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DOE OSTI2021

Reference document for LANL stack sampling and ANSI N13.1 (Article) Gielow RL and McNamee MR 1993. Numerical Flue Gas Flow Modeling for Continuous Emissions Monitoring Applications. EPRI CEM Users Group Meeting. Baltimore. RP1961-13

American National Standard N13.1 “sets forth guidelines and performance criteria for sampling the emissions of airborne radioactive substances in the air discharge ducts and stacks of nuclear facilities. Emphasis is on extractive sampling from a location in a stack or duct where the contaminant is well mixed. At such a location, sampling may be conducted at a single point. This standard provides performance-based criteria for the use of air sampling probes, transport lines, sample collectors, sample monitoring instruments, and gas flow measuring methods. This standard also covers sampling program objectives, quality assurance issues, developing air sampling action levels, system optimization, and system performance verification. Workplace, containment, and environmental air monitoring are not addressed. Specific sample analysis methods and the reporting or interpreting of results are also not addressed.” (HPS 2011).

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2018

Seventy-Five Years of Nuclear Criticality Safety Documents - A Bibliography

A collection of nuclear criticality documents was begun in the 1970s at the University of California’s Lawrence Livermore Laboratory (now Lawrence Livermore National Laboratory). Documents in this bibliography are dated as early as 1940. The early documents described experimental work that was of vital importance to the safe use of fissile materials at nuclear reactors, the facilities for preparing or transporting nuclear fuel, or its eventual storage. The experiments were of direct value to support safe operations with fissile material, but they were also needed for validating early physics data and calculational methods and then for validating computational methods used in criticality safety evaluations. Bibliographic information from the past seventy-five years have been entered into a computerized bibliographic database. The database continues to expand. Publications were issued several decades ago based on the information collected at that time. Our new publication is based on a current “snapshot” of the present status of the database. Contributions of information or corrections to this bibliography will be appreciated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Modeling Enhancements, Cross-Section Generation Updates, and Benchmarking with Shift

This technical report documents the modeling enhancements, cross-section generation updates, and bench marking with the Shift Monte Carlo code performed under the US Department of Energy Nuclear Energy Advanced Modeling and Simulation Program in FY 2024. The work performed included several modeling enhancements, such as integration of cross-section generation in Titan and the ability to produce microscopic multigroup cross sections with Shift. Benchmarking of the cross sections produced by Shift and the two-step workflow with Griffin was performed for three problems: the Advanced Breeder Test Reactor, a generic pebble bed reactor, and a TRISO heat pipe microreactor. Comparisons of results from these benchmark problems were done with Serpent, OpenMC, and Griffin. These enhancements provide a robust foundation for applying Shift for both reference and two-step neutronics analysis for advanced reactor simulation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

LUCID Thrust 1 - Dataset Identification and Biodata Catalog Creation

The LUCID DOE consortium, part of the Department of Energy’s Biological and Environmental Research (BER) program, advances Low Dose Radiation (LDR) research through multidisciplinary efforts across seven key thrusts. This document focuses on Thrust 1, which centers on the creation of curated multimodal population health datasets and supports broader efforts within the LUCID program, including AI-based hypothesis generation, experimental design, and the study of LDR-induced health risks. Specifically, it describes the identification and cataloging of Thrust 1’s curated LDR datasets and biodata, emphasizing their critical role in supporting various research thrusts within the consortium, with potential applications in healthcare and public policy. In addition, the document includes an evaluation of three Large Language Models (LLMs)—GPT-4, SOLAR-10B, and Mixtral-8x7B—based on their ability to extract features from 25 LDR studies. The results indicate that GPT-4 performed the best, while Mixtral-8x7B demonstrated limited knowledge. Overall, this work advances understanding in radiation protection, risk assessment, and medical treatments, while providing valuable resources for researchers, educators, and policymakers.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2018

sympl (v. 0.4.0) and climt (v. 0.15.3) – towards a flexible framework for building model hierarchies in Python

