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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Containerization in ATLAS Software Development and Data Production

The ATLAS experiment's software production and distribution on the grid benefits from a semi-automated infrastructure that provides up-to-date information about software usability and availability through the CVMFS dis-tribution service for all relevant systems. The software development process uses a Continuous Integration pipeline involving testing, validation, packag-ing and installation steps. For opportunistic sites that can not access CVMFS, containerized releases are needed. These standalone containers are currently created manually to support Monte-Carlo data production at such sites. In this paper we will describe an automated procedure for the containerization of AT-LAS software releases in the existing software development infrastructure, its motivation, integration and testing in the distributed computing system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

BatteryPro: A Python Toolkit for Battery Data Analysis and Machine Learning Predictions

Analyzing battery test data for research & development can be time-consuming since battery tests often run on the order of months to years, generating large volumes of data. BatteryPro is a comprehensive Python package and software designed to facilitate advanced analysis and performance predictions for battery test data. Developed for battery researchers, it supports data types from widely used battery testing instruments, including MACCOR and Biologic cycling systems. The software provides a variety of tools for extracting and plotting key battery parameters such as time, voltage, capacity, current, and pressure. In addition to its extensive data analysis capabilities, BatteryPro features a dedicated machine learning module that employs a Bayesian Gaussian Mixture Model (GMM) to predict battery performance and degradation. Users can generate synthetic capacity fade data, calculate fade metrics, and leverage predictive models to forecast long-term battery behavior. The software's graphical user interface (GUI) enhances usability, allowing researchers to upload, merge, and analyze multiple data files with full customizability. The GUI also supports machine learning predictions, enabling users to fit models and make predictions based on selected data and parameters. BatteryPro is built using QtDesigner, scikit-learn, matplotlib, and pandas, ensuring a high level of customization, flexibility, and accuracy in battery data analysis. This tool aims to empower researchers with the ability to perform detailed battery analysis and make informed predictions, ultimately advancing the field of battery research.

25 - ENERGY STORAGE↗
DOE OSTI2016

Airside HVAC BESTEST. Adaptation of ASHRAE RP 865 Airside HVAC Equipment Modeling Test Cases for ASHRAE Standard 140. Volume 1, Cases AE101-AE445

This report documents a set of diagnostic analytical verification cases for testing the ability of whole building simulation software to model the air distribution side of typical heating, ventilating and air conditioning (HVAC) equipment. These cases complement the unitary equipment cases included in American National Standards Institute (ANSI)/American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) Standard 140, Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs, which test the ability to model the heat-transfer fluid side of HVAC equipment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Agile Acceleration of LLVM Flang Support for Fortran 2018 Parallel Programming

The LLVM Flang compiler ("Flang") is currently Fortran 95 compliant, and the frontend can parse Fortran 2018. However, Flang does not have a comprehensive 2018 test suite and does not fully implement the static semantics of the 2018 standard. We are investigating whether agile software development techniques, such as pair programming and test-driven development (TDD), can help Flang to rapidly progress to Fortran 2018 compliance. Because of the paramount importance of parallelism in high-performance computing, we are focusing on Fortran’s parallel features, commonly denoted “Coarray Fortran.” We are developing what we believe are the first exhaustive, open-source tests for the static semantics of Fortran 2018 parallel features, and contributing them to the LLVM project. A related effort involves writing runtime tests for parallel 2018 features and supporting those tests by developing a new parallel runtime library: the CoArray Fortran Framework of Efficient Interfaces to Network Environments (Caffeine).

Rasmussen, Katherine↗
DOE OSTI2020

Investigating Scientific Data Change with User Research Methods

Scientific datasets are continually expanding and changing due to fluctuations with instruments, quality assessment and quality control processes, and modifications to software pipelines. Datasets include minimal information about these changes or their effects requiring scientists manually assess modifications through a number of labor intensive and ad-hoc steps. The Deduce project is investigating data change to develop metrics, methods, and tools that will help scientists systematically identify and make decisions around data changes. Currently, there is a lack of understanding, and common practices, for identifying and evaluating changes in datasets since systematically measuring and managing data change is under explored in scientific work. We are conducting user research to address this need by exploring scientist's conceptualizations, behaviors, needs, and motivations when dealing with changing datasets. Our user research utilizes multiple methods to produce foundational, generative insights and evaluate research products produced by our team. In this paper, we detail our user research process and outline our findings about data change that emerge from our studies. Our work illustrates how scientific software teams can push beyond just usability testing user interfaces or tools to better probe the underlying ideas they are developing solutions to address.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2018

