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DOE OSTI2024

Structured Neural Network Modeling for Developing Digital Twins Models of Hydropower Generation Units

Dynamic modeling is a key part in the development of digital twin (DT) for dynamic systems. This is true for hydropower systems, where whole system modeling including penstock, turbine and generators, etc is important in realizing actuate modeling for the real systems. On the other hand, in response to the large variations of the power demand due to increased penetration of renewables such as wind and solar, hydropower systems are now required to operate in a large power generation range. This situation triggers the nonlinear characteristics of the generation unit with respect to its models. As such, it is imperative to use data driven modeling such as neural networks to learn the nonlinear dynamics of the hydropower generation unit. To achieve this objective, this study constructs a modeling and learning algorithm integrated with multiple structured neural network models for the modeling of turbine shaft speed, penstock pressure, and generator power output based on the generator power control setpoint, field current, and field voltage. In addition, the study uses the hydropower data from Tacoma Public Utilities to train and validate the proposed neural network algorithm. The results have shown that this structured neural network modeling approach can learn the system dynamics effectively by using the real-time data collected from the hydropower system with the desired modeling results.

Wang, Hong↗

NASA NTRS1994

Pulsed acceleration in solar flares

We study the nonlinear dynamics of particle acceleration in solar flares by analyzing the time series of various quasi-periodic radio signatures during flares. In particular we present the radio and hard X-ray data of three flares which suppport the following tentative conclusions: (1) Particle acceleration and injection into magnetic structures occurs intrinsically in a pulsed mode (with a typical period of 1-2 s), produced by a single, spatially coherent, nonlinear system, rather than by a stochastic system with many spatially independent components ('statistical flare' produced by a fragmented primary energy release). (2) The nonlinear (quasi-periodic) mode of pulsed particle acceleration and injection into a coronal loop can be stabilized by phase locking with an MHD wave (oscillation) mode, if both periods are close to each other. (3) Pulsed injection of electron beams into a coronal loop may trigger nonlinear relaxational oscillations of wave-particle interactions. This is particularly likely when the limit cycles of both systems are similar.

Aschwanden, Markus J.↗

DOE OSTI2025

Nonlinear behavior of urban flood peaks in the U.S. Mid-Atlantic region

Urbanization, i.e., increasing urban development areas in a watershed, is well known as a major cause of increasing flood magnitudes. This study analyzes the observed flood peaks at 262 watersheds in the U.S. Mid-Atlantic region with varying levels of urban development and free from reservoir impacts. Our analysis reveals an interesting, V-shaped nonlinear behavior: flood peaks first decrease and then increase with increasing percentage of urban development area at the watershed scale (PDAW), with the shift occurring at a PDAW threshold of around 10%. Regression analyses suggest that the V-shaped pattern primarily results from complex interactions among climate conditions (e.g., storm-event rainfall) and landscape properties (e.g., elevation, distance to the coast). A neural network model was then developed to capture such interactions, satisfactorily reproducing the V-shaped pattern with an R-squared value of 0.58, RMSE of 6.72 mm/day, and NSE of 0.55. These findings highlight the need to account for nonlinear dynamics in flood prediction and management in the coastal environment.

flood peaks↗

NASA NTRS1982

Gain optimization with nonlinear controls

An algorithm has been developed for the analysis and design of controls for nonlinear systems. The technical approach is to use statistical linearization to model the nonlinear dynamics of a system. A covariance analysis is performed to determine the behavior of the dynamical system and a quadratic cost function. Expressions for the cost function and its derivatives are determined so that numerical optimization techniques can be applied to determine optimal feedback laws. The primary application for this report is centered about the design of controls for nominally linear systems but where the controls are saturated or limited by fixed constraints. The analysis is general however and numerical computation requires only that the specific nonlinearity be considered in the analysis.

Slater, G. L.↗

DOE OSTI2021

Improving the MJO Forecast of S2S Operation Models by Correcting Their Biases in Linear Dynamics

The operational dynamic subseasonal to seasonal (S2S) models for Madden-Julian oscillation (MJO) forecasting mostly still suffer from systematic errors in capturing the MJO's key dynamic features, such as its growth rate and propagation speed. By deriving the linear dynamic operators using the linear inverse modeling (LIM) approach, we propose a method to partly correct the errors in MJO linear dynamic operators to improve the MJO predictions of three operational dynamic S2S models. Correcting the deficiencies of the too-fast decay rates and the unrealistic propagating phase speeds lead to MJO prediction skills being extended by approximately 2–4 days. The improvements are more significant for the models with larger biases in MJO amplitude and propagation. This approach in principle may be extendable to predictions of other types of climate variability such as ENSO on one hand, and possible inclusions of nonlinear dynamics effects on the other hand.

