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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A Simple Hybrid Electric Vehicle Fuel Consumption Model for Transportation Applications(DOI: 10.5772/intechopen.89055)

This study presents a simple power-based microscopic hybrid electric vehicle (HEV) fuel consumption model for use in microscopic traffic software and various connected and automated vehicle (CAV) applications, including eco-routing and eco-drive systems. While numerous HEV energy consumption models have been developed, these models are complex and require vehicle engine data deeming them difficult to implement and making them nontransferable. The proposed model was developed using empirical data for a 2010 Toyota Prius—the most popular HEV. The model was then extended to other HEVs thus extending the domain of application of the model. The proposed fuel consumption model estimates the instantaneous fuel consumption rates of an HEV using instantaneous vehicle operational input variables, including the vehicle’s speed, acceleration, and roadway grade, which can be acquired from global positioning system (GPS) equipment or other sensors. The model estimates vehicle fuel consumption rates consistent with empirical data producing an average error of 2.1% for the Toyota Prius and up to 4% for other HEVs demonstrating the applicability and transferability of the model to various HEVs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

DeCOIL: Optimization of Degenerate Codon Libraries for Machine Learning-Assisted Protein Engineering

With advances in machine learning (ML)-assisted protein engineering, models based on data, biophysics, and natural evolution are being used to propose informed libraries of protein variants to explore. Synthesizing these libraries for experimental screens is a major bottleneck, as the cost of obtaining large numbers of exact gene sequences is often prohibitive. Degenerate codon (DC) libraries are a cost-effective alternative for generating combinatorial mutagenesis libraries where mutations are targeted to a handful of amino acid sites. However, existing computational methods to optimize DC libraries to include desired protein variants are not well suited to design libraries for ML-assisted protein engineering. To address these drawbacks, we present DEgenerate Codon Optimization for Informed Libraries (DeCOIL), a generalized method which directly optimizes DC libraries to be useful for protein engineering: to sample protein variants that are likely to have both high fitness and high diversity in the sequence search space. Using computational simulations and wet-lab experiments, we demonstrate that DeCOIL is effective across two specific case studies, with potential to be applied to many other use cases. DeCOIL offers several advantages over existing methods, as it is direct, easy-to-use, generalizable, and scalable. With accompanying software, DeCOIL can be readily implemented to generate desired informed libraries.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Performance Assessment of a New Gamma Spectroscopy Toolkit: Peak Doctor and the Spectral Nondestructive Assay Platform (SNAP) - 17397