Closeout Phase II Qualification of the Thermal Conductivity Microscope for IMCL

The FY18 milestone for this work involved the completion of qualification testing of the Thermal Conductivity Microscope (TCM) in preparation for installation in the Irradiated Materials Characterization Laboratory (IMCL). In FY17 the TCM was entered into stage one mockup at the Materials and Fuels Complex (MFC) and initial testing was completed. This initial testing at the MFC centered on the ability operate the equipment remotely using manipulators and functional testing of the instrument. During FY18 issues noted during initial testing were addressed, a sample heater indexing system was developed, software enhancements were integrated and a sputter coater for use in the glove was procured. Additional testing was preformed to ensure instrument accuracy and reproducibility. The Phase II qualification plan, MFC-EQP-0267, completed approval on August 14, 2018.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Autonomous Controls For Reactor Technologies (acorn)

ACORN (Autonomous Controls fOr Reactor techNologies) software utilizes data, obtained from an experimental test bed and/or simulation, to implement a control command for microreactor operation. Command examples include a change to the temperature profile, power profiles, heat fluxes, etc. The control command recommended by the code is derived based on future predicted states of a microreactor, allowing proactive optimal and autonomous microreactor operation. The software is written in Python languages. The current software supports autonomous temperature controls of heat pipe simulator and autonomous heat flux controls of a 37 heat pipe non-nuclear testbed simulator (or its surrogate models).

Lin, Linyu [Idaho National Laboratory (INL), Idaho↗
DOE OSTI2018

A self-referential HOWTO on release engineering

Release engineering is a fundamental part of the software development cycle: it is the point at which quality control is exercised and bug fixes are integrated. The way in which software is released also gives the end user her first experience of a software package, while in scientific computing release engineering can guarantee reproducibility. For these reasons and others, the release process is a good indicator of the maturity and organization of a development team. Software teams often do not put in place a release process at the beginning. This is unfortunate because the team does not have early and continuous execution of test suites, and it does not exercise the software in the same conditions as the end users. I describe an approach to release engineering based on the software tools developed and used by the GNU project, together with several specific proposals related to packaging and distribution. I do this in a step-by-step manner, demonstrating how this very paper is written and built using proper release engineering methods. Because many aspects of release engineering are not exercised in the building of the paper, the accompanying software repository also contains examples of software libraries.

42 ENGINEERING↗
DOE OSTI2016

WHITE DWARF MERGERS ON ADAPTIVE MESHES. I. METHODOLOGY AND CODE VERIFICATION

The Type Ia supernova (SN Ia) progenitor problem is one of the most perplexing and exciting problems in astrophysics, requiring detailed numerical modeling to complement observations of these explosions. One possible progenitor that has merited recent theoretical attention is the white dwarf (WD) merger scenario, which has the potential to naturally explain many of the observed characteristics of SNe Ia. To date there have been relatively few self-consistent simulations of merging WD systems using mesh-based hydrodynamics. This is the first paper in a series describing simulations of these systems using a hydrodynamics code with adaptive mesh refinement. In this paper we describe our numerical methodology and discuss our implementation in the compressible hydrodynamics code CASTRO, which solves the Euler equations, and the Poisson equation for self-gravity, and couples the gravitational and rotation forces to the hydrodynamics. Standard techniques for coupling gravitation and rotation forces to the hydrodynamics do not adequately conserve the total energy of the system for our problem, but recent advances in the literature allow progress and we discuss our implementation here. We present a set of test problems demonstrating the extent to which our software sufficiently models a system where large amounts of mass are advected on the computational domain over long timescales. Future papers in this series will describe our treatment of the initial conditions of these systems and will examine the early phases of the merger to determine its viability for triggering a thermonuclear detonation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Ongoing solution reproducibility of earth system models as they progress toward exascale computing

