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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

SU-C-207-01: Four-Dimensional Inverse Geometry Computed Tomography: Concept and Its Validation

Purpose: In past few years, the inverse geometry computed tomography (IGCT) system has been developed to overcome shortcomings of a conventional computed tomography (CT) system such as scatter problem induced from large detector size and cone-beam artifact. In this study, we intend to present a concept of a four-dimensional (4D) IGCT system that has positive aspects above all with temporal resolution for dynamic studies and reduction of motion artifact. Methods: Contrary to conventional CT system, projection data at a certain angle in IGCT was a group of fractionated narrow cone-beam projection data, projection group (PG), acquired from multi-source array which have extremely short time gap of sequential operation between each of sources. At this, for 4D IGCT imaging, time-related data acquisition parameters were determined by combining multi-source scanning time for collecting one PG with conventional 4D CBCT data acquisition sequence. Over a gantry rotation, acquired PGs from multi-source array were tagged time and angle for 4D image reconstruction. Acquired PGs were sorted into 10 phase and image reconstructions were independently performed at each phase. Image reconstruction algorithm based upon filtered-backprojection was used in this study. Results: The 4D IGCT had uniform image without cone-beam artifact on the contrary to 4D CBCT image. In addition, the 4D IGCT images of each phase had no significant artifact induced from motion compared with 3D CT. Conclusion: The 4D IGCT image seems to give relatively accurate dynamic information of patient anatomy based on the results were more endurable than 3D CT about motion artifact. From this, it will be useful for dynamic study and respiratory-correlated radiation therapy. This work was supported by the Industrial R&D program of MOTIE/KEIT [10048997, Development of the core technology for integrated therapy devices based on real-time MRI guided tumor tracking] and the Mid-career Researcher Program (2014R1A2A1A10050270) through the National Research Foundation of Korea funded by the Ministry of Science, ICT&Future Planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Efficient Probability of Failure Calculations for QMU using Computational Geometry (LDRD 13-0144 Final Report)

This SAND report summarizes our work on the Sandia National Laboratory LDRD project titled "Efficient Probability of Failure Calculations for QMU using Computational Geometry" which was project #165617 and proposal #13-0144. This report merely summarizes our work. Those interested in the technical details are encouraged to read the full published results, and contact the report authors for the status of the software and follow-on projects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SU-E-I-12: Flexible Geometry Computed Tomography

Purpose: The concept separates the mechanical connection between the radiation source and detector. This design allows the trajectory and orientation of the radiation source/detector to be customized to the object that is being imaged. This is in contrast to the formulaic rotation-translation image acquisition of conventional computed tomography(CT).Background/significance:CT devices that image a full range of: anatomy, patient populations, and imaging procedures are large. The root cause of the expanding size of comprehensive CT is due to the commitment to helical geometry that is hardwired into the image reconstruction. FGCT extends the application of alternative reconstruction techniques, i.e. tomosynthesis, by separating the two main components— radiation source and detector— and allow for 6 degrees of freedom motion for radiation source, detector, or both. The image acquisition geometry is then tailored to how the patient/object is positioned. This provides greater flexibility on the position and location that the patient/object is being imaged. Additionally, removing the need of a rotating gantry reduces the footprint so that CT is more mobile and more available to move to where the patient/object is at, instead of the other way around. Methods: As proof-of-principle, a reconstruction algorithm is designed to produce FGCT images. Using simulated detector data, voxels intersecting a line drawn between the radiation source and an individual detector are traced and modified using the detector signal. The detector signal is modified to compensate for changes in the source to detector distance. Adjacent voxels are modified in proportion to the detector signal, providing a simple image filter. Results: Image-quality from the proposed FGCT reconstruction technique is proving to be a challenge, producing hardily recognizable images from limited projections angles. Conclusion: Preliminary assessment of the reconstruction technique demonstrates the inevitable tradeoff of producing meaningful image-quality verses the practicality of how to obtain sufficient image data.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Fluctuating Hydrodynamic Methods for Fluid-Structure Interactions in Confined Channel Geometries

