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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Trapped-ion quantum simulation of collective neutrino oscillations

It is well known that the neutrino flavor in extreme astrophysical environments changes under the effect of three contributions: the vacuum oscillation, the interaction with the surrounding matter, and the collective oscillations due to interactions between different neutrinos. The latter adds a nonlinear contribution to the equations of motion, making the description of their dynamics complex. In this work we study various strategies to simulate the coherent collective oscillations of a system of N neutrinos in the two-flavor approximation using quantum computation. This was achieved by using a pair-neutrino decomposition designed to account for the fact that the flavor Hamiltonian, in the presence of the neutrino-neutrino term, presents an all-to-all interaction that makes the implementation of the evolution dependent on the qubit topology. We analyze the Trotter error caused by the decomposition demonstrating that the complexity of the implementation of time evolution scales polynomially with the number of neutrinos and that the noise from near-term quantum device simulation can be reduced by optimizing the quantum circuit decomposition and exploiting a full-qubit connectivity. We find that the gate complexity using second order Trotter-Suzuki formulas scales better with system size than with other decomposition methods such as quantum signal processing. In conclusion, we finally present the application and the results of our algorithm on a real quantum device based on trapped-ion qubits.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Quantum Squeezing and Sensing with Pseudo-Anti-Parity-Time Symmetry

The emergence of parity-time (PT) symmetry has greatly enriched our study of symmetry-enabled non-Hermitian physics, but the realization of quantum PT symmetry faces an intrinsic issue of unavoidable symmetry-breaking Langevin noises. Here we construct a quantum pseudo-anti-PT (pseudo-APT) symmetry in a two-mode bosonic system without involving Langevin noises. We show that the spontaneous pseudo-APT symmetry breaking leads to an exceptional point, across which there is a transition between different types of quantum squeezing dynamics; i.e., the squeezing factor increases exponentially (oscillates periodically) with time in the pseudo-APT-symmetric (broken) region. Such dramatic changes of squeezing factors and quantum dynamics near the exceptional point are utilized for ultraprecision quantum sensing. These exotic quantum phenomena and sensing applications can be experimentally observed in two physical systems: spontaneous wave mixing nonlinear optics and atomic Bose-Einstein condensates. Furthermore, our Letter offers a physical platform for investigating exciting APT symmetry physics in the quantum realm, paving the way for exploring fundamental quantum non-Hermitian effects and their quantum technological applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Solving Eco-Driving Problems Using Indirect Collocation Method and Smooth Representation

Here, we discuss the eco-driving problem, considering both electric and conventional powertrains, and presents a pathway to solving it numerically using an indirect collocation method. Despite the low-order system dynamics, the piecewise fuel/efficiency map, gear shifting, and real-world traffic/road situations bring system discontinuities/switchings and pure state constraints into the problem formulation, which make the problem highly nonlinear and nontrivial to solve. This letter introduces smooth approximations to convert the original problem to an unconstrained (and penalized) smooth boundary-value problem. This approach eliminates the discussion of the switching structure and leads to a lightweight Newton-method-based solution procedure.

42 ENGINEERING↗
DOE OSTI2026

Neural operator transformers capture bifurcating drift-wave turbulence in fusion plasma simulations

Self-consistent modeling of turbulence-driven transport is critical for optimizing confinement in magnetically confined fusion plasmas, such as tokamaks and stellarators. In particular, capturing the long-term co-evolution of turbulence, flow, and background plasma profiles remains computationally challenging. Direct numerical simulation of these multiscale, highly nonlinear processes is often demanding and impractical for real-time control or design optimization. To address this bottleneck, we investigate transformer-based neural operator partial differential equation surrogates for emulating the dynamics of drift-wave turbulence bifurcation mediated by zonal flows, using the modified Hasegawa–Wakatani (MHW) model as a prototypical system. We find that the finetuned neural operator model has excellent performance in capturing the multi-spatiotemporal-scales of MHW turbulence bifurcation and is robust to testing on rare and out-of-distribution dynamics. Specifically, we demonstrate that a single unified model accurately predicts both quasi-steady-state turbulence and a wide range of dynamical transition processes, such as nonlinear saturation, spontaneous suppression of turbulence, and the emergence of macroscopic zonal flows, over time horizons vastly exceeding the local turbulence correlation time. This computationally efficient approach establishes a strong foundation for fast, AI-based modeling of complex, multiscale phenomena in magnetized fusion plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Nonlinear solution of classical three-wave interaction via finite-dimensional quantum model

