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NASA NTRS1977

JSME scatterometer data processing

A software system was developed which processes digitized scatterometer data from the 13.3 GHz, 1.6 GHz and 400 MHz scatterometer systems. In addition to this, the hardware capability has been developed to recover the raw analog radar signals and the aircraft parameters from an ADAS data stream in a digital format for processing by the software package. Software for the preparation of data reports and chart presentation of scattering coefficients time histories has also been developed. This report documents the development of the software, describes key components of the processing system and presents examples of the processed data and procedure for software operation.

Source record↗

DOE OSTI2025

Application of Raman Spectroscopy to Determine Uranium Content in ADUN Solution

The work presented in this report is part of the ongoing efforts to address the nuclear material control and accounting needs for advanced reactor fuel fabrication facilities. This work was supported by the Materials Protection, Accounting, and Control Technologies (MPACT) program under the US Department of Energy Office of Nuclear Energy‘s Nuclear Fuel Cycle and Supply Chain program. The activities and engagements under the MPACT program are designed to support a robust US civilian nuclear energy enterprise. In the work described in this report, we supported MPACT objectives by developing measurement techniques that could be used for material accounting and process monitoring and by working with industry partners to identify existing gaps and areas for improvement. Oak Ridge National Laboratory has been working with commercial tristructural isotropic (TRISO) fuel fabricators such as Standard Nuclear to develop technology for rapid and cost-effective uranium content assessment. This work has focused on demonstrating advanced measurement techniques (e.g., Raman spectroscopy) that can be used for rapid, reliable, and cost-effective routine measurements of uranium content in feed solutions and liquid waste streams as well as for monitoring in-line process measurements and product streams. Specifically, this report explores techniques for accurately determining uranium content in acid-deficient uranyl nitrate (ADUN) solutions and detecting low uranium concentrations in ammonia solutions. Developing such measurement techniques will benefit TRISO fuel fabrication facilities, facilities involved in other parts of the fuel cycle that require online monitoring of aqueous solutions, and potentially molten salt fuel reactors. This work supports developing Raman spectroscopy procedures to determine uranium concentrations in ADUN solutions, which are used as feedstock in the sol–gel process for creating TRISO fuel. Some additional benefits of using Raman spectroscopy for uranium quantification in fabrication facilities include enabling online monitoring of the chemical process, which would provide near real-time feedback; eliminating the need for sample transfers, preparation, or dilution; providing nondestructive measurements; and user friendliness. In this fiscal year, FY25, we determined the identity of the unknown Raman band at approximately 853 cm−1 that was discovered in ADUN Raman spectra in FY24, created calibration curves and determined uranium concentrations of two ADUN solutions, and compared the Raman results to results obtained from inductively coupled plasma mass spectrometry and Davies–Gray titration. Furthermore, we have identified focus areas for experimentation in future fiscal years. A key result is that the accuracy of using Raman can provide accuracy comparable to destructive analysist techniques, With a well-developed calibration curve, using standards and a large number of samples (more than five samples), uncertainty on the order of 1%–3% is achievable. Given that the uncertainties achieved by Raman spectroscopy were on the order of the uncertainties achieved using ICP-MS, we conclude that with a well-developed procedure Raman spectroscopy can be used to determine uranium concentrations in ADUN solutions for NMC&A applications. The benefits of such an approach are that the time and effort will be less than that of comparable destructive analysis techniques, with approximately the same level of technical expertise. This will be attractive to operators of fuel fabrication facilities as it will lower costs and improve efficiencies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2002

Requirements Development Issues for Advanced Life Support Systems: Solid Waste Management

Long duration missions pose substantial new challenges for solid waste management in Advanced Life Support (ALS) systems. These possibly include storing large volumes of waste material in a safe manner, rendering wastes stable or sterilized for extended periods of time, and/or processing wastes for recovery of vital resources. This is further complicated because future missions remain ill-defined with respect to waste stream quantity, composition and generation schedule. Without definitive knowledge of this information, development of requirements is hampered. Additionally, even if waste streams were well characterized, other operational and processing needs require clarification (e.g. resource recovery requirements, planetary protection constraints). Therefore, the development of solid waste management (SWM) subsystem requirements for long duration space missions is an inherently uncertain, complex and iterative process. The intent of this paper is to address some of the difficulties in writing requirements for missions that are not completely defined. This paper discusses an approach and motivation for ALS SWM requirements development, the characteristics of effective requirements, and the presence of those characteristics in requirements that are developed for uncertain missions. Associated drivers for life support system technological capability are also presented. A general means of requirements forecasting is discussed, including successive modification of requirements and the need to consider requirements integration among subsystems.

