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At least 1,189 records · Page 66

SU-F-BRA-07: Dosimetric Verification of the Valencia Skin Applicator Using Gafchromic EBT3 Film

Purpose: The Valencia applicators have recently been introduced for HDR treatment of small and shallow superficial skin lesions (< 20 mm diameter and 3-mm depth). Per AAPM TG 56, any HDR applicator internal dimensions must be verified prior to clinical use. However radiographic and tomographic imaging to validate the Valencia applicators is impractical due to the Tungsten alloy housing and flattening filter. In this study, we propose to use EBT3 film to indirectly confirm the physical integrity of the Valencia applicators. Methods: Treatment plans were created using the Oncentra MasterPlan TPS v4.5 for the H2 (20-mm dia.) and H3 (30-mm dia.) Valencia Applicators. A virtual CT phantom (2-mm slice thickness) was created with one source position in water. The published effective depth method was used for each applicator to delivery 500 cGy to a 3-mm depth using the TG-43 formalism. Film measurements (n=3) at 3-mm depth and vertical plane in solid water were performed for each applicator to verify the prescribed dose calculated by the TPS. Percent depth dose curves and off-axis profiles (phantom surface and 3-mm depth) were measured and compared to published data. Films were analyzed using an in-house written program and RIT113 v6 software. Film calibration was performed per TG-55 protocol using the Ir-192 source with NIST-traceable calibration. Results: The prescription absolute dose difference was 1% for the Valencia H2 applicator and 4% for the Valencia H3 applicator. The measured percent depth dose curves and off-axis dose profiles measured for the H2 and H2 Valencia applicators are in excellent agreement with the Granero et al. Monte Carlo results{sup 1}. Conclusion: Gafchromic EBT3 film can be used to indirectly verify the internal components of special HDR skin applicators constructed from high Z materials.{sup 1}Granero et al. “Design and evaluation of a HDR skin applicator with flattening filter”, Med. Phys. 35(2), 495–503, 2008.

60 APPLIED LIFE SCIENCES↗

MO-F-CAMPUS-I-01: A System for Automatically Calculating Organ and Effective Dose for Fluoroscopically-Guided Procedures

Purpose: A system was developed that automatically calculates the organ and effective dose for individual fluoroscopically-guided procedures using a log of the clinical exposure parameters. Methods: We have previously developed a dose tracking system (DTS) to provide a real-time color-coded 3D- mapping of skin dose. This software produces a log file of all geometry and exposure parameters for every x-ray pulse during a procedure. The data in the log files is input into PCXMC, a Monte Carlo program that calculates organ and effective dose for projections and exposure parameters set by the user. We developed a MATLAB program to read data from the log files produced by the DTS and to automatically generate the definition files in the format used by PCXMC. The processing is done at the end of a procedure after all exposures are completed. Since there are thousands of exposure pulses with various parameters for fluoroscopy, DA and DSA and at various projections, the data for exposures with similar parameters is grouped prior to entry into PCXMC to reduce the number of Monte Carlo calculations that need to be performed. Results: The software developed automatically transfers data from the DTS log file to PCXMC and runs the program for each grouping of exposure pulses. When the dose from all exposure events are calculated, the doses for each organ and all effective doses are summed to obtain procedure totals. For a complicated interventional procedure, the calculations can be completed on a PC without manual intervention in less than 30 minutes depending on the level of data grouping. Conclusion: This system allows organ dose to be calculated for individual procedures for every patient without tedious calculations or data entry so that estimates of stochastic risk can be obtained in addition to the deterministic risk estimate provided by the DTS. Partial support from NIH grant R01EB002873 and Toshiba Medical Systems Corp.

