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DOE OSTI2012

Incorporation of Multi-Member Substructure Capabilities in FAST for Analysis of Offshore Wind Turbines: Preprint

FAST, developed by the National Renewable Energy Laboratory (NREL), is an aero-hydro-servo-elastic tool widely used for analyzing onshore and offshore wind turbines. This paper discusses recent modifications made to FAST to enable the examination of offshore wind turbines with fixed-bottom, multi-member support structures (which are commonly used in transitional-depth waters). ; This paperaddresses the methods used for incorporating the hydrostatic and hydrodynamic loading on multi-member structures in FAST through its hydronamic loading module, HydroDyn. Modeling of the hydrodynamic loads was accomplished through the incorporation of Morison and buoyancy loads on the support structures. Issues addressed include how to model loads at the joints of intersecting members and ontapered and tilted members of the support structure. Three example structures are modeled to test and verify the solutions generated by the modifications to HydroDyn, including a monopile, tripod, and jacket structure. Verification is achieved through comparison of the results to a computational fluid dynamics (CFD)-derived solution using the commercial software tool STAR-CCM+.

17 WIND ENERGY↗

NASA NTRS1996

User Interface Developed for Controls/CFD Interdisciplinary Research

The NASA Lewis Research Center, in conjunction with the University of Akron, is developing analytical methods and software tools to create a cross-discipline "bridge" between controls and computational fluid dynamics (CFD) technologies. Traditionally, the controls analyst has used simulations based on large lumping techniques to generate low-order linear models convenient for designing propulsion system controls. For complex, high-speed vehicles such as the High Speed Civil Transport (HSCT), simulations based on CFD methods are required to capture the relevant flow physics. The use of CFD should also help reduce the development time and costs associated with experimentally tuning the control system. The initial application for this research is the High Speed Civil Transport inlet control problem. A major aspect of this research is the development of a controls/CFD interface for non-CFD experts, to facilitate the interactive operation of CFD simulations and the extraction of reduced-order, time-accurate models from CFD results. A distributed computing approach for implementing the interface is being explored. Software being developed as part of the Integrated CFD and Experiments (ICE) project provides the basis for the operating environment, including run-time displays and information (data base) management. Message-passing software is used to communicate between the ICE system and the CFD simulation, which can reside on distributed, parallel computing systems. Initially, the one-dimensional Large-Perturbation Inlet (LAPIN) code is being used to simulate a High Speed Civil Transport type inlet. LAPIN can model real supersonic inlet features, including bleeds, bypasses, and variable geometry, such as translating or variable-ramp-angle centerbodies. Work is in progress to use parallel versions of the multidimensional NPARC code.

Source record↗

DOE OSTI2025

Control Strategies and Validation in the Hybrid Optimization and Performance Platform (HOPP)

The Hybrid Optimization and Performance Platform (HOPP) is a tool that simulates hybrid power plants in various configurations, and also calculates the financial feasibility of these plants. This report outlines an overview of HOPP and the energy storage dispatch strategies available. It then presents three case studies which demonstrate different applications of HOPP. The first case looks at the profitability of hybrid power plants in different locations in the USA. The second case examines the availability of hybrid power plants to provide energy reliability services. The third case presents a plant that produces both hydrogen and electricity, and demonstrates a dispatch strategy that chooses the most profitable energy vector based on price signals. The next section shows the validation of HOPP on operational data, using data from both unit-scale and utility-scale power plants. This validation process demonstrated that HOPP can simulate the power output of both wind and solar PV plants at both scales with comparable fidelity to an existing commercial software tool. Finally, HOPP is applied in a field test which applies an optimal dispatch strategy to a physical battery in a unit-scale hybrid plant at NREL. HOPP's optimal dispatch strategy, applied in a real-world setting, improved this hybrid plant's ability to meet a load signal while minimizing operational costs.

