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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Leveraging OpenStudio's Application Programming Interfaces: Preprint

OpenStudio development efforts have been focused on providing Application Programming Interfaces (APIs) where users are able to extend OpenStudio without the need to compile the open source libraries. This paper will discuss the basic purposes and functionalities of the core libraries that have been wrapped with APIs including the Building Model, Results Processing, Advanced Analysis, UncertaintyQuantification, and Data Interoperability through Translators. Several building energy modeling applications have been produced using OpenStudio's API and Software Development Kits (SDK) including the United States Department of Energy's Asset ScoreCalculator, a mobile-based audit tool, an energy design assistance reporting protocol, and a portfolio scale incentive optimization analysismethodology. Each of these software applications will be discussed briefly and will describe how the APIs were leveraged for various uses including high-level modeling, data transformations from detailed building audits, error checking/quality assurance of models, and use of high-performance computing for mass simulations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Pronghorn: A Multidimensional Coarse Mesh Application for Advanced Reactor Thermal-Hydraulics

This paper presents an overview of Pronghorn, a multiscale thermal-hydraulic (T/H) application developed by Idaho National Laboratory and the University of California, Berkeley. Pronghorn, built on the open-source finite element Multiphysics Object-Oriented Simulation Environment (MOOSE), leverages state-of-the-art physical models, numerical methods, and nonlinear solvers to deliver fast-running advanced reactor T/H simulation capabilities within a modern software engineering environment. This work summarizes the physical models, multiphysics and multiscale coupling, and numerical discretization in Pronghorn with emphasis on our initial target application to pebble bed reactors (PBRs). A diverse set of applications are shown to depressurized natural circulation in the SANA experiments, forced convection in the Pebble Bed Modular Reactor, three-dimensional (3-D)/one-dimensional coupling of Pronghorn and RELAP-7 systems T/H for loop analysis in the High Temperature Reactor Power Module, and forced convection in the Mark-1 Pebble Bed Fluoride-Salt-Cooled High-Temperature Reactor. A multiphysics coupling of Pronghorn, RELAP-7, and Griffin deterministic neutronics for a gas-cooled PBR demonstrates the capability of the MOOSE framework for reactor design calculations. These applications highlight the verification and validation underlying Pronghorn’s software development while emphasizing features that improve upon capabilities offered by legacy tools in areas such as 3-D unstructured meshing, physics modeling, and multiphysics coupling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

An LLVM Instrumentation Plug-in for Score-P

Reducing application runtime, scaling parallel applications to higher numbers of processes/threads, and porting applications to new hardware architectures are tasks necessary in the software development process. Therefore, developers have to investigate and understand application runtime behavior. Tools such as monitoring infrastructures that capture performance relevant data during application execution assist in this task. The measured data forms the basis for identifying bottlenecks and optimizing the code.Monitoring infrastructures need mechanisms to record application activities in order to conduct measurements. Automatic instrumentation of the source code is the preferred method in most application scenarios. We introduce a plug-in for the LLVM infrastructure that enables automatic source code instrumentation at compile-time. In contrast to available instrumentation mechanisms in LLVM/Clang, our plug-in can selectively include/exclude individual application functions. This enables developers to fine-tune the measurement to the required level of detail while avoiding large runtime overheads due to excessive instrumentation.

Tschüter, Ronny↗
DOE OSTI2022

Caldera_Grid

Caldera Grid is part of Caldera software platform, a suite of collective, open-source tools that was developed to improve the state of the art in modeling the impacts of Electric Vehicle (EV) charging on the grid. Caldera Grid is a co-simulation framework implemented using Hierarchical Engine for Large scale Infrastructure Co-Simulation (HELICS). The framework facilitates the co-simulation of EV charging and Smart Charge Management (SCM) strategies in Caldera Infrastructure Charge Model (ICM) with distribution level grid models in OpenDSS. Vehicle energy needs and charge session requirements generated using Caldera Charge Decision Module (CDM) are fed in as input to Caldera Grid. The EV charging models in Caldera ICM simulates both the uncontrolled charging loads as well as loads modified by the SCM strategies to develop distributed load profiles for each grid node hosting an Electric Vehicle Supply Equipment (EVSE) – also known as chargers. These loads were simulated in OpenDSS alongside existing distribution feeder loads. Each of these models are co-simulated in a HELICS federate. The HELICS co-simulation framework facilitates communication and synchronization between the federates. By co-simulating EV loads and distribution feeder loads, Caldera Grid can assess the potential grid impacts of EV charging on distribution feeders under various grid conditions. A control strategy federate is implemented with an interface where control strategies based on feedback from EV charging status and grid conditions can be developed and implemented. The platform can also support multiple control strategies in a single co-simulation.

