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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Forward variable selection enables fast and accurate dynamic system identification with Karhunen-Loève decomposed Gaussian processes

A promising approach for scalable Gaussian processes (GPs) is the Karhunen-Loève (KL) decomposition, in which the GP kernel is represented by a set of basis functions which are the eigenfunctions of the kernel operator. Such decomposed kernels have the potential to be very fast, and do not depend on the selection of a reduced set of inducing points. However KL decompositions lead to high dimensionality, and variable selection thus becomes paramount. This paper reports a new method of forward variable selection, enabled by the ordered nature of the basis functions in the KL expansion of the Bayesian Smoothing Spline ANOVA kernel (BSS-ANOVA), coupled with fast Gibbs sampling in a fully Bayesian approach. It quickly and effectively limits the number of terms, yielding a method with competitive accuracies, training and inference times for tabular datasets of low feature set dimensionality. Theoretical computational complexities are O ( N P 2 ) in training and O ( P ) per point in inference, where N is the number of instances and P the number of expansion terms. The inference speed and accuracy makes the method especially useful for dynamic systems identification, by modeling the dynamics in the tangent space as a static problem, then integrating the learned dynamics using a high-order scheme. The methods are demonstrated on two dynamic datasets: a ‘Susceptible, Infected, Recovered’ (SIR) toy problem, along with the experimental ‘Cascaded Tanks’ benchmark dataset. Comparisons on the static prediction of time derivatives are made with a random forest (RF), a residual neural network (ResNet), and the Orthogonal Additive Kernel (OAK) inducing points scalable GP, while for the timeseries prediction comparisons are made with LSTM and GRU recurrent neural networks (RNNs) along with the SINDy package.

Hayes, Kyle↗
DOE OSTI2015

M3FT-15OR0202237: Submit Report on Results From Initial Coating Layer Development For UN TRISO Particles

In support of fully ceramic matrix (FCM) fuel development, coating development work has begun at the Oak Ridge National Laboratory (ORNL) to produce tri-isotropic (TRISO) coated fuel particles with UN kernels. The nitride kernels are used to increase heavy metal density in these SiC-matrix fuel pellets with details described elsewhere. The advanced gas reactor (AGR) program at ORNL used fluidized bed chemical vapor deposition (FBCVD) techniques for TRISO coating of UCO (two phase mixture of UO 2 and UC x ) kernels. Similar techniques were employed for coating of the UN kernels, however significant changes in processing conditions were required to maintain acceptable coating properties due to physical property and dimensional differences between the UCO and UN kernels.

Jolly, Brian C.↗
DOE OSTI2016

Safety Testing of AGR-2 UCO Compacts 5-2-2, 2-2-2, and 5-4-1

Post-irradiation examination (PIE) is being performed on tristructural-isotropic (TRISO) coated-particle fuel compacts from the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program second irradiation experiment (AGR-2). This effort builds upon the understanding acquired throughout the AGR-1 PIE campaign, and is establishing a database for the different AGR-2 fuel designs. The AGR-2 irradiation experiment included TRISO fuel particles coated at BWX Technologies (BWXT) with a 150-mm-diameter engineering-scale coater. Two coating batches were tested in the AGR-2 irradiation experiment. Batch 93085 had 508-μm-diameter uranium dioxide (UO 2 ) kernels. Batch 93073 had 427-μm-diameter UCO kernels, which is a kernel design where some of the uranium oxide is converted to uranium carbide during fabrication to provide a getter for oxygen liberated during fission and limit CO production. Fabrication and property data for the AGR-2 coating batches have been compiled and compared to those for AGR-1. The AGR-2 TRISO coatings were most like the AGR-1 Variant 3 TRISO deposited in the 50-mm-diameter ORNL lab-scale coater. In both cases argon-dilution of the hydrogen and methyltrichlorosilane coating gas mixture employed to deposit the SiC was used to produce a finer-grain, more equiaxed SiC microstructure. In addition to the fact that AGR-1 fuel had smaller, 350-μm-diameter UCO kernels, notable differences in the TRISO particle properties included the pyrocarbon anisotropy, which was slightly higher in the particles coated in the engineering-scale coater, and the exposed kernel defect fraction, which was higher for AGR-2 fuel due to the detected presence of particles with impact damage introduced during TRISO particle handling.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Measurement of Average Burnup in TRISO-Coated Particles from AGR-2 UCO Compacts 2-2-2 and 6-4-2

