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At least 1,369 records · Page 76

Investigating the AGN-201M research reactor's unique dominance ratio

The AGN-201M reactor is a small, thermal spectrum reactor located at the University of New Mexico (UNM). It is moderated by polyethylene, reflected by graphite, with fuel comprised of uranium microspheres embedded in polyethylene plates that are separated by an aluminum baffle. The dominance ratio of a multiplying system is the ratio of the first higher-mode eigenvalue to the fundamental, k{sub 1}/k{sub 0}. It is a key parameter in characterizing the rate of convergence, analyzing system stability, and determining how tightly coupled the system's neutron fission is. The purpose of this paper is to investigate the system's unusually low dominance ratio of 0.632. This investigation varied the reactor's physical parameters, such as the fuel geometry, fuel density, and reflector thickness, and examined their impact on the reactor's dominance ratio. Additionally, this study examined neutronically similar systems in hopes of identifying common causes for systems with low dominance ratios. The reason why the dominance ratio of the reactor is small compared to larger thermal reactors was determined to be because of its significantly smaller geometry and the composition of the fuel plates. The reflector's effect on the dominance ratio is small in comparison to the other factors, but was found to have a non-zero effect. Furthermore, the AGN-201M was found to have a significantly lower dominance ratio than systems in which it shares a very high (c{sub k} >95%) degree of neutronic similarity.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

miniXyce

miniXyce uses a modified nodal analysis to approximate the governing differential algebraic equations (DAEs) for electronic devices and their coupling via a network and Kirchoff's conservation laws. The resulting nonlinear problem is solved iteratively using a fully coupled Newton method,which in turn results in a linear system that is solved using an iterative method.

Keiter, Eric↗

miniXyce

miniXyce uses a modified nodal analysis to approximate the governing differential algebraic equations (DAEs) for electronic devices and their coupling via a network and Kirchoff's conservation laws. The resulting nonlinear problem is solved iteratively using a fully coupled Newton method,which in turn results in a linear system that is solved using an iterative method.

Source record↗

Theoretical Calculation for the Ionization of Molecules by Short Strong Laser Pulses

We have developed several calculation methods for the ionization of atoms and molecules by strong and ultrashort laser pulses, based on the numerical solution of the time dependent Schroedinger equation (TDSE) in the momentum space. We have performed calculations within the strong field approximation (Volkov) and using iterative and direct methods for solving the TDSE. The investigated molecules are H{sub 2}{sup +} and H{sub 2}O. In case of the ionization of diatomic molecules the interference effects in the ejected electron spectra due to the coherent addition of the waves associated to the electrons ejected from the vicinity of different nuclei were also analysed.

74 ATOMIC AND MOLECULAR PHYSICS↗

Angular Distribution of Dimuons from Drell-Yan Production in p+Fe Interactions at 120 GeV Beam Energy

In the E906/SeaQuest Fermilab experiment, we report a measurement of the angular distributions by measuring the angular parameters $\lambda$, $\mu$, and $\nu$ of Drell-Yan dimuons produced using a 120 GeV proton beam incident on an iron target. The angular distribution in the naive Drell-Yan model does not show any $\cos2\phi$ dependency, where $\phi$ denotes the azimuthal angle of dimuons in the Collins-Soper frame. However, pion-induced Drell-Yan experiments, such as NA10 and E615, have observed a significant dependence on $\cos2\phi$. The Boer–Mulders function, a transverse momentum-dependent distribution function, represents the correlation between the transverse spin and the transverse momentum of the quark. A non-zero Boer-Mulders function or an improved higher-order Drell-Yan model considering QCD effects can produce a $\cos 2\phi$ modulation in the Drell-Yan angular distribution. To measure the angular distributions, we have used an event mixing method to construct the combin atorial background, which was then subtracted from the data to isolate the Drell-Yan signal. Following this, we corrected the detector, trigger, and reconstruction efficiencies using a doubly-iterative Bayesian Unfolding method. This iterative unfolding technique improves the response matrix based on the results of the previous unfolding step, ensuring robust convergence without exaggeration of uncertainties. The angular distributions of the dimuons were measured over the invariant mass range $5.0 < M_{\mu^+ \mu^-} < 8.0$ $GeV/c^2$, with dimuon transverse momentum $P_T < 2$ GeV/c and Feynman-x $-0.18 < x_F < 0.9$. The measured angular distributions are then compared with the QCD calculations for $p + \text{Fe}$ interactions, and proton-induced angular distribution measurements from other experiments. We have observed weak $\cos 2\phi$ modulations as a function of $P_T$. For $P_T > 1.0 \, \text{GeV}/c$, the predicted NNLO perturbative QCD value of $\nu$ is larger than what we have me asured at E906/SeaQuest. Moreover, we have not observed a strong dependence of $\nu$ on the kinematic variables, such as dimuon mass $M_{\mu^+ \mu^-}$ and Bjorken-$x$. The spin alignment of the virtual photon, $\lambda$, measured from the SeaQuest Drell-Yan $p+\text{Fe}$ data, is found to be strongly dependent on $P_T$, decreasing as $P_T$ increases. $\lambda$ also holds to the upper bound condition $\lambda < 1.0$ within the statistical uncertainty, showing a trend similar to that predicted by NNLO perturbative QCD. However, for $1.0 < P_T < 2.0 \, \text{GeV}/c$, the extracted $\lambda$ value from SeaQuest is smaller than that predicted by perturbative QCD at NNLO.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Preliminary Study on TRISO Fuel Cross Section Generation

