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At least 901 records · Page 50

WE-F-304-01: Overview of the Working Group On Stereotactic Body Radiation Therapy (WGSBRT)

Stereotactic Body Radiation Therapy (SBRT) was introduced clinically more than twenty years ago, and many subsequent publications have reported safety and efficacy data. The AAPM Working Group on Biological Effects of Hypofractionated Radiotherapy/SBRT (WGSBRT) extracted published treatment outcomes data from extensive literature searches to summarize and construct tumor control probability (TCP) and normal tissue complication probability (NTCP) models for six anatomical regions: Cranial, Head and Neck, Thoracic, Abdominal, Pelvic, and Spinal. In this session, we present the WGSBRT’s work for cranial sites, and recurrent head and neck cancer. From literature-based data and associated models, guidelines to aid with safe and effective hypofractionated radiotherapy treatment are being determined. Further, the ability of existing and proposed radiobiological models to fit these data is considered as to the ability to distinguish between the linear-quadratic and alternative radiobiological models such as secondary cell death from vascular damage, immunogenic, or bystander effects. Where appropriate, specific model parameters are estimated. As described in “The lessons of QUANTEC,” (1), lack of adequate reporting standards continues to limit the amount of useful quantitative information that can be extracted from peer-reviewed publications. Recommendations regarding reporting standards are considered, to enable such reviews to achieve more complete characterization of clinical outcomes. 1 Jackson A, Marks LB, Bentzen SM, Eisbruch A, Yorke ED, Ten Haken RK, Constine LS, Deasy JO. The lessons of QUANTEC: recommendations for reporting and gathering data on dose-volume dependencies of treatment outcome. Int J Radiat Oncol Biol Phys. 2010 Mar 1;76(3 Suppl):S155–60. Learning Objectives: Describe the techniques, types of cancer and dose schedules used in treating recurrent H&N cancers with SBRT List the radiobiological models that compete with the linear-quadratic model in explaining the results of hypofractionated RT Describe the dose/volume metrics that are considered safe in SBRT treatment of tumors near the optic structures. Discuss the efficacy of hypofractionation and dosing schedules used in treating vestibular schwannomas Identify some difficulties in modeling TCP and NTCP for cranial tumors treated with hypofractionation. One moderator, Dr. Grimm, designed and holds intellectual property rights to the DVH Evaluator software tool which is an FDA-cleared product in commercial use, and can analyze some of this data. No others have relevant conflicts of interest.

60 APPLIED LIFE SCIENCES↗

WE-F-304-02: Recurrent HNC Treated with SBRT: TCP-Based Outcome Estimates

Stereotactic Body Radiation Therapy (SBRT) was introduced clinically more than twenty years ago, and many subsequent publications have reported safety and efficacy data. The AAPM Working Group on Biological Effects of Hypofractionated Radiotherapy/SBRT (WGSBRT) extracted published treatment outcomes data from extensive literature searches to summarize and construct tumor control probability (TCP) and normal tissue complication probability (NTCP) models for six anatomical regions: Cranial, Head and Neck, Thoracic, Abdominal, Pelvic, and Spinal. In this session, we present the WGSBRT’s work for cranial sites, and recurrent head and neck cancer. From literature-based data and associated models, guidelines to aid with safe and effective hypofractionated radiotherapy treatment are being determined. Further, the ability of existing and proposed radiobiological models to fit these data is considered as to the ability to distinguish between the linear-quadratic and alternative radiobiological models such as secondary cell death from vascular damage, immunogenic, or bystander effects. Where appropriate, specific model parameters are estimated. As described in “The lessons of QUANTEC,” (1), lack of adequate reporting standards continues to limit the amount of useful quantitative information that can be extracted from peer-reviewed publications. Recommendations regarding reporting standards are considered, to enable such reviews to achieve more complete characterization of clinical outcomes. 1 Jackson A, Marks LB, Bentzen SM, Eisbruch A, Yorke ED, Ten Haken RK, Constine LS, Deasy JO. The lessons of QUANTEC: recommendations for reporting and gathering data on dose-volume dependencies of treatment outcome. Int J Radiat Oncol Biol Phys. 2010 Mar 1;76(3 Suppl):S155–60. Learning Objectives: Describe the techniques, types of cancer and dose schedules used in treating recurrent H&N cancers with SBRT List the radiobiological models that compete with the linear-quadratic model in explaining the results of hypofractionated RT Describe the dose/volume metrics that are considered safe in SBRT treatment of tumors near the optic structures. Discuss the efficacy of hypofractionation and dosing schedules used in treating vestibular schwannomas Identify some difficulties in modeling TCP and NTCP for cranial tumors treated with hypofractionation. One moderator, Dr. Grimm, designed and holds intellectual property rights to the DVH Evaluator software tool which is an FDA-cleared product in commercial use, and can analyze some of this data. No others have relevant conflicts of interest.

