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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Gravitation and Mesh Adaption

The Gravitation and Mesh Adaptation (GaMA) toolbox consists of a set of Matlab classes for modeling the environment around asteroids and comets. A variety of gravitational models and supporting algorithms from are consolidated alongside a custom meshing utility tailored for the application. This allows the user to work within a single streamlined environment to import and manipulate surface definitions, probe the dynamical environment, integrate trajectories, and post-process results. For other applications, modified surface meshes can be exported. Gravity Models: 1) Werner's analytic polyhedron model 2) Mascon model 3) Gottlieb's spherical harmonic model 4) Approximate polyhedron models 5) Curvilinear surface models 6) Custom composite models Meshing Features: 1) Array-based half-edge data structure 2) Supports curvilinear surface definitions up to degree 4 3) Ray-tracing 4) Coarsening 5) Feature-based refinement 6) Projection 7) Smoothing 8) Mesh quality validity tests 9) Mesh repair Additional Features: 1) Solar radiation pressure model 2) Distant 3rd body model 3) Collision detection 4) Trajectory integration and post-processing 5) Visualization of surface fields

Pearl, Jason↗
DOE OSTI2021

Strangeness-changing rates and hyperonic bulk viscosity in neutron star mergers

In this paper we present a computation of the rates of strangeness-changing processes and the resultant bulk viscosity in matter at the densities and temperatures typical of neutron star mergers. To deal with the high temperature in this environment we go beyond the Fermi surface approximation in our rate calculations and numerically evaluate the full phase space integral. Here, we include processes where quarks move between baryons via meson exchange: these have generally been omitted in previous analyses but provide the dominant contribution to the rates of strangeness-changing processes and the bulk viscosity. The calculation of these rates is an essential step towards any calculation of dissipation mechanisms in hyperonic matter in mergers. As one application, we calculate the dissipation times for density oscillations at the frequencies seen in merger simulations. We find that hyperon bulk viscosity for temperatures in the MeV regime can probably be neglected in this context, but becomes highly relevant for keV-range temperatures.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Reconstructing Masses of Merging Neutron Stars from Stellar r -process Abundance Signatures

We report that neutron star mergers (NSMs) are promising astrophysical sites for the rapid neutron-capture ("r") process, but can their integrated yields explain the majority of heavy-element material in the Galaxy? One method to address this question implements a forward approach that propagates NSM rates and yields along with stellar formation rates and compares those results with observed chemical abundances of r-process-rich, metal-poor stars. In this work, we take the inverse approach by utilizing r-process-element abundance ratios of metal-poor stars as input to reconstruct the properties -especially the masses - of their neutron star (NS) binary progenitors. This novel analysis provides an independent avenue for studying the population of the original NS binary systems that merged and produced the r-process material now incorporated in Galactic metal-poor halo stars. We use ratios of elements typically associated with the limited-r-process and the actinide region to those in the lanthanide region (i.e., Zr/Dy and Th/Dy) to probe the NS masses of the progenitor merger. We find that NSMs can account for all r-process material in metal-poor stars that display r-process signatures, while simultaneously reproducing the present-day distribution of double-NS systems. Notably, with our model assumptions and the studied stellar sample, we postulate that the most r-process enhanced stars (the r–II stars) on their own would require progenitor NSMs of asymmetric systems that are distinctly different from present ones in the Galaxy. We also explore variations to the model and find that the predicted degree of asymmetry is most sensitive to the electron fraction of the remnant disk wind.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

NREL 2012 Achievement of Ethanol Cost Targets: Biochemical Ethanol Fermentation via Dilute-Acid Pretreatment and Enzymatic Hydrolysis of Corn Stover

