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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

hkl-projects/ioc-hkl

HKL-IOC is an open source EPICS IOC that performs real‑time crystallographic HKL calculations for diffractometers and scattering instruments. It integrates the Python hkl library with EPICS through PyDevice, exposing HKL calculations and diffractometer geometry transformations as standard EPICS process variables. This allows beamline and laboratory control systems to convert between motor positions and reciprocal‑space coordinates, configure diffractometer geometries, and drive scans directly in HKL space. The software is written in Python and designed to run alongside existing EPICS deployments without requiring changes to core EPICS components. It is intended for use at synchrotron and neutron scattering facilities, as well as laboratory X‑ray diffractometers, where reliable and reproducible HKL calculations are needed for experiment control, data collection, and automation. HKL-IOC is distributed under the GNU General Public License v3.0 (GPL‑3.0) and contributions and extensions for additional geometries and beamlines are welcomed.

Baekey, Alex↗
DOE OSTI2018

GASNet-EX Performance Improvements Due to Specialization for the Cray Aries Network

GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of PGAS runtime systems and other alternative models on future exascale machines. This paper reports on the improvements in performance observed on Cray XC-series systems due to enhancements made to the GASNet-EX software. These enhancements, known as "specializations", primarily consist of replacing network-independent implementations of several recently added features with implementations tailored to the Cray Aries network. Performance gains from specialization include (1) Negotiated-Payload Active Messages improve bandwidth of a ping-pong test by up to 14%, (2) Immediate Operations reduce running time of a synthetic benchmark by up to 93%, (3) non-bulk RMA Put bandwidth is increased by up to 32%, (4) Remote Atomic performance is 70% faster than the reference on a point-to-point test and allows a hot-spot test to scale robustly, and (5) non-contiguous RMA interfaces see up to 8.6x speedups for an intra-node benchmark and 26% for inter-node. These improvements are all available in GASNet-EX version 2018.3.0 and later.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

NREL's OpenStudio Helps Design More Efficient Buildings (Fact Sheet)

The National Renewable Energy Laboratory (NREL) has created the OpenStudio software platform that makes it easier for architects and engineers to evaluate building energy efficiency measures throughout the design process. OpenStudio makes energy modeling more accessible and affordable, helping professionals to design structures with lower utility bills and less carbon emissions, resulting in a healthier environment. OpenStudio includes a user-friendly application suite that makes the U.S. Department of Energy's EnergyPlus and Radiance simulation engines easier to use for whole building energy and daylighting performance analysis. OpenStudio is freely available and runs on Windows, Mac, and Linux operating systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

guppy i : a code for reducing the storage requirements of cosmological simulations

ABSTRACT As cosmological simulations have grown in size, the permanent storage requirements of their particle data have also grown. Even modest simulations present a major logistical challenge for the groups which run these boxes and researchers without access to high performance computing facilities often need to restrict their analysis to lower quality data. In this paper, we present guppy, a compression algorithm and code base tailored to reduce the sizes of dark matter-only cosmological simulations by approximately an order of magnitude. guppy is a ‘lossy’ algorithm, meaning that it injects a small amount of controlled and uncorrelated noise into particle properties. We perform extensive tests on the impact that this noise has on the internal structure of dark matter haloes, and identify conservative accuracy limits which ensure that compression has no practical impact on single-snapshot halo properties, profiles, and abundances. We also release functional prototype libraries in C, Python, and Go for reading and creating guppy data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

A Runtime Environment for Supporting Research in Resilient HPC System Software & Tools

