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NASA NTRS2023

Spectral and Spatial Dependencies in the Validation of Satellite-Based Aerosol Optical Depth from the Geostationary Ocean Color Imager Using the Aerosol Robotic Network

The regional and global scale of aerosols in the atmosphere can be quantified using the aerosol optical depth (AOD) retrieved from satellite observations. To obtain reliable satellite AODs, conducting consistent validations and refining retrieval algorithms are crucial. AODs and Ångström exponents (AEs) measured with the aerosol robotic network (AERONET) are considered as the ground truth for satellite validations. AERONET AEs are used to collocate the wavelength of the AERONET AODs to those of the satellite AODs when there is a discordancy in their wavelengths. However, numerous validation studies have proposed different strategies by applying the AERONET AODs and AEs, and spatiotemporal collocation criteria. This study examined the impact of the wavelength and spatial collocation radius variations by comparing AODs at 550 nm derived from the geostationary ocean color imager (GOCI) with those obtained from the AERONET for the year 2016. The estimated AERONET AODs at 550 nm varied from 5.18% to 11.73% depending on the selection of AOD and AE, and the spatial collocation radii from 0 to 40 km, respectively. The longer the collocation radius and the higher the AODs, the greater the variability observed in the validation results. Overall, the selection of the spatial collocation radius had a stronger impact on the variability in the validation results obtained compared to the selection of the wavelength. The variability was also found in seasonal analysis. Therefore, it is recommended to carefully select the data wavelength and spatial collocation radius, consider seasonal effects, and provide this information when validating satellite AODs using AERONET.

GOCI↗

DOE OSTI2019

Evaluation and Validation Approaches for Simulation of Social Behavior: Challenges and Opportunities

While models of social systems have grown in scope to represent increasingly complex phenomena, efforts to validate these models against observations suffer from a number of challenges that include the lack of shared approaches, the use of single-dimensional evaluation criteria, and the difficulty in evaluating causal mechanisms. Moreover, current evaluation approaches suffer from sensitivity of the existing measurements to initial conditions and model assumptions, and failure to account for uncertainty. These effects lead to the lack of generalizability to new contexts, inability to replicate the validation approach for new models, and difficulties in interpretation of validation results. These challenges can be addressed by building a set of diverse and robust evaluation metrics and by developing best practices for comparative, reproducible validation of varied social simulation approaches against real-world data. Herein, we outline several best practices for data-drive model validation, such as defining evaluation strategies consistent with the intended use case and defining broad comparison criteria to highlight both model strengths and weaknesses. Leveraging common validation practices will enable robust analysis of simulation performance across diverse social scenarios and modeling approaches.

Saldanha, Emily G.↗

DOE OSTI2024

Chlorine Validation through Critical Integral Experiments

An increased interest in the validation of chlorine nuclear data, specifically 35Cl, in recent years has led to the prioritization of conducting chlorine critical experiments for nuclear data validation and criticality safety evaluations. A previous experiment was conducted with PVC and CPVC (chlorinated polyvinyl chloride) to reduce the margin of subcriticality for PF-4 operations with aqueous plutonium chloride solutions. Challenges in determining the composition of specific polymers, namely the CPVC, made it difficult to characterize, and therefore benchmark. Additional materials that were utilizable for chlorine validation were not immediately clear, as form, strength, purity, and composition are all important. A series of possible absorber materials were identified and studied, but ultimately granular sodium chloride was chosen. In addition to the needs of LANL’s PF-4 other industry collaborators have brought attention to the need for chlorine validation. Specifically, the need for HEU electrorefining with LiCl salts at Y-12 was taken into consideration for this experiment, with the experimental configurations being finely tuned to best meet their needs. Needs for validation were also presented by Idaho National Lab (INL) and TerraPower for validation of their Molten Chloride Reactor Experiment (MCRE) and Molten Chloride Fast Reactor (MCFR) and have also been considered.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2013

