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At least 1,441 records · Page 80

Achieving 280 Gbar hot spot pressure in DT-layered CH capsule implosions at the National Ignition Facility

We are reporting on a series of indirect-drive 0.9-scale CH capsule implosions (inner radius = 840 μm) fielded in low gas-fill (0.6 mg/cm 3 ) hohlraums of 6.72 mm diameter at the National Ignition Facility. Thanks to the 11%-reduction of the capsule size at a given hohlraum diameter compared to previously tested full-scale capsules, we achieved good hot spot symmetry control near 33% cone-fraction and without the need to invoke cross beam energy transfer. As a result, we achieved a hot spot pressure of 280 ± 40 Gbar, which is the highest pressure demonstrated in layered DT implosions with CH capsules to date. Pushing this design to higher velocity resulted in a reduction of neutron yield. Highly resolved capsule simulations suggest that higher Au M-shell preheat resulted in an increase in Atwood number at the ablator–ice interface, which leads to increased fuel-ablator instability and mixing. The results reported here provide important scaling information for next-generation CH designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Controller-Hardware-in-the-Loop Test Bed for Fast-Switching SiC-Based 50-kW PV Inverter

The recent advent of wideband gap power semiconductor devices will lay the path to the future power converters. These devices provide the advantage of high switching speed and lower losses. The high cost and high switching speeds of these devices provide a challenge in the development and validation of the fast switching inverter controls with accuracy of that of a hardware setup. In this paper an FPGA real-time simulator-based controller-hardware-in-the-loop (CHIL) testbed is used to verify the low-level and advanced inverter controls fast switching wide bandgap-based string photovoltaic inverter. The paper also includes development of the CHIL testbed, which is run at a time-step of 500 ns in order to implement 20 kHz switching frequency. The developed CHIL testbed is validated through experimental results from a three-phase, 50 kW, 480 VLLrms SiC devices based inverter.

14 SOLAR ENERGY↗

MPC4CLR (Model-Predictive-Control-for-Critical-Load-Restoration-in-Power-Distribution-Systems) [SWR-22-24]

Model predictive control (MPC) is a system or process control technique for making decisions under uncertainty via rolling look-ahead optimizations at each control step where only the current step decisions are applied, and the rest are discarded. In this work, we developed an MPC for a critical load restoration (CLR) in power distribution systems to recover system service (electricity delivery) following an extreme event-triggered substation outage. The method considers the problem of controlling distributed energy resources (DERs) of the distribution system with the objective of achieving maximum load pick up while satisfying distribution network flow and voltage constraints. A linearized optimal power flow (OPF) model is employed to represent the physics of the network. The problem formulation is augmented with a ramping (up) reserve product for the DERs to ensure improved and upward monotonic load restoration as time evolves. Simulation analysis and performance tests are performed using a modified IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage battery. The software is developed using various software packages in Julia and Python. The MPC model is implemented using the JuMP optimization language in Julia while the data analytics including renewable generation and load demand forecasts, running the MPC simulation and visualizations is performed in Python.

Eseye, Abinet Tesfaye↗

PSCAD Modules Representing PV Generator

Photovoltaic power plants (PVPs) have been growing in size, and the installation time is very short. With the cost of photovoltaic (PV) panels dropping in recent years, it can be predicted that in the next 10 years the contribution of PVPs to the total number of renewable energy power plants will grow significantly. In this project, the National Renewable Energy Laboratory (NREL) developed a dynamic modeling of the modules to be used as building blocks to develop simulation models of single PV arrays, expanded to include Maximum Power Point Tracker (MPPT), expanded to include PV inverter, or expanded to cover an entire PVP. The focus of the investigation and complexity of the simulation determines the components that must be included in the simulation. The development of the PV inverter was covered in detail, including the control diagrams. Both the current-regulated voltage source inverter and the current-regulated current source inverter were developed in PSCAD. Various operations of the PV inverters were simulated under normal and abnormal conditions. Symmetrical and unsymmetrical faults were simulated, presented, and discussed. Both the three-phase analysis and the symmetrical component analysis were included to clarify the understanding of unsymmetrical faults. The dynamic model validation was based on the testing data provided by SCE. Testing was conducted at SCE with the focus on the grid interface behavior of the PV inverter under different faults and disturbances. The dynamic model validation covers both the symmetrical and unsymmetrical faults.

14 SOLAR ENERGY↗

A feasibility and optimization study to determine cooling time and burnup of advanced test reactor fuels using a nondestructive technique