Sundarrajan, ManojKumar Cebol↗
DOE OSTI2024

minervachem

Minervachem is a tool for cheminformatics and machine learning in chemistry. It includes both algorithms from existing literature and algorithms which we have developed. Its features center around two main themes: molecular representations and algorithms, both for molecular machine learning. It provides a scikit-learn transformer interface for molecular featurization and an estimator interface for machine learning algorithms. It also provides visualization tools for explaining machine learning predictions. We aim to continue developing this software to improve its performance and usability and expand its capabilities within the realm of molecular machine learning, cheminformatics, and visualization.

Lubbers, Nicholas↗
DOE OSTI2015

Integrated PEV Charging Solutions and Reduced Energy for Occupant Comfort [Brochure]

Brochure on Vehicle Testing and Integration Facility, featuring the Vehicle Modification Facility, Vehicle Test Pad and ReCharge Integrated Demonstration System. Plug-in electric vehicles (PEVs) offer the opportunity to shift transportation energy demands from petroleum to electricity, but broad adoption will require integration with other systems. While automotive experts work to reduce the cost of PEVs, fossil fueled cars and trucks continue to burn hundreds of billions of gallons of petroleum each year - not only to get from point A to point B, but also to keep passengers comfortable with air conditioning and heat. At the National Renewable Energy Laboratory (NREL), three installations form a research laboratory known as the Vehicle Testing and Integration Facility (VTIF). At the VTIF, engineers are developing strategies to address two separate but equally crucial areas of research: meeting the demands of electric vehicle-grid integration and minimizing fuel consumption related to vehicle climate control. Part of NREL's Center for Transportation Technologies and Systems (CTTS), the VTIF is dedicated to renewable and energy efficient solutions. This facility showcases technology and systems designed to increase the viability of sustainably powered vehicles. NREL researchers instrument every class of on-road vehicle, conduct hardware and software validation for electric vehicle (EV) components and accessories, and develop analysis tools and technology for the Department of Energy, other government agencies and industry partners. Research conducted at the VTIF examines the interaction of building energy systems, utility grids, renewable energy sources and PEVs, integrating energy management solutions, and maximizing potential greenhouse gas (GHG) reduction, while smoothing the transition and reducing costs for EV owners. NREL's collaboration with automakers, charging station manufacturers, utilities and fleet operators to assess technologies using VTIF resources is designed to enable PEV communication with the smart grid and create opportunities for vehicles to play an active role in building and grid management. Ultimately, this creates value for the vehicle owner and will help renewables be deployed faster and more economically, making the U.S. transportation sector more flexible and sustainable.

02 PETROLEUM↗
DOE OSTI2016

Parallel Execution of Functional Mock-up Units in Buildings Modeling

A Functional Mock-up Interface (FMI) defines a standardized interface to be used in computer simulations to develop complex cyber-physical systems. FMI implementation by a software modeling tool enables the creation of a simulation model that can be interconnected, or the creation of a software library called a Functional Mock-up Unit (FMU). This report describes an FMU wrapper implementation that imports FMUs into a C++ environment and uses an Euler solver that executes FMUs in parallel using Open Multi-Processing (OpenMP). The purpose of this report is to elucidate the runtime performance of the solver when a multi-component system is imported as a single FMU (for the whole system) or as multiple FMUs (for different groups of components as sub-systems). This performance comparison is conducted using two test cases: (1) a simple, multi-tank problem; and (2) a more realistic use case based on the Modelica Buildings Library. In both test cases, the performance gains are promising when each FMU consists of a large number of states and state events that are wrapped in a single FMU. Load balancing is demonstrated to be a critical factor in speeding up parallel execution of multiple FMUs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Evaluation of the FIR Example using Xilinx Vivado High-Level Synthesis Compiler