Validation of Criticality Safety Calculations with SCALE 6.2

SCALE 6.2 provides numerous updates in nuclear data, nuclear data processing, and computational tools utilized in the criticality safety calculational sequences relative to SCALE 6.1. A new 252-group ENDF/B-VII.0 multigroup neutron library, improved ENDF/B-VII.0 continuous energy data, as well as the previously deployed 238-group ENDF/B-VII.0 neutron library are included in SCALE 6.2 for criticality safety analysis. The performance of all three libraries for keff calculations is examined with a broad sampling of critical experiment models covering a range of fuels and moderators. Critical experiments from the International Handbook of Evaluated Criticality Safety Benchmark Experiments (IHECSBE) that are available in the SCALE Verified, Archived Library of Inputs and Data (VALID) are used in this validation effort. Over 300 cases are used in the validation of KENO V.a, and a more limited set of approximately 50 configurations are used for KENO-VI validation. Additionally, some KENO V.a cases are converted to KENO-VI models so that an equivalent set of experiments can be used to validate both codes. For continuous-energy calculations, SCALE 6.2 provides improved performance relative to SCALE 6.1 in most areas with notable improvements in fuel pin lattice cases, particularly those with mixed oxide fuel. Multigroup calculations with the 252-group library also demonstrate improved performance for fuel lattices, uranium (high and intermediate enrichment) and plutonium metal experiments, and plutonium solution systems. Overall, SCALE 6.2 provides equivalent or smaller biases than SCALE 6.1, and the two versions of KENO provide similar results on the same suite of problems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Summary Report Of The FY25 Reactor Physics Verification And Validation Exercises In The Advanced Reactor Technologies - Gas-cooled Reactor Program

Valdiation and verification of numerical tools is critical for ensuring reasonable predictions for design scoping, licensing, and safety analsyis. In this report, two reactor physics verification and validation exercises are presented. The first of these exercises focuses on burnup analysis with data from the Advanced Gas Reactor (AGR) program. Simulations are performed with Monte Carlo N-Particle (MCNP) and are compared with the experimental measurements for the AGR 1 and 2 experiments that utilize both UCO and UO2 fuel. The second exercises utilizes data from the HTR-Proteus experiments to perform reactor physics validation. Specifications of the experimental facility are provdied, along with a demonstration of initial modeling efforts in Serpent for one of the determistic packing experiments. Both cases are part of the Generation-IV international forum (GIF) Very High-Temperature Reactor (VHTR) Computational Methods, Validation, and Benchmarking (CMVB) program, an international collaborative organization dedicated to the verification and validation of High-Temperature Gas-Cooled Reactor (HTGR) analysis. Participation in the CMVB allows the US Department of Energy (DOE) to leverage these existing validation activities to provide extra value through benchmarking activities with other CMVB members.

and Benchmarking (CMVB) program↗

DOE OSTI2025

Summary Report Of The FY25 Computational Fluid Dynamics Verification And Validation Exercises In The Advanced Reactor Technologies - Gas-cooled Reactor Program

Verification and Validation (V&V) of numerical tools is critical for ensuring reasonable predictions during design, safety analysis, and licensing. Recent work in the Advanced Reactor Technologies - Gas-cooled Reactor (ART-GCR) program has focused on V&V of common Computational Fluid Dynamics (CFD) tools that are used within the Untied States. This report presents an update on these CFD V&V activities. These Generation IV Forum (GIF) Very High Temperature Reactor (VHTR) Computational Methods, Validation, and Benchmarking (CMVB) is an international organization dedicated to the verification and validation of High Temperature Gas-Cooled Reactor (HTGR) simulation tools. Participation in the CMVB provides additional value to the V&V activities, as it allows for access to a wider range of data, and provides valuable benchmarking exercises. Three HTGR phenomena are targeted: Reactor Cavity Cooling System (RCCS) performance, core bypass flow, and lower plenum mixing. Simulations of the University of Wisconsin-Madison (UW-Madison) RCCS facilities are performed with Reynolds Averaged Navier-Stokes (RANS) in StarCCM+. Results are compared for both forced and natural convection conditions, with both exhibiting good agreement with experimental measurements. The Idaho National Laboratory (INL) matched index of refraction (MIR) and Korean Atomic Energy Research Institute (KAERI) bypass flow expeirments are used to validation CFD predictions of bypass flow. Simulations are performed with RANS in StarCCM+ and with Large Eddy Simulation (LES) in NekRS. Finally, preliminary simulations of the Institute of Nuclear and New Energy Technology (INET) lower plenum mixing facilities are presented. Initial work has developed models with LES, RANS, and porous media models. These preliminary models are presented and compared to each other to gauge differences in predictions with each of the three methods.

