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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

NLR HPC Eagle Node Power Data

Power time series captured from all Eagle nodes using iLO (Integrated Lights Out) The Eagle HPC operated at NLR from 2019 through 2024. Eagle was a 2,000-node, 8-petaflop system. This dataset is a comprehensive time series of instantaneous snapshots of power usage at 1 minute intervals from all nodes at the node level. Data provided in compressed Hive dataset/Parquet format. iLO Power Time Series Fields ts: Timestamp dv: Device / Node - Rack and Unit - r103u17 == r(ack)103u(nit)17 vl: Value - Value in watts (instantaneous value at sampling time) day month year

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2015

EOS Aura Mission Status

This PowerPoint presentation will discuss EOS Aura mission and spacecraft subsystem summary, recent and planned activities, inclination adjust maneuvers, propellant usage lifetime estimate. Eric Moyer, ESMO Deputy Project Manager-Technical (code 428) has reviewed and approved the slides on April 30, 2015.

propellant usage↗
NASA NTRS2024

Bridging the Gap: Enhancing Prominence and Provenance of NASA Datasets in Research Publications

Attribution of datasets that were used to generate research results described in peer-reviewed publications to the original source of these datasets (which are often archived at NASA Earth Science data centers) has been very challenging. Even though the data citation standard of citing datasets as research artifacts and citing them with Digital Object Identifiers (DOIs) was introduced over a decade ago, most authors do not properly reference the data used in their studies and merely mention them in the text. The lack of proper citations of datasets makes the peer-reviewed publication less transparent, imperils reproducibility, and impedes open science. We offer an open-source publication management methodology and a tool that can help to enhance usage-based data discovery, prominence, and provenance of the data; reproducibility of the research results; and potentially increase the return on investment on NASA-funded research.

open-source↗
NASA NTRS2024

Analyzing EOSDIS Dataset Research Outputs using Knowledge Graphs and Large Language Models

Datasets, unlike publications, can be updated over time, with each new version receiving a DOI but not always being linked to previous ones. This complicates tracking citations across a dataset’s lifecycle. We address this by integrating dataset versions and citations into a knowledge graph (KG), which helps trace dataset citations and analyze dataset usage in applied research. To categorize publications from various journals, we fine-tuned NASA IMPACT INDUS Large Language Model (LLM) on a labeled publication set, assigning publications to one of twenty applied research areas. By linking datasets to these research areas, we improved dataset searchability and discovery through these domains.

open-source↗
NASA NTRSDate not supplied

Discovering Research Areas in Dataset Applications Through Knowledge Graphs and Large Language Models

Scientific datasets are increasingly cited in peer-reviewed journal publications, facilitating easy access to research utilizing those datasets. Datasets undergo a life cycle where older versions of datasets are replaced by newer versions often due to improvements in data resolution, algorithms, and other factors. Unlike peer reviewed documents registered with a single Digital Unique Identifier (DOI), datasets can be updated over time and the newer version of the datasets are registered with a new DOI which is not necessarily linked to the previous version of the dataset. It is challenging when publications citing a dataset need to be traced over the entire life cycle of that dataset. We provide an innovative approach to link the dataset versions and publications using a knowledge graph (KG). KG can help to trace the dataset cited in publications over the entire dataset life cycle and shed light into dataset usage in various applied research areas. We fine-tuned the pretrained NASA IMPACTINDUS Large Language Model (LLM) on a set of labeled publications abstracts. Our results showed that 87% of the publications were classified into one of twenty applied research areas, while the remaining 13% were classified into non-applied research areas. By linking datasets to applied research areas through the KG and employing Global Change Master Directory(GCMD), a well-established controlled vocabulary of scientific keywords describing Earth science datasets, we contribute to a transparent and advanced search and discovery mechanism for datasets across the Earth data ecosystem. The integrated KG and LLM approach is now incorporated and operational in dataset publication management at one of NASA’s Earth science data archival centers.

data provenance↗
DOE OSTI2013

Techno-Economic Analysis of BEV Service Providers Offering Battery Swapping Services (Presentation)

Battery electric vehicles (BEVs) could significantly reduce the nation's gasoline consumption and greenhouse gas emissions rates. However, both the upfront cost and the limited range of the vehicle are perceived to be deterrents to the widespread adoption of BEVs. A service provider approach to marketing BEVs, coupled with a battery swapping infrastructure deployment could address both issues and accelerate BEV adoption. This presentation examines customer selection, service usage statistics, service plan fees and driver economics. Our results show it is unlikely that a battery swapping service plan will be more cost-effective than ownership of a conventional vehicle. A battery swapping service plan may be a more cost-effective solution than a directly owned BEV for some single-vehicle, high-mileage consumers. However, other factors not considered in this analysis could decrease the viability of such a service.

