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DOE OSTI2022

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↗

DOE OSTI2020

Dust and gas absorption in the high mass X-ray binary IGR J16318-4848

With an absorption column density on the order of 10 24 cm -2 , IGR J16318-4848 is one of the most extreme cases of a highly obscured high mass X-ray binary. In addition to the overall continuum absorption, the source spectrum exhibits a strong iron and nickel fluorescence line complex at 6.4 keV. Previous empirical modeling of these features and comparison with radiative transfer simulations raised questions about the structure and covering fraction of the absorber and the profile of the fluorescence lines. We aim at a self-consistent description of the continuum absorption, the absorption edges, and the fluorescence lines to constrain the properties of the absorbing material, such as ionization structure and geometry. We further investigate the effects of dust absorption on the observed spectra and the possibility of fluorescence emission from dust grains. We used XMM-Newton and NuSTAR spectra to first empirically constrain the incident continuum and fluorescence lines. Next we used XSTAR to construct a customized photoionization model where we vary the ionization parameter, column density, and covering fraction. In the third step we modeled the absorption and fluorescence in a dusty olivine absorber and employed both a simple analytical model for the fluorescence line emission and a Monte Carlo simulation of radiative transfer that generates line fluxes, which are very close to the observational data. Our empirical spectral modeling is in agreement with previous works. Our second model, the single gas absorber does not describe the observational data. In particular, irrespective of the ionization state or column density of the absorber, a much higher covering fraction than previously estimated is needed to produce the strong fluorescence lines and the large continuum absorption. A dusty, spherical absorber (modeled as consisting of olivine dust, although the nature of dust cannot be constrained) is able to produce the observed continuum absorption and edges. A dense, dusty absorber in the direct vicinity of the source consisting of dust offers a consistent description of both the strong continuum absorption and the strong emission features in the X-ray spectrum of IGR J16318-4848. In particular, for low optical depth of individual grains, which is the case for typical volume densities and grain size distribution models, the dust will contribute significantly to the fluorescence emission.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Scoping Study for Fast Flux Testing in the Advanced Test Reactor

The value of fast spectrum reactors remains prominent in the nuclear technology portfolio. The performance of these reactors can be maximized with advancements in nuclear fuel technologies, but development of these technologies is currently held back by lack of fast spectrum test reactors available to the United States. Spectral modification of experiment positions in the thermal spectrum Advanced Test Reactor (ATR) has long been used to support fast reactor fuel development, but these methods have not been progressed to their full potential. This study investigated the use of concentric rings of aluminum-clad fuel plates in ATR flux traps and thermal neutron absorbing filters to increase fast neutron flux on test specimens. This concept was termed the Boosted Energy Advanced Spectrum Test (BEAST). This approach will enable irradiation of advanced fuel designs in prototypic-length fuel pins and representative flux environment to support post irradiation exams, enable transient testing, and produce the type of data that will permit lead test assembly irradiations in true Sodium Fast Reactors (SFRs) when they become available. Neutronic predictions were performed to investigate BEAST design options and thermal hydraulic models were produced to ensure feasibility of BEAST. Two versions were considered based on the geometric limitations of ATR’s small and large flux traps. The small version was found to be preferable due to slightly higher fast flux and fast-to-thermal neutron ratio. Perhaps more influentially, the small flux trap option was also preferred to avoid conflict with ongoing very high temperature reactor fuel irradiation programs in ATR’s large northeast flux trap. The small flux trap option provided less than half the test volume of the large version, but still had adequate volume for seven SFR pins in cross section which could be stacked two-high in ATR’s 1.2m long core to accommodate up to 14 EBR-II size pins. The preference for the small flux trap configuration should be revisited if additional collaborative test programs emerge with the need to irradiate a significant volume of additional specimens. Calculations were performed regarding a lithium deuteride ring to convert thermal neutrons into 14 MeV fusion neutrons. At the time this report was written these calculations were partially complete and it remains to be seen whether the concept would be worth including in BEAST. Given the preference for the small flux trap option, which does not afford enough room for the 14 MeV ring, it was concluded to defer future work on the lithium deuteride ring. This decision could be revisited if fusion material research programs emerge for collaborative testing in BEAST. A cadmium-lined specimen holder design was found to be adequate in filtering thermal neutrons and preferred over other neutron absorbers based on past experience with cadmium baskets. It was acknowledged that cadmium-bearing hardware would become depleted and need to be replaced occasionally, which appeared feasible from a mechanical design perspective. Neutronic studies investigated different enrichment levels in the booster fuel using uranium-molybdenum alloy dispersion fuel which has performed well in past ATR irradiations. Both options were able to drive fuel pins to SFR-like fission heating rates. The high enriched booster fuel option outperformed the low enriched option by ~20% on key metrics including fast flux and fast-to-thermal ratio, but the low enriched option was favored in order to broaden options for potential fuel suppliers. The preferred BEAST design options including cadmium filter with low enriched booster fuel in the small flux trap configuration was predicted to achieve 6.2E14 n/cm2sec fast flux (>0.1 MeV) with a fast-to-thermal ratio of 44.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Search for leptonic charge asymmetry in $t\overline{t}W$ production in final states with three leptons at $\sqrt{s}$ = 13 TeV

