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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Technical Gaps in Hanford High-Level Waste Solids Settling Behavior and Settling Time Evaluation for Direct Feed High-Level Waste (DFHLW) Operations

Settling of high-level waste (HLW) solids in process vessels is a key conceptual process step in providing HLW feed directly to the Hanford Waste Treatment and Immobilization Plant (WTP) HLW Vitrification Facility. Direct Feed High-Level Waste (DFHLW) is a potential approach to initiating HLW vitrification prior to completing of the WTP Pretreatment Facility. Settling would be used with subsequent supernatant decant to concentrate HLW feed. To support planning for DFHLW, Washington River Protection Solutions (WRPS) requested support from the Pacific Northwest National Laboratory to evaluate the current data set available to predict the time needed for HLW solids to settle, to identify gaps in the understanding and predictive capability of HLW solids waste settling times, and to provide scoping estimates of the potential settling time. Eight technical gaps were identified for predicting settling times and characteristics of the formed sediment layers including: Gap 1: In-Tank Settling Rates Faster than Settling of Laboratory Samples, Gap 2: Effect of Sludge Leaching/Washing on Predicted Settling Times, Gap 3: Predicting Waste Settling from Waste Chemistry (Waste Type), Gap 4: Predicting Waste Settling from Particle Size and Density Distributions (PSDDs), Gap 5: Insufficient Laboratory and In-Tank Settling Data to Represent Hanford Waste, Gap 6: Methods for Real-Time, In-Tank Tracking of Settling, Gap 7: Prediction of Sediment Erosion Resistance as a Function of Settling Time, and Gap 8: Prediction of Sediment Solids Content as a Function of Settling Time. In addition to the data gaps, an overarching observation of the settling rate and settled layer data is the significant variation in behavior. At similar solids concentrations, settling rates can vary by as much as 3 orders of magnitude depending on the source waste tank, and significantly different settling rates are noted between laboratory and in situ tests for the same waste tank. The range of average solids concentration in existing HLW sediment, which may have been quiescent for decades, can vary from less than 7 wt% to greater than 74 wt% solids. The shear strengths (or yield stresses) measured on laboratory samples range from less than 27 Pa to greater than 6400 Pa. These variations can challenge process planning for the application of a settle/decant process for DFHLW. This report describes the significance of the gaps to the settle/decant process and presents uncertainties by way of examples. Potential technical approaches for resolving these gaps are described and the estimated difficulty in resolving these gaps is evaluated. Based on the significance of the gap and the difficulty of resolution, recommendations are made to address specific gaps. Scoping estimates of the potential settling times for DFHLW solids have been made based on the existing data set with its associated gaps. Depending on the process vessel depth and final sediment concentration, substantial fractions of the scoping estimate results for settling times for characterized HLW exceed the 2-week period that has been previously assumed for process planning. There is also significant disparity, potentially greater than a factor of 5000 difference, in the estimated settling times depending on process vessel depth and final sediment solid concentration. This variation in results underscores the significance of the identified gaps and uncertainties with respect to process planning for utilizing settle/decant operations for DFHLW.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Discovering the Unknowns: A First Step

This article aims at discovering the unknown variables in the system through data analysis. The main idea is to use the time of data collection as a surrogate variable and try to identify the unknown variables by modeling gradual and sudden changes in the data. We use Gaussian process modeling and a sparse representation of the sudden changes to efficiently estimate the large number of parameters in the proposed statistical model. The method is tested on a realistic dataset generated using a one-dimensional implementation of a Magnetized Liner Inertial Fusion (MagLIF) simulation model, and encouraging results are obtained.

