SEARCH · Engineering Papers
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.
Timing data for mixed precision GEMM matrix product operations on several GPU models, including NVIDIA V100 and A100, AMD MI100 and Intel P580. Also data from machine learning model training on this data using Scikit-learn.
This dataset provides three formats of Road Elevation Model (REM) data: 3D road line/polygon GeoPackage (GPKG), road lidar LAZ and COPC LAZ, and road digital surface model (DSM) GeoTIFF. Data are produced from the ~50TB TxGIO (formerly TNRIS) state lidar collections. This dataset is currently organized by maintenance section in each TxDOT district. Computation is done on GPU computing resources at Oak Ridge National Laboratory (ORNL), through a Strategic Partnership Project with UT Austin and an NSF ACCESS computing allocation award that enables fast massive data movement between TACC Corral and ORNL CADES/OLCF using Globus. In addition to this release from ORNL, a copy of this dataset can also be downloaded at https://web.corral.tacc.utexas.edu/nfiedata/road3d/.
Many important chemical and physical phenomena involve dynamics on large number of electronic states. Thus, there is a critical need to develop methods to simulate dynamics in dense manifolds of states. Towards this end, we have: a) developed the multiple cloning in dense manifolds of states (MCDMS) method, which is capable of accurately modeling the quantum mechanical coherence between populations on a large number of electronic states, b) implemented MCDMS into the free, open-source PySpawn software package, c) developed graphics processing unit-accelerated algorithms modeling electron dynamics in light fields via Floquet time-dependent configuration interaction (F-TDCI), and d) critically compared different orbital bases in order to achieve an accurate and efficient F-TDCI expansion. This grant ended in August 2020, when our group moved to from Michigan State University to Stony Brook University, where this project continues under grant number DE-SC0021643.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Application developers are partnering with supercomputing experts and hardware vendors to ready a stable of mission-critical applications for the next generation of computing architectures.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
The scientific goal of the ExaWind project is to advance our fundamental understanding of the flow physics governing whole wind plant performance, including wake formation, complex terrain impacts, and turbine-turbine-interaction effects. The primary application codes in the ExaWind environment are Nalu-Wind, an unstructured-grid computational fluid dynamics (CFD) code, AMR-Wind, a structured-grid CFD code, and OpenFAST, a whole-turbine simulation code. In this poster we present the current status of the ExaWind software stack in the context of the modeling and simulation capabilities when the project started in 2016.
Alpha particles diffusion due to charge changes in a magnetized plasma is studied. Analytical calculations and numerical simulations are employed to show that this process can be very important in the pedestal-edge-SOL regions. This is the first study that presents clear evidence of the importance of atomic processes on the diffusion of alpha particles. A simple 1D model that includes inelastic collisions with plasma species, “cold” neutrals, and partially ionized species was employed. The code, which follows the exact particle orbits and includes the effect of inelastic collisions via a Monte Carlo type random process, runs on a graphic processor unit (GPU). The analytical and numerical results show excellent agreement when a uniform background (plasma and cold species) is assumed. The simulations also show that the gradients in the density of the plasma and cold species, which are large and opposite in the edge region, produce an inward flux of alpha particles. Calculations of the alpha particles flux reaching the walls or divertor plates should include these processes.
The process of sol–gel synthesis was applied to obtain LiMn{sub 1.5}M{sub 0.5}O{sub 4} (M=Al, Mg, Ni, Fe) and LiMn{sub 2}O{sub 4}/TiO{sub 2} nanopowders. The samples were characterized by following methods: X-ray diffraction (XRD), scanning electron microscopy (SEM/EDX), X-ray photoelectron spectroscopy (XPS) and SQUID magnetometry. XPS was used to examine the chemical composition and oxidation state of manganese, in particular the Mn{sup 3+}/Mn{sup 4+} ratio from the deconvolution of the complex Mn3p lines. The size of the grains and crystallites were independently obtained from SEM images and XRD patterns, respectively. In all the cases a critical interplay of electronic (Mn{sup 3+}/Mn{sup 4+} ratio), structural (unit cell volume) and magnetic properties was observed depending on the synthesis process. - Graphical abstract: SEM image of Li{sub 0.79}Ni{sub 0.41}Mn{sub 1.35}O{sub 4.45} sample. Display Omitted - Highlights: • LiMn{sub 1.5}M{sub 0.5}O{sub 4} (M=Al, Mg, Ni, Fe) and LiMn{sub 2}O{sub 4}/TiO{sub 2} obtained by sol–gel method. • XRD method was used to determine the crystal structure. • SEM/EDX imaging have been done. • XPS electronic structure was examined and discussed. • Experimental effective magnetic moment and the calculated one were compared.
