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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Status and future plans for C 3 R&D

C 3 is an opportunity to realize an e + e - collider for the study of the Higgs boson at √s = 250 GeV, with a well defined upgrade path to 550 GeV while staying on the same short facility footprint. C 3 is based on a fundamentally new approach to normal conducting linear accelerators that achieves both high gradient and high efficiency at relatively low cost. Given the advanced state of linear collider designs, the key system that requires technical maturation for C 3 is the main linac. This paper presents the staged approach towards a facility to demonstrate C 3 technology with both Direct (source and main linac) and Parallel (beam delivery, damping ring, ancillary component) R&D. The primary goal of the C 3 Demonstration R&D Plan is to reduce technical and cost risk by building and operating the key components of C 3 at an adequate scale. This R&D plan starts with the engineering design, and demonstration of one cryomodule and will culminate in the construction of a 3 cryomodule linac with pre-production prototypes. This R&D program would also demonstrate the linac rf fundamentals including achievable gradient and gradient stability over a full electron bunch train and breakdown rates. It will also investigate beam dynamics including energy spread, wakefields, and emittance growth. This work will be critical to confirm the suitability of the C 3 beam parameters for the physics reach and detector performance in preparation for a Conceptual Design Report (CDR), as well as for follow-on technology development and industrialization. The C 3 Demonstration R&D Plan will open up significant new scientific and technical opportunities based on development of high-gradient and high-efficiency accelerator technology. It will push this technology to operate both at the GeV scale and mature the technology to be reliable and provide high-brightness electron beams. The timeline for progressing with C 3 technology development will be governed by practical limitations on both the technical progress and resource availability. It consists of four stages: Stage 0) Ongoing fundamental R&D on structure prototypes, damping and vibrations. Stage 1) Advancing the engineering maturity of the design and developing start-to-end simulations including space-charge and wakefield effects. This stage will include testing of strucutres operating at cryogenic temperatures. Beam tests would be performed with high beam current to test full beam loading. Stage 2) Production and testing of the first cryomodule at cryogenic temperatures. This would provide sufficient experimental data to compile a CDR and it is anticipated for Stage 2 to last 3 years and to culminate with the transport of photo-electrons through the first cryomodule. Stage 3) Updates to the engineering design of the cryomodules, production of the second and third cryomodule and their installation. Lower charge and lower emittance beams will be used to investigate emittance growth. The successful full demonstration of the 3 cryomodules to deliver up to a 3 GeV beam and achieve the C 3 five gradient will allow a comprehensive and robust evaluation of the technical design of C 3 as well as mitigate technical, schedule, and cost risks required to proceed with a Technical Design Report (TDR).

radiation hardened magnets↗
DOE OSTI2019

Optimum Planning for Inductively Charged On-Demand Automated Electric Shuttles at Greenville, South Carolina

Wireless charging technology presents perfect fits for autonomous electric vehicles for realizing a fully automated system (vehicle and charger). This paper presents a planning optimization analysis for a pilot project of in-route wireless charging infrastructure serving fixed-route on-demand shared automated electric shuttles (SAESs) at Greenville, South Carolina, USA. A single-objective non-linear integer planning optimization problem is formulated. A comprehensive cost function representing the inductively charged SAESs is developed, considering road construction, power electronics and materials, traction battery, and installation costs. The optimization problem is solved to determine the best combination of the system key design parameters (number and allocations of wireless chargers, charging power level, track length and on-board battery capacity) that show the most cost-effective solution and allow the SAESs realizing charge sustaining operation. The planning platform incorporates representative simulated traffic data (drive cycles and routes) for four SAESs at Greenville project using the Simulation of Urban Mobility (SUMO) tool. These data are fed to a vehicle powertrain model and a wireless charger power model to predict the battery power, energy and state-of-charge (SOC) profiles, which are provided to the search algorithm to assess the design objectives under specific constraints. The results indicated that implementing wireless charging at a few designated stops for fixed-route SAESs with proper design allows the vehicles realizing charge sustaining operation, infinite range and zero recharge downtime, with a significant reduction in the on-board battery (36 % ) and road coverage (69%), at minimum cost.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Simulation Planning Using Component Based Cost Model

