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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 649 records · Page 36

Calculated Condenser Performance for a Mercury-Turbine Power Plant for Aircraft

As part of an investigation af the application of nuclear energy to various types of power plants for aircraft, calculations have been made to determine the effect of several operating conditions on the performance of condensers for mercury-turbine power plants. The analysis covered 8 range of turbine-outlet pressures from 1 to 200 pounds per square inch absolute, turbine-inlet pressures from 300 to 700 pounds per square inch absolute,and a range of condenser cooling-air pressure drops, airplane flight speeds, and altitudes. The maximum load-carrying capacity (available for the nuclear reactor, working fluid, and cargo) of a mercury-turbine powered aircraft would be about half the gross weight of the airplane at a flight speed of 509 miles per hour and an altitude of 30,000 feet. This maximum is obtained with specific condenser frontal areas of 0.0063 square foot per net thrust horsepower with the condenser in a nacelle and 0.0060 square foot per net thrust horsepower with the condenser submerged in the wings (no external condenser drag) for a turbine-inlet pressure of 500 pounds per square inch absolute, a turbine-outlet pressure of 10 pounds per square inch absolute, and 8 turbine-inlet temperature of 1600 F.

Doyle, Ronald B.↗

Space Shuttle Day-of-Launch Trajectory Design Operations

A top priority of any launch vehicle is to insert as much mass into the desired orbit as possible. This requirement must be traded against vehicle capability in terms of dynamic control, thermal constraints, and structural margins. The vehicle is certified to specific structural limits which will yield certain performance characteristics of mass to orbit. Some limits cannot be certified generically and must be checked with each mission design. The most sensitive limits require an assessment on the day-of-launch. To further minimize vehicle loads while maximizing vehicle performance, a day-of-launch trajectory can be designed. This design is optimized according to that day s wind and atmospheric conditions, which increase the probability of launch. The day-of-launch trajectory design and verification process is critical to the vehicle s safety. The Day-Of-Launch I-Load Update (DOLILU) is the process by which the National Aeronautics and Space Administration's (NASA) Space Shuttle Program tailors the vehicle steering commands to fit that day s environmental conditions and then rigorously verifies the integrated vehicle trajectory s loads, controls, and performance. This process has been successfully used for almost twenty years and shares many of the same elements with other launch vehicles that execute a day-of-launch trajectory design or day-of-launch trajectory verification. Weather balloon data is gathered at the launch site and transmitted to the Johnson Space Center s Mission Control. The vehicle s first stage trajectory is then adjusted to the measured wind and atmosphere data. The resultant trajectory must satisfy loads and controls constraints. Additionally, these assessments statistically protect for non-observed dispersions. One such dispersion is the change in the wind from the last measured balloon to launch time. This process is started in the hours before launch and is repeated several times as the launch count proceeds. Should the trajectory design not meet all constraint criteria, Shuttle would be No-Go for launch. This Shuttle methodology is very similar to other unmanned launch vehicles. By extension, this method would likely be employed for any future NASA launch vehicle. This paper will review the Shuttle s day-of-launch trajectory optimization and verification operations as an example of a more generic application of day-of-launch design and validation. With Shuttle s retirement, it is fitting to document the current state of this critical process and capture lessons learned to benefit current and future launch vehicle endeavors.

Harrington, Brian E.↗

Novel Materials for Prosthetic Liners

Existing materials for prosthetic liners tend to be thick and airtight, causing perspiration to accumulate inside the liner and potentially causing infection and injury that reduce quality of life. The purpose of this project was to examine the suitability of aerogel for prosthetic liner applications. Three tests were performed on several types of aerogel to assess the properties of each material. Moisture vapor permeability was tested by incubating four aerogel varieties with an artificial sweat solution at 37.0 C and less than 20% relative humidity for 24 hours. Two aerogel varieties were eliminated from the study due to difficulties in handling the material, and further testing proceeded with Pyrogel in 2.0 and 6.0 mm thicknesses. Force distribution was tested by compressing samples under a load of 4448 N at a rate of 2.5 mm/min. Biofilm formation was tested in a high-shear CDC Biofilm Reactor. Results showed that 2.0 mm Pyrogel blanket allowed 55.7 plus or minus 28.7% of an artificial sweat solution to transpire, and 35.5 plus or minus 27.8% transpired through 6.0 mm Pyrogel blanket. Samples also outperformed the load-bearing capabilities of existing liner materials. No statistically significant difference was found between the two Pyrogel thicknesses for either moisture vapor permeability or force distribution. In addition, biofilm formation results showed no change between the two Pyrogel thicknesses. The breathability and load bearing properties of aerogel make it a suitable material for application to prosthetic liners.

Ragolta, Carolina I.↗

Modeling and Energy Analysis of Refrigeration Systems in Supermarkets: A Case Study

Refrigeration systems are the single largest consumer of electricity in supermarkets, accounting for approximately 40–60% of total store electricity use. As supermarkets face increasing pressures to improve efficiency and reduce operational costs, understanding the energy performance of refrigeration systems in supermarkets has become essential. In this paper, we investigate the energy performance and patterns of the refrigeration system using field measurements in one supermarket. The compressor coefficient of performance (COP) averaged 4.5 during nighttime steady-state operation, providing a practical efficiency benchmark. We develop simple physical-based load models for the display cases in the supermarket, where the refrigeration system uses R404A. The results show the display case models achieve a good agreement with measured data, validating its utility for energy estimation during unoccupied hours. Finally, the analysis reveals several challenges of data collection systems for refrigeration systems in the supermarket industry as well.

Chen, Yimin [ORNL] (ORCID:0000000338181655)↗

SWS Building Electric Demand Profile

This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SWS Building Electric Demand Profile

This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SWS Building Electric Demand Profile

This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SWS Building Electric Demand Profile

This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SWS Building Electric Demand Profile

This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SWS Building Electric Demand Profile

This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SWS Building Electric Demand Profile

This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SWS Building Electric Demand Profile

This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SWS Building Electric Demand Profile

This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SWS Building Electric Demand Profile

This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SWS Building Electric Demand Profile

This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SWS Building Electric Demand Profile

This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SWS Building Electric Demand Profile

This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SWS Building Electric Demand Profile

This dataset contains data on the electric use of the building in 15-minute increments (kilowatt-hours and average kilowatts).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