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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Transfer function verification and block diagram simplification of a very high-order distributed pole closed-loop servo by means of non-linear time-response simulation

Linear frequency domain methods are inadequate in analyzing the 1975 Viking Orbiter (VO75) digital tape recorder servo due to dominant nonlinear effects such as servo signal limiting, unidirectional servo control, and static/dynamic Coulomb friction. The frequency loop (speed control) servo of the VO75 tape recorder is used to illustrate the analytical tools and methodology of system redundancy elimination and high order transfer function verification. The paper compares time-domain performance parameters derived from a series of nonlinear time responses with the available experimental data in order to select the best possible analytical transfer function representation of the tape transport (mechanical segment of the tape recorder) from several possible candidates. The study also shows how an analytical time-response simulation taking into account most system nonlinearities can pinpoint system redundancy and overdesign stemming from a strictly empirical design approach. System order reduction is achieved through truncation of individual transfer functions and elimination of redundant blocks.

Mukhopadhyay, A. K.↗
NASA NTRS1990

Fighter agility metrics, research, and test

Proposed new metrics to assess fighter aircraft agility are collected and analyzed. A framework for classification of these new agility metrics is developed and applied. A completed set of transient agility metrics is evaluated with a high fidelity, nonlinear F-18 simulation provided by the NASA Dryden Flight Research Center. Test techniques and data reduction methods are proposed. A method of providing cuing information to the pilot during flight test is discussed. The sensitivity of longitudinal and lateral agility metrics to deviations from the pilot cues is studied in detail. The metrics are shown to be largely insensitive to reasonable deviations from the nominal test pilot commands. Instrumentation required to quantify agility via flight test is also considered. With one exception, each of the proposed new metrics may be measured with instrumentation currently available. Simulation documentation and user instructions are provided in an appendix.

Liefer, Randall K.↗
NASA NTRS2001

Effect of Under-Resolved Grids on High Order Methods

There has been much discussion on verification and validation processes for establishing the credibility of CFD simulations. Since the early 1990s, many of the aeronautical and mechanical engineering related reference journals mandated that any accepted articles in numerical simulations (without known solutions to compared with) need to perform a minimum of one level of grid refinement and time step reduction. Due to the difficulty in analysis, the effect of under-resolved grids and the nonlinear behavior of available spatial discretizations, are scarcely discussed in the literature. Here, an under-resolved numerical simulation is one where the grid spacing being used is too coarse to resolve the smallest physically relevant scales of the chosen continuum governing equations that are of interest to the numerical modeler. With the advent of new developments in fourth-order or higher spatial schemes, it has become common to regard high order schemes as more accurate, reliable and require less grid points. The danger comes when one tries to perform computations with the coarsest grid possible while still hoping to maintain numerical results sufficiently accurate for complex flows, and especially, data-limited problems. On one hand, high order methods when applies to highly coupled multidimensional complex nonlinear problems might have different stability, convergence and reliability behavior than their well studied low order counterparts, especially for nonlinear schemes such as TVD, MUSCL with limiters, ENO, WENO and discrete Galerkin. On the other hand, high order methods involve more operation counts and systematic grid convergence study can be time consuming and prohibitively expansive. At the same time it is difficult to fully understand or categorize the different nonlinear behavior of finite discretizations, especially at the limits of under-resolution when different types of bifurcation phenomena might occur, depending on the combination of grid spacings, time steps, initial conditions and numerical treatments of boundary conditions.

Yee, H. C.↗
NASA NTRS1985

Reduction method for thermal analysis of complex aerospace structures

A reduction method which combines classical Rayleigh-Ritz modal superposition techniques with contemporary finite-element methods is applied to transient nonlinear thermal analysis of aerospace structures. The essence of the method is the use of a few thermal modes from eigenvalue analyses as basis vectors to represent the temperature response in the structure. The method is used to obtain approximate temperature histories for a portion of the Shuttle orbiter wing subject to reentry heating and for a large space antenna reflector subject to heating associated with a low Earth orbit. The reduction method has excellent potential for significant size reduction for radiation-dominated problems such as the antenna reflector. However, for conduction-dominated problems such as the Shuttle wing, especially those with complex spatial and temporal variations in the applied heating, additional work appears necessary to find alternate sources of basis vectors which will permit significant problem size reductions.

