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At least 181 records · Page 10

On the integration of reinforcement learning and approximate reasoning for control

The author discusses the importance of strengthening the knowledge representation characteristic of reinforcement learning techniques using methods such as approximate reasoning. The ARIC (approximate reasoning-based intelligent control) architecture is an example of such a hybrid approach in which the fuzzy control rules are modified (fine-tuned) using reinforcement learning. ARIC also demonstrates that it is possible to start with an approximately correct control knowledge base and learn to refine this knowledge through further experience. On the other hand, techniques such as the TD (temporal difference) algorithm and Q-learning establish stronger theoretical foundations for their use in adaptive control and also in stability analysis of hybrid reinforcement learning and approximate reasoning-based controllers.

Berenji, Hamid R.↗

Semiclassical approximation for electron impact excitation of hydrogenic ions

The threshold behavior of the electron impact excitation cross sections for hydrogenic ions is investigated using the semiclassical approximation with the hyperbolic orbit for the projectile path, rather than the straight line path. The symmetric approximation is applied to modify the ordinary hyperbolic orbit. The modification factor due to the hyperbolic orbit approximation produces the correct energy dependence of the cross section near the excitation threshold. This result is very similar to that of the quantum mechanical case. The semiclassical enhancement factor due to this simple modification corresponds to the Coulomb focusing factor in the Born-Bethe approximation. In the high-energy limit, the semiclassical cross sections approach the Born-Bethe cross sections, with a finite cutoff in the momentum transfer for dipole transitions.

Jung, Young-Dae↗

Improved approximations for dynamic displacements using intermediate response quantities

An approximation for dynamic displacements, which captures the nonlinearities associated with resonance, is presented. This approximation is constructed using approximate intermediate response quantities. When dynamic displacements are constrained using this high quality approximation, frequency constraints are no longer needed to keep the design away from resonance.

Thomas, Harold L.↗

A comparison of approximate interval estimators for the Bernoulli parameter

The goal of this paper is to compare the accuracy of two approximate confidence interval estimators for the Bernoulli parameter p. The approximate confidence intervals are based on the normal and Poisson approximations to the binomial distribution. Charts are given to indicate which approximation is appropriate for certain sample sizes and point estimators.

Leemis, Lawrence↗

Approximate analysis for repeated eigenvalue problems with applications to controls-structure integrated design

A method for eigenvalue and eigenvector approximate analysis for the case of repeated eigenvalues with distinct first derivatives is presented. The approximate analysis method developed involves a reparameterization of the multivariable structural eigenvalue problem in terms of a single positive-valued parameter. The resulting equations yield first-order approximations to changes in the eigenvalues and the eigenvectors associated with the repeated eigenvalue problem. This work also presents a numerical technique that facilitates the definition of an eigenvector derivative for the case of repeated eigenvalues with repeated eigenvalue derivatives (of all orders). Examples are given which demonstrate the application of such equations for sensitivity and approximate analysis. Emphasis is placed on the application of sensitivity analysis to large-scale structural and controls-structures optimization problems.

Kenny, Sean P.↗

Approximate two layer (inviscid/viscous) methods to model aerothermodynamic environments

Approximate inviscid and boundary layer techniques for aerodynamic heating calculations are discussed. An inviscid flowfield solution is needed to provide surface pressures and boundary-layer edge properties. Modified Newtonian pressures coupled with an approximate shock shape will suffice for relatively simple shapes like sphere-cones with cone half-angles between 15 and 45 deg. More accurate approximate methods have been developed which make use of modified Maslen techniques. Slender and large angle sphere-cones and more complex shapes generally require an Euler code, like HALIS, to provide that information. The boundary-layer solution is reduced significantly by using the axisymmetric analog and approximate heating relations developed by Zoby, et al. (1981). Analysis is presented for the calculation of inviscid surface streamlines and metrics. Entropy-layer swallowing effects require coupling the inviscid and boundary-layer solutions.

Dejarnette, Fred R.↗

Finite dimensional approximation of a class of constrained nonlinear optimal control problems

An abstract framework for the analysis and approximation of a class of nonlinear optimal control and optimization problems is constructed. Nonlinearities occur in both the objective functional and in the constraints. The framework includes an abstract nonlinear optimization problem posed on infinite dimensional spaces, and approximate problem posed on finite dimensional spaces, together with a number of hypotheses concerning the two problems. The framework is used to show that optimal solutions exist, to show that Lagrange multipliers may be used to enforce the constraints, to derive an optimality system from which optimal states and controls may be deduced, and to derive existence results and error estimates for solutions of the approximate problem. The abstract framework and the results derived from that framework are then applied to three concrete control or optimization problems and their approximation by finite element methods. The first involves the von Karman plate equations of nonlinear elasticity, the second, the Ginzburg-Landau equations of superconductivity, and the third, the Navier-Stokes equations for incompressible, viscous flows.