A search for the leptonic charge asymmetry (${A}_{c}^{\ell}$) of top-quark-antiquark pair production in association with a $W$ boson ($t\overline{t}W$) is presented. The search is performed using final states with exactly three charged light leptons (electrons or muons) and is based on $\sqrt{s}$= 13 TeV proton-proton collision data collected with the ATLAS detector at the Large Hadron Collider at CERN during the years 2015–2018, corresponding to an integrated luminosity of 139 fb –1 . A profile-likelihood fit to the event yields in multiple regions corresponding to positive and negative differences between the pseudorapidities of the charged leptons from top-quark and top-antiquark decays is used to extract the charge asymmetry. At reconstruction level, the asymmetry is found to be –0.12 ± 0.14 (stat.) ± 0.05 (syst.). An unfolding procedure is applied to convert the result at reconstruction level into a charge-asymmetry value in a fiducial volume at particle level with the result of –0.11 ± 0.17 (stat.) ± 0.05 (syst.). The Standard Model expectations for these two observables are calculated using Monte Carlo simulations with next-to-leading-order plus parton shower precision in quantum chromodynamics and including next-to-leading-order electroweak corrections. They are ${–0.084}_{–0.003}^{+0.005}$ (scale) ± 0.006 (MC stat.) and ${–0.063}_{–0.004}^{+0.007}$ (scale) ± 0.004 (MC stat.) respectively, and in agreement with the measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Chemical and genetic characterization of the ungrouped pallasite Lieksa

The meteorite Lieksa was found in 2017 in Löpönvaara, Finland, and later donated to the Finnish Museum of Natural History. Here, we report siderophile element concentrations, genetic isotopic data, and a metal–silicate segregation age for the meteorite. The ~280 g Lieksa is ~80% metal and ~20% silicate and oxide inclusions by volume, with the inclusions consisting primarily of Fe-rich olivine. Due to Lieksa's silicate content, coupled with a texture characterized by metal enclosing the silicates, it has been classified as a pallasite. Lieksa's olivine and bulk chemical characteristics are distinct from those of the known pallasite and iron meteorite groups, consistent with its classification as ungrouped. The meteorite exhibits a flat, chondrite-normalized highly siderophile element pattern, consistent with an origin as an early crystallization product from a metallic melt with chondritic relative abundances. Molybdenum, Ru, and 183 W isotopic data indicate that Lieksa formed in the non-carbonaceous (NC) domain of the solar nebula. Radiogenic 182 W abundances for Lieksa yield a model metal–silicate segregation age of 1.5 ± 0.8 Myr after calcium-aluminum-rich inclusion formation, which is within the range established for other NC-type pallasite and iron meteorite parent bodies.

