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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Imaging and controlling vortex dynamics in mesoscopic superconductor–normal-metal–superconductor arrays

Harnessing the properties of vortices in superconductors is crucial for fundamental science and technological applications; thus, it has been an ongoing goal to locally probe and control vortices. Here, we use a scanning probe technique that enables studies of vortex dynamics in superconducting systems by leveraging the resonant behavior of a raster-scanned, magnetic-tipped cantilever. This experimental setup allows us to image and control vortices, as well as extract key energy scales of the vortex interactions. Applying this technique to lattices of superconductor island arrays on a metal, we obtain a variety of striking spatial patterns that encode information about the energy landscape for vortices in the system. We interpret these patterns in terms of local vortex dynamics and extract the relative strengths of the characteristic energy scales in the system, such as the vortex-magnetic field and vortex-vortex interaction strengths, as well as the vortex chemical potential. We also demonstrate that the relative strengths of the interactions can be tuned and show how these interactions shift with an applied bias. The high degree of tunability and local nature of such vortex imaging and control not only enable new understanding of vortex interactions, but also have potential applications in more complex systems such as those relevant to quantum computing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Dealing with Measurement Uncertainties as Nuisance Parameters in Bayesian Model Calibration

In the presence of model discrepancy, the calibration of physics-based models for physical parameter inference is a challenging problem. Lack of identifiability between calibration parameters and model discrepancy requires additional identifiability constraints to be placed on the model discrepancy to obtain unique physical parameter estimates. If these assumptions are violated, the inference for the calibration parameters can be systematically biased. In many applications, such as in dynamic material property experiments, many of the calibration inputs refer to measurement uncertainties. Here, we develop a metric for identifying overfitting of these measurement uncertainties, propose a prior capable of reducing this overfitting, and show how this leads to a diagnostic tool for validation of physical parameter inference. The approach is demonstrated for a benchmark example and applied for a material property application to perform inference on the equation of state parameters of tantalum.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Development of a Gibbs Energy Minimiser for the MOOSE-based Corrosion Modelling App Yellowjacket and Validation of MSTDB

Nuclear materials are highly complex multiscale, multiphysics systems,and an effective prediction of nuclear reactor performance and safety requires simulation capabilities that tightly couple different physical phenomena. The Idaho National Laboratory’s Multiphysics Object Oriented Simulation Environment (MOOSE) provides the computational foundation for performing such simulations. With the move towards advanced reactors, such as the Molten Salt Reactor (MSR), that employ high temperature fluids compared to conventional reactors, corrosion has become a problem of great interest. A new application called Yellowjacket is currently under development to directly couple thermodynamic equilibrium and kinetics with phase field models in order to model corrosion in MSRs. As part of Yellowjacket, a Gibbs energy minimiser is being developed to perform thermochemical equilibrium calculations for a range of different materials, which is currently in its infancy. This report describes the further progress towards the development of Yellowjacket Gibbs energy minimiser. Ontario Tech University is developing a new Gibbs energy minimiser for Yellowjacket which is the primary contribution of this work. The aim to develop a thermochemistry solver for the MOOSE framework following the same development philosophy and using the same tools and libraries. A special focus is on performance, documentation and SQA. Furthermore through a scope extension partway through the fiscal year a thorough assessment of the MSTDB-TC v1.3 was performed at Ontario Tech University in the context of continuous improvement and quality assurance. The objective of the work was to have an arm’s length review of the database to give confidence that the database is performing as it was intended while assessing its current state to give recommendations to future developments. This assessment involved two parts: A) a quantitative assessment, and B) a qualitative assessment. Part A involved developing an automated test-suite that would compute values from the database using Thermochimica with comparisons to experimental measurements for validation purposes, which gives confidence to the database’s stakeholders that its functioning properly. Part B involved reviewing all binary systems in the database and making a qualitative assessment with two performance indicators: comprehensiveness and overall confidence. It is important to note that the models in the database are empirical, which is to say that the quality of any model is highly dependent on the experimental data used to inform its development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Novel Relativistic Electronic Structure Theories for Actinide-Containing Compounds

