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Results for “Linear and nonlinear operators”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Implicit TVD schemes for hyperbolic conservation laws in curvilinear coordinates

The Harten (1983, 1984) total variation-diminishing (TVD) schemes, constituting a one-parameter explicit and implicit, second-order-accurate family, have the property of not generating spurious oscillations when applied to one-dimensional, nonlinear scalar hyperbolic conservation laws and constant coefficient hyperbolic systems. These methods are presently extended to the multidimensional hyperbolic conservation laws in curvilinear coordinates. Means by which to linearize the implicit operator and solution strategies, in order to improve the computation efficiency of the implicit algorithm, are discussed. Numerical experiments with steady state airfoil calculations indicate that the proposed linearized implicit TVD schemes are accurate and robust.

Yee, H. C.↗
NASA NTRS1993

Interference effects on Space Station Freedom and space shuttle orbiter Ku-band downlinks

The space shuttle orbiter (SSO) and Ku-band single access return (KSAR) link and the Space Station Freedom (SSF) KSAR link via the tracking and data relay satellite system (TDRSS) use the same carrier frequency. The interference between spacecraft is minimized by opposite antenna polarizations and by TDRSS antenna beam pointing, but if the SSF and SSO are in close proximity, it is expected that mutual interference will be significant. Recently, Tsang and Su (1988, 1989) simulated the mutual interference effects, using a practical nonlinear bandlimited channel. The purpose of this paper is to demonstrate that a simplified (i.e., linear band-limited channel) analytical approach will yield adequate accuracy for the expected range of operating conditions. Relative degradation in bit energy-to-thermal noise power spectral density ratio to achieve a 10 exp -5 coded bit-error-probability is determined to be 4 dB for the Ku-band SSO-to-TDRS I-channel return link with a 4.5 dB effective signal-to-interference total power ratio (S/I) when the Ku-band SSF-to-TDRS return link interferes, whereas Su's simulation yields approximately 5 dB degradation. For the Ku-band SSF-to-TDRS return link, both analysis and simulation results yield a relative signal degradation of 0.4 dB at the effective S/I = 21.6 dB. In conclusion, interference on the Ku-band SSO-to-TDRS I-channel return link is significant, but on the Ku-band SSF-to-TDRS return link it is negligible.

Kwon, Hyuck M.↗
DOE OSTI2022

Ensuring Transient Stability With Guaranteed Region of Attraction in DC Microgrids

DC microgrids have promising applications in renewable integration due to their better energy efficiency when connecting DC components. However, they might be unstable since many loads in a DC microgrid are regulated as constant power loads (CPLs) that have a destabilizing negative impedance effect. As a result, the state trajectory displacement caused by abrupt load changes or contingencies can easily lead to instability. Many existing works have been devoted to studying the region of attraction (ROA) of a DC microgrid, in which the system is guaranteed to be asymptotically stable. Nevertheless, existing work either focuses on using numerical methods for ROA approximations that generally have no performance guarantees or cannot ensure a desired ROA for a general DC microgrid. To close this gap, this paper develops an innovative control synthesis algorithm to make a general DC microgrid have a theoretically guaranteed ROA, for example, to cover the entirety of its operating range regarding state trajectories. Here, we first study the nonlinear dynamics of a DC microgrid to derive a novel transient stability condition to rigorously certify whether a given operating range is a subset of the ROA; then, we formulate a control synthesis optimization problem to guarantee the condition’s satisfaction. This condition is a linear constraint, and the optimization problem resembles an optimal power flow problem and has a good computational behavior. Simulation case studies verify the validity of the proposed work.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A new operator-split Compton scattering method

In high-energy-density physics, when the temperatures are high (keV-range) and/or the densities are low, Compton scattering becomes the main energy transfer mechanism between the radiation field and the material. The interaction between the radiation field and the material is non-linear in the radiation field – due to induced processes caused by photons being bosons – and in the material temperature. Many existing codes use a Compton-Fokker-Planck (CFP) approximation – which is inaccurate for high photon energies or material temperatures – or use linear approximations within a time-step. Here, we have implemented a new Compton-heating method called OS-FBC (Operator-Split Full-Boltzmann Compton) that solves the full, nonlinear Compton-heating system with few approximations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A set of test problems for nonlinear optimization

The software is a set of test problems for nonlinear optimization algorithms, including subroutines such as linear algebra routines and automatic differentiation algorithms. The test problems come from chemical engineering open literature, and describe optimization tasks related to the design and operation of processes such as carbon capture, Hydrogen production, heat exchange, and distillation.