Shore, C. P.↗
NASA NTRS1985

Interaction of finite-amplitude sound with air-filled porous materials

The propagation of high intensity sound waves through an air-filled porus material was studied. The material is assumed: (1) to be rigid, incompressible, and homogeneous, and (2) to be adequately described by two properties: resistivity r and porosity. The resulting wave equation is still nonlinear, however, because of the u sgn(u) term in the resistivity. The equation is solved in the frequency domain as an infinite set of coupled inhomogeneous Helmholtz equations, one for each harmonic. An approximate but analytical solution leads to predictions of excess attenuation, saturation, and phase speed reduction for the fundamental component. A more general numerical solution is used to calculate the propagation curves for the higher harmonics. The u sgn(u) nonlinearity produces a cubic distortion pattern; when the input signal is a pure tone, only odd harmonic distortion products are generated.

Nelson, D. A.↗
NASA NTRS2016

Active Control of Solar Array Dynamics During Spacecraft Maneuvers

Recent NASA mission plans require spacecraft to undergo potentially significant maneuvers (or dynamic loading events) with large solar arrays deployed. Therefore there is an increased need to understand and possibly control the nonlinear dynamics in the spacecraft system during such maneuvers. The development of a nonlinear controller is described. The utility of using a nonlinear controller to reduce forces and motion in a solar array wing during a loading event is demonstrated. The result is dramatic reductions in system forces and motion during a 10 second loading event. A motion curve derived from the simulation with the closed loop controller is used to obtain similar benefits with a simpler motion control approach.

nonlinear controls↗
DOE OSTI2025

Heterogeneous Mixtures of Dictionary Functions to Approximate Subspace Invariance in Koopman Operators: Why Deep Koopman Operators Work

Abstract Koopman operators model nonlinear dynamics as a linear dynamic system acting on a nonlinear function as the state. This nonstandard state is often called a Koopman observable and is usually approximated numerically by a superposition of functions drawn from a dictionary . In a widely used algorithm, extended dynamic mode decomposition (EDMD), the dictionary functions are drawn from a fixed class of functions. Deep learning combined with EDMD has been used to learn novel dictionary functions in an algorithm called deep dynamic mode decomposition (deepDMD). The learned representation both (1) accurately models and (2) scales well with the dimension of the original nonlinear system. In this paper, we analyze the learned dictionaries from deepDMD and explore the theoretical basis for their strong performance. We explore State-Inclusive Logistic Lifting (SILL) dictionary functions to approximate Koopman observables. Error analysis of these dictionary functions show they satisfy a property of subspace approximation, which we define as uniform finite approximate closure. Typically, a Koopman dictionary’s nonlinear functions are homogeneous. In this paper, we discover that structured mixing of heterogeneous dictionary functions drawn from different classes of nonlinear functions achieve the same accuracy and dimensional scaling as the deep-learning-based deepDMD algorithm Yeung et al. ( In: 2019 American Control Conference (ACC), 2019). We specifically show this by building a heterogeneous dictionary comprised of SILL functions and conjunctive radial basis functions (RBFs). This mixed dictionary achieves similar accuracy and dimensional scaling to deepDMD with an order of magnitude reduction in parameters, while maintaining geometric interpretability. These results strengthen the viability of dictionary-based Koopman models to solving high-dimensional nonlinear learning problems.

Johnson, Charles A.↗
NASA NTRS1995

An approximate Kalman filter for ocean data assimilation: An example with an idealized Gulf Stream model

A practical method of data assimilation for use with large, nonlinear, ocean general circulation models is explored. A Kalman filter based on approximation of the state error covariance matrix is presented, employing a reduction of the effective model dimension, the error's asymptotic steady state limit, and a time-invariant linearization of the dynamic model for the error integration. The approximations lead to dramatic computational savings in applying estimation theory to large complex systems. We examine the utility of the approximate filter in assimilating different measurement types using a twin experiment of an idealized Gulf Stream. A nonlinear primitive equation model of an unstable east-west jet is studied with a state dimension exceeding 170,000 elements. Assimilation of various pseudomeasurements are examined, including velocity, density, and volume transport at localized arrays and realistic distributions of satellite altimetry and acoustic tomography observations. Results are compared in terms of their effects on the accuracies of the estimation. The approximate filter is shown to outperform an empirical nudging scheme used in a previous study. The examples demonstrate that useful approximate estimation errors can be computed in a practical manner for general circulation models.

