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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Critical percolation on the kagome hypergraph

In this report we study the percolation critical surface of the kagome lattice in which each triangle is allowed an arbitrary connectivity. Using the method of critical polynomials, we find points along this critical surface to high precision. This kagome hypergraph contains many unsolved problems as special cases, including bond percolation on the kagome and (3, 12 2 ) lattices, and site percolation on the hexagonal, or honeycomb, lattice, as well as a single point for which there is an exact solution. We are able to compute enough points along the critical surface to find a very accurate fit, essentially a Taylor series about the exact point, that allows estimations of the critical point of any system that lies on the surface to precision rivaling Monte Carlo and traditional techniques of similar accuracy. We find also that this system sheds light on some of the surprising aspects of the method of critical polynomials, such as why it is so accurate for certain problems, like the kagome and (3, 12 2 ) lattices. The bond percolation critical points of these lattices can be found to 17 and 18 digits, respectively, because they are in close proximity, in a sense that can be made quantitative, to the exact point on the critical surface. We also discuss in detail a parallel implementation of the method which we use here for a few calculations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

An Adaptive Bayesian Parameter Estimation of a Synchronous Generator Under Gross Errors

Polynomial-chaos-expansion-based surrogate models have recently been advocated in the literature for power system dynamic parameter estimation. Regarding the estimation of the uncertain generator parameters, a Bayesian inference framework has been proposed based on a polynomial-based reduced-order representation of the synchronous machines using assumed parameter values. Then, the non-Gaussian posterior probability distribution functions (pdfs) of these parameters are recovered through the stochastic sampling approach efficiently. However, facing very large parameter errors, the reliability of the surrogate model decreases, yielding biased estimation results. To overcome this problem, here we develop hierarchical Bayesian inference framework that processes the measurements provided by phasor measurement units, while making use of multifidelity surrogates together with the importance sampling method. The latter allows us to estimate in an efficient manner the posterior pdfs of the uncertain parameters through the normalized weights of the prior samples. To improve the accuracy of the posterior pdfs, an adaptive procedure is further adopted in the importance sampling for the gradual evolution of its proposal functions. The new proposals assist in fine-tuning the sample space and thereby help to construct surrogates with higher fidelity. Through an iterative process, this approach is able to estimate accurately and efficiently non-Gaussian posterior pdfs of the uncertain generator parameters subject to gross errors.

42 ENGINEERING↗
DOE OSTI2016

Conduction and rectification in NbO{sub x}- and NiO-based metal-insulator-metal diodes

Conduction and rectification in nanoantenna-coupled NbO{sub x}- and NiO-based metal-insulator-metal (MIM) diodes (“nanorectennas”) are studied by comparing new theoretical predictions with the measured response of nanorectenna arrays. A new quantum mechanical model is reported and agrees with measurements of current–voltage (I–V) curves, over 10 orders of magnitude in current density, from [NbO{sub x}(native)-Nb{sub 2}O{sub 5}]- and NiO-based samples with oxide thicknesses in the range of 5–36 nm. The model, which introduces new physics and features, including temperature, electron effective mass, and image potential effects using the pseudobarrier technique, improves upon widely used earlier models, calculates the MIM diode's I–V curve, and predicts quantitatively the rectification responsivity of high frequency voltages generated in a coupled nanoantenna array by visible/near-infrared light. The model applies both at the higher frequencies, when high-energy photons are incident, and at lower frequencies, when the formula for classical rectification, involving derivatives of the I–V curve, may be used. The rectified low-frequency direct current is well-predicted in this work's model, but not by fitting the experimentally measured I–V curve with a polynomial or by using the older Simmons model (as shown herein). By fitting the measured I–V curves with our model, the barrier heights in Nb-(NbO{sub x}(native)-Nb{sub 2}O{sub 5})-Pt and Ni-NiO-Ti/Ag diodes are found to be 0.41/0.77 and 0.38/0.39 eV, respectively, similar to literature reports, but with effective mass much lower than the free space value. The NbO{sub x} (native)-Nb{sub 2}O{sub 5} dielectric properties improve, and the effective Pt-Nb{sub 2}O{sub 5} barrier height increases as the oxide thickness increases. An observation of direct current of ∼4 nA for normally incident, focused 514 nm continuous wave laser beams are reported, similar in magnitude to recent reports. This measured direct current is compared to the prediction for rectified direct current, given by the rectification responsivity, calculated from the I–V curve times input power.

