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DOE OSTI2020

DPSIR-ESA Vulnerability Assessment (DEVA) Framework: Synthesis, Foundational Overview, and Expert Case Studies

Land resources are central to understanding the relationship between humans and their environment. We broadly define a land resource to include all the ecological resources of climate, water, soil, landforms, flora, and fauna, and all the socioeconomic systems that interact with agriculture, forestry, and other land uses within some system boundary. Understanding the vulnerability of land resources to changes in land management or climate forcing is critical to developing sustainable land management strategies. Vulnerability assessments are complex given the multiple uses of the assessments, the multi-disciplinary nature of the problem, limited understanding, the dynamic structure of vulnerability, scale issues, and problems with identifying effective vulnerability indicators. Here, we propose a novel conceptual framework for vulnerability assessments of land resources that combines the driver– pressure–state–impact–response (DPSIR) framework adopted by the European Environment Agency to describe interactions between society and the environment, and the exposure-sensitivity-adaptive capacity (ESA) framework used by the Intergovernmental Panel on Climate Change to assess impacts of climate change. The DPSIR-ESA Vulnerability Assessment (DEVA) framework operationalizes the process of assessing the vulnerability of a target system to external stressors. The DEVA framework includes the following elements: 1) Definition of the target system (Land resource), 2) Description of internal characteristics of the target system (State), 3) Description of target system vulnerability indicators (Adaptive capacity, Sensitivity), 4) Description of stressor characteristics (Drivers, Pressures), 5) Description of stressor vulnerability indicators (Exposure), 6) Description of target system response to stressors (Impacts), and 7) Description of modifications to target systems or stressors (Responses). In stating that they have “applied the DEVA framework”, analysts acknowledge that they have (a) considered the full breadth of each DEVA element, (b) have made conscious decisions to limit the scope and complexity of certain elements, and (c) can communicate both the rationale for these decisions and the impact of these decisions on the vulnerability assessment results and recommendations. The DEVA framework was refined during invited presentations and follow-up discussions from a series of Special Sessions with leading experts at two successive ASABE Annual International Meetings. Six case studies drawn from the sessions elaborate upon the DEVA framework and provide concrete examples of the key concepts. The DEVA approach gives engineers, planners, and analysts a new, flexible framework to apply a broad array of useful tools toward assessment of land resource system vulnerability.

Anandhi, Aauvadi↗

DOE OSTI2022

Shielding Analyses for SNS Accelerator Power Upgrade

The Proton Power Upgrade (PPU) project [1] at Spallation Neutron Source (SNS) is aiming at increasing the neutron beam intensities at the First Target Station (FTS) and advancing accelerator capability to additionally power a future Second Target Station (STS) [2]. PPU will involve upgrading the SNS accelerator complex to double the currently available proton beam power from 1.4 to 2.8 MW, by increasing the proton beam energy from 1 GeV to 1.3 GeV and by increasing the proton beam current.PPU will enable new science capabilities enhancing the experiment throughput of the 19 existing FTS instruments, which are heavily oversubscribed. STS will include 22 additional neutron scattering instruments. Numerous neutronics analyses are performed to support PPU evaluating the FTS systems for higher beam power and for system upgrades. Part of the PPU scope is an extension of the Ring to Target Beam Transport (RTBT) line, a stub out of the accelerator tunnel for the future Ring to STS Transport (RTST) line[3]. As the RTST tunnel will not be built within the PPU project, the stub will be shielded by a plug, which is planned to be made from regular concrete.In order to provide radiation protection safety, analyses are required to design adequate plug thickness for the stub. The thickness of the stub is driven by the criterion that the area downstream of the plug is “unrestricted access area”, demanding the dose rate downstream the stub be below 0.25 mrem/h at 30 cm from the surface at normal operation and below 20 Rem/hr for accident cases. Additionally, analyses verifying the amount of soil for shielding the accelerator tunnel to the above stated requirements are performed.

