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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 505 records · Page 28

A generalized 2D pencil beam scaling algorithm for proton dose calculation in heterogeneous slab geometries

Purpose: Pencil beam algorithms are commonly used for proton therapy dose calculations. Szymanowski and Oelfke ['Two-dimensional pencil beam scaling: An improved proton dose algorithm for heterogeneous media,' Phys. Med. Biol. 47, 3313-3330 (2002)] developed a two-dimensional (2D) scaling algorithm which accurately models the radial pencil beam width as a function of depth in heterogeneous slab geometries using a scaled expression for the radial kernel width in water as a function of depth and kinetic energy. However, an assumption made in the derivation of the technique limits its range of validity to cases where the input expression for the radial kernel width in water is derived from a local scattering power model. The goal of this work is to derive a generalized form of 2D pencil beam scaling that is independent of the scattering power model and appropriate for use with any expression for the radial kernel width in water as a function of depth. Methods: Using Fermi-Eyges transport theory, the authors derive an expression for the radial pencil beam width in heterogeneous slab geometries which is independent of the proton scattering power and related quantities. The authors then perform test calculations in homogeneous and heterogeneous slab phantoms using both the original 2D scaling model and the new model with expressions for the radial kernel width in water computed from both local and nonlocal scattering power models, as well as a nonlocal parameterization of Moliere scattering theory. In addition to kernel width calculations, dose calculations are also performed for a narrow Gaussian proton beam. Results: Pencil beam width calculations indicate that both 2D scaling formalisms perform well when the radial kernel width in water is derived from a local scattering power model. Computing the radial kernel width from a nonlocal scattering model results in the local 2D scaling formula under-predicting the pencil beam width by as much as 1.4 mm (21%) at the depth of the Bragg peak for a 220 MeV proton beam in homogeneous water. This translates into a 32% dose discrepancy for a 5 mm Gaussian proton beam. Similar trends were observed for calculations made in heterogeneous slab phantoms where it was also noted that errors tend to increase with greater beam penetration. The generalized 2D scaling model performs well in all situations, with a maximum dose error of 0.3% at the Bragg peak in a heterogeneous phantom containing 3 cm of hard bone. Conclusions: The authors have derived a generalized form of 2D pencil beam scaling which is independent of the proton scattering power model and robust to the functional form of the radial kernel width in water used for the calculations. Sample calculations made with this model show excellent agreement with expected values in both homogeneous water and heterogeneous phantoms.

61 RADIATION PROTECTION AND DOSIMETRY↗

Acquisition of STEM Images by Adaptive Compressive Sensing

Compressive Sensing (CS) allows a signal to be sparsely measured first and accurately recovered later in software [1]. In scanning transmission electron microscopy (STEM), it is possible to compress an image spatially by reducing the number of measured pixels, which decreases electron dose and increases sensing speed [2,3,4]. The two requirements for CS to work are: (1) sparsity of basis coefficients and (2) incoherence of the sensing system and the representation system. However, when pixels are missing from the image, it is difficult to have an incoherent sensing matrix. Nevertheless, dictionary learning techniques such as Beta-Process Factor Analysis (BPFA) [5] are able to simultaneously discover a basis and the sparse coefficients in the case of missing pixels. On top of CS, we would like to apply active learning [6,7] to further reduce the proportion of pixels being measured, while maintaining image reconstruction quality. Suppose we initially sample 10% of random pixels. We wish to select the next 1% of pixels that are most useful in recovering the image. Now, we have 11% of pixels, and we want to decide the next 1% of “most informative” pixels. Active learning methods are online and sequential in nature. Our goal is to adaptively discover the best sensing mask during acquisition using feedback about the structures in the image. In the end, we hope to recover a high quality reconstruction with a dose reduction relative to the non-adaptive (random) sensing scheme. In doing this, we try three metrics applied to the partial reconstructions for selecting the new set of pixels: (1) variance, (2) Kullback-Leibler (KL) divergence using a Radial Basis Function (RBF) kernel, and (3) entropy. Figs. 1 and 2 display the comparison of Peak Signal-to-Noise (PSNR) using these three different active learning methods at different percentages of sampled pixels. At 20% level, all the three active learning methods underperform the original CS without active learning. However, they all beat the original CS as more of the “most informative” pixels are sampled. One can also argue that CS equipped with active learning requires less sampled pixels to achieve the same value of PSNR than CS with pixels randomly sampled, since all the three PSNR curves with active learning grow at a faster pace than that without active learning. For this particular STEM image, by observing the reconstructed images and the sensing masks, we find that while the method based on RBF kernel acquires samples more uniformly, the one on entropy samples more areas of significant change, thus less uniformly. The KL-divergence method performs the best in terms of reconstruction error (PSNR) for this example [8].

