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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

MCNP6 Monte Carlo Code Optimization [Slides]

The MCNP6.1 Monte Carlo code, released in 2013, offers many features not available in previous versions, but runs 20-30% slower for most problems and 2-5x slower for some problems. The MCNP 2020 initiative was established in mid-2013 to address code performance and other issues, with 3 basic components: (1) Improve MCNP performance, with the specific goal of achieving a 2x performance gain within 2 years; (2) Upgrade the core MCNP software and algorithms in an evolutionary fashion, with the goal of achieving more agile and sustainable code; (3) Prepare for future exascale systems that will include massive parallelism and limited memory per core, with the goal of providing flexible and adaptable coding for possible exascale systems. This talk reviews the initial performance improvements to MCNP6.1 that have been incorporated into the 2014 update, MCNP6.1.1. The performance improvements to date have included both classic code optimizations and algorithm improvements. Testing on a variety of problems has demonstrated that the performance improvements were effective, yielding speedups by factors of 1.2x - 4x compared to MCNP6.1, depending on the type of problem. For criticality problems, MCNP6.1.1 runs 1.5x - 1.7x faster than MCNP6.1. Much more work is planned for improving MCNP6 performance, structure, and algorithms.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

NWPEsSe: an Adaptive-Learning Global Optimization Algorithm for Nanosized Cluster Systems

Global optimization constitutes an important and fundamental problem in theoretical studies in many chemical fields, such as catalysis, materials or separations problems. In this paper, a novel algorithm has been developed for the global optimization of large systems including neat and ligated clusters in gas phase, and supported clusters in periodic boundary conditions. The method is based on an updated artificial bee colony (ABC) algorithm method, that allows for adaptive-learning during the search process. The new algorithm is tested against four classes of systems of diverse chemical nature: gas phase Au_55, ligated Au_8^(2+), Au_8 supported on graphene oxide and defected rutile, and a large cluster assembly ?[Co?_6 Te_8 (PEt_3 )_6][C_60 ]_n, with sizes ranging between 1 to 3 nm and containing up to 1300 atoms. Reliable global minima (GMs) are obtained for all cases, either confirming published data or reporting new lower energy structures. The algorithm and interface to other codes in the form of an independent program, Northwest Potential Energy Search Engine (NWPEsSe), is freely available and it provides a powerful and efficient approach for global optimization of nanosized cluster systems. The work described in this publication was performed at Pacific Northwest National Laboratory (PNNL), which is operated by Battelle for the United States Department of Energy (DOE) under Contract DE-AC05-76RL0180. J. Z. and V.-A. G. acknowledge support from DOE, Office of Science, Office of Basic Energy Sci-ences, Chemical, Geological and Biological Sciences Division and computing resources from PNNL’s Research Computing Facility and the National Energy Research Scientific Computing Center.

Zhang, Jun↗
DOE OSTI2020

Electronic Structure Theories of Singlet Fission and Multiple Exciton Generation (Final Report)

This DOE grant supported the development of electronic structure theory, algorithms, and computer programs for simulating singlet fission and multiple excision generation processes from Sept. 2013 to Aug. 2018 (which was terminated due to the PI’s departure from Northwestern University to industry). One of the main achievements is the development of the so-called active space decomposition (ASD) method hat describes exciton dynamics in organic semiconductors and spin dynamics in strongly correlated materials. The resulting software was interfaced with the Brilliantly Advanced General Electronic-structure Library (BAGEL) package and widely disseminated to the research community.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Direct numerical simulations of agglomeration of circular colloidal particles in two-dimensional shear flow

Colloidal agglomeration of nanoparticles in shear flow is investigated by solving the fluid-particle and particle-particle interactions in a 2D system. We use an extended finite element method in which the dynamics of the particles is solved in a fully coupled manner with the flow, allowing an accurate description of the fluid-particle interfaces without the need of boundary-fitted meshes or of empirical correlations to account for the hydrodynamic interactions between the particles. Adaptive local mesh refinement using a grid deformation method is incorporated with the fluid-structure interaction algorithm, and the particle-particle interaction at the microscopic level is modeled using the Lennard-Jones potential. Motivated by the process used in fabricating fuel cell catalysts from a colloidal ink, the model is applied to investigate agglomeration of colloidal particles under external shear flow in a sliding bi-periodic Lees-Edwards frame with varying shear rates and particle fraction ratios. Both external shear and particle fraction are found to have a crucial impact on the structure formation of colloidal particles in a suspension. Segregation intensity and graph theory are used to analyze the underlying agglomeration patterns and structures, and three agglomeration regimes are identified.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

