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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Considering the Variability of Soiling in Long-Term PV Performance Forecasting: Preprint

This study presents the development of a methodology for evaluating the variability associated with soiling on long-term PV forecasting. Independent engineering firms typically build P50 forecasts for large PV plants through the use of the PVsyst software, where monthly soiling losses are one of many inputs to the P50 model. Subsequently, long-term performance distributions, or Pvalues, are constructed through a Monte Carlo analysis that includes various factors such as: satellite irradiance modeling uncertainty, uncertainty in the PVsyst model, and long-term irradiance variability. Often the PVsyst model uncertainty is increased to account for sites with significant soiling concerns but no systematic method has been presented in the literature to specifically include soiling variability within Pvalues. In this work soiling information from 16 sites in the U.S. Southwest are combined with 20 years of rainfall data to generate 20 years of energy production with soiling losses and then subsequently generate Pvalues. The results show that the spread of Pvalues (P1-P99) can increase from 0-13% when interannual soiling variability is included.

interannual variability↗
DOE OSTI2023

New Developments and Verification of the Fusion Blanket Simulation Capabilities in the MOOSE Framework

This poster contains new developments and updates in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework related to fusion modeling and simulation, and forms the basis for an on-going effort in modeling whole fusion devices at Idaho National Laboratory using MOOSE. In this work, a slice of the midplane of a proposed ceramic breeder blanket design for the Fusion Nuclear Science Facility is simulated using a combination of neutronics, 1D system level thermal hydraulics for helium, 3D heat conduction, and tritium transport. Previous work focused on the engineering scale full assembly of a blanket sector, but the simulations here form the basis for software quality and verification efforts to increase confidence as the large scale simulations continue. This poster was presented at the Idaho National Laboratory Intern Poster Session 2023.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

COSMIC DAWN: Distributed Analysis of Wireless at Nextscale

Distributed Analysis of Wireless at Nextscale (DAWN) is a novel simulation framework for large-scale design-space exploration (DSE) of unmodified software-defined radio (SDR) applications interacting in a scalable, high-fidelity, virtual physics environment. The software-defined nature of the coupled software-physics simulation leverages hardware emulation to permit in-depth examination and modification of not only the electromagnetic environment, including each signal in flight, but also the precise state of system software and components. DAWN supports modular, customizable physics environments allowing realistic propagation effects so that computationally efficient empirical models, reduced order/surrogate models, or large-scale, high-fidelity, site-specific simulations can be used as a propagation medium based on scenario requirements. This paper introduces DAWN’s design and initial implementation, detailing key architectural components, including the Physics Realization Engine (PhyRE), Runtime Infrastructure for Simulation Environments (RISE), and the design space exploration (DSE) suite. It concludes with demonstrations using unmodified 4G/LTE software available from srsRAN on computing resources ranging from a small cluster to ORNL’s Frontier Exascale system.

Wise, Mike [ORNL] (ORCID:0000000266120641)↗
DOE OSTI2024

Hardware Fuzzing with An Emulator

Bugs in digital logic have led to some significant security vulnerabilities. Hardware bugs are particularly troublesome since they cannot be easily patched. Additionally, if the bug is in the root of trust, all trust built upon it can be vulnerable. Traditional testing either require a deep knowledge of the system, creative attack vectors and lots of human interaction. This is not scalable as there are very few engineers that can wear the hat of a designer, a verification engineer, and a cybersecurity expert. Hardware fuzzing is a relatively new research area in dynamic hardware testing. It has proven to be an effective method for discovering bugs, unexpected behaviors, and security vulnerabilities in software. While hardware fuzzing is new to the hardware domain, it has a strong track record in software testing. Fuzzing is a testing technique that randomly mutates the input data to uncover bugs or vulnerabilities in the design. It is especially good at finding corner cases that test engineers can not envision. Another advantage over other dynamic testing techniques is that, if done well, deep knowledge of the design is not required. Additionally, fuzzing scales well. If the system is set up correctly, it can run unsupervised for weeks if necessary. In this work, we propose using hardware fuzzing to improve the input vector generation for an information flow tracking tool. To get reasonable throughput of test vectors, an emulator is targeted as the execution platform. Efficient emulator execution has some specific requirements.