Fukumori, Ichiro↗
DOE OSTI2020

On differentiable local bounds preserving stabilization for Euler equations

This work presents the design of nonlinear stabilization techniques for the finite element discretization of Euler equations in both steady and transient form. Implicit time integration is used in the case of the transient form. A differentiable local bounds preserving method has been developed, which combines a Rusanov artificial diffusion operator and a differentiable shock detector. Nonlinear stabilization schemes are usually stiff and highly nonlinear. This issue is mitigated by the differentiability properties of the proposed method. Moreover, in order to further improve the nonlinear convergence, we also propose a continuation method for a subset of the stabilization parameters. The resulting method has been successfully applied to steady and transient problems with complex shock patterns. Numerical experiments show that it is able to provide sharp and well resolved shocks. Furthermore, the importance of the differentiability is assessed by comparing the new scheme with its non-differentiable counterpart. Numerical experiments suggest that, for up to moderate nonlinear tolerances, the method exhibits improved robustness and nonlinear convergence behavior for steady problems. Additionally, in the case of transient problem, we also observe a reduction in the computational cost.

42 ENGINEERING↗
DOE OSTI2025

Plasmonic Ag nanocomposite phosphate glasses produced via γ-ray irradiation as reduction route

This paper reports on the impact of γ-ray irradiation (10, 100 kGy) on melt-quenched Ag + -doped phosphate glass and the effects of subsequent thermal processing leading to the production of plasmonic Ag nanocomposites. The γ-irradiated glasses were characterized alongside the pristine by differential scanning calorimetry (DSC), Raman spectroscopy, electron paramagnetic resonance (EPR) spectroscopy, optical absorption, and photoluminescence (PL) spectroscopy. DSC characterization showed consistent glass transition temperatures (T g ) before and after γ-irradiation whereas the crystallization temperatures tended to decrease with increasing γ-ray dose. However, a lack of alteration of the glass network structure was supported by Raman spectroscopy. Room temperature EPR spectra clearly showed the formation of phosphorus oxygen hole center (POHC) defects in the undoped host, in addition to another doublet likely associated with a P 3 defect. The presence of paramagnetic silver species encompassing Ag 2+ and 107/109 Ag 0 atoms was also indicated in the silver-activated glass together with POHC defects. Optical absorption spectra were also consistent with the presence of various radiation-induced centers. Further analyzing the glass absorption edge via Tauc plots suggested the formation of electron center (EC) defects in γ-irradiated samples wherein the silver-doped glass exhibited decreasing band gap energies with increasing γ-ray dose. The PL characterization showed the silver-related radio-PL effect was induced exhibiting broad band emission with two maxima around 500 and 625 nm stemming from various molecular Ag$^{x+}_{n}$ clusters. Emission decay analyses revealed that the longer wavelength emission exhibited slower decay. The highest radiation dose of 100 kGy however resulted in weaker emission and faster decay kinetics attributed to energy transfer between the luminescent silver species and POHC defects. Finally subjecting the γ-irradiated Ag-doped glasses to heat treatment near the T g at 490 °C led to the development of the surface plasmon resonance of Ag nanoparticles (NPs) and the vanishing of the Ag$^{x+}_{n}$ clusters luminescence. In conclusion, the presence of the matrix-related EC defects was deemed accountable for the thermally induced reduction and consequent precipitation of Ag NPs making the plasmonic glasses attractive for photonic applications such as nonlinear optics.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Chiral Anomaly in Interacting Condensed Matter Systems