High resolution gamma spectroscopy (HRGS) is a widely used technique for non-destructive characterization of nuclear materials, and assay of radioactive waste. The ability to accurately evaluate raw spectral data is an important step in producing high-quality results. A spectral analysis application known as Peak Doctor has been developed under a Cooperative Research and Development Agreement (CRADA) between LANL and Pajarito Scientific Corporation (PSC). The software has undergone several years of testing and validation by the Radioactive Waste Characterization Team of the LANL Waste Management Services Group (WM-SVS). PeakDoctor is designed to work with the Spectral Nondestructive Assay Platform (SNAP{sup TM}) to provide a complete HRGS analysis engine. SNAP{sup TM} performs model specific corrections for attenuation and geometry. These applications are the major components of a new toolkit designed primarily for portable far-field non-destructive assay. Peak Doctor performs a very accurate peak fit analysis with the goal of improving upon the capabilities of existing commercially available routines. It is designed to be user-configurable and can be customized to any given type of detector and any given type of spectrum. Peak Doctor was developed to resolve many of the inherent complexities in gamma ray spectra including overlapping peaks, complex multiplet regions, large step peaks, backscatter regions and Compton edges. Unlike most spectral analysis platforms, Peak Doctor does not rely on the energy calibration and detector resolution parameters that are saved by the operator in the spectrum file. Instead, key parameters are pre-defined for individual detectors. The software fits a continuum using a series of splines between a series of junctions or 'knots'. Fitting techniques are used to join the splines together to create a near-continuous multi-element curve. Optimizing the location of the knots is one of Peak Doctor's most powerful features. The knots are initially configured using a pre-defined list and are removed or added automatically during the fitting process. Knots are also created when new features are identified such as Step Peaks and Compton Edges. The user can also manually specify knots in order to improve the continuum fit. The initial fit is improved on by removing any outlier regions (which are converted to peaks) and the continuum fitting process is repeated. At this stage, an experienced user can work interactively with the fit by manually converting peak regions to continuum or vice versa. The final step is to fit a series of peaks above the continuum based on detector parameters. Single and multiplet peaks are then processed by either the tailing (piecewise) or non-tailing (Gaussian) Levenberg Marquardt non-linear peak fitting routine depending on the user defined selection. Only a rough knowledge of the detector characteristics (energy calibration and resolution) is required for the fitting process to proceed with good accuracy. Any peaks that are missed can be manually added by the user and will also be fitted. Discontinuities in the peak / continuum fit can be rapidly identified by reviewing the 'residuals scale' plot. For waste streams that are well characterized, it is often the case that routinely encountered spectra will have similar peaks and continuum features. For these cases a handy 'One Step' method is available that proceeds in an automated fashion without user interaction. Peak Doctor has been configured with a set of default spectrum types including plutonium / transuranic waste (including Weapons Grade Pu, Heat Source Pu, Am-241, Am-243 and Np-237), depleted or enriched uranium, nuclear power plant / intermediate level waste (with fission and activation products such as Cs-137 and Co-60) as well as Naturally Occurring Radioactive Materials (NORM). The user can easily add new spectrum types for specific waste streams or other types of radiological / special nuclear materials. The output from PeakDoctor (including net peak area, centroid energy and a list of minimum detectable activity levels at pre-defined regions) is used by SNAP{sup TM} to complete the data analysis process. Isotope activities are calculated using configurable template-driven geometry and attenuation correction methods. The software accounts for matrix and container wall effects, collimator / angular corrections, detector efficiency (based on calibration curves) and stand-off distance. SNAP{sup TM} uses published algorithms incorporating a series of decision points during its operation to allow the analyst to provide logical input to guide the software during the analysis of each unique spectrum. The Peak Doctor / SNAP{sup TM} toolkit has been extensively tested and validated under a variety of conditions using 'benchmark' reference spectra. Test scenarios reported include HPGe-based measurements of well characterized uranium and plutonium standards and radioactive sources with a variety of different geometries and matrix materials including surrogate drums and boxes. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Hybrid metal additive/subtractive machine tools and applications

Additive manufacturing creates parts by depositing a preform, typically layer by layer. Subtractive manufacturing involves removing material from a preform to create parts. Hybrid machine tools combine both additive and subtractive processes in the same workspace. They can be used to create parts that meet functional tolerance and surface finish requirements, or to create features that are difficult to produce using additive or subtractive processes alone. Here, this paper describes hybrid metal additive/subtractive machine tools. It covers design considerations, sensors and controls, process management, programming and software, and the impact on the design space. It also identifies future research challenges.

42 ENGINEERING↗
DOE OSTI2015

3D Imaging with Structured Illumination for Advanced Security Applications

Three-dimensional (3D) information in a physical security system is a highly useful discriminator. The two-dimensional data from an imaging systems fails to provide target distance and three-dimensional motion vector, which can be used to reduce nuisance alarm rates and increase system effectiveness. However, 3D imaging devices designed primarily for use in physical security systems are uncommon. This report discusses an architecture favorable to physical security systems; an inexpensive snapshot 3D imaging system utilizing a simple illumination system. The method of acquiring 3D data, tests to understand illumination design, and software modifications possible to maximize information gathering capability are discussed.

