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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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At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Cosmogenic background rejection for the sterile neutrino search with the Short-Baseline Neutrino Program Far Detector

As the Short-Baseline Neutrino Program Far Detector, the ICARUS liquid argon time-projection chamber will operate at shallow depth and therefore be exposed to the full surface flux of cosmic rays. This poses a problematic background to the sterile neutrino search. A direct way to reject this background is to surround the cryostat with a detector capable of tagging incident cosmic muons with high efficiency, the Cosmic Ray Tagging System (CRT). I have worked to develop the CRT detector hardware and the simulation and reconstruction software. This system, currently undergoing installation, is approximately 25% commissioned and taking data. I have developed a powerful method for cosmogenic background rejection utilizing the CRT and Photon Detection System. Results from a simulation based study, informed by CRT data, demonstrate the power of the technique in rejecting cosmogenic events with little adverse impact on the neutrino sample.

Hilgenberg, Christopher Michael↗
DOE OSTI2020

Quantum Approximate Optimization Algorithm in Python

This is software in Python that simulates the quantum approximate optimization algorithm (QAOA) as described in https://arxiv.org/abs/1411.4028. The software has customization that speeds up simulation and provides interface to the Rapid Optimization Library (ROL) developed at Sandia. SAND2019-8935 M 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.

von Winckel, Gregory↗
DOE OSTI2013

Vertical-Axis Wind Turbine Mesh Generator

VAWTGen is a mesh generator for creating a finite element beam mesh of arbitrary vertical-axis wind turbines (VAWT). The software accepts input files specifying tower and blade structural and aerodynamic descriptions and constructs a VAWT using a minimal set of inputs. VAWTs with an arbitrary number of blades can be constructed with or without a central tower. Strut connections between the tower and blades can be specified in an arbitrary manner. The software also facilitates specifying arbitrary joints between structural components and concentrated structural tenns (mass and stiffness). The output files which describe the VAWT configuration are intended to be used with the Offshore Wind ENergy Simulation (OWENS) Toolkit software for structural dynamics analysis of VAWTs. Furthermore, VAWTGen is useful for visualizing output from the OWENS analysis software.

Owens, BrianC.↗
DOE OSTI2016

Quantifying the Impact of Nanoparticle Coatings and Non-uniformities on XPS Analysis: Gold/silver Core-shell Nanoparticles

Abstract or short description: Spectral modeling of photoelectrons can serve as a valuable tool when combined with X-ray photoelectron spectroscopy (XPS) analysis. Herein, a new version of the NIST Simulation of Electron Spectra for Surface Analysis (SESSA 2.0) software, capable of directly simulating spherical multilayer NPs, was applied to model citrate stabilized Au/Ag-core/shell nanoparticles (NPs). The NPs were characterized using XPS and scanning transmission electron microscopy (STEM) to determine the composition and morphology of the NPs. The Au/Ag-core/shell NPs were observed to be polydispersed in size, non-circular, and contain off-centered Au-cores. Using the average NP dimensions determined from STEM analysis, SESSA spectral modeling indicated that washed Au/Ag-core shell NPs were stabilized with a 0.8 nm l

Core-shell nanoparticles↗
NASA NTRS1971

Antenna control system

The objective of the antenna control system is to utilize the analysis and software developed for the simulated 40 foot antenna system to produce a unified software package providing complete computer control of the 40 foot antenna. The control system comprises a position programmer, scan generator and a digital controller.

Source record↗
DOE OSTI2017

Process Modeling and Validation for Metal Big Area Additive Manufacturing

Metal Big Area Additive Manufacturing (mBAAM) is a new additive manufacturing (AM) technology based on the metal arc welding. A continuously fed metal wire is melted by an electric arc that forms between the wire and the substrate, and deposited in the form of a bead of molten metal along the predetermined path. Objects are manufactured one layer at a time starting from the base plate. The final properties of the manufactured object are dependent on its geometry and the metal deposition path, in addition to depending on the basic welding process parameters. Computational modeling can be used to accelerate the development of the mBAAM technology as well as a design and optimization tool for the actual manufacturing process. We have developed a finite element method simulation framework for mBAAM using the new features of software ABAQUS. The computational simulation of material deposition with heat transfer is performed first, followed by the structural analysis based on the temperature history for predicting the final deformation and stress state. In this formulation, we assume that two physics phenomena are coupled in only one direction, i.e. the temperatures are driving the deformation and internal stresses, but their feedback on the temperatures is negligible. The experiment instrumentation (measurement types, sensor types, sensor locations, sensor placements, measurement intervals) and the measurements are presented. The temperatures and distortions from the simulations show good correlation with experimental measurements. Ongoing modeling work is also briefly discussed.

