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At least 55 records · Page 3

Sudoku Online Testing Framework v.0.2

The Sudoku Online Testing Framework provides a configurable basis for testing user interactions to solve visualization-related problems with sudoku puzzles and games. It consists of a server, a client, and test code. The python server implements sudoku puzzle logic and board selection functions. The JavaScript client implements a graphical user interface (GUI) front-end to display the puzzles and facilitate interactions with users. Within the GUI, logical rules may be selected. Cells may be selected to “pivot” on to make a board for each possible value in the cell. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-6409 O

Leger, Michelle↗

Sequential Training ToolKit - STTK

Sequential Training ToolKit, or STTK, is a software toolkit plugin for the Unity development platform that enables software developers to easily develop structured Sequential Training applications for gaming and extended reality (XR) environments. STTK is architected to easily import the toolkit as a plugin for the Unity platform and then interact with the graphical user interface (GUI) for drag-and-drop functionality. STTK also includes easy add-on plugins for Prefabs and auto-builds a State Machine. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-3059 O

Klein, BrandonThorin↗

Coincidence Doppler Broadening Analysis Program

A graphical user interface (GUI) that helps analyze data from coincidence Doppler broadening positron annihilation spectroscopy. It is a quick tool to rapidly reduce large data and conveniently analyze multiple datasets.

Watkins, JosephM.↗

ISO 15118 Node-Red Dashboard

This is a graphical user interface (GUI) that can be deployed in a Node-RED environment and be configured to provide monitoring and control of an ISO 15118 EV Charger (DC or AC).

Harper, Jason↗

ORNL Slicer 2 - Open Source Copyright

ORNL Slicer 2 is a slicing program for additive manufacturing. It takes a solid body mesh object, typically as .STL file, and converts that into machine readable instructions, called g-code, that a 3D printer can use to build the object. The functionality includes loading and positioning an object, slicing it into layers, fitting toolpaths to the layers, and outputting g-code to construct the object. All of this is contained within a graphical user interface (GUI) that allows the user to define all of the settings specific to their machine and process, then preview the resultant g-code before starting the printing process.

Roschli, Alex (0000000213084632)↗

phenix v. 7.0

SAND2021-6741 O phenix is Sandia's orchestration tool that allows users to quickly deploy, un-deploy, and interact with SCEPTRE ICS environments. phenix is an orchestration tool used for managing the creation, configuration, and deployment of modeling and simulation environments. As an abstraction layer on top of an underlying virtual machine manager called minimega, phenix organizes the network, application, and scenario information for a given deployment. It allows users to create, configure, and deploy experiments in a repeatable and rapid fashion. An application framework provides the flexibility to manipulate an experiment to suit various needs and requirements. phenix also includes a web-based graphical user interface (GUI) where experiments can be created, configured, and interacted with.

Sahakian, Meghan↗

System Validation Platform Working Directories

A suite of software tools used to interface with power electronic equipment for laboratory testing and device certification. They are typically used as equipment drivers with using the System Validation Platform (SVP) graphical user interface (GUI). Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-1185 O

Johnson, JayT↗

Imaging Bragg Edge Analysis TooLs for Engineering Structures (iBeatles)

