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.
This is an opensource library for benchmarking the system's GPU mixed precision capabilities. The software calculates solution of the system of linear equation in 64bit accuracy using mixed precision techniques and iterative refinement. Original benchmark designed is done by ICL, and it is name HPL-MxP (HPL-AI)
SAND2023-05829O ROMNet is a toolbox built on the Tensorflow library for training reduced-order, neural operator surrogate models. The software is used for training reduced order neural operator surrogate models for dynamical systems applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
This library builds a framework for defending ML models against adversarial attacks. The library will be developed at various stages leading to publication and software release at each stage. We employ tensor decomposition strategies as preprocessing stages for the first stage to provide robustness against the prominent adversarial noise. In the second stage, we develop a latent noise generator capable of generating novel adversarial noise that threatens the existing state-of-the-art defense strategy. In the third stage, we develop a UNSUP-GAN model, where the generator is trained to denoise against latent noise and most adversarial noises. This generator can provide a robust adversarial attack against any unseen attack.
IPyOverlay is a Python library that provides several IPyWidget components for use within the Jupyter software ecosystem. These components add novel UI capabilities to enable details-on-demand interaction paradigms by providing the ability to render widgets on top of other widgets with arbitrary and controllable positioning. This capability enables adding click-and-draggable overlay windows containing other widgets, right-click context menus, and more complex tooltip functionality.
Optimization is a key tool for scientific and engineering applications; however, in the presence of models affected by uncertainty, the optimization formulation needs to be extended to consider statistics of the quantity of interest. Optimization under uncertainty (OUU) deals with this endeavor and requires uncertainty quantification analyses at several design locations; i.e., its overall computational cost is proportional to the cost of performing a forward uncertainty analysis at each design location. An OUU workflow has two main components: an inner loop strategy for the computation of statistics of the quantity of interest, and an outer loop optimization strategy tasked with finding the optimal design, given a merit function based on the inner loop statistics. Here, in this work, we propose to alleviate the cost of the inner loop uncertainty analysis by leveraging the so-called multilevel Monte Carlo (MLMC) method, which is able to allocate resources over multiple models with varying accuracy and cost. The resource allocation problem in MLMC is formulated by minimizing the computational cost given a target variance for the estimator. We consider MLMC estimators for statistics usually employed in OUU workflows and solve the corresponding allocation problem. For the outer loop, we consider a derivative-free optimization strategy implemented in the SNOWPAC library; our novel strategy is implemented and released in the Dakota software toolkit. We discuss several numerical test cases to showcase the features and performance of our approach with respect to its Monte Carlo single fidelity counterpart.
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.
The purpose of this data services request was to demonstrate integration of the Atmospheric Radiation Measurement (ARM) User Facility’s “met” datastreams with time series data from other earth science data sources using the BASIN-3D data synthesis software tool. BASIN-3D is an open-source Python library that enables researchers to integrate data across configured public and private data sources. It provides a common query language for researchers to request measurement locations and time series data based on specified locations, variables, time period, statistics, aggregation, and data quality. BASIN-3D acquires the data that match the query from each configured data source and translates the results into harmonized vocabularies, thus reducing researchers' data-wrangling effort. In addition, because the queries are executed on demand, researchers can easily regenerate their synthesized data sets as new data and/or data updates become available, eliminating one-off data products. BASIN-3D can output data using a variety of different data structures for end-user applications including Python pandas data frames and hdf5 output formats.
Engineering software development was automated using an expert system (rule-based) approach. The use of this technology offers benefits not available from current software development and maintenance methodologies. A workstation was built with a library or program data base with methods for browsing the designs stored; a system for graphical specification of designs including a capability for hierarchical refinement and definition in a graphical design system; and an automated code generation capability in FORTRAN. The workstation was then used in a demonstration with examples from an attitude control subsystem design for the space station. Documentation and recommendations are presented.
A software environment has been developed to assist in analysis and visualization of numerical outputs from NCAR's thermospheric general circulation models. The codes produce vector graphics, raster imagery, and time dependent animation of model results, with provision for comparison with empirical models and relevant data from satellite and ground based instruments. Separate programs are executed on the NCAR CRAY YMP8/864 and HAO divisional Sun workstations, providing both large volume highspeed batch and custom interactive computing environments. The visualization system assembles a suite of existing software packages including NCAR Graphics, IDL, netCDF, and the Xt intrinsics library with the Athena widget set.
The Spatial Data Management System (SDMS) is a testbed for retrieval and display of spatially related material. SDMS permits the linkage of large graphical display objects with detail displays and explanations of its smaller components. SDMS combines UNIX workstations, MIT's X Window system, TCP/IP and WAIS information retrieval technology to prototype a means of associating aggregate data linked via spatial orientation. SDMS capitalizes upon and extends previous accomplishments of the Software Technology Branch in the area of Virtual Reality and Automated Library Systems.