58 GEOSCIENCES↗

DOE OSTI2020

A Hybrid Deep Learning Approach to Cosmological Constraints from Galaxy Redshift Surveys

We present a deep machine learning (ML)–based technique for accurately determining σ g and Ω m from mock 3D galaxy surveys. The mock surveys are built from the AbacusCosmos suite of N -body simulations, which comprises 40 cosmological volume simulations spanning a range of cosmological parameter values, and we account for uncertainties in galaxy formation scenarios through the use of generalized halo occupation distributions (HODs). We explore a trio of ML models: a 3D convolutional neural network (CNN), a power spectrum–based fully connected network, and a hybrid approach that merges the two to combine physically motivated summary statistics with flexible CNNs. We describe best practices for training a deep model on a suite of matched-phase simulations, and we test our model on a completely independent sample that uses previously unseen initial conditions, cosmological parameters, and HOD parameters. Despite the fact that the mock observations are quite small (~0.07 h -3 Gpc 3 ) and the training data span a large parameter space (six cosmological and six HOD parameters), the CNN and hybrid CNN can constrain estimates of σ g and Ω m to ~3% and ~4%, respectively.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

NGEE Arctic Rainfall Simulator Validation Data from Los Alamos National Laboratory, New Mexico, Summer 2022

Experiments evaluating the uniformity and intensity of rainfall produced by the NGEE Arctic Rainfall Simulator (NARS) were conducted at Los Alamos National Laboratory, New Mexico, over summer 2022. Petri dishes were placed in a grid within the NARS plot. Simulated rainfall was collected in each petri dish and the intensity and uniformity of the simulator was subsequently calculated. This data package contains two .csv files, one that summarizes the rainfall intensity and uniformity for each experiment, the other that contains individual petri dish water volume and intensity for each plot location and experiment. The Python scripts to control NARS are also included. The NGEE Arctic Rainfall Simulator (NARS) is a variable intensity rainfall simulator (RFS) with a frame design based on the Humphry et al. (2002) RFS and a water delivery system based on the Walnut Gulch (Paige et al., 2004) RFS. The NARS uses an aluminum frame that is fully deconstructable for transportation to field locations and a water system that enables variable rain intensity. Rain intensity control and data collection are automated using a Raspberry Pi microcomputer. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Validation of seismic velocity models in southern California with full-waveform simulations

SUMMARY Crustal seismic velocity models provide essential information for many applications including earthquake source properties, simulations of ground motion and related derivative products. We present a systematic workflow for assessing the accuracy of velocity models with full-waveform simulations. The framework is applied to four regional seismic velocity models for southern California: CVM-H15.11, CVM-S4.26, CVM-S4.26.M01 that includes a shallow geotechnical layer, and the model of Berg et al. For each model, we perform 3-D viscoelastic wave propagation simulations for 48 virtual seismic noise sources (down to 2 s) and 44 moderate-magnitude earthquakes (down to 2 s generally and 0.5 s for some cases) assuming a minimum shear wave velocity of 200 m s–1. The synthetic waveforms are compared with observations associated with both earthquake records and noise cross-correlation data sets. We measure, at multiple period bands for well-isolated seismic phases, traveltime delays and normalized zero-lag cross-correlation coefficients between the synthetic and observed data. The obtained measurements are summarized using the mean absolute derivation of time delay and the mean correlation coefficient. These two metrics provide reliable statistical representations of model quality with consistent results in all data sets. In addition to assessing the overall (average) performance of different models in the entire study area, we examine spatial variations of the models’ quality. All examined models show good phase and waveform agreements for surface waves at periods longer than 5 s, and discrepancies at shorter periods reflecting small-scale heterogeneities and near-surface structures. The model performing best overall is CVM-S4.26.M01. The largest misfits for both body and surface waves are in basin structures and around large fault zones. Inaccuracies generated in these areas may affect tomography and model simulation results at other regions. The seismic velocity models for southern California can be improved by adding better resolved structural representations of the shallow crust and volumes around the main faults.

