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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

VpROM: a novel variational autoencoder-boosted reduced order model for the treatment of parametric dependencies in nonlinear systems

Reduced Order Models (ROMs) are of considerable importance in many areas of engineering in which computational time presents difficulties. Established approaches employ projection-based reduction, such as Proper Orthogonal Decomposition. The limitation of the linear nature of such operators is typically tackled via a library of local reduction subspaces, which requires the assembly of numerous local ROMs to address parametric dependencies. Our work attempts to define a more generalisable mapping between parametric inputs and reduced bases for the purpose of generative modeling. We propose the use of Variational Autoencoders (VAEs) in place of the typically utilised clustering or interpolation operations, for inferring the fundamental vectors, termed as modes, which approximate the manifold of the model response for any and each parametric input state. The derived ROM still relies on projection bases, built on the basis of full-order model simulations, thus retaining the imprinted physical connotation. However, it additionally exploits a matrix of coefficients that relates each local sample response and dynamics to the global phenomena across the parametric input domain. The VAE scheme is utilised for approximating these coefficients for any input state. This coupling leads to a high-precision low-order representation, which is particularly suited for problems where model dependencies or excitation traits cause the dynamic behavior to span multiple response regimes. Moreover, the probabilistic treatment of the VAE representation allows for uncertainty quantification on the reduction bases, which may then be propagated to the ROM response. The performance of the proposed approach is validated on an open-source simulation benchmark featuring hysteresis and multi-parametric dependencies, and on a large-scale wind turbine tower characterised by nonlinear material behavior and model uncertainty.

Conditional VAEs↗
NASA NTRS2012

Efficient Global Aerodynamic Modeling from Flight Data

A method for identifying global aerodynamic models from flight data in an efficient manner is explained and demonstrated. A novel experiment design technique was used to obtain dynamic flight data over a range of flight conditions with a single flight maneuver. Multivariate polynomials and polynomial splines were used with orthogonalization techniques and statistical modeling metrics to synthesize global nonlinear aerodynamic models directly and completely from flight data alone. Simulation data and flight data from a subscale twin-engine jet transport aircraft were used to demonstrate the techniques. Results showed that global multivariate nonlinear aerodynamic dependencies could be accurately identified using flight data from a single maneuver. Flight-derived global aerodynamic model structures, model parameter estimates, and associated uncertainties were provided for all six nondimensional force and moment coefficients for the test aircraft. These models were combined with a propulsion model identified from engine ground test data to produce a high-fidelity nonlinear flight simulation very efficiently. Prediction testing using a multi-axis maneuver showed that the identified global model accurately predicted aircraft responses.

Morelli, Eugene A.↗
NASA NTRS2011

User Selection Criteria of Airspace Designs in Flexible Airspace Management

A method for identifying global aerodynamic models from flight data in an efficient manner is explained and demonstrated. A novel experiment design technique was used to obtain dynamic flight data over a range of flight conditions with a single flight maneuver. Multivariate polynomials and polynomial splines were used with orthogonalization techniques and statistical modeling metrics to synthesize global nonlinear aerodynamic models directly and completely from flight data alone. Simulation data and flight data from a subscale twin-engine jet transport aircraft were used to demonstrate the techniques. Results showed that global multivariate nonlinear aerodynamic dependencies could be accurately identified using flight data from a single maneuver. Flight-derived global aerodynamic model structures, model parameter estimates, and associated uncertainties were provided for all six nondimensional force and moment coefficients for the test aircraft. These models were combined with a propulsion model identified from engine ground test data to produce a high-fidelity nonlinear flight simulation very efficiently. Prediction testing using a multi-axis maneuver showed that the identified global model accurately predicted aircraft responses.

Lee, Hwasoo E.↗
DOE OSTI2021

Nonlinear two-fluid modeling of plasma response to RMPs for the ELM control in the ITER baseline

