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At least 721 records · Page 40

A novel tool for improving the data collection process during control room modernization human-system interface testing and evaluation activities - 271

The U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program is developing a scientific basis to extend the existing U.S. nuclear power plant (NPP) operating life beyond the current 60-year licensing period and to ensure NPP long-term reliability, productivity, safety, and security. Under the Advanced Instrumentation, Information, and Control (II and C) Systems Technologies pathway, the LWRS Program conducts targeted research and development to address long-term aging and obsolescence of existing instrumentation and control technologies, as well as to implement and test new digital II and C technology that enables broad innovation and business improvement in the NPP operating model. To this end, the role of human factors engineering (HFE) is important as part of ensuring that the control room modernization (CRM) activities account for the operator's cognitive and physiological characteristics. Part of the HFE process for CRM entails conducting tests and evaluations (T and Es) that will inform the design of new human-system interface (HSI) technologies. Qualitative data that captures operator feedback and important human-system interactions are an important part of T and E. However, the analyzing this qualitative data in order to provide actionable design recommendations can be time-consuming and error prone. This paper presents an early version of a tool, which uses a combination of natural language processing and supervised machine learning to support the analysis of qualitative data. The objectives of this tool is to improve the process of (1) sifting through freeform text for improved design issue identification, (2) maintaining consistency in theme coding conventions, and (3) readily providing actionable design guidance that can be traceable to state-of-the-art HFE guidelines such as NUREG-0700. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Leveraging interpolation models and error bounds for verifiable scientific machine learning

Effective verification and validation techniques for modern scientific machine learning workflows are challenging to devise. Statistical methods are abundant and easily deployed, but often rely on speculative assumptions about the data and methods involved. Error bounds for classical interpolation techniques can provide mathematically rigorous estimates of accuracy, but often are difficult or impractical to determine computationally. Here, in this work, we present a best-of-both-worlds approach to verifiable scientific machine learning by demonstrating that (1) multiple standard interpolation techniques have informative error bounds that can be computed or estimated efficiently; (2) comparative performance among distinct interpolants can aid in validation goals; (3) deploying interpolation methods on latent spaces generated by deep learning techniques enables some interpretability for black-box models. We present a detailed case study of our approach for predicting lift-drag ratios from airfoil images. Code developed for this work is available in a public Github repository.

97 MATHEMATICS AND COMPUTING↗

PIPER: Performance Insights for Programmers and Exascale Runtimes

During the lifetime of the project, the PIPER at the University of Utah worked in collaboration with the team from the partner institutions to establish a set of software tools for analyzing and improving the performance parallel computing tools. These activities complement and complete the work performed by the other X-Stack 2 projects with the definition of a common data models and computing infrastructures, which have been a central element in the targeted performance analysis pipeline and new programming models. The University of Utah team have focused mainly on developing data analysis and visualization systems to facilitate exploration, comparison and evaluation of the behavior and performance of complex algorithms in modern HPC infrastructures. This is involved several demonstrations of the performance achieved and presentation of the results in a way that facilitates the users understand bottlenecks and ways to overcome them. One major focus of the University of Utah activities has been the analysis of the performance characteristics of Fat-Tree and Dragonfly topology networks. The work involved the development of practical visualization systems especially in collaboration with the team at LLNL, and published several papers and gave invited talks at prestigious venues such as the Salishan Conference on High-Speed Computing or the International Conference on High Performance Computing, Data, and Analytics. In addition, the university of Utah team has advanced the core activities on analyzing the performance characteristics of I/O and other data movement systems and their practical use for scaling Uintah and other simulation codes poised for use in the exascale computing environments of the future.

