Deep learning analysis of deeply virtual exclusive photoproduction
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72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Adaptive linear predictor FIR filter based on the Cyclone V FPGA with HPS to reduce narrow band RFI in AERA radio detection of cosmic rays
We present the new approach to a filtering of radio frequency interferences (RFI) in the Auger Engineering Radio Array (AERA) which study the electromagnetic part of the Extensive Air Showers. The radio stations can observe radio signals caused by coherent emissions due to geomagnetic radiation and charge excess processes. AERA observes frequency band from 30 to 80 MHz. This range is highly contaminated by human-made RFI. In order to improve the signal to noise ratio RFI filters are used in AERA to suppress this contamination. The first kind of filter used by AERA was the Median one, based on the Fast Fourier Transform (FFT) technique. The second one, which is currently in use, is the infinite impulse response (IIR) notch filter. The proposed new filter is a finite impulse response (FIR) filter based on a linear prediction (LP). A periodic contamination hidden in a registered signal (digitized in the ADC) can be extracted and next subtracted to make signal cleaner. The FIR filter requires a calculation of n=32, 64 or even 128 coefficients (dependent on a required speed or accuracy) by solving of n linear equations with coefficients built from the covariance Toeplitz matrix. This matrix can be solved by the Levinson recursion, which is much faster than the Gauss procedure. The filter has been already tested in the real AERA radio stations on Argentinean pampas with a very successful results. The linear equations were solved either in the virtual soft-core NIOSR processor (implemented in the FPGA chip as a net of logic elements) or in the external Voipac PXA270M ARM processor. The NIOS processor is relatively slow (50 MHz internal clock), calculations performed in an external processor consume a significant amount of time for data exchange between the FPGA and the processor. Test showed a very good efficiency of the RFI suppression for stationary (long-term) contaminations. However, we observed a short-time contaminations, which could not be suppressed either by the IIR-notch filter or by the FIR filter based on the linear predictions. For the LP FIR filter the refreshment time of the filter coefficients was to long and filter did not keep up with the changes of a contamination structure, mainly due to a long calculation time in a slow processors. We propose to use the Cyclone V SE chip with embedded micro-controller operating with 925 MHz internal clock to significantly reduce a refreshment time of the FIR coefficients. The lab results are promising. (authors)
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Microstructural and infiltration properties of woven preforms during chemical vapor infiltration
Interface-resolved direct numerical simulations (DNSs) of chemical vapor infiltration (CVI) have been performed over a range of furnace-operating conditions (Thiele moduli) and for practical woven preform geometries. A level-set method is used to resolve the geometry of the initial preform at tow scale. The interface between the vapor and solid phase is then evolved in time through the entire CVI densification cycle, fully resolving the time-varying topology between the two phases. In contrast to previous level-set methods for CVI simulation, the physical reaction and diffusion processes govern the level-set movement in the current approach. The surface deposition kinetics is described by the usual one-step model. In this paper, the DNS data are used to study the evolving porosity, surface-to-volume ratio, and flow infiltration properties (permeability and effective diffusivities). Additionally, comparisons are made to popularly-assumed structure functions and the standard, Kozeny–Carmen porous media model commonly employed in modeled CFD simulations of CVI. The virtual DNS experiments reveal a Thiele modulus and preform geometry (fabric layup) dependence which the existing microstructural and infiltration models are not able to describe throughout the entire densification process. The DNS-based, woven geometry-specific correlations can be applied directly to mean-field, furnace-scale CFD simulations.
