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At least 865 records · Page 48

Sub-problem Optimization With Regression and Neural Network Approximators

Design optimization of large systems can be attempted through a sub-problem strategy. In this strategy, the original problem is divided into a number of smaller problems that are clustered together to obtain a sequence of sub-problems. Solution to the large problem is attempted iteratively through repeated solutions to the modest sub-problems. This strategy is applicable to structures and to multidisciplinary systems. For structures, clustering the substructures generates the sequence of sub-problems. For a multidisciplinary system, individual disciplines, accounting for coupling, can be considered as sub-problems. A sub-problem, if required, can be further broken down to accommodate sub-disciplines. The sub-problem strategy is being implemented into the NASA design optimization test bed, referred to as "CometBoards." Neural network and regression approximators are employed for reanalysis and sensitivity analysis calculations at the sub-problem level. The strategy has been implemented in sequential as well as parallel computational environments. This strategy, which attempts to alleviate algorithmic and reanalysis deficiencies, has the potential to become a powerful design tool. However, several issues have to be addressed before its full potential can be harnessed. This paper illustrates the strategy and addresses some issues.

Guptill, James D.↗

Visual Computing Environment

The Visual Computing Environment (VCE) is a NASA Lewis Research Center project to develop a framework for intercomponent and multidisciplinary computational simulations. Many current engineering analysis codes simulate various aspects of aircraft engine operation. For example, existing computational fluid dynamics (CFD) codes can model the airflow through individual engine components such as the inlet, compressor, combustor, turbine, or nozzle. Currently, these codes are run in isolation, making intercomponent and complete system simulations very difficult to perform. In addition, management and utilization of these engineering codes for coupled component simulations is a complex, laborious task, requiring substantial experience and effort. To facilitate multicomponent aircraft engine analysis, the CFD Research Corporation (CFDRC) is developing the VCE system. This system, which is part of NASA's Numerical Propulsion Simulation System (NPSS) program, can couple various engineering disciplines, such as CFD, structural analysis, and thermal analysis. The objectives of VCE are to (1) develop a visual computing environment for controlling the execution of individual simulation codes that are running in parallel and are distributed on heterogeneous host machines in a networked environment, (2) develop numerical coupling algorithms for interchanging boundary conditions between codes with arbitrary grid matching and different levels of dimensionality, (3) provide a graphical interface for simulation setup and control, and (4) provide tools for online visualization and plotting. VCE was designed to provide a distributed, object-oriented environment. Mechanisms are provided for creating and manipulating objects, such as grids, boundary conditions, and solution data. This environment includes parallel virtual machine (PVM) for distributed processing. Users can interactively select and couple any set of codes that have been modified to run in a parallel distributed fashion on a cluster of heterogeneous workstations. A scripting facility allows users to dictate the sequence of events that make up the particular simulation.

Lawrence, Charles↗

Search for Spectral Irregularities due to Photon-Axionlike-Particle Oscillations with the Fermi Large Area Telescope

We report on the search for spectral irregularities induced by oscillations between photons and axion-like particles (ALPs) in the gamma-ray spectrum of NGC 1275, the central galaxy of the Perseus cluster. Using 6 years of Fermi Large Area Telescope data, we find no evidence for ALPs and exclude couplings above 5 times 10 (sup -12) per gigaelectronvolt for ALP masses less than or approximately equal to 0.5 apparent magnitude (m (sub a)) less than or approximately equal to 5 nanoelectronvolts at 95 percent confidence. The limits are competitive withthe sensitivity of planned laboratory experiments, and, together with other bounds, strongly constrain thepossibility that ALPs can reduce the gamma-ray opacity of the Universe.

Ajello, M.↗

Dynamic Shaping of Grid Response of Multi-Machine Multi-Inverter Systems Through Grid-Forming IBRs

We consider the problem of controlling the frequency response of weakly-coupled multi-machine multi-inverter low-inertia power systems via grid-forming inverter-based resources (IBRs). In contrast to existing methods, our approach relies on dividing the larger system into multiple strongly-coupled subsystems, without ignoring either the underlying network or approximating the subsystem response as an aggregate harmonic mean model. Rather, through a structured clustering and recursive dynamic shaping approach, the frequency response of the overall system to load perturbations is shaped appropriately. We demonstrate the proposed approach for a three-node triangular configuration and a small-scale radial network. Furthermore, previous synchronization analysis for heterogeneous systems requires the machines to satisfy certain proportionality property. In our approach, the effective transfer functions for each cluster can be tuned by the IBRs to satisfy such property, enabling us to apply the shaping control to systems with a wider range of heterogeneous machines.