pnnl/SHAD

Scalable High-performance Algorithms and Data-structures. Scalable High-performance Algorithms and Data-structures (SHAD) is an application programming interface based on a generic software library. It has a modular design that enables reuse of modules. The core of this software tool set is built on an Abstract Runtime interface and it's library includes the common data structures such as array, vector, map and set. It is designed to accommodate significant amount of data which can be accessed in massively parallel environments, and used as building blocks for SHAD extensions, i.e. higher level software libraries.

Castellana, Vito↗
DOE OSTI2016

Array-based, parallel hierarchical mesh refinement algorithms for unstructured meshes

In this paper, we describe an array-based hierarchical mesh refinement capability through uniform refinement of unstructured meshes for efficient solution of PDE's using finite element methods and multigrid solvers. A multi-degree, multi-dimensional and multi-level framework is designed to generate the nested hierarchies from an initial coarse mesh that can be used for a variety of purposes such as in multigrid solvers/preconditioners, to do solution convergence and verification studies and to improve overall parallel efficiency by decreasing I/O bandwidth requirements (by loading smaller meshes and in memory refinement). We also describe a high-order boundary reconstruction capability that can be used to project the new points after refinement using high-order approximations instead of linear projection in order to minimize and provide more control on geometrical errors introduced by curved boundaries.The capability is developed under the parallel unstructured mesh framework "Mesh Oriented dAtaBase" (MOAB Tautges et al. (2004)). We describe the underlying data structures and algorithms to generate such hierarchies in parallel and present numerical results for computational efficiency and effect on mesh quality. Furthermore, we also present results to demonstrate the applicability of the developed capability to study convergence properties of different point projection schemes for various mesh hierarchies and to a multigrid finite-element solver for elliptic problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Influence of computed tomography contrast agent on radiotherapy dose calculation for pancreatic carcinoma: A dosimetric study based on tomotherapy and volumetric-modulated arc therapy techniques

The main purpose of our investigation was to quantify the dosimetric influence of intravenous contrast agent for pancreatic cancer radiotherapy treatment. This study focused on complex modulated irradiation techniques of tomotherapy (TOMO) and volumetric-modulated arc therapy (VMAT) to investigate if novel conformal treatment methods could reduce the influence of contrast agent. In our study, patients with pancreatic cancer were enrolled to have 2 computed tomography (CT) scans in the same position without and with intravenous contrast agent for treatment planning. Then tumors and organ at risks were countered on contrast-enhanced CT (CECT) images. Each patient's CECT was assigned a TOMO plan and a VMAT plan. Then these plans were copied onto the non-CECT image and dose distribution was calculated with the same algorithm and structure sets. Finally, the dose distribution and the dose difference were analyzed for the target volume and organs at risk between the 2 sets of images. The statistic dosimetric result showed that for both TOMO and VMAT, no significant dose difference between CECT and non-CECT-based plan was observed. Dose difference was clinically negligible because the average relative percentage dose difference was 1% ± 1% for target volume, except a blurring effect at the higher dose region of the target volume. It implied that intravenous contrast agent will not affect dose calculation for pancreatic cancer radiotherapy significantly. Also the dose deviation based on TOMO showed no statistical difference compared with that on VMAT. For both superposition/conversation algorithm used by TOMO and Monte Carlo algorithm used by VMAT, the dosimetric difference was nonsignificant. A full analysis demonstrated a negligible dose difference of less than 1% between CECT-based plan and non-CECT-based plan. Therefore, contrast-enhanced CT image can be used directly for dose calculation of TOMO and VMAT plans for pancreatic cancer. It is unnecessary to scan twice then make a fusion of CECT and non-CECT, which would result to additional unnecessary radiation dose to patient and decrease work efficiency.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

OperonSEQer: A set of machine-learning algorithms with threshold voting for detection of operon pairs using short-read RNA-sequencing data

