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DOE OSTI2020

Production Through Simulation: Using Simulation Technologies to Create and Evaluate Nuclear Fuel Fabrication Facility Designs

This project explores how physics-based and discrete-event simulation technologies can be jointly employed to model a suite of nuclear fuel fabrication facility designs with variable radiological environments, optimize their design to lower operational costs subject to a set of design constraints, and evaluate their performance. Initially, three variants of U-20Pu-10Zr metallic nuclear fuel in three specific geometric configurations are modeled and studied across more than 50 physics simulations in nuclear physics software packages SCALE and Monte Carlo N-Particle Transport (MCNP6.2). From these tests, values for effective dose rate and criticality are recorded for each of the nine alloy-geometry configurations. These values are then incorporated into discrete-event models of fuel fabrication in the simulation program ExtendSim Pro 10 as process attributes. This allows one to track the dose to facility personnel as fuel is fabricated, dually enabling us to evaluate the safety of a given facility design in terms of absorbed dose per worker per year and to craft operational guidelines that adhere to federal and local safety regulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Transient Photocurrent From High-Voltage Vertical GaN Diodes Irradiated With Electrons: Experiments and Simulations

Radiation-hard high-voltage vertical GaN p-n diodes are being developed for use in power electronics subjected to ionizing radiation. Here, we present a comparison of the measured and simulated photocurrent response of diodes exposed to ionizing irradiation with 70 keV and 20 MeV electrons at dose rates in the range of 1.4x10 7 - 5.0x10 8 rad(GaN)/s. The simulations correctly predict the trend in measured steady-state photocurrent and agree with experimental results within a factor of 2. Furthermore, simulations of the transient photocurrent response to dose rates with uniform and non-uniform ionization depth profiles uncover the physical processes involved that cannot be otherwise experimentally observed due to orders of magnitude larger RC time constant of the test circuit. The simulations were performed using an Exploratory Physics Development code developed at Sandia National Laboratories. The code offers the capability to include defect physics under more general conditions, not included in commercially available software packages, extending the applicability of the simulations to different types of radiation environments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

TeraChem Cloud: A High-Performance Computing Service for Scalable Distributed GPU-Accelerated Electronic Structure Calculations

The encapsulation and commoditization of electronic structure arise naturally as interoperability, and the use of nontraditional compute resources (e.g., new hardware accelerators, cloud computing) remains important for the computational chemistry community. Here, we present TERACHEM CLOUD, a high-performance computing service (HPCS) that offers on-demand electronic structure calculations on both traditional HPC clusters and cloud-based hardware. The framework is designed using off-the-shelf web technologies and containerization to be extremely scalable and portable. Within the HPCS model, users can quickly develop new methods and algorithms in an interactive environment on their laptop while allowing TERACHEM CLOUD to distribute ab initio calculations across all available resources. This approach greatly increases the accessibility of hardware accelerators such as graphics processing units (GPUs) and flexibility for the development of new methods as additional electronic structure packages are integrated into the framework as alternative backends. Cost-performance analysis indicates that traditional nodes are the most cost-effective long-term solution, but commercial cloud providers offer cutting-edge hardware with competitive rates for short-term large-scale calculations. We demonstrate the power of the TERACHEM CLOUD framework by carrying out several showcase calculations, including the generation of 300,000 density functional theory energy and gradient evaluations on medium-sized organic molecules and reproducing 300 fs of nonadiabatic dynamics on the B800-B850 antenna complex in LH2, with the latter demonstration using over 50 Tesla V100 GPUs in a commercial cloud environment in 8 h for approximately $1250.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