Successful simulations for scientific discovery on high-performance computing platforms require careful planning, including verification of specific application configuration and runtime parameters, estimation of resource requirements, and steering and monitoring of the simulation. However, simulation planning is an aspect of scientific computing that is extremely sparse in available literature or training. In this paper we focus on the resource management aspect of such planning through formulation of a component-based cost model. We illustrate the methodology and formulation through FLASH, a highly configurable simulation code used in multiple scientific domains.

Dubey, Anshu↗
DOE OSTI2019

Community Microgrid Planning Considering Building Thermal Dynamics

In this paper, the building thermal dynamic characteristics are introduced in the community microgrid (MG) planning model. The proposed planning model is formulated as a mixed integer linear programming (MILP) which seeks to determine the optimal deployment strategy for various distributed energy resources (DER). The objective is to minimize the annualized cost of community MG, including investment cost in DER, operation cost for dispatchable fuel-generators (DFG), energy storage system (ESS) degradation cost, energy purchasing and peak demand charge at PCC, customer discomfort cost due to the room temperature deviation and load curtailment cost. Given the slow thermal dynamic characteristics of buildings, the heating, ventilation and air-conditioning (HVAC) system in the proposed model is treated as a demand side management (DSM) component, whose dispatch commands are provided by the central MG controller. Numerical results based on a community MG comprising of 20 residential buildings demonstrate the effectiveness of the proposed planning model and the benefits of introducing the building thermal dynamic model.

Zhang, Xiaohu↗
DOE OSTI2022

Advanced Metering Infrastructure for Distribution Planning and Operation: Closing the Loop on Grid-Edge Visibility

In the recent history of electric utilities, the potential to have visibility of the grid edge is gaining significance for the reliable planning and operation of a clean energy smart grid. Before the recent large-scale customer adoption of distributed energy resources (DERs), distribution networks were planned with a simpler fit-and-forget philosophy. The importance of customer-sited DERs to achieve climate change goals marks a major shift for utility operations. Changes to traditional fit-and-forget planning paradigms require better availability of grid-edge data. Smart metering is an enterprise-wide tool that is enabling visibility when and where it has been most needed. As of 2020, the rollout of smart metering, or advanced metering infrastructure (AMI), had reached more than 100 million meters in the United States, and nearly half of all electricity customers are now equipped with a smart meter (Figure 1). Smart meters are quickly becoming a ubiquitous data capture feature of smart grids. AMI enables utilities to record and measure electricity usage and power-flow metrics at a minimum of hourly intervals and at least once a day. At a minimum, AMI enables interval metering, automatic meter reading enabling accurate and time-interval billing, and the ability to provide feedback on customer energy consumption.

advanced metering infrastructure↗
DOE OSTI2022

Distribution System Planning for Growth in Residential Electric Vehicle Adoption

Anticipated growth in Electric Vehicles (EV) adoption could stress distribution system circuits beyond their original design limits. Uncertainties related to when households will begin buying EVs in large numbers challenges existing distribution system planning approaches and complicates efforts to assess grid impacts. Anticipated location, timing, and demand for EV charging is critical information for distribution system planners as it guides investment strategies for infrastructure upgrades to ensure continued reliability. This research makes two significant contributions: an EV adoption model that uses socioeconomic data to forecast location and year-specific adoption patterns through a bottoms-up approach, and an EV hosting capacity assessment methodology that offers improvements to current utility planning and asset management practices for infrastructure investments. Both contributions are applied to a Southern California Edison feeder in 7 adoption years from 2025 to 2050, with the results indicating that they are likely valuable additions to distribution systems planning capabilities.

