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SU-D-12A-07: Optimization of a Moving Blocker System for Cone-Beam Computed Tomography Scatter Correction

Purpose: A moving blocker based strategy has shown promising results for scatter correction in cone-beam computed tomography (CBCT). Different parameters of the system design affect its performance in scatter estimation and image reconstruction accuracy. The goal of this work is to optimize the geometric design of the moving block system. Methods: In the moving blocker system, a blocker consisting of lead strips is inserted between the x-ray source and imaging object and moving back and forth along rotation axis during CBCT acquisition. CT image of an anthropomorphic pelvic phantom was used in the simulation study. Scatter signal was simulated by Monte Carlo calculation with various combinations of the lead strip width and the gap between neighboring lead strips, ranging from 4 mm to 80 mm (projected at the detector plane). Scatter signal in the unblocked region was estimated by cubic B-spline interpolation from the blocked region. Scatter estimation accuracy was quantified as relative root mean squared error by comparing the interpolated scatter to the Monte Carlo simulated scatter. CBCT was reconstructed by total variation minimization from the unblocked region, under various combinations of the lead strip width and gap. Reconstruction accuracy in each condition is quantified by CT number error as comparing to a CBCT reconstructed from unblocked full projection data. Results: Scatter estimation error varied from 0.5% to 2.6% as the lead strip width and the gap varied from 4mm to 80mm. CT number error in the reconstructed CBCT images varied from 12 to 44. Highest reconstruction accuracy is achieved when the blocker lead strip width is 8 mm and the gap is 48 mm. Conclusions: Accurate scatter estimation can be achieved in large range of combinations of lead strip width and gap. However, image reconstruction accuracy is greatly affected by the geometry design of the blocker.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Meta-Level Design Guidance and Operator Performance Measures for Hybrid Control Rooms

The purpose of this grant was to refine and test methods to evaluate digital human system interfaces (HSI) for existing largely analog nuclear power plant (NPP) control rooms (CRs). We hypothesized that CR operator performance (CROP) in hybrid NPP CRs will be improved if future digital HSI is designed based on: 1) more robust design guidelines for operator situation awareness (SA) and decision-making (DM); 2) enhanced CROP metrics during HSI evaluation; 3) an ontology for selecting simulation scenarios to evaluate digital HSI; and 4) a model to predict optimal HSI design attributes given CROP objectives. The team conducted numerous nuclear power plant site visits (e.g., to Brown’s Ferry, Palo Verde, Sequoyah and Vogtle) to study control room operations and crisis management and 3 visits to the NRC Chattanooga Training Center. We observed research studies at DC Cook and NRC Chattanooga in collaboration with the Halden Reactor Project. We collected operator performance and workload data in one NPP simulator. A comprehensive human (i.e., CROP) performance literature review was published in Applied Ergonomics. We obtained operator team performance data from CAER to produce our data fusion model and a paper delineating the results have been accepted (revision submitted) in Resilience Engineering and System Safety. We analyzed interview data related to scenario ontology development; a manuscript is still in preparation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Impact of extraneous mispositioned events on motion-corrected brain SPECT images of freely moving animals

Purpose: Single photon emission computed tomography (SPECT) brain imaging of freely moving small animals would allow a wide range of important neurological processes and behaviors to be studied, which are normally inhibited by anesthetic drugs or precluded due to the animal being restrained. While rigid body motion of the head can be tracked and accounted for in the reconstruction, activity in the torso may confound brain measurements, especially since motion of the torso is more complex (i.e., nonrigid) and not well correlated with that of the head. The authors investigated the impact of mispositioned events and attenuation due to the torso on the accuracy of motion corrected brain images of freely moving mice. Methods: Monte Carlo simulations of a realistic voxelized mouse phantom and a dual compartment phantom were performed. Each phantom comprised a target and an extraneous compartment which were able to move independently of each other. Motion correction was performed based on the known motion of the target compartment only. Two SPECT camera geometries were investigated: a rotating single head detector and a stationary full ring detector. The effects of motion, detector geometry, and energy of the emitted photons (hence, attenuation) on bias and noise in reconstructed brain regions were evaluated. Results: The authors observed two main sources of bias: (a) motion-related inconsistencies in the projection data and (b) the mismatch between attenuation and emission. Both effects are caused by the assumption that the orientation of the torso is difficult to track and model, and therefore cannot be conveniently corrected for. The motion induced bias in some regions was up to 12% when no attenuation effects were considered, while it reached 40% when also combined with attenuation related inconsistencies. The detector geometry (i.e., rotating vs full ring) has a big impact on the accuracy of the reconstructed images, with the full ring detector being more advantageous. Conclusions: Motion-induced inconsistencies in the projection data and attenuation/emission mismatch are the two main causes of bias in reconstructed brain images when there is complex motion. It appears that these two factors have a synergistic effect on the qualitative and quantitative accuracy of the reconstructed images.

