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At least 1,099 records · Page 61

SU-E-T-29: A Web Application for GPU-Based Monte Carlo IMRT/VMAT QA with Delivered Dose Verification

Purpose: To enable an existing web application for GPU-based Monte Carlo (MC) 3D dosimetry quality assurance (QA) to compute “delivered dose” from linac logfile data. Methods: We added significant features to an IMRT/VMAT QA web application which is based on existing technologies (HTML5, Python, and Django). This tool interfaces with python, c-code libraries, and command line-based GPU applications to perform a MC-based IMRT/VMAT QA. The web app automates many complicated aspects of interfacing clinical DICOM and logfile data with cutting-edge GPU software to run a MC dose calculation. The resultant web app is powerful, easy to use, and is able to re-compute both plan dose (from DICOM data) and delivered dose (from logfile data). Both dynalog and trajectorylog file formats are supported. Users upload zipped DICOM RP, CT, and RD data and set the expected statistic uncertainty for the MC dose calculation. A 3D gamma index map, 3D dose distribution, gamma histogram, dosimetric statistics, and DVH curves are displayed to the user. Additional the user may upload the delivery logfile data from the linac to compute a 'delivered dose' calculation and corresponding gamma tests. A comprehensive PDF QA report summarizing the results can also be downloaded. Results: We successfully improved a web app for a GPU-based QA tool that consists of logfile parcing, fluence map generation, CT image processing, GPU based MC dose calculation, gamma index calculation, and DVH calculation. The result is an IMRT and VMAT QA tool that conducts an independent dose calculation for a given treatment plan and delivery log file. The system takes both DICOM data and logfile data to compute plan dose and delivered dose respectively. Conclusion: We sucessfully improved a GPU-based MC QA tool to allow for logfile dose calculation. The high efficiency and accessibility will greatly facilitate IMRT and VMAT QA.

07 ISOTOPE AND RADIATION SOURCES↗

Machine learning accelerated discrete element modeling of granular flows

Granular flows are widely encountered in many industrial processes and natural phenomena. Discrete Element Modeling (DEM) is a useful tool for understanding and troubleshooting devices, which handle granular materials. However, its applicability is significantly limited by the huge computational cost associated with detecting and computing collisions. In this research, the computation speed of DEM was accelerated by orders of magnitude using a convolutional neural network to replace the direct calculation of particle-particle and particle-boundary collisions. The MFiX software was used to generate the training and testing dataset. Additionally, a GPU accelerated TensorFlow model was used to train the neural network and test the results. The model fluctuations caused by different training steps were reduced with a multi-scale loss function. The accuracy was improved with more frames within one training step. The modeling of a rotating drum and a hopper demonstrated the accuracy and efficiency of this machine learning accelerated DEM in the simulation of granular flows.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Validation of a FAST Model of the SWAY Prototype Floating Wind Turbine

As part of a collaboration of the National Renewable Energy Laboratory (NREL) and SWAY AS, NREL installed scientific wind, wave, and motion measurement equipment on the spar-type 1/6.5th-scale prototype SWAY floating offshore wind system. The equipment enhanced SWAY's data collection and allowed SWAY to verify the concept and NREL to validate a FAST model of the SWAY design in an open-water condition. Nanyang Technological University (NTU), in collaboration with NREL, assisted with the validation. This final report gives an overview of the SWAY prototype and NREL and NTU's efforts to validate a model of the system. The report provides a summary of the different software tools used in the study, the modeling strategies, and the development of a FAST model of the SWAY prototype wind turbine, including justification of the modeling assumptions. Because of uncertainty in system parameters and modeling assumptions due to the complexity of the design, several system properties were tuned to better represent the system and improve the accuracy of the simulations. Calibration was performed using data from a static equilibrium test and free-decay tests.

