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DOE OSTI2024

Estimating scalar turbulent fluxes with slow-response sensors in the stable atmospheric boundary layer

Conventional and recently developed approaches for estimating turbulent scalar fluxes under stable atmospheric conditions are evaluated, with a focus on gases for which fast sensors are not readily available. First, the relaxed eddy accumulation (REA) classical approach and a recently proposed mixing length parameterization, labeled A22, are tested against eddy-covariance computations. Using high-frequency measurements collected from two contrasting sites (the frozen tundra near Utqiaġvik, Alaska, and a sparsely vegetated grassland in Wendell, Idaho, during winter), it is shown that the REA and A22 models outperform the conventional Monin–Obukhov similarity theory (MOST) utilized widely to infer fluxes from mean gradients. Second, scenarios where slow trace gas sensors are the only viable option in field measurements are investigated using digital filtering applied to fast-response sensors to simulate their slow-response counterparts. With a filtered scalar signal, the observed filtered eddy-covariance fluxes are referred to here as large-eddy-covariance (LEC) fluxes. A virtual eddy accumulation (VEA) approach, akin to the REA model but not requiring a mechanical apparatus to separate the gas flows, is also formulated and tested. A22 outperforms VEA and LEC in predicting the observed unfiltered (total) eddy-covariance (EC) fluxes; however, VEA can still capture the LEC fluxes well. This finding motivates the introduction of a sensor response time correction into the VEA formulation to offset the effect of sensor filtering on the underestimated net averaged fluxes. The only needed parameter for this correction is the mean velocity at the instrument height, a surrogate of the advective timescale. The VEA approach is very suitable and simple to use with gas sensors of intermediate speed (∼ 0.5 to 1 Hz) and with conventional open- or closed-path setups.

58 GEOSCIENCES↗

DOE OSTI2021

Water vapor oxidation of SiC layer in surrogate TRISO fuel particles

Under accidental conditions for high temperature gas-cooled reactors (HTGR), the SiC layer in tri-structural-isotropic (TRISO) fuel particles can be exposed to water vapor. In this study, oxidation behaviors of surrogate TRISO fuel particles were investigated in a He-20 vol% water vapor mixed atmosphere at temperatures up to 1600 °C. The growth of the crystalline oxide passivation layer with cracks and pores followed a parabolic law with time, where the maximum was 2.3 μm at 1600 °C. The oxide layer and the SiC surface under the oxide became flattened with increasing temperature, as a function of the silica viscosity and the diffusion path of water vapor. Volatilization of the oxide layer was analyzed using a mechanistic model that an inert gas in oxidizing atmospheres could influence the magnitude of volatilization. The fracture load and strength of the oxidized and thinned SiC layer were numerically estimated to decrease from 2.27 to 1.69 N and from 317 to 299 MPa, respectively, with the SiC thickness decrease from 35 to 32 μm. This prediction indicates that the oxidized SiC layer should retain fission products. Additionally, the mechanical integrity of each layer in the TRISO fuel particle after oxidation was evaluated. The results in this work provide important data for the safety analysis of accidental scenarios in HTGRs.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Advanced Light-Duty Spark Ignition Engine Research: Co-Optimization of Fuels and Engines and Partnership to Advance Combustion Engines (FY2020 Annual Progress Report)

This report covers recent progress on research tasks that support both the Co-Optimization of Fuels and Engines (Co-Optima) initiative and the Partnership to Advance Combustion Engines (PACE) consortium. The Co-Optima tasks further the science-base needed by industry stakeholders to co-evolve the next generation of highly efficient direct injection spark ignition (DISI) engines and new gasoline-type fuels. The research emphasis is on fuel effects on multimode spark ignition (SI) engine operation, which uses traditional non-dilute stoichiometric operation for peak load and power but reverts to lean operation at lower loads to provide higher fuel economy. This work focuses on determining desirable fuel specifications in terms of well-established metrics like research octane number (RON) and motor octane number, but it also involves the assessment of new fuel metrics, including fuel sooting propensity and phi-sensitivity. The PACE task supports the development of predictive computational fluid dynamics (CFD) modeling, which promises to unlock new strategies for high-efficiency combustion while minimizing tailpipe emissions. Here, the primary fuel is a regular E10 gasoline (i.e., a regular gasoline blend containing 10% ethanol), and focus is on fuel-spray dynamics and soot emissions. Soot-formation pathways are studied to determine how the pathways change with injection strategies and the thermal state of the engine (i.e., cold-starting vs. fully warmed-up operation). This PACE task also contributed to the development of an optimal E10 gasoline surrogate fuel, as reported in detail elsewhere