60 APPLIED LIFE SCIENCES↗

Mass Spectral Library Quality Assurance by Inter-Library Comparison

A method to discover and correct errors in mass spectral libraries is described. Comparing across a set of highly curated reference libraries compounds that have the same chemical structure quickly identifies entries that are outliers. In cases where three or more entries for the same compound are compared, the outlier as determined by visual inspection was almost always found to contain the error. These errors were either in the spectrum itself or in the chemical descriptors that accompanied it. The method is demonstrated on finding errors in compounds of forensic interest in the NIST/EPA/NIH Mass Spectral Library. The target list of compounds checked was the Scientific Working Group for the Analysis of Seized Drugs (SWGDRUG) mass spectral library. Some examples of errors found are described. A checklist of errors that curators should look for when performing inter-library comparisons is provided. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Development of a BISON validation case for the TRISO transient irradiations in NSRR using effective heat capacity methods

The current tristructural isotropic (TRISO) fuel assessment and validation database in BISON primarily covers steady- state irradiation and high-temperature furnace testing. Transient assessment cases are potentially needed to support U.S. industry efforts in designing and deploying commercial reactors using TRISO fuels. Historical transient tests in- volving TRISO fuels used highly conservative conditions compared to the typical high-temperature gas-cooled reactor accident scenarios. Despite this, modeling historical transient tests is fundamental for evaluating BISON’s predictive capabilities, adapting material properties for high-temperature and high-particle-power regimes, and developing a sys- tematic validation approach for TRISO transient applications. This work developed a 1D model of transient experiments carried out at the Nuclear Safety Research Reactor using BISON. BISON’s predictions of energy deposition, UO 2 melting onset, and molten volume fractions are compared against experimental measurements. Melting was modeled using an effective specific heat capacity model for UO 2 . We found that BISON’s predictions are in reasonable agreement with experimental data for low-energy-deposition cases, and that BISON overpredicts melting at higher energy depositions. We also discuss the potential causes of discrepancies between the simulated and measured results and propose ways to further develop the model. Although these simulations used conservative conditions compared to those expected for actual TRISO-fueled reactors, they extended the range of conditions reflected in the data in the existing BISON database for TRISO fuels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

SU-E-T-318: Dosimetric Evaluation of ArcCHECK and 3DVH System Using Customized Polymer Gel Dosimeter

Purpose: ArcCHECK and 3DVH system (Sun Nuclear) can reconstruct the three-dimensional (3D) dose distribution and provide the DVH analysis in a patient. The aim of this study was to evaluate dosimetric accuracy of this system using customized polymer gel dosimeter, and also Gafchromic EBT3 films. Methods: Polyacrylamide-based gel contained magnesium chloride as a sensitizer (iPAGAT) was used in this study. Volumetric-modulated arc therapy (VMAT) plan was performed for the C-shape structure by the Eclipse treatment planning system (Varian) and used to irradiate the ArcCHECK by the Novalis Tx linear accelerator (Varian/BrainLAB). The cubic phantom filled with iPAGAT and EBT3 films placed in three orthogonal planes (axial, sagittal, and coronal) inserted into the I’mRT Phantom (IBA Dosimetry) simulated a patient were irradiated with the same VMAT plan. The measurement-guided 3D dose distribution was reconstructed using 3DVH software from the measured data of the ArcCHECK. The 3D dose distribution in iPAGAT was read out by Signa 1.5 T MRI system (GE), and 2D dose distribution on EBT3 was read out by color scanner (Epson). The comparison of all the dose distributions was performed with dose profiles and gamma index analysis in orthogonal planes using in-house developed software. Results: A good agreement was observed by overlaying the dose profiles of 3DVH, EBT3, and iPAGAT. The mean pass rates by gamma index analysis with 3%/3 mm criteria in orthogonal planes were 94.3% (3DVH vs EBT3), 91.1% (3DVH vs iPAGAT), and 96.4% (iPAGAT vs EBT3), respectively. Conclusion: 3D dose distribution reconstructed by ArcCHECK and 3DVH system was estimated accurately in a patient. However, slightly differences were observed between 3DVH and iPAGAT because of MRI noise, therefore further study is required to improve the accuracy of MRI based polymer gel dosimetry for the DVH analysis.

