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At least 469 records · Page 26

An electrochemical mesoscale tool for modeling the corrosion of structural alloys by molten salt

Understanding the impact of microstructure on corrosion rates can aid the development of corrosion-resistant alloys for molten salt reactors. Here in this work, we develop an electrochemical phase-field model for capturing the microstructure-dependent corrosion of structural alloys by molten salts. As a demonstration problem, we apply this model to capture the selective depletion of Cr from Ni-Cr grain boundaries during corrosion in molten FLiBe salt. We perform sensitivity analysis and model verification on 1D simulations to confirm that the model predicts diffusion-limited kinetics. The model is validated using 1D, 2D, and 3D simulations against experimental data for Ni-5Cr and Ni-20Cr corrosion in molten FLiBe. The 1D simulations predict the corrosion behavior with reasonable accuracy when using an effective diffusion coefficient that accurately represents the grain boundary diffusion. 2D simulations that represent the grain structure underpredict the corrosion. 3D simulations that represent the grain structure predict the corrosion with reasonable accuracy. The corrosion rate predicted by the 3D simulations is proportional to the average grain size at the alloy/salt interface.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Tracking blobs in the turbulent edge plasma of a tokamak fusion device

Abstract The analysis of turbulence in plasmas is fundamental in fusion research. Despite extensive progress in theoretical modeling in the past 15 years, we still lack a complete and consistent understanding of turbulence in magnetic confinement devices, such as tokamaks. Experimental studies are challenging due to the diverse processes that drive the high-speed dynamics of turbulent phenomena. This work presents a novel application of motion tracking to identify and track turbulent filaments in fusion plasmas, called blobs, in a high-frequency video obtained from Gas Puff Imaging diagnostics. We compare four baseline methods (RAFT, Mask R-CNN, GMA, and Flow Walk) trained on synthetic data and then test on synthetic and real-world data obtained from plasmas in the Tokamak à Configuration Variable (TCV). The blob regime identified from an analysis of blob trajectories agrees with state-of-the-art conditional averaging methods for each of the baseline methods employed, giving confidence in the accuracy of these techniques. By making a dataset and benchmark publicly available, we aim to lower the entry barrier to tokamak plasma research, thereby greatly broadening the community of scientists and engineers who might apply their talents to this endeavor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fugitive methane detection using open-path stand-off chirped laser dispersion spectroscopy

We report an open-path chirped laser dispersion spectrometer capable of detecting the atmospheric methane concentration above the background using both specular and diffusive reflective surfaces via two distinct operation modes in a stand-off detection configuration. The system is integrated with simultaneous ranging functionality, which enables average concentration measurements for varying optical pathlengths. The system was first tested for accuracy and characterized to achieve sensitivity of 2.9 p p m - m / H z 1 / 2 and pathlength precision of 0.2 m / H z 1 / 2 with a controlled release of methane outside the laboratory. The instrument was subsequently field-deployed in the proximity of a natural gas compressor station for fugitive methane detection. The instrument successfully detected methane plumes and narrowed down the location of the plume through multi-path measurement. The field measurements were verified by a co-located reference mobile methane sensor.

Chen, Yifeng↗

Enhancing Fluid Flow Pressure and Saturation Prediction Accuracy and Reducing Uncertainty with Committee Machine – Illinois Basin Decatur Project (IBDP) as a Case Study

Presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. Carbon capture and storage (CCS) is a way to play a critical role in the global transition to a low-emission economy. Current progress is hampered by a number of factors, among which the lack of risk-informed design tools and decision support frameworks is seen as a major roadblock. Significant interest exists in using artificial intelligence to accelerate CCS site feasibility studies, as well as to facilitate the permit application process. Existing works commonly train a single deep learning model. This work investigates the feasibility of using a conventional ensemble learning (committee machine) technique to further improve prediction accuracy. Ensemble-based algorithms generally improve over individual base learners in terms of robustness and accuracy. Deep ensembles, however, are time-consuming to create and train. A pragmatic question is whether small-sized ensembles may lead to prediction improvement. Here we evaluated the efficacy of an ensemble learning technique using the latent spectral model (LSM), an efficient deep neural operator algorithm, as base learners. Preliminary results, obtained using the Illinois Basin-Decatur Project (IBDP) carbon sequestration data/model, show that small-sized ensembles can improve prediction over the base learners, achieving prediction accuracy of ~1.6 psi root mean square error (RMSE) on pressure (relative the average reservoir pressure of 3150 psi), and less than 1.3% for saturation.

