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DOE OSTI2024

Uncertainty quantification of graph convolution neural network models of evolving processes

The application of neural network models to scientific machine learning tasks has proliferated in recent years. In particular, neural networks have proved to be adept at modeling processes with spatial–temporal complexity. Nevertheless, these highly parameterized models have garnered skepticism in their ability to produce outputs with quantified error bounds over the regimes of interest. Hence there is a need to find uncertainty quantification methods that are suitable for neural networks. In this work we present comparisons of the parametric uncertainty quantification of neural networks modeling complex spatial–temporal processes with Hamiltonian Monte Carlo and Stein variational gradient descent and its projected variant. Specifically we apply these methods to graph convolutional neural network models of evolving systems modeled with recurrent neural network and neural ordinary differential equations architectures. We show that Stein variational inference is a viable alternative to Monte Carlo methods with some clear advantages for complex neural network models. For our exemplars, Stein variational interference gave similar pushed forward uncertainty profiles through time compared to Hamiltonian Monte Carlo, albeit with generally more generous variance. As a result, projected Stein variational gradient descent also produced similar uncertainty profiles to the non-projected counterpart, but large reductions in the active weight space were confounded by the stability of the neural network predictions and the convoluted likelihood landscape.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Surrogates for Valve-Controlled Pipe Flow: Accelerating Nuclear Reactor Design

Neural surrogate models are developed to replace expensive steady-state RANS CFD simulations for valve-controlled pipe flow in nuclear reactor design. Using parametric CFD data generated with MOOSE Pronghorn across a range of valve geometry and flow conditions, three approaches are compared: a POD-based reduced-order model, a structured UNet on a cylindrical grid, and unstructured models (DeepONet and BiStride MeshGraphNet) on nondimensionalized point clouds. POD achieves the highest accuracy (99%) with fast inference but requires storing all solution snapshots, while the DeepONet and BSMS-GNN both achieve ~89% accuracy at sub-second inference, with the BSMS-GNN offering superior geometric generalizability. These surrogates enable rapid ranking of candidate valve designs and can warm-start CFD solvers to accelerate convergence, supporting agentic design iteration on the Prometheus platform.

42 - ENGINEERING↗

NASA NTRS2013

On Inferring Extinction Laws in Z -approximately 6 Quasars as Signatures of Supernova Dust

Unusual extinction curves of high-redshift QSOs have been taken as evidence that dust is primarily produced by supernovae at high redshift. In particular, the 3000 ˚A Todini-Ferrara-Maiolino kink in the extinction curve of the z = 6.20 SDSS J1048+4637 has been attributed to supernova dust. Here we discuss the challenges in inferring robust extinction curves of high-redshift QSOs and critically assess previous claims of detection of supernova dust. In particular, we address the sensitivity to the choice of intrinsic QSO spectrum, the need for a long wavelength baseline, and the drawbacks in fitting theoretical extinction curves. In a sample of 21 QSOs at z ∼ 6 we detect significant ultraviolet extinction using existing broad-band optical, near-infrared, and Spitzer photometry. The median extinction curve is consistent with a Small Magellanic Cloud curve with A1450 ∼ 0.7 mag and does not exhibit any conspicuous (restframe) 2175 ˚A or 3000 ˚A features. For two QSOs, SDSS J1044−0125 at z = 5.78 and SDSS J1030+0524 at z = 6.31, we further present X-shooter spectra covering the wavelength range 0.9-2.5 μm. The resulting non-parametric extinction curves do not exhibit the 3000 ˚A kink. Finally, in a re-analysis of literature spectra of SDSS J1048+4637, we do not find evidence for a conspicuous kink. We conclude that the existing evidence for a 3000 ˚A feature is weak and that the overall dust properties at high and low redshift show no significant differences. This, however, does not preclude supernovae from dominating the dust budget at high redshift.