60 APPLIED LIFE SCIENCES↗

Facilitating guest transport in clathrate hydrates by tuning guest-host interactions

The understanding and eventual control of guest molecule transport in gas hydrates is of central importance for the efficient synthesis and processing of these materials for applications in the storage, separation, and sequestration of gases and natural gas production. Previously, some links have been established between dynamics of the host water molecules and guest-host hydrogen bonding interactions, but direct observation of transport in the form of cage-to-cage guest diffusion is still lacking. Recent calculations have suggested that pairs of different guest molecules in neighboring cages can affect guest-host hydrogen bonding and, therefore, defect injection and water lattice motions. We have chosen two sets of hydrate guest pairs, tetrahydrofuran (THF)-CO{sub 2} and isobutane-CO{sub 2}, that are predicted to enhance or to diminish guest–host hydrogen bonding interactions as compared to those in pure CO{sub 2} hydrate and we have studied guest dynamics in each using {sup 13}C nuclear magnetic resonance (NMR) methods. In addition, we have obtained the crystal structure of the THF-CO{sub 2} sII hydrate using the combined single crystal X-ray diffraction and {sup 13}C NMR powder pattern data and have performed molecular dynamics-simulation of the CO{sub 2} dynamics. The NMR powder line shape studies confirm the enhanced and delayed dynamics for the THF and isobutane containing hydrates, respectively, as compared to those in the CO{sub 2} hydrate. In addition, from line shape studies and 2D exchange spectroscopy NMR, we observe cage-to-cage exchange of CO{sub 2} molecules in the THF-CO{sub 2} hydrate, but not in the other hydrates studied. We conclude that the relatively rapid intercage guest dynamics are the result of synergistic guest A–host water–guest B interactions, thus allowing tuning of the guest transport properties in the hydrates by choice of the appropriate guest molecules. Our experimental value for inter-cage hopping is slower by a factor of 10{sup 6} than a published calculated value.

2-METHYLPROPANE↗

DE-NE0000724 - Research Performance Final Report - Investigation of Thermal Aging Effects on the Evolution of Microstructure and Mechanical Properties of Cast Duplex Stainless Steels

