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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A data-driven approach to real-time vertical position estimation for NSTX-U vertical stability control

In this paper, a database of 77 996 plasma equilibrium reconstructions from 727 discharges during the initial operation of the NSTX-U spherical tokamak is analyzed to develop a statistically robust model of the plasma vertical position for real-time control. A variety of regression models are developed and tested, ranging in complexity from linear models to deep neural networks, and including input signals ranging from the four pairs of flux loops used historically on NSTX-U up to the full set of 389 real-time signals available to the plasma control system. A linear model based on 140 real-time magnetics signals is found to offer excellent accuracy, with a coefficient of determination R 2 = 0.906. The robustness of this model to limited training data, new operating scenarios, and signal errors is tested, and a procedure is demonstrated to tune the model parameters to optimize its robustness. A time-dependent plasma equilibrium solver, TokaMaker, is used to simulate vertical stability control in NSTX-U, demonstrating that it should be possible to iteratively tune the parameters of a linear vertical position model to stabilize both positive and negative triangularity plasmas in future experiments.

magnetic diagnostics↗
DOE OSTI2022

Real-time wall conditioning and recycling modification utilizing boron and boron nitride powder injections into the Large Helical Device

Controlled particulate injections from the PPPL impurity powder dropper (IPD) into the Large Helical Device have demonstrated positive effects on the wall conditions on both an intra and inter-shot basis. Here injections over a range of densities, input powers, pulse lengths, heating schemes, injection quantities and main ion species show conclusive evidence of improvement to plasma wall conditions. Successful injections are confirmed by both spectroscopic measurements as well as real-time visible camera signals. In 7 s long plasmas the responses include a reduction in wall recycling as well as a reduction in native impurity content as observed over the course of several discharges. For plasmas longer than 40 s, improvements to the recycling rate and increased impurity control are observed in real time as a consequence of the extended particulate injections. These experiments demonstrate the extended applicability of this solid particulate conditioning technique to the control and maintenance of the plasma wall conditions. In addition they are an important initial step in the development of the real-time boronization technique as a supplement to standard conditioning scenarios.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Considerations for in situ, real time measurement of plasma-material interactions using Digital Holographic imaging

Digital Holographic (DH) imaging is a laser-based measurement technique, which can be used to monitor a material surface as it is being exposed to fusion-relevant plasmas. Both single-laser and dual-laser DH measurements have been demonstrated ex situ at Oak Ridge National Laboratory (ORNL). A DH diagnostic system is being assessed for deployment at ORNL to make in situ, real-time measurements of plasma erosion/redeposition in the Prototype Material Plasma Exposure eXperiment (Proto-MPEX). In situ, real time measurements pose unique challenges to diagnostic systems, which are not encountered by ex situ analysis techniques. The absolute surface height (tracked at the nm to μm position) during plasma exposure can be modified by: 1) surface movement due to vibration or thrust exerted by the plasma device, 2) surface growth due to the thermal expansion of the material under steady MW/m2 or transient GW/m2 plasma heat loads, and 3) surface modification due to plasma erosion/redeposition of the material substrate. To assess these effects, 1) the vibration spectrum of the diagnostic and the pulsed plasma device have been measured, 2) the thermal growth of the surface has been measured for an applied heat flux, and 3) the surface modification has been measured ex situ post plasma exposure, and ex situ post laser ablation as a proxy for the plasma. This paper will provide an overview of the results that have been achieved in the development of a DH diagnostic for in situ real-time measurements of plasma exposed surfaces in the Proto-MPEX device.