Sun, Alexander↗

Convergence and Quantum Advantage of Trotterized MERA for Strongly-Correlated Systems

Strongly-correlated quantum many-body systems are difficult to study and simulate classically. We recently proposed a variational quantum eigensolver (VQE) based on the multiscale entanglement renormalization ansatz (MERA) with tensors constrained to certain Trotter circuits. Here, we determine the scaling of computation costs for various critical spin chains which substantiates a polynomial quantum advantage in comparison to classical MERA simulations based on exact energy gradients or variational Monte Carlo. Algorithmic phase diagrams suggest an even greater separation for higher-dimensional systems. Hence, the Trotterized MERA VQE is a promising route for the efficient investigation of strongly-correlated quantum many-body systems on quantum computers. Furthermore, we show how the convergence can be substantially improved by building up the MERA layer by layer in the initialization stage and by scanning through the phase diagram during optimization. For the Trotter circuits being composed of single-qubit and two-qubit rotations, it is experimentally advantageous to have small rotation angles. We find that the average angle amplitude can be reduced considerably with negligible effect on the energy accuracy. Benchmark simulations suggest that the structure of the Trotter circuits for the TMERA tensors is not decisive; in particular, brick-wall circuits and parallel random-pair circuits yield very similar energy accuracies.

Miao, Qiang [Duke Quantum Center, Duke University,↗

The uses and limitations of HF standard broadcasts for time and frequency comparison

The most practical methods of using high-frequency (HF) broadcasts for frequency and time comparison are reviewed. Although standard broadcast and receiving equipment has improved vastly throughout the past fifty years, the HF propagation medium is no more stable today than it was a half century ago. Doppler shift resulting from changes in the effective height of the ionosphere typically limits the usable accuracy of received high frequencies to a few parts in 10 to the 7th power. At locations beyond groundwave range of the transmitter, uncertainties in path delay generally restrict the usable accuracy of HF time signals to the order of a millisecond. Signal-averaging techniques are sometimes employed to extract frequency or time signals from a noisy background.

Stanley, J. T.↗

A note on the diurnal averaging of aeronomical models

An approximate technique for diurnally time-averaging atmospheric photochemical-dynamical models which eliminates the need for a detailed numerical resolution of sunrise and sunset transitions is developed. The scheme is equivalent to scaling certain chemical rate constants and photodissociation coefficients by appropriate aeronomical factors. To calculate the scaling factors, diurnal variations are parameterized with a step-function behavior, assuming that each species has a constant day-time and night-time concentration whose ratio can be determined by analyzing the chemical interactions occurring after sunset. The solution accounts for the effects of night-time reactions on the 24 h average values of species abundances, and on the average daily rates of the catalytic processes consuming ozone in the stratosphere. The accuracy of the technique is demonstrated by comparing its predictions to those of a full diurnal simulation; typically, the precision is better than 10%. By contrast, it is shown that the use of some other well-known computational schemes can result in significantly larger predictive errors.

Turco, R. P.↗

Program for narrow-band analysis of aircraft flyover noise using ensemble averaging techniques

A package of computer programs was developed for analyzing acoustic data from an aircraft flyover. The package assumes the aircraft is flying at constant altitude and constant velocity in a fixed attitude over a linear array of ground microphones. Aircraft position is provided by radar and an option exists for including the effects of the aircraft's rigid-body attitude relative to the flight path. Time synchronization between radar and acoustic recording stations permits ensemble averaging techniques to be applied to the acoustic data thereby increasing the statistical accuracy of the acoustic results. Measured layered meteorological data obtained during the flyovers are used to compute propagation effects through the atmosphere. Final results are narrow-band spectra and directivities corrected for the flight environment to an equivalent static condition at a specified radius.