This report details the research activities carried out under DOE-NEUP award number DE-NE0000724 concerning the evolution of structural and mechanical properties during thermal aging of CF–3 and CF–8 cast duplex stainless steels (CDSS). The overall objective of this project was to use state-of-the-art characterization techniques to elucidate trends and phenomena in the mechanical and structural evolution of cast duplex stainless steels (CDSS) during thermal aging. These steels are commonly used as structural materials in commercial light water nuclear power plants, undergoing aging for decades in operation as cooling water pipes, pump casings, valve bodies, etc. During extended exposure to these conditions, CDSS are known to undergo a change in mechanical properties resulting in a loss of ductility, i.e. embrittlement. While it is generally accepted that structural changes within the ferrite phase, such as decomposition into iron (Fe)-rich and chromium (Cr)-rich domains, lead to the bulk embrittlement of the steels, many questions remain as to the mechanisms of embrittlement at multiple length scales. This work is intended to shed insight into the atomic level composition changes, associated kinetic mechanisms, and effects of changing phase structure on micro- and nano-scale deformation that lead to loss of impact toughness and tensile ductility in these steels. In general, this project provides a route to answer some of these major questions using techniques such as 3-dimensional (3-D) atom probe tomography (APT) and real-microstructure finite element method (FEM) modeling, which were not readily available when these steels were originally selected for service in light water reactors. Mechanical properties evaluated by Charpy V-notch impact testing (CVN), tensile testing, and microhardness and nanohardness measurements were obtained for each condition and compared with the initial baseline properties to view trends in deformation behavior during aging. Concurrent analysis of the microstructure and nanostructure by atom probe tomography (APT) and transmission electron microscopy (TEM) provide mechanistic insight into the kinetic and mechanical behavior occurring on the nano-scale. The presence and morphology of the ferrite, austenite, and carbide phases have been characterized, and formation of new phases during aging, including spinodal decomposition products (α- and α'-ferrite) and G-phase, have been observed. The mechanical and structural characterization have been used to create accurate FEM models based on the real micro- and nano-structures of the systems. These models provide new insight into the local deformation behavior of these steels and the effects of each individual phase (including ferrite, austenite, carbides, and spinodal decomposition products) on the evolving bulk mechanical behavior of the system. The project was divided into three major tasks: 1. Initial Microstructure and Mechanical Property Survey and Initiate Heat Treatment; 2. Microstructural Characterization and Mechanical Property Testing During Aging; and 3. Microstructure-based Finite Element Modeling. Each of these tasks was successfully executed, resulting in reliable data and analysis that add to the overall body of work on the CDSS materials. Baseline properties and aging trends in mechanical data confirm prior observations and add new insights into the mechanical behavior of the steels. Structural characterization on multiple length scales provides new information on phase changes occurring during aging and sheds light on the kinetic processes occurring at the atomic scale. Furthermore, a combination of mechanical testing and microstructural characterization techniques was utilized to design FEM models of local deformation behavior of the ferrite and austenite phases, providing valuable new information regarding the effects of each of the microstructural components on the hardening and embrittlement processes. The data and analysis presented in this report and the publication associated with this project (§V) increase the understanding of aging and deformation in CF–3 and CF–8 steels. These results provide valuable information that can be utilized to aid in making informed decisions regarding the ongoing use of these steels in commercial nuclear infrastructure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Predictive Maturity of Multi-Scale Simulation Models for Fuel Performance

The project proposed to provide a Predictive Maturity Framework with its companion metrics that (1) introduce a formalized, quantitative means to communicate information between interested parties, (2) provide scientifically dependable means to claim completion of Validation and Uncertainty Quantification (VU) activities, and (3) guide the decision makers in the allocation of Nuclear Energy’s resources for code development and physical experiments. The project team proposed to develop this framework based on two complimentary criteria: (1) the extent of experimental evidence available for the calibration of simulation models and (2) the sophistication of the physics incorporated in simulation models. The proposed framework is capable of quantifying the interaction between the required number of physical experiments and degree of physics sophistication. The project team has developed this framework and implemented it with a multi-scale model for simulating creep of a core reactor cladding. The multi-scale model is composed of the viscoplastic self-consistent (VPSC) code at the meso-scale, which represents the visco-plastic behavior and changing properties of a highly anisotropic material and a Finite Element (FE) code at the macro-scale to represent the elastic behavior and apply the loading. The framework developed takes advantage of the transparency provided by partitioned analysis, where independent constituent codes are coupled in an iterative manner. This transparency allows model developers to better understand and remedy the source of biases and uncertainties, whether they stem from the constituents or the coupling interface by exploiting separate-effect experiments conducted within the constituent domain and integral-effect experiments conducted within the full-system domain. The project team has implemented this procedure with the multi- scale VPSC-FE model and demonstrated its ability to improve the predictive capability of the model. Within this framework, the project team has focused on optimizing resource allocation for improving numerical models through further code development and experimentation. Related to further code development, we have developed a code prioritization index (CPI) for coupled numerical models. CPI is implemented to effectively improve the predictive capability of the coupled model by increasing the sophistication of constituent codes. In relation to designing new experiments, we investigated the information gained by the addition of each new experiment used for calibration and bias correction of a simulation model. Additionally, the variability of ‘information gain’ through the design domain has been investigated in order to identify the experiment settings where maximum information gain occurs and thus guide the experimenters in the selection of the experiment settings. This idea was extended to evaluate the information gain from each experiment can be improved by intelligently selecting the experiments, leading to the development of the Batch Sequential Design (BSD) technique. Additionally, we evaluated the importance of sufficiently exploring the domain of applicability in experiment-based validation of high-consequence modeling and simulation by developing a new metric to quantify coverage. This metric has also been incorporated into the design of new experiments. Finally, we have proposed a data-aware calibration approach for the calibration of numerical models. This new method considers the complexity of a numerical model (the number of parameters to be calibrated, parameter uncertainty, and form of the model) and seeks to identify the number of experiments necessary to calibrate the model based on the level of sophistication of the physics. The final component in the project team’s work to improve model calibration and validation methods is the incorporation of robustness to non-probabilistic uncertainty in the input parameters. This is an improvement to model validation and uncertainty quantification stemming beyond the originally proposed scope of the project. We have introduced a new metric for incorporating the concept of robustness into experiment-based validation of numerical models. This project has accounted for the graduation of two Ph.D. students (Kendra Van Buren and Josh Hegenderfer) and two M.S. students (Matthew Egeberg and Parker Shields). One of the doctoral students is now working in the nuclear engineering field and the other one is a post-doctoral fellow at the Los Alamos National Laboratory. Additionally, two more Ph.D. students (Garrison Stevens and Tunc Kulaksiz) who are working towards graduation have been supported by this project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