Levri, Julie A.↗

DOE OSTI2026

Data, model inputs, and analysis scripts associated with a manuscript on stream intermittency controls across spatial scales in Pacific Northwest watersheds

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript "Hydroclimatic Memory and Watershed Template Shape Stream Intermittency: Multi-scale Attribution Using Process-based Simulation and Explainable ML" by Niroula et al. (2026), submitted to Water Resources Research (WRR). The study investigates the dominant controls on stream intermittency across local, reach, and watershed scales using a coupled process-based simulation and explainable machine-learning framework. Long-term daily simulations from the Advanced Terrestrial Simulator (ATS) were used to generate wetness states and ponded-depth responses over river-corridor cells. These ATS outputs were then aggregated across scales and used to train XGBoost (eXtreme Gradient Boosting) models. SHAP (SHapley Additive exPlanations) was applied to quantify the relative importance of hydroclimatic forcings, watershed template attributes, and antecedent-memory effects in shaping intermittency behavior. The analysis is carried out for three contrasting Pacific Northwest watersheds: Oak Creek (OCW), American River Watershed (ARW), and H.J. Andrews (HJA). Across these testbeds, the package contains ATS-ready watershed inputs, ATS run configuration and selected output files, model-evaluation data products, intermittency-analysis datasets, machine-learning target-feature tables, SHAP outputs, and notebooks used to organize, analyze, and visualize results. At a high level, the package documents a workflow in which ATS provides the physically based simulation backbone and explainable machine learning is used as a post-processing attribution tool. The contents are intended to support interpretation of the manuscript figures and results, provide context for how intermittency metrics were generated at multiple scales, and preserve the key artifacts needed to understand and reuse the analysis workflow. The package contains a high-level directory summary file (`summary.txt`) and four main content folders (1) `evaluation_plots` contains evaluation figures and supporting evaluation datasets; (2) `intermittency_plots` contains intermittency-focused analysis notebook and prepared datasets; (3) `ml-training-and-shap_values_plots` contains ML training inputs, SHAP outputs, and figure-generation notebooks; and (4) `watershed_mesh_and_ats_input` contains ATS model setup materials, forcing inputs, geometry, and selected run files. More specifically, the `evaluation_plots` folder contains the notebook used for ATS evaluation plotting and site-specific evaluation datasets. These include evapotranspiration and water-balance products for three watersheds, as well as an Oak Creek field-measurement discharge file. The `intermittency_plots` folder contains the notebook used for intermittency analysis and the prepared datasets used to analyze intermittent and non-intermittent wetness behavior across the study watersheds. The `ml-training-and-shap_values_plots` folder contains notebooks and outputs for the machine-learning and explainability workflow. This includes the main XGBoost and SHAP notebook(s), a beeswarm plotting notebook, target-feature tables for machine-learning training, SHAP summary tables, and per-sample SHAP value archives. The `watershed_mesh_and_ats_input` folder contains ATS-related watershed inputs and supporting materials. This includes mesh and shape products, ATS-readable LAI and meteorological forcing inputs, selected ATS spinup and transient-run files, and a watershed workflow example notebook. Subdirectories are organized by watershed where applicable.All files are .cpg (codepage files), .csv (comma-separated values), .dbf (database files), .exo (Exodus mesh format), .h5 (HDF5 format), .ipynb (Jupyter notebooks), .pkl (Python pickle), .prj (projection files), .sh (shell scripts), .shp (shapefile geometry), .shx (shapefile index), .txt (text files), or .xml (markup data).