58 GEOSCIENCES↗

DOE OSTI2022

Atomistic Simulations of the Elastic Compression of Platinum Nanoparticles

Abstract The elastic behavior of nanoparticles depends strongly on particle shape, size, and crystallographic orientation. Many prior investigations have characterized the elastic modulus of nanoscale particles using experiments or simulations; however their reported values vary widely depending on the methods for measurement and calculation. To understand these discrepancies, we used classical molecular dynamics simulation to model the compression of platinum nanoparticles with two different polyhedral shapes and a range of sizes from 4 to 20 nm, loaded in two different crystal orientations. Multiple standard methods were used to calculate the elastic modulus from stress-vs-strain data for each nanoparticle. The magnitudes and particle-size dependence of the resulting moduli varied with calculation method and, even for larger nanoparticles where bulk-like behavior may be expected, the effective elastic modulus depended strongly on shape and orientation. Analysis of per-atom stress distributions indicated that the shape- and orientation-dependence arise due to stress triaxiality and inhomogeneity across the particle. When the effective elastic modulus was recalculated using a representative volume element in the center of a large nanoparticle, the elastic modulus had the expected value for each orientation and was shape independent. It is only for single-digit nanoparticles that meaningful differences emerged, where even the very center of the particle had a lower modulus due to the effect of the surface. These findings provide better understanding of the elastic properties of nanoparticles and disentangle geometric contributions (such as stress triaxiality and spatial inhomogeneity) from true changes in elastic properties of the nanoscale material.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Improving climate model coupling through a complete mesh representation: a case study with E3SM (v1) and MOAB (v5.x)

One of the fundamental factors contributing to the spatiotemporal inaccuracy in climate modeling is the mapping of solution field data between different discretizations and numerical grids used in the coupled component models. The typical climate computational workflow involves evaluation and serialization of the remapping weights during the preprocessing step, which is then consumed by the coupled driver infrastructure during simulation to compute field projections. Tools like Earth System Modeling Framework (ESMF) and TempestRemap offer capability to generate conservative remapping weights, while the Model Coupling Toolkit (MCT) that is utilized in many production climate models exposes functionality to make use of the operators to solve the coupled problem. However, such multistep processes present several hurdles in terms of the scientific workflow and impede research productivity. In order to overcome these limitations, we present a fully integrated infrastructure based on the Mesh Oriented datABase (MOAB) library, which allows for a complete description of the numerical grids and solution data used in each submodel. Through a scalable advancing-front intersection algorithm, the supermesh of the source and target grids are computed, which is then used to assemble the high-order, conservative, and monotonicity-preserving remapping weights between discretization specifications. The Fortran-compatible interfaces in MOAB are utilized to directly link the submodels in the Energy Exascale Earth System Model (E3SM) to enable online remapping strategies in order to simplify the coupled workflow process. We demonstrate the superior computational efficiency of the remapping algorithms in comparison with other state-of-the-science tools and present strong scaling results on large-scale machines for computing remapping weights between the spectral element atmosphere and finite volume discretizations on the polygonal ocean grids.

58 GEOSCIENCES↗

DOE OSTI2025

Direct Measurement of Galaxy Assembly Bias using DESI DR1 Data

We report the first direct measurement of galaxy assembly bias, a critical systematic in cosmology, from the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey. We introduce a novel, cosmology-independent method to measure the halo occupation distribution (HOD) by combining a state-of-the-art group catalog with weak gravitational lensing. For groups binned by total luminosity, we determine the galaxy occupation number $N_{\rm gal}$ from group-galaxy cross-correlations, while weak lensing constrains the average halo mass $M_h$. Applying this to a volume-limited sample at $z{\in}[0.05,0.2]$, we measure the dependence of HOD, $N_{\rm gal}(M_h)$, on large-scale overdensity $δ_{g}$. Focusing on the satellite galaxies, we find an assembly bias parameter of $Q_{\rm sat}{=}0.05{\pm}0.14$, a result consistent with zero and in tension with many empirical galaxy formation models. Our method provides a robust approach for characterizing galaxy assembly bias to achieve precision cosmology with DESI and future Stage-V surveys.