ARDP Natrium Neutronic Methodology: Argonne Neutronic Assessment of ABR-1000

The Natrium Sodium-cooled Fast Reactor (SFR) concept developed by TerraPower, LLC was selected as one of the advanced reactor designs for demonstration under the Advanced Reactor Demonstration Program Natrium Demo project. In collaboration with TerraPower, the Argonne National Laboratory (ANL) team provide independent reviews of the neutronic methodology being used for the Natrium design. As part of this activity, both the TerraPower and ANL teams agreed to perform independent neutronics analyses of the ABR-1000 reactor problem as a demonstration on the usage of the neutronics methodologies. Comparison of the results from TerraPower and ANL would expose any methodological differences in the modeling approaches. This report describes and presents the Argonne analysis work on the ABR-1000, and will be provided to TerraPower, along with data files, to complete the comparison study. The comparison will cover the methodology to evaluate the reactivity coefficients for a safety analysis, the shutdown margin, and the reconstructed pin power distribution. The methods and models used to calculate the kinetic parameters and the reactivity coefficients (density, Doppler, axial/radial expansion, etc.) are described in detail with recommendations of specific method options and modelling techniques. The control system reactivity worth and the excess reactivity due to temperature defect are calculated for the shutdown margin analysis. The method to evaluate the excess reactivity is discussed in detail. The pin power reconstruction methodology used in SE2ANL, SE2RCT, and DASSH are discussed in this report. The pin power distribution evaluated by different methods are compared and discussed in the report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Flying Cages in Traveling Wave Ion Mobility: Influence of the Instrumental Parameters on the Topology of the Host–Guest Complexes

Supramolecular mass spectrometry has emerged in the last decade as an orthogonal method to access, at the molecular level, the structures of noncovalent complexes extracted from the condensed phase to the rarefied gas phase using electrospray ionization. It is often considered that the soft nature of the ESI source confers to the method the capability to generate structural data comparable to those in the condensed phase. In the present paper, using the ammonium ion/cucurbituril combination as a model system, we investigate using ion mobility and computational chemistry the influence of the instrumental parameters on the topology, i.e., internal versus external association, of gaseous host/guest complex ions. MS and theoretical data are confronted to condensed phase data derived from nuclear magnetic resonance spectroscopy to assess whether the instrumental parameters can play an insidious role when trying to derive condensed phase data from mass spectrometry results. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SU-D-12A-06: A Comprehensive Parameter Analysis for Low Dose Cone-Beam CT Reconstruction

Purpose: There is always a parameter in compressive sensing based iterative reconstruction (IR) methods low dose cone-beam CT (CBCT), which controls the weight of regularization relative to data fidelity. A clear understanding of the relationship between image quality and parameter values is important. The purpose of this study is to investigate this subject based on experimental data and a representative advanced IR algorithm using Tight-frame (TF) regularization. Methods: Three data sets of a Catphan phantom acquired at low, regular and high dose levels are used. For each tests, 90 projections covering a 200-degree scan range are used for reconstruction. Three different regions-of-interest (ROIs) of different contrasts are used to calculate contrast-to-noise ratios (CNR) for contrast evaluation. A single point structure is used to measure modulation transfer function (MTF) for spatial-resolution evaluation. Finally, we analyze CNRs and MTFs to study the relationship between image quality and parameter selections. Results: It was found that: 1) there is no universal optimal parameter. The optimal parameter value depends on specific task and dose level. 2) There is a clear trade-off between CNR and resolution. The parameter for the best CNR is always smaller than that for the best resolution. 3) Optimal parameters are also dose-specific. Data acquired under a high dose protocol require less regularization, yielding smaller optimal parameter values. 4) Comparing with conventional FDK images, TF-based CBCT images are better under a certain optimally selected parameters. The advantages are more obvious for low dose data. Conclusion: We have investigated the relationship between image quality and parameter values in the TF-based IR algorithm. Preliminary results indicate optimal parameters are specific to both the task types and dose levels, providing guidance for selecting parameters in advanced IR algorithms. This work is supported in part by NIH (1R01CA154747-01)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Analysis of Time Dependent Data and PRA