Gridley, D.↗

ERBE data inversion

Instruments on board the (presently two) satellites of the Earth Radiation Budget Experiment (ERBE) are collecting data for determining monthly averaged radiation exitances at the top of the atmosphere (TOA). To achieve the accuracy desired of the mission, radiances at the satellite are first calculated, with allowance made of sensor optical properties and the directionality of the TOA radiation field. The subsatellite surface type is classified to adjust for albedo changes and correction values are added for the types of cloud cover detected.

Smith, G. L.↗

Nonintrusive, multipoint velocity measurements in high-pressure combustion flows

A combined experimental and analytical effort was conducted to demonstrate the applicability of OH Doppler-shifted fluorescence imaging of velocity distributions in supersonic combustion gases. The experiments were conducted in the underexpanded exhaust flow from a 6.8 atm, 2400 K, H2-O2-N2 burner exhausting into the atmosphere. In order to quantify the effects of in-plane variations of the gas thermodynamic properties on the measurement accuracy, a set of detailed measurements of the OH (1,0) band collisional broadening and shifting in H2-air gases was produced. The effect of pulse-to-pulse variations in the dye laser bandshape was also examined in detail and a modification was developed which increased in the single pulse bandwidth, thereby increasing the intraimage velocity dynamic range as well as reducing the sensitivity of the velocity measurement to the gas property variations. Single point and imaging measurements of the velocity field in the exhaust flowfield were compared with 2D, finite-rate kinetics simulations of the flowfield. Relative velocity accuracies of +/- 50 m/s out of 1600 m/s were achieved in time-averaged imaging measurements of the flow over an order of magnitude variation in pressure and a factor of two variation in temperature.

Allen, M.↗

Improved Algorithm to Estimate Convective and Stratiform Rain from TRMM Microwave Radiometer Data

The rain rates associated with Mesoscale Convective Systems (MCSS) deduced from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) follow the well known log-normal type frequency distribution characteristic of conventional radars and rain gauges. On the other hand, the current microwave radiometer rain retrieval algorithms cannot give good representations of convective and stratiform precipitation. Thus they capture poorly this log-normal character. In particular, this is noticed clearly over land areas. The objective of the present study is to improve TRMM Microwave Imager (TMI) retrievals of convective and stratiform rain to a level comparable to the PR. For this purpose, we have developed a TMI rain retrieval algorithm that depends primarily on the 85 GHz brightness temperatures (Tbs) and their spatial distribution. We emphasize the 85 GHz channel because of its fine footprint size (about 5.5 km) and strong extinction property. The other spectral channels, because they are poorer in these respects, are given less importance. The brightness temperatures and spatial distribution information in the 85 GHz allows us to detect thunderstorms, or cumulonimbus clouds (Cbs), that are in different stages of development, as well as stratiform rain outside of these Cbs. Utilizing our retrieval technique, we have produced maps of convective and stratiform rain for several MCS events over land and ocean that agree well with those given by the PR. On average, the convective and stratiform rain rates given by our technique have an accuracy of about 15 % with respect to those given by the PR.

Prabhakara, C.↗

Review of TRMM/GPM Rainfall Algorithm Validation

A review is presented concerning current progress on evaluation and validation of standard Tropical Rainfall Measuring Mission (TRMM) precipitation retrieval algorithms and the prospects for implementing an improved validation research program for the next generation Global Precipitation Measurement (GPM) Mission. All standard TRMM algorithms are physical in design, and are thus based on fundamental principles of microwave radiative transfer and its interaction with semi-detailed cloud microphysical constituents. They are evaluated for consistency and degree of equivalence with one another, as well as intercompared to radar-retrieved rainfall at TRMM's four main ground validation sites. Similarities and differences are interpreted in the context of the radiative and microphysical assumptions underpinning the algorithms. Results indicate that the current accuracies of the TRMM Version 6 algorithms are approximately 15% at zonal-averaged / monthly scales with precisions of approximately 25% for full resolution / instantaneous rain rate estimates (i.e., level 2 retrievals). Strengths and weaknesses of the TRMM validation approach are summarized. Because the dew of convergence of level 2 TRMM algorithms is being used as a guide for setting validation requirements for the GPM mission, it is important that the GPM algorithm validation program be improved to ensure concomitant improvement in the standard GPM retrieval algorithms. An overview of the GPM Mission's validation plan is provided including a description of a new type of physical validation model using an analytic 3-dimensional radiative transfer model.

