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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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Extensional tectonics during the igneous emplacement of the mafic-ultramafic rocks of the Barberton greenstone belt

The simatic rocks (Onverwacht Group) of the Barberton greenstone belt are part of the Jamestown ophiolite complex. This ophiolite, together with its thick sedimentary cover occupies a complex thrust belt. Field studies have identified two types of early faults which are entirely confined to the simatic rocks and are deformed by the later thrusts and associated folds. The first type of fault (F1a) is regional and always occurs in the simatic rocks along and parallel to the lower contacts of the ophiolite-related cherts (Middle Marker and equivalent layers). These fault zones have previously been referred to both as flaser-banded gneisses and as weathering horizons. In general the zones range between 1-30m in thickness. Displacements along these zones are difficult to estimate, but may be in the order of 1-100 km. The structures indicate that the faults formed close to horizontal, during extensional shear and were therefore low angle normal faults. F1a zones overlap in age with the formation of the ophiolite complex. The second type of faults (F1b) are vertical brittle-ductile shear zones, which crosscut the complex at variable angles and cannot always be traced from plutonic to overlying extrusive (pillowed) simatic rocks. F1b zones are also apparently of penecontemporaneous origin with the intrusive-extrusive igneous processs. F1b zones may either represent transform fault-type activity or represent root zones (steepened extensions) of F1a zones. Both fault types indicate extensive deformation in the rocks of the greenstone belt prior to compressional overthrust tectonics.

Dewit, M. J.↗

Method of recertifying a loaded bearing member

A method is described of recertifying a loaded bearing member using ultrasound testing to compensate for different equipment configurations and temperature conditions. The standard frequency F1 of a reference block is determined via an ultrasonic tone burst generated by a first pulsed phased locked loop (P2L2) equipment configuration. Once a lock point number S is determined for F1, the reference frequency F1a of the reference block is determined at this lock point number via a second P2L2 equipment configuration to permit an equipment offset compensation factor Fo1=((F1-F1a)/F1)(1000000) to be determined. Next, a reference frequency F2 of the unloaded bearing member is determined using a second P2L2 equipment configuration and is then compensated for equipment offset errors via the relationship F2+F2(Fo1)/1000000. A lock point number b is also determined for F2. A resonant frequency F3 is determined for the reference block using a third P2L2 equipment configuration to determine a second offset compensation factor F02=((F1-F3)/F1) 1000000. Next the resonant frequency F4 of the loaded bearing member is measured at lock point number b via the third P2L2 equipment configuration and the bolt load determined by the relationship (-1000000)CI(((F2-F4)/F2)-Fo2), wherein CI is a factor correlating measured frequency shift to the applied load. Temperature compensation is also performed at each point in the process.

Allison, Sidney G.↗

High-Lift Propeller Noise Prediction for a Distributed Electric Propulsion Flight Demonstrator

Over the past several years, the use of electric propulsion technologies within aircraft design has received increased attention. The characteristics of electric propulsion systems open up new areas of the aircraft design space, such as the use of distributed electric propulsion (DEP). In this approach, electric motors are placed in many different locations to achieve increased efficiency through integration of the propulsion system with the airframe. Under a project called Scalable Convergent Electric Propulsion Technology Operations Research (SCEPTOR), NASA is designing a flight demonstrator aircraft that employs many "high-lift propellers" distributed upstream of the wing leading edge and two cruise propellers (one at each wingtip). As the high-lift propellers are operational at low flight speeds (take-off/approach flight conditions), the impact of the DEP configuration on the aircraft noise signature is also an important design consideration. This paper describes efforts toward the development of a mulit-fidelity aerodynamic and acoustic methodology for DEP high-lift propeller aeroacoustic modeling. Specifically, the PAS, OVERFLOW 2, and FUN3D codes are used to predict the aerodynamic performance of a baseline high-lift propeller blade set. Blade surface pressure results from the aerodynamic predictions are then used with PSU-WOPWOP and the F1A module of the NASA second generation Aircraft NOise Prediction Program to predict the isolated high-lift propeller noise source. Comparisons of predictions indicate that general trends related to angle of attack effects at the blade passage frequency are captured well with the various codes. Results for higher harmonics of the blade passage frequency appear consistent for the CFD based methods. Conversely, evidence of the need for a study of the effects of increased azimuthal grid resolution on the PAS based results is indicated and will be pursued in future work. Overall, the results indicate that the computational approach is acceptable for fundamental assessment of low-noise high-lift propeller designs. The extent to which the various approaches may be used in a complementary manner will be further established as measured data becomes available for validation. Ultimately, it is anticipated that this combined approach may be used to provide realistic incident source fields for acoustic shielding/scattering studies on various aircraft configurations.

Nark, Douglas M.↗

Prediction-Based Auralization of a Multirotor Urban Air Mobility Vehicle

Recent advances in auralization methods applicable to rotary wing vehicles have made it possible to undertake a prediction-based auralization of a representative multirotor urban air mobility vehicle. These advances include a new capability for synthesizing loading and thickness noise directly from the prediction method and a new capability for predicting and synthesizing modulating broadband self noise within a unified system noise prediction-auralization framework. These capabilities are demonstrated for a six passenger quadrotor reference vehicle design using collective-pitch control. Propagation of the source noise to a ground observer completes the auralization process. The demonstrated capability serves as the basis for future work directed at perception-influenced design of low noise urban air mobility vehicles.

Auralization↗