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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

AC compensation of 3D magnetic diagnostic signals in DIII-D and National Spherical Torus Experiment-Upgrade (NSTX-U) for real-time application

A time domain algorithm has been developed to remove the vacuum pickup generated by both coil current (DC) and induced vessel current (AC) in real time from three dimensional (3D) magnetic diagnostic signals in the National Spherical Torus Experiment-Upgrade (NSTX-U) and DIII-D tokamaks. The possibility of detecting 3D plasma perturbations in real time is essential in modern and future tokamaks to avoid and control MHD instabilities. The presence of vacuum field pickup, due to toroidally asymmetric (3D) coils or to misalignment between sensors and axisymmetric (2D) coils, pollutes the measured plasma 3D field, making the detection of the magnetic field produced by the plasma challenging. Although the DC coupling between coils and sensors can be easily calculated and removed, the AC part is more difficult. Here, an algorithm based on a layered low-pass filter approach for the AC compensation and its application for DIII-D and NSTX-U data is presented, showing that this method reduces the vacuum pickup to the noise level. Comparison of plasma response measurements with and without vacuum compensation shows that accurate mode locking detection and plasma response identification require precise AC and DC compensations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak

Active feedback control in magnetic confinement fusion devices is desirable to mitigate plasma instabilities and enable robust operation. Optical high-speed cameras provide a powerful, non-invasive diagnostic and can be suitable for these applications. Here, in this study, we process high-speed camera data, at rates exceeding 100 kfps, on in situ field-programmable gate array (FPGA) hardware to track magnetohydrodynamic (MHD) mode evolution and generate control signals in real time. Our system utilizes a convolutional neural network (CNN) model, which predicts the n = 1 MHD mode amplitude and phase using camera images with better accuracy than other tested non-deep-learning-based methods. By implementing this model directly within the standard FPGA readout hardware of the high-speed camera diagnostic, our mode tracking system achieves a total trigger-to-output latency of 17.6 μs and a throughput of up to 120 kfps. This study at the High Beta Tokamak-Extended Pulse (HBT-EP) experiment demonstrates an FPGA-based high-speed camera data acquisition and processing system, enabling application in real-time machine-learning-based tokamak diagnostic and control as well as potential applications in other scientific domains.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Bayesian Gaussian process inference for neutron spin echo measurement

Neutron spin echo (NSE) spectroscopy provides unique access to microscopic dynamics, but its application is often constrained by low neutron flux, long acquisition times, and significant noise. Here, we present a Bayesian inference approach based on Gaussian process regression (GPR) to reconstruct high-quality spin echo signals from sparse and noisy data by exploiting correlations in reciprocal space. Benchmarks on synthetic datasets and validation with experimental NSE measurements of dendrimers show that GPR suppresses noise, interpolates missing intensity values, and accommodates irregular observations. The method improves accuracy, shortens acquisition times, and enables high-throughput and real-time studies. Beyond NSE, the framework is broadly applicable to other low signal-to-noise ratio scattering techniques, thereby extending the scope of neutron spectroscopy.

Tung, Chi-Huan [Oak Ridge National Laboratory (ORN↗
DOE OSTI2024

Chemical bond reorganization in intramolecular proton transfer revealed by ultrafast X-ray photoelectron spectroscopy

Time-resolved X-ray photoelectron spectroscopy (TR-XPS) is used in a simulation study to monitor the excited state intramolecular proton transfer between oxygen and nitrogen atoms in 2-(iminomethyl)phenol. Real-time monitoring of the chemical bond breaking and forming processes is obtained through the time evolution of excited-state chemical shifts. By employing individual atomic probes of the proton donor and acceptor atoms, we predict distinct signals with opposite chemical shifts of the donor and acceptor groups during proton transfer. Details of the ultrafast bond breaking and forming dynamics are revealed by extending the classical electron spectroscopy chemical analysis to real time. Through a comparison with simulated time-resolved photoelectron spectroscopy at the valence level, the distinct advantage of TR-XPS is demonstrated thanks to its atom specificity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