36 MATERIALS SCIENCE↗
TH-CD-202-04: Evaluation of Virtual Non-Contrast Images From a Novel Split-Filter Dual-Energy CT Technique
Purpose: To compare the ability of two dual-energy CT techniques, a novel split-filter single-source technique of superior temporal resolution against an established sequential-scan technique, to remove iodine contrast from images with minimal impact on CT number accuracy. Methods: A phantom containing 8 tissue substitute materials and vials of varying iodine concentrations (1.7–20.1 mg I /mL) was imaged using a Siemens Edge CT scanner. Dual-energy virtual non-contrast (VNC) images were generated using the novel split-filter technique, in which a 120kVp spectrum is filtered by tin and gold to create high- and low-energy spectra with < 1 second temporal separation between the acquisition of low- and high-energy data. Additionally, VNC images were generated with the sequential-scan technique (80 and 140kVp) for comparison. CT number accuracy was evaluated for all materials at 15, 25, and 35mGy CTDIvol. Results: The spectral separation was greater for the sequential-scan technique than the split-filter technique with dual-energy ratios of 2.18 and 1.26, respectively. Both techniques successfully removed iodine contrast, resulting in mean CT numbers within 60HU of 0HU (split-filter) and 40HU of 0HU (sequential-scan) for all iodine concentrations. Additionally, for iodine vials of varying diameter (2–20 mm) with the same concentration (9.9 mg I /mL), the system accurately detected iodine for all sizes investigated. Both dual-energy techniques resulted in reduced CT numbers for bone materials (by >400HU for the densest bone). Increasing the imaging dose did not improve the CT number accuracy for bone in VNC images. Conclusion: VNC images from the split-filter technique successfully removed iodine contrast. These results demonstrate a potential for improving dose calculation accuracy and reducing patient imaging dose, while achieving superior temporal resolution in comparison sequential scans. For both techniques, inaccuracies in CT numbers for bone materials necessitate consideration for radiation therapy treatment planning.
60 APPLIED LIFE SCIENCES↗
Development of a high-fidelity multi-cycle model of the NuScale small modular reactor using VERA
With growing renewables penetration, there is increased interest in flexible power operation for nuclear reactors. For multi-unit SMRs, in particular the NuScale SMR, which is an integral pressurized water reactor, there are opportunities to optimize flexible power operation across multiple units to limit the degradation of structural and control components. Here, we focus on degradation of in-core components, specifically the control rods and reactor pressure vessel. To perform these studies a high-fidelity, multi-cycle representation of the NuScale SMR is required, with a detailed representation of the structural and control components. To this end, the NuScale SMR has been modelled using the Virtual Environment for Reactor Applications (VERA) software. The entire transition to equilibrium is simulated, from Cycle 1 through to the equilibrium cycle. The equilibrium cycle model shows a good agreement with the NuScale design certification application (DCA) results, with differences attributable to a combination of using public domain data for the present study, and methodological differences. K-effective, power distributions, reactivity coefficients, and boron letdown curves are compared and all found to closely match. This shows that the VERA model is suitable for further studies. (authors)
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Advanced Data Science Model for Detecting Intelligent Malware
This study focused on developing a robust artificial intelligence (AI) model capable of detecting and characterizing advanced malware in Internet of Things (IoT) devices using network data. By analyzing network traffic with various machine learning (ML) models, our AI model can identify and characterize malicious activities to significantly improve malware detection accuracy and reliability as compared to traditional methods. The developed AI/ML model was trained using network data from IoT devices, leveraging classifiers such as Random Forest, Gradient Boosting, AdaBoost, and others to optimize detection performance. This project demonstrates a scalable framework for real-time malware detection and characterization in IoT networks, capable of identifying infected devices and facilitating the necessary steps to remove or isolate them, thereby preventing further infections. Although digital twin (DT) integration is not yet implemented in the current model, it represents a promising future enhancement. By creating a virtual replica of physical IoT devices, DT technology would allow for real-time monitoring and analysis without directly accessing operational technology, thus reducing the risk of compromising or reducing the performance of actual devices. This integration would further enhance the security of IoT ecosystems, combining AI technology to better flag and detect indications of malware-infected devices within a nuclear system environment.