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Quantification of Lanthanides in a Molten Salt Reactor Surrogate Off-Gas Stream Using Laser-Induced Breakdown Spectroscopy

To enable the deployment of molten salt reactor technology, the development of off-gas treatment systems and advanced monitoring tools capable of operating with high temperatures and radiation fields while delivering near real-time information is necessary. Here, we aim to fulfill this requirement and proposes laser-induced breakdown spectroscopy (LIBS) for monitoring molten salt aerosol streams. A sheath gas measuring method was developed to protect optical elements from aerosol particles and to ensure a relatively constant aerosol stream for measurement. An aqueous system was studied to demonstrate the utility of LIBS for monitoring possible fission products in an aerosol stream: Gd, Nd, and Sm up to 2000 parts per million (ppm). A calibration model was built using partial least squares (PLS) regression with five, six, and nine latent variables for Gd, Nd, and Sm, respectively. This calibration model successfully estimated the concentrations of three test samples, which were validated with inductively charged plasma optical emission spectroscopy measurements at a 99.9% confidence interval. To enhance these models, a genetic algorithm was used to filter the spectra before entering the PLS model, thereby limiting the spectral features being regressed to those with greater correlations to concentration. This allowed for the number of latent variables used in the PLS models to be reduced to four, three, and three for Gd, Nd, and Sm, respectively. Finally, the genetic algorithm-filtered PLS models were used to predict the concentrations of the aerosol stream on a real-time dataset and resulted in a 73%, 18%, and 25% improvement in root mean squared error of prediction compared to the original PLS models developed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Sorption of Anionic Iodine and Molybdenum to Multi-sorbing Barrier (MSB) Materials - 20030

A multi-sorbing barrier (MSB) material containing sodium bentonite (NaB), organoclay, and anion resin is being evaluated for containment of anionic radionuclides. Batch tests on the MSB were conducted using two non-radioactive analog isotopes ({sup 127}I, {sup 95}Mo) as surrogates for {sup 129}I and {sup 99}Tc due to their similar valence and molecular weight relative to the radionuclides. Tests were conducted on the organoclay, anion resin, and NaB individually and on NaB-resin blends with resin contents of 1% and 5% by mass. The anion resin exhibits very strong sorption of {sup 127}I and {sup 95}Mo relative to the other materials. The organoclay exhibited modest sorption of {sup 95}Mo and {sup 127}I, and NaB little sorption. The sorption isotherms follow a linear model for NaB, a Freundlich model for the organoclay, and a Langmuir model for the anion resin and NaB-resin mixtures. Combining resin with NaB significantly enhances sorption relative to NaB alone, with a larger resin fraction yielding greater sorption. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

A novel approach to characterize the full spectrum and radiative properties of aerosols

Organic aerosols play a significant role in the absorption and radiative budget of the atmosphere, but current modeling approaches do not adequately capture the photo-chemical and oxidative bleaching that occurs during their lifetimes. Most climate models inaccurately assume constant optical properties of these particles, therefore leading to errors in their predictions. In this study we present an approach to better parameterize the optical properties of atmospheric aerosols, including brown carbon (BrC). Using thin-film spectrometry, the full spectrum of reflectivity and emissivity was used to calculate the complex refractive index for multiple species of organic aerosols. This is in contrast to previous techniques which only probe single wavelengths. Since BrC is a complex molecular mixture, we initially focused on single species absorption using four molecular surrogates. Dye-doped polyacrylic-acid thin-films were prepared on glass slides and compared to an aerosolized collection method. Verification of the collection method will open the door to characterizing the complex refractive index of smoke and ambient aerosol.