Popova, Irina I.↗

DOE OSTI2022

Neutronic Safety Analysis of Pu-238 Production at Idaho National Laboratory

This analysis was completed to support the irradiation of plutonium fuel services (PFS) targets in the NEFT in the Advanced Test Reactor (ATR) as a part of the campaign to restart domestic production of plutonium-238 used in radioisotope power systems (RPS) by the National Aeronautical and Space Administration (NASA) and Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Nuclear Infrastructure Program (NE-3). Referred to as the PFS-ATR-GEN1-NEFT experiment, the assembly was designed to hold 46 PFS targets in the NEFT. The scope of this paper is to outline the MOPY method used to calculate the heat generation rates (HGRs), flux, fission density, and quantify the viability of the target design for Pu-238 production in ATR.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2020

Description and Use of SCALE Sampler Parametric Capability for Engineering Analysis and Optimization

The Sampler sequence was introduced into the SCALE nuclear modeling and simulation suite in SCALE 6.2 to perform uncertainty quantification via random sampling of nuclear data, material number densities, and dimensions. Sampler was expanded with the introduction of a parametric capability in SCALE 6.2.2. This paper discusses input for the Sampler parametric sequence and presents two case studies of analyses performed using the sequence. These case studies include preconceptual design of a package for transporting high assay low-enriched uranium (HALEU) oxide and scoping calculations to support subcritical limit development for a future update of the ANSI/ANS-8.1 (ANS-8.1) standard. The parametric capability within Sampler provides many benefits to analysts. For instance, parametric sweeps are frequently used to identify optimum parameter values as part of safety analysis or system design, but such sweeps can require substantial engineering time or may rely on custom-written scripts or scripts such as Write One, Run Many (or WORM) developed outside of any software quality assurance program. With the parametric capabilities in Sampler, however, a large number of inputs can be generated automatically without recourse to scripting by individual analysts. The parametric capability can also be used in lieu of the CSAS5S search sequence to identify optimum parameters more simply with straightforward inputs and outputs. Sampler can also be used to calculate input parameters from engineering specifications. For example, diameters can be converted to radii, or masses can be used to calculate number densities. Overall, the Sampler parametric capability provides a robust feature within SCALE, eliminating the need for user-developed scripting.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Using Generative AI to implement the discrepancy checker for a Nearly Autonomous Management and Control System for Advanced Reactors

Developments related to generative artificial intelligence (AI) have brought a major breakthrough in AI. These developments are rapidly accelerating developments in different science and engineering applications. Nearly Autonomous Management and Control (NAMAC) system provides recommendations to the operator for maintaining the safety and performance of the reactor. The discrepancy checker (DC) is an important component of the NAMAC) system, whose goal is to determine if the plant is moving towards the expected system state after the control actions are injected. In this work, we explore generative AI methods, particularly, a generative pretrained transformer (GPT) for implementing the DC function in NAMAC. The GPT-based DC aims to alert the operator in situations outside NAMAC’s scope and act as a chatbot the operator can use to retrieve relevant information. This study involves two versions of GPT developed by OpenAI: GPT-3.5 and GPT-4. These GPTs are trained on huge amounts of undisclosed general domain datasets. We explored two methods to adapt GPTs for DC implementation in NAMAC: fine-tuning and retrieval augmented generation. A small knowledge base (information file) that encompasses rules for DC implementation and some general information related to NAMAC has been created to support DC implementation using GPT. In this work, the GPT-based DC implementations have been tested for their reasoning abilities, comprehension, information retrieval, and extraction abilities. It should be noted that this paper only presents a preliminary study to test the feasibility of DC implementation using generative AI technology. Given the potential risks and severe consequences associated with nuclear reactor applications, combined with the black-box nature of AI, extensive offline and online testing and reliability analyses of GPT-based DCs are needed for further developing such capabilities.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Chromatic interferometry with small frequency differences