14 SOLAR ENERGY↗

DOE OSTI2014

Tools for Accurate and Efficient Analysis of Complex Evolutionary Mechanisms in Microbial Genomes (Final Report)

I proposed to develop computationally efficient tools for accurate detection and reconstruction of microbes' complex evolutionary mechanisms, thus enabling rapid and accurate annotation, analysis and understanding of their genomes. To achieve this goal, I proposed to address three aspects. (1) Mathematical modeling. A major challenge facing the accurate detection of HGT is that of distinguishing between these two events on the one hand and other events that have similar "effects." I proposed to develop a novel mathematical approach for distinguishing among these events. Further, I proposed to develop a set of novel optimization criteria for the evolutionary analysis of microbial genomes in the presence of these complex evolutionary events. (2) Algorithm design. In this aspect of the project, I proposed to develop an array of efficient and accurate algorithms for analyzing microbial genomes based on the formulated optimization criteria. Further, I proposed to test the viability of the criteria and the accuracy of the algorithms in an experimental setting using both synthetic as well as biological data. (3) Software development. I proposed the final outcome to be a suite of software tools which implements the mathematical models as well as the algorithms developed.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2023

NASA GRC ICME Schema for Materials Data Management: An Executive Summary

Integrated Computational Materials Engineering (ICME) has received a growing emphasis in attention due its potential impact on rapid material design, reduction in cost and time to market for new applications, and the promise of ‘fit-for-purpose’ materials coupled with recent advances in high performance computing and material characterization tools. However, for an organization to implement ICME practices for material discovery and design, a series of both technical and cultural challenges must be overcome to foster an environment that enables efficient, traceable, and predictive multiscale simulations of material behavior to enable virtual design of materials. In 2016, NASA sponsored a 2040 Vision study to define the potential 25-year future state required for integrated multiscale modeling of materials and systems to improve both the associated time and cost for aerospace and aeronautical innovation. The study envisions a cyber-physical-social ecosystem of experimentally validated computational models, tools, and techniques, along with the associated digital tapestry, that can enable rapid, optimized, ‘fit-for-purpose’ design of materials, components, and systems. A key requirement for such an ecosystem is the development of a robust information management system for materials across their full lifecycle, including material pedigree, experimental (real) and virtual (simulation) data, developed material models, and the implementation of models in engineering applications, such that process-structure-property-performance relationships can be established, thereby enabling the virtual design and optimization of materials. Such an information management system must be able to effectively capture: i) material information at each length scale; ii) test data and analysis; iii) associated material models; and iv) material and model deployment in engineering applications. These systems must also provide traceability between experimental and virtual representations of the material to ensure, when appropriate, the material digital twin is maintained. Additionally, this robust material information management system must be able to seamlessly connect with both commercial and an organization’s in-house software tools, be they analysis tools, other material databases, product lifecycle management (PLM) or simulation data management (SDM) tools, etc., such that automation of the design and analysis of a material across multiple length scales is possible. In this paper, an executive summary of the NASA GRC ICME Schema for materials information management is presented. The database best practices and schema design philosophy specifically for ICME materials data management and an overview description of each element in the schema is given, along with its associated role in an ICME workflow. Additionally, auxiliary tools that interact with the database and provide judicious automation with regards to importing, exporting, and analyzing materials data are presented. Such tools are critical to an ICME ecosystem, not only for their role in enabling optimization, but also in relieving users of tedious manual tasks, thus helping to promote adoption and combat the cultural challenges organizations face in enabling ICME.

Materials↗

DOE OSTI2021

Interactive Mesh Generation and Comparison Tools for Nuclear Energy Advanced Modeling & Simulation Phase I. Final Report

The promise of computer simulations for nuclear reactor designs is the opportunity to speed up the design process while also improving safety, providing more detail and higher fidelity, reducing cost, minimizing schedule risk, and avoiding many other potential problems; because simulations have the potential to be much less expensive and time-consuming than traditional development – where scale models and physical tests require construction and long lead times – it is possible to consider more alternatives and complete more comprehensive assessments before the design is finalized and constructed. As more design scenarios are studied by simulation, the speed that simulations promise is only available as long as bottlenecks are addressed for these scenarios. A frequent bottleneck is the amount of human labor required to describe the shape of the objects being designed and decompose the shape into simple elements, such as hexahedra, that are small enough to capture the physical phenomena of interest without being so small that even fast computers cannot perform the simulation in a reasonable amount of time. Recently, techniques for creating all-hexahedral decompositions have been developed, but they require some human input. Many simulation codes prefer all-hexahedral decompositions, so we proposed to evaluate the feasibility of these techniques on nuclear reactor geometries to see whether they required too much human input to be commercially viable. Our study concluded that they can be made viable with some additional software tools to reduce the amount of user input required.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2011