25 ENERGY STORAGE↗
DOE OSTI2015

Gauging User Interest in Non-Traditional Library Resources

The National Renewable Energy Laboratory (NREL) is a government funded research laboratory based in Golden, Colorado. In addition to collecting traditional library resources such as journals, conference proceedings, and print and electronic books, the library also spends a significant portion of its collection development funds on resources not often found in many libraries: technical industry standards (e.g., ISO, IEC, ASTM, IEEE) and energy-related market reports. Assessing user needs for these resources is difficult for a number of reasons, particularly because standardized usage statistics are lacking or non-existent. Standards and market reports are generally costly and include fairly restrictive license agreements, which increase the importance of making informed collection development decisions. This presentation will discuss the NREL Library's current collection assessment and development practices as they relate to these unique resources.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Sustainable Immersive Visualization: A Tale of Two Visualization Labs

For large-scale immersive installations, sustainability is a challenge. This talk presents a comparative analysis of two immersive visualization laboratories, each following distinct trajectories. At the core of this discussion lies the question of what has made the NREL ESIF Insight Center a sustainable success for the last decade. Our examination encompasses three pivotal ingredients: the right funding model, the right usage model, and demonstrating added value.

funding model↗
DOE OSTI2016

An improved multilevel Monte Carlo method for estimating probability distribution functions in stochastic oil reservoir simulations

In this paper, we develop an improved multilevel Monte Carlo (MLMC) method for estimating cumulative distribution functions (CDFs) of a quantity of interest, coming from numerical approximation of large-scale stochastic subsurface simulations. Compared with Monte Carlo (MC) methods, that require a significantly large number of high-fidelity model executions to achieve a prescribed accuracy when computing statistical expectations, MLMC methods were originally proposed to significantly reduce the computational cost with the use of multifidelity approximations. The improved performance of the MLMC methods depends strongly on the decay of the variance of the integrand as the level increases. However, the main challenge in estimating CDFs is that the integrand is a discontinuous indicator function whose variance decays slowly. To address this difficult task, we approximate the integrand using a smoothing function that accelerates the decay of the variance. In addition, we design a novel a posteriori optimization strategy to calibrate the smoothing function, so as to balance the computational gain and the approximation error. The combined proposed techniques are integrated into a very general and practical algorithm that can be applied to a wide range of subsurface problems for high-dimensional uncertainty quantification, such as a fine-grid oil reservoir model considered in this effort. The numerical results reveal that with the use of the calibrated smoothing function, the improved MLMC technique significantly reduces the computational complexity compared to the standard MC approach. Finally, we discuss several factors that affect the performance of the MLMC method and provide guidance for effective and efficient usage in practice.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Large-scale inverse model analyses employing fast randomized data reduction: INVERSE MODELING WITH DATA REDUCTION

When the number of observations is large, it is computationally challenging to apply classical inverse modeling techniques. We have developed a new computationally efficient technique for solving inverse problems with a large number of observations (e.g., on the order of 10 7 or greater). Our method, which we call the randomized geostatistical approach (RGA), is built upon the principal component geostatistical approach (PCGA). We employ a data reduction technique combined with the PCGA to improve the computational efficiency and reduce the memory usage. Specifically, we employ a randomized numerical linear algebra technique based on a so-called “sketching” matrix to effectively reduce the dimension of the observations without losing the information content needed for the inverse analysis. In this way, the computational and memory costs for RGA scale with the information content rather than the size of the calibration data. Our algorithm is coded in Julia and implemented in the MADS open-source high-performance computational framework (http://mads.lanl.gov). We apply our new inverse modeling method to invert for a synthetic transmissivity field. Compared to a standard geostatistical approach (GA), our method is more efficient when the number of observations is large. Moreover, our method is capable of solving larger inverse problems than the standard GA and PCGA approaches. Thus, our new model inversion method is a powerful tool for solving large-scale inverse problems. The method can be applied in any field and is not limited to hydrogeological applications such as the characterization of aquifer heterogeneity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Climate impact of a regional nuclear weapons exchange: An improved assessment based on detailed source calculations