58 GEOSCIENCES↗

NASA NTRS1991

Dynamics of free drops on USML-1

Drop-dynamics experiments are described in terms of scope and methodology that are designed for the USML-1 flight. Included are experiments regarding: (1) the equilibrium shapes of acoustically rotated drops; (2) large-amplitude drop and bubble-shape oscillations; (3) the collision and coalescence of free drops; and (4) the deformation and instability of levitated drops. The space flight is concluded to provide an effective containerless microgravity environment for studying linear and nonlinear dynamics.

Wang, Taylor G.↗

NASA NTRS1989

Computational chaos in massively parallel neural networks

A fundamental issue which directly impacts the scalability of current theoretical neural network models to massively parallel embodiments, in both software as well as hardware, is the inherent and unavoidable concurrent asynchronicity of emerging fine-grained computational ensembles and the possible emergence of chaotic manifestations. Previous analyses attributed dynamical instability to the topology of the interconnection matrix, to parasitic components or to propagation delays. However, researchers have observed the existence of emergent computational chaos in a concurrently asynchronous framework, independent of the network topology. Researcher present a methodology enabling the effective asynchronous operation of large-scale neural networks. Necessary and sufficient conditions guaranteeing concurrent asynchronous convergence are established in terms of contracting operators. Lyapunov exponents are computed formally to characterize the underlying nonlinear dynamics. Simulation results are presented to illustrate network convergence to the correct results, even in the presence of large delays.

Barhen, Jacob↗

DOE OSTI2017

Data-Driven Nonlinear Subspace Modeling for Prediction and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking

Blast furnace (BF) in ironmaking is a nonlinear dynamic process with complicated physical-chemical reactions, where multi-phase and multi-field coupling and large time delay occur during its operation. In BF operation, the molten iron temperature (MIT) as well as Si, P and S contents of molten iron are the most essential molten iron quality (MIQ) indices, whose measurement, modeling and control have always been important issues in metallurgic engineering and automation field. This paper develops a novel data-driven nonlinear state space modeling for the prediction and control of multivariate MIQ indices by integrating hybrid modeling and control techniques. First, to improve modeling efficiency, a data-driven hybrid method combining canonical correlation analysis and correlation analysis is proposed to identify the most influential controllable variables as the modeling inputs from multitudinous factors would affect the MIQ indices. Then, a Hammerstein model for the prediction of MIQ indices is established using the LS-SVM based nonlinear subspace identification method. Such a model is further simplified by using piecewise cubic Hermite interpolating polynomial method to fit the complex nonlinear kernel function. Compared to the original Hammerstein model, this simplified model can not only significantly reduce the computational complexity, but also has almost the same reliability and accuracy for a stable prediction of MIQ indices. Last, in order to verify the practicability of the developed model, it is applied in designing a genetic algorithm based nonlinear predictive controller for multivariate MIQ indices by directly taking the established model as a predictor. Industrial experiments show the advantages and effectiveness of the proposed approach.

Blast furnace (BF)↗

NASA NTRS2005

Simulating Vibrations in a Complex Loaded Structure

The Dynamic Response Computation (DIRECT) computer program simulates vibrations induced in a complex structure by applied dynamic loads. Developed to enable rapid analysis of launch- and landing- induced vibrations and stresses in a space shuttle, DIRECT also can be used to analyze dynamic responses of other structures - for example, the response of a building to an earthquake, or the response of an oil-drilling platform and attached tanks to large ocean waves. For a space-shuttle simulation, the required input to DIRECT includes mathematical models of the space shuttle and its payloads, and a set of forcing functions that simulates launch and landing loads. DIRECT can accommodate multiple levels of payload attachment and substructure as well as nonlinear dynamic responses of structural interfaces. DIRECT combines the shuttle and payload models into a single structural model, to which the forcing functions are then applied. The resulting equations of motion are reduced to an optimum set and decoupled into a unique format for simulating dynamics. During the simulation, maximum vibrations, loads, and stresses are monitored and recorded for subsequent analysis to identify structural deficiencies in the shuttle and/or payloads.