Purpose: The purpose of this work is to develop a new patient set-up monitoring system using force sensing resistor (FSR) sensors that can confirm pressure of contact surface and evaluate its feasibility. Methods: In this study, we focused on develop the patient set-up monitoring system to compensate for the limitation of existing optical based monitoring system, so the developed system can inform motion in the radiation therapy. The set-up monitoring system was designed consisting of sensor units (FSR sensor), signal conditioning devices (USB cable/interface electronics), a control PC, and a developed analysis software. The sensor unit was made by attaching FSR sensor and dispersing pressure sponge to prevent error which is caused by concentrating specific point. Measured signal from the FSR sensor was sampled to arduino mega 2560 microcontroller, transferred to control PC by using serial communication. The measured data went through normalization process. The normalized data was displayed through the developed graphic user interface (GUI) software. The software was designed to display a single sensor unit intensity (maximum 16 sensors) and display 2D pressure distribution (using 16 sensors) according to the purpose. Results: Changes of pressure value according to motion was confirmed by the developed set-up monitoring system. Very small movement such as little physical change in appearance can be confirmed using a single unit and using 2D pressure distribution. Also, the set-up monitoring system can observe in real time. Conclusion: In this study, we developed the new set-up monitoring system using FSR sensor. Especially, we expect that the new set-up monitoring system is suitable for motion monitoring of blind area that is hard to confirm existing optical system and compensate existing optical based monitoring system. As a further study, an integrated system will be constructed through correlation of existing optical monitoring system. 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.
A closed-loop proportional-integral (PI) control software is provided for fully mechanically controlled automated electron microscopic tomography. The software is developed based on Gatan DigitalMicrograph, and is compatible with Zeiss LIBRA 120 transmission electron microscope. However, it can be expanded to other TEM instrument with modification. The software consists of a graphical user interface, a digital PI controller, an image analyzing unit, and other drive units (i.e.: image acquire unit and goniometer drive unit). During a tomography data collection process, the image analyzing unit analyzes both the accumulated shift and defocus value of the latest acquired image, and provides the results to the digital PI controller. The digital PI control compares the results with the preset values and determines the optimum adjustments of the goniometer. The goniometer drive unit adjusts the spatial position of the specimen according to the instructions given by the digital PI controller for the next tilt angle and image acquisition. The goniometer drive unit achieves high precision positioning by using a backlash elimination method. The major benefits of the software are: 1) the goniometer drive unit keeps pre-aligned/optimized beam conditions unchanged and achieves position tracking solely through mechanical control; 2) the image analyzing unit relies on only historical data and therefore does not require additional images/exposures; 3) the PI controller enables the system to dynamically track the imaging target with extremely low system error.
Molecular dynamics simulation is a powerful tool to simulate and analyze complex physical processes and phenomena at atomic characteristic for predicting the natural time-evolution of a system of atoms. Precise simulation of physical processes has strong requirements both in the simulation size and computing timescale. Therefore, finding available computing resources is crucial to accelerate computation. However, a tremendous computational resource (GPGPU) are recently being utilized for general purpose computing due to its high performance of floating-point arithmetic operation, wide memory bandwidth and enhanced programmability. As for the most time-consuming component in MD simulation calculation during the case of studying liquid metal solidification processes, this paper presents a fine-grained spatial decomposition method to accelerate the computation of update of neighbor lists and interaction force calculation by take advantage of modern graphics processors units (GPU), enlarging the scale of the simulation system to a simulation system involving 10 000 000 atoms. In addition, a number of evaluations and tests, ranging from executions on different precision enabled-CUDA versions, over various types of GPU (NVIDIA 480GTX, 580GTX and M2050) to CPU clusters with different number of CPU cores are discussed. The experimental results demonstrate that GPU-based calculations are typically 9∼11 times faster than the corresponding sequential execution and approximately 1.5∼2 times faster than 16 CPU cores clusters implementations. On the basis of the simulated results, the comparisons between the theoretical results and the experimental ones are executed, and the good agreement between the two and more complete and larger cluster structures in the actual macroscopic materials are observed. Moreover, different nucleation and evolution mechanism of nano-clusters and nano-crystals formed in the processes of metal solidification is observed with large-sized system.
This paper describes the design of data acquisition system (DAQ) that is connected to a PC and development of a feedback control system that maintains the coolant temperature of the process at a desired set point using a digital controller system based on the graphical programming language. The paper will provide details about the data acquisition unit, shows the implementation of the controller, and present test results. (authors)
The BioC2G tool provides an interface for running technoeconomic analyses and life-cycle assessments of biofuel and bioproduct production pathways. Models for the pathways are currently built into the tool: limonene, limonane, bisabolene, bisabolane, ethanol, isoprenol, DMCO, and HEFA. Additionally, a "Custom" option is available for analyzing a bioproduction pathway not included among the built-in examples. Users must supply key product properties and process parameters. Three types of model runs are available in the tool: minimum selling price (MSP), water consumption, and greenhouse gas (GHG) emissions. Running the MSP model yields a breakdown of MSP by major process stage of production, along with a a table of estimated capital expenditures (CAPEX) and annual operating expenditures (OPEX). Running the water consumption and GHG models yields a breakdown of water consumed and carbon emissions respectively, per unit of end product. A breakdown of these metrics by major process stage is also provided. Model run results can be viewed in the web interface numerically and graphically, as well as downloaded in CSV format. Detailed documentation on model methodology and assumptions is also available for download.