42 ENGINEERING↗
DOE OSTI2026

An Exploration of the Equation of State Dependence of Core-collapse Supernova Explosion Outcomes and Signatures

We explore, using a state-of-the-art simulation code in 3D and late-enough times to witness final observables, the dependence of core-collapse supernova explosions on the nuclear equation of state (EOS). Going beyond questions of explodability, we compare final explosion energies, nucleosynthetic yields, recoil kicks, and gravitational-wave and neutrino signatures using the SFHo and DD2 nuclear EOSs for a 9 M ⊙ /solar-metallicity progenitor star. The DD2 EOS is stiffer and has a lower effective nucleon mass. The result is a more extended protoneutron star (PNS) and lower central densities. As a consequence, the mean neutrino energies, final explosion energy, and recoil kick speed are lower. Moreover, the evolution of PNS convection differs between the two EOS models in significant ways. This translates in part into interestingly altered neutrino “light” curves and noticeably altered gravitational-wave signal strengths and frequency characteristics that may be diagnostic. The faster exploding model (SFHo) yields slightly more neutron-rich ejecta and more species with atomic weights between 60 and 90 and a weak r-process. However, this is merely a preliminary study. The next step is a more comprehensive and multiprogenitor set of 3D supernova simulations for various EOSs to late times when the observables have asymptoted. Such a future investigation will have a direct bearing on the neutron star and black hole birth mass functions and the quest toward a fully quantitative theory of supernova observables.

Rusakov, Aleksandr [Princeton University, NJ (Unit↗
DOE OSTI2026

Mitigation of Cu-Induced Grain Boundary Sensitization in Steel Wire Rods Through a Desensitization Heat Treatment

Steel wire rods are essential for manufacturing high-strength steel tire cords. Yet, the presence of residual copper (Cu) in recycled steel can cause grain-boundary sensitization, embrittlement, and deterioration of the mechanical performance of the final product. This study introduces a desensitization heat treatment step designed to redistribute Cu away from austenite grain boundaries after sensitization occurs. The treatment consists of a 10 min dwell at 1000 °C in a 5%H 2 -Ar reducing atmosphere followed by quench. The temperature and hold time were selected based on diffusion calculations to promote solid-state back diffusion of Cu without altering grain morphology. Experimental validation showed that the dwell step reduced the length of Cu-rich sensitized zones of steel wire rod samples containing 0.21 wt.% Cu by approximately 89% and restored the mechanical properties to nearly 95–98% relative to low-Cu baseline steel (0.01 wt.% Cu). Compared with sensitized and as-obtained samples, these results highlight the effectiveness of the proposed method in improving both the microstructure and tensile performance of recycled steel wire rods, enabling their potential application in tire manufacturing.

copper↗
DOE OSTI2023

Design and performance of the Fermilab Constant Fraction Discriminator ASIC

Here, we present the design and performance characterization results of the novel Fermilab Constant Fraction Discriminator ASIC (FCFD) developed to readout low gain avalanche detector (LGAD) signals by directly using a constant fraction discriminator (CFD) to measure signal arrival time. Silicon detectors with time resolutions less than 30ps will play a critical role in future collider experiments, and LGADs have been demonstrated to provide the required time resolution and radiation tolerance for many such applications. The FCFD has a specially designed discriminator that is robust against amplitude variations of the signal from the LGAD that normally requires an additional correction step when using a traditional leading edge discriminator. The application of the CFD directly in the ASIC promises to be more reliable and reduces the complication of evolving time-walk corrections throughout the operational lifetime of the detector system. We will present a summary of the measured performance of the FCFD for input signals generated by internal charge injection, LGAD signals from an infrared laser, and LGAD signals from minimum-ionizing particles. The mean time response for LGAD signals with charge ranging between 5 and 26 fC has been measured to vary no more than 10ps, orders of magnitude more stable than an uncorrected leading edge discriminator based measurement, and effectively removes the need for any additional time-walk correction. The measured contribution to the time resolution from the FCFD ASIC is found to be 10ps for signals with charge above 20fC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

High-Throughput Field Plant Phenotyping: A Self-Supervised Sequential CNN Method to Segment Overlapping Plants