sympl (System for Modelling Planets) andclimt (Climate Modelling and Diagnostics Toolkit) are anattempt to rethink climate modelling frameworks from the ground up. The aimis to use expressive data structures available in the scientific Pythonecosystem along with best practices in software design to allow scientists toeasily and reliably combine model components to represent the climate systemat a desired level of complexity and to enable users to fully understandwhat the model is doing. sympl is a framework which formulates the model in terms of astate that gets evolved forward in time or modified within a specifictime by well-defined components. sympl's design facilitates buildingmodels that are self-documenting, are highly interoperable, and providefine-grained control over model components and behaviour. symplcomponents contain all relevant information about the input they expect andoutput that they provide. Components are designed to be easily interchanged,even when they rely on different units or array configurations.sympl provides basic functions and objects which could be used inany type of Earth system model. climt is an Earth system modelling toolkit that contains scientificcomponents built using sympl base objects. These include both purePython components and wrapped Fortran libraries. climt providesfunctionality requiring model-specific assumptions, such as stateinitialization and grid configuration. climt's programming interfacedesigned to be easy to use and thus appealing to a wide audience. Model building, configuration and execution are performed through a Pythonscript (or Jupyter Notebook), enabling researchers to build an end-to-endPython-based pipeline along with popular Python data analysis andvisualization tools.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

High-Fidelity Measurements for Flattop-HEU Benchmark Reevaluation

Flattop was first built in the 1950’s at Los Alamos National Laboratory. Flattop-HEU is composed of a sphere of highly enriched uranium (HEU) surrounded by a thick spherical natural uranium (NU) reflector. The reflector is composed of three parts: a stationary hemisphere and two movable quarter spheres. For fine control of the reactivity of the system, there are three control rods of natural uranium located in voids in the stationary hemisphere. The final components that make Flattop a useful critical assembly are the glory hole and mass adjustment pieces. These pieces can be loaded in various configurations into the glory hole and the core pedestal to control the known worth of the system. The glory hole and mass adjustment pieces are mostly small pieces of HEU with some mass adjustment pieces fabricated from NU. This allows for the irradiation of samples to a specified level. To better document the system, Flattop was evaluated and included in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) handbook. The original benchmark evaluation of Flattop-HEU was written in 1999 based on an experiment completed in the 1960’s. This original evaluation was written to provide a single diameter that defined critical mass; however, as computational capabilities have increased, the focus for benchmark evaluations has shifted to include detailed modelswith all physical dimensions. Thus, as Flattop is a lynchpin in critical experiment work, the benchmark is being reevaluated at current standards. This summary discusses some of the largest known uncertainties from the evaluation and the high-fidelity measurements taken to reduce these uncertainties.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Event Definition for the Automated Detection of Nuclear Proliferation Activities

In FY2020, Savannah River National Laboratory (SRNL) in collaboration with the Discovery Analytics Center (DAC) at Virginia Polytechnic Institute and State University (VT) began developing a demonstration prototype system that uses multiple machine learning and data analytic methods on largescale open data sources to identify new, developing, or undeclared nuclear programs. One of the most challenging aspects of applying machine learning techniques to such a problem is the high likelihood of extremely sparse data from disparate sources. To overcome this challenge, the current work will use a strategic combination of supervised, semi-supervised, and unsupervised learning techniques to ingest and fuse data streams to make a forecast of nuclear activities in a targeted geospatial location. Identifying potential data sources and training supervised learning algorithms is dependent upon the development of a robust foundation of targeted event domains that fundamentally define the nuclear activities of interest. This report documents the definition of a hierarchical structure for both nuclear activity and event domains that will be used to guide the research team in development or use of existing semantic dictionaries that are instrumental to searching, parsing, and categorizing events for the forecasting system’s use.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

THF Co-Solvent Biomass Fractionation to Catalytic Fuel Precursors with High Yields (Final Report)

