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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 217 records · Page 12

Grain boundary effects in high-temperature liquid-metal dealloying: a multi-phase field study

Abstract A multi-phase field model is employed to study the microstructural evolution of an alloy undergoing liquid dealloying, specifically considering the role of grain boundaries. A semi-implicit time-stepping algorithm using spectral methods is implemented, which enables simulating large 2D and 3D domains over long time scales while still maintaining a realistic interfacial thickness. Simulations reveal a mechanism of coupled grain–boundary migration to maintain equilibrium contact angles with the topologically complex solid–liquid interface, which locally accelerates diffusion-coupled growth of a liquid channel into the precursor. This mechanism asymmetrically disrupts the ligament connectivity of the dealloyed structure in qualitative agreement with published experimental observations. The grain boundary migration-assisted corrosion channels form even for precursors with small amounts of the dissolving alloy species, below the parting limit . The activation of this grain boundary dealloying mechanism depends strongly on grain boundary mobility.

36 MATERIALS SCIENCE↗

Spin-optomechanical cavity interfaces by deep subwavelength phonon-photon confinement

A central goal of quantum information science is transferring qubits between space, time, and modality. Spin-based systems in solids are promising quantum memories, but high-fidelity transfer of their quantum states to telecom optical fields remains challenging. Here, we introduce a phonon-mediated interface between spins in a diamond nanobeam optomechanical crystal and telecom optical fields by a simultaneous deep-subwavelength confinement of optical and acoustic fields with mode volumes $V_{\textrm{mech}}$$/Λ^3_\textrm{p} ~ 10^{-5}$ and $V_{\textrm{opt}}$$/λ^3 ~ 10^{−3}$, respectively. This confinement boosts the spin-mechanical coupling rate of Group-IV silicon vacancy (SiV − ) centers by an order of magnitude to ~ 32 MHz while retaining high acousto-optical couplings. The optical cavity couples to the spin irrespective of the emitter’s native excited states, avoiding spectral diffusion. Using Quantum Monte Carlo simulations, we estimate heralded entanglement fidelities exceeding 0.96 between two such interfaces. We anticipate broad utility beyond diamond emitter-telecom systems to most solid-state quantum memories.

Raniwala, Hamza [Massachusetts Inst. of Technology↗

Efficient sampling of free energy landscapes with functions in Sobolev spaces

Molecular simulations of biological and physical phenomena generally involve sampling complicated, rough energy landscapes characterized by multiple local minima. In this work, we introduce a new family of methods for advanced sampling that draw inspiration from functional representations used in machine learning and approximation theory. As shown here, such representations are particularly well suited for learning free energies using artificial neural networks. As a system evolves through phase space, the proposed methods gradually build a model for the free energy as a function of one or more collective variables, from both the frequency of visits to distinct states and generalized force estimates corresponding to such states. Implementation of the methods is relatively simple and, more importantly, for the representative examples considered in this work, they provide computational efficiency gains of up to several orders of magnitude over other widely used simulation techniques.

Approximation theory↗

Realizability-preserving discontinuous Galerkin method for spectral two-moment radiation transport in special relativity

Here we present a realizability-preserving numerical method for solving a spectral two-moment model to simulate the transport of massless, neutral particles interacting with a steady background material moving with relativistic velocities. The model is obtained as the special relativistic limit of a four-momentum-conservative general relativistic two-moment model. Using a maximum-entropy closure, we solve for the Eulerian-frame energy and momentum. The proposed numerical method is designed to preserve moment realizability, which corresponds to moments defined by a nonnegative phase-space density. The realizability-preserving method is achieved with the following key components: (i) a discontinuous Galerkin phase-space discretization with specially constructed numerical fluxes in the spatial and energy dimensions; (ii) a strong stability-preserving implicit-explicit time-integration method; (iii) a realizability-preserving conserved to primitive moment solver; (iv) a realizability-preserving implicit collision solver; and (v) a realizability-enforcing limiter. Component (iii) is necessitated by the closure procedure, which closes higher order moments nonlinearly in terms of primitive moments. The nonlinear conserved to primitive and the implicit collision solves are formulated as fixed-point problems, which are solved with custom iterative solvers designed to preserve the realizability of each iterate. With a series of numerical tests, we demonstrate the accuracy and robustness of this discontinuous-Galerkin-implicit-explicit method.

