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At least 1,747 records · Page 97

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NASA NTRS1990

Adaptive state estimation for control of flexible structures

This paper proposes a new approach of obtaining adaptive state estimation of a system in the presence of unknown system disturbances and measurement noise. In the beginning, a non-optimal Kalman filter with arbitrary initial guess for the process and measurement noises is implemented. At the same time, an adaptive transversal predictor (ATP) based on the recursive least-squares (RLS) algorithm is used to yield optimal one- to p- step-ahead output predictions using the previous input/output data. Referring to these optimal predictions the Kalman filter gain is updated and the performance of the state estimation is thus improved. If forgetting factor is implemented in the recursive least-squares algorithm, this method is also capable of dealing with the situation when the noise statistics are slowly time-varying. This feature makes this new approach especially suitable for the control of flexible structures. A numerical example demonstrates the feasibility of this real time adaptive state estimation method.

Chen, Chung-Wen↗

NASA NTRS1972

Low-energy electron transport with the method of discrete ordinates

The one-dimensional discrete ordinates code ANISN was adapted to transport low energy (a few MeV) electrons. Calculated results obtained with ANISN were compared with experimental data for transmitted electron energy and angular distribution data for electrons normally incident on aluminum slabs of various thicknesses. The calculated and experimental results are in good agreement for a thin slab (0.2 of the electron range), but not for the thicker slabs (0.6 of the electron range). Calculated results obtained with ANISN were also compared with results obtained using Monte Carlo methods.

Bartine, D. E.↗

DOE OSTI2024

Quantum mechanical model of crossing and anti-crossing points in 3D full-band Monte Carlo simulations

This work presents a 3D quantum mechanics based model to address the physics at band structure crossing/anti-crossing points in full band Monte Carlo (FBMC) simulations. The model solves the Krieger and Iafrate (KI) equations in real time using pre-computed coefficients at k-points spatially sampled within the first Brillouin zone. Solving the KI equations in real time makes this model applicable for all electric fields, which enables its use in FBMC device simulations. In this work, a two-level refinement scheme is used to aggressively sample regions in proximity to band crossings for accurate solutions to the KI equations and coarsely sample everywhere else to limit the number of k-points used. The presented sampling method is demonstrated on the band structure of silicon but is effective for the band structure of any semiconductor material. Next, the adaptation of the fully quantum KI model into the semi-classical FBMC method is discussed. Finally, FBMC simulations of hole transport in 4H silicon carbide with and without the KI model are performed. Results along different crystallographic directions for a wide range of electric fields are compared to previously published simulation and experimental values.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1990

Hydrogen induced fracture characteristics of single crystal nickel-based superalloys

A stereoscopic method for use with x ray energy dispersive spectroscopy of rough surfaces was adapted and applied to the fracture surfaces single crystals of PWA 1480E to permit rapid orientation determinations of small cleavage planes. The method uses a mathematical treatment of stereo pair photomicrographs to measure the angle between the electron beam and the surface normal. One reference crystal orientation corresponding to the electron beam direction (crystal growth direction) is required to perform this trace analysis. The microstructure of PWA 1480E was characterized before fracture analysis was performed. The fracture behavior of single crystals of the PWA 1480E nickel-based superalloy was studied. The hydrogen-induced fracture behavior of single crystals of the PWA 1480E nickel-based superalloy was also studied. In order to understand the temperature dependence of hydrogen-induced embrittlement, notched single crystals with three different crystal growth orientations near zone axes (100), (110), and (111) were tensile tested at 871 C (1600 F) in both helium and hydrogen atmospheres at 34 MPa. Results and conclusions are given.

Chen, Po-Shou↗

NASA NTRS1993

Time-accurate simulation of a self-excited oscillatory supersonic external flow with a multi-block solution-adaptive mesh algorithm

Results are presented of an investigation of the time-accurate simulation of supersonic unsteady flow oscillations over spike-tipped bodies using the multistage Runge-Kutta scheme coupled with a dynamic solution-adaptive grid algorithm modified for multiblock capabilities. The inviscid fluxes are described by a modified advective upwind split method to obviate the need for artificial dissipation. If a time-varying, solution-adaptive mesh algorithm is incorporated, resolution of the details of the unsteady spike-tipped body flow is improved. The adaptive algorithm is also shown to resolve multiple and diverse features of the flow simultaneously, with the adapted regions in the mesh convecting with these features as they translate.