Actinides of importance to basic energy sciences contain electrons moving at speed comparable to the speed of light. Reliable computational simulation of these electrons and hence actinide chemistry requires accurate description of relativistic effects. The present project advances computational actinide chemistry with development of new methodologies, algorithms, and computer programs in relativistic quantum chemistry, as well as applications to actinide chemistry and spectroscopy. A new “electrons-only” exact two-component approach has been developed to provide efficient treatments of relativistic effects, while maintaining chemical accuracy. New computational algorithms developed here extend the applicability of relativistic electron-correlation methods to larger molecules. The method-development work in this project also features the first implementation of analytic gradient technique for relativistic electron-correlation methods, which provides significantly enhanced ability to compute properties for molecules containing actinides. The applicability and usefulness of these new methods and computer programs have been demonstrated in calculations of actinide-containing molecules to facilitate understanding of actinide chemistry and spectroscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Development of Decay Heat Sensitivity Analysis Capability in SCALE/ORIGEN

In this work, a decay heat sensitivity analysis capability was developed and implemented in the ORIGEN code of the SCALE nuclear modeling and simulation suite. This capability introduces improved numerical integration schemes, which overcome the challenges associated with accurately modeling the behavior of adjoint nuclide amounts during coarse time steps for both nuclide amount and decay heat sensitivity calculations. This capability significantly improves the accuracy of calculations without compromising computational efficiency compared to the existing method. Extensive verification was conducted for various benchmark problems, including a 238 Pu decay and an irradiation problem involving 135 Xe, evaluated with both coarse and fine time grids. The results show excellent agreement with reference direct perturbation solutions, reaffirming the computational accuracy of the newly proposed numerical integration methods. Furthermore, sensitivity analyses were performed for fission product inventories ( 147 Sm, 150 Sm, 155 Gd) in pressurized water reactor UO 2 and MOX fuel assemblies. These analyses demonstrated that the ORIGEN sensitivity analysis capability can capture detailed sensitivity coefficients and underlying physics in real applications. Additionally, a decay heat sensitivity analysis for high-assay low-enriched uranium fuel, including various initial 235 U enrichment and burnup points, highlights the extended capabilities of SCALE/ORIGEN in comprehensively assessing the factors influencing total decay heat. These advancements in ORIGEN offer valuable insights for reactor analysis, fuel design, and safety assessments, especially in the context of advanced nuclear fuel development and design changes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1984

Research in Structures and Dynamics, 1984

A symposium on advanced and trends in structures and dynamics was held to communicate new insights into physical behavior and to identify trends in the solution procedures for structures and dynamics problems. Pertinent areas of concern were (1) multiprocessors, parallel computation, and database management systems, (2) advances in finite element technology, (3) interactive computing and optimization, (4) mechanics of materials, (5) structural stability, (6) dynamic response of structures, and (7) advanced computer applications.

Robert J Hayduk↗
NASA NTRS1990

Constructing an advanced software tool for planetary atmospheric modeling

A prototype is described that can serve as a scientific-modeling software tool to facilitate the development of useful scientific models. The prototype is developed for applications to planetary modeling, and specific examples are given that relate to the atmosphere of Titan. The scientific modeling tool employs a high-level domain-specific modeling language, several data-display facilities, and a library of experimental datasets and scientific equations. The planetary modeling prototype links uncomputed physical variables to computed variables with computational transformations based on a backchaining procedure. The system - implemented in LISP with an object-oriented knowledge-representation tool - is run on a workstation that provides interface with several models. The prototype is expected to form the basis for a sophisticated modeling tool that can permit active experimentation.

Keller, Richard M.↗
NASA NTRS1994

Low-Flow-Rate Dry-Powder Feeder

Apparatus feeds small, precise flow of dry powder through laser beam of optical analyzer measuring patterns of light created by forward scattering (Fraunhofer diffraction) of laser beam from powder particles. From this optical measurement, statistical distribution of sizes of powder particles computed. Rates of flow optimized for measurement of particle-size distributions. Developed for analyzing particle-size distributions of solid-propellant powders. Also adapted to pharmaceutical industry, in manufacture of metal powder, and in other applications where particle-size distributions of materials used to control rates of chemical reactions and/or physical characteristics of processes.