79 ASTRONOMY AND ASTROPHYSICS↗

Symplectic machine learning model for fast simulation of space-charge effects

Symplectic simulation of space-charge effects is crucial for the design and operation of high-intensity particle accelerators. Traditional methods for simulating these effects are often computationally expensive, resulting in significant overhead. In this work, we introduce a generative model based on a U-Net architecture within a generative adversarial network framework to efficiently simulate space-charge effects. The model is trained to predict the transverse multiparticle space-charge Hamiltonian, which can be physically computed using a gridless spectral method. The one-step symplectic transverse transfer map for the particles is then obtained by differentiating the predicted Hamiltonian. Benchmarking results demonstrate that this generative model achieves an order of magnitude higher computational efficiency compared to the spectral method, providing a highly efficient alternative for simulating space-charge effects with a large number of particles. By maintaining symplecticity, the model effectively preserves the phase-space structure and mitigates nonphysical errors in long-term simulations. This model has been integrated into jutrack, a novel autodifferentiable accelerator modeling code developed in the julia programming language.

Beam code development & simulation techniques↗

Paired Neural Network for Matching Experimental and Predicted Infrared Spectra

Here, we present a novel machine learning (ML)-based scoring technique for determining the similarity between experimental and predicted infrared (IR) spectra for identification purposes. IR spectroscopy is a powerful technique used to identify the molecular structure and composition of a sample by measuring the unique vibrational frequency pattern of the molecule’s functional groups. Molecular identifications are often made by comparing experimental and reference spectra. However, the limited number of reference spectra available in spectral libraries can confound the identification process. Alternative identification procedures rely on in silico techniques to simulate spectra for a wide range of molecules. However, scoring spectral similarity between an experimental query and computationally predicted reference remains a significant challenge. Our proposed ML-based scoring technique overcomes these barriers by accurately and efficiently determining spectral similarity.

Neural Network↗

Searching for correlations between vibrational spectral features and structural parameters of silicate glass network

Infrared (IR) and Raman spectroscopic features of silicate glasses are usually interpreted based on the analogy with those of smaller molecules, molecular clusters, or crystalline counterparts; this study tests the accuracy and validity of these widely cited peak assignment schemes by comparing vibrational spectral features with bond parameters of the glass network created by molecular dynamics (MD) simulations. A series of sodium silicate glasses with compositions of [Na 2 O] x [Al 2 O 3 ] 2 [SiO 2 ] 98- x with x = 7, 12, 17, and 22 were synthesized and analyzed with IR and Raman. A silica glass substrate and a crystalline quartz were also analyzed for comparison. Glass structures with the same compositions were generated with MD simulations using three types of potentials: fixed partial charge pairwise (Teter), partial diffuse charge potential (MGFF), and bond order-based charge transfer potential (ReaxFF). The comparison of simulated and experimental IR spectra showed that, among these three potentials tested, ReaxFF reproduces the concentration dependence of spectral features closest to the experimentally observed trend. Hence, the bond length and angle distributions as well as Si– Q n species and ring size distributions of silica and sodium silicate glasses were obtained from ReaxFF-MD simulations and further compared with the peak assignment or deconvolution schemes—which have been widely used since 1970s and 1980s—(a) correlation between the IR peak position in the Si–O stretch region (1050-1120 cm -1 ) and the Si–O–Si bond angle; (b) deconvolution of the Raman bands in the Si–O stretch region with the Q n speciation; and (c) assignment of the Raman bands in the 420-600 cm -1 region to the bending modes of (SiO) n rings with different sizes (typically, n = 3-6). The comparisons showed that none of these widely used methods is congruent with the bond parameters or structures of silicate glass networks produced via ReaxFF-MD simulations. This result invokes that the adequacy of these spectral interpretation methods must be questioned. Alternative interpretations are proposed, which are to be tested independently in future studies.