For the DOE Bioenergy Technologies Office, the annual State of Technology (SOT) assessment is an essential activity for quantifying the benefits of biochemical platform research. This assessment has historically allowed the impact of research progress achieved through targeted Bioenergy Technologies Office funding to be quantified in terms of economic improvements within the context of a fully integrated cellulosic ethanol production process. As such, progress toward the ultimate 2012 goal of demonstrating cost-competitive cellulosic ethanol technology can be tracked. With an assumed feedstock cost for corn stover of $\$$58.50/ton this target has historically been set at $\$$1.41/gal ethanol for conversion costs only (exclusive of feedstock) and $\$$2.15/gal total production cost (inclusive of feedstock) or minimum ethanol selling price (MESP). This year, fully integrated cellulosic ethanol production data generated by National Renewable Energy Laboratory (NREL) researchers in their Integrated Biorefinery Research Facility (IBRF) successfully demonstrated performance commensurate with both the FY 2012 SOT MESP target of $\$$2.15/gal (2007$\$$, $\$$58.50/ton feedstock cost) and the conversion target of $\$$1.41/gal through core research and process improvements in pretreatment, enzymatic hydrolysis, and fermentation.

09 BIOMASS FUELS↗
DOE OSTI2023

Assessment of Existing OpenStudio Measures: Reviews, Interviews, and Future Developments

OpenStudio Measure development is continuously in progress and greatly propelled by the collaborative efforts within the building energy modeling community. To ensure the widespread adoption and benefit of OpenStudio Measures, developers must understand the current status of Measure development and the needs of OpenStudio Measure users. The first step involves a comprehensive review of existing content to prevent redundancy and gain insights into how OpenStudio Measures are used in the building energy modeling community. This knowledge can then be integrated into the Measure development process, and the expertise of practitioners and OpenStudio Measure users can be leveraged to shape future Measures. Numerous OpenStudio Measures have been created and shared on the Building Component Library (BCL). The BCL is an open-source repository housing various OpenStudio-related resources, including building component blocks, descriptive metadata, and Measures describing modifications to building energy models. The OpenStudio Measures in BCL encompass a wide range of energy conservation Measures from basic lighting power reduction to complex HVAC model transformation. They also enable users to generate customized reports and facilitate the integration of energy simulation with other analytical processes. This report presents review of 272 currently available OpenStudio Measures in BCL. The OpenStudio Measures were reviewed by category and subcategory. These Measures are summarized by their functionalities and keywords. To gain insights into how OpenStudio Measures are used in building energy modeling community, interviews were conducted. A total of 12 interview responses were collected from 6 individuals in the industry and 6 individuals in academia. The knowledge acquired from reviewing the existing Measures and interview results will be integrated into the Measure development process, and the expertise of practitioners and OpenStudio Measure users will be leveraged to shape future Measures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Open Source Visualization and Analysis Platform for 3D Reconstructions of Materials by Transmission Electron Microscopy

Three-dimensional characterization of materials at the nano- and meso-scale has become possible with transmission and scanning transmission electron microscopes (S/TEM). Its importance has extended to a wide class of nanomaterials such as hydrogen fuel cells, solar cells, industrial catalysts, new battery materials and semiconductor devices, as well as spanning high-tech industry, universities, and national labs. While capable instrumentation is abundant, this rapidly expanding demand for high-resolution tomography is bottlenecked by software that is instead tailored for lower-dose, biological applications and not optimized for higher-resolution materials applications. Existing tomography fails to utilize the chemical information provided by S/TEM spectrometers. To address this problem, this project delivered a scalable, fully functional, freely-distributable, open Source materials tomography package with a modern user interface that enables automated acquisition, alignment, and real-time reconstruction of raw tomography data, and provides advanced segmentation, three-dimensional chemical visualization and analysis optimized for materials applications. It has established an extendable framework capable of automation for high-throughput for the tomography of materials from data acquisition to visualization. Phase I and II delivered a full-featured, cross-platform, clean and integrated application for S/TEM materials tomography. It can read projection data from the microscope, with graphical tools for alignment of data, tomographic reconstruction, segmentation, and visualization of the reconstructed 3D volume. The entire pipeline can be saved to an XML state file, enabling fully reproducible data processing and analysis with a full Python environment for the development of custom algorithms, processing, and analysis requirements. Phase IIB extended the application to provide real-time tomographic reconstruction, "live updates" as data is processed, analysis of big data, and multi-channel tomography. Here, quantitative assessment of nanomaterials can occur as data is being recorded on a 3D visualization platform that accommodates additional information from multiple channels. We provide unmatched high-throughput tomography, where the complete tomographic pipeline from measurement to 3D visualization can occur rapidly. The project was extended to offer capabilities for micro-CT, X-ray, neutron, focused ion beam, atomic electron tomography and atom probe tomography. With over 600 transmission electron microscopes worldwide and approximately 50 coming online each year, the demand and impact of an open-source tomography tool is large. Significant opportunities exist in high-tech industry, universities, and national labs to enable or enhance three-dimensional imaging at the nanoscale and bring automated high-throughput approaches that will accelerate progress in materials characterization and metrology. The project supports a service based business model by enabling lab-specific acquisition and processing customization and integration-support and development that will be provided into Phase III and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Decoding Resilience by Modeling Outage and Restoration Processes in Distribution Grids: A Pittsburgh Case Study

