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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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22 records · Page 2

Moisture-Induced Alumina Scale Spallation: The Hydrogen Factor

For some time our community has been concerned with interfacial spallation of protective alumina scales, not just upon immediate cooldown, but as a time-delayed phenomenon. Moisture-induced delayed spallation (MIDS) and desktop spallation (DTS) of TBC's refer to this process. It is most apparent for relatively adherent alumina scales that have survived cool down in a dry environment, built up considerable thickness and strain energy, and have been somewhat damaged, such as by cyclic oxidation cracking. Indeed, a "sweet zone" can be defined that maximizes the observed effect as a function of all the relevant factors. Moisture has been postulated to serve as a source of interfacial hydrogen embrittlement derived from reaction with aluminum in the alloy at an exposed interface. The purpose of this monograph is to trace the close analogy of this phenomenon to other hydrogen effects, such as embrittlement of aluminides and blistering of alloys and anodic alumina films. A formalized, top-down, logic tree structure is presented as a guide to this discussion. A theoretical basis for interfacial weakening by hydrogen is first cited, as are demonstrations of hydrogen as a reaction product or detected interfacial species. Further support is provided by critical experiments that produce the same moisture effect, but by isolating hydrogen from other potential causative factors. These experiments include tests in H2-containing atmospheres or cathodic hydrogen charging.

Smialek, James L.↗

Changing Circulation Structure and Precipitation Characteristics in Asian Monsoon Regions: Greenhouse Warming vs. Aerosol Effects

Using model outputs from CMIP5 historical integrations, we have investigated the relative roles of anthropogenic emissions of greenhouse gases (GHG) and aerosols in changing the characteristics of the large-scale circulation and rainfall in Asian summer monsoon (ASM) regions. Under GHG warming, a strong positive trend in low-level moist static energy (MSE) is found over ASM regions, associated with increasing large-scale land-sea thermal contrast from 1870's to present. During the same period, a mid tropospheric convective barrier (MCB) due to widespread reduction in relative humidity in the mid- and lower troposphere is strengthening over the ASM regions, in conjunction with expanding areas of anomalous subsidence associated with the Deep Tropical Squeeze (DTS) [Lau and Kim, 2015]. The opposing effects of MSE and MCB lead to enhanced total ASM rainfall, but only a partial strengthening of the southern portion of the monsoon meridional circulation, coupled to anomalous multi-cellar overturning motions over ASM land. Including anthropogenic aerosol emissions strongly masks MSE but enhances MCB via increased stability in the lower troposphere, resulting in an overall weakened ASM circulation with suppressed rainfall. Rainfall characteristics analyses indicate that under GHG, overall precipitation efficiency over the ASM region is reduced, manifesting in less moderate but more extreme heavy rain events. Under combined effects of GHG and aerosols, precipitation efficiency is unchanged, with more moderate, but less extreme rainfall.

Asian monsoon↗

Statistical Study on Multispacecraft Widespread Solar Energetic Particle Events During Solar Cycle 24

We conduct a statistical study on the large three-spacecraft widespread solar energetic particle (SEP) events. Longitudinal distributions of the peak intensities, onset delays, and relation between the SEP intensity, coronal mass ejection (CME) shock speed, width, and the kinetic energy of the CME have been investigated. We apply a Gaussian fit to obtain the SEP intensity Io and distribution width and a forward-modeling fit to determine the true shock speed and true CME width. We found a good correction between and connection angel to the flare site and Io and the kinetic energy of the CME. By including the true chock speed and true CME widths, we reduce root-mean-square errors on the predicted SEP intensity by ~41% for protons compared to Richards et al.'s (2014, https://doi.org/10.1007/s11207-014-0524-8) prediction. The improved correction between the CME kinetic energy and SEP intensity provides strong evidence for the CME-shock acceleration theory of SEPs. In addition, we found that electron and proton release time delays (DTs) relative to Type II radio bursts increase with connection angles. The average electron (proton) DT is ~14 (32) min for strongly anisotropic events and ~2.5 (4.4) hr for weakly anisotropic events. Poor magnetic connectivity and large scattering effects are two main reasons to cause large delays.

Xie, H.↗

Quantum Leap: Evaluating the Feasibility of Quantum Machine Learning Using NASA Earth Observational Data

This study explores the feasibility of leveraging quantum machine learning (QML) to analyze NASA Earth Observational (EO) data for climate change research, with a particular focus on the phenomenon of ”crop frosting” which has become more prevalent due to climate change. We implemented and evaluated two QML models, the Variational Quantum Classifier (VQC) and Quantum Support Vector Classifier (QSVC), in both simulated and real quantum computing environments using a 127 qubit IBM quantum processor. Our study emphasizes the scientific rigor in comparing these quantum models with a classical Support Vector Machine (SVM) classifier, highlighting their performance in processing climate data. The results offer valuable insights into the potential scientific advantages, limitations, and scalability of QML for analyzing EO datasets, thus paving the way for more advanced climate modeling and predictive analytics using quantum computing. We showcased how Environmental Interaction Knowledge Graphs (EIKGs) and Digital Twins (DTs) can be integrated into this study. This research underscores the transformative potential of Classical and QML leveraging KGs and DT to address the multifaceted challenges posed by climate change.

Quantum Computing↗