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ACS3: Flight Dynamics

The NASA's Advanced Composite Solar Sail System (ACS3) mission consist of a spacecraft that will deploy an 80 m2 solar sail in Low Earth Orbit (LEO). The main objective of the mission is to demonstrate that the solar wind can impulse the spacecraft to change the semimajor-axis and obtain a different orbit altitude. The sail will be composed of a combination of composite materials with distinct properties, and it will be deployed with lightweight booms from a 12U CubeSat bus, developed by Nanoavionics. The spacecraft will be launched aboard an Electron launch vehicle from Rocket LAB Launch Complex in New Zealand. This paper covers the orbital mechanics and navigation developments to support the mission, from the solar sail trajectory model to the actual flight dynamics system to provide the orbit determination analysis prior to flight. First, we introduce a description of our high-fidelity propagation that accounts for the solar radiation pressure to produce predictive ephemeris of the solar sail performance with several spacecraft attitude modes. As part of our results, we present plots of the expected altitudes achieved by the spacecraft once the solar sail is deployed under various assumptions of the solar weather. In addition to that, we present a full description of our orbit determination process which relies in GPS state vectors to accurately estimate the position and velocity uncertainties at a frequent cadence during the mission. The outcome of this process will be critical to achieving the objective of determining effective altitude change produced by the solar sail.

Solar sail↗
DOE OSTI2015

Inventory Uncertainty Quantification using TENDL Covariance Data in Fispact-II

The new inventory code Fispact-II provides predictions of inventory, radiological quantities and their uncertainties using nuclear data covariance information. Central to the method is a novel fast pathways search algorithm using directed graphs. The pathways output provides (1) an aid to identifying important reactions, (2) fast estimates of uncertainties, (3) reduced models that retain important nuclides and reactions for use in the code's Monte Carlo sensitivity analysis module. Described are the methods that are being implemented for improving uncertainty predictions, quantification and propagation using the covariance data that the recent nuclear data libraries contain. In the TENDL library, above the upper energy of the resolved resonance range, a Monte Carlo method in which the covariance data come from uncertainties of the nuclear model calculations is used. The nuclear data files are read directly by FISPACT-II without any further intermediate processing. Variance and covariance data are processed and used by FISPACT-II to compute uncertainties in collapsed cross sections, and these are in turn used to predict uncertainties in inventories and all derived radiological data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Major improvements on the longwave radiative interactions between surface and clouds in the Polar Regions in atmospheric global circulation model (GCM). Final Project Report

