and nonlinear interpretation of CV-580 lightning data

Numerical models developed for the study of lightning strike data acquired by in-flight aircraft are applied to the data measured on the CV-580. The basic technique used is the three dimensional time domain finite difference solution of Maxwell's equations. Both linear and nonlinear models are used in the analysis. In the linear model, the lightning channel and the aircraft are assumed to form a linear time invariant system. A transfer function technique can then be used to study the response of the aircraft to a given lightning strike current. Conversely, the lightning current can be inferred from the measured response. In the nonlinear model, the conductivity of air in the vicinity of the aircraft is calculated and incorporated into the solution of the Maxwell's equations. The nonlinear model thus simulates corona formation and air breakdown. Results obtained from the models are in reasonable agreement with the measured data. This study provides another validation of the models and increases confidence that the models may be used to predict aircraft response to any general lightning strike.

Ng, Poh H.↗

Simulations of Turbulent Momentum and Scalar Transport in Non-Reacting Confined Swirling Coaxial Jets

This paper presents the numerical simulations of confined three-dimensional coaxial water jets. The objectives are to validate the newly proposed nonlinear turbulence models of momentum and scalar transport, and to evaluate the newly introduced scalar APDF and DWFDF equation along with its Eulerian implementation in the National Combustion Code (NCC). Simulations conducted include the steady RANS, the unsteady RANS (URANS), and the time-filtered Navier-Stokes (TFNS); both without and with invoking the APDF or DWFDF equation. When the APDF (ensemble averaged probability density function) or DWFDF (density weighted filtered density function) equation is invoked, the simulations are of a hybrid nature, i.e., the transport equations of energy and species are replaced by the APDF or DWFDF equation. Results of simulations are compared with the available experimental data. Some positive impacts of the nonlinear turbulence models and the Eulerian scalar APDF and DWFDF approach are observed.

combustors↗

Time domain flutter analysis of cascades using a full-potential solver

A time domain approach is used to determine the dynamic aeroelastic stability of a cascade of blades. The structural model for each blade is a typical section with two degrees of freedom. The aerodynamic model is the unsteady, two-dimensional, full-potential flow through the cascade of airfoils. The unsteady equations of motion for the structure and the fluid are integrated simultaneously in time starting with the steady flowfield and a small initial disturbance applied to the airfoils. The motion of each blade is analyzed to determine the aeroelastic stability of the cascade. The effect of interblade phase angle is included in the analysis by allowing each blade to have an independent motion and considering a number of blade passages. Calculations are made using an airfoil section and structural parameters that are representative of a propfan. The results are compared with those from a separate frequency domain analysis. Good agreement between the results is observed. With the time domain approach, it is possible to consider nonlinear structural models and nonlinear force-displacement relations. The method allows a realistic simulation of the motion of the fluid and the cascade blades for a better physical understanding and it also has the potential for saving computational time when compared to the frequency domain approach for the flutter analysis of cascades.

Bakhle, Milind A.↗

A three-dimensional time-dependent model of the plasmasphere

A three-dimensional, time-dependent, nonlinear, hydrodynamic model of the plasmasphere has been developed which includes the self-consistent coupling of conjugate hemispheres within the plasmasphere as well as the effects of cross-L drifts due to convection electric fields. The inner region of the plasmasphere was modeled from an L of 1.5 to an L of 3.5 to 4.5, depending on local time. In this first study of the global plasmasphere, the model was run for solar minimum conditions until diurnally reproducible results were obtained, indicating that the plasmasphere was fully filled. The results of the model were then compared with applicable measurements of the plasmasphere. It was found that the model tends to overestimate densities somewhat, although it is within a factor of 2 of an average of June and December whistler observations. The model predicts densities within a factor of 2 of most of the satellite observations as well. As anticipated, the diurnal variation of the plasmasphere was found to depend on magnetic latitude. At low latitudes the diurnal variation in density was relatively small, with the largest densities occurring in the afternoon time sector. However, near the plasmapause, the effects of changes in volume of drifting tubes of plasma due to cross-L drifts led to a factor of 3 variation in equatorial density, with the highest densities occurring near local midnight where the volume was lowest. Various limitations of the current model and suggested improvements are also discussed.

Rasmussen, C. E.↗

A robust model predictive control algorithm for uncertain nonlinear systems that guarantees resolvability

A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees resolvability. With resolvability, initial feasibility of the finite-horizon optimal control problem implies future feasibility in a receding-horizon framework. The control consists of two components; (i) feed-forward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives and derivatives in polytopes. An illustrative numerical example is also provided.

feed - forward↗

A non-Gaussian statistical model for surface elevation of nonlinear random wave fields

Probability density function of the surface elevation of a nonlinear random wave field is obtained. The wave model is based on the Stokes expansion carried to the third order for both deep water waves and waves in finite depth. The amplitude and phase of the first-order component of the Stokes wave are assumed to be Rayleigh and uniformly distributed and slowly varying, respectively. The probability density function for the deep water case was found to depend on two parameters: the root-mean-square surface elevation and the significant slope. For water of finite depth, an additional parameter, the nondimensional depth, is also required. An important difference between the present result and the Gram-Charlier representation is that the present probability density functions are always nonnegative. It is also found that the 'constant' term in the Stokes expansion, usually neglected in deterministic studies, plays an important role in determining the details of the density function. The results compare well with laboratory and field experiment data.

