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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Reinforcement Learning for Distribution Grid Optimization (PyCIGAR) v0.1

PyCIGAR is a python software package that merges off-the-shelf reinforcement learning libraries (RLLib and Ray) with electric power distribution system simulation tools (OpenDSS and a custom power flow solver built by LBL). PyCIGAR enables the training of neural networks to optimize the behavior of different components in the electric distribution grid, such as control systems in photovoltaic rooftop solar inverters and electric battery storage systems. The software package has been used to train neural networks to update settings in photovoltaic rooftop solar inverter control systems to mitigate cyber attacks on other solar photovoltaic rooftop devices.

Arnold, Daniel↗
DOE OSTI2020

PyNetUQ

SAND2021-3242 O PyNetUQ is a Python library for network uncertainty propagation. Custom interface classes for components are modeled individually with potentially distinct simulation tools. 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.

Tencer, John↗
DOE OSTI2022

cabbi-bio/BECT-ABM

The emergence of the cellulosic bioeconomy requires not only adequate technological, economic, and policy advances, but also effective communication and coordination among the multiple stakeholders in the bioeconomy community. Aiming to facilitate stakeholder communication and collaboration for cellulosic bioeconomy growth, an agent-based model is developed as a community communication tool in this study. The tool simulates the behaviors and interactions of key stakeholders, as well as the responses and interactions between the stakeholders and biophysical, socioeconomic, and environmental conditions. The agent behavior rules are developed and validated based on behavior and economic theories and information attained from a stakeholder focus group study and a land use survey.

Yang, Pan↗
DOE OSTI2025

The Satellite Image Simulation Toolkit

The Satellite Image Simulation Toolkit (SatIST) is a python software package designed to generate diverse and realistic satellite imaging scenarios. It serves as a toolkit for simulating data that supports the development and testing of algorithms used in satellite detection, calibration, and characterization. SIST provides a suite of simulation tools that allow users to replicate various satellite observation conditions, including sidereal and target tracking. By enabling the creation of scenarios that mimic real-world satellite operations, SIST facilitates advancements in satellite image data processing and the study of satellite behavior under different observational parameters.

Perloff, AlexxS [Lawrence Livermore National Labor↗
DOE OSTI2018

A massively parallel and memory-efficient FEM toolbox with a hybrid total FETI solver with accelerator support

In this article, we present the ExaScale PaRallel finite element tearing and interconnecting SOlver (ESPRESO) finite element method (FEM) library, which includes an FEM toolbox with interfaces to professional and open-source simulation tools, and a massively parallel hybrid total finite element tearing and interconnecting (HTFETI) solver which can fully utilize the Oak Ridge Leadership Computing Facility Titan supercomputer and achieve superlinear scaling. This article presents several new techniques for finite element tearing and interconnecting (FETI) solvers designed for efficient utilization of supercomputers with a focus on (i) performance—we present a fivefold reduction of solver runtime for the Laplace equation by redesigning the FETI solver and offloading the key workload to the accelerator. We compare Intel Xeon Phi 7120p and Tesla K80 and P100 accelerators to Intel Xeon E5-2680v3 and Xeon Phi 7210 central processing units; and (ii) memory efficiency—we present two techniques which increase the efficiency of the HTFETI solver 1.8 times and push the limits of the largest possible problem ESPRESO that can solve from 124 to 223 billion unknowns for problems with unstructured meshes. Finally, we show that by dynamically tuning hardware parameters, we can reduce energy consumption by up to 33%.

Computer Science↗
DOE OSTI2022

New capabilities of the MORET 6 Monte Carlo neutron transport code

The MORET code is a simulation tool that solves the transport equation for neutrons using the Monte Carlo method. It allows users to model complex three-dimensional geometrical configurations in a user-friendly way. New features have been introduced to extend the application field of MORET beyond the usual criticality calculations for which it has been initially designed. The most important change is the addition of an analog fixed source mode which allows studies of systems of any reactivity combined with very flexible outputs. Other useful improvements have been added concerning the geometric part, the fission matrix, the multigroup sensitivity coefficients and the outputs. This paper presents an overview of these new features. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Technical and Regulatory Aspects of Integrating Safety and Security at Nuclear Power Plants