By 1997, the Thomas Jefferson National Accelerator Facility will collect over one Terabyte of raw information per day of Accelerator operation from three concurrently operating Experimental Halls. When post-processing is included, roughly 250 TB of raw and formatted experimental data will be generated each year. By the year 2000, a total of one Petabyte will be stored on-line. Critical to the experimental program at Jefferson Lab (JLab) is the networking and computational capability to collect, store, retrieve, and reconstruct data on this scale. The design criteria include support of a raw data stream of 10-12 MB/second from Experimental Hall B, which will operate the CEBAF (Continuous Electron Beam Accelerator Facility) Large Acceptance Spectrometer (CLAS). Keeping up with this data stream implies design strategies that provide storage guarantees during accelerator operation, minimize the number of times data is buffered allow seamless access to specific data sets for the researcher, synchronize data retrievals with the scheduling of postprocessing calculations on the data reconstruction CPU farms, as well as support the site capability to perform data reconstruction and reduction at the same overall rate at which new data is being collected. The current implementation employs state-of-the-art StorageTek Redwood tape drives and robotics library integrated with the Open Storage Manager (OSM) Hierarchical Storage Management software (Computer Associates, International), the use of Fibre Channel RAID disks dual-ported between Sun Microsystems SMP servers, and a network-based interface to a 10,000 SPECint92 data processing CPU farm. Issues of efficiency, scalability, and manageability will become critical to meet the year 2000 requirements for a Petabyte of near-line storage interfaced to over 30,000 SPECint92 of data processing power.
Architecture Adaptive Computing Environment (aCe) is a software system that includes a language, compiler, and run-time library for parallel computing. aCe was developed to enable programmers to write programs, more easily than was previously possible, for a variety of parallel computing architectures. Heretofore, it has been perceived to be difficult to write parallel programs for parallel computers and more difficult to port the programs to different parallel computing architectures. In contrast, aCe is supportable on all high-performance computing architectures. Currently, it is supported on LINUX clusters. aCe uses parallel programming constructs that facilitate writing of parallel programs. Such constructs were used in single-instruction/multiple-data (SIMD) programming languages of the 1980s, including Parallel Pascal, Parallel Forth, C*, *LISP, and MasPar MPL. In aCe, these constructs are extended and implemented for both SIMD and multiple- instruction/multiple-data (MIMD) architectures. Two new constructs incorporated in aCe are those of (1) scalar and virtual variables and (2) pre-computed paths. The scalar-and-virtual-variables construct increases flexibility in optimizing memory utilization in various architectures. The pre-computed-paths construct enables the compiler to pre-compute part of a communication operation once, rather than computing it every time the communication operation is performed.
The DOE Standard Canister Demonstration Project includes the development of an internal support structure (ISS) for the 4.6-m long and 45.7-cm diameter canister. This study presents structural evaluations, criticality safety assessments, and dose rate calculations conducted within the scope of the ISS design process to support smooth canister loading operations and to ensure safe storage, transportation, and disposal of Peach Bottom 1 Core II (PB2) and Fort St. Vrain (FSV) SNF, currently stored at the CPP-603 facility of the INL. The ISS includes a 316L stainless steel basket that holds twelve PB2 SNF rods. Further, six individual, 78.7-cm long, 316L stainless steel columns are equally spaced and welded to the inner canister wall at the lower end of the shell. These columns represent the FSV basket and can hold one FSV SNF element. An A92014 T6 aluminum spacer disc is bolted to the bottom plate of the PB2 basket to vertically restrain the FSV SNF element after the PB2 basket is placed inside the canister on top of the FSV basket. The structural evaluations of the ISS followed applicable ASME BPVC.III.3 guidelines and included finite element (FE) analyses of the PB2 basket structure; analyses of welds and bolds; buckling analyses of selected components, and acceptability assessments of the expected basket deformations under loading operations. The criticality safety assessments used the Monte Carlo N-Particle (MCNP) software architecture version 6.2 including ENDF/B-V continuous energy cross-section libraries, considering intact SNF in a single storage overpack or two multi-storage overpack configurations, and intact or failed SNF configured for disposal. The dose rate computations are based on source terms taken from the DOE Spent Fuel Database. The isotopic composition was decay corrected for the year 2022 using the ORIGEN module in the SCALE suite. A 19-group photon spectrum and 27-group neutron-source spectra were generated and used in MCNP to calculate estimated dose-equivalent rates, both on DOE Standard Canister contact and at a radial distance of from the canister surface. The results of this study indicate a structurally sound system that can uphold its criticality safety functions throughout its intended operational phases. Further, they increase confidence that sufficient radiological protection is technically achievable.