60 APPLIED LIFE SCIENCES↗

WE-F-304-03: Optic Nerve/Chiasm Hypofractionated SRS/SRT Dose Tolerance

Stereotactic Body Radiation Therapy (SBRT) was introduced clinically more than twenty years ago, and many subsequent publications have reported safety and efficacy data. The AAPM Working Group on Biological Effects of Hypofractionated Radiotherapy/SBRT (WGSBRT) extracted published treatment outcomes data from extensive literature searches to summarize and construct tumor control probability (TCP) and normal tissue complication probability (NTCP) models for six anatomical regions: Cranial, Head and Neck, Thoracic, Abdominal, Pelvic, and Spinal. In this session, we present the WGSBRT’s work for cranial sites, and recurrent head and neck cancer. From literature-based data and associated models, guidelines to aid with safe and effective hypofractionated radiotherapy treatment are being determined. Further, the ability of existing and proposed radiobiological models to fit these data is considered as to the ability to distinguish between the linear-quadratic and alternative radiobiological models such as secondary cell death from vascular damage, immunogenic, or bystander effects. Where appropriate, specific model parameters are estimated. As described in “The lessons of QUANTEC,” (1), lack of adequate reporting standards continues to limit the amount of useful quantitative information that can be extracted from peer-reviewed publications. Recommendations regarding reporting standards are considered, to enable such reviews to achieve more complete characterization of clinical outcomes. 1 Jackson A, Marks LB, Bentzen SM, Eisbruch A, Yorke ED, Ten Haken RK, Constine LS, Deasy JO. The lessons of QUANTEC: recommendations for reporting and gathering data on dose-volume dependencies of treatment outcome. Int J Radiat Oncol Biol Phys. 2010 Mar 1;76(3 Suppl):S155–60. Learning Objectives: Describe the techniques, types of cancer and dose schedules used in treating recurrent H&N cancers with SBRT List the radiobiological models that compete with the linear-quadratic model in explaining the results of hypofractionated RT Describe the dose/volume metrics that are considered safe in SBRT treatment of tumors near the optic structures. Discuss the efficacy of hypofractionation and dosing schedules used in treating vestibular schwannomas Identify some difficulties in modeling TCP and NTCP for cranial tumors treated with hypofractionation. One moderator, Dr. Grimm, designed and holds intellectual property rights to the DVH Evaluator software tool which is an FDA-cleared product in commercial use, and can analyze some of this data. No others have relevant conflicts of interest.

60 APPLIED LIFE SCIENCES↗

WE-F-304-04: Radiosurgery for Vestibular Schwannomas: Tumor Control Probability Analyses and Recommended Reporting Standards