Xie, Weiyi↗

αAMG based on Weighted Matching for Systems of Elliptic PDEs Arising From Displacement and Mixed Methods

Adaptive Algebraic Multigrid (or Multilevel) Methods (αAMG) are introduced to improve robustness and efficiency of classical algebraic multigrid methods in dealing with problems where no a-priori knowledge or assumptions on the near-null kernel of the underlined matrix are available. Recently we proposed an adaptive (bootstrap) AMG method, αAMG, aimed to obtain a composite solver with a desired convergence rate. Each new multigrid component relies on a current (general) smooth vector and exploits pairwise aggregation based on weighted matching in a matrix graph to define a new automatic, general-purpose coarsening process, which we refer to as “the compatible weighted matching”. In this work, we present results that broaden the applicability of our method to different finite element discretizations of elliptic PDEs. In particular, we consider systems arising from displacement methods in linear elasticity problems and saddle-point systems that appear in the application of the mixed method to Darcy problems.

97 MATHEMATICS AND COMPUTING↗

Reducing the error of geoid undulation computations by modifying Stokes' function

The truncation theory as it pertains to the calculation of geoid undulations based on Stokes' integral, but from limited gravity data, is reexamined. Specifically, the improved procedures of Molodenskii et al. are shown through numerical investigations to yield substantially smaller errors than the conventional method that is often applied in practice. In this improved method, as well as in a simpler alternative to the conventional approach, the Stokes' kernel is suitably modified in order to accelerate the rate of convergence of the error series. These modified methods, however, effect a reduction in the error only if a set of low-degree potential harmonic coefficients is utilized in the computation. Consider, for example, the situation in which gravity anomalies are given in a cap of radius 10 deg and the GEM 9 (20,20) potential field is used. Then, typically, the error in the computed undulation (aside from the spherical approximation and errors in the gravity anomaly data) according to the conventional truncation theory is 1.09 m; with Meissl's modification it reduces to 0.41m, while Molodenskii's improved method gives 0.45 m. A further alteration of Molodenskii's method is developed and yields an RMS error of 0.33 m. These values reflect the effect of the truncation, as well as the errors in the GEM 9 harmonic coefficients. The considerable improvement, suggested by these results, of the modified methods over the conventional procedure is verified with actual gravity anomaly data in two oceanic regions, where the GEOS-3 altimeter geoid serves as the basis for comparison. The optimal method of truncation, investigated by Colombo, is extremely ill-conditioned. It is shown that with no corresponding regularization, this procedure is inapplicable.

Jekeli, C.↗

SU-E-I-17: Comparison of Two Novel Algorithms for the Modulation Transfer Function of CT Using a Simple Cylindrical Phantom

Purpose: To compare and analyze two novel algorithms for the assessment of modulation transfer functions (MTFs) of computed tomography (CT) systems using a simple acrylic cylindrical phantom Method and Materials: Images of the acrylic cylindrical phantom were acquired by a GE LightSpeed 16 RT (GE Healthcare, Milwaukee, WI) using 120 kVp, 330 mA, 2.5 mm slice thickness, 10 cm field-of view (FOV), four reconstruction kernels (e.g. standard, soft, detail, bone, and lung). Two different algorithms were used to analyze images for MTF assessment. First, Richard et al. suggested a task-based MTF assessment method through an edge spread function (ESF) which described pixel intensities as a function of distance from the center. The MTF was obtained as the absolute value of Fourier transform of the differentiated ESF. Second, Ohkubo et al. devised an effective method to determine the point spread function (PSF) of CT system accompanied with verification. The line spread function (LSF), which was the one-dimensional integration of the PSF, was used to obtain the MTF. We validated the reliability of two above-mentioned methods through the comparison with a conventional method using a thin tungsten wire phantom. Results: The measured MTFs by two methods were mostly similar each other for standard, soft, and detail kernels. In 0.6 lp/mm, the MTF difference between two methods were 0.012(standard), 0.004(soft), and 0.037(detail). They also coincided with the MTF by the conventional method well. However, there were considerable distinctions for bone and lung kernels containing edge enhancement that might cause undershoots near the peak of the LSF. Conclusions: We compared two novel methods to assess task-based MTFs for clinical CT systems especially using a simple acrylic cylindrical phantom with high-convenience and low-cost, and validated them against a conventional method. This work can provide a practical solution to users for the quality assurance of CT.