Gunzburger, Max D.↗

Approximation Of Multi-Valued Inverse Functions Using Clustering And Sugeno Fuzzy Inference

Finding the inverse of a continuous function can be challenging and computationally expensive when the inverse function is multi-valued. Difficulties may be compounded when the function itself is difficult to evaluate. We show that we can use fuzzy-logic approximators such as Sugeno inference systems to compute the inverse on-line. To do so, a fuzzy clustering algorithm can be used in conjunction with a discriminating function to split the function data into branches for the different values of the forward function. These data sets are then fed into a recursive least-squares learning algorithm that finds the proper coefficients of the Sugeno approximators; each Sugeno approximator finds one value of the inverse function. Discussions about the accuracy of the approximation will be included.

Walden, Maria A.↗

An Approximate Dissipation Function for Large Strain Rubber Thermo-Mechanical Analyses

Mechanically induced viscoelastic dissipation is difficult to compute. When the constitutive model is defined by history integrals, the formula for dissipation is a double convolution integral. Since double convolution integrals are difficult to approximate, coupled thermo-mechanical analyses of highly viscous rubber-like materials cannot be made with most commercial finite element software. In this study, we present a method to approximate the dissipation for history integral constitutive models that represent Maxwell-like materials without approximating the double convolution integral. The method requires that the total stress can be separated into elastic and viscous components, and that the relaxation form of the constitutive law is defined with a Prony series. Numerical data is provided to demonstrate the limitations of this approximate method for determining dissipation. Rubber cylinders with imbedded steel disks and with an imbedded steel ball are dynamically loaded, and the nonuniform heating within the cylinders is computed.

Johnson, Arthur R.↗

Approximating the Helium Wavefunction in Positronium-Helium Scattering

In the Kohn variational treatment of the positronium- hydrogen scattering problem the scattering wave function is approximated by an expansion in some appropriate basis set, but the target and projectile wave functions are known exactly. In the positronium-helium case, however, a difficulty immediately arises in that the wave function of the helium target atom is not known exactly, and there are several ways to deal with the associated eigenvalue in formulating the variational scattering equations to be solved. In this work we will use the Kohn variational principle in the static exchange approximation to d e t e e the zero-energy scattering length for the Ps-He system, using a suite of approximate target functions. The results we obtain will be compared with each other and with corresponding values found by other approximation techniques.

DiRienzi, Joseph↗

The narrow pulse approximation and long length scale determination in xenon gas diffusion NMR studies of model porous media

We report a systematic study of xenon gas diffusion NMR in simple model porous media, random packs of mono-sized glass beads, and focus on three specific areas peculiar to gas-phase diffusion. These topics are: (i) diffusion of spins on the order of the pore dimensions during the application of the diffusion encoding gradient pulses in a PGSE experiment (breakdown of the narrow pulse approximation and imperfect background gradient cancellation), (ii) the ability to derive long length scale structural information, and (iii) effects of finite sample size. We find that the time-dependent diffusion coefficient, D(t), of the imbibed xenon gas at short diffusion times in small beads is significantly affected by the gas pressure. In particular, as expected, we find smaller deviations between measured D(t) and theoretical predictions as the gas pressure is increased, resulting from reduced diffusion during the application of the gradient pulse. The deviations are then completely removed when water D(t) is observed in the same samples. The use of gas also allows us to probe D(t) over a wide range of length scales and observe the long time asymptotic limit which is proportional to the inverse tortuosity of the sample, as well as the diffusion distance where this limit takes effect (approximately 1-1.5 bead diameters). The Pade approximation can be used as a reference for expected xenon D(t) data between the short and the long time limits, allowing us to explore deviations from the expected behavior at intermediate times as a result of finite sample size effects. Finally, the application of the Pade interpolation between the long and the short time asymptotic limits yields a fitted length scale (the Pade length), which is found to be approximately 0.13b for all bead packs, where b is the bead diameter. c. 2002 Elsevier Sciences (USA).

