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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Using the GeoFEST Faulted Region Simulation System

GeoFEST (the Geophysical Finite Element Simulation Tool) simulates stress evolution, fault slip and plastic/elastic processes in realistic materials, and so is suitable for earthquake cycle studies in regions such as Southern California. Many new capabilities and means of access for GeoFEST are now supported. New abilities include MPI-based cluster parallel computing using automatic PYRAMID/Parmetis-based mesh partitioning, automatic mesh generation for layered media with rectangular faults, and results visualization that is integrated with remote sensing data. The parallel GeoFEST application has been successfully run on over a half-dozen computers, including Intel Xeon clusters, Itanium II and Altix machines, and the Apple G5 cluster. It is not separately optimized for different machines, but relies on good domain partitioning for load-balance and low communication, and careful writing of the parallel diagonally preconditioned conjugate gradient solver to keep communication overhead low. Demonstrated thousand-step solutions for over a million finite elements on 64 processors require under three hours, and scaling tests show high efficiency when using more than (order of) 4000 elements per processor. The source code and documentation for GeoFEST is available at no cost from Open Channel Foundation. In addition GeoFEST may be used through a browser-based portal environment available to approved users. That environment includes semi-automated geometry creation and mesh generation tools, GeoFEST, and RIVA-based visualization tools that include the ability to generate a flyover animation showing deformations and topography. Work is in progress to support simulation of a region with several faults using 16 million elements, using a strain energy metric to adapt the mesh to faithfully represent the solution in a region of widely varying strain.

Geophyical Finite Element Simulation Tool (GeoFEST↗
DOE OSTI2023

QMCPACK v3.16.0

QMCPACK is an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance portable GPU support.

Kent, Paul R. C. [Oak Ridge National Laboratory] (↗
DOE OSTI2023

QMCPACK v3.17.0

QMCPACK is an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance portable GPU support.

Kent, Paul R. C. [Oak Ridge National Laboratory] (↗
DOE OSTI2023

QMCPACK v3.17.1

QMCPACK is an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance portable GPU support.

Kent, Paul R. C. [Oak Ridge National Laboratory] (↗
DOE OSTI2022

QMCPACK v3.14.0

QMCPACK is an open-source production level many-body ab initio Quantum Monte Carlo code for computing the electronic structure of atoms, molecules, and solids with full performance portable GPU support.

Kent, Paul R. C.↗
DOE OSTI2021

Modelling a Heaving Point-Absorber with a Closed-Loop Control System Using the DualSPHysics Code

The present work addresses the need for an efficient, versatile, accurate and open-source numerical tool to be used during the design stage of wave energy converters (WECs). The device considered here is the heaving point-absorber developed and tested by Sandia National Laboratories. The smoothed particle hydrodynamics (SPH) method, as implemented in DualSPHysics, is proposed since its meshless approach presents some important advantages when simulating floating devices. The dynamics of the power take-off system are also modelled by coupling DualSPHysics with the multi-physics library Project Chrono. A satisfactory matching between experimental and numerical results is obtained for: (i) the heave response of the device when forced via its actuator; (ii) the vertical forces acting on the fixed device under regular waves and; (iii) the heave response of the WEC under the action of both regular waves and the actuator force. This proves the ability of the numerical approach proposed to simulate accurately the fluid–structure interaction along with the WEC’s closed-loop control system. In addition, radiation models built from the experimental and WAMIT results are compared with DualSPHysics by plotting the intrinsic impedance in the frequency domain, showing that the SPH method can be also employed for system identification.