Stereotactic Body Radiation Therapy (SBRT) was introduced clinically more than twenty years ago, and many subsequent publications have reported safety and efficacy data. The AAPM Working Group on Biological Effects of Hypofractionated Radiotherapy/SBRT (WGSBRT) extracted published treatment outcomes data from extensive literature searches to summarize and construct tumor control probability (TCP) and normal tissue complication probability (NTCP) models for six anatomical regions: Cranial, Head and Neck, Thoracic, Abdominal, Pelvic, and Spinal. In this session, we present the WGSBRT’s work for cranial sites, and recurrent head and neck cancer. From literature-based data and associated models, guidelines to aid with safe and effective hypofractionated radiotherapy treatment are being determined. Further, the ability of existing and proposed radiobiological models to fit these data is considered as to the ability to distinguish between the linear-quadratic and alternative radiobiological models such as secondary cell death from vascular damage, immunogenic, or bystander effects. Where appropriate, specific model parameters are estimated. As described in “The lessons of QUANTEC,” (1), lack of adequate reporting standards continues to limit the amount of useful quantitative information that can be extracted from peer-reviewed publications. Recommendations regarding reporting standards are considered, to enable such reviews to achieve more complete characterization of clinical outcomes. 1 Jackson A, Marks LB, Bentzen SM, Eisbruch A, Yorke ED, Ten Haken RK, Constine LS, Deasy JO. The lessons of QUANTEC: recommendations for reporting and gathering data on dose-volume dependencies of treatment outcome. Int J Radiat Oncol Biol Phys. 2010 Mar 1;76(3 Suppl):S155–60. Learning Objectives: Describe the techniques, types of cancer and dose schedules used in treating recurrent H&N cancers with SBRT List the radiobiological models that compete with the linear-quadratic model in explaining the results of hypofractionated RT Describe the dose/volume metrics that are considered safe in SBRT treatment of tumors near the optic structures. Discuss the efficacy of hypofractionation and dosing schedules used in treating vestibular schwannomas Identify some difficulties in modeling TCP and NTCP for cranial tumors treated with hypofractionation. One moderator, Dr. Grimm, designed and holds intellectual property rights to the DVH Evaluator software tool which is an FDA-cleared product in commercial use, and can analyze some of this data. No others have relevant conflicts of interest.

60 APPLIED LIFE SCIENCES↗

Design-Technology Co-Optimization for NVM-based Neuromorphic Processing Elements

An emerging use-case of machine learning (ML) is to train a model on a high-performance system and deploy the trained model on energy-constrained embedded systems. Neuromorphic hardware platforms, which operate on principles of the biological brain, can significantly lower the energy overhead of a machine learning inference task, making these platforms an attractive solution for embedded ML systems. In this paper, we present a design-technology tradeoff analysis to implement such inference tasks on the processing elements (PEs) of a Non-Volatile Memory (NVM)-based neuromorphic hardware. Through detailed circuit-level simulations at scaled process technology nodes, we show the negative impact of technology scaling on the information-processing latency, which impacts the quality-of-service (QoS) of an embedded ML system. At a finer granularity, the latency inside a PE depends on 1) the delay introduced by parasitic components on its current paths, and 2) the varying delay to sense different resistance states of its NVM cells. Based on these two observations, we make the following three contributions. First, on the technology front, we propose an optimization scheme where the NVM resistance state that takes the longest time to sense is set on current paths having the least delay, and vice versa, reducing the average PE latency, which improves the QoS. Second, on the architecture front, we introduce isolation transistors within each PE to partition it into regions that can be individually power-gated, reducing both latency and energy. Finally, on the system-software front, we propose a mechanism to leverage the proposed technological and architectural enhancements when implementing a machine-learning inference task on neuromorphic PEs of the hardware. Evaluations with a recent neuromorphic hardware architecture show that our proposed design-technology co-optimization approach improves both performance and energy efficiency of machine-learning inference tasks without incurring high cost-per-bit.

42 ENGINEERING↗

Multiscale Solar Water Heating (MSWH) v1.0

The main purpose of the software is to model energy use for individual and community scale solar water heating projects in California. Usage The user provides a climate zone for a project, an occupancy for each household and whether any of the occupants stay at home during the day. The software can then load a set of example California specific hourly domestic hot water end-use load profiles from a database, size and locate the systems. The user can now simulate the hourly system performance over a period of one representative year, visualize and explore the simulation results using time-series plots for temperature profiles, heat and power rates, or look at annual summaries. Similarly the user can model individual household solar water heating projects and base case conventional gas tank water heater systems, such that the results can be compared between the individual, community and base case systems. This functionality is readily available through a Jupyter notebook and a Django web framework, depending on what level of detail the user would like to access. Features - Python module to calculate solar irradiation on a tilted surface - Python module with simplified component models for Converter (solar collectors, electric resistance heater, gas burner, photovoltaic panels, heat pump), Storage (solar thermal tank, heat pump thermal tank, conventional gas tank water heater), and Distribution (distribution and solar pump, piping losses) components - Python module with preconfigured system simulation models for: base case gas tank water heaters, solar thermal water heaters (solar collector feeding a storage tank, with a tankeless gas water heater backup in a new installation cases and a base case gas tank water heater in a retrofit case) and solar electric water heaters (heat pump storage tank with an electric resistance backup) - Database with component performance parameters, California specific weather data and domestic hot water end-use load profiles - Django web framework to configure project, parametrize components and run simulation from a web browser The package contains functional and unit tests and it is structured so that it can be extended with further technologies, applications and locations.