36 MATERIALS SCIENCE↗

Experimental demonstration and modeling of a robotic neutron detector with spectral and directional sensitivity for treaty verification

International safeguards and arms control agreements often require labor-intensive, intrusive onsite inspections to perform verification tasks. The ability to localize a neutron source and/or characterize a neutron field may be imperative for identifying anomalies. We are interested in the role of autonomous mobile robots, which, if designed properly, may be more effective and efficient and less intrusive than their human counterparts. Toward developing such a capability, we, for this study, have constructed the N-SpecDir Bot, comprised of three boron-coated straw detectors azimuthally-distributed within a cylinder of high-density polyethylene, which is mounted on an omni-directional robotic platform. Our N-SpecDir Bot is specifically designed to provide spectral and directional sensitivity, in addition to gross counts, by utilizing the signals from the three detectors. The detection system has been extensively characterized by MCNP modeling, which has been benchmarked to experiments conducted at the Princeton Plasma Physics Laboratory. We demonstrate the spectral and directional sensitivity experimentally and in simulation, and provide a simple yet robust method for directional measurements.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Numerical investigation of gas-filled multipass cells in the enhanced dispersion regime for clean spectral broadening and pulse compression

We show via numerical simulations that the regime of enhanced frequency chirp can be achieved in gas-filled multipass cells. Our results demonstrate that there exists a region of pulse and cell parameters for which a broad and flat spectrum with a smooth parabolic-like phase can be generated. This spectrum is compatible with clean ultrashort pulses, whose secondary structures are always below the 0.5% of its peak intensity such that the energy ratio (the energy contained within the main peak of the pulse) is above 98%. This regime makes multipass cell post-compression one of the most versatile schemes to sculpt a clean intense ultrashort optical pulse.

Segundo Staels, V. W. (ORCID:0000000200056157)↗

Observations of compact sources in galaxy clusters using MUSTANG2

Compact sources can cause scatter in the scaling relationships between the amplitude of the thermal Sunyaev–Zel’dovich Effect (tSZE) in galaxy clusters and cluster mass. Estimates of the importance of this scatter vary – largely due to limited data on sources in clusters at the frequencies at which tSZE cluster surveys operate. In this paper, we present 90 GHz compact source measurements from a sample of 30 clusters observed using the MUSTANG2 instrument on the Green Bank Telescope. We present simulations of how a source’s flux density, spectral index, and angular separation from the cluster’s centre affect the measured tSZE in clusters detected by the Atacama Cosmology Telescope (ACT). By comparing the MUSTANG2 measurements with these simulations we calibrate an empirical relationship between 1.4 GHz flux densities from radio surveys and source contamination in ACT tSZE measurements. We find 3 per cent of the ACT clusters have more than a 20 per cent decrease in Compton-y but another 3 per cent have a 10 per cent increase in the Compton-y due to the matched filters used to find clusters. As sources affect the measured tSZE signal and hence the likelihood that a cluster will be detected, testing the level of source contamination in the tSZE signal using a tSZE-selected catalogue is inherently biased. We confirm this by comparing the ACT tSZE catalogue with optically and X-ray-selected cluster catalogues. Furthermore, there is a strong case for a large, high-resolution survey of clusters to better characterize their source population.