17 WIND ENERGY↗

Requirements Document for Development of a Livermore Tomography Tools Interface

In this document, we outline an exercise performed at LLNL to evaluate the user interface deficits of a LLNL-developed CT reconstruction software package, Livermore Tomography Tools (LTT). We observe that a difficult-to-use command line interface and the lack of support functions compound to generate a bottleneck in the CT reconstruction process when input parameters to key functions are not well known. Through the exercise of systems engineering best practices, we generate key performance parameters for a LTT interface refresh, and specify a combination of back-end (“test-mode” functions) and front-end (graphical user interface visualization and command scripting tools) solutions to LTT’s poor user interface that aim to mitigate issues and lower costs associated with CT reconstruction using LTT. Key functional and non-functional requirements and risk mitigation strategies for the solution are outlined and discussed.

42 ENGINEERING↗

A Model-Based Expert System for Space Power Distribution Diagnostics

When engineers diagnose system failures, they often use models to confirm system operation. This concept has produced a class of advanced expert systems that perform model-based diagnosis. A model-based diagnostic expert system for the Space Station Freedom electrical power distribution test bed is currently being developed at the NASA Lewis Research Center. The objective of this expert system is to autonomously detect and isolate electrical fault conditions. Marple, a software package developed at TRW, provides a model-based environment utilizing constraint suspension. Originally, constraint suspension techniques were developed for digital systems. However, Marple provides the mechanisms for applying this approach to analog systems such as the test bed, as well. The expert system was developed using Marple and Lucid Common Lisp running on a Sun Sparc-2 workstation. The Marple modeling environment has proved to be a useful tool for investigating the various aspects of model-based diagnostics. This report describes work completed to date and lessons learned while employing model-based diagnostics using constraint suspension within an analog system.

Quinn, Todd M.↗

High Energy Micron Scale Pixel Hybrid Detector

The objective of this technology development project has been to fabricate and characterize a new X-ray area image sensor innovation designed for high efficiency detection and imaging of hard X-rays (>20 KeV) with micron scale pixel resolution. A key technology component consists of a monolithic hybrid X-ray detector built by layering an amorphous Selenium X-ray photoconductor film directly deposited on a small pitch (7.8μm) CMOS active pixel readout array. A specific goal of this work is to provide a new detector tool to researchers working with synchrotron light sources, to extend the depth of exploration into nanoscale structures, and do so cost effectively. Early generation X-ray imaging detector tools fail to provide adequate resolving power and efficiency at high energies and our innovation provides a solution. A majority of proposed phase I tasks were completed. Those tasks included, in collaboration with KA Imaging, successful fabrication of specified a-Se layers on a 1Mpixel CMOS readout array to create the direct hybrid X-ray imaging array, packaging of the imaging array, assembly of electronics into a shielded detector box, loading user interface software for camera control and image capture, and performing initial (no X-ray) detector evaluation at Farrier Microengineering facilities. After initial tests, extensive testing using the X-ray beam line 1-BM source at Argonne National Laboratory Advanced Photon Source(ANL-APS) was performed. Imaging performance studies were conducted at multiple X-ray beam energies. Studies included X-ray response vs. X-ray energy, vs. applied detector field strength (HV), response linearity vs. integration time, MTF vs. beam energy, image lag measurements, and micron scale resolution pattern target imaging. This high energy micron scale X-ray detection technology is a first of a kind to be evaluated at the ANL-APS and is supported by Dr. Antonino Miceli, head of the detector physics group. Accomplishments include the first successful demonstration of a 1Mpix amorphous Selenium on CMOS readout direct hybrid X-ray imaging detector at a DOE sponsored National Laboratory. Modeled performance predictions were confirmed, proving micron scale resolution as well as an order of magnitude increase in conversion efficiency over conventional scintillator detector performance. A discovery of evidence of propagation-based phase contrast edge enhancement was unplanned and will be exploited in future experiments. This phase 1 technology demonstration verifies the efficacy of proposed high energy micron scale pixel X-ray hybrid a-Se imaging array products. The new detector products will cost effectively replace early generation detector technologies that currently fail to address increasing demand for tools to study nano structures and physical processes at high X-ray energies above 20keV. For example, current systems for transmission X-ray microscopy have low efficiency and available large pixel (~55µm) direct detectors do not offer sufficient resolution for Bragg fringe imaging at high energies. This detector innovation will solve these inadequacies. The new detector technology will compete in a $50M scientific X-ray detector market, growing at 6%, and will benefit Microtomography(µCT), X-ray diffractometry (XRD), Coherent Diffraction Imaging (CDI) applications. One application specified by Dr. Miceli at ANL is the 3D reconstruction of compact crystals at high energies requires small pixel high efficiency X-ray detectors. Farrier Microengineering, working with colleagues at KA Imaging and the University of Waterloo, successfully achieved the critical objectives of the Phase I proposal. We have proven the technical feasibility of this innovation by building and successfully testing a 1Mpixel a-Se/CMOS hybrid direct X-ray imaging array. Our commercialization roadmap of detector products will be implemented during a phase II project. We will demonstrate a migration of the technology to larger detector array sizes, improved temporal performance with detector layer engineering, and improved environmental and operational stability. Manufacturability and cost effectiveness are key objectives and product designs will leverage current state of the art CMOS wafer fabrication quality and volume manufacturing economics.