60 APPLIED LIFE SCIENCES↗

An extension to the Chahine method of inverting the radiative transfer equation

An extension of the Chahine relaxation method (1970) for inverting the radiative transfer equation is presented. This method is superior to the original method in that it takes into account in a realistic manner the shape of the kernel function, and its extension to nonlinear systems is much more straightforward. A comparison of the new method with a matrix method due to Twomey (1965), in a problem involving inference of vertical distribution of ozone from spectroscopic measurements in the near ultraviolet, indicates that in this situation this method is stable with errors in the input data up to 4%, whereas the matrix method breaks down at these levels. The problem of non-uniqueness of the solution, which is a property of the system of equations rather than of any particular algorithm for solving them, remains, although it takes on slightly different forms for the two algorithms.

Twomey, S.↗

Edge-Based Viscous Method for Mixed-Element Node-Centered Finite-Volume Solvers

A novel, efficient, edge-based viscous (EBV) discretization method has been recently developed, implemented in a practical, unstructured-grid, node-centered, finite-volume flow solver, and applied to viscous-kernel computations that include evaluations of meanflow viscous fluxes, turbulence-model and chemistry-model diffusion terms, and the corresponding Jacobian contributions. Initially, the EBV method had been implemented for tetrahedral grids and demonstrated multifold acceleration of all viscous-kernel computations. This paper presents an extension of the EBV method for mixed-element grids. In addition to the primal edges of a given mixed-element grid, virtual edges are introduced to connect cell nodes that are not connected by a primal edge. The EBV method uses an efficient loop over all (primal and virtual) edges and features a compact discretization stencil based on the nearest neighbors. This study verifies the EBV method and assesses its efficiency on mixed-element grids by comparing the EBV solution accuracy and iterative convergence with those of well-established solutions obtained using a cell-based viscous (CBV) discretization method. The EBV solver’s memory footprint is optimized and often smaller than the memory footprint of the CBV solver. A multifold speedup is demonstrated for all viscous-kernel computations resulting in significant reduction of the time to solutions for several benchmark mixed-element-grid computations, including simulations of a flow around NASA’s juncture-flow model and a hypersonic, chemically reacting flow around a blunt body.

Edge-based viscous method↗

Edge-Based Viscous Method for Mixed-Element Node-Centered Finite-Volume Solvers

A novel, efficient, edge-based viscous (EBV) discretization method has been recently developed, implemented in a practical, unstructured-grid, node-centered, finite-volume flow solver, and applied to viscous-kernel computations that include evaluations of meanflow viscous fluxes, turbulence-model and chemistry-model diffusion terms, and the corresponding Jacobian contributions. Initially, the EBV method had been implemented for tetrahedral grids and demonstrated multifold acceleration of all viscous-kernel computations. This paper presents an extension of the EBV method for mixed-element grids. In addition to the primal edges of a given mixed-element grid, virtual edges are introduced to connect cell nodes that are not connected by a primal edge. The EBV method uses an efficient loop over all (primal and virtual) edges and features a compact discretization stencil based on the nearest neighbors. This study verifies the EBV method and assesses its efficiency on mixed-element grids by comparing the EBV solution accuracy and iterative convergence with those of well-established solutions obtained using a cell-based viscous (CBV) discretization method. The EBV solver’s memory footprint is optimized and often smaller than the memory footprint of the CBV solver. A multifold speedup is demonstrated for all viscous-kernel computations resulting in significant reduction of the time to solutions for several benchmark mixed-element-grid computations, including simulations of a flow around NASA’s juncture-flow model and a hypersonic, chemically reacting flow around a blunt body.