Burnup analysis was performed on tristructural-isotropic (TRISO)-coated particles deconsolidated from compacts irradiated by the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program in the second irradiation experiment (AGR-2) [Collin 2014]. The AGR-2 irradiation experiment included TRISO fuel particles with kernels containing both uranium oxide and uranium carbide, called UCO, where uranium carbide is included with the commonly-used uranium oxide in the kernel to provide a getter for oxygen liberated during fission and limit CO production. This allows the UCO-TRISO particles to be taken to higher burnup without failure from excessive internal CO pressure or CO-corrosion of the SiC layer. The UCO kernels were fabricated and coated at BWX Technologies Nuclear Operations Group (BWXT-NOG) with a 150-mm-diameter engineering-scale coater. The UCO-TRISO batch used in the AGR-2 irradiation experiment was Batch 93073, which had kernels with an average diameter of 426.7 μm and average coating thicknesses moving out from the kernel of 98.9 μm (buffer), 40.4 μm (IPyC), 35.2 μm (SiC), 43.4 μm (OPyC) [Barnes and Marshall 2009]. The TRISO particle were shipped to ORNL to be formed into compacts for irradiation testing. The compact lot qualified for the AGR-2 irradiation test was lot LEU09-OP2-Z and had an average of 3176 UCO-TRISO particles in each compact [Hunn, Montgomery, and Pappano 2010]. Compilations of the properties data for the particles and compacts are available in a pre-irradiation characterization summary report for the AGR-2 fuel composites [Hunn, Savage, and Silva 2010].

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Safety Testing and Destructive Examination of AGR-2 UCO Compact 6-4-3

Post-irradiation examination (PIE) and elevated-temperature safety testing are being performed on tristructural-isotropic (TRISO) coated-particle fuel compacts from the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program’s second irradiation experiment (AGR-2). Details on this irradiation experiment have been previously reported. The AGR-2 PIE effort builds upon the understanding acquired throughout the AGR-1 PIE campaign (Demkowicz et al. 2015) and is establishing a database for the different AGR-2 fuel designs. The AGR-2 irradiation experiment included TRISO fuel particles coated at BWX Technologies (BWXT) with an engineering-scale coater, which had a coating chamber 150 mm in diameter. Two coating batches were tested in the AGR-2 irradiation experiment. Batch G73H-10-93085B had uranium dioxide (UO2) kernels with an average diameter of 508 µm. Batch G83J-14-93073A had UCO kernels with an average diameter of 427 µm; in this kernel design, some of the uranium oxide is converted to uranium carbide during fabrication to provide a getter for oxygen liberated during fission and to limit CO production. Fabrication and property data for the AGR-2 coating batches have been compiled and compared to AGR-1. The AGR-2 TRISO coatings were most like the AGR-1 Variant 3 TRISO deposited in the Oak Ridge National Laboratory (ORNL) laboratory-scale coater, which had a coating chamber 50 mm in diameter (Hunn and Lowden 2006). In both cases, the hydrogen and methyltrichlorosilane coating gas mixture that was used to deposit the SiC was diluted with argon to produce a finer grained, more equiaxed SiC microstructure. In addition to the fact that AGR-1 fuel had smaller UCO kernels that were 350 µm in diameter, other notable differences in the TRISO particle properties included (1) the pyrocarbon anisotropy, which was slightly higher in the particles coated in the engineering-scale coater, and (2) the exposed kernel defect fraction, which was higher for AGR-2 fuel due to the detected presence of particles with impact damage that was introduced during TRISO particle handling.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Safety Testing and Destructive Examination of SGR-2 UCO Compact 2-1-2