Advanced Terrestrial Simulator↗

NASA NTRS1995

The microscopic state of the solar wind: Links between composition, velocity distributions, waves and turbulence

An overview is given of the microscopic state of the solar wind with emphasis on recent Ulysses high-latitude observations and previous Helios in-ecliptic observations. The possible links between composition, ionization state. velocity distribution functions of electrons, protons and heavy ions. kinetic plasma waves and MHD-scale turbulence are elaborated. Emphasis is placed on a connection of interplanetary kinetic-scale phenomena with their generating microscopic processes in the corona. The fast streams seem to consist of mesoscale pressure-balanced plasma filaments and magnetic flux tubes, reminiscent of the supergranular-size structures building the open corona, from which copious Alfven waves emanate. The wind from the magnetically structured and active corona shows developed compressive turbulence and considerable abundance and ionization state variations. Some modelling attempts to explain the observed element fractionation are briefly reviewed. The causes of the nonthermal particle features. such as proton-ion differential streaming, ion beams. temperature anisotropies, and skewed distributions associated with collisionless heat conduction, are ultimately to be searched in the fact, that the corona is never quiescent but fundamentally variable in space and time. Consequently, the radial evolution of the internal state of the wind resembles at all latitudes a complicated relaxation process, in the course of which the free (in comparison with LTE conditions) particle kinetic energy is converted into plasma waves and MHD turbulence on a wide range of scales. This leads to intermittent wave-particle interactions and unsteady anomalous transport, mixed with the weak effects of the rare Coulomb collisions. Spherical expansion and large-scale inhomogeneity forces the wind to attain microscopically a complex internal state of dynamic statistical equilibrium.

Marsch, E.↗

NASA NTRS2019

Developing a Machine-Learning-Based Processing Framework for Twitter and Other Crowdsourced Data

Crowdsourced data streams such as Twitter and other social media are important sources of real-time and historical global information for Earth science applications. At the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), we have been exploring the Twitter data stream for its potential in augmenting the validation program of NASA's Global Precipitation Measurement (GPM) mission. To realize this potential, we need to increase the information density and enhance the quality of filtered precipitation tweets. We have implemented various components of a machine learning (ML)-based processing infrastructure for crowdsourced data that outputs, in this instance, useful and usable information derived from precipitation tweets. We have test enriched the Twitter stream with higher quality active tweets from those knowingly contributing to our effort and from existing crowdsourced programs (e.g., mPING, CoCoRaHS). We have experimented with various algorithms for processing tweets, including NaÃ ve Bayes, Convolutional Neural Network (CNN), Hierarchical Attention Network (HAN), and semi-supervised learning (with tri-training). Our current work focuses on (1) automated review of Earth science-related publications to determine relationships between discipline research needs and ML algorithms; (2) investigating Sequential Generative Adversarial Network (SeqGAN) for processing precipitation tweets for anomaly detection; and (3) managing crowdsourced data in a way that is compatible with existing NASA satellite data archives and using the data for ML applications. Key results include (1) network visualization of NLP-processed publications in various Earth science disciplines; (2) difference between GPM-linked, generated tweets and collected actual tweets that is small for GPM-determined light to moderate rain cases and high for GPM-determined heavy rain cases; and (3) identification of MongoDB for storing raw tweets and Zarr format for gridded tweets (compatible with GPM data). Our results have taken us a step closer to an operational ML-based tweet processing infrastructure and have already demonstrated that tweet-derived precipitation information is potentially useful for validation of Earth science satellite data.

Teng, William↗

NASA NTRS1992

An optimal GPS data processing technique

A formula is derived to optimally combine dual-frequency GPS (Global Positioning System) pseudorange and carrier phase data streams into a single equivalent data stream, reducing the data volume and computing time in the filtering process for parameter estimation by a factor of four. The resulting single data stream is that of carrier phase measurements with both data noise and bias uncertainty strictly defined. With this analytical formula the single stream of equivalent GPS measurements can be efficiently formed by simple numerical calculations without any degradation in data strength. The formulation for the optimally combined GPS data and their covariances are given in closed form. Carrier phase ambiguity resolution, when feasible, is improved due to the preservation of the full data strength with the optimal data combining process.

Wu, S. C.↗

NASA NTRS1984

Some current uses of array processors for preprocessing of remote sensing data

The preparation of remotely sensed data sets into a form useful to the analyst is a significant computational task, involving the processing of spacecraft data (e.g., orbit, attitude, temperatures, etc.), decommutation of the video telemetry stream, radiometric correction and geometric correction. Many of these processes are extremely well suited for implementation on attached array processors. Currently, at Goddard Space Flight Center a number of computer systems provide such capability for earth observations or are under development as test beds for future ground segment support. Six such systems will be discussed.