NASA Discipline Life Sciences Technologies↗

A Comparison of Approximation Modeling Techniques: Polynomial Versus Interpolating Models

Two methods of creating approximation models are compared through the calculation of the modeling accuracy on test problems involving one, five, and ten independent variables. Here, the test problems are representative of the modeling challenges typically encountered in realistic engineering optimization problems. The first approximation model is a quadratic polynomial created using the method of least squares. This type of polynomial model has seen considerable use in recent engineering optimization studies due to its computational simplicity and ease of use. However, quadratic polynomial models may be of limited accuracy when the response data to be modeled have multiple local extrema. The second approximation model employs an interpolation scheme known as kriging developed in the fields of spatial statistics and geostatistics. This class of interpolating model has the flexibility to model response data with multiple local extrema. However, this flexibility is obtained at an increase in computational expense and a decrease in ease of use. The intent of this study is to provide an initial exploration of the accuracy and modeling capabilities of these two approximation methods.

Giunta, Anthony A.↗

Engine With Regression and Neural Network Approximators Designed

At the NASA Glenn Research Center, the NASA engine performance program (NEPP, ref. 1) and the design optimization testbed COMETBOARDS (ref. 2) with regression and neural network analysis-approximators have been coupled to obtain a preliminary engine design methodology. The solution to a high-bypass-ratio subsonic waverotor-topped turbofan engine, which is shown in the preceding figure, was obtained by the simulation depicted in the following figure. This engine is made of 16 components mounted on two shafts with 21 flow stations. The engine is designed for a flight envelope with 47 operating points. The design optimization utilized both neural network and regression approximations, along with the cascade strategy (ref. 3). The cascade used three algorithms in sequence: the method of feasible directions, the sequence of unconstrained minimizations technique, and sequential quadratic programming. The normalized optimum thrusts obtained by the three methods are shown in the following figure: the cascade algorithm with regression approximation is represented by a triangle, a circle is shown for the neural network solution, and a solid line indicates original NEPP results. The solutions obtained from both approximate methods lie within one standard deviation of the benchmark solution for each operating point. The simulation improved the maximum thrust by 5 percent. The performance of the linear regression and neural network methods as alternate engine analyzers was found to be satisfactory for the analysis and operation optimization of air-breathing propulsion engines (ref. 4).

Patnaik, Surya N.↗

Can the Equivalent Sphere Model Approximate Organ Doses in Space?

For space radiation protection it is often useful to calculate dose or dose,equivalent in blood forming organs (BFO). It has been customary to use a 5cm equivalent sphere to. simulate the BFO dose. However, many previous studies have concluded that a 5cm sphere gives very different dose values from the exact BFO values. One study [1] . concludes that a 9 cm sphere is a reasonable approximation for BFO'doses in solar particle event environments. In this study we use a deterministic radiation transport [2] to investigate the reason behind these observations and to extend earlier studies. We take different space radiation environments, including seven galactic cosmic ray environments and six large solar particle events, and calculate the dose and dose equivalent in the skin, eyes and BFO using their thickness distribution functions from the CAM (Computerized Anatomical Man) model [3] The organ doses have been evaluated with a water or aluminum shielding of an areal density from 0 to 20 g/sq cm. We then compare with results from the equivalent sphere model and determine in which cases and at what radius parameters the equivalent sphere model is a reasonable approximation. Furthermore, we address why the equivalent sphere model is not a good approximation in some cases. For solar particle events, we find that the radius parameters for the organ dose equivalent increase significantly with the shielding thickness, and the model works marginally for BFO but is unacceptable for the eye or the skin. For galactic cosmic rays environments, the equivalent sphere model with an organ-specific constant radius parameter works well for the BFO dose equivalent, marginally well for the BFO dose and the dose equivalent of the eye or the skin, but is unacceptable for the dose of the eye or the skin. The ranges of the radius parameters are also being investigated, and the BFO radius parameters are found to be significantly, larger than 5 cm in all cases, consistent with the conclusion of an earlier study [I]. The radius parameters for the dose equivalent in GCR environments are approximately between 10 and I I cm for the BFO, 3.7 to 4.8 cm for the eye, and 3.5 to 5.6 cm for the skin; while the radius parameters are between 10 and 13 cm for the BFO dose.