42 ENGINEERING↗
DOE OSTI2014

SU-E-T-246: MU Model Implementation for a Passively Scattered Proton Beam: Inclusion of the Bolus Gap and Nozzle Extension Factors

Purpose: To develop and implement an MU model for a passively scattered proton beam, and eliminate the need for patient specific calibrations for field sizes from 3cm to 15cm. This would enable consistent and timely calibrations for a wide variety of patient portals, streamlining the treatment process. Methods: Measurements were initially made using a Standard Imaging A-16 ion chamber and a modified water tank to determine the bolus gap factors (BGF) for multiple combinations of aperture size, bolus thickness, and air gap. The BGF was then separated into two component factors: the bolus thickness factor (BTF) and the nozzle extension factor (NEF). Polynomial curves were generated using the measured data to produce BTF tables for air gaps from 0cm to 30cm and for bolus thicknesses from 0cm to 10cm, and NEF tables for the full range of clinically used nozzle extensions. Additionally, data tables were created for every factor that affects beam output in the MU model. The MUs were then modeled for 487 patient portals and retrospectively compared to the MUs generated from the physical calibrations previously performed. Results: Of the 487 patient portals tested, 100% of the portals used for the comparison were within 2.5% from the MUs generated using a physical calibration, and 95.9% of the MU model portals tested were within 2%. The patient portals tested had field sizes ranging from 2.1cm to 10.1cm, with air gaps from 2cm to 25cm. Output factors for field sizes below 3cm with irregularly shaped fields demonstrated inconsistent results and will be further studied. Conclusion: The most problematic output factor, the BGF, was modeled accurately and consistently using the lowest order polynomial curve fits and interpolation between measured data. The study results demonstrate the robustness of the MU model and the potential for saving valuable personnel and beam time.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

TU-CD-207-11: Patient-Driven Automatic Exposure Control for Dedicated Breast CT

Purpose: To implement automatic exposure control (AEC) in dedicated breast CT (bCT) on a patient-specific basis using only the pre-scan scout views. Methods: Using a large cohort (N=153) of bCT data sets, the breast effective diameter (D) and width in orthogonal planes (Wa,Wb) were calculated from the reconstructed bCT image and pre-scan scout views, respectively. D, Wa, and Wb were measured at the breast center-of-mass (COM), making use of the known geometry of our bCT system. These data were then fit to a second-order polynomial “D=F(Wa,Wb)” in a least squares sense in order to provide a functional form for determining the breast diameter. The coefficient of determination (R{sup 2}) and mean percent error between the measured breast diameter and fit breast diameter were used to evaluate the overall robustness of the polynomial fit. Lastly, previously-reported bCT technique factors derived from Monte Carlo simulations were used to determine the tube current required for each breast diameter in order to match two-view mammographic dose levels. Results: F(Wa,Wb) provided fitted breast diameters in agreement with the measured breast diameters resulting in R{sup 2} values ranging from 0.908 to 0.929 and mean percent errors ranging from 3.2% to 3.7%. For all 153 bCT data sets used in this study, the fitted breast diameters ranged from 7.9 cm to 15.7 cm corresponding to tube current values ranging from 0.6 mA to 4.9 mA in order to deliver the same dose as two-view mammography in a 50% glandular breast with a 80 kV x-ray beam and 16.6 second scan time. Conclusion: The present work provides a robust framework for AEC in dedicated bCT using only the width measurements derived from the two orthogonal pre-scan scout views. Future work will investigate how these automatically chosen exposure levels affect the quality of the reconstructed image.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

A general framework of noise suppression in material decomposition for dual-energy CT

