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DOE OSTI2023

Ocean Mesoscale and Frontal-Scale Ocean–Atmosphere Interactions and Influence on Large-Scale Climate: A Review

Two decades of high-resolution satellite observations and climate modeling studies have indicated strong ocean–atmosphere coupled feedback mediated by ocean mesoscale processes, including semipermanent and meandrous SST fronts, mesoscale eddies, and filaments. The air–sea exchanges in latent heat, sensible heat, momentum, and carbon dioxide associated with this so-called mesoscale air–sea interaction are robust near the major western boundary currents, Southern Ocean fronts, and equatorial and coastal upwelling zones, but they are also ubiquitous over the global oceans wherever ocean mesoscale processes are active. Current theories, informed by rapidly advancing observational and modeling capabilities, have established the importance of mesoscale and frontal-scale air–sea interaction processes for understanding large-scale ocean circulation, biogeochemistry, and weather and climate variability. However, numerous challenges remain to accurately diagnose, observe, and simulate mesoscale air–sea interaction to quantify its impacts on large-scale processes. This article provides a comprehensive review of key aspects pertinent to mesoscale air–sea interaction, synthesizes current understanding with remaining gaps and uncertainties, and provides recommendations on theoretical, observational, and modeling strategies for future air–sea interaction research.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Sea Ice and Cloud Processes Mediating Compensation between Atmospheric and Oceanic Meridional Heat Transports across the CMIP6 Preindustrial Control Experiment

Abstract Bjerknes compensation (BJC) refers to the anticorrelation observed between atmospheric and oceanic heat transport (AHT/OHT) variability, particularly on decadal to longer time scales that may be important to the predictability of the climate system. This study investigates the spread in BJC across fully coupled simulations of phase 6 of the Coupled Model Intercomparison Project (CMIP6) and critical processes (particularly related to sea ice and clouds) that may contribute to that spread. BJC on decadal to longer time scales is confirmed across all the simulations evaluated, and it is strongest in the Northern Hemisphere (NH) between 60° and 70°N. At these latitudes, BJC appears to be primarily driven by the exchange of turbulent fluxes (sensible and latent) in the Greenland, Iceland, and Barents Seas. Metrics to break down how sea ice and clouds uniquely modify the radiative balance of the polar atmosphere during anomalous OHT events are presented. These metrics quantify the impacts of sea ice and clouds on surface and top of atmosphere (latent, sensible, longwave, and shortwave radiative) energy fluxes. Cloud responses tend to counter the clear sky impacts over the Marginal Ice Zone (MIZ). It is further shown that the degree of BJC present in a simulation at high latitudes is heavily influenced by the sensitivity of the sea ice to OHT, which is most influential over the MIZ. These results are qualitatively robust across models and explain the intermodel spread in NH BJC in the preindustrial control experiment.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Machine learning in analytical spectroscopy for nuclear diagnostics [Invited]

Analytical spectroscopy methods have shown many possible uses for nuclear material diagnostics and measurements in recent studies. In particular, the application potential for various atomic spectroscopy techniques is uniquely diverse and generates interest across a wide range of nuclear science areas. Over the last decade, techniques such as laser-induced breakdown spectroscopy, Raman spectroscopy, and x-ray fluorescence spectroscopy have yielded considerable improvements in the diagnostic analysis of nuclear materials, especially with machine learning implementations. These techniques have been applied for analytical solutions to problems concerning nuclear forensics, nuclear fuel manufacturing, nuclear fuel quality control, and general diagnostic analysis of nuclear materials. The data yielded from atomic spectroscopy methods provide innovative solutions to problems surrounding the characterization of nuclear materials, particularly for compounds with complex chemistry. Implementing these optical spectroscopy techniques can provide comprehensive new insights into the chemical analysis of nuclear materials. In particular, recent advances coupling machine learning methods to the processing of atomic emission spectra have yielded novel, robust solutions for nuclear material characterization. This review paper will provide a summation of several of these recent advances and will discuss key experimental studies that have advanced the use of analytical atomic spectroscopy techniques as active tools for nuclear diagnostic measurements.