Smith, Eric A.↗

Lunar Polar Illumination for Power Analysis

This paper presents illumination analyses using the latest Earth-based radar digital elevation model (DEM) of the lunar south pole and an independently developed analytical tool. These results enable the optimum sizing of solar/energy storage lunar surface power systems since they quantify the timing and durations of illuminated and shadowed periods. Filtering and manual editing of the DEM based on comparisons with independent imagery were performed and a reduced resolution version of the DEM was produced to reduce the analysis time. A comparison of the DEM with lunar limb imagery was performed in order to validate the absolute heights over the polar latitude range, the accuracy of which affects the impact of long range, shadow-casting terrain. Average illumination and energy storage duration maps of the south pole region are provided for the worst and best case lunar day using the reduced resolution DEM. Average illumination fractions and energy storage durations are presented for candidate low energy storage duration south pole sites. The best site identified using the reduced resolution DEM required a 62 hr energy storage duration using a fast recharge power system. Solar and horizon terrain elevations as well as illumination fraction profiles are presented for the best identified site and the data for both the reduced resolution and high resolution DEMs compared. High resolution maps for three low energy storage duration areas are presented showing energy storage duration for the worst case lunar day, surface height, and maximum absolute surface slope.

Fincannon, James↗

Microstructural Influence on Deformation and Fatigue Life of Composites Using the Generalized Method of Cells

A fully coupled deformation and damage approach to modeling the response of composite materials and composite laminates is presented. It is based on the semi-­‐analytical generalized method of cells (GMC) micromechanics model as well as its higher fidelity counterpart, HFGMC, both of which provide closed-form constitutive equations for composite materials as well as the micro scale stress and strain fields in the composite phases. The provided constitutive equations allow GMC and HFGMC to function within a higher scale structural analysis (e.g., finite element analysis or lamination theory) to represent a composite material point, while the availability of the micro fields allow the incorporation of lower scale sub­‐models to represent local phenomena in the fiber and matrix. Further, GMC's formulation performs averaging when applying certain governing equations such that some degree of microscale field accuracy is surrendered in favor of extreme computational efficiency, rendering the method quite attractive as the centerpiece in a integrated computational material engineering (ICME) structural analysis; whereas HFGMC retains this microscale field accuracy, but at the price of significantly slower computational speed. Herein, the sensitivity of deformation and the fatigue life of graphite/epoxy PMC composites, with both ordered and disordered microstructures, has been investigated using this coupled deformation and damage micromechanics based approach. The local effects of fiber breakage and fatigue damage are included as sub‐models that operate on the microscale for the individual composite phases. For analysis of laminates, classical lamination theory is employed as the global or structural scale model, while GMC/HFGMC is embedded to operate on the microscale to simulate the behavior of the composite material within each laminate layer. A key outcome of this study is the statistical influence of microstructure and micromechanics idealization (GMC or HFGMC) on the overall accuracy of unidirectional and laminated composite deformation and fatigue response.

Microscale Models↗

Pressure Monitoring Using Hybrid fs/ps Rotational CARS

We investigate the feasibility of gas-phase pressure measurements at kHz-rates using fs/ps rotational CARS. Femtosecond pump and Stokes pulses impulsively prepare a rotational Raman coherence, which is then probed by a high-energy 6-ps pulse introduced at a time delay from the Raman preparation. Rotational CARS spectra were recorded in N2 contained in a room-temperature gas cell for pressures from 0.1 to 3 atm and probe delays ranging from 10-330 ps. Using published self-broadened collisional linewidth data for N2, both the spectrally integrated coherence decay rate and the spectrally resolved decay were investigated as means for detecting pressure. Shot-averaged and single-laser-shot spectra were interrogated for pressure and the accuracy and precision as a function of probe delay and cell pressure are discussed. Single-shot measurement accuracies were within 0.1 to 6.5% when compared to a transducer values, while the precision was generally between 1% and 6% of measured pressure for probe delays of 200 ps or more, and better than 2% as the delay approached 300 ps. A byproduct of the pressure measurement is an independent but simultaneous measurement of the gas temperature.

