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Measurement of the Static Nonlinear Third-Order Elastic Moduli of Rocks: Problems and Applicability

The third-order elastic (TOE) model has been used to describe the widely observed nonlinear mechanical behaviors of earth materials. In addition to linear elastic constants ( λ , μ ), three nonlinear elastic moduli ( A , B , C ) are required for isotropic rocks. Contrary to previous research on dynamic TOE moduli, this study followed the protocol to measure strain and stress under uniaxial and hydrostatic compressive tests statically, which were later used to invert for the full set of TOE moduli for four standard rock types with differing pore structures of a porous oolitic limestone, quartz-rich sandstones, and a dense crystalline basalt. The applicability of the TOE model to characterize nonlinearity depends on the fulfillment of path-independence and small-strain assumptions. Using the measured static TOE moduli, the finite element model demonstrates that the stress in the vicinity of the wellbore is more amplified than the stress in the linear elastic case, which leads to a wider zone of rock failure around the wellbore. Due to the long-standing discrepancy between static and dynamic moduli, the rarely reported full set of static TOE moduli is necessary and will benefit future research in understanding the effect of rock nonlinearity on geophysical and geomechanical applications, such as long-term safe storage of CO 2 and generating process of geohazards.

58 GEOSCIENCES↗

ANISOTROPY IN COSMIC-RAY ARRIVAL DIRECTIONS IN THE SOUTHERN HEMISPHERE BASED ON SIX YEARS OF DATA FROM THE ICECUBE DETECTOR

The IceCube Neutrino Observatory accumulated a total of 318 billion cosmic-ray-induced muon events between 2009 May and 2015 May. This data set was used for a detailed analysis of the sidereal anisotropy in the arrival directions of cosmic rays in the TeV to PeV energy range. The observed global sidereal anisotropy features large regions of relative excess and deficit, with amplitudes of the order of 10{sup 3} up to about 100 TeV. A decomposition of the arrival direction distribution into spherical harmonics shows that most of the power is contained in the low-multipole ( ℓ ≤ 4) moments. However, higher multipole components are found to be statistically significant down to an angular scale of less than 10°, approaching the angular resolution of the detector. Above 100 TeV, a change in the morphology of the arrival direction distribution is observed, and the anisotropy is characterized by a wide relative deficit whose amplitude increases with primary energy up to at least 5 PeV, the highest energies currently accessible to IceCube. No time dependence of the large- and small-scale structures is observed in the period of six years covered by this analysis. The high-statistics data set reveals more details of the properties of the anisotropy and is potentially able to shed light on the various physical processes that are responsible for the complex angular structure and energy evolution.

79 ASTRONOMY AND ASTROPHYSICS↗

Graph characterization of higher-order structure in atmospheric chemical reaction mechanisms

Atmospheric chemical reactions play an important role in air quality and climate change. While the structure and dynamics of individual chemical reactions are fairly well understood, the emergent properties of the entire atmospheric chemical system, which can involve many different species that participate in many different reactions, are not well described. In this work, we leverage graph-theoretic techniques to characterize patterns of interaction (“motifs”) in three different representations of gas-phase atmospheric chemistry, termed “chemical mechanisms.” These widely used mechanisms, the master chemical mechanism, the GEOS-Chem mechanism, and the Super-Fast mechanism, vary dramatically in scale and application, but they all generally aim to simulate the abundance and variability of chemical species in the atmosphere. This motif analysis quantifies the fundamental patterns of interaction within the mechanisms, which are directly related to their construction. For example, the gas-phase chemistry in the very small Super-Fast mechanism is entirely composed of bimolecular reactions, and its motif distribution matches that of an individual bimolecular reaction well. The larger and more complex mechanisms show emergent motif distributions that differ strongly from any specific reaction type, consistent with their complexity. The proposed motif analysis demonstrates that while these mechanisms all have a similar design goal, their higher-order structure of interactions differs strongly and thus provides a novel set of tools for exploring differences across chemical mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reduced-order microstructure-sensitive protocols to rank-order the transition fatigue resistance of polycrystalline microstructures