This paper provides an overview of lessons learned in applying a dynamic computational framework that links results from a commercially available FOF simulation tool, a commercially available thermal-hydraulic tool, and EMRALD to an operating commercial nuclear power plant. This process of including plant procedures and multiple analysis results is being called Modeling and Analysis for Safety Security using Dynamic EMRALD Framework. It describes how a user could integrate their plant-specific FOF models with safety mitigation actions in EMRALD, and with thermal-hydraulic tools, such as MAAP. The work performed in this paper is based on a generic EMRALD model with actual plant data used for the analysis. However, only the generic model and general results of the analysis are presented for dissemination. No plant’s sensitive information is included in this paper. The discussion shows examples of insights that can be obtained from the proposed methodology.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Small-angle X-ray scattering characteristics of mouse brain: Planar imaging measurements and tomographic imaging simulations

Small-angle x-ray scattering (SAXS) imaging can differentiate tissue types based on their nanoscale molecular structure. However, characterization of the coherent scattering cross-section profile of relevant tissues is needed to optimally design SAXS imaging techniques for a variety of biomedical applications. Reported measured nervous tissue x-ray scattering cross sections under a synchrotron source have had limited agreement. We report a set of x-ray cross-section measurements obtained from planar SAXS imaging of 1 mm thick mouse brain (APP/PS1 wild-type) coronal slices using an 8 keV laboratory x-ray source. Two characteristic peaks were found at 0.96 and 1.60 nm -1 attributed to myelin. The peak intensities varied by location in the slice. We found that regions of gray matter, white matter, and corpus callosum could be segmented by their increasing intensities of myelin peaks respectively. Measured small-angle x-ray scattering cross sections were then used to define brain tissue scattering properties in a GPU-accelerated Monte Carlo simulation of SAXS computed tomography (CT) using a higher monochromatic x-ray energy (20 keV) to study design trade-offs for noninvasive in vivo SAXS imaging on a small-animal head including radiation dose, signal-to-noise ratio (SNR), and the effect of skull presence on the previous two metrics. Simulation results show the estimated total dose to the mouse head for a single SAXS-CT slice was 149.4 mGy. The pixel SNR was approximately 30.8 for white matter material whether or not a skull was present. In this early-stage proof-of-principle work, we have demonstrated our brain cross-section data and simulation tools can be used to assess optimal instrument parameters for dedicated small-animal SAXS-CT prototypes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Performance data for an axial-flow turbine with passive adaptive blades

To support the development of simulation tools for passive adaptive turbine rotors, an experimental data set from a laboratory-scale axial-flow turbine with passive adaptive blades is provided. The 0.45-meter diameter turbine was tested in the Alice C. Tyler Flume at the University of Washington. Blade and rotor loads were measured at 1 kHz using six-axis force/torque sensors while deflection and twist at the blade tip were tracked using a high-speed camera. This data submission includes a technical report, the raw and processed experimental data, and a README file explaining the file/folder structure and where to find the processing/plotting scripts used to produce the figures in the technical report.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Model America - 2022 Arizona Building Energy Simulation Results from ORNL's AutoBEM

This dataset contains energy simulation outputs using ORNL's AutoBEM, covering the summer months (June 1st to August 31st) (named by "county_name.csv") and full-year periods (in output_all_year.zip) for each county in Arizona, USA. The data package includes simulation results such as basic energy metrics and anthropogenic emissions estimates. Files are provided in .csv. These data were generated to analyze the impact of weather conditions on energy use and emissions across urban and rural environments in Arizona, aiming to support research on urban heat islands, energy efficiency, and building retrofitting strategies. The source data for this work include NASA POWER weather datasets and computational models run using AutoBEM (i.e., an automated, large-scale energy simulation tool leveraging OpenStudio/EnergyPlus). This dataset can assist researchers, urban planners, and policymakers in developing climate-resilient energy systems and understanding anthropogenic contributions to local environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Electron Beam Dynamics Simulation for Electron Lenses

A test stand is under construction at CERN to study high perveance electron guns, electron beam dynamics, and electron beam diagnostics for electron lenses. It will be used to test electron guns for the Hollow Electron Lenses under consideration for beam halo control for High Luminosity LHC (CERN), and for the Space Charge Compensation at SIS18 (GSI) in the frame of the EU funded ARIES project. In order to prepare for this test stand, simulations will be presented and compared with experiments undertaken at the Fermilab (FNAL) electron lens test stand. These were conducted using a hollow electron gun, with the magnetic field configuration and beam current varied to study their effect. The impact of imperfections on the beam dynamics and overall quality of the electron beam will be discussed. A method for comparing experimental data with simulation is also presented to allow bench-marking of the computer models and simulation tools that will later be applied to the analysis of measurements performed at CERN.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