79 ASTRONOMY AND ASTROPHYSICS↗

High Fidelity CFD Simulations Supporting the KP-FHR

Kairos Power, LLC, is developing its version of the Fluoride-cooled High-temperature Reactor, the KP-FHR. The design uses a pebble bed core with fluoride salt as a coolant. The pebbles used in the KP-FHR have a diameter of 4 cm, with a shell fuel region where TRISO particles are embedded. A Pebble bed core design is adopted by several Gen IV reactors, They boast many benefits, such as fuel integrity, highly efficient heat transfer, and passive safety. However, it is challenging to accurately predict temperature and flow inside a pebble bed. Traditional approaches use the porous media model, which regards the pebble bed as a continuous medium, but with different temperature fields representing different levels, such as the fluid temperature, pebble surface temperature, and pebble center temperature. Empirical heat transfer correlations are adopted to calculate the heat transfer coefficient between different phases. However, empirical correlations are usually validated with experimental data, which usually lacks detail inside the pebble bed. The available experimental data is also generally at a high Reynolds number, which falls outside of the conditions of KP-FHR. Explicit computational fluid dynamics (CFD) simulations of randomly packed pebble beds have only become feasible recently. This is thanks to the rapid development of computational power and scalable algorithms. In this work, we used the Spectral Element Method (SEM) CFD code NekRS to simulate the randomly packed pebble bed in a cylindrical container. NekRS, which is the GPU variant of Nek5000, but refactored to utilize the computational power of GPUs using the OCCA library to run on hybrid architecture high performance computing systems. It was initially developed with the libParamunal library, but truncated and tuned for large-scale turbulence simulation. As a result, the SEM reaches higher precision with the same degrees of freedom by using a high-order Lagrange polynomial basis distributed on Gauss-Lobatto-Legendre quadrature inside each element, compared to lower-order methods, such the Finite Volume Method and Finite Element Method. The report is divided into five parts. We start with a general discussion of the pebble bed reactor, along with a specific investigation into the KP-FHR. The second part presents the numerical methodology. In the third part, we study a modular pebble bed with 1741 pebbles in a container of 7 pebble-diameter radius. Beyond LES simulations done by NekRS, we also leveraged the thermal radiation model in OpenFOAM to study heat transfer under no-forced-flow scenarios. Then, in the fourth part we simulated a pebble bed similar to the size of the Hermes Test Reactor. The total number of pebbles is in these simulations is 34,374. The container radius is 14 pebble-diameters. Finally, the report concludes in part five, with a discussion of future work.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DUAL-PARTICLE DOSEMETER BASED ON ORGANIC SCINTILLATOR

Abstract Traditionally available handheld dosemeters are generally sensitive to only one type of radiation: neutrons or photons. Some dosemeters also rely on very specific attenuation correlations between response and dose, are not scalable in size and multiple dosemeters are required to characterise mixed-particle fields. The research presented here serves as a proof-of-concept for a method to simultaneously measure dose rates from neutrons and photons using a particle discriminating organic scintillation detector without the need for spectral deconvolution. The method was compared with traditional instruments and to simulation. Isotopic photon dose rates measured with this method were within 4% of simulated truth, whereas fission spectrum neutron dose rates were measured within 21%. Measurements of dose rates from both particles agree with simulated truth better than traditional instruments. This new method allows for measurement of dose equivalent from both neutrons and photons with a single instrument and no reliance on spectral deconvolution.

Miller, C. A.↗

Block Island Noise Modeling Data

Noise propagation near Block Island was simulated to assess environmental impacts of impact pile driving during wind turbine construction. Computational models complement field-recorded acoustic data, providing insights into sound attenuation, spectral variability, and propagation dynamics. The dataset includes: 1. Propagation Models: Simulated underwater sound fields documenting sound pressure and directional variability across frequency bands and distances. 2. Spectral Analysis (LTSA): Long-term averages and processed outputs calculating acoustic intensity over time. 3. Visualization Files: Graphs, 2D/3D simulation results, and reference calculations used in sound modeling.

17 WIND ENERGY↗

A Model of Double Coronal Hard X-Ray Sources in Solar Flares

A number of double coronal X-ray sources have been observed during solar flares by RHESSI, where the two sources reside at different sides of the inferred reconnection site. However, where and how these X-ray-emitting electrons are accelerated remains unclear. Here we present the first model of the double coronal hard X-ray (HXR) sources, where electrons are accelerated by a pair of termination shocks driven by bidirectional fast reconnection outflows. We model the acceleration and transport of electrons in the flare region by numerically solving the Parker transport equation using velocity and magnetic fields from the macroscopic magnetohydrodynamic simulation of a flux rope eruption. We show that electrons can be efficiently accelerated by the termination shocks and high-energy electrons mainly concentrate around the two shocks. The synthetic HXR emission images display two distinct sources extending to >100 keV below and above the reconnection region, with the upper source much fainter than the lower one. The HXR energy spectra of the two coronal sources show similar spectral slopes, consistent with the observations. Our simulation results suggest that the flare termination shock can be a promising particle acceleration mechanism in explaining the double-source nonthermal emissions in solar flares.