Extinction↗

NASA NTRS2013

The Global Land-Ocean Temperature Index in Relation to Sunspot Number, the Atlantic Multidecadal Oscillation Index, the Mauna Loa Atmospheric Concentration of CO2, and Anthropogenic Carbon Emissions

Global warming/climate change has been a subject of scientific interest since the early 19th century. In particular, increases in the atmospheric concentration of carbon dioxide (CO2) have long been thought to account for Earth's increased warming, although the lack of a dependable set of observational data was apparent as late as the mid 1950s. However, beginning in the late 1950s, being associated with the International Geophysical Year, the opportunity arose to begin accurate continuous monitoring of the Earth's atmospheric concentration of CO2. Consequently, it is now well established that the atmospheric concentration of CO2, while varying seasonally within any particular year, has steadily increased over time. Associated with this rising trend in the atmospheric concentration of CO2 is a rising trend in the surface-air and sea-surface temperatures (SSTs). This Technical Publication (TP) examines the statistical relationships between 10-year moving averages (10-yma) of the Global Land-Ocean Temperature Index (GLOTI), sunspot number (SSN), the Atlantic Multidecadal Oscillation (AMO) index, and the Mauna Loa CO2 (MLCO2) index for the common interval 1964-2006, where the 10-yma values are used to indicate trends in the data. Scatter plots using the 10-yma values between GLOTI and each of the other parameters are determined, both as single-variate and multivariate fits. Scatter plots are also determined for MLCO2 using single-variate and bivariate (BV) fits, based on the GLOTI alone and the GLOTI in combination with the AMO index. On the basis of the inferred preferential fits for MLCO2, estimates for MLCO2 are determined for the interval 1885-1964, thereby yielding an estimate of the preindustrial level of atmospheric concentration of CO2. Lastly, 10-yma values of MLCO2 are compared against 10-yma estimates of the total carbon emissions (TCE) to determine the likelihood that manmade sources of carbon emissions are indeed responsible for the recent warming now being experienced. (Parametric values used in this TP are those available prior to the end of 2012.)

Wilson, Robert M.↗

NASA NTRS2008

Anticipating Cycle 24 Minimum and its Consequences: An Update

This Technical Publication updates estimates for cycle 24 minimum and discusses consequences associated with cycle 23 being a longer than average period cycle and cycle 24 having parametric minimum values smaller (or larger for the case of spotless days) than long term medians. Through December 2007, cycle 23 has persisted 140 mo from its 12-mo moving average (12-mma) minimum monthly mean sunspot number occurrence date (May 1996). Longer than average period cycles of the modern era (since cycle 12) have minimum-to-minimum periods of about 139.0+/-6.3 mo (the 90-percent prediction interval), inferring that cycle 24 s minimum monthly mean sunspot number should be expected before July 2008. The major consequence of this is that, unless cycle 24 is a statistical outlier (like cycle 21), its maximum amplitude (RM) likely will be smaller than previously forecast. If, however, in the course of its rise cycle 24 s 12-mma of the weighted mean latitude (L) of spot groups exceeds 24 deg, then one expects RM >131, and if its 12-mma of highest latitude (H) spot groups exceeds 38 deg, then one expects RM >127. High-latitude new cycle spot groups, while first reported in January 2008, have not, as yet, become the dominant form of spot groups. Minimum values in L and H were observed in mid 2007 and values are now slowly increasing, a precondition for the imminent onset of the new sunspot cycle.

Wilson, Robert M.↗

NASA NTRS1979

On the inference of properties of Saturn's Ring E from energetic charged particle observations

The paper demonstrates that information about Saturn's Ring E particle size is potentially obtainable from observations of Saturnian trapped radiation. It is shown that observations of the radial dependence of the intensities, energy spectra, electron-to-proton intensity ratio, and pitch angle distributions of energetic charged particles trapped outside of Ring A can potentially provide information (1) on the existence of Ring E, (2) on the effective size of the particulate matter therein, and (3) on the magnitude of the radial diffusion coefficient for energetic particles. A parametric study of these possibilities is specialized to the characteristics of the University of Iowa detectors on Pioneer 11 which was scheduled to make a close encounter with Saturn in 1979.

