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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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111 records · Page 7

A Microphone Phased Array for Launch Acoustics Application

A new, portable, phased array of microphones is built at NASA Ames Research Center specifically for the harsh environment encountered in launch pads of rocket vehicles. It uses 70 rugged, piezo-electric, dynamic pressure sensors optimally distributed on a 10.5ft diameter open frame dome structure. The open frame is light yet robust to sustain the high wind load of typical seaside launch pads, and the blast and acoustic loads from the launch. A 200-ft long cable bundle carries the microphone signals to a weather-protected electronic cabinet containing the data acquisition system, computers, and other equipment. The array is equipped with an infra-red camera and a visible wavelength camera for imaging the launch site. The beamformed noise maps will be superimposed on the video footages collected by the cameras for correct identification of the noise sources. The array is tested with very loud noise sources to determine the beamforming ability. Multiple mathematical models, such as the conventional beamforming, orthogonal-functional beamforming, spectral element method etc. are used to determine the minimum spatial resolution of the sound sources that can be measured at different frequencies. Additionally, the array hardware is being tested for different environmental conditions and electro-magnetic compliance. The goal is to use the array for NASA’s Artemis/SLS vehicle that will be launched from a newly built Mobile Launch platform and a modified launch pad. Data from a couple of validation tests will be presented in this paper. The first test involves an outdoor setup where the array was placed on a crane at several different heights and distances from a pair of very loud noise sources. The second test from the static firing of the RS25 engines in an outdoor test stand.

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Innovative Tools Advance Revolutionary Weld Technique

The iconic, orange external tank of the space shuttle launch system not only contains the fuel used by the shuttle s main engines during liftoff but also comprises the shuttle s backbone, supporting the space shuttle orbiter and solid rocket boosters. Given the tank s structural importance and the extreme forces (7.8 million pounds of thrust load) and temperatures it encounters during launch, the welds used to construct the tank must be highly reliable. Variable polarity plasma arc welding, developed for manufacturing the external tank and later employed for building the International Space Station, was until 1994 the best process for joining the aluminum alloys used during construction. That year, Marshall Space Flight Center engineers began experimenting with a relatively new welding technique called friction stir welding (FSW), developed in 1991 by The Welding Institute, of Cambridge, England. FSW differs from traditional fusion welding in that it is a solid-state welding technique, using frictional heat and motion to join structural components without actually melting any of the material. The weld is created by a shouldered pin tool that is plunged into the seam of the materials to be joined. The tool traverses the line while rotating at high speeds, generating friction that heats and softens but does not melt the metal. (The heat produced approaches about 80 percent of the metal s melting temperature.) The pin tool s rotation crushes and stirs the plasticized metal, extruding it along the seam as the tool moves forward. The material cools and consolidates, resulting in a weld with superior mechanical properties as compared to those weld properties of fusion welds. The innovative FSW technology promises a number of attractive benefits. Because the welded materials are not melted, many of the undesirables associated with fusion welding porosity, cracking, shrinkage, and distortion of the weld are minimized or avoided. The process is more energy efficient, safe (no toxic smoke or shielding gas, liquid metal splatter, arcing, dangerous voltage, or radiation), and environmentally sound (no consumables, fumes, or noise) than fusion welding. Under computer control, an automated FSW machine can create welds with high reproducibility, improving efficiency and overall quality of manufactured materials. The process also allows for welding dissimilar metals as well as those metals considered to be "unweldable" such as the 7xxx series aluminum alloys. Its effectiveness and versatility makes FSW useful for aerospace, rail, automotive, marine, and military applications. A downside to FSW, however, is the keyhole opening left in the weld when the FSW pin tool exits the weld joint. This is a significant problem when using the FSW process to join circumferential structures such as pipes and storage containers. Furthermore, weld joints that taper in material thickness also present problems when using the conventional FSW pin tool, because the threaded pin rotating within the weld joint material is a fixed length. There must be capability for the rotating pin to both increase and decrease in length in real time while welding the tapered material. (Both circumferential and tapered thickness weldments are found in the space shuttle external tank.) Marshall engineers addressed both the keyhole and tapered material thickness problems by developing the auto-adjustable pin tool. This unique piece of equipment automatically withdraws the pin into the tool s shoulder for keyhole closeout. In addition, the auto-adjustable pin tool retracts, or shortens, the rotating pin while welding a weld joint that tapers from one thickness to a thinner thickness. This year, the impact of the Marshall innovation was recognized with an "Excellence in Technology Transfer Award" from the Federal Laboratory Consortium.

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Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

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