Biewer, Theodore↗
DOE OSTI2026

Towards a self-driving trigger at the LHC: adaptive response in real time

Real-time data filtering and selection—or trigger—systems at high-throughput scientific facilities such as the experiments at the Large Hadron Collider must process extremely high-rate data streams under stringent bandwidth, latency, and storage constraints. Yet these systems are typically designed as static, hand-tuned menus of selection criteria grounded in prior knowledge and simulation. In this work, we further explore the concept of a self-driving trigger, an autonomous data-filtering framework that reallocates resources and adjusts thresholds dynamically in real-time to optimize signal efficiency, rate stability, and computational cost as instrumentation and environmental conditions evolve. We introduce a benchmark ecosystem to emulate realistic collider scenarios and demonstrate real-time optimization of a menu including canonical energy sum triggers as well as modern anomaly-detection algorithms that target non-standard event topologies using machine learning. Using simulated data streams and publicly available collision data from the Compact Muon Solenoid experiment, we demonstrate the capability to dynamically and automatically optimize trigger performance under specific cost objectives without manual retuning. Our adaptive strategy shifts trigger design from static menus with heuristic tuning to intelligent, automated, data-driven control, unlocking greater flexibility and discovery potential in future high-energy physics analyses.

Emami, Shaghayegh [Michigan U.] (ORCID:00090007589↗
DOE OSTI2026

Diagonal state designs with reconfigurable real-time circuits

Unitary designs are widely used in quantum computation, but in many practical settings it suffices to construct a diagonal state design generated with unitary gates diagonal in the computational basis. In this work, we introduce a simple and efficient diagonal state 3-design based on real-time evolutions under 2-local Hamiltonians. Our construction is inspired by the classical Girard-Hutchinson trace estimator in that it involves the stochastic preparation of many random-phase states. Though the exact Girard-Hutchinson states are not tractably implementable on a quantum computer, we can construct states that match the statistical moments of the Girard-Hutchinson states with real-time evolution. Importantly, our random states are all generated using the same Hamiltonians for real-time evolution, with the randomness arising solely from stochastic variations in the durations of the evolutions. In this sense, the circuit is fully reconfigurable and thus suited for near-term realizations on both digital and analog platforms. Moreover, we show how to extend our construction to achieve diagonal state designs of arbitrarily high order.

Shen, Yizhi [LBL, Berkeley] (ORCID:000000024160548↗
DOE OSTI2026

Real-time simulation of asymmetry generation in fermion-bubble collisions

Motivated by the out-of-equilibrium dynamics during an early-Universe first-order phase transition, we perform real-time simulations of fermion-bubble scattering in 1 + 1 dimensions. This nonequilibrium process can generate a charge-conjugation C asymmetry outside the bubble wall, induced by the complex fermion mass profile. The resulting C asymmetry is the 1 + 1 -dimensional analog of the C P asymmetry in 3 + 1 dimensions, a key ingredient in baryon asymmetry generation at the electroweak scale. Using tensor network methods, we track the real-time evolution of the C asymmetry in the charge density as the fermion interacts with the bubble wall, a regime inaccessible to analytic calculations. We further introduce two observables to quantify the asymmetry in the asymptotic region where reflected particles are well separated from the scattering point: one based on the net charge outside the bubble wall, and the other on the spatial displacement between the reflected particle and antiparticle wave packets. Our study represents a first step toward nonperturbative, real-time computations of C P asymmetry in 3 + 1 dimensions for electroweak baryogenesis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Real-space inversion and super-resolution of ultrafast scattering

Ultrafast scattering using x-rays or electrons is an emerging method to obtain structure dynamics at the atomic lengthscales and timescales. However, directly resolving in real-space atomic motions is inherently limited by the finite detector range and the probe energy. So, as a result, the time-resolved signal interpretation is mostly done in reciprocal space and relies on modeling and simulations of specific structures and processes. Here, we introduce a model-free approach to directly resolve scattering signals in real space, surpassing the diffraction limit, using scattering kernels and signal priors that naturally arise from the measurement constraints. We demonstrate the approach on simulated and experimental data, recover multiple atomic motions at sub-angstrom resolutions, and discuss the recovery accuracy and resolution limits versus signal fidelity. The approach offers a robust path to obtain high-resolution real-space information of atomic-scale structure dynamics using current time-resolved x-ray or electron scattering sources.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