42 ENGINEERING↗
DOE OSTI2021

QTRAJ 1.0: A Lindblad equation solver for heavy-quarkonium dynamics

Here we introduce an open-source package called QTraj that solves the Lindblad equation for heavy-quarkonium dynamics using the quantum trajectories algorithm. The package allows users to simulate the suppression of heavy-quarkonium states using externally-supplied input from 3+1D hydrodynamics simulations. The code uses a split-step pseudo-spectral method for updating the wave-function between jumps, which is implemented using the open-source multi-threaded FFTW3 package. This allows one to have manifestly unitary evolution when using real-valued potentials. In this paper, we provide detailed documentation of QTraj 1.0, installation instructions, and present various tests and benchmarks of the code.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2018

NOS3: NASA Operational Simulator for Small Satellites

The NASA Operational Simulator for Small Satellites (NOS3) is a suite of open-source software tools to aid in areas such as software development, integration & test (I&T), mission operations/training, verification and validation (V&V), and software systems check-out. NOS3 provides a software development environment, a multi-target build system, operational interface/ground software, dynamics and environment simulations, and software-based hardware models. NOS3 has just recently been open-sourced by NASA and is available for immediate use. It enables the development of flight software (FSW) early in the project life cycle when hardware availability is limited. Small satellite development suffers from extensive lead times on many of the commercial-off-the-shelf (COTS) components as well as limited funding for engineering test units (ETUs). To alleviate the need to provide a hardware test-bed for each developer/tester, NOS3 hardware models are based upon characteristic data or manufacturer's data sheets for each individual component. The NOS3 hardware models' fidelity is such that FSW executes unaware that physical hardware is not present. This allows FSW binaries to be compiled for both the simulation environment and the flight computer without changing the FSW source code. For hardware models that provide data which is dependent upon the environment and spacecraft dynamics, such as a GPS receiver or magnetometer, an open-source tool from NASA GSFC (42 Spacecraft Simulator) is used to provide the necessary data. The underlying infrastructure used to transfer messages between FSW and the hardware models can also be used to monitor, intercept, and inject messages, which has proven to be beneficial for V&V of larger missions such as James Webb Space Telescope (JWST). As hardware is selected and becomes available, drivers can be added to the NOS3 environment to enable hardware-in-the-loop (HWIL) testing. When strict time synchronization is not vital, any number of combinations of hardware components and software-based models can be tested. NOS3 was actively used for FSW development and component testing of the Simulation-to-Flight 1 (STF-1) CubeSat and the Lunar IceCube CubeSat. As NOS3 matures, hardware models have been added for common small satellite components such as GPS receivers, electrical power systems and batteries, and antenna systems.

Suder, Mark↗
DOE OSTI2024

ARPA-E Grid Optimization (GO) Competition Challenge 1

The ARPA-E Grid Optimization (GO) Competition Challenge 1, from 2018 to 2019, focused on the basic Security Constrained AC Optimal Power Flow problem (SCOPF) for a single time period. The Challenge utilized sets of unique datasets generated by the ARPA-E GRID DATA program. Each dataset consisted of a collection of power system network models of different sizes with associated operating scenarios (snapshots in time defining instantaneous power demand, renewable generation, generator and line availability, etc.). The datasets were of two types: Real-Time, which included starting-point information, and Online, which did not. Week-Ahead data is also provided for some cases but was not used in the Competition. Although most datasets were synthetic and generated by GRIDDATA, a few came from industry and were only used in the Final Event. All synthetic Input Data and Team Results for the GO Competition Challenge 1 for the Sandbox, Trial Events 1 to 3, and the Final Event along with problem, format, scoring and rules descriptions are available here. Data for industry scenarios will not be made public. Challenge 1, a minimization problem, required two computational steps. Solver 1 or Code 1 solved the base SCOPF problem under a strict wall clock time limit, as would be the case in industry, and reported the base case operating point as output, which was used to compute the Objective Function value that was used as the scenario score. The feasibility of the solution was provided by the Solver 2 or Code 2, which solves the power flow problem for all contingencies based on the results from Solver 1. This is not normally done in industry, so the time limits were relaxed. In fact, there were no time limits for Trial Event 1. This proved to be a mistake, with some codes running for more than 90 hours, and a time limit of 2 seconds per contingency was imposed for all other events. Entrants were free to use their own Solver 2 or use an open-source version provided by the Competition. Containers, such as Docker, were considered to improve the portability of codes, but none that could reliably support a multi-node parallel computing environment, e.g., MPI, could be found. For more information on the competition and challenge see the "GO Competition Challenge 1 Information" and "GO Competition Challenge 1 Additional Information" resources below.