42 ENGINEERING↗
Longitudinal short-distance constraints for the hadronic light-by-light contribution to (g - 2) μ with large-N c Regge models
While the low-energy part of the hadronic light-by-light (HLbL) tensor can be constrained from data using dispersion relations, for a full evaluation of its contribution to the anomalous magnetic moment of the muon (g – 2) μ also mixed- and high-energy regions need to be estimated. Both can be addressed within the operator product expansion (OPE), either for configurations where all photon virtualities become large or one of them remains finite. Imposing such short-distance constraints (SDCs) on the HLbL tensor is thus a major aspect of a model-independent approach towards HLbL scattering. Here, we focus on longitudinal SDCs, which concern the amplitudes containing the pseudoscalar-pole contributions from π o , η, η'. Since these conditions cannot be fulfilled by a finite number of pseudoscalar poles, we consider a tower of excited pseudoscalars, constraining their masses and transition form factors from Regge theory, the OPE, and phenomenology. Implementing a matching of the resulting expressions for the HLbL tensor onto the perturbative QCD quark loop, we are able to further constrain our calculation and significantly reduce its model dependence. We find that especially for the π0 the corresponding increase of the HLbL contribution is much smaller than previous prescriptions in the literature would imply. Overall, we estimate that longitudinal SDCs increase the HLbL contribution by Δa$^{LSDC}_{μ}$ = 13(6) × 10 -11 . This number does not include the contribution from the charm quark, for which we find a$^{c–quark}_{μ}$ = 3(1) × 10 –11 .
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Rapid response sensor for analyzing Special Nuclear Material
Rapid in-situ analytical techniques are attractive for characterizing Special Nuclear Material (SNM). Present techniques are time consuming, and require sample dissolution. Proof-of-principal studies are performed to demonstrate the utility of employing low energy neutrons from a portable pulsed neutron generator for non-destructive isotopic analysis of nuclear material. In particular, time-sequenced data acquisition, operating synchronously with the pulsing of a neutron generator, partitions the characteristic elemental prompt gamma-rays according to the type of the reaction; inelastic neutron scattering reactions during the ON state and thermal neutron capture reactions during the OFF state of the generator. Thus, the key challenge is isolating these signature gamma- rays from the prompt fission and β-delayed gamma-rays that are also produced during the neutron interrogation. A commercial digital multi-channel analyzer has been specially customized to enable time-resolved gamma-ray spectral data to be acquired in multiple user-defined time bins within each of the ON/OFF gate periods of the neutron generator. Preliminary results on new signatures from depleted uranium as well as modeling and benchmarking of the concept are presented, however this approach should should be applicable for virtually all forms of SNM.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Development of a new virtual diagnostic for V3FIT
The determination of plasma equilibria from diagnostic information is a fundamental issue. V3FIT is a fully three-dimensional reconstruction code capable of solving the inverse problem using both magnetic and kinetic measurements. It uses VMEC as core equilibrium solver and supports both free- and fixed-boundary reconstruction approaches. In fixed-boundary mode VMEC does not use explicit information about currents in external coils, even though it has important effects on the shape of the safety factor profile. Indeed, the edge safety factor influences the reversal position in RFP plasmas, which then determines the position of the m = 0 island chain and the edge transport properties. In order to exploit such information a new virtual diagnostic has been developed, that thanks to Ampère's law relates the external current through the center of the torus to the circulation of the toroidal magnetic field on the outermost flux surface. The reconstructions that exploit the new diagnostic are indeed found to better interpret the experimental data with respect to edge physics.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
VERA and VERA-EDU 3.5 Release Notes
The Virtual Environment for Reactor Applications components included in this distribution include selected computational tools and supporting infrastructure that solve neutronics, thermal-hydraulics, fuel performance, and coupled neutronics-thermal hydraulics problems. The infrastructure components provide a simplified common user input capability and provide for the physics integration with data transfer and coupled-physics iterative solution algorithms. Neutronics analysis can be performed for 2D lattices, 2D core and 3D core problems for pressurized water reactor geometries that can be used to calculate criticality and fission rate distributions by pin for input fuel compositions. MPACT uses the Method of Characteristics transport approach for 2D problems. For 3D problems, MPACT uses the 2D/1D method which uses 2D MOC in a radial plane and diffusion or SPn in the axial direction. MPACT includes integrated cross section capabilities that provide problem-specific cross sections generated using the subgroup methodology. The code can be executed both 2D and 3D problems in parallel to