In this paper, we present a multi-scale study examining the impact of a regional exchange of nuclear weapons on global climate. Our models investigate multiple phases of the effects of nuclear weapons usage, including growth and rise of the nuclear fireball, ignition and spread of the induced firestorm, and comprehensive Earth system modeling of the oceans, land, ice, and atmosphere. This study follows from the scenario originally envisioned by Robock et al. (2007a), based on the analysis of Toon et al. (2007), which assumes a regional exchange between India and Pakistan of fifty 15-kiloton weapons detonated by each side. We expand this scenario by modeling the processes that lead to production of black carbon, in order to refine the black carbon forcing estimates of these previous studies. When the Earth system model is initiated with 5 × 10 9 kg of black carbon in the upper troposphere (approximately 9 to 13 km), the impact on climate variables such as global temperature and precipitation in our simulations is similar to that predicted by previously published work. However, while our thorough simulations of the firestorm produce about 3.7 × 10 9 kg of black carbon, we find that the vast majority of the black carbon never reaches an altitude above weather systems (approximately 12 km). Therefore, our Earth system model simulations conducted with model-informed atmospheric distributions of black carbon produce significantly lower global climatic impacts than assessed in prior studies, as the carbon at lower altitudes is more quickly removed from the atmosphere. In addition, our model ensembles indicate that statistically significant effects on global surface temperatures are limited to the first 5 years and are much smaller in magnitude than those shown in earlier works. None of the simulations produced a nuclear winter effect. We find that the effects on global surface temperatures are not uniform and are concentrated primarily around the highest arctic latitudes, dramatically reducing the global impact on human health and agriculture compared with that reported by earlier studies. Lastly, our analysis demonstrates that the probability of significant global cooling from a limited exchange scenario as envisioned in the previous studies is highly unlikely, a conclusion supported by examination of natural analogs, such as large forest fires and volcanic eruptions.

58 GEOSCIENCES↗
DOE OSTI2018

Intrinsic Constraints on Asymmetric Turbulent Transport of Scalars Within the Constant Flux Layer of the Lower Atmosphere: CONSTANT FLUX LAYER

A widely used assumption in boundary layer meteorology is the z independence of turbulent scalar fluxes F s throughout the atmospheric surface layer, where z is the distance from the boundary. This assumption is necessary for the usage of Monin-Obukhov Similarity Theory and for the interpretation of eddy covariance measurements of F s when using them to represent emissions or uptake from the surface. It is demonstrated here that the constant flux assumption offers intrinsic constraints on the third-order turbulent transport of F s in the unstable atmospheric surface layer. When enforcing z independence of F s on multilevel F s measurements collected above different surface cover types, it is shown that increasing instability leads to a novel and universal description of (i) the imbalance between ejecting and sweeping eddy contributions to F s and (ii) the ratio formed by a dimensionless turbulent transport of Fs and a dimensionless turbulent transport of scalar variance. When combined with structural models for the turbulent transport of F s , these two findings offer a new perspective on “closing” triple moments beyond conventional gradient diffusion schemes. A practical outcome is a diagnostic of the constant flux assumption from single-level F s measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Membrane‐acting biomimetic peptoids against visceral leishmaniasis

Visceral leishmaniasis (VL) is among the most neglected tropical diseases in the world. Drug cell permeability is essential for killing the intracellular residing parasites responsible for VL, making cell‐permeating peptides a logical choice to address VL. Unfortunately, the limited biological stability of peptides restricts their usage. Sequence‐specific oligo‐ N ‐substituted glycines (‘peptoids’) are a class of peptide mimics that offers an excellent alternative to peptides in terms of ease of synthesis and good biostability. We tested peptoids against the parasite Leishmania donovani in both forms, that is, intracellular amastigotes and promastigotes. N ‐alkyl hydrophobic chain addition (lipidation) and bromination of oligopeptoids yielded compounds with good antileishmanial activity against both forms, showing the promise of these antiparasitic peptoids as potential drug candidates to treat VL.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Worldwide Population Estimates for Small Geographic Areas

This chapter discusses the basis for these population estimates, scope, and limitations based on experiences in development of massive global population datasets and usage of these datasets as a basis for sampling design. It presents tools and approaches for using these georeferenced population estimates for complex household survey sampling. The chapter provides a unified resource for understanding current gridded population datasets, their use in survey research, and promising areas of future work toward improved population estimates. It includes an overview of popular gridded population datasets, common methodological frameworks for developing gridded population estimates, and discusses pros and cons for selecting a gridded population dataset from a survey perspective. The chapter focuses on survey methods that use gridded population estimates specifically. It highlights differences between census population estimates and gridded population estimates that may be relevant when planning data collection. The chapter presents a case study of gridded population data and sampling methods in Nigeria.