The FRB-searching Pipeline of the Tianlai Cylinder Pathfinder Array

This paper presents the design, calibration, and survey strategy of the Fast Radio Burst (FRB) digital backend and its real-time data processing pipeline employed in the Tianlai Cylinder Pathfinder Array. The array, consisting of three parallel cylindrical reflectors and equipped with 96 dual-polarization feeds, is a radio interferometer array designed for conducting drift scans of the northern celestial semi-sphere. The FRB digital backend enables the formation of 96 digital beams, effectively covering an area of approximately 40 square degrees with the 3 dB beam. Our pipeline demonstrates the capability to conduct an automatic search of FRBs, detecting at quasi-real-time and classifying FRB candidates automatically. The current FRB searching pipeline has an overall recall rate of 88%. During the commissioning phase, we successfully detected signals emitted by four well-known pulsars: PSR B0329+54, B2021+51, B0823+26, and B2020+28. We report the first discovery of an FRB by our array, designated as FRB 20220414A. We also investigate the optimal arrangement for the digitally formed beams to achieve maximum detection rate by numerical simulation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Adaptive sampling for accelerating neutron diffraction-based strain mapping *

Abstract Neutron diffraction is a useful technique for mapping residual strains in dense metal objects. The technique works by placing an object in the path of a neutron beam, measuring the diffracted signals and inferring the local lattice strain values from the measurement. In order to map the strains across the entire object, the object is stepped one position at a time in the path of the neutron beam, typically in raster order, and at each position a strain value is estimated. Typical dwell times at neutron diffraction instruments result in an overall measurement that can take several hours to map an object that is several tens of centimeters in each dimension at a resolution of a few millimeters, during which the end users do not have an estimate of the global strain features and are at risk of incomplete information in case of instruments outages. In this paper, we propose an object adaptive sampling strategy to measure the significant points first. We start with a small initial uniform set of measurement points across the object to be mapped, compute the strain in those positions and use a machine learning technique to predict the next position to measure in the object. Specifically, we use a Bayesian optimization based on a Gaussian process regression method to infer the underlying strain field from a sparse set of measurements and predict the next most informative positions to measure based on estimates of the mean and variance in the strain fields estimated from the previously measured points. We demonstrate our real-time measure-infer-predict workflow on additively manufactured steel parts—demonstrating that we can get an accurate strain estimate even with 30%–40% of the typical number of measurements—leading the path to faster strain mapping with useful real-time feedback. We emphasize that the proposed method is general and can be used for fast mapping of other material properties such as phase fractions from time-consuming point-wise neutron measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Strong-field Driven Sub-cycle Band Structure Modulation and Dephasing Control

In this work, we present measurements of ultrafast electric-field observables in magnesium oxide using a non-resonant nonlinear optical interaction. Using field observables, we show that strong laser fields modulate the band structure on sub-cycle timescales, thereby altering the material’s nonlinear optical response. We perform time-dependent perturbation theory calculations using a field-dependent dispersion relation and semiconductor Bloch equation calculations, both of which agree with experimental observations. Furthermore, we extract pulse decay times from the real-time signal electric field envelope and show sub-cycle control of dephasing times. Our work offers a new perspective on strong-field-driven electron dynamics in solids through electric-field observables. The demonstrated attosecond modulation of the nonlinear response could have important implications for quantum light generation and quantum spectroscopy using nonlinear optical processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

ML–Enabled FPGA Framework for Fast Quantum State Discrimination in Mid-Circuit Measurement Regimes

Accurate and low-latency quantum state discrimination is essential for protocols involving mid-circuit measurement (MCM) and conditional feed-forward. In superconducting quantum systems, conventional readout pipelines transfer measurement data to host processors for post-processing, introducing millisecond-scale delays that far exceed qubit coherence times. To overcome this bottleneck, we present an in-situ machine learning (ML) inference engine implemented on an FPGA for real-time quantum state discrimination. Our design performs inference directly on digitized readout signals with 40 ns latency, supports both qubit and qutrit readout, and enables conditional operations without host-side intervention. This capability is critical for MCM and for feedback-driven protocols such as quantum error correction. We validate the system on superconducting transmon hardware, demonstrating robust discrimination fidelity across multiple qubit and qutrit channels. We further demonstrate conditional qutrit logic driven by FPGA-resident classification, highlighting the potential of low-latency ML-on-FPGA control for NISQ applications and scalable fault-tolerant quantum computing.

