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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Prediction of DIII-D Pedestal Structure from Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. An experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (ne) and electron temperature (Te) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (Ip), toroidal magnetic field (Bφ), neutral beam heating power (PNBI) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Prediction of DIII-D Pedestal Structure From Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. Here, an experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (n e ) and electron temperature (T e ) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (I p ), toroidal magnetic field (B Φ ), neutral beam heating power (P NBI ) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Experimental Analysis of Distribution Network Voltage Regulation Using Smart Inverters

Smart inverters (SIs) have demonstrated their potential to provide grid services for both transmission and distribution systems. One of these grid services, distribution network voltage regulation by SIs, has the potential to improve network voltage regulation through controlling the reactive and active power output of the SIs. Voltage regulation by SIs will be distributed and might be better suited to controlling local conditions to complement traditional voltage-regulating assets, e.g., tap-changing transformers, capacitor banks, and line voltage regulators. There is a gap in the literature on comparing the SI response characteristics when the SIs are controlled by a local controller or external control signals. This paper presents an experimental study to characterize SI reactive power regulation responses to two different control methods: autonomous control and remote dispatch. We found that SI reactive power regulation responses exhibit important differences between these methods in terms of delays and ramp rate. Finally, power-hardware-in-the-loop (PHIL) tests were conducted to evaluate the performance of these two methods. The PHIL test results show that the SI response characteristics for autonomous control and remote dispatch need to be considered when planning for distribution network voltage regulation using SIs.

autonomous control↗
DOE OSTI2023

Experimental Analysis of Distribution Network Voltage Regulation Using Smart Inverters: Preprint

Smart inverters (SI) have huge potential in providing grid services which has not been fully realized yet. One of these grid services, distribution network voltage regulation by SI, can improve the network voltage by regulating the SI reactive and active power output. Voltage regulation by SI is much faster compared to traditional voltage regulating devices, e.g. tap changing transformer, capacitor banks. However, there is gap in available published literature on the characteristics of SIs when the SI is controlled by local controller or external control signal. This paper presents the experimental study to characterize SI reactive power regulation response to two different control methods: autonomous control method and remote dispatch method. It was found that IS reactive power regulation response could be significantly different in terms of delay, and ramp rate for these two methods. Finally, Power-Hardware-in-The-Loop (PHIL) tests were conducted to evaluate the performance of these two methods. The PHIL tests results show that SI response characteristics for autonomous control method and remote dispatch method need to be considered during planning for distribution network voltage regulation using SI.

autonomous control↗
DOE OSTI2021

Suppression of MHD modes with active phase-control of probe-injected currents

Abstract Active phase-control of probe-injected current is shown to both suppress and amplify long-wavelength rotating magnetohydrodynamic instabilities in the HBT-EP tokamak. Four probes are connected in quadrature and energized to drive non-axisymmetric currents through the edge of the tokamak, creating magnetic perturbations comparable to previously-studied saturated kink modes or resonant magnetic perturbations that are generated by an external control coil array. Measurements of the magnetic perturbations from the probe-injected currents determine a set of current-carrying helical filaments used to model active feedback control of resistive wall modes. These experiments suggest current-injection feedback may be an effective alternative to external control coils for control of RWMs and other long-wavelength kink-like modes at the edge of tokamaks.

Physics↗
DOE OSTI2022

Control of internal transport barriers in magnetically confined tokamak burning plasmas

The initiation, termination, and control of internal transport barriers associated with E × B flow shear near local minima of magnetic shear are examined for burning plasmas to determine if the positive feedback loops between profiles, instability, transport, and flow shear operate in regimes with fusion self-heating. A five-field transport model for the evolution of profiles of density, ion and electron temperature, ion and electron fluctuations, and radial electric field is utilized to examine the efficacy of controls associated with external inputs of heat and particles, including neutral beam injection, RF, pellets, and gas puffing. The response of the plasma to these inputs is studied in the presence of self-heating. The latter is affected by the external inputs and their modification of profiles and is, therefore, not an external control. Provided sufficient external power is applied, internal transport barriers can be created and controlled, both in ion and electron channels. Barrier control is sensitive to the locations of power deposition and pellet ablation, as well as temporal sequencing of external inputs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Needed computations and computational capabilities for stellarators

Stellarator plasmas are externally controlled to a degree unparalleled by any other fusion concept, magnetic or inertial. This control is largely through the magnetic fields produced by external coils. The development of fusion energy could be expedited by carrying out remarkably straight-forward computations to define strategies for exploiting this external control. In addition to these computations, which have a reliability limited only by competence, certain physics areas that affect the development of stellarator power plants should have a more intense study. The low cost and speed with which computations can be carried out relative to experiments have implications for the development of fusion. Computations should be used to develop a strategy that to the extent possible allows major issues to be circumvented. Required computations for this strategy are the subject of this paper.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Synthetic Reference-based Transition Optimal Control of Inverter for Surge-Current-Free Rapid Interface to Grid

This article addresses the problem of the transition between objective functions in optimal control for power inverters when switching between standalone and grid-connected modes. The work proposes the use of a synthetic reference during the transition between the corresponding objective functions. Moreover, the authors aim to show that a transition function can be imposed and controlled externally from the main optimal control routine. In the end, the simulation results demonstrate the importance of properly applying the proposed strategy for a smooth transition between the operating modes with minimal surge current. These results contrast with the strategies found in the literature where the smooth transition comes with the price of a few grid cycles to sync.