The goal of this study presented is to determine the best available non-destructive technique necessary to collect validation data as well as to determine burn-up and cooling time of the fuel elements onsite at the Advanced Test Reactor (ATR) canal. This study makes a recommendation of the viability of implementing a permanent fuel scanning system at the ATR canal and leads3 to the full design of a permanent fuel scan system. The study consisted at first in determining if it was possible and which equipment was necessary to collect useful spectra from ATR fuel elements at the canal adjacent to the reactor. Once it was establish that useful spectra can be obtained at the ATR canal the next step was to determine which detector and which configuration was better suited to predict burnup and cooling time of fuel elements non-destructively. Three different detectors of High Purity Germanium (HPGe), Lanthanum Bromide (LaBr3), and High Pressure Xenon (HPXe) in two system configurations of above and below the water pool were used during the study. The data collected and analyzed was used to create burnup and cooling time calibration prediction curves for ATR fuel. The next stage of the study was to determine which of the three detectors tested was better suited for the permanent system. From spectra taken and the calibration curves obtained, it was determined that although the HPGe detector yielded better results, a detector that could better withstand the harsh environment of the ATR canal was needed. The in-situ nature of the measurements required a rugged fuel scanning system, low in maintenance and easy to control system. Based on the ATR canal feasibility measurements and calibration results it was determined that the LaBr3 detector was the best alternative for canal in-situ measurements; however in order to enhance the quality of the spectra collected using this scintillator a deconvolution method was developed. Following the development of the deconvolution method for ATR applications the technique was tested using one-isotope, multi-isotope and fuel simulated sources. Burnup calibrations were perfomed using convoluted and deconvoluted data. The calibrations results showed burnup prediction by this method improves using deconvolution. The final stage of the deconvolution method development was to perform an irradiation experiment in order to create a surrogate fuel source to test the deconvolution method using experimental data. A conceptual design of the fuel scan system is path forward using the rugged LaBr3 detector in an above the water configuration and deconvolution algorithms.

07 ISOTOPE AND RADIATION SOURCES↗

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↗

BISON Capability, Validation and Demonstration for Reactivity-Initiated Accidents

Reactivity Initiated Accidents (RIA) are design basis accidents that could have adverse impacts on the core coolability. In the unlikely event that sufficient reactivity is inserted into the reactor core by the ejected/dropped control rod, prompt energy deposition into the fuel can occur, which when sufficiently high can lead to fuel rod failure or, at large energy deposition levels, expulsion of UO2 fragments or molten UO2 material from the fuel rod. This results in a release of fission product and fuel into the coolant and has the potential to compromise core coolability and threatening the pressure boundary of the primary coolant system. The design basis RIA is one of the industry challenging problems that the CASL aimed to address; the CASL RIA Challenge Problem Charter [1] states, ?The Pressurized Water Reactor (PWR) Rod Ejection Accident (REA) and Boiling Water Reactor (BWR) Control Rod Drop Accident (CRDA) are postulated accidents with consequences that are important to nuclear safety (fuel rod integrity and core coolability). Currently each reload core design must be analyzed to meet regulatory acceptance criteria. The goal of CASLs ModSim capability for RIA is to model the event at a higher fidelity, with validation to existing tests, to better model the transient neutronics and the progression of the fuel and cladding thermal-mechanical behavior. These improved analytical capabilities can be used to better inform reload core design, limits on fuel assembly discharge burnup, restrictions on placement of fuel in the reactor, control rod insertion limits, operating margin, and performance sensitivities.? In support of that charter, BISON, the fuel performance code has been used to demonstrate the simulation of thermal-mechanical behavior of LWR fuels during a reactivity-initiated accident. The combination of mechanical, thermal, and thermal-hydraulic phenomena all present during an RIA makes a multi-physics code such as BISON a valuable tool for modeling these scenarios. This paper will highlight many of the activities associated with BISON relevant to reactivity-initiated accident capability development and validation efforts. These efforts have been performed under both CASL and the Nuclear Energy Advanced Modeling and Simulation (NEAMS) programs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Technetium and Iodine Getters to Improve Cast Stone Performance

To determine the effectiveness of the various getter materials prior to their solidification in Cast Stone, a series of batch sorption experiments was performed at Pacific Northwest National Laboratory. To quantify the effectiveness of the removal of Tc(VII) and I(I) from solution by getters, the distribution coefficient, Kd (mL/g), was calculated. Testing involved placing getter material in contact with spiked waste solutions at a 1:100 solid-to-solution ratio for periods up to 45 days with periodic solution sampling. One Tc getter was also tested at a 1:10 solid-to-solution ratio. Two different solution media, 18.2 MΩ deionized water (DI H2O) and a 7.8 M Na LAW simulant, were used in the batch sorption tests. Each test was conducted at room temperature in an anoxic chamber containing N2 with a small amount of H2 (0.7%) to maintain anoxic conditions. Each getter-solution combination was run in duplicate. Three Tc- and I-doping concentrations were used separately in aliquots of both the 18.2 MΩ DI H2O and a 7.8 M Na LAW waste simulant. The 1× concentration was developed based on Hanford Tank Waste Operations Simulator (HTWOS) model runs to support the River Protection Project System Plan Revision 6. The other two concentrations were 5× and 10× of the HTWOS values. The Tc and I tests were run separately (i.e., the solutions did not contain both solutes). Sampling of the solid-solution mixtures occurred nominally after 0.2, 1, 3, 6, 9, 12, 15 days and ~35 to 45 days. Seven getter materials were tested for Tc and five materials were tested for I. The seven Tc getters were blast furnace slag 1 (BFS1) (northwest source), BFS2 (southeast source), Sn(II)-treated apatite, Sn(II) chloride, nano tin phosphate, KMS (a potassium-metal-sulfide), and tin hydroxapatite. The five iodine getters were layered bismuth hydroxide (LBH), argentite mineral, synthetic argentite, silver-treated carbon, and silver-treated zeolite. The Tc Kd values measured from experiments conducted using the 7.8 M Na LAW simulant (the simulant selected to represent LAW) for the first 15 days for four Tc getters (BFS1, BFS2, Sn(II)-treated apatite, and Sn(II) chloride) show no, to a very small, capacity to remove Tc from the LAW simulant. For the Tc-getter experiments in the 7.8 M LAW simulant, the majority of the effluent samples show very small drops in Tc concentrations for the 35-day compared to the 15-day samplings. However, the Tc concentration in the simulant blanks also dropped slightly during this period, so the effect of the getter contacting LAW simulant at 35 days compared to 15 days is minimal; except that the BFS1 1:10 test shows a slow but steady decrease in Tc concentration in the LAW simulant supernatant from the beginning to the 35 day contact at which point about 20% of the original Tc has been removed from solution. Lastly, the KMS getter gives the highest Kd value for Tc at 35 days where Kd values have increased to 104 mL/g. When considering the different I getters reacting with the 7.8 M LAW simulant, two getters are much more effective than the others: Ag zeolite and Syn Arg. The other getters have calculated iodide distribution coefficients that show very limited effectiveness in the caustic conditions created by the LAW simulant. These are preliminary results that will need more detailed analyses including both pre- and post-batch sorption getter solid-phase characterization using state-of-the-art instrumentation such as synchrotron X ray absorption spectroscopy, which can delineate the oxidation state of the Tc and likely iodine species as well as some of the getters key major components, sulfur and iron in the BFS, and tin and sulfur in the tin-bearing and sulfur-bearing getters. This report also describes future experimental studies to be performed to better elucidate the mechanisms controlling the Tc and I sequestration processes in the various getters and leach tests of getter-bearing Cast Stone monoliths.