SpeckleNN: a unified embedding for real-time speckle pattern classification in X-ray single-particle imaging with limited labeled examples

With X-ray free-electron lasers (XFELs), it is possible to determine the three-dimensional structure of noncrystalline nanoscale particles using X-ray single-particle imaging (SPI) techniques at room temperature. Classifying SPI scattering patterns, or `speckles', to extract single-hits that are needed for real-time vetoing and three-dimensional reconstruction poses a challenge for high-data-rate facilities like the European XFEL and LCLS-II-HE. Here, we introduce SpeckleNN, a unified embedding model for real-time speckle pattern classification with limited labeled examples that can scale linearly with dataset size. Trained with twin neural networks, SpeckleNN maps speckle patterns to a unified embedding vector space, where similarity is measured by Euclidean distance. We highlight its few-shot classification capability on new never-seen samples and its robust performance despite having only tens of labels per classification category even in the presence of substantial missing detector areas. Without the need for excessive manual labeling or even a full detector image, our classification method offers a great solution for real-time high-throughput SPI experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Real-time Simulation Framework for Hardware-in-the-Loop Testing of Multi-port Autonomous Reconfigurable Solar Power Plant (MARS)

Multiport autonomous reconfigurable solar power plant (MARS) has been proposed for integrated development of photovoltaic (PV) and energy storage system (ESS) that can connect to high-voltage direct current (HVdc) and alternating current (ac) transmission grid. To de-risk the development of this complex integrated system that consists of hundreds to thousands of power electronics modules, a controller hardware-in-the-loop (cHIL) test setup will be extremely beneficial. The cHIL testing can be used for evaluation of modules as well as the hierarchical control system in MARS. With the unique configuration of power electronics modules in MARS, it becomes necessary to develop custom-designed real-time simulation models in the cHIL setup in absence of off-the-shelf models. In this paper, high-fidelity dynamic model of MARS, control algorithms at the lower level, and required communication algorithms are developed and optimized for real-time performance in the cHIL setup. Real-time experimental results from the cHIL are provided.

Dong, Zerui↗
DOE OSTI2023

A Real-Time Degradation Estimation Approach for Batteries in PV and Battery Hybrid Plant Operation

Conventional cyclic degradation assessment for batteries is often limited in its ability to provide real-time degradation information during operation, because the estimation of degradation is commonly performed after a specific evaluation period. Modified methods can provide real-time evaluation but at the cost of high computation complexity. This paper proposes a novel estimation method that addresses these limitations. It efficiently determines the incremental degradation of any two consecutive state-of-charge (SOC) samples during battery operation, thus enabling real-time estimation. To validate the proposed method, measurement data from lithium-ion phosphate (LFP) battery testing was adopted, and the results were compared with the conventional model and the measured capacity. The results demonstrate accuracy over the evaluation period in terms of cumulative degradation, and a reduced computation cost compared with other methods. This approach has benefits in various applications, especially in cases where batteries experience irregular charging and discharging stress cycles such as PV and battery hybrid plants.

Wang, Shumeng↗
DOE OSTI2021

Real-time Implementation of a Dual-Active-Bridge Based Multi-Level Photovoltaic Converter

Silicon-carbide based, multi-level converters with dual-active-bridge (DAB) are getting attention for medium voltage, direct grid-connected, utility-scale photovoltaic (PV) applications due to their higher efficiency and power density. To de-risk complex control development for these high-voltage and high-power inverters, hardware-in-the-loop techniques are often required. Due to the high switching frequency and the large number of power electronic switches, off-the-shelf, real-time simulation tools are not yet fully developed for this application, even with FPGA-based simulators. To address this, a new co-simulation approach in FPGA is presented that utilizes Time-Stamped Bridge (TSB) for the higher frequency converters along with detailed fixed conductance based discrete device simulation of the rest of the circuit. A complex DAB-based PV converter with maximum switching frequency of 50 kHz is successfully simulated in real-time in the FPGA and the results are compared with offline simulation results. A controller hardware-in-the-loop (CHIL) platform is developed to demonstrate real-time, closed-loop test results for this DAB-based PV converter.

