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All sources NASA NTRS DOE OSTI

DOE OSTI2020

Improvements to CTF Closure Models for Modelling of Two-Phase Flow

This report documents the efforts to improve the CTF prediction of void fraction and two-phase pressure drop by improving two-phase closure models. Previous validation activities have revealed that CTF tends to overpredict void fraction and two-phase pressure drop. In response to this, two approaches were taken to improve CTF’s predictive capabilities. Based on findings that the interfacial drag and subcooled boiling models significantly impact void prediction, alternative closure models for these physical effects were found and implemented into the code. An extensive assessment was performed by using the existing and newly added two-phase experimental data, which showed that void prediction, wall temperature, and two-phase pressure-drop results are improved by using the newly implemented models. A second approach for improving CTF modeling accuracy involved the use of a Bayesian calibration process that uses CTF validation data to optimize selected modeling coefficients and closure model multipliers to achieve a more accurate prediction of experimental results. A similar assessment was performed with calibrated models that improved the void and pressure-drop prediction for test cases that were both included and not included in the calibration dataset. Results of this study will be used to change the models used in CTF to achieve more accurate BWR analyses moving forward. This study also identified opportunities for improving additional closure models and other opportunities to use calibration techniques to improve CTF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Partnership Center for High-Fidelity Boundary Plasma Simulation (Final Report)

Within the Partnership Center for High-Fidelity Boundary Plasma Simulation (HBPS), work at UT-Austin was aimed at improved verification, validation, and uncertainty quantification (VVUQ) for edge plasma simulations and on performing gyrokinetics simulations of pedestal instabilities and turbulence in order to expand foundational understanding of pedestal transport. Regarding VVUQ, the accomplishments can be summarized as follows. First, it was shown that the Moment Preserving Constrained Resampling technique, when applied periodically in particle-in-cell simulations in the XGC code, can dramatically improve the accuracy of the simulation at essentially equivalent computational cost. Second, a technique for estimating model correlations, which are required to solve the model selection and sample allocation problem in multifidelity UQ techniques, without sampling the highest fidelity, most computationally expensive model, was developed and demonstrated. Third, previously developed methods for estimating statistical and discretization errors were applied to numerical methods relevant to edge plasma simulations, namely in particle-in-cell-based approaches, and shown to work. Finally, benchmark studies for comparing gyrokinetic codes were developed and performed, leading to reasonable agreement between four commonly used codes. Regarding physics studies, gyrokinetic simulations to investigate microtearing modes in the DIII-D pedestal were performed using the GENE code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Evaluating Economic Impact: An Investment Tool for Large Language Model Integration in Workweek Management

This paper explores the development and application of an investment tool designed to quantify the costs and potential savings associated with integrating large language models (LLMs) into work week management optimization (WMO) within the nuclear industry. LLMs, with their advanced natural language processing capabilities, can significantly enhance various aspects of work management, such as problem identification, prioritization, planning, scheduling, information retrieval, and information summary. Our investment tool focuses on evaluating the return on investment (ROI) for LLM applications in WMO by considering four pivotal decision factors: model selection, application, user training, and hosting options. This paper details the development and implementation of the ROI model and illustrates its application through multiple case studies, analyzing the impact of different variables, such as work time saved, number of requests, and model performance, on the computed ROI over two years. The computed ROI is also compared over different hosting solutions. Our findings indicate that ROI increases with enhanced work time savings and optimal request load but can decline with high request volumes or increased model costs. This model aids decision-makers in the nuclear industry by providing a structured approach to assessing the economic viability and potential savings from integrating LLMs into WMO processes.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Evaluating Economic Impact: An Investment Tool for Large Language Model Integration in Workweek Management