Huang, N. E.↗

Theory of wing rock

Wing rock is one type of lateral-directional instabilities at high angles of attack. To predict wing rock characteristics and to design airplanes to avoid wing rock, parameters affecting wing rock characteristics must be known. A new nonlinear aerodynamic model is developed to investigate the main aerodynamic nonlinearities causing wing rock. In the present theory, the Beecham-Titchener asymptotic method is used to derive expressions for the limit-cycle amplitude and frequency of wing rock from nonlinear flight dynamics equations. The resulting expressions are capable of explaining the existence of wing rock for all types of aircraft. Wing rock is developed by negative or weakly positive roll damping, and sustained by nonlinear aerodynamic roll damping. Good agreement between theoretical and experimental results is obtained.

Hsu, C.-H.↗

Evaluation and applicability of transfinite element formulations with particular reference to radiation

The evaluation and applicability of hybrid transfinite element formulations are described for transient nonlinear thermal models with particular reference to account for radiation effects. The formulations are developed from basic concepts and evaluated for both one- and two-dimensional thermal models. The methodology presented is a hybrid approach as it combines finite elements, classical Galerkin schemes, and transform methods. Basic features of the hybrid formulations and the associated solution scheme used are first described. Therein, numerical test models are presented to evaluate the applicability for predicting the nonlinear transient response in one- and two-dimensional thermal models influenced due to radiation effects.

Tamma, Kumar K.↗

Improvement of structural models using covariance analysis and nonlinear generalized least squares

The next generation of large, flexible space structures will be too light to support their own weight, requiring a system of structural supports for ground testing. The authors have proposed multiple boundary-condition testing (MBCT), using more than one support condition to reduce uncertainties associated with the supports. MBCT would revise the mass and stiffness matrix, analytically qualifying the structure for operation in space. The same procedure is applicable to other common test conditions, such as empty/loaded tanks and subsystem/system level tests. This paper examines three techniques for constructing the covariance matrix required by nonlinear generalized least squares (NGLS) to update structural models based on modal test data. The methods range from a complicated approach used to generate the simulation data (i.e., the correct answer) to a diagonal matrix based on only two constants. The results show that NGLS is very insensitive to assumptions about the covariance matrix, suggesting that a workable NGLS procedure is possible. The examples also indicate that the multiple boundary condition procedure more accurately reduces errors than individual boundary condition tests alone.

Glaser, R. J.↗

Numerical model for the weakly nonlinear propagation of sound through turbulence

When finite amplitude (or intense) sound, such as a sonic boom, propagates through a turbulent atmosphere, the propagation is strongly affected by the turbulence. The interaction between sound and turbulence has mostly been studied as a linear phenomenon, i.e., the nonlinear behavior of the intense sound has been neglected. It has been shown that turbulence has an effect on the perceived loudness of sonic booms, mainly by changing its peak pressure and rise time. Peak pressure and rise time are important factors that determine the loudness of the sonic boom when heard outdoors. However, the interaction between turbulence and nonlinear effects has mostly not been included in propagation studies of sonic booms. It is therefore important to investigate the influence of acoustical nonlinearity on the interaction of intense sound with turbulence.

Lipkens, Bart↗

Development of a Low-Reynolds Number, Nonlinear kappa-epsilon Model for the Reduced Navier-Stokes Equations

Previous work at NASA LeRC has shown that flow distortions in aircraft engine inlet ducts can be significantly reduced by mounting vortex generators, or small wing sections, on the inside surface of the engine inlet. The placement of the vortex generators is an important factor in obtaining the optimal effect over a wide operating envelope. In this regard, the only alternative to a long and expensive test program which would search out this optimal configuration is a good prediction procedure which could narrow the field of search. Such a procedure has been developed in collaboration with NASA LeRC, and results obtained by NASA personnel indicate that it shows considerable promise for predicting the viscous turbulent flow in engine inlet ducts in the presence of vortex generators. The prediction tool is a computer code which numerically solves the reduced Navier-Stokes equations and so is commonly referred to as RNS3D. Obvious deficiencies in RNS3D have been addressed in previous work. Primarily, it is known that the predictions of the mean velocity field of a turbulent boundary layer flow approaching separation are not in good agreement with data. It was suggested that the use of an algebraic mixing-length turbulence model in RNS3D is at least partly to blame for this. Additionally, the current turbulence model includes an assumption of isotropy which will ultimately fail to capture turbulence-driven secondary flow known to exist in noncircular ducts.

Boger, David A.↗