Computational Needs for the Next Generation Electric Grid Proceedings

The April 2011 DOE workshop, 'Computational Needs for the Next Generation Electric Grid', was the culmination of a year-long process to bring together some of the Nation's leading researchers and experts to identify computational challenges associated with the operation and planning of the electric power system. The attached papers provide a journey into these experts' insights, highlighting a class of mathematical and computational problems relevant for potential power systems research. While each paper defines a specific problem area, there were several recurrent themes. First, the breadth and depth of power system data has expanded tremendously over the past decade. This provides the potential for new control approaches and operator tools that can enhance system efficiencies and improve reliability. However, the large volume of data poses its own challenges, and could benefit from application of advances in computer networking and architecture, as well as data base structures. Second, the computational complexity of the underlying system problems is growing. Transmitting electricity from clean, domestic energy resources in remote regions to urban consumers, for example, requires broader, regional planning over multi-decade time horizons. Yet, it may also mean operational focus on local solutions and shorter timescales, as reactive power and system dynamics (including fast switching and controls) play an increasingly critical role in achieving stability and ultimately reliability. The expected growth in reliance on variable renewable sources of electricity generation places an exclamation point on both of these observations, and highlights the need for new focus in areas such as stochastic optimization to accommodate the increased uncertainty that is occurring in both planning and operations. Application of research advances in algorithms (especially related to optimization techniques and uncertainty quantification) could accelerate power system software tool performance, i.e. speed to solution, and enhance applicability for new and existing real-time operation and control approaches, as well as large-scale planning analysis. Finally, models are becoming increasingly essential for improved decision-making across the electric system, from resource forecasting to adaptive real-time controls to online dynamics analysis. The importance of data is thus reinforced by their inescapable role in validating, high-fidelity models that lead to deeper system understanding. Traditional boundaries (reflecting geographic, institutional, and market differences) are becoming blurred, and thus, it is increasingly important to address these seams in model formulation and utilization to ensure accuracy in the results and achieve predictability necessary for reliable operations. Each paper also embodies the philosophy that our energy challenges require interdisciplinary solutions - drawing on the latest developments in fields such as mathematics, computation, economics, as well as power systems. In this vein, the workshop should be viewed not as the end product, but the beginning of what DOE seeks to establish as a vibrant, on-going dialogue among these various communities. Bridging communication gaps among these communities will yield opportunities for innovation and advancement. The papers and workshop discussion provide the opportunity to learn from experts on the current state-of-the-art on computational approaches for electric power systems, and where one may focus to accelerate progress. It has been extremely valuable to me as I better understand this space, and consider future programmatic activities. I am confident that you too will enjoy the discussion, and certainly learn from the many experts. I would like to thank the authors of the papers for sharing their perspectives, as well as the paper discussants, session recorders, and participants. The meeting would not have been as successful without your commitment and engagement. I also would like to thank Joe Eto and Bob Thomas for their vision and leadership in bringing together such a well-structured and productive forum.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Detector Simulation Challenges for Future Accelerator Experiments

Detector simulation is a key component for studies on prospective future high-energy colliders, the design, optimization, testing and operation of particle physics experiments, and the analysis of the data collected to perform physics measurements. This review starts from the current state of the art technology applied to detector simulation in high-energy physics and elaborates on the evolution of software tools developed to address the challenges posed by future accelerator programs beyond the HL-LHC era, into the 2030–2050 period. New accelerator, detector, and computing technologies set the stage for an exercise in how detector simulation will serve the needs of the high-energy physics programs of the mid 21st century, and its potential impact on other research domains.