58 GEOSCIENCES↗

DOE OSTI2022

Snowmass2021 Computational Frontier White Paper: Cosmological Simulations and Modeling

Powerful new observational facilities will come online over the next decade, enabling a number of discovery opportunities in the "Cosmic Frontier", which targets understanding of the physics of the early universe, dark matter and dark energy, and cosmological probes of fundamental physics, such as neutrino masses and modifications of Einstein gravity. Synergies between different experiments will be leveraged to present new classes of cosmic probes as well as to minimize systematic biases present in individual surveys. Success of this observational program requires actively pairing it with a well-matched state-of-the-art simulation and modeling effort. Next-generation cosmological modeling will increasingly focus on physically rich simulations able to model outputs of sky surveys spanning multiple wavebands. These simulations will have unprecedented resolution, volume coverage, and must deliver guaranteed high-fidelity results for individual surveys as well as for the cross-correlations across different surveys. The needed advances are as follows: (1) Development of scientifically rich and broadly-scoped simulations, which capture the relevant physics and correlations between probes (2) Accurate translation of simulation results into realistic image or spectral data to be directly compared with observations (3) Improved emulators and/or data-driven methods serving as surrogates for expensive simulations, constructed from a finite set of full-physics simulations (4) Detailed and transparent verification and validation programs for both simulations and analysis tools. (Abridged)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Experimental evaluation of respiratory droplet spread to rooms connected by a central ventilation system

This article presents results from an experimental study to ascertain the transmissibility of the SARS-CoV-2 virus between rooms in a building that are connected by a central ventilation system. Respiratory droplet surrogates made of mucus and virus mimics were released in one room in a test building and measurements of concentration levels were made in other rooms connected via the ventilation system. The paper presents experimental results for different ventilation system configurations, including ventilation rate, filtration level (up to MERV-13), and fractional outdoor air intake. The most important finding is that respiratory droplets can and do transit through central ventilation systems, suggesting a mechanism for viral transmission (and COVID-19 specifically) within the built environment in reasonable agreement with well-mixed models. We also find the deposition of these droplets on room walls to be negligibly small. Furthermore, the energy use impact of the different configuration settings is also quantified to help inform intelligent building operation that can simultaneously address energy use and occupant health.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Bridging microscale to macroscale mechanical property measurements of FeCrAl alloys by crystal plasticity modeling

FeCrAl alloys are candidates for accident tolerant fuel cladding of light water reactors. In this work, a microstructure- and temperature-dependent crystal plasticity model is employed to bridge microscale to macroscale mechanical property measurements of FeCrAl alloys. With the visco-plastic self-consistent (VPSC) polycrystal plasticity framework, a mechanism-based single crystal plasticity (MSCP) model adopts the Arrhenius type rate equation to describe the dependence of the critical resolved shear stress for dislocation slips on their temperature-dependent intrinsic frictional resistance and the microstructure-dependent irradiation hardening. The intrinsic frictional resistance associated with {110}<111> and {112}<111> slip systems were measured by in-situ micromechanical testing on unirradiated/irradiated samples at 25-500 °C. The irradiation hardening is estimated by the Bacon-Kocks-Scattergood (BKS) model with density and size of radiation-induced defects measured from microstructural characterization. Several features associated with thermo-mechanical behavior of unirradiated/irradiated polycrystalline FeCrAl alloys are captured. High density of deformation-induced dislocations and radiation-induced defects results in obvious hardening at room temperature, which is weakened at high temperature, and facilitates damage evolution during deformation. Moreover, both high temperature and radiation-induced defects, which facilitate dislocation multiplication, trigger large hardening rate. Finally, the proposed method together with application of accelerator-based ion irradiation technique is a surrogate approach to simulate neutron damage, improving the efficiency associated with evaluation of mechanical properties of FeCrAl alloys exposed to temperature, stress and radiation conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Evaluation of lithium as a tritium storage medium for betavoltaics