Fischel, D.↗

NASA NTRS2021

A High Dynamic-Range Photon-Counting Receiver for Deep Space Optical Communication

The Deep Space Optical Communication (DSOC) project will demonstrate free-space optical communication at almost 3 AU, or 3 orders of magnitude further than any previous attempt. DSOC will utilize the 5m Palomar Hale Telescope to receive the downlink signal, which will couple the downlink light onto an optical table and into a superconducting nanowire single photon detector (SNSPD). The output of the SNSPD is digitized by the Ground Laser Receiver Signal Processing Assembly (GSPA) using a high throughput streaming time to digital converter (TDC). The GSPA is a scalable FPGA-based receiver which demodulates and decodes the DSOC downlink signal through novel signal processing algorithms implemented on Xilinx UltraScale+ FPGAs, as well as Python-based software monitor and control routines. Exploiting the unique TDC-based architecture, the GSPA supports over four orders of magnitude of downlink data rates across multiple orders of magnitude of signal and background powers. In this paper we present an overview of the hardware, firmware and software architectures to implement this system, as well as performance analysis for links ranging from near-Earth to 2.8 AU.

Srinivasan, Meera↗

DOE OSTI2024

Mark-18A Cold Runs

The Savannah River National Laboratory (SRNL) is tasked by the National Nuclear Security Administration (NNSA) to recover highly valued isotopes from irradiated Mark-18A (Mk-18A) targets. The Savannah River Site (SRS) has sixty-five Mk-18A targets available for the recovery of the high valued materials. The sixty-five Mk-18A targets are currently stored in the L-Area Basin and will be removed one at a time and individually transported to SRNL. Upon receipt at SRNL, the Mk-18A target material will be removed from the confinement, dissolved, chemically separated, and calcined to a stable oxide. The flowsheet is designed to recover the plutonium as well as the trivalent actinides. The remaining unrecovered material will be discarded to the high activity drain (HAD) system in SRNL. A specially designed cask was procured for transport of the targets from L-Area to SRNL. Once received at SRNL, the targets will be loaded into the back of Cell 7 and resized as they enter the cell. The resized targets (1/4 lengths) will then be processed one at a time through the following processes: caustic dissolution and filtration; acidic dissolution and filtration, Reillex anion exchange, diglycolamide (DGA) cation exchange; and DGA calcination. This processing will result in two product streams. The first is an aqueous plutonium solution which will be removed from the shielded cells and taken to a glovebox for further purification and conversion to an oxide. The second is a calcined oxide containing the Am and Cm as well as other lanthanide fission products which will be removed from the shielded cells using a bagless transfer system. Both materials will be packaged for shipment to Oak Ridge National Laboratory (ORNL). All equipment to carry out this process was designed, procured or fabricated, and installed in a mock-up facility (716-4A) at SRS to allow for simulation testing in a non-radioactive area. This equipment was then dismantled and transferred from 716-4A to 773-A and installed in the SRNL Shielded Cells. After installation in the shielded cells facility testing was performed using water followed by surrogates and cold chemicals. Issues were identified during these evaluations, including equipment issues as well as technical challenges. Many of the issues were rectified during performance of the cold runs, and the remaining have a resolution identified. Table ES-1 provides a summary of all issues identified during the cold run operations, as well as the status and identified resolutions to outstanding issues.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2026

Conversion of real-world aluminum scrap streams into high-performance Al–Mg–Si–Cu automotive alloys using shear assisted processing and extrusion

