Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Graphics”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Codiscovering graphical structure and functional relationships within data: A Gaussian Process framework for connecting the dots

Most problems within and beyond the scientific domain can be framed into one of the following three levels of complexity of function approximation. Type 1: Approximate an unknown function given input/output data. Type 2: Consider a collection of variables and functions, some of which are unknown, indexed by the nodes and hyperedges of a hypergraph (a generalized graph where edges can connect more than two vertices). Given partial observations of the variables of the hypergraph (satisfying the functional dependencies imposed by its structure), approximate all the unobserved variables and unknown functions. Type 3: Expanding on Type 2, if the hypergraph structure itself is unknown, use partial observations of the variables of the hypergraph to discover its structure and approximate its unknown functions. These hypergraphs offer a natural platform for organizing, communicating, and processing computational knowledge. While most scientific problems can be framed as the data-driven discovery of unknown functions in a computational hypergraph whose structure is known (Type 2), many require the data-driven discovery of the structure (connectivity) of the hypergraph itself (Type 3). We introduce an interpretable Gaussian Process (GP) framework for such (Type 3) problems that does not require randomization of the data, access to or control over its sampling, or sparsity of the unknown functions in a known or learned basis. Its polynomial complexity, which contrasts sharply with the super-exponential complexity of causal inference methods, is enabled by the nonlinear ANOVA capabilities of GPs used as a sensing mechanism.

Science & Technology - Other Topics↗
DOE OSTI2017

Cosmological histories in bimetric gravity: a graphical approach

The bimetric generalization of general relativity has been proven to be able to give an accelerated background expansion consistent with observations. Apart from the energy densities coupling to one or both of the metrics, the expansion will depend on the cosmological constant contribution to each of them, as well as the three parameters describing the interaction between the two metrics. Even for fixed values of these parameters can several possible solutions, so called branches, exist. Different branches can give similar background expansion histories for the observable metric, but may have different properties regarding, for example, the existence of ghosts and the rate of structure growth. In this paper, we outline a method to find viable solution branches for arbitrary parameter values. We show how possible expansion histories in bimetric gravity can be inferred qualitatively, by picturing the ratio of the scale factors of the two metrics as the spatial coordinate of a particle rolling along a frictionless track. A particularly interesting example discussed is a specific set of parameter values, where a cosmological dark matter background is mimicked without introducing ghost modes into the theory.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Sequenceserver: A Modern Graphical User Interface for Custom BLAST Databases

Comparing newly obtained and previously known nucleotide and amino-acid sequences underpins modern biological research. BLAST is a well-established tool for such comparisons but is challenging to use on new data sets. We combined a user-centric design philosophy with sustainable software development approaches to create Sequenceserver, a tool for running BLAST and visually inspecting BLAST results for biological interpretation. Sequenceserver uses simple algorithms to prevent potential analysis errors and provides flexible text-based and visual outputs to support researcher productivity. Our software can be rapidly installed for use by individuals or on shared servers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Resident Block-Structured Adaptive Mesh Refinement on Thousands of Graphics Processing Units, In: 2015 44th International Conference on Parallel Processing

Block-structured adaptive mesh refinement (AMR) is a technique that can be used when solving partial differential equations to reduce the number of cells necessary to achieve the required accuracy in areas of interest. These areas (shock fronts, material interfaces, etc.) are recursively covered with finer mesh patches that are grouped into a hierarchy of refinement levels. Despite the potential for large savings in computational requirements and memory usage without a corresponding reduction in accuracy, AMR adds overhead in managing the mesh hierarchy, adding complex communication and data movement requirements to a simulation. In this paper, we describe the design and implementation of a resident GPU-based AMR library, including: the classes used to manage data on a mesh patch, the routines used for transferring data between GPUs on different nodes, and the data-parallel operators developed to coarsen and refine mesh data. We validate the performance and accuracy of our implementation using three test problems and two architectures: an 8 node cluster, and 4,196 nodes of Oak Ridge National Laboratory's Titan supercomputer. Our GPU-based AMR hydrodynamics code performs up to 4.87× faster than the CPU-based implementation, and is scalable on 4,196 K20x GPUs using a combination of MPI and CUDA.

Computer Science↗
DOE OSTI2014

WE-E-BRE-05: Ensemble of Graphical Models for Predicting Radiation Pneumontis Risk