PyPVRPM: Photovoltaic Reliability and Performance Model in Python

The ability to perform accurate techno-economic analysis of solar photovoltaic (PV) systems is essential for bankability and investment purposes. Most energy yield models assume an almost flawless operation (i.e., no failures); however, realistically, components fail and get repaired stochastically. This package, PyPVRPM, is a Python translation and improvement of the Language Kit (LK) based PhotoVoltaic Reliability Performance Model (PVRPM), which was first developed at Sandia National Laboratories in Goldsim software (Granata et al., 2011) (Miller et al., 2012). PyPVRPM allows the user to define a PV system at a specific location and incorporate failure, repair, and detection rates and distributions to calculate energy yield and other financial metrics such as the levelized cost of energy and net present value (Klise, Lavrova, et al., 2017). Our package is a simulation tool that uses NREL’s Python interface for System Advisor Model (SAM) (National Renewable Energy Laboratory, 2020b) (National Renewable Energy Laboratory, 2020a) to evaluate the performance of a PV plant throughout its lifetime by considering component reliability metrics. Besides the numerous benefits from migrating to Python (e.g., speed, libraries, batch analyses), it also expands on the failure and repair processes from the LK version by including the ability to vary monitoring strategies. These failures, repairs, and monitoring processes are based on user-defined distributions and values, enabling a more accurate and realistic representation of cost and availability throughout a PV system’s lifetime.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

EchemFEM: A Firedrake-based Python package for electrochemical transport

The transition from fossil fuels to renewable energy has brought about a rapid increase in the availability of clean electricity. However, electricity generated from sources such as wind and solar are limited to intermittent operation due to daily and seasonal variation. One solution is to utilize electrochemical devices in energy storage and electrochemical manufacturing applications, where they can harness surplus energy and decarbonize chemical industries traditionally reliant on petrochemical feedstocks. Managing the growing prevalence of renewable energy underscores the importance of developing and scaling up these technologies, which can in turn facilitate the achievement of carbon emission reduction commitments of companies and developed economies. Likewise, the electrification of transport creates an increasing need for energy-dense electrochemical energy storage devices such as batteries and supercapacitors. Naturally, simulation tools are required to assist in the design of efficient and industrial-scale electrochemical devices.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2011

Gasification Studies Task 4 Topical Report, Utah Clean Coal Program

A key objective of the Task 4 activities has been to develop simulation tools to support development, troubleshooting and optimization of pressurized entrained-flow coal gasifiers. The overall gasifier models (Subtask 4.1) combine submodels for fluid flow (Subtask 4.2) and heat transfer (Subtask 4.3) with fundamental understanding of the chemical (Subtask 4.4) and physical (Subtask 4.5) processes that take place as coal particles are converted to synthesis gas and slag. However, it is important to be able to compare predictions from the models against data obtained from actual operating coal gasifiers, and Subtask 4.6 aims to provide an accessible, non-proprietary system, which can be operated over a wide range of conditions to provide well-characterized data for model validation.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2011

Southern Regional Center for Lightweight Innovative Design

The three major objectives of this Phase III project are: To develop experimentally validated cradle-to-grave modeling and simulation tools to optimize automotive and truck components for lightweighting materials (aluminum, steel, and Mg alloys and polymer-based composites) with consideration of uncertainty to decrease weight and cost, yet increase the performance and safety in impact scenarios; To develop multiscale computational models that quantify microstructure-property relations by evaluating various length scales, from the atomic through component levels, for each step of the manufacturing process for vehicles; and To develop an integrated K-12 educational program to educate students on lightweighting designs and impact scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Underground Coal Thermal Treatment

The long-term objective of this work is to develop a transformational energy production technology by insitu thermal treatment of a coal seam for the production of substitute natural gas (SNG) while leaving much of the coal's carbon in the ground. This process converts coal to a high-efficiency, low-GHG emitting gas fuel. It holds the potential of providing environmentally acceptable access to previously unusable coal resources. This topical report discusses the development of experimental capabilities, the collection of available data, and the development of simulation tools to obtain process thermo-chemical and geo-thermal parameters in preparation for the eventual demonstration in a coal seam. It also includes experimental and modeling studies of CO 2 sequestration.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2012

FY2012 Report on Fast Reactor Toolset Work (PROTEUS-Fast)