ACOPF↗
DOE OSTI2024

Numerical eigen-spectrum slicing, accurate orthogonal eigen-basis, and mixed-precision eigenvalue refinement using OpenMP data-dependent tasks and accelerator offload

Performing a variety of numerical computations efficiently and, at the same time, in a portable fashion requires both an overarching design followed by a number of implementation strategies. All of these are exemplified below as we present transitioning the PLASMA numerical library from relying on dependence-driven large tasks to achieving utilization of fine grain tasking and offload to hardware accelerators while keeping its core dependence sets: OpenMP source code pragmas and runtime for most system-level functionality and basic low-level numerical kernels provided directly by hardware vendors or open source projects with vendor contributions. We also present new algorithmic methods and their efficient parallel implementations including fine grained tasking for eigen-spectrum slicing and offload for mixed-precision eigenvalue refinement. We provide performance, scaling, and numerical results showing sizable gains over the available solutions from either the open source and vendor-provided packages.

Luszczek, Piotr↗
DOE OSTI2024

Multiphysics modeling of accelerators through code integration

This work aims to improve the ability of particle accelerator researchers to develop high-performance accelerator cavity designs by creating an overall multiphysics framework that integrates and couples existing application codes. This framework will allow accelerator researchers to build multiphysics models that will optimize cavity design, improve understanding of whole-device performance, and reduce the development and fabrication costs of accelerator research. We utilize the open-source VizSchema data standard as an intermediate data structure interface layer to standardize interfaces between individual application codes. VizScema is extensively documented online, and plugins for VizSchema are available for popular visualization packages, including VisIt and ParaView. Currently, the work focuses on coupling the EM field solver COMSOL and the electron gun code MICHELLE to allow COMSOL field-solve results to be seamlessly used by MICHELLE for particle-solve. Later work will extend this integration to include other fields, particles, and thermodynamics simulation codes.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

SPISEA: A Python-based Simple Stellar Population Synthesis Code for Star Clusters

We present Stellar Population Interface for Stellar Evolution and Atmospheres (SPISEA), an open-source Python package that simulates simple stellar populations. The strength of SPISEA is its modular interface which offers the user control of 13 input properties including (but not limited to) the initial mass function, stellar multiplicity, extinction law, and the metallicity-dependent stellar evolution and atmosphere model grids used. The user also has control over the initial–final mass relation in order to produce compact stellar remnants (black holes, neutron stars, and white dwarfs). We demonstrate several outputs produced by the code, including color–magnitude diagrams, HR-diagrams, luminosity functions, and mass functions. SPISEA is object-oriented and extensible, and we welcome contributions from the community. The code and documentation are available on GitHub (https://github.com/astropy/SPISEA) and ReadtheDocs (https://spisea.readthedocs.io/en/latest/), respectively.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

mzapy : An Open-Source Python Library Enabling Efficient Extraction and Processing of Ion Mobility Spectrometry-Mass Spectrometry Data in the MZA File Format

We have recently reported MZA, a new and simple mass spectrometry data structure based on the broadly supported HDF5 format and created to facilitate software development. While this format is inherently supportive of application development, the availability of a core library with standard mass spectrometry utilities greatly facilitates fast software development. Here, we present a Python library, mzapy, for efficient extraction and processing of mass spectrometry data in the MZA format. In addition to raw data extraction, mzapy contains supporting utilities enabling tasks including calibration, signal processing, peak finding, and generating plots. Being implemented in pure Python with minimal and largely standardized dependencies makes mzapy uniquely suited to application development in the multi-omics domain. The free and open source mzapy is built with extensibility in mind, and future development will support cloud computing and artificial intelligence/machine learning applications. The software source code is freely available at https://github.com/PNNL-m-q/mzapy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Introducing GPU Acceleration into the Python-Based Simulations of Chemistry Framework

