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At least 1,585 records · Page 88

A Bottom-Up Cost Estimation Tool for Nuclear Microreactors

The rising interest in nuclear microreactors has highlighted the need for comprehensive technoeconomic assessments. However, the scarcity of publicly available designs and cost data has posed significant challenges. To address this issue, the Microreactor Optimization Using Simulation and Economics (MOUSE) tool is developed. MOUSE is a tool that integrates nuclear microreactor design with reactor economics. The design calculations encompass core simulations using the OpenMC Monte Carlo Particle Transport Code [romano2015], along with simplified balance of plant calculations. On the economic side, MOUSE provides detailed bottom-up cost estimates, calculating both the total capital cost and the levelized cost of energy for first-of-a-kind and nth-of-a-kind microreactors. The cost estimation correlations are developed using data from the MARVEL project and additional literature sources. MOUSE has released as an open-source tool on GitHub (MOUSE Tool). By combining design calculations with cost equations, MOUSE enables users to evaluate the impact of various technological consideration, advanced moderators, design changes, material/fuel changes, and geometry modifications—as well as economic parameters like interest rates and construction duration. This comprehensive framework can guide stakeholders towards technological solutions that enhance microreactor competitiveness. Additionally, powered by the WATTS toolkit [romano2022], MOUSE supports optimization studies, parametric analyses, and uncertainty calculations/propagation. Currently, preconceptual designs of three microreactor types are included in MOUSE: a liquid metal thermal microreactor (LTMR), gas cooled TRISO-fueled microreactor (GCMR) and heat-pipe TRISO fueled microreactor (HPMR). To showcase its ability, MOUSE was used to conduct detailed bottom-up cost estimates for the first of a kind (FOAK) and Nth of a kind (NOAK) of the following microreactors • A 20MWt LTMR that is built on the ongoing MARVEL demonstration at Idaho National Laboratory (INL) • A 15 MWt GCMR that was designed to be more representative of the typical commercial microreactor • A 7 MWt HPMR that was built on previous work (Choi 2024) The The reader should note that these three designs and corresponding cost estimates are examples to demonstrate the MOUSE capability. The designs are pre-conceptual, the reactor designs were not optimized, and the cost estimates were developed with incomplete information. Additionally, stakeholders might be interested in a variety of designs that may differ from the examples provided in this report. The MOUSE tool can also be used to study how design choices affect economics. To demonstrate its capability, MOUSE was used conduct parametric studies such as examining the economic impact of the reflector's material and thickness, the moderator's booster material and dimensions, fuel composition and enrichment, core size, and power level. Several insights were gained from these parametric studies.

Hanna, Botros↗

SYS-5620-Project - Achieving Robust Laser Performance utilizing Historical Shot Experiments - A Systems Engineering Proposal

The National Ignition Facility (NIF) at Lawrence Livermore National Laboratory precisely guides, amplifies, reflects, and focuses 192 powerful laser beams into a target about the size of a pencil eraser in a few billionths of a second, delivering more than 2 million joules of ultraviolet energy and 500 trillion watts of peak power. A crucial goal of the system is to trigger precise implosions of fuel capsules. This is achieved by delivering all 192 beams at user-specified times and locations on the target, minimizing any deviation from the requested performance. Power requirements can vary substantially on each experiment and the facility supports numerous amplifier pumping configurations and their attendant nonlinear effects. To achieve the tight performance required across such a broad array of configurations, constant comparison of measured and requested power delivery are tracked and long-term trends analyzed as a guide to understanding future performance. A very common question asked is given the current state of the laser today – how well would a similar experiment from the past perform today? Additionally, if one were to specify an alternate amplifier configuration using today’s model would and damage limits be exceeded and would there be an increase in performance. The physics model used to make these predictions and equipment protection checks is called the Virtual Beamline (VBL). VBL is used with an incoming desired pulse shape and energy to be delivered on target, and then does an iterative solve to predict the needed injected pulse in the front-end of the system to achieve this result. To effectively guide and predict future NIF experiment performance, laser scientists explore current amplifier configurations and compare them with historical data utilizing a tool called the Reverify Toolbox.

