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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Missing Wedge Completion via Unsupervised Learning with Coordinate Networks

Cryogenic electron tomography (cryoET) is a powerful tool in structural biology, enabling detailed 3D imaging of biological specimens at a resolution of nanometers. Despite its potential, cryoET faces challenges such as the missing wedge problem, which limits reconstruction quality due to incomplete data collection angles. Recently, supervised deep learning methods leveraging convolutional neural networks (CNNs) have considerably addressed this issue; however, their pretraining requirements render them susceptible to inaccuracies and artifacts, particularly when representative training data is scarce. To overcome these limitations, we introduce a proof-of-concept unsupervised learning approach using coordinate networks (CNs) that optimizes network weights directly against input projections. This eliminates the need for pretraining, reducing reconstruction runtime by 3–20× compared to supervised methods. Our in silico results show improved shape completion and reduction of missing wedge artifacts, assessed through several voxel-based image quality metrics in real space and a novel directional Fourier Shell Correlation (FSC) metric. Our study illuminates benefits and considerations of both supervised and unsupervised approaches, guiding the development of improved reconstruction strategies.

42 ENGINEERING↗
DOE OSTI2022

Dynamic Economic Dispatch Considering Transmission–Distribution Coordination and Automatic Regulation Effect

With the rapid increase of renewable energy sources, the variability and uncertainty in power systems are significantly increased, and the power system operation is facing more and more challenges. In the traditional dynamic economic dispatch (DED) of transmission systems, the frequency and voltage regulation effects are not actively utilized. In addition, the transmission systems and distribution systems are optimized separately; the transmission–distribution coordination effect is not considered. In this article, a new DED is proposed. The optimal scheduling results are obtained by making a balance between operating cost and reliability cost. Both the automatic regulation effect and transmission–distribution coordination effect are explored and exploited in terms of the equivalent reserve, which can reduce the reserve provided by generating units, and can further enhance the security and economics of power system operation. The validity and effectiveness of the proposed model are illustrated by case studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

A CPS Based Optimal Operational Control System for Fused Magnesium Furnace

Fused magnesia smelting for fused magnesium furnace (FMF) is an energy intensive process with high temperature and comprehensive complexities. Its operational index namely energy consumption per ton (ECPT) is defined as the consumed electrical energy per ton of acceptable quality and is difficult to measure online. Moreover, the dynamics of ECPT cannot be precisely modelled mathematically. The model parameters of the three-phase currents of the electrodes such as the molten pool level, its variation rate and resistance are uncertain and nonlinear functions of the changes in both the smelting process and the raw materials composition. In this paper, an integrated optimal operational control algorithm proposed is composed of a current set-point control, a current switching control and a self-optimized tuning mechanism. The tight conjoining of and coordination between the computational resources including the integrated optimal operational control, embedded software, industrial cloud, wireless communication and the physical resources of FMF constitutes a cyber-physical system (CPS) based embedded optimal operational control system. Successful application of this system has been made for a production line with ten fused magnesium furnaces in a factory in China, leading to a significant reduced ECPT.

Cyber-Physical Systems↗
DOE OSTI2018

Photoluminescent properties and Judd–Ofelt analysis of novel Na0.5Sr0.25NbO3: Eu3+ red phosphor with high quantum efficiency

Highlights: • The Na{sub 0.5}Sr{sub 0.25}NbO{sub 3}: Eu{sup 3+} phosphor with high quantum efficiency has been successfully synthesized by using a molten salt synthesis method. • The effect of the crystal field surrounding the Eu{sup 3+} ions on the luminescent performance was analyzed by the Judd–Ofelt theory. • Photoluminescent properties of Na{sub 0.5}Sr{sub 0.25}NbO{sub 3}: Eu{sup 3+} phosphor were investigated for the first time. - Abstract: We report on a novel Na{sub 0.5}Sr{sub 0.25}NbO{sub 3}: Eu{sup 3+} phosphor fabricated by a molten salt synthesis method with the potential application in white light-emitting diodes (WLEDs) as a red phosphor. The crystal structure, morphology, emission/excitation spectra, as well as decay curves were characterized with X-ray diffraction, Scanning Electron Microscope and photoluminescence spectrometer, respectively. Concentration quenching occurred when the concentration of Eu{sup 3+} was beyond 5 mol% due to the dipole-dipole interaction by nonradiative energy transfer. Besides, the effect of the crystal field surrounding the Eu{sup 3+} ions on the luminescent performance under 396 nm and 466 nm excitions has been investigated by the Judd–Ofelt theory. The result indicated that the quantum efficiency of the phosphor was 62.65% excited by 466 nm, which was superior to 41.43% excited by 396 nm. The optimal sample’s CIE coordinates were (0.6471, 0.3504) with the color purity of 97%, showing a potential application in (WLEDs) illumination field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Optimized structure and electronic band gap of monolayer GeSe from quantum Monte Carlo methods