Vora, Neel [Lawrence Berkeley National Laboratory ↗
DOE OSTI2023

Deployment of ADTimePix3 areaDetector Driver at Neutron and X-ray User Facilities

TimePix3 is a 65k hybrid pixel readout chip with simultaneous Time-of-Arrival (ToA) and Time-over-Threshold (ToT) recording in each pixel*. The chip operates without a trigger signal with a sparse readout where only pixels containing events are read out. The flexible architecture allows 40 MHits/s/cm² readout throughput, using simultaneous readout and acquisition by sharing readout logic with transport logic of superpixel matrix formed using 2x4 structure. The chip ToA records 1.5625 ns time resolution. The X-ray and charged particle events are counted directly. However, indirect neutron counts use 6Li fission in a scintillator matrix, such as ZnS(Ag). The fission space-charge region is limited to 5-9 um. A photon from scintillator material excites a photocathode electron, which is further multiplied in dual-stack MCP. The neutron count event is a cluster of electron events at the chip. We report on the EPICS areaDetector** ADTimePix3 driver that controls Serval*** using json commands. The driver directs data to storage and to a real-time processing pipeline and configures the chip. The time-stamped data are stored in raw .tpx3 file format and passed through a socket where the clustering software identifies individual neutron events. The conventional 2D images are available as images for each exposure frame, and a preview is useful for sample alignment. The areaDetector driver allows integration of time-enhanced capabilities of this detector into SNS beamlines controls and unprecedented time resolution.

Gofron, Kaz↗
DOE OSTI2023

Ultrasonic Measurements of Temperature Profile and Heat Fluxes in Coal-Fired Power Plants (Final Report)

Many industrial processes are inaccessible or inhospitable to characterization by traditional temperature measurement methods, such as thermocouples, especially over prolonged exposure to harsh environments. Ultrasound is an established characterization technology with diverse applications ranging from medical imaging to therapies to flaw detection to nondestructive evaluation. Ultrasound may characterize solid materials and components noninvasively as a nondestructive evaluation modality and obtain internal measurements of material properties. For example, the speed of ultrasound propagation changes with Young’s modulus and Poisson’s ratio, which can be found from its measurements. Traditional ultrasonic characterization assumes all material properties remain constant with the position. When this assumption holds, a property of interest may be measured by relating it to the speed of ultrasound propagation (or a speed of sound, SOS) and measuring the SOS by timing the ultrasound propagation through a known distance. However, when a property of interest is spatially distributed, the propagation time depends on the SOS changing with the position along the ultrasound propagation path. The multiple temperature distributions may lead to an identical time of flight (TOF). Temperature is one property that impacts the speed of ultrasound and often cannot be assumed to remain constant with the position. Previously, in the context of temperature, we addressed the challenge of ultrasonic characterization of spatially distributed properties by developing a method for measuring segmental temperature distributions (MSTD). This method divides the ultrasonic propagation into segments bound by echogenic features. These features provide ultrasonic interfaces where some energy is reflected toward the receiving transducer, and the rest continues through the medium. The time-of-flight between the echoes reflected from echogenic features characterizes the spatial distribution in the properties of interest in the corresponding segment of the ultrasonic propagation path. This project demonstrated the application of the MSTD method in industrial conditions of the coal-fired power plant. We implemented the MSTD using metals and alloys waveguides, which may be the existing structure for which the temperature distribution is characterized or purposefully designed waveguides added to the structure by welding or other means specifically to quantify thermal properties using the MSTD method. Previous iterations of the MSTD method used ceramic and cementitious waveguides, which significantly attenuate ultrasound. On the other hand, low attenuation in metallic waveguides creates interactions between echogenic features which compilates the signal analysis in the segmental TOF measurements. We have established the WG design principles that minimize the interferences between trailing and primary echoes and, in some cases, eliminate them. The waveguides in which echoes do not interfere improve the timing accuracy and the robustness of ultrasonic measurements of the spatial distributions in material properties. Our emphasis remained on the estimation of the temperature distributions. We have developed general recommendations for designing ultrasonically segmented waveguides with the reduced influence of trailing echoes. Two of our waveguide designs were tested in the industry. The first waveguide was designed for insertion into a combustion zone of the utility-scale coal-fired power plant boiler. The second design allows the characterization of temperature distribution in the direction normal to the boiler’s water wall, a large heat exchanger converting the chemical energy released during combustion to the steam driving the electrical power generation turbines. These waveguides were designed to operate within a restrictive space of thermally insulated water wall and incorporate densely located echogenic features while combatting the influence of trailing echoes. The project has successfully demonstrated the feasibility of using the developed method for accurate, continuous, and robust temperature measurements in extreme environments of power generation and other industrial processes. It, therefore, has achieved its overarching goal of advancing the technology readiness level of the novel Ultrasound Measurements of Segmental Temperature Distribution (US-MSTD) method for real-time measurements of the temperature distribution and heat fluxes closer to commercial availability, developing a prototype multipoint measurement system, and validating its performance on coal-fired utility boilers. The success of this project was achieved in collaboration with the power generator, Rocky Mountain Power, and set the stage for the transfer of this technology from the laboratory to the industry.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Evaluating a Semi-Quantitative, Spectrophotometric Method for the Rapid Determination of Total Rare Earth Element Concentrations in Citrate Leaching Solutions

