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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,171 records · Page 65

MO-DE-207A-11: Sparse-View CT Reconstruction Via a Novel Non-Local Means Method

Purpose: Sparse-view computed tomography (CT) reconstruction is an effective strategy to reduce the radiation dose delivered to patients. Due to its insufficiency of measurements, traditional non-local means (NLM) based reconstruction methods often lead to over-smoothness in image edges. To address this problem, an adaptive NLM reconstruction method based on rotational invariance (RIANLM) is proposed. Methods: The method consists of four steps: 1) Initializing parameters; 2) Algebraic reconstruction technique (ART) reconstruction using raw projection data; 3) Positivity constraint of the image reconstructed by ART; 4) Update reconstructed image by using RIANLM filtering. In RIANLM, a novel similarity metric that is rotational invariance is proposed and used to calculate the distance between two patches. In this way, any patch with similar structure but different orientation to the reference patch would win a relatively large weight to avoid over-smoothed image. Moreover, the parameter h in RIANLM which controls the decay of the weights is adaptive to avoid over-smoothness, while it in NLM is not adaptive during the whole reconstruction process. The proposed method is named as ART-RIANLM and validated on Shepp-Logan phantom and clinical projection data. Results: In our experiments, the searching neighborhood size is set to 15 by 15 and the similarity window is set to 3 by 3. For the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, the ART-RIANLM produces higher SNR (35.38dB<24.00dB) and lower MAE (0.0006<0.0023) reconstructed image than ART-NLM. The visual inspection demonstrated that the proposed method could suppress artifacts or noises more effectively and preserve image edges better. Similar results were found for clinical data case. Conclusion: A novel ART-RIANLM method for sparse-view CT reconstruction is presented with superior image. Compared to the conventional ART-NLM method, the SNR and MAE from ART-RIANLM increases 47% and decreases 74%, respectively.

60 APPLIED LIFE SCIENCES↗

Purdue Contribution of Fusion Simulation Program

The overall science goal of the FSP is to develop predictive simulation capability for magnetically confined fusion plasmas at an unprecedented level of integration and fidelity. This will directly support and enable effective U.S. participation in research related to the International Thermonuclear Experimental Reactor (ITER) and the overall mission of delivering practical fusion energy. The FSP will address a rich set of scientific issues together with experimental programs, producing validated integrated physics results. This is very well aligned with the mission of the ITER Organization to coordinate with its members the integrated modeling and control of fusion plasmas, including benchmarking and validation activities. [1]. Initial FSP research will focus on two critical areas: 1) the plasma edge and 2) whole device modeling including disruption avoidance. The first of these problems involves the narrow plasma boundary layer and its complex interactions with the plasma core and the surrounding material wall. The second requires development of a computationally tractable, but comprehensive model that describes all equilibrium and dynamic processes at a sufficient level of detail to provide useful prediction of the temporal evolution of fusion plasma experiments. The initial driver for the whole device model (WDM) will be prediction and avoidance of discharge-terminating disruptions, especially at high performance, which are a critical impediment to successful operation of machines like ITER. If disruptions prove unable to be avoided, their associated dynamics and effects will be addressed in the next phase of the FSP.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

GDB: A global 3D two-fluid model of plasma turbulence and transport in the tokamak edge

Here, the global drift-ballooning (GDB) code is developed to study tokamak edge low frequency turbulence and transport, and their relationship to global profile evolution. The code employs a 3D electromagnetic fluid model that does not discriminate between equilibrium and perturbative contributions, capturing arbitrary amplitude fluctuations. Primitive plasma variables, including the flow profiles, are evolved self-consistently in both closed-flux surfaces and the scrape-off-layer (SOL). A suite of numerical techniques described here handle the linear and non-linear components of the model efficiently so as to support realistic discharge parameters (such as realistic deuterium mass ratio √m i /m e ≈ 60) and yield good scaling on high performance computing (HPC) systems. GDB resolves turbulence slower than the ion gyrofrequency in simulations that capture the millisecond-scale evolution of global plasma profiles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Walking Method for Non-Decomposition Intersection and Union of Arbitrary Polygons and Polyhedrons

We present a method for computing the intersection and union of non- convex polyhedrons without decomposition in O(n log n) time, where n is the total number of faces of both polyhedrons. We include an accompanying Python package which addresses many of the practical issues associated with implementation and serves as a proof of concept. The key to the method is that by considering the edges of the original ob- jects and the intersections between faces as walking routes, we can e ciently nd the boundary of the intersection of arbitrary objects using directional walks, thus handling the concave case in a natural manner. The method also easily extends to plane slicing and non-convex polyhedron unions, and both the polyhedron and its constituent faces may be non-convex.