Numerical modeling, combining the toroidal ideal MHD code GPEC and the nonlinear two-fluid MHD code TM1, was used for comprehensive studies of the plasma response to resonant magnetic perturbations (RMPs) with toroidal mode number n = 1–5 for controlling edge-localized modes (ELMs) in ITER for the standard operation scenario (15 MA Q = 10). Several issues related to RMP ELM control are investigated, including the optimization of the RMP coils configuration, the evaluation of the magnitude of density pump-out and the q95 windows of ELM suppression. GPEC calculates the magnetic response, which consistently includes the very important edge kink/peeling response to static magnetic perturbations. Furthermore, GPEC two-dimensional scans of the relative coil current phasing among the three rows of internal coils, at fixed coil current amplitude, reveal the optimal phasing for the RMP coil configuration with n = 1–5, respectively. The poloidal half wavelength of resonant mode at the edge of plasma calculated by GPEC indicates that the midplane row coils have the best resonant coupling with the plasma for n = 2, while the upper and lower row coils have the best resonant coupling with the plasma for n = 3. Based on the plasma kinetic equilibrium and the GPEC calculations of the magnetic response, TM1 was used to simulate the conditions for RMP field penetration in the ITER pedestal. TM1 shows magnetic island formation at the foot of ITER pedestal with RMP coil current threshold ranging from 4 kAt to 8 kAt with n = 2 to 4. These magnetic islands at the pedestal-foot lead to density pump-out, the magnitude of which scales as ${I}_{\text{RMP}}^{0.5}$ and ranges from 5% to 20% at the pedestal-top when scanning the coil current from 4 to 60 kAt. The density pump-out is found to be weaker for higher n RMP. The nonlinear TM1 simulations also show field penetration at the pedestal-top, where the threshold of RMP coil current depends on the q 95 . The alignment of the magnetic island and the location of the pedestal-top decreases the height and width of the pedestal to suppress ELMs. Simulations by two-dimensional scans of RMP coil current and q 95 reveal the accessible q 95 windows of ELM suppression for both n = 3 and 4 RMPs. The predicted q 95 windows of ELM suppression are very similar to the ones in currently operating tokamaks and the required RMP coil current for ELM suppression is less than 40–50 kAt, which is well within the designed capability for ITER. In addition, the simulations indicate that wide q 95 windows of ELM suppression may be accessible in ITER by operating with dominant n = 4 (or n = 5) RMPs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1988

Time-dependent models of radiatively driven stellar winds. I - Nonlinear evolution of instabilities for a pure absorption model

Numerical radiation-hydrodynamics simulations of the nonlinear evolution of instabilities in radiatively driven stellar winds have been performed. The results show a strong tendency for the unstable flow to form rather sharp rarefactions in which the highest speed material has very low density. The qualitative features of the model agree well with the reqirements of displaced narrow absorption components in UV lines.

Owocki, Stanley P.↗
NASA NTRS1996

Assimilation of Geosat Altimetric Data in a Nonlinear Shallow-Water Model of the Indian Ocean by Adjoint Approach. Part II: Some Validation and Interpretation of the Assimilated Results: Some Validation and Interpretation of the Assimilated Results - Part 2

This paper examines the results of assimilating Geosat sea level variations relative to the November 1986-November 1988 mean reference, in a nonlinear reduced-gravity model of the Indian Ocean, Data have been assimilated during one year starting in November 1986 with the objective of optimizing the initial conditions and the yearly averaged reference surface. The thermocline slope simulated by the model with or without assimilation is validated by comparison with the signal, which can be derived from expandable bathythermograph measurements performed in the Indian Ocean at that time. The topography simulated with assimilation on November 1986 is in very good agreement with the hydrographic data. The slopes corresponding to the South Equatorial Current and to the South Equatorial Countercurrent are better reproduced with assimilation than without during the first nine months. The whole circulation of the cyclonic gyre south of the equator is then strongly intensified by assimilation. Another assimilation experiment is run over the following year starting in November 1987. The difference between the two yearly mean surfaces simulated with assimilation is in excellent agreement with Geosat. In the southeastern Indian Ocean, the correction to the yearly mean dynamic topography due to assimilation over the second year is negatively correlated to the one the year before. This correction is also in agreement with hydrographic data. It is likely that the signal corrected by assimilation is not only due to wind error, because simulations driven by various wind forcings present the same features over the two years. Model simulations run with a prescribed throughflow transport anomaly indicate that assimilation is rather correcting in the interior of the model domain for inadequate boundary conditions with the Pacific.