42 ENGINEERING↗
DOE OSTI2013

The MCDB System for Management and Analysis of Petabyte-Scale Uncertain Data

Analysts working with very large data sets often use statistical models to “guess” at unknown, inaccurate, or missing information associated with the data. For example, a distant object viewed through an optical lens will have its position slightly shifted by imperfections in the lens. Thus, rather than considering the object’s observed position to be absolutely correct, it makes sense to take into account the lens’s imperfections to obtain a probabilistic guess as to the object’s true position. For another example, it might be important to associate some sort of error distribution with each of the individual sensors in an array of magnetometers. This error distribution may be complex and include spatially-driven covariances, because errors in nearby sensors are likely to be correlated (caused, for example, by the presence of some nearby, fixed metal object). This project is concerned with the design and implementation of a prototype data management system called the Monte Carlo Database System, or MCDB for short. MCDB allows an expert-level analyst or statistician to attach arbitrary stochastic models to very large data sets in order to “guess” the values for unknown or inaccurate data, such as the actual position of the observed object in the lens example above. When the resulting data set is analyzed, the underlying stochastic models are used to generate hundreds or thousands of possible data set instances, and each of those possible instances is analyzed separately by MCDB. Thus, MCDB does not just give a single answer to the analysis, but it actually gives an empirical distribution of query results that embody the underlying uncertainty, and can in turn be analyzed using standard statistical techniques. The stochastic models in MCDB are implemented as user-defined, external C++ libraries called Variable Generation functions (VG functions for short). Because the VG function interface is exceedingly general, it allows MCDB to be used in a very wide variety of application domains, in conjunction with virtually any stochastic model. Ultimately, we ended up calling the system that we developed over the course of the project SimSQL, to denote the fact that it allowed for stochastic simulation of data. The software developed during the lifetime of the project is available for download from the SimSQL project website: http://cmj4.web.rice.edu/SimSQL/SimSQL.html.

42 ENGINEERING↗
DOE OSTI2026

UltraSep Acoustic Separation Platform

UltraSep is an intelligent ultrasonic separation platform that transforms solid–liquid separation through real-time eigenfrequency resonance locking and ultra-low power energy optimization. By dynamically matching ultrasonic output to system resonance while maximizing particulate removal per unit of applied energy, UltraSep replaces centrifugation and fouling-prone filtration with precision-controlled acoustic forces that significantly reduce power consumption, mechanical complexity, and operating cost while improving recovery performance. This integrated platform unites patented resonance-based acoustic control and energy-per-removal optimization with chemistry-enhanced separation and proprietary system software into a scalable, high-impact commercial technology.

42 ENGINEERING↗
DOE OSTI2019

Information Science in Occupational Safety Management

Approaches to information technology in occupational safety management at industrial enterprises are considered. Obstacles to such uses of information technology are noted. Available software and approaches to workplace automation for occupational safety specialists are reviewed. Analysis of the advantages and disadvantages of the available software permits selection of the optimal product for specific problems in occupational safety.

42 ENGINEERING↗
DOE OSTI2022

ExaWind: Opportunity for Discovery

The predictive simulation of the dynamics of modern wind turbines and wind farms is a high-performance-computing (HPC) grand challenge. Modern wind turbines are the largest rotating machines in the world, with rotor diameters exceeding 200 meters, and with heights well into the atmospheric boundary layer. To address this grand challenge, the U.S. Department of Energy (DOE) Wind Energy Technologies Office and the Exascale Computing Project have been supporting the creation of the ExaWind modeling and simulation environment since 2016. ExaWind is composed of the incompressible-flow computational-fluid-dynamics (CFD) solvers AMR-Wind and Nalu-Wind and the wind-turbine-dynamics solver OpenFAST. In our hybrid CFD approach, Nalu-Wind unstructured-grid models resolve the near-body flow around the turbine; those models are embedded in, and two-way coupled to, an AMR-Wind structured-grid mesh through overset meshes. In this talk I give an overview of ExaWind software stack and describe how it is being used to address important problems in wind energy.