60 APPLIED LIFE SCIENCES↗

ExaSAT: An exascale co-design tool for performance modeling

One of the emerging challenges to designing HPC systems is understanding and projecting the requirements of exascale applications. In order to determine the performance consequences of different hardware designs, analytic models are essential because they can provide fast feedback to the co-design centers and chip designers without costly simulations. However, current attempts to analytically model program performance typically rely on the user manually specifying a performance model. Here we introduce the ExaSAT framework that automates the extraction of parameterized performance models directly from source code using compiler analysis. The parameterized analytic model enables quantitative evaluation of a broad range of hardware design trade-offs and software optimizations on a variety of different performance metrics, with a primary focus on data movement as a metric. Finally, we demonstrate the ExaSAT framework’s ability to perform deep code analysis of a proxy application from the Department of Energy Combustion Co-design Center to illustrate its value to the exascale co-design process. ExaSAT analysis provides insights into the hardware and software trade-offs and lays the groundwork for exploring a more targeted set of design points using cycle-accurate architectural simulators.

97 MATHEMATICS AND COMPUTING↗

ZFP Hardware Implementation

ZFP is a floating-point compression format gaining traction in high-performance computing applications. A software implementation has demonstrated the ability to reduce data movement across communication channels and to reduce the footprint of floating-point arrays in memory. Nevertheless, any benefit in performance is limited to the spare compute cycles available before reaching bandwidth limitations. A hardware implementation of ZFP has the potential to substantially improve HPC application performance. Hardware compression speedup over software alone on a single CPU core ranges from 15x for 1-D arrays to over 200x for 3-D arrays. The implementation of ZFP is sourced in SystemC to facilitate its evaluation in various architectures. The encode pipeline consists of several modules. Uncompressed blocks of floating-point numbers in IEEE format flow into the pipeline in a stream and a compressed bitstream flows out from the pipeline. The decode pipeline is the inverse of the encode pipeline. A modular design enables formats other than IEEE (such as posits) to be considered with minor adaptations. Best performance will be realized from the hardware ZFP unit when batches of blocks are processed at a time. The implementation supports 1-D, 2- D and 3-D blocks of floating-point numbers. The hardware implementation of ZFP has been validated with the software implementation of ZFP. C++ template parameters are used to specify the bit width of floating-point numbers and the array dimension of the encoder. A test bench program has been created with several test cases, some with continuous data that is ideal for ZFP, and others with extreme cases containing numbers near or at the maximum or minimum values supported by the number format.

Lloyd, GS↗

Status of the Atlas of Neutron Resonances [Slides]

The Atlas of Neutron Resonances is the most comprehensive compilation of neutron resonances, thermal cross sections, resonance integrals and Maxwellian averaged cross sections generally available. For decades, the Atlas was carefully curated and maintained by Dr. Said Mughabghab who sadly passed on during the summer of 2018 after publishing the 2018 edition of the Atlas . We are continuing the development of this important compendium. To a large extent, the Atlas book is generated from a series of text files given in a single purpose domain-specific format. Therefore, we developed a software API and began the systematic assessment of the Atlas files. With this work past, we are now focusing on new efforts to expand the quality and scope of the Atlas . Current and recently completed projects include a cross comparison of the Atlas bibliography with Nuclear Science References and the EXFOR data library, a better determination of average resonance parameters, and using machine learning to assess the correctness of the spin group assignments of resonances tabulated in the Atlas .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Developing a GUM Compliant Uncertainty Approach for NDA Gamma Analysis Using FRAM

The Fixed-Energy Response-Function Analysis with Multiple Efficiency (FRAM) code was developed at Los Alamos National Laboratory (LANL) to analyze gamma-ray spectra for the isotopic composition of plutonium or uranium. This software provides means to easily process gamma-ray spectra to obtain isotopic information and is used globally for international safeguards applications. In a recent review of the FRAM code for the use in nuclear forensics applications, it was determined that a more complete understanding and definition of the various sources of uncertainty that contribute to the overall uncertainty of the FRAM measurement process is required. As one of the ISO 17025 accredited Bulk Special Nuclear Materials Analysis Program (BSAP) laboratories, LANL is required to perform an accurate and transparent uncertainty calculation on every analysis it performs. This paper describes a new approach to calculate a Guide to the Expression of Uncertainty in Measurement (GUM) compliant FRAM uncertainty to support nuclear forensics applications.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Novel Modified Optical Fibers for High Temperature In-Situ Miniaturized Gas Sensors in Advanced Fossil Energy Systems