Quick, reliable methods to measure the rare earth elements (REEs) in process streams are needed to support real-time parameterization and monitoring for a burgeoning number of REE extraction schemes. Such methods would ideally be fast, reproducible, and field-deployable. This study evaluates the feasibility of using a chromogenic indicator, arsenazo(III) (hereafter abbreviated as Arsz(III)) to detect the concentration of REEs in complex citrate leaching solutions using a spectrophotometer. Arsz(III) forms a chromogenic complex with the lanthanide elements that produces a blue/purple color detectable in the visible light range. Matrices of solutions containing varied concentrations of calcium, iron, and lanthanum were scanned in the presence of an Arsz(III) indicator to generate a modeled relationship that could be used to back calculate REE concentrations. While relatively quick (scan times on the order of seconds), the results indicated that the calcium and iron concentrations of typical mining solutions overwhelm the signal of the REEs, to the extent that sensitivity of the method is no less than 50 µM REEs. These results demonstrate the difficulties of accurately measuring trace metals in complex solutions, although the method may still hold utility for processes with significantly lower calcium and iron concentrations or REE concentrations much greater than 50 µM.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Using Hardware-In-The-Loop Methodology to Develop Test Systems

Hardware in the Loop (HIL) testing methodologies have become widespread in industry. Typically, they focus on developing control algorithms for systems such as autonomous vehicles or aircraft. An oft overlooked aspect of product development is the design and fabrication of a test system for validating that the product meets requirements. Abstractly, a test system differs little from a control system—testers provide signals to the unit, monitor feedback, and base decisions on the results. While the time scales may differ, the functionalities are conceptually similar. Viewed in this light, it becomes natural to extend HIL approaches to tester development. By replacing a physical unit with a proxy model deployed to a real-time or pseudo real-time target, test systems can be developed in parallel with the design and fabrication of a first production unit. This saves considerable time in the life cycle from conceptual design to realized product. This manuscript demonstrates the process flow using a capacitive discharge unit as an exemplar.

42 ENGINEERING↗
DOE OSTI2025

Fusion of Experiments and Simulations for Real-Time Identification of Pipeline Defects

In this study, we explored fusion of experiments and simulations for real time identification of pipeline defects across physical and non-physical domains. The challenges associated to data processing were addressed and a combined classification models was presented via CNN models. In addition, regression model based on XGBOOST is built to determine the defect location and defect dimension from data-driven features of guided wave signals captured by SMS fiber optic sensor.

deep learning↗
DOE OSTI2025

Towards Online Machine Learning in DUNE Data Acquisition

Processing the large volumes of data produced by liquid argon time projection chamber (LArTPC) experiments presents a significant challenge, especially those at the scale of DUNE. This is a particular challenge when aiming to trigger on low-energy neutrinos from core-collapse supernovae, which are typically buried in a high-rate radiological background. To enable real-time event selection suitable for such rare signals, we are developing machine learning based data filtering methods. In order to demonstrate the feasibility of this approach, we implemented such pipeline using the ICEBERG detector at Fermilab as a small-scale LArTPC, with a focus on identifying Michel electrons as a proxy for low-energy neutrino interactions. This poster will present the current status of integrating these machine learning models into the data acquisition (DAQ) system of this detector.