42 ENGINEERING↗
DOE OSTI2021

Grizzly Development for Light Water Reactor and Advanced Reactor Applications in Fiscal Year 2021

This report summarizes work performed during Fiscal Year (FY) 2021 at Idaho National Laboratory (INL) for the U.S. Department of Energy’s Nuclear Engineering Advanced Modeling and Simulation (NEAMS) program for the Structural Materials and Chemistry Technical Area in the work package entitled “MS-21IN050106 - Structural Materials - INL.” This effort mainly focused on development and application of capabilities for engineering-scale analysis of nuclear reactor structural components in the Grizzly and BlackBear codes. These efforts include performance improvements and application of models for high-temperature component response, cluster dynamics modeling of precipitation in light water reactor pressure vessel steel, engineering-scale capability development in the areas of concrete simulation and reactor pressure vessel analysis, and preparation for and conducting an independent assessment of the adherence of these codes to software quality standards.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Building a Simplistic Automatic Extruder: Instrument Development Opportunities for the Laboratory

This work presents an automatic extruder as a research experience for undergraduate students. The system offers a user-friendly approach to preparing vesicles, such as liposomes or polymersomes, with a defined size and polydispersity properties crucial for research in biology and macromolecules. It comprises two syringe pumps connected by a membrane filter. The setup is controlled by software. Compared to manual extrusion, this automated system provides advantages, such as precisely controlled variables. The project describes a tool to enhance undergraduate learning in science and engineering laboratories. Building an automatic extruder serves as a simplified model of a complex industrial process. It offers a clear advantage: automating a well-understood manual extrusion process. To make this project accessible, it is broken down into three manageable tasks: software development, hardware assembly, and testing procedures. This breakdown describes the software created, the hardware components used, and the testing procedures conducted for this project. All project data, including software code, testing data, and procedures, are freely available online. This allows undergraduate students to not only begin their own projects but also contribute to this educational instrument’s ongoing development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Lessons learned from the development and implementation of a workforce training curriculum for advanced controls for high performance HVAC systems

Over the past decade, academic research on advanced controls has slowly transitioned into new software platforms, giving rise to various companies developing and deploying these innovative products, including solutions for light commercial HVAC systems. However, the current workforce remains widely unprepared to install, maintain and operate these systems, particularly complex software-based control platforms, as most workforce training programs still focus on traditional building automation for large commercial buildings. This paper presents the development and piloting of curriculum for three key types of professionals: ● Technicians (trade-level): installing and maintaining modern high-performance HVAC systems and controls ● Programmers (undergrad-level): developing and implementing advanced controls ● Engineers and energy professionals (undergrad/grad-level): managing and evaluating system performance We share details of the material developed including training videos, open-source software, instruction manuals. We also present the results of a pilot implementation of the training materials with real students.

Casillas, Armando↗
DOE OSTI2021

Quantitative concentration measurements in a turbulent helium jet using rainbow schlieren deflectometry

Rainbow schlieren deflectometry (RSD) is applied to acquire quantitative concentration measurements in a turbulent environment for the first time. RSD methodology is developed and validated using Rayleigh scattering data available in the literature. Experiments were performed in an initially laminar, momentum-driven helium jet injected into ambient air. Full-field measurements are acquired that span the laminar, transition, and fully turbulent regions of the jet. Furthermore, the RSD results are shown to provide accurate measurements in each region and also confirm the self-similar nature of the fully turbulent jet. Analysis shows that the transition from laminar to turbulent flow occurs across an axial span that decreases with increasing Reynolds number. Experiments with a long exposure time were conducted to evaluate the limitations of hardware averaging of the RSD signal in comparison with software averaging.