42 ENGINEERING↗

Visual feedback and guided balance training in an immersive virtual reality environment for lower extremity rehabilitation

Balance training is essential for physical rehabilitation procedures, as it can improve functional mobility and enhance cognitive coordination. However, conventional balance training methods may have limitations in terms of motivation, real-time objective feedback, and personalization, which a virtual reality (VR) setup may provide a better alternative. In this work, we present an immersive VR training environment for lower extremity balance rehabilitation with real-time guidance and feedback. The VR training environment immerses the user in a 3D ice rink model where a virtual coach (agent) leads them through a series of balance poses, and the user controls a trainee avatar with their own movements. Here we developed two coaching styles: positive-reinforcement and autonomous-supportive, and two viewpoints of the trainee avatar: first-person and third-person. The proposed environment was evaluated in a user study with healthy, non-clinical participants (n = 16, 24.4 ± 5.7 years old, 9 females). Our results show that participants showed stronger performance in the positive-reinforcement style compared to the autonomous-supportive style. Additionally, in the third-person viewpoint, the participants exhibited more stability in the positive-reinforcement style compared to the autonomous-supportive style. For viewpoint, participants exhibited stronger performance in the first-person viewpoint compared to third-person in the autonomous-supportive style, while they were comparable in the positive-reinforcement style. We observed no significant effects on the foot height and number of mistakes. Furthermore, we report the analysis of user performance with balance training poses and subjective measures based on questionnaires to assess the user experience, usability, and task load. The proposed VR balance training could offer an interactive, adaptive, and engaging environment and open new potential research directions for lower extremity rehabilitation.

97 MATHEMATICS AND COMPUTING↗

HALE UAS Concept of Operations. Version 3.0

This document is a system level Concept of Operations (CONOPS) from the perspective of future High Altitude Long Endurance (HALE) Unmanned Aircraft Systems (UAS) service providers and National Airspace System (NAS) users. It describes current systems (existing UAS), describes HALE UAS functions and operations to be performed (via sample missions), and offers insight into the user s environment (i.e., the UAS as a system of systems). It is intended to be a source document for NAS UAS operational requirements, and provides a construct for government agencies to use in guiding their regulatory decisions, architecture requirements, and investment strategies. Although it does not describe the technical capabilities of a specific HALE UAS system (which do, and will vary widely), it is intended to aid in requirements capture and to be used as input to the functional requirements and analysis process. The document provides a basis for development of functional requirements and operational guidelines to achieve unrestricted access into the NAS. This document is an FY06 update to the FY05 Access 5 Project-approved Concept of Operations document previously published in the Public Domain on the Access 5 open website. This version is recommended to be approved for public release also. The updates are a reorganization of materials from the previous version with the addition of an updated set of operational requirements, inclusion of sample mission scenarios, and identification of roles and responsibilities of interfaces within flight phases.

Source record↗

Adaptive Fault Tolerance for Many-Core Based Space-Borne Computing

This paper describes an approach to providing software fault tolerance for future deep-space robotic NASA missions, which will require a high degree of autonomy supported by an enhanced on-board computational capability. Such systems have become possible as a result of the emerging many-core technology, which is expected to offer 1024-core chips by 2015. We discuss the challenges and opportunities of this new technology, focusing on introspection-based adaptive fault tolerance that takes into account the specific requirements of applications, guided by a fault model. Introspection supports runtime monitoring of the program execution with the goal of identifying, locating, and analyzing errors. Fault tolerance assertions for the introspection system can be provided by the user, domain-specific knowledge, or via the results of static or dynamic program analysis. This work is part of an on-going project at the Jet Propulsion Laboratory in Pasadena, California.

