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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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This presentation details efforts to integrate 120V HPWHs into ResStock, including detailing the required upgrades to the ResStock tools. Example results from this dataset are shown to inform the audience of what will be available in the next release.
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Hydrogen embrittlement is a form of chemo-mechanical damage that is special in that it can be partially reversible. Here, in this paper, we propose a method for recovering structural alloys from hydrogen embrittlement at room temperature by electrochemically biased desorption of hydrogen. We demonstrate that the method can enable the reversion of hydrogen-induced degradation of mechanical properties, by comparing the mechanical behavior of commercial stainless steel specimens at different hydrogen charging and desorption states. These case studies also reveal the influence of electrochemical potential, H content and the characteristics of H trapping sites, on the effectiveness of this recovery approach. The limitations arising from the presence of unhealable forms of hydrogen damage, and the generic applicability of this electrochemically-assisted recovery method are also discussed.
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Commercial buildings are responsible for approximately 20 % of the total energy consumption and greenhouse gas emissions in the United States. Over 85 % of these buildings lack building automation systems, and many are small (<50,000 square feet), underserved, and use rooftop units (RTUs) for heating, ventilation, and air-conditioning needs. Because these buildings lack proper energy management systems, several operational deficiencies lead to excess energy consumption. Studies have shown that managing the RTUs’ heating and cooling set points, schedules, setbacks, and optimal start can result in a 20 % to 25 % reduction in electricity consumption in small commercial buildings. These buildings typically use fixed schedules to start the RTUs 60 to 120 min before occupancy begins, which results in excess energy consumption. This paper presents research that demonstrates and evaluates the performance of four optimal start methods, which utilize data-based modeling as a key element in facilitating adaptive control in response to time-varying inputs while requiring minimal sensor inputs. The evaluation found energy savings in two commercial buildings equipped with RTUs by periodically alternating four different optimal start models during the cooling and heating season. The resulting energy savings are positive for all models and range from 2 to 5 kWh/day/unit. The units on the east side of the building showed higher savings, while interior units showed greater variability in savings due to the differences in capacities and room sizes. Savings were considerably greater during the heating season compared to the cooling season. The performance of all four models on Mondays was poor; models suggested a shorter optimal start time, which resulted in relatively larger errors. Finally, the future work will look at using a different model for the days after weekends and holidays.
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