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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Load Mitigation on Floating Offshore Wind Turbines with Advanced Controls and Tuned Mass Dampers

General Electric, the National Renewable Energy Laboratory (NREL), the University of Massachusetts Amherst (UMass), and Glosten have recently completed a US Department of Energy (DOE)-funded research program to study technologies for mitigating loads on floating offshore wind turbines through the use of advanced turbine controls and tuned mass dampers (TMDs). The analysis was based upon the Glosten PelaStar tension leg platform (TLP) with GE Haliade 150 turbine, a system developed in a previous front end engineering design (FEED) study funded by the Energy Technology Institute (ETI) in the UK. The platform was designed for the WaveHub wave energy research site, with a mean water depth of 59-m. Loads were analyzed by running time-domain simulations in four 50-year return period (50-YRP) ultimate load state (ULS) conditions and 77 fatigue load state (FLS) environmental conditions. In 50-YRP conditions advanced controls are not active. The influence of TMDs on ULS loads have been reported previously (Park et al. [2]). In FLS conditions advanced controls and TMDs afford dramatic reductions in fatigue damage, offering the potential of significant savings in tower structural requirements. Simulations in turbine idling conditions were run in OrcaFlex, and simulations in operating conditions were run in FAST. Simulations were run with a baseline turbine controller, representative of the current state of the art, and an advanced controller developed by NREL to use collective and individual blade pitch control to maintain rotor speed and reduce tower loads. UMass developed a number of TMD types, with varying system configurations, including passive nonlinear dampers and semi-actively controlled dampers with an inverse velocity groundhook control algorithm. Loads and accelerations in FLS conditions were evaluated on the basis of damage equivalent loads (DELs), and fatigue damage was computed by Miner's summations of stress cycles at the tower base. To study sensitivity to water depth, loads were analyzed at both the 59-m WaveHub depth and a more commercially realistic depth of 100 m. TMDs reduce fatigue damage at the tower-column interface flange by up to 52% in 59-m water depth and up to 28% in 100 m water depth. Advanced controls reduce fatigue damage at the tower-column flange by up to 22% in 59-m water depth and up to 40% in 100 m water depth. The most effective load-mitigation strategy is combining advanced controls with TMDs. This strategy affords a 71% reduction in fatigue damage in both 59-m and 100-m water depths.

17 WIND ENERGY↗
DOE OSTI2022

Review of Radio Frequency Interference and Potential Impacts on the CMB-S4 Cosmic Microwave Background Survey

CMB-S4 will map the cosmic microwave background to unprecedented precision, while simultaneously surveying the millimeter-wave time-domain sky, in order to advance our understanding of cosmology and the universe. CMB-S4 will observe from two sites, the South Pole and the Atacama Desert of Chile. A combination of small- and large-aperture telescopes with hundreds of thousands of polarization-sensitive detectors will observe in several frequency bands from 20-300 GHz, surveying more than 50% of the sky to arcminute resolution with unprecedented sensitivity. CMB-54 seeks to make a dramatic leap in sensitivity while observing across a broad range of largely unprotected spectrum which is increasingly being utilized for terrestrial and satellite transmissions. Fundamental aspects of CMB instrument technology leave them vulnerable to radio frequency interference (RFI) across a wide range of frequencies, including frequencies outside of their observing bands. Ground-based CMB instruments achieve their extraordinary sensitivities by deploying large focal planes of superconducting bolometers to extremely dry, high-altitude sites, with large fractional bandwidths, wide fields of view, and years of integration time. Suitable observing sites have historically offered significant protection from RFI, both naturally through their extremely remote locations as well as through restrictions on local emissions. Since the coupling mechanisms are complex, "safe" levels or frequencies of emission that would not interfere with CMB measurements cannot always be determined through straightforward calculations. We discuss models of interference for various types of RFI relevant to CMB-54, mitigation strategies, and the potential impacts on survey sensitivity.