computational fluid dynamics↗
DOE OSTI2015

Simulation of Internal Combustion Engines with High-Performance Computing Tools

Traditional Lagrangian spray modeling approaches for internal combustion engines are highly griddependent due to insufficient resolution in the near nozzle region. This is primarily because of inherent restrictions of volume fraction with the Lagrangian assumption together with high computational costs associated with small grid sizes. A state-of-the-art grid-convergent spray modeling approach was developed and implemented by Senecal et al. (ASME-ICEF2012-92043) in the CONVERGE software. The key features of the methodology include Adaptive Mesh Refinement (AMR), advanced liquid-gas momentum coupling, and improved distribution of the liquid phase, which enables use of cell sizes smaller than the nozzle diameter. This modeling approach was rigorously validated against nonevaporating, evaporating, and reacting data from the literature. The current numerical study focusses on further demonstration of the grid-convergent modeling approach for simulating a single-cylinder Cat® compression ignition engine. The simulated injector is characterized with a nominal nozzle exit diameter of 259 μm. Simulations using various minimum grid sizes (ranging from 125 μm to 1000 μm) are compared for engine performance and emissions parameters of interest such as pressure, heat release rate, ignition delay, NOx, HC, and soot emissions. The peak cell-count for the highest resolution simulation was on the order of 34 million. These computationally expensive simulations were facilitated at a high-performance computing facility at Argonne National Laboratory. METIS load-balancing algorithm was developed and implemented in Converge code for the simulations. Scaling studies were also performed. The validity of previously recommended grid settings (ASME-ICEF2012-92043) for accuracy/runtime trade-off is further assessed. Efficacy of a simplified combustion model is also compared against a detailed chemical kinetics based combustion model.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2013

3D Flow and Temperature Analysis of Filling a Plutonium Mold (Revision 1) [Poster]

The plutonium foundry at Los Alamos National Laboratory casts products for various special nuclear applications. However, plutonium’s radioactivity, material properties, and security constraints complicate the ability to perform experimental analysis of mold behavior. The Manufacturing Engineering and Technologies (MET-2) group previously developed a graphite mold to vacuum cast small plutonium disks to be used by the Department of Homeland Security as point sources for radiation sensor testing. A two-stage pouring basin consisting of a funnel and an angled cavity directs the liquid into a vertical runner. A stack of ten disk castings connect to the runner by horizontal gates. Volumetric flow rates were implemented to limit overflow into the funnel and minimize foundry returns. Models using Flow-3D computational fluid dynamics software are employed here to determine liquid Pu flow paths, optimal pour regimes, temperature changes, and pressure variations.

36 MATERIALS SCIENCE↗
DOE OSTI2018

FUSRAP Case Study - Benefits and Lessons Learned from Implementation of a Modern Data Solution at Maywood - 18399

This paper focuses on data production and management practices dating back to 1999 that continue to evolve to support the project today. In 2000, the FUSRAP Maywood Project began using a software environmental data management system and laboratory information management system, developed by a single database administrator (DA) and authored in Microsoft Access{sup TM} (MS Access). The original databases included basic functionality including sample number assignment and label generation, tracking of LIMS gamma spec QC and assignment of basic qualifiers and basic database queries. The DA continued over the next fifteen years to refine the EDMS/LIMS by integrating project-specific data evaluation guidance document processes and Quality Assurance/Quality Control (QA/QC) charting and excursion warning tools. With the retirement of the original DA, the U.S. Army Corps of Engineers (USACE)-Cabrera Team procured and implemented a commercial-leaning solution using modern database tools and an established EDMS vendor. For the database transition process, the project team established and configured the new EDMS/LIMS with basic architecture and accessibility; evaluated existing workflows; established/revised LIMS and EDMS-related documentation (manuals and procedures); and conducted dry runs and validation testing. The overall team coordinated closely to facilitate a seamless transition from initial assessment and authoring, to data migration, and finally to resumption of normal ongoing operations. Key features of the new EDMS Subcontractor's software included lookup tables, an import wizard, data checking options and unique indexes. Since the database systems became operational, the technical staff gathered useful feedback from end users (e.g., lab staff, field engineers, task managers, and the third-party data validator) to refine the EDMS/LIMS operation. This feedback triggered improvements in the performance of onsite laboratory qualification forms, promoted consistency in sample ID numbers between the database sample planning screens and field chain-of-custodies, corrected bugs in the LIMS Duplicate Evaluation Report, eliminated data import issues such as blank, inconsistent or missing data from key fields. One of the advantages of the commercial database solution was that it allowed the project to cut cost over time due to the lower cost of database maintenance provided by the commercial database vendor versus the cost of an on-staff DA. Cost savings are estimated at $40,000 per year. There were also indirect cost savings resulting from implementation of the new database since it allowed better integration of the LIMS and EDMS. While there will always be challenges associated with long term records/data management for any old remediation site, the Maywood Team's approach to an upgraded EDMS/LIMS implementation serves as one element of the overall effort to enhance the integrity and reproducibility of critical data that supports the remediation program while at the same time, more effectively using available resources. These lessons-learned will enhance implementation of cost-effective solutions for similar environmental remediation sites. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A cost–benefit framework to evaluate capacity upgrade options in overhead line transmission planning