Post-irradiation examination (PIE) and elevated-temperature safety testing are being performed on tristructural-isotropic (TRISO) coated-particle fuel compacts from the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program’s second irradiation experiment (AGR-2). Details on this irradiation experiment have been previously reported. The AGR-2 PIE effort builds upon the understanding acquired throughout the AGR-1 PIE campaign and is establishing a database for the different AGR-2 fuel designs. The AGR-2 irradiation experiment included TRISO fuel particles coated at BWX Technologies (BWXT) with an engineering-scale coater, which had a coating chamber 150 mm in diameter. Two coating batches were tested in the AGR-2 irradiation experiment. Batch G73H-10-93085B had uranium dioxide (UO2) kernels with an average diameter of 508 µm. Batch G83J-14-93073A had UCO kernels with an average diameter of 427 µm; in this kernel design, some of the uranium oxide is converted to uranium carbide during fabrication to provide a getter for oxygen liberated during fission and to limit CO production. Fabrication and property data for the AGR-2 coating batches have been compiled and compared to AGR-1. The AGR-2 TRISO coatings were most like the AGR-1 Variant 3 TRISO deposited in the Oak Ridge National Laboratory (ORNL) laboratory-scale coater, which had a coating chamber 50 mm in diameter (Hunn and Lowden 2006). In both cases, the hydrogen and methyltrichlorosilane coating gas mixture that was used to deposit the SiC was diluted with argon to produce a finer grained, more equiaxed SiC microstructure. In addition to the fact that AGR-1 fuel had smaller UCO kernels that were 350 µm in diameter, other notable differences in the TRISO particle properties included (1) the pyrocarbon anisotropy, which was slightly higher in the particles coated in the engineering-scale coater, and (2) the exposed kernel defect fraction, which was higher for AGR-2 fuel due to the detected presence of particles with impact damage that was introduced during TRISO particle handling.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Initial CEED API (CEED-MS10)

Key components of CEED software development involve fast finite element operator storage and evaluation, architecture optimizations, performant algorithms for all orders, global kernels for finite element operators, efficient use of the memory sub-system, optimal data locality and motion, enhanced scalability and parallelism, and fast tensor contractions. As ultimate goals of the project, CEED is exploring and identifying the best algorithms for the full range of discretizations and applying algorithmic and software development to support ECP applications’ needs. In this milestone, we initiated the development and implementation of a common CEED API consisting of two main components: low-level and high-level APIs. We accomplished the goal of having the low-level component ready for the release of CEED v1.0 in the next quarter, see CEED-MS13. In this report we also provide a highlight from CEED’s integration with the MARBL app and the corresponding Laghos miniapp. A main theme in this work has been the systematic transition of advanced algorithms, developed and tested in Laghos, to the large-scale multi-physics settings of the MARBL code. The low-level CEED API provides a set of FE kernels and components for writing new low-level kernels. Examples include: vector and sparse linear algebra, element matrix assembly over a batch of elements, partial assembly and action for efficient high-order operators like mass, diffusion, advection, etc. The main goal of the low-level API is to establish the basis for the high-level API. Also, identifying such low-level kernels and providing a reference implementation for them serves as the basis for collaboration with vendors and STs. Another goal for the low-level API is to make it easy for applications with their own discretization infrastructure, who do not want to switch directly to using the high-level CEED API, to still evaluate and use the core operations provided by the low-level API. One of the challenges with high-order methods is that a global sparse matrix is no longer a good representation of a high-order linear operator, both with respect to the FLOPs needed for its evaluation, as well as the memory transfer needed for a matvec. Thus, another important question we tried to address while developing the low-level API is: is it possible to abstract out in a natural and efficient way the different implementations and data structures that arise when dealing with various computational device types: CPUs, GPUs, etc. Fully answering this question is beyond the scope of this particular milestone, since that requires longer time as we develop and expand the devices we support. The future high-level API will be the frontend provided by CEED consisting of high-level abstractions such as meshes, finite element spaces and solutions, bilinear forms, solvers, etc. At this high-level, an important aspect of the API will be to provide a uniform abstraction layer for writing code in a portable manner. To achieve that, we plan to utilize the MPI programming model combined with a device abstraction layer (DAL) for finite element computations that we will develop. The DAL will serve as the bridge between the low- and the high-level APIs, allowing a variety of programming models to be used for the low-level kernel implementations. The software artifacts delivered as part of this milestone include an initial CEED API software implementation (libCEED) provided through the CEED website, http://ceed.exascaleproject.org and the CEED GitHub organization, http://github.com/ceed. In addition to details and results from the above R&D efforts, in this document we are also reporting on other project-wide activities performed in Q1 of FY18, including: the Nek5000 v17.0 MFEM v3.3.2 and PETSc v3.8 releases, collaborations with ECP/ST and SciDAC projects, the inaugural Nek5000 hackathon and various outreach activities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Towards TDDFT for Strongly Correlated Materials