Purpose: As a general problem of dual-energy CT (DECT), noise amplification in material decomposition severely reduces the signal-to-noise ratio on the decomposed images compared to that on the original CT images. In this work, the authors propose a general framework of noise suppression in material decomposition for DECT. The method is based on an iterative algorithm recently developed in their group for image-domain decomposition of DECT, with an extension to include nonlinear decomposition models. The generalized framework of iterative DECT decomposition enables beam-hardening correction with simultaneous noise suppression, which improves the clinical benefits of DECT. Methods: The authors propose to suppress noise on the decomposed images of DECT using convex optimization, which is formulated in the form of least-squares estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, the authors include the inverse of the estimated variance–covariance matrix of the decomposed images as the penalty weight in the least-squares term. Analytical formulas are derived to compute the variance–covariance matrix for decomposed images with general-form numerical or analytical decomposition. As a demonstration, the authors implement the proposed algorithm on phantom data using an empirical polynomial function of decomposition measured on a calibration scan. The polynomial coefficients are determined from the projection data acquired on a wedge phantom, and the signal decomposition is performed in the projection domain. Results: On the Catphan{sup ®}600 phantom, the proposed noise suppression method reduces the average noise standard deviation of basis material images by one to two orders of magnitude, with a superior performance on spatial resolution as shown in comparisons of line-pair images and modulation transfer function measurements. On the synthesized monoenergetic CT images, the noise standard deviation is reduced by a factor of 2–3. By using nonlinear decomposition on projections, the authors’ method effectively suppresses the streaking artifacts of beam hardening and obtains more uniform images than their previous approach based on a linear model. Similar performance of noise suppression is observed in the results of an anthropomorphic head phantom and a pediatric chest phantom generated by the proposed method. With beam-hardening correction enabled by their approach, the image spatial nonuniformity on the head phantom is reduced from around 10% on the original CT images to 4.9% on the synthesized monoenergetic CT image. On the pediatric chest phantom, their method suppresses image noise standard deviation by a factor of around 7.5, and compared with linear decomposition, it reduces the estimation error of electron densities from 33.3% to 8.6%. Conclusions: The authors propose a general framework of noise suppression in material decomposition for DECT. Phantom studies have shown the proposed method improves the image uniformity and the accuracy of electron density measurements by effective beam-hardening correction and reduces noise level without noticeable resolution loss.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Localization and the Weyl algebras

Let W{sub n}(ℝ) be the Weyl algebra of index n. It is well known that so(p, q) Lie algebras can be viewed as quadratic polynomial (Lie) algebras in W{sub n}(ℝ) for p + q = n with the Lie algebra multiplication being given by the bracket [a, b] = ab − ba for a, b quadratic polynomials in W{sub n}(ℝ). What does not seem to be so well known is that the converse statement is, in a certain sense, also true, namely, that, by using extension and localization, it is possible, at least in some cases, to construct homomorphisms of W{sub n}(ℝ) onto its image in a localization of U(so(p + 2, q)), the universal enveloping algebra of so(p + 2, q), and m = p + q. Since Weyl algebras are simple, these homomorphisms must either be trivial or isomorphisms onto their images. We illustrate this remark for the so(2, q) case and construct a mappping from W{sub q}(ℝ) onto its image in a localization of U(so(2, q)). We prove that this mapping is a homomorphism when q = 1 or q = 2. Some specific results about representations for the lowest dimensional case of W{sub 1}(ℝ) and U(so(2, 1)) are given.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Constructing Surrogate Models of Complex Systems with Enhanced Sparsity: Quantifying the influence of conformational uncertainty in biomolecular solvation

Biomolecules exhibit conformational fluctuations near equilibrium states, inducing uncertainty in various biological properties in a dynamic way. We have developed a general method to quantify the uncertainty of target properties induced by conformational fluctuations. Using a generalized polynomial chaos (gPC) expansion, we construct a surrogate model of the target property with respect to varying conformational states. We also propose a method to increase the sparsity of the gPC expansion by defining a set of conformational “active space” random variables. With the increased sparsity, we employ the compressive sensing method to accurately construct the surrogate model. We demonstrate the performance of the surrogate model by evaluating fluctuation-induced uncertainty in solvent-accessible surface area for the bovine trypsin inhibitor protein system and show that the new approach offers more accurate statistical information than standard Monte Carlo approaches. Further more, the constructed surrogate model also enables us to directly evaluate the target property under various conformational states, yielding a more accurate response surface than standard sparse grid collocation methods. In particular, the new method provides higher accuracy in high-dimensional systems, such as biomolecules, where sparse grid performance is limited by the accuracy of the computed quantity of interest. Our new framework is generalizable and can be used to investigate the uncertainty of a wide variety of target properties in biomolecular systems.