and Benchmarking (CMVB)↗

DOE OSTI2014

Verification as a Foundation for Validation of a Nuclear Fuel Performance Code

Complex multiphysics simulations such as nuclear fuel performance analysis are composed of many submodels used to describe specific phenomena. These phenomena include, as examples, the relationship between stress and strain, heat transfer across a gas gap, and mechanical contact. These submodels work in concert to simulate real-world events, like the behavior of a fuel rod in a reactor. If a simulation tool is able to represent real-world behavior, the tool is said to be validated. While much emphasis is rightly placed on validation, model verification may be undervalued. Verification involves showing that a model performs as intended, that it computes results consistent with its mathematical description. This paper explains the differences between verification and validation and shows how validation should be preceded by verification. Specific verification problems, including several specific to nuclear fuel analysis, are given. Validation results are also presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2017

OC5 Project Phase II: Validation of Global Loads of the DeepCwind Floating Semisubmersible Wind Turbine

This paper summarizes the findings from Phase II of the Offshore Code Comparison, Collaboration, Continued, with Correlation project. The project is run under the International Energy Agency Wind Research Task 30, and is focused on validating the tools used for modeling offshore wind systems through the comparison of simulated responses of select system designs to physical test data. Validation activities such as these lead to improvement of offshore wind modeling tools, which will enable the development of more innovative and cost-effective offshore wind designs. For Phase II of the project, numerical models of the DeepCwind floating semisubmersible wind system were validated using measurement data from a 1/50th-scale validation campaign performed at the Maritime Research Institute Netherlands offshore wave basin. Validation of the models was performed by comparing the calculated ultimate and fatigue loads for eight different wave-only and combined wind/wave test cases against the measured data, after calibration was performed using free-decay, wind-only, and wave-only tests. The results show a decent estimation of both the ultimate and fatigue loads for the simulated results, but with a fairly consistent underestimation in the tower and upwind mooring line loads that can be attributed to an underestimation of wave-excitation forces outside the linear wave-excitation region, and the presence of broadband frequency excitation in the experimental measurements from wind. Participant results showed varied agreement with the experimental measurements based on the modeling approach used. Modeling attributes that enabled better agreement included: the use of a dynamic mooring model; wave stretching, or some other hydrodynamic modeling approach that excites frequencies outside the linear wave region; nonlinear wave kinematics models; and unsteady aerodynamics models. Also, it was observed that a Morison-only hydrodynamic modeling approach could create excessive pitch excitation and resulting tower loads in some frequency bands.