CFD↗

Symmetry-preserving contact interaction model for heavy-light mesons

We use a symmetry-preserving regularization method of ultraviolet divergences in a vector-vector contact interaction model for low-energy QCD. The contact interaction is a representation of nonperturbative kernels used Dyson-Schwinger and Bethe-Salpeter equations. The regularization method is based on a subtraction scheme that avoids standard steps in the evaluation of divergent integrals that invariably lead to symmetry violation. Aiming at the study of heavy-light mesons, we have implemented the method to the pseudoscalar π and K mesons. We have solved the Dyson-Schwinger equation for the u, d and s quark propagators, and obtained the bound-state Bethe-Salpeter amplitudes in a way that the Ward-Green-Takahashi identities reflecting global symmetries of the model are satisfied for arbitrary routing of the momenta running in loop integrals.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Transport-constrained extensions of collision and track length estimators for solutions of radiative transport problems

In this paper we develop novel extensions of collision and track length estimators for the complete space-angle solutions of radiative transport problems. We derive the relevant equations, prove that our new estimators are unbiased, and compare their performance with that of more conventional estimators. Such comparisons based on numerical solutions of simple one dimensional slab problems indicate the the potential superiority of the new estimators for a wide variety of more general transport problems.

97 MATHEMATICS AND COMPUTING↗

A Step towards Energy Efficient Computing: Redesigning a Hydrodynamic Application on CPU-GPU, In: 2014 IEEE 28th International Parallel and Distributed Processing Symposium

Power and energy consumption are becoming an increasing concern in high performance computing. Compared to multi-core CPUs, GPUs have a much better performance per watt. In this paper we discuss efforts to redesign the most computation intensive parts of BLAST, an application that solves the equations for compressible hydrodynamics with high order finite elements, using GPUs BLAST, Dobrev. In order to exploit the hardware parallelism of GPUs and achieve high performance, we implemented custom linear algebra kernels. We intensively optimized our CUDA kernels by exploiting the memory hierarchy, which exceed the vendor's library routines substantially in performance. We proposed an auto tuning technique to adapt our CUDA kernels to the orders of the finite element method. Compared to a previous base implementation, our redesign and optimization lowered the energy consumption of the GPU in two aspects: 60% less time to solution and 10% less power required. Compared to the CPU-only solution, our GPU accelerated BLAST obtained a 2.5× overall speedup and 1.42× energy efficiency (green up) using 4th order (Q_4) finite elements, and a 1.9× speedup and 1.27× green up using 2nd order (Q2) finite elements.

Computer Science↗

PARFUME Theory and Model Basis Report

The success of gas reactors depends upon the safety and quality of the coated particle fuel. The fuel performance modeling code PARFUME simulates the mechanical, thermal and physico-chemical behavior of fuel particles during irradiation. This report documents the theory and material properties behind vari¬ous capabilities of the code, which include: 1) various options for calculating CO production and fission product gas release, 2) an analytical solution for stresses in the coating layers that accounts for irradiation-induced creep and swelling of the pyrocarbon layers, 3) a thermal model that calculates a time-dependent temperature profile through a pebble bed sphere or a prismatic block core, as well as through the layers of each analyzed particle, 4) simulation of multi-dimensional particle behavior associated with cracking in the IPyC layer, partial debonding of the IPyC from the SiC, particle asphericity, and kernel migration (or amoeba effect), 5) two independent methods for determining particle failure probabilities, 6) a model for calculating release-to-birth (R/B) ratios of gaseous fission products that accounts for particle failures and uranium contamination in the fuel matrix, and 7) the evaluation of an accident condition, where a particle experiences a sudden change in temperature following a period of normal irradiation. The accident condi¬tion entails diffusion of fission products through the particle coating layers and through the fuel matrix to the coolant boundary. This document represents the initial version of the PARFUME Theory and Model Basis Report. More detailed descriptions will be provided in future revisions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

PV-Finder: ML Based Algorithm for Primary Vertex Identification

he CMS detector at the High-Luminosity Large Hadron Collider (HL-LHC) will operate in challenging conditions with expected pile-up of up to 200 collisions per bunch crossing, necessitating the development of a more resilient primary vertex (PV) reconstruction method to ensure the integrity of data analysis and the efficiency of the CMS triggering system. This contribution describes preliminary studies on a new ML based PV-Finder method for PV identification. The method is based on a model trained using Kernel Density Estimations (KDEs) derived from the positions of reconstructed tracks at the beamline, incorporating uncertainties from track parameters. It also utilizes target histograms, modeled as Gaussian distributions centered on the actual ground truth values of specific primary vertices.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