We present a methodology for solution reproducibility for the Energy Exascale Earth System Model during its ongoing software infrastructure development to prepare for exascale computers. The nonlinear chaotic nature of climate system simulations precludes traditional model verification approaches since machine precision differences—resulting from code refactoring, changes in software environment, and so on—grow exponentially to a different weather state. Here, we leverage the nature of climate as a statistical description of the atmosphere in order to establish model reproducibility. We evaluate the degree to which two-sample equality of distribution tests can confidently detect the change in climate from minor tuning parameter changes on model output variables in order to establish the level of difference that indicates a new climate. To apply this (baselined test), we target a section of the model’s development cycle wherein no intentional science changes have been applied to its source code. We compare an ensemble of short simulations that were conducted using a verified model configuration against a new ensemble with the same configuration but with the latest software infrastructure (Common Infrastructure for Modeling the Earth, CIME5.0), compiler versions, and software libraries. We also compare these against ensemble simulations conducted using the original version of the software infrastructure (CIME4.0) of the earlier model configuration, but with the latest compilers and software libraries, to test the impact of new compilers and libraries in isolation from additional software infrastructure. The two-sample equality of distribution tests indicates that these ensembles indeed represent the same climate.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

FGMS-poster

Idaho National Laboratory (INL) performs post irradiation examination (PIE) of tri-structural isotropic (TRISO)-coated particle fuel to help qualify it for high temperature gas cooled reactors. TRISO fuel compacts are re-irradiated in the Neutron Radiography Reactor (NRAD) to generate the short lived fission products needed for fission product release testing. The Fuel Accident Condition Simulator (FACS) furnace and newly added Screen Neutron Irradiated Fuel for Failure (SNIFF) furnace heat the compacts in helium to temperatures of up to 2,000°C, prompting fission product release—predominantly gaseous xenon and krypton isotopes and condensable products such as cesium—from failed particles. These released isotopes are transported to a fission gas monitoring system (FGMS 1 or FGMS 3), where they accumulate in cryogenic cold traps and are quantified using high-purity germanium (HPGe) detectors. The addition of SNIFF and FGMS 3 increases throughput by enabling simultaneous testing of multiple compacts. Furthermore, automated INL developed software provides continuous, near-real time monitoring of fission product inventories and manages the liquid nitrogen cooling of the traps. These system enhancements improve the efficiency, data quality, and testing capacity of TRISO fuel performance evaluations.

07 - ISOTOPES AND RADIATION SOURCES↗
DOE OSTI2014

The OME Framework for genome-scale systems biology

The life sciences are undergoing continuous and accelerating integration with computational and engineering sciences. The biology that many in the field have been trained on may be hardly recognizable in ten to twenty years. One of the major drivers for this transformation is the blistering pace of advancements in DNA sequencing and synthesis. These advances have resulted in unprecedented amounts of new data, information, and knowledge. Many software tools have been developed to deal with aspects of this transformation and each is sorely needed. However, few of these tools have been forced to deal with the full complexity of genome-scale models along with high throughput genome-scale data. This particular situation represents a unique challenge, as it is simultaneously necessary to deal with the vast breadth of genome-scale models and the dizzying depth of high-throughput datasets. It has been observed time and again that as the pace of data generation continues to accelerate, the pace of analysis significantly lags behind. It is also evident that, given the plethora of databases and software efforts, it is still a significant challenge to work with genome-scale metabolic models, let alone next-generation whole cell models. We work at the forefront of model creation and systems scale data generation. The OME Framework was borne out of a practical need to enable genome-scale modeling and data analysis under a unified framework to drive the next generation of genome-scale biological models. Here we present the OME Framework. It exists as a set of Python classes. However, we want to emphasize the importance of the underlying design as an addition to the discussions on specifications of a digital cell. A great deal of work and valuable progress has been made by a number of communities towards interchange formats and implementations designed to achieve similar goals. While many software tools exist for handling genome-scale metabolic models or for genome-scale data analysis, no implementations exist that explicitly handle data and models concurrently. The OME Framework structures data in a connected loop with models and the components those models are composed of. This results in the first full, practical implementation of a framework that can enable genome-scale design-build-test. Over the coming years many more software packages will be developed and tools will necessarily change. However, we hope that the underlying designs shared here can help to inform the design of future software.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Investigation of Best-Practices and Computationally Inexpensive Radiative Exchange Models for Discrete Element Method Modeling of Aluminosilicate Particles in Concentrating Solar Power Environments