Grahovac, Milica↗

How does the connectivity of open-framework conglomerates within multi-scale hierarchical fluvial architecture affect oil-sweep efficiency in waterflooding?

Understanding multi-phase fluid flow and transport processes within aquifers, candidate reservoirs for CO 2 sequestration, and petroleum reservoirs requires understanding a diverse set of geologic properties of the aquifer or reservoir, over a wide range of spatial and temporal scales. We focus on multiphase flow dynamics with wetting (e.g., water) and non-wetting (e.g., gas or oil) fluids, with one invading another. This problem is of general interest in a number of fields and is illustrated here by considering the sweep efficiency of oil during a waterflood. Using a relatively fine-resolution grid throughout a relatively large domain in these simulations and probing the results with advanced scientific visualization tools (Reservoir Visualization Analysis [RVA]/ ParaView software) promote a better understanding of how smaller-scale features affect the aggregate behavior at larger scales. We studied the effects on oil-sweep efficiency of the proportion, hierarchical organization, and connectivity of high-permeability open-framework conglomerate (OFC) cross-sets within the multi-scale stratal architecture found in fluvial deposits. We further analyzed oil production rate, water breakthrough time, and spatial and temporal distribution of residual oil saturation. As expected, the effective permeability of the reservoir exhibits large-scale anisotropy created by the organization of OFC cross-sets within unit bars, and the organization of unit bars within compound- bars. As a result, oil-sweep efficiency critically depends on the direction of the pressure gradient. However, contrary to expectations, the total amount of trapped oil due to the effect of capillary trapping does not depend on the magnitude of the pressure gradient within the examined range. Hence the pressure difference between production and injection wells does not affect sweep efficiency; although the spatial distribution of oil remaining in the reservoir depends on this value. Whether or not clusters of connected OFC span the domain affects only the absolute rate of oil production—not sweep efficiency.

58 GEOSCIENCES↗

Powering Data Centers with Clean Energy: A Techno-Economic Case Study of Nuclear and Renewable Energy Dependability

Rising data demands from artificial intelligence (AI) and large language models (LLMs) generating images, videos, and text have prompted increased need for larger and more robust data centers in the United States. Major companies interested in these larger data centers face the choice of linking them to existing regional grids, building stand-alone power supplies onsite, or a combination of both. The request, review, and approval process for new transmission lines to grids in the United States, however, has grown in recent years to times spans rivaling those of new construction for nuclear power plants. Building an islanded power supply for each data center is therefore becoming a prominent option. In this case study, several technologies are modeled in techno-economic simulations for long-term system costs subject to fixed electricity demand from a singular data center. A 250 MWe data center is assumed with additional 50 MWe for resiliency. Techno-economic simulations are conducted using the Holistic Energy Resource Optimization Network (HERON) software, which is a part of the Framework for Optimization of Resources and Economics (FORCE) tool suite. Technologies considered include solar, wind, lithium-ion batteries, and several types of nuclear reactors: large-scale reactors, small modular reactors, and microreactors. A low- and high-cost estimate for each technology is assumed to develop a range of expected economic performance. Low-cost estimates included several clean energy production tax credits. Different combinations of renewable energy generators with nuclear reactors are considered, ranging from a fully renewable-powered data center to a fully nuclear-powered data center. Historic time series of wind and solar availability from the Texas grid are used to train a reduced order model; this model then generates unique time series with similar characteristics of the training dataset. Multiple scenarios of weather and subsequent operations are simulated for each renewable-nuclear combination to determine total costs throughout the project lifetime. Fully renewable-powered configurations required large amounts of installed capacity (GW scale) in the simulations to meet the fixed demand of the data center. This is due to some scenarios in the historical dataset which captured low-wind and low-solar days, requiring over-building of these technologies as well as batteries to compensate for the low amounts of electricity generation. Fully nuclear-powered configurations outperformed the fully renewable and mixed renewable-nuclear configurations in terms of cost, with ranges between $1B and $10B in 2023 USDs compared to $40B+ for fully renewable configurations. Of the nuclear technologies, small modular reactors performed better economically than large-scale nuclear models due to lower projected capital costs, and both performed better than the microreactor models. These results demonstrate the applicability of firm, dispatchable electricity resources from baseload generators like nuclear power plants for operating facilities that run at constant power without daily variability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SU-E-J-190: Characterization of Radiation Induced CT Number Changes in Tumor and Normal Lung During Radiation Therapy for Lung Cancer