Compared to central processing units (CPUs) and graphics processing units (GPUs), field programmable gate arrays (FPGAs) have major advantages in reconfigurability and performance achieved per watt. This development flow has been augmented with high-level synthesis (HLS) flow that can convert programs written in a high-level programming language to Hardware Description Language (HDL). Using high-level programming languages such as C, C++, and OpenCL for FPGA-based development could allow software developers, who have little FPGA knowledge, to take advantage of the FPGA-based application acceleration. This improves developer productivity and makes the FPGA-based acceleration accessible to hardware and software developers. Xilinx Vivado HLS compiler is a high-level synthesis tool that enables C, C++ and System C specification to be directly targeted into Xilinx FPGAs without the need to create RTL manually. The white paper [1] published recently by Xilinx uses a finite impulse response (FIR) example to demonstrate the variable-precision features in the Vivado HLS compiler and the resource and power benefits of converting floating point to fixed point for a design. To get a better understanding of variable-precision features in terms of resource usage and performance, this report presents the experimental results of evaluating the FIR example using Vivado HLS 2017.1 and a Kintex Ultrascale FPGA. In addition, we evaluated the half-precision floating-point data type against the double-precision and single-precision data type and present the detailed results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Autonomous Discovery in Science and Engineering

The Center for Advanced Mathematics for Energy Research Applications (CAMERA) is an integrated, cross-disciplinary center aimed at inventing, developing, and delivering the fundamental new mathematics required to capitalize on experimental investigations at scientific facilities. Jointly funded by the Office of Advanced Scientific Computing Research (ASCR) and the Office of Basic Energy Sciences (BES) within the US Department of Energy’s Office of Science, CAMERA identifies areas in experimental science that can be aided by new mathematical insights, develops the needed algorithmic tools, and delivers them as user-friendly software to the experimental community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Fixed-Energy Response-Function Analysis with Multi-Efficiency (FRAM) Software, Version 6

Researchers at Los Alamos National Laboratory have developed FixedEnergy Response- Function Analysis with Multiple Efficiency (FRAM), a powerful software tool for gamma-ray spectrometry isotopic analysis. This tool leverages Los Alamos expertise in nuclear safeguards, radiation detection systems, and related analysis techniques. A household name in the non-destructive assay community for over two decades, FRAM determines a special nuclear material source's isotopic composition by analyzing gamma-ray spectra. Los Alamos researchers have released the latest version of FRAM that incorporates several updates to the 2013 major release of FRAM, Version 5.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Distribution Integration Solution Cost Options (DISCO) [Slides]

DISCO is a Python-based NREL software tool for conducting scalable, repeatable distribution analyses. Although DISCO was originally developed to support photovoltaic impact analyses, it can also be used to understand the impact of other distributed energy resources and load changes on distribution systems. This presentation took place on April 9, 2024, and included NREL power grid researchers Sherin Ann Abraham and Shibani Ghosh.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Vitis CI/CD & Containerization

Modern development flows that use tooling for automated building, testing, and deployment of software are becoming the norm for large scale software and hardware projects. These flows offer quite a few advantages that make them desirable, but when attempting to implement them for projects that use FPGAs, some complications can arise when attempting to integrate them with traditional FPGA toolchains and deployment workflows. In this poster, we present early our early efforts integrating the Vitis FPGA toolchain into a modern, Kuberentes and Github actions based CI/CD pipeline.

