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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

First Ever Field Pilot on Alaska's North Slope to Validate the Use of Polymer Floods for Heavy Oil EOR a.k.a Alaska North Slope Field Laboratory (ANSFL)

Alaska’s high viscosity oil resources that range between 20–30+ billion barrels represent about a third of known North Slope original oil in place (OOIP). These resources are primarily concentrated in the Schrader Bluff formation (also called West Sak on the Western North Slope) and Ugnu reservoirs and are categorized as “viscous oils” and “heavy oils” owing to their in-situ viscosities between 5–10,000 cP and up to a million+ cP respectively. The viscous oil deposits are relatively deeper (2,000 – 5,000 ft), whereas the heavy oils are somewhat shallower (2,000 – 4,000 ft). The typically shallow depths and the proximity to the continuous permafrost results in relatively lower formation temperatures and pressures, and consequently higher viscosities. The vertical depth vs. viscosity delineated in Paskvan et al. (2016) differentiates the viscous and heavy oils. As depicted in Paskvan et al. (2016), currently the main focus (referred to as “developing”) is on the viscous oils in the Schrader Bluff formation in the Milne Point Unit (MPU). Notwithstanding this Alaska North Slope (ANS) specific categorization, we use the industry adopted, all-inclusive term “heavy oil” for all high viscosity oils. Resource characterization and additional details can be found in topical publications of Paskvan et al. (2016) and Targac et al. (2005). Despite the vast resource base, the development pace, vis-à-vis the production of heavy oils has been very slow and limited due to multiple factors such as cost, logistics, challenging arctic environment, poor waterflood sweep efficiency due to mobility contrasts, and significantly high minimum miscibility pressures (MMP). Most importantly, typical or standard thermal methods that are commonplace elsewhere (Canada, California) are inapplicable due to the continuous permafrost. As a consequence, cumulative production of heavy and viscous oils is a little over 1% of OOIP slope wide and currently, there is hardly any production from Ugnu. However, on a broader level, these unfavorable factors are outweighed by the fact that (1) these resources, within the established infrastructure, are too large to ignore because of their strategic importance to the Nation and the State of Alaska and (2) Prudhoe Bay type diluent crude oil is still available for heavy oil transport through the Trans Alaska Pipeline System (TAPS). Similarly, from a reservoir standpoint, the following factors also are important offsets: (1) favorable rock characteristics of Schrader Bluff; (2) the promise demonstrated by the initial scoping studies (Seright 2010, 2011) suggesting significant increase of heavy oil recovery using polymer flooding; (3) successful field implementation in Canada, China and elsewhere in the world, and (4) availability of the existing pairs of horizontal injector-producer in Schrader Bluff The foregoing was recognized as the best readily available opportunity for significant investment by the US Department of Energy and the field operator Hilcorp Alaska LLC to conduct the first ever field scale experiment to test the polymer flooding technology to unlock the vast heavy oil resources on ANS. With this primary goal in mind, the research team embarked on a ~4.5 years long project that focused on the field polymer pilot complemented by supporting laboratory and simulation studies. As documented in this final report, over the course of the project, many lessons have been learned and valuable field and supporting laboratory data has been collected, which also is complemented by numerical reservoir simulations. We have been able to establish the injectivity of polymer solution, evidence of significant reduction in the water cut of previously waterflooded pattern, effective propagation of a hydrolyzed polyacrylamide (HPAM), benefits of low salinity water, provide practical guidance on handling of produced fluids containing breakthrough polymer, fit-for-purpose forecast-worthy history matched simulation model, polymer EOR benefit of 700-1000 bopd over waterflood, and most importantly a low polymer utilization factor of ~1.7 lb/stb. In summary this project is deemed as a scientific, technical and economic success, having met all objectives, fulfilled deliverables and within budget, providing impetus to apply polymer EOR throughout the Milne Point Field paving the way for even heavier viscosity oils in the Ugnu area, eventually extending the economic life of TAPS.

