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At least 253 records · Page 14

All sources NASA NTRS DOE OSTI

DOE OSTI2016

A tracking system to calculate patient skin dose in real-time during neurointerventional procedures using a biplane x-ray imaging system

Purpose: Neurovascular interventional procedures using biplane fluoroscopic imaging systems can lead to increased risk of radiation-induced skin injuries. The authors developed a biplane dose tracking system (Biplane-DTS) to calculate the cumulative skin dose distribution from the frontal and lateral x-ray tubes and display it in real-time as a color-coded map on a 3D graphic of the patient for immediate feedback to the physician. The agreement of the calculated values with the dose measured on phantoms was evaluated. Methods: The Biplane-DTS consists of multiple components including 3D graphic models of the imaging system and patient, an interactive graphical user interface, a data acquisition module to collect geometry and exposure parameters, the computer graphics processing unit, and functions for determining which parts of the patient graphic skin surface are within the beam and for calculating dose. The dose is calculated to individual points on the patient graphic using premeasured calibration files of entrance skin dose per mAs including backscatter; corrections are applied for field area, distance from the focal spot and patient table and pad attenuation when appropriate. The agreement of the calculated patient skin dose and its spatial distribution with measured values was evaluated in 2D and 3D for simulated procedure conditions using a PMMA block phantom and an SK-150 head phantom, respectively. Dose values calculated by the Biplane-DTS were compared to the measurements made on the phantom surface with radiochromic film and a calibrated ionization chamber, which was also used to calibrate the DTS. The agreement with measurements was specifically evaluated with variation in kVp, gantry angle, and field size. Results: The dose tracking system that was developed is able to acquire data from the two x-ray gantries on a biplane imaging system and calculate the skin dose for each exposure pulse to those vertices of a patient graphic that are determined to be in the beam. The calculations are done in real-time with a typical graphic update time of 30 ms and an average vertex separation of 3 mm. With appropriate corrections applied, the Biplane-DTS was able to determine the entrance dose within 6% and the spatial distribution of the dose within 4% compared to the measurements with the ionization chamber and film for the SK150 head phantom. The cumulative dose for overlapping fields from both gantries showed similar agreement. Conclusions: The Biplane-DTS can provide a good estimate of the peak skin dose and cumulative skin dose distribution during biplane neurointerventional procedures. Real-time display of this information should help the physician manage patient dose to reduce the risk of radiation-induced skin injuries.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

WE-A-17A-05: Differences in Applicator Configuration and Dwell Loading Between Standard and Image-Guided Tandem and Ring (T and R) HDR Brachytherapy

Purpose: To investigate differences in: (i) relative location of the tandem and the ring compared to a rigid standard applicator model; and (ii) relative loading and changes in loading pattern between standard and image-guided planning. Methods: All T and R insertions performed in 2013 in our institution under CT- or MR-guidance were analyzed. Standard plans were generated using library applicator models with a fixed relationship between ring and tandem, standardized uniform dwell loading and normalization to point A. The graphic plans and the associated standard-plan dwell configurations were compared: the rings were rigidly registered, and the residual tandem shift, rotation and maximum distance between plan tandem dwell and corresponding model tandem dwell were calculated. The normalization ratio (NR = the ratio of graphic versus standard-plan total reference air kerma [TRAK]), the general loading difference (GLD = the difference between graphic and standard ratios of the tandem versus the ring TRAK), and the percent standard deviation (SD% = SD/mean) of the tandem and the ring TRAK for the graphic plan (all standard-plans SD% = 0) were calculated. Results: 71 T and R were analyzed. Residual tandem shift, rotation and maximum corresponding dwell distance were 1.2±0.8mm (0.4±0.4mm lateral, 0.9±0.8mm craniocaudal, 0.4±0.3mm anterior-posterior), 2.3±1.9deg and 3.4±2.3mm. NR was 0.86±0.11 indicating a lower overall loading of the graphic compared to the standard plans. GLD was -0.12±0.16 indicating a modest increased ring loading relative to the tandem in the graphic plans. SD% was 2.1±1.6% for tandem and 2.8±1.9% for ring, indicating small deviations from uniform loading. Conclusion: Variability in the relative locations of the tandem and the ring necessitates the independent registration of each component model for accurate digitization. Our clinical experience suggests that graphically planned T and R results on average in a lower total dose to the patient, and in an increased relative loading of the ring component.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Chroma Shift and Gamut Shape: Going Beyond Average Color Fidelity and Gamut Area