The high-performance computing (HPC) community continues to increase the size and complexity of hardware platforms that support advanced scientific workloads. The runtime environment (RTE) is a crucial layer in the software stack for these large-scale systems. The RTE manages the interface between the operating system and the application running in parallel on the machine. The deployment of applications and tools on large-scale HPC computing systems requires the RTE to manage process creation in a scalable manner, support sparse connectivity, and provide fault tolerance. We have developed a new RTE that provides a basis for building distributed execution environments and developing tools for HPC to aid research in system software and resilience. This paper describes the software architecture of the Scalable runTime Component Infrastructure (STCI), which is intended to provide a complete infrastructure for scalable start-up and management of many processes in large-scale HPC systems. We highlight features of the current implementation, which is provided as a system library that allows developers to easily use and integrate STCI in their tools and/or applications. The motivation for this work has been to support ongoing research activities in fault-tolerance for large-scale systems. We discuss the advantages of the modular framework employed and describe two use cases that demonstrate its capabilities: (i) an alternate runtime for a Message Passing Interface (MPI) stack, and (ii) a distributed control and communication substrate for a fault-injection tool.

Computer Science↗
DOE OSTI2016

Development of an Efficient Approach to Perform Neutronics Simulations for Plutonium-238 Production

Conversion of 238Pu decay heat into usable electricity is imperative to power National Aeronautics and Space Administration (NASA) deep space exploration missions; however, the current stockpile of 238Pu is diminishing and the quality is less than ideal. In response, the US Department of Energy and NASA have undertaken a program to reestablish a domestic 238Pu production program and a technology demonstration sub-project has been initiated. Neutronics simulations for 238Pu production play a vital role in this project because the results guide reactor safety-basis, target design and optimization, and post-irradiation examination activities. A new, efficient neutronics simulation tool written in Python was developed to evaluate, with the highest fidelity possible with approved tools, the time-dependent nuclide evolution and heat deposition rates in 238Pu production targets irradiated in the High Flux Isotope Reactor (HFIR). The Python Activation and Heat Deposition Script (PAHDS) was developed specifically for experiment analysis in HFIR and couples the MCNP5 and SCALE 6.1.3 software quality assured tools to take advantage of an existing high-fidelity MCNP HFIR model, the most up-to-date ORIGEN code, and the most up-to-date nuclear data. Three cycle simulations were performed with PAHDS implementing ENDF/B-VII.0, ENDF/B-VII.1, and the Hybrid Library GPD-Rev0 cross-section libraries. The 238Pu production results were benchmarked against VESTA-obtained results and the impact of various cross-section libraries on the calculated metrics were assessed.

depletion↗
DOE OSTI2022

Traveler: Navigating Task Parallel Traces for Performance Analysis

Understanding the behavior of software in execution is a key step in identifying and fixing performance issues. This is especially important in high performance computing contexts where even minor performance tweaks can translate into large savings in terms of computational resource use. To aid performance analysis, developers may collect an execution trace —a chronological log of program activity during execution. As traces represent the full history, developers can discover a wide array of possibly previously unknown performance issues, making them an important artifact for exploratory performance analysis. However, interactive trace visualization is difficult due to issues of data size and complexity of meaning. Traces represent nanosecond-level events across many parallel processes, meaning the collected data is often large and difficult to explore. The rise of asynchronous task parallel programming paradigms complicates the relation between events and their probable cause. Here, to address these challenges, we conduct a continuing design study in collaboration with high performance computing researchers. We develop diverse and hierarchical ways to navigate and represent execution trace data in support of their trace analysis tasks. Through an iterative design process, we developed Traveler , an integrated visualization platform for task parallel traces. Traveler provides multiple linked interfaces to help navigate trace data from multiple contexts. We evaluate the utility of Traveler through feedback from users and a case study, finding that integrating multiple modes of navigation in our design supported performance analysis tasks and led to the discovery of previously unknown behavior in a distributed array library.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Matminer: An open source toolkit for materials data mining