Chemically inert, aluminosilicate based particles have been investigated as both a thermal transport and sensible energy storage medium for concentrating solar power facilities. These particles will experience a wide range of operating temperatures (300-1000 K) and handling conditions (dense to dilute falling particle curtains, dense granular flows, or dense structures), requiring specially-designed and optimized infrastructures. The relative influence of collisional and frictional interactions between particles varies based on temperature-dependent particulate properties and greatly impacts the bulk, granular flow behavior. These underlying physics are captured using discrete element method modeling tools. However, this modeling method is computationally expensive as each particle position and interaction is tracked during the simulation. These modeling methods are further complicated by introducing temperature-dependent particle properties, high-temperature radiative exchange, and directional irradiation sources experienced by granular flows in concentrating solar power environments. In this study, coupled experimental and numerical slump testing of aluminosilicate particles was performed and computationally efficient radiative exchange models were evaluated to establish best-practices for discrete element method models for concentrating solar power environments. The three particle types investigated included Carbobead HSP 30 /60, Carbobead CP 30/60, and Granusil 4030. Existing modeling limitations and computationally-efficient multi-modal heat transfer models were evaluated using Aspherix®, a commercial discrete element method software. High-temperature (< 1073 K) slump testing of aluminosilicate particles was performed to investigate the deviation between experimentally-observed and numerically-predicted angles of repose introduced by computation-time reduction practices including the relaxation of the particle elastic modulus and coarse-graining. Coarse-graining is used to use a single modeled particle that is representative of a collection of smaller particles, decreasing the computational cost at the expense of geometric accuracy. Additionally, relaxation of the elastic modulus is used to reduce computational time at the expense of an increased, modeled particle overlap. Prior studies have determined that aluminosilicate particles retain a high elastic modulus at high temperatures (< 1073 K), requiring small simulation timesteps to ensure resolved contact forces resemble appropriate solid mechanics. A parametric study was performed to evaluate the influence of computation time improvements on the deviation between experimental and modeled angle of repose across high temperatures < 1073 K. Additionally, numerical case studies were performed on candidate particle systems at varying porosities and temperatures. These studies were performed to investigate the influence of computationally-efficient radiative-exchange modeling methods coupled to Aspherix® on modeled accuracy and computation time. The recently-developed distance-based approximation was evaluated in estimating radiative exchange between particles and participating surfaces located in close proximity. The distance based approximation was developed to use tabulated estimates of the radiative distribution factor between individual particles and surfaces in close proximity (< 40 particle radii). These methods were expanded to the aluminosilicate particles of interest, including the influence of particle size distributions. To capture radiative exchange between particles and surfaces not in close proximity (> 40 particle radii) and to capture the absorption of directional irradiation from concentrating solar resources, a volumetrically-averaged radiative distribution factor was calculated between the modeled granular flow and surfaces using Monte Carlo ray-tracing for participating media. Volume-averaged absorption and scattering coefficients were predicted using a volumetric discretization of the modeled domain with monodisperse approximations based on geometric optics and experimentally-determined scattering phase functions for aluminosilicate particles.

14 SOLAR ENERGY↗
DOE OSTI2024

An Update on Microreactor Automated Control System (MACS)

Automation of control systems is expected to be important in the economic and safe operation of microreactors. There is a need to develop and demonstrate automated control for microreactors, along with the development of testbeds for this purpose. This report provides updates on the status of a microreactor automated control system (MACS) testbed developed to test control system automation. While a future goal is to demonstrate this system using a prototypic microreactor such as MARVEL, the present focus is on developing and testing within a non-nuclear testbed. The testbed, developed in collaboration with Idaho National Laboratory, includes hardware-in-the-loop simulation and uses a Modelica-based model of a prototypic microreactor for use in testing control automation. Research to date at Oak Ridge National Laboratory has focused on the development of prototypic software for automating plant-level control under selected scenarios. Empirical testing on the integrated MACS testbed was performed to quantify key characteristics of the integrated testbed and to demonstrate the use of the software for automating the calculation and use of actuation setpoints for selected load-following scenarios. Ongoing research is focused on integrating additional control algorithms that utilize data from newly included sensors within the MACS hardware testbed, as well as demonstrating and assessing the performance of the different automated control algorithms on multiple additional operational scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

SU-F-J-53: A 3D Printed Phantom for the Use of Daily Quality Assurance Alignment Tests