Rao, Ashwin P. (ORCID:0000000319312568)↗

DOE OSTI2021

Bandwidth extension and conversion efficiency improvements beyond phase matching limitations using cavity-enhanced OPCPA

The conversion efficiency and phase matching bandwidth of ultrafast optical parametric amplification (OPA) are constrained by the dispersion and nonlinear coefficient of the employed crystal as well as pulse shaping effects. In our work we show that an enhancement cavity resonant with the pump seeded at the full repetition rate of the pump laser can automatically reshape the small-signal gain in optical parametric chirped-pulse amplification (OPCPA) to achieve close-to-optimal operation. This new method termed cavity-enhanced OPCPA or C-OPCPA significantly increases both the gain bandwidth and the conversion efficiency, in addition to boosting gain for high-repetition-rate amplification. The goal in C-OPCPA is to arrive at a condition of impedance matching at all temporal coordinates, such that, in the absence of linear losses, all the incident pump power is dissipated in the nonlinear loss element, i.e., converted to signal and idler. The use of a low finesse enhancement cavity resonant with a low average power (<1W) and a high repetition rate (78MHz) pump source is shown to achieve more than 50% conversion efficiency into signal and idler from the coupled pump in an optical parametric process, whereas an equivalent amount of pump power in a single-pass configuration leads to negligible conversion. Additionally, the gain bandwidth is extended by a factor of 3-4 beyond the phase-matching limit. Our empirical observations are corroborated by a numerical analysis of depletion optimizing the single-pass case, which assesses the underlying impedance matching that is responsible for the observed performance improvements.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Direct Measurements with Neutron Sources [Slides]

The majority of heavy elements are produced through neutron capture. This presentation discusses progress in measurements for the Weak s-Process, how measurements are done, and future capabilities for direct measurement at LANSCE. Conclusion: Major advances have been made in improving neutron capture rates for the weak s process in the last 15 years. Coupling these measurements to stellar simulations is key to understanding where the next opportunities lie. New capabilities for performing measurements, particularly on unstable isotopes are being developed around the world

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

CO 2 to Bioplastics: Beneficial Re-use of Carbon Emissions from Coal-fired Power Plants using Microalgae

This project sought to address the technical and economic barriers to carbon dioxide (CO 2 ) capture and utilization using microalgae. Specifically, a dual photobioreactor (PBR)/open raceway pond (ORP) cultivation system was evaluated with respect to capital and operational costs, productivity, and culture health, and compared to an ORP-only cultivation system. In the dual (or “hybrid”) system, a cyclic flow PBR was used to provide inoculum for two open raceway ponds after each harvest, with the hypothesis that this PBR + pond system should result in improved performance compared to traditional raceway ponds. Two other raceway ponds were operated conventionally as a control, the experiments being performed at Duke Energy’s East Bend Station in northern KY using coal-derived flue gas as the CO 2 source. Although algae productivity achieved was mediocre due to the fact that the experiments had to be performed late in the growing season when climatic conditions were not optimal for high growth, the hybrid cultivation system showed a higher level of algae productivity (statistically significant) compared to the traditional ponds. In order to realize the maximum value of the algal biomass produced, fractionation of the biomass was examined. Bioplastic compounding and material characterization was subsequently performed using three feed stocks: whole biomass, lipid-extracted biomass and the proteinaceous residue from full fractionation. In general, the whole and lipid-extracted biomass gave similar results in terms of the properties of the resulting bioplastics, while the proteinaceous residue showed promise for the production of a polybutylene adipate terephthalate (PBAT) blend. Finally, sustainability assessment of a putative biorefinery system was conducted, including techno-economic and life cycle impact assessment. Nine different production scenarios were considered, comprising combinations of the three different biomass growth architectures (ORP, PBR and dual PBR-ORP systems) coupled with three different algae biomass processing pathways (drying only, lipid extraction and fractionation). Results show that the minimum selling price of the bioplastic feed stock (BPFS) is within the realm of economic competition with prices as low as $970 USD tonne -1 . Additionally, life cycle impact assessment results indicate drastic improvements in performance of the produced BPFS, with reductions in greenhouse gas emissions ranging between 67 and 116% compared to a petroleum based plastic feedstock.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

GoldSim E-Area Low-Level Waste Facility Aquifer Zone Model Calibration Methodology

This report documents the development and calibration of the E-Area Low-Level Waste Facility (ELLWF) Gold Sim aquifer model. It provides a methodology on how a Gold Sim aquifer model can be calibrated to specific PORFLOW-based aquifer predictions. The calibration activity presented within this report focuses on the Slit Trench #06 (ST06) location that resides within the center set of Slit Trenches. This Gold Sim-based aquifer model is a generic model capable of being calibrated to any of the other trench locations within E-Area. In addition, subsequent activities (beyond the scope of this effort) will couple this GoldSim-based aquifer model to various GoldSim-based trench models, with the intent of performing stochastic analyses that couple all pertinent fate and transport processes from the ground surface up to the 100-m point of assessment (POA).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