79 ASTRONOMY AND ASTROPHYSICS↗

Frequency Emitter Geolocation Using Signal Strength Fingerprinting Informed By 3D Propagation Modeling

This work focuses on the problem of RF geolocation in complex multipath environments. Using 3D electromagnetic propagation modeling to characterize environments of interest will enable more accurate RF geolocation. Specifically, a path-loss radio map can be generated in simulation for use in received signal strength indicators (RSSI) fingerprinting, or pattern matching. RSSI fingerprinting is an example of data-based method that takes site specific information into account which should allow for better performance than other model-based methods that use a generalized model of electromagnetic propagation. This modeling capability will also be used to evaluate the relative performance of RSSI fingerprinting, pathloss model based RSSI methods such as differential received signal strength circles (DRSS), RSSI joint gaussian estimation, and time-difference of arrival (TDOA). New methods using this simulation derived electromagnetic characterization could improve the efficacy of currently deployed and future RF spectral monitoring solutions. Wireless InSite developed by Remcom is used as the simulation tool of choice in this work. An indoor location is simulated with a grid of fixed receivers and a grid of transmit locations. Using the output of the Wireless InSite simulation the response from a given transmit location to a given receive location can be generated. During the first year of the project various geolocation methods evaluated on purely synthetic, but realistic, data. The second year focused on testing and validating the efficacy of simulation informed RF geolocation using two physical testbeds. This work has shown that data-based approaches are more accurate than model-based ones at the expensive of requiring measured or simulated site-specific training data.

47 OTHER INSTRUMENTATION↗

Comparison of stellar populations in simulated and real post-starburst galaxies in MaNGA

ABSTRACT Recent integral field spectroscopic (IFS) surveys have revealed radial gradients in the optical spectral indices of post-starburst (PSB) galaxies, which can be used to constrain their formation histories. We study the spectral indices of post-processed mock IFS datacubes of binary merger simulations, carefully matched to the properties of the MaNGA IFS survey, with a variety of black hole (BH) feedback models, progenitor galaxies, orbits, and mass ratios. Based on our simulation sample, we find that only major mergers on prograde–prograde or retrograde–prograde orbits in combination with a mechanical BH feedback model can form galaxies with weak enough ongoing star formation, and therefore absent H α emission, to be selected by traditional PSB selection methods. We find strong fluctuations in nebular emission line strengths, even within the PSB phase, suggesting that H α selected PSBs are only a subsample of the underlying population. The global PSB population can be more robustly identified using stellar continuum-based approaches. The difficulty in reproducing the very young PSBs in simulations potentially indicates that new sub-resolution star formation recipes are required to properly model the process of star formation quenching. In our simulations, we find that the starburst peaks at the same time at all radii, but is stronger and more prolonged in the inner regions. This results in a strong time evolution in the radial gradients of the spectral indices that can be used to estimate the age of the starburst without reliance on detailed star formation histories from spectral synthesis models.

Zheng, Yirui↗

Modeling aerosol transmission spectra from n(λ) and k(λ) infrared optical constants measurements of organic liquids and solids

The effects of light scattering and refraction play significantly different roles for aerosols than for bulk materials, making it challenging to identify aerosolized chemicals using traditional spectral methods or spectral reference libraries. Due to a potentially infinite number of particle morphologies, sizes, and compositions, constructing a database of laboratory-measured aerosol spectra is not a practical solution. Here, as an alternative approach, the measured n / k optical vectors of two example organic materials (diethyl phthalate and D-mannitol) are used in combination with particle absorption / scattering theory (Mie theory and FDTD) and the Beer-Lambert law to generate a series of synthetic infrared transmission / scattered light spectra. The synthetic spectra show significant differences versus simple slab transmission spectra, even for small changes in particle size (e.g., 5 vs. 10 µm) for both single particles and ensembles, potentially serving as useful reference data for aerosol sensing. For spherical single particles with diameters of 1 to 10 µm, FDTD simulations predict changes in the magnitudes of spectral shifts and the shapes of the peaks vs. particle size with only small deviations from Mie theory predictions, yet reliably capture the direction of the shifts. Typical spectral peak shifts in the longwave infrared correspond to Δλ ∼0.20 µm (∼34 cm -1 ) when compared to corresponding slab transmission spectra. Additionally, synthetic spectra generated from the n / k values derived using two different methods (KBr pellet transmission and single-angle reflectance) are compared using the Mie theory model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