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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

A Virtual Reality Visualization Tool for Neuron Tracing

Tracing neurons in large-scale microscopy data is crucial to establishing a wiring diagram of the brain, which is needed to understand how neural circuits in the brain process information and generate behavior. Automatic techniques often fail for large and complex datasets, and connectomics researchers may spend weeks or months manually tracing neurons using 2D image stacks. We present a design study of a new virtual reality (VR) system, developed in collaboration with trained neuroanatomists, to trace neurons in microscope scans of the visual cortex of primates. We hypothesize that using consumer-grade VR technology to interact with neurons directly in 3D will help neuroscientists better resolve complex cases and enable them to trace neurons faster and with less physical and mental strain. We discuss both the design process and technical challenges in developing an interactive system to navigate and manipulate terabyte-sized image volumes in VR. Using a number of different datasets, we demonstrate that, compared to widely used commercial software, consumer-grade VR presents a promising alternative for scientists.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

On the Formalization of Development and Assessment Process for Digital Twins in the Nearly Autonomous Management and Control System

In recent years, the autonomous control system has been encouraged in advanced reactors for restoring economic viability, simplifying the operation and maintenance, and enabling remote-site power generations [1]. Since the reactor is expected to be operated for a long period of time with a limited number of individuals onsite, it is recommended that the autonomous control system should have access to very realistic models of the state of processes in the whole lifecycle, together with these process behaviors in interaction with their environment in the real world. As a result, digital twin (DT) technology is suggested in autonomous control systems. DT is defined as a digital representation of a physical object or system, which contains a record for the histories of loads, operation and maintenance status, predictions for the near-term transient of important state variables, and decision-making process [2]. Since machine learning (ML) can recognize patterns within a complex system in real-time applications, it has been used to build DTs in the autonomous control systems for advanced reactors. Meanwhile, due to the rareness of operation data in accident scenarios, the development and assessment of DTs is expected to be mainly driven by simulations. Although the capability and feasibility of ML-based DTs are recognized in improving the safety and efficiency of reactor control, a major concern from the regulatory commission and the nuclear industry is whether the information from a DT is developed and assessed in accordance with expectation and requirements by the target decision. Such concerns not only affect the acceptance criteria for DTs, but also values that can be extracted from DTs and autonomous control system during operations. Inspired by the success of formal methods in improving the reliability and robustness of computer programming and software development, it is suggested that the development and assessment process (DAP) for both separate DTs and integral control system should be formalized in a transparent, consistent, and improvable manner. In this study, a digital-twin development and assessment process (DT-DAP) is proposed by adapting the evaluation model development and assessment process (EMDAP) [3] to requirements by the autonomous control system, ML algorithms, and DT technology. To demonstrate the framework, a baseline nearly autonomous management and control (NAMAC) system with ML-based DTs for diagnosis and prognosis is developed and assessed based on the framework. It is found that with selected testing methods and techniques, the DT-DAP can help identify errors in DTs and NAMAC which would otherwise be left unverified. Meanwhile, it is found that the DT-DAP can improve the DTs and NAMAC by continuously learning and iterating through different elements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Hybrid Optimization Software Suite

The hybrid optimization software suite (HOSS) is a general purpose fully 2D/3D parallel combined finite discrete element (FDEM) code that can be used to simulate problems involving fracture and fragmentation processes, large deformation and large rotations, discrete particle systems, solid-fluid interaction in hydro fracture problems, etc. HOSS uses a hybrid approach that combines finite-element and discrete-element methods with a novel computational fluid dynamics solver. The finite-element method is often used to analyze a material or object and how it responds to stress. The discrete-element method analyzes stresses and displacements in a volume containing a large number of particles, such as grains of sand. Fluid dynamics analyzes the fluid flow inside, around, or through solid domains. With these processes combined, HOSS represents a paradigm shift when it comes to generating accurate simulations of material deformations and failure. HOSS can perform the following: Resolves problems that consist of millions of deforming fracturing, and interacting solid particles; Requires no coupling—it naturally integrates with all regimes of fluid flow; Resolves all regimes of fluid flow, such as Stokes, low/high Reynolds, subsonic/transonic/supersonic/hypersonic, compressible/incompressible, viscid/inviscid, Newtonian/Non-Newtonian and turbulent/laminar flow; Combines all flow regimes in the same solver; Numerically stable for all flow regimes; Naturally combines different flow regimes in the same problem; Possesses material library for fluid behavior; Naturally matches fluid solver to solid solver; Includes non-inertial Eulerian formulation for fluids; Uses highly efficient parallel computing based on the Virtual Parallel Machine, thus enabling easy porting between different parallel architectures, including possible future architectures; Designed specifically for multi-physics problems in research and industry in virtual experimentation format, thereby complementing both theoretical-computational and experimental tools; Can be extended to address millions of deforming solid particles immersed in fluid flowing at all regimes; Can be extended to address biological applications, such as modeling bone fracture or red blood cells in blood plasma

