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DOE OSTI2020

Fate of Internal Waves on a Shallow Shelf

Internal waves strongly influence the physical and chemical environment of coastal ecosystems worldwide. We report novel observations from a distributed temperature sensing (DTS) system that tracked the transformation of internal waves from the shelf break to the surf zone over a narrow shelf slope region in the South China Sea. The spatially continuous view of temperature fields provides a perspective of physical processes commonly available only in laboratory settings or numerical models, including internal wave reflection off a natural slope, shoreward transport of dense fluid within trapped cores, and observations of internal rundown (near-bed, offshore-directed jets of water preceding a breaking internal wave). Analysis shows that the fate of internal waves on this shelf—whether transmitted into shallow waters or reflected back offshore—is mediated by local water column density structure and background currents set by the previous shoaling internal waves, highlighting the importance of wave-wave interactions in nearshore internal wave dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Wave and Particle Analysis of Z-Mode and O-Mode Emission in the Jovian Inner Magnetosphere

We report some of the most intense Z-mode and O-mode observations obtained by the Juno spacecraft while in orbit about Jupiter in a low to mid-latitude region near the inner edge of the Io torus. We have been able to estimate the density of the plasma in this region based on the lower frequency cutoff of the observed Z-mode emission. The results are compatible with the electron density measurements of the Jovian Auroral Distributions Experiment (JADE), on board the Juno spacecraft, if we account for unmeasured cold plasma. Direction-finding measurements indicate that the Z- and O-mode emission have distinct source regions. We have also used the measured phase space density of the JADE and the Jupiter energetic particle detector instruments to calculate estimated local growth rates of the observed O-mode and Z-mode emission assuming a loss cone instability and quasilinear analysis. The results suggest the emissions were observed near, but not within, a source region, and the free energy source is consistent with a loss cone. We have thus carried out the quasilinear wave analysis of the assumed remote Z- and O-mode wave growths. It is shown that the remotely generated waves, propagated through an inhomogeneous medium to the satellite location, may account for the observed wave characteristics. The importance of Z-mode in accelerating electrons in the inner Jovian magnetosphere makes these new wave mode confirmations at Jupiter of particular interest.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Multichannel Analysis of Surface Waves Accelerated (MASWAccelerated): Software for efficient surface wave inversion using MPI and GPUs

Multichannel Analysis of Surface Waves (MASW) is a technique frequently used in geotechnical engineering and engineering geophysics to infer 1D layered models of seismic shear wave velocities in the top tens to hundreds of meters of the subsurface. We aim to accelerate MASW calculations by capitalizing on modern computer hardware available in the workstations of most engineers: multiple cores and graphics processing units (GPUs). We propose new parallel and GPU accelerated algorithms for computing 1D MASW inversion, and provide software implementations in C using Message Passing Interface (MPI) and CUDA. These algorithms take advantage of sparsity that arises in the problem, and the work balance between processes considers typical data trends. We compare our methods to an existing open source Matlab MASW tool. Our serial C implementation achieves a 2x speedup over the Matlab software, and we continue to see improvements by parallelizing the problem with MPI. Here we see nearly perfect strong and weak scaling for uniform data, and improve strong scaling for realistic data by repartitioning the problem to process mapping. By utilizing GPUs available on most modern workstations, we observe an additional 1.3x speedup over the serial C implementation on the first use of the method. We typically repeatedly evaluate theoretical dispersion curves as part of an optimization procedure, and on the GPU the kernel can be cached for faster reuse on later runs. We observe a 3.2x speedup on the cached GPU runs compared to the serial C runs. This work is the first open-source parallel or GPU-accelerated software tool for MASW imaging, and should enable geotechnical engineers to fully utilize all computer hardware at their disposal.

58 GEOSCIENCES↗

DOE OSTI2024

code for "Improving the QBO forcing by resolved waves with vertical grid refinement in E3SMv2"

This is all code that used in the journal article "Improving the QBO forcing by resolved waves with vertical grid refinement in E3SMv2", including: Running and post processing E3SM: Run E3SM: run_E3SM.2023.scidac.MMF.amip.py Regrid: regrid.E3SM.py post processing, diagnostics, archive: run_post.2023.scidac.MMF.py TEM calculation, including filter TEM, E3SM: calculate.TEM.v2.py calculate.TEM.monthly_mean.v1.py TEM, ERA5: ERA5_calculate_TEM_90.py merge TEM data: merge_TEM_E3SM_ERA5.py TEM, filter, E3SM: filter_TEM_E3SM.py TEM, filter, ERA5: filter_TEM_ERA5.py WK wave analysis code from (https://github.com/brianpm/wavenumber_frequency): wavenumber_frequency_functions.py calculate the wave spectra so easy to plot: wk_calculation.py Make figures some functions for plot: plot.py code for drawing paper plots: figures_for_paper.ipynb

Hannah, WalterM↗

DOE OSTI2022

TRUST Contact Thermal Conductance (TRUST-CTC) Report: FY2022

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainties in Simulations and Tests (TRUST) work package is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Staff development will include cross-discipline training to provide engineers with experience in both numerical simulations and experimental methods. This work will use and provide feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development: engineering common model framework (ECMF), engineering quantification of margins and uncertainties (EQMU), test information management system (TIMS), and [WAVES] Analysis for Verified Engineering Simulation (WAVES).