By developing a ‘two-crystal’ method for color erasure, we can broaden the scope of chromatic interferometry to include optical photons whose frequency difference falls outside of the 400 nm to 4500 nm wavelength range, which is the passband of a PPLN crystal. We demonstrate this possibility experimentally, by observing interference patterns between sources at 1064.4 nm and 1063.6 nm, corresponding to a frequency difference of about 200 GHz.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Non-contact imaging of terahertz surface currents with aperture-type near-field microscopy

Terahertz (THz) near-field imaging and spectroscopy provide valuable insights into the fundamental physical processes occurring in THz resonators and metasurfaces on the subwavelength scale. However, so far, the mapping of THz surface currents has remained outside the scope of THz near-field techniques. In this study, we demonstrate that aperture-type scanning near-field microscopy enables non-contact imaging of THz surface currents in subwavelength resonators. Through extensive near-field mapping of an asymmetric D-split-ring THz resonator and full electromagnetic simulations of the resonator and the probe, we demonstrate the correlation between the measured near-field images and the THz surface currents. The observed current dynamics in the interval of several picoseconds reveal the interplay between several excited modes, including dark modes, whereas broadband THz near-field spectroscopy analysis enables the characterization of electromagnetic resonances defined by the resonator geometry.

Norman, Sarah↗

DOE OSTI2025

Enhancing the performance of solvent-borne poly(ethyl methacrylate) coatings for high-power laser applications via low-temperature drying

Organic polymers are a versatile class of materials employed in a broad range of optical coating applications. However, their use as coatings in high-power laser applications, particularly in the UV spectral region, has been limited in scope due to their relatively low laser-induced damage thresholds (LIDTs), which decrease further with exposure to multiple pulses. This study explores the effect of post-deposition drying temperature and residual solvent on the LIDT of solvent-borne polymer coatings. In this work, poly(ethyl methacrylate) (PEMA) coatings were deposited by first spin coating solutions of PEMA (dissolved in 2,2,2-trichloroethanol (TCE)) onto fused silica substrates, then baking at temperatures of either 130°C (soft-bake) or 180°C (hard-bake). Analysis of the two coatings revealed that the soft-bake coating retained a significant amount of TCE within the polymer matrix, which functioned to plasticize the coating and reduce internal stress. The laser-induced damage resistance of the two coatings was evaluated using 351-nm, 1-ns laser pulses. The testing protocols included single-pulse (1-on-1), 1-pulse ramp (R-on-1), and a 1000-pulse ramp (1000R-on-1) test. The results showed that the plasticized, soft-bake coating exhibits a significantly increased LIDT, especially for multipulse irradiation conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Floquet engineering with spatially nonuniform driving fields

In Floquet engineering, we apply a time-periodic modulation to change the effective behavior of a wave system. In this work, we generalize Floquet engineering to more fully exploit spatial degrees of freedom, expanding the scope of effective behaviors we can access. We develop a perturbative procedure to engineer space-time dependent driving forces that effectively transform broad classes of tight-binding systems into one another. We demonstrate several applications, including removing disorder, undoing Anderson localization, and enhancing localization to an extreme in spatially modulated waveguides. This procedure straightforwardly extends to other types of physical systems and different Floquet driving field implementations.

42 ENGINEERING↗

DOE OSTI2023

Identifying ecological and evolutionary research targets and risks in climate change studies to break barriers to broad inference