fault tolerance↗

PAGOSA Mesh Block Calculator

A method for automatically generating the “mesh namelist block” portion of a PAGOSA input file, which specifies the boundaries and zone sizes of the computational mesh, has been developed. This application standardizes the mesh block for 2-, and 3-dimensional problems and is computed after the user specifies the extent and resolution of the mesh and the number of processors which will be used to run the problem. The inputs may be provided directly through a series of command-line guided questions, or a separate input file. The mesh block is written to both standard output and to disk.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Dial-A-Cluster User Manual

The Dial-A-Cluster (DAC) model allows interactive visualization of multivariate time series data. A multivariate time series dataset consists of an ensemble of data points, where each data point consists of a set of time series curves. The example of a DAC dataset used in this guide is a collection of 100 cities in the United States, where each city collects a year's worth of weather data, including daily temperature, humidity, and wind speed measurements.

97 MATHEMATICS AND COMPUTING↗

MCNP6.3 Code and Nuclear Data Installation Guide [Slides]

This presentation discusses the MCNP6.3 release package and examines how it offers more MCNP6-specific executables and options available than ever before. It also discusses the installer and that it streamlines the MCNP6.3 installation and automatically downloads all production nuclear data and generates xsdir files for the user. Additionally, the nd_manager is also discussed regarding how it allows the LANL Nuclear Data and Monte Carlo teams to work and distribute their products independently. It also allows updates, fixes (errata), and newly released data to be made available in a much faster timescale than ever before.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

A summary of Michigan program for earth resource information systems

A summary and guide to the development of earth resources information systems which employ multispectral remote sensing are reported. Major areas of activities center on improved throughput parallel processing systems, improved processing techniques, practical use of techniques in user applications, and improved sensors. Cost effectiveness considerations point to signature extension, parallel processing all-digital computers, and airborne multispectral imaging radar as some of the improvement technologies.

Erickson, J. D.↗

Using bibliographic databases in technology transfer

When technology developed for a specific purpose is used in another application, the process is called technology transfer--the application of an existing technology to a new use or user for purposes other than those for which the technology was originally intended. Using Bibliographical Databases in Technology Transfer deals with demand-pull transfer, technology transfer that arises from need recognition, and is a guide for conducting demand-pull technology transfer studies. It can be used by a researcher as a self-teaching manual or by an instructor as a classroom text. A major problem of technology transfer is finding applicable technology to transfer. Described in detail is the solution to this problem, the use of computerized, bibliographic databases, which currently contain virtually all documented technology of the past 15 years. A general framework for locating technology is described. NASA technology organizations and private technology transfer firms are listed for consultation.

Huffman, G. David↗

NASA Platform for Autonomous Systems (NPAS)

NASA Platform for Autonomous Systems (NPAS) is a disruptive software platform and processes being developed by the NASA Stennis Space Center (SSC) Autonomous Systems Laboratory (ASL). Autonomous operations are critical for the success, safety and crew survival of NASA deep space missions beyond low Earth orbit, including the Gateway, and for the future of cost-effective ground mission operations. NPAS represents the embodiment of an innovative paradigm for “thinking” autonomy in contrast to brute-force autonomy. NPAS uniquely addresses the requirements and integrates the primary functionalities for autonomous operations, in one platform that includes: (1) Integrated System Health Management (ISHM); (2) autonomy strategies, guided by system health and concepts of operations; (3) domain objects (system elements) and infrastructure to create complete application domain knowledge models (4) infrastructure to create, schedule, and execute mission plans; (5) infrastructure to develop user interfaces for comprehensive awareness; and (6) infrastructure to integrate distributed autonomous applications across networks. NPAS is a single platform that can be used to make any system operate with any desirable degree of autonomy, as well as provide comprehensive system awareness to operators and users.

Figueroa, Fernando↗

The QUIC Start Guide (V.6.4.9)

QUIC stands for the Quick Urban & Industrial Complex (QUIC) dispersion modeling system. QUIC is a fast response urban dispersion model that runs on a laptop. QUIC is comprised of a 3D wind field model called QUIC-URB, a transport and dispersion model called QUIC-PLUME, and graphical user interface called QUIC-GUI. QUIC also includes QUIC-PRESSURE to solve for pressure fields in and around buildings, a population exposure assessment tool called QUIC-POP, and an indoor infiltration calculator for computing indoor concentrations. Transport and dispersion for different types of airborne contaminants can be computed on building to neighborhood scales in tens of seconds to tens of minutes. QUIC will never give perfect answers, but it will account for the effects of buildings in an approximate way and provide more realism than non-building aware dispersion models.