reduce overall run time. A thermal-hydraulics capability is provided with CTF (an updated version of COBRA-TF) that allows thermal-hydraulics analyses for single and multiple assemblies using the simplified VERA common input. This distribution also includes coupled neutronics/thermal-hydraulics capabilities to allow calculations using MPACT coupled with CTF. The VERA fuel rod performance component BISON calculates, on a 2D or 3D basis, fuel rod temperature, fuel rod internal pressure, free gas volume, clad integrity and fuel rod waterside diameter. These capabilities allow simulation of power cycling, fuel conditioning and deconditioning, high burnup performance, power uprate scoping studies, and accident performance. Input/Output capabilities include the VERA Common Input (VERAIn) script which converts the ASCII common input file to the intermediate XML used to drive all of the physics codes in the VERA Core Simulator (VERA-CS). VERA component codes either input the VERA XML format directly, or provide a preprocessor which can convert the XML into native input. VERAView is an interactive graphical interface for the visualization and engineering analyses of output data from VERA. The python-based software is easy to install and intuitive to use, and provides instantaneous 2D and 3D images, 1D plots, and alpha-numeric data from VERA multi-physics simulations. Testing within CASL has focused primarily on Westinghouse four-loop reactor geometries and conditions with example problems included in the distribution.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
VERA 3.6 Release Notes
The Virtual Environment for Reactor Applications components included in this distribution include selected computational tools and supporting infrastructure that solve neutronics, thermal-hydraulics, fuel performance, and coupled neutronics-thermal hydraulics problems. The infrastructure components provide a simplified common user input capability and provide for the physics integration with data transfer and coupled-physics iterative solution algorithms.
97 MATHEMATICS AND COMPUTING↗
CSRI Summer Proceedings 2020
The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researchers to learn about problems in computer and computational science at DOE laboratories. Participants conduct leading-edge research, interact with scientists and engineers at the laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, adaptivity and mesh refinement, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, data-intensive computing, environments for scalable computing, parallel input/output, advanced architectures, and theoretical computer science. The CSRI Summer Program is organized by CSRI and typically includes the organization of a weekly seminar series and the publication of a summer proceedings. In 2020, the CSRI summer program was executed completely virtually; all student interns worked from home, due to the COVID-19 pandemic.
97 MATHEMATICS AND COMPUTING↗
Neutron and photon in-vivo materials characterization at the evolving plasma-material interface in plasma-burning fusion environments
This report includes the first set of MOSS data collected in the context of fusion-relevant plasma-material interactions. The data collected show that the surface curvature and stress irreversibly change during low-energy deuterium ion irradiation. This holds for both tungsten thin films, bulk tungsten, and single-crystal silicon. Meanwhile, argon irradiation did not produce this same effect. The surface morphology of the exposed samples was virtually identical regardless of gas species. There were, however, some surface chemistry differences between argon-exposed and deuterium-exposed samples, mainly concerning the oxide states of the W4f XPS signal. The changes in surface chemistry could be due to hydrogen dynamics on the tungsten surfaces, though further investigation will be required with in-situ irradiation and analysis. The changes in surface stress could also not be explained by temperature alone, as the temperature reached during the ion irradiations was too low to induce non-elastic strain. With this in mind, deuterium retention in the materials could change the surface curvature and stress. To confirm this, further work will be needed to quantify the change in curvature and relate it to ion flux, fluence, and deuterium retention. Unfortunately, when this work was conducted, the experimental setup for thermal desorption spectroscopy was not operating correctly, and that work could not be included in this dissertation. Despite experimental difficulties, this work shows the first results of a promising technique to study deuterium dynamics in tungsten-based reconstituted thin films.
36 MATERIALS SCIENCE↗
Renewable and Energy Efficiency Technologies Overview
Renewable energy and energy efficiency technologies are growing rapidly and, with increased penetration, are increasingly impacting how the electricity grid operates. This presentation outlines a number of the technologies and describes the research, development, and deployment the National Renewable Energy Laboratory is partaking on them. It also provides data on the growth of renewable electricity generation technologies over the last decade and how their increasing generation impacts grid operations. It is intended for an audience familiar with energy technologies but who are not experts in either renewable energy or the electricity grid such as attendees at the virtual course nuclear-renewable integrated systems.
