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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

TRINIDI (Time-of-Flight Resonance Imaging with Neutrons for Isotopic Density Inference)

This software is an open-source Python library that provides tools for processing hyperspectral neutron time-of-flight radiography data. This type of data allows material decomposed reconstructions to be generated with the use of material characteristic spectral responses and the algorithms provided in this code library. The software library will contain tools for pre-processing the neutron measurement data, estimating measurement system parameters, reconstructing material decomposed radiographs, and computing material decomposed computed tomography (CT). Furthermore, it will have capability to generate and process simulated neutron time-of-flight data with the goal of benchmarking and demonstrating the tools that are provided. The software will include thorough documentation and application examples.

Balke, Thilo↗
DOE OSTI2022

pnnl/blueprint-styler

Make custom blueprint.css styles A framework for creating custom visual themes and styles for the Blueprintjs React component library: https://blueprintjs.com/docs/ Features create custom css themes and styles for Blueprintjs components visualize the effect of the custom styles during development publish an example application that includes all available themes: https://stash.pnnl.gov/pages/UXRSRC/blueprint-styler/master/browse/build/index.html publish the compiled theme to npm (or artifactory)

Bradford, James↗
DOE OSTI2025

Open-Source Ambient-Signal-Based Inertia Monitoring Tool for Power systems [SWR-25-59]

This script, developed by NREL, implements an inertia estimation algorithm using a sliding window approach. The inertia (H) is estimated based on frequency deviations and active power deviations, utilizing the swing equation from power system dynamics. An example application is provided using the WECC 240-bus system.

Peng, Jiangkai [National Renewable Energy Laborato↗
DOE OSTI2018

Computing with Spikes: The Advantage of Fine-Grained Timing

Neural-inspired spike-based computing machines often claim to achieve considerable advantages in terms of energy and time efficiency by using spikes for computation and communication. However, fundamental questions about spike-based computation remain unanswered. For instance, how much advantage do spike-based approaches have over conventional methods, and under what circumstances does spike-based computing provide a comparative advantage? Simply implementing existing algorithms using spikes as the medium of computation and communication is not guaranteed to yield an advantage. Here, we demonstrate that spike-based communication and computation within algorithms can increase throughput, and they can decrease energy cost in some cases. We present several spiking algorithms, including sorting a set of numbers in ascending/descending order, as well as finding the maximum or minimum or median of a set of numbers. We also provide an example application: a spiking median-filtering approach for image processing providing a low-energy, parallel implementation. Furthermore, the algorithms and analyses presented here demonstrate that spiking algorithms can provide performance advantages and offer efficient computation of fundamental operations useful in more complex algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

On the convergence of Neumann series for electrostatic fracture response

Here, the feasibility of Neumann series expansion of Maxwell’s equations in the electrostatic limit is investigated for potentially rapid and approximate subsurface imaging of geologic features proximal to metallic infrastructure in an oilfield environment. While generally useful for efficient modeling of mild conductivity perturbations in uncluttered settings, we raise the question of its suitability for situations, such as oilfield, where metallic artifacts are pervasive, and in some cases, in direct electrical contact with the conductivity perturbation on which the Neumann series is computed. Convergence of the Neumann series and its residual error are computed using the hierarchical finite element framework for a canonical oilfield model consisting of an “L” shaped, steel-cased well, energized by a steady state electrode, and penetrating a small set of mildly conducting fractures near the heel of the well. For a given node spacing h in the finite element mesh, we find that the Neumann series is ultimately convergent if the conductivity is small enough - a result consistent with previous presumptions on the necessity of small conductivity perturbations. However, we also demonstrate that the spectral radius of the Neumann series operator grows as ~ 1/ h , thus suggesting that in the limit of the continuous problem h → 0, the Neumann series is intrinsically divergent for all conductivity perturbation, regardless of their smallness. The hierarchical finite element methodology itself is critically analyzed and shown to possess the h 2 error convergence of traditional linear finite elements, thereby supporting the conclusion of an inescapably divergent Neumann series for this benchmark example. Application of the Neumann series to oilfield problems with metallic clutter should therefore be done with careful consideration to the coupling between infrastructure and geology. Here, the methods used here are demonstrably useful in such circumstances.