Simunovic, Srdjan↗
NASA NTRS1997

SimGraph: A Flight Simulation Data Visualization Workstation

Today's modern flight simulation research produces vast amounts of time sensitive data, making a qualitative analysis of the data difficult while it remains in a numerical representation. Therefore, a method of merging related data together and presenting it to the user in a more comprehensible format is necessary. Simulation Graphics (SimGraph) is an object-oriented data visualization software package that presents simulation data in animated graphical displays for easy interpretation. Data produced from a flight simulation is presented by SimGraph in several different formats, including: 3-Dimensional Views, Cockpit Control Views, Heads-Up Displays, Strip Charts, and Status Indicators. SimGraph can accommodate the addition of new graphical displays to allow the software to be customized to each user s particular environment. A new display can be developed and added to SimGraph without having to design a new application, allowing the graphics programmer to focus on the development of the graphical display. The SimGraph framework can be reused for a wide variety of visualization tasks. Although it was created for the flight simulation facilities at NASA Langley Research Center, SimGraph can be reconfigured to almost any data visualization environment. This paper describes the capabilities and operations of SimGraph.

Kaplan, Joseph A.↗
DOE OSTI2022

Anomaly Detection in Gamma Spectra Using Hopfield Neural Network with B-SAT and Grover’s Algorithm on a Quantum Computing Simulator

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. In principle, gamma radiation sources can be detected and identified by their unique spectral lines. However, detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. In recent prior work, we have developed a Hopfield Neural Network (HNN) in conjunction with an image processing algorithm to detect a weak signal anomaly hidden among the highly fluctuating background spectra. The objective of this work is to explore quantum computing methods to increase the speed of HNN. The approach is based on the Grover’s search algorithm in conjunction with a 3-SAT problem formalism. The Grover’s algorithm is implemented on a quantum computing simulator using Qiskit software. Performance of HNN algorithm is benchmarked using search data from an environmental screening campaign, where the anomaly is a subset of measurements containing a 137 Cs source. Results indicate that using Grover’s algorithm on a quantum simulator reduces runtime of HNN by two orders of magnitude.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Optimizing a magnitude-limited spectroscopic training sample for photometric classification of supernovae

ABSTRACT In preparation for photometric classification of transients from the Legacy Survey of Space and Time (LSST) we run tests with different training data sets. Using estimates of the depth to which the 4-m Multi-Object Spectroscopic Telescope (4MOST) Time Domain Extragalactic Survey (TiDES) can classify transients, we simulate a magnitude-limited sample reaching rAB ≈ 22.5 mag. We run our simulations with the software snmachine, a photometric classification pipeline using machine learning. The machine-learning algorithms struggle to classify supernovae when the training sample is magnitude limited, in contrast to representative training samples. Classification performance noticeably improves when we combine the magnitude-limited training sample with a simulated realistic sample of faint high-redshift supernovae observed from larger spectroscopic facilities; the algorithms’ range of average area under receiver operator characteristic curve (AUC) scores over 10 runs increases from 0.547–0.628 to 0.946–0.969 and purity of the classified sample reaches 95 per cent in all runs for two of the four algorithms. By creating new, artificial light curves using the augmentation software avocado, we achieve a purity in our classified sample of 95 per cent in all 10 runs performed for all machine-learning algorithms considered. We also reach a highest average AUC score of 0.986 with the artificial neural network algorithm. Having ‘true’ faint supernovae to complement our magnitude-limited sample is a crucial requirement in optimization of a 4MOST spectroscopic sample. However, our results are a proof of concept that augmentation is also necessary to achieve the best classification results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Physical optics simulations with PHASE for SwissFEL beamlines

PHASE is a software tool for physical optics simulation based on the stationary phase approximation method. The code is under continuous development since about 20 years and has been used for instance for fundamental studies and ray tracing of various beamlines at the Swiss Light Source. Along with the planning for SwissFEL a new hard X-ray free electron laser under construction, new features have been added to permit practical performance predictions including diffraction effects which emerge with the fully coherent source. We present the application of the package on the example of the ARAMIS 1 beamline at SwissFEL. The X-ray pulse calculated with GENESIS and given as an electrical field distribution has been propagated through the beamline to the sample position. We demonstrate the new features of PHASE like the treatment of measured figure errors, apertures and coatings of the mirrors and the application of Fourier optics propagators for free space propagation.

43 PARTICLE ACCELERATORS↗
NASA NTRS1992

Automated Simulation For Analysis And Design

Design Assistant Workstation (DAWN) software being developed to facilitate simulation of qualitative and quantitative aspects of behavior of life-support system in spacecraft, chemical-processing plant, heating and cooling system of large building, or any of variety of systems including interacting process streams and processes. Used to analyze alternative design scenarios or specific designs of such systems. Expert system will automate part of design analysis: reason independently by simulating design scenarios and return to designer with overall evaluations and recommendations.