We present some details of our recently-proposed Time-Dependent Density-Functional Theory (TDDFT) for strongly-correlated materials in which the exchange-correlation (XC) kernel is derived from the charge susceptibility obtained using Dynamical Mean-Field Theory (the TDDFT + DMFT approach). We proceed with deriving the expression for the XC kernel for the one-band Hubbard model by solving DMFT equations via two approaches, the Hirsch–Fye Quantum Monte Carlo (HF-QMC) and an approximate low-cost perturbation theory approach, and demonstrate that the latter gives results that are comparable to the exact HF-QMC solution. Furthermore, through a variety of applications, we propose a simple analytical formula for the XC kernel. Additionally, we use the exact and approximate kernels to examine the nonhomogeneous ultrafast response of two systems: a one-band Hubbard model and a Mott insulator YTiO3. We show that the frequency dependence of the kernel, i.e., memory effects, is important for dynamics at the femtosecond timescale. We also conclude that strong correlations lead to the presence of beats in the time-dependent electric conductivity in YTiO3, a feature that could be tested experimentally and that could help validate the few approximations used in our formulation. We conclude by proposing an algorithm for the generalization of the theory to non-linear response.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

ELECTRON PROBE MICROANALYSIS OF IRRADIATED AND 1600°C SAFETY-TESTED AGR-1 TRISO FUEL PARTICLES WITH LOW AND HIGH RETAINED 110MAG

AGR-1 fuel Compact 4-3-3 achieved 18.63% FIMA and was exposed subsequently to a safety test at 1600°C. Two particles, AGR1-433-003 and AGR1-433-007, with measured-to-calculated 110mAg inventories of <22% and 100%, respectively, were selected for comparative electron microprobe analysis to determine whether the distribution or abundance of fission products differed proximally and distally from the deformed kernel in AGR1-433-003, and how this compared to fission product distribution in AGR1-433-007. On the deformed side of AGR1-433-003, Xe, Cs, I, Eu, Sr, and Te concentrations in the kernel buffer interface near the protruded kernel were up to six times higher than on the opposite, non-deformed side. At the SiC-inner pyrolytic carbon (IPyC) interface proximal to the deformed kernel, Pd and Ag concentrations were 1.2 wt% and 0.04 wt% respectively, whereas on the SiC-IPyC interface distal from the kernel deformation those elements measured 0.4 and 0.01 wt%, respectively. Palladium and Ag concentrations at the SiC-IPyC interface of AGR1-433-007 were 2.05 and 0.05 wt.%, respectively. Rare earth element concentrations at the SiC-IPyC interface of AGR1-433-007 were a factor of ten higher than at the SiC-IPyC interfaces measured in particle AGR1-433-003. Palladium permeated the SiC layer of AGR1-433-007 and the non-deformed SiC layer of AGR1-433-003.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Automated Defect Identification for Tri-structural Isotropic Fuels (AUDIT)

During the manufacture of tri-structural isotropic (TRISO)-coated nuclear fuel particles, the potential exists for the formation of internal fissure defects in the uranium oxycarbide (UCO) kernels. These fissures result in a defective fuel particle that can fracture during subsequent fuel processing. Therefore, it is necessary to detect the presence of fissured kernels in a batch to determine if the batch meets specification prior to blending with other batches and upgrading processes. Previous attempts at identifying fissures involved manual inspection of micrographs of UCO fuel kernel cross-sections. This process is tedious, time-consuming and may introduce counting errors making it a good candidate for automation. This work presents a method for the automated detection of fissures in UCO kernels. Image segmentation is used for the extraction of relevant features in the micrographs which then serve as the input to a convolutional neural network used to automatically distinguish between fissured and non-fissured kernels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Spatially Resolved Thermal Transport Measurements in PyC Coated Fuel Particles

Self-regulating, low-power, compact, nuclear reactors are of immense interest to a community of sponsors who have power needs in space, underwater and in remote areas. Recent exploratory studies have provided valuable understanding into the underlying physics of self-regulation, including, how a material's self-regulation (or reactivity feedback) can be controlled by engineering its micro-scale and mesoscale properties. The approach being explored at Los Alamos National Laboratory involves a core matrix that is constructed of fuel kernels dispersed in a graphite matrix. The timing of the feedback is influenced by thermal properties of the fuel composite, which can be 'tuned' by micro-engineering. A pyrolytic carbon (PyC) layer coats the kernels to ensure that during a reactivity spike, the majority of the heat is trapped within the fuel kernel. The resulting precipitous temperature rise triggers a strong negative Doppler feedback. The ability to measure the local thermal properties of the individual materials that compose the fuel particle are crucial to fully understanding and controlling this feedback mechanism. The work covered in this presentation involves using laser-based thermal wave microscopy to measure the local thermal properties of the fuel particles. Specifically we measure the thermal conductivity and diffusivity of the fuel kernel and the PyC layer as well as the contact resistance between the kernel and the PyC layer. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