The overall goal of this project is to utilize the Co-Solvent Enhanced Lignocellulosic Fractionation (CELF) as a platform technology to realize transformation of real biomass feedstocks to fungible transportation fuels. CELF is a solvolysis method that seeks to break the cost barrier for biomass deconstruction so that high yield liquid intermediates from both sugars and lignin can be recovered for their subsequent catalytic conversion to fungible transportation fuels. It is important for the DOE EERE mission to focus on supporting platform technologies that enable greater end-to-end utilization of biomass whereby the co-development of both process and catalyst is streamlined. CELF is one of the most competitive platform technologies that uses multifunctional co-solvents THF and water to provide the cleanest intermediate product streams that can allow advanced catalysts to be developed on real feedstocks instead of model compounds. For this project, we developed a hybrid catalytic process that first applies CELF homogeneous catalysis to convert solid biomass to a liquid stream containing intermediate fuel precursors (FPs) such as furfural (FF) and 5-hydroxymethylfurfural (5-HMF). Afterwards, a second heterogeneous catalytic step was then applied to selectively hydrodeoxygenate (HDO) the FPs produced from biomass into gasoline blendstocks methylfuran (MF) and dimethylfuran (DMF). Concurrently, capitalizing on CELF’s efficient lignin extraction capabilities, we further explored production C9+ cyclic hydrocarbons from biomass lignin to improve overall process economics. For the first step, the CELF process was optimized to achieve yields of >95% for FF and >60% for HMF from the xylan and glucan fractions in poplar wood, respectively. For the second step, we created a patent-pending bifunctional Cu-Ni solid catalyst that is tolerant to real product streams from the CELF process and simultaneously produce MF and DMF blendstocks at >80% yields. To provide more market versatility, we further explored the production of 2-pentanol from MF and have achieved >70% yields. During this project’s three year period, we also developed a dynamically informed technoeconomic computer model that helped to guide key project decisions that allowed us to reach a final biofuel selling price (MFSP) of <$\$$3/GGE (gallon gasoline equivalent) and total biomass carbon utilization of 60%. We also determined that the MFSP in our model could be further reduced to below $\$$2/GGE if the value of the lignin-derived aromatic hydrocarbon fuels could be sold at diesel-range prices (>$\$$500/tonne). Our process model was designed to consume 288 tonnes per day of poplar wood chips with minor consumption of hydrogen to produce a range of fuel blendstocks suitable for use in the transportation sector. The project was successful in meeting DOE EERE program criteria for application of an all-catalytic biofuels process to achieve a biofuel selling price target of <$\$$3/GGE as well as to achieve a 60% reduction in greenhouse gas emissions (GHG) compared to conventional fossil petroleum processes. At project completion, the outlined catalytic process reported total utilization of up to 60% of the carbon found in biomass, rivaling more mature biological cellulosic ethanol technologies at a fraction of the fixed and operating costs. This project also resulted in 7 peer-reviewed publications, 2 provisional inventions, and 1 patent pending. NOTE: This public version of the document contains redacted text, tables, and figures as indicated within the document.

09 BIOMASS FUELS↗

DOE OSTI2014

MAMA Software User Guide: Tips for Segmenting with MAMA

This document reviews the six ways to segment with the MAMA software. Mama is not a threshold based segmentation system, like many of the image analyses programs you may be have used in the past. The MAMA software is set up to allow you to segment iteratively, and do so in a variety of ways. Six different ways are show below. They can be used in almost any combination—sometimes the choice depends on the image, sometimes it depends on user preferences for what type of interactions a user is willing to do. In the examples below, by “easy”, we mean an image for which MAMA segmentation works great and little clean-up is needed. By hard image, we mean an image for which accurate segmentation is very challenging. Many metal micrographs, and particles with rough textures fall into this class.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Advanced Reactor Safeguards & Security Program: Cybersecurity Scenarios

The use of digital control systems and automation in advanced nuclear power systems introduces different types of vulnerabilities compared to legacy (i.e. analog) control systems that cyber adversaries can exploit. These vulnerabilities pose a challenge to reactor operators and cyber operations staff due to the dynamic nature of the event in which a human response or a lack of response can potentially evolve into a worsening plant condition. Using the Department of Homeland Security Cyber and Infrastructure Security Agency’s (CISA) critical infrastructure exercise framework, this document presents several cyber security scenarios typical of digital control systems that could be used in advanced reactor designs. These scenarios can be used in tabletop exercises to evaluate cyber security posture or conduct training on different aspects of cyber security, including detection, threat hunting using indicators of compromise, evaluating incident response, risk mitigation, incident reporting, information sharing and recovery.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Improved Cross Section Generation Capability of Griffin in FY22