ENERGY PLANNING, POLICY, AND ECONOMY↗
Modeling Dynamic Fracture of Cryogenic Pellets
This work is part of an investigation with the long-range objective of predicting the size distribution function and velocity dispersion of shattered pellet fragments after a large cryogenic pellet impacts a solid surface at high velocity. The study is vitally important for the shattered pellet injection (SPI) technique, one of the leading technologies being implemented at ORNL for the mitigation of disruption damage on current tokamaks and ITER. The report contains three parts that are somewhat interwoven. In Part I we formulated a self-similar model for the expansion dynamics and velocity dispersion of the debris cloud following pellet impact against a thick (rigid) target plate. Also presented in Part I is an analytical fracture model that predicts the nominal or mean size of the fragments in the debris cloud and agrees well with known SPI data. The aim of Part II is to gain an understanding of the pellet fracturing process when a pellet is shattered inside a miter tube with a sharp bend. Because miter tubes have a thin stainless steel (SS) wall a permanent deformation (dishing) of the wall is produced at the site of the impact. A review of the literature indicates that most projectile impact on thin plates are those for which the target is deformed and the projectile is perfectly rigid. Such impacts result in “projectile embedding” where the projectile speed is reduced to zero during the interaction so that all the kinetic energy (KE) of the projectile goes into the energy stored in plastic deformation. Much of the literature deals with perforation of the target. The problem here is quite different; the softer pellet easily undergoes complete material failure causing only a small transfer of KE to stored energy of wall deformation. For the real miter tube, we derived a strain energy function for the wall deflection using a non-linear (plastic) stress-strain relation for 304 SS. Using a dishing profile identical to the linear Kirchkoff-Love profile (for lack of a rigorously derived profile) we derived the strain energy associated with the deflection and applied a virtual work principle to find a relationship between the impact (load) pressure to the measured wall deflection depth. The inferred impact pressure was in good agreement with the expected pressure for oblique cryogenic pellet impacts where the pellet shear stress causing cleavage fracture is well above the yield stress for pure shear. The section is concluded with additional discussion on how this wall deformation data lends further support to the analytical fracture model presented in Part I. In Part III we present three different size distribution models. A summary, with a few brief suggestions for a follow on study, is provided at the end of this report.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Model Inputs, Outputs, and Scripts associated with: “Combined effects of stream hydrology and land use on basin-scale hyporheic zone denitrification in the Columbia River Basin”
This data package is associated with the publication “Combined effects of stream hydrology and land use on basin‐scale hyporheic zone denitrification in the Columbia River Basin”, published in Water Resource Research (Son et al.2022) available at https://doi.org/10.1029/2021WR031131. This data package includes the key model inputs/outputs of the river corridor model for the Columbia River Basin (CRB) and the model source codes used in the manuscript. The model is a carbon-nitrogen-coupled river corridor model (RCM), and the model is used to quantify hyporheic zone (HZ) denitrification at the NHDPLUS stream reach scales. The RCM used in this study combines empirical substrate models derived from observations and three microbially driven reactions, including two-step denitrification and aerobic respiration, are considered within the HZ. The key input data of the model are exchange flux, residence time, and stream solute (dissolved organic carbon (DOC), dissolved oxygen (DO), and nitrate concentrations). These inputs are constant over time and represent long-term averaged values. This study uses the RCM to explore the spatial patterns of HZ denitrification across reaches with different sizes and land use in the CRB. Our main objective is to use the RCM as a virtual reality model, and the machine-learning models as surrogates that encapsulate the complexities of the physics-based model while identifying the importance of different variables that are not evident in the model conceptualization. We do not include a direct comparison of the modeled HZ denitrification and measurements; however, the RCM can capture the overall spatial patterns of the HZ denitrification because the model inputs and its reaction networks are based on well-established theory and a physical-based model. The combination of the model-based predictions and a machine-learning approach (e.g., random forest) is used to improve our understanding of what variables of the model are associated with spatial patterns of the modeled denitrification across reaches with different sizes and land uses, and to develop a proxy model using measurable variables to reproduce the simulated patterns.This dataset contains five folders: (1) model_inputs, (2) model_outputs, (3) Rscripts, (4) figures, and (5) model_codes. It also contains a readme, file level metadata (FLMD), and data dictionary (dd). Please see the FLMD for a list of all the files contained in this data package and descriptions for each. The model_inputs folder contains the model inputs used to drive the model simulations. The model_outputs folder contains key model output files from the river corridor model. The Rscripts folder contains the Rscripts for pre- and post- processing model results. The figures folder contains the raw figures associated with the manuscript. The model_codes folder includes key model source codes/input files. All files are .jpg, .jpeg, .out, .e, .od, .dat, .sub, .F90, .0, .R, .sbx, .cpg, .sbn, .shx, .shp, .dbf, .prj, .tfw, .tif, .xml, .pdf, or .csv.