Shao, Zhiwei [Shanghai Jiaotong U.; Shanghai Jiao ↗

DOE OSTI2021

A two-equation soot-in-flamelet modeling approach applied under Spray A conditions

Soot production (including formation and oxidation) is studied in the transient, high-pressure and turbulent n-dodecane Spray A flames from the Engine Combustion Network (ECN) using computational fluid dynamics (CFD) simulations. A two-equation soot-in-flamelet modeling approach is applied within the framework of the Unsteady Flamelet Progress Variable (UFPV) model and results are validated against experimental data. Equations for soot mass fraction and soot number density derived in the mixture fraction space are solved in the context of detailed flamelet calculations. Source terms for the different steps in the soot chemistry are tabulated and incorporated in the flamelet manifold. For the reference condition, the modeling approach based on the tabulated flamelet manifold reduces the computational cost of a CFD calculation by approximately 40 times compared to a non-tabulated well-mixed (WM) modeling approach. The soot-in-flamelet approach is then extended to study the effect of ambient oxygen concentration, ambient mixture composition and ambient temperature on soot production. Results show that the modeling approach is able to capture the experimental trends for the soot volume fraction (SVF) with good quantitative agreement, especially in the soot ramp-up region.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Updimensioning strategy derived from synthetic equiaxed grain structures for approximating 3D grain size distributions from 2D visualizations with 1D parameters

We generated synthetic equiaxed grain structures using computer graphics software to explore the relationship between various grain size determination methods and true three-dimensional (3D) grain diameters. Mirroring grain measurement techniques, the synthetic 3D grain structures are imaged as 2D micrographs which are measured to yield 1D grain size parameters. Synthetic grain structures provide data at a mass scale and permit exploration of both polished and fractured surface micrographs, revealing one-to-one correspondence between exposed 2D grain cross-sections and individual 3D grains. Analysis of this correspondence yielded a procedure to approximate 3D equiaxed grain size and volume distributions based on the mode of the 2D fractograph grain size distribution. The 3D approximation procedure is shown to be less susceptible to different imaging conditions that affect small, undiscernible grains compared to the standard planimetric and linear intercept methods, which by design also tend to underestimate the 3D grain diameter. The procedure requires larger sample sizes to lower variance and a deeper analysis which could become more practical with machine learning (ML) models for grain boundary segmentation, which synthetic grain structures can help train. This work lays the foundation for analyzing other grain distributions such as columnar and composite grains in similar depth.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Signs of nonmonotonic finite-volume corrections to 𝑔 𝐴

We study finite-volume (FV) corrections to determinations of 𝑔 𝐴 via lattice quantum chromodynamics (QCD) using analytic results and numerical analysis. We observe that 𝑆⁢𝑈⁡(2) heavy Baryon chiral perturbation theory does not provide an unambiguous prediction for the sign of the FV correction, which is not surprising when one also considers large-𝑁 𝑐 constraints on the axial couplings. We further show that nonmonotonic FV corrections are naturally allowed when one considers either including explicit Δ-resonance degrees of freedom or one works to higher orders in the chiral expansion. We investigate the potential impact of these FV corrections with a precision study of 𝑔 𝐴 using models of FV corrections that are monotonic and nonmonotonic. Using lattice QCD data that is approximately at the 1% level of precision, we do not see significant evidence of nonmonotonic corrections. Looking forward to the next phase of lattice QCD calculations, we estimate that calculations that are between the 0.1% and 1% level of precision may be sensitive to these FV artifacts. Finally, we present an update of the CalLat prediction of 𝑔 𝐴 in the isospin limit with subpercent precision, 𝑔$^{QCD}_{𝐴}$ = 1.2674⁢(96).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Laminar flame speed measurements of a gasoline surrogate and its mixtures with ethanol at elevated pressure and temperature

Laminar Flame speed measurements of a gasoline surrogate and mixtures of it with ethanol were conducted using a heated, constant-volume vessel. A spherical propagating flame was observed using a high-speed camera, and laminar flame speed was determined therefrom. Here, the gasoline surrogate, which serves as the baseline for the current study, consisted of four components, namely, iso-octane, n-heptane, toluene, and 1-hexene. Different mixtures of the gasoline surrogate and ethanol were studied, governed by the ethanol percentage in the mixture. That is, E0, E30, E50, and E85 mixtures represent 0%, 30%, 50%, and 85% ethanol in the gasoline surrogate mixture by liquid volume, respectively. Initial temperatures of 335, 359, and 408 K and initial pressures of 1 and 3 bar were investigated. The findings of this study are compared to results in the literature, which show good agreement for E0 but some deviation for the E30 blend. In general, the study showed an increase in laminar flame speed as the ethanol percentage increases in the mixture. Similarly, increasing the initial temperature with fixed ethanol percentage resulted in an increase in laminar flame speed, as expected. In contrast, increasing the initial pressure with fixed Ethanol percentage showed a decrease in laminar flame speed. Finally, the results are compared to an existing chemical kinetics model designed for ethanol and gasoline. Although agreement between the model and data is reasonable and mostly within about 10%, some improvement to the kinetics model is needed to uniformly lower the calculated flame speeds.

