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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Turbine modeling technique to generate off-design performance data for both single and multistage axial-flow turbines

This technique is applicable to larger axial flow turbines which may or may not incorporate variable geometry in the first stage stator. A user specified option will also permit the calculation of design point cooling flow levels and the corresponding change in turbine efficiency. The modeling technique was incorporated into a time sharing computer program in order to facilitate its use. Because this report contains a description of the input output data, values of typical inputs, and example cases, it is suitable as a user's manual.

Converse, G. L.↗
NASA NTRS1992

Performance data of the new free-piston shock tunnel at GALCIT

The new free-piston shock tunnel has been partially calibrated, and a range of operating conditions has been found. A large number of difficulties were encountered during the shake-down period, of which the ablation of various parts was the most severe. Solutions to these problems were found. The general principles of high-enthalpy simulation are outlined, and the parameter space covered by T5 is given. Examples of the operating data show that, with care, excellent repeatability may be obtained. The temporal uniformity of the reservoir pressure is very good, even at high enthalpy, because it is possible to operate at tailored-interface and tuned-piston conditions over the whole enthalpy range. Examples of heat transfer and Pitot-pressure measurements are also presented.

Hornung, Hans G.↗
NASA NTRS1994

High performance data acquisition, identification, and monitoring for active magnetic bearings

Future active magnetic bearing systems (AMB) must feature easier on-site tuning, higher stiffness and damping, better robustness with respect to undesirable vibrations in housing and foundation, and enhanced monitoring and identification abilities. To get closer to these goals we developed a fast parallel link from the digitally controlled AMB to Matlab, which is used on a host computer for data processing, identification, and controller layout. This enables the magnetic bearing to take its frequency responses without using any additional measurement equipment. These measurements can be used for AMB identification.

Herzog, Raoul↗
NASA NTRS1953

Preliminary Transient Performance Data on the J73 Turbojet Engine: Altitude, 45,000 Feet - 3

A program was undertaken to determine the J73 turbojet engine compressor stall and surge characteristics and combustor blow-out limits enc ountered during transient engine operation. Data were obtained in the form of oscillograph traces showing the time history of several engi ne parameters with changes in engine fuel flow. The data presented in this report are for step and ramp changes in fuel flow at an altitude of 45,000 feet and flight Mach numbers of 0 and 0.8.

McAulay, John E.↗
NASA NTRS1950

Preliminary Performance Data on Westinghouse Electronic Power Regulator Operating on J34-WE-32 Turbojet Engine in Altitude Wind Tunnel

The behavior of the Westinghouse electronic power regulator operating on a J34-WE-32 turbojet engine was investigated in the NACA Lewis altitude wind tunnel at the request of the Bureau of Aeronautics, Department of the Navy. The object of the program was to determine the, steady-state stability and transient characteristics of the engine under control at various altitudes and ram pressure ratios, without afterburning. Recordings of the response of the following parameters to step changes in power lever position throughout the available operating range of the engine were obtained; ram pressure ratio, compressor-discharge pressure, exhaust-nozzle area, engine speed, turbine-outlet temperature, fuel-valve position, jet thrust, air flow, turbine-discharge pressure, fuel flow, throttle position, and boost-pump pressure. Representative preliminary data showing the actual time response of these variables are presented. These data are presented in the form of reproductions of oscillographic traces.

Ketchum, James R.↗
DOE OSTI2021

Deciphering Degradation: Machine Learning on Real-World Performance Data (Final Report)

This project addresses a fundamental flaw in solar PV research and solar project financing; the assumed rate of degradation for solar plants. The solar industry currently relies on an out-dated report that observed a 0.5% degradation rate based on a small sample size of systems (~100). While the research conducted at the time was new and innovative, the solar community has not updated this research and universally applies this 0.5% degradation assumption in financial models. Our project updates this assumption by analyzing observed degradation from the industry’s largest dataset of operating solar assets (>10,000 systems) and creating the first machine-learning model based on these observed results to quantify and identify features that drive degradation. There are two strategic goals for this award: reduce the cost of capital (enable solar to attract more capital) and improve the reliability of solar itself. These dual goals are achieved by leveraging an industry dataset to observe system degradation on a large scale, deploying advanced data analysis and machine learning methods to quantify and predict system reliability, and engaging with industry stakeholders to help them accurately price degradation in financial models.

14 SOLAR ENERGY↗