Tc getters, I getters, Cast Stone, Waste Forms↗

Effect of compensatory immigration on the genetic structure of coyotes

Despite efforts to reduce their impacts on livestock and native ungulates within the southeastern United States, coyotes (Canis latrans) are able to recover from control programs. It is unknown how coyotes compensate for high mortality following trapping, so there is great interest to identify methods that can provide insight into coyote response to intensive trapping. To investigate if population genetic tools can decipher how coyotes recover from intensive trapping, we combined an empirical test of how genetic differentiation, diversity, and familial structure changed following trapping on the Savannah River Site (SRS), South Carolina with spatially explicit genetic simulations.The empirical dataset found that pre- and post-trapping periods had similar genetic diversities and were not genetically differentiated as expected by either compensatory reproduction or immigration from a single genetic source. The post-trapping coyote populations exhibited weaker signatures of philopatry with little evidence for increased dispersal distances of young coyotes, which suggests immigration caused a decrease in familial structure. Our simulations indicated that spatial autocorrelation coefficients and observed heterozygosities change as immigration increases while population differentiation, allelic richness, and displacement distances do not. Collectively, our results suggest that coyotes recover from intensive trapping via both reproduction and immigration, which likely makes preventing compensation difficult. Furthermore, monitoring post-trapping populations may offer more insight into maximizing the effectiveness of control efforts, and based on our simulations, population genetics can provide critical information about the amount of compensatory immigration following trapping.

59 BASIC BIOLOGICAL SCIENCES↗

CO 2 -brine relative permeability and capillary pressure of Tuscaloosa sandstone: Effect of anisotropy

Relative permeability and capillary pressure are known as essential properties that have substantial impacts on the accuracy of reservoir simulations. The effect of small-scale heterogeneity and lamination in the rock structure is often ignored during the measurement of capillary pressure and relative permeability curves in core samples. This study highlights the remarkable impact of anisotropy on the multiphase flow properties of stratified formations. A series of steady-state CO 2 -brine drainage and imbibition tests are conducted at reservoir conditions in horizontal and vertical core samples of the Tuscaloosa sandstone from the Cranfield CO 2 injection site in Mississippi. The relative permeability curves represent an anisotropic behavior influenced by the heterogeneous and laminated structure of realistic rock samples. The CO 2 saturation profiles during drainage and imbibition cycles indicate that the phase distribution in the pore space is controlled by core-scale heterogeneity in the porosity distribution among the laminations that causes capillary pressure inhomogeneity. Using the saturation profile during the imbibition cycle, the trapping characteristic of the horizontal and vertical rock samples are compared and we found that the capillary trapping is less likely in the vertical direction. Furthermore, the centrifuge-measured capillary pressure demonstrates distinctive characteristics for horizontal and vertical core samples. Since the flooding experiments are performed under capillary controlled flow, the capillary pressure contrast in the laminated structure of the rock strongly affects the relative permeability. The presented results can potentially improve the accuracy of the large-scale simulations for the CO 2 post-injection period, in which the vertical displacement has an important role in the plume migration.

