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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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The Federal Energy Management Program (FEMP) encourages federal agencies and organizations to improve data center energy efficiency, which can offer tremendous opportunities for energy and cost savings. In this success story, a novel liquid cooling system provides reliable, resilient, and energy-efficient cooling for high-performance computing (HPC) systems at Sandia National Laboratories.
In 2014, the Mickey Leland Federal Building in Houston, Texas installed a 192 kW PV system on top of its parking structure. To monitor and optimize its performance, the General Services Administration, which manages the site, responded to the Federal Energy Management Program’s request for federal agency participation in the Federal Energy Management Program Solar PV Performance Initiative.
A very low frequency (VLF) antenna includes a metal monopole and a dielectric metamaterial cladding surrounding a periphery of the monopole.
Fact sheet describes evaluating and optimizing a PV system on the Mickey Leland Federal Building.
At a fraction of the cost of window replacement, energy-efficient window attachments (e.g., interior and exterior shading, secondary glazing) offer a cost-effective and user-friendly way for consumers to save money year-round on their energy bills.
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Pumped storage hydropower is often overlooked in future grid planning efforts, in part because the cost to build a new facility is not always clear. That's why the National Renewable Energy Laboratory (NREL), along with the U.S. Department of Energy's Water Power Technologies Office, is developing improved cost estimates and cost models to reduce that uncertainty and give developers the data they need to decide where and when to construct new PSH facilities to support the country's evolving energy grid.
The disclosure provides an electricity generating insert for a piece of footwear, the insert can be removably placed in the heel portion, e.g. under the insole. The insert comprises a multilayer piezoelectric stack that alternatively flexes under the compression-decompression that occurs during locomotion, which flexing causes friction in the stack to generate electricity capable of charging electronic devices and the like, e.g. via a port on the footwear.
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It is common practice to use pure copper as the material of choice in applications requiring adequate strength and high electrical conductivity (EC). However, the overwhelming increase in the cost and worldwide demand for copper is becoming a major concern. As the move towards electrification throughout the world is occurring, so is a parallel move to make aluminum (Al) and Al alloys suitable as a replacement for copper. To make this goal a reality, exploration into enhancements in the strength and EC of high conductivity Al alloys is necessary. This study compiles strength and EC data for current Al powder metallurgy (PM) alloys to better understand existing data and target future research. Also highlighted are reviews of completed research projects, including studies relating to liquid metallurgy, by industry professionals and academia, noting both shortcomings and successes.
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Our technology leverages artificial intelligence (AI) to enhance the user experience in High Performance Computing (HPC) environments. By analyzing user behavior and providing personalized recommendations, our AI system helps HPC users optimize their workflows and improve productivity. Additionally, we offer an advanced image similarity search feature, which utilizes AI algorithms to identify and retrieve visually similar images, saving users valuable time and effort in their research and analysis.
Advanced reactors promise enhanced safety, greater efficiency, and waste reductions. To fully realize these benefits, it is crucial to address the need for autonomous or semi-autonomous control systems that require fewer operators. This research primarily supports the MARVEL autonomous control system, which requires real-time operation. However, the current RELAP5 reactor thermal hydraulic transient simulation is excessively time-consuming. Therefore, this study aims to leverage deep learning techniques to develop a surrogate model, providing a more efficient and accurate alternative for real-time performance. The model was trained using a combination of one-timestep prediction and scheduled sampling. It was then used for recursive prediction of the reactor state. This developed surrogate model significantly improves computational efficiency, achieving a 12 times acceleration.