Cross section self-shielding methodologies for TRISO fuel were assessed to provide accurate multigroup cross sections for a high-fidelity reactor physics code so that the code is able to accurately model and simulate advanced reactors with TRISO fuel. Initially, the two existing methodologies (the SCALE method and the Sanchez-Pomraning method) were studied and implemented to MC2-3 for detailed performance tests. Additionally, a new spatial self-shielding method, named the iterative local spatial self-shielding (ILSS) method, for particulate fuels was developed based on the disadvantage factor and implemented to MC2-3 as well. The new method approximately accounts for the effect of randomly distributed particles on the particle shadowing effect using a homogenized compact region surrounding a particle of interest at the center. The self-shielded cross sections of the particle at the center are determined iteratively since the cross sections of the homogenized compact region are calculated using them. For the energy range above 100 keV where the fuel-to-moderator ratio is more important than the random distribution of particles, a single particle unit-cell model is used by preserving the average amount of moderator per fuel particle in the system. The three self-shielding methods implemented in MC2-3 were tested using numerical benchmark problems made based on fuel compact problems of a prismatic-type very high temperature reactor. Test results indicated that the ILSS method produced slightly better results than the SCALE and Sanchez-Pomraning methods, compared to the Serpent-2 Monte Carlo results obtained with 25 independent random particle configurations. The SCALE and Sanchez-Pomraning methods tend to underestimate the heterogeneity effect by 150 and 100 pcm, respectively, while the new ILSS method overestimates the heterogeneity effect by 70 pcm. In future, the new self-shielding method will be extended to perform pebble calculations and compare results with those from the SCALE and Sanchez-Pomraning methods. Furthermore, the new method will be optimized for practical applications to on-the-fly resonance treatment for lattice or whole-core calculations for advanced reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Simultaneous iterations algorithm for general eigenvalue problems on parallel processors

The method of simultaneous iteration with shift is extended to extraction of m-eigenpairs of a general eigenvalue problem of large order n in a parallel processing environment. The algorithm combines the power method and the Jacobi technique, and reduces to performing four basic operations. Parallel implementation of the algorithm is discussed in detail. The analysis accounts for computation and communication costs, and utilizes a parallel processing architecture of the ensemble type. Expressions for the computational efficiency and speedup are defined as a function of the problem and hardware parameters. Selected representative problems exhibit efficiencies ranging from 60 to 98 percent.

Utku, S.↗

Rayleigh Quotient Iteration in 3D, Deterministic Neutron Transport

Today's "grand challenge" neutron transport problems require 3-D meshes with billions of cells, hundreds of energy groups, and accurate quadratures and scattering expansions. Leadership-class computers provide platforms on which high-fidelity fluxes can be calculated. However, appropriate methods are needed that can use these machines effectively. Such methods must be able to use hundreds of thousands of cores and have good convergence properties. Rayleigh quotient iteration (RQI) is an eigenvalue solver that has been added to the Sn code Denovo to address convergence. Rayleigh quotient iteration is an optimal shifted inverse iteration method that should converge in fewer iterations than the more common power method and other shifted inverse iteration methods for many problems of interest. Denovo's RQI uses a new multigroup Krylov solver for the fixed source solutions inside every iteration that allows parallelization in energy in addition to space and angle. This Krylov solver has been shown to scale successfully to 200,000 cores: for example one test problem scaled from 69,120 cores to 190,080 cores with 98% efficiency. This paper shows that RQI works for some small problems. However, the Krylov method upon which it relies does not always converge because RQI creates ill-conditioned systems. This result leads to the conclusion that preconditioning is needed to allow this method to be applicable to a wider variety of problems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Observation of a high-energy tail in ion energy distribution in the cylindrical Hall thruster plasma