Greiner, Eric↗
DOE OSTI2023

Modeling the Yaw Behavior of Tail Fins for Small Wind Turbines: November 22, 2021 - May 21, 2024

This report describes the aerodynamic modelling of the yaw behavior of tail fins for small wind turbines (SWTs). The analysis is based on unsteady slender body theory (USBT) and is formulated to be used with the proposed tail fin module to be added to OpenFAST. Linearized USBT, which has been applied in the past to SWT tail fins, is developed in three main ways. First, USBT is extended to high yaw angles and aspect ratios by modelling the associated nonlinear vortex dynamics and the chordwise load distribution respectively. Second, we consider the effect of time-varying wind speed. The extended theory is compared to recent unpublished measurements at the University of Perugia, Italy, for the yaw behavior of delta, elliptical, and rectangular tail fins without a rotor and nacelle. The fins were released from initial yaw angles of -40 degrees and -80 degrees ; the latter is of sufficient magnitude to show the importance of the nonlinear yaw dynamics. Further, the friction in the model tail fin bearings was measured and modelled. The constants in the aerodynamic models were taken from the literature but significant improvement in accuracy is achieved by using system identification techniques to optimize the values. This leads to the third main finding: extended USBT is accurate for all generic tail fin shapes that we considered and is, therefore, very suitable for inclusion in aeroelastic codes for SWTs. The final development is of a general nonlinear equation for yaw response that is simpler than the extended USBT and is also suitable for inclusion in OpenFAST. The two nonlinear models are used to highlight the geometric requirements for good tail fin design.

distributed wind↗
NASA NTRSDate not supplied

Estimation of Permanent Magnet Synchronous Motor Parameters using a Linear Unknown Input Interval Observer

This paper develops and evaluate a technique to estimate the speed and unknown load torque of a permanent magnet synchronous motor (PMSM). An interval unknown input observer (UIO) for linear time-invariant (LTI) systems is designed and utilized to estimate the PMSM parameters. Interval UIOs are advantageous as they allow for the estimation of both states and unknown inputs, while accounting for varying uncertainty sources, such as model and measurement uncertainties inherent in dynamic systems and processes. First, the nonlinear PMSM model is linearized to transform it to a suitable form for application of the linear interval UIO. Then, the interval UIO is applied to jointly estimate the motor speed and the unknown load torque disturbance. Assuming that the measurement noise and disturbances are bounded, lower and upper bounds are first computed for the unmeasured state (motor speed) and then for the unknown input (load torque). The proposed approach and its limitations are demonstrated for the nonlinear PMSM model derived from its equivalent electrical circuit.

Elinirina I Robinson↗
NASA NTRS1986

Variable structure control of nonlinear systems through simplified uncertain models

A variable structure control approach is presented for the robust stabilization of feedback equivalent nonlinear systems whose proposed model lies in the same structural orbit of a linear system in Brunovsky's canonical form. An attempt to linearize exactly the nonlinear plant on the basis of the feedback control law derived for the available model results in a nonlinearly perturbed canonical system for the expanded class of possible equivalent control functions. Conservatism tends to grow as modeling errors become larger. In order to preserve the internal controllability structure of the plant, it is proposed that model simplification be carried out on the open-loop-transformed system. As an example, a controller is developed for a single link manipulator with an elastic joint.

Sira-Ramirez, Hebertt↗
NASA NTRS1990

Nonlinear response of unidirectional boron/aluminum

Experimental results obtained for unidirectional boron/aluminum subjected to combined loading using off-axis tension, compression and Iosipescu shear specimens are correlated with a nonlinear micromechanics model. It is illustrated that the nonlinear response in the principal material directions is markedly influenced by the different loading modes and different ratios of the applied stress components. The observed nonlinear response under pure and combined loading is discussed in terms of initial yielding, subsequent hardening, stress-interaction effects and unloading-reloading characteristics. The micromechanics model is based on the concept of a repeating unit cell representative of the composite-at-large and employs the unified theory of Bodner and Partom to model the inelastic response of the matrix. It is shown that the employed micromechanics model is sufficiently general to predict the observed nonlinear response of unidirectional boron/aluminum with good accuracy.

Pindera, M.-J.↗
NASA NTRS2003

Unified Models of Turbulence and Nonlinear Wave Evolution in the Extended Solar Corona and Solar Wind