Ramsey, Keith E.↗
NASA NTRS2007

An Integrated High Resolution Hydrometeorological Modeling Testbed using LIS and WRF

Scientists have made great strides in modeling physical processes that represent various weather and climate phenomena. Many modeling systems that represent the major earth system components (the atmosphere, land surface, and ocean) have been developed over the years. However, developing advanced Earth system applications that integrates these independently developed modeling systems have remained a daunting task due to limitations in computer hardware and software. Recently, efforts such as the Earth System Modeling Ramework (ESMF) and Assistance for Land Modeling Activities (ALMA) have focused on developing standards, guidelines, and computational support for coupling earth system model components. In this article, the development of a coupled land-atmosphere hydrometeorological modeling system that adopts these community interoperability standards, is described. The land component is represented by the Land Information System (LIS), developed by scientists at the NASA Goddard Space Flight Center. The Weather Research and Forecasting (WRF) model, a mesoscale numerical weather prediction system, is used as the atmospheric component. LIS includes several community land surface models that can be executed at spatial scales as fine as 1km. The data management capabilities in LIS enable the direct use of high resolution satellite and observation data for modeling. Similarly, WRF includes several parameterizations and schemes for modeling radiation, microphysics, PBL and other processes. Thus the integrated LIS-WRF system facilitates several multi-model studies of land-atmosphere coupling that can be used to advance earth system studies.

Kumar, Sujay V.↗
NASA NTRS2013

Advanced Usage of Vehicle Sketch Pad for CFD-Based Conceptual Design

Conceptual design is the most fluid phase of aircraft design. It is important to be able to perform large scale design space exploration of candidate concepts that can achieve the design intent to avoid more costly configuration changes in later stages of design. This also means that conceptual design is highly dependent on the disciplinary analysis tools to capture the underlying physics accurately. The required level of analysis fidelity can vary greatly depending on the application. Vehicle Sketch Pad (VSP) allows the designer to easily construct aircraft concepts and make changes as the design matures. More recent development efforts have enabled VSP to bridge the gap to high-fidelity analysis disciplines such as computational fluid dynamics and structural modeling for finite element analysis. This paper focuses on the current state-of-the-art geometry modeling for the automated process of analysis and design of low-boom supersonic concepts using VSP and several capability-enhancing design tools.

Ordaz, Irian↗
NASA NTRS2014

Adapting the Reconfigurable SpaceCube Processing System for Multiple Mission Applications

This paper will detail the use of SpaceCube in multiple space flight applications including the Hubble Space Telescope Servicing Mission 4 (HST-SM4), an International Space Station (ISS) radiation test bed experiment, and the main avionics subsystem for two separate ISS attached payloads. Each mission has had varying degrees of data processing complexities, performance requirements, and external interfaces. We will show the methodology used to minimize the changes required to the physical hardware, FPGA designs, embedded software interfaces, and testing.This paper will summarize significant results as they apply to each mission application. In the HST-SM4 application we utilized the FPGA resources to accelerate portions of the image processing algorithms more than 25 times faster than a standard space processor in order to meet computational speed requirements. For the ISS radiation on-orbit demonstration, the main goal is to show that we can rely on the commercial FPGAs and processors in a space environment. We describe our FPGA and processor radiation mitigation strategies that have resulted in our eight PowerPCs being available and error free for more than 99.99 of the time over the period of four years. This positive data and proven reliability of the SpaceCube on ISS resulted in the Department of Defense (DoD) selecting SpaceCube, which is replacing an older and slower computer currently used on ISS, as the main avionics for two upcoming ISS experiment campaigns. This paper will show how we quickly reconfigured the SpaceCube system to meet the more stringent reliability requirements

SpaceCube↗
DOE OSTI2024

Data-driven Quasi-static Surrogate Models for Nuclear-powered Integrated Energy Systems