02 PETROLEUM↗
DOE OSTI2023

Status Report of Joint RPI/ORNL NCSP Task for Thermal Neutron Total Cross Section Measurements

A new cold neutron moderator system was developed and constructed at the Rensselaer Polytechnic Institute (RPI) Gaerttner Linear Accelerator. This system was then used to measure the neutron total cross section in the thermal energy range for polyethylene, polystyrene, Lucite, and yttrium hydride. In tandem with these measurements, a fitting procedure was developed at Oak Ridge National Laboratory to vary computationally simulated phonon density of states until a fit with differential and integral data was achieved. This model, combined with the new RPI total cross section data, was used to generate thermal scattering law files for the materials measured at RPI.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Electrolyte-Assisted Hydrogen Cycling in Lithium and Sodium Alanates at Low Pressures and Temperatures

An investigation of electrolyte-assisted hydrogen storage reactions in complex aluminum hydrides (LiAlH4 and NaAlH4) reveals significantly reduced reaction times for hydrogen desorption and uptake in the presence of an electrolyte. LiAlH4 evolves ~7.8 wt% H2 over ~3 h in the presence of a Li-KBH4 eutectic at 130 °C compared to ~25 h for the same material without the electrolyte. Similarly, NaAlH4 exhibits 4.8 wt% H2 evolution over ~4 h in the presence of a diglyme electrolyte at 150 °C compared to 4.4 wt% in ~15 h for the same material without the electrolyte. These reduced reaction times are composed of two effects, an increase in reaction rates and a change in the reaction kinetics. While typical solid state dehydrogenation reactions exhibit kinetics with rates that continuously decrease with the extent of reaction, we find that the addition of an electrolyte results in rates that are relatively constant over the full desorption window. Fitting the kinetics to an Avrami-Erofe’ev model supports these observations. The desorption rate coefficients increase in the presence of an electrolyte, suggesting an increase in the velocities of the reactant-product interfaces. In addition, including an electrolyte increases the growth parameters, primarily for the second desorption steps, resulting in the observed relatively constant reaction rates. Similar effects occur upon hydrogen uptake in NaH/Al where the presence of an electrolyte enables hydrogenation under more practical low temperature (75 °C) and pressure (50 bar H2) conditions.

25 ENERGY STORAGE↗
DOE OSTI2021

Two Bright M Dwarfs Hosting Ultra-Short-Period Super-Earths with Earth-like Compositions

We present observations of two bright M dwarfs (TOI-1634 and TOI-1685: J = 9.5–9.6) hosting ultra-short-period (USP) planets identified by the TESS mission. The two stars are similar in temperature, mass, and radius (T {sub eff} ≈ 3500 K, M {sub &middot;} ≈ 0.45–0.46 M {sub ⊙}, and R {sub &middot;} ≈ 0.45–0.46 R {sub ⊙}), and the planets are both super-Earth size (1.25 R {sub ⊕} < R {sub p} < 2.0 R {sub ⊕}). For both systems, light curves from ground-based photometry exhibit planetary transits, whose depths are consistent with those from the TESS photometry. We also refine the transit ephemerides based on the ground-based photometry, finding the orbital periods of P = 0.9893436 ± 0.0000020 days and P = 0.6691416 ± 0.0000019 days for TOI-1634b and TOI-1685b, respectively. Through intensive radial velocity (RV) observations using the InfraRed Doppler (IRD) instrument on the Subaru 8.2 m telescope, we confirm the planetary nature of the TOIs and measure their masses: 10.14 ± 0.95 M {sub ⊕} and 3.43 ± 0.93 M {sub ⊕} for TOI-1634b and TOI-1685b, respectively, when the observed RVs are fitted with a single-planet circular-orbit model. Combining those with the planet radii of R {sub p} = 1.749 ± 0.079 R {sub ⊕} (TOI-1634b) and 1.459 ± 0.065 R {sub ⊕} (TOI-1685b), we find that both USP planets have mean densities consistent with an Earth-like internal composition, which is typical for small USP planets. TOI-1634b is currently the most massive USP planet in this category, and it resides near the radius valley, which makes it a benchmark planet in the context of discussing the size limit of rocky planet cores as well as testing the formation scenarios for USP planets. Excess scatter in the RV residuals for TOI-1685 suggests the presence of a possible secondary planet or unknown activity/instrumental noise in the RV data, but further observations are required to check those possibilities.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Timing Six Energetic Rotation-powered X-Ray Pulsars, Including the Fast-spinning Young PSR J0058-7218 and Big Glitcher PSR J0537-6910