High-throughput plant phenotyping—the use of imaging and remote sensing to record plant growth dynamics—is becoming more widely used. The first step in this process is typically plant segmentation, which requires a well-labeled training dataset to enable accurate segmentation of overlapping plants. However, preparing such training data is both time and labor intensive. To solve this problem, we propose a plant image processing pipeline using a self-supervised sequential convolutional neural network method for in-field phenotyping systems. This first step uses plant pixels from greenhouse images to segment nonoverlapping in-field plants in an early growth stage and then applies the segmentation results from those early-stage images as training data for the separation of plants at later growth stages. The proposed pipeline is efficient and self-supervising in the sense that no human-labeled data are needed. We then combine this approach with functional principal components analysis to reveal the relationship between the growth dynamics of plants and genotypes. We show that the proposed pipeline can accurately separate the pixels of foreground plants and estimate their heights when foreground and background plants overlap and can thus be used to efficiently assess the impact of treatments and genotypes on plant growth in a field environment by computer vision techniques. This approach should be useful for answering important scientific questions in the area of high-throughput phenotyping.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Effect of Sample Mass, Confinement, and Preheating Time on the Thermal Response of LLM‐105: Experiments and Kinetic Analysis

Various small-scale experiments were performed to provide data for developing a model to predict the thermal response of LLM-105 over a wide range of conditions. The thermal decomposition of LLM-105 was studied as a function of sample mass, confinement of volatile products, and preheating time in both isothermal and ramped heating experiments. The thermal decomposition of LLM-105 is a two-step process, as shown by the two exothermic peaks in the heat flow profiles, which were fitted to two nth-order autocatalytic reaction models with a similar activation energy of ∼289 kJ/mol. The magnitude and shape of these peaks varied with sample mass and confinement. Increasing sample mass enhanced the second exotherm with respect to the first one, while increasing the level of confinement promoted a transition from a sublimation-dominated regime towards thermal decomposition. The effect of LLM-105 particle size on the rate of weight loss was evident for open-pan experiments, where bigger particles sublimed at lower temperatures than smaller particles. Thermal response and solid residue composition of LLM-105 samples were analyzed following preheating for different durations. Longer preheating times caused a shift of the second exotherm to lower temperatures and a decrease in the reaction enthalpy, confirming that LLM-105 decay is a consecutive reaction mechanism, probably autocatalytic. In conclusion, the kinetic model derived from ramped experiments was validated against the measured LLM-105 fraction remaining and the enthalpy remaining of the solid residue as a function of preheating times and showed good agreement.

Chemistry - Chemical explosives↗
DOE OSTI2023

Methane, ethane, and propane production in Greenland ice core samples and a first isotopic characterization of excess methane

Air trapped in polar ice provides unique records of the past atmospheric composition ranging from key greenhouse gases such as methane (CH 4 ) to short-lived trace gases like ethane (C 2 H 6 ) and propane (C 3 H 8 ). Recently, the comparison of CH 4 records obtained using different extraction methods revealed disagreements in the CH 4 concentration for the last glacial in Greenland ice. Elevated methane levels were detected in dust-rich ice core sections measured discretely, pointing to a process sensitive to the melt extraction technique. To shed light on the underlying mechanism, we performed targeted experiments and analyzed samples for methane and the short-chain alkanes ethane and propane covering the time interval from 12 to 42 kyr. Here, we report our findings of these elevated alkane concentrations, which scale linearly with the amount of mineral dust within the ice samples. The alkane production happens during the melt extraction step of the classic wet-extraction technique and reaches 14 to 91 ppb of CH 4 excess in dusty ice samples. We document for the first time a co-production of excess methane, ethane, and propane, with the observed concentrations for ethane and propane exceeding their past atmospheric background at least by a factor of 10. Independent of the produced amounts, excess alkanes were produced in a fixed molar ratio of approximately 14 : 2 : 1, indicating a shared origin. The measured carbon isotopic signature of excess methane is (-47.0 ± 2.9) ‰ and its deuterium isotopic signature is (-326 ± 57) ‰. With the co-production ratios of excess alkanes and the isotopic composition of excess methane we established a fingerprint that allows us to constrain potential formation processes. This fingerprint is not in line with a microbial origin. Moreover, an adsorption–desorption process of thermogenic gas on dust particles transported to Greenland does not appear very likely. Instead, the alkane pattern appears to be indicative of abiotic decomposition of organic matter as found in soils and plant leaves.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