We present that the transition fatigue regime between low cycle fatigue (LCF) and high cycle fatigue (HCF) is often addressed in the design and performance evaluation of load-bearing components used in many structural applications. Transition fatigue is characterized by elevated levels of local inelastic deformation in significant regions of the microstructure as compared to HCF. Typically, crystal plasticity finite element method (CPFEM) simulations are performed to model this phenomenon and to rank-order microstructures by their resistance to crack formation and early growth in the regime of transition fatigue. Unfortunately, these approaches require significant computational resources, inhibiting their use to explore novel materials for transition fatigue resistance. Reduced-order, microstructure-sensitive models are needed to accelerate the search for next-generation, fatigue-resistant materials. In a recent study, Paulson et al. (2018) extended the materials knowledge system (MKS) framework for rank-ordering the HCF resistance of polycrystalline microstructures. The efficacy of this approach lies in the reduced-dimensional representation of microstructures through 2-point spatial correlations and principal component analysis (PCA), in addition to the characterization of the HCF response with a small set of performance measures. In this work, these same protocols are critically evaluated for their applicability to rank-order the transition fatigue resistance of the same class of polycrystalline microstructures subjected to increased strain amplitudes. Success in this endeavor requires the formation of homogenization linkages that account for the significantly higher levels of local inelastic deformation and stress redistribution in transition fatigue as compared to HCF. Finally, a set of 12 α-titanium microstructures generated using the open access DREAM.3D software (Groeber and Jackson, 2014) are employed for this evaluation.

2-point correlations↗

Accurate Cross-section Calculations for Low-Energy Electron-Atom Collisions

We describe a recently developed fully relativistic B-spline R-matrix method for atomic structure as well as calculations for electron and photon collision with atoms and ions. The method is based on the solution of the many-electron Fock-Dirac equation and allows to employ non-orthogonal sets of atomic orbitals. A B-spline basis is used to generate both the target description and the R-matrix basis functions in the inner region. Employing B-splines of different orders for the large and small components prevents the appearance of spurious states in the spectrum of the Dirac equation. Using term-dependent and thus nonorthogonal sets of one-electron functions enables us to generate accurate and flexible representations of the target states and the scattering function. Our method is based upon the Dirac-Coulomb Hamiltonian and thus may be employed for any complex atom or ion, without the use of phenomenological core potentials. Example results from recent applications of the method for accurate calculations of low-energy electron scattering from noble gases are presented. In most cases we obtained a substantial improvement over results obtained in previous Breit-Pauli R-matrix calculations.

74 ATOMIC AND MOLECULAR PHYSICS↗

Order reduction in linear state estimation under performance constraints

The design and analysis of minimal-order state estimators for possibly time-varying linear systems, under constraints on the maximal allowable mean-square error, are considered. A global lower bound on the optimal error is derived, along with a lower bound on the minimal estimator order, needed for meeting the performance constraint. The ideal reduced-order estimator which satisfies the lower bound is derived, along with conditions for its realizability. When the ideal estimator is not realizable, its structure forms a suboptimal estimator, which maintains, in some sense, a local optimality property and is called the pseudoideal estimator. The mean-square error of the pseudoideal estimator defines upper bounds on the optimal error and on the estimator order needed for meeting the performance constraint. The lower and the upper bounds on the order define a reduced search set for the design problem. When the distance between the ideal and the pseudoideal estimators is sufficiently small in a certain numerical sense, the pseudoideal estimator may be considered optimal for practical purposes.

Baram, Yoram↗

Magnetic Field Intermittency in the Solar Wind: Parker Solar Probe and SolO Observations Ranging from the Alfvén Region up to 1AU

Parker Solar Probe (PSP) and SolO data are utilized to investigate magnetic field intermittency in the solar wind (SW). Small-scale intermittency (20−100 di) is observed to radially strengthen when methods relying on higher-order moments are considered (SFq; SDK), but no clear trend is observed at larger scales. However, lower-order moment-based methods (e.g., partial variance of increments; PVI) are deemed more appropriate for examining the evolution of the bulk of coherent structures (CSs), PVI ≥ 3. Using PVI, we observe a scale-dependent evolution in the fraction of the data set occupied by CSs, fPVI≥3. Specifically, regardless of the SW speed, a subtle increase is found in fPVI≥3 for ℓ = 20 di, in contrast to a more pronounced radial increase in CSs observed at larger scales. Intermittency is investigated in relation to plasma parameters. Though, slower SW speed intervals exhibit higher fPVI≥6 and higher kurtosis maxima, no statistical differences are observed for fPVI≥3. Highly Alfvénic intervals display lower levels of intermittency. The anisotropy with respect to the angle between the magnetic field and SW flow, ΘVB is investigated. Intermittency is weaker at ΘVB ≈ 0° and is strengthened at larger angles. Considering the evolution at a constant alignment angle, a weakening of intermittency is observed with increasing advection time of the SW. Our results indicate that the strengthening of intermittency in the inner heliosphere is driven by the increase in comparatively highly intermittent perpendicular intervals sampled by the probes with increasing distance, an effect related directly to the evolution of the Parker spiral.