Sridhar, Siddharth↗
DOE OSTI2019

Planning Optimization for Inductively Charged On-demand Automated Electric Shuttles Project at Greenville, South Carolina

Wireless charging technology presents an ideal fit for autonomous electric vehicles for realizing a fully automated system (vehicle and charger). This paper presents a planning optimization analysis for a pilot project of in-route wireless charging infrastructure serving fixed-route on-demand shared automated electric shuttles (SAESs) at Greenville, South Carolina, USA. A single-objective non-linear mixed integer system planning optimization problem is formulated. A comprehensive cost model representing the overall inductively charged SAESs system is developed, considering road construction, power electronics and materials, traction battery, and installation costs. The optimization problem is solved to determine the best combination of the system key design parameters (number and allocations of wireless chargers, charging power level, track length and on-board battery capacity) that show the most cost-effective solution and allow the SAESs to achieve charge-sustaining operation. The planning platform incorporates representative simulated traffic data (driving speed and routes) for four SAESs in the Greenville using the Simulation of Urban Mobility tool. These data are fed to a vehicle powertrain model and a wireless charger power model to predict the battery power, energy and state-of-charge profiles, which are provided to the search algorithm to assess the design objectives under specific constraints. Finally, the results indicate that implementing high-power (100 kW) wireless charger at a few designated stops for fixed-route SAESs with the proper track length allows the vehicles to realize charge-sustaining operation, infinite range, and zero recharge downtime, with a significant reduction in the on-board battery (36%) and road coverage (69%), at minimum cost.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Data-Driven Stochastic Transmission Expansion Planning

Due to the significant improvements of power generation technologies and the trend of replacing traditional power plants with renewable generation resources, the generation portfolio will experience dramatic changes in the near future. The uncertainty and variability of renewable energy and their sitting call for strategic and economic plans for expanding the transmission capacities. In this study, we develop a data-driven two-stage stochastic transmission expansion planning with uncertainties. In the proposed approach, purely by learning from the historical data, we first construct a confidence set for the unknown distribution of the uncertain parameters. Then, we develop a two-stage data-driven transmission expansion framework, by considering the worst-case distribution within the constructed confidence set, so as to provide a reliable while economic transmission planning decision. Furthermore, to tackle the model complexity, we propose a decomposition framework embedded with Benders' and Column-and-Constraint generation methods. We implement our approach on 6-bus and 118-bus systems to test its effectiveness. Finally, we show as the amount of historical data grows, the conservativeness of the model decreases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Approximate Latent Factor Algorithm for Scenario Selection and Weighting in Transmission Expansion Planning

One major difficulty in transmission expansion planning is selecting the representative scenarios to use to evaluate candidate transmission networks. The variability in demand and renewable generation makes the inclusion of several scenarios critical when calculating reliability and cost, but including too many scenarios in an optimization is computationally intractable. To reduce the number of representative operating conditions needed to obtain an accurate approximation of the system, we propose a method rooted in multivariate statistics that exploits the latent correlative structure between different scenarios and network configurations. The proposed algorithm includes an objective and rigorous way to select a subset of scenarios that provide as much information about the system as possible, and a method to accurately approximate the system cost from that scenario subset. The result is a set of scenarios and weights that are easily incorporated into traditional transmission expansion planning formulations. We apply this to a 312-bus WECC model with 8,736 distinct operating conditions. The transmission plans found with the proposed method are more reliable and have a lower total cost than those from other scenario reduction techniques, as well as a smaller error between the expected system performance from the optimization objective and the actual system performance.

