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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Dynamic Testing of a High-Specific-Torque Concentric Magnetic Gear

This paper presents initial measurements of the efficiency of NASA's 2nd magnetic gear prototype. A detailed discussion of the test rig's design and capabilities was presented, along with a thorough uncertainty analysis. The reported uncertainties are 95% confidence intervals that include the effects of temperature and parasitic loads. The prototype's response was measured at output speeds between 124 rpm and 744 rpm for a controlled output torque of 10 Nm (8% of the prototype's maximum torque). After correcting for tare losses, the prototype's efficiency was found to decrease from 90.0% to 83.0% as speed increased. If the efficiency is extrapolated to a typical operating condition (85% of maximum torque) using the good assumption that energy loss is approximately independent of the transmitted torque, the expected efficiency would be 99.0% to 98.4%, which exceeds the state of the art for these speeds.

magnetic gears↗
NASA NTRS2016

Summary of the Second High-Altitude, Supersonic Flight Dynamics Test for the LDSD Project

NASA’s Low-Density Supersonic Decelerator Project is developing and testing the next generation of supersonic aerodynamic decelerators for planetary entry. A key element of that development is the testing of full-scale articles in conditions relevant to their intended use, primarily in the tenuous Mars atmosphere. To achieve this testing, the LDSD project developed a new test architecture for the qualification of their supersonic parachute. A large, helium filled scientific balloon is used to hoist a 4.7 m blunt body test vehicle to an altitude of approximately 32 kilometers. The test vehicle is released from the balloon, spun up for gyroscopic stability, and accelerated to over four times the speed of sound and an altitude of 50 kilometers using a large solid rocket motor. Once at those conditions, the vehicle is despun and the test period begins.

Clark, Ian↗
NASA NTRS2019

Dynamic Testing of a High-Specific-Torque Concentric Magnetic Gear

This presentation presents measurements of the efficiency of NASA's 2nd magnetic gear prototype. A detailed discussion of the test rig used to make these measurements was presented, including a thorough uncertainty analysis. The reported uncertainties are 95% confidence intervals that include the effects of temperature and parasitic loads. The prototype's response was measured at output speeds between 124 rpm and 744 rpm for a controlled output torque of 10 Nm (8% of the prototype's maximum torque). After correcting for tare losses, the prototype's efficiency was found to decrease from 90.0% to 83.0% as speed increased. If the efficiency is extrapolated to a typical operating condition (85% of maximum torque) using the good assumption that energy loss is approximately independent of the transmitted torque,the expected efficiency would be 99.0% to 98.4%, which exceeds the state of the art for these speeds.

Scheidler, Justin↗
NASA NTRS2019

Structural Dynamic Testing Results for Air-Independent Proton Exchange Membrane (PEM) Fuel Cell Technologies for Space Applications

In 2016, the NASA Advanced Exploration Systems (AES) project office funded research at the NASA Glenn Research Center to evaluate the maturity of the Proton Exchange Membrane (PEM) fuel cell technology and its viability for supporting launch vehicle and space applications. This technology evaluation included vibration, reactant purity, and vacuum exposure sensitivity testing. The evaluation process did not include microgravity testing. This paper discusses the vibration sensitivity testing of two air-independent fuel cell stacks provided by different vendors to assess the ability of currently available fuel cell stack hardware to survive the projected random vibrational environment that would be encountered in an upper stage launch vehicle. Baseline performance testing was utilized to quantify stack performance and overboard leak rate at standard atmospheric conditions in order to provide a reference for post-test comparison. Both fuel cell stacks were tested at a random vibration qualification level of 10.4 grms for five minutes in each axis. Low-level sinusoidal sweeps were conducted before and after each random vibration level run to see if any significant change in resonances were detected. Following vibration facility testing, the baseline performance testing was repeated. Test results demonstrated no measurable change in fuel cell electrochemical or mechanical performance, indicating that the two evaluated PEM fuel cell stacks may be suitable for space applications pending microgravity testing.

Gilligan, Ryan P.↗
NASA NTRSDate not supplied

Machine Learning for Dynamic Test Sensor Placement

There are multiple different algorithms to perform modal test sensor placement optimization: effective independence, residual kinetic energy, iterative Guyan reduction, genetic algorithms, or a brute-force methodology. However, any of these methods may be computationally expensive, especially for structural models with a large number of degrees of freedom. Given the high-cost and the need to optimize the solution, modal sensor placement is a great application for machine learning (ML) algorithms. In this paper, we will apply ML algorithms to determine the optimal sensor locations for simple and complex structures. We will also discuss the benefits and drawbacks of using machine learning over other sensor placement algorithms.

Kelsey Buckles↗
DOE OSTI2023

Quantification and prediction of error in MIMO tests

Dynamic testing of systems is most realistic of real-world conditions when multiple input and multiple output (MIMO) techniques are used. To replicate measured environmental conditions, a series of desired outputs (responses) on the system must be realized by inverting the frequency response functions (FRF) matrix for input estimation. System identification is dependent on the number of inputs and outputs, which affect the type of solutions. In input estimation, the auto spectra of the determined inputs are affected by both the auto spectra and cross spectra of the desired outputs. This research evaluates errors and investigates two sources in an experimental setting. The first significant error source is test-to-test variability in FRFs from system identification tests, quantified by magnitude variability from long-duration tests. The second significant error source is the realization of time histories from frequency domain inputs. The spectral content of the realized random process deviates from the desired content and is also quantified. The structure is a linear three-story frame fixed at the base; two inputs are provided uniaxially with the use of suspended electrodynamic shakers. The proposed model for error sources was found to be effective in predicting errors in a SISO (single-input single-output) and a square (2-input 2-output) MIMO test.

Yousef, Odey↗
NASA NTRS1994

Eighteenth Space Simulation Conference: Space Mission Success Through Testing

The Institute of Environmental Sciences' Eighteenth Space Simulation Conference, 'Space Mission Success Through Testing' provided participants with a forum to acquire and exchange information on the state-of-the-art in space simulation, test technology, atomic oxygen, program/system testing, dynamics testing, contamination, and materials. The papers presented at this conference and the resulting discussions carried out the conference theme 'Space Mission Success Through Testing.'

Stecher, Joseph L., III↗