58 GEOSCIENCES↗
DOE OSTI2014

RAVEN and Dynamic Probabilistic Risk Assessment: Software overview

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7 [], currently under development at the Idaho National Laboratory. Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism has been employed by providing Application Programming Interfaces (APIs). These interfaces are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable to investigate the system response, investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The paper presents an overview of the software capabilities and their implementation schemes followed by some application examples.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Pycheron: A Python-Based Seismic Waveform Data Quality Control Software Package

Supplementing an existing high-quality seismic monitoring network with openly available station data could improve coverage and decrease magnitudes of completeness; however, this can present challenges when varying levels of data quality exist. Without discerning the quality of openly available data, using it poses significant data management, analysis, and interpretation issues. Incorporating additional stations without properly identifying and mitigating data quality problems can degrade overall monitoring capability. If openly available stations are to be used routinely, a robust, automated data quality assessment for a wide range of quality control (QC) issues is essential. To meet this need, we developed Pycheron, a Python-based library for QC of seismic waveform data. Pycheron was initially based on the Incorporated Research Institutions for Seismology’s Modular Utility for STAtistical kNowledge Gathering but has been expanded to include more functionality. Pycheron can be implemented at the beginning of a data processing pipeline or can process stand-alone data sets. Its objectives are to (1) identify specific QC issues; (2) automatically assess data quality and instrumentation health; (3) serve as a basic service that all data processing builds on by alerting downstream processing algorithms to any quality degradation; and (4) improve our ability to process orders of magnitudes more data through performance optimizations. This article provides an overview of Pycheron, its features, basic workflow, and an example application using a synthetic QC data set.

58 GEOSCIENCES↗
DOE OSTI2018

Modeling City Building Stock for Large-Scale Energy Efficiency Improvements using CityBES

Buildings in San Francisco consumed 52% of total primary energy. Improving building energy efficiency is one of the key strategies cities are adopting towards their energy and climate goals. Urban building energy models (UBEM) can support city managers to evaluate and prioritize energy conservation measures for investment and to design effective incentive and rebate programs. This paper introduces methods to develop a standardized dataset of city building stock, and it demonstrates the use of a UBEM tool, City Building Energy Saver (CityBES), for an urban-scale energy retrofit analysis of building stock in the city of San Francisco. CityBES is an open web-based data and computing platform providing city-scale building energy modeling and performance visualization and benchmarking. CityBES utilizes an international standard CityGML to represent the three-dimensional building stock in cities. As an application example, 940 office and retail buildings in six districts of northeast San Francisco were modeled and analyzed with CityBES to evaluate energy savings for five selected measures. The analysis found that replacing existing lighting with LED and adding an air economizer to HVAC systems are cost-effective measures with combined savings per building between 17% to 31%. The CityBES retrofit analysis feature does not require users to have deep knowledge of building systems or building energy models, which helps overcome barriers for city managers and their consultants to adopt UBEM.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

A biofilm microreactor system for simultaneous electrochemical and nuclear magnetic resonance techniques

In order to fully understand electrochemically active biofilms and the limitations to their scale-up in industrial biofilm reactors, a complete picture of the microenvironments inside the biofilm is needed. Nuclear magnetic resonance (NMR) techniques are ideally suited for the study of biofilms and for probing their microenvironments because these techniques allow for non-invasive interrogation and in situ monitoring with high resolution. By combining NMR with simultaneous electrochemical techniques, it is possible to sustain and study live electrochemically active biofilms. Here, we introduce a novel biofilm microreactor system that allows for simultaneous electrochemical and NMR techniques (EC-NMR) at the microscale. Microreactors were designed with custom radiofrequency resonator coils, which allowed for NMR measurements of biofilms growing on polarized gold electrodes. For an example application of this system, we grew Geobacter sulfurreducens biofilms. NMR was used to investigate growth media flow velocities, which were compared to simulated laminar flow, and electron donor concentrations inside the biofilms. We use Monte Carlo error analysis to estimate standard deviations of the electron donor concentration measurements within the biofilm. The EC-NMR biofilm microreactor system can ultimately be used to correlate extracellular electron transfer rates with metabolic reactions and explore extracellular electron transfer mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

GOMA 6.0 - A Full-Newton Finite Element Program for Free and Moving Boundary Problems with Coupled Fluid/ Solid Momentum, Energy, Mass, and Chemical Species Transport: User’s Guide

Goma 6.0 is a finite element program which excels in analyses of multiphysical processes, particularly those involving the major branches of mechanics (viz. fluid/solid mechanics, energy transport and chemical species transport). Goma is based on a full-Newton-coupled algorithm which allows for simultaneous solution of the governing principles, making the code ideally suited for problems involving closely coupled bulk mechanics and interfacial phenomena. Example applications include, but are not limited to, coating and polymer processing flows, super-alloy processing, welding/soldering, electrochemical processes, and solid-network or solution film drying. This document serves as a user's guide and reference.