Hawks, Benjamin G. [Fermilab]↗
DOE OSTI2020

Machine Learning for Automated Extraction of Building Geometry

As data science comes to buildings, the promise of using machine learning and novel sources of data has received much attention. Advances in machine learning and computer vision algorithms, combined with increased access to unstructured data (e.g., images and text), have created an opportunity for automated extraction of building characteristics – cost-effectively, and at scale. Acquisition of features such as footprint are time consuming and costly to acquire with today’s manual methods, but can be streamlined through intelligent software-based solutions applied to satellite images. When combined with aerial RGB and thermal images, full 3D geometries and thermal maps can be constructed to determine additional characteristics such as window to wall ratio, height, number of stories and envelope thermal characteristics. In this paper we present three contributions to accelerate these high potential opportunities: (1) a methodical analysis of how these features can be integrated into today’s simulation and data driven software tools to enhance efficiency measure identification and owner/operator decision making; (2) development and accuracy testing of open source deep neural network methods to extract building footprints from satellite imagery, including the curation and application of openly available GIS datasets for training and continued development by others; and (3) an open framework for drone-based image capture and creation of 3D building geometries. This work represents an important bridge between high-level studies that span diverse application areas and those that detail point solutions yet cannot be easily replicated or extended.

Touzani, Samir↗
DOE OSTI2022

The DeepLynx Data Warehouse

Digital Engineering and the development of digital twins necessitate the use of highly sophisticated tools and software. These methodologies and systems bring many benefits but rely on accomplishing challenging goals such as disparate data and systems integration into a single cohesive and holistic system. Idaho National Laboratory has recently released an open-source data warehouse – DeepLynx – to help in the planning, creation, execution, and management of projects in the digital engineering space, with an emphasis on supporting digital twins in an operational space.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Methodology and Tool for the Physical Security Analysis of Micro and Advanced Reactors

This work proposes a dynamic evaluation methodology to relax the conservatism in physical security evaluation, by leveraging an ongoing work in the Light Water Reactor Sustainability pathway. This methodology is implemented in a dynamic risk assessment tool named Event Modeling Risk Assessment using Linked Diagrams (EMRALD). The work extends EMRALD’s capability to support a sandbox feature where analysts can easily create attack scenarios and modify advanced/small modular reactor (A/SMR) security and safety features using templates. This approach saves time and cost since the analysis does not require creating detailed computer-aided design models, as is commonly required in commercial force-on-force software tools. EMRALD is completely free to use at https://emraldapp.inl.gov. We have developed basic templates including physical barriers, intrusion sensors, physical areas, and safety actions, that can be downloaded from EMRALD’s GitHub site: https://github.com/idaholab/EMRALD. These templates use generic data commonly used for training purposes, which do not reflect any actual operating nuclear reactor. Users may adjust the data in the templates with their own dataset and/or create new templates in EMRALD. The proposed methodology combines security and safety by assessing sabotage effects up to the radiological consequence to the public instead of merely the core damage state. This practice follows the industry standard for advanced non-light-water reactors currently proposed for endorsement by the Nuclear Regulatory Commission. The combination of security and safety is expressed in an achievability-consequence chart. EMRALD can be used to generate data for this chart. A hypothetical case study using a representative sodium-cooled fast reactor (SFR) facility is presented in this report to demonstrate this methodology. This case study does not contain any actual nuclear plant information. This work will benefit A/SMR vendors and utilities to implement security by design during the reactor design iteration phase, such that they do not have to perform upgrades and retrofits to the reactor after it is installed to improve its physical protection system. The tool may also be used to analyze domestic or foreign reactor designs to support the International Nuclear Security Techniques for Advanced Reactors (INSTAR) bilateral missions. Future works are planned to implement the methodology on a reference SFR reactor and a reference high-temperature gas-cooled reactor to obtain insights and lessons-learned for the A/SMR community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Modeling receiver flux of commercial power tower concentrating solar power plants using ray tracing: a round-robin comparison of SolTrace, Solstice, and TieSOL

This study presents a multi-stage, cross-validation comparison of three software packages for Monte Carlo ray tracing (MCRT) applied to central tower concentrating solar power (CSP) systems. The three packages evaluated are: (1) SolTrace, an open-source tool developed by the National Renewable Energy Laboratory (NREL); (2) Solstice, an open-source program created by CNRS-PROMES and Meso-Star, with enhancements for CSP applications (called solsticepy) from the Australian National University; and (3) TieSOL, a commercial software developed by Tietronix. This investigation extends previous ray tracing comparisons by incorporating models of multi-facet heliostats within a commercial-scale solar field, taking into account zoned focal lengths and canting configurations. Receiver flux distributions were compared across the tools using a series of case studies, including single-heliostat scenarios, isolated blocking situations, and comprehensive full-field simulations. The case studies were designed to diagnose differences across the models at varying levels of complexity, and to identify and resolve discrepancies as additional parameters were introduced. Key factors examined in the analysis include sun positions, heliostat location, facet and canting focus, and aimpoint strategies. The comparison aims to improve the accuracy and reliability of these tools while providing benchmark cases for validating future optical modeling tools.