The Griffin code is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor multiphysics analysis application jointly developed by Idaho National Laboratory and Argonne National Laboratory. The code includes a variety of deterministic steady-state transport solvers for fixed source, k-eigenvalue, adjoint, and subcritical multiplication as well as transient solvers for spatial dynamics with the improved quasi-static method. Griffin uses cross section data in the ISOXML format generated from external deterministic or Monte Carlo cross section generation codes. In recent years, the MC 2 -3 modules have been added to Griffin for fast reactor cross section generation, and the self-shielding application programming interface (SSAPI) was implemented in the ISOXML module for thermal reactor cross section generation. The on-the-fly slowing down method and double-heterogeneity treatment have been implemented to SSAPI and verified against particulate fuel-bearing graphite-moderated thermal reactor problems with high accuracy. This year, work has been focused on improving the cross section generation capability of ISOXML and streamlining the cross section generation procedures. In addition, the form function data were added to ISOXML in order to support the pin power reconstruction capability that was newly implemented in Griffin in this fiscal year. To facilitate the cross section generation using MC 2 -3 and SSAPI in Griffin, the cross section generation workflows have been set up for both fast and thermal spectrum reactors. The MOOSE action system tool was devised for fast spectrum problems, and the MOOSE stochastic tool was adopted to the branch calculation procedure for thermal spectrum problems. Meanwhile, to ensure the accuracy of group-constants, the thermal up-scattering kernel calculator accounting for resonance scattering was implemented in ISOXML, demonstrating the accurate computation of a Doppler-broadened scattering kernel of any Legendre order within a reasonable timescale. Other aspects of ISOXML, such as deletion solver and data, documentation, ISOXML file management, and the interface for Mixture, were improved as well.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Cyber Halo Innovation Research Program (CHIRP) Handbook: CHIRP Program Document 2026

The Cyber Halo Innovation Research Program (CHIRP) handbook outlines a comprehensive framework designed to advance space cybersecurity education, workforce development, recruitment efforts for United States Space Force (USSF) Space Systems Command (SSC) and the Department of the Airforce, and foster students’ professional growth. It provides an overview of CHIRP's objectives and strategic focus, establishing the foundation for participant engagement through a network of collaborations with academic institutions, contracted industry partners, training and certification organizations, federal agencies, and community organizations. It states a clear participation strategy for SSC and Pacific Northwest National Laboratory (PNNL) for program execution and successful support for student transition to a career in space cybersecurity.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2016

ExactPack Documentation

For code verification, one compares the code output against known exact solutions. There are many standard test problems used in this capacity, such as the Noh and Sedov problems. ExactPack is a utility that integrates many of these exact solution codes into a common API (application program interface), and can be used as a stand-alone code or as a python package. ExactPack consists of python driver scripts that access a library of exact solutions written in Fortran or Python. The spatial profiles of the relevant physical quantities, such as the density, fluid velocity, sound speed, or internal energy, are returned at a time specified by the user. The solution profiles can be viewed and examined by a command line interface or a graphical user interface, and a number of analysis tools and unit tests are also provided. We have documented the physics of each problem in the solution library, and provided complete documentation on how to extend the library to include additional exact solutions. ExactPack’s code architecture makes it easy to extend the solution-code library to include additional exact solutions in a robust, reliable, and maintainable manner.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Human-System Interface Design Review Guidelines

The U.S. Nuclear Regulatory Commission (NRC) staff reviews the human factors engineering (HFE) aspects of nuclear power plants in accordance with the Standard Review Plan (NUREG-0800, Standard Review Plan for the Review of Safety Analysis Reports for Nuclear Power Plants: LWR Edition). The Human Factors Engineering Program Review Model (NUREG-0711, Revision 3, issued November 2012) contains detailed design review procedures. As part of the review process, the interfaces between plant personnel and the plant's systems and components are evaluated for conformance with HFE guidelines. This document, Human-System Interface Design Review Guidelines (NUREG-0700, Revision 3), provides the guidelines necessary to perform this evaluation. The review guidelines address the physical and functional characteristics of human-system interfaces (HSIs). Because these guidelines only address the HFE aspects of design and not other related considerations, such as instrumentation and control and structural design, they are referred to as HFE guidelines. In addition to the review of actual HSIs, the NRC staff can use the NUREG-0700 guidelines to evaluate a design-specific HFE guidelines document or style guide. The HFE guidelines are organized into four basic parts, which are divided into sections. Part I contains guidelines for the basic HSI elements: information displays, user-interface interaction and management, and analog displays and controls. These elements are used as building blocks to develop HSI systems to serve specific functions. Part II contains the guidelines for reviewing the following HSI systems: alarm system, safety parameter display system, group-view display system, soft control system, computer-based procedure system, automation system, and communication system. Part III provides guidelines for the review of workstations and workplaces. Part IV provides guidelines for the review of HSI support (i.e., maintainability of digital systems and degraded HSI and instrumentation and control conditions).