The integration of nuclear power into energy systems presents a promising avenue to address the growing global energy demands while minimizing greenhouse gas emissions. In this paper, we introduce a data-driven quasi-static surrogate model for nuclear-powered Integrated Energy Systems (IES) that comprises various components, including a small modular reactor (SMR), steam manifold, balance of plant (BOP), high-temperature steam electrolysis (HTSE), and district heating (DH) system. Traditional physics-based models for these components often entail significant computational resource and time consumption, necessitating the development of efficient surrogate models. The development of a complete surrogate model for the IES involves the creation of individual surrogate models for each component, leveraging machine learning techniques and simulated data. These isolated surrogate models are subsequently integrated, enabling a holistic view of the IES and reducing the computational burden associated with detailed physics-based simulations. This paper outlines the development process, validation, and the performance evaluation of the surrogate models. The exceptional performance, with low root-mean-squared errors and R-squared scores of at least 99.8% across all individual surrogate models, underscores their accuracy and practical applicability. These results demonstrate the potential of these models to expedite the analysis of nuclear-powered IES, offering insights that can shape future research and development efforts.

08 HYDROGEN↗
DOE OSTI2021

Nanosecond Gated CMOS Camera (NSGCC) ICD (Rev. 2.1)

The Ultra-Fast X-ray Imager (UXI) program is an ongoing effort at Sandia National Laboratories to create high speed, multi-frame, time-gated Read Out Integrated Circuits (ROICs), and a corresponding suite of photodetectors to image a wide variety of High Energy Density (HED) physics experiments on both Sandia’s Z-Machine and LLNL’s National Ignition Facility (NIF). Several cameras have been designed over the length of the program; one of the most recent is the Icarus, which is an improvement on past imagers (Furi and Hippogriff). A second sensor that can be connected is the Daedalus sensor. The Icarus is a 1024 × 512-pixel array with either 25 μm or 8 µm spatial resolution containing four frames of storage per pixel and has improved timing generation and distribution components while achieved 2 ns time gating. The Daedalus sensor is also a 1024 x 512-pixel array with 25 µm special resolution containing three frames of storage per pixel and has an increased set of features for a wider variety of applications from interlacing of rows in each frame to configurability of all shutters. See Section 14 for details regarding the Icarus implementation of the firmware and Section 15 for details regarding the Daedalus implementation. Due to the unique test environments UXI sensors are targeted for, full custom hardware was required to physically mount an Icarus or Daedalus sensor, manage its various functions, and read out pixel data for transfer to a host computer. Beyond experimental functionality, the hardware also needed to accommodate sensor characterization requirements. Lawrence Livermore National Laboratory’s ‘Version 4.0 Board’ was the result of these efforts. It mounts all the components required to fully utilize the Icarus and Daedalus sensors including analog to digital converters to convert pixel data and various system voltages to digital form for readout and analysis, DAC channels for remote configuration of critical bias voltages, static random-access memories to buffer pixel data, RS422 and Gigabit Ethernet communications for remote access, and an FPGA to tie these components together. This document describes the FPGA electrical interfaces in detail to allow the reader a greater understanding of the device, and to facilitate implementation of custom software to control and manage it. The Version 4.0 Board is a continuation of the Nano-second Gated CMOS hardware design that retains much of the functionality of the Version 1.0 Board while adding features including a DAC instead of digital potentiometers, as well as sensors for pressure and radiation. The Version 4.0 board is intended for applications requiring tight form-factor enclosures. It is composed of two stacking boards; one holds the FPGA and regulators to power the various components of the board while the other contains the mating connector to the sensor, image-readoff ADCs, the DAC, and other components.

42 ENGINEERING↗
NASA NTRS2016

Wind-US Users Guide Version 4.0

Wind-US is a computational platform which may be used to numerically solve various sets of equations governing physical phenomena. Currently, the code supports the solution of the Euler and Navier-Stokes equations of fluid mechanics, along with supporting equation sets governing turbulent and chemically reacting flows. Wind-US is a product of the NPARC Alliance, a partnership between the NASA Glenn Research Center (GRC) and the Arnold Engineering Development Complex (AEDC) dedicated to the establishment of a national, applications-oriented flow simulation capability. The Boeing Company has also been closely associated with the Alliance since its inception, and represents the interests of the NPARC User's Association. The "Wind-US User's Guide" describes the operation and use of Wind-US, including: a basic tutorial; the physical and numerical models that are used; the boundary conditions; monitoring convergence; the files that are read and/or written; parallel execution; and a complete list of input keywords and test options. For current information about Wind-US and the NPARC Alliance, please see the Wind-US home page at http://www.grc.nasa.gov/WWW/winddocs/ and the NPARC Alliance home page at http://www.grc.nasa.gov/WWW/wind/.