GoldSim E-Area Low-Level Waste Lacility Vadose Zone Model Benchmarking

This report documents the development and benchmarking of the E-Area Low-Level Waste Facility (ELLWF) GoldSim Engineered and Slit Trench (ET and ST) vadose zone models. Subsequent activities (beyond the scope of this effort) will couple the GoldSim-based vadose zone models to the GoldSim aquifer model, with the intent of performing stochastic analyses that couple all pertinent fate and transport processes from the ground surface up to the 100-m Point of Assessment (POA). The benchmarking presented within this report focuses on the Slit Trench 06 (ST06) bydrostratigraphic location that resides within the center set of slit trenches. These GoldSim-based vadose zone models are generic models capable of being benchmarked to any of the other trench locations within E-Area.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Demonstration of Integrated PostIrradiation Process Steps forMultikilogram Amounts of Low- and High-Burnup Used Nuclear Fuels

sponsored research and development (R&D) on the advanced, closed nuclear fuel cycle, including post-irradiation processing of used fuels, recovery of separated components, and preparation of recycle nuclear fuels. During the period 2007–2010, kilogram-scale demonstrations of the integrated processing steps were performed for actual light water reactor (LWR) used nuclear fuels (UNF). These integrated processing demonstrations were called “the Coupled-End-to-End” (CETE) campaigns and were associated with the Global Nuclear Energy Partnership program, which ran concurrently. The demonstrations were carried out in the shielded hot cells and associated gloveboxes located in the Irradiated Fuels Examination Laboratory (IFEL) and the Radiochemical Engineering Development Center (REDC) at the Oak Ridge National Laboratory (ORNL). Limited circulation program reports and a few technical papers were issued. The subject document provides a comprehensive summary of results, technical comparisons, and conclusions obtained from the demonstration campaigns and subsequent associated R&D.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Assimilating Scanning Radar Data into High-Resolution Models

This report documents the findings of a project aiming to improve the initial conditions of km-scale simulations of deep convective storms by assimilating cloud-scale weather radar observations. More accurate numerical analyses will increase the effectiveness of research efforts using LES cloud models as tool to better understand land-atmosphere coupling, boundary layer turbulence, and cloud processes, each used for model parameterization development. Work reported on herein includes: i) assessment of radar data sets for use in data assimilation (‘DA’) experiments, ii) quality control of the radar data set and format conversion to one acceptable to DA schemes utilized by the Weather Research and Forecasting (WRF) model, and iii) examination of the sensitivity of the numerical representation of cloud-scale wind and microphysical features to a variety of tunable DA parameters.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Assimilating Scanning Radar Data into Cloud-Scale Models

The aim of this project is to improve the initial conditions of large eddy simulations (LES) of deep convective storms by assimilating scanning radar reflectivity and radial velocity data as well as local environmental observations. Accomplishing this goal often results in more accurate numerical forecasts of clouds and precipitation than if the background initial meteorological conditions are solely relied upon for convection initiation and intensification, as is typical of most operational and research models. Conducted in a storm-scale LES framework, these more accurate numerical analyses can serve as tool to better understand and parameterize land-atmosphere coupling, boundary layer turbulence, and cloud processes, each used for model parameterization development of convection. Our work examined the sensitivity of the numerical representation of cloud-scale wind and microphysical structures to: i) the assimilation of radiosonde observations characterizing the near-storm inflow, ii) the assimilation of radar data of varying resolution for model simulations with grid spacings of 1-km and 0.25-km, and iii) to the assimilation of three-dimensional plan-projection-indicator (PPI) and range-height indicator (RHI) radar volumes. Few studies have explored deep convective storm analyses and forecasts produced by assimilation of radar observations to cloud-scale LES. Furthermore, to our knowledge, no storm-scale DA study has explored the value of assimilating high-resolution sector RHI volumes to determine if they can improve the retrieval of the vertical kinematic and microphysical storm structure aloft over the use of traditionally utilized PPI scans.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Modular Subsurface Sensors and Integrated Software for Advanced Subsurface Characterization and Monitoring using Unoccupied Vehicles