We introduce the first version of GPU4P Y SCF, a module that provides GPU acceleration of methods in P Y SCF. As a core functionality, this provides a GPU implementation of two-electron repulsion integrals (ERIs) for contracted basis sets comprising up to g functions using the Rys quadrature. As an illustration of how this can accelerate a quantum chemistry workflow, we describe how to use the ERIs efficiently in the integral-direct Hartree–Fock build and nuclear gradient construction. Benchmark calculations show a significant speedup of 2 orders of magnitude with respect to the multithreaded CPU Hartree–Fock code of P Y SCF and the performance comparable to other open-source GPU-accelerated quantum chemical packages, including GAMESS and QUICK, on a single NVIDIA A100 GPU.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

ExaWind: A multifidelity modeling and simulation environment for wind energy

We introduce the open-source ExaWind modeling and simulation environment for wind energy. The primary physics codes of ExaWind are Nalu-Wind and OpenFAST. Nalu-Wind is a wind-focused computational fluid dynamics (CFD) code that is coupled to the whole-turbine simulation code OpenFAST. The ExaWind environment was created under U.S. Department of Energy funding to achieve the highest-fidelity simulations of wind turbines and wind farms to date, with the goal of enabling disruptive changes to turbine and plant design and operation. Innovation will be gleaned through better understanding of the complex flow dynamics in wind farms, including wake evolution and the impact of wakes on downstream turbines and turbulent flow from complex terrain. High-fidelity predictive simulations employ hybrid turbulence models, geometry/boundary-layer-resolving CFD meshes, atmospheric turbulence, nonlinear structural dynamics, and fluid-structure interaction. While there is an emphasis on very high-fidelity simulations (e.g., blade resolved with full fluid-structure coupling), the ExaWind environment supports lower-fidelity modeling capabilities including actuator-line and -disk methods. Important in the development of ExaWind codes is that the codes scale well on today's largest petascale supercomputers and on the next-generation platforms that will enable exascale computing.

17 WIND ENERGY↗
DOE OSTI2026

Multi-Artifact Analysis of Self-Admitted Technical Debt in Scientific Software

Context: Self-admitted technical debt (SATD) occurs when developers acknowledge shortcuts in code. In scientific software (SSW), such debt poses unique risks to the validity and reproducibility of results. Objective: This study aims to identify, categorize, and evaluate scientific debt, a specialized form of SATD in SSW, and assess the extent to which traditional SATD categories capture these domain-specific issues. Method: We conduct a multi-artifact analysis across code comments, commit messages, pull requests, and issue trackers from 23 open-source SSW projects. We construct and validate a curated dataset of scientific debt, develop a multi-source SATD classifier to guide SATD management, and conduct a practitioner validation to assess the practical relevance of scientific debt. Results: Our classifier performs strongly across 900,358 artifacts from 23 SSW projects. SATD is most prevalent in pull requests and issue trackers, underscoring the value of multi-artifact analysis. Models trained on traditional SATD often miss scientific debt, emphasizing the need for its explicit detection in SSW. Practitioner validation confirmed that scientific debt is both recognizable and useful in practice. Conclusions: Scientific debt represents a unique form of SATD in SSW that that is not adequately captured by traditional categories and requires specialized identification and management. Our dataset, classification analysis, and practitioner validation results provide the first formal multi-artifact perspective on scientific debt, highlighting the need for tailored SATD detection approaches in SSW.

Melin, Eric [Boise State University]↗
DOE OSTI2020

PFLOTRAN

PFLOTRAN is a GNU LGPL licensed code that simulates single phase water and multiphase (air, co2, water) flow, energy transport, geochemical reaction and biological reaction in the earth's subsurface environment. The problem may be discretized on structured and unstructured grids. The code is designed to run in parallel on supercomputers and leverages the open source PETSc library for solvers and data structures and open source HDF5 for binary file I/O. See www.pflotran.org and/or doc-dev.pflotran.org for further information. SAND2020-12161 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.

Hammond, Glenn↗