Cantwell, E.↗
DOE OSTI2017

LArSoft: Toolkit for Simulation, Reconstruction and Analysis of Liquid Argon TPC Neutrino Detectors

LArSoft is a set of detector-independent software tools for the simulation, reconstruction and analysis of data from liquid argon (LAr) neutrino experiments The common features of LAr time projection chambers (TPCs) enable sharing of algorithm code across detectors of very dierent size and conguration. LArSoft is currently used in production simulation and reconstruction by the ArgoNeuT, DUNE, LArIAT, MicroBooNE, and SBND experiments. The software suite oers a wide selection of algorithms and utilities, including those for associated photo-detectors and the handling of auxiliary detectors outside the TPCs. Available algorithms cover the full range of simulation and reconstruction, from raw waveforms to high- level reconstructed objects, event topologies and classication. The common code within LArSoft is contributed by adopting experiments, which also provide detector-specic geometry descriptions, and code for the treatment of electronic signals. LArSoft is also a collaboration of experiments, Fermilab and associated software projects which cooperate in setting requirements, priorities, and schedules. In this talk, we outline the general architecture of the software and the interaction with external libraries and detector-specic code. We also describe the dynamics of LArSoft software development between the contributing experiments, the projects supporting the software infrastructure LArSoft relies on, and the core LArSoft support project.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

Scout: high-performance heterogeneous computing made simple

Researchers must often write their own simulation and analysis software. During this process they simultaneously confront both computational and scientific problems. Current strategies for aiding the generation of performance-oriented programs do not abstract the software development from the science. Furthermore, the problem is becoming increasingly complex and pressing with the continued development of many-core and heterogeneous (CPU-GPU) architectures. To acbieve high performance, scientists must expertly navigate both software and hardware. Co-design between computer scientists and research scientists can alleviate but not solve this problem. The science community requires better tools for developing, optimizing, and future-proofing codes, allowing scientists to focus on their research while still achieving high computational performance. Scout is a parallel programming language and extensible compiler framework targeting heterogeneous architectures. It provides the abstraction required to buffer scientists from the constantly-shifting details of hardware while still realizing higb-performance by encapsulating software and hardware optimization within a compiler framework.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2014

Upgrading Custom Simulink Library Components for Use in Newer Versions of Matlab

The Spaceport Command and Control System (SCCS) at Kennedy Space Center (KSC) is a control system for monitoring and launching manned launch vehicles. Simulations of ground support equipment (GSE) and the launch vehicle systems are required throughout the life cycle of SCCS to test software, hardware, and procedures to train the launch team. The simulations of the GSE at the launch site in conjunction with off-line processing locations are developed using Simulink, a piece of Commercial Off-The-Shelf (COTS) software. The simulations that are built are then converted into code and ran in a simulation engine called Trick, a Government off-the-shelf (GOTS) piece of software developed by NASA. In the world of hardware and software, it is not uncommon to see the products that are utilized be upgraded and patched or eventually fade away into an obsolete status. In the case of SCCS simulation software, Matlab, a MathWorks product, has released a number of stable versions of Simulink since the deployment of the software on the Development Work Stations in the Linux environment (DWLs). The upgraded versions of Simulink has introduced a number of new tools and resources that, if utilized fully and correctly, will save time and resources during the overall development of the GSE simulation and its correlating documentation. Unfortunately, simply importing the already built simulations into the new Matlab environment will not suffice as it will produce results that may not be expected as they were in the version that is currently being utilized. Thus, an upgrade execution plan was developed and executed to fully upgrade the simulation environment to one of the latest versions of Matlab.

Matlab Simulation↗
DOE OSTI2020

Distribution System Segmented Model Simplification with Independent Dynamically Changing End-Use Loads

With more emerging technologies in power distribution systems, to support quasi-static time-series (QSTS) simulation over short time frames, accurately modeling the dynamic behavior of end-use load under various conditions is im- portant. However, time and cost can be a burden for the QSTS simulation of thousands of houses representing dynamic load behaviors on large distribution feeders. There are two main contributions of this paper in order to reduce the QSTS simulation complexity. First, the paper presents a method to stochasti- cally model the dynamic behavior of end-use load for QSTS simulations. Second, using the stochastically modeled load behavior as an input to a distribution sys- tem, and building on our previous QSTS simulation simplification/acceleration method that relies on uniform load behavior, this paper presents a segment substitution approach for the simplification of distribution system models with independent dynamically changing end-use loads. Our numerical results show that compared to GridLAB-D, a software tool that simulates end-use load be- havior through physical models, the proposed stochastic modeling approach achieved an 89.3% simulation time reduction for end-use loads, while accurately capturing the temporally changing total load behavior. Moreover, the QSTS simulation of a large test distribution system through OpenDSS showed that the proposed simplification method decreased the feeder simulation time by a factor of three at less than 0.3% voltage error. Compared to our previous method with independent dynamic loads, the voltage error is reduced by a factor of four.

Power distribution system modeling, stochastic pro↗
DOE OSTI2018

PyBioNetFit

Systems biology models written in the BioNetGen language often contain parameters that must be fit based on experimental data. PyBioNetFit is a software tool designed to fit parameters of BioNetGen models. The user is expected to provide a BioNetGen model that contains unknown parameters, along with one or more text files containing experimental data. PyBioNetFit will perform a series of calls to the BioNetGen simulator using different parameter sets, to identify the parameter set that best fits the data. The parameter search is dictated by the user's choice of one of several metaheuristic optimization algorithms, including differential evolution, particle swarm optimization, scatter search, and simulated annealing. The software supports parallelized computing on multi-core computers and on computing clusters. We expect this software to be a useful tool for researchers designing BioNetGen models in collaboration with experimentalists.

Mitra, Eshan↗