14 SOLAR ENERGY↗
DOE OSTI2025

RAG for FLAG: AI Assistance for a Physics Code

Artificial intelligence (AI) has quickly become an important tool in scientific research, where significant efforts are underway to develop tools that will expedite the research process. One area of particular impact is scientific software, which can be particularly complex, and therefore time consuming to learn and use effectively. AI assistants are increasingly helping to streamline the process by performing tasks such as interactively answering user questions or suggesting solutions. Los Alamos National Laboratory (LANL) develops several advanced scientific codes, such as FLAG, which can be used to run multiphysics simulations. With this study, our goal was to develop an AI assistant for FLAG that could help make the process of understanding the software and running physics simulations more efficient. To develop an AI assistant for FLAG, we used a method called retrieval-augmented generation (RAG), which is a technique that uses information from relevant data sources to enhance the accuracy of large language models (LLMs). We used the FLAG user manual and other FLAG documentation as the knowledge base for the RAG system. When a user provides a query, RAG retrieves relevant sections from the knowledge base in response, then uses those excerpts to generate grounded and contextually rich answers. We found that our AI assistant was able to provide context aware answers and source references to user queries. To evaluate performance, we developed a set of 40 benchmark questions and compared the accuracy of the responses to those of two standard LLMs without retrieval. Our AI assistant significantly outperformed the standard LLMs at answering FLAG-related questions, with an 82.5% accuracy rate, compared to 47.5% for both of the standard LLMs. This has the potential to make the process of learning and using FLAG much easier, especially for new users. Ultimately, it supports LANL’s broader mission by empowering scientists and engineers to focus more on discovery and analysis rather than on navigating complex software systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Cementitious Barriers Partnership (CBP): Training and Release of CBP Toolbox Software, Version 1.0 - 13480

The Cementitious Barriers Partnership (CBP) Project is a multi-disciplinary, multi-institutional collaboration supported by the Office of Tank Waste Management within the Office of Environmental Management of U.S. Department of Energy (US DOE). The CBP program has developed a set of integrated tools (based on state-of-the-art models and leaching test methods) that improve understanding and predictions of the long-term hydraulic and chemical performance of cementitious barriers used in nuclear applications. Tools selected for and developed under this program are intended to evaluate and predict the behavior of cementitious barriers used in near-surface engineered waste disposal systems for periods of performance up to or longer than 100 years for operating facilities and longer than 1,000 years for waste management purposes. CBP software tools were made available to selected DOE Office of Environmental Management and field site users for training and evaluation based on a set of important degradation scenarios, including sulfate ingress/attack and carbonation of cementitious materials. The tools were presented at two-day training workshops held at U.S. National Institute of Standards and Technology (NIST), Savannah River, and Hanford included LeachXS{sup TM}/ORCHESTRA, STADIUM{sup R}, and a CBP-developed GoldSim Dashboard interface. Collectively, these components form the CBP Software Toolbox. The new U.S. Environmental Protection Agency leaching test methods based on the Leaching Environmental Assessment Framework (LEAF) were also presented. The CBP Dashboard uses a custom Dynamic-link library developed by CBP to couple to the LeachXS{sup TM}/ORCHESTRA and STADIUM{sup R} codes to simulate reactive transport and degradation in cementitious materials for selected performance assessment scenarios. The first day of the workshop introduced participants to the software components via presentation materials, and the second day included hands-on tutorial exercises followed by discussions of enhancements desired by participants. Tools were revised based on feedback obtained during the workshops held from April through June 2012. The resulting improved CBP Software Toolbox, including evaluation versions of and LeachXS{sup TM}/ORCHESTRA and STADIUM{sup R} has been made available to workshop and selected other participants for further assessment. Inquiries about future workshops and requests for access to the Toolbox software can be made via the CBP web site [1]. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