Nikos Sioulas↗

Coupled Calculations in Helical Steam Generator: Validation on Legacy Data

The NEAMS program aims to develop an integrated multi-physics simulation capability “pellet-to-plant” for the design and analysis of future generations of nuclear power plants. In particular, the Reactor Product Line code suite's multi-resolution hierarchy is being designed to ultimately span the full range of length and time scales present in relevant reactor design and safety analyses, as well as scale from desktop to petaflop computing platforms. Flow-induced vibration (FIV) is widespread problem in energy systems because they rely on fluid movement for energy conversion. Vibrating structures may be damaged as fatigue or wear occurs. Given the importance of reliable components in the nuclear industry, flow-induced vibration has long been a major concern in safety and operation of nuclear reactors. In particular, nuclear fuel rods and steam generators have been known to suffer from flow-induced vibration and related failures. Advanced reactors, such as integral Pressurized Water Reactors (PWRs) considered for Small Modular Reactors (SMR), often rely on innovative component designs to meet cost and safety targets. One component that is the subject of advanced designs is the steam generator, some designs of which forego the usual shell-and-tube architecture in order to fit within the primary vessel. In addition to being more cost- and space-efficient, such steam generators need to be more reliable, since failure of the primary vessel represents a potential loss of coolant and a safety concern. A significant amount of data exists on flow-induced vibration in shell-and-tube heat exchangers, and heuristic methods are available to predict their occurrence based on a set of given assumptions. In contrast, advanced designs have far less data available. Advanced modeling and simulation based on coupled structural and fluid simulations have the potential to predict flow-induced vibration in a variety of designs, reducing the need for expensive experimental programs, especially at the design stage. Over the past five years, the Reactor Product Line has developed the integrated multi-physics code suite SHARP. The goal of developing such a tool is to perform multi-physics neutronics, thermal/fluid, and structural mechanics modeling of the components inside the full reactor core or portions of it with a user-specified fidelity. In particular SHARP contains high-fidelity single-physics codes Diablo for structural mechanics and Nek5000 for fluid mechanics calculations. Both codes are state-of-the-art, highly scalable tools that have been extensively validated. These tools form a strong basis on which to build a flow-induced vibration modeling capability. In this report we discuss one-way coupled calculations performed with Nek5000 and Diablo aimed at simulating available FIV experiments in helical steam generators in the turbulent buffeting regime. In this regime one-way coupling is judged sufficient because the pressure loads do not cause substantial displacements. It is also the most common source of vibration in helical steam generators at the low flows expected in integral PWRs. The legacy data is obtained from two datasets developed at Argonne and B&W.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Demonstration of Fully Coupled Calculations in Helical Steam Generator: Toward Predictions of Fluid Elastic Instability