Understanding the responses of plants, microbes, and their interactions to long-term climate change is essential to identifying the traits, genes, and functions of organisms that maintain ecosystem stability and function of the biosphere. However, many studies investigating organismal responses to climate change are limited in their scope along several key ecological, evolutionary, and environmental axes, creating barriers to broader inference. Broad inference, or the ability to apply and validate findings across these axes, is a vital component of achieving climate preparedness in the future. Breaking barriers to broad inference requires accurate cross-ecosystem interpretability and the identification of reliable frameworks for how these responses will manifest. Current approaches have generated a valuable, yet sometimes contradictory or context dependent, understanding of responses to climate change factors from the organismal- to ecosystem-level. In this synthesis, we use plants, soil microbial communities, and their interactions as examples to identify five major barriers to broad inference and resultant target research areas. We also explain risks associated with disregarding these barriers to broad inference and potential approaches to overcoming them. Developing and funding experimental frameworks that integrate basic ecological and evolutionary principles and are designed to capture broad inference across levels of organization is necessary to further our understanding of climate change on large scales.

Love, Sarah J. (ORCID:0000000180787373)↗

DOE OSTI2021

A proposed framework for the development and qualitative evaluation of West Nile virus models and their application to local public health decision-making

West Nile virus (WNV) is a globally distributed mosquito-borne virus of great public health concern. The number of WNV human cases and mosquito infection patterns vary in space and time. Many statistical models have been developed to understand and predict WNV geographic and temporal dynamics. However, these modeling efforts have been disjointed with little model comparison and inconsistent validation. In this paper, we describe a framework to unify and standardize WNV modeling efforts nationwide. WNV risk, detection, or warning models for this review were solicited from active research groups working in different regions of the United States. A total of 13 models were selected and described. The spatial and temporal scales of each model were compared to guide the timing and the locations for mosquito and virus surveillance, to support mosquito vector control decisions, and to assist in conducting public health outreach campaigns at multiple scales of decision-making. Our overarching goal is to bridge the existing gap between model development, which is usually conducted as an academic exercise, and practical model applications, which occur at state, tribal, local, or territorial public health and mosquito control agency levels. The proposed model assessment and comparison framework helps clarify the value of individual models for decision-making and identifies the appropriate temporal and spatial scope of each model. This qualitative evaluation clearly identifies gaps in linking models to applied decisions and sets the stage for a quantitative comparison of models. Specifically, whereas many coarse-grained models (county resolution or greater) have been developed, the greatest need is for fine-grained, short-term planning models (m–km, days–weeks) that remain scarce. We further recommend quantifying the value of information for each decision to identify decisions that would benefit most from model input.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Characterization of a broadly specific cadaverine N-hydroxylase involved in desferrioxamine B biosynthesis in Streptomyces sviceus

N-hydroxylating flavin-dependent monooxygenases (FMOs) are involved in the biosynthesis of hydroxamate siderophores, playing a key role in microbial virulence. Herein, we report the first structural and kinetic characterization of a novel alkyl diamine N-hydroxylase DesB from Streptomyces sviceus (SsDesB). This enzyme catalyzes the first committed step in the biosynthesis of desferrioxamine B, a clinical drug used to treat iron overload disorders. X-ray crystal structures of the SsDesB holoenzyme with FAD and the ternary complex with bound NADP + were solved at 2.86 Å and 2.37 Å resolution, respectively, providing a structural view of the active site environment. SsDesB crystallized as a tetramer and the structure of the individual protomers closely resembles the structures of homologous N-hydroxylating FMOs from Erwinia amylovora (DfoA), Pseudomonas aeruginosa (PvdA), and Aspergillus fumigatus (SidA). Using NADPH oxidation, oxygen consumption, and product formation assays, kinetic parameters were determined for various substrates with SsDesB. SsDesB exhibited typical saturation kinetics with substrate inhibition at high concentrations of NAD(P)H as well as cadaverine. The apparent k cat values for NADPH in steady-state NADPH oxidation and oxygen consumption assays were 0.28 ± 0.01 s -1 and 0.24 ± 0.01 s -1 , respectively. However, in product formation assays used to measure the rate of N-hydroxylation, the apparent k cat for NADPH (0.034 ± 0.008 s -1 ) was almost 10-fold lower under saturating FAD and cadaverine concentrations, reflecting an uncoupled reaction, and the apparent NADPH K M was 33 ± 24 μM. Under saturating FAD and NADPH concentrations, the apparent k cat and K M for cadaverine in Csaky assays were 0.048 ± 0.004 s -1 and 19 ± 9 μM, respectively. SsDesB also N-hydroxylated putrescine, spermidine, and L-lysine substrates but not alkyl (di)amines that were branched or had fewer than four methylene units in an alkyl chain. These data demonstrate that SsDesB has wider substrate scope compared to other well-studied ornithine and lysine N-hydroxylases, making it an amenable biocatalyst for the production of desferrioxamine B, derivatives, and other N-substituted products.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

