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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Chromium Poisoning Mitigation Strategy in Strontium-Doped Lanthanum Manganite-Based Air Electrodes in Solid Oxide Fuel Cells

Abstract Chromium poisoning of the air electrode remains an obstacle to the long-term performance of solid oxide fuel cells (SOFCs). In Sr-doped LaMnO3 (LSM) air electrodes, the poisoning process results in two types of deposits, chromium oxide (Cr2O3), and Mn, Cr spinel (MnCr2O4). The former forms electrochemically and the latter forms via a chemical reaction. By applying a small anodic reverse bias, Cr2O3 deposits can be removed because their formation is electrochemical in nature. However, MnCr2O4 deposits remain because their formation is chemical, rather than electrochemical, in nature. In situ chemical decomposition of the Mn, Cr spinel was investigated as an alternate removal method as thermodynamics supports its decomposition into constituent oxides below ∼540 °C in pure oxygen. The spinel decomposition process was characterized using thermogravimetric and X-ray diffraction analyses. The experimentally determined rate of spinel decomposition was undetectable (very slow) with isolated MnCr2O4 powders. The addition of 10 mol% gadolinia doped ceria (GDC) and silver powders significantly increased the rate of decomposition. However, the rate is limited by the diffusion of oxygen through the decomposed oxide layer. Although one strategy may be the addition of GDC and silver to the LSM air electrode to enhance spinel decomposition, the more effective mitigation strategy would be to prevent the formation of MnCr2O4 spinel in the first place through the removal of the reactants: Cr2O3 via electrochemical cleaning and mobile Mn ions in the zirconia electrolyte by incorporating a diffusion barrier layer such as GDC between the air electrode and electrolyte.

Electrochemistry↗
DOE OSTI2025

Mitigation of Boiling-Induced Thermal Degradation Using Microporous Nickel Inverse Opals Structures

Engineered microporous structures have received much attention in high-heat-flux electronics cooling due to their high thermal conductivity and permeability, and large surface area for heat transfer, but are susceptible to boiling-induced thermal degradation. Here, this study investigates the efficacy of nickel inverse opals (NiIOs) in mitigating structural degradation caused by corrosion-assisted erosion during pool boiling with water as the working fluid. First, we compared the reliability of NiIOs to copper inverse opals (CuIOs) for a 3-day pool boiling test at constant heat flux. The NiIOs demonstrated superior resistance to thermal degradation due to their inherent corrosion resistance and mechanical strength. Subsequently, we conducted a more controlled experiment to show the effect of heat flux on the degradation of the NiIOs while excluding the effect of temperature variations. Pool boiling tests of 20-μm-thickness NiIOs covering an area of ∼11 × 11 mm 2 with a 2.5 × 2.5 mm 2 heater at the center were conducted at heat flux levels of 20%, 40%, and 60% of the critical heat flux (CHF) for 3 days. The NiIOs subjected to heat flux levels of 20% and 40% CHF showed minimal degradation, while the sample subjected to 60% CHF showed erosion on the top surface due to higher bubble formation and departure rate. These results show the potential of NiIOs as a promising solution for long-term thermal management in high-power electronic devices, although design considerations for maximum allowable heat flux are necessary for reliable operation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mitigation of Leakage and Water Ingress for a Promising Phase Change Material (PCM) Containing Polyethylene Glycol (PEG)

A promising and cost-effective phase change material (PCM) containing polyethylene glycol (PEG) 600, 800, and/or 1000 has been synthesized. It is shape stabilized using a sol-gel method and displays promising thermal properties. These properties make the PCMs good candidates for thermal batteries and other thermal energy storage applications in the building sector. However, PEG leakage is observed at elevated temperatures, and due to the hygroscopic nature of PEG, moisture ingress is also observed, which can have a significant effect on performance and durability. Thus, we have developed hydrophobic coatings to prevent PEG leakage and mitigate moisture ingress. The selected approach involves a secondary sol-gel process during which a thin layer formulated with hydrophobic precursors is deposited onto the surface of the PCM samples. Several coating formulations have been investigated, including formulations composed of tetraethyl orthosilicate (TEOS), diethoxy(dimethyl)silane (DEDMS), triethoxymethylsilane (TEMS), and n-octyltriethoxysilane (OTES). We find that this is effective at increasing hydrophobicity of the PCM substrates. It also decreases substrate leakage.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2016