Thomsen, M. F.↗

DOE OSTI2026

Multiprobe constraints on early and late time dark energy

We perform a multiprobe analysis combining cosmic microwave background (CMB) data from Planck and the Atacama Cosmology Telescope (ACT), ACT CMB lensing, and large-scale structure (LSS) measurements from the Dark Energy Spectroscopic Instrument (DESI), including DESI Legacy Imaging Survey (LS) galaxies and baryon acoustic oscillations (BAOs). We present the first 5×2 pt analysis of ACT DR6 lensing, DESI LS, and Planck Integrated Sachs-Wolfe (ISW). Within Λ⁢CDM, this yields 𝑆 8 =𝜎 8 ⁢(Ω 𝑚 /0.3) 0.5 =0.819 ±0.016, in good agreement with primary CMB inferences and provides a sound-horizon-free Hubble constant constraint of 𝐻 0 =70.0±4.4 km s −1 Mpc −1 . Then, combining with CMB primary and BAO, we reconfirm a CMB–BAO discrepancy in the Ω 𝑚 –$\frac{𝐷𝑣}{𝑟𝑑}$ plane, which is heightened when combining BAO with the 5 ×2 pt data vector. We explore two dark-energy extensions that may reconcile this: an early-time modification, early dark energy (EDE), and late-time dynamical dark energy (DDE) parametrized by 𝑤 0 ⁢𝑤 𝑎 . For CMB primary +BAO +5 ×2 pt, we find a 3.3⁢𝜎 preference for DDE over Λ⁢CDM, while EDE is modestly favored at 2.3⁢𝜎. The models address different shortcomings of Λ⁢CDM: DDE relaxes the neutrino mass bound (𝑀 𝜈 <0.17 eV vs <0.050 eV under Λ⁢CDM), making it compatible with neutrino oscillation measurements, while EDE raises the Hubble constant to 𝐻 0 =70.5±1.2 km s −1 Mpc −1 , easing the discrepancy with SH0ES. However, neither model resolves both issues simultaneously. Our analysis indicates that both DDE and EDE remain viable extensions of Λ⁢CDM within current uncertainties and demonstrates the capacity of combined probes to place increasingly stringent constraints on cosmological parameters.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Non-intrusive reduced-order modeling for dynamical systems with spatially localized features

This work presents a non-intrusive reduced-order modeling framework for dynamical systems with spatially localized features characterized by slow singular value decay. The proposed approach builds upon two existing methodologies for reduced and full-order non-intrusive modeling, namely Operator Inference (OpInf) and sparse Full-Order Model (sFOM) inference. We decompose the domain into two complementary subdomains that exhibit fast and slow singular value decay. The dynamics of the subdomain exhibiting slow singular value decay are learned with sFOM while the dynamics with intrinsically low dimensionality on the complementary subdomain are learned with OpInf. The resulting, coupled OpInf-sFOM formulation leverages the computational efficiency of OpInf and the high resolution of sFOM, and thus enables fast non-intrusive predictions for conditions beyond those sampled in the training data set. A novel regularization technique with a closed-form solution based on the Gershgorin disk theorem is introduced to promote stable sFOM and OpInf models. We also provide a data-driven indicator for subdomain selection and ensure solution smoothness over the interface via a post-processing interpolation step. We evaluate the efficiency of the approach in terms of offline and online speedup through a quantitative, parametric computational cost analysis. We demonstrate the coupled OpInf-sFOM formulation for two test cases: a one-dimensional Burgers’ model for which accurate predictions beyond the span of the training snapshots are presented, and a two-dimensional parametric model for the Pine Island Glacier ice thickness dynamics, for which the OpInf-sFOM model achieves an average prediction error on the order of 1% with an online speedup factor of approximately 8$\times$ compared to the numerical simulation.

42 ENGINEERING↗

DOE OSTI2026

Gaussian processes for inferring parton distributions

The extraction of parton distribution functions (PDFs) from experimental or lattice QCD data is an ill-posed inverse problem, where regularization strongly impacts both systematic uncertainties and the reliability of the results. We study a framework based on Gaussian Process Regression (GPR) to reconstruct PDFs from lattice QCD matrix elements. Within a Bayesian framework, Gaussian processes serve as flexible priors that encode uncertainties, correlations, and constraints without imposing rigid functional forms. We investigate a wide range of kernel choices, mean functions, and hyperparameter treatments. We quantify information gained from the data using the Kullback-Leibler divergence. Synthetic data tests demonstrate the consistency and robustness of the method. Our study establishes GPR as a systematic and non-parametric approach to PDF reconstruction, offering controlled uncertainty estimates and reduced model bias in lattice QCD analyses.