Parker, Robert↗
NASA NTRS1972

Development of welded metal bellows having minimum effective diameter change

A program of analysis, design, and fabrication was conducted to develop welded metal bellows having a minimum change in effective diameter for cryogenic turbomachinery face seal applications. Linear analysis of the principle types of bellows provided identification of concepts capable of meeting basic operation requirements. For the 6-inch (.152 m) mean diameter, 1.5-inch free length bellows studied, nonlinear analysis showed that opposed and nested toroidal bellows plates stiffened by means of alternating stiffener rings were capable of maintaining constant effective diameter within 0.3% and 0.1% respectively under the operating conditions of interest. Changes in effective diameter were due principally to bellows axial deflection with pressure differential having a lesser influence. Fabrication problems associated with joining the thin bellows plates to the relatively heavy stiffener rings were encountered and precluded assembly and testing of a bellows core. Fabrication problems are summarized and recommended fabrication methods for future effort are presented.

Henschel, J. K.↗
DOE OSTI2020

Stochastic multi-period optimal dispatch of energy storage in unbalanced distribution feeders

This report presents a convex, multi-period, AC-feasible Optimal Power Flow (OPF) framework that robustly dispatches flexible demand-side resources in unbalanced distribution feeders against uncertainty in very-short timescale solar Photo-Voltaic (PV) forecasts. This is valuable for power systems with significant behind-the-meter solar PV generation as their operation is affected by uncertainty from forecasts of demand and solar PV generation. The aim of this work is then to ensure the feasibility and reliability of distribution system operation under high solar PV penetration. We develop and present a novel, robust OPF formulation that accounts for both the nonlinear power flow constraints and the uncertainty in forecasts. This is achieved by linearizing an optimal trajectory and using first-order methods to systematically tighten voltage bounds. Case studies on a realistic distribution feeder shows the effectiveness of a receding-horizon implementation.

25 ENERGY STORAGE↗
DOE OSTI2021

Universal Compiling and (No-)Free-Lunch Theorems for Continuous-Variable Quantum Learning

Quantum compiling, where a parameterized quantum circuit is trained to learn a target unitary, is an important primitive for quantum computing that can be used as a subroutine to obtain optimal circuits or as a tomographic tool to study the dynamics of an experimental system. While much attention has been paid to quantum compiling on discrete-variable hardware, less has been paid to compiling in the continuous-variable paradigm. Here we motivate several, closely related, short-depth continuous-variable algorithms for quantum compilation. We analyze the trainability of our proposed cost functions and numerically demonstrate our algorithms by learning arbitrary Gaussian operations and Kerr nonlinearities. We further make connections between this framework and quantum learning theory in the continuous-variable setting by deriving no-free-lunch theorems. These generalization bounds demonstrate a linear resource reduction for learning Gaussian unitaries using entangled coherent-Fock states and an exponential resource reduction for learning arbitrary unitaries using two-mode-squeezed states.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1970

Coulometer battery state-of-charge indicator

Mercury-column electrochemical coulometer is a linear ampere-hour integrating device consisting of a sealed glass tube containing two columns of mercury separated by a gap containing an electrolyte. The drive circuit uses operational amplifier techniques to match nonlinear charge-discharge characteristics of an alkaline battery.

Birchenough, A. G.↗
NASA NTRS1984

Exact nonlinear command generation and tracking for robot manipulators and spacecraft slewing maneuvers

In connection with the current interest in agile spacecraft maneuvers, it has become necessary to consider the nonlinear coupling effects of multiaxial rotation in the treatment of command generation and tracking problems. Multiaxial maneuvers will be required in military missions involving a fast acquisition of moving targets in space. In addition, such maneuvers are also needed for the efficient operation of robot manipulators. Attention is given to details regarding the direct nonlinear command generation and tracking, an approach which has been successfully applied to the design of control systems for V/STOL aircraft, linearizing transformations for spacecraft controlled with external thrusters, the case of flexible spacecraft dynamics, examples from robot dynamics, and problems of implementation and testing.

