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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

North America’s Potential for an Environmentally Sustainable Nickel, Manganese, and Cobalt Battery Value Chain

The Detroit Big Three General Motors (GMs), Ford, and Stellantis predict that electric vehicle (EV) sales will comprise 40–50% of the annual vehicle sales by 2030. Among the key components of LIBs, the LiNixMnyCo1−x−yO2 cathode, which comprises nickel, manganese, and cobalt (NMC) in various stoichiometric ratios, is widely used in EV batteries. This review reveals NMC cathodes from laboratory research. Furthermore, this study examines the environmental effect of NMC cathode production for EV batteries (including coating technologies), encompassing aspects such as energy consumption, water usage, and air emissions. Although gaps persist in NMC cathode environmental assessments (NMC111, NMC532, NMC622, and NMC811), limited life cycle assessments “(LCA)” have been conducted. Most available data originate from Asia (primarily China), accounting for 85% of the production of EV LIB cathode materials. The concept of battery passports for data collection on LIB components has been proposed to facilitate material traceability as a system for ensuring a sustainable supply chain for critical minerals. The automotive industry’s shift to electrification necessitates a sustainable supply chain from mine to vehicle end-of-life. As the critical mineral supply moves from Asia to North America, environmentally friendly industrial methods must be studied to provide this supply chain direction.

25 ENERGY STORAGE↗
DOE OSTI2021

Exploring the Value of Nodes with Multicommunity Membership for Classification with Graph Convolutional Neural Networks

Sampling is an important step in the machine learning process because it prioritizes samples that help the model best summarize the important concepts required for the task at hand. The process of determining the best sampling method has been rarely studied in the context of graph neural networks. In this paper, we evaluate multiple sampling methods (i.e., ascending and descending) that sample based off different definitions of centrality (i.e., Voterank, Pagerank, degree) to observe its relation with network topology. We find that no sampling method is superior across all network topologies. Additionally, we find situations where ascending sampling provides better classification scores, showing the strength of weak ties. Two strategies are then created to predict the best sampling method, one that observes the homogeneous connectivity of the nodes, and one that observes the network topology. In both methods, we are able to evaluate the best sampling direction consistently.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Enabling Renewable Energy While Protecting Wildlife: An Ecological Risk-Based Approach to Wind Energy Development Using Ecosystem-Based Management Values

Acceptance of wind energy development is challenged by stakeholders’ concerns about potential effects on the environment, specifically on wildlife, such as birds, bats, and (for offshore wind) marine animals, and the habitats that support them. Communities near wind energy developments are also concerned with social and economic impacts, as well as impacts on aesthetics, historical sites, and recreation and tourism. Lack of a systematic, widely accepted, and balanced approach for measuring the potential damage to wildlife, habitats, and communities continues to leave wind developers, regulators, and other stakeholders in an uncertain position. This paper explores ecological risk-based management (RBM) in wind energy development for land-based and offshore wind installations. This paper provides a framework for the adaptation of ecosystem-based management to wind energy development and examines that framework through a series of case studies and best management practices for applying risk-based principles to wind energy. Ten case studies indicate that wind farm monitoring is often driven by regulatory requirements that may not be underpinned by scientific questions. While each case applies principles of adaptive management, there is room for improvement in applying scientific principles to the data collection and analysis. Challenges and constraints for wind farm development to meet RBM framework criteria include collecting sufficient baseline and monitoring data year-round, engaging stakeholder facilitators, and bringing together large and diverse scientific teams. The RBM framework approach may provide insights for improved siting and consenting/permitting processes for regulators and their advisors, particularly in those nations where wind energy is still in the early development stages on land or at sea.

17 WIND ENERGY↗
DOE OSTI2017

Can the Discrepancy between Locally and Globally Derived Neutral Hydrogen Mass Functions be Explained by a Varying Value of M {sup *}?

I investigate whether it is possible to reconcile the recent Arecibo Legacy Fast Arecibo L-band Feed Array (ALFALFA) observation that the neutral hydrogen mass function (HIMF) across different galactic densities has the same, non-flat, faint-end slope, with observations of isolated galaxies and many galaxy groups that show their HIMFs to have flat faint-end slopes. I find that a fairly simple model in which the position of the knee in the mass function of each individual group is allowed to vary is able to account for both of these observations. If this model reflects reality, the ALFALFA results point to an interesting “conspiracy” whereby the differing group HIMFs always sum up to form global HIMFs with the same faint-end slope in different environments. More generally, this result implies that global environmental HIMFs do not necessarily reflect the HIMFs in individual groups belonging to that environment and cannot be used to directly measure variations in group-specific HIMFs with environment.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Exploring the Value of Learned Representations for Automated Syndromic Definitions

Objective: To better define and automate biosurveillance syndrome categorization using modern unsupervised vector embedding techniques. Introduction: Comprehensive medical syndrome definitions are critical for outbreak investigation, disease trend monitoring, and public health surveillance. However, because current definitions are based on keyword string-matching, they may miss important distributional information in free text and medical codes that could be used to build a more general classifier. Here, we explore the idea that individual ICD codes can be categorized by examining their contextual relationships across all other ICD codes. We extend previous work in representation learning with medical data [1] by generating dense vector embeddings of these ICD codes found in emergency department (ED) visit records. The resulting representations capture information about disease co-occurrence that would typically require SME involvement and support the development of more robust syndrome definitions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Demonstrating the Value of 3D Models to Support Large-Scale Digital Modifications at Nuclear Power Plants

Many Nuclear Power Plants are currently in the process of extending their operating licenses for continued generation. The use of three-dimensional (3D) modeling in the early stages of large scale NPP modernization efforts is one lower cost method that can verify proposed design changes against established guidelines and allows for visual presentation of the 3D model to various stakeholders in the project. Guidance from Nuclear Regulatory Commission NUREG 0711 and 0700, and other sources on performing HF/E for control rooms and design modifications can be visually represented in 3D models. Distance and measurements, workstation design, anthropometric considerations, and early feedback of modifications are used in 3D models to identify potential human issues early in the design process. 3D modeling is a useful tool for early design and help to reduce costs and present visuals to stakeholders early in the design.

3D Models↗