43 PARTICLE ACCELERATORS↗

DOE OSTI2018

SISTec: Mathematical Calibration of Large Clearance Monitors - 18265

One major path for clearance of large amount of waste arising from the decommission of nuclear power plants is based on measurement with large clearance monitors (also known as free release measurement facilities). These devices utilize multi-detector plastic scintillator arrays (large clearance monitors can consist of up to 24 plastic scintillators) to offer both, extremely low minimum detectable activities (MDA) and short measurement times for waste packages weighing up to one metric ton. However, a major problem with these devices is to obtain nuclide specific efficiencies, especially for geometrically complex large waste packages. Normal procedure for estimating the efficiency is to device dummy waste packages and attach point sources with well-known activities to unfavourable positions in these packages. In accordance with this procedure, calibration factors can be derived in a radiological conservative way. Devising such test dummies is not always possible and the procedure is prone to generating large measurement uncertainties. In this publication, we propose a new method to derive calibration factors by means of the Los Alamos National Laboratory (LANL) simulation tool Monte Carlo N-Particle (MCNP) and a statistical-phenomenological model for the detector characterization. In a multi-step approach, first the detector response for a distribution of activity in a waste package is calculated and subsequently the detectors are mathematically characterized. Applying state of the art statistical and optimizing procedures, parameters for the detector response are derived in a self-consistent way. This also allows to rigorously propagate the uncertainties to the final calculated calibration factors according to the Guide to the Expression of Uncertainty in Measurement (GUM supplement 1). To validate the derived parameters for the detector characterization a minimally invasive experimental setup was devised and installed into the large clearance monitor. It consisted of an aluminum swivel arm which could position point sources to the relevant coordinates. The so collected measurement data not only allowed to investigate the precision of the calculated calibration factors, but also to probe the location of concentrated activity sources in the waste package. Furthermore, data on measurements with dummy waste packages were collected to test the reproducibility of well-known calibration factors. We present the software tool SIStec, which will provide an intuitive user-interface to generate and simulate waste package models and execute the above-mentioned method. Using SIStec, different scenarios for the distribution of activity in the waste package can be probed. This will also allow to optimize the clearance process on various levels. For example, measurement time for pre-measurements can be reduced in exchange for unfavourable calibration factors, which would still allow to meet the regulator limits for clearance. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Demonstration of a modeling toolkit for the design of building electrical distribution systems

The deployment of building equipment (e.g., lighting, security) and miscellaneous electrical loads that fundamentally require DC power for operation is increasing. Powering these DC loads has traditionally required an AC/DC converter, but the installation of photovoltaic (PV) and battery energy storage systems that primarily produce DC power eliminates the need for AC/DC converters at each end-device. However, analyzing system energy efficiency and cost for different electrical distribution architectures can be challenging as software tools that support this are not readily available. This paper presents preliminary results from a laboratory verification of the Building Electrical Efficiency Analysis Model (BEEAM) toolkit that was developed to address this gap. Three different eight-luminaire lighting systems comprised of market-available products were designed and modeled: one that used traditional AC distribution, a second that used a hybrid AC -to- centralized DC electrical distribution architecture, and a third that used a hybrid AC -to- distributed DC architecture. Notably, AC/DC conversions are required in all three systems. BEEAM models for LED drivers as well as Power-over-Ethernet (PoE) switches were created using laboratory characterization data. The lighting systems were simulated in Modelica, and the results were compared with each other and physics-based expectations. Simulation results show that PoE system energy efficiency is highly dependent on both device specification (e.g., LED driver and PoE switch efficiency) and system architecture (e.g., PoE switch loading) choices, as expected. For the products and system architectures selected for this study, the two DC systems were found to be less efficient than the AC system over the course of typical operation. In future work, simulation results will be compared with laboratory measurements to validate the usefulness of this software for design, and lighting systems with integrated PV and battery energy storage will be simulated to quantify the energy performance improvements that result from the elimination of some AC/DC converters.