02 PETROLEUM↗
DOE OSTI2020

Hazard analysis for identifying common cause failures of digital safety systems using a redundancy-guided systems-theoretic approach

Replacing the existing aging analog instrumentation and control (I&C) systems with modern safety control and protection, digital technology offers one of the foremost means of performance improvements and cost reductions for the existing nuclear power plants (NPPs). However, the qualification of digital I&C systems remains a challenge, especially considering the issue of software common-cause failures (CCFs), which are difficult to address. With the application and upgrades of advanced digital I&C systems, software CCFs have become a potential threat to plant safety because most redundant designs use similar digital platforms or software in the operating and application systems. With complex designs of multilayer redundancy to meet the single-failure criterion, digital I&C safety systems (e.g., engineered safety-features actuation system [ESFAS]) are of a particular concern in the U.S. Nuclear Regulatory Commission (NRC) licensing procedures. Here, this paper applies a modularized approach to conduct redundancy-guided systems-theoretic hazard analysis for an advanced digital ESFAS with multilevel redundancy designs. Systematic methods and risk-informed tools are incorporated to address both hardware and software CCFs, which provide guidance to eliminate the causal factors of potential single points of failure in the design of digital safety systems in advanced plant designs.

42 ENGINEERING↗
DOE OSTI2023

Quantum Computing and Visualization: A Disruptive Technological Change Ahead

The focus of this Visualization Viewpoints article is to provide some background on quantum computing (QC), to explore ideas related to how visualization helps in understanding QC, and examine how QC might be useful for visualization with the growth and maturation of both technologies in the future. In a quickly evolving technology landscape, QC is emerging as a promising pathway to overcome the growth limits in classical computing. In some cases, QC platforms offer the potential to vastly outperform the familiar classical computer by solving problems more quickly or that may be intractable on any known classical platform. As further performance gains for classical computing platforms are limited by diminishing Moore’s Law scaling, QC platforms might be viewed as a potential successor to the current field of exascale-class platforms. Importantly, while present-day QC hardware platforms are still limited in scale, the field of quantum computing is robust and rapidly advancing in terms of hardware capabilities, software environments for developing quantum algorithms, and educational programs for training the next generation of scientists and engineers. After a brief introduction to QC concepts, the focus of this article is to explore the interplay between the fields of visualization and QC. First, visualization has played a role in QC by providing the means to show representations of the quantum state of single-qubits in superposition states and multiple-qubits in entangled states. Second, there are a number of ways in which the field of visual data exploration and analysis may potentially benefit from this disruptive new technology though there are challenges going forward.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

SAM™ (System Advisor Model™) [SWR-16-02, SWR-10-13]

See the SAM™ website to build a desktop version of the National Laboratory of the Rockies' (NLR's) System Advisor Model™ (SAM). https://sam.nlr.gov/ The System Advisor Model™ (SAM™) is a free techno-economic software model that facilitates decision-making for people in the renewable energy industry: -Project managers and engineers -Policy analysts -Technology developers -Researchers SAM can model many types of renewable energy systems: -Photovoltaic systems, from small residential rooftop to large utility-scale systems -Battery storage with Lithium ion, lead acid, or flow batteries for front-of-meter or behind-the-meter applications -Concentrating Solar Power systems for electric power generation, including parabolic trough, power tower, and linear Fresnel -Industrial process heat from parabolic trough and linear Fresnel systems -Wind power, from individual turbines to large wind farms -Marine energy wave and tidal systems -Solar water heating -Fuel cells -Geothermal power generation -Biomass combustion for power generation -High concentration photovoltaic systems SAM's financial models are for the following types of projects: -Residential and commercial projects where the renewable energy system is on the customer side of the electric utility meter (behind the meter), and power from the system is used to reduce the customer's electricity bill. -Power purchase agreement (PPA) projects where the system is connected to the grid at an interconnection point, and the project earns revenue through power sales. The project may be owned and operated by a single owner or by a partnership involving a flip or leaseback arrangement. -Third party ownership where the system is installed on the customer's (host) property and owned by a separate entity (developer), and the host is compensated for power generated by the system through either a PPA or lease agreement. For a more detailed description of SAM, see Blair et al. (2018), System Advisor Model (SAM) General Description (Version 2017.9.5), NREL/TP-6A20-70414. https://www.nrel.gov/docs/fy18osti/70414.pdf