97 MATHEMATICS AND COMPUTING↗

High-fidelity multiphysics load following and accidental transient modeling of microreactors using NEAMS tools: Application of NEAMS codes to perform multiphysics modeling analyses of micro-reactor concepts

The feasibility of modeling microreactors using high-fidelity models with the Nuclear Energy Advanced Modeling and Simulation (NEAMS) tools is investigated in this report. Three overarching questions guided this research: can NEAMS tools readily be applied for high-fidelity multiphysics modeling of different types of transients in microreactor designs; how accurate are the results obtained; and are improvements needed in accuracy or user experience of NEAMS tools, especially considering newly developed capabilities? This work builds upon FY-2022 work, and two microreactor concepts considering heat pipe (HP-MR) and gas-cooled (GC-MR) technologies were further analyzed using high-fidelity multiphysics simulations. The NEAMS tools considered and coupled within the MultiApp environment are Griffin for neutronics, BISON for thermo-mechanics, Sockeye for heat pipe modeling (in HP-MR), SAM for 1D Fluid – 3D solid modeling of coolant channels and system modeling of balance of plant components (in GC-MR), and the SWIFT code for hydrogen redistribution in hydride moderator. The Heat Pipe MicroReactor (HP-MR) concept was further analyzed in FY-2023 to demonstrate the stochastic TRISO failure modeling capability in BISON to check operational limits of the TRISO fuel. A new full-core Gas-Cooled MicroReactor (GC-MR) model was developed based on the initial assembly-model used in Y-2022 and used for steady-state and accidental depressurization transient simulations. Accuracy of the simulations performed was assessed through 1) verification analyses completed on the different physics with code-to-code comparison, and 2) validation of the multiphysics simulations based on modeling of the Kilopower Reactor Using Stirling Technology (KRUSTY) experiment. In FY-2023, the mesh and model of KRUSTY was updated to closely match publicly available data, and the neutronic model was verified and validated against experimental control rod worth measurements. The multiphysics model of KRUSTY was developed and used for steady-state analysis and for modeling reactivity insertion transient. The calculated power increase and stabilization agrees well with experimental data following adjustment in fuel thermal expansion coefficient. As an important component of this project, the ANL team gathered experience with a wide range of NEAMS tools: the MOOSE Mesh System, Griffin, BISON, SWIFT, Sockeye, SAM, Workbench, and the MOOSE MultiApp System, and provided assessment of new capabilities. Noteworthy are the user assessment of the “vapor-only” flow model in Sockeye and development of a multiphysics startup transient in HP-MR unit cell for use as tutorial in Sockeye. The full-core GC-MR model was used for assessment of SAM for balance of plant modeling and for demonstrating the SWIFT code capability for hydrogen redistribution modeling in multiphysics transient analyses. In this process, several bugs/issues were identified and reported to developers. Finally, the assembly GC-MR model developed in FY-2022 coupling Griffin, BISON and SAM through flow blockage and rod ejection transients was published to the National Reactor Innovation Center (NRIC) Virtual Test Bed (VTB). The Heat Pipe MicroReactor (HP-MR) concept high-fidelity multiphysics coupling of Griffin/BISON/Sockeye in load-following and heat pipe failure transients was also published on the VTB. Those submissions are enabling thorough review of these models as well as wide distribution to industry, regulator, and university users. In this analysis, several new research questions were uncovered, and follow-up analyses are recommended to further improve some models, consider additional transients, and continue development of VTB models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files

This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a fictional power plant. A forecast was produced using the GOOML data model framework and fictional input data, and a genetic optimization is included which determines optimal flash plant parameters. The inputs and outputs associated with the forecast and genetic optimization are included. The input and output files consist of data, configuration files, and plots. A link to the Physics-Guided Neural Networks (phygnn) GitHub repository is also included, which augments a traditional neural network loss function with a generic loss term that can be used to guide the neural network to learn physical or theoretical constraints. phygnn is used by the GOOML framework to help integrate its machine learning models into the relevant physics and engineering applications. Note that the data included in this submission are intended to provide a demonstration of GOOML's capabilities. Additional files that have not been released to the public are needed for users to run these models and reproduce these results. Units can be found in the readme data resource.