The PI (Cranmer) and Co-I (A. van Ballegooijen) made significant progress toward the goal of building a "unified model" of the dominant physical processes responsible for the acceleration of the solar wind. The approach outlined in the original proposal comprised two complementary pieces: (1) to further investigate individual physical processes under realistic coronal and solar wind conditions, and (2) to extract the dominant physical effects from simulations and apply them to a one-dimensional and time-independent model of plasma heating and acceleration. The accomplishments in the report period are thus divided into these two categories: 1a. Focused Study of Kinetic MHD Turbulence. We have developed a model of magnetohydrodynamic (MHD) turbulence in the extended solar corona that contains the effects of collisionless dissipation and anisotropic particle heating. A turbulent cascade is one possible way of generating small-scale fluctuations (easy to dissipate/heat) from a pre-existing population of low-frequency Alfven waves (difficult to dissipate/heat). We modeled the cascade as a combination of advection and diffusion in wavenumber space. The dominant spectral transfer occurs in the direction perpendicular to the background magnetic field. As expected from earlier models, this leads to a highly anisotropic fluctuation spectrum with a rapidly decaying tail in the parallel wavenumber direction. The wave power that decays to high enough frequencies to become ion cyclotron resonant depends on the relative strengths of advection and diffusion in the cascade. For the most realistic values of these parameters, though, there is insufficient power to heat protons and heavy ions. The dominant oblique waves undergo Landau damping, which implies strong parallel electron heating. We thus investigated the nonlinear evolution of the electron velocity distributions (VDFs) into parallel beams and discrete phase-space holes (similar to those seen in the terrestrial magnetosphere) which are an alternate means of heating protons via stochastic interactions similar to particle-particle collisions. 1b. Focused Study of the Multi-Mode Detailed Balance Formalism. The PI began to explore the feasibility of using the "weak turbulence," or detailed-balance theory of Tsytovich, Melrose, and others to encompass the relevant physics of the solar wind. This study did not go far, however, because if the "strong" MHD turbulence discussed above is a dominant player in the wind's acceleration region, this formalism is inherently not applicable to the corona. We will continue to study the various published approaches to the weak turbulence formalism, especially with an eye on ways to parameterize nonlinear wave reflection rates. 2. Building the Unified Model Code Architecture. We have begun developing the computational model of a time-steady open flux tube in the extended corona. The model will be "unified" in the sense that it will include (simultaneously for the first time) as many of the various proposed physical processes as possible, all on equal footing. To retain this generality, we have formulated the problem in two interconnected parts: a completely kinetic model for the particles, using the Monte Carlo approach, and a finite-difference approach for the self-consistent fluctuation spectra. The two codes are run sequentially and iteratively until complete consistency is achieved. The current version of the Monte Carlo code incorporates gravity, the zero-current electric field, magnetic mirroring, and collisions. The fluctuation code incorporates WKJ3 wave action conservation and the cascade/dissipation processes discussed above. The codes are being run for various test problems with known solutions. Planned additions to the codes include prescriptions for nonlinear wave steepening, kinetic velocity-space diffusion, and multi-mode coupling (including reflection and refraction).

Cranmer, Steven R.↗
DOE OSTI2025

Nonlinear Ensemble Filtering with Diffusion Models: Application to the Surface Quasigeostrophic Dynamics

The intersection between classical data assimilation methods and novel machine learning techniques has attracted significant interest in recent years. Here, we explore another promising solution in which diffusion models are used to formulate a robust nonlinear ensemble filter for sequential data assimilation. Unlike standard machine learning methods, the proposed ensemble score filter (EnSF) is completely training free and can efficiently generate a set of analysis ensemble members. Here, in this study, we apply the EnSF to a surface quasigeostrophic model and compare its performance against the popular local ensemble transform Kalman filter (LETKF), which makes Gaussian assumptions in the analysis step. Numerical tests demonstrate that EnSF maintains stable performance in the absence of localization and for a variety of experimental settings. We find that while LETKF maintains optimal performance in the case of linear observations of the entire state and a perfect model, EnSF shows improvements over LETKF when nonlinear observations are assimilated and the system is subject to unexpected model errors. A spectral decomposition of the analysis results in this nonlinear observation regime shows that the largest improvements over LETKF occur at large scales (small wavenumbers), where LETKF lacks sufficient ensemble spread. Overall, this initial application of EnSF to a geophysical model of intermediate complexity motivates further development of the algorithm for more realistic problems.