The advent and subsequent proliferation of autonomous airborne, waterborne, and groundbased vehicles (i.e., “drones”) promises to broadly transform the geosciences and associated industries, including fossil energy exploration and development, mineral resource exploration and development, water-resource management, and environmental remediation. For geophysical characterization and monitoring, the prospect of programming highly repeatable and low-cost drone missions for subsurface imaging will allow for deployments in hazardous and previously inaccessible areas. Coupled with autonomous workflows for data processing, management, and visualization, drone-based geophysical characterization and monitoring will enable unprecedented, real-time insight into diverse subsurface properties and processes of scientific and engineering importance. Toward this end, the objectives of this Lab Directed Research and Development (LDRD) project were to develop new (1) instrumentation for dronebased electromagnetic induction (EMI) geophysical imaging, including separated transmitter and receivers and associated electronics, (2) software for real-time data telemetry, processing, management, and visualization. Although EMI has been previously deployed using unoccupied aerial systems (UASs), these applications failed to capitalize on the game-changing capabilities of drone platforms. Whereas drone-based data acquisition allows for collection of rich, three-dimensional (3D) multi-offset/multi-angle configurations between transmitters and receivers, past efforts have relied on conventional instrumentation that was designed for ground-based data collection with the transmitter and a single receiver housed in the same unit; nor did these previous applications demonstrate real-time delivery of results to support rapid management decisions in the field. In this 1-year project, we (1) designed and constructed new lightweight independent transmitter and receiver antenna platforms that communicate with a laptop computer; (2) developed software to control data acquisition, manage/transfer data, and visualize data as its collected; and (3) demonstrated the operation of the new hardware and software systems in a ground-based field test. Our work entails major technological advances for EMI and established a foundation on which to build a new drone-based, real-time geophysical EMI imaging capability to support diverse challenges facing the nation.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Plasma Assisted Catalytic Conversion of Carbon Dioxide (CO2) and Propane to Propylene and Carbon Monoxide (CO)

Presented at the NETL Project Review Meetings in 2022, the presentation summary includes the following status updates: -Feasibility of the CO2-ODH reaction with plasma demonstrated at much lower temperatures than conventional processes -Presence of CO2 enhances propane conversion in the plasma reactor -Ce doped, 5 wt.%/CexZr1-xO2 catalyst demonstrated enhanced selectivity and stability for propylene production via CO2-ODH process under thermal conditions -Comprehensive characterization coupled with designed catalytic experiments identified Cr3+ as the active site CO2-ODH proceeds via dehydrogenation route -Coke formation, which causes catalyst deactivation, inhibited by both Ce and CO2

Zhou, S. James↗

DOE OSTI2025

Towards a Robust Adaptive Digital Twin for Fusion Applications

The development of a digital twin system for fusion applications is essential for enhancing the prediction, analysis, and optimization of complex plasma processes. Machine learning (ML), particularly deep learning has demonstrated strong capabilities in modeling such highly nonlinear and intricate systems. However, two critical challenges limit the deployment of deep learning-based digital twins: Uncertainty Quantification (UQ) and data drift. UQ is vital for ensuring trustworthy predictions, especially in decision-support scenarios. Additionally, data-driven models are often sensitive to changes in the underlying data distribution, such as shot-to-shot variations in fusion experiments, which can lead to performance degradation over time. To address these challenges, we are developing an uncertainty-aware, adaptive digital twin framework. Our approach incorporates deep learning models enhanced with Gaussian Process approximations for predictive uncertainty estimation, coupled with an online learning mechanism that enables continuous model adaptation to new experimental data. This adaptive capability allows the data driven models to respond effectively to evolving plasma behaviors and equipment conditions. Specifically, to mitigate the effects of shot-to-shot drift, our system updates itself incrementally as new data becomes available, improving both robustness and fidelity. Our vision is to evolve this data driven model into a self-sustaining digital twin system that leverages UQ based feedback to continuously refine itself and potentially support real-time decision making. This presentation will cover a brief background on uncertainty quantification for ML, our ongoing effort on development of UQ capabilities for ML, our data science pipeline from data collection to model development and analysis and online learning framework for modeling coil deflection at DIII-D. I will also briefly touch upon opportunities and challenges in development of digital twin framework.