Ingram, Clint L.↗

DOE OSTI2021

A Sparse-Grid Probabilistic Scheme for Approximation of the Runaway Probability of Electrons in Fusion Tokamak Simulation

Runaway electrons (RE) generated during magnetic disruptions present a major threat to the safe operation of plasma nuclear fusion reactors. A critical aspect of understanding RE dynamics is to calculate the runaway probability, i.e., the probability that an electron in the phase space will runaway on, or before, a prescribed time. Such probability can be obtained by solving the adjoint equation of the underlying Fokker-Planck equation that controls the electron dynamics. In this effort, we present a sparse-grid probabilistic scheme for computing the runaway probability. The key ingredient of our approach is to represent the solution of the adjoint equation as a conditional expectation, such that discretizing the differential operator reduces to the approximation of a set of integrals. Adaptive sparse grid interpolation is utilized to approximate the map from the phase space to the runaway probability. The main novelties of this effort are the integration of the sparse-grid method into the probabilistic numerical scheme for computing escape probability, and the application of the proposed method in computing RE probabilities. Two numerical examples are given to illustrate that the proposed method can achieve O(Δt) convergence, and that the local anisotropic adaptive refinement strategy (M. Stoyanov, Adaptive sparse grid construction in a context of local anisotropy and multiple hierarchical parents. In: Sparse Grids and Applications-Miami 2016, Springer, Berlin, 2018, pp. 175–199) can effectively handle the sharp transition layer between the runaway and non-runaway regions.

Yang, Minglei↗

NASA NTRS1989

A recursive technique for adaptive vector quantization

Vector Quantization (VQ) is fast becoming an accepted, if not preferred method for image compression. The VQ performs well when compressing all types of imagery including Video, Electro-Optical (EO), Infrared (IR), Synthetic Aperture Radar (SAR), Multi-Spectral (MS), and digital map data. The only requirement is to change the codebook to switch the compressor from one image sensor to another. There are several approaches for designing codebooks for a vector quantizer. Adaptive Vector Quantization is a procedure that simultaneously designs codebooks as the data is being encoded or quantized. This is done by computing the centroid as a recursive moving average where the centroids move after every vector is encoded. When computing the centroid of a fixed set of vectors the resultant centroid is identical to the previous centroid calculation. This method of centroid calculation can be easily combined with VQ encoding techniques. The defined quantizer changes after every encoded vector by recursively updating the centroid of minimum distance which is the selected by the encoder. Since the quantizer is changing definition or states after every encoded vector, the decoder must now receive updates to the codebook. This is done as side information by multiplexing bits into the compressed source data.

Lindsay, Robert A.↗

DOE OSTI2021

Decentralized Data-Driven Estimation of Generator Rotor Speed and Inertia Constant Based on Adaptive Unscented Kalman Filter

This paper proposes an online decentralized and data-driven method for synchronous generator rotor speed and inertia estimation. First, an analytical relationship between the generator terminal voltage/current phasors and its internal rotor speed is derived using the Thevenin equivalent. The parameters of the latter are obtained via a recursive estimator, which allows us to estimate the generator's internal rotor speed from voltage/current phasors without the need for any generator information. Second, we reformulate the equivalent swing equation into the Kalman filter form, which enables us to use a priori-estimated internal rotor speed along with measured real and reactive power injections to obtain an estimate of the inertia for each online synchronous generator. This is achieved through an adaptive unscented Kalman filter. We demonstrate that the use of terminal bus frequency to approximate the rotor speed for inertia estimation by existing methods leads to large estimation biases/errors. Numerical simulations carried out on the IEEE 39-bus and Texas 2000-bus systems reveal that our proposed method is consistently more accurate than existing methods. Moreover, our proposed method is insensitive to both the type and location of system disturbances, and it is robust to different levels of measurement noise.

bus frequency↗

NASA NTRS1980

An adaptive-control switching buck regulator - Implementation, analysis, and design

Describing-function techniques and averaging methods have been employed to characterize a multiloop switching buck regulator by three functional blocks: power stage, analog signal processor, and pulse modulator. The model is employed to explore possible forms of pole-zero cancellation and the adaptive nature of the control to filter parameter changes. Analysis-based design guidelines are provided including a suggested additional RC-compensation loop to optimize regulator performances such as stability, audiosusceptibility, output impedance, and load transient response.