Dong, Zerui↗
DOE OSTI2020

Quantifying Load Uncertainty Using Real Smart Meter Data

As we get closer to customers in distribution systems, load stochasticity increases. In the past, due to lack of real-time data, the comprehensive knowledge of load behavior was limited, and simplistic assumptions had to be made for distribution system modeling and analysis, especially in the processes of network design and expansion. With the deployment of Advanced Metering Infrastructure (AMI), ample real-time smart meter data has become available to utilities. In this paper, using real hourly smart meter data, we have quantified load uncertainty in terms of average, maximum and maximum noncoincident demands on a daily basis, as well as load factor and diversity factor. These uncertainty metrics are examined for individual residential, commercial and industrial customers, as well as distribution transformers serving residential customers. This paper provides a benchmark on load uncertainty quantification for practicing engineers and researchers.

Bu, Fankun↗
DOE OSTI2022

Real-Time Hardware-in-The-Loop Implementation of Protection and Self-Healing of Microgrids

The design of a reliable protection scheme for microgrids often requires communication between protective devices and microgrid controllers. The authors have developed such a communication assisted scalable protection scheme with a self healing feature to protect a microgrid with 100% Inverter Based Resources (IBRs). The communication assisted scheme must be validated in real time with cyber physical co-simulation for successful demonstration. In this regard, the paper presents a co-simulation platform between a simulated power system model using RTDS and physical protective devices. The primary protection of the scheme is programmed in SEL 421-7 relay and backup protection is programmed in MATLAB on a generic computer acting as a microgrid controller. The IEC 61850 models are used to communicate between SEL-421-7 relay and RTDS, whereas TCP/IP communication connects the microgrid controller to RTDS. The paper’s focus is to demonstrate the co- simulation platform with communication links established using both protocols and validate the proposed scheme in real-time on the IEEE 123 node distribution feeder. The paper explains the configuration of the IEC 61850 and TCP/IP communications as the interface requires proper hardware and software setup. Furthermore, the real time performance indicates the Hardware In the Loop (HIL) framework as a competent testing environment for the developed protection scheme for microgrids.

42 ENGINEERING↗
DOE OSTI2024

Development of Real-Time High-Density Pulsar Data Transmission and Processing for Grid Synchronization

Taking advantage of the extreme stability of the pulsar period, it can serve as the timing source for grid synchronization to compensate for the timing drift instigated by the loss of GPS signal. Nevertheless, the real-time transmission and processing of the pulsar data suffer from its high-frequency data rate, varying from megahertz to gigahertz, resulting in reduced computing speed and increased time delay. To mitigate this issue, the hardware and software frameworks are implemented for the high-density pulsar data transmission and processing for grid synchronization in this research. Initially, the high-density pulsar data is transferred using open-source software. The complementary duty cycle timing module is designed to coordinate the operation of the dual-channel high-speed interface and software. Subsequently, the multiple-threading is applied to the receiving, parsing, and splicing pulsar data. Next, the pulsar signal extraction method is implemented based on the polyphase filterbank and time of arrival estimation. Ultimately, real-time performance verification experiments are carried out for different components under two hardware platforms. Finally, the results demonstrate that only 0.482 s is required for processing 4 Gigabyte data through multiple-threading, which is 3.8 times faster than the single thread. The pulsar signal extraction can also be executed within 707 ms for 4.8 seconds of data, thereby indicating that real-time requirements can be met.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Development of ML FPGA Filter for Particle Identification and Tracking in Real Time