Lithium foils were demonstrated to absorb surrogate protium for tritium-powered betavoltaics. 20μm thick lithium foils were hole-punched from a ribbon of electrodeposited lithium on copper foil. The lithium foils were loaded with hydrogen in a custom Sievert apparatus where the pressure drop showed full hydriding at a hydrogen pressure of 2 bar and at all loading temperatures above the lithium melting point at 190, 200, 225, 250, and 300. Lithium hydride formation was confirmed with Raman spectroscopy after hydrogen loading. The kinetics of experimental hydride formation was compared to the diffusion-limited Mintz–Bloch model. While the Mintz–Bloch model showed good fit with the experimental loadings, the model overpredicted the loading kinetics starting at 250 °C and at higher temperatures. In conclusion, The overprediction was either caused by lithium hydride outgassing due to some reduction with some residual lithium hydroxide created from brief air exposure when sealing the lithium in the reactor or a transition from diffusion-limited hydride growth to surface or metal–hydride interface-limited hydride growth.

25 ENERGY STORAGE↗

DOE OSTI2021

Enabling Particulate Materials Processing Science for High-Consequence, Small-Lot Precision Manufacturing

This Laboratory Directed Research and Development project developed and applied closely coupled experimental and computational tools to investigate powder compaction across multiple length scales. The primary motivation for this work is to provide connections between powder feedstock characteristics, processing conditions, and powder pellet properties in the context of powder-based energetic components manufacturing. We have focused our efforts on multicrystalline cellulose, a molecular crystalline surrogate material that is mechanically similar to several energetic materials of interest, but provides several advantages for fundamental investigations. We report extensive experimental characterization ranging in length scale from nanometers to macroscopic, bulk behavior. Experiments included nanoindentation of well-controlled, micron-scale pillar geometries milled into the surface of individual particles, single-particle crushing experiments, in-situ optical and computed tomography imaging of the compaction of multiple particles in different geometries, and bulk powder compaction. In order to capture the large plastic deformation and fracture of particles in computational models, we have advanced two distinct meshfree Lagrangian simulation techniques: 1.) bonded particle methods, which extend existing discrete element method capabilities in the Sandia-developed , open-source LAMMPS code to capture particle deformation and fracture and 2.) extensions of peridynamics for application to mesoscale powder compaction, including a novel material model that includes plasticity and creep. We have demonstrated both methods for simulations of single-particle crushing as well as mesoscale multi-particle compaction, with favorable comparisons to experimental data. We have used small-scale, mechanical characterization data to inform material models, and in-situ imaging of mesoscale particle structures to provide initial conditions for simulations. Both mesostructure porosity characteristics and overall stress-strain behavior were found to be in good agreement between simulations and experiments. We have thus demonstrated a novel multi-scale, closely coupled experimental and computational approach to the study of powder compaction. This enables a wide range of possible investigations into feedstock-process-structure relationships in powder-based materials, with immediate applications in energetic component manufacturing, as well as other particle-based components and processes.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Elucidation of the Reaction Mechanisms of Autooxidative Processes in Complex Condensed-Phase Mixtures

In this report, we discuss the oxidative processes of gasoline surrogate fuels comprised of a neat olefin, such as 1-hexene. Oxidative reactions are thought to involve the peroxyl radical and peroxide chemistry with initial hydrogen abstraction by O 2 , followed by addition of O 2 or HOO· to the hydrocarbon to form unstable peroxy radicals and peroxides that result in a chain reaction. In the condensed phase environment (liquid), we also consider polymeric-forming chain reactions, such as hydrocarbon radical-radical carbon chain growth. We present our experimental results showing the reaction products resulting from 1-hexene oxidation, along with chemical kinetic modeling of the system showing product ratios as a function of time. Applicability of our observations to oxidation-promoted fouling in hydrocarbon fuels (i.e., formation of gum) and radical-promoted polymerizations will also be discussed.