09 BIOMASS FUELS↗

DOE OSTI2023

Ensemble flow reconstruction in the atmospheric boundary layer from spatially limited measurements through latent diffusion models

Due to costs and practical constraints, field campaigns in the atmospheric boundary layer typically only measure a fraction of the atmospheric volume of interest. Machine learning techniques have previously successfully reconstructed unobserved regions of flow in canonical fluid mechanics problems and two-dimensional geophysical flows, but these techniques have not yet been demonstrated in the three-dimensional atmospheric boundary layer. Here, we conduct a numerical analogue of a field campaign with spatially limited measurements using large-eddy simulation. We pose flow reconstruction as an inpainting problem, and reconstruct realistic samples of turbulent, three-dimensional flow with the use of a latent diffusion model. The diffusion model generates physically plausible turbulent structures on larger spatial scales, even when input observations cover less than 1% of the volume. Through a combination of qualitative visualization and quantitative assessment, we demonstrate that the diffusion model generates meaningfully diverse samples when conditioned on just one observation. These samples successfully serve as initial conditions for a large-eddy simulation code. We find that diffusion models show promise and potential for other applications for other turbulent flow reconstruction problems.

17 WIND ENERGY↗

DOE OSTI2023

Conservation of Helium while Maintaining High System Purity

Recent helium shortages and helium price increases have lead to an increased emphasis being placed on conserving helium. The need to conserve helium must be balanced with need to maintain the high levels of purity necessary to prevent operational problems caused by contamination. Helium losses and contamination control are especially important for test stands that have cryogenic distribution systems operating continuously with frequent changeover of cryogenic temperature components that are being tested. This paper describes a mathematical model to estimate the quantity of helium lost and the purity of the helium after the pump and backfill procedure is complete. The process to determine the optimal time during pump down to cut off pumping and start backfilling is described. There is a tradeoff between trying to achieve the lowest possible pressure during pumping and the quantity of air leaking into the volume while pumping is occurring. An additional benefit of careful selection of pump and backfill parameters in conjunction with real-time pressure monitoring can reduce the labor and time required to complete a successful pump and backfill procedure. This paper is intended to be a tool for engineers to review their pump and backfill procedures and measured data to optimize helium losses, system purity, and labor required.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Process Optimization of Carbon Electrode Materials Manufacturing by Experimental Study and Machine Learning Techniques

Electrospun carbon fibers from coal have been investigated as electrodes for batteries and supercapacitors. Despite the excellent properties of coal-derived carbon fibers (CCNF) for energy storage devices, there still lacks systematic understanding on how various process parameters affect final electrode performances, which poses challenges to scale from pilot to high volume manufacturing. The goals of this project are twofold. First, we focuse on process optimization for converting a new precursor from powder river basin (PRB) coal, referred to as coal-based polyurethane (CPU) to CCNF using electrospinning. Second, different machine learning techniques will be examined using experimental data from this work and open literature. Specifically, for CPU the following process parameters need to be characterized and optimized in order to produce CCNFs with desirable mechanical integrity and physiochemical properties: precursor composition and viscosity, operating voltage and distance, oxidation and carbonization temperature and duration. Consequently, physiochemical properties of the fibers were characterized to correlate these process parameters with desirable electrochemical performance. Given the complex nature of the fiber production process, ML models are assessed for their ability to capture the nonlinear relationship between process parameters and the electrochemical properties in applications including supercapacitors. As such, we applied various machine learning techniques, to determine which technique produces a model that best predicts device function.

Cincotta, Robert E.F.↗