58 GEOSCIENCES↗

WE-AB-201-00: Treatment Planning System Commissioning and QA

Treatment planning systems (TPS) are a cornerstone of modern radiation therapy. Errors in their commissioning or use can have a devastating impact on many patients. To support safe and high quality care, medical physicists must conduct efficient and proper commissioning, good clinical integration, and ongoing quality assurance (QA) of the TPS. AAPM Task Group 53 and related publications have served as seminal benchmarks for TPS commissioning and QA over the past two decades. Over the same time, continuing innovations have made the TPS even more complex and more central to the clinical process. Medical goals are now expressed in terms of the dose and margins around organs and tissues that are delineated from multiple imaging modalities (CT, MR and PET); and even temporally resolved (i.e., 4D) imaging. This information is passed on to optimization algorithms to establish accelerator movements that are programmed directly for IMRT, VMAT and stereotactic treatments. These advances have made commissioning and QA of the TPS much more challenging. This education session reviews up-to-date experience and guidance on this subject; including the recently published AAPM Medical Physics Practice Guideline (MPPG) #5 “Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams”. Treatment Planning System Commissioning and QA: Challenges and Opportunities (Greg Salomons) This session will provide some key background and review publications describing prominent incidents relating to TPS commissioning and QA. Traditional approaches have been hardware and feature oriented. They aim to establish a functional configuration and establish specifications for regular testing of features (like dose calculation) to assure stable operation and detect failures. With the advent of more complex systems, more patient-specific testing has also been adopted. A number of actual TPS defects will be presented along with heuristics for identifying similar defects in the future. Finally, the Gamma test has become a popular metric for reporting TPS Commissioning and QA results. It simplifies complex testing into a numerical index, but noisy data and casual application can make it misleading. A brief review of the issues around the use of the Gamma test will be presented. TPS commissioning and QA: A process orientation and application of control charts (Michael Sharpe) A framework for commissioning a treatment planning system will be presented, focusing on preparations, practical aspects of configuration, priorities, specifications, and establishing performance. The complexity of the modern TPS make modular testing of features inadequate, and modern QA tools can provide “too much information” about the performance of techniques like IMRT and VMAT. We have adopted a process orientation and quality tools, like control charts, for ongoing TPS QA and assessment of patient-specific tests. The trending nature of these tools reveals the overall performance of the TPS system, and quantifies the variations that arise from individual plans, discrete calculations, and experimentation based on discrete measurements. Examples demonstrating application of these tools to TPS QA will be presented. TPS commissioning and QA: Incorporating the entire planning process (Sasa Mutic) The TPS and its features do not perform in isolation. Instead, the features and modules are key components in a complex process that begins with CT Simulation and extends to treatment delivery, along with image guidance and verification. Most importantly, the TPS is used by people working in a multi-disciplinary environment. It is very difficult to predict the outcomes of human interactions with software. Therefore, an interdisciplinary approach to training, commissioning and QA will be presented, along with an approach to the physics chart check and end-to-end testing as a tool for TPS QA. The role of standardization and automation in QA will also be discussed. The recommendations of MPPG #5 and practical implementation strategies (Jennifer Smilowitz) The recently published recommendations from Task Group No. 244, Medical Physics Practice Guideline on Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams will be presented. The recommendations focus on the validation of commissioning data and dose calculations. Tolerance values for non-IMRT beam configurations are summarized based on established criteria and data collected by the IROC. More stringent evaluation criteria for IMRT dose calculations are suggested to test the limitations of the TPS dose algorithms for advanced delivery conditions. The MPPG encourages users to create a suite of validation tests for dose calculation for various conditions for static photon beams, heterogeneities, IMRT/VMAT and electron beams. This test suite is intended to be used for subsequent testing, including TPS software upgrades. In the past, the recommendations of some reports have not been widely implemented due to practical limitations. Implementation strategies, tools and processes developed by multiple centers for efficient and “do-able” MPPG # 5 testing will be presented, as well as a discussion on the overall validation experience. Learning Objectives: Identify some of the key documents relevant for TPS commissioning and QA Understand strategies for testing TPS software Gain a practical knowledge of the Gamma test criteria Increase familiarity with the process of commissioning a TPS Learn about the use of Control Charts for TPS QA Review the role of the TPS in the overall planning process Increase awareness of the link between TPS QA and chart checking Gain an increased appreciation for the importance of interdisciplinary communication Understand the new recommendations from MPPG #5 on TPS Dose Algorithm Commissioning and QC/QA Learn practical implementation processes and tools for MPPG #5 validation recommendations.

60 APPLIED LIFE SCIENCES↗

WE-AB-201-01: Treatment Planning System Commissioning and QA: Challenges and Opportunities