Wind Turbine Controller to Mitigate Structural Loads on a Floating Wind Turbine Platform

This paper summarizes the control design work that was performed to optimize the controller of a wind turbine on the WindFloat structure. The WindFloat is a semi-submersible floating platform designed to be a support structure for a multi-megawatt power-generating wind turbine. A controller developed for a bottom-fixed wind turbine configuration was modified for use when the turbine is mounted on the WindFloat platform. This results in an efficient platform heel resonance mitigation scheme. In addition several control modules, designed with a coupled linear model, were added to the fixed-bottom baseline controller. The approach was tested in a fully coupled nonlinear aero-hydroelastic simulation tool in which wind and wave disturbances were modeled. This testing yielded significant improvements in platform global performance and tower-base-bending loading.

17 WIND ENERGY↗
DOE OSTI2017

Mitigating e-beam-induced hydrocarbon deposition on graphene for atomic-scale scanning transmission electron microscopy studies

Chemical vapor deposition (CVD) grown graphene used in (scanning) transmission electron microscopy [(S)TEM] studies must undergo a careful transfer of the one-atom-thick membrane from the growth surface (typically a Cu foil) to the TEM grid. During this transfer process, the graphene invariably becomes contaminated with foreign materials. This contamination proves to be very problematic in the (S)TEM because often >95% of the graphene is obscured, and imaging of the pristine areas results in e-beam-induced hydrocarbon deposition which further acts to obscure the desired imaging area. In this article, the authors examine two cleaning techniques for CVD grown graphene that mitigate both aspects of the contamination problem: visible contamination covering the graphene, and “invisible” contamination that deposits onto the graphene under e-beam irradiation. Furthermore, the visible contamination may be removed quickly by a rapid thermal annealing to 1200 °C in situ and the invisible e-beam-deposited contamination may be removed through an Ar/O 2 annealing procedure prior to imaging in the (S)TEM.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON): A statistical model based iterative image reconstruction method to eliminate limited-view artifacts and to mitigate the temporal-average artifacts in time-resolved CT

Purpose: In x-ray computed tomography (CT), a violation of the Tuy data sufficiency condition leads to limited-view artifacts. In some applications, it is desirable to use data corresponding to a narrow temporal window to reconstruct images with reduced temporal-average artifacts. However, the need to reduce temporal-average artifacts in practice may result in a violation of the Tuy condition and thus undesirable limited-view artifacts. In this paper, the authors present a new iterative reconstruction method, synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON), to eliminate limited-view artifacts using data acquired within an ultranarrow temporal window that severely violates the Tuy condition. Methods: In time-resolved contrast enhanced CT acquisitions, image contrast dynamically changes during data acquisition. Each image reconstructed from data acquired in a given temporal window represents one time frame and can be denoted as an image vector. Conventionally, each individual time frame is reconstructed independently. In this paper, all image frames are grouped into a spatial–temporal image matrix and are reconstructed together. Rather than the spatial and/or temporal smoothing regularizers commonly used in iterative image reconstruction, the nuclear norm of the spatial–temporal image matrix is used in SMART-RECON to regularize the reconstruction of all image time frames. This regularizer exploits the low-dimensional structure of the spatial–temporal image matrix to mitigate limited-view artifacts when an ultranarrow temporal window is desired in some applications to reduce temporal-average artifacts. Both numerical simulations in two dimensional image slices with known ground truth and in vivo human subject data acquired in a contrast enhanced cone beam CT exam have been used to validate the proposed SMART-RECON algorithm and to demonstrate the initial performance of the algorithm. Reconstruction errors and temporal fidelity of the reconstructed images were quantified using the relative root mean square error (rRMSE) and the universal quality index (UQI) in numerical simulations. The performance of the SMART-RECON algorithm was compared with that of the prior image constrained compressed sensing (PICCS) reconstruction quantitatively in simulations and qualitatively in human subject exam. Results: In numerical simulations, the 240{sup ∘} short scan angular span was divided into four consecutive 60{sup ∘} angular subsectors. SMART-RECON enables four high temporal fidelity images without limited-view artifacts. The average rRMSE is 16% and UQIs are 0.96 and 0.95 for the two local regions of interest, respectively. In contrast, the corresponding average rRMSE and UQIs are 25%, 0.78, and 0.81, respectively, for the PICCS reconstruction. Note that only one filtered backprojection image can be reconstructed from the same data set with an average rRMSE and UQIs are 45%, 0.71, and 0.79, respectively, to benchmark reconstruction accuracies. For in vivo contrast enhanced cone beam CT data acquired from a short scan angular span of 200{sup ∘}, three 66{sup ∘} angular subsectors were used in SMART-RECON. The results demonstrated clear contrast difference in three SMART-RECON reconstructed image volumes without limited-view artifacts. In contrast, for the same angular sectors, PICCS cannot reconstruct images without limited-view artifacts and with clear contrast difference in three reconstructed image volumes. Conclusions: In time-resolved CT, the proposed SMART-RECON method provides a new method to eliminate limited-view artifacts using data acquired in an ultranarrow temporal window, which corresponds to approximately 60{sup ∘} angular subsectors.