Abstract Measuring a pulsar’s rotational evolution is crucial to understanding the nature of the pulsar. Here, we provide updated timing models for the rotational evolution of six pulsars, five of which are rotation phase-connected using primarily NICER X-ray data. For the newly discovered fast energetic young pulsar, PSR J0058−7218, we increase the baseline of its timing model from 1.4 days to 8 months and not only measure more precisely its spin-down rate ν ̇ = ( − 6.2324 ± 0.0001 ) × 10 − 11 Hz s − 1 but also for the first time the second time derivative of its spin rate ν ̈ = ( 4.2 ± 0.2 ) × 10 − 21 Hz s − 2 . For the fastest and most energetic young pulsar, PSR J0537−6910 (with a 16 ms spin period), we detect four more glitches, for a total of 15 glitches over 4.5 yr of NICER monitoring, and show that its spin-down behavior continues to set this pulsar apart from all others, including a long-term braking index n = −1.234 ± 0.009 and interglitch braking indices that asymptote to ≲7 for long times after a glitch. For PSR J1101−6101, we measure a much more accurate spin-down rate that agrees with a previous value measured without phase connection. For PSR J1412+7922 (also known as Calvera), we extend the baseline of its timing model from our previous 1 yr model to 4.4 yr, and for PSR J1849−0001, we extend the baseline from 1.5 to 4.7 yr. We also present a long-term timing model of the energetic pulsar PSR J1813−1749, by fitting previous radio and X-ray spin frequencies from 2009–2019 and new ones measured here using 2018 NuSTAR and 2021 Chandra data.

Ho, Wynn C. G. (ORCID:0000000260896836)↗
DOE OSTI2024

Angular analysis of B → K * e + e − in the low- q 2 region with new electron identification at Belle

We perform an angular analysis of the B → K * e + e − decay for the dielectron mass squared, q 2 , range of 0.0008 – 1.1200 GeV 2 / c 4 using the full Belle dataset in the K * 0 → K + π − and K * + → K S 0 π + channels, incorporating new methods of electron identification to improve the statistical power of the dataset. This analysis is sensitive to contributions from right-handed currents from physics beyond the Standard Model by constraining the Wilson coefficients C 7 ( ′ ) . We perform a fit to the B → K * e + e − differential decay rate and measure the imaginary component of the transversality amplitude to be A T Im = − 1.27 ± 0.52 ± 0.12 , and the K * transverse asymmetry to be A T ( 2 ) = 0.52 ± 0.53 ± 0.11 , with F L and A T Re fixed to the Standard Model values. The resulting constraints on the value of C 7 ′ are consistent with the Standard Model within a 2 σ confidence interval. Published by the American Physical Society 2024

Ferlewicz, D. (ORCID:0000000243741234)↗
DOE OSTI2021

Methods for Precision Studies of Neutrino Interactions

Accelerator neutrino oscillation experiments provide a sensitive way to investigatea number of major open questions in neutrino physics. To achieve precision neutrinooscillation measurements, we need a good understanding of key aspects of the experiments,such as the detection technologies used and neutrino interactions at few-GeV energies.The MicroBooNE experiment has advanced the development of technologies for LArTPCs.An ultra-violet laser system was introduced to MicroBooNE in order to measure theelectric field in situ, which plays a central role in the formation of charge and lightsignals in LArTPCs. This thesis describes the setup and operation of the laser system. Ideveloped a general methodology to measure the electric field and the consequent spatialdistortion in LArTPCs, which supports precision measurements in accelerator neutrinooscillation experiments. In MicroBooNE, the measured electric field distortions are upto 15 ± 3 % with respect to the nominal value, and the measured spatial distortions areup to 15 ± 3 cm. The result of the electric field measurement is applied to the detectorsimulation and the event reconstruction, which leads to a better detector characterizationfor neutrino analyses. A significant concern for measurements of neutrino interactions ismodel dependence, as the currently available models are not sufficient for describing thepicture of neutrino interacting at few-GeV energies. In this thesis, I developed a detailedstrategy for a model-independent cross-section measurement at low energy transfers,where the available model predictions do not agree with the inclusive measurementsfrom multiple experiments. A likelihood fit technique for cross-section extraction isrealized in an accelerator neutrino experiment using a LArTPC for the first time. Thetreatment of systematic uncertainties developed in this thesis is generally applicable foranalyses using similar fitting techniques. This neutrino interaction study at low energytransfers provides a probe to the poorly understood region of neutrino cross sections. Themeasurement scheme developed here aims to guide future model-independent cross-sectionmeasurements, particularly for neutrino experiments using LArTPCs.