Cosmic Microwave Background↗
DOE OSTI2016

WE-H-BRC-03: Failure Mode and Effects Analysis in the First Clinical Implementation of a Novel Stereotactic Breast Radiotherapy Device: GammaPod™

Purpose: GammaPod™, the first stereotactic radiotherapy device for early stage breast cancer treatment, has been recently installed and commissioned at our institution. A multidisciplinary working group applied the failure mode and effects analysis (FMEA) approach to perform a risk analysis. Methods: FMEA was applied to the GammaPod™ treatment process by: 1) generating process maps for each stage of treatment; 2) identifying potential failure modes and outlining their causes and effects; 3) scoring the potential failure modes using the risk priority number (RPN) system based on the product of severity, frequency of occurrence, and detectability (ranging 1–10). An RPN of higher than 150 was set as the threshold for minimal concern of risk. For these high-risk failure modes, potential quality assurance procedures and risk control techniques have been proposed. A new set of severity, occurrence, and detectability values were re-assessed in presence of the suggested mitigation strategies. Results: In the single-day image-and-treat workflow, 19, 22, and 27 sub-processes were identified for the stages of simulation, treatment planning, and delivery processes, respectively. During the simulation stage, 38 potential failure modes were found and scored, in terms of RPN, in the range of 9-392. 34 potential failure modes were analyzed in treatment planning with a score range of 16-200. For the treatment delivery stage, 47 potential failure modes were found with an RPN score range of 16-392. The most critical failure modes consisted of breast-cup pressure loss and incorrect target localization due to patient upper-body alignment inaccuracies. The final RPN score of these failure modes based on recommended actions were assessed to be below 150. Conclusion: FMEA risk analysis technique was applied to the treatment process of GammaPod™, a new stereotactic radiotherapy technology. Application of systematic risk analysis methods is projected to lead to improved quality of GammaPod™ treatments. Ying Niu and Cedric Yu are affiliated with Xcision Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Stabilizing electrodeposition in elastic solid electrolytes containing immobilized anions

Ion transport–driven instabilities in electrodeposition of metals that lead to morphological instabilities and dendrites are receiving renewed attention because mitigation strategies are needed for improving rechargeability and safety of lithium batteries. The growth rate of these morphological instabilities can be slowed by immobilizing a fraction of anions within the electrolyte to reduce the electric field at the metal electrode. We analyze the role of elastic deformation of the solid electrolyte with immobilized anions and present theory combining the roles of separator elasticity and modified transport to evaluate the factors affecting the stability of planar deposition over a wide range of current densities. Lastly, we find that stable electrodeposition can be easily achieved even at relatively high current densities in electrolytes/separators with moderate polymer-like mechanical moduli, provided a small fraction of anions are immobilized in the separator.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Large regional shortwave forcing by anthropogenic methane informed by Jovian observations

Recently, it was recognized that widely used calculations of methane radiative forcing systematically underestimated its global value by 15% by omitting its shortwave effects. We show that shortwave forcing by methane can be accurately calculated despite considerable uncertainty and large gaps in its shortwave spectroscopy. We demonstrate that the forcing is insensitive, even when confronted with much more complete methane absorption spectra extending to violet light wavelengths derived from observations of methane-rich Jovian planets. We undertake the first spatially resolved global calculations of this forcing and find that it is dependent on bright surface features and clouds. Localized annual mean forcing from preindustrial to present-day methane increases approaches +0.25 W/m 2 , 10 times the global annualized shortwave forcing and 43% of the total direct CH 4 forcing. Shortwave forcing by anthropogenic methane is sufficiently large and accurate to warrant its inclusion in historical analyses, projections, and mitigation strategies for climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Persistent urban heat

Urban surface and near-surface air temperatures are known to be often higher than their rural counterparts, a phenomenon now labeled as the urban heat island effect. However, whether the elevated urban temperatures are more persistent than rural temperatures at timescales commensurate to heat waves has not been addressed despite its importance for human health. Combining numerical simulations by a global climate model with a surface energy balance theory, it is demonstrated here that urban surface and near-surface air temperatures are significantly more persistent than their rural counterparts in cities dominated by impervious materials with large thermal inertia. Further use of these materials will result in even stronger urban temperature persistence, especially for tropical cities. The present findings help pinpoint mitigation strategies that can simultaneously ameliorate the larger magnitude and stronger persistence of urban temperatures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Transcriptomic and functional analyses uncover a conserved effector driving genotype-dependent virulence in the Sphaerulina musiva-Populus trichocarpa interaction