99 - GENERAL AND MISCELLANEOUS↗

NASA NTRS2012

Status of Turbulence Modeling for Hypersonic Propulsion Flowpaths

This report provides an assessment of current turbulent flow calculation methods for hypersonic propulsion flowpaths, particularly the scramjet engine. Emphasis is placed on Reynolds-averaged Navier-Stokes (RANS) methods, but some discussion of newer meth- ods such as Large Eddy Simulation (LES) is also provided. The report is organized by considering technical issues throughout the scramjet-powered vehicle flowpath including laminar-to-turbulent boundary layer transition, shock wave / turbulent boundary layer interactions, scalar transport modeling (specifically the significance of turbulent Prandtl and Schmidt numbers) and compressible mixing. Unit problems are primarily used to conduct the assessment. In the combustor, results from calculations of a direct connect supersonic combustion experiment are also used to address the effects of turbulence model selection and in particular settings for the turbulent Prandtl and Schmidt numbers. It is concluded that RANS turbulence modeling shortfalls are still a major limitation to the accuracy of hypersonic propulsion simulations, whether considering individual components or an overall system. Newer methods such as LES-based techniques may be promising, but are not yet at a maturity to be used routinely by the hypersonic propulsion community. The need for fundamental experiments to provide data for turbulence model development and validation is discussed.

Georgiadis, Nicholas J.↗

NASA NTRS2018

Test and Analysis of Full-Scale 27.5-Foot-Diameter Stiffened Metallic Launch Vehicle Cylinders

The Shell Buckling Knockdown Factor Project (SBKF) was established with the goal of developing improved (i.e., less-conservative, more robust) shell buckling knockdown factors (KDFs) for modern launch-vehicle structures. To this end, SBKF has engaged in several activities to support the development, validation, and implementation of the new design factors, including subscale and full-scale structural testing. Tests on eight different subscale, 8-foot-diameter, integrally stiffened aluminum-lithium 2195 (Al-Li 2195) cylinders were conducted in order to obtain the majority of the required validation data. In addition, two full-scale, 27.5-foot-diameter, Al-Li 2195, integrally stiffened cylinders were tested to provide additional validation data and to determine structural scaling trends. Presented herein are the details of a recent analysis model development and test and analysis correlation effort on the full-scale test articles. The effects of selected modeling assumptions and approaches are discussed, and results from a modeling sensitivity study are presented. It was found that simplified finite element models, that assume nominal test article geometry and material properties, can predict the overall response characteristics well. However, several discrepancies in the test and analysis results were observed. A sensitivity study was performed to determine the effects of several modeling assumptions and address the observed discrepancies. The results from the study indicated that the evolution of local skin pocket buckling and the presence of residual stresses due to the manufacturing process can have a significant influence on the predicted buckling response of the cylinders considered.

Lovejoy, Andrew E.↗

DOE OSTI2021

The galaxy–halo connection of emission-line galaxies in IllustrisTNG

ABSTRACT We employ the hydrodynamical simulation IllustrisTNG-300-1 to explore the halo occupation distribution (HOD) and environmental dependence of luminous star-forming emission-line galaxies (ELGs) at z ∼ 1. Such galaxies are key targets for current and upcoming cosmological surveys. We select model galaxies through cuts in colour–colour space allowing for a direct comparison with the Extended Baryon Oscillation Spectroscopic Survey and the Dark Energy Spectroscopic Instrument (DESI) surveys and then compare them with galaxies selected based on specific star formation rate (sSFR) and stellar mass. We demonstrate that the ELG populations are twice more likely to reside in lower density regions (sheets) compared with the mass-selected populations and twice less likely to occupy the densest regions of the cosmic web (knots). We also show that the colour-selected and sSFR-selected ELGs exhibit very similar occupation and clustering statistics, finding that the agreement is best for lower redshifts. In contrast with the mass-selected sample, the occupation of haloes by a central ELG peaks at ∼20 per cent. We furthermore explore the dependence of the HOD and the autocorrelation on environment, noticing that at fixed halo mass, galaxies in high-density regions cluster about 10 times more strongly than low-density ones. This result suggests that we should model carefully the galaxy–halo relation and implement assembly bias effects into our models (estimated at ∼4 per cent of the clustering of the DESI colour-selected sample at z = 0.8). Finally, we apply a simple mock recipe to recover the clustering on large scales (r ≳ 1 Mpc h−1) to within 1 per cent by augmenting the HOD model with an environment dependence, demonstrating the power of adopting flexible population models.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1992