Ryberg, David↗
DOE OSTI2023

pyNuMAD v.0.1

SAND2024-08606O The pyNuMAD software is used for managing wind turbine blade model data. pyNuMAD specializes in defining the geometry, materials, and boundary conditions for structural analysis of wind turbine blades. This includes loading in data files and providing an interface for users to make updates to the model. The software also features meshing functionality, which takes the blade model and creates a shell or brick mesh for use in finite element analysis. A typical user workflow might be: load in blade information from a yaml file, make adjustments to the blade properties, update the blade based on the adjustments, create a mesh of the blade, export this blade to another software for structural analysis. 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.

Paquette, Joshua↗
DOE OSTI2021

EXAGRAPH: Graph and combinatorial methods for enabling exascale applications

Combinatorial algorithms in general and graph algorithms in particular play a critical enabling role in numerous scientific applications. However, the irregular memory access nature of these algorithms makes them one of the hardest algorithmic kernels to implement on parallel systems. With tens of billions of hardware threads and deep memory hierarchies, the exascale computing systems in particular pose extreme challenges in scaling graph algorithms. The codesign center on combinatorial algorithms, ExaGraph, was established to design and develop methods and techniques for efficient implementation of key combinatorial (graph) algorithms chosen from a diverse set of exascale applications. Algebraic and combinatorial methods have a complementary role in the advancement of computational science and engineering, including playing an enabling role on each other. In this paper, we survey the algorithmic and software development activities performed under the auspices of ExaGraph from both a combinatorial and an algebraic perspective. In particular, we detail our recent efforts in porting the algorithms to manycore accelerator (GPU) architectures. We also provide a brief survey of the applications that have benefited from the scalable implementations of different combinatorial algorithms to enable scientific discovery at scale. We believe that several applications will benefit from the algorithmic and software tools developed by the ExaGraph team.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Twinac: initiation of a community-driven accelerator digital twin framework

We present the initiation of a community-driven framework for the integration of accelerator digital twins into control systems: Twinac. Few facilities have fully integrated accelerator digital twins like at Cornell’s CHESS. Many facilities have active research to employ surrogate models to aid in operational decisions like at Argonne’s ALS, MSU’s FRIB, SLAC’s LCLS-II, and Fermilab’s FAST/IOTA, PIP-II, and main complex. To lower the barrier to entry for all accelerator facilities to build and benefit from a digital twin of their own accelerators, we propose the following software framework. Twinac will provide the capability to compose one’s own digital twin using reusable components engineered at other facilities. With this model in place, Twinac will also support tools for (1) predictive maintenance systems; (2) discovery of correlated but uncontrolled environmental factors, like seasonal temperature variations causing performance changes on power supplies, magnets, etc.; and (3) prototyping and updating sophisticated optimization and controls algorithms. The Twinac framework will enable sharing and simplified deployment of modeled components and control algorithms at all facilities. With an inter-facility team to build and support the Twinac framework, it will be easy to publish and try out the latest advancements at one’s own facility.

Miceli, Tia [Fermilab]↗
DOE OSTI2026

Truchas Overview

Truchas and Truchas-PBF are two sister codes for part-scale multi-physics modeling of manufacturing processes. Both programs are open source and made publicly available. They’re designed for efficient use of HPC resources and can be programmatically driven from Python packages. This enables automatic execution and analysis of ensembles of simulations, in some cases allowing 1000s of simulations to be evaluated in a day on HPC. Beyond just giving engineers a window into the concealed internal state of a system, the goal of Truchas is to provide a framework for developing novel manufacturing processes by understanding how the entire space of engineering inputs affects thermal state. It often is used to explore combinations of capabilities uncommon in commercial software, or to scale up analyses beyond the capabilities of commercial software.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Added value for integrated marine energy data systems