Treatment planning systems (TPS) are a cornerstone of modern radiation therapy. Errors in their commissioning or use can have a devastating impact on many patients. To support safe and high quality care, medical physicists must conduct efficient and proper commissioning, good clinical integration, and ongoing quality assurance (QA) of the TPS. AAPM Task Group 53 and related publications have served as seminal benchmarks for TPS commissioning and QA over the past two decades. Over the same time, continuing innovations have made the TPS even more complex and more central to the clinical process. Medical goals are now expressed in terms of the dose and margins around organs and tissues that are delineated from multiple imaging modalities (CT, MR and PET); and even temporally resolved (i.e., 4D) imaging. This information is passed on to optimization algorithms to establish accelerator movements that are programmed directly for IMRT, VMAT and stereotactic treatments. These advances have made commissioning and QA of the TPS much more challenging. This education session reviews up-to-date experience and guidance on this subject; including the recently published AAPM Medical Physics Practice Guideline (MPPG) #5 “Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams”. Treatment Planning System Commissioning and QA: Challenges and Opportunities (Greg Salomons) This session will provide some key background and review publications describing prominent incidents relating to TPS commissioning and QA. Traditional approaches have been hardware and feature oriented. They aim to establish a functional configuration and establish specifications for regular testing of features (like dose calculation) to assure stable operation and detect failures. With the advent of more complex systems, more patient-specific testing has also been adopted. A number of actual TPS defects will be presented along with heuristics for identifying similar defects in the future. Finally, the Gamma test has become a popular metric for reporting TPS Commissioning and QA results. It simplifies complex testing into a numerical index, but noisy data and casual application can make it misleading. A brief review of the issues around the use of the Gamma test will be presented. TPS commissioning and QA: A process orientation and application of control charts (Michael Sharpe) A framework for commissioning a treatment planning system will be presented, focusing on preparations, practical aspects of configuration, priorities, specifications, and establishing performance. The complexity of the modern TPS make modular testing of features inadequate, and modern QA tools can provide “too much information” about the performance of techniques like IMRT and VMAT. We have adopted a process orientation and quality tools, like control charts, for ongoing TPS QA and assessment of patient-specific tests. The trending nature of these tools reveals the overall performance of the TPS system, and quantifies the variations that arise from individual plans, discrete calculations, and experimentation based on discrete measurements. Examples demonstrating application of these tools to TPS QA will be presented. TPS commissioning and QA: Incorporating the entire planning process (Sasa Mutic) The TPS and its features do not perform in isolation. Instead, the features and modules are key components in a complex process that begins with CT Simulation and extends to treatment delivery, along with image guidance and verification. Most importantly, the TPS is used by people working in a multi-disciplinary environment. It is very difficult to predict the outcomes of human interactions with software. Therefore, an interdisciplinary approach to training, commissioning and QA will be presented, along with an approach to the physics chart check and end-to-end testing as a tool for TPS QA. The role of standardization and automation in QA will also be discussed. The recommendations of MPPG #5 and practical implementation strategies (Jennifer Smilowitz) The recently published recommendations from Task Group No. 244, Medical Physics Practice Guideline on Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams will be presented. The recommendations focus on the validation of commissioning data and dose calculations. Tolerance values for non-IMRT beam configurations are summarized based on established criteria and data collected by the IROC. More stringent evaluation criteria for IMRT dose calculations are suggested to test the limitations of the TPS dose algorithms for advanced delivery conditions. The MPPG encourages users to create a suite of validation tests for dose calculation for various conditions for static photon beams, heterogeneities, IMRT/VMAT and electron beams. This test suite is intended to be used for subsequent testing, including TPS software upgrades. In the past, the recommendations of some reports have not been widely implemented due to practical limitations. Implementation strategies, tools and processes developed by multiple centers for efficient and “do-able” MPPG #5 testing will be presented, as well as a discussion on the overall validation experience. Learning Objectives: Identify some of the key documents relevant for TPS commissioning and QA Understand strategies for testing TPS software Gain a practical knowledge of the Gamma test criteria Increase familiarity with the process of commissioning a TPS Learn about the use of Control Charts for TPS QA Review the role of the TPS in the overall planning process Increase awareness of the link between TPS QA and chart checking Gain an increased appreciation for the importance of interdisciplinary communication Understand the new recommendations from MPPG #5 on TPS Dose Algorithm Commissioning and QC/QA Learn practical implementation processes and tools for MPPG #5 validation recommendations.

60 APPLIED LIFE SCIENCES↗

WE-AB-201-02: TPS Commissioning and QA: A Process Orientation and Application of Control Charts