1. Summary of Work and Accomplishments in Year 1 (01/15/2015-01/14/2016). We developed new ice cloud parameterizations based on state-of-the-art MODIS Collection 6 (MC6) ice particle model. Features of the model include the consideration of surface roughness of ice crystals and spectral consistency in cloud property retrievals. Using more than 14,000 particle size distributions (PSDs) from in-situ measurements and the latest ice particle single-scattering property library, our parameterizations provide band-averaged bulk-scattering properties. According to statistics of fittings, the parameterization schemes represent the band-averaged bulk-scattering properties very well. Compared to the ice particle model developed by Fu (1998), flux simulations with the MC6 particle model result in larger upward flux at the top of the atmosphere (TOA) and smaller at the surface for typical cirrus clouds. In the assessment of the effect of longwave light scattering, our results also support the conclusions of previous studies. The error in flux calculations reaches about 10 W/m 2 when a cirrus cloud is thin and its particle size is small. 2. Summary of Work and Accomplishments in Year 2 (01/15/2016-01/14/2017) Clouds are a major modulator of the global radiation budgets. However, representations of clouds in general circulation models (GCMs) neglect many important processes, particularly those related to ice clouds. One major uncertainty source is the radiative transfer scheme in GCMs. To reduce the computational burden in most GCMs, absorption is the only radiative transfer process considered in longwave spectral bands. Recently, a state-of-the-art MC6 ice model has been available, which provides spectral consistency in ice cloud retrievals. With an advanced light scattering library for ice particles, we performed sensitivity studies of the potential impacts on the climate including light scattering for MC6 model and other 11 ice cloud models. Specifically, we modified RRTMG_LW (the GCM version of Longwave Rapid Radiative Transfer Model), a radiative transfer module widely used in GCMs and numerical prediction models, to identify flux simulation differences with and without considering light scattering processes. The simulations with light scattering come from a rigorous radiative solver, DISORT (Discrete Ordinates Radiative Transfer Program for a Multi-Layered Plane-Parallel Medium), are used as benchmarks. The results show that the weighted annual mean biases of RRTMG_LW for the upward flux at the top of the atmosphere, the downward flux at the surface, and the net flux into the atmosphere are about 0.8 ± 0.3, -0.1 ± 0.05, and -0.7 ± 0.3 W m-2, respectively. According to the different the ice crystal shapes, the weighted annual mean bias for heating rate is about -0.006 ± 0.02 to 0.04 K/day. 3. Summary of Work and Accomplishments in Year 3 (01/15/2017-01/14/2018) Since absorption dominates optical properties of clouds in the longwave (LW) spectrum, most of general circulation models (GCMs) only take absorption properties of clouds into account in the radiative transfer modules in order to reduce computational costs. To quantify the biases of excluding LW scattering when clouds exist, we simulated fluxes and heating rates by using satellite data from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, Clouds and the Earth’s Radiant Energy System (CERES) and Moderate Resolution Imaging Spectrometer (MODIS) merged products (CCCM) in 2010. In annual global average, neglecting LW scattering causes overestimation by 2.6 W/m 2 for the top-of-atmosphere (TOA) upward fluxes and underestimation by 1.2 W/m 2 for surface downward fluxes. In particular, regional extreme biases are approximately 12 W/m 2 for TOA upward fluxes and are approximately -3.6 W/m 2 for surface downward fluxes, or are approximately 5% of the global averaged outgoing longwave radiation (OLR) and 1% of the global averaged surface downward fluxes, respectively. In terms of heating rates, on average, LW scattering heats the whole atmosphere column by 0.0045 K/day, heats the cloud layers by 0.0420 K/day, heats the surface by 0.028 K/day, and cools the tropopause by 0.018 K/day.

58 GEOSCIENCES↗
DOE OSTI2022

Advanced stationary and nonstationary kernel designs for domain-aware Gaussian processes

Gaussian process regression is a widely-applied method for function approximation and uncertainty quantification. The technique has gained popularity recently in the machine learning community due to its robustness and interpretability. The mathematical methods we discuss in this paper are an extension of the Gaussian-process framework. We are proposing advanced kernel designs that only allow for functions with certain desirable characteristics to be elements of the reproducing kernel Hilbert space (RKHS) that underlies all kernel methods and serves as the sample space for Gaussian process regression. These desirable characteristics reflect the underlying physics; two obvious examples are symmetry and periodicity constraints. In addition, non-stationary kernel designs can be defined in the same framework to yield flexible multi-task Gaussian processes. We will show the impact of advanced kernel designs on Gaussian processes using several synthetic and two scientific data sets. The results of our research show that including domain knowledge, communicated through advanced kernel designs, has a significant impact on the accuracy and relevance of the function approximation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

The 21 cm signal and the interplay between dark matter annihilations and astrophysical processes

Future dedicated radio interferometers, including HERA and SKA, are very promising tools that aim to study the epoch of reionization and beyond via measurements of the 21 cm signal from neutral hydrogen. Dark matter (DM) annihilations into charged particles change the thermal history of the Universe and, as a consequence, affect the 21 cm signal. Accurately predicting the effect of DM strongly relies on the modeling of annihilations inside halos. In this work, we use up-to-date computations of the energy deposition rates by the products from DM annihilations, a proper treatment of the contribution from DM annihilations in halos, as well as values of the annihilation cross section allowed by the most recent cosmological measurements from the Planck satellite. Given current uncertainties on the description of the astrophysical processes driving the epochs of reionization, X-ray heating and Lyman-α pumping, we find that disentangling DM signatures from purely astrophysical effects, related to early-time star formation processes or late-time galaxy X-ray emissions, will be a challenging task. We conclude that only annihilations of DM particles with masses of ∼100 MeV, could leave an unambiguous imprint on the 21 cm signal and, in particular, on the 21 cm power spectrum. This is in contrast to previous, more optimistic results in the literature, which have claimed that strong signatures might also be present even for much higher DM masses. Additional measurements of the 21 cm signal at different cosmic epochs will be crucial in order to break the strong parameter degeneracies between DM annihilations and astrophysical effects and undoubtedly single out a DM imprint for masses different from ∼100 MeV.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Uncertainty Quantification for Smooth Functional Data with Application to Material Properties