42 ENGINEERING↗
DOE OSTI2023

Quantitative approaches for including equity in risk and resilience infrastructure planning analyses

Risk and resilience assessments for critical infrastructure focus on myriad objectives, from natural hazard evaluations to optimizing investments. Although research has started to characterize externalities associated with current or possible future states, incorporation of equity priorities at project inception is increasingly being recognized as critical for planning related activities. However, there is no standard methodology that guides development of equity-informed quantitative approaches for infrastructure planning activities. Here, to address this gap, we introduce a logic model that can be tailored to capture nuances about specific geographies and community priorities, effectively incorporating them into different mathematical approaches for quantitative risk assessments. Specifically, the logic model uses a graded, iterative approach to clarify specific equity objectives as well as inform the development of equations being used to support analysis. We demonstrate the utility of this framework using case studies spanning aviation fuel, produced water, and microgrid electricity infrastructures. For each case study, the use of the logic model helps clarify the ways that local priorities and infrastructure needs are used to drive the types of data and quantitative methodologies used in the respective analyses. The explicit consideration of methodological limitations (e.g., data mismatches) and stakeholder engagements serves to increase the transparency of the associated findings as well as effectively integrate community nuances (e.g., ownership of assets) into infrastructure assessments. Such integration will become increasingly important to ensure that planning activities (which occur throughout the lifecycle of the infrastructure projects) lead to long-lasting solutions to meet both energy and sustainable development goals for communities.

community-based↗
DOE OSTI2014

SU-E-J-55: Dosimetric Evaluation of Centrally Located Lung Tumors: A Monte Carlo (MC) Study of Lung SBRT Planning

Purpose: To compare dose distributions calculated using the iPlan XVMC algorithm and heterogeneities corrected/uncorrected Pencil Beam (PB-hete/PB-homo) algorithms for SBRT treatments of lung tumors. Methods: Ten patients with centrally located solitary lung tumors were treated using MC-based SBRT to 60Gy in 5 fractions for PTVV100%=95%. ITV was delineated on MIP-images based on 4D-CT scans. PTVs(ITV+5mm margins) ranged from 10.1–106.5cc(mean=48.6cc). MC-SBRT plans were generated with a combination of non-coplanar conformal arcs/beams using iPlan-XVMC-algorithm (BrainLABiPlan ver.4.1.2) for Novalis-TX consisting of HD-MLCs and 6MV-SRS(1000MU/min) mode, following RTOG 0813 dosimetric criteria. For comparison, PB-hete/PB-homo algorithms were used to re-calculate dose distributions using same beam configurations, MLCs/monitor units. Plans were evaluated with isocenter/maximal/mean doses to PTV. Normal lung doses were evaluated with V5/V10/V20 and mean-lung-dose(MLD), excluding PTV. Other OAR doses such as maximal spinal cord/2cc-esophagus/max bronchial tree (BT/maximal heart doses were tabulated. Results: Maximal/mean/isocenter doses to PTV calculated by PB-hete were uniformly larger than MC plans by a factors of 1.09/1.13/1.07, on average, whereas they were consistently lower by PB-homo by a factors of 0.9/0.84/0.9, respectively. The volume covered by 5Gy/10Gy/20Gy isodose-lines of the lung were comparable (average within±3%) when calculated by PB-hete compared to XVMC, but, consistently lower by PB-homo by a factors of 0.90/0.88/0.85, respectively. MLD was higher with PB-hete by 1.05, but, lower by PB-homo by 0.9, on average, compared to XVMC. XVMC max-cord/max-BT/max-heart and 2cc of esophagus doses were comparable to PB-hete; however, PB-homo underestimates by a factors of 0.82/0.89/0.88/0.86, on average, respectively. Conclusion: PB-hete significantly overestimates dose to PTV relative to XVMC -hence underdosing the target. MC is more complex and accurate with tissue-heterogeneities.The magnitude of variation significantly varies with ‘small-island-tumor’ surrounded by low-density lung tissues -PB algorithms lacks later electron scattering. Dose calculation with XVMC for lung SBRT is routinely performed in our clinic, its performance for head'neck/sinus cases will also be investigated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-03: 3D GPU-Accelerated Secondary Checks of Radiation Therapy Treatment Plans