frequency-shaping control↗

Sequential surface synthesis of dispersed sub-nanometer iridium on titanium nitride for acidic water oxidation

Maximizing iridium utilization while maintaining high oxygen evolution reaction (OER) performance remains a persistent challenge in acidic water electrolysis. Immobilizing Ir on conductive, acid-stable supports is promising, yet simultaneously achieving sub-nanometer size, high area coverage, and strong electronic coupling is difficult. Here, we report a sequential surface synthesis on titanium nitride (TiN) that yields uniformly distributed sub-nanometer Ir arrays (∼0.7 nm). Our method uses ethylenediaminetetraacetic acid (EDTA) as a temporal scaffold: it chemisorbs to TiN to install dense chelating sites, captures Ir 3+ ions, and confines Ir cluster growth. A subsequent thermal treatment at 500 °C in a reducing atmosphere removes the ligand shell, while preserving ultrasmall particle size and establishing direct Ir–TiN electronic coupling. The optimized catalyst exhibits mixed Ir 0 /Ir x+ coordination with low charge-transfer resistance (R ct = 19.2 Ω), delivering a mass activity of 342 A g Ir −1 at 1.54 V in acidic electrolyte. In situ X-ray absorption spectroscopy reveals irreversible surface oxidation as the primary stability-limiting factor. This stepwise strategy provides a general framework for supported catalysts that maximize precious metal utilization via sub-nanometer dispersion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Global Dynamical Atlas of the Milky Way Mergers: Constraints from Gaia EDR3–based Orbits of Globular Clusters, Stellar Streams, and Satellite Galaxies

The Milky Way halo was predominantly formed by the merging of numerous progenitor galaxies. However, our knowledge of this process is still incomplete, especially in regard to the total number of mergers, their global dynamical properties and their contribution to the stellar population of the Galactic halo. Here, we uncover the Milky Way mergers by detecting groupings of globular clusters, stellar streams, and satellite galaxies in action (J) space. While actions fully characterize the orbits, we additionally use the redundant information on their energy (E) to enhance the contrast between the groupings. For this endeavor, we use Gaia EDR3–based measurements of 170 globular clusters, 41 streams, and 46 satellites to derive their J and E. To detect groups, we use the ENLINK software, coupled with a statistical procedure that accounts for the observed phase-space uncertainties of these objects. We detect a total of N = 6 groups, including the previously known mergers Sagittarius, Cetus, Gaia–Sausage/Enceladus, LMS-1/Wukong, Arjuna/Sequoia/I'itoi, and one new merger that we call Pontus. All of these mergers, together, comprise 62 objects (≈25% of our sample). We discuss their members, orbital properties, and metallicity distributions. We find that the three most-metal-poor streams of our galaxy—"C-19" ([Fe/H] = –3.4 dex), "Sylgr" ([Fe/H] = –2.9 dex), and "Phoenix" ([Fe/H] = –2.7 dex)—are associated with LMS-1/Wukong, showing it to be the most-metal-poor merger. The global dynamical atlas of Milky Way mergers that we present here provides a present-day reference for galaxy formation models.

79 ASTRONOMY AND ASTROPHYSICS↗

Cluster Analysis of Spectroscopic Line Profiles and EUV Emission in RMHD Simulations and Observations of the Solar Atmosphere

Spatially-resolved observations from the IRIS, SDO/AIA, and other space mission and ground-based telescopes, coupled with realistic 3D RMHD simulations, are a powerful tool for analysis of processes in the solar atmosphere. To better understand the dynamical and thermodynamic properties in the simulation data and their connection to observations, it is essential to determine similarities in the behaviors of the synthesized and observed emission. However, the complexity of observational data and physical processes makes comparison of observations and modeling results difficult. In this work, we show the initial results of application of K-Means clustering (unsupervised machine learning) algorithm to two different problems: 1) recognition of the typical spectroscopic line profiles observed by IRIS during solar flares and their typical dynamic behavior; 2) recognition of shocks and heating events in synthetic AIA emission data obtained from StellarBox quiet-Sun simulations. The average silhouette width technique for the KMeans algorithm is utilized in different ways to obtain optimal numbers of clusters. We discuss application of the emission clustering to visualizations of the computational volume, understanding its evolutionary trends and behavior patterns, and inversion (reconstruction) of physical properties of the solar atmosphere from synthesizes emission data.