60 APPLIED LIFE SCIENCES↗
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 OSTI2019

A sequential DNN based Baseline Energy Prediction Framework with Long term Error Mitigation

In this paper,we aim to present a novel sequential framework containing two deep network architectures for baseline energy prediction, applied to a simulated commercial building dataset. We have observed that this sequential framework helps to improve long term prediction accuracy, there by mitigating prediction error accumulation over time. The proposed framework utilizes convolution layers to extract features from the input data space without changing spatial relations between variables. These features are memorized by tensor train based gated recurrent units for an accurate long-term prediction. Although, architecture comprising the amalgamation of convolution layers and memory cell have shown promising results in domains such as social media analysis, language modeling, video frame prediction and image recognition, this paper extends its scope to the context of energy applications. Furthermore, the addition of tensor train based gated recurrent units is motivated by the necessity of computational time reduction during the training process, there by making this framework more suitable for future in-field deployment. Lastly, results show the current framework outperforms other existing machine learning based methods, in both short-term and long-term prediction categories.

Chakraborty, Indrasis↗
DOE OSTI2022

Fragile Earth: AI for Climate Mitigation, Adaptation, and Environmental Justice

The Fragile EarthWorkshop is a recurring event that gathers the research community to find and explore howdata science can measure and progress climate and social issues, following the framework of the United Nations Sustainable Development Goals (SDGs).Fragile Earth 2022: AI for Climate Mitigation, Adaptation, and Environmental Justice is a workshop taking place as part of the ACM's KDD 2022 Conference on research in knowledge discovery and data mining and their applications. The dates for the Conference are August 14-18, 2022.

Abe, Naoki↗
DOE OSTI2023

Quantum Noise Mitigation: Introducing the Robust Quantum Circuit Scheduler for Enhanced Fidelity and Throughput

Undoubtedly, quantum computing offers valuable acceleration for solving intricate problems. One of the primary hurdles lies in executing large-scale quantum applications on backend machines. Qubit noise, among other factors, dramatically influences the execution process. Implementing effective scheduling techniques for quantum circuits is crucial for practical quantum computing and preventing excessive waiting times. The quantum realm is distinct from classical computing in terms of optimization, performance, utilization, and waiting periods. Consequently, the parameters and components of quantum circuit scheduling diverge from those of classical computing. This paper presents Quantum Noise Mitigation: Introducing the Robust Quantum Circuit Scheduler for Enhanced Fidelity and Throughput, a straightforward yet effective scheduling framework and policy that enhances noise resilience, throughput, and the fidelity of quantum circuits. Drawing inspiration from classical methods, our scheduling approach incorporates additional constraints tailored for quantum logic. The outcome demonstrates a substantial improvement in fidelity and resource management, which is vital for real-world quantum applications.

Baheri, Betis↗
DOE OSTI2020

Passive Mitigation of Cascading Propagation in Multi-Cell Lithium Ion Batteries

The heat generated during a single cell failure within a high energy battery system can force adjacent cells into thermal runaway, creating a cascading propagation effect through the entire system. This work examines the response of modules of stacked pouch cells after thermal runaway is induced in a single cell. The prevention of cascading propagation is explored on cells with reduced states of charge and stacks with metal plates between cells. Reduced states of charge and metal plates both reduce the energy stored relative to the heat capacity, and the results show how cascading propagation may be slowed and mitigated as this varies. These propagation limits are correlated with the stored energy density. Results show significant delays between thermal runaway in adjacent cells, which are analyzed to determine intercell contact resistances and to assess how much heat energy is transmitted to cells before they undergo thermal runaway. A propagating failure of even a small pack may stretch over several minutes including delays as each cell is heated to the point of thermal runaway. This delay is described with two new parameters in the form of gap-crossing and cell-crossing time to grade the propensity of propagation from cell to cell.