Purpose: Redundant treatment verifications in conformal and intensity-modulated radiation therapy techniques are traditionally performed with single point calculations. New solutions can replace these checks with 3D treatment plan verifications. This work describes a software tool (Mobius3D, Mobius Medical Systems) that uses a GPU-accelerated collapsed cone algorithm to perform 3D independent verifications of TPS calculations. Methods: Mobius3D comes with reference beam models for common linear accelerators. The system uses an independently developed collapsed cone algorithm updated with recent enhancements. 144 isotropically-spaced cones are used for each voxel for calculations. These complex calculations can be sped up by using GPUs. Mobius3D calculate dose using DICOM information coming from TPS (CT, RT Struct, RT Plan RT Dose). DVH-metrics and 3D gamma tests can be used to compare both TPS and secondary calculations. 170 patients treated with all common techniques as 3DCFRT (including wedged), static and dynamic IMRT and VMAT have been successfully verified with this solution. Results: Calculation times are between 3–5 minutes for 3DCFRT treatments and 15–20 for most complex dMLC and VMAT plans. For all PTVs mean dose and 90% coverage differences are (1.12±0.97)% and (0.68±1.19)%, respectively. Mean dose discrepancies for all OARs is (0.64±1.00)%. 3D gamma (global, 3%/3 mm) analysis shows a mean passing rate of (97.8 ± 3.0)% for PTVs and (99.0±3.0)% for OARs. 3D gamma pasing rate for all voxels in CT has a mean value of (98.5±1.6)%. Conclusion: Mobius3D is a powerful tool to verify all modalities of radiation therapy treatments. Dose discrepancies calculated by this system are in good agreement with TPS. The use of reference beam data results in time savings and can be used to avoid the propagation of errors in original beam data into our QA system. GPU calculations permit enhanced collapsed cone calculations with reasonable calculation times.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-188: Film Dosimetry Verification of Monte Carlo Generated Electron Treatment Plans

Purpose: The purpose of this study was to compare dose distributions from film measurements to Monte Carlo generated electron treatment plans. Irradiation with electrons offers the advantages of dose uniformity in the target volume and of minimizing the dose to deeper healthy tissue. Using the Monte Carlo algorithm will improve dose accuracy in regions with heterogeneities and irregular surfaces. Methods: Dose distributions from GafChromic{sup ™} EBT3 films were compared to dose distributions from the Electron Monte Carlo algorithm in the Eclipse{sup ™} radiotherapy treatment planning system. These measurements were obtained for 6MeV, 9MeV and 12MeV electrons at two depths. All phantoms studied were imported into Eclipse by CT scan. A 1 cm thick solid water template with holes for bonelike and lung-like plugs was used. Different configurations were used with the different plugs inserted into the holes. Configurations with solid-water plugs stacked on top of one another were also used to create an irregular surface. Results: The dose distributions measured from the film agreed with those from the Electron Monte Carlo treatment plan. Accuracy of Electron Monte Carlo algorithm was also compared to that of Pencil Beam. Dose distributions from Monte Carlo had much higher pass rates than distributions from Pencil Beam when compared to the film. The pass rate for Monte Carlo was in the 80%–99% range, where the pass rate for Pencil Beam was as low as 10.76%. Conclusion: The dose distribution from Monte Carlo agreed with the measured dose from the film. When compared to the Pencil Beam algorithm, pass rates for Monte Carlo were much higher. Monte Carlo should be used over Pencil Beam for regions with heterogeneities and irregular surfaces.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-250: New IMRT Sequencing Strategy: Towards Intra-Fraction Plan Adaptation for the MR-Linac