As materials data sets grow in size and scope, the role of data mining and statistical learning methods to analyze these materials data sets and build predictive models is becoming more important. This manuscript introduces matminer, an open-source, Python-based software platform to facilitate data-driven methods of analyzing and predicting materials properties. Matminer provides modules for retrieving large data sets from external databases such as the Materials Project, Citrination, Materials Data Facility, and Materials Platform for Data Science. It also provides implementations for an extensive library of feature extraction routines developed by the materials community, with 47 featurization classes that can generate thousands of individual descriptors and combine them into mathematical functions. Finally, matminer provides a visualization module for producing interactive, shareable plots. These functions are designed in a way that integrates closely with machine learning and data analysis packages already developed and in use by the Python data science community. We explain the structure and logic of matminer, provide a description of its various modules, and showcase several examples of how matminer can be used to collect data, reproduce data mining studies reported in the literature, and test new methodologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Overview of the OECD-NEA Working Party on International Nuclear Data Evaluation Cooperation (WPEC)

The OECD Nuclear Energy Agency (NEA) Working Party on International Nuclear Data Evaluation Cooperation (WPEC) was established in 1989 to facilitate collaboration in nuclear data activities. Over its thirty year history, different Subgroups have been created to address topics in nearly every aspect of nuclear data, including: experimental measurements, evaluation, validation, model development, quality assurance of databases and the development of software tools. WPEC has recently completed activities on fission yield evaluation, the general nuclear database structure (GNDS) to replace the ENDF-6 format, methods to provide feedback to evaluation, studies of specific capture cross sections, new methods in thermal scattering kernel evaluation and the Collaborative International Evaluated Library Organisation (CIELO) Pilot Project. Ongoing activities in GNDS application programming interface (API) development, methods for covariance evaluation and quality assurance in nuclear data validation using the International Criticality Safety Benchmark Evaluation Project (ICSBEP) database are complemented by the work of two Expert Groups that oversee the High-Priority Request List (HPRL) for Nuclear Data and the continuous development of the GNDS. New activities on the use of integral experiments for nuclear data validation and adjustment, as well as the use of the Shielding Integral Benchmark Archive and Database (SINBAD) for validation have begun and will be coordinated alongside future Subgroups. After three decades we will review the status of WPEC, how it integrates other collections and activities organised by the NEA and how it dovetails with the initiatives of the IAEA and other bodies to effectively coordinate international activities in nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Exascale Dislocation Simulator

ExaDiS, or Exascale Dislocation Simulator, is a set of software modules written to enable numerical simulations of large groups of moving and interacting dislocations, line defects in crystals responsible for crystal plasticity. By tracking time evolution of sufficiently large dislocation ensembles, ExaDiS predicts plasticity response and plastic strength of crystalline materials. ExaDiS is built around a library of core functions for Discrete Dislocation Dynamics method specifically written to perform efficient computations on GPUs.

Bertin, Nicolas↗
DOE OSTI2016

PvaPy: Python API for EPICS PV Access

As the number of sites deploying and adopting EPICS Version 4 grows, so does the need to support PV Access from multiple languages. Especially important are the widely used scripting languages that tend to reduce both software development time and the learning curve for new users. In this paper we describe PvaPy, a Python API for the EPICS PV Access protocol and its accompanying structured data API. Rather than implementing the protocol itself in Python, PvaPy wraps the existing EPICS Version 4 C++ libraries using the Boost.Python framework. This approach allows us to benefit from the existing code base and functionality, and to significantly reduce the Python API development effort. PvaPy objects are based on Python dictionaries and provide users with the ability to access even the most complex of PV Data structures in a relatively straightforward way. Its interfaces are easy to use, and include support for advanced EPICS Version 4 features such as implementation of client and server Remote Procedure Calls (RPC).