The chiral anomaly is a fundamental quantum mechanical phenomenon which is of great importance to both particle physics and condensed matter physics alike. In the context of QED, it manifests as the breaking of chiral symmetry in the presence of electromagnetic fields. It is also known that anomalous chiral symmetry breaking can occur through interactions alone, as is the case for interacting one-dimensional systems. In this Letter, we investigate the interplay between these two modes of anomalous chiral symmetry breaking in the context of interacting Weyl semimetals. Using Fujikawa’s path integral method, we show that the chiral charge continuity equation is modified by the presence of interactions which can be viewed as including the effect of the electric and magnetic fields generated by the interacting quantum matter. This can be understood further using dimensional reduction and a Luttinger liquid description of the lowest Landau level. These effects manifest themselves in the nonlinear response of the system. In particular, we find an interaction-dependent density response due to a change in the magnetic field as well as a contribution to the nonequilibrium and inhomogeneous anomalous Hall response while preserving its equilibrium value.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1993

Arcjet space thrusters

Electrically powered arc jets which produce thrust at high specific impulse could provide a substantial cost reduction for orbital transfer and station keeping missions. There is currently a limited understanding of the complex, nonlinear interactions in the plasma propellant which has hindered the development of high efficiency arc jet thrusters by making it difficult to predict the effect of design changes and to interpret experimental results. A computational model developed at the University of Tennessee Space Institute (UTSI) to study laser powered thrusters and radio frequency gas heaters has been adapted to provide a tool to help understand the physical processes in arc jet thrusters. The approach is to include in the model those physical and chemical processes which appear to be important, and then to evaluate our judgement by the comparison of numerical simulations with experimental data. The results of this study have been presented at four technical conferences. The details of the work accomplished in this project are covered in the individual papers included in the appendix of this report. We present a brief description of the model covering its most important features followed by a summary of the effort.

Keefer, Dennis↗
NASA NTRS1994

An Approximate Kalman Filter for Ocean Data Assimilation; An Example with an Idealized Gulf Stream Model

A practical method of data assimilation for use with large, nonlinear, ocean general circulation models is explored. A Kalman filter based on approximations of the state error covariance matrix is presented, employing a reduction of the effective model dimension, the error's asymptotic steady-state limit, and a time-invariant linearization of the dynamic model for the error integration. The approximations lead to dramatic computational savings in applying estimation theory to large complex systems. We examine the utility of the approximate filter in assimilating different measurement types using a twin experiment of an idealized Gulf Stream. A nonlinear primitive equation model of an unstable east-west jet is studied with a state dimension exceeding 170,000 elements. Assimilation of various pseudo measurements is examined, including velocity, density, and volume transport at localized arrays, and realistic distributions of satellite altimetry and acoustic tomography observations. Results are compared in terms of their effects on the accuracies of the estimation. The approximate filter is shown to outperform a previous study that used an empirical nudging scheme. The examples demonstrate that useful approximate estimation errors can be computed in a practical manner for general circulation models.

['Kalman↗
NASA NTRS2014

Nonlinear Finite Element Analysis of a Composite Non-Cylindrical Pressurized Aircraft Fuselage Structure

The Environmentally Responsible Aviation Project aims to develop aircraft technologies enabling significant fuel burn and community noise reductions. Small incremental changes to the conventional metallic alloy-based 'tube and wing' configuration are not sufficient to achieve the desired metrics. One of the airframe concepts that might dramatically improve aircraft performance is a composite-based hybrid wing body configuration. Such a concept, however, presents inherent challenges stemming from, among other factors, the necessity to transfer wing loads through the entire center fuselage section which accommodates a pressurized cabin confined by flat or nearly flat panels. This paper discusses a nonlinear finite element analysis of a large-scale test article being developed to demonstrate that the Pultruded Rod Stitched Efficient Unitized Structure concept can meet these challenging demands of the next generation airframes. There are specific reasons why geometrically nonlinear analysis may be warranted for the hybrid wing body flat panel structure. In general, for sufficiently high internal pressure and/or mechanical loading, energy related to the in-plane strain may become significant relative to the bending strain energy, particularly in thin-walled areas such as the minimum gage skin extensively used in the structure under analysis. To account for this effect, a geometrically nonlinear strain-displacement relationship is needed to properly couple large out-of-plane and in-plane deformations. Depending on the loading, this nonlinear coupling mechanism manifests itself in a distinct manner in compression- and tension-dominated sections of the structure. Under significant compression, nonlinear analysis is needed to accurately predict loss of stability and postbuckled deformation. Under significant tension, the nonlinear effects account for suppression of the out-of-plane deformation due to in-plane stretching. By comparing the present results with the previously published preliminary linear analysis, it is demonstrated in the present paper that neglecting nonlinear effects for the structure and loads of interest can lead to appreciable loss in analysis fidelity.