The conversion of post-consumer aluminum (Al) scrap into usable Al alloys without adding primary Al is challenging because of excess impurities. In this work, >99% post-consumer Twitch, used beverage cans (UBCs), and remelt scrap ingots (RSIs) were used as feedstock materials. As-cast and solution heat-treated feedstock billets were extruded using Shear Assisted Processing and Extrusion (ShAPE) at ~510°C, followed by press quenching. To explore the development of the microstructure, texture, and underlying mechanisms and how they contribute to the overall strengthening in as-extruded and artificially aged samples, scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD) were used to collect microstructure and texture data. The enhanced strength and ductility were corroborated with the microstructural features and crystallographic texture. Simple shear $\textrm{A}/\bar{\textrm{A}}$, $\textrm{A}_1^*/\textrm{A} _2^*$ texture components along with weak $\textrm{C}$ and $\textrm{B}/\bar{\textrm{B}}$ texture components were formed during extrusion; the texture was strengthened after heat treatment. The refined second-phase particles helped to retain the deformed microstructure and texture. The contributions of dislocation and precipitate strengthening were maximized when billets were solution-heat-treated prior to extrusion. This is attributed to the formation of effective supersaturated solid solutions during the ShAPE process, which precipitate out during the peak age treatment. Overall, the highest yield strength of 305 MPa, ultimate tensile strength of 350 MPa, and elongation of 12% were achieved in artificially aged samples, which are comparable to those of Al 6082-T6.

Al alloy↗

NASA NTRS1971

Combustion process of impinging hypergolic propellants

Combustor pressure poppings, stream mixing, and stream separation associated with combustion of impinging hypergolic propellants

White, J. R.↗

NASA NTRS2018

Methods and Apparatus for Aggregation of Multiple Pulse Code Modulation Channels into a Signal Time Division Multiplexing Stream

Methods and apparatus are provided for telemetry processing using a telemetry processor. The telemetry processor can include a plurality of communications interfaces, a computer processor, and data storage. The telemetry processor can buffer sensor data by: receiving a frame of sensor data using a first communications interface and clock data using a second communications interface, receiving an end of frame signal using a third communications interface, and storing the received frame of sensor data in the data storage. After buffering the sensor data, the telemetry processor can generate an encapsulated data packet including a single encapsulated data packet header, the buffered sensor data, and identifiers identifying telemetry devices that provided the sensor data. A format of the encapsulated data packet can comply with a Consultative Committee for Space Data Systems (CCSDS) standard. The telemetry processor can send the encapsulated data packet using a fourth and a fifth communications interfaces.

Chang, Chen J.↗

NASA NTRS2013

Aerospace Fuels from Nonpetroleum Raw Materials

Recycling human metabolic and plastic wastes minimizes cost and increases efficiency by reducing the need to transport consumables and return trash, respectively, from orbit to support a space station crew. If the much larger costs of transporting consumables to the Moon and beyond are taken into account, developing waste recycling technologies becomes imperative and possibly mission enabling. Reduction of terrestrial waste streams while producing energy and/or valuable raw materials is an opportunity being realized by a new generation of visionary entrepreneurs; several relevant technologies are briefly compared, contrasted and assessed for space applications. A two-step approach to nonpetroleum raw materials utilization is presented; the first step involves production of supply or producer gas. This is akin to synthesis gas containing carbon oxides, hydrogen, and simple hydrocarbons. The second step involves production of fuel via the Sabatier process, a methanation reaction, or another gas-to-liquid technology, typically Fischer- Tropsch processing. Optimization to enhance the fraction of product stream relevant to transportation fuels via catalytic (process) development at NASA GRC is described. Energy utilization is a concern for production of fuels whether for operation on the lunar or Martian surface, or beyond. The term "green" relates to not only mitigating excess carbon release but also to the efficiency of energy usage. For space, energy usage can be an essential concern. Other issues of great concern include minimizing impurities in the product stream(s), especially those that are potential health risks and/or could de-grade operations through catalyst poisoning or equipment damage; technologies being developed to remove heteroatom impurities are discussed. Alternative technologies to utilize waste fluids, such as a propulsion option called the resistojet, are discussed. The resistojet is an electric propulsion technology with a powered thruster to vaporize and heat a propellant to high temperature, hot gases are subsequently passed through a converging-diverging nozzle expanding gases to supersonic velocities. A resistojet can accommodate many different fluids, including various reaction chamber (by-)products.

