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At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Neural-Network Inverse Design of SRF Cavities and Transmons for Bosonic Quantum Computation

Three-dimensional superconducting radio-frequency (SRF) cavities provide exceptionally long-lived electromagnetic modes and, when coupled to nonlinear elements such as transmon qubits, become promising architectures for bosonic quantum information processing. The inverse design of such systems, i.e., recovering device geometries that produce specified electromagnetic and coupling targets, is generally a one-to-many problem. The qubit-cavity coupling strength depends sensitively on both the transmon geometry and its position within the cavity's electromagnetic field. As these systems scale up and their design parameter spaces grow, the cost of conventional iterative simulation becomes prohibitive. We present two deep neural network (DNN) approaches that address this inverse-design problem at complementary levels of the design stack. The first proposes SRF cavity geometries that produce target cavity observables. The second proposes transmon qubit designs that produce target qubit-cavity parameters - the coupling rate, qubit frequency, and anharmonicity $(g, ν_q, α)$. The recovered candidate designs match the targets to within ~5% (cavity) and ~2% (transmon), confirmed by end-to-end re-simulation. Both approaches map desired device behavior directly to candidate designs, a fast alternative to the iterative simulation studies usually required.

Yaker, Joseph [Fermilab; Northwestern U.]↗
NASA NTRS1987

The convergence of spectral methods for nonlinear conservation laws

The convergence of the Fourier method for scalar nonlinear conservation laws which exhibit spontaneous shock discontinuities is discussed. Numerical tests indicate that the convergence may (and in fact in some cases must) fail, with or without post-processing of the numerical solution. Instead, a new kind of spectrally accurate vanishing viscosity is introduced to augment the Fourier approximation of such nonlinear conservation laws. Using compensated compactness arguments, it is shown that this spectral viscosity prevents oscillations, and convergence to the unique entropy solution follows.

Tadmor, Eitan↗
NASA NTRS1992

Tailored metal matrix composites for high-temperature performance

A multi-objective tailoring methodology is presented to maximize stiffness and load carrying capacity of a metal matrix cross-ply laminated at elevated temperatures. The fabrication process and fiber volume ratio are used as the design variables. A unique feature is the concurrent effects from fabrication, residual stresses, material nonlinearity, and thermo-mechanical loading on the laminate properties at the post-fabrication phase. For a (0/90)(sub s) graphite/copper laminate, strong coupling was observed between the fabrication process, laminate characteristics, and thermo-mechanical loading. The multi-objective tailoring was found to be more effective than single objective tailoring. Results indicate the potential to increase laminate stiffness and load carrying capacity by controlling the critical parameters of the fabrication process and the laminate.

Morel, M. R.↗
NASA NTRS1992

Tailored metal matrix laminates for high-temperature performance

A multi-objective tailoring methodology is presented to maximize stiffness and load carrying capacity of a metal matrix cross-ply laminated at elevated temperatures. The fabrication process and fiber volume ratio are used as the design variables. A unique feature is the concurrent effects from fabrication, residual stresses, material nonlinearity, and thermo-mechanical loading on the laminate properties at the post-fabrication phase. For a (0.90) (sub s) graphite/copper laminate, strong coupling was observed between the fabrication process, laminate characteristics, and thermo-mechanical loading. The multi-objective tailoring was found to be more effective than single objective tailoring. Results indicate the potential to increase laminate stiffness and load carrying capacity by controlling the critical parameters of the fabrication process and the laminate.