Purpose: To develop a new sequencer for IMRT planning that during treatment makes the inclusion of external factors possible and by doing so accounts for intra-fraction anatomy changes. Given a real-time imaging modality that will provide the updated patient anatomy during delivery, this sequencer is able to take these changes into account during the calculation of subsequent segments. Methods: Pencil beams are generated for each beam angle of the treatment and a fluence optimization is performed. The pencil beams, together with the patient anatomy and the above optimal fluence form the input of our algorithm. During each iteration the following steps are performed: A fluence optimization is done and each beam's fluence is then split to discrete intensity levels. Deliverable segments are calculated for each one of these. Each segment's area multiplied by its intensity describes its efficiency. The most efficient segment among all beams is then chosen to deliver a part of the calculated fluence and the dose that will be delivered by this segment is calculated. This delivered dose is then subtracted from the remaining dose. This loop is repeated until 90% of the dose has been delivered and a final segment weight optimization is performed to reach full convergence. Results: This algorithm was tested in several prostate cases yielding results that meet all clinical constraints. Quality assurance was performed on Delta4 and film phantoms for one of these prostate cases and received clinical acceptance after passing both gamma analyses with the 3%/3mm criteria. Conclusion: A new sequencing algorithm was developed to facilitate the needs of intensity modulated treatment. The first results on static anatomy confirm that it can calculate clinical plans equivalent to those of the commercially available planning systems. We are now working towards 100% dose convergence which will allow us to handle anatomy deformations. This work is financially supported by Elekta AB, Stockholm, Sweden.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-261: Plan Quality Assurance of VMAT Using Fluence Images Reconstituted From Log-Files

Purpose: A successful VMAT plan delivery includes precise modulations of dose rate, gantry rotational and multi-leaf collimator (MLC) shapes. One of the main problem in the plan quality assurance is dosimetric errors associated with leaf-positional errors are difficult to analyze because they vary with MU delivered and leaf number. In this study, we calculated integrated fluence error image (IFEI) from log-files and evaluated plan quality in the area of all and individual MLC leaves scanned. Methods: The log-file reported the expected and actual position for inner 20 MLC leaves and the dose fraction every 0.25 seconds during prostate VMAT on Elekta Synergy. These data were imported to in-house software that developed to calculate expected and actual fluence images from the difference of opposing leaf trajectories and dose fraction at each time. The IFEI was obtained by adding all of the absolute value of the difference between expected and actual fluence images corresponding. Results: In the area all MLC leaves scanned in the IFEI, the average and root mean square (rms) were 2.5 and 3.6 MU, the area of errors below 10, 5 and 3 MU were 98.5, 86.7 and 68.1 %, the 95 % of area was covered with less than error of 7.1 MU. In the area individual MLC leaves scanned in the IFEI, the average and rms value were 2.1 – 3.0 and 3.1 – 4.0 MU, the area of errors below 10, 5 and 3 MU were 97.6 – 99.5, 81.7 – 89.5 and 51.2 – 72.8 %, the 95 % of area was covered with less than error of 6.6 – 8.2 MU. Conclusion: The analysis of the IFEI reconstituted from log-file was provided detailed information about the delivery in the area of all and individual MLC leaves scanned.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-578: MCEBRT, A Monte Carlo Code for External Beam Treatment Plan Verifications