42 ENGINEERING↗

DOE OSTI2023

TRUST Contact Thermal Conductance (TRUST-CTC) Report: FY23

42 ENGINEERING↗

DOE OSTI2023

Amplitude analysis of the ${D}_s^{+}$ → π - π + π + decay

A Dalitz plot analysis of the ${D}_s^{+}$ → π - π + π + decay is presented. The analysis is based on proton-proton collision data recorded by the LHCb experiment at a centre of-mass energy of 8 TeV and corresponding to an integrated luminosity of 1.5 fb -1 . The resonant structure of the decay is obtained using a quasi-model-independent partial-wave analysis, in which the π + π - S-wave amplitude is parameterised as a generic complex function determined by a fit to the data. The S-wave component is found to be dominant, followed by the contribution from spin-2 resonances and a small contribution from spin-1 resonances. The latter includes the first observation of the ${D}_s^{+}$ → ω(782)π + channel in the ${D}_s^{+}$ → π - π + π + decay. The resonant structures of the ${D}_s^{+}$ → π - π + π + and ${D}^{+}$ → π - π + π + decays are compared, providing information about the mechanisms for the hadron formation in these decays.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Use of Convolutional Neural Network Image Classification and High-Speed Ion Probe Data Toward Real-Time Detonation Characterization in a Water-Cooled Rotating Detonation Engine

As rotating detonation engines (RDEs) progress in maturity, the importance of monitoring advancements toward development of active control becomes more critical. Experimental RDE data processing at time scales which satisfy real-time diagnostics will likely require the use of machine learning. This study aims to develop and deploy a novel real-time monitoring technique capable of determining detonation wave number, direction, frequency, and individual wave speeds throughout experimental RDE operational windows. To do so, the diagnostic integrates image classification by a convolutional neural network (CNN) and ionization current signal analysis. Wave mode identification through single-image CNN classification bypasses the need to evaluate sequential images and offers instantaneous identification of the wave mode present in the RDE annulus. Here, real-time processing speeds are achieved due to low data volumes required by the methodology, namely one short-exposure image and a short window of sensor data to generate each diagnostic output. The diagnostic acquires live data using a modified experimental setup alongside Pylon and PyDAQmx libraries within a python data acquisition environment. Lab-deployed diagnostic results are presented across varying wave modes, operating conditions, and data quality, currently executed at 3–4 Hz with a variety of iteration speed optimization options to be considered as future work. These speeds exceed that of conventional techniques and offer a proven structure for real-time RDE monitoring. The demonstrated ability to analyze detonation wave presence and behavior during RDE operation will certainly play a vital role in the development of RDE active control, necessary for RDE technology maturation toward industrial integration.

42 ENGINEERING↗

DOE OSTI2022

Monitoring Fracture Saturation With Internal Seismic Sources and Twin Neural Networks

Seismic coda-wave analysis is a well-developed method for detecting subtle physical changes in complex media by measuring arrival times in the late-arriving energy from multiply scattered or reflected waves. However, a challenge arises when multiply scattered waves are not sufficiently separated in time from the direct arrivals to provide a clear coda wave train. Additional complications for monitoring changes in fracture systems arise when the signals originate from unsynchronized internal sources, such as natural or induced seismicity, from acoustic emission, or from transportable intra-fracture sources (chattering dust), that generate uncontrolled signals that vary in arrival time, amplitude and frequency content. Here, we use a twin neural network (TNN also known as a Siamese neural network) for dimensionality reduction to analyze signals from chattering dust to classify the fluid saturation state of a synthetic fracture system. The TNN with shared weights generates a low-dimensional representation of the data input by minimizing contrastive loss, serving as the input to a multiclass classifier that accurately classifies whether multiple fractures in a fracture system are fully saturated or partially saturated, or whether a change in saturation has occurred in different fractures in the system. Furthermore, these results show that information buried in unresolved codas from uncontrolled sources can be extracted using machine learning to monitor the evolution of fracture systems caused by physical and chemical processes even when the scattered and direct wave fields overlap.