Application of activity pencil beam algorithm using measured distribution data of positron emitter nuclei for therapeutic SOBP proton beam

Purpose: Recently, much research on imaging the clinical proton-irradiated volume using positron emitter nuclei based on target nuclear fragment reaction has been carried out. The purpose of this study is to develop an activity pencil beam (APB) algorithm for a simulation system for proton-activated positron-emitting imaging in clinical proton therapy using spread-out Bragg peak (SOBP) beams.Methods: The target nuclei of activity distribution calculations are {sup 12}C nuclei, {sup 16}O nuclei, and {sup 40}Ca nuclei, which are the main elements in a human body. Depth activity distributions with SOBP beam irradiations were obtained from the material information of ridge filter (RF) and depth activity distributions of compounds of the three target nuclei measured by BOLPs-RGp (beam ON-LINE PET system mounted on a rotating gantry port) with mono-energetic Bragg peak (MONO) beam irradiations. The calculated data of depth activity distributions with SOBP beam irradiations were sorted in terms of kind of nucleus, energy of proton beam, SOBP width, and thickness of fine degrader (FD), which were verified. The calculated depth activity distributions with SOBP beam irradiations were compared with the measured ones. APB kernels were made from the calculated depth activity distributions with SOBP beam irradiations to construct a simulation system using the APB algorithm for SOBP beams.Results: The depth activity distributions were prepared using the material information of RF and the measured depth activity distributions with MONO beam irradiations for clinical therapy using SOBP beams. With the SOBP width widening, the distal fall-offs of depth activity distributions and the difference from the depth dose distributions were large. The shapes of the calculated depth activity distributions nearly agreed with those of the measured ones upon comparison between the two. The APB kernels of SOBP beams were prepared by making use of the data on depth activity distributions with SOBP beam irradiations that were made from the depth activity distributions with MONO beam irradiations and sorted in terms of energy, SOBP width, and thickness of FD. The data on APB kernels of SOBP beams were determined as installment data for the simulation system using the APB algorithm for SOBP beam irradiations.Conclusions: A method of obtaining the depth activity distributions and the APB algorithm for clinical use of SOBP beams have been developed. It is suggested that the simulation system for imaging the clinical irradiated volume with the APB algorithm can be used in clinical proton therapy using SOBP beams by preparing and investigating the data on APB kernels of SOBP beams.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Model-based PSF and MTF estimation and validation from skeletal clinical CT images

Purpose: A method was developed to correct for systematic errors in estimating the thickness of thin bones due to image blurring in CT images using bone interfaces to estimate the point-spread-function (PSF). This study validates the accuracy of the PSFs estimated using said method from various clinical CT images featuring cortical bones. Methods: Gaussian PSFs, characterized by a different extent in the z (scan) direction than in the x and y directions were obtained using our method from 11 clinical CT scans of a cadaveric craniofacial skeleton. These PSFs were estimated for multiple combinations of scanning parameters and reconstruction methods. The actual PSF for each scan setting was measured using the slanted-slit technique within the image slice plane and the longitudinal axis. The Gaussian PSF and the corresponding modulation transfer function (MTF) are compared against the actual PSF and MTF for validation. Results: The differences (errors) between the actual and estimated full-width half-max (FWHM) of the PSFs were 0.09 ± 0.05 and 0.14 ± 0.11 mm for the xy and z axes, respectively. The overall errors in the predicted frequencies measured at 75%, 50%, 25%, 10%, and 5% MTF levels were 0.06 ± 0.07 and 0.06 ± 0.04 cycles/mm for the xy and z axes, respectively. The accuracy of the estimates was dependent on whether they were reconstructed with a standard kernel (Toshiba's FC68, mean error of 0.06 ± 0.05 mm, MTF mean error 0.02 ± 0.02 cycles/mm) or a high resolution bone kernel (Toshiba's FC81, PSF FWHM error 0.12 ± 0.03 mm, MTF mean error 0.09 ± 0.08 cycles/mm). Conclusions: The method is accurate in 3D for an image reconstructed using a standard reconstruction kernel, which conforms to the Gaussian PSF assumption but less accurate when using a high resolution bone kernel. The method is a practical and self-contained means of estimating the PSF in clinical CT images featuring cortical bones, without the need phantoms or any prior knowledge about the scanner-specific parameters.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