Purpose: Present a new Monte Carlo code (MCEBRT) for patient-specific dose calculations in external beam radiotherapy. The code MLC model is benchmarked and real patient plans are re-calculated using MCEBRT and compared with commercial TPS. Methods: MCEBRT is based on the GEPTS system (Med. Phys. 29 (2002) 835–846). Phase space data generated for Varian linac photon beams (6 – 15 MV) are used as source term. MCEBRT uses a realistic MLC model (tongue and groove, rounded ends). Patient CT and DICOM RT files are used to generate a 3D patient phantom and simulate the treatment configuration (gantry, collimator and couch angles; jaw positions; MLC sequences; MUs). MCEBRT dose distributions and DVHs are compared with those from TPS in absolute way (Gy). Results: Calculations based on the developed MLC model closely matches transmission measurements (pin-point ionization chamber at selected positions and film for lateral dose profile). See Fig.1. Dose calculations for two clinical cases (whole brain irradiation with opposed beams and lung case with eight fields) are carried out and outcomes are compared with the Eclipse AAA algorithm. Good agreement is observed for the brain case (Figs 2-3) except at the surface where MCEBRT dose can be higher by 20%. This is due to better modeling of electron contamination by MCEBRT. For the lung case an overall good agreement (91% gamma index passing rate with 3%/3mm DTA criterion) is observed (Fig.4) but dose in lung can be over-estimated by up to 10% by AAA (Fig.5). CTV and PTV DVHs from TPS and MCEBRT are nevertheless close (Fig.6). Conclusion: A new Monte Carlo code is developed for plan verification. Contrary to phantombased QA measurements, MCEBRT simulate the exact patient geometry and tissue composition. MCEBRT can be used as extra verification layer for plans where surface dose and tissue heterogeneity are an issue.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TU-C-BRE-06: Effect of Implementing In-House Treatment Couch Model On Patient Specific QA for Pinnacle SmartArc Treatment Plans

Purpose: Failure to model the treatment couch during VMAT QA planar dose calculation may Result in discrepancies between measured and calculated dose. These discrepancies are due to beam attenuation by the treatment couch that is not included in dose calculation. This work evaluates effects of accounting for this attenuation on patient specific VMAT QA results using an in-house created Varian Exact couch model in Pinnacl Methods: Patient specific VMAT QA results for 13 Pinnacle SmartArc plans generated for treatment on a Varian iX accelerator were studied. These plans included 3 treatment sites (7 H'N, 5 brain, 1 prostate). A Pinnacle model for Varian Exact couch was created in-house to replace the CT simulator couch. Composite arc planar doses were calculated with no couch present (NC) and with the Exact couch model (CM) in place for each plan. QA measurements were taken using IBA Matrixx Evolution ion chamber array set up in IBA MultiCube and were compared to each planar dose. Gamma passing criteria of both 3%/3mm and 2%/2mm tolerances were used. Results: Over all treatment sites, increases in gamma passing rates from NC to CM ranged from -0.4% to +27.3% at 3%/3mm and +0.1% to +30.5% at 2%/2mm. Mean increases in passing rates were +3.7% and +5.3% for 3%/3mm and 2%/2mm tolerances, respectively. Site-specific mean increases (NC to CM) in gamma passing rates were +4.4%, +3.4%, +0.4% (3%/3mm tolerance) and +6.9%, +3.7%, and +2.9% at (2%/2mm tolerance) for H'N, brain, and prostate, respectively. Conclusion: Results support use of a couch model when generating planar dose for patient specific VMAT QA analysis. The improvements were most noticeable at 2%/2mm tolerance and for the H'N and brain sites. Eliminating treatment couch beam attenuation as a source of discrepancy in QA measurements may improve the ability to recognize otherwise masked delivered dose errors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Poster — Thur Eve — 61: A new framework for MPERT plan optimization using MC-DAO

This work combines the inverse planning technique known as Direct Aperture Optimization (DAO) with Intensity Modulated Radiation Therapy (IMRT) and combined electron and photon therapy plans. In particular, determining conditions under which Modulated Photon/Electron Radiation Therapy (MPERT) produces better dose conformality and sparing of organs at risk than traditional IMRT plans is central to the project. Presented here are the materials and methods used to generate and manipulate the DAO procedure. Included is the introduction of a powerful Java-based toolkit, the Aperture-based Monte Carlo (MC) MPERT Optimizer (AMMO), that serves as a framework for optimization and provides streamlined access to underlying particle transport packages. Comparison of the toolkit's dose calculations to those produced by the Eclipse TPS and the demonstration of a preliminary optimization are presented as first benchmarks. Excellent agreement is illustrated between the Eclipse TPS and AMMO for a 6MV photon field. The results of a simple optimization shows the functioning of the optimization framework, while significant research remains to characterize appropriate constraints.

60 APPLIED LIFE SCIENCES↗