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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

solposx: A Python package for determining solar position and atmospheric refraction

solposx is a Python package of reference algorithms for calculating the sun’s position and atmospheric refraction. The package includes 11 solar position algorithms and 6 refraction models from the past 50 years. All functions follow a standardized design pattern, making it easy to compare different algorithms. The provided algorithm implementations have been thoroughly vetted, making the package a valuable research tool and a reliable reference for implementing solar position algorithms in other programming languages or applications.

Jensen, Adam R. [Technical University of Denmark, ↗
DOE OSTI2019

Pit Realization Process Manufacturing Readiness Assessments

This document defines a manufacturing readiness assessment process within a Product Realization Process (PRP) for pit manufacturing at Los Alamos National Laboratory (LANL) having the following objectives. Meet National Nuclear Security Administration (NNSA) Defense Programs Business Process System (DPBPS) PRP requirements. Use language established within LANL’s pit manufacturing program. Enable a disciplined approach to evaluate pit manufacturing readiness. Provide effective tools and metrics to assess manufacturing system maturity.

42 ENGINEERING↗
DOE OSTI2019

FAST FY 2018 Data Call: A Preliminary Review [Slides]

This presentation provides an overview of fiscal year 2018 federal motor vehicle fleet data at the individual vehicle level during the fall of 2018, a preliminary summary of the data collected, and how the collecting project has reviewed that information for potential quality issues. This presentation will be given at the March 2019 INTERFUEL group meeting, hosted by DOE's Federal Energy Management Program (DOE FEMP). The information is collected through the Federal Automotive Statistical Tool (FAST) project. FAST is a Web-based information system managed by the US Department of Energy, the US General Services Administration, and the Energy Information Administration. FAST is used to collect information about the fleet of motor vehicles used and managed by the Federal government. FAST is developed and maintained by DOE's Idaho National Laboratory (INL).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Microstructural Simulation of Ion-Irradiated Natural Rocks and Minerals

This report details the contribution of Oak Ridge National Laboratory to the Nuclear Energy University Program (NEUP) project, "Rapid Characterization of Concrete Mineralogy using Multi-Scale Tools" led by the University of Illinois at Urbana-Champaign. To support the subsequent license renewal (SLR) of the US nuclear power plants (NPPs) fleet, the performance of concrete-forming aggregates against neutron irradiation needs to be assessed. Ion irradiation is proposed as a rapid, cost-effective surrogate method to full neutron irradiation testing. To complement the characterization of ion-irradiated rock specimens, ORNL has run finite-elements and fast-Fourier transform (FFT-based) simulations using the codes MARS and Microstructure-Oriented Scientific Analysis of Irradiated Concrete (MOSAIC). The main conclusion of this analysis is that the apparent post–ion-irradiation step-height underestimates the accumulated free radiation-induced volumetric expansion (RIVE) in the ion-implanted depth by about 15% at full amorphization and about 25% toward the beginning of the ion irradiation experiment. The discrepancy is explained by the fact that the step height is proportional to the sum of the RIVE (i.e., one third of the RIVE) and the irradiation-assisted plastic strains in the vertical direction (lower than two thirds of the RIVE). Because of the large lateral compressive stresses caused by the restraining effect of the unirradiated substrate, the stress field in the mineral grains and at the grain boundary (GB) in the ion-implanted layer is much different than the comparable stress field occurring during neutron irradiation. Hence, the mismatch RIVE causing cracks in the rock-forming minerals leads to different cracking patterns. Ion irradiation continues to be used as a rapid technique to assess the RIVE potential of rocks.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

SMART Deliverable 6.1.2a: Application of the ORION tool to the IBDP Carbon Storage Site

Forecasting and managing potential induced seismic activity is one of the challenges facing commercialscale geologic carbon sequestration (GCS), as well as other geologic energy extraction and byproduct disposal technologies. Historically, the process to develop robust, science-based forecasts of induced seismicity has required an integrated effort from experts in seismology, geomechanics, and reservoir engineering to manage data, develop and evaluate models of subsurface processes, and to calibrate and interpret the results from a range of models to understand site behavior relative to prescribed standards and in the context of uncertainty in geologic characterization data, forecasting models, and operational scenario uncertainty. The Operational Forecasting of Induced Seismicity (ORION) toolkit is an open-source, observation-based forecasting toolkit that is being co-developed by two U.S. DOE-funded initiatives: the National Risk Assessment Partnership (NRAP) and the Scienceinformed Machine Learning for Accelerating Real Time Decisions in Subsurface Applications (SMART) Initiative. ORION is designed to provide functionality to support decision making about seismic hazard analysis and risk management for GCS stakeholders ranging from the public to site operators to expert seismologists. The tool, which is written as open-source code in the Python programming language, is composed of a desktop graphical user interface (GUI) and an underlying forecasting engine. The forecasting engine uses available reservoir properties, well and fluid injection scenario details, and observed seismic catalog data as inputs to produce a set of temporal and spatio-temporal seismic forecasts.