Here, we have used highly accurate quantum Monte Carlo methods to determine the chemical structure and electronic band gaps of monolayer GeSe. Two-dimensional (2D) monolayer GeSe has received a great deal of attention due to its unique thermoelectric, electronic, and optoelectronic properties with a wide range of potential applications. Density functional theory (DFT) methods have usually been applied to obtain optical and structural properties of bulk and 2D GeSe. For the monolayer, DFT typically yields a larger band-gap energy than for bulk GeSe but cannot conclusively determine if the monolayer has a direct or indirect gap. Moreover, the DFT-optimized lattice parameters and atomic coordinates for monolayer GeSe depend strongly on the choice of approximation for the exchange-correlation functional, which makes the ideal structure-and its electronic properties-unclear. In order to obtain accurate lattice parameters and atomic coordinates for the monolayer, we use a surrogate Hessian-based parallel line search within diffusion Monte Carlo to fully optimize the GeSe monolayer structure. The DMC-optimized structure is different from those obtained using DFT, as are calculated band gaps. The potential energy surface has a shallow minimum at the optimal structure. This, combined with the sensitivity of the electronic structure to strain, suggests that the optical properties of monolayer GeSe are highly tunable by strain.

36 MATERIALS SCIENCE↗
DOE OSTI2017

A new relativistic viscous hydrodynamics code and its application to the Kelvin–Helmholtz instability in high-energy heavy-ion collisions

Here, we construct a new relativistic viscous hydrodynamics code optimized in the Milne coordinates. We also split the conservation equations into an ideal part and a viscous part, using the Strang spitting method. In the code a Riemann solver based on the two-shock approximation is utilized for the ideal part and the Piecewise Exact Solution (PES) method is applied for the viscous part. Furthemore, we check the validity of our numerical calculations by comparing analytical solutions, the viscous Bjorken’s flow and the Israel–Stewart theory in Gubser flow regime. Using the code, we discuss possible development of the Kelvin–Helmholtz instability in high-energy heavy-ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

NLC ZDR: Zero Order Design Report for the NEXT Linear Collider (Volume 1)

This “Zeroth-Order Design Report” (ZDR) for the Next Linear Collider (NLC) is being created at a time of both great opportunity and uncertainty in the future directions that will be taken by the world-wide community of high-energy physics. There is exciting news that the Large Hadron Collider project has been approved for construction at CERN, and the planned involvement by physicists and engineers from countries around the globe will make this the first accelerator to be designed and built by a truly world-wide collaboration. By contrast, the cancellation of the SSC has demonstrated the necessity of international collaboration on such large scientific projects. The community of scientists and engineers at work on the accelerator physics and technologies of high-energy electron-positron colliders has recognized this need, and has made concerted effort to coordinate research activities to optimize our combined understanding and knowledge. This ZDR is one further step in this process.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

NLC ZDR: Zero Order Design Report for the NEXT Linear Collider (Volume 2)

This “Zeroth-Order Design Report” (ZDR) for the Next Linear Collider (NLC) is being created at a time of both great opportunity and uncertainty in the future directions that will be taken by the world-wide community of high- energy physics. There is exciting news that the Large Hadron Collider project has been approved for construction at CERN, and the planned involvement by physicists and engineers from countries around the globe will make this the first accelerator to be designed and built by a truly world-wide collaboration. By contrast, the cancellation of the SSC has demonstrated the necessity of international collaboration on such large scientific projects. The community of scientists and engineers at work on the accelerator physics and technologies of high-energy electron-positron colliders has recognized this need, and has made concerted effort to coordinate research activities to optimize our combined understanding and knowledge. This ZDR is one further step in this process.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Quantum Computing in Next-Generation Transportation Optimization

We explore how quantum computing (QC) can advance transportation optimization, with a focus on two high-impact areas: traffic signal control and vehicle electrification with grid integration. As transportation systems grow in complexity, classical optimization methods increasingly struggle to deliver scalable and efficient solutions, particularly for real-time, data-rich environments. This work identifies key challenges within these two domains where QC may offer advantages, particularly in handling combinatorial decision spaces and dynamic constraints. We begin by outlining the limitations of classical approaches for traffic signal control optimization and electric vehicle charging coordination, highlighting where computational limitations arise. Previous quantum formulations are presented and new formulations are proposed to demonstrate how emerging quantum algorithms, including quantum annealing and the Quantum Approximation Optimization Algorithm, could be leveraged to reformulate and address these problems. We also evaluate the suitability of current quantum hardware and discuss recent trends that indicate when QC may become a viable tool for transportation applications. While acknowledging the present limitations of QC technologies, this poster emphasizes the importance of preparing quantum-compatible models today. By reviewing and establishing formulations that align with the strengths of quantum algorithms, researchers and practitioners can better position themselves to take advantage of QC advancements as they occur. This work aims to provide a practical, forward-looking perspective on the near-term potential of quantum computing in transportation optimization.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Integrated Coordination of Voltage Regulators with Distributed Cooperative Inverter Control in Systems with High Penetration of DGs