Knight, Earl E.↗
NASA NTRS1999

Sonic Boom Prediction and Minimization of the Douglas Reference OPT5 Configuration

Conventional CFD methods and grids do not yield adequate resolution of the complex shock flow pattern generated by a real aircraft geometry. As a result, a unique grid topology and supersonic flow solver was developed at Northrop Grumman based on the characteristic behavior of supersonic wave patterns emanating from the aircraft. Using this approach, it was possible to compute flow fields with adequate resolution several body lengths below the aircraft. In this region, three-dimensional effects are diminished and conventional two-dimensional modified linear theory (MLT) can be applied to estimate ground pressure signatures or sonic booms. To accommodate real aircraft geometries and alleviate the burdensome grid generation task, an implicit marching multi-block, multi-grid finite-volume Euler code was developed as the basis for the sonic boom prediction methodology. The Thomas two-dimensional extrapolation method is built into the Euler code so that ground signatures can be obtained quickly and efficiently with minimum computational effort suitable to the aircraft design environment. The loudness levels of these signatures can then be determined using a NASA generated noise code. Since the Euler code is a three-dimensional flow field solver, the complete circumferential region below the aircraft is computed. The extrapolation of all this field data from a cylinder of constant radius leads to the definition of the entire boom corridor occurring directly below and off to the side of the aircraft's flight path yielding an estimate for the entire noise "annoyance" corridor in miles as well as its magnitude. An automated multidisciplinary sonic boom design optimization software system was developed during the latter part of HSR Phase 1. Using this system, it was found that sonic boom signatures could be reduced through optimization of a variety of geometric aircraft parameters. This system uses a gradient based nonlinear optimizer as the driver in conjunction with a computationally efficient Euler CFD solver (NIIM3DSB) for computing the three-dimensional near-field characteristics of the aircraft. The intent of the design system is to identify and optimize geometric design variables that have a beneficial impact on the ground sonic boom. The system uses a simple wave drag data format to specify the aircraft geometry. The geometry is internally enhanced and analytic methods are used to generate marching grids suitable for the multi-block Euler solver. The Thomas extrapolation method is integrated into this system, and hence, the aircraft's centerline ground sonic boom signature is also automatically computed for a specified cruise altitude and yields the parameters necessary to evaluate the design function. The entire design system has been automated since the gradient based optimization software requires many flow analyses in order to obtain the required sensitivity derivatives for each design variable in order to converge on an optimal solution. Hence, once the problem is defined which includes defining the objective function and geometric and aerodynamic constraints, the system will automatically regenerate the perturbed geometry, the necessary grids, the Euler solution, and finally the ground sonic boom signature at the request of the optimizer.