In the past decades, several numerical simulation codes have been employed to simulate accident dynamics (e.g., RELAP5-3D, MELCOR, MAAP). In order to evaluate the impact of uncertainties into accident dynamics, several stochastic methodologies have been coupled with these codes. These stochastic methods range from classical Monte-Carlo and Latin Hypercube sampling to stochastic polynomial methods. Similar approaches have been introduced into the risk and safety community where stochastic methods (such as RAVEN, ADAPT, MCDET, ADS) have been coupled with safety analysis codes in order to evaluate the safety impact of timing and sequencing of events. These approaches are usually called Dynamic PRA or simulation-based PRA methods. These uncertainties and safety methods usually generate a large number of simulation runs (database storage may be on the order of gigabytes or higher). The scope of this paper is to present a broad overview of methods and algorithms that can be used to analyze and extract information from large data sets containing time dependent data. In this context, 'extracting information' means constructing input-output correlations, finding commonalities, and identifying outliers. Some of the algorithms presented here have been developed or are under development within the RAVEN statistical framework. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Nuclear data uncertainty propagation and modeling uncertainty impact evaluation in neutronics core simulation

Uncertainty analysis is a critical requirement in reactor simulation as it is used to quantify the reliability of best-estimate calculation. A comprehensive uncertainty analysis should characterize all sources of uncertainties in a computationally-feasible and scientifically-defendable manner. Here we employ a well-established reduced order modeling (ROM) based uncertainty quantification methodology to propagate uncertainties throughout neutronic calculations. ROM relies on recent advances in randomized data mining techniques applied to large data streams. In our proposed implementation, the nuclear data uncertainties are first propagated from multi-group level through lattice physics calculation to generate few-group parameter uncertainties, described using a vector of mean values and a covariance matrix. Employing an ROM-based compression of the covariance matrix, the few-group uncertainties are then propagated through downstream core simulation in a computationally efficient manner. This straightforward approach, albeit efficient as compared to brute force forward and/or adjoint-based methods, often employs a number of assumptions that have been unquestioned in the literature of neutronic uncertainty analysis. This manuscript argues that these assumptions could introduce another source of uncertainty referred to as modeling uncertainties, whose magnitude needs to be quantified in tandem with nuclear data uncertainties. Thus, our primary goal is to explore the interactions between these two uncertainty sources in order to assess whether modeling uncertainties have an impact on parameter uncertainties. To explore this endeavor, the impact of a number of modeling assumptions on core attributes uncertainties is quantified. The study employs a CANDU reactor model, with Serpent and NEWT as lattice physics solvers and NESTLE-C as core simulator. The modeling assumptions investigated include those related with the uncertainty propagation method employed, e.g., deterministic vs. stochastic, the few-group energy structure employed to represent the cross-sections, the resonance treatment in lattice physics calculation, the reference values for the cross-section, and the number of samples employed to render ROM compression. Results indicate that some of the modeling assumptions could have a non-negligible impact on the core responses propagated uncertainties, highlighting the need for a more comprehensive approach to combine parameter and modeling uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Harmonic analysis for the characterization and correction of geometric distortion in MRI