First season MWA EoR power spectrum results at redshift 7

The Murchison Widefield Array (MWA) has collected hundreds of hours of Epoch of Reionization (EoR) data and now faces the challenge of overcoming foreground and systematic contamination to reduce the data to a cosmological measurement. We introduce several novel analysis techniques, such as cable reflection calibration, hyper-resolution gridding kernels, diffuse foreground model subtraction, and quality control methods. Each change to the analysis pipeline is tested against a two-dimensional power spectrum figure of merit to demonstrate improvement. We incorporate the new techniques into a deep integration of 32 hours of MWA data. This data set is used to place a systematic-limited upper limit on the cosmological power spectrum of Δ{sup 2}⩽2.7×10{sup 4} mK{sup 2} at k = 0.27 h Mpc{sup −1} and z = 7.1, consistent with other published limits, and a modest improvement (factor of 1.4) over previous MWA results. From this deep analysis, we have identified a list of improvements to be made to our EoR data analysis strategies. These improvements will be implemented in the future and detailed in upcoming publications.

79 ASTRONOMY AND ASTROPHYSICS↗

DMTN-197: Streak Masking in DM Image Processing

Streaks caused by satellites are a persistent problem in optical images, and their occurrence will likely increase in the coming years. Many Hyper Suprime-Cam images are already affected by streaks, and the same is expected for Rubin Observatory data. In the LSST Data Release Production (DRP), most streaks and other artifacts are already detected and masked by the algorithm CompareWarpAssembleCoadd. However, some streaks are not caught at this stage and can contaminate the final coadds and detection catalogs. To find and mask these, we adopt a morphologically-based method for detecting streaks, which uses the Kernel-Based Hough Transform to detect straight lines. Once the lines are detected, the streak profile is fit and the affected portion of the image is masked out. This algorithm, maskStreaks, is included in the meas_algorithms package and is used in CompareWarpAssembleCoadd to remove streaks from coadds. Similar implementation in the Alert Production Pipeline is possible but has not been implemented.

79 ASTRONOMY AND ASTROPHYSICS↗

3DRT-MPASS

Data from all current JPL missions are stored in files called SPICE kernels. At present, animators who want to use data from these kernels have to either read through the kernels looking for the desired data, or write programs themselves to retrieve information about all the needed objects for their animations. In this project, methods of automating the process of importing the data from the SPICE kernels were researched. In particular, tools were developed for creating basic scenes in Maya, a 3D computer graphics software package, from SPICE kernels.

Lickly, Ben↗

Eigenvalue sensitivity studies for the Fort St. Vrain high temperature gas-cooled reactor to account for fabrication and modeling uncertainties

Uncertainties in the composition and fabrication of fuel compacts for the Fort St. Vrain (FSV) high temperature gas reactor have been studied by performing eigenvalue sensitivity studies that represent the key uncertainties for the FSV neutronic analysis. The uncertainties for the TRISO fuel kernels were addressed by developing a suite of models for an 'average' FSV fuel compact that models the fuel as (1) a mixture of two different TRISO fuel particles representing fissile and fertile kernels, (2) a mixture of four different TRISO fuel particles representing small and large fissile kernels and small and large fertile kernels and (3) a stochastic mixture of the four types of fuel particles where every kernel has its diameter sampled from a continuous probability density function. All of the discrete diameter and continuous diameter fuel models were constrained to have the same fuel loadings and packing fractions. For the non-stochastic discrete diameter cases, the MCNP compact model arranged the TRISO fuel particles on a hexagonal honeycomb lattice. This lattice-based fuel compact was compared to a stochastic compact where the locations (and kernel diameters for the continuous diameter cases) of the fuel particles were randomly sampled. Partial core configurations were modeled by stacking compacts into fuel columns containing graphite. The differences in eigenvalues between the lattice-based and stochastic models were small but the runtime of the lattice-based fuel model was roughly 20 times shorter than with the stochastic-based fuel model. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