Operon prediction in prokaryotes is critical not only for understanding the regulation of endogenous gene expression, but also for exogenous targeting of genes using newly developed tools such as CRISPR-based gene modulation. A number of methods have used transcriptomics data to predict operons, based on the premise that contiguous genes in an operon will be expressed at similar levels. While promising results have been observed using these methods, most of them do not address uncertainty caused by technical variability between experiments, which is especially relevant when the amount of data available is small. In addition, many existing methods do not provide the flexibility to determine the stringency with which genes should be evaluated for being in an operon pair. We present OperonSEQer, a set of machine learning algorithms that uses the statistic and p-value from a non-parametric analysis of variance test (Kruskal-Wallis) to determine the likelihood that two adjacent genes are expressed from the same RNA molecule. We implement a voting system to allow users to choose the stringency of operon calls depending on whether your priority is high recall or high specificity. In addition, we provide the code so that users can retrain the algorithm and re-establish hyperparameters based on any data they choose, allowing for this method to be expanded as additional data is generated. We show that our approach detects operon pairs that are missed by current methods by comparing our predictions to publicly available long-read sequencing data. OperonSEQer therefore improves on existing methods in terms of accuracy, flexibility, and adaptability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

An algorithm for computing the 2D structure of fast rotating stars

Stars may be understood as self-gravitating masses of a compressible fluid whose radiative cooling is compensated by nuclear reactions or gravitational contraction. The understanding of their time evolution requires the use of detailed models that account for a complex microphysics including that of opacities, equation of state and nuclear reactions. The present stellar models are essentially one-dimensional, namely spherically symmetric. However, the interpretation of recent data like the surface abundances of elements or the distribution of internal rotation have reached the limits of validity of one-dimensional models because of their very simplified representation of large-scale fluid flows. In this article, we describe the ESTER code, which is the first code able to compute in a consistent way a two-dimensional model of a fast rotating star including its large-scale flows. Compared to classical 1D stellar evolution codes, many numerical innovations have been introduced to deal with this complex problem. First, the spectral discretization based on spherical harmonics and Chebyshev polynomials is used to represent the 2D axisymmetric fields. A nonlinear mapping maps the spheroidal star and allows a smooth spectral representation of the fields. The properties of Picard and Newton iterations for solving the nonlinear partial differential equations of the problem are discussed. It turns out that the Picard scheme is efficient on the computation of the simple polytropic stars, but Newton algorithm is unsurpassed when stellar models include complex microphysics. Finally, we discuss the numerical efficiency of our solver of Newton iterations. This linear solver combines the iterative Conjugate Gradient Squared algorithm together with an LU-factorization serving as a preconditioner of the Jacobian matrix.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Structures and magnetic properties of iron silicide from adaptive genetic algorithm and first-principles calculations

We performed a systematic search for low-energy structures of binary iron silicide over a wide range of compositions using the crystal structure prediction method based on adaptive genetic algorithm. 36 structures with formation energies within 50 meV/atom (11 of them are within 20 meV) above the convex hull formed by experimentally known stable structures are predicted. Magnetic properties of these low-energy structures are investigated. Some of these structures can be promising candidates for rare-earth-free permanent magnet.

36 MATERIALS SCIENCE↗
DOE OSTI2016

TU-AB-202-02: Deformable Image Registration Accuracy Between External Beam Radiotherapy and HDR Brachytherapy CT Images for Cervical Cancer Using a 3D-Printed Deformable Pelvis Phantom