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) provides pulsed neutrons with energies varying from epithermal to cold. In preparation for VENUS, the neutron imaging beamline to be located at beam port 10, we have performed a series of experiments focused on wavelength-dependent radiography and computed tomography for a broad range of applications, from materials science to biological tissues.One of the time-of-flight (TOF) techniques that is of interest to the scientific community is the 2-dimensional mapping of phases and average crystalline plane orientation in samples both ex-situ and during applied stresses such as tensile loading and heating. This technique is known as Bragg edgeimaging and relies on the identification of changes of transmission values, fitting of the edge to measure its displacement, and thus identify the shift in lattice parameter due to stresses. One of the challenges of TOF imaging measurements is the amount of data and the inability to observe Bragg edge shifts in real time during an experiment. Thus, we have been focusing on creating a Python-based interface that allows fast data processing and instantaneous mapping and fitting of the Bragg edges, and their evolution through time. Python libraries and Jupyter notebooks have been implemented to facilitate decision making during an experiment. The advantage of the notebooks is the possibility to guide an experiment as they can quickly process and display Bragg edge data. These notebooks can be used independently, or can be combined in a Python Graphical User Interface (GUI) tool called iBeatles. This interface permits visualization and fitting of the Bragg edges, and ultimately back-projects the fitting results onto the radiographs to display a strain map. Assuming data collection has sufficient statistics, the strain mapping analysis can be performed on a pixel-by-pixel basis. This development is a step forward toward a better user experience at the future VENUS beamline in terms of live feedback and productivity. Analysis that used to take days of switching between different applications can now be done in minutes within the

Bilheux, JeanChristophe [Oak Ridge National Labora↗

Coreii - Scout

COREII Scout employs React, Vite, TypeScript, Tailwind, and Daisy UI for its graphical user interface (GUI), offering both dark and light modes. The code is modular, with components and reusable wrappers to enhance efficiency. The primary goal of COREII Scout is to aid analysts in collecting and analyzing various sources related to cyber attacks, utilizing models to automate the report writing process. It uses Named Entity Recognition (NER), a type of Natural Language Processing (NLP), to extract key entities from each source. Analysts review and classify these entities using the COREII Attack Chain Estimator (ACE), adding their comments. Ultimately, a Large Language Model (LLM) generates a detailed report with user guidance. This setup ensures a streamlined and effective approach to cyber attack analysis and reporting.

Pluth, Adam [Idaho National Laboratory (INL), Idah↗

Dynamic Contingency Analysis Tool 2.0 User Manual with Test System Examples

This document introduces Version 2 of the Dynamic Contingency Analysis Tool (DCAT) software package developed by Pacific Northwest National Laboratory and serves as a guide for using this package to conduct cascading failure simulations for the electric power system. The DCAT is an open-platform and publicly available software; it is intended to help develop applications that aim to improve the capabilities of power system planning engineers to assess the impact and likelihood of extreme contingencies and potential cascading events across their systems and interconnections. Outputs from the DCAT will support finding mitigating actions to reduce the risk of cascading outages in technically sound and effective ways. This manual provides detailed instructions on how to use this tool on multicore Windows workstations or servers. In the public version of DCAT, several improvements have been made over the previous version: (1) it was modularized; (2) a graphical user interface (GUI) was developed; (3) a new version of the MPjobs parallel processing module was incorporated; and (4) a batch-processing function was added. The features of the DCAT GUI are described, including some examples of how to use the GUI to perform simulations. A full explanation of the DCAT methodology is available in the Phase 1 report.

24 POWER TRANSMISSION AND DISTRIBUTION↗

KENO V.a Primer: Performing Calculations using SCALE’s Criticality Safety Analysis Sequence (CSAS5) with Fulcrum