Though sometimes referred to as a two-measure system for evaluating color rendition, IES TM-30-15 includes other key components that go beyond the high-level average values IES Rf and IES Rg. This article focuses on the Color Vector Graphic and Local Chroma Shift (IES Rcs,hj), discussing the calculation methods for these evaluation tools and providing context for the interpretation of the values. It also presents alternatives for quantifying the same characteristics, which can inform the development of future measures. The Color Vector Graphic (CVG) is a visual representation of hue and chroma shifts across different hues. It quickly communicates complex information about how object colors will be rendered by a light source, although it is difficult or impossible to use for writing a specification. CVGs demonstrate that increases in chroma for certain hues sometimes means a decrease in chroma for other hues, and illustrates hue shifts for intermediate colors. The combination of shifts over different hues can be referred to as gamut shape. Complementing this information are the IES Rcs,hj values, which quantify the average relative chroma shift for samples in each of the 16 hue-angle bins (j) specified in IES TM-30-15. Unlike measures of average color fidelity and gamut area, gamut shape and hue-specific chroma shift are new concepts with no directly-comparable historical references. It will be critical to incorporate the Color Vector Graphic and Local Chroma Shift values into practice because they capture information about color rendition that is impossible to describe with average measures (such as CIE Ra, IES Rf, or IES Rg), but that is critical to understanding human evaluations of color quality in architectural environments.

Chroma Shift↗

DOE OSTI2015

Acceleration of GPU-based Krylov solvers via data transfer reduction

Krylov subspace iterative solvers are often the method of choice when solving large sparse linear systems. At the same time, hardware accelerators such as graphics processing units continue to offer significant floating point performance gains for matrix and vector computations through easy-to-use libraries of computational kernels. However, as these libraries are usually composed of a well optimized but limited set of linear algebra operations, applications that use them often fail to reduce certain data communications, and hence fail to leverage the full potential of the accelerator. In this study, we target the acceleration of Krylov subspace iterative methods for graphics processing units, and in particular the Biconjugate Gradient Stabilized solver that significant improvement can be achieved by reformulating the method to reduce data-communications through application-specific kernels instead of using the generic BLAS kernels, e.g. as provided by NVIDIA’s cuBLAS library, and by designing a graphics processing unit specific sparse matrix-vector product kernel that is able to more efficiently use the graphics processing unit’s computing power. Furthermore, we derive a model estimating the performance improvement, and use experimental data to validate the expected runtime savings. Finally, considering that the derived implementation achieves significantly higher performance, we assert that similar optimizations addressing algorithm structure, as well as sparse matrix-vector, are crucial for the subsequent development of high-performance graphics processing units accelerated Krylov subspace iterative methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

An MCNP6 Version of the Visual Editor - Paper 2

The Visual Editor is a graphical user interface for working with the MCNP computer code developed at Los Alamos National Laboratory. It consists of a graphical user interface written in C++ that is linked directory to the MCNP Fortran code. Work on the original Visual Editor started in 1992 and was first published in 1993. The original version of the Visual Editor was created on Unix/Linux operating systems and was linked to the MCNP computer code. The Visual Editor was adapted to the Windows operating system in 1999. In 2008 the Visual Editor was adapted to work with the MCNPX computer code. This paper discusses the latest upgrade of the Visual Editor to be compatible with the MCNP6 computer code. Two graphical user interfaces have been created, the Visual MCNP6 Plotter and the Visual MCNP6 Editor. The Visual MCNP6 Plotter includes all of the standard plotting features available in the default MCNP6 plotting package including geometry plotting, tally plotting, cross section plotting, mesh tally plotting and weight window mesh plotting. The Visual MNCP6 Editor has additional capabilities to allow for the creation of MCNP input files with graphical tools. The Visual MCNP6 Editor allows user to create and modify the input file within the Editor. Modifications are not allowed in the Visual MCNP6 Plotter. Both graphical user interfaces allow for advanced plotting features including 3D geometry plots and particle track plotting. Complete details on these tools along with their current status can be found at the Visual Editor website (www.mcnpvised.com). (author)