42 ENGINEERING↗

Direct NeTS sampling of nuclear graphite $S(α, β, T)$ in Serpent

For advanced reactor applications, Neural Thermal Scattering (NeTS) modules were developed to predict the thermal scattering law (TSL or $S(α, β, T)$) of a nuclear graphite neutron moderator. NeTS are multi-layer, feedforward artificial neural networks, which act as universal function approximators designed for TSL datasets. In this case, a 4-layer neural network with 164 neurons per layer is trained using FLASSH evaluated data in PyTorch and serialized as a torchscript dictionary to predict $S(α, β, T)$ on-the-fly. Relative, absolute and maximum percent deviations of NeTS from File 7 data generated using the FLASSH code are on the order of 0.01%, 0.1% and 1%, respectively, with low inference latencies of 0.000172 s per $S(α, β, T)$ at a given temperature. Capturing the full dimensionality of possible inelastic neutron-lattice interactions, NeTS functionality is embedded in the Serpent Monte Carlo code, where $S(α, β, T)_{NeTS}$ sampling is conducted on-the-fly and compared to ACE look-up-tables for predicting TREAT criticality. k-eff differences between sampling algorithms of 6 pcm are observed and are within the order of Monte Carlo uncertainty. Compared to discrete and continuous-energy ACE files (30 MB and 131 MB per temperature), the NeTS format is on the order of 200–300 kB for a continuous-temperature, interpolation-free representation of $S(α, β, T)$ and cross sections. NeTS-in-Serpent runtimes comparable with ACE look-up tables are achieved by scaling NeTS for high performance computing architectures with hybrid OpenMP + MPI parallelization. This work validates a novel, self-contained reactor physics framework for predictive cross sections, and demonstrates a general methodology for embedding modern machine learning libraries within existing neutronic analysis frameworks.

Nuclear Criticality Safety Program (NCSP)↗

Texas authorizes disposal of large quantities of depleted uranium at wcs - 15626

The U.S. Nuclear Regulatory Commission (NRC) has been actively engaged in a rulemaking process that would revise Title 10 of the Code of Federal Regulations (CFR), Part 61, Licensing Requirements for Land Disposal of Radioactive Waste, to govern the disposal of large quantities of Depleted Uranium (DU) and Blended Waste (referred to as Unique Waste Streams). While the NRC plans to propose a Site Specific Analysis (SSA) rulemaking in early 2015, they have already issued guidance to Agreement States which identified general disposal criteria that could be used should a licensee propose to dispose of Unique Waste Streams before their rulemaking was completed. On August 5, 2013, Waste Control Specialists LLC (WCS) submitted a major license amendment application for review and approval to the Texas Commission on Environmental Quality (TCEQ). This major license amendment request proposed, among other things, authorization to dispose of large quantities of DU at its Federal Facility Waste Disposal Facility (FWF). Pursuant to Title 30 of the Texas Administrative Code (TAC), Rule 336.709, Technical and Environmental Analyses, disposal of waste must be sufficient to meet the radiological dose criteria for a minimum period of performance of 1,000 years after closure or the period where peak dose occurs, whichever is longer. These regulations are more stringent than those of any other state that hosts a facility authorized to dispose of Low-Level Radioactive Waste (LLW) in the U.S. On August 28, 2014, the TCEQ approved the major amendment request authorizing disposal of large quantities of DU. During the licensing review process, significant technical issues were successfully resolved ensuring that large quantities of DU could be safely isolated from the biosphere for long time periods after site closure. Many important lessons were learned during the licensing proceedings that have potential significant impacts to the licensed community. Namely that a modern, well designed disposal facility that is properly sited geologically and in an arid environment is ideal for ensuring that long-lived alpha emitting radionuclides are sufficiently isolated to protect public health for long into the future. The DOE is currently finalizing plans to complete a Supplemental Environmental Analysis (EA) to support shipments of DU for disposal at WCS' FWF as required under the National Environmental Policy Act of 1970. The DOE may begin shipments of DU for disposal to WCS FWF that was licensed and constructed to support disposal of waste that is the responsibility of the federal government as stipulated in the Low-Level Radioactive Waste Policy Amendments Act of 1985. This paper will present the regulatory history of events that initiated the NRC's rulemaking for Unique Waste Streams and the technical analysis that were conducted in support of WCS' major amendment that has been approved by the TCEQ. A description of the geological characteristics and engineering designs used to support the Performance Assessment will be included. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Spectrally accelerated edge and scrape-off layer gyrokinetic turbulence simulations