An Accelerated Creep Testing Program For Nickel Based Superalloys

In order to improve the energy production within the United States, new materials are developed with the goal of increased functionality. These materials are required to perform at extreme pressures and temperatures (up to and beyond 200MPa and 650â??) as well as be sustainable beyond 105 hours. Before developing these materials into components for power generation, mechanical testing is required to better understand the behavior of these materials at various loads and temperatures. The longest of these tests is the conventional creep test which is a real time test that can beyond 105 hours depending on service conditions. Hundreds of specimens must be tested before being approved for use in power generation, but it is extremely difficult to rapidly qualify when each material is required to exceed 105 hours making testing through conventional means unfeasible. While others have designed accelerated testing methods to help qualify materials, many of these experiments use an empirical approach that requires test data to fit already existing creep data. In this study, an accelerated creep test called the stepped isostress method (SSM) is then applied to wrought Inconel 718 (IN 718) specimens. A test matrix is designed using deformation mechanism maps, time-temperature-transformation diagrams, and time-temperature-precipitation diagrams, in order to ensure that microstructurally, the accelerated creep tests fail similarly to the conventional creep tests. The data from the stepped isostress method is then applied to the McVetty and Sin-hyperbolic (Sinh) constitutive models in order to generate a creep master curve. The results from the model fits are then compared to the conventional creep data done from experiments as well as from the NIMS database for Inconel 718. Optical microscopy and scanning electron microscopy are used to compare the evolution of the microstructure from the conventional creep and accelerated creep tests. It is found that using the Sinh model on the accelerated creep data provides reasonable creep rupture predictions when compared to the scatter band of creep tests. It was also observed that the microstructural evolution between the SSM experiments and creep tests were very similar in terms of the volume fraction of precipitates and phases.

Mach, Robert↗
DOE OSTI2022

Flow-Assisted Selective Mineral Extraction from Seawater

The sustainable production of critical materials from natural sources requires a paradigm shift away from currently used resource-intensive processes. In this paper, we report a single-step, laminar co-flow method (LCM) that leverages non-equilibrium conditions to selectively extract pure Mg(OH) 2 from natural seawater. Conventional seawater-based Mg extraction involves adding individual or a combination of precipitants to obtain Mg(OH) 2 , but the co-existence of Ca 2+ unavoidably results in CaCO 3 impurities requiring additional purification steps. Here we show that the non-equilibrium conditions in LCM achieved using a microfluidics device and by simply co-injecting a NaOH solution with seawater can result in improved selectivity for Mg(OH) 2 unlike in conventional bulk mixing method. The resulting precipitates are characterized for composition and the process yield and purity are optimized through systematic variations of the reaction time and the concentration of NaOH. This is the first demonstration of LCM for selective separation, and as a one-step process that does not rely on novel sorbents, membranes, or external stimuli, it is easy to scale-up. LCM has the potential to be broadly relevant to selective separations from complex feed streams and diverse chemistries—enabling more sustainable materials extraction and processing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

TETRIS-ADAPT-VQE: An adaptive algorithm that yields shallower, denser circuit Ansätze

Adaptive quantum variational algorithms are particularly promising for simulating strongly correlated systems on near-term quantum hardware, but they are not yet viable due, in large part, to the severe coherence time limitations on current devices. In this paper, we introduce an algorithm called TETRIS-ADAPT-VQE (tiling efficient trial circuits with rotations implemented simultaneously adaptive derivative-assembled problem-tailored variational quantum eigensolver), which iteratively builds up variational a few operators at a time in a way dictated by the problem being simulated. This algorithm is a modified version of the ADAPT-VQE algorithm, in which the one-operator-at-a-time rule is lifted to allow for the addition of multiple operators with disjoint supports in each iteration. TETRIS-ADAPT-VQE results in denser but significantly shallower circuits, without increasing the number of controlled- gates or variational parameters. Its advantage over the original algorithm in terms of circuit depths increases with the system size. Moreover, the expensive step of measuring the energy gradient with respect to each candidate unitary at each iteration is performed only a fraction of the time compared with ADAPT-VQE. These improvements bring us closer to the goal of demonstrating a practical quantum advantage on quantum hardware. Published by the American Physical Society 2024

Anastasiou, Panagiotis G. (ORCID:0000000256601791)↗
DOE OSTI2021

New Insights into the High‐Performance Black Phosphorus Anode for Lithium‐Ion Batteries