Lin, Zi-Wei↗

The Morphology of Passively Evolving Galaxies at Z approximately 2 from HST/WFC3 Deep Imaging in the Hubble Ultradeep Field

We present near-IR images of six passive galaxies (SSFR< 10(exp -2)/ Gyr) at redshift 1.3 < z < 2.4 with stellar mass M approximately 10(exp 11) solar M, selected from the Great Observatories Origins Deep Survey (GOODS), obtained with the Hubble Space Telescope (HST) and the WFC3/IR camera. These images provide the deepest and highest angular resolution view of the optical rest-frame morphology of such systems to date. We find that the light profile of these galaxies is generally regular and well described by a Sersic model with index typical of today's spheroids. We confirm the existence of compact and massive early-type galaxies at z approximately 2: four out of six galaxies have r(sub e) approximately 1 kpc or less. The images reach limiting surface brightness mu approximates 26.5 mag/square arcsec in the F160W bandpass; yet there is no evidence of a faint halo in the galaxies of our sample, even in their stacked image. We also find very weak "morphological k-correction" in the galaxies between the rest-frame UV (from the ACS z-band), and the rest-frame optical (WFC3 H-band): the visual classification, Sersic indices and physical sizes of these galaxies are independent or only mildly dependent on the wavelength, within the errors. The presence of an active nucleus is suspected in two out of six galaxies (33%), opening the intriguing possibility that a large, presently unaccounted population of AGN is hosted in these galaxies, possibly responsible for the cessation of star formation.

Cassata, P.↗

Application of Approximate Unsteady Aerodynamics for Flutter Analysis

A technique for approximating the modal aerodynamic influence coefficient (AIC) matrices by using basis functions has been developed. A process for using the resulting approximated modal AIC matrix in aeroelastic analysis has also been developed. The method requires the unsteady aerodynamics in frequency domain, and this methodology can be applied to the unsteady subsonic, transonic, and supersonic aerodynamics. The flutter solution can be found by the classic methods, such as rational function approximation, k, p-k, p, root locus et cetera. The unsteady aeroelastic analysis using unsteady subsonic aerodynamic approximation is demonstrated herein. The technique presented is shown to offer consistent flutter speed prediction on an aerostructures test wing (ATW) 2 and a hybrid wing body (HWB) type of vehicle configuration with negligible loss in precision. This method computes AICs that are functions of the changing parameters being studied and are generated within minutes of CPU time instead of hours. These results may have practical application in parametric flutter analyses as well as more efficient multidisciplinary design and optimization studies.

Pak, Chan-gi↗

Application of Approximate Unsteady Aerodynamics for Flutter Analysis

A technique for approximating the modal aerodynamic influence coefficient (AIC) matrices by using basis functions has been developed. A process for using the resulting approximated modal AIC matrix in aeroelastic analysis has also been developed. The method requires the unsteady aerodynamics in frequency domain, and this methodology can be applied to the unsteady subsonic, transonic, and supersonic aerodynamics. The flutter solution can be found by the classic methods, such as rational function approximation, k, p-k, p, root locus et cetera. The unsteady aeroelastic analysis using unsteady subsonic aerodynamic approximation is demonstrated herein. The technique presented is shown to offer consistent flutter speed prediction on an aerostructures test wing (ATW) 2 and a hybrid wing body (HWB) type of vehicle configuration with negligible loss in precision. This method computes AICs that are functions of the changing parameters being studied and are generated within minutes of CPU time instead of hours. These results may have practical application in parametric flutter analyses as well as more efficient multidisciplinary design and optimization studies.

Pak, Chan-gi↗

Basis Function Approximation of Transonic Aerodynamic Influence Coefficient Matrix

A technique for approximating the modal aerodynamic influence coefficients [AIC] matrices by using basis functions has been developed and validated. An application of the resulting approximated modal AIC matrix for a flutter analysis in transonic speed regime has been demonstrated. This methodology can be applied to the unsteady subsonic, transonic and supersonic aerodynamics. The method requires the unsteady aerodynamics in frequency-domain. The flutter solution can be found by the classic methods, such as rational function approximation, k, p-k, p, root-locus et cetera. The unsteady aeroelastic analysis for design optimization using unsteady transonic aerodynamic approximation is being demonstrated using the ZAERO(TradeMark) flutter solver (ZONA Technology Incorporated, Scottsdale, Arizona). The technique presented has been shown to offer consistent flutter speed prediction on an aerostructures test wing [ATW] 2 configuration with negligible loss in precision in transonic speed regime. These results may have practical significance in the analysis of aircraft aeroelastic calculation and could lead to a more efficient design optimization cycle

Li, Wesley Waisang↗