The SCALE code system developed at Oak Ridge National Laboratory is widely used and accepted around the world for criticality safety analyses. The well-known KENO V.a three-dimensional Monte Carlo criticality computer code is one of the primary criticality safety analysis tools in SCALE. The KENO V.a primer is designed to help a new user understand and use the SCALE/KENO V.a Monte Carlo code for nuclear criticality safety analyses. It assumes that the user has a college education in a technical field. There is no assumption of familiarity with Monte Carlo codes in general or with SCALE/KENO V.a in particular. The primer is designed to teach by example, with each example illustrating two or three features of SCALE/KENO V.a that are useful in criticality analyses. The primer is based on SCALE 6.2 and 6.3, which includes the Fulcrum graphical user interface (GUI). Each example uses Fulcrum to provide the framework for preparing input data and viewing output results. Starting with a Quickstart section, the primer gives an overview of the basic requirements for SCALE/KENO V.a input and allows the user to quickly run a simple criticality problem with SCALE/KENO V.a. The sections that follow Quickstart include a list of basic objectives at the beginning that identifies the goal of the section and the individual SCALE/KENO V.a features that are covered in detail in the sample problems in that section. Upon completion of the primer, a new user should be comfortable using Fulcrum to set up criticality problems in SCALE/KENO V.a. The primer provides a starting point for the criticality safety analyst who uses SCALE/KENO V.a. Complete descriptions are provided in the SCALE/KENO V.a manual. Although the primer is self-contained, it is intended as a companion volume to the SCALE/KENO V.a training and documentation. The SCALE manual and training schedule are available at https://scale.ornl.gov. The primer provides specific examples of using SCALE/KENO V.a for criticality analyses; the SCALE/KENO V.a manual provides information on the use of SCALE/KENO V.a and all its modules. The primer also contains an appendix with sample input files. In addition, this primer, its errata and sample inputs are also available at https://code.ornl.gov/scale/primers/kenova.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

NMDQi Thermal-hydraulic Optimization, Analysis, and Scoping Tool (TOAST)

The Thermal-hydraulic Optimization, Analysis, and Scoping Tool (TOAST) is developed to support the thermal-hydraulic aspects for the design of optimal irradiation vehicles for the Nuclear Materials Discovery and Qualification initiative (NMDQi). TOAST is currently a MATLAB-based tool that utilizes a simplified steady-state analytical model where a radial thermal resistance circuit is utilized to account for conduction through up to 2 capsules, a gas gap, a thermal bond, a sample cladding, and a sample, as well as the convection from a water coolant outside the capsules. The geometry is discretized axially along the user-defined height of a basket with a user-defined number of points/nodes, essentially turning TOAST into a semi-2D heat transfer analysis utility for cylindrical irradiation vehicles with practically any configuration, solving for temperatures radially at multiple axial locations. TOAST utilizes a Graphical User Interface (GUI) in-which a user can define the geometrical layout, the materials utilized for each component, the coolant characteristics, and the required solution. The user can define the geometry by inputting the diameters, thicknesses, and heights for each component, whereas the materials are defined via the user-provided constant or variable thermal conductivities. The user can select the coolant's inlet temperature, pressure, and the pressure drop across the height of the problem (which is used to calculate the velocity of the flow). Finally, the user can choose to solve for a sample heat generation rate limit by inputting temperature limits for the sample and capsules or can choose to purely solve for the axial temperature distributions of each component by inputting a pre-selected heat generation rate. Either way, TOAST provides the user with axial temperature distributions of all the components including the coolant, and the heat generation rate limit as well as the maximum outlet coolant temperature. The user can also choose to do one of 6 sensitivity analyses in TOAST. The sensitivity analyses yield plots of the sensitivity of the heat generation rate limit, the maximum coolant temperature, and the pressure limit for the annular components due to perturbations in 1-2 unknown variables based on the selected sensitivity analysis. Benchmarks between computations in TOAST and equivalent 2D axis symmetric ABAQUS models are presented, showing that TOAST results are within less than 3% of ABAQUS results in most cases, and a maximum of 8% difference in some cases. The benchmarks also revealed that this uncertainty is tied to the selection of an appropriate Nusselt number correlation and appropriate thermal conductivities, which the user can do from the GUI. Regardless, TOAST is demonstrated as a computationally efficient, highly accessible, and accurate utility for optimization and scoping s of studies different irradiation vehicles.