This document outlines a method for processing functional output (i.e., curves) for the ultimate purpose of sampling curves under specified input conditions for use in modeling and simulation uncertainty quantification (UQ) studies. A set of benchmark curves sufficiently representative of the relevant scenario(s) being simulated are provided to the process and formatted as described in Section 1. Principal Component Analysis (PCA) is utilized to discover the components of uncertainty in the benchmark curves and is outlined in Section 2. Section 3 describes the application of uncertainty quantification to the PCA results for the purpose of sampling curves to be used in UQ analysis. Section 4 applies these techniques to an example benchmark dataset. Concluding remarks are provided in the final section.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Upgrading a high-throughput spectrometer for high-frequency (<400 kHz) measurements

The upgraded spectrometer used for charge exchange recombination spectroscopy on the Madison Symmetric Torus resolves emission fluctuations up to 400 kHz. The transimpedance amplifier’s cutoff frequency was increased based upon simulations comparing the change in the measured photon counts for time-dynamic signals. We modeled each signal-processing stage of the diagnostic and scanned the filtering frequency to quantify the uncertainty in the photon counting rate. This modeling showed that uncertainties can be calculated based on assuming each amplification stage is a Poisson process and by calibrating the photon counting rate with a DC light source to address additional variation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Scenario Generation for Built Environment Decision Support under Uncertainty: Case Studies of Airflow Modeling and Climate-Resilient Infrastructure System Design

When confronted with unforeseen challenges, practicing informed decision making is crucial for enhancing resilience in the built environment. While scan-to-building information modeling (BIM) is a well-established approach for creating detailed digital representations of physical assets, its application in assessing and improving infrastructure resilience remains underexplored. This study addresses this gap by proposing a novel application of scan-to-BIM, namely, scan-to-BIM-to-digital twin (S-BIM-DT) workflow. By integrating reality capture and digital twin technologies, this workflow creates continuously updated and accurate digital representations of physical assets, enabling the generation of various scenarios. Unlike traditional methods, the S BIM-DT workflow facilitates continuous model refinement, supporting informed resilience strategies. By combining these technologies into a cohesive process, the workflow facilitates decision making under uncertainty, enabling stakeholders to evaluate and respond to various scenarios effectively. We demonstrate the implementation of the S-BIM-DT workflow through two use cases that highlight its capability to enhance resilience at different scales. The first use case involves the Combined Transportation, Emergency, and Communications Center (CTECC) in Austin, Texas. BIM-enriched computational fluid dynamics (CFD) modeling simulates airflow and develops alternative scenarios for optimizing the heating, ventilation, and air conditioning (HVAC) systems. This approach enhances resilience against airborne health threats in a postCOVID context. The second use case focuses on designated areas within Beaumont, Texas, as part of the Southeast Texas Urban Integrated Field Laboratory (SETx-UIFL) research. By developing inundation maps to assess extreme weather events, this modeling aids in preparedness efforts and informs the development of climate-resilient infrastructure in vulnerable neighborhoods. Results indicate that the S-BIM-DT workflow effectively generates scenarios that enhance resilience in the built environment by facilitating informed decision making. Furthermore, this study serves as a bridge between advanced scan-to-BIM methodologies and the practical strategies needed to improve built infrastructure resilience.

Built environment↗
DOE OSTI2024

AI Driven Experiment Calibration and Control

One critical step on the path from data taking to physics analysis is calibration. For many experiments this step is both time consuming and computationally expensive. The AI Experimental Calibration and Control project seeks to address these issues, starting first with the GlueX Central Drift Chamber (CDC). We demonstrate the ability of a Gaussian Process to estimate the gain correction factor (GCF) of the GlueX CDC accurately, and also the uncertainty of this estimate. Using the estimated GCF, the developed system infers a new high voltage (HV) setting that stabilizes the GCF in the face of changing environmental conditions. This happens in near real time during data taking and produces data which are already approximately gain-calibrated, eliminating the cost of performing those calibrations which vary ±15% with fixed HV. We also demonstrate an implementation of an uncertainty aware system which exploits a key feature of a Gaussian process.