The quantum three-wave interaction, the lowest-order nonlinear interaction in plasma physics, describes energy–momentum transfer between three resonant waves in the quantum regime. We describe how it may also act as a finite-degree-of-freedom approximation to the classical three-wave interaction in certain circumstances. By promoting the field variables to operators, we quantize the classical system, show that the quantum system has more free parameters than the classical system and explain how these parameters may be selected to optimize either initial or long-term correspondence. We then numerically compare the long-time quantum–classical correspondence far from the fixed point dynamics. We discuss the Poincaré recurrence of the system and the mitigation of quantum scrambling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

A symbolic framework to obtain mid-fidelity models of flexible multibody systems with application to horizontal-axis wind turbines

Abstract. The article presents a symbolic framework (also called computer algebra program) that is used to obtain, in symbolic mathematical form, the linear and nonlinear equations of motion of a mid-fidelity multibody system including rigid and flexible bodies. Our approach is based on Kane's method and a nonlinear shape function representation for flexible bodies. The shape function approach does not represent the state of the art for flexible multibody dynamics but is an effective trade-off to obtain mid-fidelity models with few degrees of freedom, taking advantage of the separation of space and time. The method yields compact symbolic equations of motion with implicit account of the constraints. The general and automatic framework facilitates the creation and manipulation of models with various levels of complexity by adding or removing degrees of freedom. The symbolic treatment allows for analytical gradients and linearized equations of motion. The linear and nonlinear equations can be exported to Python code or dedicated software. There are multiple applications, such as time domain simulation, stability analyses, frequency domain analyses, advanced controller design, state observers, and digital twins. In this article, we describe the method we used to systematically generate the equations of motion of multibody systems and present the implementation of the framework using the Python package SymPy. We apply the framework to generate illustrative land-based and offshore wind turbine models. We compare our results with OpenFAST simulations and discuss the advantages and limitations of the method. The Python implementation is provided as an open-source project.

Branlard, Emmanuel (ORCID:0000000277506128)↗
DOE OSTI2022

Mesoscopic-scale complexity in macroscopically-uniform plastic flow of an Al 0.3 CoCrFeNi high-entropy alloy

The concept of a smooth and homogeneous plastic flow of solids is nowadays constantly challenged by various observations of the self-organization of crystal defects on mesoscopic scales pertaining, e.g., to acoustic emission or the evolution of the local strain field. Such investigations would be of particular interest for High-Entropy Alloys (HEAs) characterized by extremely complex microstructures. However, the complexity of their deformation has been only studied in relation to the jerky flow. The present work explores a mesoscale complexity of the macroscopically-smooth plastic flow of an Al 0.3 CoCrFeNi alloy. Here, an inclusive approach involving various experimental methods and complementary nonlinear analyses allowed to reveal transitions between distinct dynamical regimes, which may be assimilated with noises of different colors, in particular the blue noise that is rarely observed in complex systems, and various kinds of reddened behavior. Such findings provide significant new insights into the micro/macro transition in the deformation behavior of HEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ultrastrong magnon-magnon coupling and chiral spin-texture control in a dipolar 3D multilayered artificial spin-vortex ice