The introduction of invasive microbes compromises the structure, biodiversity, and function of naïve ecosystems. Sphaerulina musiva, a hemibiotrophic pathogen that causes leaf spot and stem cankers in Populus species, exemplifies an invasive fungal pathogen spread by human activities. However, the genetic mechanisms of pathogenicity and virulence are poorly understood, impeding mitigation strategies. We utilized RNA sequencing to identify fungal effectors linked to stem canker formation, informing the development of future strategies for effective disease management. Our analysis revealed 70 genes differentially expressed at 2 weeks and 110 genes at 3 weeks between inoculated trees and controls. Notably, the gene with the highest expression at 2 weeks and the second highest at 3 weeks was homologous to Extracellular protein 2 (Ecp2). Complementary genome-wide association studies linked sequence polymorphisms in this locus to phenotypic variation in disease severity. Infiltration of S. musiva Ecp2 into Populus trichocarpa leaves induced necrosis in susceptible genotypes. Gene disruption using a CRISPR-Cas9 RNP system resulted in a genotype-dependent reduction of stem canker and disease severity. Tracing the evolutionary history of this effector across the fungal kingdom, we uncovered clade-specific gene-family expansions and orthologs in new species. These findings raise questions about the function and adaptive significance of these gene families in fungal lifestyles. Our study provides the first tractable target for breeding resistant poplar genotypes, addressing the challenges of managing S. musiva and uncovering mechanisms that drive its virulence, and provides deeper insights into the evolutionary dynamics of a conserved small-secreted protein with a diversity of functions.

Sondreli, Kelsey L [Oregon State University]↗
DOE OSTI2025

Genetic and biochemical characterization of a radical SAM enzyme required for post-translational glutamine methylation of methyl-coenzyme M reductase

ABSTRACT Methyl-coenzyme M reductase (MCR), the key catalyst in the anoxic production and consumption of methane, contains an unusual 2-methylglutamine residue within its active site. In vitro data show that a B12-dependent radical SAM (rSAM) enzyme, designated MgmA, is responsible for this post-translational modification (PTM). Here, we show that two different MgmA homologs are able to methylate MCR in vivo when expressed in Methanosarcina acetivorans , an organism that does not normally possess this PTM. M. acetivorans strains expressing MgmA showed small, but significant, reductions in growth rates and yields on methylotrophic substrates. Structural characterization of the Ni(II) form of Gln-methylated M. acetivorans MCR revealed no significant differences in the protein fold between the modified and unmodified enzyme; however, the purified enzyme contained the heterodisulfide reaction product, as opposed to the free cofactors found in eight prior M. acetivorans MCR structures, suggesting that substrate/product binding is altered in the modified enzyme. Structural characterization of MgmA revealed a fold similar to other B12-dependent rSAMs, with a wide active site cleft capable of binding an McrA peptide in an extended, linear conformation. IMPORTANCE Methane plays a key role in the global carbon cycle and is an important driver of climate change. Because MCR is responsible for nearly all biological methane production and most anoxic methane consumption, it plays a major role in setting the atmospheric levels of this important greenhouse gas. Thus, a detailed understanding of this enzyme is critical for the development of methane mitigation strategies.

Rodriguez Carrero, Roy J. (ORCID:0000000184475641)↗
DOE OSTI2023

Disentangling the sources of ionizing radiation in superconducting qubits

Abstract Radioactivity was recently discovered as a source of decoherence and correlated errors for the real-world implementation of superconducting quantum processors. In this work, we measure levels of radioactivity present in a typical laboratory environment (from muons, neutrons, and $$\gamma $$ γ -rays emitted by naturally occurring radioactive isotopes) and in the most commonly used materials for the assembly and operation of state-of-the-art superconducting qubits. We present a GEANT-4 based simulation to predict the rate of impacts and the amount of energy released in a qubit chip from each of the mentioned sources. We finally propose mitigation strategies for the operation of next-generation qubits in a radio-pure environment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

A Graph-Based Impact Metric for Mitigating Lateral Movement Cyber Attacks

Most cyber network attacks begin with an adversary gain- ing a foothold within the network and proceed with lateral movement until a desired goal is achieved. The mechanism by which lateral movement occurs varies but the basic signa- ture of hopping between hosts by exploiting vulnerabilities is the same. Because of the nature of the vulnerabilities typ- ically exploited, lateral movement is very difficult to detect and defend against. In this paper we define a dynamic reach- ability graph model of the network to discover possible paths that an adversary could take using different vulnerabilities, and how those paths evolve over time. We use this reacha- bility graph to develop dynamic machine-level and network- level impact scores. Lateral movement mitigation strategies which make use of our impact scores are also discussed, and we detail an example using a freely available data set.