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2013

Recovery Act: Advanced Interaction, Computation, and Visualization Tools for Sustainable Building Design

Current building energy simulation technology requires excessive labor, time and expertise to create building energy models, excessive computational time for accurate simulations and difficulties with the interpretation of the results. These deficiencies can be ameliorated using modern graphical user interfaces and algorithms which take advantage of modern computer architectures and display capabilities. To prove this hypothesis, we developed an experimental test bed for building energy simulation. This novel test bed environment offers an easy-to-use interactive graphical interface, provides access to innovative simulation modules that run at accelerated computational speeds, and presents new graphics visualization methods to interpret simulation results. Our system offers the promise of dramatic ease of use in comparison with currently available building energy simulation tools. Its modular structure makes it suitable for early stage building design, as a research platform for the investigation of new simulation methods, and as a tool for teaching concepts of sustainable design. Improvements in the accuracy and execution speed of many of the simulation modules are based on the modification of advanced computer graphics rendering algorithms. Significant performance improvements are demonstrated in several computationally expensive energy simulation modules. The incorporation of these modern graphical techniques should advance the state of the art in the domain of whole building energy analysis and building performance simulation, particularly at the conceptual design stage when decisions have the greatest impact. More importantly, these better simulation tools will enable the transition from prescriptive to performative energy codes, resulting in better, more efficient designs for our future built environment.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2013

Sustain

Source record↗

DOE OSTI2017

CUDA Computation of the Feynman Distribution

In 2006, NVIDIA Corporation introduced the Computer Unified Device Architecture (CUDA) for C, C++, and Fortran programming languages. The CUDA parallel computing platform uses the Graphics Processing Unit (GPU) of NVIDIA graphics card, and it is designed for parallel computations. In these computations, the same algorithms are executed on the data in parallel. The GPU contains many Streaming Multiprocessors (SM) that can independently execute blocks of threads. A thread is a sequence of serial programmed instructions. The SM executes threads in groups of 32 and a group of 32 threads is called warp. The threads within a block can be synchronized and have access to a shared memory that is visible only to them. Conversely, blocks of threads cannot be synchronized and have access only to the global memory of the graphics card. This memory is called device memory and is independent of the host memory controlled by the Central Processing Unit (CPU). A single thread has access to a local memory (register) that is not visible to any other thread. The part of the program that is executed on the graphics card is called kernel. Each thread of the kernel has a unique identification index that is accessible by the in-built variable threadIdx; the latter is a 3-component vector. A threads block can contain up to 1024 threads. Blocks of threads have a unique identification index that is accessible by the in-built variable blockIdx; the latter is a 3-component vector. The in-built variable blockDim contains the number of threads per block; this variable is a 3-component vector. Threads and blocks represent different levels of parallelism; a kernel is executed as a grid of blocks of threads. Figure 1 illustrates a grid of thread blocks for a GPU with 2 SM. A SM can execute multiple blocks of threads in parallel; a block of threads is executed on a single SM. A GPU can execute multiple kernels concurrently. This work has used the Quadro M5000 graphics card with the following technical specifications: - 2048 cores with 861 MHz frequency, - 16 streaming multiprocessors, - 5.2 trillion transistors, - 8.2 Gb device memory, - 64 kb register memory (per thread), - 48 kb shared memory (per block) - 211.6 GB/s memory bandwidth, and - 3.5 GFLOPS floating point performance.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Multiple response optimization for higher dimensions in factors and responses