Treatment planning systems (TPS) are a cornerstone of modern radiation therapy. Errors in their commissioning or use can have a devastating impact on many patients. To support safe and high quality care, medical physicists must conduct efficient and proper commissioning, good clinical integration, and ongoing quality assurance (QA) of the TPS. AAPM Task Group 53 and related publications have served as seminal benchmarks for TPS commissioning and QA over the past two decades. Over the same time, continuing innovations have made the TPS even more complex and more central to the clinical process. Medical goals are now expressed in terms of the dose and margins around organs and tissues that are delineated from multiple imaging modalities (CT, MR and PET); and even temporally resolved (i.e., 4D) imaging. This information is passed on to optimization algorithms to establish accelerator movements that are programmed directly for IMRT, VMAT and stereotactic treatments. These advances have made commissioning and QA of the TPS much more challenging. This education session reviews up-to-date experience and guidance on this subject; including the recently published AAPM Medical Physics Practice Guideline (MPPG) #5 “Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams”. Treatment Planning System Commissioning and QA: Challenges and Opportunities (Greg Salomons) This session will provide some key background and review publications describing prominent incidents relating to TPS commissioning and QA. Traditional approaches have been hardware and feature oriented. They aim to establish a functional configuration and establish specifications for regular testing of features (like dose calculation) to assure stable operation and detect failures. With the advent of more complex systems, more patient-specific testing has also been adopted. A number of actual TPS defects will be presented along with heuristics for identifying similar defects in the future. Finally, the Gamma test has become a popular metric for reporting TPS Commissioning and QA results. It simplifies complex testing into a numerical index, but noisy data and casual application can make it misleading. A brief review of the issues around the use of the Gamma test will be presented. TPS commissioning and QA: A process orientation and application of control charts (Michael Sharpe) A framework for commissioning a treatment planning system will be presented, focusing on preparations, practical aspects of configuration, priorities, specifications, and establishing performance. The complexity of the modern TPS make modular testing of features inadequate, and modern QA tools can provide “too much information” about the performance of techniques like IMRT and VMAT. We have adopted a process orientation and quality tools, like control charts, for ongoing TPS QA and assessment of patient-specific tests. The trending nature of these tools reveals the overall performance of the TPS system, and quantifies the variations that arise from individual plans, discrete calculations, and experimentation based on discrete measurements. Examples demonstrating application of these tools to TPS QA will be presented. TPS commissioning and QA: Incorporating the entire planning process (Sasa Mutic) The TPS and its features do not perform in isolation. Instead, the features and modules are key components in a complex process that begins with CT Simulation and extends to treatment delivery, along with image guidance and verification. Most importantly, the TPS is used by people working in a multi-disciplinary environment. It is very difficult to predict the outcomes of human interactions with software. Therefore, an interdisciplinary approach to training, commissioning and QA will be presented, along with an approach to the physics chart check and end-to-end testing as a tool for TPS QA. The role of standardization and automation in QA will also be discussed. The recommendations of MPPG #5 and practical implementation strategies (Jennifer Smilowitz) The recently published recommendations from Task Group No. 244, Medical Physics Practice Guideline on Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams will be presented. The recommendations focus on the validation of commissioning data and dose calculations. Tolerance values for non-IMRT beam configurations are summarized based on established criteria and data collected by the IROC. More stringent evaluation criteria for IMRT dose calculations are suggested to test the limitations of the TPS dose algorithms for advanced delivery conditions. The MPPG encourages users to create a suite of validation tests for dose calculation for various conditions for static photon beams, heterogeneities, IMRT/VMAT and electron beams. This test suite is intended to be used for subsequent testing, including TPS software upgrades. In the past, the recommendations of some reports have not been widely implemented due to practical limitations. Implementation strategies, tools and processes developed by multiple centers for efficient and “do-able” MPPG #5 testing will be presented, as well as a discussion on the overall validation experience. Learning Objectives: Identify some of the key documents relevant for TPS commissioning and QA Understand strategies for testing TPS software Gain a practical knowledge of the Gamma test criteria Increase familiarity with the process of commissioning a TPS Learn about the use of Control Charts for TPS QA Review the role of the TPS in the overall planning process Increase awareness of the link between TPS QA and chart checking Gain an increased appreciation for the importance of interdisciplinary communication Understand the new recommendations from MPPG #5 on TPS Dose Algorithm Commissioning and QC/QA Learn practical implementation processes and tools for MPPG #5 validation recommendations.

60 APPLIED LIFE SCIENCES↗

WE-AB-201-03: TPS Commissioning and QA: Incorporating the Entire Planning Process

Treatment planning systems (TPS) are a cornerstone of modern radiation therapy. Errors in their commissioning or use can have a devastating impact on many patients. To support safe and high quality care, medical physicists must conduct efficient and proper commissioning, good clinical integration, and ongoing quality assurance (QA) of the TPS. AAPM Task Group 53 and related publications have served as seminal benchmarks for TPS commissioning and QA over the past two decades. Over the same time, continuing innovations have made the TPS even more complex and more central to the clinical process. Medical goals are now expressed in terms of the dose and margins around organs and tissues that are delineated from multiple imaging modalities (CT, MR and PET); and even temporally resolved (i.e., 4D) imaging. This information is passed on to optimization algorithms to establish accelerator movements that are programmed directly for IMRT, VMAT and stereotactic treatments. These advances have made commissioning and QA of the TPS much more challenging. This education session reviews up-to-date experience and guidance on this subject; including the recently published AAPM Medical Physics Practice Guideline (MPPG) #5 “Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams”. Treatment Planning System Commissioning and QA: Challenges and Opportunities (Greg Salomons) This session will provide some key background and review publications describing prominent incidents relating to TPS commissioning and QA. Traditional approaches have been hardware and feature oriented. They aim to establish a functional configuration and establish specifications for regular testing of features (like dose calculation) to assure stable operation and detect failures. With the advent of more complex systems, more patient-specific testing has also been adopted. A number of actual TPS defects will be presented along with heuristics for identifying similar defects in the future. Finally, the Gamma test has become a popular metric for reporting TPS Commissioning and QA results. It simplifies complex testing into a numerical index, but noisy data and casual application can make it misleading. A brief review of the issues around the use of the Gamma test will be presented. TPS commissioning and QA: A process orientation and application of control charts (Michael Sharpe) A framework for commissioning a treatment planning system will be presented, focusing on preparations, practical aspects of configuration, priorities, specifications, and establishing performance. The complexity of the modern TPS make modular testing of features inadequate, and modern QA tools can provide “too much information” about the performance of techniques like IMRT and VMAT. We have adopted a process orientation and quality tools, like control charts, for ongoing TPS QA and assessment of patient-specific tests. The trending nature of these tools reveals the overall performance of the TPS system, and quantifies the variations that arise from individual plans, discrete calculations, and experimentation based on discrete measurements. Examples demonstrating application of these tools to TPS QA will be presented. TPS commissioning and QA: Incorporating the entire planning process (Sasa Mutic) The TPS and its features do not perform in isolation. Instead, the features and modules are key components in a complex process that begins with CT Simulation and extends to treatment delivery, along with image guidance and verification. Most importantly, the TPS is used by people working in a multi-disciplinary environment. It is very difficult to predict the outcomes of human interactions with software. Therefore, an interdisciplinary approach to training, commissioning and QA will be presented, along with an approach to the physics chart check and end-to-end testing as a tool for TPS QA. The role of standardization and automation in QA will also be discussed. The recommendations of MPPG #5 and practical implementation strategies (Jennifer Smilowitz) The recently published recommendations from Task Group No. 244, Medical Physics Practice Guideline on Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams will be presented. The recommendations focus on the validation of commissioning data and dose calculations. Tolerance values for non-IMRT beam configurations are summarized based on established criteria and data collected by the IROC. More stringent evaluation criteria for IMRT dose calculations are suggested to test the limitations of the TPS dose algorithms for advanced delivery conditions. The MPPG encourages users to create a suite of validation tests for dose calculation for various conditions for static photon beams, heterogeneities, IMRT/VMAT and electron beams. This test suite is intended to be used for subsequent testing, including TPS software upgrades. In the past, the recommendations of some reports have not been widely implemented due to practical limitations. Implementation strategies, tools and processes developed by multiple centers for efficient and “do-able” MPPG #5 testing will be presented, as well as a discussion on the overall validation experience. Learning Objectives: Identify some of the key documents relevant for TPS commissioning and QA Understand strategies for testing TPS software Gain a practical knowledge of the Gamma test criteria Increase familiarity with the process of commissioning a TPS Learn about the use of Control Charts for TPS QA Review the role of the TPS in the overall planning process Increase awareness of the link between TPS QA and chart checking Gain an increased appreciation for the importance of interdisciplinary communication Understand the new recommendations from MPPG #5 on TPS Dose Algorithm Commissioning and QC/QA Learn practical implementation processes and tools for MPPG #5 validation recommendations.