97 MATHEMATICS AND COMPUTING↗

Sensitivity Analysis of Genome-Scale Metabolic Flux Prediction

TRIMER, Transcription Regulation Integrated with MEtabolic Regulation, is a genome-scale modeling pipeline targeting at metabolic engineering applications. Using TRIMER, regulated metabolic reactions can be effectively predicted by integrative modeling of metabolic reactions with a Transcription Factor (TF)-gene regulatory network (TRN), which is modeled via a Bayesian network (BN). In this paper, we focus on sensitivity analysis of metabolic flux prediction for uncertainty quantification of BN structures for TRN modeling in TRIMER. We propose a computational strategy to construct the uncertainty class of TRN models based on the inferred regulatory order uncertainty given transcriptomic expression data. With that, we analyze the prediction sensitivity of the TRIMER pipeline for the metabolite yields of interest. The obtained sensitivity analyses can guide Optimal Experimental Design (OED) to help acquire new data that can enhance TRN modeling and achieve specific metabolic engineering objectives, including metabolite yield alterations. Here we have performed small- and large-scale simulated experiments, demonstrating the effectiveness of our developed sensitivity analysis strategy for BN structure learning to quantify the edge importance in terms of metabolic flux prediction uncertainty reduction and its potential to effectively guide OED.

59 BASIC BIOLOGICAL SCIENCES↗

Comprehensive Phase Diagrams of MoS 2 Edge Sites Using Dispersion-Corrected DFT Free Energy Calculations

A comprehensive set of surface phase diagrams addressing the catalytically relevant edges of the (100) surface of MoS 2 catalysts is developed using dispersion-corrected density functional theory and ab initio thermodynamic modeling. The results of the temperature-dependent, free energy-based thermodynamic model are presented over the full range of catalytically relevant temperatures and pressures, in addition to S- and H-coverages ranging from 0 to 100%. The results of this work allow for a full thermodynamic analysis to be performed at the conditions relevant to any promising reaction involving MoS 2 , ranging from hydrodesulfurization to dehydrogenation to electrocatalysis. Several methodological recommendations are discussed and implemented with the goal of improving the accuracy of the surface phase diagrams at minimal computational expense. A library of the most stable S- and H-adsorption modes is also developed so that linear scaling relationships can be used to correlate thermodynamic stability with kinetic activity. Applying the results to C–H bond activation of methane with a S 2 oxidant, here we predict S-coverages near 100% on the Mo- and S-edges to be thermodynamically favored and S monomers on edge sites with high S-coverages to be kinetically favorable. For H-abstraction on surface S atoms, the Mo-edge is also predicted to be more active than the S-edge.

36 MATERIALS SCIENCE↗

Validation of transport models using additive flux minimization technique

A new additive flux minimization technique is proposed for carrying out the verification and validation (V and V) of anomalous transport models. In this approach, the plasma profiles are computed in time dependent predictive simulations in which an additional effective diffusivity is varied. The goal is to obtain an optimal match between the computed and experimental profile. This new technique has several advantages over traditional V and V methods for transport models in tokamaks and takes advantage of uncertainty quantification methods developed by the applied math community. As a demonstration of its efficiency, the technique is applied to the hypothesis that the paleoclassical density transport dominates in the plasma edge region in DIII-D tokamak discharges. A simplified version of the paleoclassical model that utilizes the Spitzer resistivity for the parallel neoclassical resistivity and neglects the trapped particle effects is tested in this paper. It is shown that a contribution to density transport, in addition to the paleoclassical density transport, is needed in order to describe the experimental profiles. It is found that more additional diffusivity is needed at the top of the H-mode pedestal, and almost no additional diffusivity is needed at the pedestal bottom. The implementation of this V and V technique uses the FACETS::Core transport solver and the DAKOTA toolkit for design optimization and uncertainty quantification. The FACETS::Core solver is used for advancing the plasma density profiles. The DAKOTA toolkit is used for the optimization of plasma profiles and the computation of the additional diffusivity that is required for the predicted density profile to match the experimental profile.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Uncovering the Atomistic Mechanism for Calcite Step Growth