GDSA Framework Development and Process Model Integration FY2022

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Spent Fuel & Waste Disposition (SFWD) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). A high priority for SFWST disposal R&D is disposal system modeling (Sassani et al. 2021). The SFWST Geologic Disposal Safety Assessment (GDSA) work package is charged with developing a disposal system modeling and analysis capability for evaluating generic disposal system performance for nuclear waste in geologic media. This report describes fiscal year (FY) 2022 advances of the Geologic Disposal Safety Assessment (GDSA) performance assessment (PA) development groups of the SFWST Campaign. The common mission of these groups is to develop a geologic disposal system modeling capability for nuclear waste that can be used to assess probabilistically the performance of generic disposal options and generic sites. The modeling capability under development is called GDSA Framework (pa.sandia.gov). GDSA Framework is a coordinated set of codes and databases designed for probabilistically simulating the release and transport of disposed radionuclides from a repository to the biosphere for post-closure performance assessment. Primary components of GDSA Framework include PFLOTRAN to simulate the major features, events, and processes (FEPs) over time, Dakota to propagate uncertainty and analyze sensitivities, meshing codes to define the domain, and various other software for rendering properties, processing data, and visualizing results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

GDSA Framework Development and Process Model Integration FY2023

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

The Roadrunner Trap: A QSCOUT Device

The Roadrunner ion trap is a micro-fabricated surface-electrode ion trap based on silicon technology. This trap has one long linear section and a junction to allow for chain storage and reconfiguration. It uses a symmetric rf-rail design with segmented inner and outer control electrodes and independent control in the junction arms. The trap is fabricated on Sandia’s High Optical Access (HOA) platform to provide good optical access for tightly focused laser beams skimming the trap surface. It is packaged on our custom Bowtie-102 ceramic pin or land grid array packages using a 2.54 mm pitch for backside pins or pads. This trap also includes an rf sensing capacitive divider and tungsten wires for heating or temperature monitoring. The Roadrunner builds on the knowledge gained from previous surface traps fabricated at Sandia while improving ion control capabilities.

42 ENGINEERING↗

DOE OSTI2025

Measuring 3D Profilometry of SAVY-4000 Nuclear Material Storage Containers: Novacam TubeInspect Capabilities Report

The SAVY-4000 container series is a general-purpose interim storage container for nuclear materials, developed and maintained by Los Alamos National Laboratory (LANL). It is the first vented, general-use nuclear material container to be demonstrated as meeting the requirements outlined in DOE M 441.1-1, the Nuclear Material Packaging Manual. Due to the challenging radiation, thermal, and corrosive storage conditions that the SAVY containers must endure, continuous surveillance techniques are employed to ensure the containers meet all safety standards and specifications. These inspections are typically performed by human operators, who check for issues such as corrosion, O-ring deterioration, corrosion, filter integrity, and potential manufacturing defects. However, human inspections alone are not sufficient, and automated inspection technologies, such as the ATIS system, as well as other automated systems are also utilized. The MicroCam TubeInspect, developed by Novacam Technologies Inc., is designed to address the challenges of understanding how manufacturing variations in the SAVY-4000 container series may affect performance. It is a 3D profilometry measurement system that enables detailed analysis of surface features, including defects, surface roughness, and manufacturing variations. This advanced tool significantly enhances rapid surveillance techniques for both pristine and used containers. In this study, container properties such as surface roughness, thickness, and geometric attributes like circularity are measured for SAVY-4000 containers. Artificially corroded or dented containers are examined to demonstrate the MicroCam's ability to quantify defects. A sensitivity analysis is also conducted, comparing the MicroCam results to those obtained using more precise instruments such as confocal microscopy. This comparison aims to provide valuable insights into container quality, durability, and potential improvements in manufacturing processes.

42 ENGINEERING↗

DOE OSTI2020

M4SF-20LL010301042: Updated Thermodynamic Database for Use in Generic Disposal System Assessment

This progress report (Level 4 Milestone Number M4SF-20LL010301042) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Argillite Activity Number SF-20LL010301041. LLNL is leading efforts in the development of thermodynamic databases in support of the Spent Fuel and Waste Science Technology (SFWST) program. Thermodynamic models provide the basis for understanding the stability of solid phases and speciation of aqueous species and modeling the evolution of repository conditions. The LLNL effort is being performed in coordination with other US database development efforts. The effort includes a review of available thermochemical databases and a path forward for database integration. International coordination with the NEA-TDB is supported through crystalline international work package.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