Chen, Yifan↗
DOE OSTI2024

Refractive index of lithium fluoride at high dynamic stresses

Alkali halides are prototypical ionic solids whose refractive index is a fundamental property related to their lattice structure and ionic polarizability. In particular, lithium fluoride (LiF) has the largest band gap of any known transparent material and maintains transparency at high pressures, making it well suited for use as an optical window in dynamic compression experiments. While empirical fits to the measured density dependence of the refractive index have been provided, a model that is valid over the entire pressure range of experiments and based on a polarization-based theoretical description is lacking. We present a refractive index model for dynamically compressed LiF based on the Lorentz-Lorenz equation, where the molecular polarizability is determined using a single oscillator model with a strain polarizability parameter Λ=0.73. Here, we show that our modeling approach provides an excellent match to the LiF refractive index data for both shock and ramp compression experiments to 900 GPa (density compression greater than threefold). Additionally, updated fits are provided to determine the refractive index correction for LiF windows used in dynamic compression experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Determining reference standard strength for neutron-irradiated reduced activation ferritic/martensitic steel F82H by Bayesian method

The deterministic approach widely adopted in the design of structural components relies on systematically defined design limits using empirically determined safety factors. However, this approach is not always appropriate because structures are subjected to a variety of loads in the practical environment, which may result in excessively conservative design limits. In recent years, a more rigorous probabilistic approach that incorporates material strength distributions has become an important solution. In the probabilistic approach, the probability density functions of material strength properties underpin the design criteria. Here, the objective of this study is to identify the density distribution functions that best describe tensile properties of irradiated F82H to define a reference strength for DEMO design. Due to the limited number of existing data, this study specifically employs a Bayesian prediction method based on Monte Carlo simulations to determine a material reference value with statistical reliability and to investigate its effectiveness. For example, the dependence of tensile properties of 300 °C irradiated materials on irradiation damage and the range predicted by 95% Bayesian estimation was evaluated. As a statistical model for the dose dependence of statistical parameters, the normal distribution exhibited a better fit for 0.2% proof strength and tensile strength, whereas the distribution of total elongation data gave comparable reference values for both the normal and Weibull distribution models. Both models gave comparable criteria for the distribution of total elongation data. The Weibull model also gave better results for uniform elongation. The function best describing the model was a logarithmic law for both 0.2% proof strength and tensile strength, while a power law for both total and uniform elongation, which allowed for more comprehensive data prediction of irradiation data with statistical accuracy for DEMO reactor design.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Parameter-Varying Hydrodynamic Model of a Single Vane in a Variable-Geometry Oscillating Surge Wave Energy Converter

This paper presents a preliminary study on the parameter-varying hydrodynamic modeling of an individual vane of a variable-geometry oscillating surge wave energy converter (VGOSWEC). The WEC design incorporates controlled surfaces that can modify their orientation relative to the wave motion, reducing hydrodynamic pressure and related loads. This research focuses on characterizing the behavior of the oscillating WEC using a simplified model and three methods for achieving a continuous parameter-varying model: coarse hydrodynamic parameters, interpolation of hydrodynamic parameters, and a fitting function. The results of this study contribute to the understanding of parameter-varying hydrodynamic effects in variable geometry oscillating WECs. The findings provide insights into the potential for reducing structural loads and improving the overall performance of such devices. Further research and development in this area could lead to advancements in WEC technologies, enabling their integration into the competitive energy market.