cyber security↗
DOE OSTI2020

Toward Large-Scale Image Segmentation on Summit

Semantic segmentation of images is an important computer vision task that emerges in a variety of application domains such as medical imaging, robotic vision and autonomous vehicles to name a few. While these domain-specific image analysis tasks involve relatively small image sizes (~ 10 2 × 10 2 ), there are many applications that need to train machine learning models on image data with extents that are orders of magnitude larger (~10 4 × 10 4 ). Training deep neural network (DNN) models on large extent images is extremely memory-intensive and often exceeds the memory limitations of a single graphical processing unit, a hardware accelerator of choice for computer vision workloads. Here, an efficient, sample parallel approach to train U-Net models on large extent image data sets is presented. Its advantages and limitations are analyzed and near-linear strong-scaling speedup demonstrated on 256 nodes (1536 GPUs) of the Summit supercomputer. Using a single node of the Summit supercomputer, an early evaluation of a recently released model parallel framework called GPipe is demonstrated to deliver ~ 2X speedup in executing a U-Net model with an order of magnitude larger number of trainable parameters than reported before. Performance bottlenecks for pipelined training of U-Net models are identified and mitigation strategies to improve the speedups are discussed. Together, these results open up the possibility of combining both approaches into a unified scalable pipelined and data parallel algorithm to efficiently train U-Net models with very large receptive fields on data sets of ultra-large extent images.

Seal, Sudip↗
DOE OSTI2023

A Design of Activity-Based Mobility Intervention

Human mobility influences our society and vice versa. During the COVID-19 pandemic, non-pharmaceutical intervention that alters activity-based mobility such as work-from-home greatly impacted human mobility patterns. Many studies on developing mitigation strategies have employed or implemented their own mobility intervention within their model assumption. For fair evaluation between intervention strategies across models, it is significant to set up compatible experimental environments. However, it is difficult to apply the identical intervention to different kinds of models and compare their effectiveness because each model might have different assumptions, capabilities, and implementations. Even if one can apply intervention to heterogeneous models, it may produce undesirable artifacts due to difference of models and integration with intervention. Therefore, minimizing undesirable artifacts and facilitating intervention experiments across heterogeneous models are substantial. Taking this into account, this paper investigates a design of activity-based mobility intervention (ABMI). We define ABMI together with related concepts and develop an extensible data model and schema of ABMI based on the 5W1H method that can be used in different models. As a case study, we apply the ABMI model to a micro-simulation to demonstrate the usability of the proposed model. We expect that standardized ABMI and interfaces may help to streamline development and experiments of intervention strategies across heterogeneous models.

Kim, Joon-Seok↗
DOE OSTI2023

Detection and Calibration of Low-Energy Nuclear Recoils for Dark Matter and Neutrino Scattering Experiments

Detection of low-energy nuclear recoil events plays a central role in searches for particle dark matter interactions with atomic matter and studies of coherent neutrino scatters. Precise nuclear recoil calibration data allow the responses of these dark matter and neutrino detectors to be characterized and enable in situ evaluation of an experiment's sensitivity to anticipated signals. This article reviews the common methods for detection of nuclear recoil events and the wide variety of techniques that have been developed to calibrate detector response to nuclear recoils. We summarize the main experimental factors that are critical for accurate nuclear recoil calibrations, investigate mitigation strategies for different backgrounds and biases, and discuss how the presentation of calibration results can facilitate comparison between experiments. Lastly, we discuss the challenges for future nuclear recoil calibration efforts and the physics opportunities they may enable.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Reversible Losses in Proton Exchange Membrane Water Electrolysis

Lower anode catalyst loadings and higher current densities are essential to lowering the levelized cost of H 2 production via proton exchange membrane water electrolysis (PEMWE). However, these approaches can induce significant durability challenges. Here, we show that cell degradation can include large reversible voltage losses across a variety of conditions, including low loadings and high currents. Although there is limited published discussion of reversible voltage losses in PEMWE, we demonstrate that they are an important consideration in cell efficiency and durability. Understanding the mechanisms of reversible losses and developing mitigation strategies is therefore a key priority for enabling low-cost PEMWE.