Determining a complete atomic-level picture of how minerals grow from aqueous solution remains a challenge as macroscopic rates can be a convolution of many reactions. For the case of calcite (CaCO 3 ) in water, computer simulations have been used in this paper to map the complex thermodynamic landscape leading to growth of the two distinct steps, acute and obtuse, on the basal surface. The carbonate ion is found to preferentially adsorb at the upper edge of acute steps while Ca 2+ only adsorbs after CO 3 2- . In contrast to the conventional picture, ion pairs prefer to bind at the upper edge of the step with only one ion, at most, coordinated to the step and lower terrace. Finally, migration of the first carbonate ion to a growth site is found to be rate-limiting for kink nucleation, with this process having a lower activation energy on the obtuse step.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Realization of fermionic Laughlin state on a quantum processor

Strongly correlated topological phases of matter are central to modern condensed matter physics and quantum information technology but often challenging to probe and control in material systems. The experimental difficulty of accessing these phases has motivated the use of engineered quantum platforms for simulation and manipulation of exotic topological states. Among these, the Laughlin state stands as a cornerstone for topological matter, embodying fractionalization, anyonic excitations, and incompressibility. Although its bosonic analogs have been realized on programmable quantum simulators, a genuine fermionic Laughlin state has yet to be demonstrated on a quantum processor. Here, we realize the ν = 1/3 fermionic Laughlin state on IonQ’s trapped-ion quantum computer using an efficient and scalable Hamiltonian variational ansatz with 369 two-qubit gates on a 16-qubit circuit. Employing symmetry-verification error mitigation, we extract key observables that characterize the Laughlin state, including correlation hole, bulk-edge correspondence, and topological entanglement entropy, with strong agreement to exact diagonalization benchmarks. This work demonstrates an end-to-end workflow to simulate material-intrinsic topological orders and provides a starting point to explore its dynamics and excitations on digital quantum processors.

Shen, Lingnan [Univ. of Washington, Seattle, WA (U↗

Drift-kinetic effects of tungsten on plasma response to RMP in ITER

Here, effects of high- Z ( Z is the particle charge number) tungsten impurity ions on the plasma response to the resonant magnetic perturbation (RMP) field are numerically investigated for the ITER 15 MA baseline scenario, where the tungsten contribution to the plasma response is computed with a drift-kinetic model while the bulk thermal particle contributions follow the fluid approximation. The study yields three highlights: (i) the drift-kinetic contribution of the tungsten impurity exerts minor influence on the plasma response compared to that computed by the pure fluid model without tungsten; (ii) a new figure of merit, based on the resonant spectrum perturbation at the plasma boundary surface, results in different optimal coil phasing compared to that previously obtained by maximizing the edge-peeling plasma response; (iii) the optimal $n = 3$ RMP (for edge localized mode (ELM) control, $n$ is the toroidal mode number) is found to induce a large tungsten particle influx near the plasma edge associated with the neoclassical toroidal viscosity. The study thus provides useful data on the compatibility of the full tungsten wall with RMP ELM control in ITER.

ITER↗

Community detection robustness of graph neural networks

Graph neural networks (GNNs) are increasingly widely used for community detection in attributed networks. They combine structural topology with node attributes through message passing and pooling. However, their robustness or lack thereof with respect to different perturbations and targeted attacks in conjunction with community detection tasks is not well understood. To shed light on latent mechanisms behind GNN sensitivity on community detection tasks, we conduct a systematic computational evaluation of six widely adopted GNN architectures graph convolutional network, graph attention network, graph sample and aggregate (GraphSAGE), differentiable pooling (DiffPool), minimum cut pooling (MinCUT), and deep modularity networks (DMoN). The analysis covers three perturbation categories: node attribute manipulations, edge topology distortions, and adversarial attacks. We use element-centric similarity as the evaluation metric on synthetic benchmarks and real-world citation networks. Our findings indicate that supervised GNNs tend to achieve higher baseline accuracy, while unsupervised methods, particularly DMoN, maintain stronger resilience under targeted and adversarial perturbations. Furthermore, robustness appears to be strongly influenced by community strength, with well-defined communities reducing performance loss. Across all models, node attribute perturbations associated with targeted edge deletions and shifts in attribute distributions tend to cause the largest degradation in community recovery. These findings highlight important trade-offs between accuracy and robustness in GNN-based community detection and offer insights into selecting architectures resilient to noise and adversarial attacks.