analytical models↗
DOE OSTI2023

Modeling DOE Standard Canister Configurations with Updated Surface Chemistry

Road-ready and final disposition packaging configurations for the advanced test reactor (ATR) fuel currently specifies storage within helium backfilled DOE sealed standard canisters. The aluminum cladding of the ATR fuel contains an oxyhydroxide layer of boehmite/bayerite that generates hydrogen when subjected to irradiation. Understanding the effect of this hydrogen buildup over time to important for long term storage considerations. Previous modeling efforts have built a coupled CFD-chemical model to simulate the temperature gas phase concentrations within the DOE sealed standard canisters. These models have coupled the temperature conditions to both the gas phase radiolysis chemistry and the surface chemistry associated with the oxyhydroxide layer. Continued experimental work has identified trends for aluminum surrogate samples with oxyhydroxide layers for tests done at higher dose rates. At low initial doses a fast generation rate of hydrogen occurs which starts to roll over to a lower generation rate as the total dose applied in increased. A previous study created a small-scale chemical model was built to replicate a mini-canister surrogate system at SRNL as well as for the smaller capsule tests performed at INL. The previous iteration of the model utilized step function for its G-values for the hydrogen generation over a 200-year period. This model makes an update to the surface chemistry to account for theorized surface chemistry reactions allowing for oxygen to remain bounded to the oxyhydroxide layer. As additional experiments continue, the kinetic fits may be adjusted to adapt to new data. Three canister configurations are modeled – the base 18-inch, 15-foot DOR standard canister with 30 ATR fuel elements, an 18-inch, 10-foot DOE standard canister with 32 ATR fuel elements and a 24-inch, 10-foot DOE standard canister with 40 ATR fuel elements. In previous reports, the primary sensitivity of the canister conditions was identified as the decay heat of the fuel and the dried condition of the fuel. Only these parameters are studied in the report. For the nominal case with dried fuel, the hydrogen generation is only about 2%, so it is even less than the flammability limit if it were exposed to oxygen. For the densely packed 18-inch case the total hydrogen concentration is only around 4% with the nominal decay heat. For the densely packed 24-inch case the total hydrogen concentration is only 2.5%, roughly 20% higher than the original packing design, and still under flammability conditions if exposed to oxygen.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Experimental Validation of Models of a Hull-Based Tuned Mass Damper System for a Semisubmersible Floating Offshore Wind Turbine Platform

Floating offshore wind turbine designs can be further optimized if the controller and remaining systems are designed together, known as control co-design. To effectively perform control co-design, modeling tools predicting the influence of the control systems on the response of a system must be validated. This article presents an experimental validation that utilizes a scale model of a semisubmersible platform for an offshore wind turbine that is fitted with adjustable tuned mass dampers. These dampers can be tuned to attenuate either the hull-pitch resonance or the tower-bending resonance. The data from the experiment are used to validate state-of-the-art modeling tools. It is shown that the models capture the overall effects of the tuned mass dampers; however, some models overpredict the reduction in platform pitch motion when the dampers are tuned to the pitch resonance. The relative reduction in the tower-base bending moment is more consistently captured by the models when the dampers are tuned to the tower-bending resonance. However, there are significant differences in the absolute level of tower-base bending moment between the models and the experiment. Much of the differences observed are a consequence of the challenge with accurately predicting the baseline platform resonance motion and the tower-bending moment, which should be addressed in future modeling efforts.

17 WIND ENERGY↗
DOE OSTI2025

Physical Interpretation of Early Battery Life Prediction Models

Early battery life prediction models are most useful for R&D if they help us understand the early changes in battery electrochemical response that correspond with long-term degradation and failure. Linear regression models such as Fused lasso and Partial Least Squares can fit coefficients directly to high-dimensional electrochemical data like capacity-voltage and ΔV–state-of-charge, i.e., Q(V) and ΔV(SOC) curves, learning coefficients that can be physically interpreted. We leverage the ISU-ILCC battery aging data set to learn high-dimensional coefficients for early battery life prediction from traditional slow-rate capacity check data, demonstrating learning on Q(V), d Q· d V −1 , and ΔV(SOC) curves. A thorough study on the dependence of coefficient values on train/test size and data preprocessing methods is made, demonstrating the reliability of high-dimensional regression approaches unless very small amounts of data are used for model training. For this data set, coefficients from Q(V) and d Q· d V −1 models highlight changes in electrode stoichiometry due to lithium loss, while ΔV(SOC) coefficients highlight changes in positive electrode diffusivity due to particle cracking as well as electrode stoichiometry shifts. By directly interpreting the coefficients of a regression model, we make physical insights into battery degradation mechanisms without requiring the assumptions of traditional battery data analysis methods.

25 ENERGY STORAGE↗
DOE OSTI2026

Combined effective field theory interpretation of Higgs boson, electroweak vector boson, top quark, and multijet measurements

Constraints on Wilson coefficients (WCs) corresponding to dimension-6 operators of the standard model effective field theory (SMEFT) are determined from a simultaneous fit to seven sets of CMS measurements probing Higgs boson, electroweak vector boson, top quark, and multijet production. Measurements of electroweak precision observables are also included and provide complementary constraints to those from the CMS experiment. The CMS measurements, using LHC proton-proton collision data at $\sqrt{s}=13\,\text {Te}\text {V} $, corresponding to integrated luminosities of 36.3 or 138$\,\text {fb}^{-1}$, are chosen to provide sensitivity to a broad set of operators, for which consistent SMEFT predictions can be derived. These are primarily measurements of differential cross sections which are parameterized as functions of the WCs. In measurements targeting ${\text {t}} (\bar{\textrm{t}})\text {X} $ production, SMEFT effects are modelled at the detector level. Individual constraints on 64 WCs, and constraints on 43 linear combinations of WCs, are obtained.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Tuning Shinkarev’s Bicycle: Separating the Parallel Cycles of Photosystem II Using Empirical Wavelet Transform