A comparison between backscattering models for rough surfaces

The ease of applicability of three scattering models is examined. This is accomplished by considering the time taken to numerically evaluate these models and by comparing their predictions as a function of surface roughness, frequency, incident angle and polarization with the moment-method solution in two dimensions. The complexity of the analytic models in three dimensions and their analytic reduction to high- and low-frequency regions are also compared. The selected models are an integral equation model (IEM), a full wave model (FWM), and the phase perturbation model (PPM). It is noted that in three dimensions, the full-wave model requires an evaluation of a tenfold integral and the phase perturbation model requires a fourfold and a twofold integral, whereas the integral equation model is an algebraic equation in like polarization under single scattering conditions. It is found that both the IEM and PPM agree with the moment-method solution from low to high frequencies numerically.

Chen, K. S.↗

DOE OSTI2021

Plasma-catalyst modeling for materials selection: challenges and opportunities in nitrogen oxidation

Reliable kinetic models are essential to rationalize observations and to guide the selection of appropriate plasma-catalyst combinations. Kinetic models coupling plasma- and heterogeneous-catalytic-chemistries, however, are primitive. Here, we combine reduced plasma chemistries and density functional theory parameterized surface reactions to model NO formation from N2 oxidation, an alternative nitrogen fixation process. We first show plasma excited species can enhance turnover frequencies of both Pt and Au. The enhancing potential is a function of plasma species and their densities. We then compare NO production between plasma/Pt and plasma/Au with an integral reactor model and explore the dependence of NO production as a function of plasma conditions, reactor configurations and chemical compositions. Plasma/Pt generates more NO than plasma/Au under most thermal and plasma parametric conditions. Plasma/Au outperforms plasma/Pt under high plasma excitations at low temperatures. Furthermore, these results highlight that selection of plasma-catalyst combinations should consider the properties of plasmas, materials and the coupling of the two.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1982

Numerical simulation of steady supersonic flow over spinning bodies of revolution

A recently reported parabolized Navier-Stokes code has been employed to compute the supersonic flowfield about a spinning cone and spinning and nonspinning ogive cylinder and boattailed bodies of revolution at moderate incidence. The computations were performed for flow conditions where extensive measurements for wall pressure, boundary-layer velocity profiles, and Magnus force had been obtained. Comparisons between the computational results and experiment indicate excellent agreement for angles of attack up to 6 deg. At angles greater than 6 deg discrepancies are noted which are tentatively attributed to turbulence modeling errors. The comparisons for Magnus effects show that the code accurately predicts the effects of body shape for the selected models.

Sturek, W. B.↗

NASA NTRS2006

Structure Detection of Nonlinear Aeroelastic Systems with Application to Aeroelastic Flight Test Data

This viewgraph presentation reviews the applicability of NARMAX structure detection to aeroelastic systems. In conclusion, the simulation results demonstrate bootstrap approach for structure computation of aircraft structural stiffness provided a high rate of true model selection: 1. T-test and stepwise regression methods had difficulty providing accurate results 2. Work contributes to understanding of the use of structure detection for modelling and identification of aerospace systems. 3. Limitation of model complexity that can be studied with these structure computation techniques 4. Result of the large number of candidate terms, for a given model order, and the data length required to guarantee convergence 5. Another approach to structure computation problem uses a least absolute shrinkage and selection operator (LASSO)