25 ENERGY STORAGE↗
DOE OSTI2025

Mitigation of Pitting on Nitrogen-Doped Niobium Surfaces through Two-Step Electropolishing

Surface processing of niobium superconducting RF cavities used in particle accelerators is crucial for determining their performance. The nitrogen (N)-doping method, developed at Fermilab, enhances the cavities’ quality factor by doping the cavity’s interior surface with N atoms at 800 °C. After N-doping, electropolishing (EP) is employed to remove the niobium nitride phases and attain the desired concentration of interstitial N atoms. This study explores the effects of EP conditions on N-doped niobium samples. The samples were electropolished at 5 to 40 °C and voltages between 3 and 22 V. Different EP voltage ranges produced two types of pits, classified based on their sizes. Larger pits, linked to higher voltages, are also affected by the reaction rate. Pitting could be reduced at a lower temperature and adequate EP voltage. However, to effectively minimize gas evolution forming large-sized pitting, peeling off the top nitride layer before EP might be beneficial. This was achieved through precise low-voltage etching, forming a two-step EP process. The process involves removing the top 100–200 nm layer at a low voltage, followed by standard EP to remove the required material. This two-step EP process effectively mitigated the pitting risk associated with gas evolution on N-doped surfaces.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Review—Understanding and Mitigating Some of the Key Factors that Limit Non-Aqueous Lithium-Air Battery Performance

In this article, we have reviewed our work on understanding and mitigating some of the key factors that limit non-aqueous Li-air battery performance. Advances in Li-air battery technology require fundamental understanding of the discharge and charge processes. We first summarize an investigation of Li-air batteries based on a well-defined cathode surfaces having size-selected silver clusters. This work provided key insight into the nucleation and growth mechanism of the discharge product and its relationship to lowering charge potentials. We then describe the development of new cathode materials including ones based on Pd and Mo2C nanoparticles that give very low charge potentials. This work has shown that it is possible to achieve very good round-trip efficiencies as well as up to 100 cycles in a Li-air cell. Finally, we discuss investigations of likely sources of electrolyte decomposition at the cathode and anode, which need to be resolved in order to achieve the long cycle life that is necessary to enable Li-air batteries.

charge overpotential↗
DOE OSTI2016

Mitigation of Alfven activity by 3D magnetic perturbations on NSTX

Observations on the National Spherical Torus eXperiment (NSTX) indicatethat externally applied non-axisymmetric magnetic perturbations (MP) canreduce the amplitude of Toroidal Alfven Eigenmodes (TAE) and Global AlfvenEigenmodes (GAE) in response to pulsed n=3 non-resonant fields. Fromfull-orbit following Monte Carlo simulations with the 1- and 2-fluidresistive MHD plasma response to the magnetic perturbation included,it was found that in response to MP pulses the fast-ion losses increasedand the fast-ion drive for the GAEs was reduced. The MP did not affectthe fast-ion drive for the TAEs significantly but the Alfven continuumat the plasma edge was found to be altered due to the toroidal symmetrybreaking which leads to coupling of different toroidal harmonics. TheTAE gap was reduced at the edge creating enhanced continuum damping ofthe global TAEs, which is consistent with the observations. The resultssuggest that optimized non-axisymmetric MP might be exploited to controland mitigate Alfven instabilities by tailoring the fast-ion distributionfunction and/or continuum structure.

fast ions↗
DOE OSTI2021

Type-I ELM mitigation by continuous lithium granule gravitational injection into the upper tungsten divertor in EAST