Przekop, Adam↗
DOE OSTI2020

Sampling Low-Dimensional Markovian Dynamics for Preasymptotically Recovering Reduced Models from Data with Operator Inference

This work introduces a method for learning low-dimensional models from data of high-dimensional black-box dynamical systems. The novelty is that the learned models are exactly the reduced models that are traditionally constructed with classical projection-based model reduction techniques. Thus, the proposed approach learns models that are guaranteed to have the well-studied properties of reduced models known from model reduction, without requiring full knowledge of the governing equations and without requiring the operators of the high-dimensional systems. The key ingredient is a new data sampling scheme to obtain re-projected trajectories of high-dimensional systems that correspond to Markovian dynamics in low-dimensional subspaces. The exact recovery of reduced models from these re-projected trajectories is guaranteed pre-asymptotically under certain conditions for finite amounts of data and for a large class of systems with polynomial nonlinear terms. Numerical results demonstrate that the low-dimensional models learned with the proposed approach match reduced models from traditional model reduction up to numerical errors in practice. In conclusion, the numerical results further indicate that low-dimensional models fitted to re-projected trajectories are predictive even in situations where models fitted to trajectories without re-projection are inaccurate and unstable.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Plasma self-driven current in tokamaks with magnetic islands

Magnetic island perturbations may cause a reduction in plasma self-driven current that is needed for tokamak operation. A novel effect on tokamak self-driven current revealed by global gyrokinetic simulations is due to magnetic-island-induced 3D electric potential structures, which have the same dominant mode numbers as that of the magnetic island, whereas centered at both the inner and outer edge of the island. The non-resonant potential islands are shown to drive a current through an efficient nonlinear parallel acceleration of electrons. In large aspect ratio (large-A) tokamak devices, this new effect can result in a significant global reduction of the electron bootstrap current when the island size is sufficiently large, in addition to the local current loss across the island region due to the pressure profile flattening. It is shown that there exists a critical magnetic island width for large-A tokamaks beyond which the electron bootstrap current loss is global and increases rapidly with the island size. As such, this process may introduce a size limit for tolerable magnetic islands in large-A tokamak devices in the context of steady state operation. On the other hand, the current loss caused by magnetic islands in low-A tokamaks such as spherical tokamak (ST) NSTX/U is minor. The reduction of the axisymmetric current by magnetic islands scales with the square of island width. However, the loss of the current is mainly local to the island region, and the pace of current loss as the island size increases is substantially slower compared to large-A tokamaks. In particular, the bootstrap current reduction in STs is even smaller in the reactor-relevant high-β p regime where neoclassical tearing modes are more likely to develop.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems

We explore using neural operators, or neural network representations of nonlinear maps between function spaces, to accelerate infinite-dimensional Bayesian inverse problems (BIPs) with models governed by nonlinear parametric partial differential equations (PDEs). Neural operators have gained significant attention in recent years for their ability to approximate the parameter-to-solution maps defined by PDEs using as training data solutions of PDEs at a limited number of parameter samples. The computational cost of BIPs can be drastically reduced if the large number of PDE solves required for posterior characterization are replaced with evaluations of trained neural operators. However, reducing error in the resulting BIP solutions via reducing the approximation error of the neural operators in training can be challenging and unreliable. We provide an a priori error bound result that implies certain BIPs can be ill-conditioned to the approximation error of neural operators, thus leading to inaccessible accuracy requirements in training. To reliably deploy neural operators in BIPs, we consider a strategy for enhancing the performance of neural operators: correcting the prediction of a trained neural operator by solving a linear variational problem based on the PDE residual. We show that a trained neural operator with error correction can achieve a quadratic reduction of its approximation error, all while retaining substantial computational speedups of posterior sampling when models are governed by highly nonlinear PDEs. The strategy is applied to two numerical examples of BIPs based on a nonlinear reaction–diffusion problem and deformation of hyperelastic materials. We demonstrate that posterior representations of the two BIPs produced using trained neural operators are greatly and consistently enhanced by error correction.

97 MATHEMATICS AND COMPUTING↗