Purpose: To measure CT number (CTN) changes in tumor and normal lung as a function of radiation therapy (RT) dose during the course of RT delivery for lung cancer using daily IGRT CT images and single respiration phase CT images. Methods: 4D CT acquired during planning simulation and daily 3D CT acquired during daily IGRT for 10 lung cancer cases randomly selected in terms of age, caner type and stage, were analyzed using an in-house developed software tool. All patients were treated in 2 Gy fractions to primary tumors and involved nodal regions. Regions enclosed by a series of isodose surfaces in normal lung were delineated. The obtained contours along with target contours (GTVs) were populated to each singlephase planning CT and daily CT. CTN in term of Hounsfield Unit (HU) of each voxel in these delineated regions were collectively analyzed using histogram, mean, mode and linear correlation. Results: Respiration induced normal lung CTN change, as analyzed from single-phase planning CTs, ranged from 9 to 23 (±2) HU for the patients studied. Normal lung CTN change was as large as 50 (±12) HU over the entire treatment course, was dose and patient dependent and was measurable with dose changes as low as 1.5 Gy. For patients with obvious tumor volume regression, CTN within the GTV drops monotonically as much as 10 (±1) HU during the early fractions with a total dose of 20 Gy delivered. The GTV and CTN reductions are significantly correlated with correlation coefficient >0.95. Conclusion: Significant RT dose induced CTN changes in lung tissue and tumor region can be observed during even the early phase of RT delivery, and may potentially be used for early prediction of radiation response. Single respiration phase CT images have dramatically reduced statistical noise in ROIs, making daily dose response evaluation possible.

60 APPLIED LIFE SCIENCES↗

radkit v1.2

The radkit software suite (python) consists of three primary libraries: stark, trajan, and curie. The trajan library provides the tools to analyze and manipulate data from lidar and inertial measurement unit (IMU) devices as well as trajectories from algorithms such as simultaneous localization and mapping (SLAM). These components allow reading and writing standard data formats, performing rigid affine transformations, discretizing three-dimensional space, and visualizing data products. The curie library comprises a standard set of object-oriented tools for radiation data and analysis in the following modules: (1) listmode and binmode data classes with methods for manipulation, plotting, slicing and file IO; (2) radiological/nuclear source detection/identification analysis results; (3) source encounters of correlated analyses and (4) energy-dependent angular detector response functions. The stark package provides low-level tools that are leveraged by both curie and trajan. The tools are flexible for offline analysis as well as performant for real-time integrations. The radkit libraries have associated Robot Operating System packages for use in real-time and robotic systems.

Joshi, Tenzing↗

Generation of random geological models using multi-randomization for machine learning

Generating high-fidelity geological models is essential for advancing machine learning (ML) methods in automated seismic interpretation. For instance, seismic images paired with corresponding fault labels are foundational for ML-based fault detection from seismic migration sections. While several open-access datasets of random geological models exist, open-source tools specifically designed to produce large volumes of such models for ML applications remain scarce. To address this gap, we present RGM (Random Geological Model), an open-source software package for efficiently generating 2D and 3D synthetic geological models tailored for ML workflows. RGM supports the creation of diverse model components, including medium property distributions (P-/S-wave velocities and density), seismic reflectivity images (i.e., synthetic migration sections), relative geological time, and discrete fault attributes such as probability, dip, strike, rake, and displacement. It also accommodates the creation of complex geological features such as salt bodies and unconformities. The model generation algorithm employs a multi-randomization strategy, yielding an effectively infinite-dimensional model space that encompasses a wide range of geological scenarios and associated seismic features. Furthermore, RGM incorporates a method to generate synthetic elastic migration images using analytical elastic reflection coefficients combined with frequency-dependent scaling. This functionality enables the creation of training datasets for ML models that leverage elastic seismic images. RGM is implemented in modern object-oriented Fortran, allowing users to flexibly control statistical parameters governing model variability. We demonstrate the capability, performance, and geological realism of the package through comprehensive 2D and 3D examples.