42 ENGINEERING↗

Prototype Distributed Ledger Technology of UF 6 Cylinder Tracking in Ethereum

We have created a demonstration permissioned Distributed Ledger Technology (DLT) datastore for the UF 6 cylinder tracking safeguards use-case utilizing the Ethereum DLT framework and using Solidity for smart contract code. Our demonstration creates a simulated dataset representing tracking of 75,000 UF 6 cylinders across 11 example nuclear facilities worldwide. Our DLT system allows for easy input and reading of shipping and receiving data, including a Graphical User Interface (GUI). Sandia’s Emulytics capability was leveraged to help create the DLT node network and assess performance. We find that our DLT prototype can easily handle to ~150,000 UF 6 cylinder shipments per year worldwide, without any excessive computational or storage burden on the IAEA or Member States. Next steps could include a demonstration to the IAEA and potentially demonstrating integration with TradeLens, a DLT in use by a consortium of international shipping companies representing over half of world shipping trade.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

VERAIO Software Management Plan

VERAIO is a set of utility codes used to provide a common set of input and outputs to the Virtual Environment for Reactor Applications (VERA). VERA is a collection of several different computer codes that all have a common input and output. This prevents the need to manage input and output from each individual code, allowing for ease of use and reducing errors associated with code operability. The VERAIO utilities include VERAIn, VERAView, and VERARun. Each of these utilities is described below. VERAIn is an input processor that reads an ASCII input file generated by users, parses the file, performs some error checking, and writes an XML file to be read by other VERA codes. The main purpose of VERAIn is to provide a common input to all of the VERA codes so users only need to learn one input. VERAIn is written in Perl and uses YAML configuration files to provide flexibility. VERAView is a graphical user interface (GUI) that reads a VERA HDF output file and allows users to visualize results. VERAView is written in Python. VERARun is a script that drives the VERA execution in a high performance computing (HPC) environment. Work performed at the code level supports the Quality Assurance Program Plan (QAPP) (VERA-QA-001), and VERA Software Quality Assurance Plan (VERA-QA-002).

97 MATHEMATICS AND COMPUTING↗

NEAMS Workbench MOOSE Integration Update

The Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench is a graphical user interface (GUI) that provides a common analysis environment for the accelerated use of the NEAMS toolkit. To improve design and analysis of current and future nuclear energy systems, the NEAMS Workbench provides an integrated development environment for model creation, review, execution, output review, and visualization for integrated tools. In addition to a GUI, the NEAMS Workbench provides the Workbench Analysis Sequence Processor, an open-source tool set that facilitates input-content assistance for supported domain-specific input languages and user-friendly syntaxes. These supported syntaxes enable accelerated development and deployment of enhanced user inputs and workflows. The Multiphysics Object-Oriented Simulation Environment (MOOSE) has been supported in the NEAMS Workbench since 2016 and receives continuous updates. Efforts to improve MOOSE-based tool integration in the NEAMS Workbench are ongoing. This document details the current and planned enhancements of the NEAMS Workbench and the MOOSE framework to improve integration and usability of MOOSE-based applications within the NEAMS Workbench.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Real-Time Drilling Optimization System for Improved Overall Rate of Penetration and Reduced Cost Per Foot in Geothermal Drilling