Palaszewski, B. A.↗

NASA NTRS2013

Aerospace Fuels From Nonpetroleum Raw Materials

Recycling human metabolic and plastic wastes minimizes cost and increases efficiency by reducing the need to transport consumables and return trash, respectively, from orbit to support a space station crew. If the much larger costs of transporting consumables to the Moon and beyond are taken into account, developing waste recycling technologies becomes imperative and possibly mission enabling. Reduction of terrestrial waste streams while producing energy and/or valuable raw materials is an opportunity being realized by a new generation of visionary entrepreneurs; several relevant technologies are briefly compared, contrasted and assessed for space applications. A two-step approach to nonpetroleum raw materials utilization is presented; the first step involves production of supply or producer gas. This is akin to synthesis gas containing carbon oxides, hydrogen, and simple hydrocarbons. The second step involves production of fuel via the Sabatier process, a methanation reaction, or another gas-to-liquid technology, typically Fischer-Tropsch processing. Optimization to enhance the fraction of product stream relevant to transportation fuels via catalytic (process) development at NASA Glenn Research Center is described. Energy utilization is a concern for production of fuels whether for operation on the lunar or Martian surface, or beyond. The term green relates to not only mitigating excess carbon release but also to the efficiency of energy usage. For space, energy usage can be an essential concern. Another issue of great concern is minimizing impurities in the product stream(s), especially those that are potential health risks and/or could degrade operations through catalyst poisoning or equipment damage; technologies being developed to remove heteroatom impurities are discussed. Alternative technologies to utilize waste fluids, such as a propulsion option called the resistojet, are discussed. The resistojet is an electric propulsion technology with a powered thruster to vaporize and heat a propellant to high temperature, hot gases are subsequently passed through a converging-diverging nozzle expanding gases to supersonic velocities. A resistojet can accommodate many different fluids, including various reaction chamber (by-)products.

Palaszewski, Bryan A.↗

NASA NTRS1989

Cryogenic reactant storage for lunar base regenerative fuel cells

There are major advantages to be gained by integrating a cryogenic reactant storage system with a hydrogen-oxygen regenerative fuel cell (RFC) to provide on-site electrical power during the lunar night. Although applicable to any power system using hydrogen-oxygen RFC's for energy storage, cryogenic reactant storage offers a significant benefit whenever the sun/shade cycle and energy storage period approach hundreds of hours. For solar power installations on the moon, cryogenic reactant storage reduces overall specific mass and meteoroid vulnerability of the system. In addition, it offers synergistic benefits to on-site users, such as availability of primary fuel cell reactants for surface rover vehicles and cryogenic propellants for OTV's. The integration involves processing and storing the RFC reactant streams as cryogenic liquids rather than pressurized gases, so that reactant containment (tankage per unit mass of reactants) can be greatly reduced. Hydrogen-oxygen alkaline RFC's, GaAs photovoltaic (PV) arrays, and space cryogenic processing/refrigeration technologies are assumed to be available for the conceptual system design. Advantages are demonstrated by comparing the characteristics of two power system concepts: a conventional lunar surface PV/RFC power system using pressurized gas storage in SOA filament wound pressure vessels and, that same system with gas liquefaction and storage replacing the pressurized storage. Comparisons are made at 20 and 250 kWe. Although cryogenic storage adds a processing plant (drying and liquefaction) to the system plus 30 percent more solar array to provide processing power, the approximate order of magnitude reduction in tankage mass, confirmed by this analysis, results in a reduction in overall total system mass of approximately 50 percent.

Kohout, Lisa L.↗

NASA NTRS1989

Cryogenic reactant storage for lunar base regenerative fuel cells

Kohout, Lisa L.↗

DOE OSTI2025

Intelligent experiments through real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and future EIC detectors

This R&D project, initiated by the DOE Nuclear Physics AI-Machine Learning initiative in 2022, leverages AI to address data processing challenges in high-energy nuclear experiments (RHIC, LHC, and future EIC). Our focus is on developing a demonstrator for real-time processing of high-rate data streams from sPHENIX experiment tracking detectors. The limitations of a 15 kHz maximum trigger rate imposed by the calorimeters can be negated by intelligent use of streaming technology in the tracking system. The approach efficiently identifies low momentum rare heavy flavor events in high-rate p+p collisions (3MHz), using Graph Neural Network (GNN) and High Level Synthesis for Machine Learning (hls4ml). Success at sPHENIX promises immediate benefits, minimizing resources and accelerating the heavy-flavor measurements. The approach is transferable to other fields. For the EIC, we develop a DIS-electron tagger using Artificial Intelligence - Machine Learning (AI-ML) algorithms for real-time identification, showcasing the transformative potential of AI and FPGA technologies in high-energy nuclear and particle experiments real-time data processing pipelines.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