54 ENVIRONMENTAL SCIENCES↗
Assessing state-of-the-art capabilities for probing the atmospheric boundary layer: The XPIA field campaign
To assess current capabilities for measuring flow within the atmospheric boundary layer, including within wind farms, the U.S. Dept. of Energy sponsored the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign at the Boulder Atmospheric Observatory (BAO) in spring 2015. Herein, we summarize the XPIA field experiment, highlight novel measurement approaches, and quantify uncertainties associated with these measurement methods. Line-of-sight velocities measured by scanning lidars and radars exhibit close agreement with tower measurements, despite differences in measurement volumes. Virtual towers of wind measurements, from multiple lidars or radars, also agree well with tower and profiling lidar measurements. Estimates of winds over volumes from scanning lidars and radars are in close agreement, enabling assessment of spatial variability. Strengths of the radar systems used here include high scan rates, large domain coverage, and availability during most precipitation events, but they struggle at times to provide data during periods with limited atmospheric scatterers. In contrast, for the deployment geometry tested here, the lidars have slower scan rates and less range, but provide more data during non-precipitating atmospheric conditions. Microwave radiometers provide temperature profiles with approximately the same uncertainty as Radio-Acoustic Sounding Systems (RASS). Using a motion platform, we assess motion-compensation algorithms for lidars to be mounted on offshore platforms. As a result, we highlight cases for validation of mesoscale or large-eddy simulations, providing information on accessing the archived dataset. We conclude that modern remote sensing systems provide a generational improvement in observational capabilities, enabling resolution of fine-scale processes critical to understanding inhomogeneous boundary-layer flows.
17 WIND ENERGY↗
Evaluation of dose recalculation vs dose deformation in a commercial platform for deformable image registration with a computational phantom
Deformable image registration (DIR) is an important tool for mapping both dose and contours of a new set of planning images when recurrent, that is, adaptive radiotherapy, or further treatment, that is, re-treatment, is required. The aim of this study was to evaluate the need for plan recalculation in deformed anatomies and to develop a reliable workflow for validating the DIR algorithm to be applied to dose warping such as dose accumulation (DA) for adaptive radiation therapy, and dose summation (DS) in the case of re-treatment. A set of 3 computational phantoms was developed to validate the application of B-Spline-based registrations for dose mapping among the various computed tomography image data sets. Two different versions were defined for each phantom to simulate clinical needs: adaptive radiotherapy and re-treatment; a DIR was performed to obtain a displacement vector field (DVF) for dose applications. Comparison of calculated and deformed doses was carried out by means of known markers inside the virtual phantoms. The differences were evaluated using a 3% dose index as acceptance criteria. A paired Wilcoxon signed-rank test was carried out to test the statistical significance of differences within the markers. Significant differences were only observed for the deformed dose in the DA test; no significant differences were observed for recalculated dose values in the DA and DS tests. The dose index is in accordance with these results. The warping dose process obtained by registering various sets of images was validated; a recalculation approach seems to be more accurate for DA purposes and image-guided adaptive radiation therapy (IGART) applications.
62 RADIOLOGY AND NUCLEAR MEDICINE↗