10 SYNTHETIC FUELS↗

DOE OSTI2021

Oxide evolution on the SiC layer of TRISO particles during extended air oxidation

Tristructural isotropic (TRISO) fuel particles have been primarily developed for high-temperature gas-cooled nuclear reactors and can be subjected to oxidizing environments for extended periods in an off-normal accident scenario. Surrogate TRISO fuel particles were oxidized in air at 1,000 or 1,100 °C for up to 120 h. Here, the oxide scale morphology and thickness were studied via scanning electron microscopy, focused ion beam, and atomic force microscopy. TRISO particles oxidized at 1,100 °C exhibited a highly crystalline oxide scale, which led to significant cracking and irregularly shaped closed porosity, whereas those oxidized at 1,000 °C possessed a primarily amorphous oxide scale, which contained small, rounded internal pores and no larger defects. The observed phenomena deviated from the expected behavior based on models for oxide growth on flat-plate and fiber SiC. The oxidation kinetics of TRISO fuel particles in high-temperature air were investigated without mechanically deforming the surface and were analyzed with respect to oxide morphology.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Considerations for Defining G-Values for Aluminum-Clad Spent Nuclear Fuel

Sealed-canister dry storage of aluminum-clad spent nuclear fuel (ASNF) generated by research reactors is an alternative to current storage and disposition pathways as directed by the U.S. Department of Energy. The major challenge faced for this storage approach is radiolytic H 2 generation, including from the aluminum (oxy)hydroxide layers on the surface of ASNF. Experimental and modeling activities have been carried out to characterize the radiolytic yield as part of a DOE-sponsored research program to develop the technical basis for ASNF dry storage. The G-value is a commonly way to report results of radiolysis testing and is defined as the radiolytic yield of a species (e.g. molecular hydrogen) per unit radiation energy deposited into the material system. An independent technical review of the ASNF dry storage technical basis performed by Pacific Northwest National Laboratory raised questions about differences in G-value definitions used for experiments on ASNF surrogates consisting of aluminum samples with adherent (oxy)hydroxides compared to G-values reported in prior literature and how the magnitudes compared between different studies. Material systems resembling ASNF pose complications for measuring/defining G-values to predict the evolution of H 2 in a sealed canister, including i) accounting for radiolytic yields potentially arising from multiple sources, i.e., residual free (vapor), physisorbed, and chemisorbed/chemically bound waters; ii) deciding what portions of the multi-material system to include in the absorbed energy (radiation dose) calculation, considering possible energy exchange between materials as well as measurement limitations, and iii) capturing variations in G-value associated with non-linear yield vs. dose curves and/or dependence on the cover gas. This report summarizes previous literature information on radiolytic H 2 generation and associated G-values from mixed-material systems (generally oxides in contact with water or organic compounds) and from (oxy)hydroxides/hydrates to compare with the definitions and values for ASNF surrogate samples containing adherent aluminum (oxy)hydroxides.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Bayesian inference of fiber orientation and polymer properties in short fiber-reinforced polymer composites

Herein we present a Bayesian methodology to infer the elastic modulus of the constituent polymer and the fiber orientation state in a short-fiber reinforced polymer composite (SFRP). The properties are inversely determined using only a few experimental tests. Developing composite manufacturing digital twins for SFRP composite processes, including injection molding and extrusion deposition additive manufacturing (EDAM) requires extensive experimental material characterization. In particular, characterizing the composite mechanical properties is time consuming and therefore, micromechanics models are used to fully identify the elasticity tensor. Hence, the objective of this paper is to infer the fiber orientation and the effective polymer modulus and therefore, identify the elasticity tensor of the composite with minimal experimental tests. To that end, we develop a hierarchical Bayesian model coupled with a micromechanics model to infer the fiber orientation and the polymer elastic modulus simultaneously which we then use to estimate the composite elasticity tensor. We motivate and demonstrate the methodology for the EDAM process but the development is such that it is applicable to other SFRP composites processed via other methods. Our results demonstrate that the approach provides a reliable framework for the inference, with as few as three tensile tests, while accounting for epistemic and aleatory uncertainty. Posterior predictive checks show that the model is able to recreate the experimental data well. The ability of the Bayesian approach to calibrate the material properties and its associated uncertainties, make it a promising tool for enabling a probabilistic predictive framework for composites manufacturing digital twins.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Identifying Entangled Physics Relationships Through Sparse Matrix Decomposition to Inform Plasma Fusion Design