Veseli, S.↗
DOE OSTI2026

Active learning emulators for nuclear two-body scattering in momentum space

In this work we extend the active learning emulators for two-body scattering in coordinate space with error estimation, recently developed by Maldonado et al. [Phys. Rev. C 112, 024002], to coupled-channel scattering in momentum space. Our full-order model (FOM) solver is based on the Lippmann-Schwinger integral equation for the scattering t-matrix as opposed to the radial Schrödinger equation. We use (Petrov-)Galerkin projections and high-fidelity calculations at a few snapshots across the parameter space of the interaction to construct efficient reduced-order models (ROMs), trained by a greedy algorithm for locally optimal snapshot selection. Both the FOM solver and the corresponding ROMs are implemented efficiently in Python using Google's JAX library. We present results for emulating scattering phase shifts in coupled and uncoupled channels and cross sections, and assess the accuracy of the developed ROMs and their computational speedup factors. We also develop emulator error estimation for both the t-matrix and the total cross section. The software framework for reproducing and extending our results is publicly available. Together with our recent advances in developing active-learning emulators for three-body scattering, these emulator frameworks set the stage for full Bayesian calibrations of chiral nuclear interactions and optical models against scattering data with quantified emulator errors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Spawn v.0.5.0 Released 12.15.2023 [SWR-SWR-20-10]

Spawn is a software package for performing co-simulations involving NREL's EnergyPlus™ tool and Modelica. This package bundles the following items in one self-contained package. 1. A method for connecting EnergyPlus models to Modelica 2. A Modelica compiler toolchain for compiling and running Modelica models 3. Modelica libraries and content, including the Modelica Buildings Library (MBL) and the Modelica Standard Library. The Spawn installation package is fully self-contained, and there are no external third-party dependencies. Together the capabilities in this package provide a single integrated environment for performing hybrid Modelica and EnergyPlus simulations. The primary entry point is the Spawn command line interface.

Li, Yanfei↗
DOE OSTI2021

`SkyPy`: A package for modelling the Universe

SkyPy is an open-source Python package for simulating the astrophysical sky. It comprises a library of physical and empirical models across a range of observables and a command-line script to run end-to-end simulations. The library provides functions that sample realisations of sources and their associated properties from probability distributions. Simulation pipelines are constructed from these models using a YAML-based configuration syntax, while task scheduling and data dependencies are handled internally and the modular design allows users to interface with external software. SkyPy is developed and maintained by a diverse community of domain experts with a focus on software sustainability and interoperability. By fostering development, it provides a framework for correlated simulations of a range of cosmological probes including galaxy populations, large scale structure, the cosmic microwave background, supernovae and gravitational waves. Version 0.4 implements functions that model various properties of galaxies including luminosity functions, redshift distributions and optical photometry from spectral energy distribution templates. Future releases will provide additional modules, for example, to simulate populations of dark matter halos and model the galaxy-halo connection, making use of existing software packages from the astrophysics community where appropriate.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Open Source Release of NJOY2016 and NJOY21

NJOY has been the standard for nuclear data processing for many decades. NJOY is a comprehensive computer code used to produce point-wise and multigroup nuclear data application libraries from cross sections and related quantities obtained from evaluated nuclear data in the Evaluated Nuclear Data Format (ENDF). NJOY was first publicly released in 1977 and distributed by what is now the Radiation Safety Information Computational Center (RSICC) at Oak Ridge National Laboratory and the National Energy Software Center (NESC) at Argonne National Laboratory. From that time until the release of NJOY2012, NJOY has been distributed by RSICC and made available to researchers outside the United States by agreements between RSICC and the NEA Databank. NJOY2012 was distributed by the Feynman Center at Los Alamos National Laboratory which did not have agreements with the NEA Databank, thus making it more difficult for non US citizens to obtain copies of NJOY2012. Furthermore, NJOY has had export control restrictions preventing some researchers from obtaining NJOY at all. Two new versions of NJOY have been released, NJOY2016 and NJOY21, in January of 2017. Both NJOY2016 and NJOY21 have been released with no export control restrictions and are distributed with an open-source license. This is a big departure from previous releases and impacts not only who has access to NJOY, but also how updates are made available to users and how collaboration is facilitated among interested developers. In addition to distributing NJOY2016 and NJOY21 with an open-source license, these two new versions provide new capabilities for NJOY which will maintain NJOY as the standard for nuclear data processing into the foreseeable future. We report in this summary about the changes that come with these two new versions of NJOY and how this impacts the users and long-time contributors to NJOY.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Autotuning in High-Performance Computing Applications