17 WIND ENERGY↗

DOE OSTI2017

Patient-Reported Outcomes After Radiation Therapy in Men With Prostate Cancer: A Systematic Review of Prognostic Tool Accuracy and Validity

Purpose: To identify, through a systematic review, all validated tools used for the prediction of patient-reported outcome measures (PROMs) in patients being treated with radiation therapy for prostate cancer, and provide a comparative summary of accuracy and generalizability. Methods and Materials: PubMed and EMBASE were searched from July 2007. Title/abstract screening, full text review, and critical appraisal were undertaken by 2 reviewers, whereas data extraction was performed by a single reviewer. Eligible articles had to provide a summary measure of accuracy and undertake internal or external validation. Tools were recommended for clinical implementation if they had been externally validated and found to have accuracy ≥70%. Results: The search strategy identified 3839 potential studies, of which 236 progressed to full text review and 22 were included. From these studies, 50 tools predicted gastrointestinal/rectal symptoms, 29 tools predicted genitourinary symptoms, 4 tools predicted erectile dysfunction, and no tools predicted quality of life. For patients treated with external beam radiation therapy, 3 tools could be recommended for the prediction of rectal toxicity, gastrointestinal toxicity, and erectile dysfunction. For patients treated with brachytherapy, 2 tools could be recommended for the prediction of urinary retention and erectile dysfunction. Conclusions: A large number of tools for the prediction of PROMs in prostate cancer patients treated with radiation therapy have been developed. Only a small minority are accurate and have been shown to be generalizable through external validation. This review provides an accessible catalogue of tools that are ready for clinical implementation as well as which should be prioritized for validation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2020

Enhancing nuclear data validation analysis by using machine learning

In this work, we demonstrate how machine learning (ML) techniques can be used as an auxiliary tool for nuclear data validation analysis. The output of the ML analysis can inform evaluators and validators on the quality, or lack thereof, of specific nuclear data and benchmark experiments with respect to simulating these experimental benchmark values. To this end, measured and simulated effective neutron multiplication factors, k eff , of 875 selected ICSBEP critical assemblies and the latter's sensitivities with respect to nuclear data as well as benchmarks' features (e.g., material nuclide, core geometry) are used as input for a random forest (RF) regression model. The RF is used to encode the complex inter-dependencies between thousands of nuclear data features (i.e., sensitivity profiles and aspects describing the measurements) and 875 simulated and experimental k eff values in order to understand what nuclear data features are most informative for predicting bias. The complexity of relationships and high-dimensional space is difficult-to-impossible to search fully using simply expert judgment. As a first proof-of-concept—step, it is demonstrated that this technique is able to correctly trace large discrepancies between simulated and experimental k eff back to fabricated shortcomings in nuclear data that were perturbed to simulated k eff values. In a second, real-case scenario, step, the RF algorithm is used to validate the ENDF/B-VIII.0 library in comparison to ENDF/B-VII.1 nuclear data. One case is showcased where the chosen ML algorithms highlighted nuclear data (the 19 F(n,inl) cross section from 0.4–0.9 MeV) that are shown to be problematic by comparing them to associated differential experimental data and nuclear data from other libraries. In addition to that, it is shown that the RF results point towards poor benchmark experiments and associated underestimated uncertainties (e.g., the PU-SOL-THERM-028 series). However, using the RF algorithm for validating nuclear data with respect to k eff is currently limited to pinpointing groups of questionable nuclear data due to the inherent correlations between features introduced by the nuclear data themselves and how k eff is simulated. Due to this, we recommend that the ML methods presented be used to augment—rather than replace—the expert knowledge of evaluators and validators.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2016