The NEAMS program aims to develop an integrated multi-physics simulation capability “pellet-to-plant” for the design and analysis of future generations of nuclear power plants. In particular, the Reactor Product Line code suite's multi-resolution hierarchy is being designed to ultimately span the full range of length and time scales present in relevant reactor design and safety analyses, as well as scale from desktop to petaflop computing platforms. Flow-induced vibration (FIV) is widespread problem in energy systems because they rely on fluid movement for energy conversion. Vibrating structures may be damaged as fatigue or wear occurs. Given the importance of reliable components in the nuclear industry, flow-induced vibration has long been a major concern in safety and operation of nuclear reactors. In particular, nuclear fuel rods and steam generators have been known to suffer from flow-induced vibration and related failures. Advanced reactors, such as integral Pressurized Water Reactors (PWRs) considered for Small Modular Reactors (SMR), often rely on innovative component designs to meet cost and safety targets. One component that is the subject of advanced designs is the steam generator, some designs of which forego the usual shell-and-tube architecture in order to fit within the primary vessel. In addition to being more cost- and space-efficient, such steam generators need to be more reliable, since failure of the primary vessel represents a potential loss of coolant and a safety concern. A significant amount of data exists on flow-induced vibration in shell-and-tube heat exchangers, and heuristic methods are available to predict their occurrence based on a set of given assumptions. In contrast, advanced designs have far less data available. Advanced modeling and simulation based on coupled structural and fluid simulations have the potential to predict flow-induced vibration in a variety of designs, reducing the need for expensive experimental programs, especially at the design stage. Over the past seven years, the Reactor Product Line has developed the integrated multi-physics code suite SHARP. The goal of developing such a tool is to perform multi-physics neutronics, thermal/fluid, and structural mechanics modeling of the components inside the full reactor core or portions of it with a user-specified fidelity. In particular SHARP contains high-fidelity single-physics codes Diablo for structural mechanics and Nek5000 for fluid mechanics calculations. Both codes are state-of-the-art, highly scalable tools that have been extensively validated. These tools form a strong basis on which to build a flow-induced vibration modeling capability. In the last two years a significant effort was devoted to 1) develop and validate a fully coupled capability in SHARP for Fluid-Structure calculations (FSI) and 2) validate the use of SHARP for one-way coupled calculations in helical steam generators on legacy data available as well as novel experiments. In this report we discuss an extension of previous one-way coupled calculations performed with Nek5000 and Diablo aimed at simulating available FIV experiments in helical steam generators in the turbulent buffeting regime. It was demonstrated that in the buffeting regime one-way coupling was judged sufficient because the pressure loads do not cause substantial displacements. However, higher speeds led to a reduction in accuracy and the need for a fully coupled capability for velocity or approaching the critical velocity and fluid elastic instability. In this report we demonstrate such fully coupled capability on the Argonne test case discussed in previous reports.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Predicting the Conformational Variability of Abl Tyrosine Kinase using Molecular Dynamics Simulations and Markov State Models

Understanding protein conformational variability remains a challenge in drug discovery. The issue arises in protein kinases, whose multiple conformational states can affect the binding of small-molecule inhibitors. To overcome this challenge, we propose a comprehensive computational framework based on Markov state models (MSMs). Our framework integrates the information from explicit-solvent molecular dynamics simulations to accurately rank-order the accessible conformational variants of a target protein. We tested the methodology using Abl kinase with a reference and blind-test set. Only half of the Abl conformational variants discovered by our approach are present in the disclosed X-ray structures. We report the approach successfully identified a protein conformational state not previously observed in public structures but evident in a retrospective analysis of Lilly in-house structures: the X-ray structure of Abl with WHI-P154. Using a MSM-derived model, the free energy landscape and kinetic profile of Abl was analyzed in detail highlighting opportunities for targeting the unique metastable states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Search for Hydrodynamical Interaction Between the ISM and Radio Jets in IC4296

The ROSAT HRI Data set on IC 4296 has been reduced and analysed. A draft paper on the small-scale structure of x-ray emission and its relation to the radio emission has been written. Mackie left the Smithsonian Astrophysical Observatory in September 1997 and in January 1998 he joined the staff at Carter Observatory, New Zealand. Mackie is currently (May 1998) upgrading computer software at Carter to run IRAF-PROS and XSPEC x-ray software packages in order to reduce and analyze archival ROSAT PSPC data on IC 4296. The PSPC results are needed to investigate the hot gas temperature and abundance properties that will be used in conjunction with the radio jet properties to determine the hydrodynamical interaction status of IC 4296, and finalize the results of a research paper.

Mackie, Glen↗

Phase Diagrams of Alloys and Their Hydrides via On-Lattice Graph Neural Networks and Limited Training Data

Efficient prediction of sampling-intensive thermodynamic properties is needed to evaluate material performance and permit high-throughput materials modeling for a diverse array of technology applications. To alleviate the prohibitive computational expense of high-throughput configurational sampling with density functional theory (DFT), surrogate modeling strategies like cluster expansion are many orders of magnitude more efficient but can be difficult to construct in systems with high compositional complexity. We therefore employ minimal-complexity graph neural network models that accurately predict and can even extrapolate to out-of-train distribution formation energies of DFT-relaxed structures from an ideal (unrelaxed) crystallographic representation. This enables the large-scale sampling necessary for various thermodynamic property predictions that may otherwise be intractable and can be achieved with small training data sets. Two exemplars, optimizing the thermodynamic stability of low-density high-entropy alloys and modulating the plateau pressure of hydrogen in metal alloys, demonstrate the power of this approach, which can be extended to a variety of materials discovery and modeling problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Afterglow Population Studies from Swift Follow-Up Observations of Fermi LAT GRBs