Sammuli, Brian [General Atomics]↗

DOE OSTI2021

Higrad/Firetec Wildfire Simulations

Wildfire behavior is a result of complex nonlinear interactions between a variety of physical processes and chemical reactions. Understanding the coupling between these components and the ways in which their interactions are influenced by their surrounding environment (e.g. winds, fuels, and topography) is a challenging undertaking. The IEEE SciVis 2022 Contest is focused on the visualization and analysis of simulations of wildfires.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Comparative Genomic Analysis of Three Pseudomonas Species Isolated from the Eastern Oyster (Crassostrea virginica) Tissues, Mantle Fluid, and the Overlying Estuarine Water Column

The eastern oysters serve as important keystone species in the United States, especially in the Gulf of Mexico estuarine waters, and at the same time, provide unparalleled economic, ecological, environmental, and cultural services. One ecosystem service that has garnered recent attention is the ability of oysters to sequester impurities and nutrients, such as nitrogen (N), from the estuarine water that feeds them, via their exceptional filtration mechanism coupled with microbially-mediated denitrification processes. It is the oyster-associated microbiomes that essentially provide these myriads of ecological functions, yet not much is known on these microbiota at the genomic scale, especially from warm temperate and tropical water habitats. Among the suite of bacterial genera that appear to interplay with the oyster host species, pseudomonads deserve further assessment because of their immense metabolic and ecological potential. To obtain a comprehensive understanding on this aspect, we previously reported on the isolation and preliminary genomic characterization of three Pseudomonas species isolated from minced oyster tissue (P. alcaligenes strain OT69); oyster mantle fluid (P. stutzeri strain MF28) and the water collected from top of the oyster reef (P. aeruginosa strain WC55), respectively. In this comparative genomic analysis study conducted on these three targeted pseudomonads, native to the eastern oyster and its surrounding environment, provided further insights into their unique functional traits, conserved gene pools between the selected pseudomonads, as well as genes that render unique characteristics in context to metabolic traits recruited during their evolutionary history via horizontal gene transfer events as well as phage-mediated incorporation of genes. Moreover, the strains also supported extensively developed resistomes, which suggests that environmental microorganisms native to relatively pristine environments, such as Apalachicola Bay, Florida, have also recruited an arsenal of antibiotic resistant gene determinants, thus posing an emerging public health concern.

Pathak, Ashish↗

DOE OSTI2020

Utilizing Temperature and Brine Inflow Measurements to Constrain Reservoir Parameters During a Salt Heater Test

Brine availability in salt has multiple implications for the safety and design of a nuclear waste storage facility. Brine availability includes both the distribution and transport of brine through a damaged zone around boreholes or drifts excavated into the salt. Coupled thermal, hydrological, mechanical, and chemical processes taking place within heated bedded salt are complex; as part of DECOVALEX 2023 Task E this study takes a parsimonious modeling approach utilizing analytical and numerical one-dimensional simulations to match field measurements of temperature and brine inflow around a heater. The one-dimensional modeling results presented arrive at best-fit thermal conductivity of intact salt, and the permeability and porosity of damaged salt of 5.74 W/m∙K, 10 –17 m 2 , and ≈ 0.02, respectively.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Localized basal area affects soil respiration temperature sensitivity in a coastal deciduous forest

Abstract. Soil respiration (Rs), the flow of CO2 from the soil surface to the atmosphere, is one of the largest carbon fluxes in the terrestrial biosphere. The spatial variability of Rs is both large and poorly understood, limiting our ability to robustly scale it in space. One factor in Rs spatial variability is the autotrophic contribution from plant roots, but it is uncertain how the presence of plants affects the magnitude and temperature sensitivity of Rs. This study used 1 year of Rs measurements to examine the effect of localized basal area on Rs in the growing and dormant seasons, as well as during moisture-limited times, in a temperate, coastal, deciduous forest in eastern Maryland, USA. In a linear mixed-effects model, tree basal area within a 5 m radius (BA5) exerted a significant positive effect on the temperature sensitivity of soil respiration. Soil moisture was the dominant control on Rs during the dry portions of the year, while soil moisture, temperature, and BA5 all exerted significant effects on Rs in wetter periods. Our results suggest that autotrophic respiration is more sensitive to temperature than heterotrophic respiration at these sites, although we did not measure these source fluxes directly, and that soil respiration is highly moisture sensitive, even in a record-rainfall year. The Rs flux magnitudes (0.46–15.0 µmol m-2 s-1) and variability (coefficient of variability 10 %–23 % across plots) observed in this study were comparable to values observed in similar forests. Six Rs observations would be required in order to estimate the mean across all study sites to within 50 %, and 518 would be required in order to estimate it to within 5 %, with 95 % confidence. A better understanding of the spatial interactions between plants and microbes, as well as the strength and speed of above- and belowground coupling, is necessary to link these processes with large-scale soil-to-atmosphere C fluxes.

54 ENVIRONMENTAL SCIENCES↗