We report a sustainable burn platform through inertial confinement fusion (ICF) has been an ongoing challenge for over 50 years. Mitigating engineering limitations and improving the current design involves an understanding of the complex coupling of physical processes. While sophisticated simulation codes are used to model ICF implosions, these tools contain necessary numerical approximation but miss physical processes that limit predictive capability. Identification of relationships between controllable design inputs to ICF experiments and measurable outcomes (e.g., neutron yield, neutron velocity, areal density) from performed experiments can help guide the future design of experiments and development of simulation codes, to potentially improve the accuracy of the computational models used to simulate ICF experiments. We use sparse matrix decomposition methods to identify clusters of a few related design variables. Sparse principal component analysis (SPCA) identifies groupings that are related to the physical origin of the variables (laser, hohlraum, and capsule). A variable importance analysis finds that in addition to variables highly correlated with neutron yield, such as picket power and laser energy, variables that represent a dramatic change of the ICF design, such as number of pulse steps, are also very important. The obtained sparse components are then used to train a random forest (RF) regression surrogate for predicting total yield. The RF performance on the training and testing data compares with the performance of the RF trained using all the design variables considered. This work is intended to inform design changes in future ICF experiments by augmenting the expert intuition and simulation results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Diagnosing hot-spot symmetry in surrogate ignition experiments via secondary DT-neutron spectroscopy at the NIF

The directional energy spectrum of neutrons generated from the in-flight fusion reaction of 1-MeV tritons contains information about the hot-spot symmetry. The National Ignition Facility (NIF) fields Symmetry Capsule (Symcap) implosions, which have historically measured the symmetry of the radiation, drive by measuring the hot-spot shape via x-ray self-emission. Symcaps are used to tune the hot-spot symmetry for ignition experiments at the NIF. This work shows the relationship between directional secondary DT-n spectra and x-ray imaging data for a large database of Symcap implosions. A correlation is observed between the relative widths of the DT-n spectra measured with nTOFs and the shape measured with x-ray imaging. A Monte Carlo model, which computes the directional secondary DT-n spectrum, is used to interpret the results. A comparison of the x-ray and secondary DT-n data with the Monte Carlo model indicates that 56% of the variance between the two datasets is explained by a P2 asymmetry. More advanced simulations using HYDRA suggest that the unaccounted variance is due to P1 and P4 asymmetries present in the hot spot. The comparison of secondary DT-n data and x-ray imaging data to the modeling shows the DT-n data contain important information that supplements current P2 measurements and contain new information about the P1 asymmetry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics

AI-based foundation models like FourCastNet, GraphCast are revolutionizing weather and climate predictions but are not yet ready for operational use. Their limitation lies in the absence of a data assimilation system to incorporate real-time Earth system observations, crucial for accurately forecasting events like tropical cyclones. To overcome these obstacles, we introduce a generic real-time data assimilation framework and demonstrate its end-to-end performance on the Frontier supercomputer. This framework comprises two primary modules: an ensemble score filter (EnSF), which significantly outperforms the state-of-the-art data assimilation method, and a vision transformer-based surrogate capable of real-time adaptation through the integration of observational data. We demonstrate both the strong and weak scaling of our framework up to 1024 GPUs on the Exascale supercomputer, Frontier. Our results not only illustrate the framework's exceptional scalability on high-performance computing systems, but also demonstrate the importance of supercomputers in real-time data assimilation for weather and climate predictions.

Lu, Dan↗