Validating the BISON fuel performance code to integral LWR experiments

BISON is a modern finite element-based nuclear fuel performance code that has been under development at the Idaho National Laboratory (INL) since 2009. The code is applicable to both steady and transient fuel behavior and has been used to analyze a variety of fuel forms in 1D spherical, 2D axisymmetric, or 3D geometries. Code validation is underway and is the subject of this study. A brief overview of BISON’s computational framework, governing equations, and general material and behavioral models is provided. BISON code and solution verification procedures are described, followed by a summary of the experimental data used to date for validation of Light Water Reactor (LWR) fuel. Validation comparisons focus on fuel centerline temperature, fission gas release, and rod diameter both before and following fuel-clad mechanical contact. Comparisons for 35 LWR rods are consolidated to provide an overall view of how the code is predicting physical behavior, with a few select validation cases discussed in greater detail. Our results demonstrate that 1) fuel centerline temperature comparisons through all phases of fuel life are very reasonable with deviations between predictions and experimental data within ±10% for early life through high burnup fuel and only slightly out of these bounds for power ramp experiments, 2) accuracy in predicting fission gas release appears to be consistent with state-of-the-art modeling and with the involved uncertainties and 3) comparison of rod diameter results indicates a tendency to overpredict clad diameter reduction early in life, when clad creepdown dominates, and more significantly overpredict the diameter increase late in life, when fuel expansion controls the mechanical response. In the initial rod diameter comparisons they were unsatisfactory and have lead to consideration of additional separate effects experiments to better understand and predict clad and fuel mechanical behavior. Results from this study are being used to define priorities for ongoing code development and validation activities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Code validation of SAM using natural-circulation experimental data from the compact integral effects test (CIET) facility

The primary objective of this study is to validate the system analysis code, SAM, using experimental data from the Compact Integral Effects Test (CIET) experimental loop. SAM is a modern system analysis code being developed at Argonne National Laboratory for safety analysis of designs for advanced non-light water reactors (non-LWRs), such as sodium-cooled fast reactors, high-temperature gas-cooled reactors, and fluoride salt-cooled high-temperature reactors (FHRs). To support SAM code development for the wide range of non-LWR applications, it is of paramount importance to validate the code against experiments highly relevant to these reactor concepts. Additionally, the CIET facility, which was designed to reproduce the thermal-hydraulics response of FHRs under both forced- and natural-circulation conditions, has been identified and selected as one of the benchmark test facilities for SAM code validation. In this study, two sets of available CIET tests were selected for SAM code validation purposes, namely, power step change transient tests and steady-state natural-circulation tests. For all selected tests, SAM-predicted results show very good agreement with experimental data. The successful validation of SAM against these selected CIET experiments demonstrates that the computer code is well suited for thermal-hydraulics analysis of FHR designs.

42 ENGINEERING↗

DOE OSTI2022

Validation of edge turbulence codes against the TCV-X21 diverted L-mode reference case

Self-consistent full-size turbulent-transport simulations of the divertor and scrape-off-layer (SOL) of existing tokamaks have recently become feasible. This enables the direct comparison of turbulence simulations against experimental measurements. In this work, we perform a series of diverted ohmic L-mode discharges on the tokamak à configuration variable (TCV) tokamak, building a first-of-a-kind dataset for the validation of edge turbulence models. This dataset, referred to as TCV-X21, contains measurements from five diagnostic systems from the outboard midplane (OMP) to the divertor targets—giving a total of 45 one- and two-dimensional comparison observables in two toroidal magnetic field directions. The experimental dataset is used to validate three flux-driven 3D fluid-turbulence models—GBS, GRILLIX and TOKAM3X. With each model, we perform simulations of the TCV-X21 scenario, individually tuning the particle and power source rates to achieve a reasonable match of the upstream separatrix value of density and electron temperature. We find that the simulations match the experimental profiles for most observables at the OMP—both in terms of profile shape and absolute magnitude—while a comparatively poorer agreement is found towards the divertor targets. The match between simulation and experiment is seen to be sensitive to the value of the resistivity, the heat conductivities, the power injection rate and the choice of sheath boundary conditions. Additionally, despite targeting a sheath-limited regime, the discrepancy between simulations and experiment also suggests that the neutral dynamics should be included. The results of this validation show that turbulence models are able to perform simulations of existing devices and achieve reasonable agreement with experimental measurements. Where disagreement is found, the validation helps to identify how the models can be improved. By publicly releasing the experimental dataset and validation analysis, this work should help to guide and accelerate the development of predictive turbulence simulations of the edge and SOL.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