Goel, Jaidev [Virginia Polytechnic Inst. and State↗

Geometric remapping of particle distributions in the Discrete Element Model for Sea Ice (DEMSI v0.0)

Abstract. A new sea ice dynamical core, the Discrete Element Model for Sea Ice (DEMSI), is under development for use in coupled Earth system models. DEMSI is based on the discrete element method, which models collections of ice floes as interacting Lagrangian particles. In basin-scale sea ice simulations the Lagrangian motion results in significant convergence and ridging, which requires periodic remapping of sea ice variables from a deformed particle configuration back to an undeformed initial distribution. At the resolution required for Earth system models we cannot resolve individual sea ice floes, so we adopt the sub-grid-scale thickness distribution used in continuum sea ice models. This choice leads to a series of hierarchical tracers depending on ice fractional area or concentration that must be remapped consistently. The circular discrete elements employed in DEMSI help improve the computational efficiency at the cost of increased complexity in the effective element area definitions for sea ice cover that are required for the accurate enforcement of conservation. An additional challenge is the accurate remapping of element values along the ice edge, the location of which varies due to the Lagrangian motion of the particles. In this paper we describe a particle-to-particle remapping approach based on well-established geometric remapping ideas that enforces conservation, bounds preservation, and compatibility between associated tracer quantities, while also robustly managing remapping at the ice edge. One element of the remapping algorithm is a novel optimization-based flux correction that enforces concentration bounds in the case of nonuniform motion. We demonstrate the accuracy and utility of the algorithm in a series of numerical test cases.

58 GEOSCIENCES↗

Unsupervised, supervised and reinforced learning via spiking computation

The present invention relates to unsupervised, supervised and reinforced learning via spiking computation. The neural network comprises a plurality of neural modules. Each neural module comprises multiple digital neurons such that each neuron in a neural module has a corresponding neuron in another neural module. An interconnection network comprising a plurality of edges interconnects the plurality of neural modules. Each edge interconnects a first neural module to a second neural module, and each edge comprises a weighted synaptic connection between every neuron in the first neural module and a corresponding neuron in the second neural module.

Modha, Dharmendra S.↗

TH-A-19A-07: The Effect of Particle Tracking Step Size Limit On Monte Carlo- Computed LET Spectrum of Therapeutic Proton Beams

Purpose: To investigate the effect of charged particle tracking step size limit in the determination of the LET spectrum of therapeutic proton beams using Monte Carlo simulations. Methods: The LET spectra at different depths in a water phantom from a 79.7 MeV spot-scanning proton beam were calculated using Geant4. Five different tracking step limits 0.5 mm, 0.1 mm, 0.05 mm, 0.01 mm and 1 μm were adopted. The field size was set to 10×10 cm{sup 2} on the isocenter plane. A 40×40×6 cm{sup 3} water phantom was modelled as the irradiation target. The voxel size was set to 1×1×0.5 mm{sup 3} to obtain high resolution results. The LET spectra were scored ranging from 0.01 keV/μm to 10{sup 4}keV/μm in the logarithm scale. In addition, the proton energy spectra at different depths were also scored. Results: The LET spectra calculated using different step size limits were compared at four depths along the Bragg curve. At any depths, the spread of the LET spectra increases with the decrease of step size limit. In the dose buildup region (z = 1.9 cm) and in the region proximal to the Bragg peak (z = 3.95 cm), the frequency mean LET does not vary with decreasing step size limit. At Bragg peak (z = 4.75 cm) and in the distal edge (z = 4.85 cm), frequency mean LET decreases with decreasing step size limit. The energy spectrum at any specified depths does not vary with the step size limit. Conclusion: The calculated LET has a spectral distribution rather than a single value at any depths along the Bragg curve and the spread of the computed spectrum depends on the tracking step limit. Incorporating the LET spectrum distribution into the robust IMPT optimization plan may provide more accurate biological dose distribution than using the dose- or fluence-averaged LET. NIH Program Project Grant P01CA021239.