The key to success in geothermal drilling is economic feasibility, and a major cost in the development of geothermal resources is the actual drilling of the wells. In this project, a real-time drilling optimization system for geothermal drilling was developed. The system couples three individual components while drilling. The first component is a drill stem vibration analysis model, the second is Mechanical Specific Energy (MSE) analyses, and the third is a detailed PDC Rate of Penetration (ROP) drill bit model for optimum RPM and WOB combinations. The benefit of the coupled system is that the range of WOB and RPM could be selected to avoid drill stem vibrations. Secondly, MSE is used as an efficiency measure and the detailed PDC drill bit model ensures the drill bit does not endure temperatures that exceed the temperature at which the PDC cutters experience accelerated wear. The new detailed PDC bit model is based on rock/bit interaction that physically tracks the PDC cutter wear flats as the bit drills ahead giving the capability to calculate the temperature being generated underneath the worn cutters to better advise on operational parameters to avoid accelerated cutter wear and failure and to ensure that operational parameters are applied so that overall ROP is maximized. By combining the drill stem vibrations and the detailed PDC bit cutter wear and “safe” non-accelerated cutter wear temperature and optimum ranges of operating parameters, it results in higher ROP and lower cost drilling. Single cutter PDC testing performed in different lithologies at Sandia was utilized to verify the PDC cutter forces and depth of cut for new and worn cutters. Based on single cutter PDC temperature modeling, verification using single cutter data from the testing done by National Oilwell Varco (NOV) was performed. Sandia’s Hard-Rock Drilling Facility (HRDF) was utilized to test different drill bit configurations with different cutter designs and wear status with different induced modes of vibration to obtain the critical bit RPM/WOB ranges resulting in ineffective drilling and low ROP. The collected test data were further used to verify and calibrate the full hole PDC ROP model that was developed based on single cutter interaction data. A full coupled drill stem vibration model was formulated and verified with geothermal field data from the Chocolate Mountain Aerial Gunnery Range (CMAGR). A graphical user interface (GUI) was developed using Tkinter library in the computer programming language Python, which integrates all the developed models in one system. The developed system consists mainly of the PDC ROP model, PDC bit wear model, PDC cutter temperature model, Mechanical Specific Energy (MSE) model, and drillstring vibration model integrated into one system. The developed system can be used for both, post well analysis and real-time optimization using different criteria such as ROP maximization or MSE minimization. The software uses Differential Evolution Algorithm (DEA) to find optimum values for operational parameters based on last foot drilled while avoiding the drillstring vibration and cutter temperature critical operating parameters.

15 GEOTHERMAL ENERGY↗

CO 2 Storage prospeCtive Resource Estimation Excel aNalysis (CO 2 -SCREEN) User’s Manual: Python_V4.1

This user’s manual guides the use of the National Energy Technology Laboratory’s (NETL) CO 2 Storage prospeCtive Resource Estimation Excel aNalysis (CO 2 -SCREEN) tool, which was developed to aid users in screening geologic formations for prospective CO 2 storage resources. This manual is specific to the CO 2 -SCREEN 4.1 version which is based in Python. The 4.1 version of CO 2 -SCREEN adds in newly updated storage efficiency factors for saline formations. CO 2 -SCREEN applies U.S. Department of Energy (DOE) methods and equations for estimating prospective CO 2 storage resources for saline formations, shale formations, and residual oil zones (ROZ). CO 2 -SCREEN was developed to be substantive and user-friendly and provide a consistent method for calculating prospective CO 2 storage resources. CO 2 -SCREEN uses a Java- based graphical user interface (GUI) for data inputs and uses Python to calculate prospective CO 2 storage resources.

54 ENVIRONMENTAL SCIENCES↗

Produced Water-Economic, Socio, Environmental Simulation Model (PW-ESEim) Model: Proof-of-Concept for Southeastern New Mexico

A proof-of-concept tool, the Produced Water-Economic, Socio, Environmental Simulation model (PW-ESESim), was developed to support ease of analysis. The tool was designed to facilitate head-to-head comparison of alternative produced water source, treatment, and reuse water management strategies. A graphical user interface (GUI) guides the user through the selection and design of alternative produced water treatment and reuse strategies and the associated health and safety risk and economic benefits. At the highest conceptual level, alternative water strategies include the selection of a source water (locally or regionally available produced water), treatment strategy (pre-treatment, physical, chemical, biological, desalination, and post-treatment processes) and product water purpose (e.g., irrigation, industrial processing, environmental). After selection of these details, the PW-ESESim output a number of key economic, societal, environmental, public/ecological health and safety metrics to support user decision-making; specific examples include, cost of treatment, improvements in freshwater availability, human and ecologic health impacts and growth in local jobs and the economy. Through the simulation of different produced water treatment and management strategies, tradeoffs are identified and used to inform fit-for-purpose produced water treatment and reuse management decisions. While the tool was initially designed using Southeastern New Mexico (Permian Basin) as a case study, the general design of the PW-ESESim model can be extended to support other oil and gas regions of the U.S.

54 ENVIRONMENTAL SCIENCES↗