Real-time data processing is a frontier field in experimental particle physics. Machine Learning methods are widely used and have proven to be very powerful in particle physics. The growing computational power of modern FPGA boards allows us to add more sophisticated algorithms for real time data processing. Many tasks could be solved using modern Machine Learning (ML) algorithms which are naturally suited for FPGA architectures. The FPGA-based machine learning algorithm provides an extremely low, sub-microsecond, latency decision and makes information-rich data sets for event selection. We report work has started to evaluate an FPGA based Machine Learning (ML) algorithm for a real-time particle identification and tracking with Transition Radiation Detector (TRD) and e/m calorimeter. The first target is the GlueX experiment, with a plan to build a TRD based on GEM technology. GlueX trigger latency is 3.3 μs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Event-Driven Predictive Approach for Real-Time Volt/VAR control with CVR in solar PV rich Active Distribution Network

The focus of this paper is on analyzing the impact of conservation voltage reduction in the presence of active devices such as solar photovoltaic (PV) and developing controls that leverage these distributed energy resources. An event-driven predictive approach for real-time volt/volt-ampere reactive (VAR) optimization, along with local two-level adaptive volt/VAR droop-based control algorithm for advanced distribution management systems, is introduced. The methodology covers aggregated and autonomous controls under different timescale operations, including the impact and effect of unpredicted events such as cloud transients on PV power production. In addition, the control schemes include the uncertainties in PV power generation and load power demand. The proposed methodology is validated in a real-time framework using the real-time digital simulator platform through co-simulation with models based on Python and OpenDSS (Open Distribution System Simulator). The developed methodology is tested on the modified IEEE 123-feeder test system. The results reveal that the proposed methodology works well in the presence of high penetrations of PV power, produces significant energy savings, and mitigates over-/undervoltage problems.

14 SOLAR ENERGY↗
DOE OSTI2022

Real-Time Ecodriving Control in Electrified Connected and Autonomous Vehicles Using Approximate Dynamic Programing

Connected and automated vehicles (CAVs), particularly those with a hybrid electric powertrain, have the potential to significantly improve vehicle energy savings in real-world driving conditions. In particular, the ecodriving problem seeks to design optimal speed and power usage profiles based on available information from connectivity and advanced mapping features to minimize the fuel consumption over an itinerary. This paper presents a hierarchical multilayer model predictive control (MPC) approach for improving the fuel economy of a 48 V mild-hybrid powertrain in a connected vehicle environment. Approximate dynamic programing (DP) is used to solve the receding horizon optimal control problem, whose terminal cost is approximated with the base policy obtained from the long-term optimization. The controller was tested virtually (with deterministic and Monte Carlo simulation) across multiple real-world routes, demonstrating energy savings of more than 20%. The controller was then deployed on a test vehicle equipped with a rapid prototyping embedded controller. In-vehicle testing confirm the energy savings obtained in simulation and demonstrate the real-time ability of the controller.

Automation & Control Systems↗
DOE OSTI2022

AviSense: A Real-time System for Detection, Classification, and Analysis of Aviation Signals

Wireless systems are an integral part of aviation. Apart from their apparent use in air-to-ground communication, wireless systems play a crucial role in avionic functions including navigation and landing. An interference-free wireless environment is therefore critical for the uninterrupted operation and safety of an aircraft. Hence, there is an urgency for airport facilities to acquire the capability to continuously monitor aviation frequency bands for real-time detection of interference and anomalies. To meet this critical need, we design and build AviSense, an SDR-based real-time, versatile system for monitoring aviation bands. AviSense detects and characterizes signal activities to enable practical and effective anomaly detection. We identify and tackle the challenges posed by a diverse set of critical aviation bands and technologies. We evaluate our methodology with real-world aviation signal measurements and two custom datasets of anomalous signals. We find that our signal classification capability achieves a true positive rate of ~99%, with few exceptions, and a false positive rate of less than 4%. We also demonstrate that AviSense can effectively distinguish between different types of anomalies. We build and evaluate a prototype implementation of AviSense that supports distributed monitoring.

42 ENGINEERING↗