Computational methods are developed for the study of fluid-structure interactions subject to thermal fluctuations when conned within channels having slit-like geometry. The methods take into account the hydrodynamic coupling and diusivity of microstructures when influenced by their proximity to no-slip walls. We develop stochastic numerical methods subject to no-slip boundary conditions using a staggered nite volume discretization. We show that by imposing an exact fluctuation-dissipation condition to discretize the stochastic driving elds combined with using an exact projection method to enforce incompressibility is sucient to ensure results consistent with statistical mechanics. We demonstrate our methods by investigating how the proximity of ellipsoidal colloids to the channel wall eects their active hydrodynamic responses and passive diusivity. We also study the collective dynamics of a large number of particles by considering the intermediate scattering functions for the relaxation of density fluctuations. We expect our introduced stochastic computational methods to be applicable broadly to applications in which confinement effects play an important role in the dynamics of microstructures subject to hydrodynamic coupling and thermal fluctuations. uctuations.

Wang, Yaohong↗
DOE OSTI2024

Landau Singularities Revisited: Computational Algebraic Geometry for Feynman Integrals

We reformulate the analysis of singularities of Feynman integrals in a way that can be practically applied to perturbative computations in the standard model in dimensional regularization. After highlighting issues in the textbook treatment of Landau singularities, we develop an algorithm for classifying and computing them using techniques from computational algebraic geometry. We introduce an algebraic variety called the principal Landau determinant, which captures the singularities even in the presence of massless particles or UV/IR divergences. We illustrate this for 114 example diagrams, including a cutting-edge 2-loop 5-point nonplanar QCD process with multiple mass scales. Published by the American Physical Society 2024

Physics↗
DOE OSTI2018

Fast and accurate normalization of vectors and quaternions

We present fast and accurate ways to normalize two and three-dimensional vectors and quaternions and compute their length. Our approach is an adaptation of ideas used in the linear algebra library LAPACK, and we believe that the computational geometry and computer-aided design communities are not aware of the possibility of speeding up these fundamental operations in the robust way proposed here.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Multisource inverse-geometry CT. Part II. X-ray source design and prototype

Purpose: This paper summarizes the development of a high-power distributed x-ray source, or “multisource,” designed for inverse-geometry computed tomography (CT) applications [see B. De Man et al., “Multisource inverse-geometry CT. Part I. System concept and development,” Med. Phys. 43, 4607–4616 (2016)]. The paper presents the evolution of the source architecture, component design (anode, emitter, beam optics, control electronics, high voltage insulator), and experimental validation. Methods: Dispenser cathode emitters were chosen as electron sources. A modular design was adopted, with eight electron emitters (two rows of four emitters) per module, wherein tungsten targets were brazed onto copper anode blocks—one anode block per module. A specialized ceramic connector provided high voltage standoff capability and cooling oil flow to the anode. A matrix topology and low-noise electronic controls provided switching of the emitters. Results: Four modules (32 x-ray sources in two rows of 16) have been successfully integrated into a single vacuum vessel and operated on an inverse-geometry computed tomography system. Dispenser cathodes provided high beam current (>1000 mA) in pulse mode, and the electrostatic lenses focused the current beam to a small optical focal spot size (0.5 × 1.4 mm). Controlled emitter grid voltage allowed the beam current to be varied for each source, providing the ability to modulate beam current across the fan of the x-ray beam, denoted as a virtual bowtie filter. The custom designed controls achieved x-ray source switching in <1 μs. The cathode-grounded source was operated successfully up to 120 kV. Conclusions: A high-power, distributed x-ray source for inverse-geometry CT applications was successfully designed, fabricated, and operated. Future embodiments may increase the number of spots and utilize fast read out detectors to increase the x-ray flux magnitude further, while still staying within the stationary target inherent thermal limitations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Fast and Accurate Intersections on a Sphere

We introduce a fast, high-precision algorithm for calculating intersections between great circle arcs and lines of constant latitude on the unit sphere. We first propose a simplified intersection point formula with improved speed and numerical robustness over the ones traditionally implemented in geoscience software. We then show how algorithms based on the concept of error-free transformations (EFT) can be applied to evaluate this formula within a relative error bound that is on the order of machine precision. Here, we demonstrate that, with a vectorized and parallelized implementation, this enhanced accuracy is achieved with no compute time overhead compared to a direct calculation in hardware floating point, making our algorithm suitable for performance-sensitive applications like regridding of high-resolution climate data. In contrast, evaluating our formula using high-precision data types like quadruple precision and arbitrary precision, or using the robust intersection computation routines from the Computational Geometry Algorithms Library, leads to significant computational overhead, especially since these alternatives inhibit vectorization. More generally, our work demonstrates how EFT techniques can be combined and extended to implement nontrivial geometric calculations with high accuracy and speed.