Britton, Thomas↗
DOE OSTI2018

Measurement of Sauter mean diameter in diesel sprays using a scattering–absorption measurement ratio technique

A new diagnostic for the quantification of Sauter mean diameter in high-pressure fuel sprays has been recently developed using combined optical and X-ray measurements at the Georgia Institute of Technology and Argonne National Laboratory, respectively. This diagnostic utilizes liquid scattering extinction measurements from diffuse back-illumination imaging, conducted at Georgia Tech, and liquid absorption measurements from X-ray radiography, conducted at Argonne’s Advanced Photon Source. The new diagnostic, entitled the scattering–absorption measurement ratio, quantifies two-dimensional distributions of path-integrated Sauter mean diameter, enabling the construction of the spatial history of drop size development within practical fuel sprays. This technique offers unique benefits over conventional drop-sizing methods in that it can be more robust in optically dense regions of the spray, while also providing high spatial resolution of the corresponding droplet field. The methodology for quantification of Sauter mean diameter distributions using the scattering–absorption measurement ratio technique has been previously introduced and demonstrated in diesel sprays using the Engine Combustion Network Spray D injector; however, a more detailed treatment of measurement uncertainties has been needed. In this work, we present a summary of the various sources of measurement uncertainty in the scattering–absorption measurement ratio diagnostic, like those due to the experimental setup, data processing methods, and theoretical assumptions, and assess how these sources of uncertainty affect the quantified Sauter mean diameter. The spatially resolved Sauter mean diameter measurements that result from the scattering–absorption measurement ratio diagnostic will be especially valuable to the engine modeling community for the quantitative validation of spray submodels in engine computational fluid dynamics codes. Careful evaluation and quantification of measurement uncertainties are important to support accurate model validation and to ensure the development of more predictive spray models.

42 ENGINEERING↗
NASA NTRS1982

Application of a recursive distortion estimator to the geodetic correction of thematic mapper imagery

It is pointed out that the higher resolution provided by the Thematic Mapper increases the demands on the accuracy needed by the ground processing in correcting for geodetic errors deriving from internal misalignments and uncertainties in the knowledge of spacecraft ephemeris and attitude. In addition, the Thematic Mapper will also process longer imagery intervals than previous missions. The recursive distortion estimator to be used is a Kalman filter. Here, a minimum variance spacecraft state error vector is estimated for known initial covariance of the elements of that vector and known image noise. Tests of the recursive distortion estimator with various spacecraft models carried out using a simulation of real world state vector dynamics are described. A determination is made of the density of control points needed to meet specified geometric correction requirements; it is expressed as a function of imagery interval length and control point measurement error.

Arnold, P.↗
DOE OSTI2012

AHTR Refueling Systems and Process Description

The Advanced High-Temperature Reactor (AHTR) is a design concept for a central station-type [1500 MW(e)] Fluoride salt-cooled High-temperature Reactor (FHR) that is currently undergoing development by Oak Ridge National Laboratory for the US. Department of Energy, Office of Nuclear Energy's Advanced Reactor Concepts program. FHRs, by definition, feature low-pressure liquid fluoride salt cooling, coated-particle fuel, a high-temperature power cycle, and fully passive decay heat rejection. The overall goal of the AHTR development program is to demonstrate the technical feasibility of FHRs as low-cost, large-size power producers while maintaining full passive safety. The AHTR is approaching a preconceptual level of maturity. An initial integrated layout of its major systems, structures, and components (SSCs), and an initial, high-level sequence of operations necessary for constructing and operating the plant is nearing completion. An overview of the current status of the AHTR concept has been recently published and a report providing a more detailed overview of the AHTR structures and mechanical systems is currently in preparation. This report documents the refueling components and processes envisioned at this early development phase. The report is limited to the refueling aspects of the AHTR and does not include overall reactor or power plant design information. The report, however, does include a description of the materials envisioned for the various components and the instrumentation necessary to control the refueling process. The report begins with an overview of the refueling strategy. Next a mechanical description of the AHTR fuel assemblies and core is provided. The reactor vessel upper assemblies are then described. Following this the refueling path structures and the refueling mechanisms and components are described. The sequence of operations necessary to fuel and defuel the reactor is then discussed. The report concludes with a discussion of the levels of maturity of the various SSCs to provide guidance for future technology developments. The conceptual design information presented in this report is very preliminary in nature. Significant uncertainty remains about several aspects of the process and even the radiation and mechanical performance of plate-type coated-particle fuel.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