GDSA Framework Development and Process Model Integration FY2021

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Spent Nuclear Fuel Exploratory Roadmaps - 20054

The U.S. Department of Energy manages nearly 2,500 metric tons of heavy metal (MTHM) of spent nuclear fuel (SNF) resulting from several decades of research, testing, and production reactors [DOE 1995]. This SNF is managed at the DOE Hanford Site in Washington State (Hanford), Idaho National Laboratory (INL), and Savannah River Site in South Carolina (SRS). From 1995 to 2004, the Department of Energy (DOE) made several key programmatic decisions, supported by appropriate documentation in accordance with the National Environmental Policy Act (NEPA) for the management of SNF [DOE 1995]. These decisions have provided an overarching framework for SNF management, as well as site-specific and SNF-related management decisions for the past two decades. In the years since these decisions were made, with the notable exception of the successful drying and packaging of the production reactor fuel at Hanford, a majority of the decisions have been largely unimplemented. Also, since these decisions were made, a number of changes that bear on considerations relative to the path forward have occurred. A SNF Exploratory Road map activity, identified reasonable alternate pathways for DoE's inventory of SNF. Three fundamental pathways were identified in this activity for the long-term management and disposition of DOE SNF: Direct Disposal Pathway, Existing Processing Pathway and Alternate Processing Pathway. Further actions would be required (e.g., evaluation of NEPA analysis, technology maturity evaluations, refinement of cost and risks, benefits and advantages relative to other alternate paths) to define and inform many key decisions that will result in the selection of the disposition pathways that are most beneficial to the US Government in dispositioning DoE's SNF inventory. DOE is currently managing all SNF safely; however, the age of DOE-owned SNF and facilities for storing and processing SNF, coupled with the uncertainty of the storage duration, necessitates decisions and actions to ensure that the infrastructure will be in place to ensure continued safe and effective long-term management and eventual disposal. The identification of reasonable alternate pathways took these considerations into account in an effort to proactively manage conditions that could challenge the safety of storing and managing DOE SNF over the time periods now contemplated and also to ensure that flexibility is preserved to ensure that the DOE SNF remains compatible with final disposition pathways when they become available. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

BatAnalysis - A Comprehensive Python Pipeline for Swift BAT Survey Analysis

The Swift Burst Alert Telescope (BAT) is a coded-aperture gamma-ray instrument with a large field of view that primarily operates in survey mode when it is not triggering on transient events. The survey data consist of 80- channel detector plane histograms that accumulate photon counts over periods of at least 5 minutes. These histograms are processed on the ground and are used to produce the survey data set between 14 and 195 keV. Survey data comprise >90% of all BAT data by volume and allow for the tracking of long-term light curves and spectral properties of cataloged and uncataloged hard X-ray sources. Until now, the survey data set has not been used to its full potential due to the complexity associated with its analysis and the lack of easily usable pipelines. Here, we introduce the BatAnalysis Python package, a wrapper for HEASoftpy, which provides a modern, opensource pipeline to process and analyze BAT survey data. BatAnalysis allows members of the community to use BAT survey data in more advanced analyses of astrophysical sources, including pulsars, pulsar wind nebula, active galactic nuclei, and other known/unknown transient events that may be detected in the hard X-ray band. We outline the steps taken by the Python code and exemplify its usefulness and accuracy by analyzing survey data of the Crab Nebula, NGC 2992, and a previously uncataloged MAXI transient. The BatAnalysis package allows for ~18 yr of BAT survey data to be used in a systematic way to study a large variety of astrophysical sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

A low-cost centralized HVAC control system solution for energy savings, load shedding, and improved maintenance