Climate-induced extreme weather events, such as floods and heatwaves, pose significant challenges to the resilience of urban power distribution grids. This paper examines the outage and restoration dynamics of Pittsburgh's power grid during the flood event in April 2024 and three heatwaves in June, July, and August 2024. We introduce a comprehensive modeling framework that integrates outage and restoration processes, enabling the quantification of resilience metrics, including total customer-hours of power outage, maximum residual values, and restoration durations across various ZIP codes. Our analysis highlights spatial disparities in outage impacts and restoration efficiencies, with ZIP Code 15222 experiencing the highest cumulative disruptions, while ZIP Code 15217 shows lower susceptibility. By linking statistical trends with weather events, this study underscores the critical need for targeted infrastructure upgrades and advanced restoration strategies. Furthermore, the proposed framework offers valuable insights for planning and managing resilient power systems in the face of increasing climate stress.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Ion traps fabricated in a CMOS foundry

We demonstrate trapping in a surface-electrode ion trap fabricated in a 90-nm CMOS (complementary metal-oxide-semiconductor) foundry process utilizing the top metal layer of the process for the trap electrodes. The process includes doped active regions and metal interconnect layers, allowing for co-fabrication of standard CMOS circuitry as well as devices for optical control and measurement. With one of the interconnect layers defining a ground plane between the trap electrode layer and the p-type doped silicon substrate, ion loading is robust and trapping is stable. We measure a motional heating rate comparable to those seen in surface-electrode traps of similar size. This demonstration of scalable quantum computing hardware utilizing a commercial CMOS process opens the door to integration and co-fabrication of electronics and photonics for large-scale quantum processing in trapped-ion arrays.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Guest Editorial

Energy Systems Integration (ESI) is the process of coordinating the operation and planning of energy systems across multiple pathways and/or geographical scales to deliver reliable, cost-effective energy services with minimal impact on the environment. Energy systems have evolved from individual systems with little or no dependencies into a complex set of integrated systems at scales that include customers, cities, and regions. This evolution has been driven by political, economic, and environmental objectives. As we try to meet the globally recognized imperative to reduce carbon emissions through the deployment of large renewable energy capacities while also maintaining reliability and competitiveness, flexible energy systems are required. This flexibility can be attained through integrating various systems: by physically linking energy vectors, namely electricity, heat, and fuels; by coordinating these vectors across other infrastructures, namely water, data, and transport; by institutionally coordinating energy markets; and, spatially, by increasing market footprint with granularity all the way down to the customer level. Smart grids and ESI are related, in particular, the coupling between electricity, consumers, data and transport. This special section focuses on the aspects of ESI where electricity is coupled to water, heat and fuels and where this coupling brings challenges and/or opportunities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Advanced computational tools for optimization and uncertainty quantification of carbon capture processes

Advanced multi-scale modeling and simulation has the potential to dramatically reduce development time, resulting in considerable cost savings. The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and universities that is developing, demonstrating, and deploying a suite of multi-scale modeling and simulation tools. One significant computational tool is FOQUS, a Framework for Optimization and Quantification of Uncertainty and Sensitivity, which enables basic data submodels, including thermodynamics and kinetics, to be used within detailed process models to rapidly synthesize and optimize a process and determine the level of uncertainty associated with the resulting process. The overall approach of CCSI is described with a more detailed discussion of FOQUS and its application to carbon capture systems.