hadronic spectroscopy↗

DOE OSTI2024

Weak-form inference for hybrid dynamical systems in ecology

Species subject to predation and environmental threats commonly exhibit variable periods of population boom and bust over long timescales. Understanding and predicting such behaviour, especially given the inherent heterogeneity and stochasticity of exogenous driving factors over short timescales, is an ongoing challenge. A modelling paradigm gaining popularity in the ecological sciences for such multi-scale effects is to couple short-term continuous dynamics to long-term discrete updates. We develop a data-driven method utilizing weak-form equation learning to extract such hybrid governing equations for population dynamics and to estimate the requisite parameters using sparse intermittent measurements of the discrete and continuous variables. The method produces a set of short-term continuous dynamical system equations parametrized by long-term variables, and long-term discrete equations parametrized by short-term variables, allowing direct assessment of interdependencies between the two timescales. We demonstrate the utility of the method on a variety of ecological scenarios and provide extensive tests using models previously derived for epizootics experienced by the North American spongy moth ( Lymantria dispar dispar ).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1994

Attitude stability of a spinning spacecraft during appendage deployment/retraction

The work presented is motivated by the need for a national satellite rescue policy, not the ad hoc policy now in place. In studying different approaches for a national policy, the issue of capture and stabilization of a tumbling spacecraft must be addressed. For a rescue mission involving a tumbling spacecraft, it may be advantageous to have a rescue vehicle which is compact and 'rigid' during the rendezvous/capture phase. After capture, passive stabilization techniques could be utilized as an efficient means of detumbling the resulting system (i.e., both the rescue vehicle and captures spacecraft). Since the rescue vehicle is initially compact and 'rigid,' significant passive stabilization through energy dissipation can only be achieved through the deployment of flexible appendages. Once stabilization is accomplished, retraction of the appendages before maneuvering the system to its final destination may also prove advantageous. It is therefore of paramount interest that we study the effect of appendage deployment/retraction on the attitude stability of a spacecraft. Particular interest should be paid to appendage retraction, since if this process is destabilizing, passive stabilization as proposed may not be useful. Over the past three decades, it has been an 'on-again-off-again affair' with the problem of spacecraft appendage deployment. In most instances, these studies have been numerical simulations of specific spacecraft configurations for which there were specific concerns. The primary focus of these studies was the behavior of the appendage during deployment; the effects of appendage retraction was considered only in one of these studies. What is missing in the literature is a thorough study of the effects of appendage deployment/retraction on the attitude stability of a spacecraft. This paper presents a rigorous analysis of the stability of a spinning spacecraft during the deployment or the retraction of an appendage. The analysis is simplified such that meaningful insights into the problem can be inferred; it is not overly simplified such that critical dynamical behavior is neglected. The system is analyzed assuming that the spacecraft hub is rigid. The appendage deployment mechanism is modeled as a point mass on a massless rod whose length undergoes prescribed changes. Simplified flexibility effects of the appendage are included. The system is examined for stability by linearizing the equations in terms of small deviations from steady, noninterfering coning motion. Routh's procedure for analyzing small deviations from steady motion in dynamical systems is utilized in the analysis. The system of equations are nondimensionalized to facilitate parametric studies. The results are presented in terms of a reduced number of nondimensional parameters so that some general conclusions may be drawn. Verification of the linear analysis is presented through numerical simulations of the complete nonlinear, nonautonomous, coupled equations.

Fitz-Coy, Norman↗

NASA NTRS2004

Bayesian Vision for Shape Recovery

We present a new Bayesian vision technique that aims at recovering a shape from two or more noisy observations taken under similar lighting conditions. The shape is parametrized by a piecewise linear height field, textured by a piecewise linear irradiance field, and we assume Gaussian Markovian priors for both shape vertices and irradiance variables. The observation process. also known as rendering, is modeled by a non-affine projection (e.g. perspective projection) followed by a convolution with a piecewise linear point spread function. and contamination by additive Gaussian noise. We assume that the observation parameters are calibrated beforehand. The major novelty of the proposed method consists of marginalizing out the irradiances considered as nuisance parameters, which is achieved by Laplace approximations. This reduces the inference to minimizing an energy that only depends on the shape vertices, and therefore allows an efficient Iterated Conditional Mode (ICM) optimization scheme to be implemented. A Gaussian approximation of the posterior shape density is computed, thus providing estimates both the geometry and its uncertainty. We illustrate the effectiveness of the new method by shape reconstruction results in a 2D case. A 3D version is currently under development and aims at recovering a surface from multiple images, reconstructing the topography by marginalizing out both albedo and shading.