Purpose: We propose a prior knowledge-based approach to construct an interaction graph of biological and dosimetric radiation pneumontis (RP) covariates for the purpose of developing a RP risk classifier. Methods: We recruited 59 NSCLC patients who received curative radiotherapy with minimum 6 month follow-up. 16 RP events was observed (CTCAE grade ≥2). Blood serum was collected from every patient before (pre-RT) and during RT (mid-RT). From each sample the concentration of the following five candidate biomarkers were taken as covariates: alpha-2-macroglobulin (α2M), angiotensin converting enzyme (ACE), transforming growth factor β (TGF-β), interleukin-6 (IL-6), and osteopontin (OPN). Dose-volumetric parameters were also included as covariates. The number of biological and dosimetric covariates was reduced by a variable selection scheme implemented by L1-regularized logistic regression (LASSO). Posterior probability distribution of interaction graphs between the selected variables was estimated from the data under the literature-based prior knowledge to weight more heavily the graphs that contain the expected associations. A graph ensemble was formed by averaging the most probable graphs weighted by their posterior, creating a Bayesian Network (BN)-based RP risk classifier. Results: The LASSO selected the following 7 RP covariates: (1) pre-RT concentration level of α2M, (2) α2M level mid- RT/pre-RT, (3) pre-RT IL6 level, (4) IL6 level mid-RT/pre-RT, (5) ACE mid-RT/pre-RT, (6) PTV volume, and (7) mean lung dose (MLD). The ensemble BN model achieved the maximum sensitivity/specificity of 81%/84% and outperformed univariate dosimetric predictors as shown by larger AUC values (0.78∼0.81) compared with MLD (0.61), V20 (0.65) and V30 (0.70). The ensembles obtained by incorporating the prior knowledge improved classification performance for the ensemble size 5∼50. Conclusion: We demonstrated a probabilistic ensemble method to detect robust associations between RP covariates and its potential to improve RP prediction accuracy. Our Bayesian approach to incorporate prior knowledge can enhance efficiency in searching of such associations from data. The authors acknowledge partial support by: 1) CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council (Grant number: 432290) and 2) The Terry Fox Foundation Strategic Training Initiative for Excellence in Radiation Research for the 21st Century (EIRR21)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-DE-201-11: Sensitivity and Specificity of Verification Methods Based On Total Reference Air Kerma (TRAK) Or On User Provided Dose Points for Graphically Planned Skin HDR Brachytherapy

Purpose: To investigate the sensitivity and specificity of a novel verification methodology for image-guided skin HDR brachytherapy plans using a TRAK-based reasonableness test, compared to a typical manual verification methodology. Methods: Two methodologies were used to flag treatment plans necessitating additional review due to a potential discrepancy of 3 mm between planned dose and clinical target in the skin. Manual verification was used to calculate the discrepancy between the average dose to points positioned at time of planning representative of the prescribed depth and the expected prescription dose. Automatic verification was used to calculate the discrepancy between TRAK of the clinical plan and its expected value, which was calculated using standard plans with varying curvatures, ranging from flat to cylindrically circumferential. A plan was flagged if a discrepancy >10% was observed. Sensitivity and specificity were calculated using as a criteria for true positive that >10% of plan dwells had a distance to prescription dose >1 mm different than prescription depth (3 mm + size of applicator). All HDR image-based skin brachytherapy plans treated at our institution in 2013 were analyzed. Results: 108 surface applicator plans to treat skin of the face, scalp, limbs, feet, hands or abdomen were analyzed. Median number of catheters was 19 (range, 4 to 71) and median number of dwells was 257 (range, 20 to 1100). Sensitivity/specificity were 57%/78% for manual and 70%/89% for automatic verification. Conclusion: A check based on expected TRAK value is feasible for irregularly shaped, image-guided skin HDR brachytherapy. This test yielded higher sensitivity and specificity than a test based on the identification of representative points, and can be implemented with a dedicated calculation code or with pre-calculated lookup tables of ideally shaped, uniform surface applicators.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

DaMoScope and its internet graphics for the visual control of adjusting mathematical models describing experimental data

The experience of using the dynamic atlas of the experimental data and mathematical models of their description in the problems of adjusting parametric models of observable values depending on kinematic variables is presented. The functional possibilities of an image of a large number of experimental data and the models describing them are shown by examples of data and models of observable values determined by the amplitudes of elastic scattering of hadrons. The Internet implementation of an interactive tool DaMoScope and its interface with the experimental data and codes of adjusted parametric models with the parameters of the best description of data are schematically shown. The DaMoScope codes are freely available.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Tensor Algebra Library for NVidia Graphics Processing Units

This is a general purpose math library implementing basic tensor algebra operations on NVidia GPU accelerators. This software is a tensor algebra library that can perform basic tensor algebra operations, including tensor contractions, tensor products, tensor additions, etc., on NVidia GPU accelerators, asynchronously with respect to the CPU host. It supports a simultaneous use of multiple NVidia GPUs. Each asynchronous API function returns a handle which can later be used for querying the completion of the corresponding tensor algebra operation on a specific GPU. The tensors participating in a particular tensor operation are assumed to be stored in local RAM of a node or GPU RAM. The main research area where this library can be utilized is the quantum many-body theory (e.g., in electronic structure theory).

Liakh, Dmitry↗
DOE OSTI2019

WinGridder-A graphic grid generator for TOUGH2 simulators (WinGridder) v3.0

WINGRIDDER V3.0 is a Windows-based software for designing and generating numerical grids for numerical simulators that are based on the "integral finite difference" or the "control volume" numerical scheme (e.g., TOUGH2, Pruess et al., 1996). The user can design and generate grid that properly represents the stratigraphic features, inclined faults, and repository. WINGRIDDER V3.0 is an upgrade from WINGRIDDER V2.0. This revision includes testable requirements as listed in the Requirements Document (RD), 10024-RD-3.0-00, Section 2. With new features, WINGRIDDER V3.0 adds the ability to generate a multiple-interactive-continuum (MINC) grid.

Pan, Lehua↗