Purpose: Accurate deformable image registration (DIR) between external beam radiotherapy (EBRT) and HDR brachytherapy (BT) CT images in cervical cancer is challenging. DSC has been evaluated only on the basis of the consistency of the structure, and its use does not guarantee an anatomically reasonable deformation. We evaluate the DIR accuracy for cervical cancer with DSC and anatomical landmarks using a 3D-printed pelvis phantom. Methods: A 3D-printed, deformable female pelvis phantom was created on the basis of the patient’s CT image. Urethane and silicon were used as materials for creating the uterus and bladder, respectively, in the phantom. We performed DIR in two cases: case-A with a full bladder (170 ml) in both the EBRT and BT images and case-B with a full bladder in the BT image and a half bladder (100 ml) in the EBRT image. DIR was evaluated using DSCs and 70 uterus and bladder landmarks. A Hybrid intensity and structure DIR algorithm with two settings (RayStation) was used. Results: In the case-A, DSCs of the intensity-based DIR were 0.93 and 0.85 for the bladder and uterus, respectively, whereas those of hybrid-DIR were 0.98 and 0.96, respectively. The mean landmark error values of intensity-based DIR were 0.73±0.29 and 1.70±0.19 cm for the bladder and uterus, respectively, whereas those of Hybrid-DIR were 0.43±0.33 and 1.23±0.25 cm, respectively. In both cases, the Hybrid-DIR accuracy was better than the intensity-based DIR accuracy for both evaluation methods. However, for several bladder landmarks, the Hybrid-DIR landmark errors were larger than the corresponding intensity-based DIR errors (e.g., 2.26 vs 1.25 cm). Conclusion: Our results demonstrate that Hybrid-DIR can perform with a better accuracy than the intensity-based DIR for both DSC and landmark errors; however, Hybrid-DIR shows a larger landmark error for some landmarks because the technique focuses on both the structure and intensity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

An algorithm to unveil the inner structure of objects concealed by beam divergence in radiographic image acquisition systems

Two main parameters rule the performance of an Image Acquisition System, namely, spatial resolution and contrast. For radiographic systems using cone beam arrangements, the farther the source, the better the resolution, but the contrast would diminish due to the lower statistics. A closer source would yield a higher contrast but it would no longer reproduce the attenuation map of the object, as the incoming beam flux would be reduced by unequal large divergences and attenuation factors. This work proposes a procedure to correct these effects when the object is comprised of a hull - or encased in it - possessing a shape capable to be described in analytical geometry terms. Such a description allows the construction of a matrix containing the attenuation factors undergone by the beam from the source until its final destination at each coordinate on the 2D detector. Each matrix element incorporates the attenuation suffered by the beam after its travel through the hull wall, as well as its reduction due to the square of distance to the source and the angle it hits the detector surface. When the pixel intensities of the original image are corrected by these factors, the image contrast, reduced by the overall attenuation in the exposure phase, are recovered, allowing one to see details otherwise concealed due to the low contrast. In order to verify the soundness of this approach, synthetic images of objects of different shapes, such as plates and tubes, incorporating defects and statistical fluctuation, have been generated, recorded for further comparison and afterwards processed to improve their contrast. The developed algorithm which, generates processes and plots the images has been written in Fortran 90 language. As the resulting final images exhibit the expected improvements, it therefore seemed worthwhile to carry out further tests with actual experimental radiographies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Solid phase stability of molybdenum under compression: Sound velocity measurements and first-principles calculations

The high-pressure solid phase stability of molybdenum (Mo) has been the center of a long-standing controversy on its high-pressure melting. In this work, experimental and theoretical researches have been conducted to check its solid phase stability under compression. First, we performed sound velocity measurements from 38 to 160 GPa using the two-stage light gas gun and explosive loading in backward- and forward-impact geometries, along with the high-precision velocity interferometry. From the sound velocities, we found no solid-solid phase transition in Mo before shock melting, which does not support the previous solid-solid phase transition conclusion inferred from the sharp drops of the longitudinal sound velocity [Hixson et al., Phys. Rev. Lett. 62, 637 (1989)]. Then, we searched its structures globally using the multi-algorithm collaborative crystal structure prediction technique combined with the density functional theory. By comparing the enthalpies of body centered cubic structure with those of the metastable structures, we found that bcc is the most stable structure in the range of 0–300 GPa. The present theoretical results together with previous ones greatly support our experimental conclusions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2013

