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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Cooperative fault management for resilient integration of renewable energy

Cooperative fault management (CFM) is designed herein to control different types of renewable energy resources cooperatively during electrical faults. This paper studies systems with a high penetration of photovoltaic (PV) energy and wind energy. First, CFM leverages power converters of PV farms to boost the ride-through capability of nearby doubly-fed induction generators (DFIGs). By controlling PV farms’ output voltages to change smoothly during both fault initiation and fault clearance, the widely used crowbar in DFIGs is less likely to be activated. Crowbar activation adversely makes DFIGs lose controllability and absorb reactive power. The second contribution is the development of a software-defined CFM controller and a controller in-the-loop demonstration of the real-time performance of this optimization-based CFM. CFM capitalizes on distributed optimization formulation to enable flexibility, plug-and-play, and privacy-preserving. Computation time, however, is a major concern for optimization-based dynamics control. Here, real-time controller-in-the-loop simulation results show optimization-based CFM can output reference values around 60 ms and is quick enough for dynamic control.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Hydrogen production with seawater-resilient bipolar membrane electrolyzers

Generation of H 2 and O 2 from untreated water sources represents a promising alternative to ultrapure water required in contemporary proton exchange membrane-based electrolysis. Bipolar membrane-based devices, often used in electrodialysis and CO 2 electrolysis, facilitate impure water electrolysis via the simultaneous mediation of ion transport and enforcement of advantageous microenvironments. Herein, we report their application in direct seawater electrolysis; we show that upon introduction of ionic species such as Na + and Cl - from seawater, bipolar membrane electrolyzers limit the oxidation of Cl - to corrosive OCl - at the anode to a Faradaic efficiency (FE) of 0.005%, while proton exchange membrane electrolyzers under comparable operating conditions exhibit up to 10% FE to Cl oxidation. In conclusion, the effective mitigation of Cl - oxidation by bipolar membrane electrolyzers underpins their ability to enable longer-term seawater electrolysis than proton exchange membrane assemblies by a factor of 140, suggesting a path to durable seawater electrolysis.

08 HYDROGEN↗
DOE OSTI2023

Effect of Cr and Ni concentrations on resilience of cast Nb- alloyed heat resistant austenitic steels at extreme high temperatures

Austenitic Cr–Ni alloyed heat resistant steels with Nb additions are used for intensively thermo-mechanically loaded cast components working in extreme high temperature oxidizing environment. Their performance during static oxidation and transient thermo-mechanical loading was investigated to recommend an optimal cost-effective Cr/Ni composition of Nb-alloyed austenitic class steels. Here, the static oxidation and transient thermo-mechanical behavior of three austenitic steels with different Cr/Ni alloying levels were investigated and compared for variety of working conditions. Static oxidation was performed between 900 °C and 1000 °C in air for 400 h. The critical temperature which increases spallation during static oxidation was determined for each of the steel alloying levels. In addition, thermal cycling of a constrained specimen was done with varying upper cycling temperatures between 850 °C and 1000 °C. SEM and TEM analyses were supported by thermodynamic simulation of the phases precipitated in the metal matrix and the structure of formed oxide layers. These studies were used to determine the mechanisms of degradation of thermo-mechanically loaded Cr/Ni austenitic steels at extreme high temperatures. A recommendation for a cost-effective Cr/Ni alloying level for different working conditions was determined.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Soil microbial EPS resiliency is influenced by carbon source accessibility

The adaptability of soil microbial communities to prolonged periods of drought is influenced by their ability to produce extracellular polymeric substances (EPS) with sufficient water retention properties. Microbial EPSs as water reservoirs during drought have been extensively investigated, but it remains unknown how carbon substrate accessibility to soil microbial communities will affect the chemical properties of the EPS they generate, and whether this in turn will alter their water retention ability. In this work, we observed that the accessibility of carbon substrates influenced microbial community structure and, consequently, the chemical properties of EPS produced by the microbial communities. Further, our results demonstrated that an insoluble carbon substrate (i.e., chitin), stimulated microbial communities to produce EPS with better water retention properties in comparison to a soluble carbon substrate (i.e., N-acetylglucosamine; NAG). In all, this study demonstrates the importance of carbon substrate accessibility by soil microorganisms in regulating the community structure and consequently, the EPS carbon chemistry, which in turn can greatly influence the adaptability of soil microbial communities to drought.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Designing resilient IoT and Edge Computing with federated tinyML

The rapid growth of the Internet of Things (IoT) and Edge Computing (EC) has brought significant conveniences to modern society but has also greatly expanded the cyber attack surfaces, particularly as these technologies are being increasingly integrated into critical systems such as power grids, healthcare, and smart homes. Here, to improve IoT/EC’s cybersecurity posture, we leveraged Artificial Intelligence (AI) and Machine Learning (ML) by employing tinyML to monitor voluminous IoT data for cyber threats while addressing devices’ resource constraints, and utilizing Federated Learning (FL) to share local detection knowledge across the system while preserving privacy. Building on our three-layer architecture combining tinyML and FL to enhance autonomous cyber attack detection, this paper demonstrated that the architecture improves detection accuracy, reduces resource consumption, and enables lightweight, secure IoT device monitoring. These results were validated using the public N-BaIoT dataset as well as real IoT network traffic data collected under multiple attack scenarios from our testbeds. Additionally, we introduced an enhanced FL methodology with a novel preprocessing stage, including federated feature selection and global preprocessor construction, to address IoT/EC data heterogeneity. We developed a physical IoT testbed for attack simulations and data collection, implemented a tinyML-powered detector for realistic model validation, and also built a virtual testbed for scalable evaluations of FL models across diverse network environments.

Cognitive cyber↗