This report covers the technical progress on the program “Novel Modified Optical Fibers for High Temperature In-Situ Miniaturized Gas Sensors in Advanced Fossil Energy Systems”, funded by the National Energy Technology Laboratory of the U.S. Department of Energy, and performed by the Materials Science & Engineering and Electrical & Computer Engineering Departments at Virginia Tech, and summarizes technical progress from July 1st, 2005 –June 30th, 2014. The objective of this program was to develop novel fiber materials for high temperature gas sensors based on evanescent wave absorption in optical fibers. This project focused on two primary areas: the study of a sapphire photonic crystal fiber (SPCF) for operation at high temperature and long wavelengths, and a porous glass based fiber optic sensor for gas detection. The sapphire component of the project focused on the development of a sapphire photonic crystal fiber, modeling of the new structures, fabrication of the optimal structure, development of a long wavelength interrogation system, testing of the optical properties, and gas and temperature testing of the final sensor. The fabrication of the 6 rod SPCF gap bundle (diameter of 70μm) with a hollow core was successfully constructed with lead-in and lead-out 50μm diameter fiber along with transmission and gas detection testing. Testing of the sapphire photonic crystal fiber sensor capabilities with the developed long wavelength optical system showed the ability to detect CO 2 at or below 1000ppm at temperatures up to 1000°C. Work on the porous glass sensor focused on the development of a porous clad solid core optical fiber, a hollow core waveguide, gas detection capabilities at room and high temperature, simultaneous gas species detection, suitable joining technologies for the lead-in and lead-out fibers and the porous sensor, sensor system sensitivity improvement, signal processing improvement, relationship between pore structure and fiber geometry to optical properties, and the development of a sensor packaging prototype for laboratory testing. Analysis and experiments determined that a bonding technique using a CO 2 laser is the most suitable joining technique. Pore morphology alteration showed that transmission improved with increasing annealing temperature (producing smaller pores), while the sensor response time increased and the mechanical strength decreased with increasing annealing temperature. Software was developed for data acquisition and signal processing to collect and interpret spectral gas absorption data. Gas detection on porous glass sensors was completed and the detection limit was evaluated using acetylene and was found to be around 1- 200ppm. A complete materials package for porous glass sensors was manufactured for testing.

36 MATERIALS SCIENCE↗

Gaussian Process Optimization of Sensitivity-Based Similarity Metrics between New Nuclear Applications and New/Existing Benchmarks

Confidently designing safe, new nuclear criticality experiments requires expert judgement, which could take years of experience. Sensitivity/uncertainty (S/U) analysis can be utilized by less experienced individuals to conservatively estimate uncertainties in important parameters, such as k eff , in newly proposed nuclear applications. This type of analysis relies on matching new nuclear applications with existing benchmark experiments. The Whisper-1.1 software package included in MCNP6.2 ®1 contains more than 1,100 International Criticality Safety Benchmark Evaluation Project (ICSBEP) benchmarks. These benchmarks however rarely match new nuclear applications. The number of benchmarks available to match a given set of materials or geometric configurations varies significantly. Furthermore, recently performed benchmark experiments may not have had enough time to be properly documented and published. Benchmarks are vital for determining the accuracy of nuclear data and can assist nuclear physics and evaluators in improving nuclear data libraries. Exhaustively exploring the parameter space using simulations with software such as MCNP is too computationally expensive. In this work, Gaussian process optimization was implemented to reduce the number of simulations needed for optimization over multiple parameters. This optimization scheme was designed to selectively generate new benchmarks with high sensitivity-based similarity metrics to user-defined nuclear applications. Two benchmark models of spherically nested shells containing plutonium, uranium, tantalum, and water were used in the optimization to match an application containing plutonium plates, stacked in a tantalum reflector, surrounded by water.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