This paper presents the first gyrokinetic (GK) simulations of edge and scrape-off layer (SOL) turbulence accelerated by a velocity-space spectral approach in the full-f GK code GENE-X. Building upon the original grid velocity-space discretization, we derive and implement a new spectral formulation and verify the numerical implementation using the method of manufactured solution. We conduct a series of spectral turbulence simulations focusing on the TCV-X21 reference case (Oliveira et al., 2022 [26]) and compare these results with previously validated grid simulations (Ulbl et al., 2023 [25]). The spectral approach reproduces the outboard midplane (OMP) profiles (density, temperature, and radial electric field), dominated by trapped electron mode (TEM) turbulence, with excellent agreement and significantly lower velocity-space resolution. As a consequence, the spectral approach reduces the computational cost (CPUh) by at least an order of magnitude, of approximately 50 for the TCV-X21 case. This enables high-fidelity GK simulations to be performed within a few days on modern CPU-based supercomputers for medium-sized devices and establishes GENE-X as a powerful tool for studying edge and SOL turbulence, moving towards reactor-relevant devices like ITER.

Gyrokinetic↗

ProteoSign: an end-user online differential proteomics statistical analysis platform

Profiling of proteome dynamics is crucial for understanding cellular behavior in response to intrinsic and extrinsic stimuli and maintenance of homeostasis. Over the last 20 years, mass spectrometry (MS) has emerged as the most powerful tool for large-scale identification and characterization of proteins. Bottom-up proteomics, the most common MS-based proteomics approach, has always been challenging in terms of data management, processing, analysis and visualization, with modern instruments capable of producing several gigabytes of data out of a single experiment. Here, we present ProteoSign, a freely available web application, dedicated in allowing users to perform proteomics differential expression/abundance analysis in a userfriendly and self-explanatory way. Although several non-commercial standalone tools have been developed for post-quantification statistical analysis of proteomics data, most of them are not end-user appealing as they often require very stringent installation of programming environments, third-party software packages and sometimes further scripting or computer programming. To avoid this bottleneck, we have developed a user-friendly software platform accessible via a web interface in order to enable proteomics laboratories and core facilities to statistically analyse quantitative proteomics data sets in a resource-efficient manner. ProteoSign is available at http://bioinformatics.med.uoc.gr/ProteoSign and the source code at https://github.com/yorgodillo/ ProteoSign.

59 BASIC BIOLOGICAL SCIENCES↗

RingX: Scalable Parallel Attention for Long-Context Learning on HPC

The attention mechanism has become foundational for remarkable AI breakthroughs since the introduction of the Transformer, driving the demand for increasingly longer context to power frontier models such as large-scale reasoning language models and high-resolution image/video generators. However, its quadratic computational and memory complexities present substantial challenges. Current state-of-the-art parallel attention methods, such as ring attention, are widely adopted for long-context training but utilize a point-to-point communication strategy that fails to fully exploit the capabilities of modern HPC network architectures. In this work, we propose ringX, a scalable family of parallel attention methods optimized explicitly for HPC systems. By enhancing workload partitioning, refining communication patterns, and improving load balancing, ringX achieves up to 3.4 × speedup compared to conventional ring attention on the Frontier supercomputer. Optimized for both bi-directional and causal attention mechanisms, ringX demonstrates its effectiveness through training benchmarks of a Vision Transformer (ViT) on a climate dataset and a Generative Pre-Trained Transformer (GPT) model, Llama3 8B. Our method attains an end-to-end training speedup of approximately 1.5 × in both scenarios. To our knowledge, the achieved 38% model FLOPs utilization (MFU) for training Llama3 8B with a 1M-token sequence length on 4,096 GPUs represents one of the highest training efficiencies reported for long-context learning on HPC systems. Our code implementation is available at https://github.com/jqyin/ringX-attention.

Yin, Junqi [ORNL] (ORCID:0000000338435520)↗

Bringing Fenton Hill into the Digital Age: Data Conversion in Support of the Geothermal Technologies Office Code Comparison Study Challenge Problems