SU-F-T-428: An Optimization-Based Commissioning Tool for Finite Size Pencil Beam Dose Calculations

Purpose: Finite size pencil beam (FSPB) algorithms are commonly used to pre-calculate the beamlet dose distribution for IMRT treatment planning. FSPB commissioning, which usually requires fine tuning of the FSPB kernel parameters, is crucial to the dose calculation accuracy and hence the plan quality. Yet due to the large number of beamlets, FSPB commissioning could be very tedious. This abstract reports an optimization-based FSPB commissioning tool we have developed in MatLab to facilitate the commissioning. Methods: A FSPB dose kernel generally contains two types of parameters: the profile parameters determining the dose kernel shape, and a 2D scaling factors accounting for the longitudinal and off-axis corrections. The former were fitted using the penumbra of a reference broad beam’s dose profile with Levenberg-Marquardt algorithm. Since the dose distribution of a broad beam is simply a linear superposition of the dose kernel of each beamlet calculated with the fitted profile parameters and scaled using the scaling factors, these factors could be determined by solving an optimization problem which minimizes the discrepancies between the calculated dose of broad beams and the reference dose. Results: We have commissioned a FSPB algorithm for three linac photon beams (6MV, 15MV and 6MVFFF). Dose of four field sizes (6*6cm2, 10*10cm2, 15*15cm2 and 20*20cm2) were calculated and compared with the reference dose exported from Eclipse TPS system. For depth dose curves, the differences are less than 1% of maximum dose after maximum dose depth for most cases. For lateral dose profiles, the differences are less than 2% of central dose at inner-beam regions. The differences of the output factors are within 1% for all the three beams. Conclusion: We have developed an optimization-based commissioning tool for FSPB algorithms to facilitate the commissioning, providing sufficient accuracy of beamlet dose calculation for IMRT optimization.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

MO-FG-CAMPUS-TeP1-05: Rapid and Efficient 3D Dosimetry for End-To-End Patient-Specific QA of Rotational SBRT Deliveries Using a High-Resolution EPID

Purpose: EPID-based patient-specific quality assurance provides verification of the planning setup and delivery process that phantomless QA and log-file based virtual dosimetry methods cannot achieve. We present a method for EPID-based QA utilizing spatially-variant EPID response kernels that allows for direct calculation of the entrance fluence and 3D phantom dose. Methods: An EPID dosimetry system was utilized for 3D dose reconstruction in a cylindrical phantom for the purposes of end-to-end QA. Monte Carlo (MC) methods were used to generate pixel-specific point-spread functions (PSFs) characterizing the spatially non-uniform EPID portal response in the presence of phantom scatter. The spatially-variant PSFs were decomposed into spatially-invariant basis PSFs with the symmetric central-axis kernel as the primary basis kernel and off-axis representing orthogonal perturbations in pixel-space. This compact and accurate characterization enables the use of a modified Richardson-Lucy deconvolution algorithm to directly reconstruct entrance fluence from EPID images without iterative scatter subtraction. High-resolution phantom dose kernels were cogenerated in MC with the PSFs enabling direct recalculation of the resulting phantom dose by rapid forward convolution once the entrance fluence was calculated. A Delta4 QA phantom was used to validate the dose reconstructed in this approach. Results: The spatially-invariant representation of the EPID response accurately reproduced the entrance fluence with >99.5% fidelity with a simultaneous reduction of >60% in computational overhead. 3D dose for 10{sub 6} voxels was reconstructed for the entire phantom geometry. A 3D global gamma analysis demonstrated a >95% pass rate at 3%/3mm. Conclusion: Our approach demonstrates the capabilities of an EPID-based end-to-end QA methodology that is more efficient than traditional EPID dosimetry methods. Displacing the point of measurement external to the QA phantom reduces the necessary complexity of the phantom itself while offering a method that is highly scalable and inherently generalizable to rotational and trajectory based deliveries. This research was partially supported by Varian.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MPACT Subgroup Self-Shielding Efficiency Improvements