fluid dynamics↗
NASA NTRS2003

Computational Aspects of Data Assimilation and the ESMF

The scientific challenge of developing advanced data assimilation applications is a daunting task. Independently developed components may have incompatible interfaces or may be written in different computer languages. The high-performance computer (HPC) platforms required by numerically intensive Earth system applications are complex, varied, rapidly evolving and multi-part systems themselves. Since the market for high-end platforms is relatively small, there is little robust middleware available to buffer the modeler from the difficulties of HPC programming. To complicate matters further, the collaborations required to develop large Earth system applications often span initiatives, institutions and agencies, involve geoscience, software engineering, and computer science communities, and cross national borders.The Earth System Modeling Framework (ESMF) project is a concerted response to these challenges. Its goal is to increase software reuse, interoperability, ease of use and performance in Earth system models through the use of a common software framework, developed in an open manner by leaders in the modeling community. The ESMF addresses the technical and to some extent the cultural - aspects of Earth system modeling, laying the groundwork for addressing the more difficult scientific aspects, such as the physical compatibility of components, in the future. In this talk we will discuss the general philosophy and architecture of the ESMF, focussing on those capabilities useful for developing advanced data assimilation applications.

daSilva, A.↗
DOE OSTI2020

DOE Express Quantum Computing Application Teams (QCAT FY20 Report)

The QCOR project consists of 4 main research tasks: 1) scientific applications and algorithm development for machine learning (ML) and quantum theories of condensed matter systems and lattice gauge theories; 2) high-level quantum-classical (HLQC) language and domain specific language (DSL) development; 3) compiler and interfaces development for the HLQC language; and 4) hardware-level control, optimization, and algorithms libraries. In the succeeding sections we report on progress towards our research tasks during the 2020 calendar year.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

A Tailored Convolutional Neural Network for Nonlinear Manifold Learning of Computational Physics Data Using Unstructured Spatial Discretizations

In this work, we propose a nonlinear manifold learning technique based on deep convolutional autoencoders that is appropriate for model order reduction of physical systems in complex geometries. Convolutional neural networks have proven to be highly advantageous for compressing data arising from systems demonstrating a slow-decaying Kolmogorov n-width. However, these networks are restricted to data on structured meshes. Unstructured meshes are often required for performing analyses of real systems with complex geometry. Our custom graph convolution operators based on the available differential operators for a given spatial discretization effectively extend the application space of deep convolutional autoencoders to systems with arbitrarily complex geometry that are typically discretized using unstructured meshes. We propose sets of convolution operators based on the spatial derivative operators for the underlying spatial discretization, making the method particularly well suited to data arising from the solution of partial differential equations. We demonstrate the method using examples from heat transfer and fluid mechanics and show better than an order of magnitude improvement in accuracy over linear methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Differentiable Simulation of a Liquid Argon Time Projection Chamber

Liquid argon time projection chambers (LArTPCs) are widely used in particle detection for their tracking and calorimetric capabilities. The particle physics community actively builds and improves high-quality simulators for such detectors in order to develop physics analyses in a realistic setting. The ability of these simulators to mimic real, measured data is limited by the modeling of the physical detectors used for data collection. This modeling can be improved by performing dedicated calibration measurements. Conventional approaches calibrate individual detector parameters or processes one at a time. However, the impact of detector processes is entangled, making this a poor description of the underlying physics. We introduce a differentiable simulator that enables a gradient-based optimization, allowing for the first time a simultaneous calibration of all detector parameters. We describe the procedure of making a differentiable simulator, highlighting the challenges of retaining the physics quality of the standard, non-differentiable version while providing meaningful gradient information. We further discuss the advantages and drawbacks of using our differentiable simulator for calibration. Finally, we provide a starting point for extensions to our approach, including applications of the differentiable simulator to physics analysis pipelines.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