The Geothermal Technologies Office Code Comparison Study (GTO-CCS) was established by the U.S. Department of Energy to facilitate collaboration among members of the geothermal modeling community and to evaluate and improve upon the ability of existing codes to simulate thermal, hydrological, mechanical, and chemical processes associated with complex enhanced geothermal systems (EGS). The first stage of the project, which has been completed, involved comparing simulations for seven benchmark problems that were primarily designed using well-prescribed, simplified data sets. In the second stage, the participating teams are tackling two challenge problems based on the EGS research conducted in hot dry rock (HDR) at Fenton Hill, near Los Alamos, New Mexico. The Fenton Hill project, conducted by Los Alamos National Laboratory (LANL) from 1970 to 1995, was the world’s first HDR demonstration project. One of the criteria for selecting this experiment as the basis for the challenge problems was the amount and availability of data for generating model inputs. The Fenton Hill HDR system consisted of two reservoirs – an earlier Phase I reservoir tested from 1974 to 1981 and a deeper Phase II reservoir tested from 1980 to 1995. Detailed accounts of both phases of the HDR project have been presented in a number of books and reports, including a recently published summary of the lessons learned and a final report with a chronological description of the Fenton Hill project, prepared by LANL. Project documents and records have been archived and made public through the National Geothermal Data System (NGDS). Some of the data acquired from Phase II are available in electronic format readable on modern computers. These include the microseismic data from some of the important experiments (e.g. the massive hydraulic fracturing test conducted in 1983) and the injection/production wellhead data from the circulation tests conducted between 1992-1995. However, much of the data collected during the project, while publicly available, currently only exist in the form of tables or graphs within scanned documents. Therefore, in support of the GTO-CCS, the data needed for developing simulation inputs are being compiled and converted to platform independent, open readable formats so that all participating teams will have access to the same electronic data set. In some cases this requires conversion using optical character recognition, digitizing existing images, and generating the appropriate metadata from project documents. The GTO-Velo knowledge management framework, developed by Pacific Northwest National Laboratory (PNNL), was used for the benchmark problem stage of the comparison study and will also be used as the data repository for the challenge problem data sets. It is staggering and impractical to convert all published data for the Fenton Hill site, so the focus is on data that supports simulations for the three topical areas defined by the study for the challenge problems: 1) reservoir creation/stimulation, 2) reactive and passive transport, and 3) thermal recovery. Conversion of these data provide value not only to GTO-CCS participants, but also to members of the geothermal community at large who may be interested in revisiting the Fenton Hill experiment in the future.

Code Comparison Study↗

FULCRUM user interface for SCALE 6.2

SCALE 6.2 consolidated the multiple special-purpose graphical user interfaces (GUI) of SCALE 6.1 into a completely new and modern interface called FULCRUM. FULCRUM is a cross-platform GUI designed to create, edit, validate, and visualize SCALE input, output, and data. It is intended to be usable by both novice and experienced SCALE users with an unobtrusive design. This paper presents a summary of FULCRUM capabilities. Specifically, interactive input validation, context-aware auto-completion, navigation, interactive geometry visualization with mesh results overlay, job execution, data plotting, and highly configurable workspace layouts will be discussed. (authors)

97 MATHEMATICS AND COMPUTING↗

SU-F-P-09: A Global Medical Physics Collaboration for Implementation of Modern Radiotherapy in Botswana

Purpose: The global burden of cancer is considerable, particularly in low and middle-income countries. Massachusetts General Hospital (MGH) and Botswana-Harvard AIDS Institute have partnered with the oncology community and government of Botswana to form BOTSOGO (BOTSwana Oncology Global Outreach) to address the rising burden of cancer in Botswana. Currently, radiation therapy (RT) is only available at a single linear accelerator (LINAC) in Gaborone Private Hospital (GPH). BOTSOGO worked to limit the absence of RT during a LINAC upgrade and ensure a safe transition to modern radiotherapy techniques. Methods: The existing Elekta Precise LINAC was decommissioned in November 2015 and replaced with a new Elekta VERSA-HD with IMRT/VMAT/CBCT capability. Upgraded treatment planning and record-and-verify systems were also installed. Physicists from GPH and MGH collaborated during an intensive on-site visit in Botswana during the commissioning process. Measurements were performed using newly purchased Sun Nuclear equipment. Photon beams were matched with an existing model to minimize the time needed for beam modeling and machine down time. Additional remote peer review was also employed. Independent dosimetry was performed by irradiating OSLDs, which were subsequently analyzed at MGH. Results: Photon beam quality agreed with reference data within 0.2%. Electron beam data agreed with example clinical data within 3%. Absolute dose calibration was performed using both IAEA and AAPM protocols. Absolute dose measurements with OSLDs agreed within 5%. Quentry cloud-based software was installed to facilitate remote review of treatment plans. Patient treatments resumed in February 2016. The time without RT was reduced, therefore likely resulting in reduced patient morbidity/mortality. Conclusion: A global physics collaboration was utilized to commission a modern LINAC in a resource-constrained setting. This can be a useful model in other areas with limited resources. Further use of technology and on-site exchanges will facilitate the introduction of more advanced techniques in Botswana. We acknowledge funding support from the AAPM International Educational Activities Committee and the NCI Federal Share Proton Beam Program Income Grant.