Morei, Michael R.↗
DOE OSTI2023

Integrated membrane material design and system synthesis

In designing membrane systems, the synergy between membrane materials and the process design is often overlooked. In this paper, we present a mixed-integer nonlinear programming (MINLP) model for synthesizing membrane systems while simultaneously designing the respective membrane materials for multicomponent gas separation. The approach considers superstructure representations for systems with: (1) same, (2) potentially different, and (3) property-targeting membrane materials. In the first two systems, the selection of membrane material is a decision, while in the final type, membrane permeances are subject to optimization. Physics-based surrogate models are used to describe permeation in crossflow and countercurrent flow permeators. We show that, through a case study of biogas upgrading, our approach obtains high quality solutions. Furthermore, we use the proposed approach while considering permeance-based production cost to find the optimal membrane.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

Potential Flow Interactions With Directional Solidification

The effect of convective melt motion on the growth of morphological instabilities in crystal growth has been the focus of many studies in the past decade. While most of the efforts have been directed towards investigating the linear stability aspects, relatively little attention has been devoted to experimental and numerical studies. In a pure morphological case, when there is no flow, morphological changes in the solid-liquid interface are governed by heat conduction and solute distribution. Under the influence of a convective motion, both heat and solute are redistributed, thereby affecting the intrinsic morphological phenomenon. The overall effect of the convective motion could be either stabilizing or destabilizing. Recent investigations have predicted stabilization by a flow parallel to the interface. In the case of non-parallel flows, e.g., stagnation point flow, Brattkus and Davis have found a new flow-induced morphological instability that occurs at long wavelengths and also consists of waves propagating against the flow. Other studies have addressed the nonlinear aspects (Konstantinos and Brown, Wollkind and Segel)). In contrast to the earlier studies, our present investigation focuses on the effects of the potential flow fields typically encountered in Hele-Shaw cells. Such a Hele-Shaw cell can simulate a gravity-free environment in the sense that buoyancy-driven convection is largely suppressed, and hence negligible. Our interest lies both in analyzing the linear stability of the solidification process in the presence of potential flow fields, as well as in performing high-accuracy nonlinear simulations. Linear stability analysis can be performed for the flow configuration mentioned above. It is observed that a parallel potential flow is stabilizing and gives rise to waves traveling downstream. We have built a highly accurate numerical scheme which is validated at small amplitudes by comparing with the analytically predicted results for the pure morphological case. We have been able to observe nonlinear effects at larger times. Preliminary results for the case when flow is imposed also provide good validation at small amplitudes.

Buddhavarapu, Sudhir S.↗
DOE OSTI2023

Towards Smart Grids Enhanced Situation Awareness: A Bi-Level Quasi-Static State Estimation Model

Smart Grid situational awareness is provided by Energy Management Systems. A core process of these systems is State Estimation. The great majority of state estimators model the Smart Grid through a set of nonlinear algebraic equations, named the measurement model. Problem formulation considers the Gauss solution. Several model improvements have been presented regarding the Gauss solution, aiming between others to provide measurement noise robustness to the state estimation process. While considerable effort has been focused on such developments, state estimation is still constrained by the implicit modelling error, and thus inevitably vulnerable to cyber-threats. In this work, a state estimation bi-level formal model is presented towards Smart Grids enhanced situational awareness considering the concepts of synthetic measurements and innovation. Comparative test results with the state-of-the-art on the IEEE 14-bus system are presented highlighting improved situational awareness to bad data. Easy-to-implement model, without hard-to-derive parameters, built-on the classic weighted least squares solution, highlight potential aspects for real-life implementation.

cyber security↗
NASA NTRS1994

A note on the accuracy of spectral method applied to nonlinear conservation laws

Fourier spectral method can achieve exponential accuracy both on the approximation level and for solving partial differential equations if the solutions are analytic. For a linear partial differential equation with a discontinuous solution, Fourier spectral method produces poor point-wise accuracy without post-processing, but still maintains exponential accuracy for all moments against analytic functions. In this note we assess the accuracy of Fourier spectral method applied to nonlinear conservation laws through a numerical case study. We find that the moments with respect to analytic functions are no longer very accurate. However the numerical solution does contain accurate information which can be extracted by a post-processing based on Gegenbauer polynomials.