08 HYDROGEN↗
DOE OSTI2025

Impact of Testing Method on Safety Assessment of Aged Li-Ion Cells: Part II – Aged Cells Without Li Plating

Understanding the safety profile of aged Li-ion batteries is essential for developing effective battery management and hazard mitigation strategies. However, most safety assessments have focused on fresh batteries, with just a few calorimetry studies on aged batteries with metal oxide positive electrodes. This study provides a broad assessment of commercial 18650-type Li-ion batteries with NCA, NMC, and LFP positive electrodes, both uncycled and aged under conditions that promoted solid electrolyte interphase (SEI) growth as the dominant degradation mechanism. The cells underwent mechanical (nail penetration, crush), electrical (overcharge, overdischarge), and thermal (accelerating rate calorimetry) abuse tests. Safety was rated on general characteristics such as mass loss, maximum temperature, and EUCAR (European Council for Automotive R&D) hazard level, as well as characteristics specific to individual abuse tests. Generally, aged cells with SEI growth exhibited similar or improved safety compared to uncycled cells, contrasting with our previous findings on NCA cells with Li plating as the dominant aging mechanism (Part I of this series). Yet, some tests and characteristics indicated reduced aged cell safety, such as earlier triggering of mechanical failure. These results emphasize the need to examine aged battery safety across diverse empirical techniques, degradation modes, and chemistries.

Lithium-ion cells↗
DOE OSTI2025

Modeling Electrodeposition in 3D Porous Architectures for Solid-State Li-Metal Batteries

Li-metal storage in three-dimensional (3D) electrodes is considered a potential dendrite-mitigation strategy. The large surface area and high porosity of these electrodes result in reduced local Li-plating current densities. The porous topology provides a scaffold for Li-deposition and stripping, maintaining both mechanical integrity and Li accessibility. The goal of this study is to understand how characteristics, such as geometry and material properties, affect the current distribution and deposition pattern. To this end, we developed a computational method to track material growth driven by electrodeposition within a complex geometry. This method ensures that the finite-element discretization remains conforming to the moving boundary while preserving an adequate mesh quality, and thus maintains solution accuracy. Using this new computational tool, we analyze the conditions under which porous anode architectures effectively expand the surface area of the charge-transfer interface, and self-regulate current density and dendrite growth.

3D electrode architectures↗
DOE OSTI2023

Reports From The Frontier: Overcoming Limitations for Pure-water Anion-exchange-membrane Electrolysis

Anion-exchange-membrane electrolysis is positioned to play a key role in the predicted exponential growth of green hydrogen technology with essential R&D advances. We reveal key design parameters essential to commercialization. First, stable alkaline oxygen-evolution reaction catalysts with high electronic conductivity and minimal surface reconstruction during operation must be designed. Alkaline catalyst layers must also be applied to the membrane electrode assembly with scalable, industrially relevant techniques. Second, ionomer oxidation mitigation strategies must be developed. Furthermore, this approach could also target other creative catalyst layer design, such as phase-separation control to protect oxidation-prone organic components or catalyst engineering to direct selectivity for hydroxide over polymer oxidation. If competitive efficiency and durability can be achieved in pure water, AEM electrolysis has the potential to become a dominant electrolyzer technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Artificial Diversity and Defense Security (ADDSec)

Artificial Diversity and Defense Security (ADDSec) machine learning algorithms are used to classify and cluster threats so that an appropriate response can be initiated as a mitigation strategy. The package includes an ensemble of machine learning algorithms such as Support Vector Machines, naïve bayes, logistic regression, and random forest that evolve with the data to recognize anomalous behavior at the host and network levels. Inputs into the machine learning algorithms include end host system calls, system utilization, packet captures, and syslog messages. The machine learning algorithms can be retrained based on user defined intervals or on the number of packets received. ADDSEC's threat responses include Internet Protocol (IP) Address randomization, application port number randomization, and application library randomization. The IP randomization implementation is built on top of a Software Defined Networking (SDN) framework. The SDN controller installs flows on each of the SDN switches with randomized source and destination IP addresses. The application port numbers are randomized using iptables. The application library randomization is created with a LLVM compiler. All randomization schemes are transparent to the endpoints on the network. 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. SAND2021-3379 O

Cox, RebeccaE.↗