The small population of Fermi LAT detected GRBs discovered over the last year has been providing interesting and unexpected clues into GRB prompt and afterglow emission mechanisms. Over the last 5 years, it has been Swift that has provided the robust data set of UV/optical and X-ray afterglow observations that opened many windows into other components of GRB emission structure. We explore the new ability to utilize both of these observatories to study the same GRBs over 10 orders of magnitude in energy, although not always concurrently. Almost all LAT GRBs that have been followed-up by Swift within 1-day have been clearly detected and carefully observed. We will present the context of the lower-energy afterglows of this special subset of GRBs that has > 100 MeV emission compared to the hundreds in the Swift database that may or may not have been observed by LAT, and theorize upon the relationship between these properties and the origin of the high energy gamma-ray emission.

Racusin, Judith L.↗

COMBIgor: Data-Analysis Package for Combinatorial Materials Science

Combinatorial experiments involve synthesis of sample libraries with lateral composition gradients requiring spatially-resolved characterization of structure and properties. Here, due to maturation of combinatorial methods and their successful application in many fields, the modern combinatorial laboratory produces diverse and complex data sets requiring advanced analysis and visualization techniques. In order to utilize these large data sets to uncover new knowledge, the combinatorial scientist must engage in data science. For data science tasks, most laboratories adopt common-purpose data management and visualization software. However, processing and cross-correlating data from various measurement tools is no small task for such generic programs. Here we describe COMBIgor, a purpose-built open-source software package written in the commercial Igor Pro environment, designed to offer a systematic approach to loading, storing, processing, and visualizing combinatorial data sets. It includes (1) methods for loading and storing data sets from combinatorial libraries, (2) routines for streamlined data processing, and (3) data analysis and visualization features to construct figures. Most importantly, COMBIgor is designed to be easily customized by a laboratory, group, or individual in order to integrate additional instruments and data-processing algorithms. Utilizing the capabilities of COMBIgor can significantly reduce the burden of data management on the combinatorial scientist.

97 MATHEMATICS AND COMPUTING↗

Exploring Quantum State Preparation Using Tensor Networks and Sparse Wavefunction Simulations

The variational quantum eigenvalue solver is a powerful hybrid quantum-classical approach that has been suggested as a candidate method to run on near-term quantum hardware for computing ground state electronic energies of molecular systems. However, even for small molecules, the number of variational parameters and qubits required to minimize the electronic energy is beyond the reach of current quantum computers except for small basis sets. We explore a new paradigm for state preparation where we test how much of the optimization can be approximately prepared with classical computers to reduce the number of optimization steps performed using a quantum device. By adapting a recent algorithm for the factorized form of the UCC ansatz, we can study molecular electronic structure problems with up to 64 qubits. In addition, we also test a related approach of using tensor networks to optimize quantum circuits in order to benchmark various lattice models. We present results using these approaches and discuss strategies for incorporating these ideas into variational algorithms involving near-term quantum computers. Our results help demonstrate the strength of the UCC ansatz and address pressing questions about optimal initial parameterizations and circuit construction.