Dywer, T. A. W., III↗
NASA NTRS1992

Experimental results in nonlinear compensation of a one degree-of-freedom magnetic suspension

Nonlinear control techniques are of increasing interest in magnetic bearing applications. A one-degree-of-freedom magnetic suspension system has been constructed to serve as a test system for nonlinear control. The objective of this effort is to build an accurate model for the nonlinear suspension dynamics and to show the advantages of compensating for these nonlinearities by using a nonlinear controller. The results obtained with a nonlinear controller are experimentally demonstrated as superior to those obtained with a linear controller. Specifically, a controller which contains a force-control block yields transient responses which are largely independent of the operating point air gap.

Trumper, David L.↗
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↗
DOE OSTI2021

Edge localized mode characteristics and divertor heat flux during stationary and transient phase for CFETR hybrid scenario

The study of edge localized mode (ELM) behavior, stationary heat flux and transient heat flux during the ELM crash phase is performed for a China Fusion Engineering Test Reactor (CFETR) 1 GW hybrid mode operation scenario ($R$ = 7.2 m, ${B_{\text{T}}}$ = 6.5 T, ${I_{\text{p}}}$ = 13.78 MA). Modeling and simulation start with a scenario obtained by multi-code integrated modeling on the one modeling framework for integrated tasks framework. Linear stability and nonlinear simulations of ELM dynamics are carried out using the BOUT++ six-field reduced magnetohydrodynamic module, which show a much smaller ELM energy loss (Δ ELM ~ 0.13%) compared to that of a Type-I ELM. Parametric analysis of the weak linear growth rate and small ELM energy loss characteristics shed light on physics corresponding to a grassy ELM regime for CFETR 1 GW hybrid scenario. The transient heat flux on the divertor target during this small ELM phase is investigated using BOUT++. Here we found that upstream radial transport in the scrape-off-layer (SOL) induced by small ELMs is weak, which keeps it in the drift-dominated region. However, the heat flux width is still broadened to ${\lambda _{\text{q}}}$ = 4.64 mm by the increase of separatrix temperature during ELM nonlinear evolution. The impact of transient peak heat load and ELM energy fluence on tungsten melting and net erosion rate of divertor target is evaluated for the first-time using physics-based transport that connects the pedestal with the SOL. Energy fluence caused by a single ELM pulse is below the tungsten melting limit, while tungsten erosion would exceed the material requirements. We conclude that external mitigation methods, such as divertor detachment and advanced divertor geometry are likely needed for the steady state operation of CFETR.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1993

The piecewise-linear predictor-corrector code - A Lagrangian-remap method for astrophysical flows

We describe a time-explicit finite-difference algorithm for solving the nonlinear fluid equations. The method is similar to existing Eulerian schemes in its use of operator-splitting and artificial viscosity, except that we solve the Lagrangian equations of motion with a predictor-corrector and then remap onto a fixed Eulerian grid. The remap is formulated to eliminate errors associated with coordinate singularities, with a general prescription for remaps of arbitrary order. We perform a comprehensive series of tests on standard problems. Self-convergence tests show that the code has a second-order rate of convergence in smooth, two-dimensional flow, with pressure forces, gravity, and curvilinear geometry included. While not as accurate on idealized problems as high-order Riemann-solving schemes, the predictor-corrector Lagrangian-remap code has great flexibility for application to a variety of astrophysical problems.