Sadykov, Viacheslav↗

Disruption of the Globular Cluster Pal 5

Orbit calculations suggest that the sparse globular cluster, Pal 5, will pass within 7 kpc of the Galactic center the next time it crosses the plane, where it might be destroyed by tidal stresses. We study this problem, treating Pal 5 as a self-consistent dynamical system orbiting through an external potential that represents the Galaxy. The first part of the problem is to find suitable analytic approximations to the Galactic potential. They must be valid in all regions the cluster is likely to explore. Observed velocity and positional data for Pal 5 are used as initial conditions to determine the orbit. Methods we used for a different problem some 12 years ago have been adapted to this problem. Three experiments have been run, with M/L= 1, 3, and 10, for the cluster model. The cluster blew up shortly after passing through the Galactic plane (about 130 Myrs after the beginning of the run) with M/L=1. At M/L = 3 and 10 the cluster survived, although it got quite a kick in the fundamental mode on passing through the plane. But the fundamental mode oscillation died out in a couple of oscillation cycles at M/L=10. Pal 5 will probably be destroyed on its next crossing of the Galactic plane if M/L=1, but it can survive (albeit with fairly heavy damage) if NI/L=3. We haven't tried to trap the mass limits more closely than that. Pal 5 comes through pretty well unscathed at M/L=10. An interesting follow-up experiment would be to back the cluster up along its orbit to look at its previous passage through the Galactic plane, to see what kind of object it might have been at earlier times.

Miller, R. H.↗

Pt Nanoparticle Disintegration at Oxide Interfaces Enhances CO Oxidation Catalysis

Understanding how supported metal nanoparticles dynamically evolve under reaction conditions is critical for controlling their catalytic function. Here, the mechanism behind the dynamic disintegration of Pt nanoparticles (NPs) supported on CeOx-TiO2 (CT) during CO oxidation is elucidated, leading to the formation of single atoms (SAs) and/or sub-nanometer clusters. Density functional theory (DFT) calculations reveal that strong Pt-CO interactions weaken Pt─Pt cohesion, while electronic coupling between Pt and Ce ions stabilizes Pt-CO* intermediates at the oxide interface. Surface oxygen vacancies kinetically trap Pt-CO*, but the vacancies are replenished under oxygen-rich conditions, enabling Pt-CO* surface diffusion and subsequent structural reorganization. In situ spectroscopic analyses confirm the oxygen-driven transformation of Pt NPs, correlating with a threefold increase in mass-specific activity at 150 °C. These findings demonstrate that interfacial oxygen dynamics and metal-support interactions can be leveraged to induce nanoparticle disintegration and optimize catalytic performance, highlighting the catalytic potential of interface-engineered Pt nanostructures.

CO oxidation↗

Electronic and Geometric effects on Photochemistry of Molecules in Well-Defined Environments

Assemblies of molecular switches at surfaces are of great interest for applications in solar energy conversion, optoelectronic and optomechanical devices. Experimental studies have demonstrated that it is possible to optically probe photoactive molecules in well-defined nanoscale environments. To understand these systems, we have developed a polarizable frozen-density embedding (FDEpol) to model the optical properties of molecules adsorbed on metal clusters. We have demonstrated that the FDEpol method can describe the ground state and linear response properties of strongly coupled systems with results that are in good agreement with exact projection based embedding method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Decentralized Failure-Tolerant Optimization of Electric Vehicle Charging

We present a decentralized failure-tolerant algorithm for optimizing electric vehicle (EV) charging, using charging stations as computing agents. The algorithm is based on the alternating direction method of multipliers (ADMM) and it has the following features: (i) It handles capacity, peak demand, and ancillary services coupling constraints. (ii) It does not require a central agent collecting information and performing coordination (e.g. an aggregator), instead all agents exchange information and computations are carried out in a fully decentralized fashion. (iii) It can withstand the failure of any number of computing agents, as long as the remaining computing agents are in a connected communications network. We construct this algorithm by reformulating the optimal EV charging problem in a decomposable form, amenable to ADMM, and then developing efficient decentralized solution methods for the subproblems dealing with coupling constraints. We conduct numerical experiments on industry-scale synthetic EV charging datasets, with up to 1,152 charging stations, using a high performance computing cluster. The experiments demonstrate that the proposed algorithm can solve the optimal EV charging problem fast enough to permit the integration of EV charging with real-time electricity markets, even in the presence of failures.