QUANTIFYING OBSERVATIONAL PROJECTION EFFECTS USING MOLECULAR CLOUD SIMULATIONS

The physical properties of molecular clouds are often measured using spectral-line observations, which provide the only probes of the clouds' velocity structure. It is hard, though, to assess whether and to what extent intensity features in position-position-velocity (PPV) space correspond to 'real' density structures in position-position-position (PPP) space. In this paper, we create synthetic molecular cloud spectral-line maps of simulated molecular clouds, and present a new technique for measuring the reality of individual PPV structures. Using a dendrogram algorithm, we identify hierarchical structures in both PPP and PPV space. Our procedure projects density structures identified in PPP space into corresponding intensity structures in PPV space and then measures the geometric overlap of the projected structures with structures identified from the synthetic observation. The fractional overlap between a PPP and PPV structure quantifies how well the synthetic observation recovers information about the three-dimensional structure. Applying this machinery to a set of synthetic observations of CO isotopes, we measure how well spectral-line measurements recover mass, size, velocity dispersion, and virial parameter for a simulated star-forming region. By disabling various steps of our analysis, we investigate how much opacity, chemistry, and gravity affect measurements of physical properties extracted from PPV cubes. For the simulations used here, which offer a decent, but not perfect, match to the properties of a star-forming region like Perseus, our results suggest that superposition induces a ∼40% uncertainty in masses, sizes, and velocity dispersions derived from {sup 13}CO (J = 1-0). As would be expected, superposition and confusion is worst in regions where the filling factor of emitting material is large. The virial parameter is most affected by superposition, such that estimates of the virial parameter derived from PPV and PPP information typically disagree by a factor of ∼2. This uncertainty makes it particularly difficult to judge whether gravitational or kinetic energy dominate a given region, since the majority of virial parameter measurements fall within a factor of two of the equipartition level α ∼ 2.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Vectorization, threading, and cache-blocking considerations for hydrocodes on emerging architectures

This work reports on considerations for improving computational performance in preparation for current and expected changes to computer architecture. The algorithms studied will include increasingly complex prototypes for radiation hydrodynamics codes, such as gradient routines and diffusion matrix assembly (e.g., in [1-6]). The meshes considered for the algorithms are structured or unstructured meshes. The considerations applied for performance improvements are meant to be general in terms of architecture (not specifically graphical processing unit (GPUs) or multi-core machines, for example) and include techniques for vectorization, threading, tiling, and cache blocking. Out of a survey of optimization techniques on applications such as diffusion and hydrodynamics, we make general recommendations with a view toward making these techniques conceptually accessible to the applications code developer. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Accelerated impurity solver for DMFT and its diagrammatic extensions

Here, we present ComCTQMC, a GPU accelerated quantum impurity solver. It uses the continuous-time quantum Monte Carlo (CTQMC) algorithm wherein the partition function is expanded in terms of the hybridisation function (CT-HYB). ComCTQMC supports both partition and worm-space measurements, and it uses improved estimators and the reduced density matrix to improve observable measurements whenever possible. ComCTQMC efficiently measures all one and two-particle Green's functions, all static observables which commute with the local Hamiltonian, and the occupation of each impurity orbital. ComCTQMC can solve complex-valued impurities with crystal fields that are hybridized to both fermionic and bosonic baths. Most importantly, ComCTQMC utilizes graphical processing units (GPUs), if available, to dramatically accelerate the CTQMC algorithm when the Hilbert space is sufficiently large. We demonstrate acceleration by a factor of over 600 (100) in a simulation of δ-Pu at 600 K with (without) crystal fields. In easier problems, the GPU offers less impressive acceleration or even decelerates the CTQMC. Here we describe the theory, algorithms, and structure used by ComCTQMC in order to achieve this set of features and level of acceleration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Array-based Hierarchical Mesh Generation in Parallel

In this paper, we describe an array-based hierarchical mesh generation capability through uniform refinement of unstructured meshes for efficient solution of PDE's using finite element methods and multigrid solvers. A multi-degree, multi-dimensional and multi-level framework is designed to generate the nested hierarchies from an initial mesh that can be used for a number of purposes such as multi-level methods to generating large meshes. The capability is developed under the parallel mesh framework “Mesh Oriented dAtaBase” a.k.a MOAB. We describe the underlying data structures and algorithms to generate such hierarchies and present numerical results for computational efficiency and mesh quality. In conclusion, we also present results to demonstrate the applicability of the developed capability to a multigrid finite-element solver.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

The Third Ambient Aspirin Polymorph

Polymorphism in aspirin (acetylsalicylic acid), one of the most widely consumed medications, was equivocal until the structure of a second polymorph II, similar in structure to the original form I, was reported in 2005. Here, the third ambient polymorph of aspirin is described. Lastly, it was crystallized from the melt and its structure was determined using a combination of X-ray powder diffraction analysis and crystal structure prediction algorithms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