58 GEOSCIENCES↗
DOE OSTI2025

Flexible Integration of Diverse HVAC Technologies in EnergyPlus via Python-Enabled Workflows

Analysis of advanced controls and novel system types is often not directly feasible in building energy simulation tools. Various techniques extend building energy simulation tool capabilities to allow the use of user-defined scripts and programs, but these approaches have limitations. The EnergyPlus Python plugin offers users new flexibility to use EnergyPlus to call an external Python module at specific points in the simulation, as well as to use Python to call EnergyPlus functionality through an application programming interface (API). This paper presents four case studies leveraging the EnergyPlus Python plugin to facilitate analysis of advanced controls and system types. The use of the Python plugin offers greater modularity and flexibility relative to previous approaches, is less error prone, and is simpler for users to adopt. The Python plugin allows EnergyPlus to be used in a more flexible manner and to accommodate the expanding realm of energy modeling applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Improving RNA-Seq Precision with MapAl

With currently available RNA-Seq pipelines, expression estimates for most genes are very noisy. We here introduce MapAl, a tool for RNA-Seq expression profiling that builds on the established programs Bowtie and Cufflinks. In the post-processing of RNA-Seq reads, it incorporates gene models already at the stage of read alignment, increasing the number of reliably measured known transcripts consistently by 50%. Adding genes identified de novo then allows a reliable assessment of double the total number of transcripts compared to other available pipelines. This substantial improvement is of general relevance: Measurement precision determines the power of any analysis to reliably identify significant signals, such as in screens for differential expression, independent of whether the experimental design incorporates replicates or not.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Multi-trait multi-environment genomic prediction strategies for Miscanthus sacchariflorus

Genomic selection holds the potential to serve as a strategic tool to enhance the genetic gain of complex traits in Miscanthus breeding programs. The development of improved cultivars requires their assessment for various traits across diverse environments to ensure suitable overall performance. Hence, the multi-trait multi-environment (MTME) genomic prediction (GP) models offer an opportunity to improve selection accuracy. This study aims to evaluate the potential of five GP models: (1) three MTME models including genotype-by-trait-by-environment interaction (G×E×T) and (2) two single-trait multi-environment (STME) models (with and without G×E interaction). A Miscanthus sacchariflorus population comprising 336 genotypes evaluated in three environments and scored for four traits (biomass yield YDY, total culm number TCM, average internode length AIL, and culm node number CNN) was analyzed. The predictive ability of the models was evaluated considering three cross-validation schemes resembling realistic scenarios (CV1: predicting new genotypes, CVP: predicting missing traits in a given environment, and CV2: predicting partially observed genotypes). On average, in all cross-validation schemes compared to the STME the predictive ability of the MTME models was 10% to 70% higher for TCM and AIL. On the other hand, for YDY and CNN, both STME models performed similarly or slightly better (between 5 to 64%) than the MTME models in most environments. While the MTME models were not successful for all traits when compared to their STME counterparts, MTME models improved the prediction of the performance of genotypes that were untested across environments or lacked trait information in a specific environment. Overall, our study suggests that MTME GP models can be implemented in Miscanthus breeding programs to improve the predictive ability of the complex traits, shorten breeding cycles, and accelerate selection decisions.

genomic prediction (GP)↗
DOE OSTI2023

Early Detection of Drought Stress in Durum Wheat Using Hyperspectral Imaging and Photosystem Sensing

Wheat, being the third largest U.S. crop and the principal food grain, faces significant risks from climate extremes such as drought. This necessitates identifying and developing methods for early water-stress detection to prevent yield loss and improve water-use efficiency. This study investigates the potential of hyperspectral imaging to detect the early stages of drought stress in wheat. The goal is to utilize this technology as a tool for screening and selecting drought-tolerant wheat genotypes in breeding programs. Additionally, this research aims to systematically evaluate the effectiveness of various existing sensors and methods for detecting early stages of water stress. The experiment was conducted in a durum wheat experimental field trial in Maricopa, Arizona, in the spring of 2019 and included well-watered and water-limited treatments of a panel of 224 replicated durum wheat genotypes. Spectral indices derived from hyperspectral imagery were compared against other plant-level indicators of water stress such as Photosystem II (PSII) and relative water content (RWC) data derived from proximal sensors. Our findings showed a 12% drop in photosynthetic activity in the most affected genotypes when compared to the least affected. The Leaf Water Vegetation Index 1 (LWVI1) highlighted differences between drought-resistant and drought-susceptible genotypes. Drought-resistant genotypes retained 43.36% more water in leaves under well-watered conditions compared to water-limited conditions, while drought-susceptible genotypes retained only 15.69% more. The LWVI1 and LWVI2 indices, aligned with the RWC measurements, revealed a strong inverse correlation in the susceptible genotypes, underscoring their heightened sensitivity to water stress in earlier stages. Several genotypes previously classified based on their drought resistance showed spectral indices deviating from expectations. Results from this research can aid farmers in improving crop yields by informing early management practices. Moreover, this research offers wheat breeders insights into the selection of drought-tolerant genotypes, a requirement that is becoming increasingly important as weather patterns continue to change.