Carbon capture↗
DOE OSTI2017

Surface integrity and fatigue behaviour of electric discharged machined and milled austenitic stainless steel

Machining of austenitic stainless steels can result in different surface integrities and different machining process parameters will have a great impact on the component fatigue life. Understanding how machining processes affect the cyclic behaviour and microstructure are of outmost importance in order to improve existing and new life estimation models. Milling and electrical discharge machining (EDM) have been used to manufacture rectangular four-point bend fatigue test samples; subjected to high cycle fatigue. Before fatigue testing, surface integrity characterisation of the two surface conditions was conducted using scanning electron microscopy, surface roughness, residual stress profiles, and hardness profiles. Differences in cyclic behaviour were observed between the two surface conditions by the fatigue testing. The milled samples exhibited a fatigue limit. EDM samples did not show the same behaviour due to ratcheting. Recrystallized nano sized grains were identified at the severely plastically deformed surface of the milled samples. Large amounts of bent mechanical twins were observed ~ 5 μm below the surface. Grain shearing and subsequent grain rotation from milling bent the mechanical twins. EDM samples showed much less plastic deformation at the surface. Surface tensile residual stresses of ~ 500 MPa and ~ 200 MPa for the milled and EDM samples respectively were measured. - Highlights: •Milled samples exhibit fatigue behaviour, but not EDM samples. •Four-point bending is not suitable for materials exhibiting pronounced ratcheting. •LAGB density can be used to quantitatively measure plastic deformation. •Grain shearing and rotation result in bent mechanical twins. •Nano sized grains evolve due to the heat of the operation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A co-registered in-situ and ex-situ dataset from wire arc additive manufacturing process

Recent progress in sensing techniques and data analytics tools have significantly accelerated the development of Wire Arc Additive Manufacturing (WAAM) systems. This data-centric approach emphasizes leveraging sensor data available throughout the production process to optimize performance. Integration of extensive data analysis provides opportunities for improving precision, reducing waste, and enhancing the quality of produced parts. This method relies on AI/ML models and optimization techniques, which are developed using the data collected from various sources, including in-situ sensors, ex-situ imaging, and manufacturing process parameters. The quality and diversity of this data, along with the alignment between different data streams (achieved through spatiotemporal registration) are critical for the successful development of AI/ML and optimization models. In this work, we present a spatiotemporally registered dataset generated during the WAAM process of deposition of a rectangular block. The dataset includes a comprehensive description of the deposition process, process parameters, welding characteristics and acoustic data collected in-situ, and X-Ray Computed Tomography data of the build.

42 ENGINEERING↗
DOE OSTI2018

Feature Detection From LiDAR Point Cloud and Aerial Imagery Using Distance Dependent Chinese Restaurant Process [Slides]

It is possible to integrate data captured by UAS from multiple data modalities spatially. We can detect features by combining information across images and LiDAR point clouds. Performance issues exist with the current algorithms in place & could be improved. We hope to test it for at least 500 iterations. Post processing of data takes enormous efforts in case of data generated by proprietary software tools…We intend to develop a better framework for seamless integration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Oxygen Incorporation During Fabrication of Substrate CdTe Photovoltaic Devices: Preprint

Recently, CdTe photovoltaic (PV) devices fabricated in the nonstandard substrate configuration have attracted increasing interest because of their potential compatibility with flexible substrates such as metal foils and polymer films. This compatibility could lead to the suitability of CdTe for roll-to-roll processing and building-integrated PV. Currently, however, the efficiencies of substrateCdTe devices reported in the literature are significantly lower (6%-8%) than those of high-performance superstrate devices (17%) because of significantly lower open-circuit voltage (Voc) and fill factor (FF). In our recent device development efforts, we have found that processing parameters required to fabricate high-efficiency substrate CdTe PV devices differ from those necessary fortraditional superstrate CdTe devices. Here, we investigate how oxygen incorporation in the CdTe deposition, CdCl2 heat treatment, CdS deposition, and post-deposition heat treatment affect device characteristics through their effects on the junction. By adjusting whether oxygen is incorporated during these processing steps, we have achieved Voc values greater than 860 mV and efficiencies greaterthan 10%.