Fispact-II is a code system and library database for modelling activation-transmutation processes, depletion-burn-up, time dependent inventory and radiation damage source terms caused by nuclear reactions and decays. The Fispact-II code, written in object-style Fortran, follows the evolution of material irradiated by neutrons, alphas, gammas, protons, or deuterons, and provides a wide range of derived radiological output quantities to satisfy most needs for nuclear applications. It can be used with any ENDF-compliant group library data for nuclear reactions, particle-induced and spontaneous fission yields, and radioactive decay (including but not limited to TENDL-2015, ENDF/B-VII.1, JEFF-3.2, JENDL-4.0u, CENDL-3.1 processed into fine-group-structure files, GEFY-5.2 and UKDD-16), as well as resolved and unresolved resonance range probability tables for self-shielding corrections and updated radiological hazard indices. The code has many novel features including: extension of the energy range up to 1 GeV; additional neutron physics including self-shielding effects, temperature dependence, thin and thick target yields; pathway analysis; and sensitivity and uncertainty quantification and propagation using full covariance data. The latest ENDF libraries such as TENDL encompass thousands of target isotopes. Nuclear data libraries for Fispact-II are prepared from these using processing codes PREPRO, NJOY and CALENDF. These data include resonance parameters, cross sections with covariances, probability tables in the resonance ranges, PKA spectra, kerma, dpa, gas and radionuclide production and energy-dependent fission yields, supplemented with all 27 decay types. All such data for the five most important incident particles are provided in evaluated data tables. The Fispact-II simulation software is described in detail in this paper, together with the nuclear data libraries. The Fispact-II system also includes several utility programs for code-use optimisation, visualisation and production of secondary radiological quantities. Included in the paper are summaries of results from the suite of verification and validation reports available with the code.
FermiLib is an open source software package designed to facilitate the development and testing of algorithms for simulations of fermionic systems on quantum computers. Fermionic simulations represent an important application of early quantum devices with a lot of potential high value targets, such as quantum chemistry for the development of new catalysts. This software strives to provide a link between the required domain expertise in specific fermionic applications and quantum computing to enable more users to directly interface with, and develop for, these applications. It is an extensible Python library designed to interface with the high performance quantum simulator, ProjectQ, as well as application specific software such as PSI4 from the domain of quantum chemistry. Such software is key to enabling effective user facilities in quantum computation research.
We introduce Mitiq, a Python package for error mitigation on noisy quantum computers. Error mitigation techniques can reduce the impact of noise on near-term quantum computers with minimal overhead in quantum resources by relying on a mixture of quantum sampling and classical post-processing techniques. Mitiq is an extensible toolkit of different error mitigation methods, including zero-noise extrapolation, probabilistic error cancellation, and Clifford data regression. The library is designed to be compatible with generic backends and interfaces with different quantum software frameworks. We describe Mitiq using code snippets to demonstrate usage and discuss features and contribution guidelines. We present several examples demonstrating error mitigation on IBM and Rigetti superconducting quantum processors as well as on noisy simulators.
This dataset comprises of the input files and other files required for Advanced Terrestrial Simulator (ATS) simulations at 7 catchments across the continental United States. ATS is an integrated surface-subsurface hydrology model. We include Jupyter notebooks (within scripts folder) for individual catchments showing information (including data sources, river network, soil, geology, landuse types etc.) on preparing the machine readable input files. ATS observation output files are provided in the output folder. Figures and analyses (.xlsx sheets) are also provided. The catchments include, Taylor River Upstream (Colorado); (b) Cossatot River (Arkansas); (c) Panther Creek (Alabama); (d) Little Tennessee River (North Carolina and Georgia); (e) Mayo River (Virginia); (f) Flat Brook (New Jersey); (g) Neversink River headwaters (New York). Readme files are provided inside the directories providing more details. Files types include: .xml, .h5, .xlsx, .png, .ipynb, .py, .nc, .txt. All of the files types can be accessed by open source software, details on software requirements are following: .xml (any text editors including notepad and textedit), .h5 (in python using hdf libraries), .xlsx (WPS Office Spreadsheets, OpenOffice Calc, LibreOffice Calc, Microsoft Office etc.), .png (any image viewer), .ipynb (Jupyter notebook), .py (any text editors including notepad and textedit), .nc (using python or other open source software).
In this age of the computer, more and more business firms are automating their operations for increased efficiency in a great variety of jobs, from simple accounting to managing inventories, from precise machining to analyzing complex structures. In the interest of national productivity, NASA is providing assistance both to longtime computer users and newcomers to automated operations. Through a special technology utilization service, NASA saves industry time and money by making available already developed computer programs which have secondary utility. A computer program is essentially a set of instructions which tells the computer how to produce desired information or effect by drawing upon its stored input. Developing a new program from scratch can be costly and time-consuming. Very often, however, a program developed for one purpose can readily be adapted to a totally different application. To help industry take advantage of existing computer technology, NASA operates the Computer Software Management and Information Center (COSMIC)(registered TradeMark),located at the University of Georgia. COSMIC maintains a large library of computer programs developed for NASA, the Department of Defense, the Department of Energy and other technology-generating agencies of the government. The Center gets a continual flow of software packages, screens them for adaptability to private sector usage, stores them and informs potential customers of their availability.