Amer, Safaa↗
DOE OSTI2023

Smartly Optimizing Crystallinity, Compatibility, and Morphology for Polymer Solar Cells by Small Molecule Acceptor with Unique 2D-EDOT Side Chain

A desired morphology is essential for achieving efficient polymer solar cells. Donors and acceptors with appropriate crystallization can lead to a suitable phase-separated morphology for effective photocurrent generation process. Inspired by the success of Y6 acceptors and the 2D side chain engineering on popular polymer donors and small molecule acceptors, the usage of unique 2D 3,4-ethylene dioxythiophene (EDOT) side chains on Y6 to regulate its crystallinity, compatibility, and thus the related blend morphology is explored. Here, in this study, two molecules of BTP-EDOT-4F and BTP-EDOT-4Cl with such unique 2D EDOT side chains are designed and synthesized. Due to the advantage of EDOT side chain, when these molecules are blended with PM6, the decent power conversion efficiencies (PCEs) of 16.78% and 15.87% are obtained. Furthermore, BTP-EDOT-4F is selected as the third component and added into PM6:L8-BO binary system to form ternary blends. The optimized crystallinity, compatibility, and morphology of such ternary blend are discovered in the presence of BTP-EDOT-4F, which enables efficient exciton dissociation and charge transport as well as decreased recombination, resulting in higher short circuit current density (J sc ) and fill factor. Finally, the outstanding PCE of 18.56% is achieved in ternary blends containing PM6, L8-BO, and BTP-EDOT-4F.

2D EDOT side chains↗
DOE OSTI2024

Constructing Crown Ether-Based Supramolecular Adhesives with Ambient-Temperature Applicable and Durable Adhesion

Supramolecular adhesives are attracting considerable attentions owing to their dynamic and reversible bonding, while the complex curing conditions and poor performance under extreme conditions severely restrict their applicability. Herein, a series of tetra-crown ether-terminated polyethylene glycol (TCE-PEG) adhesives are presented in which plenty of supramolecular interactions, including Van der Waals, hydrogen bonding, π–π staking, metal coordination, and electrostatic ones, provide strong adhesion on multiple types of substrates. Highly relevant for practical applications, ultra-strong adhesivity of TCE-PEG can be achieved without requiring additional ultraviolet radiation, heat, or chemical treatment at ambient temperature. It also exhibits durable adhesive behavior, excellent underwater stability, and low-temperature tolerance. Especially, by incorporating ionic polymer fragments of polyethyleneimine hydrochloride, additional hydrogen bonding between secondary amines and crown ether rings can be induced to enhance the lap-shear strength to 7.21 MPa due to the formation of supramolecular cross-linked network. Finally, this work pioneers a rather unique supramolecular approach for easily formed, ultra-strong crown-ether-based adhesives bearing great potential for applications in critical environments of limited heat source and unallowed solvent usage.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Low‐PGM and PGM‐Free Catalysts for Proton Exchange Membrane Fuel Cells: Stability Challenges and Material Solutions

Abstract Fuel cells as an attractive clean energy technology have recently regained popularity in academia, government, and industry. In a mainstream proton exchange membrane (PEM) fuel cell, platinum‐group‐metal (PGM)‐based catalysts account for ≈50% of the projected total cost for large‐scale production. To lower the cost, two materials‐based strategies have been pursued: 1) to decrease PGM catalyst usage (so‐called low‐PGM catalysts), and 2) to develop alternative PGM‐free catalysts. Grand stability challenges exist when PGM catalyst loading is decreased in a membrane electrode assembly (MEA)—the power generation unit of a PEM fuel cell—or when PGM‐free catalysts are integrated into an MEA. More importantly, there is a significant knowledge gap between materials innovation and device integration. For example, high‐performance electrocatalysts usually demonstrate undesired quick degradation in MEAs. This issue significantly limits the development of PEM fuel cells. Herein, recent progress in understanding the degradation of low‐PGM and PGM‐free catalysts in fuel cell MEAs and materials‐based solutions to address these issues are reviewed. The key factors that degrade the MEA performance are highlighted. Innovative, emerging material concepts and development of low‐PGM and PGM‐free catalysts are discussed.

Du, Lei↗