58 GEOSCIENCES↗

DOE OSTI2022

Data for Monitoring Fracture Saturation with Internal Transportable Seismic Sources and Twin Neural Networks

Seismic coda-wave analysis is a well-developed method for detecting subtle physical changes in complex media by measuring arrival times in the late-arriving energy from multiply-scattered or reflected waves. However, a challenge arises when multiply-scattered waves are not sufficiently separated in time from the direct arrivals to provide a clear coda wave train. Additional complications for monitoring changes in fracture systems arise when the signals originate from unsynchronized internal sources, such as natural induced seismicity, from acoustic emission, or from transportable intra-fracture sources (chattering dust), that generate uncontrolled signals that vary in arrival time, amplitude and frequency content. Here, we use a twin neural network (also known as a Siamese neural network) for dimensionality reduction to analyze signals from chattering dust to classify the fluid saturation state of a synthetic fracture system. The twin neural network with shared weights generates a low-dimensional representation of the data input by minimizing contrastive loss, serving as the input to a multiclass classifier that accurately classifies whether multiple fractures in a fracture system are fully saturated or partially saturated, or whether a change in saturation has occurred in different fractures in the system. These results show that information buried in unresolved codas from uncontrolled sources can be extracted using machine learning to monitor the evolution of fracture systems caused by physical and chemical processes even when the scattered and direct wave fields overlap.

58 GEOSCIENCES↗

DOE OSTI2020

Observation of the p η ' Cusp in the New Precise Beam Asymmetry Σ Data for γ p → p η

Data on the beam asymmetry Σ in the photoproduction of η mesons off protons are reported for tagged photon energies from 1130 to 1790 MeV (mass range from W = 1748 MeV to W = 2045 MeV). The data cover the full solid angle that allows for a precise moment analysis. For the first time, a strong cusp effect in a polarization observable has been observed that is an effect of a branch-point singularity at the pη' threshold [E γ = 1447 MeV (W = 1896 MeV)]. Here, the latest BnGa partial wave analysis includes the new beam asymmetry data and yields a strong indication for the N(1895)1/2 – nucleon resonance, demonstrating the importance of including all singularities for a correct determination of partial waves and resonance parameters.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Spin wave Hamiltonian and anomalous scattering in NiPS 3

Here, we report a comprehensive spin wave analysis of the semiconducting honeycomb van der Waal antiferromagnet NiPS 3 . Using single-crystal inelastic neutron scattering, we map out the full Brillouin zone and fit the observed modes to a spin wave model with rigorously defined uncertainty. We find that the third-nearest-neighbor exchange J 3 dominates the Hamiltonian, a feature which we fully account for by ab initio density functional theory calculations. We also quantify the degree to which the threefold rotation symmetry is broken and account for the Q = 0 excitations observed in other measurements, yielding a spin exchange model which is consistent across multiple experimental probes. We also identify a strongly reduced static ordered moment and reduced low-energy intensity relative to the linear spin wave calculations, signaling unexplained features in the magnetism which requires going beyond the linear spin wave approximation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

All-epitaxial long-range surface plasmon polariton structures with integrated active materials

We demonstrate all-epitaxial structures capable of supporting short- and long-range surface plasmon polariton (SRSPP and LRSPP) modes in the long-wave infrared region of the electromagnetic spectrum. The SRSPP and LRSPP modes are bound to the interfaces of a buried heavily doped (n ++ ) semiconductor layer and surrounding quantum-engineered type-II superlattice (T2SL) materials. The surrounding T2SLs are designed to allow optical transitions across the frequency dispersion of the SPP modes. We map the SPP dispersion in our structure using grating-coupled angle- and polarization-dependent reflection and photoluminescence spectroscopy. The epitaxial structures are analytically described using a simplified three-layer system (T2SL/n ++ /T2SL) and modeled using rigorous coupled wave analysis with excellent agreement to our experimental results. The presented structures offer the potential to serve as long-range interconnects or waveguides in all-epitaxial plasmonic/optoelectronic systems operating in the long-wave infrared.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Photoproduction of K 0 S Pairs at GlueX

We present an study of the ¿¿ ¿ ¿0 ¿¿0 ¿¿ channel measured by the GlueX experiment. This channel selects for resonances with ¿¿¿ = even++ quantum numbers (the ¿0, ¿2, ¿0, and ¿2 light, flavorless mesons) and potentially contains contributions from the lightest scalar glueball (¿0). Data from the 2017, 2018, and 2020 run periods are used to perform a mass independent (binned) partial-wave analysis to distinguish spin states. Due to the polarized photon beam at GlueX, we are also able to extract reflectivity amplitudes for the first time in this channel. Additionally, we perform mass-dependent partial-wave analyses using a fixed ¿-matrixparameterization to attempt a determination of the relative contribution of each res onance, and we present a guided initialization method which facilitates navigation through a parameter space with many local minima. These mass-dependent fits are a proof-of-concept in using fixed ¿-matrix models constrained by other experiments to measure photoproduc tion amplitudes for overlapping states which may only differ by isospin, a property which cannot be distinguished in this channel.