When optimizing a product or process with multiple responses, a two-stage Pareto front approach is a useful strategy to evaluate and balance trade-offs between different estimated responses to seek optimum input locations for achieving the best outcomes. After objectively eliminating non-contenders in the first stage by looking for a Pareto front of superior solutions, graphical tools can be used to identify a final solution in the second subjective stage to compare options and match with user priorities. Until now, there have been limitations on the number of response variables and input factors that could effectively be visualized with existing graphical summaries. We present novel graphical tools that can be more easily scaled to higher dimensions, in both the input and response spaces, to facilitate informed decision making when simultaneously optimizing multiple responses. A key aspect of these graphics is that the potential solutions can be flexibly sorted to investigate specific queries, and that multiple aspects of the solutions can be simultaneously considered. As a result, recommendations are made about how to evaluate the impact of the uncertainty associated with the estimated response surfaces on decision making with higher dimensions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

The Generality of the GUGA MRCI Approach in COLUMBUS for Treating Complex Quantum Chemistry

The core part of the program system COLUMBUS allows highly efficient calculations using variational multireference (MR) methods in the framework of configuration interaction with single and double excitations (MR-CISD) and averaged quadratic coupled-cluster calculations (MR-AQCC), based on uncontracted sets of configurations and the graphical unitary group approach (GUGA). The availability of analytic MR-CISD and MR-AQCC energy gradients and analytic nonadiabatic couplings for MR-CISD enables exciting applications including, e.g., investigations of π-conjugated biradicaloid compounds, calculations of multitudes of excited states, development of diabatization procedures, and furnishing the electronic structure information for on-the-fly surface nonadiabatic dynamics. With fully variational uncontracted spin-orbit MRCI, COLUMBUS provides a unique possibility of performing high-level calculations on compounds containing heavy atoms up to lanthanides and actinides. Crucial for carrying out all of these calculations effectively is the availability of an efficient parallel code for the CI step. Configuration spaces of several billion in size now can be treated quite routinely on standard parallel computer clusters. Emerging developments in COLUMBUS, including the all configuration mean energy multiconfiguration self-consistent field method and the graphically contracted function method, promise to allow practically unlimited configuration space dimensions. Spin density based on the GUGA approach, analytic spin-orbit energy gradients, possibilities for local electron correlation MR calculations, development of general interfaces for nonadiabatic dynamics, and MRCI linear vibronic coupling models conclude this overview.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

Optimization of the fractionated irradiation scheme considering physical doses to tumor and organ at risk based on dose–volume histograms

Purpose: Radiotherapy of solid tumors has been performed with various fractionation regimens such as multi- and hypofractionations. However, the ability to optimize the fractionation regimen considering the physical dose distribution remains insufficient. This study aims to optimize the fractionation regimen, in which the authors propose a graphical method for selecting the optimal number of fractions (n) and dose per fraction (d) based on dose–volume histograms for tumor and normal tissues of organs around the tumor. Methods: Modified linear-quadratic models were employed to estimate the radiation effects on the tumor and an organ at risk (OAR), where the repopulation of the tumor cells and the linearity of the dose-response curve in the high dose range of the surviving fraction were considered. The minimization problem for the damage effect on the OAR was solved under the constraint that the radiation effect on the tumor is fixed by a graphical method. Here, the damage effect on the OAR was estimated based on the dose–volume histogram. Results: It was found that the optimization of fractionation scheme incorporating the dose–volume histogram is possible by employing appropriate cell surviving models. The graphical method considering the repopulation of tumor cells and a rectilinear response in the high dose range enables them to derive the optimal number of fractions and dose per fraction. For example, in the treatment of prostate cancer, the optimal fractionation was suggested to lie in the range of 8–32 fractions with a daily dose of 2.2–6.3 Gy. Conclusions: It is possible to optimize the number of fractions and dose per fraction based on the physical dose distribution (i.e., dose–volume histogram) by the graphical method considering the effects on tumor and OARs around the tumor. This method may stipulate a new guideline to optimize the fractionation regimen for physics-guided fractionation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Rasterization with Data-Parallel Primitives