SLIA Reference Architecture Models

The SLIA Reference Architecture Models project, sponsored by the DOE CESER Energy CyberSense Program (Oct 2024–Sep 2025), advanced LLNL’s PySCES simulation tool to better support CyTRICS Prioritization and Initial Risk Assessment (PIRA) reference architectures. Key achievements include enhancements to the PySCES transmission substation facility model, expanded asset coverage, and enhancements to the PySCES code base. Software improvements reduced code complexity, migrated PySCES to Python version 3.11, introduced an object-oriented design, and added a schema database for easier updates and validation. New features support device criticality assessments and a more precise parametric simulation mode. Remaining gaps include model validation, workflow limitations, Monte Carlo convergence issues, full device criticality metric implementation, model fidelity, and general software improvements. Continued development is recommended to address these gaps and fully align PySCES with CyTRICS PIRA requirements.

97 MATHEMATICS AND COMPUTING↗

The History of MCNP and about 20 Related Programs

The history of the MCNP code is a long and complicated one that touches a huge number of other software packages over the decades. This document will attempt to place the direct lineage of the MCNP code into a single document and track the people who worked on and around the software. This report is necessarily incomplete. The author only has access to the LANL archives, which have gaps in key areas. Speculation will be used to fill gaps where necessary. It is hoped that future revisions will have more detail than this report, especially as others come forward with their knowledge. The history will be broken into a few segments. Sec. 1 will go through the low-energy history from MCS to MCNP version 4. In Sec. 2, the history of high-energy physics from Oak Ridge’s NTC to MCNP version 6 will be discussed. Sec. 3 will go through some important notes to complete this history. Finally, Sec. 4 contains a chart of the lineage of the code.

97 MATHEMATICS AND COMPUTING↗

Involving the new generations in Fermilab endeavors

Since 1984 the Italian groups of the Istituto Nazionale di Fisica Nucleare (INFN) and Italian Universities, collaborating with the DOE laboratory of Fermilab (US) have been running a two-month summer training program for Italian university students. While in the first year the program involved only four physics students of the University of Pisa, in the following years it was extended to engineering students. This extension was very successful and the engineering students have been since then extremely well accepted by the Fermilab Technical, Accelerator, and Scientific Computing Division groups. Over the many years of its existence, this program has proven to be the most effective way to engage new students in Fermilab endeavors. Many students have extended their collaboration with Fermilab with their Master’s Thesis and PhD. Since 2004 the program has been supported in part by DOE in the frame of an exchange agreement with INFN. Over its almost 40 years of history, the program has grown in scope and size and has involved more than 550 Italian students from more than 20 Italian Universities, Several Institutes of Research, including ASI and INAF in Italy, and the ISSNAF Foundation in the US, have provided additional financial support. Since the program does not exclude appropriately selected non-Italian students, a handful of students from European and non-European Universities were also accepted over the years. Each intern is supervised by a Fermilab Mentor responsible for performing the training program. Training programs spanned from Tevatron, CMS, Muon (g-2), Mu2e, and Short Baseline Neutrino Experiments and DUNE design and experimental data analysis, development of particle detectors (silicon trackers, calorimeters, drift chambers, neutrino and dark matter detectors), design of electronic and accelerator components, development of infrastructures and software for exascale data handling, research on superconductive elements and on accelerating cavities, and theory of particle accelerators. Since 2010, within an extended program supported by the Italian Space Agency and the Italian National Institute of Astrophysics, a total of 30 students in physics, astrophysics, and engineering have been hosted for two months in the summer at US space science Research Institutes and laboratories. In 2015 the University of Pisa included these programs within its educational programs. Accordingly, Summer School students are enrolled at the University of Pisa for the duration of the internship and are identified and ensured as such. At the end of the internship, the students are required to write summary reports on their achievements. After positive evaluation by a University Examining Board, interns are acknowledged credits for their Diploma Supplement. The program was canceled in 2020 and 2021 due to the pandemic but restarted successfully in 2022. We believe this program can be taken as a model and easily adopted by interested institutions.