Cao, Tim T.↗

NASA NTRS2004

Dynamics of Earth orbiting formations

In this paper the equations of motion of a formation consisting of n spacecraft in Earth orbit are derived via Lagrange's equations. The equations of motion of the formation are developed with respect to both (1) a bound Keplerian reference orbit, and (2) a specific spacecraft in the formation. The major orbital perturbations acting on a formation in low Earth orbit are also included in the analysis. In contrast to the traditional approach based on the balance of linear momentum, the use of Lagrange's equations leads to a high-level matrix derivation of the formation equations of motion. The matrix form of the nonlinear motion equations is then linearized about a bound Keplerian reference orbit. Next, it is demonstrated that under the assumption of a circular reference orbit, the linearized equations of motion reduce to the well-known Hill-Clohessy-Wiltshire equations. The resulting linear and nonlinear dynamic equations lead to maximal physical insight into the structure of formation dynamics, and are ideally suited for use in the design and validation of formation guidance and control laws.

formation flying↗

DOE OSTI2017

Small-amplitude shock waves and double layers in dusty plasmas with opposite polarity charged dust grains

Theoretical investigation is carried out for understanding the properties of nonlinear dust-acoustic (DA) waves in an unmagnetized dusty plasma whose constituents are massive, micron-sized, positive and negatively charged inertial dust grains along with q (nonextensive) distributed electrons and ions. The reductive perturbation method is employed in order to derive two types of nonlinear dynamical equations, namely, Burgers equation and modified Gardner equation (Gardner equation with dissipative term). They are also numerically analyzed to investigate the basic features (viz., polarity, amplitude, width, etc.) of shock waves and double layers. It has been observed that the effects of nonextensivity, opposite polarity charged dust grains, and different dusty plasma parameters have significantly modified the fundamental properties of shock waves and double layers. The results of this investigation may be used for researches of the nonlinear wave propagation in laboratory and space plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1990

Neural networks for self-learning control systems

It is shown how a neural network can learn of its own accord to control a nonlinear dynamic system. An emulator, a multilayered neural network, learns to identify the system's dynamic characteristics. The controller, another multilayered neural network, next learns to control the emulator. The self-trained controller is then used to control the actual dynamic system. The learning process continues as the emulator and controller improve and track the physical process. An example is given to illustrate these ideas. The 'truck backer-upper,' a neural network controller that steers a trailer truck while the truck is backing up to a loading dock, is demonstrated. The controller is able to guide the truck to the dock from almost any initial position. The technique explored should be applicable to a wide variety of nonlinear control problems.

Nguyen, Derrick H.↗

NASA NTRS1991

Control and dynamics of a flexible spacecraft during stationkeeping maneuvers

A case study of a spacecraft having flexible solar arrays is presented. A stationkeeping attitude control mode using both earth and rate gyro reference signals and a flexible vehicle dynamics modeling and implementation is discussed. The control system is designed to achieve both pointing accuracy and structural mode stability during stationkeeping maneuvers. Reduction of structural mode interactions over the entire mode duration is presented. The control mode using a discrete time observer structure is described to show the convergence of the spacecraft attitude transients during Delta-V thrusting maneuvers without preloading thrusting bias to the onboard control processor. The simulation performance using the three axis, body stabilized nonlinear dynamics is provided. The details of a five body dynamics model are discussed. The spacecraft is modeled as a central rigid body having cantilevered flexible antennas, a pair of flexible articulated solar arrays, and to gimballed momentum wheels. The vehicle is free to undergo unrestricted rotations and translations relative to inertial space. A direct implementation of the equations of motion is compared to an indirect implementation that uses a symbolic manipulation software to generate rigid body equations.

Liu, D.↗

NASA NTRS1987

High speed, precision motion strategies for lightweight structures

Abstracts of published papers and dissertations generated during the reporting period are compiled. Work on fine motion control was completed. Specifically, real time control of flexible manipulator vibrations were experimentally investigated. A linear model based on the application of Lagrangian dynamics to a rigid body mode and a series of separable flexible modes was examined with respect to model order requirements, and modal candidate selection. State feedback control laws were implemented based upon linear quadratic regulator design. Specification of the closed loop poles in the regulator design process was obtained by inclusion of a prescribed degree of stability in the manipulator model. Work on gross motion planning and control is also summarized. A systematic method to symbolically derive the full nonlinear dynamic equations of motion of multi-link flexible manipulators was developed.