42 ENGINEERING↗

A Clustering-based biased Monte Carlo Approach to Protein Titration Curve Prediction

We develop and implement a novel approach to computing the ensemble averages in systems characterized by pair-wise interactions between the entities. Methods involving full enumeration of the configuration space result in exponential complexity. Sampling methods such as Markov Chain Monte Carlo (MCMC) algorithms have been proposed to tackle the exponential complexity of these problems. In certain scenarios where significant energetic coupling exists between the entities, the accuracy of the such algorithms can be diminished. We propose a strategy to improve the accuracy of the MCMC runs by taking advantage of the cluster structure in the interaction energy matrix. We propose two different schemes for performing the biased MCMC runs on the partitioned systems and show that they are valid MCMC schemes. We then apply these algorithms to the problem of computing the protonation fractions and hence the titration curves of titratable protein residues that constitute a given protein. We leverage both synthesized and real-world systems and show the improved performance of our biased MCMC methods when compared to the regular MCMC method.

Visweswara Sathanur, Arun↗

CONUS-wide Projected Flood Frequency and Uncertainty Estimates, Version 1.0

This dataset presents a large-ensemble of CONUS-wide projected flood frequency and uncertainty estimates across ~2.7 million NHDPlusV2 river reaches over the CONUS. The framework producing this dataset leverages a multi-model, uncertainty-aware modeling framework that allows evaluating shifts in flood frequences at the stream reach level across the CONUS. CONUS-wide ensemble streamflow projections generated from hydrologic simulations driven by downscaled and bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) outputs are used to derive these flood frequency and uncertainty estimates over the period 1980 - 2099. A spatially consistent regional L-moment algorithm is applied across clusters defined by the US Hydrologic Unit Code Subregions (HUC4s and HUC8s) and NHDPlusV2 stream orders to estimate flood frequencies. The dataset also includes at-site based flood estimates that allow for the comparison between local and regional approach-based estimates, assess projected changes, and characterize their uncertainties. For more reliable estimation of rare flood frequencies such as 500 and 1000-year return periods, super-ensemble based estimates are also included in the dataset. This dataset is derived to support the "Impact-Informed Dam Safety Risk Assessment for Securing Hydropower Assests" project for the US Department of Energy (DOE) Hydropower and Hydrokinetic Office (H2O). For further details, refer to Kao et al. (2022), Ghimire et al. (2023), Ghimire et al. (2025), and Hosking and Wallis (1997).

Ghimire, Ganesh [ORNL] (ORCID:0000000242843941)↗

Strain-Induced Spin-Nematic State and Nematic Susceptibility Arising from 2 × 2 Fe Clusters in KFe 0.8 Ag 1.2 Te 2

Spin nematics break spin-rotational symmetry while maintaining time-reversal symmetry, analogous to liquid crystal nematics that break spatial rotational symmetry while maintaining translational symmetry. Although several candidate spin nematics have been proposed, the identification and characterization of such a state remain challenging because the spin-nematic order parameter does not couple directly to experimental probes. $\mathrm{KFe_{0.8}Ag_{1.2}Te_{2} (K_{5}Fe_{4}Ag_{6}Te_{10}}$, KFAT) is a local-moment magnet consisting of well-separated 2×2 Fe clusters, and in its ground state the clusters order magnetically, breaking both spin-rotational and time-reversal symmetries. Using uniform magnetic susceptibility and neutron scattering measurements, we find a small strain induces sizable spin anisotropy in the paramagnetic state of KFAT, manifestly breaking spin-rotational symmetry while retaining time-reversal symmetry, resulting in a strain-induced spin-nematic state in which the 2×2 clusters act as the spin analog of molecules in a liquid crystal nematic. Finally, the strain-induced spin anisotropy in KFAT allows us to probe its nematic susceptibility, revealing a divergentlike increase upon cooling, indicating the ordered ground state is driven by a spin-orbital entangled nematic order parameter.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Rayleigh Scattering Density Measurements, Cluster Theory, and Nucleation Calculations at Mach 10

In an exploratory investigation, quantitative unclustered laser Rayleigh scattering measurements of density were performed in the air in the NASA Langley Research Center's 31 in. Mach 10 wind tunnel. A review of 20 previous years of data in supersonic and Mach 6 hypersonic flows is presented where clustered signals typically overwhelmed molecular signals. A review of nucleation theory and accompanying nucleation calculations are also provided to interpret the current observed lack of clustering. Data were acquired at a fixed stagnation temperature near 990Kat five stagnation pressures spanning 2.41 to 10.0 MPa (350 to 1454 psi) using a pulsed argon fluoride excimer laser and double-intensified charge-coupled device camera. Data averaged over 371 images and 210 pixels along a 36.7mmline measured freestream densities that agree with computed isentropic-expansion densities to less than 2% and less than 6% at the highest and lowest densities, respectively. Cluster-free Mach 10 results are compared with previous clustered Mach 6 and condensation-free Mach 14 results. Evidence is presented indicating vibrationally excited oxygen and nitrogen molecules are absorbed as the clusters form, release their excess energy, and inhibit or possibly reverse the clustering process. Implications for delaying clustering and condensation onset in hypersonic and hypervelocity facilities are discussed.