Shu, Chi-Wang↗
NASA NTRS1994

Dripping handrails and the quasi-periodic oscillations of the AM Herculis objects

AM Her objects exhibit periodic, quasi-periodic, and aperiodic variability on timescales ranging from seconds to years. Here, we investigate a process for the production of aperiodic and quasi-periodic accretion rate fluctuations. We consider the nonlinear dynamical model known as the dripping handrail (DHR). The DHR, basically a model for certain types of spatially extended systems and loosely based on water condensing on and dripping off a handrail, has recently been used as a model for the quasi-periodic oscillations (QPO) and very low frequency noise of the low-mass X-ray binary Sco X-1. Here, we show that (1) the DHR is a robust QPO generation process in that it leads to QPO production under a wide range of conditions and assumptions; (2) the phenomenology of the DHR is consistent with the observed aperiodic and quasi-periodic varibility of the AM Her QPO source VV Pup over timescales ranging from 16 ms to 20 s; and (3) a single DHR model can produce both broadband QPOs and features with quality Q greater than 20 as observed in several AM Her QPO sources.

Steiman-Cameron, Thomas Y.↗
DOE OSTI2021

Latent-space time evolution of non-intrusive reduced-order models using Gaussian process emulation

Non-intrusive reduced-order models (ROMs) have recently generated considerable interest for constructing computationally efficient counterparts of nonlinear dynamical systems emerging from various domain sciences. They provide a low-dimensional emulation framework for systems that may be intrinsically high-dimensional. This is accomplished by utilizing a construction algorithm that is purely data-driven. It is no surprise, therefore, that the algorithmic advances of machine learning have led to non-intrusive ROMs with greater accuracy and computational gains. However, in bypassing the utilization of an equation-based evolution, it is often seen that the interpretability of the ROM framework suffers. This becomes more problematic when black-box deep learning methods are used which are notorious for lacking robustness outside the physical regime of the observed data. In this article, we propose the use of a novel latent-space interpolation algorithm based on Gaussian process regression. Notably, this reduced-order evolution of the system is parameterized by control parameters to allow for interpolation in space. The use of this procedure also allows for a continuous interpretation of time which allows for temporal interpolation. The latter aspect provides information, with quantified uncertainty, about full-state evolution at a finer resolution than that utilized for training the ROMs. This research assesses the viability of this algorithm for an advection-dominated system given by the inviscid shallow water equations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

The coalescence instability in collisionless plasmas

The process whereby magnetic island structures tend to merge into larger units is known as magnetic island coalescence. This coalescence process is investigated for the case of a collisionless plasma by means of 2D particle simulations. The pairwise merging of a preformed island chain leads to a gentle redistribution of the density and current density profiles. The nonlinear evolution of the collisionless tearing instability in a long system is found to lead to a much more violent coalescence process resulting in the formation of a vacuum X region. This stage is characterized by enhanced growth rates for the long-wavelength modes that exceed the maximum linear tearing growth rate, super-Alfvenic flows away from the reconnection X line, substantial bulk heating in the parallel direction, and the formation of energetic particle tails in the direction of the inductive electric field.

Pritchett, P. L.↗
NASA NTRS2008

A Computational Procedure for Identifying Bilinear Representations of Nonlinear Systems Using Volterra Kernels

A computational procedure for identifying the state-space matrices corresponding to discrete bilinear representations of nonlinear systems is presented. A key feature of the method is the use of first- and second-order Volterra kernels (first- and second-order pulse responses) to characterize the system. The present method is based on an extension of a continuous-time bilinear system identification procedure given in a 1971 paper by Bruni, di Pillo, and Koch. The analytical and computational considerations that underlie the original procedure and its extension to the title problem are presented and described, pertinent numerical considerations associated with the process are discussed, and results obtained from the application of the method to a variety of nonlinear problems from the literature are presented. The results of these exploratory numerical studies are decidedly promising and provide sufficient credibility for further examination of the applicability of the method.