coarse graining↗
DOE OSTI2020

Block Krylov Subspace Methods for Functions of Matrices II: Modified Block FOM

We analyze an expansion of the generalized block Krylov subspace framework of [Electron. Trans. Numer. Anal., 47 (2017), pp. 100--126]. This expansion allows the use of low-rank modifications of the matrix projected onto the block Krylov subspace and contains, as special cases, the block GMRES method and the new block Radau--Arnoldi method. Within this general setting, we present results that extend the interpolation property from the nonblock case to a matrix polynomial interpolation property for the block case, and we relate the eigenvalues of the projected matrix to the latent roots of these matrix polynomials. Some error bounds for these modified block FOM methods for solving linear systems are presented. We then show how cospatial residuals can be preserved in the case of families of shifted linear block systems. This result is used to derive computationally practical restarted algorithms for block Krylov approximations that compute the action of a matrix function on a set of several vectors simultaneously. Finally, we prove some error bounds and present numerical results showing that two modifications of FOM, the block harmonic and the block Radau--Arnoldi methods for matrix functions, can significantly improve the convergence behavior.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Verification of the LOTUS code with C5G7 benchmark

In this study, the verification of the neutron transport code LOTUS through the well-known C5G7 benchmark is performed. LOTUS uses the current coupled collision probability method with the expansion of the flux by orthogonal polynomials (CCCPO) for the solution of the neutron transport equation. The expansion of the flux by orthogonal polynomials allows one to avoid discretization of the calculation regions and significantly decreases the simulation time. The results of the LOTUS calculations are compared with the results of the reference OpenMC Monte Carlo simulations. The results of the comparison demonstrate almost perfect agreement with Monte-Carlo for the second order of the flux expansion. Even though the results obtained in the presented study agree well with the results of reference Monte Carlo calculations, further investigations are necessary for a better understanding of the stability and limitations of the code.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Parametric Synthesis of Supply Drives for CNC Metalworking Machines

Parametric synthesis of a two-mass supply drive is considered, in the case where one mass is the moment of inertia of the drive’s rotating part, while the other is the reduced moment of inertia of the drive’s linearly moving part. The elastic coupling between the masses determines the axial rigidity of the drive. In synthesis, the parameters of the electromechanical system are determined by setting the coefficients of the characteristic polynomial equal to the coefficients of the polynomial approximating an ideal low-frequency filter.

42 ENGINEERING↗
NASA NTRS1967

Bounds for Horner sums

Estimation of absolute values of Horner sum, using Chebyshev polynomials as maximizing polynomials

POLYNOMIAL↗
NASA NTRS2006

An improved method for precise automatic co-registration of moderate and high-resolution spacecraft imagery

Improvements to the automated co-registration and change detection software package, AFIDS (Automatic Fusion of Image Data System) has recently completed development for and validation by NGA/GIAT. The improvements involve the integration of the AFIDS ultra-fine gridding technique for horizontal displacement compensation with the recently evolved use of Rational Polynomial Functions/ Coefficients (RPFs/RPCs) for image raster pixel position to Latitude/Longitude indexing. Mapping and orthorectification (correction for elevation effects) of satellite imagery defies exact projective solutions because the data are not obtained from a single point (like a camera), but as a continuous process from the orbital path. Standard image processing techniques can apply approximate solutions, but advances in the state-of-the-art had to be made for precision change-detection and time-series applications where relief offsets become a controlling factor. The earlier AFIDS procedure required the availability of a camera model and knowledge of the satellite platform ephemeredes. The recent design advances connect the spacecraft sensor Rational Polynomial Function, a deductively developed model, with the AFIDS ultrafine grid, an inductively developed representation of the relationship raster pixel position to latitude /longitude. As a result, RPCs can be updated by AFIDS, a situation often necessary due to the accuracy limits of spacecraft navigation systems. An example of precision change detection will be presented from Quickbird.