Lufkin, Eric A.↗
DOE OSTI2024

Learning physics-based reduced-order models from data using nonlinear manifolds

Here we present a novel method for learning reduced-order models of dynamical systems using nonlinear manifolds. First, we learn the manifold by identifying nonlinear structure in the data through a general representation learning problem. The proposed approach is driven by embeddings of low-order polynomial form. A projection onto the nonlinear manifold reveals the algebraic structure of the reduced-space system that governs the problem of interest. The matrix operators of the reduced-order model are then inferred from the data using operator inference. Numerical experiments on a number of nonlinear problems demonstrate the generalizability of the methodology and the increase in accuracy that can be obtained over reduced-order modeling methods that employ a linear subspace approximation.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1981

Parameter estimation of large flexible aerospace structures with application to the control of the Maypole Deployable Reflector

Systems such as the Maypole deployable reflector have a distributed parameter nature. The flexible column and hoop structure and the circular antenna of 30-100 meter diameter which it supports are described by partial, rather than ordinary, differential equations. Progress completed in reduced order modelling andd controller design and digital parameter estimation and control is summarized. Topics covered include depolyment and on-orbit operation; quasi-static (steady state) operation; dynamic distributed parameter system; autoregressive moving average identification; frequency domain procedures; direct or implicit active control; adaptive observers; parameter estimation using a linear reinforcement learning factor; feedback control; and reduced order modeling for nonlinear systems.

Balas, M. J.↗
DOE OSTI2020

Models and Strategies for Optimal Demand Side Management in the Chemical Industries

Deregulation and the increase of renewable electricity generation from wind and solar photovoltaics have transformed the U.S. electricity market. Economic and environmental benefits notwithstanding, the presence of renewables has increased variability and uncertainty on the supply side of the grid. Managing demand, rather than generation – a strategy referred to as “demand response (DR)” – is an attractive approach for mitigating this imbalance. DR efforts aim to reduce electricity usage during peak demand times, lessening stress on the grid. Industrial users are particularly attractive entities for DR participation since they present large, localized loads that can provide significant relief on grid demand and –unlike other large loads, such as buildings – are minimally dependent on human needs and preferences. In this project, we accomplished three main objectives. (1) We developed data-driven low-order DR scheduling-relevant dynamic models of chemical processes. Concurrently, we studied the formulation and solution of the associated optimal DR production scheduling problems. (a) A prototype air separation unit (ASU) model was used to generate simulated operating data for initial modeling efforts, which enabled the later use of industrial data for data-driven modeling. (b) We utilized Hammerstein-Wiener (HW) and Finite Step Response (FSR) models to represent nonlinear plant dynamics. (c) The HW models were linearized using exact linearization so they could potentially be embedded in power system models, which are formulated as mixed integer linear programs (MILPs). (d) We solved DR optimization problems under uncertainty and found that even naïve predictions of electricity price and product demand led to significant cost savings benefits. (2) Our DR scheduling optimization problem formulations are amenable to real-time solution. (a) We utilized Lagrangian Relaxation (LR) to efficiently solve the optimization problem by decoupling subproblems linked by complicating constraints. (b) We have achieved computation times for the 3-day DR scheduling problem of an ASU as low as 1.88 minutes. (3) Our representations of the DR behavior of chemical process as grid-level batteries were embedded in power system models. (a) For a small-scale grid, we found that incorporating the dynamics of the chemical plant in the optimal power flow calculations resulted in better resource management leading to up to 15% and 46% cost reduction for the grid and chemical plant operations, respectively, during periods of power line congestion. We have published several works dedicated to modeling and solving DR optimization problems from the user side. These were published in top peer-reviewed journals and are summarized in this report. The most recent work (and papers in preparation) considers DR scheduling from the grid side. Future efforts will consider networked plants (e.g., air separation units operating on a common pipeline) for DR participation, which is expected to amplify the capabilities of industrial DR participants to perform load-shifting. Our consideration of uncertainty in DR has inspired future directions in this area as well: we plan to develop multistage methods to fully account for the effects of uncertainty in DR scheduling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1990

Application of the operator spline technique to nonlinear estimation and control of moving elastic systems

A bilinear model of the vibrational dynamics of a deformable maneuvering body is described. Estimates of the deformation state are generated through a low dimensional operator spline interpolator of bilinear systems combined with a feedback linearized based observer. Upper bounds on error estimates are also generated through the operator spline, and potential application to shaping control purposes is highlighted.

Karray, Fakhreddine↗