60 APPLIED LIFE SCIENCES↗

WE-AB-201-04: The Recommendations of MPPG #5 and Practical Implementation Strategies

Treatment planning systems (TPS) are a cornerstone of modern radiation therapy. Errors in their commissioning or use can have a devastating impact on many patients. To support safe and high quality care, medical physicists must conduct efficient and proper commissioning, good clinical integration, and ongoing quality assurance (QA) of the TPS. AAPM Task Group 53 and related publications have served as seminal benchmarks for TPS commissioning and QA over the past two decades. Over the same time, continuing innovations have made the TPS even more complex and more central to the clinical process. Medical goals are now expressed in terms of the dose and margins around organs and tissues that are delineated from multiple imaging modalities (CT, MR and PET); and even temporally resolved (i.e., 4D) imaging. This information is passed on to optimization algorithms to establish accelerator movements that are programmed directly for IMRT, VMAT and stereotactic treatments. These advances have made commissioning and QA of the TPS much more challenging. This education session reviews up-to-date experience and guidance on this subject; including the recently published AAPM Medical Physics Practice Guideline (MPPG) #5 “Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams”. Treatment Planning System Commissioning and QA: Challenges and Opportunities (Greg Salomons) This session will provide some key background and review publications describing prominent incidents relating to TPS commissioning and QA. Traditional approaches have been hardware and feature oriented. They aim to establish a functional configuration and establish specifications for regular testing of features (like dose calculation) to assure stable operation and detect failures. With the advent of more complex systems, more patient-specific testing has also been adopted. A number of actual TPS defects will be presented along with heuristics for identifying similar defects in the future. Finally, the Gamma test has become a popular metric for reporting TPS Commissioning and QA results. It simplifies complex testing into a numerical index, but noisy data and casual application can make it misleading. A brief review of the issues around the use of the Gamma test will be presented. TPS commissioning and QA: A process orientation and application of control charts (Michael Sharpe) A framework for commissioning a treatment planning system will be presented, focusing on preparations, practical aspects of configuration, priorities, specifications, and establishing performance. The complexity of the modern TPS make modular testing of features inadequate, and modern QA tools can provide “too much information” about the performance of techniques like IMRT and VMAT. We have adopted a process orientation and quality tools, like control charts, for ongoing TPS QA and assessment of patient-specific tests. The trending nature of these tools reveals the overall performance of the TPS system, and quantifies the variations that arise from individual plans, discrete calculations, and experimentation based on discrete measurements. Examples demonstrating application of these tools to TPS QA will be presented. TPS commissioning and QA: Incorporating the entire planning process (Sasa Mutic) The TPS and its features do not perform in isolation. Instead, the features and modules are key components in a complex process that begins with CT Simulation and extends to treatment delivery, along with image guidance and verification. Most importantly, the TPS is used by people working in a multi-disciplinary environment. It is very difficult to predict the outcomes of human interactions with software. Therefore, an interdisciplinary approach to training, commissioning and QA will be presented, along with an approach to the physics chart check and end-to-end testing as a tool for TPS QA. The role of standardization and automation in QA will also be discussed. The recommendations of MPPG #5 and practical implementation strategies (Jennifer Smilowitz) The recently published recommendations from Task Group No. 244, Medical Physics Practice Guideline on Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams will be presented. The recommendations focus on the validation of commissioning data and dose calculations. Tolerance values for non-IMRT beam configurations are summarized based on established criteria and data collected by the IROC. More stringent evaluation criteria for IMRT dose calculations are suggested to test the limitations of the TPS dose algorithms for advanced delivery conditions. The MPPG encourages users to create a suite of validation tests for dose calculation for various conditions for static photon beams, heterogeneities, IMRT/VMAT and electron beams. This test suite is intended to be used for subsequent testing, including TPS software upgrades. In the past, the recommendations of some reports have not been widely implemented due to practical limitations. Implementation strategies, tools and processes developed by multiple centers for efficient and “do-able” MPPG #5 testing will be presented, as well as a discussion on the overall validation experience. Learning Objectives: Identify some of the key documents relevant for TPS commissioning and QA Understand strategies for testing TPS software Gain a practical knowledge of the Gamma test criteria Increase familiarity with the process of commissioning a TPS Learn about the use of Control Charts for TPS QA Review the role of the TPS in the overall planning process Increase awareness of the link between TPS QA and chart checking Gain an increased appreciation for the importance of interdisciplinary communication Understand the new recommendations from MPPG #5 on TPS Dose Algorithm Commissioning and QC/QA Learn practical implementation processes and tools for MPPG #5 validation recommendations.