Strongly-interacting nanomagnetic arrays are ideal systems for exploring reconfigurable magnonics. They provide huge microstate spaces and integrated solutions for storage and neuromorphic computing alongside GHz functionality. These systems may be broadly assessed by their range of reliably accessible states and the strength of magnon coupling phenomena and nonlinearities. Increasingly, nanomagnetic systems are expanding into three-dimensional architectures. This has enhanced the range of available magnetic microstates and functional behaviours, but engineering control over 3D states and dynamics remains challenging. Here, we introduce a 3D magnonic metamaterial composed from multilayered artificial spin ice nanoarrays. Comprising two magnetic layers separated by a non-magnetic spacer, each nanoisland may assume four macrospin or vortex states per magnetic layer. This creates a system with a rich 16 N microstate space and intense static and dynamic dipolar magnetic coupling. The system exhibits a broad range of emergent phenomena driven by the strong inter-layer dipolar interaction, including ultrastrong magnon-magnon coupling with normalised coupling rates of $\frac{Δf}{v}$ = 0.57, GHz mode shifts in zero applied field and chirality-control of magnetic vortex microstates with corresponding magnonic spectra.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

AI-Based EMT Dynamic Model of PV Systems

Several electromagnetic transient (EMT) dynamic modeling methods are available to model systems like photovoltaic (PV) plants, wind power plants, variable-speed drives, among others. The methods include: (a) physics-based models and (b) data-driven models. The physics-based dynamic models may include high-fidelity switched system model and average-value model that both require the control algorithms included in the models. However, manufacturers typically prefer to provide black-box models to avoid disclosing proprietary. One of the solutions to prevent disclosing control algorithms is the use of data-driven dynamic EMT models of PV systems. In this paper, data-driven dynamic EMT model based on artificial intelligence (AI) algorithms are presented. The AI algorithms evaluated include convolutional neural networks, recurrent neural networks, and nonlinear auto-regressive exogenous model. Automation in generating data and training these models is also discussed in this paper. The results generated by the best AI algorithms have been observed to be greater than 95 % accurate.

Debnath, Suman↗
DOE OSTI2022

Data-driven Resilience Characterization of Control Dynamical Systems

In this paper, we define and quantify resiliency of a power network and propose data-driven algorithms for computing the same for the power grid. To do this, we use the Koopman operator framework to lift the controlled dynamical system to an abstract (possibly higher) dimensional space, where the evolution is linear. The linear system representation allows us to relate small time local controllability and observability of a general nonlinear control system to the controllability and observability of the lifted linear system. Finally, we define the resiliency of the underlying power grid in terms of the controllability and observability gramians of the lifted linear system. We illustrate the proposed approach to compute the resiliency metrics on time-series data obtained from a microgrid.

koopman operator, resilience, control↗
DOE OSTI2022

Effect of injected flux and current temporal phasing on self-organization in the HIT-SI3 experiment

The HIT-SI3 device at the University of Washington uses three oscillating inductive helicity injectors to form and sustain spheromak plasma equilibria. By adjusting the temporal phase of the injector waveforms with respect to each other, the toroidal spectrum of the imposed perturbations can be controlled. Using a recently implemented GPU-based control system, the available mode spectra were explored experimentally by scanning the space of relative injector phasing. In this space, significant variation in the toroidal mode spectrum ($n$ = 1, 2, 3) of the perturbations was observed. Additionally, variation in characteristics of driven equilibria was also observed, including a ≈ $30$% range in toroidal current gain ($I$ $Φ$ / $I$ $Inj$ ). Experimental results are compared with both a composite-equilibria and nonlinear dynamic model, including extended MHD simulations using the NIMROD code and composite Taylor state equilibria computed using the PSI-Tet code. In conclusion, qualitative agreement is seen with the nonlinear models, but not with composite-equilibria models, suggesting the use of nonlinear models to better capture observed plasma dynamics and provide predictive use for future experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Transmission spectroscopy of CF 4 molecules in intense x-ray fields