Recent developments to improve the efficiency of the MOC solvers in MPACT have yielded effective kernels that loop over several energy groups at once, rather that looping over one group at a time. These kernels have produced roughly a 2x speedup on the MOC sweeping time during eigenvalue calculation. However, the self-shielding subgroup calculation had not been reevaluated to take advantage of these new kernels, which typically requires substantial solve time. The improvements covered in this report start by integrating the multigroup kernel concepts into the subgroup calculation, which are then used as the basis for further extensions. The next improvement that is covered is what is currently being termed as “Lumped Parameter MOC”. Because the subgroup calculation is a purely fixed source problem and multiple sweeps are performed only to update the boundary angular fluxes, the sweep procedure can be condensed to allow for the instantaneous propagation of the flux across a spatial domain, without the need to sweep along all segments in a ray. Once the boundary angular fluxes are considered to be converged, an additional sweep that will tally the scalar flux is completed. The last improvement that is investigated is the possible reduction of the number of azimuthal angles per octant in the shielding sweep. Typically 16 azimuthal angles per octant are used for self-shielding and eigenvalue calculations, but it is possible that the self-shielding sweeps are less sensitive to the number of angles than the full eigenvalue calculation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

ExtremeMETA: High-speed Lightweight Image Segmentation Model by Remodeling Multi-channel Metamaterial Imagers

Deep neural networks (DNNs) have heavily relied on traditional computational units, such as CPUs and GPUs. However, this conventional approach brings significant computational burden, latency issues, and high power consumption, limiting their effectiveness. This has sparked the need for lightweight networks such as ExtremeC3Net. Meanwhile, there have been notable advancements in optical computational units, particularly with metamaterials, offering the exciting prospect of energy-efficient neural networks operating at the speed of light. Yet, the digital design of metamaterial neural networks (MNNs) faces precision, noise, and bandwidth challenges, limiting their application to intuitive tasks and low-resolution images. In this study, we proposed a large kernel lightweight segmentation model, ExtremeMETA. Based on ExtremeC3Net, our proposed model, ExtremeMETA maximized the ability of the first convolution layer by exploring a larger convolution kernel and multiple processing paths. With the large kernel convolution model, we extended the optic neural network application boundary to the segmentation task. To further lighten the computation burden of the digital processing part, a set of model compression methods was applied to improve model efficiency in the inference stage. The experimental results on three publicly available datasets demonstrated that the optimized efficient design improved segmentation performance from 92.45 to 95.97 on mIoU while reducing computational FLOPs from 461.07 MMacs to 166.03 MMacs. The large kernel lightweight model ExtremeMETA showcased the hybrid design’s ability on complex tasks.

large convolution kernel↗
DOE OSTI2016

Neutronic feasibility analysis of fully ceramic microencapsulated fuel for commercial PWRs

The fully ceramic microencapsulated (FCM) fuel is based on tri-structural isotropic (TRISO) coated particles embedded in silicon carbide (SiC) matrix, which is among the accident tolerant fuel concept options. With the strength of high fission product retention, the FCM fuel provides potential superior safety performance. Compared to the conventional standard UO{sub 2} fuel, the deficiency of FCM fuel is its considerable lower fissile inventory, which results in a reduced reactor power or/and life. Supposing the FCM fuel is used as direct replacement of the fuel in commercial PWRs, the spectrum is softened due to the usage of SiC as matrix, and the moderator temperature coefficient is possible to be positive at the beginning of life, leading to high risk during operation. A neutronic feasibility study of FCM fuel utilized in commercial PWRs is performed in the paper. The fuel enrichment and under-moderated lattice are evaluated by analyzing the typical TRISO particle with UO{sub 2} kernels which is widely used in high temperature gas reactors and that with enlarged UN fuel kernels. It was found that under the mandatory constraint of low enriched uranium, the FCM fuel with UO{sub 2} kernels, although relatively mature, is only capable of small reactor designs, and the assembly lattice needs to be modified. The FCM fuel with UN kernels, when directly loading in the commercial PWRs, can yield comparable reactor power and life; however, a higher fuel enrichment and the fuel design and fabrication need to be optimized. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