Balla, R. Jeffrey↗

Ab initio calculations of anharmonic vibrational spectroscopy for hydrogen fluoride (HF)n (n = 3, 4) and mixed hydrogen fluoride/water (HF)n(H2O)n (n = 1, 2, 4) clusters

Anharmonic vibrational frequencies and intensities are computed for hydrogen fluoride clusters (HF)n, with n = 3, 4 and mixed clusters of hydrogen fluoride with water (HF)n(H2O)n where n = 1, 2. For the (HF)4(H2O)4 complex, the vibrational spectra are calculated at the harmonic level, and anharmonic effects are estimated. Potential energy surfaces for these systems are obtained at the MP2/TZP level of electronic structure theory. Vibrational states are calculated from the potential surface points using the correlation-corrected vibrational self-consistent field method. The method accounts for the anharmonicities and couplings between all vibrational modes and provides fairly accurate anharmonic vibrational spectra that can be directly compared with experimental results without a need for empirical scaling. For (HF)n, good agreement is found with experimental data. This agreement shows that the Moller-Plesset (MP2) potential surfaces for these systems are reasonably reliable. The accuracy is best for the stiff intramolecular modes, which indicates the validity of MP2 in describing coupling between intramolecular and intermolecular degrees of freedom. For (HF)n(H2O)n experimental results are unavailable. The computed intramolecular frequencies show a strong dependence on cluster size. Intensity features are predicted for future experiments.

Water/chemistry↗

Ab Initio Calculations of Anharmonic Vibrational Spectroscopy for Hydrogen Fluoride (HF)n (n=3,4) and Mixed Hydrogen Fluoride/Water (HF)n(H20)n (n=1,2,4) Clusters

Anharmonic vibrational frequencies and intensities are computed for hydrogen fluoride clusters (HF)n with n=3,4 and mixed clusters of hydrogen fluoride with water (HF)n(H2O)n where n=1,2. For the (HF)4(H2O)4 complex, the vibrational spectra are calculated at the harmonic level, and anharmonic effects are estimated. Potential energy surfaces for these systems are obtained at the MP2/TZP level of electronic structure theory. Vibrational states are calculated from the potential surface points using the correlation-corrected vibrational self-consistent field (CC-VSCF) method. The method accounts for the anharmonicities and couplings between all vibrational modes and provides fairly accurate anharmonic vibrational spectra that can be directly compared with experimental results without a need for empirical scaling. For (HF)n, good agreement is found with experimental data. This agreement shows that the MP2 potential surfaces for these systems are reasonably reliable. The accuracy is best for the stiff intramolecular modes, which indicates the validity of MP2 in describing coupling between intramolecular and intermolecular degrees of freedom. For (HF)n(H2O)n experimental results are unavailable. The computed intramolecular frequencies show a strong dependence on cluster size. Intensity features are predicted for future experiments.

Chaban, Galina M.↗

Evidence for Low-Valent Electronic Configurations in Iron–Sulfur Clusters

Although biological iron-sulfur (Fe–S) clusters perform some of the most difficult redox reactions in Nature, they are thought to be composed exclusively of Fe 2+ and Fe 3+ ions, as well as mixed-valent pairs with average oxidation states of Fe 2.5+ . We herein show that Fe–S clusters formally composed of these valences can access a wider range of electronic configurations—in particular, those featuring low-valent Fe 1+ centers. We demonstrate that CO binding to a synthetic [Fe 4 S 4 ] o cluster supported by N-heterocyclic carbene ligands induces generation of Fe 1+ centers via intracluster electron transfer, wherein a neighboring pair of Fe 2+ sites reduces the CO-bound site to a low-valent Fe 1+ state. Similarly, CO binding to an [Fe 4 S 4 ] + cluster induces electron delocalization with a neighboring Fe site to form a mixed-valent Fe 1.5+ Fe 2.5+ pair in which the CO-bound site adopts partial low-valent character. Furthermore, these low-valent configurations engender remarkable C–O bond activation without having to traverse highly negative and physiologically inaccessible [Fe 4 S 4 ] o /[Fe 4 S 4 ] – redox couples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