University campuses rely on centralized controls for managing and optimizing complex HVAC systems in larger buildings. However, most campuses also have many smaller buildings with packaged HVAC systems controlled by a stand-alone thermostat. Even when these distributed and often overlooked systems have modern programmable thermostats, they cannot be centrally monitored or controlled, and they are typically not programmed adequately. This paper describes the implementation of a low-cost centralized control solution for these systems serving smaller campus buildings, mostly under 5,000 sf and representative of light commercial spaces. Thanks to advances in technology spurred by residential and commercial IoT developments, simple networked thermostat solutions exist that can easily replace original thermostats, and, connect these systems to a web-based portal for monitoring and control. We show that, with small customizations, these platforms can be integrated into facility management workflows. Beyond the energy savings potential from improved scheduling and closer management of these systems, there are significant advantages for maintenance crews since these systems can now be monitored on smart phones or tablets. A grid-responsive load-shedding program has also been implemented for additional cost savings. The networked thermostats can also be connected to additional systems such as economizer controls for improved ventilation management and energy savings. With data from these systems integrated centrally, it can also be used for improved analytics and fault detection. A toolkit has been developed to share the program with other campuses, whether for energy savings, improved management of ventilation, or a more proactive maintenance approach.

Fauchier-Magnan, Nicolas↗

DOE OSTI2021

Technical Assessment of Novel Hydrogen Producing Solid Oxide Fuel Cell Power System

Solid oxide cell-based electrolysis (SOEC) systems are being considered for hydrogen production due to their potential for high efficiencies and for their integrability with base load power generation systems when operated in solid oxide fuel cell (SOFC) mode. However, a cost prohibitive combination of SOFC power systems and SOEC systems may be required to operate the plant flexibly to produce a combination of H 2 and power on-demand. A single (consequently less expensive) reversible SOFC/SOEC system, on the other hand, poses technological challenges related to the on demand switching between power and H 2 production. This report provides a high-level technical assessment of a novel SOFC based H 2 production concept that averts the potential drawbacks of the SOEC systems. The novel concept combines the advantages of steam-reforming of natural gas to produce H 2 with the high efficiency power generation capabilities of a SOFC in a single package.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2024

A Skipper-CCD Light Shield for X-Ray Detection in Space

We present advancements in the design of Skipper-CCD sensors for X-ray detection in environments with high optical backgrounds, such as those expected in space. These packages incorporate a custom-made aluminum shield on the CCD surface that blocks over 99% of visible light while preserving the efficiency for keV X-rays. These features allow us to perform precise X-ray measurements in environments challenged by visible light interference. Furthermore, we briefly discuss the potential implementation of this design concept in frame-transfer CCDs, opening opportunities for broader applications and advancements in imaging technologies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Fluor Solvent Evaluation and Testing New Scope: Techno-economic Assessment of EEMPA Solvent for CO 2 Separations from Natural Gas Combined Cycle Power Plant

In this project, a techno-economic analysis (TEA) and sensitivity studies were conducted to assess the PNNL’s leading water-lean CO 2 capture solvent, EEMPA, for capture CO 2 from a natural gas combined cycle (NGCC) power plant at different levels of capture rate. Process models for the NGCC power plant, integrated with EEMPA carbon capture processes, were developed in Aspen Plus V14 using the most up-to-date property package for EEMPA-H 2 O-CO 2 system. The TEA evaluated EEMPA carbon capture process at normal capture rates (90%, 95% and 97%) against Case B32B (Cansolv) described in NETL Rev4a baseline report, and at higher capture rates aimed at achieving zero or negative emissions from the power plant (400 ppmv, 200 ppmv, and 100 ppmv CO 2 in exhaust gas), compared to typical Direct Air Capture (DAC) technologies. A manuscript was drafted for peer-reviewed publication. The results suggested that the carbon capture cost reaches a minimum of $\$$53.7/tonne CO 2 at 90% capture rate. Compared to Cansolv, one of the industrial benchmarks, EEMPA demonstrates 2-4% cost savings at capture rates up to 95%, but minimal savings at higher capture rate. The water lean-solvent system proves economically attractive for achieving moderate negative emissions (about 200 ppmv CO 2 in exhaust gas, and equivalent to 50% CO 2 removal from air) for NGCC flue gas, with marginal capture costs comparable to direct air capture (DAC) technologies. A sensitivity analysis results reveal that its economic advantage, unaffected by EEMPA price due to low solvent loss and degradation rate. However, the marginal carbon capture cost exceeds $\$$1,000/tonne CO 2 when transitioning from moderate to extreme negative emissions (100 ppmv CO 2 in exhaust gas), suggesting that water-lean solvents may not be economically competitive with other DAC technologies for removing more than 75% CO 2 from air. In addition, initial connection was established with Technology Center Mongstad (TCM) for a potential pilot testing proposal. However, detailed modeling and proposal preparation was not conducted due to the delay of non-disclosure agreement.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2023