99 GENERAL AND MISCELLANEOUS↗

Implementation of a Grid Connected Battery-Inverter Fleet Model

Batteries are designed to store electrical energy. The increasing variation in time value of energy has driven the use of batteries as controllable distributed energy resources (DER). This is enabled though low-cost power electronic inverters that are able to precisely control charge and discharge. This paper describes the software implementation of an open-source battery inverter fleet models in python. The Sandia BatterylnverterFleet class model can be used by scientists, researchers, and engineers to perform simulations of one or more fleets of similar battery-inverter systems connected to the grid. The program tracks the state- of-charge of the simulated batteries and ensures that they stay within their limits while responding to separately generated service requests to charge or discharge. This can be used to analyze control and coordination, placement and sizing, and many other problems associated with the integration of batteries on the power grid. The development of these models along with their python implementation was funded by the Grid Modernization Laboratory Consortium (GMLC) project 1.4.2. Definitions, Standards and Test Procedures for Grid Services from Devices.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Status of the NEAMS and ARC fast reactor tools integration to the NEAMS Workbench

The Workbench initiative was launched in FY-2017 within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to facilitate the transition from conventional tools to high-fidelity tools. The NEAMS Workbench provides a common user interface for model creation, real-time validation, execution, output processing, and visualization for integrated codes. The integration of the Argonne Reactor Computation (ARC) suite of codes into the NEAMS Workbench through the PyARC module was initiated in FY-2017. The ARC codes, which focus on fast reactor multiphysics analysis, contain both legacy codes like DIF3D and REBUS-3 that were developed with over 30 years of experience, and newer NEAMS additions like MC 2 -3, PERSENT, and PROTEUS. Recent work expended this integration to other tools to support the U.S. fast reactor community such as DASSH for sub-channel thermal-hydraulics, Griffin for high-fidelity deterministic transport calculations, and OpenMC for Monte Carlo simulations (with Shift integration planned for FY-2023). The integration of the “extended ARC” suite of codes into the NEAMS Workbench interface relies on the PyARC and PyGriffin modules to handles the pre- and post-processing of these codes input, and the runtime environment. The PyARC module together with the NEAMS Workbench interface are both released under Open Source Software licenses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

CTF Theory Manual: Version 4.3

Coolant-Boiling in Rod Arrays—Two Fluids (COBRA-TF) is a thermal/hydraulic (T/H) simulation code designed for light water reactor (LWR) vessel analysis. It uses a two-fluid, three-field (i.e., fluid film, fluid drops, and vapor) modeling approach. Both subchannel and three-dimensional Cartesian forms of its governing equations are available for the solution. The code was originally developed by Pacific Northwest Laboratory in 1980, and had been used and modified by several institutions over the last few decades. COBRA-TF also found use at the Pennsylvania State University (PSU) by the Reactor Dynamics and Fuel Modeling Group (RDFMG) and has been improved, updated, and subsequently rebranded as CTF. CTF was later adopted in the early 2010s by Oak Ridge National Laboratory (ORNL) for use in the Consortium for Advanced Simulation of Light Water Reactors (CASL) program, which led to a significant advancement of the code software quality, modeling accuracy, testing systems, and capabilities for improved support of modeling of common LWR nominal and transient behavior. As part of the improvement process, it was necessary to generate sufficient documentation for the public domain code which had lacked such material upon being adopted by RDFMG. This document serves as a theory manual for CTF, detailing the many two-phase heat transfer, drag, and important accident scenario models contained in the code, as well as the numerical solution process utilized. Additional documents available in the CTF documentation suite include the user manual and verification and validation manual.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DEReliction: A Cybersecurity Vulnerability Assessment Methodology for Distributed Energy Resources