Benchmarks for Model Validation based on LiDAR Wake Measurements

Technology development and design decisions in wind energy are often based on results from simulations performed for individual wind turbines or entire wind plants. It is therefore critical to ensure that the models being used for research and industry applications in wind energy be thoroughly validated against measurements. A full-system validation of wind plant simulations must consider the atmospheric inflow, the response of the wind turbines, and their wakes. This task is complicated by the lack of freely available, quality-controlled, high-quality measurements. Here, such measurements are used to offer a validation exercise that can be used to assess the accuracy of models of any fidelity level. When it comes to real-world measurements, the dataset considered herein is simple in terms of terrain but exhibits pronounced diurnal cycles. Instead of a full-scale wind plant, we consider an individual research-scale, utility wind turbine instrumented for power and loads measurements. Three benchmarks are defined, with increasing levels of complexity: near neutral, slightly unstable, and very stable atmospheric stratification. Through comparisons between observations and simulations, the benchmarks provide complementary information about the model performance and its ability to reproduce mean and dynamic wake characteristics. This article describes the measurements and methodology used to define these benchmarks and provides the information required to perform simulations and conduct the model-measurement comparison. The objective is to provide a robust wake model validation exercise open to anyone, which will serve to minimize uncertainty in model validation practices related to varying methodologies across simulation tools and users.

17 WIND ENERGY↗

DOE OSTI2021

Advanced Performance Metrics and their Application to the Sensitivity Analysis for Model Validation and Calibration

High-quality generator dynamic models are critical to reliable and accurate power systems studies and planning. With the availability of PMUs, measurement-based approach for model validation has gained significant prominence. In this approach, the quality of a model is analyzed by visually comparing measured generator response with the model-based simulated response for large system disturbances. This paper proposes a new set of performance metrics to assess the model validation results to facilitate automation of the model validation process. In the proposed methodology, first, the slow governor response and comparatively faster oscillatory response are separated, and then a separate set of performance metrics is calculated for each of these two components. These proposed metrics quantify the mismatch between the actual and model-based response in a comprehensive manner without missing any information enabling automation of the process. Furthermore, in this paper, we are also proposing that the sensitivity analysis for model calibration be performed with respect to the proposed metrics for the systematic identification of key parameters. In this work, results obtained using both simulated and real-world case-studies validate the effectiveness of the proposed performance metrics for model validation and their application to the sensitivity analysis for model calibration.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Validation of Numerical Models of the Offshore Wind Turbine From the Alpha Ventus Wind Farm Against Full-Scale Measurements Within OC5 Phase III

The main objective of the Offshore Code Comparison Collaboration Continuation, with Correlation (OC5) project is validation of aero-hydro-servo-elastic simulation tools for offshore wind turbines (OWTs) through comparison of simulated results to the response data of physical systems. Phase III of the OC5 project validates OWT models against the measurements recorded on a Senvion 5M wind turbine supported by the OWEC Quattropod from the alpha ventus offshore wind farm. The following operating conditions of the wind turbine were chosen for the validation: (1) idling below the cut-in wind speed, (2) rotor-nacelle assembly (RNA) rotation maneuver below the cut-in wind speed, (3) power production below and above the rated wind speed, and (4) shutdown. A number of validation load cases were defined based on these operating conditions. The following measurements were used for validation: (1) strains and accelerations recorded on the support structure and (2) pitch, yaw, and azimuth angles, generator speed, and electrical power recorded from the RNA. Strains were not directly available from the majority of the OWT simulation tools; therefore, strains were calculated based on out-of-plane bending moments, axial forces, and cross-sectional properties of the structural members. The simulation results and measurements were compared in terms of time series, discrete Fourier transforms, power spectral densities, and probability density functions of strains and accelerometers. A good match was achieved between the measurements and models setup by OC5 Phase III participants.