Parallel rasterization can suffer from race conditions during fragment generation, which is traditionally addressed by using specialized hardware accessible via vendor graphics APIs. Unfortunately, graphics APIs are increasingly problematic on high-performance computers, either because they are not provided or because of concerns about dependencies with in situ visualization. In response, we present a hardware-agnostic rasterization algorithm that handles race conditions using only data-parallel primitives (DPPs), enabling efficient rendering on HPC systems without graphics API dependencies and aligning with recent efforts to deliver visualization software with DPPs. Our evaluation consists of three phases: (1) evaluating portability across different CPU and GPU architectures, (2) evaluating competitiveness with a community standard, and (3) evaluating performance across varying workloads and available parallelism. The supporting experiments run on both AMD and NVIDIA GPUs, considering data sets as large as 460 million triangles and 160 million pixels. While performance generally falls short of graphics API baselines, it achieves interactive frame rates on most workloads. As a result, we conclude our approach is a viable solution for rasterization on high-performance computers since our approach is portably performant across different architectures without the need for specialized vendor support.

Buckley, Makani [University of Oregon] (ORCID:0009↗

DOE OSTI2016

Data graphing methods, articles of manufacture, and computing devices

Data graphing methods, articles of manufacture, and computing devices are described. In one aspect, a method includes accessing a data set, displaying a graphical representation including data of the data set which is arranged according to a first of different hierarchical levels, wherein the first hierarchical level represents the data at a first of a plurality of different resolutions which respectively correspond to respective ones of the hierarchical levels, selecting a portion of the graphical representation wherein the data of the portion is arranged according to the first hierarchical level at the first resolution, modifying the graphical representation by arranging the data of the portion according to a second of the hierarchal levels at a second of the resolutions, and after the modifying, displaying the graphical representation wherein the data of the portion is arranged according to the second hierarchal level at the second resolution.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Solar Decathlon Celebrates 20 Years of Building Impact

The U.S. Department of Energy Solar Decathlon® is a collegiate competition that has inspired students worldwide to enter the clean energy workforce since its inception. Celebrating its 20th anniversary in 2022, the Solar Decathlon has challenged more than 25,000 students to create efficient, affordable buildings powered by renewables, while promoting student innovation, STEM education, and workforce development opportunities in the buildings industry. Compelling graphics, videos, and visuals are being developed to launch a 20th anniversary campaign in January 2022. These graphics include an interactive 20th anniversary infographic, a "Solar Decathlon - By the Numbers" video, and a graphic highlighting the diverse group of more than 25,000 past participants. In presenting these graphics at the ACEEE summer 2022 panel, attendees will be exposed to the latest communications techniques to apply to their own work. The Solar Decathlon invests in compelling visuals to recruit and inspire an imaginative and diverse group of participants each year - something that organizations of all sizes in the energy efficiency sector also need to do as they recruit for new talent. The Virtual Village of the 2020 Build Challenge homes (with more than 11,000 unique views) and the map of past competition houses highlight the competition's emphasis on multimedia that connects with competitors and the general public. Using more than 4,400 publicly available photos, including engaging virtual event snapshots with Department of Energy leaders, the Solar Decathlon captures the innovate ideas of the Build Challenge and Design Challenge teams in a way that everyone can understand.

collegiate competition↗

DOE OSTI2021

A Range and Performance Optimized Version of the Computer-Aided Speckle Interferometry Algorithm for Real-Time Displacement-Strain Field Monitoring