Roy, Bishal (ORCID:0000000199125505)↗
DOE OSTI2017

Microlensing Constraints on the Mass of Single Stars from HST Astrometric Measurements

Here, we report on the first results from a large-scale observing campaign aiming to use astrometric microlensing to detect and place limits on the mass of single objects, including stellar remnants. We used the Hubble Space Telescope to monitor stars near the Galactic Center for three years, and we measured the brightness and positions of ~2 million stars at each observing epoch. In addition to this, we monitored the same pointings using the VIMOS imager on the Very Large Telescope. The stars we monitored include several bright microlensing events observed from the ground by the OGLE collaboration. In this paper, we present the analysis of our photometric and astrometric measurements for six of these events, and derive mass constraints for the lens in each of them. Although these constraints are limited by the photometric precision of ground-based data, and our ability to determine the lens distance, we were able to constrain the size of the Einstein ring radius thanks to our precise astrometric measurements—the first routine measurements of this type from a large-scale observing program. In conclusion, this demonstrates the power of astrometric microlensing as a tool to constrain the masses of stars, stellar remnants, and, in the future, extrasolar planets, using precise ground- and space-based observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Advanced Pellet Cladding Interaction Modeling Using the US DOE CASL Fuel Performance Code: Peregrine

The US DOE’s Consortium for Advanced Simulation of LWRs (CASL) program has undertaken an effort to enhance and develop modeling and simulation tools for a virtual reactor application, including high fidelity neutronics, fluid flow/thermal hydraulics, and fuel and material behavior. The fuel performance analysis efforts aim to provide 3-dimensional capabilities for single and multiple rods to assess safety margins and the impact of plant operation and fuel rod design on the fuel thermomechanical- chemical behavior, including Pellet-Cladding Interaction (PCI) failures and CRUD-Induced Localized Corrosion (CILC) failures in PWRs. [1-3] The CASL fuel performance code, Peregrine, is an engineering scale code that is built upon the MOOSE/ELK/FOX computational FEM framework, which is also common to the fuel modeling framework, BISON [4,5]. Peregrine uses both 2-D and 3-D geometric fuel rod representations and contains a materials properties and fuel behavior model library for the UO2 and Zircaloy system common to PWR fuel derived from both open literature sources and the FALCON code [6]. The primary purpose of Peregrine is to accurately calculate the thermal, mechanical, and chemical processes active throughout a single fuel rod during operation in a reactor, for both steady state and off-normal conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2012

Lateral position detection and control for friction stir systems

An apparatus and computer program are disclosed for processing at least one workpiece using a rotary tool with rotating member for contacting and processing the workpiece. The methods include oscillating the rotary tool laterally with respect to a selected propagation path for the rotating member with respect to the workpiece to define an oscillation path for the rotating member. The methods further include obtaining force signals or parameters related to the force experienced by the rotary tool at least while the rotating member is disposed at the extremes of the oscillation. The force signals or parameters associated with the extremes can then be analyzed to determine a lateral position of the selected path with respect to a target path and a lateral offset value can be determined based on the lateral position. The lateral distance between the selected path and the target path can be decreased based on the lateral offset value.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Visualizing Safeguards: Software for Conceptualizing and Communicating Safeguards Data

The nuclear programs of states are complex and varied, comprising a wide range of fuel cycles and facilities. Also varied are the types and terms of states’ safeguards agreements with the IAEA, each placing different limits on the inspectorate’s access to these facilities. Such nuances make it difficult to draw policy significance from the ground-level nuclear activities of states, or to attribute ground-level outcomes to the implementation of specific policies or initiatives. While acquiring a firm understanding of these relationships is critical to evaluating and formulating effective policy, doing so requires collecting and synthesizing large bodies of information. Maintaining a comprehensive working knowledge of the facilities comprising even a single state’s nuclear program poses a challenge, yet marrying this information with relevant safeguards and verification information is more challenging still. To facilitate this task, Brookhaven National Laboratory has developed a means of capturing the development, operation, and safeguards history of all the facilities comprising a state’s nuclear program in a single graphic. The resulting visualization offers a useful reference tool to policymakers and analysts alike, providing a chronology of states’ nuclear development and an easily digestible history of verification activities across their fuel cycles.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2015