58 GEOSCIENCES↗

VTAnDeM: A python toolkit for simultaneously visualizing phase stability, defect energetics, and carrier concentrations of materials

Phase stability, defect formation energies, and carrier concentrations are closely interrelated features of semiconductors. Due to their joint dependence on the multidimensional chemical potential space, it is challenging to quantitatively establish patterns between these quantities in a given semiconductor, especially when the semiconductor is comprised of multiple elements. To enable synchronous visualization and analysis of these complementary material properties and their interdependence, we developed the Visualization Toolkit for Analyzing Defects in Materials (VTAnDeM). This python-based toolkit allows users to interactively explore how defect formation energies and carrier concentrations vary across the composition and chemical potential spaces of multicomponent semiconductors. Here, we illustrate the computational workflow that employs VTAnDeM as a post-processing tool for first-principles calculations and describe the data organization and theory underlying the visualization scheme. Furthermore, we believe that this software will serve as a useful tool for simultaneously visualizing the often complex and non-intuitive chemical potential – defect – carrier concentration phase space of semiconductors.

36 MATERIALS SCIENCE↗

Simple and statistically sound recommendations for analysing physical theories

Physical theories that depend on many parameters or are tested against data from many different experiments pose unique challenges to statistical inference. Many models in particle physics, astrophysics and cosmology fall into one or both of these categories. These issues are often sidestepped with statistically unsound ad hoc methods, involving intersection of parameter intervals estimated by multiple experiments, and random or grid sampling of model parameters. Whilst these methods are easy to apply, they exhibit pathologies even in low-dimensional parameter spaces, and quickly become problematic to use and interpret in higher dimensions. In this article we give clear guidance for going beyond these procedures, suggesting where possible simple methods for performing statistically sound inference, and recommendations of readily-available software tools and standards that can assist in doing so. Our aim is to provide any physicists lacking comprehensive statistical training with recommendations for reaching correct scientific conclusions, with only a modest increase in analysis burden. Furthermore, our examples can be reproduced with the code publicly available at Zenodo.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Clinical introduction of image lag correction for a cone beam CT system

Purpose: Image lag in the flat-panel detector used for Linac integrated cone beam computed tomography (CBCT) has a degrading effect on CBCT image quality. The most prominent visible artifact is the presence of bright semicircular structure in the transverse view of the scans, known also as radar artifact. Several correction strategies have been proposed, but until now the clinical introduction of such corrections remains unreported. In November 2013, the authors have clinically implemented a previously proposed image lag correction on all of their machines at their main site in Amsterdam. The purpose of this study was to retrospectively evaluate the effect of the correction on the quality of CBCT images and evaluate the required calibration frequency. Methods: Image lag was measured in five clinical CBCT systems (Elekta Synergy 4.6) using an in-house developed beam interrupting device that stops the x-ray beam midway through the data acquisition of an unattenuated beam for calibration. A triple exponential falling edge response was fitted to the measured data and used to correct image lag from projection images with an infinite response. This filter, including an extrapolation for saturated pixels, was incorporated in the authors’ in-house developed clinical CBCT reconstruction software. To investigate the short-term stability of the lag and associated parameters, a series of five image lag measurement over a period of three months was performed. For quantitative analysis, the authors have retrospectively selected ten patients treated in the pelvic region. The apparent contrast was quantified in polar coordinates for scans reconstructed using the parameters obtained from different dates with and without saturation handling. Results: Visually, the radar artifact was minimal in scans reconstructed using image lag correction especially when saturation handling was used. In patient imaging, there was a significant reduction of the apparent contrast from 43 ± 16.7 to 15.5 ± 11.9 HU without the saturation handling and to 9.6 ± 12.1 HU with the saturation handling, depending on the date of the calibration. The image lag correction parameters were stable over a period of 3 months. The computational load was increased by approximately 10%, not endangering the fast in-line reconstruction. Conclusions: The lag correction was successfully implemented clinically and removed most image lag artifacts thus improving the image quality. Image lag correction parameters were stable for 3 months indicating low frequency of calibration requirements.