Siclari, Michael J.↗
DOE OSTI2020

Phase I Closeout Report: Invoking Artificial Neural Networks to Measure Insider Threat Mitigation

Researchers from Sandia National Laboratories (Sandia) and the University of Texas at Austin (UT) conducted this study to explore the effectiveness of commercial artificial neural network (ANN) software to improve insider threat detection and mitigation (ITDM). This study hypothesized that ANNs could be "trainee to learn patterns of organizational behaviors, detect off-normal (or anomalous) deviations from these patterns, and alert when certain types, frequencies, or quantities of deviations emerge. The ReconaSense ANN system was installed at UT's Nuclear Engineering Teaching Laboratory (NETL) and collected 13,653 access control data points and 694 intrusion sensor data points over a three-month period. Preliminary analysis of this baseline data demonstrated regularized patterns of life in the facility, and that off-normal behaviors are detectable under certain situations -- even for a facility with anticipated highly non-routine, operational behaviors. Completion of this pilot study demonstrated how the ReconaSense ANN could be used to identify expected operational patterns and detect unexpected anomalous behaviors in support of a data-analytic approach to ITDM. While additional studies are needed to fully understand and characterize this system, the results of this initial study are overall very promising for demonstrating a new framework for ITDM utilizing ANNs and data analysis techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

A technique for measuring the quality of an elliptically bent pentaerythritol [PET(002)] crystal

We present a technique for determining the X-ray spectral quality from each region of an elliptically curved PET(002) crystal. The investigative technique utilizes the shape of the crystal rocking curve which changes significantly as the radius of curvature changes. This unique quality information enables the spectroscopist to verify where in the spectral range that the spectrometer performance is satisfactory and where there are regions that would show spectral distortion. A collection of rocking curve measurements for elliptically curved PET(002) has been built up in our X-ray laboratory. The multi-lamellar model from the XOP software has been used as a guide and corrections were applied to the model based upon measurements. But, the measurement of R{sub I} at small radius of curvature shows an anomalous behavior; the multi-lamellar model fails to show this behavior. The effect of this anomalous R{sub I} behavior on an X-ray spectrometer calibration is calculated. It is compared to the multi-lamellar model calculation which is completely inadequate for predicting R{sub I} for this range of curvature and spectral energies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Modeling the direct sun component in buildings using matrix algebraic approaches: Methods and validation

Simulation tools that enable annual energy performance analysis of optically-complex fenestration systems have been widely adopted by the building industry for use in building design, code development, and the development of rating and certification programs for commercially-available shading and daylighting products. The tools rely on a three-phase matrix operation to compute solar heat gains, using as input low-resolution bidirectional scattering distribution function (BSDF) data (10–15° angular resolution; BSDF data define the angle-dependent behavior of light-scattering materials and systems). Measurement standards and product libraries for BSDF data are undergoing development to support solar heat gain calculations. Simulation of other metrics such as discomfort glare, annual solar exposure, and potentially thermal discomfort, however, require algorithms and BSDF input data that more accurately model the spatial distribution of transmitted and reflected irradiance or illuminance from the sun (0.5° resolution). This study describes such algorithms and input data, then validates the tools (i.e., an interpolation tool for measured BSDF data and the five-phase method) through comparisons with ray-tracing simulations and field monitored data from a full-scale testbed. Simulations of daylight-redirecting films, a micro-louvered screen, and venetian blinds using variable resolution, tensor tree BSDF input data derived from interpolated scanning goniophotometer measurements were shown to agree with field monitored data to within 20% for greater than 75% of the measurement period for illuminance-based performance parameters. The three-phase method delivered significantly less accurate results. We discuss the ramifications of these findings on industry and provide recommendations to increase end user awareness of the current limitations of existing software tools and BSDF product libraries.

14 SOLAR ENERGY↗
DOE OSTI2025

ExaCA v2.0: A versatile, scalable, and performance portable cellular automata application for additive manufacturing solidification

The previously established ExaCA software for performance portable alloy grain structure simulation has been updated to better represent the solidification behavior during complex alloy processing conditions, such as those encountered during metal additive manufacturing (AM), and for improved performance and scalability. Here, an extension to the time–temperature history input data format and the core ExaCA algorithm to include an arbitrary number of melting and solidification events yielded improved prediction of texture for various melt pool geometries, expanding the range of AM-relevant conditions that can be accurately simulated. Improved heat transport process simulation coupling, including the creation of large raster datasets from single track time–temperature history data and in-memory coupling with the new, performance portable finite difference code Finch, were also demonstrated in example studies on the effect of multilayer AM microstructure predictions on hatch spacing and cell size, respectively. Additional new features are detailed and demonstrated, including the ability to perform simulations using various interfacial response function forms, execute simulations on state-of-the-art hardware, improved usability through post-processing versatility, and improved strong and weak scaling performance. The performance, physics, and versatility improvements demonstrated here will further enable large-scale studies on AM process–microstructure relationships that were not previously possible. Furthermore, the usability improvements and ability to run coupled AM process–microstructure simulations using the Finch-ExaCA workflow will facilitate broader use of this open-source software by the computational materials community.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Building an open source software ecosystem for cross-disciplinary plasma research and education