60 APPLIED LIFE SCIENCES↗

Technetium and Iodine Getters to Improve Cast Stone Performance

To determine the effectiveness of the various getter materials prior to their solidification in Cast Stone, a series of batch sorption experiments was performed at Pacific Northwest National Laboratory. To quantify the effectiveness of the removal of Tc(VII) and I(I) from solution by getters, the distribution coefficient, K d (mL/g), was calculated. Testing involved placing getter material in contact with spiked waste solutions at a 1:100 solid-to-solution ratio for periods up to 45 days with periodic solution sampling. One Tc getter was also tested at a 1:10 solid-to-solution ratio. Two different solution media, 18.2 MΩ deionized water (DI H 2 O) and a 7.8 M Na LAW simulant, were used in the batch sorption tests. Each test was conducted at room temperature in an anoxic chamber containing N2 with a small amount of H 2 (0.7%) to maintain anoxic conditions. Each getter-solution combination was run in duplicate. Three Tc- and I-doping concentrations were used separately in aliquots of both the 18.2 MΩ DI H2O and a 7.8 M Na LAW waste simulant. The 1× concentration was developed based on Hanford Tank Waste Operations Simulator (HTWOS) model runs to support the River Protection Project System Plan Revision 6. The other two concentrations were 5× and 10× of the HTWOS values. The Tc and I tests were run separately (i.e., the solutions did not contain both solutes). Sampling of the solid-solution mixtures occurred nominally after 0.2, 1, 3, 6, 9, 12, 15 days and ~35 to 45 days. Seven getter materials were tested for Tc and five materials were tested for I. The seven Tc getters were blast furnace slag 1 (BFS1) (northwest source), BFS2 (southeast source), Sn(II)-treated apatite, Sn(II) chloride, nano tin phosphate, KMS (a potassium-metal-sulfide), and tin hydroxapatite. The five iodine getters were layered bismuth hydroxide (LBH), argentite mineral, synthetic argentite, silver-treated carbon, and silver-treated zeolite. The Tc Kd values measured from experiments conducted using the 7.8 M Na LAW simulant (the simulant selected to represent LAW) for the first 15 days for four Tc getters (BFS1, BFS2, Sn(II)-treated apatite, and Sn(II) chloride) show no, to a very small, capacity to remove Tc from the LAW simulant. For the Tc-getter experiments in the 7.8 M LAW simulant, the majority of the effluent samples show very small drops in Tc concentrations for the 35-day compared to the 15-day samplings. However, the Tc concentration in the simulant blanks also dropped slightly during this period, so the effect of the getter contacting LAW simulant at 35 days compared to 15 days is minimal; except that the BFS1 1:10 test shows a slow but steady decrease in Tc concentration in the LAW simulant supernatant from the beginning to the 35 day contact at which point about 20% of the original Tc has been removed from solution. Lastly, the KMS getter gives the highest K d value for Tc at 35 days where K d values have increased to 104 mL/g. When considering the different I getters reacting with the 7.8 M LAW simulant, two getters are much more effective than the others: Ag zeolite and Syn Arg. The other getters have calculated iodide distribution coefficients that show very limited effectiveness in the caustic conditions created by the LAW simulant. These are preliminary results that will need more detailed analyses including both pre- and post-batch sorption getter solid-phase characterization using state-of-the-art instrumentation such as synchrotron X-ray absorption spectroscopy, which can delineate the oxidation state of the Tc and likely iodine species as well as some of the getters key major components, sulfur and iron in the BFS, and tin and sulfur in the tin-bearing and sulfur-bearing getters. This report also describes future experimental studies to be performed to better elucidate the mechanisms controlling the Tc and I sequestration processes in the various getters and leach tests of getter-bearing Cast Stone monoliths.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Numerical Simulation of Measurements during the Reactor Physical Startup at Unit 3 of Rostov NPP

The results of numerical calculations and measurements of some reactor parameters during the physical startup tests at unit 3 of Rostov NPP are presented. The following parameters are considered: the critical boron acid concentration and the currents from ionization chambers (IC) during the scram system efficiency evaluation. The scram system efficiency was determined using the inverse point kinetics equation with the measured and simulated IC currents. The results of steady-state calculations of relative power distribution and efficiency of the scram system and separate groups of control rods of the control and protection system are also presented. The calculations are performed using several codes, including precision ones.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Advanced Simulation and Computing Fiscal Year 2016 Implementation Plan, Version 0

The Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, surety, and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational capabilities to support these programs. The purpose of this IP is to outline key work requirements to be performed and to control individual work activities within the scope of work. Contractors may not deviate from this plan without a revised WA or subsequent IP.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