DEEPEN Leapfrog Geodata Model Cleaned and Reformatted Exploration Datasets from Newberry Volcano

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the DEEPEN 3D play fairway analysis (PFA) conducted at Newberry Volcano for multiple play types (conventional hydrothermal, superhot EGS, and supercritical), existing geoscientific exploration datasets needed to be acquired, cleaned, reformatted, and assembled in Leapfrog Geothermal. This GDR submission includes all of the cleaned and reformatted (X (m), Y (m), elevation (m), processed data values) datasets used to build the Leapfrog Geodata model. Existing datasets were acquired from the GDR, from AltaRock, and from other sources. This yielded the following datasets: - Digital elevation model produced from LiDAR data by Ramsey and Bard, 2016 - MT surveys from 2006, 2011, 2014, and 2017 (including single inversions) - Gravity surveys from 2006, 2007, and 2011 (including single) - Earthquake catalogs from PNSN, LLNL, and the Newberry EGS Demonstration project - Seismic velocity model from Templeton et al., 2014 - The Frone, 2015 temperature model and a new one produced through extrapolating downhole temperature measurements and the SMU temperature at depth maps. Two versions of the new model are provided: 250 m spacing and 500 m spacing - EarthVision geologic model with alteration from Moser et al., 2016 - Well data from EGS well 55-29, deep geothermal wells, coreholes (GEO N-2 through 5) and several thermal gradient holes - "Newberry Well Data:" Location, simple lithology, directional survey data, and temperature data for the 34 wells and coreholes used in the Newberry PFA Although there are additional 2D datasets available in the area, such as aeromagnetic surveys, these were not included in the analysis. While it may be possible to project these datasets into three dimensions by assuming the surface measurements do not vary with depth, this method is associated with high uncertainty. Preexisting inversions of these data were unavailable, and inverting additional geophysical datasets is outside the scope of this project.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

Community Geothermal: Energy, Cost, and Carbon Modeling for District Design - Ann Arbor, MI

This data includes results on an analysis of existing and projected energy, cost, and carbon for the City of Ann Arbor - District Geothermal Design and Deployment to Equitably Decarbonize Low Income Neighborhoods in Ann Arbor project. The scope of the project includes designing and implementing a geothermal district heating and cooling system that reduces thermal heating and cooling load by 75% and greenhouse gas emissions by 40% in the project area (262 households, 6 commercial buildings). The existing neighborhood was modeled using Design Builder, an EnergyPlus software, to understand the current energy load. The energy model was then flipped to reflect the designed district geothermal heating and cooling system to project the effect on energy, carbon, and cost. This dataset includes the analysis files utilized and created for this study. There are 3 categories of data: 1) existing/benchmarking, 2) energy modeling, and 3) post processed calculations. This follows the methodology and process of the project team, which is fully explained in file 00_Technical Economic Environmental Assessment. All uses of data are referenced throughout this assessment to their respective files included below.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

Exploring the impact of vibrational cavity coupling strength on ultrafast CN + c -C 6 H 12 reaction dynamics