60 APPLIED LIFE SCIENCES↗

Nuclear Power Plant Cyber Security Discrete Dynamic Event Tree Analysis (LDRD 17-0958) FY17 Report

Instrumentation and control of nuclear power is transforming from analog to modern digital assets. These control systems perform key safety and security functions. This transformation is occurring in new plant designs as well as in the existing fleet of plants as the operation of those plants is extended to 60 years. This transformation introduces new and unknown issues involving both digital asset induced safety issues and security issues. Traditional nuclear power risk assessment tools and cyber security assessment methods have not been modified or developed to address the unique nature of cyber failure modes and of cyber security threat vulnerabilities. iii This Lab-Directed Research and Development project has developed a dynamic cyber-risk in- formed tool to facilitate the analysis of unique cyber failure modes and the time sequencing of cyber faults, both malicious and non-malicious, and impose those cyber exploits and cyber faults onto a nuclear power plant accident sequence simulator code to assess how cyber exploits and cyber faults could interact with a plants digital instrumentation and control (DI&C) system and defeat or circumvent a plants cyber security controls. This was achieved by coupling an existing Sandia National Laboratories nuclear accident dynamic simulator code with a cyber emulytics code to demonstrate real-time simulation of cyber exploits and their impact on automatic DI&C responses. Studying such potential time-sequenced cyber-attacks and their risks (i.e., the associated impact and the associated degree of difficulty to achieve the attack vector) on accident management establishes a technical risk informed framework for developing effective cyber security controls for nuclear power.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Real Time - Optimal Power Flow Based Distributed Energy Resources Management System (DERMS) (CRADA Number CRD-20-16909 Final Report)

The integration of behind-the-meter distributed energy resources (DERs) into distribution systems brings transformative changes to power systems. This requires operators and planners to find solutions to modernize electric grids and to effectively manage DERs for grid services. NREL developed novel DER management algorithms (referred to as Real-Time Optimal Power Flow, RT-OPF) through U.S. Department of Energy (DOE)-funded efforts, including Advanced Research Projects Agency–Energy (ARPA-E) Network Optimized Distributed Energy Systems (NODES) funding. This cutting-edge control technology aims to modernize distribution systems with large amounts of DER integration, which will help utilities solve issues brought by renewable integration and build resilient and renewable-based electric grids nationwide. Utilidata worked with NREL to investigate the commercialization opportunity of this RT-OPF-based distributed energy resource management system (DERMS). In this project, NREL performs the technology transfer of the RT-OPF to Utilidata to help them fully understand the RT-OPF solution, to identify potential engineering hurdles, and to assess the expected commercial value of various RT-OPF use cases and deployment. The technology transfer work includes two major tasks. First, NREL performs an in-depth knowledge transfer of the entire RT-OPF solution to Utilidata to help them gain an extensive and detailed understanding of the complete RT-OPF solution. In this task, NREL provides exhaustive information (e.g., documentation, code packages, laboratory and field trial data, performance results) while conducting in-depth training sessions to provide a thorough explanation of the entire solution. NREL hosts meetings to present different topics related to the RT-OPF solution, and question-and-answer sessions are included in each meeting to better explain the RT-OPF-related work. Second, the RT-OPF simulations are performed in a laboratory environment. The main objectives of this task are to walk through with Utilidata engineers how to set up a simulation of RT-OPF, identifying each RT-OPF code block/component in operation, learning how these components interact with each other, and eventually running RT-OPF simulations under various system conditions. This task helps Utilidata engineers understand performance limitations and constraints while also quantifying the commercial value of the RT-OPF for different use cases. Based on these two tasks, Utilidata engineers should be able to define and prioritize the next steps of RT-OPF implementation with an eye toward commercial success and scalability of the solution. The next steps are expected to be part of a new project following the conclusion of this project.