Purpose: Magnetic resonance imaging (MRI) is gaining widespread use in radiation therapy planning, patient setup verification, and real-time guidance of radiation delivery. Successful implementation of these technologies relies on the development of simple and efficient methods to characterize and monitor the geometric distortions arising due to system imperfections and gradient nonlinearities. To this end, the authors present the theory and validation of a novel harmonic approach to the quantification of system-related distortions in MRI. Methods: The theory of spatial encoding in MRI is applied to demonstrate that the 3D distortion vector field (DVF) is given by the solution of a second-order boundary value problem (BVP). This BVP is comprised of Laplace’s equation and a limited measurement of the distortion on the boundary of a specified region of interest (ROI). An analytical series expansion solving this BVP within a spherical ROI is obtained, and a statistical uncertainty analysis is performed to determine how random errors in the boundary measurements propagate to the ROI interior. This series expansion is then evaluated to obtain volumetric DVF mappings that are compared to reference data obtained on a 3 T full-body scanner. This validation is performed within two spheres of 20 cm diameter (one centered at the scanner origin and the other offset +3 cm along each of the transverse directions). Initially, a high-order mapping requiring measurements at 5810 boundary points is used. Then, after exploring the impact of the boundary sampling density and the effect of series truncation, a reduced-order mapping requiring measurements at 302 boundary points is evaluated. Results: The volumetric DVF mappings obtained from the harmonic analysis are in good agreement with the reference data. Following distortion correction using the high-order mapping, the authors estimate a reduction in the mean distortion magnitude from 0.86 to 0.42 mm and from 0.93 to 0.39 mm within the central and offset ROIs, respectively. In addition, the fraction of points with a distortion magnitude greater than 1 mm is reduced from 35.6% to 2.8% and from 40.4% to 1.5%, respectively. Similarly, following correction using the reduced-order mapping, the mean distortion magnitude reduces to 0.45–0.42 mm within the central and offset ROIs, and the fraction of points with a distortion magnitude greater than 1 mm is reduced to 2.8% and 1.5%, respectively. Conclusions: A novel harmonic approach to the characterization of system-related distortions in MRI is presented. This method permits a complete and accurate mapping of the DVF within a specified ROI using a limited measurement of the distortion on the ROI boundary. This technique eliminates the requirement to exhaustively sample the DVF at a dense 3D array of points, thereby permitting the design of simple, inexpensive phantoms that may incorporate additional modules for auxiliary quality assurance objectives.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Use of Percutaneous Aspiration Thrombectomy vs. Anticoagulation Therapy to Treat Acute Iliofemoral Venous Thrombosis: 1-year Follow-up Results of a Randomised, Clinical Trial

PurposeThe purpose of this study was to compare the efficacy of percutaneous aspiration thrombectomy (PAT) followed by standard anticoagulant therapy, with anticoagulation therapy alone, for the treatment of acute proximal lower extremity deep vein thrombosis.MethodsIn this randomised, prospective study, 42 patients with acute proximal iliofemoral deep vein thrombosis documented via Doppler ultrasound examination, were separated into an interventional treatment group (16 males, 5 females, average age 51 years) and a medical treatment group (13 males, 8 females, average age 59 years). In the interventional group, PAT with large-lumen 9-F diameter catheterisation was applied, after initiation of standard anticoagulant therapy. Balloon angioplasty (n 19) and stent implementation (n: 14) were used to treat patients with residual stenosis (>50 %) after PAT. Prophylactic IVC filters were placed in two patients. The thrombus clearance status of the venous system was evaluated by venography. In both the medical and interventional groups, venous patency rates and clinical symptom scores were evaluated at months 1, 3, and 12 after treatment.ResultsDeep venous systems became totally cleared of thrombi in 12 patients treated with PAT. The venous patency rates in month 12 were 57.1 and 4.76 % in the interventional and medical treatment groups, respectively. A statistically significant improvement was observed in clinical symptom scores of the interventional group (PAT) with or without stenting (4.23 ± 0.51 before treatment; 0.81 ± 0.92 at month 12) compared with the medical treatment group (4.00 ± 0.63 before treatment; 2.43 ± 0.67 at month 12). During follow-up, four patients in the medical treatment and one in the interventional group developed pulmonary embolisms.ConclusionsFor treatment of acute deep vein thrombosis, PAT with or without stenting is superior to anticoagulant therapy alone in terms of both ensuring venous patency and improving clinical symptoms. PAT is a safe, inexpensive, and easily performed method of endovascular treatment with a low rate of major complications. Our present findings and literature data suggest that PAT can be used as first-line treatment in proximal deep vein thrombosis patients, especially when thrombolytic treatment is contraindicated.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