Roig Greidanus, Mateo D.↗
DOE OSTI2020

Needle-Like Ferroelastic Domains in Individual Ferroelectric Nanoparticles

Superior structural, physical and electronic properties make ferroelectric nanocrystals essential in enabling a range of next-generation devices. Ferroelectric responses are determined by crystal structure and domain morphology. The ability to reversibly displace, create and annihilate elastic domains is critical to device applications. Whereas electric-field control has been demonstrated for ferroelectric 180° surface domain walls and vortices, similar control of ferroelastic domains and domain boundaries within individual nanocrystals remains challenging. Using controlled external compressive and tensile axial stress, deterministic and reversible control of highly mobile ferroelastic domains and axial polarization in three dimensions is demonstrated in this study. While many studies exist on ferroelastic domains in thin films and bulk, little is known about ferroelastic interactions at the single nanoparticle level, especially involving domain boundaries. Through combining Bragg coherent X-ray diffractive imaging and Landau theory, strain gradients in individual BaTiO3 nanocrystals are shown to stabilize needle-like ferroelastic twin domains. These domains are highly labile under applied axial stress, producing a locally enhanced electric polarization mediated by a ferroelectric phase transition. The efficacy of Bragg coherent X-ray diffractive imaging in studying in operando domains in three-dimensions is demonstrated, while synergy with theory provides a paradigm for domain boundary engineering and potential for nanoscale functional devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Bottom-up Approach to Improve the Representation of Deep Convective Clouds in Weather and Climate Models (Final Report)

A fundamental yet outstanding question about deep cumulus convection regards how convective updrafts, downdrafts, and surface-based cold pools are inter-related within organized storms, and how these three convective components are modulated by external and internal factors. We considered this question through numerical model simulations as well as data collected during the MC3E field campaign. One of our basic hypotheses was that deep cold pools are forced by wide downdrafts which arise from wide updrafts. This “bottom-up” perspective required consideration of the external controls on updraft width, and then the internal controls on cold-pool characteristics including depth. Model experiments showed that environmental vertical wind shear (an external factor) exerts a particularly strong control on updraft width; analyses of linear and nonlinear dynamic pressure forcing readily explain this control. The experiments also showed that increases in updraft width are accompanied by corresponding increases in downdraft width and cold-pool depth. The updraft–downdraft connection is through precipitation: the wide area of precipitation that will be initiated in a wide updraft will in turn lead to a wide downdraft. The downdraft–cold pool connection is through mass continuity: at the downdraft terminus, the large downdraft mass flux through a wide downdraft must lead to a deep cold pool. Model experiments also showed that the cold-pool depth and other characteristics can be significantly modulated by microphysical processes (internal factors). Specifically, the cold-pool expansion rate, depth, and intensity was found to depend most strongly on the amount of rain evaporation near the ground. However, the sustenance of the cold pool itself depended upon the downdrafts strengthened by sublimation of graupel higher in the storm. Finally, field campaign data revealed compelling inter-relationships between the cold-pool characteristics, and downdraft transience in terms of the microphysics. For example, pulses of hail and graupel (also internal factors) within downdrafts resulted in short-lived increases in the cold-pool depth. However, the cold-pool speed appeared to be relatively independent of the cold-pool depth and intensity, suggesting limitations of density current theory to convective cold pools in nature.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Photon-magnon coupling using gain-assisted spoof-localized surface plasmons

Improving the photon-magnon coupling strength can be done by tuning the structure of microwave resonators to better interact with the magnon counterpart. Planar resonators accommodating unconventional photon modes beyond the half- and quarter-wavelength designs have been explored due to their optimized mode profiles and potentials for on-chip integration. Here, we designed and fabricated an actively controlled ring resonator supporting the spoof localized surface plasmons (LSPs), and implemented it in the investigation of photon-magnon coupling for hybrid magnonic applications. We demonstrated gain-assisted photon-magnon coupling with the YIG magnon mode under several different sample geometries. The achieved coupling amplification largely benefits from the high quality factor (Q-factor) due to the additional gain provided by a semiconductor amplifier, which effectively increases the Q-factor from a nearly null state (passive resonance) to more than 1000 for a quadrupole LSP mode. Our results suggest an additional control knob for manipulating photon-magnon coupled systems exploiting external controls of gain and loss.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Variation of carrier density in semimetals via short-range correlation: A case study with nickelate NdNiO 2