Jalobeanu, Andre↗

NASA NTRS2005

Analysis of Quantum Information Test-Bed by Parametric Down-Converted Photons Interference Measurement

Quantum optical experiments require all the components involved to be extremely stable relative to each other. The stability can be "measured" by using an interferometric experiment. A pair of coherent photons produced by parametric down-conversion could be chosen to be orthogonally polarized initially. By rotating the polarization of one of the wave packets, they can be recombined at a beam splitter such that interference will occur. Theoretically, the interference will create four terms in the wave function. Two terms with both photons going to the same detector, and two terms will have the photons each going to different detectors. However, the latter will cancel each other out, thus no photons will arrive at the two detectors simultaneously under ideal conditions. The stability Of the test-bed can then be inferred by the dependence of coincidence count on the rotation angle.

To, Wing H.↗

DOE OSTI2024

Earth System Reanalysis in Support of Climate Model Improvements

Recent climate model developments, established through increased model resolution, have led to substantial improvements in model simulations of the time-evolving, coupled Earth system and its subcomponents. However, regardless of resolution, climate models will always produce climate features and variability that differ from the real world and will be prone to biases. This is due to many remaining uncertainties, such as in parametric and structural model uncertainty, in the initial conditions prescribed, and in the prescribed (scenario) forcing which varies on decadal to centennial timescales. Further model improvements are expected to arise specifically from improved representation of physical processes realized through model-data fusion. This will create an unprecedented opportunity to better exploit a large array of Earth observations, from in situ measurements to weather radars and satellite observations, as the resolved scales of the models approach those of the observations. For this, climate DA will be the central tool to bring models and observations into consistency, by improving initial conditions, inferring uncertain model parameters and structure, and quantifying uncertainty. Generally, there will be advantages and complementarities of adjoint-based smoother approaches, ensemble-based filter approaches, or new ML-inspired approaches. Yet, the ever-increasing model resolution will present growing challenges arising from computational cost, calling for new ways of performing data assimilation and model optimization. Using the complementarity in a hybrid approach, blending tools and concepts from variational, ensemble and ML methods might be what is required in the future. In this context ML could be important to handle non-linear responses, and to better approximate non-Gaussian distributions.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1995

The global heliosphere: A parametric study

As the Pioneer 10 and 11 and Voyager 1 and 2 spacecraft continue their penetration into the outer heliosphere, more attention has been focused on the nature of the solar wind interaction with the Very Local Interstellar Medium (VLISM). Since the initial pioneering concepts of Davis in 1955 and Parker in the early 1960's both in situ and remote measurements have led to various constraints that do not fit well into a coherent picture. To provide a context for these various observable constraints, we have adapted an explicitly time-dependent, explicitly three-dimensional magnetohydrodynamic (MHD) code to simulate the dependence of the heliospheric configuration and interaction with the VLISM on the properties of the external medium. The code also allows us to study temporal variations brought about by both short- and long-term changes in the solar wind and/or VLISM properties. We will discuss some of the initial results from this new effort and implications for the distances inferred to the termination shock and heliopause boundary. In particular, we will consider the effect of the Very Local Interstellar Magnetic Field (VLIMF) on the configuration and compare it with inferences from observations of outer heliosphere cosmic rays and the Very Low Frequency (VLF) outer heliospheric radio emissions.

McNutt, R. L., Jr.↗

NASA NTRS2011

What Turns Galaxies Off? the Different Morphologies of Star-Forming and Quiescent Galaxies Since z Approximates 2 from CANDELS