Abstract Black phosphorus (BP) is a promising anode material in lithium‐ion batteries (LIBs) owing to its high electrical conductivity and capacity. However, the huge volume change of BP during cycling induces rapid capacity fading. In addition, the unclear electrochemical mechanism of BP hinders the development of rational designs and preparation of high‐performance BP‐based anodes. Here, a high‐performance nanostructured BP–graphite–carbon nanotubes composite (BP/G/CNTs) synthesized using ball‐milling method is reported. The BP/G/CNTs anode delivers a high initial capacity of 1375 mA h g −1 at 0.15 A g −1 and maintains 1031.7 mA h g −1 after 450 cycles. Excellent high‐rate performance is demonstrated with a capacity of 508.1 mA h g −1 after 3000 cycles at 2 A g −1 . Moreover, for the first time, direct evidence is provided experimentally to present the electrochemical mechanism of BP anodes with three‐step lithiation and delithiation using ex situ X‐ray diffraction (XRD), ex situ X‐ray absorption spectroscopy (XAS), ex situ X‐ray emission spectroscopy, operando XRD, and operando XAS, which reveal the formation of Li 3 P 7 , LiP, and Li 3 P. Furthermore, the study indicates an open‐circuit relaxation effect of the electrode with ex situ and operando XAS analyses.

Li, Minsi↗
DOE OSTI2019

Cloning, Purification, and Characterization of Recombinant Thermostable β-Xylanase Tnap-0700 from Thermotoga naphthophila

The gene of a β-xylanase (Tnap-0700) was cloned from a hyperthermophilic Thermotoga naphthophila strain ATCC BAA-489 and expressed in Escherichia coli BL21 (DE3) via pET-21a (+) as an expression vector. The growth steps were upgraded for highest β-xylanase expression via several factors, for example, IPTG concentration, time of induction, pH, and temperature. The pH and temperature optima for the extreme expression of β-xylanase were 7.0 pH and 37 °C, correspondingly. Recombinant enzyme purified by heat treatment process, then later by immobilized metal ion affinity chromatography. Molecular mass of the purified β-xylanase was 38 kDa observed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). The enzyme was stable at room temperature for 30 days. It exhibited high stability over wide series of temperature 50–90 °C and pH 4.0–9.0 upon the addition of 1 mM Ca{sup +2} and reduced in the existence of Cu{sup +2} and EDTA. The addition of about 10–30% different organic solvents have no considerable effect on enzyme. However, SDSF and urea acting as an inhibitor leads to decrease in the enzyme activity. The β-xylanase enzyme was active to hydrolyze xylan from beechwood forming xylose. Thermostable β-xylanase causes the breakdown of complex carbohydrates into monosaccharide components. This thermostable β-xylanase revealed remarkable properties, which make it an encouraging candidate for various industrial applications especially in the alteration of renewable biomaterials into ethanol production, and biofuels from lignocellulosics has acknowledged much devotion subsequently in the last decade.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Nonlinear control of the minimum safety factor in tokamaks by optimal allocation of spatially moving electron cyclotron current drive

The minimum value of the safety factor profile is related to the magnetohydrodynamic (MHD) stability of the plasma confined in a tokamak. Therefore, active control of the minimum safety factor may mitigate MHD instabilities that can degrade or even terminate plasma confinement. Typically, in most tokamak scenarios, the minimum safety factor evolves spatially with time, i.e., the location at which the safety factor achieves the minimum value changes with time. In addition to the inherent nonlinearities in the minimum safety factor evolution, its spatial variation makes the control design challenging. In particular, complexity in control design may arise from the need for time-dependent nonlinear models that account for spatial variation of the minimum safety factor. Furthermore, the minimum safety factor may drift to locations where the actuator authority is low. The problem of minimum safety factor control with target location tracking and moving electron cyclotron current drive (ECCD) is addressed in this work. A nonlinear time-dependent model that incorporates the spatial variation of the minimum safety factor is presented. A nonlinear controller based on optimal feedback linearization is developed to track a target minimum safety factor. The proposed controller treats the ECCD position as a controllable variable. In other words, the controller prescribes the ECCD position (in addition to the non-inductive powers) in real time based on an optimal criterion that is defined a priori. This work also presents the steps necessary to integrate the minimum safety factor controller with a total energy controller to achieve multiple control objectives simultaneously. In conclusion, the proposed integrated control algorithm is tested using nonlinear simulations in the Control Oriented Transport SIMulator (COTSIM) for a DIII-D tokamak scenario.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