14 SOLAR ENERGY↗
DOE OSTI2024

A Co-Registered In-Situ and Ex-Situ Dataset of Electrical, Acoustic, and CT Characteristics from Wire Arc Additive Manufacturing Process

Recent progress in sensing techniques and data analytics tools have significantly accelerated the development of Wire Arc Additive Manufacturing (WAAM) systems. This data centric approach emphasizes leveraging available data throughout the production process to optimize performance. Integration of extensive data analysis provides the opportunity to improve precision, reduce waste, and enhance the quality of produced parts. This method relies on AI/ML models and optimization techniques, which are developed using the data collected from various sources, including in-situ sensors, ex-situ imaging, and manufacturing process parameters. The quality and diversity of this data, along with the alignment between different data streams (achieved through spatiotemporal registration) are critical for the successful development of AI/ML and optimization models. In this work, we present a spatiotemporally registered dataset generated during the WAAM process of deposition of a rectangular block. The dataset includes the comprehensive description of deposition process, process parameters, in-situ collected welding characteristics, acoustic data, and X-Ray Computed Tomography analysis data for the build. Dataset A Co-Registered In-Situ and Ex-Situ Dataset of Electrical, Acoustic, and CT Characteristics from Wire Arc Additive Manufacturing Process has arisen under UT-Battelle, LLC’s Prime Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy (DOE) to manage and operate the Oak Ridge National Laboratory. UT-Battelle, LLC will not assert any rights under United States law or under the Prime Contract it has in the dataset against any user of the dataset, including any copyrights or patent rights. UT-Battelle, LLC requests that attribution to the dataset is provided as academically appropriate.

42 ENGINEERING↗
DOE OSTI2026

Data for Physiological Controls on Carbon Fluxes and Biomass Production in Miscanthus: Insights From a Process- Based Agroecosystem Model

Biomass crops serve as essential feedstocks for renewable energy and bioproducts and play a critical role in achieving lower emissions in the transportation sector. However, dedicated perennial biomass crops such as Miscanthus × giganteus (Miscanthus) remain underrepresented in process- based agroecosystem models, limiting robust evaluation of their economic and environmental performance. In this study, we developed a data- constrained representation of the sterile triploid Miscanthus (IL clone) within the process- based model ecosys, integrating global sensitivity analysis, ensemble simulation, and parameter calibration. Planting, harvesting, and fertilization practices consistent with field management were incorporated, and phenology was constrained using PhenoCam- derived Green Chromatic Coordinate (GCC) data. Using the Morris global sensitivity analysis method, we identified 11 key physiological parameters governing plant carbon, water, and nutrient relations, particularly processes associated with CO2 assimilation. We then conducted ensemble simulations by perturbing these parameters and calibrated the model against eddy covariance fluxes and field- measured biomass. Building on the calibrated operating state, parameter- response analyses show that different photosynthetic processes influence productivity in different ways. Protein allocation determines whether productivity increases toward a higher level, whereas electron transport capacity controls additional gains once protein allocation approaches saturation. These findings demonstrate that parameter importance depends on physiological context and on which photosynthetic processes remain limiting. Calibration and validation against observations show that ecosys can reliably reproduce carbon and water fluxes, as well as both above- and belowground biomass, with post- calibration GPP R2 improving from 0.67 to 0.95 during the calibration period and remaining high during validation (R2 = 0.95). These results provide a mechanistic foundation for regional simulations and sustainable bioenergy assessments.

Carbon↗
DOE OSTI2021

Microfabricated ion trap chip with an integrated microwave antenna

An ion trap chip, which may be used for quantum information processing and the like, includes an integrated microwave antenna. The antenna is formed as a radiator connected by one of its ends to the center trace of a microwave transmission line and connected by its other end to a current return path through a ground trace of the microwave transmission line. The radiator includes several parallel, coplanar radiator traces connected in series. The radiator traces are connected such that they all carry electric current in the same direction, so that collectively, they simulate a single, unidirectionally flowing sheet of current. In embodiments, induced currents in underlying metallization planes are suppressed by parallel slots that extend in a direction perpendicular to the radiator traces.

Nordquist, Christopher↗