24 POWER TRANSMISSION AND DISTRIBUTION↗

High-Throughput Material Characterization using the Virtual Fields Method

Modeling material and component behavior using finite element analysis (FEA) is critical for modern engineering. One key to a credible model is having an accurate material model, with calibrated model parameters, which describes the constitutive relationship between the deformation and the resulting stress in the material. As such, identifying material model parameters is critical to accurate and predictive FEA. Traditional calibration approaches use only global data (e.g. extensometers and resultant force) and simplified geometries to find the parameters. However, the utilization of rapidly maturing full-field characterization techniques (e.g. Digital Image Correlation (DIC)) with inverse techniques (e.g. the Virtual Feilds Method (VFM)) provide a new, novel and improved method for parameter identification. This LDRD tested that idea: in particular, whether more parameters could be identified per test when using full-field data. The research described in this report successfully proves this hypothesis by comparing the VFM results with traditional calibration methods. Important products of the research include: verified VFM codes for identifying model parameters, a new look at parameter covariance in material model parameter estimation, new validation techniques to better utilize full-field measurements, and an exploration of optimized specimen design for improved data richness.

36 MATERIALS SCIENCE↗

Preliminary Cyber-Informed Dynamic Branch Conditions for Analysis with the Dynamic Simplified Cyber MELCOR Model

Instrumentation and control of nuclear power is transforming from analog to modern digital assets. These control systems perform key safety and security functions. This transformation is occurring in new plant designs as well as in the existing fleet of plants as the operation of those plants is extended to 60 years. This transformation introduces new and unknown exploits involving both digital asset induced safety issues and security exploits. Traditional the open literature of nuclear power risk assessment tools and cyber security assessment methods have not been modified or developed to address the unique nature of cyber failure modes and of cyber security threats. Starting in 2015, Sandia National Laboratories (SNL) embarked on a two year dynamic cyber-risk informed project to facilitate the analysis of unique cyber failure modes and the time sequencing of cyber faults, both malicious and non-malicious, and impose those cyber exploits and cyber faults onto a nuclear power plant accident sequence simulator code to assess how cyber exploits and cyber faults could interact with a plant's digital instrumentation and control (DI and C) system in the absence of digital controls. This will be achieved by coupling SNL's existing dynamic scheduler code (ADAPT), nuclear accident simulator code (MELCOR), and cyber Emulytics code (SCEPTRE) to demonstrate real-time simulation of cyber exploits and their impact on automatic DI and C responses. Studying such potential time-sequenced cyber-attacks and their risks (i.e., the associated impact and the associated degree of difficulty to achieve the attack vector) as they pertain to accident management will provide a risk informed basis for developing effective cyber security controls for nuclear power. This paper will discuss the rationale behind the proposed generic cyber exploits for an abstracted Pressurized Water Reactor that has adopted a unified DI and C System. Other papers related to this project submitted to this conference discuss: - The MELCOR model for this abstracted reactor, called the Dynamic Simplified Cyber (DSC) model, - Modifications to ADAPT to: Extend the framework for multiple simulators, Incorporation of importance measures into dynamic event tree analysis, Sort and reduce the dynamic event tree based upon inputs to or outputs from the tree, and - A feasibility study for using density based clustering methods with dynamic time wrapping to cluster and prune dynamic event trees. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Computer-controlled finishing via dynamically constraint position-velocity-time scheduler