Increased penetration of distributed generation (DG) in recent years has a significant impact on operation and control of power systems. One of the main issues with the increased penetration of DGs is the effect of voltage rise. This paper investigates integration of coordinated voltage regulator (VRs) operation with cooperative distributed inverter control to maintain voltages in appropriate limits in distribution systems with high penetration of DGs. The coordinated VR control is used to optimize the settings of multiple nested VRs while the cooperative distributed control optimally dispatches reactive power of the DGs. The integrated approach is compared with the case without coordinated VRs control (uncoordinated local control). Simulation results illustrate the effective performance of the proposed method to achieve unified voltage profile.

coordinated voltage regulator control↗
DOE OSTI2021

Outcomes and Insights From Simplified Analytic Trajectory Optimization for a Tethered Underwater Kite

This letter formulates and solves a periodic trajectory optimization problem for a tethered underwater kite. The goal is to maximize the average mechanical power harvested by the kite. The type of kite considered in this letter extracts electricity from ocean currents by moving cross-current as its reel away from its base station, and consumes electricity to reel back. The problem of optimizing this kite’s trajectory is challenging due to the high dimensionality and nonlinearity of its dynamics. To tackle this challenge, the literature often separates the problem into two subproblems focusing on optimizing the cross-current and the reel-in/reel-out components of the trajectory, respectively, which may be sub-optimal. In contrast, this letter solves for the combined cross-current and reel-in/reel-out trajectory by linearizing the dynamics of the kite around a zero-power reference equilibrium trajectory in spherical coordinates. This allows the trajectory optimization problem to be solved analytically for simple sinusoidal input perturbations from equilibrium. Here we use linear quadratic regulation to enable the nonlinear kite model to track the optimized trajectory. The result is a computationally efficient approach that achieves an attractive Loyd factor of 19.9%, while providing important insights into the nature of the optimal trajectory.

42 ENGINEERING↗
DOE OSTI2019

Coordination of Behind-the-Meter Energy Storage and Building Loads: Optimization with Deep Learning Models*

With the increasing penetration of renewable energy systems and energy storage systems in buildings, it is critical to optimize system operation. In this paper, we develop an optimization strategy to minimize the operation cost as well as maintain indoor thermal comfort, for a building integrated with battery and PV. A Recurrent Neural Network (RNN) is used to predict building thermal load and zone temperatures. A black-box optimization algorithm known as nonlinear optimization by mesh adaptive direct search (NOMADS) is employed in simulation to provide look-ahead optimal battery dispatch and zone temperature set-point schedules so that the operation cost is minimized. Field data collected from a medium sized office building at Pacific Northwest National Laboratory (PNNL) integrated with Photovoltaic (PV) system model and battery storage system model is used to demonstrate the proposed methodology. Compared with rule based methods, the optimization strategy obtained a lower cost of operation while satisfying comfort constraints.

Chen, Yimin↗
DOE OSTI2023

Coordination Stoichiometry Effects on the Binding Hierarchy of Histamine and Imidazole–M 2+ Complexes

Histidine–M 2+ coordination bonds are a recognized bond motif in biogenic materials with high hardness and extensibility, which has led to growing interest in their use in soft materials for mechanical function. However, the effect of different metal ions on the stability of the coordination complex remains poorly understood, complicating their implementation in metal-coordinated polymer materials. Herein, rheology experiments and density functional theory calculations are used to characterize the stability of coordination complexes and establish the binding hierarchy of histamine and imidazole with Ni 2+ , Cu 2+ , and Zn 2+ . It is found that the binding hierarchy is driven by the specific affinity of the metal ions to different coordination states, which can be macroscopically tuned by changing the metal-to-ligand stoichiometry of the metal-coordinated network. These findings facilitate the rational selection of metal ions for optimizing the mechanical properties of metal-coordinated materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Communication-Constrained Robust Control and Learning of Grid-Connected