Software is crucial to all areas of modern plasma science research. Laboratory plasma physicists use software to interpret plasma diagnostics, analyze experimental results, and glean insights using advanced techniques from data science. Space scientists use software to reduce and understand in situ observations. Numericists use software to simulate the behavior of laboratory, heliospheric, and astrophysical plasmas, and then analyze or visualize the results. Theorists use symbolic manipulation software to perform or check derivations. Cross-disciplinary research and cross-comparisons between experiments, observations, simulations, and theories all require software. Despite our heavy reliance on software, funding agencies have traditionally had few avenues available to support development of general purpose research software infrastructure.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

The Integration of Plant Sample Analysis, Laboratory Studies, and Thermodynamic Modeling to Predict Slag-Matte Equilibria in Nickel Sulfide Converting

The Kalgoorlie Nickel Smelter (KNS) produces low Fe, low Cu nickel matte in its Peirce–Smith converter operations. To inform process development in the plant, new fundamental data are required on the effect of CaO in slag on the distribution of arsenic between slag and matte. A combination of plant sample analysis, high-temperature laboratory experiments, and thermodynamic modeling was carried out to identify process conditions in the converter and to investigate the effect of slag composition on the chemical behavior of the system. The high-temperature experiments involved re-equilibration of industrial matte-slag-lime samples at 1498 K (1225 °C) and P(SO{sub 2}) = 0.12 atm on a magnetite/quartz substrate, rapid quenching in water, and direct measurement of phase compositions using electron probe X-ray microanalysis (EPMA) and laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS). A private thermodynamic database for the Ca-Cu-Fe-Mg-Ni-O-S-Si-(As) system was used together with the FactSage software package to assist in the analysis. Thermodynamic predictions combined with plant sample characterization and the present experimental data provide a quantitative basis for the analysis of the effect of CaO fluxing on the slag-matte thermochemistry during nickel sulfide converting, in particular on the spinel liquidus and the distribution of elements between slag and matte as a function of CaO addition.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Correct Compilation of Concurrent C Code

The CompCert compiler represents a landmark effort in program verification as both a piece of verified software and as a compiler for verified C programs. A key shortcoming of CompCert however is that it does not support multithreaded programs. Prior work to add threads to CompCert has either required major rewrites of parts of the proof or only works for well synchronized programs. The problem is that CompCert’s backward simulation derives from a forward simulation via the determinism of the semantics of intermediate representation languages. This makes the proofs in CompCert easier but also makes them incompatible with standard models of multithreading which are non-deterministic. Here we propose an alternate formulation of CompCert’s proof structure that parameterizes the existing single threaded semantics with nondeterministic behavior generated at the multithreading level. While this is an old trick where program equivalence is concerned, performing it in the context of CompCert is quite subtle. Our approach allows for expressive concurrent semantics and does not require major proof rewrites but still results in a global backward simulation for multithreaded programs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

ADAM: A web platform for graph-based modeling and optimization of supply chains

Modeling and optimization are essential tasks that arise in the analysis and design of supply chains (SCs). SC models are essential for understanding emergent behavior such as transactions between participants, inherent value of products exchanged, as well as impact of externalities (e.g., policy and climate) and of constraints. Unfortunately, most users of SC models have limited expertise in mathematical optimization, and this hinders the adoption of advanced decision-making tools. Here, in this work, we present ADAM, a web platform that enables the modeling and optimization of SCs. ADAM facilitates modeling by leveraging intuitive and compact graph-based abstractions that allow the user to express dependencies between locations, products, and participants. ADAM model objects serve as repositories of experimental, technology, and socio-economic data; moreover, the graph abstractions facilitate the organization and exchange of models and provides a natural framework for education and outreach. Here, we discuss the graph abstractions and software design principles behind ADAM, its key functional features and workflows, and application examples.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2023