quantum computing↗

The evolution of the FIGARO data reduction system

The Figaro data reduction system originated at Caltech around 1983. It was based on concepts being developed in the U.K. by the Starlink organization, particularly the use of hierarchical self-defining data structures and the abstraction of most user-interaction into a set of 'parameter system' routines. Since 1984 it has continued to be developed at AAO, in collaboration with Starlink and Caltech. It was adopted as Starlink's main spectroscopic data reduction package, although it is by no means limited to spectra; it has operations for images and data cubes and even a few (very specialized) for four-dimensional data hypercubes. It continued to be used at Caltech and will be used at the Keck. It is also in use at a variety of other organizations around the world. Figaro was originally a system for VMS Vaxes. Recently it was ported (at Caltech) to run on SUN's, and work is underway at the University of New South Wales on a DecStation version. It is hoped to coordinate all this work into a unified release, but coordination of the development of a system by organizations covering three continents poses a number of interesting administrative problems. The hierarchical data structures used by Figaro allow it to handle a variety of types of data, and to add new items to data structures. Error and data quality information was added to the basic file format used, error information being particularly useful for infrared data. Cooperating sets of programs can add specific sub-structures to data files to carry information that they understand (polarimetry data containing multiple data arrays, for example), without this affecting the way other programs handle the files. Complex instrument-specific ancillary information can be added to data files written at a telescope and can be used by programs that understand the instrumental details in order to produce properly calibrated data files. Once this preliminary data processing was done the resulting files contain 'ordinary' spectra or images that can be processed by programs that are not instrument-specific. The structures holding the instrumental information can then be discarded from the files. Much effort has gone into trying to make it easy to write Figaro programs; data access subroutines are now available to handle access to all the conventional items found in Figaro files (main data arrays, error information, quality information etc), and programs that only need to access such items can be very simple indeed. A large number of Figaro users do indeed write their own Figaro applications using these routines. The fact that Figaro programs are written as callable subroutines getting information from the user through a small set of parameter routines means that they can be invoked in numerous ways; they are normally linked and run as individual programs (called by a small main routine that is generated automatically), but are also available linked to run under the ADAM data acquisition system and there is an interface that lets them be called as part of a user-written Fortran program. The long-term future of Figaro probably depends to a large extent on how successfully it manages the transition from being a VMS-only system to being a multi-platform system.

Shortridge, K.↗

New Poly(dimethylsiloxane)/Poly(perfluorooctylethyl acrylate) Block Copolymers: Structure and Order Across Multiple Length Scales in Thin Films

Three sets of a new class of low surface tension block copolymers were synthesized consisting of a poly(dimethylsiloxane) (PDMS) block and a poly(perfluorooctylethyl acrylate) (AF8) block. The polymers were prepared using a bromo-terminated PDMS macroinitiator, to which was attached an AF8 block grown using atom transfer radical polymerization (ATRP) in such a designed way that the molecular weight and composition of the two polymer blocks were regularly varied. The interplay of both the phase separated microstructure and the mesomorphic character of the fluorinated domains with their effect on surface structure was evaluated using a suite of analytical tools. Surfaces of spin-coated and thermally annealed films were assessed using a combination of X-ray photoelectron spectroscopy (XPS) and near-edge X-ray absorption fine structure (NEXAFS) studies. Both atomic force microscopy (AFM) measurements and grazing incidence small angle X-ray scattering (GISAXS) studies were carried out to evaluate the microstructure of the thin films. Even in block copolymers in which the PDMS block was the majority component, a significant presence of the lower surface energy AF8 block was detected at the film surface. Moreover, the perfluorooctyl helices of the AF8 repeat units were highly oriented at the surface in an ordered, tilted smectic structure, which was compared with those of the bulk powder samples using wide-angle X-ray powder diffraction (WAXD) studies.

36 MATERIALS SCIENCE↗

Unlocking hidden information in sparse small-angle neutron scattering measurements

Hypothesis Small-Angle Neutron Scattering (SANS) is a powerful technique for studying soft matter systems such as colloids, polymers, and lyotropic phases, providing nanoscale structural insights. However, its effectiveness is limited by low neutron flux, leading to long acquisition times and noisy data. Here, we hypothesize that Bayesian statistical inference using Gaussian Process Regression (GPR) can reconstruct high-fidelity scattering data from sparse measurements by leveraging intensity smoothness and continuity. Experiments and Simulations The method was benchmarked computationally and validated through SANS experiments on various soft matter systems, including wormlike micelles, colloidal suspensions, polymeric structures, and lyotropic phases. GPR-based inference was applied to both experimental and synthetic data to evaluate its effectiveness in noise reduction and intensity reconstruction. Findings GPR significantly enhances SANS data quality and therefore reducing measurement times by up to two orders of magnitude. This cost-effective approach maximizes experimental efficiency, enabling high-throughput studies and real-time monitoring of dynamic systems. It is particularly beneficial for weakly scattering and time-sensitive studies. Beyond SANS, this framework applies to other low-SNR techniques, including laboratory-based small-angle X-ray scattering and various dynamical scattering methods. Furthermore, it offers transformative potential for compact neutron sources, enhancing their viability for structural analysis in resource-limited settings.

Small angle neutron scattering↗