Purpose: To discuss experiences and results for a 3D printed QA phantom used for daily alignment purposes for a six degrees-of-freedom (6DoF) table Methods: A 3D model was created using a fused deposition modeling (FDM) printer using free online computer-aided design (CAD) software. The model has been under use for daily QA alignment tests for a 6DoF couch. An aligned and angled baseplate were also printed in order to introduce known angles for 6DoF corrections during image-guidance. Unique registration contours were created on the faces of the phantom in order to achieve a better cone-beam computed tomography (CBCT) match using an auto-registration algorithm. A BB was also introduced at the center of the phantom in order to deliver an integrated daily Winston-Lutz (WL) test. Translational, rotational, and WL results were tabulated over one month. Results: The ’honeycomb’ structure of the print was apparent in the EPID images for the WL test, which affected the results of the analysis software. This was fixed by inserting a cube made of polyoxymethylene within the 3D phantom that encompass the BB. Auto-registration results for the three translational and three rotational from a known offset to the BB isocenter consistently fell within 1 mm and 0.2°, respectively. WL tests resulted in an average of 0.71 ± 0.14 mm. Conclusion: 3D printed models allow for accurate builds that can be customized to a variety of clinical needs. Results from translational, rotational, and WL show consistent results over a month’s time. Given its relatively cheap and streamlined workflow, 3D printing could be implemented into any clinic looking to create customized phantoms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

October 2019 SAPHIRE 8 Software Quality Assurance Oversight Status Report

The software quality assurance oversight consists of updating and maintaining revision control of the System Analysis Program for Hands-on Integrated Reliability Evaluations (SAPHIRE) Version 8 quality assurance program documentation and of monitoring revision control of the SAPHIRE Version 8 source code. This report summarizes the oversight efforts through description of the revision control system (RCS) setup, operation and contents. Documents maintained under revision control include the Acceptance Test Plan (ATP), Configuration Management Plan, Quality Assurance Plan, Software Project Plan, Requirements Traceability Matrix (RTM), System Test Plan, Significance Determination Process (SDP) Interface Training Manual, and the SAPHIRE 8 “New Features and Capabilities Overview.” These documents are referred to and can be transmitted upon request of the Nuclear Regulatory Commission (NRC) Contracting Officer’s Representative (COR).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Fisher Forecasting for the DESC with $\texttt{Augur}$

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) has begun its ten-year survey of the entire visible southern hemisphere. To ensure robust cosmological measurements, computationally inexpensive investigations of modeling choices must be made to gauge the performance of proposed cosmological analyses. In this paper, we introduce the $\texttt{Augur}$ tool of the Dark Energy Science Collaboration (DESC), which provides Fisher forecasts for cosmological inference for the LSST using software frameworks designed for DESC science. We test the pipeline by comparing it to forecasts produced by external code and direct sampling of the posterior via nested sampling methods, finding good agreement between all methods. We additionally investigate a range of modeling and hyperparameter choices for a 3$\times$2pt investigation in harmonic space, providing users with diagnostics to obtain reliable forecasts. $\texttt{Augur}$ will be continually updated to be compatible with the other tools in the DESC software ecosystem as additional probes and functionality become available.

Rogozenski, Paul [Carnegie Mellon U.; Arizona U.] ↗
DOE OSTI2023

CYVET: A Cyber-Physical Assurance Framework Based on a Semi-Supervised Vetting Approach

The project is designed to directly address the needs described in the Topic Area 4 (“Cybersecurity Verification and Validation”) of the CEDS’19 Research Call. The proposed CYVET system directly addresses the need to elevate the current industry capabilities to verify and validate OT cybersecurity and associated control system infrastructure. Currently, there is a significant gap in the energy sector’s capability in that regard during infrastructure improvement, equipment procurement, and compliance certification. CYVET provides that needed capability. CYVET is device and architecture agnostic and thus broadly applicable across the energy sector. The goal of this project is to develop and deliver a cybersecurity verification and validation framework testing capability to verify and validate OT equipment, software, and the underlying control system architecture. The primary project objectives are (i) Verification: the synthesis and reconciliation of standards and vendor supplied features, (ii) Validation: the generation, execution, and presentation of testing scripts of verified security features, and (3) Demonstration: apply the developed technology capabilities for verification and validation at a relevant end-user facility in the energy sector.

Lopez Jr, Juan↗