This paper presents the methodology behind the new Reconductoring Economic and Financial Analysis (REFA) tool, an open-access software, used by transmission utilities to evaluate transmission capacity enhancement options. The proposed methodology is intended to be used in a new planning stage, after the capacity expansion and prior to the individual transmission project engineering, allowing capacity upgrade options (reconductoring, rebuild or voltage upgrade), and respective conductor selection, to be compared under the same economic basis. Furthermore, the REFA tool implements a methodology to rank project options and conductor types based on economic criteria, considering an approximation of the ampacity and sag constraints. Results, using 5 real transmission lines in the US, show that least-cost combinations of project and conductor types can be very diverse, which emphasizes the need for the proposed methodology and tool.

Advanced conductors↗
DOE OSTI2020

Quantum Approximate Optimization Algorithm in Python

This is software in Python that simulates the quantum approximate optimization algorithm (QAOA) as described in https://arxiv.org/abs/1411.4028. The software has customization that speeds up simulation and provides interface to the Rapid Optimization Library (ROL) developed at Sandia. SAND2019-8935 M 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.

von Winckel, Gregory↗
DOE OSTI2022

sCO2 heat exchanger control software

SAND2022-6992 O The sCO2 Heat Exchanger Control Software was written for control and operation of high temperature, high pressure supercritical CO2 systems designed for use as heat exchangers. The software was written using the basic LabVIEW package with LabVIEW modules added to it. The software controls valves and actuators, displays data from pressure transducers and thermocouples, and is able to record data at different storage rates. 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.

Garcia Maldonado, Luis↗
DOE OSTI2022

Wiretap

SAND2023-12116O Wiretap is an offensive security software package meant for penetration testers and red teams. Unlike a traditional VPN, Wiretap transparently proxies networking traffic without requiring administrator privileges. 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.

Rindels, Raymond↗
DOE OSTI2022

Hod Carrier

SAND2023-06720O Hod Carrier is a simple proof-of-concept library for moving data from host to NVIDIA BlueField device memory using remote direct memory access. The Hod Carrier software also facilitates research activities related to the potential uses of NVIDIA BlueField data processing unit devices. Using well-established technologies (e.g., RDMA over Infiniband), it will move data from the host to the data processing unit’s memory. This software is a middleware utility for moving data without regard to its semantic meaning. Its operation is fundamentally unaffected by storage allocation. 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.

SciDAC↗
DOE OSTI2025

Ghidra Galore

SAND2025-00232O Ghidra Galore is a software tool that provides a test harness for running an analysis script in multiple versions of Ghidra, an open-source binary disassembler, using Docker. It allows users to understand how different versions of Ghidra evolve over time by analyzing a corpus of input files. The software includes a Python script that wraps the Docker functionality, simplifying the process of running the analysis script across different Ghidra versions. 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.

Crussell, Jonathan [Sandia National Lab. (SNL-CA),↗