36 MATERIALS SCIENCE↗

LLMs and GenAI Tools to Depict Contributions of Human Systems to Spaceflight Tasks Execution

Recent advancements in Artificial Intelligence and Machine Learning (AI/ML) technologies, particularly Large Language Models (LLMs) capable of sophisticated syntax analysis, offer substantial potential in automating complex processes, thereby saving time and human resources. This study explores the development of an LLM-driven model designed to analyze and categorize a diverse set of Mars mission tasks into 18 predefined Human System Task Categories (HSTCs) based on their textual descriptions. As part of developing the Crew Health and Performance – Probabilistic Risk Assessment (CHP-PRA projects Performance Risk Model (PRisM) proof-of-concept, we established a framework to project performance scores from small-scale tests onto a preliminary list of Mars tasks. The foundation of our model was a comprehensive spreadsheet populated by NASA experts and clinicians, which detailed each Mars task alongside binary indicators of HSTC involvement. This dataset enabled the initial application of supervised ML, training and testing on existing HSTC labels. The HSTCs were originally defined from a medical system perspective, focusing on task impairments due to deteriorated human health. To expand our model's scope to include categories impacting performance, we face the challenge of generating binary labels (0 or 1) for new categories without pre-existing data. We address this by employing Generative AI (GenAI) software to determine whether a given task involved a new category by asking, "Does task A involve using category B?" We validate our approach by comparing the GenAI's binary classifications with the expert-provided labels for existing HSTCs. Notably, we utilize Ollama [4], a locally hosted GenAI tool that does not require cloud access, thus safeguarding NASA's proprietary data from unauthorized exposure. This study demonstrates the feasibility of leveraging cutting-edge AI tools to advance research, paving the way for automation and rapid decision-making in space exploration.

Mona Matar↗

Security Risks: Management and Mitigation in the Software Life Cycle

A formal approach to managing and mitigating security risks in the software life cycle is requisite to developing software that has a higher degree of assurance that it is free of security defects which pose risk to the computing environment and the organization. Due to its criticality, security should be integrated as a formal approach in the software life cycle. Both a software security checklist and assessment tools should be incorporated into this life cycle process and integrated with a security risk assessment and mitigation tool. The current research at JPL addresses these areas through the development of a Sotfware Security Assessment Instrument (SSAI) and integrating it with a Defect Detection and Prevention (DDP) risk management tool.

securiy↗

OpenFAST [SWR-08-12]

OpenFAST is a wind turbine simulation tool which builds on NREL's FAST v8 software. NREL's FAST.Farm software extends the capability of OpenFAST to simulate multi-turbine wind farms. They were created with the goal of being community models developed and used by research laboratories, academia, and industry. They are managed by a dedicated team at the National Renewable Energy Laboratory (NREL). Our objective is to ensure that OpenFAST and FAST.Farm are sustainable software that are well tested and well documented. If you'd like to contribute, see the Developer Documentation and any open GitHub issues with the Help Wanted tag.