Book, Wayne J.↗

DOE OSTI2026

Analysis of the elliptic integrable non-linear system in IOTA using tracking of a single electron

Integrable nonlinear lattices that can be realized in practical accelerators are of great interest, as they offer the potential to support high-intensity beams via Landau damping of collective instabilities. One such system, based on an elliptic potential, has been extensively studied at the IOTA storage ring at Fermilab. The analysis of strongly nonlinear dynamics with multi-particle bunches is challenging due to the rapid decoherence of kicked beams. IOTA has the capability to track single electrons using linear multi-anode photomultiplier tubes for simultaneously measuring transverse coordinates and arrival times of synchrotron-radiation pulses. This technology enables the full reconstruction of turn-by-turn positions and momenta in all three planes for a single particle. Using this apparatus, we measured the dependence of small-amplitude tunes on the strength of the nonlinear magnet, as well as tunes dependence on oscillations amplitudes.

Romanov, A. [Fermilab]↗

DOE OSTI2025

Analysis of the Elliptic Integrable Non-Linear System in IOTA Using Tracking of a Single Electron

Romanov, Aleksandr Leonidovich [Fermilab] (ORCID:0↗

NASA NTRS1994

Multiscale low-frequency circulation modes in the global atmosphere

In this paper, fundamental multiscale circulation modes in the global atmosphere are identified with the objective of providing better understanding of atmospheric low-frequency variabilities over a wide range of spatial and temporal scales. With the use of a combination of rotated principal component technique, singular spectrum analysis, and phase space portraits, three categories of basic multiscale modes in the atmosphere are found. The first is the interannual-mode (IAM), which is dominated by time scales longer than a year and can be attributed to heating and circulation anomalies associated with the coupled tropical ocean-atmosphere, in particular the El Nino-Southern Oscillation. The second is a set of tropical intraseasonal modes consisting of three separate multiscale patterns (ISO-1, -2, -3) related to tropical heating that can be identified with the different phases of the Madden-Julian Oscillation (MJO), including its teleconnection to the extratropics. The ISO spatial and temporal patterns suggest that the extratropical wave train in the North Pacific and North America is related to heating over the Maritime Continent and that the evolution of the MJO around the equator may require forcing from the extratropics spawning convection over the Indian Ocean. The third category represents extratropical intraseasonal oscillations arising from internal dynamics of the basic-state circulation. In the Northern Hemisphere, there are two distinct circulation modes with multiple frequencies in this category: the Pacific/North America (PNA) and the North Atlantic/Eurasia (NAE). In the Southern Hemisphere, two phase-locked modes (PSA-1 and PSA-2) are found depicting an eastward propagating wave train from eastern Australia, via the Pacific South America to the South Atlantic. The extratropical modes exhibit temporal characteristics such as phase locking and harmonic oscillations possibly associated with quadratically nonlinear dynamical systems. Additionally, the observed monthly and seasonal anomalies arise from a complex interplay of the various multiscale low-frequency modes. The relative dominance of the different modes varies widely from month to month and from year to year. On the monthly time scale, while one or two mechanisms may dominate in one year, no single mechanism seems to dominate for all years. There are indications that when the IAM, that is, ENSO heating patterns are strong, the extratropical modes may be suppressed and vice versa. For the seasonal mean, the interannual mode tends to dominate and the contribution from the PNA remains quite significant.

Lau, K.-M.↗

DOE OSTI2024

Lyapunov-based nonlinear control of nonautonomous systems with individual input constraints

A control algorithm that can locally stabilize a specific class of multi-input multi-output nonautonomous nonlinear dynamical systems while satisfying individual input constraints is developed. The proposed Lyapunov-based state-feedback control law inherently accounts for the actuator amplitude saturation limits without the need for computationally expensive real-time optimization techniques. In addition to the control law, a formal definition for the local “controllable region” within which the controller can asymptotically drive the system states to the origin and satisfy the input saturation limits is also presented. The nonautonomous nature of the system dynamics implies that the “controllable region” continuously evolves with time. Therefore, a sufficient condition to maintain the system states within the “controllable region” is proposed in this work to make practical implementation feasible. The effectiveness of the controller is tested for a specific control problem arising in tokamaks, which are toroidal devices that use strong magnetic fields to confine a plasma (hot ionized gas). Here, the primary emphasis of tokamak research is to regulate the plasma properties around predetermined values to achieve stable plasma confinement. Nonlinear simulations show that the proposed controller can achieve the desired plasma control objectives in a DIII-D tokamak scenario.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