Environmental sciences↗
DOE OSTI2016

Monte Carlo Techniques for Nuclear Systems - Theory Lectures

These are lecture notes for a Monte Carlo class given at the University of New Mexico. The following topics are covered: course information; nuclear eng. review & MC; random numbers and sampling; computational geometry; collision physics; tallies and statistics; eigenvalue calculations I; eigenvalue calculations II; eigenvalue calculations III; variance reduction; parallel Monte Carlo; parameter studies; fission matrix and higher eigenmodes; doppler broadening; Monte Carlo depletion; HTGR modeling; coupled MC and T/H calculations; fission energy deposition. Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. These lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo calculations. Beginning MCNP users are encouraged to review LA-UR-09-00380, "Criticality Calculations with MCNP: A Primer (3nd Edition)" (available at http:// mcnp.lanl.gov under "Reference Collection") prior to the class. No Monte Carlo class can be complete without having students write their own simple Monte Carlo routines for basic random sampling, use of the random number generator, and simplified particle transport simulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

DIATOM (Data Initialization and Modification) Library Version 7.0

DIATOM is a library that provides numerical simulation software with a computational geometry front end that can be used to build up complex problem geometries from collections of simpler shapes. The library provides a parser which allows for application-independent geometry descriptions to be embedded in simulation software input decks. Descriptions take the form of collections of primitive shapes and/or CAD input files and material properties that can be used to describe complex spatial and temporal distributions of numerical quantities (often called “database variables” or “fields”) to help define starting conditions for numerical simulations. The capability is designed to be general purpose, robust and computationally efficient. By using a combination of computational geometry and recursive divide-and-conquer approximation techniques, a wide range of primitive shapes are supported to arbitrary degrees of fidelity, controllable through user input and limited only by machine resources. Through the use of call-back functions, numerical simulation software can request the value of a field at any time or location in the problem domain. Typically, this is used only for defining initial conditions, but the capability is not limited to just that use. The most recent version of DIATOM provides the ability to import the solution field from one numerical solution as input for another.

Crawford, David A.↗
DOE OSTI2015

Coupling extended magnetohydrodynamic fluid codes with radiofrequency ray tracing codes for fusion modeling

Neoclassical tearing modes are macroscopic ($L$ ~ 1 m) instabilities in magnetic fusion experiments; if unchecked, these modes degrade plasma performance and may catastrophically destroy plasma confinement by inducing a disruption. Fortunately, the use of properly tuned and directed radiofrequency waves ($λ$ ~ 1 mm) can eliminate these modes. Numerical modeling of this difficult multiscale problem requires the integration of separate mathematical models for each length and time scale [T. G. Jenkins, S. E. Kruger, Phys. Plasmas 19 (2012) 122508]; the extended MHD model captures macroscopic plasma evolution while the RF model tracks the flow and deposition of injected RF power through the evolving plasma profiles. The scale separation enables use of the eikonal (ray-tracing) approximation to model the RF wave propagation. In this work we demonstrate a technique, based on methods of computational geometry, for mapping the ensuing RF data (associated with discrete ray trajectories) onto the finite-element/pseudospectral grid that is used to model the extended MHD physics. In the new representation, the RF data can then be used to construct source terms in the equations of the extended MHD model, enabling quantitative modeling of RF-induced tearing mode stabilization. Though our specific implementation uses the NIMROD extended MHD [C. R. Sovinec et al., J. Comp. Phys. 195 (2004) 355] and GENRAY RF [A. P. Smirnov, R. W. Harvey, K. Kupfer, Bull. Amer. Phys. Soc. 39 (1994) 1626] codes, the approach presented can be applied more generally to any code coupling requiring the mapping of ray tracing data onto Eulerian grids.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Validation of Methods for Computational Catalyst Design: Geometries, Structures, and Energies of Neutral and Charged Silver Clusters