Kvaternik, Raymond G.↗
DOE OSTI2023

Bayesian sequential optimal experimental design for nonlinear models using policy gradient reinforcement learning

We present a mathematical framework and computational methods for optimally designing a finite sequence of experiments. This sequential optimal experimental design (sOED) problem is formulated as a finite-horizon partially observable Markov decision process (POMDP) under a Bayesian setting and with information-theoretic utilities. The formulation is general and may accommodate continuous random variables, non-Gaussian posteriors, and nonlinear forward models. The sOED design policy incorporates elements of feedback and lookahead simultaneously, and we show it to generalize the commonly-used batch and greedy design strategies. We solve for the sOED policy using the policy gradient (PG) method from reinforcement learning, and provide a derivation for the PG expression in the sOED context. Adopting an actor-critic approach, the policy and value functions are parameterized using deep neural networks and improved via PG estimates produced from simulated episodes of designs and observations. The new PG-sOED algorithm is first validated on a linear-Gaussian benchmark, and then compared against other design baselines on a sensor movement problem for contaminant source inversion in a convection-diffusion field. As a result, we provide explanation for the policy behaviors using knowledge of the underlying physical process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

An initial exploration of Bayesian model calibration for estimating the composition of rocks and soils on Mars

The Mars Curiosity rover carries an instrument, ChemCam, designed to measure the composition of surface rocks and soil using laser-induced breakdown spectroscopy (LIBS). The measured spectra from this instrument must be analyzed to identify the component elements in the target sample, as well as their relative proportions. This process, which we call disaggregation, is complicated by so-called matrix effects, which describe nonlinear changes in the relative heights of emission lines as an unknown function of composition due to atomic interactions within the LIBS plasma. In this work, we explore the use of the plasma physics code ATOMIC, developed at Los Alamos National Laboratory, for the disaggregation task. ATOMIC has recently been used to model LIBS spectra and can robustly reproduce matrix effects from first principles. The ability of ATOMIC to predict LIBS spectra presents an exciting opportunity to perform disaggregation in a manner not yet tried in the LIBS community, namely via Bayesian model calibration. However, using it directly to solve our inverse problem is computationally intractable due to the large parameter space and the computation time required to produce a single output. Therefore, we also explore the use of emulators as a fast solution for this analysis. We discuss a proof of concept Gaussian process emulator for disaggregating two-element compounds of sodium and copper. The training and test datasets were simulated with ATOMIC using a Latin hypercube design. After testing the performance of the emulator, we successfully recover the composition of 25 test spectra with Bayesian model calibration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Magnetic resonance insights into the heterogeneous, fractal-like kinetics of chemically recyclable polymers

Moving toward a circular plastics economy is a vital aspect of global resource management. Chemical recycling of plastics ensures that high-value monomers can be recovered from depolymerized plastic waste, thus enabling circular manufacturing. However, to increase chemical recycling throughput in materials recovery facilities, the present understanding of polymer transport, diffusion, swelling, and heterogeneous deconstruction kinetics must be systematized to allow industrial-scale process design, spanning molecular to macroscopic regimes. To develop a framework for designing depolymerization processes, we examined acidolysis of circular polydiketoenamine elastomers. We used magnetic resonance to monitor spatially resolved observables in situ and then evaluated these data with a fractal method that treats nonlinear depolymerization kinetics. This approach delineated the roles played by network architecture and reaction medium on depolymerization outcomes, yielding parameters that facilitate comparisons between bulk processes. These streamlined methods to investigate polymer hydrolysis kinetics portend a general strategy for implementing chemical recycling on an industrial scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1998

Constraints on Nonlinear and Stochastic Growth Theories for Type 3 Solar Radio Bursts from the Corona to 1 AU