SDYN-GANs: Adversarial learning methods for multistep generative models for general order stochastic dynamics

We introduce adversarial learning methods for data-driven generative modeling of dynamics of nth-order stochastic systems. Our approach builds on Generative Adversarial Networks (GANs) with generative model classes based on stable m-step stochastic numerical integrators. From observations of trajectory samples, we introduce methods for learning long-time predictors and stable representations of the dynamics. Our approaches use discriminators based on Maximum Mean Discrepancy (MMD), training protocols using both conditional and marginal distributions, and methods for learning dynamic responses over different time-scales. We show how our approaches can be used for modeling physical systems to learn force-laws, damping coefficients, and noise-related parameters. Our adversarial learning approaches provide methods for obtaining stable generative models for dynamic tasks including long-time prediction and developing simulations for stochastic systems.

• Artificial intelligence (AI) / machine learning ↗
DOE OSTI2022

Friction extrusion of ODS copper rod made from powder

Meters-long oxide dispersion strengthened copper rods were manufactured directly from powder by a single-step process, called friction extrusion. The average grain size was 880 nm, which was refined 40 times from powder precursor due to extensive shear deformation. Meanwhile, the average size of alumina particles was 60 nm which retains a decent oxide dispersion strengthening. Here, mechanical properties, including hardness, tensile strength, and ductility, were tested and found to have better or similar values than conventional sintered-then-extruded oxide dispersion strengthened copper materials. The presented technique promises a convenient avenue for the fabrication of oxide dispersion strengthened copper from powder.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Root cause analysis of a molten salt pump in FLUSTFA

The primary salt pump installed in the high-temperature FLUoride Salt Test Facility (FLUSTFA) was successfully operated for some time, but later ceased operation. To understand what occurred, a Root Cause Analysis (RCA) was performed. Steps taken to try to get the pump operational include adjusting the shaft position, increasing the heating power of the tape heaters on the pump volute, and manually rotating the pump shaft. While removing the insulation, corrosion was noted on the outside of the pump volute, and decolorization of the insulation and tape heaters was observed. Significant corrosion products were also observed in the pump itself and the piping connected to the pump. The nitrogen cover gas was maintained from before salt was introduced into the loop until the pump was dismounted and continues to be maintained even after the pump was removed. After considering probable scenarios, causes were assigned and corrective actions were developed to prevent those causes. Then, the RCA was presented to an advisory committee for review, the “Review Committee,” consisting of experts in large molten salt systems: Brandon Haugh, David Holcomb, Kevin Robb, and Vicente Rojas. As a result, the advisory committee provided comprehensive feedback, which have been incorporated into a revised RCA. Findings have then been summarized and reported in this publication.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Machine Learning for Optimized Polarization at Jefferson Lab

Polarized cryo-targets and polarized photon beams are widely used in experiments at Jefferson Lab. Traditional methods for maintaining the optimal polarization involve manual adjustments throughout data taking by human shift takers. This may introduce some level of inconsistency simply due to the wide variety of experience and expertise of the shift takers themselves. Implementing machine learning-based control systems can improve the stability of the polarization without relying on human intervention. The cryo-target polarization is influenced by temperature, microwave energy, the distribution of paramagnetic radicals, as well as operational conditions including the radiation dose. Diamond radiators are used to generate linearly polarized photons from a primary electron beam. The energy spectrum of these photons can drift over time due to changes in the primary electron beam conditions and diamond degradation. As a first step towards automating the continuous optimization and control processes, uncertainty aware surrogate models have been developed to predict the polarization based on historical data. This talk will provide an overview of the use cases and models developed, highlighting the collaboration between data scientists and physicists at Jefferson Lab.

Jeske, Torri [Thomas Jefferson National Accelerato↗