Hoffman, Nathaniel [Carnegie Mellon University]↗

DOE OSTI2021

Deep Learning Analysis of Polaritonic Wave Images

Deep learning (DL) is an emerging analysis tool across the sciences and engineering. Encouraged by the successes of DL in revealing quantitative trends in massive imaging data, we applied this approach to nanoscale deeply subdiffractional images of propagating polaritonic waves in complex materials. Utilizing the convolutional neural network (CNN), we developed a practical protocol for the rapid regression of images that quantifies the wavelength and the quality factor of polaritonic waves. Using simulated near-field images as training data, the CNN can be made to simultaneously extract polaritonic characteristics and material parameters in a time scale that is at least 3 orders of magnitude faster than common fitting/processing procedures. The CNN-based analysis was validated by examining the experimental near-field images of charge-transfer plasmon polaritons at graphene/α-RuCl3 interfaces. Our work provides a general framework for extracting quantitative information from images generated with a variety of scanning probe methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Spectroscopy of Mesons Produced by Linearly Polarized Photons

A formalism for the experimental analysis of mesons produced by a beam of linearly polarized photons is presented. This formalism introduces a more general use of the reflectivity operator. The goal is to recognize resonances in cross-sections, their associated quantum numbers, and production mechanisms by performing partial wave analysis of multiple-meson final states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Electrocatalytic Effects of Au Nanoclusters in its Electrochemiluminescence Enhanced by Coreactant Tertiary Amines

Abstract Atomically precise metal nanoclusters are increasingly exploited in electrocatalysis such as water electrolysis and CO 2 reduction. The catalytic effects are generally evaluated by conventional electrochemical methods or end‐product analysis. Herein, near infrared electrochemiluminescence (ECL) of the nanoclusters is introduced as a new signaling mechanism to complement classical voltammetric analysis for elucidating essential electrocatalytic parameters. Coreactant ECL from an aqueous soluble Au 22 nanocluster (NCs) enhanced by a common pH buffer materials 4‐(2‐hydroxyethyl)‐1‐piperazineethanesulfonic acid (HEPES) and by a piperazine drug hydroxyzine (HDZ) is studied under oxidative reduction pathways. Foot of the wave analysis on voltametric features and the kinetics profiles in potential‐step experiments are studied in different nanocluster and coreactant concentrations. Benchmark parameters such as rate constants are determined under EC (Electron‐transfer‐Chemical‐reaction) mechanism as feasibility validations. Because the luminescence properties of AuNCs are sensitive to the surface ligands or adsorbents, ECL is proposed as a new signal readout for operando studies providing insights for governing reaction mechanism and kinetics during catalytic reactions. Retrospectively, mechanistic understanding of the complex multi‐step reactions during ECL generation can provide guidance for the evaluation and optimization of ECL property for better quantitative applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

A Methodology for the Analysis of Water Oxidation Electrocatalysts in the Absence of Limiting Current that Avoids the Pitfalls of Existing Methods

Water oxidation is an important reaction studied as a way to generate electrons from water, to promote water splitting and the formation of green hydrogen. When using electrodes to drive homogeneous water oxidation catalysis, cyclic voltammograms are analyzed to provide catalytic rate constants. There are two main methods, foot-of-the-wave analysis (FOWA) and limiting current analysis. FOWA relies on approximations inherent to analyzing water oxidation catalysis, such as determining the formal potential of the catalytic intermediate, E 0 cat . Limiting current methods are the optimal way to analyze catalyst performance but rely on observable limiting current, which is virtually never seen in water oxidation. To avoid those issues, a method is proposed for analyzing nonideal cyclic voltammetry waveshapes in water oxidation: by analyzing rate data across a large range of potentials, an optimal potential, E 0 cat , can be obtained, where catalytic current, i cat , is nearly independent of scan rate and has a linear dependency on buffer concentration. Here, the method is applied to four homogeneous water oxidation catalysts with prior extensive electrochemical elucidation, all of which lack an ideal, purely kinetic waveshape in cyclic voltammetry. Application of the method avoids the biases of the other methods cited for the kinetic analyses of water oxidation catalysts.

14 SOLAR ENERGY↗