Jonkman, Jason↗

Cross-Validation of Computational and Experimental Distributed Surface Pressures on the Space Launch System

This paper presents a new workflow for comparing experimental pressure-sensitive paint (PSP) data to computational fluid dynamic (CFD) simulations by way of mapping data from corresponding grids utilizing interpolation methods. In addition to generating quantitative and qualitative point-to-point comparisons between PSP and CFD data, this workflow extracts sectional loading data from both grids and generates lineload comparison charts for corresponding PSP and CFD runs. Experimental PSP data presented in this paper were taken from a 2016 NASA Ames Research Center Unitary Plan Wind Tunnel 11- by 11-Foot Transonic WindTunnel Facility test of the NASA Space Launch System. CFD simulation data for comparison purposes were generated using the FUN3D code. Overall, interpolation onto PSP grids versus CFD grids yields comparable surface pressure fields. However, lineload comparisons are easier to make on the CFD grid-mapped data due to the grid topology and the current capabilities of the lineload analysis tools at NASA Langley Research Center. This workflow is written using contemporary software (Python, Tecplot, PyTecplot), is compatible with existing tools at NASA Langley, and is developed to be adaptable depending on the situation.

SLS↗

Development and Assessment of CTF for Pin-resolved BWR Modeling

CTF is the modernized and improved version of the subchannel code, COBRA-TF. It has been adopted by the Consortium for Advanced Simulation for Light Water Reactors (CASL) for subchannel analysis applications and thermal hydraulic feedback calculations in the Virtual Environment for Reactor Applications Core Simulator (VERA-CS). CTF is now jointly developed by Oak Ridge National Laboratory and North Carolina State University. Until now, CTF has been used for pressurized water reactor modeling and simulation in CASL, but in the future it will be extended to boiling water reactor designs. This required development activities to integrate the code into the VERA-CS workflow and to make it more ecient for full-core, pin resolved simulations. Additionally, there is a significant emphasis on producing high quality tools that follow a regimented software quality assurance plan in CASL. Part of this plan involves performing validation and verification assessments on the code that are easily repeatable and tied to specific code versions. This work has resulted in the CTF validation and verification matrix being expanded to include several two-phase flow experiments, including the General Electric 3 3 facility and the BWR Full-Size Fine Mesh Bundle Tests (BFBT). Comparisons with both experimental databases is reasonable, but the BFBT analysis reveals a tendency of CTF to overpredict void, especially in the slug flow regime. The execution of these tests is fully automated, analysis is documented in the CTF Validation and Verification manual, and the tests have become part of CASL continuous regression testing system. This paper will summarize these recent developments and some of the two-phase assessments that have been performed on CTF.

Salko, Robert K↗

A Dynamic Waste Isolation Pilot Plant Performance Assessment Tool - 12490

The Waste Isolation Pilot Plant (WIPP) Performance Assessment (PA) methodology comprises a toolbox used to demonstrate regulatory compliance of the repository after facility closure. The PA framework rests upon an extensive suite of computational codes. In some cases, significant alteration of code inputs is a tedious and difficult task. Due to the nature of the application for which they are used, PA codes used in support of WIPP regulatory compliance demonstration must satisfy stringent quality assurance requirements. Consequently, many of the coding practices used during original code development are still implemented today. A more efficient workflow configuration has the potential to alleviate difficulties associated with extensive code input modifications. Here, this potential is assessed via an implementation of a more flexible scientific workflow system for a subset of the codes used in WIPP PA. The scientific workflow approach taken here for a dynamic PA system enables users from disparate backgrounds to dramatically shorten the time between hypothesis and analysis by decreasing the amount of a priori knowledge, from a range of disciplines, needed to execute the code. Having smaller iteration times allows for more ideas to be tested and explored, which leads to safer and more optimized systems. Note that these high-level, dynamic tools are intended only for initial scoping studies on the personal computer of a researcher. Full, regulatory compliance calculations may occur only within a qualified computing environment. However, the WIPP PA tools here may guide future research and indicate regions of the analysis space that are worth further study. This next generation of PA software provides the ability to perform scoping investigations of repository performance quickly and easily, and has an accessible and useful interface to a variety of users, such as fuel cycle systems designers, domain experts such as repository modelers, and policy makers. The purview of this project allows for many opportunities for future work. Foremost among these is the desire to implement the full BRAGFLO suite within the workflow. This will entail porting or wrapping Genmesh, Matset, LHS, and ICSet within Python. Moreover, unifying the two GUIs into a single driver application would be a natural next step. Once the BRAGFLO suite is completed, other portions of WIPP PA could be implemented with corresponding and inter-operable work-flows. Likely first candidates for this are those codes that are similarly computationally intensive, such as the one used to generate complementary cumulative distribution functions used to demonstrate regulatory compliance (code CCDFGF). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