Dalager, Olivia [Fermilab]↗
DOE OSTI2026

Digital Grid Twin–Direct Communication Scheme Test Bed for Assessing Relay-to-Relay Radio Antenna and Optical Fiber Performance and Misoperations

This study introduces a novel “Digital Grid Twin–Direct Communication Scheme” test bed. This advanced platform evaluates point-to-point communication between transmitter and receiver relays with optical fiber and radio omnidirectional antenna systems, implemented at the Advanced Protection lab in the Grid Research Innovation and Development Center at Oak Ridge National Laboratory. The increased diversity of energy sources has led to more protective relay misoperations. In North America, microgrid protection schemes now use point-to-point communication along distribution lines between relays to implement advanced logic in nonradial grids that include both high- and low-inertia generators. This trend challenges utilities to minimize misoperations while ensuring rapid fault clearance and accurate selectivity coordination between primary and backup relays. This study assesses relay-to-relay communication schemes by introducing an advanced testing platform based on a digital grid twin protection test bed using a synchronized time source system. The platform evaluates the communication system using radio antennas or optical fiber links by integrating protective relays that operate breakers within the digital twin and record relay events and communication signals. In the experiments, transmitter and receiver relays were configured with inverse time overcurrent and breaker trip detection logic to assess the total time of the communication protection schemes based on the sum of the relay protection element operating time, radio latency, propagation delay, baud rate delay, and relay processing time. These delays were derived from recorded relay events and communication signals from the interface of a real-time simulator set as a digital grid twin. The test bed successfully simulated various electrical faults along a distribution line while ensuring effective and reliable point-to-point communication between transmitter and receiver relays. The radio antenna communication system exhibited latency because of the radio. This latency depends on the baud rate setting and type of radio application; in general, the higher the baud rate, the lower the radio latency. The measured radio latency (for Mirrored Bits with an encryption card at 9,600 bps) was about 9–10 ms. Additionally, calculated propagation delay per mile for radio antennas and optical fiber was 5.36 µs/mi and 8.04 µs/mi, respectively. Optical fiber communication did not demonstrate radio latency. Instead, the protection element operating time depends mainly on the protection logic function set in the relay, and the relay processing time depends on the processing rate of the relay in samples per power system cycle.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Overview of IMPACT Data Acquisition System and Data Reduction Process

This report documents the development of the data acquisition system (DAS) and data reduction methodologies for the Irradiated Material Property Accelerated Characterization Test (IMPACT) experiment at the Advanced Test Reactor (ATR). The IMPACT experiment is designed to enable in-pile measurement of thermal conductivity in metallic nuclear fuels, specifically U-10Zr, using an instrumented thermal conductivity probe. The DAS supports both passive temperature monitoring and active thermal interrogation of the probe through controlled AC and DC excitation. Significant modifications to laboratory-scale systems were required to accommodate the higher resistance paths associated with the in-pile application. Custom electronics and relay-controlled measurement sequencing were developed to enable the measurement and sufficient power delivery to the sensing region. A reduced-order, axisymmetric thermal model based on the thermal quadrupoles method is presented to support data interpretation. This model enables efficient evaluation of transient heat transfer behavior and facilitates solution of the inverse problem required to extract thermal properties from measured signals. Multiple boundary condition formulations are discussed to address varying experimental time scales and geometries. Additionally, machine learning techniques are introduced to support data reduction and improve confidence in inverse solutions. Convolutional neural networks are applied to identify the presence of gas gaps and other evolving geometric features that significantly impact thermal response during irradiation. These efforts contribute to the broader integration of digital twin frameworks and real-time modeling capabilities within the Advanced Fuels Campaign.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2024

Emerging Jets Search, Triton Server Deployment, and Track Quality Development: Machine Learning Applications in High Energy Physics

Machine learning is becoming prevalent in high energy physics, with numerous applications in physics analyses and event reconstruction showing great improvements compared to traditional computing methods. This thesis studies three projects which each propose new avenues for machine learning applications within the high energy physics CMS experiment located at CERN. In the first project, a search for a dark matter signal called “emerging jets” is performed, using graph neural networks to greatly increase sensitivity to the signal’s signature within the data. The result of this dark matter search sets the most stringent exclusion limits to date on theoretical emerging jet models. Motivated by inefficiencies encountered when processing the emerging jet graph neural network at Fermi National Accelerator Laboratory’s computing centers, the second project re-optimizes the computing centers for machine learning inference. This re-optimization uses NVIDIA Triton Inference Servers to process users’ analysis code heterogeneously, therefore achieving high processing throughput and decreasing user time-to-insight. The last project focuses on an upgrade to the CMS experiment’s real-time event selection system which improves physics object reconstruction under harsh processing conditions. A boosted decision tree is used to quickly and efficiently quantify a reconstructed particle’s “track quality” in order to remove particle tracks reconstructed erroneously. In summary, this thesis will not only present examples of how high energy physics can greatly benefit by leveraging machine learning techniques for physics analysis and reconstruction, but will also provide guidance on how the field can prepare for the inevitable increase in machine learning applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