With the increasing integration of Distributed Energy Resources (DER) into the electric grid, maintaining grid reliability and resilience requires that these devices remain secure. This paper discusses a cybersecurity vulnerability assessment methodology that incorporates best practices from Sandia National Laboratories, SANS Institute, OWASP Foundation, and other web and Internet of Things (IoT) penetration testing (“pen testing”) programs, courses, and frameworks for assessing the security posture of devices. The methodology involves five sequential steps: (1) Collect Public Information, (2) Extract Hardware Details, (3) Inventory Software Components, (4) Identify Vulnerabilities, and (5) Test Vulnerabilities. Each step uncovers potential weaknesses in both hardware and software components of DER devices, considering adversary tactics, techniques, and procedures (TTPs), and potential attack vectors along the way. The results from the execution of this method on multiple residential- and small commercial-scale photovoltaic (PV) inverters reveled hardware and software vulnerabilities, which highlight the benefit of taking a methodical approach to discover vulnerabilities. While the specific vulnerability details are not shared here, a generalized overview of findings underscore the importance of robust security assessments for DER devices. Adoption of an assessment framework of this kind will identify and mitigate cybersecurity threats and bolster the resilience of DER-integrated electric grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Updating a PWR Simulator in Python

A nuclear reactor is a complicated system that is comprised of many systems and components. In order to fully model a reactor, several approximations and correlations must be used for a real-time simulation. In 1984 as part of a doctoral dissertation at Massachusetts Institute of Technology (MIT), a FORTRAN 77 program was developed to simulate a four-loop, Westinghouse pressurized water reactor (PWR). The program was later called PRISM and extended to include a comprehensive set of features accessible in a DOS-based user interface. This present work seeks to update the original PRISM program for cross platform deployment using the Python language. The goal of this present work is to update and improve a teaching tool for both students and reactor operators. Originally, PRISM was created as part of a PhD project in FORTRAN 77, but the code no longer works readily on modern operating systems. Python was chosen to rewrite the program because of the ease of use of the Python modules including Kivy as well as the portability of the program to various operating systems. This project aims to develop desktop and mobile versions of the software, allowing the user flexibility in choice of platform. This simulator is scheduled to be deployed in time for a live demonstration at the 2016 Annual ANS meeting. The project aims to produce a reactor simulator that will showcase the dynamics of a PWR system in real-time under various conditions. Some potential scenarios include startup conditions, scram operations, or failure conditions such as a break in a coolant leg. The user will be able to induce various failure scenarios and the program will simulate how the reactor will behave. The simulation will include a suite of monitoring functions that will allow automatic systems to attempt to adapt to the changing conditions, e.g., control rod movement. This program will provide an educational resource for anyone learning about nuclear reactor kinetics or dynamics of a reactor system. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

End-to-End Workflow for Machine-Learning-Based Qubit Readout With QICK and hls4ml

In this article, we present an end-to-end workflow for superconducting qubit readout that embeds codesigned neural networks into the quantum instrumentation control kit (QICK). Capitalizing on the custom firmware and software of the QICK platform, which is built on Xilinx radiofrequency system-on-chip field-programmable gate arrays (FPGAs), we aim to leverage machine learning (ML) to address critical challenges in qubit readout accuracy and scalability. The workflow utilizes the hls4ml package and employs quantization-aware training to translate ML models into hardware-efficient FPGA implementations via user-friendly Python application programming interfaces. We experimentally demonstrate the design, optimization, and integration of an ML algorithm for single transmon qubit readout, achieving 96% single-shot fidelity with a latency of 32.25 ns and less than 16% FPGA lookup table resource utilization. Our results offer the community an accessible workflow to advance ML-driven readout and adaptive control in quantum information processing applications.

42 ENGINEERING↗