A novel method is presented to determine populations and ion energy distribution functions (IEDFs) of individual ion species having different charge states in an ion beam from the measured spectrum of an E × B probe. The inversion of the problem is performed by adopting the iterative Tikhonov regularization method with the characteristic matrices obtained from the calculated ion trajectories. In a cylindrical Hall thruster plasma, an excellent agreement is observed between the IEDFs by an E × B probe and those by a retarding potential analyzer. The existence of a high-energy tail in the IEDF is found to be mainly due to singly charged Xe ions, and is interpreted in terms of non-linear ion acceleration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

RAYLEIGH QUOTIENT ITERATION IN 3D, DETERMINISTIC NEUTRON TRANSPORT

Today’s “grand challenge” neutron transport problems require 3-D meshes with billions of cells, hundreds of energy groups, and accurate quadratures and scattering expansions. Leadership-class computers provide platforms on which high-fidelity fluxes can be calculated. However, appropriate methods are needed that can use these machines effectively. Such methods must be able to to use hundreds of thousands of cores and have good convergence properties. Rayleigh quotient iteration (RQI) is an eigenvalue solver that has been added to the SN code Denovo to address convergence. Rayleigh quotient iteration is an optimal shifted inverse iteration method that should converge in fewer iterations than the more common power method and other shifted inverse iteration methods for many problems of interest. Denovo’s RQI uses a new multigroup Krylov solver for the fixed source solutions inside every iteration that allows parallelization in energy in addition to space and angle. This Krylov solver has been shown to scale successfully to 200,000 cores: for example one test problem scaled from 69,120 cores to 190,080 cores with 98% efficiency. This paper shows that RQI works for some small problems. However, the Krylov method upon which it relies does not always converge because RQI creates ill-conditioned systems. This result leads to the conclusion that preconditioning is needed to allow this method to be applicable to a wider variety of problems.

Slaybaugh, R. N.↗

SymProp: Scaling Sparse Symmetric Tucker Decomposition via Symmetry Propagation

Sparse symmetric tensors are an important class of tensors, and their decompositions serve as powerful tools for revealing low-rank structures. This paper introduces SymProp, a novel approach for scaling sparse symmetric Tucker decomposition by propagating symmetry through intermediate computations. SymProp optimizes two key computational kernels: Sparse Symmetric Tensor Times Same Matrix chain (S3 TTMc) for Higher-Order Orthogonal Iteration (HOOI) and Sparse Symmetric Tensor Times Same Matrix chain Times Core (S3 TTMcTC) for Higher-Order QR Iteration (HOQRI). Our method employs a metaprogramming-based index iteration approach to efficiently handle the upper triangular parts of intermediate dense symmetric tensors. SymProp achieves up to 50.9× speedup over SPLATT and up to 360.8× over Compressed Sparse Symmetric (CSS) format on the S3 TTMc operation. Moreover, our S3 TTMc and S3 TTMcTC implementations support tensor orders four levels higher than state-of-the-art methods. Our HOQRI demonstrates superior scalability and up to a 33.6× speedup over optimized HOOI. By enabling more scalable Tucker decompositions for higher orders, decomposition ranks, and dimension sizes, SymProp opens new possibilities for analyzing complex hypergraph structures in fields such as network science, data mining, and machine learning.