The nonlinear interaction of x rays with matter is at the heart of understanding and controlling ultrafast molecular dynamics from an atom-specific viewpoint, providing new scientific and analytical opportunities to explore the structure and dynamics of small quantum systems. At increasingly high x-ray intensity, the sensitivity of ultrashort x-ray pulses to specific electronic states and emerging short-lived transient intermediates is of particular relevance for our understanding of fundamental multiphoton absorption processes. In this work, intense x-ray free-electron laser (XFEL) pulses at the European XFEL are combined with a gas cell and grating spectrometer for a high-intensity transmission spectroscopy study of multiphoton-induced ultrafast molecular fragmentation dynamics in CF 4 . This approach unlocks the direct intrapulse observation of transient fragments, including neutral atoms, by their characteristic absorption lines in the transmitted broadband x-ray spectrum. The dynamics with and without initially producing fluorine 𝐾-shell holes are studied by tuning the central photon energy. The absorption spectra are measured at different FEL intensities to observe nonlinear effects. Transient isolated fluorine atoms and ions are spectroscopically recorded within the ultrashort pulse duration of a few tens of femtoseconds. An isosbestic point that signifies the correlated transition between intact neutral CF 4 molecules and charged atomic fragments is observed near the fluorine 𝐾 edge. The dissociation dynamics and the multiphoton absorption-induced dynamics encoded in the spectra are theoretically interpreted. Overall, this study demonstrates the potential of high-intensity x-ray transmission spectroscopy to study ultrafast molecular dynamics with sensitivity to specific intermediate species and their electronic structure.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Nonlinear Lifshitz photon theory in condensed matter systems

We present an interacting theory of a U(1) gauge boson with a quadratic dispersion relation, which we call the "nonlinear Lifshitz photon theory.'' The Lifshitz photon is a three-dimensional generalization of the Tkachenko mode in rotating superfluids. Starting from the Wigner crystal of charged particles coupled to a dynamical U(1) gauge field, after integrating out gapped degrees of freedom, we arrive at the Lagrangian for the nonlinear Lifshitz photon. The symmetries of the theory include a global U(1) 1-form symmetry and nonlinearly realized "magnetic" translation and rotation symmetries. The interaction terms in the theory lead to the decay of the Lifshitz photon, the rate of which we estimate. We show that the Wilson loop, which plays the role of the order parameter of the spontaneous breaking of the 1-form global symmetry, deviates from the perimeter law by an additional logarithmic factor. Here, we explore potential connections to other condensed matter systems, with a particular focus on quantum spin ice and ferromagnets. Finally, we generalize our theory to higher dimensions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Utilizing CellBox to Describe Varied Dynamical Systems

CellBox is a hybrid modeling framework that integrates machine-learning approaches with explicit mathematical modeling to determine the behavior of dynamical systems, intended for determining the complex interactions of molecule and phenotype within a cellular environment using perturbation/response-based data. The original work utilized analysis of a melanoma cell line, SK-Mel-133, which we sought to expand to and evaluate effectiveness in describing other nonlinear systems both within and outside of biology. We evaluated with two models. One model is based upon the free-fall of an object under a velocity-dependent drag force; this produced inherent perturbation/response data. The other model is based upon a form of mass-action molecular kinetics; for this, we ran the simulation to steady state in each species for each perturbation and select the steady state as input for CellBox. We determined that CellBox, outside of its original use case, can still strongly predict even non-biological dynamical systems in the small-perturbation regime, with r = 0.99977 to 0.85123, p < 0.05 for freefall. However, CellBox cannot accurately predict behavior within large-perturbation regimes, p >> 0.05 for freefall. In addition, we performed a naïve comparison of CellBox network structure to known network structure in the mass-action model to assess accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Response of Sulfonated Polystyrene Melts to Nonlinear Elongation Flows

Ionizable polymers form dynamic networks with domains controlled by two distinct energy scales, ionic interactions and van der Waals forces; both evolve under elongational flows during their processing into viable materials. A molecular level insight of their nonlinear response, paramount to controlling their structure, is attained by fully atomistic molecular dynamics simulations of a model ionizable polymer, polystyrene sulfonate. As a function of increasing elongational flow rate, the systems display an initial elastic response, followed by an ionic fraction-dependent strain hardening, stress overshoot, and eventually strain-thinning. As the sulfonation fraction increases, the chain elongation becomes more heterogeneous. Finally, flow-driven ionic assembly dynamics that continuously break and reform control the response of the system.