Kukreja, Sunil L.↗

DOE OSTI2023

Pair distribution function analysis of discrete nanomaterials in PDFgui

Pair distribution functions (PDFs) are a leading tool for atomic structure analysis of nanomaterials. However, the most widely used programs for refining atomic structure against PDF data are based on extended crystallographic models, which cannot be applied to discrete, whole nanoparticles. Furthermore, this work describes a straightforward approach to simulate and refine atomistic models of discrete clusters and nanoparticles employing widely used PDF modelling programs such as PDFgui that utilize extended crystallographic models. In this approach, the whole particle to be modelled is contained within an expanded, and otherwise empty, unit cell that is sufficiently large to avoid correlations between atoms in neighbouring unit cells over the r range analyzed. The PDF of the particle is simulated as a composite using two conventional `phases': one that calculates the atom–atom correlations and one that approximates the local number density. This approach is first validated for large nanoparticles that are well modelled by a conventional shape factor model, and then applied to simulate the PDF of discrete particles and low-dimensional materials (graphene and MXene) and to model the experimental PDF data for single-layer FeS nanosheets. A comparison of this approach with the DiffPy-CMI program, which calculates the PDF of discrete species, shows that the composite modelling approach is equally or more accurate. Example input files for implementing this approach within PDFgui and TOPAS, and recommendations for selecting model parameters for reliable application of this refinement strategy, are provided.

36 MATERIALS SCIENCE↗

DOE OSTI2026

A Machine Learning based Approach of Estimating Equivalent Circuit Model Parameters at Different SoCs of Li-ion Batteries from Voltage Relaxation

Abstract: In this study, an approach of estimating the equivalent circuit model (ECM) parameters for Li-ion batteries (LIBs) is proposed based on the voltage value at different intervals while relaxing the LIB after discharge. The typical approach for estimating ECM parameters of a LIB is to conduct electrochemical impedance spectroscopy (EIS) measurements at different frequencies and fit them to a predefined circuit model, which requires additional measuring arrangements and specialized devices. The proposed methodology utilizes four different voltages at 0s, 60s, 360s, and 1800s alongside the specific state of charge (SoC) value for a specific constant discharge current value of ~1C until the relaxation stage to train and evaluate three regression-based machine learning models— Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), and Gaussian Process Regression (GPR)—for estimating the ECM parameters of the selected model. Bayesian optimization is employed for hyperparameter tuning to achieve optimal performance for all the regressor models, among which, the GPR provided the best performance with the root-mean-squared error (RMSE) of less than 4x10-4 on average for the resistive components and less than 0.27 for capacitive components with excellent R2 scores. The simplicity of the approach enables it to eliminate the need for sophisticated measuring equipment and computation power.

Sagar, Md. Samiul [The University of Alabama (UA)]↗

DOE OSTI2022

Comprehensive compartmental model and calibration algorithm for the study of clinical implications of the population-level spread of COVID-19: a study protocol

The complex dynamics of the coronavirus disease 2019 (COVID-19) pandemic has made obtaining reliable long-term forecasts of the disease progression difficult. Simple mechanistic models with deterministic parameters are useful for short-term predictions but have ultimately been unsuccessful in extrapolating the trajectory of the pandemic because of unmodelled dynamics and the unrealistic level of certainty that is assumed in the predictions. We propose a 22-compartment epidemiological model that includes compartments not previously considered concurrently, to account for the effects of vaccination, asymptomatic individuals, inadequate access to hospital care, post-acute COVID-19 and recovery with long-term health complications. Additionally, new connections between compartments introduce new dynamics to the system and provide a framework to study the sensitivity of model outputs to several concurrent effects, including temporary immunity, vaccination rate and vaccine effectiveness. Subject to data availability for a given region, we discuss a means by which population demographics (age, comorbidity, socioeconomic status, sex and geographical location) and clinically relevant information (different variants, different vaccines) can be incorporated within the 22-compartment framework. Considering a probabilistic interpretation of the parameters allows the model's predictions to reflect the current state of uncertainty about the model parameters and model states. We propose the use of a sparse Bayesian learning algorithm for parameter calibration and model selection. This methodology considers a combination of prescribed parameter prior distributions for parameters that are known to be essential to the modelled dynamics and automatic relevance determination priors for parameters whose relevance is questionable. This is useful as it helps prevent overfitting the available epidemiological data when calibrating the parameters of the proposed model. Population-level administrative health data will serve as partial observations of the model states.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1974

Model atmospheres for cool stars

This report contains an extensive series of model atmospheres for cool stars having a wide range in chemical composition. Model atmospheres (temperature, pressure, density, etc.) are tabulated, along with emergent energy flux distributions, limb darkening, and information on convection for selected models. The models are calculated under the usual assumptions of hydrostatic equilibrium, constancy of total energy flux (including transport both by radiation and convection) and local thermodynamic equilibrium. Some molecular and atomic line opacity is accounted for as a straight mean. While cool star atmospheres are regimes of complicated physical conditions, and these atmospheres are necessarily approximate, they should be useful for a number of kinds of spectral and atmospheric analysis.