Li, Zecheng [North Carolina State University]↗

Statistical model based iterative reconstruction (MBIR) in clinical CT systems: Experimental assessment of noise performance

Purpose: To reduce radiation dose in CT imaging, the statistical model based iterative reconstruction (MBIR) method has been introduced for clinical use. Based on the principle of MBIR and its nonlinear nature, the noise performance of MBIR is expected to be different from that of the well-understood filtered backprojection (FBP) reconstruction method. The purpose of this work is to experimentally assess the unique noise characteristics of MBIR using a state-of-the-art clinical CT system. Methods: Three physical phantoms, including a water cylinder and two pediatric head phantoms, were scanned in axial scanning mode using a 64-slice CT scanner (Discovery CT750 HD, GE Healthcare, Waukesha, WI) at seven different mAs levels (5, 12.5, 25, 50, 100, 200, 300). At each mAs level, each phantom was repeatedly scanned 50 times to generate an image ensemble for noise analysis. Both the FBP method with a standard kernel and the MBIR method (Veo{sup ®}, GE Healthcare, Waukesha, WI) were used for CT image reconstruction. Three-dimensional (3D) noise power spectrum (NPS), two-dimensional (2D) NPS, and zero-dimensional NPS (noise variance) were assessed both globally and locally. Noise magnitude, noise spatial correlation, noise spatial uniformity and their dose dependence were examined for the two reconstruction methods. Results: (1) At each dose level and at each frequency, the magnitude of the NPS of MBIR was smaller than that of FBP. (2) While the shape of the NPS of FBP was dose-independent, the shape of the NPS of MBIR was strongly dose-dependent; lower dose lead to a “redder” NPS with a lower mean frequency value. (3) The noise standard deviation (σ) of MBIR and dose were found to be related through a power law of σ ∝ (dose){sup −β} with the component β ≈ 0.25, which violated the classical σ ∝ (dose){sup −0.5} power law in FBP. (4) With MBIR, noise reduction was most prominent for thin image slices. (5) MBIR lead to better noise spatial uniformity when compared with FBP. (6) A composite image generated from two MBIR images acquired at two different dose levels (D1 and D2) demonstrated lower noise than that of an image acquired at a dose level of D1+D2. Conclusions: The noise characteristics of the MBIR method are significantly different from those of the FBP method. The well known tradeoff relationship between CT image noise and radiation dose has been modified by MBIR to establish a more gradual dependence of noise on dose. Additionally, some other CT noise properties that had been well understood based on the linear system theory have also been altered by MBIR. Clinical CT scan protocols that had been optimized based on the classical CT noise properties need to be carefully re-evaluated for systems equipped with MBIR in order to maximize the method's potential clinical benefits in dose reduction and/or in CT image quality improvement.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Upper bounds for convergence rates of vector extrapolation methods on linear systems with initial iterations

The application of the minimal polynomial extrapolation (MPE) and the reduced rank extrapolation (RRE) to a vector sequence obtained by the linear iterative technique x(sub j) + 1 = Ax(sub j) = b,j = 1,2,..., is considered. Both methods produce a two dimensional array of approximations s(sub n,k) to the solution of the system (I - A)x = b. Here, s(sub n,k) is obtained from the vectors x(sub j), n is less than or equal to j is less than or equal to n + k + 1. It was observed in an earlier publication by the first author that the sequence s(sub n,k), k = 1,2,..., for n greater than 0, but fixed, possesses better convergence properties than the sequence s(sub 0,k), k = 1,2,.... A detailed theoretical explanation for this phenomenon is provided in the present work. This explanation is heavily based on approximations by incomplete polynomials. It is demonstrated by numerical examples when the matrix A is sparse that cycling with s(sub n,k) for n greater than 0, but fixed, produces better convergence rates and costs less computationally than cycling with s(sub 0,k). It is also illustrated numerically with a convection-diffusion problem that the former may produce excellent results where the latter may fail completely. As has been shown in an earlier publication, the results produced by s(sub 0,k) are identical to the corresponding results obtained by applying the Arnoldi method or generalized minimal residual scheme (GMRES) to the system (I - A)x = b.