Lee, F. C.↗

DOE OSTI2021

Controllable Reset Behavior in Domain Wall–Magnetic Tunnel Junction Artificial Neurons for Task-Adaptable Computation

Neuromorphic computing with spintronic devices has been of interest due to the limitations of CMOS-driven von Neumann computing. Domain wall–magnetic tunnel junction (DW-MTJ) devices have been shown to be able to intrinsically capture biological neuron behavior. Edgy-relaxed behavior, where a frequently firing neuron experiences a lower action potential threshold, may provide additional artificial neuronal functionality when executing repeated tasks. In this letter, we demonstrate that this behavior can be implemented in DW-MTJ artificial neurons via three alternative mechanisms: shape anisotropy, magnetic field, and current-driven soft reset. Using micromagnetics and analytical device modeling to classify the Optdigits handwritten digit dataset, we show that edgy-relaxed behavior improves both classification accuracy and classification rate for ordered datasets while sacrificing little to no accuracy for a randomized dataset. This letter establishes methods by which artificial spintronic neurons can be flexibly adapted to datasets.

42 ENGINEERING↗

NASA NTRS2010

Augmented Adaptive Control of a Wind Turbine in the Presence of Structural Modes

Wind turbines operate in highly turbulent environments resulting in aerodynamic loads that can easily excite turbine structural modes, potentially causing component fatigue and failure. Two key technology drivers for turbine manufacturers are increasing turbine up time and reducing maintenance costs. Since the trend in wind turbine design is towards larger, more flexible turbines with lower frequency structural modes, manufacturers will want to develop methods to operate in the presence of these modes. Accurate models of the dynamic characteristics of new wind turbines are often not available due to the complexity and expense of the modeling task, making wind turbines ideally suited to adaptive control. In this paper, we develop theory for adaptive control with rejection of disturbances in the presence of modes that inhibit the controller. We use this method to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine operating in Region 3. The objective of the adaptive pitch controller is to regulate generator speed, accommodate wind gusts, and reduce the interference of certain structural modes in feedback. The control objective is accomplished by collectively pitching the turbine blades. The adaptive pitch controller for Region 3 is compared in simulations with a baseline classical Proportional Integrator (PI) collective pitch controller.

Frost, Susan A.↗

DOE OSTI2024

Diffusion Limit–Preserving Lumped DFEMs on AMR Meshes

Here, we present sweep-compatible, novel upwinding recipes for the bilinear discontinuous (BLD) finite element method (FEM) that allows lumped BLD to be used on adaptive mesh refinement (AMR) meshes for thick transport applications without adding additional degrees of freedom at hanging nodes that exist on refinement boundaries. We analyze the properties of the upwinding and lumping that are needed for BLD to get the thick diffusion limit on such meshes, present results demonstrating locking with the wrong recipe, and present results showing error convergence and robustness properties for two diffusive problems on a variety of AMR meshes.

42 ENGINEERING↗

NASA NTRS1986

Computational solid mechanics (finite elements and boundary elements) - Present status and future directions

Computational finite-element and boundary-element methods are reviewed, and their application to the mechanics of solids is discussed. Stability conditions for general FEMs are considered in addition to the use of least-order, stable, invariant, or hybrid/mixed isoparametric elements as alternatives to the displacement-based isoparametric elements. The use of symbolic manipulation, adaptive mesh refinement, transient dynamic response, and boundary-element methods for linear elaslticity and finite-strain problems of inelastic materials are also discussed.

Atluri, S. N.↗

NASA NTRS1989

Experience with some repeat tests on the 9 inch chord CAST-10-2/DOA 2 airfoil model in the Langley 0.3-m TCT adaptive wall test section

A co-operative testing program is in progress between the Langley Research Center (NASA) and the National Aeronautical Establishment (NAE, Canada) to validate two different techniques of airfoil testing at transonic speeds. The procedure employed is to test the same airfoil model in the NAE two-dimensional tunnel and the Langley 0.3-m Transonic Cryogenic Tunnel (0.3-m TCT). The airfoil model used in testing was CAST-10-2/DOA-2 super-critical airfoil. The Langley 0.3-m TCT has a relatively small cross section of 13 in x 13 in, giving a (h/c) ratio of 1.44 for the same 9 in chord model. The approach employed in the 0.3-m TCT aims towards eliminating the wall effects by using active walls. The top and bottom walls are flexible. By changing the wall shapes during a test in an iterative manner, the wall interference effects are reduced. The method employed to change the wall shapes is the adaptive wall technique. The current test program provided an opportunity to validate the adaptive wall technique in the 0.3-m TCT. The relatively long chord airfoil represents a severe test case to test the efficacy of the adaptive wall technique under cryogenic conditions. The program also involved removal of side wall boundary-layer thus increasing the complexity of the wall adaptation technique. This paper deals with some salient results obtained regarding repeatability of test data and possible residual interference effects.