Waghale, Anay S.↗

DOE OSTI2012

GAMMA-RAY BURST AFTERGLOW BROADBAND FITTING BASED DIRECTLY ON HYDRODYNAMICS SIMULATIONS

We present a powerful new tool for fitting broadband gamma-ray burst afterglow data, which can be used to determine the burst explosion parameters and the synchrotron radiation parameters. By making use of scale invariance between relativistic jets of different energies and different circumburst medium densities, and by capturing the output of high-resolution two-dimensional relativistic hydrodynamical (RHD) jet simulations in a concise summary, the jet dynamics are generated quickly. Our method calculates the full light curves and spectra using linear radiative transfer sufficiently fast to allow for a direct iterative fit of RHD simulations to the data. The fit properly accounts for jet features that so far have not been successfully modeled analytically, such as jet decollimation, inhomogeneity along the shock front, and the transitory phase between the early-time relativistic and late-time non-relativistic outflow. As a first application of the model we simultaneously fit the radio, X-ray, and optical data of GRB 990510. We find not only noticeable differences between our findings for the explosion and radiation parameters and those of earlier authors, but also an improved model fit when we include the observer angle in the data fit. The fit method will be made freely available on request and online at http://cosmo.nyu.edu/afterglowlibrary. In addition to data fitting, the software tools can also be used to quickly generate a light curve or spectrum for arbitrary observer position, jet, and radiation parameters.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Exploring MDSplus data-acquisition software and custom devices

MDSplus is a software tool designed for data acquisition, storage, and analysis of complex scientific experiments. Over the years, MDSplus has primarily been used for data management for fusion experiments. This paper demonstrates that MDSplus can be used for a much wider variety of systems and experiments. We present a step-by-step tutorial describing how to create a simple experiment, manage the data, and analyze it using MDSplus and Python. To this end, a custom example device was developed to be used as the data source. This device was built on an open-source electronic hardware platform, and it consists of a microcontroller and two sensors. Finally, we read data from these sensors, store it in MDSplus, and use JupyterLab to visualize and process it.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

PQML: Enabling the Predictive Reproducibility on NISQ Machines for Quantum ML Applications

Quantum computing represents a groundbreaking approach to high-performance computing. In recent years, quantum computers have progressed from single-qubit processors to systems boasting over 400 qubits. The presence of such a large number of qubits offers significant advantages, including enhanced computational speed—a capability beyond classical computing methods. However, the current stage of quantum computing is referred to as the noisy intermediate-scale quantum (NISQ) era. The existence of noise in this era presents challenges in testing quantum computing applications, leading to considerable variance in application results. Furthermore, the diverse noise characteristics observed across different machines exacerbate this issue, complicating the selection of the appropriate machine for application execution. In response to these challenges, we introduce our Predictive Quantum Machine Learning (PQML) tool. This tool is designed to predict outcomes when executing identical quantum machine learning applications—specifically, a critical suite of variational quantum algorithms—across various quantum computers during the NISQ era. This effort relies on data collected over a 12-month period. To the best of our knowledge, this study represents the first attempt to ensure reproducibility across quantum computers for complex circuits. Additionally, we have developed a model capable of forecasting the accuracy of quantum computers for variational quantum algorithms, with a particular emphasis on quantum machine learning as a case study.

Senapati, Priyabrata [Kent State University]↗

DOE OSTI2022

Tools for Design and Scale-Up of Solar Thermochemical Reactors: Cooperative Research and Development Final Report, CRADA Number CRD-13-00530

NREL will be collaborating with the Participant on a United States - Australia Solar Energy Collaboration (USASEC) Project Number 1-USO034 "Tools for design and scale-up of solar thermochemical reactors." The grant funds for the Participant's 3.5 year project number 1-US034 commencing on 1 February 2013 have been awarded to the Participant by the Australian Renewable Energy Agency and NREL will be collaborating with the Participant during the final 28 months of this project. This project seeks to provide basic knowledge required to design solar thermochemical reactors able to perform the required energy conversions. In several proposed and demonstrated reactors, concentrated sunlight directly irradiates small solid particles suspended in fluid, enabling very high heat transfer rates to the particles which are the sites of chemical reaction. The reactors, therefore, involve the complex and couple dynamics of turbulent, chemically reacting, particle-laden flows and their interaction with concentrating solar radiation. A strong understanding of these coupled interactions will be crucial important in predicting and optimizing the performance of prototype reactors, but this understanding does not yet exist, since they have never been studied in any fundamental way. The project has a assembled an internationally leading team from The University of New South Wales (UNSW) and the University of Adelaide in Australia and the NREL in the United States to address this key gap in available know-how. The project will use U.S. Dept. of Energy (DOE) supercomputers, among the most powerful available worldwide, with cutting-edge software tools to perform first-principles simulations of the relevant interactions. These studies will be combined with detailed laser-based measurements in Australia to provide the first comprehensive databases concerning the governing phenomena in directly irradiated solar-thermochemical reactors. The outcomes will be the basic scientific knowledge, engineering knowhow and modeling tools necessary to design new reactor concepts and then scale up from the laboratory bench to practical size systems.