Digital camera imagery for vegetation phenology, Seward Peninsula, Alaska, 2021-2022

Timelapse camera images from Council Mile Marker (MM) 71, Kougarok MM 64, Kougarok Fire Complex (KFC, also referred to as the Garfield Fire Site), and Teller MM 27 NGEE-Arctic field sites on the Seward Peninsula, Alaska, captured from August 2021 to July 2022. Ten Wingscape Timelapse Pro cameras, and twenty seven Power-interval Camera Automation Modules (PiCAMs) designed by Brookhaven National Laboratory's Terrestrial Ecosystem Science and Technology (TEST) group were deployed targeting patches of low and tall shrubs (including Alnus sp. and Salix sp.) and general vegetation and landscape views. Images from Wingscape cameras were recorded at hourly intervals from 11 AM to 2 PM, and images from PiCAMs were recorded at 5 hourly intervals from 12 AM to 8 PM, continuously for 12 months and capture vegetation phenology, snow accumulation and snow melt events. This data package includes images (*.jpg), organized by site and camera ID, and metadata with details of the cameras used, number of images recorded, start and end dates, GPS locations and example fields of view. Additional information available in *.pdf and *.csv files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort 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 OSTI2024

Digital camera imagery for vegetation phenology, Seward Peninsula, Alaska, 2022-2023

Timelapse camera images from Council Mile Marker (MM) 71, Kougarok MM 64, Kougarok Fire Complex (KFC), and Teller MM 27 NGEE-Arctic field sites on the Seward Peninsula, Alaska, captured from July 2022 to July 2023. Eight Wingscape Timelapse Pro cameras, and thirty-one Power-interval Camera Automation Modules (PiCAMs) designed by Brookhaven National Laboratory?s Terrestrial Ecosystem Science and Technology (TEST) group were deployed targeting patches of low and tall shrubs (including Alnus sp. and Salix sp.) and general vegetation and landscape views. Images from Wingscape cameras were recorded at hourly intervals from 11 AM to 2 PM, and images from PiCAMs were recorded at 5 hourly intervals from 12 AM to 8 PM, continuously for 12 months and capture vegetation phenology, snow accumulation and snow melt events. This data package includes images (*.jpg), organized by site and camera ID, and metadata with details of the cameras used, number of images recorded, start and end dates, GPS locations and example fields of view. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort 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 OSTI2020

Smart Planning Support for Nuclear Power Plant Work Planners

Operation and Maintenance costs of a nuclear power plant account for 60% of overall plant costs due to the nuclear industry?s risk-adverse culture (World Nuclear Association, 2020). The industry relies on highly conservative estimates to avoid risk and brute force reactions to manage the unexpected and keep a plant running safely. This approach has kept plants operating safer than any other power source available over the last six decades (Ritchie, 2020). However, these conservative methods have cost the nuclear industry in market competitiveness. The solution? Transform the conservative approaches to accurate, efficient, and still safe data-driven approaches that leverage advanced technologies available in the digital age of operation. This project endeavored to identify two key aspects to successfully incorporate historical work execution data. First, where in the work management process is that information most pertinent? Next, what variables are key to informing the best strategy for organizing the upcoming work? The Smart Planner uses data collected by dynamic work instructions to provide a basis for suggesting requirements of similar, upcoming work packages. Further, it curbs inefficiencies of the work management process by analyzing the likelihood of discovery work, offering suggestions to build a contingency package. All this taking place as the work planner builds work packages that meet the predetermined scope of work to be performed.

99 GENERAL AND MISCELLANEOUS↗