Abstract This work presents an optimized implementation of the Computer-Aided Speckle Interferometry algorithm which enables full-field determination of displacements and strains on commodity Graphics Processing Units at high resolution and frame rates. By combining careful control of the average speckle size in a laser speckle pattern with a simple sampling rate conversion scheme, a compact representation of the optical speckle is achieved. This allows for optimal use of Graphics Processing Unit architecture with robust range extension. The optimal mapping of the Computer-Aided Speckle Interferometry algorithm to Graphics Processing Unit architecture is shown in detail, and a straightforward method for disambiguating large displacements is illustrated. Lastly, this paper demonstrates a two-step subimage-tapering modification to the original algorithm that enables robust range enhancement while maintaining resolution. Results from numerical simulations on synthetic speckle patterns are shown, and runtime performance metrics are provided, with performance ranging up to 60 frames per second in some cases. The method is suitable for interactive experimental mechanics research, process and testing or any application where real-time high-resolution displacement-strain monitoring is needed. A .NET Framework class library enabling the incorporation of the algorithm into 3rd -party applications is available for download.

42 ENGINEERING↗

DOE OSTI2014

A convex pseudolikelihood framework for high dimensional partial correlation estimation with convergence guarantees

Sparse high dimensional graphical model selection is a topic of much interest in modern day statistics. A popular approach is to apply l1-penalties to either parametric likelihoods, or regularized regression/pseudolikelihoods, with the latter having the distinct advantage that they do not explicitly assume Gaussianity. As none of the popular methods proposed for solving pseudolikelihood-based objective functions have provable convergence guarantees, it is not clear whether corresponding estimators exist or are even computable, or if they actually yield correct partial correlation graphs. We propose a new pseudolikelihood-based graphical model selection method that aims to overcome some of the shortcomings of current methods, but at the same time retain all their respective strengths. In particular, we introduce a novel framework that leads to a convex formulation of the partial covariance regression graph problem, resulting in an objective function comprised of quadratic forms. The objective is then optimized via a coordinate wise approach. The specific functional form of the objective function facilitates rigorous convergence analysis leading to convergence guarantees; an important property that cannot be established by using standard results, when the dimension is larger than the sample size, as is often the case in high dimensional applications. These convergence guarantees ensure that estimators are well defined under very general conditions and are always computable. In addition, the approach yields estimators that have good large sample properties and also respect symmetry. Furthermore, application to simulated and real data, timing comparisons and numerical convergence is demonstrated. We also present a novel unifying framework that places all graphical pseudolikelihood methods as special cases of a more general formulation, leading to important insights.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Learning planar Ising models

Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a collection of random variables within some tractable family of graphical models. In this paper, we focus on the class of planar Ising models, for which exact inference is tractable using techniques of statistical physics. Based on these techniques and recent methods for planarity testing and planar embedding, we propose a greedy algorithm for learning the best planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. Finally, we demonstrate our method in simulations and for two applications: modeling senate voting records and identifying geo-chemical depth trends from Mars rover data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Simulation Exploration through Immersive Parallel Planes

We present a visualization-driven simulation system that tightly couples systems dynamics simulations with an immersive virtual environment to allow analysts to rapidly develop and test hypotheses in a high-dimensional parameter space. To accomplish this, we generalize the two-dimensional parallel-coordinates statistical graphic as an immersive 'parallel-planes' visualization for multivariate time series emitted by simulations running in parallel with the visualization. In contrast to traditional parallel coordinate's mapping the multivariate dimensions onto coordinate axes represented by a series of parallel lines, we map pairs of the multivariate dimensions onto a series of parallel rectangles. As in the case of parallel coordinates, each individual observation in the dataset is mapped to a polyline whose vertices coincide with its coordinate values. Regions of the rectangles can be 'brushed' to highlight and select observations of interest: a 'slider' control allows the user to filter the observations by their time coordinate. In an immersive virtual environment, users interact with the parallel planes using a joystick that can select regions on the planes, manipulate selection, and filter time. The brushing and selection actions are used to both explore existing data as well as to launch additional simulations corresponding to the visually selected portions of the input parameter space. As soon as the new simulations complete, their resulting observations are displayed in the virtual environment. This tight feedback loop between simulation and immersive analytics accelerates users' realization of insights about the simulation and its output.

97 MATHEMATICS AND COMPUTING↗