14 SOLAR ENERGY↗

DOE OSTI2014

SU-E-T-532: Validation and Implementation of Model-Based Patient Specific Quality Assurance Using Mobius3D and MobiusFX in a Clinical Setting

Purpose: This work carries out the commissioning and validation of the Mobius3D and MobiusFX software tools, which can replace the time-consuming measurement-based patient specific quality assurance (PSQA). Methods: The beam model supplied by Mobius3D was validated against a 21EX linac's beam measured data. Complex patient (VMAT) plans using Eclipse treatment planning system (TPS) was used to test the consistency between Mobius3D (calculates dose using patient image and field data) and MobiusFx (calculates dose using treatment dynalog files). Dose difference and gamma analysis (3%/3mm) between Mobius3D and MobiusFx were used to assess treatment plan and treatment delivery consistency. An end-to-end test was performed to validate Mobius3D and MobiusFx against ion chamber measurements. Effect of the dosimetric leaf gap (DLG) on Mobius3D dose calculation was additionally investigated. Results: Mobius3D beam model parameters matched within 1%-3% with our beam measured data. A comparison of Mobius3D and MobiusFx dose matrices for VMAT planned prostate cases showed (0.33±0.07)% mean dose difference with gamma values above 95%. The end-to-end test showed dose differences of 1% between Mobius3D and MobiusFx. Dependence of Mobius3D dose calculation upon DLG was explored by introducing a ±0.5 mm change in the default value for DLG. This change resulted in agreement differences above 2% Conclusion: Use of reference beam data would appear to speed up commissioning process for the clinical implementation of Mobius3D. However, careful consideration is required when comparing the information provided by the software, since large dose variations can be seen when the proper parameters are not optimized. The plan and delivered dose were in good agreement; hence MobiusFx has the potential to significantly speed up the PSQA process and at the same time helps to verify treatment parameters that are not possible with measurement-based PSQA.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2012

Enforcing elemental mass and energy balances for reduced order models

Development of economically feasible gasification and carbon capture, utilization and storage (CCUS) technologies requires a variety of software tools to optimize the designs of not only the key devices involved (e., g., gasifier, CO{sub 2} adsorber) but also the entire power generation system. High-fidelity models such as Computational Fluid Dynamics (CFD) models are capable of accurately simulating the detailed flow dynamics, heat transfer, and chemistry inside the key devices. However, the integration of CFD models within steady-state process simulators, and subsequent optimization of the integrated system, still presents significant challenges due to the scale differences in both time and length, as well the high computational cost. A reduced order model (ROM) generated from a high-fidelity model can serve as a bridge between the models of different scales. While high-fidelity models are built upon the principles of mass, momentum, and energy conservations, ROMs are usually developed based on regression-type equations and hence their predictions may violate the mass and energy conservation laws. A high-fidelity model may also have the mass and energy balance problem if it is not tightly converged. Conservations of mass and energy are important when a ROM is integrated to a flowsheet for the process simulation of the entire chemical or power generation system, especially when recycle streams are connected to the modeled device. As a part of the Carbon Capture Simulation Initiative (CCSI) project supported by the U.S. Department of Energy, we developed a software framework for generating ROMs from CFD simulations and integrating them with Process Modeling Environments (PMEs) for system-wide optimization. This paper presents a method to correct the results of a high-fidelity model or a ROM such that the elemental mass and energy are conserved perfectly. Correction factors for the flow rates of individual species in the product streams are solved using a minimization algorithm based on Lagrangian multiplier method. Enthalpies of product streams are also modified to enforce the energy balance. The approach is illustrated for two ROMs, one based on a CFD model of an entrained-flow gasifier and the other based on the CFD model of a multiphase CO{sub 2} adsorber.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2015