We report a systematic study of small silver clusters, Agn, Agn+, and Agn–, n = 1–7. We studied all possible isomers of clusters with n = 5–7. We tested 42 exchange–correlation functionals, and we assess these functionals for their accuracy in three respects: geometries (quantitative prediction of internuclear distances), structures (the nature of the lowest-energy structure, for example, whether it is planar or nonplanar), and energies. We find that the ingredients of exchange–correlation functionals are indicators of their success in predicting geometries and structures: local exchange–correlation functionals are generally better than hybrid functionals for geometries; functionals depending on kinetic energy density are the best for predicting the lowest-energy isomer correctly, especially for predicting two-dimensional to three-dimenstional transitions correctly. The accuracy for energies is less sensitive to the ingredient list. Our findings could be useful for guiding the selection of methods for computational catalyst design.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2021

Community-Driven Methods for Open and Reproducible Software Tools for Analyzing Datasets from Atom Probe Microscopy

Atom probe tomography, and related methods, probe the three-dimensional architecture of a material. The software tools that microscopists use, and how these tools are connected into workflows, makes a substantial contribution to the accuracy and precision of such a material characterization experiment. Typically, we adapt methods from other communities like mathematics, data science, computational geometry, artificial intelligence, or scientific computing. We also realize that improving on research data management is a challenge when it comes to align with the FAIR data stewardship principles. Faced with this global challenge, we are convinced that collaborating is useful. Here, we report the results and challenges with an inter-laboratory call for developing test cases for several types of atom probe software tools. The results support why defining detailed recipes of software workflows and sharing these recipes is necessary and rewarding: Open source tools and (meta)data exchange can help to make our day-to-day data processing tasks become more efficient, the training of new users and knowledge transfer become easier, and assist us with automated quantification of uncertainties to gain access to substantiated results.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Geometry-Driven Longitudal Topic Model

A simple and scalable framework for longitudinal analysis of Twitter data is developed that combines latent topic models with computational geometric methods. Dimensionality reduction tools from computational geometry are applied to learn the intrinsic manifold on which the latent, temporal topics reside. Then shortest path distances on the manifold are used to link together these topics. The proposed framework permits visualization of the low-dimensional embedding which provides clear interpretation of the complex, high-dimensional trajectories that may exist among latent topics. Practical application of the proposed framework is demonstrated through its ability to capture and effectively visualize natural progression of latent COVID-19 related topics learned from Twitter data. Interpretability of the trajectories is achieved by comparing to real-world events. In addition, the framework permits study of spatial variation in Twitter behavior for learned topics. The analysis demonstrates that the proposed framework is able to capture granular-level impact of COVID-19 on public discussions. We end by arguing that Twitter data, when analyzed within the proposed framework, can serve as a valuable supplementary data stream for COVID-related studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

An extension to V ORO ++ for multithreaded computation of Voronoi cells

V ORO ++ is a software library written in C++ for computing the Voronoi tessellation, a technique in computational geometry that is widely used for analyzing systems of particles. V ORO ++ was released in 2009 and is based on computing the Voronoi cell for each particle individually. Here, we take advantage of modern computer hardware, and extend the original serial version to allow for multithreaded computation of Voronoi cells via the OpenMP application programming interface. We test the performance of the code, and demonstrate that it can achieve parallel efficiencies greater than 95% in many cases. Further, the multithreaded extension follows standard OpenMP programming paradigms, allowing it to be incorporated into other programs. We provide an example of this using the VoroTop software library, performing a multithreaded Voronoi cell topology analysis of up to 102.4 million particles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

High-Performance Computation of Distributed-Memory Parallel 3D Voronoi and Delaunay Tessellation

Computing a Voronoi or Delaunay tessellation from a set of points is a core part of the analysis of many simulated and measured datasets: N-body simulations, molecular dynamics codes, and LIDAR point clouds are just a few examples. Such computational geometry methods are common in data analysis and visualization; but as the scale of simulations and observations surpasses billions of particles, the existing serial and shared-memory algorithms no longer suffice. A distributed-memory scalable parallel algorithm is the only feasible approach. The primary contribution of this paper is a new parallel Delaunay and Voronoi tessellation algorithm that automatically determines which neighbor points need to be exchanged among the subdomains of a spatial decomposition. Other contributions include periodic and wall boundary conditions, comparison of our method using two popular serial libraries, and application to numerous science datasets.

97 MATHEMATICS AND COMPUTING↗