Murthy, A. V.↗

DOE OSTI2026

pyFLANK, a graph neural network based null distribution inference model for F ST outlier detection

Detecting genomic regions under selection is essential for understanding how populations adapt to different environments, yet it remains challenging due to the confounding effects of demographic history and linkage disequilibrium (LD). Fixation index (F ST ) is a widely used statistic to identify genomic regions under adaptation. However, identifying genes under selection by defining F ST outliers often remains challenging, owing to confounding effects of underlying demographic history. Traditional methods assume independence among loci and rely on simple demographic models, while newer models perform much better but are computationally expensive and not easily scalable. Here, we present pyFLANK, an open-source and automated Python implementation which detects F ST outliers using a null distribution inferred from quasi-independent loci. Our tool integrates three approaches to identify loci obeying a null distribution: graph neural network (GNN) inference, linkage disequilibrium (LD)-based inference, and user-defined input. Because pyFLANK uses GNN-based inference of quasi-independent loci, it yields a more accurate null model with less need for user parameter input. In simulation experiments, pyFLANK achieved lower false positive rates than current methods while maintaining comparable detection power, indicating that its refined null model better distinguishes true adaptive loci from background variation. The GNN-based model, in particular, detected additional loci associated with phenotypic variance that were not identified by existing methods. Assessments of simulation and real data from different species demonstrate that pyFLANK achieves lower false positive rates compared with other commonly used F ST outlier detectors, while maintaining comparable detection power and excellent computational performance, providing a robust and user-friendly tool for identifying loci under divergent selection. It extends existing F ST outlier frameworks by incorporating explicit LD-aware strategies for null model calibration. The method is intended as a practical and scalable complement to existing genome scan approaches.

FST↗

NASA NTRS1986

Iterative adaption of the bidimensional wall of the French T2 wind tunnel around a C5 axisymmetrical model: Infinite variation of the Mach number at zero incidence and a test at increased incidence

The top and bottom two-dimensional walls of the T2 wind tunnel are adapted through an iterative process. The adaptation calculation takes into account the flow three-dimensionally. This method makes it possible to start with any shape of walls. The tests were performed with a C5 axisymmetric model at ambient temperature. Comparisons are made with the results of a true three-dimensional adaptation.

Archambaud, J. P.↗

NASA NTRS1990

The application of the triple probe method to MPD thruster plumes

The triple probe method is an attractive technique for measuring axial and radial profiles of electron temperature T(e) and electron number density n(e) in magnetoplasmadynamic (MPD) thruster plumes. In this paper the performance and applicability of the triple probe to MPD thruster plumes is evaluated by identifying sources of error, correction methods, and error estimation techniques. Included in the analysis is an adaptation of Laframboise's exact calculations to the triple probe, aligned with the flow vector, and a preliminary investigation of the effect of flow transverse to the probe axis. In MPD thrusters, the triple probe method can provide measurement accuracy of T(e) wintin about 10 percent and n(e) within about 60 percent.

Kelly, Arnold J.↗

DOE OSTI2022

Smoothed aggregation for difficult stretched mesh and coefficient variation problems

Abstract Four adaptations of the smoothed aggregation algebraic multigrid (SA‐AMG) method are proposed with an eye toward improving the convergence and robustness of the solver in situations when the discretization matrix contains many weak connections. These weak connections can cause higher than expected levels of fill‐in within the coarse discretization matrices and can also give rise to suboptimal smoothing within the prolongator smoothing phase. These smoothing drawbacks are due to the relatively small size of some diagonal entries within the filtered matrix that one obtains after dropping the weak connections. The new algorithms consider modifications to the Jacobi‐like step that defines the prolongator smoother, modifications to the filtered matrix, and also direct modifications to the resulting grid transfer operators. Numerical results are given illustrating the potential benefits of the proposed adaptations.

Hu, Jonathan J.↗