SU-E-T-616: Plan Quality Assessment of Both Treatment Planning System Dose and Measurement-Based 3D Reconstructed Dose in the Patient

Purpose: Systematic radiotherapy plan quality assessment promotes quality improvement. Software tools can perform this analysis by applying site-specific structure dose metrics. The next step is to similarly evaluate the quality of the dose delivery. This study defines metrics for acceptable doses to targets and normal organs for a particular treatment site and scores each plan accordingly. The input can be the TPS or the measurement-based 3D patient dose. From this analysis, one can determine whether the delivered dose distribution to the patient receives a score which is comparable to the TPS plan score, otherwise replanning may be indicated. Methods: Eleven neuroblastoma patient plans were exported from Eclipse to the Quality Reports program. A scoring algorithm defined a score for each normal and target structure based on dose-volume parameters. Each plan was scored by this algorithm and the percentage of total possible points was obtained. Each plan also underwent IMRT QA measurements with a Mapcheck2 or ArcCheck. These measurements were input into the 3DVH program to compute the patient 3D dose distribution which was analyzed using the same scoring algorithm as the TPS plan. Results: The mean quality score for the TPS plans was 75.37% (std dev=14.15%) compared to 71.95% (std dev=13.45%) for the 3DVH dose distribution. For 3/11 plans, the 3DVH-based quality score was higher than the TPS score, by between 0.5 to 8.4 percentage points. Eight/11 plans scores decreased based on IMRT QA measurements by 1.2 to 18.6 points. Conclusion: Software was used to determine the degree to which the plan quality score differed between the TPS and measurement-based dose. Although the delivery score was generally in good agreement with the planned dose score, there were some that improved while there was one plan whose delivered dose quality was significantly less than planned. This methodology helps evaluate both planned and delivered dose quality. Sun Nuclear Corporation has provded a license for the software described.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2011

PARETO: A novel evolutionary optimization approach to multiobjective IMRT planning

Purpose: In radiation therapy treatment planning, the clinical objectives of uniform high dose to the planning target volume (PTV) and low dose to the organs-at-risk (OARs) are invariably in conflict, often requiring compromises to be made between them when selecting the best treatment plan for a particular patient. In this work, the authors introduce Pareto-Aware Radiotherapy Evolutionary Treatment Optimization (pareto), a multiobjective optimization tool to solve for beam angles and fluence patterns in intensity-modulated radiation therapy (IMRT) treatment planning. Methods: pareto is built around a powerful multiobjective genetic algorithm (GA), which allows us to treat the problem of IMRT treatment plan optimization as a combined monolithic problem, where all beam fluence and angle parameters are treated equally during the optimization. We have employed a simple parameterized beam fluence representation with a realistic dose calculation approach, incorporating patient scatter effects, to demonstrate feasibility of the proposed approach on two phantoms. The first phantom is a simple cylindrical phantom containing a target surrounded by three OARs, while the second phantom is more complex and represents a paraspinal patient. Results: pareto results in a large database of Pareto nondominated solutions that represent the necessary trade-offs between objectives. The solution quality was examined for several PTV and OAR fitness functions. The combination of a conformity-based PTV fitness function and a dose-volume histogram (DVH) or equivalent uniform dose (EUD) -based fitness function for the OAR produced relatively uniform and conformal PTV doses, with well-spaced beams. A penalty function added to the fitness functions eliminates hotspots. Comparison of resulting DVHs to those from treatment plans developed with a single-objective fluence optimizer (from a commercial treatment planning system) showed good correlation. Results also indicated that pareto shows promise in optimizing the number of beams. Conclusions: This initial evaluation of the evolutionary optimization software tool pareto for IMRT treatment planning demonstrates feasibility and provides motivation for continued development. Advantages of this approach over current commercial methods for treatment planning are many, including: (1) fully automated optimization that avoids human controlled iterative optimization and potentially improves overall process efficiency, (2) formulation of the problem as a true multiobjective one, which provides an optimized set of Pareto nondominated solutions refined over hundreds of generations and compiled from thousands of parameter sets explored during the run, and (3) rapid exploration of the final nondominated set accomplished by a graphical interface used to select the best treatment option for the patient.

62 RADIOLOGY AND NUCLEAR MEDICINE↗