Johnson, H. R.↗

DOE OSTI2023

Smoothing Lexis diagrams using kernel functions: A contemporary approach

Lexis diagrams are rectangular arrays of event rates indexed by age and period. Analysis of Lexis diagrams is a cornerstone of cancer surveillance research. Typically, population-based descriptive studies analyze multiple Lexis diagrams defined by sex, tumor characteristics, race/ethnicity, geographic region, etc. Inevitably the amount of information per Lexis diminishes with increasing stratification. Several methods have been proposed to smooth observed Lexis diagrams up front to clarify salient patterns and improve summary estimates of averages, gradients, and trends. In this article, we develop a novel bivariate kernel-based smoother that incorporates two key innovations. First, for any given kernel, we calculate its singular values decomposition, and select an optimal truncation point—the number of leading singular vectors to retain—based on the bias-corrected Akaike information criterion. Second, we model-average over a panel of candidate kernels with diverse shapes and bandwidths. The truncated model averaging approach is fast, automatic, has excellent performance, and provides a variance-covariance matrix that takes model selection into account. We present an in-depth case study (invasive estrogen receptor-negative breast cancer incidence among non-Hispanic white women in the United States) and simulate operating characteristics for 20 representative cancers. The truncated model averaging approach consistently outperforms any fixed kernel. Our results support the routine use of the truncated model averaging approach in descriptive studies of cancer.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

A Bayesian framework to investigate radiation reaction in strong fields

Recent experiments aiming to measure phenomena predicted by strong-field quantum electrodynamics (SFQED) have done so by colliding relativistic electron beams and high-power lasers. In such experiments, measurements of collision parameters are not always feasible. However, precise knowledge of these parameters is required to accurately test SFQED. Here, we present a novel Bayesian inference procedure that infers collision parameters that could not be measured on-shot. This procedure is applicable to all-optical non-linear Compton scattering experiments investigating radiation reaction. The framework allows multiple diagnostics to be combined self-consistently and facilitates the inclusion of known information pertaining to the collision parameters. Using this Bayesian analysis, the relative validity of the classical, quantum-continuous and quantum-stochastic models of radiation reaction was compared for several test cases, which demonstrates the accuracy and model selection capability of the framework and highlight its robustness if the experimental values of fixed parameters differ from their values in the models.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Growth of Well-Defined Model Catalysts for Electrochemistry: From Surface Science Studies to Electrocatalytic CO2 Conversion

We combined ultrahigh vacuum (UHV) surface science techniques, electrochemical measurements, and computational modeling to investigate electrocatalytic systems that are crucial components of the carbon management effort, including oxygen evolution reactions (OER) and CO2 reduction reactions (CO2RR). Well-defined Model catalysts were grown on substrates in the UHV chamber and characterized with X-ray photoelectron spectroscopy (XPS) and scanning tunneling microscopy (STM). Selected model electrocatalysts were then tested in electrochemical cells to establish the structure-property relationships in OER and CO2RR. Our results showed that the edge sites of Fe2O3 grown on Au(111) were the most active toward OER and incorporation of Ni at the edge sites (NiFeOx) further boosted their OER activity. We also resolved the size-dependent electrocatalytic CO2-to-CO conversion of the Ag nanoparticle electrocatalysts with average particle diameter between 2 to 6 nm: smaller diameter (< 3 nm) particles favored H2 evolution reaction (HER) due to a high population of Ag edge sites, whereas larger diameter particles favored CO2RR as the population of Ag(100) surface sites grew. We further discovered that electronic interactions between small diameter Ag particles and highly defective carbon supports could break the size-dependent CO2RR selectivity, resulting in highly selective (CO Faradaic Efficiency > 90%) and active Ag nanoparticle electrocatalysts with sizes < 2 nm diameter.

Deng, Xingyi↗