We use HST/WFC3 imaging from the CANDELS multicyc1e treasury survey, in conjunction with the Sloan Digital Sky Survey, to explore the evolution of galactic structure for galaxies with stellar masses > 3 x 10(exp 10) Solar Mass from Z= 2.2 to the present epoch, a time span of 10 Gyr. We explore the relationship between rest-frame optical color, stellar mass, star formation activity and the structural parameters of galaxies as determined from parametric fits to the surface brightness profiles of galaxies. We confirm the dramatic evolution from z= 2.2 to the present day in the number density of non-star-forming galaxies above 3 x 10(exp 10) Solar Mass reported by other authors. We find that the vast majority of these quiescent systems have concentrated light profiles, as parameterized by the Sersic index, and the population of concentrated galaxies grows similarly rapidly. We examine the joint distribution of star formation activity, Sersic index, stellar mass, mass divided by radius (a proxy for velocity dispersion), and stellar surface density. Quiescence correlates poorly with stellar mass at all z < 2.2 (given the approx < 0.2 dex scatter between halo mass and stellar mass at z approximates 0 inferred by More et al, this argues against halo mass being the only factor determining quiescence). Quiescence correlates better with Sersic index, 'velocity dispersion' and stellar surface density, where Sersic index correlates the best (increasingly so at lower redshift). Yet, there is significant scatter between quiescence and galaxy structure: while the vast majority of quiescent galaxies have prominent bulges, many of them have significant disks, and a number of bulge-dominated galaxies have significant star formation. Noting the rarity of quiescent galaxies without prominent bulges, we argue that a prominent bulge (and, perhaps by association, a supermassive black hole) is a necessary but not sufficient condition for quenching star formation on galactic scales over the last 10 Gyr; such a result is qualitatively consistent with the expectations of the AGN feedback paradigm.

Bell, Eric F.↗

DOE OSTI2025

DESI DR2 results. II. Measurements of baryon acoustic oscillations and cosmological constraints

We present baryon acoustic oscillation (BAO) measurements from more than 14 million galaxies and quasars drawn from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2), based on three years of operation. For cosmology inference, these galaxy measurements are combined with DESI Lyman-𝛼 forest BAO results presented in a companion paper (M. Abdul-Karim et al., companion paper, Phys. Rev. D 112, 083514 2025.). The DR2 BAO results are consistent with DESI DR1 and the Sloan Digital Sky Survey, and their distance-redshift relationship matches those from recent compilations of supernovae (SNe) over the same redshift range. The results are well described by a flat Λ cold dark matter (Λ⁢CDM) model, but the parameters preferred by BAO are in mild, 2.3⁢𝜎 tension with those determined from the cosmic microwave background (CMB), although the DESI results are consistent with the acoustic angular scale 𝜃 * that is well measured by Planck. This tension is alleviated by dark energy with a time-evolving equation of state parametrized by 𝑤0 and 𝑤𝑎, which provides a better fit to the data, with a favored solution in the quadrant with 𝑤 0 >−1 and 𝑤 𝑎 <0. This solution is preferred over Λ ⁢CDM at 3.1⁢𝜎 for the combination of DESI BAO and CMB data. When also including SNe, the preference for a dynamical dark energy model over Λ⁢ CDM ranges from 2.8 − 4.2⁢𝜎 depending on which SNe sample is used. We present evidence from other data combinations which also favor the same behavior at high significance. From the combination of DESI and CMB we derive 95% upper limits on the sum of neutrino masses, finding ∑𝑚 𝜈 < 0.064 eV assuming Λ ⁢CDM and ∑𝑚 𝜈 < 0.16 eV in the 𝑤0⁢𝑤𝑎 model. Unless there is an unknown systematic error associated with one or more datasets, it is clear that Λ⁢ CDM is being challenged by the combination of DESI BAO with other measurements and that dynamical dark energy offers a possible solution.

Baryon acoustic oscillations↗

NASA NTRSDate not supplied

Sensitivity of Simulated Radiative Emission from Nitrogen Flows to Chemical Parameters

Numerical models of hypersonic flows rely on chemistry data inferred from experiments and quantum calculations. Experiments from NASA's Electric Arc Shock Tube (EAST) measure the spectral emission of strong shocks in pure nitrogen flows. These spectral profiles are only approximately captured by numerical simulations. To address these discrepancies, one wishes to calibrate some of the chemical parameters to better match experiment. Because there are hundreds of parameters in the numerical model, a sensitivity analysis was carried out on the entire chemistry database to determine which parameters are most important to analyze in the future. In order to perform this work it was necessary to generate a consistent chemical database that interfaced with both the CFD and line-by-line radiation solver. Using Monte Carlo methods, the total Sobol index was calculated for important parameters. Twenty parameters were identified as important across the nitrogen system. However, it was noted that in some spectral regions, the parametric uncertainty was unable to bound EAST measurements. Further improvements could be made by increasing the parameter uncertainties or addressing other sources of modeling error.

Kaelan B Hansson↗