Schunk, Peter Randall↗
DOE OSTI2013

Updated Subsurface Data Base For Bear Creek Valley, Chestnut Ridge, And Parts Of Bethel Valley On The U.S. Department of Energy Oak Ridge Reservation

This document represents a compilation of location, construction, and hydrologic information relating to boreholes, groundwater monitoring wells, and surface water locations that have been installed/established at the Y-12 National Security Complex (Y-12) through August 2013. To date, a total of 1422 boreholes and wells have been installed in and around the Y-12 area. Of those, 835 existing boreholes and wells continue to be utilized for groundwater monitoring programs, research, remedial investigations, plume characterization and delineation studies, and various other hydrogeologic endeavors. In addition, 215 surface water locations, such as rivers, streams, seeps, springs, lakes, ponds, and building sumps are included in this database. General data about boreholes and wells included in the database are survey coordinates, survey system, elevations, alternative names and well status. Surface water location information (Appendix I) includes name, alias, functional area, northing and easting coordinates, survey system, map number and sampling history. Tabulated construction data include total depth, completion method, borehole diameter, casing and screen materials, casing and screen diameters, casing and screen depths, filter pack depths, open-hole intervals, and open-hole diameters. Hydrogeological data summarized in this document include the aquifer monitored by the completion interval, depth to weathered and fresh bedrock, formations penetrated, well sampling history, and whether rock core and geophysical logs were obtained. This document (which is the sixth revision to Y/TS–881 and the ninth overall update of a previous compilation) is published on a regular basis by the Y-12 Groundwater Protection Program (GWPP), which serves as custodian of drilling records and well construction data for the network of wells and other groundwater monitoring stations at Y-12. The tabulations in this database are arranged in appendices of like information. An example application of the data compiled in this document would be the evaluation of the suitability of wells for continued use in groundwater investigations and monitoring studies. Other uses may include: the siting of hydrogeological characterization activities, background evaluations of sites prior to initiation of new drilling activities, and hydrogeological review of selected sites prior to the initiation of remedial actions or new construction activity. Existing boreholes, wells, and surface water locations are presented on a series of maps (Appendix K). Boreholes and wells that have been plugged and abandoned, destroyed, could not be located, or otherwise are of unknown status/condition appear on a second series of maps of identical coverage (Appendix L).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

3D Simulation of External Flooding Events for the RISMC Pathway

Incorporating 3D simulations as part of the Risk-Informed Safety Margins Characterization (RISMIC) Toolkit allows analysts to obtain a more complete picture of complex system behavior for events including external plant hazards. External events such as flooding have become more important recently – however these can be analyzed with existing and validated simulated physics toolkits. In this report, we describe these approaches specific to flooding-based analysis using an approach called Smoothed Particle Hydrodynamics. The theory, validation, and example applications of the 3D flooding simulation are described. Integrating these 3D simulation methods into computational risk analysis provides a spatial/visual aspect to the design, improves the realism of results, and can prove visual understanding to validate the analysis of flooding.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Demonstration of finite element simulations in MOOSE using crystallographic models of irradiation hardening and plastic deformation

This report describes the implementation of a crystal plasticity framework (VPSC) for irradiation hardening and plastic deformation in the finite element code, MOOSE. Constitutive models for irradiation hardening and the crystal plasticity framework are described in a previous report [1]. Here we describe these models briefly and then describe an algorithm for interfacing VPSC with finite elements. Example applications of tensile deformation of a dog bone specimen and a 3D pre-irradiated bar specimen performed using MOOSE are demonstrated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Light Water Reactor Sustainability Program Status of Adaptive Surrogates within the RAVEN framework

The RAVEN code has been under development at the Idaho National Laboratory since 2012. Its main goal is to create a multi-purpose platform for the deploying of all the capabilities needed for Probabilistic Risk Assessment, uncertainty quantification, data mining analysis and optimization studies. RAVEN has demonstrated a good level of maturity in terms of state-of-art and advanced analysis methodologies. Indeed, in the past year the RAVEN code has been released as open-source project and is available to download (raven.inl.gov) free of charge. The main subject of this report is to show the activities that have been recently accomplished with respect the adaptive surrogate modeling: Implementation of the metric system for the assessment of surrogate model validity; Implementation of cross-validation techniques for the global assessment of surrogate models; Implementation of an automatic infrastructure for switching between a high-fidelity model (e.g. physical code) and a surrogate or set of surrogates; Implementation of a scheme for automatic optimization of surrogate model parameters. The aim of this document is to report the status of the development of methods, within the RAVEN framework, to assess the validity of the predictive capabilities of surrogate models. Indeed, after the construction of a surrogate tight to a certain physical model, it is crucial to assess the goodness of its representation, in order to be confident with its prediction. A cross-validation technique has been employed. This report will highlight the implementation details and proof its correct implementation by an application example. The implementation of a way to assess the predictive capabilities of a surrogate allowed the construction of a RAVEN new entity named “HybridModel” that is aimed to switch between an high-fidelity code and its linked surrogate. In addition, leveraging the optimization algorithms that have been implemented in RAVEN last fiscal year, a new scheme has been developed for automatic tuning of the surrogates’ parameters (e.g. penalty factors in support vector machines).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