Existing, competing theories for coronal and interplanetary type III solar radio bursts appeal to one or more of modulational instability, electrostatic (ES) decay processes, or stochastic growth physics to preserve the electron beam, limit the levels of Langmuir-like waves driven by the beam, and produce wave spectra capable of coupling nonlinearly to generate the observed radio emission. Theoretical constraints exist on the wavenumbers and relative sizes of the wave bandwidth and nonlinear growth rate for which Langmuir waves are subject to modulational instability and the parametric and random phase versions of ES decay. A constraint also exists on whether stochastic growth theory (SGT) is appropriate. These constraints are evaluated here using the beam, plasma, and wave properties (1) observed in specific interplanetary type III sources, (2) predicted nominally for the corona, and (3) predicted at heliocentric distances greater than a few solar radii by power-law models based on interplanetary observations. It is found that the Langmuir waves driven directly by the beam have wavenumbers that are almost always too large for modulational instability but are appropriate to ES decay. Even for waves scattered to lower wavenumbers (by ES decay, for instance), the wave bandwidths are predicted to be too large and the nonlinear growth rates too small for modulational instability to occur for the specific interplanetary events studied or the great majority of Langmuir wave packets in type III sources at arbitrary heliocentric distances. Possible exceptions are for very rare, unusually intense, narrowband wave packets, predominantly close to the Sun, and for the front portion of very fast beams traveling through unusually dilute, cold solar wind plasmas. Similar arguments demonstrate that the ES decay should proceed almost always as a random phase process rather than a parametric process, with similar exceptions. These results imply that it is extremely rare for modulational instability or parametric decay to proceed in type III sources at any heliocentric distance: theories for type III bursts based on modulational instability or parametric decay are therefore not viable in general. In contrast, the constraint on SGT can be satisfied and random phase ES decay can proceed at all heliocentric distances under almost all circumstances. (The contrary circumstances involve unusually slow, broad beams moving through unusually hot regions of the Corona.) The analyses presented here strongly justify extending the existing SGT-based model for interplanetary type III bursts (which includes SGT physics, random phase ES decay, and specific electromagnetic emission mechanisms) into a general theory for type III bursts from the corona to beyond 1 AU. This extended theory enjoys strong theoretical support, explains the characteristics of specific interplanetary type III bursts very well, and can account for the detailed dynamic spectra of type III bursts from the lower corona and solar wind.

Cairns, Iver H.↗
NASA NTRS1991

Simulation of the nonlinear evolution of electron plasma waves

Electrostatic waves driven by an electron beam in an ambient magnetized plasma were studied using a quasi-1D PIC simulation of electron plasma waves (i.e., Langmuir waves). The results disclose the presence of a process for moving wave energy from frequencies and wavenumbers predicted by linear theory to the Langmuir-like frequencies during saturation of the instability. A decay process for producing backward propagating Langmuir-like waves, along with low-frequency waves, is observed. The simulation results, however, indicate that the backscattering process is not the conventional Langmuir wave decay. Electrostatic waves near multiples of the electron plasma frequency are generated by wave-wave coupling during the nonlinear stage of the simulations, confirming the suggestion of Klimas (1983).

Nishikawa, K.-I.↗
NASA NTRS1985

Nonlinear astrophysical Alfven waves - Onset and outcome of the modulational instability

The nonlinear development of Alfven waves is numerically studied, with applications to Alfven waves in astrophysical plasmas. It is found that amplitude-modulated Alfven wave packets undergo a collapse instability in which the wave packets become more intense and of smaller spatial extent. The wave packet steepening is eventually halted in a process most aptly described as soliton formation. A simple analytic model based on the method of characteristics can account for many of the results of the numerical calculations. The instability probably cannot prevent particle pitch angle isotropization due to self-generated Alfven waves. Nonlinear effects of the collapse may modify the process by which energetic electrons are reaccelerated by plasma turbulence. The model calculations can semiquantitatively account for properties of shock-associated Alfven waves in the solar system.

Spangler, S. R.↗