MOOSE: A Modular Platform for Fission and Fusion Multiphysics

The Multiphysics Object-Oriented Simulation Environment (MOOSE) Framework, as well as MOOSE-based simulation tools, have accelerated the development of fission energy and advanced reactor technologies through the United States Department of Energy, Office of Nuclear Science, Nuclear Energy Advanced Modeling & Simulation (NEAMS) Program. MOOSE contains a complete platform of multiphysics simulation capabilities, capable of running on massively parallel systems, and is developed in an open-source manner with great attention paid to high-quality software quality assurance practices. This overall approach could greatly benefit the fusion energy community, which requires rapid design iteration and improvement in order to facilitate the successful development of fusion as an alternative energy source to fossil fuels. In the first half of this talk, applications of MOOSE and MOOSE-based tools for advanced reactor designs will be showcased, as well as MOOSE ecosystem infrastructure (such as the NEAMS Virtual Test Bed) that enables and accelerates fission reactor design. In the second half, a discussion of how the MOOSE approach to modeling and simulation is currently being applied internationally in fusion energy research and development at the United Kingdom Atomic Energy Authority will be discussed, and ongoing/future domestic research efforts will be highlighted.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Multiplexer/Demultiplexer Loading Tool (MDMLT)

The purpose of the MDMLT is to improve the reliability and speed of loading multiplexers/demultiplexers (MDMs) in the Software Development and Integration Laboratory (SDIL) by automating the configuration management (CM) of the loads in the MDMs, automating the loading procedure, and providing the capability to load multiple or all MDMs concurrently. This loading may be accomplished in parallel, or single MDMs (remote). The MDMLT is a Web-based tool that is capable of loading the entire International Space Station (ISS) MDM configuration in parallel. It is able to load Flight Equivalent Units (FEUs), enhanced, standard, and prototype MDMs as well as both EEPROM (Electrically Erasable Programmable Read-Only Memory) and SSMMU (Solid State Mass Memory Unit) (MASS Memory). This software has extensive configuration management to track loading history, and the performance improvement means of loading the entire ISS MDM configuration of 49 MDMs in approximately 30 minutes, as opposed to 36 hours, which is what it took previously utilizing the flight method of S-Band uplink. The laptop version recently added to the MDMLT suite allows remote lab loading with the CM of information entered into a common database when it is reconnected to the network. This allows the program to reconfigure the test rigs quickly between shifts, allowing the lab to support a variety of onboard configurations during a single day, based on upcoming or current missions. The MDMLT Computer Software Configuration Item (CSCI) supports a Web-based command and control interface to the user. An interface to the SDIL File Transfer Protocol (FTP) server is supported to import Integrated Flight Loads (IFLs) and Internal Product Release Notes (IPRNs) into the database. An interface to the Monitor and Control System (MCS) is supported to control the power state, and to enable or disable the debug port of the MDMs to be loaded. Two direct interfaces to the MDM are supported: a serial interface (debug port) to receive MDM memory dump data and the calculated checksum, and the Small Computer System Interface (SCSI) to transfer load files to MDMs with hard disks. File transfer from the MDM Loading Tool to EEPROM within the MDM is performed via the MILSTD- 1553 bus, making use of the Real- Time Input/Output Processors (RTIOP) when using the rig-based MDMLT, and via a bus box when using the laptop MDMLT. The bus box is a cost-effective alternative to PC-1553 cards for the laptop. It is noted that this system can be modified and adapted to any avionic laboratory for spacecraft computer loading, ship avionics, or aircraft avionics where multiple configurations and strong configuration management of software/firmware loads are required.