A Comparison Framework for Reactor Anti-Neutrino Detectors in Near-Field Nuclear Safeguards Applications

Electron anti-neutrino ( e) detectors can support nuclear safeguards, from reactor monitoring to spent fuel characterization. In recent years, the scientific community has developed multiple detector concepts, many of which have been prototyped or deployed for specific measurements by their respective collaborations. However, the diversity of technical approaches, deployment conditions, and analysis techniques complicates direct performance comparison between designs. We have begun development of a simulation framework to compare and evaluate existing and proposed detector designs for nonproliferation applications in a uniform manner. This report demonstrates the intent and capabilities of the framework by evaluating four detector design concepts, calculating generic reactor antineutrino counting sensitivity, and capabilities in a plutonium disposition application example.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Fluid-Structure Interaction of Deforming Porous Media

Sandia National Laboratories (SNL) and the Procter and Gamble Company (P&G) collaborated to develop a computational tool that predicts the in-use performance of consumer good products based on specific loading, geometries, materials, and boundary conditions. This computational tool is particularly useful in exploring the consumer-product interface and product performance. The benefit to P&G was many-fold, as the numerous project-tasks that were funded under this agreement led to advanced analysis software that allowed P&G to improve the performance and manufacturing of many of their products across several business units. The benefit to SNL was many-fold as well, including improved reduced-order models for thin-region dynamics (used for customers through DSA, NW, and EC PMUs), improved computational mechanics capability for capillary hydrodynamics, porous flow, structural mechanics, and more. Example applications of these improved capabilities at SNL include, but are not limited to, encapsulation, welding, soldering, and brazing models for NW, interface sliding models for DoD SPP programs, and porous-elastic subsidence modeling for energy and climate applications. Moreover, many current code developers on the ASC program’s SIERRA applications gained valuable skills working on this CRADA.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Material and Energy Efficiency: A Framework for Broader Analysis of Energy Use in the U.S. Economy

Energy efficiency analysis has focused predominantly on reducing energy at its point of use by individual components, processes, or products. Efforts to address the energy embodied in materials through strategies and technologies that reduce raw material production - while maintaining the function and use of materials - offer a complementary and expansive approach to traditional energy efficiency analysis. The U.S. Department of Energy (DOE) energy analysis community currently lacks analytical tools that are appropriate for 1) estimating on a product and economy-wide basis energy efficiency potential achieved through material efficiency strategies and 2) evaluating how these new strategies may complement existing energy efficiency efforts. The goal of this report is to describe a standardized analysis framework that would enable calculation of embodied and direct energy and the estimation of energy reduction potential achieved through changes in material use. The proposed framework meets this functionality by spanning the entire U.S. economy, including international trade flows; capturing material and energy use in products and services from raw material extraction to retirement; maintaining material and energy balances; and adjusting dynamically to absolute and relative changes in materials and energy use. The framework is composed of two main elements: a dynamic hybrid input-output (IO) model and a material energy identity. The hybrid IO model defines recipes for material and energy flows in physical (e.g., British thermal units [Btus] and tons) and monetary units, and allows for dynamic adjustments to the amount of materials and energy used. The second element of the analytical framework, the material energy identity, acts as a way of identifying and organizing energy and material efficiency strategies, which are then implemented and analyzed in the hybrid IO model. The report also provides a simple example application of the proposed framework, which illustrates the concept of reducing energy use through changes to material efficiency.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Life-Cycle Cost and Optimization of PV Systems Based on Power Duration Curve with Variable Performance Ratio and Availability

A new derivation of Power Duration Curve is presented and applied to analysis of photovoltaic system life cycle cost. The effect of non-unity Performance Ratio and non-unity Availability on the power duration curve are illustrated. The effect of these two key performance indicators on calculation of life cycle cost and PV system design optimization (optimal DC/AC ratio) are illustrated as example applications of the method.

14 SOLAR ENERGY↗