Autotuning refers to the automatic generation of a search space of possible implementations of a computation that are evaluated through models and/or empirical measurement to identify the most desirable implementation. Autotuning has the potential to dramatically improve the performance portability of petascale and exascale applications. To date, autotuning has been used primarily in high-performance applications through tunable libraries or previously tuned application code that is integrated directly into the application. This paper draws on the authors' extensive experience applying autotuning to high-performance applications, describing both successes and future challenges. If autotuning is to be widely used in the HPC community, researchers must address the software engineering challenges, manage configuration overheads, and continue to demonstrate significant performance gains and portability across architectures. In particular, tools that configure the application must be integrated into the application build process so that tuning can be reapplied as the application and target architectures evolve.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Modeling Tool Development and Validation for Solar Industry Process Heat Using Particle Thermal Energy Storage

U.S. industry sectors used 26.2 quadrillion Btu and accounted for 33% of total energy consumption in 2021 according to the Energy Information Agency. Industrial process heat accounts for 70% of industrial energy use with application temperatures ranging from 60 degrees -1100 degrees C. Industry processes, heavily relying on fossil fuels of cheap coal or natural gas, differ widely in operating conditions and load requirements which makes them difficult to standardize and imposes great challenges in decarbonization. Industry processes require reliable energy supply and vary widely in temperature ranges. Storing energy from renewable sources is necessary to improve reliability and to mitigate renewable intermittency when replacing carbon fuel-based heat supplies to achieve energy savings and reduce emissions. To this end, we have developed a particle-based thermal energy storage (TES) technology using low-cost and highly stable silica sand as a storage medium. The economic and performance-based analysis is key for renewable energy sources to reliably supply industry process heat and ultimately displace fossil fuels for decarbonization. The diversified industrial processes need case-by-case analysis and design. Therefore, an adaptive modeling tool is key for renewable power with energy storage to meet industry demands. Thus, a modeling tool to simulate a solar industry process heat system using the particle TES has been developed using the object-oriented equation-based language Modelica and the commercial platform of Modelon Impact. The Modelica-based software tool provides a general simulation environment for the design of reliable solar energy sources integrated with TES for various industrial process applications at different temperatures for economic competence with fossil fuels such as coal and natural gases. It uses both customized and standard component modeling modules in Modelon libraries for the flexibility to be adapted to a specific energy demand application. The particle TES system establishes a uniform energy supply platform with an efficient heat exchanger and particle thermal energy reservoir integrated with renewable powers. The particle TES system can provide a wide temperature range and can have a large storage temperature difference that increases storage energy density; therefore, it can be an adaptable energy storage system integrated with renewable power to supply 24/7 heat for industry decarbonization.

concentrated solar thermal↗
DOE OSTI2022

Enabling New Flexibility in the SUNDIALS Suite of Nonlinear and Differential/Algebraic Equation Solvers

In recent years, the SUite of Nonlinear and DIfferential/ALgebraic equation Solvers (SUNDIALS) has been redesigned to better enable the use of application-specific and third-party algebraic solvers and data structures. Throughout this work, we have adhered to specific guiding principles that minimized the impact to current users while providing maximum flexibility for later evolution of solvers and data structures. The redesign was done through the addition of new linear and nonlinear solvers classes, enhancements to the vector class, and the creation of modern Fortran interfaces. The vast majority of this work has been performed “behind-the-scenes,” with minimal changes to the user interface and no reduction in solver capabilities or performance. These changes allow SUNDIALS users to more easily utilize external solver libraries and create highly customized solvers, enabling greater flexibility on extreme-scale, heterogeneous computational architectures.

97 MATHEMATICS AND COMPUTING↗