Model-Based Design and Integration of Large Li-ion Battery Systems

This presentation introduces physics-based models of batteries and software toolsets, including those developed by the U.S. Department of Energy's (DOE) Computer-Aided Engineering for Electric-Drive Vehicle Batteries Program (CAEBAT). The presentation highlights achievements and gaps in model-based tools for materials-to-systems design, lifetime prediction and control.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2014

Advanced Pellet-Cladding Interaction Modeling using the US DOE CASL Fuel Performance Code: Peregrine

The US DOE’s Consortium for Advanced Simulation of LWRs (CASL) program has undertaken an effort to enhance and develop modeling and simulation tools for a virtual reactor application, including high fidelity neutronics, fluid flow/thermal hydraulics, and fuel and material behavior. The fuel performance analysis efforts aim to provide 3-dimensional capabilities for single and multiple rods to assess safety margins and the impact of plant operation and fuel rod design on the fuel thermo-mechanical-chemical behavior, including Pellet-Cladding Interaction (PCI) failures and CRUD-Induced Localized Corrosion (CILC) failures in PWRs. [1-3] The CASL fuel performance code, Peregrine, is an engineering scale code that is built upon the MOOSE/ELK/FOX computational FEM framework, which is also common to the fuel modeling framework, BISON [4,5]. Peregrine uses both 2-D and 3-D geometric fuel rod representations and contains a materials properties and fuel behavior model library for the UO2 and Zircaloy system common to PWR fuel derived from both open literature sources and the FALCON code [6]. The primary purpose of Peregrine is to accurately calculate the thermal, mechanical, and chemical processes active throughout a single fuel rod during operation in a reactor, for both steady state and off-normal conditions.

CASL, Consortium for Advanced Simulation of LWRs, ↗
DOE OSTI2015

Optimizing Geothermal Drilling: Oil and Gas Technology Transfer

There is a significant amount of financial risk associated with geothermal drilling. This study of drilling operations seeks opportunities to improve upon current practices and technologies. The scope of this study included analyzing 21 geothermal wells and 21 oil and gas wells. The goal was to determine a 'Perfect Well' using historical data to compare the best oil and gas well to the best geothermal well. Unfortunately, limitations encountered in the study included missing data (bit records, mud information, etc.) and poor data collection practices An online software database was used to format drilling data to IADC coded daily drilling reports and generate figures for analysis. Six major issues have been found in geothermal drilling operations. These problems include lost circulation, rig/ equipment selection, cementing, penetration rate, drilling program, and time management. As a result of these issues, geothermal drilling averaged 56.4 days longer than drilling comparable oil and gas wells in the wells in this study. Roughly $13.9 million was spent on non-productive time in the 21 geothermal wells, compared with only $1.3 million in the oil and gas wells, assuming a cost of $50,000 per day. Comparable events such as drilling the same sized hole, tripping in/out, cementing, and running the same size casing took substantially less time in the oil and gas wells. Geothermal wells were drilled using older and/or less advanced technology to depths less than 10,000 feet, while oil and gas wells reached 12,500 feet faster with purpose built rigs. A new approach is now underway that will optimize drilling programs throughout the drilling industry using Mechanical Specific Energy (MSE) as a tool to realize efficient drilling processes. Potential improvements for current geothermal operations are: the use of electronic records, real time services, and official glossary terms to describe rig operations, and advanced drilling rigs/technology.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Revised Extended Grid Library

The Revised Eolus Grid Library (REGL) is a mesh-tracking library that was developed for use with the MCNP6TM computer code so that (radiation) particles can track on an unstructured mesh. The unstructured mesh is a finite element representation of any geometric solid model created with a state-of-the-art CAE/CAD tool. The mesh-tracking library is written using modern Fortran and programming standards; the library is Fortran 2003 compliant. The library was created with a defined application programmer interface (API) so that it could easily integrate with other particle tracking/transport codes. The library does not handle parallel processing via the message passing interface (mpi), but has been used successfully where the host code handles the mpi calls. The library is thread-safe and supports the OpenMP paradigm. As a library, all features are available through the API and overall a tight coupling between it and the host code is required. Features of the library are summarized with the following list: Can accommodate first and second order 4, 5, and 6-sided polyhedra; any combination of element types may appear in a single geometry model; parts may not contain tetrahedra mixed with other element types; pentahedra and hexahedra can be together in the same part; robust handling of overlaps and gaps; tracks element-to-element to produce path length results at the element level; finds element numbers for a given mesh location; finds intersection points on element faces for the particle tracks; produce a data file for post processing results analysis; reads Abaqus .inp input (ASCII) files to obtain information for the global mesh-model; supports parallel input processing via mpi; and support parallel particle transport by both mpi and OpenMP.

Martz, Roger L.↗