AHTR Refueling Systems and Process Description

The Advanced High-Temperature Reactor (AHTR) is a design concept for a central station-type [1500 MW(e)] Fluoride salt–cooled High-temperature Reactor (FHR) that is currently undergoing development by Oak Ridge National Laboratory for the US. Department of Energy, Office of Nuclear Energy’s Advanced Reactor Concepts program. FHRs, by definition, feature low-pressure liquid fluoride salt cooling, coated-particle fuel, a high-temperature power cycle, and fully passive decay heat rejection. The overall goal of the AHTR development program is to demonstrate the technical feasibility of FHRs as low-cost, large-size power producers while maintaining full passive safety. The AHTR is approaching a preconceptual level of maturity. An initial integrated layout of its major systems, structures, and components (SSCs), and an initial, high-level sequence of operations necessary for constructing and operating the plant is nearing completion. An overview of the current status of the AHTR concept has been recently published, and a report providing a more detailed overview of the AHTR structures and mechanical systems is currently in preparation. This report documents the refueling components and processes envisioned at this early development phase. The report is limited to the refueling aspects of the AHTR and does not include overall reactor or power plant design information. The report, however, does include a description of the materials envisioned for the various components and the instrumentation necessary to control the refueling process. The report begins with an overview of the refueling strategy. Next a mechanical description of the AHTR fuel assemblies and core is provided. The reactor vessel upper assemblies are then described. Following this the refueling path structures and the refueling mechanisms and components are described. The sequence of operations necessary to fuel and defuel the reactor is then discussed. The report concludes with a discussion of the levels of maturity of the various SSCs to provide guidance for future technology developments. The conceptual design information presented in this report is very preliminary in nature. Significant uncertainty remains about several aspects of the process and even the radiation and mechanical performance of plate-type coated-particle fuel.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1998

PCEMCAN - Probabilistic Ceramic Matrix Composites Analyzer: User's Guide, Version 1.0

PCEMCAN (Probabalistic CEramic Matrix Composites ANalyzer) is an integrated computer code developed at NASA Lewis Research Center that simulates uncertainties associated with the constituent properties, manufacturing process, and geometric parameters of fiber reinforced ceramic matrix composites and quantifies their random thermomechanical behavior. The PCEMCAN code can perform the deterministic as well as probabilistic analyses to predict thermomechanical properties. This User's guide details the step-by-step procedure to create input file and update/modify the material properties database required to run PCEMCAN computer code. An overview of the geometric conventions, micromechanical unit cell, nonlinear constitutive relationship and probabilistic simulation methodology is also provided in the manual. Fast probability integration as well as Monte-Carlo simulation methods are available for the uncertainty simulation. Various options available in the code to simulate probabilistic material properties and quantify sensitivity of the primitive random variables have been described. The description of deterministic as well as probabilistic results have been described using demonstration problems. For detailed theoretical description of deterministic and probabilistic analyses, the user is referred to the companion documents "Computational Simulation of Continuous Fiber-Reinforced Ceramic Matrix Composite Behavior," NASA TP-3602, 1996 and "Probabilistic Micromechanics and Macromechanics for Ceramic Matrix Composites", NASA TM 4766, June 1997.