17 WIND ENERGY↗

DOE OSTI2015

SU-E-T-793: Validation of COMPASS 3D Dosimetry as Pre Treatment Verification with Commercial TPS Algorithms

Purpose: The purpose of this study was to validate the advent of COMPASS 3D dosimetry as a routine pre treatment verification tool with commercially available CMS Monaco and Oncentra Masterplan planning system. Methods: Twenty esophagus patients were selected for this study. All these patients underwent radical VMAT treatment in Elekta Linac and plans were generated in Monaco v5.0 with MonteCarlo(MC) dose calculation algorithm. COMPASS 3D dosimetry comprises an advanced dose calculation algorithm of collapsed cone convolution(CCC). To validate CCC algorithm in COMPASS, The DICOM RT Plans generated using Monaco MC algorithm were transferred to Oncentra Masterplan v4.3 TPS. Only final dose calculations were performed using CCC algorithm with out optimization in Masterplan planning system. It is proven that MC algorithm is an accurate algorithm and obvious that there will be a difference with MC and CCC algorithms. Hence CCC in COMPASS should be validated with other commercially available CCC algorithm. To use the CCC as pretreatment verification tool with reference to MC generated treatment plans, CCC in OMP and CCC in COMPASS were validated using dose volume based indices such as D98, D95 for target volumes and OAR doses. Results: The point doses for open beams were observed <1% with reference to Monaco MC algorithms. Comparisons of CCC(OMP) Vs CCC(COMPASS) showed a mean difference of 1.82%±1.12SD and 1.65%±0.67SD for D98 and D95 respectively for Target coverage. Maximum point dose of −2.15%±0.60SD difference was observed in target volume. The mean lung dose of −2.68%±1.67SD was noticed between OMP and COMPASS. The maximum point doses for spinal cord were −1.82%±0.287SD. Conclusion: In this study, the accuracy of CCC algorithm in COMPASS 3D dosimetry was validated by compared with CCC algorithm in OMP TPS. Dose calculation in COMPASS is feasible within < 2% in comparison with commercially available TPS algorithms.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

A GPU-accelerated Monte Carlo dose calculation platform and its application toward validating an MRI-guided radiation therapy beam model

Purpose: The clinical commissioning of IMRT subject to a magnetic field is challenging. The purpose of this work is to develop a GPU-accelerated Monte Carlo dose calculation platform based on PENELOPE and then use the platform to validate a vendor-provided MRIdian head model toward quality assurance of clinical IMRT treatment plans subject to a 0.35 T magnetic field. Methods: PENELOPE was first translated from FORTRAN to C++ and the result was confirmed to produce equivalent results to the original code. The C++ code was then adapted to CUDA in a workflow optimized for GPU architecture. The original code was expanded to include voxelized transport with Woodcock tracking, faster electron/positron propagation in a magnetic field, and several features that make gPENELOPE highly user-friendly. Moreover, the vendor-provided MRIdian head model was incorporated into the code in an effort to apply gPENELOPE as both an accurate and rapid dose validation system. A set of experimental measurements were performed on the MRIdian system to examine the accuracy of both the head model and gPENELOPE. Ultimately, gPENELOPE was applied toward independent validation of patient doses calculated by MRIdian’s KMC. Results: An acceleration factor of 152 was achieved in comparison to the original single-thread FORTRAN implementation with the original accuracy being preserved. For 16 treatment plans including stomach (4), lung (2), liver (3), adrenal gland (2), pancreas (2), spleen(1), mediastinum (1), and breast (1), the MRIdian dose calculation engine agrees with gPENELOPE with a mean gamma passing rate of 99.1% ± 0.6% (2%/2 mm). Conclusions: A Monte Carlo simulation platform was developed based on a GPU- accelerated version of PENELOPE. This platform was used to validate that both the vendor-provided head model and fast Monte Carlo engine used by the MRIdian system are accurate in modeling radiation transport in a patient using 2%/2 mm gamma criteria. Future applications of this platform will include dose validation and accumulation, IMRT optimization, and dosimetry system modeling for next generation MR-IGRT systems.

60 APPLIED LIFE SCIENCES↗