42 ENGINEERING↗

DOE OSTI2026

Center for Integrated Simulation of Fusion Relevant RF Actuators

This project was part of the “Center for Integrated Simulation of Fusion Relevant RF Actuators” SciDAC-4 project, led by Dr. Paul Bonoli (MIT). Rather than use an acronym (CISFRRFA), the project will be referred to in this document as the “RF-SciDAC4”. The larger SciDAC-4 project goals were to: 1. Develop an integrated simulation of the antenna + sheath + scrape-off-layer + core plasma system which fully utilizes leadership class computing resources to move towards a quantitative predictive capability for the response to RF power. 2. Work closely with the SciDAC-4 Whole Device Modeling (WDM) community to make both our new code development efforts, as well as the established hierarchy of RF tools, available within their environment, and to utilize WDM technologies to implement the couplings below. 3. Validate this predictive capability on appropriately diagnosed experiments including dedicated RF test stands, linear devices, and existing tokamaks. 4. Use these tools to inform design of robust, impurity-mitigating RF heating and current drive sources for future fusion devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

Microgrid Design Toolkit (MDT) Technical Documentation and Component Summaries

The Microgrid Design Toolkit (MDT) is a decision support software tool for microgrid designers to use during the microgrid design process. The models that support the two main capabilities in MDT are described. The first capability, the Microgrid Sizing Capability (MSC), is used to determine the size and composition of a new microgrid in the early stages of the design process. MSC is a mixed-integer linear program that is focused on developing a microgrid that is economically viable when connected to the grid. The second capability is focused on refining a microgrid design for operation in islanded mode. This second capability relies on two models: the Technology Management Optimization (TMO) model and Performance Reliability Model (PRM). TMO uses a genetic algorithm to create and refine a collection of candidate microgrid designs. It uses PRM, a simulation based reliability model, to assess the performance of these designs. TMO produces a collection of microgrid designs that perform well with respect to one or more performance metrics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Review of V&V Documentation

Consortium for Advance Simulation of Light Water Reactors (CASL) is a Department of Energy Innovation Hub whose mission is the following, "CASL is a collaboration of the nation's leading scientists, institutions, and supercomputers, with an aggressive 10-year mission to confidently predict the performance of existing and next-generation commercial nuclear reactors through comprehensive, science-based modeling and simulation." The CASL program to date has focused on developing the necessary predictive capability. Rightly so, it is characterized by many as a research project. As a matter of intent, the first 6 years of CASL focused on developing and demonstrating the prediction capability of a suite of independent physics codes: MPACT (neutronics), CTH (thermal hydraulics in the core), BISON (fuel performance), and MAMBA (CRUD and boron uptake on fuel rod surfaces) The last 4 years focused on initial attempts to couple the codes and to demonstrate those capabilities through a series of challenge problems aligned to 3 key issues of interest to the nuclear power industry.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Reactivity Coefficient Measurements and Sensitivity Studies [Abstract]

Nuclear data validation is often performed today using criticality measurements. The gold standard for criticality measurements is the International Criticality Safety Benchmark Experiment Project (ICSBEP). The validation specifically focuses on the effective multiplication factor (k eff ). K eff is a relatively easy parameter to infer and has reduced uncertainty due to being at or above critical. However, while k eff is a well-documented parameter with detailed sensitivity and uncertainty analysis, it cannot be used as a standalone metric to determine inaccuracies in nuclear data (e.g., cross section data, PFNS, nu), which is based on theory, physics, and differential measurements. The Experiments Underpinned by Computational Learning for Improvements in nuclear Data (EUCLID) project aims to identify compensating errors in specific nuclear data by optimally designing experiments that are sensitive to a suite of measurement parameters beyond k eff . By identifying how each parameter's nuclear data sensitivity differs from others, experiments can be designed to constrain questionable nuclear data. One sensitivity that is of particular interest to this project includes reactivity coefficient sensitivities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