WE-G-18A-04: 3D Dictionary Learning Based Statistical Iterative Reconstruction for Low-Dose Cone Beam CT Imaging

Purpose: To develop a 3D dictionary learning based statistical reconstruction algorithm on graphic processing units (GPU), to improve the quality of low-dose cone beam CT (CBCT) imaging with high efficiency. Methods: A 3D dictionary containing 256 small volumes (atoms) of 3x3x3 voxels was trained from a high quality volume image. During reconstruction, we utilized a Cholesky decomposition based orthogonal matching pursuit algorithm to find a sparse representation on this dictionary basis of each patch in the reconstructed image, in order to regularize the image quality. To accelerate the time-consuming sparse coding in the 3D case, we implemented our algorithm in a parallel fashion by taking advantage of the tremendous computational power of GPU. Evaluations are performed based on a head-neck patient case. FDK reconstruction with full dataset of 364 projections is used as the reference. We compared the proposed 3D dictionary learning based method with a tight frame (TF) based one using a subset data of 121 projections. The image qualities under different resolutions in z-direction, with or without statistical weighting are also studied. Results: Compared to the TF-based CBCT reconstruction, our experiments indicated that 3D dictionary learning based CBCT reconstruction is able to recover finer structures, to remove more streaking artifacts, and is less susceptible to blocky artifacts. It is also observed that statistical reconstruction approach is sensitive to inconsistency between the forward and backward projection operations in parallel computing. Using high a spatial resolution along z direction helps improving the algorithm robustness. Conclusion: 3D dictionary learning based CBCT reconstruction algorithm is able to sense the structural information while suppressing noise, and hence to achieve high quality reconstruction. The GPU realization of the whole algorithm offers a significant efficiency enhancement, making this algorithm more feasible for potential clinical application. A high zresolution is preferred to stabilize statistical iterative reconstruction. This work was supported in part by NIH(1R01CA154747-01), NSFC((No. 61172163), Research Fund for the Doctoral Program of Higher Education of China (No. 20110201110011), China Scholarship Council.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

AN ESTIMATE OF SPENT NUCLEAR FUEL MECHANICAL LOADS IN THE GENERAL 30 CM PACKAGE DROP SCENARIO

The US Department of Energy Spent Fuel and Waste Science and Technology (SFWST) program is performing research to determine the mechanical loading conditions applied to spent nuclear fuel (SNF) during normal conditions of transport to inform mechanical tests of SNF and close an important knowledge gap related to the practical disposition of SNF in the US. Researchers at Pacific Northwest National Laboratory (PNNL) have completed an extensive finite element study to characterize and estimate the potential mechanical loads on SNF during a hypothetical 30 cm drop of an SNF transportation package. This modeling study is validated with test data collected by the SFWST program during a physical test campaign that included one-third scale package drop tests and full-scale single fuel assembly drop tests. The test campaign was led by Sandia National Laboratories (SNL) and included international collaboration with Equipos Nucleares S.A, S.M.E (ENSA) and Bundesanstalt für Materialforschung und -prüfung (BAM). The key contribution of the modeling study is to go beyond the limitations of the limited number of physical tests to estimate the impact response to variations in impact angle, initial gap conditions, fuel assembly design, burnup and other parameters that affect the mechanical loads. The methodology of this study included a classic parametric study to calculate the impact response of highly detailed fuel assemblies over many combinations of parameters. Models of a 17x17 pressurized water reactor fuel assembly and a generic 10x10 boiling water reactor fuel assembly were both used in this study to cover the major fuel assembly types in the US inventory. Over 2,000 impact responses were calculated. The results of the parametric study were evaluated using traditional methods and basic statistics. The results were also used to construct a damage model using multiple nonlinear regression techniques to predict the mechanical loads over the full range of all input parameters. The damage model was found to work very well for all impact angle cases where the cask came to rest on its side. It was concluded that end drop cases where the cask remained vertical (instead of tipping over onto its side) were not sufficiently characterized by the current set of parametric study cases to include in the damage model, but it was not a priority to fully investigate that range because the highest mechanical loads were observed in the broader range of side impact cases. This modeling work provides sufficient insight into the mechanical loads on SNF during a hypothetical 30 cm package drop that, when considered along with the physical test data collected by the SNL-led team, the SFSWT program can consider the knowledge gap closed.

Klymyshyn, Nicholas A.↗