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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 55 records · Page 3

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 9: Viability of Data-Driven Approach for Outage Management (Deliverable D6))

This technical report is provided to US Department of Energy for progress made on the AGGERGATE project led by the Washington State University. This report is specifically related to the deliverable: ’D6: Technical report discussing the viability of the developed data-driven models and co-simulation architecture for models for operation in a real-world operational setting and the results of Tasks 1 to 8, summarizing the project findings and accomplishments to date’.

42 ENGINEERING↗

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 11 & 12: Components and Capabilities of the Resiliency Driven Outage Management and Feeder Restoration System (Deliverable D8))

This report provides progress update for the development of a outage management, feeder restoration, and restoration action feasibility check modules as part of the AGGREGATE project. Details for integration with controllability module, data driven situational awareness of network and distributed energy resources as well cyber security plan for these modules integrated with GE ADMS are also presented in the report. These three modules for outage management, feeder restoration, and restoration action feasibility check modules are developed in MATLAB and validated with a modified IEEE 123-node feeder. Results demonstrate ability of these new modules to improve the restoration process post-disaster to enhance the system resilience.

42 ENGINEERING↗

Wind-driven emissions of coarse-mode particles in an urban environment

Abstract. Quantifying surface–atmosphere exchange rates of particles is important for understanding the role of suspended particulate matter in radiative transfer, clouds, precipitation, and climate change. Emissions of coarse-mode particles with a diameter greater than 0.5 µm provide giant cloud condensation nuclei and ice nuclei. These emissions are critical for understanding the evolution of cloud microphysical properties yet remain poorly understood. Here we introduce a new method that uses lidar retrievals of the elastic backscatter and Doppler velocity to obtain surface number emissions of particles with a diameter greater than 0.53 µm. The technique is applied to study particle number fluxes over a 2-month period from 1 June to 10 August 2022 during the TRACER campaign at an urban site near Houston, TX, USA. We found that all the observed fluxes were positive (upwards), indicating particle emission from the surface. The fluxes followed a diurnal pattern and peaked near noon local time. Flux intensity varied through the 2 months with multi-day periods of strong fluxes and multi-day periods of weak fluxes. Emission particle number fluxes peaked near ∼ 100 cm−2 s−1. The daily averaged emission fluxes correlated with friction velocity and were anticorrelated with surface relative humidity. The emission flux can be parameterized as F= 3000 u*4, where u* is the friction velocity in m s−1 and the emission flux F is in cm−2 s−1. The u* dependence is consistent with emission from wind-driven erosion. Estimated values for the mass flux are in the lower range of literature values from non-urban sites. These results demonstrate that urban environments may play an important role in supplying coarse-mode particles to the boundary layer. We anticipate that quantification of these emissions will help constrain aerosol–cloud interaction models that use prognostic aerosol schemes.

54 ENVIRONMENTAL SCIENCES↗

Using machine learning to jointly harness the strength of microscopic, fundamental-science driven and macroscopic, application-driven experiments

The PARADIGM project aims at accelerating progress in science by quantitatively answering the following question: What is the optimal combination of fundamental-science and application driven experiments to maximally reduce pertinent data uncertainties? Hence, we are bridging between microscopic experiments and data, and macroscopic simulations and experiments. Answering this question entails solving a high-dimensional and complex optimization problem which we solve with machine learning techniques.

LANSCE↗

An Interaction-Free Quantum Measurement-Driven Engine

Recently highly-efficient quantum engines were devised by exploiting the stochastic energy changes induced by quantum measurement. Here we show that such an engine can be based on an interaction-free measurement, in which the meter seemingly does not interact with the measured object. We use a modified version of the Elitzur–Vaidman bomb tester, an interferometric setup able to detect the presence of a bomb triggered by a single photon without exploding it. In our case, a quantum bomb subject to a gravitational force is initially in a superposition of being inside and outside one of the interferometer arms. We show that the bomb can be lifted without blowing up. This occurs when a photon traversing the interferometer is detected at a port that is always dark when the bomb is located outside the arm. The required potential energy is provided by the photon (which plays the role of the meter) even though it was not absorbed by the bomb. A natural interpretation is that the photon traveled through the arm which does not contain the bomb—otherwise the bomb would have exploded—but it implies the surprising conclusion that the energy exchange occurred at a distance despite a local interaction Hamiltonian. We use the weak value formalism to support this interpretation and find evidence of contextuality. Regardless of interpretation, this interaction-free quantum measurement engine is able to lift the most sensitive bomb without setting it off.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Microwave-driven heterogeneous catalysis for activation of dinitrogen to ammonia under atmospheric pressure

This paper presents an innovative approach to producing energy-dense, carbon–neutral liquid ammonia as a means for carrying energy. This approach synergistically integrates microwave reaction chemistry with novel heterogeneous catalysis that decouples dinitrogen activation from high-temperature and high-pressure reactions, altering reaction pathways and increasing ammonia formation rate. Results presented here demonstrate that ammonia synthesis can be conducted at 280 ? and ambient pressure to achieve ~1 mmol ammonia/g cat/h over supported ruthenium catalyst systems utilizing microwave irradiation. It is further shown that adding promoter ions such as potassium, cerium, and barium significantly improves the ammonia production rate over undoped ruthenium-based catalysts. This effect could be attributed to enhanced dielectric loss processes that lead to stronger microwave absorption by the catalyst. Measurement of the equilibrium constant under microwave conditions showed a higher ammonia yield than under thermal equilibrium conditions for both the iron- and ruthenium-based catalysts. Finally, this study also illustrates the advantages of using a variable-frequency microwave reactor for ambient-pressure ammonia synthesis. Mechanistically, investigators believed that the oscillating electric fields of the radiation can couple with adsorbed nitrogen on the surface and accelerate its dissociation. Since dinitrogen dissociation on the surface is rate limiting, this effectively accelerates the reaction.

Hu, Jianli (John)↗

Patience is a virtue: A data-driven analysis of rooftop solar PV permitting timelines in the United States

© 2020 The Authors Local permitting can ensure the safe installation and operation of rooftop solar photovoltaic (PV) systems. At the same time, burdensome local permitting processes and local variation in requirements may pose challenges to PV deployment. In this article, we explore new data on the durations between key steps in the PV permitting process in the United States. The data suggest that a typical customer can expect to wait around 25–100 days from permit application until an installed system passes inspection. Permit durations vary significantly across jurisdictions, due in part to differences in local permitting policies. However, permit durations vary as significantly within jurisdictions as across them, in part due to significant variation across installers, suggesting that installer strategies and practices play an important role in permitting timelines. Permit durations have declined over time, reflecting progress from permit streamlining policies and jurisdiction learning-by-doing, though durations have stabilized in recent years. The data suggest that typical PV customers still face long and uncertain permitting timelines in the United States.

O'Shaughnessy, E↗