Kearney, Sean P.↗

California Agriculture: Using Earth Observations to Estimate the Age and Carbon Stock of Perennial Agriculture

California seeks to become a carbon neutral state by 2045. To track progress toward this goal, it is important to quantify the amount of carbon stored by various landcover types across the state. Vineyards and orchards make up a large portion of California's agricultural landcover and store considerable amounts of carbon. For this project, NASA DEVELOP partnered with the California Air Resources Board to estimate the age and carbon stock of crop-specific agricultural regions across California between 1984 and 2021. The DEVELOP team created the Perennial Agriculture Age and Carbon Estimation Tool (PAACET), a Google Earth Engine tool that employs Earth observation from the Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI) to estimate the age and carbon stock of vineyards and almond, walnut, pistachio, and orange orchards. The team used an ocular sampling accuracy assessment consisting of 53 sample vineyards and orchards and found that on average, PAACET estimated ages within ±4.3 years of their actual age. The tool estimated that vineyards and walnut orchards are the oldest woody croplands, and almond orchards store the largest total carbon.

Rachael Ross↗

Evidence for a Dense, Inhomogeneous Circumstellar Medium in the Type Ia SNR 0519-69.0

We perform an expansion study of the Balmer dominated outer shock of the SNR0519−69.0 in the LMC by using a combination of newHSTWFC3 imagery obtained in 2020 and archival ACS images from 2010 and 2011. Thanks to the very long time baseline, our proper motion measurements are of unprecedented accuracy. We find a wide range of shock velocities, with the fastest shocks averaging 5280 km s−1and the slowest grouping of shocks averaging just 1670 km s−1. We compare the Hα images from HST with X-ray images from Chandra and mid-IR images from Spitzer, finding a clear anti-correlation between the brightness of the remnant in a particular location and the velocity of the blast wave at that location, supporting the idea that the bright knots of X-ray and IR emission result from an interaction with a dense inhomogeneous circumstellar medium. We find no evidence for X-ray emission, thermal or nonthermal, associated with the fastest shocks, as expected if the fastest velocities are the result of the blast wave encountering the lower density ambient medium of the LMC. We derive an age of the remnant of≤670±70 yr, consistent with results derived from previous investigations.

Brian J Williams↗

Enhancing Fluid Flow Pressure and Saturation Prediction Accuracy and Reducing Uncertainty with Committee Machine – Illinois Basin Decatur Project (IBDP) as a Case Study

This is the conference paper accompanying an oral presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. Carbon capture and storage (CCS) is a way to play a critical role in the global transition to a low-emission economy. Current progress is hampered by a number of factors, among which the lack of risk-informed design tools and decision support frameworks is seen as a major roadblock. Significant interest exists in using artificial intelligence to accelerate CCS site feasibility studies, as well as to facilitate the permit application process. Existing works commonly train a single deep learning model. This work investigates the feasibility of using a conventional ensemble learning (committee machine) technique to further improve prediction accuracy. Ensemble-based algorithms generally improve over individual base learners in terms of robustness and accuracy. Deep ensembles, however, are time-consuming to create and train. A pragmatic question is whether small-sized ensembles may lead to prediction improvement. Here we evaluated the efficacy of an ensemble learning technique using the latent spectral model (LSM), an efficient deep neural operator algorithm, as base learners. Preliminary results, obtained using the Illinois Basin-Decatur Project (IBDP) carbon sequestration data/model, show that small-sized ensembles can improve prediction over the base learners, achieving prediction accuracy of ~1.6 psi root mean square error (RMSE) on pressure (relative the average reservoir pressure of 3150 psi), and less than 1.3% for saturation.

Sun, Alexander↗