Sidi, Avram↗

4D cone beam CT via spatiotemporal tensor framelet

Purpose: On-board 4D cone beam CT (4DCBCT) offers respiratory phase-resolved volumetric imaging, and improves the accuracy of target localization in image guided radiation therapy. However, the clinical utility of this technique has been greatly impeded by its degraded image quality, prolonged imaging time, and increased imaging dose. The purpose of this letter is to develop a novel iterative 4DCBCT reconstruction method for improved image quality, increased imaging speed, and reduced imaging dose. Methods: The essence of this work is to introduce the spatiotemporal tensor framelet (STF), a high-dimensional tensor generalization of the 1D framelet for 4DCBCT, to effectively take into account of highly correlated and redundant features of the patient anatomy during respiration, in a multilevel fashion with multibasis sparsifying transform. The STF-based algorithm is implemented on a GPU platform for improved computational efficiency. To evaluate the method, 4DCBCT full-fan scans were acquired within 30 s, with a gantry rotation of 200°; STF is also compared with a state-of-art reconstruction method via spatiotemporal total variation regularization. Results: Both the simulation and experimental results demonstrate that STF-based reconstruction achieved superior image quality. The reconstruction of 20 respiratory phases took less than 10 min on an NVIDIA Tesla C2070 GPU card. The STF codes are available at https://sites.google.com/site/spatiotemporaltensorframelet . Conclusions: By effectively utilizing the spatiotemporal coherence of the patient anatomy among different respiratory phases in a multilevel fashion with multibasis sparsifying transform, the proposed STF method potentially enables fast and low-dose 4DCBCT with improved image quality.

60 APPLIED LIFE SCIENCES↗

Light field moment imaging with the ptychographic iterative engine

The recently developed Light Field Moment Imaging (LMI) is adopted to show the stereoscopic structure of the sample studied in Coherent Diffractive Imaging (CDI), where 3D image were always generated with complicated experimental procedure such as the rotation of the sample and time-consuming computation. The animation of large view angle can be generated with LMI very quickly, and the 3D structure of sample can be shown vividly. This method can find many applications for the coherent diffraction imaging with x-ray and electron beams, where a glimpse of the hierarchical structure required and the quick and simple 3D view of object is sufficient. The feasibility of this method is demonstrated theoretically and experimentally with a recently developed CDI method called Ptychographic Iterative Engine.

36 MATERIALS SCIENCE↗

TH-EF-BRB-05: 4pi Non-Coplanar IMRT Beam Angle Selection by Convex Optimization with Group Sparsity Penalty

Purpose: Integrated beam orientation and fluence map optimization is expected to be the foundation of robust automated planning but existing heuristic methods do not promise global optimality. We aim to develop a new method for beam angle selection in 4π non-coplanar IMRT systems based on solving (globally) a single convex optimization problem, and to demonstrate the effectiveness of the method by comparison with a state of the art column generation method for 4π beam angle selection. Methods: The beam angle selection problem is formulated as a large scale convex fluence map optimization problem with an additional group sparsity term that encourages most candidate beams to be inactive. The optimization problem is solved using an accelerated first-order method, the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). The beam angle selection and fluence map optimization algorithm is used to create non-coplanar 4π treatment plans for several cases (including head and neck, lung, and prostate cases) and the resulting treatment plans are compared with 4π treatment plans created using the column generation algorithm. Results: In our experiments the treatment plans created using the group sparsity method meet or exceed the dosimetric quality of plans created using the column generation algorithm, which was shown superior to clinical plans. Moreover, the group sparsity approach converges in about 3 minutes in these cases, as compared with runtimes of a few hours for the column generation method. Conclusion: This work demonstrates the first non-greedy approach to non-coplanar beam angle selection, based on convex optimization, for 4π IMRT systems. The method given here improves both treatment plan quality and runtime as compared with a state of the art column generation algorithm. When the group sparsity term is set to zero, we obtain an excellent method for fluence map optimization, useful when beam angles have already been selected. NIH R43CA183390, NIH R01CA188300, Varian Medical Systems; Part of this research took place while D. O’Connor was a summer intern at RefleXion Medical.

60 APPLIED LIFE SCIENCES↗

Development of generalized block correction procedures for the solution of discretized Navier-Stokes equations

Effort is directed towards developing a solution method which combines advantages of both the iterative and the direct methods. It involves iterative solution on the fine grid, convergence of which is enhanced by a direct solution for correction quantities on a coarse grid. The proposed block correction procedure was applied to compute recirculating flow in a driven cavity.

Kelkar, Kanchan M.↗

Progressive content-based retrieval of image and video with adaptive and iterative refinement

A method and apparatus for minimizing the time required to obtain results for a content based query in a data base. More specifically, with this invention, the data base is partitioned into a plurality of groups. Then, a schedule or sequence of groups is assigned to each of the operations of the query, where the schedule represents the order in which an operation of the query will be applied to the groups in the schedule. Each schedule is arranged so that each application of the operation operates on the group which will yield intermediate results that are closest to final results.

Li, Chung-Sheng↗