co-registration↗
NASA NTRS2014

A Flexible Parameterization for Shortwave Optical Properties of Ice Crystals

A parameterization is presented that provides extinction cross section sigma (sub e), single-scattering albedo omega, and asymmetry parameter (g) of ice crystals for any combination of volume, projected area, aspect ratio, and crystal distortion at any wavelength in the shortwave. Similar to previous parameterizations, the scheme makes use of geometric optics approximations and the observation that optical properties of complex, aggregated ice crystals can be well approximated by those of single hexagonal crystals with varying size, aspect ratio, and distortion levels. In the standard geometric optics implementation used here, sigma (sub e) is always twice the particle projected area. It is shown that omega is largely determined by the newly defined absorption size parameter and the particle aspect ratio. These dependences are parameterized using a combination of exponential, lognormal, and polynomial functions. The variation of (g) with aspect ratio and crystal distortion is parameterized for one reference wavelength using a combination of several polynomials. The dependences of g on refractive index and omega are investigated and factors are determined to scale the parameterized (g) to provide values appropriate for other wavelengths. The parameterization scheme consists of only 88 coefficients. The scheme is tested for a large variety of hexagonal crystals in several wavelength bands from 0.2 to 4 micron, revealing absolute differences with reference calculations of omega and (g) that are both generally below 0.015. Over a large variety of cloud conditions, the resulting root-mean-squared differences with reference calculations of cloud reflectance, transmittance, and absorptance are 1.4%, 1.1%, and 3.4%, respectively. Some practical applications of the parameterization in atmospheric models are highlighted.

parameterization↗
NASA NTRS2021

Improving Automated Strategies for Univariate Quantifier Elimination

This report discusses improved support for univariate quantifier elimination in the Prototype Verification System (PVS). Previously, PVS had three strategies for quantifier elimination—hutch, tarski, and sturm. Of these, only hutch is able to decide queries in any input format—sturm only works on queries regarding a single polynomial on an interval and tarski resolves queries in the universal existential fragment. This paper describes an extended version of tarski. The extension is accomplished by formally verifying a disjunctive normal form transformation in PVS and using tarski on each conjunctive clause. Additionally, a preprocessing step is added to the decision procedure underlying tarski. This preprocessing is designed to exploit properties of polynomial structure to quickly resolve queries that have certain formats. The preprocessing produces dramatic speedup when it succeeds in resolving a query, and seems to introduce negligible overhead when it does not resolve a query. Finally, testing reveals some ways to improve the hutch and tarski strategies.

Polynomial Constraints↗
NASA NTRSDate not supplied

Design Under Uncertainty with Design-Dependent Uncertain Variables

Uncertainty quantification (UQ) can provide a more robust understanding of a system, leading to better informed decisions earlier in the design process. The additional information that UQ provides can be leveraged during a design optimization process known as design under uncertainty that, when incorporated with multidisciplinary design and optimization, can become computationally infeasible due to the large number of responses required for meaningful results. Previous work addressed reducing the computational expense in design under uncertainty by incorporating analytic derivatives throughout polynomial chaos expansion. Although this allows design under uncertainty to be feasible for more systems, some multidisciplinary systems have design-dependent uncertain variables. This paper details an implementation of design dependent uncertain variables in a manner than preserves derivatives required for efficient gradient-based optimization throughout the process. Two analytic examples of design-dependent uncertain variables are given: the first transforms a uniform uncertain variable with one design variable and the second transforms a normal uncertain variable with two design variables. The polynomial chaos expansion (PCE) results are comparable to both the Monte Carlo (MC) results and the analytic results for the two examples. A case study that maximizes the lift-to-drag ratio with a design-dependence between the wing leading edge sweep angle and uncertain parameter percentage of laminar flow is compared to a MC and alternative optimization formulations. This paper demonstrates that design-dependent uncertain variables are valid and hold throughout PCE.