The electric grid of things (EGoT) promises great potential for innovative grid services by tapping into vast load flexibility. However, the unique characteristics of EGoT, being a part of the cyber-physical electric power system, present both opportunities and challenges, especially concerning supply-demand balancing, stability, and communication constraints. Traditionally, centralized control was employed to ensure balance and stability in power systems. However, with the massive influx of EGoT devices, new strategies are needed to efficiently coordinate and control these distributed devices for optimal grid operations. While some studies have explored efficiency and economic models, there remains a gap in ensuring reliability under everyday operations and resilience during extreme conditions. Addressing this gap, this project develops the technology for an Energy Service Interface (ESI) that includes novel pricing, control, learning, and distributed optimization algorithms, which will enable utilities to recruit EGoT assets for crucial grid services such as load flexibility, voltage regulation, and situation-awareness. The key novelty of the proposed technology is the careful distribution of learning and control functions across utility and EGoT asset owners such that provably efficient and resilient grid operations are attained while respecting communication and information-exchange constraints. Specifically, the project team develops machine-learning enhanced load modeling methods to allow EGoT asset owners to learn their load capability and flexibility, and develops pricing-based and decentralized learning-based control so that asset owners can coordinate to meet system-wide demand-supply balance and reliability goals. For extreme situations involving high-impact, low-probability catastrophic events (termed the “black-sky” events), the team also develops (1) a “Feeder-Operating Center-on-a-Laptop” (FOCAL) software that can assist utility personnel in leveraging EGoT assets to accelerate the service recovery of damaged feeders, and (2) distributed optimization algorithms that can coordinate the operation points of EGoT devices under severe communication constraints. The proposed technology has been extensively tested and evaluated through simulations and on a testbed. In summary, as we transition into a more interconnected and digital power grid era, our project’s findings and developments offer a pivotal step toward guaranteeing both efficiency and resilience in the face of both everyday operations and rare “black-sky” events.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Vehicle Localization in 3D World Coordinates Using Single Camera at Traffic Intersection

Optimizing traffic control systems at traffic intersections can reduce the network-wide fuel consumption, as well as emissions of conventional fuel-powered vehicles. While traffic signals have been controlled based on predetermined schedules, various adaptive signal control systems have recently been developed using advanced sensors such as cameras, radars, and LiDARs. Among these sensors, cameras can provide a cost-effective way to determine the number, location, type, and speed of the vehicles for better-informed decision-making at traffic intersections. In this research, a new approach for accurately determining vehicle locations near traffic intersections using a single camera is presented. For that purpose, a well-known object detection algorithm called YOLO is used to determine vehicle locations in video images captured by a traffic camera. YOLO draws a bounding box around each detected vehicle, and the vehicle location in the image coordinates is converted to the world coordinates using camera calibration data. During this process, a significant error between the center of a vehicle’s bounding box and the real center of the vehicle in the world coordinates is generated due to the angled view of the vehicles by a camera installed on a traffic light pole. As a means of mitigating this vehicle localization error, two different types of regression models are trained and applied to the centers of the bounding boxes of the camera-detected vehicles. The accuracy of the proposed approach is validated using both static camera images and live-streamed traffic video. Based on the improved vehicle localization, it is expected that more accurate traffic signal control can be made to improve the overall network-wide energy efficiency and traffic flow at traffic intersections.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Novel red-emitting phosphor Ba3ZrNb4O15:Pr3+: The structure, characteristic photoluminescence property and thermal quenching behaviour investigation

Highlights: • Novel red emitting phosphors BZN:Pr{sup 3+} were successfully synthesized. • Phase purity, morphology and luminescent property of BZN:Pr{sup 3+} were studied. • Different concentration behavior and related mechanism were discussed. • Decay times and the fluorescence dynamics process were investigated. • Temperature sensitive thermal quenching behavior and mechanism was studied. - Abstract: Pr{sup 3+} activated niobate phosphors Ba{sub 3-x}ZrNb{sub 4}O{sub 15}:xPr{sup 3+} were firstly synthesized through high temperature solid-state method. The phase purity, crystal structure, morphology, luminescence property as well as thermal quenching behavior were carefully determined by using X-ray diffractometer, scanned electron microscope, photoluminescence and temperature dependent emission spectra, respectively. The luminescent property showed that Ba{sub 3-x}ZrNb{sub 4}O{sub 15}:xPr{sup 3+} (0.002 ≤ x ≤ 0.03) had dominate excitation around 451 nm and could exhibit red emissions peaking at 608, 618 and 651 nm, attributed to the {sup 1}D{sub 2}-{sup 3}H{sub 4}, {sup 3}P{sub 0}-{sup 3}H{sub 6} and P{sub 0}-{sup 3}F{sub 2} transitions of Pr{sup 3+} ions. The different concentration quenching behaviors were found while the related mechanism was investigated. The room temperature decay times and the related fluorescence dynamics process of Pr{sup 3+} ions in Ba{sub 3}ZrNb{sub 4}O{sub 15} were investigated. In addition, the optimal doping contents, CIE chromaticity coordinates as well as the color purity were determined. At last, the temperature sensitive emission quenching and decay behavior were discussed and the activation energy was calculated based on Arrhenius equation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