61 RADIATION PROTECTION AND DOSIMETRY↗

radkit base v1.6

The radkit (base) software suite (python) consists of three primary libraries: stark, trajan, and curie. The trajan library provides the tools to analyze and manipulate data from lidar and inertial measurement unit (IMU) devices, cameras, as well as trajectories from algorithms such as simultaneous localization and mapping (SLAM). These components allow reading and writing standard data formats, performing rigid affine transformations, discretizing three-dimensional space, and visualizing data products. The curie library comprises a standard set of object-oriented tools for radiation data and analysis in the following modules: (1) listmode and binmode data classes with methods for manipulation, plotting, slicing and file IO; (2) radiological/nuclear source detection/identification analysis results; (3) source encounters of correlated analyses and (4) energy-dependent angular detector response functions. The stark package provides low-level tools that are leveraged by both curie and trajan. The tools are flexible for offline analysis as well as performant for real-time integrations.

Salathe, Marco [Lawrence Berkeley National Laborat↗

Simulation Tools for Characterizing Stress Distribution in Laser Welded Dissimilar Joints

This project focuses on developing a thermo-metallurgical-mechanical modeling method to accurately predict the microstructural evolution and residual stress in laser welding between dissimilar metals, such as HSLA steel and high carbon equivalent (CE) gear steel. The method leverages a comprehensive material database to model the temperature and rate dependent phase transformations, along with their associated effects on material properties, such as thermal expansion and flow stress, throughout the welding process. A key innovation is the incorporation of phase transformation and phase-specific properties, which enhances the accuracy of residual stress predictions. The mixture material in the fusion zone due to the dissimilar metals will also be addressed in the numerical model. This is especially critical in scenarios involving phase transformations in the fusion zone and heat-affected zone (HAZ), where the phase changes can induce substantial residual stress variations. The material database has been generated using JMatPro. The modeling approach is implemented through a custom User Material (UMAT) subroutine, executed with the commercial finite element software Abaqus.

36 MATERIALS SCIENCE↗

Simulation Tools for Characterizing Stress Distribution in Laser Welded Dissimilar Joints

This project focuses on developing a thermo-metallurgical-mechanical modeling method to accurately predict the microstructural evolution and residual stress in laser welding between dissimilar metals, such as HSLA steel and high carbon equivalent (CE) gear steel. The method leverages a comprehensive material database to model the temperature and rate dependent phase transformations, along with their associated effects on material properties, such as thermal expansion and flow stress, throughout the welding process. A key innovation is the incorporation of phase transformation and phase-specific properties, which enhances the accuracy of residual stress predictions. The mixture material in the fusion zone due to the dissimilar metals will also be addressed in the numerical model. This is especially critical in scenarios involving phase transformations in the fusion zone and heat-affected zone (HAZ), where the phase changes can induce substantial residual stress variations. The material database has been generated using JMatPro. The modeling approach is implemented through a custom User Material (UMAT) subroutine, executed with the commercial finite element software Abaqus.

36 MATERIALS SCIENCE↗

Development of X-Ray FEL Oscillators with Higher Out-Coupling Efficiency

This program focused on the development of high-outcoupling efficiency resonators for x-ray free-electron laser oscillators (XFELOs). The goal was to produce a viable design for an XFELO that can be implemented on the LCLS-II which is the x-ray FEL facility under construction at the Stanford Linear Accelerator Center (SLAC). The program designed at regenerative amplifier (RAFEL) design that employs a high-gain undulator with a low-Q resonator with the goal of producing a scientific design for the RAFEL as well as a software suite that can be used to design XFELOs. The Phase I program considered a resonator consisting of six diamond Bragg reflectors/mirrors with two focusing lenses. This resonator was used in conjunction with the electron beam produced by the LCLS-II and the HXR undulator to design a RAFEL producing 3.05 keV photons in the fundamental resonance and 9.15 keV photons in the 3rd harmonic. The research program included the extension of the Optics Propagation Code (OPC) to describe Bragg reflection from diamond crystal mirrors and went on to use OPC, in conjunction with the MINERVA simulation code to treat the undulator interaction, to simulate the RAFEL. Simulations were conducted in both the steady-state and time-dependent regimes to determine the basic performance characteristics of the RAFEL.

43 PARTICLE ACCELERATORS↗