Artificial intelligence↗
DOE OSTI2020

Nonlinear Photovoltaic Degradation Rates: Modeling and Comparison Against Conventional Methods

Although common practice for estimating photovoltaic (PV) degradation rate (RD) assumes a linear behavior, field data have shown that degradation rates are frequently nonlinear. This article presents a new methodology to detect and calculate nonlinear RD based on PV performance time-series from nine different systems over an eight-year period. Prior to performing the analysis and in order to adjust model parameters to reflect actual PV operation, synthetic datasets were utilized for calibration purposes. A change-point analysis is then applied to detect changes in the slopes of PV trends, which are extracted from constructed performance ratio (PR) time-series. Once the number and location of change points is found, the ordinary least squares method is applied to the different segments to compute the corresponding rates. The obtained results verified that the extracted trends from the PR time-series may not always be linear and therefore, “nonconventional” models need to be applied. All thin-film technologies demonstrated nonlinear behavior whereas nonlinearity detected in the crystalline silicon systems is thought to be due to a maintenance event. A comparative analysis between the new methodology and other conventional methods demonstrated levelized cost of energy differences of up to 6.14%, highlighting the importance of considering nonlinear degradation behavior

14 SOLAR ENERGY↗
DOE OSTI2024

Modeling information flow in a computer processor with a multi-stage queuing model

In this paper, we introduce a nonlinear stochastic model to describe the propagation of information inside a computer processor. In this model, a computational task is divided into stages, and information can flow from one stage to another. The model is formulated as a spatially-extended, continuous-time Markov chain where space represents different stages. This model is equivalent to a spatially-extended version of the M/M/s queue. The main modeling feature is the throttling function which describes the processor slowdown when the amount of information falls below a certain threshold. We derive the stationary distribution for this stochastic model and develop a closure for a deterministic ODE system that approximates the evolution of the mean and variance of the stochastic model. In conclusion, we demonstrate the validity of the closure with numerical simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Time-dependent SOLPS-ITER simulations of the tokamak plasma boundary for model predictive control using SINDy *

Abstract Time-dependent SOLPS-ITER simulations have been used to identify reduced models with the sparse identification of nonlinear dynamics (SINDy) method and develop model-predictive control of the boundary plasma state using main ion gas puff actuation. A series of gas actuation sequences are input into SOLPS-ITER to produce a dynamic response in upstream and divertor plasma quantities. The SINDy method is applied to identify reduced linear and nonlinear models for the electron density at the outboard midplane n e , s e p O M P and the electron temperature at the outer divertor T e , s e p d i v . Note that T e , s e p d i v is not necessarily the peak value of T e along the divertor. The identified reduced models are interpretable by construction (i.e. not black box), and have the form of coupled ordinary differential equations. Despite significant noise in T e , s e p d i v , the reduced models can be used to predict the response over a range of actuation levels to a maximum deviation of 0.5% in n e , s e p O M P and 5%–10% in T e , s e p d i v for the cases considered. Model retraining using time history data triggered by a preset error threshold is also demonstrated. A model predictive control strategy for nonlinear models is developed and used to perform feedback control of a SOLPS-ITER simulation to produce a setpoint trajectory in n e , s e p O M P using the integrated plasma simulator framework. The developed techniques are general and can be applied to time-dependent data from other boundary simulations or experimental data. Ongoing work is extending the approach to model identification and control for divertor detachment, which will present transient nonlinear behavior from impurity seeding, including realistic latency and synthetic diagnostic signals derived from the full SOLPS-ITER output.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1972

Circuit model for characterizing the nearly linear behavior of avalanche diodes in amplifier circuits

A nonlinear circuit model for avalanche diodes is proposed. The model was derived by assuming that the bias dependence of the elements in a known small-signal equivalent-circuit model for existing diodes arises in a manner consistent with the theory of an idealized Read-type device. The model contains a nonlinear R-L branch, a controlled source, and a linear depletion capacitance. The model is used in the nearly linear sense to predict intermodulation distortion and gain compression in avalanche diode amplifiers. Computed results for amplifiers with existing diodes are shown to be in good agreement with experiment.

Penfield, P., Jr.↗
NASA NTRS1986

Evaluation of a nonlinear parameter extraction mathematical model including the term C(subm(sub delta e squared))

Shuttle flight test data were used to determine values for the short-period parameters. The best identified, as judged by its estimated standard deviation, was the elevon effectiveness parameter C (sub m (sub sigma e squared)). However, the scatter about the preflight prediction of C (sub m (sub sigma e squared)) was large. Other investigators have suggested that adding nonlinear terms to the mathematical model used to identify C (sub m (sub sigma e)) could reduce the scatter. The results of this investigation show that C (sub m (sub sigma e squared)) is the only identifiable nonlinear parameter applicable and that the changes in C (sub m (sub sigma e)) values when C (sub m (sub sigma e squared)) is included are in the order of ten percent for the data estimated.

Suit, W. T.↗