A Stochastic Controller for Primary Frequency Regulation Using ON/OFF Demand Side Resources
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Additive Manufacturing (AM) offers advantages over conventional manufacturing processes, particularly by reducing the number of parts produced through multistage combined technologies, but these often result in low manufacturing yields or require post-processing. AM facilitates the production of complex geometries with fine features, overhangs, and lattice structures. For instance, Laser Powder Bed Fusion (LPBF) technology enables the fabrication of intricate parts that can be easily post-processed by removing residual powder. Laser powder bed AM technologies are widely discussed in the literature due to their design freedom in creating complex geometries, with and without the need for support generation. However, rapid solidification due to a thermal gradient in the build direction, which leads to the formation of columnar grains and warpage, is one of the challenges. To address this challenge, we propose layer-by-layer metal FFF technology, followed by the debinding and sintering process, as an alternative to powder- and laser-based approaches. Furthermore, design for additive manufacturing (DfAM) principles are discussed to minimize the need for support generation and enable easy post-processing, thereby improving surface finish to meet high tolerances in fabricating components for aerospace and healthcare applications.
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There has been significant recent interest in studying multiscale characteristics of current and next-generation batteries, including lithium-metal and lithium-sulfur batteries. Advances in computing power make researchers believe that the detailed multiscale models can be efficiently simulated to arrive at the insights for the degradation and performance loss; however, this is not true and special attention needs to be paid to local singularities, boundary layers, moving boundaries, etc. This article presents 2D examples that illustrate the importance of grid convergence studies, provides well-defined detailed models to test the efficiency of numerical schemes, and discusses the associated simulation challenges.
Simulations under this dataset were targeted to a specific fuelshed in Iowa. Integrated land management (ILM) applications were targeted under this research, although the results of these simulations are at the county level; downscaling post-processing will be applied.
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).
This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).