NASA GRC ICME Schema for Materials Data Management: An Executive Summary

Integrated Computational Materials Engineering (ICME) has received a growing emphasis in attention due its potential impact on rapid material design, reduction in cost and time to market for new applications, and the promise of ‘fit-for-purpose’ materials coupled with recent advances in high performance computing and material characterization tools. However, for an organization to implement ICME practices for material discovery and design, a series of both technical and cultural challenges must be overcome to foster an environment that enables efficient, traceable, and predictive multiscale simulations of material behavior to enable virtual design of materials. In 2016, NASA sponsored a 2040 Vision study to define the potential 25-year future state required for integrated multiscale modeling of materials and systems to improve both the associated time and cost for aerospace and aeronautical innovation. The study envisions a cyber-physical-social ecosystem of experimentally validated computational models, tools, and techniques, along with the associated digital tapestry, that can enable rapid, optimized, ‘fit-for-purpose’ design of materials, components, and systems. A key requirement for such an ecosystem is the development of a robust information management system for materials across their full lifecycle, including material pedigree, experimental (real) and virtual (simulation) data, developed material models, and the implementation of models in engineering applications, such that process-structure-property-performance relationships can be established, thereby enabling the virtual design and optimization of materials. Such an information management system must be able to effectively capture: i) material information at each length scale; ii) test data and analysis; iii) associated material models; and iv) material and model deployment in engineering applications. These systems must also provide traceability between experimental and virtual representations of the material to ensure, when appropriate, the material digital twin is maintained. Additionally, this robust material information management system must be able to seamlessly connect with both commercial and an organization’s in-house software tools, be they analysis tools, other material databases, product lifecycle management (PLM) or simulation data management (SDM) tools, etc., such that automation of the design and analysis of a material across multiple length scales is possible. In this paper, an executive summary of the NASA GRC ICME Schema for materials information management is presented. The database best practices and schema design philosophy specifically for ICME materials data management and an overview description of each element in the schema is given, along with its associated role in an ICME workflow. Additionally, auxiliary tools that interact with the database and provide judicious automation with regards to importing, exporting, and analyzing materials data are presented. Such tools are critical to an ICME ecosystem, not only for their role in enabling optimization, but also in relieving users of tedious manual tasks, thus helping to promote adoption and combat the cultural challenges organizations face in enabling ICME.

Materials↗
DOE OSTI2018

pysrim: Automation, Analysis, and Plotting of SRIM Calculations

The behavior of ions traveling through a material is of great interest to many fields. For instance, radiation damage in nuclear materials and ion beam modification of materials are most concerned with understanding the formation and evolution of defects along the ion path (Was 2016). Some of the important properties that can be gleaned from investigating the initial damage from the ion include: numbers of interstitials and vacancies produced, energy deposited per unit length to electrons and atomic nuclei, track diameter, and implanted ion profile. These properties enable further simulations and allow computing a common unit of radiation damage dose, displacements per atom (dpa), which can be used to compare irradiation experiments with different ions (Backman et al. 2013) (Stoller et al. 2013). Additionally, the ejection of materials near the surface due to incident ions is important to sputtering and ion-beam analysis techniques, such as elastic recoil detection analysis (ERDA) and secondary ion mass spectrometry (SIMS) (Vickerman and Gilmore 2011). The interaction of ions within a material can be broken into two parts: electronic and nuclear stopping. Electronic stopping is the energy lost from the ion due to inelastic collisions with electrons along its path. Nuclear stopping is the energy lost due to elastic collisions between the ion and atomic nuclei within the material. The Stopping and Range of Ions in Matter (SRIM) code is a well known software in the radiation damage and ion-beam communities that allows the simulation, via Monte Carlo, of ions through a material by modeling the energy transfer through electronic and nuclear stopping (J. F. Ziegler, Ziegler, and Biersack 2010). SRIM was originally developed in 1985 and has had numerous updates on the electronic stopping powers since then, with the nuclear stopping well explained by the ZBL potential (J. F. Ziegler 1988). The executable SRIM is free to use for non-commercial use but the source code is not available to the community despite requests. While SRIM is a scientifically accurate code it does not get updated frequently and has many bugs from a usability standpoint.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Effects of Zr Ion Implantation on Surface Mechanical Properties and Corrosion Resistance of Pure Magnesium