Large edge-localized modes (ELMs) were mitigated by gravitational injection of lithium granules into the upper X-point region of the EAST device with tungsten plasma-facing components. The maximum ELM size was reduced by ~ 70% in high βN H-mode plasmas. Large ELM stabilization was sustained for up to about 40 energy confinement times, with constant core radiated power and no evidence of high-Z or low-Z impurity accumulation. The lithium granules injection reduced the edge plasma pedestal density and temperature and their gradients, due to increased edge radiation and reduced recycling from the plasma-facing components. Ideal stability calculations using the ELITE code indicate that the stabilization of large ELMs correlates with improved stability of intermediate-n peeling-ballooning modes, due to reduced edge current resulting from the profile changes. The pedestal pressure reduction was partially offset by a core density increase, which resulted in a modest ~ 7% drop in core stored energy and normalized energy confinement time. We surmise that the remnant small ELMs are triggered by the penetration of multiple Li granules just past the separatrix, similar to small ELMs triggered by deuterium pellet [S. Futatani et al., Nucl. Fusion 54 (2014) 073008]. This study extends previous ELM elimination with Li powder injection [R. Maingi et al., Nucl. Fusion 58 (2018) 024003] in EAST because 1) use of small, dust-like powder and the related potential health hazards were eliminated, and 2) use of macroscopic granules should be more applicable to future devices, due to deeper penetration than dust particles, e.g. inside the separatrix with velocities ~ 10 m/s in EAST.

EAST↗
DOE OSTI2022

Wall conditioning and ELM mitigation with boron nitride powder injection in KSTAR

Results from KSTAR powder injection experiments, in which tens of milligrams of boron nitride (BN) were dropped into low-power H-mode plasmas, show an improvement in wall conditions in subsequent discharges and, in some cases, a reduction or elimination of edge-localized modes (ELMs). Injected powder is distributed by the plasma flow and is deposited on the wall and, over the course of several discharges, was observed to gradually reduce recycling by 33%, and decrease both the ELM amplitude and frequency. This is the first demonstration of the use of BN for ELM mitigation. In all of these experiments, an Impurity Powder Dropper (IPD) was used to introduce precise, controllable amounts of the materials into ELMy H-mode KSTAR discharges. The plasma duration was between 10 s and 15 s, 𝐼𝑝 = 500 kA, 𝐵𝑇 = 1.8 T, 𝑃NBI = 1.6 MW, and 𝑃ECH = 0.6 MW. Plasma densities were between 2 and 3 × 1019 m−3. In all cases, the pre-fill and startup gas-fueling was kept constant, suggesting that the decrease in baseline D𝛼 emission is in fact due to a reduction in recycling. The results presented herein highlight the viability of powder injection for intra-shot and between-shot wall conditioning.

Gilson, Erik↗
DOE OSTI2025

Optimal Mitigation Planning For Adversarial Scenarios

We propose a generalized framework which performs an optimal partitioning of a limited budget into various organizational sectors in order to improve the cybersecurity of a smart device or component in the Cyber Physical Energy System (CPS). The framework identifies the adversarial threats and possible attack sequences which can be performed to exploit cyber vulnerabilities of the component. Thereafter, we formulate an Mixed Integer Linear Programming (MILP) optimization problem which aims to evaluate the optimal budget partitions in order to minimize the number of highly likely attack sequences. Though we provide results for using the framework in CPES, the proposed methodology can be extended for multiple domains with a set of known adversarial and mitigation actions.

Purohit, Sumit [Pacific Northwest National Laborat↗
DOE OSTI2024

Mitigative Strategies for Recovering From Large Language Model Trust Violations

In this study, we investigated strategies to address trust issues arising from errors in large language models (LLMs). The study examined the impact of confidence scores, system capability explanations, and user feedback on trust restoration post-error. 68 participants viewed the responses of an LLM to 20 general trivia questions, with an error introduced on the third trial. Each participant was presented with one mitigation strategy. Participants rated their overall trust in the model and the reliability of the answer. Results showed an immediate drop in trust after the error; however, there were no differences across the three strategies in trust recovery. All conditions had a logarithmic trend in trust recovery following error. Differences in overall trust were predicted by perceived reliability of the answer, suggesting that participants were evaluating results critically and using that to inform their trust in the model. Qualitative data supported this finding; participants expressed lasting distrust despite the LLM’s later accuracy. Results showcase the need to prioritize accuracy in LLM deployment, because early errors may irrevocably damage user trust calibration and later adoption.

97 MATHEMATICS AND COMPUTING↗