15 GEOTHERMAL ENERGY↗

General Applications for Hamilton Vantage (GenApps for Vantage) v0.6.1

General applications for Hamilton Vantage is a flexible liquid handling method used to automate the most widely applicable types of automated liquid transfers. General applications can also be used as a tool to onboard new fully-automated workflows by breaking them down step by step into single transfers. The goal of General Applications is to make using the Hamilton Vantage liquid handler as easy & practical as using a handheld pipette for the end user. The software supports plate-to-plate transfers for a variety of method types including: Stamp: One-to-One, Stamp: One-To-Many, Split, Combine, Hitpick, and Qtray plating. General Applications eliminates the need for automation engineers to customize individual methods for each new workflow that gets onboarded. Steps can be customized within GenApps according to the needs of the researcher. The software utilizes a GUI to prompt the users to input variables – Allowing for flexible control over plate types, transfer volumes, number of replicates, tip types, liquid classes, mixing steps, aspiration/dispense heights and more. General Applications also generates a deck image and setup instructions to guide the researcher on how to load the deck and start the instrument.

Yoder, Sam↗

Prioritizing Aquatic Science and Applications Needs in the Chesapeake Bay for a Space-Borne Hyperspectral Mission

The Chesapeake Bay is the largest estuary in North America, benefiting a growing population through its ecosystem services, fishing, recreations, and transportation routes. Studies indicate the health of the Bay as seen some improvement in recent years, yet threats to its health persist (e.g. warming, pollution nutrient run-off). Increasing human activities in coastal regions requires constant vigilance by agencies managing water quality, to ensure the safety of the population. Since April 2018, an interagency working group has been meeting monthly and a daylong workshop was convened with science and applications stakeholders around the overall theme of monitoring water quality from space. Current ocean color images indicate bloom locations used to guide in situ sampling efforts, despite limited spatial, spectral and temporal resolution. High resolution hyperspectral remote sensing provides a potential opportunity to measure additional indicators of ecological health and water quality. Assessing the needs of the aquatic user community around the Chesapeake Bay will inform science and applications recommendations during the current architecture study for a Surface Biology and Geology (SBG) Mission, as well as future scoping studies of other coastal and inland water bodies.

Schollaert Uz, Stephanie↗

Guiding Integration of Formal Verification in Assurance Cases

Assurance cases are being increasingly acknowledged as away to build trust in complex systems with autonomous capabilities. An assurance case is a comprehensive, defensible, and valid justification that a system will function as intended for a specific mission and operating environment. Formal verification is often reserved for the most critical components of such systems. However, formal verification tools are often complex, and their usage is subject to many constraints and contextual dependencies. This can raise challenges both for performing the verification as well as reflecting the verification results appropriately in the assurance case, especially for non-expert users of the verification tool. To address these challenges, we present a tool-supported methodology for integrating formal verification results in an assurance case by capturing key verification method information in a rigorously constructed assurance case. In particular, we capture the tool specification in terms of its inputs, outputs, and assurance constraints as assumptions over inputs and guarantees provided over its outputs. The tool specification is parametrized over the inputs and outputs to both guide the intended application of the tool, as well as to check that the tool has been applied following the stated assumptions and that the guarantees hold. We define a generic tool assurance argument pattern that enables integration of the verification results in the assurance case by allowing custom refinement and automated instantiation for each tool use. We demonstrate our methodology on two formal verification tools and their applications to the verification of neural network properties for the aircraft domain.

Assurance Cases↗