Zirconium (Zr) was implanted into pure Mg by metal vapor vacuum arc (MEVVA) at the dose of 2 × 10{sup 16} ions/cm{sup 2} at room temperature. The surface characteristics of Zr-implanted Mg were analyzed by the Stopping and Range of Ions in Matter software (SRIM) and x-ray photoelectron spectroscopy (XPS), the surface nanohardness and tribological behavior were measured through nanoindentation and a friction-abrasion testing machine, and the corrosion resistance of Zr-implanted Mg was evaluated by electrochemical measurement and immersion test in simulated body fluid (SBF). The results demonstrated that a gradient modified layer composed of MgO, Mg(OH){sub 2}, ZrO{sub 2} and Zr was formed on the near surface of pure Mg and the nanohardness of pure Mg was improved by 48%. Furthermore, the Zr-implanted Mg exhibited a more positive corrosion potential of − 1.43 V (versus SCE) and a lower corrosion current density of 19.9 μA/cm{sup 2}, and localized corrosion was effectively retarded during 24 h immersion in SBF, suggesting that the corrosion resistance of pure Mg was remarkably improved after Zr ion implantation. The mechanisms of surface strengthening and improved corrosion resistance were also discussed in this paper.

36 MATERIALS SCIENCE↗
DOE OSTI2019

FEAA90: Physics-based Creep Simulation of Thick Section Welds in High Temperature and Pressure Applications

Welded microstructures of ?’-strengthened, nickel-based alloy, 740H, contain significant microstructural heterogeneities that can have a strong influence on the dislocation dynamics, resulting in very different creep behavior compared to the base metal. Crystal plasticity-based finite element method (CPFEM) has been widely used to incorporate the effect of microstructural heterogeneities on deformation at the polycrystalline scale and is being utilized in this work to model the creep behavior of 740H GTA welds. Current model development is focused on secondary creep considering dislocation climb, glide, and, anti-phase boundary shearing or Orowan looping. A dislocation-density based CPFEM model addressing these mechanisms is currently being implemented in the Multi-Physics Object Oriented Simulation Environment (MOOSE: mooseframework.org) software that provides the ability to solve problems involving multiple physics concurrently and implicitly. Short term creep tests at 700-800°C of cross weld and all-weld metal samples from GTA welds in Alloy 740 will be used to determine input parameters for the model. Long term creep tests at 750°C on Alloy 740H GTA welds will be used to validate the results of modeling and simulation. The model will also be applied to welds with microstructures that develop during hybrid laser arc welding (HLAW) of Alloy 740H to evaluate the effect of weld microstructure on of the validity of the model.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Modeling Induction Stirring and Particle Tracking in Molten Uranium

Two independent numerical models have been developed to simulate the behavior of carbon impurities in molten uranium metal. Informed by experimental parameters, one model was created using the commercial software Star-CCM+ and compared with another developed using open-source codes, including OpenFOAM, Finite Element Method Magnetics (FEMM) and a First Passage Kinetic Monte Carlo (FPKMC) approach. The target experimental system features a 404g uranium metal charge containing an average carbon concentration of 139 ppm which was melted in a vacuum induction furnace at 1400° C then resolidified. The microstructures of the uranium and its impurities before and after melting have been characterized and reported separately. Prior to simulating the uranium-carbon system described, the numerical models were validated using a previously published nonradioactive experimental system to ensure agreement with expected output values. Focus has been placed on modeling velocity fields under induction stirring and impurity particle trajectories.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