robust design↗
DOE OSTI2016

Radiation Transport in Random Media With Large Fluctuations

Strongly heterogeneous media arise in several applications that include radiation shields, nuclear fuel, BWR moderators, clouds, planetary and stellar atmospheres, turbulent gases and plasmas. Neutral and charged particle transport computations in such media have relied heavily on formulating transport equations with spatially random coefficients (physical data) and developing solution methods to deal with the additional stochastic dimensions. Attempts at developing approximate closures that yield only low order statistical information (e.g., mean and variance of the flux) have proved to be highly restrictive under real physics conditions or rely on techniques that require fluctuation amplitudes to be small for robustness. Recently, stochastic spectral methods such as polynomial chaos and stochastic collocation have been developed for aleatoric uncertainty quantification and sensitivity analysis, and successfully applied in radiation transport work. Advances in UQ techniques have tended to focus on efficiently handling large numbers of uncertain variables but the rigorous stochastic basis of the approach also promotes its use in situations where stochasticity is due to spatial heterogeneity and the associated uncertainty is large. Here we apply these techniques to radiation transport in media with spatially randomly varying cross sections without restriction on fluctuation amplitudes. Specifically, we represent the cross sections as a lognormal spatial random process with specified mean, variance and covariance function and use a Karhunen-Loeve (KL) decomposition to generate cross section realizations that are strictly positive. Woodcock Monte Carlo (WMC) is then used to simulate transport using random sampling of cross sections and deterministic sampling based on a stochastic collocation technique. Numerical results for the mean and variance in the scalar flux and leakage currents are obtained for weak and strong random variations. We focus in this work on demonstrating the approach and defer application to specific problems to a future investigation. We have demonstrated that a combination of stochastic spectral representation and Woodcock Monte Carlo simulation allows efficient computation of radiation transport in strongly random media. The use of a lognormal distribution to represent the fluctuations in medium properties facilitates enforcement of strict positivity of cross section realizations, a condition that has challenged standard approaches that assume Gaussian fluctuations. The fact that the lognormal random process is a memoryless nonlinear transformation of a Gaussian process further enables efficient and accurate reconstruction of the random cross section realizations using a Karhunen-Loeve representation of the cross section. Finally, the robustness of this model enables fluctuations of arbitrarily large amplitude to be studied, using both random sampling Monte Carlo and more efficient stochastic collocation techniques. The present work is being extended to allow reconstruction of probability density functions of output variables using polynomial chaos representation, and to accommodate general cross section covariance functions. Also, techniques are being explored to more judiciously select ceiling cross sections to enhance the efficiency of Woodcock Monte Carlo for transport in random media. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Diffusion Synthetic Acceleration for High Order S{sub N} Transport on Meshes with Curved Surfaces

Thermal radiation transport is integral to multiphysics applications such as inertial confinement fusion and astrophysics. Materials in these problems can be exceptionally optically thick and diffusive. A transport solver must be capable of accurate and efficient solutions to such problems. Previously, Woods et al. established a proof-of-concept for high order (HO) discontinuous Galerkin finite element (DGFEM) transport on meshes with curved surfaces. They numerically demonstrated the spatial convergence is order p + 1. Remarkably, these convergence rates are relatively invariant to the amount of curvature of the spatial mesh. We present here an extension of this work that demonstrates a rapidly-convergent iterative solver for the FEM transport equations on meshes with curved sides. We use the modified interior penalty (MIP) diffusion synthetic acceleration (DSA) established by Wang and Ragusa. The partially consistent MIP equations stem from the symmetric interior penalty (IP) derivation of the diffusion equation. The IP method is not stable for optically thick cells so it was combined with the diffusion conforming form (DCF), a discretized diffusion equation derived from the discretized S N equations that is not stable for intermediate optical thicknesses. The MIP equations adapt a 'switch' to the IP method in optically thinner regions and the DCF method in optically thicker regions. The literature does not reveal any Fourier analyses performed for iterative transport on meshes with curved surfaces. Wang and Ragusa performed a Fourier analysis for orthogonal meshes and our results appear to be as expected. Previous literature has reported on some of the sensitivities that affect the spectral radius of DSA schemes: polynomial order, and scattering ratios. Presently, we focus on the sensitivity of the spectral radius to polynomial order, scattering ratio, the constant C, and mesh curvature for varying cell thicknesses. We also numerically study the behavior of the spectral radius to verify our DSA implementation. A sequence of problems is designed to exercise the acceleration. As the problems become more optically thick and diffusive, the accelerated solution continues to converge toward the analytic solution. We employ the Modular Finite Element Methods (MFEM) package, developed at Lawrence Livermore National Laboratory, to generate the linear algebraic system of equations for each angle in the discrete ordinates quadrature set, and use UMFPack to solve this system of equations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