07 ISOTOPE AND RADIATION SOURCES↗

One-loop integrals from volumes of orthoschemes

Recently in arXiv:2012.05599 Rudenko presented a formula for the volume of hyperbolic orthoschemes in terms of alternating polylogarithms. We use this result to provide an explicit analytic result for the one-loop scalar n -gon Feynman integral in n dimensions, for even n , with massless or massive internal and external edges. Furthermore, we evaluate the general six-dimensional hexagon integral in terms of classical polylogarithms.

97 MATHEMATICS AND COMPUTING↗

Comparing Exciton-Polariton Couplings in Two-Dimensional MoS2 Cavities

Exciton-polaritons (EPs) are an emerging approach to achieve strong light-matter coupling and robust quantum phenomena, with application to areas such as photonic neuromorphic computing for instance reservoir computing. 2D transition metal dichalcogenides (TMDs) are promising candidates to host EPs due to their potential for strong coupling as evidenced by large Rabi splitting energies, which in the case of few-layer MoS2 has been demonstrated to reach 293 meV when coupled to the C exciton, placing it in the ultrastrong coupling regime, at room temperature. Here we examine how the Rabi splitting of CVD-grown monolayer MoS2 in a cavity can be optimized by tuning two variables: cavity geometry (thickness of silver and dielectric spacers) and the targeted exciton for coupling (A at about 1.9 eV, B at about 2.06 eV, or C at about 2.9 eV). With the cavity geometry, there is a tradeoff between optical field confinement and transmission. With the targeted exciton, there may be a tradeoff between Rabi splitting and lifetime. Transfer matrix simulations are used to inform how thick the cavity layers need to be, and at what angle measurements should be performed, to achieve Rabi splitting at a certain exciton energy. Experimentally, the Rabi splitting is measured by placing the cavity at a specified angle and measuring the optical reflectance and transmittance. By fitting the data, we find Rabi splittings of 124 meV, 194 meV, and 288 meV for the A, B, and C excitons, respectively, which places them in the strong, and on the edge of the ultrastrong, coupling regime.

exciton-polaritons↗

SPH with dynamical smoothing length adjustment based on the local flow kinematics

Due to the Lagrangian nature of Smoothed Particle Hydrodynamics (SPH), the adaptive resolution remains a challenging task. In this work, we first analyse the influence of the simulation parameters and the smoothing length on solution accuracy, in particular in high strain regions. Based on this analysis we develop a novel approach to dynamically adjust the kernel range for each SPH particle separately, accounting for the local flow kinematics. We use the Okubo–Weiss parameter that distinguishes the strain and vorticity dominated regions in the flow domain. The proposed development is relatively simple and implies only a moderate computational overhead. We validate the modified SPH algorithm for a selection of two-dimensional test cases: the Taylor–Green flow, the vortex spin-down, the lid-driven cavity and the dam-break flow against a sharp-edged obstacle. The simulation results show good agreement with the reference data and improvement of the long-term accuracy for unsteady flows. For the lid-driven cavity case, the proposed dynamical adjustment remedies the problem of tensile instability (particle clustering).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Radiocesium interaction with clay minerals: Theory and simulation advances Post–Fukushima

Insights at the microscopic level of the process of radiocesium adsorption and interaction with clay mineral particles have improved substantially over the past several years, triggered by pressing social issues such as management of huge amounts of waste soil accumulated after the Fukushima Dai-ichi nuclear power plant accident. In particular, computer-based molecular modeling supported by advanced hardware and algorithms has proven to be a powerful approach. Its application can now generally encompass the full complexity of clay particle adsorption sites from basal surfaces to interlayers with inserted water molecules, to edges including fresh and weathered frayed ones. On the other hand, its methodological schemes are now varied from traditional force-field molecular dynamics on large-scale realizations composed of many thousands of atoms including water molecules to first-principles methods on smaller models in rather exacting fashion. In this article, we overview new understanding enabled by simulations across methodological variations, focusing on recent insights that connect with experimental observations, namely: 1) the energy scale for cesium adsorption on the basal surface, 2) progress in understanding the structure of clay edges, which is difficult to probe experimentally, 3) cesium adsorption properties at hydrated interlayer sites, 4) the importance of the size relationship between the ionic radius of cesium and the interlayer distance at frayed edge sites, 5) the migration of cesium into deep interlayer sites, and 6) the effects of nuclear decay of radiocesium. Key experimental observations that motivate these simulation advances are also summarized. Furthermore, some directions toward future solutions of waste soil management are discussed based on the obtained microscopic insights.

54 ENVIRONMENTAL SCIENCES↗