36 MATERIALS SCIENCE↗
DOE OSTI2021

EXPERIMENTAL STUDIES OF NONLINEAR INTEGRABLE OPTICS

State-of-the-art accelerators at energy and intensity frontiers require increasingly bright and powerful particle beams. In conventional linear lattices, intense beams suffer from collective instabilities, resulting in beam losses and maximum beam intensity limits. This thesis presents experimental studies of a novel lattice design concept, the nonlinear integrable optics (NIO), aimed at enhancing beam stability limits with little to no beam dynamics degradation. Single-particle beam dynamics measurements of two NIO devices, the quasi-integrable octupole system and the fully integrable Danilov-Nagaitsev system, were carried out at the purpose-built Integrable Optics Test Accelerator (IOTA) at Fermilab. Their simulation, hardware design, and commissioning process are presented. Extensive model and analysis algorithm development and benchmarking is described. Electron beam data from two scientific runs is analyzed, yielding frequency and phase space dynamics consisten t with m odels. These results demonstrate viability and advantages of the NIO design, providing the groundwork for proton studies in the strong space-charge regime and future integrable accelerators.

Kuklev, Nikita↗
DOE OSTI2024

Frequency Support From Electric Vehicles for Advancing Renewable Energy Integration

The integration of renewable energy resources (RERs) in the modern power grid is increasing rapidly because of aggressive decarbonization goals, lower costs, and increased government investment. However, higher penetrations of inverter-based generation can lead to frequency stability issues because of reduced system inertia. This paper develops a framework for quantifying the contribution of electric vehicles (EVs) toward providing frequency support to the grid and thus increasing the penetration limit of renewable energy resources (RERs). EVs are considered to provide both inertial response and primary frequency response support to the grid. A stochastic approach incorporating the uncertainties associated with the behavior of EVs is developed to derive the discharge limit of EV aggregators. A multi-machine system frequency response (MM-SFR) model is developed, which incorporates the dynamic virtual inertia and droop coefficients of EV aggregators derived from the EV control modules. Frequency security constraints are developed from this MM-SFR model, which, along with the converter voltage security and low voltage ride-through constraints, are integrated within a nonlinear optimization framework to determine the RER integration limit. Here, the efficacy of the proposed approach is validated using the RTS-GMLC test system.

25 ENERGY STORAGE↗
DOE OSTI2020

Model-Agnostic Algorithm for Real-Time Attack Identification in Power Grid using Koopman Modes

Malicious activities on measurements from sensors like Phasor Measurement Units (PMUs) can mislead the control center operator into taking wrong control actions resulting in disruption of operation, financial losses, and equipment damage. In particular, false data attacks initiated during power systems transients caused due to abrupt changes in load and generation can fool the conventional model-based detection methods relying on thresholds comparison to trigger an anomaly. In this paper, we propose a Koopman mode decomposition (KMD) based algorithm to detect and identify false data attacks in real-time. The Koopman modes (KMs) are capable of capturing the nonlinear modes of oscillation in the transient dynamics of the power networks and reveal the spatial embedding of both natural and anomalous modes of oscillations in the sensor measurements. The Koopman-based spatio-temporal nonlinear modal analysis is used to filter out the false data injected by an attacker. The performance of the algorithm is illustrated on the IEEE 68-bus test system using synthetic attack scenarios generated on GridSTAGE, a recently developed multivariate spatio-temporal data generation framework for simulation of adversarial scenarios in cyber-physical power systems.

Nandanoori, Sai Pushpak↗