The oxygen-evolving complex (OEC) of Photosystem II (PSII) catalyzes light-driven water oxidation, a process necessary to sustain Earth’s atmospheric oxygen. Oxygen yields measured during single-turnover flash sequences exhibit period-four oscillations, which form the basis of the Joliot–Kok (S-state) model. However, when the oscillations of other processes contribute to the measured oxygen yield, fitting methods can conflate these signals and distort estimates of inefficiencies and initial S-state populations. To address this, we applied the empirical wavelet transform (EWT) as a model-independent method to separate overlapping oscillators and capture damping dynamics that are not well represented in Fourier analysis. We tested this framework on polarographic flash-oxygen traces from both our Synechocystis sp. PCC 6803 thylakoid membrane preparations and archival datasets on Chlorella and isolated chloroplasts. EWT consistently resolves the expected period-four component alongside a distinct binary oscillation. Simulations suggest that fitting this isolated period-four signal recovers VZAD parameters more accurately than analysis of raw traces, yielding different estimates for S-state distributions and transition probabilities. Notably, this binary oscillation aligns closely with semiquinone dynamics predicted solely from period-four fit parameters. These findings indicate that EWT can effectively distinguish complex signals in oxygen evolution, offering a framework potentially applicable to other spectroscopic probes of the S-state cycle.

Ferrari, Nicholas [Louisiana State Univ., Baton Ro↗
DOE OSTI2024

Measurement of (anti)alpha production in central Pb–Pb collisions at $\sqrt{s_{NN}} = 5.02$ TeV

In this letter, measurements of (anti)alpha production in central (0–10%) Pb–Pb collisions at a center-of-mass energy per nucleon–nucleon pair of $\sqrt{s_{NN}} = 5.02$ TeV are presented, including the first measurement of an antialpha transverse-momentum spectrum. Owing to its large mass, the production of (anti)alpha is expected to be sensitive to different particle production models. The production yields and transverse-momentum spectra of nuclei are of particular interest because they provide a stringent test of these models. The averaged antialpha and alpha spectrum is compared to the spectra of lighter particles, by including it into a common blast-wave fit capturing the hydrodynamic-like flow of all particles. This fit is indicating that the (anti)alpha also participates in the collective expansion of the medium created in the collision. A blast-wave fit including only protons, (anti)alpha, and other light nuclei results in a similar flow velocity as the fit that includes all particles. A similar flow velocity, but a significantly larger kinetic freeze-out temperature is obtained when only protons and light nuclei are included in the fit. The coalescence parameter B 4 is well described by calculations from a statistical hadronization model but significantly underestimated by calculations assuming nucleus formation via coalescence of nucleons. Similarly, the (anti)alpha-to-proton ratio is well described by the statistical hadronization model. On the other hand, coalescence calculations including approaches with different implementations of the (anti)alpha substructure tend to underestimate the data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Particle Filter Based Inference Testing

The primary intent of PAR-FIT (Particle Filter based Inference Testing) is to provide hard inductive evidence that a machine learning model is capable and proven for an individual test input. By examining training data used to form the underlying model functional correlation, an estimate of the reliability that a model will make the correct prediction can be made. The Sequential Probability Ratio Test is used to derive a qualitative evaluation for reliability based on hypothesis testing. The PAR-FIT framework achieves this by implementing a particle filter and the sequential probability ratio test algorithms on the machine learning model training data to determine relevancy of new individual test samples to the training dataset. The kernel function evaluates the local proximity and density of training data used to derive a prediction outcome. Particles are used to probabilistically determine which training data to evaluate for proximity. For test samples that are within a close proximity to and surrounded by multiple training data points, the evaluated reliability of the prediction is high. For test samples that are anomalies not represented by the training dataset, in low density data clusters, or are far from existing data points, the evaluated reliability is low as insufficient training evidence exists to suggest the model is capable of making the correct prediction. Sequential Probability Ratio Test is further used to determine when a hypothesis on whether a signal can be rejected or accepted for use. The ratio test collects sequence information from the particle filter to test whether the signal is anomalous or normal via hypothesis testing of the underlying distributions.

Chen, Edward [Idaho National Laboratory (INL), Ida↗