As part of the NEAMS activity in DOE, a fast reactor simulation program was launched in April 2007, termed SHARP. The initial goal of SHARP was to develop a suite of modern simulation tools specifically for the analysis and design of sodium cooled fast reactors, and this goal has since been extended to consider all reactor types of interest. As part of that work, a high‐fidelity deterministic neutron transport code named UNIC was started, providing a common framework for fast reactor neutronics tools. Focusing on UNIC, spatial de‐homogenization increased the typical neutronics problem with a few hundred million degrees of freedom (DOF) into ones with hundreds of trillions of DOF. Such problems are beyond the capabilities of existing supercomputers. With the advent of future computer hardware, these high‐fidelity problems can be solved but only after a multiyear development program to adapt codes such as UNIC to that technology. UNIC can presently be used on smaller problems (single assembly, multiple assemblies) with today’s hardware, but it is also necessary to provide tools to solve the larger problems of interest, albeit without the aforementioned level of spatial de‐homogenization. To address the desire to demonstrate the coupling capability of NEAMS, part of the FY12 funding was focused on preparing the legacy codes, termed PROTEUS‐Fast, which are fully capable of solving full‐scale fast reactor problems. A bulk of the work this year was focused on preparing and distributing the PROTEUS‐Fast codes for use by all NEAMS users. The demonstration of a full coupling capability will require more follow on work, but significant progress was made this year preparing the interface coupling routines and preparing PROTEUS‐Fast for use. The primary targets of interest in PROTEUS‐Fast are DIF3D, DIF3D‐K (kinetics), and VARI3D (reactivity coefficients), with REBUS (fuel cycle) being an auxiliary component updated for convenience. All codes in PROTEUS‐Fast were verified and added to the BuildBot regression test. Unfortunately, all of the older codes suffered significant problems from the deprecated coding practices used within them and resulting conflicts with modern compilers. After some work, all of these issues were resolved and we feel confident in releasing them for use by others NEAMS members. With regard to specific upgrades, DIF3D‐VARIANT was upgraded with a few months of effort to allow the large scale problems of interest to be executed. After significant study, we choose not to modify VARI3D to include a transport option, but to develop a new code, PERSENT (partially funded by an external project) which uses the DIF3D‐VARIANT transport solution option. The outstanding features missing from MC 2 ‐3 were added, and MC 2 ‐3 has been released to RSICC. All of the remaining PROTEUS‐Fast codes are either finished with the copyright and licensing procedure or are actively going through it. While that process will delay the targeted August 2012 release to RSICC for a few more months, the codes are ready for immediate use and can be connected to the framework either by us or by others as the interface readers and documentation will be released with the PROTEUS‐Fast codes.

Wolters, E. R.↗
DOE OSTI2012

FY2012 Status Report on Subgroup Library Development

The goal of SHARP is to develop a suite of modern simulation tools for use on all reactor types of interest. Part of that desire is to build a heterogeneous neutron transport capability which gives accurate, detailed power distributions throughout the entire reactor core, of which we have focused our efforts on deterministic methodologies. The existing SHARP neutronics tool has demonstrated good accuracy when using conventional homogeneous modeling, but when applied on fully heterogeneous problems such as the Advanced Test Reactor (ATR) and Zero Power Reactors (ZPR), the results were not acceptable. These errors are primary attributable to the use of a three step cross section generation procedure (unit cell, lattice, and whole core). Given the success of the DeCART tool on thermal spectrum systems such as PWR, BWR, and VHTR, the subgroup methodology was identified as a potential means by which to resolve the cross section related problems in the NEAMS tools. The subgroup project in NEAMS is thus focused on creating a general purpose cross section methodology that is usable on both thermal and fast spectrum systems. The subgroup methodology is a well studied scheme appearing very early in the nuclear engineering literature. We investigated using the subgroup methodology as a potential means to handle fast reactor problems. A considerable amount of work was performed on the subgroup library software for NEAMS where several subgroup formulations were investigated. Further, while the subgroup method has been demonstrated to be accurate enough on several problems via our own experiences with DeCART, it is not clear what its accuracy will be on more complicated problems such as the ATR. In any case, one must have a capability to generate a library in which subgroup parameters can cover neutron spectrum characteristics of the reactor of interest. For better accuracy, we propose to use MCNP as an alternative pin-cell calculation means of generating the subgroup data and have developed a prototype code package to demonstrate the capability. With regard to fast spectrum systems, there are numerous concerns with the subgroup methodology in which the conventional Bondarenko iteration approach often used would not accurately handle the resonance interference effect that becomes more complex and important in a fast reactor. An alternative methodology involving the local escape cross section looks promising, but substantial research needs to be completed and a basic algorithm tested before success can be confirmed. Overall, the creation of a subgroup library application was not finished, primarily due to the fact that a bulk of the funding was moved into the next fiscal year. A better understanding of the underlying methodology was gained and a means by which to generate subgroup data was created. The work on the subgroup method for an

Smith, M. A.↗