In a Computer Numerical Controlled (CNC) finishing process, the target material removal from an optical surface is guided by the convolution between the influence function of a machine tool and its dwell time at certain points over the surface. To reduce dynamics stressing and increase machining efficiency, the dwell time must be converted to varying velocities, which are the actual inputs to the machine tool controller. Conventionally, the conversion assumed constant acceleration and relied on linear motion interpolation, which caused discontinuities in velocities. This unsmooth motion affects the material removal distribution, and, thus, the accuracy of the finished surface shape. Many modern CNC machines support the smoother, cubic-polynomial interpolated Position-Velocity-Time (PVT) motion mode; however, the conventional scheduler may fail to provide suitable velocities for the PVT. Here in this study answers this challenge by proposing a novel PVT-based velocity scheduler that achieves smooth motion while considering CNC dynamic limits. Firstly, the principle of the PVT is explained, and the PVT-based velocity scheduler is formulated. Secondly, a quadratic programming is used to optimize the velocities by imposing the CNC dynamic constraints and the C 1 continuities (zeroth and first derivatives are continuous) simultaneously. Thirdly, the smoothness and accuracy of the scheduled velocities are studied on different kinds of tool paths via simulation. Finally, a sub-0.3 nm level surface finishing experiment using ion beam figuring is demonstrated to verify the feasibility of the proposed method. The PVT-based scheduler and simulator code is open-sourced.

36 MATERIALS SCIENCE↗

SU-C-BRB-05: Investigation of Conformal Arc Therapy Utilizing Newly Designed Cobalt 60 Machine

Purpose: A new modernized design for cobalt 60 (Co-60) machines is being developed with a ring type gantry. In this study we investigate the beneficial outcome of the new design for conformal arc therapy for various clinical sites. The new modality was evaluated based on isodose distributions and dose volume histograms as compared to 6MV photon beams from conventional linear accelerators. Methods: Computed tomographic images of seven different SBRT patients were selected from our patient database. All of these cases were previously planned on the Eclipse treatment planning system. New plans for these patients were generated with a modified conformal arc technique using both 6MV and Co-60 beams. The conformal arc was created by the delivery of treatment fields conformal to the target cross-section at every 5 or 10 degrees. The field shape was modified or turned off when it initially passed through a critical structure. Monte Carlo codes, MCBEAM and MCPLAN, were used for the machine head simulation and phantom/patient dose calculation, respectively. In the new Co-60 machine design, the source-to-isocenter distance was 60cm and the treatment head included the Co-60 source, primary collimator, jaws and MLC. Results: For all cases investigated, conformal arc plans utilizing Co-60 beams achieved similar conformity (mean conformity index=1.19) comparing to 6MV photon beams. Isodose distributions were tailored similarly around the PTV; both Co-60 and 6MV plans met our clinical acceptance criteria for the target coverage, and the maximum and minimum target doses. The DVH for the Co-60 plans showed slightly lower doses to the critical structures although the differences were small in most cases. Conclusion: There were no significant dosimetric differences between 6MV and Co-60 plans. Our results confirmed that this new Co-60 design could be a cost-effective machine for advanced radiotherapy due to its low cost, low maintenance and high up time.

60 APPLIED LIFE SCIENCES↗

SU-F-T-656: Monte Carlo Study On Air Activation Around a Medical Electron Linac

Purpose: In high energy photon therapy, several radiation protection issues result from photonuclear reactions. The activation of air - directly by photonuclear reactions as well as indirectly by capture of photoneutrons generated inside the linac head - is a major point of concern for the medical staff. The purpose of this study was to estimate the annual effective dose to medical workers due to activated air around a medical high energy electron linac by means of Monte Carlo simulations. Methods: The treatment head of a Varian Clinac in 18 MV-X mode as well as the surrounding concrete bunker were modeled and the radiation transport was simulated using the Monte Carlo code FLUKA, starting from the primary electron striking the bremsstrahlung target. The activation yields in air from photo-disintegration of O-16 and N-14 nuclei as well as from neutron capture on Ar-40 nuclei were obtained from the simulations. The activation build-up, radioactive decay and air ventilation were studied using a mathematical model. The annual effective dose to workers was estimated by using published isotope specific conversion factors. Results: The oxygen and nitrogen activation yields were in contrast to the argon activation yield found to be field size dependent. The impact of the treatment room ventilation on the different air activation products was investigated and quantified. An estimate with very conservative assumptions gave an annual effective dose to workers of < 1 mSv/a. Conclusion: From the results of this study it can be concluded that the contribution of air activation to the radiation exposure to medical workers should be negligible in modern photon therapy, especially when it is compared to the dose due to prompt neutrons and the activation of heavy solid materials such as the jaws and the collimators inside the linac head.

60 APPLIED LIFE SCIENCES↗