Carrier density is one of the key controlling factors of material properties, particularly in controlling the essential correlations in strongly correlated materials. Typically, carrier density is externally tuned by doping or gating and remains fixed below room temperature. Strangely, the carrier density in correlated semimetals is often found to vary sensitively against weak external controls such as temperature, magnetic field, and pressure. Here, we develop a realistic simulation scheme that incorporates interatomic noncollinear magnetic correlation without a long-range order. Using the recently discovered nickelate superconductor as an example, we demonstrate a rather generic low-energy mechanism that in semimetals short-range correlation can reversely modulate the carrier density as well. Such a mutual influence between correlation and carrier density provides an extra ingredient for sensitive bifurcating behavior. This special feature of correlated semimetals explains their versatile carrier density at low energy and opens up new possibilities of functionalizing these materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Adaptive nonequilibrium design of actin-based metamaterials: Fundamental and practical limits of control

The adaptive and surprising emergent properties of biological materials self-assembled in far-from-equilibrium environments serve as an inspiration for efforts to design nanomaterials. In particular, controlling the conditions of self-assembly can modulate material properties, but there is no systematic understanding of either how to parameterize external control or how controllable a given material can be. Here, we demonstrate that branched actin networks can be encoded with metamaterial properties by dynamically controlling the applied force under which they grow and that the protocols can be selected using multi-task reinforcement learning. These actin networks have tunable responses over a large dynamic range depending on the chosen external protocol, providing a pathway to encoding “memory” within these structures. Interestingly, we obtain a bound that relates the dissipation rate and the rate of “encoding” that gives insight into the constraints on control—both physical and information theoretical. Taken together, these results emphasize the utility and necessity of nonequilibrium control for designing self-assembled nanostructures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Singular Perturbation-Based Large-Signal Order Reduction of Microgrids for Stability and Accuracy Synthesis With Control

The increasing penetration of distributed energy resources (DERs) highlights the growing importance of microgrids (MGs) in enhancing power system reliability. Employing electromagnetic transient (EMT) analysis in MGs becomes crucial for controlling the rapid transients. However, this requires an accurate but high-order model of power electronics and their underlying control loops, complexifying the stability analysis from the viewpoint of a higher control level. To overcome these challenges, this paper proposes a large-signal order reduction (LSOR) method for MGs with considerations of external control inputs and the detailed dynamics of underlying control levels based on singular perturbation theory (SPT). Specially, we innovatively proposed and strictly proved a general stability and accuracy assessment theorem that allows us to analyze the dynamic stability of a full-order nonlinear system by only leveraging our derived reduced-order model (ROM) and boundary layer model (BLM). Furthermore, this theorem furnishes a set of conditions that determine the accuracy of the developed ROM. Lastly, by embedding such a theorem into the SPT, we propose a novel LSOR approach with guaranteed accuracy and stability analysis equivalence. Case studies are conducted on MG systems to show the effectiveness of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Next-Cycle Optimal Fuel Control for Cycle-to-Cycle Variability Reduction in EGR-Diluted Combustion

In this simulation study, cycle-to-cycle fuel control was used to reduce CCV by injecting additional fuel in operating conditions with sporadic misfires and partial burns. An optimal control policy was proposed that utilizes 1) a physics-based model that tracks in-cylinder gas composition and 2) a one-step-ahead prediction of the combustion efficiency based on a kernel density estimator. The optimal solution, however, presents a tradeoff between the reduction in combustion CCV and the increase in fuel injection quantity required to stabilize the charge. Such a tradeoff can be ad- just by a single parameter embedded in the cost function.

Maldonado, BryanP. [Oak Ridge National Lab. (ORNL)↗
DOE OSTI2021

Quantum optimal control for pure-state preparation using one initial state

This paper presents a framework for solving the pure-state preparation problem using numerical optimal control. As an example, we consider the case where a number of qubits are dispersively coupled to a readout cavity. Herein, we model open system quantum dynamics using the Markovian Lindblad master equation driven by external control pulses. The main result of this paper develops a basis of density matrices (a parameterization) where each basis element is a density matrix by itself. Utilizing a specific objective function, we show how an ensemble of the basis elements can be used as a single initial state throughout the optimization process—independent of the system dimension. We apply the general framework to the specific application of ground-state reset of one and two qubits coupled to a readout cavity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Chemical Control of Symmetry and Bandgap in Tungsten Oxyhalide van der Waals Semiconductors

Tunability in solid-state materials is essential for testing theory, discovering quantum phases, and enabling functionality. Layered van der Waals (vdW) semiconductors offer a unique platform, providing new degrees of freedom at the two-dimensional (2D) limit through exfoliation and external controls. Here, in this study, we demonstrate tunability of symmetry and electronic structure via halogen substitution in a family of layered vdW tungsten oxyhalides. Substituting the halogens in WO 2 X 2 (X = I, Br, Cl) tunes the bandgap across a broad energy range and modifies the structural symmetry from centrosymmetric to noncentrosymmetric. By alloying WO 2 I 2– y Br y , we continuously tune the polar distortion and optical gap across the visible range. These insights into halogen substitution effects on symmetry and electronic structure lay the foundation for new tunable vdW semiconductors for optoelectronics and nonlinear optics.

36 MATERIALS SCIENCE↗