Abstract Molecular polaritons, hybrid light-matter states resulting from strong cavity coupling of optical transitions, may provide a new route to guide chemical reactions. However, demonstrations of cavity-modified reactivity in clean benchmark systems are still needed to clarify the mechanisms and scope of polariton chemistry. Here, we use transient absorption to observe the ultrafast dynamics of CN radicals interacting with a cyclohexane ( c -C 6 H 12 ) and chloroform (CHCl 3 ) solvent mixture under vibrational strong coupling of a C–H stretching mode of c- C 6 H 12 . By modulating the c -C 6 H 12 :CHCl 3 ratio, we explore how solvent complexation and hydrogen (H)-abstraction processes proceed under collective cavity coupling strengths ranging from 55 to 85 cm −1 . Reaction rates remain unchanged for all extracavity, on-resonance, and off-resonance cavity coupling conditions, regardless of coupling strength. These results suggest that insufficient vibrational cavity coupling strength may not be the determining factor for the negligible cavity effects observed previously in H-abstraction reactions of CN with CHCl 3 .

Chen, Liying↗

DOE OSTI2021

ESS-DIVE Reporting Format for File-level Metadata

The ESS-DIVE reporting format for file-level metadata (FLMD) provides granular information at the data file level to describe the contents, scope, and structure of the data file to enable comparison of data files within a data package. The FLMD are fully consistent with and augment the metadata collected at the data package level. We developed the FLMD template based on a review of a small number of existing FLMD in use at other agencies and repositories with valuable input from the Environmental Systems Science (ESS) Community. Also included is a template for a CSV Data Dictionary where users can provide file-level information about the contents of a CSV data file (e.g., define column names, provide units). Files are in .csv, .xlsx, and .md. Templates are in both .csv and .xlsx (open with e.g. Microsoft Excel, LibreOffice, or Google Sheets). Open the .md files by downloading and using a text editor (e.g. Notepad or TextEdit). Though we provide Excel templates for the file-level metadata reporting format, our instructions encourage users to 'Save the FLMD template as a CSV following the CSV Reporting Format guidance'. In addition, we developed the ESS-DIVE File Level Metadata Extractor which is a lightweight python script that can extract some FLMD fields following the recommended FLMD format and structure.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

ESS-DIVE Reporting Format for Hydrologic Monitoring Data and Metadata

The ESS-DIVE Reporting Format (RF) for Hydrologic Monitoring Data and Metadata was designed for water level, temperature, electrical conductivity, specific conductance, dissolved oxygen, and pH measured in situ using sensors deployed in water bodies. It can also be applied to a broader suite of variables beyond its original scope. The RF is intended to provide clear and easy guidance to data generators aiming to upload consistent findable, accessible, interoperable, and reusable (FAIR) datasets. The RF includes instructions (pdf), a term guide (csv), templates (csv and xlsx), and a list of recommended vocabulary (csv) to equip the data generator with all of the tools needed to successfully apply the RF. There is also a crosswalk to some key data resources and standards (csv). Users should cite this dataset when using the RF but are encouraged to access the RF files on GitHub (https://github.com/ess-dive-community/essdive-hydrologic-monitoring) where the RF documentation is maintained and updated on the ESS-DIVE Community Space GitHub. Questions and suggestions for improvement can be submitted as GitHub issues.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Materials science for quantum information science and technology

Quantum computing, sensing, and communications are emerging technologies that may circumvent known limitations of their existing traditional counterparts. While the promises of these technologies are currently narrow in scope, it is possible that they will broadly impact our lives by revolutionizing the capabilities of data centers and medical diagnostics, for example. At the heart of these technologies is the use of a quantum object to contain information, called a quantum bit or qubit. Current realizations of qubits exist in a broad variety of material systems, including individual spins in semiconductors or insulators, superconducting circuits, and trapped ions. Further advancement of qubits requires significant contributions from materials science in areas of materials selection, synthesis, fabrication, simulation and characterization. In this paper, we discuss some of the needs and opportunities for contributions to advance the fundamental understanding of materials used in quantum information applications.

36 MATERIALS SCIENCE↗