Shah, Ashwin R.↗
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↗
NASA NTRS2026

Towards an improved understanding of the Antarctic coastal zone and its contribution to future global sea level

Understanding the coastal zone of the Antarctic Ice Sheet, where it interacts with the Southern Ocean and warmer air masses, is crucial for predicting Antarctica's influence on the global climate. This region has multiple tipping mechanisms that could trigger large, rapid, and potentially irreversible changes in the coming centuries. The Antarctic Ice Sheet remains the largest source of uncertainty in future sea-level projections. Insufficient knowledge of bed topography beneath the ice shelves and the coastal ice sheet is not yet well documented, but is a major source of this uncertainty. This review assesses current knowledge of the coastal zone and highlights methods to investigate it, including aerogeophysical surveys, ground- and ship-based measurements, satellite observations, and computer modeling. An ensemble analysis of published bed topography datasets identifies significant data gaps and their regional distribution, framed in the context of current ice-sheet behavior and potential instability. We propose scientific priorities and guidelines for future aerogeophysical surveys, advocating for a comprehensive, coordinated international effort to build a next-generation dataset of Antarctic bed properties. Such an initiative would significantly advance understanding of the role of coastal processes in ice-sheet dynamics, reducing uncertainties in sea-level rise projections and enhancing predictions of future ocean and climate changes.

Kenichi Matsuoka↗
NASA NTRS2026

Towards an Improved Understanding of the Antarctic Coastal Zone and Its Contribution to Future Global Sea Level

Understanding the coastal zone of the Antarctic Ice Sheet (AIS), where it interacts with the Southern Ocean and warmer air masses, is crucial for predicting Antarctica's influence on the global climate and sea level. This region has multiple tipping mechanisms that could trigger large, rapid, and potentially irreversible changes in the AIS, the Southern Ocean and their global connections in the coming centuries. The AIS remains the largest source of uncertainty in future sea-level projections. Bed topography beneath the ice shelves and the coastal ice sheet is not yet well documented, and is a major source of this uncertainty. This review assesses current knowledge of the coastal zone and highlights methods to investigate it, including aerogeophysical surveys, ground- and ship-based measurements, satellite observations, and computer modeling. An ensemble analysis of published bed topography data sets identifies significant data gaps and their regional distribution, framed in the context of current ice-sheet behavior and potential instability. We propose scientific priorities and guidelines for future aerogeophysical surveys, advocating for a comprehensive, coordinated international effort to build a next-generation data set of Antarctic bed properties. Such an initiative would significantly advance understanding of the role of coastal processes in ice-sheet dynamics, reducing uncertainties in sea-level rise projections and improving predictions of future ocean and climate changes.

Kenichi Matsuoka↗
DOE OSTI2026

Bayesian Exploration and Surrogate Emulation of Nonlinear Beam-Response Geometry in the LBNF Beamline

Next-generation long-baseline neutrino experiments aim to achieve multi-MW proton beam power while reducing accelerator-induced systematic uncertainties. At Fermilab, the LBNF beamline is designed for 1.2 MW operation with PIP-II and is upgradeable to 2.4 MW. DUNE will probe the three-flavor neutrino paradigm and search for CP violation, requiring precise neutrino-flux normalization and improved control of accelerator-related uncertainties. Within the LBNF beamline, the System for On-Axis Neutrino Detection (SAND) will constrain flux uncertainties using precision near-detector measurements, while the Muon Monitor System (MuMS) will provide beamline diagnostics sensitive to the proton beam, target, and horn configuration. However, the pion phase space relevant for DUNE depends simultaneously on many correlated parameters, including beam centroid, beam width, horn current and alignment, target position, optics shifts, and radiation-induced changes. Consequently, MuMS observables exhibit nonlinear and coupled responses that are difficult to characterize using traditional one-parameter scans. To address this challenge, we are developing a Bayesian Exploration framework coupled to physics-informed surrogate emulators trained on Geant4 beamline simulations. Gaussian-process emulators provide both fast predictions and uncertainty estimates, enabling adaptive selection of new simulation points in beam-parameter space. As an initial demonstration, we construct surrogate emulators for MuMS response observables using a verified simulation campaign spanning proton-beam steering conditions. The emulators reproduce the simulated dependence of MuMS centroid and gradient observables while providing predictive uncertainties, and serve as the foundation for future multidimensional exploration including beam width, horn current, and additional beamline parameters. This work establishes a framework for uncertainty-aware beam monitoring, adaptive simulation campaigns, and rapid beam-response inference for future DUNE operations.

Ganguly, Sudeshna [Fermilab] (ORCID:00000003163482↗