Brewer, Lenox Allen↗

Dynamic mass accountancy modeling of a molten salt reactor using equilibrium thermodynamics

A mechanistic-based mass accountancy model in the context of liquid-fueled molten salt reactors was implemented in the dynamic systems modeling software library TRANSFORM by way of coupling with the equilibrium thermodynamics code Thermochimica. Liquid-fueled molten salt reactors present new challenges for mass accountancy because of the dissolution of fuel and evolved fission products, which may be soluble in the salt, off-gas, or precipitate. Two cases of mass loss from the molten salt were addressed: off-gassing and precipitation. The software implementation was tested through a series of increasingly complex demonstration problems, culminating in a model of the primary fuel and primary coolant loops of the molten salt demonstration reactor. Analysis shows that negligible mass was lost from the salt under normal operating conditions, but an overheating event caused by partial loss of fuel loop cooling resulted in release of measurable amounts of uranium (among other elements) via off-gassing. The tools developed here are primarily aimed at capability development but are readily available for use in further modeling of molten salt reactor concepts. As a result, these tools have not yet been validated, and future experimental work to perform this validation is recommended.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Cybersecurity Vulnerability Mitigation Framework through Empirical Paradigm (CyFEr): Prioritized Gap Analysis

Cybersecurity vulnerability assessment tools, frameworks, methodologies, and processes are commonly used to understand the cybersecurity maturity and posture of a system or a facility. Although, those tools are strictly developed based on standards defined by organizations such as the National Institute of Standards and Technology (NIST) and the U.S. Department of Energy, the majority of these tools and frameworks do not provide a platform to prioritize the requirements to reach a desired cybersecurity maturity. To address that challenge, we have been developing a framework and a software application called the cybersecurity vulnerability mitigation framework through empirical paradigm (CyFEr). The efficacy of CyFEr was evaluated by implementing it on the NIST Cybersecurity Framework (CSF). This paper provides a detailed architecture of CyFEr and demonstrates its application to CSF by testing against a real-world cyber-attack that targeted industrial control systems in a critical infrastructure facility.

Gourisetti, Sri Nikhil G.↗

GlassForm

GlassForm is a software tool for generating preliminary waste glass formulas for a given waste stream. The software is useful because it reduces the number of verification melts required to develop a suitable additive composition. The software includes property models that calculate glass properties of interest from the chemical composition of the waste glass. The software includes property models for glass viscosity, electrical conductivity, glass transition temperature, and leach resistance as measured by the 7-day product consistency test (PCT).

Nelson, LeeO.↗

Automated Generation and Assessment of Autonomous Systems Test Cases

This slide presentation reviews some of the issues concerning verification and validation testing of autonomous spacecraft routinely culminates in the exploration of anomalous or faulted mission-like scenarios using the work involved during the Dawn mission's tests as examples. Prioritizing which scenarios to develop usually comes down to focusing on the most vulnerable areas and ensuring the best return on investment of test time. Rules-of-thumb strategies often come into play, such as injecting applicable anomalies prior to, during, and after system state changes; or, creating cases that ensure good safety-net algorithm coverage. Although experience and judgment in test selection can lead to high levels of confidence about the majority of a system's autonomy, it's likely that important test cases are overlooked. One method to fill in potential test coverage gaps is to automatically generate and execute test cases using algorithms that ensure desirable properties about the coverage. For example, generate cases for all possible fault monitors, and across all state change boundaries. Of course, the scope of coverage is determined by the test environment capabilities, where a faster-than-real-time, high-fidelity, software-only simulation would allow the broadest coverage. Even real-time systems that can be replicated and run in parallel, and that have reliable set-up and operations features provide an excellent resource for automated testing. Making detailed predictions for the outcome of such tests can be difficult, and when algorithmic means are employed to produce hundreds or even thousands of cases, generating predicts individually is impractical, and generating predicts with tools requires executable models of the design and environment that themselves require a complete test program. Therefore, evaluating the results of large number of mission scenario tests poses special challenges. A good approach to address this problem is to automatically score the results based on a range of metrics. Although the specific means of scoring depends highly on the application, the use of formal scoring - metrics has high value in identifying and prioritizing anomalies, and in presenting an overall picture of the state of the test program. In this paper we present a case study based on automatic generation and assessment of faulted test runs for the Dawn mission, and discuss its role in optimizing the allocation of resources for completing the test program.

Testing challenges↗