Launched in 2019, the Portal and Repository for Information on Marine Renewable Energy (PRIMRE) provides centralized access, standardization, community building, and integration of United States (U.S.) databases, tools and codes, and other resources that cover a range of marine energy information. The PRIMRE universe contains a series of Knowledge Hubs that represent data and information on testing of marine energy devices (MHKDR); environmental effects (Tethys); engineering and technical papers (Tethys Engineering); descriptions of marine energy companies and technologies (Marine Energy Projects Database); codes and models (Marine Energy Software); and guidance on testing and measurements (Telesto). Content is added to PRIMRE by applying a set of Guidelines and Best Practices (PRIMRE Guidelines). An aggregate search across the PRIMRE site enables users to find data and information from all the PRIMRE Knowledge Hubs simultaneously, using a single entry-point (PRIMRE Search). In addition to providing access to a range of data and information on marine energy development, testing, and effects, PRIMRE allows for the development of value added products and processes that will help move the marine energy industry forward. The PRIMRE team has recently launched two key initiatives in the U.S.—Signature Projects and Lessons Learned. Outputs and outcomes from these two initiatives will be highlighted in this paper. The Signature Projects initiative is intended to bring focus to a selection of ongoing and completed marine energy projects funded by the U.S. Department of Energy’s Water Power Technologies Office (WPTO), and to inform the marine energy community of what investigations have been undertaken, what tools are available, and where gaps in information persist. Each Signature Project tags papers, reports, and data from large marine energy research projects, providing easy access and attention to all the output and associated products from each project. The Lessons Learned initiative is intended to ensure that hard-won achievements are recognized and available for those who come later, that missteps and unfortunate outcomes can be prevented in future, and that efficiencies and effective shortcuts can be publicized and used as the marine energy industry moves forward. This initiative builds off the Knowledge Hubs and reaches out to members of the marine energy community, particularly technology developers and researchers, to integrate experience in the development, deployment, assessment, success, and challenges while creating this new industry and field of study.

Copping, Andrea E.↗
DOE OSTI2021

Added value for integrated marine energy data systems

Launched in 2019, the Portal and Repository for Information on Marine Renewable Energy (PRIMRE) provides centralized access, standardization, community building, and integration of United States (U.S.) databases, tools and codes, and other resources that cover a range of marine energy information. The PRIMRE universe contains a series of Knowledge Hubs that represent data and information on testing of marine energy devices (MHKDR); environmental effects (Tethys); engineering and technical papers (Tethys Engineering); descriptions of marine energy companies and technologies (Marine Energy Projects Database); codes and models (Marine Energy Software); and guidance on testing and measurements (Telesto). Content is added to PRIMRE by applying a set of Guidelines and Best Practices (PRIMRE Guidelines). An aggregate search across the PRIMRE site enables users to find data and information from all the PRIMRE Knowledge Hubs simultaneously, using a single entry-point (PRIMRE Search). In addition to providing access to a range of data and information on marine energy development, testing, and effects, PRIMRE allows for the development of value added products and processes that will help move the marine energy industry forward. The PRIMRE team has recently launched two key initiatives in the U.S.—Signature Projects and Lessons Learned. Outputs and outcomes from these two initiatives will be highlighted in this paper. The Signature Projects initiative is intended to bring focus to a selection of ongoing and completed marine energy projects funded by the U.S. Department of Energy’s Water Power Technologies Office (WPTO), and to inform the marine energy community of what investigations have been undertaken, what tools are available, and where gaps in information persist. Each Signature Project tags papers, reports, and data from large marine energy research projects, providing easy access and attention to all the output and associated products from each project. The Lessons Learned initiative is intended to ensure that hard-won achievements are recognized and available for those who come later, that missteps and unfortunate outcomes can be prevented in future, and that efficiencies and effective shortcuts can be publicized and used as the marine energy industry moves forward. This initiative builds off the Knowledge Hubs and reaches out to members of the marine energy community, particularly technology developers and researchers, to integrate experience in the development, deployment, assessment, success, and challenges while creating this new industry and field of study.

Copping, Andrea E.↗