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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Effect of Dilute Magnetism in a Topological Insulator

Three-dimensional (3D) topological insulator (TI) has emerged as a unique state of quantum matter and generated enormous interests in condensed matter physics. The surfaces of a 3D TI consist of a massless Dirac cone, which is characterized by the Z 2 topological invariant. Introduction of magnetism on the surface of a TI is essential to realize the quantum anomalous Hall effect and other novel magneto-electric phenomena. Here, by using a combination of first-principles calculations, magneto-transport and angle-resolved photoemission spectroscopy (ARPES), we study the electronic properties of gadolinium (Gd)-doped Sb 2 Te 3 . Our study shows that Gd doped Sb 2 Te 3 is a spin-orbit-induced bulk band-gap material, whose surface is characterized by a single topological surface state. Our results provide a new platform to investigate the interactions between dilute magnetism and topology in magnetic doped topological materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Dilute Combustion Control Using Spiking Neural Networks

Dilute combustion with exhaust gas recirculation (EGR) in spark-ignition engines presents a cost-effective method for achieving higher levels of engine efficiency. At high levels of EGR, however, cycle-to-cycle variability (CCV) of the combustion process is exacerbated by sporadic occurrences of misfires and partial burns. Previous studies have shown that temporal deterministic patterns emerge at such conditions and certain combustion cycles have a significant influence over future events. Due to the complexity of the combustion process and the nature of CCV, harnessing all the deterministic information for control purposes has remained challenging even with physics based 0-D, 1-D, and high-fidelity computational fluid dynamics (CFD) models. In this study, we present a data-driven approach to optimize the combustion process by controlling CCV adjusting the cycle-to-cycle fuel injection quantity. Readily available data from in-cylinder pressure was used to train a spiking neural network (SNN) which learns the optimal way to manage fuel injection in order to reduce CCV while maintaining acceptable levels of fuel consumption. SNNs are particularly well suited for powertrain control applications due to their ability to be deployed on FPGA-based neuromorphic hardware which are small, inexpensive, and have a low power demand. The high-performance computing (HPC) resources of Oak Ridge National Laboratory were used to run an evolutionary-based training approach for choosing the best SNN configuration that minimizes the size of the network while achieving the desired goal. The neuromorphic hardware with the optimized SNN deployed was connected to the rapid prototyping engine control system for real-time control implementation and tested on a single cylinder version of a GM LNF 4-cylinder engine. The results show a significant reduction of CCV with a small percentage of additional fuel used to stabilize the charge.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Refinement of Pitting Factor Basis to Evaluate Minimum Nitrite Requirement in Dilute Waste Chemistries

Considering that chloride concentrations are an order of magnitude lower at SRS than the maximum chloride previously tested to evaluate pitting susceptibility of carbon steel, it has been proposed that the Pitting Factor methodology be refined to determine if a reduction in the minimum nitrite requirement is warranted in more dilute solutions and those with chloride concentrations more indicative of waste tank chemistries at SRS. Through the use of cyclic potentiodynamic polarization, the susceptibility of A537 carbon steel to pitting corrosion was evaluated. The Pitting Factor was shown to accurately predict pitting susceptibility throughout the chemistry envelope evaluated. In addition, it was shown that nitrite is not required for inhibition of pitting corrosion in tank conditions with chloride concentrations observed at SRS and up to 4 M nitrate. Based upon these findings, new control limits were proposed that removed the minimum nitrite requirement within the chemistry envelope evaluated up to 50 °C.

36 MATERIALS SCIENCE↗